Noushin Niknafs

Exome sequencing identifies frequent inactivating mutations in BAP1, ARID1A and PBRM1 in intrahepatic cholangiocarcinomas

Through exomic sequencing of 32 intrahepatic cholangiocarcinomas, we discovered frequent inactivating mutations in multiple chromatin-remodeling genes (including BAP1, ARID1A and PBRM1), and mutation in one of these genes occurred in almost half of the carcinomas sequenced. We also identified frequent mutations at previously reported hotspots in the IDH1 and IDH2 genes encoding metabolic enzymes in intrahepatic cholangiocarcinomas. In contrast, TP53 was the most frequently altered gene in a series of nine gallbladder carcinomas. These discoveries highlight the key role of dysregulated chromatin remodeling in intrahepatic cholangiocarcinomas.

The genomic landscape of response to EGFR blockade in colorectal cancer

Colorectal cancer is the third most common cancer worldwide, with 1.2 million patients diagnosed annually. In late-stage colorectal cancer, the most commonly used targeted therapies are the monoclonal antibodies cetuximab and panitumumab, which prevent epidermal growth factor receptor (EGFR) activation. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in colorectal cancer and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in colorectal cancer on response to anti-EGFR antibody therapy, here we perform complete exome sequence and copy number analyses of 129 patient-derived tumour grafts and targeted genomic analyses of 55 patient tumours, all of which were KRAS wild-type. We analysed the response of tumours to anti-EGFR antibody blockade in tumour graft models and in clinical settings and functionally linked therapeutic responses to mutational data. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumours with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumour graft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluating response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and delineate new avenues for intervention in managing colorectal cancer.

A Combination of Molecular Markers and Clinical Features Improve the Classification of Pancreatic Cysts

BACKGROUND & AIMS The management of pancreatic cysts poses challenges to both patients and their physicians. We investigated whether a combination of molecular markers and clinical information could improve the classification of pancreatic cysts and management of patients. METHODS We performed a multi-center, retrospective study of 130 patients with resected pancreatic cystic neoplasms (12 serous cystadenomas, 10 solid pseudopapillary neoplasms, 12 mucinous cystic neoplasms, and 96 intraductal papillary mucinous neoplasms). Cyst fluid was analyzed to identify subtle mutations in genes known to be mutated in pancreatic cysts (BRAF, CDKN2A, CTNNB1, GNAS, KRAS, NRAS, PIK3CA, RNF43, SMAD4, TP53, and VHL); to identify loss of heterozygozity at CDKN2A, RNF43, SMAD4, TP53, and VHL tumor suppressor loci; and to identify aneuploidy. The analyses were performed using specialized technologies for implementing and interpreting massively parallel sequencing data acquisition. An algorithm was used to select markers that could classify cyst type and grade. The accuracy of the molecular markers was compared with that of clinical markers and a combination of molecular and clinical markers. RESULTS We identified molecular markers and clinical features that classified cyst type with 90%-100% sensitivity and 92%-98% specificity. The molecular marker panel correctly identified 67 of the 74 patients who did not require surgery and could, therefore, reduce the number of unnecessary operations by 91%. CONCLUSIONS We identified a panel of molecular markers and clinical features that show promise for the accurate classification of cystic neoplasms of the pancreas and identification of cysts that require surgery.

Mutational Signature of Aristolochic Acid Exposure as Revealed by Whole-Exome Sequencing

