Lung cancer staging: a concise update

Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Is Associated With Recurrence and Survival of Resectable Non-Small Cell Lung Cancer (NSCLC): A Retrospective Study

INTRODUCTION

Curative lung resection remains the key therapeutic strategy for early-stage non-small cell lung cancer (NSCLC). However, a proportion of patients still experience variable outcomes and eventually develop recurrence or die from their disease. Proprotein convertase subtilisin/kexin type 9 (PCSK9) has been identified as a deleterious factor that inhibits tumor cells apoptosis and leads to reduction of lymphocyte infiltration. However, there has been no research on the predicted role of PCSK9 as an immunohistochemical biomarker with survival in resectable NSCLC.

METHODS

One hundred sixty-three patients with resectable NSCLC were retrospectively reviewed, and PCSK9 expression of resected NSCLC was analyzed by immunohistochemistry using tissue microarrays.

RESULTS

PCSK9 was associated with recurrence (42.1% relapsed in the PCSK9lo group versus 57.9% relapsed in the PCSK9hi group, P = 0.006) and survival status (39.6% dead in PCSK9lo group versus 60.4% dead in PCSK9hi group, P = 0.004) in patients with resectable NSCLC. Moreover, resectable NSCLC patients with higher PCSK9 expression in tumor tissue experienced poorer disease-free survival (median disease-free survival: 10.5 versus 25.2 mo, hazard ratio = 1.620, 95% confidence interval: 1.124-2.334) and overall suvrival (median overall suvrival: 20.0 versus 54.1 mo, hazard ratio = 1.646, 95% confidence interval: 1.101-2.461) compared to those with lower PCSK9 expression.

CONCLUSIONS

High PCSK9 expression of tumor was correlated with recurrence and worse survival status of resectable NSCLC in our retrospective study, which indicated that PCSK9 in NSCLC may be an immunohistochemical biomarker of poor prognosis for patients with resectable NSCLC. Further large-scale prospective studies are warranted to establish these results.

Diagnostic and prognostic value of serum soluble B7-H3 in nonsmall cell lung cancer

The aim of this study was to investigate the utility of serum soluble B7-H3 (sB7-H3) as a diagnostic marker for early-stage nonsmall cell lung cancer (NSCLC) and its potential for evaluating the prognosis of patients with advanced-stage NSCLC. In this study, an ELISA was employed to detect the expression levels of sB7-H3 in a cohort of patients diagnosed with NSCLC ( n  = 122) and a control group ( n  = 42) during the same observation period. Comparative analyses were conducted to ascertain the variations in sB7-H3 concentrations between the NSCLC cohort and the healthy control group, as well as across pathological types and the presence and absence of lymph node metastasis. (1) The concentration of sB7-H3 in patients diagnosed with NSCLC exhibited a statistically significant increase compared to that observed in the healthy control group ( P  < 0.05). Elevated expression levels of sB7-H3 demonstrated a significant correlation with pathological type, lymph node metastasis, tumor, node and metastasis stage and programmed cell death ligand (PD-L1) expression ( P  < 0.05). (2) The diagnostic utility of sB7-H3 for the diagnosis of NSCLC and the heightened expression of PD-L1 demonstrated high levels of sensitivity and specificity. (3) Elevated levels of sB7-H3 emerged as an independent risk factor impacting the overall survival of patients diagnosed with advanced NSCLC. The findings of this study suggest that sB7-H3 holds promise as a diagnostic tool for early-stage NSCLC. The elevated expression of sB7-H3 appears to serve as a reliable indicator for assessing the prognosis of patients diagnosed with advanced NSCLC.

Prognostic significance of CT-determined sarcopenia in older patients with advanced squamous cell lung cancer treated with programmed death-1 inhibitors

Sarcopenia has been associated with higher toxicity induced by anti-cancer treatments and shorter survival in patients with squamous cell lung carcinoma (SqCLC). Over the past few decades, immune checkpoint inhibitors (ICIs) significantly improves the prognosis. However, few clinical studies explored the effectiveness of immunotherapy in the elderly population. Here, we performed a retrospective analysis to determine the prognostic role of sarcopenia in older patients with SqCLC receiving ICIs. We retrospectively assessed SqCLC patients who were treated with PD-1 inhibitors and all patients were at least 70 years old. Pre-treatment sarcopenic status was determined by analyzing L3 skeletal muscle index (SMI) with chest CT. Progression-free survival (PFS), disease-specific survival (DSS) and overall survival (OS) were estimated using the Kaplan-Meier method, and the differences in survival were compared using the log-rank test. Among 130 male SqCLC patients, 93 had sarcopenia. Patients with sarcopenia were older and had a lower body mass index (BMI). Over an average follow-up of 20.8 months, 92 patients died. For all 130 patients, the mean OS was 13.3 months. Patients with sarcopenia had a significantly shorter OS and PFS than those without sarcopenia (OS, 12.4 ± 5.2 months vs. 15.5 ± 10.5 months, P = 0.028; PFS, 6.4 ± 2.9 months vs. 7.7 ± 4.2 months; P = 0.035). Multivariable analysis showed that sarcopenia was an independent prognostic factor for shorter OS and PFS. CT-determined sarcopenia is an independent prognostic factor for older patients with SqCLC receiving ICIs.

Molecular Stratification and Treatment Monitoring of Lung Cancer Using a Small Extracellular Vesicle-Activated Nanocavity Architecture

Development of molecular diagnostics for lung cancer stratification and monitoring is crucial for the rational planning and timely adjustment of treatments to improve clinical outcomes. In this regard, we propose a nanocavity architecture to sensitively profile the protein signature on small extracellular vesicles (sEVs) to enable accurate, noninvasive staging and treatment monitoring of lung cancer. The nanocavity architecture is formed by molecular recognition through the binding of sEVs with the nanobox-based core-shell surface-enhanced Raman scattering (SERS) barcodes and mirrorlike, asymmetric gold microelectrodes. By imposing an alternating current on the gold microelectrodes, a nanofluidic shear force was stimulated that supported the binding of sEVs and the efficient assembly of the nanoboxes. The binding of sEVs further induced a nanocavity between the nanobox and the gold microelectrode that significantly amplified the electromagnetic field to enable the simultaneous enhancement of Raman signals from four SERS barcodes and generate patient-specific molecular sEV signatures. Importantly, evaluated on a cohort of clinical samples (n = 76) on the nanocavity architecture, the acquired patient-specific sEV molecular signatures achieved accurate identification, stratification, and treatment monitoring of lung cancer patients, highlighting its potential for transition to clinical utility.

A ferroptosis-related signature predicts the clinical diagnosis and prognosis, and associates with the immune microenvironment of lung cancer

Targeting ferroptosis-related pathway is a potential strategy for treatment of lung cancer (LC). Consequently, exploration of ferroptosis-related markers is important for treating LC. We collected LC clinical data and mRNA expression profiles from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained through FerrDB database. Expression analysis was performed to obtain differentially expressed FRGs. Diagnostic and prognostic models were constructed based on FRGs by LASSO regression, univariate, and multivariate Cox regression analysis, respectively. External verification cohorts GSE72094 and GSE157011 were used for validation. The interrelationship between prognostic risk scores based on FRGs and the tumor immune microenvironment was analyzed. Immunocytochemistry, Western blotting, and RT-qPCR detected the FRGs level. Eighteen FRGs were used for diagnostic models, 8 FRGs were used for prognostic models. The diagnostic model distinguished well between LC and normal samples in training and validation cohorts of TCGA. The prognostic models for TCGA, GSE72094, and GSE157011 cohorts significantly confirmed lower overall survival (OS) in high-risk group, which demonstrated excellent predictive properties of the survival model. Multivariate Cox regression analysis further confirmed risk score was an independent risk factor related with OS. Immunoassays revealed that in high-risk group, a significantly higher proportion of Macrophages_M0, Neutrophils, resting Natural killer cells and activated Mast cells and the level of B7H3, CD112, CD155, B7H5, and ICOSL were increased. In conclusion, diagnostic and prognostic models provided superior diagnostic and predictive power for LC and revealed a potential link between ferroptosis and TIME.

N1-positive non-small cell lung cancer: surgeons' perspective before undertaking a major resection

Among various reasons for a rise in surgical referrals for locally advanced non-small cell lung cancer, few are improved clinical-pathological staging, better understanding of oncological driver mutation, and aggressive neoadjuvant treatment options. These cases with positive ipsilateral bronchopulmonary lymph nodes are intriguing subset where multiple treatment options have been explored to improve disease-free survival. Targeted neoadjuvant therapy followed by surgical resection is becoming a new norm and surgeons are referred these complex cases. This narrative review is highlighting the importance of proper preoperative staging, contemporary practices in surgical decision-making, and procedural aspect of hilar node dissection.

