Genetic testing is a key tool for cancer prevention through family history analysis and the identification of inherited mutations. Thus, testing for individuals at risk of hereditary breast and ovarian cancer (HBOC) is encouraged to implement control and prevention measures through genetic counselling [1
]. Uncovering the genetic causes of HBOC cases enables early detection and prevention. Due to its inheritable nature, family members may benefit from genetic counselling [2
Although hereditary cancer accounts for a small proportion of the total cases, in absolute numbers they represent a significant number of mutation carriers who can benefit from clinical management in order to reduce morbidity and mortality [4
After screening for BRCA1/2 genes, the underlying genetic predisposition remains elusive in a proportion of high risk cancer cases. Therefore, we undertook screening of other genes in a cohort of patients with a presumed genetic predisposition for breast and ovarian cancer, in whom germline mutations in BRCA1 and BRCA2 were previously ruled out.
DNA repair defects prompt genetic instability, a well-known carcinogenic trigger. Therefore, functional defects in any DNA repair gene can contribute to the accumulation of errors and, ultimately, to cellular transformation. In fact, most HBOC susceptibility genes encode proteins which are involved in DNA repair. Mutations in these genes compromise the effectiveness of DNA repair, leading to genomic instability. Reciprocally, the accumulation of these mutations would be promoted by genomic instability, and this mutagenic environment would eventually enhance tumour progression. Proteins, such as ATM, BARD1, and Fanconi Anemia (FA) BRIP1, ERCC4, PALB2, RAD51C and RAD51D proteins, are involved in DNA repair pathways and have previously been linked to HBOC susceptibility associated with low to moderate risks [5
Exploiting DNA repair defects of the mutated cells has emerged as a targeted therapy strategy. Germline mutations in HBOC susceptibility genes not only confer cancer risk to carriers, but may also determine the response to certain treatment options, providing the opportunity to customise chemotherapy [7
In Spain, particularly in our region, the standard practice for patients at high risk for HBOC is to screen germline mutations in BRCA1 and BRCA2 genes. Consequently, the purpose of this work is to investigate whether by increasing the number of genes tested (some BRCA-FA pathway genes involved in HBOC susceptibility and ATM
genes), more families could benefit from prevention measures according to SEOM Clinical Guidelines [3
]. Furthermore, it aims to be a first approach to select other clinically useful genes for better management in our BRCA negative families; and, hence, to implement a personalised panel for families that meet high-risk criteria in our target population.
The clinical management of HBOC families makes cancer prevention possible through the identification of individuals at high-risk. High penetrance genes explain a small number of cases, while it is also necessary to look for mutations in other moderate and low penetrance genes. Of these, genes which are crucial in DNA repair and DNA damage response have been postulated as good candidates.
The main goal of this work was to detect mutations in other genes to explain inherited breast/ovarian cancer predisposition, enabling the clinical management of the carrier families. Firstly, we focused on some FA/BRCA pathway genes such as BRIP1, ERCC4
has a pivotal role in the detection and response to DNA damage, and BARD1
mediating the initial nucleolytic resection of DNA lesions and the recruitment of RAD51
, we decided to examine these key DNA damage response genes as well. The FA genes were screened by heteroduplex analysis by capillary array electrophoresis (HA-CAE) [13
] or high resolution melting analysis (HRMA) as these techniques were used in our routine until 2018. Thereafter, we adopted NGS thus we decided to test ATM
with this technology. Our results demonstrate that increasing the number of assessed candidate genes, molecular diagnosis improves.
had been known to be linked to breast cancer predisposition in BRCA-negative families [14
]. Furthermore, ATM
mutations have been found in ovarian cancer [16
]. In accordance with this, we identified three ATM
pathogenic variants in the index-case with breast cancer, one of whom also developed an ovarian cancer (Table 1
). The patient II.5 (Figure 1
C), diagnosed with breast cancer at the age of 43, carried the ATM
variant c.3663G > A. Her family had, on the paternal side, two very early cancer cases at 25 (I.10) and 36 (I.11) years-old (Figure 1
C). Unfortunately, DNA was not available for segregation analysis.
