CLM296: a highly selective inhibitor targeting ALDH1A3-driven tumor growth and metastasis in breast cancer

Опубликована: Апрель 18, 2025

ABSTRACT Aldehyde dehydrogenase 1A3 (ALDH1A3) increases tumor growth, metastasis, and chemoresistance in many solid tumors, including triple-negative breast cancer (TNBC), glioblastoma, melanoma, lung, colon cancers, yet no clinically approved inhibitors exist. Here, we present CLM296, a novel highly selective ALDH1A3 inhibitor designed to address this unmet need. CLM296 exhibits potent inhibition of activity TNBC cells (half-maximal inhibitory concentration = 2 nM) with off-target effects on the homologous ALDH1A1 isoform. RNA sequencing confirmed its specificity, demonstrating suppression ALDH1A3-regulated gene expression only, lack effect control that have minimal expression. Transwell assays showed reduced increased invasion induced by ALDH1A3. Once daily dosing 4mg/kg mice specifically ALDH1A3-mediated tumors impeded ALDH1A3-driven growth lung metastasis xenografts. There was observed toxicity as evidenced stable mouse body weights significant changes blood creatinine ALT levels. Pharmacokinetic studies revealed broad tissue distribution, tumor, liver, brain. With oral administration terminal elimination half-life exceeded 12 hours, resulting sustained ALDH1A3-inhibiting concentrations beyond 24 hours. Together, these findings establish potential first-in-class high selectivity for ALDH1A3, favorable pharmacokinetics, positive preclinical safety profile. represents promising therapeutic candidate complement standard-of-care treatments ALDH1A3+ cancers.

Язык: Английский

Revealing metastatic castration‐resistant prostate cancer master regulator through lncRNAs‐centered regulatory network

Cancer Medicine, Год журнала: 2023, Номер 12(18), С. 19279 - 19290

Опубликована: Авг. 29, 2023

Metastatic castration-resistant prostate cancer (mCRPC) is an aggressive form of unresponsive to androgen deprivation therapy (ADT) that spreads quickly other organs. Despite reduced levels after ADT, mCRPC development and lethality continues be conducted by the receptor (AR) axis. The maintenance AR signaling in a result alterations, intratumoral production, action regulatory elements, such as noncoding RNAs (ncRNAs). ncRNAs are key elements signaling, acting tumor growth, metabolic reprogramming, progression. In (PCa), have been reported associated with expression, PCa proliferation, castration resistance. this study, we aimed reconstruct lncRNA-centered network identify lncRNAs which act master regulators (MRs).We used publicly available RNA-sequencing infer mCRPC. Five gene signatures were employed conduct regulator analysis. Inferred MRs then subjected functional enrichment symbolic regression modeling. latter approach was applied greater predictive capacity potential biomarker mCRPC.We identified 31 involved cellular metabolism, invasion-metastasis cascade. SNHG18 HELLPAR highlights our results. downregulated enriched metastasis signatures. It accurately distinguished both primary CRPC from normal tissue epithelial-mesenchymal transition (EMT) cell-matrix adhesion pathways. consistently using only its expression.Our results contribute understanding behavior indicate new diagnostic targets tumor.

Язык: Английский

Computational Ensemble Gene Co-Expression Networks for the Analysis of Cancer Biomarkers

Informatics, Год журнала: 2024, Номер 11(2), С. 14 - 14

Опубликована: Март 28, 2024

Gene networks have become a powerful tool for the comprehensive examination of gene expression patterns. Thanks to these generated by means inference algorithms, it is possible study different biological processes and even identify new biomarkers such diseases. These are essential discovery treatments genetic diseases as cancer. In this work, we introduce an algorithm network based on ensemble method that improves robustness results combining two main steps: first, evaluation relationship between pairs genes using three co-expression measures, and, subsequently, voting strategy. The utility approach was demonstrated applying human dataset encompassing breast prostate cancer-associated stromal cells. Two were computed microarray data, one cancer obtained revealed, hand, distinct cell behaviors in other list potential both case tumor, ST6GAL2, RIPOR3, COL5A1, DEPDC7 found, GATA6-AS1, ARFGEF3, PRR15L, APBA2. demonstrate usefulness field biomarker discovery.

Язык: Английский