TY - JOUR

T1 - Lynch syndrome, molecular mechanisms and variant classification

AU - Abildgaard, Amanda B.

AU - Nielsen, Sofie

AU - Bernstein, Inge

AU - Stein, Amelie

AU - Lindorff-Larsen, Kresten

AU - Hartmann-Petersen, Rasmus

PY - 2023

Y1 - 2023

N2 - Patients with the heritable cancer disease, Lynch syndrome, carry germline variants in the MLH1, MSH2, MSH6 and PMS2 genes, encoding the central components of the DNA mismatch repair system. Loss-of-function variants disrupt the DNA mismatch repair system and give rise to a detrimental increase in the cellular mutational burden and cancer development. The treatment prospects for Lynch syndrome rely heavily on early diagnosis; however, accurate diagnosis is inextricably linked to correct clinical interpretation of individual variants. Protein variant classification traditionally relies on cumulative information from occurrence in patients, as well as experimental testing of the individual variants. The complexity of variant classification is due to (1) that variants of unknown significance are rare in the population and phenotypic information on the specific variants is missing, and (2) that individual variant testing is challenging, costly and slow. Here, we summarise recent developments in high-throughput technologies and computational prediction tools for the assessment of variants of unknown significance in Lynch syndrome. These approaches may vastly increase the number of interpretable variants and could also provide important mechanistic insights into the disease. These insights may in turn pave the road towards developing personalised treatment approaches for Lynch syndrome.

AB - Patients with the heritable cancer disease, Lynch syndrome, carry germline variants in the MLH1, MSH2, MSH6 and PMS2 genes, encoding the central components of the DNA mismatch repair system. Loss-of-function variants disrupt the DNA mismatch repair system and give rise to a detrimental increase in the cellular mutational burden and cancer development. The treatment prospects for Lynch syndrome rely heavily on early diagnosis; however, accurate diagnosis is inextricably linked to correct clinical interpretation of individual variants. Protein variant classification traditionally relies on cumulative information from occurrence in patients, as well as experimental testing of the individual variants. The complexity of variant classification is due to (1) that variants of unknown significance are rare in the population and phenotypic information on the specific variants is missing, and (2) that individual variant testing is challenging, costly and slow. Here, we summarise recent developments in high-throughput technologies and computational prediction tools for the assessment of variants of unknown significance in Lynch syndrome. These approaches may vastly increase the number of interpretable variants and could also provide important mechanistic insights into the disease. These insights may in turn pave the road towards developing personalised treatment approaches for Lynch syndrome.

KW - NONPOLYPOSIS COLORECTAL-CANCER

KW - SUSCEPTIBILITY GENE-MUTATIONS

KW - AMINO-ACID SUBSTITUTIONS

KW - MISMATCH-REPAIR

KW - MICROSATELLITE INSTABILITY

KW - FUNCTIONAL-ANALYSIS

KW - MISSENSE VARIANTS

KW - PROTEIN FUNCTION

KW - QUALITY-CONTROL

KW - HMUTS-ALPHA

U2 - 10.1038/s41416-022-02059-z

DO - 10.1038/s41416-022-02059-z

M3 - Review

C2 - 36434153

VL - 128

JO - The British journal of cancer. Supplement

JF - The British journal of cancer. Supplement

SN - 0007-0920

ER -