CUB Domain-Containing Protein 1 (CDCP1) is a rational target for the development of imaging tracers and antibody-drug conjugates for cancer detection and therapy

Integrative Computational Framework, Dyscovr, Links Mutated Driver Genes to Expression Dysregulation Across 19 Cancer Types

Though somatic mutations play a critical role in driving cancer initiation and progression, the systems-level functional impacts of these mutations-particularly, how they alter expression across the genome and give rise to cancer hallmarks-are not yet well-understood, even for well-studied cancer driver genes. To address this, we designed an integrative machine learning model, Dyscovr, that leverages mutation, gene expression, copy number alteration (CNA), methylation, and clinical data to uncover putative relationships between nonsynonymous mutations in key cancer driver genes and transcriptional changes across the genome. We applied Dyscovr pan-cancer and within 19 individual cancer types, finding both broadly relevant and cancer type-specific links between driver genes and putative targets, including a subset we further identify as exhibiting negative genetic relationships. Our work newly implicates-and validates in cell lines-KBTBD2 and mutant PIK3CA as putative synthetic lethals in breast cancer, suggesting a novel combinatorial treatment approach.

Targeting CDCP1 boost CD8+ T cells-mediated cytotoxicity in cervical cancer via the JAK/STAT signaling pathway

BACKGROUND

Cervical cancer remains a global health challenge. The identification of new immunotherapeutic targets may provide a promising platform for advancing cervical cancer treatment.

OBJECTIVE

This study aims to investigate the role of CUB domain-containing protein 1 (CDCP1) in cervical cancer progression and evaluate its potential as a therapeutic target.

METHODS

We performed comprehensive analyses using patient cohorts and preclinical models to examine the association between CDCP1 expression and cervical cancer prognosis. Then in immunodeficient and immunocompetent mouse models, we further investigated the impact of CDCP1 on the tumor immune microenvironment, focusing on its effects on tumor-infiltrating T cells, including cytotoxic T lymphocytes (CTLs) and regulatory T cells (Tregs). Mechanistic studies were performed to elucidate the pathways involved in CDCP1-mediated immune modulation, in particular its interaction with the T cell receptor CD6 and the activation of the JAK-STAT signaling pathway.

RESULTS

Our results show that CDCP1 overexpression is associated with poor prognosis and T cell infliction in cervical cancer. Specifically, it affects the activity of CTLs and Tregs. Mechanistically, CDCP1 binds to CD6 and inhibits the JAK-STAT pathway of T cells. The study further demonstrates that targeting CDCP1 with the inhibitor 8-prenylnaringenin (8PN) effectively suppresses tumor growth in vivo and enhances antitumor immunity.

CONCLUSIONS

CDCP1 plays a critical role in cervical cancer progression by modulating the tumor immune microenvironment. Targeting CDCP1 offers a promising therapeutic strategy to improve the outcome of patients with cervical cancer.

Olink Proteomics for the Identification of Biomarkers for Early Diagnosis of Postmenopausal Osteoporosis

This investigation aims to employ Olink proteomics in analyzing the distinct serum proteins associated with postmenopausal osteoporosis (PMOP) and identifying prognostic markers for early detection of PMOP via molecular mechanism research on postmenopausal osteoporosis. Postmenopausal women admitted to Beijing Jishuitan Hospital were randomly selected and categorized into three groups based on their dual-energy X-ray absorptiometry (DXA) T-scores: osteoporosis group (n = 24), osteopenia group (n = 20), and normal bone mass group (n = 16). Serum samples from all participants were collected for clinical and bone metabolism marker measurements. Olink proteomics was utilized to identify differentially expressed proteins (DEPs) that are highly associated with postmenopausal osteoporosis. The functional analysis of DEPs was performed using Gene Ontology and Kyto Encyclopedia Genes and Genomes (KEGG). The biological characteristics of these proteins and their correlation with PMOP were subsequently analyzed. ROC curve analysis was performed to identify potential biomarkers with the highest diagnostic accuracy for early stage PMOP. Through Olink proteomics, we identified five DEPs highly associated with PMOP, including two upregulated and three downregulated proteins. TWEAK and CDCP1 markers exhibited the highest area under the curve (0.8188 and 0.8031, respectively). TWEAK and CDCP1 have the potential to serve as biomarkers for early prediction of postmenopausal osteoporosis.

Antibody-drug conjugates in urinary tumors: clinical application, challenge, and perspectives

Urinary tumors primarily consist of kidney, urothelial, and prostate malignancies, which pose significant treatment challenges, particularly in advanced stages. Antibody-drug conjugates (ADCs) have emerged as a promising therapeutic approach, combining monoclonal antibody specificity with cytotoxic chemotherapeutic payloads. This review highlights recent advancements, opportunities, and challenges in ADC application for urinary tumors. We discuss the FDA-approved ADCs and other novel ADCs under investigation, emphasizing their potential to improve patient outcomes. Furthermore, we explore strategies to address challenges, such as toxicity management, predictive biomarker identification, and resistance mechanisms. Additionally, we examine the integration of ADCs with other treatment modalities, including immune checkpoint inhibitors, targeted therapies, and radiation therapy. By addressing these challenges and exploring innovative approaches, the development of ADCs may significantly enhance therapeutic options and outcomes for patients with advanced urinary tumor.