Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Application and Progress of Texture Analysis in the Therapeutic Effect Prediction and Prognosis of Neoadjuvant Chemoradiotherapy for Colorectal Cancer

Colorectal cancer is one of the most common malignant tumors, and the morbidity and mortality are increasing gradually over the last years in China. Neoadjuvant chemoradiotherapy(nCRT) is currently applied to the treatment of colorectal cancer patients, and it is helpful to improve the prognosis. The sensitivity of patients to nCRT is different due to individual differences. Predicting the therapeutic effect of nCRT is of great importance for the further treatment methods. Texture analysis, as an image post-processing technique, has been more and more utilized in the field of oncologic imaging. This article reviews the application and progress of texture analysis in the therapeutic effect prediction and prognosis of nCRT for colorectal cancer.

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients

AIM To identify multiple micro RNAs(mi RNAs) for predicting the prognosis of gastric cancer(GC) patients by bioinformatics analysis.METHODS The original microarray dataset GSE93415,which included 20 GC and 20 tumor adjacent normal gastric mucosal tissues,was downloaded from the Gene Expression Omnibus database and used for screening differentially expressed mi RNAs(DEMs).The cutoff criteria were P < 0.05 and fold change > 2.0.In addition,we acquired the mi RNA expression profiles and clinical information of 361 GC patients from The Cancer Genome Atlas database to assess the prognostic role of the DEMs.The target genes of mi RNAs were predicted using Target Scan,mi RDB,mi RWalk,and DIANA,and then the common target genes were selected for functional enrichment analysis.RESULTS A total of 110 DEMs including 19 up-regulated and 91 down-regulated mi RNAs were identified between 20 pairs of GC and tumor adjacent normal tissues,and the Kaplan-Meier survival analysis found that a threemi RNA signature(mi R-145-3 p,mi R-125 b-5 p,and mi R-99 a-5 p) had an obvious correlation with the survival of GC patients.Furthermore,univariate and multivariate Cox regression analyses indicated that the three-mi RNA signature could be a significant prognostic marker in GC patients.The common target genes of the three mi RNAs are added up to 108 and used for Gene Functional Enrichment analysis.Biological Process and Molecular Function analyses showed that the target genes are involved in cell recognition,gene silencing and nucleic acid binding,transcription factor activity,and transmembrane receptor activity.Cellular Component analysis revealed that the genes are portion of nucleus,chromatin silencing complex,and TORC1/2 complex.Biological Pathway analysis indicated that the genes participate in several cancer-related pathways,such as the focal adhesion,PI3 K,and m TOR signaling pathways.CONCLUSION This study justified that a three-mi RNA signature could play a role in predicting the survival of GC patients.

Bioinformatics Analysis and Identification of Potential Genes Associated with Pathogenesis and Prognosis of Gastric Cancer

Objective Gastric cancer(GC)is a deadly cancer and a challenging public health problem globally.This study aimed to analyze potential genes associated with pathogenesis and prognosis of gastric cancer.Methods This work selected the overlapping differentially expressed genes(DEGs)in GC from four datasets,the GSE29272,GSE29998,GSE54129 and GSE118916 Gene Expression Omnibus databases.These DEGs were used to carry out comprehensive bioinformatic analysis to analyze the related functions and pathways enriched,the relative expression levels and immune infiltrates,the prognostic characteristics and the interaction network.Results In total,55 DEGs increased while 98 decreased in their expression levels.For those DEGs with increased expression,they were mostly concentrated on“focal adhesion”and“ECM-receptor interaction”,whereas DEGs with decreased expression were mostly associated with“gastric acid secretion”and“drug metabolism cytochrome P450”.MCODE and ClueGO results were then integrated to screen 10 hub genes,which were FN1,COL1A1,COL3A1,BGN,TIMP1,COL1A2,LUM,VCAN,COL5A2 and SPP1.Survival analysis revealed that higher expression of the ten hub genes significantly predicted lower overall survival of GC patients.TIMP1 was most significantly related to neutrophils,CD8+T cells,as well as dendritic cells,while LUM was most significantly related to macrophages.Conclusion Immunohistochemistry results and functional testing showed that the expression of COL5A2 was elevated in GC and that it might be a key gene in GC tumorigenesis.

