Akinyemi I. Ojesina

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

Summary Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahepatic CCA cases and propose a molecular classification scheme. We identified an IDH mutant-enriched subtype with distinct molecular features including low expression of chromatin modifiers, elevated expression of mitochondrial genes, and increased mitochondrial DNA copy number. Leveraging the multi-platform data, we observed that ARID1A exhibited DNA hypermethylation and decreased expression in the IDH mutant subtype. More broadly, we found that IDH mutations are associated with an expanded histological spectrum of liver tumors with molecular features that stratify with CCA. Our studies reveal insights into the molecular pathogenesis and heterogeneity of cholangiocarcinoma and provide classification information of potential therapeutic significance.

Racial disparities in individual breast cancer outcomes by hormone-receptor subtype, area-level socio-economic status and healthcare resources

The aim of the study is to determine the influence of area-level socio-economic status and healthcare access in addition to tumor hormone-receptor subtype on individual breast cancer stage, treatment, and mortality among Non-Hispanic (NH)-Black, NH-White, and Hispanic US adults. Analysis was based on 456,217 breast cancer patients in the SEER database from 2000 to 2010. Multilevel and multivariable-adjusted logistic and Cox proportional hazards regression analysis was conducted to account for clustering by SEER registry of diagnosis. NH-Black women had greater area-level access to healthcare resources compared with women of other races. For instance, the average numbers of oncology hospitals per million population in counties with NH-Black, NH-White, and Hispanic women were 8.1, 7.7, and 5.0 respectively; average numbers of medical doctors per million in counties with NH-Black, NH-White, and Hispanic women were 100.7, 854.0, and 866.3 respectively; and average number of Ob/Gyn in counties with NH-Black, NH-White, and Hispanic women was 155.6, 127.4, and 127.3, respectively (all p values <0.001). Regardless, NH-Black women (HR 1.39, 95xa0% CI 1.36–1.43) and Hispanic women (HR 1.05, 95xa0% CI 1.03–1.08) had significantly higher breast cancer mortality compared with NH-White women even after adjusting for hormone-receptor subtype, area-level socio-economic status, and area-level healthcare access. In addition, lower county-level socio-economic status and healthcare access measuresxa0were significantly and independently associated with stage at presentation, surgery, and radiation treatment as well as mortality after adjusting for age, race/ethnicity, and HR subtype. Although breast cancer HR subtype is a strong, important, and consistent predictor of breast cancer outcomes, we still observed significant and independent influences of area-level SES and HCA on breast cancer outcomes that deserve further study and may be critical to eliminating breast cancer outcome disparities.

Pathway-Structured Predictive Model for Cancer Survival Prediction: A Two-Stage Approach

Heterogeneity in terms of tumor characteristics, prognosis, and survival among cancer patients has been a persistent problem for many decades. Currently, prognosis and outcome predictions are made based on clinical factors and/or by incorporating molecular profiling data. However, inaccurate prognosis and prediction may result by using only clinical or molecular information directly. One of the main shortcomings of past studies is the failure to incorporate prior biological information into the predictive model, given strong evidence of the pathway-based genetic nature of cancer, i.e., the potential for oncogenes to be grouped into pathways based on biological functions such as cell survival, proliferation, and metastatic dissemination. To address this problem, we propose a two-stage approach to incorporate pathway information into the prognostic modeling using large-scale gene expression data. In the first stage, we fit all predictors within each pathway using the penalized Cox model and Bayesian hierarchical Cox model. In the second stage, we combine the cross-validated prognostic scores of all pathways obtained in the first stage as new predictors to build an integrated prognostic model for prediction. We apply the proposed method to analyze two independent breast and ovarian cancer datasets from The Cancer Genome Atlas (TCGA), predicting overall survival using large-scale gene expression profiling data. The results from both datasets show that the proposed approach not only improves survival prediction compared with the alternative analyses that ignore the pathway information, but also identifies significant biological pathways.

Notch Signaling Activation Is Associated with Patient Mortality and Increased FGF1-Mediated Invasion in Squamous Cell Carcinoma of the Oral Cavity.

