Impact TMPRSS2-ERG Molecular Subtype on Prostate Cancer Recurrence

Exploring therapeutic applications of PTEN, TMPRSS2:ERG fusion, and tumour molecular subtypes in prostate cancer management

Background

Prostate cancer is defined by the suppression of genes that suppress tumours and the activation of proto-oncogenes. These are the hallmarks of prostate cancer, and they have been linked to numerous genomic variations, which lead to unfavourable treatment outcomes. Prostate cancer can be categorised into various risk groups of tumour molecular subtypes grounded in the idea of genomic structural variations connected to TMPRSS2:ERG fusion and loss of PTEN. Research suggests that certain genomic alterations may be more prevalent or exhibit different patterns in prostate cancer tumours across populations. Studies have reported a higher frequency of PTEN loss and TMPRSS2:ERG fusion in prostate tumours of Black/African American men, which may contribute to the more aggressive nature of the disease in this population. Thus, therapeutically important information can be obtained from these structural variations, including correlations with poor prognosis and disease severity.

Methods

Peer-reviewed articles from 1998 to 2024 were sourced from PubMed and Google Scholar. During the review process, the following search terms were employed: "Tumour suppressor genes OR variations OR alterations OR oncogenes OR diagnostics OR ethnicity OR biomarkers OR prostate cancer genomics OR prostate cancer structural variations OR tumour and molecular subtypes OR therapeutic implications OR immunotherapy OR immunogenetics."

Results

There was a total of 13,012 results for our search query: 5,903 publications from Google Scholar with the patent and citation unchecked filer options, and 7127 articles from PubMed with the abstract, free full text, and full-text options selected. Unpublished works were not involved. Except for four articles published between 1998 and 1999, all other selected articles published in 2000 and later were considered. However, papers with irrelevant information or redundant or duplicate content were not chosen for this review. Thus, 134 met the inclusion criteria and were ultimately retained for this review.

Conclusion

This review extracted 134 relevant articles about genomic structure variations in prostate cancer. Our findings demonstrate the importance of PTEN and TMPRSS2:ERG fusion and tumour molecular subtyping in prostate cancer precision medicine.

Contemporary review of prognostic markers of prostate cancer from a pathologist perspective

Prostate cancer is the most frequently diagnosed malignant tumour in men worldwide. To treat this condition, prognostic markers to distinguish indolent from aggressive disease, and biomarkers for metastatic forms are needed. From a pathologist's perspective, despite the plethora of emerging biomarkers, none to date has made its way into clinical practice. The need for prognostic and predictive markers following histological evaluation remains. This overview of some putative immunohistochemical and genetic markers reveals the pitfalls of biomarker research, notably verifiability, validity and interlaboratory comparison. Meta-analyses and extensive cooperation between pathology departments are a sine qua non. Codes of Best Practice such as the REMARK guidelines have been advocated as a path forward. Currently, the most widely used and validated prognostic marker remains the Gleason score. Ki67 along with PTEN are the most promising prognostic markers.

AR and YAP crosstalk: impacts on therapeutic strategies in prostate cancer

Prostate cancer ranks as one of the most common types of cancer affecting men worldwide, and its progression is shaped by a diverse array of influencing factors. The AR signaling pathway plays a pivotal role in the pathogenesis of prostate cancer. While existing anti-androgen treatments show initial efficacy, they ultimately do not succeed in halting the advancement to CRPC. Recent studies have identified alterations in the Hippo-YAP signaling pathway within prostate cancer, highlighting intricate crosstalk with the AR signaling pathway. In this review, we examine the interactions and underlying mechanisms between AR and YAP, the key molecules in these two signaling pathways. AR regulates the stability and function of YAP by modulating its transcription, translation, and phosphorylation status, while YAP exerts both promotional and inhibitory regulatory effects on AR. Based on these findings, this paper investigates their significant roles in the onset, progression, and therapeutic resistance of prostate cancer, and discusses the clinical potential of YAP in prostate cancer treatment.

