Prediction Of Prognosis And Chemotherapy Survival Benefits,and Neutrophils Promote Cancer Progression In Gastric Cancer

Staging according to the TNM(tumor,node,and metastasis)system and histological subtype has been the most commonly used benchmark for prognostic definition and establishment of treatment strategy in gastric cancer(GC).However,large variations in clinical outcomes have been shown in patients with the same stage and similar treatment regimens.These findings suggest that the present staging system of gastric cancer is not adequate for definition of prognosis and cannot predict the candidates who are likely to benefit from chemotherapy.Hence,new strategies are urgently required for prediction of prognostic and chemotherapy benefits.Tumor progression has been recognized as the product of an evolving crosstalk between different cell types within the tumor and its stroma.Immune cells,including myeloid cells,monocytes/macrophages,neutrophils and lymphocytes,are prominent components of tumor stroma.Extensive literature has suggested that the immune infiltrates in cancer are of clinical importance.Neutrophil is an important component of the immune infiltrates,but its role in gastric cancer is still unclear.Base on multidimensional characteristic of gastric cancer,we developed 5 models to predict prognosis and chemotherapy survival benefit.With the combination of clinical sample examination and in vitro/in vivo study,we investigated the influence of tumor microenvironments on the phenotypic and functional features of neutrophils.The results are summarized as followed:First,ImmunoScore signature predicts postsurgical survival and chemotherapeutic benefits in gastric cancer.A prediction model for GC patients was developed using data from 879 consecutive patients.The expression of 27 immune features was detected in 251 specimens by using immunohistochemistry(IHC).Using the LASSO Cox model,we established an ISGC classifier based on 5 features:CD3invasive margin(IM),CD3center of tumor(CDT),CD8IM,CD45ROCT,and CD66bIM.Significant differences were found between the high-ISGc and low-ISGC patients in the training cohort in 5-year disease-free survival(DFS)(45.0%vs.4.4%,respectively;P<0.001)and 5-year overall survival(OS)(48.8%vs.6.7%,respectively;P<0.001).Multivariate analysis revealed that the ISGC classifier was an independent prognostic factor.A combination of ISGC and TNM stage had better prognostic value than TNM stage alone.Further analysis revealed that stage Ⅱ and Ⅲ GC patients with high-ISGc exhibited a favorable response to adjuvant chemotherapy.Second,Clinicalpathological nomograms for estimating the survival benefit of adjuvant chemotherapy for stage Ⅱ and Ⅲ gastric cancer.Of the 1719 patients analyzed,1183(68.8%)were men and 536(31.2%)were women and the median(interquartile range)age was 57(49-66)years.Age,location,differentiation,carcinoembryonic antigen,cancer antigen 19-9,depth of invasion,lymph node metastasis,and adjuvant chemotherapy were significantly associated with OS and DFS,with P<0.05.The survival prediction model demonstrated good calibration and discrimination,with relatively high bootstrap-corrected concordance indexes(C-index)in the training and validation cohorts.In the validation cohort,the C-indexes for OS and DFS were 0.693(95%CI,0.671-0.715)and 0.704(0.681-0.728),respectivly.Two nomograms and a calculating tool were built on the basis of specific input variables to estimate an individual’s net survival gain attributable to adjuvant chemotherapy.Third,Immunomarker support vector machines classifier for prediction of gastric cancer survival and adjuvant chemotherapeutic benefits.In this research,we constructed a GC-SVM classifier integrating sex,CEA,lymph node metastasis and 8 IHC features,including CD3IM,CD3CT,CD45ROCT,CD57IM,CD66bIM,CD68CT and CD34.Significant differences were found between the high-and low-GC-SVM patients in 5-year OS and DFS in training and validation cohorts.Multivariate analysis revealed that the GC-SVM classifier was an independent prognostic factor.Moreover,the GC-SVM classifer might be able to predict which patients will benefit from adjuvant chemotherapy.Fourth,Prognostic and predictive value of six-biomarker support vector machine classifier in gastric cancer treated by 5-fluorouracil/oxaliplatin chemotherapy.We retrospectively analyzed the expression levels of PAK6,cyclooxygenase 2(COX-2),p21WAF1,Ki-67,excision repair cross-complementing gene 1(ERCC1),and thymidylate synthase(TS)in 242 paraffin-embedded GC specimens by IHC.Then,we used support vector machine(SVM)-based methods to develop a predictive classifier for chemotherapy(chemotherapy score-SVM classifier:CS-SVM classifier).Further validation was performed in an independent cohort of 279 patients.High PAK6 expression was associated with poor prognosis and increased chemoresistance to 5-FU/oxaliplatin chemotherapy.The CS-SVM classifier distinguished patients with stage Ⅱ and Ⅲ GC into low-and high-CS-SVM groups,with significant differences in the 5-year DFS and OS in chemotherapy patients.Moreover,chemotherapy significantly prolonged the DFS and OS of the high CS-SVM patients stage Ⅱ and Ⅲ GC.In conclusion,PAK6 was an independent prognostic factor and increased chemoresistance.The CS-SVM classifier distinguished a subgroup of stage Ⅱ and Ⅲ patients who would highly benefit from chemotherapy,thus facilitating patient counseling and individualizing the management.Fifth,Radiomics signature predicts postsurgical survival and chemotherapeutic benefits in gastric cancer.We analyzed radiomics features of portal venous-phase computed tomography in 1,591 consecutive patients.A radiomics signature was generated by using the LASSO Cox regression model in 228 patients and validated in internal and external validation cohorts.The radiomics signature consisted of 19 selected features and was significantly associated with DFS and OS.Multivariate analysis demonstrated that the radiomics signature was an independent prognostic factor.Incorporating the radiomics signature into the radiomics-based nomograms resulted in better performance for the estimation of DFS(C-index:0.849(95%CI 0.799-0.899))and OS(0.862(0.811-0.913))than the clinicopathologic nomograms and the TNM staging system,with improved accuracy of the classification of survival outcomes.Further analysis showed stage Ⅱ and Ⅲ patients with higher radiomics scores exhibited a favorable response to adjuvant chemotherapy.Sixth,IL-17+ neutrophils promote gastric cancer progression by fostering angiogenesis.In tissues of GC,neutrophils were enriched predominantly in the invasive margin(IM),and neutrophil levels were a powerful predictor of poor survival in GC patients.Interleukin-17+(IL-17)neutrophils constitute a large portion of IL-17-producing cells in human GC.Pro-inflammatory IL-17 is a critical mediator of the recruitment of neutrophils into the IM by CXC chemokines.Moreover,neutrophils at the IM were a major source of matrix metalloproteinase-9,a secreted protein that stimulates proangiogenic activity in GC cells.Accordingly,high levels of infiltrated neutrophils at the IM were positively correlated with angiogenesis progression in GC.