Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.

BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. METHODS: We constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. RESULTS: Our final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. CONCLUSIONS: In conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples.

Analytical validation and clinical utilization of K-4CARE™: a comprehensive genomic profiling assay with personalized MRD detection.

Background: Biomarker testing has gradually become standard of care in precision oncology to help physicians select optimal treatment for patients. Compared to single-gene or small gene panel testing, comprehensive genomic profiling (CGP) has emerged as a more time- and tissue-efficient method. This study demonstrated in-depth analytical validation of K-4CARE, a CGP assay that integrates circulating tumor DNA (ctDNA) tracking for residual cancer surveillance. Methods: The assay utilized a panel of 473 cancer-relevant genes with a total length of 1.7 Mb. Reference standards were used to evaluate limit of detection (LOD), concordance, sensitivity, specificity and precision of the assay to detect single nucleotide variants (SNVs), small insertion/deletions (Indels), gene amplification and fusion, microsatellite instability (MSI) and tumor mutational burden (TMB). The assay was then benchmarked against orthogonal methods using 155 clinical samples from 10 cancer types. In selected cancers, top tumor-derived somatic mutations, as ranked by our proprietary algorithm, were used to detect ctDNA in the plasma. Results: For detection of somatic SNVs and Indels, gene fusion and amplification, the assay had sensitivity of >99%, 94% and >99% respectively, and specificity of >99%. Detection of germline variants also achieved sensitivity and specificity of >99%. For TMB measurement, the correlation coefficient between whole-exome sequencing and our targeted panel was 97%. MSI analysis when benchmarked against polymerase chain reaction method showed sensitivity of 94% and specificity of >99%. The concordance between our assay and the TruSight Oncology 500 assay for detection of somatic variants, TMB and MSI measurement was 100%, 89%, and 98% respectively. When CGP-informed mutations were used to personalize ctDNA tracking, the detection rate of ctDNA in liquid biopsy was 79%, and clinical utility in cancer surveillance was demonstrated in 2 case studies. Conclusion: K-4CARE™ assay provides comprehensive and reliable genomic information that fulfills all guideline-based biomarker testing for both targeted therapy and immunotherapy. Integration of ctDNA tracking helps clinicians to further monitor treatment response and ultimately provide well-rounded care to cancer patients.

De novo variants of dominant monogenic disorders in Vietnam detected by a noninvasive prenatal test: a case series.

Background: Noninvasive prenatal tests for monogenic diseases (NIPT-SGG) have recently been reported as helpful in early-stage antenatal screening. Our study describes the clinical and genetic features of cases identified by NIPT-SGG. Materials & methods: In a cohort pregnancy with abnormal sonograms, affected cases were confirmed by invasive diagnostic tests concurrently, with NIPT-SGG targeting 25 common dominant single-gene diseases. Results: A total of 13 single-gene fetuses were confirmed, including Noonan and Costello syndromes, thanatophoric dysplasia, achondroplasia, osteogenesis imperfecta and Apert syndrome. Two novel variants seen were tuberous sclerosis complex (TSC2 c.4154G>A) and Alagille syndrome (JAG1 c.3452del). Conclusion: NIPT-SGG and standard tests agree on the results for 13 fetuses with monogenic disorders. This panel method of screening can benefit high-risk Vietnamese pregnancies, but further research is encouraged to expand on the causative gene panel.

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling.

Introduction: Neoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow. Methods: In this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP). Results: We detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data. Discussion: This integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

Multimodal analysis of genome-wide methylation, copy number aberrations, and end motif signatures enhances detection of early-stage breast cancer.

