Knowledge mapping of exosomes in prostate cancer from 2003 to 2022: a bibliometric analysis.

BACKGROUND: Prostate cancer (PCa) is highly prevalent among males worldwide. The investigation of exosomes in PCa has emerged as a dynamic and important research area. To visually depict the prominent research areas and evolutionary patterns of exosomes in PCa, we performed a comprehensive analysis via bibliometric methods. METHODS: Studies were retrieved from the Web of Science Core Collection. CiteSpace, VOSviewers, and the R package "bibliometrix" were employed to analyze the relationships and collaborations among countries/regions, organizations, authors, journals, references, and keywords. RESULTS: Over the past 20 years (2003-2022), 995 literatures on exosomes in PCa have been collected. The findings indicate a consistent upward trend in annual publications with the United States being the leading contributor. Cancers is widely recognized as the most prominent journal in this area. In total, 5936 authors have contributed to these publications, with Alicia Llorente being the most prolific. The primary keywords associated with research hotspots include "liquid biopsy", "identification", "growth", "microRNAs", and "tumor-derived exosomes". CONCLUSION: Our analysis reveals that investigating the intrinsic mechanisms of exosomes in PCa pathogenesis and exploring the potential of exosomes as biomarkers of PCa constitute the principal focal points in this domain of research.

The oncogene MYBL2 promotes the malignant phenotype and suppresses apoptosis through hedgehog signaling pathway in clear cell renal cell carcinoma.

Multiple cancers have been associated with MYB-related protein B (MYBL2), its involvement in clear cell renal cell carcinoma (ccRCC) has yet to be demonstrated. Our study revealed a significant upregulation of MYBL2 in ccRCC tissues, correlating with clinicopathological features and patient prognosis. Increased MYBL2 expression promoted cell proliferation and suppressed apoptosis. RNA-seq analysis unveiled a reduction in smoothened (SMO) expression upon MYBL2 silencing. However, luciferase and chromatin immunoprecipitation (ChIP) assays demonstrated MYBL2's positive regulation of SMO expression by directly targeting the SMO promoter. Reintroduction of SMO expression in MYBL2-knocked down cells partially restored cell proliferation and mitigated apoptosis inhibition. Overall, these results indicate that MYBL2 facilitates ccRCC progression by enhancing SMO expression, suggesting its potential as an intriguing drug target for ccRCC therapy.

SHOX2 promotes prostate cancer proliferation and metastasis through disruption of the Hippo-YAP pathway.

The transcription factor SHOX2 gene is critical in regulating gene expression and the development of tumors, but its biological role in prostate cancer (PCa) remains unclear. In this study, we found that SHOX2 expression was significantly raised in PCa tissues and was associated with clinicopathological features as well as disease-free survival (DFS) of PCa patients. Phenotypic tests showed that the absence of SHOX2 inhibited PCa growth and invasion, while SHOX2 overexpression promoted these effects. Mechanistically, SHOX2 was found to activate the transcription of nephronophthisis type 4 (NPHP4), a gene located downstream of SHOX2. Further analysis revealed that SHOX2 could potentially interfere with the Hippo-YAP signaling pathway through NPHP4 activation, facilitating the oncogenic behavior of PCa cells. These findings highlight SHOX2 as an oncogene in PCa and provide a basis for developing potential therapeutic approaches against this disease.

Machine learning to improve prognosis prediction of metastatic clear-cell renal cell carcinoma treated with cytoreductive nephrectomy and systemic therapy.

Cytoreductive nephrectomy (CN) combined with systemic therapy is commonly used to treat metastatic clear-cell renal cell carcinoma (mccRCC). However, prognostic models for these patients are limited. In the present study, the clinical data of 782 mccRCC patients who received both CN and systemic therapy were obtained from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2016), and patients were divided into training and internal test cohorts. A total of 144 patients who met the same criteria from our center (Peking Union Medical College Hospital) were placed in the external test cohort. The cancer-specific survival rate (CSS) at 1, 3, and 5 years was set as the research outcome. Then, four ML models, i.e., a gradient boosting machine (GBM), support vector machine (SVM), random forest (RF), and logistic regression (LR), were established. Fifteen potential independent features were included in this study.  Model performance was evaluated using the area under the receiver operating characteristic curves (AUC), calibration plots, and decision curve analysis (DCA). Seven clinical features, namely pathological grade, T stage, N stage, number of metastatic sites, brain or liver metastases, and metastasectomy were selected for subsequent analysis via the recursive feature elimination (RFE) algorithm. In conclusion, the GBM model performed best at 1-, 3- and 5-year CSS prediction (0.836, 0.819 and 0.808, respectively in the internal test cohort and 0.819, 0.805 and 0.786, respectively in the external cohort). Furthermore, we divided the patients into three strata (high-, intermediate- and low-risk) via X-tile analysis and concluded that clinically individualized treatment can be aided by these practical prognostic models.

A comprehensive analysis of the FOX family for predicting kidney renal clear cell carcinoma prognosis and the oncogenic role of FOXG1.