c.8934_8935delTG variant was found in the III.12 breast cancer patient (Figure 1
d). Her daughter, IV.2, who carries the mutation, may benefit from prevention measures [2
]. This mutation was previously reported in an Ataxia-Telangiectasia family [17
]. In addition, other cancer types in this family have been associated with ATM
mutations such as thyroid [18
], ovarian [16
] and breast tumours [15
The variant c.4776+2T>C in ATM
), previously reported in a breast cancer case [19
], modifies a canonical splicing site, potentially resulting in a splicing disruption. In addition, cells from an individual, homozygous for this mutation, showed an increased radio-sensitivity [12
]. This mutation was identified in a triple-negative breast cancer patient at 52 years-old and ovarian cancer at the age of 60. It is worth noting that several cancer types associated with pathogenic ATM
mutations were all present in her family (Table 1
): three gastric cancer cases [20
], two breast cancers [19
], two pancreatic cancers [21
] and three colon cancers [22
]. To assess the pathogenic effect of this mutation, we have experimentally demonstrated that this genetic change causes an alteration of splicing (Figure 4
). Although this variant causes an in-frame deletion of 55 amino acid, it has been classified as pathogenic (ClinVar, and ACGM guidelines).
The implication of pathogenic BRIP1
variants in ovarian cancer predisposition have been described before [16
]. The c.484C > T BRIP1
mutation was identified in an ovarian and melanoma cancer patient (Figure 1
a, II.12). Interestingly, the mutation was inherited by her daughter, who developed breast cancer at age 32 (III.2).
loss of function variants have been identified in two breast cancer cases. The c.584+1G>A mutation has been previously published as part of a Spanish collaborative study [11
]. The patient has a strong breast cancer family history, with five affected women (Table 1
). Unfortunately, DNA of the other breast cancer cases was not available to confirm familial segregation. In fact, three out of the five affected women died immediately after being diagnosed, so we assume tumour aggressiveness. The other ERCC4
mutation—c.1251T>A—was identified in a bilateral breast cancer case (Table 1
). Three endometrial cancer cases (the mother and two sisters of the patient) and two gastric tumours are the family antecedents. Other authors have associated ERCC4
mutations with endometrial cancer [24
] and colorectal [26
]; however, until now, the relatives with endometrial cancer have refused genetic testing. Both mutations are classified as pathogenic according to the ACMG standards.
Only one pathogenic variant in the RAD51D
gene- c.94_95delGT- was detected in an ovarian cancer patient (Figure 1
B individual III.1, Table 1
). The association between RAD51D
pathogenic mutations and ovarian cancer has already been established [23
], endorsing the causal role of the c.94_95delGT RAD51D
mutation in the patient’s pathogenesis. Furthermore, her son, III.3, carried the mutation; accordingly, the following information could be taken into account for prevention and follow-up: COSMIC database records RAD51D
somatic mutations in gastric, prostatic, pancreatic and liver tumours. In fact, germline RAD51D
variants and susceptibility to prostate cancer has also been described [30
]. Clinical guidelines have been developed for some genes such as ATM, BRIP1, PALB2
], enabling genetic counselling.
A large proportion of the variants identified in genetic analysis present conflicts of interpretation [32
]; ambiguity concerning their molecular effect impairs clinical management. Therefore, it is essential to make an effort to classify these variants [33
]. Hence, another goal of this work was to characterise the spectrum of rare variants, other than pathogenic ones, which may lead to an increased risk for breast/ovarian cancer predisposition. The CADD tool seems very useful for identifying causal mutations with a high score of pathogenicity [34
]. Moreover, it offers a practical and unbiased approach for estimating the pathogenicity of human genetic variants by integrating many diverse annotations into a single, quantitative score [35
After CADD analysis, a total of 14 missense variants with high-CADD score were selected, apart from the eight properly pathogenic mutations. Interestingly, two variants altering the splicing, c.584+1G>A in ERCC4 and c.4776+2T>C in ATM, presented a high-CADD score, denoting a possible link between CADD output and cDNA analysis.
In practice, the CADD score alone could not be used for variant classification, but the algorithm might be useful for prioritising variants for further functional and segregation studies [35
Current records of the response to certain drugs, depending on the genetic profile, can serve as a reference [36
] for the chemotherapy regimen choice. The main challenge in the genetic diagnosis of hereditary cancer is to transfer the findings to clinical practice; integrating information from in silico tools and drug response records to allow us to make these mutations useful.
