A Genetic Basis for Luminal and Basal-Type Breast Cancer

In the Western world, breast cancer not only is the most frequently diagnosed cancer in women, but also the second leading cause of cancer death. Clinically, breast cancer is a heterogeneous disease. About two-thirds of breast cancer patients survive their disease, whereas, one-third of breast cancer patients will die of metastases of their primary cancer within 15 years from diagnosis. Therefore, it is important for clinicians to accurately predict the prognosis and most appropriate therapy for each breast cancer patient. However, appropriate molecular targets have as yet not been identified for most breast cancer subtypes, implying suboptimal treatment for a significant fraction of the breast cancer patients. Thus, a better understanding of the disease is needed to improve upon current methods to treat breast cancer patients. In this thesis, we set out to determine the genetic basis for the two major subtypes of breast cancer, by mutation screening of 27 known cancer genes in a model of human breast cancer cell lines. Two distinct mutation profiles were identified: a “luminal mutation profile” among luminal-type breast cancer cell lines and a “basal mutation profile” among basal-type breast cancer cell lines. The gene mutation profiles give insight in the mechanisms of breast carcinogenesis. For example, we found that mutation and hypermethylation of the E-cadherin gene, two mechanisms involved in tumor suppre

Identifying Transcripts with Tandem Duplications from RNA‐Sequencing Data to Predict BRCA1‐Type Primary Breast Cancer

SIMPLE SUMMARY: Homologous recombination repair deficiency (HRD) is a biomarker for the response to PARP inhibitor anti-cancer treatment. Therefore, methods that detect the HRD phenotype in cancers in a (cost-)effective manner are pivotal. In this respect, the HRDetect and CHORD algorithms were developed to classify (the type of) HRD cancers from whole genome sequencing data. In addition, functional assays have also been established, but these require fresh cancer tissue. Here we present a novel method to specifically classify BRCA1-type HRD from RNA-sequencing data with high sensitivity. BRCA1-type cancers typically display small (<10 kb) tandem duplications, in contrast to BRCA2-type cancers. By detecting these small TDs among transcripts, we increase the toolbox for detecting HRD with a method that does not require whole genome sequencing of both tumor and normal tissue. ABSTRACT: Patients with cancers that are deficient for homologous recombination repair (HRD) may benefit from PARP inhibitor treatment. Therefore, methods that identify such cancers are crucial. Using whole genome sequencing data, specific genomic scars derived from somatic mutations and genomic rearrangements can identify HRD tumors, with only BRCA1-like HRD cancers profoundly displaying small (<10 kb) tandem duplications (TDs). In this manuscript we describe a method of detecting BRCA1-type HRD in breast cancer (BC) solely from RNA sequencing data by identifying TDs surfacing in transcribed genes. We find that the number of identified TDs (TD-score) is significantly higher in BRCA1-type vs. BRCA2-type BCs, or vs. HR-proficient BCs (p = 2.4 × 10(−6) and p = 2.7 × 10(−12), respectively). A TD-score ≥2 shows an 88.2% sensitivity (30 out of 34) to detect a BRCA1-type BC, with a specificity of 64.7% (143 out of 221). Pathway enrichment analyses showed genes implicated in cancer to be affected by TDs of which PTEN was found significantly more frequently affected by a TD in BRCA1-type BC. In conclusion, we here describe a novel method to identify TDs in transcripts and classify BRCA1-type BCs with high sensitivity

Elucidating the underlying functional mechanisms of breast cancer susceptibility through post-GWAS analyses

Genome-wide association studies (GWAS) have identified more than 170 single nucleotide polymorphisms (SNPs) associated with the susceptibility to breast cancer. Together, these SNPs explain 18% of the familial relative risk, which is estimated to be nearly half of the total familial breast cancer risk that is collectively explained by low-risk susceptibility alleles. An important aspect of this success has been the access to large sample sizes through collaborative efforts within the Breast Cancer Association Consortium (BCAC), but also collaborations between cancer association consortia. Despite these achievements, however, understanding of each variant's underlying mechanism and how these SNPs predispose women to breast cancer remains limited and represents a major challenge in the field, particularly since the vast majority of the GWAS-identified SNPs are located in non-coding regions of the genome and are merely tags for the causal variants. In recent years, fine-scale mapping studies followed by functional evaluation of putative causal variants have begun to elucidate the biological function of several GWAS-identified variants. In this review, we discuss the findings and lessons learned from these post-GWAS analyses of 22 risk loci. Identifying the true causal variants underlying breast cancer s

