Genomic profiling of pleomorphic rhabdomyosarcoma reveals a genomic signature distinct from that of embryonal rhabdomyosarcoma.

Pleomorphic rhabdomyosarcoma (PRMS) is a rare and highly aggressive sarcoma, occurring mostly in the deep soft tissues of middle-aged adults and showing a variable degree of skeletal muscle differentiation. The diagnosis is challenging as pathologic features overlap with embryonal rhabdomyosarcoma (ERMS), malignant Triton tumor, and other pleomorphic sarcomas. As recurrent genetic alterations underlying PRMS have not been described to date, ancillary molecular diagnostic testing is not useful in subclassification. Herein, we perform genomic profiling of a well-characterized cohort of 14 PRMS, compared to a control group of 23 ERMS and other pleomorphic sarcomas (undifferentiated pleomorphic sarcoma and pleomorphic liposarcoma) using clinically validated DNA-targeted Next generation sequencing (NGS) panels (MSK-IMPACT). The PRMS cohort included eight males and six females, with a median age of 53 years (range 31-76 years). Despite similar tumor mutation burdens, the genomic landscape of PRMS, with a high frequency of TP53 (79%) and RB1 (43%) alterations, stood in stark contrast to ERMS, with 4% and 0%, respectively. CDKN2A deletions were more common in PRMS (43%), compared to ERMS (13%). In contrast, ERMS harbored somatic driver mutations in the RAS pathway and loss of function mutations in BCOR, which were absent in PRMS. Copy number variations in PRMS showed multiple chromosomal arm-level changes, most commonly gains of chr17p and chr22q and loss of chr6q. Notably, gain of chr8, commonly seen in ERMS (61%) was conspicuously absent in PRMS. The genomic profiles of other pleomorphic sarcomas were overall analogous to PRMS, showing shared alterations in TP53, RB1, and CDKN2A. Overall survival and progression-free survival of PRMS were significantly worse (p < 0.0005) than that of ERMS. Our findings revealed that the molecular landscape of PRMS aligns with other adult pleomorphic sarcomas and is distinct from that of ERMS. Thus, NGS assays may be applied in select challenging cases toward a refined classification. Finally, our data corroborate the inclusion of PRMS in the therapeutic bracket of pleomorphic sarcomas, given that their clinical outcomes are comparable.

HPV genotyping in clinical samples using long-read single-molecule real-time sequencing.

Human papillomavirus (HPV) genotyping is widely used, particularly in combination with high-risk (HR) HPV tests for cervical cancer screening. We developed a genotyping method using sequences of approximately 800 bp in the E6/E7 region obtained by PacBio single molecule real-time sequencing (SMRT) and evaluated its performance against MY09-11 L1 sequencing and after the APTIMA HPV genotyping assay. The levels of concordance of PacBio E6/E7 SMRT sequencing with MY09-11 L1 sequencing and APTIMA HPV genotyping were 100% and 90.8%, respectively. The sensitivity of PacBio E6/EA7 SMRT was slightly greater than that of L1 sequencing and, as expected, lower than that of HR-HPV tests. In the context of cervical cancer screening, PacBio E6/E7 SMRT is then best used after a positive HPV test. PacBio E6/E7 SMRT genotyping is an attractive alternative for HR and LR-HPV genotyping of clinical samples. PacBio SMRT sequencing provides unbiased genotyping and can detect multiple HPV infections and haplotypes within a genotype.

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction.

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking.

