Heterogeneity of gene expression profiles in head and neck cancer

Prognostic modeling of oral cancer by gene profiles and clinicopathological co-variables

Accurate staging and outcome prediction is a major problem in clinical management of oral cancer patients, hampering high precision treatment and adjuvant therapy planning. Here, we have built and validated multivariable models that integrate gene signatures with clinical and pathological variables to improve staging and survival prediction of patients with oral squamous cell carcinoma (OSCC). Gene expression profiles from 249 human papillomavirus (HPV)-negative OSCCs were explored to identify a 22-gene lymph node metastasis signature (LNMsig) and a 40-gene overall survival signature (OSsig). To facilitate future clinical implementation and increase performance, these signatures were transferred to quantitative polymerase chain reaction (qPCR) assays and validated in an independent cohort of 125 HPV-negative tumors. When applied in the clinically relevant subgroup of early-stage (cT1-2N0) OSCC, the LNMsig could prevent overtreatment in two-third of the patients. Additionally, the integration of RT-qPCR gene signatures with clinical and pathological variables provided accurate prognostic models for oral cancer, strongly outperforming TNM. Finally, the OSsig gene signature identified a subpopulation of patients, currently considered at low-risk for disease-related survival, who showed an unexpected poor prognosis. These well-validated models will assist in personalizing primary treatment with respect to neck dissection and adjuvant therapies.

Prospective technical validation and assessment of intra-tumour heterogeneity of a low density array hypoxia gene profile in head and neck squamous cell carcinoma

BACKGROUND AND PURPOSE

Tumour hypoxia is associated with a poor prognosis in head and neck squamous cell carcinoma (HNSCC), however there is no accepted method for assessing hypoxia clinically. We aimed to conduct a technical validation of a hypoxia gene expression signature using the TaqMan Low Density Array (TLDA) platform to investigate if this approach reliably identified hypoxic tumours.

MATERIALS AND METHODS

Tumour samples (n=201) from 80 HNSCC patients were collected prospectively from two centres. Fifty-three patients received pimonidazole prior to surgery. TaqMan Low Density Array-Hypoxia Scores (TLDA-HS) were obtained by quantitative real-time PCR (qPCR) using a 25-gene signature and customised TLDA cards. Assay performance was assessed as coefficient of variation (CoV).

RESULTS

The assay was sensitive with linear reaction efficiencies across a 4 log(10) range of inputted cDNA (0.001-10 ng/μl). Intra- (CoV=6.9%) and inter- (CoV=2.0%) assay reproducibility were excellent. Intra-tumour heterogeneity was lower for TLDA-HS (23.2%) than for pimonidazole (67.2%) or single gene measurements of CA9 (62.2%), VEGFA (45.0%) or HIG2 (39.4%). TLDA-HS in HNSCC cell lines increased with decreasing pO(2). TLDA-HS correlated with Affymetrix U133 Plus 2.0 microarray HS (p<0.01) and positive pimonidazole scores (p=0.005).

CONCLUSIONS

Gene expression measurements of hypoxia using a 25-gene signature and TLDA cards are sensitive, reproducible and associated with lower intra-tumour heterogeneity than assaying individual genes or pimonidazole binding. The approach is suitable for further assessment of prognostic and predictive capability in clinical trial material.

Molecular signatures of metastasis in head and neck cancer

BACKGROUND

Metastases are the primary cause of cancer treatment failure and death, yet metastatic mechanisms remain incompletely understood.

METHODS

We studied the molecular basis of head and neck cancer metastasis by transcriptionally profiling 70 samples from 27 patients-matching normal adjacent tissue, primary tumor, and cervical lymph node metastases.

RESULTS

We identified tumor-associated expression signatures common to both primary tumors and metastases. Use of matching metastases revealed an additional 46 dysregulated genes associated solely with head and neck cancer metastasis. However, despite being metastasis-specific in our sample set, these 46 genes are concordant with genes previously discovered in primary tumors that metastasized.

CONCLUSIONS

Although our data and related studies show that most of the metastatic potential appears to be inherent to the primary tumor, they are also consistent with the notion that a limited number of additional clonal changes are necessary to yield the final metastatic cell(s), albeit in a variable temporal order.