Pancreatic ductal adenocarcinoma (PDA) is a lethal disease notoriously resistant to therapy1,2. This is mediated in part by a complex tumour microenvironment3, low vascularity4, and metabolic aberrations5,6. Although altered metabolism drives tumour progression, the spectrum of metabolites used as nutrients by PDA remains largely unknown. Here we identified uridine as a fuel for PDA in glucose-deprived conditions by assessing how more than 175 metabolites impacted metabolic activity in 21 pancreatic cell lines under nutrient restriction. Uridine utilization strongly correlated with the expression of uridine phosphorylase 1 (UPP1), which we demonstrate liberates uridine-derived ribose to fuel central carbon metabolism and thereby support redox balance, survival and proliferation in glucose-restricted PDA cells. In PDA, UPP1 is regulated by KRAS-MAPK signalling and is augmented by nutrient restriction. Consistently, tumours expressed high UPP1 compared with non-tumoural tissues, and UPP1 expression correlated with poor survival in cohorts of patients with PDA. Uridine is available in the tumour microenvironment, and we demonstrated that uridine-derived ribose is actively catabolized in tumours. Finally, UPP1 deletion restricted the ability of PDA cells to use uridine and blunted tumour growth in immunocompetent mouse models. Our data identify uridine utilization as an important compensatory metabolic process in nutrient-deprived PDA cells, suggesting a novel metabolic axis for PDA therapy..

Pancreatic ductal adenocarcinoma (PDAC) is the most common and aggressive type of pancreatic cancer and has abysmal survival rates. In the past two decades, immunotherapeutic agents with success in other cancer types have gradually been trialled against PDACs at different stages of cancer progression, either as a monotherapy or in combination with chemotherapy. Unfortunately, to this day, chemotherapy still prolongs the survival rates the most and is prescribed in clinics despite the severe side effects in other cancer types. The low success rates of immunotherapy against PDAC have been attributed most frequently to its complex and multi-faceted tumour microenvironment (TME) and low mutational burden. In this review, we give a comprehensive overview of the immunotherapies tested in PDAC clinical trials thus far, their limitations, and potential explanations for their failure. We also discuss the existing classification of heterogenous PDACs into cancer, cancer-associated fibroblast, and immune subtypes and their potential opportunity in patient selection as a form of personalisation of PDAC immunotherapy. © 2023 The Pathological Society of Great Britain and Ireland..

Soft tissue sarcomas (STS) are rare and diverse mesenchymal cancers with limited treatment options. Here we undertake comprehensive proteomic profiling of tumour specimens from 321 STS patients representing 11 histological subtypes. Within leiomyosarcomas, we identify three proteomic subtypes with distinct myogenesis and immune features, anatomical site distribution and survival outcomes. Characterisation of undifferentiated pleomorphic sarcomas and dedifferentiated liposarcomas with low infiltrating CD3 + T-lymphocyte levels nominates the complement cascade as a candidate immunotherapeutic target. Comparative analysis of proteomic and transcriptomic profiles highlights the proteomic-specific features for optimal risk stratification in angiosarcomas. Finally, we define functional signatures termed Sarcoma Proteomic Modules which transcend histological subtype classification and show that a vesicle transport protein signature is an independent prognostic factor for distant metastasis. Our study highlights the utility of proteomics for identifying molecular subgroups with implications for risk stratification and therapy selection and provides a rich resource for future sarcoma research..

BACKGROUND: The effect of chemoradiation on the anti-cancer immune response is being increasingly acknowledged; however, its clinical implications in treatment responses are yet to be fully understood. Human papillomavirus (HPV)-driven malignancies express viral oncogenic proteins which may serve as tumor-specific antigens and represent ideal candidates for monitoring the peripheral T-cell receptor (TCR) changes secondary to chemoradiotherapy (CRT). METHODS: We performed intra-tumoral and pre- and post-treatment peripheral TCR sequencing in a cohort of patients with locally-advanced HPV16-positive cancers treated with CRT. An in silico computational pipeline was used to cluster TCR repertoire based on epitope-specificity and to predict affinity between these clusters and HPV16-derived epitopes. RESULTS: Intra-tumoral repertoire diversity, intra-tumoral and post-treatment peripheral CDR3β similarity clustering were predictive of response. In responders, CRT triggered an increase peripheral TCR clonality and clonal relatedness. Post-treatment expansion of baseline peripheral dominant TCRs was associated with response. Responders showed more baseline clustered structures of TCRs maintained post-treatment and displayed significantly more maintained clustered structures. When applying clustering by TCR-specificity methods, responders displayed a higher proportion of intra-tumoral TCRs predicted to recognise HPV16 peptides. CONCLUSIONS: Baseline TCR characteristics and changes in the peripheral T-cell clones triggered by CRT are associated with treatment outcome. Maintenance and boosting of pre-existing clonotypes are key elements of an effective anti-cancer immune response driven by CRT, supporting a paradigm in which the immune system plays a central role in the success of CRT in current standard-of-care protocols..

Pancreatic ductal adenocarcinoma (PDAC) shows pronounced epithelial and mesenchymal cancer cell populations1-4. Cellular heterogeneity in PDAC is an important feature in disease subtype specification3-5, but how distinct PDAC subpopulations interact, and the molecular mechanisms that underlie PDAC cell fate decisions, are incompletely understood. Here we identify the BMP inhibitor GREM16,7 as a key regulator of cellular heterogeneity in pancreatic cancer in human and mouse. Grem1 inactivation in established PDAC in mice resulted in a direct conversion of epithelial into mesenchymal PDAC cells within days, suggesting that persistent GREM1 activity is required to maintain the epithelial PDAC subpopulations. By contrast, Grem1 overexpression caused an almost complete 'epithelialization' of highly mesenchymal PDAC, indicating that high GREM1 activity is sufficient to revert the mesenchymal fate of PDAC cells. Mechanistically, Grem1 was highly expressed in mesenchymal PDAC cells and inhibited the expression of the epithelial-mesenchymal transition transcription factors Snai1 (also known as Snail) and Snai2 (also known as Slug) in the epithelial cell compartment, therefore restricting epithelial-mesenchymal plasticity. Thus, constant suppression of BMP activity is essential to maintain epithelial PDAC cells, indicating that the maintenance of the cellular heterogeneity of pancreatic cancer requires continuous paracrine signalling elicited by a single soluble factor..

BACKGROUND: Colorectal cancer (CRC) consensus molecular subtypes (CMS) have different immunological, stromal cell, and clinicopathological characteristics. Single-cell characterization of CMS subtype tumor microenvironments is required to elucidate mechanisms of tumor and stroma cell contributions to pathogenesis which may advance subtype-specific therapeutic development. We interrogate racially diverse human CRC samples and analyze multiple independent external cohorts for a total of 487,829 single cells enabling high-resolution depiction of the cellular diversity and heterogeneity within the tumor and microenvironmental cells. RESULTS: Tumor cells recapitulate individual CMS subgroups yet exhibit significant intratumoral CMS heterogeneity. Both CMS1 microsatellite instability (MSI-H) CRCs and microsatellite stable (MSS) CRC demonstrate similar pathway activations at the tumor epithelial level. However, CD8+ cytotoxic T cell phenotype infiltration in MSI-H CRCs may explain why these tumors respond to immune checkpoint inhibitors. Cellular transcriptomic profiles in CRC exist in a tumor immune stromal continuum in contrast to discrete subtypes proposed by studies utilizing bulk transcriptomics. We note a dichotomy in tumor microenvironments across CMS subgroups exists by which patients with high cancer-associated fibroblasts (CAFs) and C1Q+TAM content exhibit poor outcomes, providing a higher level of personalization and precision than would distinct subtypes. Additionally, we discover CAF subtypes known to be associated with immunotherapy resistance. CONCLUSIONS: Distinct CAFs and C1Q+ TAMs are sufficient to explain CMS predictive ability and a simpler signature based on these cellular phenotypes could stratify CRC patient prognosis with greater precision. Therapeutically targeting specific CAF subtypes and C1Q + TAMs may promote immunotherapy responses in CRC patients..

PURPOSE: Triple-negative breast cancer (TNBC) is a heterogeneous disease with a significant challenge to effectively manage in the clinic worldwide. Immunotherapy may be beneficial to TNBC patients if responders can be effectively identified. Here we sought to elucidate the immune landscape of TNBCs by stratifying patients into immune-specific subtypes (immunotypes) to decipher the molecular and cellular presentations and signaling events of this heterogeneous disease and associating them with their clinical outcomes and potential treatment options. EXPERIMENTAL DESIGN: We profiled 730 immune genes in 88 retrospective Indian TNBC samples using the NanoString platform, established immunotypes using non-negative matrix factorization-based machine learning approach, and validated them using Western TNBCs (n=422; public datasets). Immunotype-specific gene signatures were associated with clinicopathological features, immune cell types, biological pathways, acute/chronic inflammatory responses, and immunogenic cell death processes. Responses to different immunotherapies associated with TNBC immunotypes were assessed using cross-cancer comparison to melanoma (n=504). Tumor-infiltrating lymphocytes (TILs) and pan-macrophage spatial marker expression were evaluated. RESULTS: We identified three robust transcriptome-based immunotypes in both Indian and Western TNBCs in similar proportions. Immunotype-1 tumors, mainly representing well-known claudin-low and immunomodulatory subgroups, harbored dense TIL infiltrates and T-helper-1 (Th1) response profiles associated with smaller tumors, pre-menopausal status, and a better prognosis. They displayed a cascade of events, including acute inflammation, damage-associated molecular patterns, T-cell receptor-related and chemokine-specific signaling, antigen presentation, and viral-mimicry pathways. On the other hand, immunotype-2 was enriched for Th2/Th17 responses, CD4+ regulatory cells, basal-like/mesenchymal immunotypes, and an intermediate prognosis. In contrast to the two T-cell enriched immunotypes, immunotype-3 patients expressed innate immune genes/proteins, including those representing myeloid infiltrations (validated by spatial immunohistochemistry), and had poor survival. Remarkably, a cross-cancer comparison analysis revealed the association of immunotype-1 with responses to anti-PD-L1 and MAGEA3 immunotherapies. CONCLUSION: Overall, the TNBC immunotypes identified in TNBCs reveal different prognoses, immune infiltrations, signaling, acute/chronic inflammation leading to immunogenic cell death of cancer cells, and potentially distinct responses to immunotherapies. The overlap in immune characteristics in Indian and Western TNBCs suggests similar efficiency of immunotherapy in both populations if strategies to select patients according to immunotypes can be further optimized and implemented..

