Biomarkers Correlating with the Development of Oral Squamous Cell Carcinoma from Leukoplakia

Biomarkers Correlating with the Development of Oral Squamous Cell Carcinoma from Leukoplakia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Biomarkers Correlating with the Development of Oral Squamous Cell Carcinoma from Leukoplakia Daniel Giglio, Divya Ganesh, Bishwa Prakash Bhattarai, Tine Merete Søland, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6688707/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract We here assessed protein biomarkers expressed in oral leukoplakia (OL) associated with the risk of transformation to oral squamous cell carcinoma (OSCC). Tissue specimen sections of OL transforming into OSCC (leuko-ca), the corresponding OSCC and OL not developing to OSCC (leuko-nonca) were analyzed with proteomics using nano-liquid chromatography-mass spectrometry, and immunohistochemistry was performed on identified biomarkers. The top enriched biological pathways in OL turning to OSCC within 5–26 months from diagnosis (short duration (SD)-leuko-ca) vs. leuko-nonca were Cytoplasmic translation, Gene expression and Ribosomal large subunit biogenesis. Kininogen-1, apolipoprotein E (apoE), collagen alpha-1(XVIII) chain, sortilin and perlecan were top down-regulated candidate biomarkers, while EEF1D was the top up-regulated biomarker in SD-leuko-ca compared with leuko-nonca. The expressions in OL and OSCC of kininogen-1, apoE, perlecan and EEF1D were confirmed by immunohistochemistry. The top enriched biological pathways in OSCC compared with leuko-ca were Skin development, Antigen processing and presentation of endogenous peptide antigen, Epidermis development, Keratinocyte differentiation, Antigen processing and presentation of peptide antigen via MHC class Ib, Antigen processing and presentation of peptide antigen and Immune response. In conclusion, we have identified biomarkers in OL correlating with the risk of malignant transformation where the immune system seems to play an important role. Biological sciences/Cancer/Oral cancer Biological sciences/Molecular biology/Proteomics Biological sciences/Cell biology/Mechanisms of disease Biological sciences/Cancer/Cancer screening oral potentially malignant disorder oral squamous cell carcinoma malignant transformation proteomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Oral leukoplakia (OL) is a white plaque in the oral mucosa and constitutes an oral potentially malignant disorder (OPMD) where one lesion out of ten develops into oral squamous cell carcinoma (OSCC) 1 , 2 . OL should therefore be closely monitored, biopsied to assess for dysplastic changes in the lesion or be surgically removed 3 . However, even after surgery in toto , 22% of OL may recur 4 . In particular, the non-homogenous phenotype is associated with recurrence, and recurrence is further associated with an increased risk of malignant transformation 4 , 5 . We showed recently that OL with high co-expression of p53 and p63 more often recurs 6 , which signals increased risk for malignant transformation. In addition to clinical features, dysplasia is also a known risk factor for malignant transformation of OL 7 , 8 . At present only a few biomarkers are known to identify OLs with a high risk of OSCC transformation. Studies show that OLs with high expression of p53, podoplanin, ki67 or enhancer of zeste homolog 2 (EZH2) are associated with malignant transformation 9 – 13 . However, while most studies have assessed the relationship between biomarkers in OPMD and oral squamous cell carcinoma (OSCC), only a few longitudinal studies have examined the global expression of protein biomarkers associated with the development of OSCC from OL. Genomics, transcriptomics, proteomics and metabolomics are important tools to identify biomarkers associated with the development of malignant transformation of OPMD 14 . With transcriptomics, fibronectin 1, STAT1 and members of the collagen family were identified to be associated with malignant transformation from OL 15 . With proteomics, L-lactate dehydrogenase A chain, plectin, WD repeat-containing protein 1, thioredoxin 1, spectrin alpha chain and nonerythrocytic 1 were identified as proteins changing their expression linearly from normal mucosa, to OL and to OSCC 16 . In the present study using global proteomics on diagnostic biopsy specimens, we examined and compared the proteome in OL at the timepoint of OL diagnosis between OL that eventually transformed into OSCC with OLs not transforming to OSCC during a period of up to five years. Methods Cohort of patients with OL and OSCC The present study was approved by Clinical Directors at participating clinics in Region Västra Götaland and Region Uppsala, Sweden, and by the Regional Ethical Review Board in Gothenburg, Sweden (Dnr. 673–10, T864-11). Informed consent was obtained from all study participants and the study was conducted in accordance with Swedish law and with the tenets of the Declaration of Helsinki. Patients included in the study were part of a prospective, longitudinal multicenter study (ORA-LEU-CAN study) where patients diagnosed with OL were followed every three months for two years and then every six months for three years and treated according to the standard of care. All included patients in the present study had a clinical diagnosis of OL, a histopathological diagnosis of hyperkeratosis with or without dysplasia and a follow-up time of ≥5 months between the primary biopsy and OSCC transformation. Included in the study were 12 patients with OL not developing to OSCC (leuko-nonca) during a follow-up period of up to five years (2 patients followed for 15 months and 10 patients followed for 60 months) and 10 patients with OL developing OSCC (leuko-ca) during a follow-up time of 5-54 months. Biopsies of OL at baseline at the time of diagnosis were taken and biopsies from the OSCC developing in the corresponding area of the OL were taken and examined. The analysis was performed from formalin-fixed paraffin-embedded tissue specimens stored at the Department of Pathology, Sahlgrenska University Hospital, Gothenburg. Patients´ characteristics are presented in Table 1-3. Table 1. Patients´ characteristics. OSCC Transforming leukoplakia Non-transforming Leukoplakia N N N Patients 10 10 12 Age (years) Mean 59 59 57 Median 59 59 59 Gender Male 3 3 6 Female 7 7 6 Histopathological grading Benign hyperkeratosis - 4 5 Mild dysplasia - 3 2 Moderate dysplasia - 1 5 Severe dysplasia - 2 0 Well differentiated OSCC 1 - - Moderately differentiated OSCC 3 - - Poorly differentiated OSCC 0 - - Not specified OSCC 6 - - Site of lesion Floor of the mouth 1 1 1 Buccal mucosa 1 1 1 Tongue 7 7 8 Gingiva 0 0 1 Hard palate 1 1 1 OSCC: oral squamous cell carcinoma Table 2. Characteristics of patients with malignant transformation of leukoplakia Patient No. Age at diagnosis (years) Gender Site of leukoplakia Presence of dysplasia Site of tumour Time to malignant transformation (months) 1 28 Female Tongue Yes Tongue 32 2 56 Female Tongue No Tongue 26 3 79 Male Buccal mucosa Yes Buccal mucosa 12 4 31 Male Tongue Yes Tongue 18 5 72 Female Tongue No Tongue 54 6 89 Female Hard Palate No Hard palate 36 7 56 Male Floor of the mouth Yes Floor of the mounth 47 8 62 Female Tongue Yes Tongue 10 9 44 Female Tongue Yes Tongue 18 10 71 Female Tongue No Tongue 5 Table 3. Characteristics of patients without malignant transformation of leukoplakia Patient No. Age at diagnosis (years) Gender Site of leukoplakia Presence of dysplasia Follow-up time (months) 1 53 Female Tongue Yes 15 2 40 Male Tongue Yes 60 3 69 Female Buccal mucosa No 60 4 28 Male Tongue yes 60 5 77 Female Tongue No 60 6 65 Female Floor of the mouth No 15 7 40 Male Tongue Yes 60 8 56 Female Tounge Yes 60 9 71 Male Tounge Yes 60 10 62 Female Hard palate No 60 11 52 Male Tongue Yes 60 12 65 Male Gingiva No 60 Preparation of tissue samples Ten to 15 sections à 4 mm of thickness per tissue biopsy were deparaffinated after treatment with xylene and dehydrated in absolute ethanol according to a standardized protocol. The retrieved pellets were used for proteomic analysis. S ample preparation The proteomic analysis was performed at the Proteomics Core Facility at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. Proteins were extracted using lysis buffer (50 mM triethylammonium bicarbonate (TEAB) and 2% sodium dodecyl sulfate (SDS)) and the protocol for FFPE scrolls on the ML430 Covaris instrument, according to manufacturer instruction. The protein concentration was determined using Pierce BCA Protein Assay (Thermo Scientific). The samples and references (representative pool containing aliquots from all groups) were digested using modified filter-aided sample preparation (FASP) method 17 . In short, samples (25 µg) were reduced with 