Predicting the Likelihood of Carrying a BRCA1 or BRCA2 Mutation in Asian Patients With Breast Cancer

[News in breast oncology genetics for female and male population]

OBJECTIVES

Breast oncology genetics emerged almost 30 years ago with the discovery of the BRCA1 and BRCA2 genes. The evolution of analytical practices has progressively allowed access to tests whose results now have a considerable impact on the management of both female and male breast cancers. The Sénologie commission of the Collège national des gynécologues et obstétriciens français (CNGOF) asked five specialists in breast surgery, oncology and oncological genetics to draw up a summary of the oncogenetic testing criteria used and the clinical implications for the female and male population of the test results, with or without an identified causal variant. In the case of proven genetic risk, surveillance, risk-reduction strategies, and the specificities of surgical and medical management (with PARP inhibitors in particular) were updated.

METHODS

This summary was based on national and international guidelines on the monitoring and therapeutic management of genetic risk, and a recent review of the literature covering the last five years.

RESULTS

Despite successive technical developments, the probability of identifying a causal variant in a situation suggestive of a predisposition to breast and ovarian cancer remains around 10% in France. The risk of breast cancer in women with a causal variant of the BRCA1, BRCA2, PALB2, TP53, CDH1 and PTEN genes is estimated at between 35% and 85% at age 70. The presence of a causal variant in one of these genes is the subject of different recommendations for men and women, concerning both surveillance, the age of onset and imaging modalities of which vary according to the genes involved, and risk-reduction surgery, which is possible for women as soon as their risk level exceeds 30% and remains exceptionally indicated for men. In the case of breast cancer, PARP inhibitors are a promising new class of treatment for BRCA germline mutations.

CONCLUSION

A discipline resolutely focused on understanding molecular mechanisms, screening and preventive medicine/surgery, oncology genetics is currently also involved in new medical/surgical approaches, the long-term benefits/risks of which will need to be monitored.

Development and validation of ultrasound-based radiomics model to predict germline BRCA mutations in patients with breast cancer

BACKGROUND

Identifying breast cancer (BC) patients with germline breast cancer susceptibility gene (gBRCA) mutation is important. The current criteria for germline testing for BC remain controversial. This study aimed to develop a nomogram incorporating ultrasound radiomic features and clinicopathological factors to predict gBRCA mutations in patients with BC.

MATERIALS AND METHODS

In this retrospective study, 497 women with BC who underwent gBRCA genetic testing from March 2013 to May 2022 were included, including 348 for training (84 with and 264 without a gBRCA mutation) and 149 for validation(36 patients with and 113 without a gBRCA mutation). Factors associated with gBRCA mutations were identified to establish a clinicopathological model. Radiomics features were extracted from the intratumoral and peritumoral regions (3 mm and 5 mm) of each image. The least absolute shrinkage and selection operator regression algorithm was used to select the features and logistic regression analysis was used to construct three imaging models. Finally, a nomogram that combined clinicopathological and radiomics features was developed. The models were evaluated based on the area under the receiver operating characteristic curve (AUC), calibration, and clinical usefulness.

RESULTS

Age at diagnosis, family history of BC, personal history of other BRCA-related cancers, and human epidermal growth factor receptor 2 status were independent predictors of the clinicopathological model. The AUC of the imaging radiomics model combining intratumoral and peritumoral 3 mm areas in the validation set was 0.783 (95% confidence interval [CI]: 0.702-0.862), which showed the best performance among three imaging models. The nomogram yielded better performance than the clinicopathological model in validation sets (AUC: 0.824 [0.755-0.894] versus 0.659 [0.563-0.755], p = 0.007).

CONCLUSION

The nomogram based on ultrasound images and clinicopathological factors performs well in predicting gBRCA mutations in BC patients and may help to improve clinical decisions about genetic testing.

Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank

PURPOSE

The benefit of using individual risk prediction tools to identify high-risk individuals for breast cancer (BC) screening is uncertain, despite the personalized approach of risk-based screening.

METHODS

We studied the overlap of predicted high-risk individuals among 246,142 women enrolled in the UK Biobank. Risk predictors assessed include the Gail model (Gail), BC family history (FH, binary), BC polygenic risk score (PRS), and presence of loss-of-function (LoF) variants in BC predisposition genes. Youden J-index was used to select optimal thresholds for defining high-risk.

