Integrative analyses of bulk and single-cell RNA-seq identified cancer-associated fibroblasts-related signature as a prognostic factor for immunotherapy in NSCLC

Wang, Shasha; Fan, Guangyu; Li, Lin; He, Yan-Ling; Lou, Ning; Xie, Tongji; Dai, Lan; Gao, Ruyun; Yang, Mengwei; Shi, Yuankai; Han, Xiaohong

doi:10.1007/s00262-023-03428-0

Cited by 7 publications

(3 citation statements)

References 54 publications

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“…Using expression data, the ESTIMATE algorithm was used to estimate stromal cells and immune cells in malignant tumor tissue and calculate the stromal score, which indicates the level of stromal infiltration in each sample ( 35 ). Moreover, CAF infiltration, co-expression network and hub genes for matrix score were determined and identified using WGCNA ( 36 , 37 ). Pearson correlation was used to compute the similarity matrix between any pair of genes.…”

Section: Methodsmentioning

confidence: 99%

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Cancer-associated fibroblasts refine the classifications of gastric cancer with distinct prognosis and tumor microenvironment characteristics

Wei

Zhou

2023

Front. Oncol.

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BackgroundCancer-associated fibroblasts (CAFs) are essential tumoral components of gastric cancer (GC), contributing to the development, therapeutic resistance and immune-suppressive tumor microenvironment (TME) of GC. This study aimed to explore the factors related to matrix CAFs and establish a CAF model to evaluate the prognosis and therapeutic effect of GC.MethodsSample information from the multiply public databases were retrieved. Weighted gene co-expression network analysis was used to identify CAF-related genes. EPIC algorithm was used to construct and verify the model. Machine-learning methods characterized CAF risk. Gene set enrichment analysis was employed to elucidate the underlying mechanism of CAF in the development of GC.ResultsA three-gene (GLT8D2, SPARC and VCAN) prognostic CAF model was established, and patients were markedly divided according to the riskscore of CAF model. The high-risk CAF clusters had significantly worse prognoses and less significant responses to immunotherapy than the low-risk group. Additionally, the CAF risk score was positively associated with CAF infiltration in GC. Moreover, the expression of the three model biomarkers were significantly associated with the CAF infiltration. GSEA revealed significant enrichment of cell adhesion molecules, extracellular matrix receptors and focal adhesions in patients at a high risk of CAF.ConclusionThe CAF signature refines the classifications of GC with distinct prognosis and clinicopathological indicators. The three-gene model could effectively aid in determining the prognosis, drug resistance and immunotherapy efficacy of GC. Thus, this model has promising clinical significance for guiding precise GC anti-CAF therapy combined with immunotherapy.

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Section: Methodsmentioning

confidence: 99%

“…All statistical analyses were performed using R software and SPSS software. The median CAF risk score was the cutoff for each cohort to classify patients with GC ( 36 , 37 ). Finally, the wilcoxon test was used for pairwise comparisons.…”

Section: Methodsmentioning

confidence: 99%

Cancer-associated fibroblasts refine the classifications of gastric cancer with distinct prognosis and tumor microenvironment characteristics

Wei

Zhou

2023

Front. Oncol.

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“…As prospective therapeutic targets, T-cell exclusion in NSCLC is governed by the distinct ECM profiles and spatial distribution of CAFs ( 54 ). Furthermore, CAFs serve as a prognostic indicator for immunotherapy efficacy in non-small cell lung cancer ( 55 ). The ‘Reverse Warburg Effect’ in LC is supported by research, but it is limited to certain tumor cell lines and can be modified by different CAFs ( 56 ).…”

Section: Overview Of Tumor Immune Microenvironment and Lung Cancermentioning

confidence: 99%

A review of natural products targeting tumor immune microenvironments for the treatment of lung cancer

Yao,

Liang,

Liu

et al. 2024

Front. Immunol.

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Lung cancer (LC) produces some of the most malignant tumors in the world, with high morbidity and mortality. Tumor immune microenvironment (TIME), a component of the tumor microenvironment (TME), are critical in tumor development, immune escape, and drug resistance. The TIME is composed of various immune cells, immune cytokines, etc, which are important biological characteristics and determinants of tumor progression and outcomes. In this paper, we reviewed the recently published literature and discussed the potential uses of natural products in regulating TIME. We observed that a total of 37 natural compounds have been reported to exert anti-cancer effects by targeting the TIME. In different classes of natural products, terpenoids are the most frequently mentioned compounds. TAMs are one of the most investigated immune cells about therapies with natural products in TIME, with 9 natural products acting through it. 17 natural products exhibit anti-cancer properties in LC by modulating PD-1 and PD-L1 protein activity. These natural products have been extensively evaluated in animal and cellular LC models, but their clinical trials in LC patients are lacking. Based on the current review, we have revealed that the mechanisms of LC can be treated with natural products through TIME intervention, resulting in a new perspective and potential therapeutic drugs.

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Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma

Mao,

Wang,

Chao

et al. 2024

Cell Oncol.

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Integrative analyses of bulk and single-cell RNA-seq identified cancer-associated fibroblasts-related signature as a prognostic factor for immunotherapy in NSCLC

Cited by 7 publications

References 54 publications

Cancer-associated fibroblasts refine the classifications of gastric cancer with distinct prognosis and tumor microenvironment characteristics

Cancer-associated fibroblasts refine the classifications of gastric cancer with distinct prognosis and tumor microenvironment characteristics

A review of natural products targeting tumor immune microenvironments for the treatment of lung cancer

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma

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