Values in Action: Unveiling the Impact of Self-Transcendence and Self-Enhancement on Domestic Consumption Choices.

Against the backdrop of a global emphasis on supporting local businesses and fostering domestic consumption, this study aims to shed light on the influence of personal values on the intentions behind domestic-product consumption. Drawing from the Schwartz value theory, we explore how values of self-transcendence, which embody benevolence and universalism, versus self-enhancement, characterized by a focus on power and achievement, influence consumer behavior. Utilizing data from the Chinese Social Survey (CSS2021) and a survey of 316 participants, structural equation modeling and Dematel analysis are employed to reveal causal relationships between values and consumption intentions. We reveal a dichotomous impact of these value orientations. Self-transcendence values are found to positively affect domestic consumption intentions by enhancing awareness of consequence and ascription of responsibility, thereby strengthening personal norms. In contrast, self-enhancement values tend to impede these intentions. By integrating the Norm-Activation Model (NAM), this study comprehensively uncovers the unique mechanism through which values activate personal norms and subsequently encourage the consumption of domestic products. It enriches the body of research related to values and domestic consumption and offers pertinent recommendations for promoting local enterprises' products.

Long-term efficacy, safety, and cumulative retention rate of antitumor necrosis factor-alpha treatment for patients with Behcet's uveitis: A systematic review and meta-analysis.

AIM: This study aims to evaluate the long-term efficacy, safety, and cumulative retention rate of antitumor necrosis factor-alpha (anti-TNF-α) therapy for patients with Behcet's uveitis (BU) using meta-analysis. METHODS: We searched the Web of Science and PubMed databases for eligible studies up to December 1, 2022. The quality of each identified study was assessed using the Joanna Briggs Institute's case series literature quality assessment tool. Statistical analysis was conducted using Stata 16.0 software with a random-effects model. RESULTS: Twelve studies comprising 1156 patients with BU were included in our analysis. We found that 85.0% of patients achieved ocular inflammation remission after receiving anti-TNF-α treatment, with a 95% confidence interval (CI) ranging from 78.7% to 90.5%. Additionally, 77.4% (95% CI: 57.5%-92.5%) experienced an improvement in visual acuity (VA). Moreover, the pooled dose reduction of glucocorticoids (GCs) was 11.08 mg (95% CI: -13.34 mg to -8.83 mg). Throughout the follow-up period, the cumulative retention rate of the medication was 67.3% (95% CI: 53.7%-79.6%). Serious adverse events occurred in 5.8% (95% CI: 3.1%-8.9%) of cases, with the three most common types being severe infusion or injection reactions (2.7%; 95% CI: 0.8%-5.4%), tuberculosis (1.3%; 95% CI: 0.0%-3.9%), and bacterial pneumonia (1.3%; 95% CI: 0.1%-3.4%). Subgroup analysis revealed that ocular inflammation remission rates were 89.3% (95% CI: 81.2%-95.5%) for adalimumab treatment and 83.7% (95% CI: 75.3%-90.8%) for infliximab treatment. The drug retention rate after adalimumab therapy was 70.3% (95% CI: 62.0%-78.0%) compared to 66.4% (95% CI: 48.6%-82.2%) for infliximab treatment. Furthermore, the incidence of severe infusion or injection reactions was 2.2% (95% CI: 0.1%-5.8%) following adalimumab treatment and 3.5% (95% CI: 0.7%-7.7%) following infliximab treatment. CONCLUSIONS: Anti-TNF-α therapy represents an effective treatment for BU patients with favorable safety profile and high drug retention rate and a potential advantage of adalimumab over infliximab in terms of ocular inflammation remission, drug retention, and the incidence of severe infusion or injection reactions.

The Effects of Drug Exposure and Single Nucleotide Polymorphisms on Aaptinib-Induced Severe Toxicities in Solid Tumors.

