Biology subjects

Horvath, L. G.

Publications and source records attributed to Horvath, L. G..

6 recordsLinked to original sources

bioRxiv2024

Profiling of epithelial functional states and fibroblast phenotypes in hormone therapy-naive localised prostate cancer

Localised prostate cancers (PCa) are heterogeneous and multifocal, with diverse outcomes. Current prognostic methods are epithelium-centric, overlooking the complex cellular landscape within the tumour microenvironment (TME), which remains incompletely characterised. We performed a comprehensive analysis of cancerous and adjacent-benign cores from 24 patients with hormone therapy-naive localised PCa using single-cell RNA-sequencing. By integrating copy number variation and transcriptional signatures, we classified epithelial cells across a malignant spectrum, revealing widespread molecular perturbation. We found an expansion of Club cell phenotypes, suggestive of Luminal dedifferentiation. We also performed a detailed annotation of stromal phenotypes, focusing on fibroblasts, and identified a novel peri-neural fibroblast population. Spatial transcriptomics elucidated the precise anatomical distribution of CAFs within the PCa TME. This study provides a valuable foundation for advancing our understanding of PCa pathobiology and developing a comprehensive cellular model of the disease. Statement of SignificanceOur study leverages single-cell RNA-sequencing and spatial transcriptomics to provide a comprehensive cellular annotation of hormone therapy-naive localised PCa. We reveal widespread molecular perturbations in epithelial cells and map distinct fibroblast populations to specific anatomical niches. Notably, we identify a novel peri-neural phenotype associated with nerves, which merits further functional characterisation and exploration as a potential therapeutic target.

cancer biology↗

bioRxiv2024

Federated deep learning enables cancer subtyping by proteomics

Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a Federated Deep Learning (FDL) approach (ProCanFDL), training local models on simulated sites containing data from a pan-cancer cohort (n=1,260) and 29 cohorts held behind private firewalls (n=6,265), representing 19,930 replicate data-independent acquisition mass spectrometry (DIA-MS) runs. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain on the hold-out test set (n=625) in 14 cancer subtyping tasks compared to local models, and matching centralized model performance. The approachs generalizability was demonstrated by retraining the global model with data from two external DIA-MS cohorts (n=55) and eight acquired by tandem mass tag (TMT) proteomics (n=832). ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data, e.g., for discovering predictive biomarkers or treatment targets, while maintaining data privacy. Statement of SignificanceA federated deep learning approach applied to human proteomic data, acquired using two distinct proteomic technologies from 40 tumor cohorts from eight countries, enabled accurate cancer histopathological subtyping while preserving data privacy. This approach will enable privacy-compliant development of large-scale proteomic AI models, including foundation models, across institutions globally.

cancer biology↗

bioRxiv2020

Lipidomic profiling of clinical prostate cancer reveals targetable alterations in lipid composition

Dysregulated lipid metabolism is a prominent feature of prostate cancer that is driven by androgen receptor (AR) signaling. Herein, we used quantitative mass spectrometry to define the "lipidome" in prostate tumors with matched benign tissues (n=21), independent tissues (n=47), and primary prostate explants cultured with a clinical AR antagonist, enzalutamide (n=43). Significant differences in lipid composition were detected and spatially visualized in tumors compared to matched benign samples. Notably, tumors featured higher proportions of monounsaturated lipids overall and elongated fatty acid chains in phosphatidylinositol and phosphatidylserine lipids. Significant associations between lipid profile and malignancy were validated in unmatched samples, and PL composition was characteristically altered in patient tissues that responded to AR inhibition. Importantly, targeting of altered tumor-related lipid features, via inhibition of acetyl CoA carboxylase 1, significantly reduced cellular proliferation in tissue explants (n=13). This first characterization of the prostate cancer lipidome in clinical tissues revealed enhanced fatty acid synthesis, elongation and desaturation as tumor-defining features, with potential for therapeutic targeting.

cancer biology↗

bioRxiv2020

Inhibition of guanosine monophosphate synthetase (GMPS) blocks glutamine metabolism and prostate cancer growth in vitro and in vivo

