Adult granulosa cell tumors (AGCTs) of the ovary are characterized by their propensity for late recurrences and are primarily managed surgically due to the limited efficacy of systemic treatment. The FOXL2 p.C134W somatic mutation has been identified in ∼95% of AGCT cases, and TERT promoter alterations have been linked to worse overall survival. This study highlights the potential prognostic significance of FOXO1 mutations, suggesting that they may be associated with poorer overall survival and shorter time to recurrence. A total of 183 primary AGCTs and 44 recurrences without corresponding primary tumors were analyzed. The primary AGCTs were categorized into 3 groups: 77 nonrecurrent tumors, 18 tumors that later recurred (including 9 cases with matched primary-recurrence pairs), and 88 tumors with unknown recurrence status. Targeted next-generation sequencing was conducted on 786 cancer-related genes to investigate their genetic profile. The study aimed to identify the molecular alterations associated with AGCT pathogenesis and recurrence rate, comparing primary versus recurrent tumors, and primary recurrent versus primary nonrecurrent cases. Our findings confirmed the high prevalence (99%) of the FOXL2 p.C134W mutation in AGCTs. Secondary truncating FOXL2 mutations were observed in 5% of cases. Two cases with typical AGCT morphology were FOXL2 wild-type, harboring mutations in KRAS or KMT2D instead, suggesting alternative genetic pathways. TERT promoter mutations were found in 43% of cases, more frequently in recurrences. Other recurrent mutations detected in the cohort included KMT2D (10%), FOXO1 (7%), CHEK2 (5%), TP53 (3.5%), PIK3CA (3.5%), and AKT1 (3%). Two recurrent, FOXL2-mutated cases also carried DICER1 mutations. One tumor exhibited MSI-high status and a tumor mutation burden of 19 mut/Mb.Our results indicate the need for further investigation into the role of FOXO1 as a potential prognostic marker in AGCTs.

• MeSH
• Adult MeSH
• Forkhead Box Protein O1 * genetics   metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Neoplasm Recurrence, Local * genetics   MeSH
• Mutation * MeSH
• Granulosa Cell Tumor * genetics   pathology   MeSH
• Ovarian Neoplasms * genetics   pathology   MeSH
• Prognosis MeSH
• Disease Progression MeSH
• Forkhead Box Protein L2 genetics   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Telomerase genetics   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Endometrial carcinomas (EC) of no special molecular profile (NSMP) represent the largest molecular category of EC, comprising a mixture of tumors with different histology and molecular profiles. These facts likely point to different tumor biology, clinical outcomes, and targeted therapy responses within this molecular category. The PIK3CA is currently the only targetable kinase oncoprotein directly implicated in EC carcinogenesis. Investigating a unique single-institution cohort, we attempted to stratify NSMP ECs based on the presence of the PIK3CA pathogenic mutation. Those cases were further analyzed for other well-established-associated oncogenic driver gene mutations. Histological and clinical variables were also correlated in each case. Altogether, 175 ECs were prospectively tested by a limited custom NGS panel containing ARID1A, BCOR, BRCA1, BRCA2, CTNNB1, KRAS, MLH1, MSH2, MSH6, NRAS, PIK3CA, PMS2, POLD1, POLE, PTEN,and TP53 genes. We identified 24 PIK3CA mutated cases in the group of 80 NSMP ECs, with another co-occurring mutation in at least one oncogenic driver gene (CTNNB1, PTEN, ARID1A, KRAS, BCOR, PMS2) in 19 cases. In conclusion, a limited NGS panel can effectively test EC tissue for specific pathogenetically relevant oncogene mutations. The NSMP EC category contains 30% of the PIK3CA mutated cases. Of those, 21% contain the PIK3CA mutation as a sole EC-associated oncogene mutation, while 79% harbor at least one more mutated gene. These findings may inform future healthcare planning and improve the effectiveness of EC patient selection for the PIK3CA-targeted therapy.

