Whole genome sequencing; not ready for prime time

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(Reuters Health) - Routine genome-wide screening of cancers is likely a long way off, a new paper says.

The technology, known as next-generation sequencing, promises to revolutionize doctors' understanding of cancer and underpins perhaps the biggest paradigm shift taking place in cancer research today: the growing emphasis on a cancer's genetic makeup, rather than its location within the body.

Understanding the genetic makeup of an individual patient's tumor may allow physicians to pick the drug that best targets that specific tumor, as well as recognize when a tumor has developed resistance to the drug through new genetic mutations.

"Next-generation sequencing is especially promising in cancer because in a single test, one can interrogate all clinically relevant cancer genes for all types of genomic alterations, including sequence mutations and chromosomal rearrangements," Dr. Michael Berger, a geneticist at Memorial Sloan-Kettering Cancer Center in New York City, told Reuters Health in an email.

There are several different specific screening technologies that are considered "next-generation" - but all share the ability to sequence entire human genomes in a matter of days. When applied to cancer, the technology is used to screen the entire genome of cancer cells.

By some measures, this promise is already being realized. For example, last year The Cancer Genome Atlas Research Network used genome-wide screening of breast cancer tumors to demonstrate that there are four main breast cancer types defined by differing genomic and epigenetic mutations. The study showed that individual breast cancers have many genetic differences from each other but that one subgroup of breast cancers, basal-like breast cancer, was similar genetically to serous ovarian cancer.

Cancer cells present unique and complex challenges, they note. Because they are genetically so different from normal human tissue, there is not always a 'reference sequence' against which to compare the tumor DNA. There are also frequent chromosome-scale as well as epigenetic changes, and even significant genetic differences among cells within the same tumor, an issue specific to cancer cells known as tumor heterogeneity.

The authors of the new paper, writing online July 25 in the British Journal of Cancer, pointed out that this complexity creates a number of problems that must be solved before next-generation sequencing is a common part of cancer care.

One of the first issues is developing the algorithms that are used to map the genome.

"The computational challenges involved in analyzing and storing clinical (next-generation sequencing) data cannot be overstated," said Dr. Berger, who wasn't involved in the new study. "Better algorithms must be developed to reliably and accurately detect mutations in heterogeneous tumors."

In genome-wide sequencing, a seemingly minuscule misstep in the analysis could have massive consequences. For example, say the authors of the new paper, led by Dr. Danny Ulahannan of the Wellcome Trust Center for Human Genetics in Oxford, UK, "the sheer quantity of data means that getting 0.01% of the human genome wrong would correspond to 300,000 errors scattered along the three billion base pairs."

Dr. Lynda Chin, the chair of Genomic Medicine and scientific director of the Institute for Applied Cancer Science at MD Anderson Cancer Center, told Reuters Health this is often an overlooked problem.

"One barrier that is often overlooked or underestimated from the clinical side is the technical challenge of generating high-quality (next-generation sequencing) data," Dr. Chin said. "There is a sense that generating (the data) is easy, and it is the analysis that is hard. I would disagree, as I believe that the technology is still unstable, for lack of a better word, not yet turn-key, and no matter how good the analytics-interpretation become, if the data is poor quality, the result will be poor."

And mapping the genome is really only the first step. The next step is figuring out which mutations are relevant to the development of cancer and whether they can be targeted with a drug.

"I agree with the obvious barriers of interpretation. Not just analytically that we need improved algorithms, (but) more importantly, more knowledge and understanding of what each alteration means and how each event impact on clinical decision," Dr. Chin said.

The advances will require a "cultural change" in cancer research, Dr. Chin said, that makes "patient-oriented genomic research a standard, rather than a heroic effort by a researcher."

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Next-generation sequencing (NGS) technologies have come a long way since 1977 when Frederick Sanger developed chain-termination sequencing, but are they ready for prime time in drug selection?

Researchers have realized that cancer biology is driven by signaling pathways. Cells speak to each other and the messages they send are interpreted via intracellular pathways known as signal transduction. Many of these pathways are activated or deactivated by phosphorylations on select cellular proteins.

