Metastasis In Lung Cancer Patients Research Articles

Gastric Metastasis of Primary Lung Cancer: Case Report and Systematic Review With Pooled Analysis

BackgroundGastric metastasis from lung cancer (GMLC) is a rare occurrence. The clinicopathological characteristics, outcomes, and prognostic factors remain largely elusive.MethodsWe conducted a systematic review on case reports and case series of GMLC by scanning MEDLINE, Embase, and ISI Web of Knowledge. Data involving the clinicopathological features, treatment, and outcomes were extracted and analyzed. Survival analysis was performed using Kaplan–Meier method. The Cox proportional hazards regression model was used to identify potential prognostic factors associated with survival. Furthermore, a case of metastatic gastric adenocarcinoma of pulmonary origin with epidermal growth factor receptor (EGFR) L858R+T790M mutation was also described and included.ResultsSeventy-eight records involving 114 cases (including ours) were finally included. The median age on admission was 65 years with a male predominance of 79.8%. Lung adenocarcinoma (42.1%), located in the right upper lobe (30.3%), was the most frequent primary tumor. Bleeding (36.7%) and abdominal pain (35.8%) were the two most common symptoms. Endoscopically, gastric lesions were typically presented as elevated lesions with or without volcano-like ulceration, or ulcerative lesions, mostly involving the gastric corpus. The median overall survival time and survival time after diagnosis of metastatic cancer were 11 months [95% confidence interval (CI): 7–14] and 4.5 months (95% CI: 3–9), respectively. The survival analyses revealed that surgical interventions (including lung surgery and/or abdominal surgery) and systemic therapy (including chemotherapy, radiotherapy, and/or targeted therapy) seemed to be positive prognostic factors for both overall survival and survival after diagnosis of metastatic cancer.ConclusionsClinicians should be alerted to the occurrence of gastric metastasis in lung cancer patients. Comprehensive evaluation and appropriate treatment for specific patients may improve the survival rate of GMLC patients.

WITHDRAWN: Proteomic analysis of plasma-derived exosomes identifies biomarkers that distinguish brain and liver metastasis in lung cancer patients

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Machine Learning for the Prediction of Synchronous Organ-Specific Metastasis in Patients With Lung Cancer.

BackgroundThis study aimed to develop an artificial neural network (ANN) model for predicting synchronous organ-specific metastasis in lung cancer (LC) patients.MethodsA total of 62,151 patients who diagnosed as LC without data missing between 2010 and 2015 were identified from Surveillance, Epidemiology, and End Results (SEER) program. The ANN model was trained and tested on an 75/25 split of the dataset. The receiver operating characteristic (ROC) curves, area under the curve (AUC) and sensitivity were used to evaluate and compare the ANN model with the random forest model.ResultsFor distant metastasis in the whole cohort, the ANN model had metrics AUC = 0.759, accuracy = 0.669, sensitivity = 0.906, and specificity = 0.613, which was better than the random forest model. For organ-specific metastasis in the cohort with distant metastasis, the sensitivity in bone metastasis, brain metastasis and liver metastasis were 0.913, 0.906 and 0.925, respectively. The most important variable was separate tumor nodules with 100% importance. The second important variable was visceral pleural invasion for distant metastasis, while histology for organ-specific metastasis.ConclusionsOur study developed a “two-step” ANN model for predicting synchronous organ-specific metastasis in LC patients. This ANN model may provide clinicians with more personalized clinical decisions, contribute to rationalize metastasis screening, and reduce the burden on patients and the health care system.

