Efficacy of neoadjuvant chemo-immunotherapy in non-small cell lung cancer: a real-world, multicenter, retrospective study.

Background: Resectable non-small cell lung cancer (NSCLC) patients have a high risk of recurrence. Multiple randomized controlled trials (RCTs) have shown that neoadjuvant chemo-immunotherapy brings new hope for these patients. The study aims to evaluate the safety, surgery-related outcomes and oncological outcomes for neoadjuvant chemo-immunotherapy in real-world setting with a large sample size and long-term follow-up. Methods: Patients with clinical stage IB-IIIB NSCLC who received neoadjuvant chemo-immunotherapy at two Chinese institutions were included in this retrospective cohort study. Surgical and oncological outcomes of the enrolled NSCLC patients were collected and analyzed. Results: There were 158 patients identified, of which 124 (78.5%) were at stage IIIA-IIIB and the remaining 34 (21.5%) were at stage IB-IIB. Forty-one patients (25.9%) received two cycles of neoadjuvant treatment, 80 (50.6%) had three cycles, and 37 (23.4%) had four cycles. Twenty-four patients (15.2%) experienced grade 3 or worse immune-related adverse events. The median interval time between the last neoadjuvant therapy and surgery was 37 [interquartile range (IQR), 31-43] days. Fifty-eight out of 96 (60.4%) central NSCLC patients who were expected to undergo complex surgery had the scope or the difficulty of operation reduced. Ninety-five (60.1%) patients achieved major pathologic response (MPR), including 62 (39.2%) patients with pathologic complete response (pCR). Multivariate regression analysis showed that no clinical factor other than programmed death-ligand 1 (PD-L1) expression was predictive of the pathological response. The median follow-up time from diagnosis was 27.1 months. MPR and pCR were significantly associated with improved progression-free survival (PFS) and overall survival (OS). Neither stage nor PD-L1 expression was significantly associated with long-term survival. Conclusions: The neoadjuvant chemo-immunotherapy is a feasible strategy for NSCLC with a favorable rate of pCR/MPR, modified resection and 2-year survival. No clinical factor other than PD-L1 expression was predictive of the pathological response. pCR/MPR may be effective surrogate endpoint for survival in NSCLC patients who received neoadjuvant chemo-immunotherapy.

Development of new techniques and clinical applications of liquid biopsy in lung cancer management.

Lung cancer is an exceedingly malignant tumor reported as having the highest morbidity and mortality of any cancer worldwide, thus posing a great threat to global health. Despite the growing demand for precision medicine, current methods for early clinical detection, treatment and prognosis monitoring in lung cancer are hampered by certain bottlenecks. Studies have found that during the formation and development of a tumor, molecular substances carrying tumor-related genetic information can be released into body fluids. Liquid biopsy (LB), a method for detecting these tumor-related markers in body fluids, maybe a way to make progress in these bottlenecks. In recent years, LB technology has undergone rapid advancements. Therefore, this review will provide information on technical updates to LB and its potential clinical applications, evaluate its effectiveness for specific applications, discuss the existing limitations of LB, and present a look forward to possible future clinical applications. Specifically, this paper will introduce technical updates from the prospectives of engineering breakthroughs in the detection of membrane-based LB biomarkers and other improvements in sequencing technology. Additionally, it will summarize the latest applications of liquid biopsy for the early detection, diagnosis, treatment, and prognosis of lung cancer. We will present the interconnectedness of clinical and laboratory issues and the interplay of technology and application in LB today.

Intelligent prognosis evaluation system for stage I-III resected non-small-cell lung cancer patients on CT images: a multi-center study.

