Single-cell analysis extracted CAFs-related genes to established online app to predict clinical outcome and radiotherapy prognosis of prostate cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) play a significant role in regulating the clinical outcome and radiotherapy prognosis of prostate cancer (PCa). The aim of this study is to identify CAFs-related genes (CAFsRGs) using single-cell analysis and evaluate their potential for predicting the prognosis and radiotherapy prognosis in PCa.

METHODS

We acquire transcriptome and single-cell RNA sequencing (scRNA-seq) results of PCa and normal adjacent tissues from The GEO and TCGA databases. The "MCPcounter" and "EPIC" R packages were used to assess the infiltration level of CAFs and examine their correlation with PCa prognosis. ScRNA-seq and differential gene expression analyses were used to extract CAFsRGs. We also applied COX and LASSO analysis to further construct a risk score (CAFsRS) to assess biochemical recurrence-free survival (BRFS) and radiotherapy prognosis of PCa. The predictive efficacy of CAFsRS was evaluated by ROC curves and subgroup analysis. Finally, we integrated the CAFsRS gene signature with relevant clinical features to develop a nomogram, enhancing the predictive accuracy.

RESULTS

The abundance of CAFs is associated with a poor prognosis of PCa patients. ScRNA-seq and differential gene expression analysis revealed 323 CAFsRGs. After COX and LASSO analysis, we obtained seven CAFsRGs with prognostic significance (PTGS2, FKBP10, ENG, CDH11, COL5A1, COL5A2, and SRD5A2). Additionally, we established a risk score model based on the training set (n = 257). The ROC curve was used to confirm the performance of CAFsRS (The AUC values for 1, 3 and 5-year survival were determined to be 0.732, 0.773, and 0.775, respectively.). The testing set (n = 129), GSE70770 set (n = 199) and GSE116918 set (n = 248) revealed that the model exhibited exceptional predictive performance. This was also confirmed by clinical subgroup analysis. The violin plot demonstrated a statistically significant disparity in the CAFs infiltrations between the high-risk and low-risk groups of CAFsRS. Further analysis confirmed that both CAFsRS and T stage were independent prognostic factors for PCa. The nomogram was then established and its excellent predictive performance was demonstrated through calibration and ROC curves. Finally, we developed an online prognostic prediction app ( https://sysu-symh-cafsnomogram.streamlit.app/ ) to facilitate the practical application of the nomogram.

CONCLUSIONS

The prognostic prediction risk score model we constructed could accurately predict BRFS and radiotherapy prognosis PCa, which can provide new ideas for clinicians to develop personalized PCa treatment and follow-up programs.

Developing and validating a nomogram for penile cancer survival: A comprehensive study based on SEER and Chinese data

OBJECTIVE

The primary aim of this study was to create a nomogram for predicting survival outcomes in penile cancer patients, utilizing data from the Surveillance, Epidemiology, and End Results (SEER) and a Chinese organization.

METHODS

Our study involved a cohort of 5744 patients diagnosed with penile cancer from the SEER database, spanning from 2004 to 2019. In addition, 103 patients with penile cancer from Sun Yat-sen Memorial Hospital of Sun Yat-sen University were included during the same period. Based on the results of regression analysis, a nomogram is constructed and validated internally and externally. The predictive performance of the model was evaluated by concordance index (c-index), area under the curve, decision curve analysis, and calibration curve, in internal and external datasets. Finally, the prediction efficiency is compared with the TNM staging model.

RESULTS

A total of 3154 penile patients were randomly divided into the training group and the internal validation group at a ratio of 2:1. Nine independent risk factors were identified, including age, race, marital status, tumor grade, histology, TNM stage, and the surgical approach. Based on these factors, a nomogram was constructed to predict OS. The nomogram demonstrated relatively better consistency, predictive accuracy, and clinical relevance, with a c-index over 0.73 (in the training cohort, the validation cohort, and externally validation cohort.) These evaluation indexes are far better than the TNM staging system.

CONCLUSION

Penile cancer, often overlooked in research, has lacked detailed investigative focus and guidelines. This study stands as the first to validate penile cancer prognosis using extensive data from the SEER database, supplemented by data from our own institution. Our findings equip surgeons with an essential tool to predict the prognosis of penile cancer better suited than TNM, thereby enhancing clinical decision-making processes.

The predictive significance of chromobox family members in prostate cancer in humans

PURPOSE

The Chromobox (CBX) family proteins are crucial elements of the epigenetic regulatory machinery and play a significant role in the development and advancement of cancer. Nevertheless, there is limited understanding regarding the role of CBXs in development or progression of prostate cancer (PCa). Our objective is to develop a unique prognostic model associated with CBXs to improve the accuracy of predicting outcomes of patients with PCa.

