Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors.
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ABSTRACT:
SUBMITTER: Liu QF
PROVIDER: S-EPMC8247483 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe SET and MYND domain-containing (SMYD) gene family comprises a set of genes encoding lysine methyltransferases. This study aimed to clarify the relationship between the expression levels of SMYD family members and the prognosis and immune infiltration of malignant tumors of the digestive system.MethodsThe Oncomine, Ualcan, Kaplan-Meier Plotter, cBioPortal, Metascape, and TIMER databases and tools were used to analyze the correlation of SMYD family mRNA expression, clinical stage, TP53 mutation status, prognostic value, gene mutation, and immune infiltration in patients with esophageal carcinoma (ESCA), liver hepatocellular carcinoma (LIHC), and stomach adenocarcinoma (STAD).ResultsIn ESCA, the mRNA expression of SMYD2/3/4/5 was significantly correlated with the incidence rate, that of SMYD2/3 with the clinical stage, that of SMYD2/3/4/5 with TP53 mutation status, that of SMYD2/4/5 with overall survival (OS), and that of SMYD1/2/3/4 with relapse-free survival (RFS). In LIHC, the mRNA expression of SMYD1/2/3/4/5 was significantly correlated with the incidence rate, that of SMYD2/4/5 with the clinical stage, that of SMYD3/5 with TP53 mutation status, that of SMYD2/3/4/5 with OS, and that of SMYD3/5 with RFS. In STAD, the mRNA expression of SMYD2/3/4/5 was significantly correlated with the incidence rate, that of SMYD1/4 with the clinical stage, that of SMYD1/2/3/5 with TP53 mutation status, that of SMYD1/3/4 with OS, and that of SMYD1/3 with RFS. Furthermore, the function of SMYD family mutation-related genes in ESCA, LIHC, and STAD patients was mainly related to pathways, such as mitochondrial gene expression, mitochondrial matrix, and mitochondrial translation. The expression of SMYD family genes was significantly correlated with the infiltration of six immune cell types and eight types of immune check sites.ConclusionSMYD family genes are differentially expressed and frequently mutated in malignant tumors of the digestive system (ESCA, LIHC, and gastric cancer). They are potential markers for prognostic prediction and have important significance in immunity and targeted therapy.
| S-EPMC8322783 | biostudies-literature
Project description:The digestive system cancers are aggressive cancers with the highest mortality worldwide. In this study, we undertook a systematic investigation of the tumor immune microenvironment to identify diagnostic and prognostic biomarkers. The fraction of 22 immune cell types of patients were estimated using CIBERSORT. The least absolute shrinkage and selection operator (LASSO) analysis was carried out to identify important immune predictors. By comparing immune cell compositions in 801 tumor samples and 46 normal samples, we constructed the diagnostic immune score (DIS), showing high specificity and sensitivity in the training (area under the receiver operating characteristic curve [AUC] = 0.929), validation (AUC = 0.935), and different cancer type cohorts (AUC > 0.70 for all). We also established the prognostic immune score (PIS), which was an effective prognostic factor for relapse-free survival in training, validation, and entire cohorts (P < .05). In addition, PIS provided a higher net benefit than TNM stage. A composite nomogram was built based on PIS and patients' clinical information with well-fitted calibration curves (c-index = 0.84). We further used other cohorts from Gene Expression Omnibus databases and obtained similar results, confirming the reliability and validity of the DIS and PIS. In addition, the unsupervised clustering analysis using immune cell proportions revealed 6 immune subtypes, suggesting that the immune types defined as having relatively high levels of M0 or/and M1 macrophages were the high-risk subtypes of relapse. In conclusion, this study comprehensively analyzed the tumor immune microenvironment and identified DIS and PIS for digestive system cancers.
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Project description:BackgroundMalignant mesothelioma (MM) is a relatively rare and highly lethal tumor with few treatment options. Thus, it is important to identify prognostic markers that can help clinicians diagnose mesothelioma earlier and assess disease activity more accurately. Alternative splicing (AS) events have been recognized as critical signatures for tumor diagnosis and treatment in multiple cancers, including MM.MethodsWe systematically examined the AS events and clinical information of 83 MM samples from TCGA database. Univariate Cox regression analysis was used to identify AS events associated with overall survival. LASSO analyses followed by multivariate Cox regression analyses were conducted to construct the prognostic signatures and assess the accuracy of these prognostic signatures by receiver operating characteristic (ROC) curve and Kaplan-Meier survival analyses. The ImmuCellAI and ssGSEA algorithms were used to assess the degrees of immune cell infiltration in MM samples. The survival-related splicing regulatory network was established based on the correlation between survival-related AS events and splicing factors (SFs).ResultsA total of 3976 AS events associated with overall survival were identified by univariate Cox regression analysis, and ES events accounted for the greatest proportion. We constructed prognostic signatures based on survival-related AS events. The prognostic signatures proved to be an efficient predictor with an area under the curve (AUC) greater than 0.9. Additionally, the risk score based on 6 key AS events proved to be an independent prognostic factor, and a nomogram composed of 6 key AS events was established. We found that the risk score was significantly decreased in patients with the epithelioid subtype. In addition, unsupervised clustering clearly showed that the risk score was associated with immune cell infiltration. The abundances of cytotoxic T (Tc) cells, natural killer (NK) cells and T-helper 17 (Th17) cells were higher in the high-risk group, whereas the abundances of induced regulatory T (iTreg) cells were lower in the high-risk group. Finally, we identified 3 SFs (HSPB1, INTS1 and LUC7L2) that were significantly associated with MM patient survival and then constructed a regulatory network between the 3 SFs and survival-related AS to reveal potential regulatory mechanisms in MM.ConclusionOur study provided a prognostic signature based on 6 key events, representing a better effective tumor-specific diagnostic and prognostic marker than the TNM staging system. AS events that are correlated with the immune system may be potential therapeutic targets for MM.
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Project description:Tumour-infiltrating immune cells are a source of important prognostic information for patients with resectable colon cancer. We developed a novel immune model based on systematic assessments of the immune landscape inferred from bulk tumor transcriptomes of stage I-III colon cancer patients. The "Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT)" algorithm was used to estimate the fraction of 22 immune cell types from six microarray public datasets. The random forest method and least absolute shrinkage and selection operator model were then used to establish immunoscores for diagnosis and prognosis. By comparing immune cell compositions in samples of 870 colon cancer patients and 70 normal controls, we constructed a diagnostic model, designated the diagnostic immune risk score (dIRS), that showed high specificity and sensitivity in both the training [area under the curve (AUC)?=?0.98, p?<?0.001] and validation (AUC 0.96, p?<?0.001) sets. We also established a prognostic immune risk score (pIRS) that was found to be an independent prognostic factor for relapse-free survival in every series (training: HR?2.23; validation: HR 1.65; entire: HR 2.01; p?<?0.001 for all), which showed better prognostic value than TNM stage. In addition, integration of the pIRS with clinical characteristics in a composite nomogram showed improved accuracy of relapse risk prediction, providing a higher net benefit than TNM stage, with well-fitted calibration curves. The proposed dIRS and pIRS models represent promising novel signatures for the diagnosis and prognosis prediction of colon cancer.
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Project description:The tumor biomarkers already have proven clinical value and have become an integral part in cancer management and modern translational oncology. The tumor tissue microenvironment (TME), which includes extracellular matrix (ECM), signaling molecules, immune and stromal cells, and adjacent non-tumorous tissue, contributes to cancer pathogenesis. Thus, TME-derived biomarkers have many clinical applications. This review is predominately based on the most recent publications (manuscripts published in a last 5 years, or seminal publications published earlier) and fills a gap in the current literature on the cancer biomarkers derived from the TME, with particular attention given to the ECM and products of its processing and degradation, ECM-associated extracellular vesicles (EVs), biomechanical characteristics of ECM, and ECM-derived biomarkers predicting response to the immunotherapy. We discuss the clinical utility of the TME-incorporating three-dimensional in vitro and ex vivo cell culture models for personalized therapy. We conclude that ECM is a critical driver of malignancies and ECM-derived biomarkers should be included in diagnostics and prognostics panels of markers in the clinic.
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Project description:BackgroundSarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we characterize infiltrating immune cells and analyze immune scores to identify the molecular mechanism of immunologic response to sarcomas.MethodThe "CIBERSORT" algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the "ESTIMATE" algorithm was used to assess the "Estimate," "Immune," and "Stromal" scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the "clusterProfiler" package in R for annotation and visualization.ResultsMacrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level.ConclusionBased on the immune cell infiltration and immune microenvironment, three key genes were identified, thus presenting novel molecular mechanisms of sarcoma metastasis.
