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Article

Rare Germline Variants in DNA Repair Genes Detected in BRCA-Negative Finnish Patients with Early-Onset Breast Cancer

by
Viivi Kurkilahti
1,
Venkat Subramaniam Rathinakannan
1,
Erja Nynäs
2,
Neha Goel
1,
Kristiina Aittomäki
3,
Heli Nevanlinna
2,
Vidal Fey
1,4,
Minna Kankuri-Tammilehto
5,† and
Johanna Schleutker
1,6,*,†
1
Cancer Research Unit and FICAN West Cancer Centre, Institute of Biomedicine, University of Turku and Turku University Hospital, 20014 Turku, Finland
2
Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, 00280 Helsinki, Finland
3
Department of Clinical Genetics, University of Helsinki and Helsinki University Hospital, 00250 Helsinki, Finland
4
Faculty of Medicine and Health Technology/BioMediTech, Tampere University, 33520 Tampere, Finland
5
Department of Clinical Genetics, Turku University Hospital, 20520 Turku, Finland
6
Department of Genomics, Laboratory Division, Turku University Hospital, 20520 Turku, Finland
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2024, 16(17), 2955; https://doi.org/10.3390/cancers16172955
Submission received: 24 June 2024 / Revised: 14 August 2024 / Accepted: 20 August 2024 / Published: 24 August 2024
(This article belongs to the Section Cancer Causes, Screening and Diagnosis)
Browse Figures
Versions Notes

Abstract

:

Simple Summary

Breast cancer is the most common cancer in females. Although rare in the younger population, individuals with a susceptible genetic background are at higher risk of breast cancer. A study was conducted on 63 Finnish breast cancer patients without any BRCA1/2 variants who had an onset of breast cancer at age 40 or younger. These patients were sequenced, and variants in DNA repair genes were identified. These variants were then prioritized based on their allele frequency in the population and pathogenicity prediction scores to identify potential new risk variants. Seventy-two deleterious variants were found, including eight novel variants. For the novel variants, protein structure modeling was conducted, and all deleterious variants were validated in another Finnish BRCA1/2-negative breast cancer population.

Abstract

Background: Breast cancer is the most common malignancy, with a mean age of onset of approximately 60 years. Only a minority of breast cancer patients present with an early onset at or before 40 years of age. An exceptionally young age at diagnosis hints at a possible genetic etiology. Currently, known pathogenic genetic variants only partially explain the disease burden of younger patients. Thus, new knowledge is warranted regarding additional risk variants. In this study, we analyzed DNA repair genes to identify additional variants to shed light on the etiology of early-onset breast cancer. Methods: Germline whole-exome sequencing was conducted in a cohort of 63 patients diagnosed with breast cancer at or before 40 years of age (median 33, mean 33.02, range 23–40 years) with no known pathogenic variants in BRCA genes. After filtering, all detected rare variants were sorted by pathogenicity prediction scores (CADD score and REVEL) to identify the most damaging genetic changes. The remaining variants were then validated by comparison to a validation cohort of 121 breast cancer patients with no preselected age at cancer diagnosis (mean 51.4 years, range 28–80 years). Analysis of novel exonic variants was based on protein structure modeling. Results: Five novel, deleterious variants in the genes WRN, RNF8, TOP3A, ERCC2, and TREX2 were found in addition to a splice acceptor variant in RNF4 and two frameshift variants in EXO1 and POLE genes, respectively. There were also multiple previously reported putative risk variants in other DNA repair genes. Conclusions: Taken together, whole-exome sequencing yielded 72 deleterious variants, including 8 novel variants that may play a pivotal role in the development of early-onset breast cancer. Although more studies are warranted, we demonstrate that young breast cancer patients tend to carry multiple deleterious variants in one or more DNA repair genes.

1. Introduction

Breast cancer (BC) is the most common cancer among females worldwide and the second leading cause of cancer deaths in European countries, including Finland [1]. BC is usually diagnosed after menopause, with only 4–6% of BCs diagnosed prior to the age of 40 years [2,3]. Patients with early-onset BC (EOBC) tend to exhibit poorer prognosis likely due to its more aggressive tumor subtypes [4]. Among EOBC patients, BRCA1/2 mutation carriers tend to have a poorer prognosis [5].
BC is a heterogeneous group of diseases that can be classified into subtypes according to responses to therapies or according to the expression of molecular features [6,7]. EOBC patients have more triple-negative subtype tumors (TNBC) [8]. TNBC comprises the most aggressive cluster of all breast cancer types. TNBCs present with a rapid progression, a high probability of early recurrence and distant metastasis, and account for 15–20% of all BC cases [9].
Genetic predisposition is a pivotal risk factor particularly for developing EOBC and also BC at a later age. Up to 10% of all BC cases are estimated to be hereditary with an underlying high breast cancer risk, but only a fraction of BCs is associated with pathogenic variants (PVs) in BRCA1/2 genes [10]. Approximately 20 years ago in Finland, pathogenic BRCA1/2 variants were observed in 25% of high-risk breast and ovarian cancer families [11]. This has decreased over time in Finland as well as worldwide due to the refining of referral criteria and their easy discoverability online as well as widened gene test criteria and technological improvements in testing. Currently, in southwestern Finland, the amount of pathogenic BRCA1/2 variants is approximately 10% in all high-risk breast and ovarian cancer families. However, regional variations in the BRCA1/2 variants and their frequencies have been observed [12]. In addition to BRCA1/2, several other high-risk cancer susceptibility genes have been previously found. In the Finnish population, also unique low and intermediate risk alleles have been identified [13]. The polygenic risk model explains the combined effect of genetic predisposition with additional variants that together create the overall cancer risk [14,15]. Thus, patients with aggressive and EOBC may carry several PVs that together lead to an elevated risk of developing breast cancer at an early age [10].
To date, the genetic predisposition factors remain unidentified in many EOBC patients despite increasing knowledge of PVs. To analyze the contribution of rare variants to the development of diseases such as BC, these variants require identification by DNA sequencing. As genome sequencing continues to identify more rare variants, their role in diseases will also become clearer with the accumulating data [16]. Rare variants can have distinctive and unique roles in gene function and expression, and they can display a larger population specificity, which present excellent possibilities for candidates of precision medicine. In this study, whole-exome sequencing (WES) and the created pipeline for variant calling and prioritization were used to identify novel and rare risk variants in DNA repair genes. To elucidate the role of these deleterious variants in the Finnish population, we carefully analyzed the clinical picture, validated the findings in another cohort of Finnish BC patients with a family history of BC and without known BRCA1/2 variants, and created protein modeling for novel variants.

