Neoadjuvant sintilimab plus chemotherapy in EGFR-mutant NSCLC: Phase 2 trial interim results (NEOTIDE/CTONG2104).

The clinical efficacy of neoadjuvant immunotherapy plus chemotherapy remains elusive in localized epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC). Here, we report interim results of a Simon's two-stage design, phase 2 trial using neoadjuvant sintilimab with carboplatin and nab-paclitaxel in resectable EGFR-mutant NSCLC. All 18 patients undergo radical surgery, with one patient experiencing surgery delay. Fourteen patients exhibit confirmed radiological response, with 44% achieving major pathological response (MPR) and no pathological complete response (pCR). Similar genomic alterations are observed before and after treatment without influencing the efficacy of subsequent EGFR-tyrosine kinase inhibitors (TKIs) in vitro. Infiltration and T cell receptor (TCR) clonal expansion of CCR8+ regulatory T (Treg)hi/CXCL13+ exhausted T (Tex)lo cells define a subtype of EGFR-mutant NSCLC highly resistant to immunotherapy, with the phenotype potentially serving as a promising signature to predict immunotherapy efficacy. Informed circulating tumor DNA (ctDNA) detection in EGFR-mutant NSCLC could help identify patients nonresponsive to neoadjuvant immunochemotherapy. These findings provide supportive data for the utilization of neoadjuvant immunochemotherapy and insight into immune resistance in EGFR-mutant NSCLC.

Redoxhigh phenotype mediated by KEAP1/STK11/SMARCA4/NRF2 mutations diminishes tissue-resident memory CD8+ T cells and attenuates the efficacy of immunotherapy in lung adenocarcinoma.

Metabolism reprogramming within the tumor microenvironment (TME) can have a profound impact on immune cells. Identifying the association between metabolic phenotypes and immune cells in lung adenocarcinoma (LUAD) may reveal mechanisms of resistance to immune checkpoint inhibitors (ICIs). Metabolic phenotypes were classified by expression of metabolic genes. Somatic mutations and transcriptomic features were compared across the different metabolic phenotypes. The metabolic phenotype of LUAD is predominantly determined by reductase-oxidative activity and is divided into two categories: redoxhigh LUAD and redoxlow LUAD. Genetically, redoxhigh LUAD is mainly driven by mutations in KEAP1, STK11, NRF2, or SMARCA4. These mutations are more prevalent in redoxhigh LUAD (72.5%) compared to redoxlow LUAD (17.4%), whereas EGFR mutations are more common in redoxlow LUAD (19.0% vs. 0.7%). Single-cell RNA profiling of pre-treatment and post-treatment samples from patients receiving neoadjuvant chemoimmunotherapy revealed that tissue-resident memory CD8+ T cells are responders to ICIs. However, these cells are significantly reduced in redoxhigh LUAD. The redoxhigh phenotype is primarily attributed to tumor cells and is positively associated with mTORC1 signaling. LUAD with the redoxhigh phenotype demonstrates a lower response rate (39.1% vs. 70.8%, p = 0.001), shorter progression-free survival (3.3 vs. 14.6 months, p = 0.004), and overall survival (12.1 vs. 31.2 months, p = 0.022) when treated with ICIs. The redoxhigh phenotype in LUAD is predominantly driven by mutations in KEAP1, STK11, NRF2, and SMARCA4. This phenotype diminishes the number of tissue-resident memory CD8+ T cells and attenuates the efficacy of ICIs.

Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer.

BACKGROUND: Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood. METHODS: TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort. RESULTS: TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor. CONCLUSIONS: Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.

Correlation of distribution characteristics and dynamic changes of gut microbiota with the efficacy of immunotherapy in EGFR-mutated non-small cell lung cancer.

BACKGROUND: The effects of gut microbiota and metabolites on the responses to immune checkpoint inhibitors (ICIs) in advanced epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC) have been studied. However, their effects on EGFR-mutated (EGFR +) NSCLC remain unknown. METHODS: We prospectively recorded the clinicopathological characteristics of patients with advanced EGFR + NSCLC and assessed potential associations between the use of antibiotics or probiotics and immunotherapy efficacy. Fecal samples were collected at baseline, early on-treatment, response and progression status and were subjected to metagenomic next-generation sequencing and ultra-high-performance liquid chromatography-mass spectrometry analyses to assess the effects of gut microbiota and metabolites on immunotherapy efficacy. RESULTS: The clinical data of 74 advanced EGFR + NSCLC patients were complete and 18 patients' fecal samples were dynamically collected. Patients that used antibiotics had shorter progression-free survival (PFS) (mPFS, 4.8 vs. 6.7 months; P = 0.037); probiotics had no impact on PFS. Two dynamic types of gut microbiota during immunotherapy were identified: one type showed the lowest relative abundance at the response time point, whereas the other type showed the highest abundance at the response time point. Metabolomics revealed significant differences in metabolites distribution between responders and non-responders. Deoxycholic acid, glycerol, and quinolinic acid were enriched in responders, whereas L-citrulline was enriched in non-responders. There was a significant correlation between gut microbiota and metabolites. CONCLUSIONS: The use of antibiotics weakens immunotherapy efficacy in patients with advanced EGFR + NSCLC. The distribution characteristics and dynamic changes of gut microbiota and metabolites may indicate the efficacy of immunotherapy in advanced EGFR + NSCLC.

Plasma ddPCR for the detection of MET amplification in advanced NSCLC patients: a comparative real-world study.

