Cancer Genomics: Special Issue Published By Genome Research

Main Category: Breast Cancer
Also Included In: Colorectal Cancer;  Genetics
Article Date: 03 Feb 2012 - 1:00 PST


Genome Research publishes online and in print a special issue entitled, "Cancer Genomics," highlighting insights gained form cutting-edge genomic and epigenomic analyses of cancer.

Included in this special issue are novel biological insights gained from genomic analyses of pancreatic cancer, ovarian cancer, and melanoma, including, functional genomic analyses of breast cancer genes, large scale colorectal and breast cancer epigenomics, advances in methodology identifying driver genes and networks in cancer, in genome-wide cancer association analyses, and using next-generation sequencing technology to detect driver mutations. Additionally, the issue includes unique perspectives from leaders in the field on the translation of cancer genomics to improved outcomes in medicine. The following sections highlight several of the papers published in the issue.

1. Whole-genome and whole-exome sequencing: Searching for the drivers of cancer

Cancer is believed to arise through the accumulation of genetic and epigenetic mutations that give tumor cells an advantage over normal tissue, driving the proliferation and spread of disease. Next-generation sequencing technologies are ushering in a new era of discovery in cancer genomics, shedding light on the genomic alterations underlying various cancers. And as sensitive and high-resolution sequencing is rapidly becoming affordable, routine clinical sequencing of whole exomes and whole genomes of cancers is nearly within reach.

In a rare opportunity to sequence the genome of a primary and a corresponding metastatic melanoma in a patient who had not received prior treatment with therapeutic DNA-damaging agents, Turajilic and colleagues have characterized somatic mutations and genomic structural variation in a primary acral melanoma, a rare sub-type of cutaneous melanoma that can arise on the non-hairy skin of the palms of the hands, soles of the feet, and in nail beds, and also sequenced its lymph node metastasis. By mapping the mutational landscape of the tumor and its metastasis, the study presents new genetic evidence to support the hypothesis that acral melanoma is a distinct melanoma subtype. Interestingly, although acral skin is perceived to protected from the sun, the group observed a mutational signature consistent with UV-damage.

However, until sequencing costs are low enough such that whole-genome sequencing is routine, strategies such as whole-exome sequencing, in which protein-coding genes are selectively captured and analyzed, are being employed to detect gene variants that could be driving progression of diseases such as cancer.

 

Wang et al. have performed whole-exome sequencing of 15 pancreatic ductal adenocarcinoma cell lines and matched normal tissue samples. Pancreatic cancer is one of the most lethal human cancers, claiming the lives of 95% of patients within five years of diagnosis. The authors describe how their study uncovered widely varying mutation rates between the cell lines, and notably, a significant correlation between loss of one copy of the MLH1 gene, involved in DNA repair, and the rate of small insertions and deletions (called "indels") in the genome of pancreatic cancer cell lines. Although loss of a copy of the chromosome region where MLH1 resides has been widely described in cancers, this is the first time that MLH1 has been associated with indel mutation rate. The whole-exome sequencing analysis showed how loss of one of the two copies of the MLH1 gene from the genome raised the rate of indel mutations ten-fold, which disrupted several well-known cancer genes, including TP53.

References:
Turajlic et al., Whole genome sequencing of matched primary and metastatic acral melanomas. Genome Res. doi:10.1101/gr.125591.111
Wang et al., Whole-exome sequencing of human pancreatic cancers and characterization of genomic instability caused by MLH1 haploinsufficiency and complete deficiency. Genome Res. doi:10.1101/gr.123109.111

2. Circulating free DNA holds clues to cancer diagnosis and risk of relapse
Despite recent advances that have improved breast cancer survival rates, means of monitoring residual disease and the risk for relapse with metastatic cancer have remained elusive. Circulating free DNA (cfDNA), present in the blood at low levels in healthy individuals but elevated in patients suffering from different cancers, has been suggested as a means of diagnosing disease. Because elevated cfDNA can also occur in benign disease, its utility in the clinic has been limited and thus there has been no reliable method using blood to diagnose patients with primary breast cancer or monitor relapse following treatment.

However, cfDNA might still be a key to efficient and reliable diagnosis of breast cancer and effective monitoring of potential for relapse. Shaw and colleagues recognized that a genomic analysis of cfDNA could shed light on the genetic signatures of disease progression. Utilizing genotyping technology that identifies single nucleotide variations and copy number variations in cfDNA and the DNA of primary tumors, the research group was able to distinguish between healthy individuals and patients with breast cancer. "CfDNA analysis can predict whether a patient has evidence of dormancy or not, and intriguingly, may predict the onset of relapse," said Dr. Jacqueline Shaw of the University of Leicester and lead author of the report.

The research team's analysis of patients on follow-up after treatment showed that even 12 years after diagnosis and despite no clinical evidence of disease reoccurrence, breast cancer patients still have cfDNA with genetic signatures of their primary cancer, suggesting dormancy of the cancer or minimal residual disease. Further cfDNA monitoring could predict relapse. "This should enable clinicians to target therapy earlier, at a time when disease is potentially curable," Shaw noted.

