Showing papers by "Gad Getz published in 2017"

An immunogenic personal neoantigen vaccine for patients with melanoma

Abstract: Effective anti-tumour immunity in humans has been associated with the presence of T cells directed at cancer neoantigens, a class of HLA-bound peptides that arise from tumour-specific mutations. They are highly immunogenic because they are not present in normal tissues and hence bypass central thymic tolerance. Although neoantigens were long-envisioned as optimal targets for an anti-tumour immune response, their systematic discovery and evaluation only became feasible with the recent availability of massively parallel sequencing for detection of all coding mutations within tumours, and of machine learning approaches to reliably predict those mutated peptides with high-affinity binding of autologous human leukocyte antigen (HLA) molecules. We hypothesized that vaccination with neoantigens can both expand pre-existing neoantigen-specific T-cell populations and induce a broader repertoire of new T-cell specificities in cancer patients, tipping the intra-tumoural balance in favour of enhanced tumour control. Here we demonstrate the feasibility, safety, and immunogenicity of a vaccine that targets up to 20 predicted personal tumour neoantigens. Vaccine-induced polyfunctional CD4+ and CD8+ T cells targeted 58 (60%) and 15 (16%) of the 97 unique neoantigens used across patients, respectively. These T cells discriminated mutated from wild-type antigens, and in some cases directly recognized autologous tumour. Of six vaccinated patients, four had no recurrence at 25 months after vaccination, while two with recurrent disease were subsequently treated with anti-PD-1 (anti-programmed cell death-1) therapy and experienced complete tumour regression, with expansion of the repertoire of neoantigen-specific T cells. These data provide a strong rationale for further development of this approach, alone and in combination with checkpoint blockade or other immunotherapies.

Toil enables reproducible, open source, big biomedical data analyses

Abstract: Toil is portable, open-source workflow software that supports contemporary workflow definition languages and can be used to securely and reproducibly run scientific workflows efficiently at large-scale. To demonstrate Toil, we processed over 20,000 RNA-seq samples to create a consistent meta-analysis of five datasets free of computational batch effects that we make freely available. Nearly all the samples were analysed in under four days using a commercial cloud cluster of 32,000 preemptable cores.

Resistance to checkpoint blockade therapy through inactivation of antigen presentation.

Abstract: Treatment with immune checkpoint blockade (CPB) therapies often leads to prolonged responses in patients with metastatic melanoma, but the common mechanisms of primary and acquired resistance to these agents remain incompletely characterized and have yet to be validated in large cohorts. By analyzing longitudinal tumor biopsies from 17 metastatic melanoma patients treated with CPB therapies, we observed point mutations, deletions or loss of heterozygosity (LOH) in beta-2-microglobulin (B2M), an essential component of MHC class I antigen presentation, in 29.4% of patients with progressing disease. In two independent cohorts of melanoma patients treated with anti-CTLA4 and anti-PD1, respectively, we find that B2M LOH is enriched threefold in non-responders (~30%) compared to responders (~10%) and associated with poorer overall survival. Loss of both copies of B2M is found only in non-responders. B2M loss is likely a common mechanism of resistance to therapies targeting CTLA4 or PD1.

Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq

Abstract: Tumor subclasses differ according to the genotypes and phenotypes of malignant cells as well as the composition of the tumor microenvironment (TME). We dissected these influences in isocitrate dehydrogenase (IDH)-mutant gliomas by combining 14,226 single-cell RNA sequencing (RNA-seq) profiles from 16 patient samples with bulk RNA-seq profiles from 165 patient samples. Differences in bulk profiles between IDH-mutant astrocytoma and oligodendroglioma can be primarily explained by distinct TME and signature genetic events, whereas both tumor types share similar developmental hierarchies and lineages of glial differentiation. As tumor grade increases, we find enhanced proliferation of malignant cells, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia expression programs in TME. Our work provides a unifying model for IDH-mutant gliomas and a general framework for dissecting the differences among human tumor subclasses.

Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq

Abstract: Tumor subclasses differ according to the genotypes and phenotypes of malignant cells as well as the composition of the tumor microenvironment (TME). We dissected these influences in isocitrate dehydrogenase (IDH)-mutant gliomas by combining 14,226 single-cell RNA sequencing (RNA-seq) profiles from 16 patient samples with bulk RNA-seq profiles from 165 patient samples. Differences in bulk profiles between IDH-mutant astrocytoma and oligodendroglioma can be primarily explained by distinct TME and signature genetic events, whereas both tumor types share similar developmental hierarchies and lineages of glial differentiation. As tumor grade increases, we find enhanced proliferation of malignant cells, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia expression programs in TME. Our work provides a unifying model for IDH-mutant gliomas and a general framework for dissecting the differences among human tumor subclasses.

Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors

Abstract: Whole-exome sequencing of cell-free DNA (cfDNA) could enable comprehensive profiling of tumors from blood but the genome-wide concordance between cfDNA and tumor biopsies is uncertain. Here we report ichorCNA, software that quantifies tumor content in cfDNA from 0.1× coverage whole-genome sequencing data without prior knowledge of tumor mutations. We apply ichorCNA to 1439 blood samples from 520 patients with metastatic prostate or breast cancers. In the earliest tested sample for each patient, 34% of patients have ≥10% tumor-derived cfDNA, sufficient for standard coverage whole-exome sequencing. Using whole-exome sequencing, we validate the concordance of clonal somatic mutations (88%), copy number alterations (80%), mutational signatures, and neoantigens between cfDNA and matched tumor biopsies from 41 patients with ≥10% cfDNA tumor content. In summary, we provide methods to identify patients eligible for comprehensive cfDNA profiling, revealing its applicability to many patients, and demonstrate high concordance of cfDNA and metastatic tumor whole-exome sequencing.

A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer

Abstract: Biallelic inactivation of BRCA1 or BRCA2 is associated with a pattern of genome-wide mutations known as signature 3. By analyzing ∼1,000 breast cancer samples, we confirmed this association and established that germline nonsense and frameshift variants in PALB2, but not in ATM or CHEK2, can also give rise to the same signature. We were able to accurately classify missense BRCA1 or BRCA2 variants known to impair homologous recombination (HR) on the basis of this signature. Finally, we show that epigenetic silencing of RAD51C and BRCA1 by promoter methylation is strongly associated with signature 3 and, in our data set, was highly enriched in basal-like breast cancers in young individuals of African descent.

Genomic complexity of multiple myeloma and its clinical implications

Abstract: Multiple myeloma (MM) is a genetically complex disease that evolves from pre-malignant stages, such as monoclonal gammaopathy of undetermined significance and smouldering multiple myeloma, and progresses to symptomatic MM; this continuum provides a unique framework to study the sequential genomic evolution of MM. In the past 5 years, results from large-scale whole-exome sequencing studies have provided new insights into the clonal heterogeneity and evolution of the disease. Moreover, the recurrent co-occurrence of genomic events helps to dissect the genomic complexity underlying tumour progression. According to the primary genetic events involved in tumorigenesis, MM tumours are hierarchically subdivided into hyperdiploid and non-hyperdiploid subtypes; subsequently, secondary genetic events lead to tumour progression. In this Review, we describe the 'driver' gene alterations involved in the development and progression of MM, with a focus on the sequential acquisition of the main genomic aberrations. We also provide valuable insight into the clonal heterogeneity and clonal evolution of the disease, as well as into the therapeutic implications of a comprehensive understanding of the genomic complexity of MM.

Polyclonal Secondary FGFR2 Mutations Drive Acquired Resistance to FGFR Inhibition in Patients with FGFR2 Fusion-Positive Cholangiocarcinoma.

