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.

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.

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.

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.

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).

A Novel Inflammatory-Related Gene Signature Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma.

Inflammation is an important hallmark of cancer and plays a role in both neogenesis and tumor development. Despite this, inflammatory-related genes (IRGs) remain to be poorly studied in lung adenocarcinoma (LUAD). We aim to explore the prognostic value of IRGs for LUAD and construct an IRG-based prognosis signature. The transcriptomic profiles and clinicopathological information of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression were applied in the TCGA set to generate an IRG risk signature. LUAD cases with from the GSE31210 and GSE30219 datasets were used to validate the predictive ability of the signature. Analysis of the TCGA cohort revealed a five-IRG risk signature consisting of EREG, GPC3, IL7R, LAMP3, and NMUR1. This signature was used to divide patients into two risk groups with different survival rates. Multivariate Cox regression analysis verified that the risk score from the five-IRG signature negatively correlated with patient outcome. A nomogram was developed using the IRG risk signature and stage, with C-index values of 0.687 (95% CI: 0.644-0.730) in the TCGA training cohort, 0.678 (95% CI: 0.586-0.771) in GSE30219 cohort, and 0.656 (95% CI: 0.571-0.740) in GSE30219 cohort. Calibration curves were consistent between the actual and the predicted overall survival. The immune infiltration analysis in the TCGA training cohort and two GEO validation cohorts showed a distinctly differentiated immune cell infiltration landscape between the two risk groups. The IRG risk signature for LUAD can be used to predict patient prognosis and guide individual treatment. This risk signature is also a potential biomarker of immunotherapy.

Fibrin sealant for esophageal anastomosis: A phase II study.

BACKGROUND: Esophagectomy is a pivotal curative modality for localized esophageal or esophagogastric junction cancer (EC or EJC). Postoperative anastomotic leakage (AL) remains problematic. The use of fibrin sealant (FS) may improve the strength of esophageal anastomosis and reduce the incidence of AL. AIM: To assess the efficacy and safety of applying FS to prevent AL in patients with EC or EJC. METHODS: In this single-arm, phase II trial (Clinicaltrial.gov identifier: NCT03529266), we recruited patients aged 18-80 years with resectable EC or EJC clinically staged as T1-4aN0-3M0. An open or minimally invasive McKeown esophagectomy was performed with a circular stapled anastomosis. After performing the anastomosis, 2.5 mL of porcine FS was applied circumferentially. The primary endpoint was the proportion of patients with AL within 3 mo. RESULTS: From June 4, 2018, to December 29, 2018, 57 patients were enrolled. At the data cutoff date (June 30, 2019), three (5.3%) of the 57 patients had developed AL, including two (3.5%) with esophagogastric AL and one (1.8%) with gastric fistula. The incidence of anastomotic stricture and other major postoperative complications was 1.8% and 17.5%, respectively. The median time needed to resume oral feeding after operation was 8 d (Interquartile range: 7.0-9.0 d). No adverse events related to FS were recorded. No deaths occurred within 90 d after surgery. CONCLUSION: Perioperative sealing with porcine FS appears safe and may prevent AL after esophagectomy in patients with resectable EC or EJC. Further phase III studies are warranted.

Mutation Profile of Resected EGFR-Mutated Lung Adenocarcinoma by Next-Generation Sequencing.

BACKGROUND: The efficacy of adjuvant targeted therapy for operable lung cancer is still under debate. Comprehensive genetic profiling is needed for detecting co-mutations in resected epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma (ADC), which may interfere the efficacy of adjuvant tyrosine kinase inhibitor (TKI) treatment. MATERIALS AND METHODS: Mutation profiling of 416 cancer-relevant genes was conducted for 139 resected stage I-IIIa lung ADCs with EGFR mutations using targeted next-generation sequencing. Co-mutation profiles were systematically analyzed. RESULTS: Rare EGFR alterations other than exon 19 deletion and L858R, such as L861Q (∼3%) and G719A (∼2%), were identified at low frequencies. Approximately 10% of patients had mutations in EGFR exon 20 that could confer resistance to first-generation TKIs. Ninety-one percent of patients harbored at least one co-mutation in addition to the major EGFR mutation. TP53 was the top mutated gene and was found more frequently mutated at later stage. Markedly, NF1 mutations were found only in stage II-III ADCs. Conversely, RB1 mutations were more frequent in stage I ADCs, whereas APC mutations were observed exclusively in this group. Thirty-four percent of patients with EGFR TKI-sensitizing mutations had genetic alterations involving EGFR downstream effectors or bypass pathways that could affect the response to EGFR TKIs, such as PIK3CA, BRCA1, and NOTCH1. CONCLUSION: Operable lung ADCs with EGFR TKI-sensitizing mutations are associated with a high proportion of co-mutations. Mutation profiling of these resected tumors could facilitate in determining the applicability and efficacy of adjuvant EGFR TKI therapeutic strategy. IMPLICATIONS FOR PRACTICE: The efficacy of adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) therapy for lung cancer harboring EGFR mutation after surgical resection is still under debate. Next-generation sequencing of 416 cancer-relevant genes in 139 resected lung cancers revealed the co-mutational landscape with background EGFR mutation. Notably, the study identified potential EGFR TKI-resistant mutations in 34.71% of patients with a drug-sensitizing EGFR mutation and who were naive in terms of targeted therapy. A comprehensive mutation profiling of these resected tumors could facilitate in determining the applicability and efficacy of adjuvant EGFR TKI therapeutic strategy for these patients.

Prognostic Effect of TP53 and PKD Co-Mutations in Patients with Resected Epidermal Growth Factor Receptor-Mutated Lung Adenocarcinoma.

BACKGROUND: The impact of specific co-mutations in epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma is unclear. METHODS: Tissues from 147 consecutive patients with resected EGFR-mutated lung adenocarcinomas treated at Sun Yat-Sen University Cancer Center were analyzed by next-generation sequencing (NGS). Associations between mutation status, patient baseline characteristics, and survival outcomes (disease-free survival [DFS] and overall survival [OS]) after surgical resection were analyzed. RESULTS: TP53 and protein kinase D (PKD) mutations were the two most frequently observed co-mutations in this cohort. Dual PKD/EGFR and TP53/EGFR mutations were found in 39 (27%) and 72 patients (49%), respectively, with dual TP53/EGFR mutations more commonly observed in male patients (P = 0.021). Both TP53 (hazard ratio [HR] 2.08, 95% confidence interval [CI] 1.23-3.54, P = 0.007) and PKD co-mutations (HR 1.72, 95% CI 1.01-2.93, P = 0.044) were associated with shorter DFS, but not OS, in univariate analysis. In multivariate analysis, patients harboring PKD/TP53 co-mutations had shorter DFS compared with PKD-/TP53- cases (HR 2.49, 95% CI 1.15-5.37, P = 0.02). In a subgroup of never-smokers, TP53 co-mutations were associated with significantly worse OS (HR 50.11, 95% CI 2.39-1049.83, P = 0.012). CONCLUSION: TP53 and PKD mutations were the two most frequently observed co-mutations in resected EGFR-mutated lung adenocarcinoma. Both mutations were associated with poorer prognoses in affected patients.