Qiyu Fang’s research while affiliated with Tongji University and other places

Introduction Despite the benefit of adjuvant systemic therapy for patients with resected non-small cell lung cancer (NSCLC), the risk of postoperative recurrence remains high. Our objective was to characterize temporal genetic heterogeneity between primary resected and recurrent tumors, and its impact on treatment outcomes. Methods In this study, next-generation sequencing (NGS) testing was performed on tissue specimens and circulating tumor DNA (ctDNA) collected at postoperative recurrence, and results were compared to the genotypes of initial surgical specimens. Results Of forty-five patients with matched primary and post-operative recurrent tumors, EGFR status switched in 17 patients (37.8%) at post-operative recurrence and 28 patients (62.2%) had no genotype change (17 mutant, 11 wild-type). Based on the changes of EGFR status, patients were divided into 4 groups. Following subsequent treatment with EGFR TKI o chemotherapy: In group A, with sustained sensitive mutation, the percentage achieving partial response (PR) was the highest, at 72.2%, the median progression-free survival (PFS) was 17 months, and the median overall survival (OS) was 44.0 months respectively; In group B, with genotype changed from wild-type to mutant, 50% achieved PR, PFS was 10 months, and OS was 35 months; In group C, in which mutant status shifted to wild-type or new co-mutation emerged, the percentage achieving PR was 30%, PFS was 9 months, and OS was 35 months. In group D, with sustained wild type, the percentage achieving PR was 27.3%, PFS was 8 months, and OS was 22 months. Discussion Genotypic shift between paired primary and post-operative recurrent tumors was not infrequent, and this temporal genomic heterogeneity substantially impacted subsequent treatment outcomes.

Circulating extracellular vesicle (EV) PD-L1 is correlated with the occurrence and progression of lung cancer and has great potential as a valuable diagnostic and immunotherapy predictive biomarker. In this work, we propose a fluorescent biosensing method for the sensitive and accurate determination of circulating EV PD-L1. Specifically, after the phosphatidylserine-targeting peptide-assisted magnetic enrichment, a programmable DNA circuit is designed to translate the presence of PD-L1 to the appearance of numerous duplex DNA probes on the circulating EV surface. Upon fructose treatment, these newly formed duplex DNA probes are released from the EV surface to activate the trans-cleavage activity of CRISPR/Cas12a system, which finally produces a significant fluorescence signal. Experimental results reveal that the method not only enables sensitive determination of EV PD-L1 with a detection limit of 67 particles/mL but also demonstrates the potential use in the diagnosis and immunotherapy response prediction of lung cancer in a principle-of-proof study. Therefore, the method may provide a useful tool for EV PD-L1 determination, which may provide valuable information for the precise diagnosis and personalized treatment of lung cancer patients.

Though immunotherapy has to some extent improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), only a few patients benefit. Furthermore, immunotherapy efficacy is affected by inflammatory and nutritional status of patients. To investigate whether dynamics of inflammatory and nutritional indexes were associated with prognosis, two hundred and twenty-three patients were analyzed retrospectively. The inflammatory indexes of interest were neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) while prognostic nutritional index (PNI) and the hemoglobin, albumin, lymphocyte and platelet (HALP) score were considered as nutritional indexes. Patients were divided into high and low groups or into 'increase' and 'decrease' groups based on pre-treatment cut-off values and index dynamics after six-week follow-up respectively. High pre-treatment PLR (OR =2.612) and increase in NLR during follow-up (OR =2.516) were significantly associated with lower objective response rates. Using multivariable analysis, high pre-treatment PLR (HR, 2.319) and increase in SII (HR, 1.731) predicted shorter progression-free survival, while high pre-treatment NLR (HR, 1.635), increase in NLR (HR, 1.663) and PLR (HR, 1.691) and decrease in PNI (HR, 0.611) predicted worse overall survival. The nomogram's c-index in inside validation was 0.718 (95% CI: 0.670-0.766). Our results indicated both nutritional and inflammatory indexes are associated with survival outcomes. Inflammatory indexes were additionally linked to treatment response. Index dynamics are better predictors than baseline values in predicting survival in advanced NSCLC patients receiving PD-1 inhibitor combined with chemotherapy as first-line. This article is protected by copyright. All rights reserved.

