Biomedical subjects

Matthew D Wilkerson

Publications and source records attributed to Matthew D Wilkerson.

6 recordsLinked to original sources

PubMed2026

HRAS promotes mutant NRAS-driven transformation with codon and allele specificity.

Wild-type RAS family members determine the signaling and therapeutic response in cancers driven by mutant HRAS and KRAS because they activate alternate RAS effector pathways. Here, we found that the requirement for wild-type RAS to support mutant NRAS-driven transformation correlated with codon-specific differences in GTP hydrolysis. NRAS with mutations at either Gly12 (G12X) or Gly13 (G13X), which retained the GDP-GTP cycling function, had modest autonomous transforming potential. In contrast, NRAS with GTP-locking mutations at Gln61 (Q61X mutants) was uncoupled from receptor tyrosine kinase (RTK) input, rendering wild-type RAS an obligate partner for RTK-stimulated signaling and oncogenesis. In RASless cells expressing mutant NRAS, reintroduction of wild-type HRAS was sufficient to restore signaling and transformation. Global dependency mapping in human cancer cells revealed functional partitioning, wherein mutant NRAS promoted MAPK signaling and wild-type HRAS promoted PI3K-AKT survival signaling. Consequently, allele-specific or pan-RAS(ON) inhibitors synergized with inhibitors of proximal RTK signaling or of wild-type HRAS or KRAS to overcome this signaling plasticity. Pan-RAS(ON) and HRAS inhibition was synergistic for all NRAS mutants tested, with Q61X mutants showing greater sensitivity. These findings define the signaling partnership between mutant NRAS and wild-type HRAS as a targetable vulnerability and provide a biochemical blueprint for dual RAS inhibition in NRAS-mutated malignancies.

Humans↗

PubMed2026

RAS signaling in lung adenocarcinoma is defined by lineage context and DUSP4 loss.

BACKGROUNDThe molecular landscape of lung adenocarcinoma (LUAD) is often illustrated as a driver-oncogene pie chart, but identical mutations exhibit heterogeneous signaling shaped by comutations, transcriptional programs, and lineage context. We propose a lineage-integrated signaling framework using an EGFR mutation signature (mSig).METHODSWe defined EGFR mSig using differentially expressed genes in EGFR-mutant (EGFR-mt) LUADs. Semisupervised clustering and machine learning models were used to test reproducibility in different combinations of datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and EGFR copy number alterations in EGFR mSig-defined subtypes of LUAD.RESULTSEGFR mSig showed robust classification performance (area under receiver operating characteristic curve = 0.83-0.95; mean negative predictive value = 96.3%). Validated gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. Most EGFR mSig+ tumors, including many without EGFR mutations, belonged to the bronchioid subtype. A subset of canonical RAS mutations were mSig+ and mirrored the EGFR mutation pattern. EGFR WT/mSig- tumors were enriched for nonbronchioid subtypes and had comutations in TP53 or RAS/RAF/RTKs. We highlight a parsimonious collection of coordinated mutations, including RAS, KEAP1, STK11, TP53, and CDKN2A, that taken together suggest coordination of tumor signaling previously suggested but now reproduced and expanded.CONCLUSIONA potentially novel EGFR mSig that captures the transcriptional footprint of EGFR activation revealed a subset of EGFR WT LUADs with mt-like features. mSig refines LUAD taxonomy beyond mutation-only pie-chart models by incorporating lineage and comutation context. Lineage-directed stratification with coalteration identifies clinically relevant groups across EGFR and RAS states and highlights treatment opportunities for patients currently considered oncogene-negative.FUNDINGNational Cancer Institute (NCI) U01CA272541, R01CA262296, U24CA264021, UG1CA233333, R01CA211939.

Humans↗

PubMed2006

xGDB: open-source computational infrastructure for the integrated evaluation and analysis of genome features.

The eXtensible Genome Data Broker (xGDB) provides a software infrastructure consisting of integrated tools for the storage, display, and analysis of genome features in their genomic context. Common features include gene structure annotations, spliced alignments, mapping of repetitive sequence, and microarray probes, but the software supports inclusion of any property that can be associated with a genomic location. The xGDB distribution and user support utilities are available online at the xGDB project website, http://xgdb.sourceforge.net/.

Arabidopsis↗

PubMed2006

yrGATE: a web-based gene-structure annotation tool for the identification and dissemination of eukaryotic genes.

Your Gene structure Annotation Tool for Eukaryotes (yrGATE) provides an Annotation Tool and Community Utilities for worldwide web-based community genome and gene annotation. Annotators can evaluate gene structure evidence derived from multiple sources to create gene structure annotations. Administrators regulate the acceptance of annotations into published gene sets. yrGATE is designed to facilitate rapid and accurate annotation of emerging genomes as well as to confirm, refine, or correct currently published annotations. yrGATE is highly portable and supports different standard input and output formats. The yrGATE software and usage cases are available at http://www.plantgdb.org/prj/yrGATE.

DNA, Complementary↗

PubMed2005

Community-based gene structure annotation.

Uncertainty and inconsistency of gene structure annotation remain limitations on research in the genome era, frustrating both biologists and bioinformaticians, who have to sort out annotation errors for their genes of interest or to generate trustworthy datasets for algorithmic development. It is unrealistic to hope for better software solutions in the near future that would solve all the problems. The issue is all the more urgent with more species being sequenced and analyzed by comparative genomics - erroneous annotations could easily propagate, whereas correct annotations in one species will greatly facilitate annotation of novel genomes. We propose a dynamic, economically feasible solution to the annotation predicament: broad-based, web-technology-enabled community annotation, a prototype of which is now in use for Arabidopsis.

Arabidopsis↗

PubMed2005

Comparative plant genomics resources at PlantGDB.

PlantGDB (http://www.plantgdb.org/) is a database of plant molecular sequences. Expressed sequence tag (EST) sequences are assembled into contigs that represent tentative unique genes. EST contigs are functionally annotated with information derived from known protein sequences that are highly similar to the putative translation products. Tentative Gene Ontology terms are assigned to match those of the similar sequences identified. Genome survey sequences are assembled similarly. The resulting genome survey sequence contigs are matched to ESTs and conserved protein homologs to identify putative full-length open reading frame-containing genes, which are subsequently provisionally classified according to established gene family designations. For Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), the exon-intron boundaries for gene structures are annotated by spliced alignment of ESTs and full-length cDNAs to their respective complete genome sequences. Unique genome browsers have been developed to present all available EST and cDNA evidence for current transcript models (for Arabidopsis, see the AtGDB site at http://www.plantgdb.org/AtGDB/; for rice, see the OsGDB site at http://www.plantgdb.org/OsGDB/). In addition, a number of bioinformatic tools have been integrated at PlantGDB that enable researchers to carry out sequence analyses on-site using both their own data and data residing within the database.

Computational Biology↗