Worldwide research trends on tumor burden and immunotherapy: a bibliometric analysis.

Various immunotherapy has been greatly applied to comprehensive treatment of malignant cancer under different degrees of tumor burden. Scientific researchers have gained considerable progress in the relationship between immunotherapy and tumor burden in recent years. This review aimed to explore the prospect and developing trends in the field of tumor burden and immunotherapy from a bibliometric perspective. Articles about tumor burden and immunotherapy were collected from the Web of Science Core Collection (WoSCC) (retrieved on 3 January 2023). The R package 'Bibliometrix' analyzed the primary bibliometric features and created a three-filed plot to display the relationship between institutions, countries, and keywords. VOSviewer was used for co-authorship analysis, co-occurrence analysis, and their visualization. And CiteSpace calculated the citation burst references and keywords. A total of 1030 publications were retrieved from 35 years of scientific researches. The United States (US) and China published the most articles. The most productive journals were Cancer Immunology Immunotherapy and Journal for ImmunoTherapy of Cancer . The top one institution of the highest output was University of Texas MD Anderson Cancer Center. The hot keywords of strong citation burst strength in recent years were 'nivolumab', 'tumor microenvironment', and 'immune checkpoint inhibitor'. The most popular tumor type is melanoma. This bibliometric analysis mapped a basic knowledge structure. The field of tumor burden and immunotherapy is entering a rapid growing stage and keeping it value for future research.

The role of large language models in medical image processing: a narrative review.

Background and Objective: The rapid advancement of artificial intelligence (AI) has ushered in a new era in natural language processing (NLP), with large language models (LLMs) like ChatGPT leading the way. This paper explores the profound impact of AI, particularly LLMs, in the field of medical image processing. The objective is to provide insights into the transformative potential of AI in improving healthcare by addressing historical challenges associated with manual image interpretation. Methods: A comprehensive literature search was conducted on the Web of Science and PubMed databases from 2013 to 2023, focusing on the transformations of LLMs in Medical Imaging Processing. Recent publications on the arXiv database were also reviewed. Our search criteria included all types of articles, including abstracts, review articles, letters, and editorials. The language of publications was restricted to English to facilitate further content analysis. Key Content and Findings: The review reveals that AI, driven by LLMs, has revolutionized medical image processing by streamlining the interpretation process, traditionally characterized by time-intensive manual efforts. AI's impact on medical care quality and patient well-being is substantial. With their robust interactivity and multimodal learning capabilities, LLMs offer immense potential for enhancing various aspects of medical image processing. Additionally, the Transformer architecture, foundational to LLMs, is gaining prominence in this domain. Conclusions: In conclusion, this review underscores the pivotal role of AI, especially LLMs, in advancing medical image processing. These technologies have the capacity to enhance transfer learning efficiency, integrate multimodal data, facilitate clinical interactivity, and optimize cost-efficiency in healthcare. The potential applications of LLMs in clinical settings are promising, with far-reaching implications for future research, clinical practice, and healthcare policy. The transformative impact of AI in medical image processing is undeniable, and its continued development and implementation are poised to reshape the healthcare landscape for the better.

Development and validation of web-based nomograms for predicting survival status in patients with intrahepatic cholangiocarcinoma depending on the surgical status: a SEER database analysis.

