Tissue-based genomic instability markers for predicting malignant transformation in oral leukoplakia and proliferative verrucous leukoplakia: a systematic review

Abstract

Objectives:

Although several biomarkers have been described for predicting malignant transformation in oral leukoplakias (OLs) and proliferative verrucous leukoplakias (PVLs), no systematic review has comprehensively evaluated tissue-based genomic instability markers. This review aimed to evaluate the evidence for these markers and their potential role in biomarker panel development.

Methods:

A systematic review across PubMed, Embase and Cochrane Library was performed to identify studies evaluating the differences in tissue-based genomic markers between OL and PVL patients with and without malignant transformation.

Results:

34 observational studies comprising 3,237 patients were included, and genomic aberrations were categorised into DNA-level, chromosomal, and gene-specific alterations. For studies on OLs, DNA-level and chromosomal markers for which individual studies reported associations with malignant transformation included aneuploidy, impaired DNA repair capacity, loss of heterozygosity, chromosomal instability, and copy number alterations. Multiple gene-specific alterations also showed associations (e.g., TP53, MKI67, FGFR1), but findings varied across studies. The genomic markers of PVLs differed substantially, with fewer consistent predictors found. No meta-analysis was performed as all included studies were observational.

Conclusions:

Genomic instability across multiple levels contributes to malignant transformation, and represents a promising biological framework for predicting malignant transformation for OLs. While no single marker reliably demonstrates sufficient predictive performance, the integration of complementary genomic alterations with clinical and histopathological risk factors may provide a basis for the development of robust multi-marker panels. Future prospective studies using standardised detection methods and multivariable prediction models are required before clinical implementation.

Systematic Review Registration:

identifier CRD42024585830.

1 Introduction

Oral cancer is the sixth most common cancer in the world, with an estimated incidence of more than 370,000 cases and a mortality rate of more than 177,000 individuals annually (1, 2). Oral squamous cell carcinoma (OSCC) accounts for more than 90% of oral cancers (3), and despite advancements in surgery, radiotherapy and chemotherapy alone or in combination, lip and oral cavity cancers remain among the top global causes of death, with the largest number of increases between 2000 and 2023 (4). The 5-year overall survival rate and disease-free survival rates for OSCC have remained at 60% and 50% respectively in recent years, and almost every second patient has postoperative recurrence or metastasis even after radical surgery (5).

The aggressive nature and high mortality associated with OSCC underscore the necessity of early diagnosis and risk stratification. The search for early indicators invariably leads to the study of oral potentially malignant disorders (OPMDs). Oral leukoplakia (OL), one of the most common OPMDs, is defined by the World Health Organisation (WHO) as a predominantly white plaque of questionable risk, having excluded other known diseases that carry no increased risk for cancer (6). It has a worldwide prevalence of 4.11% (7), a malignant transformation rate of 9.8% (95% CI: 7.9–11.7), and a mean evolution time of 3.2 years. While non-homogeneous OL has four times the risk of malignant transformation compared to homogeneous OL (8), the proliferative verrucous leukoplakia (PVL) subtype, defined as a progressive, persistent, and irreversible disorder characterised by the presence of multiple leukoplakias that frequently become warty, is notorious for its increased risk for malignant transformation, with a transformation rate of 45.8% reported (9).

Clinical and demographic risk factors for malignant transformation include lesion size and location, female gender, betel quid or tobacco use, and exposure to nickel (8). Histopathologic assessment by the presence of dysplasia has been considered (10). However, the grading of dysplasia alone may not be entirely sufficient to deduce the risk of malignant transformation. A large cohort study by Hsue et al. found only 4.83% of dysplastic oral leukoplakias (OLs) subsequently progressed to OSCC, and 3.55% among non-dysplastic OLs over a mean follow-up time of 42.6 months (11). Furthermore, the grading of dysplasia is subjective and requires standardisation (6). Hence, the challenge lies especially in the identification of high-risk lesions with little to no dysplasia, with an ever-present clinical dilemma between wide surgical excision and surveillance needs.

Genomic instability represents a fundamental hallmark of cancer and encompasses a wide spectrum of DNA, chromosomal or gene-specific alterations. These alterations collectively reflect progressive genomic derangement preceding malignant transformation, and may provide a foundation for the development of predictive marker panels. While previous reviews have evaluated the role of biomarkers in the malignant transformation of OLs, these reviews have largely investigated a broader range of biomarkers involved in various aspects of the hallmarks of cancer, and different sample types such as tissue, saliva or serum (12–14). Studies on genomic alterations have largely focused on specific parts of genomic instability, such as aneuploidy, loss of heterozygosity or specific genes (15, 16). Consequently, these prior studies provide limited insight into genomic instability as a unified biological process underlying malignant transformation or its potential utility in objective risk prediction.