Feature Extraction Technique for Fault Prognosis Based on Fault Trend Analysis

Fault prognosis is one of the key techniques for prognosis and health management,and an effective fault feature can improve prediction accuracy and performance. A novel approach of feature extraction for fault prognosis based on fault trend analysis was proposed in this paper. In order to describe the ability of tracking fault growth process,definitions and calculations of fault trackability was developed, and the feature which had the maximum fault trackability was selected for fault prognosis. The vibration data in bearing life tests were used to verify the effectiveness of the method was proposed. The results showed that the trackability of energy entropy for bearing fault growth was the maximum,and it was the best fault feature among selected features root mean square( RMS),kurtosis,new moment and energy entropy. The proposed approach can provide a better strategy for fault feature extraction of bearings in order to improve prediction accuracy.

Multivariate time delay analysis based local KPCA fault prognosis approach for nonlinear processes

Currently, some fault prognosis technology occasionally has relatively unsatisfied performance especially for in- cipient faults in nonlinear processes duo to their large time delay and complex internal connection. To overcome this deficiency, multivariate time delay analysis is incorporated into the high sensitive local kernel principal component analysis. In this approach, mutual information estimation and Bayesian information criterion （BIC） are separately used to acquire the correlation degree and time delay of the process variables. Moreover, in order to achieve prediction, time series prediction by back propagation （BP） network is applied whose input is multivar- iate correlated time series other than the original time series. Then the multivariate time delayed series and future values obtained by time series prediction are combined to construct the input of local kernel principal component analysis （LKPCA） model for incipient fault prognosis. The new method has been exemplified in a sim- ple nonlinear process and the complicated Tennessee Eastman （TE） benchmark process. The results indicate that the new method has suoerioritv in the fault prognosis sensitivity over other traditional fault prognosis methods.

FDG-PET in diagnosis, staging and prognosis of pancreatic carcinoma: A meta-analysis

AIM: To investigate the potential role of positron emission tomography (PET) in the diagnosis, staging and prognosis predicting of pancreatic carcinoma (PC). METHODS: A systematic review of relevant literatures in PubMed, Embase and Cochrane Library was performed. The sensitivity and specificity of diagnostic and staging studies, and HRs for prognosis predicting studies were pooled. The bivariate model was used for diagnostic studies and the random-effect model for prognostic studies. Heterogeneity between included studies was tested using χ 2 test, and subgroup analysis was performed to explain the heterogeneities. All of the calculations were performed using Stata version 11.0.RESULTS: A total of 39 studies were included. The pooled sensitivity of PET in diagnosing PC (30 studies, 1582 patients), evaluating N stating (4 studies, 101 patients) and liver metastasis (7 studies, 316 patients) were 0.91 (95%CI: 0.88-0.93), 0.64 (95%CI: 0.50-0.76), and 0.67 (95%CI: 0.52-0.79), respectively; and the corresponding specificity was 0.81 (95%CI: 0.75-0.85), 0.81 (95%CI: 0.25-0.85), and 0.96 (95%CI: 0.89-0.98), respectively. In prognosis analysis (6 studies, 198 patients), significant difference of overall survival was observed between high and low standardized uptake value groups (HR = 2.39, 95%CI: 1.57-3.63). Subgroup analysis showed that PET/CT was more sensitive than PET alone in evaluating liver metastasis of PC, 0.82 (95%CI: 0.48-0.98) and 0.67 (95%CI: 0.52-0.79), respectively. CONCLUSION: PET can be used as a valuable diagnostic and predictive tool for PC, but its effect in the staging of PC remains indeterminate.