This study aimed to develop and validate prognostic nomograms that can estimate the probability of 1-, 3- and 5-year overall survival (OS) as well as cancer-specific survival (CSS) for Intrahepatic cholangiocarcinoma (ICCA) patients. Clinical data of 1446 patients diagnosed with ICCA between 2010 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database were analyzed. In both the OS and the CSS group, the training cohort and validation cohort were divided into a 7:3 ratio. Age, sex, AJCC T stage, AJCC N stage, AJCC M stage, surgical status, and tumor grade were selected as independent prognostic risk factors to build the nomograms. To compare the efficacy of predicting 1-, 3-, and 5-year OS and CSS rates of the nomogram with the 8th edition of the American Joint Committee on Cancer (AJCC) staging system, we evaluated the Harrell's index of concordance (C-index), area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) in both cohorts. The results showed the nomogram for 1-, 3-, and 5-year OS and CSS prediction performed better than the AJCC staging system. In the subgroup analysis for patients could not receive surgery as the primary treatment. We developed two nomograms for predicting the 1-, and 2-year OS and CSS rates following the same analysis procedure. Results indicate that the performance of both nomograms, which contained sex, AJCC T stage, AJCC M stage, chemotherapy, and tumor grade and prognostic factors, was also superior to the AJCC staging system. Meanwhile, four dynamic network-based nomograms were published. The survival analysis showed the survival rate of patients classified as high-risk based on the nomogram score was significantly lower compared to those categorized as low-risk (P < 0.0001). Finally, accurate and convenient nomograms were established to assist clinicians in making more personalized prognosis predictions for ICCA patients.

Unravelling the liver-brain connection: A two-sample Mendelian randomization study investigating the causal relationship between NAFLD and cortical structure.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) has been linked to cognitive decline and neuropsychiatric conditions, implying a potential connection between NAFLD and brain health. However, the causal association between NAFLD and cortical changes remains uncertain. This study aimed to examine the causal impact of NAFLD on cortical structures using a two-sample Mendelian randomization (MR) approach. METHODS: Summary data from genome-wide association studies (GWAS) for NAFLD were gathered from large-scale cohorts. Surface area (SA) and cortical thickness (TH) measurements were derived from Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium magnetic resonance imaging (MRI) data of 33,992 participants. Inverse-variance weighted (IVW) served as the primary method. Additional sensitivity analyses, including MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO), MR-Egger, and weighted median procedures, were conducted to detect heterogeneity and pleiotropy. RESULTS: Our MR analysis revealed that NAFLD led to notable alterations in cortical structures, particularly in the pars orbitalis gyrus. Specifically, genetically predicted NAFLD was linked to a decrease in TH (ß = -0.008 mm, 95 % CI: -0.013 mm to -0.004 mm, P = 3.00 × 10-4) within this region. No significant heterogeneity and pleiotropy were identified. CONCLUSION: The two-sample MR study supports the existence of a liver-brain axis by demonstrating a causal association between NAFLD and changes in cortical structures. These findings emphasize the potential association between NAFLD and brain health, which could have implications for preventing and treating cognitive deficits and neuropsychiatric conditions in patients with NAFLD.

Worldwide productivity and research trend of publications concerning tumor immune microenvironment (TIME): a bibliometric study.

BACKGROUND: As the complexity and diversity of the tumor immune microenvironment (TIME) are becoming better understood, burgeoning research has progressed in this field. However, there is a scarcity of literature specifically focused on the bibliometric analysis of this topic. This study sought to investigate the development pattern of TIME-related research from 2006 to September 14, 2022, from a bibliometric perspective. METHODS: We acquired both articles and reviews related to TIME from the Web of Science Core Collection (WoSCC) (retrieved on September 14, 2022). R package "Bibliometrix" was used to calculate the basic bibliometric features, present the collaborative conditions of countries and authors, and generate a three-field plot to show the relationships among authors, affiliations, and keywords. VOSviewer was utilized for co-authorship analysis of country and institution and keyword co-occurrence analysis. CiteSpace was used for citation burst analysis of keywords and cited references. In addition, Microsoft Office Excel 2019 was used to develop an exponential model to fit the cumulative publication numbers. RESULTS: A total of 2545 publications on TIME were included, and the annual publication trend exhibited a significant increase over time. China and Fudan University were the most productive country and institution, with the highest number of publications of 1495 and 396, respectively. Frontiers in Oncology held the highest number of publications. A number of authors were recognized as the main contributors in this field. The clustering analysis revealed six clusters of keywords that highlighted the research hot spots in the fields of basic medical research, immunotherapy, and various cancer types separately. CONCLUSIONS: This research analyzed 16 years of TIME-related research and sketched out a basic knowledge framework that includes publications, countries, journals, authors, institutions, and keywords. The finding revealed that the current research hot spots of the TIME domain lie in "TIME and cancer prognosis", "cancer immunotherapy", and "immune checkpoint". Our researchers identified the following areas: "immune checkpoint-based immunotherapy", "precise immunotherapy" and "immunocyte pattern", which may emerge as frontiers and focal points in the upcoming years, offering valuable avenues for further exploration.

