Tumor innate immunity primed by specific interferon-stimulated endogenous retroviruses.

Mesenchymal tumor subpopulations secrete pro-tumorigenic cytokines and promote treatment resistance1-4. This phenomenon has been implicated in chemorefractory small cell lung cancer and resistance to targeted therapies5-8, but remains incompletely defined. Here, we identify a subclass of endogenous retroviruses (ERVs) that engages innate immune signaling in these cells. Stimulated 3 prime antisense retroviral coding sequences (SPARCS) are oriented inversely in 3' untranslated regions of specific genes enriched for regulation by STAT1 and EZH2. Derepression of these loci results in double-stranded RNA generation following IFN-γ exposure due to bi-directional transcription from the STAT1-activated gene promoter and the 5' long terminal repeat of the antisense ERV. Engagement of MAVS and STING activates downstream TBK1, IRF3, and STAT1 signaling, sustaining a positive feedback loop. SPARCS induction in human tumors is tightly associated with major histocompatibility complex class 1 expression, mesenchymal markers, and downregulation of chromatin modifying enzymes, including EZH2. Analysis of cell lines with high inducible SPARCS expression reveals strong association with an AXL/MET-positive mesenchymal cell state. While SPARCS-high tumors are immune infiltrated, they also exhibit multiple features of an immune-suppressed microenviroment. Together, these data unveil a subclass of ERVs whose derepression triggers pathologic innate immune signaling in cancer, with important implications for cancer immunotherapy

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

Mechanisms of human telomerase reverse transcriptase (hTERT) regulation: clinical impacts in cancer

Background Limitless self-renewal is one of the hallmarks of cancer and is attained by telomere maintenance, essentially through telomerase (hTERT) activation. Transcriptional regulation of hTERT is believed to play a major role in telomerase activation in human cancers. Main body The dominant interest in telomerase results from its role in cancer. The role of telomeres and telomere maintenance mechanisms is well established as a major driving force in generating chromosomal and genomic instability. Cancer cells have acquired the ability to overcome their fate of senescence via telomere length maintenance mechanisms, mainly by telomerase activation. hTERT expression is up-regulated in tumors via multiple genetic and epigenetic mechanisms including hTERT amplifications, hTERT structural variants, hTERT promoter mutations and epigenetic modifications through hTERT promoter methylation. Genetic (hTERT promoter mutations) and epigenetic (hTERT promoter methylation and miRNAs) events were shown to have clinical implications in cancers that depend on hTERT activation. Knowing that telomeres are crucial for cellular self-renewal, the mechanisms responsible for telomere maintenance have a crucial role in cancer diseases and might be important oncological biomarkers. Thus, rather than quantifying TERT expression and its correlation with telomerase activation, the discovery and the assessment of the mechanisms responsible for TERT upregulation offers important information that may be used for diagnosis, prognosis, and treatment monitoring in oncology. Furthermore, a better understanding of these mechanisms may promote their translation into effective targeted cancer therapies. Conclusion Herein, we reviewed the underlying mechanisms of hTERT regulation, their role in oncogenesis, and the potential clinical applications in telomerase-dependent cancers.info:eu-repo/semantics/publishedVersio

Tumor mutational burden is a determinant of immune-mediated survival in breast cancer

Mounting evidence supports a role for the immune system in breast cancer outcomes. The ability to distinguish highly immunogenic tumors susceptible to anti-tumor immunity from weakly immunogenic or inherently immune-resistant tumors would guide development of therapeutic strategies in breast cancer. Genomic, transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohorts were used to examine statistical associations between tumor mutational burden (TMB) and the survival of patients whose tumors were assigned to previously-described prognostic immune subclasses reflecting favorable, weak or poor immune-infiltrate dispositions (FID, WID or PID, respectively). Tumor immune subclasses were associated with survival in patients with high TMB (TMB-Hi, P < 0.001) but not in those with low TMB (TMB-Lo, P = 0.44). This statistical relationship was confirmed in the METABRIC cohort (TMB-Hi, P = 0.047; TMB-Lo, P = 0.39), and also found to hold true in the more-indolent Luminal A tumor subtype (TMB-Hi, P = 0.011; TMB-Lo, P = 0.91). In TMB-Hi tumors, the FID subclass was associated with prolonged survival independent of tumor stage, molecular subtype, age and treatment. Copy number analysis revealed the reproducible, preferential amplification of chromosome 1q immune-regulatory genes in the PID immune subclass. These findings demonstrate a previously unappreciated role for TMB as a determinant of immune-mediated survival of breast cancer patients and identify candidate immune-regulatory mechanisms associated with immunologically cold tumors. Immune subtyping of breast cancers may offer opportunities for therapeutic stratification.fals