100 mM dithiothreitol at 60°C for 30 min, transferred to Microcon-30kDa Centrifugal Filter Units (Merck), washed several times with 8 M urea and once with digestion buffer (DB, 50 mM TEAB, 0.5% sodium deoxycholate (SDC)) prior to alkylation with 10 mM methyl methanethiosulfonate in DB for 30 min in room temperature. Samples were digested with trypsin (Pierce MS grade Trypsin, Thermo Fisher Scientific, ratio 1:100) at 37°C overnight and an additional portion of trypsin was added and incubated for another two hours. Peptides were collected by centrifugation and labelled using TMTpro 18-plex isobaric mass tagging reagents (Thermo Fisher Scientific) according to the manufacturer instructions. The samples were combined into two TMT-set and SDC was removed by acidification with 10% TFA. The TMT-sets were further purified using High Protein and Peptide Recovery Detergent Removal Spin Column and Pierce peptide desalting spin columns (both Thermo Fischer Scientific) according to the manufacturer instructions prior to basic reversed-phase chromatography (bRP-LC) fractionation. Peptide separation was performed using a Dionex Ultimate 3000 UPLC system (Thermo Fischer Scientific) and a reversed-phase XBridge BEH C18 column (3.5 μm, 3.0x150 mm, Waters Corporation) with a gradient from 3% to 100% acetonitrile in 10 mM ammonium formate at pH 10.00 over 23 min at a flow of 400 µL/min. The 40 fractions were concatenated into 20 fractions, dried and reconstituted in 3% acetonitrile, 0.2% formic acid. Nano-liquid chromatography-mass spectrometry (LC-MS) analysis Each fraction was analysed on Orbitrap Fusion™ Tribrid™ mass spectrometer interfaced with nLC 1200 liquid chromatography system (all Thermo Fisher Scientific). Peptides were trapped on an Acclaim Pepmap 100 C18 trap column (100 μm x 2 cm, particle size 5 μm, Thermo Fischer Scientific) and separated on an in-house constructed analytical column (350x0.075 mm I.D.) packed with 3 μm Reprosil-Pur C18-AQ particles (Dr. Maisch, Germany) using a gradient from 3% to 80% acetonitrile in 0.2% formic acid over 85 min at a flow of 300 nL/min. Precursor ion mass spectra were acquired at 120 000 resolution where the most intense doubly or multiply charged precursors were isolated in the quadrupole with a 0.7 m/z isolation window and dynamic exclusion within 10 ppm for 45 s. The isolated precursors were fragmented by collision induced dissociation (CID) at 35% collision energy and detected in the ion trap, followed by multinotch (simultaneous) isolation of the top 10 MS2 fragment ions for fragmentation (MS3) by higher-energy collision dissociation (HCD) at 55% collision energy and detection in the Orbitrap at 50 000 resolution m/z range 100-500. Proteomic Data Analysis The data files for each set were merged for identification and relative quantification using Proteome Discoverer version 2.4 (Thermo Fisher Scientific). The search was against Homo Sapiens (Swissprot Database Mars 2019) using Mascot 2.5 (Matrix Science) as a search engine with precursor mass tolerance of 10 ppm and fragment mass tolerance of 0.6 Da. Tryptic peptides were accepted with zero missed cleavage, variable modifications of methionine oxidation and fixed cysteine alkylation, TMT-label modifications of N-terminal and lysine were selected. Percolator was used for PSM validation with the strict FDR threshold of 1%. TMT reporter ions were identified with 3 mmu mass tolerance in the MS3 HCD spectra, and the TMT reporter abundance values for each sample were normalized on the total peptide amount. Only the quantitative results for the unique peptide sequences with the minimum SPS match % of 50 and the average S/N above 10 were taken into account for the protein quantification. The reference samples were used as denominator and for calculation of the ratios. The quantified proteins were filtered at 1% FDR and grouped by sharing the same sequences to minimize redundancy. Genetically OL would be closer to OSCC if OSCC is diagnosed short after OL diagnosis and genetically OL would be closer to OL not developing to OSCC if OSCC is diagnosed long after OL diagnosis. Therefore, leuko-ca was subdivided into two subgroups, i.e. , the first group denoted long duration leuko-ca (LD-leuko-ca) where OSCC was developed from OL 32-54 months after OL diagnosis (n=4) and the second group denoted short duration leuko-ca (SD-leuko-ca) where OSCC was developed 5-26 months after OL diagnosis (n=6). The cut-off in months between the two groups was set to have similarly equally sized groups and a gap in months between the two groups. String analysis, creation of volcano plots and Venn diagrams and identification of biomarkers To identify biological pathways of importance in OL and OSCC, the Search Tool for the Retrieval of Interacting Genes/Proteins (String) software (version 11.0) was used for where the confidence was set to medium (0.400) for the minimum interaction score 18 . The top 40 differently expressed proteins (DEPs; in either direction, i.e. , up- or down-regulated) or all DEPs with an absolute fold-change over 0.7 were included in the pathways analyses. In the volcano plots, the negative log10 of the p-value was plotted against the log2 fold change between groups of comparison. To identify proteins that were separated the most between groups, proteins with the longest distances from the origo of the volcano plot were identified (√ (x 2 + y 2 ). Only significantly DEPs expressed by more than 58% of samples in both groups were considered in the heat maps and String analyses. For any missing values, the average expression for the sample group was imputed. Graphpad Prism (version 10.4.2) was used to create volcano plots. The Perseus software (Perseus v2.1.4.0) was used to create heat maps by employing the squared Euclidean distance-based hierarchical clustering analyses 19 . The interactive tool Venny 2.1 was used to develop the Venn diagram (https://bioinfogp.cnb.csic.es/tools/venny/index.html). Immunohistochemistry Among the proteins showing significant differences in expression between SD-leuko-ca and leuko-nonca based on proteomics analysis, kininogen-1, apolipoprotein E (apoE), basement-membrane-specific heparan sulfate proteoglycan core protein (perlecan), and eukaryotic elongation factor 1 delta (EEF1D) were further analyzed using immunohistochemistry. Immunohistochemistry was performed on all 31 samples (12 leuko-nonca, four LD-leuko-ca, six SD-leuko-ca, and 10 OSCC). After retrieving formalin-fixed paraffin-embedded tissue blocks, 4 mm sections were cut and mounted on poly-l-lysine-coated slides. Sections were then heated at 60°C for two hours, followed by deparaffinization in xylene and rehydration in serial dilutions of ethanol. The sections were then immersed in 3% hydrogen peroxide in 70% methanol for quenching endogenous peroxidase. After washing the sections in water followed by phosphate-buffered saline (PBS, pH 7.4), epitope retrieval was performed in a decloaking chamber at 100°C for 15 minutes and at 90°C for 10 seconds. Citraconic anhydride (CCA) at pH 7.4 was used as the epitope retrieval solution. The sections were then cooled to room temperature and washed in PBS. Blocking, primary, and secondary antibody incubation steps are summarized in Table 4. Table 4. Details of blocking, antibody dilutions, and incubation times for immunohistochemistry. Blocking 45 min RT Primary antibody overnight incubation at 4°C Clone Isotype Dilution Manufactured by 2 nd antibody 1 hour incubation at RT 5% goat serum in 1% BSA Rabbit-anti-Kininogen 1 --x-- IgG 1/600 (0.17 µg/ml) Invitrogen Goat-anti-Rabbit IgG Bio (7.5 µg/ml) 5% horse serum in 1% BSA Mouse-anti-Apolipoprotein E D6E10 IgG1, k 1/200 (2.5 µg/ml) Abcam Horse-anti-Mouse IgG Bio (7.5 µg/ml) Mouse-anti-Perlecan 7B5 IgG1 1/50 (5 µg/ml) Invitrogen Mouse-anti-EEF1D OTI4B9 IgG1 1/250 (4 µg/ml) Invitrogen RT = room temperature; BSA = bovine serum albumin. After incubation with the secondary antibody, the sections were washed twice in PBS. The sections were then incubated with avidin-biotin-complex conjugated to horseradish peroxidase (ABC HRP ) for 30 minutes. 