Posttranslational Modification as a Critical Determinant of Cytoplasmic Innate Immune Recognition.

Cell surface innate immune receptors can directly detect a variety of extracellular pathogens to which cytoplasmic innate immune sensors are rarely exposed. Instead, within the cytoplasm, the environment is rife with cellular machinery and signaling pathways that are indirectly perturbed by pathogenic microbes to activate intracellular sensors, such as pyrin, NLRP1, NLRP3, or NLRC4. Therefore, subtle changes in key intracellular processes such as phosphorylation, ubiquitination, and other pathways leading to posttranslational protein modification are key determinants of innate immune recognition in the cytoplasm. This concept is critical to establish the "guard hypothesis" whereby otherwise homeostatic pathways that keep innate immune sensors at bay are released in response to alterations in their posttranslational modification status. Originally identified in plants, evidence that a similar guardlike mechanism exists in humans has recently been identified, whereby a mutation that prevents phosphorylation of the innate immune sensor pyrin triggers a dominantly inherited autoinflammatory disease. It is also noteworthy that even when a cytoplasmic innate immune sensor has a direct ligand, such as bacterial peptidoglycan (NOD1 or NOD2), RNA (RIG-I or MDA5), or DNA (cGAS or IFI16), it can still be influenced by posttranslational modification to dramatically alter its response. Therefore, due to their existence in the cytoplasmic milieu, posttranslational modification is a key determinant of intracellular innate immune receptor functionality.

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).

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.

Anti-CD40L therapy prevents the formation of precursor lesions to gastric B-cell MALT lymphoma in a mouse model.

Mucosa-associated lymphoid tissue (MALT) lymphoma is a B-cell tumour that develops over many decades in the stomachs of individuals with chronic Helicobacter pylori infection. We developed a new mouse model of human gastric MALT lymphoma in which mice with a myeloid-specific deletion of the innate immune molecule, Nlrc5, develop precursor B-cell lesions to MALT lymphoma at only 3 months post-Helicobacter infection versus 9-24 months in existing models. The gastric B-cell lesions in the Nlrc5 knockout mice had the histopathological features of the human disease, notably lymphoepithelial-like lesions, centrocyte-like cells, and were infiltrated by dendritic cells (DCs), macrophages, and T-cells (CD4+ , CD8+ and Foxp3+ ). Mouse and human gastric tissues contained immune cells expressing immune checkpoint receptor programmed death 1 (PD-1) and its ligand PD-L1, indicating an immunosuppressive tissue microenvironment. We next determined whether CD40L, overexpressed in a range of B-cell malignancies, may be a potential drug target for the treatment of gastric MALT lymphoma. Importantly, we showed that the administration of anti-CD40L antibody either coincident with or after establishment of Helicobacter infection prevented gastric B-cell lesions in mice, when compared with the control antibody treatment. Mice administered the CD40L antibody also had significantly reduced numbers of gastric DCs, CD8+ and Foxp3+ T-cells, as well as decreased gastric expression of B-cell lymphoma genes. These findings validate the potential of CD40L as a therapeutic target in the treatment of human gastric B-cell MALT lymphoma. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

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.

Multimodal analysis of ctDNA methylation and fragmentomic profiles enhances detection of nonmetastatic colorectal cancer.

Aims: Early detection of colorectal cancer (CRC) provides substantially better survival rates. This study aimed to develop a blood-based screening assay named SPOT-MAS ('screen for the presence of tumor by DNA methylation and size') for early CRC detection with high accuracy. Methods: Plasma cell-free DNA samples from 159 patients with nonmetastatic CRC and 158 healthy controls were simultaneously analyzed for fragment length and methylation profiles. We then employed a deep neural network with fragment length and methylation signatures to build a classification model. Results: The model achieved an area under the curve of 0.989 and a sensitivity of 96.8% at 97% specificity in detecting CRC. External validation of our model showed comparable performance, with an area under the curve of 0.96. Conclusion: SPOT-MAS based on integration of cancer-specific methylation and fragmentomic signatures could provide high accuracy for early-stage CRC detection.

A novel blood test for early detection of colorectal cancer. Colorectal cancer is a cancer of the colon or rectum, located at the lower end of the digestive tract. The early detection of colorectal cancer can help people with the disease have a higher chance of survival and a better quality of life. Current screening methods can be invasive, cause discomfort or have low accuracy; therefore newer screening methods are needed. In this study we developed a new screening method, called SPOT-MAS, which works by measuring the signals of cancer DNA in the blood. By combining different characteristics of cancer DNA, SPOT-MAS could distinguish blood samples of people with colorectal cancer from those of healthy individuals with high accuracy.