Introduction: Breast cancer causes the most cancer-related death in women and is the costliest cancer in the US regarding medical service and prescription drug expenses. Breast cancer screening is recommended by health authorities in the US, but current screening efforts are often compromised by high false positive rates. Liquid biopsy based on circulating tumor DNA (ctDNA) has emerged as a potential approach to screen for cancer. However, the detection of breast cancer, particularly in early stages, is challenging due to the low amount of ctDNA and heterogeneity of molecular subtypes. Methods: Here, we employed a multimodal approach, namely Screen for the Presence of Tumor by DNA Methylation and Size (SPOT-MAS), to simultaneously analyze multiple signatures of cell free DNA (cfDNA) in plasma samples of 239 nonmetastatic breast cancer patients and 278 healthy subjects. Results: We identified distinct profiles of genome-wide methylation changes (GWM), copy number alterations (CNA), and 4-nucleotide oligomer (4-mer) end motifs (EM) in cfDNA of breast cancer patients. We further used all three signatures to construct a multi-featured machine learning model and showed that the combination model outperformed base models built from individual features, achieving an AUC of 0.91 (95% CI: 0.87-0.95), a sensitivity of 65% at 96% specificity. Discussion: Our findings showed that a multimodal liquid biopsy assay based on analysis of cfDNA methylation, CNA and EM could enhance the accuracy for the detection of early- stage breast cancer.

Dual-targeting exosomes for improved drug delivery in breast cancer.

Aims: The authors investigated whether displaying more than one homing peptide enhanced the tumor-targeting efficiency of exosomes. Materials & methods: Exosomes from human embryonic kidney cells (HEK293F) were engineered to display either mono- or dual-tumor-penetrating peptides, iRGD and tLyp1. Exosomes were purified via tangential flow filtration followed by ultracentrifugation. Results: When loaded with doxorubicin (Dox), the dual iRGD-tLyp1 exosomes strongly enhanced Dox uptake in both MCF-7 and MDA-MB-231 breast cancer cell lines, superior to single iRGD or tLyp1 exosomes. The dual iRGD-tLyp1 exosomal Dox was also the most potent, with IC50/GI50 values being 3.7-17.0-times lower than those of free Dox and other exosomal Dox. Conclusion: Selecting appropriate combinatorial homing peptides could be an approach for future precision nanomedicine.

epiTCR: a highly sensitive predictor for TCR-peptide binding.

MOTIVATION: Predicting the binding between T-cell receptor (TCR) and peptide presented by human leucocyte antigen 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 CDR3ß sequences and antigen sequences, which are encoded by flattened BLOSUM62. epiTCR performed with area under the curve (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 AND IMPLEMENTATION: epiTCR is available on GitHub (https://github.com/ddiem-ri-4D/epiTCR).

Fragment length profiles of cancer mutations enhance detection of circulating tumor DNA in patients with early-stage hepatocellular carcinoma.

BACKGROUND: Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. METHODS: Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. RESULTS: Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. CONCLUSIONS: Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Genetic landscape and personalized tracking of tumor mutations in Vietnamese women with breast cancer.

Breast cancer is the leading cause of cancer death in Vietnamese women, but its mutational landscape and actionable alterations for targeted therapies remain unknown. After treatment, a sensitive biomarker to complement conventional imaging to monitor patients is also lacking. In this prospective multi-center study, 134 early-stage breast cancer patients eligible for curative-intent surgery were recruited. Genomic DNA from tumor tissues and paired white blood cells were sequenced to profile all tumor-derived mutations in 95 cancer-associated genes. Our bioinformatic algorithm was then utilized to identify top mutations for individual patients. Serial plasma samples were collected before surgery and at scheduled visits after surgery. Personalized assay tracking the selected mutations were performed to detect circulating tumor DNA (ctDNA) in the plasma. We found that the mutational landscape of the Vietnamese was largely similar to other Asian cohorts, showing higher TP53 mutation frequency than in Caucasians. Alterations in PIK3CA and PI3K signaling were dominant, particularly in our triple-negative subgroup. Using top-ranked mutations, we detected ctDNA in pre-operative plasma in 24.6-43.5% of the hormone-receptor-positive groups and 76.9-80.8% of the hormone-receptor-negative groups. The detection rate was associated with breast cancer subtypes and clinicopathological features that increased the risk of relapse. Interim analysis after a 15-month follow-up revealed post-operative detection of ctDNA in all three patients that had recurrence, with a lead time of 7-13 months ahead of clinical diagnosis. Our personalized assay is streamlined and affordable with promising clinical utility in residual cancer surveillance. We also generated the first somatic variant dataset for Vietnamese breast cancer women that could lay the foundation for precision cancer medicine in Vietnam.

