Dataset Information

Fibroblast-derived LPP as a biomarker for treatment response and therapeutic target in gastric cancer.

ABSTRACT: Association of tumor microenvironment and immune checkpoint (e.g., PD-L1) is important for immune escape, impacting chemotherapy and immunotherapy efficacy. We aimed to investigate biomarkers and therapeutic targets against treatment resistance in gastric cancer. Abundances of tumor-infiltrating immune cells were estimated in multiple datasets. Three patient subgroups (A, B, and C) were identified based on seven types of PD-L1- and IFN-γ-associated immune cells. Patients yielded increased prognosis from subgroup A to C (p = 0.027). Subgroup A was characterized by high activated CD4⁺ memory T cell infiltration, while more resting CD4⁺ memory T cells were in subgroup C. Further, a risk score was developed for prognostication. Lipoma preferred partner (LPP), as the hub gene in subgroup-related regulatory network, was upregulated (p < 0.01) and was associated with high risk score (p < 0.001) and poor survival (p < 0.05). Bioinformatics analyses and experiments found that LPP expressed restrictively in fibroblasts and associated with activated CD4⁺ memory T cell infiltration and tumor growth. High-LPP patients yielded fewer benefits from chemotherapy or immunotherapy, compared with the low-LPP group. We finally identified 28 compounds as sensitive drugs for high-LPP patients. Our findings suggested LPP might be a biomarker for treatment response and therapeutic target in gastric cancer.

SUBMITTER: Wang H

PROVIDER: S-EPMC8857546 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Fibroblast-derived LPP as a biomarker for treatment response and therapeutic target in gastric cancer.

Wang Hao H Wu Jing J Ling Ruoyu R Li Fengping F Yang Qingbin Q He Jiayong J Lei Xuetao X Wu Chaorui C Zhang Guofan G Zheng Boyang B Peng Yanmei Y Zhang Yihao Y Chen Hao H Ye Gengtai G Li Guoxin G

Molecular therapy oncolytics 20220201

Association of tumor microenvironment and immune checkpoint (e.g., PD-L1) is important for immune escape, impacting chemotherapy and immunotherapy efficacy. We aimed to investigate biomarkers and therapeutic targets against treatment resistance in gastric cancer. Abundances of tumor-infiltrating immune cells were estimated in multiple datasets. Three patient subgroups (A, B, and C) were identified based on seven types of PD-L1- and IFN-γ-associated immune cells. Patients yielded increased progno ...[more]

PMID: 35229032

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Project description:BackgroundCancer-associated fibroblasts (CAFs) contribute to the progression and treatment of breast cancer (BRCA); however, risk signatures and molecular targets based on CAFs are limited. This study aims to identify novel CAF-related biomarkers to develop a risk signature for predicting the prognosis and therapeutic response of patients with BRCA.MethodsCAF-related genes (CAFRGs) and a risk signature based on these genes were comprehensively analyzed using publicly available bulk and single-cell transcriptomic datasets. Modular genes identified from bulk sequencing data were intersected with CAF marker genes identified from single-cell analysis to obtain reliable CAFRGs. Signature CAFRGs were screened via Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. Multiple patient cohorts were used to validate the prognosis and therapeutic responsiveness of high-risk patients stratified based on the CAFRG-based signature. In addition, the relationship between the CAFRG-based signature and clinicopathological factors, tumor immune landscape, functional pathways, chemotherapy sensitivity and immunotherapy sensitivity was examined. External datasets were used and sample experiments were performed to examine the expression pattern of MFAP4, a key CAFRG, in BRCA.ResultsIntegrated analyses of single-cell and bulk transcriptomic data as well as prognostic screening revealed a total of 43 prognostic CAFRGs; of which, 14 genes (TLN2, SGCE, SDC1, SAV1, RUNX1, PDLIM4, OSMR, NT5E, MFAP4, IGFBP6, CTSO, COL12A1, CCDC8 and C1S) were identified as signature CAFRGs. The CAFRG-based risk signature exhibited favorable efficiency and accuracy in predicting survival outcomes and clinicopathological progression in multiple BRCA cohorts. Functional enrichment analysis suggested the involvement of the immune system, and the immune infiltration landscape significantly differed between the risk groups. Patients with high CAF-related risk scores (CAFRSs) exhibited tumor immunosuppression, enhanced cancer hallmarks and hyposensitivity to chemotherapy and immunotherapy. Five compounds were identified as promising therapeutic agents for high-CAFRS BRCA. External datasets and sample experiments validated the downregulation of MFAP4 and its strong correlation with CAFs in BRCA.ConclusionsA novel CAF-derived gene signature with favorable predictive performance was developed in this study. This signature may be used to assess prognosis and guide individualized treatment for patients with BRCA.

Project description:BackgroundGastric cancer (GC) is one of the most prevalent cancer types that reduce human life expectancy. The current tumor-node-metastasis (TNM) staging system is inadequate in identifying higher or lower risk of GC patients because of tumor heterogeneity. Research shows that complement plays a dual role in the tumor development and progression of GC.MethodsWe downloaded GC data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A complement-related risk signature was constructed through bioinformatics analysis. Subsequently, the predictive ability of this signature was validated with GSE84437 dataset, and a nomogram integrating risk score and common clinical factors was established. Besides, we evaluated the association of risk score with the immune and stromal cell infiltration in TCGA. Furthermore, immunotherapy response prediction and drug susceptibility analysis were conducted to access the ability of the risk signature in predicting the therapeutic effect.ResultsA complement-related gene (CRG) signature, based on six genes (SPLG, C9, ITIH1, ZFPM2, CD36, and SERPINE1), was established. In both the training and validation sets, the overall survival of GC patients in the high-risk group was lower than that of the low-risk group, and the nomogram to predict the 1-, 2-, and 3-year survival rates of GC patients was developed. In addition, CIBERSORT algorithm showed the high-risk patients had higher levels of immune cell infiltration than low-risk patients, and the ESTIMATE results implied that the high-risk group had more stromal component in tumor microenvironment. Besides, compared to the low-risk group, there were higher expressions of most immune checkpoint genes and HLA genes in the high-risk group, and the high-risk patients showed higher sensitivity to the chemotherapy and targeted drugs (axitinib, dasatinib, pazopanib, saracatinib, sunitinib and temsirolimus).ConclusionsThe novel CRG signature may act as a reliable, efficient tool for prognostic prediction and treatment guidance in future clinical practice.

Dataset Information

Fibroblast-derived LPP as a biomarker for treatment response and therapeutic target in gastric cancer.

Publications

Fibroblast-derived LPP as a biomarker for treatment response and therapeutic target in gastric cancer.

Similar Datasets

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