Biology subjects

Wang, M.

Publications and source records attributed to Wang, M..

At least 487 records · Page 27Linked to original sources

bioRxiv2023

Predicting Parkinson's disease progression using MRI-based white matter radiomic biomarker and machine learning: a reproducibility and replicability study

BackgroundThe availability of reliable biomarkers of Parkinsons disease (PD) progression is critical to the understanding of the disease and development of treatment options. Magnetic Resonance Imaging (MRI) provides a promising source of PD biomarkers, however, neuroimaging results have been shown to be markedly sensitive to analytical conditions and population sampling, which motivates investigations of their robustness. This study is part of a project to investigate the replicability of 11 structural MRI measures of PD identified in a recent review. ObjectiveThis paper attempts to reproduce (similar data, similar analysis) and replicate (variations in data and analysis) the design of the machine learning (ML) model described in [1] to predict PD progression from T1-weighted MRIs. MethodsWe used the Parkinsons Progression Markers Initiative dataset (PPMI, ppmi-info.org) used in [1] and we followed as closely as possible the original methods. We also investigated slight methodological variations in cohort selection, feature extraction, ML model design, and evaluation techniques. ResultsThe Area under the ROC Curve (AUC) achieved by our model closely reproducing the original study remained lower than 0.5. Across all tested models, we obtained a peak AUC of 0.685, which is better than chance performance but remained lower than the AUC value of 0.795 reported in [1]. ConclusionWe managed to train a model that predicts disease progression with a performance better than chance on a cohort extracted from the PPMI dataset, using methods adapted from [1]. However, the performance of this model remains substantially lower than the one reported in [1]. Our difficulties to reproduce or replicate the original work are likely explained by the relatively low sample size in the original study. We provide recommendations on how to improve the reproducibility of MRI-based ML models of PD in the future.

neuroscience↗

bioRxiv2023

Longitudinal brain structure changes in Parkinson's disease: a replication study

ContextAn existing major challenge in Parkinsons disease (PD) research is the identification of biomarkers of disease progression. While Magnetic Resonance Imaging (MRI) is a potential source of PD biomarkers, none of the MRI measures of PD are robust enough to warrant their adoption in clinical research. This study is part of a project that aims to replicate 11 PD studies reviewed in a recent survey (JAMA neurology, 78(10) 2021) to investigate the robustness of PD neuroimaging findings to data and analytical variations. ObjectiveThis study attempts to replicate the results in Hanganu et al. (Brain, 137(4) 2014) using data from the Parkinsons Progression Markers Initiative (PPMI). MethodsUsing 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between MRI structural changes and cognitive decline. We compared our findings to the results in the original study. ResultsSimilarly to the original study, PD patients with mild cognitive impairment (MCI) exhibited increased cortical thinning over time compared to patients without MCI in the right middle temporal gyrus, insula, and precuneus. (2) The rate of cortical thinning in the left inferior temporal and precentral gyri in PD patients correlated with the change in cognitive performance. (3) There were no group differences in the change of subcortical volumes. (4) We did not find a relationship between the change in subcortical volumes and the change in cognitive performance. ConclusionDespite important differences in the dataset used in this replication study, and despite differences in sample size, we were able to partially replicate the original results. We produced a publicly available reproducible notebook allowing researchers to further investigate the reproducibility of the results in Hanganu et al. (2014) when more data becomes available in PPMI.

neuroscience↗

bioRxiv2023

The trade-off between individual metabolic specialization and versatility determines the metabolic efficiency of microbial communities