To investigate the value of drug exposure and host germline genetic factors in predicting apatinib (APA)-related toxicities. METHOD: In this prospective study, plasma APA concentrations were quantified using liquid chromatography with tandem mass spectrometry, and 57 germline mutations were genotyped in 126 advanced solid tumor patients receiving 250 mg daily APA, a vascular endothelial growth factor receptor II inhibitor. The correlation between drug exposure, genetic factors, and the toxicity profile was analyzed. RESULTS: Non-small cell lung cancer (NSCLC) was more prone to APA-related toxicities and plasma concentrations of APA, and its main metabolite M1-1 could be associated with high-grade adverse events (AEs) (P < 0.01; M1-1, P < 0.01) and high-grade antiangiogenetic toxicities (APA, P = 0.034; P < 0.05), including hypertension, proteinuria, and hand-foot syndrome, in the subgroup of NSCLC. Besides, CYP2C9 rs34532201 TT carriers tended to have higher levels of APA (P < 0.001) and M1-1 (P < 0.01), whereas CYP2C9 rs1936968 GG carriers were predisposed to higher levels of M1-1 (P < 0.01). CONCLUSION: Plasma APA and M1-1 exposures were able to predict severe AEs in NSCLC patients. Dose optimization and drug exposure monitoring might need consideration in NSCLC patients with CYP2C9 rs34532201 TT and rs1936968 GG. SIGNIFICANCE STATEMENT: Apatinib is an anti-VEGFR2 inhibitor for the treatment of multiple cancers. Though substantial in response, apatinib-induced toxicity has been a critical issue that is worth clinical surveillance. Few data on the role of drug exposure and genetic factors in apatinib-induced toxicity are available. Our study demonstrated a distinct drug-exposure relationship in NSCLC but not other tumors and provided invaluable evidence of drug exposure levels and single nucleotide polymorphisms as predictive biomarkers in apatinib-induced severe toxicities.

Pan-Immune-Inflammatory Value in Patients with Non-Small-Cell Lung Cancer Undergoing Neoadjuvant Immunochemotherapy.

Background: We aimed to investigate the predictive value of a systematic serum inflammation index, pan-immune-inflammatory value (PIV), in pathological complete response (pCR) of patients treated with neoadjuvant immunotherapy to further promote ideal patients' selection. Methods: The clinicopathological and baseline laboratory information of 128 NSCLC patients receiving neoadjuvant immunochemotherapy between October 2019 and April 2022 were retrospectively reviewed. We performed least absolute shrinkage and selection operator (LASSO) algorithm to screen candidate serum biomarkers for predicting pCR, which further entered the multivariate logistic regression model to determine final biomarkers. Accordingly, a diagnostic model for predicting individual pCR was established. Kaplan-Meier method was utilized to estimate curves of disease-free survival (DFS), and the Log rank test was analyzed to compare DFS differences between patients with and without pCR. Results: Patients with NSCLC heterogeneously responded to neoadjuvant immunotherapy, and those with pCR had a significant longer DFS than patients without pCR. Through LASSO and the multivariate logistic regression model, PIV was identified as a predictor for predicting pCR of patients. Subsequently, a diagnostic model integrating with PIV, differentiated degree and histological type was constructed to predict pCR, which presented a satisfactory predictive power (AUC, 0.736), significant agreement between actual and our nomogram-predicted pathological response. Conclusion: Baseline PIV was an independent predictor of pCR for NSCLC patients receiving neoadjuvant immunochemotherapy. A significantly longer DFS was achieved in patients with pCR rather than those without pCR; thus, the PIV-based diagnostic model might serve as a practical tool to identify ideal patients for neoadjuvant immunotherapeutic guidance.

Prognostic value of L4 lymph node dissection during video-assisted thoracoscopic surgery in patients with left-sided non-small cell lung cancer: a single-center, retrospective cohort study.