Endobronchial ultrasound-transbronchial needle aspiration: effectiveness and accuracy in non-small cell lung cancer staging

INTRODUCTION

Endobronchial ultrasound-transbronchial needle aspiration (EBUS-TBNA) has a cardinal role in the diagnosis and staging of non-small cell lung cancer (NSCLC), providing an accurate nodal staging in a less invasive way than surgical biopsy. The aim of this study was to assess the diagnostic accuracy of EBUS-TBNA in the pre-operative NSCLC mediastinal staging, as well as to evaluate EBUS-TBNA specificity and sensibility in our cohort.

METHODS

We retrospectively analyzed data of NSCLC patients who underwent EBUS-TBNA followed by major pulmonary resection between January 2020 and December 2022. EBUS-TBNA was performed in patients with NSCLC (central T ≤ 3 cm, peripheral/central T > 3 cm), following the ESTS guidelines. The target nodes were selected on the basis of their radiologic/metabolic characteristics. Each procedure was conducted together with rapid on-site cytological evaluation (ROSE).

RESULTS

Twenty-five patients were included (M/F = 17/8). At least three needle passages on each target lymph node were performed. No complications during or after the procedures occurred. We found a 100% correspondence between ROSE on the sampled nodes and postoperative pathologic findings. An upstaging occurred in three cases (12%) because of the involvement of stations 5 and 6 (not accessible via EBUS), while the only case of downstaging (N2 → N0, 4%) was probably due to intercurrent neoadjuvant chemotherapy. In all cases, EBUS-TBNA has proved to achieve a diagnostic procedure on the target nodes.

CONCLUSIONS

EBUS-TBNA is a safe and effective procedure that offers high sensitivity and specificity when performed together with ROSE, which improves the accuracy of sampling. Doubt on nodal stations 5 and 6 involvement should be settled by other techniques.

Exploration and machine learning model development for T2 NSCLC with bronchus infiltration and obstructive pneumonia/atelectasis

In the 8th edition of the American Joint Committee on Cancer (AJCC) staging system for Non-Small Cell Lung Cancer (NSCLC), tumors exhibiting main bronchial infiltration (MBI) near the carina and those presenting with complete lung obstructive pneumonia/atelectasis (P/ATL) have been reclassified from T3 to T2. Our investigation into the Surveillance, Epidemiology, and End Results (SEER) database, spanning from 2007 to 2015 and adjusted via Propensity Score Matching (PSM) for additional variables, disclosed a notably inferior overall survival (OS) for patients afflicted with these conditions. Specifically, individuals with P/ATL experienced a median OS of 12 months compared to 15 months (p < 0.001). In contrast, MBI patients demonstrated a slightly worse prognosis with a median OS of 22 months versus 23 months (p = 0.037), with both conditions significantly correlated with lymph node metastasis (All p < 0.001). Upon evaluating different treatment approaches for these particular T2 NSCLC variants, while adjusting for other factors, surgery emerged as the optimal therapeutic strategy. We counted those who underwent surgery and found that compared to surgery alone, the MBI/(P/ATL) group experienced a much higher proportion of preoperative induction therapy or postoperative adjuvant therapy than the non-MBI/(P/ATL) group (41.3%/54.7% vs. 36.6%). However, for MBI patients, initial surgery followed by adjuvant treatment or induction therapy succeeded in significantly enhancing prognosis, a benefit that was not replicated for P/ATL patients. Leveraging the XGBoost model for a 5-year survival forecast and treatment determination for P/ATL and MBI patients yielded Area Under the Curve (AUC) scores of 0.853 for P/ATL and 0.814 for MBI, affirming the model's efficacy in prognostication and treatment allocation for these distinct T2 NSCLC categories.

Understand how machine learning impact lung cancer research from 2010 to 2021: A bibliometric analysis

Advances in lung cancer research applying machine learning (ML) technology have generated many relevant literature. However, there is absence of bibliometric analysis review that aids a comprehensive understanding of this field and its progress. Present article for the first time performed a bibliometric analysis to clarify research status and focus from 2010 to 2021. In the analysis, a total of 2,312 relevant literature were searched and retrieved from the Web of Science Core Collection database. We conducted a bibliometric analysis and further visualization. During that time, exponentially growing annual publication and our model have shown a flourishing research prospect. Annual citation reached the peak in 2017. Researchers from United States and China have produced most of the relevant literature and strongest partnership between them. Medical image analysis and Nature appeared to bring more attention to the public. The computer-aided diagnosis, precision medicine, and survival prediction were the focus of research, reflecting the development trend at that period. ML did make a big difference in lung cancer research in the past decade.

Influencing Factors on the Quality of Lymph Node Dissection for Stage IA Non-Small Cell Lung Cancer: A Retrospective Nationwide Cohort Study

Lymphadenectomy is an essential part of complete surgical operation for non-small cell lung cancer (NSCLC). This retrospective, multicenter cohort study aimed to identify factors that influence the lymphadenectomy quality. Data were obtained from the Polish Lung Cancer Study Group Database. The primary endpoint was lobe-specific mediastinal lymph node dissection (L-SMLND). The study included 4271 patients who underwent VATS lobectomy for stage IA NSCLC, operated between 2007 and 2022. L-SMLND was performed in 1190 patients (27.9%). The remaining 3081 patients (72.1%) did not meet the L-SMLND criteria. Multivariate logistic regression analysis showed that patients with PET-CT (OR 3.238, 95% CI: 2.315 to 4.529; p < 0.001), with larger tumors (pT1a vs. pT1b vs. pT1c) (OR 1.292; 95% CI: 1.009 to 1.653; p = 0.042), and those operated on by experienced surgeons (OR 1.959, 95% CI: 1.432 to 2.679; p < 0.001) had a higher probability of undergoing L-SMLND. The quality of lymphadenectomy decreased over time (OR 0.647, 95% CI: 0.474 to 0.884; p = 0.006). An analysis of propensity-matched groups showed that more extensive lymph node dissection was not related to in-hospital mortality, complication rates, and hospitalization duration. Actions are needed to improve the quality of lymphadenectomy for NSCLC.

Does Multidisciplinary Team Management Improve Clinical Outcomes in NSCLC? A Systematic Review With Meta-Analysis

Introduction

The implementation of multidisciplinary teams (MDTs) has been found to be effective for improving outcomes in oncology. Nevertheless, there is still a dearth of robust literature on patients with NSCLC. The aim of this study was to conduct a systematic review regarding the impact of MDTs on patient with NSCLC outcomes.

Methods

Databases were systematically searched up to February 2023. Two reviewers independently performed study selection and data extraction. Risk of bias was evaluated using the Newcastle-Ottawa and certainty of evidence by the Grading of Recommendations Assessment, Development and Evaluation approach. Overall survival was the primary outcome. Secondary outcomes included mortality, length of survival, progression-free survival, time from diagnosis to treatment, complete staging, treatment received, and adherence to guidelines. A meta-analysis with a random-effect model was performed. Statistical analysis was performed with the R 3.6.2 package.

Results

A total of 22 studies were included in the systematic review. Ten outcomes were identified, favoring the MDT group over the non-MDT group. Pooled analysis revealed that patients managed by MDTs had better overall survival (three studies; 38,037 participants; hazard ratio 0.60, 95% confidence interval [CI]: 0.49-0.75, I2 = 78%), shorter treatment time compared with patients in the non-MDT group (six studies; 15,235 participants; mean difference = 12.20 d, 95% CI: 10.76-13.63, I2 = 63%), and higher proportion of complete staging (four studies; 14,925 participants; risk ratio = 1.36, 95% CI: 1.17-1.57, I2 = 89%).

Conclusions

This meta-analysis revealed that MDT-based patient care was associated with longer overall survival and better quality-of-care-related outcomes.

Behind the Indolent Facade: Uncovering the Molecular Features and Malignancy Potential in Lung Minimally Invasive Adenocarcinoma by Single-Cell Transcriptomics

The increased use of low-dose computed tomography screening has led to more frequent detection of early stage lung tumors, including minimally invasive adenocarcinoma (MIA). To unravel the intricacies of tumor cells and the immune microenvironment in MIA, this study performs a comprehensive single-cell transcriptomic analysis and profiles the transcriptomes of 156,447 cells from fresh paired MIA and invasive adenocarcinoma (IA) tumor samples, peripheral blood mononuclear cells, and adjacent normal tissue samples from three patients with synchronous multiple primary lung adenocarcinoma. This study highlights a connection and heterogeneity between the tumor ecosystem of MIA and IA. MIA tumor cells exhibited high expression of aquaporin-1 and angiotensin II receptor type 2 and a basal-like molecular character. Furthermore, it identifies that cathepsin B+ tumor-associated macrophages may over-activate CD8+ T cells in MIA, leading to an enrichment of granzyme K+ senescent CD8+ T cells, indicating the possibility of malignant progression behind the indolent appearance of MIA. These findings are further validated in 34 MIA and 35 IA samples by multiplexed immunofluorescence. These findings provide valuable insights into the mechanisms that maintain the indolent nature and prompt tumor progression of MIA and can be used to develop more effective therapeutic targets and strategies for MIA patients.

