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The WHO recently designated salivary gland lymphoepithelial carcinoma as a unique malignant tumor that most commonly occurs in the parotid gland. This is a rare cancer and there are few reports in the literature. Among 854 patients with parotid gland tumors who were admitted to our institution, we diagnosed 12 patients (1.41%) with parotid lymphoepithelial carcinoma. Retrospective analysis of 12 patients with parotid lymphoepithelial carcinoma diagnosed by the Department of Pathology, Xiangya Hospital of Central South University. All 12 patients had unilateral parotid gland disease and 8 had cervical lymph node metastasis. Five patients received PCR testing for the Epstein–Barr virus and two were positive. All patients received surgical treatment, two received surgical resection alone, nine received surgery and postoperative radiotherapy and chemotherapy, and one received surgery and postoperative chemotherapy. The postoperative follow-up time ranged from 13 to 77 months. As of the last follow-up, eight patients were tumor-free, one patient was lost to follow-up, and three patients died. The main cause of death was local tumor recurrence and multiple metastases throughout the body. Parotid lymphoepithelial carcinoma is a malignant neoplasm characterized by proliferation, invasion, and inclusion of poorly differentiated or undifferentiated carcinoma, and a high rate of metastasis to ipsilateral cervical lymph nodes. The comprehensive treatment method consists of radical resection combined with postoperative radiotherapy and chemotherapy. After this comprehensive treatment, the 1-year, 3-year, and 5-year overall survival rates of our patients were 100%, 78.8%, and 39.4%.

The KEYNOTE-590 trial showed that individuals with advanced esophageal cancer who received Pembrolizumab in combination with chemotherapy as a first-line regimen achieved a significant extension of survival. However, this treatment option increases the financial burden on patients and the economic benefits remain to be further evaluated.A Markov model was used to simulate 10-year survival of patients with esophageal cancer from the perspective of United States (US) Medicare payers. We evaluated the economics of Pembrolizumab plus chemotherapy in the PD-L1 positive score (CPS ≥10) and any PD-L1 expression groups, respectively. We estimated total costs, quality-adjusted life years (QALYs), and calculated incremental cost effectiveness ratios (ICERs). Sensitivity analyses were conducted to explore the impact of uncertainties on the results. Subgroup analysis was also performed.The analysis results showed that the ICER for pembrolizumab plus chemotherapy versus chemotherapy alone was $293,513.17/QALYs in the any PD-L1 expression group. This exceeded the threshold of willingness to pay ($150,000/QALYs). ICERs were most sensitive to the cost of pembrolizumab and the ICERs exceeded $150,000/QALYs in all subgroups.Evidence suggests that first-line pembrolizumab in combination with chemotherapy is not a cost-effective option for advanced esophageal cancer in the US, regardless of PD-L1 expression status.

Objective: We evaluated the cost-effectiveness of Toripalimab plus TP in treating patients with esophageal cancer in this study.Perspective: the Chinese payers.Methods: A Markov model was developed from the Chinese payers’ perspectives.We conducted a cost-effectiveness analysis.One-way and probabilistic sensitivity analyses were conducted to explore the impact of uncertainties on the cost-effectiveness’s results. Scenario analysis was also performed.Results: The ICER for Toripalimab plus chemotherapy versus chemotherapy was $16834.30. An increase of 0.83 QALYs and 1.39 LYs. For Toripalimab plus TP, the ICER/QALY is $20302.54 compared to TP alone at the WTP of $37653.The ICERs were the most sensitive to the utility of PD. Conclusions: Toripalimab plus TP therapy for advanced oesophageal cancer would be cost-effective compared with TP.

