Prostate cancer radiogenomics reveals proliferative gene expression programs associated with distinct MRI-based hypoxia levels

Radiogenomic profiling of global DNA methylation associated with molecular phenotypes and immune features in glioma

BACKGROUND

The radiogenomic analysis has provided valuable imaging biomarkers with biological insights for gliomas. The radiogenomic markers for molecular profile such as DNA methylation remain to be uncovered to assist the molecular diagnosis and tumor treatment.

METHODS

We apply the machine learning approaches to identify the magnetic resonance imaging (MRI) features that are associated with molecular profiles in 146 patients with gliomas, and the fitting models for each molecular feature (MoRad) are developed and validated. To provide radiological annotations for the molecular profiles, we devise two novel approaches called radiomic oncology (RO) and radiomic set enrichment analysis (RSEA).

RESULTS

The generated MoRad models perform well for profiling each molecular feature with radiomic features, including mutational, methylation, transcriptional, and protein profiles. Among them, the MoRad models have a remarkable performance in quantitatively mapping global DNA methylation. With RO and RSEA approaches, we find that global DNA methylation could be reflected by the heterogeneity in volumetric and textural features of enhanced regions in T2-weighted MRI. Finally, we demonstrate the associations of global DNA methylation with clinicopathological, molecular, and immunological features, including histological grade, mutations of IDH and ATRX, MGMT methylation, multiple methylation-high subtypes, tumor-infiltrating lymphocytes, and long-term survival outcomes.

CONCLUSIONS

Global DNA methylation is highly associated with radiological profiles in glioma. Radiogenomic global methylation is an imaging-based quantitative molecular biomarker that is associated with specific consensus molecular subtypes and immune features.

Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography-Derived Radiomic Models in Prostate Cancer Prognostication

The clinical integration of prostate membrane specific antigen (PSMA) positron emission tomography and computed tomography (PET/CT) scans represents potential for advanced data analysis techniques in prostate cancer (PC) prognostication. Among these tools is the use of radiomics, a computer-based method of extracting and quantitatively analyzing subvisual features in medical imaging. Within this context, the present review seeks to summarize the current literature on the use of PSMA PET/CT-derived radiomics in PC risk stratification. A stepwise literature search of publications from 2017 to 2023 was performed. Of 23 articles on PSMA PET/CT-derived prostate radiomics, PC diagnosis, prediction of biopsy Gleason score (GS), prediction of adverse pathology, and treatment outcomes were the primary endpoints of 4 (17.4%), 5 (21.7%), 7 (30.4%), and 7 (30.4%) studies, respectively. In predicting PC diagnosis, PSMA PET/CT-derived models performed well, with receiver operator characteristic curve area under the curve (ROC-AUC) values of 0.85-0.925. Similarly, in the prediction of biopsy and surgical pathology results, ROC-AUC values had ranges of 0.719-0.84 and 0.84-0.95, respectively. Finally, prediction of recurrence, progression, or survival following treatment was explored in nine studies, with ROC-AUC ranging 0.698-0.90. Of the 23 studies included in this review, 2 (8.7%) included external validation. While explorations of PSMA PET/CT-derived radiomic models are immature in follow-up and experience, these results represent great potential for future investigation and exploration. Prior to consideration for clinical use, however, rigorous validation in feature reproducibility and biologic validation of radiomic signatures must be prioritized.

Comparative Serum Proteome Profiling of Canine Benign Prostatic Hyperplasia before and after Castration

BPH is the most prevalent prostatic condition in aging dogs. Nevertheless, clinical diagnosis and management remain inconsistent. This study employed in-solution digestion coupled with nano-liquid chromatography tandem mass spectrometry to assess serum proteome profiling of dogs with BPH and those dogs after castration. Male dogs were divided into two groups; control and BPH groups. In the BPH group, each dog was evaluated at two time points: Day 0 (BF subgroup) and Day 30 after castration (AT subgroup). In the BF subgroup, three proteins were significantly upregulated and associated with dihydrotestosterone: solute carrier family 5 member 5, tyrosine-protein kinase, and FRAT regulator of WNT signaling pathway 1. Additionally, the overexpression of polymeric immunoglobulin receptors in the BF subgroup hints at its potential as a novel protein linked to the BPH development process. Conversely, alpha-1-B glycoprotein (A1BG) displayed significant downregulation in the BF subgroup, suggesting A1BG's potential as a predictive protein for canine BPH. Finasteride was associated with increased proteins in the AT subgroup, including apolipoprotein C-I, apolipoprotein E, apolipoprotein A-II, TAO kinase 1, DnaJ homolog subfamily C member 16, PH domain and leucine-rich repeat protein phosphatase 1, neuregulin 1, and pseudopodium enriched atypical kinase 1. In conclusion, this pilot study highlighted alterations in various serum proteins in canine BPH, reflecting different pathological changes occurring in this condition. These proteins could be a source of potential non-invasive biomarkers for diagnosing this disease.