Genetic evaluation of patients with multiple primary cancers

  • Authors:
    • Maria Valeria Freire
    • Romain Thissen
    • Marie Martin
    • Corinne Fasquelle
    • Laura Helou
    • Keith Durkin
    • Maria Artesi
    • Aimé Lumaka
    • Natacha Leroi
    • Karin Segers
    • Michelle Deberg
    • Jean-Stéphane Gatot
    • Lionel Habran
    • Leonor Palmeira
    • Claire Josse
    • Vincent Bours
  • View Affiliations

  • Published online on: October 15, 2024     https://doi.org/10.3892/ol.2024.14750
  • Article Number: 4
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Abstract

Regarding inherited cancer predisposition, single gene carriers of pathogenic variants (PVs) have been extensively reported on in the literature, whereas the oligogenic coinheritance of heterozygous PVs in cancer‑related genes is a poorly studied event. Currently, due to the increased number of cancer survivors, the probability of patients presenting with multiple primary cancers (MPCs) is higher. The present study included patients with MPCs aged ≤45 years without known PVs in common cancer predisposition genes. This study used whole exome sequencing (WES) of germline and tumoral DNA, chromosomal microarray analysis (CMA) of germline DNA (patients 1‑7, 9 and 10), and a karyotype test of patient 8 to detect variants associated with the disease. The 10 patients included in the study presented a mean of 3 cancers per patient. CMA showed two microduplications and one microdeletion, while WES of the germline DNA identified 1‑3 single nucleotide variants of potential interest to the disease in each patient and two additional copy number variants. Most of the identified variants were classified as variants of uncertain significance. The mapping of the germline variants into their pathways showed a possible additive effect of these as the cause of the cancer. A total of 12 somatic samples from 5 patients were available for sequencing. All of the germline variants were also present in the somatic samples, while no second hits were identified in the same genes. The sequencing of patients with early cancers, family history and multiple tumors is already a standard of care. However, growing evidence has suggested that the assessment of patients should not stop at the identification of one PV in a cancer predisposition gene.

Introduction

Multiple primary cancers (MPCs) are defined as the occurrence of more than one synchronous or metachronous cancer in a patient. For reporting purposes, the identification of MPCs is variable across the regulatory agencies. The Surveillance, Epidemiology and End Results (SEER) program considers the histology, site, laterality, and time since initial diagnosis of the tumor, while for the International Agency for Research on Cancer (IARC) only one tumor is registered for an organ, irrespective of time. The definition of synchronous and metachronous tumors also varies, having a threshold of 2 months in SEER and 6 months in IARC (1,2).

The development of screening tests and new cancer therapies improved cancer patient survival. By 2005, almost 900,000 of the 11 million cancer survivors were diagnosed with more than one cancer. The risk of developing subsequent cancers varies with regards to the type of first primary site, age at diagnosis, environmental exposure and genetic factors (3).

The identification of genes associated with hereditary cancer risk started 25 years ago with the discovery of BRCA pathogenic variants in families with breast and ovarian cancers. Since then, more than 80 cancer predisposition syndromes and 100 cancer-related genes were identified (4). For each syndrome, the most commonly associated cancers are defined but the exact risk profile remains often unknown. One common characteristic of these conditions is the young age at cancer diagnosis in most patients, although a considerable heterogeneity is observed. Additionally, it is widely stated that patients with multiple primary cancers are more likely to carry germline pathogenic variants in cancer-related genes (5).

For patients with MPCs without a germline molecular genetic diagnosis after initial evaluation, single-nucleotide variants (SNVs), copy number variants (CNVs), or de novo chromosomal rearrangements could be the cause of the disease. Another possibility could be the additive effect of multiple genetic events influencing a single biochemical mechanism. The aim of this study was to identify novel genetic mechanisms associated with risk of tumor development in patients with MPCs.