RESULTS

In total, 147,399 were considered at high risk for developing BC within the next 2 years by at least 1 of the 4 risk prediction tools examined (Gail2-year > 0.5%: 47%, PRS2-yea r > 0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only 1 risk predictor. The overlap between individuals flagged as high-risk because of genetic (PRS) and Gail model risk factors was 30%. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and, LoF (AUC2-year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability.

CONCLUSION

Risk-based BC screening may require a multipronged approach that includes PRS, predisposition genes, FH, and other recognized risk factors.

Diverse genetic spectrum among patients who met the criteria of hereditary breast, ovarian and pancreatic cancer syndrome

OBJECTIVE

Genetic high-risk assessment combines hereditary breast, ovarian and pancreatic cancer into one syndrome. However, there is a lack of data for comparing the germline mutational spectrum of the cancer predisposing genes between these three cancers.

METHODS

Patients who met the criteria of the hereditary breast, ovarian and pancreatic cancer were enrolled and received multi-gene sequencing.

RESULTS

We enrolled 730 probands: 418 developed breast cancer, 185 had ovarian cancer, and 145 had pancreatic cancer. Out of the 18 patients who had two types of cancer, 16 had breast and ovarian cancer and 2 had breast and pancreatic cancer. A total of 167 (22.9%) patients had 170 mutations. Mutation frequency in breast, ovarian and pancreatic cancer was 22.3%, 33.5% and 17.2%, respectively. The mutation rate was significantly higher in patients with double cancers than those with a single cancer (p<0.001). BRCA1 and BRCA2 were the most dominant genes associated with hereditary breast and ovarian cancer, whereas ATM was the most prevalent gene related to hereditary pancreatic cancer. Genes of hereditary colon cancer such as lynch syndrome were presented in a part of patients with pancreatic or ovarian cancer but seldom in those with breast cancer. Families with a history of both ovarian and breast cancer were associated with a higher mutation rate than those with other histories.

CONCLUSION

The mutation spectrum varies across the three cancer types and family histories. Our analysis provides guidance for physicians, counsellors, and counselees on the offer and uptake of genetic counseling.

Outcomes in breast cancer-does ethnicity matter?

Ethnic or racial differences in breast cancer (BC) survival outcomes have been reported, but current data are largely restricted to comparisons between African Americans and non-Hispanic whites. Most analyses have traditionally been based on self-reported race which may not always be accurate, or are oversimplified in their classification. With increasing globalization, quantification of the genetic ancestry from genomic data may offer a solution to infer the complex makeup from admixture of races. Focusing on the larger and the latest studies, we will discuss recent findings on the differing host and tumor biology that may be driving these disparities, in addition to the extrinsic environmental or lifestyle factors. Socioeconomic disparities with lower cancer literacy may lead to late presentation, poorer adherence to treatment, and other lifestyle factors such as unhealthy diet, obesity, and inadequate physical activity. These hardships may also result in greater allostatic load, which is in turn associated with aggressive BC features in disadvantaged populations. Epigenetic reprogramming may mediate the effects of the environment or lifestyle factors on gene expression, with ensuing differences in BC characteristics and outcome. There is increasing evidence that germline genetics can influence somatic gene alterations or expression, as well as modulate the tumor or immune microenvironment. Although the precise mechanisms remain elusive, this may account for the varying distribution of different BC subtypes across ethnicities. These gaps in our knowledge highlight the need to interrogate the multiomics landscape of BC in diverse populations, ideally in large-scale collaborative settings with standardized methodology for the comparisons to be statistically robust. Together with improving BC awareness and access to good quality health care, a holistic approach with insights of the biological underpinnings is much needed to eradicate ethnic disparities in BC outcomes.

Validation of the BOADICEA model for predicting the likelihood of carrying pathogenic variants in eight breast and ovarian cancer susceptibility genes

