Title |
Novel biomarkers that assist in accurate discrimination of squamous cell carcinoma from adenocarcinoma of the lung
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Published in |
BMC Cancer, September 2016
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DOI | 10.1186/s12885-016-2792-1 |
Pubmed ID | |
Authors |
Kazuya Takamochi, Hiroko Ohmiya, Masayoshi Itoh, Kaoru Mogushi, Tsuyoshi Saito, Kieko Hara, Keiko Mitani, Yasushi Kogo, Yasunari Yamanaka, Jun Kawai, Yoshihide Hayashizaki, Shiaki Oh, Kenji Suzuki, Hideya Kawaji |
Abstract |
Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. Cap Analysis of Gene Expression (CAGE) is a method used to quantify promoter activities across the whole genome by determining the 5' ends of capped RNA molecules with next-generation sequencing. We performed CAGE on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD), and confirmed the findings by immunohistochemical analysis (IHC) in an independent group (29 SCC and 45 AD). Using the genome-wide promoter activity profiles, we confirmed that the expression of known molecular markers used in IHC for SCC (CK5, CK6, p40 and desmoglein-3) and AD (TTF-1 and napsin A) were different between SCC and AD. We identified two novel marker candidates, SPATS2 for SCC and ST6GALNAC1 for AD, as showing comparable performance and complementary utility to the known markers in discriminating PDSCC and non-lepidic AD. We subsequently confirmed their utility at the protein level by IHC in an independent group. We identified two genes, SPATS2 and ST6GALNAC1, as novel complemental biomarkers discriminating SCC and AD. These findings will contribute to a more accurate diagnosis of NSCLC, which is crucial for precision medicine for lung cancer. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 3 | 100% |
Demographic breakdown
Type | Count | As % |
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Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Scientists | 1 | 33% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 61 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 9 | 15% |
Student > Ph. D. Student | 7 | 11% |
Other | 5 | 8% |
Researcher | 5 | 8% |
Student > Postgraduate | 4 | 7% |
Other | 9 | 15% |
Unknown | 22 | 36% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 12 | 20% |
Biochemistry, Genetics and Molecular Biology | 9 | 15% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 7% |
Agricultural and Biological Sciences | 3 | 5% |
Computer Science | 3 | 5% |
Other | 8 | 13% |
Unknown | 22 | 36% |