Biology subjects

Maurya, M.

Publications and source records attributed to Maurya, M..

3 recordsLinked to original sources

bioRxiv2026

BiomarkerKB: FAIR and Integrated Biomarker Knowledge Connecting Biomolecular and Clinical Data Types

Biomarkers are essential tools for disease detection, risk assessment, therapeutic monitoring, and precision medicine. However, biomarker data are dispersed across heterogeneous resources, inconsistently reported in the literature, and rarely standardized for computational use. This fragmentation limits reproducibility, cross-study integration, and the discovery of novel biomarker and disease relationships. We developed BiomarkerKB, a knowledgebase designed to harmonize and integrate biomarker information under a standardized data model. The model follows the FDA-NIH BEST biomarker definition and captures both core fields (biomarker entity, disease/condition, exposure agent) and contextual metadata (specimen, biomarker role, evidence, provenance). Biomarker data and related annotations were either curated from publications or collected from public resources (e.g., OpenTargets, GWAS Catalog, ClinVar, CIViC, OncoMX) and were also contributed by the Common Fund Data Coordinating Centers and the Early Detection Research Network (EDRN). Standardization was achieved using ontologies and reference resources such as Disease Ontology, UBERON, UniProtKB, and HUGO Gene Nomenclature Committee (HGNC) gene symbols. BiomarkerKB data were ingested into a Neo4j-based knowledge graph and integrated with the Common Fund Data Ecosystem (CFDE) Knowledge Graph. The initial release of BiomarkerKB contains over 200,000 biomarker-disease associations spanning genes, proteins, metabolites, glycans, and chemical elements. The knowledge graph comprises more than 300,000 nodes and 1.2 million edges, enabling structured exploration of biomarker relationships within CFDE data as demonstrated through the knowledge graph query-based use cases presented in this study. A publicly accessible web portal (https://biomarkerkb.org) provides keyword search, filtering, data downloads, and access to graph visualization to support both researchers and computational analyses. BiomarkerKB addresses a critical gap in biomarker informatics by providing an integrated, FAIR (Findable, Accessible, Interoperable, and Reusable), and unified framework for biomarker knowledge exploration and discovery.

bioinformatics↗

bioRxiv2024

Tumor suppressor NME1/NM23-H1 modulates DNA binding of NF-κB RelA

The dimeric NF-{kappa}B family of transcription factors activates transcription by binding sequence-specifically to DNA response elements known as {kappa}B sites, located within the promoters and enhancers of their target genes. While most NF-{kappa}B remain inactive in the cytoplasm of unstimulated cells, a small amount of RelA, one of its members, persists in the nucleus, ensuring low-level expression of genes essential for homeostasis. Several cofactors have been identified that aid in DNA binding of RelA. In this study, we identify NME1 (nucleoside diphosphate kinase 1) as a cofactor that enhances RelAs ability to bind {kappa}B sites within the promoters of a subset of its target genes, promoting their expression under both unstimulated and stimulated conditions. Depletion of NME1 influences activation or repression of several genes that are unresponsive to TNF, despite containing {kappa}B sites in their promoters but not in clusters. This suggests that clustering of kB sites may be necessary for RelA-dependent transcription complex assembly. NME1 appears to act as a cofactor for other transcription factors to regulate these genes. NME1 does not directly contact {kappa}B DNA but interacts with RelA, with this interaction being further strengthened in the presence of {kappa}B DNA. Notably, NME1 alone has a marginal effect in enhancing RelAs DNA binding, suggesting that NME1 likely cooperate with other cofactors to regulate DNA binding and transcription through RelA. These observations underscore the intricate assembly of transcription complexes centered on NF-{kappa}B.

biochemistry↗

bioRxiv2022

Bcl-xL is a key mediator of apoptosis following KRASG12C inhibition in KRASG12C mutant colorectal cancer.

PurposeNovel covalent inhibitors of KRASG12C have shown limited response rates in KRASG12C mutant (MT) colorectal cancer (CRC) patients. Thus, novel KRASG12C inhibitor combination strategies that can achieve deep and durable responses are needed. Experimental designSmall molecule KRASG12C inhibitors AZ1569 and AZ8037 were employed. To identify novel candidate combination strategies for AZ1569, we performed RNA sequencing, siRNA and high-throughput drug screening. Top hits were validated in a panel of KRASG12CMT CRC cells and in vivo. AZ1569-resistant CRC cells were generated and characterised. ResultsResponse to AZ1569 was heterogeneous across the KRASG12CMT models. AZ1569 was ineffective at inducing apoptosis when used as single-agent or combined with chemotherapy or agents targeting the EGFR/KRAS/AKT axis. Using a systems biology approach, we identified the anti-apoptotic BH3-family member BCL2L1/Bcl-xL as a top hit mediating resistance to AZ1569. Further analyses identified acute increases in the pro-apoptotic protein BIM following AZ1569 treatment. ABT-263 (Navitoclax), a pharmacological Bcl-2 family-inhibitor that blocks the ability of Bcl-xL to bind and inhibit BIM, led to dramatic and universal apoptosis when combined with AZ1569. Furthermore, this combination also resulted in dramatically attenuated tumour growth in KRASG12CMT xenografts. Finally, AZ1569-resistant cells showed amplification of KRASG12C, EphA2/c-MET activation, increased pro-inflammatory chemokine profile and cross-resistance to several targeted agents. Importantly, KRAS amplification and AZ1569-resistance were reversible upon drug withdrawal, arguing strongly for the use of drug holidays in the case of KRAS amplification. ConclusionsCombinatorial targeting of Bcl-xL and KRASG12C is highly effective, suggesting a novel therapeutic strategy for KRAS G12CMT CRC patients.

cancer biology↗