Abstract: Genetic alterations in the fibroblast growth factor receptor (FGFR) pathway are promising therapeutic targets in many cancers, including intrahepatic cholangiocarcinoma (ICC). The FGFR inhibitor BGJ398 displayed encouraging efficacy in patients with FGFR2 fusion-positive ICC in a phase II trial, but the durability of response was limited in some patients. Here, we report the molecular basis for acquired resistance to BGJ398 in three patients via integrative genomic characterization of cell-free circulating tumor DNA (cfDNA), primary tumors, and metastases. Serial analysis of cfDNA demonstrated multiple recurrent point mutations in the FGFR2 kinase domain at progression. Accordingly, biopsy of post-progression lesions and rapid autopsy revealed marked inter- and intralesional heterogeneity, with different FGFR2 mutations in individual resistant clones. Molecular modeling and in vitro studies indicated that each mutation led to BGJ398 resistance and was surmountable by structurally distinct FGFR inhibitors. Thus, polyclonal secondary FGFR2 mutations represent an important clinical resistance mechanism that may guide the development of future therapeutic strategies.Significance: We report the first genetic mechanisms of clinical acquired resistance to FGFR inhibition in patients with FGFR2 fusion-positive ICC. Our findings can inform future strategies for detecting resistance mechanisms and inducing more durable remissions in ICC and in the wide variety of cancers where the FGFR pathway is being explored as a therapeutic target. Cancer Discov; 7(3); 252-63. ©2016 AACR.See related commentary by Smyth et al., p. 248This article is highlighted in the In This Issue feature, p. 235.

Tumor-suppressor genes that escape from X-inactivation contribute to cancer sex bias

Abstract: There is a striking and unexplained male predominance across many cancer types. A subset of X-chromosome genes can escape X-inactivation, which would protect females from complete functional loss by a single mutation. To identify putative 'escape from X-inactivation tumor-suppressor' (EXITS) genes, we examined somatic alterations from >4,100 cancers across 21 tumor types for sex bias. Six of 783 non-pseudoautosomal region (PAR) X-chromosome genes (ATRX, CNKSR2, DDX3X, KDM5C, KDM6A, and MAGEC3) harbored loss-of-function mutations more frequently in males (based on a false discovery rate < 0.1), in comparison to zero of 18,055 autosomal and PAR genes (Fisher's exact P < 0.0001). Male-biased mutations in genes that escape X-inactivation were observed in combined analysis across many cancers and in several individual tumor types, suggesting a generalized phenomenon. We conclude that biallelic expression of EXITS genes in females explains a portion of the reduced cancer incidence in females as compared to males across a variety of tumor types.

The evolutionary history of 2,658 cancers

Abstract: Cancer develops through a process of somatic evolution. Here, we reconstruct the evolutionary history of 2,778 tumour samples from 2,658 donors spanning 39 cancer types. Characteristic copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma, are found amongst the earliest events in tumour evolution. The early phases of oncogenesis are driven by point mutations in a restricted set of cancer genes, often including biallelic inactivation of tumour suppressors. By contrast, increased genomic instability, a more than three-fold diversification of driver genes, and an acceleration of mutational processes are features of later stages. Clock-like mutations yield estimates for whole genome duplications and subclonal diversification in chronological time. Our results suggest that driver mutations often precede diagnosis by many years, and in some cases decades. Taken together, these data reveal common and divergent trajectories of cancer evolution, pivotal for understanding tumour biology and guiding early cancer detection.

Recurrent and functional regulatory mutations in breast cancer

Abstract: Genomic analysis of tumours has led to the identification of hundreds of cancer genes on the basis of the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here we perform deep sequencing in 360 primary breast cancers and develop computational methods to identify significantly mutated promoters. Clear signals are found in the promoters of three genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbours a mutational hotspot in its promoter leading to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that affect protein binding to their promoters and alter expression levels. Our study shows that promoter regions harbour recurrent mutations in cancer with functional consequences and that the mutations occur at similar frequencies as in coding regions. Power analyses indicate that more such regions remain to be discovered through deep sequencing of adequately sized cohorts of patients.

Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Abstract: Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.

The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy.

Abstract: Treatment of chronic lymphocytic leukemia (CLL) has shifted from chemo-immunotherapy to targeted agents. To define the evolutionary dynamics induced by targeted therapy in CLL, we perform serial exome and transcriptome sequencing for 61 ibrutinib-treated CLLs. Here, we report clonal shifts (change >0.1 in clonal cancer cell fraction, Q < 0.1) in 31% of patients during the first year of therapy, associated with adverse outcome. We also observe transcriptional downregulation of pathways mediating energy metabolism, cell cycle, and B cell receptor signaling. Known and previously undescribed mutations in BTK and PLCG2, or uncommonly, other candidate alterations are present in seventeen subjects at the time of progression. Thus, the frequently observed clonal shifts during the early treatment period and its potential association with adverse outcome may reflect greater evolutionary capacity, heralding the emergence of drug-resistant clones. In a subset of patients with chronic lymphocytic leukemia (CLL) treated with targeted agents, such as ibrutinib, drug resistant subclones emerge. Here, the authors report on transcriptional changes in CLL patients treated with ibrutinib and identify early clonal shifts associated with evolution of resistant clones.

Analysis of somatic microsatellite indels identifies driver events in human tumors

Abstract: Microsatellites (MSs) are tracts of variable-length repeats of short DNA motifs that exhibit high rates of mutation in the form of insertions or deletions (indels) of the repeated motif. Despite their prevalence, the contribution of somatic MS indels to cancer has been largely unexplored, owing to difficulties in detecting them in short-read sequencing data. Here we present two tools: MSMuTect, for accurate detection of somatic MS indels, and MSMutSig, for identification of genes containing MS indels at a higher frequency than expected by chance. Applying MSMuTect to whole-exome data from 6,747 human tumors representing 20 tumor types, we identified >1,000 previously undescribed MS indels in cancer genes. Additionally, we demonstrate that the number and pattern of MS indels can accurately distinguish microsatellite-stable tumors from tumors with microsatellite instability, thus potentially improving classification of clinically relevant subgroups. Finally, we identified seven MS indel driver hotspots: four in known cancer genes (ACVR2A, RNF43, JAK1, and MSH3) and three in genes not previously implicated as cancer drivers (ESRP1, PRDM2, and DOCK3).

Mutational patterns in chemotherapy resistant muscle-invasive bladder cancer

Abstract: Despite continued widespread use, the genomic effects of cisplatin-based chemotherapy and implications for subsequent treatment are incompletely characterized. Here, we analyze whole exome sequencing of matched pre- and post-neoadjuvant cisplatin-based chemotherapy primary bladder tumor samples from 30 muscle-invasive bladder cancer patients. We observe no overall increase in tumor mutational burden post-chemotherapy, though a significant proportion of subclonal mutations are unique to the matched pre- or post-treatment tumor, suggesting chemotherapy-induced and/or spatial heterogeneity. We subsequently identify and validate a novel mutational signature in post-treatment tumors consistent with known characteristics of cisplatin damage and repair. We find that post-treatment tumor heterogeneity predicts worse overall survival, and further observe alterations in cell-cycle and immune checkpoint regulation genes in post-treatment tumors. These results provide insight into the clinical and genomic dynamics of tumor evolution with cisplatin-based chemotherapy, suggest mechanisms of clinical resistance, and inform development of clinically relevant biomarkers and trials of combination therapies. The impact of cisplatin-based chemotherapy on tumor genomes is complex. Here, the authors study matched pre- and post-chemotherapy primary samples in muscle-invasive bladder cancer, finding a cisplatin-based mutational signature, and highlighting the impact of intratumor heterogeneity on survival.