One-step nucleic acid amplification for intraoperative diagnosis of lymph node metastasis in lung cancer patients: a single-center prospective study

One-step nucleic acid amplification (OSNA) is a rapid intraoperative molecular detection technique for sentinel node assessment via the quantitative measurement of target cytokeratin 19 (CK19) mRNA to determine the presence of metastasis. It has been validated in breast cancer but its application in lung cancer has not been adequately investigated. 214 LNs from 105 patients with 100 primary lung cancers, 2 occult primary lung tumors, and 3 metastatic lung tumors, who underwent surgical lung resection with LN dissection between February 2018 and January 2020, were assessed. Resected LNs were divided into two parts: one was snap-frozen for OSNA and the other underwent rapidly frozen histological examination. Intraoperatively collected LNs were evaluated by OSNA using loop-mediated isothermal amplification and compared with intraoperative pathological diagnosis as a control. Among 214 LNs, 14 were detected as positive by OSNA, and 11 were positive by both OSNA and intraoperative pathological diagnosis. The sensitivity and specificity of OSNA was 84.6% and 98.5%, respectively. The results of 5 of 214 LNs were discordant, and the remainder all matched (11 positive and 198 negative) with a concordance rate of 97.7%. Although the analysis of public mRNA expression data from cBioPortal showed that CK19 expression varies greatly depending on the cancer type and histological subtype, the results of the five cases, except for primary lung cancer, were consistent. OSNA provides sufficient diagnostic accuracy and speed and can be applied to the intraoperative diagnosis of LN metastasis for non-small cell lung cancer.

Bone metastases in non-small cell lung cancer: a narrative review.

Background and ObjectiveBone metastases are common in patients with non-small cell lung cancer (NSCLC) and remain a significant source of morbidity, mortality, and diminished quality of life, despite the considerable progress made in the overall management of patients with metastatic NSCLC over the last decade. Understanding the molecular pathogenesis of bone metastases is critical to improving survival, preserving function, and managing symptoms in this patient population. The objective of our review is to provide a comprehensive review of the pathophysiology, clinical presentation, management, and factors predicting the development and prognosis of patients with NSCLC with bone metastases.MethodsAn online electronic search was performed on PubMed and Google Scholar of all English-language literature using combinations of the following keywords: bone metastases, non-small cell lung cancer, pathophysiology, skeletal related events, response to therapy, predictive factors, and immunotherapy. Bibliographies of identified papers were reviewed for additional articles of interest. Observational cohort, retrospective studies, randomized controlled trials (RCTs), meta-analyses, and review articles were examined for this review.Key Content and FindingsBone metastases in lung cancer patients remain a common occurrence, impacting morbidity, mortality, and quality of life. Patients with skeletal related events (SREs) have worse prognosis. There is data supporting use of bisphosphonates and/or denosumab, and these should be considered in all patients with bone metastases. Novel studies comparing the genomic alterations of skeletal metastases and primary tumors are needed. As therapy for patients with advanced disease evolves, more studies are needed to evaluate the interplay between immunotherapy and bone metastases, and in determining the response to treatment in bone.ConclusionsPredicting development and progression of bone metastases could allow earlier and targeted therapy in patients with bone metastases. Predicting and evaluating response to conventional chemotherapy and immune checkpoint inhibitors in NSCLC patients with bone metastases remains an unmet need and merits further study.

Analysis of risk factors and gene mutation characteristics of different metastatic sites of lung cancer.

Risk factors vary in terms of the pattern of lung cancer metastasis and specific metastatic organs. In this study, we retrospectively analyzed the clinical risk factors of tumor metastasis in lung cancer patients and used second‐generation gene sequencing to characterize relevant gene mutations. The risk factors of different metastatic sites of real‐world lung cancer were explored to find the differentially expressed genes and risk factors in different metastatic organs, which laid a foundation for further study on the metastasis patterns and mechanisms of lung cancer. The clinical risk factors of tumor metastasis in 137 lung cancer patients who attended our department from May 2017 to March 2019 were retrospectively analyzed and grouped based on bone metastasis, brain metastasis, other distant metastasis, and no metastasis. Single‐ or multi‐factor logistic regression analysis was performed to analyze the effect of neutrophil/lymphocyte ratio/platelet/lymphocyte ratio/lymphocyte to monocyte ratio on platelets (PLTs) and bone metastasis by combining PLT values, age, pathology type, gender, and smoking history. Based on the presence or absence of bone metastasis, distal metastasis, and PLT values of lung cancer, 39 tissue specimens of primary lung cancer were taken for 773 gene grouping and gene mutation characterization. The tumor mutation load, gene copy number instability, microsatellite instability, and tumor heterogeneity among different groups were analyzed. Age and PLT level were independent risk factors for bone metastasis and distal metastasis, but not for brain metastasis. The RB1 gene was mutated during bone metastasis, and tumor heterogeneity was less in the elevated PLT group. PLT values were an independent risk factor for distant metastases from lung cancer other than the brain. Age has a significant effect on bone metastasis formation. RB1 gene mutation was significantly associated with bone metastasis.

