Samirkumar Amin

Systematic analysis of telomere length and somatic alterations in 31 cancer types

Cancer cells survive cellular crisis through telomere maintenance mechanisms. We report telomere lengths in 18,430 samples, including tumors and non-neoplastic samples, across 31 cancer types. Telomeres were shorter in tumors than in normal tissues and longer in sarcomas and gliomas than in other cancers. Among 6,835 cancers, 73% expressed telomerase reverse transcriptase (TERT), which was associated with TERT point mutations, rearrangements, DNA amplifications and transcript fusions and predictive of telomerase activity. TERT promoter methylation provided an additional deregulatory TERT expression mechanism. Five percent of cases, characterized by undetectable TERT expression and alterations in ATRX or DAXX, demonstrated elongated telomeres and increased telomeric repeat–containing RNA (TERRA). The remaining 22% of tumors neither expressed TERT nor harbored alterations in ATRX or DAXX. In this group, telomere length positively correlated with TP53 and RB1 mutations. Our analysis integrates TERT abnormalities, telomerase activity and genomic alterations with telomere length in cancer.

Gene Expression Profile Alone Is Inadequate In Predicting Complete Response In Multiple Myeloma

With advent of several treatment options in multiple myeloma (MM), a selection of effective regimen has become an important issue. Use of gene expression profile (GEP) is considered an important tool in predicting outcome; however, it is unclear whether such genomic analysis alone can adequately predict therapeutic response. We evaluated the ability of GEP to predict complete response (CR) in MM. GEP from pretreatment MM cells from 136 uniformly treated MM patients with response data on an IFM, France led study were analyzed. To evaluate variability in predictive power due to microarray platform or treatment types, additional data sets from three different studies (n=511) were analyzed using same methods. We used several machine learning methods to derive a prediction model using training and test subsets of the original four data sets. Among all methods employed for GEP-based CR predictive capability, we got accuracy range of 56–78% in test data sets and no significant difference with regard to GEP platforms, treatment regimens or in newly diagnosed or relapsed patients. Importantly, permuted P-value showed no statistically significant CR predictive information in GEP data. This analysis suggests that GEP-based signature has limited power to predict CR in MM, highlighting the need to develop comprehensive predictive model using integrated genomics approach.

Systematic Epigenomic Analysis Reveals Chromatin States Associated with Melanoma Progression

The extent and nature of epigenomic changes associated with melanoma progression is poorly understood. Through systematic epigenomic profiling of 35 epigenetic modifications and transcriptomic analysis, we define chromatin state changes associated with melanomagenesis by using a cell phenotypic model of non-tumorigenic and tumorigenic states. Computation of specific chromatin state transitions showed loss of histone acetylations and H3K4me2/3 on regulatory regions proximal to specific cancer-regulatory genes in important melanoma-driving cell signaling pathways. Importantly, such acetylation changes were also observed between benign nevi and malignant melanoma human tissues. Intriguingly, only a small fraction of chromatin state transitions correlated with expected changes in gene expression patterns. Restoration of acetylation levels on deacetylated loci by histone deacetylase (HDAC) inhibitors selectively blocked excessive proliferation in tumorigenic cells and human melanoma cells, suggesting functional roles of observed chromatin state transitions in driving hyperproliferative phenotype. Through these results, we define functionally relevant chromatin states associated with melanoma progression.

Synthetic vulnerabilities of mesenchymal subpopulations in pancreatic cancer

Malignant neoplasms evolve in response to changes in oncogenic signalling. Cancer cell plasticity in response to evolutionary pressures is fundamental to tumour progression and the development of therapeutic resistance. Here we determine the molecular and cellular mechanisms of cancer cell plasticity in a conditional oncogenic Kras mouse model of pancreatic ductal adenocarcinoma (PDAC), a malignancy that displays considerable phenotypic diversity and morphological heterogeneity. In this model, stochastic extinction of oncogenic Kras signalling and emergence of Kras-independent escaper populations (cells that acquire oncogenic properties) are associated with de-differentiation and aggressive biological behaviour. Transcriptomic and functional analyses of Kras-independent escapers reveal the presence of Smarcb1–Myc-network-driven mesenchymal reprogramming and independence from MAPK signalling. A somatic mosaic model of PDAC, which allows time-restricted perturbation of cell fate, shows that depletion of Smarcb1 activates the Myc network, driving an anabolic switch that increases protein metabolism and adaptive activation of endoplasmic-reticulum-stress-induced survival pathways. Increased protein turnover renders mesenchymal sub-populations highly susceptible to pharmacological and genetic perturbation of the cellular proteostatic machinery and the IRE1-α–MKK4 arm of the endoplasmic-reticulum-stress-response pathway. Specifically, combination regimens that impair the unfolded protein responses block the emergence of aggressive mesenchymal subpopulations in mouse and patient-derived PDAC models. These molecular and biological insights inform a potential therapeutic strategy for targeting aggressive mesenchymal features of PDAC.