Background Low baseline prognostic nutritional index (PNI) scores are associated with poor survival for various malignancies; however, they vary based on the cohort and time resulting in inaccurate results. We determined the predictive value of the PNI score variations in addition to the baseline PNI scores for patients with advanced non-small cell lung cancer (NSCLC) who received programmed cell death protein 1 (PD-1) inhibitor. Methods We retrospectively analysed 115 patients with advanced NSCLC who received PD-1 inhibitor. The median follow-up period was 28 months. Patients were clustered into four groups based on the combined PNI scores (combination of baseline and variation of PNI scores): ΔPNI-L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups. For instance, if PNI scores of patients with high baseline PNI score increased from baseline to 6 weeks after treatment, they were included in the ΔPNI-H-H subgroup. Cox regression models were used to identify the factors associated with survival. Results The baseline PNI score was only related to the overall survival (OS) (P = .026), and not to the overall response rate (ORR) (P = .299) and progression-free survival (PFS) (P = .207). The ORR was associated with the combined PNI scores (P = .017). A multivariable Cox regression analysis confirmed that the combined PNI scores were independent factors for PFS (ΔPNI-L-H, 12 months, hazard ratio [HR] = 0.449, P = .009; ΔPNI-H-L, 14 months, HR = 0.500, P = .019; and ΔPNI-H-H, 17 months, HR = 0.390, P = .012; vs ΔPNI-L-L, 8 months) and OS (ΔPNI-L-H, 27 months, HR = 0.403, P = .019; ΔPNI-H-L, 28 months, HR = 0.369, P = .010; and ΔPNI-H-H, not reached, HR = 0.087, P = .002; vs ΔPNI-L-L, 15 months). Conclusions Patients with high baseline PNI and increased PNI score had the better survival outcome. On dynamic monitoring and comprehensive assessment, the combined PNI scores significantly enhanced the survival predictive ability of patients with NSCLC treated with PD-1 inhibitor.

Objective: To accurately evaluate tumor heterogeneity, make multidimensional diagnosis according to the causes and phenotypes of tumor heterogeneity, and assist in the individualized treatment of tumors. Background: Tumor heterogeneity is one of the most essential characteristics of malignant tumors. In tumor recurrence, development, and evolution, tumor heterogeneity can lead to the formation of different cell groups with other molecular characteristics. Tumor heterogeneity can be characterized by the uneven distribution of tumor cell subsets of other genes between and within the disease site (spatial heterogeneity) or the time change of cancer cell molecular composition (temporal heterogeneity). The discovery of tumor targeting drugs has dramatically promoted tumor therapy. However, the existence of heterogeneity seriously affects the effect of tumor treatment and the prognosis of patients. Methods: The literature discussing tumor heterogeneity and its resistance to tumor therapy was broadly searched to analyze tumor heterogeneity as well as the challenges and solutions for gene detection and tumor drug therapy. Conclusions: Tumor heterogeneity is affected by many factors consist of internal cell factors and cell microenvironment. Tumor heterogeneity greatly hinders effective and individualized tumor treatment. Understanding the fickle of tumors in multiple dimensions and flexibly using a variety of detection methods to capture the changes of tumors can help to improve the design of diagnosis and treatment plans for cancer and benefit millions of patients.

