Role of mitochondria in early molecular diagnosis and prognosis of cancer

Sammanfattning: Background:Earlier clinical detection of cancer may improve survival as well as offer opportunities for less invasive treatment options. This thesis explores whether the mitochondria and its related genes in the nuclear genome can be used as novel methods for the diagnosis and prognosis of cancers.Aims and Methods:Paper I: To investigate if mitochondrial dysfunction (characterized by mtDNA copy number variations) is associated with prevalent, incident cancer and cancer mortality – droplet digital PCR (ddPCR).Paper II: To investigate the potential causal relationship between mitochondrial dysfunction (characterized by genetic predispositions in all mitochondrial-related genes) and common cancer risks – Mendelian randomization, colocalization.Paper III: To investigate mitochondrial mutations as potential biomarkers for the early diagnosis of breast cancer – whole mitochondrial genome sequencing, bioinformatics, ddPCR.Paper IV: To investigate the mitochondrial-related gene expression signature as a prognostic model to predict the clinical outcome for breast cancer patients – machine learning.Results and conclusions:Paper I: We found that mtDNA-CN was significantly associated with prevalent and incident cancer as well as cancer mortality. However, these associations were cancer-type specific and need further investigation.Paper II: We identified potential causal relationships between mitochondrial-related genes and breast, prostate and lung cancer. Furthermore, this study identified candidate genes that can be the targets of potential pharmacological agents for cancer prevention.Paper III: We comprehensively characterized the mtDNA mutation landscape of breast cancer biopsies and matched baseline whole blood samples. Notably, we have identified and validated mt.16093T>C mutation, which was associated with a 67% increased risk of developing breast cancer, and could potentially be used as early breast cancer diagnostic biomarkers.Paper IV: We built a novel 14 genes mitochondrial signature model that could be an independent prognostic predictor and together with clinical variables as an improved model for predicting overall earlystage of breast cancer survival.