scholarly journals Establishing the Mutational Spectrum of Hungarian Patients with Familial Hypercholesterolemia

Genes ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 153
Author(s):  
László Madar ◽  
Lilla Juhász ◽  
Zsuzsanna Szűcs ◽  
Lóránt Kerkovits ◽  
Mariann Harangi ◽  
...  

Familial hypercholesterolemia (FH) is one of the most common autosomal, dominantly inherited diseases affecting cholesterol metabolism, which, in the absence of treatment, leads to the development of cardiovascular complications. The disease is still underdiagnosed, even though an early diagnosis would be of great importance for the patient to receive proper treatment and to prevent further complications. No studies are available describing the genetic background of Hungarian FH patients. In this work, we present the clinical and molecular data of 44 unrelated individuals with suspected FH. Sequencing of five FH-causing genes (LDLR, APOB, PCSK9, LDLRAP1 and STAP1) has been performed by next-generation sequencing (NGS). In cases where a copy number variation (CNV) has been detected by NGS, confirmation by multiplex ligation-dependent probe amplification (MLPA) has also been performed. We identified 47 causal or potentially causal (including variants of uncertain significance) LDLR and APOB variants in 44 index patients. The most common variant in the APOB gene was the c.10580G>A p.(Arg3527Gln) missense alteration, this being in accordance with literature data. Several missense variants in the LDLR gene were detected in more than one index patient. LDLR variants in the Hungarian population largely overlap with variants detected in neighboring countries.

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 206
Author(s):  
Matteo Giulietti ◽  
Monia Cecati ◽  
Berina Sabanovic ◽  
Andrea Scirè ◽  
Alessia Cimadamore ◽  
...  

The increasing availability of molecular data provided by next-generation sequencing (NGS) techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal cancer. Reliable and accurate predictors based on selected gene panels are urgently needed for better stratification of renal cell carcinoma (RCC) patients in order to define a personalized treatment plan. Artificial intelligence (AI) algorithms are currently in development for this purpose. Here, we reviewed studies that developed predictors based on AI algorithms for diagnosis and prognosis in renal cancer and we compared them with non-AI-based predictors. Comparing study results, it emerges that the AI prediction performance is good and slightly better than non-AI-based ones. However, there have been only minor improvements in AI predictors in terms of accuracy and the area under the receiver operating curve (AUC) over the last decade and the number of genes used had little influence on these indices. Furthermore, we highlight that different studies having the same goal obtain similar performance despite the fact they use different discriminating genes. This is surprising because genes related to the diagnosis or prognosis are expected to be tumor-specific and independent of selection methods and algorithms. The performance of these predictors will be better with the improvement in the learning methods, as the number of cases increases and by using different types of input data (e.g., non-coding RNAs, proteomic and metabolic). This will allow for more precise identification, classification and staging of cancerous lesions which will be less affected by interpathologist variability.


2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 287-287
Author(s):  
Ari M. Vanderwalde ◽  
Esprit Ma ◽  
Elaine Yu ◽  
Tania Szado ◽  
Richard Price ◽  
...  

287 Background: Recent approvals of targeted treatments (tx) have improved personalized care in aNSCLC. Biomarker testing is crucial for patients (pts) to receive optimal tx expeditiously. This study examined aNSCLC biomarker testing and tx patterns at OneOnc. Methods: Pts diagnosed with aNSCLC (stage ≥ IIIb) from 1/1/2015 to 5/31/2020, aged ≥ 18 years, and with ≥ 1 visit ≤ 90 days of advanced (Adv) diagnosis (Dx) were retrospectively evaluated using the nationwide Flatiron Health electronic health record derived de-identified database from selected OneOnc sites. Descriptive analyses were conducted to evaluate testing patterns for ALK, BRAF, EGFR, KRAS, PD-L1, and ROS-1 biomarkers and actionable mutation tx pattern. Results: Overall 3,860 aNSCLC pts were included, median age was 69 years, 47% females, 66% non-squamous, 29% squamous, 4% histology NOS, and 23% with ECOG performance status 0-1. Of the 3,152 (82%) pts tested for any biomarker, 64% received next-generation sequencing (NGS) vs. 36% received other biomarker tests only. Testing rates varied by biomarker: EGFR (74%), ALK (72%), ROS-1 (66%), PD-L1 (57%), BRAF (56%), KRAS (54%). Pts who received all 6 biomarker tests increased from 12% (2015), 23% (2016), 40% (2017), 41% (2018), 48% (2019) to 56% (2020). Among the tested pts, the median time from Adv Dx to the first test result was 20 days (d) and from specimen collection after Adv Dx to the first test result was 12 d. Pts tested and treated before test result available declined from 28% (2015) to 16% (2020). Of 1,207 pts with actionable mutations, 390 (32%) received tx before the test result: 35% chemotherapy (chemo) only, 28% chemo + cancer immunotherapy (CIT), and 15% CIT only. After the test result, 26% to 81% of pts received no or other tx not specific to actionable mutations [Table]. Conclusions: Findings from this study demonstrated an increase in aNSCLC biomarker testing at OneOnc over time, while 44% pts in 2020 did not receive testing on all 6 biomarkers. Some pts had tx prior to the test result, but this trend appeared to decline. Further studies are warranted to better understand the reasons for pts receiving tx that were not specific to their actionable mutations.[Table: see text]