Optimal Therapeutic Strategy for PD-L1 Negative Metastatic Non-Small Cell Lung Cancer: A Decision-Making Guide Based on Clinicopathological and Molecular Features

OPINION STATEMENT

Strategies using immune checkpoint inhibitors (ICI), which can enhance antitumor immune responses, have revolutionized the lung cancer therapeutic landscape. The ICI mechanism of action involves the blockade of regulatory cell surface molecules using antibodies against the Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) (ipilimumab, tremelimumab); the programmed death receptor-1 (PD-1; nivolumab, pembrolizumab); or the PD ligand-1 (PD-L1; atezolizumab, durvalumab). Notably, anti-PD-1 demonstrated long-term survival benefits, durable objective responses, and a manageable safety profile in patients with non-small cell lung cancer (NSCLC). The combination of anti-PD1 or anti-PD-L1 and platinum chemotherapy achieved better survival outcomes than chemotherapy alone, which was observed irrespective of PD-L1 expression on cancer cells. Although promising results have been reported from large clinical trials, especially for patients with high PD-L1 expression, the optimal treatment approach for patients with PD-L1-negative NSCLC has yet to be defined. We propose a guide for clinicians in the therapeutic decision-making process based on the latest data available about treatments, prognostic factors, predictive biomarkers, and real-world evidence in PD-L1-negative NSCLC patients.

Endobronchial Ultrasound/Transbronchial Needle Aspiration-Biopsy for Systematic Mediastinal lymph Node Staging of Non-Small Cell Lung Cancer in Patients Eligible for Surgery: A Prospective Multicenter Study

BACKGROUND

The treatment of lung cancer depends on histological and/or cytological evaluation of the mediastinal lymph nodes. Endobronchial ultrasound/transbronchial needle aspiration-biopsy (EBUS/TBNA-TBNB) is the only minimally invasive technique for a diagnostic exploration of the mediastinum. The aim of this study is to analyze the reliability of EBUS in the preoperative staging of non-small cell lung cancer (NSCLC).

METHODS

A prospective study was conducted from December 2019 to December 2022 on 217 NSCLC patients, who underwent preoperative mediastinal staging using EBUS/TBNA-TBNB according to the ACCP and ESTS guidelines. The following variables were analyzed in order to define the performance of the endoscopic technique-comparing the final staging of lung cancer after pulmonary resection with the operative histological findings: clinical characteristics, lymph nodes examined, number of samples, and likelihood ratio for positive and negative outcomes.

RESULTS

No morbidity or mortality was noted. All patients were discharged from hospital on day one. In 201 patients (92.6%), the preoperative staging using EBUS and the definitive staging deriving from the evaluation of the operative specimen after lung resection were the same; the same number of patients were detected in downstaging and upstaging (8 and 8, 7.4%). The sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy were 90%, 90%, 82%, 94%, and 90%, respectively. The likelihood ratio for positive and negative results was 9 and 0.9, respectively, confirming cancer when present and excluding it when absent.

CONCLUSIONS

EBUS is the only low-invasive and easy procedure for mediastinal staging. The possibility to check the method in each of its phases-through direct visualization of the vessels regardless of their location in relation to the lymph nodes-makes it safe both for the endoscopist and for the patient. Certainly, the cytologist/histologist and/or operator must have adequate expertise in order not to negatively affect the outcome of the method, although three procedures appear to reduce the impact of the individual professional involved on performance.

Real-world relationship of early end points to survival end points in patients with resectable non-small-cell lung cancer

Aim: Pathologic response has been shown to be a promising surrogate for survival in non-small-cell lung cancer. We examined the real-world relationship between these end  points in patients with resectable stage IB-IIIA non-small-cell lung cancer receiving neoadjuvant chemotherapy/chemoradiotherapy (CT/CRT). Methods: Electronic health records/medical charts were analyzed. Overall and event-free survival (OS/EFS) were assessed by Kaplan-Meier stratified by pathologic response. Associations between the end  points were assessed by Cox analyses. Results: A total of 425 patients were selected for the study; 147 and 278 received CT and CRT, respectively. Pathologic complete response (pCR) was associated with longer OS (adjusted HR = 0.50; 95% CI: 0.29-0.85) and EFS (adjusted HR = 0.44; 95% CI: 0.28-0.68) versus no pCR, and EFS was associated with OS (HR = 0.51, 95% CI: 0.38, 0.69). Conclusion: In patients receiving neoadjuvant CT/CRT, pCR and EFS were associated with improved survival in this real-world dataset.

Bilateral Deep Vein Thrombosis (DVT) as a Harbinger of Lung Adenocarcinoma: A Rare Presentation

Oncologic disorders, such as lung adenocarcinoma, can intricately interplay with the coagulation cascade, often leading to thromboembolic events, of which deep vein thrombosis (DVT) stands out prominently. In this report, we present a unique case of a 50-year-old non-smoking Jordanian male who exhibited bilateral DVT as an unexpected preliminary manifestation of an aggressive lung adenocarcinoma. Although the patient did not possess common risk factors for DVT, the bilateral presentation drew attention to the possibility of an underlying malignancy. Subsequent investigations revealed a stage 4 primary lung adenocarcinoma. This case underscores the imperative of maintaining a broad differential in cases of DVT, especially when presenting bilaterally and without evident etiology. Such early detection and intervention, accompanied by collaborative medical strategies and specialized care, can play a pivotal role in enhancing patient prognosis and survival rates. This case exemplifies the potential of DVT, particularly when bilateral, as a harbinger of a more sinister underlying pathology like lung adenocarcinoma.

Clinical application of common inflammatory and nutritional indicators before treatment in prognosis evaluation of non-small cell lung cancer: a retrospective real-world study

Objective

To evaluate the prognostic value of common clinical inflammatory and nutritional indicators before treatment in patients with non-small cell lung cancer in the real world.

Method

A total of 5,239 patients with pathologically confirmed non-small cell lung cancer from 2011 to 2018 in the Affiliated Cancer Hospital of Xinjiang Medical University were selected. Their inflammatory and nutritional indicators (RDW, PDW, NLR, LMR, NMR, PLR, SII, PNI, TP, ALB, CYRFA21-1, CEA, CA125, NSE, α1-globulin, α2-globulin, β1-globulin, β2-globulin, and γ-globulin) before treatment were collected. From the total number, 1,049 patients were randomly sampled (18 to 20% of patients each year) and used as the validation set; the remaining 4,190 patients were used as the training set. According to the eighth edition of the guidelines for the diagnosis, treatment, and stage risk stratification of lung cancer, the patients were divided into four groups: stage I/II operable, stage III operable, stage III inoperable, and stage IV. We used the X-tile software to intercept and classify the cut-off values of each index in the validation set. Univariate and multivariate Cox proportional-hazard regression were used to screen the independent risk factors affecting the prognosis of non-small cell lung cancer and establish a prognostic model for 1, 3, and 5 years. The validation set was used to verify its performance. Finally, the Kaplan-Meier curve was used to assess the survival rate, and the corresponding nomogram was established for clinical use.

Results

After screening, no effective indicators were found in the stage I/II operable group. RDW and CA125 were effective indicators for the stage III operable group (cut-off values were 14.1 and 9.21, respectively, compared with the low-value group; univariate HR was 2.145 and 1.612, and multivariate HR was 1.491 and 1.691, respectively). CYRFA21-1 and CA125 were effective prognostic indicators for the stage III inoperable group (cut-off values were 10.62 and 44.10, respectively, compared with the low-value group; univariate HR was 1.744 and 1.342, and multivariate HR was 1.284 and 1.304, respectively). CYRFA21-1, CA125, NLR, and α1-globulin were effective indicators of prognosis in stage IV (cut-off values were 3.07, 69.60, 4.08, and 5.30, respectively, compared with the low-value group; univariate HR was 1.713, 1.339, 1.388, and 1.539; and multivariate HR was 1.407, 1.119, 1.191, and 1.110, respectively). The model was constructed with the best validation power in stage IV patients (C-index = 0.733, 0.749, and 0.75 at 1, 3, and 5 years, respectively).

Conclusion

For patients with stage III and IV non-small cell lung cancer, some inflammatory markers, serum tumor markers, and nutritional indicators are independent prognostic factors. Combined with the general data of patients, the constructed prognostic evaluation model has the best efficacy in patients with stage IV and can be widely used in clinical practice.

