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Background: Platinum-based therapy is an effective treatment for a subset of triple-negative breast cancer and ovarian cancer patients. In order to increase response rate and decrease unnecessary use, robust biomarkers that predict response to therapy are needed. Patients and methods: We performed an integrated genomic approach combining differential analysis of gene expression and DNA copy number in sensitive compared with resistant triple-negative breast cancers in two independent neoadjuvant cisplatin-treated cohorts. Functional relevance of significant hits was investigated in vitro by overexpression, knockdown and targeted inhibitor treatment. Results: We identified two genes, the Bloom helicase (BLM) and Fanconi anemia complementation group I (FANCI), that have both increased DNA copy number and gene expression in the platinum-sensitive cases. Increased level of expression of these two genes was also associated with platinum but not with taxane response in ovarian cancer. As a functional validation, we found that overexpression of BLM promotes DNA damage and induces sensitivity to cisplatin but has no effect on paclitaxel sensitivity. Conclusions: A biomarker based on the expression levels of the BLM and FANCI genes is a potential predictor of platinum sensitivity in triple-negative breast cancer and ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: Exome or whole-genome deep sequencing of tumor DNA along with paired normal DNA can potentially provide a detailed picture of the somatic mutations that characterize the tumor. However, analysis of such sequence data can be complicated by the presence of normal cells in the tumor specimen, by intratumor heterogeneity, and by the sheer size of the raw data. In particular, determination of copy number variations from exome sequencing data alone has proven difficult; thus, single nucleotide polymorphism (SNP) arrays have often been used for this task. Recently, algorithms to estimate absolute, but not allele-specific, copy number profiles from tumor sequencing data have been described. Materials and methods We developed Sequenza, a software package that uses paired tumor-normal DNA sequencing data to estimate tumor cellularity and ploidy, and to calculate allele-specific copy number profiles and mutation profiles. We applied Sequenza, as well as two previously published algorithms, to exome sequence data from 30 tumors from The Cancer Genome Atlas. We assessed the performance of these algorithms by comparing their results with those generated using matched SNP arrays and processed by the allele-specific copy number analysis of tumors (ASCAT) algorithm. Results: Comparison between Sequenza/exome and SNP/ASCAT revealed strong correlation in cellularity (Pearson's r = 0.90) and ploidy estimates (r = 0.42, or r = 0.94 after manual inspecting alternative solutions). This performance was noticeably superior to previously published algorithms. In addition, in artificial data simulating normal-tumor admixtures, Sequenza detected the correct ploidy in samples with tumor content as low as 30%. Conclusions: The agreement between Sequenza and SNP array-based copy number profiles suggests that exome sequencing alone is sufficient not only for identifying small scale mutations but also for estimating cellularity and inferring DNA copy number aberrations.

Background Molecular biomarkers aim to stratify cancer patients into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumour stage. Transcriptomic intra-tumour heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types. Methods Here, we analyse multi-region whole-exome and RNA sequencing data for 156 tumour regions from 48 TRACERx patients to explore and control for RNA-ITH in non-small cell lung cancer (NSCLC). Results We find that chromosomal instability (CIN) is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumour sampling bias. To address this, we identify genes expressed homogeneously within individual tumours that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumour evolution. Leveraging single-cell data, we examine the origins of the expression signals, and relate our findings to published biological and clinical gene expression signatures. Conclusions Clonal transcriptomic biomarkers overcome tumour sampling bias, associate with survival independently of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types. Clinical trial identification NCT0188860. Legal entity responsible for the study University College London (UCL/12/0279) and has been approved by an independent Research Ethics Committee (13/LO/1546). Funding