Deep proteome profiling of sera from never-smoked lung cancer patients.
Previous studies on the serum proteome are hampered by the huge dynamic range of concentration of different protein species. The use of Equalizer Beads coupled with a combinatorial library of ligands has been shown to allow access to many low-abundance proteins or polypeptides undetectable by classical analytical methods. This study focused on never-smoked lung cancer, which is considered to be more homogeneous and distinct from smoking-related cases both clinically and biologically. Serum samples obtained from 42 never-smoked lung cancer patients (28 patients with active untreated disease and 14 patients with tumor resected) were compared with those from 30 normal control subjects using the pioneering Equalizer Beads technology followed by subsequent analysis by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Eighty-five biomarkers were significantly different between lung cancer and normal control. The application of classification algorithms based on significant biomarkers achieved good accuracy of 91.7%, 80% and 87.5% in class-prediction with respect to presence or absence of disease, subsequent development of metastasis and length of survival (longer or shorter than median) respectively. Support vector machine (SVM) performed best overall. We have proved the feasibility and convenience of using the Equalizer Beads technology to study the deep proteome of the sera of lung cancer patients in a rapid and high-throughput fashion, and which enables detection of low abundance polypeptides/proteins biomarkers. Coupling with classification algorithms, the technologies will be clinically useful for diagnosis and prediction of prognosis in lung cancer.
Au
Joseph S K
JS
Department of Clinical Oncology, Queen Elizabeth Hospital, 30 Gascoigne Road, Kowloon, Hong Kong. ausk@ha.org.hk
Cho
William C S
WC
Yip
Tai Tung
TT
Yip
Christine
C
Zhu
Hailong
H
Leung
Wallace W F
WW
Tsui
Philip Y B
PY
Kwok
Davy L P
DL
Kwan
Simon S M
SS
Cheng
Wai Wai
WW
Tzang
Lawrence C H
LC
Yang
Mengsu
M
Law
Stephen C K
SC
D000230:Adenocarcinoma / Q000145:classification / Q000235:genetics* / Q000601:surgery; D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis* / Q000145:classification / Q000235:genetics; D001798:Blood Proteins / Q000032:analysis / Q000235:genetics; D016172:DNA Fingerprinting; D006801:Humans; D008175:Lung Neoplasms / Q000145:classification / Q000235:genetics* / Q000601:surgery; D013058:Mass Spectrometry; D009362:Neoplasm Metastasis / Q000235:genetics; D011237:Predictive Value of Tests; D011379:Prognosis; D020543:Proteome / Q000235:genetics*; D012907:Smoking; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D016019:Survival Analysis
D014408:Biomarkers, Tumor; D001798:Blood Proteins; D020543:Proteome