Abstract
Mammography is an important screening modality for the early detection of DCIS and breast cancer lesions. More specifically, high mammographic density is associated with an increased risk of breast cancer. However, the biological processes underlying this phenomenon remain largely unknown. Here, we re-interrogated genome-wide transcriptional profiling data obtained from low-density (LD) mammary fibroblasts (n = 6 patients) and high-density (HD) mammary fibroblasts (n = 7 patients) derived from a series of 13 female patients. We used these raw data to generate a “breast density” gene signature consisting of >1250 transcripts that were significantly increased in HD fibroblasts, relative to LD fibroblasts. We then focused on the genes that were increased by ≥ 1.5-fold (P < 0.05) and performed gene set enrichment analysis (GSEA), using the molecular signatures database (MSigDB). Our results indicate that HD fibroblasts show the upregulation and/or hyper-activation of several key cellular processes, including the stress response, inflammation, stemness, and signal transduction. The transcriptional profiles of HD fibroblasts also showed striking similarities to human tumors, including head and neck, liver, thyroid, lung, and breast cancers. This may reflect functional similarities between cancer-associated fibroblasts (CAFs) and HD fibroblasts. This is consistent with the idea that the presence of HD fibroblasts may be a hallmark of a pre-cancerous phenotype. In these biological processes, GSEA predicts that several key signaling pathways may be involved, including JNK1, iNOS, Rho GTPase(s), FGF-R, EGF-R, and PDGF-R-mediated signal transduction, thereby creating a pro-inflammatory, pro-proliferative, cytokine, and chemokine-rich microenvironment. HD fibroblasts also showed significant overlap with gene profiles derived from smooth muscle cells under stress (JNK1) and activated/infected macrophages (iNOS). Thus, HD fibroblasts may behave like activated myofibroblasts and macrophages, to create and maintain a fibrotic and inflammatory microenvironment. Finally, comparisons between the HD fibroblast gene signature and breast cancer tumor stroma revealed that JNK1 stress signaling is the single most significant biological process that is shared between these 2 data sets (with P values between 5.40E-09 and 1.02E-14), and is specifically associated with tumor recurrence. These results implicate “stromal JNK1 signaling” in the pathogenesis of human breast cancers and the transition to malignancy. Augmented TGF-β signaling also emerged as a common feature linking high breast density with tumor stroma and breast cancer recurrence (P = 5.23E-05). Similarities between the HD fibroblast gene signature, wound healing, and the cancer-associated fibroblast phenotype were also noted. Thus, this unbiased informatics analysis of high breast density provides a novel framework for additional experimental exploration and new hypothesis-driven breast cancer research, with a focus on cancer prevention and personalized medicine.
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