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Biomedical subjects

Jyoti S Choudhary

Publications and source records attributed to Jyoti S Choudhary.

6 recordsLinked to original sources
PubMed2026

Virtual Tumors Enable Prediction of Personalized Therapeutic Combinations for Non-Small Cell Lung Cancer.

UNLABELLED: The disease burden from non-small cell lung cancer (NSCLC) adenocarcinoma is substantial, with a million new cases diagnosed globally each year and a 5-year survival rate of less than 20%. The lack of therapeutic options personalized to individual patients leads to high variation in survival. The combination of patient stratification with personalized treatment has the potential to improve outcomes; however, the variation in mutations found in patients with NSCLC adenocarcinoma makes experimentally determining treatment combinations time-consuming and expensive. In this study, we developed an interpretable mechanistic model to decipher complex signaling interplay and guide personalized therapy in NSCLC adenocarcinoma. This "virtual tumor" model encompassed key tumor-intrinsic oncogenic signaling pathways for efficiently predicting rational drug-drug and drug-radiotherapy combination therapies in NSCLC. Diverse genetic profiles were simulated for testing more than 10,000 therapeutic strategies to identify optimal approaches to overcome resistance mechanisms specific to genetic profiles and p53 status. The virtual tumor model reproduced drug additivity screens, predicted radiosensitizing genes validated in a CRISPR screen, and identified 53BP1 as a potential drug target that improved the therapeutic window during radiotherapy. A 19-gene signature derived from the virtual tumor framework stratified patients most likely to benefit from radiotherapy, which was validated using The Cancer Genome Atlas (TCGA) data. These results show the utility of virtual tumors to predict effective therapeutic combinations and present a computational resource for large-scale screening of personalized therapies to guide clinical decision-making in patients with NSCLC. SIGNIFICANCE: A computational framework that simulates thousands of personalized treatment strategies offers a scalable, cost-effective way to tailor therapies and improve outcomes for patients with genetically diverse NSCLC.

Humans↗
PubMed2026

Expanding the human proteome with microproteins and peptideins.

A major scientific drive is to characterize the protein-coding genome, which is a primary basis for studying human health. But the fundamental question remains of what has been missed in previous analyses. Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states1-3, with major implications for biomedical science. However, a key gap in knowledge has been which ncORFs produce small microproteins or alternative protein molecules that contribute to the human proteome. Here we report the collaborative efforts of the TransCODE Consortium4 to produce a consensus landscape of protein-level evidence for ncORFs. We show that about 25% of a set of 7,264 ncORFs gives rise to detectable peptides in a large-scale analysis of 95,520 proteomics experiments. We develop an annotation framework for ncORF-encoded microproteins as human proteins and codify the new conceptual model of 'peptideins' as microproteins that have indeterminate potential as functional proteins. To probe the biological implications of peptideins, we create an evolutionary analysis approach, termed ORF relative branch length (ORBL), and determine that evolutionary constraint is common and associates with observation of ncORF-derived peptides. We then characterize a pan-essential cellular phenotype for one peptidein from the OLMALINC long non-coding RNA. Overall, we generate public research tools supported by GENCODE and PeptideAtlas and advance biomedical discovery for understudied components of the human proteome.

Humans↗
PubMed2006

Molecular characterization and comparison of the components and multiprotein complexes in the postsynaptic proteome.

Characterization of the composition of the postsynaptic proteome (PSP) provides a framework for understanding the overall organization and function of the synapse in normal and pathological conditions. We have identified 698 proteins from the postsynaptic terminal of mouse CNS synapses using a series of purification strategies and analysis by liquid chromatography tandem mass spectrometry and large-scale immunoblotting. Some 620 proteins were found in purified postsynaptic densities (PSDs), nine in AMPA-receptor immuno-purifications, 100 in isolates using an antibody against the NMDA receptor subunit NR1, and 170 by peptide-affinity purification of complexes with the C-terminus of NR2B. Together, the NR1 and NR2B complexes contain 186 proteins, collectively referred to as membrane-associated guanylate kinase-associated signalling complexes. We extracted data from six other synapse proteome experiments and combined these with our data to provide a consensus on the composition of the PSP. In total, 1124 proteins are present in the PSP, of which 466 were validated by their detection in two or more studies, forming what we have designated the Consensus PSD. These synapse proteome data sets offer a basis for future research in synaptic biology and will provide useful information in brain disease and mental disorder studies.

Animals↗
PubMed2005

Robust enrichment of phosphorylated species in complex mixtures by sequential protein and peptide metal-affinity chromatography and analysis by tandem mass spectrometry.

Reversible protein phosphorylation mediated by kinases, phosphatases, and regulatory molecules is an essential mechanism of signal transduction in living cells. Although phosphorylation is the most intensively studied of the several hundred known posttranslational modifications on proteins, until recently the rate of identification of phosphorylation sites has remained low. The use of tandem mass spectrometry has greatly accelerated the identification of phosphorylation sites, although progress was limited by difficulties in phosphoresidue enrichment techniques. We have improved upon existing immobilized metal-affinity chromatography (IMAC) techniques for capturing phosphopeptides, to selectively purify phosphoproteins from complex mixtures. Combinations of phosphoprotein and phosphopeptide enrichment were more effective than current single phosphopeptide purification approaches. We have also implemented iterative mass spectrometry-based scanning techniques to improve detection of phosphorylated peptides in these enriched samples. Here, we provide detailed instructions for implementing and validating these methods together with analysis by tandem mass spectrometry for the study of phosphorylation at the mammalian synapse. This strategy should be widely applicable to the characterization of protein phosphorylation in diverse tissues, organelles, and in cell culture.

Animals↗
PubMed2004

Proteomic analysis of in vivo phosphorylated synaptic proteins.

In the nervous system, protein phosphorylation is an essential feature of synaptic function. Although protein phosphorylation is known to be important for many synaptic processes and in disease, little is known about global phosphorylation of synaptic proteins. Heterogeneity and low abundance make protein phosphorylation analysis difficult, particularly for mammalian tissue samples. Using a new approach, combining both protein and peptide immobilized metal affinity chromatography and mass spectrometry data acquisition strategies, we have produced the first large scale map of the mouse synapse phosphoproteome. We report over 650 phosphorylation events corresponding to 331 sites (289 have been unambiguously assigned), 92% of which are novel. These represent 79 proteins, half of which are novel phosphoproteins, and include several highly phosphorylated proteins such as MAP1B (33 sites) and Bassoon (30 sites). An additional 149 candidate phosphoproteins were identified by profiling the composition of the protein immobilized metal affinity chromatography enrichment. All major synaptic protein classes were observed, including components of important pre- and postsynaptic complexes as well as low abundance signaling proteins. Bioinformatic and in vitro phosphorylation assays of peptide arrays suggest that a small number of kinases phosphorylate many proteins and that each substrate is phosphorylated by many kinases. These data substantially increase existing knowledge of synapse protein phosphorylation and support a model where the synapse phosphoproteome is functionally organized into a highly interconnected signaling network.

Animals↗