Ultrasound predictors of left adrenal metastasis in patients with lung cancer: a comparison of computed tomography, positron emission tomography-computed tomography, and endoscopic ultrasound using ultrasound bronchoscope.

Patients with resectable lung cancer require invasive evaluation of the enlarged left adrenal gland (LAG). Few studies showed the utility of endoscopic ultrasound using ultrasound bronchoscope (EUS‑B) in LAG assessment. Moreover, little is known on the combination of computed tomography (CT), positron emission tomography-computed tomography (PET‑CT), and EUS‑B for predicting left adrenal metastasis. In this retrospective cohort study performed from 2012 to 2019, patients with left adrenal enlargement were evaluated by CT, PET‑CT, and EUS‑B, followed by complete endoscopic mediastinal staging. The adrenal glands were sampled by EUS‑B-guided fine‑needle aspiration. Patients were followed for 6 months. During the staging of lung cancer in 2176 patients, 113 enlarged LAGs (5.19%) were biopsied. Malignancy was reported in 51 LAGs (45.13%). Endoscopic ultrasound upstaged 7 patients (6.2%) and downstaged 11 patients (9.37%) after false CT or PET‑CT findings. There were no biopsy‑related complications. Radiologic predictors of left adrenal metastases had the highest yield at the following cutoff points: Hounsfield units >23, standardized uptake value >4.2, and LAG size >25 mm. Hypoechogenic LAGs with loss of sea‑gull shape on EUS‑B were associated with a 28.67‑fold higher likelihood of metastases. The sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for all ultrasound predictors were 86.21%, 85.45%, 85.84%, 85.45%, and 86.21%, respectively. When combined with radiologic features, the respective values were 93.10%, 94.55%, 93.81%, 92.86%, and 94.74%. Hypoechogenicity and loss of sea‑gull shape on EUS‑B are the most reliable predictors of left adrenal metastasis. The combination of CT, PET‑CT, and EUS‑B improves the noninvasive diagnosis of left adrenal metastases in lung cancer patients.

P40.10 Brain Metastases in Patients With Non-Small Cell Lung Cancer Treated With Immunotherapy. Real World Data From a Tertiary Hospital in Spain

