Early-stage Lung Cancer Patients Research Articles

Non-invasive Detection of Exosomal MicroRNAs via Tethered Cationic Lipoplex Nanoparticles (tCLN) Biochip for Lung Cancer Early Detection.

Circulating microRNAs carried by exosomes have emerged as promising diagnostic biomarkers for cancer because of their abundant amount and remarkable stability in body fluids. Exosomal microRNAs in blood are typically quantified using the RNA isolation-qRT-PCR workflow, which cannot distinguish circulating microRNAs secreted by cancer cells from those released by non-tumor cells, making it potentially less sensitive in detecting cancer-specific microRNA biomarkers. We have developed a sensitive and simple tethered cationic lipoplex nanoparticles (tCLN) biochip to detect exosomal microRNAs in human sera. The tCLN biochip allows the discrimination of tumor-derived exosomes from their non-tumor counterparts, and thus achieves higher detection sensitivity and specificity than qRT-PCR. We have demonstrated the clinical utility of the tCLN biochip in lung cancer diagnosis using sera from normal controls, therapy-naive early stage and late stage non-small cell lung cancer (NSCLC) patients. Total five microRNAs (miR-21, miR-25, miR-155, miR-210, and miR-486) were selected as the biomarkers. Each microRNA biomarker measured by tCLN assay showed higher sensitivity and specificity in lung cancer detection than that measured by qRT-PCR. When all five microRNAs were combined, the tCLN assay distinguished normal controls from all NSCLC patients with sensitivity of 0.969, specificity of 0.933 and AUC of 0.970, and provided much better diagnostic accuracy than qRT-PCR (sensitivity = 0.469, specificity = 1.000, AUC = 0.791). Remarkably, the tCLN assay achieved absolute sensitivity and specificity in discriminating early stage NSCLC patients from normal controls, demonstrating its great potential as a liquid biopsy assay for lung cancer early detection.

Integration of IgA and IgG Autoantigens Improves Performance of Biomarker Panels for Early Diagnosis of Lung Cancer

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

Circulating Tumor Cells as a Biomarker to Assist Molecular Diagnosis for Early Stage Non-Small Cell Lung Cancer.

Background and ObjectiveCompared with tissue biopsy, liquid biopsy is the most preferable non-invasive promising method in personalized medicine, although it has many limitations in isolating circulating tumor cells (CTC). Lung cancer associated mortality is drastically increased due to a shortfall of early-stage detection, which remains a challenge. Herein, we aimed to detect lung cancer at an early-stage using CellCollector device.Methods39,627 volunteers underwent low-dose computed tomography; 2508 cases with pulmonary nodules and 7080 with no pulmonary nodules were chosen. After follow-up, 24 patients were diagnosed with early-stage non-small cell lung cancer (NSCLC), and subjected to CTC detection using CellCollector, along with 72 healthy volunteers. Immunofluorescence staining for EpCAM/CKs and CD45 were performed for CTC validation.ResultsFifteen out of twenty-four (stage I, n = 18; stage II, n = 6) early-stage lung cancer patients were found to be CTC-positive, whereas no CTC was found in the control group. Genetic mutation of TP53, ERBB2, PDGFRA, CFS1R and FGFR1 in the CTC revealed 71.6% of the mutation sites similar to the tumor tissues of 13 patients. Molecular characterization revealed higher expression of protein PD-LI in CTC (40%) as compared to tumor tissue (26.7%). Moreover, CTC clusters were detected in 40% of patients.ConclusionCTC detection using the CellCollector in early-stage NSCLC had a relative high capture rate. Moreover, CTC analysis is a prospective setting for molecular diagnostic in cases when tumor tissue biopsy is not desirable.

Is Thiol-Disulphide Homeostasis an Indicative Marker in Prediction of Metastasis in Lung Cancer Patients.

