The invasive capacity of lung adenocarcinoma (LUAD) is an important factor influencing patients’ metastatic status and survival outcomes. However, there is still a lack of suitable biomarkers to evaluate tumor invasiveness. LUAD molecular subtypes were identified by unsupervised consistent clustering of LUAD. The differences in prognosis, tumor microenvironment (TME), and mutation were assessed among different subtypes. After that, the invasion-related gene score (IRGS) was constructed by genetic differential analysis, WGCNA analysis, and LASSO analysis, then we evaluated the relationship between IRGS and invasive characteristics, TME, and prognosis. The predictive ability of the IRGS was verified by in vitro experiments. Next, the “oncoPredict” R package and CMap were used to assess the potential value of IRGS in drug therapy. The results showed that LUAD was clustered into two molecular subtypes. And the C1 subtype exhibited a worse prognosis, higher stemness enrichment activity, less immune infiltration, and higher mutation frequency. Subsequently, IRGS developed based on molecular subtypes demonstrated a strong association with malignant characteristics such as invasive features, higher stemness scores, less immune infiltration, and worse survival. In vitro experiments showed that the higher IRGS LUAD cell had a stronger invasive capacity than the lower IRGS LUAD cell. Predictive analysis based on the “oncoPredict” R package showed that the high IRGS group was more sensitive to docetaxel, erlotinib, paclitaxel, and gefitinib. Among them, in vitro experiments verified the greater killing effect of paclitaxel on high IRGS cell lines. In addition, CMap showed that purvalanol-a, angiogenesis-inhibitor, and masitinib have potential therapeutic effects in the high IRGS group. In summary we identified and analyzed the molecular subtypes associated with the invasiveness of LUAD and developed IRGS that can efficiently predict the prognosis and invasive ability of the tumor. IRGS may be able to facilitate the precision treatment of LUAD to some extent.

Objective To construct and validate a prognostic model for lung adenocarcinoma based on bioinformatics of metabolic genes. Methods Lung adenocarcinoma-related data from The Cancer Genome Atlas (TCGA) database and gene expression omnibus (GEO) were acquired, and LASSO regression was used to construct multi-gene prognostic models and calculate risk-score (RS). Univariate and multivariate Cox independent prognostic analysis was performed. The area under receiver operating characteristic (ROC) curve (AUC) of the model was evaluated by ROC curve and survival analysis was performed. Nomogram were constructed to evaluate the feasibility of the model, and metabolic gene functional enrichment analysis was performed by GSEA. Tumor immune estimation resource (TIMER) database was used to analyze the correlation of patients RS with immune cell infiltration and with the expression of immune checkpoint molecules. Results The TCGA database was used to construct a prognostic model for lung adenocarcinoma based on 18 metabolism-related genes, and RS was used as an independent prognostic factor. The area under the ROC curve was 0.713. Survival analysis showed that overall survival was higher in the low-risk group compared to the high-risk group, and the prognostic model was associated with infiltration of immune cells and with the expression of immune checkpoint molecules. Conclusion RS is an independent prognostic factor in the prognostic model of lung adenocarcinoma with metabolic genes, suggesting a high prognostic value of this model.

Object Focus on immune-related gene pairs (IRGPs) and develop a prognostic model to predict the prognosis of patients with lung adenocarcinoma (LUAD). Methods First, the LUAD patient dataset was downloaded from The Cancer Genome Atlas database, and paired analysis of immune-related genes was subsequently conducted. Then, LASSO regression was used to screen prognostic IRGPs for building a risk prediction model. Meanwhile, the Gene Expression Omnibus database was used for external validation of the model. Next, the clinical predictive power of IRGPs features was assessed by uni-multivariate Cox regression analysis, the infiltration of key immune cells in high and low IRGPs risk groups was analyzed with CIBERSORT, quanTIseq, and Timer, and the key pathways enriched for IRGPs were assessed using the Kyoto Encyclopedia of Genes and Genomes. Finally, the expression and related functions of key immune cells and genes were verified by immunofluorescence and cell experiments of tissue samples. Results It was revealed that the risk score of 19 IRGPs could be used as accurate indicators to evaluate the prognosis of LUAD patients, and the risk score was mainly related to T cell infiltration based on CIBERSORT analysis. Two genes of IRGPs, IL6, and CCL2, were found to be closely associated with the expression of PD-1/PD-L1 and the function of T-cells. Depending on the results of tissue immunofluorescence, IL6, CCL2, and T cells were highly expressed in the LUAD tissues of patients. Furthermore, IL6 and CCL2 were positively correlated with the expression of T cells. Besides, qRT-PCR assay in four different LUAD cells proved that IL6 and CCL2 were positively correlated with the expression of PD-L1 (P < .001). Conclusions Based on 19 IRGPs, an effective prognosis model was established to predict the prognosis of LUAD patients. In addition, IL6 and CCL2 are closely related to the function of T-cells.

