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Biology subjects

Sawant, V.

Publications and source records attributed to Sawant, V..

2 recordsLinked to original sources

IL-17A potentiates malignant T-cell viability via electron transport chain complex I in cutaneous T-cell lymphoma

Cutaneous T-cell lymphoma (CTCL) is a rare malignancy of skin-resident T cells characterized by an aberrant cytokine profile, notably elevated Interleukin-17A (IL-17A) levels. However, the functional importance of IL-17A dysregulation in the CTCL pathogenesis remains poorly understood. Our analysis revealed increased IL-17A receptor (IL-17RA) expression in CTCL patient samples, supporting the importance of IL-17A signaling in CTCL progression. Proteomic and metabolomic profiling of IL-17A-treated malignant T cells revealed mitochondrial electron transport chain (ETC) complex I as a key downstream target of IL-17A signaling. Furthermore, we confirmed the elevated expression of ETC complex I in CTCL patient samples compared to healthy control T cells, hence highlighting the clinical relevance of the IL-17A signaling-ETC complex 1 axis. Altogether, our data unveil the function of IL-17A signaling in the metabolic axis in CTCL progression, which could be useful for developing advanced therapeutic strategies. Significance statement: We uncover an IL-17A-induced electron transport chain (ETC) complex I pro-tumorigenic circuit and provide proof of concept evidence that ETC complex I can be targeted to combat the challenges posed by Cutaneous T-cell Lymphoma aggressiveness.

cancer biology↗

Application of spatial transcriptomics across organoids: a high-resolution spatial whole-transcriptome benchmarking dataset

Stem cell-derived organoids hold promise to model tissue-specific disease. To enable this, it is crucial to assess how transcriptional signatures, cellular organisation and composition of organoids compare to in vivo counterparts. However, technologies which elucidate regional molecular identity, like spatial transcriptomics, have been challenging to apply to organoids. This study presents the first systematic profiling of multiple stem cell derived organoid models (brain, heart muscle, heart valve, kidney, lung, cartilage, and haematopoietic) with Stereo-seq, a full transcriptome, spatial transcriptomics assay using on-chip in situ RNA capture at subcellular resolution. It describes optimisation of this assay to characterise organoids, use of multiple organoid samples on a single chip, assess differences in RNA capture efficiency compared to reference tissues and its limitations. This study introduces a bespoke analysis method that partitions samples into regions and further characterises them. These findings inform future works to characterise organoids using spatial transcriptomics, providing insights in optimising RNA capture of multiple organoids across a chip and novel methods for regional analysis.

bioinformatics↗