2018 ◽  
Vol 275 ◽  
pp. e79
Author(s):  
M. Iacocca ◽  
J. Wang ◽  
J. Dron ◽  
H. Cao ◽  
J. Robinson ◽  
...  

2017 ◽  
Vol 58 (11) ◽  
pp. 2202-2209 ◽  
Author(s):  
Michael A. Iacocca ◽  
Jian Wang ◽  
Jacqueline S. Dron ◽  
John F. Robinson ◽  
Adam D. McIntyre ◽  
...  

2022 ◽  
Vol 17 (4) ◽  
pp. 74-78
Author(s):  
N. G. Lozhkina ◽  
A. N. Spiridonov

Familial hypercholesterolemia is a hereditary autosomal dominant disease characterized by a violation of cholesterol metabolism. This nosology was first described in the late 1930s by the Norwegian clinician Karl Moeller, he proposed the idea that hypercholesterolemia and tendon xanthomas are associated with cardiovascular diseases through the inheritance of a single gene. In 1964, two clinical phenotypes of familial hypercholesterolemia were discovered: heterozygous and homozygous, associated with an unfavorable prognosis. To date, it is known that the long-running process of accumulation of low-density lipoproteins in the intima of blood vessels may not have clinical symptoms for many years due to the developed system of collaterals and the absence of hemodynamically significant stenosis. However, without timely diagnosis and appropriate therapy, this condition inevitably leads to the development of a cardiovascular event. The article presents a clinical case demonstrating the development of myocardial infarction in a patient with a late diagnosis of this disease.


2017 ◽  
Vol 49 (12) ◽  
pp. 951-956 ◽  
Author(s):  
Kei Omata ◽  
Scott Tomlins ◽  
William Rainey

AbstractPrimary aldosteronism (PA) significantly increases the risk of cardiovascular complications, and early diagnosis and targeted treatment based on its pathophysiology is warranted. Next-generation sequencing (NGS) has revealed recurrent somatic mutations in aldosterone-driving genes in aldosterone-producing adenoma (APA). By applying CYP11B2 (aldosterone synthase) immunohistochemistry and NGS to adrenal glands from normal subjects and PA patients, we and others have shown that CYP11B2-positive cells make small clusters, termed aldosterone-producing cell clusters (APCC), beneath the adrenal capsule, and that APCC harbor somatic mutations in genes mutated in APA. We have shown that APCC are increased in CT-negative PA adrenals, while others showed potential progression from APCC to micro APA through mutations. These results suggest that APCC are a key factor for understanding the origin of PA, and further investigation on the relation between APCC and PA is highly needed.


2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 623-623
Author(s):  
Afsaneh Barzi ◽  
Mohamed E. Salem ◽  
Joanne Xiu ◽  
Wolfgang Michael Korn ◽  
John Marshall ◽  
...  

