Background: In view of the fact that peripheral blood parameters have been reported as predictors of immunotherapy to various cancers, this study aimed to determine the predictors of response to anti-programmed death-1 (anti-PD-1) therapy in patients with esophageal squamous cell carcinoma (ESCC) from peripheral blood parameters. Methods: A retrospective analysis was conducted to investigate the predictive value of peripheral blood parameters including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) in the response to anti-PD-1 antibody treatment. 119 ESCC patients receiving combined treatment including anti-PD-1 antibody were enrolled in this study. Results: The median progression-free survival (PFS) of all ESCC patients was 3.73 months. PFS rate in ESCC patients with low NLR at 6 weeks post treatment was higher than patients with high NLR (HR = 2.097, 95% CI 0.996–4.417, P = 0.027). However, PFS rate in ESCC patients with low NLR at baseline (HR = 1.060, 95% CI 0.524–2.146, P = 0.869) or 3 weeks post treatment (HR = 1.293, 95% CI 0.628–2.663, P = 0.459) was comparable with high NLR. And no statistically different was found in PFS rate between low PLR and high PLR at baseline (HR = 0.786, 95% CI 0.389–1.589, P = 0.469), 3 weeks post treatment (HR = 0.767, 95% CI 0.379–1.552, P = 0.452) or 6 weeks post treatment (HR = 1.272, 95% CI 0.624–2.594, P = 0.488) in ESCC patients. PFS rate was also comparable between low MLR and high MLR at baseline (HR = 0.826, 95% CI 0.408–1.670, P = 0.587), 3 weeks post treatment (HR = 1.209, 95% CI 0.590–2.475, P = 0.580) or 6 weeks post treatment (HR = 1.199, 95% CI 0.586–2.454, P = 0.596). PFS rate was similar between patients with low SII and high SII at baseline (HR = 1.120, 95% CI 0.554–2.264, P = 0.749), 3 weeks post treatment (HR = 1.022, 95% CI 0.500–2.089, P = 0.951) and 6 weeks post treatment (HR = 1.759, 95% CI 0.851–3.635, P = 0.097). Conclusions: NLR at 6 weeks post treatment is a predictor of the response to anti-PD-1 treatment in patients with ESCC.

Immune checkpoint blockade therapy targeting the programmed death-1(PD-1) pathway has shown remarkable efficacy and durable response in patients with various cancer types. Early prediction of therapeutic efficacy is important for optimizing treatment plans and avoiding potential side effects. In this work, we developed an efficient machine learning prediction method using routine hematologic and biochemical parameters to predict the efficacy of PD-1 combination treatment in Pan-Cancer patients. A total of 431 patients with nasopharyngeal carcinoma, esophageal cancer and lung cancer who underwent PD-1 checkpoint inhibitor combination therapy were included in this study. Patients were divided into two groups: progressive disease (PD) and disease control (DC) groups. Hematologic and biochemical parameters were collected before and at the third week of PD-1 therapy. Six machine learning models were developed and trained to predict the efficacy of PD-1 combination therapy at 8–12 weeks. Analysis of 57 blood biomarkers before and after three weeks of PD-1 combination therapy through statistical analysis, heatmaps, and principal component analysis did not accurately predict treatment outcome. However, with machine learning models, both the AdaBoost classifier and GBDT demonstrated high levels of prediction efficiency, with clinically acceptable AUC values exceeding 0.7. The AdaBoost classifier exhibited the highest performance among the 6 machine learning models, with a sensitivity of 0.85 and a specificity of 0.79. Our study demonstrated the potential of machine learning to predict the efficacy of PD-1 combination therapy based on changes in hematologic and biochemical parameters.

BACKGROUND: EBV is associated with nasopharyngeal carcinoma (NPC), but the existence of a NPC protective antibody against EBV-associated antigens remains unclear. METHODS: Patients with NPC and matched controls were identified from prospective cohorts comprising 75,481 participants in southern China. ELISA and conditional logistic regression were applied to assess the effects of gp42-IgG on NPC. The expression of HLA-II, the gp42 receptor, in nasopharyngeal atypical dysplasia and its effect on EBV infection of epithelial cells were evaluated. FINDINGS: gp42-IgG titers were significantly lower in patients with NPC compared with controls across various follow-up years before NPC diagnosis ( P < 0.05). Individuals in the highest quartile for gp42-IgG titers had a 71% NPC risk reduction compared with those in the lowest quartile (ORs _Q4vsQ1 = 0.29, 95% CIs = 0·15 to 0.55, P < 0.001). Each unit antibody titer increase was associated with a 34% lower risk of NPC (OR = 0.66, 95% CI = 0.54–0.81, P _trend < 0.001). The protective effect of of gp42-IgG was observed in patients diagnosed 5 years or more, 1–5 years, and less than 1 year after blood collection ( P < 0.05). HLA-II expression was detected in 13 of 27 specimens of nasopharyngeal atypical dysplasia, and its overexpression substantially promoted epithelial cell–origin EBV infection. CONCLUSION: Elevated EBV gp42-IgG titers can reduce NPC risk, indicating that gp42 is a potential EBV prophylactic vaccine target. TRIAL REGISTRATION: NCT00941538, NCT02501980, ChiCTR2000028776, ChiCTR2100041628. FUNDING: Noncommunicable Chronic Diseases-National Science and Technology Major Project (2023ZD0501003), National Natural Science Foundation of China (82030046, 82073625, 81860601, 82373655), Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2019BT02Y198), and Central Financial Transfer Payment Projects of the Chinese Government, Cancer Research Grant of Zhongshan City.

