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: 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.

Immunotherapy has produced durable responses in numerous advanced and metastatic cancers, especially advanced non‐small cell lung carcinoma (NSCLC). However, opportunistic infection has become a major risk for patients who have received immune checkpoint inhibitors (ICIs). Early diagnosis of infection is difficult due to an acute disease course and heterogeneity in clinical manifestation. We retrospectively analyzed four cases with NSCLC who received ICIs and developed opportunistic infections. Two of our cases received antecedent glucocorticoids to treat immune‐related adverse events (irAEs), whereas immunosuppressive agents were not used beforehand in the other cases. We highlight that opportunistic infections complicating immunotherapy can be severe and even fatal. When patients deteriorate after initial remission from irAEs by glucocorticoids, infections should be thoroughly investigated and carefully distinguished from an irAE flare. Bronchoscopy and bronchoalveolar lavage (BAL) are essential. In patients where limited results from traditional microbiological tests have been obtained, next‐generation sequencing (NGS) of BAL fluid is beneficial in guiding a precise antimicrobial treatment. An antipneumocystis prophylaxis may also be considered in selected patients.

Background: Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor with a short replication time and a rapid growth rate. Prognostic factors for SCLC in clinical practice are scarce. Retrospective analysis of 8‐year extensive‐stage SCLC data from the Department Respiratory and Intensive Care Unit, Peking Union Medical College Hospital (Beijing, China) was performed to develop a risk prediction model that can facilitate the identification of extensive‐stage SCLC with differing prognosis in clinical practice.Methods: A retrospective analysis of data from patients with extensive‐stage SCLC at a single‐center from January 2013 to January 2021, including age, sex, ECOG physical score, immunohistochemistry (CgA, Syn, CD56, TTF1, and Ki67), staging, treatment regimen, laboratory examinations, and survival period, was performed. Clinical variables with potential prognostic significance were screened by univariate Cox analysis. Next, multifactor Cox risk prediction regression analysis was performed to establish an extensive‐stage SCLC risk prognostic model. Survival curves and ROC curves for high and low risk groups were plotted according to risk scores. Nomogram and calibration curves were developed to assess the accuracy of the risk prediction model.Results: This study included 300 patients who were diagnosed with extensive‐stage SCLC at our center from January 2013 to January 2021. The most common first presentation was respiratory symptoms, especially cough (162, 54%). The most common extra‐thoracic metastatic organs were bone (36.3%), liver (24.7%), brain (15.7%), and adrenal glands (15.7%). A total of 99% of patients received first‐line systemic therapy, with 86.3% of patients treated with platinum‐etoposide and 10.7% of patients treated with immune checkpoint inhibitor combined with platinum‐etoposide backbone. First‐line progression‐free survival was up to 198 days, and the median OS was 439 days. After Cox regression screening and backward stepwise selection, “time from initial therapy to relapse or progression (PFS1), liver metastases, adrenal metastases, M stage and first‐line treatment pattern” were retained to establish a prognostic model with an AUC value of 0.763. The prognostic model was shown as a nomogram with good agreement between predicted and observed outcomes.Conclusions: The first‐line treatment of SCLC patients admitted to our hospital in the past 8 years was relatively standardized, and the progression‐free survival and OS were slightly longer than those reported in the literature. We developed a prognostic risk score model for extensive‐stage SCLC to calculate individual survival in clinical practice.

Background: Immune checkpoint inhibitors (ICIs) have greatly improved the prognosis and overall management of non‐small cell lung cancer (NSCLC) patients, but in the long term less than 20% of patients benefit from treatment with ICIs. Therefore, it is necessary to guide the choice of immunotherapy population through biomarkers in order to maximize the benefit for NSCLC patients. This article mainly explores the relationship between the efficacy of immunotherapy and specific tumor mutation gene characteristics in an NSCLC population.Methods: This was a prospective analysis of patients with advanced NSCLC who visited the Department of Respiratory Medicine of Peking Union Medical College Hospital from March 2018 to June 2019 and were instructed to use PD‐1 inhibitors. The follow‐up deadline was 31 December 2019. The tumor pathological tissues were tested for tumor mutation genes, and the patients were evaluated for efficacy according to RECIST 1.1. The patients were divided into the durable benefit group (DCB) and the nonsustainable benefit group (NDB). DCB/NDB was used as the outcome variable. Various statistics methods were used to explore the independent predictors of long‐term benefits associated with immunotherapy and to draw a progression‐free survival curve for the relevant predictors.Results: A total of 44 patients were examined for tumor mutation genes in pathological tissues; 20 in the DCB group and 24 in the NDB group. Specific gene mutations occurred in TP53 38.64%, KRAS 31.82%, EGFR 20.45%, BRCA 20.45%, ERBB (excluding EGFR) 18.18%, PTEN 15.91%, CDK4/6 13.64%, POLE 11.36%, MET 11.36%, PIK3CA 9.10%, FGFR 9.10%, BRAF 9.10%, JAK 9.10%, ALK 6.82%, POLD1 4.55%, BLM 4.55%. Chi‐square test results showed that there were statistically significant differences between DCB and NDB groups with eight mutations such as KRAS. Logistic regression showed that the KRAS mutation was statistically significant (P < 0.001). Two accuracy indicators, Random Forest Classification of Mean Decrease Gini and Mean Decrease Accuracy, evaluated the importance of the impact of different gene mutations on the outcome. Under two different measures, the variables were all KRAS mutations. It is suggested that the mutation of the KRAS gene is an independent predictor of the long‐term benefit of immunotherapy.Conclusions: The mutation of KRAS gene in tumor tissues is an independent predictor of the long‐term benefit of immunotherapy, and the predictive ability is better.