The story of “one size fits all” should be never spread, and pharmacogenomics is the
most basic and essential part for individualized therapy and medicine. It is promising
to know that the potential of translational medical science has become reality in the
field of pharmacogenomics, with the classical examples of UGT1A1 and irinotecan,
TMPT and thiopurine, and CYP2D6 and tamoxifen. However, the fight with cancers
is just at the beginning.
In this summary, most of the studies are case-control investigations for one or
two ethnics. The inconsistency of choosing the SNPs and insufficiency sample size
limited the multiple comparisons of the human populations around the world. The
good examples of classification and regression tree analysis by some groups95, 113 are
straightforward to the goal of personalized medicine. Further incorporations and
integrations of genotype-phenotype relationship analysis, population-based tissue and
blood functional measurements, clinical outcome records, especially those in chemo-
and radiotherapy responses, are in urgent need for international studies on
inter-ethnic variations, using these pharmacogenomic biomarkers. The integration of
pharmacogenomic biomarkers, phenotypic biomarkers, pathological biomarkers, is
necessary in the systems for cancer risk prediction, and personalized medicine and
therapy evaluation.
The knowledge about these pharmacogenomic biomarkers may provide new
directions and practical tools for personalized medicine. After the knowing of specific
critical SNPs, especially those located in exons and the genetic polymorphisms may
lead to alterations in the protein structures (so-called nonsynonmous SNPs), the
scientists in bioinformatics may perform the molecular dynamic simulation among the
docking sites between the target proteins, gaining the insight into the impact of these
SNPs on structural changes. Quantitative structure-activity relationship analysis can
be used to quantitatively analyze the impact of those non-synonymous polymorphisms
on the function of the target protein. These methods would provide powerful and
practical tools for high-speed screening of synthetic and natural compounds, and the
deduced data can be applied to the molecular design for new anticancer drugs.
Conflict of interests
All the authors declare no competing financial interests.
Executive summary
XRCC5/XRCC6 played critical roles in genomic instability and carcinogenesis
Defects in DNA repair systems were closely related to genome instability and
carcinogenesis.
Homologous recombination and non-homologous end-joining were two major DNA
repair systems for DNA double strand breaks, one of the most deleterious DNA
damaging types.
XRCC5/XRCC6 was the upstream heterodimer in detecting double strand breaks for
the non-homologous end-joining repair system.
Some SNPs on XRCC5/XRCC6 were investigated of their associations with specific
cancer risks
Molecular epidemiologists can investigate the association of XRCC5/XRCC6
genotypes with cancer risks via genome-wide, pathway-based and candidate-gene
approaches.
The XRCC5/XRCC6 polymorphic genotypes have been investigated of their
associations with glioma, meningiomas, head and neck, thyroid, digestive system,
lung, breast, urinary system cancers, and cancer like disease pterygium.
The haplotypes, gene-gene and gene-environment interactions for carcinogenesis,
and their associations with prognosis and anticancer treatment response may also
be evaluated in population study.
XRCC/XRCC6 may contribute to individualized cancer pharmacogenomics
The XRCC5/XRCC6 may be potential targets for anticancer drug development.
The genotypes of XRCC5/XRCC6 SNPs may be potential bio-predictors of personal
cancer risk and cancer prognosis outcome.
The genotyping of XRCC5/XRCC6 SNPs, together with individual clinical data,
may also be helpful in individualized cancer therapy strategy determination.
Future prospective on the road ahead
The worldwide cancer epidemiologists should make progress in international
integration for studies in cancer genomics and pharmacogenomics to make cancer
eliminated.
Larger sample sizes, more validations in different ethnicities and more detail clinical
information should be incoperated into the worldwide cancer prediction system of
individualized cancer pharmacogenomics.
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Papers of special note have been highlighted as:
* = of interest,
** = of considerable interest
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