Communication Challenges Loom as Germline Versus Somatic Cancer Data Evolve

Maurie Markman, MD

Editor-in-Chief of OncologyLive

Senior vice president for Clinical Affairs and National Director for Medical Oncology Cancer Treatment Centers of America, Eastern Regional Medical Center

Essentially all members of the medical community, including the most “generalist” family practice physicians, are being required to understand and incorporate into their daily practice an ever-increasing quantity of information related to the broad realm of molecular medicine¹—and there is no area of medicine that is more impacted by reports of paradigm changes in the basics of disease management than oncology. However, the focus of this commentary is not on the revolutionary changes the oncology community will surely witness during the coming years, but rather on the critical need for clinicians to effectively communicate— among ourselves, as well as to our patients, their families, the general public, and health policy experts—as precisely as possible the meaning and implication of a variety of complex concepts within this new world of molecular cancer medicine.

Consider, for example, the fundamental differences and similarities between the purpose and utility of genomic data generated from an individual’s germline versus data that accompany a specific analysis of somatic (nongermline) abnormalities in the cancer itself. While it is perhaps rather simple to distinguish these two genetic compartments at a definitional level (Table), it is becoming evident that both of these factors will be highly relevant in optimizing cancer outcomes in the future and that their clinical impact will increasingly overlap.

It had been appropriately argued in the past that the primary purpose of obtaining detailed knowledge of germline genomic data from a patient with cancer was limited to an assessment of the cancer risk in family members or the uncommon potential for excessive anticancer drug-related toxicity (eg, with irinotecan or 5-fluorouracil) due to a rare normal genetic variant (polymorphism). However, rapidly accumulating and impressive data suggest that normal polymorphisms may play a critical role in influencing a wide variety of cancer-related outcomes. These include, for example, such widely varying effects as the risk of serious cardiac toxicity in children receiving high-dose anthracyclines,² the risk of neurocognitive dysfunction following treatment for childhood acute lymphoblastic leukemia,³ and the risk of aspergillosis as a complication of stem cell transplantation.⁴

Conversely, specific polymorphisms have been shown to have a favorable impact on the outcome of allogeneic stem cell transplantation, hypothesized to result from a more robust immune response to residual cancer.5 In addition, the population of patients with ovarian cancer with BRCA1 or BRCA2 germline mutations has been shown to have superior overall survival compared with women without such an abnormality, presumably secondary to an enhanced sensitivity of cancer cells to platinum (cisplatin or carboplatin) antineoplastic agents.

In the future, the currently assumed rather clearcut distinction between the clinical relevance of germline characteristics versus somatic cancer abnormalities within the realm of cancer management likely will blur further. As a result, it is highly likely that oncologists, their clinical staffs, and genetic counselors, increasingly will be called upon to explain to patients and their caregivers the meaning, implications, and limitations of increasingly complex genomic analyses that will surely become a routine component of cancer care in the future.

Table. Germline Versus Somatic Cancer Genomic Data in an Individual Patient

Germline Genomic Data

Somatic Cancer Genomic Data

Unique characteristic

Present in all cells throughout life, including any developing and subsequently established cancer cells

Specifically present only in cancer cells (mutations, rearrangements, translocations, etc) and not in germline; abnormalities may or may not be clinically relevant, may change in level of expression, and may occur as a component of the natural history of the cancer or (at least partially) secondary to the influence of treatment

Standard-of-care utility

Defines risk for the development of specific genetic diseases (eg, Down syndrome)

Defines a level of risk for the development of a type of cancer (eg, BRCA mutations for cancers of the breast/ovary)

Defines the potential effectiveness of antineoplastic agents (eg, EGFR mutation in non-small cell lung cancer; BRAF mutation in melanoma; ALK rearrangements in lung cancer)

Future/current developing utility

Specific normal polymorphisms define metabolic profiles of anticancer agents in individuals, which may impact toxicity (eg, slower clearance) and efficacy (eg, more rapid clearance of active metabolites from systemic compartment)

Specific polymorphisms help define probability of favorable/unfavorable clinical outcomes

Effective targeting of unique non-DNA somatic molecular events (eg, epigenetic, RNA, “networks”) to favorably impact outcomes

References

1. Bianchi DW, Parker RL, Wentworth J, et al. DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med. 2014;370(9):799-808.
2. Wang X, Liu W, Sun C-L, et al. Hyaluronan synthase 3 variant and anthracycline-related cardiomyopathy: a report from the Children’s Oncology Group [published online January 27, 2014]. J Clin Onocl. 2014;32(7):647-653.
3. Krull KR, Brinkman TM, Li C, et al. Neurocognitive outcomes decades after treatment for childhood acute lymphoblastic leukemia: a report from the St. Jude Lifetime Cohort Study [published online November 4, 2013]. J Clin Oncol. 2013;31(35):4407-4415.
4. Cunha C, Aversa F, Lacerda JF, et al. Genetic PTX3 deficiency and aspergillosis in stem-cell transplantation. N Engl J Med. 2014;370(5):421-432.
5. Bari R, Rujkijyanont P, Sullivan E, et al. Effect of donor KIR2DL1 allelic polymorphism on the outcome of pediatric allogeneic hematopoietic stem-cell transplantation [published online September 16, 2013]. J Clin Oncol. 2013;31(30):3782-3790.