Wei Nie

Extensive-stage small-cell lung cancer (ES-SCLC) is associated with a poor prognosis. Although first-line immunochemotherapy improves clinical outcomes, ro

Background: The association of body mass index (BMI) with survival outcomes in patients with advanced non-small cell lung cancer (NSCLC) treated with first-line chemotherapy, immunotherapy, or chemoimmunotherapy is controversial. We aimed to investigate these associations, including associations in male and female patients specifically, in a multicenter cohort study. Methods: We retrospectively analyzed data from seven cohorts comprising 7021 advanced non-small cell lung cancer patients who received chemotherapy (three cohorts), immunotherapy (two cohorts), and chemoimmunotherapy (two cohorts) from five data sources, including a de-identified nationwide (US-based) NSCLC clinico-genomic database and two randomized, double-blind, phase 3 clinical trials. BMI was categorized as underweight, normal weight, overweight, or obese. Underweight patients were excluded because of their small proportion. The primary endpoints were the associations between BMI and progression-free survival (PFS) and overall survival (OS) stratified by treatment type and sex, which were assessed using Kaplan–Meier methods and adjusted Cox modeling. Meta-analyses were performed to combine the adjusted hazard ratios. Results: In the pooled analysis, obesity was significantly associated with improved OS in patients receiving chemotherapy (hazard ratios [HR] = 0.84, 95% confidence interval (CI) 0.76–0.93), but there was no association with PFS (HR = 0.91, 95% CI 0.82–1.02). The association of BMI with OS for patients receiving chemotherapy differed by sex, with an inverse association in men (HR = 0.74, 95% CI 0.64–0.84), but no association observed in women (HR = 0.96, 95% CI 0.81–1.13, P_{interaction =} 0.018). No impact of BMI on OS or PFS was detected in patients receiving immunotherapy or chemoimmunotherapy. Obese patients had the lowest level of tumor mutational burden, similar level of programmed death-ligand 1 expression and ESTIMATE scores. Conclusions: Obesity may be associated with an increased overall survival among male patients treated with chemotherapy, whereas not associated with the outcomes in patients treated with immunotherapy or chemoimmunotherapy.

Background Combining immune checkpoint inhibitors (ICIs) with chemotherapy has become a standard treatment for patients with non-small cell lung cancer (NSCLC) lacking driver gene mutations. Reliable biomarkers are essential for predicting treatment outcomes. Emerging evidence from various cancers suggests that early assessment of serum metabolites could serve as valuable biomarkers for predicting outcomes. This study aims to identify metabolites linked to treatment outcomes in patients with advanced NSCLC undergoing first-line or second-line therapy with programmed cell death 1 (PD-1) inhibitors plus chemotherapy. Method 200 patients with advanced NSCLC receiving either first-line or second-line PD-1 inhibitor plus chemotherapy, and 50 patients undergoing first-line chemotherapy were enrolled in this study. The 200 patients receiving combination therapy were divided into a Discovery set (n=50) and a Validation set (n=150). These sets were further categorized into respond and non-respond groups based on progression-free survival PFS criteria (PFS≥12 and PFS1 and pConclusion Improved outcomes were associated with lower levels of N-(3-Indolylacetyl)-L-alanine in patients with stage IIIB-IV NSCLC lacking driver gene mutations, who underwent first-line or second-line therapy with PD-1 inhibitors combined with chemotherapy. Further exploration of the potential predictive value of pretreatment detection of N-(3-Indolylacetyl)-L-alanine in peripheral blood for the efficacy of combination therapy is warranted. Statement The combination of ICIs and chemotherapy has established itself as the new standard of care for first-line or second-line treatment in patients with advanced NSCLC lacking oncogenic driver alterations. Therefore, identifying biomarkers that can predict the efficacy and prognosis of immunotherapy plus chemotherapy is of paramount importance. Currently, the only validated predictive biomarker is programmed cell death ligand-1 (PD-L1), but its predictive value is not absolute. Our study suggests that the detection of N-(3-Indolylacetyl)-L-alanine in patient serum with untargeted metabolomics prior to combined therapy may predict the efficacy of treatment. Compared with detecting PD-L1 expression, the advantage of our biomarker is that it is more convenient, more dynamic, and seems to work synergistically with PD-L1 expression.

