CD74 as a prognostic and M1 macrophage infiltration marker in a comprehensive pan-cancer analysis

Identifying genetic variants associated with lung cancer (LC) risk and their impact on plasma protein levels is crucial for understanding LC predisposition. The discovery of risk biomarkers can enhance early LC screening protocols and improve prognostic interventions. In this study, we performed a genome-wide association analysis using the UK Biobank and FinnGen. We identified genetic variants associated with LC and protein levels leveraging the UK Biobank Pharma Proteomics Project. The dysregulated proteins were then analyzed in pre-symptomatic LC cases compared to healthy controls followed by training machine learning models to predict future LC diagnosis. We achieved median AUCs ranging from 0.79 to 0.88 (0-4 years before diagnosis/YBD), 0.73 to 0.83 (5-9YBD), and 0.78 to 0.84 (0-9YBD) based on 5-fold cross-validation. Conducting survival analysis using the 5-9YBD cohort, we identified eight proteins, including CALCB, PLAUR/uPAR, and CD74 whose higher levels were associated with worse overall survival. We also identified potential plasma biomarkers, including previously reported candidates such as CEACAM5, CXCL17, GDF15, and WFDC2, which have shown associations with future LC diagnosis. These proteins are enriched in various pathways, including cytokine signaling, interleukin regulation, neutrophil degranulation, and lung fibrosis. In conclusion, this study generates novel insights into our understanding of the genome-proteome dynamics in LC. Furthermore, our findings present a promising panel of non-invasive plasma biomarkers that hold potential to support early LC screening initiatives and enhance future diagnostic interventions.

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Repurposing Ivermectin and ATRA as Potential Therapeutics for Glioblastoma Multiforme

Sayad,

Hiatt,

Mustafa

2024

Preprint

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BackgroundGlioblastoma multiforme (GBM) is the most aggressive and lethal form of primary brain tumor, characterized by rapid growth and resistance to conventional therapies. Despite advances in treatment, most patients succumb to the disease within 15 months. Drug repurposing, which involves finding new uses for existing drugs, is a promising strategy to develop new GBM treatments faster and more cost-effectively.MethodWe obtained single-cell RNA sequencing (scRNA-seq) data (GSE84465) from the National Institutes of Health (NIH) Gene Expression Omnibus (GEO) repository to compare gene expression in GBM neoplastic cells and non-neoplastic cells. We identified genes that were abnormally expressed in tumor cells and linked these genes to potential drug targets. To identify potential repurposed drugs for GBM, we leveraged the Chemical Entities of Biological Interest (ChEBI) database to assess the interaction of various compounds with the differentially expressed genes identified in the scRNA-seq analysis. We focused on compounds that could reverse the aberrant gene expression observed in GBM neoplastic cells.ResultsOur analysis suggests that ivermectin and all-trans-retinoic acid (ATRA) could be repurposed as effective treatments for GBM. Ivermectin, typically used as an antiparasitic, demonstrated strong anti-tumor activity by downregulating 40 of the top 100 upregulated genes in GBM, indicating its potential to suppress tumor growth. ATRA, known for promoting cell differentiation, upregulated 60 genes typically downregulated in GBM neoplastic cells, showing its potential to correct transcriptional dysregulation and support tumor suppression. These findings underscore the promise of drug repurposing to target key pathways in GBM, offering new therapeutic options for this aggressive cancer.ConclusionsOur results provide compelling evidence that ivermectin and ATRA may be effective in treating GBM. The observed alterations in gene expression indicate the ability of these two agents to disrupt key genes and pathways crucial for tumor progression. Given the increasing interest in drug repurposing for cancer treatment, comprehensive preclinical and clinical investigations are warranted to assess fully the therapeutic efficacy of these compounds against this disease.

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CD74 as a prognostic and M1 macrophage infiltration marker in a comprehensive pan-cancer analysis

Cited by 5 publications

References 56 publications

GBM immunotherapy: Exploring molecular and clinical frontiers

GBM immunotherapy: Exploring molecular and clinical frontiers

Machine learning-based proteogenomic data modeling identifies circulating plasma biomarkers for early detection of lung cancer

Repurposing Ivermectin and ATRA as Potential Therapeutics for Glioblastoma Multiforme

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