The present study was aimed at establishing a method that combines multiple factors of protein and genetic changes that enables prediction of radiosensitivity in the head and neck squamous cell carcinoma (HNSCC) cell lines. In nine HNSCC cell lines, the quantity of protein expression and the type of genetic alterations were translated into a point system, called the Number of Negative Points. The expression of 14 proteins involved in growth control and/or apoptosis was quantified using a densitometric assessment of Western blots. The blots were adjusted to actin and standardised to normal oral keratinocytes classifying them into four groups depending on the amount of protein expressed (0-3 points). Mutations of the p53 gene were classified into three groups and each mutation was given one point. Since the cell lines each had a known intrinsic radiosensitivity, a multivariate statistical calculation could then be performed to select for the combination of factors having the strongest correlation to radiosensitivity. The strongest correlation of the investigated factors was the combination of epidermal growth factor receptor, survivin and splice site/missense p53 mutations (R=0.990 and P<0.0001). No single factor had a significant correlation to the intrinsic radiosensitivity. Since a significant correlation to the intrinsic radiosensitivity was achieved only when two or more factors were combined, we conclude that a method such as the Number of Negative Points is necessary for prediction of treatment response. We present a novel method to combine factors which enables the prediction of radiosensitivity of HNSCC cell lines.

Concomitant chemoradiotherapy is a common treatment for advanced head and neck squamous cell carcinomas (HNSCC). Cisplatin is the backbone of chemotherapy regimens used to treat HNSCC. Therefore, the aim of this study was to identify predictive markers for cisplatin treatment outcome in HNSCC. The intrinsic cisplatin sensitivity (ICS) was determined in a panel of tumour cell lines. From this panel, one sensitive and two resistant cell lines were selected for comparative transcript profiling using microarray analysis. The enrichment of Gene Ontology (GO) categories in sensitive versus resistant cell lines were assessed using the Gene Ontology Tree Machine bioinformatics tool. In total, 781 transcripts were found to be differentially expressed and 11 GO categories were enriched. Transcripts contributing to this enrichment were further analyzed using Ingenuity Pathway Analysis (IPA) for identification of key regulator genes. IPA recognized 20 key regulator genes of which five were differentially expressed in sensitive versus resistant cell lines. The mRNA level of these five genes was further assessed in a panel of 25 HNSCC cell lines using quantitative real-time PCR. Among these key regulators, MMP-7 and MMP-13 are implicated as potential biomarkers of ICS. Taken together, genome-wide transcriptional analysis identified single genes, GO categories as well as molecular networks that are differentially expressed in HNSCC cell lines with different ICS. Furthermore, two novel predictive biomarkers for cisplatin resistance, MMP-7 and MMP-13, were identified.

Radiotherapy remains the backbone of head and neck cancer therapy but response is sometimes impeded by tumor radioresistance. Identifying predictive biomarkers of radiotherapy response is a crucial step towards personalized therapy. The aim of this study was to explore gene expression data in search of biomarkers predictive of the response to radiotherapy in head and neck squamous cell carcinoma (HNSCC). Microarray analysis was performed on five cell lines with various intrinsic radiosensitivity, selected from a panel of 29 HNSCC cell lines. The bioinformatics approach included Gene Ontology (GO) enrichment profiling and Ingenuity Pathway Analysis (IPA). The GO-analysis detected 16 deregulated categories from which development, receptor activity and extracellular region represented the largest groups. Fourteen hub genes (CEBPA, CEBPB, CTNNB1, FN1, MYC, MYCN, PLAU, SDC4, SERPINE1, SP1, TAF4B, THBS1, TP53 and VLDLR) were identified from the IPA network analysis. The hub genes in the highest ranked network, (FN1, SERPINE1, THBS1 and VLDLR) were further subjected to qPCR analysis in the complete panel of 29 cell lines. Of these genes, high FN1 expression associated to high intrinsic radiosensitivity (p = 0.047). In conclusion, gene ontologies and hub genes of importance for intrinsic radiosensitivity were defined. The overall results suggest that FN1 should be explored as a potential novel biomarker for radioresistance.

The epidermal growth factor receptor (EGFR) is commonly overexpressed in head and neck squamous cell carcinomas (HNSCC). The monoclonal antibody cetuximab (Erbitux®) inhibits its signaling and has been approved for treatment of HNSCC. However, since many patients do not benefit from cetuximab treatment, predictive biomarkers of cetuximab response are required. The present study aims at finding novel markers of cetuximab resistance.

The intrinsic cetuximab sensitivity of 35 HNSCC cell lines was determined, and revealed a great variation in the response between cell lines. Five cell lines (14%) were cetuximab sensitive, and 12 (34%) were resistant. Interestingly, two cell lines proliferated after cetuximab treatment.

10 cell lines (five cetuximab sensitive and five cetuximab resistant) were selected for gene copy number array analysis on the Affymetrix SNP 6.0 platform. 39 protein coding genes were amplified in cetuximab resistant cells and normal in sensitive cells, all present on genomic regions 11q22.1 or 5p13-15. Five genes were selected for quantitative PCR  verification, namely, YAP1 and TRPC6 (11q22.1) and PDCD6, TPPP, and PTGER4 (5p13-15). An extended panel of totally 10 cetuximab resistant and 10 sensitive cell lines verified that YAP1 amplified cells are cetuximab resistant.

YAP1 gene amplification was highly correlated to the YAP1 mRNA expression, which was significantly higher in cetuximab resistant cells than in sensitive. YAP1 downregulation resulted in increased cetuximab sensitivity in one of two cetuximab resistant cell lines investigated and growth inhibition in another. We conclude that YAP1 is a marker for cetuximab resistance in head and neck cancer.