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Analysis of Interleukin-1 Signaling Alterations of Colon Adenocarcinoma Identified Implications for Immunotherapy.

ABSTRACT: Immune checkpoint inhibitors (ICIs) have made breakthrough progress in the treatment of various malignant tumors. However, only some patients receiving ICIs obtain long-lasting clinical effects, and some patients still do not achieve remission. Improving the treatment benefits of this part of the population has become a concern of clinicians. IL-1 signaling plays an important role in the tumor microenvironment (TME). However, the relationship between the IL-1 signaling mutation status and the prognosis of colon adenocarcinoma (COAD) patients receiving ICIs has not been reported. We downloaded the data of a COAD cohort receiving ICIs, including prognostic data and mutation data. Additionally, we downloaded the data of a COAD cohort from The Cancer Genome Atlas (TCGA) database, including clinical data, expression data and mutation data. Gene set enrichment analysis (GSEA) was used to assess differences in the activity of some key physiological pathways between the IL-1 signaling mutated-type (IL-1-MT) and IL-1 signaling wild-type (IL-1-WT) groups. The CIBERSORT algorithm was used to evaluate the contents of immune cells in the TME of COAD patients. The multivariate Cox regression model results suggested that IL-1-MT can be used as an independent predictor of a better prognosis in COAD patients receiving ICIs (P = 0.03, HR = 0.269, 95% CI: 0.082-0.883). Additionally, IL-1-MT COAD patients had significantly longer overall survival (OS) (log-rank P = 0.015). CIBERSORT analysis showed that the IL-1-MT group had high infiltration levels of activated dendritic cells (DCs), M1 macrophages, neutrophils, activated natural killer (NK) cells, activated CD4+ memory T cells and CD8+ T cells. Similarly, the IL-1-MT group had significantly upregulated immunogenicity, including in terms of the tumor mutation burden (TMB), neoantigen load (NAL) and number of mutations in DNA damage repair (DDR) signaling. GSEA showed that the IL-1-MT group was highly enriched in the immune response and proinflammatory mediators. Additionally, the expression levels of immune-related genes, immune checkpoint molecules and immune-related signatures were significantly higher in the IL-1-MT group than in the IL-1-WT group. IL-1-MT may be an independent predictor of a good prognosis in COAD patients receiving ICIs, with significantly longer OS in IL-1-MT COAD patients. Additionally, IL-1-MT was associated with significantly increased immunogenicity, activated immune cell and inflammatory mediator levels and immune response-related scores.

SUBMITTER: Zhou X

PROVIDER: S-EPMC8344046 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSuccinate dehydrogenase (SDH), one of the key enzymes in the tricarboxylic acid cycle, is mainly found in the mitochondria. SDH consists of four subunits encoding SDHA, SDHB, SDHC, and SDHD. The biological function of SDH is significantly related to cancer progression. Colorectal cancer (CRC) is one of the most common malignant tumors globally, whose most common histological subtype is colon adenocarcinoma (COAD). However, the correlation between SDH factors and COAD remains unclear.MethodsThe data on pan-cancer was obtained from The Cancer Genome Atlas (TCGA) database. Kaplan-Meier survival analysis showed the prognostic ability of SDHs. The cBioPortal database reflected genetic variations of SDHs. The correlation analysis was conducted between SDHs and mitochondrial energy metabolism genes (MMGs) and the protein-protein interaction (PPI) network was built. Consequently, Univariate and Multivariate Cox Regression Analysis on SDHs and other clinical characteristics were conducted. A nomogram was established. The ssGSEA analysis visualized the association between SDHs and immune infiltration. Immunophenoscore (IPS) explored the correlation between SDHs and immunotherapy, and the correlation between SDHs and targeted therapy was investigated through Genomics of Drug Sensitivity in Cancer. Finally, qPCR and immunohistochemistry detected SDHs' expression.ResultsAfter assessing SDHs differential expression in pan-cancer, we found that SDHB, SDHC, and SDHD benefit COAD patients. The cBioPortal database demonstrated that SDHA was the top gene in mutation frequency rank. Correlation analysis mirrored a strong link between SDHs and MMGs. We formulated a nomogram and found that SDHB, SDHC, SDHD, and clinical characteristics correlated with COAD patients' survival. For T helper cells, Th2 cells, and Tem, SDHA, SDHB, SDHC, and SDHD were significantly enriched in the high expression group. Moreover, COAD patients with high SDHA expression were more suitable for immunotherapy. And COAD patients with different SDHs' expression have different sensitivity to targeted drugs. Further verifying the gene and protein expression levels of SDHs, we found that the tissues were consistent with the bioinformatics analysis.ConclusionsOur study analyzed the expression and prognostic value of SDHs in COAD, explored the pathway mechanisms involved, and the immune cell correlations, indicating that SDHs might be biomarkers for COAD patients.

