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The Global Cancer Statistics Report in 2022:A Narrow Spectrum Summary and Outlook

Xiaoyu LI ; Qing HUANG ; Yumeng WU ; Sheng HU

Cancer Research on Prevention and Treatment.2024;51(5):307-312. doi:10.3971/j.issn.1000-8578.2024.24.0437

According to the global cancer statistics in 2022 updated by the International Agency for Research on Cancer(IARC),there were nearly 20 million new cases of cancer and 9.7 million deaths.Lung cancer was the most commonly diagnosed cancer,accounting for nearly 2.5 million new cases(12.4%of all global cancers),followed by female breast cancer(11.6%),colorectal cancer(9.6%),prostate cancer(7.3%),and stomach cancer(4.9%).Lung cancer was also the leading cause of cancer deaths,with an estimated 1.8 million deaths(18.7%),followed by colorectal cancer(9.3%),liver cancer(7.8%),female breast cancer(6.9%),and stomach cancer(6.8%).Population-based projections suggest that the number of new cancer cases will reach 35 million by 2050.Increasing the investment in prevention and control measures targeting key cancer risk factors,including smoking,obesity,and infections,could save many lives globally and bring significant economic and social returns to countries in the coming decades.

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Global Landscape of Clinical Trials in Lung Cancer

Yale JIANG ; Yan WANG

Cancer Research on Prevention and Treatment.2024;51(5):313-320. doi:10.3971/j.issn.1000-8578.2024.24.0022

Lung cancer,the second most prevalent cancer in the world with a persistently high mortality rate,threatens the life and health of all humanity.With the development of clinical trials,the treatment options for lung cancer have been enriched,and the understanding of the timing of intervention has become more explicit than before.Thus,the prognosis of lung cancer has significantly improved.However,unmet clinical needs still exist.This review provides the global trend of clinical research in lung cancer treatment and describes the evolution of clinical trials in terms of design,implementation,and regulation.The change in study endpoints is conducive to shortening the research and development cycle and accelerating the launch of drugs.The refinement of study populations and therapeutic targets facilitates the realization of the maximum efficacy of precision treatment.The integration of comprehensive and diversified therapeutic strategies and the combination of prevention and treatment further promote the improvement of survival and the alleviation of social burden.This review also proposes a prospective direction for future development of clinical research in lung cancer.

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Conceptual Framework of A Next-generation General-purpose Clinical Scientific Disease Database

Min PENG ; Qianru CHEN ; Kai CHEN

Cancer Research on Prevention and Treatment.2024;51(5):321-327. doi:10.3971/j.issn.1000-8578.2024.23.1224

Empowered by the rapid development of artificial intelligence technology and information security technology,basic medicine,translational medicine,and clinical medicine have entered a new era.In this process,the relevant data such as text,genetics,images,and videos have increased at an astonishing rate.Traditional specialized disease databases cannot adapt to the multimodality of data and the multicentralization of data sources in the present/future.Therefore,establishing a next-generation multimodal and multicenter collaborative specialized disease database that is suitable for secure data sharing and ethical in clinical research is essential.This paper expounds the concept and basic framework of developing a next-generation clinical research disease database with universal use,emphasizing the establi-shment of a multimodal data integration mechanism,a multicenter collaborative system supported by privacy-preserving computing,highly intelligent software and hardware entities,and an integrated operational management mode.It also introduces the application of this conce-pt in the construction of a breast cancer three-dimensional life database,a proje-ct of China Breast Cancer Innovation Alliance.

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Transcription Factor ETS1 Promotes Glioma Cell Growth by Activating LncRNA XIST

Ran LUO ; Wenyi LUO ; Mingkai LU ; Meng ZHOU ; Yanting LIU ; Chunlei TIAN

Cancer Research on Prevention and Treatment.2024;51(5):328-335. doi:10.3971/j.issn.1000-8578.2024.23.1055

Objective To explore the biological function and downstream mechanism of ETS1 in glioma.Methods Bioinformatics and immunohistochemistry were used to analyze the differential expression characteristics of ETS1 in gliomas;qRT-PCR was employed to detect the expression level of ETS1 mRNA and lncRNA X-inactive specific transcript(XIST).CCK-8 and 5-ethyl-2′-deoxyuridine experiments were conducted to detect cell growth.Western blot was used to detect the expression of apoptosis-related proteins(Bax,Bak,Bcl-2).PROMO database was utilized to predict the binding sites between ETS1 and XIST promoter.Dual-luciferase reporter gene assay and chromatin immunoprecipitation-quantitative polymerase chain reaction assays were performed to verify the binding relationship between ETS1 and the XIST promoter region.cBioPortal database was used to analyze the correlation between the expression of ETS1 mRNA and XIST in glioma tissues.Results The expression levels of ETS1 mRNA and protein were significantly upregulated in glioma(P<0.05).The depletion of ETS1 significantly inhibited the proliferation of glioma cells and promoted cell apoptosis(P<0.05).ETS1 could target and bind with the XIST promoter and promote the expression of XIST(P<0.05).The overexpression of XIST reversed the effects of ETS1 on the proliferation of glioma cells and the promotion of cell apoptosis(P<0.05).Conclusion ETS1 is highly expressed in glioma tissues.It could promote the expression of lncRNA XIST,boost the proliferation of glioma cells,and inhibit cell apoptosis.

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Network Meta-Analysis of Effectiveness of First-Line Immunotherapy Treatments for Patients with Brain Metastases from Advanced Non-Small Cell Lung Cancer

Muyuan JIA ; Hongjun ZHANG ; Lin LI ; Jianhui WU ; Huanhuan GONG ; Bowen REN ; Han LIU

Cancer Research on Prevention and Treatment.2024;51(5):336-341. doi:10.3971/j.issn.1000-8578.2024.23.1212

Objective To conduct a network meta-analysis on the effectiveness of first-line immunotherapy on patients with brain metastases from advanced non-small cell lung cancer(NSCLC).Methods Two investigators conducted a computerized search of Pubmed,Embase,Cochrane,and other databases to screen the literature,extract the information,and assess the risk of bias of the included studies.The included clinical trials were statistically analyzed using R(4.1.3)software.For the study outcome indicators OS and PFS,the risk ratios(HRs),and the 95%confidence intervals(CIs)were extracted from the included studies and logarithmically transformed into effect analysis statistics.Results Six randomized controlled trials were finally included,including 327 patients with non-excludable NSCLC brain metastases.Network meta-analysis suggested that PD-1 inhibitor+CTLA-4 was more advantageous than the conventional chemotherapy for enhancing patients'OS(HR:0.13,95%CI:0.03-0.71),followed by PD-L1 inhibitor(HR:0.17,95%CI:0.04-0.74)and PD-1 inhibitor+chemotherapy(HR:0.36,95%CI:0.2-0.63).PD-1 inhibitor+CTLA-4 was also more advantageous(HR:0.37,95%CI:0.15-0.93)than the conventional chemotherapy for boosting patients'PFS,followed by PD-L1 inhibitor+chemotherapy(HR:0.44,95%CI:0.29-0.66)and PD-1 inhibitor(HR:0.48,95%CI:0.27-0.86).Conclusion Immune checkpoint inhibitor therapy improves the survival of patients with brain metastases from advanced NSCLC.In particular,the combination of PD-1 inhibitor and CTLA-4 inhibitor show excellent survival benefit.

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Circulating Inflammatory Proteins in Relation to Risk of Breast Cancer:A Two-sample Mendelian Randomization Study

Longjiao LIU ; Yufeng YAO

Cancer Research on Prevention and Treatment.2024;51(5):342-347. doi:10.3971/j.issn.1000-8578.2024.23.1344

Objective To investigate the causal association between 91 kinds of circulating inflammatory proteins and different subtypes of breast cancer(estrogen receptor-positive and-negative breast cancer)using a two-sample Mendelian randomization(MR)method.Methods Corresponding exposure and outcome data were extracted from the genome-wide association study database.The data were analyzed by two-sample MR with inverse-variance weighting(IVW)as the primary study method,and MR-Egger,weighted median,simple mode,and weighted mode were used to complement the results.The results were complemented by sensitivity analysis to verify the reliability of the data.Results The IVW results showed that SULT1A1(P=0.0007)was associated with an increased risk of total BC,whereas IL-5(P=0.0011)was associated with a decreased risk of total BC.SULT1A1(P=0.0011)and CX3CL1(P=0.0005)were associated with an increased risk of ER+BC,whereas beta-NGF(P=0.0001)was associated with an increased risk of ER-BC.Supplem-entary analysis methods validated that the findings were consistent in direction and magnitude.The results of the sensitivity analysis showed that the data were reliable and unbiased.Conclusion Using the MR method,this study confirms that SULT1A1 is a risk factor for overall breast cancer,whereas IL-5 is a protective factor for overall breast cancer.SULT1A1 and CX3CL1 are risk factors for estrogen receptor-positive breast cancer,and beta-NGF is a risk factor for estrogen receptor-negative breast cancer.

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Analysis of Association Between Immune Cells and Breast Cancer Based on Two-sample Mendelian Randomization Method

Yuanhang WANG ; Zhiyuan SONG ; Ping LU ; Min ZHANG

Cancer Research on Prevention and Treatment.2024;51(5):348-352. doi:10.3971/j.issn.1000-8578.2024.23.1125

Objective To explore the causal relationship among 731 types of immune cells and breast cancer.Methods Genome-wide association data for immune cells and breast cancer were used.Mendelian randomization analysis was performed using the inverse variance weighting(IVW)and weighted median(WM)methods,and sensitivity analysis was conducted to assess heterogeneity and pleiotropy.Results A total of 19 immune cell phenotypes were identified to potentially have a causal association with breast cancer,using IVW as the main analysis method(P>0.05)and correcting P values using the false discovery rate method at a significance level of 0.05,excluding reverse causality.Of these,eight and 11 immune phenotypes may increase and decrease the risk of breast cancer,respectively.Conclusion This study explored the causal relationship between immune cells and breast cancer.Results show that certain immune cell phenotypes could serve as predictive markers for the early diagnosis of breast cancer and the development of new immun-otherapeutic strategies.

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A Prediction Model for Colorectal Adenoma and Colorectal Cancer Based on Routine Test

Junsheng LIN ; Ziling YING ; Zhengyuan HUANG ; Xianjin ZHU ; Yingping CAO ; Pingxia LU

Cancer Research on Prevention and Treatment.2024;51(5):353-360. doi:10.3971/j.issn.1000-8578.2024.23.1169

Objective To analyze the routine test parameter levels of patients with colorectal adenoma and colorectal cancer,and develop a prediction model.Methods A total of 580 patients diagnosed with colorectal adenoma(117 patients)and colorectal cancer(463 patients)were included in the retrospective study.The patients were randomly divided into two groups according to a 7:3 ratio:a training set with 406 cases and a validation set with 174 cases.Logistic regression analysis was used to establish a prediction model,and a nomogram was drawn.The model′s discrimination,calibration,and clinical applicability were evaluated using receiver operating characteristic curve(ROC),calibration plot,and decision curve analysis(DCA).Results Univariate logistic regression analysis identified 13 potential predictors:age,fecal occult blood test(FOBT),fibrinogen(FIB),thrombin time(TT),albumin(ALB),white blood cell value(WBC),neutrophil count(NEUT#),hematocrit value(HCT),mean corpuscular hemoglobin(MCH),red cell distribution width(RDW),platelet count(PLT),mean platelet volume(MPV),and activated partial thromboplastin time(APTT).Multivariate logistic regression analysis showed MPV,FIB,ALB,FOBT,TT,and HCT were risk factors for colorectal cancer in patients with colorectal adenoma(P<0.05).A nomogram was constructed based on these predictors to build a prediction model.The AUC of the ROC curve was 0.915 for colorectal cancer in the training set and 0.836 in the validation set.Calibration plots demonstrated high prediction accuracy and good model calibration.DCA results indicated the prediction model provided greater net benefit compared with the extreme models at threshold probabilities of approximately 55%-95%.Conclusion The developed prediction model exhibits satisfactory discrimination,calibration,and clinical applicability.The model can serve as an auxiliary tool in distinguishing between colorectal adenoma and colorectal cancer in patients.