Evolutionary patterns and research frontiers in neoadjuvant immunotherapy: a bibliometric analysis.

Research has shown that neoadjuvant immunotherapy may provide more significant clinical benefits to cancer patients undergoing surgery than adjuvant therapy. This study examines the development of neoadjuvant immunotherapy research using bibliometric analysis. As of 12 February 2023, articles on neoadjuvant immunotherapy in the Web of Science Core Collection were collected. Co-authorship and keyword co-occurrence analyses and visualizations were performed using VOSviewer, while CiteSpace was used to identify bursting keywords and references. The study analyzed a total of 1222 neoadjuvant immunotherapy publications. The top contributors to this field were the United States, China, and Italy, and the journal with the most publications was Frontiers in Oncology. Francesco Montorsi had the highest H-index. The most common keywords were 'immunotherapy' and 'neoadjuvant therapy'. The study conducted a bibliometric analysis of over 20 years of neoadjuvant immunotherapy research, identifying the countries, institutions, authors, journals, and publications involved in this field. The findings provide a comprehensive overview of neoadjuvant immunotherapy research.

Research on liquid biopsy for cancer: A bibliometric analysis.

BACKGROUND: In recent years, liquid biopsy has shown great potential for improving cancer diagnosis and treatment. This study aimed to explore the trends and prospects in liquid biopsy for cancer from a bibliometric perspective. METHODS: Reviews and articles on liquid biopsy and cancer were collected from the Web of Science Core Collection (WoSCC). Key bibliometric characteristics were analyzed using CiteSpace. Co-occurrence analysis of keywords and co-citation analysis of references was performed. RESULTS: A total of 6331 publications from 11 years of scientific research were retrieved. Ninety-five countries and 7004 institutions in liquid biopsy and cancer contributed. The United States (US) and China published the most articles. The institution with the most published articles was the University of Texas MD Anderson Cancer Center. The most published journals were Cancer and Frontiers in Oncology. "Bettegowda (2014)" was the most cited reference with the highest burst strength in the last decade. Cluster analysis revealed that the recent hot topics were "circulating tumor cells," "cancer," and "exosomes." CONCLUSIONS: This bibliometric analysis maps the basic knowledge structure of the field of liquid biopsy for cancer. The field is entering a phase of rapid development. The hot spots identified in this study deserve further investigation.

Primary gastrinoma of the gallbladder: a case report and review of the literature.

Background: Primary gallbladder gastrinoma is an exceptionally uncommon tumor and is a rare form of neuroendocrine neoplasm. Until now, no cases of primary gallbladder gastrinoma and rare cases of primary gastrinoma from the biliary system have been reported. Case presentation: We report a case of a 50-year-old woman with watery diarrhea who intermittently received proton pump inhibitors (PPIs) as treatment. A serum gastrin level of 711 pg/ml was recorded after the withdrawal of PPI over 1 week. Enhanced computed tomography (CT) imaging and octreotide imaging uncovered a solitary tumor at the hepatic hilar region. During the laparoscopic surgery, it was determined that the tumor had its origin in the wall of the gallbladder neck, prompting the implementation of a laparoscopic cholecystectomy. Histological analysis revealed a primary neuroendocrine tumor from the neck of the gallbladder. The patient's symptoms disappeared after the surgery with a follow-up of 6 months. Conclusions: This case confirmed that primary gallbladder gastrinoma represents a distinct nosological entity. Immunohistochemical analysis plays a pivotal role in the diagnostic process. Given the limited understanding of primary gallbladder gastrinoma, our objective is to offer novel insights into this rare disease by delivering distinctive information and highlighting the therapeutic significance of surgical intervention.

