METHODS: The experimental approach in the present study was based on a bioassay-guided fractionation. The crude methanol and fractionated extracts (hexane, chloroform and water) from different parts of A. scabra (leaves, rhizomes, roots and pseudo stems) were prepared prior to the cytotoxicity evaluation against human ovarian (SKOV-3) and hormone-dependent breast (MCF7) carcinoma cells. The identified cytotoxic extracts were then subjected to chemical investigations in order to identify the active ingredients. A normal human lung fibroblast cell line (MRC-5) was used to determine the specificity for cancerous cells. The cytotoxic extracts and fractions were also subjected to morphological assessment, DNA fragmentation analysis and DAPI nuclear staining.
RESULTS: The leaf (hexane and chloroform) and rhizome (chloroform) extracts showed high inhibitory effect against the tested cells. Ten fractions (LC1-LC10) were yielded after purification of the leaf chloroform extract. Fraction LC4 which showed excellent cytotoxic activity was further purified and resulted in 17 sub-fractions (VLC1-VLC17). Sub-fraction VLC9 showed excellent cytotoxicity against MCF7 and SKOV-3 cells but not toxic against normal MRC-5 cells. Meanwhile, eighteen fractions (RC1-RC18) were obtained after purification of the rhizome chloroform extract, of which fraction RC5 showed cytotoxicity against SKOV-3 cells with high selectivity index. There were marked morphological changes when observed using phase-contrast inverted microscope, DAPI nuclear staining and also DNA fragmentations in MCF7 and SKOV-3 cells after treatment with the cytotoxic extracts and fractions which were indicative of cell apoptosis. Methyl palmitate and methyl stearate were identified in the hexane leaf extract by GC-MS analysis.
CONCLUSIONS: The data obtained from the current study demonstrated that the cell death induced by cytotoxic extracts and fractions of A. scabra may be due to apoptosis induction which was characterized by apoptotic morphological changes and DNA fragmentation. The active ingredients in the leaf sub-fraction VLC9 and rhizome fraction RC5 may lead to valuable compounds that have the ability to kill cancer cells but not normal cells.
SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
METHODS: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.
RESULTS: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.
CONCLUSIONS: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.
IMPACT: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.
METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls).
RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network.
CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development.
IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization.
METHODS: From October 2008 to February 2015, we established a hospital-based cohort of ovarian cancer patients and the germline status of all 218 women with invasive epithelial ovarian cancer was tested using targeted amplification and sequencing of the intron-exon junctions and exonic sequences of BRCA1, BRCA2, PALB2 and TP53.
RESULTS: BRCA1 and BRCA2 mutations were found in 8% (17 cases) and 3% (7 cases) of the ovarian cancer patients, respectively. Mutation carriers were diagnosed at a similar age to non-carriers, but were more likely to be Indian, have serous ovarian cancer, and have more relatives with breast or ovarian cancer. Nonetheless, 42% (10/24) of mutation carriers did not have any family history of breast or ovarian cancer and offering genetic counselling and genetic testing only to women with family history would mean that 35% (6/17) of BRCA1 mutation carriers and 57% (4/7) of BRCA2 mutation carriers would not be offered genetic testing.
CONCLUSIONS: Our data suggest that, similar to Caucasians, a significant proportion of Asian ovarian cancer was attributed to germline mutations in BRCA1 and to a lesser extent in BRCA2.
OBJECTIVE: To identify mutation-specific cancer risks for carriers of BRCA1/2.
DESIGN, SETTING, AND PARTICIPANTS: Observational study of women who were ascertained between 1937 and 2011 (median, 1999) and found to carry disease-associated BRCA1 or BRCA2 mutations. The international sample comprised 19,581 carriers of BRCA1 mutations and 11,900 carriers of BRCA2 mutations from 55 centers in 33 countries on 6 continents. We estimated hazard ratios for breast and ovarian cancer based on mutation type, function, and nucleotide position. We also estimated RHR, the ratio of breast vs ovarian cancer hazard ratios. A value of RHR greater than 1 indicated elevated breast cancer risk; a value of RHR less than 1 indicated elevated ovarian cancer risk.
EXPOSURES: Mutations of BRCA1 or BRCA2.
MAIN OUTCOMES AND MEASURES: Breast and ovarian cancer risks.
RESULTS: Among BRCA1 mutation carriers, 9052 women (46%) were diagnosed with breast cancer, 2317 (12%) with ovarian cancer, 1041 (5%) with breast and ovarian cancer, and 7171 (37%) without cancer. Among BRCA2 mutation carriers, 6180 women (52%) were diagnosed with breast cancer, 682 (6%) with ovarian cancer, 272 (2%) with breast and ovarian cancer, and 4766 (40%) without cancer. In BRCA1, we identified 3 breast cancer cluster regions (BCCRs) located at c.179 to c.505 (BCCR1; RHR = 1.46; 95% CI, 1.22-1.74; P = 2 × 10(-6)), c.4328 to c.4945 (BCCR2; RHR = 1.34; 95% CI, 1.01-1.78; P = .04), and c. 5261 to c.5563 (BCCR2', RHR = 1.38; 95% CI, 1.22-1.55; P = 6 × 10(-9)). We also identified an ovarian cancer cluster region (OCCR) from c.1380 to c.4062 (approximately exon 11) with RHR = 0.62 (95% CI, 0.56-0.70; P = 9 × 10(-17)). In BRCA2, we observed multiple BCCRs spanning c.1 to c.596 (BCCR1; RHR = 1.71; 95% CI, 1.06-2.78; P = .03), c.772 to c.1806 (BCCR1'; RHR = 1.63; 95% CI, 1.10-2.40; P = .01), and c.7394 to c.8904 (BCCR2; RHR = 2.31; 95% CI, 1.69-3.16; P = .00002). We also identified 3 OCCRs: the first (OCCR1) spanned c.3249 to c.5681 that was adjacent to c.5946delT (6174delT; RHR = 0.51; 95% CI, 0.44-0.60; P = 6 × 10(-17)). The second OCCR spanned c.6645 to c.7471 (OCCR2; RHR = 0.57; 95% CI, 0.41-0.80; P = .001). Mutations conferring nonsense-mediated decay were associated with differential breast or ovarian cancer risks and an earlier age of breast cancer diagnosis for both BRCA1 and BRCA2 mutation carriers.
CONCLUSIONS AND RELEVANCE: Breast and ovarian cancer risks varied by type and location of BRCA1/2 mutations. With appropriate validation, these data may have implications for risk assessment and cancer prevention decision making for carriers of BRCA1 and BRCA2 mutations.