Housezimmermann3614
sinensis infection in Korea.The correct identification of filamentous fungi is challenging. We evaluated the performance of the VITEK MS v3.0 system (bioMérieux, Marcy-l'Étoile, France) for the identification of a wide spectrum of clinically relevant filamentous fungi using a Korean collection. Strains that were added to the upgraded v3.2 database were additionally identified by the VITEK MS v3.2 system. Of the 105 tested isolates, including 37 Aspergillus (nine species), 41 dermatophytes (seven species), and 27 other molds (17 species), 43 (41.0%) showed "no identification" or "multiple species identification" results at the initial VITEK MS testing; these isolates were retested using the same method. Compared with sequence-based identification, the correct identification rate using VITEK MS for Aspergillus, dermatophytes, other molds, and total mold isolates was 67.6%, 56.1%, 48.1%, and 58.1% at the initial testing and 94.6%, 78.0%, 55.6%, and 78.1% with retesting, respectively. Following retesting, 19 (18.1%) and two (1.9%) isolates showed "no identification" and "misidentification" results, respectively. VITEK MS reliably identified various filamentous fungi recovered in Korea, with a very low rate of misidentification.
Hereditary leiomyomatosis and renal cell cancer (HLRCC) is an autosomal dominant cancer predisposition syndrome. HLRCC is characterized by the development of cutaneous leiomyomas, early-onset uterine leiomyomas, and HLRCC-associated renal cell cancer (RCC) and caused by germline fumarate hydratase (FH) deficiency. We investigated the genotypic and phenotypic characteristics of Korean patients with HLRCC.
We performed direct sequencing analysis of
in 13 patients with suspected HLRCC and their family members. Selleck Eganelisib A chromosomal microarray test was performed in female patients with negative sequencing results but highly suspected HLRCC. In addition, we analyzed the clinical characteristics and evaluated the genotype-phenotype correlations in Korean patients with HLRCC.
We identified six different pathogenic or likely pathogenic
variants in six of the 13 patients (46.2%). The variants included two nonsense variants, two splicing variants, one frameshift variant, and one missense variant. Of the six variants, two (33.3%) were novel (c.132+1G>C, and c.243dup). RCC and early-onset uterine leiomyoma were frequently observed in families with HLRCC, while cutaneous leiomyoma was less common. No significant genotype-phenotype correlation was observed.
We describe the genotypic and phenotypic spectrum in a small series of Korean patients with HLRCC. Our data reveal the unique characteristics of Korean patients with HLRCC and suggest a need for establishing an optimal diagnostic approach for them.
We describe the genotypic and phenotypic spectrum in a small series of Korean patients with HLRCC. Our data reveal the unique characteristics of Korean patients with HLRCC and suggest a need for establishing an optimal diagnostic approach for them.
Hepatocellular carcinoma (HCC) is the second-most-common cause of cancer-related deaths worldwide, and an accurate and non-invasive biomarker for the early detection and monitoring of HCC is required. We assessed pathogenic variants of HCC driver genes in cell-free DNA (cfDNA) from HCC patients who had not undergone systemic therapy.
Plasma cfDNA was collected from 20 HCC patients, and deep sequencing was performed using a customized cfDNA next-generation sequencing panel, targeting the major HCC driver genes (
,
,
) that incorporates molecular barcoding.
In 13/20 (65%) patients, we identified at least one pathogenic variant of two major HCC driver genes (
and
), including 16 variants of
and nine variants of
. The
and
variants showed low allele frequencies, with median values of 0.17% (range 0.06%-6.99%) and 0.07% (range 0.05%-0.96%), respectively. However, the molecular coverage of variants was sufficient, with median values of 5,543 (range 2,317-9,088) and 7,568 (range 2,400-9,633) for
and
variants, respectively.
Our targeted DNA sequencing successfully identified low-frequency pathogenic variants in the cfDNA from HCC patients by achieving high coverage of unique molecular families. Our results support the utility of cfDNA analysis to identify somatic gene variants in HCC patients.
Our targeted DNA sequencing successfully identified low-frequency pathogenic variants in the cfDNA from HCC patients by achieving high coverage of unique molecular families. Our results support the utility of cfDNA analysis to identify somatic gene variants in HCC patients.
HLA-DQ typing in deceased donors is not mandatory in Korea. Therefore, when patients develop DQ antibodies after kidney transplantation (KT) from deceased donor, it is impossible to determine whether they are donor-specific antibodies (DSA). We developed DQ prediction programs for the HLA gene and evaluated their clinical utility.
Two HLA-DQ prediction programs were developed one based on Lewontin's linkage disequilibrium (LD) and haplotype frequency and the other on an artificial neural network (ANN). Low-resolution HLA-A, -B, -DR, and -DQ typing data of 5,603 Korean patients were analyzed in terms of haplotype frequency and used to develop an ANN DQ prediction program. Predicted DQ (pDQ) genotype accuracy was analyzed using the typed DQ data of 403 patients. pDQ DSA agreement, sensitivity, specificity, and false-negative rate was evaluated using 1,970 single-antigen bead assays performed on 885 KT recipients. The clinical significance of DQ and pDQ DSA was evaluated in 411 KT recipients.
pDQ genotype accuracies were 75.4% (LD algorithm) and 75.7% (ANN). When the second most likely pDQ (LD algorithm) was also considered, the genotype accuracy increased to 92.6%. pDQ DSA (LD algorithm) agreement, sensitivity, specificity, and false-negative rate were 97.5%, 97.3%, 98.6%, and 2.4%, respectively. The antibody-mediated rejection treatment frequency was significantly higher in DQ or pDQ DSA-positive patients than in DQ or pDQ DSA-negative patients (
<0.001).
Our DQ prediction programs showed good accuracy and could aid DQ DSA detection in patients who had undergone deceased donor KT without donor HLA-DQ typing.
Our DQ prediction programs showed good accuracy and could aid DQ DSA detection in patients who had undergone deceased donor KT without donor HLA-DQ typing.