Background: Lymph node dissection (LND) is crucial procedure during radical resection of non-small cell lung cancer (NSCLC), but the prognostic value of L4 LND remains elusive. To investigate the prognostic value of L4 LND in patients with left-side NSCLC who underwent video-assisted thoracoscopic surgery (VATS). Methods: Three hundred twelve patients who underwent VATS between Jan. 2007 and Dec. 2016 were reviewed. Of those, 119 underwent L4 LND (L4D+), whereas the other 193 patients did not (L4D-). The inclusion criteria were as follows: patients diagnosed with primary left-sided NSCLC who underwent VATS lobectomy combined with LND; patients subjected to R0 resection and tumor pathological stage T1-4N0-2M0. The primary endpoint was overall survival (OS). OS was calculated from the operation date to the date of death. The chi-square test was used for categorical variables, and a t test was used for continuous variables. Results: A total of 119 patients underwent L4 LND, and the procedure was more likely to be performed on upper lobe tumors (P=0.019). Patient distributions with respect to age, gender, smoking history, clinical stage, adjuvant therapy, tumor differentiation and tumor size were well balanced between two groups. More lymph nodes (LNs) were dissected in the L4D+ group than in the L4D- group (P<0.001). The rate of metastasis to L4 lymph nodes was 9.2%, which was comparable between patients with upper and lower lobe tumors (8.9% vs. 10.0%, P=1.000). The L4D+ group exhibited a significantly better OS than the L4D- group (median OS: undefined vs. 130 months, HR 0.47; 95% CI: 0.31-0.72; P=0.002). Multivariate analysis showed that L4 LND was an independent factor for OS. However, OS did not significantly differ between the two groups of cT1aN0 and cT1bN0 patients (OS: HR 0.44; 95% CI: 0.18-1.06; P=0.12). Conclusions: L4 LND is recommended for patients with left-sided NSCLC as an essential component of radical resection. The role of L4 LND in cT1a-bN0 disease warrants further study.

Invasiveness assessment by artificial intelligence against intraoperative frozen section for pulmonary nodules ≤ 3 cm.

PURPOSE: To investigate the performance of an artificial intelligence (AI) algorithm for assessing the malignancy and invasiveness of pulmonary nodules in a multicenter cohort. METHODS: A previously developed deep learning system based on a 3D convolutional neural network was used to predict tumor malignancy and invasiveness. Dataset of pulmonary nodules no more than 3 cm was integrated with CT images and pathologic information. Receiver operating characteristic curve analysis was used to evaluate the performance of the system. RESULTS: A total of 466 resected pulmonary nodules were included in this study. The areas under the curves (AUCs) of the deep learning system in the prediction of malignancy as compared with pathological reports were 0.80, 0.80, and 0.75 for all, subcentimeter, and solid nodules, respectively. Additionally, the AUC in the AI-assisted prediction of invasive adenocarcinoma (IA) among subsolid lesions (n = 184) was 0.88. Most malignancies that were misdiagnosed by the AI system as benign diseases with a diameter measuring greater than 1 cm (26/250, 10.4%) presented as solid nodules (19/26, 73.1%) on CT. In an exploratory analysis involving nodules underwent intraoperative pathologic examination, the concordance rate in identifying IA between the AI model and frozen section examination was 0.69, with a sensitivity of 0.50 and specificity of 0.97. CONCLUSION: The deep learning system can discriminate malignant diseases for pulmonary nodules measuring no more than 3 cm. The AI model has a high positive predictive value for invasive adenocarcinoma with respect to intraoperative frozen section examination, which might help determine the individualized surgical strategy.

Neoadjuvant Immunotherapy in Oncogene-Positive Non-Small Cell Lung Cancer: A Multicenter Study.