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.

Innate Immune Molecule NLRC5 Protects Mice From Helicobacter-induced Formation of Gastric Lymphoid Tissue.

BACKGROUND & AIMS: Helicobacter pylori induces strong inflammatory responses that are directed at clearing the infection, but if not controlled, these responses can be harmful to the host. We investigated the immune-regulatory effects of the innate immune molecule, nucleotide-binding oligomerization domain-like receptors (NLR) family CARD domain-containing 5 (NLRC5), in patients and mice with Helicobacter infection. METHODS: We obtained gastric biopsies from 30 patients in Australia. We performed studies with mice that lack NLRC5 in the myeloid linage (Nlrc5møKO) and mice without Nlrc5 gene disruption (controls). Some mice were gavaged with H pylori SS1 or Helicobacter felis; 3 months later, stomachs, spleens, and sera were collected, along with macrophages derived from bone marrow. Human and mouse gastric tissues and mouse macrophages were analyzed by histology, immunohistochemistry, immunoblots, and quantitative polymerase chain reaction. THP-1 cells (human macrophages, controls) and NLRC5-/- THP-1 cells (generated by CRISPR-Cas9 gene editing) were incubated with Helicobacter and gene expression and production of cytokines were analyzed. RESULTS: Levels of NLRC5 messenger RNA were significantly increased in gastric tissues from patients with H pylori infection, compared with patients without infection (P < .01), and correlated with gastritis severity (P < .05). H pylori bacteria induced significantly higher levels of chemokine and cytokine production by NLRC5-/- THP-1 macrophages than by control THP-1 cells (P < .05). After 3 months of infection with H felis, Nlrc5mø-KO mice developed gastric hyperplasia (P < .0001), splenomegaly (P < .0001), and increased serum antibody titers (P < .01), whereas control mice did not. Nlrc5mø-KO mice with chronic H felis infection had increased numbers of gastric B-cell follicles expressing CD19 (P < .0001); these follicles had features of mucosa-associated lymphoid tissue lymphoma. We identified B-cell-activating factor as a protein that promoted B-cell hyperproliferation in Nlrc5mø-KO mice. CONCLUSIONS: NLRC5 is a negative regulator of gastric inflammation and mucosal lymphoid formation in response to Helicobacter infection. Aberrant NLRC5 signaling in macrophages can promote B-cell lymphomagenesis during chronic Helicobacter infection.

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.

NOD1 is required for Helicobacter pylori induction of IL-33 responses in gastric epithelial cells.

Helicobacter pylori (H. pylori) causes chronic inflammation which is a key precursor to gastric carcinogenesis. It has been suggested that H. pylori may limit this immunopathology by inducing the production of interleukin 33 (IL-33) in gastric epithelial cells, thus promoting T helper 2 immune responses. The molecular mechanism underlying IL-33 production in response to H. pylori infection, however, remains unknown. In this study, we demonstrate that H. pylori activates signalling via the pathogen recognition molecule Nucleotide-Binding Oligomerisation Domain-Containing Protein 1 (NOD1) and its adaptor protein receptor-interacting serine-threonine Kinase 2, to promote production of both full-length and processed IL-33 in gastric epithelial cells. Furthermore, IL-33 responses were dependent on the actions of the H. pylori Type IV secretion system, required for activation of the NOD1 pathway, as well as on the Type IV secretion system effector protein, CagA. Importantly, Nod1+/+ mice with chronic H. pylori infection exhibited significantly increased gastric IL-33 and splenic IL-13 responses, but decreased IFN-γ responses, when compared with Nod1-/- animals. Collectively, our data identify NOD1 as an important regulator of mucosal IL-33 responses in H. pylori infection. We suggest that NOD1 may play a role in protection against excessive inflammation.

Membrane vesicles from Pseudomonas aeruginosa activate the noncanonical inflammasome through caspase-5 in human monocytes.