3, 3′-Diaminobenzidine (DAB) was used to visualize the epitopes, followed by nuclear counterstaining with Mayer’s hematoxylin. The sections were washed, dehydrated, and mounted with Histokitt mounting solution (Glaswarenfabrik Karl Hecht GmbH & Co, Söndheim v.d. Rhön, Germany). Sections incubated with PBS instead of the primary antibodies were used as internal negative controls. Images were acquired using a Nikon Digital Sight 10 camera mounted on a Nikon E90i microscope unit (Nikon, Japan) with 4X, 10X, and 20X magnifications. Based on the images, a qualitative assessment of protein expression was conducted, which included the area of positive staining in the epithelium and connective tissue, the intensity of positive staining, and the types of positively stained cells. Statistics All values from proteomics were logarithmized (base 2). The Student´s paired t-test was used to assess differences between groups. A p-value of less than 0.05 was considered statistically significant. Results In the OL and OSCC samples 5530 proteins were identified. The number of deregulated proteins between the different OL groups and OSCC are displayed in Fig. 1 A-B (full list of proteins in Supplementary file 1). The highest number of DEPs was between OSCC and leuko-nonca and the lowest number was between LD-leuko-ca and SD-leuko-ca (Fig. 1 A). Including all proteins present in > 58% of samples showed that 87 proteins were in common between leuko-nonca vs. SD-leuko-ca and leuko-nonca vs. OSCC and 229 proteins were in common between leuko-nonca vs. OSCC and SD-leuko-ca vs. OSCC but only 2 proteins were in common between leuko-nonca vs. SD-leuko-ca and SD-leuko-ca vs. OSCC (Fig. 1 B). SD-leuko-ca vs. leuko-nonca In SD-leuko-ca 130 proteins were upregulated and 102 proteins were down-regulated compared with leuko-nonca (Figs. 1 A-B). Including the top 40 DEPs in String analysis identified Collagen fibril organization, Regulation of very-low-density lipoprotein particle remodeling, Phospholipid efflux, Negative regulation of cholesterol transport, Extracellular matrix organization and Reverse cholesterol transport as enriched biological pathways in SD-leuko-ca compared with leuko-nonca (Fig. 2 A; full list presented in Supplementary file 2). Including all DEPs (absolute fold-change 0.12–1.19) identified Cytoplasmic translation, Gene expression, Ribosomal large subunit, Acute-phase response, Negative regulation of blood coagulation and Reverse cholesterol transport as top enriched biological pathways (Fig. 2 B-D; full list in Supplementary file 2). In SD-leuko-ca compared to leuko-nonca, proteins regulating cytoplasmic translation, gene expression and ribosomal large subunit were upregulated, while proteins regulating acute-phase response, negative regulation of blood coagulation, reverse cholesterol and collagen fibril organization were downregulated (Fig. 2 C). Kininogen-1, apoE, collagen alpha-1(XVIII) chain, sortilin, basement-membrane-specific heparan sulfate proteoglycan core protein, histone-lysine N-methyltransferase EHMT1, lanC-like protein 2, chloride intracellular channel protein 6, serine/threonine-protein phosphatase PGAM5, mitochondrial, elongation factor 1-delta, ATP-binding cassette sub-family F member 2 and apolipoprotein CII were the proteins significantly changed and the most distant from the origo on the volcano plot (Fig. 1 B and Fig. 3 ). Among these potential biomarkers, collagen alpha-1(VII) chain, sortilin, basement-membrane-specific heparan sulfate proteoglycan core protein and apolipoprotein CII were also significantly down-regulated and lanC-like protein 2, serine/threonine-protein phosphatase PGAM5, mitochondrial and ATP-binding cassette sub-family F member 2 were significantly up-regulated in OSCC compared with leuko-nonca (data not shown). Kininogen-1 tended to be down-regulated in SD-leuko-ca compared with leuko-nonca (p = 0.097). OSCC vs. leuko-nonca In OSCC 1284 proteins were upregulated and 184 proteins were down-regulated compared with leuko-nonca. By including the top 40 DEPs in String analysis we identified Collagen fibril organization, Skin development, External encapsulating structure organization, Collagen biosynthetic process, Supramolecular fiber organization and Extracellular matrix organization as enriched biological pathways in OSCC compared with leuko-nonca (Fig. 4 A; full list in Supplementary file 2). Including instead all DEPs (absolute fold-change > 0.7) in String analysis identified Antigen processing and presentation of endogenous antigen, Skin development, Antigen processing and presentation of endogenous peptide antigen, Antigen processing and presentation of peptide antigen, Supramolecular fiber organization and Peptide cross-linking as enriched biological pathways in OSCC compared with leuko-nonca (Fig. 4 B-D; full list in Supplementary file 2). In OSCC compared to leuko-nonca, proteins regulating antigen processing and presentation were upregulated, while proteins regulating skin development and peptide cross-linking were downregulated (Fig. 4 C). OSCC vs. Leuko-ca Serpin B9, cytosol aminopeptidase, small ubiquitin-related modifier 2, coactosin-like protein, interferon regulatory factor 9, cleavage stimulation factor subunit 2, tapasin, heat shock protein 105 kDa, damage-control phosphatase ARMT1, N-myc interactor, synembryn-A and sequestome-1 were the twelve DEPs the most significantly increased in OSCC compared with leuko-ca and the most distant from the origo of the volcano plot (Fig. 2 and Fig. 5 ). Including the top 40 DEPs in String analysis identified Establishment of skin barrier, Skin development, Epidermis development, Antigen processing and presentation of endogenous peptide antigen, Defense response to other organism and Keratinocyte differentiation as enriched biological pathways in OSCC compared with leuko-ca (Fig. 6 A; full list in Supplementary file 2). Including all DEPs (absolute fold-change > 0.7) in String analysis identified Skin development, Antigen processing and presentation of endogenous peptide antigen, Epidermis development, Keratinocyte differentiation, Antigen processing and presentation of peptide antigen via MHC class Ib, Antigen processing and presentation of peptide antigen and Immune response as enriched biological pathways in OSCC compared with leuko-ca (Fig. 6 B-D; full list in Supplementary file 2). In OSCC compared to leuko-ca, proteins regulating antigen processing and presentation and immune responses were upregulated, while proteins regulating skin and epidermis development and keratinocyte differentiation were downregulated (Fig. 6 C). Immunohistochemical expression of kininogen-1, apolipoprotein E, perlecan, and EEF1D in OL and OSCC Among the top ten proteins identified with proteomic analysis distinguishing SD-leuko-ca from leuko-nonca, kininogen-1, apolipoprotein E (ApoE), basement-membrane-specific heparan sulfate proteoglycan core protein (perlecan), and eukaryotic elongation factor 1 delta (EEF1D) were selected to be assessed by immunohistochemistry on the same tissue specimens that were used for proteomics. Immunohistochemical staining demonstrated the presence of all four proteins identified in the proteomic analysis. Positive kininogen-1 staining was present in the epithelium in OLs with and without malignant transformation as well as in OSCC (Fig. 7 A-D). The epithelial cells displayed cytoplasmic staining in the majority of samples, and with occasional membrane staining. In the connective tissue, kininogen-1-positive endothelial cells and striated muscle cells were observed. In some areas, cells resembling lymphocytes and fibroblasts were positive. Weak ApoE staining was observed in the connective tissue (Fig. 7 E-H). In the epithelium of leuko-nonca, there were some focal areas of membranous staining (Fig. 7 E). In general, a very weak cytoplasmic staining was found in OSCC (Fig. 7 H). Positive perlecan cytoplasmic staining was seen in the epithelium of leuko-nonca, leuko-ca, and OSCC specimens (Fig. 7 I-L). Particularly, the cytoplasm of OSCC cells in tumor islands was positive (Fig. 7 L). Granular cytoplasmic staining was identified in two of the four LD-leuko-ca samples (Fig. 7 J). SD-leuko-ca samples exhibited weak cytoplasmic staining of the keratinocytes (Fig. 7 K). EEF1D staining was hardly present in the epithelium of leuko-nonca and LD-leuko-ca specimens (Fig. 7 M-N). In SD-leuko-ca, very weak cytoplasmic staining was identified in the epithelial cells (Fig. 7 O). In OSCC cells, EEF1D-staining dominated in the nuclei (Fig. 7 P). Discussion In the present study, we identified a panel of potential biomarkers that could identify OL with risk of malignant transformation. Furthermore, our findings provide additional evidence that the immune system might play a key role in the progression of OL to OSCC. We had a time span of 5 months to 54 months from diagnosis of OL to the diagnosis of OSCC in the current cohort of patients. Since we hypothesized that OL with short duration till OSCC diagnosis would be closer genetically to OSCC than OL with longer duration to OSCC diagnosis, we divided the cohort into two groups depending on the duration till OSCC diagnosis. In fact, more proteins were differently expressed compared with the leuko-nonca in the SD-leuko-ca compared with the LD-leuko-ca. This supports the idea that OL undergoes dynamic genetic changes during its transformation into OSCC. Biomarkers discriminating SD-leuko-ca from leuko-nonca Among the top twelve biomarkers that