Reference:
Shaw et al., Genomic analysis of circulating cell free DNA infers breast cancer dormancy. Genome Res. doi:10.1101/gr.123497.111

3. Epigenomic analyses shed new light on breast, colon, and prostate cancers
Epigenetic modifications (cellular changes that alter gene expression, phenotype, and disease by mechanisms other than variation in DNA sequence) are increasingly being recognized for playing a role in diseases including cancer. Published in this special issue of Genome Research are four studies that have investigated the role of DNA methylation in cancer, a chemical modification of DNA associated with gene silencing, shedding new light on the biology of breast cancer, colon cancer, and prostate cancer.

DNA methylation and chromatin (the DNA/protein complex that regulates gene expression and DNA replication) are both know to be altered in cancer, but little is known how these two factors play a coordinated role in cancer progression. In this issue, Hon et al. have used next-generation sequencing technology to investigate this interplay in breast cancer. Surprisingly, although they observed widespread loss of DNA methylation that would be predicted to increase gene expression, they find that the genes are silenced by the formation of gene-repressing chromatin. This mechanism could play an important role in breast cancer progression by repressing genes that normally suppress tumors.

Colorectal cancer is a complex disease, classified into multiple subtypes by genetic and epigenetic alterations in the cancer genome. Two studies published in this issue investigate methylation and the classification of colon cancers. The first of these studies, by Hinoue et al., performed comprehensive DNA methylation profiling of colorectal tumor genomes. The group identified four distinct DNA methylation subgroups of colorectal cancer, and provided new insight into the role of DNA hypermethylation in gene silencing critical for tumor suppression. The report by Xu and colleagues also delves into DNA hypermethylation in colorectal cancer, describing the mapping and comparison of DNA methylation profiles by genome sequencing. The group found that certain sites of the genome are prone to hypermethylation in colorectal cancer, with a certain class of tumors prone to even more extensive hypermethylation, suggesting specific defects in the control of this epigenetic modification.

Chemical modification of chromatin, the complex of DNA and protein that packages the genome within the nucleus, also plays a critical regulatory role in gene expression in healthy and disease states. In this issue, Valdes-Mora and colleagues have investigated the interplay between a specific chromatin modification, H2A.Z acetylation, and other epigenetic modifications including DNA methylation in prostate cancer. This work reconciles conflicting evidence in the field regarding the role of H2A.Z acetylation, and further shows for the first time that it is a critical modification associated with gene activity in normal cells, and epigenetic deregulation of genes in cancer.

References:
Hon et al., Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Res. doi:10.1101/gr.125872.111
Hinoue et al., Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Genome Res. doi:10.1101/gr.117523.110
Xu et al., Unique DNA methylome profiles in CpG island methylator phenotype colon cancers. Genome Res. doi:10.1101/gr.122788.111
Valdés-Mora et al., Acetylation of H2A.Z is a key epigenetic modification associated with gene deregulation and epigenetic remodeling in cancer. Genome Res. doi:10.1101/gr.118919.110

4. Cutting-edge methods to detect the genes and networks that drive cancer
The special Cancer Genomics issue of Genome Research also features cutting-edge methodological advances, including three reports that address the problem of identifying the genes, networks, and pathways that drive cancer.

A significant challenge to the identification of genetic alterations that lead to cancer is the experimental determination of which mutations are driving cancer and which mutations are random "passengers." Further complicating discovery of drivers is that driver mutations can target multiple cellular pathways and processes, and each cancer can present different mutations that are sufficient to disrupt critical pathways.

Two reports in this issue present new computational strategies to finding biological pathways that are commonly disrupted by diverse genomic alterations. Vandin and colleagues developed a pair of computational strategies collectively called Dendrix to spot groups of genes that constitute "driver pathways." Applying Dendrix to three cancer studies, Vandin et al. successfully identify sets of genes that are mutated in large numbers of patients, including well-known cancer-related pathways such as Rb, p53, mTOR, and MAPK.

Ciriello and colleagues have developed the Mutual Exclusivity Modules in Cancer (MEMo) method to identify previously unrecognized oncogenic pathways. Applying MEMo to datasets of genomic alterations in glioblastoma and ovarian cancer, MEMo successfully identified known oncogenic pathways and presented evidence for a new hypothesis for the striking genomic instability of ovarian tumors. Dendrix and MEMo will be particularly useful for the interpretation of very large cancer genome sequencing studies, many currently underway.

Also in this issue, Xiong et al. present Gene Set Association Analysis (GSAA), a statistical framework that integrates and simultaneously analyzes the two dominant strategies for identifying sets of genes or pathways associated with disease: genetic variation analysis and gene expression analysis. Applied to the analysis of diseases such as glioblastoma, GSAA identified pathways known to be associated with disease, and also predicted novel pathway associations such as the association of perturbations in the ABC transporter family with glioblastoma.

References:
Vandin et al., De novo discovery of mutated driver pathways in cancer. Genome Res. doi:10.1101/gr.120477.111
Ciriello et al., Mutual exclusivity analysis identifies oncogenic network modules. Genome Res. doi:10.1101/gr.125567.111
Xiong et al., Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets. Genome Res. doi:10.1101/gr.124370.111

Cancer Genomics: Special Issue Published By Genome Research