In a pharmacological context, the Cancer Genome Interpreter compiles information about the implications of these possible causal variants for drug response. It is worth noting that most of the variants with a high-CADD score have been catalogued as driver mutations at the somatic level, assuming that they confer an advantage to the cell, triggering the transformation. Regarding the therapeutic approach, these relevant mutations may be used for drug selection: for PALB2
mutations, a response of the tumours has been registered for PARP inhibitors [37
], mitomycin C [39
] and platinum compounds [40
]. for deleterious ERCC4
variants, the effectiveness of cisplatin is expected for disrupting mutations [41
]; PARP inhibitors are selectively toxic to tumours with RAD51C
], and tumours with ATM
mutations had a positive response to cisplatin [43
], and inhibitors of PARP1 [37
], ATR [44
] and DNA-PKc [46
Tumour onset in hereditary cancer is expected to be a distinguishing feature from sporadic cases: germline mutation would imply a high risk for early-onset cancer. According to this hypothesis, we checked whether the mean age of diagnosis was different between high-CADD score mutation carriers and non-carriers. Statistically, we could not discard the fact that the diagnosis age was the same in the two compared groups. This could be due to sporadic tumours that appear earlier as a consequence of other risk factors such as lifestyle. As a consequence, the inclusion of sporadic cancer cases in our cohort is possible. The immediate impact of the inclusion of sporadic cases is the presence of samples without genetic variants, which, at the same time, decrease the mean age of this group [47
Conversely, a trend was observed upon close examination of the family information: carrying a pathogenic or rare variants with high-CADD score mutation seems to be determined by the presence of a family history with more cases and more diverse tumour types. Interestingly, the statistical analysis confirmed this association between high-CADD score mutation carriers and family cancer history: patients with these mutations presented more cancer cases and more tumour types in their pedigrees. This supports the hypothesis that familial history is relevant in sample selection for cancer predisposition [49
]. In brief, we may face a possibly non-typified hereditary cancer syndrome, in view of the family history profile of our positive families (tumour type diversity beyond breast and ovarian cancer). In fact, different cancer syndromes have overlapping clinical features, so expanding the analysed gene set might imply a higher diagnostic yield.
4. Materials and Methods
The selected 180 cases were screened for deleterious mutations in the BRCA1 and BRCA2 genes, and resulting negatives. We have studied 180 probands from breast and ovarian cancer families meeting high-risk criteria, enrolled from the Regional Hereditary Cancer Prevention Program of Castilla-León (Spain). The participants in this study are ovarian or breast cancer patients who have first-degree ovarian cancer relatives in the same side of the family. Ethical approval for this study was obtained from Comité Ético de Investigación Clínica (CEIC). Informed consent, family history and clinical features were collected (The approval code from the ethical committee is PI-13-66 and it was obtained at the meeting of the Clinical Committee on 03/21/2013).
4.2. DNA and RNA Extraction
Genomic DNA from peripheral blood was automatically extracted by Roche MagNaPure® Compact, using the “MagNA Pure Compact Nucleic Acid Isolation Kit I—Large Volume” (Roche Diagnostics, Penzberg, Germany), following the manufacturer’s instructions. RNA was extracted from peripheral blood lymphocytes using the GeneMATRIX Human Blood RNA Purification Kit (EURx, Gdánsk, Poland). DNA concentration was measured in a NanoDrop™ (NanoDrop 2000c, ThermoFisher Scientific, Waltham, MA, USA).
4.3. Mutation Screening
The entire coding sequence and splicing sites of PALB2
were screened using HA-CAE [13
were screened by HRMA.
specific primers were designed with the UMelt software [50
] Ideally, amplicons ranged from 100–250 bp with a single melting peak. Our design targeted the coding exons and the corresponding exon/intron boundaries. Sequences of primers are available upon request.
PCR (HRMA were conducted in a LightCycler 480 Instrument (Roche Diagnostics, Penzberg, Germany). All reactions were performed in 10 μL final volume. PCR annealing temperatures (Ta) and MgCl2
concentrations were optimised for each amplicon, lastly confirmed by direct sequencing. In brief, for PCR reactions, we used the LightCycler®
480 High-Resolution Melting Master Mix kit (Ref: 04909631001, Roche): Mix HRM Roche 1×, 2.5 mM MgCl2
, (3.5 mM of MgCl2
when the amplification was suboptimal), 2.5 μM each forward and reverse primers and 2 ng/μL of genomic DNA. Thermal cycling consisted of an initial 10-minute hold at 95 °C, followed by 10 s hold at 95 °C, 15 s hold at the specific Ta, and 20 s hold at 72 °C for 40 cycles. Consecutively, HRMA consisted in a 65 °C to 95 °C melting gradient with a 0.02 °C/s ramp rate and continuous 25 acquisitions/°C mode. The LightCycler 480 Software version 1.5 (Roche Diagnostics, Indianapolis, IN, USA) was used for the melting curve analysis. After checking the melting curves, we selected the temperature to normalise data. When the curves differed in shape and/or melting temperature, the corresponding samples were subsequently sequenced. Primers were designed using Primer3 tool software (http://bioinfo.ut.ee/primer3-0.4.0/
were sequenced using MiSeq Technology at the Centre for Medical Genetics Ghent, as previously described [51
Mutation nomenclature was based on the following reference sequences: ATM NM_000051.3; BARD1 NM_000465.3; BRIP1 NM_032043.2; ERCC4 NM_005236.2; PALB2 NM_024675.3; RAD51C NM_058216.1; RAD51D NM_002878.3.