BACKGROUND: Preoperative immunotherapy has shed light on the management of resectable non-small cell lung cancer (NSCLC). However, whether neoadjuvant immunotherapy benefits patients with oncogene-positive NSCLC remains unknown. METHODS: Data were retrieved from 4 institutions in the period from August 2018 to May 2021. Eligible patients were aged ≥18 years with histologically confirmed stage IIA to stage IIIB (T1-2 N1-2 or T3-4 N0-2) NSCLC that was deemed to be surgically resectable. The neoadjuvant regimen included immune checkpoint inhibitors alone or in combination with platinum-based doublets. Surgical resection was performed 4 to 6 weeks after the first day of the last cycle of treatment. The primary end point was major pathologic response (MPR; ≤10% viable tumor cells). Analyses were categorized according to the patients' oncogene (EGFR, ALK, KRAS, MET, BRAF, ROS1, RET) status. RESULTS: Overall, 137 patients were identified; 46 (33%) patients had nonsquamous cell cancer, and 114 (83%) had stage IIIA/B disease. Oncogene alterations were identified in 22 (16%) patients, of whom only 2 patients (2/22 [9%]) had an MPR compared with 65 (65/115 [56.5%]) in the oncogene-negative population (P < .001). Similar results were retained after propensity score matching for age, sex, smoking status, histologic type, stage, and cycles of neoadjuvant treatment. Squamous cell carcinoma (odds ratio, 2.54; 95% CI, 1.08-5.99) and positive oncogene status (odds ratio, 0.13; 95% CI, 0.03-0.64) were found to be indicators for MPR by logistic regression. The 1-year event-free survival rate was 75.4% in the oncogene-positive group, which was not significantly different from 85.5% in the oncogene-negative population (P = .23). CONCLUSIONS: Patients with stage II-III oncogene-positive NSCLCs respond less than patients with oncogene-negative NSCLCs after neoadjuvant immunotherapy.

Risk stratification and prognosis prediction based on inflammation-related gene signature in lung squamous carcinoma.

BACKGROUND: Inflammation is known to have an intricate relationship with tumorigenesis and tumor progression while it is also closely related to tumor immune microenvironment. Whereas the role of inflammation-related genes (IRGs) in lung squamous carcinoma (LUSC) is barely understood. Herein, we recognized IRGs associated with overall survival (OS), built an IRGs signature for risk stratification and explored the impact of IRGs on immune infiltration landscape of LUSC patients. METHODS: The RNA-sequencing and clinicopathological data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, which were defined as training and validation cohorts. Cox regression and least absolute shrinkage and selection operator analyses were performed to build an IRG signature. CIBERSORT, microenvironment cell populations-counter and tumor immune dysfunction and rejection (TIDE) algorithm were used to perform immune infiltration analysis. RESULTS: A two-IRG signature consisting of KLF6 and SGMS2 was identified according to the training set, which could categorize patients into two different risk groups with distinct OS. Patients in the low-risk group had more anti-tumor immune cells infiltrated while patient with high-risk had lower TIDE score and higher levels of immune checkpoint molecules expressed. The IRG signature was further identified as an independent prognostic factor of OS. Subsequently, a prognostic nomogram including IRG signature, age, and cancer stage was constructed for predicting individualized OS, whose concordance index values were 0.610 (95% CI: 0.568-0.651) in the training set and 0.652 (95% CI: 0.580-0.724) in validation set. Time-dependent receiver operator characteristic curves revealed that the nomogram had higher prediction accuracy compared with the traditional tumor stage alone. CONCLUSION: The IRG signature was a predictor for patients with LUSC and might serve as a potential indicator of the efficacy of immunotherapy. The nomogram based on the IRG signature showed a relatively good predictive performance in survival.

Comprehensive 18F-FDG PET-based radiomics in elevating the pathological response to neoadjuvant immunochemotherapy for resectable stage III non-small-cell lung cancer: A pilot study.