TumorFusions: An integrative resource for cancer-associated transcript fusions

Abstract Gene fusion represents a class of molecular aberrations in cancer and has been exploited for therapeutic purposes. In this paper we describe TumorFusions, a data portal that catalogues 20 731 gene fusions detected in 9966 well characterized cancer samples and 648 normal specimens from The Cancer Genome Atlas (TCGA). The portal spans 33 cancer types in TCGA. Fusion transcripts were identified via a uniform pipeline, including filtering against a list of 3838 transcript fusions detected in a panel of 648 non-neoplastic samples. Fusions were mapped to somatic DNA rearrangements identified using whole genome sequencing data from 561 cancer samples as a means of validation. We observed that 65% of transcript fusions were associated with a chromosomal alteration, which is annotated in the portal. Other features of the portal include links to SNP array-based copy number levels and mutational patterns, exon and transcript level expressions of the partner genes, and a network-based centrality score for prioritizing functional fusions. Our portal aims to be a broadly applicable and user friendly resource for cancer gene annotation and is publicly available at http://www.tumorfusions.org.

Glioma through the looking GLASS: molecular evolution of diffuse gliomas and the Glioma Longitudinal Analysis Consortium

Abstract Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal Analysis Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities and, ultimately, improved outcomes for a patient population in need.

TumorFusions: an integrative resource for reporting cancer-associated transcript fusions in 33 tumor types

Fusion genes, particularly those involving kinases, have been demonstrated as drivers and are frequent therapeutic targets in cancer1. Here, we describe our results on detecting transcript fusions across 33 cancer types from The Cancer Genome Atlas (TCGA), totaling 9,966 cancer samples and 648 normal samples2. Preprocessing, including read alignment to both genome and transcriptome, and fusion detection were carried out using a uniform pipeline3. To validate the resultant fusions, we also called somatic structural variations for 561 cancers from whole genome sequencing data. A summary of the data used in this study is provided in Table S1. Our results can be accessed per our portal at http://www.tumorfusions.org.

Pan-cancer study of heterogeneous RNA aberrations

Pan-cancer studies have transformed our understanding of recurrent somatic mutations that contribute to cancer pathogenesis; however, there has yet to be a full investigation of the multiple mechanisms in which genes can be somatically altered, particularly at the transcriptome level. We present the most comprehensive catalogue of cancer-associated gene alterations through extensive characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project with matched whole-genome sequence data. We processed the RNA-seq data with a unified analysis pipeline that included both sequence alignment and extensive quality control. Subsequently, we identified gene alterations through gene expression, alternative splicing, alternative transcription starts, allele-specific expression, RNA-edited sites, and gene fusions, and by comparing with RNA-Seq from a panel of normal tissue samples from the Genotype-Tissue Expression (GTEx) project. Our data represent an extensive pan-cancer catalog of RNA-level aberrations for each gene and will be the basis for further analyses within PCAWG. NOTE TO READERS: This is a draft of a marker paper from the PCAWG Transcriptome Working Group and is intended to describe technical aspects of RNA-Seq analysis associated with the PCAWG project. The full marker paper is currently in preparation.We present the most comprehensive catalogue of cancer-associated gene alterations through characterization of tumor transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes project. Using matched whole-genome sequencing data, we attributed RNA alterations to germline and somatic DNA alterations, revealing likely genetic mechanisms. We identified 444 associations of gene expression with somatic non-coding single-nucleotide variants. We found 1,872 splicing alterations associated with somatic mutation in intronic regions, including novel exonization events associated with Alu elements. Somatic copy number alterations were the major driver of total gene and allele-specific expression (ASE) variation. Additionally, 82% of gene fusions had structural variant support, including 75 of a novel class called “bridged” fusions, in which a third genomic location bridged two different genes. Globally, we observe transcriptomic alteration signatures that differ between cancer types and have associations with DNA mutational signatures. Given this unique dataset of RNA alterations, we also identified 1,012 genes significantly altered through both DNA and RNA mechanisms. Our study represents an extensive catalog of RNA alterations and reveals new insights into the heterogeneous molecular mechanisms of cancer gene alterations.

An integrated platform for genome-wide mapping of chromatin states using high-throughput chip-sequencing in tumor tissues

Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.

An In Vivo Screen Identifies PYGO2 as a Driver for Metastatic Prostate Cancer

Advanced prostate cancer displays conspicuous chromosomal instability and rampant copy number aberrations, yet the identity of functional drivers resident in many amplicons remain elusive. Here, we implemented a functional genomics approach to identify new oncogenes involved in prostate cancer progression. Through integrated analyses of focal amplicons in large prostate cancer genomic and transcriptomic datasets as well as genes upregulated in metastasis, 276 putative oncogenes were enlisted into an in vivo gain-of-function tumorigenesis screen. Among the top positive hits, we conducted an in-depth functional analysis on Pygopus family PHD finger 2 (PYGO2), located in the amplicon at 1q21.3. PYGO2 overexpression enhances primary tumor growth and local invasion to draining lymph nodes. Conversely, PYGO2 depletion inhibits prostate cancer cell invasion in vitro and progression of primary tumor and metastasis in vivo In clinical samples, PYGO2 upregulation associated with higher Gleason score and metastasis to lymph nodes and bone. Silencing PYGO2 expression in patient-derived xenograft models impairs tumor progression. Finally, PYGO2 is necessary to enhance the transcriptional activation in response to ligand-induced Wnt/β-catenin signaling. Together, our results indicate that PYGO2 functions as a driver oncogene in the 1q21.3 amplicon and may serve as a potential prognostic biomarker and therapeutic target for metastatic prostate cancer.Significance: Amplification/overexpression of PYGO2 may serve as a biomarker for prostate cancer progression and metastasis. Cancer Res; 78(14); 3823-33. ©2018 AACR.