Thiol/disulfide (SH/SS) homeostasis plays an essential and dynamic role in our body and in various cellular activities and pathways such as cell death, regulation of enzyme activities, mechanisms of transcription and cellular signal transduction. Lung cancer is the most commonly seen cancer type in the adult population. Therefore, prediction of metastases gains importance in this population. We included 150 patients with lung cancer who attended Kirikkale University Medical Faculty Hospital between June 2017 and June 2018. Our purpose was to evaluate whether metastases can be predicted in lung cancer patients by testing SH/SS homeostasis as a novel and easily applicable biochemical test. The mean age of the patients was 63.8 ± 8.1 (41 - 71) years. Advanced stage lung cancer, adenocarcinoma, squamous-cell and small cell lung cancers, and other types were detected in 54.7%, 42.7%, 41.3%, 13.3%, and 2.7% of the patients, respectively. SS values of the patients with advanced stage lung cancer were higher than in patients with early stage lung cancer (p < 0.001). It was determined that the patients with advanced stage lung cancer had statistically significantly higher mean values of SS, SS/SH (%), and SS/total SH (%) than patients with early stage lung cancer and that a statistically significantly lower mean value of SH/total SH (%) was found in advanced stage compared with early stage lung cancer patients. No statistically significant difference was found between the patient groups with advanced and early stage lung cancer regarding mean values of native SH and total SH levels. It can be concluded that SH/SS parameters may vary in advanced and early stage lung cancer patients; however, further studies should be conducted with SH/SS parameters in order to use them as indicators of cancer severity in lung cancer patients.

Peak oxygen consumption measurement and postoperative outcome in patients with early-stage lung cancer

INTRODUCTION: In early-stage lung cancer (LC) patients, the best survival rates are achieved when the patient undergoes surgical resection. Cardiopulmonary exercise testing is an important preoperative test because of its ability to detect disturbance in the oxygen transport system, which is, in turn, related to the development of postoperative complications. OBJECTIVES: The aim of the study is to investigate the value of peak oxygen consumption (peakVO2) to determine postoperative pulmonary complications (PPCs) in LC patients with surgical resection. MATERIALS AND METHODS: LC patients who were candidates for surgery between February 2015 and 2017 were included in this prospectively conducted study. PeakVO2 measurement was performed by utilizing cycle ergometry during incremental exercise. All patients were on follow-up for PPCs for a period of 30 days postoperatively. RESULTS: The study included 41 patients (mean age: 63.9 ± 9.7 years) who had undergone surgical resection (28 lobectomies/13 pneumonectomies). There was no mortality, but 8 (19.5%) PPCs were observed. Mean peakVO2 values were not different in patients with and without PPCs. When the patients were divided into two groups based on absolute forced expiratory volume 1 second (FEV1) (≤1.5 L and >1.5 L) and ppo FEV1% (≤30% and >30%); mean peakVO2, mean stay days in intensive care unit and hospital, and PPC rates were similar between groups. Fourteen patients with FEV1≤1.5 L and 11 patients with ppo FEV1≤30% underwent successful surgical resections. CONCLUSION: PeakVO2 measurement prevents patients to be deprived of a surgical resection, which is an important treatment modality for LC. PPCs were in acceptable limits in patients with a value of peakVO2≥15 ml/kg/min.

Factores de riesgo para el desarrollo de complicaciones tras tratamiento quirúrgico del carcinoma broncopulmonar