Background: Inflammation is a factor that promotes tumor progression and immunosuppression. Lung immune prognostic index (LIPI) is a non-invasive and easily calculated indicator of inflammation. This study aimed to investigate whether continuous assessment of LIPI has predictive value for chemoimmunotherapy in non-small cell lung cancer (NSCLC) patients receiving first-line programmed cell death 1 (PD-1) inhibitor plus chemotherapy. In addition, the predictive value of LIPI in patients with the negative or low programmed death-ligand (PD-L1) expression level was also explored.Methods: Totally, 146 stage IIIB to IV or recurrent NSCLC patients who received first-line PD-1 inhibitor combined with chemotherapy were enrolled in this study. The LIPI scores were calculated at baseline (PRE-LIPI) and after two cycles of the combined administration (POST-LIPI). This study analyzed the relationship between good/intermediate/poor PRE (POST)-LIPI and objective response rate (ORR), as well as progression-free survival (PFS) using logistic and Cox regression models. In addition, the predictive value of LIPI in patients with the negative or low PD-L1 expression level was explored. To further assess the potential predictive value of continuous assessment of LIPI, the association of sum (LIPI) [sum(LIPI) = PRE-LIPI + POST-LIPI] and PFS was analyzed in the 146 patients.Results: Compared with good POST-LIPI group, significantly lower ORRs were found in intermediate POST-LIPI (P = 0.005) and poor POST-LIPI (P = 0.018) groups. Moreover, intermediate POST-LIPI (P =0.003) and poor POST-LIPI (P < 0.001) were significantly associated with a shorter PFS than good POST-LIPI. Additionally, a higher POST-LIPI score was still significantly associated with poorer treatment efficacy in patients with the negative or low PD-L1 expression level. Moreover, a higher sum (LIPI) score was significantly correlated with a shorter PFS (P = 0.001).Conclusion: Continuous assessment of LIPI might be an effective method for predicting the efficacy of PD-1 inhibitor plus chemotherapy in NSCLC patients. In addition, in patients with the negative or low PD-L1 expression level, it might also have a potential predictive value for therapeutic efficacy to continuously assess LIPI during the treatment.

Objectives: Immune-checkpoint inhibitors (ICIs) combined with chemotherapy are more widely used than monotherapy and have shown better survival in patients with advanced non-small cell lung cancer (NSCLC) without oncogenic driver alterations. The monocyte-to-lymphocyte ratio (MLR) might predict the treatment outcomes of ICI therapy in advanced NSCLC patients but has not yet been investigated. In addition, the cutoff of MLR is controversial. Therefore, the present study aimed to explore the associations between changes in MLR at the initial stage of treatment and clinical outcomes in stage IIIB-IV NSCLC patients receiving first-line PD-1 inhibitor combined with chemotherapy.Methods: The present study included 139 stage IIIB-IV NSCLC patients treated with first-line PD-1 inhibitor combined with chemotherapy. The blood results were assessed 10 days before initiation of PD-1 inhibitor-based combination therapy (time point 1, baseline) and before the third cycle of combined therapy (time point 2). Compared to altered MLR, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) in baseline and in time point 2, patients were divided into decreased MLR/NLR/PLR and increased MLR/NLR/PLR groups. The objective response rate (ORR), progression-free survival (PFS), and the association with the changes in blood indicators were analyzed.Results: A total of 48 patients were categorized in the decreased MLR group and 91 in the increased MLR group. Patients with decreased MLR had a significantly higher ORR in the univariate (P<0.001) and multivariate (P<0.001) Cox proportional hazards models. On the other hand, decreased MLR was significantly associated with prolonged PFS in the univariate (P=0.007) and multivariate (P=0.016) analyses. Next, 91 patients comprised the decreased NLR group and 48 as the increased NLR group. Patients with decreased NLR exhibited high ORR (P=0.001) and prolonged PFS in univariate analysis (P=0.033). Then, 64 patients comprised the decreased PLR group and 75 the increased PLR group. Decreased PLR was significantly associated with high ORR in univariate (P<0.001) and multivariate (P=0.017) analyses. The subgroup analyses showed that decreased MLR was significantly associated with satisfactory outcomes in patients with all PD-L1 expressions.Conclusion: Decreased MLR was associated with high ORR and long PFS and might have a potential predictive value in patients with stage IIIB-IV NSCLC treated with first-line PD-1 inhibitor combined with chemotherapy. In addition, changes in MLR might have predictive value in all PD-L1-expressing populations. Decreased NLR and PLR also showed improved survival, suggesting that changes in NLR and PLR may be complementary to predicting prognosis.

