The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 “polymorphic” SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model, MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors.

Hepatocellular carcinoma (HCC) is a highly malignant tumor, and chronic infection with hepatitis B virus is one of its major risk factors. To identify the proteins involved in HCC carcinogenesis, we used two-dimensional fluorescence DIGE to study the differentially expressed proteins in tumor and adjacent nontumor tissue samples. Samples from 12 hepatitis B virus-associated HCC patients were analyzed. A total of 61 spots were significantly up-regulated (ratio > 2, p < 0.01) in tumor samples, whereas 158 spots were down-regulated (ratio < ؊2, p < 0.01). Seventyone gene products were identified among these spots. Members of the heat shock protein 70 and 90 families were simultaneously up-regulated, whereas metabolismassociated proteins were decreased in HCC samples. The down-regulation of mitochondrial and peroxisomal proteins in these results suggested loss of special organelle functions during HCC carcinogenesis. Four metabolic enzymes involved in the methylation cycle in the liver were down-regulated in HCC tissues, indicating S-adenosylmethionine deficiency in HCC. Two gene products, glyceraldehyde-3-phosphate dehydrogenase and formimidoyltransferase-cyclodeaminase, were identified from inversely altered spots, suggesting that different isoforms or post-translational modifications of these two proteins might play different roles in HCC. For the first time, the overexpression of Hcp70/Hsp90-organizing protein and heterogeneous nuclear ribonucleoproteins C1/C2 in HCC tissues was confirmed by Western blot and then by immunohistochemistry staining in 70 HCC samples, suggesting their potential as protein tumor markers. In summary, we profiled proteome alterations in HCC tissues, and these results may provide useful insights for understanding the mechanism involved in the process of Proteomics analysis is currently considered to be a powerful tool for global evaluation of protein expression, and proteomics has been widely applied in analysis of diseases, especially in fields of cancer research. Quantitative protein expression profiling is a crucial part of proteomics, and such profiling requires methods that are able to efficiently provide accurate and reproducible differential expression values for proteins in two or more biological samples. Two-dimensional electrophoresis (2DE) 1 was a technique that was widely used for proteomics research. However, intergel variation and excessive time/labor costs have been common problems with standard 2DE. Two-dimensional (2D) DIGE might therefore be considered as one of the most significant advances in quantitative proteomics. Using the 2D DIGE approach, different samples prelabeled with mass-and charge-matched fluorescent cyanine dyes are co-separated in the same 2D gel, and an internal standard is used in every gel that has negated the problem of intergel variation (1). Moreover with the great sensitivity and dynamic range that is afforded by these dyes, 2D DIGE can give greater accuracy of quantitation than silver staining (2). It has been reported that the correlation betw...

The expression of many genes is altered in colon cancer, but the roles of these genes in carcinogenesis are unclear. Using real-time quantitative PCR, we demonstrated that several genes previously implicated in human colon cancer undergo altered expression in the APC min mouse adenomatous polyp, a precursor of cancer, as well as in normal-appearing surrounding mucosa. The five genes that were most highly up-regulated in mouse polyp were also significantly up-regulated in polyp-free colon mucosa. Similar changes occurred in morphologically normal mucosa of surgical sections taken from human cancer patients, frequently extending to the margins. Thus, morphologically normal colon mucosa in APC min mice and in human cancer patients is not metabolically normal. Altered gene expression in this tissue does not appear to result from a field effect because there was no correlation between extent of altered regulation and distance from polyp or tumor. Our data suggest that alterations of expression levels of these genes may be an early event in carcinogenesis and a marker of risk for the development of colon cancer.

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