Objective To evaluate the safety and efficacy of neoadjuvant chemotherapy combined with PA-MSHA injection for the treatment of locally advanced breast cancer. Methods An open, randomized, controlled clinical trial was conducted in this study. 42 locally advanced breast cancer patients were randomly assigned to two groups, namely the experimental group (20 cases) and control group (22 cases). All the patients received chemotherapy of TEC regimen, while, in addition, the patients in experiment group received PA-MSHA injection. After the treatment, the efficacy of treatment was evaluated. The safety and tolerance of patients were also measured during the treatment. Results The overall response rate (CR+PR) [75.0 %(15/20)]in the experiment group was significant higher than that [54.6 %(12/22)]in control group (P < 0.01). Adverse reactions were found for 9 cases in experiment group, four of whom received medical care while the others recovered automatically. Conclusion PA-MSHA injection can significantly enhance the efficaey of neoadjuvant chemotherapy on the patients with locally advanced breast cancer. The PA-MSHA injection which has been proved safety in treatment is an ideal supplementary therapy for breast cancer.

Objective To investigate the association between single nucleotide polymorphisms(SNPs)of YTHDF1 rs6011668,HNRNPA2B1 rs2070601 and rs76558212 with the risk of gastric cancer.Methods A total of 457 cases with gastric cancer and 525 healthy controls were collected.The candidate SNPs were genotyped using Hi-SNP genotyping methods by multiplex rounds of PCR and high-throughput sequencing;the association between the three SNPs with the risk of gastric cancer was analyzed by test and Logistic regression.Multifactorial logistic regression and Risk Score(RS)model was used to analyze the influence of environmental and genetic factors on the risk of gastric cancer.Results YTHDF1rs6011668 TT genotype carriers had 3.075 times higher risk of gastric cancer than CC genotype carriers(95%CI:1.128～8.382,P = 0.028),and 2.961 times higher risk than CC/TC genotypes carriers(95%CI:1.091～8.033,P = 0.033).Subgroups-analysis revealed that TT genotype mainly increased the risk of gastric cancer in non-tea drinkers,pickled food eaters and fried food eaters(P<0.05).In addition,TT genotype carriers had the increased risk of gastric cancer infiltration,lymph node metastasis,distal metastasis and intermediate to advanced stages(P<0.05).The RS of the case and control groups were calculated by combining environmental and genetic factors.The higher the RS score,the higher the risk of gastric cancer was found in the RS quartile groups.Compared with the RS

Objective    To establish the gene-based esophageal cancer (ESCA) risk score prediction models via whole transcriptome analysis to provide ideas and basis for improving ESCA treatment strategies and patient prognosis. Methods    RNA sequencing data of esophageal squamous cell carcinoma (ESCC), esophageal adenocarcinoma (EAC) and adjacent tissues were obtained from The Cancer Genome Atlas database. The edgeR method was used to screen out the differential genes between ESCA tissue and normal tissue, and the key genes affecting the survival status of ESCC and EAC patients were initially identified through univariate Cox regression analysis. The least absolute shrinkage and selection operator regression analysis and multivariate Cox regression analysis were used to further screen genes and establish ESCC and EAC risk score prediction models. Results    The risk score prediction models were the independent prognostic factors for ESCA, and the risk score was significantly related to the survival status of patients. In ESCC, the risk score was related to T stage. In EAC, the risk score was related to lymph node metastasis, distant metastasis and clinical stage. The constructed nomogram based on risk score showed good predictive ability. In ESCC, the risk score was related to tumor immune cell infiltration and the expression of immune checkpoint genes. However, this feature was not obvious in EAC. Conclusion 聽 聽The ESCC and EAC risk score prediction models have shown good predictive capabilities, which provide certain inspiration and basis for optimizing the management of ESCA and improving the prognosis of patients.