Location of stage I-III non-small cell lung cancer and survival rate: Systematic review and meta-analysis

Tumor Location Is an Independent Prognostic Factor in Completely Resected Pathological Stage I Non-Small Cell Lung Cancer: A Multicenter Retrospective Study

Previous studies suggested that the location of the primary tumor in non-small cell lung cancer (NSCLC) is associated with clinical features and prognosis, but results are conflicting. The purpose of this study was to explore tumor location as an independent risk factor of survival for patients with completely resected pathological stage I NSCLC. This was a multicenter retrospective study conducted in Taiwan. Included patients were diagnosed with stage I NSCLC and had undergone primary tumor resection. Variables including tumor location, pathological stage, histological differentiation, and International Association for the Study of Lung Cancer (IASLC) grade were evaluated for predictive ability for disease-free survival (DFS) and overall survival (OS). A total of 208 patients were included, with 123 (59.1%) patients having a primary tumor in the upper and middle lobes. The median duration of follow-up for survivors was 60.5 months. Compared to patients with IASLC Grade 3 disease, patients with Grade 1 disease had significantly longer DFS. Tumor location and IASLC grade were independent predictors for OS in multivariate analysis. Specifically, patients with NSCLC in the lower lobe and patients who are histologically classified as IASLC Grade 3 may have poorer prognosis and require greater attention to improve outcomes.

The Cancer Spectrum Theory

SUMMARY

Biological characteristics of tumors are heterogeneous, forming spectra in terms of several factors such as age at onset, anatomic spatial localization, tumor subtyping, and the degree of tumor aggressiveness (encompassing a neoplastic property spectrum). Instead of blindly using dichotomized approaches, the application of the multicategorical and continuous analysis approaches to detailed cancer spectrum data can contribute to a better understanding of the etiology of cancer, ultimately leading to effective prevention and precision oncology. We provide examples of cancer spectra and emphasize the importance of integrating the cancer spectrum theory into large-scale population cancer research.

Distribution and characteristics of malignant tumours by lung lobe

BACKGROUND

The main focus on the characteristics of malignant lung tumours has been the size, position within the lobe, and infiltration into neighbouring structures. The aim of this study was to investigate the distribution and characteristics of malignant tumours between the lung lobes and whether the diagnosis, treatment, and outcome differed based on location.

METHODS

This study is based on 10,849 lung cancer patients diagnosed in 2018-2022 with complete data on the location and characteristics of the tumours. The proportions of tumours in each lobe divided by its volume were termed the relative proportion.

RESULTS

The right upper lobe comprised 31.2% of the tumours and 17.6% of the lung volume. The relative proportion of 1.77 was higher than in the other lobes (p < 0.001). The right middle lobe had a relative proportion of 0.64 but the highest proportion of neuroendocrine tumours (26.1% vs. 15.3 on average). Surgical resection was more often performed in patients with tumours in the lower lobes, and curative radiotherapy was more often performed in the upper lobes. After adjusting for age, sex, stage, and histology, the location of the tumour was found to be a significant independent predictor for resection but not for survival.

CONCLUSION

The main finding of the right upper lobe as a site of predilection for lung cancer is similar to tuberculosis and pneumoconiosis. This may be explained that most of the inhaled air, containing bacilli, inorganic particles or tobacco smoke goes to the upper and right parts of the lung.

Changes in the symptom clusters of elderly patients with lung cancer over the course of postoperative rehabilitation and their correlation with frailty and quality of life: A longitudinal study

OBJECTIVE

To explore changes in the symptom clusters of perioperatively elderly patients with lung cancer at different time points (i.e., the day of admission [T0]), 2-4 days after surgery [T1], 1 month after discharge [T2] and 3 months after discharge [T3]) and to analyze correlations between cluster severity, frailty and quality of life (QOL).

METHODS

A longitudinal study was conducted from August 2020 to June 2021 among elderly lung cancer patients undergoing surgery at hospitals in Jiangsu Province. Data were collected using the Chinese Tilburg Frailty Indicator, the MD Anderson Symptom Inventory and the Quality of Life-Core scale.

RESULTS

According to exploratory factor analysis, a total of 5 symptom clusters were found and three of them (the global mental function symptom cluster, the special mental function symptom cluster and the respiratory function symptom cluster) were persistent. The incidence of the top four symptoms varied at different time points. The severity of symptom clusters at different time points was positively correlated with frailty and negatively correlated with QOL.

CONCLUSIONS

The findings may serve as a reference for medical staff to implement symptom management in elderly lung cancer patients after surgery. Frailty may be an important variable affecting the severity of symptom clusters and the QOL of patients.

[Development and Validation of A Prognostic Nomogram to Guide Decision-making in Lung Large Cell Neuroendocrine Carcinoma]

BACKGROUND

Lung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly malignant lung tumor with a poor prognosis. Currently, most research on LCNEC is based on retrospective studies and lacks validation in the real world. The study aims to identify independent risk factors and establish and validate a predictive model for the prognosis of LCNEC.

METHODS

Patient data were extracted from Surveillance, Epidemiology, and End Results (SEER) and our department's hospitalization records from 2010 to 2015 and 2016 to 2020, respectively. Kaplan-Meier analysis was used to evaluate overall survival (OS). OS is defined as the time from diagnosis to death or last follow-up for a patient. Univariate and multivariate Cox regression analyses were performed to identify significant prognostic factors and construct a Nomogram for predicting the prognosis of LCNEC.

RESULTS

In total, 1892 LCNEC patients were included and divided into a training cohort (n=1288) and two validation cohorts (n=552, n=52). Univariate Cox regression analysis showed that age, gender, primary tumor site, laterality, T stage, N stage, M stage, surgery, and radiotherapy were factors that could affect the prognosis of LCNEC patients (P<0.05). Multivariate Cox analysis indicated that age, gender, primary tumor site, T stage, N stage, M stage, surgery, and radiotherapy were independent risk factors for the prognosis of LCNEC patients (P<0.05). Calibration curves and the concordance index (internal: 0.744±0.015; external: 0.763±0.020, 0.832±0.055) demonstrated good predictive performance of the model.

CONCLUSIONS

Patients aged ≥65 years, male, with advanced tumor-node-metastasis (TNM) staging, and who have not undergone surgery or radiotherapy have a poor prognosis. Nomogram can provide a certain reference for personalized clinical decision-making for patients.