• MeSH
• Molecular Targeted Therapy MeSH
• Adult MeSH
• Class I Phosphatidylinositol 3-Kinases * genetics   antagonists & inhibitors   MeSH
• Middle Aged MeSH
• Humans MeSH
• Mutation MeSH
• DNA Mutational Analysis MeSH
• Biomarkers, Tumor * genetics   MeSH
• Endometrial Neoplasms * genetics   pathology   drug therapy   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Patient Selection MeSH
• High-Throughput Nucleotide Sequencing * methods   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Základem léčby pokročilého karcinomu prostaty je hormonální terapie, která ale u pacientů s mutacemi v genech pro opravy DNA ztrácí účinnost. Tyto mutace se vyskytují u téměř 30 % pacientů s diseminovaným karcinomem prostaty; nejčastěji se jedná o mutace v genech BRCA. Pomocí sekvenování nové generace jsme schopni tyto pacienty identifikovat a nabídnout jim účinnou cílenou léčbu inhibitory poly(adenosindifosfát-ribóza) polymerázy (PARP). Článek popisuje mechanismus účinku PARP inhibitorů, zaměřuje se na významné klinické studie s olaparibem, na jeho přínosy a nežádoucí účinky.

Hormone therapy is the cornerstone of treatment for advanced prostate cancer. However, it loses effectiveness in patients with mutations in DNA repair genes. These mutations are found in nearly 30% of patients with disseminated disease, the most common are BRCA mutations. Using next generation sequencing (NGS) testing, we can identify these patients and offer them effective targeted treatment with poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors. This article describes the mechanism of action of PARP inhibitors, focusing on key clinical trials involving olaparib, along with its benefits and side effects.

BACKGROUND: Only a limited number of biomarkers guide personalized management of pancreatic neuroendocrine tumors (PanNETs). Transcriptome profiling of microRNA (miRs) and mRNA has shown value in segregating PanNETs and identifying patients more likely to respond to treatment. Because miRs are key regulators of mRNA expression, we sought to integrate expression data from both RNA species into miR-mRNA interaction networks to advance our understanding of PanNET biology. METHODS: We used deep miR/mRNA sequencing on six low-grade/high-risk, well-differentiated PanNETs compared with seven non-diseased tissues to identify differentially expressed miRs/mRNAs. Then we crossed a list of differentially expressed mRNAs with a list of in silico predicted mRNA targets of the most and least abundant miRs to generate high probability miR-mRNA interaction networks. RESULTS: Gene ontology and pathway analyses revealed several miR-mRNA pairs implicated in cellular processes and pathways suggesting perturbed neuroendocrine function (miR-7 and Reg family genes), cell adhesion (miR-216 family and NLGN1, NCAM1, and CNTN1; miR-670 and the claudins, CLDN1 and CLDN2), and metabolic processes (miR-670 and BCAT1/MPST; miR-129 and CTH). CONCLUSION: These novel miR-mRNA interaction networks identified dysregulated pathways not observed when assessing mRNA alone and provide a foundation for further investigation of their utility as diagnostic and predictive biomarkers.

• MeSH
• Gene Regulatory Networks MeSH
• Middle Aged MeSH
• Humans MeSH
• RNA, Messenger * genetics   MeSH
• MicroRNAs * genetics   MeSH
• Biomarkers, Tumor genetics   MeSH
• Pancreatic Neoplasms * genetics   pathology   diagnosis   MeSH
• Neuroendocrine Tumors * genetics   pathology   diagnosis   MeSH
• Pancreas * metabolism   pathology   MeSH
• Gene Expression Regulation, Neoplastic MeSH
• Gene Expression Profiling MeSH
• Transcriptome MeSH
• High-Throughput Nucleotide Sequencing methods   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