In microbial systems, a metabolic pathway can be either completed by one autonomous population or alternatively be distributed among a consortium performing metabolic division of labor (MDOL), where several specialized populations cooperate to complete the pathway. MDOL facilitates the systems function by reducing the metabolic burden; however, it may also hinder the function by reducing the exchange efficiency of metabolic intermediates among individuals. As a result, the metabolic efficiency of a community is influenced by trade-offs between the metabolic specialization and versatility of individuals, with the latter potentially introducing metabolic redundancy into the community. However, it remains unclear how metabolic specialization and versatility of the individuals involved can be controlled in order to optimize the function of the community. In this study, we deconstructed the metabolic pathway of naphthalene degradation into four specialized steps and introduced them individually or combinatorically into different strains, with varying levels of metabolic specialization. Using these strains, we engineered 1,456 synthetic consortia with varying levels of metabolic redundancy and tested their naphthalene degradation efficiency. We found that 74 consortia possessing metabolic redundancy exhibited higher degradation efficiency than both the autonomous population and the rigorous MDOL community. Quantitative modeling derived from our experiments provides general strategies for identifying the most effective MDOL consortium with functional redundancy (MCFR) from a range of possible MCFRs. Our large-scale genomic analysis suggests that natural communities for hydrocarbon degradation are mostly functionally redundant. In summary, our study provides critical insights into the engineering of high-performance microbial systems and explains why functional redundancy is prevalent in natural microbial communities.

microbiology↗

bioRxiv2023

Discovery of microRNA-derived RNAs and proteins in human cells

MicroRNAs (miRNAs) are short noncoding RNAs that can regulate gene expression through the binding of their 5-ends to mRNAs. However, the biological effects of miRNA binding via their 3-ends remain unclear. Here, we discover that the exact reverse pairing of the 3-ends of miRNAs or miRNA-like RNAs, collectively termed microsized RNAs (msRNAs), with template RNAs can initiate the production of msRNA-derived RNAs (msdRs), which can subsequently be translated into polypeptides (msdPs). Using 2,632 human msRNAs from miRBase, 11,121 msdRs and 1,239 msdPs were predicted based on a 15-nucleotide pairing threshold, and the presence of representative msdRs and msdPs was confirmed in human cells. Of clinical relevance, msdP0188 is highly expressed in human lung and breast cancers, and its corresponding msRNAs and msdRs represent novel anti-cancer targets. Notably, inhibiting telomerase reverse transcriptase, a putative RNA-dependent RNA polymerase identified by bioinformatic screening, led to reduced levels of msdP0188 in human cancer cells. Our findings reveal a novel "msRNA [->] msdR [->] msdP" axis, expanding the classical central dogma and predicting many previously unrecognized RNAs and polypeptides with potential biological functions in human cells and other systems.

cell biology↗

bioRxiv2023

Gemcitabine plus nab-paclitaxel preserves skeletal and cardiac mass and function in a murine model of pancreatic cancer cachexia

More than 85% of patients with pancreatic ductal adenocarcinoma (PDAC) suffer from cachexia, a debilitating syndrome characterized by the loss of muscle and fat and remains an unmet medical need. While chemotherapy remains an effective treatment option, it can also induce weight and muscle loss in patients with cancer. Gemcitabine combined with nab paclitaxel (GnP) is a first line treatment option for patients with PDAC but GnPs effect on cachexia has not been comprehensively investigated. We interrogated the effects of GnP in a murine model of pancreatic cancer cachexia. Mice were orthotopically implanted with the cachexia inducing pancreatic cell line (KPC) and were administered GnP or vehicle. The controls underwent sham surgery. We defined GnP effects on cachexia and tumor burden by evaluating muscle and cardiac mass and function, fat mass, bone morphometry, and hematology measurements. We completed RNA sequencing and deep proteome profiling in skeletal and cardiac muscle. KPC+GnP reduced tumor burden over 50% and increased survival compared to KPC. KPC vehicle group had more than 15% muscle mass loss and decreased left ventricular mass, this was not present in KPC+GnP when compared to controls. RNA Seq and deep proteomics analyses suggested that muscle and cardiac dysfunction pathways activated in KPC group were either reversed or decreased in KPC+GnP. In all, our data suggests that GnP protects against muscle and cardiac wasting in an experimental model of PDAC cachexia. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/536434v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1d394f7org.highwire.dtl.DTLVardef@1d8fdaforg.highwire.dtl.DTLVardef@f709d4org.highwire.dtl.DTLVardef@a668e0_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

cancer biology↗

bioRxiv2023

PaxDB 5.0: curated protein quantification data suggests adaptive proteome changes

