Radiogenomic analysis of ultrasound phenotypic features coupled to proteomes predicts metastatic risk in primary prostate cancer.

BACKGROUND: Primary prostate cancer with metastasis has a poor prognosis, so assessing its risk of metastasis is essential. METHODS: This study combined comprehensive ultrasound features with tissue proteomic analysis to obtain biomarkers and practical diagnostic image features that signify prostate cancer metastasis. RESULTS: In this study, 17 ultrasound image features of benign prostatic hyperplasia (BPH), primary prostate cancer without metastasis (PPCWOM), and primary prostate cancer with metastasis (PPCWM) were comprehensively analyzed and combined with the corresponding tissue proteome data to perform weighted gene co-expression network analysis (WGCNA), which resulted in two modules highly correlated with the ultrasound phenotype. We screened proteins with temporal expression trends based on the progression of the disease from BPH to PPCWOM and ultimately to PPCWM from two modules and obtained a protein that can promote prostate cancer metastasis. Subsequently, four ultrasound image features significantly associated with the metastatic biomarker HNRNPC (Heterogeneous nuclear ribonucleoprotein C) were identified by analyzing the correlation between the protein and ultrasound image features. The biomarker HNRNPC showed a significant difference in the five-year survival rate of prostate cancer patients (p < 0.0053). On the other hand, we validated the diagnostic efficiency of the four ultrasound image features in clinical data from 112 patients with PPCWOM and 150 patients with PPCWM, obtaining a combined diagnostic AUC of 0.904. In summary, using ultrasound imaging features for predicting whether prostate cancer is metastatic has many applications. CONCLUSION: The above study reveals noninvasive ultrasound image biomarkers and their underlying biological significance, which provide a basis for early diagnosis, treatment, and prognosis of primary prostate cancer with metastasis.

Proteomics coupled transcriptomics reveals Slc34a1 and Slc34a3 downregulation as potential features of nephrotoxin-induced acute kidney injury.

Acute kidney injury (AKI) stands as a prevalent and economically burdensome condition worldwide, yet its complex molecular mechanisms remain incompletely understood. To address this gap, our study employs a multifaceted approach, combining mass spectrometry and RNA sequencing technologies, to elucidate the intricate molecular landscape underlying nephrotoxin-induced AKI in mice by cisplatin- and LPS-induced. By examining the protein and RNA expression profiles, we aimed to uncover novel insights into the pathogenesis of AKI and identify potential diagnostic and therapeutic targets. Our results demonstrate significant down-regulation of Slc34a1 and Slc34a3, shedding light on their crucial roles in AKI pathology and highlighting their promise as actionable targets for diagnosis and treatment. This comprehensive analysis not only enhances our understanding of AKI pathophysiology but also offers valuable avenues for the development of targeted interventions to mitigate its clinical impact. SIGNIFICANCE: Nephrotoxicity acute kidney injury (AKI) is a common clinical condition whose pathogenesis is the process by which some drugs, chemicals or other factors cause damage to the kidneys, resulting in impaired kidney function. Although it has been proved that different nephrotoxic substances can affect the kidney through different pathways, whether they have a commonality has not been registered. Here, we combined transcriptomics and proteomics to study the molecular mechanism of LPS and cisplatin-induced nephrotoxic acute kidney injury finding that the down-regulation of Slc34a1 and Slc34a3 may be a critical link in nephrotoxic acute kidney injury, which can be used as a marker for its early diagnosis.