TY - JOUR
T1 - Multiple reaction monitoring of multiple low-abundance transcription factors in whole lung cancer cell lysates
AU - Kim, Jun Seok
AU - Lee, Youngju
AU - Lee, Min Young
AU - Shin, Jihye
AU - Han, Jung Min
AU - Yang, Eun Gyeong
AU - Yu, Myeong Hee
AU - Kim, Sunghoon
AU - Hwang, Daehee
AU - Lee, Cheolju
PY - 2013/6/7
Y1 - 2013/6/7
N2 - Lung cancer-related transcription factors (TFs) were identified by integrating previously reported genomic, transcriptomic, and proteomic data and were quantified by multiple reaction monitoring (MRM) in various cell lines. All experiments were performed without affinity depletion or subfractionation of cell lysates. Since the target proteins were expected to be present in low abundance, we experimentally optimized MRM transition parameters with chemically synthesized peptides. Quantitation was based on stable isotope-labeled standard peptides (SIS peptides). Out of 288 MRM measurements (36 peptides representing 28 TFs × 8 cell lines), 241 were successfully obtained within a quantitation limit of 15 amol, 221 measurements (91.7%) showed coefficients of variation (CVs) of ≤20%, and 149 (61.8%) showed CVs of ≤10%, quantifying as low as 19.4 amol/μg protein for STAT2 with a CV of 6.3% in an A549 cell. Comparisons between MRM measurements and levels of the corresponding mRNAs revealed linear, nonlinear, or no relationship between protein and mRNA levels, indicating the need for an MRM assay. An integrative analysis of MRM and gene expression profiles from doxorubicin-resistant H69AR and sensitive H69 cells further showed that 14 differentially expressed TFs, such as STAT1 and SMAD4, regulated genes associated with drug resistance and cell differentiation-related processes. Thus, the analytical performance of MRM for the quantitation of low abundance TFs suggests its usefulness for biological application.
AB - Lung cancer-related transcription factors (TFs) were identified by integrating previously reported genomic, transcriptomic, and proteomic data and were quantified by multiple reaction monitoring (MRM) in various cell lines. All experiments were performed without affinity depletion or subfractionation of cell lysates. Since the target proteins were expected to be present in low abundance, we experimentally optimized MRM transition parameters with chemically synthesized peptides. Quantitation was based on stable isotope-labeled standard peptides (SIS peptides). Out of 288 MRM measurements (36 peptides representing 28 TFs × 8 cell lines), 241 were successfully obtained within a quantitation limit of 15 amol, 221 measurements (91.7%) showed coefficients of variation (CVs) of ≤20%, and 149 (61.8%) showed CVs of ≤10%, quantifying as low as 19.4 amol/μg protein for STAT2 with a CV of 6.3% in an A549 cell. Comparisons between MRM measurements and levels of the corresponding mRNAs revealed linear, nonlinear, or no relationship between protein and mRNA levels, indicating the need for an MRM assay. An integrative analysis of MRM and gene expression profiles from doxorubicin-resistant H69AR and sensitive H69 cells further showed that 14 differentially expressed TFs, such as STAT1 and SMAD4, regulated genes associated with drug resistance and cell differentiation-related processes. Thus, the analytical performance of MRM for the quantitation of low abundance TFs suggests its usefulness for biological application.
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U2 - 10.1021/pr3011414
DO - 10.1021/pr3011414
M3 - Article
C2 - 23586733
AN - SCOPUS:84879356633
VL - 12
SP - 2582
EP - 2596
JO - Journal of Proteome Research
JF - Journal of Proteome Research
SN - 1535-3893
IS - 6
ER -