Background: mTOR pathway is known to promote cancer malignancy and influence cancer immunity but is unknown for its role in immune checkpoint inhibitors (ICI) therapy. Methods: Using Memorial Sloan-Kettering Cancer Center dataset (MSKCC), we extracted mTOR pathway gene mutations for stepwise Cox regression in 1661 cancer patients received ICI. We associated the mutation of the gene signature resulted from the stepwise Cox regression with the 1661 patients’ survival. Other 553 ICI-treated patients were collected from 6 cohorts for validation. We also performed this survival association in patients without ICI treatment from MSKCC as discovery (n = 2244) and The Cancer Genome Atlas (TCGA) as validation (n = 763). Pathway enrichment analysis were performed using transcriptome profiles from TCGA and IMvigor210 trial to investigate the potential mechanism. Results: We identified 8 genes involved in mTOR pathway, including FGFR2, PIK3C3, FGFR4, FGFR1, FGF3, AKT1, mTOR, and RPTOR, resulted from stepwise Cox regression in discovery (n = 1661). In both discovery (n = 1661) and validation (n = 553), the mutation of the 8-gene signature was associated with better survival of the patients treated with ICI, which was independent of tumor mutation burden (TMB) and mainly attributed to the missense mutations. This survival association was not observed in patients without ICI therapy. Intriguingly, the mutation of the 8-gene signature was associated with increased TMB and PD1/PD-L1 expression. Immunologically, pathways involved in anti-tumor immune response were enriched in presence of this mutational signature in mTOR pathway, leading to increased infiltration of immune effector cells (e.g., CD8 + T cells, NK cells, and M1 macrophages), but decreased infiltration of immune inhibitory M2 macrophages. Conclusions: These results suggested that mTOR pathway gene mutations were predictive of better survival upon ICI treatment in multiple cancers, likely by its association with enhanced anti-tumor immunity. Larger studies are warranted to validate our findings.

Background: Anlotinib is a novel anti-angiogenesis drug. In non-small cell lung cancer (NSCLC), high body mass index (BMI) was not associated with worse survival in patients treated with bevacizumab compared with those with normal or low BMI. However, it remains unknown whether such an association still exists in NSCLC patients receiving anlotinib therapy. Hence, we conducted this study to investigate whether BMI is associated with clinical outcomes in patients treated with anlotinib for advanced NSCLC.Methods: Data of 554 patients from the ALTER-0302 and the ALTER-0303 trials were analyzed in this study. The patients were classified into non-obesity (BMI 2) and obesity (BMI ≥28 kg/m²) subgroups. The primary endpoint was overall survival (OS). The secondary endpoints included progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). OS was defined as the interval between the first drug administration and death. PFS was defined as the time span from the date of initiating the treatment to the first documented progression or death from any cause, whichever occurred first. ORR included complete response (CR) and partial response (PR).Results: There were 354 patients (63.9%) who received anlotinib in this study. Restricted cubic spline model showed a U-shaped relation between BMI and the risk of death in the anlotinib group. In a multivariable Cox regression model, a trend of worse overall survival was observed in obese patients who received anlotinib compared with placebo (HR, 2.33; 95% CI, 0.77–7.06; p = 0.136). The interaction between BMI stratification and treatment was significant for OS (P for interaction = 0.038).Conclusion: Our results revealed a U-shaped relationship between BMI and risk of death in patients receiving anlotinib for advanced NSCLC. More importantly, obesity (BMI ≥28 kg/m²) might be a potential predictor of use of anlotinib in advanced NSCLC.

Background. Herein, we tried to develop a prognostic prediction model for patients with LUAD based on the expression profiles of lipid metabolism-related genes (LMRGs). Methods. Molecular subtypes were identified by non-negative matrix factorization (NMF) clustering. The overall survival (OS) predictive gene signature was developed and validated internally and externally based on online data sets. Time-dependent receiver operating characteristic (ROC) curve, KaplanMeier curve, nomogram, restricted mean survival time (EMST), and decision curve analysis (DCA) were used to assess the performance of the gene signature. Results. We identified three molecular subtypes in LUAD with distinct characteristics on immune cells infiltration and clinical outcomes. Moreover, we confirmed a seven-gene signature as an independent prognostic factor for patients with LUAD. Calibration and DCA analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the gene signature. In addition, the nomogram showed higher robustness and clinical usability compared with four previously reported prognostic gene signatures. Conclusions. Findings in the present study shed new light on the characteristics of lipid metabolism within LUAD, and the established seven-gene signature can be utilized as a new prognostic marker for predicting survival in patients with LUAD.

The presence of comutations (co-mut+) in DNA damage response and repair (DDR) pathways was associated with improved survival for immune checkpoint inhibitor (ICI) therapy in non-small cell lung cancer (NSCLC). However, it remains unknown whether co-mut+ status could be a predictive biomarker for immunotherapy. We aimed to explore the predictive role of co-mut+ status in the efficacy of ICIs. A total of 853 NSCLC patients from OAK and POPLAR trials were included in the analyses for the relationship between co-mut status and clinical outcomes with atezolizumab treatment. In co-mut+ NSCLC patients, significantly prolonged progression-free survival (PFS) (p = 0.004) and overall survival (OS) (p < 0.001) were observed in atezolizumab over docetaxel. The interaction between co-mut status and treatment was significant for PFS (p for interaction = 0.010) and OS (p for interaction = 0.017). In patients with negative or low programmed death receptor-ligand 1 expression, co-mut+ status still predicted improved clinical outcomes from atezolizumab therapy. These findings suggested that co-mut status may be a promising predictor of ICI therapy in NSCLC.