BACKGROUND: High-throughput sequencing (HTS) has become the gold standard approach for variant analysis in cancer research. However, somatic variants may occur at low fractions due to contamination from normal cells or tumor heterogeneity; this poses a significant challenge for standard HTS analysis pipelines. The problem is exacerbated in scenarios with minimal tumor DNA, such as circulating tumor DNA in plasma. Assessing sensitivity and detection of HTS approaches in such cases is paramount, but time-consuming and expensive: specialized experimental protocols and a sufficient quantity of samples are required for processing and analysis. To overcome these limitations, we propose a new computational approach specifically designed for the generation of artificial datasets suitable for this task, simulating ultra-deep targeted sequencing data with low-fraction variants and demonstrating their effectiveness in benchmarking low-fraction variant calling. RESULTS: Our approach enables the generation of artificial raw reads that mimic real data without relying on pre-existing data by using NEAT, a fine-grained read simulator that generates artificial datasets using models learned from multiple different datasets. Then, it incorporates low-fraction variants to simulate somatic mutations in samples with minimal tumor DNA content. To prove the suitability of the created artificial datasets for low-fraction variant calling benchmarking, we used them as ground truth to evaluate the performance of widely-used variant calling algorithms: they allowed us to define tuned parameter values of major variant callers, considerably improving their detection of very low-fraction variants. CONCLUSIONS: Our findings highlight both the pivotal role of our approach in creating adequate artificial datasets with low tumor fraction, facilitating rapid prototyping and benchmarking of algorithms for such dataset type, as well as the important need of advancing low-fraction variant calling techniques.

Epitope binning for multiple antibodies simultaneously using mammalian cell display and DNA sequencing.

Epitope binning, an approach for grouping antibodies based on epitope similarities, is a critical step in antibody drug discovery. However, conventional methods are complex, involving individual antibody production. Here, we established Epitope Binning-seq, an epitope binning platform for simultaneously analyzing multiple antibodies. In this system, epitope similarity between the query antibodies (qAbs) displayed on antigen-expressing cells and a fluorescently labeled reference antibody (rAb) targeting a desired epitope is analyzed by flow cytometry. The qAbs with epitope similar to the rAb can be identified by next-generation sequencing analysis of fluorescence-negative cells. Sensitivity and reliability of this system are confirmed using rAbs, pertuzumab and trastuzumab, which target human epidermal growth factor receptor 2. Epitope Binning-seq enables simultaneous epitope evaluation of 14 qAbs at various abundances in libraries, grouping them into respective epitope bins. This versatile platform is applicable to diverse antibodies and antigens, potentially expediting the identification of clinically useful antibodies.

A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing.

The B-cell acute lymphoblastic leukemia (ALL) cell line REH, with the t(12;21) ETV6::RUNX1 translocation, is known to have a complex karyotype defined by a series of large-scale chromosomal rearrangements. Taken from a 15-yr-old at relapse, the cell line offers a practical model for the study of pediatric B-ALL. In recent years, short- and long-read DNA and RNA sequencing have emerged as a complement to karyotyping techniques in the resolution of structural variants in an oncological context. Here, we explore the integration of long-read PacBio and Oxford Nanopore whole-genome sequencing, IsoSeq RNA sequencing, and short-read Illumina sequencing to create a detailed genomic and transcriptomic characterization of the REH cell line. Whole-genome sequencing clarified the molecular traits of disrupted ALL-associated genes including CDKN2A, PAX5, BTG1, VPREB1, and TBL1XR1, as well as the glucocorticoid receptor NR3C1 Meanwhile, transcriptome sequencing identified seven fusion genes within the genomic breakpoints. Together, our extensive whole-genome investigation makes high-quality open-source data available to the leukemia genomics community.

The Search for and Functional Analysis of Genetic Variants in microRNA-Binding Sites using Massively Parallel Reporter Assay.

A large-scale search for the genetic variants with a bias in the representation of alleles in transcriptome data (AE SNPs) and the binding sites in microRNA 3'-UTRs was performed and their functional significance was assessed using massively parallel reporter assay (MPRA). Of the 629,559 associated "SNP-gene" pairs (eQTLs) discovered in the human liver tissue according to the GTEx Analysis V8 data, 4394 polymorphic positions in the 3'-UTRs of the genes, which represent the eQTLs for these genes were selected. The TargetScanHuman 7.0 algorithm and PolymiRTS database were searched for the potential microRNA-binding sites. Of the predicted microRNA sites affected by eQTL-SNPs, we selected 51 sites with the best evidence of functionality according to Ago2-CLIP-seq, CLEAR-CLIP, and eCLIP-seq for RNA-binding proteins. For MPRA, a library of the plasmids carrying the main and alternative alleles for each AE SNP (in total, 102 constructs) was created. Allele-specific expression for 6 SNPs was detected by transfection of the HepG2 cell line with the constructed plasmid library and sequencing of target DNA and RNA sequences using the Illumina (MiSeq) platform.

