Identification of a prognostic signature in colorectal cancer using combinatorial algorithm-driven analysis.
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Embargo End Date
ICR Authors
Authors
Alnabulsi, A
Wang, T
Pang, W
Ionescu, M
Craig, SG
Humphries, MP
McCombe, K
Salto Tellez, M
Alnabulsi, A
Murray, GI
Wang, T
Pang, W
Ionescu, M
Craig, SG
Humphries, MP
McCombe, K
Salto Tellez, M
Alnabulsi, A
Murray, GI
Document Type
Journal Article
Date
2022-05-01
Date Accepted
2021-12-23
Abstract
Colorectal carcinoma is one of the most common types of malignancy and a leading cause of cancer-related death. Although clinicopathological parameters provide invaluable prognostic information, the accuracy of prognosis can be improved by using molecular biomarker signatures. Using a large dataset of immunohistochemistry-based biomarkers (n = 66), this study has developed an effective methodology for identifying optimal biomarker combinations as a prognostic tool. Biomarkers were screened and assigned to related subsets before being analysed using an iterative algorithm customised for evaluating combinatorial interactions between biomarkers based on their combined statistical power. A signature consisting of six biomarkers was identified as the best combination in terms of prognostic power. The combination of biomarkers (STAT1, UCP1, p-cofilin, LIMK2, FOXP3, and ICOS) was significantly associated with overall survival when computed as a linear variable (χ2 = 53.183, p < 0.001) and as a cluster variable (χ2 = 67.625, p < 0.001). This signature was also significantly independent of age, extramural vascular invasion, tumour stage, and lymph node metastasis (Wald = 32.898, p < 0.001). Assessment of the results in an external cohort showed that the signature was significantly associated with prognosis (χ2 = 14.217, p = 0.007). This study developed and optimised an innovative discovery approach which could be adapted for the discovery of biomarkers and molecular interactions in a range of biological and clinical studies. Furthermore, this study identified a protein signature that can be utilised as an independent prognostic method and for potential therapeutic interventions.
Citation
The journal of pathology. Clinical research, 2022, 8 (3), pp. 245 - 256
Source Title
Publisher
WILEY
ISSN
2056-4538
eISSN
2056-4538
2056-4538
2056-4538
Collections
Research Team
Integrated Pathology