Abstract
The use of multigene panel testing for patients with a predisposition to breast/ovarian cancer is increasing as the identification of variants is useful for diagnosis and disease management. We identified pathogenic and likely pathogenic (P/LP) variants of high‐and moderate‐risk genes using a 23‐gene germline cancer panel in 518 patients with hereditary breast and ovarian cancers (HBOC). The frequency of P/LP variants was 12.4% (64/518) for high‐ and moderate‐penetrant genes, namely, BRCA2 (5.6%), BRCA1 (3.3%), CHEK2 (1.2%), MUTYH (0.8%), PALB2 (0.8%), MLH1 (0.4%), ATM (0.4%), BRIP1 (0.4%), TP53 (0.2%), and PMS2 (0.2%). Five patients possessed two P/LP variants in BRCA1/2 and other genes. We also compared the results from in silico splicing predictive tools and exon splicing patterns from patient samples by analyzing RT‐PCR product sequences in six P/LP intronic variants and two intronic variants of unknown significance (VUS). Altered transcriptional fragments were detected for P/LP intronic variants in BRCA1, BRIP1, CHEK2, PARB2, and PMS2. Notably, we identified an in‐frame deletion of the BRCA1 C‐terminal (BRCT) domain by exon skipping in BRCA1 c.5152+6T>C—as known VUS—indicating a risk for HBOC. Thus, exon splicing analysis can improve the identification of veiled intronic variants that would aid decision making and determination of hereditary cancer risk.
Keywords: germline mutation, hereditary breast and ovarian cancer syndrome, next‐generation sequencing, pathogenic/likely Pathogenic, RNA splicing
This study identified 12.4% (64/518) pathogenic or likely pathogenic (P/LP) variants using a comprehensive multi‐gene panel including 23 cancer susceptibility genes and analyzed the pathogenic effects in the intronic variants identified by analyzing exon splicing patterns. These analyses would help further identify the uncharacterized variants that are expected to increase hereditary breast/ovarian cancer risk.

Abbreviations
- HBOC
hereditary breast and ovarian cancer
- IDC
invasive ductal carcinoma
- P/LP
pathogenic/likely pathogenic
- VUS
variants of unknown significance
1. INTRODUCTION
Breast cancer is a multifactorial disease caused by a combination of environmental and genetic factors. 1 , 2 Hereditary breast and ovarian cancers (HBOCs) account for approximately 5‐10% of breast cancer and 10%‐15% of ovarian cancer and primarily involve BRCA1 and BRCA2 variants. 2 , 3 , 4 The identification of BRCA1 and BRCA2 germline variants significantly improve HBOC diagnosis, as they are predictors of cancer susceptibility for patients as well as their families. 5 , 6
Recent advances in genetic sequencing technology have led to the discovery of novel genes that increase the risk of cancer in patients with familial predisposition. 5 , 6 , 7 , 8 However, the rapid introduction of multigene panel testing has raised several issues to be addressed for implementation in clinical settings. 9 First, many of the tested genes are low‐ to moderate‐risk genes for which consensus management guidelines have not been established. 9 , 10 In the absence of identified variants, recommendations for cancer‐specific screening and prevention approaches for patients and family members are typically based on personal and/or family cancer history. 11 Second, it is uncertain whether identifying such low‐ to moderate‐risk gene variants would influence the individual clinical management of patients referred for genetic testing. 11 Although several studies have identified variants in moderate‐risk genes, such as ATM, BRIP1, CHEK2, BARD1, MRE11A, NBN, RAD50, RAD51, and XRCC2, as well as in high‐penetrant genes, including BRCA1/2, TP53, PTEN, STK11, CDH1, and PALB2, 12 , 13 , 14 establishing clinical relevance and analyzing these variants across diverse ethnic populations is warranted.
Correct exon splicing is important for appropriate protein translation as alterations in this process can lead to aberrant cellular metabolism or functions. Abnormal splicing caused by mutation events may alter consensus splicing regulator sequences, leading to hereditary disorders. 15 Although in silico bioinformatics algorithms were developed for evaluating the possible exon splicing effects of identified variants, the exact effects of variants should be demonstrated in functional assays.
In this study, we employed a comprehensive multigene panel that included 23 known or suspected cancer susceptibility genes to test Korean patients suspected of HBOC. We aimed to identify possible pathogenic or likely pathogenic (P/LP) variants as well as variants of unknown significance (VUS) for various genes including BRCA1. We also analyzed exon splicing patterns in intronic variants to evaluate their deleterious effects.
2. MATERIAL AND METHODS
2.1. Study population
A total of 700 patients who were suspected of a familial predisposition to cancer were referred to a genetic counseling clinic in the Korea National Cancer Center and underwent BRCA1/2 testing between January 1, 2017 and December 31, 2018. Suspected clinical characteristics of HBOC were defined as follows: (a) at least one case of breast or ovarian cancer with a family history of breast and ovarian cancer; (b) first diagnosis of breast cancer onset ≤ 40 years old; (c) bilateral breast cancer or other primary cancer with other primary malignancy; and (d) simultaneous diagnosis of breast and ovarian cancers. All were in accordance with the criteria of HBOC testing according to the NCCN guidelines on genetic/familial high‐risk assessment: breast and ovarian (version 2, 2017). 13 Of these, 518 patients who had agreed to the study underwent further evaluation with a customized 23‐gene hereditary cancer panel (Figure 1). Data on demographics, personal and familial history of cancer, and panel testing results were retrospectively collected for patients harboring P/LP variants. Clinicopathological characteristics of cancer, such as the stage and presence of the hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) states, were assessed by reviewing medical records. As a control group, 393 healthy female controls were recruited among individuals who had visited the National Cancer Center as part of a cancer‐screening program.
FIGURE 1.

Germline variants in patients with hereditary breast and ovarian cancer detected using a high‐ and moderate‐penetrance hereditary cancer gene panel of 23 genes. Schematic representation of the patients and study workflow. A total of 700 breast/ovarian cancer patients visited the genetic counseling clinic between January 2017 and December 2018 at the National Cancer Center (Republic of Korea) and underwent BRCA1/2 testing. Of these, 518 patients were enrolled in the study and tested using a customized 23‐gene hereditary cancer panel. The frequency of pathogenic (P) or likely pathogenic (LP) variants was 12.4% (64/518)
2.2. BRCA1 and BRCA2 direct sequencing
BRCA1/2 genetic testing was performed by the Green Cross Company (Yongin, Republic of Korea) via direct sequencing. Briefly, genomic DNA was extracted from peripheral blood samples with a QIAamp DNA Blood Mini Kit (Qiagen) or Chemagic DNA Blood 200 Kit (Chemagen). Amplified products were sequenced on an ABI 3500xl Analyzer (Applied Biosystems) using the Bigdye Terminator v3.1 Cycle Sequencing Kit. Sequences were analyzed using Sequencher v5.0 software (Gene Codes). All variants are described according to HUGO‐approved systematic nomenclature (http://www.hgvs.org/mutnomen/).