IntroductionThe most suitable treatment in most early-stage lung cancer patients is surgical resection. Despite previously assessing each patient's status being relevant to detect possible complications inherent to surgery, no consensus has been reached on which factors are “high risk” in such patients. Our study aimed to analyse the morbidity and the mortality incidence associated with this surgery in our setting with a multicentre study and to detect risk parameters. MethodsA prospective analysis study with 3,307 patients operated for bronchopulmonary carcinoma in 24 hospitals. Study variables were age, TNM, gender, stage, smoking habit, surgery approach, surgical resection, ECOG, neoadjuvant therapy, comorbidity, spirometric values, and intraoperative and postoperative morbidity and mortality. A multivariate logistic regression analysis of the morbidity and mortality predictor factors was done. ResultsWe recorded 34.2% postoperative morbidity and 2.1% postoperative mortality. Gender, myocardial infarction, angina, ECOG ≥1, COPD, DLCO <60%, clinical pathological status, surgical resection and surgery approach were shown as morbidity and mortality predictor factors in lung cancer surgery in our series. ConclusionsThe main variables to consider when assessing the lung cancer patients to undergo surgery are gender, myocardial infarction, angina, ECOG, COPD, DLCO, clinical pathological status, surgical resection and surgery approach.

Identification of differentially expressed genes in non-small cell lung cancer.

Lung cancer is the most common malignant tumor and the leading cause of cancer-related deaths worldwide. Because current treatments for advanced non-small cell lung cancer (NSCLC), the most prevalent lung cancer histological subtype, show limited efficacy, screening for tumor-associated biomarkers using bioinformatics reflects the hope to improve early diagnosis and prognosis assessment. In our study, a Gene Expression Omnibus dataset was analyzed to identify genes with prognostic significance in NSCLC. Upon comparison with matched normal tissues, 118 differentially expressed genes (DEGs) were identified in NSCLC, and their functions were explored through bioinformatics analyses. The most significantly upregulated DEGs were TOP2A, SLC2A1, TPX2, and ASPM, all of which were significantly associated with poor overall survival (OS). Further analysis revealed that TOP2A had prognostic significance in early-stage lung cancer patients, and its expression correlated with levels of immune cell infiltration, especially dendritic cells (DCs). Our study provides a dataset of potentially prognostic NSCLC biomarkers, and highlights TOP2A as a valuable survival biomarker to improve prediction of prognosis in NSCLC.

Therapeutic effects of statins against lung adenocarcinoma via p53 mutant-mediated apoptosis

The p53 gene is an important tumour suppressor gene. Mutant p53 genes account for about half of all lung cancer cases. There is increasing evidence for the anti-tumour effects of statins via inhibition of the mevalonate pathway. We retrospectively investigated the correlation between statin use and lung cancer prognosis using the Taiwanese National Health Insurance Research Database, mainly focusing on early-stage lung cancer. This study reports the protective effects of statin use in early-stage lung cancer patients regardless of chemotherapy. Statin treatments reduced the 5-year mortality (odds ratio, 0.43; P < 0.001) in this population-based study. Significantly higher levels of cellular apoptosis, inhibited cell growth, and regulated lipid raft content were observed in mutant p53 lung cancer cells treated with simvastatin. Further, simvastatin increased the caspase-dependent apoptotic pathway, promotes mutant p53 protein degradation, and decreased motile activity in lung cancer cells with p53 missense mutations. These data suggest that statin use in selected lung cancer patients may have clinical benefits.

Role of the YAP-1 Transcriptional Target cIAP2 in the Differential Susceptibility to Chemotherapy of Non-Small-Cell Lung Cancer (NSCLC) Patients with Tumor RASSF1A Gene Methylation from the Phase 3 IFCT-0002 Trial.

RASSF1 gene methylation predicts longer disease-free survival (DFS) and overall survival (OS) in patients with early-stage non-small-cell lung cancer treated using paclitaxel-based neo-adjuvant chemotherapy compared to patients receiving a gemcitabine-based regimen, according to the randomized Phase 3 IFCT (Intergroupe Francophone de Cancérologie Thoracique)-0002 trial. To better understand these results, this study used four human bronchial epithelial cell (HBEC) models (HBEC-3, HBEC-3-RasV12, A549, and H1299) and modulated the expression of RASSF1A or YAP-1. Wound-healing, invasion, proliferation and apoptosis assays were then carried out and the expression of YAP-1 transcriptional targets was quantified using a quantitative polymerase chain reaction. This study reports herein that gemcitabine synergizes with RASSF1A, silencing to increase the IAP-2 expression, which in turn not only interferes with cell proliferation but also promotes cell migration. This contributes to the aggressive behavior of RASSF1A-depleted cells, as confirmed by a combined knockdown of IAP-2 and RASSF1A. Conversely, paclitaxel does not increase the IAP-2 expression but limits the invasiveness of RASSF1A-depleted cells, presumably by rescuing microtubule stabilization. Overall, these data provide a functional insight that supports the prognostic value of RASSF1 gene methylation on survival of early-stage lung cancer patients receiving perioperative paclitaxel-based treatment compared to gemcitabine-based treatment, identifying IAP-2 as a novel biomarker indicative of YAP-1-mediated modulation of chemo-sensitivity in lung cancer.

