Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility

Tumor only analysis of whole exome sequencing from a multi-institutional Nigerian prostate cancer cohort reveals DNA repair genes associated with African ancestry

Men of African ancestry (MAA) have the highest global incidence and mortality of prostate cancer (PCa); however, the biology underlying this harsh disease presentation remains poorly understand, largely due to Africans and people within the African diaspora being under-represented in genomics research. MAA are younger at diagnosis, have higher tumor volume at diagnosis and have higher tumor aggression compared to European American men. Additionally, genomic profiling continues to show that PCa etiology and phenotype are influenced by higher amounts of African ancestry and that West African ancestry is associated with unique genomic alterations. Herein we utilize whole exome sequencing of a unique cohort of 45 advanced stage, treatment naïve Nigerian primary PCa tumors and 11 unmatched non-tumor tissue to compare genomic variants with African (AA) and European (EA) American TCGA PCa tumors. Nigerian samples were collected from 6 sites in central and southwest Nigeria. After whole exome sequencing, samples were processed using GATK best practices. Four genes [BRCA1 (100%), BARD1 (45%), BRCA2 (27%) and PMS2 (18%)] had germline variants in at least two Nigerian non-tumor samples. Across 111 germline variants, the AA cohort reflected a pattern [BRCA1 (68%), BARD1 (34%), BRCA2 (28%) and PMS2 (16%)] similar to Nigerian samples. Of the most frequently mutated genes, BRCA1 showed a statistically (p ≤ 0.05) higher mutation frequency in MAA. Disaggregating gene level mutation frequencies by variant revealed both ancestry linked and Nigerian specific germline variant patterns. Driven by rs799917, BRCA1 showed increasing mutation frequency as African admixture increased. BRCA2_rs11571831 was only present in MAA and BRCA2_rs766173 was increased in Nigerian men. 133 somatic variants were present in 26 PCa associated genes within the Nigerian tumor cohort. Nine genes [BRCA2 (27%), APC (20%), ATM (20%), BRCA1 (13%), DNAJC6 (13%), EGFR (13%), MAD1L1 (13%), MLH1 (11%) and PMS2 (11%)] showed mutation frequencies above 10%. Compared to TCGA cohorts, BRCA2, APC and BRCA1 showed statistically significant increases in Nigerian tumors. The Nigerian cohort variant pattern shared similarities (cosign similarities ≥ 0.734) with COSMIC signatures 5 and 6 and mutated genes showed significant (q < 0.001) GO and functional enrichment in mismatch repair and non-homologous repair deficiency (HRD) pathways. Here, we show that variants in DDR genes are increased in Nigerian PCa and that a portion of those variants correlate with increased African ancestry. Moreover, we identify variants of unknown significance that may contribute to population specific routes of tumorigenesis and treatment. These results present the most comprehensive characterization of the Nigerian PCa exome to date and further highlight the need to increase study population diversity

Utility of formalin-fixed, paraffin-embedded prostate biospecimens from low-resource settings for use in next-generation sequencing studies in African-descent populations

# Background Men of African ancestry experience higher burden from prostate cancer compared to men of other ancestral backgrounds. Limitations in the availability of high-quality biospecimens hinder the inclusion of this population in genetic studies of prostate cancer. The use of formalin-fixed paraffin-embedded (FFPE) tissues represent a potential rich source of genetic material particularly in some international settings, where fresh frozen tissue is difficult to obtain. In this study, we investigate the feasibility of using FFPE biospecimens acquired from various international sites for utility in next-generation sequencing. # Methods A total of 976 FFPE blocks were collected between 2002 and 2017 from six international sites in Africa and the Caribbean representing three consortia: Prostate Cancer Transatlantic Consortium; African-Caribbean Cancer Consortium; and Men of African Descent and Carcinoma of the Prostate. Genomic DNA was checked for quality and quantity. Differences in mean quality control (QC) for pre-and-post pathology training were assessed using t-test. Pearson chi-square with trend analysis examined association between time-category and QC success status. Association of continuous DNA quality (Q129/Q41 ratio) and time of specimen collection was estimated with linear regression. Samples with a DNA quantity \>0.2µg and a Q129/Q41 ratio \>0.00225 were submitted for whole exome sequencing (WES). # Results There was a positive relative percentage change in DNA quantity from 2002 to 2017 for Jamaica, Kenya and Senegal. There was a decline in DNA quantity over the same time period for Nigeria. There was a statistically significant improvement in quality of samples from Kenya (*P*=0.032), Nigeria (*P*\<.001) and Senegal (*P*=0.043). There was a significant improvement in the collected DNA sample quality over time with an R^2^ of 0.12. # Conclusions FFPE samples from low-resource settings could potentially provide sufficient DNA for WES. Improvements in biospecimen collection processing and storage for research are needed in some of these settings