To our knowledge, no systematic review has comprehensively synthesised tissue-based genomic instability markers specifically evaluated as longitudinal predictors of malignant transformation for oral leukoplakias (OLs) and proliferative verrucous leukoplakias (PVLs). This systematic review therefore aimed to evaluate the available evidence for tissue-based genomic instability markers associated with malignant transformation, and to identify promising candidates for biomarker panel development.

2 Materials and methods

2.1 Search strategy

A search was performed on 3 September 2024 and updated on 27 September 2025 and 1 August 2026 through the PubMed, Embase, and Cochrane Library databases. The search terms encompassed the following: (1) oral leukoplakia, (2) transformation or progression, and (3) genomic or genetic factors. The full search terms are shown in Supplementary Table S1. From the search results, duplicates were removed, and the articles were then screened by their titles and abstracts, followed by screening of the full-length articles for inclusion on Covidence by two team investigators (B.Q. and Y.Z.).

A manual search of the references of relevant articles was also done, and eligible articles were included. Disagreements were reconciled through discussion and mediation with a third team investigator (N.B.S.) to arrive at a consensus.

2.2 Inclusion and exclusion criteria

2.3 Data extraction

While a meta-analysis was planned to be done if possible, it was not performed due to the lack of sufficient studies for each domain and the heterogeneity of the studies' methods.

2.4 Quality assessment

Two authors (B.Q. and Y.Z.) performed the risk of bias assessment for each study independently. The Newcastle-Ottawa Scale for cohort studies was employed as part of the assessment for risk of bias for observational studies (18), with 7–9 stars being considered Low risk of bias, 4–6 stars considered Unclear risk of bias, and 0–3 stars considered High risk of bias. The Risk of Bias 2 (RoB 2) tool was employed for randomised controlled trials if any were to be included (19). Discrepancies were discussed with a third team investigator (N.B.S.) until a consensus was reached before the final compilation.

3 Results

A total of 1,855 records were identified through the database search, of which 34 studies fulfilled our inclusion criteria and were thus included in the review (Figure 1) (20–53). All studies included were observational, and none were clinical trials. A total of 3,237 patients were included, of which 3,131 patients (30 studies) presented with OL and 106 patients (five studies) presented with PVL. Of these, 622 of the OLs and 52 of the PVLs underwent malignant transformation, translating to a malignant transformation rate of 19.9% and 49.1% respectively, over a reported follow-up duration across studies of 5–300 months. A summary of the included studies' characteristics is shown in Table 1.

Figure 1

To align with the multifaceted nature of genomic instability, the genomic changes are classified into three major domains: DNA-level alterations, chromosomal alterations and gene-specific alterations. Details of these genomic alterations observed in the included cohorts are presented in Tables 2–4 for OL and Table 5 for PVL.

3.1 DNA-level alterations

Four studies involving 389 patients investigated the role of DNA-level alterations in the malignant transformation of OL (Table 2) (23, 30, 32, 46). Three studies investigated DNA ploidy status, all of which reported significant associations between aneuploidy and malignant transformation (23, 30, 46). The studies reported the presence of aneuploidy to have a poor to fair sensitivity of 54%–66.7%, specificity of 59%–77.3%, a positive predictive value (PPV) of 10.8%–26%, and a notably high negative predictive value of 83%–97.9%.

Two studies evaluated the role of damage repair capacity and pathways in the malignant transformation of OL (30, 32). Thomas et al. quantified DNA repair capacity using a bleomycin-induced Mutagen Sensitivity Assay (MSA) and reported a significantly increased proportion of hypersensitivity to bleomycin in OL with malignant transformation (p = 0.0001), with a sensitivity of 91.7% and a specificity of 84.0%. Farah et al. similarly found that DNA damage repair-related pathways were some of the most significantly affected pathways in patients with progressive OL.

Thomas et al. also investigated DNA telomerase activity. While a higher proportion of telomerase positivity was seen in progressive OL, the difference was not significant (p = 0.065). The authors also reported a sensitivity of 83.3% and a specificity of 46.2% for DNA telomerase activity.

3.2 Chromosomal alterations

Nine studies comprising 1,253 patients evaluated the role of structural aberrations at the chromosomal level in OL progression (Table 3) (20, 21, 24, 25, 27, 39, 41, 44, 52). These included loss of heterozygosity (LOH), microsatellite instability, chromosomal instability, fractional allelic loss, and copy number alterations/variations. LOH was evaluated in two studies (41, 52); Graveland et al. identified LOH at chromosome 9p to be significantly associated with malignant transformation, while Jiang et al. found LOH at 5q21–23 to be significantly different between progressive and non-progressive lesions. Jiang et al. also reported significant differences in mean fractional allelic loss between the two groups (p < 0.05).

Two studies evaluated the role of microsatellite instability (20, 52). Jiang et al. did not report high levels of microsatellite instability in any progressive OLs. Qurishi et al. found a higher proportion of patients with microsatellite instability in progressive lesions; although statistical analyses showed a significant association with malignant transformation, these analyses were in combination with other markers (p53 and cyclin D1). Chromosomal instability was studied by Siebers et al. who reported it as a strong marker of malignant transformation, with hazard ratios of 6.8–7.2 (44).

