TY - JOUR
T1 - A functional biological network centered on XRCC3
T2 - A new possible marker of chemoradiotherapy resistance in rectal cancer patients
AU - Agostini, Marco
AU - Zangrando, Andrea
AU - Pastrello, Chiara
AU - D’Angelo, Edoardo
AU - Romano, Gabriele
AU - Giovannoni, Roberto
AU - Giordan, Marco
AU - Maretto, Isacco
AU - Bedin, Chiara
AU - Zanon, Carlo
AU - Digito, Maura
AU - Esposito, Giovanni
AU - Mescoli, Claudia
AU - Lavitrano, Marialuisa
AU - Rizzolio, Flavio
AU - Jurisica, Igor
AU - Giordano, Antonio
AU - Pucciarelli, Salvatore
AU - Nitti, Donato
N1 - Publisher Copyright:
© 2015 Taylor & Francis Group, LLC.
PY - 2015
Y1 - 2015
N2 - Preoperative chemoradiotherapy is widely used to improve local control of disease, sphincter preservation and to improve survival in patients with locally advanced rectal cancer. Patients enrolled in the present study underwent preoperative chemoradiotherapy, followed by surgical excision. Response to chemoradiotherapy was evaluated according to Mandard’s Tumor Regression Grade (TRG). TRG 3, 4 and 5 were considered as partial or no response while TRG 1 and 2 as complete response. From pretherapeutic biopsies of 84 locally advanced rectal carcinomas available for the analysis, only 42 of them showed 70% cancer cellularity at least. By determining gene expression profiles, responders and non-responders showed significantly different expression levels for 19 genes (P < 0.001). We fitted a logistic model selected with a stepwise procedure optimizing the Akaike Information Criterion (AIC) and then validated by means of leave one out cross validation (LOOCV, accuracy D 95%). Four genes were retained in the achieved model: ZNF160, XRCC3, HFM1 and ASXL2. Real time PCR confirmed that XRCC3 is overexpressed in responders group and HFM1 and ASXL2 showed a positive trend. In vitro test on colon cancer resistant/susceptible to chemoradioterapy cells, finally prove that XRCC3 deregulation is extensively involved in the chemoresistance mechanisms. Protein-protein interactions (PPI) analysis involving the predictive classifier revealed a network of 45 interacting nodes (proteins) with TRAF6 gene playing a keystone role in the network. The present study confirmed the possibility that gene expression profiling combined with integrative computational biology is useful to predict complete responses to preoperative chemoradiotherapy in patients with advanced rectal cancer.
AB - Preoperative chemoradiotherapy is widely used to improve local control of disease, sphincter preservation and to improve survival in patients with locally advanced rectal cancer. Patients enrolled in the present study underwent preoperative chemoradiotherapy, followed by surgical excision. Response to chemoradiotherapy was evaluated according to Mandard’s Tumor Regression Grade (TRG). TRG 3, 4 and 5 were considered as partial or no response while TRG 1 and 2 as complete response. From pretherapeutic biopsies of 84 locally advanced rectal carcinomas available for the analysis, only 42 of them showed 70% cancer cellularity at least. By determining gene expression profiles, responders and non-responders showed significantly different expression levels for 19 genes (P < 0.001). We fitted a logistic model selected with a stepwise procedure optimizing the Akaike Information Criterion (AIC) and then validated by means of leave one out cross validation (LOOCV, accuracy D 95%). Four genes were retained in the achieved model: ZNF160, XRCC3, HFM1 and ASXL2. Real time PCR confirmed that XRCC3 is overexpressed in responders group and HFM1 and ASXL2 showed a positive trend. In vitro test on colon cancer resistant/susceptible to chemoradioterapy cells, finally prove that XRCC3 deregulation is extensively involved in the chemoresistance mechanisms. Protein-protein interactions (PPI) analysis involving the predictive classifier revealed a network of 45 interacting nodes (proteins) with TRAF6 gene playing a keystone role in the network. The present study confirmed the possibility that gene expression profiling combined with integrative computational biology is useful to predict complete responses to preoperative chemoradiotherapy in patients with advanced rectal cancer.
KW - Biological network
KW - Integrated approach
KW - Microarray
KW - Preoperative chemoradiotherapy
KW - Rectal cancer
KW - Treatment response
KW - XRCC3
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U2 - 10.1080/15384047.2015.1046652
DO - 10.1080/15384047.2015.1046652
M3 - Article
AN - SCOPUS:84983445056
SN - 1538-4047
VL - 16
SP - 1160
EP - 1171
JO - Cancer Biology and Therapy
JF - Cancer Biology and Therapy
IS - 8
ER -