Patients and methods

Patient selection

We selected patients with ≥2 tumors before 45 years old, who were evaluated by the genetic department of the CHU de Liège from March 2019 to December 2022. The routine genetic assessment and testing with targeted next-generation sequencing (NGS) failed to establish a germline molecular genetic diagnosis. Additionally, the patients lacked family history suggestive of a cancer predisposition syndrome. Tumors in the same tissue or organ were considered separate primary tumors if, in the case of paired organs, they presented bilaterally or if the clinical history clearly indicated that they were different. All participants gave informed consent to participate in the study.

Data collection

Patient sex, age, age at diagnosis of each of the tumors, personal and family history were extracted from the medical records. Data regarding cancer diagnosis and treatment was collected from the institutions database.

Germline analysis

Whole exome sequencing (WES, Novogene) and a high-resolution (180K and 60K) chromosomal microarray analysis reference (CMA, Agilent) were performed on the DNA extracted from the blood of the patients. The WES data was analyzed using our own Humanomics pipeline [as described in (6)] and two interpretation software (Illumina BaseSpace Variant Interpreter and Diploid Moon). The variants were filtered according to their quality (allele depth and genotype quality), population frequency, the effect on the gene and the classification of the variant in databases. Variant classification was performed according to ACMG Standards and Guidelines for the Interpretation of Sequence Variants (7). The variants identified in the WES analysis were confirmed by Sanger sequencing (Fig. S1).

CNV analysis was conducted on the BAM file (mapping with bwa version v0.7.17 and cleaning with elprep version v4.1.5) arising from the identical sequencing batch using the Humanomics BED file, which enabled the detection of CNVs bigger than one whole exon. The depth of coverage was calculated specifically on exons within these files, and the normalization set comprised 400 patients (200 males and 200 females). The CNVs were detected by implementing of our in-house pipeline (StueckFinder v2.2) that integrates the well-established tool CANOES (8) and code modifications to enable CNV detection on the gonosomes. Variant classification was performed according to the ACMG/ClinGen technical standards for the interpretation and reporting of constitutional copy number variants (9). The detected CNVs were confirmed by nanopore sequencing.

Tumor analysis

WES of the tumoral DNA (using Mechanical Fragmentation and the Twist Universal Adapter System) was performed on the DNA extracted from the available Formalin-Fixed Paraffin-Embedded (FFPE) patient's samples. The data analysis was performed using QIAGEN Digital Insight Software Genomics Workbench 21 for data preparation, mapping, variant calling and annotation. The tumoral WES results were analyzed separately and as a tumor-normal pair. Variant classification was performed according to ACMG Standards and Guidelines for the Interpretation of Sequence Variants in Cancer (10) and the ClinGen specification when available. Mutational signatures in the samples were analyzed Using Mutational Patterns R package (11) and COSMIC v2 signatures (12), taking only the somatic variants into account.

Results

Patients' characteristics

Ten patients with multiple cancers were included in the study. The mean age was 40.7±5.4 years, 7 patients were female and 3 were male. None of the patients had family cancer history suggestive of a cancer predisposition syndrome. Before enrolment, by targeted NGS sequencing a CHEK2 and ATM variant was identified in two patients, however they could not explain the full phenotype observed. The CMA results included two microduplications and one microdeletion (Table I).

Table I.

Patient characteristics.

Table I.

Patient characteristics.

