Vice President Joe Biden, in describing the cancer research initiative President Obama asked him to lead, said “the goal of this initiative—this ‘moonshot’—is to seize this moment…to accelerate our efforts to progress toward a cure, and to unleash new discoveries and breakthroughs for other deadly diseases.”
As he noted during his recent visit to the University of Pennsylvania's Abramson Cancer Center to officially launch the initiative, however, he was “not naive about the likelihood of soon curing an entire group of diseases that have bedeviled humanity for centuries.” Rather, he said, the intention of the initiative is to accelerate progress already underway.
Biden personally lobbied for a major increase in cancer research funding in the government spending bill that Congress passed in December, pledging to pursue an initiative to end cancer for the rest of his term and beyond. The bill will raise funding for the NIH by $2 billion, including a $264 million boost specifically for the NCI, the biggest increase for the institute in more than a decade. Scientists concur with the VP’s lack of naiveté.
As Jose Baselga, M.D., Ph.D., the president of the American Association for Cancer Research and physician-in-chief and chief medical officer at Memorial Sloan Kettering Cancer Center (MSKCC), told The New York Times, “Cancer is way more complex than anyone had imagined in 1970,” reflecting many scientists’ sentiments that this kind of approach won’t succeed quickly or easily.
Rebecca A. Burrell and colleagues, writing in the September 19, 2013, issue of Nature noted that the recently revealed genetic diversity both between and within tumors affecting key cancer pathways and driving phenotypic variation poses a significant challenge to personalized cancer medicine.
Among the researchers focused on tumor heterogeneity is MSKCC biologist Scott W. Lowe, Ph.D., chair of the Cancer Biology and Genetics Program and the Geoffrey Beene Cancer Research Center, who commented in a MSKCC blog that “We are increasingly becoming aware of the problem of intra-tumor heterogeneity, the fact that one person’s tumor cells can vary depending on where in the body they are located. Even within the same tumor from the same patient, tumor cells might be subtly or even dramatically different. And there can be very important implications of this type of heterogeneity.”
If doctors are dealing with a highly heterogeneous cancer, the tiny fraction of cells in the biopsy may not be representative of the entire tumor mass, which means important disease features could be missed. What this means in practical terms, said Dr. Lowe, is that “A potentially effective therapy could be overlooked because the indicator for that drug, such as a specific gene mutation, wasn’t found in the biopsy. Conversely, the wrong drug might be chosen if a biopsy reveals the presence of an indicator that isn’t actually that prevalent in the tumor.”
Cancer Therapeutic Challenges
Recent investigations of tumor heterogeneity provide ample evidence of the challenges for cancer therapy and the scope of the problem. Particularly worrisome is the recent finding that post-treatment relapse among acute myelogenous leukemia (AML) patients is associated with the addition of new mutations and clonal evolution.
Li Ding, Ph.D., and colleagues reported in the January 11, 2012 issue of Nature that they had sequenced the primary tumor and relapse genomes from eight AML patients and validated hundreds of somatic mutations using deep sequencing, allowing precise definition of clonality and clonal evolution patterns at relapse.
The scientists pointed out the occurrence of novel, recurrently mutated genes (WAC, SMC3, DIS3, DDX41, and DAXX) in AML, as well as two major clonal evolution patterns during AML relapse. They discovered that the founding clone in the primary tumor gained mutations and evolved into the relapse clone, or that a subclone of the founding clone survived initial therapy, gained additional mutations, and expanded at relapse. In all cases, chemotherapy failed to eradicate the founding clone.
The researchers concluded that comparison of relapse-specific vs. primary tumor mutations in all eight cases revealed an increase in transversions, probably due to DNA damage caused by cytotoxic chemotherapy. These data demonstrate, the authors said, that AML relapse is associated with the addition of new mutations and clonal evolution, shaped in part by the chemotherapy that the patients receive to establish and maintain remissions.
A team working at Harvard and the Broad Institute sought to estimate the extent of clonal heterogeneity in multiple myeloma in a large-scale MM genome sequencing dataset that included untreated and previously treated patients. Jens G. Lohr, M.D., Ph.D., and colleagues, reporting results in the January 13, 2014 issue of Cancer Cell, performed a massive parallel sequencing of paired tumor/normal samples from 203 MM patients.
