RefAI: a GPT-powered retrieval-augmented generative tool for biomedical literature recommendation and summarization.

OBJECTIVES: Precise literature recommendation and summarization are crucial for biomedical professionals. While the latest iteration of generative pretrained transformer (GPT) incorporates 2 distinct modes-real-time search and pretrained model utilization-it encounters challenges in dealing with these tasks. Specifically, the real-time search can pinpoint some relevant articles but occasionally provides fabricated papers, whereas the pretrained model excels in generating well-structured summaries but struggles to cite specific sources. In response, this study introduces RefAI, an innovative retrieval-augmented generative tool designed to synergize the strengths of large language models (LLMs) while overcoming their limitations. MATERIALS AND METHODS: RefAI utilized PubMed for systematic literature retrieval, employed a novel multivariable algorithm for article recommendation, and leveraged GPT-4 turbo for summarization. Ten queries under 2 prevalent topics ("cancer immunotherapy and target therapy" and "LLMs in medicine") were chosen as use cases and 3 established counterparts (ChatGPT-4, ScholarAI, and Gemini) as our baselines. The evaluation was conducted by 10 domain experts through standard statistical analyses for performance comparison. RESULTS: The overall performance of RefAI surpassed that of the baselines across 5 evaluated dimensions-relevance and quality for literature recommendation, accuracy, comprehensiveness, and reference integration for summarization, with the majority exhibiting statistically significant improvements (P-values <.05). DISCUSSION: RefAI demonstrated substantial improvements in literature recommendation and summarization over existing tools, addressing issues like fabricated papers, metadata inaccuracies, restricted recommendations, and poor reference integration. CONCLUSION: By augmenting LLM with external resources and a novel ranking algorithm, RefAI is uniquely capable of recommending high-quality literature and generating well-structured summaries, holding the potential to meet the critical needs of biomedical professionals in navigating and synthesizing vast amounts of scientific literature.

Alpha-Emitter Radium-223 Induces STING-Dependent Pyroptosis to Trigger Robust Antitumor Immunity.

Radium-223 (223 Ra) is the first-in-class alpha-emitter to mediate tumor eradication, which is commonly thought to kill tumor cells by directly cleaving double-strand DNA. However, the immunogenic characteristics and cell death modalities triggered by 223 Ra remain unclear. Here, it is reported that the 223 Ra irradiation induces the pro-inflammatory damage-associated molecular patterns including calreticulin, HMGB1, and HSP70, hallmarks of tumor immunogenicity. Moreover, therapeutic 223 Ra retards tumor progression by triggering pyroptosis, an immunogenic cell death. Mechanically, 223 Ra-induced DNA damage leads to the activation of stimulator of interferon genes (STING)-mediated DNA sensing pathway, which is critical for NLRP3 inflammasome-dependent pyroptosis and subsequent DCs maturation as well as T cell activation. These findings establish an essential role of STING in mediating alpha-emitter 223 Ra-induced antitumor immunity, which provides the basis for the development of novel cancer therapeutic strategies and combinatory therapy.

TAK1 is an essential kinase for STING trafficking.

The translocation of stimulator of interferon genes (STING) from the endoplasmic reticulum (ER) to the ER-Golgi intermediate compartment (ERGIC) enables its activation. However, the mechanism underlying the regulation of STING exit from the ER remains elusive. Here, we found that STING induces the activation of transforming growth factor beta-activated kinase 1 (TAK1) prior to STING trafficking in a TAK1 binding protein 1 (TAB1)-dependent manner. Intriguingly, activated TAK1 directly mediates STING phosphorylation on serine 355, which facilitates its interaction with STING ER exit protein (STEEP) and thereby promotes its oligomerization and translocation to the ERGIC for subsequent activation. Importantly, activation of TAK1 by monophosphoryl lipid A, a TLR4 agonist, boosts cGAMP-induced antitumor immunity dependent on STING phosphorylation in a mouse allograft tumor model. Taken together, TAK1 was identified as a checkpoint for STING activation by promoting its trafficking, providing a basis for combinatory tumor immunotherapy and intervention in STING-related diseases.

