The full potential of gene-expression profiling of cancer has been hindered in part by technical limitations — in particular, the requirement of frozen material for analysis. Although frozen tissues are increasingly being banked at tertiary care centers, the duration of clinical follow-up of these collections is usually short, and the vast majority of tumor-biopsy specimens and resections are performed outside of major research hospitals. There is therefore a need for methods that allow for the genomewide expression profiling of formalin-fixed tissue samples, which are routinely collected in the clinical setting. Such approaches have been described,17
but their extensive validation has yet to be reported. We describe here a DASL-based method capable of profiling approximately 6000 human transcripts, and we have tested the method on more than 2000 formalin-fixed, paraffin-embedded blocks collected as long as 24 years ago. Through the assay of 6000 genes across the genome that show maximal variation in expression, this approach is expected to capture the bulk of transcriptional differences in any collection of samples. However, recent increases in array density support the analysis of all human genes on a single array (whole-genome DASL assay, Illumina).
The DASL-based discovery method that we describe here should be distinguished from candidate-gene profiling methods based on the reverse transcriptase (RT)-PCR assay, such as those used in the commercially available OncotypeDx test for determining the prognosis in patients with breast cancer.18
Whereas standard RT-PCR methods can measure a small number of transcripts in formalin-fixed, paraffin-embedded samples, genomewide discovery studies are not feasible with the use of RT-PCR–based methods. In addition, we speculate that the use of formalin-fixed, paraffin-embedded tissue specimens will aid the transition from exploratory research to clinical implementation. We applied the DASL profiling method to an increasingly important challenge in the care of patients with hepatocellular carcinoma. Tumors are often small at the time of diagnosis (owing to increased surveillance and advanced imaging in patients at risk), and existing prognostic factors are less informative for patients with small tumors than for those with larger tumors.
We did not observe a significant association between the expression profiles of the tumors themselves and the outcome for patients with surgically resected early hepatocellular carcinoma. In contrast, others have described tumor-derived prognostic signatures for hepatocellular carcinoma.15,19
The populations of patients in those studies, however, tended to have more advanced disease. Our training set primarily exhibited a pattern of late recurrence that is typical of small tumors.1,9
Accordingly, it is likely that early recurrence (reflecting locally invasive and incompletely resected tumor) is associated with molecular features of the primary tumor, but such features are not associated with late recurrences, which seem to result from new primary tumors arising in a damaged organ (the “field effect”) rather than the proliferation of residual tumor cells derived from the original tumor.
Also supporting the concept that late recurrence of hepatocellular carcinoma represents new primary tumors in patients at risk, we found little correlation between the molecular characteristics of tumors resected at initial diagnosis and those from the same patients at the time of recurrence. In particular, the results of clonality analysis indicated that the late recurrences of hepatocellular carcinoma tended to derive from a different clone than the preceding primary tumors. In addition, the obvious measures of liver damage (e.g., the extent of cirrhosis and the Child–Pugh stage20
) were not associated with survival in our study, given that we restricted our analysis to patients with preserved liver function. Our findings indicate a field effect, in which environmental exposure (e.g., viral infection) leads to an increased potential for future malignant transformation. This has in general been overlooked by genomic approaches to studying cancer that have focused only on tumor cells. Our results suggest that a gene-expression signature can serve as a sensitive “readout” of the biologic state of the liver in at-risk patients. It is likely that the survival signature reflects the extent of liver damage and the presence or absence of a proinflammatory milieu, which is mediated in part by gene products involved in an inflammatory response. A heritable basis for the signature, although improbable, cannot be ruled out. Additional work is needed to fully understand the biologic basis of the signature.
Further clinical validation of the survival signature will be needed before it is introduced into clinical practice; our observation that the signature is associated with the outcome across heterogeneous populations of patients is encouraging. We envision the use of this test to identify the patients at highest risk for recurrence of hepatocellular carcinoma and to target intensive clinical follow-up or chemopreventive strategies in such patients.21
This article (10.1056/NEJMoa0804525) was published at www.nejm.org
on October 15, 2008.