Early detection of lung cancer using small RNAs.

person Amita Sharma Massachusetts General Hospital, Boston, MA info_outline Amita Sharma, Tobias Sikosek, Rastislav Horos, Timothy Rajakumar, Kaja Tikk, Christian Schumann, Stephan Walterspacher, Petros Christopoulos, Martin H. Schuler, Kaid Darwiche, Christian Taube, Balazs Hegedus, Klaus Rabe, Kimberly M. Rieger-Christ, Francine Jacobnson, Clemens Aigner, Alexander A. Bankier, Martin Reck, Bruno Steinkraus

Authors person Amita Sharma Massachusetts General Hospital, Boston, MA info_outline Amita Sharma, Tobias Sikosek, Rastislav Horos, Timothy Rajakumar, Kaja Tikk, Christian Schumann, Stephan Walterspacher, Petros Christopoulos, Martin H. Schuler, Kaid Darwiche, Christian Taube, Balazs Hegedus, Klaus Rabe, Kimberly M. Rieger-Christ, Francine Jacobnson, Clemens Aigner, Alexander A. Bankier, Martin Reck, Bruno Steinkraus Organizations Massachusetts General Hospital, Boston, MA, Hummingbird Diagnostics, Heidelberg, Germany, Klinikverbund Allgäu, Kempten, Germany, Klinikum Konstanz, Konstanz, Germany, Department of Thoracic Oncology, Thoraxklinik and National Center for Tumor Diseases at Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany, University Hospital Essen, West German Cancer Center, Essen, Germany, Universitätsmedizin Essen, Essen, Germany, University Medicine Essen, Essen, Germany, LungenClinic Grosshansdorf, Airway Research Center North, German Center for Lung Research, Grosshansdorf, Germany, Lahey Hospital and Medical Center, Burlington, MA, Brigham and Women's Hospital, Boston, MA, Department of Thoracic Surgery and Thoracic Endoscopy - Ruhrlandklinik, University Hospital Essen, University of Duisburg-Essen, Essen, Germany, University of Massachusetts Chan Medical School, Worcester, MA, Department of Thoracic Oncology, Airway Research Center North, German Center for Lung Research, LungClinic, Grosshansdorf, Germany, Hummingbird Diagnostics GmbH, Heidelberg, Germany Abstract Disclosures Research Funding Pharmaceutical/Biotech Company Hummingbird Diagnostics GmbH Background: Low-dose computed tomography (LDCT) screening can significantly reduce lung cancer mortality. However, annual screening is limited by low adherence in the USA and still not broadly implemented in Europe. As a result, <10% of lung cancers are detected through existing programs. Thus, there is great need for additional diagnostic modalities, such as a blood test that could be deployed in the primary care setting. Methods: We prospectively recruited 1,189 patients meeting the 2013 USPSTF screening criteria for lung cancer and collected stabilized whole blood. Ultra-deep small RNA sequencing was performed with a method to remove highly abundant erythroid RNAs, opening bandwidth for the detection of less abundant species originating from plasma or the immune cellular compartment. We utilized 100 random data splits to train and evaluate logistic regression classifiers using small RNA expression, discovered an 18-small RNA feature consensus signature (miLung), and validated this in an independent cohort (246 patients). Blood cell sorting and tumor tissue sequencing were performed to deconvolve small RNAs into their source of origin. Results: We generated diagnostic models and report a median ROC AUC of 0.86 (95% CI 0.84-0.86) in the discovery cohort, and generalized performance of 0.84 in the validation cohort. Diagnostic performance increased stage-dependently from 0.73 (95% CI 0.71-0.76) for Stage I to 0.90 (95% CI 0.89-0.90) for Stage IV. We identified a tumor-shed, plasma-bound ribosomal RNA fragment of the L1 stalk as a dominant predictor of lung cancer. The fragment is decreased following surgery with curative intent. In additional experiments, dried blood spot collection and sequencing revealed that small RNA analysis could potentially be conducted via home-sampling. Conclusions: These data suggest the potential of a small RNA-based blood test as a viable alternative to LDCT screening for early detection of smoking-associated lung cancer. Clinical trial information: NCT03452514. Patient characteristics. Discovery Cohort Validation Cohort Controls Cancers p-value Controls Cancers p-value n = 498 n = 445 n = 127 n = 119 Sex, n (%) Female 200 (40.2) 175 (39.3) 0.846 66 (52.0) 49 (41.2) 0.117 Male 298 (59.8) 270 (60.7) 61 (48.0) 70 (58.8) Age, Yr Mean ±SD 64.1 ± 5.4 64.7 ± 5.4 0.121 63.7 ± 5.8 65.8 ± 4.8 0.005 Median (range) 64.0 (55-75) 65.0 (55-75) 64.0 (55-74) 66.0 (55-74) 0.007 Smoking Status, n (%) Current 206 (41.4) 223 (50.1) 0.009 65 (51.2) 70 (58.8) 0.282 Former 292 (58.6) 222 (49.9) 62 (48.8) 49 (41.2) Pack Years, Mean ±SD 48.8 ± 20.0 53.7 ± 22.3 <0.001 49.1 ± 24.3 42.2 ± 20.4 0.035 Histological Subtype, n (%) NSCLC Adenocarcinoma 206 (46.3) <0.001 68 (57.1) <0.001 NSCLC Squamous 119 (26.7) 32 (26.9) NSCLC Other 38 (8.5) 1 (0.8) SCLC 57 (12.8) 13 (10.9) Other lung cancer 25 (5.6) 5 (4.2) Pathological Stage, n (%) Ia 69 (15.5) 18 (15.1) Ib 23 (5.2) 4 (3.4) IIa 14 (3.1) 3 (2.5) IIb 46 (10.3) 7 (5.9) IIIa 59 (13.3) 8 (6.7) IIIb 55 (12.4) 8 (6.7) IIIc 18 (4.0) 4 (3.4) III 5 (1.1) 4 (3.4) IV 156 (35.1) 64 (52.9)

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