van der Noordaa, M.
de Croze, D.
van Seijen, M.
del Monte-Millán, M.
van 't Veer, L.J.
van't Veer, L.J.
(2022). Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients. The lancet oncology,
(2022). AACR Project GENIE: 100,000 Cases and Beyond. Cancer discovery,
The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain. Here, we demonstrate the use of these real-world data, harmonized through a centralized data resource, to accurately predict enrollment on genome-guided trials, discover driver alterations in rare tumors, and identify cancer types without actionable mutations that could benefit from comprehensive genomic analysis. The extensible data infrastructure and governance framework support additional deep patient phenotyping through biopharmaceutical collaborations and expansion to include new data types such as cell-free DNA sequencing. AACR Project GENIE continues to serve a global precision medicine knowledge base of increasing impact to inform clinical decision-making and bring together cancer researchers internationally.
AACR Project GENIE has now accrued data from >110,000 tumors, placing it among the largest repository of publicly available, clinically annotated genomic data in the world. GENIE has emerged as a powerful resource to evaluate genome-guided clinical trial design, uncover drivers of cancer subtypes, and inform real-world use of genomic data.
This article is highlighted in the In This Issue feature, p. 2007
(2022). Multi-omic machine learning predictor of breast cancer therapy response. Nature,
Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded byERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers..
(2019). Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups. Nature,
De Mattos-Arruda, L.
Dias Amarante, T.
Ramon y Cajal, S.
(2019). The Genomic and Immune Landscapes of Lethal Metastatic Breast Cancer. Cell reports,
(2019). T-cell bispecific antibodies in node-positive breast cancer: novel therapeutic avenue for MHC class I loss variants. Annals of oncology,
(2019). Personalized circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer. Science translational medicine,
A robust personalized ctDNA test, TARDIS, achieves high accuracy for residual disease after completion of neoadjuvant therapy..
(2019). Next Generation-Targeted Amplicon Sequencing (NG-TAS): an optimised protocol and computational pipeline for cost-effective profiling of circulating tumour DNA. Genome medicine,
(2018). Shallow whole genome sequencing for robust copy number profiling of formalin-fixed paraffin-embedded breast cancers. Experimental and molecular pathology,
(2018). Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts. Bmc genomics,
(2017). Predicting treatment resistance and relapse through circulating DNA. The breast,
(2017). Big data in cancer genomics. Current opinion in systems biology,
De Mattos-Arruda, L.
(2017). Intersect-then-combine approach: improving the performance of somatic variant calling in whole exome sequencing data using multiple aligners and callers. Genome medicine,
(2017). New Model for Estimating Glomerular Filtration Rate in Patients With Cancer. Journal of clinical oncology,
Purpose The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. Methods We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 ( 51 Cr) EDTA excretion measurements ( 51 Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. 51 Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. Results Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)–adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. Conclusion In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care..
van 't Veer, L.J.
(2016). Prognostic Value of MammaPrint® in Invasive Lobular Breast Cancer. Biomarker insights,
MammaPrint® is a microarray-based gene expression test cleared by the US Food and Drug Administration to assess recurrence risk in early-stage breast cancer, aimed to guide physicians in making neoadjuvant and adjuvant treatment decisions. The increase in the incidence of invasive lobular carcinomas (ILCs) over the past decades and the modest representation of ILC in the MammaPrint development data set calls for a stratified survival analysis dedicated to this specific subgroup. Study Aim
The current study aimed to validate the prognostic value of the MammaPrint test for breast cancer patients with early-stage ILCs. Materials and Methods
Univariate and multivariate survival associations for overall survival (OS), distant metastasis-free interval (DMFI), and distant metastasis-free survival (DMFS) were studied in a study population of 217 early-stage ILC breast cancer patients from five different clinical studies. Results and Discussion
A significant association between MammaPrint High Risk and poor clinical outcome was shown for OS, DMFI, and DMFS. A subanalysis was performed on the lymph node-negative study population. In the lymph node-negative study population, we report an up to 11 times higher change in the diagnosis of an event in the MammaPrint High Risk group. For DMFI, the reported hazard ratio is 11.1 (95% confidence interval = 2.3–53.0). Conclusion
Study results validate MammaPrint as an independent factor for breast cancer patients with early-stage invasive lobular breast cancer. Hazard ratios up to 11 in multivariate analyses emphasize the independent value of MammaPrint, specifically in lymph node-negative ILC breast cancers. .
