The increasing use of immune checkpoint inhibitors in tumors has brought new hope of survival to patients with advanced tumors. However, the immune system activated by immune checkpoint inhibitors, mainly activated T‐cells, can attack normal tissues and organs in the body and lead to a variety of adverse effects. In the lung, these attacks can induce checkpoint inhibitor pneumonitis (CIP). CIP is different from known pulmonary interstitial pneumonitis, and has the potential to be fatal if not treated correctly. In this review, we summarize the characteristics of CIP and provide advice on how to manage this disease.

Background: Many immune checkpoint inhibitors (ICIs) have been approved in China to treat non‐small cell lung cancer (NSCLC). However, in the long term, less than 20% of patients benefit from ICIs. To maximize the benefit for NSCLC patients, it is necessary to guide the choice of immunotherapy through biomarkers. Recent studies have shown that gut microbiota can affect tumor response to immunotherapy and might be a potential predictive biomarker. This study analyzed the relationship between intestinal flora structure and metabolomic characteristics in NSCLC and the efficacy of ICIs.Methods: Prospective analysis of samples from 63 patients with advanced NSCLC who attended the Department of Respiratory Medicine of the Peking Union Medical College Hospital from March 2018 to June 2019, and were prescribed programmed cell death 1 (PD‐1) inhibitors, was carried out. The follow‐up deadline was 31 December 2019. Stool samples were collected from all patients before the start of immunotherapy. DNA was extracted from all samples and libraries were constructed. This was followed by sequencing using the Illumina sequencing platform, and results were studied using a biological information data analysis process. We divided the data into two groups based on progression‐free survival (PFS) ≥ six months and PFS < six months.Results: The median PFS was 7.0 months, not reaching the median overall survival (OS). We obtained 373.5 G of original sequencing data. The phyla Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria accounted for most of the bacterial communities in the stool samples studied. Compared with the PFS < six‐month group, the patients in the PFS ≥ six‐month group had significantly higher β‐diversity in the intestinal microbiome at the baseline level. There were also differences in composition between the two groups. Samples in the PFS ≥ six‐month group were rich in Parabacteroides and Methanobrevibacter, while those in the PFS < six‐month group were rich in Veillonella, Selenomonadales, and Negativicutes. The KO, COG, and CAZy databases were used to study functional group protein families, yielding 390 (KO), 264 (COG), and 859 (CAZy) functional group abundances, with significant differences between the two groups. Bacterial metabolites analysis suggested significant differences in the metabolic potential of methanol and methane between the two groups.Conclusions: We found a close correlation between intestinal microbiome β‐diversity and anti‐PD‐1 immunotherapy response in Chinese patients with advanced NSCLC. The intestinal flora composition, functional group protein family, and KEGG metabolism also differed between the two groups. Differences in pathways and flora metabolites were also noted.

Background: Anlotinib is an oral tyrosine kinase inhibitor targeting vascular endothelial growth factor receptor, fibroblast growth factor receptor, platelet‐derived growth factor receptor, and stem cell factor receptor (c‐Kit). In the phase III ALTER‐0303 trial (Clinical Trial Registry ID: NCT 02388919), anlotinib significantly improved overall survival versus placebo in advanced non‐small cell lung cancer patients who had received at least two previous chemotherapy and epidermal growth factor receptor/anaplastic lymphoma kinase targeted therapy regimens. This study summarized adverse event management in this trial.Methods: Patients were randomized (2:1) to anlotinib or placebo up to progression or intolerable toxicity. Adverse events were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events Version 4.0 and managed by investigators. Key strategies for preventing and managing the most common adverse events included patient education, supportive care, and dose modification.Results: Between February 2015 and August 2016, 294 patients received anlotinib. A total of 170 (57.8%) patients received antihypertensive medications for hypertension, 53 (18.0%) patients received levothyroxine for hypothyroidism, 24 (8.2%) patients received fibrates for hypertriglyceridemia, 11 (3.7%) patients took cortisone cream for hand‐foot syndrome, and 38 (12.9%) patients received anti‐diarrheal medications for diarrhea. Dose reduction and drug discontinuation were required in 24 (8.16%) and 31 (10.54%) patients in the anlotinib group, respectively.Conclusion: Anlotinb‐related adverse events could be controlled by patient education, prophylactic measures, early and active intervention, and dose modification.

Immune checkpoint inhibitors (ICIs) are able to reactivate the immune system, thereby enhancing the anti‐tumor effects. However, over‐activated T cells may induce immune‐related adverse events (irAEs). Hematological irAEs are rarely reported which mainly represent monolineage cytopenia or pancytopenia, including autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP), neutropenia and aplastic anemia, sometimes even life‐threatening diseases such as hemophagocytic lymphohistiocytosis. Here, the clinical manifestations of hematological irAEs are summarized and recommendations for diagnosis and treatment proposed.Key points: Significant findings of the study: • Hematological immune‐related adverse events (irAEs) caused by checkpoint inhibitors are rare and may sometimes be life‐threatening. This study summarizes the manifestations of hematological irAEs and proposes preliminary recommendations for diagnosis and treatment.What this study adds: • Much still remains unknown regarding hematological irAEs caused by checkpoint inhibitors. This study delineates the overview of hematological irAEs, and provides practical treatment suggestions, in particular addressing the issue of rechallenge.

Background: The aim of this study was to determine the demographic profile of driver gene alterations, especially low‐frequency gene alterations in Chinese patients with non‐small cell lung cancer (NSCLC).Methods: A total of 7395 Chinese patients with NSCLC were enrolled in the study. Next‐generation sequencing (NGS) was performed on formalin‐fixed paraffin‐embedded specimens collected via either surgical resection or biopsy.Results: The frequent genomic alterations found in the study were EGFR mutations (51.7%), KRAS mutations (13.1%), MET alterations (5.6%; 3.2% copy number gains and 0.5% exon 14 skipping mutation), HER2 alterations (7.0%; 2.0% copy number gains and 5.4% mutations), ALK alterations (7.2%; 3.9% rearrangements), RET rearrangements (1.4%), ROS1 rearrangements (0.9%), and NTRK rearrangements (0.6%). The EGFR mutation rate was found to be significantly higher in women than in men (69.1% vs. 38.5%, P < 0.001), while the KRAS mutation (17.5% vs. 7.3%, P < 0.001) and MET alteration rates (6.5% vs. 4.5%, P < 0.001) were significantly higher in men than in women. The EGFR mutation rate tended to decrease with age in the group aged >40 years, while the KRAS mutation rate tended to increase with age. The HER2 mutation (13.9% vs. 6.7%, P < 0.001) and ALK alteration rates (14.3% vs. 6.9%, P < 0.001) were significantly higher in the group aged <40 years than in groups aged 40 years or older.Conclusions: The frequency of different driver genes was diverse in different age‐gender groups, and the results of this study may assist clinicians in clinical decision‐making and the development of public healthcare strategies in the future.Key points: Significant findings of the study: This study demonstrated that the frequency of different driver genes was diverse in different age‐gender groups. What this study adds It may enable clinicians to make clinical decisions, and assist government, pharmaceutical researchers and insurance companies develop public healthcare strategies.