Commenting on the study, co-senior author Todd Golub, M.D., founding core member of the Broad Institute, director of its cancer program, and professor of pediatrics at Harvard Medical School, said “What this new work shows us is that when we treat an individual patient with multiple myeloma, it’s possible that we’re not just looking at one disease, but at many. In the same person, there could be cancer cells with different genetic makeups. These findings indicate a need to identify the extent of genetic diversity within a tumor as we move toward precision cancer medicine and genome-based diagnostics.”
The Cancer Cell authors identified significantly mutated genes and copy number alterations and discovered putative tumor suppressor genes by determining homozygous deletions and loss of heterozygosity. They reported their observation of frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53, and DIS3 (particularly in nonhyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient.
These studies demonstrate how acquisition of genetic alterations over time leads to clonal evolution. Systemic treatment with chemotherapy may affect the fitness of some subclones more than others, and thus may alter the tumor composition by promoting particular subclones.
Noting that accumulating evidence suggests that intratumor heterogeneity likely is the key to understanding Glioblastoma (GB) treatment failure, Andrea Sottoriva, Ph.D., and colleagues in the department of oncology at University of Cambridge developed a surgical multisampling scheme to collect spatially distinct tumor fragments from 11 GB patients.
The authors reported their findings in the March 5, 2013 issue of PNAS. Their integrated genomic analysis, they said, uncovers extensive intratumor heterogeneity, with most patients displaying different GB subtypes within the same tumor. They also reconstructed the phylogeny of the fragments for each patient, identifying copy number alterations in EGFR and CDKN2A/B/p14ARF as early events, and aberrations in PDGFRA and PTEN as later events during cancer progression. Their clonal characterization of each tumor fragment at the single-molecule level detected multiple coexisting cell lineages.
Taken together, the researchers concluded, their results reveal the genome-wide architecture of intratumor variability in GB across multiple spatial scales and patient-specific patterns of cancer evolution, with consequences for treatment design.
Asked how his findings in MM and those of others with different tumors might immediately translate into practice for oncologists, Dr. Golub said that the notion of a yes or no answer, that is, whether or not a given mutation is present in a tumor, is too simplistic, particularly in interpreting clinical trial results testing targeted agents.
“It is unreasonable to expect that an entire tumor would respond to a drug if the target of the drug is only present in a minority of the tumor cells,” he explained. “If the mutation, for example, is sub-clonal and the patient doesn’t respond clinically, it would be the wrong conclusion to say the drug is ineffective.”
He added that what is needed is a quantitative approach to know in what proportion of the tumor the mutation is found.
“For example, if a mutation is only present in a minority of the tumor cells, the drug might not be so good for the patient. But if the mutation were present in 100 percent of the cells, it’s a better choice,” he said. “Targeted agents that go after the least-heterogeneous aspect of the tumor might be a better choice.”
The same goes for clinical trials as you might come to different results, continued Dr. Golub. In the MM study, for example, “we found that in some patients the BRAF mutation was clonal (present in all of the cells), but in some patients present only in a minority.” If you did a clinical trial of a BRAF inhibitor and you only enrolled sub-clonal patients, you might conclude that BRAF is not a good target in MM, “whereas, if you enroll only patients with clonal mutations in clinical trials, you might come to a completely different conclusion.”
With respect to drug discovery, Dr. Golub is more optimistic about developing drugs that go after the founding mutations that will be present in all of a tumor’s cells. “Those will make the best therapeutic targets,” he said. “I am less optimistic about trying to pick off five sub-clones with a five-drug combination.”
Beverly Mitchell, M.D., director of the Stanford Cancer Institute, David Rubenson, associate director for administration and strategic planning, and Daniel S. Kapp, M.D., professor emeritus of radiation oncology, posed some tough questions about the meaning of these findings for cancer therapeutics in the April 11, 2015 edition of The Scientist. These include whether intra-tumor heterogeneity implies that a single targeted therapeutic, while producing short-term responses, brings us any closer to enduring disease control. Or, they ask, do we simply need a better, or a second or third, targeted therapeutic?
While uncertainties remain, they said, there is sufficient data for every major cancer research and treatment center to assess how intra-patient heterogeneity will affect research priorities, clinical trial design, and the patient’s choice of treatment.