623 Background: Females (F) have a lower incidence of CRC and carry a better overall prognosis than males(M). We explored the differences in the molecular profile of CRC as an explanation for the differences in the outcome. Methods: CRC cases submitted to Caris Life Sciences from 2015 to 2017 were analyzed. These cases were tested with next generation sequencing (NGS) of 592 genes and a panel of IHC and copy number variation assessment. Microsatellite instability (MSI) was evaluated with NGS for known MSI loci in the target regions. High Tumor mutational load (TML-H) was defined as ≥17 mutations/megabase. Results: Data from a total of 1768 CRC tumors (F: 859; M: 909) was available for analysis. The mean age at testing was similar between the two groups (F 59 vs. M 60 years). Tumor location was unknown in more than 40% of the cases. For those with known tumor location (1056) F had a higher rate in right sided than left sided and rectal tumors (51% vs. 47% vs. 40%, p = 0.006). Overall, F carried significantly lower frequency of mutation in APC (68% vs. 74%, p = 0.02), higher frequency of BRAF (11% vs. 6.6%, p = 0.003) and BRCA1 (2% vs. 0.6%, p = 0.007). PDL1 expression was higher in F (4.5% vs. 2.1%, p = 0.006) and MGMT expression was higher in M (63% vs. 56%, p = 0.04). There was no significant difference in the TML-H (F:6.4% vs. M:5.9%) and MSI-high (F:6.2% in vs M:4.8%). When primary (877) and metastatic tumors (838) were investigated separately, mutations in APC was higher in M primary tumors (74% vs. 68% p = 0.03) while not different in metastatic sites. On the contrary, BRCA1 mutations were higher in the metastatic sites for F (2% vs. 0.2%, p = 0.02). PD-L1 was higher in the primary tumor of F (5.2% vs. 1.8%, p = 0.008) and PD-1 on tumor infiltrating lymphocyte in metastatic tumors in F (48% vs. 30%, p = 0.01). Conclusions: The profile of female patients (higher rates of PDL1 in primary and PD1 in metastatic tumors) supports a higher degree of immune evasion. The differences in the profile of metastatic vs. primary sites may be due to the differences in the mechanism of metastasis in females vs. males and may have implications for PDX models.


2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 565-565
Author(s):  
Lesli Ann Kiedrowski ◽  
Roby Antony Thomas ◽  
Nicholas J. Vogelzang ◽  
Guru Sonpavde ◽  
Sumati Gupta ◽  
...  

565 Background: Erdafitinib is approved in pts with aUC with relevant FGFR2/3 GA. BLC2001 trials in pts with activating FGFR2/3 mutations reported 40% ORR to erdafitinib (49% for those with single nucleotide variants [SNVs] and 16% with fusions), 39% stable disease rate, and potentially reduced response to anti-PD-L1. Genomic profiling with plasma cfDNA next-generation sequencing (NGS) is increasingly used to identify targetable GA in pts with advanced solid tumors and presents a minimally invasive option for identification of FGFR2/3 GA. Methods: Genomic data from the Guardant360 database were queried from clinical results released from 10/19/15 - 8/28/19 for clinical samples submitted with diagnoses of aUC or related diagnoses (e.g. bladder cancer, renal pelvis carcinoma). All assays included FGFR2/3 fusions and complete sequencing of all critical exons harboring sensitizing FGFR2/3 SNVs. Results: 1349 results from 1096 unique pts were identified. Somatic GA were identified in 1192 tests (88%) from 997 pts. Fusions and/or nonsynonymous SNVs in FGFR2/3 were identified in 201 pts (20%); 141 pts (14%) had at least one characterized activating FGFR2/3 GA. Of 34 pts (3.4%) with FGFR3 fusions, partners included TACC3 (32), JAKMIP1 (1), and TNIP2 (1). Overall, most SNVs identified in FGFR3 were predicted to be activating (103/125, 82%) whereas in FGFR2 most were variants of uncertain significance (VUS; 62/72, 86%). Of 89 unique variants (59 in FGFR2, 30 in FGFR3), 19 (21%) were activating mutations (7 in FGFR2, 12 in FGFR3). The most common activating SNVs in FGFR3 were S249C (58 pts), Y373C (20) and R248C (10), and in FGFR2 was N549K (4). VUS in both genes were individually uncommon (no VUS recurring in >3 pts). Median copy number-adjusted clonality of SNVs in FGFR3 was higher than those in FGFR2 (0.80 vs 0.20); this remained true when limiting to only characterized activating mutations (0.84 vs 0.17). Conclusions: cfDNA NGS analysis identifies fusions and a broad spectrum of SNVs in FGFR2/3, including heterogeneous subclonal mutations, at a rate similar to reported tissue testing. cfDNA is a minimally invasive option for pts with aUC to assess candidacy for erdafitinib and clinical trials.


Sign in / Sign up

Export Citation Format

Share Document