distinguished SD-leuko-ca from leuko-nonca, the expression of four biomarkers—collagen alpha-1(VII) chain, sortilin, basement-membrane-specific heparan sulfate proteoglycan core protein, and apolipoprotein CII—were significantly decreased in OSCC compared to leuko-nonca (similar to SD-leuko-ca). Meanwhile, three others—lanC-like protein 2, serine/threonine-protein phosphatase PGAM5, mitochondrial, and ATP-binding cassette sub-family F member 2—were significantly increased in OSCC, following the same pattern as SD-leuko-ca. Previous studies have shown that collagen alpha-1(VII) chain encoded by the COL7A1 gene is up-regulated in esophageal squamous cell carcinoma, lung squamous cell carcinoma, pancreatic cancer and clear cell renal cell carcinoma and that such up-regulation is associated with poor overall survival 20 – 23 . Moreover, COL7A1 is often mutated in microsatellite-instable high gastric adenocarcinoma 24 . In our study we observed a down-regulation of kininogen-1 in SD-leuko-ca and a tendency to a down-regulation in OSCC compared with leuko-nonca. Kininogen-1 is expressed in different cancer types including clear cell renal cell carcinoma, colorectal cancer and laryngeal squamous cell carcinoma 25 – 27 . Protein-protein interaction analysis has suggested that kininogen-1 constitutes a hub-bottleneck protein for OSCC 28 . Based on salivary proteomics, kininogen-1 has been put forward as a biomarker identifying patients with OSCC from healthy controls 29 . Microarray studies demonstrated that kininogen-1 levels are positively correlated with shorter overall survival and recurrence-free survival in OSCC 28 . Moreover, among the top identified biomarkers we found collagen alpha-1 (XVIII)-chain. Endostatin is a cleavage product of the collagen alpha-1 (XVIII)-chain and treatment with endostatin may inhibit angiogenesis and inhibit growth of various forms of cancer including renal cell carcinoma 30 . Among biomarkers discriminating SD-leuko-ca from leuko-nonca, ApoE and apolipoprotein C-II (ApoC-II) were identified among the twelve top potential biomarkers. Regulation of very-low-density lipoprotein particle remodeling and reverse cholesterol transport were identified as pathways in the top of activated biological pathways in leuko-ca vs. leuko-nonca. The lipidome is changed in OSCC where up-regulation occurs in cholesterol and glycerophospholipids in OSCC compared to healthy oral tongue mucosa 31 . Apolipoproteins have important and various roles in cancer development including regulation of authophagy, oxidative stress and drug resistance 32 . Serum levels of ApoC-II is a prognosticator for pancreatic cancer 33 . ApoE is increased in OSCC and a regulator of cancer invasion 34 , 35 . Among potential biomarkers distinguishing SD-leuko-ca from leuko-nonca, elongation factor 1-delta and sortilin were found. Elongation factor 1-delta is a regulator of various cancer forms and it is overexpressed in mesenchymal stem cells derived from malignant salivary gland tumours 36 , 37 . Sortilin is the receptor to the precursor to nerve growth factor (proNGF) and it is abundantly expressed in the nervous system but also involved in tumorigenesis and overexpressed in different cancer forms, e.g. , lung cancer and cervical cancer 38 , 39 . Interestingly, in head and neck squamous cell carcinoma (HNSCC), sortilin seems to regulate epidermal growth factor receptor (EGFr) expression and the expression is associated with worse prognosis 40 . Biomarkers distinguishing OSCC from leuko-nonca Of the top twelve biomarkers distinguishing OSCC from leuko-nonca, all have been identified previously as biomarkers in cancer. Serpin B9 has been demonstrated to have multiple roles in cancer development. Studies show that serpin B9 seems to be a positive prognosticator for overall survival in colorectal cancer and melanoma 41 – 43 . Cytosol aminopeptidase constitutes a prognosticator in diffuse large B cell lymphoma 44 . The coding gene LAP3 for cytosol aminopeptidase constitutes a hub gene in Epstein-Barr virus-associated gastric carcinoma 45 . SUMOylation is a post-translational modification regulating a number of biological processes and involved in carcinogenesis 46 . The small ubiquitin-related modifier (SUMO)1–4 proteins resemble the ubiquitin proteins in structure and SUMO1 and SUMO2 have been suggested to play a role in OSCC 47 – 49 . Coactosin-like protein is involved in carcinogenesis and is significantly overexpressed in HNSCC and breast cancer compared to healthy breast tissue 50 , 51 . Interferon regulatory family proteins including interferon regulatory factor 9 (IRF9) are up-regulated in HNSCC and IRF9 is correlated with better overall survival in HNSCC 52 . Cleavage stimulation factor subunit 2 is a prognosticator for poor overall survival in hepatocellular carcinoma and OSCC 53 , 54 . Decreased expression of tapasin and increased expression of heat shock protein 105 kDa are correlated with poor survival in OSCC 55 , 56 . Damage-control phosphatase ARMT1 methylates proliferating cell nuclear antigen (PCNA) in breast cancer cell lines and modulates their sensitivity to chemotherapy and ultraviolet light 57 . N-myc interactor modulates proliferation, migration and invasion of the cervical cancer cell line HeLa 58 . The gene encoding synembryn-A, RIC8A, is more often mutated in metastatic breast cancer compared to early breast cancer 59 . Sequestome-1 is up-regulated in OSCC and correlated with EGFR expression, and sequestome-1 and EGFR expressions are positively correlated with poor survival in OSCC 60 . Taken together, the proteins identified in this study have earlier been shown to be of importance in established cancers, and our results point to an involvement also in the precancer stage. This raises possibilities for future use of these biomarker in predicting cancer development. Proteins involved in epithelial differentiation in OSCC transformation As a result of the loss of epithelial differentiation, biological pathways involved in skin development, epidermal development, and keratinocyte differentiation were downregulated in OSCC compared to leuko-ca. Among the downregulated proteins were keratin 1, keratin 10, keratin 76, cystatin-A, and corneodesmosin. Previous studies have shown that keratin 1 and keratin 10 are downregulated in OSCC compared to normal mucosa, and that keratin 76 is expressed at lower levels in OSCC than in OL 61 – 63 . CSTA (cystatin-A) and CDSN (corneodesmosin) are important hub genes in OSCC, and their reduced expression is associated with poor prognosis 64 , 65 . These observations indicate that deregulation of epithelial differentiation is more pronounced in OSCC as compared to the leuko-ca. Involvement of the immune system in OSCC transformation Importantly, our study provides further evidence that the immune system is involved in the development of OSCC from OL. Antigen processing and presentation of endogenous peptide antigen, Antigen processing and presentation of peptide antigen via MHC class Ib, Antigen processing and presentation of peptide antigen and Immune response were in top of up-regulated biological pathways in OSCC compared with leuko-ca. Previous studies showed that the numbers of T cells, NK cells, macrophages and Langerhans cells increase in dysplastic OL and are associated with OSCC development 66 – 68 . The numbers of CD8 + T cells and T regulatory (Treg) cells are increased in proliferative OL compared with localized OL independently of the degree of dysplasia 69 . Thus, activation of different branches of the immune system occurs, which also our results confirm. Immunohistochemical expression of biomarkers Among the top ten proteins identified from proteomics distinguishing SD-leuko-ca vs. leuko-nonca we selected kininogen-1, ApoE, perlecan and EEF1D to assess the expression in all tissue specimens with immunohistochemistry. All four proteins were expressed in the examined tissues; however, a quantitative analysis of the immunohistochemical results was not possible to conduct primarily due to insufficient number of samples across the four groups of tissues to support the objectivity of the statistical analysis. Nevertheless, we provided a qualitative description of the staining pattern of the proteins, which could serve as a basis for future research. The strength of our study is that we have longitudinally followed patients with OL to OSCC development and identified potential biomarkers identifying OL at risk of transformation to OSCC. However, our study has limitations since we studied only a low number of patients with OL. There was also a mixture of dysplastic and non-dysplastic lesions in the leuko-nonca and the leuko-ca groups. However, the limited number of patients did not allow consideration of dysplasia grade. In conclusion, biomarkers