Lung cancer treatment potential and limits associated with the STAT family of transcription factors

Lung cancer is one of the mortal cancers and the leading cause of cancer-related mortality, with a cancer survival rate of fewer than 5% in developing nations. This low survival rate can be linked to things like late-stage detection, quick postoperative recurrences in patients receiving therapy, and chemoresistance developing against various lung cancer treatments. Signal transducer and activator of transcription (STAT) family of transcription factors are involved in lung cancer cell proliferation, metastasis, immunological control, and treatment resistance. By interacting with specific DNA sequences, STAT proteins trigger the production of particular genes, which in turn result in adaptive and incredibly specific biological responses. In the human genome, seven STAT proteins have been discovered (STAT1 to STAT6, including STAT5a and STAT5b). Many external signaling proteins can activate unphosphorylated STATs (uSTATs), which are found inactively in the cytoplasm. When STAT proteins are activated, they can increase the transcription of several target genes, which leads to unchecked cellular proliferation, anti-apoptotic reactions, and angiogenesis. The effects of STAT transcription factors on lung cancer are variable; some are either pro- or anti-tumorigenic, while others maintain dual, context-dependent activities. Here, we give a succinct summary of the various functions that each member of the STAT family plays in lung cancer and go into more detail about the advantages and disadvantages of pharmacologically targeting STAT proteins and their upstream activators in the context of lung cancer treatment.

An eleven-gene risk model associated with lymph node metastasis predicts overall survival in lung adenocarcinoma

Lung adenocarcinoma (LUAD) occupies major causes of tumor death. Identifying potential prognostic risk genes is crucial to predict the overall survival of patients with LUAD. In this study, we constructed and proved an 11-gene risk signature. This prognostic signature divided LUAD patients into low- and high-risk groups. The model outperformed in prognostic accuracy at varying follow-up times (AUC for 3 years: 0.699, 5 years: 0.713, and 7 years: 0.716). Two GEO datasets also indicate the great accuracy of the risk signature (AUC = 782 and 771, respectively). Multivariate analysis identified 4 independent risk factors including stage N (HR 1.320, 95% CI 1.102-1.581, P = 0.003), stage T (HR 3.159, 95% CI 1.920-3.959, P < 0.001), tumor status (HR 5.688, 95% CI 3.883-8.334, P < 0.001), and the 11-gene risk model (HR 2.823, 95% CI 1.928-4.133, P < 0.001). The performance of the nomogram was good in the TCGA database (AUC = 0.806, 0.798, and 0.818 for 3-, 5- and 7-year survival). The subgroup analysis in different age, gender, tumor status, clinical stage, and recurrence stratifications indicated that the accuracy was high in different subgroups (all P < 0.05). Briefly, our work established an 11-gene risk model and a nomogram merging the model with clinicopathological characteristics to facilitate individual prediction of LUAD patients for clinicians.

Activities against Lung Cancer of Biosynthesized Silver Nanoparticles: A Review

Nanomedicine is an interdisciplinary field where nanostructured objects are applied to treat or diagnose disease. Nanoparticles (NPs) are a special class of materials at nanometric scale that can be prepared from lipids, polymers, or noble metals through bottom-up approaches. Biological synthesis is a reliable, sustainable, and non-toxic bottom-up method that uses phytochemicals, microorganisms, and enzymes to induce the reduction of metal ions into NPs. Silver (Ag) NPs exhibit potent therapeutic properties that can be exploited to overcome the limitations of current treatment modalities for human health issues such as lung cancer (LC). Here, we review the preparation of AgNPs using biological synthesis and their application against LC using in vitro and in vivo models. An overview of the staging, diagnosis, genetic mutations, and treatment of LC, as well as its main subtypes, is presented. A summary of the reaction mechanisms of AgNPs using microbial cell cultures, plant extracts, phytochemicals, and amino acids is included. The use of capping agents in the biosynthesis of AgNPs with anticancer activity is also detailed. The history and biological activities of metal-based nanostructures synthesized with gold, copper, palladium, and platinum are considered. The possible anticancer mechanisms of AgNPs against LC models are covered. Our perspective about the future of AgNPs in LC treatment and nanomedicine is added.

Novel nutritional indicator as predictors among subtypes of lung cancer in diagnosis

Introduction

Lung cancer is a serious global health concern, and its subtypes are closely linked to lifestyle and dietary habits. Recent research has suggested that malnutrition, over-nutrition, electrolytes, and granulocytes have an effect on the development of cancer. This study investigated the impact of combining patient nutritional indicators, electrolytes, and granulocytes as comprehensive predictors for lung cancer treatment outcomes, and applied a machine learning algorithm to predict lung cancer.

Methods

6,336 blood samples were collected from lung cancer patients classified as lung squamous cell carcinoma (LUSC), lung adenocarcinoma (LUAD), and small cell lung cancer (SCLC). 2,191 healthy individuals were used as controls to compare the differences in nutritional indicators, electrolytes and granulocytes among different subtypes of lung cancer, respectively.

Results

Our results demonstrated significant differences between men and women in healthy people and NSCLC, but no significant difference between men and women in SCLC patients. The relationship between indicators is basically that the range of indicators for cancer patients is wider, including healthy population indicators. In the process of predicting lung cancer through nutritional indicators by machine learning, the AUC of the random forest model was as high as 93.5%, with a sensitivity of 75.9% and specificity of 96.5%.

Discussion

This study supports the feasibility and accuracy of nutritional indicators in predicting lung cancer through the random forest model. The successful implementation of this novel prediction method could guide clinicians in providing both effective diagnostics and treatment of lung cancers.

Nanoparticle-containing lyophilized dry powder inhaler formulations optimized using central composite design with improved aerodynamic parameters and redispersibility

Objectives: The aim of this study was to improve the aerodynamic behavior and redispersibility of a lyophilized dry powder inhaler (DPI) formulation containing nanoparticles.Methods: Paclitaxel (PTX)-human serum albumin (HSA) nanoparticles were used as a model, and DPIs containing the nanoparticles were produced by lyophilization using different carriers and carrier ratios. A central composite design was employed to optimize the formulation. L-leucine and mannitol were chosen as independent variables, and mass median aerodynamic diameter (MMAD), emitted fraction, fine particle fraction (FPF), nanoparticle size, polydispersity index (PDI), zeta potential were selected as dependent variables.Results: The water content of DPIs was less than 5% for all DPIs. The cytotoxicity of the DPIs, determined using A549 cells, was due to PTX alone. Particle sizes of 204.3 ± 1.65 nm and 94.3-1353.0 nm were obtained before and after lyophilization, respectively. The developed method resulted in a reduction in the MMAD from 8.148 µm to 5.274 µm, an increase in the FPF from 17.63% to 33.60%, and an increase in the emitted fraction from 77.68% to 97.03%. The physico-chemical characteristics of the optimized formulation were also assessed.Conclusions: In conclusion, this study demonstrates that lyophilization can be used to produce nanoparticle-containing DPI formulations with improved redispersibility and aerodynamic properties.