A tumor mutational burden-derived immune computational framework selects sensitive immunotherapy/chemotherapy for lung adenocarcinoma populations with different prognoses

Background

Lung adenocarcinoma (LUAD) kills millions of people every year. Recently, FDA and researchers proved the significance of high tumor mutational burden (TMB) in treating solid tumors. But no scholar has constructed a TMB-derived computing framework to select sensitive immunotherapy/chemotherapy for the LUAD population with different prognoses.

Methods

The datasets were collected from TCGA, GTEx, and GEO. We constructed the TMB-derived immune lncRNA prognostic index (TILPI) computing framework based on TMB-related genes identified by weighted gene co-expression network analysis (WGCNA), oncogenes, and immune-related genes. Furthermore, we mapped the immune landscape based on eight algorithms. We explored the immunotherapy sensitivity of different prognostic populations based on immunotherapy response, tumor immune dysfunction and exclusion (TIDE), and tumor inflammation signature (TIS) model. Furthermore, the molecular docking models were constructed for sensitive drugs identified by the pRRophetic package, oncopredict package, and connectivity map (CMap).

Results

The TILPI computing framework was based on the expression of TMB-derived immune lncRNA signature (TILncSig), which consisted of AC091057.1, AC112721.1, AC114763.1, AC129492.1, LINC00592, and TARID. TILPI divided all LUAD patients into two populations with different prognoses. The random grouping verification, survival analysis, 3D PCA, and ROC curve (AUC=0.74) firmly proved the reliability of TILPI. TILPI was associated with clinical characteristics, including smoking and pathological stage. Furthermore, we estimated three types of immune cells threatening the survival of patients based on multiple algorithms. They were macrophage M0, T cell CD4 Th2, and T cell CD4 memory activated. Nevertheless, five immune cells, including B cell, endothelial cell, eosinophil, mast cell, and T cell CD4 memory resting, prolonged the survival. In addition, the immunotherapy response and TIDE model proved the sensitivity of the low-TILPI population to immunotherapy. We also identified seven intersected drugs for the LUAD population with poor prognosis, which included docetaxel, gemcitabine, paclitaxel, palbociclib, pyrimethamine, thapsigargin, and vinorelbine. Their molecular docking models and best binding energy were also constructed and calculated.

Conclusions

We divided all LUAD patients into two populations with different prognoses. The good prognosis population was sensitive to immunotherapy, while the people with poor prognosis benefitted from 7 drugs.

Construction of an STK11 Mutation and Immune-Related Prognostic Prediction Model in Lung Adenocarcinoma

Background

STK11 mutation in LUAD affects immune cell infiltration in tumor tissue, and is associated with tumor prognosis.

Objective

This study aimed to construct a STK11 mutation and immune-related LUAD prognostic model.

Materials and Methods

The mutation frequency of STK11 in LUAD was queried via cBioPortal in TCGA and PanCancer Atlas databases. The degree of immune infiltration was analyzed by CIBERSORT analysis. DEGs in STK11mut and STK11wt samples were analyzed. Metascape, GO and KEGG methods were adopted for functional and signaling pathway enrichment analysis of DEGs. Genes related to immune were overlapped with DEGs to acquire immune-related DEGs, whose Cox regression and LASSO analyses were employed to construct prognostic model. Univariate and multivariate Cox regression analyses verified the independence of riskscore and clinical features. A nomogram was established to predict the OS of patients. Additionally, TIMER was introduced to analyze relationship between infiltration abundance of 6 immune cells and expression of feature genes in LUAD.

Results

The mutation frequency of STK11 in LUAD was 16%, and the degrees of immune cell infiltration were different between the wild-type and mutant STK11. DEGs of STK11 mutated and unmutated LUAD samples were mainly enriched in immune-related biological functions and signaling pathways. Finally, 6 feature genes were obtained, and a prognostic model was established. Riskscore was an independent immuno-related prognostic factor for LUAD. The nomogram diagram was reliable.

Conclusion

Collectively, genes related to STK11 mutation and immunity were mined from the public database, and a 6-gene prognostic prediction signature was generated.

Sec61γ is a vital protein in the endoplasmic reticulum membrane promoting tumor metastasis and invasion in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors worldwide. Finding effective prognostic markers and therapeutic targets is of great significance for controlling metastasis and invasion clinically.

METHODS

The open copy-number aberrations and gene expression datasets were analysed, and the data of 102 LUAD patients was used for further validation. The cell proliferation, colony formation, migration, invasion assays and mice tumor models were used to detect the function of SEC61G. The epidermal growth factor receptor (EGFR) pathway was also detected to find the mechanism of Sec61γ.

RESULTS

Based on the open datasets, we found that the high level of SEC61G mRNA may drive LUAD metastasis. Furthermore, the overexpression of Sec61γ protein was significantly associated with poor prognosis and greater tumor cell proliferation and metastasis. The SEC61G knockdown could inhibit the EGFR pathway, including STAT3, AKT and PI3K, which can be reversed by Sec61γ overexpression and epithelial growth factor (EGF) supplement.

CONCLUSIONS

Sec61γ promoted the proliferation, metastasis, and invasion of LUAD through EGFR pathways. Sec61γ might be a potential target for the treatment of LUAD metastases.

Rate and Predictors of Unforeseen PN1/PN2-Disease in Surgically Treated cN0 NSCLC-Patients with Primary Tumor > 3 cm: Nationwide Results from Italian VATS-Group Database

Background. Since no robust data are available on the real rate of unforeseen N1-N2 disease (uN) and the relative predictive factors in clinical-N0 NSCLC with peripheral tumours > 3 cm, the usefulness of performing a (mini)invasive mediastinal staging in this setting is debated. Herein, we investigated these issues in a nationwide database. Methods. From 01/2014 to 06/2020, 15,784 thoracoscopic major lung resections were prospectively recorded in the “Italian VATS-Group” database. Among them, 1982 clinical-N0 peripheral solid-type NSCLC > 3 cm were identified, and information was retrospectively reviewed. A mean comparison of more than two groups was made by ANOVA (Bonferroni correction for multiple comparisons), while associations between the categorical variables were estimated with a Chi-square test. The multivariate logistic regression model and Kaplan–Meyer method were used to identify the independent predictors of nodal upstaging and survival results, respectively. Results. At pathological staging, 229 patients had N1-involvement (11.6%), and 169 had uN2 disease (8.5%). Independent predictors of uN1 were SUVmax (OR: 1.98; CI 95: 1.44–2.73, p = 0.0001) and tumour-size (OR: 1.52; CI: 1.11–2.10, p = 0.01), while independent predictors of uN2 were age (OR: 0.98; CI 95: 0.96–0.99, p = 0.039), histology (OR: 0.48; CI 95: 0.30–0.78, p = 0.003), SUVmax (OR: 2.07; CI 95: 1.15–3.72, p = 0.015), and the number of resected lymph nodes (OR: 1.03; CI 95: 1.01–1.05, p = 0.002). Conclusions. The unforeseen N1-N2 disease in cN0/NSCLCs > 3 cm undergoing VATS resection is observable in between 12 and 8% of all cases. We have identified predictors that could guide physicians in selecting the best candidate for (mini)invasive mediastinal staging.

Distribution and prognostic impact of EGFR and KRAS mutations according to histological subtype and tumor invasion status in pTis-3N0M0 lung adenocarcinoma

BACKGROUND

The prognostic impact of EGFR mutation as major targetable somatic gene variant on lung adenocarcinoma is controversial. KRAS is another major somatic variant in lung adenocarcinoma, and a therapeutic agent for KRAS G12C became available in clinical settings. These mutations represent clinicopathological features of lung adenocarcinoma and can guide the treatment choice after recurrence. We evaluated the prognostic impact of EGFR and KRAS mutations by considering other clinicopathological recurrence risks in resected pTis-3N0M0 lung adenocarcinoma.

METHODS

Clinicopathological features related to recurrence and genetic status were estimated in consecutive 877 resected cases. Recurrence-free survival (RFS), cumulative recurrence rate (CRR), and overall survival (OS) were compared. Uni- and multivariate analyses for RFS were performed after excluding cases with little or no recurrence risks.

RESULTS

EGFR mutation was more likely to be harbored in female, never-smoker, or patients accompanied by > 5% lepidic component. KRAS mutation was more likely to be harbored in patients with current/ex-smoking history, International Association for the Study of Lung Cancer (IASLC) grade 3, or accompanied lymphatic or vascular invasion. In IASLC grade 2 and 3 patients, EGFR or KRAS mutation cases had significantly worse 5-year RFS than wild type patients (76.9% vs. 85.0%, hazard ratio [HR] = 1.55, 95% confidence interval [CI] = 1.62-6.41, P < 0.001). EGFR or KRAS mutation cases had significantly higher 5-year CRR than wild type patients (17.7% vs. 9.8%, HR = 1.69, 95% CI = 1.44-6.59, P = 0.0038). KRAS mutation cases had higher 5-year CRR than EGFR mutation cases (16.7% vs. 21.4%, HR = 1.62, 95% CI = 0.96-7.19, P = 0.061). There was no significant difference in OS between cohorts. Multivariate analysis revealed that a positive EGFR/KRAS mutation status was risk factor for worse RFS (HR = 2.007, 95% CI = 1.265-3.183, P = 0.003).