2.3. Panel‐based sequencing assay
Genomic DNA was extracted from peripheral blood of each patient. We employed a customized hereditary cancer panel (Celemics) that included all coding sequences and intron‐exon boundaries of the coding exon from 23 cancer predisposition genes (APC, ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH, MEN1, NBN, PALB2, PMS2, PTEN, RAD50, RAD51C, RET, STK11, and TP53; Table 2). Products with each capture reaction were sequenced on an Illumina MiSeqDX (Illumina Inc) generating 2 × 150 bp paired‐end reads. Alignment of sequence reads, indexing of the reference genome (hg19), and variant calling were performed with a pipeline based on Genome Analysis Tool Kit (GATK) Best Practices. 16 Alignment was performed with BWA‐mem (version 0.7.10), 17 duplicated reads were marked with Picard (version 1.138; http://picard.sourceforge.net), and local alignment, base quality recalibration, and variant calling were performed using the GATK (version 3.5), 18 samtools (version 0.1.19), 19 FreeBayes (v0.9.21‐26‐gbfd9832), and Scalpel (version 0.5.3). 20
TABLE 2.
Pathogenic or likely pathogenic variants distributed according to hereditary penetrance
| Hereditary penetrance | Gene | Disease/syndrome | No. of patients | % | Total (%) |
|---|---|---|---|---|---|
| High penetrance and high risk | BRCA1 | Hereditary breast and ovarian cancer syndrome | 17 | 3.3 | 52 (10.0) |
| BRCA2 | Hereditary breast and ovarian cancer syndrome | 29 | 5.6 | ||
| CDH1 | Hereditary diffuse gastric cancer, Blepharocheilodontic syndrome | 0 | 0.0 | ||
| PALB2 | Fanconi anemia, complementation group N | 4 | 0.8 | ||
| PTEN | Cowden syndrome, Bannayan‐Riley‐Ruvalcaba syndrome | 1 | 0.2 | ||
| STK11 | Peutz‐Jeghers syndrome | 0 | 0.0 | ||
| TP53 | Li‐Fraumeni syndrome | 1 | 0.2 | ||
| Moderate penetrance and high risk | ATM | Ataxia‐telangiectasia | 2 | 0.4 | 8 (1.5) |
| BARD1 | Breast cancer, Ovarian cancer | 0 | 0.0 | ||
| CHEK2 | Li‐Fraumeni syndrome, Breast cancer | 6 | 1.2 | ||
| NBN | Nijmegen breakage syndrome, Breast cancer, Ovarian cancer, Leukemia | 0 | 0.0 | ||
| Increased penetrance but less well‐defined risk | APC | Adenomatous polyposis coli, Desmoid cancer | 0 | 0.0 | 9 (1.7) |
| BRIP1 | Breast cancer, Fanconi anemia | 2 | 0.4 | ||
| EPCAM | Lynch syndrome, Congenital tufting enteropathy | 0 | 0.0 | ||
| MEN1 | Multiple endocrine neoplasia 1, Familial isolated hyperparathyroidism | 0 | 0.0 | ||
| MLH1 | Colorectal cancer, hereditary nonpolyposis, type 2, Lynch syndrome | 2 | 0.4 | ||
| MSH2 | Colorectal cancer, hereditary nonpolyposis, type 1, Lynch syndrome | 0 | 0.0 | ||
| MSH6 | Colorectal cancer, hereditary nonpolyposis, type 5, Lynch syndrome | 0 | 0.0 | ||
| MUTYH | Familiar adenomatous polyposis | 4 | 0.8 | ||
| PMS2 | Lynch syndrome, Alopecia areata, Ovarian cancer | 1 | 0.2 | ||
| RAD50 | Nijmegen‐breakage‐syndrome–like disorder, Polycystic ovary syndrome | 0 | 0.0 | ||
| RAD51C | Fanconi anemia, complementation group O, Familial breast‐ovarian cancer | 0 | 0.0 | ||
| RET | Multiple endocrine neoplasia IIA, Hirschsprung disease | 0 | 0.0 |
2.4. Variant classification
Variant annotation was performed with VEP (Ensembl Variant Effect Predictor) 21 and dbNSFP v 3.0. 22 We obtained all single‐base pair substitutions, insertions and/or deletions for each gene. Genetic variants were classified using a five‐tier system following the American College of Medical Genetics and Genomics (ACMG) guidelines as follows 23 : P, LP, VUS, likely benign, or benign.
2.5. In silico exon splicing analysis of intronic variants
We used the following five splice site prediction programs to predict the effect of intronic variants on the efficiency of splicing: Splice Site Finder (http://www.interactive‐biosoftware.com), GeneSplicer (http://www.cbcb.umd.edu/software/GeneSplicer), Splice Site Prediction by Neural Network (http://www.fruitfly.org/seq_tools/splice.html), MaxEntScan (http://genes.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html), and Human Splicing Finder (http://www.umd.be/HSF/). Analysis was conducted by the integrated software Alamut Visual (version 2.12; http://www.interactive‐biosoftware.com) using default settings for all predictions. A variation of more than 10% in at least two algorithms was considered to have an effect on splicing. All intronic variants classified as P/LP were analyzed and the two intronic VUS of BRCA1/2 were evaluated using the available samples.
2.6. Functional analysis and genotyping of splice acceptor variants
We analyzed RNA transcripts from patient samples to compare outcomes via in silico splicing analysis. Total RNA was extracted from peripheral blood lymphocytes using the NucleoSpin RNA Blood Kit (Macherey‐Nagel) or from normal tissues using the AllPrep DNA/RNA Mini Kit (Qiagen) according to manufacturer's instructions. Using total RNA (1 µg) as template, cDNA was reverse‐transcribed using the Transcriptor First Strand cDNA Synthesis Kit (Roche Life Science) or ReverTra Ace qPCR RT Master Mix (Toyobo), followed by amplification via reverse transcription PCR (RT‐PCR) as previously reported. 24 , 25 , 26 , 27 Transcriptional products for intronic variants in BRCA1, BRCA2, BRIP1, CHEK2, PALB2, and PMS2 were obtained and validated by Sanger sequencing. Primer sequences are listed in Table S1.
Intronic variants were further genotyped in healthy female controls. Variants were identified by TaqMan SNP Genotyping Assays (Applied Biosystems) using the QuantStudio 7 Flex Real‐Time PCR System (Applied Biosystems).
3. RESULTS
3.1. Baseline characteristics of the study population
Clinical characteristics of patients with breast/ovarian cancer subjected to multigene panel testing are listed in Table 1. A total of 507 patients (507/518; 97.9%) were diagnosed with breast cancer, whereas eight (8/518; 1.5%) were diagnosed with ovarian cancer; three patients were diagnosed with both cancers. Among patients with breast cancer, 35.8% were diagnosed before 40 years of age. Histologically, invasive ductal carcinoma (IDC) was predominant, and 51.8% of patients were categorized as stage I. Initial diagnosis of 54.5% of patients with ovarian cancer revealed that they were in their 50s; notably, these patients had a familial predisposition to cancer.
TABLE 1.
