Recent research data showed the concept that "surgery is still the main treatment for early non-small cell lung cancer (NSCLC)" now has new connotation: (1) Pure ground glass nodule (GGO) like lung adenocarcinoma should be regarded as a new clinical issue compared to solid tumors to avoid over-treatment. (2) The deep meaning of multidisciplinary pathological classification of lung adenocarcinoma should be fully understood to avoid over-diagnosis. (3) The T staging of lung adenocarcinoma mixed with GGO components should be correctly understood to avoid over-staging. (4) We should carefully understand the new data of relationship between lung resection extent and prognosis to avoid excessive resection. (5) Attention should be paid to the research progress of minimal residual disease (MRD) to avoid possible insufficient treatment.
Lung cancer has the highest incidence and mortality rates among malignant tumors both in China and worldwide, with approximately 85% of cases being non-small cell lung cancer (NSCLC). In the diagnosis and treatment of lung cancer, conventional imaging and tissue biopsy are often limited by insufficient sensitivity or invasive risks, making it difficult to meet the demands of future precision medicine. In recent years, artificial intelligence (AI)-based radiomics and autoantibody-based liquid biopsy have developed rapidly and have become major research focuses. AI radiomics significantly improves the accuracy of traditional imaging diagnosis by autonomously learning from large-scale imaging databases. Autoantibody liquid biopsy, on the other hand, utilizes tumor-associated autoantigens and antibodies as biomarkers, offering the advantages of being non-invasive, precise, efficient, and capable of reflecting spatiotemporal tumor heterogeneity, thereby demonstrating great potential in NSCLC diagnosis and treatment. This review summarizes recent research advances in autoantibody liquid biopsy and AI radiomics for the management of lung cancer.
Lung cancer is the most frequent cancer and the leading cause of cancer death all around the world. Anti-programmed cell death 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) therapies have significantly improved the outcomes of non-small cell lung cancer (NSCLC) patients in recent years. However, the objective response rate in non-screened patients is only about 20%. It is very important to screen out the potential patients suitable for immunotherapy. Immunohistochemical staining of tumor tissue biopsies with PD-L1 antibodies can predict the therapeutic response to immunotherapy to some extent, but it still has some limitations. Recently some clinical studies have shown that PD-L1 expression in circulating tumor cells (CTC-PD-L1) is a potential independent biomarker and may provide important information for immunotherapy in NSCLC. This article will review technology for CTC-PD-L1 detection and the predictive value of CTC-PD-L1 for immunotherapy in NSCLC and review the latest clinical research progress.
Objective To systematically evaluate the profitability and efficacy of neoadjuvant chemotherapy in patients with stage Ⅲa non-small cell lung cancer. Methods Randomized controlled trials (RCT) on neoadjuvant chemotherapy for stage Ⅲa non-small cell lung cancer were collected from WangFang Data database, Web of Science, PubMed, EMbase, CNKI, The Cochrane Library, VIP and CBM databases. From building to October 2017. After two independent reviewers screened the literature, extracted data and assessed the risk of being included in the study, Meta-analysis was performed using RevMan 5.3 software. Results A total of 15 RCT were included, including 1899 non-small cell lung cancer patients. The results of Meta analysis showed that the resection rate of R0 in neoadjuvant chemotherapy group was significantly higher than that in control group (OR=2.04, 95%CI 1.52 to 2.74, P<0.05), and there was no significant difference in postoperative complications between two groups (OR=1.23, 95%CI 0.89 to 1.69, P=0.22). In terms of survival rate, the neoadjuvant chemotherapy group could improve patients for one year (OR=1.38, 95%CI 1.01 to 1.88, P=0.04), three years (OR=1.57, 95%CI 1.16 to 2.12, P=0.004) and 5 years survival rate (OR=2.09, 95%CI 1.24 to 3.53, P=0.005) significance of learning. Conclusion Compared with the control group, neoadjuvant chemotherapy can improve the surgical R0 resection rate and the one, three and five year survival rate of patients with stage Ⅲa non-small cell lung cancer without increasing the postoperative complications. Due to the quantity and quality limitations of the included studies, the above conclusion still needs to be verified by more high-quality research.
ObjectiveTo explore the short-term efficacy and safety of pembrolizumab combined with chemotherapy in the neoadjuvant treatment of non-small cell lung cancer. MethodsThe clinical data of 11 male patients with non-small cell lung cancer who underwent pembrolizumab combined with neoadjuvant chemotherapy in the Department of Thoracic Surgery, the First Affiliated Hospital of Xi'an Jiaotong University from December 2019 to June 2021 were retrospectively analyzed. The average age of the patients was 52.0-79.0 (62.0±6.9) years. The imaging data and pathological changes before and after neoadjuvant treatment were compared, and adverse reactions during neoadjuvant treatment were recorded. Objective remission rate (ORR) and main pathological remission rate (MPR) and pathological complete remission rate (pCR) were the main observation endpoints. ResultsAfter preoperative neoadjuvant therapy with pembrolizumab combined with platinum or paclitaxel, all patients successfully underwent thoracoscopic radical resection of lung cancer. The ORR was 72.7%, and the MPR was 81.8%. Among them, 45.5% of patients achieved pCR. The main adverse reactions were hypoalbuminemia, decreased appetite and nausea. The mortality rate within 30 days after surgery was 0, and no tumor metastasis was observed. ConclusionPembrolizumab combined with neoadjuvant chemotherapy is safe and feasible to treat non-small cell lung cancer, and the short-term efficacy is beneficial.