Purpose: To develop a comprehensive PET radiomics model to predict the pathological response after neoadjuvant toripalimab with chemotherapy in resectable stage III non-small-cell lung cancer (NSCLC) patients. Methods: Stage III NSCLC patients who received three cycles of neoadjuvant toripalimab with chemotherapy and underwent 18F-FDG PET/CT were enrolled. Baseline 18F-FDG PET/CT was performed before treatment, and preoperative 18F-FDG PET/CT was performed three weeks after the completion of neoadjuvant treatment. Surgical resection was performed 4-5 weeks after the completion of neoadjuvant treatment. Standardized uptake value (SUV) statistics features and radiomics features were derived from baseline and preoperative PET images. Delta features were derived. The radiologic response and metabolic response were assessed by iRECIST and iPERCIST, respectively. The correlations between PD-L1 expression, driver-gene status, peripheral blood biomarkers, and the pathological responses (complete pathological response [CPR]; major pathological response [MPR]) were assessed. Associations between PET features and pathological responses were evaluated by logistic regression. Results: Thirty patients underwent surgery and 29 of them performed preoperative PET/CT. Twenty patients achieved MPR and 16 of them achieved CPR. In univariate analysis, five SUV statistics features and two radiomics features were significantly associated with pathological responses. In multi-variate analysis, SUVmax, SUVpeak, SULpeak, and End-PET-GLDM-LargeDependenceHighGrayLevelEmphasis (End-GLDM-LDHGLE) were independently associated with CPR. SUVpeak and SULpeak performed better than SUVmax and SULmax for MPR prediction. No significant correlation, neither between the radiologic response and the pathological response, nor among PD-L1, driver gene status, and baseline PET features was found. Inflammatory response biomarkers by peripheral blood showed no difference in different treatment responses. Conclusion: The logistic regression model using comprehensive PET features contributed to predicting the pathological response after neoadjuvant toripalimab with chemotherapy in resectable stage III NSCLC patients.

Response of primary tumor and lymph node in non-small cell lung cancer after neoadjuvant immunotherapy: a pooled analysis.

The good pathological response of primary tumors (PTs) to neoadjuvant immunotherapy has been acknowledged in non-small cell lung cancer (NSCLC), however, it remains unclear whether neoadjuvant immunotherapy shows consistent effects in metastatic lymph nodes (LNs). We compared the pathological response of PT and nodal downstaging using a pooled analysis to assess the effect of neoadjuvant immunotherapy on LNs. Original articles reporting the tumor major pathological response (ypT(MPR)), pathological complete response (ypT0) and nodal downstaging following neoadjuvant immunotherapy in NSCLC were retrieved. The OR and 95% CI were calculated by Review Manager V.5.3. Subgroup analysis was performed according to the neoadjuvant therapy regimen used. A total of 209 patients from 6 studies were included in this analysis. The frequency of nodal downstaging was comparable to that of ypT(MPR) (OR 1.31; 95% CI 0.84 to 2.05; p=0.24). Interestingly, ypN0 was observed more frequently than ypT0 (OR 3.26; 95% CI 2.06 to 5.16; p<0.0001). However, this difference was not observed in the subgroup of cN2 patients who underwent immune checkpoint inhibitor monotherapy (OR 1.58; 95% CI 0.56 to 4.48; p=0.39). Neoadjuvant immunotherapy results in satisfactory response in metastatic LN. Patients had a high probability of node clearance when ypT0 was confirmed, especially in patients treated with immunochemotherapy.

Integrative Analysis of Bioinformatics and Machine Learning Algorithms Identifies a Novel Diagnostic Model Based on Costimulatory Molecule for Predicting Immune Microenvironment Status in Lung Adenocarcinoma.

Costimulatory molecules are an indispensable signal for activating immune cells. However, the features of many costimulatory molecule genes (CMGs) in lung adenocarcinoma (LUAD) are poorly understood. This study systematically explored expression patterns of CMGs in the tumor immune microenvironment (TIME) status of patients with LUAD. Their expression profiles were downloaded from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Two robust TIME subtypes ("hot" and "cold") were classified by K-means clustering and estimation of stromal and immune cells in malignant tumor tissues using expression data. The "hot" subtype presented higher infiltration in activated immune cells and enrichments in the immune cell receptor signaling pathway and adaptive immune response. Three CMGs (CD80, LTB, and TNFSF8) were screened as final diagnostic markers by means of Least Absolute Shrinkage Selection Operator and Support Vector Machine-Recursive Feature Elimination algorithms. Accordingly, the diagnostic nomogram for predicting individualized TIME status showed satisfactory diagnostic accuracy in The Cancer Genome Atlas training cohort as well as GSE31210 and GSE180347 validation cohorts. Immunohistochemistry staining of 16 specimens revealed an apparently positive correlation between the expression of CMG biomarkers and pathologic response to immunotherapy. Thus, this diagnostic nomogram provided individualized predictions in TIME status of LUAD patients with good predictive accuracy, which could serve as a potential tool for identifying ideal candidates for immunotherapy.