Demographic characteristics of patients with breast/ovarian cancer
| Risk category | Breast cancer | Ovarian cancer | ||
|---|---|---|---|---|
| n = 510 | % | n = 11 | % | |
| Age at diagnosis | ||||
| <40 | 183 | 35.9 | 0 | 0.0 |
| 40‐49 | 173 | 33.9 | 3 | 27.3 |
| 50‐59 | 99 | 19.4 | 6 | 54.5 |
| 60≤ | 55 | 10.8 | 2 | 18.2 |
| Pathological stage | ||||
| 0 | 20 | 3.9 | 0 | 0.0 |
| I | 264 | 51.8 | 1 | 9.1 |
| II | 110 | 21.6 | 0 | 0.0 |
| III | 39 | 7.6 | 8 | 72.7 |
| IV | 0 | 0.0 | 1 | 9.1 |
| pCR | 43 | 8.4 | 1 | 9.1 |
| Unknown | 34 | 6.7 | 0 | 0.0 |
| Personal history | ||||
| Early‐onset cancer (age < 40) | 183 | 35.8 | ||
| Bilateral breast cancer | 31 | 6.1 | ||
| Multiple‐organ cancers (with other primary‐organ cancer except ovarian or breast cancer) | 62 | 12.2 | 1 | 9.1 |
| Both breast and ovarian cancer | 3 | 0.6 | 3 | 27.3 |
| Male breast cancer | 3 | 0.6 | ||
| Family history | ||||
| Breast cancer | 216 | 42.4 | 1 | 9.1 |
| Ovarian cancer | 10 | 2.0 | 3 | 27.3 |
| Breast and ovarian cancer | 6 | 1.2 | 2 | 18.2 |
| Other cancers | 125 | 24.5 | 3 | 27.3 |
| Without family history | 153 | 30.0 | 2 | 18.2 |
| Subtype according to hormone receptor and HER2 status for breast cancer | ||||
| HR+, HER2‐ | 286 | 56.1 | ||
| HR‐, HER2+ | 41 | 8.0 | ||
| HR+, HER2+ | 121 | 23.7 | ||
| Triple‐negative (TNBC) | 54 | 10.6 | ||
| Unclassifiable | 8 | 1.6 | ||
| Pathological classification of breast cancer type | ||||
| Invasive ductal carcinoma | 411 | 80.6 | ||
| Ductal carcinoma in situ | 70 | 13.7 | ||
| Metastatic ductal carcinoma | 6 | 1.2 | ||
| Invasive lobular carcinoma | 5 | 1.0 | ||
| Mucinous carcinoma | 3 | 0.6 | ||
| Lobular carcinoma in situ | 2 | 0.4 | ||
| Others | 13 | 2.5 | ||
| Pathological classification of ovarian cancer type | ||||
| Serous adenocarcinoma | 5 | 45.5 | ||
| Mixed‐germ cell tumor | 1 | 9.1 | ||
| Endometrioid adenocarcinoma | 1 | 9.1 | ||
| Clear cell adenocarcinoma | 2 | 18.2 | ||
| Others | 2 | 18.2 | ||
Abbreviations: HER2, human epidermal growth factor receptor 2; HR, hormone receptors (estrogen receptor, progesterone receptor); TNBC, triple‐negative breast cancer.
3.2. Cancer‐predisposing germline variants including the BRCA1/2
P/LP variants were detected in 12.4% (64/518) of the 518 patients with breast and ovarian cancer tested with the multigene panel (Figure 1). As shown in Table 2, we divided the genes included in the panel into three groups based on hereditary penetrance. Of the P/LP variants, 10.0% were in group A, 1.5% in group B, and 1.7% in group C. In our cohort, group A variants were detected in BRCA2 (5.6%), BRCA1 (3.3%), PALB2 (0.8%), TP53 (0.2%), and PTEN (0.2%) genes. Group B variants were found in CHEK2 (1.2%) and ATM (0.4%), whereas group C variants were in MUTYH (0.8%), MLH1 (0.4%), BRIP1 (0.4%), and PMS2 (0.2%) (Table 2).
Of the 19 patients who harbored cancer‐predisposing germline variants except for BRCA1/2, 15 patients had a family history of cancer (Table 3). These patients were mainly diagnosed with IDC tumor type, and some also had bilateral breast cancer or multiple cancers (Table 3). The median age of diagnosis in these patients was 48.3 ± 11.8 years (ranging from 33 to 72 years; Table 2). Five patients possessed two P/LP variants in BRCA1/2 and other genes in the panel (Table S2). Variants in genes other than BRCA1/2 were as follows: one BRIP1 c.1794+1 G>A, two CHEK2 c.1555 C>T (p.Arg159*), and one MUTYH c.544 C>T (p.Arg182Cys); one patient had two pathogenic variants in the BRCA2. These patients were diagnosed with IDC tumor type HR+ and HER2‐ and had at least one clinical feature of suspected HBOC, ie, disease onset at less than 40 years of age, bilateral cancer, or family history of cancer.
TABLE 3.
Characteristics of BRCA 1/2‐variant‐negative patients with pathogenic/likely pathogenic variants in other cancer‐associated genes
| Gene | Variant | Classification (ACMG guidelines) | ClinVar | No. | Patient | Personal history | Family history | ||
|---|---|---|---|---|---|---|---|---|---|
| Tumor type | Molecular subtype | Age | |||||||
| ATM | c.1402_1403delAA (p.Lys468Glufs*18) | Pathogenic (PVS1, PM2, PP5) | Pathogenic/likely pathogenic | 1 | PT9 | Breast cancer (IDC) | HR+, HER2‐ | 41 | No |
| c.442dupG (p.Asp148Glyfs*11) | Pathogenic (PVS1, PM2, PP5) | Pathogenic | 2 | PT44 | Breast cancer (DCIS) | HR+, HER2‐ | 41 | 1 FDR (breast cancer) | |
| BRIP1 | c.937dupT (p.Tyr313Leufs*6) | Likely pathogenic (PVS1, PM2, PP5) | Likely pathogenic | 3 | PT10 | Ovarian cancer (serous adenocarcinoma) | 72 | 1 FDR (breast cancer), 1 FDR (laryngeal cancer) | |
| CHEK2 | c.1555C>T (p.Arg519*) | Pathogenic (PVS1, PM2, PP5) | Pathogenic/likely pathogenic | 4 | PT11 | Breast cancer (DCIS) + thyroid cancer | HR+, HER2‐ | 52 | 1 FDR (gastric cancer + colorectal cancer), 1 FDR (thyroid cancer) |
| 5 | PT12 | Breast cancer (DCIS) + thyroid cancer | HR+, HER2‐ | 52 | No | ||||
| 6 | PT14 | Breast cancer (IDC) | HR‐, HER2+ | 38 | 1 FDR (gastric cancer), 1 SDR (thyroid cancer), 1 SDR (breast cancer) | ||||
| c.846+1G>T | Likely pathogenic (PVS1, PM2) | Pathogenic | 7 | PT13 | Bilateral, breast cancer (IDC) | HR‐, HER2+ | 43 | 1 FDR (breast cancer) | |
| MLH1 | c.1758dupC (p.M587Hfs*6) | Pathogenic (PVS1, PM2, PP5) | Pathogenic | 8 | PT15 | Breast cancer (IDC) | HR‐, HER2+ | 58 | 2 FDR (colorectal cancer), 1 FDR (colorectal cancer + endometrial cancer) |
| c.2080G>T(p.Glu694*) | Pathogenic (PVS1, PM2, PP5) | Likely pathogenic | 9 | PT48 | Breast cancer (IDC) + thyroid cancer | HR+, HER2‐ | 44 | No | |
| MUTYH | c.857G>A (p.Gly286Glu) | Likely pathogenic (PS3, PM2) | Pathogenic/likely pathogenic | 10 | PT26 | Breast cancer (IDC) | HR+, HER2‐ | 36 | 1 SDR (cervical cancer) |