2. Methods

2.1. Turku Whole-Exome Sequencing Set

2.1.1. Study Subjects

Genomic DNA samples from the blood of 63 individuals were used for WES. Study subjects were females with BC who had received genetic counseling on BC susceptibility in the Turku University Hospital between 1996 and 2018. The Department of Clinical Genetics at the University Hospital District of Southwest Finland provides a high level of specialized health care for three hospital districts. Some patients in our study received their cancer treatments in another hospital district, but the genetic counseling took place in Turku. All patients had previously provided a signed informed consent form. The Ethics Committee of the Hospital District of Southwest Finland approved the study.
All 63 patients were diagnosed with BC at the age of 40 years or younger (median 33, average 33.02, range 23–40 years). The cut-off of 40 years was selected based on the oncology literature [2,17]. Among the 63 patients, 18 (28.6%) were tested due to their young age of onset without a family history of breast or ovarian cancer, and others fulfilled the modified Lund criteria, which is used in the clinical evaluation of familial BC risk [12]. Seventeen (27%) patients were younger than 30 years at the time of the diagnosis, twelve patients (19%) suffered from TNBC, and five individuals (7.9%) were included in both subgroups. Twelve patients (19%) had bilateral BC (Table 1).
Clinical and histological parameters were obtained from the pathology reports. They included hormonal receptor status, HER2-mutational status, tumor grade, tumor histology, and age at diagnosis. Here, TNBC is defined as a tumor with the absence or very low levels (0–2%) of cells expressing ER and PR and an absence of HER2 overexpression [18]. The family history of cancer was obtained from the pedigrees and medical data used in the genetic counseling. An inclusion criterion was no known PV in prior BRCA1/2 analyzes. For population controls, we used genomic data from the gnomAD database [19].

2.1.2. Sample Preparation and Whole-Exome Sequencing

For whole-exome sequencing, we used genomic DNA, which was extracted from blood leukocytes with the Cytiva Nucleon DNA Extraction Kit BACC3 (Illustra, Fisher Scientific, Waltham, MA, USA). Exome capture and sequencing were conducted by CeGaT (Tübingen, Germany) with the Illumina HiSeq instrument (Illumina, Inc., San Diego, CA, USA). Library preparation was performed with 1 µg of genomic DNA per sample by the Agilent SureSelectXT Library Prep Kit and Agilent Sure SelectXT Human All Exon V6 enrichment kit (Agilent, Santa Clara, CA, USA). Genome coverage depth was on average 50× per sample.

2.1.3. Data Analysis

The pipeline for the analysis of the data was programmed using Nextflow [20], and each step of the pipeline was implemented as a module. This enabled us to store the results after each step in the analysis process, so that any failure in one of the steps does not require the entire process to be repeated. The quality control for the raw fastq files was performed via FASTQC [21]. The preprocessing step involved removing the adaptor sequences using the tool CutAdapt [22], so that reads below 70 bp and mapping quality lower than 20 were removed. The processed reads were aligned using the BWA-MEM [23] alignment tool against human reference genome (Hg38). Variant calling was conducted using GATK Haplotypecaller [24] and DeepVariant [25]. The resulting vcf files generated from the two variant callers were then combined to give a consensus file, which had the common SNPs and InDels from both callers.
Variant call files from all patients were combined using bcftools [26] to arrive at a single VCF file which was annotated using the Ensembl Variant Effect Predictor (VEP) [27] and downloaded cache files for assembly version GRCh38. For filtering, variants in the merged file were split into SNVs and InDels as the two classes require different approaches.

2.1.4. Variant Filtering

The filtering procedure was performed in R [28] and on the Linux command line, as well as by using biostatistical add-on packages for both platforms.
Both SNV and InDel variants were first tested for missing CADD scores [29]. This step was necessary since, in particular, InDels are not fully scored automatically due to the vast number of possible variations. As expected, missing CADD scores were found only in the InDel files. The following steps were conducted for both SNVs and InDels in the same way.
In the first filtering step, only variants in DNA repair genes were retained. The gene symbols for filtering were obtained from https://www.mdanderson.org/documents/Labs/Wood-Laboratory/human-dna-repair-genes.html [30], where an updated list of DNA repair genes is maintained. The symbols were then updated to their current version and converted to Ensembl Gene IDs by means of functions in the converted R package (https://cran.r-project.org/package=convertid, accessed on 21 March 2022). The resulting DNA repair gene variants were subjected to a general filter excluding variants with a CADD score smaller than 20 and non-canonical transcript variants. In addition to canonical transcript variants, all non-transcript variants were retained as well as all variants with missing CADD scores.
Next, variants were split into two groups for frequency filtering, rare variants with an allele frequency (AF) smaller than 0.01, and ultra-rare variants with no AF reported. AFs were obtained from the gnomAD database [31,32], where both the frequencies calculated from the exome sequencing cohort (gnomADe) and the frequencies calculated from the genome sequencing cohort (gnomADg) had to meet the threshold (or were missing). Exome AFs were obtained from gnomAD version 2 and genome AFs from gnomAD version 3. Both rare and ultra-rare variants were extracted, filtering each by the frequencies calculated for the gnomAD global cohort (gnomADe_AF and gnomADg_AF) and the gnomAD FIN cohort (gnomADe_FIN_AF and gnomADg_FIN_AF).
To arrive at the two main prioritization groups, all variants from the previous step were filtered by “Consequence”. Group 1 has variants that were categorized as “splice_site–altering”, “stop_gain”, “start_lost”, or “non_coding_transcript_exon” variants. Group 2 has only “non-synonymous” (e.g., frameshift) or “missense” variants. Group 2 was further filtered by the REVEL (Rare Exome Variant Ensemble Learner) score [33] for likely pathogenic variants using a threshold of 0.75. Variants with missing REVEL scores were also retained. These variants are considered subcategory 1 (Table 1).
Since the original project objective was to investigate DNA repair genes, the variant locations identified in the previous filtering round were used to obtain a list of genes affected by those variants. To discover any other less harmful variants in the same genes, the filtering was then repeated, starting with all variants found in the original merged VCF that were then mapped to the affected genes. The thresholds for allele frequency and REVEL score were relaxed, using AF < 0.02, which excludes common variants, and REVEL > 0.4, a value chosen according to the comparison of sensitivity and specificity in the supplementary section of the REVEL publication [33]. These variants are considered subcategory 2 (Table 1).

2.2. Validation Set Helsinki

To validate our findings, another Finnish patient series from the Helsinki region was analyzed for the respective variants. The additional patients consisted of 121 familial exome- or whole-genome-sequenced breast cancer patients from 77 families. The breast cancer index patients were recruited in the Helsinki University Hospital at the Departments of Oncology in 1997–1998 and 2000 [34,35] and Surgery in 2001–2004 [36], with additional familial patients recruited in the Department of Clinical Genetics [36,37,38]. Altogether, 99 patients were from 56 families with at least three members affected with BC or OC among first- or second-degree relatives; 21 patients had one affected first-degree relative, and 1 breast cancer index patient had a family history of other cancers. In more detail, 17 families also included OC and 9 included male BC; 6 of the breast cancer patients in this study were males. The mean age at breast cancer diagnosis among the patients was 51.4 years (range 28–80 years). No patient had a pathogenic BRCA1, BRCA2, TP53, PALB2, CHEK2, ATM, RAD51C, RAD51D, or FANCM variant. The genomic DNA used in the exome and genome sequencing was isolated from peripheral blood samples. The study was approved by the Ethics Committee of the Helsinki University Hospital, with informed consent obtained from all patients.