RAF kinases are highly conserved serine/threonine kinases, and among the three RAF isoforms (ARAF, BRAF, and CRAF), the pathophysiological relevance of ARAF is not well defined. Here, we show that patients with lung cancer exhibit low expression of ARAF, which is associated with lymph node metastasis and poor patient survival. We uncover that depletion of ARAF promotes anchorage-independent growth and metastasis through activation of AKT signaling in a subset of lung cancer cells. We identified that loss of ARAF was associated with an increase in ERBB3 expression in a kinase-independent manner. ARAF suppressed the promoter activity of ERBB3, and reconstitution of ARAF in ARAF-depleted cells led to the reversal of enhanced ERBB3-AKT signaling. Furthermore, ARAF inhibited neuregulin 1 (hNRG1)-mediated AKT activation through controlling ERBB3 expression via the transcription factor KLF5. Our results disclose a critical dual role for ARAF kinase in the negative regulation of ERBB3-AKT signaling, thereby suppressing tumor metastasis..

BACKGROUND: Most patients with pancreatic ductal adenocarcinoma (PDAC) are metastatic at presentation with dismal prognosis warranting improved systemic therapy options. Longitudinal sampling for the assessment of treatment response poses a challenge for validating novel therapies. In this case study, we evaluate the feasibility of collecting endoscopic ultrasound (EUS)-guided longitudinal fine-needle aspiration biopsies (FNABs) from two PDAC patients and conduct gene expression studies associated with tumour microenvironment changes associated with radiofrequency ablation (RFA). METHODS: EUS-guided serial/longitudinal FNABs of tumour were collected before and after treatment from two stage III inoperable gemcitabine-treated PDAC patients treated with targeted RFA three times. Biopsies were analysed using a custom NanoString panel (144 genes) consisting of cancer and cancer-associated fibroblast (CAFs) subtypes and immune changes. CAF culture was established from one FNAB and characterised by immunofluorescence and immunoblotting. RESULTS: Two-course RFA led to the upregulation of the CD1E gene (involved in antigen presentation) in both patients 1 and 2 (4.5 and 3.9-fold changes) compared to baseline. Patient 1 showed increased T cell genes (CD4-8.7-fold change, CD8-35.7-fold change), cytolytic function (6.4-fold change) and inflammatory response (8-fold change). A greater than 2-fold upregulation of immune checkpoint genes was observed post-second RFA in both patients. Further, two-course RFA led to increased PDGFRα (4.5-fold change) and CAF subtypes B and C genes in patient 1 and subtypes A, B and D genes in patient 2. Patient 2-derived CAFs post-first RFA showed expression of PDGFRα, POSTN and MYH11 proteins. Finally, RFA led to the downregulation of classical PDAC subtype-specific genes in both patients. CONCLUSIONS: This case study suggests longitudinal EUS-FNAB as a potential resource to study tumour and microenvironmental changes associated with RFA treatment. A large sample size is required in the future to assess the efficacy and safety of the treatment and perform comprehensive statistical analysis of EUS-RFA-based molecular changes in PDAC..

Here we report the DNA methylation profile of 84 sporadic pancreatic neuroendocrine tumors (PanNETs) with associated clinical and genomic information. We identified three subgroups of PanNETs, termed T1, T2 and T3, with distinct patterns of methylation. The T1 subgroup was enriched for functional tumors and ATRX, DAXX and MEN1 wild-type genotypes. The T2 subgroup contained tumors with mutations in ATRX, DAXX and MEN1 and recurrent patterns of chromosomal losses in half of the genome with no association between regions with recurrent loss and methylation levels. T2 tumors were larger and had lower methylation in the MGMT gene body, which showed positive correlation with gene expression. The T3 subgroup harboured mutations in MEN1 with recurrent loss of chromosome 11, was enriched for grade G1 tumors and showed histological parameters associated with better prognosis. Our results suggest a role for methylation in both driving tumorigenesis and potentially stratifying prognosis in PanNETs..

BACKGROUND: Rectal cancers show a highly varied response to neoadjuvant radiotherapy/chemoradiation (RT/CRT) and the impact of the tumor immune microenvironment on this response is poorly understood. Current clinical tumor regression grading systems attempt to measure radiotherapy response but are subject to interobserver variation. An unbiased and unique histopathological quantification method (change in tumor cell density (ΔTCD)) may improve classification of RT/CRT response. Furthermore, immune gene expression profiling (GEP) may identify differences in expression levels of genes relevant to different radiotherapy responses: (1) at baseline between poor and good responders, and (2) longitudinally from preradiotherapy to postradiotherapy samples. Overall, this may inform novel therapeutic RT/CRT combination strategies in rectal cancer. METHODS: We generated GEPs for 53 patients from biopsies taken prior to preoperative radiotherapy. TCD was used to assess rectal tumor response to neoadjuvant RT/CRT and ΔTCD was subjected to k-means clustering to classify patients into different response categories. Differential gene expression analysis was performed using statistical analysis of microarrays, pathway enrichment analysis and immune cell type analysis using single sample gene set enrichment analysis. Immunohistochemistry was performed to validate specific results. The results were validated using 220 pretreatment samples from publicly available datasets at metalevel of pathway and survival analyses. RESULTS: ΔTCD scores ranged from 12.4% to -47.7% and stratified patients into three response categories. At baseline, 40 genes were significantly upregulated in poor (n=12) versus good responders (n=21), including myeloid and stromal cell genes. Of several pathways showing significant enrichment at baseline in poor responders, epithelial to mesenchymal transition, coagulation, complement activation and apical junction pathways were validated in external cohorts. Unlike poor responders, good responders showed longitudinal (preradiotherapy vs postradiotherapy samples) upregulation of 198 immune genes, reflecting an increased T-cell-inflamed GEP, type-I interferon and macrophage populations. Longitudinal pathway analysis suggested viral-like pathogen responses occurred in post-treatment resected samples compared with pretreatment biopsies in good responders. CONCLUSION: This study suggests potentially druggable immune targets in poor responders at baseline and indicates that tumors with a good RT/CRT response reprogrammed from immune "cold" towards an immunologically "hot" phenotype on treatment with radiotherapy..

INTRODUCTION: The consensus molecular subtypes (CMS) demonstrated prognostic value in metastatic colorectal cancer (mCRC). Similarly, a prognostic impact was suggested for the pre-consensus CRCAssigner (CRCA) classifier in early stages. The potential predictive role of these classifiers with regard to the choice of the first-line therapy has not been established. We investigated the prognostic and predictive impact of CMS and CRCA subtypes among mCRC patients treated in the TRIBE2 study. METHODS: Among 679 randomized patients, 426 and 428 (63%) samples were profiled according to CMS and CRCA classifications, respectively. The prognostic and predictive impact of both CMS and CRCA subtypes was investigated with univariate and multivariate analyses for progression-free survival (PFS), PFS 2 (PFS2), and overall survival (OS). RESULTS: Significant associations of CMS and CRCA subtypes with PFS, PFS2, and OS were demonstrated; the CMS classifier confirmed its independent prognostic value in the multivariable model (P value for PFS/PFS2/OS = 0.01/0.07/0.08). The effect of treatment intensification was independent of CMS subtypes (P value for interaction for PFS/PFS2/OS = 0.88/0.75/0.55). A significant interaction effect between CRCA subtypes and treatment arm was demonstrated in PFS (P = 0.02), PFS2 (P = 0.01), and OS (P = 0.008). The benefit of FOLFOXIRI seemed more relevant in the stem-like (PFS, hazard ratio = 0.60; P = 0.03) and mixed subtypes (hazard ratio = 0.44; P = 0.002). These findings were confirmed in a subgroup of patients of the previous TRIBE study. CONCLUSIONS: We confirmed the independent prognostic role of CMS classification in mCRC independently of RAS/BRAF status. CRCA classification may help identifying subgroups of patients who may derive more benefit from FOLFOXIRI/bevacizumab..

BACKGROUND: Intratumor heterogeneity (ITH) is described as the presence of various clones within one tumor, each with their own unique features in terms of morphology, inflammation, genetics or transcriptomics. Heterogeneity provides the fuel for drug resistance; therefore, an accurate assessment of tumor heterogeneity is essential for the development of effective therapies. The purpose of this study was to dissect morphologic and molecular ITH in colorectal adenocarcinoma. MATERIALS AND METHODS: A series of 120 V600EBRAF-mutated (V600EBRAFmt) consecutive metastatic colorectal adenocarcinomas was assessed for morphologic heterogeneity. The two heterogeneous components of each specimen underwent a histopathological, immunohistochemical and molecular characterization to evaluate: histologic variant, grading, tumor-infiltrating lymphocytes (TILs), mismatch repair proteins' expression, KRAS/BRAF/NRAS mutations, microsatellite instability (MSI) status and consensus molecular subtype (CMS). RESULTS: Thirty-one out of 120 (25.8%) V600EBRAFmt primary colorectal adenocarcinomas presented a heterogeneous morphology. Among these, eight cases had adequate material for molecular profiling. Five out of the eight (62.5%) cases resulted instable at MSI testing. The majority (62.5%) of the samples showed a CMS4 phenotype based on gene expression profiling. Heterogeneity in CMS classification was observed in four out of eight cases. One out of eight cases presented significant heterogeneity in the number of TILs between the two components of the tumor. CONCLUSIONS: Although the distribution of the immune infiltrate appears relatively conserved among heterogeneous areas of the same tumor, changes in gene expression profile and CMS occur in 50% of V600EBRAFmt adenocarcinoma cases in our small series and might contribute to variability in response to anticancer therapy and clinical outcomes. Assessment of morphological and molecular ITH is needed to improve colorectal cancer classification and to tailor anticancer treatments and should be included in the pathology report..

INTRODUCTION: Cannabinoids are a group of terpenophenolic compounds derived from the Cannabis sativa L. plant. There is a growing body of evidence from cell culture and animal studies in support of cannabinoids possessing anticancer properties. METHOD: A database search of peer reviewed articles published in English as full texts between January 1970 and April 2021 in Google Scholar, MEDLINE, PubMed and Web of Science was undertaken. References of relevant literature were searched to identify additional studies to construct a narrative literature review of oncological effects of cannabinoids in pre-clinical and clinical studies in various cancer types. RESULTS: Phyto-, endogenous and synthetic cannabinoids demonstrated antitumour effects both in vitro and in vivo. However, these effects are dependent on cancer type, the concentration and preparation of the cannabinoid and the abundance of receptor targets. The mechanism of action of synthetic cannabinoids, (-)-trans-Δ9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD) has mainly been described via the traditional cannabinoid receptors; CB1 and CB2, but reports have also indicated evidence of activity through GPR55, TRPM8 and other ion channels including TRPA1, TRPV1 and TRPV2. CONCLUSION: Cannabinoids have shown to be efficacious both as a single agent and in combination with antineoplastic drugs. These effects have occurred through various receptors and ligands and modulation of signalling pathways involved in hallmarks of cancer pathology. There is a need for further studies to characterise its mode of action at the molecular level and to delineate efficacious dosage and route of administration in addition to synergistic regimes..

