e23524 Background: Soft tissue sarcomas are heterogeneous mesenchymal malignancies with overlapping histology, making diagnosis challenging. According to World Health Organization (WHO) classification of STS and bone sarcomas, >150 recurrent fusions have emerged as central diagnostic hallmarks for many sarcoma entities. RNA-based next-generation sequencing, particularly RNA-exome sequencing, enables sensitive detection of known and novel fusion transcripts with precise breakpoint characterization, and comprehensive molecular profiling even from limited tissue samples. The aim of this study was to assess the diagnostic utility of exome-capture RNA sequencing compared to targeted RNA next-generation sequencing for the detection of sarcoma-associated gene fusions, particularly in cases with challenging histology or negative results on targeted fusion panels. Methods: Total RNA was extracted from formalin-fixed, paraffin-embedded (FFPE) tissue using the MagMAX FFPE DNA/RNA Ultra Kit (Thermo Fisher Scientific). RNA-exome libraries were prepared with the NadPrep Total RNA to DNA – EZ DNA Library Preparation Kit (Nanodigmbio) and sequenced on the DNBSEQ-T7 platform (MGI Tech). Fusion transcript detection was performed using SeqPilot, complemented by bioinformatic tools STAR-Fusion and FusionInspector. In parallel, targeted RNA NGS libraries were generated using a custom sarcoma fusion panel, sequenced on the Ion GeneStudio S5 Prime System (Thermo Fisher Scientific) and analysed via the Torrent Suite software. Results: A total of 143 samples from patients with various histological subtypes of sarcoma were analyzed using a custom sarcoma panel (Ion AmpliSeq). Sarcoma-associated rearrangements were identified in 34% of cases (49/143). The most frequently detected alteration was the EWSR1::FLI1 fusion, observed in 7.7% of samples, a well-established molecular hallmark of Ewing sarcoma. Subsequently, 24 samples that were negative by the custom sarcoma panel were further analyzed using the RNA exome panel. In addition, in 17% (4/24) of cases, detection of TFE3::ASPSCR1 , HEY1::NCOA2 , FGFR1::WHSC1L1 , and EWSR1-NR4A3 fusions aided histological classification and confirmed the initial sarcoma diagnosis. Conclusions: RNA-exome sequencing provided additional diagnostic yield in panel-negative cases, enabling the detection of clinically informative fusions that supported or refined histological classification. These findings highlight the significant role of RNA-exome sequencing in the molecular diagnosis of STSs, particularly in diagnostically challenging cases, and support its integration into advanced diagnostic workflows. Nevertheless, prior review by sarcoma-expert pathologists remains essential to determine the appropriate indication for NGS testing.

In the era of precision oncology, comprehensive molecular profiling is critical for guiding targeted and immunotherapy strategies. This study presents the analytical and clinical validation of a 1021-gene next-generation sequencing (NGS) panel, designed for use with both formalin-fixed paraffin-embedded (FFPE) tissue- and liquid-biopsy specimens. Analytical validation confirmed the assay’s high sensitivity and specificity across variant types—including SNVs (Single Nucleotide Variations), indels, CNVs (Copy Number Variations), and fusions—down to a 0.5% variant allele frequency. The assay also accurately identified microsatellite instability (MSI) and tumor mutational burden (TMB), essential biomarkers for immunotherapy. Clinical validation was performed on over 1300 solid tumor samples from diverse histologies, revealing actionable alterations in over 50% of cases. The panel detected on-label treatment biomarkers in 12.57% of patients, increasing to 20.15% when immunotherapy markers were included. Additionally, the assay demonstrated strong concordance with orthogonal methods and was effective in detecting variants in plasma-derived circulating tumor DNA in 70% of evaluable cases. These findings support the robust performance and broad clinical applicability of the 1021-gene panel for comprehensive genomic profiling in both tissue and liquid biopsies, offering a valuable tool for personalized cancer treatment.

