Objective To explore therapeutic effect of endocrine therapy in breast cancer patients with negative hormone receptor (HR–) of primary lesion and positive HR (HR+) of metastatic axillary lymph node lesion. Methods Sixty-seven cases of breast cancer with HR– of primary lesion and HR+ of metastatic axillary lymph node lesion from January 2011 to January 2016 were selected. All the patients were randomly divided into endocrine therapy group (33 cases) and control group (34 cases). The patients were given the oral drug of tamoxifen on the basis of conventional chemotherapy in the endocrine therapy group after the surgery, 10 mg/time, twice daily, 5 years; while the patients in the control group were not given the oral drug of tamoxifen but the other therapy same as the endocrine therapy group. The survivals were compared in both groups. Results There were no significant differences in the age, menstrual condition, tumor diameter, preoperative TNM stage, and so on between the endocrine therapy group and the control group (P>0.05). All the patients were followed up for 12–60 months with a 48.5 months of median time. There were no significant differences in the rates of the local recurrence and metastasis, or death rate due to the recurrence and metastasis in both groups (P>0.05). The progression-free survival and overall survival in the endocrine therapy group were significantly higher than those in the control group (P<0.05). The 5-year cumulative progression-free survival and overall survival in the endocrine therapy group were significantly better than those in the control group (P<0.05). Conclusion Pay attention to molecular classification of primary lesion and metastatic axillary lymph node lesion in patients with breast cancer, and endocrine therapy might be able to improve survival rate of breast cancer patients with primary lesion HR– and metastatic axillary lymph node lesion HR+.
ObjectiveTo understand the research advances in molecular classification systems of gastric cancer and explore their clinical application value in precision diagnosis and treatment, as well as future development directions. MethodA literature search was conducted to identify and summarize the classic classification systems, including the Singapore-Duke typing, The Cancer Genome Atlas (TCGA) typing, and the Asian Cancer Research Group (ACRG) typing, as well as novel precision typing frameworks driven by cutting-edge technologies such as single-cell sequencing, spatial transcriptomics, epigenetics, metabolomics, and multi-omics integrative analysis. ResultsGastric cancer is characterized by high heterogeneity, and traditional pathological typing is difficult to meet the requirements of precision diagnosis and treatment. Among the classic molecular classifications, the Singapore-Duke classification classifies gastric cancer into proliferative, mesenchymal, and metabolic subtypes, and which are correlated with drug sensitivity. According to the multi-omics features, the TCGA classification categorizes gastric cancer into four subtypes: Epstein-Barr virus (EBV)-positive, microsatellite instability (MSI), genomically stability (GS), and chromosomal instabilty (CIN), among which EBV-positive and MSI subtypes are associated with the best prognosis, while the GS subtype shows the worst prognosis. The ACRG classification (Asian cohort) categorizes gastric cancer into MSI, microsatellite stable (MSS)/TP53-active, MSS/TP53-inactive, and MSS/epithelial-mesenchymal transition (EMT) subtypes, among which MSI tumors show the best prognosis, and MSS/EMT tumors the worst. Regarding novel frontier classifications, tumor microenvironment ecotypes and cancer-associated fibroblast subpopulations are identified by single-cell and spatial transcriptomics. Additionally, immune consensus subtypes, a PANoptosis-related long non-coding RNA prognostic model, and tumor immune microenvironment classifications, and other subtypes have been constructed through epigenetics, metabolomics, and multi-omics integrative analysis. In clinical translation, different molecular subtypes are matched with corresponding therapeutic strategies, and the combination of molecular classification and TNM staging is enabled to improve the accuracy of prognostic evaluation. ConclusionsMolecular classification of gastric cancer provides a stratification basis for precise diagnosis and treatment, yet its clinical translation still faces challenges such as high technical cost and intratumoral heterogeneity. In the future, relying on artificial intelligence, liquid biopsy, and other technologies, clinically practical subtype-guided individualized therapeutic strategies can be realized.