Carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) are established prognostic biomarkers for patients with gastric cancer. However, their potential as predictive markers for neoadjuvant chemotherapy (NACT) efficacy has not been fully elucidated. Methods: We conducted a retrospective analysis to determine values of CEA and CA19-9 prior to NACT (pre-NACT) and after NACT (post-NACT) in 399 patients with locally advanced gastric cancer (LAGC) who received intended NACT and surgery. Results: Among the 399 patients who underwent NACT plus surgery, 132 patients (33.1%) had elevated pre-NACT CEA/CA19-9 values. Furthermore, either pre-NACT or post-NACT CEA /CA19-9 levels were significantly associated with prognosis (p = 0.0023) compared to patients with non-elevated levels. Moreover, among the patients, a significant proportion (73/132, 55.3%) achieved normalized CEA/CA19-9 following NACT, which is a strong marker of a favorable treatment response and survival benefits. In addition, the patients with normalized CEA/CA19-9 also had a prolonged survival compared to those who underwent surgery first (p = 0.0140), which may be attributed to the clearance of micro-metastatic foci. Additionally, the magnitude of CEA/CA19-9 changes did not exhibit a statistically significant prognostic value. Conclusions: Normalization of CEA/CA19-9 is a strong biomarker for the effectiveness of treatment, and can thus be exploited to prolong the long-term survival of patients with LAGC.

Neoadjuvant chemotherapy (NACT) has been established as being an effective treatment for advanced gastric cancer (GC), while the predictive biomarker of NACT efficacy remains under investigation. Aspartate β-hydroxylase (ASPH) represents an attractive target which is a highly conserved transmembrane enzyme overexpressed in human GC, and participates in the malignant transformation by promoting tumor cell motility. Here, we evaluated the expression of ASPH by immunohistochemistry in 350 GC tissues (including samples for NACT) and found that ASPH expression was higher in patients undergoing NACT compared with patients without NACT pre-operation. The OS and PFS time of ASPH-intensely positive patients was significantly shorter than that of the negative patients in the NACT group, while the difference was not significant in patients without NACT. We showed that ASPH knockout enhanced the inhibitory effects of chemotherapeutic drugs on the cell proliferation, migration, and invasion in vitro and suppressed tumor progression in vivo. Co-immunoprecipitation revealed that ASPH might interact with LAPTM4B to perform chemotherapeutic drug resistance. Our results suggested that ASPH might serve as a candidate biomarker to predict prognosis and a novel therapeutic target for gastric cancer patients treated with neoadjuvant chemotherapy.

Background: Immunogenic cell death (ICD) is considered a promising type of regulated cell death and exerts effects by activating the adaptive immune response, reshaping the tumor environment (TME) and improving therapeutic efficacy. However, the potential roles and prognostic value of ICD-associated genes in gastric cancer (GC) remain unclear. Methods: The RNA expression data and clinical information of 1090 GC patients from six cohorts were collected. Consensus clustering was used to identify three distinct molecular subtypes. Then, a robust prognostic ICD_score for predicting prognosis was built via WGCNA and LASSO Cox regression according to the TCGA cohort, and the predictive capability of the ICD_score in GC patients was validated in the other cohorts. ICD-related immune features were analyzed using a CIBERSORT method and verified by immunofluorescence. Results: We found that ICD-related gene variations were correlated with clinical outcomes, tumor immune microenvironment (TIME) characteristics and treatment response. We then constructed an ICD signature that classifies cases as low- and high-ICD_score groups. The high-ICD_score group indicates unfavorable OS, a more advanced TNM stage, and presents an immune-suppressed phenotype, which has more infiltrations of pro-tumor immune cells, such as macrophages, which was verified by immunofluorescence. In addition, a nomogram containing the ICD_score showed a high predictive accuracy with AUCs of 0.715, 0.731 and 0.8 on Years 1, 3, and 5. Conclusion: We performed the first and synthesis ICD analysis in GC and built a clinical application tool based on the ICD signature, which paved a new path for assessing prognosis and guiding individual treatment.

Adequate reporting is essential for evaluating the performance and clinical utility of a prognostic prediction model. Previous studies indicated a prevalence of incomplete or suboptimal reporting in translational and clinical studies involving development of multivariable prediction models for prognosis, which limited the potential applications of these models. While reporting templates introduced by the established guidelines provide an invaluable framework for reporting prognostic studies uniformly, there is a widespread lack of qualified adherence, which may be due to miscellaneous challenges in manual reporting of extensive model details, especially in the era of precision medicine. Here, we present ReProMSig (Reproducible Prognosis Molecular Signature), a web-based integrative platform providing the analysis framework for development, validation and application of a multivariable prediction model for cancer prognosis, using clinicopathological features and/or molecular profiles. ReProMSig platform supports transparent reporting by presenting both methodology details and analysis results in a strictly structured reporting file, following the guideline checklist with minimal manual input needed. The generated reporting file can be published together with a developed prediction model, to allow thorough interrogation and external validation, as well as online application for prospective cases. We demonstrated the utilities of ReProMSig by development of prognostic molecular signatures for stage II and III colorectal cancer respectively, in comparison with a published signature reproduced by ReProMSig. Together, ReProMSig provides an integrated framework for development, evaluation and application of prognostic/predictive biomarkers for cancer in a more transparent and reproducible way, which would be a useful resource for health care professionals and biomedical researchers.