Different In Situ Immune Patterns between Primary Tumor and Lymph Node in Non-Small-Cell Lung Cancer: Potential Impact on Neoadjuvant Immunotherapy.

Background: Neoadjuvant immunotherapy is promising for locally advanced non-small-cell lung cancer (NSCLC). The in situ immune patterns, as a predictor of PD-1/PD-L1 blockade outcomes, of the primary tumor (PT) and metastatic lymph nodes (mLNs) are unknown. Methods: Multiplex immunofluorescence staining and multispectral imaging were used to evaluate the in situ immune patterns of T cells (CD3+) and cytotoxic T cells (CD8+) in terms of density, location (center of tumor (CT) and invasive margin (IM)), and the PD-L1 expression status of tumor cells and stromal T cells of paired PTs and mLNs in 38 stage III NSCLCs. Results: The densities of T cells and cytotoxic T cells were correlated between PTs and mLNs at both CT and IM. Higher densities of stromal T cells (S-CD3+) at CT and both S-CD3+ and cytotoxic T cells (S-CD8+) at IM were observed in mLNs compared to PTs, while in tumor compartment, there were no differences in the densities of T cells (T-CD3+) or cytotoxic T cells (T-CD8+). Only the density of stromal PD-L1-positive T cells (S-PD-L1+CD3+) at CT was correlated between PTs and mLNs, while the densities and frequencies of S-PD-L1+CD3+ at CT and IM of mLNs were higher than PTs. Combining positive score discordance of PD-L1 between PTs and mLNs was greater than tumor proportion score. Conclusions. In situ immune patterns of T cells and cytotoxic T cells were different between PTs and mLNs in NSCLC. The heterogeneity of the in situ immune patterns may result in different immune-mediated responses to neoadjuvant immunotherapy in PT and mLNs.

A novel Phe-206-Leu mutation in acetolactate synthase confers resistance to penoxsulam in barnyardgrass (Echinochloa crus-galli (L.) P. Beauv).

BACKGROUND: Barnyardgrass (Echinochloa crus-galli (L.) P. Beauv) has evolved resistance to the acetolactate synthase (ALS) inhibitor penoxsulam which is used to control weeds in rice fields in China. The present study is conducted to identify the target-site resistance (TSR) mechanisms conferring resistance in a penoxsulam-resistant population. RESULTS: The ALS sensitivity in vitro of the resistant population was sixfold lower to penoxsulam than that of the sensitive population. ALS sequencing revealed that no known mutation conferring ALS herbicide resistance was detected. However, a novel mutation Phe-206-Leu was identified in the ALS gene. Additionally, ALS gene expression level of the resistant population was lower than that of the sensitive population. Therefore, the penoxsulam resistance was not due to the overexpression of ALS gene. Molecular docking revealed that this mutation may change the interaction of the penoxsulam-ALS binding and weaken its mutual affinity by approximately 10%. Arabidopsis thaliana transformed with mutant ALS had fourfold greater resistance to penoxsulam and varied cross-resistance to other ALS herbicides than those transformed with sensitive ALS. Mutant and sensitive ALS proteins expressed by the baculovirus system exhibited different in vitro penoxsulam sensitivity levels. Mutant ALS had eightfold lower sensitivity to penoxsulam than sensitive ALS. CONCLUSION: This report provides clear evidence that the ALS mutation at position 206 (Phe-206-Leu) confers penoxsulam resistance in barnyardgrass. Phe-206 was confirmed to be the ninth amino acid residue related to ALS herbicide resistance in weeds. © 2022 Society of Chemical Industry.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Squamous Carcinoma.