Background: Interventional bronchoscopy exhibits substantial effects for patients with malignant airway obstruction (MAO), while little information is available regarding the potential prognostic factors for these patients. Methods: Between October 31, 2016, and July 31, 2019, a total of 150 patients undergoing interventional bronchoscopy and histologically-confirmed MAO were collected, in which 112 eligible participants formed the cohort for survival study. External validation cohort from another independent institution comprised 33 MAO patients with therapeutic bronchoscopy. The least absolute shrinkage and selection operator regression (LASSO) was applied to the model development dataset for selecting features correlated with MAO survival for inclusion in the Cox regression from which we elaborated the risk score system. A nomogram algorithm was also utilized. Results: In our study, we observed a significant decline of stenosis rate after interventional bronchoscopy from 71.7%±2.1% to 36.6%±2.7% (P<0.001) and interventional bronchoscopy dilated airway effectively. Patients in our study undergoing interventional bronchoscopy had a median survival time of 614.000 days (95% CI: 269.876-958.124). Patients receiving distinct therapeutic methods of interventional bronchoscopy had different prognosis (P=0.022), and patients receiving treatment of electrocoagulation in combination with stenting and electrosurgical snare had worse survival than those receiving other options. Multivariate Cox analysis revealed that nonsmoking status, adenoid cystic carcinoma, and low preoperative stenosis length, as independent predictive factors for better overall survival (OS) of MAO patients. Then, the nomogram based on Cox regression and risk score system based on results from LASSO regression were elaborated respectively. Importantly, this risk score system was proved to have better performance than the nomogram and other single biomarkers such as traditional staging system (area under the curve 0.855 vs. 0.392-0.739). Survival curves showed that patients with the higher risk-score had poorer prognosis than those with lower risk-score (third quantile of OS: 126.000 days, 95% CI: 73.588-178.412 vs. 532.000 days, 95% CI: 0.000-1,110.372; P<0.001). Conclusions: Nonsmoking status, adenoid cystic carcinoma, and low preoperative stenosis length, were independent predictive factors for better OS of MAO patients. We proposed a nomogram and risk score system for survival prediction of MAO patients undergoing interventional bronchoscopy with good performance.

Background: Conventional analysis of single-plex chromogenic immunohistochemistry (IHC) focused on quantitative but spatial analysis. How immune checkpoints localization related to non-small cell lung cancer (NSCLC) prognosis remained unclear. Methods: Here, we analyzed ten immune checkpoints on 1,859 tumor microarrays (TMAs) from 121 NSCLC patients and recruited an external cohort of 30 NSCLC patients with 214 whole-slide IHC. EfficientUnet was applied to segment tumor cells (TCs) and tumor-infiltrating lymphocytes (TILs), while ResNet was performed to extract prognostic features from IHC images. Results: The features of galectin-9, OX40, OX40L, KIR2D, and KIR3D played an un-negatable contribution to overall survival (OS) and relapse-free survival (RFS) in the internal cohort, validated in public databases (GEPIA, HPA, and STRING). The IC-Score and Res-Score were two predictive models established by EfficientUnet and ResNet. Based on the IC-Score, Res-Score, and clinical features, the integrated score presented the highest AUC for OS and RFS, which could achieve 0.9 and 0.85 in the internal testing cohort. The robustness of Res-Score was validated in the external cohort (AUC: 0.80-0.87 for OS, and 0.83-0.94 for RFS). Additionally, the neutrophil-to-lymphocyte ratio (NLR) combined with the PD-1/PD-L1 signature established by EfficientUnet can be a predictor for RFS in the external cohort. Conclusions: Overall, we established a reliable model to risk-stratify relapse and death in NSCLC with a generalization ability, which provided a convenient approach to spatial analysis of single-plex chromogenic IHC.

Background Immunotherapies may prolong the survival of patients with small-cell lung cancer (SCLC) to some extent. The role of forkhead box protein P3 (FOXP3) in tumor microenvironment (TME) remains controversial. We aimed to examine FOXP3-related expression characteristics and prognostic values and to develop a clinically relevant predictive system for SCLC. Methods We enrolled 102 patients with histologically confirmed SCLC at stages I–III. Through immunohistochemistry, we determined the expression pattern of FOXP3 and its association with other immune biomarkers. By machine learning and statistical analysis, we constructed effective immune risk score models. Furthermore, we examined FOXP3-related enrichment pathways and TME traits in distinct cohorts. Results In SCLC, FOXP3 level was significantly associated with status of programmed death-ligand 1 (PD-L1), programmed cell death protein 1 (PD-1), CD4, CD8, and CD3 (p=0.002, p=0.001, p=0.002, p=0.030, and p<0.001). High FOXP3 expression showed longer relapse-free survival (RFS) than the low-level group (41.200 months, 95% CI 26.937 to 55.463, vs 14.000 months, 95% CI 8.133 to 19.867; p=0.008). For tumor-infiltrating lymphocytes (TILs), subgroup analysis demonstrated FOXP3 and PD-1, PD-L1, lymphocyte activation gene-3, CD3, CD4, or CD8 double positive were significantly correlated with longer RFS. We further performed importance evaluation for immune biomarkers, constructed an immune risk score incorporating the top three important biomarkers, FOXP3, TIL PD-L1, and CD8, and found their independently prognostic role to predict SCLC relapse. Better predictive performance was achieved in this immune risk model compared with single-indicator-based or two-indicator-based prediction systems (area under the curve 0.715 vs 0.312–0.711). Then, relapse prediction system integrating clinical staging and immune risk score was established, which performed well in different cohorts. High FOXP3-related genes were enriched in several immune-related pathways, and the close relationships of interleukin-2, CD28 , basic excision repair genes MUTYH , POLD1 , POLD2 , and oxidative phosphorylation related gene cytochrome c oxidase subunit 8A with FOXP3 expression were revealed. Moreover, we found low-immune risk score group had statistically higher activated CD4 ⁺ memory T cells (p=0.014) and plasma cells (p=0.049) than the high-risk group. The heterogeneity of tumor-infiltrating immune cells might represent a promising feature for risk prediction in SCLC. Conclusion FOXP3 interacts closely with immune biomarkers on tumor-infiltrating cells in TME. This study highlighted the crucial prognostic value and promising clinical applications of FOXP3 in SCLC.

