Pathogenic germline variants in cancer predisposition genes in patients with multiple primary cancers in an Asian population and the role of extended panel genetic testing - PubMed (original) (raw)

doi: 10.1016/j.esmoop.2025.104495. Epub 2025 Mar 10.

J J Zhao 2, P Y Ong 1, S G W Ow 1, C J L Ow 3, G H J Chan 1, R J Walsh 1, J S J Lim 4, S E Lim 1, Y W Lim 1, A L A Wong 1, J E-L Wong 1, S C Lee 5

Affiliations

Pathogenic germline variants in cancer predisposition genes in patients with multiple primary cancers in an Asian population and the role of extended panel genetic testing

S W Cheo et al. ESMO Open. 2025 Mar.

Abstract

Background: Multiple primary cancers (MPC) are an indicator of potential hereditary cancer predisposition syndrome. There remains insufficient data on genetic testing outcomes and the optimal testing panel for MPC. We evaluated the prevalence of MPC, the spectrum of pathogenic germline variants (PGVs) and the role of extended panel testing in MPC.

Methods: Cancer patients seen in a cancer genetics clinic in a tertiary cancer centre in Singapore from 2000 to 2023 were included. Clinical characteristics, PGV and patterns of cancer were analysed. Most patients were tested with 49 genes, but in a selected 156 patients with MPC, extended testing with 216 genes was carried out.

Results: Of 3514 cancer patients (male = 17.9%, female = 82.1%), 668 (19%) had MPC (2 primaries, n = 570; 3 primaries, n = 81; ≥4 primaries, n = 17). The most common tumour pairs were breast-breast (33.2%), breast-ovary (8.9%), breast-endometrial (4.6%) and endometrial-ovary (4.6%). Patients with MPC had a younger median age of first cancer. Of the MPC patients, 29.4% tested positive for at least one PGV, with PGVs detected in BRCA1/2 (39.9%), other homologous recombination repair (HRR) genes (18.9%), mismatch repair (MMR) genes (11.2%) and TP53 (7%) genes. HRR genes included ATM, BARD1, BRIP1, CHEK2, PALB2, FANCL, RAD51C and RAD51D, while MMR genes included MLH1, MSH2, MSH6 and PMS2. MPC patients were more likely to have PGVs in TP53 and BARD1 compared with patients with single primary cancer. Extended testing detected more PGVs in MPC despite initial noninformative testing. It increased the number of PGVs detected in less established cancer predisposition genes, which include CFTR, SPINK1, TNFRSF13B, TET2, ADA, CDKN1C, CTNNA1, DDX41, HAX1, RECQL4 and MBD4.

Conclusion: Patients with MPC were more likely to harbour a PGV. Extended testing improved PGV detection rates, particularly for less well-known cancer predisposition genes.

Keywords: extended testing; germline genetic testing; hereditary cancer predisposition syndrome; multiple primary cancers; pathogenic germline variants.

Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.

PubMed Disclaimer

Figures

Figure 1

Figure 1

Heatmaps showing mutation pattern observed in patients tested positive for any pathogenic germline variant (PGV) in (A) single primary cancer (SPC; n = 367) and (B) multiple primary cancer (MPC; n = 143). Each column represents each individual patient and each row represent a gene. Clinical characteristics including index primary cancer, sex, ethnicity and suspected clinical syndrome are shown in colour at the bottom. Percentages reflect the number of patients with the respective mutations among patients with PGV. Among the patients, 14 with SPC and 8 with MPC had more than one mutation. (C) Chord diagram describing the pairs of first and second cancer diagnoses among all patients with MPC. (D) Chord diagram describing the pairs of second and third cancer diagnoses among patients with three or more primary cancers. Each connection in (C) and (D) reflects the cancer pairs, where the colour of the line denotes the preceding cancer. CRC, colorectal cancer; HCC, hepatocellular carcinoma; NET, neuroendocrine tumour; NPC, nasopharyngeal carcinoma.

Figure 2

Figure 2

Key comparisons: (A) frequency of pathogenic germline variants (PGVs) among patients stratified by number of cancers; (B) number of PGVs identified per patient stratified by type of gene panels utilized. Other gene panel refers to gene panel other than the 216-gene panel. (C) Distribution of causative genes in patients identified with PGV stratified by number of primaries. (D) Comparisons of PGVs between patients with single versus multiple cancer across all cancer types. Each row denotes percentage of patients tested positive for the PGV (single versus multiple primary cancer). The percentage is calculated based on number of positive patients over total number of patients tested for the PGV. (E) Comparisons of PGVs between patients with single versus multiple cancer by cancer type. CRC, colorectal cancer; MMR, mismatch repair; PGL, paraganglioma–pheochromocytoma syndrome; prop, proportion; VHL, Von Hippel-Lindau.

Figure 3

Figure 3

Three or more primary cancers. (A) Heatmap showing mutation patterns observed in 24 patients with three or more primary cancers with at least one pathogenic germline variant (PGV) identified. The plot represents a graphical summary of the distribution of PGVs across patients who underwent germline genetic testing. Each column represents each individual patient and each row represents a gene. Legend for clinical characteristics is shown on the right. Percentages reflect the number of patients with the respective mutations among patients with PGVs. (B) This Sankey plot illustrates the pattern of subsequent cancers for all patients. Each column represents a different cancer at the different timepoint, with nodes labelled by cancer types (e.g. breast, lung, colorectal cancer and others). The leftmost column lists the index primary cancers, followed by the subsequent primary cancers. Flows between nodes indicate transitions from one cancer type to another, with the thickness of each flow proportional to the number of patients making that transition. The final column, labelled ‘nil further ca’, represents patients who did not develop further additional cancers. The plot illustrates the patterns of multiple primary cancer among our patients. CRC, colorectal cancer; HCC, hepatocellular carcinoma; mut, mutation; nil further ca, no further cancer; NPC, nasopharyngeal cancer; wt, wild type.

References

    1. Vogt A., Schmid S., Heinimann K., et al. Multiple primary tumours: challenges and approaches, a review. ESMO Open. 2017;2(2) -PMC -PubMed
    1. Cavazos T.B., Kachuri L., Graff R.E., et al. Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies. BMC Med. 2022;20(1):332. -PMC -PubMed
    1. Savkova A., Gulyaeva L., Gerasimov A., Krasil’nikov S. Genetic analysis of multiple primary malignant tumors in women with breast and ovarian cancer. Int J Mol Sci. 2023;24(7):6705. -PMC -PubMed
    1. Demoor-Goldschmidt C., de Vathaire F. Review of risk factors of secondary cancers among cancer survivors. Br J Radiol. 2019;92(1093) -PMC -PubMed
    1. Whitworth J., Hoffman J., Chapman C., et al. A clinical and genetic analysis of multiple primary cancer referrals to genetics services. Eur J Hum Genet. 2015;23(5):581–587. -PMC -PubMed

MeSH terms

LinkOut - more resources