BACKGROUND Gastric carcinoma (GC) is one of the most aggressive primary digestive cancers. It has unsatisfactory therapeutic outcomes and is difficult to diagnose early. AIM To identify prognostic biomarkers for GC patients using comprehensive bioinformatics analyses. METHODS Differentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas and Gene Expression Omnibus databases for GC. Overlapping DEGs were analyzed using univariate and multivariate Cox regression analyses. A risk score model was then constructed and its prognostic value was validated utilizing an independent Gene Expression Omnibus dataset (GSE15459). Multiple databases were used to analyze each gene in the risk score model. High-risk score-associated pathways and therapeutic small molecule drugs were analyzed and predicted, respectively. RESULTS A total of 95 overlapping DEGs were found and a nine-gene signature ( COL8A1, CTHRC1, COL5A2, AADAC, MAMDC2, SERPINE1, MAOA, COL1A2 , and FNDC1 ) was constructed for the GC prognosis prediction. Receiver operating characteristic curve performance in the training dataset (The Cancer Genome Atlas-stomach adenocarcinoma) and validation dataset (GSE15459) demonstrated a robust prognostic value of the risk score model. Multiple database analyses for each gene provided evidence to further understand the nine-gene signature. Gene set enrichment analysis showed that the high-risk group was enriched in multiple cancer-related pathways. Moreover, several new small molecule drugs for potential treatment of GC were identified. CONCLUSION The nine-gene signature-derived risk score allows to predict GC prognosis and might prove useful for guiding therapeutic strategies for GC patients.

Background In breast cancer (BC), tumor‐associated macrophages (TAMs) are an important component of the tumor microenvironment and are closely related to poor prognosis. A growing number of studies have focused on the role of TAMs in BC progression and therapeutic strategies targeting TAMs. As an emerging treatment, the application of nanosized drug delivery systems (NDDSs) in the treatment of BC by targeting TAMs has attracted much attention. Aims This review is to summarize the characteristics and treatment strategies targeting TAMs in BC and to clarify the applications of NDDSs targeting TAMs in the treatment of BC by targeting TAMs. Materials & Methods The existing results related to characteristics of TAMs in BC, BC treatment strategies by targeting TAMs, and the applications of NDDSs in these strategies are described. Through analyzing these results, the advantages and disadvantages of the treatment strategies using NDDSs are discussed, which could provide advices on designing NDDSs for BC treatment. Results TAMs are one of the most prominent noncancer cell types in BC. TAMs not only promote angiogenesis, tumor growth and metastasis but also lead to therapeutic resistance and immunosuppression. Mainly four strategies have been used to target TAMs for BC therapy, which include depleting macrophages, blocking recruitment, reprogramming to attain an anti‐tumor phenotype, and increasing phagocytosis. Since NDDSs can efficiently deliver drugs to TAMs with low toxicity, they are promising approaches for targeting TAMs in tumor therapy. NDDSs with various structures can deliver immunotherapeutic agents and nucleic acid therapeutics to TAMs. In addition, NDDSs can realize combination therapies. Discussion TAMs play a critical role in the progression of BC. An increasing number of strategies have been proposed to regulate TAMs. Compared with free drugs, NDDSs targeting TAMs improve drug concentration, reduce toxicity and realize combination therapies. However, in order to achieve better therapeutic efficacy, there are still some disadvantages that need to be considered in the design of NDDSs. Conclusion TAMs play an important role in the progression of BC, and targeting TAMs is a promising strategy for BC therapy. In particular, NDDSs targeting TAMs have unique advantages and are potential treatments for BC.

Background Neratinib plus capecitabine(N + C)has a good effect for HER2-positive metastatic breast cancer (MBC), but considering these tradeoffs in quality of life and cost, the optimal choice of treatment sequencing is unclear. Cost-effectiveness analysis can clearly quantify such tradeoffs to make more informed decisions. Our objective was to evaluate the social cost-effectiveness of the N + C regimen for HER2 positive MBC. METHODS Clinical data were extracted from a randomized controlled trial, NALA (NCT01808573). Patients were randomized into the N + C group or the lapatinib plus capecitabine (L + C) group. A Markov model was established with a 21-day cycle length. Costs were acquired from local hospitals, effect parameters included quality-adjusted life year (QALY) and incremental cost-effectiveness ratio (ICER). RESULTS In the main analysis, the QALY in N + C is 0.04492 higher than that in L + C (N + C, 0.62954 QALY; L + C, 0.58462 QALY). The ICER between N + C and L + C was − 1,796,801.93 CNY/QALY. In the subanalysis, the QALY in N + C is 0.05643 higher than that in L + C (N + C, 0.65047 QALY; L + C, 0.59404 QALY) in the Asian group. The ICER between N + C and L + C was − 1,584,528.96 CNY/QALY. Sensitivity analyses indicated the stability of the model and the impact of utility. CONCLUSION N + C was cost-effective compared with L + C for HER2 positive MBC.