PatientSexAge, yearsFamily cancer history and age at diagnosis, yearsCancer type and age at diagnosis, yearsInitial genetic evaluationCMA results
P1M44Choroidal melanoma inMelanoma at 18,Kit BRCA HEREDITARY CANCER MASTR Plus: BRCA1,arr[hg19]
father at 68left seminoma at 21,BRCA2, PALB2, CHEK2, BARD1, BRIP1, RAD51C, RAD51D,2q13(111,408,
right seminoma at 37,TP53, MRE11A, RAD50, NBN, FAM175A, ATM, STK11,390–113,098,
thyroid cancer at 38MEN1, PTEN, CDH1, MUTYH, BLM, XRCC2, MLH1, MSH6,686)x1
PMS2 and MSH2, and the 3′ UTR of EPCAM
P2F43Basal cell carcinoma at 37Bilateral breast tumorKit BRCA HEREDITARY CANCER MASTR Plus: BRCA1,arr[hg19]
at 23, melanoma atBRCA2, PALB2, CHEK2, BARD1, BRIP1, RAD51C, RAD51D, 16p13.11(14910205-
unknown ageTP53, MRE11A, RAD50, NBN, FAM175A, ATM, STK11,16525348)x3
MEN1, PTEN, CDH1, MUTYH, BLM, XRCC2, MLH1, MSH6,
PMS2 and MSH2, and the 3′ UTR of EPCAM
P3F38Generalized cancer inMelanoma at 23, 24,Sanger sequencing of CDK4 and BAP1, direct sequencing ofarr[hg19] (1–22, X)x2
half-sister at 3530, 34 and 35c.1100delC in gene CHEK2. High-throughput sequencing:
BRCA MASTR Dx kit (BRCA1, BRCA2), PALB2, TP53
(exons 2–11), ATM, CDKN2A
P4F33Pancreatic cancer inMedulloblastoma at 10,Sanger sequencing of CDK4 and BAP1, direct sequencing ofarr[hg19] (1–22, X)x2
paternal grandmother at 64ovary tumor at 26c.1100delC in gene CHEK2. High-throughput sequencing:
BRCA MASTR Dx kit (BRCA1, BRCA2), PALB2, TP53
(exons 2–11), ATM, CDKN2A
P5M42No historyColorectal cancer at 37,Kit HNPCC MASTR Plus: MLH1, MSH2, MSH6, PMS2, andarr[hg19] (122)x2,
melanoma at unknown3′ UTR of EPCAM. Sequencing of APC, MTYH, NTHL1, TP53,(XY)x1
ageBAP1
P6F36Thyroid cancer in sister atThyroid tumor at 26,Kit SUREMASTR HEREDITARY CANCER: BRCA1, BRCA2,arr[hg19] (1–22, X)x2
unknown age, breast cancermelanoma at 28PALB2, TP53, CHEK2, MLH1, MSH2, MSH6, ATM, BRIP1,
in mother after the age of 50 RAD51C, RAD51D
and maternal grandmother
P7F44Ovarian cancer in motherBreast tumor at 35,Kit BRCA HEREDITARY CANCER MASTR Plus: BRCA1,arr[hg19] (1–22, X)x2
at 45, breast cancer inthyroid tumor at 36BRCA2, PALB2, CHEK2, BARD1, BRIP1, RAD51C, RAD51D,
half-sister (same mother) TP53, MRE11A, RAD50, NBN, FAM175A, ATM, STK11,
at 37 MEN1, PTEN, CDH1, MUTYH, BLM, XRCC2, MLH1, MSH6,
PMS2 and MSH2, and the 3′ UTR of EPCAM
P8F52Prostate cancer at 57,Breast tumor at 33,High-throughput sequencing: Kit SUREMASTRarr[hg19] (1–22, X)x2
pheochromocytoma atthyroid cancer at 38HEREDITARY CANCER (BRCA1, BRCA2, PALB2, TP53,
68 and paraganglioma at CHEK2, MLH1, MSH2, MSH6, ATM, BRIP1, RAD51C,
unknown age in father, RAD51D). PTEN gene sequencing and MLPA
breast cancer in mother at
49 and grandmother at 60
P9F38Synovial sarcoma inMelanoma at 31,Arrhythmia/Primary Electrical disease panel: ABCB4, ABCC9,arr[hg19] (1–22, X)x2
mother at 35thyroid cancer at 34ACTN2, AKAP9, ANK2, CACNA1C, CACNA2D1, CACNB2,
CALM1, CALM2, CALM3, CASO2, CAY3, CTNNA3, DES,
DPP6, DSC2, DSG2, DSP, GJA1 (CX43), GJAS (CX40), GNB5,
GPD1L, HCN4, JUP, KCNAS, KCND3, KCNE1, KCNE2,
KCNE3, KCNE5 (KCNE1L), KCNH2, KCNJ2, KCNJ5 (GIRK4),
KCNJ8, KCNKI7, KCNQI, LMNA, NKX2-5 (NKX2E), NOS1AP,
NPPA, PKP2, PLN, PPA2, PRKAG2, RANGRF (MOG1), RRAD,
RYR2, SCN1B, SCN2B, SCN3B, SCN4B, SCN5A, SCN10A,
SLMAP, SNTA1, TGFB3, TMEM43, TRDN, TRPM4
P10M37No historySeminoma at 24,High-throughput sequencing: Kit SUREMASTR HEREDITARYarr[hg19]
bladder cancer at 33,CANCER (BRCA1, BRCA2, PALB2, TP53, CHEK2, MLH1, 2q13(110862477-
kidney cancer at 34MSH2, MSH6, ATM, BRIP1, RAD51C, RAD51D). FH gene110964737)x4
sequencing. Hereditary pheochromocytoma and paraganglioma
panel (SDHA, SDHB, SDHC, SDHD, VHL, RET). Hereditary
non-polyposis colorectal cancer panel (MLH1, MSH2, MSH6).
MLPA of BRCA1, BRCA2, FH, SDHB, SDHC, SDHD, VHL,
MLH1, MSH2, MSH6