Background: Colonic adenocarcinoma (COAD) is a common gastrointestinal tract tumor, and its occurrence and progression are usually associated with genomic instability, tumor suppressor gene and oncogene mutations, and tumor mutational load.The biological importance of RNA N6-methyladenosine (m6A) modification and long non-coding RNA (lncRNA) expression in tumorigenesis and progression has been demonstrated. However, the regulatory role of m6A ‐ associated lncRNAs in the tumor microenvironment (TME) and the stratification of prognosis and immunotherapy have not been determined.Methods: We screened 43 prognostic lncRNAs linked to m6A and conducted consistent molecular typing of COAD using consensus clustering. The ssGSEA algorithm and the ESTIMATE algorithm were employed to assess the immune characteristics describing the different subgroups. Covariation between methylation-related prognostic lncRNAs was then eliminated by least absolute shrinkage and selection operator (Lasso) Cox regression. A nomogram was created and evaluated by combining the methylation-related prognostic lncRNA model with other clinical factors. And, the relationship between prognostic model grouping and microsatellite instability (MSI), immunophenotype score (IPS) and tumor mutation burden (TMB) was further validated using R language. Finally we used the linkage map (CMAP) to filter sensitive medicines to suppress the expression of high-risk genes.Results: Three separate m6A-associated lncRNA modes were discovered in 446 COAD specimens with different clinical endpoints and biological status. Risk scores were constructed based on m6A-associated lncRNA signature genes. Patients with lesser risk scores demonstrated superior immunotherapy response and clinical benefit. Further profiling suggested that lesser risk scores were also correlated with higher IPS scores, tumor mutation burden, and mutation rates in significant mutated genes (SMGs) (e.g., FAT4 and MUC16). Piperidolate, quinostatin, and mecamylamin were then screened for their ability to suppress expression of high-risk genes in the model.Conclusions: Quantitative assessment of m6A-associated lncRNAs in single tumors is expected to enhance our comprehension of the TME profile. M6A-associated lncRNAs constructed a prognostic model that facilitates prognosis and immunotherapy stratification in COAD patients, and based on the model we screened three drugs with potential therapeutic value.

This work aimed to investigate tumor-infiltrating immune cells (TIICs) and immune-associated genes in the tumor microenvironment of osteosarcoma. An algorithm known as ESTIMATE was applied for immune score assessment, and osteosarcoma cases were assigned to the high and low immune score groups. Immune-associated genes between these groups were compared, and an optimal immune-related risk model was built by Cox regression analyses. The deconvolution algorithm (referred to as CIBERSORT) was applied to assess 22 TIICs for their amounts in the osteosarcoma microenvironment. Osteosarcoma cases with high immune score had significantly improved outcome (P

Supplemental Digital Content is available in the text, Background: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with osteosarcoma (OS) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with OS. Methods: Databases were searched to identify association studies of SNPs and OS published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database, and Wan fang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability for noteworthy associations. The methodological quality of data was assessed based on the STrengthening the REporting of Genetic Association Studies statement Stata 14.0 will be used for systematic review and meta-analysis. Results: This study will provide a high-quality evidence to find the SNP most associated with OS susceptibility and the best genetic model. Conclusions: This study will explore which SNP is most associated with OS susceptibility. Registration: INPLASY202040023.

In this meta-analysis, we systematically investigated the correlation between single nucleotide polymorphisms (SNPs) and pancreatic cancer (PC) risk. We searched PubMed, Network Science, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang databases up to January 2020 for studies on PC risk-associated SNPs. We identified 45 case-control studies (36,360 PC patients and 54,752 non-cancer individuals) relating to investigations of 27 genes and 54 SNPs for this meta-analysis. Direct meta-analysis followed by network meta-analysis and Thakkinstian algorithm analysis showed that homozygous genetic models for CTLA-4 rs231775 (OR =0.326; 95% CI: 0.218-0.488) and VDR rs2228570 (OR = 1.976; 95% CI: 1.496-2.611) and additive gene model for TP53 rs9895829 (OR = 1.231; 95% CI: 1.143-1.326) were significantly associated with PC risk. TP53 rs9895829 was the most optimal SNP for diagnosing PC susceptibility with a false positive report probability < 0.2 at a stringent prior probability value of 0.00001. This systematic review and meta-analysis suggest that TP53 rs9895829, VDR rs2228570, and CTLA-4 rs231775 are significantly associated with PC risk. We also demonstrate that TP53 rs9895829 is a potential diagnostic biomarker for estimating PC risk.