may discriminate OL with high risk of developing to OSCC. The immune system is involved in the pathogenesis of OL to OSCC. Future studies, validating the present identified panel discriminating OL with high risk of developing to OSCC from OL with low risk of developing to OSCC are warranted. Declarations Acknowledgment We thank the Proteomics Core Facility, Sahlgrenska academy at the University of Gothenburg (with financial support from SciLifeLab and BioMS), for help with proteomics and analysis. We also would like to thank Olaf Schreurs at the Department of Oral Biology, University of Oslo, for valuable contribution in performing immunohistochemistry. The present study was sponsored by TUA (TUAGBG-978132; given to Professor Bengt Hasséus) and King Gustav V Jubilee Clinic Cancer Research Foundation (2021:352; given to Associate Professor Daniel Giglio). Authors´ contribution Daniel Giglio: conceptualization, study design, planning, analyzed and interpreted data and drafted the manuscript. Divya Ganesh: retrieved tissue specimens and characterized patients´ clinical data. Took part in analysis, interpretation of data and co-drafted the manuscript. Bishwa Prakash Bhattarai: performed and evaluated immunohistochemistry analyses, took part in analysis, interpretation of data and co-drafted the manuscript. Tine Merete Søland: evaluation of histopathological diagnoses and immunohistochemistry analyses, interpretation of data and co-drafted the manuscript. Jonas Sundberg: patient collection, evaluation, analyses and interpretation, critically reviewed the manuscript. Annika Thorsell: study design, proteomics analyses of tissue specimens, evaluation, and interpretation of data, critically reviewed the manuscript. Jenny Öhman: patient collection, evaluation of clinical and histopathological diagnoses, analyses, interpretation of data and co-drafted the manuscript. Dipak Sapkota: evaluation of histopathological diagnoses and immunohistochemistry analyses, interpretation of data and co-drafted the manuscript. Bengt Hasséus: conceptualization, study design, planning, patient collection, analyzed and interpreted data and co-drafted the manuscript. Declarations and Competing Interests Statement Parts of the results have been presented at the European Association of Oral Medicine Conference 2023, London, UK. DG has been part of scientific advisory boards and/or has held scientific presentations for Merck, Roche and AstraZeneca. All other authors declare no conflict of interest. Data availability statement Additional data can be available upon request from the Institute of Clinical Sciences at the Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 3A SE-413 90 Göteborg, Sweden. Email: [email protected] . Ethics declarations The present study was approved by the Regional Ethical Review Board in Gothenburg, Sweden (Dnr. 673–10, T864-11). References Warnakulasuriya, S. Oral potentially malignant disorders: A comprehensive review on clinical aspects and management. Oral Oncol 102 , 104550, doi:10.1016/j.oraloncology.2019.104550 (2020). Pinto, A. C. et al. Malignant transformation rate of oral leukoplakia-systematic review. Oral Surg Oral Med Oral Pathol Oral Radiol 129 , 600-611.e602, doi:10.1016/j.oooo.2020.02.017 (2020). Lodi, G. et al. Interventions for treating oral leukoplakia to prevent oral cancer. Cochrane Database Syst Rev 7 , CD001829, doi:10.1002/14651858.CD001829.pub4 (2016). Bhattarai, B. P. et al. 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Supplementary2proteomicsleukoplakia16May2025.xlsx Supplementary file 2. All enriched biological pathways between OL and OSCC groups. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6688707","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":482836361,"identity":"8976f8c6-25c5-466a-b99b-b7bee2fecc2c","order_by":0,"name":"Daniel Giglio","email":"data:image/png;base64,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","orcid":"","institution":"Department of Oncology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Giglio","suffix":""},{"id":482836362,"identity":"d3b322fc-f8b4-4ad8-a420-7f4695565a29","order_by":1,"name":"Divya Ganesh","email":"","orcid":"","institution":"Department of Oral Medicine and Pathology, Institute of Odontology, Sahlgrenska Academy at the University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Divya","middleName":"","lastName":"Ganesh","suffix":""},{"id":482836363,"identity":"e001ee1a-02de-4561-ae83-51a33cc7bb31","order_by":2,"name":"Bishwa Prakash Bhattarai","email":"","orcid":"","institution":"Institute of Oral Biology, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Bishwa","middleName":"Prakash","lastName":"Bhattarai","suffix":""},{"id":482836364,"identity":"60f91632-174e-4f91-ab6d-340e6d802129","order_by":3,"name":"Tine Merete Søland","email":"","orcid":"","institution":"Institute of Oral Biology, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Tine","middleName":"Merete","lastName":"Søland","suffix":""},{"id":482836365,"identity":"568eb286-fd6d-47e2-b017-bb58f9a35883","order_by":4,"name":"Jonas Sundberg","email":"","orcid":"","institution":"Department of Oral Medicine and Pathology, Institute of Odontology, Sahlgrenska Academy at the University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Jonas","middleName":"","lastName":"Sundberg","suffix":""},{"id":482836366,"identity":"c1141c10-2d76-4e02-bc96-1627c6ab0373","order_by":5,"name":"Annika Thorsell","email":"","orcid":"","institution":"Proteomics Core Facility, Sahlgrenska Academy at the University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Annika","middleName":"","lastName":"Thorsell","suffix":""},{"id":482836367,"identity":"5eb54019-58f7-4e79-a2d6-09cb78103f54","order_by":6,"name":"Jenny Öhman","email":"","orcid":"","institution":"Department of Oral Medicine and Pathology, Institute of Odontology, Sahlgrenska Academy at the University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Jenny","middleName":"","lastName":"Öhman","suffix":""},{"id":482836368,"identity":"bfa764cb-9084-4f46-b679-f04131875455","order_by":7,"name":"Dipak Sapkota","email":"","orcid":"","institution":"Institute of Oral Biology, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Dipak","middleName":"","lastName":"Sapkota","suffix":""},{"id":482836369,"identity":"952ab101-14fb-4db5-bd49-67767af03f43","order_by":8,"name":"Bengt Hasséus","email":"","orcid":"","institution":"Department of Oral Medicine and Pathology, Institute of Odontology, Sahlgrenska Academy at the University of Gothenburg","correspondingAuthor":false,"prefix":"","firstName":"Bengt","middleName":"","lastName":"Hasséus","suffix":""}],"badges":[],"createdAt":"2025-05-17 19:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6688707/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6688707/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86435646,"identity":"576b12fa-ad95-4d10-88f3-62efc44f7109","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2360383,"visible":true,"origin":"","legend":"\u003cp\u003eThe number of DEPs between groups (A). Positive values indicate up-regulated proteins and negative values indicate down-regulated proteins in OSCC, SD-LC and LD-LC, respectively, compared with groups listed on the x-axis. Venn diagram of DEPs present in \u0026gt;58% of samples in leuko-nonca, SD-leuko-ca and OSCC (B). Volcano plots of proteins expressed in the different groups. Red triangles indicate significantly DEPs and black boxes not significantly expressed proteins between the two indicated groups (C). OSCC-oral squamous cell carcinoma; SD-LC=short duration leuko-ca; LD-LC=long duration leukoca; L-NC=leuko-nonca.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/f0bc50539302b12f41120539.png"},{"id":86435648,"identity":"1499e0a7-0b73-464c-b818-1734fa4a1e70","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5379089,"visible":true,"origin":"","legend":"\u003cp\u003eString analysis of the top 40 DEPs between SD-leuko-ca and leuko non-ca (A). String analysis of all DEPs between SD-leuko-ca and leuko non-ca (B). Disconnected nodes are hidden in the network in figure B. The line thickness indicates the strength of data support. Heat map of the top five enriched biological pathways for all DEPs (A-F) + top biological pathways for the top 40 DEPS (G; collagen fibrillar organization) between short duration leuko-ca vs. leuko-nonca (C). The most important biological processes (gene ontology) are displayed in Figure D. Immunoglobulin heavy constant alpha 1, immunoglobulin lambda-1 light chain, immunoglobulin delta heavy chain, HLA class II histocompatibility antigen, DR beta 3 chain and uncharacterized protein FLJ45252 were not found in the String database and are not included in Figures A, B and D.