The "Protein Abundances Across Organisms" database (PaxDB) is an integrative meta-resource dedicated to protein abundance levels, in tissue-specific or whole-organism proteomes. PaxDB focuses on computing best-estimate abundances for proteins in normal/healthy contexts, and expresses abundance values for each protein in "parts per million" (ppm) in relation to all other protein molecules in the cell. The uniform data re-processing, quality scoring, and integrated orthology relations have made PaxDB one of the preferred tools for comparisons between individual datasets, tissues or organisms. In describing the latest version 5.0 of PaxDB, we particularly emphasise the data integration from various types of raw data, and how we expanded the number of organisms and tissue groups as well as the proteome coverage. The current collection of PaxDB includes 831 original datasets from 170 species, including 22 Archaea, 81 Bacteria and 67 Eukaryota. Apart from detailing the data update, we also show a comparative analysis of the human proteome subset of PaxDB against the two most widely-used human proteome data resources: Human Protein Atlas (HPA) and Genotype-Tissue Expression (GTEx). Lastly, we present a use case of PaxDB, showing how protein abundance data can be used to study the evolution of relative amino acid usage in Fungi.

bioinformatics↗

bioRxiv2023

Granulins rescue inflammation, lysosome dysfunction, and neuropathology in a mouse model of progranulin deficiency.

Progranulin (PGRN) deficiency is linked to neurodegenerative diseases including frontotemporal dementia, Alzheimers disease, Parkinsons disease, and neuronal ceroid lipofuscinosis. Proper PGRN levels are critical to maintain brain health and neuronal survival, however the function of PGRN is not well understood. PGRN is composed of 7.5 tandem repeat domains, called granulins, and is proteolytically processed into individual granulins inside the lysosome. The neuroprotective effects of full-length PGRN are well-documented, but the role of granulins is still unclear. Here we report, for the first time, that expression of single granulins is sufficient to rescue the full spectrum of disease pathology in mice with complete PGRN deficiency (Grn-/-). Specifically, rAAV delivery of either human granulin-2 or granulin-4 to Grn-/- mouse brain ameliorates lysosome dysfunction, lipid dysregulation, microgliosis, and lipofuscinosis similar to full-length PGRN. These findings support the idea that individual granulins are the functional units of PGRN, likely mediate neuroprotection within the lysosome, and highlight their importance for developing therapeutics to treat FTD-GRN and other neurodegenerative diseases.

neuroscience↗

bioRxiv2023

High-efficiency base editing for Stargardt disease in mice, non-human primates, and human retina tissue

Stargardt disease is a currently untreatable, inherited neurodegenerative disease that leads to macular degeneration and blindness due to loss-of-function mutations in the ABCA4 gene. We have designed a dual adeno-associated viral vector split-intein adenine base-editing strategy to correct the most common mutation in ABCA4 (c.5882G>A, p.G1961E). We optimized ABCA4 base editing in human models, including retinal organoids, iPSC-derived retinal pigment epithelial (RPE) cells, as well as adult human retinal- and RPE/choroid explants in vitro. The resulting gene therapy vectors achieved high levels of gene correction in mutation-carrying mice and in non-human primates, with an average editing of 37% of photoreceptors and 73% of RPE cells in vivo. The high editing rates in primates make way for precise and efficient gene editing in other neurodegenerative ocular diseases.

neuroscience↗

bioRxiv2023

mEMbrain: an interactive deep learning MATLAB tool for connectomic segmentation on commodity desktops

Connectomics is fundamental in propelling our understanding of the nervous systems organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from 4 different animals and 5 datasets, amounting to around 180 hours of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of 4 pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

neuroscience↗

bioRxiv2023

Driving and suppressing the human language network using large language models

Transformer models such as GPT generate human-like language and are highly predictive of human brain responses to language. Here, using fMRI-measured brain responses to 1,000 diverse sentences, we first show that a GPT-based encoding model can predict the magnitude of brain response associated with each sentence. Then, we use the model to identify new sentences that are predicted to drive or suppress responses in the human language network. We show that these model-selected novel sentences indeed strongly drive and suppress activity of human language areas in new individuals. A systematic analysis of the model-selected sentences reveals that surprisal and well-formedness of linguistic input are key determinants of response strength in the language network. These results establish the ability of neural network models to not only mimic human language but also noninvasively control neural activity in higher-level cortical areas, like the language network.