OBJECTIVE: A comprehensive analysis of the immune landscape of pancreatic neuroendocrine tumours (PanNETs) was performed according to clinicopathological parameters and previously defined molecular subtypes to identify potential therapeutic vulnerabilities in this disease. DESIGN: Differential expression analysis of 600 immune-related genes was performed on 207 PanNET samples, comprising a training cohort (n=72) and two validation cohorts (n=135) from multiple transcriptome profiling platforms. Different immune-related and subtype-related phenotypes, cell types and pathways were investigated using different in silico methods and were further validated using spatial multiplex immunofluorescence. RESULTS: The study identified an immune signature of 132 genes segregating PanNETs (n=207) according to four previously defined molecular subtypes: metastasis-like primary (MLP)-1 and MLP-2, insulinoma-like and intermediate. The MLP-1 subtype (26%-31% samples across three cohorts) was strongly associated with elevated levels of immune-related genes, poor prognosis and a cascade of tumour evolutionary events: larger hypoxic and necroptotic tumours leading to increased damage-associated molecular patterns (viral mimicry), stimulator of interferon gene pathway, T cell-inflamed genes, immune checkpoint targets, and T cell-mediated and M1 macrophage-mediated immune escape mechanisms. Multiplex spatial profiling validated significantly increased macrophages in the MLP-1 subtype. CONCLUSION: This study provides novel data on the immune microenvironment of PanNETs and identifies MLP-1 subtype as an immune-high phenotype featuring a broad and robust activation of immune-related genes. This study, with further refinement, paves the way for future precision immunotherapy studies in PanNETs to potentially select a subset of MLP-1 patients who may be more likely to respond..

FOLFIRINOX, a combination of chemotherapy drugs (Fluorouracil, Oxaliplatin, Irinotecan -FOI), provides the best clinical benefit in pancreatic ductal adenocarcinoma (PDAC) patients. In this study we explore the role of miRNAs (MIR) as modulators of chemosensitivity to identify potential biomarkers of response. We find that 41 and 84 microRNA inhibitors enhance the sensitivity of Capan1 and MiaPaCa2 PDAC cells respectively. These include a MIR1307-inhibitor that we validate in further PDAC cell lines. Chemotherapy-induced apoptosis and DNA damage accumulation are higher in MIR1307 knock-out (MIR1307KO) versus control PDAC cells, while re-expression of MIR1307 in MIR1307KO cells rescues these effects. We identify binding of MIR1307 to CLIC5 mRNA through covalent ligation of endogenous Argonaute-bound RNAs cross-linking immunoprecipitation assay. We validate these findings in an in vivo model with MIR1307 disruption. In a pilot cohort of PDAC patients undergoing FOLFIRONX chemotherapy, circulating MIR1307 correlates with clinical outcome..

The Cancer Genome Atlas (TCGA) is a landmark cancer genomics program that molecularly characterized over 20,000 primary cancer and matched normal samples spanning 33 cancer types. On similar lines, the establishment of an 'Indian Cancer Genomics Atlas (ICGA)' has been initiated in 2019-2020 by a consortium of key stakeholders in India led by Council for Scientific and Industrial Research (CSIR), Government of India and several reputed governmental agencies, cancer hospitals, academic institutions, and private sector partners. In parallel, Bangladesh Medical Research Council (BMRC) has announced the launch of 'Bangladesh Cancer Genome Atlas (BCGA) project with support from the ICGA teams. Teams from United States - National Cancer Institute (NCI) office of TCGA and Centre for Global Oncology, Institute of Cancer Research, London, United Kingdom are interested in extending their collaborations to these large-scale initiatives by acting as knowledge partners. With this background, an online version of the 2nd TCGA conference and workshop in India was organised with the theme of 'Towards Team Science for Multi-omics Studies in South Asia' on December 3-5, 2020. Over 1,500 delegates comprising of onco-clinicians, basic researchers, bioinformaticians, geneticists, translational researchers, big-data and machine-learning scientists, bioethicists and regulatory experts from across the globe attended the event. The conference agenda focused on the vision, design and plans of the ICGA project with regards to common standard operating protocols (SOPs), operations, logistics, bioethics, policy and governance models. More importantly, conference sessions were planned around the central theme of building a culture of team science for undertaking mega-cancer research projects in India and neighbouring countries. Experts from the globe deliberated on the latest technical aspects of data/biospecimen/multi-omics studies and applications of Precision Oncology in clinical cancer management..

Pancreatic neuroendocrine neoplasms (PanNENs) are rare, highly heterogeneous tumours. There have been significant recent advances in our knowledge of genomic events underlying their pathogenesis. However, treatment decisions remain largely based on tumour stage and grade which is inadequate, the current classification paradigm failing to capture the significant heterogeneity in tumour biology. There is a well-acknowledged unmet clinical need for novel biomarkers to enable individualised risk-adapted therapeutic strategies for PanNEN patients. Improvements in our understanding of the molecular biology of multiple solid tumours have led to the development of new biomarker assays and gene expression signatures to guide treatment decisions in other cancer types. A similar index for PanNENs, to improve patient prognostication and classification, would be highly clinically relevant and with advances in the field now seems potentially possible. This article will seek to review the molecular biology of PanNENs, the subtypes developed to date and the potential clinical opportunities these advances may afford..

COVID-19 patients show heterogeneity in clinical presentation and outcomes that makes pandemic control and strategy difficult; optimizing management requires a systems biology approach of understanding the disease. Here we sought to potentially understand and infer complex disease progression, immune regulation, and symptoms in patients infected with coronaviruses (35 SARS-CoV and 3 SARS-CoV-2 patients and 57 samples) at two different disease progression stages. Further, we compared coronavirus data with healthy individuals (n = 16) and patients with other infections (n = 144; all publicly available data). We applied inferential statistics (the COVID-engine platform) to RNA profiles (from limited number of samples) derived from peripheral blood mononuclear cells (PBMCs). Compared to healthy individuals, a subset of integrated blood-based gene profiles (signatures) distinguished acute-like (mimicking coronavirus-infected patients with prolonged hospitalization) from recovering-like patients. These signatures also hierarchically represented multiple (at the system level) parameters associated with PBMC including dysregulated cytokines, genes, pathways, networks of pathways/concepts, immune status, and cell types. Proof-of-principle observations included PBMC-based increases in cytokine storm-associated IL6, enhanced innate immunity (macrophages and neutrophils), and lower adaptive T and B cell immunity in patients with acute-like disease compared to those with recovery-like disease. Patients in the recovery-like stage showed significantly enhanced TNF, IFN-γ, anti-viral, HLA-DQA1, and HLA-F gene expression and cytolytic activity, and reduced pro-viral gene expression compared to those in the acute-like stage in PBMC. Besides, our analysis revealed overlapping genes associated with potential comorbidities (associated diabetes) and disease-like conditions (associated with thromboembolism, pneumonia, lung disease, and septicemia). Overall, our COVID-engine inferential statistics platform and study involving PBMC-based RNA profiling may help understand complex and variable system-wide responses displayed by coronavirus-infected patients with further validation..

BACKGROUND: Colon cancer (CC) is a heterogeneous disease. Novel prognostic factors beyond pathological staging are required to accurately identify patients at higher risk of relapse. Integrating these new biological factors, such as plasma circulating tumour DNA (ctDNA), CDX2 staining, inflammation-associated cytokines and transcriptomic consensus molecular subtypes (CMS) classification, into a multimodal approach may improve our accuracy in determining risk of recurrence. METHODS: One hundred and fifty patients consecutively diagnosed with localised CC were prospectively enrolled in our study. ctDNA was tracked to detect minimal residual disease by droplet digital PCR. CDX2 expression was analysed by immunostaining. Plasma levels of cytokines potentially involved in disease progression were measured using ELISAs. A 96 custom gene panel for nCounter assay was used to classify CC into colorectal cancer assigner and CMS. RESULTS: Most patients were classified into CMS4 (37%) and CMS2 (28%), followed by CMS1 (20%) and CMS3 (15%) groups. CDX2-negative tumours were enriched in CMS1 and CMS4 subtypes. In univariable analysis, prognosis was influenced by primary tumour location, stage, vascular and perineural invasion together with high interleukin-6 plasma levels at baseline, tumours belonging to CMS 1 vs CMS2 +CMS3, ctDNA presence in plasma and CDX2 loss. However, only positive ctDNA in plasma samples (HR 13.64; p=0.002) and lack of CDX2 expression (HR 23.12; p=0.001) were found to be independent prognostic factors for disease-free survival in the multivariable model. CONCLUSIONS: ctDNA detection after surgery and lack of CDX2 expression identified patients at very high risk of recurrence in localised CC..

Advances in surgery, peri-operative care and systemic chemotherapy have not significantly improved the prognosis of pancreatic cancer for several decades. Early clinical trials of immunotherapy have yielded disappointing results proposing other means by which the tumour microenvironment serves to decrease the immune response. Additionally, the emergence of various subtypes of pancreatic cancer has emerged as a factor for treatment responses with immunogenic subtypes carrying a better prognosis. Herein we discuss the reasons for the poor response to checkpoint inhibitors and outline a rationale why combination treatments are likely to be most effective. We review the therapies which could provide optimal synergistic effects to immunotherapy including chemotherapy, agents targeting the stroma, co-stimulatory molecules, vaccinations and methods of immunogenic tumour priming including radiofrequency ablation. Finally, we discuss reasons why peri-operative and in particular neoadjuvant combination treatments are likely to be most effective and should be considered for early clinical trials..

One of the major challenges in defining clinically-relevant and less heterogeneous tumor subtypes is assigning biological and/or clinical interpretations to etiological (intrinsic) subtypes. Conventional clustering/subtyping approaches often fail to define such subtypes, as they involve several discrete steps. Here we demonstrate a unique machine-learning method, phenotype mapping (PhenMap), which jointly integrates single omics data with phenotypic information using three published breast cancer datasets (n = 2045). The PhenMap framework uses a modified factor analysis method that is governed by a key assumption that, features from different omics data types are correlated due to specific "hidden/mapping" variables (context-specific mapping variables (CMV)). These variables can be simultaneously modeled with phenotypic data as covariates to yield functional subtypes and their associated features (e.g., genes) and phenotypes. In one example, we demonstrate the identification and validation of six novel "functional" (discrete) subtypes with differential responses to a cyclin-dependent kinase (CDK)4/6 inhibitor and etoposide by jointly integrating transcriptome profiles with four different drug response data from 37 breast cancer cell lines. These robust subtypes are also present in patient breast tumors with different prognosis. In another example, we modeled patient gene expression profiles and clinical covariates together to identify continuous subtypes with clinical/biological implications. Overall, this genome-phenome machine-learning integration tool, PhenMap identifies functional and phenotype-integrated discrete or continuous subtypes with clinical translational potential..