Comparison of algorithms for the detection of cancer drivers at subgene resolution

Abstract: Understanding genetic events that lead to cancer initiation and progression remains one of the biggest challenges in cancer biology. Traditionally, most algorithms for cancer-driver identification look for genes that have more mutations than expected from the average background mutation rate. However, there is now a wide variety of methods that look for nonrandom distribution of mutations within proteins as a signal for the driving role of mutations in cancer. Here we classify and review such subgene-resolution algorithms, compare their findings on four distinct cancer data sets from The Cancer Genome Atlas and discuss how predictions from these algorithms can be interpreted in the emerging paradigms that challenge the simple dichotomy between driver and passenger genes.

Survival of Del17p CLL Depends on Genomic Complexity and Somatic Mutation.

Abstract: Purpose: Chronic lymphocytic leukemia (CLL) with 17p deletion typically progresses quickly and is refractory to most conventional therapies. However, some del(17p) patients do not progress for years, suggesting that del(17p) is not the only driving event in CLL progression. We hypothesize that other concomitant genetic abnormalities underlie the clinical heterogeneity of del(17p) CLL. Experimental Design: We profiled the somatic mutations and copy number alterations (CNA) in a large group of del(17p) CLLs as well as wild-type CLL and analyzed the genetic basis of their clinical heterogeneity. Results: We found that increased somatic mutation number associates with poor overall survival independent of 17p deletion (P = 0.003). TP53 mutation was present in 81% of del(17p) CLL, mostly clonal (82%), and clonal mutations with del(17p) exhibit shorter overall survival than subclonal mutations with del(17p) (P = 0.019). Del(17p) CLL has a unique driver mutation profile, including NOTCH1 (15%), RPS15 (12%), DDX3X (8%), and GPS2 (6%). We found that about half of del(17p) CLL cases have recurrent deletions at 3p, 4p, or 9p and that any of these deletions significantly predicts shorter overall survival. In addition, the number of CNAs, but not somatic mutations, predicts shorter time to treatment among patients untreated at sampling. Indolent del(17p) CLLs were characterized by absent or subclonal TP53 mutation and few CNAs, with no difference in somatic mutation number. Conclusions: We conclude that del(17p) has a unique genomic profile and that clonal TP53 mutations, 3p, 4p, or 9p deletions, and genomic complexity are associated with shorter overall survival. Clin Cancer Res; 23(3); 735–45. ©2016 AACR.

The whole-genome panorama of cancer drivers

Abstract: Somatic genetic mutations have been linked to tumorigenesis for more than 30 years. However, only partial insights into their contribution to tumor development have been possible to date. Using a comprehensive approach, here we obtained a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, and each carry on average 4.6 driver events. Despite several orders of magnitude of variation of tumor mutation burden, the number of driver point mutations is strikingly stable. Twenty-two percent of tumors contain driver non-coding mutations and half of all cancer genes undergo various types of mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics.

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

Abstract: Discovery of cancer drivers has traditionally focused on the identification of protein-coding genes. Here we present a comprehensive analysis of putative cancer driver mutations in both protein-coding and non-coding genomic regions across >2,500 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We developed a statistically rigorous strategy for combining significance levels from multiple driver discovery methods and demonstrate that the integrated results overcome limitations of individual methods. We combined this strategy with careful filtering and applied it to protein-coding genes, promoters, untranslated regions (UTRs), distal enhancers and non-coding RNAs. These analyses redefine the landscape of non-coding driver mutations in cancer genomes, confirming a few previously reported elements and raising doubts about others, while identifying novel candidate elements across 27 cancer types. Novel recurrent events were found in the promoters or 5’UTRs of TP53, RFTN1, RNF34, and MTG2, in the 3’UTRs of NFKBIZ and TOB1, and in the non-coding RNA RMRP. We provide evidence that the previously reported non-coding RNAs NEAT1 and MALAT1 may be subject to a localized mutational process. Perhaps the most striking finding is the relative paucity of point mutations driving cancer in non-coding genes and regulatory elements. Though we have limited power to discover infrequent non-coding drivers in individual cohorts, combined analysis of promoters of known cancer genes show little excess of mutations beyond TERT.