| 11 | PT36 | Breast cancer (IDC) | HR+, HER2+ | 64 | 1 FDR (breast cancer) | ||||
| 12 | PT38 | Breast cancer (IDC) | HR+, HER2‐ | 33 | No | ||||
| PALB2 | c.2834+2T>C a | Pathogenic (PVS1, PM2, PP5) | Likely pathogenic | 13 | PT39 | Breast cancer (IDC) | HR+, HER2‐ | 35 | 1 SDR (breast cancer), 2 SDR (lung cancer) |
| c.902delA (p.Asp301Valfs*5) | Pathogenic (PVS1, PM2, PP5) | N/A | 14 | PT40 | Bilateral, breast cancer (DCIS) | HR‐, HER2+ | 46 | 1 SDR (cervical cancer) | |
| c.454A>T (p.Lys152*) | Pathogenic (PVS1, PM2, PP5) | N/A | 15 | PT41 | Breast cancer (IDC) | HR+, HER2+ | 52 | 1 FDR (pancreas cancer), 1 SDR (breast cancer), 1 SDR (lung cancer), 1 SDR (gastric cancer) | |
| c.1048C>T (p.Gln350*) | Pathogenic (PVS1, PM2, PP5) | Pathogenic | 16 | PT42 | Breast cancer (IDC) | TNBC | 69 | 1 FDR (lung cancer), 1 FDR (thyroid cancer) | |
| PMS2 | c.164‐1G>C | Likely pathogenic (PVS1, PM2, PP5) | Likely pathogenic | 17 | PT43 | Breast cancer (IDC) + gastric cancer | HR‐, HER2+ | 47 | 1 FDR (colorectal cancer), 1 SDR (gastric cancer) |
| PTEN | c.464A>G (p.Tyr155Cys) | Likely pathogenic (PS3, PM2) | Conflicting interpretations of pathogenicity_Likely_pathogenic (1), pathogenic (1), uncertain_significance (1) | 18 | PT45 | Breast cancer (DCIS) + endometrial cancer | HR+, HER2+ | 35 | 2 SDR (breast cancer) |
| TP53 | c.838A>G (p.Arg280Gly) | Likely pathogenic (PS3, PM2) | Conflicting interpretations of pathogenicity_Likely_pathogenic (19), uncertain_significance (1) | 19 | PT46 | Breast cancer (IDC) | HR+, HER2‐ | 59 | 1 FDR (breast cancer) |
Abbreviations: ACMG, American College of Medical Genetics and Genomics; DCIS, ductal carcinoma in situ; FDR, first‐degree relative; HER2, human epidermal growth factor receptor 2; HR, hormone receptors (estrogen receptor, progesterone receptor); IDC, invasive ductal carcinoma; N/A, not available; SDR, second‐degree relative; TNBC, triple‐negative breast cancer.
Reported by Nakagomi H et al 26
3.3. mRNA transcript and pedigree analysis of patients with intronic P/LP variants
Via multigene panel analysis, we identified six P/LP intronic variants: BRCA1 c.302‐2A>C, BRCA1 c.5277+1G>A, CHEK2 c.846+1G>T, PALB2 c.2834+2T>C, BRIP1 c.1794+1 G>A, and PMS2 c.164‐1G>A (Table 4). To predict the exon splicing patterns of these intronic variants, we employed five in silico splice site prediction programs. The natural splicing sites of the variants were predicted to be affected (Table 4). To evaluate the predicted exon splicing effects by in silico programs, we analyzed mRNA transcripts from patient samples via RT‐PCR (Table 4 and Figure S1‐S6).
TABLE 4.
In silico exon splicing analysis and RT‐PCR results of intronic variants detected in patients with hereditary breast/ovarian cancer
| Gene (reference) | Variant | Splicing site (natural splicing site) |
Splice Site Finder (0‐100) |
Max ent scan (0‐16) |
NN SPICE (0‐1) |
Gene splicer (0‐15) |
Alamut predicted change | Functional assay |
Classification (ACMG guidelines) |
db SNP 147 |
gnom AD _exome _ALL |
ExAC_ALL | 1000G |
KRGDB_ 1100 |
Controls (n = 393) | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| WT | MUT | WT | MUT | WT | MUT | WT | MUT | ||||||||||||
| BRCA1 (NM_007294.3) | c.302‐2A>C | Exon 7‐c.302N (A) | 91.5 | ㅡ | 11.68 | ㅡ | 0.99 | ㅡ | 8.44 | ㅡ | Acceptor splicing site: −100% | Exon 7 partial deletion, truncated protein |
Pathogenic (PVS1, PM2, PP5) |
rs80358011 | ‐ | ‐ | ‐ | ‐ | 0 |
| BRCA1 (NM_007294.3) | c.5277+1G>A | Exon 20‐c.5277N (D) | 82.52 | ㅡ | 9.06 | ㅡ | 0.93 | ㅡ | 7.25 | ㅡ | Donor splicing site: −100% | (1) 87‐bp intron insertion, truncated protein; (2) exon 20 skipping, in‐frame deletion | Pathogenic (PVS1, PM2, PP5) | rs80358150 | ‐ | ‐ | ‐ | ‐ | 0 |
| BRCA1 (NM_007294.3) | c.5152+6T>C | Exon 18‐c.5152N (D) | 74.34 | ㅡ | 7.96 | 4.33 | 0.95 | 0.41 | 2.25 | ㅡ | Donor splicing site: −51.3% | Exon 18 skipping, in‐frame deletion | Uncertain significance (PP3) | rs80358074 | ‐ | ‐ | ‐ | ‐ | 0 |
| BRCA2 (NM_000059.3) | c.317‐10A>G | Exon 4‐c.317N (A) | 90.45 | 90.51 | ‐ | 8.88 | 0.66 | 0.83 | 4.7 | 4.54 | Acceptor splicing site: +15.1% | Not affected | Uncertain significance (PP3) | rs81002824 | 8.E‐06 | 9.E‐06 | 0.0 | ‐ | 0 |
| BRIP1 (NM_032043.2) | c.1794+1G>A | Exon 12‐c.1794N (D) | 82.66 | ㅡ | 8.15 | ㅡ | 0.99 | ㅡ | NE | NE | Donor splicing site: −100% | Exon 12 skipping, truncated protein | Pathogenic (PVS1, PM2, PP5) | rs766516963 | 8.E‐06 | 8.E‐06 | ‐ | 5.E‐04 | 0 |
| CHEK2 (NM_007194.3) | c.846+1G>T | Exon 7‐c.846N (D) | 87.38 | ㅡ | 8.31 | ㅡ | 0.99 | ㅡ | 0.63 | ㅡ | Donor splicing site: −100% | Exon 7 skipping, in‐frame deletion | Likely pathogenic (PVS1, PM2) | rs864622149 | ‐ | ‐ | ‐ | ‐ | 0 |
| PALB2 (NM_024675.3) | c.2834+2T>C | Exon 8‐c.2834N (D) | 89.83 | 89.9 | 9.8 | ㅡ | 1 | ㅡ | 5.06 | ㅡ | Donor splicing site: −100% | Exon 8 skipping, truncated protein | Pathogenic (PVS1, PM2, PP5) | ‐ | ‐ | ‐ | ‐ | ‐ | 0 |
| Intron 8‐c.2834+4 (D) | 70.86 | 74.99 | ㅡ | 1.05 | NE | NE | NE | NE | Cryptic splicing activated? | ||||||||||
| PMS2 (NM_000535.5) | c.164‐1G>C | Exon 3‐c.162N (A) | 80.17 | ㅡ | ㅡ | ㅡ | ㅡ | Acceptor splicing site: −100% | Exon 3 partial deletion, truncated protein | Likely pathogenic (PVS1, PM2, PP5) | rs763308607 | 4.E‐06 | ‐ | ‐ | ‐ | 0 | |||
| Exon 3‐c.172 (A) | ㅡ | 75.2 | ㅡ | 4.89 | NE | NE | NE | NE | Cryptic splicing activated? | ||||||||||
Abbreviations: A, acceptor site; ACMG, American College of Medical Genetics and Genomics; D, donor site; ExAC, Exome Aggregation Consortium; gnomAD, The Genome Aggregation Database; MUT, mutation; NE, splice site not evaluated by the algorithm; WT, wild type; 1000G, 1000 Genomes Project; ㅡ, splice site not detected.
