Original contributionFour-protein signature accurately predicts lymph node metastasis and survival in oral squamous cell carcinoma☆
Introduction
Metastasis involves the migration and colonization of cancer cells beyond the primary tumor and is governed by molecular mechanisms that facilitate the multiple steps required for this process. Despite a better understanding of some of the factors influencing metastasis through in vitro and in vivo studies, metastatic disease still remains the principal event leading to death in patients with cancer. In oral squamous cell carcinoma (OSCC), metastasis spreads predominantly via a lymphatic route, where the cervical lymph nodes (LN) are the first location [1], whereas metastasis to distant sites is relatively uncommon. Cervical LN metastasis is an important determinant of the outcome of OSCC [2] and the status is correlated with patient survival [3]. An accurate assessment of the cervical LN metastasis status in OSCC helps to predict the prognosis of patients and also helps clinicians perform the appropriate treatment. Currently, the clinical assessment of cervical LNs is conducted by clinical examination of the neck region or by ultrasound, computed tomography, and magnetic resonance imaging. Notably, postoperative histology examination has demonstrated that approximately 30% of clinically diagnosed metastasis-negative (N0) patients have metastasis-positive LNs in the neck. Furthermore, 10% to 20% of clinically diagnosed metastasis-positive (N+) patients were actually metastasis-free, where the highest overall accuracy for current preoperative neck assessment is 76%, strongly indicating that the sensitivity of these methods is still limited [4], [5], [6]. Clearly, the development of other parameters that could help with the assessment of LN metastasis is urgently needed.
Recent evidence has demonstrated that primary tumors are preconfigured to metastasize, and this propensity is detectable at the time of initial diagnosis [7], [8], [9]. Despite the large amount of information from these studies, these markers have not yet been validated as clinical tools to predict LN status in patients. In this study, we used high-throughput tissue microarrays (TMAs) to validate biomarkers that could accurately predict LN metastasis in a cohort of patients with OSCC. We identified a 4-protein signature that could reliably distinguish patients with LN metastasis from those who were metastasis-free. The sensitivity and specificity of this gene signature suggest that it could be a useful tool to complement current diagnostic procedures for managing patients with OSCC.
Section snippets
Case materials and the construction of the TMA
Two hundred eleven tissue cores obtained from 55 individuals, comprising 47 patients and 8 nonmalignant controls, were included in the training and validation sets in this retrospective study. OSCCs that were diagnosed at the Kuala Lumpur General Hospital, Malaysia, between 2003 and 2010 were included. Non–squamous cell carcinomas and verrucous carcinomas were excluded. The histopathologic examination of specimens and neck node metastases was performed by an oral pathologist according to the
Demographics and clinicopathologic characteristics of patients recruited
Tissue specimens in excess of diagnostic value obtained from patients who were treated surgically were used in this study. Twenty-eight patients with OSCC diagnosed from 2003 to 2008 were used for the training set. The demographics and clinicopathologic parameters of these patients are included in Table 1. According to histopathologic assessment, 9 of 28 of the patients had LN metastasis. Survival information was available for 25 of 28 patients, in which the length of follow-up ranged from 1 to
Discussion
Cervical LN metastasis is a major determinant in predicting patient survival in OSCC [2], and the accurate removal of positive LNs is one of the most important determinants of OSCC treatment. Therefore, the ability to predict LN metastasis at the first biopsy of the primary tumor will significantly improve the management of patients with OSCC. Patients with similar pathological disease stage can exhibit varying survival outcomes, in part, due to the molecular heterogeneity within each of the
Supplementary data
The following are the supplementary data to this article.
Acknowledgment
We are grateful to Mr David Lyn and Ms Tan Bee Ying from Matrix Optics (M) for their technical assistance. The Cancer Research Initiatives Foundation (CARIF) is a nonprofit research organization. We are committed to an understanding of cancer prevention, diagnosis, and treatment through a fundamental research program.
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This study was funded by the Ministry of Science, Technology and Innovation, Putrajaya, Malaysia (grant no. 06-00-00-000), High Impact Research (HIR) grant from University of Malaya, Kuala Lumpur, Malaysia (J-00000-73561), and other sponsors of the Cancer Research Initiatives Foundation.