ABSTRACT
Introduction 76 Family history of hematologic malignancies/lymphoma 76 Inherited syndromes 77 Candidate genes 80 One-carbon metabolism 80 Immunoregulatory genes 83 Other immune regulatory variants 86
Obesity and energy regulation genes 87 Hormones 87 Xenobiotic metabolism genes 89 Conclusions 90 Key points 91 References 92
Most human cancers arise as a result of genetically influenced host responses to environmental causative factors. In some cases such as with familial cancer syndromes, the influence of an inherited genetic defect is great enough to predispose to the disease. The study of these cancer syndromes can provide mechanistic clues and identify molecular lesions that may give rise to malignancy. Though the risk of disease from these mutations may be great, their frequency in the population is low. Of perhaps greater significance on the population level are common genetic polymorphisms that may pose small increases in individual risk, but affect more people than cancer syndromes caused by inherited defects in major cancer genes. Moreover, gene-gene and gene-environment interactions are likely to result in a genetic predisposition to a ‘high-risk’ phenotype. These considerations may be particularly relevant to the study of lymphoid neoplasms. The inherent heterogeneity of lymphoma and the relatively subtle effects of common genetic polymorphisms make complex diseases such as lymphoma difficult to study. Surprisingly, candidate gene association studies have provided some valuable clues to date as to what genes and related pathways may be of relevance in lymphomagenesis. Some of these susceptibility alleles may be useful markers in the search for environmental causative agents. Furthermore, rapid technologic advances in high-throughput genotyping and bioinformatics have paved the way for an agnostic exploration of the entire genome to identify lymphoma risk alleles. This unbiased approach is likely to yield major benefits to lym-
Here we will concentrate on the genetics underlying leukemia, lymphoma and multiple myeloma including familial aggregations, associations with specific genetic syndromes, and common genetic polymorphisms with particular attention, where possible, to risk estimates.
