Oral cancer is one of the most common types of cancer worldwide, with 377,713 new cases and 177,757 deaths reported in 2020 [1]. While smoking, alcohol consumption, and Human papilloma virus (HPV) infection are the primary risk factors, certain genetic disorders can increase the likelihood of developing oral cancer [2]. One such disorder, Fanconi anemia (FA), is an inherited cancer susceptibility syndrome caused by a bi-allelic mutation in one of the 23 genes that are a part of the FA DNA repair pathway [3, 4]. Physiologically, the FA gene products work to remove interstrand crosslinks in DNA [5]. However, in individuals with FA, unrepaired interstrand crosslinks contribute to genomic instability and tumorigenesis [3, 6].

Compared with the non-FA population, FA patients face a 500–700-fold higher risk of developing head and neck squamous cell carcinoma (HNSCC), with most of these lesions located in the oral cavity [7, 8]. Similar to other cancers, oral cancers have a better prognosis if diagnosed early [8, 9, 10]. Compared to the general population, FA patients are often diagnosed at a later stage leading to a significantly poor prognosis [8]. Standard chemoradiation treatments are not applicable for FA due to their hypersensitivity to DNA-cross-linking agents, which can also harm normal cells [11]. Therefore, early detection of cancer or its immediate precursor lesions, such as high-grade oral epithelial dysplasia is crucial for successful treatment [8].

In a study involving 713 FA patients, Velleuer et al. [12] demonstrated that brush biopsy-based cytology, including DNA ploidy analysis, is a highly accurate first-level diagnostic tool for detecting visible (pre) malignant oral lesions in FA patients. Moreover, patients diagnosed in the early stages show excellent survival, proving that early detection improves quantity and quality of life. The detection of DNA aneuploidy using interactive DNA image cytometry is strongly associated with malignant transformation and is detectable in oral cancers and oral potentially malignant disorders (OPMDs), that show malignant progression [13]. Nonetheless, the interactive (i.e., manual) DNA image cytometry analysis is time-consuming and demands up to 60 minutes for a complete DNA ploidy analysis.

This problem may be overcome with the introduction of DNA ploidy analysis via Artificial intelligence (AI)-assisted DNA-KM, which enables a semi-automated or automated analysis of liquid-based cytological samples [14]. Similar to interactive DNA image cytometry, DNA-KM enables precise quantification of the nuclear DNA content. However, it further incorporates digital nuclear classifiers, which are developed through expert-based classification of nuclear images and machine learning algorithms [15]. The complete process of slide scanning in different focal planes, segmentation of nuclei, and measurement of the DNA content is performed autonomously, reducing the investigator’s workload. DNA-KM automatically classifies various cell types, including normal squamous cells, granulocytes, lymphocytes, abnormal cells, or defocused nuclei and artifacts, and presents them in an image gallery [16]. The workload for cytotechnicians or cytopathologists is reduced by verifying the accuracy of the automated classifications, and when necessary, reclassifying the nuclei or artifacts. This approach allows for the analysis of a greater number of cells across the entire cytological slide, compared to interactive DNA image cytometry.

The present study aims to evaluate the diagnostic accuracy of DNA ploidy analysis using DNA-KM for the detection of (pre) malignant oral lesions in patients with FA. In addition, a combined statistical analysis was conducted, integrating the results from DNA-KM with those from liquid-based oral cytology.