neuroscience↗

bioRxiv2023

Chromosomal instability can favor macrophage-mediated immune response and induce a broad, vaccination-like anti-tumor IgG response

Chromosomal instability (CIN), a state in which cells undergo mitotic aberrations that generate chromosome copy number variations, generates aneuploidy and is thought to drive cancer evolution. Although associated with poor prognosis and reduced immune response, CIN generates aneuploidy-induced stresses that could be exploited for immunotherapies. In such contexts, macrophages and the CD47-SIRP checkpoint are understudied. Here, CIN is induced pharmacologically induced in poorly immunogenic B16F10 mouse melanoma cells, generating persistent micronuclei and diverse aneuploidy while skewing macrophages towards an anti-cancer M1-like phenotype, based on RNA-sequencing profiling, surface marker expression and short-term antitumor studies. These results further translate to in vivo efficacy: Mice bearing CIN-afflicted tumors with wild-type CD47 levels survive only slightly longer relative to chromosomally stable controls, but long-term survival is maximized when combining macrophage-stimulating anti-tumor IgG opsonization and some form of disruption of the CD47-SIRP checkpoint. Survivors make multi-epitope, de novo anti-cancer IgG that promote macrophage-mediated phagocytosis of CD47 knockout B16F10 cells and suppress tumoroids in vitro and growth of tumors in vivo. CIN does not greatly affect the level of the IgG response compared to previous studies but does significantly increase survival. These results highlight an unexpected therapeutic benefit from CIN when paired with maximal macrophage anti-cancer activity: an anti-cancer vaccination-like antibody response that can lead to more durable cures and further potentiate cell-mediated acquired immunity.

cancer biology↗

bioRxiv2023

The novel roles of bovine milk-derived exosomes on skin anti-aging

Exosomes are small vesicles released from cells and present in various mammal biological fluids, such as bovine milk, which worked for skin care for many years besides dairy. In addition, Exosomes were regarded as a vehicle for intercellular communication. Therefore, we aimed to investigate the novel roles of bovine milk-derived exosomes (MK-Exo) on human skin anti-aging. Purified MK-Exo can be directly uptake by the keratinocytes and fibroblast in vitro and upregulate the expression of the natural factors related to skin moisturizing, including Filaggrin (FLG), Aquaporin 3 (AQP3), CD44 in the keratinocytes and hyaluronidase (HAS2) in the fibroblast, and MK-Exo promoted the cell migration of the fibroblast, while rescue its expression of type I collagen (Col I), type III collagen (Col III) after ultraviolet radiation. Furthermore, the phototoxicity test, photoallergy test, repeated skin irritation test, skin allergy test, and patch test confirm the safety of MK-Exo on the skin. Finally, the roles of MK-Exo in preserving moisture and anti-wrinkle were also identified in humans. Then, MK-Exo was smeared on the facial skin of 31 female volunteers twice a day for 28 days, and the functions were evaluated following the safety assessment in vivo. These studies reveal the novel roles of bovine milk-derived exosomes in human skin aging, which opens a new way of skin care.