PURPOSE: Metastatic colorectal cancers (mCRCs) assigned to the transit-amplifying (TA) CRCAssigner subtype are more sensitive to anti-epidermal growth factor receptor (EGFR) therapy. We evaluated the association between the intratumoral presence of TA signature (TA-high/TA-low, dubbed as TA-ness classification) and outcomes in CRCs treated with anti-EGFR therapy. PATIENTS AND METHODS: The TA-ness classes were defined in a discovery cohort (n = 84) and independently validated in a clinical trial (CO.20; cetuximab monotherapy arm; n = 121) and other samples using an established NanoString-based gene expression assay. Progression-free survival (PFS), overall survival (OS), and disease control rate (DCR) according to TA-ness classification were assessed by univariate and multivariate analyses. RESULTS: The TA-ness was measured in 772 samples from 712 patients. Patients (treated with anti-EGFR therapy) with TA-high tumors had significantly longer PFS (discovery hazard ratio [HR], 0.40; 95% CI, 0.25 to 0.64; P < .001; validation HR, 0.65; 95% CI, 0.45 to 0.93; P = .018), longer OS (discovery HR, 0.48; 95% CI, 0.29 to 0.78; P = .003; validation HR, 0.67; 95% CI, 0.46 to 0.98; P = .04), and higher DCR (discovery odds ratio [OR]; 14.8; 95% CI, 4.30 to 59.54; P < .001; validation OR, 4.35; 95% CI, 2.00 to 9.09; P < .001). TA-ness classification and its association with anti-EGFR therapy outcomes were further confirmed using publicly available data (n = 80) from metastatic samples (PFS P < .001) and patient-derived xenografts (P = .042). In an exploratory analysis of 55 patients with RAS/BRAF wild-type and left-sided tumors, TA-high class was significantly associated with longer PFS and trend toward higher response rate (PFS HR, 0.53; 95% CI, 0.28 to 1.00; P = .049; OR, 5.88; 95% CI, 0.71 to 4.55; P = .09; response rate 33% in TA-high and 7.7% in TA-low). CONCLUSION: TA-ness classification is associated with prognosis in patients with mCRC treated with anti-EGFR therapy and may further help understanding the value of sidedness in patients with RAS/BRAF wild-type tumors..

PURPOSE: ATR inhibitors (ATRi) are in early phase clinical trials and have been shown to sensitize to chemotherapy and radiotherapy preclinically. Limited data have been published about the effect of these drugs on the tumor microenvironment.Experimental Design: We used an immunocompetent mouse model of HPV-driven malignancies to investigate the ATR inhibitor AZD6738 in combination with fractionated radiation (RT). Gene expression analysis and flow cytometry were performed posttherapy. RESULTS: Significant radiosensitization to RT by ATRi was observed alongside a marked increase in immune cell infiltration. We identified increased numbers of CD3+ and NK cells, but most of this infiltrate was composed of myeloid cells. ATRi plus radiation produced a gene expression signature matching a type I/II IFN response, with upregulation of genes playing a role in nucleic acid sensing. Increased MHC I levels were observed on tumor cells, with transcript-level data indicating increased antigen processing and presentation within the tumor. Significant modulation of cytokine gene expression (particularly CCL2, CCL5, and CXCL10) was found in vivo, with in vitro data indicating CCL3, CCL5, and CXCL10 are produced from tumor cells after ATRi + RT. CONCLUSIONS: We show that DNA damage by ATRi and RT leads to an IFN response through activation of nucleic acid-sensing pathways. This triggers increased antigen presentation and innate immune cell infiltration. Further understanding of the effect of this combination on the immune response may allow modulation of these effects to maximize tumor control through antitumor immunity..

Despite showing clinical activity in BRAF-mutant melanoma, the MEK inhibitor (MEKi) trametinib has failed to show clinical benefit in KRAS-mutant colorectal cancer. To identify mechanisms of resistance to MEKi, we employed a pharmacogenomic analysis of MEKi-sensitive versus MEKi-resistant colorectal cancer cell lines. Strikingly, interferon- and inflammatory-related gene sets were enriched in cell lines exhibiting intrinsic and acquired resistance to MEK inhibition. The bromodomain inhibitor JQ1 suppressed interferon-stimulated gene (ISG) expression and in combination with MEK inhibitors displayed synergistic effects and induced apoptosis in MEKi-resistant colorectal cancer cell lines. ISG expression was confirmed in patient-derived organoid models, which displayed resistance to trametinib and were resensitized by JQ1 co-treatment. In in vivo models of colorectal cancer, combination treatment significantly suppressed tumor growth. Our findings provide a novel explanation for the limited response to MEK inhibitors in KRAS-mutant colorectal cancer, known for its inflammatory nature. Moreover, the high expression of ISGs was associated with significantly reduced survival of colorectal cancer patients. Excitingly, we have identified novel therapeutic opportunities to overcome intrinsic and acquired resistance to MEK inhibition in colorectal cancer..

The Colorectal Cancer Subtyping Consortium identified four gene expression consensus molecular subtypes, CMS1 (immune), CMS2 (canonical), CMS3 (metabolic), and CMS4 (mesenchymal), using multiple microarray or RNA-sequencing datasets of primary tumor samples mainly from early stage colon cancer patients. Consequently, rectal tumors and stage IV tumors (possibly reflective of more aggressive disease) were underrepresented, and no chemo- and/or radiotherapy pretreated samples or metastatic lesions were included. In view of their possible effect on gene expression and consequently subtype classification, sample source and treatments received by the patients before collection must be carefully considered when applying the classifier to new datasets. Recently, several correlative analyses of clinical trials demonstrated the applicability of this classification to the metastatic setting, confirmed the prognostic value of CMS subtypes after relapse and hinted at differential sensitivity to treatments. Here, we discuss why contexts and equivocal factors need to be taken into account when analyzing clinical trial data, including potential selection biases, type of platform, and type of algorithm used for subtype prediction. This perspective article facilitates both our clinical and research understanding of the application of this classifier to expedite subtype-based clinical trials..

Cancer-associated fibroblasts (CAF) are orchestrators of the pancreatic ductal adenocarcinoma (PDAC) microenvironment. Stromal heterogeneity may explain differential pathophysiological roles of the stroma (pro- versus anti-tumoural) in PDAC. We hypothesised that multiple CAF functional subtypes exist in PDAC, that contribute to stromal heterogeneity through interactions with cancer cells. Using molecular and functional analysis of patient-derived CAF primary cultures, we demonstrated that human PDAC-derived CAFs display a high level of inter- and intra-tumour heterogeneity. We identified at least four subtypes of CAFs based on transcriptomic analysis, and propose a classification for human PDAC-derived CAFs (pCAFassigner). Multiple CAF subtypes co-existed in individual patient samples. The presence of these CAF subtypes in bulk tumours was confirmed using publicly available gene expression profiles, and immunostainings of CAF subtype markers. Each subtype displayed specific phenotypic features (matrix- and immune-related signatures, vimentin and α-smooth muscle actin expression, proliferation rate), and was associated with an assessable prognostic impact. A prolonged exposure of non-tumoural pancreatic stellate cells to conditioned media from cancer cell lines (cancer education experiment) induced a CAF-like phenotype, including loss of capacity to revert to quiescence and an increase in the expression of genes related to CAF subtypes B and C. This classification demonstrates molecular and functional inter- and intra-tumoural heterogeneity of CAFs in human PDAC. Our subtypes overlap with those identified from single-cell analyses in other cancers, and pave the way for the development of therapies targeting specific CAF subpopulations in PDAC. © 2018 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland..

Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRCs). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF1 and non-canonical RAS/RAF aberrations with primary resistance and validated transcriptomic CRC subtypes as non-genetic predictors of benefit. Sixty-four percent of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype at baseline to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PD-L1 and LAG3 immune checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy..

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Previously, we classified colorectal cancers (CRCs) into five CRCAssigner (CRCA) subtypes with different prognoses and potential treatment responses, later consolidated into four consensus molecular subtypes (CMS). Here we demonstrate the analytical development and validation of a custom NanoString nCounter platform-based biomarker assay (NanoCRCA) to stratify CRCs into subtypes. To reduce costs, we switched from the standard nCounter protocol to a custom modified protocol. The assay included a reduced 38-gene panel that was selected using an in-house machine-learning pipeline. We applied NanoCRCA to 413 samples from 355 CRC patients. From the fresh frozen samples (n = 237), a subset had matched microarray/RNAseq profiles (n = 47) or formalin-fixed paraffin-embedded (FFPE) samples (n = 58). We also analyzed a further 118 FFPE samples. We compared the assay results with the CMS classifier, different platforms (microarrays/RNAseq) and gene-set classifiers (38 and the original 786 genes). The standard and modified protocols showed high correlation (> 0.88) for gene expression. Technical replicates were highly correlated (> 0.96). NanoCRCA classified fresh frozen and FFPE samples into all five CRCA subtypes with consistent classification of selected matched fresh frozen/FFPE samples. We demonstrate high and significant subtype concordance across protocols (100%), gene sets (95%), platforms (87%) and with CMS subtypes (75%) when evaluated across multiple datasets. Overall, our NanoCRCA assay with further validation may facilitate prospective validation of CRC subtypes in clinical trials and beyond..

OBJECTIVE: Primary tumour location is regarded as a reliable surrogate of colorectal cancer biology. Sensitivity to anti-EGFRs (Epidermal Growth Factor Receptor) of metastatic transverse colon cancers (mTCCs) has usually been assumed similar to right-sided tumours; however, evidence about the clinical behaviour of mTCC is limited. Thus, to verify sensitivity of mTCC to anti-EGFRs we conducted the present study. METHODS: Patients with RAS/BRAF wild-type microsatellite stable (MSS) mTCC receiving anti-EGFR monotherapy, or in combination with irinotecan if clearly irinotecan-refractory, were included. Hypothesising an overall response rate (ORR) of 35%, 11 patients, of whom at least 3 were responders, were necessary to be able to reject the null hypothesis of an ORR of 5%, with α and β errors of 0.05 and 0.20. PRESSING panel and consensus molecular subtypes (CMS) were assessed on tumour samples, whereas in-silico data were obtained from TCGA dataset. RESULTS: Among nine eligible patients, four and three achieved response and disease stabilisation (ORR 44%). At a median follow-up of 23.1 months, median progression-free survival and overall survival were 7.3 (95% CI 3.9 to NA) and 15.0 months (95% CI 10.0 to NA), respectively. A MET amplification and an ERBB4 S303F substitution were detected in patients with rapid disease progression, while others had PRESSING panel-negative tumours with CMS2 or CMS4 subtypes. CONCLUSIONS: RAS/BRAF wild-type MSS mTCCs may be sensitive to anti-EGFRs, as confirmed by molecular analyses..

