Dataset Information

Proteomic Analysis of FFPE Tissue Samples Identifies Potential Molecular Mechanisms Mediating Resistance to Radiotherapy in Rectal Cancer

ABSTRACT: Chemoradiation prior to surgery in locally advanced rectal cancer is the current standard therapy. Unfortunately, this is not effective in all rectal cancer patients and associated with severe side effects, thus, prognostic marker molecules predicting the effectiveness of radiation would be of great interest. Aim of this study was to investigate pathophysiological mechanisms underlying radioresistance. Therefore, FFPE rectal tumor (n=50) and control tissue (n=39) of non-responders and responders to chemoradiation were analyzed using LC-MS-based proteomics. As a result, 1683 proteins were robustly identified. Comparing tumor with corresponding control samples revealed 199 significantly regulated proteins with FTL, PCOLCE and RCN3 being most striking in tumor tissue. While CAECAM 1, 5 and 6 as well as MCM protein complex components were significantly up-regulated in tumor tissue of non-responders compared to all types of responders, ER-stress and autophagic activity-related proteins, namely HYOU1, PDIA4 and RAB1B were only found significantly regulated when compared to complete responders, suggesting their importance in radioresistance mechanisms. Analyzing not only tumor but also surrounding control tissue allowed us to highlight the contribution of stroma to radioresistance. This study demonstrates the suitability of FFPE samples for proteomic analysis and presents potential molecular mechanisms mediating resistance to chemoradiation in rectal cancer.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Rectal Cancer Cell, Colorectal Cancer Cell, Colon

DISEASE(S): Rectum Cancer,Colorectal Carcinoma

SUBMITTER: Christopher Gerner

LAB HEAD: Christopher Gerner

PROVIDER: PXD060201 | Pride | 2025-08-25

REPOSITORIES: Pride

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			Action	DRS
	23-Prot-0408_RD1_1_13110.d.rar	Other
	23-Prot-0409_RD2_1_13111.d.rar	Other
	23-Prot-0410_RD3_1_13113.d.rar	Other
	23-Prot-0411_RD4_1_13114.d.rar	Other
	23-Prot-0412_RD5_1_13116.d.rar	Other

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Proteomic Analysis of FFPE Tissue Samples Identifies Potential Molecular Mechanisms Mediating Resistance to Radiotherapy in Rectal Cancer.

Zott Tobias T Wolf Michael M Plessl-Walder Günter G Regele Heinz H Bergmann Michael M Meier-Menches Samuel M SM Gerner Christopher C Silberhumer Gerd R GR Bileck Andrea A

Journal of proteome research 20250626 8

Chemoradiation prior to surgery in locally advanced rectal cancer is the current standard therapy but is not effective in all rectal cancer patients. Prognostic markers supporting patient stratification with respect to clinical response would therefore be desirable. The aim of this study was to investigate pathophysiological mechanisms underlying radioresistance and to identify potential prognostic markers by comparative proteome profiling. Therefore, formalin fixed paraffin-embedded tissue (FFP ...[more]

PMID: 40574313

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Project description:Objective: Insights about differences in tumor vasculature and how it reacts to VEGF inhibition is limited, but nevertheless of major relevance to anti-angiogenic therapy. In this study we therefore characterize the effect of bevacizumab combined with chemoradiotherapy (CRT), and explore molecular and genetic markers for response prediction to this combination treatment. Material and Methods: In an academic multicentric randomized phase II study, patients with advanced rectal cancer have been treated with bevacizumab (5mg/kg) in combination with capecitabine (1650mg/m2/day) and radiotherapy (45Gy; 1.8Gy/day) with (50mg/m2) or without oxaliplatin prior to surgery. Of 59 patients, tumor tissue and blood samples were collected before treatment and after the first loading dose of bevacizumab but before CRT (week 3). First, cDNA micro-arrays were performed on the biopsies to investigate differences in gene expression of tumors from patients with and without a pathological complete response (pCR) before start of treatment and to identify biological processes affected by bevacizumab delivery. The paraffin embedded tissue was stained for blood vessels (CD31/CD34) combined with Î±-SMA (pericytes) and CA-IX (hypoxia). To explore candidate blood-based biomarkers ELISAâs were performed for PDGF-AA, PDGF-BB, THBS-1, IL-8, CYR61 and Ang-2. The expression of all markers was correlated with the pathological response of the patients. Results: Differences in tumoral gene expression are observed between patients with and without a pCR, with the first response group presenting a more angiogenic phenotype before start of treatment and changes in angiogenic processes after bevacizumab delivery. One dose of bevacizumab leads to a decrease in the number of pericyte covered blood vessels, a decrease in circulating PDGF-AA, PDGF-BB and Thrombospondin-1. Patients showing a pCR having less pericyte covered blood vessels, more hypoxia, and less circulating PDGF-BB compared to patients who did not have a pCR after bevacizumab treatment with chemoradiation and bevacizumab. Conclusions: The translational data demonstrate that tumors with an angiogenic expression profile respond better to bevacizumab combined with CRT and points towards a possible role for PDGF, CA-IX and pericyte covered blood vessels for the early response prediction to this treatment. Our findings suggest a role for mural cell recruitment and vessel maturation for the susceptibility of the tumor vasculature to bevacizumab treatment. Further validation of our biological observations and hypothesis generating data in randomized trials is needed. This study involves samples of patients enrolled in the AXEbeam trail that were analysed by Primeview microarray (Affymetrix). Biopsies were taken at two different timepoints: before treatment (tumor and normal mucosa) and after the first loading dose of bevacizumab but before chemoradiation (only tumor, week 3). Patients were classified into two groups: with a complete pathological response at time of surgery (Responders=R) or non-responders (NR). For the responders, we collected 21 samples in total (7 tumor samples and 8 normal mucosa samples taken before treatment and 6 tumor samples collected at week 3). From the non-responders we had 26 samples in total (9 tumor and 10 mucosa samples before treatment and 7 tumor samples at week 3 after a single dose of bevacizumab). Microarrays were run in two batches (15xxx versus 16xxx CEL file samples; indicated in the description field). Three samples (NJ 04/003 T1, RVS 09/002 M and NJ 04/003 W3) were put twice on the array (15897+16789; 15893+16790; 15898+16791) to verify and exclude batch effects. Please note that, due to these three technical repeats the total number of microarray CEL files is 50 (21 Responders, 26 Non-responders and 3 repeats).