Gastric cancer (GC) is one of the most common tumor in the world, and remains a major public health problem and one of the leading causes of death. Recently many researches have demonstrated that systemic inflammatory response is associated with prognosis and response to therapy in gastric cancer, and the peripheral blood count test can partly reflect the systemic inflammatory response. Based on the peripheral blood count test, there are a lot of research regarding the relation between the platelet count (PLT), neutrophil, lymphocyte, white blood cell (WBC), neutrophil to lymphocyte ratio(NLR), platelet to lymphocyte ratio (PLR) with their prognostic role in gastric cancer. A high PLT and preoperative lymphocytopenia are both associated with increased lymph node metastasis, stage (III(+IIII(), serosal invasion (T3+T4) risk and poorer overall survival. Besides above, platelet monitoring following surgery can be applied to predict the recurrence for patients with GC that suffer preoperative high PLT but have restored PLT levels following resection. Moreover systemic inflammatory factors based on blood parameters, such as PLR, NLR and so on, have relation with the poor prognosis of patients with GC. Among them, high NLR is a negative predictor of prognosis in GC patients. However PLR remains inconsistent, while most researches demonstrated high PLR may be useful prognostic factor rather than independent prognostic factor. There are still some limitations which include various cut-off values, little of clinician attention, the uncertain mechanism, etc. Here we review the research progress in the prognostic role of the blood count test in gastric cancer.
Blood Cell Count ; methods ; statistics & numerical data ; Blood Platelets ; physiology ; Humans ; Inflammation ; blood ; diagnosis ; immunology ; Leukocyte Count ; statistics & numerical data ; Lymphatic Metastasis ; diagnosis ; immunology ; Lymphocyte Count ; statistics & numerical data ; Lymphopenia ; blood ; physiopathology ; Neoplasm Invasiveness ; immunology ; Neoplasm Recurrence, Local ; blood ; diagnosis ; Neoplasm Staging ; statistics & numerical data ; Neutrophils ; immunology ; Platelet Count ; statistics & numerical data ; Prognosis ; Stomach Neoplasms ; blood ; diagnosis ; immunology ; mortality ; Treatment Outcome

Objective:To investigate the risk factors for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer, and application value of a nomogram prediction model.Methods:The retrospective case-control study was conducted. The clinicopathological data of 228 patients with stage Ⅱ-Ⅲ colon cancer who underwent radical resection in the First Affiliated Hospital of Xi′an Jiaotong University from January 2013 to June 2016 were collected. There were 118 males and 110 females, aged from 25 to 87 years, with a median age of 62 years. All patients underwent open or laparoscopic-assisted radical resection of colon cancer. Observation indicators: (1) postoperative tumor recurrence; (2) risk factors analysis for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer; (3) development and evaluation of a nomogram prediction model for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer. Follow-up using outpatient examination and telephone interview was performed to detect postoperative 3-year tumor recurrence up to June 2019. Measurement data with skewed distribution were represented as M (range). Count data were described as absolute numbers, and comparison between groups was analyzed using the Pearson chi-square test or Fisher exact probability. Multivariate analysis was performed using Logistic stepwise regression analysis. The independent risk factors were included into R 3.6.1 software to construct a nomogram prediction model. The receiver operating characteristic curve (ROC) was drawed, and the area under curve (AUC) was used to evaluate discrimination of the nomogram prediction model. The calibration chart with R software was used to evaluate consistency of the nomogram prediction model. Results:(1)Postoperative tumor recurrence: 53 of 228 patients had postoperative tumor recurrence including 19 cases with locoregional recurrence and 34 cases with distant metastasis. Of the 34 patients with distant metastasis, there were 14 cases with liver metastasis, 7 cases with lung metastasis, 4 cases with brain metastasis, and 9 cases with multiple metastasis or isolated metastasis in other sites. The time to recurrence was 12 months (range, 6-19 months). (2) Risk factors analysis for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer:results of univariate analysis showed that bowel obstruction, preoperative carcinoembryonic antigen (CEA) level, ascites, vascular invasion were related factors for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer ( χ2=4.463, 13.622, 10.914, 5.911, P<0.05). Pathological N stage was also a related factor for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer ( P<0.05). Results of multivariate analysis showed that preoperative CEA level >5 μg/L, ascites, vascular invasion and pathological N stage as stage N1 or N2 were independent risk factors for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer ( odds ratio=3.129, 3.071, 7.634, 3.439, 15.467, 95% confidence interval as 1.328-7.373, 1.047-9.007, 1.103-52.824, 1.422-8.319, 3.498-68.397, P<0.05). (3) Development and evaluation of a nomogram prediction model for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer: based on preoperative CEA level, ascites, vascular invasion and pathological N stage of multivariate analysis, a nomogram prediction model for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer was developed using R 3.6.1 software. The nomogram score was 41.7 for preoperative CEA level >5 μg/L, 41.0 for ascites, 74.2 for vascular invasion, 45.1 and 100.0 for pathological N stage as stage N1 and N2, respectively. The total of different scores for risk factors corresponded to the probability of postoperative recurrence. The ROC of nomogram for recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer was drawed,with the AUC of 0.805(95% confidence interval as 0.737-0.873, P<0.05). The calibration chart showed a good consistency between the probability of recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer predicted by nomogram and the actual probability of postoperative recurrence. Conclusions:Preoperative CEA level >5 μg/L, ascites, vascular invasion and pathological N stage as stage N1 or N2 are independent risk factors for tumor recurrence after radical resection of stage Ⅱ-Ⅲ colon cancer. The nomogram prediction model contributes to prediction of the recurrent risks after radical resection of stage Ⅱ-Ⅲ colon cancer.

Objective:To investigate the relationship between transcription factors (TFs) and the prognosis of colon cancer, and to construct a prognosis model through TCGA and GEO dual databases, so as to quantify the risk of patients and guide clinical treatment decisions.Methods:The transcriptome and clinical data of colon cancer in TCGA and GEO databases were used in this study. The transcriptome data were annotated and the gene expression was calculated. The difference analysis of TFs in TCGA and GEO (log2FC > 1, P-value (Fdr) < 0.05) was performed. The difference TFs of double data intersection were used for correlation prognosis analysis ( P<0.01). The risk coefficient and risk value of prognosis-related TFs were calculated by COX multivariate analysis, and the prognosis model of TFs was constructed by COX model with "survival" and "glmnet" package. The survival curve ( P<0.001) and ROC curve (AUC>0.75) of the sequence set and verification set were drawn, and the distribution of risk value was visualized. After grouping according to risk value, GSEA enrichment analysis was calculated, gene set grid was constructed, target genes were predicted, and finally, pathway enrichment analysis of GO and KEGG was carried out. Results:387 TFs with different expressions in TCGA and GEO databases were used to draw heat map, volcanic map and TFs-related forest map, and the prognosis model of colon cancer was constructed according to COX multivariate analysis=0.310×HSF4+0.137×IRX3-0.127×ATOH1+0.290×OVOL3+0.137×HOXC6+0.155×SIX2+0.092×ZNF556-0.444×CXXC5+0.429×TIGD1+0.413×TCF7L1. Through enrichment analysis, our results showed that these prognostic factors may directly or indirectly act on cancer pathways, such as basic cell carcinoma and cancer signaling pathway, local tissue-cell adhesion, and extracellular matrix.Conclusions:The constructed TFs prognosis model of colon cancer can quantify the prognostic risk of colon cancer, and its high-risk group is an independent risk factor of colon cancer prognosis. This model is a new way to evaluate the prognosis of colon cancer.