Breast cancer is a highly heterogeneous disease. Although differences between intrinsic breast cancer subtypes have been well studied, heterogeneity within each subtype, especially luminal-A cancers, requires further interrogation to personalize disease management. Here, we applied well-characterized and cancer-associated heterocellular signatures representing stem, mesenchymal, stromal, immune, and epithelial cell types to breast cancer. This analysis stratified the luminal-A breast cancer samples into five subtypes with a majority of them enriched for a subtype (stem-like) that has increased stem and stromal cell gene signatures, representing potential luminal progenitor origin. The enrichment of immune checkpoint genes and other immune cell types in two (including stem-like) of the five heterocellular subtypes of luminal-A tumors suggest their potential response to immunotherapy. These immune-enriched subtypes of luminal-A tumors (containing only estrogen receptor positive samples) showed good or intermediate prognosis along with the two other differentiated subtypes as assessed using recurrence-free and distant metastasis-free patient survival outcomes. On the other hand, a partially differentiated subtype of luminal-A breast cancer with transit-amplifying colon-crypt characteristics showed poor prognosis. Furthermore, published luminal-A subtypes associated with specific somatic copy number alterations and mutations shared similar cellular and mutational characteristics to colorectal cancer subtypes where the heterocellular signatures were derived. These heterocellular subtypes reveal transcriptome and cell-type based heterogeneity of luminal-A and other breast cancer subtypes that may be useful for additional understanding of the cancer type and potential patient stratification and personalized medicine..

BACKGROUND: Following neoadjuvant chemotherapy for operable gastroesophageal cancer, lymph node metastasis is the only validated prognostic variable; however, within lymph node groups there is still heterogeneity with risk of relapse. We hypothesized that gene profiles from neoadjuvant chemotherapy treated resection specimens from gastroesophageal cancer patients can be used to define prognostic risk groups to identify patients at risk for relapse. PATIENTS AND METHODS: The Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) trial (n = 202 with high quality RNA) samples treated with perioperative chemotherapy were profiled for a custom gastric cancer gene panel using the NanoString platform. Genes associated with overall survival (OS) were identified using penalized and standard Cox regression, followed by generation of risk scores and development of a NanoString biomarker assay to stratify patients into risk groups associated with OS. An independent dataset served as a validation cohort. RESULTS: Regression and clustering analysis of MAGIC patients defined a seven-Gene Signature and two risk groups with different OS [hazard ratio (HR) 5.1; P < 0.0001]. The median OS of high- and low-risk groups were 10.2 [95% confidence interval (CI) of 6.5 and 13.2 months] and 80.9 months (CI: 43.0 months and not assessable), respectively. Risk groups were independently prognostic of lymph node metastasis by multivariate analysis (HR 3.6 in node positive group, P = 0.02; HR 3.6 in high-risk group, P = 0.0002), and not prognostic in surgery only patients (n = 118; log rank P = 0.2). A validation cohort independently confirmed these findings. CONCLUSIONS: These results suggest that gene-based risk groups can independently predict prognosis in gastroesophageal cancer patients treated with neoadjuvant chemotherapy. This signature and associated assay may help risk stratify these patients for post-surgery chemotherapy in future perioperative chemotherapy-based clinical trials..

Patient-derived organoids (PDOs) have recently emerged as robust preclinical models; however, their potential to predict clinical outcomes in patients has remained unclear. We report on a living biobank of PDOs from metastatic, heavily pretreated colorectal and gastroesophageal cancer patients recruited in phase 1/2 clinical trials. Phenotypic and genotypic profiling of PDOs showed a high degree of similarity to the original patient tumors. Molecular profiling of tumor organoids was matched to drug-screening results, suggesting that PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared responses to anticancer agents ex vivo in organoids and PDO-based orthotopic mouse tumor xenograft models with the responses of the patients in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic and could be implemented in personalized medicine programs..

BACKGROUND: To ensure cancer patients are stratified towards treatments that are optimally beneficial, it is a priority to define robust molecular subtypes using clustering methods applied to high-dimensional biological data. If each of these methods produces different numbers of clusters for the same data, it is difficult to achieve an optimal solution. Here, we introduce "polyClustR", a tool that reconciles clusters identified by different methods into subtype "communities" using a hypergeometric test or a measure of relative proportion of common samples. RESULTS: The polyClustR pipeline was initially tested using a breast cancer dataset to demonstrate how results are compatible with and add to the understanding of this well-characterised cancer. Two uveal melanoma datasets were then utilised to identify and validate novel subtype communities with significant metastasis-free prognostic differences and associations with known chromosomal aberrations. CONCLUSION: We demonstrate the value of the polyClustR approach of applying multiple consensus clustering algorithms and systematically reconciling the results in identifying novel subtype communities of two cancer types, which nevertheless are compatible with established understanding of these diseases. An R implementation of the pipeline is available at: https://github.com/syspremed/polyClustR..

How tumor microenvironmental forces shape plasticity of cancer cell morphology is poorly understood. Here, we conduct automated histology image and spatial statistical analyses in 514 high grade serous ovarian samples to define cancer morphological diversification within the spatial context of the microenvironment. Tumor spatial zones, where cancer cell nuclei diversify in shape, are mapped in each tumor. Integration of this spatially explicit analysis with omics and clinical data reveals a relationship between morphological diversification and the dysregulation of DNA repair, loss of nuclear integrity, and increased disease mortality. Within the Immunoreactive subtype, spatial analysis further reveals significantly lower lymphocytic infiltration within diversified zones compared with other tumor zones, suggesting that even immune-hot tumors contain cells capable of immune escape. Our findings support a model whereby a subpopulation of morphologically plastic cancer cells with dysregulated DNA repair promotes ovarian cancer progression through positive selection by immune evasion..

Malignancies of the gastrointestinal tract are among the most common human cancers. The distinct tissues of origin give rise to a diverse set of diseases, such as colorectal cancer, pancreatic carcinoma and gastric cancers, with each associating with specific clinical features. Genomic and transcriptomic analyses have further defined the heterogeneity that occurs within these cancers by identifying so-called molecular subtypes. These subtypes are characterized by specific genetic aberrations and expression signatures that suggest important biological differences. Although at first sight this subdivision of organ-specific cancers might increase the complexity of classification, closer analysis suggests that the subtypes detected in the various malignancies are recurring. For example, nearly all gastrointestinal cancers appear to present with subtypes that are either characterized by a mesenchymal gene expression signatures, extensive immune infiltration or metabolic dysregulation. Additionally, in each of the gastrointestinal malignancies, a 'canonical' subtype is recognized that retains characteristic features of the epithelial tissue of origin. These common themes can enhance our collective understanding of these malignancies, and could perhaps be therapeutically exploited. In this Review, the identification of subtypes in the various gastrointestinal cancer types are discussed along with how they could be incorporated into clinical practice..

Genome projects now generate large-scale data often produced at various time points by different laboratories using multiple platforms. This increases the potential for batch effects. Currently there are several batch evaluation methods like principal component analysis (PCA; mostly based on visual inspection), and sometimes they fail to reveal all of the underlying batch effects. These methods can also lead to the risk of unintentionally correcting biologically interesting factors attributed to batch effects. Here we propose a novel statistical method, finding batch effect (findBATCH), to evaluate batch effect based on probabilistic principal component and covariates analysis (PPCCA). The same framework also provides a new approach to batch correction, correcting batch effect (correctBATCH), which we have shown to be a better approach to traditional PCA-based correction. We demonstrate the utility of these methods using two different examples (breast and colorectal cancers) by merging gene expression data from different studies after diagnosing and correcting for batch effects and retaining the biological effects. These methods, along with conventional visual inspection-based PCA, are available as a part of an R package exploring batch effect (exploBATCH; https://github.com/syspremed/exploBATCH )..

BACKGROUND: Pre-operative chemoradiotherapy (CRT) for MRI-defined, locally advanced rectal cancer is primarily intended to reduce local recurrence rates by downstaging tumours, enabling an improved likelihood of curative resection. However, in a subset of patients complete tumour regression occurs implying that no viable tumour is present within the surgical specimen. This raises the possibility that surgery may have been avoided. It is also recognised that response to CRT is a key determinant of prognosis. Recent radiological advances enable this response to be assessed pre-operatively using the MRI tumour regression grade (mrTRG). Potentially, this allows modification of the baseline MRI-derived treatment strategy. Hence, in a 'good' mrTRG responder, with little or no evidence of tumour, surgery may be deferred. Conversely, a 'poor response' identifies an adverse prognostic group which may benefit from additional pre-operative therapy. METHODS/DESIGN: TRIGGER is a multicentre, open, interventional, randomised control feasibility study with an embedded phase III design. Patients with MRI-defined, locally advanced rectal adenocarcinoma deemed to require CRT will be eligible for recruitment. During CRT, patients will be randomised (1:2) between conventional management, according to baseline MRI, versus mrTRG-directed management. The primary endpoint of the feasibility phase is to assess the rate of patient recruitment and randomisation. Secondary endpoints include the rate of unit recruitment, acute drug toxicity, reproducibility of mrTRG reporting, surgical morbidity, pathological circumferential resection margin involvement, pathology regression grade, residual tumour cell density and surgical/specimen quality rates. The phase III trial will focus on long-term safety, regrowth rates, oncological survival analysis, quality of life and health economics analysis. DISCUSSION: The TRIGGER trial aims to determine whether patients with locally advanced rectal cancer can be recruited and subsequently randomised into a control trial that offers MRI-directed patient management according to radiological response to CRT (mrTRG). The feasibility study will inform a phase III trial design investigating stratified treatment of good and poor responders according to 3-year disease-free survival, colostomy-free survival as well as an increase in cases managed without a major resection. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT02704520 . Registered on 5 February 2016..

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Tumor heterogeneity is reflected and influenced by genetic, epigenetic, and metabolic differences in cancer cells and their interactions with a complex microenvironment. This heterogeneity has resulted in the stratification of tumors into subtypes, mainly based on cancer-specific genomic or transcriptomic profiles. Subtyping can lead to biomarker identification for personalized diagnosis and therapy, but stratification alone does not explain the origins of tumor heterogeneity. Heterogeneity has traditionally been thought to arise from distinct mutations/aberrations in "driver" oncogenes. However, certain subtypes appear to be the result of adaptation to the disrupted microenvironment caused by abnormal tumor vasculature triggering metabolic switches. Moreover, heterogeneity persists despite the predominance of single oncogenic driver mutations, perhaps due to second metabolic or genetic "hits." In certain cancer types, existing subtypes have metabolic and transcriptomic phenotypes that are reminiscent of normal differentiated cells, whereas others reflect the phenotypes of stem or mesenchymal cells. The cell-of-origin may, therefore, play a role in tumor heterogeneity. In this review, we focus on how cancer cell-specific heterogeneity is driven by different genetic or metabolic factors alone or in combination using specific cancers to illustrate these concepts. Cancer Res; 76(18); 5195-200. ©2016 AACR..

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-β activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions..