2.3. Protein Structure Modeling

The structural change was predicted for the five novel missense variants in the genes WRN(R732P), RNF8(C55W), TOP3A(S395C), ERCC2(Q698R), and TREX2(R152P). Other three novel variants were not included for protein modeling as these were a splice acceptor variant in RNF4 and two frameshift variants in EXO1 and POLE genes, respectively.
The PDB (Protein Data Bank) structures of the proteins were downloaded from the UNIPROT database (WRN-Q14191, RNF8-O76064, TOP3A-Q13472, ERCC2-P18074, TREX2-Q9BQ50). The wild structures were showing a 90% confidence score as per residue in the Alpha Fold Protein Structure Database. The mutations were created into these PDBs using the mutagenesis plugin in PYMOL. These wild and mutated tertiary structures were used for the energy minimization of molecule models with Steepest descent steps 1000, conjugate gradient steps 10, and default amber parameters in UCSF-Chimera [39].

3. Results

3.1. Turku Whole-Exome Sequencing Set Results

After the analysis pipeline (Figure 1), a total of 72 variants remained for 45 patients (Table 1), while 18 patients had no variants. All detected variants were heterozygous. Patient 433 (marked with ^ in Table 2) with bilateral BC and TNBC diagnosed at the age of 31 years was known to be a homozygote for the intermediate risk variant FANCM c.5101C>T. The patient did not have any other deleterious variants. A total of 27 of our 63 patients (67%) were found to have more than one deleterious variant after all filtering steps. One patient had a maximum of five different deleterious variants (Table 2).
Eight novel variants were found in eight different genes. Novel variants were WRN (chr8:31111721 G/C), ERCC2 (chr19:45352306 T/C), TREX2 (chrX:153444976 C/G), RNF8 (chr6:37360499 C/G), RNF4 (chr4:2490336 G/T), EXO1 (chr1:241861448-/T), POLE (chr12:132677395-/T), and TOP3A (chr17:18292743 T/A). The identified 64 known variants were located in 48 genes (Table 1). Among these, PALB2 (rs180177100) was the only variant that had been previously linked to BC susceptibility. Each novel variant was identified in one individual only.
Patient “634” carrying the novel variant in WRN (chr8:31111721 G/C) had TNBC (Table 2). The age of onset in this patient was 34. She also had another variant in WRN gene (rs11574410) and a novel variant in POLE (chr12:13267795-T), as well as a variant in BRCA1 (rs28897689). This patient did not show a family history of breast cancer, neither did she have Werner syndrome, which is a progeroid syndrome [40] (Table 2). Patient “435” with RNF8 (chr6:37360499 C/G) variant also did not show a family history of the disease. She was diagnosed at the age of 32. She also carried variants in WRN (rs78488552) and RECQL5 (rs565251228) genes (Table 1 and Table 2). Patient “623” with novel RNF4 (chr4:2490336 G/T) variant was diagnosed at 31 years of age and had a positive family history of BC. No other variants were found in this study, but she was known to carry a CHEK2 c.1100delC variant. Patient “440” with novel ERCC2 (chr19:45352306 T/C) variant had bilateral BC at the age of 34 and 37. She also had variants in BRCA2 (rs55712212) and PER1 (rs137923123).
The most deleterious variant based on its CADD score of 42 was detected in MLH3 (rs193219754). In our data, this variant was detected in patient “631”. This patient did not have a family history of BC. We also identified one additional deleterious variant in MLH3 (rs775001669), with a CADD score of 22,6. Patient “72” had this MLH3 variant together with other variants in POLQ (rs41540016) and in MSH3 (rs199791286). Through our pipeline, we identified five predicted deleterious variants in POLQ. One of these variants (rs41540016) was detected in four patients.

3.2. Validation Set Helsinki Results

In the validation cohort of 121 patients with familial BC with no existing BRCA1/2 mutations, 18 of our variants were found and 33 of the patients in the set were found to have at least one of the variants. However, none of the novel variants were detected in this sample set. Five of the patients had multiple variants. Overall, only five patients with a found variant were 40 years or younger at the time of diagnosis. Variants found in these young patients were PNKP rs201503405, BRCA2 rs11571833, ERCC4 rs1799802, LIG1 rs3730947, NEIL1 rs5745908, and SPIDR rs187418762. Only two of the CADD>30 variants were found in the validation set. These were BRCA2 rs11571833 which was found on two patients and NEIL1 rs5745908 which was found on two patients.

3.3. Protein Structure Modeling of Novel Variants

For six exonic novel variants present in this study, we present a lollipop diagram (Supplementary Figure S1), in which the mutation is marked in the amino acid chain with a pin alongside the functional domains. TREX2 is not shown because of a lack of knowledge of the protein’s functional domains, and RNF4 is not shown because the detected variant is in a splice acceptor site.
Novel WRN variant was interesting because the amino acid change is located in the DNA binding site of the protein and arginine is replaced by proline. This changes the conformation and bonding in the proteins active site (Figure 2).
For all other novel missense variants in ERCC2 (chr19:45352306 T/C), TREX2 (chrX:153444976 C/G), RNF8 (chr6:37360499 C/G), and TOP3A (chr17:18292743 T/A), we present the protein structure model in wild and mutated form. Active sites are presented in wild-type and mutated form in the figure next to the protein structure (Supplementary Figure S2).

4. Discussion

This study focused on BRCA1/2-negative early-onset BC patients with or without a family history of BC. All identified deleterious variants were classified as damaging by our pipeline. Furthermore, particular alterations were classified as very damaging variants. Due to the strict filtering criteria in our pipeline, a deleterious variant in DNA repair genes was not detected in all patients of the cohort.