Background Single nucleotide polymorphisms (SNPs) have been inconsistently associated with hepatocellular carcinoma (HCC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with HCC in the Asian population. Methods Databases were searched to identify association studies of SNPs and HCC in Asians published through January 2019. Summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated based on 41 studies (13,167 patients with HCC and 15,886 noncancer controls). Network meta-analysis and Thakkinstian’s algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. Results Eleven SNPs meeting the inclusion criteria were tested for association with HCC, including CCND1 rs9344, PTGS2 rs689466, IL18 rs187238 and rs1946518, KIF1B rs17401966, MDM2 rs2279744, MIR146A rs2910164, MIR149 rs2292832, MIR196A2 rs11614913, MIR499A rs3746444, and TGFB1 rs1800469. A significant increase for HCC risk was observed for MDM2 rs2279744, and the dominant (pooled OR = 1.59, 95% CI: 1.26–2.00) and codominant (pooled OR = 1.37, 95% CI: 1.18–1.60) models were determined to be the most appropriate models. MIR499A rs3746444 also showed a significant association with HCC risk under the allele contrast model (pooled OR = 1.36, 95% CI: 1.05–1.77). Only the significance of MDM2 rs2279744 was noteworthy (FPRP Conclusions MDM2 rs2279744 is associated with HCC susceptibility in Asians, and the dominant and codominant models are likely the most appropriate models to estimate HCC risk.

Supplemental Digital Content is available in the text, Background: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with atrophic gastritis (AG) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with AG. Methods: To identify all associated studies of SNPs and AG published, databases had been searched through January 2020 from the databases of PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, Embase, the Chinese Science and Technology Periodical Database (VIP), Cochrane Library, and Wanfang databases. With the help of network meta-analysis and Thakkinstian algorithm, the best genetic model with the strongest correlation with AG was selected, the final result – matching to the noteworthy correlation – was obtained by referring to the false positive reporting rate (false positive report probability, FPRP). Based on STREGA's stated criteria, the methodological quality of the data we collected was valued. Both Stata 14.0 and GeMTC will be used for a comprehensive review of the system and will be used in our meta-analysis. Results: This study will provide a high-quality evidence to find the SNP most associated with AG susceptibility and the best genetic model. Conclusions: This study will explore which SNP is most associated with AG susceptibility. Registration: INPLASY202050016.

Background According to the relevant reports that single nucleotide polymorphisms (SNPs) may contribute to change of homocysteine (HCY) levels and increase the risk of hypertension (HTN). During the inconsistent results, this meta-analysis purpose is systematically review and synthesized relevant data on HCY levels and SNPs in HTN. Methods The systematic search database, from the following database to find out the association studies of SNPs and HTN publications up until March 2020 from the databases of PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), the Chinese Science and Technology Periodical Database (VIP) and Wan fang databases, and Chinese Biomedical Literature Database (CBM). Network meta-analysis and Thakkinstian's algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. All statistical analyses were calculated with STATA software (version 14.0; StataCorp, College Station, TX). Results This meta-analysis will provide high-quality evidence to the effects of SNP on HTN and levels of HCY, and find between SNPs and HTN susceptibility on in all the genetic models, and choose the best one. Conclusions This meta-analysis will research which SNP is the most correlated with HTN risk. Registration INPLASY202050002.

Supplemental Digital Content is available in the text, Background: Single nucleotide polymorphisms (SNPs) have been inconsistently associated with pancreatic cancer (PC) risk. This meta-analysis aimed to synthesize relevant data on SNPs associated with PC. Methods: Databases were searched to identify association studies of SNPs and PC published through January 2020 from the databases of PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, the Chinese Science and Technology Periodical Database (VIP) and Wanfang databases. Network meta-analysis and Thakkinstian algorithm were used to select the most appropriate genetic model, along with false positive report probability (FPRP) for noteworthy associations. The methodological quality of data was assessed based on the STREGA statement Stata 14.0 will be used for systematic review and meta-analysis. Results: This study will provide a high-quality evidence to find the SNP most associated with pancreatic cancer susceptibility and the best genetic model. Conclusions: This study will explore which SNP is most associated with pancreatic cancer susceptibility. Registration: INPLASY202040023.