Analysis of Prognosis of 122 Colorectal Cancer Patients with Concurrent Liver Metastasis

OBJECTIVE To explore prognostic factors and treatmentchoices for colorectal cancer (CRC) patients with concurrent livermetastases (CLM).METHODS The data of the 122 CRC patients with CLM, whowere treated in our hospital from January 2000 to December 2005,were collected. Overall survival rate of the patients in our groupwas analyzed using Kaplan-Meier method, and the univariateand multivariate analyses of the 18 factors affecting the survivalrate, including clinicopathologic factors and treatment methods,were conducted using Log-rank test and Cox regression model(SPSS13.0).RESULTS The median survival time of the 122 patients withCRC was 13 months. The 1, 2, 3 and 5-year survival rate was52.46%, 24.59%, 12.30% and 3.28%, respectively. Univariateanalysis combined with Kaplan-Meier curve revealed that thefactors of prognosis included the size of the primary tumor, thelevels of differentiation, lymphatic status, cancerous ileus (CI),the number, size and distribution of liver metastases, extrahepaticinvolvement, the serum CEA level at diagnosis, treatmentmodality, the extent of primary resection, chemotherapeuticmodality and regimen. Multivariate analysis showed that CI,differentiation levels, serum CEA value at diagnosis and treatmentmodality were the independent prognostic factors of CRC patientswith CLM.CONCLUSION For the CRC patients with CLM, poordifferentiation of the tumor and CI, as well as a high CEAlevel indicate an unfavorable prognosis. Treatment choice is ofspecial significance in treating the CRC patients with CLM, soactive radical excision of the primary tumor and liver metastasisis strongly recommended in the CRC patients with hepaticmetastasis alone. Interventional chemotherapy has advantagescompared with the whole-body chemotherapy via peripheral vein,and the regimen of systemic chemotherapy containing oxaliplatinis preferred.

Efficacy and prognosis of vacuum-assisted excision for benign intraductal papilloma of breast:A meta-analysis

Objective:To evaluate the safety and effectiveness of vacuum-assisted excision for benign intraductal papilloma of breast.Methods:The databases including PubMed,Embase,Cochrane Library,WangFang,CNIK,VIP and Web of Science were searched by computer,according the inclusion and exclusion criteria after screening of literature.The Cochrane handbook and Newcastle-Ottawa scale was used to evaluate the studies.Then the Review Manager 5.3 software was to used analyze the data.Results:A total of 1016 patients was included in 9 articles.The amount of blood loss in vacuum-assisted surgery was less than that in open surgery[MD=-6.38,95%CI(-9.90,-2.86),P<0.05].The drainage[MD=-2.56,95%CI(-4.97,-0.15,P<0.05]and drainage time[MD=-0.25,95%CI(-0.40,-0.09),P<0.05]in vacuum-assisted surgery was less than that in open surgery.There were also few postoperative complications than that in open surgery[RR=0.43,95%CI(0.29,0.64),P<0.05].Compared with open surgery,the postoperative recurrence rate was lower in vacuum-assisted surgery[RR=0.26,95%CI(0.14,0.49),P<0.05].Last,there was no statistically significant difference in the operative time between vacuum-assisted surgery and open surgery,[SD=-12.82,95%CI(-25.70,0.06),P=0.05].Conclusion:Compared with open surgery,vacuum-assisted excision has the advantages of less blood loss and lower postoperative complications,but the operative time is not statistically significant compared with open surgery.In addition,compared with open surgery in this study,vacuum-assisted excision has the advantages of lower recurrence rate,but it still needs long-term dynamic observation.

