Required Evidence for Clinical Applications of Liquid Biopsy Using Especially CTCs in Lung Cancer

As therapies have become more and more dependent on tumor as well as patient characteristics, obtaining tumor material has become of great importance. Liquid biopsies hold much potential as shown by a large amount of evidence across several studies. Clinical applications for circulating tumor cells (CTCs) are unfortunately still lacking. In part this is due to a lack of studies comparing liquid biopsies to conventional diagnostics and response measurements as well as studies showing that liquid biopsies can be used to switch therapies leading to improved outcomes. However, liquid biopsies using ctDNA for specific markers such as EGFR, ALK, ROS1 or RET have clinical applications because specific drugs are available

Decoding circulating tumor DNA to identify durable benefit from immunotherapy in lung cancer

Objectives: Predicting the outcome of immunotherapy-treated non-small cell lung cancer (NSCLC) patients is challenging. Measuring circulating tumor DNA (ctDNA) in plasma is promising, but its application for outcome delineation needs further refinement. Since most information from the next-generation sequencing (NGS) panel is typically left unused, we aim to integrate more information. Materials and Methods: Patient and ctDNA data were compiled from five published studies involving advanced NSCLC. Plasma samples collected prior (t0) and early during (t1) immunotherapy were selected, tracking the changes of the highest t0 variant per gene. Durable benefit (DB, defined as progression free survival ≥ ½ year) was predicted. Performance was quantified using the integrated receiver operating characteristic curve (ROC AUC) and compared with the traditional molecular response (MR). Results: A total of 365 patients were pooled. Seven recurrently mutated genes were selected which optimally predicted DB (ROC AUC: 0.77-0.11+0.10), outperforming the MR predictor (with a ROC AUC: 0.64-0.11+0.11). Inclusion of patient characteristics led to a slight further improvement (ROC AUC: 0.80-0.10+0.09). The model performed satisfactory across all ctDNA platforms despite differences in panel size and content. Conclusion: Relative to a non-informative classifier (ROC AUC: 0.5), a twofold improvement in predictive value was achieved compared to MR by an integration of changes across seven selected genes in immunotherapy-treated NSCLC patients, whilst being broadly applicable across ctDNA NGS panels

Patterns of recurrence and survival after surgery or stereotactic radiotherapy for early stage NSCLC

IntroductionSurgery is the standard treatment for early stage non–small-cell lung cancer (NSCLC). For medically inoperable patients, stereotactic ablative radiotherapy (SABR) has emerged as widely used standard treatment. The aim of this study was to analyze survival and patterns of tumor recurrence in patients with clinical stage I NSCLC treated with surgery or SABR.MethodsClinical data from all subsequent fluoro-deoxyglucose positron emission tomography/computed tomography-based stage I NSCLC patients (cT1-T2aN0M0) treated with surgery or SABR at our center between 2007 and 2010 were collected. Primary endpoints were overall survival and tumor recurrences/new primary lung tumors. Treatment groups were compared using multivariable Cox regression and competing risk analyses.ResultsThree hundred-forty patients treated with surgery (n = 143) or SABR (n = 197) were included. Surgical patients were younger, had a better WHO performance status and less comorbidities. After adjustment for prognostic covariables, treatment did not influence overall survival (adjusted hazard ratio [HR], SABR versus surgery 1.07; 95% confidence interval [CI]: 0.74–1.54; p = 0.73). Local control and distant recurrence were equal, whereas locoregional recurrences were significantly more frequent after SABR compared with surgery (adjusted sub-HR 2.51; 95% CI: 1.10–5.70; p = 0.028). Nodal failure (HR: 2.16; 95% CI: 1.34–3.48) and distant metastases (HR: 2.12; 95% CI: 1.52–2.97), but not local failure (HR: 1.00; 95% CI: 0.53–1.89) predicted overall survival.ConclusionsIn patients with fluoro-deoxyglucose positron emission tomography/computed tomography-based stage I NSCLC, SABR confers worse locoregional tumor control because of more nodal failures compared with surgery, stressing the need to improve mediastinal and hilar staging

3D radiomics predicts EGFR mutation, exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma

Background: To establish a radiomic approach to identify epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients based on CT images, and to distinguish exon-19 deletion and exon-21 L858R mutation. Methods: Two hundred sixty-three patients who underwent pre-surgical contrast-enhanced CT and molecular testing were included, and randomly divided into the training (80%) and test (20%) cohort. Tumor images were three-dimensionally segmented to extract 1,672 radiomic features. Clinical features (age, gender, and smoking history) were added to build classification models together with radiomic features. Subsequently, the top-10 most relevant features were used to establish classifiers. For the classifying tasks including EGFR mutation, exon-19 deletion, and exon-21 L858R mutation, four logistic regression models were established for each task. Results: The training and test cohort consisted of 210 and 53 patients, respectively. Among the established models, the highest accuracy and sensitivity among the four models were 75.5% (61.7-86.2%) and 92.9% (76.5-99.1%) to classify EGFR mutation, respectively. The highest specificity values were 86.7% (69.3-96.2%) and 70.4% (49.8-86.3%) to classify exon-19 deletion and exon-21 L858R mutation, respectively. Conclusions: CT radiomics can sensitively identify the presence of EGFR mutation, and increase the certainty of distinguishing exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma patients. CT radiomics may become a helpful non-invasive biomarker to select EGFR mutation patients for invasive sampling

Temporal trends and spatial variation in stage distribution of non-small cell lung cancer in the Netherlands

Introduction To explore regional and temporal variation in clinical stage distribution of non-small cell lung cancer (NSCLC) and link the observations to the introduction of positron emission tomography (PET). Method All NSCLC patients diagnosed between 1989 and 2007 were selected from the Netherlands Cancer Registry (n=126,962). Maps of smoothed percentage distribution of clinical stage NSCLC were conducted by period of diagnosis. Join point regression analyses were performed to detect trends over time. Geographic variation in stage distribution was evaluated using spatial scan statistic. To evaluate the impact of PET in regions proportions of stage IV and Estimated Annual Percentage of Change (EAPC) were calculated for two regions in which PET was introduced between 1995 and 2000 and for two regions without a PET scanner during this period. Results The percentage of stage I and unknown decreased with 7.4% and 13.3% between 1989 and 2007, while the percentage of stage IV increased with 23.4%. The most rapid increase in stage I and IV were observed between 1997 and 2003. In two regions with a PET scan the proportion of stage IV increased annually with 10.3 and 8.5% compared to 5.4 and 6.4% in two regions without a PET scan. Conclusion The most rapid changes towards more stage IV NSCLC diagnoses correspond with the implementation of PET. However, trends were already visible before PET was introduced and regions without PET also showed considerable increases in stage IV diagnose, suggesting other factors or improvements in diagnostics also contributed substantially

Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations

Objectives: To compare the cost-effectiveness of first-line gefitinib, erlotinib, afatinib, and osimertinib in patients with non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. Methods: A systematic review and network meta-analysis (NMA) were conducted to compare the relative efficacy of gefitinib, erlotinib, afatinib, and osimertinib in EGFR-mutated NSCLC. To assess the cost-effectiveness of these treatments, a Markov model was developed from Dutch societal perspective. The model was based on the clinical studies included in the NMA. Incremental costs per life-year (LY) and per quality-adjusted life-year (QALY) gained were estimated. Deterministic and probabilistic sensitivity analyses (PSA) were conducted. Results: Total discounted per patient costs for gefitinib, erlotinib, afatinib, and osimertinib were €65,889, €64,035, €69,418, and €131,997, and mean QALYs were 1.36, 1.39, 1.52, and 2.01 per patient, respectively. Erlotinib dominated gefitinib. Afatinib versus erlotinib yielded incremental costs of €27,058/LY and €41,504/QALY gained. Osimertinib resulted in €91,726/LY and €128,343/QALY gained compared to afatinib. PSA showed that gefitinib, erlotinib, afatinib, and osimertinib had 13%, 19%, 43%, and 26% probability to be cost-effective at a threshold of €80,000/QALY. A price reduction of osimertinib of 30% is required for osimertinib to be cost-effective at a threshold of €80,000/QALY. Conclusions: Osimertinib has a better effectiveness compared to all other TKIs. However, at a Dutch threshold of €80,000/QALY, osimertinib appears not to be cost-effective

Evaluation of elastix-based propagated align algorithm for VOI- and voxel-based analysis of longitudinal F-18-FDG PET/CT data from patients with non-small cell lung cancer (NSCLC)

