RNA-seq profile of African American men with a clinically localized prostate cancer

Anti-prostate cancer mechanism of black ginseng during the "nine steaming and nine sun-drying" process based on HPLC analysis combined with vector space network pharmacology

HPLC analysis determined six small-molecule organic acids, maltol, 5-hydroxymethylfurfural (5-HMF), 17 ginsenosides, four oligosaccharides, and 20 amino acids in black ginseng samples with different processing times. Based on the content determination results, the differential ingredients in the processing of black ginseng were screened by multivariate statistical analysis. Network pharmacological methods obtained the core targets and pathways of the above ingredients against prostate cancer. Finally, the entropy weight method was used to assign values to the above ingredients, targets, and pathways, and the vector space network pharmacology method was established to study the anti-prostate cancer mechanism of black ginseng in the process of "nine steaming and nine sun-drying". Based on principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA), fructose, glucose, dencichin, glutamate, ginsenoside 20 (S)-Rg3, 20 (R)-Rg3, 20 (S)-Rh2, Rg1, Re, and Rc were the main differential ingredients in various steaming and sun-drying cycle periods of black ginseng. The results of vector space network pharmacology showed that the main reason for the change in the anti-prostate cancer pathway of black ginseng with the number of steaming and sun-drying was the different regulatory ability of black ginseng on the PI3K-Akt signaling pathway and chemical carcinogenesis-receptor activation pathway. It gave researchers a fresh perspective for exploring the anti-prostate cancer active components of black ginseng and the change in the mechanism of the effect of traditional Chinese medicine in processing.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Genomic, epigenomic, and transcriptomic signatures of prostate cancer between African American and European American patients

Prostate cancer is the second most common cancer in men in the United States, and racial disparities are greatly observed in the disease. Specifically, African American (AA) patients have 60% higher incidence and mortality rates, in addition to higher grade and stage prostate tumors, than European American (EA) patients. In order to narrow the gap between clinical outcomes for these two populations, genetic and molecular signatures contributing to this disparity have been characterized. Over the past decade, profiles of prostate tumor samples from different ethnic groups have been developed using molecular and functional assays coupled with next generation sequencing or microarrays. Comparative genome-wide analyses of genomic, epigenomic, and transcriptomic profiles from prostate tumor samples have uncovered potential race-specific mutations, copy number alterations, DNA methylation, and gene expression patterns. In this study, we reviewed over 20 published studies that examined the aforementioned molecular contributions to racial disparities in AA and EA prostate cancer patients. The reviewed genomic studies revealed mutations, deletions, amplifications, duplications, or fusion genes differentially enriched in AA patients relative to EA patients. Commonly reported genomic alterations included mutations or copy number alterations of FOXA1, KMT2D, SPOP, MYC, PTEN, TP53, ZFHX3, and the TMPRSS2-ERG fusion. The reviewed epigenomic studies identified that CpG sites near the promoters of PMEPA1, RARB, SNRPN, and TIMP3 genes were differentially methylated between AA and EA patients. Lastly, the reviewed transcriptomic studies identified genes (e.g. CCL4, CHRM3, CRYBB2, CXCR4, GALR1, GSTM3, SPINK1) and signaling pathways dysregulated between AA and EA patients. The most frequently found dysregulated pathways were involved in immune and inflammatory responses and neuroactive ligand signaling. Overall, we observed that the genomic, epigenomic, and transcriptomic alterations evaluated between AA and EA prostate cancer patients varied between studies, highlighting the impact of using different methods and sample sizes. The reported genomic, epigenomic, and transcriptomic alterations do not only uncover molecular mechanisms of tumorigenesis but also provide researchers and clinicians valuable resources to identify novel biomarkers and treatment modalities to improve the disparity of clinical outcomes between AA and EA patients.

Molecular Insight into Drug Resistance Mechanism Conferred by Aberrant PIK3CD Splice Variant in African American Prostate Cancer

Targeting PI3Kδ has emerged as a promising therapy for hematologic and non-hematologic malignancies. Previously, we identified an oncogenic splice variant, PIK3CD-S, conferring Idelalisib resistance in African American (AA) prostate cancer (PCa). In the current study, we employed a comprehensive analysis combining molecular biology, biochemistry, histology, in silico simulation, and in vitro functional assays to investigate the PIK3CD-S expression profiles in PCa samples and to elucidate the drug resistance mechanism mediated by PI3Kδ-S (encoded by PIK3CD-S). The immunohistochemistry, RT-PCR, and Western blot assays first confirmed that PI3Kδ-S is highly expressed in AA PCa. Compared with PCa expressing the full-length PI3Kδ-L, PCa expressing PI3Kδ-S exhibits enhanced drug resistance properties, including a higher cell viability, more antiapoptotic and invasive capacities, and constitutively activated PI3K/AKT signaling, in the presence of PI3Kδ/PI3K inhibitors (Idelalisib, Seletalisib, Wortmannin, and Dactolisib). Molecular docking, ATP-competitive assays, and PI3 kinase assays have further indicated a drastically reduced affinity of PI3Kδ inhibitors with PI3Kδ-S vs. PI3Kδ-L, attributed to the lack of core binding residues in the PI3Kδ-S catalytic domain. Additionally, SRSF2 has been identified as a critical splicing factor mediating exon 20 skipping in PIK3CD pre-mRNA. The inhibition of the SRSF2 activity by SRPIN340 successfully sensitizes AA PCa cells to PI3Kδ inhibitors, suggesting a novel therapeutic option for Idelalisib-resistant tumors.

Challenges in next generation sequencing of homology recombination repair genomic variants in prostate cancer: A nationwide survey and calibration project in China

Background

Homologous Recombination Repair (HRR) is the most reliable and important signaling pathway for repairing DNA damage. We initiated a calibration project to better understand the NGS landscape for HRR gene testing in China, provide indications for testing standardization, and guide clinical practice.

Methods

A questionnaire was used to collect laboratory information, panel design for HRR gene testing, tissue sample test parameters, plasma ctDNA sample test parameters, and procedures for variant interpretation. The testing quality of the participating laboratories was further evaluated by external quality assessment (EQA), which provided 5 FFPE slices and 5 mimic ctDNA samples as standard references for evaluation. Test results and reports were collected to assess laboratory performance.

Results

Our results showed that different laboratories had significant differences in sequencing platforms, library construction technologies, genes in the testing panel, detectable mutation types, probe coverage regions, sequencing parameters, variants interpretation guidelines, and positive test rates. For the EQA test, the overall pass rate was about 60%. The average accuracy for tissue samples and ctDNA samples was 79.55% and 74.13%, respectively. It is worth noting that variants in tandem repetition regions and splice sites, and those with low allele frequency were more prone to misdetection. The most common reasons for misdetection were as follows: the testing panel did not cover the genes or the whole exon and splice sites of the genes; the variants were misclassified as benign or likely benign, and the variants failed the QC criteria.

Conclusions

The discrepancies observed in our survey and EQA test affect the authenticity of HRR gene test results for prostate cancer, underlining the need to establish guidelines for HRR gene testing and variant interpretation in China, and to optimize HRR gene testing in clinical practice to improve management and patient care.