PARP inhibitors have revolutionized ovarian cancer treatment, with benefits strongly linked to the presence of Homologous Recombination Deficiency (HRD). Although HRD testing was originally conducted on centralized platforms, there is growing demand for scalable, accessible, and robust solutions capable of supporting expanded clinical utilization. In the present study, a decentralized NGS-based assay was compared for its ability to effectively identify HRD positive patients when compared to the reference assay as well as other testing platforms.Eighty-two cases of ovarian cancer patients previously tested using the reference HRD assay (Myriad MyChoice® CDx assay) were evaluated by an NGS based HRD assay, the 1021-HRD assay (GenePlus), that provides genomic instability (GI) analysis along with tumor molecular profiling. HRD status, GI status (referred to as HRD-score), and even BRCA1/2 mutation detection were assessed for concordance with the reference test and the analytical accuracy of the assay was calculated. Additionally, GI alignment across alternative HRD testing platforms was examined. Finally, the association between key tumor alterations and the HRD status was evaluated.The 1021-HRD assay demonstrated an overall HRD classification agreement of approximately 92.68 % (κ = 0.841) in comparison to the reference method, as evidenced by the results, with 81.25 % specificity and 100 % sensitivity. These features generally suggest consistent performance, with only minor discrepancies observed. The BRCA1/2 alterations detected were 97.56 % in agreement with the approved assay. The Pearson r value of 0.878 indicates a strong correlation between the GI values obtained. The assay's capacity to detect non-BRCA1/2 HRD phenotypes was verified by the observation that 55.56 % of BRCA-wildtype malignancies were HRD-positive. Of particular interest, combining molecular profiling with GI analysis, the assay identified additional actionable alterations in 65 % of the cases, revealing clinically relevant biomarkers beyond the homologous recombination pathway. This wide-ranging approach may provide more diagnostic and therapeutic insight than HRD testing alone.In conclusion, the 1021-HRD assay is a dependable, decentralized alternative for HRD testing. It can provide a more comprehensive genomic characterization and exhibits remarkable analytical concordance with current standards. Its combined format and accessibility render it well-suited for real-world use in personalized ovarian cancer care. Its additional capacity to reveal more extensive tumor genomic alterations improves clinical decision-making and underscores the importance of integrating HRD scoring with comprehensive molecular profiling in personalized oncology.

e13070 Background: The new targeted treatment options for HR+/HER2- recurrent breast cancer patients, has enhanced the value of biomarker analysis by NGS. The aim of this study was to evaluate the utility of liquid biopsy in identifying actionable and resistance-associated variants in relapsed breast cancer patients treated with hormone therapy. Methods: Plasma samples were collected from 1011 metastatic breast cancer (BC) patients. cfDNA was extracted and then analyzed using the commercially available gene panel Oncomine™ Breast cfDNA with the Ion GeneStudio S5 Prime NGS platform (ThermoFisher Scientific). The assay targets genes with therapeutic relevance, with the current study focusing on the mutational status of the ESR1 and PIK3CA genes. Results: ESR1 and PIK3CA actionable variations were detected in 42% of the BC patients. Variations in the PIK3CA gene were found in 27% of patients, with the most common ones being H1047X (12%), E545X (8%), and E542K (5%). ESR1 variation were identified in 24% of patients, with hotspot mutations D538G (11%) and Y537S (8%) being the most frequent . Notably, 9% of patients exhibited co-mutations in both ESR1 and PIK3CA genes. Additionally, 13% of ESR1 -positive patients carried multiple ESR1 variations, while multiple PIK3CA alterations were detected in 10% of PIK3CA -positive patients. Conclusions: The detection of variations in genes with approved therapies, such as ESR1 and PIK3CA , is essential for the implementation of precision oncology in breast cancer patients. PIK3CA and ESR1 mutations opt breast cancer patients for on-label therapy while ESR1 mutations are also associated with acquired resistance to endocrine therapy necessitating therapeutic modifications. Molecular analysis of ctDNA highlights the feasibility of integrating liquid biopsy into routine molecular pathology, as it demonstrates high sensitivity and specificity thus offering real-time insights for dynamic therapeutic adjustments. Its incorporation into clinical oncology workflows marks a significant step forward in personalized medicine, enhancing the possibility of application of on-label therapies hence improving patient outcomes.

