Added Value of Whole-Exome and Transcriptome Sequencing for Clinical Molecular Screenings of Advanced Cancer Patients With Solid Tumors.

Comprehensive genomic profiling using high-throughput sequencing brings a wealth of information, and its place in the clinical setting has been increasingly prominent. This review emphasizes the utility of whole-exome sequencing (WES) and transcriptome sequencing (RNAseq) in patient care and clinical research, based on published reports as well as our experience with the MOSCATO-01 (MOlecular Screening for CAncer Treatment Optimization) molecular triage trial at Gustave Roussy Cancer Center. In this trial, all contributive samples of patients with advanced solid tumors were analyzed prospectively with targeted gene sequencing (TGS) and comparative genomic hybridization. In addition, 92 consecutive metastatic patients with contributive biopsies were sequenced for WES and RNAseq and compared with TGS and comparative genomic hybridization. Whole-exome sequencing allowed the reporting of additional variants in relevant genes in 38% of patients. Mutation detection sensitivity of WES was 95% compared with TGS. Additional information derived from WES and RNAseq could influence clinical decision, including fusion transcripts, expression levels, allele-specific expression, alternate transcripts, RNA-based pathogen diagnostic, tumor mutation load, mutational signatures, expression signatures, HLA genotyping, and neoepitope prediction. The current challenge is to be able to process the large-scale data from these comprehensive genome-wide technologies in an efficient way.

Mutational Profile of Metastatic Breast Cancers: A Retrospective Analysis.

BACKGROUND: Major advances have been achieved in the characterization of early breast cancer (eBC) genomic profiles. Metastatic breast cancer (mBC) is associated with poor outcomes, yet limited information is available on the genomic profile of this disease. This study aims to decipher mutational profiles of mBC using next-generation sequencing. METHODS AND FINDINGS: Whole-exome sequencing was performed on 216 tumor-blood pairs from mBC patients who underwent a biopsy in the context of the SAFIR01, SAFIR02, SHIVA, or Molecular Screening for Cancer Treatment Optimization (MOSCATO) prospective trials. Mutational profiles from 772 primary breast tumors from The Cancer Genome Atlas (TCGA) were used as a reference for comparing primary and mBC mutational profiles. Twelve genes (TP53, PIK3CA, GATA3, ESR1, MAP3K1, CDH1, AKT1, MAP2K4, RB1, PTEN, CBFB, and CDKN2A) were identified as significantly mutated in mBC (false discovery rate [FDR] < 0.1). Eight genes (ESR1, FSIP2, FRAS1, OSBPL3, EDC4, PALB2, IGFN1, and AGRN) were more frequently mutated in mBC as compared to eBC (FDR < 0.01). ESR1 was identified both as a driver and as a metastatic gene (n = 22, odds ratio = 29, 95% CI [9-155], p = 1.2e-12) and also presented with focal amplification (n = 9) for a total of 31 mBCs with either ESR1 mutation or amplification, including 27 hormone receptor positive (HR+) and HER2 negative (HER2-) mBCs (19%). HR+/HER2- mBC presented a high prevalence of mutations on genes located on the mechanistic target of rapamycin (mTOR) pathway (TSC1 and TSC2) as compared to HR+/HER2- eBC (respectively 6% and 0.7%, p = 0.0004). Other actionable genes were more frequently mutated in HR+ mBC, including ERBB4 (n = 8), NOTCH3 (n = 7), and ALK (n = 7). Analysis of mutational signatures revealed a significant increase in APOBEC-mediated mutagenesis in HR+/HER2- metastatic tumors as compared to primary TCGA samples (p < 2e-16). The main limitations of this study include the absence of bone metastases and the size of the cohort, which might not have allowed the identification of rare mutations and their effect on survival. CONCLUSIONS: This work reports the results of the analysis of the first large-scale study on mutation profiles of mBC. This study revealed genomic alterations and mutational signatures involved in the resistance to therapies, including actionable mutations.

Improving the Performance of Somatic Mutation Identification by Recovering Circulating Tumor DNA Mutations.

