Quantification of spatial pharmacogene expression heterogeneity in breast tumors

• Published in: Cancer reports Vol. 6; no. 1; pp. e1686 - n/a
• Main Authors: Powell, Nicholas R., Silvola, Rebecca M., Howard, John S., Badve, Sunil, Skaar, Todd C., Ipe, Joseph
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.01.2023; John Wiley and Sons Inc; Wiley
• Subjects: Bar codes; Biobanks; Breast - pathology; Breast - surgery; Breast Neoplasms - drug therapy; Breast Neoplasms - genetics; Breast Neoplasms - pathology; Cancer; Chemotherapy; Data analysis; Enzymes; Female; Gene expression; Gene Expression Profiling; Genomics; Humans; Medical prognosis; Metabolism; Optimization; Original; pharmacogene; resistance; spatial; Transcriptome; transcriptomics; Tumors; Indiana; United States > US; transcriptomics; pharmacogene; spatial; chemotherapy; resistance
• ISSN: 2573-8348; 2573-8348
• DOI: 10.1002/cnr2.1686

Background Chemotherapeutic drug concentrations vary across different regions of tumors and this is thought to be involved in development of chemotherapy resistance. Insufficient drug delivery to some regions of the tumor may be due to spatial differences in expression of genes involved in the disposition, transport, and detoxification of drugs (pharmacogenes). Therefore, in this study, we analyzed the spatial expression of 286 pharmacogenes in six breast cancer tissues using the recently developed Visium spatial transcriptomics platform to (1) determine if these pharmacogenes are expressed heterogeneously across tumor tissue and (2) to determine which pharmacogenes have the most spatial expression heterogeneity. Methods and Results The spatial transcriptomics technology sequences the transcriptome of 55 um diameter barcoded sections (spots) across a tissue sample. We analyzed spatial gene expression profiles of four biobank‐sourced breast tumor samples in addition to two breast tumor sample datasets from 10× Genomics. We define heterogeneity as the interquartile range of read counts. Collectively, we identified 8887 spots in tumor regions, 3814 in stroma, 44 in lymphocytes, and 116 in normal regions based on pathologist annotation of the tissues. We showed statistically significant differences in expression of pharmacogenes in tumor regions compared to surrounding non‐tumor regions. We also observed that the most heterogeneously expressed genes within tumor regions were involved in reactive oxygen species (ROS) handling and detoxification mechanisms. GPX4, GSTP1, MGST3, SOD1, CYP4Z1, CYB5R3, GSTK1, and NAT1 showed the most heterogeneous expression within tumor regions. Conclusions The heterogeneous expression of these pharmacogenes may have important implications for cancer therapy due to their ability to impact drug distribution and efficacy throughout the tumor. Our results suggest that chemoresistance caused by expression of GPX4, GSTP1, MGST3, and SOD1 may be intrinsic, not acquired, since the heterogeneity is not specific to chemotherapy‐treated samples or cell type. Additionally, we identified candidate chemoresistance pharmacogenes that can be further tested through focused follow‐up studies.