Previous studies have confirmed that the forkhead box (FOX) superfamily of transcription factors regulates tumor progression and metastasis in multiple cancer. The purpose of this study was to develop a model based on FOX family genes for predicting kidney renal clear cell carcinom (KIRC) prognosis. We downloaded the transcriptional profiles and clinical data of KIRC patients from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. To build a new prognosis model, we screened prognosis-related FOX family genes using Lasso regression and Multivariate Cox regression analyses. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Additionally, a prognostic nomogram was developed using clinical information and selected genes to improve the accuracy of prognostic prediction. We also investigated whether prognosis-related FOX family genes are related to the immune response in KIRC. Finally, we validated the oncogenic role of FOXG1 in KIRC using an in vitro tumor function assay. Six prognosis-related FOX family genes were screened: FOXO1, FOXM1, FOXK2, FOXG1, FOXA1, and FOXD1. The ROC curves indicated that our model was capable of making accurate predictions for 1-, 3-, and 5-year overall survival (OS). The nomogram further improved the accuracy of prognostic predictions. In addition, compared to those in patients with low-risk scores, high-risk scores predicted a decreased level of immune cell infiltration and a lower immune response rate. Moreover, the results of in vitro studies confirmed that FOXG1 supports the proliferation and invasion of KIRC.

Integrated Analysis Revealed an Inflammatory Cancer-Associated Fibroblast-Based Subtypes with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Bladder Cancer Patients.

Inflammatory cancer-associated fibroblasts (iCAFs) are closely related to progression, anticancer therapeutic resistance, and poor prognosis of bladder cancer (BCa). However, the functional role of iCAFs in BCa has been poorly studied. In our study, two BCa scRNA-seq datasets (GSE130001 and GSE146137) were obtained and integrated by the Seurat pipeline. Based on reported markers (COL1A1 and PDGFRA), iCAFs were identified and the related signature of 278 markers was developed. Following unsupervised consensus clustering, two molecular subtypes of TCGA-BLCA were identified and characterized by distinct dysregulated cancer hallmarks, immunological tumor microenvironments, prognoses, responses to chemotherapy/immunotherapy, and stemness. Subsequently, the robustness of the signature-based clustering, in terms of prognosis and therapeutic response prediction, was validated in a GEO-meta cohort with seven independent GEO datasets of 519 BCa patients, and three immune checkpoint inhibitor (ICI)-treated cohorts. Considering the heterogeneity, re-clustering of iCAFs was performed and a subpopulation, named "LOXL2+ iCAFs", was identified. Co-culture CM derived from LOXL2 overexpression/silencing CAFs with T24 cells revealed that overexpression of LOXL2 in CAFs promoted while silencing LOXL2 inhibited the proliferation, migration, and invasion of T24 cells through IL32. Moreover, the positive correlation between LOXL2 and CD206, an M2 macrophage polarization marker, has been observed and validated. Collectively, integrated single-cell and bulk RNA sequencing analyses revealed an iCAF-related signature that can predict prognosis and response to immunotherapy for BCa. Additionally, the hub gene LOXL2 may serve as a promising target for BCa treatment.

Neoadjuvant immunotherapy and chemoimmunotherapy for stage II-III muscle invasive bladder cancer.

Objective: Considering the striking evidence revealed by immunotherapy in advanced or metastatic bladder cancer, investigators have explored neoadjuvant immunotherapy and chemoimmunotherapy in muscle-invasive bladder cancer (MIBC). Currently, there have been a large number of studies reporting varied efficacy and safety of these approaches. Herein, we pooled the available evidence in terms of oncological outcomes (pathological complete response [pCR] and pathological partial response [pPR]) and safety outcomes (immune-related adverse events [irAEs], treatment-related adverse events [TRAEs]), through a systematic review and meta-analysis. Method: We searched PubMed, Embase, Cochrane Library, and American Society of Clinical Oncology meeting abstracts to identify relevant studies up to June 2022. Studies were included if they evaluated the neoadjuvant immunotherapy or chemoimmunotherapy in MIBC and reported at least the pCR. Results: A total of 22 records involving 843 patients were included. For pCR of immunotherapy, the pooled rate of immune checkpoint inhibitor (ICI) monotherapy and dual-ICIs therapy was 24% (95% confidence interval [CI]: 15.3% - 32.8%) and 32.1% (95%CI: 20.6% - 43.7%), respectively. For pCR of chemoimmunotherapy, the overall pooled rate was 42.6% (95% CI: 34.9% - 50.2%). Subgroup of gemcitabine/cisplatin (GC) plus ICI had a pCR rate of 41.7% (95%CI: 35.8% - 47.5%). In terms of safety, the pooled rate of Grade≥3 irAEs was 11.7% (95% CI: 6.5%-16.9%). In subgroup analysis, the Grade≥3 irAEs rate of ICI monotherapy, dual-ICIs therapy, and GC plus ICI therapy was 7.4% (95% CI: 4.3%-10.5%), 30.3% (95% CI: 15.3%-45.3%), and 14.5% (95% CI: 3.5% - 25.4%), respectively. Besides, the pooled Grade≥3 TRAEs rate for chemoimmunotherapy was 32.4% (95% CI: 13.1% - 51.6%). Conclusion: Neoadjuvant immunotherapy and chemoimmunotherapy were effective and safe in the treatment of MIBC. Compared to ICI monotherapy, dual-ICIs therapy or chemoimmunotherapy can improve the response rate, while increasing the morbidity of Grade≥ 3 irAEs or Grade≥ 3 TRAEs. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD4202233771.