Meta-analysis:The relationship of expression level of long non-coding RNA GAS5 and prognosis in cancers

lncRNA GAS5(growth of arrest-speeific transeript 5)controls the occurrence,development and prognoses of cancer cells.In order to explore the association bet ween dy sregulated expression of GAS5 and patient prognosis,we performed a meta-analysis.Data were extracted from the Databases,including PubMed,Web of Science,EMBASE,Cochrane Library,and CNBL.English literatures were cllcted on the correlation between lncRNA GAS5 expression and cancer prognostic.The retrieval time was from inception to February 2021.The meta-analysis was performed with Stata Statistical Software version 12.0.According to the inclusion and exclusion criteria,a total of 917 patients from 11 studies were included in this meta-analysis.

Bioinformatics analysis of key genes associated with the prognosis of breast cancer

Objective:We sought to identify potential therapeutic targets for breast cancer patients by employing a bioinformatics analysis to screen for genes linked with an unfavorable prognosis.Methods:The Gene Expression Omnibus(GEO)database was utilized to obtain three gene expression profile datasets,namely GSE42568,GSE86374,and GSE71053.To identify differentially expressed genes(DEGs),the GEO2R online tool was employed.Subsequently,a func-tional enrichment analysis was conducted.Moreover,a protein-protein interaction network was established using STRING,and DEGs were subjected to module analysis via Cytoscape software to identify pivotal genes.Additionally,the selected pivotal genes underwent further ex-amination and validation utilizing three databases:GEPIA,UALCAN,and Kaplan-Meier Plotter.Results:A total of 121 DEGs were detected,comprising 74 genes with increased expression and 47 genes with decreased expression.Ten key genes were identified:HMMR,RRM2,CDK1,TOP2A,AURKA,CCNB1,MAD2L1,KIF2C,BUB1B,UBE2C.Validation in the GEPIA database revealed high expression levels for all key genes except CDK1.A survival analysis conducted using the Kaplan-Meier Plotter database revealed noteworthy associations between nine crucial genes and the overall survival(OS)of individuals diagnosed with breast cancer.Moreover,these nine key genes exhibited significantly increased expression across different molecular subtypes of breast cancer according to the UALCAN data platform.Conclusions:We identified nine crucial genes significantly linked to the onset,progression,and unfavorable prognosis of breast cancer,providing potential targets for novel treatment options and biomarkers to predict patient outcomes.

Analysis of correlation between MSCT classification and prognosis of basal ganglia hypertensive intracerebral hemorrhage

Objective:To investigate the correlation between MSCT grading and the prognosis of basal ganglia hypertensive intracerebral hemorrhage.Methods:A total of 86 patients with basal ganglia hypertensive cerebral hemorrhage admitted to our hospital from May 2017 to March 2018 were selected.The clinical data and imaging data were collected from 86 patients.The MSCT images were observed and summarized by two radiologists.Based on the morphology of cisterna ambiens and brain stem,the correlation of MSCT grading to Glasgow Coma Scale(GCS)and Glasgow Outcome Scale(GOS)grading was analyzed by use of Spearman correlation analysis.Results:Among 86 patients,the number of MSCT gradeⅠ,Ⅱ,ⅢandⅣwere 29 cases,38 cases,9 cases and 10 cases respectively.There was no significant correlation between MSCT grading and age,sex as well as types of combined underlying diseases in the patients with basal ganglia hypertensive intracerebral hemorrhage(p>0.05).Spearman correlation analysis showed that there was a positive correlation between MSCT grading and GCS score of basal ganglia hypertensive intracerebral hemorrhage.The higher MSCT grade was,the higher GCS score was(r=0.719,p<0.001).There was a positive correlation between MSCT grading and GOS grading of basal ganglia hypertensive intracerebral hemorrhage.The higher MSCT grade was,the higher GOS grade was,leading to a poor prognosis(r=0.734,p<0.001).86 cases of basal ganglia hypertensive intracerebral hemorrhage showed round or quasi-circular high-density shadows in MSCT images,the CT value ranged from 50 Hu to 80 Hu.Low-density bands surrounded the hematoma in the acute stage,and space-occupying effect could be seen in some patients,which resulted in the compression of ventricular sulcus and cistern and the displacement of midline structure.Subacute basal ganglia hypertensive intracerebral hemorrhage patients showed a relative decrease in the density of hematoma,with the extent of edema gradually reduced,the focus showed a high-density shadow in the center;chronic basal ganglia hypertensive intracerebral hemorrhage focus showed a cystic low-density shadow.Conclusion:MSCT grading of basal ganglia hypertensive intracerebral hemorrhage is positively correlated to GCS and GOS grading.MSCT grading can contribute to the prognostic evaluation to the patients.