Project description:Colorectal cancer is the third most common cancer worldwide, with 1.4 million people diagnosed in 2012 according to GLOBOCAN 2012. 95% of the colon cancer cases are that of adenocarcinomas. Removal of high-risk adenomas and tumors at early stage of colorectal cancer (CRC) can prevent its onset/progression into higher grades of cancer. The prognosis of colorectal cancer and the stage of diagnosis are closely correlated. 5-year survival rate is observed among 90% patients when diagnosed early and in less than 10% when the metastases develop. This makes the implementation of screening methods aimed at early detection paramount for reduced incidence and mortality rate. Adenocarcinomas are the cancers originating from the gland forming cells of the colon and rectal lining and are known to be the most common type of colorectal cancer. The current diagnosis options for colorectal cancers are limited to biopsy, stool tests and other laboratory tests, barium enema based imaging and other imaging techniques, colonoscopy and other endoscopic procedures which are time consuming. In this study, we used proteomics approach with an aim to identify protein biomarkers which can aid in early detection of colon adenocarcinomas to be precise. Proteins from tumor tissue of colon adenocarcinoma subjects (n=11) and their matched controls were subjected to 4-plex iTRAQ labelling followed by off-gel fractionation prior to LC-MS/MS run. The mass spectrometry data was analysed independently using two different analysis software - Spectrum Mill (SM) and Trans Proteome Pipeline (TPP). The proteins identified using either SM and/or TPP were subjected to pathway analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 and the proteins common between the two analyses were compared with the data from CPTAC portal and Human Protein Atlas. The expression level of the shortlisted panel of proteins was studied in brain cancers as a non-colon adenocarcinoma control group and validated using MRM approach. A list of 285 unique proteins was identified to be significantly dysregulated in colon adenocarcinoma as compared to its matched controls. These proteins were found to be involved in glycolysis, pentose phosphate pathway, biosynthesis of amino acids, protein processing, spliceosome, proteosome, focal adhesion and proteoglycans in cancer. 94 of the 285 proteins were identified by both- SM and TPP. 34 of these 94 proteins were found to be dysregulated with same trend as that in data reported on CPTAC portal and 9 of these 34 proteins were validated using MRM approach. The proteins identified from this study could be validated further to investigate the role of these proteins as potential biomarkers for early detection of colon adenocarcinoma.

Project description:BACKGROUND Colon adenocarcinoma (COAD) is one of the most common and fatal malignant tumors, which increases the difficulty of prognostic predictions. Thus, new biomarkers for the diagnosis and prognosis of COAD should be explored. Ferroptosis is a recently identified programmed cell death process that has the characteristics of iron-dependent lipid peroxide accumulation. However, the predictive value of ferroptosis-related genes (FRGs) for COAD still needs to be further clarified. AIM To identify some critical FRGs and construct a COAD patient prognostic signature for clinical utilization. METHODS The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus databases were the data sources for mRNA expression and corresponding COAD patient clinical information. Differentially expressed FRGs were recognized using R and Perl software. We constructed a multi-FRG signature of the TCGA-COAD cohort by performing a univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis. COAD patients from the Gene Expression Omnibus cohort were utilized for verification. RESULTS Our research showed that most of the FRGs (85%) were differentially expressed between the corresponding adjacent normal tissues and cancer tissues in the TCGA-COAD cohort. Seven FRGs were related to overall survival (OS) in the univariate Cox analysis (all P < 0.05). A model with five FRGs (AKR1C1, AKR1C3, ALOX12, CRYAB, and FDFT1) was constructed to divide patients into high- and low-risk groups. The OS of patients in the high-risk group was significantly lower than that of the low-risk group (all P < 0.01 in the TCGA and Gene Expression Omnibus cohorts). The risk score was an independent prognosticator of OS in the multivariate Cox analysis (hazard ratio > 1, P < 0.01). The predictive capacity of the model was verified by a receiver operating characteristic curve analysis. In addition, a nomogram based on the expression of five hub FRGs and risk score can precisely predict the OS of individual COAD cancer patients. Immune correlation analysis and functional enrichment analysis results revealed that immunology-related pathways were abundant, and the immune states of the high-risk group and the low-risk group were different. CONCLUSION In conclusion, a novel five FRG model can be utilized for predicting prognosis in COAD. Targeting ferroptosis may be a treatment option for COAD.

Project description:BackgroundLung adenocarcinoma (LUAD) is a fatal malignancy in the world. Growing evidence demonstrated that autophagy-related genes regulated the immune cell infiltration and correlated with the prognosis of LUAD. However, the autophagy-based signature that can predict the prognosis and the efficiency of checkpoint immunotherapy in LUAD patients is yet to be discovered.MethodsWe used conventional autophagy-related genes to screen candidates for signature construction in TCGA cohort and 9 GEO datasets (tumor samples, n=2181; normal samples, n=419). An autophagy-based signature was constructed, its correlation with the prognosis and the immune infiltration of LUAD patients was explored. The prognostic value of the autophagy-based signature was validated in an independent cohort with 70 LUAD patients. Single-cell sequencing data was used to further characterize the various immunological patterns in tumors with different signature levels. Moreover, the predictive value of autophagy-based signature in PD-1 immunotherapy was explored in the IMvigor210 dataset. At last, the protective role of DRAM1 in LUAD was validated by in vitro experiments.ResultsAfter screening autophagy-related gene candidates, a signature composed by CCR2, ITGB1, and DRAM1 was established with the ATscore in each sample. Further analyses showed that the ATscore was significantly associated with immune cell infiltration and low ATscore indicated poor prognosis. Meanwhile, the prognostic value of ATscore was validated in our independent LUAD cohort. GSEA analyses and single-cell sequencing analyses revealed that ATscore was associated with the immunological status of LUAD tumors, and ATscore could predict the efficacy of PD-1 immunotherapy. Moreover, in vitro experiments demonstrated that the inhibition of DRAM1 suppressed the proliferation and migration capacity of LUAD cells.ConclusionOur study identified a new autophagy-based signature that can predict the prognosis of LUAD patients, and this ATscore has potential applicative value in the checkpoint therapy efficiency prediction.

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Analysis of Interleukin-1 Signaling Alterations of Colon Adenocarcinoma Identified Implications for Immunotherapy.

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