The metastatic involvement of the central nervous system (CNS) has been traditionally related with an ominous prognosis in non-small cell lung cancer (NSCLC). Immunotherapy (IO) has (dramatically changed) revolutionized the treatment of non-oncogene addicted NSCLC but its tumour effectivity in the CNS has not been well established. The aim of this study is to identify if CNS metastases in lung cancer patients continue to be a major problem and a major cause of mortality in patients treated with IO. We performed a retrospective, observational and comparative study. We collected information regarding clinical factors, treatment, CNS involvement and outcomes from 185 patients with metastatic NSCLC treated with immunotherapy in Hospital Universitario Puerta de Hierro Majadahonda between March, 2014 and March, 2020. We performed a statistical analysis in order to exclude significant differences between both groups. We compared outcomes from patients with and without brain metastasis. 22.2% of patients had brain metastasis (CNS involvement) at diagnosis or during the course of the disease. No significant differences were found between groups regarding sex, age, histology, PD-L1, IO line, type of IO and performance status (PS). No significant differences in survival (p = 0.437) nor in the presence of long-term survivors (p = 0.723 for 2 years or more) were found. Comparative data from both groups are shown in Table-1. Specific data from patients with CNS metastases are in Table-2.Table-1Comparative dataWithout CNS metastases (N=144)With CNS metastases (N=41)PSexM: 45 (31.3%) F: 99 (68.8%)M: 19 (46.3%) F: 22 (53.7%)0.073Age (median, years; range)64.0 (40.0-82.0)58.0 (44.0-78.0)0.114HistologyAdenocarcinoma: 87 (60.4%)Squamous cell carcinoma: 42 (29.2%)Carcinoma NOS: 15 (10.4%)Adenocarcinoma: 31 (75.6%)Squamous cell carcinoma: 7 (17.1%)Carcinoma NOS: 3 (7.3%)0.199PD-L1 (median)60.055.00.638ECOG PS0-1: 134 (93.1%) 2 or more: 6 (4.1%) Unknown: 4 (2.7%)0-1: 37 (90.2%) 2 or more: 2 (4.9%) Unknown: 2 (4.9%)0.170IO line1: 41 (28.5%) 2: 50 (34.7%) Subsequent: 53 (36.8%)1: 9 (22.0%) 2: 16 (39.0%) Subsequent: 16 (9.0%)0.553Type of IOImmunotherapy: 122 (84.7%)Chemoimmunotherapy: 15 (14.9%) IO + TKI: 7 (4.9%)Immunotherapy: 35 (85.4%)Chemoimmunotherapy: 5 (12.2%) IO + TKI: 1 (2.4%)0.768Overall survival, months (median, CI 95%)Global: 16.0 (7.7-24.3) 1 line: 18.0 (7.5-28.5) 2 line: 21.0 (7.0-35.0) Subsequent lines: 8.0 (4.3-11.7)Global: 15.0 (10.3-19.7) 1 line: 19.0 (11.7-26.3) 2 line: 20.0 (0.0-43.7) Subsequent lines: 6.0 (0.1-11.9)0.437 0.860 0.342 0.706Long-term survivors2 years or more: 28 (19.4%) 3 years or more: 8 (5.6%)5 years or more: 4 (2.8%)2 years or more: 9 (22.0%) 3 years or more: 4 (9.8%)5 years or more: 2 (4.9%)0.723 0.335 0.503 Open table in a new tab Table-2Specific data from patients with brain metastasesBrain metastases before starting IO treatment20 (50.0%)Number of radiological metastases1-2: 17 (41.5%)3-10: 9 (22.0%) More than 10: 12 (29.3%) Unknown: 3 (7.30%)Meningeal carcinomatosis3 (7.5%)Local treatmentsSurgery: 3 (7.5%) Whole brain radiotherapy (WBRT): 24 (60.0%) Radiosurgery: 13 (32.5%)Radiation necrosis1 (2.5%)Best CNS responseProgressive disease: 13 (31.7%) Stable disease: 5 (12.2%) Partial response: 16 (39.0%) Complete response: 2 (4.9%) Unknown: 5 (12.2%) Open table in a new tab In our study, no significant differences were found in survival nor in the number of long-term survivors in the group of patients with brain metastases. The activity of immunotherapy on the central nervous system still needs to be defined and the impact on the outcomes of this subgroup of patients requires further investigation.

Immunotherapy in Non-Small Cell Lung Cancer Patients with Brain Metastases: Clinical Challenges and Future Directions.

Simple SummaryAlthough brain metastasis is a common and serious complication in lung cancers, current therapies with surgery, radiation, and traditional systemic agents are insufficient. Recently, immunotherapy has been shown to be effective against brain metastases in lung cancers, paving the way for a newer generation of systemic therapies. This review attempts to summarize our current understanding of immunotherapy in lung cancer brain metastases and explores future directions for research.Immune checkpoint inhibitors have revolutionized the treatment landscape for patients with non-small cell lung cancers. Existing treatment paradigms for brain metastases in lung cancer patients leave patients with adverse neurocognitive function, poor quality of life, and dismal prognosis, thus highlighting the need to develop more effective systemic therapies. Although data are limited, emerging knowledge suggests promising activity and safety of immune checkpoint inhibitors in brain metastases in non-small cell lung cancer patients. This review aims to summarize the current data, highlight the challenges of incorporating immune checkpoint inhibitors in treating these patients, and identify areas for future research.

