IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures.
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ABSTRACT:
SUBMITTER: Zeng D
PROVIDER: S-EPMC8283787 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundLung adenocarcinoma (LUAD) contains a variety of genomic and epigenomic abnormalities; the effective tumor markers related to these abnormalities need to be further explored.MethodsClustering analysis was performed based on DNA methylation (MET), DNA copy number variation (CNV), and mRNA expression data, and the differences in survival and tumor immune microenvironment (TIME) between subtypes were compared. Further, we evaluated the signatures in terms of both prognostic value and immunological characteristics.ResultsThere was a positive correlation between MET and CNV in LUAD. Integrative analysis of multi-omics data from 443 samples determined molecular subtypes, iC1 and iC2. The fractions of CD8+ T cells and activated CD4+ T cells were higher, the fraction of Tregs was lower, and the expression level of programmed death-ligand 1 (PD-L1) was higher in iC2 with a poor prognosis showing a higher TIDE score. We selected PTTG1, SLC2A1, and FAM83A as signatures of molecular subtypes to build a prognostic risk model and divided patients into high-risk group and low-risk group representing poor prognosis and good prognosis, respectively, which were validated in 180 patients with LUAD. Further, the low-risk group with lower TIDE score had more infiltrating immune cells. In 100 patients with LUAD, the high-risk group with an immunosuppressive state had a higher expression of PD-L1 and lower counts of CD8+ T cells and dendritic cells.ConclusionsThese findings demonstrated that combined multi-omics data could determine molecular subtypes with significant differences of prognosis and TIME in LUAD and suggested potent utility of the signatures to guide immunotherapy.
| S-EPMC8446514 | biostudies-literature
Project description:Current tumor thermal ablation techniques rely on extreme temperatures to induce irreversible cellular injury and coagulative tissue necrosis. Ablation-induced cellular injury or death releases cancer neoantigens and activates the cancer-immunity cycle, potentially generating tumor-specific immune effectors. However, multiple negative regulatory modulators exist at each step of the cycle, mitigating meaningful and therapeutic anticancer effect provided by the immune system. Recent studies have focused on the introduction and testing of adjuvant immunotherapy combined with ablation to synergistically shift the equilibrium out of inhibitory immune modulation. This article reviews the immune microenvironment in relation to image-guided ablation techniques and discusses current and upcoming novel strategies to take advantage of antitumor immunity.
| S-EPMC6823044 | biostudies-literature
Project description:BackgroundThe enrichment of Gram-negative bacteria of oral origin in the esophageal microbiome has been associated with the development of metaplasia. However, to date, no study has comprehensively assessed the relationships between the esophageal microbiome and the host.MethodsHere, we examine the esophageal microenvironment in gastro-esophageal reflux disease and metaplasia using multi-omics strategies targeting the microbiome and host transcriptome, followed by targeted culture, comparative genomics, and host-microbial interaction studies of bacterial signatures of interest.ResultsProfiling of the host transcriptome from esophageal mucosal biopsies revealed profound changes during metaplasia. Importantly, five biomarkers showed consistent longitudinal changes with disease progression from reflux disease to metaplasia. We showed for the first time that the esophageal microbiome is distinct from the salivary microbiome and the enrichment of Campylobacter species as a consistent signature in disease across two independent cohorts. Shape fitting and matrix correlation identified associations between the microbiome and host transcriptome profiles, with a novel co-exclusion relationship found between Campylobacter and napsin B aspartic peptidase. Targeted culture of Campylobacter species from the same cohort revealed a subset of isolates to have a higher capacity to survive within primary human macrophages. Comparative genomic analyses showed these isolates could be differentiated by specific genomic features, one of which was validated to be associated with intracellular fitness. Screening for these Campylobacter strain-specific signatures in shotgun metagenomics data from another cohort showed an increase in prevalence with disease progression. Comparative transcriptomic analyses of primary esophageal epithelial cells exposed to the Campylobacter isolates revealed expression changes within those infected with strains with high intracellular fitness that could explain the increased likelihood of disease progression.ConclusionsWe provide a comprehensive assessment of the esophageal microenvironment, identifying bacterial strain-specific signatures with high relevance to progression of metaplasia.