Sequencing the genome of cancer cells is explicitly based upon the assumption that the pathways - network of genes - of tumor cells can be known in sufficient detail to control cancer. Each cancer cell can be different and the cancer cells that are present change and evolve with time.

Although the theory behind inhibitor targeted therapy is appealing, the reality is more complex. Cancer cells often have many mutations in many different pathways, so even if one route is shut down by a targted treatment, the cancer cell may be able to use other routes.

In other words, cancer cells have "backup systems" that allow them to survive. The result is that the drug does not affect the tumor as expected. The cancer state is typically characterized by a signaling process that is unregulated and in a continuous state of activation.

In chemotherapy selection, genotype analysis (genomic profiling) examines a single process within the cell or a relatively small number of processes. All a gene mutation study can tell is whether or not the cells are potentially susceptible to a mechanism of attack. The aim is to tell if there is a theoretical predisposition to drug response.

It doesn't tell you the effectiveness of one drug (or combination) or any other drug which may target this in the individual. There are many pathways to altered cellular function. Phenotype analysis (functional profiling) measures the end result of pathway activation or deactivation to predict whether patients will actually respond (clinical responders).

It measures what happens at the end, rather than the status of the individual pathway, by assessing the activity of a drug (or combinations) upon combined effect of all cellular processes, using combined metabolic and morphologic endpoints, at the cell population level, measuring the interaction of the entire genome.

Should oncologists begin using deep genome sequencing in their clinical practice? At the annual meeting of the European Society for Medical Oncology, two key opinion leaders battled it out over this topic in a debate.

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At ESMO, experts assess the clinical use of genome sequencing

Vienna—Should oncologists begin using deep genome sequencing in their clinical practice? Next-generation sequencing (NGS) technologies have come a long way since 1977 when Frederick Sanger developed chain-termination sequencing, but are they ready for prime time? At the annual meeting of the European Society for Medical Oncology, two key opinion leaders battled it out over this topic in a debate.

The Argument for Deep Genome Sequencing

Arguing the pro position, Fabrice Andre, MD, PhD, of the Institut Gustave Roussy in Villejuif, France, said that embracing deep sequencing in daily clinical practice is not only the right thing to do, it is a necessity. The number of genetic biomarkers known to influence patient outcomes and care has risen dramatically in recent years and is only expected to grow, he said.

“The current system is not sustainable for hospitals and academic centers,” said Dr. Andre. “It’s not possible for [them] to run more than 10 bioassays per patient. We need to move to multiplex technology.”

For breast cancer, he said, clinicians can run tests for ER/HER2, TOP2A, FGR1, IGFR1R, EGFR, PAK1, BRCA1, CYP2D6, PTEN and PI3KCA among others. With whole genome sequencing, “you can assess all the genes that you want,” said Dr. Andre. “When you do one test for each biomarker, each biomarker has a cost. Keep in mind that three FISH [fluorescence in situ hybridization] is equal to the same cost of one whole genome CGH [comparative genomic hybridization] array.”

Whole genome sequencing also offers a number of other potential advantages. High throughput approaches can identify a large number of rare targetable gene alterations. This is increasingly important as researchers find genetic alterations that exist in 1% or 2% of patients. The technology also can capture minority clones that may be hard to identify when there is a low percentage of tumor cells in a sample. The next-generation sequencers have been proven to be accurate and they do not need large samples of tissue. Dr. Andre pointed out that some protein-based assays, which are used because they are less expensive than FISH, are not reliable. One study found that the immunohistochemistry test for the HER2 protein was accurate only 81.6% of the time (J Clin Oncol 2006;24:3032-3038, PMID: 16809727).

The “robust” deep sequencing technology is already being used for patient care at academic centers. One such example is the MOSCATO trial, which began in fall 2011. This trial enrolled 120 patients with difficult-to-treat cancers and is using whole genome sequencing to identify potential therapeutic targets. Once a target has been identified, patients receive targeted therapy in a clinical trial if one is available. The turnover time for sequencing is 15 days and the total cost is 1,500 euros, or roughly $2,000 per patient.

