Polycystic ovary syndrome (PCOS) represents the most common cause of anovulatory infertility and affects 5-10% of women of reproductive age. The etiology of PCOS is still unknown. The current study is the first to describe consistent differences in gene expression profiles in human ovaries comparing PCOS patients vs. healthy normoovulatory individuals. The microarray analysis of PCOS vs. normal ovaries identifies dysregulated expression of genes encoding components of several biological pathways or systems such as Wnt signaling, extracellular matrix components, and immunological factors. Resulting data may provide novel clues for ovarian dysfunction in PCOS. Intriguingly, the gene expression profiles of ovaries from (long-term) androgen-treated female-to-male transsexuals (TSX) show considerable overlap with PCOS. This observation provides supportive evidence that androgens play a key role in the pathogenesis of PCOS. Presented data may contribute to a better understanding of dysregulated pathways in PCOS, which might ultimately reveal novel leads for therapeutic intervention.
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http://dx.doi.org/10.1210/me.2004-0074 | DOI Listing |
Brief Bioinform
November 2024
Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States.
Pathway analysis plays a critical role in bioinformatics, enabling researchers to identify biological pathways associated with various conditions by analyzing gene expression data. However, the rise of large, multi-center datasets has highlighted limitations in traditional methods like Over-Representation Analysis (ORA) and Functional Class Scoring (FCS), which struggle with low signal-to-noise ratios (SNR) and large sample sizes. To tackle these challenges, we use a deep learning-based classification method, Gene PointNet, and a novel $P$-value computation approach leveraging the confusion matrix to address pathway analysis tasks.
View Article and Find Full Text PDFClin Cancer Res
January 2025
Stanford University, Palo Alto, CA, United States.
Purpose: After failing primary and secondary hormonal therapy, castration-resistant and neuroendocrine prostate cancer metastatic to the bone is invariably lethal, although treatment with docetaxel and carboplatin can modestly improve survival. Therefore, agents targeting biologically relevant pathways in PCa and potentially synergizing with docetaxel and carboplatin in inhibiting bone metastasis growth are urgently needed.
Experimental Design: Phosphorylated (activated) AXL expression in human prostate cancer bone metastases was assessed by immunohistochemical staining.
STAR Protoc
January 2025
Department of Statistics, University of Georgia, 310 Herty Drive, Athens, GA 30602, USA. Electronic address:
Spatial transcriptomics enhances our understanding of cellular organization by mapping gene expression data to precise tissue locations. Here, we present a protocol for using weighted ensemble method for spatial transcriptomics (WEST), which uses ensemble techniques to boost the robustness and accuracy of existing algorithms. We describe steps for preprocessing data, obtaining embeddings from individual algorithms, and ensemble integrating all embeddings as a similarity matrix.
View Article and Find Full Text PDFSci Transl Med
January 2025
Department of Cell Biology and Physiology, Washington University School of Medicine, Saint Louis, MO 63110, USA.
Sci Transl Med
January 2025
Graduate Program in Human Genetics, University of Miami Miller School of Medicine, 1501 NW 10th Avenue (M-860), Miami, FL 33136, USA.
Primary mitochondrial disorders are most often caused by deleterious mutations in the mitochondrial DNA (mtDNA). Here, we used a mitochondrial DddA-derived cytosine base editor (DdCBE) to introduce a compensatory edit in a mouse model that carries the pathological mutation in the mitochondrial transfer RNA (tRNA) alanine (mt-tRNA) gene. Because the original m.
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