Development and validation of tumor-to-blood based nomograms for preoperative prediction of lymph node metastasis in lung cancer.

BackgroundTo develop and validate tumor‐to‐blood based nomograms for preoperative prediction of lymph node (LN) metastasis in patients with lung cancer (LC).MethodsA prediction model was developed in a primary cohort comprising 330 LN stations from patients with pathologically confirmed LC, these data having been gathered from January 2016 to June 2019. Tumor‐to‐blood variables of LNs were calculated from positron emission tomography‐computed tomography (PET‐CT) images of LC and the short axis diameters of LNs were measured on CT images. Tumor‐to‐blood variables, number of stations suspected of harboring LN metastasis according to PET, and independent clinicopathological risk factors were included in the final nomograms. After being internally validated, the nomograms were used to assess an independent validation cohort containing 101 consecutive LN stations accumulated from July 2019 to March 2020.ResultsFour tumor‐to‐blood variables (left atrium, inferior vena cava, liver, and aortic arch) and the maximum standardized uptake value (SUVmax) for LNs were found to be significantly associated with LN status (p < 0.001 for both primary and validation cohorts). Five predictive nomograms were built. Of these, one with LN SUVmax/left atrium SUVmax was found to be optimal for predicting LN status with AUC 0.830 (95% confidence interval [CI]: 0.774–0.886) in the primary cohort and AUC 0.865 (95% CI: 0.782–0.948) in the validation cohort. All models showed good discrimination, with a modest C‐index, and good calibration in both primary and validation cohorts.ConclusionsWe have developed tumor‐to‐blood based nomograms that incorporate identified clinicopathological risk factors and facilitate preoperative prediction of LN metastasis in LC patients.

PDS5B inhibits cell proliferation, migration, and invasion via upregulation of LATS1 in lung cancer cells

PDS5B (precocious dissociation of sisters 5B) plays a pivotal role in carcinogenesis and progression. However, the biological functions of PDS5B in lung cancer and its underlying mechanisms are not fully elucidated. In the present study, we used MTT assays, wound-healing assays, and transwell migration and invasion approach to examine the cell viability, migration, and invasion of non-small cell lung cancer (NSCLC) cells after PDS5B modulation. Moreover, we investigated the function of PDS5B overexpression in vivo. Furthermore, we detected the expression of PDS5B in tissue samples of lung cancer patients by immunohistochemical study. We found that upregulation of PDS5B repressed cell viability, migration, and invasion in NSCLC cells, whereas downregulation of PDS5B had the opposite effects. We also observed that PDS5B overexpression retarded tumor growth in nude mice. Notably, PDS5B positively regulated LATS1 expression in NSCLC cells. Strikingly, low expression of PDS5B was associated with lymph node metastasis in lung cancer patients. Our findings suggest that PDS5B might be a therapeutic target for lung cancer.

Dual-Energy Computed Tomography for the Diagnosis of Mediastinal Lymph Node Metastasis in Lung Cancer Patients: A Preliminary Study.

