Distinct Mutation Signatures in Peripheral Blood Mitochondrial DNA from Liquid Biopsy Reveal Insights into Pancreatic Cancer

TL;DR

Blood mitochondrial DNA shows unique mutation patterns in pancreatic cancer patients, offering potential for non-invasive diagnosis and monitoring.

Contribution

Blood-derived mtDNA reveals systemic mitochondrial changes in pancreatic cancer, beyond tumor-specific mutations.

Findings

PC patients showed distinct mtDNA mutation distributions and allele frequency patterns despite similar overall mutational burden.

Increased mtDNA copy number variability in PC patients was linked to differences in survival outcomes.

Mutation hotspots in ND5, COI, and D-loop regions suggest roles in oxidative phosphorylation and mtDNA maintenance.

Abstract

What are the main findings?
Whole-blood mtDNA profiling revealed pancreatic cancer-associated differences in mutation allele frequency (AF), regional distribution, and heteroplasmy, despite similar overall mtDNA mutational burden between patients and healthy controls.Increased variability in mtDNA copy number and specific mtDNA features (high-AF variants, unique SNV patterns) were associated with differences in overall survival, possibly reflecting systemic mitochondrial stress rather than tumor-intrinsic mutations alone.

Whole-blood mtDNA profiling revealed pancreatic cancer-associated differences in mutation allele frequency (AF), regional distribution, and heteroplasmy, despite similar overall mtDNA mutational burden between patients and healthy controls.

Increased variability in mtDNA copy number and specific mtDNA features (high-AF variants, unique SNV patterns) were associated with differences in overall survival, possibly reflecting systemic mitochondrial stress rather than tumor-intrinsic mutations alone.

What are the implications of the main findings?
Blood-derived mtDNA captures a systemic mitochondrial signal shaped by tumor presence, immune responses, and oxidative stress, providing complementary biological insight beyond tissue-based analyses.Integrated mtDNA features may support the development of minimally invasive models for risk assessment, patient stratification, and disease monitoring in pancreatic cancer, even in the absence of a single definitive biomarker.

Blood-derived mtDNA captures a systemic mitochondrial signal shaped by tumor presence, immune responses, and oxidative stress, providing complementary biological insight beyond tissue-based analyses.

Integrated mtDNA features may support the development of minimally invasive models for risk assessment, patient stratification, and disease monitoring in pancreatic cancer, even in the absence of a single definitive biomarker.

Pancreatic cancer (PC) is a highly aggressive malignancy characterized by limited opportunities for early diagnosis and poor clinical outcomes, underscoring the need for minimally invasive biomarkers to improve detection and patient stratification. Given emerging evidence that mitochondrial DNA (mtDNA) alterations reflect cancer-related biological processes, this study investigated whether blood-derived mtDNA profiles could provide clinically relevant information in PC. In this exploratory study, whole-blood mtDNA from 33 PC patients and 10 healthy individuals were analyzed using next-generation sequencing to assess single-nucleotide variants (SNVs), allele frequencies, and mtDNA copy number. A total of 252 unique mtDNA SNVs were identified, including variants exclusive to PC patients, variants unique to controls, and variants shared between groups. While the overall SNV burden did not differ significantly between groups, PC patients showed distinct mutation distributions and allele frequency patterns, with cancer-exclusive variants occurring predominantly at low allele frequencies. Mutation hotspots were observed in the ND5, COI, and D-loop regions, implicating genes involved in oxidative phosphorylation and mtDNA maintenance. Although mtDNA copy number did not differ significantly between groups, greater variability was observed among PC patients and was associated with differences in survival outcomes. Overall, these findings indicate that blood-based mtDNA profiling captures biologically relevant variation associated with PC and supports further development of integrated mtDNA-based approaches for improved risk assessment and patient stratification.

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