Gene set analysis of post-lactational mammary gland involution gene signatures in inflammatory and triple-negative breast cancer

Abstract

BackgroundEpidemiological studies have found that triple-negative breast cancer (TNBC) and TN inflammatory breast cancer (IBC) are associated with lower frequency and duration of breast-feeding compared to non-TNBC and non-TN IBC, respectively. Limited breast-feeding could reflect abrupt or premature involution and contribute to a “primed” stroma that is permissive to the migration of cancer cells typical of IBC. We hypothesized that gene expression related to abrupt mammary gland involution after forced weaning may be enriched in the tissues of IBC patients and, if so, provide a potential correlation between limited breast-feeding and the development of aggressive breast cancer.MethodsWe utilized the Short Time-series Expression Miner (STEM) program to cluster significant signatures from two independent studies that analyzed gene expression at multiple time-points of mouse mammary gland involution. Using 10 significant signatures, we performed gene ontology analysis and gene set enrichment analysis (GSEA) on training and validation sets from human breast cancer gene expression data to identify specific genes that are enriched in IBC compared to non-IBC and in TN compared to non-TN in IBC and non-IBC groups.ResultsExamining the combined data, we identified 10 involution gene clusters (Inv1-10) that share time-dependent regulation after forced weaning. Inv5 was the only cluster significantly enriched in IBC in the training and validation set (nominal p-values <0.05) and only by unadjusted p-values (FDR q-values 0.26 and 0.46 respectively). Eight genes in Inv5 are upregulated in both the training and validation sets in IBC. Combining the training and validation sets, both Inv5 and Inv6 have nominal p-values <0.05 and q-values 0.39 and 0.20, respectively. The time course for both clusters includes genes that change within 12 hours after forced weaning.ConclusionsResults from this in silico study suggest correlation between molecular events during abrupt involution and aggressive breast cancer. Specifically, candidate genes from Inv5 merit functional investigation regarding the role of limited breast-feeding in IBC development.

Reproductive Risk Factors of Inflammatory Breast Cancer according to Luminal, HER2-Overexpressing, and Triple-Negative Subtypes: A Case Comparison Study

“…In that study the control group were cancer-free women, in our study the control group were non-IBC patients, and there was no role of long duration of breastfeeding in the TN group. Previous studies have found that TN breast cancer and TN IBC are associated with lower frequency and duration of breastfeeding compared to non-TN breast cancer and non-TN IBC, respectively [10]. Reproductive risk factors and TN breast cancer have also been observed in other studies [11,12].…”

Predictors of mammographic microcalcifications

“…Pregnancy associated histological changes in the mammary tissue are induced by steroid hormones and growth factors 12 . When this influence diminishes, epithelial cells undergo a massive programmed cell death and tissue remodeling, so called post‐lactational involution 47 . It is hypothesized that post‐lactational involution increases the number of microcalcification clusters.…”

Semaphorin 7A Promotes Macrophage-Mediated Lymphatic Remodeling during Postpartum Mammary Gland Involution and in Breast Cancer

“…Based on our data presented herein showing that SEMA7A is increased during involution, we are investigating whether SEMA7A is a primary driver of postpartum breast cancer aggressiveness in our University of Colorado Young Women’s cohort (46). Interestingly, a recent in silico analysis revealed two involution gene signatures that were significantly upregulated in inflammatory breast cancer (IBC)(47). IBC is a highly aggressive type of breast cancer that is characterized by tumor emboli in dermal lymphatics, which is reminiscent of what we have observed in mammary lymphatics of our postpartum patients(10)(Figure 6E).…”