Three possible diagnostic biomarkers for gastric cancer: miR-362-3p, miR-362-5p and miR-363-5p

Aim: MicroRNAs can be regarded as biomarkers for gastric cancer (GC) diagnosis in the early stages. This study assesses the expression levels of miR-362-3p, miR-362-5p and miR-363-5p as potential biomarkers for GC.Materials & methods: The expression levels of the miRNAs in 90 pairs of GC and adjacent normal tissue samples were analyzed by quantitative real-time reverse transcription PCR (qRT-PCR) and some bioinformatics tools were utilized for analyzing the target genes and possible molecular pathways in which these miRNAs participate.Results & conclusion: There was a significant overexpression of the miRNAs in GC cells and an outstanding correlation between their overexpression with some clinicopathological features of the patients.

Individualized detection of TMPRSS2-ERG fusion status in prostate cancer: a rank-based qualitative transcriptome signature

BACKGROUND

TMPRSS2-ERG (T2E) fusion is highly related to aggressive clinical features in prostate cancer (PC), which guides individual therapy. However, current fusion prediction tools lacked enough accuracy and biomarkers were unable to be applied to individuals across different platforms due to their quantitative nature. This study aims to identify a transcriptome signature to detect the T2E fusion status of PC at the individual level.

METHODS

Based on 272 high-throughput mRNA expression profiles from the Sboner dataset, we developed a rank-based algorithm to identify a qualitative signature to detect T2E fusion in PC. The signature was validated in 1223 samples from three external datasets (Setlur, Clarissa, and TCGA).

RESULTS

A signature, composed of five mRNAs coupled to ERG (five ERG-mRNA pairs, 5-ERG-mRPs), was developed to distinguish T2E fusion status in PC. 5-ERG-mRPs reached 84.56% accuracy in Sboner dataset, which was verified in Setlur dataset (n = 455, accuracy = 82.20%) and Clarissa dataset (n = 118, accuracy = 81.36%). Besides, for 495 samples from TCGA, two subtypes classified by 5-ERG-mRPs showed a higher level of significance in various T2E fusion features than subtypes obtained through current fusion prediction tools, such as STAR-Fusion.

CONCLUSIONS

Overall, 5-ERG-mRPs can robustly detect T2E fusion in PC at the individual level, which can be used on any gene measurement platform without specific normalization procedures. Hence, 5-ERG-mRPs may serve as an auxiliary tool for PC patient management.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

Transcriptome Profiling of Prostate Cancer, Considering Risk Groups and the TMPRSS2-ERG Molecular Subtype

Molecular heterogeneity in prostate cancer (PCa) is one of the key reasons underlying the differing likelihoods of recurrence after surgical treatment in individual patients of the same clinical category. In this study, we performed RNA-Seq profiling of 58 localized PCa and 43 locally advanced PCa tissue samples obtained as a result of radical prostatectomy on a cohort of Russian patients. Based on bioinformatics analysis, we examined features of the transcriptome profiles within the high-risk group, including within the most commonly represented molecular subtype, TMPRSS2-ERG. The most significantly affected biological processes in the samples were also identified, so that they may be further studied in the search for new potential therapeutic targets for the categories of PCa under consideration. The highest predictive potential was found with the EEF1A1P5, RPLP0P6, ZNF483, CIBAR1, HECTD2, OGN, and CLIC4 genes. We also reviewed the main transcriptome changes in the groups at intermediate risk of PCa-Gleason Score 7 (groups 2 and 3 according to the ISUP classification)-on the basis of which the LPL, MYC, and TWIST1 genes were identified as promising additional prognostic markers, the statistical significance of which was confirmed using qPCR validation.

