IntroductionMalnutrition is a complex clinical syndrome, the exact mechanism of which is yet not fully understood. Studies have found that malnutrition is associated with anorexia and inadequate intake, tumor depletion, leptin, tumor-induced metabolic abnormalities in the body, and catabolic factors produced by the tumor in the circulation and cytokines produced by the host immune system. Among these, single nucleotide polymorphisms (SNPs) are present in the gene encoding the pro-inflammatory cytokine TNF-α.AimThe objective of this study was to investigate TNF-α -1,031 T/C gene polymorphism as an unfavorable predictor of malnutrition in patients with gastric cancer.MethodsThe study group consisted of 220 gastric cancer patients treated at Affiliated Jinhua Hospital, Zhejiang University School of Medicine. Malnutrition was mainly assessed by the Global Consensus on Malnutrition Diagnostic Criteria (GLIM). DNA was extracted from peripheral leukocytes of whole blood samples using an animal DNA extraction kit. DNA was amplified using a 1.1× T3 Super PCR mixture and genotyped using SNP1 software.ResultsThere are three major genetic polymorphisms in TNF-α. Among the 220 patients with gastric cancer, there were 7 patients with the CC genotype, 61 with the CT genotype and 152 with the TT genotype. Compared to patients with the TT genotype, patients with the C allele had an approximately 2.5-fold higher risk of developing malnutrition (p = 0.003; OR = 0.406). On the basis of multivariate analysis, patients with the CC genotype had an approximately 20.1-fold higher risk of developing malnutrition (p = 0.013; OR = 20.114), while those with the CT genotype had an almost 3.7-fold higher risk of malnutrition (p = 0.002; OR = 3.218).ConclusionSNP (−1,031 T/C) of the TNF-α may be a useful marker in the assessment of the risk of nutritional deficiencies in gastric cancer patients. Patients with gastric cancer carrying the C allele should be supported by early nutritional intervention, but more research is still needed to explore confirmation.

IntroductionLung cancer has the second-ranked morbidity rate and the first-ranked mortality rate worldwide. With the progression of the cancer condition and the advancement of new treatments, the corresponding medical expenses have risen sharply. Nowadays, financial toxicity has become one of the most common concerns in patients with cancer. However, by far, the full landscape of studies on financial toxicity is unclear in patients with lung cancer. Thus, this scoping review aims to summarise the degree, affecting factors, outcomes and intervention strategies of financial toxicity in patients with lung cancer.Methods and analysisThis scoping review will be developed following the methodology described in the Joanna Briggs Institute Manual for Evidence Synthesis on scoping review protocol, which was based on Arksey and O’Malley’s methodological framework, Levac et al’s recommendations for applying this framework and Peters et al’s enhancements of the framework. From the day of database building to 31 December 2021, 10 English databases will be searched in the ‘Abstract’ field with three key search terms: “Lung”, “Cancer” and “Financial toxicity”. The studies’ screening and data extraction will be independently performed by two reviewers (MZ and RZ). Any disagreements between the two reviewers (MZ and RZ) will be resolved by consensus, and a third reviewer (BW) will be invited if necessary. The results will be analysed and presented using tables and figures. This scoping review will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist.Ethics and disseminationAn ethical approval is not required for this scoping review protocol, nor for the scoping review. The results of this scoping review will be disseminated through publication in a peer-reviewed journal or presentation at conferences.RegistrationThis scoping review protocol has been registered in the Open Science Framework (https://osf.io/ub45n/?view_only=bb93eb94e1434a0f8196b3b61cffcec2).