Options for Curative Treatment of Localized Prostate Cancer

Single-port robotic system - a paradigm shift in robot-assisted radical prostatectomy?

INTRODUCTION

Robotic-assisted radical prostatectomy (RARP) has become a cornerstone in the surgical management of prostate cancer. This study evaluates the potential of the Da Vinci single-port (SP) system, which represents a significant advancement in minimally invasive surgery.

AREAS COVERED

A narrative review was conducted using PubMed and Scopus databases to identify relevant studies published between January 2018 and February 2025. Search terms included 'single-port robotic prostatectomy,' 'Da Vinci SP system,' and 'robot-assisted radical prostatectomy.' Studies comparing SP and multi-port (MP) systems were prioritized. The SP system is discussed in terms of its technical innovations, including 360° operative field visualization, integrated optics and instruments, and enhanced depth perception. Clinical benefits, such as reduced blood loss, faster recovery, improved cosmetic outcomes, and reduced surgical trauma, are highlighted. Comparisons are drawn between the SP and multi-port systems, focusing on oncological and functional outcomes, as well as the challenges associated with the SP system's steeper learning curve.

EXPERT OPINION

The SP system holds great promise in advancing patient care in RARP, particularly through its minimally invasive approach. While achieving comparable outcomes to MP systems, it uniquely reduces surgical trauma. However, successful implementation requires overcoming technical challenges and adapting to the learning curve. Future research should focus on refining the technology and exploring its long-term impact on clinical outcomes.

TOR1 AIP1 interacts with p53 to enhance cell cycle dysregulation in prostate cancer progression

The cell cycle mechanism is an integration point where information is sent through an upstream signaling network, making it a potential target for cancer diagnosis and treatment. The LAP1 protein, encoded by the Tor1aip1 gene, is required to maintain the shape of the nuclear envelope and the progression of the cell cycle. The aim of this study was to determine the role of Tor1aip1 gene in PRAD development and its mechanism. We analyzed the expression and survival data of TOR1 AIP1 in PRAD patients in the TCGA database and verified the low expression of TOR1 AIP1 in prostate cancer by qPCR, western blot and immunohistology, which was correlated with the tumor stage and survival prognosis of PRAD. In addition, lentiviral vectors were used to mediate the up-regulation or down-regulation of TOR1 AIP1 expression in prostate cancer cells, and the effects of TOR1 AIP1 on tumor proliferation and related signaling pathways were investigated by cell counting kit- 8, colony formation assay, transwell assay, western blot, and flow cytometry. As a result, we found that TOR1 AIP1 enhances protein stability of p53 by directly interacting with p53, consequently inhibited tumor proliferation and invasion by inducing the cell cycle to be arrested in the S phase. Therefore, TOR1 AIP1 represents a promising therapeutic target in PRAD due to its ability to stabilize p53 and enhance its tumor-suppressive functions. Future studies should focus on elucidating its mechanisms, developing targeted therapies, and exploring its clinical potential in combination with existing treatments. By advancing our understanding of TOR1 AIP1, we may unlock new strategies for improving outcomes in PRAD patients.

Quadrifecta outcomes and their predictors following robotic radical prostatectomy: a study of newly established robotic center in India

Active surveillance (AS), radical prostatectomy (RP), and radical radiotherapy (RT) are the three options for localized prostate cancer. Only a few studies have been conducted in developing countries or in centers in their initial learning curve that predict the outcomes of RARP. Therefore, this study aimed to present data from a novice center; how we started and progressed, and to compare our results with the rest of the world. This is a retrospective analysis to study the outcomes following robot-assisted radical prostatectomy and to identify the predictors of quadrifecta outcomes, i.e., the patients who were continent, did not have complications, were biochemical recurrence free with at least 1 year of follow-up and had negative surgical margins. In our data, we excluded the erectile function as one of the parameters as the majority of our patients were not sexually active or did not want to discuss this parameter. Seventy-two patients were included in this study, and 50 (69.4%) of these achieved the quadrifecta outcomes. Of all the factors, studied, seven factors were statistically significantly different between Group I (quadrifecta achieved) and Group II (quadrifecta not achieved), namely, BMI, co-morbidities like CAD, COPD, ASA grade, pre-op D'Amico risk stratification groups, clinical staging, positive lymph-node status, and hospital stay. With this study, we reported outcomes of RARP in a newly established robotic center and the results were fairly comparable with the well-developed center in India and abroad, emphasizing the short learning curve, and so, the requirement of establishing more robotic surgery centers in developing as well as developed countries.

Developing a Multimodal Model for Detecting Higher-Grade Prostate Cancer Using Biomarkers and Risk Factors

A technique to predict crucial clinical prostate cancer (PC) is desperately required to prevent diagnostic errors and overdiagnosis. To create a multimodal model that incorporates long-established messenger RNA (mRNA) indicators and conventional risk variables for identifying individuals with severe PC on prostatic biopsies. Urinary has gathered for mRNA analysis following a DRE and before a prostatic examination in two prospective multimodal investigations. A first group (n = 489) generated the multimodal risk score, which was then medically verified in a second group (n = 283). The reverse transcription qualitative polymerase chain reaction determined the mRNA phase. Logistic regression was applied to predict risk in patients and incorporate health risks. The area under the curve (AUC) was used to compare models, and clinical efficacy was assessed by using a DCA. The amounts of sixth homeobox clustering and first distal-less homeobox mRNA have been strongly predictive of high-grade PC detection. In the control subjects, the multimodal method achieved a total AUC of 0.90, with the most important aspects being the messenger riboneuclic acid features' PSA densities and previous cancer-negative tests as a nonsignificant design ability to contribute to PSA, aging, and background. An AUC of 0.86 was observed for one more model that added DRE as an extra risk component. Two methods were satisfactorily verified without any significant changes within the area under the curve in the validation group. DCA showed a massive net advantage and the highest decrease in inappropriate costs.