Copy number alterations (CNAs) and variations (CNVs) were investigated by five studies (21, 24, 25, 27, 39). Cai et al., Wils et al., Li et al. and Kil et al. reported significant associations between the number of CNAs/CNVs and CNA score and malignant transformation. The locations of these CNAs were highly variable between studies. Cai et al. and Wils et al. both reported significant copy number gains at chromosome 20, and losses at chromosomes 3, 8 and 13. Li et al. and Kil et al. reported different chromosomes with high occurrences of CNAs, and neither specified if these alterations were gains or losses. While Wils et al. did not find significant associations between the presence of CNAs and progression, Li et al. and Kil et al. reported a significantly higher proportion of samples with CNAs and CNVs in the progressive group over the non-progressive lesions. A full description of the regions reported to have copy number gains and losses is depicted in Table 3.

3.3 Gene expression-specific alterations

20 studies evaluated the role of gene alterations in 26 genes in the malignant transformation of OLs (Table 4). With seven studies, the p53 gene family was most commonly investigated (20, 24, 26, 41, 48, 50, 51). While five studies reported p53 overexpression as being associated with malignant transformation (20, 24, 41, 50, 51), two studies evaluating p53 by immunohistochemistry (IHC) did not confirm the associations between p53 expression and malignant transformation (26, 41). Moreover, while Monteiro et al. found no significant relationship between p63 and p73 and malignant transformation, Matsubara et al. reported a significantly higher ΔNp63-labelling index in progressed OLs (26, 48).

3.4 Proliferative verrucous leukoplakia

Three studies on PVLs investigated the role of DNA ploidy status on malignant transformation risk (Table 5) (23, 40, 49). None of the studies reported significant associations between aneuploidy and malignant transformation. However, Gouvêa et al. and Klanrit et al. did report a high prevalence of aneuploidy in PVLs with malignant transformation (80%–83.3%), compared to those without (50%) in Gouvêa et al's study (40, 49).

Six genes were investigated over three studies for associations with malignant transformation (34, 40, 53). While Chang et al. reported significantly higher progression rates in P53-positive PVLs, Upadhyaya et al. instead found low levels of P53-positivity in PVLs (34, 53). Increased CDKN1A and MCM2 gene expressions were reported to be significantly associated with malignant transformation, while the CDKN2A, MKI67 and GMNN genes were not.

3.5 Quality assessment

The risk of bias assessment was performed with the Newcastle-Ottawa Scale for cohort studies for all studies, as shown in Supplementary Table S2. Of the 34 studies included, 19 were found to have a Low risk of bias (7–9 stars), and 15 had an Unclear risk of bias (4–6 stars). None had a High risk of bias (0–3 stars).

4 Discussion

This systematic review, encompassing 34 studies with 3,131 oral leukoplakia (OL) patients and 106 patients with proliferative verrucous leukoplakia (PVL), confirms the presence of tissue-based genomic instability markers that are strongly associated with malignant transformation. Specifically, aberrations at the DNA, chromosomal, and gene expression levels appear sequentially or synergistically to drive progression. While no single marker was found to definitively predict malignant transformation, a combination of markers or a progression of instability can be key in identifying lesions with high malignancy risk.

4.1 DNA-level and chromosomal instability: the early drivers

Several types of DNA-level and chromosomal alterations were identified to be useful in identifying malignant transformation risk; these alterations often represent early major events that destabilise the genome. DNA ploidy status refers to the number of chromosome sets within a cell, with aneuploidy representing an abnormal number of chromosomes and DNA content. Aneuploidy is a hallmark of cancer that indicates genetic damage that drives carcinogenesis, and is an established prognostic factor in other cancers (54, 55). All studies evaluating DNA ploidy status in this review found significant associations between aneuploidy and malignant transformation. In particular, the high negative predictive value of up to 97.9% may indicate the potential use of DNA ploidy status to rule out a high malignant transformation risk and allow more conservative follow-up regimens for OL patients. However, it is insufficient as a ‘rule-in’ tool for definitive prophylactic wide excision.

The genomic instability indicated by aneuploidy is further compounded by more localised events, such as loss of heterozygosity (LOH). LOH, a mutation resulting in the loss of a copy of a DNA segment, is a common genetic event in carcinogenesis. A LOH event may result in the complete inactivation of essential genes, such as tumour suppressor genes, that favour cancer development. The two studies included in this review evaluating LOH both found significant associations between LOH and malignant transformation of OL. However, no common pattern was found between the two studies; while Graveland et al. identified associations with LOH at chromosome 9p, Jiang et al. found LOH at chromosome 5q, 6p, 6q and 11q instead.

