Yangguang Xu1, Zhen Zhang2, Luoyan Zhang3, Chi Zhang4. 1. Department of Pediatrics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China. 2. Institute of Basic Medicine, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China. 3. Key Lab of Plant Stress Research, College of Life Science, Shandong Normal University, Jinan, 250014, Shandong, China. 4. Department of Breast and Thyroid Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China. zhangchi549@bjmu.edu.cn.
Abstract
BACKGROUND: As abundant and heterogeneous stromal cells in tumor microenvironment, carcinoma-associated fibroblasts (CAFs) are critically involved in cancer progression. METHODS: To identify co-expression module and hub genes of distinctive breast CAFs, weighted gene co-expression network analysis (WGCNA) was conducted based on the expression array results of CAFs from seven chemo-sensitive breast cancer (BC) patients and seven chemo-resistant ones before neo-adjuvant chemotherapy. RESULTS: A total of 4916 genes were included in WGCNA, and 12 modules were determined. Module-trait assay showed that the blue module (cor = 0.97, P < 0.001) was associated with CAF-related chemo-resistance, which was enriched mainly as "inflammatory response", "interferon-gamma-mediated signaling" and "NIK/NF-kappaB signaling" pathways. Moreover, CXCL8, CXCL10, CXCL11, PLSCR1, RIPK2 and USP18 were found to be potentially associated with chemo-resistance related to CAFs and prognosis of BC. CONCLUSIONS: Our current data offered valuable insights into the molecular mechanisms of distinctive breast CAFs, which was beneficial for revealing how chemo-resistance of BC was initiated.
BACKGROUND: As abundant and heterogeneous stromal cells in tumor microenvironment, carcinoma-associated fibroblasts (CAFs) are critically involved in cancer progression. METHODS: To identify co-expression module and hub genes of distinctive breast CAFs, weighted gene co-expression network analysis (WGCNA) was conducted based on the expression array results of CAFs from seven chemo-sensitive breast cancer (BC) patients and seven chemo-resistant ones before neo-adjuvant chemotherapy. RESULTS: A total of 4916 genes were included in WGCNA, and 12 modules were determined. Module-trait assay showed that the blue module (cor = 0.97, P < 0.001) was associated with CAF-related chemo-resistance, which was enriched mainly as "inflammatory response", "interferon-gamma-mediated signaling" and "NIK/NF-kappaB signaling" pathways. Moreover, CXCL8, CXCL10, CXCL11, PLSCR1, RIPK2 and USP18 were found to be potentially associated with chemo-resistance related to CAFs and prognosis of BC. CONCLUSIONS: Our current data offered valuable insights into the molecular mechanisms of distinctive breast CAFs, which was beneficial for revealing how chemo-resistance of BC was initiated.
Entities:
Keywords:
Breast cancer; Chemo-resistance; Gene expression; Inflammation