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.

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.

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.

Ground Glass Opacity and Adjuvant Chemotherapy in Pathological Stage IB-IIA Lung Adenocarcinoma.

Background: The prognostic value of ground glass opacity (GGO) in stage IA non-small cell lung cancer (NSCLC) has been widely recognized. However, studies investigating its value in the related stage IB-IIA lung adenocarcinoma (LUAD) remains lacking. The impact of adjuvant chemotherapy (ACT) on pathological stage IB-IIA LUAD is also controversial. Materials and Methods: We retrospectively reviewed the clinical records of 501 patients with pathological stage IB-IIA LUAD at the Sun Yat-sen University Cancer Center from January 2008 to June 2018. We calculated and compared survival curves using the Kaplan-Meier test and log-rank test. Cox regression models were performed to determine independent prognostic factors of disease-free survival (DFS) and overall survival (OS). We established nomograms to predict the OS and DFS of LUAD patients. Calibration and receiver operator characteristic curves were conducted to assess the predictive performance of two nomograms. Based on the nomogram, we identified candidate patients that may most benefit from ACT after surgery. Results: The number of patients with pure solid, part GGO, and pure GGO nodules was 240, 242, and 19, respectively, and 125 patients who received ACT. Patients with consolidation-to-tumor ratio (CTR) <0.75 had longer OS (P = 0.026) and DFS (P = 0.003). Pathological tumor size and at least 10 lymph nodes (LNs) resection were independent prognostic factors of both OS and DFS. CTR <0.75 was positively associated with DFS. The C-index of nomograms predicting individual OS and DFS was 0.660 and 0.634, respectively. Based on the nomogram for OS, ACT was found to be a positive prognostic indicator of OS (P = 0.031, HR = 0.5141, 95% CI 0.281-0.942) in patients with nomogram total points ≥5. Conclusion: CTR <0.75 is associated with a better DFS in patients with stage IB-IIA LUAD. Nomograms developed by integrating pathological tumor size, at least 10 LNs resection, and CTR ≥0.75 for predicting individual OS and DFS displayed a good predictive capacity and clinical value, which were also proved to be a useful tool for selecting patients most benefiting from ACT.

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 Inflammatory-Nutritional Prognostic Scoring System for Patients with Early-Stage Breast Cancer.

PURPOSE: We attempted to explore the prognostic value of baseline inflammatory and nutritional biomarkers at diagnosis in patients with early-stage breast cancer and develop a novel scoring system, the inflammatory-nutritional prognostic score (INPS). PATIENTS AND METHODS: We collected clinicopathological and baseline laboratory data of 1259 patients with early-stage breast cancer between December 2010 and November 2012 from Sun Yat-sen University Cancer Center. Eligible patients were randomly divided into training and validation cohorts (n = 883 and 376, respectively) in a 7:3 ratio. We selected the most valuable biomarkers to develop INPS by the least absolute shrinkage and selection operator (LASSO) Cox regression model. A prognostic nomogram incorporating INPS and other independent clinicopathological factors was developed based on the stepwise multivariate Cox regression method. Then, we used the concordance index (C-index), calibration plot, and time-dependent receiver operating characteristic (ROC) analysis to evaluate the prognostic performance and predictive accuracy of the predictive nomogram. RESULTS: Four inflammatory-nutritional biomarkers, including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), prognostic nutritional index (PNI), and albumin-alkaline phosphatase ratio (AAPR), were selected using the LASSO Cox analysis to construct INPS, which remained an independent prognostic indicator per the multivariate Cox regression analysis. Patients were stratified into low- and high-INPS groups based on the cutoff INPS determined by the maximally selected rank statistics. The prognostic model for overall survival consisting of INPS and other independent clinicopathological indicators showed excellent discrimination with C-indexes of 0.825 (95% confidence interval [CI]: 0.786-0.864) and 0.740 (95% CI: 0.657-0.822) in the training and validation cohorts, respectively. The time-dependent ROC curves showed a higher predictive accuracy of our prognostic nomogram than that of traditional tumor-node-metastasis staging. CONCLUSION: Baseline INPS is an independent indicator of OS in patients with early-stage breast cancer. The INPS-based prognostic nomogram could be used as a practical tool for individualized prognostic predictions.