Expanding from localised events like LOH, instability can also occur at the chromosomal level. Chromosomal instability (CIN) refers to alterations in chromosome number and structure during cell division, leading to widespread chromosomal abnormalities such as aneuploidy and LOH. It is a hallmark of cancer, with correlations with tumour stage and metastasis (56). Siebers et al. investigated the role of CIN in malignant transformation of OLs, and reported significant associations between the two, with hazard ratios of 6.8–7.2. The addition of image cytometry of in-situ hybridisation analysis for CIN may thus be indicative of high-risk OLs.

Beyond chromosomal alterations, impaired DNA repair mechanisms further exacerbate genomic instability to promote carcinogenesis. Thomas et al. utilised a bleomycin-induced mutagen sensitivity assay (MSA) to quantify the frequency of bleomycin-induced DNA breaks that indicate increased mutagen sensitivity and reduced DNA repair capacity, and reported significantly higher incidence of mutagen hypersensitivity in progressive OLs. The high sensitivity and specificity of 91.7% and 84.0% respectively may indicate its good applicability in differentiating at-risk lesions. Similarly, Farah et al. reported multiple DNA damage repair pathways to be significantly enriched in progressive OLs. This further highlights impaired DNA repair as a contributory factor to carcinogenesis, as defects in DNA repair pathways can lead directly to the accumulation of chromosomal and gene-specific aberrations.

4.2 Gene expression-specific alterations: mechanistic correlates

p53, also known as a “guardian of the genome”, is a critical tumour suppressor protein whose mutation is attributed to cancer development. Of the seven studies investigating p53, four reported significant associations between p53 mutation and malignant transformation of OL. Qurishi et al. only reported significant associations between p53, cyclin D1, and microsatellite instability coexpression and progression, while Nogami et al. did not perform any statistical analysis. Identification of p53 mutations by sequencing seems to correlate better with progression; Graveland et al. found significant associations between p53 and progression with sequencing but not immunohistochemistry (IHC), and Monteiro et al., who utilised IHC for detection, reported no significant associations. Therefore, in the consideration of p53 as a genomic marker, while sequencing incurs a higher cost than IHC, clinicians and pathologists should consider sequencing over IHC due to its potentially higher reliability in predicting malignant transformation.

Identifiable cancer stem cell markers may be good indicators of acquired malignant phenotypes that occur after the accumulation of initial genomic damage, characterised by invasion and stemness. Podoplanin and ALDH1 were identified by two studies each in this review to have significant associations with malignant transformation. As both of these markers are detected through IHC, the addition of IHC stains to include markers like podoplanin and ALDH1 may act as a simple risk stratification tool for malignant transformation risk.

While several other genes involved in cell cycle regulation (MKI67, FGFR1, EZH2), apoptosis (CASP8, BAX), oncogenic signalling pathways (NOTCH1, SMAD4, AXIN2), differentiation and invasion (SNAI1, TGM3), and stromal markers (PTHLH) were reported to be significantly associated with malignant transformation, these associations were only reported in one study each and have not yet been validated by other studies. Further studies should be conducted to investigate the applicability of these findings in other patient populations before implementation into clinical practice can be considered.

4.3 Contextualisation and clinical correlation

Dysplasia has traditionally been considered one of the key markers for predicting malignant transformation of OL (57). However, even as the current ‘gold standard’, the presence and grade of dysplasia are subjective, inconsistent and have poor specificity. While some studies in this review reported significant associations between dysplasia grade and OL progression, high malignant transformation rates of up to 31.9%–46.7% were still observed in lesions with low-grade dysplasia (22, 31). Furthermore, although initial univariate analyses reported dysplasia to be significantly associated with malignant transformation, multivariate analyses of several studies subsequently either indicated no or marginal associations, and instead found genomic alterations to be more independent predictors of progression (26, 33, 35). Thus, there should be strong consideration to incorporate genomic markers in conjunction with dysplasia for more robust risk evaluation, especially in lesions showing no or mild dysplasia that may, as a result, be falsely determined to be low-risk.

For translation into clinical practice, future research should not focus on identifying a single genomic marker, but on the development and validation of multi-marker genomic panels that combine the most prognostic DNA, chromosomal, and gene expression markers to provide a truly personalised risk assessment. For example, from the findings of this review, a panel combining DNA ploidy status, TP53 and podoplanin or ALDH1 is a strong candidate as a multi-marker panel, where the presence of aneuploidy, TP53 mutation and podoplanin or ALDH1 expression may help to identify a lesion where prophylactic surgery rather than surveillance should be chosen, although this requires prospective validation.

The tissue genomic profiles seen in the patients with PVLs included in this review differ greatly from those of the patients with OLs. No studies found significant associations between aneuploidy and malignant transformation. Similarly, while some gene expressions (MCM2, CDKN1A) were associated with progression, others, including TP53, showed no significant associations. This further reinforces the notion that PVL is a biologically separate entity from OL (58); with higher malignant transformation rates and few consistent clinical and histopathologic predictive factors, the management of PVLs would benefit from more aggressive early surgical intervention.