Aging is an inevitable process characterized by a decline in many physiological activities, and has been known as a significant risk factor for many kinds of malignancies, but there are few studies about aging-related genes (ARGs) in lung squamous carcinoma (LUSC). We designed this study to explore the prognostic value of ARGs and establish an ARG-based prognosis signature for LUSC patients. RNA-sequencing and corresponding clinicopathological data of patients with LUSC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The ARG risk signature was developed on the basis of results of LASSO and multivariate Cox analysis in the TCGA training dataset (n = 492). Furthermore, the GSE73403 dataset (n = 69) validated the prognostic performance of this ARG signature. Immunohistochemistry (IHC) staining was used to verify the expression of the ARGs in the signature. A five ARG-based signature, including A2M, CHEK2, ELN, FOS, and PLAU, was constructed in the TCGA dataset, and stratified patients into low- and high-risk groups with significantly different overall survival (OS) rates. The ARG risk score remained to be considered as an independent indicator of OS in the multivariate Cox regression model for LUSC patients. Then, a prognostic nomogram incorporating the ARG risk score with T-, N-, and M-classification was established. It achieved a good discriminative ability with a C-index of 0.628 (95% confidence interval [CI]: 0.586-0.671) in the TCGA cohort and 0.648 (95% CI: 0.535-0.762) in the GSE73403 dataset. Calibration curves displayed excellent agreement between the actual observations and the nomogram-predicted survival. The IHC staining discovered that these five ARGs were overexpression in LUSC tissues. Besides, the immune infiltration analysis in the TCGA cohort represented a distinctly differentiated infiltration of anti-tumor immune cells between the low- and high-risk groups. We identified a novel ARG-related prognostic signature, which may serve as a potential biomarker for individualized survival predictions and personalized therapeutic recommendation of anti-tumor immunity for patients with LUSC.

A novel diagnostic model for predicting immune microenvironment subclass based on costimulatory molecules in lung squamous carcinoma.

There is still no ideal predictive biomarker for immunotherapy response among patients with non-small cell lung cancer. Costimulatory molecules play a role in anti-tumor immune response. Hence, they can be a potential biomarker for immunotherapy response. The current study comprehensively investigated the expression of costimulatory molecules in lung squamous carcinoma (LUSC) and identified diagnostic biomarkers for immunotherapy response. The costimulatory molecule gene expression profiles of 627 patients were obtained from the The Cancer Genome Atlas, GSE73403, and GSE37745 datasets. Patients were divided into different clusters using the k-means clustering method and were further classified into two discrepant tumor microenvironment (TIME) subclasses (hot and cold tumors) according to the immune score of the ESTIMATE algorithm. A high proportion of activated immune cells, including activated memory CD4 T cells, CD8 T cells, and M1 macrophages. Five CMGs (FAS, TNFRSF14, TNFRSF17, TNFRSF1B, and TNFSF13B) were considered as diagnostic markers using the Least Absolute Shrinkage and Selection Operator and the Support Vector Machine-Recursive Feature Elimination machine learning algorithms. Based on the five CMGs, a diagnostic nomogram for predicting individual tumor immune microenvironment subclasses in the TCGA dataset was developed, and its predictive performance was validated using GSE73403 and GSE37745 datasets. The predictive accuracy of the diagnostic nomogram was satisfactory in all three datasets. Therefore, it can be used to identify patients who may benefit more from immunotherapy.

Phase 2 trial of neoadjuvant toripalimab with chemotherapy for resectable stage III non-small-cell lung cancer.

Multimodality treatment provides modest survival benefits for patients with locally advanced (stage III) non-small-cell lung cancer (NSCLC). Nevertheless, preoperative immunotherapy has continuously been shown to be promising in treating resectable NSCLC.This phase 2 trial enrolled patients with AJCC-defined stage IIIA or T3-4N2 IIIB NSCLC deemed surgically resectable. Patients received three cycles of neoadjuvant treatment with intravenous PD-1 inhibitor toripalimab (240 mg), carboplatin (area under the curve 5), and pemetrexed (500 mg/m2 for adenocarcinoma) or nab-paclitaxel (260 mg/m2 for other subtypes) on day 1 of each 21-day cycle. Surgical resection was performed 4-5 weeks afterward. The primary endpoint was major pathological response (MPR), defined as less than 10% residual tumor remaining at the time of surgery.Thirty-three patients were enrolled, of whom 13 (39.4%) had T3-4N2 stage IIIB disease. Thirty (90.9%) patients underwent resection and all except one (96.7%) achieved R0 resection. Twenty patients (60.6%) in the intention-to-treat population achieved an MPR, including 15 patients (45.5%) who achieved a pathological complete response (pCR). The MPR and pCR rates in the per-protocol population were 66.7% and 50.0%, respectively. The surgical complications included three cases of arrhythmias, one case of a prolonged air leak, and one case of chylothorax. The most common grade 3 treatment-related adverse event (TRAE) was anemia (2, [6.1%]). Severe TRAEs included one (3.0%) case of grade 3 peripheral neuropathy that resulted in surgical cancellation.Toripalimab plus platinum-based doublet chemotherapy yields a high MPR rate, manageable toxicity, and feasible resection in stage III NSCLC.Trial ClinicalTrials.gov (NCT04304248).

