Summary A number of mitochondrial diseases arise from Single Nucleotide Variant (SNV) accumulation in multiple mitochondria. Here we present a method for identification of variants present at the single mitochondrion level in individual mouse and human neuronal cells allowing for extremely high resolution study of mitochondrial mutation dynamics. We identified extensive heteroplasmy between individual mitochondrion, along with three high confidence variants in mouse and one in human that were present in multiple mitochondria across cells. The pattern of variation revealed by single mitochondrion data shows surprisingly pervasive levels of heteroplasmy in inbred mice. Distribution of SNV loci suggests inheritance of variants across generations resulting in Poisson jackpot lines with large SNV load. Comparison of human and mouse variants suggests that the two species might employ distinct modes of somatic segregation. Single mitochondrion resolution revealed mitochondria mutational dynamics that we hypothesize to affect risk probabilities for mutations reaching disease thresholds.

Motivation Predicting the binding between T-cell receptor (TCR) and peptide presented by HLA molecule is a highly challenging task and a key bottleneck in the development of immunotherapy. Existing prediction tools, despite exhibiting good performance on the datasets they were built with, suffer from low true positive rates when used to predict epitopes capable of eliciting T-cell responses in patients. Therefore, an improved tool for TCR-peptide prediction built upon a large dataset combining existing publicly available data is still needed. Results We collected data from five public databases (IEDB, TBAdb, VDJdb, McPAS-TCR, and 10X) to form a dataset of > 3 million TCR-peptide pairs, 3.27% of which were binding interactions. We proposed epiTCR, a Random Forest-based method dedicated to predicting the TCR-peptide interactions. epiTCR used simple input of TCR CDR3β sequences and antigen sequences, which are encoded by flattened BLOSUM62. epiTCR performed with AUC (0.98) and higher sensitivity (0.94) than other existing tools (NetTCR, Imrex, ATM-TCR, and pMTnet), while maintaining comparable prediction specificity (0.9). We identified seven epitopes that contributed to 98.67% of false positives predicted by epiTCR and exerted similar effects on other tools. We also demonstrated a considerable influence of peptide sequences on prediction, highlighting the need for more diverse peptides in a more balanced dataset. In conclusion, epiTCR is among the most well-performing tools thanks to the use of combined data from public sources and its use will contribute to the quest in identifying neoantigens for precision cancer immunotherapy. Availability epiTCR is available on GitHub (https://github.com/ddiem-ri-4D/epiTCR). Supplementary information Supplementary data are available at Bioinformatics online.

Targeted therapy with tyrosine kinase inhibitors (TKI) provides survival benefits to a majority of patients with non-small cell lung cancer (NSCLC). However, resistance to TKI almost always develops after treatment. Although genetic and epigenetic alterations have each been shown to drive resistance to TKI in cell line models, clinical evidence for their contribution in the acquisition of resistance remains limited. Here, we employed liquid biopsy for simultaneous analysis of genetic and epigenetic changes in 122 Vietnamese NSCLC patients undergoing TKI therapy and displaying acquired resistance. We detected multiple profiles of resistance mutations in 51 patients (41.8%). Of those, genetic alterations in EGFR, particularly EGFR amplification (n = 6), showed pronounced genome instability and genome-wide hypomethylation. Interestingly, the level of hypomethylation was associated with the duration of response to TKI treatment. We also detected hypermethylation in regulatory regions of Homeobox genes which are known to be involved in tumor differentiation. In contrast, such changes were not observed in cases with MET (n = 4) and HER2 (n = 4) amplification. Thus, our study showed that liquid biopsy could provide important insights into the heterogeneity of TKI resistance mechanisms in NSCLC patients, providing essential information for prediction of resistance and selection of subsequent treatment.

Comprehensive profiling of actionable mutations in non-small cell lung cancer (NSCLC) is vital to guide targeted therapy, thereby improving the survival rate of patients. Despite the high incidence and mortality rate of NSCLC in Vietnam, the actionable mutation profiles of Vietnamese patients have not been thoroughly examined. Here, we employed massively parallel sequencing to identify alterations in major driver genes (EGFR, KRAS, NRAS, BRAF, ALK and ROS1) in 350 Vietnamese NSCLC patients. We showed that the Vietnamese NSCLC patients exhibited mutations most frequently in EGFR (35.4%) and KRAS (22.6%), followed by ALK (6.6%), ROS1 (3.1%), BRAF (2.3%) and NRAS (0.6%). Interestingly, the cohort of Vietnamese patients with advanced adenocarcinoma had higher prevalence of EGFR mutations than the Caucasian MSK-IMPACT cohort. Compared to the East Asian cohort, it had lower EGFR but higher KRAS mutation prevalence. We found that KRAS mutations were more commonly detected in male patients while EGFR mutations was more frequently found in female. Moreover, younger patients (<61 years) had higher genetic rearrangements in ALK or ROS1. In conclusions, our study revealed mutation profiles of 6 driver genes in the largest cohort of NSCLC patients in Vietnam to date, highlighting significant differences in mutation prevalence to other cohorts. Lung cancer is the most common malignancy and the leading cause of cancer related deaths worldwide (18.4% of total cancer deaths), with non-small cell lung cancer (NSCLC) being the most common subtype, accounting for approximately 85% of all diagnosed cases 1,2. The majority of NSCLC patients display advanced disease when diagnosed and thus have poor prognosis 2,3. It is well established that acquired genetic alterations in certain driver genes result in tumour growth and invasiveness, and that patients harboring certain mutations may benefit from targeted therapies 4,5. Indeed, a randomized clinical trial reported that advanced NSCLC patients harboring activating mutations in EGFR, one of the major driver genes of NSCLC, exhibited longer progression-free period when treated with a tyrosine kinase inhibitor (TKI), gefitinib, compared to those treated with standard platinum based chemotherapy 6. However, those who were treated with TKI drugs can acquire secondary resistant mutations, in which case a new treatment regimen is needed to maintain therapeutic effect 7,8. In addition to EGFR, NSCLC patients carrying ALK or ROS1 rearrangement were shown to respond well to a different TKI drug,

No abstract