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/e578bf046df17614726f7060.png"},{"id":86437444,"identity":"56b35e77-c1e5-4a5f-8e84-855a191b8c5f","added_by":"auto","created_at":"2025-07-10 15:48:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1443657,"visible":true,"origin":"","legend":"\u003cp\u003eThe most peripheral proteins in the volcano plot of leuko-nonca vs. SD leuko-ca. Displayed are only proteins where the individual proteins were detected in all samples.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/fd094f9ae0a99467e2ed6b9e.png"},{"id":86435659,"identity":"fde510a5-d4a8-4394-a47f-1c67934ed5ed","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":6074588,"visible":true,"origin":"","legend":"\u003cp\u003eString analysis of the top 40 DEPs between leuko non-ca and OSCC (A). String analysis of all DEPs (absolute fold-change\u0026gt;0.7) between leuko non-ca and OSCC (B). Disconnected nodes are hidden in the network in figure B. The line thickness indicates the strength of data support. Heat map of the top six enriched biological pathways for all DEPs (absolute fold-change\u0026gt;0.7; A-F) between leuko non-ca and OSCC (C). The most important biological processes (gene ontology) are displayed in Figure D. Putative neutrophil cytosol factor 1B and HLA class II histocompatibility antigen, DR beta 3 chain was not found in the String database and are not included in Figures A, B and D.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/580a65b30beb19c0891a6dc5.png"},{"id":86435651,"identity":"3b313bfa-f23c-42a4-a897-d5ef47e891e7","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1310992,"visible":true,"origin":"","legend":"\u003cp\u003eThe most peripheral proteins in the volcano plot of leuko-ca \u003cem\u003evs.\u003c/em\u003e OSCC. All of the presented proteins were detected in all samples.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/32f00783c40da9c4c1280f93.png"},{"id":86435660,"identity":"827fa154-f7ae-4028-93c0-c7e78bc5e0b2","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4896444,"visible":true,"origin":"","legend":"\u003cp\u003eString analysis of the top 40 DEPs between Leuko-ca and OSCC (A). String analysis of all DEPs (absolute fold-change\u0026gt;0.7) between leuko-ca and OSCC (B). The line thickness indicates the strength of data support. Heat map of the top six enriched biological pathways for all DEPs (absolute fold-change\u0026gt;0.7; A-G) between leuko-ca and OSCC (C). The most important biological processes (gene ontology) are displayed in Figure D. Putative neutrophil cytosol factor 1B was not found in the String database and not included in Figures A, B and C.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/a70c34716b3047ff085c314a.png"},{"id":86435657,"identity":"ad985425-c9a7-4ce7-b693-30cefa0bfa4d","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":820419,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative images for immunohistochemical expression of kininogen 1 (A- D) in leuko-nonca (A), LD leuko-ca (B), SD leuko-ca (C), OSCC (D); apolipoprotein E (E- H) in leuko-nonca (E), LD leuko-ca (F), SD leuko-ca (G), OSCC (H); perlecan (I- L) in leuko-nonca (I), LD leuko-ca (J), SD leuko-ca (K), OSCC (L); EEF1D (M- P) in leuko-nonca (M), LD leuko-ca (N), SD leuko-ca (O), OSCC (P). Scale bar: 500 µm.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/895e444875b0d4263a32cb55.png"},{"id":101881507,"identity":"c514d437-1354-4fcf-95a6-a3f11d0a3b36","added_by":"auto","created_at":"2026-02-04 15:12:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":23469955,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/b68fca2b-ad03-4e4f-8687-e0d67eaf0bfa.pdf"},{"id":86435649,"identity":"b9c04519-35fd-48a3-89be-ec0ee3090de3","added_by":"auto","created_at":"2025-07-10 15:32:12","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1315436,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 1. All DEPs between OL and OSCC groups.\u003c/p\u003e","description":"","filename":"Supplementary1proteomicsleukoplakia16May2025.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/c79052379209506f29fb682c.xlsx"},{"id":86436972,"identity":"8c258d9a-f140-408d-8ed8-afe5e287254e","added_by":"auto","created_at":"2025-07-10 15:40:12","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":63921,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary file 2. All enriched biological pathways between OL and OSCC groups.\u003c/p\u003e","description":"","filename":"Supplementary2proteomicsleukoplakia16May2025.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6688707/v1/f19ef0be1ff1142da9eb6ae9.xlsx"}],"financialInterests":"Competing interest reported. DG has been part of scientific advisory boards and/or has held scientific presentations for Merck, Roche and AstraZeneca. All other authors declare no conflict of interest.","formattedTitle":"Biomarkers Correlating with the Development of Oral Squamous Cell Carcinoma from Leukoplakia ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOral leukoplakia (OL) is a white plaque in the oral mucosa and constitutes an oral potentially malignant disorder (OPMD) where one lesion out of ten develops into oral squamous cell carcinoma (OSCC) \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. OL should therefore be closely monitored, biopsied to assess for dysplastic changes in the lesion or be surgically removed \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, even after surgery \u003cem\u003ein toto\u003c/em\u003e, 22% of OL may recur \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. In particular, the non-homogenous phenotype is associated with recurrence, and recurrence is further associated with an increased risk of malignant transformation \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWe showed recently that OL with high co-expression of p53 and p63 more often recurs \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, which signals increased risk for malignant transformation. In addition to clinical features, dysplasia is also a known risk factor for malignant transformation of OL \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. At present only a few biomarkers are known to identify OLs with a high risk of OSCC transformation. Studies show that OLs with high expression of p53, podoplanin, ki67 or enhancer of zeste homolog 2 (EZH2) are associated with malignant transformation \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, while most studies have assessed the relationship between biomarkers in OPMD and oral squamous cell carcinoma (OSCC), only a few longitudinal studies have examined the global expression of protein biomarkers associated with the development of OSCC from OL.\u003c/p\u003e\u003cp\u003eGenomics, transcriptomics, proteomics and metabolomics are important tools to identify biomarkers associated with the development of malignant transformation of OPMD \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. With transcriptomics, fibronectin 1, STAT1 and members of the collagen family were identified to be associated with malignant transformation from OL \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. With proteomics, L-lactate dehydrogenase A chain, plectin, WD repeat-containing protein 1, thioredoxin 1, spectrin alpha chain and nonerythrocytic 1 were identified as proteins changing their expression linearly from normal mucosa, to OL and to OSCC \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn the present study using global proteomics on diagnostic biopsy specimens, we examined and compared the proteome in OL at the timepoint of OL diagnosis between OL that eventually transformed into OSCC with OLs not transforming to OSCC during a period of up to five years.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eCohort of patients with OL and OSCC\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was approved by Clinical Directors at participating clinics in Region V\u0026auml;stra G\u0026ouml;taland and Region Uppsala, Sweden, and by the Regional Ethical Review Board in Gothenburg, Sweden (Dnr. 673\u0026ndash;10, T864-11). Informed consent was obtained from all study participants and the study was conducted in accordance with Swedish law and with the tenets of the Declaration of Helsinki. Patients included in the study were part of a prospective, longitudinal multicenter study (ORA-LEU-CAN study) where patients diagnosed with OL were followed every three months for two years and then every six months for three years and treated according to the standard of care. All included patients in the present study had a clinical diagnosis of OL, a histopathological diagnosis of hyperkeratosis with or without dysplasia and a follow-up time of \u0026ge;5 months between the primary biopsy and OSCC transformation. Included in the study were 12 patients with OL not developing to OSCC (leuko-nonca) during a follow-up period of up to five years (2 patients followed for 15 months and 10 patients followed for 60 months) and 10 patients with OL developing OSCC (leuko-ca) during a follow-up time of 5-54 months. Biopsies of OL at baseline at the time of diagnosis were taken and biopsies from the OSCC developing in the corresponding area of the OL were taken and examined. The analysis was performed from formalin-fixed paraffin-embedded tissue specimens stored at the Department of Pathology, Sahlgrenska University Hospital, Gothenburg.