Lung cancer is one of the leading causes of cancer deaths worldwide. Many options including surgery, radiotherapy, chemotherapy, targeted therapy and immunotherapy have been applied in the treatment for lung cancer patients. However, how to develop individualized treatment plans for patients and accurately determine the prognosis of patients is still a very difficult clinical problem. In recent years, radiomics, as an emerging method for medical image analysis, has gradually received the attention from researchers. It is based on the assumption that medical images contain a vast amount of biological information about patients that is difficult to identify with naked eyes but can be accessed by computer. One of the most common uses of radiomics is the diagnosis and treatment of non-small cell lung cancer (NSCLC). In this review, we reviewed the current researches on chest CT-based radiomics in the diagnosis and treatment of NSCLC and provided a brief summary of the current state of research in this field, covering various aspects of qualitative diagnosis, efficacy prediction, and prognostic analysis of lung cancer. We also briefly described the main current technical limitations of this technology with the aim of gaining a broader understanding of its potential role in the diagnosis and treatment of NSCLC and advancing its development as a tool for individualized management of NSCLC patients.
ObjectiveTo assess the prognostic significance of the Controlling Nutritional Status (CONUT) score in patients with non-small cell lung cancer (NSCLC) and its association with clinicopathological characteristics. MethodsThe relevant studies investigating the association between CONUT score and prognosis of NSCLC patients were systematically searched in the PubMed, Web of Science, EMbase, Cochrane Library, CNKI, Wanfang Database and other databases from their inception to July 2023. Two independent researchers screened the references according to predefined inclusion and exclusion criteria, extracted data and conducted quality assessment. The quality of included references was evaluated using New Castle-Ottawa Scale (NOS). The meta-analysis was performed using Stata 17.0 software, and a combined hazard ratio (HR) or odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the association of CONUT score with prognosis and clinicopathological characteristics in NSCLC patients. ResultsA total of 17 cohort studies, comprising 5182 NSCLC patients with stage Ⅰ-Ⅳ, were included in this analysis. All studies had a NOS≥6 points. The meta-analysis showed that there was a significant correlation between CONUT score and overall survival (OS) as well as disease-free survival (DFS) among NSCLC patients: the higher the score, the shorter the OS [HR=1.87, 95%CI (1.58, 2.21), P<0.001] and DFS [HR=1.91, 95%CI (1.63, 2.24), P<0.001]. These differences were statistically significant. Furthermore, CONUT score was significantly associated with age, smoking status, tumor stage, and N stage (P<0.05). ConclusionA higher CONUT score is associated with a poorer OS and DFS in patients with NSCLC, and CONUT score can be used as a potential predictor of NSCLC prognosis.
ObjectiveTo explore the association of pretreatment hyponatremia with clinicopathological and prognostic characteristics of non-small cell lung cancer (NSCLC) patients. MethodsThe PubMed, EMbase, Web of Science, VIP, CNKI and WanFang databases were searched from the inception to July 12, 2021 for relevant literatures. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS) score. The relative risk (RR) and hazard ratio (HR) with 95% confidence interval (CI) were combined to assess the relationship between pretreatment hyponatremia and clinicopathological and prognostic characteristics. The prognostic indicators included the overall survival (OS) and progression-free survival (PFS). All statistical analysis was conducted by the STATA 15.0 software. ResultsA total of 10 high-quality studies (NOS score≥6 points) involving 10 045 patients were enrolled and all participants were from Asian or European regions. The pooled results demonstrated that male [RR=1.18, 95%CI (1.02, 1.36), P=0.026], non-adenocarcinoma [RR=0.86, 95%CI (0.81, 0.91), P＜0.001] and TNM Ⅲ-Ⅳ stage [RR=1.17, 95%CI (1.12, 1.21), P＜0.001] patients were more likely to experience hyponatremia. Besides, pretreatment hyponatremia was significantly related to worse OS [HR=1.83, 95%CI (1.53, 2.19), P＜0.001] and PFS [HR=1.54, 95%CI (1.02, 2.34), P=0.040]. Pretreatment hyponatremia was a risk factor for poor prognosis of NSCLC patients. ConclusionMale, non-adenocarcinoma and advance stage NSCLC patients are more likely to experience hyponatremia. Meanwhile, the pretreatment sodium level can be applied as one of the prognostic evaluation indicators in NSCLC and patients with hyponatremia are more likely to have poor survival. However, more researches are still needed to verify above findings.
Objective To explore the association between the preoperative systemic immune-inflammation index (SII) and prognosis in non-small cell lung cancer (NSCLC) patients. Methods A comprehensive literature survey was performed on PubMed, Web of Science, EMbase, The Cochrane Library, Wanfang, and CNKI databases to search the related studies from inception to December 2021. The hazard ratio (HR) and 95% confidence interval (CI) were combined to evaluate the correlation of the preoperative SII with overall survival (OS), disease-free survival (DFS), and recurrence-free survival (RFS) in NSCLC patients. Results A total of 11 studies involving 9 180 patients were eventually included. The combined analysis showed that high SII levels were significantly associated with worse OS (HR=1.61, 95%CI 1.36-1.90, P<0.001), DFS (HR=1.50, 95%CI 1.34-1.68, P<0.001), and RFS (HR=1.17, 95%CI 1.04-1.33, P<0.001). Subgroup analyses also further verified the above results. Conclusion Preoperative SII is a powerful prognostic biomarker for predicting outcome in patients with operable NSCLC and contribute to prognosis evaluation and treatment strategy formulation. However, more well-designed and prospective studies are warranted to verify our findings.
In recent years, the computer science represented by artificial intelligence and high-throughput sequencing technology represented by omics play a significant role in the medical field. This paper reviews the research progress of the application of artificial intelligence combined with omics data analysis in the diagnosis and treatment of non-small cell lung cancer (NSCLC), aiming to provide ideas for the development of a more effective artificial intelligence algorithm, and improve the diagnosis rate and prognosis of patients with early NSCLC through a non-invasive way.