Prior researches indicate that peripheral blood CD4 levels have an inverse correlation with distant tumor metastasis in non-small cell lung cancer (NSCLC). However, the linear relationship between CD4 and distant metastasis lacks clarity. Hence, the objective of this study was to ascertain the linear relationship between CD4 and distant metastasis in NSCLC patients. This retrospective study analyzed clinical and laboratory data of NSCLC patients between March 2016 and July 2022 at the Cancer Hospital of Anhui University of Technology. The study first applied a generalized summation model and smoothing curve fitting to determine if there was a linear relationship between CD4 and NSCLC metastasis. Secondarily, univariate logistic analysis and multiple linear regression were used to analyze the odds ratio (OR) of CD4 as a continuous variable, dichotomous variable, and trichotomous variable when predicting NSCLC metastasis. In addition, stratified and subgroup analyses were conducted to assess the reliability of CD4 in different NSCLC patient populations. The study included a total of 213 NSCLC patients, among which 122 had distant metastasis and 91 had no metastasis. The smoothing curve fitting analysis revealed a U-shaped relationship between CD4 and NSCLC metastasis with a threshold effect. The univariate logistic analysis indicated that continuous CD4 expression was not significantly associated with NSCLC metastasis (P = 0.051); however, high levels of CD4 expression (≥ 35.06

Objective To investigate the effect of artesunate (ART) on T lymphocyte immune function in patients with lung cancer. Methods Fifteen healthy people (NC group) and twenty-one lung cancer patients (LC group) were randomly selected to collect their clinical information and isolate peripheral blood mononuclear cells (PBMCs). After 24 hour-treatment of PBMCs with ART, the median lethal concentration (LC50) and the optimal concentration of ART induced high expression of CD39 and CD279 in T cell membrane were determined by flow cytometry (FCM). Following the induction of ART with the best concentration, the expression levels of CD39 and CD279 on CD8+ and CD4+ T cells in NC group, and the expression levels of CD39, CD279, CD38, CD28, granzyme B (GrzB), perforin (PerF), interferon γ(IFN-γ) and interleukin-2 (IL-2) on CD8+ and CD4+ T cells in LC group were detected by FCM. Results LC50 and optimal concentration of ART were 522 μmol/L and 200 μmol/L, respectively. Compared with the NC group, the baseline expression levels of CD279 on CD8+ and CD4+ T cells in LC group was significantly higher. Moreover, the expression levels of CD39 increased significantly after inducing 200 μmol/L ART, in the CD8+ and CD4+ T cell of NC groups; In CD8+ and CD4+ T cells of LC group, the expression of CD39, CD279 and GrzB increased significantly, while that of IL-2 decreased markedly. No significant difference was detected in the expression levels of CD38, CD28, IFN-γ and PerF. The clinical factors that promote the expression of CD39 on CD8+ T cells induced by ART showed no radiotherapy. The clinical factors that promote the expression of CD279 on CD8+ T cells induced by ART include age>60 years old, lymphocyte count>1.26×109/L, NLR<5, radiotherapy, 0.29×109/L ≤monocyte count ≤0.95×109/L. Conclusion The expression of CD279 on T lymphocytes is higher in lung cancer patients; ART induces the upregulation of CD8+ and CD4+T cells CD39, CD279 and GrzB in lung cancer patients, thus regulating the immune function of T cell subsets.

Objective To investigate the relationship between the neutrophil-to-lymphocyte ratio (NLR) of patients with non-small cell lung cancer (NSCLC) and their risk of developing brain metastases after adjusting for confounding factors. Methods A retrospective observational study of the general data of patients with NSCLC diagnosed from January 2016 to December 2020. Multivariate logistic regression was used to calculate the dominance ratio (OR) with 95% confidence interval (CI) for NLR and NSCLC brain metastases with subgroup analysis. Generalized summation models and smoothed curve fitting were used to identify whether there was a nonlinear relationship between them. Results In all 3 models, NLR levels were positively correlated with NSCLC brain metastasis (model 1: OR: 1.12, 95% CI: 1.01-1.23, P = .025; model 2: OR: 1.16, 95% CI: 1.04-1.29, P = .007; model 3: OR: 1.20, 95% CI: 1.05-1.37, P = .006). Stratified analysis showed that this positive correlation was present in patients with adenocarcinoma (LUAD) and female patients (LUAD: OR: 1.30, 95% CI: 1.10-1.54, P = .002; female: OR: 1.52, 95% CI: 1.05-2.20, P = .026), while there was no significant correlation in patients with squamous carcinoma (LUSC) and male patients (LUSC: OR:0.76,95% CI:0.38- 1.53, P = .443; male: OR:1.13, 95% CI:0.95-1.33, P = .159). Conclusion This study showed that elevated levels of NLR were independently associated with an increased risk of developing brain metastases in patients with NSCLC, and that this correlation varied by TYPE and SEX, with a significant correlation in female patients and patients with LUAD.