BACKGROUND/AIM:The application of next-generation sequencing (NGS) technology in the genetic investigation of hereditary cancer is important for clinical surveillance, therapeutic approach, and reducing the risk of developing new malignancies. The aim of the study was to explore genetic predisposition in individuals referred for hereditary cancer. MATERIALS AND METHODS:A total of 8,261 individuals were referred for multigene genetic testing, during the period 2020-2023, in the laboratory, and underwent multigene genetic testing using NGS. Among the examined individuals, 56.17% were diagnosed with breast cancer, 6.77% with ovarian cancer, 2.88% with colorectal cancer, 1.91% with prostate cancer, 6.43% were healthy with a significant family history of cancer, while 3.06% had a different type of cancer and 0.21% had not provided any information. Additionally, in 85 women with breast cancer we performed whole exome sequencing analysis. RESULTS:20% of the examined individuals carried a pathogenic variant. Specifically, 54.8% of the patients had a pathogenic variant in a clinically significant gene (BRCA1, BRCA2, PALB2, RAD51C, PMS2, CDKN2A, MLH1, MSH2, TP53, MSH6, APC, RAD51D, PTEN, RET, CDH1, MEN1, and VHL). Among the different types of pathogenic variants detected, a significant percentage (6.52%) represented copy number variation (CNV). With WES analysis, the following findings were detected: CTC1: c.880C>T, p.(Gln294*); MLH3: c.405del, p.(Asp136Metfs*2), PPM1D: c.1426_1430del, p.(Glu476Leufs*3), and SDHB: c.395A>G, p.(His132Arg). CONCLUSION:Comprehensive multigene genetic testing is necessary for appropriate clinical management of pathogenic variants' carriers. Additionally, the information obtained is important for determining the risk of malignancy development in family members of the examined individuals.

Early-onset breast cancer constitutes a major criterion for genetic testing referral. Nevertheless, studies focusing on breast cancer patients (≤30 years) are limited. We investigated the contribution and spectrum of known breast-cancer-associated genes in 267 Greek women with breast cancer ≤30 years while monitoring their clinicopathological characteristics and outcomes. In this cohort, a significant proportion (39.7%) carried germline pathogenic variants (PVs) distributed in 8 genes. The majority, namely 36.7%, involved BRCA1, TP53, and BRCA2. PVs in BRCA1 were the most prevalent (28.1%), followed by TP53 (4.5%) and BRCA2 (4.1%) PVs. The contribution of PVs in CHEK2, ATM, PALB2, PTEN, and RAD51C was limited to 3%. In the patient group ≤26 years, TP53 PVs were significantly higher compared to the group 26–30 years (p = 0.0023). A total of 74.8% of TP53 carriers did not report a family history of cancer. Carriers of PVs receiving neoadjuvant chemotherapy showed an improved event-free survival (p < 0.0001) compared to non-carriers. Overall, many women with early-onset breast cancer carry clinically actionable variants, mainly in the BRCA1/2 and TP53 genes. The inclusion of timely testing of TP53 in these patients provides essential information for appropriate clinical management. This is important for countries where reimbursement involves the cost of genetic analysis of BRCA1/2 only.

Inherited cardiovascular diseases are highly heterogeneous conditions with multiple genetic loci involved. The application of advanced molecular tools, such as Next Generation Sequencing, has facilitated the genetic analysis of these disorders. Accurate analysis and variant identification are required to maximize the quality of the sequencing data. Therefore, the application of NGS for clinical purposes should be limited to laboratories with a high level of technological expertise and resources. In addition, appropriate gene selection and variant interpretation can result in the highest possible diagnostic yield. Implementation of genetics in cardiology is imperative for the accurate diagnosis, prognosis and management of several inherited disorders and could eventually lead to the realization of precision medicine in this field. However, genetic testing should also be accompanied by an appropriate genetic counseling procedure that clarifies the significance of the genetic analysis results for the proband and his family. In this regard, a multidisciplinary collaboration among physicians, geneticists, and bioinformaticians is imperative. In the present review, we address the current state of knowledge regarding genetic analysis strategies employed in the field of cardiogenetics. Variant interpretation and reporting guidelines are explored. Additionally, gene selection procedures are accessed, with a particular emphasis on information concerning gene-disease associations collected from international alliances such as the Gene Curation Coalition (GenCC). In this context, a novel approach to gene categorization is proposed. Moreover, a sub-analysis is conducted on the 1,502,769 variation records with submitted interpretations in the Clinical Variation (ClinVar) database, focusing on cardiology-related genes. Finally, the most recent information on genetic analysis's clinical utility is reviewed.