CHEK2 c.846+1G>T was detected in patient PT13, who was diagnosed with HR‐, HER2/neu+ bilateral breast cancer (IDC); the proband's sister died from breast cancer at age 51 after being diagnosed at 47, but other family members were cancer free (Table 3 and Figure S1). CHEK2 c.846+1G>T was predicted to affect the donor splice site (Table 4). We revealed aberrant mRNA transcripts collected from the patient's lymphocytes that corresponded to the skipping of exon 7. This variant was predicted to cause an in‐frame deletion (266‐284 amino acids) in the kinase domain of CHEK2 protein (Figure S1).
PALB2 c.2834+2T>C was detected in patient PT39, who was diagnosed with HR+, HER2/neu‐ IDC at age 35; the proband had a strong family history of reproductive cancer with one paternal aunt being diagnosed with breast cancer at 45 years of age, and another diagnosed with lung cancer at 60 years of age (Table 3 and Figure S2). The proband's paternal grandfather was diagnosed with lung cancer in his late 70s, while the rest of the known family was cancer free. Via RNA analysis, PALB2 c.2834+2T>C was revealed to be the combined product of exon 7 and 9 by exon 8 skipping in PALB2 (Figure S2). This variant was predicted to truncate the PALB2 protein. Generation of truncated protein products by alternative splicing may be associated with an increased risk of breast cancer. 28
PT1 (a 50‐year‐old woman) was referred for genetic counseling after a diagnosis of bilateral IDC and was found to be HR+ and HER2/neu‐. Her family history was only notable with regards to her uncle, who was diagnosed with gastric cancer. Subsequent multigene panel testing revealed the presence of pathogenic BRCA1 c.923_924del, and BRIP1 c.1794+1G>A variants (Table S2 and Figure S3). BRIP1 c.1794+1G>A was predicted to affect the donor splice site, as evidenced by in silico analysis (Table 4). Functional analysis of the intronic variant identified a deletion within exon 12 in the BRIP1 gene, which caused abnormal transcriptional production (Figure S3). The proband's cancer‐related family history and our analysis suggest that this variant confers an increased risk of breast cancer.
PMS2 c.164‐1G>C was detected in patient PT43, who was diagnosed with breast and gastric cancers before age 50. Her father was diagnosed with colon cancer at 73 years old, while her uncle died of gastric cancer at age 60. The rest of the family was healthy (Table 3 and Figure S4). In silico analysis predicted that this variant may be problematic at the acceptor splice site or is activated at the cryptic site (Table 4). Splicing functional assays revealed that this variant induces aberrant splicing via partial exon 3 deletion (8 bp) and leads to the subsequent production of a truncated protein, as evidenced by RT‐PCR (Figure S4).
3.4. Exon splicing analysis for intronic VUS in BRCA1/2
We identified 14 BRCA1 and 24 BRCA2 P/LP variants in our cohort (Table S3). Among these variants, we analyzed exon splicing in two BRCA1 intronic variants classified as P/LP BRCA1 c.302‐2A>C and c.5277+1G>A, which were predicted to affect the donor or acceptor splice sites (Table 4). RT‐PCR identified partial exon 7 deletion (10 bp), and this BRCA1 c.302‐2A>C variant was predicted to truncate BRCA1 protein (Table 4 and Figure S5). The BRCA1 c.302‐2A>C variant was detected in patient PT49, who was diagnosed with bilateral breast cancer. The patient's father died from lung cancer at 61 years old, and her sister was also diagnosed with bilateral breast cancer (Figure S5). BRCA1 c.5277+1G>A was identified in patient PT50, who was diagnosed with ovarian cancer at the age of 44; her family is cancer free. Two abnormal mRNA transcripts were detected in the patient's lymphocytes with BRCA1 c.5277+1G>A that were identified to have an 87‐bp insertion of intron 20 and exon 20 skipping, as seen in a previous study using mini‐gene splicing assays or blood samples (Figure S6). 26
We also examined the effect of one BRCA1 and one BRCA2 VUS on splicing (Table 4, Figure 2, and Figure S7). BRCA1 c.5152+6T>C and BRCA2 c.317‐10A>G are classified with uncertain significance (Table 4). BRCA1 c.5152+6T>C was expected to affect exon splicing, whereas no splicing alterations were predicted for BRCA2 c.317‐10A>G (Table 4). BRCA1 c.5152+6T>C mRNA transcripts were abnormal compared with their corresponding wild‐type transcripts; this variant produced a combined exon 17 and 19 by exon 18 skipping in BRCA1 and was predicted to be an in‐frame deletion of the BRCA1 C‐terminal (BRCT) domain of BRCA1 (Figure 2). However, mRNA transcript indicated that BRCA2 c.317‐10A>G had no effect on exon splicing (Figure S7). Although in silico predictions and RNA analysis revealed the pathogenicity of VUS variants, additional analysis is required to classify them as pathogenic.
FIGURE 2.