The diagnostic efficiency of seven autoantibodies in lung cancer.

This study aimed to evaluate the diagnostic efficacy of seven autoantibodies in all lung cancer, lung adenocarcinoma, lung squamous cell carcinoma and early-stage lung cancer patients. ELISA testing of a seven autoantibody panel was performed on 386 lung cancer patients and 238 normal controls. The sensitivity and specificity of each autoantibody were analyzed using the receiver operating characteristic curve analysis. The diagnostic efficacy of a combination of these seven autoantibodies was evaluated by binary logistic regression. The results indicated that six of the seven autoantibodies (p53, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE) had high specificity and low sensitivity, while PGP9.5 had high sensitivity and low specificity. Further analysis showed that all seven autoantibodies had better diagnostic value in lung squamous cell carcinoma patients when compared to lung adenocarcinoma or all lung cancer patients. Logistic regression showed that a combination of the seven autoantibodies resulted in more reliable detection of lung cancer than any individual autoantibody in early-stage lung cancer (sensitivity/specificity: 47.8%/81.4%, areas under the curve: 0.764, 95% confidence interval: 0.718-0.811). Additionally, this panel had a better sensitivity of 56.5% for detection of lung squamous cell carcinoma than for all lung cancer (50.1%) or adenocarcinoma (51.7%) (P < 0.05). Our results indicated that the seven autoantibody panel could be used for early lung cancer detection, and it had better sensitivity in diagnosis of lung squamous cell carcinoma.

Pretreatment 18F-FDG PET/CT Radiomics Predict Local Recurrence in Patients Treated with Stereotactic Body Radiotherapy for Early-Stage Non-Small Cell Lung Cancer: A Multicentric Study.

The aim of this retrospective multicentric study was to develop and evaluate a prognostic 18F-FDG PET/CT radiomic signature in early-stage non-small cell lung cancer patients treated with stereotactic body radiotherapy (SBRT). Methods: Patients from 3 different centers (n = 27, 29, and 8) were pooled to constitute the training set, whereas the patients from a fourth center (n = 23) were used as the testing set. The primary endpoint was local control. The primary tumor was semiautomatically delineated in the PET images using the fuzzy locally adaptive Bayesian algorithm, and manually in the low-dose CT images. In total, 184 Image Biomarkers Standardization Initiative-compliant radiomic features were extracted. Seven clinical and treatment parameters were included. We used ComBat to harmonize radiomic features extracted from the 4 institutions relying on different PET/CT scanners. In the training set, variables found significant in the univariate analysis were fed into a multivariate regression model, and models were built by combining independent prognostic factors. Results: Median follow-up was 21.1 mo (range, 1.7-63.4 mo) and 25.5 mo (range, 7.7-57.8 mo) in training and testing sets, respectively. In univariate analysis, none of the clinical variables, 2 PET features, and 2 CT features were significantly predictive of local control. The best predictive models in the training set were obtained by combining one feature from PET (Information Correlation 2) and one feature from CT (flatness), reaching a sensitivity of 100% and a specificity of 96%. Another model combining 2 PET features (Information Correlation 2 and strength) reached sensitivity of 100% and specificity of 88%, both with an undefined hazard ratio (P < 0.001). The latter model obtained an accuracy of 0.91 (sensitivity, 100%; specificity, 81%), with a hazard ratio undefined (P = 0.023) in the testing set; however, other models relying on CT radiomic features only or the combination of PET and CT features failed to validate in the testing set. Conclusion: We showed that 2 radiomic features derived from 18F-FDG PET were independently associated with local control in patients with non-small cell lung cancer undergoing SBRT and could be combined in an accurate predictive model. This model could provide local relapse-related information and could be helpful in clinical decision making.

