Identification of Potential Predictor of Biochemical Recurrence in Prostate Cancer

Wei, Jingchao; Wu, Xiaohang; Li, Yuxiang; Tao, Xiaowu; Wang, Bo; Yin, Guangming

doi:10.2147/ijgm.s355435

Cited by 10 publications

(7 citation statements)

References 31 publications

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“…The occurrence of BCR in patients with PCa after radical treatment indicates the likelihood of distant metastasis and the development of castration-resistant prostate cancer (CRPC) [ 8 ]. Although the advancement in salvage treatment regimens, including radiation therapy, androgen deprivation therapy, chemotherapy, and even intensive multimodal therapy, has improved the prognosis of patients with PCa, most still die within 2 to 4 years [ 22 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

“…Antonarakis et al reported that the median time for metastasis-free survival of patients with BCR was 10 years [ 7 ]. Studies have shown that clinicopathological factors, such as clinical staging, PSA, Gleason score, and surgical margin, cannot accurately predict BCR [ 8 ]. Therefore, it is urgent to seek new and more accurate BCR predictive markers and explore the pathogenesis of PCa.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Four Mitochondrial Respiration-Related Signature for Predicting Biochemical Recurrence of Prostate Cancer

Xia

Liu

Fan

et al. 2023

JCM

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The biochemical recurrence (BCR) of patients with prostate cancer (PCa) after radical prostatectomy is high, and mitochondrial respiration is reported to be associated with the metabolism in PCa development. This study aimed to establish a mitochondrial respiratory gene-based risk model to predict the BCR of PCa. RNA sequencing data of PCa were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and mitochondrial respiratory-related genes (MRGs) were sourced via GeneCards. The differentially expressed mitochondrial respiratory and BCR-related genes (DE-MR-BCRGs) were acquired through overlapping BCR-related differentially expressed genes (BCR-DEGs) and differentially expressed MRGs (DE-MRGs) between PCa samples and controls. Further, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analyses were performed to construct a DE-MRGs-based risk model. Then, a nomogram was established by analyzing the independent prognostic factor of five clinical features and risk scores. Moreover, Gene Set Enrichment Analysis (GSEA), tumor microenvironment, and drug susceptibility analyses were employed between high- and low-risk groups of PCa patients with BCR. Finally, qRT-PCR was utilized to validate the expression of prognostic genes. We identified 11 DE-MR-BCRGs by overlapping 132 DE-MRGs and 13 BCR-DEGs and constructed a risk model consisting of 4 genes (APOE, DNAH8, EME2, and KIF5A). Furthermore, we established an accurate nomogram, including a risk score and a Gleason score, for the BCR prediction of PCa patients. The GSEA result suggested the risk model was related to the PPAR signaling pathway, the cholesterol catabolic process, the organic hydroxy compound biosynthetic process, the small molecule catabolic process, and the steroid catabolic process. Simultaneously, we found six immune cell types relevant to the risk model: resting memory CD4+ T cells, monocytes, resting mast cells, activated memory CD4+ T cells, regulatory T cells (Tregs), and macrophages M2. Moreover, the risk model could affect the IC50 of 12 cancer drugs, including Lapatinib, Bicalutamide, and Embelin. Finally, qRT-PCR showed that APOE, EME2, and DNAH8 were highly expressed in PCa, while KIF5A was downregulated in PCa. Collectively, a mitochondrial respiratory gene-based nomogram including four genes and one clinical feature was established for BCR prediction in patients with PCa, which could provide novel strategies for further studies.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Four Mitochondrial Respiration-Related Signature for Predicting Biochemical Recurrence of Prostate Cancer

Xia

Liu

Fan

et al. 2023

JCM

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“…The previous study has revealed that prostate cancer risk alleles are associated with prostate cancer volume and prostate size [ 63 ]. Downregulation of PAH and AOC1 and upregulation of DDC, LIN01436, and ORM1 were associated with the development of prostate cancer [ 8 , 64 ]. Molecular and cellular biological studies are also closely related to the site of prostate tumorigenesis [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

“…Serum prostate-specific antigen (PSA) is the mainstay to detect the BCR of patients after surgery [ 6 ], and it has been recommended to keep close monitoring until PSA reaches 0.2 ng/mL [ 7 ]. In addition to PSA kinetics, Gleason score, PSA density, pathological and clinical stages, surgical margin, and other clinical factors have been studied for their prognostic significance, however, these factors could not predict BCR independently [ 8 ]. To better distinguish the recurrence risk and evaluate the prognosis after RP, more innovative predictors or models are unmet clinical needs.…”