Background: Deformable image registration allows volume of interest (VOI)- and voxel-based analysis of longitudinal changes in fluorodeoxyglucose (FDG) tumor uptake in patients with non-small cell lung cancer (NSCLC). This study evaluates the performance of the elastix toolbox deformable image registration algorithm for VOI and voxel-wise assessment of longitudinal variations in FDG tumor uptake in NSCLC patients. Methods: Evaluation of the elastix toolbox was performed using F-18-FDG PET/CT at baseline and after 2 cycles of therapy (follow-up) data in advanced NSCLC patients. The elastix toolbox, an integrated part of the IMALYTICS workstation, was used to apply a CT-based non-linear image registration of follow-up PET/CT data using the baseline PET/CT data as reference. Lesion statistics were compared to assess the impact on therapy response assessment. Next, CT-based deformable image registration was performed anew on the deformed follow-up PET/CT data using the original follow-up PET/CT data as reference, yielding a realigned follow-up PET dataset. Performance was evaluated by determining the correlation coefficient between original and realigned follow-up PET datasets. The intra-and extra-thoracic tumors were automatically delineated on the original PET using a 41% of maximum standardized uptake value (SUVmax) adaptive threshold. Equivalence between reference and realigned images was tested (determining 95% range of the difference) and estimating the percentage of voxel values that fell within that range. Results: Thirty-nine patients with 191 tumor lesions were included. In 37/39 and 12/39 patients, respectively, thoracic and non-thoracic lesions were evaluable for response assessment. Using the EORTC/SUVmax-based criteria, 5/37 patients had a discordant response of thoracic, and 2/12 a discordant response of non-thoracic lesions between the reference and the realigned image. FDG uptake values of corresponding tumor voxels in the original and realigned reference PET correlated well (R-2=0.98). Using equivalence testing, 94% of all the voxel values fell within the 95% range of the difference between original and realigned reference PET. Conclusions: The elastix toolbox impacts lesion statistics and therefore therapy response assessment in a clinically significant way. The elastix toolbox is therefore not applicable in its current form and/or standard settings for PET response evaluation. Further optimization and validation of this technique is necessary prior to clinical implementation

Immune microenvironment composition in non-small cell lung cancer and its association with survival

Objectives In non-small cell lung cancer (NSCLC), the immune system and possibly its composition affect survival. In thisin silicostudy, the immune infiltrate composition in NSCLC patients was evaluated. Methods Gene expression data of tumors from early NSCLC patients were obtained from Gene Expression Omnibus (GEO). With CIBERSORT, 22 immune cell fractions were estimated. Results The immune infiltrate of 1430 pretreatment NSCLC patients contained mostly plasma cells, macrophages and CD8 T cells. Higher fractions of resting mast and CD4 T-helper cells were associated with longer overall survival (OS) (HR = 0.95,P <0.01; HR = 0.98, = 0.04, respectively) and higher fractions of M2 macrophages and active dendritic cells with shorter survival (HR = 1.02,P = 0.03; HR = 1.03,P = 0.05, respectively). Adenocarcinoma patients with survival data (n = 587) showed higher fractions of resting mast and resting CD4 T cells, and lower M0 macrophages than squamous cell carcinoma (n = 254), which were associated with OS (HR = 0.95,P = 0.04; HR = 0.97,P = 0.01; HR = 1.03,P = 0.01, respectively). Fractions of memory B cells, naive CD4 T cells and neutrophils had different associations with survival depending on the subtype. Smokers had had higher fractions of regulatory T cell, follicular helper T cell, neutrophil and M2 macrophage, which were associated with shorter survival (HR = 1.3,P <0.01; HR = 1.13,P = 0.02; HR = 1.09,P = 0.03; HR = 1.04,P = 0.02, respectively). Conclusion Pretreatment differences in immune cell composition in NSCLC are associated with survival and depend on smoking status and histological subtype. Smokers' immune composition is associated with lower survival

Oral treatment with Eubacterium hallii improves insulin sensitivity in db/db mice

F.B. is supported by Swedish Research Council, Swedish Diabetes Foundation, Swedish Heart Lung Foundation, Swedish Foundation for Strategic Research, Knut and Alice Wallenberg foundation, Göran Gustafsson Foundation, Ingbritt and Arne Lundberg’s foundation, Swedish Heart Lung Foundation, Torsten Söderberg’s Foundation, Ragnar Söderberg’s Foundation, NovoNordisk Foundation, AFA insurances, and LUA-ALF grants from Västra Götalandsregionen and Stockholm County Council. F.B. is a recipient of ERC Consolidator Grant (European Research Council, Consolidator grant 615362—METABASE). W.M.d.V. is supported by the Finland Academy of Sciences (grants 137389, 141140 and 1272870 ), the Netherlands Organization for Scientific Research (Spinoza Award and SIAM Gravity Grant 024.002.002) and the European Research Council (ERC Advanced Grant 250172 MicrobesInside). M.N. is supported by a ZONMW-VIDI grant 2013 (016.146.327).Peer reviewedPublisher PD