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Some epithelial neoplasms of the appendix, including low-grade appendiceal mucinous neoplasm and adenocarcinoma, can result in pseudomyxoma peritonei (PMP). Little is known about the mutational spectra of these tumor types and whether mutations may be of clinical significance with respect to therapeutic selection. In this study, we identified somatic mutations using the Ion Torrent AmpliSeq Cancer Hotspot Panel v2. Specimens consisted of 3 nonneoplastic retention cysts/mucocele, 15 low-grade mucinous neoplasms (LAMNs), 8 low-grade/well-differentiated mucinous adenocarcinomas with pseudomyxoma peritonei, and 12 adenocarcinomas with/without goblet cell/signet ring cell features. Barcoded libraries were prepared from up to 10 ng of extracted DNA and multiplexed on single 318 chips for sequencing. Data analysis was performed using Golden Helix SVS. Variants that remained after the analysis pipeline were individually interrogated using the Integrative Genomics Viewer. A single Janus kinase 3 (JAK3) mutation was detected in the mucocele group. Eight mutations were identified in the V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) and GNAS complex locus (GNAS) genes among LAMN samples. Additional gene mutations were identified in the AKT1 (v-akt murine thymoma viral oncogene homolog 1), APC (adenomatous polyposis coli), JAK3, MET (met proto-oncogene), phosphatidylinositol-4,5-bisphosphate 3-kinase (PIK3CA), RB1 (retinoblastoma 1), STK11 (serine/threonine kinase 11), and tumor protein p53 (TP53) genes. Among the PMPs, 6 mutations were detected in the KRAS gene and also in the GNAS, TP53, and RB1 genes. Appendiceal cancers showed mutations in the APC, ATM (ataxia telangiectasia mutated), KRAS, IDH1 [isocitrate dehydrogenase 1 (NADP+)], NRAS [neuroblastoma RAS viral (v-ras) oncogene homolog], PIK3CA, SMAD4 (SMAD family member 4), and TP53 genes. Our results suggest molecular heterogeneity among epithelial tumors of the appendix. Next generation sequencing efforts have identified mutational spectra in several subtypes of these tumors that may suggest a phenotypic heterogeneity showing mutations that are relevant for targeted therapies.

Circulating cell-free DNA (cfDNA) is an important biomarker for various cancer types, enabling a non-invasive testing approach. However, pre-analytical variables, including sample collection, tube type, processing conditions, and extraction methods, can significantly impact the yield, integrity, and overall quality of cfDNA. This study presents a comprehensive analytical validation of a magnetic bead-based, high-throughput cfDNA extraction system, with a focus on assessing its efficiency, reproducibility, and compatibility with downstream molecular applications. The validation was performed using a range of sample types: synthetic cfDNA spiked into DNA-free plasma, multi-analyte ctDNA plasma controls, Seraseq ctDNA reference material in a plasma-like matrix, extraction specificity controls, residual clinical specimen from patients, and samples from healthy individuals stored at room temperature or 4 °C for up to 48 h to assess stability. Extracted cfDNA was analyzed for concentration, percentage, and fragment size, using the Agilent TapeStation. Variant detection was evaluated using a next-generation sequencing (NGS) assay on the Seraseq ctDNA reference material. The results demonstrated high cfDNA recovery rates, consistent fragment size distribution (predominantly mononucleosomal and dinucleosomal), minimal genomic DNA (gDNA) contamination, and strong concordance between detected and expected variants in reference materials. The workflow also showed robust performance under different study parameters, variable sample conditions, including sample stability and integrity. Together, these findings confirm the efficiency and reliability of the evaluated cfDNA extraction system and underscore the importance of standardized pre-analytical workflows for the successful implementation of liquid biopsy for early cancer detection, therapeutic monitoring, and improved patient outcomes.

Nearly all cervical cancers are caused by persistent high-risk human papillomavirus (hrHPV) infection. There are 14 recognized hrHPV genotypes (HPV 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68), and hrHPV genotypes 16 and 18 comprise approximately 66% of all cases worldwide. An additional 15% of cervical cancers are caused by hrHPV genotypes 31, 33, 45, 52, and 58. Screening patients for hrHPV as a mechanism for implementation of early treatment is a proven strategy for decreasing the incidence of HPV-related neoplasia, cervical cancer in particular. Here, we present population data from an HPV screening initiative in Kosovo designed to better understand the prevalence of the country’s HPV burden and local incidence of cervical cancer by hrHPV genotype. Nearly 2000 women were screened for hrHPV using a real-time polymerase chain reaction (real-time PCR) assay followed by melt curve analysis to establish the prevalence of hrHPV in Kosovo. Additionally, DNA was extracted from 200 formalin-fixed, paraffin embedded cervical tumors and tested for hrHPV using the same method. Cervical screening samples revealed a high prevalence of hrHPV genotypes 16 and 51, while cervical cancer specimens predominantly harbored genotypes 16, 18, and 45. This is the first comprehensive screening study for evaluating the prevalence of hrHPV genotypes in Kosovo on screening cervical brush samples and cervical neoplasms. Given the geographic distribution of hrHPV genotypes and the WHO’s global initiative to eliminate cervical cancer, this study can support and direct vaccination efforts to cover highly prevalent hrHPV genotypes in Kosovo’s at-risk population.

Cyanobacteria produce a variety of secondary metabolites, including toxins that may contribute to the development of disease. Previous work was able to detect the presence of a cyanobacterial marker in human nasal and broncoalveolar lavage samples; however, it was not able to determine the quantification of the marker. To further research the relationship between cyanobacteria and human health, we validated a droplet digital polymerase chain reaction (ddPCR) assay to simultaneously detect the cyanobacterial 16S marker and a human housekeeping gene in human lung tissue samples. The ability to detect cyanobacteria in human samples will allow further research into the role cyanobacteria plays in human health and disease.