Developing global image feature analysis models to predict cancer risk and prognosis

In order to develop precision or personalized medicine,identifying new quantitative imaging markers and building machine learning models to predict cancer risk and prognosis has been attracting broad research interest recently.Most of these research approaches use the similar concepts of the conventional computer-aided detection schemes of medical images,which include steps in detecting and segmenting suspicious regions or tumors,followed by training machine learning models based on the fusion of multiple image features computed from the segmented regions or tumors.However,due to the heterogeneity and boundary fuzziness of the suspicious regions or tumors,segmenting subtle regions is often difficult and unreliable.Additionally,ignoring global and/or background parenchymal tissue characteristics may also be a limitation of the conventional approaches.In our recent studies,we investigated the feasibility of developing new computer-aided schemes implemented with the machine learning models that are trained by global image features to predict cancer risk and prognosis.We trained and tested several models using images obtained from full-field digital mammography,magnetic resonance imaging,and computed tomography of breast,lung,and ovarian cancers.Study results showed that many of these new models yielded higher performance than other approaches used in current clinical practice.Furthermore,the computed global image features also contain complementary information from the features computed from the segmented regions or tumors in predicting cancer prognosis.Therefore,the global image features can be used alone to develop new case-based prediction models or can be added to current tumor-based models to increase their discriminatory power.

Telomerase-related advances in hepatocellular carcinoma:A bibliometric and visual analysis

BACKGROUND As a critical early event in hepatocellular carcinogenesis,telomerase activation might be a promising and critical biomarker for hepatocellular carcinoma(HCC)patients,and its function in the genesis and treatment of HCC has gained much attention over the past two decades.AIM To perform a bibliometric analysis to systematically assess the current state of research on HCC-related telomerase.METHODS The Web of Science Core Collection and PubMed were systematically searched to retrieve publications pertaining to HCC/telomerase limited to“articles”and“reviews”published in English.A total of 873 relevant publications related to HCC and telomerase were identified.We employed the Bibliometrix package in R to extract and analyze the fundamental information of the publications,such as the trends in the publications,citation counts,most prolific or influential writers,and most popular journals;to screen for keywords occurring at high frequency;and to draw collaboration and cluster analysis charts on the basis of coauthorship and co-occurrences.VOSviewer was utilized to compile and visualize the bibliometric data.RESULTS A surge of 51 publications on HCC/telomerase research occurred in 2016,the most productive year from 1996 to 2023,accompanied by the peak citation count recorded in 2016.Up to December 2023,35226 citations were made to all publications,an average of 46.6 citations to each paper.The United States received the most citations(n=13531),followed by China(n=7427)and Japan(n=5754).In terms of national cooperation,China presented the highest centrality,its strongest bonds being to the United States and Japan.Among the 20 academic institutions with the most publications,ten came from China and the rest of Asia,though the University of Paris Cité,Public Assistance-Hospitals of Paris,and the National Institute of Health and Medical Research(INSERM)were the most prolific.As for individual contributions,Hisatomi H,Kaneko S,and Ide T were the three most prolific authors.Kaneko S ranked first by H-index,G-index,and overall publication count,while Zucman-Rossi J ranked first in citation count.The five most popular journals were the World Journal of Gastroenterology,Hepatology,Journal of Hepatology,Oncotarget,and Oncogene,while Nature Genetics,Hepatology,and Nature Reviews Disease Primers had the most citations.We extracted 2293 keywords from the publications,120 of which appeared more than ten times.The most frequent were HCC,telomerase and human telomerase reverse transcriptase(hTERT).Keywords such as mutational landscape,TERT promoter mutations,landscape,risk,and prognosis were among the most common issues in this field in the last three years and may be topics for research in the coming years.CONCLUSION Our bibliometric analysis provides a comprehensive overview of HCC/telomerase research and insights into promising upcoming research.