4.4 Strengths and limitations

This systematic review provides a comprehensive search and review of more than 3,200 patients over 34 studies in accordance with the PRISMA guidelines, and is registered on PROSPERO. Previous studies and reviews have focused on clinical predictors, broad biomarker inventories, or individual molecular pathways. In contrast, the present review systematically synthesises tissue-based genomic instability markers evaluated in longitudinal malignant transformation studies and integrates traditional cytogenetic markers with contemporary genomic profiling techniques to inform future biomarker panel development.

However, several limitations need to be discussed. The primary limitation lies in the heterogeneity between included studies. A wide variety of genomic alterations were studied, with few markers discussed across multiple studies. Even among markers evaluated across studies, such as p53, there were significant variations in detection methods and follow-up durations that make comparisons and meta-analyses between studies very challenging. Follow-up duration is also a key confounder for the outcome measure of malignant transformation; this lack of standardisation further limits the validity of the findings. Additionally, as not all samples of each study were successfully analysed for each genomic marker, several studies reported different sample denominators for some genomic markers compared to their reported sample size (20, 30, 39), potentially contributing to a smaller-than-anticipated sample size. Furthermore, all studies included were observational in nature, with no clinical trials. While some studies did perform analyses to account for other known risk factors such as a non-homogeneous appearance and dysplasia, the failure of many studies to control for these covariates limits the ability to determine if a genomic marker is independent of these known clinical predictors. Several included studies also originated from the same institutions or research groups (e.g., Bremmer et al., Graveland et al. and Wils et al.), and thus may have included partially overlapping patient cohorts to evaluate different genomic instability markers. These studies were retained to provide a comprehensive overview of the available literature, but this overlap should be considered when interpreting the strength of the above evidence due to potential for overrepresentation from certain populations. Finally, many gene-specific markers were evaluated in single studies and reported significant associations with malignant transformation, raising the possibility of publication or selective reporting bias, as studies with null findings may be less likely to be published. These findings should therefore be interpreted cautiously and require validation in larger, independent prospective cohorts.

It should also be noted that the malignant transformation rates reported in this review for both OL and PVL are higher than those described in previous studies. The malignant transformation rate of 19.9% for OL and 49.1% for PVL is higher than the 9.8% and 45.8% reported respectively in previous meta-analyses (8, 9). This is because some of the included studies follow a case-control design with the selection of only lesions with malignant transformation for analysis, hence over-representing the number of progressive lesions. Furthermore, for the PVL group, the malignant transformation rate calculated may not be accurate as the majority of samples were from one study (53), while the remaining studies contributed to only a minority of the sample size. More prospective studies with larger cohorts are warranted for the PVL group to obtain the most accurate estimation of its malignant transformation rate.

5 Conclusion

This systematic review highlights the key role of genomic alterations at the DNA, chromosomal and gene levels, and demonstrates potential for the use of some tissue-based genomic markers at each level to supplement current clinical and histopathological methods in determining the risk of malignant transformation for OL. While the results are promising, there is still a need for standardisation of detection methods (e.g., with a consensus gene panel or standardised cut-offs) and data reporting (e.g., follow-up duration) to further validate these findings.

References

• 1.

  SungHFerlayJSiegelRLLaversanneMSoerjomataramIJemalAet al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. (2021) 71(3):209–49. 10.3322/caac.21660

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 2.

  TranbyEPHeatonLJTomarSLKellyALFagerGLBackleyMet al. Oral cancer prevalence, mortality, and costs in medicaid and commercial insurance claims data. Cancer Epidemiol Biomarkers Prev. (2022) 31(9):1849–57. 10.1158/1055-9965.EPI-22-0114

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 3.

  MonteroPHPatelSG. Cancer of the oral cavity. Surg Oncol Clin N Am. (2015) 24(3):491–508. 10.1016/j.soc.2015.03.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 4.

  GBD 2023 Causes of Death Collaborators. Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990−2023: a systematic analysis for the Global Burden of Disease Study 2023. Lancet. (2025) 406(10513):1811–72. 10.1016/S0140-6736(25)01917-8

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 5.

  DongLXueLChengWTangJRanJLiY. Comprehensive survival analysis of oral squamous cell carcinoma patients undergoing initial radical surgery. BMC Oral Health. (2024) 24(1):919. 10.1186/s12903-024-04690-z

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 6.

  WarnakulasuriyaSJohnsonNWVan Der WaalI. Nomenclature and classification of potentially malignant disorders of the oral mucosa. J Oral Pathol Med. (2007) 36(10):575–80. 10.1111/j.1600-0714.2007.00582.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 7.

  MelloFWMiguelAFPDutraKLPorporattiALWarnakulasuriyaSGuerraENSet al. Prevalence of oral potentially malignant disorders: a systematic review and meta-analysis. J Oral Pathol Med. (2018) 47(7):633–40. 10.1111/jop.12726

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 8.

  Aguirre-UrizarJMLafuente-Ibáñez de MendozaIWarnakulasuriyaS. Malignant transformation of oral leukoplakia: systematic review and meta-analysis of the last 5 years. Oral Dis. (2021) 27(8):1881–95. 10.1111/odi.13810

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 9.