UNLABELLED: Seeking to assess the representative and instructive value of an engineered mouse model of pancreatic neuroendocrine tumors (PanNET) for its cognate human cancer, we profiled and compared mRNA and miRNA transcriptomes of tumors from both. Mouse PanNET tumors could be classified into two distinctive subtypes, well-differentiated islet/insulinoma tumors (IT) and poorly differentiated tumors associated with liver metastases, dubbed metastasis-like primary (MLP). Human PanNETs were independently classified into these same two subtypes, along with a third, specific gene mutation-enriched subtype. The MLP subtypes in human and mouse were similar to liver metastases in terms of miRNA and mRNA transcriptome profiles and signature genes. The human/mouse MLP subtypes also similarly expressed genes known to regulate early pancreas development, whereas the IT subtypes expressed genes characteristic of mature islet cells, suggesting different tumorigenesis pathways. In addition, these subtypes exhibit distinct metabolic profiles marked by differential pyruvate metabolism, substantiating the significance of their separate identities. SIGNIFICANCE: This study involves a comprehensive cross-species integrated analysis of multi-omics profiles and histology to stratify PanNETs into subtypes with distinctive characteristics. We provide support for the RIP1-TAG2 mouse model as representative of its cognate human cancer with prospects to better understand PanNET heterogeneity and consider future applications of personalized cancer therapy..

Activating mutations in KRAS are among the most frequent events in diverse human carcinomas and are particularly prominent in human pancreatic ductal adenocarcinoma (PDAC). An inducible Kras(G12D)-driven mouse model of PDAC has established a critical role for sustained Kras(G12D) expression in tumor maintenance, providing a model to determine the potential for and the underlying mechanisms of Kras(G12D)-independent PDAC recurrence. Here, we show that some tumors undergo spontaneous relapse and are devoid of Kras(G12D) expression and downstream canonical MAPK signaling and instead acquire amplification and overexpression of the transcriptional coactivator Yap1. Functional studies established the role of Yap1 and the transcriptional factor Tead2 in driving Kras(G12D)-independent tumor maintenance. The Yap1/Tead2 complex acts cooperatively with E2F transcription factors to activate a cell cycle and DNA replication program. Our studies, along with corroborating evidence from human PDAC models, portend a novel mechanism of escape from oncogenic Kras addiction in PDAC..

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction..

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods..

The ultraprecise wiring of neurons banks on the instructions provided by guidance cue proteins that steer them to their appropriate target tissue during neuronal development. Semaphorins are one such family of proteins. Semaphorins are known to play major physiological roles during the development of various organs including the nervous, cardiovascular, and immune systems. Their role in different pathologies including cancer remains an intense area of investigation. This review focuses on a novel member of this family of proteins, semaphorin 5A, which is much less explored in comparison to its other affiliates. Recent reports suggest that semaphorins play important roles in the pathology of cancer by affecting angiogenesis, tumor growth and metastasis. We will firstly give a general overview of the semaphorin family and its receptors. Next, we discuss their roles in cellular movements and how that makes them a connecting link between the nervous system and cancer. Finally, we focus our discussion on semaphorin 5A to summarize the prevailing knowledge for this molecule in developmental biology and carcinogenesis..

Recently we published two independent studies describing novel gene expression-based classifications of colorectal cancer (CRC). Notably, each study stratified CRC into a different number of subtypes: one reported 3 subtypes, whereas the second highlighted 5. Given that each ascribed clinical significance, distinctive biology, and therapeutic prognosis to the different subtypes, we sought to reconcile this apparent incongruity in subtype stratification of CRC, and to interrelate the results. To do so, we each evaluated the other's data sets and analytical methods and discovered that the subtypes and their classifiers are, in fact, clearly related to each other; indeed, the 5 subtype outcomes can be coalesced into the same three. In addition to presenting this clarification, we briefly discuss how both classification methods can be viewed within the broader literature on CRC subtypes, and potentially applied..

Colorectal cancer (CRC) is a major cause of cancer mortality. Whereas some patients respond well to therapy, others do not, and thus more precise, individualized treatment strategies are needed. To that end, we analyzed gene expression profiles from 1,290 CRC tumors using consensus-based unsupervised clustering. The resultant clusters were then associated with therapeutic response data to the epidermal growth factor receptor-targeted drug cetuximab in 80 patients. The results of these studies define six clinically relevant CRC subtypes. Each subtype shares similarities to distinct cell types within the normal colon crypt and shows differing degrees of 'stemness' and Wnt signaling. Subtype-specific gene signatures are proposed to identify these subtypes. Three subtypes have markedly better disease-free survival (DFS) after surgical resection, suggesting these patients might be spared from the adverse effects of chemotherapy when they have localized disease. One of these three subtypes, identified by filamin A expression, does not respond to cetuximab but may respond to cMET receptor tyrosine kinase inhibitors in the metastatic setting. Two other subtypes, with poor and intermediate DFS, associate with improved response to the chemotherapy regimen FOLFIRI in adjuvant or metastatic settings. Development of clinically deployable assays for these subtypes and of subtype-specific therapies may contribute to more effective management of this challenging disease..

Pancreatic neuroendocrine tumors (PanNETs) are a relatively rare but clinically challenging tumor type. In particular, high grade, poorly-differentiated PanNETs have the worst patient prognosis, and the underlying mechanisms of disease are poorly understood. In this study we have identified and characterized a previously undescribed class of poorly differentiated PanNETs in the RIP1-Tag2 mouse model. We found that while the majority of tumors in the RIP1-Tag2 model are well-differentiated insulinomas, a subset of tumors had lost multiple markers of beta-cell differentiation and were highly invasive, leading us to term them poorly differentiated invasive carcinomas (PDICs). In addition, we found that these tumors exhibited a high mitotic index, resembling poorly differentiated (PD)-PanNETs in human patients. Interestingly, we identified expression of Id1, an inhibitor of DNA binding gene, and a regulator of differentiation, specifically in PDIC tumor cells by histological analysis. The identification of PDICs in this mouse model provides a unique opportunity to study the pathology and molecular characteristics of PD-PanNETs..

Field cancerization effects as well as isolated tumor cell foci extending well beyond the invasive tumor margin have been described previously to account for local recurrence rates following breast conserving surgery despite adequate surgical margins and breast radiotherapy. To look for evidence of possible tumor cell contamination or field cancerization by genetic effects, a pilot study (Study 1: 12 sample pairs) followed by a verification study (Study 2: 20 sample pairs) were performed on DNA extracted from HER2-positive breast tumors and matching normal adjacent mammary tissue samples excised 1-3 cm beyond the invasive tumor margin. High-resolution molecular inversion probe (MIP) arrays were used to compare genomic copy number variations, including increased HER2 gene copies, between the paired samples; as well, a detailed histologic and immunohistochemical (IHC) re-evaluation of all Study 2 samples was performed blinded to the genomic results to characterize the adjacent normal tissue composition bracketing the DNA-extracted samples. Overall, 14/32 (44 %) sample pairs from both studies produced genome-wide evidence of genetic aberrations including HER2 copy number gains within the adjacent normal tissue samples. The observed single-parental origin of monoallelic HER2 amplicon haplotypes shared by informative tumor-normal pairs, as well as commonly gained loci elsewhere on 17q, suggested the presence of contaminating tumor cells in the genomically aberrant normal samples. Histologic and IHC analyses identified occult 25-200 μm tumor cell clusters overexpressing HER2 scattered in more than half, but not all, of the genomically aberrant normal samples re-evaluated, but in none of the genomically normal samples. These genomic and microscopic findings support the conclusion that tumor cell contamination rather than genetic field cancerization represents the likeliest cause of local clinical recurrence rates following breast conserving surgery, and mandate caution in assuming the genomic normalcy of histologically benign appearing peritumor breast tissue..

Breast cancers are comprised of molecularly distinct subtypes that may respond differently to pathway-targeted therapies now under development. Collections of breast cancer cell lines mirror many of the molecular subtypes and pathways found in tumors, suggesting that treatment of cell lines with candidate therapeutic compounds can guide identification of associations between molecular subtypes, pathways, and drug response. In a test of 77 therapeutic compounds, nearly all drugs showed differential responses across these cell lines, and approximately one third showed subtype-, pathway-, and/or genomic aberration-specific responses. These observations suggest mechanisms of response and resistance and may inform efforts to develop molecular assays that predict clinical response..

BACKGROUND: Our earlier reports demonstrated that membrane-bound semaphorin 5A (SEMA5A) is expressed in aggressive pancreatic cancer cells and tumours, and promotes tumour growth and metastasis. In this study, we examine whether (1) pancreatic cancer cells secrete SEMA5A and (2) that secreted SEMA5A modulates certain phenotypes associated with tumour progression, angiogenesis and metastasis through various other molecular factors and signalling proteins. METHODS AND RESULTS: In this study, we show that human pancreatic cancer cell lines secrete the extracellular domain (ECD) of SEMA5A (SEMA5A-ECD) and overexpression of mouse Sema5A-ECD in Panc1 cells (not expressing SEMA5A; Panc1-Sema5A-ECD; control cells - Panc1-control) significantly increases their invasion in vitro via enhanced ERK phosphorylation. Interestingly, orthotopic injection of Panc1-Sema5A-ECD cells into athymic nude mice results in a lower primary tumour burden, but enhances the micrometastases to the liver as compared with Panc1-control cells. Furthermore, there is a significant increase in proliferation of endothelial cells treated with conditioned media (CM) from Panc1-Sema5A-ECD cells and a significant increase in microvessel density in Panc1-Sema5A-ECD orthotopic tumours compared with those from Panc1-control cells, suggesting that the increase in liver micrometastases is probably due to increased tumour angiogenesis. In addition, our data demonstrate that this increase in endothelial cell proliferation by Sema5A-ECD is mediated through the angiogenic molecules - interleukin-8 and vascular endothelial growth factor. CONCLUSION: Taken together, these results suggest that a bioactive, secreted form of Sema5A-ECD has an intriguing and potentially important role in its ability to enhance pancreatic tumour invasiveness, angiogenesis and micrometastases..

Pancreatic ductal adenocarcinoma (PDA) is a lethal disease. Overall survival is typically 6 months from diagnosis. Numerous phase 3 trials of agents effective in other malignancies have failed to benefit unselected PDA populations, although patients do occasionally respond. Studies in other solid tumors have shown that heterogeneity in response is determined, in part, by molecular differences between tumors. Furthermore, treatment outcomes are improved by targeting drugs to tumor subtypes in which they are selectively effective, with breast and lung cancers providing recent examples. Identification of PDA molecular subtypes has been frustrated by a paucity of tumor specimens available for study. We have overcome this problem by combined analysis of transcriptional profiles of primary PDA samples from several studies, along with human and mouse PDA cell lines. We define three PDA subtypes: classical, quasimesenchymal and exocrine-like, and we present evidence for clinical outcome and therapeutic response differences between them. We further define gene signatures for these subtypes that may have utility in stratifying patients for treatment and present preclinical model systems that may be used to identify new subtype specific therapies..