Nomogram predicting the prognosis of primary liver cancer after radiofrequency ablation combined with transcatheter arterial chemoembolization

BACKGROUND The incidence and mortality rates of primary hepatocellular carcinoma(HCC)are high,and the conventional treatment is radiofrequency ablation(RFA)with transcatheter arterial chemoembolization(TACE);however,the 3-year survival rate is still low.Further,there are no visual methods to effectively predict their prognosis.AIM To explore the factors influencing the prognosis of HCC after RFA and TACE and develop a nomogram prediction model.METHODS Clinical and follow-up information of 150 patients with HCC treated using RFA and TACE in the Hangzhou Linping Hospital of Traditional Chinese Medicine from May 2020 to December 2022 was retrospectively collected and recorded.We examined their prognostic factors using multivariate logistic regression and created a nomogram prognosis prediction model using the R software(version 4.1.2).Internal verification was performed using the bootstrapping technique.The prognostic efficacy of the nomogram prediction model was evaluated using the concordance index(CI),calibration curve,and receiver operating characteristic RESULTS Of the 150 patients treated with RFA and TACE,92(61.33%)developed recurrence and metastasis.Logistic regression analysis identified six variables,and a predictive model was created.The internal validation results of the model showed a CI of 0.882.The correction curve trend of the prognosis prediction model was always near the diagonal,and the mean absolute error before and after internal validation was 0.021.The area under the curve of the prediction model after internal verification was 0.882[95%confidence interval(95%CI):0.820-0.945],with a specificity of 0.828 and sensitivity of 0.656.According to the Hosmer-Lemeshow test,χ^(2)=3.552 and P=0.895.The predictive model demonstrated a satisfactory calibration,and the decision curve analysis demonstrated its clinical applicability.CONCLUSION The prognosis of patients with HCC after RFA and TACE is affected by several factors.The developed prediction model based on the influencing parameters shows a good prognosis predictive efficacy.

Multi-factor analysis of initial poor graft function after orthotopic liver transplantation

BACKGROUND: In the early period of orthotopic liver transplantation (OLT), initial poor graft function (IPGF) is one of the complications which leads to primary graft non-function (PGNF) in serious cases. This study set out to establish the clinical risk factors resulting in IPGF after OLT. METHODS: Eighty cases of OLT were analyzed. The IPGF group consisted of patients with alanine aminotransferase (ALT) and/or aspartate aminotransferase (AST) above 1500 IU/L within 72 hours after OLT, while those in the non-IPGF group had values below 1500 IU/L. Recipient-associated factors before OLT analyzed were age, sex, primary liver disease and Child-Pugh classification; factors analyzed within the peri-operative period were non-heart beating time (NHBT), cold ischemia time (CIT), rewarming ischemic time (RWIT), liver biopsy at the end of cold ischemia; and factors analyzed within 72 hours after OLT were ALT and/or AST values. A logistic regression model was applied to filter the possible factors resulting in IPGF. RESULTS: Donor NHBT, CIT and RWIT were significantly longer in the IPGF group than in the non-IPGF group; in the logistic regression model, NHBT was the risk factor leading to IPGF (P < 0.05), while CIT and RWIT were possible risk factors. In one case in the IPGF group, PGNF appeared with moderate hepatic steatosis. CONCLUSIONS: Longer NHBT is an important risk factor leading to IPGF, while serious steatosis in the donor liver, CIT and RWIT are potential risk factors.

