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Biology subjects

Abel, M.

Publications and source records attributed to Abel, M..

3 recordsLinked to original sources

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

Assessing the relationships between neurological and psychiatric diseases with astrocyte subtypes and psychotropic medications

Astrocytes have many important functions in the brain, but their roles in CNS disorders and their responses to psychotropic medications are still being elucidated. In this study, we used gene enrichment analysis to assess the relationships between different astrocyte subtypes, neurological and psychiatric diseases, and psychotropic medications. We also carried out qPCR analyses and "look-up" studies to further assess the chronic effects of these drugs on astrocyte marker gene expression. Our bioinformatic analysis identified differential gene enrichment of different astrocyte subtypes in CNS disorders. The "common" astrocyte subtype was the most frequently enriched across disorders, but the highest level of enrichment was found in depression, supporting a role for astrocytes in this disorder. We also identified common enrichment of metabolic and signal transduction-related biological processes in astrocyte subtypes and CNS disorders. However, enrichment of different psychotropic medications, including antipsychotics, antidepressants, and mood stabilizers, was limited in astrocyte subtypes. These results were confirmed by "look-up" studies and qPCR analysis, which also reported little effect of common psychotropic medications on astrocyte marker gene expression, suggesting that astrocytes are not a primary target of these medications. Overall, this study provides a unique view of astrocyte subtypes and the effect of medications on astrocytes in disease, which will contribute to our understanding of their role in CNS disorders and offers insights into targeting astrocytes therapeutically.

neuroscience↗

Kaleidoscope: A New Bioinformatics Pipeline Web Application for In Silico Hypothesis Exploration of Omics Signatures

BackgroundIn silico data exploration is a key first step of exploring a research question. There are many publicly available databases and tools that offer appealing features to help with such a task. However, many applications lack exposure or are constrained with unfriendly or outdated user interfaces. Thus, it follows that there are many resources that are relevant to investigation of medical disorders that are underutilized. ResultsWe developed an R Shiny web application, called Kaleidoscope, to address this challenge. The application offers access to several omics databases and tools to let users explore research questions in silico. The application is designed to be user- friendly with a unified user interface, while also scalable by offering the option of uploading user-defined datasets. We demonstrate the application features with a starting query of a single gene (Disrupted in schizophrenia 1, DISC1) to assess its protein-protein interactions network. We then explore expression levels of the gene network across tissues and cell types in the brain, as well as across 34 schizophrenia versus control differential gene expression datasets. ConclusionKaleidoscope provides easy access to several databases and tools under a unified user interface to explore research questions in silico. The web application is open-source and freely available at https://kalganem.shinyapps.io/Kaleidoscope/. This application streamlines the process of in silico data exploration for users and expands the efficient use of these tools to stakeholders without specific bioinformatics expertise.

bioinformatics↗