  PalaiaGBellisarioAPampenaRPippiRRomeoU. Oral proliferative verrucous leukoplakia: progression to malignancy and clinical implications. Systematic review and meta-analysis. Cancers (Basel). (2021) 13(16):4085. 10.3390/cancers13164085

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 10.

  BukovszkyBFodorJTóthEKocsisZSObernaFFerencziÖet al. Malignant transformation and long-term outcome of oral and laryngeal leukoplakia. J Clin Med. (2023) 12(13):4255. 10.3390/jcm12134255

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 11.

  HsueSSWangWCChenCHLinCCChenYKLinLM. Malignant transformation in 1458 patients with potentially malignant oral mucosal disorders: a follow-up study based in a Taiwanese hospital. J Oral Pathol Med. (2007) 36(1):25–9. 10.1111/j.1600-0714.2006.00491.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 12.

  HuangYZhangQGuoZDengGChenRZhengY. Potential noninvasive biomarkers for the malignant transformation of oral leukoplakia: a systematic review and meta-analysis. Cancer Med. (2023) 12(13):14718–30. 10.1002/cam4.6095

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 13.

  CelentanoAGlurichIBorgnakkeWSFarahCS. World workshop on oral medicine VII: prognostic biomarkers in oral leukoplakia and proliferative verrucous leukoplakia-A systematic review of retrospective studies. Oral Dis. (2021) 27(4):848–80. 10.1111/odi.13363

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 14.

  González-RuizISamayoa-DescampsVGuagua-CortezKAGonzález-MolesMÁRamos-GarcíaP. Hallmarks of cancer expression in oral leukoplakia: a scoping review of systematic reviews and meta-analyses. Cancers (Basel). (2025) 17(15):2427. 10.3390/cancers17152427

  • CrossRef
  • Google Scholar
  • View reference in article

• 15.

  OdellEW. Aneuploidy and loss of heterozygosity as risk markers for malignant transformation in oral mucosa. Oral Dis. (2021) 27(8):1993–2007. 10.1111/odi.13797

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 16.

  YuanJZhuYWangZLvZLiuW. Evaluating the diagnostic value and prospects of genomic and mutational sequencing in malignant transformation of oral leukoplakia. J Dent Sci. (2025) 20(4):2472–8. 10.1016/j.jds.2025.07.016

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 17.

  PageMJMcKenzieJEBossuytPMBoutronIHoffmannTCMulrowCDet al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Br Med J. (2021) 372:n71. 10.1136/bmj.n71

  • CrossRef
  • Google Scholar
  • View reference in article

• 18.

  WellsGAWellsGSheaBSheaBO'ConnellDPetersonJet al. The Newcastle-Ottawa scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. (2014).

  • Google Scholar
  • View reference in article

• 19.

  SterneJACSavovićJPageMJElbersRGBlencoweNSBoutronIet al. Rob 2: a revised tool for assessing risk of bias in randomised trials. Br Med J. (2019) 366:l4898. 10.1136/bmj.l4898

  • CrossRef
  • Google Scholar
  • View reference in article

• 20.

  QurishiAAMorsyMSMAtoutAMAbzoahSEWadaniMHMGhazwaniNHAet al. Evaluating the role of genetic markers in predicting oral leukoplakia malignancy transformation. J Pharm Bioallied Sci. (2025) 17(Suppl 2):S1153–5. 10.4103/jpbs.jpbs_1523_24

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 21.

  CaiXZhangJLiLLiuLTangMZhouXet al. Copy number alterations predict development of OSCC from oral leukoplakia. J Dent Res. (2024) 103(2):138–46. 10.1177/00220345231217160

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 22.

  MarizBALASales de SáRAraújoALDFernandesCIRMarianoFVSantos-SilvaARet al. FGFR1 Is an important prognostic factor in oral leukoplakia and tongue squamous cell carcinoma. J Oral Pathol Med. (2023) 52(2):119–26. 10.1111/jop.13398

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 23.

  PenteneroMCastagnolaPCastilloFVIsaevskaESuteraSGandolfoS. Predictors of malignant transformation in oral leukoplakia and proliferative verrucous leukoplakia: an observational prospective study including the DNA ploidy status. Head Neck. (2023) 45(10):2589–604. 10.1002/hed.27483

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 24.

  WilsLJPoellJBBrinkAEvrenIBrounsERDe VisscherJGAMet al. Elucidating the genetic landscape of oral leukoplakia to predict malignant transformation. Clin Cancer Res. (2023) 29(3):602–13. 10.1158/1078-0432.CCR-22-2210

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 25.

  JäwertFFehrAÖhmanJStenmanGKjellerG. Recurrent copy number alterations involving EGFR, CDKN2A, and CCND1 in oral premalignant lesions. J Oral Pathol Med. (2022) 51(6):546–52. 10.1111/jop.13303

  • CrossRef
  • Google Scholar
  • View reference in article

• 26.