Francis Crick Institute that receives its core funding from Cancer Research UK (FC001169, FC001202), the UK Medical Research Council (FC001169, FC001202), and the Wellcome Trust (FC001169, FC001202). The research leading to these results has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007-2013) Consolidator Grant (FP7-THESEUS-617844), European Commission ITN (FP7-PloidyNet 607722), ERC Advanced Grant (PROTEUS) has received funding from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 835297), Chromavision – this project has received funding from the European's Union Horizon 2020 research and innovation programme (grant agreement No. 665233). Disclosure D. Biswas: Non-remunerated activity/ies, patent co-inventor: CRUK; Studentship: Jean Shanks Foundation MBPhD; Funding (self): MBPhD programme at University College London; Funding (institution): the NIHR BRC at University College London Hospitals. N.J. Birkbak: Non-remunerated activity/ies, patent co-inventor: CRUK; Fellow: Lundbeck Foundation; Funding (self): the Aarhus University Research Foundation; Funding (institution): Danish Cancer Society. N. McGranahan: Non-remunerated activity/ies, patent co-inventor: CRUK. Fellow: Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society (Grant Number 211179/Z/18/Z); Funding (institution): CRUK, Rosetrees, the NIHR BRC at University College London Hospitals. C. Swanton: Advisory / Consultancy, Research grant / Funding (institution): Pfizer; Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca; Advisory / Consultancy, Research grant / Funding (institution): BMS; Advisory / Consultancy, Research grant / Funding (institution): Roche; Advisory / Consultancy, Research grant / Funding (institution): Ventana; Advisory / Consultancy: Novartis; Advisory / Consultancy: GlaxoSmithKline; Advisory / Consultancy: MSD; Advisory / Consultancy: Celgene; Advisory / Consultancy: Illumina; Advisory / Consultancy: Genentech; Advisory / Consultancy, Shareholder / Stockholder / Stock options: GRAIL; Advisory / Consultancy: Medicxi; Advisory / Consultancy: Sarah Cannon Research Institute; Advisory / Consultancy: Dynamo Therapeutics; Shareholder / Stockholder / Stock options: ApoGen Biotechnologies; Shareholder / Stockholder / Stock options: Epic Bioscience; Shareholder / Stockholder / Stock options: Achilles Therapeutics. Funding (institution) Cancer Research UK (TRACERx and CRUK Cancer Immunotherapy Catalyst Network), the CRUK Lung Cancer Centre of Excellence, Stand Up 2 Cancer (SU2C), the Rosetrees Trust, Butterfield and Stoneygate Trusts, NovoNordisk Foundation (ID16584), the Prostate Cancer Foundation, the Breast Cancer Research Foundation (BCRF), National Institute for Health Research, the University College London Hospitals Biomedical Research Centre, and the Cancer Research UK University College London Experimental Cancer Medicine Centre. [ABSTRACT FROM AUTHOR]

BACKGROUND Among patients with non-small-cell lung cancer (NSCLC), data on intratumor heterogeneity and cancer genome evolution have been limited to small retrospective cohorts. We wanted to prospectively investigate intratumor heterogeneity in relation to clinical outcome and to determine the clonal nature of driver events and evolutionary processes in early-stage NSCLC. METHODS In this prospective cohort study, we performed multiregion whole-exome sequencing on 100 early-stage NSCLC tumors that had been resected before systemic therapy. We sequenced and analyzed 327 tumor regions to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between intratumor heterogeneity and recurrence-free survival. RESULTS We observed widespread intratumor heterogeneity for both somatic copy-number alterations and mutations. Driver mutations in EGFR, MET, BRAF, and TP53 were almost always clonal. However, heterogeneous driver alterations that occurred later in evolution were found in more than 75% of the tumors and were common in PIK3CA and NF1 and in genes that are involved in chromatin modification and DNA damage response and repair. Genome doubling and ongoing dynamic chromosomal instability were associated with intratumor heterogeneity and resulted in parallel evolution of driver somatic copy-number alterations, including amplifications in CDK4, FOXA1, and BCL11A. Elevated copy-number heterogeneity was associated with an increased risk of recurrence or death (hazard ratio, 4.9; P = 4.4×10-4), which remained significant in multivariate analysis. CONCLUSIONS Intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, a finding that supports the potential value of chromosome instability as a prognostic predictor. [ABSTRACT FROM AUTHOR]