WilsonGenAI a deep learning approach to classify pathogenic variants in Wilson Disease.

BACKGROUND: Advances in Next Generation Sequencing have made rapid variant discovery and detection widely accessible. To facilitate a better understanding of the nature of these variants, American College of Medical Genetics and Genomics and the Association of Molecular Pathologists (ACMG-AMP) have issued a set of guidelines for variant classification. However, given the vast number of variants associated with any disorder, it is impossible to manually apply these guidelines to all known variants. Machine learning methodologies offer a rapid way to classify large numbers of variants, as well as variants of uncertain significance as either pathogenic or benign. Here we classify ATP7B genetic variants by employing ML and AI algorithms trained on our well-annotated WilsonGen dataset. METHODS: We have trained and validated two algorithms: TabNet and XGBoost on a high-confidence dataset of manually annotated, ACMG & AMP classified variants of the ATP7B gene associated with Wilson's Disease. RESULTS: Using an independent validation dataset of ACMG & AMP classified variants, as well as a patient set of functionally validated variants, we showed how both algorithms perform and can be used to classify large numbers of variants in clinical as well as research settings. CONCLUSION: We have created a ready to deploy tool, that can classify variants linked with Wilson's disease as pathogenic or benign, which can be utilized by both clinicians and researchers to better understand the disease through the nature of genetic variants associated with it.

Combining germline, tissue and liquid biopsy analysis by comprehensive genomic profiling to improve the yield of actionable variants in a real-world cancer cohort.

BACKGROUND: Comprehensive next-generation sequencing is widely used for precision oncology and precision prevention approaches. We aimed to determine the yield of actionable gene variants, the capacity to uncover hereditary predisposition and liquid biopsy appropriateness instead of, or in addition to, tumor tissue analysis, in a real-world cohort of cancer patients, who may benefit the most from comprehensive genomic profiling. METHODS: Seventy-eight matched germline/tumor tissue/liquid biopsy DNA and RNA samples were profiled using the Hereditary Cancer Panel (germline) and the TruSight Oncology 500 panel (tumor tissue/cfDNA) from 23 patients consecutively enrolled at our center according to at least one of the following criteria: no available therapeutic options; long responding patients potentially fit for other therapies; rare tumor; suspected hereditary cancer; primary cancer with high metastatic potential; tumor of unknown primary origin. Variants were annotated for OncoKB and AMP/ASCO/CAP classification. RESULTS: The overall yield of actionable somatic and germline variants was 57% (13/23 patients), and 43.5%, excluding variants previously identified by somatic or germline routine testing. The accuracy of tumor/cfDNA germline-focused analysis was demonstrated by overlapping results of germline testing. Five germline variants in BRCA1, VHL, CHEK1, ATM genes would have been missed without extended genomic profiling. A previously undetected BRAF p.V600E mutation was emblematic of the clinical utility of this approach in a patient with a liver undifferentiated embryonal sarcoma responsive to BRAF/MEK inhibition. CONCLUSIONS: Our study confirms the clinical relevance of performing extended parallel tumor DNA and cfDNA testing to broaden therapeutic options, to longitudinally monitor cfDNA during patient treatment, and to uncover possible hereditary predisposition following tumor sequencing in patient care.

Pragmatic nationwide master observational trial based on genomic alterations in advanced solid tumors: KOrean Precision Medicine Networking Group Study of MOlecular profiling guided therapy based on genomic alterations in advanced Solid tumors (KOSMOS)-II study protocol KCSG AL-22-09.