Pharmacological boosting of cGAS activation sensitizes chemotherapy by enhancing antitumor immunity.

Enhancing chemosensitivity is one of the largest unmet medical needs in cancer therapy. Cyclic GMP-AMP synthase (cGAS) connects genome instability caused by platinum-based chemotherapeutics to type I interferon (IFN) response. Here, by using a high-throughput small-molecule microarray-based screening of cGAS interacting compounds, we identify brivanib, known as a dual inhibitor of vascular endothelial growth factor receptor and fibroblast growth factor receptor, as a cGAS modulator. Brivanib markedly enhances cGAS-mediated type I IFN response in tumor cells treated with platinum. Mechanistically, brivanib directly targets cGAS and enhances its DNA binding affinity. Importantly, brivanib synergizes with cisplatin in tumor control by boosting CD8+ T cell response in a tumor-intrinsic cGAS-dependent manner, which is further validated by a patient-derived tumor-like cell clusters model. Taken together, our findings identify cGAS as an unprecedented target of brivanib and provide a rationale for the combination of brivanib with platinum-based chemotherapeutics in cancer treatment.

The multifaceted functions of cGAS.

Pattern recognition receptors are critical for the sensing of pathogen-associated molecular patterns or danger-associated molecular patterns and subsequent mounting of innate immunity and shaping of adaptive immunity. The identification of 2'3'-cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) synthase (cGAS) as a major cytosolic DNA receptor is a milestone in the field of DNA sensing. The engagement of cGAS by double-stranded DNA from different origins, including invading pathogens, damaged mitochondria, ruptured micronuclei, and genomic DNA results in the generation of cGAMP and activation of stimulator of interferon genes, which thereby activates innate immunity mainly characterized by the activation of type I interferon response. In recent years, great progress has been made in understanding the subcellular localization and novel functions of cGAS. In this review, we particularly focus on summarizing the multifaceted roles of cGAS in regulating senescence, autophagy, cell stemness, apoptosis, angiogenesis, cell proliferation, antitumor effect, DNA replication, DNA damage repair, micronucleophagy, as well as cell metabolism.

Cytoplasmic PARP1 links the genome instability to the inhibition of antiviral immunity through PARylating cGAS.

Virus infection modulates both host immunity and host genomic stability. Poly(ADP-ribose) polymerase 1 (PARP1) is a key nuclear sensor of DNA damage, which maintains genomic integrity, and the successful application of PARP1 inhibitors for clinical anti-cancer therapy has lasted for decades. However, precisely how PARP1 gains access to cytoplasm and regulates antiviral immunity remains unknown. Here, we report that DNA virus induces a reactive nitrogen species (RNS)-dependent DNA damage and activates DNA-dependent protein kinase (DNA-PK). Activated DNA-PK phosphorylates PARP1 on Thr594, thus facilitating the cytoplasmic translocation of PARP1 to inhibit the antiviral immunity both in vitro and in vivo. Mechanistically, cytoplasmic PARP1 interacts with and directly PARylates cyclic GMP-AMP synthase (cGAS) on Asp191 to inhibit its DNA-binding ability. Together, our findings uncover an essential role of PARP1 in linking virus-induced genome instability with inhibition of host immunity, which is of relevance to cancer, autoinflammation, and other diseases.

CDK inhibitor Palbociclib targets STING to alleviate autoinflammation.

Aberrant activation of stimulator of interferon genes (STING) is tightly associated with multiple types of disease, including cancer, infection, and autoimmune diseases. However, the development of STING modulators for the therapy of STING-related diseases is still an unmet clinical need. We employed a high-throughput screening approach based on the interaction of small-molecule chemical compounds with recombinant STING protein to identify functional STING modulators. Intriguingly, the cyclin-dependent protein kinase (CDK) inhibitor Palbociclib was found to directly bind STING and inhibit its activation in both mouse and human cells. Mechanistically, Palbociclib targets Y167 of STING to block its dimerization, its binding with cyclic dinucleotides, and its trafficking. Importantly, Palbociclib alleviates autoimmune disease features induced by dextran sulphate sodium or genetic ablation of three prime repair exonuclease 1 (Trex1) in mice in a STING-dependent manner. Our work identifies Palbociclib as a novel pharmacological inhibitor of STING that abrogates its homodimerization and provides a basis for the fast repurposing of this Food and Drug Administration-approved drug for the therapy of autoinflammatory diseases.

Nonselective beta-blockers are associated with a lower risk of hepatocellular carcinoma among cirrhotic patients in the United States.

BACKGROUND: Previous studies have demonstrated an association between nonselective beta-blockers (NSBBs) and lower risk of hepatocellular carcinoma (HCC) in cirrhosis. However, there has been no population-based study investigating the risk of HCC among cirrhotic patients treated using carvedilol. AIMS: To determine the risk of HCC among cirrhotic patients with NSBBs including carvedilol. METHODS: This retrospective cohort study utilised the Cerner Health Facts database in the United States from 2000 to 2017. Kaplan-Meier estimate, Cox proportional hazards regression, and propensity score matching (PSM) were used to test the HCC risk among the carvedilol, nadolol, and propranolol groups compared with no beta-blocker group. RESULTS: The final cohort comprised 107 428 eligible patients. The 100-month cumulative HCC incidence of NSBBs was significantly lower than the no beta-blocker group (carvedilol (11.24%) vs no beta-blocker (15.69%), nadolol (27.55%) vs no beta-blocker (32.11%), and propranolol (26.17%) vs no beta-blocker (28.84%) (P values < 0.0001). NSBBs were associated with a significantly lower risk of HCC (Hazard ratio: carvedilol 0.61 (95% CI 0.51-0.73), nadolol 0.74 (95% CI 0.63-0.87), propranolol 0.75 (95% CI 0.66-0.84) after PSM in the multivariate cox analysis. In subgroup analysis, NSBBs reduced the risk of HCC in cirrhosis with complications and non-alcoholic cirrhosis. CONCLUSIONS: NSBBs, including carvedilol, were associated with a significantly decreased risk of HCC in patients with cirrhosis when compared with no beta-blocker regardless of complications status. Future randomised-controlled studies comparing the incidence of HCC among NSBBs should elucidate which NSBB would be the best option to prevent HCC in cirrhosis.

OSmfs: An Online Interactive Tool to Evaluate Prognostic Markers for Myxofibrosarcoma.

Myxofibrosarcoma is a complex genetic disease with poor prognosis. However, more effective biomarkers that forebode poor prognosis in Myxofibrosarcoma remain to be determined. Herein, utilizing gene expression profiling data and clinical follow-up data of Myxofibrosarcoma cases in three independent cohorts with a total of 128 Myxofibrosarcoma samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we constructed an easy-to-use web tool, named Online consensus Survival analysis for Myxofibrosarcoma (OSmfs) to analyze the prognostic value of certain genes. Through retrieving the database, users generate a Kaplan-Meier plot with log-rank test and hazard ratio (HR) to assess prognostic-related genes or discover novel Myxofibrosarcoma prognostic biomarkers. The effectiveness and availability of OSmfs were validated using genes in ever reports predicting the prognosis of Myxofibrosarcoma patients. Furthermore, utilizing the cox analysis data and transcriptome data establishing OSmfs, seven genes were selected and considered as more potentially prognostic biomarkers through overlapping and ROC analysis. In conclusion, OSmfs is a promising web tool to evaluate the prognostic potency and reliability of genes in Myxofibrosarcoma, which may significantly contribute to the enrichment of novelly potential prognostic biomarkers and therapeutic targets for Myxofibrosarcoma.

OSluca: An Interactive Web Server to Evaluate Prognostic Biomarkers for Lung Cancer.

