Biology subjects

Tewari, A.

Publications and source records attributed to Tewari, A..

8 recordsLinked to original sources

bioRxiv2025

High-Fidelity Tuning of Olfactory Mixture Distances in the Perceptual Space of Smell Through a Community Effort

A central goal in sensory science is to establish quantitative mappings between physical stimuli and perceptual responses. While such mappings are well characterized in vision and audition, they remain poorly defined in olfaction, limiting progress toward understanding the representations of smell. Predicting perceptual similarity between odor mixtures offers a promising route to formalize these relationships. To advance this effort, the DREAM (Dialogue for Reverse Engineering Assessment and Methods) Olfactory Mixtures Prediction Challenge assembled a curated, cross-study dataset describing the similarity of 507 mixture pairs and an unpublished test set of 46 mixture pairs. Teams competed to predict the perceptual similarity of mixture pairs, and then collaborated post-challenge to create an ensemble combining top-performing models that notably improves predictions over the existing state-of-the-art models. Moreover, ensemble model maintains high predictive accuracy in novel validation set. Our model provides a reproducible framework for neuroscientists, chemists, and engineers to compare odor mixtures and provides a foundation for future efforts towards better understanding the olfactory properties of mixtures.

neuroscience↗

bioRxiv2023

Transcriptional regulation of Dyskerin via canonical WNT signaling modulates sphingolipid biosynthesis and drives colorectal cancer.

Targeting EGFR has been effective in RAS/RAF wild-type colorectal cancer (CRC) patients. However, residual tumor relapses, necessitating the importance of biomarker-guided novel therapeutics. We show elevated DKC1 in [~]88% of CRC patients with poor recurrence-free survival. Clinically, DKC1-positive patients exhibit similarity with CMS2 class, the canonical subtype with active WNT signaling. We show functional significance of DKC1 in cell proliferation, stemness, DNA repair, and survival. Further, mice bearing DKC1 knockdown xenografts show [~]81% reduction in tumor burden. Mechanistically, WNT/{beta}-catenin signaling orchestrates DKC1 expression, then, DKC1/SOX2 complex regulates SGPP2, modulating sphingolipids metabolism. Downregulation of DKC1 in CRC lead to reduced SGPP2 levels leading to dysregulation of sphingolipid biosynthesis. Of note, DKC1-high CRC patients show accumulation of ceramides, namely C23 and C24, signifying their utility in diagnosis. Collectively, we delineate the mechanistic circuitry involved in DKC1-mediated CRC progression, propose ceramides as biomarker, and underscore WNT-based therapeutics for DKC1-positive patients.

cancer biology↗

bioRxiv2021

Extracellular Vesicles Carry Distinct Proteo-Transcriptomic Signatures That are Different from Their Cancer Cell of Origin

Circulating extracellular vesicles (EVs) contain molecular footprints from their cell of origin and may provide potential non-invasive access for detection, characterization, and monitoring of numerous diseases. Despite their growing promise, the integrated proteo-transcriptomic landscape of EVs and their donor cells remain poorly understood. To assess their cargo, we conducted small RNA sequencing and mass spectrometry (LC-MS/MS) of EVs isolated from in vitro cancer cell culture and prostate cancer patients serum. Here, we report that EVs enrich for distinct molecular cargo, and their proteo-transcriptome is predominantly different from their cancer cell of origin, implicating a coordinated disposal and delivery mechanism. We have discovered that EVs package their cargo in a non-random fusion, as their most enriched RNAs and proteins are not the most abundant cargo from their donor cells. We show that EVs enrich for 4 times more cytoskeletal and 2 times extracellular proteins than their donor cells. While the donor cells carry 10 times more mitochondrial and 3 times nuclear proteins than their EVs. EVs predominantly (40-60%) enrich for small RNA (~15-200 nucleotides) molecules that implicate cell differentiation, development, and signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched of RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2), implicating an interrelated mechanism that may protect and regulate transcripts until a biological function is achieved. Based on these results, we envision that the next-generation clinical assays will take an integrative multi-omic (proteomic and transcriptomic) approach for liquid biopsy in numerous diseases.

bioinformatics↗

bioRxiv2020

Prioritization prostate cancer to immune checkpoint therapy by ranking tumors along IFN-γ axis and identification of immune resistance mechanisms

We propose priotirization of prostate cancer patients to PD-L1 checkpoint therapy by assessing activity of IFN-{gamma}/PD-L1 signaling in tumor from transcriptional profile. To this end, we introduced a new approach for inferring pathway activity and suppression (IPAS) by assessing significance of positioning pathways genes expression levels at top (activation) or bottom (suppression) in gene expression profile of a given tumor. By ordering tumors along IFN-{gamma}/PD-L1 axis, we determined distinct "IFN-{gamma}-depleted" and "IFN-{gamma}-enriched" immune subtypes, genes involved in immune evasion and potential targets for combination therapy. Using IPAS scoring method, we proposed biomarker panels for accurate ranking tumors along IFN-{gamma}/PD-L1 axis.

