Abstract
Background: There is an unmet need for tissue-specific biomarkers that distinguish estrogen receptor (ER)- negative breast cancers from primary lung adenocarcinomas. Methods: To identify proteins that differ between primary breast and lung cancers, frozen resected samples collected from 10 ER-negative breast and 18 lung adenocarcinomas patients were analyzed using Matrix-Assisted Laser Desorption/Ionization (MALDI) Mass Spectrometry (MS). Results: MALDI MS profiles were significantly different between primary breast and lung adenocarcinomas. Importantly, 4 peaks that differentially expressed between breast and lung adenocarcinomas correctly predicted the class label of a lung metastasis of breast cancer. A peak at m/z 10,093, which was significantly overexpressed in primary lung cancer, was identified as S100A6. According to immunohistochemistry study using commercially available tissue microarray slides, S100A6 expression was significantly lower in breast cancer samples than in lung adenocarcinomas samples. Conclusion: We identified MALDI MS profiles that may distinguish primary lung adenocarcinoma from ERnegative breast adenocarcinoma. S100A6 was identified as one of the informative peaks in the MALDI MS profiles.
Highlights
The lung is a frequent site of metastasis of breast adenocarcinoma
When a solitary pulmonary nodule is detected during the follow-up of estrogen receptor (ER)-negative breast cancer patients, series of immunohistochemical studies for the lung biopsy are often needed to make a differential diagnosis of the lung lesion
Ten breast adenocarcinoma and 18 lung adenocarcinoma were used as a training set, and a breast cancer lung metastasis was used as a proof-of-concept test sample (Table 1S)
Summary
The lung is a frequent site of metastasis of breast adenocarcinoma. When a solitary pulmonary nodule is detected during the follow-up of estrogen receptor (ER)-negative breast cancer patients, series of immunohistochemical studies for the lung biopsy are often needed to make a differential diagnosis of the lung lesion. Vollmer proposed a model based on immunohistocheimcal stains for thyroid transcription factor (TTF)-1, mammaglobin, p63, and ER and epidemiologic data about primary lung and metastatic breast cancers in women [1]. Since fresh frozen tissue of the breast cancer metastasis in lung is not readily available for research, we chose to compare protein expression profiles between primary ERnegative breast cancers and primary lung adenocarcinoma, to identify tissue-specific biomarkers. This approach has been widely employed to develop a genomic predictor of tissue of origin [2], based on the assumption that expression profiles are generally similar between primary and metastatic lesions [3]. There is an unmet need for tissue-specific biomarkers that distinguish estrogen receptor (ER)negative breast cancers from primary lung adenocarcinomas
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