A novel gene signature unveils three distinct immune-metabolic rewiring patterns conserved across diverse tumor types and associated with outcome
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PROVIDER: PRJNA851463 | ENA |
REPOSITORIES: ENA
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Project description:Existing immune signatures and tumor mutational burden have only modest predictive capacity for the efficacy of immune check point inhibitors. In this study, we developed an immune-metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 77 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here, we reveal that the IMMETCOLS signature classifies tumors into three distinct immune-metabolic clusters. Cluster 1 displays markers of enhanced glycolisis, hexosamine byosinthesis and epithelial-to-mesenchymal transition. On multivariate analysis, cluster 1 tumors were enriched in pro-immune signature but not in immunophenoscore and were associated with the poorest median survival. Its predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic but also has a solid mitochondrial function, with concomitant upregulation of glutamine and essential amino acid transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together, these findings suggest that the IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches.
| S-EPMC9479210 | biostudies-literature
Project description:Existing immune markers and tumor mutational burden signatures have modest predictive accuracies of immune-check-point inhibitors (ICI) therapeutic efficacy. In this study, we developed an immune metabolic signature suitable for personalized ICI therapies. A classifier using an immune-metabolic signature (IMMETCOLS) was developed on a training set of 75 metastatic colorectal cancer (mCRC) samples and validated on 4,200 tumors from the TCGA database belonging to 11 types. Here we reveal that IMMETCOLS signature classifies tumors into 3 distinct immune-metabolic clusters. Cluster 1 displays enhanced glycolysis-Warburg, hexosamine biosynthesis and epithelial-to-mesenchymal biomarkers. On multivariate analysis, Cluster 1 tumors were enriched in pro-immune signature but not Immunophenoscore, and were associated with the poorest median survival. It’s predicted tumor metabolic features suggest an acidic-lactate-rich tumor microenvironment (TME) geared to an immunosuppressive setting, enriched in fibroblasts. Cluster 2 displays features of gluconeogenesis ability, which is needed for glucose-independent survival and preferential use of alternative carbon sources, including glutamine and lipid uptake/β-oxidation. Its metabolic features suggest a hypoxic and hypoglycemic TME, associated with poor tumor-associated antigen presentation. Finally, cluster 3 is highly glycolytic, but also has a solid mitochondrial function, with concomitant up-regulation of glutamine and essential amino acids transporters and the pentose phosphate pathway leading to glucose exhaustion in the TME and immunosuppression. Together these findings suggest that IMMETCOLS signature provides a classifier of tumors from diverse origins, yielding three clusters with distinct immune-metabolic profiles, representing a new predictive tool for patient selection for specific immune-metabolic therapeutic approaches
2022-06-26 | GSE206613 | GEO
Project description:Rewiring of gene expression in PWBC at artificial insemination is predictive of pregnancy outcome in cattle (Bos taurus)
| PRJNA609112 | ENA
Project description:Background: Understanding how tumors subvert immune destruction is essential to the development of cancer immunotherapies. New evidence suggests that tumors limit anti-tumor immunity by exploiting transcriptional programs that regulate intratumoral trafficking and accumulation of effector cells. Here, we investigated the gene expression profiles that distinguish immunologically "cold" and "hot" tumors across diverse tumor types. Methods: RNAseq profiles of tumors (n = 8,920) representing 23 solid tumor types were analyzed using immune gene signatures that quantify CD8+ T cell abundance. Genes and pathways associated with a low CD8+ T cell infiltration profile (CD8-Low) were identified by correlation, differential expression, and statistical ranking methods. Gene subsets were evaluated in immunotherapy treatment cohorts and functionally characterized in cell lines and mouse tumor models. Results: Among different cancer types, we observed highly significant overlap of genes enriched in CD8-Low tumors, which included known immunomodulatory genes (e.g., BMP7, CMTM4, KDM5B, RCOR2) and exhibited significant associations with Wnt signaling, neurogenesis, cell-cell junctions, lipid biosynthesis, epidermal development, and cancer-testis antigens. Analysis of mutually exclusive gene clusters demonstrated that different transcriptional programs may converge on the T cell-cold phenotype as well as predict for response and survival of patients to Nivo treatment. Furthermore, we confirmed that a top-ranking candidate belonging to the TGF-β superfamily, BMP7, negatively regulates CD8+ T cell abundance in immunocompetent murine tumor models, with and without anti-PD-L1 treatment. Conclusions: This study presents the first evidence that solid tumors of diverse anatomical origin acquire conserved transcriptional alterations that may be operative in the T cell-cold state. Our findings demonstrate the potential clinical utility of CD8-Low tumor-associated genes for predicting patient immunotherapy outcomes and point to novel mechanisms with potential for broad therapeutic exploitation.
