Breast Heterogeneity: Obstacles to Developing Universal Biomarkers of Breast Cancer Initiation and Progression.

BACKGROUND

Predicting outcomes and response to therapy through biomarkers is a major challenge in cancer research. In previous studies, we suggested that inappropriate "normal" tissue samples used for comparison with tumors, inter-individual heterogeneity in gene expression, and genetic ancestry all influence biomarker expression in tumors. The aim of this study was to investigate these factors in breast cancer using breast tissues from healthy women and normal tissue adjacent to tumor (NAT) with matrix metalloproteinase 7 (MMP7) as a candidate biomarker.

STUDY

DESIGN

RNA sequencing was performed on primary luminal progenitor cells from healthy breast, NATs, and tumors to identify transcriptomes enriched in NATs and breast cancer. Expression of select genes was validated via quantitative reverse transcription polymerase chain reaction of RNA and via immunohistochemistry of a tissue microarray of normal, NAT, and tumor samples of different genetic ancestry.

RESULTS

Twenty-six genes were significantly overexpressed in NATs and tumors compared with healthy controls at messenger RNA level and formed a para-inflammatory network. MMP7 had the greatest expression in tumor cells, with upregulation confirmed by quantitative reverse transcription polymerase chain reaction. Tumor-enriched but not NAT-enriched expression of MMP7 compared with healthy controls was reproduced at protein levels. When stratified by genetic ancestry, tumor-specific increase of MMP7 reached statistical significance in women of European ancestry.

CONCLUSIONS

Transcriptome differences across healthy, NAT, and tumor tissue in breast cancer demonstrate an active para-inflammatory network in NATs and indicate unsuitability of NATs as "normal controls" in biomarker discovery. The discordance between transcriptomic and proteomic MMP7 expression in NATs and the influence of genetic ancestry on its protein expression highlight the complexity in developing universally acceptable biomarkers of breast cancer and the importance of genetic ancestry in biomarker development.