The early and non-invasive diagnosis of oral (pre) cancer is essential for increasing the chances of survival and avoiding overdiagnosis for patients with FA. Velleuer et al. [12] demonstrated the high accuracy of brush biopsy-based cytology and DNA ploidy analysis using manual DNA image cytometry to detect OPMDs in FA patients who are at high risk for malignant transformation, and therefore, warrant treatment. However, manual DNA image cytometry is time-consuming and needs specialized personnel (cytopathologists or cytotechnicians), which may not be available in every country. Consequently, its practical application is limited to those cytological samples with inconclusive results, i.e., those diagnosed as “atypical” or “suspicious”, as also applied by Velleuer et al. [12]. Additionally, the production of existing manual DNA image cytometry devices has ceased, and the development of new ones has not progressed. Implementing an automated, AI-assisted alternative to manual DNA image cytometry could help to overcome these issues. The automated scanning process and detection of different types of cells using expert-trained classifiers and machine learning algorithms enable the evaluation of the entire slide. Moreover, it enables the evaluation of more samples, including those with a negative cytological result. This may help to reduce the occurrence of false-negative cytology. In this study, out of the nine liquid-based samples with false negative cytology, four showed a positive DNA-KM result. Our study on oral liquid-based cytological specimens aimed to validate the DNA-KM with the MotiCyte-auto for identifying OPMDs in a high-risk population, warrants further clinical intervention. As already shown for manual DNA ploidy analysis with DNA image cytometry [25] DNA-KM may also be useful in early detection of oral cancer in the common population.

Our study achieved a sensitivity and a specificity of 69% and 96%, respectively (Table 2) for the diagnosis of OPMDs that show at least a high-grade oral epithelial dysplasia but more often an OSCC in the follow-up. In comparison with the cytological diagnosis, the specificity is 18% higher and sensitivity is only 3% lower. This result is only surpassed by the combined application of cytology and DNA-KM (when DNA-KM results replace negative and atypical cytology), which shows the same specificity (96%) but a 6% higher sensitivity (75%). Accordingly, based on our data, the additional application of DNA-KM is most valuable in negative and atypical cytology. In comparison, its application subsequent atypical cytology only has a lower sensitivity of 63% but a slightly higher specificity of 98%. Because all suspicious and positive cytological specimens have a positive follow-up, an additional DNA-KM would have no beneficial effect in these cases.

Other automated DNA cytometry systems have already been tested in the diagnosis of OPMDs.

In a study using the automated iClearCyte® system, Parfenova et al. [26] found a sensitivity of 100% and a specificity of 86.7% for the screening of high-grade oral lesions. This study, however, had a lower number of test samples (30 controls and 35 abnormal samples) and excluded samples with histopathologically confirmed mild to moderate oral epithelial dysplasia. In measurements with the iClearCyte, the mean DNA amount is adopted as the DNA Index (DI) of a diploid cell population to calibrate the DI of other cells. The cells were categorized according to the DI into diploid (0.85 $\le$ DI 1.15), hyperdiploid (1.15 $\le$ DI 1.7), tetraploid (1.7 $\le$ DI 2.3), or aneuploid (2.3 $\le$DI). Accordingly, the definition of DNA aneuploidy is different, and the results are not directly comparable to the DNA ploidy measurements in our study.

Most recently, a successor of the MotiCyte auto system, the EasyScan-AI (Motic China Group, Ltd., Xiamen, PR China) was tested with 92 liquid-based oral brush biopsy samples from FA individuals by Böcking et al. (2022) [15]. Notably, the specimens analyzed overlapped with those included in the present study. Similar to the Moticyte auto system, the nuclear classification is based on random forest classifiers and supervised machine learning techniques. Under stringent criteria for defining DNA aneuploidy, they report a sensitivity of 35% and a specificity of 94.4%. With defining $>$4% abnormal nuclei as “suspected malignancy” as a less stringent criterion, the diagnostic accuracy to detect at least a high-grade OED is further enhanced up to 72% sensitivity and 98.5% specificity.

Using exfoliative cytology with cytobrushes for the collection of cells from OPMD, Ma et al. [27] found a sensitivity of 86.36% and a specificity of 90% for the detection of histologically proven severe dysplasia or neoplasia with an automated DNA image cytometer (Wuhan Landing Medical High-tech Co., Ltd., China). This study used the same stemline DNA ploidy interpretation as adopted in our study, but 5c exceeding events are applied to indicate DNA single-cell aneuploidy.

