Tumor Heterogeneity: The Lernaean Hydra of Oncology?

Intratumor heterogeneity is one of the biggest challenges in cancer diagnosis and treatment. Despite morphologic and clinical recognition of tumor heterogeneity, an understanding of it at a molecular level has only begun to emerge in recent years. In the review by Drs. Allison and Sledge in this issue of ONCOLOGY, the authors point out the many implications of intratumor heterogeneity, as well as the clinical pitfalls it gives rise to. In this commentary we would like to expand on their observations, with a particular emphasis on breast cancer.

Intratumor heterogeneity for clinically used biomarkers has long been recognized but until recently has largely been ignored. Current clinical guidelines focus on maximizing patient populations that may benefit from targeted therapies, with little recognition of intratumor heterogeneity. One example of this, in breast cancer, is the use of a 1% cutoff for tumor cell positivity for the estrogen and progesterone receptors (ER and PR) as the threshold for recommending the use of endocrine therapies. The correlation of intratumor heterogeneity with resistance to treatment and worse clinical outcomes has been described in several studies.[1-3] In part because of this correlation, new imaging and image processing methods are being developed that will allow for more standardized reporting of intratumor heterogeneity, which will result in a better understanding of its clinical impact. The latest American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines included a criterion for heterogeneity in the scoring and reporting of human epidermal growth factor receptor 2 (HER2) copy number in breast cancer.[4,5] However, it remains to be determined whether the definition of heterogeneity used in these guidelines is sufficient to stratify patients into clinically meaningful subgroups. Because many clinical markers, such as ER and HER2, are already assessed at the single-cell level, it would be relatively easy to use these data to calculate a true quantitative measure of intratumor heterogeneity, such as the Shannon diversity index,[6] and to then incorporate this into the clinical management of cancer patients.

In breast cancer, targeted therapy against HER2 is effective only in a subset of patients with HER2-positive tumors, which may be due in part to heterogeneity for HER2 within tumors and between different lesions (ie, primary and metastatic) in the same patient.[7] Repeated sampling of primary tumors and metastatic lesions is currently not standard clinical practice. However, the analysis of such serial tissue samples during treatment would facilitate the monitoring of clonal dynamics within tumors, which would ultimately lead to improved tailoring of cancer therapies at different stages of the disease. Liquid biopsies-the sampling and testing of easily accessible bodily fluids, such as blood and urine-are gaining in popularity, although it remains to be seen how sensitive and representative they are in patients with heterogeneous tumors.[8,9] However, the data available so far are very promising, and because of the relative ease of obtaining these samples (compared with biopsies of solid tumors), they are likely to be incorporated into standard clinical practice in the near future.

Although the complexity and implications of intratumor heterogeneity appear daunting and make effective cancer therapies seemingly impossible to achieve, only a better understanding of how tumors evolve will lead to more rational treatment design and improved clinical outcomes. For example, chemotherapy targets the more proliferative cell populations in a tumor, selecting for slower-growing cells that resist treatment. Metronomic therapy-the administration of chemotherapeutic agents at lower doses and on a frequent schedule-in principle could slow down such selection processes and provide higher therapeutic efficacy.[10] However, associations between the efficacy of metronomic therapy and intratumor heterogeneity have not been analyzed. Heterogeneous tumors are composed of multiple subclones, some of which may have intrinsic resistance to chemotherapy. In the absence of therapy, the resistant cells typically have a fitness disadvantage relative to the chemosensitive cells, as they have higher substrate and energy demands. Thus, chemosensitive cells possess a fitness advantage and can dominate the tumor mass. However, during treatment these cells will be eliminated, providing the resistant cells with an opportunity, since they will no longer be competing with the “fitter” cells for resources. Adaptive therapy, a concept introduced by Gatenby and colleagues,[11] is designed to maintain a steady population of fitter chemosensitive cells, which would keep the resistant cells at a minimal fraction, turning cancer into a manageable chronic condition. This concept has been effectively applied in animal models, but further studies are required to evaluate its clinical potential. The development of these experimental therapies requires more in-depth studies of clonal dynamics within tumors, since the understanding of interactions between different cellular populations within a tumor may provide novel therapeutic opportunities.

Another approach to slowing down tumor evolution is to identify new molecular targets that play key roles in the generation of intratumor heterogeneity. The driving force of evolution is variability for heritable phenotypic changes, such as mutations. Mutations lead to the production of aberrant proteins, which in normal cells can be efficiently buffered by molecular chaperones such as heat-shock proteins (HSPs). Cancer cells express higher levels of HSP70 and HSP90, which promote cell survival despite increased levels of mutant proteins.[12] This increased tolerance of random mutations in turn fuels genetic and phenotypic diversity in cancer cells with elevated HSP levels.[13,14] HSPs also act as sensors of environmental stress and may promote adaptation to the changing environment via the regulation of phenotypic diversity. Thus, therapeutic targeting of HSPs has the potential to decrease the evolution to treatment-resistant disease.[15]

The high intratumor genetic variability that results from increased mutation rates in certain cancer types can also potentially be exploited for therapeutic interventions. For example, in colorectal carcinomas with defective mismatch repair genes, large numbers of mutant proteins are produced that may serve as tumor antigens and induce an immune response.[16] Therefore, immunotherapy may be particularly effective in such highly heterogeneous tumors. Cancers with higher genomic instability-and thus, greater genetic heterogeneity-may also be more sensitive to certain DNA-damaging agents, such as cisplatin.

The extent of intratumor epigenetic heterogeneity is even more substantial than that of genetic heterogeneity. Cancer cells can have varying DNA methylation and chromatin states, and these can change relatively rapidly. Homogenizing epigenetic patterns within tumors to a therapy-sensitive cellular state may lead to more effective therapies.[17] An example of this is the finding that the combination of histone deacetylase inhibitors with targeted therapy is more effective than the use of agents from either class alone.[18]

Although many strategies for targeting intratumor heterogeneity are currently under preclinical and clinical investigation, there is still a burning need for a deeper understanding of the molecular mechanisms that govern the diversity of cancer cells. It may well be that deciphering the evolutionary and ecologic relationships between cancer cell populations within a patient will suggest the use of already approved drugs in new combinations and dosing schedules that may be more efficacious than current treatments. After all, as Marcel Proust said, “The real act of discovery consists not in finding new lands, but in seeing with new eyes.” When we change the way we see things, we may change what is possible. It is our hope that new ways of viewing cancer will lead to the design of more efficient therapies and improved clinical outcomes.

Financial Disclosure:The authors have no significant financial interest in or other relationship with the manufacturer of any product or provider of any service mentioned in this article.

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