INTRODUCTION: Human and animal skin is colonized by a complex microbial population. An imbalance of these microorganisms is often associated with dermatological diseases. METHODS: The aim of this work was to describe the skin bacterial microbiota composition of healthy dogs and dogs with inflammatory skin lesions. Genomic DNA was sequenced using primers that target the V4 region of the bacterial 16S rRNA gene. Superficial skin swabs were collected from eight body areas of six healthy dogs (n = 48) and directly from inflammatory altered canine skin (n = 16). RESULTS: The skin of healthy dogs was predominantly colonized by phylum Bacillota (34.4 ± 27.2%), followed by Actinomycetota (32.2 ± 20.3%), Pseudomonadota (16.4 ± 12.2%), and Bacteroidota (8.7 ± 11.6%). At the level of genera, Streptococcus spp. (19.4 ± 26.1%) was the most abundant genus across all samples collected from healthy skin, followed by Curtobacterium (5.4 ± 12.1%), Bacteroides (5.2 ± 11.1%) and Corynebacterium_1 (4.3 ± 13.2%). More specifically, Streptococcus spp. was the most abundant on the chin (49.0 ± 35.5%), nose (37.9 ± 32.1%), perianal region (21.1 ± 28.2%), abdomen (11.0 ± 12.8%), dorsal back (12.4 ± 10.3%) and interdigital area (5.5 ± 2.2%). Curtobacterium spp. was predominant on inner pinna (17.8 ± 24.8%) and axilla (6.7 ± 10.8%). Alpha diversity analysis (Shannon index) showed maximum on interdigital area but minimum on a chin (p-value: 0.0416). Beta diversity analysis showed clustering across samples from the individual skin sites but also across samples collected from individual dogs. Staphylococcus spp. was the most abundant genus in 12/16 samples collected from inflammatory skin. In addition, a lower bacterial diversity was observed in samples from skin lesions compared to samples from healthy canine skin. DISCUSSION: The results confirm the fact that the microbiome of healthy skin is very diverse. Compared to other studies, streptococci predominated on healthy canine skin. Shannon index showed only minor differences in diversity between different parts of canine skin. Results of beta-diversity showed the fact that the main force driving the skin microbiota composition is the individual, followed by the skin site. On the area of skin lesions, dysbiosis was observed with a significant predominance of staphylococci.

• Publication type
• Journal Article MeSH

OBJECTIVES: While the reported incidence of non-tuberculous mycobacterial (NTM) infections is increasing, the true prevalence remains uncertain due to limitations in diagnostics and surveillance. The emergence of rare and novel species underscores the need for characterization to improve surveillance, detection, and management. METHODS: We performed whole-genome sequencing (WGS) and/or targeted deep-sequencing using the Deeplex Myc-TB assay on all NTM isolates collected in Slovakia and the Czech Republic between the years 2019 to 2023 that were unidentifiable at the species level by the routine diagnostic line probe assays (LPA) GenoType CM/AS and NTM-DR. Minimal inhibitory concentrations against amikacin, ciprofloxacin, moxifloxacin, clarithromycin, and linezolid were determined, and clinical data were collected. RESULTS: Twenty-eight cultures from different patients were included, of which 9 (32.1%) met the clinically relevant NTM disease criteria. The majority of those had pulmonary involvement, while two children presented with lymphadenitis. Antimycobacterial resistance rates were low. In total, 15 different NTM species were identified, predominantly rare NTM like M. neoaurum, M. kumamotonense and M. arupense. Notably, clinically relevant M. chimaera variants were also identified with WGS and Deeplex-Myc TB, which, unlike other M. chimaera strains, appeared to be undetectable by LPA assays. Deeplex detected four mixed infections that were missed by WGS analysis. In contrast, WGS identified two novel species, M. celatum and M. branderi, which were not detected by Deeplex-Myc TB. Importantly, one of these novel species strains was associated with clinically relevant pulmonary disease. DISCUSSION: Our study demonstrates the clinical relevance of uncommon NTM and the effectiveness of targeted deep-sequencing combined with WGS in identifying rare and novel NTM species.

• MeSH
• Anti-Bacterial Agents * pharmacology   MeSH
• Mycobacterium Infections, Nontuberculous * microbiology   diagnosis   MeSH
• Drug Resistance, Bacterial MeSH
• Child MeSH
• Adult MeSH
• Genotype MeSH
• Clinical Relevance MeSH
• Middle Aged MeSH
• Humans MeSH
• Microbial Sensitivity Tests * MeSH
• Adolescent MeSH
• Nontuberculous Mycobacteria * drug effects   genetics   isolation & purification   MeSH
• Child, Preschool MeSH
• Whole Genome Sequencing * MeSH
• Aged MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH
• Slovakia MeSH

In chronic lymphocytic leukemia, the reliability of next-generation sequencing (NGS) to detect TP53 variants ≤10% allelic frequency (low-VAF) is debated. We tested the ability to detect 23 such variants in 41 different laboratories using their NGS method of choice. The sensitivity was 85.6%, 94.5%, and 94.8% at 1%, 2%, and 3% VAF cut-off, respectively. While only one false positive (FP) result was reported at >2% VAF, it was more challenging to distinguish true variants <2% VAF from background noise (37 FPs reported by 9 laboratories). The impact of low-VAF variants on time-to-second-treatment (TTST) and overall survival (OS) was investigated in a series of 1092 patients. Among patients not treated with targeted agents, patients with low-VAF TP53 variants had shorter TTST and OS versus wt-TP53 patients, and the relative risk of second-line treatment or death increased continuously with increasing VAF. Targeted therapy in ≥2 line diminished the difference in OS between patients with low-VAF TP53 variants and wt-TP53 patients, while patients with high-VAF TP53 variants had inferior OS compared to wild type-TP53 cases. Altogether, NGS-based approaches are technically capable of detecting low-VAF variants. No strict threshold can be suggested from a technical standpoint, laboratories reporting TP53 mutations should participate in a standardized validation set-up. Finally, whereas low-VAF variants affected outcomes in patients receiving chemoimmunotherapy, their impact on those treated with novel therapies remains undetermined. Our results pave the way for the harmonized and accurate TP53 assessment, which is indispensable for elucidating the role of TP53 mutations in targeted treatment.