| S-EPMC8375061 | biostudies-literature
Project description:Endometrial cancer (EC) can easily be cured when diagnosed at an early stage. However, advanced and metastatic EC is a common disease, affecting more than 15,000 patients per year in the United Sates. Only limited treatment options were available until recently, with a taxane-platinum combination as the gold standard in first-line setting and no efficient second-line chemotherapy or hormone therapy. EC can be split into four molecular subtypes, including hypermutated cases with POLE mutations and 25-30% harboring a microsatellite instability (MSI) phenotype with mismatch repair deficiency (dMMR). These tumors display a high load of frameshift mutations, leading to increased expression of neoantigens that can be targeted by the immune system, including (but not limited) to T-cell response. Recent data have demonstrated this impact of programmed death 1 and programmed death ligand 1 (PD-1/PD-L1) inhibitors on chemo-resistant metastatic EC. The uncontrolled KEYNOTE-158 and GARNET trials have shown high response rates with pembrolizumab and dostarlimab in chemoresistant MSI-high tumors. Most responders experiment long responses that last more than one year. Similar, encouraging results were obtained for MMR proficient (MMRp) cases treated with a combination of pembrolizumab and the angiogenesis inhibitor lenvatinib. Approvals have, thus, been obtained or are underway for EC with immune checkpoint inhibitors (ICI) used as monotherapy, and in combination with antiangiogenic agents. Combinations with other targeted therapies are under evaluation and randomized studies are ongoing to explore the impact of ICI-chemotherapy triplets in first-line setting. We summarize in this review the current knowledge of the immune environment of EC, both for MMRd and MMRp tumors. We also detail the main clinical data regarding PD-1/PD-L1 inhibitors and discuss the next steps of development for immunotherapy, including various ICI-based combinations planned to limit resistance to immunotherapy.
| S-EPMC8228955 | biostudies-literature
Project description:BackgroundImmune cell infiltration in the tumor microenvironment (TME) affects tumor initiation, patients' prognosis and immunotherapy strategies. However, their roles and interactions with genomics and molecular processes in hepatocellular carcinoma (HCC) still have not been systematically evaluated.MethodsWe performed unsupervised clustering of total 1000 HCC samples including discovery and validation group from available public datasets. Immune heterogeneity of each subtype was explored by multi-dimension analysis. And a support vector machine (SVM) model based on multi-omics signatures was trained and tested. Finally, we performed immunohistochemistry to verify the immune role of signatures.ResultsWe defined three immune subtypes in HCC, with diverse clinical, molecular, and genomic characteristics. Cluster1 had worse prognosis, better anti-tumor characteristics and highest immune scores, but also accompanied by immunosuppression and T cell dysfunction. Meanwhile, a better anti-PD1/CTLA4 immunotherapeutic response was predicted in cluster1. Cluster2 was enriched in TAM-M2 and stromal cells, indicating immunosuppression. Cluster3, with better prognosis, had lowest CD8 T cell but highest immune resting cells. Further, based on genomic signatures, we developed an SVM classifier to identify the patient's immunological status, which was divided into Type A and Type B, in which Type A had poorer prognosis, higher T cell dysfunction despite higher T cell infiltration, and had better immunotherapeutic response. At the same time, MMP9 may be a potential predictor of the immune characteristics and immunotherapeutic response in HCC.ConclusionsOur work demonstrated 3 immune clusters with different features. More importantly, multi-omics signatures, such as MMP9 was identified based on three clusters to help us recognize patients with different prognosis and responses to immunotherapy in HCC. This study could further reveal the immune status of HCC and provide potential predictors for immune checkpoint treatment response.
| S-EPMC7249423 | biostudies-literature
Project description:Although the incidence of central nervous system (CNS) cancers is not high, it significantly reduces a patient's quality of life and results in high mortality rates. A low incidence also means a low number of cases, which in turn means a low amount of information. To compensate, researchers have tried to increase the amount of information available from a single test using high-throughput technologies. This approach, referred to as single-omics analysis, has only been partially successful as one type of data may not be able to appropriately describe all the characteristics of a tumor. It is presently unclear what type of data can describe a particular clinical situation. One way to solve this problem is to use multi-omics data. When using many types of data, a selected data type or a combination of them may effectively resolve a clinical question. Hence, we conducted a comprehensive survey of papers in the field of neuro-oncology that used multi-omics data for analysis and found that most of the papers utilized machine learning techniques. This fact shows that it is useful to utilize machine learning techniques in multi-omics analysis. In this review, we discuss the current status of multi-omics analysis in the field of neuro-oncology and the importance of using machine learning techniques.