A novel cuproptosis-related gene signature for overall survival prediction in patients with hepatocellular carcinoma.

Prognosis prediction is difficult in hepatocellular carcinoma (HCC) due to high heterogeneity and complex etiology. It has recently been discovered that cuproptosis is a type of programmed cell death. However, its significance for HCC is still unclear. We analyzed mRNA expression profiles and clinical information from public databases to determine whether cuproptosis-related genes are associated with improved prognoses for HCC patients. The training cohort consisted of HCC patients from The Cancer Genome Atlas (TCGA), and the validation cohort relied on the International Cancer Genome Consortium (ICGC) database. We constructed a signature containing four genes using the least absolute shrinkage and selection operator (LASSO) COX regression model for calculating risk scores. Two risk groups were formed based on the median score. A significant improvement in survival was observed in the low-risk group compared to the high-risk. The multivariate Cox regression analysis showed that the risk score was an independent predictor of overall survival (OS). Further confirmation of the predictive accuracy of this signature is provided by receiver operating characteristic (ROC) analysis. Functional analysis revealed differences in immune status between the two risk groups. All the results described above were confirmed in the validation cohort. Therefore, a novel cuproptosis-related signature has the potential as a prognostic biomarker for HCC patients. Drugs developed to target cuproptosis-related genes may open up new pathways for treating HCC.

Systems biology approach reveals a common molecular basis for COVID-19 and non-alcoholic fatty liver disease (NAFLD).

BACKGROUND: Patients with non-alcoholic fatty liver disease (NAFLD) may be more susceptible to coronavirus disease 2019 (COVID-19) and even more likely to suffer from severe COVID-19. Whether there is a common molecular pathological basis for COVID-19 and NAFLD remains to be identified. The present study aimed to elucidate the transcriptional alterations shared by COVID-19 and NAFLD and to identify potential compounds targeting both diseases. METHODS: Differentially expressed genes (DEGs) for COVID-19 and NAFLD were extracted from the GSE147507 and GSE89632 datasets, and common DEGs were identified using the Venn diagram. Subsequently, we constructed a protein-protein interaction (PPI) network based on the common DEGs and extracted hub genes. Then, we performed gene ontology (GO) and pathway analysis of common DEGs. In addition, transcription factors (TFs) and miRNAs regulatory networks were constructed, and drug candidates were identified. RESULTS: We identified a total of 62 common DEGs for COVID-19 and NAFLD. The 10 hub genes extracted based on the PPI network were IL6, IL1B, PTGS2, JUN, FOS, ATF3, SOCS3, CSF3, NFKB2, and HBEGF. In addition, we also constructed TFs-DEGs, miRNAs-DEGs, and protein-drug interaction networks, demonstrating the complex regulatory relationships of common DEGs. CONCLUSION: We successfully extracted 10 hub genes that could be used as novel therapeutic targets for COVID-19 and NAFLD. In addition, based on common DEGs, we propose some potential drugs that may benefit patients with COVID-19 and NAFLD.

A novel nomogram based on log odds of positive lymph nodes to predict survival for non-metastatic gallbladder adenocarcinoma after surgery.