• Publication type
• Journal Article MeSH

INTRODUCTION: Renal cell carcinoma (RCC) is one of the most prevalent cancers in kidney transplant recipients (KTR). The hereditary background of RCC in native kidneys has been determined, implicating its clinical importance. MATERIALS AND METHODS: This retrospective single-center pilot study aimed to identify a potential genetic predisposition to RCC of the transplanted kidney and outcome in KTR who underwent single kidney transplantation between January 2000 and December 2020 and manifested RCC of the transplanted kidney. Next-generation sequencing (NGS) based germline genetic analysis from peripheral blood-derived genomic DNA (gDNA) was performed in both the recipient and donor using a gene panel targeting 226 cancer predisposition genes. RESULTS: The calculated incidence of RCC of the transplanted kidney among 4146 KTR was 0.43%. In fifteen KTR and donors, NGS was performed. The mean KTR age at transplantation and the diagnosis of RCC was 50.3 years (median 54; 5-67 years) and 66 years (median 66; 24-79 years), respectively. The mean donor age at transplantation and graft age at RCC diagnosis was 39.7 years (median 42; 7-68 years) and 50.2 years (median 46; 20-83 years), respectively. The mean follow-up after RCC diagnosis was 47 months (median 39.1; 0-112 months). Papillary RCC was the most prevalent (n = 8), followed by clear cell RCC (n = 6) and unspecified RCC (n = 1). Thirteen RCCs were low-stage (pT1a/b) diseases, one was pT3, and one was of unknown stage. Most RCC was higher graded. No germline pathogenic cancer-predisposition variant was found in either KTR or donors except for several variants of uncertain significance. CONCLUSION: RCC of the transplanted kidney is very rare. Germline cancer-predisposition testing has identified several variants of uncertain significance, but no germline genetic predisposition to graft RCC in KTR. Further research is needed to assess the clinical relevance of genetic testing for cancer risk in KTR.

• MeSH
• Tissue Donors MeSH
• Child MeSH
• Adult MeSH
• Genetic Predisposition to Disease MeSH
• Carcinoma, Renal Cell * genetics   MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Kidney Neoplasms * genetics   MeSH
• Pilot Projects MeSH
• Child, Preschool MeSH
• Retrospective Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Kidney Transplantation * adverse effects   MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Child, Preschool MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

BACKGROUND: Juvenile granulosa cell tumor (JGCT) of the ovary is a rare tumor with distinct clinicopathological and hormonal features primarily affecting young women and children. We conducted a complex clinicopathological, immunohistochemical, and molecular analysis of five cases of JGCT. METHODS: The immunohistochemical examination was performed with 32 markers, including markers that have not been previously investigated. Moreover, DNA next-generation sequencing (NGS) and PTEN methylation analysis was performed. RESULT: We found the expression of calretinin, inhibin A, SF1, FOXL2, CD99, CKAE1/3, ER, PR, AR in all cases. WT1 was expressed in one case. Conversely, the expression of p16, OCT3/4, SALL4, GATA3, Napsin A, SATB2, MUC4, TTF1, and CAIX was completely negative. All tumors showed the wild-type pattern of p53 expression. Regarding predictive markers, all tumors were HER2 negative and did not express PD-L1. Mismatch repair proteins (MMR) showed no loss or restriction of expression, similarly to ARID1A, DPC4, BRG1, and INI1. The molecular analysis revealed AKT1 internal tandem duplication in two tumors. Two other cases exhibited mutations in TERT and EP400 and both developed recurrence. All AKT1-wild type tumors exhibited immunohistochemical loss of PTEN expression. However, no mutations, deletions (as assessed by CNV analysis), or promoter hypermethylation in the PTEN gene were detected. CONCLUSION: The results of our study further support the hypothesis that the pathogenesis of JGCT may be driven by activation of the PIK3/AKT/mTOR pathway. These findings could potentially have future therapeutic implications, as treatment strategies targeting the PTEN/mTOR pathways are currently under investigation.