The mutational signature of aristolochic acid exemplifies how genome-wide sequencing can be used to identify environmental exposures leading to cancer. Carcinogen AAlert Aristolochic acid (AA) is a natural compound derived from plants in the Aristolochia genus. For centuries, Aristolochia has been used throughout Asia to treat a variety of ailments as a component of traditional Chinese medicine. In recent years, however, a more sinister side of this herb has come to light when it was linked to kidney damage and cancers of the urinary tract. Now, two studies by Poon et al. and Hoang et al. present a “molecular signature” of AA-induced DNA damage, which helps to explain the mutagenic effects of AA and may also be useful as a way to detect unsuspected AA exposure as a cause of cancer. The molecular signature seen in AA-associated tumors is characterized by a predominance of A:T-to-T:A transversions, a relatively unusual type of mutation that is infrequently seen in other types of cancer, including those caused by other carcinogens. These mutations concentrate at splice sites, causing the inappropriate inclusion or exclusion of entire exons in the resulting mRNA. The overall mutation rate is another notable feature of AA-associated cancers, because it is several times higher than the rate of mutations caused by other carcinogens such as tobacco and ultraviolet light. In both studies, the authors also used the molecular signature to discover that AA was a likely cause of tumors previously attributed to other carcinogens. In one case, a urinary tract cancer that had been attributed to smoking and, in the other case, a liver cancer previously attributed to a chronic hepatitis infection were both identified as having the telltale signature of AA mutagenesis. The identification of a specific molecular signature for AA has both clinical and public health implications. For individual patients, the molecular signature could help physicians identify which tumors were caused by AA. Although this information cannot yet be used to optimize the treatment of individual patients, those who are diagnosed with AA-associated cancers could be monitored more closely for the appearance of additional tumors. Meanwhile, a better understanding of the mutagenic effects of AA should also help to strengthen public health efforts to decrease exposure to this carcinogenic herb. In humans, exposure to aristolochic acid (AA) is associated with urothelial carcinoma of the upper urinary tract (UTUC). Exome sequencing of UTUCs from 19 individuals with documented exposure to AA revealed a remarkably large number of somatic mutations and an unusual mutational signature attributable to AA. Most of the mutations (72%) in these tumors were A:T-to-T:A transversions, located predominantly on the nontranscribed strand, with a strong preference for deoxyadenosine in a consensus sequence (T/CAG). This trinucleotide motif overlaps the canonical splice acceptor site, possibly accounting for the excess of splice site mutations observed in these tumors. The AA mutational fingerprint was found frequently in oncogenes and tumor suppressor genes in AA-associated UTUC. The AA mutational signature was observed in one patient’s tumor from a UTUC cohort without previous indication of AA exposure. Together, these results directly link an established environmental mutagen to cancer through genome-wide sequencing and highlight its power to reveal individual exposure to carcinogens.

Evolution of Neoantigen Landscape during Immune Checkpoint Blockade in Non–Small Cell Lung Cancer

Immune checkpoint inhibitors have shown significant therapeutic responses against tumors containing increased mutation-associated neoantigen load. We have examined the evolving landscape of tumor neoantigens during the emergence of acquired resistance in patients with non-small cell lung cancer after initial response to immune checkpoint blockade with anti-PD-1 or anti-PD-1/anti-CTLA-4 antibodies. Analyses of matched pretreatment and resistant tumors identified genomic changes resulting in loss of 7 to 18 putative mutation-associated neoantigens in resistant clones. Peptides generated from the eliminated neoantigens elicited clonal T-cell expansion in autologous T-cell cultures, suggesting that they generated functional immune responses. Neoantigen loss occurred through elimination of tumor subclones or through deletion of chromosomal regions containing truncal alterations, and was associated with changes in T-cell receptor clonality. These analyses provide insight into the dynamics of mutational landscapes during immune checkpoint blockade and have implications for the development of immune therapies that target tumor neoantigens.Significance: Acquired resistance to immune checkpoint therapy is being recognized more commonly. This work demonstrates for the first time that acquired resistance to immune checkpoint blockade can arise in association with the evolving landscape of mutations, some of which encode tumor neoantigens recognizable by T cells. These observations imply that widening the breadth of neoantigen reactivity may mitigate the development of acquired resistance. Cancer Discov; 7(3); 264-76. ©2017 AACR.See related commentary by Yang, p. 250This article is highlighted in the In This Issue feature, p. 235.

Whole Genome Sequencing Defines the Genetic Heterogeneity of Familial Pancreatic Cancer

UNLABELLED Pancreatic cancer is projected to become the second leading cause of cancer-related death in the United States by 2020. A familial aggregation of pancreatic cancer has been established, but the cause of this aggregation in most families is unknown. To determine the genetic basis of susceptibility in these families, we sequenced the germline genomes of 638 patients with familial pancreatic cancer and the tumor exomes of 39 familial pancreatic adenocarcinomas. Our analyses support the role of previously identified familial pancreatic cancer susceptibility genes such as BRCA2, CDKN2A, and ATM, and identify novel candidate genes harboring rare, deleterious germline variants for further characterization. We also show how somatic point mutations that occur during hematopoiesis can affect the interpretation of genome-wide studies of hereditary traits. Our observations have important implications for the etiology of pancreatic cancer and for the identification of susceptibility genes in other common cancer types. SIGNIFICANCE The genetic basis of disease susceptibility in the majority of patients with familial pancreatic cancer is unknown. We whole genome sequenced 638 patients with familial pancreatic cancer and demonstrate that the genetic underpinning of inherited pancreatic cancer is highly heterogeneous. This has significant implications for the management of patients with familial pancreatic cancer.