This study explored the feasibility of dual-energy computed tomography (DECT) for the diagnosis of mediastinal lymph node (LN) metastasis in patients with lung cancer. Forty-two consecutive patients with lung cancer, who underwent DECT, were included in this retrospective study. The attenuation value (Hounsfield unit) in virtual monochromatic images and the iodine concentration in the iodine map were measured at mediastinal LNs. The slope of the spectral attenuation curve (K) and normalized iodine concentration (in thoracic aorta) were calculated. The measurement results were statistically compared using 2 independent samples t test. Receiver operating characteristic curve analysis, net reclassification improvement, and integrated discrimination improvement were used to evaluate the diagnostic performance of DECT for mediastinal LN metastasis. A total of 74 mediastinal LNs were obtained, including 33 metastatic LNs and 41 nonmetastatic LNs. The attenuation value at the lower energy levels of virtual monochromatic images (40-90 keV), K, and normalized iodine concentration demonstrated a significant difference between metastatic LNs and nonmetastatic LNs. The attenuation value at 40 keV was the most favorable biomarker for the diagnosis of mediastinal LN metastasis (area under curve, 0.91; sensitivity, 0.94; specificity, 0.81), which showed a much better performance than the LN diameter-based evaluation method (area under curve, 0.72; sensitivity, 0.66; specificity, 0.82; net reclassification improvement, 0.359; integrated discrimination improvement, 0.330). Dual-energy computed tomography is a promising diagnostic approach for the diagnosis of mediastinal LN metastasis in patients with lung cancer, which may help clinicians implement personalized treatment strategies.

Management of brain metastases from lung cancer in the era of immunotherapy: a review of the literature.

The brain is one of the most frequent sites of metastases in lung cancer patients, whose prognosis is related to the histological, biomolecular and clinical features of the disease. Over the years, the survival hasimproved significantly with the introduction of immune checkpoint inhibitors (ICIs), but there are limited data concerning their efficacy in patients with brain metastases. The aim of this review is to describe the biological mechanisms supporting the use of immunotherapy for brain metastases and the outcomes experienced by lung cancer patients with brain involvement enrolled in Phase III registration trials of ICIs. We also reviewretrospective data on ICIs alone or combined with brain radiotherapy, and indicate future directions for preclinical and clinical research.

Characteristics of gastrointestinal metastasis in lung cancer: Single-center experience from Eastern India

Background: Lung cancer is one of the most common cancers associated with a poor prognosis. Gastrointestinal (GI) metastasis among lung cancer patients is often misdiagnosed or missed as a diagnosis. With a paucity of literature on this theme, we conducted a study to understand the clinicopathological characteristics of GI metastasis in lung cancer patients. Materials and Methods: A retrospective review of 793 primary lung cancer patients registered from January 2018 to December 2018 was done at a tertiary cancer hospital. The present study focused on lung cancer patients with an objective to find out the cases of GI metastasis. GI metastasis was confirmed on radiological imaging in the records and positron emission tomography, magnetic resonance imaging, or computed tomography scans. Quantitative variables were either expressed in terms of mean and standard deviation or categorized and expressed in percentages. Pearson's correlation coefficient was used to find the correlation between different symptom clusters in patients with GI metastasis in lung cancer. Results: Of the 793 lung cancer patients, 31 (3.9%) patients had metastasis to the GI tract, with as high as 70.97% (22/31) patients presenting with peritoneal/omental deposits. Of the 31 patients with GI metastasis, five (16.13%) patients were symptomatic, four patients had intestinal obstruction, and one had intestinal perforation. Due to advanced metastatic cancer and poor performance status, patients were provided palliative care and symptom management as they were deemed unfit for surgical intervention. Conclusion: With the advent of targeted and immunological therapies, patients with metastatic lung cancers are surviving longer. Palliative care specialists must work in close collaboration with oncologists to identify an impending GI complication at an early stage to direct specific interventions to avert the complication.

The construction and validation of the model for predicting the incidence and prognosis of brain metastasis in lung cancer patients.