The cost of technology is expected to decrease dramatically in the next few years. By the end of 2012, Oxford Nanopore Technology is expected to launch a technology that is the size of a USB drive and will offer whole genome sequencing in 15 minutes for less than $1,000. Dr. Andre argued that deep sequencing will be less expensive than a multiplicity of tests.

He pointed to a case study recently described in the Journal of Thoracic Oncology as an example of a success story (2012;7:e14-e16). In the case report, a 43-year-old never smoker with lung cancer had tested negative for EML4-ALK on the approved companion genetic test for crizotinib (Xalkori, Pfizer). Sensing that an oncogenic genetic driver was spurring the patient’s cancer, clinicians ordered deep sequencing and identified a novel ALK fusion. The patient was treated with crizotinib and was recently reported to have had a complete response.

“In the context of prospective cohorts, but not clinical trials, I think we need to deliver NGS in order to detect a high number of rare, relevant genomic alterations and then treatment can be done in the context of Phase I trials or drug access programs,” said Dr. Andre.

The Argument Against Deep Genome Sequencing

According to Kenneth O’Byrne, MD, a consultant medical oncologist at St. James Hospital and Trinity College Dublin, Ireland, Dr. Andre is jumping the gun. “He makes the fundamental error that all people who are enthusiastic about new technologies always make and that is the non-application of evidence-based medicine,” Dr. O’Byrne said. “Deep sequencing is a fantastic tool, but it is a research toy and an expensive toy at the moment. For day-to-day practical medicine, we have to go by evidence base.”

Dr. O’Byrne cast doubt on Dr. Andre’s success story example. “They treated the patient with crizotinib and made the false conclusion that the ALK rearrangement they detected was responsible for the response. Do we know if that patient expressed MET? Is there any other reason [he] may have responded to crizotinib?” Dr. O’Byrne said.

He agreed that the cost of the sequencing technology was decreasing, but argued that analysis would remain expensive. He argued that the clinical benefit of identifying genetic drivers is still uncertain.

“I would argue that in lung cancer, and indeed in almost every other tumor, there are only a few proven genetic alterations that can be identified that actually affect the way we treat our patients in clinic,” Dr. O’Byrne said. “EGFR [epidermal growth factor receptor] mutations and ALK rearrangements are the only validated predictive biomarkers in NSCLC [non-small cell lung cancer].” He pointed out that these affect only 15% of lung cancer patients, and although there are targeted agents available, the jury is still out on whether the drugs that target these mutations improve survival.

As an example of this, he pointed out that an interim analysis of the PROFILE 007 trial presented at the ESMO meeting (abstract LBA1) showed that although crizotinib increased progression-free survival by 4.7 months compared with chemotherapy, there was no difference in overall survival. “If you look at all of the EGFR TKI [tyrosine kinase inhibitor] randomized controlled trials versus cytotoxic chemotherapy in EGFR mutation–positive disease, there has yet to be a proven [overall] survival benefit, despite obvious clinical benefits,” Dr. O’Byrne said. Researchers say the lack of overall survival advantage in many of these trials can be blamed on the large numbers of patients who cross over to the experimental therapy. “The argument is crossover, but we don’t know that yet,” he said.

Dr. O’Byrne urged caution, as several years ago, it was thought that tumor angiogenesis inhibitors would be the salvation of lung cancer patients and that did not happen. There was clear evidence that new blood tumor vessels were associated with poor outcome, but when researchers tested a slew of antiangiogenic TKIs in patients with lung cancer, none of them worked. These included apatinib, axitinib, cedarinib, motesanib, pazopanib, sorafenib, sunitinib and vandetanib. “There is still some promise that some of these might break through,” Dr. O’Byrne said, pointing to Boehringer Ingelheim’s BIBF1120. “But to date, we’ve spent billions of euros proving that many of these are of no value.

“In my view, and I feel this quite strongly, predictive biomarker tests must undergo validation and quality assurance before they are used rou- tinely in clinical practice,” Dr. O’Byrne said. “Deep DNA sequencing holds huge promise … but it is a research tool, and I do genuinely believe that a lot of clinically irrelevant data is generated that actually confuses the clinician and the patient.”

Clinical Oncology News Issue: December 2012 | Volume: 07:12