DNA extracted from cancer patients' whole blood may contain somatic mutations from circulating tumor DNA (ctDNA) fragments. In this study, we introduce cmDetect, a computational method for the systematic identification of ctDNA mutations using whole-exome sequencing of a cohort of tumor and corresponding peripheral whole-blood samples. Through the analysis of simulated data, we demonstrated an increase in sensitivity in calling somatic mutations by combining cmDetect to two widely used mutation callers. In a cohort of 93 breast cancer metastatic patients, cmDetect identified ctDNA mutations in 54% of the patients and recovered somatic mutations in cancer genes EGFR, PIK3CA, and TP53 We further showed that cmDetect detected ctDNA in 89% of patients with confirmed mutated cell-free tumor DNA by plasma analyses (n = 9) within 46 pan-cancer patients. Our results prompt immediate consideration of the use of this method as an additional step in somatic mutation calling using whole-exome sequencing data with blood samples as controls. Cancer Res; 76(20); 5954-61. ©2016 AACR.

Mutational Landscape and Sensitivity to Immune Checkpoint Blockers.

Immunotherapy is currently transforming cancer treatment. Notably, immune checkpoint blockers (ICB) have shown unprecedented therapeutic successes in numerous tumor types, including cancers that were traditionally considered as nonimmunogenic. However, a significant proportion of patients do not respond to these therapies. Thus, early selection of the most sensitive patients is key, and the development of predictive companion biomarkers constitutes one of the biggest challenges of ICB development. Recent publications have suggested that the tumor genomic landscape, mutational load, and tumor-specific neoantigens are potential determinants of the response to ICB and can influence patients' outcomes upon immunotherapy. Furthermore, defects in the DNA repair machinery have consistently been associated with improved survival and durable clinical benefit from ICB. Thus, closely reflecting the DNA damage repair capacity of tumor cells and their intrinsic genomic instability, the mutational load and its associated tumor-specific neoantigens appear as key predictive paths to anticipate potential clinical benefits of ICB. In the era of next-generation sequencing, while more and more patients are getting the full molecular portrait of their tumor, it is crucial to optimally exploit sequencing data for the benefit of patients. Therefore, sequencing technologies, analytic tools, and relevant criteria for mutational load and neoantigens prediction should be homogenized and combined in more integrative pipelines to fully optimize the measurement of such parameters, so that these biomarkers can ultimately reach the analytic validity and reproducibility required for a clinical implementation. Clin Cancer Res; 22(17); 4309-21. ©2016 AACR.

Circulating Cell-Free Tumor DNA Analysis of 50 Genes by Next-Generation Sequencing in the Prospective MOSCATO Trial.

PURPOSE: Liquid biopsies based on circulating cell-free DNA (cfDNA) analysis are described as surrogate samples for molecular analysis. We evaluated the concordance between tumor DNA (tDNA) and cfDNA analysis on a large cohort of patients with advanced or metastatic solid tumor, eligible for phase I trial and with good performance status, enrolled in MOSCATO 01 trial (clinical trial NCT01566019). EXPERIMENTAL DESIGN: Blood samples were collected at inclusion and cfDNA was extracted from plasma for 334 patients. Hotspot mutations were screened using next-generation sequencing for 50 cancer genes. RESULTS: Among the 283 patients with tDNA-cfDNA pairs, 121 had mutation in both, 99 in tumor only, 5 in cfDNA only, and for 58 patients no mutation was detected, leading to a 55.0% estimated sensitivity [95% confidence interval (CI), 48.4%-61.6%] at the patient level. Among the 220 patients with mutations in tDNA, the sensitivity of cfDNA analysis was significantly linked to the number of metastatic sites, albumin level, tumor type, and number of lines of treatment. A sensitivity prediction score could be derived from clinical parameters. Sensitivity is 83% in patients with a high score (≥8). In addition, we analyzed cfDNA for 51 patients without available tissue sample. Mutations were detected for 22 patients, including 19 oncogenic variants and 8 actionable mutations. CONCLUSIONS: Detection of somatic mutations in cfDNA is feasible for prescreening phase I candidates with a satisfactory specificity; overall sensitivity can be improved by a sensitivity score allowing to select patients for whom cfDNA constitutes a reliable noninvasive surrogate to screen mutations. Clin Cancer Res; 22(12); 2960-8. ©2016 AACR.