Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Qian, Youliang; Wang, Jie; Wei, Wuran; Wei, Qiang; Feng, Dechao; Yang, Lu

doi:10.1038/s41598-023-36125-0

Cited by 10 publications

(4 citation statements)

References 102 publications

(123 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The molecular subtyping of tumors can be used to guide the precision diagnosis and treatment of tumor patients. Cellular and molecular characteristics of tumors have shown potential in precision therapy of PCA, such as cancer-associated fibroblasts (CAFs) and their signature genes [ 12 , 13 ]. Serum prostate-specific antigen (PSA) is the most important marker for PCA; however, it has been criticized for its poor specificity [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

Zheng,

Hai,

et al. 2023

J Transl Med

View full text Add to dashboard Cite

Background Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy. Methods An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms. Results We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments. Conclusions The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

show abstract

Section: Introductionmentioning

confidence: 99%

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

Zheng,

Hai,

et al. 2023

J Transl Med

View full text Add to dashboard Cite

show abstract

“…Fibroblasts has been reported to be important to many diseases, including cancers [ 8 , 103 – 108 ]. Our previous study also observed that P4HB was related to cancer-related fibroblasts [ 62 ]. Apart from this kind of stromal cell, we discovered that P4HB had a negative correlation with a range of immune cells in the tumor microenvironment, such as T cells, B cells, and macrophages.…”

Section: Discussionmentioning

confidence: 80%

“…The correlation between P4HB and tumor heterogeneity and stemness related indexes was analyzed and the specific methods could be seen from the previous studies [ 55 – 62 ]. GSCALite was used to examine the relationship between P4HB and medication sensitivity in pan cancer [ 63 ], which integrated the data of the cancer therapeutics response portal and genomics of drug sensitivity in cancer.…”

Section: Methodsmentioning

confidence: 99%

Prolyl 4-hydroxylase subunit beta (P4HB) could serve as a prognostic and radiosensitivity biomarker for prostate cancer patients

et al. 2023

Eur J Med Res

Self Cite

View full text Add to dashboard Cite

Background Prolyl 4-hydroxylase subunit beta (P4HB) has been reported as a suppressor in ferroptosis. However, no known empirical research has focused on exploring relationships between P4HB and prostate cancer (PCa). In this research, we initially examine the function of P4HB in PCa by thorough analysis of numerous databases and proliferation experiment. Methods We analyzed the correlations of P4HB expression with prognosis, clinical features, mutation genes, tumor heterogeneity, stemness, tumor immune microenvironment and PCa cells using multiple databases and in vitro experiment with R 3.6.3 software and its suitable packages. Results P4HB was significantly upregulated in tumor tissues compared to normal tissues and was closely related to biochemical recurrence-free survival. In terms of clinical correlations, we found that higher P4HB expression was significantly related to older age, higher Gleason score, advanced T stage and residual tumor. Surprisingly, P4HB had highly diagnostic accuracy of radiotherapy resistance (AUC 0.938). TGF beta signaling pathway and dorso ventral axis formation were upregulated in the group of low-expression P4HB. For tumor stemness, P4HB expression was positively related to EREG.EXPss and RNAss, but was negatively associated with ENHss and DNAss with statistical significance. For tumor heterogeneity, P4HB expression was positively related to MATH, but was negatively associated with tumor ploidy and microsatellite instability. For the overall assessment of TME, we observed that P4HB expression was negatively associated with all parameters, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score and ESTIMATE score. Spearman analysis showed that P4HB expression was negatively related to TIDE score with statistical significance. In vitro experiment, RT-qPCR and western blot showed that three siRNAs of P4HB were effective on the knockdown of P4HB expression. Furthermore, we observed that the downregulation of P4HB had significant influence on the cell proliferation of six PCa cell lines, including LNCap, C4-2, C4-2B, PC3, DU145 and 22RV1 cells. Conclusions In this study, we found that P4HB might serve as a prognostic biomarker and predict radiotherapy resistance for PCa patients. Downregulation of P4HB expression could inhibit the cell proliferation of PCa cells.

show abstract

“…However, the heterogeneity of PCa presents obstacles in both research and clinical management. Previous studies have shown that tumor tissue remodeling and the involvement of cancer-related fibroblasts in recurrence and metastasis underscore the complexity of PCa progression [ 7 , 8 ]. Additionally, both intratumoral and transcriptional heterogeneity may contribute to the evolution of PCa [ 9 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

Feng,

Zhu,

Wang

et al. 2024

Military Med Res

Self Cite

View full text Add to dashboard Cite

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

show abstract

Establishment of cancer-associated fibroblasts-related subtypes and prognostic index for prostate cancer through single-cell and bulk RNA transcriptome

Cited by 10 publications

References 102 publications

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

Prolyl 4-hydroxylase subunit beta (P4HB) could serve as a prognostic and radiosensitivity biomarker for prostate cancer patients

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy

Contact Info

Product

Resources

About