Background To determine the populations who suitable for surgical treatment in elderly patients (age ≥ 75 y) with IA stage. Methods The clinical data of NSCLC patients diagnosed from 2010 to 2015 were collected from the SEER database and divided into surgery group (SG) and no-surgery groups (NSG). The confounders were balanced and differences in survival were compared between groups using PSM (Propensity score matching, PSM). Cox regression analysis was used to screen the independent factors that affect the Cancer-specific survival (CSS). The surgery group was defined as the patients who surgery-benefit and surgery-no benefit according to the median CSS of the no-surgery group, and then randomly divided into training and validation groups. A surgical benefit prediction model was constructed in the training and validation group. Finally, the model is evaluated using a variety of methods. Results A total of 7297 patients were included. Before PSM (SG: n = 3630; NSG: n = 3665) and after PSM (SG: n = 1725, NSG: n = 1725) confirmed that the CSS of the surgery group was longer than the no-surgery group (before PSM: 82 vs. 31 months, P < .0001; after PSM: 55 vs. 39 months, P < .0001). Independent prognostic factors included age, gender, race, marrital, tumor grade, histology, and surgery. In the surgery cohort after PSM, 1005 patients (58.27%) who survived for more than 39 months were defined as surgery beneficiaries, and the 720 patients (41.73%) were defined surgery-no beneficiaries. The surgery group was divided into training group 1207 (70%) and validation group 518 (30%). Independent prognostic factors were used to construct a prediction model. In training group (AUC = .678) and validation group (AUC = .622). Calibration curve and decision curve prove that the model has better performance. Conclusions This predictive model can well identify elderly patients with stage IA NSCLC who would benefit from surgery, thus providing a basis for clinical treatment decisions.

The aim of this retrospective study is to evaluate the impact on efficacy and safety between epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) alone and in combination with Shenqi Fuzheng injection (SFI) in patients with advanced NSCLC harboring epidermal growth factor receptor (EGFR) activating mutations. Retrospectively, information of 88 patients receiving EGFR-TKIs as first-line targeted treatment or in combination with SFI in the Affiliated Drum Tower Hospital of Nanjing University Medical College and the Affiliated Cancer Hospital of Anhui University of Science and Technology was collected. The primary endpoint was to assess progression-free survival (PFS) and safety of EGFR-TKIs alone or in combination with SFI. Between January 2016 and December 2019, a total of 88 patients were enrolled in this research, including 50 cases in the EGFR-TKIs single agent therapy group and 38 cases in the SFI combined with EGFR-TKIs targeted-therapy group. The median PFS (mPFS) of monotherapy group was 10.50 months (95

OBJECTIVE:Patients with lung cancer are at risk of radiation pneumonia (RP) after receiving radiotherapy. We established a prediction model according to the critical indicators extracted from radiation pneumonia patients.MATERIALS AND METHODS:74 radiation pneumonia patients were involved in the training set. Firstly, the clinical data, hematological and radiation dose parameters of the 74 patients were screened by Logistics regression univariate analysis according to the level of radiation pneumonia. Next, Stepwise regression analysis was utilized to construct the regression model. Then, the influence of continuous variables on RP was tested by smoothing function. Finally, the model was externally verified by 30 patients in validation set and visualized by R code.RESULTS:In the training set, there was 40 patients suffered≥ level 2 acute radiation pneumonia. Clinical data (diabetes), blood indexes (lymphocyte percentage, basophil percentage, platelet count) and radiation dose (V15 > 40%, V20 > 30%, V35 >18%, V40 > 15%) were related to radiation pneumonia (P < 0.05). Particularly, stepwise regression analysis indicated that the history of diabetes, the basophils percentage, platelet count and V20 could be the best combination used for predicting radiation pneumonia. The column chart was obtained by fitting the regression model with the combined indicator. The receiver operating characteristic (ROC) curve showed that the AUC in the development term was 0.853, the AUC was 0.656 in the validation term. And calibration curves of both groups showed the high stability in efficiently diagnostic. Furthermore, the DCA curve showed that the model had a satisfactory positive net benefit.CONCLUSION:The combination of the basophils percentage, platelet count and V20 is available to build a predictive model of radiation pneumonia for patients with advanced lung cancer.

