Biology subjects

Vasaikar, S. V.

Publications and source records attributed to Vasaikar, S. V..

6 recordsLinked to original sources

bioRxiv2024

Patient-Derived Xenografts of Triple-Negative Breast Cancer Enable Deconvolution and Prediction of Chemotherapy Responses

Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significanceIntegration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

cancer biology↗

bioRxiv2022

PALMO: a comprehensive platform for analyzing longitudinal multi-omics data

Longitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its many intrinsic types of variations. We present PALMO (https://github.com/aifimmunology/PALMO), a platform that contains five analytical modules to examine longitudinal bulk and single-cell multi-omics data from multiple perspectives, including decomposition of sources of variations within the data, collection of stable or variable features across timepoints and participants, identification of up- or down-regulated markers across timepoints of individual participants, and investigation on samples of same participants for possible outlier events. We tested PALMO performance on a complex longitudinal multi-omics dataset of five data modalities on the same samples and six external datasets of diverse background. Both PALMO and our longitudinal multi-omics dataset can be valuable resources to the scientific community.

immunology↗

bioRxiv2022

Distinct Heterogeneity in the Naive T cell Compartments of Children and Adults

AbstractThe naive T cell compartment undergoes multiple changes across age that associate with altered susceptibility to infection and autoimmunity. In addition to the acquisition of naive-like memory T cell subsets, mouse studies describe substantial molecular reprogramming of the naive compartment in adults compared with adolescents. However, these alterations are not well delineated in human aging. Using a new trimodal single cell technology (TEA-seq), we discovered that the composition and transcriptional and epigenetic programming of the naive T cell compartment in children (11-13 yrs) is distinct from that of older adults (55-65 yrs). Naive CD4 T cells, previously considered relatively resistant to aging, exhibited far more pronounced molecular reprogramming than naive CD8 T cells, in which alterations are preferentially driven by shifts in naive-like memory subsets. These data reveal the complex nature of the naive T cell compartment that may contribute to differential immune responses across the spectrum of human age. One Sentence SummaryThe naive CD8 and CD4 T cell compartments in humans are heterogeneous and impacted differently with age, in which naive CD8 T cell subsets dramatically shift in composition and true naive CD4 T cells display significant molecular re-programming.

immunology↗

bioRxiv2022

Persistent serum protein signatures define an inflammatory subset of long COVID

Long COVID or post-acute sequelae of SARS-CoV-2 (PASC) is a clinical syndrome featuring diverse symptoms that can persist for months after acute SARS-CoV-2 infection. The etiologies are unknown but may include persistent inflammation, unresolved tissue damage, or delayed clearance of viral protein or RNA. Attempts to classify subsets of PASC by symptoms alone have been unsuccessful. To molecularly define PASC, we evaluated the serum proteome in longitudinal samples from 55 PASC individuals with symptoms lasting [≥]60 days after onset of acute infection and compared this to symptomatically recovered SARS-CoV-2 infected and uninfected individuals. We identified subsets of PASC with distinct signatures of persistent inflammation. Type II interferon signaling and canonical NF-{kappa}B signaling (particularly associated with TNF), were the most differentially enriched pathways. These findings help to resolve the heterogeneity of PASC, identify patients with molecular evidence of persistent inflammation, and highlight dominant pathways that may have diagnostic or therapeutic relevance. One Sentence SummarySerum proteome profiling identifies subsets of long COVID patients with evidence of persistent inflammation including key immune signaling pathways that may be amenable to therapeutic intervention.

immunology↗

bioRxiv2021

Acquisition of cancer stem cell properties during EMT requires cell division

Cancer cells acquire stem cell and mesenchymal properties during epithelial-to-mesenchymal transition (EMT), facilitating metastasis and chemoresistance [1-6]. In this study, we find that mammary epithelial cells quickly develop mesenchymal phenotype in response to EMT-inducing signals; however, acquiring stemness takes several days and always requires a preceding mesenchymal program. In addition, we observe that carcinoma cells, over a period of time, switch their cell division from symmetrical differentiated type to symmetrical self-renewal type. Importantly, epithelial cells can gain mesenchymal properties without undergoing cell division, but cell disivion is vital for these cells to gain stem cell properties during EMT. The EMT-induced stemness signature (SC-sig) is capable of predicting progression-free and overall-survival of breast cancer patients but not the EMT-induced mesenchymal signature (M-sig). Collectively, our findings demonstrate that the use of mesenchymal markers alone is insufficient to identify tumors with metastatic and chemoresistance potential and emphasize that the markers of EMT-induced stem cell program are central for clinical prediction. Most importantly, our data, for the first time, demonstrate that acquisition of stem cell properties during EMT depends on cell division but not the mesenchymal program.

cell biology↗

bioRxiv2021

Longitudinal immune dynamics of mild COVID-19 define signatures of recovery and persistence

SARS-CoV-2 has infected over 200 million and caused more than 4 million deaths to date. Most individuals (>80%) have mild symptoms and recover in the outpatient setting, but detailed studies of immune responses have focused primarily on moderate to severe COVID-19. We deeply profiled the longitudinal immune response in individuals with mild COVID-19 beginning with early time points post-infection (1-15 days) and proceeding through convalescence to >100 days after symptom onset. We correlated data from single cell analyses of peripheral blood cells, serum proteomics, virus-specific cellular and humoral immune responses, and clinical metadata. Acute infection was characterized by vigorous coordinated innate and adaptive immune activation that differed in character by age (young vs. old). We then characterized signals associated with recovery and convalescence to define and validate a new signature of inflammatory cytokines, gene expression, and chromatin accessibility that persists in individuals with post-acute sequelae of SARS-CoV-2 infection (PASC).

immunology↗