(2016). A Biobank of Breast Cancer Explants with Preserved Intra-tumor Heterogeneity to Screen Anticancer Compounds. Cell,
The inter- and intra-tumor heterogeneity of breast cancer needs to be adequately captured in pre-clinical models. We have created a large collection of breast cancer patient-derived tumor xenografts (PDTXs), in which the morphological and molecular characteristics of the originating tumor are preserved through passaging in the mouse. An integrated platform combining in vivo maintenance of these PDTXs along with short-term cultures of PDTX-derived tumor cells (PDTCs) was optimized. Remarkably, the intra-tumor genomic clonal architecture present in the originating breast cancers was mostly preserved upon serial passaging in xenografts and in short-term cultured PDTCs. We assessed drug responses in PDTCs on a high-throughput platform and validated several ex vivo responses in vivo. The biobank represents a powerful resource for pre-clinical breast cancer pharmacogenomic studies (http://caldaslab.cruk.cam.ac.uk/bcape), including identification of biomarkers of response or resistance..
(2015). A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer. Molecular oncology,
(2014). Pyogenic Granuloma as a Cutaneous Adverse Effect of Vemurafenib. New england journal of medicine,
de Bono, B.
van der Ent, M.
van Geet, C.
van der Reijden, B.A.
(2014). Transcriptional diversity during lineage commitment of human blood progenitors. Science,
A BLUEPRINT of immune cell development
To determine the epigenetic mechanisms that direct blood cells to develop into the many components of our immune system, the BLUEPRINT consortium examined the regulation of DNA and RNA transcription to dissect the molecular traits that govern blood cell differentiation. By inducing immune responses, Saeed
document the epigenetic changes in the genome that underlie immune cell differentiation. Cheng
demonstrate that trained monocytes are highly dependent on the breakdown of sugars in the presence of oxygen, which allows cells to produce the energy needed to mount an immune response. Chen
examine RNA transcripts and find that specific cell lineages use RNA transcripts of different length and composition (isoforms) to form proteins. Together, the studies reveal how epigenetic effects can drive the development of blood cells involved in the immune system.
, this issue
(2012). Management of febrile neutropenia in an acute oncology service. Qjm,
de Bono, B.
(2012). ApiNATOMY: A novel toolkit for visualizing multiscale anatomy schematics with phenotype-related information. Human mutation,
(2012). The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature,
DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation. Nature communications,
DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors..
The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes. Nature communications,
The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2,433 primary breast tumours that have copy number aberration (CNA), gene expression and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intra-tumour heterogeneity using mutant-allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13–14 or 8q24). High levels of intra-tumour heterogeneity are in general associated with a worse outcome, but highly aggressive tumours with 11q13–14 amplification have low levels of intra-tumour heterogeneity. These results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies..
The molecular landscape of Asian breast cancers reveals clinically relevant population-specific differences. Nature communications,
Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations..
De Mattos-Arruda, L.
The temporal mutational and immune tumour microenvironment remodelling of HER2-negative primary breast cancers. Npj breast cancer,
The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R2 = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R2 = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment..
de Koning, L.
Integration of genomic, transcriptomic and proteomic data identifies two biologically distinct subtypes of invasive lobular breast cancer. Scientific reports,
Invasive lobular carcinoma (ILC) is the second most frequently occurring histological breast cancer subtype after invasive ductal carcinoma (IDC), accounting for around 10% of all breast cancers. The molecular processes that drive the development of ILC are still largely unknown. We have performed a comprehensive genomic, transcriptomic and proteomic analysis of a large ILC patient cohort and present here an integrated molecular portrait of ILC. Mutations in CDH1 and in the PI3K pathway are the most frequent molecular alterations in ILC. We identified two main subtypes of ILCs: (i) an immune related subtype with mRNA up-regulation of PD-L1, PD-1 and CTLA-4 and greater sensitivity to DNA-damaging agents in representative cell line models; (ii) a hormone related subtype, associated with Epithelial to Mesenchymal Transition (EMT) and gain of chromosomes 1q and 8q and loss of chromosome 11q. Using the somatic mutation rate and eIF4B protein level, we identified three groups with different clinical outcomes, including a group with extremely good prognosis. We provide a comprehensive overview of the molecular alterations driving ILC and have explored links with therapy response. This molecular characterization may help to tailor treatment of ILC through the application of specific targeted, chemo- and/or immune-therapies..
Erratum: The somatic mutation profiles of 2,433 breast cancers refine their genomic and transcriptomic landscapes. Nature communications,
Nature Communications 7 Article number:11479 (2016); Published: 10 May 2016; Updated: 6 June 2016. The original version of this Article contained an error in the spelling of ‘refine’ in the title of the paper. This has now been corrected in both the PDF and HTML..
Pfam 10 years on: 10 000 families and still growing. Briefings in bioinformatics,
The Pfam protein families database. Nucleic acids research,