ABCSG was a prospective randomized

ABCSG-90 was a prospective randomized adjuvant colon cancer trial investigating the influence of adding levamisole (LEV) and/or interferon (INF) alpha to adjuvant fluorouracil. Tumor material from only 70% of patients from the ABCSG-90 was available for TP53 analysis in the here reported study. Thus study limitations may arise from incomplete analysis of the ABCSG-90 cohort as well as from the treatment combinations, which were investigated in ABCSG-90. However, we believe that random patient selection as well as different treatment effects is unlikely to bias our results: The ABCSG-90 reported no difference in survival among the investigated treatment arms. The patients included in the retrospective biomarker analysis were distributed equally among treatment arms as demonstrated in Table 2. The TP53 mutations were also distributed equally among treatment arms as well as among tumor stages and purchase RPC1063 node categories. And finally the five-year overall survival of ABCSG-90 was comparable to the smaller cohort analyzed for the biomarker. In conclusion, TP53 was found to be a strong, independent marker for predicting the effect of adjuvant 5FU chemotherapy in lymph node positive colon cancer patients. We found that adjuvant 5FU resulted in a marked survival benefit in TP53 wildtype N1 patients, while TP53 mutated N1 patients performed as bad as N2 patients. The TP53 status independently predicted the effect of adjuvant 5FU on survival in N1 patients while there was no prediction of 5FU effect in N2 patients. The significant interaction between TP53 status, nodal category and treatment effect offers an explanation for the known prognostic inconsistency in stage III colon cancer patients. Further studies are needed to validate these findings.
Funding This work was supported by the Medical Scientific Fund of the Mayor of the Capital City of Vienna (#2093, #2297 Kandioler) and by the Anniversary Fund of the Oesterreichische Nationalbank (#8916 Kandioler, #12557 Teleky).
Conflict of Interest Statement Consultant or Advisory Role: Daniela Kandioler (uncompensated) (academic sponsored clinical TP53 trials).
Author Contributions Conception and design: D. Kandioler. Development of methodology: S. Kappel, B. Wolf. Acquisition of data: H. Puhalla, F. Herbst, C. Langner, J. Tschmelitsch, W. Schippinger, G. Steger, F. Hofbauer, H. Samonigg, B. Teleky, I. Kührer. Analysis and interpretation of data: D. Kandioler, M. Mittlböck, I. Kührer. Writing, review and/or revision of the manuscript: D. Kandioler, M. Mittlböck, S. Kappel, H. Puhalla, C. Langner, M. Gnant. Administrative, technical, or material support: S. Kappel, H. Puhalla, B. Wolf. Study supervision: D. Kandioler, M. Gnant (ABCSG-90).
Acknowledgments This article is based on tumor material and clinical data of the ABCSG-90, published in 2005 by Schippinger et al. (Schippinger et al., 2005).
Introduction In the era of personalised medicine, biomarkers are required for the stratification of patients allowing therapy to be tailored. This could include molecular histology of disease to allow driver mutation targeted therapy, for example EGFR tyrosine kinase inhibitors for lung cancer patients (Lynch et al., 2004; Paez et al., 2004; Pao et al., 2004). Biomarkers which can be used as early markers of response to treatment would be particularly useful in the clinic as well as in drug development, allowing patients therapy to be tailored as early as possible (Beretta, 2007). To be used routinely in the clinic, a biomarker would have to be measurable in a non-invasive readily accessible tissue or biofluid. Plasma as well as urine is routinely used in clinics for the diagnosis of a variety of diseases. For example, monitoring prostate specific antigen levels in blood has been used for screening and monitoring progression of prostate cancer (reviewed in Lilja et al., 2008). A major issue for identification of protein biomarkers is the high dynamic range of protein content in plasma (of the order of 1010Polanski and Anderson, 2007) that can make mask lower abundance proteins reducing the opportunity for detection with current instrumentation. However advances in mass spectrometry and liquid chromatography coupled to the depletion of highly abundant proteins have allowed the plasma proteome to be investigated with approximately 6 orders of magnitude penetration allowing identification of so called tissue leakage proteins which are predicted to be rich in biomarkers (Rodriguez-Suarez and Whetton, 2013; Zhou et al., 2012). Another challenge of biomarker discovery is the large variation present both between individuals in a population and in an individual over time. We have previously published an analysis showing that with the appropriate use of longitudinal samples our isobaric tagging plasma proteomics workflow can be used to identify biomarkers from clinical studies with as few as three patients per group with a power of 0.8 for the 70% least variant proteins (Zhou et al., 2012). We have coupled this approach to our newly published bioinformatics technique which more accurately estimates specific protein technical variation, this additional modelling allows more proteins to be identified as differentially expressed with sufficient power (Zhou et al., 2013). To show the utility of these methodologies we have investigated if plasma markers with clinical utility can be identified in non-small cell lung cancer (NSCLC) patients undergoing radical radiotherapy in a deliberately small cohort (3 vs 3) using a longitudinal sampling approach. Two baseline samples prior to the start of radiotherapy were analysed from each patient, allowing the baseline variation of each protein to be assessed, and thus significant changes during radiotherapy identified. These changes were then validated in a second independent cohort of twenty three patients using a second methodology.