Brain tumor susceptibility: the role of genetic factors and uses of mouse models to unravel risk

Abstract

Brain tumors are relatively rare but deadly cancers, and present challenges in the determination of risk factors in the population. These tumors are inherently difficult to cure because of their protected location in the brain, with surgery, radiation and chemotherapy options carrying potentially lasting morbidity for patients and incomplete cure of the tumor. The development of methods to prevent or detect brain tumors at an early stage is extremely important to reduce damage to the brain from the tumor and the therapy. Developing effective prevention or early detection methods requires a deep understanding of the risk factors for brain tumors. This review explores the difficulties in assessing risk factors in rare diseases such as brain tumors, and discusses how mouse models of cancer can aid in a better understanding of genetic risk factors for brain tumors.

Figure 1

Astrocytomas in NPcis mice. A. Shows diffuse dysplastic nuclei in a World Health Organization grade (WHO) II astrocytoma. Approximately 40% of astrocytomas observed in NPcis mice are WHO II, depending of the genetic background. B. Shows an anaplastic astrocytoma in the spinal cord (V). Approximately 50% of astrocytomas observed are WHO III in the brain or spinal cord. Up to 40% of astrocytomas are found in the spinal cord and many are suggestive of a primary spinal cord lesion, as opposed to infiltration from a primary brain tumor. C. Shows an aggressive glioblastoma multiforme (GBM) that appears to have exited the brain at the bottom of the panel, broken through the skull (S), and is spreading along the surface of the skull at the top of the panel. D.,E. Show examples of diagnostic criteria in NPcis astrocytomas. Dysplastic nuclei are seen in all astrocytomas (D) with distinctive multinucleated giant cells (arrows) found in up to 15% of astrocytomas, including most WHO IV tumors. WHO III and WHO IV astrocytomas have varying degrees of mitotic activity (E). Arrows point at a couple of the mitoses visible in the panel. (F) WHO IV GBMs have regions of N. Scale bars indicate 100 µm. V = vertebra; S = skull; N = necrosis.

Figure 2

Secondary structures found in NPcis astrocytomas. A. Shows an example of satellitosis in which tumor cells form satellite structures around large neurons. An especially distinctive satellitosis pattern is found in up to 7% of observed astrocytomas. B. Shows an example of rosette‐like structures (*) in which tumor cells cluster and fan out from a central point. C. Shows an example of perivascular structures in which tumor cells line up along blood vessels in close association. D. Shows an example of hemorrhage (H) that is found in most GBMs and many of the more aggressive anaplastic astrocytomas. E.,F. Show examples of pseudopallisading tumor cells around a central necrotic core (N) that is found in rare cases of GBM. Scale bars indicate 100 µm. H = hemorrhage.

Figure 3

Genetically engineered murine peripheral nerve sheath tumors in NPcis mice. A.,B. SC, DRG and N are indicated for different MPNSTs. D. Shows a high magnification field of the spinal nerve root tumor shown in C. (box), and the arrow points to a mitotic figure found in the tumor. Scale bars indicate 100 µm. SC = spinal cord; DRG = dorsal root ganglion; N = nerve.

Figure 4

Identifying genetic risk factors between susceptible and resistant strains using F2 intercross or backcross designs. To identify a dominant modifier of resistance (M), a susceptible strain and a resistant strain are crossed to generate F1 progeny. Germline recombination events in F1 progeny will generate chromosomes that are a mixture of the two strain backgrounds. F1 progeny can be intercrossed to give rise to F2 progeny carrying different recombination events on each chromosome and allowing the possibility of detective recessive modifiers. Alternatively, F1 progeny can be backcrossed to the strain carrying the recessive allele of the modifier, simplifying the detection of dominant modifiers.

Figure 5

Reference panels for identifying genetic risk factors. Panels of strains with stable genetics and well‐characterized genotypes can be used to identify modifier genes. CSS carry one chromosome from one strain (black) on the background of another strain (gold). By examining the phenotype in a CSS line for each autosomal chromosome, the X and Y chromosomes, and the mitochondria, one can isolate which chromosomes give rise to genetic variation in phenotype. Recombinant inbred strains carry different mixtures of two strains (black and gold), with different combinations in each line. By examining a phenotype across a large number of these lines, one can identify which regions of the genome associate with a particular trait. Because there is limited variation between any two inbred strains, higher order heterogeneous stocks have been generated. A recent example of this is the CC in which eight different strains are combined to preserve variability and then inbred to form lines, with each line carrying different combinations of the eight parental lines. CSS = chromosome substitution strains; CC =  collaborative cross; RXS = resistant X susceptible recombinant inbred line.