Earlier results from our group, published by Velleuer et al. [12] applying a manual DNA image cytometer reported a sensitivity of 89.5% and a specificity of 93.4% when suspected DNA aneuploidy was considered as a negative test result in the combined evaluation with cytology. If suspected DNA aneuploidy was considered a positive test result, the sensitivity was 100% and the specificity 92.2%. As indicated above, the manual DNA ploidy analysis was applied almost exclusively to samples, that had “atypical” or “suspicious” cytological diagnoses. In comparison, our study has 75% and 96% sensitivity and specificity in the combined analysis of DNA-KM and cytology, respectively, including the analysis of all cytologically negative samples. The lower sensitivity in our present study is not expected because some of the brush biopsy-based samples analyzed are shared in both studies. However, in our previous study, reported by Velleuer et al. [12], often a conventional smear and several cytospins of liquid-based cytological preparations were available from a single lesion. The highest-grade cytological diagnosis of all these slides was always correlated with the follow-up findings. This procedure was labor-intensive but may have led to improved cytological results compared to the sole utilization of one liquid-based cytospin slide as in our present study. Besides that bias, others are conceivable like incorrect classification by the machine classifier that has been overlooked during the “safety net” validation process of the cytopathologist. Several thousands of automatically classified nuclear images must be checked during this procedure with a focus on relevant contents in the regions of the 9c exceeding events and aneuploid stemlines. Another bias may be a possible inconsistency of the Feulgen stain of different cytological preparations and different points in time of the Feulgen stain or the DNA ploidy analysis. Effects of an inconsistent Feulgen stain during manual and automated DNA ploidy analysis can be overcome by adherence to the reported guidelines for quality assurance [21]. A significant problem in our hands is the decline of the Feulgen stain in archived materials as observed in more than 30 years of DNA-ploidy analysis in our institution. Although we often use the same slides for manual and automated DNA ploidy analysis as mentioned above, the time points differ and thus an irregular attenuated Feulgen stain may have affected the automated analyses. In addition, it is known that storage may result in different intensities of the Feulgen stain of simultaneously stained specimens, that warrant the correct application of internal reference cells [28].

DNA image cytometry, whether performed using a manual cytometer or with automated devices aids in differentiating reactive lesions (inflamed or regenerating tissues) from (pre) malignant lesions in cytology. Both methods require a minimum of atypical cells to detect malignant clones. However, liquid-based or conventional cytological preparations from oral brushings often contain many normal squamous epithelial cells and white blood cells along with a few atypical cells. This scarcity may make it difficult to identify a stemline of cells with similar DNA content. To address this issue, we propose less stringent criteria for the detection of DNA aneuploidy referred to as “suspected DNA aneuploidy”. In our study, we use this category if an aneuploid DNA stemline consists of only a few cells (60 cells) and/or if single nuclei with a DNA content of $>$9c present a non-suspicious microscopic nuclear morphology in the Feulgen-stain.

To establish an objective parameter that can distinguish samples with a positive or negative reference standard for those that do not meet the standard criteria of DNA aneuploidy, we analyze the variation coefficient to define a “broad peritetraploid stemline” (BPS). We found a significant difference (p = 0.01164) between the mean CVs of samples with negative and positive reference standards (Table 3). Using the ROC curve, we determined that a CV $\ge$5.83 serves as the best cutoff for predicting a positive reference standard. This BPS definition correctly classifies 5 out of 10 otherwise false negatives as positive, resulting in a 15% increase in the sensitivity of DNA-KM (from 69% to 84%) (Table 4). However, the specificity slightly decreases (from 96% to 92%) due to the detection of 12 additional false positive cases.

In summary, the calculation of the CV of peritetraploid stemlines and establishing a cutoff for positive and negative test results enhances the diagnostic accuracy of DNA-KM compared to the traditional criteria for DNA aneuploidy (Table 3). This could also serve as an additional objective criterion in measurements with suspected single-cell DNA aneuploidy.

While our study focuses on the utility of automated DNA ploidy analysis for routine diagnostics, it does not allow us to define the biological significance of BPSs. However, in certain samples, a considerable number of cells within a peritetraploid stemline, but outside the limits of 3.6c and 4.4c (4c $\pm$ 10%) raises suspicion of an underlying malignant process. Tetraploidy can occur in benign processes such as tissue repair, inflammation, and/or infection leading to p53 stabilization, resulting in the suppression of proliferation of the tetraploid cells [29, 30, 31]. However, in the case of p53 inactivation, aneuploidy can emerge from these processes [32].