Exon splicing analysis of the BRCA1 c.5152+6T>C variant of patient PT51. A, Schematic view of variant c.5152+6T>C localization in the BRCA1 gene. PCR primer alignment is indicated with the red and blue bars. Sequencing analysis for genomic DNA is presented below. B, RT‐PCR of lymphocyte‐derived RNA. Predicted scheme of mRNA transcript in control or patient samples (upper right panel). Agarose gel (2%) electrophoresis; lane 1: control sample; lane 2: patient sample. Two PCR products were detected in the patient sample (upper middle panel). Chromatogram sequences of the control and abnormal transcripts. Vertical line in the chromatogram indicates the exonic junction in transcripts. Exon 18 (78 bp) skipping between exon 17 and exon 19 was identified (upper left panel). Functional domains of BRCA1 and sequence alignment of the BRCA1 abnormal transcript (lower panel). Amino acid sequences of the splice variant (c.5152+6T>C) were aligned using a reference sequence (NP_009225.1) via NCBI BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi). BRCA1 c.5152+6T>C was identified to encode a BRCA1 protein with an in‐frame deletion (26 amino acids) in the BRCA1 C‐terminal (BRCT) domain; this may affect the function of the BRCA1 BRCT domain. The red line indicates the location of the in‐frame deletion residues. C, Pedigree of patient PT51
3.5. Genotyping for intronic P/LP and VUS variants
We conducted genotyping of 393 healthy female Korean controls to further define P/LP or VUS intronic variants by comparing their prevalence. The eight intronic variants, analyzed in exon splicing assays, were not detected in healthy controls (Table 4). These results suggest that these intronic variants may affect the susceptibility to inherit breast and ovarian cancer.
4. DISCUSSION
Targeted multigene panel analysis can provide detailed genetic information for the identification or management of patients with hereditary cancer. 29 , 30 Previous studies showed that expanded panel testing improves the identification of hereditary cancer risk for patients and their family members, as cancer susceptibility genes were identified in 1.9%‐8.1% of patients with BRCA1/2 variant‐negative breast/ovarian cancer (Table S4). 31 , 32 , 33 , 34 , 35 By testing other genes besides BRCA1/2, we identified a frequency of 4.4% P/LP variants. These variants were identified in 5 of 19 patients (26.3%) with early‐onset breast cancer (<40 years old at onset). All patients included in the study met the criteria for HBOC genetic testing according to the NCCN 2017 guidelines; 13 however, 31.6% (6/19) also had a family history of cancers other than HBOC (Table 3). This indicates that a multigene panel study is more effective than a stepwise single‐gene approach for HBOC genetic assessment, as is advised by the NCCN guidelines. 13
Nevertheless, multigene panel testing in clinical settings represents a considerable challenge as these panels include moderate or less well‐defined genes as well as high‐penetrant genes. 36 , 37 , 38 Lack of clear management guidelines for variants in genes with undefined cancer risks or P/LP variants in genes can be problematic. A variant cannot be classified as a positive pathogenic result without an experimental study. Another concern is that the risk of overestimating the clinical interpretation of VUS results in low‐ to moderate‐risk genes. In the present study, we identified that 49.0% of patients had VUS within 23 genes including BRCA1/2 (data not shown). As the number of genes tested and the frequency of multigene panel testing continue to increase, the rate of VUS detection would also increase. 30 , 33 , 39
In this study, we observed MUTYH heterozygote c.857G>A (p.Gly286Glu) (three cases) and c.544C>T (p.Arg182Cys) variants (one case) with P/LP findings based on ClinVar data. It is known that biallelic (homozygous or compound heterozygous) MUTYH variants are related to MUTYH‐associated polyposis syndrome, which results in colorectal polyps and colorectal cancer; however, their association with malignancies other than colon cancer is less robust. 40 , 41 Previous studies have reported an increased risk of breast cancer, without statistical evidence in monoallelic MUTYH variants. 42 , 43 , 44 In a study that enrolled Sephardi Jews of North African descent, homozygote or heterozygote carriers of p.Gly396Asp in MYUTH were found to be significantly increased in breast cancer patients (6.7%) compared with controls (3.7%) (OR, 1.39; 95% CI, 0.26‐7.53). 44 Although a higher frequency of monoallelic MUTYH variants in families with both breast and colorectal cancer compared with those in the general population is increasingly being reported, 40 , 42 , 43 , 45 more evidence regarding the association between MUTYH variants and other cancers should be elucidated.
We performed mRNA transcript analysis of eight intronic variants in BRCA1, BRCA2, BRIP1, CHEK2, PALB2, and PMS2, which were classified as P/LP or VUS. The P/LP variants showed abnormal transcriptional fragments. CHEK2 (cell cycle checkpoint kinase 2) is a well‐established moderate‐penetrance breast cancer gene, but it lacks treatment and follow‐up guidelines. 1 , 46 PALB2 (partner and localizer of BRCA2) serves a crucial role in the localization and stabilization of BRCA2 in nuclear chromatin, which is essential for BRCA2 to function in the homologous recombination‐mediated repair of double‐strand DNA breaks (DSBs) 47 , 48 ; PALB2 variants have been reported to be associated with pancreatic cancer development. 49 BRIP1 (BRCA1‐interacting protein C‐terminal helicase 1) encodes proteins that interact with BRCA1 during the repair of DSBs, and pathogenic variants of this gene have been investigated. 13 , 50 Germline pathogenic variants of PMS2 (PMS1 homolog 2) are implicated in Lynch syndrome and are associated with a significantly increased risk of breast cancer. 51 Previous studies have attempted to identify some genes associated with DNA repair, such as ATM and CHEK2, which have also been added to breast–cancer‐specific gene panels. 13 , 14 , 52 , 53 However, there is controversy over whether these rare variants are clinically associated with a risk of breast cancer 36 , 37 , 54 ; nonetheless, evidence regarding breast cancer incidence is limited.
In this study, the BRIP1 c.1794+1G>A (PT1) carrier was found to possess a c.923_924del variant in the BRCA1 gene (Table 4, Table S2, and Figure S3). Recently, BRIP1 c.1794+1G>A was registered as likely pathogenic in the ClinVar database, but its effects have not been reported in the literature. In our study, exon splicing analysis indicated that BRIP1 c.1794+1G>A results in exon 12 deletion, leading to a frameshift mutation that creates a premature stop codon in the BRIP1 protein (stop codon gained at 557 a.a.; reference sequence NP_114432.2; Table S2 and Figure S3). BRCA1 c.923_924del (p.Ser308Lysfs*11) is another frameshift mutation resulting from a deletion (Table S2). BRIP1 is a DNA helicase which interacts with the C‐terminal BRCT domain (1646‐1736, 1760‐1855 a.a.) of BRCA1 through its C‐terminal‐BRCA1‐binding domain (888‐1063 a.a.) and functions in BRCA1‐dependent DNA repair and DNA‐induced checkpoint activity. 55 De Nicolo et al 50 suggested that a heterozygous germline variant in the BRIP1 gene results in a truncated protein product and is associated with loss of the wild‐type BRIP1 allele in the tissues of affected breast cancer patients. Thus, the BRIP1 c.1794+1G>A/BRCA1 c.923_924del (p.Ser308Lysfs*11) double variants of patient PT1 may further increase the risk of breast cancer through the instability and functional impairment of the encoded proteins.