Cancer cells increase their uptake of nutrients and metabolize them to provide the necessary building blocks for new cancer cells. Glutamine is a critical nutrient in cancer, however its contribution to purine metabolism in prostate cancer has not previously been determined. Guanosine monophosphate synthetase (GMPS) acts in the de novo purine biosynthesis pathway, utilizing a glutamine amide to synthesize the guanine nucleotide and replenish the purine pool in proliferative cancer cells. This study demonstrates that GMPS mRNA expression correlates with Gleason score in prostate cancer samples, while high GMPS expression was associated with decreased rates of overall and disease/progression-free survival. Pharmacological inhibition or knockdown of GMPS significantly decreased cell growth in both LNCaP and PC-3 prostate cancer cells. GMPS knockdown was rescued by addition of extracellular guanosine to the media, suggesting a direct effect on nucleotide synthesis. We utilized 15N-(amide)-glutamine and U-13C5-glutamine metabolomics to dissect the pathways involved, and intriguingly, despite similar growth inhibition by GMPS knockdown, we show unique metabolic effects across each cell line. PC-3 cells showed a build-up of purine precursors, as well as activation of purine salvage pathways highlighted by significant increases in guanine, adenosine, inosine and cytosine. Both cell lines exhibited increased levels of pyrimidines and prioritized TCA cycle in distinct ways to produce increased aspartate, another important purine precursor. Using a PC-3 xenograft mouse model, tumor growth was also significantly decreased after GMPS knockdown. These data further highlight the importance of glutamine metabolism for prostate cancer cell growth and provide support for GMPS as a new therapeutic target in prostate cancer.

cancer biology↗

bioRxiv2019

DECR1 is an androgen-repressed survival factor that regulates PUFA oxidation to protect prostate tumor cells from ferroptosis

Fatty acid {beta}-oxidation (FAO) is the main bioenergetic pathway in prostate cancer (PCa) and a promising novel therapeutic vulnerability. Here we demonstrate therapeutic efficacy of targeting FAO in clinical prostate tumors cultured ex vivo, and identify DECR1, which encodes the rate-limiting enzyme for oxidation of polyunsaturated fatty acids (PUFAs), as robustly overexpressed in PCa tissues and associated with shorter relapse-free survival. DECR1 is a negatively-regulated androgen receptor (AR) target gene and, therefore, may promote PCa cell survival and resistance to AR targeting therapeutics. DECR1 knockdown in PCa cells selectively inhibited {beta}-oxidation of PUFAs, inhibited proliferation and migration of PCa cells, including treatment resistant lines, and suppressed tumor cell proliferation in vivo. Mechanistically, targeting of DECR1 caused cellular accumulation of linoleic acid, enhanced mitochondrial oxidative stress and lipid peroxidation, and ferroptosis. These findings implicate PUFA oxidation via DECR1 as a previously unexplored facet of FAO that promotes survival of PCa cells.

cancer biology↗

bioRxiv2018

MicroRNAs as potential therapeutics to enhance chemosensitivity in advancedprostate cancer

Docetaxel and cabazitaxel are taxane chemotherapy treatments for metastatic castration-resistant prostate cancer (CRPC). However, therapeutic resistance remains a major issue. MicroRNAs are short non-coding RNAs that can silence multiple genes, regulating several signalling pathways simultaneously. Therefore, synthetic microRNAs may have therapeutic potential in CRPC by regulating genes involved in taxane response and minimise compensatory mechanisms that cause taxane resistance. To identify microRNAs that can improve the efficacy of taxanes in CRPC, we performed a genome-wide screen of 1280 microRNAs in the CRPC cell lines PC3 and DU145 in combination with docetaxel or cabazitaxel treatment. Mimics of miR-217 and miR-181b-5p enhanced apoptosis significantly in PC3 cells in the presence of these taxanes. These mimics downregulated at least a thousand different transcripts, which were enriched for genes with cell proliferation and focal adhesion functions. Individual knockdown of a selection of 46 genes representing these transcripts resulted in toxic or taxane sensitisation effects, indicating that these genes may be mediating the effects of the microRNA mimics. A range of these genes are expressed in CRPC metastases, suggesting that these microRNA mimics may be functional in CRPC. With further development, these microRNA mimics may have therapeutic potential to improve taxane response in CRPC patients.

cancer biology↗