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  1. Yoo KY
    Asian Pac J Cancer Prev, 2010;11(4):839-44.
    PMID: 21133587
    Cancer incidences as well as the most prevalent cancer types vary greatly across Asian countries since people have differing health behaviors as well as lifestyle factors related to cancer risk. Countries have varying systems of government organization, laws, resources, facilities, and management strategies for addressing the cancer burden. Examples such as Korea and Japan with existing national cancer control programs need to focus on early screening and detection and quality of screening methods. If screening and detection increase to cover more than 50% of the target population, survival rate increases and thus the number of cancer patients detected increases resulting in higher medical cost. Thus, expansion of cancer screening, in addition to smoking prevention, immunization increase, and diet control awareness, are needed for cancer prevention strategies. Countries such as Thailand, China, Malaysia, and Turkey need to begin organized efforts to reduce cancer deaths through state-wide cancer screening programs. Strategies focused on increasing survival among cancer patients are also needed. In addition, government organizations and law regulations need to be in place as the first step towards cancer prevention. For the countries such as Nepal, Pakistan, Mongolia, and Iraq which do not have any cancer-related organizations in place, the first step that is needed is to raise public awareness about cancer; a public awareness campaign is the number one priority and should begin immediately. The easiest and most feasible step at this point is dissemination of cancer education materials during school health education and physical health screening. This must be started immediately because we need to avoid the development of existing cancers where patients will need to seek specialized cancer treatment facilities that are non-existent in these regions. In addition, hospitals need to take a step further and start undergoing registration of cancer prevalence and incidence cases beginning at the regional level. Through the hospital census, countries will be able to determine the magnitude of the cancer burden. Moreover, countries with professionals and researchers with advanced cancer research, education, and training also need to contribute through international cooperation.
  2. Li J, Lindström LS, Foo JN, Rafiq S, Schmidt MK, Pharoah PD, et al.
    Nat Commun, 2014 Jun 17;5:4051.
    PMID: 24937182 DOI: 10.1038/ncomms5051
    Large population-based registry studies have shown that breast cancer prognosis is inherited. Here we analyse single-nucleotide polymorphisms (SNPs) of genes implicated in human immunology and inflammation as candidates for prognostic markers of breast cancer survival involving 1,804 oestrogen receptor (ER)-negative patients treated with chemotherapy (279 events) from 14 European studies in a prior large-scale genotyping experiment, which is part of the Collaborative Oncological Gene-environment Study (COGS) initiative. We carry out replication using Asian COGS samples (n=522, 53 events) and the Prospective Study of Outcomes in Sporadic versus Hereditary breast cancer (POSH) study (n=315, 108 events). Rs4458204_A near CCL20 (2q36.3) is found to be associated with breast cancer-specific death at a genome-wide significant level (n=2,641, 440 events, combined allelic hazard ratio (HR)=1.81 (1.49-2.19); P for trend=1.90 × 10(-9)). Such survival-associated variants can represent ideal targets for tailored therapeutics, and may also enhance our current prognostic prediction capabilities.
  3. Park J, Choi JY, Choi J, Chung S, Song N, Park SK, et al.
    Cancers (Basel), 2021 May 14;13(10).
    PMID: 34069208 DOI: 10.3390/cancers13102370
    In this study we aim to examine gene-environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10-3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10-4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.
  4. Morra A, Jung AY, Behrens S, Keeman R, Ahearn TU, Anton-Culver H, et al.
    Cancer Epidemiol Biomarkers Prev, 2021 Apr;30(4):623-642.
    PMID: 33500318 DOI: 10.1158/1055-9965.EPI-20-0924
    BACKGROUND: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.

    METHODS: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.

    RESULTS: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72-0.86)]; >0-<5 years versus ≥10 years since last full-term birth [1.31 (1.11-1.55)]; ever versus never use of oral contraceptives [0.91 (0.87-0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen-progestin therapy [0.61 (0.54-0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02-1.21) for current versus never smoking.

    CONCLUSIONS: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype.

    IMPACT: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.

  5. Michailidou K, Beesley J, Lindstrom S, Canisius S, Dennis J, Lush MJ, et al.
    Nat Genet, 2015 Apr;47(4):373-80.
    PMID: 25751625 DOI: 10.1038/ng.3242
    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.
  6. Lin WY, Camp NJ, Ghoussaini M, Beesley J, Michailidou K, Hopper JL, et al.
    Hum Mol Genet, 2015 Jan 01;24(1):285-98.
    PMID: 25168388 DOI: 10.1093/hmg/ddu431
    Previous studies have suggested that polymorphisms in CASP8 on chromosome 2 are associated with breast cancer risk. To clarify the role of CASP8 in breast cancer susceptibility, we carried out dense genotyping of this region in the Breast Cancer Association Consortium (BCAC). Single-nucleotide polymorphisms (SNPs) spanning a 1 Mb region around CASP8 were genotyped in 46 450 breast cancer cases and 42 600 controls of European origin from 41 studies participating in the BCAC as part of a custom genotyping array experiment (iCOGS). Missing genotypes and SNPs were imputed and, after quality exclusions, 501 typed and 1232 imputed SNPs were included in logistic regression models adjusting for study and ancestry principal components. The SNPs retained in the final model were investigated further in data from nine genome-wide association studies (GWAS) comprising in total 10 052 case and 12 575 control subjects. The most significant association signal observed in European subjects was for the imputed intronic SNP rs1830298 in ALS2CR12 (telomeric to CASP8), with per allele odds ratio and 95% confidence interval [OR (95% confidence interval, CI)] for the minor allele of 1.05 (1.03-1.07), P = 1 × 10(-5). Three additional independent signals from intronic SNPs were identified, in CASP8 (rs36043647), ALS2CR11 (rs59278883) and CFLAR (rs7558475). The association with rs1830298 was replicated in the imputed results from the combined GWAS (P = 3 × 10(-6)), yielding a combined OR (95% CI) of 1.06 (1.04-1.08), P = 1 × 10(-9). Analyses of gene expression associations in peripheral blood and normal breast tissue indicate that CASP8 might be the target gene, suggesting a mechanism involving apoptosis.
  7. Michailidou K, Lindström S, Dennis J, Beesley J, Hui S, Kar S, et al.
    Nature, 2017 Nov 02;551(7678):92-94.
    PMID: 29059683 DOI: 10.1038/nature24284
    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P 
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