An Investigation of Symptom Clusters and Sentinel Symptoms During the First 2 Cycles of Postoperative Chemotherapy in Patients With Lung Cancer

BACKGROUND

Lung cancer has the highest incidence and mortality of all cancers in China. Patients after a lobectomy experience serious physical and psychological symptoms during chemotherapy. Studies are lacking about symptom clusters (SCs) and sentinel symptoms during the postoperative chemotherapy period in lung cancer patients.

OBJECTIVE

The aim of this study was to explore SCs and sentinel symptoms during cycles 1 and 2 of postoperative chemotherapy in patients with lung cancer.

METHODS

Using a longitudinal study design, patients in treatment for lung cancer were measured at 2 separate points following a lobectomy: chemotherapy cycle 1 and chemotherapy cycle 2. The MD Anderson Symptom Inventory lung cancer-specific module and First Appearance of Symptoms Time Sheet were completed.

RESULTS

A total of 180 postoperative patients with lung cancer participated in the study. Four SCs were identified at chemotherapy cycle 1: gastrointestinal SC, respiratory tract SC, psychological SC, and somatic SC. The sentinel symptoms were nausea, cough, sadness, and fatigue. At chemotherapy cycle 2, similar SCs were identified, with the exception of merging the psychological SC and somatic SC, resulting in 3 clusters: gastrointestinal SC, respiratory tract SC, and psychological-somatic SC. The sentinel symptoms were nausea, cough, and fatigue.

CONCLUSIONS

Symptom clusters and sentinel symptoms were stable during the first 2 cycles of postoperative chemotherapy in patients with lung cancer.

IMPLICATIONS FOR PRACTICE

The understanding of SCs and sentinel symptoms could be beneficial to assess and manage both in postoperative patients with lung cancer during chemotherapy. Nurses should pay close attention to sentinel symptoms and develop effective interventions.

Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort

Objective

This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC).

Methods

For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves.

Results

A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718–0.735) and 0.721 (95% CI, 0.709–0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691–0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system.

Conclusion

We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10067-8.

Cost-effectiveness analysis of adjuvant therapy with atezolizumab in Chinese patients with stage IB-IIIA resectable NSCLC after adjuvant chemotherapy

Background

Atezolizumab was first shown to significantly improve progression-free survival (PFS) after platinum-based chemotherapy in early-stage non-small cell lung cancer (NSCLC) in the IMpower010 Phase 3 trial. However, the cost-effectiveness and potential economic impact of atezolizumab treatment in Chinese patients are unknown.

Methods

Markov models were constructed based on follow-up data from the IMpower010 trial and assessed separately in the programmed cell death receptor ligand-1 (PD-L1) tumor cells (TC) ≥ 1% stage II – IIIA group, all stage II – IIIA groups, and the intention-to-treat (ITT) group (stage IB–IIIA). Efficacy and safety data were obtained from the IMpower010 trial, and costs and utility values were derived from the literature and local surveys to estimate their incremental cost-effectiveness ratios (ICERs) compared with willingness-to-pay (WTP) thresholds in scenarios implementing patient assistance programs (PAP) or drug price negotiations. Univariate sensitivity analysis and probabilistic sensitivity analysis (PSA) were performed to investigate the stability of the model results.

Results

Compared with best supportive care (BSC), atezolizumab produced an additional 0.45 quality-adjusted life-years (QALYs), 0.04 QALYs, and -0.0028 QALYs in the PD-L1 TC ≥ 1% stage II – IIIA group, all stage II – IIIA groups, and the ITT group, and the ICERs were 108,825.37/QALY, 1,028,538.22/QALY, and -14,381,171.55/QALY, respectively. The ICERs all exceeded the WTP threshold of $27,354 per QALY (three times the per capita gross domestic product of China in 2022), and univariate sensitivity analysis showed that the price of atezolizumab played a crucial role in the model results. PSA showed that the probability of cost-effectiveness of atezolizumab in the PD-L1 TC ≥ 1% stage II – IIIA group, all stage II – IIIA groups, and the ITT group increased with the increasing WTP threshold.

Conclusion

From the perspective of China’s health care system, in the PD-L1 TC ≥ 1% stage II – IIIA group, all stage II – IIIA groups, and the ITT group, the use of atezolizumab in the adjuvant treatment of patients with early-stage NSCLC after platinum-based chemotherapy is unlikely to be cost-effective. The implementation of PAP or price reduction negotiations for atezolizumab might be among the most effective measures to improve its cost-effectiveness.

Infrastructure platform for privacy-preserving distributed machine learning development of computer-assisted theragnostics in cancer

INTRODUCTION

Emerging evidence suggests that data-driven support tools have found their way into clinical decision-making in a number of areas, including cancer care. Improving them and widening their scope of availability in various differing clinical scenarios, including for prognostic models derived from retrospective data, requires co-ordinated data sharing between clinical centres, secondary analyses of large multi-institutional clinical trial data, or distributed (federated) learning infrastructures. A systematic approach to utilizing routinely collected data across cancer care clinics remains a significant challenge due to privacy, administrative and political barriers.

METHODS

An information technology infrastructure and web service software was developed and implemented which uses machine learning to construct clinical decision support systems in a privacy-preserving manner across datasets geographically distributed in different hospitals. The infrastructure was deployed in a network of Australian hospitals. A harmonized, international ontology-linked, set of lung cancer databases were built with the routine clinical and imaging data at each centre. The infrastructure was demonstrated with the development of logistic regression models to predict major cardiovascular events following radiation therapy.

RESULTS

The infrastructure implemented forms the basis of the Australian computer-assisted theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning. Four radiation oncology departments (across seven hospitals) in New South Wales (NSW) participated in this demonstration study. Infrastructure was deployed at each centre and used to develop a model predicting for cardiovascular admission within a year of receiving curative radiotherapy for non-small cell lung cancer. A total of 10417 lung cancer patients were identified with 802 being eligible for the model. Twenty features were chosen for analysis from the clinical record and linked registries. After selection, 8 features were included and a logistic regression model achieved an area under the receiver operating characteristic (AUROC) curve of 0.70 and C-index of 0.65 on out-of-sample data.

CONCLUSION

The infrastructure developed was demonstrated to be usable in practice between clinical centres to harmonize routinely collected oncology data and develop models with federated learning. It provides a promising approach to enable further research studies in radiation oncology using real world clinical data.