Oral squamous cell carcinoma (OSCC) is a cancer subtype that lacks validated prognostic and therapeutic biomarkers, and human papillomavirus status has not proven beneficial in predicting patient outcomes. A gene expression pathway analysis was conducted using OSCC patient specimens to identify molecular targets that may improve management of this disease. RNA was isolated from 19 OSCCs treated surgically at the University of Alabama at Birmingham (UAB; Birmingham, AL) and evaluated using the NanoString nCounter system. Results were confirmed using the oral cavity subdivision of the Head and Neck Squamous Cell Carcinoma Cancer (HNSCC) study generated by The Cancer Genome Atlas (TCGA) Research Network. Further characterization of the in vitro phenotype produced by Notch pathway activation in HNSCC cell lines included gene expression, proliferation, cell cycle, migration, invasion, and radiosensitivity. In both UAB and TCGA samples, Notch pathway upregulation was significantly correlated with patient mortality status and with expression of the proinvasive gene FGF1. In vitro Notch activation in HNSCC cells increased transcription of FGF1 and induced a marked increase in cell migration and invasion, which was fully abrogated by FGF1 knockdown. These results reveal that increased Notch pathway signaling plays a role in cancer progression and patient outcomes in OSCC. Accordingly, the Notch–FGF interaction should be further studied as a prognostic biomarker and potential therapeutic target for OSCC. Implications: Patients with squamous cell carcinoma of the oral cavity who succumb to their disease are more likely to have upregulated Notch signaling, which may mediate a more invasive phenotype through increased FGF1 transcription. Mol Cancer Res; 14(9); 883–91. ©2016 AACR.

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.

Two high-risk susceptibility loci at 6p25.3 and 14q32.13 for Waldenström macroglobulinemia

Waldenström macroglobulinemia (WM)/lymphoplasmacytic lymphoma (LPL) is a rare, chronic B-cell lymphoma with high heritability. We conduct a two-stage genome-wide association study of WM/LPL in 530 unrelated cases and 4362 controls of European ancestry and identify two high-risk loci associated with WM/LPL at 6p25.3 (rs116446171, near EXOC2 and IRF4; ORu2009=u200921.14, 95% CI: 14.40–31.03, Pu2009=u20091.36u2009×u200910−54) and 14q32.13 (rs117410836, near TCL1; ORu2009=u20094.90, 95% CI: 3.45–6.96, Pu2009=u20098.75u2009×u200910−19). Both risk alleles are observed at a low frequency among controls (~2–3%) and occur in excess in affected cases within families. In silico data suggest that rs116446171 may have functional importance, and in functional studies, we demonstrate increased reporter transcription and proliferation in cells transduced with the 6p25.3 risk allele. Although further studies are needed to fully elucidate underlying biological mechanisms, together these loci explain 4% of the familial risk and provide insights into genetic susceptibility to this malignancy.Waldenström macroglobulinemia (WM)/lymphoplasmacytic lymphoma (LPL) is a non-Hodgkin-type B cell lymphoma. Here, the authors identify two risk loci for WM/LPL in a two-stage GWAS involving a family-oversampling approach and provide evidence for a functional role of the non-coding SNP rs116446171.

GATK PathSeq: a customizable computational tool for the discovery and identification of microbial sequences in libraries from eukaryotic hosts

Summary: We present an updated version of our computational pipeline, PathSeq, for the discovery and identification of microbial sequences in genomic and transcriptomic libraries from eukaryotic hosts. This pipeline is available in the Genome Analysis Toolkit (GATK) as a suite of configurable tools that can report the microbial composition of DNA or RNA short‐read sequencing samples and identify unknown sequences for downstream assembly of novel organisms. GATK PathSeq enables sample analysis in minutes at low cost. In addition, these tools are built with the GATK engine and Apache Spark framework, providing robust, rapid parallelization of read quality filtering, host subtraction and microbial alignment in workstation, cluster and cloud environments. Availability and implementation: These tools are available as a part of the GATK at https://github.com/broadinstitute/gatk. Supplementary information: Supplementary data are available at Bioinformatics online.