[i] CMA, chromosomal microarray analysis; F, female; M, male.

We observed a mean of 3.2 tumors per patient. The tumors included melanomas, seminomas, thyroid cancer, gynecological tumors, and others (Table II).

Table II.

Tumor characteristics.

Table II.

Tumor characteristics.

CharacteristicFirst tumor (n=10)Second tumor (n=10)Third tumor (n=6)Fourth tumor (n=4)Fifth tumor (n=2)Total (n=32)
Mean ± SD age at presentation, years26.9±8.530.8±6.033.8±4.035.3±1.535±1.4
Tumor type, n (%)
  Melanoma3 (30.0)3 (30.0)3 (50.0)2 (50.0)2 (100.0)13 (40.6)
  Seminoma1 (10.0)1 (10.0)1 (16.7)0 (0.0)0 (0.0)3 (9.4)
  Thyroid cancer1 (10.0)3 (30.0)0 (0.0)1 (25.0)0 (0.0)5 (15.6)
  Breast tumor3 (30.0)1 (10.0)0 (0.0)0 (0.0)0 (0.0)4 (12.5)
  Ovarian tumor0 (0.0)1 (10.0)1 (16.7)0 (0.0)0 (0.0)2 (6.3)
  Neuronal tumors1 (10.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (3.1)
  Muscle tumors0 (0.0)0 (0.0)0 (0.0)1 (25.0)0 (0.0)1 (3.1)
  CRC1 (10.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (3.1)
  Renal and urinary tract tumors0 (0.0)1 (10.0)1 (16.6)0 (0.0)0 (0.0)2 (6.3)

[i] CRC, colorectal cancer; SD, standard deviation.

Germline WES results

CNVs and missense, nonsense and splicing SNVs were identified in the patients included in the study (Table III). The variants were classified according to the ACMG criteria and ClinGen specifications whenever available. Most of the identified SNVs were variants of uncertain significance (VUS), and only two variants were classified as pathogenic (Table IV). One of the pathogenic variants, an ATM splicing variant (c.8988–1G>A) that affected a canonical splice site, was not present in GnomAD, was predicted as deleterious by SIFT, Mutation taster, Provean, and the splicing in silico analysis. The second pathogenic variant in the MUTYH gene was previously described in patients with MUTYH-Associated Polyposis, an autosomal recessive disease that predisposes to colorectal cancer (13). Furthermore, heterozygous deleterious MUTYH variants were described as drivers in various types of cancer (adrenocortical carcinoma, esophageal carcinoma, sarcoma, prostate adenocarcinoma and kidney renal clear cell carcinoma) (14).

Table III.

Genetic alterations identified in the patients.

Table III.

Genetic alterations identified in the patients.