Introduction Nowadays, immune checkpoint blockades (ICBs) have been extensively applied in non-small cell lung cancer (NSCLC) treatment. However, the outcome of anti-program death-1/program death ligand-1 (anti-PD-1/PD-L1) therapy is not satisfying in EGFR-mutant lung adenocarcinoma (LUAD) patients and its exact mechanisms have not been fully understood. Since tumor mutation burden (TMB) and tumor immune phenotype had been thought as potential predictors for efficacy of ICBs, we further studied the TMB and immune phenotype in LUAD patients to explore potential mechanisms for poor efficacy of ICBs in EGFR positive mutated patients and to find possible factors that could impact the tumor immune phenotype which might uncover some new therapeutic strategies or combination therapies. Methods We enrolled 223 LUAD patients who underwent surgery in our hospital. We evaluated TMB through targeted panel sequencing. The tumor immune phenotype, which could be divided into non-inflamed, intermediate and inflamed, was determined through immunohistochemistry using formalin-fixed paraffin-embedded samples. Enumeration data were analyzed by Chi-square test or Fisher exact test and shown as number (proportion). Logistic regression model was employed for univariate and multivariate analysis of the association between TMB levels and clinical characteristics. Results The median TMB level was 4.0445 mutations/Mb. Multivariate analysis showed the TMB level was significantly associated with age (P=0.026), gender (P=0.041) and EGFR mutation status (P=0.015), and in EGFR-mutant patients we found a lower proportion of patients with mutated KRAS and BRCA2. Furthermore, we found patients with or without metastatic lesions would have different immune phenotype (P=0.007). And the mutational frequencies of ALK, CDKN2A, MAP2K1, IDH2 and PTEN were significantly different among three immune phenotypes. Conclusion Low TMB level could be the reason for the poor efficacy of ICBs in patients having EGFR mutation. And mutational frequencies of KRAS and BRCA2 were lower in EGFR-mutant patients. Furthermore, ALK, CDKN2A, MAP2K1, IDH2 and PTEN might involve in the formation of immune phenotypes.

Lung cancer is the top reason for cancer-related deaths worldwide. The 5-year overall survival rate of lung cancer is approximately 20% due to the delayed diagnosis and low response rate to regular treatments. Microbiota, both host-microbiota and alien pathogenic microbiota, have been investigated to be involved in a complicated and contradictory relationship with lung cancer initiation, treatments, and prognosis. Disorders of certain host-microbiota and pathogen infection are associated with the risk of lung cancers based on epidemiological evidence, and antibiotics (ATBs) could dramatically impair anti-cancer treatment efficacy, including chemotherapy and immunotherapy. Moreover, probiotics and microbe-mediated drugs are potential approaches to enhance regular anti-tumor treatments. Therefore, the knowledge of the complex dual effect of microbes on lung cancer is beneficial to take their essence and remove their dross. This review offers insight into the current trends and advancements in microbiota or microbial components related to lung cancer.