CONCLUSION

Positive EGFR and KRAS mutation statuses were risk factors for recurrence in resected IASLC grade 2 and 3 patients. KRAS mutations were more likely to be confirmed in cases with an increased risk of recurrence. EGFR and KRAS mutation statuses should be evaluated simultaneously when assessing the risk of recurrence.

Diagnosis and management of patients with stage III non‑small cell lung cancer: A joint statement by the Lebanese Society of Medical Oncology and the Lebanese Pulmonary Society (Review)

Proper management of stage III non-small cell lung cancer (NSCLC) might result in a cure or patient long-term survival. Management should therefore be preceded by adequate and accurate diagnosis and staging, which will inform therapeutic decisions. A panel of oncologists, surgeons and pulmonologists in Lebanon convened to establish a set of recommendations to guide and unify clinical practice, in alignment with international standards of care. Whilst chest computerized tomography (CT) scanning remains a cornerstone in the discovery of a lung lesion, a positron-emission tomography (PET)/CT scan and a tumor biopsy allows for staging of the cancer and defining the resectability of the tumor(s). A multidisciplinary discussion meeting is currently widely advised for evaluating patients on a case-by-case basis, and should include at least the treating oncologist, a thoracic surgeon, a radiation oncologist and a pulmonologist, in addition to physicians from other specialties as needed. The standard of care for unresectable stage III NSCLC is concurrent chemotherapy and radiation therapy, followed by consolidation therapy with durvalumab, which should be initiated within 42 days of the last radiation dose; for resectable tumors, neoadjuvant therapy followed by surgical resection is recommended. This joint statement is based on the expertise of the physician panel, available literature and evidence governing the treatment, management and follow-up of patients with stage III NSCLC.

Radiogenomics in lung cancer: Where are we?

Huge technological and biomedical advances have improved the survival and quality of life of lung cancer patients treated with radiotherapy. However, during treatment planning, a probability that the patient will experience adverse effects is assumed. Radiotoxicity is a complex entity that is largely dose-dependent but also has important intrinsic factors. One of the most studied is the genetic variants that may be associated with susceptibility to the development of adverse effects of radiotherapy. This review aims to present the current status of radiogenomics in lung cancer, integrating results obtained in association studies of SNPs (single nucleotide polymorphisms) related to radiotherapy toxicities. We conclude that despite numerous publications in this field, methodologies and endpoints vary greatly, making comparisons between studies difficult. Analyzing SNPs from the candidate gene approach, together with the study in cohorts limited by the sample size, has complicated the possibility of having validated results. All this delays the incorporation of genetic biomarkers in predictive models for clinical application. Thus, from all analysed SNPs, only 12 have great potential as esophagitis genetic risk factors and deserve further exploration. This review highlights the efforts that have been made to date in the radiogenomic study of radiotoxicity in lung cancer.

Drug Repurposing in Non-Small Cell Lung Carcinoma: Old Solutions for New Problems

Lung cancer is the second most common cancer and the leading cause of cancer-related deaths in 2022. The majority (80%) of lung cancer cases belong to the non-small cell lung carcinoma (NSCLC) subtype. Despite the increased screening efforts, the median five-year survival of metastatic NSCLC remains low at approximately 3%. Common treatment approaches for NSCLC include surgery, multimodal chemotherapy, and concurrent radio and chemotherapy. NSCLC exhibits high rates of resistance to treatment, driven by its heterogeneity and the plasticity of cancer stem cells (CSCs). Drug repurposing offers a faster and cheaper way to develop new antineoplastic purposes for existing drugs, to help overcome therapy resistance. The decrease in time and funds needed stems from the availability of the pharmacokinetic and pharmacodynamic profiles of the Food and Drug Administration (FDA)-approved drugs to be repurposed. This review provides a synopsis of the drug-repurposing approaches and mechanisms of action of potential candidate drugs used in treating NSCLC, including but not limited to antihypertensives, anti-hyperlipidemics, anti-inflammatory drugs, anti-diabetics, and anti-microbials.

Current investigative modalities for detecting and staging lung cancers: a comprehensive summary

This narrative review compares the advantages and drawbacks of imaging and other investigation modalities which currently assist with lung cancer diagnosis and staging, as well as those which are not routinely indicated for this. We examine plain film radiography, computed tomography (CT) (alone, as well as in conjunction with positron emission tomography (PET)), magnetic resonance imaging (MRI), ultrasound, and newer techniques such as image-guided bronchoscopy (IGB) and robotic bronchoscopy (RB). While a chest X-ray is the first-line imaging investigation in patients presenting with symptoms suggestive of lung cancer, it has a high positive predictive value (PPV) even after negative X-ray findings, which calls into question its value as part of a potential national screening programme. CT lowers the mortality for high-risk patients when compared to X-ray and certain scoring systems, such as the Brock model can guide the need for further imaging, like PET-CT, which has high sensitivity and specificity for diagnosing solitary pulmonary nodules as malignant, as well as for assessing small cell lung cancer spread. In practice, PET-CT is offered to everyone whose lung cancer is to be treated with a curative intent. In contrast, MRI is only recommended for isolated distant metastases. Similarly, ultrasound imaging is not used for diagnosis of lung cancer but can be useful when there is suspicion of intrathoracic lymph node involvement. Ultrasound imaging in the form of endobronchial ultrasonography (EBUS) is often used to aid tissue sampling, yet the diagnostic value of this technique varies widely between studies. RB is another novel technique that offers an alternative way to biopsy lesions, but further research on it is necessary. Lastly, thoracic surgical biopsies, particularly minimally invasive video-assisted techniques, have been used increasingly to aid in diagnosis and staging.

Proposal of a revised International Association for the Study of Lung Cancer grading system in pulmonary non-mucinous adenocarcinoma: The importance of the lepidic proportion

OBJECTIVES

We aimed to measure the validity of the International Association for the Study of Lung Cancer (IASLC) grading system in Korean patients and propose a modification for an increase of its predictability, especially in grade 2 patients.

MATERIALS AND METHODS

From 2012 to 2017, histopathologic characteristics of 1358 patients with invasive pulmonary adenocarcinoma (stage I-III) from two institutions were retrospectively reviewed and re-classified according to the IASLC grading system. Considering the amount of the lepidic proportion, the validity of the revised model (Lepidic-10), derived from the training cohort (hospital A), was measured using the validation cohort (hospital B). Its predictability was compared to that of the IASLC system.

RESULTS

Of the 1358 patients, 259 had a recurrence, and 189 died during follow-up. The Harrell's concordance index and area under the curve of the IASLC system were 0.685 and 0.699 for recurrence-free survival (RFS) and 0.669 and 0.679 for death, respectively. From the training cohort, the IASLC grade 2 patients were divided into grades 2a and 2b (Lepidic-10 model) with a 10 % lepidic pattern. This new model further distinguished patients in both institutions that had better performance than the IASLC grading (Hospital A, p < 0.001 for RFS and death; Hospital B, p = 0.0215 for RFS, p = 0.0429 for death).

CONCLUSION

The IASLC grading system was easily applicable; its clinical use in predicting the prognosis of Korean patients with pulmonary adenocarcinoma was validated. Furthermore, the introduction of the lepidic proportion as an additional criterion to differentiate grade 2 patients improved its predictability.

Benignant and malignant epidemiology among surgical resections for suspicious solitary lung cancer without preoperative tissue diagnosis

OBJECTIVES

The aim of this study was to describe the epidemiology of patients undergoing diagnostic and/or curative surgical pulmonary resections for lung opacities suspected of being localized primary lung cancers without preoperative tissue confirmation.

METHODS

We performed a single-centre retrospective study of a prospectively implemented institutional database of all patients who underwent pulmonary resection between January 2010 and December 2020. Patients were selected when surgery complied with the Fleischner society guidelines. We performed a multivariable logistic regression to determine the preoperative variables associated with malignancy.

