Several types of pediatric cancers reportedly contain high-frequency missense mutations in histone H3, yet the underlying oncogenic mechanism remains poorly characterized. Here we report that the H3 ...lysine 36–to–methionine (H3K36M) mutation impairs the differentiation of mesenchymal progenitor cells and generates undifferentiated sarcoma in vivo. H3K36M mutant nucleosomes inhibit the enzymatic activities of several H3K36 methyltransferases. Depleting H3K36 methyltransferases, or expressing an H3K36I mutant that similarly inhibits H3K36 methylation, is sufficient to phenocopy the H3K36M mutation. After the loss of H3K36 methylation, a genome-wide gain in H3K27 methylation leads to a redistribution of polycomb repressive complex 1 and de-repression of its target genes known to block mesenchymal differentiation. Our findings are mirrored in human undifferentiated sarcomas in which novel K36M/I mutations in H3.1 are identified.
IMPORTANCE: The clinical management of BRCA1 and BRCA2 mutation carriers requires accurate, prospective cancer risk estimates. OBJECTIVES: To estimate age-specific risks of breast, ovarian, and ...contralateral breast cancer for mutation carriers and to evaluate risk modification by family cancer history and mutation location. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study of 6036 BRCA1 and 3820 BRCA2 female carriers (5046 unaffected and 4810 with breast or ovarian cancer or both at baseline) recruited in 1997-2011 through the International BRCA1/2 Carrier Cohort Study, the Breast Cancer Family Registry and the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer, with ascertainment through family clinics (94%) and population-based studies (6%). The majority were from large national studies in the United Kingdom (EMBRACE), the Netherlands (HEBON), and France (GENEPSO). Follow-up ended December 2013; median follow-up was 5 years. EXPOSURES: BRCA1/2 mutations, family cancer history, and mutation location. MAIN OUTCOMES AND MEASURES: Annual incidences, standardized incidence ratios, and cumulative risks of breast, ovarian, and contralateral breast cancer. RESULTS: Among 3886 women (median age, 38 years; interquartile range IQR, 30-46 years) eligible for the breast cancer analysis, 5066 women (median age, 38 years; IQR, 31-47 years) eligible for the ovarian cancer analysis, and 2213 women (median age, 47 years; IQR, 40-55 years) eligible for the contralateral breast cancer analysis, 426 were diagnosed with breast cancer, 109 with ovarian cancer, and 245 with contralateral breast cancer during follow-up. The cumulative breast cancer risk to age 80 years was 72% (95% CI, 65%-79%) for BRCA1 and 69% (95% CI, 61%-77%) for BRCA2 carriers. Breast cancer incidences increased rapidly in early adulthood until ages 30 to 40 years for BRCA1 and until ages 40 to 50 years for BRCA2 carriers, then remained at a similar, constant incidence (20-30 per 1000 person-years) until age 80 years. The cumulative ovarian cancer risk to age 80 years was 44% (95% CI, 36%-53%) for BRCA1 and 17% (95% CI, 11%-25%) for BRCA2 carriers. For contralateral breast cancer, the cumulative risk 20 years after breast cancer diagnosis was 40% (95% CI, 35%-45%) for BRCA1 and 26% (95% CI, 20%-33%) for BRCA2 carriers (hazard ratio HR for comparing BRCA2 vs BRCA1, 0.62; 95% CI, 0.47-0.82; P=.001 for difference). Breast cancer risk increased with increasing number of first- and second-degree relatives diagnosed as having breast cancer for both BRCA1 (HR for ≥2 vs 0 affected relatives, 1.99; 95% CI, 1.41-2.82; P<.001 for trend) and BRCA2 carriers (HR, 1.91; 95% CI, 1.08-3.37; P=.02 for trend). Breast cancer risk was higher if mutations were located outside vs within the regions bounded by positions c.2282-c.4071 in BRCA1 (HR, 1.46; 95% CI, 1.11-1.93; P=.007) and c.2831-c.6401 in BRCA2 (HR, 1.93; 95% CI, 1.36-2.74; P<.001). CONCLUSIONS AND RELEVANCE: These findings provide estimates of cancer risk based on BRCA1 and BRCA2 mutation carrier status using prospective data collection and demonstrate the potential importance of family history and mutation location in risk assessment.
