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Going After Cancer


 As the systems biology community continues to improve the tools that it uses — the past year has seen particularly major advances in genotyping and sequencing applications — researchers are taking advantage of them in almost every field of study. In cancer, they've become a mainstay in research aimed at preventing and predicting cancer earlier. The National Cancer Institute estimates that as many as 50 percent to 75 percent of cancer deaths in the US are caused by smoking, physical inactivity, and poor dietary choices. From detecting biomarkers that signal tumor growth to profiling gene expression changes in tumors, large-scale biology techniques have become especially useful to scientists studying how cancers develop and spread.

This fourth annual cancer special issue of Genome Technology looks at how cancer research has advanced alongside these toolsets during the past 12 months. Genome-wide association studies exploded onto the scene in 2007, and one story examines their use in finding susceptibility genes in prostate cancer. Likewise, miRNAs have gained tremendous popularity this year, turning out to be major players in cancer; several stories take a look at where they fit. Whether it's compiling predictive SNP profiles, finding cancer biomarkers, or sequencing tumor transcriptomes, the stories here showcase some of the year's latest advances in cancer research.

MicroRNA: Predicting Poor Outcomes in Colon Cancer

In Curtis Harris' lab at the National Cancer Institute, Aaron Schetter is trying to figure out how to tell which colon cancer patients will respond well to treatment. The secret to their prognosis may lie in the particular tumor's microRNA. "My interests were in looking for small molecules as diagnostic biomarkers and therapeutic targets, and so the potential came on to work on this project on colon cancer — and microRNAs have huge potential as both biomarkers and therapeutics," Schetter says. 

To find which microRNAs might be associated with colon cancer prognosis, Schetter and his colleagues used microRNA arrays from Carlo Croce's lab at Ohio State University to screen colon cancer tumors. Croce's microarrays contained all of the human miRNAs that had been validated by that time — about 200 mi-RNAs, complete with replicates. Using those arrays, Schetter and his colleagues screened colon tumors from a Maryland cohort of patients and identified five miRNAs associated with colon cancer prognosis. They then had to validate those miRNAs. "By the nature of the screen, there's likelihood that there's going to be a lot of false positives," he says.

To double-check that the miRNAs they identified were indeed correlated with colon cancer prognosis, Schetter and his colleagues followed them up in another cohort, this one from Hong Kong, and another analytical method, RT-PCR. "We think it's pretty strong because we were using completely different methods for measuring, so it's not an artifact of the technique. On top of that, the populations are quite different," Schetter says. "If we can find a marker in both groups, it's likely that these markers might be applicable to other populations as well." Only one miRNA, miR-21, was validated as a marker for colon cancer prognosis in both cohorts.

It isn't the first time fingers have been pointed at miR-21. It is an oncomir. Other research groups found high expression levels of miR-21 in solid tumors and even showed that over-expressing miR-21 in a cell culture inhibits apoptosis — a key feature of any cancer cell. One possible regulatory target of miR-21 could be PTEN, a tumor suppressor gene in the Wnt pathway, hypothesizes Schetter, adding that PTEN is deleted or down-regulated in most colon tumors.

But could miR-21 be a biomarker for colon cancer prognosis? Harris' lab is still hard at work on it, but the theory is there. The major chemotherapy drug for colon cancer is 5-fluorouracil, whose mechanism of action includes inducing apoptosis in colon cells. From this study, high levels of miR-21, which inhibits apoptosis, predicted a poor clinical response to chemotherapy. "While we don't have data showing it, it actually creates a nice model. Increased levels of mir-21 can inhibit apoptosis; that could actually be the mechanism for resistance to 5-FU," Schetter says. That resistance to treatment, of course, proves to be a fairly clear indicator of poor prognosis. 

