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.

Distinct Prognostic Factors of Ground Glass Opacity and Pure-Solid Lesion in Pathological Stage I Invasive Lung Adenocarcinoma.

Background: Ground glass opacity (GGO) is associated with favorable survival in lung cancer. However, the relevant evidence of the difference in prognostic factors between GGO and pure-solid nodules for pathological stage I invasive adenocarcinoma (IAC) is limited. We aimed to identify the impact of GGO on survival and find prognostic factor for part-GGO and pure-solid patients. Methods: Between December 2007 and August 2018, patients with pathological stage I IAC were retrospectively reviewed and categorized into the pure-GGO, part-GGO, and pure-solid groups. Survival curves were analyzed by the Kaplan-Meier method and compared by log-rank tests. Least absolute shrinkage and selection operator and Cox regression models were used to obtained prognostic factors for disease-free survival (DFS) and overall survival (OS). Results: The number of patients with pure-GGO, part-GGO, and pure-solid was 134, 540, and 396, respectively. Part-GGO patients with consolidation-tumor-ratio (CTR) > 0.75 had similar outcome to those with pure-solid nodules. In part-GGO patients, CTR was negatively associated with OS (P = 0.007) and solid tumor size (STS) was negatively associated with DFS (P < 0.001). Visceral pleural invasion (VPI) was negatively associated with OS (P = 0.040) and DFS (P = 0.002). Sublobectomy was negatively associated with OS (P = 0.008) and DFS (P = 0.005), while extended N1 stations examination was associated with improved DFS (P = 0.005) in pure-solid patients. Conclusions: Though GGO component is a positively prognostic factors of patients with pathological stage I IAC, a small proportion of GGO components is not associated with favorable survival. VPI, STS and CTR are the significant predictors for part-GGO patients. Sublobectomy, especially wedge resection should be used cautiously in pure-solid 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.

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).

Impact of Examined Lymph Node Count for Esophageal Squamous Cell Carcinoma in Patients who Underwent Right Transthoracic Esophagectomy.

BACKGROUND: The impact of the number of examined lymph nodes (ELNs) on stage correction and prognostication in patients with esophageal squamous cell carcinoma (ESCC) who underwent right transthoracic esophagectomy is still unclear. METHODS: Patients with ESCC who underwent right transthoracic esophagectomy at Sun Yat-sen University Cancer Center between January 1997 and December 2013 were retrospectively enrolled. The Cox proportional hazards regression model was used to determine the effect of ELN count on overall survival. The impact of ELN count on stage correction was evaluated using the hypergeometric distribution and Bayes theorem and ß-binomial distribution estimation, respectively. The threshold of ELNs was determined using the LOWESS smoother and piecewise linear regression. RESULTS: Among the 875 included patients, greater ELNs were associated with a higher rate of nodal metastasis. Significant association between staging bias and the number of ELNs is only observed through the Bayes method. The ELN count did not impact 90-day mortality but significantly impacted long-term survival (adjusted hazard ratio [aHR] 0.986), especially in those patients with node-negative disease (aHR 0.972). In patients with node-negative disease, cut-point analysis showed a threshold ELN count of 21. CONCLUSIONS: A greater number of ELNs is associated with more accurate node staging and better long-term survival in resected ESCC patients. We recommended harvesting at least 21 LNs to acquire accurate staging and long-term survival information for patients with declared node-negative disease using the right thoracic approach.

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.

Impact of treatment modality on long-term survival of stage IA small-cell lung cancer patients: a cohort study of the U.S. SEER database.

BACKGROUND: The optimal treatment modality for patients with stage IA (T1N0M0) small-cell lung cancer (SCLC) is still unclear. METHODS: Patients who received surgical resection or chemo-radiotherapy (CRT) between January 2004 and December 2014 were identified from The Surveillance, Epidemiology and End Results (SEER) database. Surgical resection included lobectomy, wedge resection, segmentectomy with lymphadenectomy [examined lymph node (ELN) ≥1]. Propensity score match analysis was utilized to balance the baseline characteristics. RESULTS: A total of 686 stage IA SCLC cases were included: 337 patients underwent surgery and 349 patients were treated by CRT alone. Surgery achieved a better outcome than CRT alone, with an adjusted hazard ratio (HR) of 0.495. Patients who underwent lobectomy demonstrated a longer overall survival (OS), compared to those who received sublobectomy (crude cohort, median OS, 69 vs. 38 months; match cohort, median OS, 67 vs. 38 months). Patients with ELN >7 presented with longer OS than those with ELN ≤7 (crude cohort, median OS, 91 vs. 49 months; matched cohort, median OS, 91 vs. 54 months). The additional efficacy of chemotherapy or radiotherapy in patients receiving lobectomy was observed. The best prognosis was achieved in the lobectomy plus CRT cohort, with a 5-year survival rate of 73.5%. CONCLUSIONS: The prolonged survival associated with lobectomy and chemotherapy or radiotherapy presents a viable treatment option in the management of patients with stage IA SCLC.

