Biology subjects

George, L. S.

Publications and source records attributed to George, L. S..

3 recordsLinked to original sources

bioRxiv2025

BC-Predict Database: A Curated Resource of Experimentally Validated Markers in Multidrug Resistance in Breast Cancer

BackgroundIn this study, we aim to develop a yearly updatable database that could predict chemotherapeutic drug resistance and overall survival probability in breast cancer patients. Existing drug sensitivity databases depend on correlation-based predictions. In our study, candidates involved in drug resistance are chosen based on cell line validation (overexpression or downregulation or inhibition of candidates) studies, curated manually. Method28,773 mRNA expression signatures from 914 breast cancer patients were extracted from cProsite. 106 of these patients had clinical information and log2 fold change information required for this study. We categorized these patients into deceased and surviving groups from TCGA. To prepare a database that can predict drug resistance and overall survival, we included mRNAs that were over-expressed in at least 80% of the breast cancer patients and mRNAs over-expressed in deceased and surviving groups. In addition, we also reported breast cancer-associated drug resistance candidates which have been reported in cell-line based studies. The database matrix preparation involved an approximate of 15000 manual searches of cell validated studies. (750 candidates x 20 drugs). The database was validated using a publicly available breast cancer patient proteomics data. ResultsOur analysis identified a list of top priority candidates associated with multidrug resistance, categorized based on their resistance to >15 drugs, 5-15 drugs, and 2-4 drugs. Analysis of patient profiles in the database revealed that the number of proteins contributing to drug resistance was high in the poor prognosis category compared to the good prognosis category. ConclusionsOur study highlights the probable gaps in breast cancer drug resistance research, as only a small subset of overexpressed mRNA candidates found in patients are studied in vitro or in vivo experiments focusing on drug resistance. We also identified candidates involved in multidrug resistance, whose role in drug resistance has not been studied in more than 15 drugs. After further validations, this will benefit the clinicians and upcoming CRISPR gene therapeutics.

cancer biology↗

bioRxiv2024

Interferonγ and IL-27 positively regulate type 1 regulatory T-cell development during adaptive tolerance

Strong T-cell receptor (TCR) and IL-27 signalling influence type-1 regulatory (Tr1) T-cell development but whether other signals determine their differentiation is unclear. Utilising Tg4 TCR transgenic mice we established a model for rapid Tr1 cell induction. A single high dose of [4Y]-MBP peptide drove the differentiation of Il10+ T-cells with bona fide Tr1 cell protein and mRNA signatures. Kinetic transcriptional analysis revealed that the Tr1 cell module was transient and preceded by a burst of Ifng transcription in CD4+ T-cells. Neutralisation of IFN{gamma} reduced Tr1 cell frequency and strong TCR signalling markers, which was correlated with reduced macrophage activation. Antibody depletion experiments inferred that T-cells - but not NK cells - provided the relevant source of IFN{gamma}. Additionally, we show that blocking IL-27 in combination with IFN{gamma} neutralisation additively reduced Tr1 cell frequency in vivo. These findings reveal that during strong tolerogenic TCR signalling IFN-{gamma} has a non-redundant regulatory role in augmenting the differentiation of Tr1 cells in vivo.

immunology↗

bioRxiv2024

Lag3 and PD-L1 govern T cell receptor signal duration in adaptively tolerised CD4+ T cells

Lag3 and PD-1 are immune checkpoints that regulate T cell responses and are current immunotherapy targets. Yet how they function to control early CD4+ T cell activation remains unclear. Here, we show that the PD-1 and Lag3 pathways exhibit layered control of the early CD4+ T cell activation process, with the effects of Lag3 more pronounced in the presence of PD-1 pathway co-blockade (CB). RNA-sequencing revealed that CB drove an early NFAT-dependent transcriptional profile, including promotion of ICOShi T follicular helper (Tfh) cell differentiation. NFAT pathway inhibition abolished CB-induced upregulation of NFAT-dependent co-receptors ICOS and OX40, whilst unaffecting the NFAT-independent gene Nr4a1. Mechanistically, Lag3 and PD-1 pathways functioned additively to regulate the duration of T cell receptor (TCR) signals during CD4+ T cell re-activation. Our data therefore reveal that PD-1 and Lag3 pathways converge to additively regulate TCR signal duration and NFAT-dependent transcriptional activity during early CD4+ T cell re-activation. HighlightsO_LIPD-1 and Lag3 pathways exhibit layered control of early CD4+ T cell activation C_LIO_LITheir co-blockade enhances NFAT-dependent TCR transcriptional programmes C_LIO_LIInhibition of NFAT signalling reverses the functional effects of PD-1 and Lag3 co-blockade C_LIO_LIMechanistically, PD-1 and Lag3 function to additively regulate TCR signal duration during re-activation of CD4+ T cells C_LI

immunology↗