Background: Prognosis is crucial for personalized treatment and surveillance suggestion of the resected non-small-cell lung cancer (NSCLC) patients in stage I-III. Although the tumor-node-metastasis (TNM) staging system is a powerful predictor, it is not perfect enough to accurately distinguish all the patients, especially within the same TNM stage. In this study, we developed an intelligent prognosis evaluation system (IPES) using pre-therapy CT images to assist the traditional TNM staging system for more accurate prognosis prediction of resected NSCLC patients. Methods: 20,333 CT images of 6371 patients from June 12, 2009 to March 24, 2022 in West China Hospital of Sichuan University, Mianzhu People's Hospital, Peking University People's Hospital, Chengdu Shangjin Nanfu Hospital and Guangan Peoples' Hospital were included in this retrospective study. We developed the IPES based on self-supervised pre-training and multi-task learning, which aimed to predict an overall survival (OS) risk for each patient. We further evaluated the prognostic accuracy of the IPES and its ability to stratify NSCLC patients with the same TNM stage and with the same EGFR genotype. Findings: The IPES was able to predict OS risk for stage I-III resected NSCLC patients in the training set (C-index 0.806; 95% CI: 0.744-0.846), internal validation set (0.783; 95% CI: 0.744-0.825) and external validation set (0.817; 95% CI: 0.786-0.849). In addition, IPES performed well in early-stage (stage I) and EGFR genotype prediction. Furthermore, by adopting IPES-based survival score (IPES-score), resected NSCLC patients in the same stage or with the same EGFR genotype could be divided into low- and high-risk subgroups with good and poor prognosis, respectively (p < 0.05 for all). Interpretation: The IPES provided a non-invasive way to obtain prognosis-related information from patients. The identification of IPES for resected NSCLC patients with low and high prognostic risk in the same TNM stage or with the same EGFR genotype suggests that IPES have potential to offer more personalized treatment and surveillance suggestion for NSCLC patients. Funding: This study was funded by the National Natural Science Foundation of China (grant 62272055, 92259303, 92059203), New Cornerstone Science Foundation through the XPLORER PRIZE, Young Elite Scientists Sponsorship Program by CAST (2021QNRC001), Clinical Medicine Plus X - Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities (K.C.), Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Chinese Academy of Medical Sciences (2021RU002), BUPT Excellent Ph.D. Students Foundation (CX2022104).

Individualized tumor-informed circulating tumor DNA analysis for postoperative monitoring of non-small cell lung cancer.

We report a personalized tumor-informed technology, Patient-specific pROgnostic and Potential tHErapeutic marker Tracking (PROPHET) using deep sequencing of 50 patient-specific variants to detect molecular residual disease (MRD) with a limit of detection of 0.004%. PROPHET and state-of-the-art fixed-panel assays were applied to 760 plasma samples from 181 prospectively enrolled early stage non-small cell lung cancer patients. PROPHET shows higher sensitivity of 45% at baseline with circulating tumor DNA (ctDNA). It outperforms fixed-panel assays in prognostic analysis and demonstrates a median lead-time of 299 days to radiologically confirmed recurrence. Personalized non-canonical variants account for 98.2% with prognostic effects similar to canonical variants. The proposed tumor-node-metastasis-blood (TNMB) classification surpasses TNM staging for prognostic prediction at the decision point of adjuvant treatment. PROPHET shows potential to evaluate the effect of adjuvant therapy and serve as an arbiter of the equivocal radiological diagnosis. These findings highlight the potential advantages of personalized cancer techniques in MRD detection.

Individualized dynamic methylation-based analysis of cell-free DNA in postoperative monitoring of lung cancer.