Outer membrane vesicles (OMVs) are constitutively produced by Gram-negative bacteria both in vivo and in vitro. These lipid-bound structures carry a range of immunogenic components derived from the parent cell, which are transported into host target cells and activate the innate immune system. Recent advances in the field have shed light on some of the multifaceted roles of OMVs in host-pathogen interactions. In this study, we investigated the ability of OMVs from two clinically important pathogens, Pseudomonas aeruginosa and Helicobacter pylori, to activate canonical and noncanonical inflammasomes. P. aeruginosa OMVs induced inflammasome activation in mouse macrophages, as evidenced by "speck" formation, as well as the cleavage and secretion of interleukin-1ß and caspase-1. These responses were independent of AIM2 and NLRC4 canonical inflammasomes, but dependent on the noncanonical caspase-11 pathway. Moreover, P. aeruginosa OMVs alone were able to activate the inflammasome in a TLR-dependent manner, without requiring an exogenous priming signal. In contrast, H. pylori OMVs were not able to induce inflammasome activation in macrophages. Using CRISPR/Cas9 knockout THP-1 cells lacking the human caspase-11 homologs, caspase-4 and -5,we demonstrated that caspase-5 but not caspase-4 is required for inflammasome activation by P. aeruginosa OMVs in human monocytes. In contrast, free P. aeruginosa lipopolysaccharide (LPS) transfected into cells induced inflammasome responses via caspase-4. This suggests that caspase-4 and caspase-5 differentially recognize LPS depending on its physical form or route of delivery into the cell. These findings have relevance to Gram-negative infections in humans and the use of OMVs as novel vaccines.

A consultation and work-up diagnosis protocol for a multicancer early detection test: a case series study.

The emergence of multicancer early detection (MCED) tests holds promise for improving early cancer detection and public health outcomes. However, positive MCED test results require confirmation through recommended cancer diagnostic imaging modalities. To address these challenges, we have developed a consultation and work-up protocol for definitive diagnostic results post MCED testing, named SPOT-MAS. Developed through circulating tumor DNA (ctDNA) analysis and in line with professional guidelines and advisory board consensus, this protocol standardizes information to aid general practitioners in accessing, interpreting and managing SPOT-MAS results. Clinical effectiveness is demonstrated through a series of identified cancer cases. Our research indicates that the protocol could empower healthcare professionals to confidently interpret circulating tumor DNA test results for 5 common types of cancer, thereby facilitating the clinical integration of MCED tests.

New tests can now screen for multiple types of cancer early, offering hope for better health outcomes. If one of these tests shows a positive result, doctors need to confirm it with imaging tests. We have developed a guide to help doctors understand and confirm these results. This guide could help healthcare professionals interpret results for five common types of cancer, making it easier to use these tests in regular medical practice.

Design and generation of mRNAs encoding conserved regions of SARS-CoV-2 ORF1ab for T cell-mediated immune activation.

Aim: To generate mRNAs encoding conserved regions within SARS-CoV-2 ORF1ab which can induce strong T-cell responses to overcome the immune invasion of newly emergent variants. Methods: We selected two conserved regions with a high density of T-cell epitopes using immunoinformatics for mRNA synthesis. The ability of testing mRNAs to activate T cells for IFN-γ production was examined by an ELISpot assay and flow cytometry. Results: Two synthesized mRNAs were successfully translated in MDA-MB-231 cells and had comparable potency to the spike mRNA to induce CD4+ and CD8+ T-cell responses in peripheral blood mononuclear cells in 29 out of 34 participants. Conclusion: This study provides a proof-of-concept for the use of SARS-CoV-2 conserved regions to develop booster vaccines capable of eliciting T-cell-mediated immunity.

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.

Detection of maternal carriers of common α-thalassemia deletions from cell-free DNA.

α-Thalassemia is a common inherited blood disorder manifested mainly by the deletions of α-globin genes. In geographical areas with high carrier frequencies, screening of α-thalassemia carrier state is therefore of vital importance. This study presents a novel method for identifying female carriers of common α-thalassemia deletions using samples routinely taken for non-invasive prenatal tests for screening of fetal chromosomal aneuploidies. A total of 68,885 Vietnamese pregnant women were recruited and α-thalassemia statuses were determined by gap-PCR, revealing 5344 women (7.76%) carried deletions including αα/--SEA (4.066%), αα/-α3.7 (2.934%), αα/-α4.2 (0.656%), and rare genotypes (0.102%). A two-stage model was built to predict these α-thalassemia deletions from targeted sequencing of the HBA gene cluster on maternal cfDNA. Our method achieved F1-scores of 97.14-99.55% for detecting the three common genotypes and 94.74% for detecting rare genotypes (-α3.7/-α4.2, αα/--THAI, -α3.7/--SEA, -α4.2/--SEA). Additionally, the positive predictive values were 100.00% for αα/αα, 99.29% for αα/--SEA, 94.87% for αα/-α3.7, and 96.51% for αα/-α4.2; and the negative predictive values were 97.63%, 99.99%, 99.99%, and 100.00%, respectively. As NIPT is increasingly adopted for pregnant women, utilizing cfDNA from NIPT to detect maternal carriers of common α-thalassemia deletions will be cost-effective and expand the benefits of NIPT.

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.

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.

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.