  MonteiroLDo AmaralBDelgadoLGarcêsFSalazarFPachecoJJet al. Podoplanin expression independently and jointly with oral epithelial dysplasia grade acts as a potential biomarker of malignant transformation in oral leukoplakia. Biomolecules. (2022) 12(5):606. 10.3390/biom12050606

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 27.

  LiXLiuLZhangJMaMSunLLiXet al. Improvement in the risk assessment of oral leukoplakia through morphology-related copy number analysis. Sci China Life Sci. (2021) 64(9):1379–91. 10.1007/s11427-021-1965-x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 28.

  LiuWYaoYShiLTangGWuL. A novel lncRNA LOLA1 may predict malignant progression and promote migration, invasion, and EMT of oral leukoplakia via the AKT/GSK-3β pathway. J Cell Biochem. (2021) 122(10):1302–12. 10.1002/jcb.29951

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 29.

  LvZCongRLiJCaoKBaoQLiLet al. PTHLH Predicts the prognosis of patients with oral leukoplakia. Onco Targets Ther. (2020) 13:10013–23. 10.2147/OTT.S261124

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 30.

  ThomasGTrSGeorgeSPSomanathanTSarojamSKrishnankuttiNet al. Prognostic implications of DNA repair, ploidy and telomerase in the malignant transformation risk assessment of leukoplakia. Asian Pac J Cancer Prev. (2020) 21(2):309–16. 10.31557/APJCP.2020.21.2.309

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 31.

  BaranCAAgaimyAWehrhanFWeberMHilleVBrunnerKet al. MAGE-A expression in oral and laryngeal leukoplakia predicts malignant transformation. Mod Pathol. (2019) 32(8):1068–81. 10.1038/s41379-019-0253-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 32.

  FarahCSJessriMBennettNCDalleyAJShearstonKDFoxSA. Exome sequencing of oral leukoplakia and oral squamous cell carcinoma implicates DNA damage repair gene defects in malignant transformation. Oral Oncol. (2019) 96:42–50. 10.1016/j.oraloncology.2019.07.005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 33.

  DingXZhengYWangZZhangWDongYChenWet al. Expression and oncogenic properties of membranous Notch1 in oral leukoplakia and oral squamous cell carcinoma. Oncol Rep. (2018) 39(6):2584–94. 10.3892/or.2018.6335

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 34.

  UpadhyayaJDFitzpatrickSGIslamMNBhattacharyyaICohenDM. A retrospective 20-year analysis of proliferative verrucous leukoplakia and its progression to malignancy and association with high-risk human papillomavirus. Head Neck Pathol. (2018) 12(4):500–10. 10.1007/s12105-018-0893-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 35.

  WuXWangRJiaoJLiSYuJYinZet al. Transglutaminase 3 contributes to malignant transformation of oral leukoplakia to cancer. Int J Biochem Cell Biol. (2018) 104:34–42. 10.1016/j.biocel.2018.08.016

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 36.

  HabibaUHidaKKitamuraTMatsudaAYHigashinoFItoYMet al. ALDH1 And podoplanin expression patterns predict the risk of malignant transformation in oral leukoplakia. Oncol Lett. (2017) 13(1):321–8. 10.3892/ol.2016.5379

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 37.

  SakataJYoshidaRMatsuokaYNagataMHirosueAKawaharaKet al. Predictive value of the combination of SMAD4 expression and lymphocyte infiltration in malignant transformation of oral leukoplakia. Cancer Med. (2017) 6(4):730–8. 10.1002/cam4.1005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 38.

  ZhangXKimKYZhengZKimHSChaIHYookJI. Snail and Axin2 expression predict the malignant transformation of oral leukoplakia. Oral Oncol. (2017) 73:48–55. 10.1016/j.oraloncology.2017.08.004

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 39.

  KilTJKimHSKimHJNamWChaIH. Genetic abnormalities in oral leukoplakia and oral cancer progression. Asian Pac J Cancer Prev. (2016) 17(6):3001–6. doi: APJCP.2016.17.6.3001

  • Pubmed Abstract
  • Google Scholar
  • View reference in article

• 40.

  GouvêaAFSantos SilvaARSpeightPMHunterKCarlosRVargasPAet al. High incidence of DNA ploidy abnormalities and increased Mcm2 expression may predict malignant change in oral proliferative verrucous leukoplakia. Histopathology. (2013) 62(4):551–62. 10.1111/his.12036

  • CrossRef
  • Google Scholar
  • View reference in article

• 41.

  GravelandAPBremmerJFDe MaakerMBrinkACobussenPZwartMet al. Molecular screening of oral precancer. Oral Oncol. (2013) 49(12):1129–35. 10.1016/j.oraloncology.2013.09.005

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 42.

  LiuWWuLShenX-MShiL-JZhangC-PXuL-Qet al. Expression patterns of cancer stem cell markers ALDH1 and CD133 correlate with a high risk of malignant transformation of oral leukoplakia. Int J Cancer. (2013) 132(4):868–74. 10.1002/ijc.27720

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 43.