RESULTS

Among 1392 patients, 213 (15.3%) had a final diagnosis of benignancy. We quantified futile parenchymal resections in 29 (2.1%) patients defined by an anatomical resection of >2 lung segments for benign lesions that did not modified the clinical management. Compared with patients with malignancies, patients with benignancies were younger (57.5 vs 63.9 years, P < 0.001), had lower preoperative risk profile (thoracoscore 0.4 vs 2.1, P < 0.001), had a higher proportion of wedge resection (50.7% vs 12.2%, P < 0.01) and experienced a lower burden of postoperative complication (Clavien-Dindo IV or V, 0.4% vs 5.6%, P < 0.001). Preoperative independent variables associated with malignancy were (adjusted odd ratio [95% confident interval]) age 1.02 [1.00; 1.04], smoking (year-pack) 1.005 (1.00; 1.01), history of cardiovascular disease 2.06 [1.30; 3.30], history of controlled cancer 2.74 [1.30; 6.88] and clinical N involvement 4.20 [1.11; 37.44].

CONCLUSIONS

Futile parenchymal lung resection for suspicious opacities without preoperative tissue diagnosis is rare (2.1%) while surgery for benign lesions represented 15.3% and has a satisfactory safety profile with very low postoperative morbi-mortality.

Correlation analysis between unenhanced and enhanced CT radiomic features of lung cancers presenting as solid nodules and their efficacy for predicting hilar and mediastinal lymph node metastases

Objectives

If hilar and mediastinal lymph node metastases occur in solid nodule lung cancer is critical for tumor staging, which determines the treatment strategy and prognosis of patients. We aimed to develop an effective model to predict hilar and mediastinal lymph node metastases by using texture features of solid nodule lung cancer.

Methods

Two hundred eighteen patients with solid nodules on CT images were analyzed retrospectively. The 3D tumors were delineated using ITK-SNAP software. Radiomics features were extracted from unenhanced and enhanced CT images based on AK software. Correlations between radiomics features of unenhanced and enhanced CT images were analyzed with Spearman rank correlation analysis. According to pathological findings, the patients were divided into no lymph node metastasis group and lymph node metastasis group. All patients were randomly divided into training group and test group at a ratio of 7:3. Valuable features were selected. Multivariate logistic regression was used to build predictive models. Two predictive models were established with unenhanced and enhanced CT images. ROC analysis was used to estimate the predictive efficiency of the models.

Results

A total of 7 categories of features, including 107 features, were extracted. There was a high correlation between the 7 categories of features from unenhanced CT images and enhanced CT images (all r > 0.7, p < 0.05). Among them, the shape features had the strongest correlation (mean r = 0.98). There were 5 features in the enhanced model and the unenhanced model, which had important predicting significance. The AUCs were 0.811 and 0.803, respectively. There was no significant difference in the predictive performance of the two models (DeLong's test, p = 0.05).

Conclusion

Our study models achieved higher accuracy for predicting hilar and mediastinal lymph node metastasis of solid nodule lung cancer and have some value in promoting the staging accuracy of lung cancer. Our results show that CT radiomics features have potential to predict hilar and mediastinal lymph node metastases in solid nodular lung cancer. In addition, enhanced and unenhanced CT radiomics models had comparable predictive power in predicting hilar and mediastinal lymph node metastases.

Characterization of fatty acid metabolism-related lncRNAs in lung adenocarcinoma identifying potential novel prognostic targets

Lung adenocarcinoma (LUAD), a malignant respiratory tumor with an extremely poor prognosis, has troubled the medical community all over the world. According to recent studies, fatty acid metabolism (FAM) and long non-coding RNAs (lncRNAs) regulation have shown exciting results in tumor therapy. In this study, the original LUAD patient data was obtained from the TCGA database, and 12 FAM-related lncRNAs (AL390755.1, AC105020.6, TMPO-AS1, AC016737.2, AC127070.2, LINC01281, AL589986.2, GAS6-DT, AC078993.1, LINC02198, AC007032.1, and AL021026.1) that were highly related to the progression of LUAD were finally identified through bioinformatics analysis, and a risk score model for clinical reference was constructed. The window explores the immunology and molecular mechanism of LUAD, aiming to shed the hoping light on LUAD treatment.

State of the Art: Lung Cancer Staging Using Updated Imaging Modalities

Lung cancer is among the most common mortality causes worldwide. This scientific article is a comprehensive review of current knowledge regarding screening, subtyping, imaging, staging, and management of treatment response for lung cancer. The traditional imaging modality for screening and initial lung cancer diagnosis is computed tomography (CT). Recently, a dual-energy CT was proven to enhance the categorization of variable pulmonary lesions. The National Comprehensive Cancer Network (NCCN) recommends usage of fluorodeoxyglucose positron emission tomography (FDG PET) in concert with CT to properly stage lung cancer and to prevent fruitless thoracotomies. Diffusion MR is an alternative to FDG PET/CT that is radiation-free and has a comparable diagnostic performance. For response evaluation after treatment, FDG PET/CT is a potent modality which predicts survival better than CT. Updated knowledge of lung cancer genomic abnormalities and treatment regimens helps to improve the radiologists’ skills. Incorporating the radiologic experience is crucial for precise diagnosis, therapy planning, and surveillance of lung cancer.

Efficient procedure planning for comprehensive lymph node staging bronchoscopy

Purpose: For a patient at risk of having lung cancer, accurate disease staging is vital as it dictates disease prognosis and treatment. Accurate staging requires a comprehensive sampling of lymph nodes within the chest via bronchoscopy. Unfortunately, physicians are generally unable to plan and perform sufficiently comprehensive procedures to ensure accurate disease staging. We propose a method for planning comprehensive lymph node staging procedures. Approach: Drawing on a patient's chest CT scan, the method derives a multi-destination tour for efficient navigation to a set of lymph nodes. We formulate the planning task as a traveling salesman problem. To solve the problem, we apply the concept of ant colony optimization (ACO) to derive an efficient airway tour connecting the target nodes. The method has three main steps: (1) CT preprocessing, to define important chest anatomy; (2) graph and staging zone construction, to set up the necessary data structures and clinical constraints; and (3) tour computation, to derive the staging plan. The plan conforms to the world standard International Association for the Study of Lung Cancer (IASLC) lymph node map and recommended clinical staging guidelines. Results: Tests with a patient database indicate that the method derives optimal or near-optimal tours in under a few seconds, regardless of the number of target lymph nodes (mean tour length = 1.4% longer than the optimum). A brute force optimal search, on the other hand, generally cannot reach a solution in under 10 min. for patients exhibiting > 16 nodes, and other methods provide poor solutions. We also demonstrate the method's utility in an image-guided bronchoscopy system. Conclusions: The method provides an efficient computational approach for planning a comprehensive lymph node staging bronchoscopy. In addition, the method shows promise for driving an image-guided bronchoscopy system or robotics-assisted bronchoscopy system tailored to lymph node staging.

Identification of lactate metabolism-related subtypes and development of a lactate-related prognostic indicator of lung adenocarcinoma

Background: Increasing evidence supports that lactate plays an important role in tumor proliferation, invasion and within the tumor microenvironment (TME). This is particularly relevant in lung adenocarcinoma (LUAD). Therefore, there is a current need to investigate lactate metabolism in LUAD patients and how lactate metabolism is affected by different therapies.

Methods: Data from LUAD patients were collected from The Cancer Genome Atlas (TCGA) and patients were divided into two subtypes according to 12 lactate metabolism-related genes to explore the effect of lactate metabolism in LUAD. We established a lactate-related prognostic indicator (LRPI) based on different gene expression profiles. Subsequently, we investigated associations between this LRPI and patient survival, molecular characteristics and response to therapy. Some analyses were conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database.

Results: The two LUAD subtypes exhibited different levels of lactate metabolism, in which patients that displayed high lactate metabolism also had a worse prognosis and a poorer immune environment. Indeed, LRPI was shown to accurately predict the prognosis of LUAD patients. Patients with a high LRPI showed a poor prognosis coupled with high sensitivity to chemotherapy using GDSC data. Meanwhile, these patients exhibited a high responsiveness to immunotherapy in TMB (Tumor mutation burden) and TIDE (Tumor Immune Dysfunction and Exclusion) analyses.

Conclusion: We validated the effect of lactate metabolism on the prognosis of LUAD patients and established a promising biomarker. LRPI can predict LUAD patient survival, molecular characteristics and response to therapy, which can aid the individualized treatment of LUAD patients.

MRI-based radiomics analysis in differentiating solid non-small-cell from small-cell lung carcinoma: a pilot study

AIM

To investigate the ability of a T2-weighted (W) magnetic resonance imaging (MRI)-based radiomics signature to differentiate solid non-small-cell lung carcinoma (NSCLC) from small-cell lung carcinoma (SCLC).