— CC

GWAS: Prostate Cancer and the Master Control Region

Genome-wide association studies have made their mark on many major diseases this past year, one of the most significant being cancer. In fact, according to NIH's Stephen Chanock, using GWAS to nail down the "genetic architecture" of breast, prostate, and colon cancers might happen as soon as 2009. Chanock has led several major collaborative studies during recent years, initiated in part by NCI's push to perform association studies for cancers of major public health importance. In his latest studies, published over the past year, Chanock found several unique regions correlated with risk for prostate cancer.

In a paper published in Nature Genetics last April, Chanock led a large-scale, collaborative genome-wide association study for prostate cancer as part of the Cancer Genetic Markers of Susceptibility project. His team looked at 550,000 SNPs across samples from 1,172 cases and 1,157 controls in European men and found a locus on chromosome 8q24 that confers, they estimate, about a  20 percent risk for men with this mutation. A locus on the same chromosome was previously identified, and the team found little evidence for linkage disequilibrium between the two. In a follow-up study done this year and published in Nature Genetics in February, the scientists confirmed the region on 8q24 plus another previously reported SNP in 17q, as well as several other novel susceptibility markers.

"We found a series of very exciting new places that no one ever had any idea that they were important in prostate cancer," Chanock says. The first study was more focused, looking specifically at chromosome 8q24 "where there was a lot of interest to begin with," he adds. "We saw that there was tremendous signal there. We followed that up and were able to dissect and recognize that there are a number of regions in that gene desert that are strongly associated with prostate cancer."

More so than finding links to prostate cancer, the results contribute to a growing body of research that has implicated various SNPs in more than one type of cancer. "There was a little bit known about one SNP, but we discovered a whole new region in 8q24," Chanock says of his work in prostate cancer. "Several other groups, in non-Caucasians, found yet another region next door to the one we discovered that's important for breast cancer. And when the colon cancer scans came out last summer, which we were part of, lo and behold, the new region we found for prostate cancer is the best hit [for] colon cancer. So clearly, breast, prostate, and colon all map to a region of 8q24." He believes this could be some sort of master region for cancer susceptibility mutations.

The ability of GWAS to identify regions that are not only implicated in cancer but can also be used as drug targets or for assessing clinical risk is what Chanock sees as the major strength of this type of study. However, determining the specific amount of risk each SNP confers, as well as what medical decisions can be made using this susceptibility data, are still hurdles to their utility.

"We're still very early on," Chanock says. "Many have rushed to make very interesting observations, but till we have a more comprehensive set of variants, I think the risk questions are still preliminary. The question is, at what point are they really ready for truly clinical application?" Like many, Chanock knows that there's no meaning in the data without studies linking the genes to their actual biological function in both causing cancers and determining the course tumors take in the body.

Now Chanock is starting a scan of another 5,000 cases and 5,000 controls, so by the end of the series of studies, his team will have scanned 20,000 patients. The goal is to be able to accurately identify a set of genomic regions that are strongly associated with both prostate and breast cancers.

"All told, there may be 12 to 15 regions in the genome that one calendar year ago no one knew about in being important in risk for prostate cancer," Chanock says.

— JS

Translational Research: Norway Unites Research, Industry

Taking drugs from the proverbial bench to the bedside is no easy task, as many companies are struggling to get their products approved by regulatory agencies and into the hands of prescribing clinicians. Norway's Oslo Cancer Cluster hopes to kick-start its translational research by putting an entire country's research forces behind it.

Funded in large part by the Norwegian government, the Oslo Cancer Cluster is a partnership among many researchers with the aim to translate Norwegian biomedical research into working therapeutics. There are nearly 40 members, including a broad array of both domestic and international pharmaceutical, small biotech, and startup companies; as well as partner researchers at the University of Oslo and affiliated hospitals and the Comprehensive Cancer Center at the Norwegian Radium Hospital. The cancer center offers significant clinical expertise and is where many of the cluster's larger phase I and phase II clinical trials are being conducted. The aim of the cluster is to give patients better and more immediate access to improved cancer therapies.

