Survival and safety analysis of COVID-19 vaccine in Chinese patients with non-small cell lung cancer.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 disease (COVID-19) has caused a worldwide challenging and threatening pandemic. We aimed to assess the safety and efficacy of the COVID-19 vaccines in Non-Small Cell Lung Cancer (NSCLC) patients. METHODS: Patient self-reported adverse events related to vaccines were recorded by follow-up through a uniform questionnaire. Survival analysis was performed by Kaplan-Meier method. A multivariate analysis was performed by the Cox proportional hazard regression model to determine the effect of each variable on the survival of lung cancer patients. RESULTS: A total of 860 patients with NSCLC on treatment were enrolled. Mean age was 57 years in patients with early stage group and 62 years in advanced stage group. The vaccination rate was 71.11% for early-stage patients and 19.48% for advanced-stage patients; most of them (86.5%) received the COVID-19 inactivated virus (Vero cell) vaccine (Coronavac; Sinovac). The most common systemic adverse reaction was weakness. The main reason for vaccine refusal in those unvaccinated patients was concern about the safety of vaccination in the presence of a tumor and undergoing treatment (56.9% and 53.4%). The 1-year disease-free survival (DFS) rate was 100% for vaccinated and 97.4% for unvaccinated early-stage patients. Then we compared the progression-free survival (PFS) of vaccinated (median PFS 9.0 months) and unvaccinated (median PFS 7.0 months) advanced stage patients (p = 0.815). Advanced NSCLC patients continued to be divided into groups receiving radio-chemotherapy, immunotherapy, and targeted therapy, with no statistical difference in PFS between the groups (p > 0.05). The median overall survival (OS) of vaccinated patients was 20.5 months, and that of unvaccinated patients was 19.0 months (p = 0.478) in advanced NSCLC patients. CONCLUSIONS: COVID-19 vaccination is safe for Chinese NSCLC patients actively receiving different antitumor treatments without increasing the incidence of adverse reactions, and vaccination does not affect cancer patient survival.

Serum iron element: A novel biomarker for predicting PD-1 immunotherapy efficacy.

This study aims to explore the relationship between serum iron by inductively coupled plasma-mass spectrometry (ICP-MS) and the efficacy of immune checkpoint inhibitors (ICIs) and potential mechanism. Totally 113 patients from 233 patients with advanced metastatic lung cancer, esophageal cancer, gastric cancer and colorectal cancer who treated with immunotherapy in Shandong Provincial Hospital were divided into training group (n=68) and validation group (n=45), whose patients were divided into clinical benefit response (CBR) and non-clinical benefit (NCB) by RECIST (v1.1) respectively. We found for the first time that high serum iron level (>1036 µg/L) was a novel biomarker of better PFS (10.13 months vs 7.37 months; p = 0.0015) and OS(16.00 months vs 11.00 months; p = 0.0235) by ROC curve (sensitivity: 78.13 %; Specificity: 80.56 %; p < 0.0001) of CBR (n=32) and NCB (n=36) patients in training group. Interestingly, consistently stable and high serum iron level predicted better efficacy during immunotherapy. Noteworthy, the predictive efficacy of PD-L1 expression was significantly inferior than serum iron (accuracy:63.49% vs 79.41%, p=0.0432), while serum iron detected by spectrophotometry did not predict the efficacy of immunotherapy (p=0.0671) indicating higher sensitivity of ICP-MS. Bioinformatics analysis showed that serum iron could enhance innate immunity and cytokine release and was verified by proteomics that KEGG and GO analysis enriched innate immune and cytokine signaling pathways. Flow cytometry showed that IL-17 (p=0.0002) increased and IL-6 (p=0.0112) decreased after immunotherapy. Based on this, Nomogram with better prediction was constructed by multiple clinical and independent factors. Our results revealed that serum iron is positively associated with ICIs efficacy by enhancing innate immunity and cytokine release in advanced metastatic cancers, and can be a biomarker for predicting ICIs response.

Clinical applications of radiomics in non-small cell lung cancer patients with immune checkpoint inhibitor-related pneumonitis.

Immune checkpoint inhibitors (ICIs) modulate the body's immune function to treat tumors but may also induce pneumonitis. Immune checkpoint inhibitor-related pneumonitis (ICIP) is a serious immune-related adverse event (irAE). Immunotherapy is currently approved as a first-line treatment for non-small cell lung cancer (NSCLC), and the incidence of ICIP in NSCLC patients can be as high as 5%-19% in clinical practice. ICIP can be severe enough to lead to the death of NSCLC patients, but there is a lack of a gold standard for the diagnosis of ICIP. Radiomics is a method that uses computational techniques to analyze medical images (e.g., CT, MRI, PET) and extract important features from them, which can be used to solve classification and regression problems in the clinic. Radiomics has been applied to predict and identify ICIP in NSCLC patients in the hope of transforming clinical qualitative problems into quantitative ones, thus improving the diagnosis and treatment of ICIP. In this review, we summarize the pathogenesis of ICIP and the process of radiomics feature extraction, review the clinical application of radiomics in ICIP of NSCLC patients, and discuss its future application prospects.