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.