Ovarian cancer is one of the most aggressive gynaecological cancers, thus understanding the different biological pathways involved in ovarian cancer progression is important in identifying potential ...therapeutic targets for the disease. The aim of this study was to investigate the potential roles of Protein Kinase C Zeta (PRKCZ) in ovarian cancer. The atypical protein kinase C isoform, PRKCZ, is involved in the control of various signalling processes including cell proliferation, cell survival, and cell motility, all of which are important for cancer development and progression. Herein, we observe a significant increase in cell survival upon PRKCZ over-expression in SKOV3 ovarian cancer cells; additionally, when the cells are treated with small interference RNA (siRNA) targeting PRKCZ, the motility of SKOV3 cells decreased. Furthermore, we demonstrate that over-expression of PRKCZ results in gene and/or protein expression alterations of insulin-like growth factor 1 receptor (IGF1R) and integrin beta 3 (ITGB3) in SKOV3 and OVCAR3 cells. Collectively, our study describes PRKCZ as a potential regulatory component of the IGF1R and ITGB3 pathways and suggests that it may play critical roles in ovarian tumourigenesis.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline
...pathogenic variants (PVs) because these risks have not been extensively characterized.
We analyzed data from 524 families with
PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes.
We found associations between
PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85;
= 6.5 × 10
), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04;
= 4.1 × 10
), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50;
= 8.7 × 10
), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18;
= 2.6 × 10
). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (
for trend = 2.0 × 10
). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (
for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer.
These results confirm
as a major breast cancer susceptibility gene and establish substantial associations between germline
PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of
into risk prediction models and optimize the clinical cancer risk management of
PV carriers.
A multinational study of 154 families with
PALB2
mutations shows that mutation carriers have a 14% risk of breast cancer by 50 years of age and a 35% risk by 70 years of age, which is similar to the ...risk associated with
BRCA2
mutations.
PALB2 (partner and localizer of BRCA2) was originally identified as a BRCA2-interacting protein that is crucial for key BRCA2 genome caretaker functions
1
,
2
; it was subsequently also shown to interact with BRCA1.
3
Biallelic germline loss-of-function mutations in
PALB2
(also known as
FANCN
) cause Fanconi’s anemia, whereas monoallelic loss-of-function mutations are associated with an increased risk of breast cancer and pancreatic cancer.
4
Previous studies of familial breast cancer have yielded estimates of risk in association with loss-of-function mutations in
PALB2
that are two to four times as high as the risk among non–mutation carriers.
5
–
7
In Finland, the
PALB2
. . .
Early detection of breast cancer through screening reduces breast cancer mortality. The benefits of screening must also be considered within the context of potential harms (e.g., false positives, ...overdiagnosis). Furthermore, while breast cancer risk is highly variable within the population, most screening programs use age to determine eligibility. A risk-based approach is expected to improve the benefit-harm ratio of breast cancer screening programs. The PERSPECTIVE I&I (Personalized Risk Assessment for Prevention and Early Detection of Breast Cancer: Integration and Implementation) project seeks to improve personalized risk assessment to allow for a cost-effective, population-based approach to risk-based screening and determine best practices for implementation in Canada. This commentary describes the four inter-related activities that comprise the PERSPECTIVE I&I project. 1: Identification and validation of novel moderate to high-risk susceptibility genes. 2: Improvement, validation, and adaptation of a risk prediction web-tool for the Canadian context. 3: Development and piloting of a socio-ethical framework to support implementation of risk-based breast cancer screening. 4: Economic analysis to optimize the implementation of risk-based screening. Risk-based screening and prevention is expected to benefit all women, empowering them to work with their healthcare provider to make informed decisions about screening and prevention.
To provide precise age-specific risk estimates of cancers other than female breast and ovarian cancers associated with pathogenic variants (PVs) in
and
for effective cancer risk management.