Tumor genomic profiling and personalized tracking of circulating tumor DNA in Vietnamese colorectal cancer patients.

Background: Colorectal cancer (CRC) is the fifth most common cancer with rising prevalence in Vietnam. However, there is no data about the mutational landscape and actionable alterations in the Vietnamese patients. During post-operative surveillance, clinical tools are limited to stratify risk of recurrence and detect residual disease. Method: In this prospective multi-center study, 103 CRC patients eligible for curative-intent surgery were recruited. Genomic DNA from tumor tissue and paired white blood cells were sequenced to profile all tumor-derived somatic mutations in 95 cancer-associated genes. Our bioinformatic algorithm identified top mutations unique for individual patient, which were then used to monitor the presence of circulating tumor DNA (ctDNA) in serial plasma samples. Results: The top mutated genes in our cohort were APC, TP53 and KRAS. 41.7% of the patients harbored KRAS and NRAS mutations predictive of resistance to Cetuximab and Panitumumab respectively; 41.7% had mutations targeted by either approved or experimental drugs. Using a personalized subset of top ranked mutations, we detected ctDNA in 90.5% of the pre-operative plasma samples, whereas carcinoembryonic antigen (CEA) was elevated in only 41.3% of them. Interim analysis after 16-month follow-up revealed post-operative detection of ctDNA in two patients that had recurrence, with the lead time of 4-10.5 months ahead of clinical diagnosis. CEA failed to predict recurrence in both cases. Conclusion: Our assay showed promising dual clinical utilities in residual cancer surveillance and actionable mutation profiling for targeted therapies in CRC patients. This could lay foundation to empower precision cancer medicine in Vietnam and other developing countries.

Molecular characteristics of young-onset colorectal cancer in Vietnamese patients.

BACKGROUND: Colorectal cancer (CRC) is one of the most common cancer globally. Understanding the genetic characteristics of CRC is essential for appropriate treatment and genetic counseling. METHODS: The genetic profile of CRC tumor tissues was identified using next-generation sequencing of 17 target genes (MLH1, MSH2, MSH6, PMS2, EPCAM, APC, SMAD4, BMPR1A, MUTYH, STK11, PTEN, TP53, ATM, CDH1, CHEK2, POLE, and POLD1) in a cohort of 101 Vietnamese patients diagnosed with young-onset CRC. Corresponding germline genetic alterations of determined somatic mutations were subsequently confirmed from patients' blood samples. RESULTS: Somatic mutations were determined in 96 out of 101 CRC patients. Two-thirds of the tumors harbored more than two mutations, and the most prevalent mutated genes were TP53 and APC. Among confirmed germline mutations, 10 pathogenic mutations and 11 variants of unknown significance were identified. CONCLUSIONS: Given the burden of CRC and the gradually reducing cost of genetic testing, multigene panel screening can benefit young-onset CRC patients as well as their relatives.

Ultra-Deep Sequencing of Plasma-Circulating DNA for the Detection of Tumor- Derived Mutations in Patients with Nonmetastatic Colorectal Cancer.

Identification of tumor-derived mutation (TDM) in liquid biopsies (LB), especially in early-stage patients, faces several challenges, including low variant-allele frequencies, interference by white blood cell (WBC)-derived mutations (WDM), benign somatic mutations and tumor heterogeneity. Here, we addressed the above-mentioned challenges in a cohort of 50 nonmetastatic colorectal cancer patients, via a workflow involving parallel sequencing of paired WBC- and tumor-gDNA. After excluding potential false positive mutations, we detected at least one TDM in LB of 56% (28/50) of patients, with the majority showing low-patient coverage, except for one TDM mapped to KMT2D that recurred in 30% (15/30) of patients.

Circulating DNA methylation profile improves the accuracy of serum biomarkers for the detection of nonmetastatic hepatocellular carcinoma.

