Background This paper describes the clinical practice and performance of cell-free DNA sequencing-based non-invasive prenatal testing (NIPT) as a screening method for fetal trisomy 21, 18, and 13 (T21, T18, and T13) and sex chromosome aneuploidies (SCA) in a general Italian pregnancy population. Methods The AMES-accredited laboratory offers NIPT in maternal blood as a screening test for fetal T21, T18, T13 and SCA. Samples were sequenced on a NextSeq 550 (Illumina) using the VeriSeq NIPT Solution v1 assay. Results A retrospective analysis was performed on 36,456 consecutive maternal blood samples, including 35,650 singleton pregnancies, 800 twin pregnancies, and 6 triplet pregnancies. Samples were tested between April 2017 and September 2019. The cohort included 46% elevated-risk and 54% low-risk patients. A result indicative of a classic trisomy was found in 356 (1%) of singleton or twin samples: 254 T21, 69 T18, and 33 T13. In addition, 145 results (0.4%) were indicative of a SCA. Of the combined 501 screen-positive cases, 484 had confirmatory diagnostic testing. NIPT results were confirmed in 99.2% (247/249) of T21 cases, 91.2% (62/68) of T18 cases, 84.4% (27/32) of T13 cases, and 86.7% (117/135) of SCA cases. In the 35,955 cases reported as unaffected by a classic trisomy or SCA, no false negative cases were reported. Assuming that false negative results would be reported, the sensitivity of NIPT was 100.00% for T21 (95% Cl 98.47–100.0), T18 (95% Cl 94.17–100.0), and T13 (95% Cl 87.54–100.0). The specificities were 99.99% (95% Cl 99.98–100.0), 99.98% (95% Cl 99.96–100.0), 99.99% (95% Cl 99.97–100.0), and 99.95% (95% Cl 99.92–99.97) for T21, T18, T13, and SCA, respectively. Conclusion This retrospective analysis of a large cohort of consecutive patients who had whole-genome sequencing-based NIPT for classic trisomies and SCA shows excellent detection rates and low false positive rates.
Genetic dynamics underlying cancer progression are largely unknown and several genes involved in highly prevalent illnesses (e.g., hypertension, obesity, and diabetes) strongly concur to cancer phenotype heterogeneity. To study genotype-phenotype relationships contributing to the mutational evolution of colorectal cancer (CRC) with a focus on liver metastases, we performed genome profiling on tumor tissues of CRC patients with liver metastatic disease and no co-morbidities. We studied 523 cancer-related genes and tumor-immune microenvironment characteristics in primary and matched metastatic tissues. We observed a loss of KRAS and SMAD4 alterations and a high granzyme-B+ T-cell infiltration when the disease did not progress. Conversely, gain in KRAS, PIK3CA and SMAD4 alterations and scarce granzyme-B+ T-cells infiltration were observed when the tumor evolved towards a poly-metastatic spread. These findings provide novel insights into the identification of tumor oligo-metastatic status, indicating that some genes are on a boundary line between these two clinical settings (oligo- vs. poly-metastatic CRC). We speculate that the identification of these genes and modification of their evolution could be a new approach for anti-cancer therapeutic strategies.
Genetics and immunologic dynamics pushing the evolution of colorectal cancer (CRC) from the primary tumor to the metastases are largely unknown; cancer heterogeneity makes challenging both therapy and mechanistic studies. We selected patients developing CRC with lung-limited metastatic disease as only illness during their life in order to find any relevant genotype-phenotype relationship. Analysis of 523 cancer-relevant genes and of immune cells infiltration in primary and metastatic tissues revealed atypical genomic trajectories (TMB decrease, KRAS and SMAD4 regressive mutations), specific genetic events (ERBB2 point mutations) and scarce T-cell infiltration. These insights provide novel information in oligometastatic CRC biology and new perspectives for cancer monitoring and anti-cancer therapeutic strategies.
Due to the complexity of the experimental procedures and the high, specific professional expertise required for both laboratory activities and the related counselling, these types of analyses should be preferentially performed in reference molecular diagnostic centres.
The present study was undertaken to analyze prognostic and genetic interactions between type 2 diabetes and metastatic colorectal cancer. Patients’ survival was depicted through the Kaplan–Meier product limit method. Prognostic factors were examined through the Cox proportional‐hazards regression model, and associations between diabetes and clinical‐pathologic variables were evaluated by the χ2 test. In total, 203 metastatic colorectal cancer patients were enrolled. Lymph nodes (P = 0.0004) and distant organs (> 2 distant sites, P = 0.0451) were more frequently involved in diabetic patients compared with those without diabetes. Diabetes had an independent statistically significant negative prognostic value for survival. Highly selected patients with cancer and/or diabetes as their only illness(es) were divided into three groups: (a) seven oligo‐metastatic patients without diabetes, (b) 10 poly‐metastatic patients without diabetes, and (c) 12 poly‐metastatic diabetic patients. These groups of patients were genetically characterized through the Illumina NovaSeq 6000 (San Diego, CA, USA) platform and TruSigt™Oncology 500 kit, focusing on genes involved in diabetes and colorectal cancer. Gene variants associated with diabetes and cancer were more frequent in patients in group 3. We found that type 2 diabetes is a negative prognostic factor for survival in colorectal cancer. Diabetes‐associated gene variants could concur with malignancy, providing a rational basis for innovative models of tumor progression and therapy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.