Section: Introductionmentioning

confidence: 99%

Tumor Location and a Tumor Volume over 2.8 cc Predict the Prognosis for Japanese Localized Prostate Cancer

Baba

Sakamoto

Zhao

et al. 2022

Cancers

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(1) Objective: Our study investigated the prognostic value of tumor volume and location in prostate cancer patients who received radical prostatectomy (RP). (2) Methods: The prognostic significance of tumor volume and location, together with other clinical factors, was studied using 557 patients who received RP. (3) Results: The receiver operating characteristic (ROC) curve identified the optimal cutoff value of tumor volume as 2.8 cc for predicting biochemical recurrence (BCR). Cox regression analysis revealed that a tumor in the posterior area (p = 0.031), peripheral zone (p = 0.0472), and tumor volume ≥ 2.8 cc (p < 0.0001) were predictive factors in univariate analysis. After multivariate analysis, tumor volume ≥ 2.8 cc (p = 0.0225) was an independent predictive factor for BCR. Among them, a novel risk model was established using tumor volume and location in the posterior area and peripheral zone. The progression-free survival (PFS) of patients who met the three criteria (unfavorable group) was significantly worse than other groups (p ≤ 0.001). Furthermore, multivariate analysis showed that the unfavorable risk was an independent prognostic factor for BCR. The prognostic significance of our risk model was observed in low- to intermediate-risk patients, although it was not observed in high-risk patients. (4) Conclusion: Tumor volume (≥2.8 cc) and localization (posterior/peripheral zone) may be a novel prognostic factor in patients undergoing RP.

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“…However, more than one quarter of patients still experience biochemical recurrence (BCR) after surgery, which subsequently progresses to distant metastasis and PCa-related death [ 2 ]. Current predictions of PCa prognosis after curative intent are based on clinical and pathological features whose predictive efficacy remains unsatisfying [ 3 ]. Therefore, it is crucial to predict and confirm the BCR status of patients in time in order to classify and manage BCR patients with individualized treatment plans.…”

Section: Introductionmentioning

confidence: 99%

A Five Glutamine-Associated Signature Predicts Prognosis of Prostate Cancer and Links Glutamine Metabolism with Tumor Microenvironment

Wang

Chen

Zhao

et al. 2023

JCM

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Glutamine has been recognized as an important amino acid that provide a variety of intermediate products to fuel biosynthesis. Glutamine metabolism participates in the progression of the tumor via various mechanisms. However, glutamine-metabolism-associated signatures and its significance in prostate cancer are still unclear. In this current study, we identified five genes associated with glutamine metabolism by univariate and Lasso regression analysis and constructed a model to predict the biochemical recurrence free survival (BCRFS) of PCa. Further validation of the prognostic risk model demonstrated a good efficacy in predicting the BCRFS in PCa patients. Interestingly, based on the CIBERSORTx, ssGSEA and ESTIMATE algorithms predictions, we noticed a distinct immune cell infiltration and immune pathway pattern in the prediction of the two risk groups stratified by the risk model. Drug sensitivity prediction revealed that patients in the high-risk group were more suitable for chemotherapy. Last but not least, glutamine deprivation significantly inhibited cell growth in GLUL or ASNS knock down prostate cancer cell lines. Therefore, we proposed a novel prognostic model by using glutamine metabolism genes for PCa patients and identified potential mechanism of PCa progression through glutamine-related tumor microenvironment remodeling.

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Identification of Potential Predictor of Biochemical Recurrence in Prostate Cancer

Cited by 10 publications

References 31 publications

A Novel Four Mitochondrial Respiration-Related Signature for Predicting Biochemical Recurrence of Prostate Cancer

A Novel Four Mitochondrial Respiration-Related Signature for Predicting Biochemical Recurrence of Prostate Cancer

Tumor Location and a Tumor Volume over 2.8 cc Predict the Prognosis for Japanese Localized Prostate Cancer

A Five Glutamine-Associated Signature Predicts Prognosis of Prostate Cancer and Links Glutamine Metabolism with Tumor Microenvironment

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