BACKGROUND: The feasibility of DNA methylation-based assays in detecting minimal residual disease (MRD) and postoperative monitoring remains unestablished. We aim to investigate the dynamic characteristics of cancer-related methylation signals and the feasibility of methylation-based MRD detection in surgical lung cancer patients. METHODS: Matched tumor, tumor-adjacent tissues, and longitudinal blood samples from a cohort (MEDAL) were analyzed by ultra-deep targeted sequencing and bisulfite sequencing. A tumor-informed methylation-based MRD (timMRD) was employed to evaluate the methylation status of each blood sample. Survival analysis was performed in the MEDAL cohort (n = 195) and validated in an independent cohort (DYNAMIC, n = 36). RESULTS: Tumor-informed methylation status enabled an accurate recurrence risk assessment better than the tumor-naïve methylation approach. Baseline timMRD-scores were positively correlated with tumor burden, invasiveness, and the existence and abundance of somatic mutations. Patients with higher timMRD-scores at postoperative time-points demonstrated significantly shorter disease-free survival in the MEDAL cohort (HR: 3.08, 95% CI: 1.48-6.42; P = 0.002) and the independent DYNAMIC cohort (HR: 2.80, 95% CI: 0.96-8.20; P = 0.041). Multivariable regression analysis identified postoperative timMRD-score as an independent prognostic factor for lung cancer. Compared to tumor-informed somatic mutation status, timMRD-scores yielded better performance in identifying the relapsed patients during postoperative follow-up, including subgroups with lower tumor burden like stage I, and was more accurate among relapsed patients with baseline ctDNA-negative status. Comparing to the average lead time of ctDNA mutation, timMRD-score yielded a negative predictive value of 97.2% at 120 days prior to relapse. CONCLUSIONS: The dynamic methylation-based analysis of peripheral blood provides a promising strategy for postoperative cancer surveillance. TRIAL REGISTRATION: This study (MEDAL, MEthylation based Dynamic Analysis for Lung cancer) was registered on ClinicalTrials.gov on 08/05/2018 (NCT03634826). https://clinicaltrials.gov/ct2/show/NCT03634826 .

The Prognostic Value of TTF-1/NKX2-1 in Lung Squamous Cell Carcinoma.

BACKGROUND: TTF-1/NKX2-1 is a lineage-specific transcription factor that is expressed in the thyroid gland, lung, and forehead. It functions as a key component in regulating lung morphogenesis and differentiation. It is mainly expressed in lung adenocarcinoma, while its prognostic value in non-small-cell lung cancer remains controversial. This study evaluates the prognostic value of TTF-1 in different cellular locations in lung squamous cell carcinoma (SCC) and adenocarcinoma (ADC). MATERIALS AND METHODS: The expression of TTF-1 was analyzed by immunohistochemistry in 492 patients (ADC 340 and SCC 152) who had undergone surgery between June 2004 and June 2012. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan-Meier method. RESULTS: Positive TTF-1 expression was 68.2% in ADC (located in the nucleus) and 29.6% in SCC (cytoplasm staining). The presence of TTF-1 was associated with better OS in SCC and ADC ( P =0.000 and P =0.003, respectively). In SCC, an increased level of TTF-1 was associated with a longer disease-free survival (DFS). Positive TTF-1 expression was an independent favorable prognostic factor in SCC ( P =0.020, HR: 2.789, 95%CI: 1.172-6.637) and ADC ( P =0.025, HR: 1.680, 95%CI: 1.069-2.641). CONCLUSIONS: TTF-1 was largely located in the nucleus of ADC, while it always accumulated in the cytoplasm of SCC. The higher level of TTF-1 in the different subcellular locations of ADC and SCC was an independent, favorable prognostic factor, respectively. Increased TTF-1 in the cytoplasm of SCC was associated with a longer OS and DFS.

Current and emerging applications of liquid biopsy in pan-cancer.

Cancer morbidity and mortality are growing rapidly worldwide and it is urgent to develop a convenient and effective method that can identify cancer patients at an early stage and predict treatment outcomes. As a minimally invasive and reproducible tool, liquid biopsy (LB) offers the opportunity to detect, analyze and monitor cancer in any body fluids including blood, complementing the limitations of tissue biopsy. In liquid biopsy, circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are the two most common biomarkers, displaying great potential in the clinical application of pan-cancer. In this review, we expound the samples, targets, and newest techniques in liquid biopsy and summarize current clinical applications in several specific cancers. Besides, we put forward a bright prospect for further exploring the emerging application of liquid biopsy in the field of pan-cancer precision medicine.

Organ preservation strategies after neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer: a multicenter retrospective cohort study.