METHODS

Data from TCGA and GEO databases were analyzed to assess differential expression, prognostic value, gene pathway enrichment, and immune cell infiltration. COX regression analysis was utilized to identify the independent prognostic factors that impact disease-free survival (DFS). The expression of CBX2 and FOXP3+ cells infiltration was verified by immunohistochemical staining of clinical tissue sections. In vitro proliferation, migration and invasion assay were conducted to examine the function of CBX2. RNA-seq was employed to examine the CBX2 related pathway enrichment.

RESULTS

CBX2, CBX3, CBX4, and CBX8 were upregulated, while CBX6 and CBX7 were downregulated in PCa tissues. CBXs expression varied by stage and grade. Elevated expression of CBX1, CBX2, CBX3, CBX4 and CBX8 is correlated with poor outcome. CBX2 expression, T stage, and Gleason score were independent prognostic factors. The expression level of CBX2 in PCa tissues was significantly higher than that in adjacent normal tissues. More Treg infiltration was observed in the group with high CBX2 expression. CBX2 expression affected PCa cell growth, migration, and invasion.

CONCLUSIONS

CBX2 is involved in the development and advancement of PCa, suggesting its potential as a reliable prognostic indicator for PCa patients.

Establishment of a prognostic risk prediction model incorporating disulfidptosis-related lncRNA for patients with prostate cancer

PURPOSE

Prostate cancer (PCa) is one of the major tumor diseases that threaten men's health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two.

METHODS

Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted.

RESULTS

The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue.

CONCLUSIONS

A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.

Nomograms for Predicting Postoperative Sperm Improvements in Varicocele Patients

Background

Varicocele is a condition that seriously affects male fertility. It can cause pathological changes in the testicles and affect their spermatogenesis and endocrine function.

Objective

To formulate nomograms to predict sperm improvements after microscopic varicocelectomy.

Design setting and participants

A retrospective analysis was conducted on varicocele patients who met the research criteria and were enrolled from March 2020 to June 2022. They were divided into a development and a validation cohort in a 2:1 ratio.

Outcome measurements and statistical analysis

Data on preoperative testicular atrophy index, bilateral testicular elastic modulus, testosterone, pre- and postoperative 6-mo total sperm count, sperm concentration, and sperm vitality were collected. An increase of ≥25% is considered a postoperative improvement in sperm parameters. Predictive nomograms were constructed through forward stepwise LR regression, based on independent risk factors filtered by univariate and multivariate logistic regression analyses. Receiver operating characteristic curve analysis, calibration curve, and decision curve analysis were employed to assess the performance of the models.

Results and limitations

The areas under the curve of nomograms for predicting the postoperative improvement of total sperm count, sperm concentration, and sperm vitality were 0.915, 0.986, and 0.924 respectively. The nomogram models demonstrated good predictive performance. The single-center sample size was a limitation of this study.

Conclusions

In this study, we developed effective predictive nomogram models for anticipating postoperative improvements in sperm quality among varicocele patients. These models offer a significant value in providing accurate predictions of surgical outcomes. However, it is crucial to conduct further external validation.

Patient summary

In this study, a predictive nomogram model was constructed for assessing the improvement of sperm quality in varicocele patients after surgery. The model offered satisfactory results.

Mechanism of prognostic marker SPOCK3 affecting malignant progression of prostate cancer and construction of prognostic model

BACKGROUND

SPOCK3 is a secreted extracellular matrix proteoglycan. This study aimed to investigate the effect of SPOCK3 on the malignant progression of prostate cancer and to construct a prognostic model to predict DFS of patients with prostate cancer.

METHODS

Clinical and transcriptome sequencing data for prostate cancer were download from the TCGA and GEO databases. The survival curve showed that SPOCK3 has prognostic significance. GO, KEGG, and GSEA enrichment analysis were used to investigate how SPOCK3 affects the malignant progression of prostate cancer. Based on ESTIMATE and ssGSEA, the relationship between SPOCK3 and immune cell infiltration in prostate cancer tissue was clarified. Univariate and multivariate COX regression analysis was used to identify the independent prognostic factors of prostate cancer OS and to construct a nomogram. The calibration curve and ROC curves were drawn to assess the nomogram's predictive power.

RESULTS

The survival curve revealed that patients in the low-expression group of SPOCK3 had a poor prognosis. According to enrichment analysis, SOPCK3-related genes were enriched in collagen-containing extracellular matrix, PI3K-Akt, and MAPK signaling pathway. ESTIMATE analysis revealed that SPOCK3 expression was positively correlated with the interstitial score, immune score, and ESTIMATE score. The results of ssGSEA analysis revealed that the infiltration levels of Mast cells, NK cells, and B cells were higher in the SPOCK3 high expression group. Cox regression analysis showed that SPOCK3 expression level, T and Gleason score were independent risk factors of patient prognosis, and a nomogram was constructed. The ROC curve showed the AUCs of DFS at 2, 3, and 5 years.

CONCLUSION

SPOCK3 is a protective factor for DFS in prostate cancer patients. SPOCK3 is significantly associated with immune cell infiltration. The prognostic model constructed based on SPOCK3 has excellent predictive performance.