Profiling mitochondrial DNA mutations in tumors and circulating extracellular vesicles of triple-negative breast cancer patients for potential biomarker development

分析三阴性乳腺癌患者肿瘤和循环细胞外囊泡中的线粒体 DNA 突变,以开发潜在的生物标志物

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作者:Kunwar Somesh Vikramdeo, Shashi Anand, Sarabjeet Kour Sudan, Paramahansa Pramanik, Seema Singh, Andrew K Godwin, Ajay Pratap Singh, Santanu Dasgupta

Abstract

Early detection and recurrence prediction are challenging in triple-negative breast cancer (TNBC) patients. We aimed to develop mitochondrial DNA (mtDNA)-based liquid biomarkers to improve TNBC management. Mitochondrial genome (MG) enrichment and next-generation sequencing mapped the entire MG in 73 samples (64 tissues and 9 extracellular vesicles [EV] samples) from 32 metastatic TNBCs. We measured mtDNA and cardiolipin (CL) contents, NDUFB8, and SDHB protein expression in tumors and in corresponding circulating EVs. We identified 168 nonsynonymous mtDNA mutations, with 73% (123/186) coding and 27% (45/168) noncoding in nature. Twenty percent of mutations were nucleotide transversions. Respiratory complex I (RCI) was the key target, which harbored 44% (74/168) of the overall mtDNA mutations. A panel of 11 hotspot mtDNA mutations was identified among 19%-38% TNBCs, which were detectable in the serum-derived EVs with 82% specificity. Overall, 38% of the metastatic tumor-signature mtDNA mutations were traceable in the EVs. An appreciable number of mtDNA mutations were homoplasmic (18%, 31/168), novel (14%, 23/168), and potentially pathogenic (9%, 15/168). The overall and RCI-specific mtDNA mutational load was higher in women with African compared to European ancestry accompanied by an exclusive abundance of respiratory complex (RC) protein NDUFB8 (RCI) and SDHB (RCII) therein. Increased mtDNA (p < 0.0001) content was recorded in both tumors and EVs along with an abundance of CL (p = 0.0001) content in the EVs. Aggressive tumor-signature mtDNA mutation detection and measurement of mtDNA and CL contents in the EVs bear the potential to formulate noninvasive early detection and recurrence prediction strategies.

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