BACKGROUND: Neoadjuvant chemoimmunotherapy has shown a good therapeutic effect on non-small cell lung cancer (NSCLC), which also opens up the possibility of applying organ preservation strategies. This study investigated the feasibility of modified surgery after potent neoadjuvant chemoimmunotherapy in central type NSCLC. METHODS: In this multicenter retrospective cohort study, patients with central type NSCLC who received 2-4 cycles of neoadjuvant chemoimmunotherapy between January 2019 and June 2022 at Air Force Medical University Tangdu Hospital and Peking University People's Hospital were eligible. Patients were divided into modified and nonmodified groups according to the extent of surgery, after which, the safety and long-term prognosis of surgery were investigated. RESULTS: A total of 84 patients were enrolled. Of 36 (42.9%) patients who underwent modified surgery, 21 patients underwent lobectomy, 12 patients underwent lobectomy with bronchoplasty, 2 patients underwent sleeve lobectomy, and 1 patient underwent bilobectomy. The modification rate for the initially estimated pneumonectomy, sleeve lobectomy, and bilobectomy was 48.6, 44.8, and 30%, respectively. Grades II-V postoperative complications were found in 5 (13.9%) patients in the modified group and 17 (35.4%) patients in the nonmodified group (relative risk, 0.393; 95% CI, 0.016-0.963; P =0.026). No significant difference was observed regarding the surgical approach, operative duration, blood loss, or R0 resection rate. The 2-year local recurrence rate was 3.7% (95% CI, 0.004-0.175) and 5.2% (95% CI, 0.012-0.168) in the modified group and nonmodified group, respectively. The 1-year PFS rate of modified and nonmodified groups was 97.1% (95% CI, 83.7-99.8) and 86.9% (95% CI, 73.4-94.4), respectively, while 2-year PFS were 89.8% (95% CI, 74.1-96.9) and 71.8% (95% CI, 56.7-83.4), respectively. CONCLUSION: Applying organ preservation strategies, that is, undergoing modified surgery after neoadjuvant chemoimmunotherapy, is feasible for selected central type NSCLC patients with favorable safety and long-term survival.

Systemic inflammation influences the prognosis of patients with radically resected non-small cell lung cancer and correlates with the immunosuppressive microenvironment.

The impact of host condition on prognosis of non-small cell lung cancer (NSCLC) and the interaction between host and NSCLC remain unclear. This study investigated the association between systemic inflammation and prognosis and characteristics of radically resected NSCLC. This study consisted of a cohort study and an exploratory study of institutional prospective databases. All participants underwent video-assisted thoracoscopic lobectomy as the primary treatment. Systemic inflammation was assessed before surgery using the advanced lung cancer inflammation index and the systemic inflammation response index. Next-generation sequencing and multiplex immunofluorescence analysis were conducted to delineate tumor characteristics. In the cohort study including 1507 participants, high inflammation was associated with poor disease-free survival and overall survival before and after propensity score matching and in multivariable analysis. Systemic inflammation showed good prognostic value for stage IA-IB NSCLC, and the prognostic value diminished with upstaging of NSCLC. In the exploratory study including 217 adenocarcinomas, tumor microenvironment of high inflammation group showed a greater abundance of PDL1+ tumor cells and immune cells, which were independent from driver gene mutations and clinicopathological characteristics. Spatial analysis demonstrated a higher frequency of immune-suppressed cellular neighborhood, increased avoidance between immune cells and PDL1- tumor cells and compromised immune killing and presentation in tumor microenvironment of high inflammation group. Systemic inflammation showed limited association with genomic mutations. Systemic inflammation may influence the prognosis of NSCLC at both the systematic level and the local immune response. The correlation between high inflammation and immunosuppressive microenvironment indicates a novel thread for anticancer treatment.

Lung adenocarcinoma promotion by air pollutants.

A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development1. Here we propose that environmental particulate matter measuring ≤2.5 µm (PM2.5), known to be associated with lung cancer risk, promotes lung cancer by acting on cells that harbour pre-existing oncogenic mutations in healthy lung tissue. Focusing on EGFR-driven lung cancer, which is more common in never-smokers or light smokers, we found a significant association between PM2.5 levels and the incidence of lung cancer for 32,957 EGFR-driven lung cancer cases in four within-country cohorts. Functional mouse models revealed that air pollutants cause an influx of macrophages into the lung and release of interleukin-1ß. This process results in a progenitor-like cell state within EGFR mutant lung alveolar type II epithelial cells that fuels tumorigenesis. Ultradeep mutational profiling of histologically normal lung tissue from 295 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 53% of healthy tissue samples, respectively. These findings collectively support a tumour-promoting role for  PM2.5 air pollutants  and provide impetus for public health policy initiatives to address air pollution to reduce disease burden.

