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Background: Whether stage T1N2-3M0 non-small cell lung cancer (NSCLC) patients could benefit from surgery and the optimal surgical procedure have remained controversial and unclear. This study aimed to investigate whether stage T1N2-3M0 NSCLC can benefit from different surgery types and develop a tool for survival prediction. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients diagnosed with stage T1N2-3M0 NSCLC between 2000 and 2015. A 1:1 propensity score-matched (PSM) analysis was used to balance the distribution of clinical characteristics. Survival analyses were performed by using the Kaplan-Meier (KM) curves and Cox proportional hazards regression. All patients were randomly split at a ratio of 7:3 into training and validation cohorts. The nomogram was constructed by integrating all independent predictors for overall survival (OS) and cancer-specific survival (CSS). The model's performance was evaluated by discrimination, calibration ability, and risk stratification ability. Results: A total of 4,671 patients were enrolled. After 1:1 PSM, the distribution proportions of clinical characteristics in 1,146 patients were balanced (all P>0.05). The non-surgical approach was associated with worse survival compared with sublobectomy and lobectomy in the unmatched and matched cohorts. The multivariate Cox analysis showed that sublobectomy and lobectomy were both related to better OS and CSS rates compared with no surgery (P<0.001). Moreover, the results of subgroup analyses based on age, N stage, and radiotherapy or chemotherapy strategy were consistent. A total of 801 patients were included in the training cohort and 345 cases constituted the validation cohort. The nomogram constructed for the 1-, 3-, and 5-year OS and CSS prediction showed good discrimination, performance, and calibration both in the training and validation sets. Significant distinctions in survival curves between different risk groups stratified by prognostic scores were also observed (all P<0.001). Conclusions: Stage T1N2-3M0 NSCLC patients could benefit from sublobectomy or lobectomy, and lobectomy provides better survival benefits. We developed and validated nomograms, which could offer clinicians instructions for strategy making.
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Background: Limited data are available regarding perioperative outcomes in patients with non-small cell lung cancer (NSCLC) who undergo robotic-assisted thoracic surgery (RATS) after neoadjuvant chemoimmunotherapy. This study aimed to compare the perioperative outcomes of RATS and video-assisted thoracic surgery (VATS) in NSCLC patients after neoadjuvant chemoimmunotherapy. Methods: The study involved consecutive NSCLC patients treated with minimally invasive surgery (MIS) after neoadjuvant chemoimmunotherapy at a high-volume single center from September 2020 to October 2022. Short-term effects, including demographic, perioperative and pathological parameters, were compared between the RATS group and the VATS group. Results: A total of 119 patients were included in this study. Of these, 33 (27.7%) patients received RATS and 86 (72.3%) patients received VATS. Major pathological response (MPR) and pathological complete response (pCR) rates were comparable between the two groups. The RATS group had a higher number of dissected lymph nodes (21 vs. 18, P=0.03) and lymph node stations (7 vs. 6, P=0.004) compared with the VATS group but no differences were found in perioperative outcomes. Conclusions: These findings suggest that both RATS and VATS are safe and feasible options for NSCLC patients who have received neoadjuvant chemoimmunotherapy. Furthermore, RATS may offer advantages over VATS in patients who require a more extensive lymph node dissection.
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BACKGROUND: One of the most prevalent malignancies in the world is lung adenocarcinoma (LUAD), with a large number of people dying from lung cancer each year. Anoikis has a crucial function in tumor metastasis, promoting cancer cell shedding and survival from the primary tumor site. However, the role of anoikis in LUAD is still unclear. METHODS: The GeneCard database (https://www.genecards.org/) was utilized to obtain anoikis-related genes with correlation greater than 0.4. Differential analysis was employed to acquire differential genes. Univariate, multifactorial Cox analyses and the least absolute shrinkage and selection operator were then utilized to capture genes connected to overall survival time. These genes were used to build prognostic models. The predictive model was analyzed and visualized. Survival analysis was conducted on the model and risk scores were calculated. The TCGA samples were split into groups of low and high risk depending on risk scores. A Gene Expression Omnibus database sample was used for external verification. Immunization estimates were performed using ESTIMATE, CiberSort and single sample gene set enrichment analysis. The connection between the prognostic gene model and immune cells was analyzed. Drug susceptibility prediction analysis was performed. The clinical information for samples was extracted and analyzed. RESULTS: We selected six genes related to anoikis in LUAD to construct a prognosis model (CDC25C, ITPRIP, SLCO1B3, CDX2, CSPG4 and PIK3CG). Compared with cases of high-risk scores, the overall survival of those with low risk was significantly elevated based on Kaplan-Meier survival analysis. Immune function analysis exhibited that different risk groups had different immune states. The results of ESTIMATE, CiberSort and single sample gene set enrichment analysis showed great gaps in immunization between patients in the two groups. The normogram of the risk score and the LUAD clinicopathological features was constructed. Principal component analysis showed that this model could effectively distinguish the two groups of LUAD patients. CONCLUSIONS: We integrated multiple anoikis-related genes to build a prognostic model. This investigation demonstrates that anoikis-related genes can be used as a stratification element for fine therapy of individuals with LUAD.
Subject(s)
Adenocarcinoma of Lung , Lung Neoplasms , Humans , Anoikis/genetics , Prognosis , Adenocarcinoma of Lung/genetics , Lung Neoplasms/genetics , ImmunizationABSTRACT
BACKGROUND: Neoadjuvant immunotherapy has been demonstrated to be effective and safe in resectable non-small cell lung cancer (NSCLC) patients. However, the presence of different oncogenic driver mutations may affect the tumor microenvironment and consequently influence the clinical benefit from immunotherapy. METHODS: This retrospective study included consecutive NSCLC patients (stage IIA to IIIB) who underwent radical surgery after receiving neoadjuvant immunotherapy at a single high-volume center between December 2019 and August 2022. Pathological response and long-term outcomes were compared based on the driver oncogene status, and RNA sequencing analysis was conducted to investigate the transcriptomic characteristics before and after treatment. RESULTS: Of the 167 patients included in this study, 47 had oncogenic driver mutations. KRAS driver mutations were identified in 28 patients, representing 59.6% of oncogenic driver mutations. Of these, 17 patients had a major pathological response, which was significantly higher than in the non-KRAS driver mutation group (60.7% vs. 31.6%, P = 0.049). Multivariate Cox regression analysis further revealed that the KRAS driver mutation group was an independent prognostic factor for prolonged disease-free survival (hazard ratio: 0.10, P = 0.032). The median proportion of CD8+ T cells was significantly higher in the KRAS driver mutation NSCLCs than in the non-driver mutation group (18% vs. 13%, P = 0.030). Furthermore, immune-related pathways were enriched in the KRAS driver mutation NSCLCs and activated after immunotherapy. CONCLUSION: Our study suggests that NSCLC patients with KRAS driver mutations have a superior response to neoadjuvant immunotherapy, possibly due to their higher immunogenicity. The findings highlight the importance of considering oncogenic driver mutations in selecting neoadjuvant treatment strategies for NSCLC patients.
