Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer.

The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.

Prediction of Prognosis and Response to Androgen Deprivation Therapy in Intermediate to High-Risk Prostate Cancer Using 18F-FDG PET/CT Radiomics.

RATIONALE AND OBJECTIVES: This study aims to predict intermediate to high-risk prostate cancer (PCa) prognosis based on 18-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) radiomics. Additionally, subgroup analysis will be performed on the androgen deprivation therapy (ADT) group and the metastatic PCa group. MATERIALS AND METHODS: In the retrospective analysis of 104 intermediate to high-risk PCa patients who underwent 18F-FDG PET/CT prior to treatment. The data set was divided into a training set (n = 72) and a testing set (n = 32). Two different PET/CT models were constructed using multivariate logistic regression with cross-validation: radiomics model A and an alternative ensemble learning-based model B. The superior model was then selected to develop a radiomics nomogram. Separate models were also developed for the ADT and metastatic PCa subgroups. RESULTS: Model A, which integrates eight radiomics features showed excellent performance with an area under curve (AUC) of 0.844 in the training set and 0.804 in the testing set. The radiomics nomogram incorporating the radiomics score (radscore) from model A and the tumor-to-liver ratio (TLR) showed good prognostic accuracy in the testing set with an AUC of 0.827. In the subgroup analyses for endocrine therapy and metastatic cancer, the PET/CT radiomics model showed AUCs of 0.845 and 0.807 respectively, suggesting its potential effectiveness. CONCLUSION: The study establishes the utility of the 18F-FDG PET/CT radiomics nomogram in predicting the prognosis of intermediate to high-risk PCa patients, indicating its potential for clinical application.

Genetic Diversity and Natural Selection of the Plasmodium knowlesi Circumsporozoite Protein Nonrepeat Regions.

BACKGROUND: Plasmodium knowlesi is a simian malaria parasite that has been identified to cause malaria in humans. To date, several thousand cases of human knowlesi malaria have been reported around Southeast Asia. Thus far, there is no detailed study on genetic diversity and natural selection of P. knowlesi circumsporozoite protein (CSP), a prominent surface antigen on the sporozoite of the parasite. In the present study, the genetic diversity and natural selection acting on the nonrepeat regions of the gene encoding P. knowlesi CSP were investigated, focusing on the T-cell epitope regions at the C-terminal of the protein. METHODS: Blood samples from 32 knowlesi malaria patients and 2 wild monkeys (Macaca fascicularis) were used. The CSP of the P. knowlesi isolates was amplified by PCR, cloned into Escherichia coli, and sequenced. The nonrepeat regions of the CSP gene were analysed for genetic diversity, natural selection and haplotypic grouping using MEGA5 and DnaSP version 5.10.00 programmes. A haplotype network was constructed based on the C-terminal (Th2R/Th3R) T-cell epitope regions using the Median-Joining method in the NETWORK version 4.6.1.2 programme. Previously published sequences from other regions (Malaysia Borneo, Singapore) were also included in the analysis. RESULTS: A total of 123 P. knowlesi CSP sequences were analysed. Multiple sequence alignment revealed 58 amino acid changes, and 42 novel amino acid haplotypes were identified. Polymorphism was higher in the C-terminal Th2R/Th3R epitope (π = 0.0293, n = 123) region compared to the overall combined nonrepeat regions (π = 0.0120, n = 123). Negative natural selection was observed within the nonrepeat regions of the CSP gene. Within the C-terminal Th2R/Th3R epitope regions, there was evidence of slight positive selection. Based on haplotype network analysis of the Th2R/Th3R regions, five abundant haplotypes were identified. Sharing of haplotypes between humans and macaques were observed. CONCLUSION: This study contributes to the understanding of the type and distribution of naturally occurring polymorphism in the P. knowlesi CSP gene. This study also provides a measurement of the genetic diversity of P. knowlesi and identifies the predominant haplotypes within Malaysia based on the C-terminal Th2R/Th3R regions.

Genetic polymorphism in domain I of the apical membrane antigen-1 among Plasmodium knowlesi clinical isolates from Peninsular Malaysia.

The simian malaria parasite Plasmodium knowlesi is now recognized as a species that can cause human malaria. The first report of large scale human knowlesi malaria was in 2004 in Malaysia Borneo. Since then, hundreds of human knowlesi malaria cases have been reported in Southeast Asia. The present study investigates the genetic polymorphism of P. knowlesi DI domain of the apical membrane antigen-1 (AMA-1), a protein considered as a promising vaccine candidate for malaria. The DI domain of AMA-1 gene of P. knowlesi clinical isolates from Peninsular Malaysia was amplified by PCR, cloned into Escherichia coli, then sequenced and analysed. Ninety-seven DI domain sequences were obtained. Comparison at the nucleotide level against P. knowlesi strain H as reference sequence showed 21 synonymous and 25 nonsynonymous mutations. Nonetheless, nucleotide sequence analysis revealed low genetic diversity of the DI domain, and it was under purifying (negative) selection. At the amino acid level, 26 different haplotypes were identified and 2 were predominant haplotypes (H1, H2) with high frequencies. Phylogenetic analysis revealed that the 26 haplotypes could be clustered into 2 distinct groups (I and II). Members of the groups were basically derived from haplotypes H1 and H2, respectively.