| S-EPMC7031496 | biostudies-literature
Project description:Cancer prognosis requires precision to identify high-risk patients and improve survival outcomes. Conventional methods struggle with the complexity of genetic biomarkers and diverse medical data. Our study uses deep learning to distil high-dimensional medical data into low-dimensional feature vectors exploring shared patterns across cancer types. We developed a multi-task bimodal neural network integrating RNA Sequencing and clinical data from three The Cancer Genome Atlas project datasets: Breast Invasive Carcinoma, Lung Adenocarcinoma, and Colon Adenocarcinoma. Our approach significantly improved prognosis prediction, especially for Colon Adenocarcinoma, with up to 26% increase in concordance index and 41% in the area under the precision-recall curve. External validation with Small Cell Lung Cancer achieved comparable metrics, indicating that supplementing small datasets with data from other cancers can improve performance. This work represents initial strides in using multi-task learning for prognosis prediction across cancer types, potentially revealing shared mechanisms among cancers and contributing to future applications in precision medicine.
| S-EPMC11522563 | biostudies-literature
Project description:Deep minimal residual disease assessment redefines outcome and unveils different modes of treatment resistance in standard and high-risk multiple myeloma
| PRJNA613235 | ENA
Project description:Circadian clocks temporally coordinate daily organismal biology over the 24-hour cycle. Their molecular design, preserved between fungi and animals, is based on a core-oscillator composed of a one-step transcriptional-translational-negative-feedback-loop (TTFL). To test whether this evolutionarily conserved TTFL architecture is the only plausible way for achieving a functional circadian clock, we adopted a transcriptional rewiring approach, artificially co-opting regulators of the circadian output pathways into the core-oscillator. Herein we describe one of these semi-synthetic clocks which maintains all basic circadian features but, notably, it also exhibits new attributes such as a "lights-on timer" logic, where clock phase is fixed at the end of the night. Our findings indicate that fundamental circadian properties such as period, phase and temperature compensation are differentially regulated by transcriptional and posttranslational aspects of the clockworks.
| S-SCDT-10_1038-S44318-024-00088-3 | biostudies-other
Project description:Infertility is a disease that affects humans and cattle in similar ways. The resemblance includes complex genetic architecture, multiple etiology, low heritability of fertility related traits in females, and the frequency in the female population. Here, we used cattle as a biomedical model to test the hypothesis that gene expression profiles of protein-coding genes expressed in peripheral white blood cells (PWBCs), and circulating micro RNAs in plasma, are associated with female fertility, measured by pregnancy outcome. We drew blood samples from 17 female calves on the day of artificial insemination and analyzed transcript abundance for 10496 genes in PWBCs and 290 circulating micro RNAs. The females were later classified as pregnant to artificial insemination, pregnant to natural breeding or not pregnant. We identified 1860 genes producing significant differential coexpression (eFDR<0.002) based on pregnancy outcome. Additionally, 237 micro RNAs and 2274 genes in PWBCs presented differential coexpression based on pregnancy outcome. Furthermore, using a machine learning prediction algorithm we detected a subset of genes whose abundance could be used for blind categorization of pregnancy outcome. Our results provide strong evidence that bloodborne transcript abundance is highly associated with fertility in females.