In short, there is evidence suggesting that tetraploidy can promote chromosomal instability. Tetraploid cells often possess supernumerary centrosomes and may be halted in the cell cycle by tetraploidy checkpoint under normal conditions [33]. In instances of mutated TP53, these cells progress through the cell cycle, leading to catastrophic mitotic failures that result in the loss of genomic material and subsequent aneuploidy. TP53 alterations are present in most FA-associated head and neck cancers [34]. A tetraploid state poses challenges for cell survival as tetraploid cells are likely to lose chromosomal material due to replication stress and chromosome missegregation during mitosis. This process can lead to a near tetraploid state, which carries a higher risk of chromosomal instability and malignant transformation [35]. Furthermore, subtetraploid cell populations have been linked to increased metastatic prevalence in colorectal cancer [36], primary renal cell carcinomas [37], and lung cancer [38]. Research by Wangsa et al. [39] indicated that despite their proliferative disadvantages due to replication stress-induced S-phase delays, subtetraploid clones exhibit increased migratory and invasive capacities. Our BPS concept captures this dynamic instability by identifying cell populations ranging from 3c to 5c, predominantly tetraploid—reflecting the expected patterns of ongoing chromosomal missegregation in unstable subtetraploid cells. Consequently, a BPS may reflect chromosomal instability and genomic alterations such as amplifications or deletions, as opposed to reactive tetraploidy caused by inflammation or tissue repair.

In conclusion, this study demonstrates that DNA-KM with automated slide-scanning and AI-assisted classification of nuclei, can significantly enhance the accuracy of brush biopsy-based cytological diagnosis of OPMD in patients with FA. The implementation of cutoffs based on CVs of broad peritetraploid stemlines significantly improves diagnostic precision. However, future prospective studies are needed to validate these findings.

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

MS conceptualized and designed the research study. BESA and LH performed the DNA ploidy analysis. BESA, MS and IKSAA analyzed the data. MS and NP did the cytopathological diagnosis. BESA and MS wrote the manuscript. MS, RD and EVC administrated the project and acquired the funds. RD and EVC were responsible for providing the samples and patient data, and also contributed critical clinical insights and played a key role in data analysis, substantially shaping the study’s interpretation. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

The study was conducted in accordance with the 1964 Declaration of Helsinki and later amendments and approved by the Western Institutional Review Board® (WIRB - Puyallup, WA, USA) prior to its initiation (number of study: 1139633). The participants gave informed consent for additional DNA ploidy analysis.

The authors express their gratitude to all individuals with Fanconi Anemia who contributed to this research. Significant contributions were provided by Christine Krieg and Marleen Schmitt from the German Fanconi Anemia Support Group. The authors extend their sincere appreciation to Dr. Leonid Berynskyy for his sustained project support, extensive expertise with the MotiCyte system, and numerous DNA-ploidy analyses, as well as to Irene Esposito from the Institute of Pathology, Heinrich Heine University of Düsseldorf for her comprehensive assistance.

This research was funded by the Fanconi Cancer Foundation, previously known as the Fanconi Anemia Research Fund (FARF), and the German Fanconi Anemia Support Group. Author Bruno Eduardo Silva de Araujo received authorization from the CAPES Foundation under the Brazilian Ministry of Education to extend his residency at Heinrich Heine University Düsseldorf and conduct this investigation following a 4-year scholarship award (2014–2018) (BEX: 99999.0013111/2013-01).

Bruno Eduardo Silva de Araujo, Isabela Karoline de Santana Almeida Araujo and Martin Schramm report grants from German Fanconi Anemia Support Group during the conduct of the study. Eunike Velleuer-Carlberg reports grants from German Fanconi Anemia Support Group and grants from Fanconi Anemia Research Fund during the conduct of the study. Until July 2019, Ralf Dietrich was managing director of the German Fanconi Anemia Support Group and reports grants from Fanconi Anemia Research Fund during the conduct of the study. Natalia Pomjanski and Leonie Hirner have nothing to disclose.

Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.31083/FBE38747.