cell biology↗

bioRxiv2023

The immune receptor SNC1 monitors helper NLRs targeted by a bacterial effector

Plants deploy intracellular receptors to counteract pathogen effectors that suppress cell-surface receptor-mediated immunity. To what extent pathogens manipulate also immunity mediated by intracellular receptors, and how plants tackle such manipulation, remains unknown. Arabidopsis thaliana encodes three very similar ADR1 class helper NLRs (ADR1, ADR1-L1 and ADR1-L2), which play key roles in plant immunity initiated by intracellular receptors. Here, we report that Pseudomonas syringae AvrPtoB, an effector with E3 ligase activity, can suppress ADR1-L1- and ADR1-L2-mediated cell death. ADR1, however, evades such suppression by diversification of two ubiquitination sites targeted by AvrPtoB. The intracellular sensor NLR SNC1 interacts with and guards the CCR domains of ADR1-L1 and ADR-L2. Removal of ADR1-L1 and ADR1-L2 or delivery of AvrPtoB activates SNC1, which then signals through ADR1 to trigger immunity. Our work not only uncovers the long sought-after physiological function of SNC1 in pathogen defense, but also that reveals how plants can use dual strategies, sequence diversification and a multiple layered guard-guardee system, to counteract pathogen attack on core immunity functions.

plant biology↗

bioRxiv2023

Lactococcus G423 Ameliorates the Growth Performance of Broilers by Modulation of Gut Microbiota- Metabolites

This study aimed to explore whether Lactococcus G423 could ameliorate growth performance of broilers by modulation of gut microbiota-metabolites based on the 16S ribosomal RNA (rRNA) and liquid chromatography-mass spectrometry (LC-MS). A total of 640 one-day-old AA broilers were randomly divided into 4 groups (Control (CON), Lac_L, Lac_H, and ABX). Average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR) were calculated on the 42nd day. The ileum content was harvested and immediately frozen in liquid nitrogen for 16S rRNA and LC-MS analyses. Then, the results of 16S rRNA analysis were confirmed by quantitative polymerase chain reaction (qPCR). Compared with the CON group, ADG significantly increased in the Lac_H group (P<0.05), and survival rate significantly decreased in the Lac_H, Lac_H, and ABX groups (all P<0.05). A significant difference in microbial diversity was found among the four groups. Compared with the CON group, the abundance rates of Firmicutes and Lactobacillus in the Lac_H group were significantly risen (P<0.05). The global and overview maps and membrane transport in the Lac_L, Lac_H, and ABX groups significantly changed versus those in the CON group (P<0.05). The results of LC-MS demonstrated that Lactococcus could significantly improve the levels of some metabolites (6-hydroxy-5-methoxyindole glucuronide, 9,10-DiHOME, carbamazepine-O-quinone, N-Acetyl-L-phenylalanine, and kynurenine), and these metabolites were involved in 5 metabolic pathways. Among them, the pathways of linoleic acid metabolism, phenylalanine metabolism, and pentose and glucuronate interconversions significantly changed (P<0.05). Lactococcus improved wight and survival rate of broilers through the gut microbiota, regulating the pathways of amino acid metabolism, lipid metabolism, bile acid metabolism, and carbohydrate metabolism. However, antibiotics may negatively influence the gut microbiota. IMPORTANCEImprovements in the growth rate of broiler chickens can be achieved through dietary manipulation of the naturally occurring bacterial populations while mitigating the withdrawal of antibiotic growth promoters. Lactococcus is industrially crucial lactic acid bacteria, can be incorporated into the diets of chickens to improve their growth performance. This study investigated the key mechanisms behind this progression and pinpointed Lactococcus improved wight and survival rate of broilers through the gut microbiota, regulating the pathways of amino acid metabolism, lipid metabolism, bile acid metabolism, and carbohydrate metabolism.

microbiology↗

bioRxiv2023

Catalytic and non-catalytic mechanisms of histone H4 lysine 20 methyltransferase SUV420H1

The intricate regulation of chromatin plays a key role in controlling genome architecture and accessibility. Histone lysine methyltransferases regulate chromatin by catalyzing the methylation of specific histone residues but are also hypothesized to have equally important non-catalytic roles. SUV420H1 di- and tri-methylates histone H4 lysine 20 (H4K20me2/me3) and plays crucial roles in DNA replication, repair, and heterochromatin formation, and is dysregulated in several cancers. Many of these processes were linked to its catalytic activity. However, deletion and inhibition of SUV420H1 have shown distinct phenotypes suggesting the enzyme likely has uncharacterized non-catalytic activities. To characterize the catalytic and non-catalytic mechanisms SUV420H1 uses to modify chromatin, we determined cryo- EM structures of SUV420H1 complexes with nucleosomes containing histone H2A or its variant H2A.Z. Our structural, biochemical, biophysical, and cellular analyses reveal how both SUV420H1 recognizes its substrate and H2A.Z stimulates its activity, and show that SUV420H1 binding to nucleosomes causes a dramatic detachment of nucleosomal DNA from histone octamer. We hypothesize that this detachment increases DNA accessibility to large macromolecular complexes, a prerequisite for DNA replication and repair. We also show that SUV420H1 can promote chromatin condensates, another non-catalytic role that we speculate is needed for its heterochromatin functions. Together, our studies uncover and characterize the catalytic and non-catalytic mechanisms of SUV420H1, a key histone methyltransferase that plays an essential role in genomic stability.

