Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

Abstract

Background: Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+) and recurrent head and neck squamous cell carcinoma (HNSCC) may increase our understanding of the complex biology of this disease.

Methods: Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category.

Results: The most frequent alterations were the repression of modules in negative lymph node (N0) and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed.

Conclusions: The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway, specially apoptosis and interactions between tumor cells and the stroma.

Figure 1

Number of genes represented in each functional module and p- values for the repressed modules hypothesis. HNSCC patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Gene expression was assessed by microarray and functional module analysis was performed. Functional modules were defined according to the following databases: Biocarta], GeneDecks, Gene Ontology, and to the Kyoto Encyclopedia of Genes and Genomes Pathway Database (KEGGPD). A module is considered to be induced or repressed when it contains a fraction of induced or repressed genes that is higher than expected. The p-value of this fraction was calculated using hypergeometric distribution and a false discovery rate of 5% was applied to correct multiple testing. A - Negative lymph node (pN0). B - Non-recurrent tumors. These figures are representative of those for positive lymph node (pN+) and for recurrent tumors, as well as for the induced modules hypothesis.

Figure 2

Literature-based connections among genes in altered modules of head and neck squamous cell carcinoma (HNSCC). HNSCC patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Gene expression was assessed by microarray and functional module analysis was performed. Functional modules were defined according to the following databases: Biocarta], GeneDecks, Gene Ontology, and to the Kyoto Encyclopedia of Genes and Genomes Pathway Database (KEGGPD). A module is considered to be induced or repressed when it contains a fraction of induced or repressed genes that is higher than expected. The p-value of this fraction was calculated using hypergeometric distribution and a false discovery rate of 5% was applied to correct multiple testing. Corrected p-values ranged between 4.1 × 10^-20 and 2.1 × 10^-2. Filled arrows represent gene connections described in KEGGPD and dotted arrows, connections described elsewhere (see Discussion for references). Pointed arrows represent activation of gene expression or protein activity, and blunt arrows, inhibition.