PatientGeneVariantType
P1CHEK2c1100delC (p.Thr367Metfs*15)Nonsense SNV
EME2c.964C>T (p.Gln322*)Nonsense SNV
ATRIPc.1637T>G (p.Leu546Trp)Missense SNV
BUB1arr[hg19] 2q13(111,408,390–113,098,686)x1CNV
P2HNF1Ac.92G>A (p.Gly31Asp)Missense SNV
TSC2c.5383C>T (p.Arg1795Cys)Missense SNV
MSR1c.(956+1_957-1)_ 3618delCNV
P3ATMc.8988–1G>ASplicing SNV
APCc.295C>T (p.Arg99Trp)Missense SNV
P5ERCC2c.2260G>C (p.Glu754Gln)Missense SNV
P6RASA2c.865T>C (p.Tyr289His)Missense SNV
P7RIF1c.1475A>G (c.1475A>G)Missense SNV
APOBEC3Bg.(?_ 39378444)_(39388168_?)delCNV
P8CHEK2c.434G>A (p.Arg145Gln)Missense SNV
P9ATMc.2057T>A (p.Leu686His)Missense SNV
P10MUTYHc.536A>G (p.Tyr179Cys)Missense SNV

[i] Reference transcripts: APC NM_000038.6, APOBEC3B NC_000081.7, ATM NM_000051.3, ATRIP NM_130384.2, BRCA1 NM_007294.3, CHEK2 NM_007194.4, EME2 NM_001257370.2, ERCC2 NM_000400.4, HNF1A NM_000545.5, MSR1 NM_138715.2, MUTYH NM_012222.2, RASA2 NM_006506.5, RIF1 NM_018151.4, TSC2 NM_000548.5.

Table IV.

Single nucleotide variants identified in the patients.

Table IV.

Single nucleotide variants identified in the patients.

PatientGeneVariantEffectPredictors classifying the variant as deleteriousGnomAD frequencyLiterature reportsClassification
P1CHEK2c1100delCNonsenseCADD0.17%Associated with higher risk of breast,LPV
(p.Thr367Metfs*15) prostate and colorectal cancer (12)
EME2c.964C>T (p.Gln322*)NonsenseMutation taster, FATHMM MKL,0.82%Reported in individual with pancreaticVUS
SIPHY ductal adenocarcinoma at 60 years (13)
ATRIPc.1637T>G (p.Leu546Trp)MissenseSIFT, PROVEAN, FATHMM0.00%-VUS
MKL, SIPHY
P2HNF1Ac.92G>A (p.Gly31Asp)MissenseMutation taster, FATHMM,0.08%Identified in a female with clear RCC andVUS
PROVEAN, SIPHY two chromophobe RCC at age 75 years.
No second variant was found (14).
Identified in person with MSS CRC at
58 years (15)
TSC2c.5383C>T (p.Arg1795Cys)MissenseSIFT, POLYPHEN, Mutation0.15%Reported as probably neutral in functionalVUS
Taster, FATHMM, PROVEAN, study using 293T cells (16). Reported in
SIPHY individual at high risk for breast and/or
ovarian cancer (17)
P3ATMc.8988–1G>ASplicingSIFT, Mutation Taster, PROVEAN,0%A splicing variant at this position wasPV
SIPHY, SPLICEAI AG, SPLICEAI proven to alter the splice acceptor
AL, SPLICING ADA site (18)
APCc.295C>T (p.Arg99Trp)MissenseSIFT, FATHMM, PROVEAN,0.04%Detected in a person from a cohort withVUS
FATHMM MKL, SIPHY B-cell neoplasms (19). Identified in one
of 40 unrelated patients with familial
CRC without classical familial
adenomatous polyposis coli (20)
P4-------
P5ERCC2c.2260G>C (p.Glu754Gln)MissensePROVEAN, SIPHY0.01%-VUS
P6RASA2c.865T>C (p.Tyr289His)MissenseSIFT, Mutation Taster, PROVEAN,0%-VUS
FATHMM MKL, SIPHY
P7RIF1c.1475A>G (c.1475A>G)MissenseSIFT, Mutation Taster, PROVEAN,0%-VUS
FATHMM MKL, SIPHY
P8CHEK2c.434G>A (p.Arg145Gln)MissenseSIFT, POLYPHEN, Mutation0.00%Reported in a female with breast cancerVUS
Taster, FATHMM, PROVEAN, at 37 years (21). Found in one individual
FATHMM MKL, SIPHY with CRC and in none of the cancer
free controls (22). A yeast in vivo assay
showed that the variant was benign (23)
P9ATMc.2057T>A (p.Leu686His)MissenseMutation taster, PROVEAN,0.00%Reported in a female older than 40 yearsVUS
FATHMM MKL, SIPHY with breast cancer (25)
P10MUTYHc.536A>G (p.Tyr179Cys)MissenseSIFT, Mutation taster, FATHMM,0.15%Observed in homozygous and compoundPV
PROVEAN, FATHMM MKL, heterozygous state in multiple individuals
SIPHY with MUTYH-Associated Polyposis (10)