BACKGROUND: Next-generation sequencing (NGS) has been introduced to many Korean institutions to support molecular diagnostics in cancer since 2017, when it became eligible for reimbursement by the National Health Insurance Service. However, the uptake of molecularly guided treatment (MGT) based on NGS results has been limited because of stringent regulations regarding prescriptions outside of approved indications, a lack of clinical trial opportunities, and limited access to molecular tumor boards (MTB) at most institutions. The KOSMOS-II study was designed to demonstrate the feasibility and effectiveness of MGT, informed by MTBs, using a nationwide precision medicine platform. METHODS: The KOSMOS-II trial is a large-scale nationwide master observational study. It involves a framework for screening patients with metastatic solid tumors for actionable genetic alterations based on local NGS testing. It recommends MGT through a remote and centralized MTB meeting held biweekly. MGT can include one of the following options: Tier 1, the therapeutic use of investigational drugs targeting genetic alterations such as ALK, EGFR, ERBB2, BRAF, FH, ROS1, and RET, or those with high tumor mutational burden; Tier 2, comprising drugs with approved indications or those permitted for treatment outside of the indications approved by the Health Insurance Review and Assessment Service of Korea; Tier 3, involving clinical trials matching the genetic alterations recommended by the MTB. Given the anticipated proportion of patients receiving MGT in the range of 50% ± 3.25%, this study aims to enroll 1,000 patients. Patients must have progressed to one or more lines of therapy and undergone NGS before enrollment. DISCUSSION: This pragmatic master protocol provides a mass-screening platform for rare genetic alterations and high-quality real-world data. Collateral clinical trials, translational studies, and clinico-genomic databases will contribute to generating evidence for drug repositioning and the development of new biomarkers. TRIAL REGISTRATION: NCT05525858.

Multi-centre analytical performance verification of an IVD assay to quantify donor-derived cell-free DNA in solid organ transplant recipients.

Donor-derived cell-free DNA (dd-cfDNA) has been widely studied as biomarker for non-invasive allograft rejection monitoring. Earlier rejection detection enables more prompt diagnosis and intervention, ultimately improving patient treatment and outcomes. This multi-centre study aims to verify analytical performance of a next-generation sequencing-based dd-cfDNA assay at end-user environments. Three independent laboratories received the same experimental design and 16 blinded samples to perform cfDNA extraction and the dd-cfDNA assay workflow. dd-cfDNA results were compared between sites and against manufacturer validation to evaluate concordance, reproducibility, repeatability and verify analytical performance. A total of 247 sample libraries were generated across 18 runs, with completion time of <24 h. A 96.0% first pass rate highlighted minimal failures. Overall observed versus expected dd-cfDNA results demonstrated good concordance and a strong positive correlation with linear least squares regression r2 = 0.9989, and high repeatability and reproducibility within and between sites, respectively (p > 0.05). Manufacturer validation established limit of blank 0.18%, limit of detection 0.23% and limit of quantification 0.23%, and results from independent sites verified those limits. Parallel analyses illustrated no significant difference (p = 0.951) between dd-cfDNA results with or without recipient genotype. The dd-cfDNA assay evaluated here has been verified as a reliable method for efficient, reproducible dd-cfDNA quantification in plasma from solid organ transplant recipients without requiring genotyping. Implementation of onsite dd-cfDNA testing at clinical laboratories could facilitate earlier detection of allograft injury, bearing great potential for patient care.

An NGS-based assay for accurate detection and quantification of immune gene expression in mouse tumor models.

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1-6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.

NTRK gene fusion testing and management in lung cancer.

Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are recurrent oncogenic drivers found in a variety of solid tumours, including lung cancer. Several tropomyosin receptor kinase (TRK) inhibitors have been developed to treat tumours with NTRK gene fusions. Larotrectinib and entrectinib are first-generation TRK inhibitors that have demonstrated efficacy in patients with TRK fusion lung cancers. Genomic testing is recommended for all patients with metastatic non-small cell lung cancer for optimal drug therapy selection. Multiple testing methods can be employed to identify NTRK gene fusions in the clinic and each has its own advantages and limitations. Among these assays, RNA-based next-generation sequencing (NGS) can be considered a gold standard for detecting NTRK gene fusions; however, several alternatives with minimally acceptable sensitivity and specificity are also available in areas where widespread access to NGS is unfeasible. This review highlights the importance of testing for NTRK gene fusions in lung cancer, ideally using the gold-standard method of RNA-based NGS, the various assays that are available, and treatment algorithms for patients.

Practical considerations for pathological diagnosis and molecular profiling of cholangiocarcinoma: an expert review for best practices.