\u003cem\u003e\u0026nbsp;\u003c/em\u003ePatients\u0026acute; characteristics are presented in Table 1-3.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"591\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 591px;\"\u003e\n \u003cp\u003eTable 1. Patients\u0026acute; characteristics.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOSCC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTransforming leukoplakia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNon-transforming\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eLeukoplakia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePatients\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHistopathological grading\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBenign hyperkeratosis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMild dysplasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModerate dysplasia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSevere dysplasia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWell differentiated OSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eModerately differentiated OSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePoorly differentiated OSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNot specified OSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of lesion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eFloor of the mouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eBuccal mucosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eGingiva\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 136px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eHard palate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 136px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 591px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eOSCC: oral squamous cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 66.0033%;\"\u003e\n \u003cp\u003eTable 2. Characteristics of patients with malignant transformation of leukoplakia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 14.262%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 19.7347%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at diagnosis (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of leukoplakia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresence of dysplasia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of tumour\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime to malignant transformation (months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eBuccal mucosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eBuccal mucosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eHard Palate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eHard palate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eFloor of the mouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eFloor of the mounth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14.0962%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.78441%;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9453%;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0763%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.1012%;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.262%;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19.7347%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 488px;\"\u003e\n \u003cp\u003eTable 3. Characteristics of patients without malignant transformation of leukoplakia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at diagnosis (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of leukoplakia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePresence of dysplasia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up time (months)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eTongue\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 146px;\"\u003e\n \u003cp\u003eBuccal mucosa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eFloor of the mouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTounge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTounge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eFemale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eHard palate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eTongue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003eGingiva\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ePreparation of tissue samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTen to 15 sections \u0026agrave; 4 mm of thickness per tissue biopsy were deparaffinated after treatment with xylene and dehydrated in absolute ethanol according to a standardized protocol. The retrieved pellets were used for proteomic analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eS\u003c/em\u003e\u003cem\u003eample preparation\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe proteomic analysis was performed at the Proteomics Core Facility at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden. Proteins were extracted using lysis buffer (50 mM triethylammonium bicarbonate (TEAB) and 2% sodium dodecyl sulfate (SDS)) and the protocol for FFPE scrolls on the ML430 Covaris instrument, according to manufacturer instruction. The protein concentration was determined using Pierce BCA Protein Assay (Thermo Scientific). The samples and references (representative pool containing aliquots from all groups) were digested using modified filter-aided sample preparation (FASP) method \u003csup\u003e17\u003c/sup\u003e. In short, samples (25 \u0026micro;g) were reduced with 100 mM dithiothreitol at 60\u0026deg;C for 30 min, transferred to Microcon-30kDa Centrifugal Filter Units (Merck), washed several times with 8 M urea and once with digestion buffer (DB, 50 mM TEAB, 0.5% sodium deoxycholate (SDC)) prior to alkylation with 10 mM methyl methanethiosulfonate in DB for 30 min in room temperature. Samples were digested with trypsin (Pierce MS grade Trypsin, Thermo Fisher Scientific, ratio 1:100) at 37\u0026deg;C overnight and an additional portion of trypsin was added and incubated for another two hours. Peptides were collected by centrifugation and labelled using TMTpro 18-plex isobaric mass tagging reagents (Thermo Fisher Scientific) according to the manufacturer instructions. The samples were combined into two TMT-set and SDC was removed by acidification with 10% TFA. The TMT-sets were further purified using High Protein and Peptide Recovery Detergent Removal Spin Column and Pierce peptide desalting spin columns (both Thermo Fischer Scientific) according to the manufacturer instructions prior to basic reversed-phase chromatography (bRP-LC) fractionation. Peptide separation was performed using a Dionex Ultimate 3000 UPLC system (Thermo Fischer Scientific) and a reversed-phase XBridge BEH C18 column (3.5 \u0026mu;m, 3.0x150 mm, Waters Corporation) with a gradient from 3% to 100% acetonitrile in 10 mM ammonium formate at pH 10.00 over 23 min at a flow of 400 \u0026micro;L/min. The 40 fractions were concatenated into 20 fractions, dried and reconstituted in 3% acetonitrile, 0.2% formic acid.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNano-liquid chromatography-mass spectrometry (LC-MS) analysis\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEach fraction was analysed on Orbitrap Fusion\u0026trade; Tribrid\u0026trade; mass spectrometer interfaced with nLC 1200 liquid chromatography system (all Thermo Fisher Scientific). Peptides were trapped on an Acclaim Pepmap 100 C18 trap column (100 \u0026mu;m x 2 cm, particle size 5 \u0026mu;m, Thermo Fischer Scientific) and separated on an in-house constructed analytical column (350x0.075 mm I.D.) packed with 3 \u0026mu;m Reprosil-Pur C18-AQ particles (Dr. Maisch, Germany) using a gradient from 3% to 80% acetonitrile in 0.2% formic acid over 85 min at a flow of 300 nL/min. Precursor ion mass spectra were acquired at 120 000 resolution where the most intense doubly or multiply charged precursors were isolated in the quadrupole with a 0.7 m/z isolation window and dynamic exclusion within 10 ppm for 45 s. The isolated precursors were fragmented by collision induced dissociation (CID) at 35% collision energy and detected in the ion trap, followed by multinotch (simultaneous) isolation of the top 10 MS2 fragment ions for fragmentation (MS3) by higher-energy collision dissociation (HCD) at 55% collision energy and detection in the Orbitrap at 50 000 resolution m/z range 100-500.