We used ...data from 3,184
and 2,157
families in the Consortium of Investigators of Modifiers of
to estimate age-specific relative (RR) and absolute risks for 22 first primary cancer types adjusting for family ascertainment.
PVs were associated with risks of male breast (RR = 4.30; 95% CI, 1.09 to 16.96), pancreatic (RR = 2.36; 95% CI, 1.51 to 3.68), and stomach (RR = 2.17; 95% CI, 1.25 to 3.77) cancers. Associations with colorectal and gallbladder cancers were also suggested.
PVs were associated with risks of male breast (RR = 44.0; 95% CI, 21.3 to 90.9), stomach (RR = 3.69; 95% CI, 2.40 to 5.67), pancreatic (RR = 3.34; 95% CI, 2.21 to 5.06), and prostate (RR = 2.22; 95% CI, 1.63 to 3.03) cancers. The stomach cancer RR was higher for females than males (6.89
2.76;
= .04). The absolute risks to age 80 years ranged from 0.4% for male breast cancer to approximately 2.5% for pancreatic cancer for
carriers and from approximately 2.5% for pancreatic cancer to 27% for prostate cancer for
carriers.
In addition to female breast and ovarian cancers,
and
PVs are associated with increased risks of male breast, pancreatic, stomach, and prostate (only
PVs) cancers, but not with the risks of other previously suggested cancers. The estimated age-specific risks will refine cancer risk management in men and women with
PVs.
Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done ...using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance.
In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20–70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and participants younger than 50 years at recruitment. We also assessed the effect that limited data input (eg, restriction of the amount of family history and non-genetic information included) had on the models' performance.
After median follow-up of 11·1 years (IQR 6·0–14·4), 619 (4%) of 15 732 women selected from the ProF-SC cohort study were prospectively diagnosed with breast cancer after recruitment, of whom 519 (84%) had histologically confirmed disease. BOADICEA and IBIS were well calibrated in the overall validation cohort, whereas BRCAPRO and BCRAT underpredicted risk (ratio of expected cases to observed cases 1·05 95% CI 0·97–1·14 for BOADICEA, 1·03 0·96–1·12 for IBIS, 0·59 0·55–0·64 for BRCAPRO, and 0·79 0·73–0·85 for BRCAT). The estimated C-statistics for the complete validation cohort were 0·70 (95% CI 0·68–0·72) for BOADICEA, 0·71 (0·69–0·73) for IBIS, 0·68 (0·65–0·70) for BRCAPRO, and 0·60 (0·58–0·62) for BCRAT. In subgroup analyses by BRCA mutation status, the ratio of expected to observed cases for BRCA-negative women was 1·02 (95% CI 0·93–1·12) for BOADICEA, 1·00 (0·92–1·10) for IBIS, 0·53 (0·49–0·58) for BRCAPRO, and 0·97 (0·89–1·06) for BCRAT. For BRCA-positive participants, BOADICEA and IBIS were well calibrated, but BRCAPRO underpredicted risk (ratio of expected to observed cases 1·17 95% CI 0·99–1·38 for BOADICEA, 1·14 0·96–1·35 for IBIS, and 0·80 0·68–0·95 for BRCAPRO). We noted similar patterns of calibration for women younger than 50 years at recruitment. Finally, BOADICEA and IBIS predictive scores were not appreciably affected by limiting input data to family history for first-degree and second-degree relatives.
Our results suggest that models that include multigenerational family history, such as BOADICEA and IBIS, have better ability to predict breast cancer risk, even for women at average or below-average risk of breast cancer. Although BOADICEA and IBIS performed similarly, further improvements in the accuracy of predictions could be possible with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS.
US National Institutes of Health, National Cancer Institute, Breast Cancer Research Foundation, Australian National Health and Medical Research Council, Victorian Health Promotion Foundation, Victorian Breast Cancer Research Consortium, Cancer Australia, National Breast Cancer Foundation, Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and Cancer Foundation of Western Australia.
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