Immune checkpoint inhibitors (ICI) have created an advanced shift in the treatment of lung cancer (LC), but the existing biomarkers were not in clinical and widespread use. The purpose of this study was to develop a new nomogram with immune factors used for monitoring the response to ICI therapy. LC patients with PD-1/PD-L1 inhibitors treatment were included in this analysis. The immune biomarkers and clinicopathological characteristic values at baseline were used to estimate the tumor response. The nomogram was based on the factors that were determined by univariate and multivariate Cox hazard analysis. For internal validation, bootstrapping with 1000 resamples was used. The concordance index (-index) and calibration curve were used to determine the predictive accuracy and discriminative ability of the nomogram. Overall survival (OS) was estimated using the Kaplan-Meier method. Patients with lung metastasis ( ), higher baseline neutrophil-lymphocyte ratio (NLR) level ( ), lower baseline lymphocyte-monocyte (LMR) ( ), and lower CD3⁺CD8⁺ T cell count ( ) were significantly related to the tumor response. The above biomarkers were contained into the nomogram. The calibration plot for the probability of OS showed an optimal agreement between the actual observation and prediction by nomogram at 3 or 5 years after therapy. The -index of nomogram for OS prediction was 0.804 (95% CI: 0.739-0.869). Decision curve analysis demonstrated that the nomogram was clinically useful. Moreover, patients were divided into two distinct risk groups for OS by the nomogram: low-risk group (OS: 17.27 months, 95% CI: 14.75-19.78) and high-risk group (OS: 6.11 months, 95% CI: 3.57-8.65), respectively. A nomogram constructed with lung metastasis baseline NLR, LMR, and CD3⁺CD8⁺ T cell count could be used to monitor and predict clinical benefit and prognosis in lung cancer patients within ICI therapy.

Background. A female prognostic advantage in younger individuals has been demonstrated in various cancers. Several large‐scale analyses based on different racial backgrounds have reported inconsistent results in colorectal cancer. The aim of the present study was to evaluate the prognostic value of sex and age in patients with colorectal cancer of different ethnic groups. Methods. We identified 71,812 eligible patients from the Surveillance, Epidemiology and End Results database. According to age at diagnosis, the patients were categorized into premenopausal age (≤45 yrs), menopausal age (46–54 yrs), and postmenopausal age (≥55 yrs) subgroups for further analysis. Results. Multivariate analysis identified the female survival advantage to be significant in the premenopausal age subgroup (P = 0.002, HR (95% CI): 0.73 (0.60–0.89)), diminished in the menopausal age subgroup (P = 0.09), and absent in the postmenopausal age subgroup (P = 0.96). Furthermore, the female survival advantage at premenopausal age was significant only in white patients (P = 0.001, HR (95% CI): 0.68 (0.54–0.87)) and not in either American Indian/Alaska Native or Asian or Pacific Islander patients. There was a trend of better survival of females in black patients (P = 0.07). Conclusions. Sex was a major prognostic factor in colorectal cancer patients, especially premenopausal women, and the difference was also associated with race.

Numerous inflammatory indicators have been demonstrated to be strongly correlated with tumor prognosis. However, the association between inflammatory indicators and the prognosis of patients with nasopharyngeal carcinoma (NPC) receiving treatment with programmed death receptor-1 (PD-1) immunosuppressant monoclonal antibodies remains uncertain. Inflammatory indicators in peripheral blood were collected from 161 NPC patients at 3 weeks after initial PD-1 treatment. Through univariate and multivariate analyses, as well as nomogram and survival analyses, we aimed to identify independent prognostic factors related to 1-year progression-free survival (PFS). Subsequently, a prognostic nomogram was devised, and its predictive and discriminating abilities were assessed utilizing calibration curves and the concordance index. Our univariate and multivariate analyses indicated that age ( P = .012), M stage ( P < .001), and systemic immune-inflammation index (SII) during the third week following initial PD-1 treatment (SII3, P = .005) were independently correlated with the 1-year PFS of NPC patients after PD-1 treatment. Notably, we constructed a novel nomogram based on the SII3, age, and M stage. Importantly, utilizing the derived cutoff point from the nomogram, the high-risk group exhibited significantly shorter PFS than did the low-risk group ( P < .001). Furthermore, the nomogram demonstrated a greater concordance index for PFS than did the tumor node metastasis stage within the entire cohort. We successfully developed a nomogram that integrates the SII3 and clinical markers to accurately predict the 1-year PFS of NPC patients receiving PD-1 inhibitor treatment.