Lung cancer is the principal cause of leading cancer-related incidence and mortality in the world. Various studies have excavated the potential prognostic biomarkers for cancer patients based on gene expression profiles. However, most of these reported biomarkers lack independent validation in multiple cohorts. Herein, we collected 35 datasets with long-term follow-up clinical information from TCGA (2 cohorts), GEO (32 cohorts), and Roepman study (1 cohort), and developed a web server named OSluca (Online consensus Survival for Lung Cancer) to assess the prognostic value of genes in lung cancer. The input of OSluca is an official gene symbol, and the output web page of OSluca displays the survival analysis summary with a forest plot and a survival table from Cox proportional regression in each cohort and combined cohorts. To test the performance of OSluca, 104 previously reported prognostic biomarkers in lung carcinoma were evaluated in OSluca. In conclusion, OSluca is a highly valuable and interactive prognostic web server for lung cancer. It can be accessed at http:// bioinfo.henu.edu.cn/LUCA/LUCAList.jsp.

Autophagy-related gene P4HB: a novel diagnosis and prognosis marker for kidney renal clear cell carcinoma.

Autophagy can protect cells and organisms from stressors such as nutrient deprivation, and is involved in many pathological processes including human cancer. Therefore, it is necessary to investigate the role of autophagy-related genes (ARGs) in cancer. In this study, we investigated the gene expression of 222 ARGs in 1048 Kidney Renal Clear Cell Carcinoma (KIRC) cases, from 5 independent cohorts. The gene expression of ARGs were first evaluated in the The Cancer Genome Atlas (TCGA) by Recevier Operating Characteristic (ROC) analysis to select potential biomarkers with extremely high ability in KIRC detection (AUC≥0.85 and p<0.0001). Then in silico procedure progressively leads to the selection of two genes in a three rounds of validation performed in four human KIRC-patients datasets including two independent Gene Expression Omnibus (GEO) datasets, Oncomine dataset and Human Protein Atlas dataset. Finally, only P4HB (Prolyl 4-hydroxylase, beta polypeptide) gene was experimentally validated by RT-PCR between control kidney cells and cancer cells. Following univariate and multivariate analyses of TCGA-KIRC clinical data showed that P4HB expression is an independent prognostic indicator of unfavorable overall survival (OS) for KIRC patients. Based on these findings, we proposed that P4HB might be one potential novel KIRC diagnostic and prognostic biomarker at both mRNA and protein levels.

Systemic analysis of the expression and prognostic significance of PAKs in breast cancer.

PAKs (p21-activated kinases) are reported to play crucial roles in a variety of cellular processes and participate in the progression of human cancers. However, the expression and prognostic values of PAKs remain poorly explored in breast cancers. In our study, we examined the mRNA and protein expression levels of PAKs and the prognostic value. We also analyzed the interaction network, genetic alteration, and functional enrichment of PAKs. The results showed that the mRNA levels of PAK1, PAK2, PAK4 and PAK6 were significantly up-regulated in breast cancer compared with normal tissues, while the reverse trend for PAK3 and PAK5 was found, furthermore, the proteins expression of PAK1, PAK2 and PAK4 in breast cancer tissues were higher than that in normal breast tissues. Survival analysis revealed breast cancer patients with low mRNA expression of PAK3 and PAK5 showed worse RFS, conversely, elevated PAK4 levels predicted worse RFS. In addition, the breast cancer patients with PAKs genetic alterations correlated with worse OS. These results indicated that PAKs might be promising potential biomarkers for breast cancer.

OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma.

Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan-Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at http://bioinfo.henu.edu.cn/ACC/ACCList.jsp.

OSkirc: a web tool for identifying prognostic biomarkers in kidney renal clear cell carcinoma.

Aim: To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). Patients & methods: A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. Results: One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan-Meier survival plot with hazard ratio and log-rank p-value. Conclusion: OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at http://bioinfo.henu.edu.cn/KIRC/KIRCList.jsp.

OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients.