We further showed that BRCA1 c.5152+6T>C, classified as VUS in ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), has an in‐frame deletion in the BRCT domain resulting from exon 18 skipping. BRCT domains can form a phospho‐recognition motif that preferentially binds proteins containing phosphoserine and interact with several proteins implicated in DNA repair, including Abraxas, BRIP1, and CtIP. 56 BRCA1 c.5152+6T>C was detected in patient PT51, who was diagnosed with triple‐negative breast cancer (TNBC) IDC at 39 years of age. The proband's grandfather died of lung cancer and the grandmother died of ovarian cancer at 77 years old (Figure 2). Splicing variants in BRCT domains of BRCA1 have been reported to be associated with aberrant splicing in patients with breast/ovarian cancer. 27 , 57 This variant does not have frequency information in genome databases, including ExAC (http://exac.broadinstitute.org/) and gnomAD (http://gnomad.broadinstitue.org), and has not been reported in the literature. Moreover, BRCA1 c.5152+6T>C was not detected in the 393 healthy female Korean controls (Table 4). By employing a saturation‐genome‐editing technique based on CRISPR‐mediated homology‐directed repair, Findlay et al 58 suggested that BRCA1 c.5152+6T>C is a loss‐of‐function variant. Thus, we propose that BRCA1 c.5152+6T>C be reclassified as likely pathogenic. Nevertheless, further analysis of the patient and relatives is needed to clarify the actual clinical impact of this variant. In addition, the detected pathogenic variants should have moderately established carcinogenic lifetime risk as well as appropriate counseling recommendations for the patient.
The use of customized multigene panels to confirm associations with genes other than BRCA1/2 in patients with HBOC has increased, and through this approach we have revealed additional pathogenic variants in 4.4% of cases. Although this study included fewer ovarian cancer patients than breast cancer patients due to the low consent rate, our results highlight the importance of performing multigene panel testing of patients with HBOC in the Korean population as an alternative strategy for identifying shaded P/LP variants. We also demonstrated how exon splicing analysis by conducting in silico predictions or functional studies using patient samples can be beneficial in the identification of uncharacterized intronic variants that are expected to increase HBOC risk. Finally, further analysis is warranted to determine the clinical impact and patient outcomes associated with the identification of P/LP variants in non‐BRCA1/2.
ETHICAL CONSIDERATIONS
This study was approved by the International Review Board (IRB) of the National Cancer Center of Korea (IRB No. NCCNCS13717 and NCC2017‐0127), and written informed consent was obtained from all participating patients.
CONFLICT OF INTEREST
None.
Supporting information
Supplementary Materials
ACKNOWLEDGMENTS
This work was supported by grants from the National Cancer Center [grant number NCC‐1611161] and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education [grant number 2018R1A6A3A01012838]. This work was also supported by the National Research Foundation of Korea (NRF) grant, funded by the Korean government (MSIT) [grant number 2020R1A2C2010566]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the researchers at the Center for Breast Cancer and Gynecologic Cancer of the National Cancer Center (Republic of Korea) for helping collect patient samples and clinical data.
Ryu J‐S, Lee H‐Y, Cho EH, et al. Exon splicing analysis of intronic variants in multigene cancer panel testing for hereditary breast/ovarian cancer. Cancer Sci. 2020;111:3912–3925. 10.1111/cas.14600
REFERENCES
- 1. O'Leary E, Iacoboni D, Holle J, et al. Expanded gene panel use for women with breast cancer: identification and intervention beyond breast cancer risk. Ann Surg Oncol. 2017;24:3060‐3066. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Lichtenstein P, Holm NV, Verkasalo PK, et al. Environmental and heritable factors in the causation of cancer–analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med. 2000;343:78‐85. [DOI] [PubMed] [Google Scholar]
- 3. Pharoah PD, Antoniou A, Bobrow M, Zimmern RL, Easton DF, Ponder BA. Polygenic susceptibility to breast cancer and implications for prevention. Nat Genet. 2002;31:33‐36. [DOI] [PubMed] [Google Scholar]
- 4. Coppa A, Nicolussi A, D'Inzeo S, et al. Optimizing the identification of risk‐relevant mutations by multigene panel testing in selected hereditary breast/ovarian cancer families. Cancer Med. 2018;7:46‐55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Kurian AW, Hare EE, Mills MA, et al. Clinical evaluation of a multiple‐gene sequencing panel for hereditary cancer risk assessment. J Clin Oncol. 2014;32:2001‐2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Howarth DR, Lum SS, Esquivel P, Garberoglio CA, Senthil M, Solomon NL. Initial results of multigene panel testing for hereditary breast and ovarian cancer and lynch syndrome. Am Surg. 2015;81:941‐944. [PubMed] [Google Scholar]
- 7. Walsh T, Lee MK, Casadei S, et al. Detection of inherited mutations for breast and ovarian cancer using genomic capture and massively parallel sequencing. Proc Natl Acad Sci USA. 2010;107:12629‐12633. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Tucker T, Marra M, Friedman JM. Massively parallel sequencing: the next big thing in genetic medicine. Am J Hum Genet. 2009;85:142‐154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Slavin TP, Niell‐Swiller M, Solomon I, et al. Clinical application of multigene panels: challenges of next‐generation counseling and cancer risk management. Front Oncol. 2015;5:208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Maxwell KN, Hart SN, Vijai J, et al. Evaluation of ACMG‐guideline‐based variant classification of cancer susceptibility and non‐cancer‐associated genes in families affected by breast cancer. Am J Hum Genet. 2016;98:801‐817. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Desmond A, Kurian AW, Gabree M, et al. Clinical actionability of multigene panel testing for hereditary breast and ovarian cancer risk assessment. JAMA Oncol. 2015;1:943‐951. [DOI] [PubMed] [Google Scholar]
- 12. Li MM, Datto M, Duncavage EJ, et al. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists. J Mol Diagn. 2017;19:4‐23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Daly MB, Pilarski R, Berry M, et al. NCCN guidelines insights: genetic/familial high‐risk assessment: breast and ovarian, version 2.2017. J Natl Compr Canc Netw. 2017;15:9‐20. [DOI] [PubMed] [Google Scholar]
- 14. Couch FJ, Shimelis H, Hu C, et al. Associations between cancer predisposition testing panel genes and breast cancer. JAMA Oncol. 2017;3:1190‐1196. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Anna A, Monika G. Splicing mutations in human genetic disorders: examples, detection, and confirmation. J Appl Genet. 2018;59:253‐268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. DePristo MA, Banks E, Poplin R, et al. A framework for variation discovery and genotyping using next‐generation DNA sequencing data. Nat Genet. 2011;43:491‐498. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Heng L. Aligning sequence reads, clone sequences and assembly contigs with BWA‐MEM arXiv Preprint. 2013; arXiv:1303.3997.