BOADICEA is a comprehensive risk prediction model for breast and/or ovarian cancer (BC/OC) and for carrying pathogenic variants (PVs) in cancer susceptibility genes. In addition to BRCA1 and BRCA2, BOADICEA version 6 includes PALB2, CHEK2, ATM, BARD1, RAD51C and RAD51D. To validate its predictions for these genes, we conducted a retrospective study including 2033 individuals counselled at clinical genetics departments in Denmark. All counselees underwent comprehensive genetic testing by next generation sequencing on suspicion of hereditary susceptibility to BC/OC. Likelihoods of PVs were predicted from information about diagnosis, family history and tumour pathology. Calibration was examined using the observed-to-expected ratio (O/E) and discrimination using the area under the receiver operating characteristics curve (AUC). The O/E was 1.11 (95% CI 0.97-1.26) for all genes combined. At sub-categories of predicted likelihood, the model performed well with limited misestimation at the extremes of predicted likelihood. Discrimination was acceptable with an AUC of 0.70 (95% CI 0.66-0.74), although discrimination was better for BRCA1 and BRCA2 than for the other genes in the model. This suggests that BOADICEA remains a valid decision-making aid for determining which individuals to offer comprehensive genetic testing for hereditary susceptibility to BC/OC despite suboptimal calibration for individual genes in this population.

Prognostic Significance of the CXCLs and Its Impact on the Immune Microenvironment in Ovarian Cancer

The chemokine (C-X-C motif) ligand (CXCL) family in tumor tissue is closely related to tumor growth, metastasis, and survival. However, the differential expression profile and prognostic value of the CXCLs in ovarian cancer (OC) have not been elucidated. Therefore, we studied the expression levels and mutations of CXCLs in OC patient in TCGA and various public databases. The expression differences of CXCLs in OC cancer tissues and normal tissues were compared through the Gene Expression Profiling Interactive Analysis (GEPIA) database. The effect of CXCLs on OC prognosis was analyzed using the Kaplan-Meier curves in GEPIA database. The impact of CXCLs on immune infiltration and clinicopathological outcomes in OC was assessed using the TIMER algorithm. Compared with normal tissues, we found that eight CXCLs were significantly differentially expressed in OC. The expression levels of CXCL9 (P = 0.0201), CXCL11 (P = 0.0385), and CXCL13 (P = 0.0288) were significantly associated with tumor stage. CXCL13 was the only gene that significantly affected both disease-free survival (DFS) and overall survival (OS) in OC, and higher CXCL13 transcript levels implied longer DFS and OS. Although there was no significant impact on DFS, CXCL10 (P = 0.0079) and CXCL11 (P = 0.0011) expression levels had a significant effect on OS in OC. At the same time, CXCLs were significantly associated with several immune-infiltrating cells in OC tissues. The CXCLs were significantly associated with one or more immune-infiltrating cells in OC tissue. CXCL13 was differentially expressed in OC and significantly affected the prognosis of patients and was a potential marker of OC prognosis.

Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients

BACKGROUND

Bilateral breast cancer (BBC), as well as ovarian cancer, are significantly associated with germline deleterious variants in BRCA1/2, while BRCA1/2 germline deleterious variants carriers can exquisitely benefit from poly (ADP-ribose) polymerase (PARP) inhibitors. However, formal genetic testing could not be carried out for all patients due to extensive use of healthcare resources, which in turn results in high medical costs. To date, existing BRCA1/2 deleterious variants prediction models have been developed in women of European or other descent who are quite genetically different from Asian population. Therefore, there is an urgent clinical need for tools to predict the frequency of BRCA1/2 deleterious variants in Asian BBC patients balancing the increased demand for and cost of cancer genetics services.

METHODS

The entire coding region of BRCA1/2 was screened for the presence of germline deleterious variants by the next generation sequencing in 123 Chinese BBC patients. Chi-square test, univariate and multivariate logistic regression were used to assess the relationship between BRCA1/2 germline deleterious variants and clinicopathological characteristics. The R software was utilized to develop artificial neural network (ANN) and nomogram modeling for BRCA1/2 germline deleterious variants prediction.

RESULTS

Among 123 BBC patients, we identified a total of 20 deleterious variants in BRCA1 (8; 6.5%) and BRCA2 (12; 9.8%). c.5485del in BRCA1 is novel frameshift deleterious variant. Deleterious variants carriers were younger at first diagnosis (P = 0.0003), with longer interval between two tumors (P = 0.015), at least one medullary carcinoma (P = 0.001), and more likely to be hormone receptor negative (P = 0.006) and HER2 negative (P = 0.001). Area under the receiver operating characteristic curve was 0.903 in ANN and 0.828 in nomogram modeling individually (P = 0.02).

CONCLUSION

This study shows the spectrum of the BRCA1/2 germline deleterious variants in Chinese BBC patients and indicates that the ANN can accurately predict BRCA deleterious variants than conventional statistical linear approach, which confirms the BRCA1/2 deleterious variants carriers at the lowest costs without adding any additional examinations.