Multi-omics integrated circulating cell-free DNA genomic signatures enhanced the diagnostic performance of early-stage lung cancer and postoperative minimal residual disease.

BACKGROUND: Liquid biopsy is a promising non-invasive alternative for cancer screening and minimal residual disease (MRD) detection, although there are some concerns regarding its clinical applications. We aimed to develop an accurate detection platform based on liquid biopsy for both cancer screening and MRD detection in patients with lung cancer (LC), which is also applicable to clinical use. METHODS: We applied a modified whole-genome sequencing (WGS) -based High-performance Infrastructure For MultIomics (HIFI) method for LC screening and postoperative MRD detection by combining the hyper-co-methylated read approach and the circulating single-molecule amplification and resequencing technology (cSMART2.0). FINDINGS: For early screening of LC, the LC score model was constructed using the support vector machine, which showed sensitivity (51.8%) at high specificity (96.3%) and achieved an AUC of 0.912 in the validation set prospectively enrolled from multiple centers. The screening model achieved detection efficiency with an AUC of 0.906 in patients with lung adenocarcinoma and outperformed other clinical models in solid nodule cohort. When applied the HIFI model to real social population, a negative predictive value (NPV) of 99.92% was achieved in Chinese population. Additionally, the MRD detection rate improved significantly by combining results from WGS and cSMART2.0, with sensitivity of 73.7% at specificity of 97.3%. INTERPRETATION: In conclusion, the HIFI method is promising for diagnosis and postoperative monitoring of LC. FUNDING: This study was supported by CAMS Innovation Fund for Medical Sciences, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, Beijing Natural Science Foundation and Peking University People's Hospital.

Towards the molecular era of discriminating multiple lung cancers.

In the era of histopathology-based diagnosis, the discrimination between multiple lung cancers (MLCs) poses significant uncertainties and has thus become a clinical dilemma. However, recent significant advances and increased application of molecular technologies in clonal relatedness assessment have led to more precision in distinguishing between multiple primary lung cancers (MPLCs) and intrapulmonary metastasis (IPMs). This review summarizes recent advances in the molecular identification of MLCs and compares various methods based on somatic mutations, chromosome alterations, microRNAs, and tumor microenvironment markers. The paper also discusses current challenges at the forefront of genomics-based discrimination, including the selection of detection technology, application of next-generation sequencing, and intratumoral heterogeneity (ITH). In summary, this paper highlights an entrance into the primary stage of molecule-based diagnostics.

Near-infrared fluorescence imaging of thoracic duct in minimally invasive esophagectomy.

Chylothorax is a serious complication after esophagectomy and there are unmet needs for new intraoperative navigation tools to reduce its incidence. The aim of this study is to explore the feasibility and effectiveness of near-infrared fluorescence imaging (NIR-FI) with indocyanine green (ICG) to identify thoracic ducts (TDs) and chyle leakage during video-assisted thoracoscopic esophagectomy. We recruited 41 patients who underwent thoraco-laparoscopic minimally invasive esophagectomy (MIE) for esophageal cancer in this prospective, open-label, single-arm clinical trial. ICG was injected into the right inguinal region before operations, after which TD anatomy and potential chyle leakage were checked under the near-infrared fluorescence intraoperatively. In 38 of 41 patients (92.7%) using NIR-FI, TDs were visible in high contrast. The mean signal-to-background ratio (SBR) value of all fluorescent TDs was 3.05 ± 1.56. Fluorescence imaging of TDs could be detected 0.5 hours after ICG injection and last up to 3 hours with an acceptable SBR value. The optimal observation time window is from about 1 to 2 hours after ICG injection. Under the guidance of real-time NIR-FI, three patients were found to have chylous leakage and the selective TD ligations were performed intraoperatively. No patient had postoperative chylothorax. NIR-FI with ICG can provide highly sensitive and real-time assessment of TDs as well as determine the source of chyle leakage, which might help reduce TD injury and direct selective TD ligation. It could be a promising navigation tool to reduce the incidence of chylothorax after minimally invasive esophagectomy.