Background: Hereditary cancer predisposition syndromes are responsible for approximately 5–10% of all diagnosed cancer cases. In order to identify individuals at risk in a cost-efficient manner, family members of individuals carrying pathogenic alterations are tested only for the specific variant that was identified in their carrier relative. The purpose of this study was to investigate the clinical use and implementation of cascade family testing (CFT) in families of breast cancer patients with pathogenic/likely pathogenic variants (PVs/LPVs) in cancer-related predisposition genes. Methods: Germline sequencing was carried out with NGS technology using a 52-gene panel, and cascade testing was performed by Sanger sequencing or MLPA. Results: In a cohort of 1785 breast cancer patients (families), 20.3% were found to have PVs/LPVs. Specifically, 52.2%, 25.1%, and 22.7% of patients had positive findings in high-, intermediate-, and low-penetrance breast cancer susceptibility genes, respectively. Although CFT was recommended to all families, only 117 families (32.3%) agreed to proceed with genetic testing. Among the first-degree relatives who underwent CFT, 70.3% were female, and 108 of 121 (89.3%) were cancer free. Additionally, 42.7%, 36.7%, and 20.6% were offspring, siblings, and parents of the subject, respectively. Our data suggest that CFT was mostly undertaken (104/117, 88.8%) in families with positive findings in high-risk genes. Conclusions: Cascade family testing can be a powerful tool for primary cancer prevention by identifying at-risk family members. It is of utmost importance to implement genetic counseling approaches leading to increased awareness and communication of genetic testing results.

Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

Implementation of next-generation sequencing (NGS) for the genetic analysis of hereditary diseases has resulted in a vast number of genetic variants identified daily, leading to inadequate variant interpretation and, consequently, a lack of useful clinical information for treatment decisions. Herein, we present MARGINAL 1.0.0, a machine learning (ML)-based software for the interpretation of rare BRCA1 and BRCA2 germline variants. MARGINAL software classifies variants into three categories, namely, (likely) pathogenic, of uncertain significance and (likely) benign, implementing the criteria established by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP). We first annotated BRCA1 and BRCA2 variants using various sources. Then, we automatically implemented the ACMG-AMP criteria, and we finally constructed the ML model for variant classification. To maximize accuracy, we compared the performance of eight different ML algorithms in a classification scheme based on a serial combination of two classifiers. The model showed high predictive abilities with maximum accuracy of 92% and 98%, recall of 92% and 98% and specificity of 90% and 98% for the first and second classifiers, respectively. Our results indicate that using a gene and disease-specific ML automated software for clinical variant evaluation can minimize conflicting interpretations.

National genetic variation registries vastly increase the level of detail for the relevant population, while directly affecting patient management. Herein, we report CanVaS, a Cancer Variation reSource aiming to document the genetic variation of cancer patients in Greece. CanVaS comprises germline genetic data from 7,363 Greek individuals with a personal and/or family history of malignancy. The dataset incorporates ~24,000 functionally annotated rare variants in 97 established or suspected cancer susceptibility genes. For each variant, allele frequency for the Greek population, interpretation for clinical significance, anonymized family and segregation information, as well as phenotypic traits of the carriers, are included. Moreover, information on the geographic distribution of the variants across the country are provided, enabling the study of Greek population isolates. Direct comparisons between Greek (sub)populations with relevant genetic resources is supported, allowing fine-grain localized adjustment of guidelines and clinical decision-making. Most importantly, anonymized data are available for download, while the Leiden Open Variation Database schema is adopted, enabling integration/interconnection with central resources. CanVaS could become a stepping-stone for a countrywide effort to characterize the cancer genetic variation landscape, concurrently supporting national and international cancer research. The database can be accessed at: https://ithaka.rrp.demokritos.gr/CanVaS