Oncologic Outcomes of Patients With Resected T3N0M0 Non-small Cell Lung Cancer

In the eighth edition TNM staging, the T3N0M0 category represents a heterogeneous group of non-small cell lung cancers (NSCLC). This study aims to compare the oncologic outcomes associated with individual T3 features. We performed a single-institution, retrospective analysis of 280 consecutive patients with pT3N0M0 NSCLC. Multivariate regression models were used to estimate associations of clinical factors with oncologic outcomes. The patients were grouped according to their T3 features into 4 prognostic groups: chest wall infiltration (CWI-PG), largest diameter >5 cm and ≤7 cm (Size-PG), presence of a satellite nodule (SN-PG), and all other T3 features. Overall survival (OS) and progression-free survival (PFS) were estimated using Kaplan-Meier and Cox proportional hazard analyses. Tumors were most often classified as T3N0M0 by size (156 patients, 55.7%), and the highest rate of incomplete resection occurred in patients with CWI (n = 7, 25.9%). In multivariate analysis, CWI (hazard ratio [HR] 2.45, 95% confidence interval [CI] 1.36, 4.44), incomplete resection (HR 3.01, 95% CI 1.29, 7.05), and age >65 (HR 1.6; 95% CI 1.08, 2.38) were independently associated with worse OS, and female sex was associated with better OS (HR 0.6, 95% CI 0.42, 0.87). The CWI-PG had poorer OS when compared with each of the other prognostic groups (P < 0.05), and the Size-PG had inferior OS when compared with the SN-PG (P = 0.039). This single-center study demonstrated significant differences in OS and PFS between patients with different T3 classifying features and suggest that further subdivision of the T3 category should be considered.

DNA methylation influences the CTCF-modulated transcription of RASSF1A in lung cancer cells

Ras-association domain family 1A (RASSF1A) is one of the most methylated genes in lung cancer (LC). We investigate whether the high DNA methylation level of RASSF1A can relieve the resistance of RASSF1A to LC by inhibiting RASSF1A's transcription factor binding to RASSF1A. RASSF1A expression in tissues and cells was tested utilizing quantitative real-time polymerase chain reaction (qRT-PCR), and Western blot. RASSF1A expression and RASSF1A methylation level in LC cells exposed to 5-Aza-dc were assessed by qRT-PCR and quantitative methylation-specific PCR. The association between CTCF and RASSF1A was assessed using hTFtarget, ChIP, and luciferase reporter gene analysis. The effects of 5-Aza-dc, CTCF, and RASSF1A on cell biological behaviors and epithelial-mesenchymal transition (EMT)-related markers were assessed by cell function experiments and Western blot. Moreover, we constructed the xenograft tumor and pulmonary nodule metastasis models, and assessed tumor volume and weight. RASSF1A expression and pulmonary nodule metastasis were tested utilizing qRT-PCR, Western blot, and H&E staining. RASSF1A was under-expressed in LC tissues and cells. 5-Aza-dc enhanced RASSF1A level and weakened RASSF1A methylation level in LC cells. RASSF1A silencing neutralized 5-Aza-dc-mediated repressing effects on LC cell biological function and EMT. The loss of CTCF binding to RASSF1A in LC cells was associated with DNA methylation. The effect of 5-Aza-dc on RASSF1A level, LC cell malignant behaviors, and EMT-related factors were strengthened by CTCF upregulation. RASSF1A overexpression suppressed LC tumor growth and pulmonary nodule metastasis in vivo. DNA methylation blocked the modulation of RASSF1A expression by CTCF and relieved the resistance of RASSF1A to LC.

A New Nomogram and Risk Stratification of Brain Metastasis by Clinical and Inflammatory Parameters in Stage III Small Cell Lung Cancer Without Prophylactic Cranial Irradiation

Background

This study was conducted to determine risk factors for developing brain metastasis (BM) and to predict brain metastasis free survival (BMFS) and overall survival (OS) by combining several clinical parameters and inflammatory indexes.

Materials and Methods

A nomogram and risk stratification were developed based on multivariate analysis results. The prognostic index (PI) predicting the high risk of BM was calculated by multiplying the weighted factor (β coefficient) with each variable.

Results

Thirty-two of one hundred patients (32.0%) developed BM. Multivariate cox regression analysis revealed that concurrent chemoradiotherapy (CCRT; hazard ratio (HR), 3.356; p = 0.020), monocyte–lymphocyte ratio (MLR; HR, 4.511; p = 0.002), neutrophil–lymphocyte ratio (NLR; HR, 4.023; p = 0.033), and prognostic-nutrition index (PNI; HR, 2.902; p = 0.018) were independent prognostic factors of BMFS. The nomogram has good accuracy in predicting BMFS, and the C-index was 0.73. The ROC curve showed that these risk factors have good discriminant ability. Similarly, tumor location (HR, 1.675; p = 0.035) and MLR (HR, 2.076; p = 0.013) were independent prognostic factors of OS. In the subgroup analysis of OS, the good group had a better prognosis than the other groups. Risk stratification by PI: the high-risk group had worse BMFS than the low-risk group, which also has certain practical significance for clinical practice in OS.

Conclusion

We developed a nomogram and corresponding risk stratification in stage III SCLC patients who developed BM. This model and risk stratification can help clinicians improve patient treatment management and better deliver personalized therapy.

Predicting 2-year survival in stage I-III non-small cell lung cancer: the development and validation of a scoring system from an Australian cohort

Background

There are limited data on survival prediction models in contemporary inoperable non-small cell lung cancer (NSCLC) patients. The objective of this study was to develop and validate a survival prediction model in a cohort of inoperable stage I-III NSCLC patients treated with radiotherapy.

Methods

Data from inoperable stage I-III NSCLC patients diagnosed from 1/1/2016 to 31/12/2017 were collected from three radiation oncology clinics. Patient, tumour and treatment-related variables were selected for model inclusion using univariate and multivariate analysis. Cox proportional hazards regression was used to develop a 2-year overall survival prediction model, the South West Sydney Model (SWSM) in one clinic (n = 117) and validated in the other clinics (n = 144). Model performance, assessed internally and on one independent dataset, was expressed as Harrell’s concordance index (c-index).

Results

The SWSM contained five variables: Eastern Cooperative Oncology Group performance status, diffusing capacity of the lung for carbon monoxide, histological diagnosis, tumour lobe and equivalent dose in 2 Gy fractions. The SWSM yielded a c-index of 0.70 on internal validation and 0.72 on external validation. Survival probability could be stratified into three groups using a risk score derived from the model.

Conclusions

A 2-year survival model with good discrimination was developed. The model included tumour lobe as a novel variable and has the potential to guide treatment decisions. Further validation is needed in a larger patient cohort.