ALDH3A2, ODF2, QSOX2, and MicroRNA-503-5p Expression to Forecast Recurrence in TMPRSS2-ERG-Positive Prostate Cancer

Following radical surgery, patients may suffer a relapse. It is important to identify such patients so that therapy tactics can be modified appropriately. Existing stratification schemes do not display the probability of recurrence with enough precision since locally advanced prostate cancer (PCa) is classified as high-risk but is not ranked in greater detail. Between 40 and 50% of PCa cases belong to the TMPRSS2-ERG subtype that is a sufficiently homogeneous group for high-precision prognostic marker search to be possible. This study includes two independent cohorts and is based on high throughput sequencing and qPCR data. As a result, we have been able to suggest a perspective-trained model involving a deep neural network based on both qPCR data for mRNA and miRNA and clinicopathological criteria that can be used for recurrence risk forecasts in patients with TMPRSS2-ERG-positive, locally advanced PCa (the model uses ALDH3A2 + ODF2 + QSOX2 + hsa-miR-503-5p + ISUP + pT, with an AUC = 0.944). In addition to the prognostic model’s use of identified differentially expressed genes and miRNAs, miRNA–target pairs were found that correlate with the prognosis and can be presented as an interactome network.

Gene of the month: ERG

The ERG gene belongs to the erythroblastosis transformation specific family of transcription factors and encodes for the transcription regulator protein ERG. It is located on chromosome 22q22 and is a nuclear transcription factor. In normal physiology, ERG protein is expressed in endothelial cells and is involved in processes including, but not limited to, angiogenesis and haematopoiesis. Of diagnostic value in clinical practice, ERG immunohistochemistry is a useful marker of endothelial differentiation for both benign and malignant vascular lesions. It is also reliable for identifying ERG gene translocated malignancies such as EWS/FUS::ERG Ewing's sarcoma and TMPSSR2::ERG prostatic carcinoma.

Characterization of Immune-Based Molecular Subtypes and Prognostic Model in Prostate Adenocarcinoma

Prostate adenocarcinoma (PRAD), also named prostate cancer, the most common visceral malignancy, is diagnosed in male individuals. Herein, in order to obtain immune-based subtypes, we performed an integrative analysis to characterize molecular subtypes based on immune-related genes, and further discuss the potential features and differences between identified subtypes. Simultaneously, we also construct an immune-based risk model to assess cancer prognosis. Our findings showed that the two subtypes, C1 and C2, could be characterized, and the two subtypes showed different characteristics that could clearly describe the heterogeneity of immune microenvironments. The C2 subtype presented a better survival rate than that in the C1 subtype. Further, we constructed an immune-based prognostic model based on four screened abnormally expressed genes, and they were selected as predictors of the robust prognostic model (AUC = 0.968). Our studies provide reference for characterization of molecular subtypes and immunotherapeutic agents against prostate cancer, and the developed robust and useful immune-based prognostic model can contribute to cancer prognosis and provide reference for the individualized treatment plan and health resource utilization. These findings further promote the development and application of precision medicine in prostate cancer.

The Expression of Proto-Oncogene ETS-Related Gene (ERG) Plays a Central Role in the Oncogenic Mechanism Involved in the Development and Progression of Prostate Cancer

The ETS-related gene (ERG) is proto-oncogene that is classified as a member of the ETS transcription factor family, which has been found to be consistently overexpressed in about half of the patients with clinically significant prostate cancer (PCa). The overexpression of ERG can mostly be attributed to the fusion of the ERG and transmembrane serine protease 2 (TMPRSS2) genes, and this fusion is estimated to represent about 85% of all gene fusions observed in prostate cancer. Clinically, individuals with ERG gene fusion are mostly documented to have advanced tumor stages, increased mortality, and higher rates of metastasis in non-surgical cohorts. In the current review, we elucidate ERG’s molecular interaction with downstream genes and the pathways associated with PCa. Studies have documented that ERG plays a central role in PCa progression due to its ability to enhance tumor growth by promoting inflammatory and angiogenic responses. ERG has also been implicated in the epithelial–mesenchymal transition (EMT) in PCa cells, which increases the ability of cancer cells to metastasize. In vivo, research has demonstrated that higher levels of ERG expression are involved with nuclear pleomorphism that prompts hyperplasia and the loss of cell polarity.