Risk stratification and adjuvant chemotherapy after radical resection based on the clinical risk scores of patients with stage IB-IIA non-small cell lung cancer.

INTRODUCTION: Despite the heterogeneity among patients with stage IB-IIA non-small cell lung cancer (NSCLC), clinically applicable models to identify patients most suitable for receiving adjuvant chemotherapy (ACT) are limited. We aimed to develop a model for risk stratification and the individualized application of ACT. METHODS: Between January 2008 and March 2018, patients with T2N0M0 NSCLC at Sun Yat-sen University Cancer Center were retrospectively enrolled. Survival curves were estimated by Kaplan-Meier method and compared with log-rank test. Cox regression models were used to identify prognostic factors for disease-free survival (DFS) and overall survival (OS). Propensity score matching (PSM) was implemented. Subgroup analysis was performed based on clinical risk score (CRS) value and epidermal growth factor receptor (EGFR) mutation status. RESULTS: Of 1063 patients with T2N0 NSCLC enrolled, 272 patients received ACT. Before PSM, patients with high CRS (>1) had a significantly worse OS and DFS outcomes. In the PSM, the baseline characteristics of the 270 pairs of patients were well matched. ACT was associated with improved OS outcomes for patients with a high CRS, while ACT was associated with improved OS and DFS outcomes in patients with wild-type EGFR. The interaction analysis showed an apparent interaction effect between ACT and EGFR-activating mutations as well as chemotherapy regimens and histology. CONCLUSIONS: The CRS can predict the prognosis of patients with stage IB-IIA NSCLC. ACT could improve the outcome of patients with a high CRS. Patients with non-squamous cell histology receiving pemetrexed plus platinum might benefit more, but not those with EGFR-activating mutations.

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.

Prognostic Nomograms Based on Ground Glass Opacity and Subtype of Lung Adenocarcinoma for Patients with Pathological Stage IA Lung Adenocarcinoma.

The value of lung adenocarcinoma (LUAD) subtypes and ground glass opacity (GGO) in pathological stage IA invasive adenocarcinoma (IAC) has been poorly understood, and reports of their association with each other have been limited. In the current study, we retrospectively reviewed 484 patients with pathological stage IA invasive adenocarcinoma (IAC) at Sun Yat-sen University Cancer Center from March 2011 to August 2018. Patients with at least 5% solid or micropapillary presence were categorized as high-risk subtypes. Independent indicators for disease-free survival (DFS) and overall survival (OS) were identified by multivariate Cox regression analysis. Based on these indicators, we developed prognostic nomograms of OS and DFS. The predictive performance of the two nomograms were assessed by calibration plots. A total of 412 patients were recognized as having the low-risk subtype, and 359 patients had a GGO. Patients with the low-risk subtype had a high rate of GGO nodules (p < 0.001). Multivariate Cox regression analysis showed that the high-risk subtype and GGO components were independent prognostic factors for OS (LUAD subtype: p = 0.002; HR 3.624; 95% CI 1.263-10.397; GGO component: p = 0.001; HR 3.186; 95% CI 1.155-8.792) and DFS (LUAD subtype: p = 0.001; HR 2.284; 95% CI 1.448-5.509; GGO component: p = 0.003; HR 1.877; 95% CI 1.013-3.476). The C-indices of the nomogram based on the LUAD subtype and GGO components to predict OS and DFS were 0.866 (95% CI 0.841-0.891) and 0.667 (95% CI 0.586-0.748), respectively. Therefore, the high-risk subtype and GGO components were potential prognostic biomarkers for patients with stage IA IAC, and prognostic models based on these indicators showed good predictive performance and satisfactory agreement between observational and predicted survival.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer.

BACKGROUND: Aging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC. METHODS: RNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort. RESULTS: A six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations. CONCLUSION: A novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.

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.

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.

