Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction

Breast Cancer Risk for Women With a TP53 Pathogenic Variant

The article highlights that breast cancer risk for women with TP53 mutations depends on family history.

Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses

A polygenic risk score (PRS) combines the associations of multiple genetic variants that could be due to direct causal effects, indirect genetic effects, or other sources of familial confounding. We have developed new approaches to assess evidence for and against causation by using family data for pairs of relatives (Inference about Causation from Examination of FAmiliaL CONfounding [ICE FALCON]) or measures of family history (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLyses [ICE CRISTAL]). Inference is made from the changes in regression coefficients of relatives' PRSs or PRS and family history before and after adjusting for each other. We applied these approaches to two breast cancer PRSs and multiple studies and found that (a) for breast cancer diagnosed at a young age, for example, <50 years, there was no evidence that the PRSs were causal, while (b) for breast cancer diagnosed at later ages, there was consistent evidence for causation explaining increasing amounts of the PRS-disease association. The genetic variants in the PRS might be in linkage disequilibrium with truly causal variants and not causal themselves. These PRSs cause minimal heritability of breast cancer at younger ages. There is also evidence for nongenetic factors shared by first-degree relatives that explain breast cancer familial aggregation. Familial associations are not necessarily due to genes, and genetic associations are not necessarily causal.

Cancer Risks Associated With TP53 Pathogenic Variants: Maximum Likelihood Analysis of Extended Pedigrees for Diagnosis of First Cancers Beyond the Li-Fraumeni Syndrome Spectrum

PURPOSE

Establishing accurate age-related penetrance figures for the broad range of cancer types that occur in individuals harboring a pathogenic germline variant in the TP53 gene is essential to determine the most effective clinical management strategies. These figures also permit optimal use of cosegregation data for classification of TP53 variants of unknown significance. Penetrance estimation can easily be affected by bias from ascertainment criteria, an issue not commonly addressed by previous studies.

MATERIALS AND METHODS

We performed a maximum likelihood penetrance estimation using full pedigree data from a multicenter study of 146 TP53-positive families, incorporating adjustment for the effect of ascertainment and population-specific background cancer risks. The analysis included pedigrees from Australia, Spain, and United States, with phenotypic information for 4,028 individuals.

RESULTS

Core Li-Fraumeni syndrome (LFS) cancers (breast cancer, adrenocortical carcinoma, brain cancer, osteosarcoma, and soft tissue sarcoma) had the highest hazard ratios of all cancers analyzed in this study. The analysis also detected a significantly increased lifetime risk for a range of cancers not previously formally associated with TP53 pathogenic variant status, including colorectal, gastric, lung, pancreatic, and ovarian cancers. The cumulative risk of any cancer type by age 50 years was 92.4% (95% CI, 82.2 to 98.3) for females and 59.7% (95% CI, 39.9 to 81.3) for males. Females had a 63.3% (95% CI, 35.6 to 90.1) cumulative risk of developing breast cancer by age 50 years.

CONCLUSION

The results from maximum likelihood analysis confirm the known high lifetime risk for the core LFS-associated cancer types providing new risk estimates and indicate significantly increased lifetime risks for several additional cancer types. Accurate cancer risk estimates will help refine clinical recommendations for TP53 pathogenic variant carriers and improve TP53 variant classification.

Circulating tumor biomarkers in early-stage breast cancer: characteristics, detection, and clinical developments

Breast cancer is the most common form of cancer in women, contributing to high rates of morbidity and mortality owing to the ability of these tumors to metastasize via the vascular system even in the early stages of progression. While ultrasonography and mammography have enabled the more reliable detection of early-stage breast cancer, these approaches entail high rates of false positive and false negative results Mammograms also expose patients to radiation, raising clinical concerns. As such, there is substantial interest in the development of more accurate and efficacious approaches to diagnosing breast cancer in its early stages when patients are more likely to benefit from curative treatment efforts. Blood-based biomarkers derived from the tumor microenvironment (TME) have frequently been studied as candidate targets that can enable tumor detection when used for patient screening. Through these efforts, many promising biomarkers including tumor antigens, circulating tumor cell clusters, microRNAs, extracellular vesicles, circulating tumor DNA, metabolites, and lipids have emerged as targets that may enable the detection of breast tumors at various stages of progression. This review provides a systematic overview of the TME characteristics of early breast cancer, together with details on current approaches to detecting blood-based biomarkers in affected patients. The limitations, challenges, and prospects associated with different experimental and clinical platforms employed in this context are also discussed at length.

Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks

BACKGROUND

The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered.

DEVELOPMENT

We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID's building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher's classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors.

