Background
Metastatic squamous cell carcinomas of the head & neck (HNSCC) and squamous cell carcinomas of the lung (lung SCC) appear similar on microscopic examination and are often indistinguishable using traditional histopathology. While immunohistochemical approaches are very useful in distinguishing squamous cell carcinomas from other carcinomas such as adenocarcinomas, they fail to clearly identify the site of origin of the squamous cell carcinoma [
1]. Both HNSCC and lung SCC show positive immunoreactivity with squamous cell carcinoma markers such as p63 and CK5/6 [
2].
Further confounding this diagnostic dilemma is the fact that head & neck cancers and lung cancers often occur in the same patient. Both cancers have similar etiologies and risk factors such as tobacco use [
3,
4]. Patients with a prior laryngeal cancer also have a 4.5-fold increased incidence ratio of lung cancer when followed for >5 years [
5]. Thus, in patients with a prior history of head & neck cancers, a new lung lesion might represent a new primary lung cancer or may represent metastasis from the previously treated head & neck cancer [
6,
7].
The distinction between HNSCC and lung SCC, and in particular the distinction of metastatic versus primary cancers for lung lesions, is important for optimal clinical management of patients. Prognosis and therapeutic options for patients with metastatic head & neck cancer are considerably different from those for patients with a localized secondary lung cancer. While metastatic head & neck cancer patients have an expected median survival of 10 months to a year, patients with solitary lung cancer have a median survival of 48 months [
8,
9]. Similarly, therapeutic strategies for metastatic head & neck cancer patients are markedly different from therapeutic strategies for patients with solitary lung cancer lesions [
3]. While patients with primary lung cancers are more likely to receive lung lobectomies, associated with a 3% mortality rate, adjuvant chemotherapy, and other aggressive forms of therapy, metastatic head & neck cancer patients are more likely to be treated with palliative chemotherapy alone [
10,
11].
Molecular diagnostic tests that use gene expression profiling with microarrays to classify cancers according to their primary sites are now a feasible tool for cancer diagnosis [
12‐
16]. Advances in gene annotation and array design along with the use of standardized protocols and array platforms across laboratories have made microarray-based gene expression profiling highly reproducible [
13,
16‐
19]. These assays have the advantage of measuring the expression of a multitude of biomarkers simultaneously. Additionally, the use of RNA from formalin-fixed paraffin embedded (FFPE) tissue in microarray-based diagnostics has become more common, considerably expanding the utility of these diagnostic tests [
13,
16,
20‐
22].
Gene expression profiling has previously been used in several studies to distinguish head & neck carcinomas from clinically normal tissues [
23‐
26]. These data have been used to develop predictive models that discriminate oral squamous cell carcinomas from normal specimens or distinguish dysplasia from normal tissue. These models have been validated in independent sets of samples and shown to have high sensitivity and specificity. In contrast, studies that use gene expression profiling to distinguish between head & neck cancers and lung cancers have been rare [
27]. One prior study showed that histologically similar squamous cell carcinomas have distinct gene expression profiles based on their anatomic sites of origin [
27]. While this profile was not validated using an independent set of samples, it does appear that it is feasible to classify squamous cell carcinomas based on their primary sites using gene expression.
In order to better clarify HNSCC versus lung SCC, we have developed a gene expression based diagnostic test, GEP-HN-LS (Pathwork® Tissue of Origin Head & Neck Test, Pathwork Diagnostics, Inc., Redwood City, CA, USA), that can be used to aid in the differential diagnosis of squamous carcinomas of the head & neck and lung in FFPE tissue. For patients with HNSCC who develop a lung nodule, a test differentiating second primary versus metastatic disease would have significant clinical utility. Patients with a second primary have a high chance at cure with aggressive therapy while patients with metastatic disease are not curable and are best treated with palliative chemotherapy.
Discussion
Squamous cell carcinomas originating in the lung and those originating in the head & neck region are morphologically similar. Additionally, there are no known immunohistochemical markers that can identify the tissue of origin of squamous cell carcinomas. GEP-HN-LS, a novel gene expression profile diagnostic test, can successfully distinguish between lung SCC and HNSCC cancers. Performance was evaluated in an independent set of specimens that were solely composed of either metastatic cancers or poorly differentiated primary cancers. GEP-HN-LS accurately identified the primary site of lung or head & neck in 82.9% of cases with a known clinical diagnosis of squamous cell carcinoma. The majority of specimens had Similarity Scores of ≥ 90 and for these specimens GEP-HN-LS indicated the correct HNSCC or lung SCC tissue 95.7% of the time. Physicians utilizing the GEP-HN-LS test receive both the tissue type result and the similarity score, and can evaluate the confidence of the tissue call based on the similarity score. The data presented in this study support the superiority of GEP-HN-LS in distinguishing HNSCC from lung SCC when compared to human papillomavirus (HPV) testing, which has low sensitivity as it is present in only a subset of HNSCC [
26]. Cytokeratin profiling has not been useful in distinguishing between squamous cell carcinomas from various primary sites as squamous cancers have overlapping cytokeratin positivity profiles.