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, µTASWako®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

The early detection of liver cancer in high-risk populations can help people with the disease have a higher chance of survival and better quality of life. However, this is still a healthcare challenge. Current commercial blood tests measuring protein signatures in the blood have low accuracy due to increased levels of these proteins being detected in both liver cancer patients and patients with chronic liver diseases. In this study, we identified a set of signatures in DNA released by cancer cells into the bloodstream and used them as biomarkers to distinguish liver cancer patients from high-risk patients. We also demonstrated that adding those signatures to a commercial blood test currently used in clinics could improve the accuracy in detecting liver cancer patients.

Liquid biopsy uncovers distinct patterns of DNA methylation and copy number changes in NSCLC patients with different EGFR-TKI resistant mutations.

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.

Pathogenic Variant Profile of Hereditary Cancer Syndromes in a Vietnamese Cohort.

BACKGROUND: Hereditary cancer syndromes (HCS) are responsible for 5-10% of cancer cases. Genetic testing to identify pathogenic variants associated with cancer predisposition has not been routinely available in Vietnam. Consequently, the prevalence and genetic landscape of HCS remain unknown. METHODS: 1165 Vietnamese individuals enrolled in genetic testing at our laboratory in 2020. We performed analysis of germline mutations in 17 high- and moderate- penetrance genes associated with HCS by next generation sequencing. RESULTS: A total of 41 pathogenic variants in 11 genes were detected in 3.2% individuals. The carrier frequency was 4.2% in people with family or personal history of cancer and 2.6% in those without history. The percentage of mutation carriers for hereditary colorectal cancer syndromes was 1.3% and for hereditary breast and ovarian cancer syndrome was 1.6%. BRCA1 and BRCA2 mutations were the most prevalent with the positive rate of 1.3% in the general cohort and 5.1% in breast or ovarian cancer patients. Most of BRCA1 mutations located at the BRCA C-terminus domains and the top recurrent mutation was NM_007294.3:c.5251C>T (p.Arg1751Ter). One novel variant NM_000038.6(APC):c.6665C>A (p.Pro2222His) was found in a breast cancer patient with a strong family history of cancer. A case study of hereditary cancer syndrome was illustrated to highlight the importance of genetic testing. CONCLUSION: This is the first largest analysis of carrier frequency and mutation spectrum of HCS in Vietnam. The findings demonstrate the clinical significance of multigene panel testing to identify carriers and their at-risk relatives for better cancer surveillance and management strategies.

Ultra-Deep Massive Parallel Sequencing of Plasma Cell-Free DNA Enables Large-Scale Profiling of Driver Mutations in Vietnamese Patients With Advanced Non-Small Cell Lung Cancer.

Population-specific profiling of mutations in cancer genes is of critical importance for the understanding of cancer biology in general as well as the establishment of optimal diagnostics and treatment guidelines for that particular population. Although genetic analysis of tumor tissue is often used to detect mutations in cancer genes, the invasiveness and limited accessibility hinders its application in large-scale population studies. Here, we used ultra-deep massive parallel sequencing of plasma cell free DNA (cfDNA) to identify the mutation profiles of 265 Vietnamese patients with advanced non-small cell lung cancer (NSCLC). Compared to a cohort of advanced NSCLC patients characterized by sequencing of tissue samples, cfDNA genomic testing, despite lower mutation detection rates, was able to detect major mutations in tested driver genes that reflected similar mutation composition and distribution pattern, as well as major associations between mutation prevalence and clinical features. In conclusion, ultra-deep sequencing of plasma cfDNA represents an alternative approach for population-wide genetic profiling of cancer genes where recruitment of patients is limited to the accessibility of tumor tissue site.

Actionable Mutation Profiles of Non-Small Cell Lung Cancer patients from Vietnamese population.

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.

Novel compound heterozygous TMEM67 variants in a Vietnamese family with Joubert syndrome: a case report.