Oncologic outcomes of lobectomy vs. segmentectomy in non-small cell lung cancer with clinical T1N0M0 stage: a literature review and meta-analysis.

BACKGROUND: Lobectomy has long been regarded as the standard treatment for operable non-small cell lung cancer (NSCLC). Recent studies suggested that segmentectomy could achieve a good prognosis for early-stage NSCLC and might be an alternative to lobectomy in this cohort. Until now, on the issue of comparison between lobectomy and segmentectomy, there remains no published randomized controlled trial (RCT), and all existing evidence is low. Recently, a categorization of lower-level evidence has been proposed, namely, the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The aim of this meta-analysis is to compare the oncologic outcome between lobectomy and segmentectomy in NSCLC with the clinical T1N0M0 stage according to the GRADE system. METHODS: PubMed, the PMC database, EMBASE, Web of Science, and the Cochrane library were searched prior to May 2019 to identify studies that compared the prognosis between lobectomy and segmentectomy for clinical T1N0M0 NSCLC. The evidence level of the included studies was assessed according to the GRADE system, including level IIA, probably not confounded nonrandomized comparison; level IIB, possibly confounded nonrandomized comparison; and level IIC, probably confounded nonrandomized comparison. The predefined outcomes included overall survival (OS) and disease-free survival (DFS). Univariable and multivariable hazard ratios (HRs) with 95% confidence intervals (95% CI) were pooled using a random-effects model. RESULTS: Twelve nonrandomized studies involving 8,072 participants were included. Of these studies, two were classified as IIA level (16.7%), six as IIB level (50.0%), and four as IIC level (33.3%). When crude HRs were included, compared with lobectomy, segmentectomy was associated with shorter OS but comparable DFS in the entire cohort (OS, pooled HR =1.45, 95% CI, 1.23 to 1.67; DFS, pooled HR =1.03, 95% CI, 0.65 to 1.82) and in patients with nodules ≤2 cm (OS, pooled HR =1.55, 95% CI, 1.33 to 1.80; DFS, pooled HR =0.98, 95% CI, 0.55 to 1.77). When adjusted HRs were included, the impact of segmentectomy on OS and DFS was comparable to that of lobectomy in the entire cohort (OS, pooled HR =1.39, 95% CI, 0.92 to 2.10; DFS, pooled HR =0.83, 95% CI, 0.66 to 1.03) and in patients with nodules ≤2 cm (OS, pooled HR =1.61, 95% CI, 0.87 to 3.00; DFS, pooled HR =0.90, 95% CI, 0.63 to 1.27). CONCLUSIONS: Based on our results, although shorter OS is observed in patients received segmentectomy, it is necessary to wait for more results from RCT to draw a valid conclusion.

Impact of examined lymph node count for oesophageal squamous cell carcinoma in patients who underwent left transthoracic oesophagectomy.

BACKGROUND: The impact of the number of examined lymph nodes (ELNs) on stage correction and prognostication in patients with oesophageal squamous cell carcinoma (ESCC) who underwent left transthoracic oesophagectomy is still unclear. METHODS: Patients with ESCC who underwent left transthoracic oesophagectomy at Sun Yat-sen University Cancer Center between January 1997 and December 2013 were retrospectively enrolled. The Cox proportional hazards regression model was used to determine the effect of ELN count on overall survival (OS). The association between ELN count and nodal status was investigated through scatter plot and binary logistic regression analyses. The impact of ELN count on stage correction was evaluated using the hypergeometric distribution and Bayes theorem. The threshold of ELNs was determined using the LOWESS smoother and piecewise linear regression. RESULTS: Among the 1826 included patients, greater ELNs were associated with a higher rate of nodal metastasis (adjusted OR = 1.018). When the ELN count increased, the omission rate of positive lymph nodes (LNs) decreased. The ELN count did not impact 90-day mortality but significantly impacted long-term survival (adjusted HR = 0.983), especially in those with node-negative disease (adjust HR = 0.972). In patients with node-negative disease, cut point analysis showed a threshold ELN count of 18. CONCLUSIONS: A greater number of ELNs is associated with more accurate node staging and better long-term survival in resected ESCC patients. We recommended harvesting at least 18 LNs to acquire accurate staging and long-term survival information for patients with declared node-negative disease in the left thoracic approach.