In this study, we investigated the use of serum peptide mass profiling by MALDI-TOF-MS coupled to bioinformatics pattern discovery to predict treatment outcome of advanced NSCLC patients treated with platinum-based therapy. Additionally, peptide patterns found in NSCLC patients were differential from those found in healthy volunteers.
To our knowledge we are the first to report on a serum peptide signature for response and survival prediction in NSCLC patients treated with cisplatin-based chemotherapy. For this study, serum samples were obtained not only pre-treatment, but also during treatment and after completion of treatment, whereas serum proteomics studies typically focus on pre-treatment samples only. In a study by Taguchi et al., a predictive MALDI-TOF-MS-based peptide algorithm for "good" or "poor" clinical outcome upon epidermal growth factor tyrosine kinase inhibitor (EGFR-TKI) therapy was established . However, in this study none of the peptides corresponding to the classifying m/z features were identified.
In our study, for the short PFS versus long PFS classification, we achieved 82% accuracy with a 6-peptide-signature. A longer overall survival of the patients classified as "long PFS" and a shorter overall survival of the patients classified as "short PFS" was observed. Interestingly, performance of the signature was improved upon inclusion of 7 differential time-course peptides, the combined 13 peptide-ion signature achieving 86% accuracy. In this regard, it has been previously reported that histological response of locally advanced rectal cancer to radiochemotherapy could be predicted by SELDI-TOF-MS-based profiling and comparison of serum samples collected pre-treatment and during treatment .
For partial responders versus non-partial responders we achieved 89% accuracy with a 5-peptide signature. Inclusion of differential time-course peptides did not improve performance of this signature. Longer duration of progression-free survival was strongly associated with tumour response as seven out of eleven patients in our study with long PFS also had a partial tumour response upon treatment, compared to one out of eleven patients in the short PFS group. This suggests that the survival signature is predictive of therapy-outcome rather than prognostic. As the Kaplan-Meier analysis showed, prediction of response using the 5- or 10-peptide signatures was significantly associated with a longer median PFS of those patients, but this did not reach significance for overall survival.
In several MALDI serum peptide profiling studies involving other solid tumour types (bladder, breast, prostate, thyroid) by Villanueva et al., methodologically comparable to our study, the hypothesis was put forward that cancer-type specific changes in exopeptidase activities yield surrogate biomarkers, reflected in the differential abundance of cleavage products of common serum substrate proteins [19, 22]. The changes in exopeptidase activity were superimposed on the proteolytic events of the complement degradation and ex vivo coagulation pathways and therefore serum-specific. Regulated peptides at m/z 1690.925, 1777.966 and 1865.002 correspond to those identified in our study at 1690.90, 1777.94 and 1864.95, respectively, previously identified by MALDI-TOF-TOF-based MS/MS analysis as Complement C3f. The peptide at 2209.093 corresponds to the one we detected at 2209.08, previously identified as HMW Kininogen .
We show that in NSCLC, the identified differential serum peptides changing in abundance over time and those distinguishing NSCLC patients from cancer-free control subjects consisted of truncated sequence clusters. The identified peptides were derived from naturally occurring serum peptides and protein precursors, and therefore not likely to be tumor-derived, thus supporting the exoprotease hypothesis. For the predictive algorithms, it is important to realize that these might be specific for the treatment combination of bortezomib, cisplatin and gemcitabine and may not apply to other treatment regimens. For this exploratory analysis, we did not perform a power calculation beforehand as we did not know the biological variation in our patient groups, nor the number of peaks we would measure as well as other variables. We only knew the technical variation. It was therefore our approach to collect as many samples as we could accommodate. It is crucial to validate and adjust the established signatures with an independent cohort in a sufficiently powered follow-up study. Additionally, since only one report excludes an age and gender bias for a cancer-specific serum peptide signature, it is advisable to include matched cancer-free control groups for the establishment of cancer-specific peptide patterns.