Malignant mixed Müllerian tumours, also known as carcinosarcomas, are rare tumours of gynaecological origin. Here we perform whole-exome analyses of 22 tumours using massively parallel sequencing to determine the mutational landscape of this tumour type. On average, we identify 43 mutations per tumour, excluding four cases with a mutator phenotype that harboured inactivating mutations in mismatch repair genes. In addition to mutations in TP53 and KRAS, we identify genetic alterations in chromatin remodelling genes, ARID1A and ARID1B, in histone methyltransferase MLL3, in histone deacetylase modifier SPOP and in chromatin assembly factor BAZ1A, in nearly two thirds of cases. Alterations in genes with potential clinical utility are observed in more than three quarters of the cases and included members of the PI3-kinase and homologous DNA repair pathways. These findings highlight the importance of the dysregulation of chromatin remodelling in carcinosarcoma tumorigenesis and suggest new avenues for personalized therapy.
Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired tumor-normal exome data from 1368 TCGA (The Cancer Genome Atlas) samples using this method revealed concordance for 74% of mutation calls but also identified likely false-positive and false-negative changes in TCGA data, including in clinically actionable genes. Determination of high-quality somatic mutation calls improved tumor mutation load-based predictions of clinical outcome for melanoma and lung cancer patients previously treated with immune checkpoint inhibitors. Integration of high-quality machine learning mutation detection in clinical next-generation sequencing (NGS) analyses increased the accuracy of test results compared to other clinical sequencing analyses. These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of cancer patients.
Disruption of NOTCH1 signaling was recently discovered in head and neck cancer. This study aims to evaluate NOTCH1 alterations in the progression of oral squamous cell carcinoma (OSCC) and compare the occurrence of these mutations in Chinese and Caucasian populations. We used a high-throughput-PCR-based enrichment technology and next generation sequencing (NGS) to sequence NOTCH1 in 144 samples collected in China. Forty nine samples were normal oral mucosa from patients undergoing oral surgery, 45 were oral leukoplakia biopsies and 50 were chemoradiation naïve OSCC samples with 22 paired-normal tissues from the adjacent unaffected areas. NOTCH1 mutations were found in 54% of primary OSCC and 60% of pre-malignant lesions. Importantly, almost 60% of leukoplakia patients with mutated NOTCH1 carried mutations that were also identified in OSCC, indicating an important role of these clonal events in the progression of early neoplasms. We then compared all known NOTCH1 mutations identified in Chinese OSCC patients with those reported in Caucasians to date. Although we found obvious overlaps in critical regulatory NOTCH1 domains alterations and identified specific mutations shared by both groups, possible gain-of-function mutations were predominantly seen in Chinese population. Our findings demonstrate that pre-malignant lesions display NOTCH1 mutations at an early stage and are thus bona fide drivers of OSCC progression. Moreover, our results reveal that NOTCH1 promotes distinct tumorigenic mechanisms in patients from different ethnical populations.
<p>Supplemental Tables 6-11. Supp. Table 6. List of all mutations identified in each of the normal samples. Supp. Table 7. List of the mutations in the unmatched OSCC and leukoplakia samples that were filtered-out as they were present in the normal samples or in the dbSNP. Supp. Table 8. Summary of the number of mutations present in each of the sets of samples and the number that were filtered-out during analysis. Supp. Table 9. Combined list of all mutations identified in Chinese OSCC patients in this study and by Song et. al (16). Supp. Table 10. List of all NOTCH1 mutations identified in Caucasians HNSCC samples. Supp. Table 11. List of all HNSCC samples from Caucasian patients used in this study: including exact site and HPV status.</p>
<p>Supplemental Figure 2. List of all NOTCH1 mutations identified in Chinese patients with oral leukoplakia.</p>
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.