  RiesJVairaktarisEAgaimyABechtoldMGoreckiPNeukamFet al. The relevance of EGFR overexpression for the prediction of the malignant transformation of oral leukoplakia. Oncol Rep. (2013) 30(3):1149–56. 10.3892/or.2013.2545

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 44.

  SiebersTJHBergshoeffVEOtte-HöllerIKremerBSpeelEJMVan Der LaakJAWMet al. Chromosome instability predicts the progression of premalignant oral lesions. Oral Oncol. (2013) 49(12):1121–8. 10.1016/j.oraloncology.2013.09.006

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 45.

  RiesJAgaimyAVairaktarisEKwonYNeukamFStrassburgLet al. Evaluation of MAGE-A expression and grade of dysplasia for predicting malignant progression of oral leukoplakia. Int J Oncol. (2012) 41(3):1085–93. 10.3892/ijo.2012.1532

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 46.

  BremmerJFBrakenhoffRHBroeckaertMAMBeliënJAMLeemansCRBloemenaEet al. Prognostic value of DNA ploidy status in patients with oral leukoplakia. Oral Oncol. (2011) 47(10):956–60. 10.1016/j.oraloncology.2011.07.025

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 47.

  CaoWYounisRHLiJChenHXiaRMaoLet al. EZH2 Promotes malignant phenotypes and is a predictor of oral cancer development in patients with oral leukoplakia. Cancer Prev Res (Phila). (2011) 4(11):1816–24. 10.1158/1940-6207.CAPR-11-0130

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 48.

  MatsubaraRKawanoSKiyosueTGotoYHiranoMJinnoT. Increased ΔNp63 expression is predictive of malignant transformation in oral epithelial dysplasia and poor prognosis in oral squamous cell carcinoma. Int J Oncol. (2011) 39(6):1391–9. 10.3892/ijo.2011.1151

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 49.

  KlanritPSperandioMBrownALShirlawPJChallacombeSJMorganPRet al. DNA Ploidy in proliferative verrucous leukoplakia. Oral Oncol. (2007) 43(3):310–6. 10.1016/j.oraloncology.2006.03.016

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 50.

  MogiSKikegawaAHiranoYSakaiENakajimaYKusamaMet al. The abnormal expression of p53 protein is a predictive prognostic marker in oral leukoplakia. Asian J Oral Maxillofac Surg. (2003) 15(1):44–50. 10.1016/S0915-6992(03)80031-6

  • CrossRef
  • Google Scholar

• 51.

  NogamiTKuyamaKYamamotoH. Histopathological and immunohistochemical study of malignant transformation of oral leukoplakia, with special reference to apoptosis-related gene products and proliferative activity. Acta Otolaryngol. (2003) 123(6):767–75. 10.1080/00016480310000700b

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 52.

  JiangWWFujiiHShiraiTMegaHTakagiM. Accumulative increase of loss of heterozygosity from leukoplakia to foci of early cancerization in leukoplakia of the oral cavity. Cancer. (2001) 92(9):2349–56. 10.1002/1097-0142(20011101)92:9<2349::AID-CNCR1582>3.0.CO;2-I

  • Pubmed Abstract
  • Google Scholar

• 53.

  ChangKWLinSCKwanPCWongYK. Association of aberrant p53 and p21(WAF1) immunoreactivity with the outcome of oral verrucous leukoplakia in Taiwan. J Oral Pathol Med. (2000) 29(2):56–62. 10.1034/j.1600-0714.2000.290202.x

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 54.

  ZainiZMMcParlandHMøllerHHusbandKOdellEW. Predicting malignant progression in clinically high-risk lesions by DNA ploidy analysis and dysplasia grading. Sci Rep. (2018) 8(1):15874. 10.1038/s41598-018-34165-5

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 55.

  XuJHuangLLiJ. DNA Aneuploidy and breast cancer: a meta-analysis of 141,163 cases. Oncotarget. (2016) 7(37):60218–29. 10.18632/oncotarget.11130

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 56.

  BakhoumSFCantleyLC. The multifaceted role of chromosomal instability in cancer and its microenvironment. Cell. (2018) 174(6):1347–60. 10.1016/j.cell.2018.08.027

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 57.

  WarnakulasuriyaSAriyawardanaA. Malignant transformation of oral leukoplakia: a systematic review of observational studies. J Oral Pathol Med. (2016) 45(3):155–66. 10.1111/jop.12339

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 58.

  ArroyoEPérez SayánsMBravoSBDe Oliveira BarbeiroCParavani PalaçonMChamorro PetronacciCMet al. Identification of proteomic biomarkers in proliferative verrucous leukoplakia through liquid chromatography with tandem mass spectrometry. Lab Invest. (2023) 103(10):100222. 10.1016/j.labinv.2023.100222

  • Pubmed Abstract
  • CrossRef
  • Google Scholar