Integrated genomic characterization of oesophageal carcinoma

Oesophageal cancers are prominent worldwide; however, there are few targeted therapies and survival rates for these cancers remain dismal. Here we performed a comprehensive molecular analysis of 164 carcinomas of the oesophagus derived from Western and Eastern populations. Beyond known histopathological and epidemiologic distinctions, molecular features differentiated oesophageal squamous cell carcinomas from oesophageal adenocarcinomas. Oesophageal squamous cell carcinomas resembled squamous carcinomas of other organs more than they did oesophageal adenocarcinomas. Our analyses identified three molecular subclasses of oesophageal squamous cell carcinomas, but none showed evidence for an aetiological role of human papillomavirus. Squamous cell carcinomas showed frequent genomic amplifications of CCND1 and SOX2 and/or TP63, whereas ERBB2, VEGFA and GATA4 and GATA6 were more commonly amplified in adenocarcinomas. Oesophageal adenocarcinomas strongly resembled the chromosomally unstable variant of gastric adenocarcinoma, suggesting that these cancers could be considered a single disease entity. However, some molecular features, including DNA hypermethylation, occurred disproportionally in oesophageal adenocarcinomas. These data provide a framework to facilitate more rational categorization of these tumours and a foundation for new therapies.ope

An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

INTRODUCTION. Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation. METHODS. We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies. RESULTS. We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient. CONCLUSIONS. Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.V Foundation for Cancer Research (Partners in Excellence grant

Reactivation of epigenetically silenced HER4/ERBB4 results in apoptosis of breast tumor cells

Experimental and clinical data support a growth inhibitory role for HER4 in breast cancer. Clinically HER4 expression is extinguished during breast tumorigenesis supporting a tumor suppressor function for HER4, however, a molecular mechanism to explain the selective loss of HER4 expression has remained elusive. Epigenetic mechanisms, for example, aberrant gene promoter hypermethylation, have been shown to ablate tumor suppressor gene expression in breast carcinomas. We identified a CpG island within the HER4 promoter and show by pyrosequencing of bisulfite-treated DNA an inverse correlation between HER4 expression and the extent of promoter methylation. Treatment of the HER4-negative BT20 cell line with the DNA demethylating agent 5-aza-2′-deoxycytidine (DAC)-enhanced HER4 expression, confirming a role for DNA methylation in suppressed HER4 expression. DAC treatment to reactive HER4 expression in combination with the HER4 ligand heregulin-β1 (HRG) resulted in apoptosis of BT20 cells providing a novel therapeutic strategy for triple-negative tumors. The BT20 cells were rescued from apoptosis when preincubated with HER4 small interfering RNA, thereby confirming a role for HER4 in DAC/HRG-induced apoptosis. We verified HER4 promoter methylation in primary breast carcinomas and detected a significant increase in HER4 promoter methylation in HER4-negative breast tumors (P<0.001). Furthermore, increased levels of HER4 promoter methylation were significantly associated with worse patient prognosis (P=0.0234). Taken together, our data support a tumor suppressor function for HER4, which is epigenetically suppressed in breast tumors through promoter hypermethylation

Analytical protocol to identify local ancestry-associated molecular features in cancer

People of different ancestries vary in cancer risk and outcome, and their molecular differences may indicate sources of these variations. Determining the "local" ancestry composition at each genetic locus across ancestry-admixed populations can suggest causal associations. We present a protocol to identify local ancestry and detect the associated molecular changes, using data from the Cancer Genome Atlas. This workflow can be applied to cancer cohorts with matched tumor and normal data from admixed patients to examine germline contributions to cancer. For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et&nbsp;al. (2020)

A strategy to incorporate prior knowledge into correlation network cutoff selection

Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization