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Cancer is a devastating disease, and there is no particularly effective treatment at present. Recently, a new treatment, cold atmospheric plasma (CAP), has been proposed. At present, CAP is confirmed to have selective killing effect on tumor by many studies in vitro and in vivo. A targeted literature search was carried out on the study of cold atmospheric plasma. Through analysis and screening, a narrative review approach was selected to describe therapeutic effects of cold atmospheric plasma on solid tumor. According to the recent studies on plasma, some hypothetical therapeutic schemes of CAP are proposed in this paper. The killing mechanism of CAP on solid tumor is expounded in terms of the selectivity of CAP to tumor, the effects of CAP on cells, tumor microenvironment (TME) and immune system. CAP has many effects on solid tumors, and these effects are dose-dependent. The effects of optimal doses of CAP on solid tumors include killing tumor cells, inhibiting non-malignant cells and ECM in TME, affecting the communication between tumor cells, and inducing immunogenic death of tumor cells. In addition, several promising research directions of CAP are proposed in this review, which provide guidance for future research.

Tuanhe Sun, Kang Li, Kun Zhu, Rong Yan, Chengxue Dang, Dawei Yuan Department of Surgical Oncology, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, People’s Republic of ChinaCorrespondence: Dawei YuanDepartment of Surgical Oncology, First Affiliated Hospital of Xi’an Jiaotong University, 277 West Yanta Road, Xi’an, Shaanxi 710061, People’s Republic of ChinaEmail dwyuan@mail.xjtu.edu.cnBackground: Cisplatin resistance results in the failure of platinum-based chemotherapy and relapse of gastric cancer. We aimed to investigate the potential regulating role of SNHG6/miR-325-3p/GITR in reversing cisplatin resistance.Patients and Methods: A total of 137 gastric cancer patients were recruited. qRT-PCR and ELISA were used to test the expression of target genes. CCK-8 and caspase 3/7 kit were used to test the cell viability and apoptosis rate. Dual luciferase reporter gene and RNA-pull down assay were used to investigate the potential interaction between target genes.Results: SNHG6 and GITR were up regulated in gastric cancer; however, miR-325-3p was down-regulated. Besides, SNHG6, miR-325-3p and GITR expression were associated with gastric cancer prognosis. Then, we found that GITR and SNHG6 promoted proliferation and inhibited apoptosis of MKN45 and MKN45 cisplatin resistance cell line; however, miR-325-3p inhibited proliferation and promoted apoptosis of these cell lines. Furthermore, SNHG6 might bind to miR-325-3p to regulate its expression, and miR-325-3p directly interacted with the 3`UTR of GITR.Conclusion: SNHG6 binds to miR-325-3p, which directly interacted with GITR to regulate cisplatin resistance of gastric cancer.Keywords: gastric cancer, cisplatin resistance, GITR, SNHG5, miR-325-3p

Additional file 1: Table S1. Cutoff values for parameters in datasets before and after PSM. Table S2. Univariate and multivariate analyses for overall survival of female GC patients (N=146). Table S3. Univariate and multivariate analyses for overall survival of male GC patients (N=469). Table S4. Univariate and multivariate analyses for disease-free survival of female GC patients (N=146). Table S5. Univariate and multivariate analyses for disease-free survival of male GC patients (N=469). Table S6. Univariate and multivariate analyses for overall survival of GC patients after PSM (N=460). Table S7. Univariate and multivariate analyses for overall survival of male GC patients after PSM (N=346). Table S8. Univariate and multivariate analyses for overall survival of female GC patients after PSM (N=114). Table S9. Univariate and multivariate analyses for disease-free survival of GC patients after PSM (N=460). Table S10. Univariate and multivariate analyses for disease-free survival of male GC patients after PSM (N=346). Table S11. Univariate and multivariate analyses for disease-free survival of female GC patients after PSM (N=114). Figure S1. ROC analysis for the prediction of OS. AUC indicates the diagnostic power of ALI (A) in overall series, (B) in female subgroup and (C) in male subgroup. AUC indicates the diagnostic power of BMI (D) in overall series, (E) in female subgroup and (F) in male subgroup. AUC indicates the diagnostic power of ALB (G) in overall series, (H) in female subgroup and (I) in male subgroup. AUC indicates the diagnostic power of NLR (J) in overall series, (K) in female subgroup and (L) in male subgroup. Respective cutoff values obtained at the maximum Youden index was used to divide them into two groups. ROC, receiver operating characteristic curve; OS, overall survival; AUC, area under the ROC curve; ALI, advanced lung cancer inflammation index; BMI, body mass index; ALB, albumin; NLR, neutrophil-lymphocyte ratio. Figure S2. ROC analysis for the prediction of DFS. AUC indicates the diagnostic power of ALI (A) in overall series, (B) in female subgroup and (C) in male subgroup. AUC indicates the diagnostic power of BMI (D) in overall series, (E) in female subgroup and (F) in male subgroup. AUC indicates the diagnostic power of ALB (G) in overall series, (H) in female subgroup and (I) in male subgroup. AUC indicates the diagnostic power of NLR (J) in overall series, (K) in female subgroup and (L) in male subgroup. Respective cutoff values obtained at the maximum Youden index was used to divide them into two groups. DFS, disease-free survival. Figure S3. Kaplan-Meier survival analysis of BMI, ALB and NLR for the prediction of OS. Kaplan-Meier survival curves of BMI (A) in all patients, (B) in female patients and (C) in male patients. Kaplan-Meier survival curves of ALB (D) in all patients, (E) in female patients and (F) in male patients. Kaplan-Meier survival curves of NLR (G) in all patients, (H) in female patients and (I) in male patients. The respective cutoff values were obtained from the ROC curves of the subgroups. Both cutoff values and statistical significance are shown in figure. (J-L) Kaplan-Meier survival curves of BMI in groups stratified by TNM stage (P=0.205, 0.344 and 0.047, respectively). Figure S4. Kaplan-Meier survival analysis of BMI, ALB and NLR for the prediction of DFS. Kaplan-Meier survival curves of BMI (A) in all patients, (B) in female patients and (C) in male patients. Kaplan-Meier survival curves of ALB (D) in all patients, (E) in female patients and (F) in male patients. Kaplan-Meier survival curves of NLR (G) in all patients, (H) in female patients and (I) in male patients. The respective cutoff values were obtained from the ROC curves of the subgroups and shown in figure. (J-L) Kaplan-Meier survival curves of BMI in groups stratified by TNM stage (P=0.229, 0.211 and 0.047, respectively). Figure S5. ROC analysis for the prediction of OS and DFS in dataset after PSM. (A) ROC curve of ALI for the prediction of OS of all patients in this dataset; (B) ROC curve of ALI for the prediction of DFS of all patients in this dataset; (C) ROC curve of ALI for the prediction of OS of male patients; (D) ROC curve of ALI for the prediction of DFS of male patients; (E) ROC curve of ALI for the prediction of OS of female patients; (F) ROC curve of ALI for the prediction of DFS of female patients.