A scientometrics and visualization analysis of oxidative stress modulator Nrf2 in cancer profiles its characteristics and reveals its association with immune response

Construction of exosome-related genes risk model in kidney cell carcinoma predicts prognosis and immune therapy response

Renal cell carcinoma (RCC) is one of the most prevalent types of urological cancer. Exosomes are vesicles derived from cells and have been found to promote the development of RCC, but the potential biomarker and molecular mechanism of exosomes on RCC remain ambiguous. Here, we first screened differentially expressed exosome-related genes (ERGs) by analyzing The Cancer Genome Atlas (TCGA) database and exoRBase 2.0 database. We then determined prognosis-related ERGs (PRERGs) by univariate Cox regression analysis. Gene Dependency Score (gDS), target development level, and pathway correlation analysis were utilized to examine the importance of PRERGs. Machine learning and lasso-cox regression were utilized to screen and construct a 5-gene risk model. The risk model showed high predictive accuracy for the prognosis of patients and proved to be an independent prognostic factor in three RCC datasets, including TCGA-KIRC, E-MTAB-1980, and TCGA-KIRP datasets. Patients with high-risk scores showed worse outcomes in different clinical subgroups, revealing that the risk score is robust. In addition, we found that immune-related pathways are highly enriched in the high-risk group. Activities of immune cells were distinct in high-/low-risk groups. In independent immune therapeutic cohorts, high-risk patients show worse immune therapy responses. In summary, we identified several exosome-derived genes that might play essential roles in RCC and constructed a 5-gene risk signature to predict the prognosis of RCC and immune therapy response.

A bibliometric analysis of the application of the PI3K-AKT-mTOR signaling pathway in cancer

PI3K-AKT-mTOR plays as important role in the growth, metabolism, proliferation, and migration of cancer cells, and in apoptosis, autophagy, inflammation, and angiogenesis in cancer. In this study, the aim was to comprehensively review the current research landscape regarding the PI3K-AKT-mTOR pathway in cancer, using bibliometrics to analyze research hotspots, and provide ideas for future research directions. Literature published on the topic between January 2006 and May 2023 was retrieved from the Web of Science core database, and key information and a visualization map were analyzed using CiteSpace and VOSviewer. A total of 5800 articles from 95 countries/regions were collected, including from China and the USA. The number of publications on the topic increased year on year. The major research institution was the University of Texas MD Anderson Cancer Center. Oncotarget and Clinical Cancer Research were the most prevalent journals in the field. Of 26,621 authors, R Kurzrock published the most articles, and J Engelman was cited most frequently. "A549 cell," "first line treatment," "first in human phase I," and "inhibitor" were the keywords of emerging research hotspots. Inhibitors of the PI3K-AKT-mTOR pathway and their use in clinical therapeutic strategies for cancer were the main topics in the field, and future research should also focus on PI3K-AKT-mTOR pathway inhibitors. This study is the first to comprehensively summarize trends and development s in research into the PI3K-AKT-mTOR pathway in cancer. The information that was obtained clarified recent research frontiers and directions, providing references for scholars of cancer management.

Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation

Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R2=0.6586, p=0.0044) and stress granule (a=0.8000, R2=0.6000, p=0.0085) as the most potential star molecule in this field. More interestingly, the Random-Walk-Strategy-based Walktrap algorithm further revealed that "phase separation, cancer, transcription, super-enhancer, epigenetics"(Relevance Percentage[RP]=100%, Development Percentage[DP]=29.2%), "stress granule, immunotherapy, tumor microenvironment, RNA binding protein"(RP=79.2%, DP=33.3%) and "nanoparticle, apoptosis"(RP=70.8%, DP=25.0%) are closely associated with this field, but are still under-developed and worthy of further exploration. In conclusion, this study profiled the global scientific landscape, discovered a crucial emerging research cluster, identified several pivotal research molecules, and predicted several crucial but still under-developed directions that deserve further research, providing an important reference value for subsequent basic and clinical research of phase separation in cancer.

Unveiling the role of YARS1 in bladder cancer: A prognostic biomarker and therapeutic target

YARS is responsible for catalysing the binding of tyrosine to its cognate tRNA and plays a crucial role in basic biosynthesis. However, its biological functions in bladder cancer remains to be proven. We analysed variations in YARS1 expression and survival in bladder cancer using multiple data sets, including TCGA-BLCA, GSE13507 and bladder cancer-specific tissue microarrays. Furthermore, we explored the biological functions of YARS1 using transcriptome data. Our findings revealed a noteworthy correlation between YARS1 and immune infiltration in bladder cancer, as determined using the XCELL algorithm and single-cell analysis. In addition, we employed the TIDE algorithm to evaluate the responsiveness of different cohorts to immune checkpoint therapy. We investigated the regulatory associations between YARS1 and various aspects of bladder cancer, including senescence, ferroptosis and stemness. Finally, we established a ceRNA network that is directly linked to the overall prognosis, YARS1 can serve as a prognostic biomarker for bladder cancer; its interaction with MYC has implications for bladder cancer cell senescence, ferroptosis and stemness. Moreover, the identified ceRNA network has potential as a therapeutic target in bladder cancer.