BackgroundBrain metastasis (BM) causes high morbidity and mortality rates in lung cancer (LC) patients. The present study aims to develop models for predicting the development and prognosis of BM using a large LC cohort.MethodsA total of 266,522 LC cases diagnosed between 2010 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program cohort. Risk factors for developing BM and prognosis were calculated by univariable and multivariable logistic and Cox regression analysis, respectively, and nomograms were constructed based on risk factors. Nomogram performance was evaluated with receiver operating characteristics (ROC) curve, or C-index and calibration curve.ResultsThe prevalence of BM was 13.33%. Associated factors for developing BM include: advanced age; Asian or Pacific Islander race; uninsured status; primary tumor site; higher T stage; higher N stage; poorly differentiated grade; the presence of lung, liver, and bone metastases; and adenocarcinoma histology. Median overall survival (OS) was 4 months; associated prognosis factors were similar to risk factors plus female gender, unmarried status, and surgery. The calibration curve showed good agreement between predicted and actual probability, and the AUC/C-index was 73.1% (95% CI: 72.6–73.6%) and 0.88 (95% CI: 0.87–0.89) for risk and prognosis predictive models, respectively.ConclusionsBM was highly developed in LC patients, and homogeneous and heterogeneous factors were found between risk and prognosis for BM. The nomogram showed good performance in predicting BM development and prognosis.

Influence of CMTM8 polymorphisms on lung cancer susceptibility in the Chinese Han population.

Lung cancer is the leading cause of cancer-related mortality worldwide and CMTM8 is a potential tumor suppressor gene, which is down-regulated in lung cancer. The objective of this research was to assess the association of CMTM8 genetic polymorphisms with lung cancer risk. To evaluate the correlation between CMTM8 polymorphisms and lung cancer risk, Agena MassArray platform was used for genotype determination among 509 lung cancer patients and 506 controls. Multiple genetic models, stratification analysis and Haploview analysis were used by calculating odds ratio (OR) and 95% confidence intervals (CIs). Significant associations were detected between CMTM8 rs6771238 and an increased lung cancer risk in codominant (adjusted OR = 1.57, 95% CI: 1.01-2.42, P = 0.044) and dominant (adjusted OR = 1.54, 95% CI: 1.01-2.36, P = 0.047) models. After sex stratification analysis, we observed that rs6771238 was related to an increased risk of lung squamous cell carcinoma, while rs6771238 was associated with an increased risk of lung adenocarcinoma. Rs9835916 was linked to increased risk of lymph node metastasis in lung cancer patients. Our study first reported that CMTM8 polymorphisms were a risk factor for lung cancer, which suggested the potential roles of CMTM8 in the development of lung cancer.

Comparative genomic analysis of primary tumors and paired brain metastases in lung cancer patients by whole exome sequencing: a pilot study.

Lung cancer brain metastases (BMs) are frequent and associated with poor prognosis despite a better knowledge of lung cancer biology and the development of targeted therapies. The inconstant intracranial response to systemic treatments is partially due to tumor heterogeneity between the primary lung tumor (PLT) and BMs. There is therefore a need for a better understanding of lung cancer BMs biology to improve treatment strategies for these patients. We conducted a study of whole exome sequencing of paired BM and PLT samples. The number of somatic variants and chromosomal alterations was higher in BM samples. We identified recurrent mutations in BMs not found in PLT. Phylogenic trees and lollipop plots were designed to describe their functional impact. Among the 13 genes mutated in ≥ 1 BM, 7 were previously described to be associated with invasion process, including 3 with recurrent mutations in functional domains which may be future targets for therapy. We provide with some insights about the mechanisms leading to BMs. We found recurrent mutations in BM samples in 13 genes. Among these genes, 7 were previously described to be associated with cancer and 3 of them (CCDC178, RUNX1T1, MUC2) were described to be associated with the metastatic process.

Pharmacological blockage of transforming growth factor-\u03b2 signalling by a Traf2- and Nck-interacting kinase inhibitor, NCB-0846