GEP-HN-LS uses 2600 probesets (2160 independent genes) to classify HNSCC and lung SCC cancers. These classification biomarkers were empirically chosen based upon maximal performance observed with the training data and the 20 markers with the highest predictive value included several genes with specific functions in lung biology and possible roles in lung cancer. Surfactant proteins are components of the lipoprotein surfactant complex that reducing surface tension at the alveolar air-liquid interface and facilitate respiratory mechanics [
35,
36]. They control pulmonary host defense and inflammation, and might have a role in lung cancer pathogenesis [
37,
38]. Interestingly, NKX2-1 (more commonly known as Thyroid Transcription Factor-1 or TTF-1), a common immunohistochemical marker of lung adenocarcinomas [
39,
40], was among the top 20 classification markers and had higher expression levels in lung SCC compared to HNSCC cancers. Squamous cell carcinomas are typically negative for nuclear NKX2-1 protein expression [
41]. However, cytoplasmic staining of the NKX2-1 protein and expression of the NKX2-1 transcript has been observed in squamous cell carcinomas [
42].
Gene expression profiling has previously been successfully used to distinguish between primary lung cancers and metastatic head and neck cancers [
27]. The top classification markers identified in the prior study were different from those used by GEP-HN-LS. This is possibly because the prior study utilized frozen tissues and the GEP-HN-LS test is optimized to work on FFPE specimens. In addition, the prior study utilized a different microarray chip and restricted the head & neck cases to those occurring in the oral tongue which is not the most common head and neck cancer subtype [
27]. Another study used gene expression profiling to identify differences between head & neck and cervical cancers, the majority of which are also squamous cell cancers [
26]. Kallikrien-related peptidase 7, KLK7, was the only marker in our list of top classification markers that was among their differentially expressed genes. Thus, this gene had higher expression levels in HNSCC compared to both lung SCC and cervical cancers.
Gene expression profiling based predictive models that distinguish oral squamous cell carcinomas from normal tissue and oral dysplasia from normal tissue have also been developed [
23‐
26]. The classification markers used by these prior models are distinct from those used by GEP-HN-LS. This is not surprising since the prior models identify the presence of cancer while GEP-HN-LS differentiates between two different cancers.
GEP-HN-LS utilizes FFPE specimens, the most commonly available clinical specimen and success rates for processing FFPE specimens was 95.0%. The use of FFPE specimens along with a high processing success rate is advantageous in the clinical setting, and allows for wide usage of GEP-HN-LS.
The test has been validated for samples that have as low as 60% tumor content. In cases where the tumor content of specimens is <60%, tissue microdissection can be used to enrich the tumor content and achieve the 60% tumor requirement. FFPE specimens used in this study were excisional biopsies. However, FFPE cell buttons from fine needle aspirates (FNA), including bone marrow aspirates, FFPE cell buttons from malignant effusions and FFPE core needle biopsies can be used with GEP-HN-LS as long as they contain ≥ 60% tumor and yield sufficient (≥ 30 ng) total RNA to allow target preparation. Test performance of GEP-HN-LS was consistent regardless of the biopsy site. Both primary and metastatic cases, which have different biopsy sites, performed well with GEP-HN-LS. While our study was not powered to perform sub-population analysis, GEP-HN-LS could distinguish specific cases of HNSCC versus lung SCC that were both in the lymph node. Additionally, test performance for specimens with a lymph node biopsy site was equivalent to specimens with other biopsy sites such as brain or skin.
Since this test has high accuracy and reliability we feel it can be used in a clinical setting. In patients who are newly diagnosed with a solitary lung nodule at the same time as locally advanced HNSCC this test can be used to determine if the patient has two simultaneous primaries or metastatic HNSCC. For patients with two primaries, aggressive therapy for both areas is recommended since cure rates remain high, while metastatic patients should receive only palliative therapies. Similarly, for patients previously treated for HNSCC who on follow-up scans are noted to have a lung nodule, GEP-HN-LS test can be used to determine if this new nodule is metastatic disease or a second primary, for patients with second primaries aggressive surgical resection is indicated.
In this study, we present data validating the accuracy and reproducibility of GEP-HN-LS. The test can be used as an adjunct to histologic and clinical information for difficult to diagnose patients where the distinction between squamous lung cancer and squamous head & neck cancer would impact surgical or drug management of these patients. We anticipate GEP-HN-LS to have particular clinical value for patients with a lung lesion and a history of prior head & neck cancers and for patients with a new diagnosis of HNSCC diagnosed with a concurrent lung lesion. In these cases, the test would aid in distinguishing between a new lung primary or metastatic disease.
Acknowledgements
We thank the management and professional staff of the three sites that processed samples – Pathwork Diagnostics Laboratory, Expression Analysis and GeneLogic, Inc. We also thank Calpath Medical Associates Gyne-Path Laboratory Inc. for assistance in pathology review of specimens and Pam Lambert for useful discussions on the manuscript. We thank Dr. Sai Yendamuri, Associate Professor of Oncology, Roswell Park Cancer Institute, for providing guidance regarding the clinical significance of GEP-HN-LS, for reviewing the manuscript and for providing valuable input on the manuscript content.
Competing interests
All authors are employees or consultants of Pathwork Diagnostics.
Authors’ contributions
AL, RP, MM, and LJB participated in conception, study design, conduct of study, data management and analysis and result interpretation. WDH, MHM and GJK participated in conception, study design and result interpretation. EF participated in study design, data analysis and result interpretation. AL authored the manuscript. All authors have reviewed and approved the final manuscript.