LncRNA HOXC-AS3 increases non-small cell lung cancer cell migration and invasion by sponging premature miR-96

BACKGROUND

HOXC cluster antisense RNA 3 (HOXC-AS3) has been characterized as a critical long noncoding RNA (lncRNA) player in breast cancer and gastric cancer, while its role in non-small cell lung cancer (NSCLC) is not clear. We hypothesized that HOXC-AS3 could interact with premature microRNA (miR)-96. This study was therefore carried out to explore the crosstalk between HOXC-AS3 and miR-96 in NSCLC.

METHODS

The expression of HOXC-AS3 and miR-96 (both mature and premature) were detected using RT-qPCR. Nuclear fractionation assay and RNA pull-down assay were performed to detect the subcellular location of HOXC-AS3 and potential interaction with premature miR-96, respectively. Overexpression assays were performed to determine the role of HOXC-AS3 in the maturation of miR-96. Transwell assays were performed to explore the role of HOXC-AS3 and miR-96 in NSCLC cell invasion and migration.

RESULTS

NSCLC tissues exhibited significantly increased expression levels of HOXC-AS3 and premature miR-96. HOXC-AS3 was localized to both nucleus and cytoplasm, and a direct interaction between HOXC-AS3 and premature miR-96 was observed. In NSCLC cells, HOXC-AS3 upregulated the expression of premature miR-96 but downregulated the expression of mature miR-96. Moreover, HOXC-AS3 suppressed the role of miR-96 in inhibiting NSCLC cell invasion and migration.

CONCLUSION

HOXC-AS3 may increase NSCLC cell growth and invasion by sponging premature miR-96 to suppress its maturation.

Primary tumor location in lung cancer: the evaluation and administration

ABSTRACT

Lung cancer continues to be the leading cause of cancer-related death in the world, which is classically subgrouped into two major histological types: Non-small cell lung cancer (NSCLC) (85% of patients) and small-cell lung cancer (SCLC) (15%). Tumor location has been reported to be associated with the prognosis of various solid tumors. Several types of cancer often occur in a specific region and are more prone to spread to predilection locations, including colorectal cancer, prostate cancer, gastric cancer, ovarian cancer, cervical cancer, bladder cancer, lung tumor, and so on. Besides, tumor location is also considered as a risk factor for lung neoplasm with chronic obstructive pulmonary disease/emphysema. Additionally, the primary lung cancer location is associated with specific lymph node metastasis. And the recent analysis has shown that the primary location may affect metastasis pattern in metastatic NSCLC based on a large population. Numerous studies have enrolled the "location" factor in the risk model. Anatomy location and lobe-specific location are both important in prognosis. Therefore, it is important for us to clarify the characteristics about tumor location according to various definitions. However, the inconsistent definitions about tumor location among different articles are controversial. It is also a significant guidance in multimode therapy in the present time. In this review, we mainly aim to provide a new insight about tumor location, including anatomy, clinicopathology, and prognosis in patients with lung neoplasm.

Change in symptom clusters perioperatively in patients with lung cancer

PURPOSE

To describe the trajectory, number, and types of symptom clusters at three time points (i.e., day of admission [T1], 2-4 days postoperatively [T2], and 1 month postoperatively [T3]) using ratings of symptom occurrence and severity and to identify the changes in these symptom clusters over time in patients with lung cancer.

METHODS

We analysed the data of 217 lung cancer patients who received surgical treatment at a tertiary hospital affiliated to Anhui Medical University, in Hefei City, China. The occurrence and severity of 19 symptoms at all points of measurement were measured using the general and lung cancer modules of the M.D. Anderson Symptom Inventory. Exploratory factor analysis was performed to extract the symptom clusters.

RESULTS

Seven symptom clusters were identified across symptom dimensions. However, only three of them (i.e., lung cancer specific, sleep disturbance, and nervous system) were relatively stable across dimensions and time. Two symptom clusters varied over time but not with dimensions (nutritional and gastrointestinal). The other two symptom clusters (psychological and respiratory) differed in terms of time and dimensions.

CONCLUSIONS

Findings may provide insights into the seven identified clusters and overall stability of three symptom clusters in lung cancer patients perioperatively.

Quantification of the spatial distribution of primary tumors in the lung to develop new prognostic biomarkers for locally advanced NSCLC

The anatomical location and extent of primary lung tumors have shown prognostic value for overall survival (OS). However, its manual assessment is prone to interobserver variability. This study aims to use data driven identification of image characteristics for OS in locally advanced non-small cell lung cancer (NSCLC) patients. Five stage IIIA/IIIB NSCLC patient cohorts were retrospectively collected. Patients were treated either with radiochemotherapy (RCT): RCT1* (n = 107), RCT2 (n = 95), RCT3 (n = 37) or with surgery combined with radiotherapy or chemotherapy: S1* (n = 135), S2 (n = 55). Based on a deformable image registration (MIM Vista, 6.9.2.), an in-house developed software transferred each primary tumor to the CT scan of a reference patient while maintaining the original tumor shape. A frequency-weighted cumulative status map was created for both exploratory cohorts (indicated with an asterisk), where the spatial extent of the tumor was uni-labeled with 2 years OS. For the exploratory cohorts, a permutation test with random assignment of patient status was performed to identify regions with statistically significant worse OS, referred to as decreased survival areas (DSA). The minimal Euclidean distance between primary tumor to DSA was extracted from the independent cohorts (negative distance in case of overlap). To account for the tumor volume, the distance was scaled with the radius of the volume-equivalent sphere. For the S1 cohort, DSA were located at the right main bronchus whereas for the RCT1 cohort they further extended in cranio-caudal direction. In the independent cohorts, the model based on distance to DSA achieved performance: AUC_RCT2 [95% CI] = 0.67 [0.55–0.78] and AUC_RCT3 = 0.59 [0.39–0.79] for RCT patients, but showed bad performance for surgery cohort (AUC_S2 = 0.52 [0.30–0.74]). Shorter distance to DSA was associated with worse outcome (p = 0.0074). In conclusion, this explanatory analysis quantifies the value of primary tumor location for OS prediction based on cumulative status maps. Shorter distance of primary tumor to a high-risk region was associated with worse prognosis in the RCT cohort.

Correlation between tumor location and survival in stage I lung adenocarcinoma and squamous cell carcinoma: a SEER-based study

Background: Whether location mattered remained controversial in early-stage non-small cell lung cancer.

Methods: We conducted a retrospective study with the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival (OS) and lung cancer-specific survival (LCSS) with landmark analysis and restricted mean survival time (RMST) were compared between patients with a tumor in upper lobe and non-upper lobe. The multivariable Cox analysis was applied to evaluate multiple prognostic factors.