BackgroundMetastasis is the primary cause of death in cancer patients, and its management is still a major challenge. Epithelial to mesenchymal transition (EMT) has been implicated in the process of cancer metastasis, and its pharmacological interference holds therapeutic promise.MethodsTraf2- and Nck-interacting kinase (TNIK) functions as a transcriptional coregulator of Wnt target genes. Given the convergence of Wnt and transforming growth factor-β (TGFβ) signalling, we examined the effects of a small-molecule TNIK inhibitor (named NCB-0846) on the TGFβ1-induced EMT of lung cancer cells.ResultsNCB-0846 inhibited the TGFβ1-induced EMT of A549 cells. This inhibition was associated with inhibition of Sma- and Mad-Related Protein-2/3 (SMAD2/3) phosphorylation and nuclear translocation. NCB-0846 abolished the lung metastasis of TGFβ1-treated A549 cells injected into the tail veins of immunodeficient mice. The inhibition of EMT was mediated by suppression of the TGFβ receptor type-I (TGFBR1) gene, at least partly through the induction of microRNAs targeting the TGFBR1 transcript [miR-320 (a, b and d) and miR-186].ConclusionsNCB-0846 pharmacologically blocks the TGFβ/SMAD signalling and EMT induction of lung cancer cells by transcriptionally downregulating TGFBRI expression, representing a potentially promising approach for prevention of metastasis in lung cancer patients.

F-18 fluorodeoxyglucose uptake in lymph nodes and sonographic features on endobronchial ultrasonography predict lymph node metastasis in lung cancer patients.

BackgroundSonographic findings of lymph nodes on endobronchial ultrasonography (EBUS) images have been reported to be useful to predict lymph node metastasis (LNM) in lung cancer patients. F-18 fluorodeoxyglucose (FDG) uptake in lymph nodes was also found to be useful. In this study, we aimed to clarify whether a combination of sonographic features and maximum standardized uptake values of lymph nodes (LN-SUVmax) is useful for predicting LNM in lung cancer patients.MethodsFrom January 2014 to December 2019, a total of 147 lymph nodes from 104 patients with lung cancer, who underwent preoperative EBUS and FDG-positron emission tomography (PET)/computed tomography (CT) followed by surgery were retrospectively assesses. The characteristics of the patients, LN-SUVmax, and sonographic findings of lymph nodes were reviewed. Predictive factors associated with LNM were identified using the logistic regression model.ResultsThe average size of the lymph nodes was 8.55 (range, 3–22) mm and the average LN-SUVmax was 5.36 (range, 1.79–31.19). The prevalence of nodal metastasis was 26/147 (17.4%), including 22 in mediastinal lymph nodes and 4 in hilar lymph nodes. Multivariate analysis demonstrated four independent predictive factors for LNM; size, round or oval shape, absence of a central hilar structure, and LN-SUVmax. The optimal cutoff value for lymph node size and LN-SUVmax were 10 mm and 6.00, respectively. By combinating of the two modalities, we obtained the results with sensitivity of 76.9%, specificity of 95.1% and accuracy of 93.2%.ConclusionsA combination of sonographic findings and LN-SUVmax showed a higher diagnostic rate of LNM than either modality alone in lung cancer patients.

Expression of CMTM4 shows clinical significance in lung cancer.

BackgroundHuman chemokine-like factor (CKLF)-like MARVEL transmembrane domain-containing family (CMTM) is implicated in the pathogenesis of immune, reproductive systems and various cancers. However, the expression and clinical significance of CMTM4 in lung cancer have not been identified.MethodsWe performed immunohistochemistry to detect the expression of CMTM4 in 75 paired lung adenocarcinoma and non-tumor lung tissues. The correlation between CMTM4 expression and clinical significance of lung cancer patients was analyzed by Chi-square test. Kaplan-Meier method and Log-Rank test were used to calculate the survival time of lung cancer patients.ResultsWe found that CMTM4 was positively expressed in 34/75 (45.3%) cases of lung adenocarcinoma tissues, while positively expressed in 59/75 (78.6%) cases of non-tumor lung tissues, suggesting a lower expression of CMTM4 in lung adenocarcinoma tissues than non-tumor lung tissues (P<0.05). In addition, the negative expression of CMTM4 was associated with gender, smoking, and metastasis in lung cancer patients. Moreover, lung cancer patients with negative expression of CMTM4 had a shorter survival time than the patients with positive expression of CMTM4. COX regression analysis showed that CMTM4 was an independent prognostic factor for the overall survival of lung cancer patients.ConclusionsOur study supports that CMTM4 can be used as a new marker for the treatment and prognosis of lung cancer.