Multi-cancer computational analysis reveals invasion-associated variant of desmoplastic reaction involving INHBA, THBS2 and COL11A1

<p>Abstract</p> <p>Background</p> <p>Despite extensive research, the details of the biological mechanisms by which cancer cells acquire motility and invasiveness are largely unknown. This study identifies an invasion associated gene signature shedding light on these mechanisms.</p> <p>Methods</p> <p>We analyze data from multiple cancers using a novel computational method identifying sets of genes whose coordinated overexpression indicates the presence of a particular phenotype, in this case high-stage cancer.</p> <p>Results</p> <p>We conclude that there is one shared "core" metastasis-associated gene expression signature corresponding to a specific variant of stromal desmoplastic reaction, present in a large subset of samples that have exceeded a threshold of invasive transition specific to each cancer, indicating that the corresponding biological mechanism is triggered at that point. For example this threshold is reached at stage IIIc in ovarian cancer and at stage II in colorectal cancer. Therefore, its presence indicates that the corresponding stage has been reached. It has several features, such as coordinated overexpression of particular collagens, mainly <it>COL11A1 </it>and other genes, mainly <it>THBS2 </it>and <it>INHBA</it>. The composition of the overexpressed genes indicates invasion-facilitating altered proteolysis in the extracellular matrix. The prominent presence in the signature of INHBA in all cancers strongly suggests a biological mechanism centered on activin A induced TGF-β signaling, because activin A is a member of the TGF-β superfamily consisting of an INHBA homodimer. Furthermore, we establish that the signature is predictive of neoadjuvant therapy response in at least one breast cancer data set.</p> <p>Conclusions</p> <p>Therefore, these results can be used for developing high specificity biomarkers sensing cancer invasion and predicting response to neoadjuvant therapy, as well as potential multi-cancer metastasis inhibiting therapeutics targeting the corresponding biological mechanism.</p

A Genome-Scale Metabolic Reconstruction of Mycoplasma genitalium, iPS189

With a genome size of ∼580 kb and approximately 480 protein coding regions, Mycoplasma genitalium is one of the smallest known self-replicating organisms and, additionally, has extremely fastidious nutrient requirements. The reduced genomic content of M. genitalium has led researchers to suggest that the molecular assembly contained in this organism may be a close approximation to the minimal set of genes required for bacterial growth. Here, we introduce a systematic approach for the construction and curation of a genome-scale in silico metabolic model for M. genitalium. Key challenges included estimation of biomass composition, handling of enzymes with broad specificities, and the lack of a defined medium. Computational tools were subsequently employed to identify and resolve connectivity gaps in the model as well as growth prediction inconsistencies with gene essentiality experimental data. The curated model, M. genitalium iPS189 (262 reactions, 274 metabolites), is 87% accurate in recapitulating in vivo gene essentiality results for M. genitalium. Approaches and tools described herein provide a roadmap for the automated construction of in silico metabolic models of other organisms

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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Tumors induce de novo steroid biosynthesis in T cells to evade immunity

Abstract: Tumors subvert immune cell function to evade immune responses, yet the complex mechanisms driving immune evasion remain poorly understood. Here we show that tumors induce de novo steroidogenesis in T lymphocytes to evade anti-tumor immunity. Using a transgenic steroidogenesis-reporter mouse line we identify and characterize de novo steroidogenic immune cells, defining the global gene expression identity of these steroid-producing immune cells and gene regulatory networks by using single-cell transcriptomics. Genetic ablation of T cell steroidogenesis restricts primary tumor growth and metastatic dissemination in mouse models. Steroidogenic T cells dysregulate anti-tumor immunity, and inhibition of the steroidogenesis pathway is sufficient to restore anti-tumor immunity. This study demonstrates T cell de novo steroidogenesis as a mechanism of anti-tumor immunosuppression and a potential druggable target

Evaluation of seven common lipid associated loci in a large Indian sib pair study.

BACKGROUND: Genome wide association studies (GWAS), mostly in Europeans have identified several common variants as associated with key lipid traits. Replication of these genetic effects in South Asian populations is important since it would suggest wider relevance for these findings. Given the rising prevalence of metabolic disorders and heart disease in the Indian sub-continent, these studies could be of future clinical relevance. METHODS: We studied seven common variants associated with a variety of lipid traits in previous GWASs. The study sample comprised of 3178 sib-pairs recruited as participants for the Indian Migration Study (IMS). Associations with various lipid parameters and quantitative traits were analyzed using the Fulker genetic association model. RESULTS: We replicated five of the 7 main effect associations with p-values ranging from 0.03 to 1.97x10(-7). We identified particularly strong association signals at rs662799 in APOA5 (beta=0.18 s.d, p=1.97 x 10(-7)), rs10503669 in LPL (beta =-0.18 s.d, p=1.0 x 10(-4)) and rs780094 in GCKR (beta=0.11 s.d, p=0.001) loci in relation to triglycerides. In addition, the GCKR variant was also associated with total cholesterol (beta=0.11 s.d, p=3.9x10(-4)). We also replicated the association of rs562338 in APOB (p=0.03) and rs4775041 in LIPC (p=0.007) with LDL-cholesterol and HDL-cholesterol respectively. CONCLUSIONS: We report associations of five loci with various lipid traits with the effect size consistent with the same reported in Europeans. These results indicate an overlap of genetic effects pertaining to lipid traits across the European and Indian populations