Bladder cancer (BC) is one of the most common malignant tumors in the urinary system. The discovery of prognostic biomarkers is still one of the major challenges to improve clinical treatment of BC patients. In order to assist biologists and clinicians in easily evaluating the prognostic potency of genes in BC patients, we developed a user-friendly Online consensus Survival tool for bladder cancer (OSblca), to analyze the prognostic value of genes. The OSblca includes gene expression profiles of 1,075 BC patients and their respective clinical follow-up information. The clinical follow-up data include overall survival (OS), disease specific survival (DSS), disease free interval (DFI), and progression free interval (PFI). To analyze the prognostic value of a gene, users only need to input the official gene symbol and then click the "Kaplan-Meier plot" button, and Kaplan-Meier curve with the hazard ratio, 95% confidence intervals and log-rank P-value are generated and graphically displayed on the website using default options. For advanced analysis, users could limit their analysis by confounding factors including data source, survival type, TNM stage, histological type, smoking history, gender, lymph invasion, and race, which are set up as optional parameters to meet the specific needs of different researchers. To test the performance of the web server, we have tested and validated its reliability using previously reported prognostic biomarkers, including KPNA2, TP53, and MYC etc., which had their prognostic values validated as reported in OSblca. In conclusion, OSblca is a useful tool to evaluate and discover novel prognostic biomarkers in BC. The web server can be accessed at http://bioinfo.henu.edu.cn/BLCA/BLCAList.jsp.

Gene Expression Profiling Reveals Distinct Molecular Subtypes of Esophageal Squamous Cell Carcinoma in Asian Populations.

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide, particularly in Asian populations, and responds poorly to conventional therapy. Subclassification of ESCCs by molecular analysis is a powerful strategy in extending conventional clinicopathologic classification, improving prognosis and therapy. Here we identified two ESCC molecular subtypes in Chinese population using gene expression profiling data and further validated the molecular subtypes in two other independent Asian populations (Japanese and Vietnamese). Subtype I ESCCs were enriched in pathways including immune response, while genes overexpressed in subtype II ESCCs were mainly involved in ectoderm development, glycolysis process, and cell proliferation. Specifically, we identified potential ESCC subtype-specific diagnostic markers (FOXA1 and EYA2 for subtype I, LAMC2 and KRT14 for subtype II) and further validated them in a fourth Asian cohort. In addition, we propose a few subtype-specific therapeutic targets for ESCC, which may guide future ESCC clinical treatment when further validated.

OSlms: A Web Server to Evaluate the Prognostic Value of Genes in Leiomyosarcoma.

The availability of transcriptome data and clinical annotation offers the opportunity to identify prognosis biomarkers in cancer. However, efficient online prognosis analysis tools are still lacking. Herein, we developed a user-friendly web server, namely Online consensus Survival analysis of leiomyosarcoma (OSlms), to centralize published gene expression data and clinical datasets of leiomyosarcoma (LMS) patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). OSlms comprises of a total of 268 samples from three independent datasets, and employs the Kaplan Meier survival plot with hazard ratio (HR) and log rank test to estimate the prognostic potency of genes of interests for LMS patients. Using OSlms, clinicians and basic researchers could determine the prognostic significance of genes of interests and get opportunities to identify novel potential important molecules for LMS. OSlms is free and publicly accessible at http://bioinfo.henu.edu.cn/LMS/LMSList.jsp.

High KRT8 Expression Independently Predicts Poor Prognosis for Lung Adenocarcinoma Patients.

Keratin 8 (KRT8), a type II basic intermediate filament (IF) protein, is essential for the development and metastasis of various cancers. In this study, by analyzing RNA-seq data from the Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), we have determined the expression profile of KRT8, and assessed its prognostic significance and the possible mechanism underlying the dysregulation. Our results showed that KRT8 mRNA expression was significantly up-regulated in both LUAD and LUSC tissues compared with normal lung tissues. The high KRT8 expression group for LUAD patients significantly reduced overall survival (OS) and recurrence-free survival (RFS). Univariate and multivariate analysis revealed that KRT8 expression was an independent prognostic indicator for poor OS and RFS in LUAD patients. However, KRT8 expression had no prognostic value in terms of OS and RFS for LUSC. By exploring DNA copy number alterations (CNAs) of the KRT8 gene in LUAD, we found that DNA low copy gain (+1 and +2) was associated with elevated KRT8 mRNA expression. From the above findings, we have deduced that KRT8 is aberrantly expressed in LUAD tissues and that its expression might independently predict poor OS and RFS for LUAD patients, but not for LUSC patients.

OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts.

Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan-Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp.