Search

Abstract Background Chemotherapy is still the standard regimen for treating acute myeloid leukemia (AML) and its disappointing efficacy requires the urgent need for new therapeutic targets. It is well known that immune response plays an increasingly significant role in the pathogenesis of AML. Methods We detected nine single nucleotide polymorphisms (SNPs) in immune checkpoint‐related genes, including PD1, LAG3, TIM3, and TIGIT in 285 AML inpatients and 324 healthy controls. SNP genotyping was performed on the MassARRAY platform. Furthermore, we analyzed the relationship between the susceptibility and prognosis of AML and the selected SNPs. Results Our results showed that rs2227982 and rs10204525 in PD1 were significantly associated with susceptibility to AML after false discovery rate correction. PD1 rs10204525 also showed a significant correlation with the response to chemotherapy and risk stratification of AML. Importantly, the AA genotype of PD1 (rs2227982) under the recessive model showed a negative impact on AML prognosis independently. Conclusions Our results indicate that PD1 SNPs are important for susceptibility and prognosis in AML, which may provide a new therapeutic target for AML patients.

Abstract Geriatric assessment can aid in optimizing treatment strategies and supportive interventions for older patients with diffuse large B‐cell lymphoma (DLBCL). Fondazione Italiana Linformi has recently introduced novel geriatric assessment tools, simplified Geriatric Assessment (sGA) and Elderly Prognostic Index (EPI), aimed at tailoring the treatment and predicting the outcomes for older patients with DLBCL. The objectives of this study are the validation and possible modification of the sGA and EPI in China. In the study, both sGA and EPI demonstrated the predictive capabilities for overall survival (OS) and early mortality (both p

Abstract Background Gastric cardia adenocarcinoma (GCA) is a highly fatal form of cancer in humans. The aim of this study was to extract clinicopathological data of postoperative patients with GCA from the Surveillance, Epidemiology, and End Results database, analyze prognostic risk factors, and build a nomogram. Methods In this study, the clinical information of 1448 patients with GCA who underwent radical surgery and were diagnosed between 2010 and 2015 was extracted from the SEER database. The patients were then randomly divided into training (n = 1013) and internal validation (n = 435) cohorts at a 7:3 ratio. The study also included an external validation cohort (n = 218) from a Chinese hospital. The study used the Cox and LASSO models to pinpoint the independent risk factors linked to GCA. The prognostic model was constructed according to the results of the multivariate regression analysis. To assess the predictive accuracy of the nomogram, four methods were used: C‐index, calibration curve, time‐dependent ROC curve, and DCA curve. Kaplan–Meier survival curves were also generated to illustrate the differences in cancer‐specific survival (CSS) between the groups. Results The results of the multivariate Cox regression analysis showed that age, grade, race, marital status, T stage, and log odds of positive lymph nodes (LODDS) were independently associated with cancer‐specific survival in the training cohort. Both the C‐index and AUC values depicted in the nomogram were greater than 0.71. The calibration curve revealed that the nomogram's CSS prediction was consistent with the actual outcomes. The decision curve analysis suggested moderately positive net benefits. Based on the nomogram risk score, significant differences in survival between the high‐ and low‐risk groups were observed. Conclusions Race, age, marital status, differentiation grade, T stage, and LODDS are independent predictors of CSS in patients with GCA after radical surgery. Our predictive nomogram constructed based on these variables demonstrated good predictive ability.

Abstract Introduction Cervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection. Materials Differentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six‐gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co‐expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six‐gene signature. Results We discovered 178 overlapping DEGs in three microarray datasets and established a six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six‐gene signature was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer. Conclusion Our study established a novel six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six‐gene signature have the potential to become novel drug targets.

Background: Cornichon homolog 4 (CNIH4) belongs to the CNIH family. It functions as an oncogene in many tumors. However, CNIH4's significance in the immune landscape and its predictive potential in cervical cancer (CESC) is unexplored. Methods: CNIH4 levels and its effect on the survival of patients with CESC were evaluated using data retrieved from The Cancer Genome Atlas (TCGA). The oncogenic effect of CNIH4 in CESC was determined using small interfering RNA‐mediated transfected cell lines and tumorigenesis experiments in animal models. Results: Higher expression of CNIH4 was found in advanced tumor and pathological stages, as well as lymph node metastasis. CNIH4 expression correlated positively with the infiltration of macrophages M2 and resting dendritic cells into the affected tissue. Additionally, functional enrichment of RNA‐sequencing of CNIH4‐knocked down CESC cell lines showed the association of CNIH4 to the PI3K‐Akt signaling pathway. Single‐sample gene set enrichment analysis highlighted several immune pathways that were elevated in the CESC samples with enhanced levels of CNIH4, including Type‐I and Type‐II IFN‐response pathways. The impact of CNIH4 on drug sensitivity was further assessed using the GDSC database. As CNIH4 is linked to the immune landscape in CESC, this study determined a four‐gene risk prediction signature utilizing CNIH4‐related immunomodulators. The risk score quantified from the prediction signature was an independent predictive indicator in CESC. Receiver operating characteristic curve analysis verified the good predictive ability of the four‐gene signature in TCGA‐CESC cohort. Thus, the CNIH4‐related model showed potential as an auxiliary TNM staging system tool. Conclusion: CNIH4 may be an effective predictive biomarker for patients with cervical cancer, thus providing new ideas and research directions for CESC. [ABSTRACT FROM AUTHOR]

Abstract The study aimed to investigate the role of serum EBV‐VCA IgG in assessing gastric cancer (GC) risk and prognosis. A total of 1790 Northern Chinese participants with pathologically confirmed disease underwent EBV‐VCA IgG serologic testing using enzyme‐linked immunosorbent assay (ELISA), including 821 controls, 410 atrophic gastritis (AG) patients, and 559 GC patients. We found that positive EBV‐VCA IgG was significantly associated with GC and its precursor, conferring a 1.55‐ and 1.36‐fold increased risk of GC and AG, respectively (P = 0.001, 95% CI = 1.21‐1.99; P = 0.011, 95% CI = 1.07‐1.72, respectively). The risk effects were more remarkable in younger, female, and Helicobacter pylori‐negative individuals than in older, male, and H. pylori‐positive individuals. EBV‐VCA IgG‐positive subjects had a lower PGI/II ratio than EBV‐VCA IgG‐negative subjects (median 8.0 vs 8.8, P = 0.001), especially those in the H. pylori‐positive (median 6.1 vs 6.8, P = 0.027) and GC subgroups (median 6.4 vs 7.9, P = 0.020). In the intestinal GC subgroup, the survival of EBV‐VCA IgG‐positive patients was worse than that of EBV‐VCA IgG‐negative patients (P = 0.041, HR = 2.45, 95% CI = 1.04‐5.78). Our study suggests that EBV‐VCA IgG seropositivity has potential in predicting the risk of GC and its precursor as well as the prognosis of histologically classified GC.

Background: Chemotherapy is still the standard regimen for treating acute myeloid leukemia (AML) and its disappointing efficacy requires the urgent need for new therapeutic targets. It is well known that immune response plays an increasingly significant role in the pathogenesis of AML. Methods: We detected nine single nucleotide polymorphisms (SNPs) in immune checkpoint‐related genes, including PD1, LAG3, TIM3, and TIGIT in 285 AML inpatients and 324 healthy controls. SNP genotyping was performed on the MassARRAY platform. Furthermore, we analyzed the relationship between the susceptibility and prognosis of AML and the selected SNPs. Results: Our results showed that rs2227982 and rs10204525 in PD1 were significantly associated with susceptibility to AML after false discovery rate correction. PD1 rs10204525 also showed a significant correlation with the response to chemotherapy and risk stratification of AML. Importantly, the AA genotype of PD1 (rs2227982) under the recessive model showed a negative impact on AML prognosis independently. Conclusions: Our results indicate that PD1 SNPs are important for susceptibility and prognosis in AML, which may provide a new therapeutic target for AML patients. [ABSTRACT FROM AUTHOR]

Background: Gastric cardia adenocarcinoma (GCA) is a highly fatal form of cancer in humans. The aim of this study was to extract clinicopathological data of postoperative patients with GCA from the Surveillance, Epidemiology, and End Results database, analyze prognostic risk factors, and build a nomogram. Methods: In this study, the clinical information of 1448 patients with GCA who underwent radical surgery and were diagnosed between 2010 and 2015 was extracted from the SEER database. The patients were then randomly divided into training (n = 1013) and internal validation (n = 435) cohorts at a 7:3 ratio. The study also included an external validation cohort (n = 218) from a Chinese hospital. The study used the Cox and LASSO models to pinpoint the independent risk factors linked to GCA. The prognostic model was constructed according to the results of the multivariate regression analysis. To assess the predictive accuracy of the nomogram, four methods were used: C‐index, calibration curve, time‐dependent ROC curve, and DCA curve. Kaplan–Meier survival curves were also generated to illustrate the differences in cancer‐specific survival (CSS) between the groups. Results: The results of the multivariate Cox regression analysis showed that age, grade, race, marital status, T stage, and log odds of positive lymph nodes (LODDS) were independently associated with cancer‐specific survival in the training cohort. Both the C‐index and AUC values depicted in the nomogram were greater than 0.71. The calibration curve revealed that the nomogram's CSS prediction was consistent with the actual outcomes. The decision curve analysis suggested moderately positive net benefits. Based on the nomogram risk score, significant differences in survival between the high‐ and low‐risk groups were observed. Conclusions: Race, age, marital status, differentiation grade, T stage, and LODDS are independent predictors of CSS in patients with GCA after radical surgery. Our predictive nomogram constructed based on these variables demonstrated good predictive ability. The nomogram for postoperative patients with GCA we constructed has good predictive power and can help clinicians accurately assess patient prognosis and identify high‐risk patients to develop more personalized treatment plans. [ABSTRACT FROM AUTHOR]

Introduction: Cervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection. Materials: Differentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six‐gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co‐expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six‐gene signature. Results: We discovered 178 overlapping DEGs in three microarray datasets and established a six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six‐gene signature was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer. Conclusion: Our study established a novel six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six‐gene signature have the potential to become novel drug targets. [ABSTRACT FROM AUTHOR]

The study aimed to investigate the role of serum EBV‐VCA IgG in assessing gastric cancer (GC) risk and prognosis. A total of 1790 Northern Chinese participants with pathologically confirmed disease underwent EBV‐VCA IgG serologic testing using enzyme‐linked immunosorbent assay (ELISA), including 821 controls, 410 atrophic gastritis (AG) patients, and 559 GC patients. We found that positive EBV‐VCA IgG was significantly associated with GC and its precursor, conferring a 1.55‐ and 1.36‐fold increased risk of GC and AG, respectively (P = 0.001, 95% CI = 1.21‐1.99; P = 0.011, 95% CI = 1.07‐1.72, respectively). The risk effects were more remarkable in younger, female, and Helicobacter pylori‐negative individuals than in older, male, and H. pylori‐positive individuals. EBV‐VCA IgG‐positive subjects had a lower PGI/II ratio than EBV‐VCA IgG‐negative subjects (median 8.0 vs 8.8, P = 0.001), especially those in the H. pylori‐positive (median 6.1 vs 6.8, P = 0.027) and GC subgroups (median 6.4 vs 7.9, P = 0.020). In the intestinal GC subgroup, the survival of EBV‐VCA IgG‐positive patients was worse than that of EBV‐VCA IgG‐negative patients (P = 0.041, HR = 2.45, 95% CI = 1.04‐5.78). Our study suggests that EBV‐VCA IgG seropositivity has potential in predicting the risk of GC and its precursor as well as the prognosis of histologically classified GC. This is an innovative report about the role of serum EBV‐VCA IgG detection in assessing the risk of gastric cancer (GC) and its precursor as well as GC prognosis. And this is the first report about the relationship between EBV‐VCA IgG serology assay and gastric function status. Our study provides theoretical and experimental basis for evaluating the potential of serum EBV‐VCA IgG as a biomarker in prediction of GC risk and prognosis. [ABSTRACT FROM AUTHOR]

Abstract: It is necessary to develop prognostic tools of metastatic pancreatic cancer (MPC) for optimizing therapeutic strategies. Thus, we tried to develop and validate a prognostic nomogram of MPC. Data from 3 clinical trials (NCT00844649, NCT01124786, and NCT00574275) and 133 Chinese MPC patients were used for analysis. The former 2 trials were taken as the training cohort while NCT00574275 was used as the validation cohort. In addition, 133 MPC patients treated in China were taken as the testing cohort. Cox regression model was used to investigate prognostic factors in the training cohort. With these factors, we established a nomogram and verified it by Harrell's concordance index (C‐index) and calibration plots. Furthermore, the nomogram was externally validated in the validation cohort and testing cohort. In the training cohort (n = 445), performance status, liver metastasis, Carbohydrate antigen 19‐9 (CA19‐9) log‐value, absolute neutrophil count (ANC), and albumin were independent prognostic factors for overall survival (OS). A nomogram was established with these factors to predict OS and survival probabilities. The nomogram showed an acceptable discrimination ability (C‐index: .683) and good calibration, and was further externally validated in the validation cohort (n = 273, C‐index: .699) and testing cohort (n = 133, C‐index: .653).The nomogram total points (NTP) had the potential to stratify patients into 3‐risk groups with median OS of 11.7, 7.0 and 3.7 months (P < .001), respectively. In conclusion, the prognostic nomogram with NTP can predict OS for patients with MPC with considerable accuracy. [ABSTRACT FROM AUTHOR]