MATERIALS AND METHODS

The present retrospective study enrolled 152 eligible patients (NSCLC = 125, SCLC = 27). All patients underwent MRI using a 3 T scanner and radiomics features were extracted from T2W MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression model was used to identify the optimal radiomics features for the construction of a radiomics model to differentiate solid NSCLC from SCLC. Threefold cross validation repeated 10 times was used for model training and evaluation. The conventional MRI morphology features of the lesions were also evaluated. The performance of the conventional MRI morphological features, and the radiomics signature model and nomogram model (combining radiomics signature with conventional MRI morphological features) was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Five optimal features were chosen to build a radiomics signature. There was no significant difference in age, gender, and the largest diameter. The radiomics signature and conventional MRI morphological features (only pleural indentation and lymph node enlargement) were independent predictive factors for differentiating solid NSCLC from SCLC. The area under the ROC curves (AUCs) for MRI morphological features, and the radiomics model, and nomogram model was 0.69, 0.85, and 0.90 (ROC), respectively.

CONCLUSIONS

The T2W MRI-based radiomics signature is a potential non-invasive approach for distinguishing solid NSCLC from SCLC.

DETECT-LC: A 3D Deep Learning and Textural Radiomics Computational Model for Lung Cancer Staging and Tumor Phenotyping Based on Computed Tomography Volumes

Lung Cancer is one of the primary causes of cancer-related deaths worldwide. Timely diagnosis and precise staging are pivotal for treatment planning, and thus can lead to increased survival rates. The application of advanced machine learning techniques helps in effective diagnosis and staging. In this study, a multistage neurobased computational model is proposed, DETECT-LC learning. DETECT-LC handles the challenge of choosing discriminative CT slices for constructing 3D volumes, using Haralick, histogram-based radiomics, and unsupervised clustering. ALT-CNN-DENSE Net architecture is introduced as part of DETECT-LC for voxel-based classification. DETECT-LC offers an automatic threshold-based segmentation approach instead of the manual procedure, to help mitigate this burden for radiologists and clinicians. Also, DETECT-LC presents a slice selection approach and a newly proposed relatively light weight 3D CNN architecture to improve existing studies performance. The proposed pipeline is employed for tumor phenotyping and staging. DETECT-LC performance is assessed through a range of experiments, in which DETECT-LC attains outstanding performance surpassing its counterparts in terms of accuracy, sensitivity, F1-score and Area under Curve (AuC). For histopathology classification, DETECT-LC average performance achieved an improvement of 20% in overall accuracy, 0.19 in sensitivity, 0.16 in F1-Score and 0.16 in AuC over the state of the art. A similar enhancement is reached for staging, where higher overall accuracy, sensitivity and F1-score are attained with differences of 8%, 0.08 and 0.14.

A narrative review of deep learning applications in lung cancer research: from screening to prognostication

Background and Objective

Deep learning (DL) algorithms have been developed for various tasks, including lung nodule detection on chest radiographs or lung cancer computed tomography screening, potential candidate selection in lung cancer screening, malignancy prediction for indeterminate pulmonary nodules, lung cancer staging, treatment response prediction, prognostication, and prediction of genetic mutations in lung cancer. Furthermore, these DL algorithms have been applied in various clinical settings in order for them to be generalized in real-world clinical practice. Multiple DL algorithms have been corroborated to be on par with experts or current clinical prediction models for several specific tasks. However, no article has yet comprehensively reviewed DL algorithms dedicated to lung cancer research. This narrative review presents an overview of the literature dealing with DL techniques applied in lung cancer research and briefly summarizes the results according to the DL algorithms’ clinical use cases.

Methods

we performed a narrative review by searching the Embase and OVID-MEDLINE databases for articles published in English from October, 2016 until September, 2021 and reviewing the bibliographies of key references to identify important literature related to DL in lung cancer research. The background, development, results, and clinical implications of each DL algorithm are briefly discussed. Lastly, we end this review article by highlighting future directions in lung cancer research using DL techniques.

Key Content and Findings

DL algorithms have been introduced to show comparable or higher performance than human experts in various clinical settings. Specifically, they have been actively applied to detect lung nodules in chest radiographs or computed tomography (CT) examinations, optimize candidate selection for lung cancer screening (LCS), predict the malignancy of lung nodules, stage lung cancer, and predict treatment response, patients’ prognoses, and genetic mutations in lung cancers.

Conclusions

DL algorithms have corroborated their potential value for various tasks, ranging from lung cancer screening to prognostication of lung cancer patients. Future research is warranted for the clinical application of these algorithms in daily clinical practice and verification of their real-world clinical usefulness.

Role of Pre-Operative Brain Imaging in Patients with NSCLC Stage I: A Retrospective, Multicenter Analysis

Simple Summary

Lung cancer is the worldwide leading cause of cancer-related death among both genders, with about 230,000 patients/year being diagnosed in the US alone. It accounts for about 40% of all brain metastases, which already occur in around 3% of early-stage patients. Nonetheless, current international guidelines do not unanimously recommend brain imaging for use in the early stages of cancer. Some studies have suggested that surgical or radiosurgical treatment of brain metastases may provide better survival, especially in asymptomatic patients. Additionally, advances in genome analysis have identified molecular targets for pharmaceutical agents. These recent advancements in treatment stress the importance of studying incidence as well as patient and tumor characteristics in order to potentially adapt future guidelines and provide the best possible treatment for early-stage lung cancer. This multicentric study analyzed the data of 577 patients diagnosed with early-stage lung cancer who had been submitted for brain imaging at initial tumor staging.

Abstract

Background: Lung cancer is the worldwide leading oncological cause of death in both genders combined and accounts for around 40–50% of brain metastases in general. In early-stage lung cancer, the incidence of brain metastases is around 3%. Since the early detection of asymptomatic cerebral metastases is of prognostic value, the aim of this study was to analyze the incidence of brain metastases in early-stage lung cancer and identify possible risk factors. Methods: We conducted a retrospective multicentric analysis of patients with Stage I (based on T and N stage only) Non-Small Cell Lung Cancer (NSCLC) who had received preoperative cerebral imaging in the form of contrast-enhanced CT or MRI. Patients with a history of NSCLC, synchronous malignancy, or neurological symptoms were excluded from the study. Analyzed variables were gender, age, tumor histology, cerebral imaging findings, smoking history, and tumor size. Results were expressed as mean with standard deviation or median with range. Results: In total, 577 patients were included in our study. Eight (1.4%) patients were found to have brain metastases in preoperative brain imaging. Tumor histology was adenocarcinoma in all eight cases. Patients were treated with radiotherapy (five), surgical resection (two), or both (one) prior to thoracic surgical treatment. Other than tumor histology, no statistically significant characteristics were found to be predictive of brain metastases. Conclusion: Given the low incidence of brain metastases in patients with clinical Stage I NSCLC, brain imaging in this cohort could be avoided.

GOECP/SEOR radiotheraphy guidelines for non-small-cell lung cancer

Non-small cell lung cancer (NSCLC) is a heterogeneous disease accounting for approximately 85% of all lung cancers. Only 17% of patients are diagnosed at an early stage. Treatment is multidisciplinary and radiotherapy plays a key role in all stages of the disease. More than 50% of patients with NSCLC are treated with radiotherapy (curative-intent or palliative). Technological advances-including highly conformal radiotherapy techniques, new immobilization and respiratory control systems, and precision image verification systems-allow clinicians to individualize treatment to maximize tumor control while minimizing treatment-related toxicity. Novel therapeutic regimens such as moderate hypofractionation and advanced techniques such as stereotactic body radiotherapy (SBRT) have reduced the number of radiotherapy sessions. The integration of SBRT into routine clinical practice has radically altered treatment of early-stage disease. SBRT also plays an increasingly important role in oligometastatic disease. The aim of the present guidelines is to review the role of radiotherapy in the treatment of localized, locally-advanced, and metastatic NSCLC. We review the main radiotherapy techniques and clarify the role of radiotherapy in routine clinical practice. These guidelines are based on the best available evidence. The level and grade of evidence supporting each recommendation is provided.

Surgical Effectiveness of Uniportal-VATS Lobectomy Compared to Open Surgery in Early-Stage Lung Cancer

Background

Although the feasibility and safety of Uniportal-Video-Assisted thoracic surgery (U-VATS) has been proven, its surgical effectiveness is still debated. The aim of this study is to assess the equivalence of the U-VATS approach compared with an open technique in terms of surgical (nodal-upstaging, complications, and post-operative results) and short-term survival outcomes.

Methods

The clinical data of patients undergoing lobectomy for NSCLC at our center, from January 2014 to December 2019, were analyzed retrospectively. All patients undergoing open or U-VATS lobectomy with lymphadenectomy for early-stage lung cancer (cT1-T3N0, stages IA-IIB) were included in the study. Only 230 patients satisfied the inclusion criteria. Group bias was reduced through 1:1 propensity score matching, which resulted in 46 patients in each group (open surgery and U-VATS).

