Prediction of risk scores for colorectal cancer patients from the concentration of proteins involved in mitochondrial apoptotic pathway
Autoři:
Anjali Lathwal aff001; Chakit Arora aff001; Gajendra P. S. Raghava aff001
Působiště autorů:
Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India
aff001
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0217527
Souhrn
One of the major challenges in managing the treatment of colorectal cancer (CRC) patients is to predict risk scores or level of risk for CRC patients. In past, several biomarkers, based on concentration of proteins involved in type-2/intrinsic/mitochondrial apoptotic pathway, have been identified for prognosis of colorectal cancer patients. Recently, a prognostic tool DR_MOMP has been developed that can discriminate high and low risk CRC patients with reasonably high accuracy (Hazard Ratio, HR = 5.24 and p-value = 0.0031). This prognostic tool showed an accuracy of 59.7% when used to predict favorable/unfavorable survival outcomes. In this study, we developed knowledge based models for predicting risk scores of CRC patients. Models were trained and evaluated on 134 stage III CRC patients. Firstly, we developed multiple linear regression based models using different techniques and achieved a maximum HR value of 6.34 with p-value = 0.0032 for a model developed using LassoLars technique. Secondly, models were developed using a parameter optimization technique and achieved a maximum HR value of 38.13 with p-value 0.0006. We also predicted favorable/unfavorable survival outcomes and achieved maximum prediction accuracy value of 71.64%. A further enhancement in the performance was observed if clinical factors are added to this model. Addition of age as a variable to the model improved the HR to 40.11 with p-value as 0.0003 and also boosted the accuracy to 73.13%. The performance of our models were evaluated using five-fold cross-validation technique. For providing service to the community we also developed a web server ‘CRCRpred’, to predict risk scores of CRC patients, which is freely available at https://webs.iiitd.edu.in/raghava/crcrpred.
Klíčová slova:
Medicine and health sciences – Oncology – Cancers and neoplasms – Colorectal cancer – Biology and life sciences – Cell biology – Cell processes – Cell death – Apoptosis – Cellular structures and organelles – Cell membranes – Membrane proteins – Outer membrane proteins – Signal transduction – Cell signaling – Signaling cascades – Stress signaling cascade – Biochemistry – Bioenergetics – Energy-producing organelles – Mitochondria – Biomarkers – Research and analysis methods – Mathematical and statistical techniques – Statistical methods – Regression analysis – Physical sciences – Mathematics – Statistics – Linear regression analysis
Zdroje
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2019 Číslo 9
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