Hypoxia-related bioinformatic signatures associated with prognosis and tumor microenvironment of pancreatic cancer:Current status,concerns,and future perspectives

Pancreatic cancer(PC),a highly lethal tumor with nearly identical incidence and mortality rates,has become the sixth leading cause of cancer-related deaths.Hypoxia is an important malignant factor in PC,as it regulates angiogenesis,metabolic reprogramming,tumor progression,and metastasis.Disrupting the hypoxic microenvironment can enhance the efficacy of antitumor therapy and improve the prognosis of patients with PC.With the advent of bioinformatics,hypoxia-related PC models have emerged in recent years.They provide a reference for estimating the prognosis and immune microenvironment of patients with PC and identify potential biomarkers for targeting hypoxic microenvironment.However,these findings based on bioinformatic analysis may not be completely reliable without further experimental evidence and clinical cohort validation.The application of these models and biomarkers in clinical practice to predict survival time and develop anti hypoxic therapeutic strategies for patients with PC remains in its infancy.In this editorial,we review the current status of hypoxia-related prognostic models in PC,analyze their similarities and differences,discuss several existing challenges,and provide potential solutions and directions for further studies.This editorial will facilitate the optimization,validation,and determination of the molecular mechanisms of related models.

Clinical and molecular significance of homologous recombination deficiency positive non-small cell lung cancer in Chinese population:An integrated genomic and transcriptional analysis

Objective:The clinical significance of homologous recombination deficiency(HRD)in breast cancer,ovarian cancer,and prostate cancer has been established,but the value of HRD in non-small cell lung cancer(NSCLC)has not been fully investigated.This study aimed to systematically analyze the HRD status of untreated NSCLC and its relationship with patient prognosis to further guide clinical care.Methods:A total of 355 treatment-naïve NSCLC patients were retrospectively enrolled.HRD status was assessed using the AmoyDx Genomic Scar Score(GSS),with a score of≥50 considered HRD-positive.Genomic,transcriptomic,tumor microenvironmental characteristics and prognosis between HRD-positive and HRDnegative patients were analyzed.Results:Of the patients,25.1%(89/355)were HRD-positive.Compared to HRD-negative patients,HRDpositive patients had more somatic pathogenic homologous recombination repair(HRR)mutations,higher tumor mutation burden(TMB)(P<0.001),and fewer driver gene mutations(P<0.001).Furthermore,HRD-positive NSCLC had more amplifications in PI3K pathway and cell cycle genes,MET and MYC in epidermal growth factor receptor(EGFR)/anaplastic lymphoma kinase(ALK)mutant NSCLC,and more PIK3CA and AURKA in EGFR/ALK wild-type NSCLC.HRD-positive NSCLC displayed higher tumor proliferation and immunosuppression activity.HRD-negative NSCLC showed activated signatures of major histocompatibility complex(MHC)-II,interferon(IFN)-γand effector memory CD8+T cells.HRD-positive patients had a worse prognosis and shorter progressionfree survival(PFS)to targeted therapy(first-and third-generation EGFR-TKIs)(P=0.042).Additionally,HRDpositive,EGFR/ALK wild-type patients showed a numerically lower response to platinum-free immunotherapy regimens.Conclusions:Unique genomic and transcriptional characteristics were found in HRD-positive NSCLC.Poor prognosis and poor response to EGFR-TKIs and immunotherapy were observed in HRD-positive NSCLC.This study highlights potential actionable alterations in HRD-positive NSCLC,suggesting possible combinational therapeutic strategies for these patients.