4.1. Novel Variants Detected

Novel rare variants were identified in genes that have not previously been associated with BC. All novel variants were detected in only a single individual, and none of them were identified in the validation set. Further studies are warranted to elucidate whether these genes can be considered new risk genes for EOBC. It is possible that the respective novel variants are so-called ‘private mutations’ that do not occur in other individuals or families. Thus, additional family members, both affected and healthy at an older age, would need to be analyzed for the segregation of these variants. This knowledge would provide pivotal information to provide accurate genetic counseling for each family.
Although none of the genes, where these novel variants were found in, have been previously regarded as EOBC risk genes, there is limited evidence linking certain variants to cancer development. Especially in the European population, several WRN gene variants have been associated with an elevated risk of BC [41,42,43,44]. Interestingly, the same amino acid site of the variant found in our study (p.Arg732Pro) has been demonstrated as a stop codon variant causing Werner syndrome when homozygous [45]. This syndrome is a rare progressive disorder characterized by the appearance of unusually accelerated aging (progeria). It is common for affected Werner syndrome individuals to develop multiple cancers during their lifetime.
WRN is a part of the RecQ family and plays a crucial role in maintaining genomic stability. Importantly, the WRN protein interacts directly with BRCA1 in DNA double-strand breakage (DSB) repair. BRCA1 binds to the WRN C-terminal area and increases the helicase activity of WRN. Both are essential for maintaining genomic stability in the case of DSB [46]. The novel variant (chr8:31111721 G/C p.Arg732Pro) is located in the middle of the gene between two helicase domains (Figure 2). Based on our modeling, arginine creates multiple bonds, which maintain the stability of the protein. These bonds are lost when arginine is replaced with proline in p.Arg732Pro, causing instability for the structure (Figure 2). Arginine amino acid has a carboxylic (-COOH) group and one basic amino group (-NH2). While the proline amino acid does not have neither a carboxylic group nor an amino group, it comprises five membered nitrogen-containing heterocyclic rings [47].
RNF8 plays a central role in DNA double-stranded break (DSB) signal transduction. DSB damage is the most toxic type of DNA damage to cells and is related to genomic instability [48]. RNF8 is also an essential factor for the protection of telomere end integrity. Additionally, it takes part in cell cycle regulation [49]. The novel deleterious variant (chr6:37360499 C/G, p.C55W) is situated in the forkhead-associated (FHA) domain (Supplementary Figures S1 and S2), which is a phosphopeptide recognition domain found in many regulatory proteins. The cysteine in RNF8 is a non-essential and polar but uncharged amino acid. Tryptophan is a non-polar essential amino acid in the human body obtained from diet that works as a precursor for neurotransmitter serotonin. Elevated tryptophan levels are reported to be associated with BC [50].
One of the novel variants was detected in another RING Finger Protein gene, RNF4. The protein encoded by this gene contains a RING finger motif and acts as a transcription regulator. Homology-Directed Repair (HDR) is among its related pathways. To date, there are no studies that show a genetic predisposition to cancer in RNF4-associated variants, but this gene has been reported as a somatic mutation in multiple cancers [51]. RNF4 has been shown to play an independent role in tumor necrosis factor-alpha (TNF-alpha)-mediated cell death. Furthermore, RNF4 has a decisive impact on DNA double-strand break repair [52,53].
The ERCC2 gene is involved in nucleotide excision repair for the removal of various DNA lesions. Variants in this gene have been studied in Indian, Chinese, and Moroccan populations and have been linked to breast cancer susceptibility [54,55,56]. To the best of our knowledge, this is the first time a deleterious variant in this gene has been identified in Finnish BC patients. The novel ERCC2 variant was only found in one patient, but we also found three other variants in the same gene.
Via modeling the novel variants with predicted amino acid changes, we conclude that these variants are deleterious. All active sites change dramatically and therefore crucially affect protein function. The dysfunction of these DNA damage repair route proteins will contribute to an elevated mutation load. For the novel variants in RNF4 and RNF8, it is challenging to propose their role in EOBC without any additional data despite their high pathogenicity scores.
Novel variants were found in combination with other deleterious variants (Table 2), which makes it difficult to identify the likely causative ones. Especially the novel WRN variant, since it was only found in combination with another variant in the same gene. This could explain why the novel variants were not seen in the Helsinki cohort validation set, which included BC patients with a family history without a restriction of a particular young age at cancer diagnosis.

4.2. Previously Known Cancer Variants Detected

All patients in this study had been screened negative for BRCA1/2 variants. However, we found five variants in these two genes (rs81002862, rs28897758, rs28897689, rs11571833, and rs55712212). Although these variants are considered deleterious in our pipeline, there is prior conflicting evidence suggesting that these are benign [57]. For example, variant rs11571833 (chr13:32398489; c.9976A>T) is a rare truncating mutation in BRCA2, associated with low breast cancer risk [58]. Variant rs55712212 (chr13:32341176; c.6821G>T) in BRCA2 has been classified as likely benign or a variant of unknown significance (VUS) in ClinVar [59]. Therefore, these variants have not been considered pathogenic when study individuals were originally evaluated.
Multiple patients in our study carried more than one predicted deleterious variant (Table 2). Some have previously been associated with other cancer types. The genes MSH3 and MLH3 are known cancer genes originally identified in colorectal cancer. Currently, the cancer spectrum associated with these genes has broadened [60]. Importantly for the present study, a later meta-analysis of MSH3 variant polymorphisms has shown an association of this gene with an increased risk of BC [61,62].
Patient “72” showed variants in both MSH3 and MLH3 mismatch DNA repair genes. Hence, these variants may at least be partially responsible for the development of EOBC. Additionally, this patient also had a deleterious variant in POLQ. No other cancer cases in the family had been reported.
CHEK2 variant rs587782401 has been associated with breast cancer, and it has been classified as likely pathogenic in ClinVar [63]. CHEK2 is a known breast cancer susceptibility gene that usually causes a moderate risk of breast cancer, and its truncating variants have been associated with a 2- to 3-fold risk of breast cancer [64]. In some families, CHEK2 variants have been considered to be even more cancer-causing. Many splice site variants in CHEK2 lead to impaired splicing and very little or no full-length transcripts [65]. CHEK2 variants have been associated with a higher risk of bilateral breast cancer [66], which was the case with this patient as well.
FANCI has been identified as a possible risk gene for BC susceptibility [67]. Loss-of-function variants have been identified in breast cancer patients [68]. FANCL variant rs759217526 has also been reported in a Spanish study on familial BC [68]. In ClinVar, it has been reported as both pathogenic and benign [69].
We found a novel EXO1 variant with a high CADD score. Some EXO1 variants have been associated with higher susceptibility for breast cancer [70]. A high expression of Exo1 is associated with poor prognosis in BC [71].
In a previous study, it has been noted that POLQ is overexpressed in BC, which leads to a poor prognosis, and this overexpression also has effects on key cancer pathways [72]. POLQ has been associated with a poor outcome in prostate cancer [73]. In our pipeline, we found four different POLQ deleterious variants, of which some variants were also found in the Helsinki familial BC set.
Some of the known variants, which have previously been associated with other cancer types, were found in the validation cohort of 121 BRCA1/2 negative familial BC patients. The Helsinki validation set differs from the Turku BC patients, as the Helsinki BC patient cohort comprised patients without a limitation on their age at diagnosis, and all patients had a positive family history, whereas 28.6% of the patients in the original set had no family history of BC. Therefore, our patients present a rather specific subpopulation of EOBC patients. In the original set, the mean age at the time of diagnosis was 33.02 (range 23–40 years), and in Helsinki set the mean was 51.4 years (range 28–80 years). All Turku EOBC patients had an onset of cancer before or at the age of 40 years.

4.3. Polygenic Variants Detected

In this study, several patients had more than a single deleterious variant (Table 2), and 28.6% did not fulfill the Lund criteria. Only a few patients carried several deleterious variants in the Helsinki validation set. An earlier study by Määttä et al. described a different patient group and only included few patients with multiple PVs [10]. The previous study focused on families with several BCs in direct lineage without limitations with respect to the age at diagnosis. Based on these studies, we suggest that multiple deleterious or pathogenic variants are characteristic for EOBC regardless of family history. Our findings suggest that there are distinct BC subgroups with different genetic backgrounds. This is also in line with the fact that PVs have rarely been recognized in EOBC patients up to date. Our results demonstrate that further studies are warranted to identify optimal genetic testing in different BC subgroups. Moreover, this study sheds new light on the yet unrecognized EOBC subgroup profiles.
Breast cancer risk factors such as personal and family history, breast histopathology, lifestyle factors, high- and moderate-risk gene PVs, polygenic risk score (PRS), and prediction models such as the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) can be used to stratify the individual risk of breast cancer [74]. We found that a considerable fraction of the analyzed young breast cancer patients tended to carry multiple deleterious variants in DNA repair genes or even multiple variants in the same gene. The results of our study support the importance of a polygenic model in risk stratification.

