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Abstract

Background

A sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.

Methodology/Principal Findings

Salivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.

Conclusions

Our findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.

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Most cited references 51

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Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

Marc Buyse, Sherene Loi, Laura Van't Veer … (2006)

A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cancer.

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The case for early detection.

Ruth Etzioni, Nicole Urban, Scott Ramsey … (2003)

Early detection represents one of the most promising approaches to reducing the growing cancer burden. It already has a key role in the management of cervical and breast cancer, and is likely to become more important in the control of colorectal, prostate and lung cancer. Early-detection research has recently been revitalized by the advent of novel molecular technologies that can identify cellular changes at the level of the genome or proteome, but how can we harness these new technologies to develop effective and practical screening tests?

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Diagnostic accuracy of mammography, clinical examination, US, and MR imaging in preoperative assessment of breast cancer.

Wendie A Berg, Lorena Gutiérrez, Moriel NessAiver … (2004)

To prospectively assess accuracy of mammography, clinical examination, ultrasonography (US), and magnetic resonance (MR) imaging in preoperative assessment of local extent of breast cancer. Institutional review board approval and informed patient consent were obtained. Results of bilateral mammography, US, and contrast-enhanced MR imaging were analyzed from 111 consecutive women with known or suspected invasive breast cancer. Results were correlated with histopathologic findings. Analysis included 177 malignant foci in 121 cancerous breasts, of which 89 (50%) foci were palpable. Median size of 139 invasive foci was 18 mm (range, 2-107 mm). Mammographic sensitivity decreased from 100% in fatty breasts to 45% in extremely dense breasts. Mammographic sensitivity was highest for invasive ductal carcinoma (IDC) in 89 of 110 (81%) cases versus 10 of 29 (34%) cases of invasive lobular carcinoma (ILC) (P < .001) and 21 of 38 (55%) cases of ductal carcinoma in situ (DCIS) (P < .01). US showed higher sensitivity than did mammography for IDC, depicting 104 of 110 (94%) cases, and for ILC, depicting 25 of 29 (86%) cases (P < .01 for each). US showed higher sensitivity for invasive cancer than DCIS (18 of 38 [47%], P < .001). MR showed higher sensitivity than did mammography for all tumor types (P < .01) and higher sensitivity than did US for DCIS (P < .001), depicting 105 of 110 (95%) cases of IDC, 28 of 29 (96%) cases of ILC, and 34 of 38 (89%) cases of DCIS. In anticipation of conservation or no surgery after mammography and clinical examination in 96 breasts, additional tumor (which altered surgical approach) was present in 30. Additional tumor was depicted in 17 of 96 (18%) breasts at US and in 29 of 96 (30%) at MR, though extent was now overestimated in 12 of 96 (12%) at US and 20 of 96 (21%) at MR imaging. After combined mammography, clinical examination, and US, MR depicted additional tumor in another 12 of 96 (12%) breasts and led to overestimation of extent in another six (6%); US showed no detection benefit after MR imaging. Bilateral cancer was present in 10 of 111 (9%) patients; contralateral tumor was depicted mammographically in six and with both US and MR in an additional three. One contralateral cancer was demonstrated only clinically. In nonfatty breasts, US and MR imaging were more sensitive than mammography for invasive cancer, but both MR imaging and US involved risk of overestimation of tumor extent. Combined mammography, clinical examination, and MR imaging were more sensitive than any other individual test or combination of tests. (c) RSNA, 2004.

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Author and article information

Contributors

: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2010

Publication date (Electronic): 31 December 2010

Volume: 5

Issue: 12

Electronic Location Identifier: e15573

Affiliations

[1 ]School of Dentistry and Dental Research Institute, University of California Los Angeles, Los Angeles, California, United States of America

[2 ]Saul and Joyce Brandman Breast Center, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

[3 ]Women's Cancer Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, United States of America

[4 ]Department of Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America

[5 ]Department of Pathology and Laboratory Medicine, Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, United States of America

[6 ]Division of Hematology and Oncology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America

[7 ]Division of Head and Neck Surgery/Otolaryngology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America

[8 ]Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California, United States of America

[9 ]Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, United States of America

Health Canada, Canada

Author notes

* E-mail: leizhang@ 123456ucla.edu (LZ); dtww@ 123456ucla.edu (DTW)

Conceived and designed the experiments: LZ SK DC BK DTW. Performed the experiments: LZ HX. Analyzed the data: LZ HX HZ DE. Contributed reagents/materials/analysis tools: SK BK JG DA XY. Wrote the paper: LZ.

Article

Publisher ID: PONE-D-10-03003

DOI: 10.1371/journal.pone.0015573

PMC ID: 3013113

PubMed ID: 21217834

SO-VID: aad75b73-d317-494f-a5a1-c1565dc4ff00

Copyright © Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 6 October 2010

Date accepted : 12 November 2010

Page count

Pages: 7

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Discovery and Preclinical Validation of Salivary Transcriptomic and Proteomic Biomarkers for the Non-Invasive Detection of Breast Cancer

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Abstract

Background

Methodology/Principal Findings

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Most cited references 51

Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

The case for early detection.

Diagnostic accuracy of mammography, clinical examination, US, and MR imaging in preoperative assessment of breast cancer.

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