Elucidating the Underlying Functional Mechanisms of Breast Cancer Susceptibility Through Post-GWAS Analyses

Genome-wide association studies (GWAS) have identified more than 170 single nucleotide polymorphisms (SNPs) associated with the susceptibility to breast cancer. Together, these SNPs explain 18% of the familial relative risk, which is estimated to be nearly half of the total familial breast cancer risk that is collectively explained by low-risk susceptibility alleles. An important aspect of this success has been the access to large sample sizes through collaborative efforts within the Breast Cancer Association Consortium (BCAC), but also collaborations between cancer association consortia. Despite these achievements, however, understanding of each variant's underlying mechanism and how these SNPs predispose women to breast cancer remains limited and represents a major challenge in the field, particularly since the vast majority of the GWAS-identified SNPs are located in non-coding regions of the genome and are merely tags for the causal variants. In recent years, fine-scale mapping studies followed by functional evaluation of putative causal variants have begun to elucidate the biological function of several GWAS-identified variants. In this review, we discuss the findings and lessons learned from these post-GWAS analyses of 22 risk loci. Identifying the true causal variants underlying breast cancer susceptibility and their function not only provides better estimates of the explained familial relative risk thereby improving polygenetic risk scores (PRSs), it also increases our understanding of the biological mechanisms responsible for causing susceptibility to breast cancer. This will facilitate the identification of further breast cancer risk alleles and the development of preventive medicine for those women at increased risk for developing the disease

The benefit of adding polygenic risk scores, lifestyle factors, and breast density to family history and genetic status for breast cancer risk and surveillance classification of unaffected women from germline CHEK2 c.1100delC families

To determine the changes in surveillance category by adding a polygenic risk score based on 311 breast cancer (BC)-associated variants (PRS311), questionnaire-based risk factors and breast density on personalized BC risk in unaffected women from Dutch CHEK2 c.1100delC families. In total, 117 unaffected women (58 heterozygotes and 59 non-carriers) from CHEK2 families were included. Blood-derived DNA samples were genotyped with the GSAMDv3-array to determine PRS311. Lifetime BC risk was calculated in CanRisk, which uses data from the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA). Women, were categorized into three surveillance groups. The surveillance advice was reclassified in 37.9 % of heterozygotes and 32.2 % of non-carriers after adding PRS311. Including questionnaire-based risk factors resulted in an additional change in 20.0 % of heterozygotes and 13.2 % of non-carriers; and a subanalysis showed that adding breast density on top shifted another 17.9 % of heterozygotes and 33.3 % of non-carriers. Overall, the majority of heterozygotes were reclassified to a less intensive surveillance, while non-carriers would require intensified surveillance. The addition of PRS311, questionnaire-based risk factors and breast density to family history resulted in a more personalized BC surveillance advice in CHEK2-families, which may lead to more efficient use of surveillance.</p

GATA3 mRNA expression, but not mutation, associates with longer progression-free survival in ER-positive breast cancer patients treated with first-line tamoxifen for recurrent disease

In breast cancer, GATA3 mutations have been associated with a favorable prognosis and the response to neoadjuvant aromatase inhibitor treatment. Therefore, we investigated whether GATA3 mutations predict the outcome of tamoxifen treatment in the advanced setting. In a retrospective study consisting of 235 hormone-naive patients with ER-positive breast cancer who received tamoxifen as first-line treatment for recurrent disease, GATA3 mutations (in 14.0% of patients) did not significantly associate with either the overall response rate (ORR) or with the length of progression-free survival (PFS) after the start of tamoxifen therapy. Interestingly, among 148 patients for whom both mutation and mRNA expression data were available, GATA3 mutations associated with an increased expression of GATA3. However, only 23.7% of GATA3 high tumors had a mutation. Evaluation of the clinical significance of GATA3 mRNA revealed that it was associated with prolonged PFS, but not with the ORR, also in multivariate analysis. Thus, GATA3 mRNA expression, but not GATA3 mutation, is an independent predictor of prolonged PFS in ER-positive breast cancer patients who received first-line tamoxifen for recurrent disease. Besides GATA3 mutation, other mechanisms must exist that underlie increased GATA3 levels