INTRODUCTION: Advances in precision medicine have expanded access to targeted therapies and demand for molecular profiling of cholangiocarcinoma (CCA) patients in routine clinical practice. However, pathologists face challenges in establishing a definitive intrahepatic CCA (iCCA) diagnosis while preserving sufficient tissue for molecular profiling. Additionally, they frequently face challenges in optimal tissue handling to preserve nucleic acid integrity. AREAS COVERED: This article first identifies the challenges in establishing a definitive diagnosis of iCCA in a lesional liver biopsy while preserving sufficient tissue for molecular profiling. Then, the authors explore the clinical value of molecular profiling, the basic principles of single gene and next-generation sequencing (NGS) techniques, and the challenges in tissue sampling for genomic testing. They also propose an algorithm for best practice in tissue management for molecular profiling of CCA. EXPERT OPINION: Several practical challenges face pathologists during tissue sampling and processing for molecular profiling. Optimized tissue processing, careful tissue handling, and selection of appropriate approaches to molecular testing are essential to ensure that the highest possible quality of diagnostic information is provided in the greatest proportion of cases.

A Brief Overview of the Molecular Landscape of Myelodysplastic Neoplasms.

Myelodysplastic neoplasm (MDS) is a heterogeneous group of clonal hematological disorders that originate from the hematopoietic and progenitor cells and present with cytopenias and morphologic dysplasia with a propensity to progress to bone marrow failure or acute myeloid leukemia (AML). Genetic evolution plays a critical role in the pathogenesis, progression, and clinical outcomes of MDS. This process involves the acquisition of genetic mutations in stem cells that confer a selective growth advantage, leading to clonal expansion and the eventual development of MDS. With the advent of next-generation sequencing (NGS) assays, an increasing number of molecular aberrations have been discovered in recent years. The knowledge of molecular events in MDS has led to an improved understanding of the disease process, including the evolution of the disease and prognosis, and has paved the way for targeted therapy. The 2022 World Health Organization (WHO) Classification and the International Consensus Classification (ICC) have incorporated the molecular signature into the classification system for MDS. In addition, specific germline mutations are associated with MDS development, especially in pediatrics and young adults. This article reviews the genetic abnormalities of MDS in adults with a brief review of germline predisposition syndromes.

Resolving Discrepancies in Idylla BRAF Mutational Assay Results Using Targeted Next-Generation Sequencing.

BRAF mutation identification is important for the diagnosis and treatment of several tumor types, both solid and hematologic. Rapid identification of BRAF mutations is required to determine eligibility for targeted BRAF inhibitor therapy. The Idylla BRAF mutation assay is a rapid, multiplex allele-specific PCR test designed to detect the most common oncogenic BRAF V600 mutations in formalin-fixed paraffin-embedded (FFPE) tissue samples. Here, we describe the validation of the Idylla BRAF mutation assay in our laboratory. During routine clinical practice, we noticed cases in which BRAF V600 mutations were identified with unusual amplification curves, with three cases displaying a delayed amplification within a double amplification pattern and two false-positive calls. We therefore initiated a quality improvement effort to systematically and retrospectively evaluate next-generation sequencing (NGS)-tested cases with BRAF mutations identified within five amino acids of BRAF codon V600 and did not identify additional false-positive cases. We hypothesize that late amplification in a double amplification pattern may represent non-specific amplification, whereas cases displaying single delayed amplification curves may stem from the presence of either non-V600 variants, very low-level V600 variants, cytosine deamination artifacts, and/or non-specific amplification by an allele-specific PCR primer. Regardless, we recommend that Idylla BRAF cases with non-classical amplification curves undergo reflex NGS testing. These findings are likely relevant for other Idylla assays interrogating hotspot mutations in genes such as EGFR, IDH1/2, KRAS, and NRAS.

Elucidating Cancer Subtypes by Using the Relationship between DNA Methylation and Gene Expression.