biochemistry↗

bioRxiv2023

Adjuvant Effects of Amphipathic Helical Peptides

Subunit vaccines are the focus of research in developing new vaccines against infectious diseases. Due to the low immunogenicity of recombinant proteins, adjuvants are required for the activation of humoral and cellular immunity against a protein antigen. In this study, we reported the identification of a novel pathway that can activate humoral immunity against a recombinant protein without inducing inflammatory responses. By fusing an amphipathic helical peptide to GFP, one can increases the immunogenicity of GFP by up to 1000 fold. This enhancement was correlated with the ability of amphipathic helical peptides to bind to cell membranes and cause lysosomal membrane permeabilization. We showed evidence that the amphipathic helical peptide may induce the delivery of antigen across the lysosomal membrane into cytosol. Amphipathic helical peptide fusion provided a new pathway for stimulating immune responses against recombinant proteins.

immunology↗

bioRxiv2023

Correlating physicochemical and biological properties to define critical quality attributes of a recombinant AAV vaccine candidate

Recombinant adeno-associated viruses (rAAVs) are a preferred vector system in clinical gene transfer. A fundamental challenge to formulate and deliver rAAVs as stable and efficacious vaccines is to elucidate interrelationships between the vectors physicochemical properties and biological potency. To this end, we evaluated an rAAV-based COVID-19 vaccine candidate which encodes the Spike antigen (AC3) and is produced by an industrially-compatible process. First, state-of-the-art analytical techniques were employed to determine key structural attributes of AC3 including primary and higher-order structures, particle size, empty/full capsid ratios, aggregates and multi-step thermal degradation pathway analysis. Next, several quantitative potency measures for AC3 were implemented and data were correlated with the physicochemical analyses on thermal-stressed and control samples. Results demonstrate links between decreasing AC3 physical stability profiles, in vitro transduction efficiency in a cell-based assay, and importantly, in vivo immunogenicity in a mouse model. These findings are discussed in the general context of future development of rAAV-based vaccines candidates as well as specifically for the rAAV vaccine application under study.

immunology↗

bioRxiv2023

A rapid, multiplex digital PCR assay for EGFR, KRAS, BRAF, ERBB2 variants and ALK, RET, ROS1, NTRK1 gene fusions in non-small cell lung cancer

Digital PCR (dPCR) is emerging as an ideal platform for the detection and tracking of genomic variants in cancer due to its high sensitivity and simple workflow. The growing number of clinically-actionable cancer biomarkers creates a need for fast, accessible methods that allow for dense information content and high accuracy. Here, we describe a proof-of-concept amplitude modulation based multiplex dPCR assay capable of detecting 12 single nucleotide and indel variants in EGFR, KRAS, BRAF, and ERBB2, 14 gene fusions in ALK, RET, ROS1, NTRK1, and MET exon 14 skipping present in non-small cell lung cancer (NSCLC). We also demonstrate the use of multi-spectral target signal encoding to improve the specificity of variant detection by reducing background noise up to 11-fold. The assay reported an overall 100% PPA and 98.5% NPA compared to a sequencing-based assay in a cohort of 62 human FFPE samples. In addition, the dPCR assay rescued actionable information in 10 samples that failed to sequence, highlighting the utility of a multiplexed digital assay as a potential reflex solution for challenging NSCLC samples.

cancer biology↗