Metalloproteinase 11, potential marker and molecular target in advanced and castration-resistant prostate cancer. Culture study of peritumoral fibroblasts

A tumor-associated macrophages related model for predicting biochemical recurrence and tumor immune environment in prostate cancer

OBJECTIVE

To identify tumor-associated macrophages (TAMs) related molecular subtypes and develop a TAMs related prognostic model for prostate cancer (PCa).

METHODS

Consensus clustering analysis was used to identify TAMs related molecular clusters. A TAMs related prognostic model was developed using univariate and multivariate Cox analysis.

RESULTS

Three TAMs related molecular clusters were identified and were confirmed to be associated with prognosis, clinicopathological characteristics, PD-L1 expression levels and tumor microenvironment. A TAMs related prognostic model was constructed. Patients in low-risk group all showed a more appreciable biochemical recurrence-free survival (BCRFS) than patients in high-risk group in train cohort, test cohort, entire TCGA cohort and validation cohort. SLC26A3 attenuated progression of PCa and prevented macrophage polarizing to TAMs phenotype, which was initially verified.

CONCLUSIONS

We successfully identified molecular clusters related to TAMs. Additionally, we developed a prognostic model involving TAMs that exhibits excellent predictive performance for biochemical recurrence-free survival in PCa.

An anoikis-related gene signature for prediction of the prognosis in prostate cancer

Purpose

This study presents a novel approach to predict postoperative biochemical recurrence (BCR) in prostate cancer (PCa) patients which involves constructing a signature based on anoikis-related genes (ARGs).

Methods

In this study, we utilised data from TCGA-PARD and GEO databases to identify specific ARGs in prostate cancer. We established a signature of these ARGs using Cox regression analysis and evaluated their clinical predictive efficacy and immune-related status through various methods such as Kaplan-Meier survival analysis, subject work characteristics analysis, and CIBERSORT method. Our findings suggest that these ARGs may have potential as biomarkers for prostate cancer prognosis and treatment. To investigate the biological pathways of genes associated with anoikis, we utilised GSVA, GO, and KEGG. The expression of ARGs was confirmed by the HPA database. Furthermore, we conducted PPI analysis to identify the core network of ARGs in PCa.

Results

Based on analysis of the TCGA database, a set of eight ARGs were identified as prognostic signature genes for prostate cancer. The reliability and validity of this signature were well verified in both the TCGA and GEO codifications. Using this signature, patients were classified into two groups based on their risk for developing BCR. There was a significant difference in BCR-free time between the high and low risk groups (P < 0.05).This signature serves as a dependable and unbiased prognostic factor for predicting biochemical recurrence (BCR) in prostate cancer (PCa) patients. It outperforms clinicopathological characteristics in terms of accuracy and reliability. PLK1 may play a potential regulatory role as a core gene in the development of prostate cancer.

Conclusion

This signature suggests the potential role of ARGs in the development and progression of PCa and can effectively predict the risk of BCR in PCa patients after surgery. It also provides a basis for further research into the mechanism of ARGs in PCa and for the clinical management of patients with PCa.

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

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.

Significance of expression of EIF3h, MMP-10 and MMP-11 in colonic adenocarcinoma

AIM

To detect the expression of eukaryotic translation initiation factor 3h (EIF3h), matrix metallopeptidase 10 (MMP-10), and matrix metallopeptidase 11 (MMP-11) in colonic adenocarcinoma and to analyze their clinical significance.

METHODS

One hundred and ten colonic adenocarcinoma tissues, 43 high-grade colorectal intraepithelial neoplasia tissues, 43 low-grade colorectal intraepithelial neoplasia tissues, and 43 normal colonic mucosal tissues were collected. The expression of EIF3h, MMP-10, and MMP-11 in the above tissues was detected by immunohistochemistry.

RESULTS

The expression of EIF3h, MMP-10, and MMP-11 differed significantly among the four groups. Expression of EIF3h, MMP-10, and MMP-11 was correlated with lymph node metastasis. Expression of EIF3h was correlated with tumor size, differentiation, proliferation index, and TNM stage. Expression of MMP-10 and MMP-11 was correlated with vascular invasion. There was a positive correlation between MMP-10 and MMP-11 expression in colonic adenocarcinoma.

CONCLUSION

High expression and synergy of EIF3h, MMP-10, and MMP-11 can promote tumor formation and progression in colonic adenocarcinoma. EIF3h may be associated with the prognosis of colonic adenocarcinoma.