The prognosis of non-metastatic gallbladder adenocarcinoma (NM-GBA) patients is affected by the status of metastatic lymph nodes. The purpose of this study was to explore the prognostic value of the log odds of positive lymph nodes (LODDS) and develop a novel nomogram to predict the overall survival in NM-GBA patients. A total of 1035 patients confirmed to have NM-GBA were selected from the Surveillance, Epidemiology, and End Results (SEER) database and further divided into training and validation cohorts. The discrimination and calibration of the nomogram were evaluated using the concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration plots. The net benefits and clinical utility of the nomogram were quantified and compared with those of the 8th edition American Joint Committee on Cancer (AJCC) Tumor-Node-Metastasis (TNM) staging system using decision curve analysis (DCA), net reclassification index (NRI), and integrated discrimination improvement (IDI). The risk stratifications of the nomogram and the TNM-staging system were compared. LODDS showed the highest accuracy in predicting OS for NM-GBA. The C-index (0.730 for the training cohort and 0.746 for the validation cohort) and the time-dependent AUC (> 0.7) indicated the satisfactory discriminative ability of the nomogram. The calibration plots showed a high degree of consistency. The DCA, NRI, and IDI indicated that the nomogram performed significantly better than the TNM-staging (P < 0.05). A novel LODDS-included nomogram was developed and validated to assist clinicians in evaluating the prognosis of NM-GBA patients.

Nomogram based on radiomics analysis of ultrasound images can improve preoperative BRAF mutation diagnosis for papillary thyroid microcarcinoma.

Background: The preoperative identification of BRAF mutation could assist to make appropriate treatment strategies for patients with papillary thyroid microcarcinoma (PTMC). This study aimed to establish an ultrasound (US) radiomics nomogram for the assessment of BRAF status. Methods: A total of 328 PTMC patients at the China-Japan Friendship Hospital between February 2019 and November 2021 were enrolled in this study. They were randomly divided into training (n = 232) and validation (n = 96) cohorts. Radiomics features were extracted from the US images. The least absolute shrinkage and selection operator (LASSO) regression was applied to select the BRAF status-related features and calculate the radiomics score (Rad-score). Univariate and multivariate logistic regression analyses were subsequently performed to identify the independent factors among Rad-score and conventional US features. The US radiomics nomogram was established and its predictive performance was evaluated via discrimination, calibration, and clinical usefulness in the training and validation sets. Results: Multivariate analysis indicated that the Rad-score, composition, and aspect ratio were independent predictive factors of BRAF status. The US radiomics nomogram which incorporated the three variables showed good calibration. The discrimination of the US radiomics nomogram showed better discriminative ability than the conventional US model both in the training set (AUC 0.685 vs. 0.592) and validation set (AUC 0.651 vs. 0.622). Decision curve analysis indicated the superior clinical applicability of the nomogram compared to the conventional US model. Conclusions: The US radiomics nomogram displayed better performance than the conventional US model in predicting BRAF mutation in patients with PTMC.

Study on the Prognostic Values of TTC36 Correlated with Immune Infiltrates and Its Methylation in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains an incurable disease with a very poor clinical outcome. The purpose of this article was to investigate whether the expression or methylation of tetrapeptide repeat domain 36 (TTC36) could be used as a prognostic marker in hepatocellular carcinoma. TCGA database was used to obtain information on HCC gene expression and the associated clinical features of HCC patients. Differentially expressed genes (DEGs) were screened between 374 HCC specimens and 50 nontumor specimens. The expression and prognostic value of TTC36 were analyzed. The correlations between TTC36 and cancer immune infiltrates were investigated via TIMER. In this study, HCC specimens and nontumor specimens were compared and 35 DEGs were found between them. Among the 35 DEGs, the expression of TTC36 was significantly reduced in HCC samples compared with nontumor samples. Survival tests revealed that patients with low TTC36 expression had a shorter overall survival than patients with high TTC36 expression. TTC36 was found to be an independent predictive factor for HCC in both univariate and multivariate regression analyses. TTC36 was negatively regulated by TTC36 methylation, leading to its low expression in HCC tissues. Immune analysis revealed that TTC36 expression has significant correlations with B cell, T cell CD4+, neutrophil, macrophage, and myeloid dendritic cell. Finally, TTC36 expression was dramatically reduced in HCC cells, and overexpression greatly suppressed HCC cell proliferation and invasion, according to our experimental results. Overall, our data suggested that TTC36 could be applied as a prognostic marker for predicting outcome and immune infiltration in HCC.