Progression-free survival and overall survival after BRCA1/2-associated epithelial ovarian cancer:A matched cohort study

INTRODUCTION: Germline BRCA1/2-associated epithelial ovarian cancer has been associated with better progression-free survival and overall survival than sporadic epithelial ovarian cancer, but conclusive data are lacking. METHODS: We matched 389 BRCA1-associated and 123 BRCA2-associated epithelial ovarian cancer patients 1:1 to sporadic epithelial ovarian cancer patients on year of birth, year of diagnosis, and FIGO stage ( = IIB). Germline DNA test was performed before or after epithelial ovarian cancer diagnosis. All patients received chemotherapy. We used Cox proportional hazards models to estimate the associations between mutation status (BRCA1 or BRCA2 versus sporadic) and progression-free survival and overall survival. To investigate whether DNA testing after epithelial ovarian cancer diagnosis resulted in survival bias, we performed additional analyses limited to BRCA1/2-associated epithelial ovarian cancer patients with a DNA test result before cancer diagnosis (n = 73 BRCA1; n = 9 BRCA2) and their matched sporadic controls. RESULTS: The median follow-up was 4.4 years (range 0.1-30.1). During the first three years after epithelial ovarian cancer diagnosis, progression-free survival was better for BRCA1 (HR 0.88, 95% CI 0.74-1.04) and BRCA2 (HR 0.58, 95% CI 0.41-0.81) patients than for sporadic patients. Overall survival was better during the first six years after epithelial ovarian cancer for BRCA1 (HR 0.7, 95% CI 0.58-0.84) and BRCA2 (HR 0.41, 95% CI 0.29-0.59) patients. After surviving these years, survival benefits disappeared or were in favor of the sporadic patients. CONCLUSION: For epithelial ovarian cancer patients who received chemotherapy, we confirmed survival benefit for BRCA1 and BRCA2 germline pathogenic variant carriers. This may indicate higher sensitivity to chemotherapy, both in first line treatment and in the recurrent setting. The observed benefit appears to be limited to a relatively short period after epithelial ovarian cancer diagnosis

Recurrent HOXB13 mutations in the Dutch population do not associate with increased breast cancer risk

The HOXB13 p.G84E mutation has been firmly established as a prostate cancer susceptibility allele. Although HOXB13 also plays a role in breast tumor progression, the association of HOXB13 p.G84E with breast cancer risk is less evident. Therefore, we comprehensively interrogated the entire HOXB13 coding sequence for mutations in 1,250 non-BRCA1/2 familial breast cancer cases and 800 controls. We identified two predicted deleterious missense mutations, p.G84E and p.R217C, that were recurrent among breast cancer cases and further evaluated their association with breast cancer risk in a larger study. Taken together, 4,520 familial non-BRCA1/2 breast cancer cases and 3,127 controls were genotyped including the cases and controls of the whole gene screen. The concordance rate for the genotyping assays compared with Sanger sequencing was 100%. The prostate cancer risk allele p.G84E was identified in 18 (0.56%) of 3,187 cases and 16 (0.70%) of 2,300 controls (OR = 0.81, 95% CI = 0.41-1.59, P = 0.54). Additionally, p.R217C was identified in 10 (0.31%) of 3,208 cases and 2 (0.087%) of 2,288 controls (OR = 3.57, 95% CI = 0.76-33.57, P = 0.14). These results imply that none of the recurrent HOXB13 mutations in the Dutch population are associated with breast cancer risk, although it may be worthwhile to evaluate p.R217C in a larger study