Acute and Late Toxicity after Three-Dimensional Conformal Image-Guided Radiotherapy for Localized Prostate Cancer

Development of a Novel Risk Signature for Predicting the Prognosis and Immunotherapeutic Response of Prostate Cancer by Integrating Ferroptosis and Immune-Related Genes

Ferroptosis and immune response correlation studies have not been reported in prostate cancer (PCa), and the main goal of this paper is to identify biomarkers that can be used for early diagnosis of prostate cancer. Data on PCa were retrieved from the TCGA and MSKCC2010 databases. Thereafter, the differentially expressed ferroptosis-related genes (DE-FRGs: ACSF2) and immune-related genes (DE-IRGs: ANGPT1, NPPC, and PTGDS) were identified using the "limma" package. Additionally, we used univariate and multivariate Cox regression analyses to obtain biochemical relapse (BCR)-free survival-related genes and construct a risk signature. Patients with high-risk scores were characterized by poor BCR-free survival, relatively low immune cell abundance, and comparably weak expression of immune checkpoint molecules. Moreover, gene set variation analysis (GSVA) was performed to explore the biological pathways related to the risk signature. Single sample gene set enrichment analysis (ssGESA) was applied to evaluate the status of immune cells in patients with PCa, which demonstrated that the risk score was intimately affiliated with immune response and cancer pathways. Ultimately, the connection between the risk score and response of PCa patients to immunotherapy was appraised using the TIDE algorithm. The TIDE algorithm implied that the high-risk score PCa population might benefit more from immunotherapy regimens. Finally, qRT-PCR were used to evaluate the expression of DE-FRGs and DE-IRGs in PCa cell and normal prostate epithelial cells. The result of qRT-PCR showed that the mRNA expression levels of ACSF2, ANGPT1, NPPC, and PTGDS in normal prostate epithelial cell were higher than that in PCa cells. Therefore, a risk score model was generated based on one DE-FRG and three DE-IRGs, which could predict the BCR-free survival and response of immunotherapy for patients with PCa.

Predicting biochemical-recurrence-free survival using a three-metabolic-gene risk score model in prostate cancer patients

BACKGROUND

Biochemical recurrence (BCR) after initial treatment, such as radical prostatectomy, is the most frequently adopted prognostic factor for patients who suffer from prostate cancer (PCa). In this study, we aimed to construct a prognostic model consisting of gene expression profiles to predict BCR-free survival.

METHODS

We analyzed 70 metabolic pathways in 152 normal prostate samples and 494 PCa samples from the UCSC Xena dataset (training set) via gene set enrichment analysis (GSEA) to select BCR-related genes and constructed a BCR-related gene risk score (RS) model. We tested the power of our model using Kaplan-Meier (K-M) plots and receiver operator characteristic (ROC) curves. We performed univariate and multivariate analyses of RS using other clinicopathological features and established a nomogram model, which has stronger prediction ability. We used GSE70770 and DFKZ 2018 datasets to validate the results. Finally, we performed differential expression and quantitative real-time polymerase chain reaction analyses of the UCSC data for further verification of the findings.

RESULTS

A total of 194 core enriched genes were obtained through GSEA, among which 16 BCR-related genes were selected and a three-gene RS model based on the expression levels of CA14, LRAT, and MGAT5B was constructed. The outcomes of the K-M plots and ROC curves verified the accuracy of the RS model. We identified the Gleason score, pathologic T stage, and RS model as independent predictors through univariate and multivariate Cox analyses and constructed a nomogram model that presented better predictability than the RS model. The outcomes of the validation set were consistent with those of the training set. Finally, the results of differential expression analyses support the effectiveness of our model.

CONCLUSION

We constructed an RS model based on metabolic genes that could predict the prognosis of PCa patients. The model can be easily used in clinical applications and provide important insights into future research on the underlying mechanism of PCa.

Identification of recurrence marker associated with immune infiltration in prostate cancer with radical resection and build prognostic nomogram

BACKGROUND

Some historic breakthroughs have been made in immunotherapy of advanced cancer. However, there is still little research on immunotherapy in prostate cancer. We explored the relationship between immune cell infiltration and prostate cancer recurrence and tried to provide new ideas for the treatment of prostate cancer.

METHODS

Prostate cancer RNA-seq data and clinical information were downloaded from the TCGA database and GEO database. The infiltration of 24 immune cells in tissues was quantified by ssGSEA. Univariate Cox regression analysis was used to screen for immune cell types associated with tumor recurrence, weighted gene co-expression network analysis (WGCNA) and LASSO were used to identify hub genes which regulate prognosis in patients through immune infiltration. Then, the nomogram was constructed based on the hub gene to predict the recurrence of prostate cancer, and the decision curve analysis (DCA) was used to compare the accuracy with the PSA and Gleason prediction models.

RESULT

Analysis showed that Th2 cells and Tcm related to prostate cancer recurrence after radical prostatectomy, and they are independent protective factors for recurrence. Through WGCNA and Lasso, we identified that NDUFA13, UQCR11, and USP34 involved in the infiltration of Th2 cells and Tcm in tumor tissues, and the expression of genes is related to the recurrence of patients. Based on the above findings, we constructed a clinical prediction model and mapped a nomogram, which has better sensitivity and specificity for prostate cancer recurrence prediction, and performed better in comparison with PSA and Gleason's predictions.

CONCLUSION

The immune cells Th2 cells and Tcm are associated with recurrence of PCa. Moreover, the genes NDUFA13, UQCR11, and USP34 may affect the recurrence of PCa by affecting the infiltration of Th2 cells and Tcm. Moreover, nomogram can make prediction effectively.

