dc.contributor.author | Alnabulsi, A | |
dc.contributor.author | Wang, T | |
dc.contributor.author | Pang, W | |
dc.contributor.author | Ionescu, M | |
dc.contributor.author | Craig, SG | |
dc.contributor.author | Humphries, MP | |
dc.contributor.author | McCombe, K | |
dc.contributor.author | Salto Tellez, M | |
dc.contributor.author | Alnabulsi, A | |
dc.contributor.author | Murray, GI | |
dc.date.accessioned | 2022-04-13T09:02:04Z | |
dc.date.available | 2022-04-13T09:02:04Z | |
dc.date.issued | 2022-05-01 | |
dc.identifier.citation | The journal of pathology. Clinical research, 2022, 8 (3), pp. 245 - 256 | |
dc.identifier.issn | 2056-4538 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/5081 | |
dc.identifier.eissn | 2056-4538 | |
dc.identifier.eissn | 2056-4538 | |
dc.identifier.doi | 10.1002/cjp2.258 | |
dc.identifier.doi | 10.1002/cjp2.258 | |
dc.description.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. | |
dc.format | Print-Electronic | |
dc.format.extent | 245 - 256 | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | WILEY | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | Humans | |
dc.subject | Colorectal Neoplasms | |
dc.subject | Prognosis | |
dc.subject | Immunohistochemistry | |
dc.subject | Algorithms | |
dc.subject | Biomarkers, Tumor | |
dc.title | Identification of a prognostic signature in colorectal cancer using combinatorial algorithm-driven analysis. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2021-12-23 | |
rioxxterms.version | VoR | |
rioxxterms.versionofrecord | 10.1002/cjp2.258 | |
dc.relation.isPartOf | The journal of pathology. Clinical research | |
pubs.issue | 3 | |
pubs.notes | Not known | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/ImmNet | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Integrated Pathology | |
pubs.publication-status | Accepted | |
pubs.volume | 8 | |
pubs.embargo.terms | Not known | |
icr.researchteam | Integrated Pathology | |
dc.contributor.icrauthor | Salto-Tellez, Manuel | |