Background: Gastric cancer (GC) is one of the most malignant diseases and threatens the health of individuals across the globe. Hitherto, the identification of prognosis risk stratification on GC has mainly depended on the TNM staging, but owing to its inaccuracy and incompleteness, the prognostic value it offers remains controversial in the current clinical setting. Thus, an effective prognostic model for GC after radical gastrectomy is still needed. Methods: Patients with pathologically confirmed GC who underwent radical gastrectomy from 2 different centers were retrospectively enrolled into a training and the validation cohort, respectively. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to select variables among multiple factors, including clinical characteristics, pathological parameters, and surgery-and treatment-related indicators. The multivariate Cox regression method was used to establish the model to predict 1-, 2-, and 3-year survival. Both internal and external validations of the nomogram were then completed in terms of discrimination, calibration, and clinical utility. Finally, prognostic risk stratification of GC was conducted with X-tile software. Results: A total of 1,424 patients with GC were eligible in this study, including 1,010 in the training cohort and 414 in the validation cohort. Seven indicators were selected by LASSO to develop the nomogram, including the number of positive lymph nodes, tumor size, adjacent organ invasion, vascular invasion, the level of carbohydrate antigen 125 (CA 125), depth of invasion, and human epidermal growth factor receptor 2 (HER2) status. The nomogram demonstrated a robust predictive capacity with favorable accuracy, discrimination, and clinical utility both in the internal and external validations. Moreover, we divided the population into 3 risk groups of survival according to the cutoff points generated by X-tile, and in this way, the nomogram was further improved into a risk-stratified prognosis model. Conclusions: We have developed a prognostic risk stratification nomogram for GC patients after radical gastrectomy with 7 available indicators that may guide clinical practice and help facilitate tailored decisionmaking, thus avoiding overtreatment or undertreatment and improving communication between clinicians and patients.

BackgroundGastric cancer (GC) is one of the most significant health problems worldwide. Some studies have reported associations between Phospholipase C epsilon 1 (PLCE1) single-nucleotide polymorphisms (SNPs) and GC susceptibility, but its relationship with GC prognosis lacked exploration, and the specific mechanisms were not elaborated fully yet. This study aimed to further explore the possible mechanism of the association between PLCE1 polymorphisms and GC.Materials and MethodsA case-control study, including 588 GC patients and 703 healthy controls among the Chinese Han population, was performed to investigate the association between SNPs of PLCE1 and GC risk by logistic regression in multiple genetic models. The prognostic value of PLCE1 in GC was evaluated by the Kaplan-Meier plotter. To explored the potential functions of PLCE1, various bioinformatics analyses were conducted. Furthermore, we also constructed the spatial structure of PLCE1 protein using the homology modeling method to analyze its mutations.ResultsRs3765524 C > T, rs2274223 A > G and rs3781264 T > C in PLCE1 were associated with the increased risk of GC. The overall survival and progression-free survival of patients with high expression of PLCE1 were significantly lower than those with low expression [HR (95% CI) = 1.38 (1.1–1.63), P < 0.01; HR (95% CI) = 1.4 (1.07–1.84), P = 0.01]. Bioinformatic analysis revealed that PLCE1 was associated with protein phosphorylation and played a crucial role in the calcium signal pathway. Two important functional domains, catalytic binding pocket and calcium ion binding pocket, were found by homology modeling of PLCE1 protein; rs3765524 polymorphism could change the efficiency of the former, and rs2274223 polymorphism affected the activity of the latter, which may together play a potentially significant role in the tumorigenesis and prognosis of GC.ConclusionPatients with high expression of PLCE1 had a poor prognosis in GC, and SNPs in PLCE1 were associated with GC risk, which might be related to the changes in spatial structure of the protein, especially the variation of the efficiency of PLCE1 in the calcium signal pathway.

e12565 Background: HER2-low could be found in some patients with triple-negative breast cancer (TNBC). However, its potential impacts on clinical features and tumor biological characteristics in TNBC remain unclear. Methods: We enrolled 251 consecutive TNBC patients retrospectively, including 157 HER2-low (HER2low) and 94 HER2-negtive (HER2neg) patients to investigate the clinical and prognostic features. Then, we performed single-cell RNA sequencing (scRNA-seq) with another seven TNBC samples (HER2neg vs. HER2low, 4 vs. 3) prospectively to further explore the differences of tumor biological properties between the two TNBC phenotypes. The underlying molecular distinctions were also explored and then verified in the additional TNBC samples. Results: Compared with HER2neg TNBC, HER2low TNBC patients exhibited malignant clinical features with larger tumor size ( P = 0.04), more lymph nodes involvement ( P = 0.02), higher histological grade of lesions ( P < 0.001), higher Ki67 status ( P < 0.01), and a worse prognosis ( P < 0.001; HR [CI 95%] = 3.44 [2.10-5.62]). Cox proportional hazards analysis showed that neoadjuvant systemic therapy, lymph nodes involvement and Ki67 levels were prognostic factors in HER2low TNBC but not in HER2neg TNBC patients. scRNA-seq revealed that HER2low TNBC which showed more metabolically active and aggressive hallmarks, while HER2neg TNBC exhibited signatures more involved in immune activities with higher expressions of immunoglobulin-related genes ( IGHG1, IGHG4, IGKC, IGLC2); this was further confirmed by immunofluorescence in clinical TNBC samples. Furthermore, HER2low and HER2neg TNBC exhibited distinct tumor evolutionary characteristics. Moreover, HER2neg TNBC revealed a potentially more active immune microenvironment than HER2low TNBC, as evidenced by positively active regulation of macrophage polarization, abundant CD8+ effector T cells, enriched diversity of T-cell receptors and higher levels of immunotherapy-targeted markers, which contributed to achieve immunotherapeutic response. Conclusions: This study suggests that HER2low TNBC patients harbor more malignant clinical behavior and aggressive tumor biological properties than the HER2neg phenotype. The heterogeneity of HER2 may be a non-negligible factor in the clinical management of TNBC patients. Our data provides new insights into the development of a more refined classification and tailored therapeutic strategies for TNBC patients.