4.4. The Homogenic Group of the Study’s EOBC Patients

The strength of this study is our well-selected, early-onset patient group without known pathogenic gene variations in BRCA1/2 genes. In this study, the patient cohort was well characterized and derived from a homogenous population (the Finnish population is a well-known founder population due to its strong genetic isolation over centuries). Our analysis was designed to detect rare, highly deleterious, and possibly pathogenic variants. For example, a well-known CHEK2 variant 1100delC that is known to moderately increase the risk of young-onset BC [38] was not detectable in our pipeline.

4.5. Limitations of the Study

Despite the very promising results, there are still many steps to be taken before these results can be used for clinical counseling. Functional analysis of the novel variants is warranted, as well as a validation of these findings in larger and more diverse cohorts. Our study focused purely on the DNA repair pathway genes, which exclude all deleterious variants in other genes. These variants can later be addressed, as WES was conducted.

5. Conclusions

This study identified multiple potential deleterious variants in DNA repair pathway genes. Novel deleterious variants were observed in the genes WRN, ERCC2, TREX2, RNF8, RNF4, EXO1, POLE, and TOP3A, which may partially explain EOBC. Furthermore, protein structure modeling supports the conclusion that the novel variants identified could potentially be pathogenic. Many of the identified variants have been previously associated with other cancer types. Additionally, we found an unexpectedly high number of patients carrying multiple variants. This presents multiple interesting cases at an individual level, as well as on a larger scale. Our findings suggest that EOBC patients without a family history should also be screened for pathogenic variants in a multigene panel, similar to the current routine treatment for outpatients. However, additional analyses are warranted, and our results require validation in larger cohorts.
Novel knowledge about polygenic risk factors may contribute to improvements in personalized screening and treatment modalities [75]. Our study sheds crucial light on the genetic architecture of EOBC and emphasizes that the polygenic model plays a pivotal role in unraveling its etiology.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers16172955/s1, Supplementary Figure S1: Lollipop diagrams showing the position of the novel variants in the gene. The pin shape (the “lollipop”) indicates the position of the identified novel variant in the gene. The position of the variants indicates that they play a key role in the formation of the protein. Supplementary Figure S2: Protein structures. Protein structures are shown by PYMOL in column A. Mutation site is marked with a square, and wild-type amino acid is highlighted with different color. In column B, each protein’s wild-type amino acid (highlighted color) is shown with bonding (dotted lines) to other amino acids. In column C, a mutated site with a replacing amino acid (highlighted color) is shown with bonding (dotted lines) to other amino acids.

Author Contributions

V.K. chose the patients for this study with M.K.-T. and completed laboratory work. V.F. created the analysis pipeline, and V.F. and V.S.R. computed bioinformatic analyses of the raw WES data. V.K. analyzed and interpreted the patient and variant data with J.S. and M.K.-T., and V.K. was a major contributor in writing the manuscript. V.S.R. and N.G. created the protein illustrations and contributed to writing the manuscript. J.S. and M.K.-T. contributed to supervision and manuscript writing. E.N. analyzed the Helsinki data. K.A. and H.N. provided the Helsinki study material. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by grants to JS from the Cancer Foundation Finland sr, the Sigrid Juselius Foundation, the Jane and Aatos Erkko Foundation, and the State Research Funding of Turku University Hospital. MKT received funding from the State Research Funding of Turku University Hospital. Funding for VK was received from the University of Turku, Turku University Foundation, and the Finnish Medical Foundation. The Helsinki study was supported by the Sigrid Jusélius Foundation and the Helsinki University Hospital Research Fund.

Institutional Review Board Statement

Ethics approval and consent to participate. All patients had given a signed informed consent to participate in this study. The Ethics Committee of the Hospital District of Southwest Finland has approved the study.

Informed Consent Statement

All patients had given a signed informed consent to participate in this study.

Data Availability Statement

Sequencing data cannot be shared publicly because the data consist of sensitive patient data. More specifically, the data consist of individual clinical data and individual genotypes for young adults. Data are available from the researchers/Turku University Hospital’s Ethics Committee for researchers who meet the criteria for access to confidential data. All other data generated or analyzed during this study are included in this published article or available from the corresponding author upon a reasonable request.

Acknowledgments

We wish to acknowledge the patients.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

BCBreast cancer
DCISDuctal carcinoma in situ
DSBDouble-strand break
EOBCEarly-onset breast cancer
EREstrogen receptor
HER2Human epidermal growth factor receptor 2
LCISLobular carcinoma in situ
PRProgesterone receptor
PRSPolygenic risk score
PVpathogenic variant
TNBCTriple-negative breast cancer
VUSVariant of unknown significance

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Cancers 16 02955 g001
Figure 1. Flow chart describing variant calling and variant prioritization. Variants were called from whole-exome sequencing (WES) data obtained from 63 patients using the Genome Analysis Toolkit (GATK) and DeepVariant software after alignment using the Burrows–Wheeler Alignment Tool (BWA). Consensus variants were annotated using the Ensembl VEP 108. Annotated variants were initially filtered by the Combined Annotation Dependent Depletion (CADD) score and allele frequency (AF) obtained from the Genome Aggregation Database (gnomAD). After the prioritization step using variant consequences, non-synonymous variants were further filtered by REVEL score.
Figure 1. Flow chart describing variant calling and variant prioritization. Variants were called from whole-exome sequencing (WES) data obtained from 63 patients using the Genome Analysis Toolkit (GATK) and DeepVariant software after alignment using the Burrows–Wheeler Alignment Tool (BWA). Consensus variants were annotated using the Ensembl VEP 108. Annotated variants were initially filtered by the Combined Annotation Dependent Depletion (CADD) score and allele frequency (AF) obtained from the Genome Aggregation Database (gnomAD). After the prioritization step using variant consequences, non-synonymous variants were further filtered by REVEL score.
Cancers 16 02955 g001
Cancers 16 02955 g002
Figure 2. The Werner protein structure. The Werner helicase structure is shown by PYMOL in green color, and the red-color-highlighted variant is arginine, which is changed to proline at 732. (chr8:31111721, G/C) The arginine-732 (red) is bonded (red dotted lines) with Leucine-735, Asparagine-731, and proline-733. Mutation arginine-732-proline as a point mutated structure is shown in red color. Proline-732 is shown bonded with Leucine-735 and Phenylalanine-730. Variant in WRN is Arg732Pro (chr8:31111721, G/C). Superimposition is shown among the wild and mutated structure of Werner helicase by using Chimera software (https://www.cgl.ucsf.edu/chimerax/), accessed on 21 March 2022. The wild-type is shown in cyan color and mutated type is shown in green color.
Figure 2. The Werner protein structure. The Werner helicase structure is shown by PYMOL in green color, and the red-color-highlighted variant is arginine, which is changed to proline at 732. (chr8:31111721, G/C) The arginine-732 (red) is bonded (red dotted lines) with Leucine-735, Asparagine-731, and proline-733. Mutation arginine-732-proline as a point mutated structure is shown in red color. Proline-732 is shown bonded with Leucine-735 and Phenylalanine-730. Variant in WRN is Arg732Pro (chr8:31111721, G/C). Superimposition is shown among the wild and mutated structure of Werner helicase by using Chimera software (https://www.cgl.ucsf.edu/chimerax/), accessed on 21 March 2022. The wild-type is shown in cyan color and mutated type is shown in green color.
Cancers 16 02955 g002
Table 1. Found variants. First column contains rs-number or bolded chromosomal position with the nucleotide change if no rs-number was available. Location: GRCh38. Consequence: the row is marked gray if variants’ consequences are stop gain, start lost, splice acceptor, or splice donor; these belong to Group 1. White rows are non-synonymous variants, which belong to Group 2. Group 2 is divided into two subcategories, of which subcategory 1 meets the criteria of AF < 0.01 and REVEL > 0.75 or missing. Subcategory 2 meets the criteria of AF < 0.02 and REVEL > 0.4. SIFT score: deleterious (0–0.05), tolerated (0.06–1). PolyPhen score: probably damaging (0.85–1.0), possibly damaging (0.15–0.85), benign (0–0.15). REVEL: range 0–1; higher score signals greater likelihood for variant to be disease-causing. CADD-Phred: higher score predicts the variant to be more deleterious, e.g., score >20 signals it belonging to 1% most deleterious, >30 to 0.1% most deleterious, and >40 to 0.01%.
Table 1. Found variants. First column contains rs-number or bolded chromosomal position with the nucleotide change if no rs-number was available. Location: GRCh38. Consequence: the row is marked gray if variants’ consequences are stop gain, start lost, splice acceptor, or splice donor; these belong to Group 1. White rows are non-synonymous variants, which belong to Group 2. Group 2 is divided into two subcategories, of which subcategory 1 meets the criteria of AF < 0.01 and REVEL > 0.75 or missing. Subcategory 2 meets the criteria of AF < 0.02 and REVEL > 0.4. SIFT score: deleterious (0–0.05), tolerated (0.06–1). PolyPhen score: probably damaging (0.85–1.0), possibly damaging (0.15–0.85), benign (0–0.15). REVEL: range 0–1; higher score signals greater likelihood for variant to be disease-causing. CADD-Phred: higher score predicts the variant to be more deleterious, e.g., score >20 signals it belonging to 1% most deleterious, >30 to 0.1% most deleterious, and >40 to 0.01%.
VariantGeneLocationNucleotide ChangeEffect on ProteinConsequenceSubcategorygnomADe FIN AFgnomADg FIN AFSIFTPolyPhenREVELCADD PHRED
rs193219754MLH3chr14:75039918c.3563C>Gp.Ser1188Terstop gained 0.0024910.003159NANANA42
rs180177100PALB2chr16:23635306c.1240C>Tp.Arg414Terstop gained 00NANANA37
rs11574410WRNchr8:31173019c.4216C>Tp.Arg1406Terstop gained 0.00064690.0002832NANANA36
rs81002862BRCA2chr13:32380005c.9118-2A>GNAsplice acceptor 0.00036970.0001885NANANA35
rs11571833BRCA2chr13:32398489c.9976A>Tp.Lys3326Terstop gained 0.010860.01045NANANA35
rs5745908NEIL1chr15:75349341c.434+2T>CNAsplice donor 0.00180.001508NANANA34
rs587782401CHEK2chr22:28734401c.319+2T>ANAsplice donor 0.00055480.0003764NANANA34
rs766240074RAD54Lchr1:46273748c.1610+1G>ANAsplice donor 4.968 × 10−50NANANA33
chr4:2490336 G/TRNF4chr4:2490336c.-157-1G>TNAsplice acceptor NANANANANA33
rs756188698RAD18chr3:8899048c.1169-1G>CNAsplice acceptor 0.00023989.457 × 10−5NANANA28.9
rs11572913GTF2H3chr12:123633862c.3G>Ap.Met1?start lost 0.00071120.0005650.02lc0.273NA24.8
rs187418762SPIDRchr8:47713484c.2189-5G>ANAsplice region, splice polypyrimidine tract, intron 0.012860.01198NANANA20.5
rs149243307FANCIchr15:89260841c.286G>Ap.Glu96Lysmissense, splice region20.0018480.001507010.44833
rs41540016POLQchr3:121436275c.7390G>Ap.Ala2464Thrmissense, splice region20.013810.01208010.8433
chr1:241861448 -/TEXO1chr1:241861447-241861448c.987dupp.Lys330Terframeshift1NANANANANA33
rs773570504ATMchr11:108326152-108326153c.6908dupp.Glu2304GlyfsTer69frameshift14.625 × 10−59.56 × 10−5NANANA33
rs762390984FANCIchr15:89301393-89301405c.2957_2969delp.Val986AlafsTer39frameshift10.0029570.002454NANANA33
rs759217526FANCLchr2:58159793-58159794c.1096_1099dupp.Thr367AsnfsTer13frameshift10.0018140.002649NANANA33
rs199791286MSH3chr5:80778737c.2336G>Ap.Arg779Hismissense10.0012940.001415010.88432
chr8:31111721 G/CWRNchr8:31111721c.2195G>Cp.Arg732Promissense2NANA010.49931
chr12:132677395 -/TPOLEchr12:132677394-132677395c.769dupp.Ile257AsnfsTer6frameshift1NANANANANA31
rs28363284RAD51Dchr17:35103294c.698A>Gp.Glu233Glymissense10.0011850.0017970.040.973NA29.9
rs746243211MSH3chr5:80672754c.923A>Tp.Lys308Metmissense100010.82329.7
rs137923123PER1chr17:8147713c.1349G>Ap.Arg450Hismissense10.0036810.00282301NA29.2
rs373080718TOP3Achr17:18277728c.2774C>Tp.Pro925Leumissense14.623 × 10−500.010.999NA29
rs2306211POLQchr3:121432937c.7640C>Tp.Ala2547Valmissense20.0073470.0062230.0310.57128.8
rs200535477RECQL5chr17:75627670c.2828G>Ap.Arg943Hismissense10.0097980.00820101NA28.7
rs202068855RPA1chr17:1880615c.1165C>Tp.Arg389Trpmissense20.015020.015201NA28.1
rs144564120ERCC2chr19:45352249c.2150C>Gp.Ala717Glymissense14.624 × 10−500.010.015NA28.1
rs28897758BRCA2chr13:32394734c.1267T>Gp.Cys423Glymissense10.00046190.000659010.78828
rs34001746TOP3Achr17:18285268c.1751T>Gp.Leu584Argmissense10.00046190.0006590.020.803NA27.3
rs121913016ERCC2chr19:45357368c.1381C>Gp.Leu461Valmissense14.633e-05000.982NA27.3
rs1805378NTHL1chr16:2044652c.503T>Cp.Ile168Thrmissense10.00043520.0003766010.87627.1
rs34642881RECQL4chr8:144517415c.212A>Gp.Glu71Glymissense, splice region10.0045110.0059410.020.803NA26.6
rs17879961CHEK2chr22:28725099c.470T>Cp.Ile157Thrmissense10.0045110.0059410.070.514NA26.5
rs142213781NEIL1chr15:75353853c.833C>Tp.Thr278Ilemissense20.0020860.002352010.56326.4
rs562132292ERCC2chr19:45357290c.1459C>Tp.Arg487Trpmissense10.00032720.000659100.998NA26.4
chr6:37360499 C/GRNF8chr6:37360499c.165C>Gp.Cys55Trpmissense2NANA010.74726.3
rs149253459FAAP100chr17:81547649c.1433A>Gp.Gln478Argmissense10.0028940.00160.010.997NA26.2
rs750771205ATMchr11:108289000c.4133C>Tp.Pro1378Leumissense20000.9690.54626.1
rs1801673ATMchr11:108304736c.5558A>Tp.Asp1853Valmissense20.0036990.0029200.9870.58926.1
rs1799802ERCC4chr16:13934224c.1135C>Tp.Pro379Sermissense20.0072070.009714010.52625.4
rs11212587ATMchr11:108315883c.6067G>Ap.Gly2023Argmissense20.00083180.000755300.3640.51125.3
rs61752784POLGchr15:89330133c.803G>Cp.Gly268Alamissense10.0041580.0054600.9990.96725.3
rs200981995LIG3chr17:34999827c.2302T>Cp.Tyr768Hismissense20.011730.0091340.110.994NA25.1
chr17:18292743 T/ATOP3Achr17:18292743c.1183A>Tp.Ser395Cysmissense1NANA0.010.976NA25
rs201920810SPIDRchr8:47712713c.2029G>Ap.Asp677Asnmissense200010.56124.9
rs140566004POLEchr12:132673646c.1288G>Ap.Ala430Thrmissense20.0001395000.9970.48724.7
rs78488552WRNchr8:31154721c.3785C>Gp.Thr1262Argmissense20.0002319.432 × 10−500.9990.41324.5
rs546221341POLQchr3:121488663-121488669c.4262_4268delp.Ile1421ArgfsTer8frameshift10.0062090.005384NANANA24.3
rs145289229POLGchr15:89328532c.1174C>Gp.Leu392Valmissense10.0078230.010850.060.9990.79624.2
rs55748151POLQchr3:121533021c.929T>Gp.Val310Glymissense20.0010630.00141300.5520.49824.1
rs150018949EXO5chr1:40515573-40515574c.1029_1030insGp.Arg344AlafsTer10frameshift10.0043520.003488NANANA24.1
rs771308001ERCC1chr19:45407145-45407146NANAdownstream gene10.0033760.00311NANANA23.7
rs565251228RECQL5chr17:75624891NANAdownstream gene10.00014610.0002827NANANA23.4
rs55801750ATMchr11:108330296c.7390T>Cp.Cys2464Argmissense24.619 × 10−500.10.0050.66822.9
rs201503405PNKPchr19:49862573c.901C>Tp.Arg301Trpmissense10.0064640.00677500.911NA22.9
chr19:45352306 T/CERCC2chr19:45352306c.2093A>Gp.Gln698Argmissense1NANA0.540.218NA22.8
chrX:153444976 C/GTREX2chrX:153444976c.455G>Cp.Arg152Promissense1NANA00.999NA22.7
rs775001669MLH3chr14:75048767c.889C>Tp.Arg297Trpmissense20.001340.001132010.65522.6
rs41549716POLGchr15:89321842c.2492A>Gp.Tyr831Cysmissense20.018030.01610.020.9950.73222.6
rs201414369EME1chr17:50380824c.1598G>Ap.Arg533Hismissense10.00013860.00018840.220.994NA22.6
rs144340710TP53chr17:7674259c.704A>Gp.Asn235Sermissense10.00027720.00047450.220.385NA22.5
rs4987202RAD23Achr19:12948812c.599C>Tp.Thr200Metmissense, splice region10.0043590.0032990.430.02NA22.5
rs146309259LIG1chr19:48121298c.2257G>Ap.Val753Metmissense10.0024510.0017880.060.407NA22.5
rs28897689BRCA1chr17:43091492c.4039A>Gp.Arg1347Glymissense10.0019440.0017880.090.255NA22.2
rs55712212BRCA2chr13:32341176c.6821G>Tp.Gly2274Valmissense20.013030.013490.370.9660.48121.8
rs144276604XAB2chr19:7625912c.790G>Ap.Asp264Asnmissense10.000231800.090.846NA21.7
rs3730947LIG1chr19:48140013c.1045G>Ap.Val349Metmissense20.015640.0164800.997NA21.5
rs776329282ERCC4chr16:13926750-13926755c.580_584+1delNAin-frame deletion, splice region19.256 × 10−50.0001884NANANA20.5
rs763165669NTHL1chr16:2038404-2038416NANAdownstream gene20.013630.007775NANANANA
rs41547220POLQchr3:121489857-121489859c.3072_3074delp.Lys1025delin-frame deletion20.018310.01925NANANANA
Table 2. Clinical data of the EOBC patients. ID column: patient identification number. The ‘–’ after ID number means negative Lund criteria. Found var columns include the variants’ rs-numbers and genes. Novel variants are bolded. Age is the age of the patient at breast cancer diagnosis. If two ages are shown, the patient had bilateral cancer. Last column includes histology, grade, and hormonal markers. Triple-negative cancers are bolded. Bilateral breast cancer is marked with 2, after which the same information is presented for the second cancer. Information was not available for all patients from patient files. If a part is left blank, no information was available. Gray marked variants’ consequences are stop gain, start lost, splice acceptor, or splice donor; these belong to Group 1. Novel variants and TNBC are bolded.
Table 2. Clinical data of the EOBC patients. ID column: patient identification number. The ‘–’ after ID number means negative Lund criteria. Found var columns include the variants’ rs-numbers and genes. Novel variants are bolded. Age is the age of the patient at breast cancer diagnosis. If two ages are shown, the patient had bilateral cancer. Last column includes histology, grade, and hormonal markers. Triple-negative cancers are bolded. Bilateral breast cancer is marked with 2, after which the same information is presented for the second cancer. Information was not available for all patients from patient files. If a part is left blank, no information was available. Gray marked variants’ consequences are stop gain, start lost, splice acceptor, or splice donor; these belong to Group 1. Novel variants and TNBC are bolded.
ID*Found var AgeHistology, Grade, ER, PR, Her2
424rs145289229rs11571833rs2306211rs546221341 25Ductal, G3, ER+, PR-, Her2+
POLGBRCA2POLQPOLQ
425 27Ductal, G3, ER+, PR+, Her2-
426 27Ductal, G3, ER-, PR-, NA
427 28Ductal, G3, ER+, PR+, Her2+
428rs11571833rs3730947 28Ductal, G3, ER-, PR-, Her2-
BRCA2LIG1
429 28Ductal, G3, ER+, PR+, Her2+
431rs140566004rs4987202 28Ductal, G3, ER-, PR+, Her2+
POLERAD23A
432-rs201920810rs773570504 30Ductal, G3, ER+, PR+, Her2-
SPIDRATM
433 31, 35Ductal, G3, ER-, PR-, Her2-;
2 Ductal, ER+, Her2- ^
434-rs200535477rs2306211 31Ductal, G3, ER-, PR-, Her2-
RECQL5POLQ
435-Novel RNF8rs78488552rs565251228 32Ductal, G3, ER-, PR-, Her2+
WRNRECQL5
436-rs1801673rs762390984rs763165669 32Micropapillar, ER+, PR+, Her2-
ATMFANCINTHL1
437rs373080718rs202068855 33DCIS, G3
TOP3ARPA1
438-rs187418762 33Ductal, G3, ER-, PR-, Her2-
SPIDR
440rs55712212rs137923123novel ERCC2 34, 37Ductal, G3, ER-, PR-; 2 LCIS
BRCA2PER1
441- 34Ductal, G3, ER+, PR+, Her2-
442rs41547220rs149253459 34Ductal, G3, ER+, PR+, Her2-
POLQFAAP100
443-rs766240074rs562132292 34Ductal, G3, ER-, PR-, Her2-
RAD54LERCC2
444- 35Ductal, G3, ER-, PR-, Her2+
445rs587782401 35,43Ductal, G3, ER-, PR-, Her2+;
2 Ductal, G3, ER-, PR-, Her2+
CHEK2
446-rs771308001 34Ductal, G2, ER+, PR+, Her2-
ERCC1
610rs28897758rs1805378 40, 40Ductal, G1, ER+, PR+, Her2-;
2 G3, ER+, PR+, Her2-
BRCA2NTHL1
611 40, 54Ductal, G2, ER+, PR-, Her2-;
2 ductal, G2, ER+, PR+, Her2-
612rs81002862rs11212587 40DCIS
BRCA2ATM
613 35
614 26DCIS, G3
615rs55748151 30Ductal, G3, ER-, PR-, Her2-
POLQ
616rs55801750rs34001746rs144276604 38Ductal, G3, ER-, PR-, Her2+
ATMTOP3AXAB2
617rs746243211Novel Trex2 40, 672 Ductal G3, ER+, PR+, Her2-
MSH3
618rs776329282 27Ductal, G2, ER+, PR+, Her2-
ERCC4
619rs5745908rs41549716Novel Top3Ars41540016 27Ductal, G3, ER-, PR-, Her2-
NEIL1POLG POLQ
61rs121913016rs180177100rs144564120 36Ductal, ER+, PR+, Her2-
ERCC2PALB2ERCC2
620 35Ductal, G2, ER+, PR+, Her2-
621rs55712212 39Lobular
BRCA2
622 38Ductal, G2, ER+, PR+, Her2+
623Novel RNF4 31Ductal, G2, ER+, PR+, Her2+
624rs149243307rs61752784rs17879961Novel EXO1 23Ductal, G3, ER+, PR+, Her2+
FANCIPOLGCHEK2
625rs3730947 28Lobular, G2, ER+, PR+, Her2-
LIG1
626rs750771205rs145289229rs146309259rs3730947rs58778240134, 34Ductal, ER+, PR+, Her2+;
2 DCIS
ATMPOLGLIG1LIG1CHEK2
627 33
628rs28363284rs41540016 28Ductal, G3, ER-, PR-, Her2-
RAD51DPOLQ
629-rs150018949 40
EXO5
62 36DCIS
630rs1799802 26Ductal, G3, ER-, PR-, Her2-
ERCC4
631-rs193219754 31Ductal, G2, ER+, PR-, Her2-
MLH3
632rs187418762rs4987202rs201503405 38, 67Ductal;
2 ductal, G3, ER+, PR+, Her2-
SPIDRRAD23APNKP
633-rs41540016 32Lobular, G2, ER+, PR+, Her2-
POLQ
634-Novel POLErs28897689Novel WRNrs11574410 34Ductal, G3, ER-, PR-, Her2-
BRCA1 WRN
635-rs144340710rs3730947 30Ductal, G3, ER+, PR-, Her2-
TP53LIG1
636rs4987202 24
RAD23A
637rs150018949 31Ductal, G3, ER+, PR+, Her2+
EXO5
639-rs759217526 24Ductal, G3, ER+, PR+, Her2-
FANCL
63rs11572913 37, 46Ductal, G2; 2 Ductal, G2, ER+, PR+, Her2-
GTF2H3
64 37, 57Ductal, G3, ER+, PR+, Her2-; 2
65rs34642881 38
RECQL4
66rs202068855rs756188698 39Ductal, G3, ER+, PR+, Her2-
RPA1RAD18
67rs142213781 39Ductal, G1, ER+, PR+, Her2-
NEIL1
68 39, 47Lobular, G2, ER+, PR+, Her2-; 2 DCIS, G3
69rs200981995rs17879961rs201503405 40Ductal, G3, ER-, PR-,Her2-
LIG3CHEK2PNKP
71 29Ductal, G3, ER-, PR-, Her2-
72-rs775001669rs41540016rs199791286 39Ductal, G3, ER+, PR+, Her2+
MLH3POLQMSH3
73- 33DCIS, G3
74-rs201414369rs150018949 36, 36Ductal, G3, ER-, PR-, Her2-; 2 ductal, G3, ER-, PR-, Her2-
EME1EXO5
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Kurkilahti, V.; Rathinakannan, V.S.; Nynäs, E.; Goel, N.; Aittomäki, K.; Nevanlinna, H.; Fey, V.; Kankuri-Tammilehto, M.; Schleutker, J. Rare Germline Variants in DNA Repair Genes Detected in BRCA-Negative Finnish Patients with Early-Onset Breast Cancer. Cancers 2024, 16, 2955. https://doi.org/10.3390/cancers16172955