BACKGROUND:The development of human tumors is associated with the abnormal expression of various functional genes, and a massive tumor-based database needs to be deeply mined. Based on a multigene prediction model, access to urgent prognosis of patients has become possible. MATERIALS AND METHODS:We selected three RNA expression profiles (GSE32863, GSE10072, and GSE43458) from the lung adenocarcinoma (LUAD) database of the Gene Expression Omnibus (GEO) and analyzed the differentially expressed genes (DEGs) between tumor and normal tissue using GEO2R program. After that, we analyzed the transcriptome data of 479 LUAD samples (54 normal tissue samples and 425 cancer tissue samples) and their clinical follow-up data from the (TCGA) database. Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) were used to assess the prediction model. Multivariate Cox analysis was used to identify independent predictors. TCGA pancreatic adenocarcinoma datasets were used to establish a nomogram model. RESULTS:We found 98 significantly prognosis-related genes using KM and COX analysis, among which six genes were found to be the DEGs in GEO. Using multivariate analysis, it was found that a single gene could not be used as an independent predictor of prognosis. However, the risk score calculated by weighting these six genes could serve as an independent prognosis predictor. COX analysis performed with multiple covariates such as age, gender, tumor stage, and TNM typing showed that risk score could still be utilized as an independent risk factor for patient survival rate (p = 0.013) and had an applicable reliability (area under the curve, AUC = 0.665). By combining risk score and various clinical features, the nomogram model was constructed, which had been proven to have high consistency for the prediction of 3- and 5-year survival rate (concordance = 0.751) and high accuracy as tested by ROC (AUC = 0.71;AUC = 0.708). CONCLUSION:We proposed a method to predict the prognosis of LUAD by weighting multiple genes and constructed a nomogram model suitable for the prognostic evaluation of LUAD, which could provide a new tool for the identification of therapeutic targets and the efficacy evaluation of LUAD.

Enhancing sensitivity of carcinoma to sorafenib (Sor) is critical to overcome the limits of high frequency resistance and moderate efficiency during chemotherapy for advanced hepatocellular carcinoma (HCC). Here, we promote sensitivity of HCC to Sor by combination with Artesunate (Art), a derivative of artemisinin extracted from Chinese medical herb. The positive synergy of Art on inhibiting HCC growth contributes 48% dosage of Sor to reduce tumor cell viability in vitro and tumor size in vivo. Mechanically, in spite of effective suppression of RAF/MEK/ERK pathway, Sor is not able to eliminate chemoresistance of HCC driven by PI3K/AKT/mTOR pathway, while Art inhibits phosphorylation of AKT and mTOR significantly. Furthermore, combination with Art and Sor further improves apoptosis of HCC by dual inhibition of both pathways. Our study reveals a function of Art that induces HCC apoptosis via PI3K/AKT/mTOR pathway inhibition and suggests a potential therapeutic regimen of combination with Art and SOR against advanced HCC.

e21179 Background: Apatinib, an oral VEGFR2 inhibitor, has been proved a confirming activity for inhibiting tumor growth on lung cancer in vitro and in vivo tests.This prospective study tried to investigate the efficacy and safety of apatinib plus S-1 as second- or third-line treatment in patients with advanced squamous cell lung carcinoma. Methods: In this open-label single-arm study, eligible patients (pts) had histologically or cytologically confirmed advanced squamous cell lung cancer and had documented disease progression after at least one platinum-based chemotherapy. Patients were treated oral apatinib (250-500 mg daily) and S-1(60mg/m2 D1-14) (allowable dose adjustment) , repeated every 3 weeks. Treatment will be continued until disease progression or unacceptable toxicity occurs. Results: From August 19, 2016 to January 29, 2018, 27 pts were enrolled. there were 19 pts available for efficiency evaluation. Among them, 7 achieved partial response (PR),10 had stable disease (SD), and 2 had progressive disease(PD), resulting in an overall response rate of 36.8% and a disease control rate of 89.5%. The mPFS is 5.0m(95%CI:3.4-6.54), The real mPFS will be longer as this study continues. The common adverse events (AEs) were hypertension (n = 5, 18.5%), fatigue (n = 4, 14.8%), hand-foot skin syndrome (n = 6, 22.2%) and pulmonary infection (n = 4, 14.8%).In addition, serious adverse events (SAEs) were hypertension (n = 2, 7.4%),diarrhea (n = 1, 3.7%), proteinuria (n = 1, 3.7%), thrombocytopenia (n = 2, 7.4%),hand-foot skin syndrome (n = 1, 3.7%), pulmonary infection (n = 3, 11.1%). Others like hoarse voice, oral ulcers, constipation, anemia, elevated bilirubin, leukopenia appeared in 1 of 27 patients respectively and could be better controlled. Overall incidence of AEs and SAEs was 74.1%, 37.0% respectively. No treatment-related death occurred. Conclusions: Apatinib plus S-1 showed promising efficacy and acceptable toxicity in advanced squamous cell lung carcinoma. The research is still ongoing. The results are subject to the verification of phase Ⅲ randomized clinical trials. Clinical trial information: ChiCTR-OPC-16009048 Clinical trial information: ChiCTR-OPC-16009048.