Background: Mesenchymal-epithelial transition (MET) amplification is a crucial oncogenic driver and a resistance mechanism to epidermal growth factor receptor tyrosine kinase inhibitors (TKIs) of non-small-cell lung cancer (NSCLC). Fluorescence in situ hybridization (FISH) is the gold standard for MET amplification detection. However, it is inapplicable when tissue samples are unavailable. Objective: This study assessed the performance of plasma droplet digital polymerase chain reaction (ddPCR) in MET amplification detection in NSCLC patients. Design and methods: A total of 87 NSCLC patients were enrolled, and 94 paired tissue and plasma samples were analyzed for the concordance between FISH and plasma ddPCR/tissue next-generation sequencing (NGS) in detecting MET amplification. In addition, the efficacy of patients with MET amplification using different detection methods who were treated with MET-TKIs was evaluated. Results: Plasma ddPCR showed substantial concordance with FISH (74.1% sensitivity, 92.5% specificity, and 87.2% accuracy with a kappa value of 0.68) and outperformed tissue NGS (kappa value of 0.64) in MET amplification detection. Combined plasma ddPCR and tissue NGS showed substantial concordance with FISH (92.3% sensitivity, 89.2% specificity, and an accuracy of 90.1% with a kappa value of 0.77). The efficacy is comparable in these NSCLC patients with MET amplification detected by FISH and plasma ddPCR who were treated with MET-TKIs. Conclusion: Plasma ddPCR is a potentially reliable method for detecting MET amplification in advanced NSCLC patients. Combined plasma ddPCR and tissue NGS might be an alternative or complementary method to MET amplification detection.

PD-L1 expression guidance on sintilimab versus pembrolizumab with or without platinum-doublet chemotherapy in untreated patients with advanced non-small cell lung cancer (CTONG1901): A phase 2, randomized, controlled trial.

No direct comparison has been performed between different programmed cell death-1 (PD-1) inhibitors for first-line treatment in patients with advanced non-small cell lung cancer (NSCLC). The feasibility of using PD-L1-expression-guided immunotherapy remains unknown. In this open-label, phase 2 study (NCT04252365), patients with advanced NSCLC without EGFR or ALK alterations were randomized (1:1) to receive sintilimab or pembrolizumab monotherapy (PD-L1 expression ≥ 50%), or sintilimab or pembrolizumab plus platinum-based chemotherapy (PD-L1 expression < 50%). The sample size was calculated by optimal two-stage design. The primary endpoint was the objective response rate (ORR). The study included 71 patients (sintilimab arms, n = 35; pembrolizumab arms, n = 36) and met its primary endpoint, with a confirmed ORR of 51.4% (18/35) in the sintilimab arms. The confirmed ORR (95% confidence interval) was 46.2% (19.2%, 74.9%) and 42.9% (17.7%, 71.1%) for patients treated with sintilimab and pembrolizumab monotherapy; and 54.5% (32.2%, 75.6%) and 45.4% (24.4%, 67.8%) for those treated with sintilimab- and pembrolizumab-based combination therapies. The median progression-free survival was 6.9 versus 8.1 months for all sintilimab-treated versus all pembrolizumab-treated patients, respectively, in which it was 7.6 versus 11.0 months in monotherapy and 7.4 versus 7.1 months in combination therapies. The median overall survival was 14.9 versus 21.3 months for all sintilimab-treated versus all pembrolizumab-treated patients, respectively, in which it was 14.9 versus 22.6 months in monotherapy and 14.7 versus 17.3 months in combination therapies. Treatment-related adverse events were consistent with safety outcomes of monotherapy and combination therapy in previous phase III studies. However, the incidence of rash was higher with sintilimab than pembrolizumab monotherapy. This is the first prospective phase 2 study to directly compare two anti-PD-1 antibodies as first-line treatment in advanced NSCLC. Sintilimab was efficacious and well-tolerated irrespective of PD-L1 expression level in patients with advanced NSCLC and had similar efficacy and safety to pembrolizumab.

Association of COVID-19 and Lung Cancer: Short-Term and Long-Term Interactions.

Background: COVID-19 has been ravaging the globe for more than three years. Due to systemic immunosuppression of anti-tumor therapy, application of chemotherapy and adverse effects of surgery, the short- and long-term prognosis of cancer patients to COVID-19 are of significant concern. Method: This research included three parts of data. The first part of the data came from the public database that covered Veneto residents. The second part of the data included participants in Guangzhou. The third part of the data was used for MR analysis. We assessed the associations by logistic, linear or Cox regression when appropriate. Result: Lung cancer patients with COVID-19 had shorter progression-free survival (PFS) after COVID-19 (Model II: HR: 3.28, 95% CI: 1.6~6.72; Model III: HR: 3.39, 95% CI: 1.45~7.95), compared with lung cancer patients without COVID-19. Targeted therapy patients recovered from SARS-CoV-2 infection more quickly (Model I: ß: -0.58, 95% CI: -0.75~-0.41; Model II: ß: -0.59, 95% CI: -0.76~-0.41; Model III: ß: -0.57; 95% CI: -0.75~-0.40). Conclusions: PFS in lung cancer patients is shortened by COVID-19. The outcome of COVID-19 in lung cancer patients was not significantly different from that of the healthy population. In lung cancer patients, targeted therapy patients had a better outcome of COVID-19, while chemotherapy patients had the worst.