2020-02-28 | GSE146041 | GEO
Project description:The lesions of enamel caries can be considered as the outcome of dysbiotic changes in the biofilm community of supragingival dental plaque. Demineralization occurs as the cumulative outcome of repeated shifts towards a less diverse microbiota that produces and tolerates a low pH environment in tooth sites that are sheltered from protective factors in host saliva. Although the etiology of caries is multifactorial, frequent consumption of foods rich in fermentable carbohydrates, notably sucrose, appears to be one of the major factors driving the microbiota in the direction of dysbiosis, particularly in the case of otherwise healthy children with normal salivary flow. Streptococcus mutans and closely related species (such as Streptococcus sobrinus) have long been considered to play a primary etiological role in dental caries. S. mutans responds to sucrose by producing large quantities of lactic acid. It is very tolerant of low pH, and produces an insoluble extracellular polysaccharide that may sequester acid at tooth surfaces. The mechanisms behind those putative virulence factors have been intensively studied in monoculture, and recently in simple multi-species consortia. Much less is known of other species that may also contribute to or protect against dysbiosis driven by dietary carbohydrates. Some strains of “non-mutans” streptococci produce and tolerate acid at levels comparable to S. mutans, while others show increased ariginolytic capabilities, which may act to raise pH within the biofilm matrix. S. mutans tends to be a minority species even in caries-active children, and carious lesions likewise can occur in children with no detectable S. mutans. 16S rDNA-based metagenomic comparisons of caries-active and caries-free subjects have detected associations between caries and a variety of oral species, including not only non-mutans streptococci, but also members of other genera, such as Scardovia and Bifidobacterium. Caries associations have not been consistent between studies. Moreover, different taxonomic clusters have been defined as subgroups within the same study. This raises an important point. Although caries-associated communities are typically less diverse than healthy supragingival plaque overall, those dysbiotic communities still display considerable taxonomic diversity between affected individuals. That in turn raises the question of whether it is desirable to define biomarkers of dysbiosis that are less dependent on taxonomy. The Human Microbiome project generated comprehensive metagenomic data for a wide variety of body sites in healthy subjects, including supragingival plaque. Although most of that data was based on 16S rDNA sequencing, shotgun metagenomics was also used to catalog the functional potential of all microbial genes within a smaller subset of subjects. One of the key findings was that healthy sites from different people were broadly similar with respect to their functional profiles, even though there was extensive individual variation in their taxonomic profiles. It is possible that the “conservation of function” concept may also extend to dysbiotic communities. This would explain why microbial communities associated with caries still show considerable taxonomic variation. In that case, differential patterns of community-wide gene and/or protein expression might provide a more accurate indicator of dysbiosis than can be achieved by counting caries-associated species. Metatranscriptomic or metaproteomic approaches can be used to provide information on function. A recent metatranscriptomic comparison of subgingival plaque from healthy and periodontally diseased sites in three subjects has provided data that support the “conservation of function” concept. They observed that taxonomically diverse diseased sites shared conserved gene expression profiles [20]. By the same token, a recent metaproteomic comparison of gut microbiotas from healthy controls to Crohn’s disease patients found that major shifts in protein expression by function did not always correlate with changes in taxon relative abundance [21]. In this metaproteomic study, we found that sucrose–induced changes in protein expression patterns for pathways involving glycolysis, lactate production, aciduricity and ammonia/glutamate metabolism were likewise conserved in taxonomically diverse dysbiotic oral microcosm biofilm communities.
2016-01-04 | PXD003151 | Pride
Project description:Homologous recombination is essential for high-fidelity DNA repair during mitotic proliferation and meiosis. Yet, context-specific modifications must tailor the recombination machinery to avoid, or enforce, formation of reciprocal exchanges – crossovers – between recombining chromosomes. To obtain molecular insight into how crossover control is achieved, we affinity-purified the 7 DNA-processing enzymes with known roles in channelling HR intermediates into crossovers, or non-crossovers, from vegetative cells, or cells undergoing meiosis. Using mass spectrometry, we provide the first global characterization of their composition. The resulting mitosis- and meiosis-specific interaction maps reveal intricate changes in enzyme architecture and a concerted rewiring of the interaction networks to support flexible control to the recombination outcome. Moreover, functional analyses of 31 novel interactions uncovered 8 meiosis-specific network components that remodel HR to support crossing-over. Chd1, which transiently associates with Exo1 during meiosis, enables the formation of MutLγ-Exo1-dependent crossovers through its conserved ability to bind and displace nucleosomes.
2019-07-31 | PXD012486 | Pride