- 18. McKenna A, Hanna M, Banks E, et al. The genome analysis toolkit: a MapReduce framework for analyzing next‐generation DNA sequencing data. Genome Res. 2010;20:1297‐1303. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27:2987‐2993. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Fang H, Bergmann EA, Arora K, et al. Indel variant analysis of short‐read sequencing data with Scalpel. Nat Protoc. 2016;11:2529‐2548. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. McLaren W, Gil L, Hunt SE, et al. The ensembl variant effect predictor. Genome Biol. 2016;17:122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Liu X, Wu C, Li C, Boerwinkle E. dbNSFP v3.0: a one‐stop database of functional predictions and annotations for human nonsynonymous and splice‐site SNVs. Hum Mutat. 2016;37:235‐241. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17:405‐424. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Frisso G, Detta N, Coppola P, et al. Functional studies and in silico analyses to evaluate non‐coding variants in inherited cardiomyopathies. Int J Mol Sci. 2016;17:1883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Santos C, Peixoto A, Rocha P, et al. Pathogenicity evaluation of BRCA1 and BRCA2 unclassified variants identified in Portuguese breast/ovarian cancer families. J Mol Diagn. 2014;16:324‐334. [DOI] [PubMed] [Google Scholar]
- 26. Steffensen AY, Dandanell M, Jonson L, et al. Functional characterization of BRCA1 gene variants by mini‐gene splicing assay. Eur J Hum Genet. 2014;22:1362‐1368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Sanz DJ, Acedo A, Infante M, et al. A high proportion of DNA variants of BRCA1 and BRCA2 is associated with aberrant splicing in breast/ovarian cancer patients. Clin Cancer Res. 2010;16:1957‐1967. [DOI] [PubMed] [Google Scholar]
- 28. Nakagomi H, Hirotsu Y, Okimoto K, et al. PALB2 mutation in a woman with bilateral breast cancer: a case report. Mol Clin Oncol. 2017;6:556‐560. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Stadler ZK, Schrader KA, Vijai J, Robson ME, Offit K. Cancer genomics and inherited risk. J Clin Oncol. 2014;32:687‐698. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Lerner‐Ellis J, Khalouei S, Sopik V, Narod SA. Genetic risk assessment and prevention: the role of genetic testing panels in breast cancer. Expert Rev Anticancer Ther. 2015;15:1315‐1326. [DOI] [PubMed] [Google Scholar]
- 31. Yoo J, Lee GD, Kim JH, et al. Clinical validity of next‐generation sequencing multi‐gene panel testing for detecting pathogenic variants in patients with hereditary breast‐ovarian cancer syndrome. Ann Lab Med. 2020;40:148‐154. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Eoh KJ, Kim JE, Park HS, et al. Detection of germline mutations in patients with epithelial ovarian cancer using multi‐gene panels: beyond BRCA1/2. Cancer Res Treat. 2018;50:917‐925. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Park JS, Lee ST, Nam EJ, et al. Variants of cancer susceptibility genes in Korean BRCA1/2 mutation‐negative patients with high risk for hereditary breast cancer. BMC Cancer. 2018;18:83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Hirotsu Y, Nakagomi H, Sakamoto I, et al. Multigene panel analysis identified germline mutations of DNA repair genes in breast and ovarian cancer. Mol Genet Genomic Med. 2015;3:459‐466. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Wang J, Li W, Shi Y, et al. Germline mutation landscape of Chinese patients with familial breast/ovarian cancer in a panel of 22 susceptibility genes. Cancer Med. 2019;8:2074‐2084. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Swisher EM. Usefulness of multigene testing: catching the train that's left the station. JAMA Oncol. 2015;1:951‐952. [DOI] [PubMed] [Google Scholar]
- 37. Evans DG, Howell SJ, Frayling IM, Peltonen J. Gene panel testing for breast cancer should not be used to confirm syndromic gene associations. NPJ Genom Med. 2018;3:32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Chan GHJ, Ong PY, Low JJH, et al. Clinical genetic testing outcome with multi‐gene panel in Asian patients with multiple primary cancers. Oncotarget. 2018;9:30649‐30660. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Ready K, Johansen Taber KA, Bonhomme N, Lichtenfeld JL. Strategies for improving access to hereditary cancer testing: recommendations from stakeholders. Genet Med. 2019;21:1702‐1704. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Win AK, Reece JC, Dowty JG, et al. Risk of extracolonic cancers for people with biallelic and monoallelic mutations in MUTYH. Int J Cancer. 2016;139:1557‐1563. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Rizzolo P, Silvestri V, Bucalo A, et al. Contribution of MUTYH variants to male breast cancer risk: results from a multicenter study in Italy. Front Oncol. 2018;8:583. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Zhu M, Chen X, Zhang H, et al. AluYb8 insertion in the MUTYH gene and risk of early‐onset breast and gastric cancers in the Chinese population. Asian Pac J Cancer Prev. 2011;12:1451‐1455. [PubMed] [Google Scholar]
- 43. Wasielewski M, Out AA, Vermeulen J, et al. Increased MUTYH mutation frequency among Dutch families with breast cancer and colorectal cancer. Breast Cancer Res Treat. 2010;124:635‐641. [DOI] [PubMed] [Google Scholar]
- 44. Rennert G, Lejbkowicz F, Cohen I, Pinchev M, Rennert HS, Barnett‐Griness O. MutYH mutation carriers have increased breast cancer risk. Cancer. 2012;118:1989‐1993. [DOI] [PubMed] [Google Scholar]
- 45. Out AA, Wasielewski M, Huijts PE, et al. MUTYH gene variants and breast cancer in a Dutch case‐control study. Breast Cancer Res Treat. 2012;134:219‐227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46. Apostolou P, Papasotiriou I. Current perspectives on CHEK2 mutations in breast cancer. Breast Cancer (Dove Med Press). 2017;9:331‐335. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47. Evans MK, Longo DL. PALB2 mutations and breast‐cancer risk. N Engl J Med. 2014;371:566‐568. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Antoniou AC, Foulkes WD, Tischkowitz M. Breast‐cancer risk in families with mutations in PALB2. N Engl J Med. 2014;371:1651‐1652. [DOI] [PubMed] [Google Scholar]
- 49. Hofstatter EW, Domchek SM, Miron A, et al. PALB2 mutations in familial breast and pancreatic cancer. Fam Cancer. 2011;10:225‐231. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50. De Nicolo A, Tancredi M, Lombardi G, et al. A novel breast cancer‐associated BRIP1 (FANCJ/BACH1) germ‐line mutation impairs protein stability and function. Clin Cancer Res. 2008;14:4672‐4680. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51. Roberts ME, Jackson SA, Susswein LR, et al. MSH6 and PMS2 germ‐line pathogenic variants implicated in Lynch syndrome are associated with breast cancer. Genet Med. 2018;20:1167‐1174. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52. Slavin TP, Maxwell KN, Lilyquist J, et al. The contribution of pathogenic variants in breast cancer susceptibility genes to familial breast cancer risk. NPJ Breast Cancer. 2017;3:22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53. Decker B, Allen J, Luccarini C, et al. Rare, protein‐truncating variants in ATM, CHEK2 and PALB2, but not XRCC2, are associated with increased breast cancer risks. J Med Genet. 2017;54:732‐741. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54. Jerzak KJ, Mancuso T, Eisen A. Ataxia‐telangiectasia gene (ATM) mutation heterozygosity in breast cancer: a narrative review. Curr Oncol. 2018;25:e176‐e180. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55. Moyer CL, Ivanovich J, Gillespie JL, et al. Rare BRIP1 missense alleles confer risk for ovarian and breast cancer. Cancer Res. 2020;80:857‐867. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Billing D, Horiguchi M, Wu‐Baer F, et al. The BRCT domains of the BRCA1 and BARD1 tumor suppressors differentially regulate homology‐directed repair and stalled fork protection. Mol Cell. 2018;72:127‐139.e8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Yoon KA, Kong SY, Lee EJ, Cho JN, Chang S, Lee ES. A Novel germline mutation in BRCA1 causes exon 20 skipping in a Korean family with a history of breast cancer. J Breast Cancer. 2017;20:310‐313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58. Findlay GM, Daza RM, Martin B, et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature. 2018;562:217‐222. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Materials