CRAVAT: cancer-related analysis of variants toolkit

Summary: Advances in sequencing technology have greatly reduced the costs incurred in collecting raw sequencing data. Academic laboratories and researchers therefore now have access to very large datasets of genomic alterations but limited time and computational resources to analyse their potential biological importance. Here, we provide a web-based application, Cancer-Related Analysis of Variants Toolkit, designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis. Cancer-Related Analysis of Variants Toolkit provides predictive scores for germline variants, somatic mutations and relative gene importance, as well as annotations from published literature and databases. Results are emailed to users as MS Excel spreadsheets and/or tab-separated text files. Availability: http://www.cravat.us/ Contact: karchin@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

MuPIT interactive: webserver for mapping variant positions to annotated, interactive 3D structures

Mutation position imaging toolbox (MuPIT) interactive is a browser-based application for single-nucleotide variants (SNVs), which automatically maps the genomic coordinates of SNVs onto the coordinates of available three-dimensional (3D) protein structures. The application is designed for interactive browser-based visualization of the putative functional relevance of SNVs by biologists who are not necessarily experts either in bioinformatics or protein structure. Users may submit batches of several thousand SNVs and review all protein structures that cover the SNVs, including available functional annotations such as binding sites, mutagenesis experiments, and common polymorphisms. Multiple SNVs may be mapped onto each structure, enabling 3D visualization of SNV clusters and their relationship to functionally annotated positions. We illustrate the utility of MuPIT interactive in rationalizing the impact of selected polymorphisms in the PharmGKB database, somatic mutations identified in the Cancer Genome Atlas study of invasive breast carcinomas, and rare variants identified in the exome sequencing project. MuPIT interactive is freely available for non-profit use at http://mupit.icm.jhu.edu.

High grade serous ovarian carcinomas originate in the fallopian tube

High-grade serous ovarian carcinoma (HGSOC) is the most frequent type of ovarian cancer and has a poor outcome. It has been proposed that fallopian tube cancers may be precursors of HGSOC but evolutionary evidence for this hypothesis has been limited. Here, we perform whole-exome sequence and copy number analyses of laser capture microdissected fallopian tube lesions (p53 signatures, serous tubal intraepithelial carcinomas (STICs), and fallopian tube carcinomas), ovarian cancers, and metastases from nine patients. The majority of tumor-specific alterations in ovarian cancers were present in STICs, including those affecting TP53, BRCA1, BRCA2 or PTEN. Evolutionary analyses reveal that p53 signatures and STICs are precursors of ovarian carcinoma and identify a window of 7 years between development of a STIC and initiation of ovarian carcinoma, with metastases following rapidly thereafter. Our results provide insights into the etiology of ovarian cancer and have implications for prevention, early detection and therapeutic intervention of this disease.It has previously been proposed that high-grade serous ovarian carcinoma (HGSOC) may originate from the fallopian tube. Here, the authors analyze genetic aberrances in fallopian tube lesions, ovarian cancers, and metastases from HGSOC patients and establish the evolutionary origins of HGSOC in the fallopian tube.

SubClonal Hierarchy Inference from Somatic Mutations: Automatic Reconstruction of Cancer Evolutionary Trees from Multi-region Next Generation Sequencing

Recent improvements in next-generation sequencing of tumor samples and the ability to identify somatic mutations at low allelic fractions have opened the way for new approaches to model the evolution of individual cancers. The power and utility of these models is increased when tumor samples from multiple sites are sequenced. Temporal ordering of the samples may provide insight into the etiology of both primary and metastatic lesions and rationalizations for tumor recurrence and therapeutic failures. Additional insights may be provided by temporal ordering of evolving subclones—cellular subpopulations with unique mutational profiles. Current methods for subclone hierarchy inference tightly couple the problem of temporal ordering with that of estimating the fraction of cancer cells harboring each mutation. We present a new framework that includes a rigorous statistical hypothesis test and a collection of tools that make it possible to decouple these problems, which we believe will enable substantial progress in the field of subclone hierarchy inference. The methods presented here can be flexibly combined with methods developed by others addressing either of these problems. We provide tools to interpret hypothesis test results, which inform phylogenetic tree construction, and we introduce the first genetic algorithm designed for this purpose. The utility of our framework is systematically demonstrated in simulations. For most tested combinations of tumor purity, sequencing coverage, and tree complexity, good power (≥ 0.8) can be achieved and Type 1 error is well controlled when at least three tumor samples are available from a patient. Using data from three published multi-region tumor sequencing studies of (murine) small cell lung cancer, acute myeloid leukemia, and chronic lymphocytic leukemia, in which the authors reconstructed subclonal phylogenetic trees by manual expert curation, we show how different configurations of our tools can identify either a single tree in agreement with the authors, or a small set of trees, which include the authors’ preferred tree. Our results have implications for improved modeling of tumor evolution and the importance of multi-region tumor sequencing.