Hong Hou1, Yali Lyu2, Jing Jiang3, Min Wang2, Ruirui Zhang2, Choong-Chin Liew4,5,6, Binggao Wang1, Changming Cheng2. 1. Qingdao Central Hospital/Qingdao Cancer Hospital, Qingdao, Shandong Province, People's Republic of China. 2. Huaxia Bangfu Technology Incorporated, Beijing, People's Republic of China. 3. Qingdao Lianchi Maternity and Infant Hospital, Qingdao, Shandong Province, People's Republic of China. 4. Golden Health Diagnostics Incorporated, Jiangsu, People's Republic of China. 5. Late of Department of Clinical Pathology and Laboratory Medicine, University of Toronto, Canada. 6. Harvard Medical School, Brigham and Women's Hospital, Boston, MA, United States of America.
Abstract
BACKGROUND: Peripheral blood transcriptome profiling is a potentially important tool for disease detection. We utilize this technique in a case-control study to identify candidate transcriptomic biomarkers able to differentiate women with breast lesions from normal controls. METHODS: Whole blood samples were collected from 50 women with high-risk breast lesions, 57 with breast cancers and 44 controls (151 samples). Blood gene expression profiling was carried out using microarray hybridization. We identified blood gene expression signatures using AdaBoost, and constructed a predictive model differentiating breast lesions from controls. Model performance was then characterized by AUC sensitivity, specificity and accuracy. Biomarker biological processes and functions were analyzed for clues to the pathogenesis of breast lesions. RESULTS: Ten gene biomarkers were identified (YWHAQ, BCLAF1, WSB1, PBX2, DDIT4, LUC7L3, FKBP1A, APP, HERC2P2, FAM126B). A ten-gene panel predictive model showed discriminatory power in the test set (sensitivity: 100%, specificity: 84.2%, accuracy: 93.5%, AUC: 0.99). These biomarkers were involved in apoptosis, TGF-beta signaling, adaptive immune system regulation, gene transcription and post-transcriptional protein modification. CONCLUSION: A promising method for the detection of breast lesions is reported. This study also sheds light on breast cancer/immune system interactions, providing clues to new targets for breast cancer immune therapy.
BACKGROUND: Peripheral blood transcriptome profiling is a potentially important tool for disease detection. We utilize this technique in a case-control study to identify candidate transcriptomic biomarkers able to differentiate women with breast lesions from normal controls. METHODS: Whole blood samples were collected from 50 women with high-risk breast lesions, 57 with breast cancers and 44 controls (151 samples). Blood gene expression profiling was carried out using microarray hybridization. We identified blood gene expression signatures using AdaBoost, and constructed a predictive model differentiating breast lesions from controls. Model performance was then characterized by AUC sensitivity, specificity and accuracy. Biomarker biological processes and functions were analyzed for clues to the pathogenesis of breast lesions. RESULTS: Ten gene biomarkers were identified (YWHAQ, BCLAF1, WSB1, PBX2, DDIT4, LUC7L3, FKBP1A, APP, HERC2P2, FAM126B). A ten-gene panel predictive model showed discriminatory power in the test set (sensitivity: 100%, specificity: 84.2%, accuracy: 93.5%, AUC: 0.99). These biomarkers were involved in apoptosis, TGF-beta signaling, adaptive immune system regulation, gene transcription and post-transcriptional protein modification. CONCLUSION: A promising method for the detection of breast lesions is reported. This study also sheds light on breast cancer/immune system interactions, providing clues to new targets for breast cancer immune therapy.
Authors: Maximilian Knoll; Maria Waltenberger; Jennifer Furkel; Ute Wirkner; Aoife Ward Gahlawat; Ivana Dokic; Christian Schwager; Sebastian Adeberg; Stefan Rieken; Tobias Kessler; Felix Sahm; Laila König; Christel Herold-Mende; Stephanie E Combs; Jürgen Debus; Amir Abdollahi Journal: Cancers (Basel) Date: 2022-01-28 Impact factor: 6.639