Gene Expression in Fixed Tissues and Outcome in Hepatocellular Carcinoma

By Yujin Hoshida, A. Villanueva, M. Kobayashi, J. Peix, Derek Y. Chiang, Amy L. Camargo, Supriya Gupta, Jamie M Moore, Matthew J Wrobel, Jim Lerner and 18 more. New England Journal of Medicine, 2008

1,244 citations recorded by the source corpus.

Background It is a challenge to identify patients who, after undergoing potentially curative treatment for hepatocellular carcinoma, are at greatest risk for recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissue. Methods We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed, paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. Results The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of tissue samples from 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (P=0.04). Conclusions We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlated with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma.

Subfields: Cancer Research, Hepatology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b54018573351b8b560f0540a584bc11b8d4f4d06

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Citations in the corpus

EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. (2012, background): “None of the biomarkers tested so far fulfil these criteria in HCC, but four just require external validation by independent groups: gene signatures or biomarkers from the tumor (EpCAM signature, G3-proliferation subclass, and miR-26a) [77,135,136] and adjacent tissue (poor-survival signature) [137].”
Liver sinusoidal endothelial cells: Physiology and role in liver diseases. (2017, background): “from patients with HCC has a higher prognostic value of than gene expression in HCC [110].”
microRNA as Biomarkers and Diagnostics (2016, background): “…Exosomal miRNAs as Disease Biomarkers miRNAs have shown high stability in formalin-fixed, paraffinembedded tissues from hepatocellular carcinoma (Hoshida et al., 2008), lung cancer (Barshack et al., 2010), melanoma (Barshack et al., 2010), pancreatic cancer (Szafranska et al., 2008), papillary…”
A Unique Metastasis Gene Signature Enables Prediction of Tumor Relapse in Early Stage Hepatocellular Carcinoma Patients (2010, neutral): “It is believed that de novo development of primary HCC in the remnant liver occurs with a lower frequency (12, 13).”
Integrative Transcriptome Analysis Reveals Common Molecular Subclasses of Human Hepatocellular Carcinoma (2009, neutral): “AFP (ng/mL) c 50 [14,332] 171 [27,1,251] 13 [5,43] <0.”
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI (2014, methodology): “Unsupervised clustering of patients in an effort to identify distinct prognosis groups has been done by examining genome-wide mRNA expression levels profiled with microarrays [1, 2].”
EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. (2012, background): “None of the biomarkers tested so far fulfil these criteria in HCC, but four just require external validation by independent groups: gene signatures or biomarkers from the tumor (EpCAM signature, G3-proliferation subclass, and miR-26a) [77,135,136] and adjacent tissue (poor-survival signature) [137].”
Promotion of Hepatocellular Carcinoma by the Intestinal Microbiota and TLR4 (2012, background): “These results are consistent with previous findings that gene expression profiles in non-tumor liver tissue, including gene sets related to NF-κB, TNFα and interferon signaling - all downstream targets of TLR4 - are crucial determinants of tumor recurrence whereas tumor profiles have no prognostic v”
The Role of Cancer-Associated Fibroblasts and Fibrosis in Liver Cancer (2016, background): “Accordingly, hepatic gene expression in surrounding nontumor tissue rather than in tumors themselves determines survival in patients undergoing potentially curative treatment for HCC (10), suggesting that the environment in which HCC arises exerts a major influence on tumor development and growth.”