Significance of accurate hilar and intrapulmonary lymph node examination and prognostication in stage IA-IIA non-small cell lung cancer, a retrospective cohort study.

BACKGROUND: The examination of lymph nodes (LNs) plays an important role in the nodal staging of non-small cell lung cancer (NSCLC). For patients without LN metastasis, the main role of thorough LN examination is accurate staging, which weakens the effect of staging migration. To date, the role of hilar and intrapulmonary (N1) station LNs has not been fully appreciated. In this study, we aimed to confirm the significance of N1 LNs in long-term survival for stage IA-IIA NSCLC patients and to find the minimum number of LN to examine. METHODS: The data of patients who underwent radical lobectomy and were confirmed as having non-metastatic LNs from January 2008 to March 2018 were retrospectively screened. Pathology records were reviewed for the number of LNs examined. The Kaplan-Meier method and Cox regression model were used to identify survival and prognostic factors. RESULTS: The median number of resected N1 LNs was 8. The number of patients with 0-2 N1 LNs, 3-5 N1 LNs, 6-8 N1 LNs, 9-11 N1 LNs, and more than 11 N1 LNs examined was 181, 425, 477, 414, and 531, respectively. Sex (P = 0.004), age (P < 0.001), tumor size (P = 0.004), differentiation degree (P = 0.001), and number of N1 LNs examined (P = 0.008) were independent prognostic factors of overall survival. Gender (P = 0.006), age (P = 0.031), tumor size (P = 0.001), differentiation degree (P = 0.001), vascular invasion (P = 0.034), and number of N1 LNs examined (P = 0.007) were independent prognostic factors of disease-free survival. Compared with patients with 0-5 N1 LNs examined, patients with more than 5 N1 LNs examined had better OS (P = 0.015) and had better DFS (P = 0.015) if only a landmark 5-year follow-up was performed. CONCLUSION: Increasing the number of N1 LN examination might improve the long-term survival of T1-2N0 NSCLC patients. These data indicate that at least 6 N1 nodes examined is an essential part in surgical and pathological management but cannot prove this. This finding should be confirmed in a large, prospective randomized clinical study.

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.

Urachal carcinoma: Impact of recurrence pattern and lymphadenectomy on long-term outcomes.

BACKGROUND: Urachal carcinoma is a rare nonurothelial malignant tumor with high rates of local recurrence and systemic metastasis. Although radical resection is widely considered the standard treatment, there is still a debate regarding the benefits of lymphadenectomy. To explore these factors, we investigated the recurrence pattern of urachal cancer and the impact of lymphadenectomy on long-term survival. METHODS: The data of 62 patients pathologically diagnosed with urachal carcinoma at Sun Yat-sen University Cancer Center from 2002 to 2019 were retrospectively reviewed. Lymphadenectomy was defined as lymph nodes retrieved from the obturator, internal iliac, and external iliac lymph node stations. The Kaplan-Meier method and Cox regression model were used to identify prognostic factors. OS and DFS were the primary endpoints. RESULTS: Of the 47 males and 15 females included, 54 patients underwent partial cystectomy, and 27 patients underwent lymphadenectomy. The number of patients with Sheldon stage IIIA, IIIB, IIIC, IVA, and IVB were 43 (69.4%), 4 (6.5%) 3 (4.8%), 6 (9.7%), and 6 (9.7%), respectively. The median DFS was 32.7 months, and the mean OS was 114.6 months. Sheldon stage (P < .001) and tumor size (P = .001) were identified as independent prognostic factors for DFS, whereas Sheldon stage (P = .003), peritoneal metastasis (P = .006), distant metastasis (P = .024), and recurrence in pelvic lymph nodes (P = .015) were independent prognostic factors for OS. CONCLUSIONS: Urachal carcinoma has a high recurrence rate, but only peritoneal metastasis, distant metastasis, and recurrence in pelvic lymph nodes were found to be associated with OS. Lymphadenectomy was recommended because of its role in accurately staging the disease, and further research is needed to focus on lymphadenectomy and standardized the procedure.