AMA Style

Kurkilahti V, Rathinakannan VS, Nynäs E, Goel N, Aittomäki K, Nevanlinna H, Fey V, Kankuri-Tammilehto M, Schleutker J. Rare Germline Variants in DNA Repair Genes Detected in BRCA-Negative Finnish Patients with Early-Onset Breast Cancer. Cancers. 2024; 16(17):2955. https://doi.org/10.3390/cancers16172955

Chicago/Turabian Style

Kurkilahti, Viivi, Venkat Subramaniam Rathinakannan, Erja Nynäs, Neha Goel, Kristiina Aittomäki, Heli Nevanlinna, Vidal Fey, Minna Kankuri-Tammilehto, and Johanna Schleutker. 2024. "Rare Germline Variants in DNA Repair Genes Detected in BRCA-Negative Finnish Patients with Early-Onset Breast Cancer" Cancers 16, no. 17: 2955. https://doi.org/10.3390/cancers16172955

APA Style

Kurkilahti, V., Rathinakannan, V. S., Nynäs, E., Goel, N., Aittomäki, K., Nevanlinna, H., Fey, V., Kankuri-Tammilehto, M., & Schleutker, J. (2024). Rare Germline Variants in DNA Repair Genes Detected in BRCA-Negative Finnish Patients with Early-Onset Breast Cancer. Cancers, 16(17), 2955. https://doi.org/10.3390/cancers16172955

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