Significance of the lobe-specific emphysema index to predict prolonged air leak after anatomical segmentectomy.

Prolonged air leak (PAL) is a major complication of pulmonary resection. Emphysema quantification with computed tomography is regarded as an important predictor of PAL for patients undergoing lobectomy. Therefore, we investigated whether this predictor might be applicable for segmentectomy. Herein, we characterized the factors that influence PAL in early stage lung cancer patients undergoing anatomical segmentectomy. Forty-one patients who underwent anatomical segmentectomy for early lung cancer between January 2014 and July 2017 were included for analysis. Several baseline and surgical variables were evaluated. In particular, the emphysema index (EI, %) and lobe-specific emphysema index (LEI, %) were assessed by using three-dimensional volumetric CT scan. PAL was observed in 13 patients (31.7%). There were statistically significant differences in DLCO (97.3% ± 18.3% vs. 111.7% ± 15.9%, p = 0.014), EI (4.61% ± 4.66% vs. 1.17% ± 1.76%, p = 0.023), and LEI (5.81% ± 5.78% vs. 0.76% ± 1.17%, p = 0.009) between patients with and without PAL. According to logistic regression analysis, both EI and LEI were significantly associated with PAL (p = 0.028 and p < 0.001, respectively). We found that EI and LEI significantly influenced the development of PAL after pulmonary resection. In particular, LEI showed stronger association with PAL, compared with EI, suggesting the importance of LEI in the prediction of PAL after anatomical segmentectomy.

Prognostic Role Of Computed Tomography Textural Features In Early-Stage Non-Small Cell Lung Cancer Patients Receiving Stereotactic Body Radiotherapy.

PurposeThe imaging features of patients with early-stage non-small cell lung cancer (NSCLC) receiving stereotactic body radiotherapy (SBRT) are crucial for the decision-making process to establish a treatment plan. The purpose of this study was to predict the clinical outcomes of SBRT from the textural features of pretreatment computed tomography (CT) images.Patients and methodsForty-one early-stage NSCLC patients who received SBRT were included in this retrospective study. In total, 72 textural features were extracted from the pretreatment contrast-enhanced CT images. Survival analysis was used to identify high-risk groups for progression-free survival (PFS) and disease-specific survival (DSS). Receiver operating characteristic (ROC) curve analysis was utilized to estimate the diagnostic abilities of the textural parameters. Univariable and multivariable Cox regression analyses were performed to evaluate the predictors of PFS and DSS.ResultsFour parameters, including entropy (P=0.003), second angular moment (SAM) (P=0.04), high-intensity long-run emphasis (HILRE) (P=0.046) and long-run emphasis (LRE) (P=0.042), were significant prognostic features for PFS. In addition, contrast (P=0.008), coarseness (P=0.017), low-intensity zone emphasis (LIZE) (P=0.01) and large number emphasis (LNE) (P=0.046) were significant prognostic factors for DSS. In the ROC analysis, the area under the curve (AUC) of coarseness for local recurrence (LR) was 0.722 (0.528–0.916), and the AUC of entropy for lymph node metastasis (LNM) was 0.771 (0.556–0.987). The four highest AUCs for distant metastasis (DM) were 0.885 (0.784–0.985) for LNE, 0.846 (0.733–0.959) for SAM, 0.731 (0.500–0.961) for LRE and 0.731 (0.585–0.876) for contrast. In the multivariable analysis, smoking and entropy were independent prognostic factors for PFS.ConclusionThis exploratory study reveals that textual features derived from pretreatment CT scans have prognostic value in early-stage NSCLC patients treated with SBRT.