Advancements in the field of next generation sequencing (NGS) have generated vast amounts of data for the same set of subjects. The challenge that arises is how to combine and reconcile results from different omics studies, such as epigenome and transcriptome, to improve the classification of disease subtypes. In this study, we introduce sCClust (sparse canonical correlation analysis with clustering), a technique to combine high-dimensional omics data using sparse canonical correlation analysis (sCCA), such that the correlation between datasets is maximized. This stage is followed by clustering the integrated data in a lower-dimensional space. We apply sCClust to gene expression and DNA methylation data for three cancer genomics datasets from the Cancer Genome Atlas (TCGA) to distinguish between underlying subtypes. We evaluate the identified subtypes using Kaplan-Meier plots and hazard ratio analysis on the three types of cancer-GBM (glioblastoma multiform), lung cancer and colon cancer. Comparison with subtypes identified by both single- and multi-omics studies implies improved clinical association. We also perform pathway over-representation analysis in order to identify up-regulated and down-regulated genes as tentative drug targets. The main goal of the paper is twofold: the integration of epigenomic and transcriptomic datasets followed by elucidating subtypes in the latent space. The significance of this study lies in the enhanced categorization of cancer data, which is crucial to precision medicine.

BRAF Mutations in Patients with Myeloid Neoplasms: A Cancer Center Multigene Next-Generation Sequencing Analysis Experience.

BRAF mutations are rare in myeloid neoplasms and are reported to be associated with poor treatment outcomes. The purpose of our study is to characterize BRAF mutations in myeloid neoplasms using a next-generation sequencing (NGS) panel based on the experiences of a single cancer center. We conducted a retrospective review of patients with myeloid neoplasms who underwent the HopeSeq studies between January 2018 and September 2023. A total of 14 patients with myeloid neoplasms carrying BRAF mutations were included in our cohort. The clinical, pathological, and molecular features of these patients were investigated. Our study indicates that BRAF mutations are rare in myeloid neoplasms, constituting only 0.53% (14/2632) of all myeloid neoplasm cases, with the most common BRAF mutation being BRAF V600E (4/14; 28.6%). Interestingly, we observed that six out of seven patients with acute myeloid leukemia (AML) exhibited AML with monocytic differentiation, and all the patients with AML exhibited an extremely poor prognosis compared to those without BRAF mutations. TET2 (5/14; 35.7%), ASXL1 (4/14; 28.6%), and JAK2 (4/14; 28.6%) were the three most frequently co-mutated genes in these patients. Moreover, we noted concurrent KMT2A gene rearrangement with BRAF mutations in three patients with AML (3/7; 42.9%). Our study suggests that although BRAF mutations are rare in myeloid neoplasms, they play a crucial role in the pathogenesis of specific AML subtypes. Furthermore, RAS pathway alterations, including BRAF mutations, are associated with KMT2A gene rearrangement in AML. However, these findings warrant further validation in larger studies.

Microfluidics-based EGFR mutation detection and its implication in the resource-limited clinical setting.

Management of lung cancer today obligates a mutational analysis of the epidermal growth factor receptor (EGFR) gene particularly when Tyrosine Kinase Inhibitor (TKI) therapy is being considered as part of prognostic stratification. This study evaluates the performance of automated microfluidics-based EGFR mutation detection and its significance in clinical diagnostic settings. Formalin-fixed, paraffin-embedded (FFPE) samples from NSCLC patients (n = 174) were included in a two-phase study. Phase I: Validation of the platform by comparing the results with conventional real-time PCR and next-generation sequencing (NGS) platform. Phase II: EGFR mutation detection on microfluidics-based platform as part of routine diagnostics workup. The microfluidics-based platform demonstrates 96.5% and 89.2% concordance with conventional real-time PCR and NGS, respectively. The system efficiently detects mutations across the EGFR gene with 88.23% sensitivity and 100% specificity. Out of 144 samples analysed in phase II, the platform generated valid results in 94% with mutation detected in 41% of samples. This microfluidics-based platform can detect as low as 5% mutant allele fractions from the FFPE samples. Therefore the microfluidics-based platform is a rapid, complete walkaway, with minimum tissue requirement (two sections of 5 µ thickness) and technical skill requirement. The method can detect clinically actionable EGFR mutations efficiently and can be considered a reliable diagnostic platform in resource-limited settings. From receiving samples to reporting the results this platform provides accurate data without much manual intervention. The study helped to devise an algorithm that emphasizes effective screening of the NSCLC cases for EGFR mutations with varying tumour content. Thus it helps in triaging the cases judiciously before proceeding with multigene testing.