bioinformatics↗

bioRxiv2020

A critical role for B cells in cancer immune surveillance

It is commonly believed that B cells play no role in cancer immune surveillance. However, this conclusion is based on studies using only a single B cell-deficient mouse strain, muMT mice, which does not show increased tumorigenesis compared with wild-type (WT) mice. In this study, we demonstrate a critical role for B cells in anti-tumor immunity and identify the cellular mechanisms that make muMT mice a special case. First, we replicate previous findings using a melanoma model in muMT mice. Then, we show that in muMT mice, B-cell deficiency is compensated for by a significant increase in another potent anti-tumor cell type, Type-1 interferon (IFN I)-producing plasmacytoid DCs (pDCs), resulting in normative anti-tumor responses. Depleting pDCs in muMT mice resulted in a significant increase in tumor size and burden. Conversely, adoptive transfer of antibodies from naive WT serum into pDC-depleted muMT mice significantly decreased the tumor load to WT levels. Additionally, a B cell antibody repertoire-deficient mouse strain, IghelMD4 mice, showed a 3-fold increase in tumors relative to WT mice. Overall, these findings indicate the need for a diverse antibody repertoire for early neoplastic cell recognition and the critical role B cells play in anti-cancer immunity.

cancer biology↗

bioRxiv2020

Subtype Heterogeneity and Epigenetic Convergence in Neuroendocrine Prostate Cancer

Neuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyzed cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single cell analysis of human clinical samples exhibit a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy.

cancer biology↗

bioRxiv2020

Unannotated small RNA clusters in circulating extracellular vesicles detect early stage liver cancer

BackgroundHepatocellular carcinoma (HCC) is among the deadliest malignancies and surveillance tools for early detection are suboptimal. Extracellular vesicles (EVs) have gained increasing scientific interest due to their involvement in tumor initiation and metastasis, however, most extracellular RNA (exRNA) biomarker studies are limited to annotated genomic regions. MethodsEVs were isolated with ultracentrifugation and nanoDLD and quality assessed by electron microscopy, immunoblotting, nanoparticle tracking, and deconvolution analysis. We performed genome-wide small exRNA sequencing, including unannotated transcripts. We identified small RNA clusters (smRCs) and delineated their key genomic features across biospecimens (blood, urine, tissue) and EV isolation techniques. A 3-smRC signature for early HCC detection was trained and validated in two independent cohorts. ResultsEV-derived smRCs were dominated by uncharacterized, unannotated small RNA and uniformly tiled across the genome with a consensus sequence of 20bp. A 3-smRC signature was significantly overexpressed in circulating EVs of HCC patients compared to controls at risk or patients with non-HCC malignancies (p<0.01, n=157). An independent validation in a phase 2 biomarker study revealed 86% sensitivity and 91% specificity for the detection of early HCC from controls at risk (i.e. cirrhosis or chronic liver disease, n=209) (positive predictive value (PPV): 89%, area under the ROC curve [AUC]: 0.87). The 3-smRC signature was independent of alpha-fetoprotein (p<0.0001) and a composite model yielded an increased AUC of 0.93 (sensitivity: 85%, specificity: 94%, PPV: 95%). ConclusionAn exRNA-based 3-smRC signature from plasma detects early stage HCC, which directly leads to the prospect of a minimally-invasive, blood-only, operator-independent surveillance biomarker. One sentence summaryWe employ a novel, data-driven approach to identify and characterize small RNA clusters from unannotated loci in extracellular vesicle-derived RNA across different cancer types, isolation techniques, and biofluids, facilitating discovery of a robust biomarker for detection of early stage liver cancer.

cancer biology↗

bioRxiv2020

Human and mouse transcriptome profiling identifies cross-species homology in pulmonary and lymph node mononuclear phagocytes

The mononuclear phagocyte (MP) system consists of macrophages, monocytes, and dendritic cells (DCs). MP subtypes play distinct functional roles in steady state and inflammatory conditions. Though murine MPs are well characterized, their pulmonary and lymph node (LN) human homologs remain poorly understood. To address this gap, we created a gene expression compendium across 15 distinct human and 9 distinct murine MPs from lung, LN, blood, and spleen. Human blood MPs and murine spleen MPs served as validation datasets, as the human-mouse MP homologs are relatively well-defined in these tissues. In-depth RNA sequencing identified corresponding human-mouse MP subtypes and determined marker genes shared and divergent across between species counterparts. Unexpectedly, at the gene expression level, only 13-23% of the top 1000 marker genes (i.e., genes not shared across species-specific MP subtypes) overlapped in corresponding human-mouse MP counterparts, indicating a need for caution when translating mouse studies to human gene targets and functions. Lastly, CD88 was useful in both species to distinguish macrophage and tissue monocytes from DCs. Our cross-species gene expression compendium serves as a resource for future translational studies to investigate beforehand whether pursuing specific MP subtypes, or genes will prove fruitful.

immunology↗