Results: Tumor in non-upper lobe had worse OS (hazard ratio [HR]: 1.354, p < 0.001) and LCSS (HR: 1.476, p = 0.005) than the upper lobe in stage IB adenocarcinoma in 32-month landmark and IA3 (OS, HR: 1.300, p < 0.001; LCSS, HR: 1.413, p = 0.004) adenocarcinoma in 48-month landmark, but not in stage IA1 and IA2 adenocarcinoma. The results remained positive in subgroups of < 4, ≥ 4 and ≥ 11 LN examined in stage IB tumor and ≥ 4 LN examined in stage IA3 tumor. For SCC, non-upper lobar tumor had similar OS and LCSS with upper lobar tumor in all stages. The multivariate Cox analysis confirmed that the non-upper lobe was an independent risk factor in stage IA3-IB adenocarcinoma, but not in SCC. Adjuvant chemotherapy (ACT) could improve OS in stage IB adenocarcinoma (HR: 0.586, p < 0.001) and SCC (HR: 0.708, p = 0.030) located in non-upper lobe.

Conclusions: Non-upper lobar adenocarcinoma in stage IA3-IB was associated with worse prognosis. ACT may improve prognosis in stage IB tumor located in non-upper lobe.

Identification of Resectable N2 in NSCLC: A Single Center Experience and Review of the SEER Database

Background

Non-small cell lung carcinoma (NSCLC) with ipsilateral and/or subcarinal mediastinal lymphatic spread (N2) is a heterogeneous disease. The role of surgical resection in patients with N2 NSCLC remains controversial and no survival-based definition of “resectable N2” exists. The purpose of this study is to evaluate the factors that potentially affect the survival of N2 NSCLC patients who receive surgical resection and to define “resectable N2” based on the survival benefits.

Methods

Data from the open Surveillance, Epidemiology, and End Results (SEER) database from the National Cancer Institute in the United States were used to construct a nomogram. Patients who received surgery between 2010 and 2015 for N2 NSCLC were included. Independent prognostic factors for survival identified through Cox regression analysis were used to create the nomogram. The C-index, receiver operating characteristics (ROC) analyses, calibration curves, and risk stratification were used to evaluate the nomogram. The nomogram was also validated using data from 222 patients from Peking Union Medical College Hospital (PUMCH). Furthermore, lung cancer–related deaths were compared using competitive risk analysis.

Results

In total, 4267 patients were included in the SEER cohort. Male gender, old age, high T stage and grade, adenosquamous and squamous cell carcinoma, lower lobe and overlapping lesions, extended lobe or bilobectomy and pneumonectomy, no chemotherapy, radiation before and after surgery, positive number of lymph nodes, and lymph node ratio (LNR) were identified as independent risk factors for higher mortality. The nomogram was created using these parameters. The C-index was 0.665 (95% confidence interval (CI), 0.651-0.679) and 0.722 (95% CI, 0.620-0.824) in the SEER and PUMCH cohorts, respectively. The calibration curves showed satisfactory consistency between the predicted and actual survival status in both the SEER and PUMCH cohorts. Competitive risk analysis confirmed that the variables in the nomogram, except radiation, are risk factors for prognosis.

Conclusions

“Resectable N2” should be assessed by a multidisciplinary team. The novel nomogram developed in this study may help with clinical decision-making for this patient population.

Kinesin family member 2A promotes cancer cell viability, mobility, stemness, and chemoresistance to cisplatin by activating the PI3K/AKT/VEGF signaling pathway in non-small cell lung cancer

Kinesin family member 2A (KIF2A), a member of the kinesin-13 protein family that functions as a regulator in mitosis, neuron branch extension, etc., is reported to be involved in the pathogenesis of multiple cancers. This study assessed KIF2A effects on cancer cell functions and sensitivity to chemotherapy and its interaction with PI3K/AKT/VEGF signaling when mediating cancer cell functions, and chemosensitivity in non-small cell lung cancer (NSCLC). Human bronchial epithelial cell line BEAS-2B and human NSCLC cell lines NCI-H1299, NCI-H385, NCI-H1650, and A549 were used. The KIF2A and negative control (NC) overexpression plasmids were transfected into A549 cells; KIF2A and NC knock-down plasmids were transfected into NCI-H1299 cells. Rescue experiments were conducted by transfecting PI3K and NC knock-down plasmids into KIF2A overexpression A549 cells and transfecting PI3K and NC overexpression plasmids into KIF2A knock-down NCI-H1299 cells. Proliferation, apoptosis, migration, invasion, CD133⁺ proportion, sensitivity to chemotherapeutics, and PI3K/AKT/VEGF pathway were assessed. KIF2A mRNA and protein expression levels were elevated in NCI-H1299, NCI-H385, NCI-H1650, and A549 cells compared to BEAS-2B cells. KIF2A overexpression elevated proliferation, migration, invasion, stemness, and resistance to cisplatin but did not affect apoptosis or resistance to pemetrexed in A549 cells. Furthermore, KIF2A knock-down repressed proliferation, migration, invasion, stemness, and resistance to cisplatin, but not to pemetrexed, and it enhanced apoptosis in NCI-H1299 cells. Rescue experiments showed that the PI3K/AKT/VEGF pathway compensated for KIF2A effects on cell functions and sensitivity to cisplatin in A549 and NCI-H1299 cells. In conclusion, KIF2A advocates NSCLC cell viability, mobility, stemness, and chemoresistance to cisplatin by activating the PI3K/AKT/VEGF signaling pathway.

The development and external validation of an overall survival nomogram in medically inoperable centrally located early-stage non-small cell lung carcinoma

BACKGROUND AND PURPOSE

Current nomograms predicting survival prognosis after stereotactic body radiation therapy (SBRT) in non-small cell lung cancer (NSCLC) are based on peripherally located tumors. However, patients with a central lung tumor tend to be older, the tumor is often larger and fraction-schedules are risk-adapted. Therefore, we developed and externally validated a nomogram to predict overall survival (OS) in patients having centrally located early-stage NSCLC treated with SBRT.

MATERIALS AND METHODS

Patients who underwent SBRT for centrally located NSCLC were identified and baseline characteristics were obtained. A nomogram was built to predict 6-month, 1-, 2- and 3-year OS using Cox proportional hazards model. The model building procedure was validated using bootstrap sampling. To determine generalizability, external validation was performed on a cohort of patients with central NSCLC treated with SBRT from another center. Discriminatory ability was measured with the concordance index (C-index) and calibration plots were used to compare Kaplan-Meier-estimated and nomogram-predicted OS.

RESULTS

The nomogram was built on data of 220 patients and consisted of the following variables: PTV, age, WHO performance status, tumor lobe location and ultracentral location. The C-index of the nomogram (corrected for optimism) was moderate at 0.64 (95% confidence interval (CI) 0.59-0.69). Calibration plots showed favorable predictive accuracy. The external validation showed acceptable validity with a C-index of 0.62 (95% CI 0.61-0.64).

