METHODS: mRNA was extracted from 44 fibroadenomas and 36 giant fibroadenomas, and transcriptomic profiling was performed to identify up- and down-regulated genes in the giant fibroadenomas as compared to the fibroadenomas.
RESULTS: A total of 40 genes were significantly up-regulated and 18 genes were significantly down-regulated in the giant fibroadenomas as compared to the fibroadenomas of the breast. The top 5 up-regulated genes were FN1, IL3, CDC6, FGF8 and BMP8A. The top 5 down-regulated genes were TNR, CDKN2A, COL5A1, THBS4 and BMPR1B. The differentially expressed genes (DEGs) were found to be associated with 5 major canonical pathways involved in cell growth (PI3K-AKT, cell cycle regulation, WNT, and RAS signalling) and immune response (JAK-STAT signalling). Further analyses using 3 supervised learning algorithms identified an 8-gene signature (FN1, CDC6, IL23A, CCNA1, MCM4, FLT1, FGF22 and COL5A1) that could distinguish giant fibroadenomas from fibroadenomas with high predictive accuracy.
CONCLUSION: Our findings demonstrated that the giant fibroadenomas are biologically distinct to fibroadenomas of the breast with overexpression of genes involved in the regulation of cell growth and immune response.
METHODS: We established PN in a dedicated breast clinic of a Malaysian state-run hospital. We compared diagnostic and treatment timeliness between navigated patients (n = 135) and patients diagnosed in the prior year (n = 148), and described factors associated with timeliness.
RESULTS: Women with PN received timely mammography compared with patients in the prior year (96.4% v 74.4%; P < .001), biopsy (92.5% v 76.1%; P = .003), and communication of news (80.0% v 58.5%; P < .001). PN reduced treatment default rates (4.4% v 11.5%; P = .048). Among navigated patients, late stage at presentation was independently associated with having emotional and language barriers ( P = .01). Finally, the main reason reported for delay, default, or refusal of treatment was the preference for alternative therapy.
CONCLUSION: PN is feasible for addressing barriers to cancer care when integrated with a state-run breast clinic of an LMIC. Its implementation resulted in improved diagnostic timeliness and reduced treatment default. Wider adoption of PN could be a key element of cancer control in LMICs.
PURPOSE: To examine the association between adult lifetime physical activity and breast cancer risk in a case-control analysis.
MATERIALS AND METHODS: This study involved 122 cases of breast cancer and 121 controls in the state of Kelantan in Malaysia. A comprehensive measure of lifetime physical activity was used to assess occupational, household, and recreational/sports activity. For every type of activity, a metabolic equivalent (MET) score was assigned using the compendium of physical activities. MET-hours/week per year for all types of activities at different levels of intensities for different age groups were calculated. Logistic regression analysis was used to estimate odds ratios between various measures of physical activity and breast cancer risk.
CONCLUSIONS: The mean MET-hours/week per year for all activities were 120.0 and 132.9 of MET-hours/week per year for cases and controls respectively. Household activities accounted for about 70% of the total lifetime physical activities. Only about 2.5% of the total lifetime physical activities were in the form of recreational/sports. This study found no association between lifetime occupational and recreational/sports physical activities with breast cancer risk among Kelantanese women. However, higher intensity lifetime household activities seemed to significantly reduce risk of breast cancer.
METHODS: Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.
FINDINGS: Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P breast cancer risk, we found 14 variants showing an association. Our findings warrant further functional investigation of these variants. FUND: National Institutes of Health.
METHODS: Germline DNA from 467 breast cancer patients in Sarawak General Hospital, Malaysia, where 93% of the breast cancer patients in Sarawak are treated, was sequenced for the entire coding region of BRCA1; BRCA2; PALB2; Exons 6, 7, and 8 of TP53; and Exons 7 and 8 of PTEN. Pathogenic variants included known pathogenic variants in ClinVar, loss of function variants, and variants that disrupt splice site.
RESULTS: We found 27 pathogenic variants (11 BRCA1, 10 BRCA2, 4 PALB2, and 2 TP53) in 34 patients, which gave a prevalence of germline mutations of 2.8, 3.23, and 0.86% for BRCA1, BRCA2, and PALB2, respectively. Compared to mutation non-carriers, BRCA1 mutation carriers were more likely to have an earlier age at onset, triple-negative subtype, and lower body mass index, whereas BRCA2 mutation carriers were more likely to have a positive family history. Mutation carrier cases had worse survival compared to non-carriers; however, the association was mostly driven by stage and tumor subtype. We also identified 19 variants of unknown significance, and some of them were predicted to alter splicing or transcription factor binding sites.
CONCLUSION: Our data provide insight into the genetics of breast cancer in this understudied group and suggest the need for modifying genetic testing guidelines for this population with a much younger age at diagnosis and more limited resources compared with Caucasian populations.