Intensity modulated radiotherapy in combination with endocrinotherapy in the treatment of middle and advanced Prostatic Cancer

Outcomes in studies regarding older patients with prostate cancer: A systematic review

INTRODUCTION

Older patients are often deemed ineligible for clinical research, and many frequently-used endpoints and outcome measures are not as relevant for older patients for younger ones. This systematic review aimed to present an overview of outcomes used in clinical research regarding patients over the age of 65 years with prostate cancer.

MATERIALS AND METHODS

PubMed and Embase were systematically searched to identify studies on prostate cancer (treatment) in patients aged ≥65 between 2016 and 2023. Data on title, study design, number of participants and age, stage of disease, treatment, and investigated outcomes were synthesized and descriptively analyzed.

RESULTS

Sixty-eight studies were included. Of these most included patients over 65 years, while others used a higher age. Overall, 39 articles (57.3%) reported on survival-related outcomes, 22 (32.4%) reported on progression of disease and 38 (55.9%) used toxicity or adverse events as an outcome measure. Health-related quality of life and functional outcomes were investigated in 29.4%, and cognition in two studies. The most frequently investigated survival-related outcomes were overall and cancer-specific survival (51.3%); however, 38.5% only studied overall survival.

DISCUSSION

The main focus of studies included in this review remains survival and disease progression. There is limited attention for health-related quality of life and functional status, although older patients often prioritize the latter. Future research should incorporate outcome measures tailored to the aged population to improve care for older patients with prostate cancer.

Prognostic value of lncRNA LINC01018 in prostate cancer by regulating miR-182-5p (The role of LINC01018 in prostate cancer)

LncRNAs are abnormally expressed in a variety of cancers and play unique roles in therapy. Based on this, the prognostic value of lncRNA LINC01018 in prostate cancer was discussed in this study. LINC01018 was underexpressed in prostate cancer tissues and cells, while miR-182-5p was elevated (***p < 0.001). Overexpression of LINC01018 may inhibit the progression of prostate cancer by targeting miR-182-5p. This study revealed that upregulated LINC01018 may prolong the overall survival of patients with prostate cancer (log-rank p = 0.042), and LINC01018 may become a prognostic biomarker for patients with prostate cancer, which brings a new direction for the treatment of patients.

Transcription Factor ELF1 Modulates Cisplatin Sensitivity in Prostate Cancer by Targeting MEIS Homeobox 2

As a widely used first-line agent for prostate cancer treatment, cisplatin is facing drug resistance which has resulted in chemotherapy failure in many prostate cancer patients, while the related molecular mechanisms remain unclear. In this study, we discovered that MEIS homeobox 2 (MEIS2) was lowly expressed in prostate cancer tissues by bioinformatics analysis, which had a close connection with the T stage and N stage of the tumor. Cell function experiments demonstrated that MEIS2 overexpression was capable of significantly suppressing proliferation of tumor cells, arresting prostate cancer cells in G0/G1 phase, and promoting DNA damage, thereby enhancing the sensitivity of prostate cancer to cisplatin. Dual-luciferase assay and chromatin co-immunoprecipitation (ChIP) assays confirmed the binding relationship between MEIS2 and ELF1. The results of rescue assay showed that ELF1 could promote DNA damage and enhance the sensitivity of tumor cells to cisplatin by activating MEIS2. In conclusion, the results of this study demonstrated that ELF1 could modulate DNA damage through activating MEIS2 and thus enhance cisplatin sensitivity in prostate cancer. This study suggested that the ELF1/MEIS2 axis may be a therapeutic target to strengthen cisplatin sensitivity in prostate cancer.

MRI-Based Nomogram of Prostate Maximum Sectional Area and Its Zone Area for Prediction of Prostate Cancer

Objective

To reduce unnecessary prostate biopsies, we designed a magnetic resonance imaging (MRI)-based nomogram prediction model of prostate maximum sectional area (PA) and investigated its zone area for diagnosing prostate cancer (PCa).

Methods

MRI was administered to 691 consecutive patients before prostate biopsies from January 2012 to January 2020. PA, central gland sectional area (CGA), and peripheral zone sectional area (PZA) were measured on axial T2-weighted prostate MRI. Multivariate logistic regression analysis and area under the receiver operating characteristic (ROC) curve were performed to evaluate and integrate the predictors of PCa. Based on multivariate logistic regression coefficients after excluding combinations of collinear variables, three models and nomograms were generated and intercompared by Delong test, calibration curve, and decision curve analysis (DCA).

Results

The positive rate of PCa was 46.74% (323/691). Multivariate analysis revealed that age, PSA, MRI, transCGA, coroPZA, transPA, and transPAI (transverse PZA-to-CGA ratio) were independent predictors of PCa. Compared with no PCa patients, transCGA (AUC = 0.801) was significantly lower and transPAI (AUC = 0.749) was significantly higher in PCa patients. Both of them have a significantly higher AUC than PSA (AUC = 0.714) and PV (AUC = 0.725). Our best predictive model included the factors age, PSA, MRI, transCGA, and coroPZA with the AUC of 0.918 for predicting PCa status. Based on this predictive model, a novel nomogram for predicting PCa was conducted and internally validated (C-index = 0.913).

Conclusions

We found the potential clinical utility of transCGA and transPAI in predicting PCa. Then, we firstly built the nomogram based on PA and its zone area to evaluate its diagnostic efficacy for PCa, which could reduce unnecessary prostate biopsies.