DISCUSSION

We developed and externally validated the first nomogram to estimate the OS-probability in patients with centrally located NSCLC treated with SBRT. This nomogram is based on 5 patient and tumor characteristics and gives an individualized survival prediction.

Outcomes of superior segmentectomy versus lower lobectomy for superior segment Stage I non-small-cell lung cancer are equivalent: An analysis of 196 patients at a single, high volume institution

OBJECTIVES

To determine if superior segmentectomy has equivalent overall (OS), disease-free (DFS), and locoregional-recurrence-free survival (LRFS) to lower lobectomy for early-stage non-small-cell lung cancer (NSCLC) in the superior segment.

METHODS

We retrospectively reviewed all Stage 1 lower lobectomies for superior segment lesions and superior segmentectomies at our hospital from 2000 to 2018. Comparison statistics and Cox hazard modeling were performed to determine differences between groups and attempt to identify risk factors for OS, DFS, and LRFS.

RESULTS

Superior segmentectomy patients, compared with lower lobectomy patients, had more current smokers, worse forced expiratory volume in 1 s percentage, radiologic emphysema scores, clinically and pathologically smaller tumors, and more occurrences of 0 lymph nodes examined. Outcomes for superior segmentectomy compared with lower lobectomy were equivalent for 5-year OS (67.0% vs. 75.1%, p = 0.70), DFS (56.9% vs. 60.4%, p = 0.59), and LRFS (87.9% vs. 91.3%, p = 0.46). Multivariable Cox modeling lacked utility due to no outcome differences.

CONCLUSIONS

In well-selected patients, superior segmentectomies can have equivalent OS, DFS, and LRFS compared with lower lobectomies of superior segment tumors for early stage lung cancer. Further data are needed to provide better risk estimates.

Human pluripotent stem cell-derived lung organoids: Potential applications in development and disease modeling

The pulmonary system is comprised of two main compartments, airways and alveolar space. Their tissue and cellular complexity ensure lung function and protection from external agents, for example, virus. Two-dimensional (2D) in vitro systems and animal models have been largely employed to elucidate the molecular mechanisms underlying human lung development, physiology, and pathogenesis. However, neither of these models accurately recapitulate the human lung environment and cellular crosstalk. More recently, human-derived three-dimensional (3D) models have been generated allowing for a deeper understanding of cell-to-cell communication. However, the availability and accessibility of primary human cell sources from which generate the 2D and 3D models may be limited. In the past few years, protocols have been developed to successfully employ human pluripotent stem cells (hPSCs) and differentiate them toward pulmonary fate in vitro. In the present review, we discuss the advantages and pitfalls of hPSC-derived lung 2D and 3D models, including the main characteristics and potentials for these models and their current and future applications for modeling development and diseases. Lung organoids currently represent the closest model to the human pulmonary system. We further focus on the applications of lung organoids for the study of human diseases such as pulmonary fibrosis, infectious diseases, and lung cancer. Finally, we discuss the present limitations and potential future applications of 3D lung organoids. This article is categorized under: Adult Stem Cells, Tissue Renewal, and Regeneration > Stem Cells and Disease Adult Stem Cells, Tissue Renewal, and Regeneration > Stem Cell Differentiation and Reversion.

Factors associated with overall survival in a population-based cohort of non- squamous NSCLC patients from northern New Zealand: A comparative analysis by EGFR mutation status

BACKGROUND

Previous studies have reported inconsistent results regarding the effect of epidermal growth factor receptor (EGFR) mutations on overall survival in patients with non-squamous non-small-cell lung cancer (NSCLC). This study assesses the effect of EGFR mutation on overall survival, and how the effects of other survival predictors differ by EGFR mutation status.

METHODS

The study used a population- based cohort of 1534 non-squamous NSCLC patients diagnosed in northern New Zealand between 1st February 2010 and 31st July 2017. Cox regression survival analyses were used to explore the associations between clinicopathological factors and overall survival by EGFR mutation status. The factors included were age at diagnosis, sex, ethnicity, smoking status, performance status, metastasis status and tumour site.

RESULTS

In this cohort, 20% had anEGFR mutation. The median overall survival times were 0.8 years and 2.79 years in EGFR-mutation-negative and -positive groups, respectively (p < 0.0001). Metastasis at diagnosis showed large effects on overall survival in both EGFR-mutation- negative (hazard ratio (HR) = 3.6) and mutation-positive (HR = 3.3) groups. In subgroup analyses by mutation status and metastasis, females had lower survival only if they were mutation-positive; Māori had lower survival (than European New Zealanders) only if the disease was metastatic, and tumour site had significant effects only in patients without metastasis. Age, performance status and smoking status showed consistent effects in all subgroups.

CONCLUSION

EGFR mutation status and metastasis are the main predictors for overall survival in non-squamous NSCLC patients. The effects of sex, ethnicity and tumour site vary depending on EGFR mutation and metastasis status.

Role of imaging biomarkers in mutation-driven non-small cell lung cancer

Lung cancer remains the leading cause of cancer-related deaths worldwide. The treatment of non-small cell lung cancer (NSCLC), which accounts for a vast majority of lung cancers, has shifted to personalized, targeted therapy following discoveries of several targetable oncogenic mutations. Targeting of specific mutations has improved outcomes in many patients. This success has led to several target-specific agents replacing chemotherapy as first-line treatment in certain mutated NSCLC. Several researchers have reported that there may be imaging biomarkers that may be predictive of the presence of these mutations. These features, when present, have the potential in triaging patients into the most appropriate diagnostic and treatment algorithms. Distinct imaging features and patterns of metastases that have been associated with NSCLC with various targetable oncogenic mutations are presented in this review.

