Techniques for digital histological morphometry of the pineal gland

In this study, we have devised a computational framework called Supervised Feature Learning and Scoring (SuperFeat) that allows for the training of a machine learning model and evaluates the canonical cellular status/features in pathological tissues that underlie the progression of disease. This framework also enables the identification of potential drugs that target the presumed detrimental cellular features. This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes. The training data comprised single-cell RNA sequencing datasets that encompassed the specific cell lineage during the developmental progression of cell features. A few models of the canonical cancer-involved cellular status/features were tested by such framework. Finally, we have illustrated the drug repurposing pipeline, utilizing the training parameters derived from the adverse cellular status/features, which has yielded successful validation results both in vitro and in vivo. SuperFeat is accessible at https://github.com/weilin-genomics/rSuperFeat.

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The Novel RXR Agonist MSU-42011 Differentially Regulates Gene Expression in Mammary Tumors of MMTV-Neu Mice

Reich¹,

Leal²,

Ellsworth

et al. 2023

IJMS

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Retinoid X receptor (RXR) agonists, which activate the RXR nuclear receptor, are effective in multiple preclinical cancer models for both treatment and prevention. While RXR is the direct target of these compounds, the downstream changes in gene expression differ between compounds. RNA sequencing was used to elucidate the effects of the novel RXRα agonist MSU-42011 on the transcriptome in mammary tumors of HER2+ mouse mammary tumor virus (MMTV)-Neu mice. For comparison, mammary tumors treated with the FDA approved RXR agonist bexarotene were also analyzed. Each treatment differentially regulated cancer-relevant gene categories, including focal adhesion, extracellular matrix, and immune pathways. The most prominent genes altered by RXR agonists positively correlate with survival in breast cancer patients. While MSU-42011 and bexarotene act on many common pathways, these experiments highlight the differences in gene expression between these two RXR agonists. MSU-42011 targets immune regulatory and biosynthetic pathways, while bexarotene acts on several proteoglycan and matrix metalloproteinase pathways. Exploration of these differential effects on gene transcription may lead to an increased understanding of the complex biology behind RXR agonists and how the activities of this diverse class of compounds can be utilized to treat cancer.

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Techniques for digital histological morphometry of the pineal gland

Cited by 3 publications

References 35 publications

An automatic histopathological image segmentation network based on global context-aware module and deep feature aggregation

An automatic histopathological image segmentation network based on global context-aware module and deep feature aggregation

SuperFeat: Quantitative Feature Learning from Single-cell RNA-seq Data Facilitates Drug Repurposing

The Novel RXR Agonist MSU-42011 Differentially Regulates Gene Expression in Mammary Tumors of MMTV-Neu Mice

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