Machine-learning-based prediction of a diagnostic model using autophagy-related genes based on RNA sequencing for patients with papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer and belongs to the category of malignant tumors of the thyroid gland. Autophagy plays an important role in PTC. The purpose of this study is to develop a novel diagnostic model using autophagy-related genes (ARGs) in patients. In this study, RNA sequencing data of PTC samples and normal samples were obtained from GSE33630 and GSE29265. Then, we analyzed GSE33630 datasets and identified 127 DE-ARGs. Functional enrichment analysis suggested that 127 DE-ARGs were mainly enriched in pathways in cancer, protein processing in endoplasmic reticulum, toll-like receptor pathway, MAPK pathway, apoptosis, neurotrophin signaling pathway, and regulation of autophagy. Subsequently, CALCOCO2, DAPK1, and RAC1 among the 127 DE-ARGs were identified as diagnostic genes by support vector machine recursive feature elimination and least absolute shrinkage and selection operator algorithms. Then, we developed a novel diagnostic model using CALCOCO2, DAPK1, and RAC1 and its diagnostic value was confirmed in GSE29265 and our cohorts. Importantly, CALCOCO2 may be a critical regulator involved in immune microenvironment because its expression was related to many types of immune cells. Overall, we developed a novel diagnostic model using CALCOCO2, DAPK1, and RAC1 which can be used as diagnostic markers of PTC.

Knowledge map of thrombopoietin receptor agonists: A bibliometric analysis

Thrombopoietin receptor agonists (TPO-RAs) have been widely used to treat thrombocytopenia, however, a scientometric profile of TPO-RAs research is lacking. Methods: This study uses VOSviewer, CiteSpace, and R software to provide an overview of current research, highlight study hotspots, and predict future research directions of TPO-RAs. Results: One thousand seven hundred and nineteen relevant studies from 1993 to 2022 with 43962 citations were identified from the Web of Science Core Collection. Over three decades, the USA has been leading TPO-RAs publications. Industries and academic institutions have been actively involved in TPO-RAs research, with funding provided by pharmaceutical companies and public funding bodies. The most productive and cited journals are British Journal of Hematology and Blood, respectively. When author keywords were categorised into three clusters, i.e., cluster 1 (immune thrombocytopenic purpura (ITP)), cluster 2 (avatrombopag, lusutrombopag, and thrombocytopenia), and cluster 3 (TPO-RAs for ITP and off-label drug use), ITP was found to be the current research hotspot, while oral TPO-RAs and licensed or unlicensed drug indications of thrombocytopenic diseases require further investigation. Conclusion: This study has generated the knowledge map of TPO-RAs, which provides a dynamic roadmap for future research in this field.

Predictors of gastrointestinal complaints in patients on metformin therapy

Although being very effective in the treatment of diabetes and a few other conditions, metformin (MTF) cannot be tolerated by many patients due to gastrointestinal (GI) complaints. A number of risk factors for intolerance were identified, but many are still controversial or uninvestigated. The aim of this study was to further investigate possible risk factors for the occurrence of GI complaints in patients on MTF therapy. A cross-sectional design was used for this multicentric study on adult patients visiting 50 community pharmacies in Montenegro. The patients were surveyed by semi-structured questionnaire after a service of a pharmacist was delivered, and their drugs dispensed. Uni- and multi-variate regression methods were used for processing the data. In total 330 patients participated in the study. A higher body mass index (OR = 1.113, p = 0.003), living at a higher altitude (OR = 1.725, p = 0.000), anaemia (OR = 4.221, p = 0.008), and intestinal infection in the last 3 months (OR = 2.801, p = 0.006) increased the risk of GI complaints in patients on MTF therapy, while the use of statins was protective (OR = 0.204, p = 0.016). Each case of MTF intolerance should be carefully investigated for risk and protective factors, which could be potentially eliminated or augmented, respectively, and MTF withdrawal avoided.

A state-of-the-art review on the NRF2 in Hepatitis virus-associated liver cancer

According to a paper released and submitted to WHO by IARC scientists, there would be 905,700 new cases of liver cancer diagnosed globally in 2020, with 830,200 deaths expected as a direct result. Hepatitis B virus (HBV) hepatitis C virus (HCV), and hepatitis D virus (HDV) all play critical roles in the pathogenesis of hepatocellular carcinoma (HCC), despite the rising prevalence of HCC due to non-infectious causes. Liver cirrhosis and HCC are devastating consequences of HBV and HCV infections, which are widespread worldwide. Associated with a high mortality rate, these infections cause about 1.3 million deaths annually and are the primary cause of HCC globally. In addition to causing insertional mutations due to viral gene integration, epigenetic alterations and inducing chronic immunological dysfunction are all methods by which these viruses turn hepatocytes into cancerous ones. While expanding our knowledge of the illness, identifying these pathways also give possibilities for novel diagnostic and treatment methods. Nuclear factor erythroid 2-related factor 2 (NRF2) activation is gaining popularity as a treatment option for oxidative stress (OS), inflammation, and metabolic abnormalities. Numerous studies have shown that elevated Nrf2 expression is linked to HCC, providing more evidence that Nrf2 is a critical factor in HCC. This aberrant Nrf2 signaling drives cell proliferation, initiates angiogenesis and invasion, and imparts drug resistance. As a result, this master regulator may be a promising treatment target for HCC. In addition, the activation of Nrf2 is a common viral effect that contributes to the pathogenesis, development, and chronicity of virus infection. However, certain viruses suppress Nrf2 activity, which is helpful to the virus in maintaining cellular homeostasis. In this paper, we discussed the influence of Nrf2 deregulation on the viral life cycle and the pathogenesis associated with HBV and HCV. We summed up the mechanisms for the modulation of Nrf2 that are deregulated by these viruses. Moreover, we describe the molecular mechanism by which Nrf2 is modulated in liver cancer, liver cancer stem cells (LCSCs), and liver cancer caused by HBV and HCV. Video Abstract.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures

Background

There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented.

Methods

After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism.

Results

The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism.

Conclusion

This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.