| S-EPMC8070530 | biostudies-literature
Project description:BackgroundColorectal cancer (CRC) is a complex malignancy characterized by diverse molecular profiles, clinical outcomes, and limited precision in prognostic markers. Addressing these challenges, this study utilized multi-omics data to define consensus molecular subtypes in CRC and elucidate their association with clinical outcomes and underlying biological processes.MethodsConsensus molecular subtypes were obtained by applying ten integrated multi-omics clustering algorithms to analyze TCGA-CRC multi-omics data, including mRNA, lncRNA, miRNA, DNA methylation CpG sites, and somatic mutation data. The association of subtypes with prognoses, enrichment functions, immune status, and genomic alterations were further analyzed. Next, we conducted univariate Cox and Lasso regression analyses to investigate the potential prognostic application of biomarkers associated with multi-omics subtypes derived from weighted gene co-expression network analysis (WGCNA). The function of one of the biomarkers MID2 was validated in CRC cell lines.ResultsTwo CRC subtypes linked to distinct clinical outcomes were identified in TCGA-CRC cohort and validated with three external datasets. The CS1 subtype exhibited a poor prognosis and was characterized by higher tumor-related Hallmark pathway activity and lower metabolism pathway activity. In addition, the CS1 was predicted to have less immunotherapy responder and exhibited more genomic alteration compared to CS2. Then a prognostic model comprising five genes was established, with patients in the high-risk group showing substantial concordance with the CS1 subtype, and those in the low-risk group with the CS2 subtype. The gene MID2, included in the prognostic model, was found to be correlated with epithelial-mesenchymal transition (EMT) pathway and distinct DNA methylation patterns. Knockdown of MID2 in CRC cells resulted in reduced colony formation, migration, and invasion capacities.ConclusionThe integrative multi-omics subtypes proposed potential biomarkers for CRC and provided valuable knowledge for precision oncology.
| S-EPMC10976740 | biostudies-literature
Project description:Colon adenocarcinoma (COAD) is one of the most frequent malignant lesions of the digestive system in humans, with an insidious onset. At the time of diagnosis, most of them have developed to the middle and late stages, and cancer cells have metastasized, and the prognosis is poor. Treatment options for progressive COAD are limited, and despite the promise of immunotherapy, immunotherapy response rates are low. The assembly and disaggregation of focal adhesion are critical for the directional migration of tumor cells to different sites, and it is unclear whether focal adhesion-related genes are involved in the development and prognosis of colon adenocarcinoma. This study aimed to investigate the role of focal adhesion genes in the occurrence and prognosis of COAD. We obtained datasets of COAD patients, including RNA-sequencing data and clinical information, from the TCGA and GEO databases (GSE17538 and GSE39582). Through CNMF clustering, two molecular subtypes with different expression patterns of focal adhesion genes were identified, and it was found that the molecular subtype with low expression of focal adhesion genes had better prognosis. Then the prediction signature was constructed by LASSO-Cox regression model, and the receiver operating characteristic (ROC) curve showed that the 4-gene signature had a good prediction effect on COAD 1-, 2-, and 3-year OS. Gene function enrichment analysis showed that the high-risk group was mainly enriched in immune and adhesion-related signaling pathways, suggesting that focal adhesion genes may affect the development and prognosis of COAD by regulating the immune microenvironment and tumor metastasis. The interaction between focal adhesion genes and immunity during the occurrence of COAD may help improve the response rate of immunotherapy, which also provides new ideas for the molecular mechanism and targeted therapy in COAD.
| S-EPMC10025302 | biostudies-literature
Project description:High-throughput technologies make it possible to produce a large amount of data representing different biological layers, examples of which are genomics, proteomics, metabolomics and transcriptomics. Omics data have been individually investigated to understand the molecular bases of various diseases, but this may not be sufficient to fully capture the molecular mechanisms and the multilayer regulatory processes underlying complex diseases, especially cancer. To overcome this problem, several multi-omics integration methods have been introduced but a commonly agreed standard of analysis is still lacking. In this paper, we present MOUSSE, a novel normalization-free pipeline for unsupervised multi-omics integration. The main innovations are the use of rank-based subject-specific signatures and the use of such signatures to derive subject similarity networks. A separate similarity network was derived for each omics, and the resulting networks were then carefully merged in a way that considered their informative content. We applied it to analyze survival in ten different types of cancer. We produced a meaningful clusterization of the subjects and obtained a higher average classification score than ten state-of-the-art algorithms tested on the same data. As further validation, we extracted from the subject-specific signatures a list of relevant features used for the clusterization and investigated their biological role in survival. We were able to verify that, according to the literature, these features are highly involved in cancer progression and differential survival.
| S-EPMC8304726 | biostudies-literature
Project description:The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.
| S-EPMC8226116 | biostudies-literature