Potential clinical utility of liquid biopsy in early-stage non-small cell lung cancer.

BACKGROUND: Liquid biopsy has been widely researched for early diagnosis, prognostication and disease monitoring in lung cancer, but there is a need to investigate its clinical utility for early-stage non-small cell lung cancer (NSCLC). METHODS: We performed a meta-analysis and systematic review to evaluate diagnostic and prognostic values of liquid biopsy for early-stage NSCLC, regarding the common biomarkers, circulating tumor cells, circulating tumor DNA (ctDNA), methylation signatures, and microRNAs. Cochrane Library, PubMed, EMBASE databases, ClinicalTrials.gov, and reference lists were searched for eligible studies since inception to 17 May 2022. Sensitivity, specificity and area under the curve (AUC) were assessed for diagnostic values. Hazard ratio (HR) with a 95% confidence interval (CI) was extracted from the recurrence-free survival (RFS) and overall survival (OS) plots for prognostic analysis. Also, potential predictive values and treatment response evaluation were further investigated. RESULTS: In this meta-analysis, there were 34 studies eligible for diagnostic assessment and 21 for prognostic analysis. The estimated diagnostic values of biomarkers for early-stage NSCLC with AUCs ranged from 0.84 to 0.87. The factors TNM stage I, T1 stage, N0 stage, adenocarcinoma, young age, and nonsmoking contributed to a lower tumor burden, with a median cell-free DNA concentration of 8.64 ng/ml. For prognostic analysis, the presence of molecular residual disease (MRD) detection was a strong predictor of disease relapse (RFS, HR, 4.95; 95% CI, 3.06-8.02; p < 0.001) and inferior OS (HR, 3.93; 95% CI, 1.97-7.83; p < 0.001), with average lead time of 179 ± 74 days between molecular recurrence and radiographic progression. Predictive values analysis showed adjuvant therapy significantly benefited the RFS of MRD + patients (HR, 0.27; p < 0.001), while an opposite tendency was detected for MRD - patients (HR, 1.51; p = 0.19). For treatment response evaluation, a strong correlation between pathological response and ctDNA clearance was detected, and both were associated with longer survival after neoadjuvant therapy. CONCLUSIONS: In conclusion, our study indicated liquid biopsy could reliably facilitate more precision and effective management of early-stage NSCLC. Improvement of liquid biopsy techniques and detection approaches and platforms is still needed, and higher-quality trials are required to provide more rigorous evidence prior to their routine clinical application.

Research Progress on Postoperative Minimal/Molecular Residual Disease Detection in Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide. Approximately 10%-50% of patients experience relapse after radical surgery, which may be attributed to the persistence of minimal/molecular residual disease (MRD). Circulating tumor DNA (ctDNA), a common liquid biopsy approach, has been demonstrated to have significant clinical merit. In this study, we review the evidence supporting the use of ctDNA for MRD detection and discuss the potential clinical applications of postoperative MRD detection, including monitoring recurrence, guiding adjuvant treatment, and driving clinical trials in lung cancer. We will also discuss the problems that prevent the routine application of ctDNA MRD detection. Multi-analyte methods and identification of specific genetic and molecular alterations, especially methylation, are effective detection strategies and show considerable prospects for future development. Interventional prospective studies based on ctDNA detection are needed to determine whether the application of postoperative MRD detection can improve the clinical outcomes of lung cancer patients, and the accuracy, sensitivity, specificity, and robustness of different detection methods still require optimization and refinement.

Spatiotemporal genomic analysis reveals distinct molecular features in recurrent stage I non-small cell lung cancers.

