Development of a Cancer-Associated Fibroblast-Related Prognostic Model in Breast Cancer via Bulk and Single-Cell RNA Sequencing

Hu, Jing; Jiang, Yuming; Wei, Qihao; Li, Bin; Xu, Sha; Guang, Wang; Пин, Ли; Chen, Wei; Lv, Wenzhi; Xiao, Xianjin; Lü, Yaping; Huang, Xuan

doi:10.1155/2022/2955359

Cited by 5 publications

(2 citation statements)

References 49 publications

(48 reference statements)

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“…Cancer-associated broblasts (CAFs), the predominant cell type within the stroma, orchestrate interaction with cancer cells and express a variety of prognostic markers (3). CAFs-related prognostic models have been described for colorectal cancer (4), breast cancer (5) and clear cell renal cell carcinoma (6). These ndings suggest that CAFs may play a signi cant role in cancer prognosis and represent a prospective cancer therapeutic target.…”

Section: Introductionmentioning

confidence: 99%

A Novel Cancer-associated Fibroblasts-Related Gene Signature Based on Adjuvant Sorafenib Efficacy for Predicting Recurrence and Immunotherapy Response in Hepatocellular Carcinoma After Hepatectomy

Liang

Feng

et al. 2023

Preprint

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Background Due to its high recurrence rate, hepatocellular carcinoma (HCC) has a poor prognosis after hepatectomy. An effective model to predict postoperative recurrence and identify high-risk patients is essential. Recent studies have revealed the important role of cancer-associated fibroblasts (CAFs) in predicting HCC prognosis. However, the prognostic value of CAFs-related gene signature in HCC recurrence remains unknown. According to the BIOSTORM study, adjuvant sorafenib efficacy data may help to predict the recurrence in HCC. Therefore, we aimed to create a novel CAFs-related gene signature based on adjuvant sorafenib efficacy to predict HCC recurrence. Methods The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to obtain the transcriptomic gene expression profiles and corresponding clinical data of HCC patients. The CAFs-related genes based on adjuvant sorafenib efficacy were identified using EPIC and weighted gene co-expression network analysis (WGCNA) algorithm. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to establish a novel risk model. Univariate and multivariate COX analyses were used to identify independent prognostic factors for disease-free survival (DFS), and a nomogram was developed. The CIBERSORT and ESTIMATE algorithms were used to assess the tumor microenvironment components. Tumor immune dysfunction and exclusion (TIDE) score was used to predict immunotherapy response. Results A novel risk model was created using ten CAFs-related genes based on adjuvant sorafenib efficacy (DCLRE1C, DDX11, MAP4K2, SHCBP1, ADAM12, PAQR4, BEND3, ADAMTSL2, NUP93 and MPP2). Survival analyses revealed that high-risk patients had worse DFS, and the risk model was found as an independent prognostic factor for DFS in both the training and validation groups. A novel nomogram combined with pathologic stage and risk score status was developed. In the high-risk group, the stromal and immune cell content was found significantly lower while the tumor purity was significantly higher. In addition, immune checkpoints genes were highly expressed in the high-risk group and a higher risk score may predict a better response to immunotherapy. Conclusions The novel risk model comprised of ten CAFs-related genes based on adjuvant sorafenib efficacy may accurately predict recurrence and immunotherapy response in HCC patients after hepatectomy.

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Section: Introductionmentioning

confidence: 99%

A Novel Cancer-associated Fibroblasts-Related Gene Signature Based on Adjuvant Sorafenib Efficacy for Predicting Recurrence and Immunotherapy Response in Hepatocellular Carcinoma After Hepatectomy

Liang

Feng

et al. 2023

Preprint

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“…Screening, mammography, clinical breast exams, and breast self-examinations have reduced BC mortality in many affluent countries [5]. BC prevention and early diagnosis reduce the risk of metastases and cancer.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Changing Levels of Immune Checkpoint Proteins in The Serum of Breast Cancer Patients

Alrahimi¹,

Yousuf²,

Pushparaj³

et al. 2022

Pharmacophore

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Breast cancer is the most frequent kind of invasive cancer in women. Biomarker monitoring and prognosis provide outstanding clinical information that may be employed to battle various cancers. This study aimed to examine a variety of biomarkers utilizing a multiplex bead array. BTLA, CD27, CD28, TIM-3, HVEM, CD40, LAG-3, TLR-2, PD-1, CD80, CD86, PDL-1, PDL-2, and ICOS are common biomarker checkpoint proteins found in a selective panel. This panel examined a research group of 59 patients with BC and 17 healthy people. The expression patterns of a handful of the fourteen biomarkers varied considerably between people with BC and healthy controls. With Pvalues of (p= 0.05), (p= 0.02), (p= 0.01), and (p= 0.02), general features of the two groups of malignant and non-malignant patients revealed significant correlations in parameters such as the age of first menstruation, pregnancy, menopausal status, and hormone replacement treatment. With P-values, there was a substantial rise in BTLA, HVEM, TLR-2, and PDL-1 serum levels, as well as a significant drop in CD86. Furthermore, these markers indicated a significant relationship with the clinic-pathological aspects of the patients. With a P-value of 0.0002, both BTLA and HVME showed a statistically significant connection with hormone receptor phenotypes. For ER status, BTLA, CD86, and PDL1 had equivalent significance values of (p= 0.0148), (p= 0.0166), and (p= 0.0001). BTLA was related to lymph node involvement (p=0.0397), whereas TLR2 was associated with HER2 status (p=0.0332). BTLA, HVEM, TLR-2 CD86, and PDL-1 may be valuable biomarkers for cancer monitoring and prognosis.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, tweak, and build upon the work non commercially, as long as the author is credited and the new creations are licensed under the identical terms.

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Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

Zheng,

2023

Mol Biotechnol

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Development of a Cancer-Associated Fibroblast-Related Prognostic Model in Breast Cancer via Bulk and Single-Cell RNA Sequencing

Cited by 5 publications

References 49 publications

A Novel Cancer-associated Fibroblasts-Related Gene Signature Based on Adjuvant Sorafenib Efficacy for Predicting Recurrence and Immunotherapy Response in Hepatocellular Carcinoma After Hepatectomy

A Novel Cancer-associated Fibroblasts-Related Gene Signature Based on Adjuvant Sorafenib Efficacy for Predicting Recurrence and Immunotherapy Response in Hepatocellular Carcinoma After Hepatectomy

Investigating the Changing Levels of Immune Checkpoint Proteins in The Serum of Breast Cancer Patients

Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

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