bims-lifras Biomed News
on Li-Fraumeni syndrome
Issue of 2024–03–31
four papers selected by
Joanna Zawacka, Karolinska Institutet



  1. Hered Cancer Clin Pract. 2024 Mar 26. 22(1): 4
      Adrenocortical carcinoma (ACC) and pheochromocytoma/paraganglioma (PPGL) are two rare types of adrenal gland malignancies. Regarding hereditary tumors, some patients with ACC are associated with with Li-Fraumeni syndrome (LFS), and those with PPGL with multiple endocrine neoplasia type 2. Recent studies have expanded this spectrum to include other types of hereditary tumors, such as Lynch syndrome or familial adenomatous polyposis. Individuals harboring germline TP53 pathogenic variants that cause LFS have heterogeneous phenotypes depending on the respective variant type. As an example, R337H variant found in Brazilian is known as low penetrant. While 50-80% of pediatric ACC patients harbored a LFS, such a strong causal relationship is not observed in adult patients, which suggests different pathophysiologies between the two populations. As for PPGL, because multiple driver genes, such as succinate dehydrogenase (SDH)-related genes, RET, NF1, and VHL have been identified, universal multi-gene germline panel testing is warranted as a comprehensive and cost-effective approach. PPGL pathogenesis is divided into three molecular pathways (pseudohypoxia, Wnt signaling, and kinase signaling), and this classification is expected to result in personalized medicine based on genomic profiles. It remains unknown whether clinical characteristics differ between cases derived from genetic predisposition syndromes and sporadic cases, or whether the surveillance strategy should be changed depending on the genetic background or whether it should be uniform. Close cooperation among medical genomics experts, endocrinologists, oncologists, and early investigators is indispensable for improving the clinical management for multifaceted ACC and PPGL.
    Keywords:  Hereditary tumors; Paraganglioma; Personalized medicine; Phenotype; Pheochromocytoma; Universal multi-gene germline panel
    DOI:  https://doi.org/10.1186/s13053-024-00276-6
  2. Br J Cancer. 2024 Mar 26.
      Liquid biopsy, a minimally invasive approach for detecting tumor biomarkers in blood, has emerged as a leading-edge technique in cancer precision medicine. New evidence has shown that liquid biopsies can incidentally detect pathogenic germline variants (PGVs) associated with cancer predisposition, including in patients with a cancer for which genetic testing is not recommended. The ability to detect these incidental PGV in cancer patients through liquid biopsy raises important questions regarding the management of this information and its clinical implications. This incidental identification of PGVs raises concerns about cancer predisposition and the potential impact on patient management, not only in terms of providing access to treatment based on the tumor molecular profiling, but also the management of revealing genetic predisposition in patients and families. Understanding how to interpret this information is essential to ensure proper decision-making and to optimize cancer treatment and prevention strategies. In this review we provide a comprehensive summary of current evidence of incidental PGVs in cancer predisposition genes identified by liquid biopsy in patients with cancer. We critically review the methodological considerations of liquid biopsy as a tool for germline diagnosis, clinical utility and potential implications for cancer prevention, treatment, and research.
    DOI:  https://doi.org/10.1038/s41416-024-02607-9
  3. Fam Cancer. 2024 Mar 26.
      Germline genetic sequencing is now at the forefront of cancer treatment and preventative medicine. Cascade genetic testing, or the testing of at-risk relatives, is extremely promising as it offers genetic testing and potentially life-saving risk-reduction strategies to a population exponentially enriched for the risk of carrying a cancer-associated pathogenic variant. However, many relatives do not complete cascade testing due to barriers that span individual, relationship, healthcare community, and societal/policy domains. We have reviewed the published research on cascade testing. Our aim is to evaluate barriers to cascade genetic testing for hereditary cancer syndromes and explore strategies to mitigate these barriers, with the goal of promoting increased uptake of cascade genetic testing.
    Keywords:  Cascade genetic testing; Hereditary cancer syndromes; Predictive testing
    DOI:  https://doi.org/10.1007/s10689-024-00373-4
  4. Genet Med. 2024 Mar 21. pii: S1098-3600(24)00057-1. [Epub ahead of print] 101124
       PURPOSE: Germline variant interpretation often depends on population-matched control cohorts. This is not feasible for population-groups that are underrepresented in current population reference databases.
    METHODS: We classify germline variants with population-matched controls for two ancestrally diverse cohorts of patients: 132 early-onset or familial CRC patients from Singapore (SG), and 100 early-onset CRC patients from the United States (US). The effects of using a population-mismatched control cohort are simulated by swapping the control cohorts used for each patient cohort, with or without the popmax computational strategy.
    RESULTS: Population-matched classifications revealed a combined 62 pathogenic or likely pathogenic (P/LP) variants in 34 genes across both cohorts. Using a population-mismatched control cohort resulted in misclassification of non-P/LP variants as P/LP, driven by the absence of ancestry-specific rare variants in the control cohort. Popmax was more effective in alleviating misclassifications for the SG cohort than the US cohort.
    CONCLUSION: Underrepresented population-groups can suffer from higher rates of false positive P/LP results. Popmax can partially alleviate these misclassifications, but its efficacy still depends on the degree with which the population-groups is represented in the control cohort.
    Keywords:  Germline variants; colorectal carcinoma; popmax; underrepresented populations; variant misclassification
    DOI:  https://doi.org/10.1016/j.gim.2024.101124