[i] CRC, colorectal cancer; LPV, likely pathogenic variant; MSS, microsatellite stable; RCC, renal cell carcinoma; PV, pathogenic variant; VUS, variant of uncertain significance. Reference transcripts: APC NM_000038.6, ATM NM_000051.3, ATRIP NM_130384.2, BRCA1 NM_007294.3, CHEK2 NM_007194.3, EME2 NM_001257370.1, ERCC2 NM_000400.4, HNF1A NM_000545.5, MUTYH NM_012222.2, RASA2 NM_006506.5, RIF1 NM_018151.4, TSC2 NM_000548.5.

Two CNVs were detected when evaluating WES data in the patients (Table III). One included a MSR1 gene heterozygous deletion of exons 7–10. This CNV was classified as variant of unknow significance according to the ACMG/ClinGen criteria. The second was a heterozygous deletion of the whole APOBEC3B gene, which was classified as pathogenic as for a full gene deletion a pathogenic classification is warranted (15).

Tumor WES results

Twelve somatic samples were available for sequencing, a seminoma and thyroid cancer from patient 1, four melanomas from patient 3, an ovary cancer from patient 4, a thyroid cancer, dermatofibroma and dysplastic nevus from patient 6, and breast and thyroid cancer from patient 7. All the germline variants were also present in the somatic samples, no second hits were identified in the same genes. The mutational signature analysis aimed to identify common etiological factors for the development of the multiple cancers in the patients. The most frequently presented Single Base Substitution (SBS) signatures with a proposed etiology were the DNA mismatch repair alteration signature, and the signatures related to chemotherapy treatment (Table SI). The only obvious correlation between the patient's signatures was observed between three of the four patient 3 melanomas.

Discussion

In this study only two out of 10 patients with MPCs presented clearly pathogenic SNVs. Previous reports showed similar results. When performing a whole-genome sequencing (WGS) of a cohort of patients with MPCs who had undergone genetic assessment, undetected germline pathogenic variants were identified in 15.2% cases (16). In another study, 21% of patients with MPCs had at least one PV identified (17). The rest of our patients had one or more VUS that could potentially act together to cause the disease, supporting the hypothesis of an oligogenic effect, which has been described before (18).

The oligogenic effect of combinations of low penetrance SNVs in cancer-related genes has been suspected for a long time, including in young patients with breast and lung cancers. In a case-control study of 631 women with breast cancer diagnosed under the age of 53, it was proposed that SNVs in ten genes with known or predicted roles in breast cancer interact to affect a woman's cancer risk in a way unpredictable from single gene effects (19). On the other hand, sets of germline SNVs were identified in young non-smokers with lung adenocarcinoma that underwent WES (20).

