RESUMEN
The zinc finger transcription factor EGR4 has previously been identified as having a critical role in the proliferation of small cell lung cancer. Here, we have identified a novel, shortened splice variant of this transcription factor (EGR4-S) that is regulated by Heat Shock Factor-1 (HSF1). Our findings demonstrate that the shortened variant (EGR4-S) is upregulated with high EGFR, HER2, and H-Rasv12-expressing breast cell lines, and its expression is inhibited in response to HER pathway inhibitors. Protein and mRNA analyses of HER2+ human breast tumours indicated the novel EGR4-S splice variant to be preferentially expressed in tumour tissue and not detectable in patient-matched normal tissue. Knockdown of EGR4-S in the HER2-amplified breast cancer cell line SKBR3 reduced cell growth, suggesting that EGR4-S supports the growth of HER2+ tumour cells. In addition to chemical inhibitors of the HER2 pathway, EGR4-S expression was also found to be suppressed by chemical stressors and the overexpression of HSF1. Under these conditions, reduced EGR4-S levels were associated with the observed lower cell growth rate, but the augmentation of properties associated with higher metastatic potential. Taken together, these findings identify EGR4-S as a potential biomarker for HER2 pathway activation in human tumours that is regulated by HSF1.
RESUMEN
PURPOSE: Patients presenting with locally advanced rectal cancer currently receive preoperative radiotherapy with or without chemotherapy. Although pathologic complete response is achieved for approximately 10% to 30% of patients, a proportion of patients derive no benefit from this therapy while being exposed to toxic side effects of treatment. Therefore, there is a strong need to identify patients who are unlikely to benefit from neoadjuvant therapy to help direct them toward alternate and ultimately more successful treatment options. EXPERIMENTAL DESIGN: In this study, we obtained expression profiles from pretreatment biopsies for 51 rectal cancer patients. All patients underwent preoperative chemoradiotherapy, followed by resection of the tumor 6 to 8 weeks posttreatment. Gene expression and response to treatment were correlated, and a supervised learning algorithm was used to generate an original predictive classifier and validate previously published classifiers. RESULTS: Novel predictive classifiers based on Mandard's tumor regression grade, metabolic response, TNM (tumor node metastasis) downstaging, and normal tissue expression profiles were generated. Because there were only 7 patients who had minimal treatment response (>80% residual tumor), expression profiles were used to predict good tumor response and outcome. These classifiers peaked at 82% sensitivity and 89% specificity; however, classifiers with the highest sensitivity had poor specificity, and vice versa. Validation of predictive classifiers from previously published reports was attempted using this cohort; however, sensitivity and specificity ranged from 21% to 70%. CONCLUSIONS: These results show that the clinical utility of microarrays in predictive medicine is not yet within reach for rectal cancer and alternatives to microarrays should be considered for predictive studies in rectal adenocarcinoma.
