A functional genetic screen for metabolic proteins unveils GART and the de novo purine biosynthetic pathway as novel targets for the treatment of luminal A ERα expressing primary and metastatic invasive ductal carcinoma

Identification and validation of a metabolic-related gene risk model predicting the prognosis of lung, colon, and breast cancers

Metabolic reprogramming, vital for cancer cells to adapt to the altered microenvironment, remains a topic requiring further investigation for different tumor types. Our study aims to elucidate shared metabolic reprogramming across breast (BRC), colorectal (CRC), and lung (LUC) cancers. Leveraging gene expression data from the Gene Expression Omnibus and various bioinformatics tools like MSigDB, WebGestalt, String, and Cytoscape, we identified key/hub metabolism-related genes (MRGs) and their interactions. The functional characteristics including survival parameters and expression of the key MRGs were analyzed and validated through Gene Expression Profiling Interactive Analysis 2 and qRT-PCR. In addition, we employed machine learning algorithms such as k-nearest neighbours (KNN), support vector regressor (SVR), and extreme gradient boosting (XGBoost) to assess MRGs' effectiveness in predicting overall patient survival. Among 11,384 DEGs analyzed, 540 overlapped across BRC, CRC, and LUC, with 46 MRGs and 20 key/hub MRGs involved in all studied cancer types. Of these, 11 key MRGs were prognostically significant. The qRT-PCR validation of key MRGs in specific cancer cell lines confirmed their expression profiles, with some showing cell-type-specific patterns. SVR exhibited remarkable accuracy in predicting overall survival, emphasizing its clinical utility. Our integrated approach combining bioinformatics analyses and experimental validations underscores the potential of MRGs as biomarkers for metabolic therapies, with machine learning models enhancing predictive capabilities for patient outcomes.

Targeting purine metabolism-related enzymes for therapeutic intervention: A review from molecular mechanism to therapeutic breakthrough

Purines are ancient metabolites with established and emerging metabolic and non-metabolic signaling attributes. The expression of purine metabolism-related genes is frequently activated in human malignancies, correlating with increased cancer aggressiveness and chemoresistance. Importantly, under certain stimulating conditions, the purine biosynthetic enzymes can assemble into a metabolon called "purinosomes" to enhance purine flux. Current evidence suggests that purine flux is regulated by a complex circuit that encompasses transcriptional, post-translational, metabolic, and association-dependent regulatory mechanisms. Furthermore, purines within the tumor microenvironment modulate cancer immunity through signaling mediated by purinergic receptors. The deregulation of purine metabolism has significant metabolic consequences, particularly hyperuricemia. Herbal-based therapeutics have emerged as valuable pharmacological interventions for the treatment of hyperuricemia by inhibiting the activity of hepatic XOD, modulating the expression of renal urate transporters, and suppressing inflammatory responses. This review summarizes recent advancements in the understanding of purine metabolism in clinically relevant malignancies and metabolic disorders. Additionally, we discuss the role of herbal interventions and the interaction between the host and gut microbiota in the regulation of purine homeostasis. This information will fuel the innovation of therapeutic strategies that target the disease-associated rewiring of purine metabolism for therapeutic applications.

PMM2 controls ERα levels and cell proliferation in ESR1 Y537S variant expressing breast cancer cells

PURPOSE

Metabolic reprogramming in breast cancer (BC) subtypes offers potential personalized treatment targets. Estrogen receptor α (ERα)-positive BC patients undergoing endocrine therapy (ET) can develop ET-resistant metastatic disease. Specific mutations, like Y537S in ERα, drive uncontrolled cell proliferation. Targeting mutant receptor levels shows promise for inhibiting growth in metastatic BC expressing ERα variants. Additionally, metabolic reprogramming occurs in ERα Y537S mutant cells. Consequently, we conducted a screen to identify metabolic proteins reducing intracellular levels of ERα Y537S and inhibiting cell proliferation.

METHODS

Nine metabolic proteins were identified in a siRNA-based screen, with phosphomannose mutase 2 (PMM2) showing the most promise. We measured the impact of PMM2 depletion on ERα stability and cell proliferation in ERα Y537S mutant cells. Additionally, we tested the effect of PMM2 reduction on the hyperactive phenotype of the mutant and its proliferation when combined with metastatic BC treatment drugs.

RESULTS

PMM2 emerged as a significant target due to its correlation with better relapse-free survival, overexpression in ERα-positive tumors, and its elevation in ERα Y537S-expressing cells. Depletion of PMM2 induces degradation of ERα Y537S, inhibits cell proliferation, and reduces ERα signaling. Notably, reducing PMM2 levels re-sensitizes ERα Y537S-expressing cells to certain ET drugs and CDK4/CDK6 inhibitors. Mechanistically, depletion of PMM2 leads to a reduction in ESR1 mRNA levels, resulting in decreased ERα receptor protein expression. Furthermore, the reduction of PMM2 decreases FOXA1 levels, which plays a crucial role in ERα regulation.

CONCLUSIONS

Our findings establish PMM2 as an innovative therapeutic target for metastatic BC expressing the ERα Y537S variant, offering alternative strategies for managing and treating this disease.

Selective impact of ALK and MELK inhibition on ERα stability and cell proliferation in cell lines representing distinct molecular phenotypes of breast cancer

Breast cancer (BC) is a leading cause of global cancer-related mortality in women, necessitating accurate tumor classification for timely intervention. Molecular and histological factors, including PAM50 classification, estrogen receptor α (ERα), breast cancer type 1 susceptibility protein (BRCA1), progesterone receptor (PR), and HER2 expression, contribute to intricate BC subtyping. In this work, through a combination of bioinformatic and wet lab screenings, followed by classical signal transduction and cell proliferation methods, and employing multiple BC cell lines, we identified enhanced sensitivity of ERα-positive BC cell lines to ALK and MELK inhibitors, inducing ERα degradation and diminishing proliferation in specific BC subtypes. MELK inhibition attenuated ERα transcriptional activity, impeding E2-induced gene expression, and hampering proliferation in MCF-7 cells. Synergies between MELK inhibition with 4OH-tamoxifen (Tam) and ALK inhibition with HER2 inhibitors revealed potential therapeutic avenues for ERα-positive/PR-positive/HER2-negative and ERα-positive/PR-negative/HER2-positive tumors, respectively. Our findings propose MELK as a promising target for ERα-positive/PR-positive/HER2-negative BC and highlight ALK as a potential focus for ERα-positive/PR-negative/HER2-positive BC. The synergistic anti-proliferative effects of MELK with Tam and ALK with HER2 inhibitors underscore kinase inhibitors' potential for selective treatment in diverse BC subtypes, paving the way for personalized and effective therapeutic strategies in BC management.