We analyzed global gene expression patterns of 91 human hepatocellular carcinomas (HCCs) to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. Unsupervised classification methods revealed two distinctive subclasses of HCC that are highly associated with patient survival. This association was validated via 5 independent supervised learning methods. We also identified the genes most strongly associated with survival by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provides new molecular insight into the pathogenesis of HCC. Tumors from the low survival subclass have strong cell proliferation and antiapoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and histone modification, suggesting an etiological involvement of these processes in accelerating the progression of HCC. In conclusion, the biological differences identified in the HCC subclasses should provide an attractive source for the development of therapeutic targets (e.g., HIF1a) for selective treatment of HCC patients. H epatocellular carcinoma (HCC) is the fifth most common cancer in the world, accounting for an estimated 500,000 deaths annually. 1 Although HCC is prevalent in Southeast Asia and sub-Sahara Africa, the incidence of HCC has doubled in the United States over the past 25 years, and incidence and mortality rates are likely to double over the next 10 -20 years. 2 Although much is known about both the cellular changes that lead to HCC and the etiological agents responsible for the majority of HCC cases (hepatitis B virus, hepatitis C virus, alcohol), the molecular pathogenesis of HCC is not well understood. 3 Considerable efforts have been devoted to establishing a prognostic model for HCC by using clinical information and pathological classification to provide information at diagnosis on both survival and treatment options. 4 -10 Although much progress has been made (reviewed by Llovet et al. 11 ), many issues still remain unresolved. For example, a staging system that reliably separates patients with early HCC as well as intermediate to advanced HCC into homogeneous groups with respect to prognosis does not exist. This is particularly important because the natural course of early HCC is unknown and the natural progression of intermediate and advanced HCC are known to be quite heterogeneous. 12 It therefore appears axiomatic that improving the classification of HCC patients into groups with homogeneous prognosis would at least improve the application of currently available treatment modalities and at best provide new treatment strategies.Recently, microarray technologies have been successfully used to predict clinical outcome and survival as well as classify different types of cancer. [13][14][15]

In our series, 28% of HCCs contained cells expressing CK7 and/or CK19. They potentially derive from HPCs. The higher recurrence rate of CK19+ HCC after transplantation suggests a worse prognosis for these HCCs compared with CK19- HCC.

In animals, the combination of oxidative liver damage and inhibited hepatocyte proliferation increases the numbers of hepatic progenitors (oval cells). We studied different murine models of fatty liver disease and patients with nonalcoholic fatty liver disease or alcoholic liver disease to determine whether oval cells increase in fatty livers and to clarify the mechanisms for this response. To varying degrees, all mouse models exhibit excessive hepatic mitochondrial production of H 2 O 2 , a known inducer of cell-cycle inhibitors. In mice with the greatest H 2 O 2 production, mature hepatocyte proliferation is inhibited most, and the greatest number of oval cells accumulates. In rodent models for hepatocarcinogenesis, small oval cells that express both hepatocyte and cholangiocyte markers accumulate in the liver before cancerous nodules develop.

ObjectiveKeratin (K)19, a biliary/hepatic progenitor cell (HPC) marker, is expressed in a subset of hepatocellular carcinomas (HCC) with poor prognosis. The underlying mechanisms driving this phenotype of K19-positive HCC remain elusive.DesignClinicopathological value of K19 was compared with EpCAM, and α-fetoprotein, in a Caucasian cohort of 242 consecutive patients (167 surgical specimens, 75 needle biopsies) with different underlying aetiologies. Using microarrays and microRNA profiling the molecular phenotype of K19-positive HCCs was identified. Clinical primary HCC samples were submitted to in vitro invasion assays and to side population analysis. HCC cell lines were transfected with synthetic siRNAs against KRT19 and submitted to invasion and cytotoxicity assays.ResultsIn the cohort of surgical specimens, K19 expression showed the strongest correlation with increased tumour size (p<0.01), decreased tumour differentiation (p<0.001), metastasis (p<0.05) and microvascular invasion (p<0.001). The prognostic value of K19 was also confirmed in a set of 75 needle biopsies. Profiling showed that K19-positive HCCs highly express invasion-related/metastasis-related markers (eg, VASP, TACSTD2, LAMB1, LAMC2, PDGFRA), biliary/HPC markers (eg, CD133, GSTP1, NOTCH2, JAG1) and members of the miRNA family 200 (eg, miR-141, miR-200c). In vitro, primary human K19-positive tumour cells showed increased invasiveness, and reside in the chemoresistant side population. Functionally, K19/KRT19 knockdown results in reduced invasion, loss of invadopodia formation and decreased resistance to doxorubicin, 5-fluorouracil and sorafenib.ConclusionsGiving the distinct invasive properties, the different molecular profile and the poor prognostic outcome, K19-positive HCCs should be considered as a seperate entity of HCCs.

Prolonged febrile illnesses remain a diagnostic challenge. Despite the technological progress of the late 20th century, the origin of the fever remains elusive in many patients, especially in those with episodic fevers. Noninfectious inflammatory diseases emerge as the most prevalent diagnostic category.