• MeSH
• Child MeSH
• Phosphatidylinositol 3-Kinases genetics   metabolism   MeSH
• PTEN Phosphohydrolase genetics   metabolism   MeSH
• Immunohistochemistry * MeSH
• Humans MeSH
• DNA Methylation MeSH
• Adolescent MeSH
• Granulosa Cell Tumor * pathology   genetics   metabolism   MeSH
• Biomarkers, Tumor * genetics   analysis   metabolism   MeSH
• Ovarian Neoplasms * pathology   genetics   metabolism   MeSH
• Proto-Oncogene Proteins c-akt * metabolism   genetics   MeSH
• Signal Transduction * MeSH
• TOR Serine-Threonine Kinases * metabolism   MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Adenoid cystic carcinomas (AdCC) of salivary gland origin have long been categorized as fusion-defined carcinomas owing to the almost universal presence of the gene fusion MYB::NFIB , or less commonly MYBL1::NFIB. Sinonasal AdCC is an aggressive salivary gland malignancy with no effective systemic therapy. Therefore, it is urgent to search for potentially targetable genetic alterations associated with AdCC. We have searched the authors' registries and selected all AdCCs arising in the sinonasal tract. The tumors were examined histologically, immunohistochemically, by next generation sequencing (NGS) and/or fluorescence in situ hybridization (FISH) looking for MYB/MYBL1 and/or NFIB gene fusions or any novel gene fusions and/or mutations. In addition, all tumors were tested for HPV by genotyping using (q)PCR. Our cohort comprised 88 cases of sinonasal AdCC, predominantly characterized by canonical MYB::NFIB (49 cases) and MYBL1::NFIB (9 cases) fusions. In addition, noncanonical fusions EWSR1::MYB ; ACTB::MYB; ESRRG::DNM3 , and ACTN4::MYB were identified by NGS, each of them in 1 case. Among nine fusion-negative AdCCs, FISH detected rearrangements in MYB (7 cases) , NFIB (1 case), and EWSR1 (1 case). Six AdCCs lacked fusions or gene rearrangements, while 11 cases were unanalyzable. Mutational analysis was performed by NGS in 31/88 (35%) AdCCs. Mutations in genes with established roles in oncogenesis were identified in 21/31 tumors (68%), including BCOR (4/21; 19%), NOTCH1 (3/21; 14%), EP300 (3/21; 14%), SMARCA4 (2/21; 9%), RUNX1 (2/21; 9%), KDM6A (2/21; 9%), SPEN (2/21; 9%), and RIT1, MGA, RB1, PHF6, PTEN, CREBBP, DDX41, CHD2, ROS1, TAF1, CCD1, NF1, PALB2, AVCR1B, ARID1A, PPM1D, LZTR1, GEN1 , PDGFRA , each in 1 case (1/21; 5%). Additional 24 cases exhibited a spectrum of gene mutations of uncertain pathogenetic significance. No morphologic differences were observed between AdCCs with MYBL1::NFIB and MYB::NFIB fusions. Interestingly, mutations in the NOTCH genes were seen in connection with both canonical and noncanonical fusions, and often associated with high-grade histology or metatypical phenotype, as well as with poorer clinical outcome. Noncanonical fusions were predominantly observed in metatypical AdCCs. These findings emphasize the value of comprehensive molecular profiling in correlating morphologic characteristics, genetic landscape, and clinical behavior in AdCC.

• MeSH
• Carcinoma, Adenoid Cystic * genetics   pathology   MeSH
• Adult MeSH
• Phenotype MeSH
• Gene Fusion MeSH
• Oncogene Proteins, Fusion genetics   MeSH
• Genetic Predisposition to Disease MeSH
• In Situ Hybridization, Fluorescence * MeSH
• Immunohistochemistry MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Mutation * MeSH
• DNA Mutational Analysis MeSH
• Biomarkers, Tumor * genetics   MeSH
• Paranasal Sinus Neoplasms * genetics   pathology   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• NFI Transcription Factors genetics   MeSH
• High-Throughput Nucleotide Sequencing * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH