Dataset Information

Development and validation of a novel T cell proliferation-related prognostic model for predicting survival and immunotherapy benefits in melanoma.

ABSTRACT:

Background

T cell plays a crucial role in the occurrence and progression of Skin cutaneous melanoma (SKCM). This research aims to identify the actions of T cell proliferation-related genes (TRGs) on the prognosis and immunotherapy response of tumor patients.

Method

The clinical manifestation and gene expression data of SKCM patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. T cell proliferation-related molecular subtypes were identified utilizing consensus clustering. Subsequently, Cox and Lasso regression analysis was conducted to identify six prognostic genes, and a prognostic signature was constructed. A series of experiments, such as qRT-PCR, Western blotting and CCK8 assay, were then conducted to verify the reliability of the six genes.

Results

In this study, a grading system was established to forecast survival time and responses to immunotherapy, providing an overview of the tumoral immune landscape. Meanwhile, we identified six prognostic signature genes. Notably, we also found that C1RL protein may inhibit the growth of melanoma cell lines.

Conclusion

The scoring system depending on six prognostic genes showed great efficiency in predicting survival time. The system could help to forecast prognosis of SKCM patients, characterize SKCM immunological condition, assess patient immunotherapy response.

SUBMITTER: Chen J

PROVIDER: S-EPMC10258015 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a novel T cell proliferation-related prognostic model for predicting survival and immunotherapy benefits in melanoma.

Chen Jiajie J Wang Daiyue D Chan Shixin S Yang Qingqing Q Wang Chen C Wang Xu X Sun Rui R Gui Yu Y Yu Shuling S Yang Jinwei J Zhang Haoxue H Zhang Xiaomin X Tang Kechao K Zhang Huabing H Liu Shengxiu S

Aging 20230524 10

<h4>Background</h4>T cell plays a crucial role in the occurrence and progression of Skin cutaneous melanoma (SKCM). This research aims to identify the actions of T cell proliferation-related genes (TRGs) on the prognosis and immunotherapy response of tumor patients.<h4>Method</h4>The clinical manifestation and gene expression data of SKCM patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. T cell proliferation-related molecular subtypes were id ...[more]

PMID: 37227816

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Project description:Background: Notch receptors (Notch 1/2/3/4), the critical effectors of the Notch pathway, participate in the tumorigenesis and progression of many malignancies. However, the clinical roles of Notch receptors in primary glioblastoma (GBM) have not been fully elucidated. Methods: The genetic alteration-related prognostic values of Notch receptors were determined in the GBM dataset from The Cancer Genome Atlas (TCGA). Two GBM datasets from TCGA and Chinese Glioma Genome Atlas (CGGA) were used to explore the differential expression between Notch receptors and IDH mutation status, and GBM subtypes. The biological functions of Notch Receptors were explored by Gene Ontology and KEGG analysis. The expression and prognostic significance of Notch receptors were determined in the TCGA and CGGA datasets and further validated in a clinical GBM cohort by immunostaining. A Notch3-based nomogram/predictive risk model was constructed in the TCGA dataset and validated in the CGGA dataset. The model performance was evaluated by receiver operating curves, calibration curves, and decision curve analyses. The Notch3-related phenotypes were analyzed via CancerSEA and TIMER. The proliferative role of Notch3 in GBM was validated in U251/U87 glioma cells by Western blot and immunostaining. Results: Notch receptors with genetic alterations were associated with poor survival of GBM patients. Notch receptors were all upregulated in GBM of TCGA and CGGA databases and closely related to the regulation of transcription, protein-lysine N-methyltransferase activity, lysine N-methyltransferase activity, and focal adhesion. Notch receptors were associated with Classical, Mesenchymal, and Proneural subtypes. Notch1 and Notch3 were closely correlated with IDH mutation status and G-CIMP subtype. Notch receptors displayed the differential expression at the protein level and Notch3 showed a prognostic significance in a clinical GBM cohort. Notch3 presented an independent prognostic role for primary GBM (IDH1 mutant/wildtype). A Notch3-based predictive risk model presented favorable accuracy, reliability, and net benefits for predicting the survival of GBM patients (IDH1 mutant/wildtype and IDH1 wildtype). Notch3 was closely related to immune infiltration (macrophages, CD4+ T cells, and dendritic cells) and tumor proliferation. Conclusion: Notch3-based nomogram served as a practical tool for anticipating the survival of GBM patients, which was related to immune-cell infiltration and tumor proliferation.

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Project description:BackgroundThe tumor microenvironment (TME) plays a critical role in tumorigenesis, development, and therapeutic efficacy. Major advances have been achieved in the treatment of various cancers through immunotherapy. Nevertheless, only a minority of patients have positive responses to immunotherapy, which is partly due to conditions of the immunosuppressive microenvironment. Therefore, it is essential to identify prognostic biomarkers that reflect heterogeneous landscapes of the TME.Methods and materialsBased upon the ESTIMATE algorithm, we evaluated the infiltrating levels of immune and stromal components derived from patients afflicted by various types of cancer from The Cancer Genome Atlas database (TCGA). According to respective patient immune and stromal scores, we categorized cases into high- and low-scoring subgroups for each cancer type to explore associations between TME and patient prognosis. Gene Set Enrichment Analyses (GSEA) were conducted and genes enriched in IFNγ response signaling pathway were selected to facilitate establishment of a risk model for predicting overall survival (OS). Furthermore, we investigated the associations between the prognostic signature and tumor immune infiltration landscape by using CIBERSORT algorithm and TIMER database.ResultsAmong the cancers assessed, the immune scores for skin cutaneous melanoma (SKCM) were the most significantly correlated with patients' survival time (P < .0001). We identified and validated a five-IFNγ response-related gene signature (UBE2L6, PARP14, IFIH1, IRF2, and GBP4), which was closely correlated with the prognosis for SKCM afflicted patients. Multivariate Cox regression analysis indicated that this risk model was an independent prognostic factor for SKCM. Tumor-infiltrating lymphocytes and specific immune checkpoint molecules had notably differential levels of expression in high- compared to low-risk samples.ConclusionIn this study, we established a novel five-IFNγ response-related gene signature that provided a better and increasingly comprehensive understanding of tumor immune landscape, and which demonstrated good performance in predicting outcomes for patients afflicted by SKCM.

Dataset Information

Development and validation of a novel T cell proliferation-related prognostic model for predicting survival and immunotherapy benefits in melanoma.

Background

Method

Results

Conclusion

Publications

Development and validation of a novel T cell proliferation-related prognostic model for predicting survival and immunotherapy benefits in melanoma.

Similar Datasets

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