Results

The intra- and post-operative mortality were null in both groups. There was no difference in the post-operative complications (p: 1.00) between U-VATS and open lobectomy. There was also no recorded difference in the pathological nodal up-staging [11 (23.9%) after thoracotomy vs. 8 (17.4%) after U-VATS, p: 0.440). The chest tube duration was longer in the open group (p: 0.025), with a higher post-operative pain (p: 0.001). Additionally, the 3-year overall survival (OS) was 78% after U-VATS lobectomy vs. 74% after open lobectomy (p: 0.204), while 3-year disease-specific survival (DSS) was 97 vs. 89% (p: 0.371), respectively. The 3-year disease-free survival (DFS) was 62% in the U-VATS group and 66% in the thoracotomy group, respectively (p: 0.917).

Conclusions

Uniportal-VATS lobectomy for the treatment of early-stage lung cancer seems to be a safe and effective technique with similar surgical and short-term survival outcomes as open surgery, but with lower post-operative pain and shorter in-hospital stay.

A rare clinical presentation of Waldenström Macroglobulinemia mimicking lung cancer

Waldenström macroglobulinemia rarely presents as pulmonary symptoms, and even rarer as chylothorax. We present a patient who presented with bilateral pleural effusion and a 30 mm solid lesion in the lung. Biochemical analysis of the pleural fluid revealed chylothorax. The 18-fluorodeoxygenase positron emission tomography, bronchoscopy, endobronchial ultrasound, and cytological examination of the pleural fluid, showed no apparent cause of the chylothorax. The diagnostic breakthrough was made with flow cytometry of the pleural fluid, which revealed a small group of clonal B-cells. Biopsy from the parietal pleura and bone marrow led to the diagnosis Waldenström macroglobulinemia. This demonstrates that flow cytometry should be considered when routine diagnostics do not lead to a reach a specific diagnosis.

Cancer statistics, 2022

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes. Incidence data (through 2018) were collected by the Surveillance, Epidemiology, and End Results program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2019) were collected by the National Center for Health Statistics. In 2022, 1,918,030 new cancer cases and 609,360 cancer deaths are projected to occur in the United States, including approximately 350 deaths per day from lung cancer, the leading cause of cancer death. Incidence during 2014 through 2018 continued a slow increase for female breast cancer (by 0.5% annually) and remained stable for prostate cancer, despite a 4% to 6% annual increase for advanced disease since 2011. Consequently, the proportion of prostate cancer diagnosed at a distant stage increased from 3.9% to 8.2% over the past decade. In contrast, lung cancer incidence continued to decline steeply for advanced disease while rates for localized-stage increased suddenly by 4.5% annually, contributing to gains both in the proportion of localized-stage diagnoses (from 17% in 2004 to 28% in 2018) and 3-year relative survival (from 21% to 31%). Mortality patterns reflect incidence trends, with declines accelerating for lung cancer, slowing for breast cancer, and stabilizing for prostate cancer. In summary, progress has stagnated for breast and prostate cancers but strengthened for lung cancer, coinciding with changes in medical practice related to cancer screening and/or treatment. More targeted cancer control interventions and investment in improved early detection and treatment would facilitate reductions in cancer mortality.

Multi-omics analysis to identify lung squamous carcinoma lactate metabolism-related subtypes and establish related index to predict prognosis and guide immunotherapy

•

Multi-omics analysis to analyze the effect of lactate metabolism on LUSC phenotype.

•

Lactate metabolism and immunogenomics crosstalk analysis to identify LUSC subtypes.

•

Lactate metabolism can reflect the level of LUSC metabolic reprogramming.

•

LMRPI can predict the prognosis of LUSC patients and guide individualized treatment.

Lung squamous carcinoma (LUSC) is a malignant tumor of the respiratory system with highly heterogeneous characteristics. Lactate is the main product of aerobic glycolysis during the metabolic reprogramming of tumors. There is growing evidence that lactate metabolic processes have a broad and sophisticated impact on tumor phenotypic plasticity and tumor microenvironment (TME). However, the pattern of lactate metabolism in patients with LUSC and its impact on TME, phenotype, prognosis, and treatment have not been fully elucidated. In this study, we identified two subtypes with different lactate metabolism patterns in LUSC by non-negative matrix factorization and explored their multi-omics features. We observed that lactate metabolism levels in LUSC extensively influenced tumor immune infiltration patterns, adaptation to the hypoxia environment, and energy metabolic reprogramming. Subsequently, we constructed the lactate metabolism-related prognostic index (LMRPI) using Cox stepwise regression analysis. LMRPI showed excellent stability and accuracy, and based on the median value of LMRPI, LUAD were divided into two subgroups. The two subgroups have different patterns of immune infiltration and somatic mutations. Meanwhile, the two subgroups had different responsiveness to immune checkpoint inhibitor (ICI) therapies and different sensitivity to various chemotherapeutic and molecular targeting agents. In conclusion, we defined two subtypes with different lactate metabolism patterns in LUSC and extensively characterized their multi-omics profile. Furthermore, we developed LMRPI that predicts the prognosis of LUSC patients while also predicting their response to various adjuvant therapies, including immunotherapy, to guide their individualized treatment.

Radiomics for Predicting Lung Cancer Outcomes Following Radiotherapy: A Systematic Review

Lung cancer's radiomic phenotype may potentially inform clinical decision-making with respect to radical radiotherapy. At present there are no validated biomarkers available for the individualisation of radical radiotherapy in lung cancer and the mortality rate of this disease remains the highest of all other solid tumours. MEDLINE was searched using the terms 'radiomics' and 'lung cancer' according to the Preferred Reporting Items for Systematic Reviews and Met-Analyses (PRISMA) guidance. Radiomics studies were defined as those manuscripts describing the extraction and analysis of at least 10 quantifiable imaging features. Only those studies assessing disease control, survival or toxicity outcomes for patients with lung cancer following radical radiotherapy ± chemotherapy were included. Study titles and abstracts were reviewed by two independent reviewers. The Radiomics Quality Score was applied to the full text of included papers. Of 244 returned results, 44 studies met the eligibility criteria for inclusion. End points frequently reported were local (17%), regional (17%) and distant control (31%), overall survival (79%) and pulmonary toxicity (4%). Imaging features strongly associated with clinical outcomes include texture features belonging to the subclasses Gray level run length matrix, Gray level co-occurrence matrix and kurtosis. The median cohort size for model development was 100 (15-645); in the 11 studies with external validation in a separate independent population, the median cohort size was 84 (21-295). The median number of imaging features extracted was 184 (10-6538). The median Radiomics Quality Score was 11% (0-47). Patient-reported outcomes were not incorporated within any studies identified. No studies externally validated a radiomics signature in a registered prospective study. Imaging-derived indices attained through radiomic analyses could equip thoracic oncologists with biomarkers for treatment response, patterns of failure, normal tissue toxicity and survival in lung cancer. Based on routine scans, their non-invasive nature and cost-effectiveness are major advantages over conventional pathological assessment. Improved tools are required for the appraisal of radiomics studies, as significant barriers to clinical implementation remain, such as standardisation of input scan data, quality of reporting and external validation of signatures in randomised, interventional clinical trials.

Pathological high malignant grade is higher risk of recurrence in pN0M0 invasive lung adenocarcinoma, even with small invasive size

Introduction

Tumor size is an absolute recurrence risk in lung cancer. Although morphological features also reflect recurrence risk, its significance among lower‐risk cases characterized by small size is unknown. We aimed to evaluate the relationship between pathological invasive tumor size and morphological features, and their prognostic impact by considering them simultaneously in lung adenocarcinoma.

Patients and methods

We retrospectively reviewed 563 pN0M0 patients with pathological invasive size of ≤40 mm. The patients were classified by pathological invasive size and pathological malignant grading using the proportion of subhistological components. The prognostic impact was evaluated using recurrence‐free survival (RFS) and overall survival (OS). The impact on prognosis was evaluated using uni‐ and multivariate analyses.

Results

The proportion of histological grade changed according to invasive tumor size. Patients with high malignant grade (G3) showed worse RFS than those with low and intermediate malignant grade (G1+2) with invasive size ≤20 mm. The 5‐year RFS (G1+2 vs. G3) in 5–10 mm was 96.0% vs. 83.3% (HR = 5.505, 95% CI = 7.156–1850, p < 0.001) and in 10–20 mm was 87.8% vs. 67.1% (HR = 2.829, 95% CI = 4.160–43.14, p < 0.001). G3 patients were significantly bigger in invasive size and included more pleural/lymphatic/vascular invasion and recurrence. Multivariate analysis indicated pathological G3 status was significantly associated with worse RFS (HR = 2.097, 95% CI = 1.320–3.333, p = 0.002).

Conclusions

Invasive tumor size and pathological malignant grade overlap in invasive adenocarcinoma. G3 patients are more likely to have pleural/lymphatic/vascular invasion and significantly worse RFS compared to G1/G2 cases, even with a small invasive size of ≤20 mm.