Classification of MSH6 Variants of Uncertain Significance Using Functional Assays

Using metabolic abnormalities of carriers in the neonatal period to evaluate the pathogenicity of variants of uncertain significance in methylmalonic acidemia

Objective

To accurately verify the pathogenicity of variants of uncertain significance (VUS) in MUT and MMACHC genes through mass spectrometry and silico analysis.

Methods

This multicenter retrospective study included 35 participating units (ClinicalTrials.gov ID: NCT06183138). A total of 3,071 newborns (within 7 days of birth) were sorted into carrying pathogenic/likely pathogenic (P/LP) variants and carrying VUS, non-variant groups. Differences in metabolites among the groups were calculated using statistical analyses. Changes in conservatism, free energy, and interaction force of MMUT and MMACHC variants were analyzed using silico analysis.

Results

The percentage of those carrying VUS cases was 68.15% (659/967). In the MMUT gene variant, we found that C3, C3/C2, and C3/C0 levels in those carrying the P/LP variant group were higher than those in the non-variant group (p < 0.000). The conservative scores of those carrying the P/LP variant group were >7. C3, C3/C0, and C3/C2 values of newborns carrying VUS (c.1159A>C and c.1286A>G) were significantly higher than those of the non-variant group and the remaining VUS newborns (p < 0.005). The conservative scores of c.1159A>C and c.1286A>G calculated by ConSurf analysis were 9 and 7, respectively. Unfortunately, three MMA patients with c.1159A>C died during the neonatal period; their C3, C3/C0, C3/C2, and MMA levels were significantly higher than those of the controls.

Conclusion

Common variants of methylmalonic acidemia in the study population were categorized as VUS. In the neonatal period, the metabolic biomarkers of those carrying the P/LP variant group of the MUT gene were significantly higher than those in the non-variant group. If the metabolic biomarkers of those carrying VUS are also significantly increased, combined with silico analysis the VUS may be elevated to a likely pathogenic variant. The results also suggest that mass spectrometry and silico analysis may be feasible screening methods for verifying the pathogenicity of VUS in other inherited metabolic diseases.

High-throughput assays to assess variant effects on disease

Interpreting the wealth of rare genetic variants discovered in population-scale sequencing efforts and deciphering their associations with human health and disease present a critical challenge due to the lack of sufficient clinical case reports. One promising avenue to overcome this problem is deep mutational scanning (DMS), a method of introducing and evaluating large-scale genetic variants in model cell lines. DMS allows unbiased investigation of variants, including those that are not found in clinical reports, thus improving rare disease diagnostics. Currently, the main obstacle limiting the full potential of DMS is the availability of functional assays that are specific to disease mechanisms. Thus, we explore high-throughput functional methodologies suitable to examine broad disease mechanisms. We specifically focus on methods that do not require robotics or automation but instead use well-designed molecular tools to transform biological mechanisms into easily detectable signals, such as cell survival rate, fluorescence or drug resistance. Here, we aim to bridge the gap between disease-relevant assays and their integration into the DMS framework.

Molecular profiling of pre- and post-treatment pediatric high-grade astrocytomas reveals acquired increased tumor mutation burden in a subset of recurrences

Diffuse gliomas are a heterogeneous category of primary central nervous system tumors. Due to their infiltrative growth precluding complete surgical resection, most diffuse high-grade gliomas are treated with adjuvant chemotherapy and radiation. Recurrent/progressive diffuse gliomas may show genetic differences when compared to the primary tumors, giving insight into their molecular evolution and mechanisms of treatment resistance. In adult-type diffuse gliomas with or without isocitrate dehydrogenase gene mutations, tumor recurrence/progression can be associated with mutations in genes encoding DNA mismatch repair proteins, leading to a dramatic increase in tumor mutation burden. This phenomenon is closely linked to treatment with the DNA alkylating agent temozolomide, a mainstay of adult diffuse glioma chemotherapeutic management. Post-treatment mismatch repair deficiency and acquired high tumor mutation burden is relatively unexplored in pediatric patients who have recurrent high-grade gliomas. Here, we report a molecular and histological analysis of an institutional cohort of eleven pediatric patients with paired initial and recurrent high-grade astrocytoma samples with intervening temozolomide treatment. We identified three cases with evidence for increased tumor mutation burden at recurrence, including two cases of diffuse hemispheric glioma H3 G34-mutant (one previously reported). We also show that molecular analysis by next-generation DNA sequencing and DNA methylation-based profiling enabled an integrated diagnosis per 2021 World Health Organization criteria in 10 of 11 cases (91%). Our findings indicate that increased tumor mutation burden at post-treatment recurrence is relevant in pediatric-type diffuse high-grade gliomas. Diffuse hemispheric glioma H3 G34-mutant may be particularly susceptible to this phenomenon.

PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype Ontology data analysis to quantify phenotypic similarity. Here we show PhenoScore's ability to recognize distinct phenotypic entities by establishing recognizable phenotypes for 37 of 40 investigated syndromes against clinical features observed in individuals with other neurodevelopmental disorders and show it is an improvement on existing approaches. PhenoScore provides predictions for individuals with variants of unknown significance and enables sophisticated genotype-phenotype studies by testing hypotheses on possible phenotypic (sub)groups. PhenoScore confirmed previously known phenotypic subgroups caused by variants in the same gene for SATB1, SETBP1 and DEAF1 and provides objective clinical evidence for two distinct ADNP-related phenotypes, already established functionally.

Estimating clinical risk in gene regions from population sequencing cohort data

While pathogenic variants can significantly increase disease risk, it is still challenging to estimate the clinical impact of rare missense variants more generally. Even in genes such as BRCA2 or PALB2, large cohort studies find no significant association between breast cancer and rare missense variants collectively. Here, we introduce REGatta, a method to estimate clinical risk from variants in smaller segments of individual genes. We first define these regions by using the density of pathogenic diagnostic reports and then calculate the relative risk in each region by using over 200,000 exome sequences in the UK Biobank. We apply this method in 13 genes with established roles across several monogenic disorders. In genes with no significant difference at the gene level, this approach significantly separates disease risk for individuals with rare missense variants at higher or lower risk (BRCA2 regional model OR = 1.46 [1.12, 1.79], p = 0.0036 vs. BRCA2 gene model OR = 0.96 [0.85, 1.07] p = 0.4171). We find high concordance between these regional risk estimates and high-throughput functional assays of variant impact. We compare our method with existing methods and the use of protein domains (Pfam) as regions and find REGatta better identifies individuals at elevated or reduced risk. These regions provide useful priors and are potentially useful for improving risk assessment for genes associated with monogenic diseases.

The performance of multi-gene panels for breast/ovarian cancer predisposition

BRCA1 and BRCA2 are the most mutated genes in breast cancer. We analyzed 48 breast cancer subjects using two methods that differ in terms of number of genes investigated and strategy used (primers: Panel A - 12 genes - vs probes: Panel B - 48 genes). Both the panels and procedures identified "pathogenic" or "likely pathogenic" variants in TP53, ATM, CHEK2 and BARD1 besides BRCA1 and BRCA2. Panel B identified two other putatively pathogenic variants in RNASEL and in RAD50. Identification of variants other than the BRCA genes can be useful in patient management. A total of 121 variants were distributed within the 12 genes and were correctly detected by both panels. However, the number of calls without divergence, namely ± 0.10 difference of allelic frequency, was 78.3%, while calls with a divergence below 0.10 was 16.7%, thus indicating that only 5% (n = 275) of 5,412 calls had a divergence above 0.10. Although these panels differ from each other, both are useful in different situations, particularly when patients should be tested for genes other than BRCA1/2 (as occurs in patients affected by a so called hereditary syndrome) or for therapeutic purposes.

Estimating clinical risk in gene regions from population sequencing cohort data

While pathogenic variants significantly increase disease risk in many genes, it is still challenging to estimate the clinical impact of rare missense variants more generally. Even in genes such as BRCA2 or PALB2 , large cohort studies find no significant association between breast cancer and rare germline missense variants collectively. Here we introduce REGatta, a method to improve the estimation of clinical risk in gene segments. We define gene regions using the density of pathogenic diagnostic reports, and then calculate the relative risk in each of these regions using 109,581 exome sequences from women in the UK Biobank. We apply this method in seven established breast cancer genes, and identify regions in each gene with statistically significant differences in breast cancer incidence for rare missense carriers. Even in genes with no significant difference at the gene level, this approach significantly separates rare missense variant carriers at higher or lower risk ( BRCA2 regional model OR=1.46 [1.12, 1.79], p=0.0036 vs. BRCA2 gene model OR=0.96 [0.85,1.07] p=0.4171). We find high concordance between these regional risk estimates and high-throughput functional assays of variant impact. We compare with existing methods and the use of protein domains (Pfam) as regions, and find REGatta better identifies individuals at elevated or reduced risk. These regions provide useful priors which can potentially be used to improve risk assessment and clinical management.

Germline variants screening of MLH1, MSH2, MSH6 and PMS2 genes in 64 Algerian Lynch syndrome families: The first nationwide study

Colorectal cancer is the second leading cause of cancer-related deaths in women and men in Algeria. Lynch syndrome (LS) is an autosomal dominant disease caused by heterozygous germline pathogenic variants in mismatch repair genes (MMR) and frequently predisposes to colorectal cancer. However, data about MMR germline pathogenic variants in Algerian patients are limited. This first nationwide study aims to describe clinicopathologic features and germline variants in MMR genes in Algerian families with suspected LS. Sixty-four (64) families with suspected LS were studied. Index cases with LS who fulfilled Amsterdam criteria were screened by PCR-direct sequencing for germline variants in MMR genes: MLH1 (exons 1, 9, 10, 13, 16), MSH2 (exons 5, 6, 7, 12), MSH6 (exons 4 and 8) and PMS2 (exons 6 and 10). We selected these specific risk exons genes since they have a higher probability of harboring pathogenic variants. In addition, two unrelated LS patients were screened by next-generation sequencing using a cancer panel of 30 hereditary cancer genes. Six germline pathogenic variants and one germline likely pathogenic variant were identified in 19 (29.68%) families (4 MLH1, 2 MSH2 and 1 MSH6). Of index cases and relatives who underwent genetic testing (n = 76), 30 (39.47%) had MMR pathogenic gene variants, one (0.13%) had MMR gene likely pathogenic variant and three had MMR variant of uncertain significance, respectively. Two novel germline pathogenic variants in MLH1 (2) and one germline likely pathogenic variant in MSH6 (1) never published in individuals with LS have been detected in the present study. The recurrent MLH1 germline pathogenic variant c.1546C>T has been found in nine LS families, six of them related with two large kindreds, from four North central provinces of Algeria. In addition, the common MSH2 germline pathogenic variant c.942+3A>T has been detected in five unrelated patients with a strong LS family history. The accumulative knowledge about clinicopathological and genetic characteristics of LS in Algerian patients will impact clinical management in the areas of both prevention and treatment.

Inflammatory leiomyosarcoma/rhabdomyoblastic tumor: a report of two cases with novel genetic findings

Inflammatory leiomyosarcoma (ILMS) is a malignant neoplasm showing smooth muscle differentiation, a prominent inflammatory infiltrate, and near‐haploidization. These tumors have significant pathologic and genetic overlap with the recently described “inflammatory rhabdomyoblastic tumor (IRT),” suggesting that ILMS and IRT may belong to one entity. Herein, we describe two cases of ILMS/IRT with attention to new cytogenetic and sequencing findings. The tumors were composed of sheets and fascicles of variably pleomorphic tumor cells showing spindled and epithelioid to rhabdoid morphology and a prominent histiocyte‐rich inflammatory infiltrate typical of ILMS/IRT. In case 1, chromosomal microarray analysis showed a near‐haploid pattern with loss of heterozygosity resulting from loss of one copy of all autosomes except for chromosomes 5, 20, 21, and 22. Case 2 showed areas with high‐grade rhabdomyosarcomatous transformation. In this case, the low‐grade tumor component revealed a hyper‐diploid pattern with loss of heterozygosity for most of autosomes but with a normal diploid copy number state except for chromosomes 5, 20, and 22, which showed a relative gain. The high‐grade tumor component showed a similar pattern of copy‐neutral loss of heterozygosity with additional abnormalities, including mosaic segmental gains at 1p, 5p, 8q, 9p, 20q, and segmental loss at 8p. Next‐generation sequencing identified sequence variants in NF1, TP53, SMARCA4, KRAS, and MSH6. MSH6 variant was confirmed as germline, consistent with the diagnosis of hereditary nonpolyposis colorectal cancer (HNPCC) syndrome in one of our study patients and suggestive that ILMS/IRT might be part of the HNPCC cancer spectrum.