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Value of Inflammatory Load in Predicting Prognosis of Elderly Patients with Epithelial Ovarian Cancer

Danni YANG ; Mengna ZHAO ; Xiaoye FENG ; Jiyu TONG ; Hua WANG ; Hongbing CAI

Cancer Research on Prevention and Treatment.2024;51(5):361-367. doi:10.3971/j.issn.1000-8578.2024.23.1174

Objective To explore the value of blood inflammatory load in predicting overall survival of elderly patients with epithelial ovarian cancer(EOC).Methods Elderly patients with EOC were selected,and their clinical data and peripheral blood parameters were collected.We constructed an inflammation-related blood scoring system using univariate and multivariate Cox regression analysis.The Kaplan-Meier method was used for survival analysis.We used Cox proportional hazards analysis to identify the independent prognostic factors.A nomogram model was constructed based on independent prognostic factors,and the receiver operating characteristic curve,C-index,and calibration curve were used to evaluate the model.Results Patients with high blood inflammatory load had worse prognosis(P=0.002).Compared with the low inflammatory load group,patients with high inflammatory load had later clinical stages and larger ascites volume(P<0.05).Cox regression analysis showed that ACCI,CA125,residual lesions,and blood score were independent factors affecting overall survival(P<0.05).Conclusion The blood inflammatory load is the biomarker for the prognosis of elderly patients with EOC.Scoring the inflammatory load in the blood can assist in efficacy monitoring and treatment intervention of ovarian cancer patients.

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Analysis of Clonal Rearrangement Characteristics and Clinical Application Value of IGH in B-cell Non-Hodgkin's Lymphoma by Next-generation Sequencing

Qiang MA ; Dongmei ZOU ; Yixian GUO ; Hong ZHAO ; Xiaoli CHANG ; Ronghua HU ; Wanling SUN

Cancer Research on Prevention and Treatment.2024;51(5):368-372. doi:10.3971/j.issn.1000-8578.2024.23.1196

Objective To investigate the clonal rearrangement characteristics and clinical application value of IGH gene in B-cell non-Hodgkin's lymphoma(B-NHL).Methods Demographic and clinical data as well as IGH sequencing results of 55 patients with B-NHL who underwent next-generation sequencing(NGS)testing were collected,and IGH gene clonal rearrangement was detected.The characteristics of IGH gene clonal rearrangement,IGHV gene usage,and the clinical application value of NGS for IGH clonal rearrangement were analyzed.Results Among 55 patients with B-NHL and IGH clonal rearrangement,single dominant clones were mainly detected(85.45%,47/55);a few patients had two(12.73%,7/55)and three dominant clones(1.82%,1/55).In terms of preference for IGHV gene usage,IGHV3 gene had the highest frequency of access in B-NHL,followed by IGHV4.Among the IGHV subtypes,IGHV3-23 had the highest frequency in chronic lymphocytic leukemia/small lymphocytic lymphoma,and IGHV4-34 had the highest frequency in primary central nervous system diffuse large B-cell lymphoma and not otherwise specified diffuse large B-cell lymphoma.Conclusion A preference for IGHV gene usage in clonal rearr-angement of IGH genes is noted in B-NHL patients with different pathological types.Using NGS to detect IGHclonal rearrangement can identify subclones and clonal correlations,and assist in disease diagnosis.

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