The impact of an N1 lymph node examination in patients with early-stage non-small cell lung cancer: a retrospective cohort study.

BACKGROUND: The examination of lymph nodes (LNs) is critical for accurate node staging in patients with non-small cell lung cancer (NSCLC), but a consensus on the examinations of hilar and intrapulmonary (N1 station) LNs has not been reached. This study aimed to evaluate the role of LN dissection and pathological examination of N1 LN stations and their effects on survival in patients with stage IA-IIA NSCLC. METHODS: Data from patients pathologically staged as IA-IIA who underwent radical surgery and confirmed as lacking LN metastases from January 2008 to March 2018 were retrospectively reviewed. The Kaplan-Meier method was used to determine the overall survival (OS) and disease-free survival (DFS). After propensity score matching (PSM), a Cox model was used to determine the prognostic factors. RESULTS: Of the 1,935 patients investigated, the median number of N1 stations examined was 3. Patients with at least 2 N1 stations examined had apparently better OS (P=0.002) and DFS (P=0.001). All patients were divided into patients with 0-1 N1 station examined and patients with 2-5 N1 stations examined. After PSM, the number of N1 stations examined was an independent prognostic factor for DFS (P=0.004). Patients with 2-5 N1 stations examined experienced prolonged DFS (P=0.010). Patients in group 12 experienced prolonged OS (P=0.021) and DFS (P=0.026). Patients in group 13 or 14 experienced prolonged OS (P=0.028). CONCLUSIONS: A larger extent of N1 station examination was associated with prolonged DFS in patients with stage IA-IIA NSCLC after lobectomy. The dissection and examination of at least 2 N1 stations included LNs from the lobar and segmental drainage fields.

[Application of Neoadjuvant Immuno-chemotherapy in NSCLC].

Even patients after standard surgery and adjuvant chemotherapy still have a high risk of recurrence and metastasis. With the success of immunotherapy in advanced non-small cell lung cancer (NSCLC), the application of immunotherapy in locally advanced NSCLC has being investigated to reduce the recurrence and metastasis. Pre-clinical studies and several phase II clinical studies had provided theoretical support and clinical evidence for neoadjuvant immunotherapy for NSCLC. This review describes the mechanism of neoadjuvant immuno-chemotherapy, summarizes up-to-date clinical studies, and analyzes efficiency and feasibility of neoadjuvant immune monotherapy or immuno-chemotherapy. Results from four studies (NCT02259621, NEOSTAR, LCMC3 and ChiCTR-OIC-17013726) showed efficiency and feasibility of neoadjuvant anti-programmed cell death 1 (PD-1)/programmed cell death ligand 1 (PD-L1) monotherapy. Neoadjuvant nivolumab plus ipilimumab achieved higher major pathological response rate than nivolumab monotherapy. However, the combination of nivolumab plus ipilimumab led to more severe adverse events as is seen in the NEOSTAR trial. Results from NCT02716038, SAKK 16/14 and NADIM studies suggest that the pathological response rate of neoadjuvant immune-chemotherapy is higher than neoadjuvant immune checkpoint inhibitor monotherapy. This review also elaborates the mechanism of chemotherapy combined with immunotherapy, and discusses the efficacy evaluation after neoadjuvant immunotherapy.
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