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https://dx.doi.org/10.17638/00...
Thesis . 2012
License: CC BY NC ND
Data sources: Datacite
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Protein expression in colorectal cancer

Authors: Tweedle, Elizabeth;
Abstract

Introduction: Colorectal cancer is the second most common UK cancer. Biomarkers which predict survival may be valuable for targeting adjuvant therapy and can provide insights into tumour biology. Small and early cancers are being diagnosed more commonly in the UK population due to the introduction of population-based colorectal cancer screening in 2005. Analysis of resected small (≤20mm across) tumours in Liverpool has established that flat and depressed morphology can predict advanced stage at presentation. Proteomic analysis of small cancers was conducted with the aim of generating biomarkers which correspond to morphology, stage and patient survival. Patients and Methods: Laser capture microdissection was used to procure enriched matched benign and malignant colorectal epithelial cell populations. Laser captured proteins were extracted into lysis buffer, normalised against a reference standard, separated using 2D SDS-PAGE and visualized with silver staining. Comparison was made between the tumour gels, (n=10) and matched normal colonic gels, (n=9) by two different observers and gel analysis software, Progenesis SameSpots. Differentially expressed proteins were identified using tandem mass spectrometry and included redox proteins peroxiredoxin 2, peroxiredoxin 6 and SH3 binding glutamic acid-rich protein-like 3; and cytoskeletal protein cofilin1. Also identified were the anti-apoptotic protein heat shock protein 27 and inflammatory protein S100A8, which had been previously identified in 2D gel analysis of undissected colorectal cancer in our Institution (n=12 gels) and previously validated in a small cohort of paraffin-embedded colorectal cancers (n=98). In this study, HSP27 was further evaluated in a large cohort of paraffin-embedded colorectal cancer tissue (n=404). S100A8 and related proteins S100A9 and Smad4 were similarly evaluated in a large cohort (n=313). Results: High HSP27 levels were strongly associated with poor cancer-specific survival in rectal cancer (n=205, P=0.0063) but not colon cancer; (n=199, P=0.7385). Multivariate Cox regression confirmed nodal metastases (P=0.0001) and HSP27 expression (P=0.0233) as independent markers of survival in rectal cancer. HSP27 levels remained unchanged in the majority of cases 65/80 (81%) between diagnostic biopsies and matched surgical samples, regardless of whether patients had undergone preoperative radiotherapy. S100A8 expression co-localised with a subset of S100A9-positive monocytes. S100A9 was co-expressed with CD14 in tumour-associated monocytes, but not with CD68 in tissue macrophages. Smad4 was expressed in the tumour cytoplasm of 262/304 (14%) tumours. Loss of Smad4 expression correlated with a reduction in the stromal S100A8-positive, but not S100A9-positive cell count, (P=0.034, Mann-Whitney U test) and was associated with a poorer overall survival in patients with stage I-II disease, but not stage III disease. Antibodies to cofilin1 and cofilin-phospho(ser3) were assessed in colorectal cancer cell and tissue lysate and found to be specific on 1D and 2D western blot. Conclusion: Elevated HSP27 is an independent marker of poor prognosis in rectal cancer whose expression is not altered by neo-adjuvant radiotherapy. Smad4-negative tumours are associated with fewer infiltrating S100A8 positive stromal monocytes. In node-negative tumours, loss of Smad4 expression in associated with a poorer prognosis. These findings provide a sound platform for further investigation of both S100A8 and HSP27 proteins in colorectal cancer.

Keywords

RC0254

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Cancer Research