Intensity-Modulated Radiotherapy Outcomes for Oropharyngeal Squamous Cell Carcinoma Patients Stratified by p16 Status

Department of Radiation Oncology, University of Virginia, Charlottesville, Virginia, USA.
Cancer (Impact Factor: 4.89). 06/2010; 116(11):2645-54. DOI: 10.1002/cncr.25040
Source: PubMed


Patients with oropharyngeal squamous cell carcinoma (OPSCC) treated with intensity-modulated radiotherapy (IMRT) were stratified by p16 status, neck dissection, and chemotherapy to correlate these factors with outcomes.
A total of 112 patients with OPSCC treated with IMRT from 2002 to 2008 were retrospectively analyzed. All patients received RT to 66-70 Gray. Forty-five of the tumors were p16 positive (p16+), 27 were p16 negative (p16-), and 41 had unknown p16 status. Sixty-two patients had postradiation neck dissections. Nine patients with p16- tumors and 28 patients with p16+ tumors received chemotherapy. The distribution of T, N, and stage grouping among the p16+ and p16- patients was not significantly different, and 87.5% patients had stage III/IV disease.
The median follow-up was 26.3 months. For patients with p16+ tumors, p16- tumors, and the overall cohort, the actuarial 3-year locoregional progression-free survival rate was 97.8%,73.5%, and 90.5% respectively (P = .006) and the disease-free survival rate was 88.2%, 61.4%, and 81.7%, respectively (P = .004). Patients with p16+ tumors had an 89.5% and 87.5% pathologic complete response (CR) on neck dissection with and without chemotherapy, respectively. In contrast, patients with p16- tumors had a 66.7% and 25.0% pathologic CR on neck dissection with and without chemotherapy, respectively.
In this series, p16 status was found to be a significant predictive biomarker and patients with p16+ tumors had much better outcomes than patients with p16- tumors. Further investigation is warranted to determine whether less intense therapy is appropriate for selected patients with p16+ OPSCC, whereas more aggressive strategies are needed to improve outcomes in patients with p16- disease.

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Available from: Paul W Read, Sep 24, 2014
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    • "We previously reported an approximate 25–30% improvement of outcomes for p16+ versus p16− OPSCC tumors at our institution. For patients with p16+ and p16− tumors, the 3-year locoregional progression-free survival rate was 97.8% and 73.5% (P = 0.006) and the DFS rate was 88.2% and 61.4%, respectively (P = 0.004) [8]. In this present study, we investigated the prognostic significance of multiple previously reported protein biomarkers in addition to p16 for patients with OPSCC treated with definitive IMRT in an attempt to further stratify patients with p16+ and p16− tumors into significantly prognostic subgroups. "
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    ABSTRACT: We evaluated a panel of 8 immunohistochemical biomarkers as predictors of clinical response to definitive intensity-modulated radiotherapy in patients with oropharyngeal squamous cell carcinoma (OPSCC). 106 patients with OPSCC were treated to a total dose of 66-70 Gy and retrospectively analyzed for locoregional control (LRC), disease-free survival (DFS), and overall survival (OS). All tumors had p16 immunohistochemical staining, and 101 tumors also had epidermal growth factor receptor (EGFR) staining. 53% of the patients had sufficient archived pathologic specimens for incorporation into a tissue microarray for immunohistochemical analysis for cyclophilin B, cyclin D1, p21, hypoxia-inducible factor-1α (HIF-1α), carbonic anhydrase, and major vault protein. Median followup was 27.2 months. 66% of the tumors were p16 positive, and 34% were p16 negative. On univariate analysis, the following correlations were statistically significant: p16 positive staining with higher LRC (P = 0.005) and longer DFS (P < 0.001); cyclin D1 positive staining with lower LRC (P = 0.033) and shorter DFS (P = 0.002); HIF-1α positive staining with shorter DFS (P = 0.039). On multivariate analysis, p16 was the only significant independent predictor of DFS (P = 0.023). After immunohistochemical examination of a panel of 8 biomarkers, our study could only verify p16 as an independent prognostic factor in OPSCC.
    International Journal of Otolaryngology 07/2012; 2012(7):685951. DOI:10.1155/2012/685951
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    • "p16 is an important tumor suppressor gene, deletion of which causes various types of tumors making it an important potential target for cancer gene therapy. It has been reported that p16 positive oropharyngeal squamous cell carcinoma (OPSCC) patients respond more favorably to intensity-modulated radiotherapy treatment in comparison to similar p16 negative tumors (Shoushtari et al., 2010). Infectious delivery of the whole p15/p16/p14ARF locus, in infectious bacterial artificial chromosomes, results in growth suppression in human glioma cells (Inoue et al., 2004). "
    Tumor Suppressor Genes, 02/2012; , ISBN: 978-953-307-879-3
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    ABSTRACT: Summary form only given, as follows. The purpose of this paper is to present the results of radio coverage studies using neural networks. The problem of finding an exact or approximation model for propagation path loss occurs frequently in planning mobile communication systems. Two strategies for propagation path loss prediction are in use: one is to derive an empirical formula for propagation path loss from measurement data and the other is a deterministic method that is based on the theory of diffraction. While the deterministic methods suffer from excessive computation time and the need for very detailed databases, the empirical methods have difficulties in making efficient use of all available data. An empirical formula based on Okumura's results has been developed by Hata in order to make the propagation loss prediction easy to apply. The advantage of using neural networks for field strength prediction is given by the possibility of deriving training patterns directly from measurements. This allows the system to become very flexible and to adapt to an arbitrary environment. The applications of neural networks discussed in this paper can be viewed as a function approximation problem consisting of a nonlinear mapping from a set of input variables containing information about potential receiver locations (i.e. distance to the transmitters, terrain, frequency) onto a single output variable representing predicted path loss. Our intention is to train a neural network with measurement data for the purpose of field strength prediction. Applications to Hata's formula and knife-edge diffraction are included to demonstrate the effectiveness of the neural network approach
    Applied Electromagnetism, 2000. Proceedings of the Second International Symposium of Trans Black Sea Region on; 02/2000
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