Dataset Information

Oral cancer prediction by noninvasive genetic screening.

ABSTRACT: Oral squamous cell carcinomas (OSCCs) develop in genetically altered epithelium in the mucosal lining, also coined as fields, which are mostly not visible but occasionally present as white oral leukoplakia (OL) lesions. We developed a noninvasive genetic assay using next-generation sequencing (NGS) on brushed cells to detect the presence of genetically altered fields, including those that are not macroscopically visible. The assay demonstrated high accuracy in OL patients when brush samples were compared with biopsies as gold standard. In a cohort of Fanconi anemia patients, detection of mutations in prospectively collected oral brushes predicted oral cancer also when visible abnormalities were absent. We further provide insight in the molecular landscape of OL with frequent changes of TP53, FAT1 and NOTCH1. NGS analysis of noninvasively collected samples offers a highly accurate method to detect genetically altered fields in the oral cavity, and predicts development of OSCC in high-risk individuals. Noninvasive genetic screening can be employed to screen high-risk populations for cancer and precancer, map the extension of OL lesions beyond what is visible, map the oral cavity for precancerous changes even when visible abnormalities are absent, test accuracy of promising imaging modalities, monitor interventions and determine genetic progression as well as the natural history of the disease in the human patient.

SUBMITTER: Poell JB

PROVIDER: S-EPMC9826173 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Oral cancer prediction by noninvasive genetic screening.

Poell Jos B JB Wils Leon J LJ Brink Arjen A Dietrich Ralf R Krieg Christine C Velleuer Eunike E Evren Ilkay I Brouns Elisabeth R ER de Visscher Jan G JG Bloemena Elisabeth E Ylstra Bauke B Brakenhoff Ruud H RH

International journal of cancer 20220918 2

Oral squamous cell carcinomas (OSCCs) develop in genetically altered epithelium in the mucosal lining, also coined as fields, which are mostly not visible but occasionally present as white oral leukoplakia (OL) lesions. We developed a noninvasive genetic assay using next-generation sequencing (NGS) on brushed cells to detect the presence of genetically altered fields, including those that are not macroscopically visible. The assay demonstrated high accuracy in OL patients when brush samples were ...[more]

PMID: 36069231

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Project description:Oral cancer is a major public health problem, and there is an increasing trend for oral cancer to affect young men and women. Public awareness is poor, and many patients present with late-stage disease, contributing to high mortality. Oral cancer is often preceded by a clinical premalignant phase accessible to visual inspection, and thus there are opportunities for earlier detection and to reduce morbidity and mortality. Screening asymptomatic individuals by systematic visual oral examinations to detect the disease has been shown to be feasible. A positive screen includes both oral cancer and oral potentially malignant disorders. We review key screening studies undertaken, including 1 randomized clinical trial. Screening of high-risk groups is cost-effective. Strengths and weaknesses of oral cancer screening studies are presented to help guide new research in primary care settings and invigorated by the prospect of using emerging new technologies that may help to improve discriminatory accuracy of case detection. Most national organizations, including the US Preventive Services Task Force, have so far not recommended population-based screening due a lack of sufficient evidence that screening leads to a reduction in oral cancer mortality. Where health care resources are high, opportunistic screening in dental practices is recommended, although the paucity of research in primary care is alarming. The results of surveys suggest that dentists do perform oral cancer screenings, but there is only weak evidence that screening in dental practices leads to downstaging of disease. Where health care resources are low, the feasibility of using primary health care workers for oral cancer screening has been tested, and measures indicate good outcomes. Most studies reported in the literature are based on 1 round of screening, whereas screening should be a continuous process. This review identifies a huge potential for new research directions on screening for oral cancer.

Project description:ImportanceOccult peritoneal metastasis frequently occurs in patients with advanced gastric cancer and is poorly diagnosed with currently available tools. Because the presence of peritoneal metastasis precludes the possibility of curative surgery, there is an unmet need for a noninvasive approach to reliably identify patients with occult peritoneal metastasis.ObjectiveTo assess the use of a deep learning model for predicting occult peritoneal metastasis based on preoperative computed tomography images.Design, setting, and participantsIn this multicenter, retrospective cohort study, a deep convolutional neural network, the Peritoneal Metastasis Network (PMetNet), was trained to predict occult peritoneal metastasis based on preoperative computed tomography images. Data from a cohort of 1225 patients with gastric cancer who underwent surgery at Sun Yat-sen University Cancer Center (Guangzhou, China) were used for training purposes. To externally validate the model, data were collected from 2 independent cohorts comprising a total of 753 patients with gastric cancer who underwent surgery at Nanfang Hospital (Guangzhou, China) or the Third Affiliated Hospital of Southern Medical University (Guangzhou, China). The status of peritoneal metastasis for all patients was confirmed by pathological examination of pleural specimens obtained during surgery. Detailed clinicopathological data were collected for each patient. Data analysis was performed between September 1, 2019, and January 31, 2020.Main outcomes and measuresThe area under the receiver operating characteristic curve (AUC) and decision curve were analyzed to evaluate performance in predicting occult peritoneal metastasis.ResultsA total of 1978 patients (mean [SD] age, 56.0 [12.2] years; 1350 [68.3%] male) were included in the study. The PMetNet model achieved an AUC of 0.946 (95% CI, 0.927-0.965), with a sensitivity of 75.4% and a specificity of 92.9% in external validation cohort 1. In external validation cohort 2, the AUC was 0.920 (95% CI, 0.848-0.992), with a sensitivity of 87.5% and a specificity of 98.2%. The discrimination performance of PMetNet was substantially higher than conventional clinicopathological factors (AUC range, 0.51-0.63). In multivariable logistic regression analysis, PMetNet was an independent predictor of occult peritoneal metastasis.Conclusions and relevanceThe findings of this cohort study suggest that the PMetNet model can serve as a reliable noninvasive tool for early identification of patients with clinically occult peritoneal metastasis, which will inform individualized preoperative treatment decision-making and may avoid unnecessary surgery and complications. These results warrant further validation in prospective studies.

Dataset Information

Oral cancer prediction by noninvasive genetic screening.

Publications

Oral cancer prediction by noninvasive genetic screening.

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