2007
DOI: 10.1093/jnci/djk195
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Mass Spectrometry to Classify Non–Small-Cell Lung Cancer Patients for Clinical Outcome After Treatment With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors: A Multicohort Cross-Institutional Study

Abstract: This MALDI MS algorithm was not merely prognostic but could classify NSCLC patients for good or poor outcomes after treatment with EGFR TKIs. This algorithm may thus assist in the pretreatment selection of appropriate subgroups of NSCLC patients for treatment with EGFR TKIs.

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Cited by 290 publications
(297 citation statements)
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“…Secondly, in the present study, patients with wild-type EGFR and no EGFR-TKI therapy were more likely to be smokers and to have brain metastasis and adrenal gland metastasis than those with wild-type EGFR and EGFR-TKI therapy. Finally, the response rate of EGFR-TKI therapy in patients with wild-type EGFR was 10-20% in previous reports [8,12,32,47,48].…”
Section: Discussionmentioning
confidence: 80%
“…Secondly, in the present study, patients with wild-type EGFR and no EGFR-TKI therapy were more likely to be smokers and to have brain metastasis and adrenal gland metastasis than those with wild-type EGFR and EGFR-TKI therapy. Finally, the response rate of EGFR-TKI therapy in patients with wild-type EGFR was 10-20% in previous reports [8,12,32,47,48].…”
Section: Discussionmentioning
confidence: 80%
“…Further, in complex mass spectra, peak widths can be influenced by the presence of proximate peaks and the peak picking and the peak intensity measurement process must take these local effects into account. With rigorous spectral pre-processing consisting of regional (in terms of m/z) background determinations and noise estimation, alignment using common peaks in training sample sets and normalization methods using partial ion current techniques, MALDI mass spectra are highly reproducible across laboratories and even across slightly different hardware [22].…”
Section: Data Analysis: Special Considerations In Profilingmentioning
confidence: 99%
“…We recently reported a study that establishes the reproducibility of the profiling approach both within and between laboratories. We developed and tested the ability of a predictive algorithm based on MALDI-TOF MS analysis of pre-treatment serum to identify patients who are likely to benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) [22]. Some but not all patients with non-small cell lung cancer (NSCLC) respond to treatment with EGFR TKIs.…”
Section: Protein Profiling Studiesmentioning
confidence: 99%
“…This technology has already been used to characterize diagnostic and prognostic markers in tumors such as breast (74), brain (75), colon (76), gastric (77), lung (78)(79)(80), and prostate cancer (81). In a large retrospective study by Taguchi et al, blood collected from patients with NSCLC before treatment with an EGFR TKI was analyzed by MALDI IMS and compared against patient outcome, and an algorithm was developed to stratify patients into "good" or "poor" risk groups based on possible clinical benefit from EGFR TKI treatment (82). Subsequently, the large phase 3 PROSE trial was able to prospectively demonstrate that patients with NSCLC carrying a good proteomic test classification predicted for benefit with erlotinib therapy over chemotherapy, whereas those with a poor proteomic classification predicted for benefit with chemotherapy over erlotinib (83).…”
Section: Future Technologies For Tumor Characterization Of Ctcsmentioning
confidence: 99%