Antiangiogenesis Roles of Exosomes with Fei-Liu-Ping Ointment Treatment are Involved in the Lung Carcinoma with the Lewis Xenograft Mouse Model

Exosomes display efficient biocompatibility and represent valuable vehicles for drug or effective material delivery in a tumour-therapeutic approach. Following treatment with Fei-Liu-Ping (FLP) ointment, a traditional Chinese herbal formula, which is used for treating lung cancer patients, could inhibit lung carcinoma growth in clinical and animal studies. In the present study, the values of VEGF and PDGF, which were closely related to angiogenesis, were estimated in serum and carcinoma tissue exosomes to unveil the FLP effects on angiogenesis. The common inflammatory factors of IL-6, IL-1β, TNF-α, and TGF-β in serum exosomes were also detected with the Lewis xenograft model. Methods. Male C57BL/6 mice were randomly divided into four groups, namely, normal, model, cyclophosphamide (CTX), and FLP treatment groups. Histological structures were observed and imaged by H&E. CD31 expressions in tumour tissues were detected by immunofluorescence (IF) and western blot (WB). VEGF, PDGF, and PDGFR levels in exosomes, serum, tumour, and lung tissues were detected by enzyme-linked immunosorbent assay (ELISA), immunohistochemistry (IHC), and WB, respectively. IL-6, IL-1β, TNF-α, and TGF-β levels in exosomes were measured by multiplex immunoassay panels. Results. The results showed that FLP had tumour growth inhibition rate (39.31%). CD31 protein expression was obviously decreased in tumour tissues of CTX- and FLP-treated MO mice, compared to that of MO mice (P < 0.05 or P < 0.001). VEGF, PDGF, and PDGFR expression levels with FLP treatment were downregulated in exosomes, serum, tumour, and lung tissues compared to model group (P < 0.05 or P < 0.01). The expressions of IL-6, IL-1β, and TNF-α were downregulated in exosomes compared to the model group (P < 0.05 or P < 0.01). Conclusions. This study suggested that FLP had the ability of inhibiting tumourigenesis in a Lewis lung xenograft mouse model, whose therapeutic mechanisms might relate with the downregulation of angiogenesis factor and tumour inflammatory cytokines levels.

Effects of the recurrence pattern on patient survival following SABR for stage I lung cancer

Background: Information on the effect of the recurrence pattern on survival for stage I lung cancer following stereotactic ablative radiotherapy (SABR) is limited.Materials and Methods: The recurrence pattern was analyzed for 100 consecutive stage I non-small-cell lung cancer patients treated with SABR using predominantly 12 Gy × 4. Recurrences were classified as local, regional lymph nodes and distant. Distant recurrences included recurrences in the lung and outside the chest. Single lung recurrences were named solitary, if no other location was involved. Kaplan-Meier survival estimates were calculated for different locations of recurrence. Clinical and dosimetrical factors affecting survival were also analyzed.Results: Median follow-up was 32 months (3-123), median age 70 years (49-95). In total, 31 patients had recurrences after a median 21 months (4-60): 5 local; 10 regional; 8 distant outside the chest; 25 non-local lung recurrences, of which 15 were single - 10 of which solitary - and 10 multiple lung nodules. Patients with a solitary lung recurrence had longer survival compared to local or distant recurrences (p = .04 each), and compared to multiple lung nodules (p = .09). 3-year local recurrence-free survival was 92%, disease-free survival 69% and overall survival 59%. On multivariate analysis, disease-free survival was associated with statin use (p = .038) and tumor location (p = .035). Smoking history predicted overall survival (p < .0006).Conclusions: A total of 81% of recurrences involved the lungs. Patients with solitary lung recurrences/second primary lung cancers had the longest overall survival suggesting definitive treatment should be considered. The effects of statin use need to be explored further.

Imaging Features and Metastatic Patterns of Advanced ALK-Rearranged Non-Small Cell Lung Cancer

OBJECTIVE.ALK rearrangements are an established targetable oncogenic driver in non-small cell lung cancer (NSCLC). The goal of this study was to determine the imaging features of the primary tumor and metastatic patterns in advanced ALK-rearranged (ALK+) NSCLC that may be different from those in EGFR-mutant (EGFR+) or EGFR/ALK wild-type (EGFR-/ALK-) NSCLC. MATERIALS AND METHODS. Patients with advanced ALK+, EGFR+, or EGFR-/ALK- NSCLC were retrospectively identified. Two radiologists concurrently assessed the imaging features of the primary tumor and the distribution of metastases in these patients. RESULTS. We identified a cohort of 333 patients with metastatic NSCLC (119 ALK+ cases, 116 EGFR+ cases, and 98 EGFR-/ALK- cases). Compared with EGFR+ and EGFR-/ALK- NSCLC, the primary tumor in ALK+ NSCLC was more likely to be located in the lower lobes (53% of ALK+, 34% of EGFR+, and 36% of EGFR-/ALK- tumors; p < 0.05), less likely to be subsolid (1% of ALK+, 11% of EGFR+, and 8% of EGFR-/ALK- tumors; p < 0.02), and less likely to have air bronchograms (7% of ALK+, 28% of EGFR+, and 29% of EGFR-/ALK- tumors; p < 0.01). Compared with EGFR+ and EGFR-/ALK- tumors, ALK+ tumors had higher frequencies of distant nodal metastasis (20% of ALK+ tumors vs 2% of EGFR+ and 9% of EGFR-/ALK- tumors; p < 0.05) and lymphangitic carcinomatosis (37% of ALK+ tumors vs 12% of EGFR+ and 12% of EGFR-/ALK- tumors; p < 0.01), but ALK+ tumors had a lower frequency of brain metastasis compared with EGFR+ tumors (24% vs 41%; p = 0.01). Although there was no statistically significant difference in the frequencies of bone metastasis among the three groups, sclerotic bone metastases were more common in the ALK+ tumors (22% vs 7% of EGFR+ tumors and 6% of EGFR-/ALK- tumors; p < 0.01). CONCLUSION. Advanced ALK+ NSCLC has primary tumor imaging features and patterns of metastasis that are different from those of EGFR+ or EGFR-/ALK- wild type NSCLC at the time of initial presentation.

Poor survival of non-small-cell lung cancer patients with main bronchus tumor: a large population-based study

Aim: In this study, we evaluated the association between tumor location and prognosis in non-small-cell lung cancer patients. Patients & methods: The SEER database was used to screen for suitable patients using our inclusion criteria. The χ2 test was used to compare baseline patient characteristics and the Kaplan–Meier method as well as the log-rank test were used to compare survival differences. At last, univariate and multivariate Cox proportional hazards regression models were used to analyze the influence of different variables on overall survival. Results: The results found no significant difference in overall survival between patients in laterality (p = 0.071). However, patients with main bronchial tumors had worse prognosis than tumors at other locations (p < 0.001). Our results also showed that tumor location including main bronchus, upper lobe, middle lobe, lower lobe and overlapping lesion was a significant factor affecting survival (p < 0.001). Subgroup analysis revealed that regardless of histology or M stage, patients with main bronchial tumors had a worse survival compared with other tumor locations (all; p < 0.001). Interestingly, we found that patients with tumor main bronchial tumors were more likely to be squamous carcinoma and terminal Tumor, Node, Metastasis stage (all; p < 0.001). Conclusion: Non-small-cell lung cancer patients’ prognosis was related to the tumor location. And patients with tumors located in main bronchus had worse outcomes than those located in other locations. Tumor primary site should be considered in treatment management and prognosis assessment.