BACKGROUND: Breast cancer is the second leading cause of cancer-related death in women in the United States. During the advanced stages of disease, many breast cancer patients suffer from bone metastasis. These metastases are predominantly osteolytic and develop when tumor cells interact with bone. In vivo models that mimic the breast cancer-specific osteolytic bone microenvironment are limited. Previously, we developed a mouse model of tumor-bone interaction in which three mouse breast cancer cell lines were implanted onto the calvaria. Analysis of tumors from this model revealed that they exhibited strong bone resorption, induction of osteoclasts and intracranial penetration at the tumor bone (TB)-interface. METHODS: In this study, we identified and used a TB microenvironment-specific gene expression signature from this model to extend our understanding of the metastatic bone microenvironment in human disease and to predict potential therapeutic targets. RESULTS: We identified a TB signature consisting of 934 genes that were commonly (among our 3 cell lines) and specifically (as compared to tumor-alone area within the bone microenvironment) up- and down-regulated >2-fold at the TB interface in our mouse osteolytic model. By comparing the TB signature with gene expression profiles from human breast metastases and an in vitro osteoclast model, we demonstrate that our model mimics both the human breast cancer bone microenvironment and osteoclastogenesis. Furthermore, we observed enrichment in various signaling pathways specific to the TB interface; that is, TGF-β and myeloid self-renewal pathways were activated and the Wnt pathway was inactivated. Lastly, we used the TB-signature to predict cyclopenthiazide as a potential inhibitor of the TB interface. CONCLUSION: Our mouse breast cancer model morphologically and genetically resembles the osteoclastic bone microenvironment observed in human disease. Characterization of the gene expression signature specific to the TB interface in our model revealed signaling mechanisms operative in human breast cancer metastases and predicted a therapeutic inhibitor of cancer-mediated osteolysis..

Semaphorin 5A (SEMA5A) is an axonal regulator molecule, which belongs to the Semaphorin family of proteins. Previously, we identified SEMA5A as a putative marker for aggressive pancreatic tumors. However, the expression, localization and functional significance of SEMA5A in pancreatic tumors remain unclear. In our study, we hypothesized that SEMA5A expression modulates pancreatic tumor growth and metastasis. We analyzed the constitutive expression and localization of SEMA5A in patient pancreatic tumors (n = 33) and unmatched normal pancreatic (n = 8) tissues and human pancreatic cancer cell lines (n = 16) with different histopathological characteristics. We observed significantly higher expression of SEMA5A protein expression (p < 0.05) in human pancreatic tumor tissue samples compared to normal pancreatic tissues. Similarly, the pancreatic cancer cell lines with higher tumorigenic and metastatic potentials as xenografts in nude mice expressed higher levels of SEMA5A mRNA compared to those with lower tumorigenic and metastatic potentials. Furthermore, we examined the functional role of SEMA5A in pancreatic tumor growth and invasion. Ectopic expression of mouse full-length Sema5A in Panc1 (SEMA5A negative) cells significantly (p < 0.05) enhanced tumorigenesis, growth and metastasis in vivo as well as proliferation, invasiveness and homotypic aggregation in vitro. Together, these data demonstrate that the expression of SEMA5A in pancreatic cancer cells regulates tumorigenesis, growth, invasion and metastasis, and it also suggests a novel target for diagnosis and treatment of pancreatic cancer..

Semaphorin 5A (mouse, Sema5A; human, SEMA5A), is an axon regulator molecule and plays major roles during neuronal and vascular development. The importance of Sema5A during vasculogenesis, however, is unclear. The fact that Sema5A deficient mice display a defective branching of cranial vasculature supports its participation in blood vessel formation. In this study, we tested our hypothesis that Sema5A regulates angiogenesis by modulating various steps during angiogenesis. Accordingly, we demonstrated that the treatment of immortalized endothelial cells with recombinant extracellular domain of mouse Sema5A significantly increased endothelial cell proliferation and migration and decreased apoptosis. We also observed a relative increase of endothelial expression of anti-apoptotic genes relative to pro-apoptotic genes in Sema5A-treated endothelial cells suggesting its role in inhibition of apoptosis. In addition, our data suggest that Sema5A decreases apoptosis through activation of Akt, increases migration through activating Met tyrosine kinases and extracellular matrix degradation through matrix metalloproteinase 9. Moreover, in vivo Matrigel plug assays demonstrated that Sema5A induces endothelial cell migration from pre-existing vessels. In conclusion, the present work shows the pro-angiogenic role of Sema5A and provides clues on the signaling pathways that underlie them..

BACKGROUND: Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profiles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profiles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fixed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. RESULTS: Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically significant negative correlation between methylation profiles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identified 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. CONCLUSIONS: Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators..

CXCR1 and CXCR2 are receptors for CXCL-8 and are differentially expressed on melanoma and endothelial cells. In this study, we determined the functional role of these receptors in melanoma progression. We stably knock-down the expression of CXCR1 and/or CXCR2 in A375-SM (SM; high metastatic) human melanoma cells by short-hairpin RNA transfection. Cell proliferation, migration, invasion, ERK phosphorlyation and cytoskeletal rearrangements were carried out in vitro. In vivo growth was evaluated using murine subcutaneous xenograft model. Our data demonstrate that knock-down of CXCR1 and/or CXCR2 expression, inhibited melanoma cell proliferation, survival, migration and invasive potential in vitro. Moreover, we also observed inhibition of ERK phosphorylation and cytoskeltal rearrangement in SM-shCXCR1, SM-shCXCR2 and SM-shCXCR1/2 cells. Furthermore, when SM-shCXCR1 or SM-shCXCR2 cells implanted in nude mice, tumor growth, proliferation and microvessel density was significantly inhibited as compared to SM-control cells. In addition, we observed a significant increase in melanoma cell apoptosis in SM-shCXCR1 and SM-shCXCR2 tumors compared to SM-control tumors. Together, these data demonstrate that CXCR1 and CXCR2 expression play a critical role in human melanoma tumor progression and, functional blockade of CXCR1 and CXCR2 could be potentially used for future therapeutic intervention in malignant melanoma..

INTRODUCTION: HJURP (Holliday Junction Recognition Protein) is a newly discovered gene reported to function at centromeres and to interact with CENPA. However its role in tumor development remains largely unknown. The goal of this study was to investigate the clinical significance of HJURP in breast cancer and its correlation with radiotherapeutic outcome. METHODS: We measured HJURP expression level in human breast cancer cell lines and primary breast cancers by Western blot and/or by Affymetrix Microarray; and determined its associations with clinical variables using standard statistical methods. Validation was performed with the use of published microarray data. We assessed cell growth and apoptosis of breast cancer cells after radiation using high-content image analysis. RESULTS: HJURP was expressed at higher level in breast cancer than in normal breast tissue. HJURP mRNA levels were significantly associated with estrogen receptor (ER), progesterone receptor (PR), Scarff-Bloom-Richardson (SBR) grade, age and Ki67 proliferation indices, but not with pathologic stage, ERBB2, tumor size, or lymph node status. Higher HJURP mRNA levels significantly decreased disease-free and overall survival. HJURP mRNA levels predicted the prognosis better than Ki67 proliferation indices. In a multivariate Cox proportional-hazard regression, including clinical variables as covariates, HJURP mRNA levels remained an independent prognostic factor for disease-free and overall survival. In addition HJURP mRNA levels were an independent prognostic factor over molecular subtypes (normal like, luminal, Erbb2 and basal). Poor clinical outcomes among patients with high HJURP expression were validated in five additional breast cancer cohorts. Furthermore, the patients with high HJURP levels were much more sensitive to radiotherapy. In vitro studies in breast cancer cell lines showed that cells with high HJURP levels were more sensitive to radiation treatment and had a higher rate of apoptosis than those with low levels. Knock down of HJURP in human breast cancer cells using shRNA reduced the sensitivity to radiation treatment. HJURP mRNA levels were significantly correlated with CENPA mRNA levels. CONCLUSIONS: HJURP mRNA level is a prognostic factor for disease-free and overall survival in patients with breast cancer and is a predictive biomarker for sensitivity to radiotherapy..

PURPOSE: Melanoma, the most aggressive form of skin cancer, accounts for 75% of all skin cancer-related deaths and current therapeutic strategies are not effective in advanced disease. In the current study, we have investigated the efficacy of orally active small-molecule antagonist targeting CXCR2/CXCR1. EXPERIMENTAL DESIGN: Human A375SM melanoma cells were treated with SCH-479833 or SCH-527123, and their effect on proliferation, motility, and invasion was evaluated in vitro. We examined the downstream signaling events in the cells following treatment with antagonists. For in vivo studies, A375SM cells were implanted subcutaneously into athymic nude mice followed by administration of SCH-479833, SCH-527123, or hydroxypropyl-beta-cyclodextrin (20%) orally for 21 days and their effect on tumor growth and angiogenesis was evaluated. RESULTS: Our data show that SCH-479833 or SCH-527123 inhibited the melanoma cell proliferation, chemotaxis, and invasive potential in vitro. Treatment of melanoma cells with SCH-479833 or SCH-527123 also inhibited tumor growth. Histologic and histochemical analyses showed significant (P < 0.05) decreases in tumor cell proliferation and microvessel density in tumors. Moreover, we observed a significant increase in melanoma cell apoptosis in SCH-479833- or SCH-527123-treated animals compared with controls. CONCLUSION: Together, these studies show that selectively targeting CXCR2/CXCR1 with orally active small-molecule inhibitors is a promising therapeutic approach for inhibiting melanoma growth and angiogenesis..

Understanding the cellular and molecular changes in the bone microenvironment is important for developing novel therapeutics to control breast cancer bone metastasis. Although the underlying mechanism(s) of bone metastasis has been the focus of intense investigation, relatively little is known about complex molecular interactions between malignant cells and bone stroma. Using a murine syngeneic model that mimics osteolytic changes associated with human breast cancer, we examined the role of tumor-bone interaction in tumor-induced osteolysis and malignant growth in the bone microenvironment. We identified transforming growth factor-beta receptor 1 (TGF-betaRI) as a commonly upregulated gene at the tumor-bone (TB) interface. Moreover, TGF-betaRI expression and activation, analyzed by nuclear localization of phospho-Smad2, was higher in tumor cells and osteoclasts at the TB interface as compared to the tumor-alone area. Furthermore, attenuation of TGF-beta activity by neutralizing antibody to TGF-beta or TGF-betaRI kinase inhibitor reduced mammary tumor-induced osteolysis, TGF-betaRI expression and its activation. In addition, we demonstrate a potential role of TGF-beta as an important modifier of receptor activator of NF-kappaB ligand (RANKL)-dependent osteoclast activation and osteolysis. Together, these studies demonstrate that inhibition of TGF-betaRI signaling at the TB interface will be a therapeutic target in the treatment of breast cancer-induced osteolysis..

