Precursor Lesions, Overdiagnosis, and Oral Cancer: A Critical Review

Despite the profession placing great emphasis on oral potentially malignant disorders (OPMDs) as a gateway for early recognition and consequently better outcomes for oral cancer, the death rates for lip and oral cavity cancer have remained stagnant for three decades. Evidence shows that only a small fraction of oral cancers are in fact preceded by OPMDs, and that most OPMDs have an annual transformation rate of less than 1%. As OPMDs encompass a very heterogeneous group of oral conditions, it could be argued that only patients with oral mucosal diseases bearing a substantial risk of malignant transformation warrant close surveillance and treatment, these include proliferative leukoplakia, erythroplakia, non-homogeneous leukoplakia, as well as diseases presenting with severe dysplasia at biopsy. In this narrative review, I discuss the intricate epidemiology of the malignancies that we colloquially refer to as oral cancer, explore the limitations of focusing on OPMDs to reduce the incidence and mortality of oral cavity cancer, and argue that a may-be cancer label represents overdiagnosis for most OPMDs.

Predicting Progression of Oral Lesions to Malignancy Using Machine Learning

OBJECTIVE

To use large-scale electronic health record (EHR) data to develop machine learning models predicting malignant transformation of oral lesions.

METHODS

A multi-institutional health system database was used to identify a retrospective cohort of patients with biopsied oral lesions. The primary outcome was malignant transformation. Chart review and automated system database queries were used to identify a range of demographic, clinical, and pathologic variables. Machine learning was used to develop predictive models for progression to malignancy.

RESULTS

There were 2192 patients with a biopsied oral lesion, of whom 1232 had biopsy proven oral dysplasia. There was malignant transformation in 34% of patients in the oral lesions dataset, and in 54% of patients in the dysplasia subset. Multiple machine learning-based models were trained on the data in two experiments, (a) including all patients with biopsied oral lesions and (b) including only patients with biopsy-proven dysplasia. In the first experiment, the best machine learning models predicted malignant transformation among the biopsied oral lesions with an area under the curve (AUC) of 86%. In the second experiment, the random forest model predicted malignant transformation among lesions with dysplasia with an AUC of 0.75. The most influential features were dysplasia grade and the presence of multiple lesions, with smaller influences from other features including anemia, histopathologic description of atypia, and other prior cancer history.

CONCLUSION

With diverse features from EHR data, machine learning approaches are feasible and allow for generation of models that predict which oral lesions are likely to progress to malignancy.

LEVEL OF EVIDENCE

3 Laryngoscope, 2022.

Expression of invadopodia markers can identify oral lesions with a high risk of malignant transformation

Oral squamous cell carcinoma (OSCC) is the most common malignant tumor of the oral cavity and is usually preceded by a range of premalignant tissue abnormalities termed oral potentially malignant disorders. Identifying malignant transformation is critical for early treatment and consequently improved survival and decreased morbidity. Invadopodia (INV) are specialized subcellular structures required for cancer cell invasion. We developed a new method to visualize INV in keratinocytes using fluorescent immunohistochemistry (FIHC) and semi‐automated images analysis. The presence of INV was used to determine the risk of malignant transformation. We analyzed 145 formalin‐fixed, paraffin‐embedded (FFPE) oral biopsy samples from 95 patients diagnosed as nondysplastic, dysplastic, and OSCC including 49 patients whose lesions transformed to OSCC (progressing) and 46 cases that did not transform to OSCC (control). All samples were stained for Cortactin, tyrosine kinase substrate with five SH3 domains (Tks5) and matrix metallopeptidase 14 (MMP14) using FIHC, imaged using confocal microscopy and analyzed using a multichannel colocalization analysis. The areas of colocalization were used to generate an INV score. Using the INV score, we were able to identify progressing lesions with a sensitivity of 75–100% and specificity of 72–76%. A positive INV score was associated with increased risk of progression to OSCC. Our results suggest that INV markers can be used in conjunction with the current diagnostic standard for early detection of OSCC.

Oral keratosis of unknown significance shares genomic overlap with oral dysplasia

OBJECTIVES

To identify molecular characteristics of keratosis of unknown significance and to nominate pathways of molecular progression to oral cancer. Our work could provide a rationale for monitoring and treating these lesions definitively.

METHODS

Patients with oral leukoplakia were eligible for our prospective observational study. We correlated alterations in cancer-associated genes with clinical and histopathologic variables (keratosis of unknown significance vs. moderate-to-severe dysplasia) and compared these alterations to a previously molecularly characterized oral cancer population.

RESULTS

Of 20 enrolled patients, 13 (65%) had evidence of keratosis of unknown significance, while seven (35%) had dysplasia. Nine patients (45%) developed oral cancer (4/13 with keratosis of unknown significance, 5/7 with dysplasia). At a median follow-up of 67 (range 22-144) months, median overall survival was significantly shorter for patients with dysplasia (hazard ratio 0.11, p = .02). KMT2C and TP53 alterations were most frequent (75% and 35%, respectively). There were molecular similarities between keratosis of unknown significance and dysplasia patients, with no significant differences in mutational frequency among genes with ≥15% rate of alteration.

CONCLUSIONS

Among patients with leukoplakia, both patients with keratosis of unknown significance and patients with dysplasia developed oral cancer. Molecular alterations between these two groups were similar at this sample size.

Activated checkpoint kinase 2 expression and risk for oral squamous cell carcinoma

BACKGROUND

Phosphoactivation of a DNA damage response molecule checkpoint kinase 2 (pChk2) may be a marker of oral epithelial cells that have entered the precancerous and squamous cell carcinoma (SCC) stages. We explored whether there was selective expression of pChk2 in precancerous lesions but not in nonneoplastic tissue of the oral mucosa.

EXPERIMENTAL DESIGN

In a retrospective cohort design, 96 biopsied clinical leukoplakias and erythroplakias with known subsequent progression to SCC were identified from 48 subjects and assigned as the cases group. Expression status of pChk2 was compared with that of the 97 leukoplakias and erythroplakias that did not progress to SCC (control groups) by immunohistochemical analysis. Included in both groups were lesions with histologically confirmed dysplasia and those that lacked histologic evidence of atypia.

RESULTS

Subjects with pChk2-positive but histology-negative (for atypia) lesions had an 8.6 times higher risk of developing SCC compared with those with pChk2-negative and histology-negative lesions. Overall, the presence of detectable pChk2 staining was able to identify lesions at risk of developing SCC within 3 years with a sensitivity of 85.2%, specificity of 74.2%, and predictive accuracy of 78.2% (odds ratio, 19.9; 95% confidence interval, 7.3-55.5).

CONCLUSION

This is the first study to include histologically nonatypical cases in the analysis of a putative biomarker for oral precancerous lesions. Our data show that pChk2 merits further investigation as a promising biomarker that can discriminate those lesions at risk for developing SCC, regardless of histologic evidence for atypia.