4.4. Sanger Sequencing
Direct automated Sanger sequencing was used to confirm the results detected by screening methods and massive parallel sequencing. For that purpose, we used the BigDye Terminator Sequencing Kit v3.1 (Applied Biosystems, Foster City, CA, USA) on an ABI 3100 DNA Sequencer (four capillaries; Applied Biosystems). Co-segregation studies were conducted when possible.
Variants predicted as disrupters of splicing in the Human Splicing Finder TM 3.0 (HSF) software (http://www.umd.be/HSF3/
) were selected to perform cDNA-based analysis. Total RNA isolated from lymphocytes was reverse transcribed into cDNA using the Transcriptor First Strand cDNA Synthesis Kit (Roche), according to the manufacturer’s protocol. Subsequently, we performed a PCR to evaluate the transcription. The products were separated in low melting 2% agarose gel and visualised with RedSafe™ nucleic acid staining solution (iNtRON Biotechnology, Korea) Isolated bands were extracted using NucleoSpin®
Gel and PCR Clean-up (Macherey-Nagel, Düren, Germany) and subsequently sequenced.
We designed the primer pair −29 Forward (5′-TGTGAGCAAGCAGCTGAAACAA-3′) and 33 Reverse (5′- TTCACCAGTGTGGTTTATTGCCA-3′)— to evaluate the transcript spanning exons 29–33 so as to characterise the splicing effect of the c.4776+2T>C ATM variant. The RT-PCR reaction consisted of a 1X Buffer A, 0.5 µM forward and reverse primers, 0.32 mM dNTP Mix, 1 Unit of Kappa Taq DNA Polymerase, 12 µL of the cDNA generated in a final volume of 100 µL. The cycling conditions were denaturation at 95 °C for 3 min, 35 cycles at 95 °C for 30 s, 62 °C for 30 s, and 72 °C for 50 s, followed by a final extension at 72 °C for 10 min.
4.6. In-Silico Analyses
Mutations with protein annotations were analysed using the MutationMapper (http://www.cbioportal.org/mutation_mapper
), the cancer genome interpreter (https://www.cancergenomeinterpreter.org
) and HSF. Mutations that lead to premature truncation of the protein, frameshift, nonsense, and splice site, were classified as deleterious mutation. On the other hand, missense variants with minor allele frequency (MAF) <0.01 according to ExAC data were selected to further in silico research (hereinafter rare variants). Combined Annotation-dependent Depletion (CADD) was applied for both deleterious mutations and rare variants. In the CADD method, the scaled- C-scores are related with the top-ranked pathogenicity: to CADD-Score-10 you are in the top 10% of the disrupting mutations, to CADD-Score-20, top 1%, CADD-Score-25, top 0.5% and to CADD-Score-30, 0.1%. CADD integrates diverse annotations into a single score by contrasting variants that survived natural selection with simulated mutations [35
]. We considered variants with a CADD-score of >25 as possibly pathogenic (top 0.5% of disrupting variants).
4.7. Variant Classification
Variants were classified as deleterious if they originated a premature stop codon, if they were located in canonical splice sites, or if there was literature evidence (ACGM guidelines, ENIGMA classification rules). The potential deleteriousness of the remaining rare variants was evaluated using the CADD method.
4.8. Genotype-Phenotypic Correlations and Statistical Analysis
Personal and family data and mutation profiling of the samples were compiled and explored, looking for genotype–phenotypic correlations. Statistical tests were carried out using the R Project for Statistical Computing (v.3.5.1). A one-sided t-test was used for two-group means comparison, and Pearson’s chi-squared test with Yates’ continuity correction was used to evaluate the association between two categorical variables.