Clinicopathologic and molecular markers in cervical carcinoma: a prospective cohort study

BACKGROUND: Cervical cancer is a major health problem worldwide. Identification of effective clinicopathologic and molecular markers is vital to improve treatment stratification. OBJECTIVES: The purpose of this study was to validate a set of well‐defined clinicopathologic features in a large population‐based, prospectively collected cervical cancer cohort to support their use in the clinic. Further, we explored p53 and human epidermal growth factor receptor 2 as potential prognostic markers in cervical cancer. STUDY DESIGN: Tissue was collected from 401 patients with cervical cancer. Clinical data that included follow‐up evaluations were collected from patient journals. Histopathologic data were evaluated and revised by an expert pathologist. The prognostic impact of selected clinicopathologic variables was analyzed in the whole cohort. Tissue microarrays were prepared from 292 carcinomas, and p53 and human epidermal growth factor receptor 2 protein levels were evaluated by immunohistochemistry. Fresh frozen samples from overlapping cervical carcinomas previously were subjected to human papilloma virus typing (n=94), whole exome (n=100) and RNA (n=79) sequencing; the results were available for our analyses. RESULTS: Among the clinicopathologic variables, vascular space invasion, histologic type, and tumor size were verified as strong independent prognostic markers. High p53 protein levels were associated significantly with markers for aggressive phenotype and survival, also in multivariate survival analysis, but did not reflect TP53 mutational status. High human epidermal growth factor receptor 2 protein levels were identified in 21% of all tumors. ERBB2 amplification was associated with poor outcome (P=.003); human epidermal growth factor receptor 2 protein level was not. CONCLUSIONS: Our findings support that the Féderation Internationale de Gynécologie et dObstétrique s guidelines should include vascular space invasion and tumor size 2–4 cm and that careful selection of histologic type is essential for stratification of patient risk groups. High p53 levels independently predict poor survival yet do not reflect mutational status in cervical cancer. Amplified ERBB2 significantly links to poor survival, while HercepTest does not. With optimal stratification, human epidermal growth factor receptor 2–based therapy may improve cervical cancer treatment.

Abstract 3301: Breast cancer subtypes have distinct microbial and immune cytolytic transcriptomic signatures

Background: The role of genetic mutations in breast cancer is well documented and has formed the basis for novel therapies. However, the impact of viral and bacterial infection in the pathogenesis of breast cancer is not well understood. Methods: We analyzed RNA sequencing (RNASeq) data generated by the Cancer Genome Atlas (TCGA) from over 900 pairs of breast tumor and adjacent normal tissues, using our pathogen discovery tool, PathSeq. We developed a novel metric for quantifying and normalizing microbial sequence abundance from RNASeq data by correcting for both the sequencing coverage and relative genome sizes of bacteria in the dataset. We also performed linear discriminant analyses (LDA) to test the hypothesis that the differences between the canonical breast cancer subtypes can be modeled on microbial abundance data. In addition, we interrogated the human gene expression data derived from the RNASeq dataset to determine the relationships between the breast cancer subtypes and immune cytolytic activity (CYT index; defined as the geometric mean of the expression levels of perforin and granzyme). Results: Viral sequences were rare but we identified bacterial sequences to varying degrees of abundance. Intriguingly, we demonstrated that microbial abundance data can be used to recapitulate the well-established PAM50 gene expression-based subsets. Comparison of tumors and adjacent normal tissues also revealed subtype-associated microbial profiles. In addition, we observed that the basal and Her2 subtypes of breast cancer had a higher frequency of tumors with high CYT index compared with luminal A and B subtypes. Conclusion: This study has revealed that the various breast cancer subtypes have unique microbial transcriptomic signatures as well as differential immune cytolytic activity profiles. These data suggest the potential for differential responses of breast cancer subsets to immunotherapy. Citation Format: Chandra Sekhar Pedamallu, Matthew Meyerson, Akinyemi Ojesina. Breast cancer subtypes have distinct microbial and immune cytolytic transcriptomic signatures. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3301.