A new risk stratification system of prostate cancer to identify high-risk biochemical recurrence patients

Abstract

Background: Biochemical recurrence (BCR) is considered a decisive risk factor for clinical recurrence and the metastasis of prostate cancer (PCa). Therefore, we developed and validated a signature which could be used to accurately predict BCR risk and aid in the selection of PCa treatments.Methods: A comprehensive genome-wide analysis of data concerning PCa from previous datasets of the Cancer Genome Atlas (TCGA) and the gene expression omnibus (GEO) was performed. Lasso and Cox regression analyses were performed to develop and validate a novel signature to help predict BCR risk. Moreover, a nomogram was constructed by combining the signature and clinical variables.Results: A total of 977 patients were involved in the study. This consisted of patients from the TCGA (n=405), GSE21034 (n=131), GSE70770 (n=193) and GSE116918 (n=248) datasets. A 9-mRNA signature was identified in the TCGA dataset (composed of C9orf152, EPHX2, ASPM, MMP11, CENPF, KIF4A, COL1A1, ASPN, and FANCI) which was significantly associated with BCR (HR =3.72, 95% CI: 2.30-6.00, P<0.0001). This signature was validated in the GSE21034 (HR =7.54, 95% CI: 3.15-18.06, P=0.019), GSE70770 (HR =2.52, 95% CI: 1.50-4.22, P=0.0025) and GSE116918 datasets (HR =4.75, 95% CI: 2.51-9.02, P=0.0035). Multivariate Cox regression and stratified analysis showed that the 9-mRNA signature was a clinical factor independent of prostate-specific antigen (PSA), Gleason score (GS), or AJCC T staging. The mean AUC for 5-year BCR-free survival predictions of the 9-mRNA signature (0.81) was higher than the AUC for PSA, GS, or AJCC T staging (0.52-0.73). Furthermore, we combined the 9-mRNA signature with PSA, GS, or AJCC T staging and demonstrated that this could enhance prognostic accuracy. Conclusions:The proposed 9-mRNA signature is a promising biomarker for predicting BCR-free survival in PCa. However, further controlled trials are needed to validate our results and explore a role in individualized management of PCa.

Screening to Identify an Immune Landscape-Based Prognostic Predictor and Therapeutic Target for Prostate Cancer

“…Except for MMP11, all of them presented a strong positive correlation with the immune score. To our knowledge, only MMP11 and HAPLN3 have been reported as possible diagnostic biomarkers or prognostic predictors for PCa (22)(23)(24)(25). There is no research on the roles of ARHGAP4 and HAOPLN3 in PCa, but the existing evidence indicates that their functions in tumor recurrence and metastases should not be ignored.…”

A Novel Gene Signature Associated With “E2F Target” Pathway for Predicting the Prognosis of Prostate Cancer

“…Recent studies show that PLK1 and KIF4A as biomarkers have a high prognosis value in patients with prostate cancer ( Gao et al, 2018 ; Cao et al, 2020 ; Liu et al, 2020 ; Wu et al, 2020 ; Das et al, 2021 ). PLK1 has been proven to be a potent and promising target for prostate cancer treatment ( Mao et al, 2018 ; Shin et al, 2019 ).…”

Identifying prognostic signatures in the microenvironment of prostate cancer

“…The immune response in the tumor immune microenvironment composed of these immune cells, including secretion and cytokines, can greatly affect the balance between tumor progression, tumor clearance and treatment response (11). In addition, increasing research has suggested that cells in the TME have clinicopathological significance in predicting patient prognosis and the therapeutic efficacy of drugs (4,5). In various malignancies, including gastric cancer and glioma, gene signatures from the TME were significantly associated with the outcomes of patients (6,12).…”

“…Prostate cancer (PCa) is the most common non-cutaneous malignancy among men and the second leading cause of cancer-related death worldwide (1,2). The prognosis and treatment decisions of PCa are based on the malignant grade using the Gleason score, the clinical stage of the tumor-node-metastasis system (TNM), and serum PSA level (3,4). Despite these well-established clinical predictive and prognostic factors, drastically variable outcomes are observed among PCa patients with similar stages and malignant grades (5).…”