Stage I non-small cell lung cancer (NSCLC) presents diverse outcomes. To identify molecular features leading to tumor recurrence in early-stage NSCLC, we perform multiregional whole-exome sequencing (WES), RNA sequencing, and plasma-targeted circulating tumor DNA (ctDNA) detection analysis between recurrent and recurrent-free stage I NSCLC patients (CHN-P cohort) who had undergone R0 resection with a median 5-year follow-up time. Integrated analysis indicates that the multidimensional clinical and genomic model can stratify the prognosis of stage I NSCLC in both CHN-P and EUR-T cohorts and correlates with positive pre-surgical deep next generation sequencing (NGS) ctDNA detection. Increased genomic instability related to DNA interstrand crosslinks and double-strand break repair processes is significantly associated with early tumor relapse. This study reveals important molecular insights into stage I NSCLC and may inform clinical postoperative treatment and follow-up strategies.

Comprehensive Analysis of Clinical Logistic and Machine Learning-Based Models for the Evaluation of Pulmonary Nodules.

Introduction: Over the years, multiple models have been developed for the evaluation of pulmonary nodules (PNs). This study aimed to comprehensively investigate clinical models for estimating the malignancy probability in patients with PNs. Methods: PubMed, EMBASE, Cochrane Library, and Web of Science were searched for studies reporting mathematical models for PN evaluation until March 2020. Eligible models were summarized, and network meta-analysis was performed on externally validated models (PROSPERO database CRD42020154731). The cut-off value of 40% was used to separate patients into high prevalence (HP) and low prevalence (LP), and a subgroup analysis was performed. Results: A total of 23 original models were proposed in 42 included articles. Age and nodule size were most often used in the models, whereas results of positron emission tomography-computed tomography were used when collected. The Mayo model was validated in 28 studies. The area under the curve values of four most often used models (PKU, Brock, Mayo, VA) were 0.830, 0.785, 0.743, and 0.750, respectively. High-prevalence group (HP) models had better results in HP patients with a pooled sensitivity and specificity of 0.83 (95% confidence interval [CI]: 0.78-0.88) and 0.71 (95% CI: 0.71-0.79), whereas LP models only achieved pooled sensitivity and specificity of 0.70 (95% CI: 0.60-0.79) and 0.70 (95% CI: 0.62-0.77). For LP patients, the pooled sensitivity and specificity decreased from 0.68 (95% CI: 0.57-0.78) and 0.93 (95% CI: 0.87-0.97) to 0.57 (95% CI: 0.21-0.88) and 0.82 (95% CI: 0.65-0.92) when the model changed from LP to HP models. Compared with the clinical models, artificial intelligence-based models have promising preliminary results. Conclusions: Mathematical models can facilitate the evaluation of lung nodules. Nevertheless, suitable model should be used on appropriate cohorts to achieve an accurate result.

Artificial intelligence: opportunities in lung cancer.

PURPOSE OF REVIEW: In this article, we focus on the role of artificial intelligence in the management of lung cancer. We summarized commonly used algorithms, current applications and challenges of artificial intelligence in lung cancer. RECENT FINDINGS: Feature engineering for tabular data and computer vision for image data are commonly used algorithms in lung cancer research. Furthermore, the use of artificial intelligence in lung cancer has extended to the entire clinical pathway including screening, diagnosis and treatment. Lung cancer screening mainly focuses on two aspects: identifying high-risk populations and the automatic detection of lung nodules. Artificial intelligence diagnosis of lung cancer covers imaging diagnosis, pathological diagnosis and genetic diagnosis. The artificial intelligence clinical decision-support system is the main application of artificial intelligence in lung cancer treatment. Currently, the challenges of artificial intelligence applications in lung cancer mainly focus on the interpretability of artificial intelligence models and limited annotated datasets; and recent advances in explainable machine learning, transfer learning and federated learning might solve these problems. SUMMARY: Artificial intelligence shows great potential in many aspects of the management of lung cancer, especially in screening and diagnosis. Future studies on interpretability and privacy are needed for further application of artificial intelligence in lung cancer.