Background: Central nervous system tumor (CNST) is one of the most complicated and lethal forms of human tumors with very limited treatment options. In recent years, growing evidence indicates that oncolytic virotherapy (OVT) has emerged as a promising therapeutic strategy for CNSTs. And a considerable amount of literature on OVT-CNSTs has been published. However, there are still no studies summarizing the global research trends and hotspots of this field through a bibliometric approach. To fulfill this knowledge gap, bibliometric analysis was conducted based on all publications relating to OVT-CNSTs since 2000s.Methods: We searched the Web of Science Core Collection for all relevant studies published between 2000 and 2022. Four different tools (online analysis platform, R-bibliometrix, CiteSpace and VOSviewer) were used to perform bibliometric analysis and network visualization, including annual publication output, active journals, contribution of countries, institutions, and authors, references, as well as keywords.Results: A total of 473 articles and reviews were included. The annual number of publications on OVT-CNSTs showed a significant increasing trend. Molecular Therapy and Cancer Research were the most active and co-cited journals, respectively. In terms of contributions, there is no doubt that the United States occupied a leading position with the most publications (n=307, 64.9%) and the highest H-index (57). The institution and author that contributed the largest number of publications were Ohio State University and Chiocca EA, respectively. As can be seen from citation analysis, the current studies mainly focused on preclinical and phase I/II clinical results of various oncolytic virus for CNSTs treatment. Keywords co-occurrence and burst analysis revealed that the following research topics including immunotherapy, T-cells, tumor microenvironment, vaccine, blood-brain-barrier, checkpoint inhibitors, macrophage, stem cell, and recurrent glioblastoma have been research frontiers of this field and also have great potential to continue to be research hotspots in the future.Conclusion: There has been increasing attention on oncolytic viruses for use as CNSTs therapeutics. Oncolytic immunotherapy is a topic of great concern in this field. This bibliometric study provides a comprehensive analysis of the knowledge base, research hotspots, development perspective in the field of OVT-CNSTs, which could become an essential reference for scholars in this area.

Background: Renal cell carcinoma (RCC) is one of the most lethal urological malignancies, and because early-stage RCC is asymptomatic, many patients present metastatic diseases at first diagnosis. With the development of immunotherapy, the treatment of RCC has entered a new stage and has made a series of progress. This study mainly outlines the knowledge map and detects the potential research hotspots by using bibliometric analysis.Methods: Publications concerning RCC immunotherapy from 2002 to 2021 in the Web of Science Core Collection were collected. Visualization and statistical analysis were mainly performed by freeware tools VOSviewer, CiteSpace, R software, and Microsoft Office Excel 2019.Results: A total of 3,432 papers were collected in this study, and the annual number of papers and citations showed a steady growth trend. The United States is the leading country with the most high-quality publications and is also the country with the most international cooperation. The University of Texas MD Anderson Cancer Center is the most productive organization. The Journal of Clinical Oncology is the highest co-cited journal, and Brian I. Rini is both the most prolific author and the author with the largest centrality. The current research hotspots may be focused on “immune checkpoint inhibitors (ICIs),” “PD-1,” and “mammalian target of rapamycin.”Conclusion: Immunotherapy has a bright future in the field of RCC treatment, among which ICIs are one of the most important research hotspots. The main future research directions of ICI-based immunotherapy may focus on combination therapy, ICI monotherapy, and the development of new predictive biomarkers.

Background: The therapeutic effectiveness of immune checkpoint inhibitors (ICIs) in bladder cancer varies among individuals. Identifying reliable predictors of response to these therapies is crucial for optimizing patient outcomes.Methods: This retrospective study analyzed 348 bladder cancer patients treated with ICIs, with additional validation using data from 248 patients at our institution who underwent PD-L1 immunohistochemical staining. We examined patient smoking history, clinicopathological characteristics, and immune phenotypes. The main focus was the correlation between smoking history and immunotherapy outcomes. Multivariate logistic and Cox proportional hazard regressions were used to adjust for confounders.Results: The study cohort comprised 348 bladder cancer patients receiving ICIs. Among them, 116 (33.3%) were never smokers, 197 (56.6%) were former smokers (median pack-years = 28), and 35 (10.1%) were current smokers (median pack-years = 40). Analysis revealed no statistically significant difference in overall survival across different smoking statuses (objective response rates were 11.4% for current smokers, 17.2% for never smokers, and 22.3% for former smokers; P = 0.142, 0.410, and 0.281, respectively). However, a notable trend indicated a potentially better response to immunotherapy in former smokers compared to current and never smokers. In the validation cohort of 248 patients from our institution, immunohistochemical analysis showed that PD-L1 expression was significantly higher in former smokers (55%) compared to current smokers (37%) and never smokers (47%). This observation underscores the potential influence of smoking history on the tumor microenvironment and its responsiveness to ICIs.Conclusion: In conclusion, our study demonstrates the importance of incorporating smoking history in predicting the response to immunotherapy in bladder cancer patients, highlighting its role in personalized cancer treatment approaches. Further research is suggested to explore the comprehensive impact of lifestyle factors on treatment outcomes.

Background: The existing studies on primary bladder lymphoma (PBL) are retrospective analyses based on individual cases or small series studies, and the research on PBL is not unified and in-depth enough at present because of the scarcity of PBL and the lack of relevant literature. This study is designed to develop and validate nomograms for overall survival (OS) and cancer-specific survival (CSS) prediction in patients with PBL. Methods: According to the Surveillance, Epidemiology, and End Results (SEER) database, 405 patients diagnosed with PBL from 1975 to 2016 were collected and randomly assigned to training (n = 283) and validation (n = 122) cohort. After the multivariable Cox regression, the OS and CSS nomograms were developed. The discrimination, calibration and clinical usefulness of the nomograms were assessed and validated, respectively, by the training and validation cohort. Furthermore, all of the patients were reclassified into high- and low-risk groups and their survival were compared through Kaplan-Meier method and log-rank test. Results: Age, subtype, Ann Arbor stage, radiation and chemotherapy were identified as independent prognostic factors for OS and age, sex, and subtype for CSS, then corresponding nomograms predicting the 3- and 5-year survival were constructed. The presented nomograms demonstrated good discrimination and calibration, which the C-index in the training and validation cohort were 0.744 (95% confidence interval [CI], 0.705–0.783) and 0.675 (95% CI, 0.603–0.747) for OS nomogram and 0.692 (95% CI, 0.632–0.752) and 0.646 (95% CI, 0.549–0.743) for CSS nomogram, respectively. Furthermore, the nomograms can be used to effectively distinguish Patients with PBL at high risk of death. The clinical usefulness of the nomograms was visually displayed by decision curve analysis. Conclusion: We updated the baseline characteristics of patients with PBL and constructed OS and CSS nomograms to predict their 3- and 5-year survival. Using these nomograms, it would be convenient to individually predict the prognosis of patients with PBL and provide guidance for clinical treatment.