EEC still ranks one of the most fatal female cancers worldwide and disease progression very often accompany with worse clinical outcomes and treatment failure. Identifying genes or canonical pathways associated with advanced cancer can help to unmask the mechanisms of tumor malignancy as well as provide us with novel drug targets. It has been recognized clinically that cancer cells, especially the advanced and metastatic ones, possess characters reminiscent of those of normal stem cells. The degree of stem cell gene expression correlates with pivotal tumor features and patient prognosis [10
]. Hence, identifying shared genes between late EECs and stem cells will provide new insights into cancer biology, as well as new prognosis markers and therapeutic targets. In this study, we identified a 217-probeset signature which could distinguish late (stages III-IV) from early (stages I-II) EECs (Figure ). More low stage disease array data than high stage ones were obtained, which may partly due to the fact that the early diagnosis takes place in almost 90% of EEC clinically. We combined primary and metastatic late EEC samples in one group since their molecular profiles are indistinguishable (not shown). Prostate EpiSCs were used as a comparative group since array data for endometrial stem cells is not available yet. Nevertheless, prostate CD133+ cells are still epithelial stem cells and therefore good controls. Other EpiSC data should reproduce part of our findings.
Our results reveal a previously unaware link between genes associated with EpiSC identity and the histopathological traits of EECs. It is possible that these genes contribute to the stem cell-like phenotypes of late EECs. A total of 26 EpiSC genes were found overexpressed in late EECs (Figure ), and genes down-regulated in late EECs (Figure ; 77 probe sets) are also absence in EpiSCs (Figure ). Among those 26 overexpressed genes there are famous oncogenes or stemness genes (Figure , underlined). ADAM17 (A Disintegrin and A Metalloproteinase 17), also known as tumor necrosis factor-alpha converting enzyme (TACE) or less commonly CD156q, is a therapeutic target in multiple diseases since major contemporary pathologies like cancer, inflammatory and vascular diseases seem to be connected to its cleavage abilities [40
]. CAP1 (adenylate cyclase-associated protein 1) overexpressed in pancreatic cancers is involved in cancer cell motility [41
]. CAPG (capping protein (actin filament), gelsolin-like) also contributes in the motility of pancreatic cancer cells [42
]. PDCD10 (CCM3) is involved in cerebral cavernous malformations (CCM) [43
] and is found to interact with Ste20-related kinase MST4 to promote cell growth and transformation via modulation of the ERK pathway [44
]. PSEN1 (presenilin 1) is involved in apoptosis, overexpressed in high-risk patients with stage I non-small cell lung cancer (NSCLC), and is in a prognosis signature of NSCLC patients [45
]. SENP2 (SUMO-specific protease 2) is highly expressed in trophoblast cells that are required for placentation, and targeted disruption of SENP2 in mice reveals its essential role in development of all three trophoblast layers via modulating the Mdm2-p53 pathway [46
]. The appearance of these known oncogenes or stemness genes in our data supports the reliability of our gene lists. The roles of EpiSC genes in both epithelial stem cell biology and EEC malignancy will be addressed further.
Several genes were previous suggested to be tumor suppressors. CSTA (cystatin A, or stefin A), a cysteine proteinases inhibitor, is implicated in preventing local and metastatic tumor spread of cancers. The risk of disease recurrence and disease-related death was thus higher in patients with low CSTA in patients with squamous cell carcinoma of the head and neck [30
]. NPAS2 (neuronal PAS domain protein 2) is a circadian gene as well as a putative tumor suppressor involved in DNA damage response [47
]. PHC3 (polyhomeotic homolog 3), a component of the hPRC-H complex, associates with E2F6 during G0 and is lost in osteosarcoma tumors [48
]. Validating their expression in different stages of EECs by further immunohistochemstry study will not only provide novel malignancy mechanisms but will also present new drug targets.
In the past few years, much effort has been put to explore the mechanisms and additional molecular markers for predicting prognosis of EECs by using high-throughput genomics technology. Gene expression microarray (GEM) is a popular platform among all of those high-throughput genomics techniques. In this study we applied GEM and machine learning algorithms to filtrate out a 217-probeset signature for disease diagnosis. Many of the filtrated genes have been linked to tumor progression and malignancy, supporting the reliability of our array data. Moreover, we narrowed down this 217-probeset profile to a six-gene mini-signature for the differentiation of early to late EECs in the training set. This signature can be validated by an independent testing cohort (Figure ). Owing to the small gene number of this signature, it is now possible to check their mRNA levels in patient tissues by real-time PCR in regular clinical labs. Recently a five-gene profile and a five-microRNA signature are identified for the prediction of clinical outcomes in non-small-cell lung cancer [49
]. Whether our six-gene signature can be correlated with relapse-free and overall survival among patients with EEC is unclear and awaited to be elucidated. Also, whether the protein expression levels of these 6 genes correlate with those of mRNAs is unclear. Since most of the patients in either training or testing data set were Caucasian (Table ), whether this gene signature can be applied in patients with various genetic backgrounds should also be studied.
In our datasets we noticed that few early EEC cases expressed already late EEC genes and therefore could not be classified correctly (Figs. , ). Since patients with late and metastatic EEC tend to have poor prognosis, whether these unusual early cases possess worse clinical outcomes is an interesting issue. It has been suggested that prognosis potential of human tumors is inherited in early lesions. For example, the gene expression patterns in metastatic colorectal carcinoma are readily distinguishable from those associated with in situ
]. A subset of primary tumors resembled metastatic tumors with respect to this gene-expression signature [24
]. Very recently Varmus and colleagues showed that when untransformed mouse mammary cells were introduced into the systemic circulation of a mouse, those cells can bypass transformation at the primary site, form long-term residence in the lungs but do not form ectopic tumors [52
]. Husemann et al. also observed that systemic spread can be an early step in breast cancer. Tumor cells can disseminate systemically from earliest epithelial alterations and form and micrometastasis in bone marrow and lungs [53
]. Therefore, release from dormancy of early-disseminated cancer cells may frequently account for metachronous metastasis. The metastatic potential of human tumors is encoded in the bulk of a primary tumor and, at least in a subset of patients, metastatic capability in cancers is an inherent feature. Our EEC gene signatures therefore hold the potential of being a novel prognosis panel. More advanced therapy and clinical follow-up should be applied on early stage patients with molecular feature similar to that of EpiSC.
In advanced EECs, tumor tissues express more genes abundant in CD133+ EpiSC and acquired a stem cell trait (Figure ). The expression of these EpiSC genes in late EECs may due to the re-expression of EpiSC features in late stage EECs, i.e., further mutations and stem cell gene reactivation in certain early EECs. The intermediate EpiSC gene expression level in early EECs supports this point (Figure &). Recent studies demonstrated that EMT contributes to the acquisition of stem cell traits in cancer cells and the induction of EMT inducer Snail results in stemness gene expression [14
]. Whether EMT also contributes in EEC progression and metastasis is an interesting issue to follow. However, we did not rule out the possibility that certain late EECs may arise from an independent rapidly progressing cancer utilizing stemness molecular pathways. According to the tumor stem cell theory, cancer cells may be originated from different cancer stem cells acquiring distinctive oncogenic mutations. Certain early EECs have the capacity to progress to late stage disease may due to a mechanism that they arose from the same mutated progenitor cells as late EECs. The observation that several early EEC cases express EpiSC genes already (Figure &) favors the later hypotheses. These 2 situations may both exist in vivo
, but our profiling work cannot favor any of them yet. Nevertheless, genes filtrated here will provide clinicians novel prognosis markers and therapeutic targets.