Screening for fear of cancer recurrence: Instrument validation and current status in early stage lung cancer patients

Fear of cancer recurrence (FCR) is one of the most distressing concerns for cancer patients. A psychometrically validated brief scale is urgently needed for use in busy clinical oncology settings. This study aimed to (1) develop and validate the 7-item fear of cancer recurrence scale Chinese version (FCR7-C), and (2) explore the severity of FCR in post-operative early-stage lung cancer patients in Taiwan. Early-stage lung cancer patients were recruited from a medical center in Taiwan. The FCR7-C was evaluated for content and construct validity and internal consistency reliability. Construct validity of FCR7-C was determined by the empirically supported correlation and confirmatory factor analysis (CFA). A total of 160 subjects were recruited. The FCR7-C was shown to have satisfactory content validity and internal consistency reliability (Cronbach's α=0.9). The uni-dimensional structure was confirmed by CFA that showed a good fit for the model. The FCR7-C score correlates positively with the degree of most of the physical symptoms, anxiety, and depression, but correlates negatively with patient age, performance status, and quality of life. We found that 81.9% of patients reported at least some FCR, with a mean FCR severity of 15.18 (SD=7.78). FCR7-C is a brief screening tool with good psychometrics. Patients with early-stage lung cancer still revealed mild to moderate level of FCR. Applying the FCR7-C for to screen cancer patients' distress and further develop personalized psychological interventions would be strongly suggested.

Identification of Risk Factors and Likelihood of Benefit from Adjuvant Chemotherapy for Early Stage Lung Cancer Patients

ABSTRACTThe purpose of the research is to develop a statistical decision support algorithm for patients who may benefit from Adjuvant Cisplatin/Vinorelbine (ACT) and improve their survival rates. Genome-wide microarray data are used to identify feasible sets of genes and probe sets that constitute the gene signature. The data are available at the National Center for Biotechnology Information Gene Expression Omnibus (GSE14814). Preliminary studies have shown that high-risk patients who received ACT resulted in an improved prognosis. However, low-risk patients showed no benefit from ACT, and the treatment was possibly detrimental to the patient. Studies using tree-based ensemble statistical learning algorithms have shown that genomic markers could potentially identify a patient’s risk factor and likelihood to benefit from ACT; however, it was noted that tree-based ensemble statistical learning algorithms do not provide an estimate of the strength of the treatment effect, nor is it possible to clearly identify subgroups of patients with similar responses to ACT treatment. Building on this idea, Accelerated Failure Time models are used to predict the probability of benefit from receiving chemotherapy or surgery only and provide a treatment recommendation for a new patient. We showed that regardless of whether the model recommended chemotherapy or surgery only, patients who followed the predicted treatment recommendation had significantly longer survival times than patients who did not. The proposed approach provides the likelihood of benefit for each treatment based on a small number of genomic biomarkers.

Lobe-Specific Lymph Node Dissection for Clinical Early-Stage (cIA) Peripheral Non-small Cell Lung Cancer Patients: What and How?

