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Purpose: Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a “watch and wait” strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging.
Experimental design: We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial.
Results: A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76).
Conclusion: The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a “watch and wait” strategy.
Translational relevance: Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for “watch and wait”.
We have recently shown that caspase-8 is a new substrate of Polo-like kinase 3 (Plk3) that phosphorylates the protein on residue T273 thereby promoting its pro-apoptotic function. In the present study we aimed to investigate the clinical relevance of Plk3 expression and phosphorylation of caspase-8 at T273 in patients with anal squamous cell carcinoma (SSC) treated with 5-fluorouracil and mitomycin C-based chemoradiotherapy (CRT). Immunohistochemical detection of the markers was performed in pretreatment biopsy specimens of 95 patients and was correlated with clinical/histopathologic characteristics including HPV-16 virus load/p16INK4a expression and cumulative incidence of local and distant failure, cancer specific survival (CSS), and overall survival (OS). We observed significant positive correlations between Plk3 expression, pT273 caspase-8 signal, and levels of HPV-16 virus DNA load/p16INK4a detection. Patients with high scores of Plk3 and pT273 caspase-8 showed increased local control (p = 0.011; p = 0.001), increased CSS (p = 0.011; p = 0.013) and OS (p = 0.024; p = 0.001), while the levels of pT273 caspase-8 were significantly associated (p = 0.033) with distant metastases. In multivariate analyses Plk3 expression remained significant for local failure (p = 0.018), CSS (p = 0.016) and OS (p = 0.023). Moreover, a combined HPV16 DNA load and Plk3 or pT273 caspase-8 variable revealed a significant correlation to decreased local failure (p = 0.001; p = 0.009), increased CSS (p = 0.016; p = 0.023) and OS (p = 0.003; p = 0.003). In conclusion these data indicate that elevated levels of Plk3 and pT273 caspase-8 are correlated with favorable clinical outcome in patients with anal SCC treated with concomitant CRT.