Gastric cancer (GC) is a heterogeneous disease. This heterogeneity applies not only to morphological and phenotypic features but also to geographical variations in incidence and mortality rates. As Chile has one of the highest mortality rates within South America, we sought to define a molecular profile of Chilean GCs (ClinicalTrials.gov identifier: NCT03158571/(FORCE1)). Solid tumor samples and clinical data were obtained from 224 patients, with subsets analyzed by tissue microarray (TMA; n = 90) and next generation sequencing (NGS; n = 101). Most demographic and clinical data were in line with previous reports. TMA data indicated that 60% of patients displayed potentially actionable alterations. Furthermore, 20.5% were categorized as having a high tumor mutational burden, and 13% possessed micro-satellite instability (MSI). Results also confirmed previous studies reporting high Epstein-Barr virus (EBV) positivity (13%) in Chilean-derived GC samples suggesting a high proportion of patients could benefit from immunotherapy. As expected, TP53 and PIK3CA were the most frequently altered genes. However, NGS demonstrated the presence of TP53, NRAS, and BRAF variants previously unreported in current GC databases. Finally, using the Kendall method, we report a significant correlation between EBV+ status and programmed death ligand-1 (PDL1)+ and an inverse correlation between p53 mutational status and MSI. Our results suggest that in this Chilean cohort, a high proportion of patients are potential candidates for immunotherapy treatment. To the best of our knowledge, this study is the first in South America to assess the prevalence of actionable targets and to examine a molecular profile of GC patients.

Cancer patients on chemotherapy have a lower immune response to SARS-CoV-2 vaccines. Therefore, through a prospective cohort study of patients with solid tumors receiving chemotherapy, we aimed to determine the immunogenicity of an mRNA vaccine booster (BNT162b2) among patients previously immunized with an inactivated (CoronaVac) or homologous (BNT162b2) SARS-CoV-2 vaccine. The primary outcome was the proportion of patients with anti-SARS-CoV-2 neutralizing antibody (NAb) seropositivity at 8–12 weeks post-booster. The secondary end points included IgG antibody (TAb) seropositivity and specific T-cell responses. A total of 109 patients were included. Eighty-four (77%) had heterologous vaccine schedules (two doses of CoronaVac followed by the BNT162b2 booster) and twenty-five had (23%) homologous vaccine schedules (three doses of BNT162b2). IgG antibody positivity for the homologous and heterologous regimen were 100% and 96% (p = 0.338), whereas NAb positivity reached 100% and 92% (p = 0.13), respectively. Absolute NAb positivity and Tab levels were associated with the homologous schedule (with a beta coefficient of 0.26 with p = 0.027 and a geometric mean ratio 1.41 with p = 0.044, respectively). Both the homologous and heterologous vaccine regimens elicited a strong humoral and cellular response after the BNT162b2 booster. The homologous regimen was associated with higher NAb positivity and Tab levels after adjusting for relevant covariates.

Tele-oncology expanded rapidly during the COVID-19 pandemic and remains central to cancer care, yet evidence on guideline adherence in tele-oncology is limited, particularly in Latin America. In Chile, the Explicit Health Guarantees (GES) program mandates oncology care standards but provides no process model for monitoring adherence. We evaluated the conformance and temporal performance of telemedicine-based oncology pathways against a guideline-derived reference model using process mining, based on event logs from 182 patients treated in 2020–2023 in a Chilean hospital network. Conformance was computed using PM4Py with token-based replay and alignment-based fitness, complemented by cohort, abstraction-level and robustness analyses with bootstrap confidence intervals and multiple-comparison-adjusted testing. Overall conformance was low (4.95% of cases fully conforming; mean alignment fitness 0.19, 95% CI 0.16–0.22) against a highly precise reference model (precision 0.90). Censoring-aware analyses showed that low conformance was driven predominantly by genuine structural deviations rather than incomplete observation alone. Event-level cohort signatures were observed, but patient-level analyses suggested that these patterns should be interpreted as exploratory. Crude differences in care duration by out-of-model activity status were largely explained by differential observation time after exposure adjustment. Process-mining conformance checking provides reproducible indicators for governing tele-oncology pathways when metrics are interpreted alongside methodological caveats.