"You might characterize us as the triple helix model, trying to bridge the life science industry focusing on cancer, trying to connect with the research institutions and also the government," says Bjarte Reve, CEO of the Oslo Cancer Cluster. In fact, the Oslo Cancer Cluster was awarded Norwegian Centres of Expertise status by the Norwegian government in June 2006 and was given long-term funding totaling about 50 percent of its current support. The NCE program hopes to strengthen innovation and internationalization processes in collaborative projects such as this one.

"Our main objective is to accelerate the progress of developing new cancer medication and new cancer diagnostics," Reve says. Helping the process is the cluster's access to the Norwegian Cancer Registry, as well as significant nationwide participation in the national biobanks. These biobanks record not only genotypic information through blood samples from cancer patients across Norway, but they also collate the phenotypic information from the national registry in order to follow up on patients' status throughout their lifetimes.

The cluster's biggest resource is being able to draw on university research, says Jónas Einarsson, chairman of the board. Two examples of successful spinout companies are PhotoCure and DiaGenic, both founded in the late 1990s and now traded on the Oslo Stock Exchange. Both companies' products were based on research done within the cluster at university hospitals. PhotoCure markets therapies for skin cancer as well as a diagnostic for bladder cancer, and DiaGenic's test for early detection for breast cancer is due to hit the market this year. "The goal for the Oslo Cancer Cluster is to help with this translational research and speed up the process because time is money for our new companies," says Einarsson.

In 2007 the cluster had 63 projects in the clinical pipeline, whose weight they hope will attract other researchers from around the world. While the design of the cluster was modeled after large-scale collaborative translational research centers in the US — such as the MD Anderson Cancer Center and the Memorial Sloan-Kettering Cancer Center, with whom the Oslo Cancer Cluster is conducting collaborative clinical trials — the ultimate goal is to become a model for this type of center in Europe. Additionally, they hope to become a bridge for US companies looking to tap into both the clinical trials and clinical markets of Europe. By 2012, the cluster has plans to aggregate all the participating organizations into one physical location as well as to build a targeted science high school within the grounds.

 — JS

Protein Biomarkers: Silent Ovarian Cancer Gets a Voice

The symptoms of ovarian cancer usually come on at a late stage, when the tumor is already advanced. At that time, the five-year survival rate hovers between 20 percent and 25 percent. But if the tumor could be detected earlier, that survival rate could rise to between 60 percent and 90 percent, says Yale University's Gil Mor. To that end, Mor and his colleagues are developing a multiplexed protein biomarker test to detect ovarian cancer, even at those early stages, with 99 percent accuracy.

"The uniqueness of our test is that we have a group of proteins," says Mor, who is a professor of obstetrics, gynecology, and reproductive science at Yale. Starting from scratch, Mor and his colleagues identified 150 proteins — including cytokines, growth factors, and hormones — associated with cancer or the development of cancer. They made a microarray containing all of those proteins and then screened clinical samples from women with ovarian cancer to whittle those 150 proteins down to 35. After screening a second patient population, Mor and his colleagues weeded out non-specific proteins and were left with 10 proteins specifically linked to ovarian cancer.

Mor's group also took a different tack on what type of proteins to include as part of the test. Many current efforts to find protein biomarkers for cancer focus on proteins that the malignant mass itself produces. But early stage cancers do not produce a high level of proteins. "When the tumor is in early stages, I like to say it is like a little baby. It's producing so little," Mor says. "It's almost impossible, at least with the technology that we have now, to detect [what the tumor produces] in the peripheral blood."

By the time the tumor produces enough protein to be detected in the blood, it's at an advanced stage. "That is really too late," Mor says, noting that by this stage, the tumor can be seen on an ultrasound. To catch the cancer earlier, Mor included normal proteins on the panel. The tissue surrounding a tumor, he says, recognizes the malignant mass and reacts to it. "They respond in a way [that changes] the levels of these normal proteins and that can be detected in the blood," he says.