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BACKGROUND: Polyamines regulate important cellular functions and polyamine dysregulation frequently occurs in cancer. The objective of this study was to use a systems approach to study the relative effects of PG-11047, a polyamine analogue, across breast cancer cells derived from different patients and to identify genetic markers associated with differential cytotoxicity. METHODS: A panel of 48 breast cell lines that mirror many transcriptional and genomic features present in primary human breast tumours were used to study the antiproliferative activity of PG-11047. Sensitive cell lines were further examined for cell cycle distribution and apoptotic response. Cell line responses, quantified by the GI50 (dose required for 50% relative growth inhibition) were correlated with the omic profiles of the cell lines to identify markers that predict response and cellular functions associated with drug sensitivity. RESULTS: The concentrations of PG-11047 needed to inhibit growth of members of the panel of breast cell lines varied over a wide range, with basal-like cell lines being inhibited at lower concentrations than the luminal cell lines. Sensitive cell lines showed a significant decrease in S phase fraction at doses that produced little apoptosis. Correlation of the GI50 values with the omic profiles of the cell lines identified genomic, transcriptional and proteomic variables associated with response. CONCLUSIONS: A 13-gene transcriptional marker set was developed as a predictor of response to PG-11047 that warrants clinical evaluation. Analyses of the pathways, networks and genes associated with response to PG-11047 suggest that response may be influenced by interferon signalling and differential inhibition of aspects of motility and epithelial to mesenchymal transition..

The aggressiveness of malignant melanoma is associated with differential expression of CXCL-8 and its receptors, CXCR1 and CXCR2. However, the precise functional role of these receptors in melanoma progression remains unclear. In this study, we investigate the precise functional role of CXCR1 and CXCR2 in melanoma progression. CXCR1 or CXCR2 were stably overexpressed in human melanoma cell lines, SBC-2 (non-tumourigenic) and A375P (low-tumourigenic) exhibiting low endogenous expression of receptors. Functional assays were performed to study the resulting changes in cell proliferation, motility and invasion, and in vivo tumour growth using a mouse xenograft model. Our data demonstrated that CXCR1- or CXCR2-overexpressing SBC-2 and A375P melanoma cells had enhanced proliferation, chemotaxis and invasiveness in vitro. Interestingly, CXCR1 or CXCR2 overexpression in SBC-2 cells induced tumourigenicity, and A375P cells significantly enhanced tumour growth as examined in vivo. Immunohistochemical analyses showed significantly increased tumour cell proliferation and microvessel density and reduced apoptosis in tumours generated from CXCR1- or CXCR2-overexpressing melanoma cells. CXCR1- or CXCR2-induced modulation of melanoma cell proliferation and migration was observed to be mediated through the activation of ERK1/2 phosphorylation. Together, these studies demonstrate that CXCR1 and CXCR2 play essential role in growth, survival, motility and invasion of human melanoma..

The bone microenvironment plays a critical role in tumor-induced osteolysis and osteolytic metastasis through tumor-bone (TB)-interaction. Receptor activator of nuclear factor-kappaB (RANK) ligand (RANKL) is one of the critical signaling molecules involved in osteolysis and bone metastasis. However, the regulation and functional significance of RANKL at the TB-interface in tumor-induced osteolysis remains unclear. In this report, we examined the role of tumor-stromal interaction in the regulation of RANKL expression and its functional significance in tumor-induced osteolysis. Using a novel mammary tumor model, we identified that RANKL expression was upregulated at the TB-interface as compared to the tumor alone area. We demonstrate increased generation of sRANKL at the TB-interface, which is associated with tumor-induced osteolysis. The ratio of RANKL to osteoprotegrin (OPG), a decoy receptor for RANKL, at the TB-interface was also increased. Targeting RANKL expression with antisense oligonucleotides (RANKL-ASO), significantly abrogated tumor-induced osteolysis, decreased RANKL expression and the RANKL:OPG ratio at the TB-interface. Together, these results demonstrate that upregulation of RANKL expression and sRANKL generation at the TB-interface potentiates tumor-induced osteolysis..

In the post-genomic era, various computational methods that predict protein-protein interactions at the genome level are available; however, each method has its own advantages and disadvantages, resulting in false predictions. Here we developed a unique integrated approach to identify interacting partner(s) of Semaphorin 5A (SEMA5A), beginning with seven proteins sharing similar ligand interacting residues as putative binding partners. The methods include Dwyer and Root-Bernstein/Dillon theories of protein evolution, hydropathic complementarity of protein structure, pattern of protein functions among molecules, information on domain-domain interactions, co-expression of genes and protein evolution. Among the set of seven proteins selected as putative SEMA5A interacting partners, we found the functions of Plexin B3 and Neuropilin-2 to be associated with SEMA5A. We modeled the semaphorin domain structure of Plexin B3 and found that it shares similarity with SEMA5A. Moreover, a virtual expression database search and RT-PCR analysis showed co-expression of SEMA5A and Plexin B3 and these proteins were found to have co-evolved. In addition, we confirmed the interaction of SEMA5A with Plexin B3 in co-immunoprecipitation studies. Overall, these studies demonstrate that an integrated method of prediction can be used at the genome level for discovering many unknown protein binding partners with known ligand binding domains..

Breast cancer commonly causes osteolytic metastases in bone, a process that is dependent on tumor-stromal interaction. Proteases play an important role in modulating tumor-stromal interactions in a manner that favors tumor establishment and progression. Whereas several studies have examined the role of proteases in modulating the bone microenvironment, little is currently known about their role in tumor-bone interaction during osteolytic metastasis. In cancer-induced osteolytic lesions, cleavage of receptor activator of nuclear factor-kappaB ligand (RANKL) to a soluble version (sRANKL) is critical for widespread osteoclast activation. Using a mouse model that mimics osteolytic changes associated with breast cancer-induced bone metastases, we identified cathepsin G, cathepsin K, matrix metalloproteinase (MMP)-9, and MMP13 to be proteases that are up-regulated at the tumor-bone interface using comparative cDNA microarray analysis and quantitative reverse transcription-PCR. Moreover, we showed that cathepsin G is capable of shedding the extracellular domain of RANKL, generating active sRANKL that is capable of inducing differentiation and activation of osteoclast precursors. The major source of cathepsin G at the tumor-bone interface seems to be osteoclasts that up-regulate production of cathepsin G via interaction with tumor cells. Furthermore, we showed that in vitro osteoclastogenesis is reduced by inhibition of cathepsin G in a coculture model and that in vivo inhibition of cathepsin G reduces mammary tumor-induced osteolysis. Together, our data indicate that cathepsin G activity at the tumor-bone interface plays an important role in mammary tumor-induced osteolysis and suggest that cathepsin G is a potentially novel therapeutic target in the treatment of breast cancer bone metastasis..

In the post-genomic era, computational identification of cell adhesion molecules (CAMs) becomes important in defining new targets for diagnosis and treatment of various diseases including cancer. Lack of a comprehensive CAM-specific database restricts our ability to identify and characterize novel CAMs. Therefore, we developed a comprehensive mammalian cell adhesion molecule (MCAM) database. The current version is an interactive Web-based database, which provides the resources needed to search mouse, human and rat-specific CAMs and their sequence information and characteristics such as gene functions and virtual gene expression patterns in normal and tumor tissues as well as cell lines. Moreover, the MCAM database can be used for various bioinformatics and biological analyses including identifying CAMs involved in cell-cell interactions and homing of lymphocytes, hematopoietic stem cells and malignant cells to specific organs using data from high-throughput experiments. Furthermore, the database can also be used for training and testing existing transmembrane (TM) topology prediction methods specifically for CAM sequences. The database is freely available online at http://app1.unmc.edu/mcam..

In previous studies, the chemokine CCL21 has shown biological activities that include T cell, natural killer (NK) cell, and dendritic cell (DC) chemoattraction. The goal of this study was to determine the effects of administering CCL21 to orthotopic mammary tumors in terms of impact on tumor growth rate, immune cell infiltration of the primary tumor and survival. We found that a single intratumoral administration of CCL21 slowed the growth of orthotopic mammary tumors and increased intratumoral infiltration by T cells, NK cells and DCs. CCL21 intratumoral administration also prolonged the survival of tumor-earing mice. Furthermore, mice that received intratumoral neoadjuvant CCL21 ior to surgical resection of tumors survived significantly longer than control mice. The urviving neoadjuvant CCL21-reated mice, when challenged again with cl-6, had significantly slower rate of tumor growth than challenged control mice. Thus, our ata indicate that CCL21 treatment prior to mammary tumor resection can significantly rolong survival and increase resistance to subsequent tumor challenge. Overall, our indings suggest that intratumoral administration of CCL21 has potential as a neoadjuvant mmunotherapy for breast cancer..

Chemokines are a large group of low molecular weight cytokines that are known to selectively attract and activate different cell types. Although the primary function of chemokines is well recognized as leukocyte attractants, recent evidences indicate that they also play a role in number of tumor-related processes, such as growth, angiogenesis and metastasis. Chemokines activate cells through cell surface seven trans-membranes, G-protein-coupled receptors (GPCR). The role played by chemokines and their receptors in tumor pathophysiology is complex as some chemokines favor tumor growth and metastasis, while others may enhance anti-tumor immunity. These diverse functions of chemokines establish them as key mediators between the tumor cells and their microenvironment and play critical role in tumor progression and metastasis. In this review, we present some of the recent advances in chemokine research with special emphasis on its role in tumor angiogenesis and metastasis..

Organ-specific homing of malignant cells involves interactions mediated through cell adhesion molecules and their receptors on the cell surface. Identification of peptides that mimic these receptor-ligand interactions is critical for analyzing the functional role of these proteins and is therapeutically significant to target or block organ-specific homing of tumor cells. Following three cycles of in vivo biopanning using a phage display peptide library injected into mice, we identified 11 unique peptides that were specific for homing to lung, liver, bone marrow, or brain. We developed a bioinformatics strategy to identify putative cell adhesion molecules (CAM) involved in tumor cell migration, invasion, and metastasis based on identified organ-specific peptides. Structural information, including surface exposure and the binding preference of any of these residues in the identified proteins, was examined. These studies resulted in identification of Semaphorin 5A (mouse, Sema5A; human, SEMA5A) and its receptor Plexin B3. The gene expression profile of these proteins in tumors and tumor cell lines was assessed using virtual microarray and serial analysis of gene expression (SAGE) databases and was further confirmed using reverse transcriptase polymerase chain reaction (RT-PCR). Our data demonstrate an association between the expression of SEMA5A and Plexin B3 and the aggressiveness of pancreatic and prostate cancer cells. In summary, using a combined experimental and bioinformatics approach, we have identified functional tumor-specific CAMs, which may be critical for organ-specific metastasis..

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