齋藤 心平

BACKGROUND: For biochemical recurrence following radical prostatectomy for prostate cancer, treatments such as radiation therapy and androgen deprivation therapy are administered. To diagnose postoperative recurrence as early as possible and to intervene with treatment at the appropriate time, it is essential to accurately predict recurrence after radical prostatectomy. However, postoperative recurrence involves numerous patient-related factors, making its prediction challenging. The purpose of this study is to accurately predict the timing of biochemical recurrence after radical prostatectomy and to analyze the risk factors for follow-up of high-risk patients and early detection of recurrence. METHODS: We utilized the machine learning survival analysis model called the Random Survival Forest utilizing the 58 clinical factors from 548 patients who underwent radical prostatectomy at Chiba University Hospital. To visualize prognostic factors and assess accuracy of the time course probability, we employed SurvSHAP(t) and time-dependent Area Under Cureve(AUC). RESULTS: The time-dependent AUC of RSF was 0.785, which outperformed the Cox proportional hazards model (0.704), the Cancer of the Prostate Risk Assessment (CAPRA) score (0.710), and the D'Amico score (0.658). The key prognostic factors for early recurrence were Gleason score(GS), Seminal vesicle invasion(SV), and PSA. The contribution of PSA to recurrence decreases after the first year, while SV and GS increase over time. CONCLUSION: Our prognostic model analyzed the time-dependent relationship between the timing of recurrence and prognostic factors. Our study achieved personalized prognosis analysis and its rationale after radical prostatectomy by employing machine learning prognostic model. This prognostic model contributes to the early detection of recurrence by enabling clinicians to conduct appropriate follow-ups for high-risk patients.

OBJECTIVES: Renal cell carcinoma (RCC) is shown to have a tendency for late recurrence, occurring 5 or more years after curative surgery. Imaging diagnosis is required for follow-up, and there is no definitive answer as to how long this should continue. Some patients discontinue follow-up visits at their own discretion. How best to predict late recurrence and loss to follow-up (LF) remains unclear. PATIENTS AND METHODS: This study targeted patients diagnosed with non-metastatic RCC who underwent either radical or partial nephrectomy at Chiba University Hospital between 1988 and 2021. Follow-up for patients with RCC is typically lifelong. We used random survival forests (RSFs), a machine learning-based survival analysis method, to predict late recurrence and LF. For verification of prediction accuracy, we applied the time-dependent area under the receiver operating characteristic curve (t-AUC). To analyse the risks of late recurrence and LF, SurvSHAP(t) and partial dependence plots were used. RESULTS: We analysed 1051 cases in this study. Median follow-up was 58.5 (range: 0-376) months. The predictive accuracy of recurrence using RSF was t-AUC 0.806, 0.761, 0.674 and 0.566 at 60, 120, 180 and 240 months postoperatively, respectively. The recurrence risk impact showed a time-dependent increase up to approximately 50 months postoperatively. Beyond 50 months, there were no distinct risk factors characteristic of late recurrence. The predictive accuracy of LF using RSF was t-AUC 0.542, 0.699, 0.685, 0.628 and 0.674 at 60, 120, 180, 240 and 300 months postoperatively, respectively. The risk of LF increased with advancing age beyond 70 years. CONCLUSION: It is difficult to identify factors that predict late recurrence. For long-term follow-up observation, it is essential to pay particular attention to patients with RCC aged 70 years and above. Establishing frameworks to facilitate collaboration with local hospitals near patients' residences and providing care within the community is necessary.

BACKGROUND: To clarify the clinical roles of changes in testosterone (T) levels with a cut-off level of 20 ng/dL as predictive factors for prostate cancer patients treated with degarelix acetate. METHODS: A total of 120 prostate cancer patients who received hormone therapies with gonadotropin-releasing hormone antagonist degarelix acetate were retrospectively analyzed. The predictive values of nadir T levels, max T levels, T bounce, and other clinical factors were evaluated for overall survival (OS), cancer-specific survival (CSS), and progression-free survival (PFS). T bounce was defined as satisfying both nadir serum T levels of <20 ng/dL and max serum T levels of ≥20 ng/dL during hormone therapies. RESULTS: In 120 prostate cancer patients, 16 (13%) patients did not achieve nadir T < 20 ng/dL, and 76 (63%) patients had max T ≥ 20 ng/dL. The median times to nadir T and max T are 108 and 312 days, respectively. T bounce was shown in 60 (50%) patients and is associated with favorable prognoses both for OS (p = 0.0019) and CSS (p = 0.0013) but not for PFS (p = 0.92). While in the subgroup analyses of the patients with the progression of the first-line hormone therapies, T bounce predicts favorable OS (p = 0.0015) and CSS (p = 0.0013) after biochemical recurrence. CONCLUSIONS: The present study revealed that T bounce with cut-off levels of 20 ng/dL is a promising biomarker that predicts OS and CSS for prostate cancer patients treated with degarelix acetate.

L-type amino acid transporter 1 (LAT1) is specifically expressed in many malignancies, contributes to the transport of essential amino acids, such as leucine, and regulates the mammalian target of rapamycin (mTOR) signaling pathway. We investigated the expression profile and functional role of LAT1 in prostate cancer using JPH203, a specific inhibitor of LAT1. LAT1 was highly expressed in castration-resistant prostate cancer (CRPC) cells, including C4-2 and PC-3 cells, but its expression level was low in castration-sensitive LNCaP cells. JPH203 significantly inhibited [14C] leucine uptake in CRPC cells but had no effect in LNCaP cells. JPH203 inhibited the proliferation, migration, and invasion of CRPC cells but not of LNCaP cells. In C4-2 cells, Cluster of differentiation (CD) 24 was identified by RNA sequencing as a novel downstream target of JPH203. CD24 was downregulated in a JPH203 concentration-dependent manner and suppressed activation of the Wnt/β-catenin signaling pathway. Furthermore, an in vivo study showed that JPH203 inhibited the proliferation of C4-2 cells in a castration environment. The results of this study indicate that JPH203 may exert its antitumor effect in CRPC cells via mTOR and CD24.

L-type amino acid transporter 1 (LAT1, SLC7A5) is an amino acid transporter expressed in various carcinomas, and it is postulated to play an important role in the proliferation of cancer cells through the uptake of essential amino acids. Cabazitaxel is a widely used anticancer drug for treating castration-resistant prostate cancer (CRPC); however, its effectiveness is lost when cancer cells acquire drug resistance. In this study, we investigated the expression of LAT1 and the effects of a LAT1-specific inhibitor, JPH203, in cabazitaxel-resistant prostate cancer cells. LAT1 was more highly expressed in the cabazitaxel-resistant strains than in the normal strains. Administration of JPH203 inhibited the growth, migration, and invasive ability of cabazitaxel-resistant strains in vitro. Phosphoproteomics using liquid chromatography-mass spectrometry to comprehensively investigate changes in phosphorylation due to JPH203 administration revealed that cell cycle-related pathways were affected by JPH203, and that JPH203 significantly reduced the kinase activity of cyclin-dependent kinases 1 and 2. Moreover, JPH203 inhibited the proliferation of cabazitaxel-resistant cells in vivo. Taken together, the present study results suggest that LAT1 might be a valuable therapeutic target in cabazitaxel-resistant prostate cancer.