Dataset Information

Comprehensive analysis of glycolysis mediated pattern clusters and immune infiltration characterization of tumor microenvironment in triple-negative breast cancer.

ABSTRACT:

Background

The involvement of glycolysis in carcinogenesis and the tumor microenvironment is being increasingly supported by the available data. The aim of this work was to develop a triple-negative breast cancer predictive model based on glycolysis.

Methods

Glycolysis mediated pattern clusters were created using the R "ConsensusClusterPlus" package. The variations in the tumor microenvironment between the pattern clusters were examined using the R "GSVA", "ESTIMATE", and "CIBERSORT" package. The risk score and nomogram were established to assess clinical outcomes of patients.

Results

Substantial differences were observed in the immunological landscape between the glycolysis-mediated pattern clusters. When it came to predicting survival and immunotherapy response, the developed risk score showed promising predictive power. Nomogram was designed to be used in therapeutic settings due to its remarkable predictive accuracy.

Conclusions

The immune microenvironment varied among cases of triple-negative breast cancer. The nomogram and the risk score based on glycolysis could both be used to help create more effective treatments.

SUBMITTER: Liu J

PROVIDER: S-EPMC10119610 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Publications

Comprehensive analysis of glycolysis mediated pattern clusters and immune infiltration characterization of tumor microenvironment in triple-negative breast cancer.

Liu Ji J Zhu Junwen J Zhang Qingyuan Q

Heliyon 20230401 4

<h4>Background</h4>The involvement of glycolysis in carcinogenesis and the tumor microenvironment is being increasingly supported by the available data. The aim of this work was to develop a triple-negative breast cancer predictive model based on glycolysis.<h4>Methods</h4>Glycolysis mediated pattern clusters were created using the R "ConsensusClusterPlus" package. The variations in the tumor microenvironment between the pattern clusters were examined using the R "GSVA", "ESTIMATE", and "CIBERSO ...[more]

PMID: 37089355

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Project description:BackgroundEven though immunotherapy has been an effective treatment for solid tumors, its efficacy in osteosarcoma remains sub-optimal. It is therefore imperative to understand the complex tumor microenvironment (TME) of osteosarcoma to facilitate the development of immunotherapies against this cancer.MethodsThe mRNA expression profiles of osteosarcoma tissues were downloaded from The Cancer Genome Atlas (TCGA) database. Next, the ssGSEA, MCP-counter, CIBERSORT, and Xcell algorithm analyses were performed to characterize the tumor microenvironment of osteosarcoma tissues. The tumor tissues were divided into inflammatory and non-inflammatory. A comprehensive assessment of immune cell infiltration in osteosarcoma tissues was then performed. Sub-group analysis of immune cell infiltration between men and women patients with osteosarcoma was also carried out.ResultsThe results revealed that the infiltration of immune cells including activated B cell, activated CD8 T cell, CD56dim natural killer cell, and cytotoxic lymphocytes cells, in osteosarcoma tissues was higher in male than in female patients. Based on the infiltration profile of different immune cells, the osteosarcoma tissues were grouped into four clusters. The four clusters were further divided into hot and cold tumors. The differently expressed genes (DEGs) between cold and hot tumors were mainly associated with the activation and regulation of immune response. Additionally, a neuronal pentraxin (NPTX2) expression which was upregulated in cold tumors was found to be negatively correlated with the expression of CD8a Molecule (CD8A), Granzyme B (GZMB), and Interferon Gamma (IFNG). NPTX2 decreased CCL4 secretion. Knockdown of NPTX2 in osteosarcoma cells inhibited tumor growth and increased tumor cell apoptosis. Moreover, a prognosis prediction model of osteosarcoma was constructed and validated in patients receiving immunotherapy using external data.ConclusionsTo the best of our knowledge, this is the first study to characterize the infiltration of immune cells in osteosarcoma tissues from patients receiving immune infiltration therapy.

Project description:Background: Recent studies have found that senescence-associated genes play a significant role in cancer biological processes. We aimed to analyze the characteristics and role of senescence-associated genes in triple-negative breast cancer (TNBC). Methods: We systematically screened senescence-associated secretory phenotype (SASP) genes based on the gene expression information in the TCGA database. According to the expression levels of senescence-associated genes, TNBC was classified into two subtypes, namely, TNBCSASP1 and TNBCSASP2, using an unsupervised cluster algorithm. We then performed gene expression, enrichment pathway, immune infiltration, mutational profile characterization, drug sensitivity and prognostic value analyses for the two subtypes. The reliability and prognostic predictive utility of this classification model were validated. The most prognostically relevant gene, FAM3B, was comprehensively identified and validated by tissue microarray in TNBC. Results: TNBC was classified into two senescence-associated subtypes, TNBCSASP1 and TNBCSASP2, based on the set of senescence-associated secretory phenotype genes, among which the TNBCSASP1 subtype had a poor prognosis. The TNBCSASP1 subtype was immunosuppressed, with suppressed immune-related signaling pathways and low immune cell infiltration. The effect of the mutation on the TP53 and TGF-β pathways could be related to the poor prognosis of the TNBCSASP1 subtype. Drug sensitivity analysis showed that AMG.706, CCT007093, and CHIR.99021 were potential targeted drugs for the TNBCSASP1 subtype. Finally, FAM3B was a key biomarker affecting the prognosis of patients with triple-negative breast cancer. Compared to normal breast tissue, the expression of FAM3B was reduced in triple-negative breast cancer. Survival analysis showed that overall survival was significantly shorter in triple-negative breast cancer patients with high FAM3B expression. Conclusion: A senescence-associated signature with different modification patterns has critical potential for providing a better understanding of TNBC biological processes, and FAM3B might serve as an applicable target for TNBC therapy.

Dataset Information

Comprehensive analysis of glycolysis mediated pattern clusters and immune infiltration characterization of tumor microenvironment in triple-negative breast cancer.

Background

Methods

Results

Conclusions

Publications

Comprehensive analysis of glycolysis mediated pattern clusters and immune infiltration characterization of tumor microenvironment in triple-negative breast cancer.

Similar Datasets

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