We investigated the possible lobe-specific lymph node (LN) metastasis pattern of early-stage peripheral non-small cell lung cancers (NSCLC) and define the extent of lobe-specific LN dissection for them. We retrospectively collected clinical data of patients undergoing lobectomy or segmentectomy with systematic lymphadenectomy for clinical T1N0M0 peripheral NSCLC from January 2015 to December 2018. The LN metastasis pattern was analyzed by tumor lobe location. A total of 590 patients were included for analysis. The mean number of total dissected LNs was 12.3 ± 5.8 and 8.2 ± 4.1 for total dissected mediastinal LNs. The rate of mediastinal LN metastasis was 9.5%. For cases of upper lobe tumor and lower lobe tumor, 8.8% and 6.0% of them respectively metastasized to the upper LN zone (P = 0.274). However, upper lobe tumors hardly metastasized to the subcarinal (0.3%) and lower (0.3%) LN zones while for lower lobe tumors, the rate of LN metastasis was 10.2% and 5.4% respectively (both P < 0.001). However, all cases (100%) metastasizing from lower lobes to the upper LN zone had a tumor size of 2-3cm, whereas cases with a tumor size ≤ 2cm had no metastasis (0%). None of the tumors in the right middle lobe metastasized to the lower LN zone (0%). A lobe-specific LN metastasis pattern was observed in clinical stage IA peripheral NSCLC. For tumors in upper lobes (≤ 3cm), there may be no need to dissect lower mediastinal LNs and for tumors in lower lobes (≤ 2cm), dissecting upper mediastinal LNs may not be required.

Outpatient Anesthesia Facilitates Stereotactic Body Radiation Therapy for Early Stage Lung Cancer Patients With Advanced Cognitive Impairments

PurposeTo report on the use of outpatient anesthesia (OPA) facilitating delivery of stereotactic body radiation therapy (SBRT) in patients with severe cognitive impairments (CI) diagnosed with inoperable early stage lung cancer. Methods and MaterialsWe surveyed our institutional review board–approved prospective lung SBRT data registry to document the feasibility of using anesthesia in CI patients and to determine their SBRT outcomes. ResultsFrom 2004 to 2018, 8 from a total 2084 patients were identified for this analysis. The median age at treatment was 68 years (range, 44-78). Most patients were female (62.5%). CI diagnoses included Alzheimer-related dementia (3 patients), chronic schizophrenia (3 patients), severe anxiety disorder (1 patient), and severe developmental disability (1 patient). The median tumor size was 3.4 cm (range, 1.1-10.5), and 7 patients (87.5 %) had central lesions. The median follow-up time was 22.5 months. The most common (50%) SBRT schedule used was 50 Gy in 5 fractions. Intravenous propofol (10 mg/mL) was used for OPA in all cases at the time of simulation and with daily treatments. OPA was well tolerated and all patients completed SBRT as prescribed. There was one grade 5 but no other grade 3 or higher SBRT-related toxicities. One patient died with local failure and one of distant failure. ConclusionsOPA made lung SBRT feasible for patients with CIs. SBRT outcomes were in keeping with those reported in the literature. CI should not be considered a contraindication per se to SBRT delivery in patients otherwise appropriate for this modality.

111P - Combined genomic and epigenomic assessment of cell-free circulating tumour DNA (cfDNA) for cancer diagnosis and recurrence-risk assessment in early-stage lung cancer