Originally, Mor and his colleagues created a panel of four proteins that, as ELISA tests, could detect ovarian cancer with 95 percent accuracy. But since ovarian cancer is a relatively rare disease, the false-positive rate needs to be low — about a 99.6 percent specificity — to prevent too many women from being misdiagnosed. So Mor improved the test, throwing aside the cumbersome ELISA to make a multiplex test with six proteins, including CA-125, the current marker for ovarian cancer which on its own is less than 60 percent sensitive in detecting early ovarian cancer.

Switching over to a multiplex test, rather than individual ELISAs, also sped up the diagnostic. "This multiplex technology allows us to study the six proteins in one single reaction with minimal amount of material. We need maybe 15 or 20 microliters of serum, and the whole test can be done in 24 hours," Mor says. With a sensitivity of 95.3 percent and a specificity of 99.4 percent, it is also more accurate.

Currently, Mor and his colleagues are finishing up a blinded validation study of their test. This study is looking at 2,000 patients and is being done in conjunction with NCI's early detection research network and LabCorp, which has licensed the technology. According to Mor, LabCorp plans to make the test commercially available soon.

— CC 

Sequencing: The Transcriptome View of Mesothelioma 

By delving into the expressed sequences of mesothelioma tumors, researchers hope to find more ways to treat patients with this asbestos-induced cancer. A team led by Brigham and Women's Hospital's chief thoracic surgeon David Sugarbaker recently sequenced the transcriptome of four mesothelioma tumors using 454 Life Sciences' GS20 technology.

To get at the transcriptome, Sugarbaker and his collaborators first developed a pipeline from the surgical suite to tissue processing and mRNA extraction to 454 sequencing and analysis. "Going forward, anyone can take a patient, get a good quality biopsy, go through the steps, and at the end, identify mutations relevant for that individual patient in six or eight weeks," says Raphael Bueno, a member of the team and the associate chief of thoracic surgery at Brigham and Women's.

Mutations in mesothelioma tumors are far from straightforward. Of the four tumors sequenced, each had a different set of mutations. After mRNA was extracted from the four mesothelioma tumors and sequenced as cDNA, the results from those 266 megabases of cDNA were then analyzed and validated. Sugarbaker and Bueno's collaborators from New Mexico's National Center for Genome Resources analyzed the sequence reads using their new software tool, Alpheus. Alpheus mapped the reads to NCBI's RefSeq mRNA database. From that, they found 15 novel mutations, seven of which were point mutations, but all of which differed from one another. RT-PCR then confirmed the 454 findings.

Sugarbaker wasn't too surprised. In the late 1980s and early 1990s, he made karyotypes of mesothelioma tumors. "When you look at the karyotype, it's a very, very disordered karyotype with lots of deletions, translocation. It's a very wildly mixed-up tumor," he says. "We expected to see a wide variation of genetic abnormalities in these tumors."

Their findings also confirm what others have reported. "Indeed, tumors are different. People have different sets of mutations in different tumors, even though the tumors are histologically identical," adds Bueno.

But four tumors aren't enough to get a full sense of mutations that can crop up in mesothelioma. "I think the next step is to sequence a few hundred more transcriptomes and really sort out pathways and say, 'Aha! These are the pathways that are messed up in these particular tumors,'" says Bueno.

As they make a library of mutations, Sugarbaker hopes that patterns will begin to emerge. "We'll then begin to, I think, identify clusters to target for drug intervention that would go beyond the single mutation," he says. Right now, there are drugs such as herceptin that target patients with a particular mutation, but a drug that targets a particular cluster of mutations — perhaps ones that all affect the same pathway — could reach a broader number of patients, Sugarbaker says.

Bueno adds, "[We can] take the drugs off the shelf that affect these pathways and try them on."