The additive effect of multiple genetic events influencing a few biochemical mechanisms was observed in patient 1, where the identified variants were mapped into the cancer-related pathways. The SNVs affected genes of the DNA repair pathways (double-strand break repair and Fanconi anemia: CHEK2, ATRIP) and cell cycle checkpoints (EME2), while the genes involved in the microdeletion were mapped into the cell cycle checkpoints (BUB1). The pathogenic variant observed in CHEK2 could explain each of the cancers observed in the patient separately due to the reports that CHEK2 can be associated with risk of melanoma (21), seminoma (22), and other cancers (23). However, each of these reported patients showed a narrower spectrum of cancer, therefore the contribution of other pathogenic variants cannot be ruled out to explain multiple cancers in a single patient. The study of this single patient with a very significant number of precocious malignant tumors thus suggests an oligogenic effect. This patient, now healthy at the age of 46, benefits from a regular clinical and imaging surveillance. However, genetic counselling for his 5 children is very difficult; so far, family testing was not proposed as patient 1 had his first diagnosis at the age of 18 (a melanoma), a clinical follow-up from the age of 13 should probably be proposed.

Patient 2 in addition to two SNVs presented a deletion of the four last exons in MSR1 gene. Germline variants in these gene have been linked to prostate cancer (24) and esophageal carcinoma (25). The importance of this gene in breast cancer and melanoma is yet to be identified. The second CNV was a complete deletion of APOBEC3B gene in patient 7. Germline deletions of this gene have been associated with breast cancer risk (26). The CNVs identified in patient 2 and patient 7 were confirmed by nanopore sequencing.

Three of the patients presented microdeletions/microduplications that could alter micro-RNA expression. However, none of the micro-RNA included in the CNVs has been associated with germline risk of cancer.

The other patients from our cohort showed limited numbers of variants or not any identified variant (patient 4). Of course, we cannot exclude mutations in non-coding areas. Other explanations could include epigenetic or environmental factors. Interestingly, there were not any variants identified in patient 4, who presented with a medulloblastoma at an early age, and a bilateral mucinous ovarian borderline tumor later in life, while her monozygotic twin sister never had a tumor, which suggested a non-genetic cause or low penetrance factors that we could not detect.

In five patients, we could analyze the tumors to search for second hits and confirm the involvement of germline variants in tumor suppressor genes. We could not identify such somatic genetic events. However, for further studies, a simultaneous analysis of the germline and tumor DNA should be done, including epigenetic analysis of the tumor DNA.

On the tumors, we investigated the mutational signatures, as they could orient the investigation toward specific oncologic mechanisms, such as DNA repair defects. We could not identify a recurrent signature in the different tumors from a single patient, except for a defective DNA mismatch repair (MMR) signature observed in the three cancers from patient 6, in which we have not identified any mutation in the MMR genes. Interestingly, several tumors showed a signature indicating exposure to chemotherapy. Although these patients were not previously exposed to chemotherapy nor radiotherapy, exposure to therapeutic or environmental DNA-damaging agents could contribute significantly to cancer risk if there is any constitutional defect in DNA-repair pathways (27).

Our study thus suggests that the simultaneous presence of multiple germline variants can confer a significant cancer risk. We also observed three families with multiple early cancers in patients carrying BRCA2 and ATM mutations (28) and other reports showed similar data (29,30). Moreover, the polygenic risk scores can identify a small population with high cancer risk, as demonstrated for breast cancer (31). Finally, rare recessive conditions could also induce a significant cancer risk as indicated for MCM9 mutations associated with primary ovarian insufficiency and cancer risk (32). Taken together these studies indicate that: i) investigations should not be limited to single gene studies in patients/families with multiple and/or early cancers; ii) In order to identify all the genetic events that could be associated with cancer genes, SNVs, CNVs, and chromosomal rearrangements including gene fusions should be tested combining different techniques such as NGS and optical genome mapping; iii) further studies are needed to investigate the respective role of genetic and epigenetic events in these patients; iv) the exact role of the observed variants and their cumulative effect should be addressed by functional studies.

The limitations of the study include the small number of participants, the challenges of correlating VUS with the disease and the limited availability of somatic samples. The limited number of participants restricts the generalizability of the findings, and makes impossible a mutation frequency analysis to identify common mutation patterns or recurring PVs. At the moment, it will be not possible to reclassify the VUS into other categories, as the information on the variants is limited, these variants are not recurrent in several patients and consequently there is not enough evidence of pathogenicity to initiate functional validation of the variants. Further studies such as dynamic variant analysis, data integration and bioinformatic analysis can provide insights into the variant role in MPCs, and discover potential biomarkers, signaling pathways, and therapeutic targets. Furthermore, it will be necessary to evaluate the effect of gene-gene, gene-environment and protein-protein interactions, and the role of genetic modifiers and environmental factors in MPCs. Indeed, it will be a real challenge to study the role of oligogenic variants in cancer predisposition. Among possibilities, it could be envisioned to inactivate several genes in cell models and study specific biochemical pathways, controlling for instance cell proliferation, apoptosis or DNA repair mechanisms. In these cell models, and in human tumors studied in parallel, proteomic and transcriptomic studies will evaluate simultaneous loss of gene or protein expression as well as protein-protein interactions. In animal models, one could cross heterozygous or homozygous knock-out animals and evaluate spontaneous or induced cancer development.

Supplementary Material

Supporting Data
Supporting Data

Acknowledgements

The CHU Liège is a member of the GENTURIS (GENetic TUmor RISk) European Reference Network.

Funding

This work was supported by Televie (grant no. 7451419F); CHU Liege (grant no. 981481200); Region Wallonne (grant no. 1710180).

Availability of data and materials

The whole exome sequencing data generated in the present study may be found in the SRA database under PRJNA1127072 or at the following URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1127072. The chromosomal microarray analysis data generated in the present study may be found in the Gene Expression Omnibus database under accession number GSE271498 or at the following URL: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE271498.

Authors' contributions

VB conceptualized the present study. MF, MM and VB collected and analyzed the data for the present study. MF was in charge of the formal analysis of the study. VB performed the funding acquisition. MF, MM, RT, MA, KD, LHe, MD, KS, NL, AL, JG, LHa and CF performed the investigation. MF, MM, RT, CJ and LP defined the methodology. VB administered the project and acquired the resources. CJ, AL, LP and VB checked and validated the data analysis. MF and VB wrote the original draft. MF, RT, MM, MA, KD, LHe, CF, MD, AL, NL, KS, JG, LHa, LP, CJ and VB reviewed and edited the manuscript. MF, JG and MD confirm the authenticity of all the raw data. All authors read and approved the final version of the manuscript.

Ethics approval and consent to participate

This study was approved by the Comité d'Éthique Hospitalo-Facultaire Universitaire de Liège (approval no. 2019/245). All subjects provided written informed consent.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Spandidos Publications style
Freire MV, Thissen R, Martin M, Fasquelle C, Helou L, Durkin K, Artesi M, Lumaka A, Leroi N, Segers K, Segers K, et al: Genetic evaluation of patients with multiple primary cancers. Oncol Lett 29: 4, 2025.
APA
Freire, M.V., Thissen, R., Martin, M., Fasquelle, C., Helou, L., Durkin, K. ... Bours, V. (2025). Genetic evaluation of patients with multiple primary cancers. Oncology Letters, 29, 4. https://doi.org/10.3892/ol.2024.14750
MLA
Freire, M. V., Thissen, R., Martin, M., Fasquelle, C., Helou, L., Durkin, K., Artesi, M., Lumaka, A., Leroi, N., Segers, K., Deberg, M., Gatot, J., Habran, L., Palmeira, L., Josse, C., Bours, V."Genetic evaluation of patients with multiple primary cancers". Oncology Letters 29.1 (2025): 4.
Chicago
Freire, M. V., Thissen, R., Martin, M., Fasquelle, C., Helou, L., Durkin, K., Artesi, M., Lumaka, A., Leroi, N., Segers, K., Deberg, M., Gatot, J., Habran, L., Palmeira, L., Josse, C., Bours, V."Genetic evaluation of patients with multiple primary cancers". Oncology Letters 29, no. 1 (2025): 4. https://doi.org/10.3892/ol.2024.14750