BackgroundCirculating tumor DNA (ctDNA) analysis has been successfully applied to therapy selection and treatment monitoring in advanced cancer patients. However, it is not yet established whether ctDNA can be used clinically for early cancer detection or recurrence prediction in early stage lung cancer patients. MethodsWe analyzed pre-operative plasma samples from 55 early stage NSCLC patients (stages I-IIIA) using next-generation sequencing assay incorporating somatic and epigenomic analysis, and a bioinformatic classifier to filter non-tumor derived variants.Table: 111PTable: 111PCell typeStageSomatic mutationEpigenetic patternTotal numberRecurrence+, n (%)Site of recurrenceAdenocarcinomastage 1ctDNA-methylation-91 (11)Lungn=17methylation+62 (33.3)Stump, bonectDNA+21 (50)lungstage 2ctDNA-methylation-00 (0)n=2methylation+00(0)ctDNA+11 (100)multiplestage 3ctDNA-methylation-00 (0)n=4methylation+20 (0)ctDNA+22 (100)brain, multipleSqaumous cell carcinomastage1ctDNA-methylation-00 (0)n=7methylation+30 (0)ctDNA+41 (25)multiplestage2ctDNA-methylation-00 (0)n=9methylation+00 (0)ctDNA+92 (22.2)multiple, lungstage3ctDNA-methylation-00 (0)n=4methylation+10 (0)ctDNA+31 (33.3)Mediastinal LNs ResultsSomatic mutation analysis alone detected ctDNA in 42% (23/55) of patients, whereas combined mutational and epigenomic analysis detected ctDNA in 67% (37/55). ctDNA detection rate varied by pathological subtypes; using combined approach, ctDNA was detected in all squamous cell carcinoma patients, while only 55% (12/22) in adenocarcinoma (ADC) (p=0.006). Within the ADC subgroup, ctDNA detection rates using the combined approach were dependent on disease stage: 47% (8/17) in stage I, 100% (2/2) in stage II, and 100% (2/2) in stage IIIA. Importantly, within 2 years of follow-up, pre-operative ctDNA status was correlated with tumor recurrence after resection; among 17 stage I ADC patients, three of eight (38%) ctDNA-positive cases showed recurrence, while only one of nine (11%) ctDNA-negative cased did (p=0.29). Interestingly, patients with somatic mutation in their ctDNA have shown higher recurrence rate. ConclusionUtilizing a plasma-only sequencing assay incorporating somatic genomic and epigenomic analysis, ctDNA detection rate in early stage lung cancer (stage I-III) can far outperform the detection rate of somatic sequence variant detection alone. And, the presence of pre-operative ctDNA in patients with early stage lung adenocarcinoma may identify those who are more likely to have disease recurrence.Legal entity responsible for the study: Guradant Health, Inc. FundingGuardant Health, Redwood City, CA, USA. DisclosureI. Kim: Full / Part-time employment, Officer / Board of Directors: Guardant Health. M. Shultz: Officer / Board of Directors: Guardant Health. A. Jaimovich: Officer / Board of Directors: Guardant Health. J. Odegaard: Officer / Board of Directors: Guardant health, Inc. S. Olsen: Officer / Board of Directors: Guardant Health, Inc. A. Talasaz: Officer / Board of Directors: Guardant health. J. Kim: Research grant / Funding (self): Guardant health, Inc. All other authors have declared no conflicts of interest.

EP1.17-35 CBCT Radiomics May Predict Short-Term SBRT Effect in Early Stage Lung Cancer Patients

EP1.17-35 CBCT Radiomics May Predict Short-Term SBRT Effect in Early Stage Lung Cancer Patients

Combining Plasma miRNAs and Computed Tomography Features to Differentiate the Nature of Pulmonary Nodules.

Objective: The purpose of this study was to evaluate the diagnostic efficiency of combining plasma microRNAs (miRNAs) and computed tomography (CT) features in the diagnosis of pulmonary nodules.Methods: Ninety-two pulmonary nodule patients who had undergone surgery were enrolled in our study from July 2016 to March 2018 at the Sun Yat-sen University Cancer Center. A prediction model was established by combining 3 miRNAs (miRNA-146a, -200b, and -7) and CT features to identify the pulmonary nodules of these patients. We evaluated the diagnostic performance of this prediction model for pulmonary nodules using the Receiver Operating Characteristic (ROC) curve.Results: The expression levels of miRNA-146a, -200b, and -7 in early-stage non-small cell lung cancer (NSCLC) patients are significantly higher than those in benign nodule patients. We used these three miRNAs and CT features (pleural indentation and speculation) to establish a prediction model for early-stage NSCLC, with a sensitivity and specificity of 92.9%, 83.3% in the training set, respectively. For the validation process, with the sensitivity of 71.8% and the specificity of 69.2%. For ROC curve analyses, area under the curve (AUC) for tumor identification in the training stage and validation stage were 0.929 and 0.781, respectively.Conclusion: Plasma miRNA-146a, miRNA-200b, and miRNA-7 may be potential biomarkers for the early diagnosis of lung cancer. Our prediction model can help to identify the nature of pulmonary nodules with a relatively high diagnostic efficiency.