— CC

MicroRNA: Tracking the p53 Effect

When it comes to solving the cancer puzzle, there are a lot of missing pieces. Several studies that came out last year found one piece of the puzzle: that transcription factor p53 influences several microRNAs of the same family.

One paper, published last August in Current Biology, found that the miRNA34 family is directly regulated by p53. p53 is known to protect cells from cancer, playing a pivotal role in initiating various intracellular signaling cascades that work against DNA damage and other carcinogenic factors. They also found genes to be directly regulated by miRNA34, with cell-cycle regulatory genes being the most important. Greg Hannon, Josh Mendell, and others published similar findings.

"Essentially, all of these papers, I think, point to the notion that p53 regulates the expression and activity of these particular transcripts," says Eric Fearon, lead author and professor at the University of Michigan. "The targets of the microRNA, that is to say the protein targets, are sort of less well understood in terms of how these microRNAs play a role in regulating cell cycle progression or survival of cells."

With the tools available today, it's more straightforward than ever to identify which molecules might be involved in cancer. However, Fearon says, determining just how individual miRNAs play a role in expressing cancer phenotypes — what are their targets and how big of an effect does each individual miRNA have — is the bigger challenge. "In terms of figuring out how this fits into what's a very big puzzle, for how does p53 normally regulate the behavior of cells in response to cellular stresses, I think is certainly one of the many avenues that needs to be pursued," he says. "What other signaling pathway factors regulate these microRNAs besides p53 is yet another thing. Ongoing work in our lab is trying to look at the physiologic role of these microRNAs in cell cycle control and response to stress using mouse genetic knockout approaches."

Using a combination of predictive bioinformatics algorithms and ChIP-chip data, Fearon and his colleague Guido Bommer took a different tack, looking for members of the same family of miRNAs whose transcription might be regulated by p53. They found highly conserved p53 binding sites in the regulatory regions of the miRNA34-a gene on chromosome 1p, and for miRNA34-b and -c on chromosome 11q. Follow-up cellular and mouse assays, as well as work using reporter genes, showed that p53 does indeed regulate transcription of these three genes. Next, they engineered cells to over-express these miRNAs and found effects on cell proliferation and survival. Finally, they attempted to find which genes these miRNAs regulated.

Considering the number of genes that p53 regulates, and the number of targets that these miRNAs might have, their work and others' is only just beginning to elucidate the entire mechanism of just how p53 regulates the cellular stress response. "p53 really [is] a hub for connecting cellular responses to stress to lots of downstream things, and if you only knock out one of the spokes, the wheel doesn't fall apart," Fearon says.

Fearon thinks the "sheer complexity" of cancer is one of the reasons it's so difficult to pin down. Cancer cells can be, and often are, genetically heterogeneous across tumors, and when tumors migrate to different parts of the body, the mutations they sustain can be different as well. Still, Fearon believes that knowing the signaling pathways involved isn't enough; learning more about how cancer cells resist therapies through genetic mutation is key. "The question is, do we need to understand all of the complexity before we'll have definitive new insights in how to treat cancer? And the answer is certainly no."

— JS

The Scan

Genome Sequences Reveal Range Mutations in Induced Pluripotent Stem Cells

Researchers in Nature Genetics detect somatic mutation variation across iPSCs generated from blood or skin fibroblast cell sources, along with selection for BCOR gene mutations.

Researchers Reprogram Plant Roots With Synthetic Genetic Circuit Strategy

Root gene expression was altered with the help of genetic circuits built around a series of synthetic transcriptional regulators in the Nicotiana benthamiana plant in a Science paper.

Infectious Disease Tracking Study Compares Genome Sequencing Approaches

Researchers in BMC Genomics see advantages for capture-based Illumina sequencing and amplicon-based sequencing on the Nanopore instrument, depending on the situation or samples available.

LINE-1 Linked to Premature Aging Conditions

Researchers report in Science Translational Medicine that the accumulation of LINE-1 RNA contributes to premature aging conditions and that symptoms can be improved by targeting them.