| Literature DB >> 28728163 |
Roopma Wadhwa1, Xuemei Wang2, Veerabhadran Baladandayuthapani2, Bin Liu3, Hironori Shiozaki1, Yusuke Shimodaira1, Quan Lin1, Elena Elimova1, Wayne L Hofstetter4, Stephen G Swisher4, David C Rice4, Dipen M Maru5, Neda Kalhor5, Manoop S Bhutani6, Brian Weston6, Jeffrey H Lee6, Heath D Skinner7, Ailing W Scott1, Dilsa Mizrak Kaya1, Kazuto Harada1, Donald Berry2, Shumei Song1, Jaffer A Ajani1.
Abstract
BACKGROUND: Predictive biomarkers or signature(s) for oesophageal cancer (OC) patients undergoing preoperative therapy could help administration of effective therapy, avoidance of ineffective ones, and establishment new strategies. Since the hedgehog pathway is often upregulated in OC, we examined its transcriptional factor, Gli-1, which confers therapy resistance, we wanted to assess Gli-1 as a predictive biomarker for chemoradiation response and validate it.Entities:
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Year: 2017 PMID: 28728163 PMCID: PMC5572179 DOI: 10.1038/bjc.2017.225
Source DB: PubMed Journal: Br J Cancer ISSN: 0007-0920 Impact factor: 7.640
Patient characteristics
| Age (years) | Median | 59 | 62 |
| Range | 35–76 | 27–80 | |
| Gender | Male | 59 (98.33) | 149 (89.22) |
| Female | 1 (1.67) | 18 (10.78) | |
| Ethnicity | White | 58 (96.67) | 152 (91.02) |
| Hispanic | 1 (1.67) | 13 (7.78) | |
| African American | 1 (1.67) | 2 (1.2) | |
| Clinical stage | IIA | 24 (40.00) | 59 (35.33) |
| IIB | 3 (5.00) | 7 (4.19) | |
| III | 30 (50.00) | 81 (48.5) | |
| IVA | 2 (3.33) | 9 (5.39) | |
| IVB | 1 (1.67) | 4 (2.40) | |
| X | 0 (0.00) | 7 (4.19) |
AJCC 6th edition.
Logistic regression model for pathCR in TDS (n=60; pathCR=16)
| Intercept | – | – | <0.0001 |
| Gli-1*100 | 0.46 | 0.33–0.64 | <0.0001 |
Abbreviations: OR=odds ratio; pathCR=pathologic complete response; TDS=the discovery set.
Logistic regression model for pathCR in TVS (n=167; pathCR=40)
| Intercept | – | – | 0.003 |
| Gli-1*100 | 0.84 | 0.78–0.90 | <0.0001 |
Abbreviations: OR=odds ration; pathCR=pathologic complete response; TVS=the validation set.
Figure 1(A) Plot of % Gli-1 LI vs the predicted probability of pathCR based on the fitted model in Table 2 for TDS (the discovery set). (B) Plot of % Gli-1 LI vs the predicted probability of pathCR based on the fitted model in Table 3 for TVS (the validation set).
Figure 2(A) ROC AUC indicating sensitivity and specificity based on the fitted model in Supplementary Table S1 for TDS (the discovery set; n=60). (B) ROC AUC indicating sensitivity and specificity based on the fitted model in Supplementary Table S2 for TVS (the validation set; n=167).
Figure 3Expression of Hh signalling components is associated with chemoradiation resistance in OC cells. (A) Protein levels of Gli-1 and Shh were determined by immunoblotting in SK-4, Flo-1 EAC cells and their resistant cells SK4-RF and Flo-1-XTR; (B) mRNA level of Hh components-Gli-1, Gli-2 and Shh was determined by quantitative real-time PCR. (C) Gene set enriched analysis of RPPA proteomic data on Sk4 cells and their resistant cells SK4-RF on cell survival signalling and many genes control oncogenic signalling are enriched in chemoresistant OC cells (SK4-RF). (D) Cell proliferation of SK4 cells and their resistant cells SK4-RF and Flo-1 and its radiation resistant cells Flo-1XTR was measured using MTS assay. (E) Colony numbers of Flo-1 and Flo-1XTR cells treated with GANT61 or 100% ethanol as control, **P<0.01. (F) Representative images of tumour spheres (left) and quantification of tumour sphere number (right) are shown in Flo-1 and Flo-1XTR cells. *P<0.05, **P<0.01.