APPLICATION

For female breast cancer, VALID quantified how much variance in risk is explained-at different ages-by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors.

CONCLUSION

VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.

Risk of estrogen receptor-specific breast cancer by family history of estrogen receptor subtypes and other cancers

BACKGROUND

The extent to which the risk of estrogen receptor (ER)-specific breast cancer is associated with ER status of breast cancer and other cancers among first-degree relatives is unclear.

METHODS

This population-based cohort included 464 707 cancer-free women in Stockholm, Sweden, during 1978-2019. For ER-negative and ER-positive breast cancers, we estimated hazard ratios (HRs) associated with ER status of female first-degree relatives with breast cancer and of other cancers in all first-degree relatives. Associations between ER-negative and ER-positive status by family cancer history were estimated using logistic regression in a case-only design.

RESULTS

Women with familial ER-positive breast cancer had 1.87 times (95% confidence interval [CI] = 1.77 to 1.97) higher risk of ER-positive subtype, whereas the corresponding hazard ratio for ER-negative was 2.54 (95% CI = 2.08 to 3.10) when having familial ER-negative breast cancer. The risk increased with an increasing number of female first-degree relatives having concordant subtypes and younger age at diagnosis (Ptrend <.001 for both). Nonbreast cancers among first-degree relatives were associated with both ER-positive (HR = 1.14, 95% CI = 1.10 to 1.17) and ER-negative (HR = 1.08, 95% CI = 1.01 to 1.16) breast cancers. Compared with women with ER-positive breast cancer, women with ER-negative breast cancer were more likely to have family history of liver (odds ratio [OR] = 1.33, 95% CI = 1.05 to 1.67), ovary (OR = 1.28, 95% CI = 1.01 to 1.61), and testicle cancer (OR = 1.79, 95% CI = 1.01 to 3.16) but less likely to have family history of endometrial cancer (OR = 0.77, 95% CI = 0.60 to 1.00) and leukemia (OR = 0.72, 95% CI = 0.56 to 0.91).

CONCLUSIONS

Risk of ER-specific breast cancer differs according to ER status of female first-degree relatives with breast cancer and some other cancers of first-degree relatives. This family history information should be considered in the individual risk prediction for ER subtypes.

Family history and breast cancer risk for Asian women: a systematic review and meta-analysis

BACKGROUND

Studies of women of European ancestry have shown that the average familial relative risk for first-degree relatives of women with breast cancer is approximately twofold, but little is known for Asian women. We aimed to provide evidence for the association between family history and breast cancer risk for Asian women by systematically reviewing published literature.

METHODS

Studies reporting the familial relative risk of breast cancer for Asian women were searched in three online databases and complemented by a manual search. Odds ratios (ORs) for the association between family history and breast cancer risk were pooled across all included studies and by subgroups in terms of the type of family history, age, menopausal status and geographical region.

RESULTS

The pooled OR for women who have a first-degree relative with breast cancer was 2.46 (95% confidence interval [CI]: 2.03, 2.97). There was no evidence that the familial risk differed by the type of affected relative (mother versus sisters), the woman's age (< 50 years versus ≥ 50 years), menopausal status (pre versus post) and geographical region (East and Southeast Asia versus other regions) (all P > 0.3). The pooled ORs for women of Asian ancestry with a family history in any relative were similar for those living in non-Asian countries (2.26, 95% CI: 1.42, 3.59) compared with those living in Asian countries (2.18, 95% CI: 1.85, 2.58).

CONCLUSIONS

Family history of breast cancer is associated with an approximately twofold relative risk of breast cancer for Asian women, which is of similar magnitude to that observed for women of European ancestry. This implies that similar familial factors are implicated in breast cancer risk between women of European and Asian ancestries. Genetic factors are likely to play a substantial role in explaining the breast cancer familial risk for Asian women, as similar risks were observed across different living environments and cultures.

Population-based analysis of POT1 variants in a cutaneous melanoma case-control cohort

Pathogenic germline variants in the protection of telomeres 1 gene (POT1) have been associated with predisposition to a range of tumour types, including melanoma, glioma, leukaemia and cardiac angiosarcoma. We sequenced all coding exons of the POT1 gene in 2928 European-descent melanoma cases and 3298 controls, identifying 43 protein-changing genetic variants. We performed POT1-telomere binding assays for all missense and stop-gained variants, finding nine variants that impair or disrupt protein-telomere complex formation, and we further define the role of variants in the regulation of telomere length and complex formation through molecular dynamics simulations. We determine that POT1 coding variants are a minor contributor to melanoma burden in the general population, with only about 0.5% of melanoma cases carrying germline pathogenic variants in this gene, but should be screened in individuals with a strong family history of melanoma and/or multiple malignancies.