Volumetric image-guided conformal radiotherapy for localized prostate cancer: Analysis of dosimetric and clinical factors affecting acute and late toxicity

Aim

To identify factors influencing toxicity in patients affected by localized prostate cancer treated with conformal image-guided radiotherapy.

Background

Image guidance in combination with conformal techniques is the standard of care in localized prostate cancer, but factors affecting toxicity are still under investigation.

Materials and methods

294 patients were analyzed. Median age at diagnosis was 71 year. 76 Gy (38 × 2 Gy) were delivered to the target volume. We used the χ² test to analyse associations between toxicity and dosimetric and clinical parameters. Multivariate analysis was performed using binary logistic regression. Kaplan-Meier method was used for survival analysis.

Results

Median follow-up was 62.9 months. Acute grade ≥2 gastro-intestinal toxicity (GI) was 12.1%. Acute genito-urinary (GU) toxicity of grade ≥2 was 33.9%. Actuarial 4 and 5 years late grade ≥2 GI was 3% and 4%, respectively. Four and 5-year late grade ≥2 GU toxicity was 6% and 10%. At multivariate analysis for acute toxicity rectal V₇₀ was correlated with GI toxicity (p = 0.01, HR 2.73 CI 1.19-6.26), and smoking habit with GU toxicity (p < 0.01, HR 2.50 CI 1.51-4.14). For late toxicity, rectal V₇₀ was correlated with gastro-intestinal toxicity (p = 0.04, HR 4.76 CI 1.07-21.13), and pre-radiotherapy urinary symptoms with genito-urinary toxicity (p = 0.01, HR 2.84 CI 1.29-6.22).

Discussion

Conformal image-guided radiotherapy shows low rates of toxicity. Smoking should be avoided during radiotherapy. Besides the evaluation of high doses received by the organs at risk, individual factors, such as co-morbidities and lifestyle choices, have an impact on normal-tissue complication risk.

Volumetric image-guided highly conformal radiotherapy of the prostate bed: Toxicity analysis

AIM

To evaluate toxicity of high conformal image-guided radiotherapy of the prostate bed.

BACKGROUND

Radiotherapy of the prostate bed has a pivotal role in the post-operative and salvage settings, but few clinical data are available on the use of daily image guidance in combination with highly conformal techniques, and data on long-term results are lacking.

MATERIALS AND METHODS

We analyzed 118 patients irradiated on the prostate bed using conformal plans processed with a micro-multileaf collimator, and daily checking treatment set-up with a cone-beam CT system. Correlation between toxicity and clinical-dosimetric parameters was assessed by the Cox regression model and log-rank test. Survival analyses were performed with the Kaplan-Meier method.

RESULTS

Median follow-up was 54.08 months. Late grade ≥2 gastro-intestinal (GI) and genito-urinary (GU) toxicity were 3.4% and 4.2%, respectively. Actuarial 4-year late grade ≥2 GI and GU toxicities were 4% and 6%, respectively. Four-year relapse-free survival was 87%. At log-rank test, acute grade ≥2 GI toxicity is associated with the use of antihypertensives (p = 0.03), and there is a trend toward significance between the use of anticoagulants and late grade ≥2 GI toxicity (p = 0.07). At Cox analysis, acute grade ≥2 GU toxicity is correlated with the percentage of bladder volume receiving more than 65 Gy (p = 0.02, HR 1.87 CI 1.25-2.8), and the maximal dose to the rectum is correlated to the development of late grade ≥2 GI toxicity (p = 0.03, HR 2.75 CI 1.10-6.9).

CONCLUSIONS

Conformal volumetric image-guided radiotherapy of the prostate bed leads to low toxicity rates.

Evaluation of serrated intraprostatic gold coils positional stability using on-board cone beam computed tomography scans acquired throughout the radiation treatment course

PURPOSE

To investigate intraprostatic gold coils positional stability analyzing intermarker distance in on-board cone beam computed tomography (CBCT) scans acquired throughout the entire treatment course.

METHODS AND MATERIALS

A total of 29 fiducial markers (FMs) were implanted in 10 patients through the transperineal approach, under ultrasound guidance. After 2 weeks from the FM implantation, all the patients underwent CT and magnetic resonance imaging under radiation therapy-planning conditions. The planning CT was the reference CT (CTref) used to calculate the initial intermarker distances. For every patient, 8 CBCTi (i varying from 1 to 8) acquired once a week during the treatment course were selected to calculate intermarker distances and compared with CTref. Reconstructed images of CBCTi were exported to the treatment planning system, and every FM was contoured. A point of interest at the center of mass of each contoured FM was created. The mean coordinates obtained for point of interest at the center of mass of FMs were used to calculate relative marker distances on CTref and CBCTi.

RESULTS

No patient developed postimplantation complications. A total of 224 marker distance variations (MDVs) were calculated for all 29 markers. The average directional variation of all MDVs (± standard deviation [SD]) was -0.14 ± 0.86 mm. The average absolute variations of all MDVs (± SD) were 0.71 ± 0.51 mm. The largest observed variation was 1.9 mm. All patients had not significant temporal trends in their marker distances. The SD of the MDVs was computed for each set of markers in all 10 patients. The SDs ranged between 0.4 and 1.1 mm in individual patients. The average of the mean SDs was 0.6 mm.

CONCLUSIONS

The three-dimensional definition of each fiducial marker volume, using on-board CBCT, demonstrated the stability of FMs position throughout the entire radiation therapy treatment course.