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Based on Multi-Factor Analysis and a Multi-Model Ensemble

Dissolved oxygen(DO)is an important indicator of aquaculture,and its accurate forecasting can effectively improve the quality of aquatic products.In this paper,a new DO hybrid forecasting model is proposed that includes three stages:multi-factor analysis,adaptive decomposition,and an optimizationbased ensemble.First,considering the complex factors affecting DO,the grey relational(GR)degree method is used to screen out the environmental factors most closely related to DO.The consideration of multiple factors makes model fusion more effective.Second,the series of DO,water temperature,salinity,and oxygen saturation are decomposed adaptively into sub-series by means of the empirical wavelet transform(EWT)method.Then,five benchmark models are utilized to forecast the sub-series of EWT decomposition.The ensemble weights of these five sub-forecasting models are calculated by particle swarm optimization and gravitational search algorithm(PSOGSA).Finally,a multi-factor ensemble model for DO is obtained by weighted allocation.The performance of the proposed model is verified by timeseries data collected by the pacific islands ocean observing system(PacIOOS)from the WQB04 station at Hilo.The evaluation indicators involved in the experiment include the Nash–Sutcliffe efficiency(NSE),Kling–Gupta efficiency(KGE),mean absolute percent error(MAPE),standard deviation of error(SDE),and coefficient of determination(R^(2)).Example analysis demonstrates that:①The proposed model can obtain excellent DO forecasting results;②the proposed model is superior to other comparison models;and③the forecasting model can be used to analyze the trend of DO and enable managers to make better management decisions.

Retrospective analysis of patients with hepatocellular carcinoma complicated with human immunodeficiency virus infection after hepatectomy

BACKGROUND Hepatocellular carcinoma(HCC)is the third leading cause of cancer death worldwide,with a 5-year relative survival rate of approximately 18%.The similarity between incidence and mortality(830000 deaths per year)underscores the bleak prognosis associated with the disease.HCC is the fourth most common malignancy and the second leading cause of cancer death in China.Most patients with HCC have a history of chronic liver disease such as chronic hepatitis B virus(HBV)or hepatitis C virus(HCV)infection,alcoholism or alcoholic steatohepatitis,nonalcoholic fatty liver disease,or nonalcoholic steatohepatitis.Early diagnosis and effective treatment are the keys to improving the prognosis of patients with HCC.Although the total number of human immunodeficiency virus(HIV)-infected patients is declining globally the incidence of HCC is increasing in HIVinfected patients,especially those who are coinfected with HBV or HCV.As a result,people infected with HIV still face unique challenges in terms of their risk of developing HCC.AIM To investigate the survival prognosis and clinical efficacy of surgical resection in patients with HCC complicated with HIV infection.METHODS The clinical data of 56 patients with HCC complicated with HIV admitted to the Third Affiliated Hospital of Nantong University from January 2013 to December 2023 were retrospectively analyzed.Among these,27 patients underwent hepatectomy(operation group)and 29 patients received conservative treatment(nonoperation group).All patients signed informed consents in line with the provisions of medical ethics.The general data,clinicopathological features and prognoses for the patients in the two groups were analyzed and the risk factors related to the prognoses of the patients in the operation group were identified.RESULTS The median disease-free survival(DFS)and overall survival(OS)of HIV-HCC patients in the surgical group were 13 months and 17 months,respectively,and the median OS of patients in the nonsurgical group was 12 months.The OS of the surgical group was significantly longer than that of the control group(17 months vs 12 months,respectively;P<0.05).The risk factors associated with DFS and OS in the surgical group were initial HIV diagnosis,postoperative microvascular invasion(MVI),a CD4+T-cell count<200/μL,Barcelona stage C-D,and men who have sex with men(MSM;P<0.05).CONCLUSION Hepatectomy can effectively prolong the survival of patients with HIV-HCC but MVI identified during postoperative pathological examination,late tumor detection,late BCLC stage,CD4+T<200/μL and MSM are risk factors affecting the survival and prognosis of patients undergoing hepatectomy.In addition,there were significant differences between the surgical group and the nonsurgical group in terms of the initial diagnosis of HIV,Child-Pugh score,alpha-fetoprotein measurement value,and HART-efficient antiretroviral therapy after the diagnosis of HIV(P<0.05).Therefore,these factors may also affect the survival and prognosis of patients.