The single cell and spatial transcriptomics in cancer therapeutics, applications, chalenges and future

Introduction: Single-cell and spatial transcriptomics techniquesallow for a more refined analysis of cancer cell stateswithin tumor microenvironments. These techniques overcomethe limitations of traditional bulk RNA sequencing methods bymeasuring the whole transcriptome at a single-cell resolution.Interferonopathy is a group of rare genetic disorders characterizedby an increased sensitivity to interferon. Lupus is anautoimmune disease where the body’s immune system attacksits own tissues and organs. The analysis of interferonopathy andlupus single cell datasets using scArches can help find commonbiomarkers between these conditions, providing valuableinsights into their underlying mechanisms.Methods/results: In this study, we prepared libraries of interferonopathyPBMCs using ۱۰X genomics ۳’ gene expressionkit with demultiplexing feature and sequenced them using Illuminanextseq ۲۰۰۰. The data was preprocessed using CellRanger pipeline and further analyzed using scanpy workflow.scArches is a deep learning strategy for mapping query datasetson top of a reference called single-cell architectural surgery.It uses transfer learning and parameter optimization to enableefficient reference building and contextualizing new datasetswithout sharing raw data. This allows for the analysis of singlecellquery data by integrating it into a reference atlas.Discussion/Conclusion: Single-cell and spatial transcriptomicstechniques provide a more refined analysis of cancer cellstates within tumor microenvironments. The analysis of interferonopathyand lupus single cell datasets using scArches canprovide valuable insights into the underlying mechanisms ofthese diseases.

کلیدواژه ها:

scRNA-seq ، sparial_transcriptomics ، cancer ، scArches