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Project description:Although more and more evidence supports CDC28 protein kinase subunit 1B (CKS1B) is involved significantly in the development of human cancers, most of the researches have focused on a single disease, and pan-cancer studies conducted from a holistic perspective of different tumor sources have not been reported yet. Here, for the first time, we investigated the potential oncogenic and prognostic role of CKS1B across 33 tumors based on public databases and further verified it in a small scale by RNA sequencing or quantitative real-time PCR. CKS1B was generally highly expressed in a majority of tumors and had a notable correlation with the prognosis of patients, but its prognostic significance in different tumors was not exactly the same. In addition, CKS1B expression was also closely related to the infiltration of cancer-associated fibroblasts in tumors such as breast invasive carcinoma, kidney chromophobe, lung adenocarcinoma, and tumor-infiltrating lymphocytes in tumors such as glioblastoma multiforme, bladder urothelial carcinoma, and brain lower grade glioma. Moreover, reduced CKS1B methylation was observed in certain tumors, for example, adrenocortical carcinoma. Cell cycle and kinase activity regulation and PI3K-Akt signaling pathway were found to be involved in the functional mechanism of CKS1B. In conclusion, our first pan-cancer analysis of CKS1B contributes to a better overall understanding of CKS1B and may provide a new target for future cancer therapy.
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Project description:GREB1L is a protein-coding gene that is an important paralog of GREB1. However, its effects in lung adenocarcinoma (LUAD) have not been determined. Thus, we evaluated the prognostic value of GREB1L in LUAD using bioinformatics approaches. In particular, we evaluated the relationship between GREB1L and LUAD using a wide range of databases and analysis tools, including TCGA, GEO, HPA, TIMER, cBioPortal, and MethSurv. Compared with its expression in normal lung tissues, GREB1L expression was significantly increased in LUAD tissues. A univariate Cox analysis showed that high GREB1L expression levels were correlated with a poor OS in LUAD. Additionally, GREB1L expression was independently associated with OS through a multivariate Cox analysis. GSEA analysis revealed enrichment in cell cycle, immune regulation, and methylation. Moreover, high GREB1L expression was associated with poor survival. We also found that the methylation and genetic alteration level was associated with prognosis in patients with LUAD. Finally, an analysis of immune infiltration showed that GREB1L is correlated with immune cell infiltration, PD-1, and PD-L1. In summary, these results indicate that GREB1L is a potential molecular marker for poor prognosis in LUAD and provide additional insight for the development of therapies and prognostic markers.
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Project description:To explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.
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Project description:PurposeFSTL3 expression is altered in various types of cancer. However, the role and mechanism of action of FSTL3 in lung adenocarcinoma development and tumor immunity are unknown. We investigated the association between FSTL3 expression and clinical characteristics and immune cell infiltration in lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) and a separate validation set from our hospital.MethodsData on immune system infiltration, gene expression, and relevant clinical information were obtained by analyzing lung adenocarcinoma sample data from TCGA database. Using online tools like GEPIA, the correlations between FSTL3 expression and prognosis, clinical stage, survival status, and tumor-infiltrating immune cells were examined. In a validation dataset, immunohistochemistry was performed to analyze FSTL3 expression and its related clinical characteristics.ResultsFSTL3 expression was markedly reduced in patients with lung adenocarcinoma. N stage, pathological stage, and overall survival were significantly correlated with FSTL3 expression. According to GSEA, FSTL3 is strongly linked to signaling pathways such as DNA replication and those involved in cell cycle regulation. Examination of TCGA database and TIMER online revealed a correlation between FSTL3 and B cell, T cell, NK cell, and neutrophil levels. The prognosis of patients with lung adenocarcinoma was significantly affected by six genes (KRT6A, VEGFC, KRT14, KRT17, SNORA12, and KRT81) related to FSTL3.ConclusionFSTL3 is significantly associated with the prognosis and progression of lung adenocarcinoma and the infiltration of immune cells. Thus, targeting FSTL3 and its associated genes in immunotherapy could be potentially beneficial for the treatment of lung adenocarcinoma.
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