BACKGROUND: Joubert syndrome is a genetically heterogeneous autosomal recessive ciliopathy characterized by the combination of hypoplasia/aplasia of the cerebellar vermis, thickened and elongated superior cerebellar peduncles and a deep interpeduncular fossa, known as "molar tooth sign" associated with hypotonia, respiratory control disturbances and abnormal eye movements. To date, pathogenic variants in over 35 genes are known to cause autosomal recessive Joubert Syndrome, while one gene is associated with X-linked recessive inheritance. CASE PRESENTATION: We describe here a non-consanguineous Vietnamese family with Joubert syndrome, a fetus and 10-year-old developmentally delayed boy. Ultrasonography showed ventriculomegaly at 26 + 6 weeks of gestation in the fetus. The 10-year-old-boy was diagnosed with cerebral palsy of unknown origin. Clinical physical examination at the age of 10, he showed clinical features of Joubert syndrome including typical facial dysmorphism, ataxia, severe psychomotor delay, oculomotor apraxia and molar tooth sign on brain MRI. Whole exome sequencing analysis identified a novel compound heterozygous c.725A > G p.Asn242Ser and c.313-3 T > G p.Lys105Valfs*16 TMEM67 variant in the proband and the affected fetus. These two variants were inherited from each parent and confirmed by Sanger sequencing. The variant c.725A > G p.Asn242Ser was previously documented in patients with JS, the novel splice-site c.313-3 T > G p.Lys105Valfs*16 TMEM67 variant produced an aberrant transcript with the loss of four nucleotides of exon 03. CONCLUSION: This study confirms the diagnosis of Joubert syndrome in a Vietnamese family and expands the mutational spectrum of TMEM67 sequence variations. We also highlight the importance of molecular approaches to unravel underlying mechanisms of human genetic disorders. Early precise diagnosis could help provide further accurate genetic counseling for recurrence-risk assessment, future diagnostic option, management as well as treatment guidance for rare disorders.

Evaluation of a Liquid Biopsy Protocol using Ultra-Deep Massive Parallel Sequencing for Detecting and Quantifying Circulation Tumor DNA in Colorectal Cancer Patients.

The identification and quantification of actionable mutations are critical for guiding targeted therapy and monitoring drug response in colorectal cancer. Liquid biopsy (LB) based on plasma cell-free DNA analysis has emerged as a noninvasive approach with many clinical advantages over conventional tissue sampling. Here, we developed a LB protocol using ultra-deep massive parallel sequencing and validated its clinical performance for detection and quantification of actionable mutations in three major driver genes (KRAS, NRAS and BRAF). The assay showed a 92% concordance for mutation detection between plasma and paired tissues and great reliability in quantification of variant allele frequency.

Ultra-deep massively parallel sequencing with unique molecular identifier tagging achieves comparable performance to droplet digital PCR for detection and quantification of circulating tumor DNA from lung cancer patients.

The identification and quantification of actionable mutations are of critical importance for effective genotype-directed therapies, prognosis and drug response monitoring in patients with non-small-cell lung cancer (NSCLC). Although tumor tissue biopsy remains the gold standard for diagnosis of NSCLC, the analysis of circulating tumor DNA (ctDNA) in plasma, known as liquid biopsy, has recently emerged as an alternative and noninvasive approach for exploring tumor genetic constitution. In this study, we developed a protocol for liquid biopsy using ultra-deep massively parallel sequencing (MPS) with unique molecular identifier tagging and evaluated its performance for the identification and quantification of tumor-derived mutations from plasma of patients with advanced NSCLC. Paired plasma and tumor tissue samples were used to evaluate mutation profiles detected by ultra-deep MPS, which showed 87.5% concordance. Cross-platform comparison with droplet digital PCR demonstrated comparable detection performance (91.4% concordance, Cohen's kappa coefficient of 0.85 with 95% CI = 0.72-0.97) and great reliability in quantification of mutation allele frequency (Intraclass correlation coefficient of 0.96 with 95% CI = 0.90-0.98). Our results highlight the potential application of liquid biopsy using ultra-deep MPS as a routine assay in clinical practice for both detection and quantification of actionable mutation landscape in NSCLC patients.