CD44 expression predicts local recurrence after radiotherapy in larynx cancer.

PURPOSE: To find molecular markers from expression profiling data to predict recurrence of laryngeal cancer after radiotherapy. EXPERIMENTAL DESIGN: We generated gene expression data on pre-treatment biopsies from 52 larynx cancer patients. Patients developing a local recurrence were matched for T-stage, subsite, treatment, gender and age with non-recurrence patients. Candidate genes were then tested by immunohistochemistry on tumor material from a second series of 76 patients. Both series comprised early stage cancer treated with radiotherapy alone. Finally, gene expression data of eight larynx cancer cell lines with known radiosensitivity were analyzed. RESULTS: Nineteen patients with a local recurrence were matched with 33 controls. Gene sets for hypoxia, proliferation and intrinsic radiosensitivity did not correlate with recurrence, whereas expression of the putative stem cell marker CD44 did. In a supervised analysis, probes for all three splice variants of CD44 on the array appeared in the top 10 most significantly correlated with local recurrence. Immunohistochemical analysis of CD44 expression on the independent validation series confirmed CD44's predictive potential. In 8 larynx cancer cell lines, CD44 gene expression did not correlate with intrinsic radiosensitivity although it did correlate significantly with plating efficiency, consistent with a relationship with stem cell content. CONCLUSIONS: CD44 was the only biological factor tested which significantly correlated with response to radiotherapy in early stage larynx cancer patients, both at the mRNA and protein levels. Further studies are needed to confirm this and to assess how general these findings are for other head and neck tumor stages and sites.

HPV and high-risk gene expression profiles predict response to chemoradiotherapy in head and neck cancer, independent of clinical factors.

PURPOSE: The purpose of this study was to combine gene expression profiles and clinical factors to provide a better prediction model of local control after chemoradiotherapy for advanced head and neck cancer. MATERIAL AND METHODS: Gene expression data were available for a series of 92 advanced stage head and neck cancer patients treated with primary chemoradiotherapy. The effect of the Chung high-risk and Slebos HPV expression profiles on local control was analyzed in a model with age at diagnosis, gender, tumor site, tumor volume, T-stage and N-stage and HPV profile status. RESULTS: Among 75 patients included in the study, the only factors significantly predicting local control were tumor site (oral cavity vs. Pharynx, hazard ratio 4.2 [95% CI 1.4-12.5]), Chung gene expression status (high vs. Low risk profile, hazard ratio 4.4 [95% CI 1.5-13.3]) and HPV profile (negative vs. Positive profile, hazard ratio 6.2 [95% CI 1.7-22.5]). CONCLUSIONS: Chung high-risk expression profile and a negative HPV expression profile were significantly associated with increased risk of local recurrence after chemoradiotherapy in advanced pharynx and oral cavity tumors, independent of clinical factors.

A gene expression model of intrinsic tumor radiosensitivity: prediction of response and prognosis after chemoradiation.

PURPOSE: Development of a radiosensitivity predictive assay is a central goal of radiation oncology. We reasoned a gene expression model could be developed to predict intrinsic radiosensitivity and treatment response in patients. METHODS AND MATERIALS: Radiosensitivity (determined by survival fraction at 2 Gy) was modeled as a function of gene expression, tissue of origin, ras status (mut/wt), and p53 status (mut/wt) in 48 human cancer cell lines. Ten genes were identified and used to build a rank-based linear regression algorithm to predict an intrinsic radiosensitivity index (RSI, high index = radioresistance). This model was applied to three independent cohorts treated with concurrent chemoradiation: head-and-neck cancer (HNC, n = 92); rectal cancer (n = 14); and esophageal cancer (n = 12). RESULTS: Predicted RSI was significantly different in responders (R) vs. nonresponders (NR) in the rectal (RSI R vs. NR 0.32 vs. 0.46, p = 0.03), esophageal (RSI R vs. NR 0.37 vs. 0.50, p = 0.05) and combined rectal/esophageal (RSI R vs. NR 0.34 vs. 0.48, p = 0.001511) cohorts. Using a threshold RSI of 0.46, the model has a sensitivity of 80%, specificity of 82%, and positive predictive value of 86%. Finally, we evaluated the model as a prognostic marker in HNC. There was an improved 2-year locoregional control (LRC) in the predicted radiosensitive group (2-year LRC 86% vs. 61%, p = 0.05). CONCLUSIONS: We validate a robust multigene expression model of intrinsic tumor radiosensitivity in three independent cohorts totaling 118 patients. To our knowledge, this is the first time that a systems biology-based radiosensitivity model is validated in multiple independent clinical datasets.

Gene expression profiling to predict outcome after chemoradiation in head and neck cancer.

PURPOSE: The goal of the present study was to improve prediction of outcome after chemoradiation in advanced head and neck cancer using gene expression analysis. MATERIALS AND METHODS: We collected 92 biopsies from untreated head and neck cancer patients subsequently given cisplatin-based chemoradiation (RADPLAT) for advanced squamous cell carcinomas (HNSCC). After RNA extraction and labeling, we performed dye swap experiments using 35k oligo-microarrays. Supervised analyses were performed to create classifiers to predict locoregional control and disease recurrence. Published gene sets with prognostic value in other studies were also tested. RESULTS: Using supervised classification on the whole series, gene sets separating good and poor outcome could be found for all end points. However, when splitting tumors into training and validation groups, no robust classifiers could be found. Using Gene Set Enrichment analysis, several gene sets were found to be enriched in locoregional recurrences, although with high false-discovery rates. Previously published signatures for radiosensitivity, hypoxia, proliferation, "wound," stem cells, and chromosomal instability were not significantly correlated with outcome. However, a recently published signature for HNSCC defining a "high-risk" group was shown to be predictive for locoregional control in our dataset. CONCLUSION: Gene sets can be found with predictive potential for locoregional control after combined radiation and chemotherapy in HNSCC. How treatment-specific these gene sets are needs further study.

Heterogeneity of gene expression profiles in head and neck cancer.

BACKGROUND: Results of gene expression profiling studies from different institutes often lack consistency. This could be due to the use of different microarray platforms and protocols, or to intratumoral heterogeneity in mRNA expression. The aim of our study was to quantify intratumoral heterogeneity in head and neck cancer. METHODS: Forty-four fresh frozen biopsies were taken from 22 patients, 2 per tumor. RNA was extracted, tested for quality, amplified, labeled, and hybridized to a 35k oligoarray. RESULTS: Unsupervised clustering analyses using all genes, the most variable genes, or random gene sets showed that 80% to 90% of biopsy pairs clustered together. A within-pair-between-pair scatter ratio analysis showed that the similarity between matching pairs was significantly greater than that between random pairs (p <.00001). CONCLUSIONS: Two biopsies from the same tumor show far greater similarity in gene expression than biopsies from different tumors, supporting the use of 1 biopsy for expression profiling.