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProteomic Data Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe data files for each set were merged for identification and relative quantification using Proteome Discoverer version 2.4 (Thermo Fisher Scientific). The search was against \u003cem\u003eHomo Sapiens\u0026nbsp;\u003c/em\u003e(Swissprot Database Mars 2019) using Mascot 2.5 (Matrix Science) as a search engine with precursor mass tolerance of 10 ppm and fragment mass tolerance of 0.6 Da.\u0026nbsp;Tryptic peptides were accepted with zero missed cleavage, variable modifications of methionine oxidation and fixed cysteine alkylation, TMT-label modifications of N-terminal and lysine were selected. Percolator was used for PSM validation with the strict FDR threshold of 1%. TMT reporter ions were identified with 3 mmu mass tolerance in the MS3 HCD spectra, and the TMT reporter abundance values for each sample were normalized on the total peptide amount. Only the quantitative results for the unique peptide sequences with the minimum SPS match % of 50 and the average S/N above 10 were taken into account for the protein quantification. The reference samples were used as denominator and for calculation of the ratios. The quantified proteins were filtered at 1% FDR and grouped by sharing the same sequences to minimize redundancy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Genetically OL would be closer to OSCC if OSCC is diagnosed short after OL diagnosis and genetically OL would be closer to OL not developing to OSCC if OSCC is diagnosed long after OL diagnosis. Therefore, leuko-ca was subdivided into two subgroups, \u003cem\u003ei.e.\u003c/em\u003e, the first group denoted long duration leuko-ca (LD-leuko-ca) where OSCC was developed from OL 32-54 months after OL diagnosis (n=4) and the second group denoted short duration leuko-ca (SD-leuko-ca) where OSCC was developed 5-26 months after OL diagnosis (n=6). The cut-off in months between the two groups was set to have similarly equally sized groups and a gap in months between the two groups. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eString analysis, creation of volcano plots and Venn diagrams and identification of biomarkers\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo identify biological pathways of importance in OL and OSCC, the Search Tool for the Retrieval of Interacting Genes/Proteins (String) software (version 11.0) was used for where the confidence was set to medium (0.400) for the minimum interaction score \u003csup\u003e18\u003c/sup\u003e. The top 40 differently expressed proteins (DEPs; in either direction, \u003cem\u003ei.e.\u003c/em\u003e, up- or down-regulated) or all DEPs with an absolute fold-change over 0.7 were included in the pathways analyses. In the volcano plots, the negative log10 of the p-value was plotted against the log2 fold change between groups of comparison. To identify proteins that were separated the most between groups, proteins with the longest distances from the origo of the volcano plot were identified (\u0026radic; (x\u003csup\u003e2\u003c/sup\u003e + y\u003csup\u003e2\u003c/sup\u003e). Only significantly DEPs expressed by more than 58% of samples in both groups were considered in the heat maps and String analyses. For any missing values, the average expression for the sample group was imputed. \u0026nbsp;Graphpad Prism (version 10.4.2) was used to create volcano plots. The Perseus software (Perseus v2.1.4.0) was used to create heat maps by employing the squared Euclidean distance-based hierarchical clustering analyses \u003csup\u003e19\u003c/sup\u003e. The interactive tool Venny 2.1 was used to develop the Venn diagram (https://bioinfogp.cnb.csic.es/tools/venny/index.html). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImmunohistochemistry\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAmong the proteins showing significant differences in expression between SD-leuko-ca and leuko-nonca based on proteomics analysis, kininogen-1, apolipoprotein E (apoE), basement-membrane-specific heparan sulfate proteoglycan core protein (perlecan), and eukaryotic elongation factor 1 delta (EEF1D) were further analyzed using immunohistochemistry. Immunohistochemistry was performed on all 31 samples (12 leuko-nonca, four LD-leuko-ca, six SD-leuko-ca, and 10 OSCC).\u003c/p\u003e\n\u003cp\u003eAfter retrieving formalin-fixed paraffin-embedded tissue blocks, 4 mm sections were cut and mounted on poly-l-lysine-coated slides. Sections were then heated at 60\u0026deg;C for two hours, followed by deparaffinization in xylene and rehydration in serial dilutions of ethanol. The sections were then immersed in 3% hydrogen peroxide in 70% methanol for quenching endogenous peroxidase. After washing the sections in water followed by phosphate-buffered saline (PBS, pH 7.4), epitope retrieval was performed in a decloaking chamber at 100\u0026deg;C for 15 minutes and at 90\u0026deg;C for 10 seconds. Citraconic anhydride (CCA) at pH 7.4 was used as the epitope retrieval solution. The sections were then cooled to room temperature and washed in PBS. Blocking, primary, and secondary antibody incubation steps are summarized in Table 4.\u003c/p\u003e\n\u003cp\u003eTable 4. Details of blocking, antibody dilutions, and incubation times for immunohistochemistry.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlocking 45 min RT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary antibody\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eovernight incubation at 4\u0026deg;C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDilution\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eManufactured by\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003csup\u003end\u003c/sup\u003e antibody\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e1 hour incubation at RT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e5% goat serum in 1% BSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003eRabbit-anti-Kininogen 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e--x--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eIgG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1/600\u003c/p\u003e\n \u003cp\u003e(0.17 \u0026micro;g/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003eGoat-anti-Rabbit IgG\u003csup\u003eBio\u003c/sup\u003e (7.5 \u0026micro;g/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 94px;\"\u003e\n \u003cp\u003e5% horse serum in 1% BSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003eMouse-anti-Apolipoprotein E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eD6E10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eIgG1,\u0026nbsp;k\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1/200\u003c/p\u003e\n \u003cp\u003e(2.5 \u0026micro;g/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eAbcam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 89px;\"\u003e\n \u003cp\u003eHorse-anti-Mouse IgG\u003csup\u003eBio\u003c/sup\u003e (7.5 \u0026micro;g/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003eMouse-anti-Perlecan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7B5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eIgG1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1/50\u003c/p\u003e\n \u003cp\u003e(5 \u0026micro;g/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 134px;\"\u003e\n \u003cp\u003eMouse-anti-EEF1D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eOTI4B9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003eIgG1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1/250\u003c/p\u003e\n \u003cp\u003e(4 \u0026micro;g/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 103px;\"\u003e\n \u003cp\u003eInvitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eRT = room temperature; BSA = bovine serum albumin.\u003c/p\u003e\n\u003cp\u003eAfter incubation with the secondary antibody, the sections were washed twice in PBS. The sections were then incubated with avidin-biotin-complex conjugated to horseradish peroxidase (ABC\u003csup\u003eHRP\u003c/sup\u003e) for 30 minutes. 3, 3\u0026prime;-Diaminobenzidine (DAB) was used to visualize the epitopes, followed by nuclear counterstaining with Mayer\u0026rsquo;s hematoxylin. The sections were washed, dehydrated, and mounted with Histokitt mounting solution (Glaswarenfabrik Karl Hecht GmbH \u0026amp; Co, S\u0026ouml;ndheim v.d. Rh\u0026ouml;n, Germany). Sections incubated with PBS instead of the primary antibodies were used as internal negative controls. \u0026nbsp;Images were acquired using a Nikon Digital Sight 10 camera mounted on a Nikon E90i microscope unit (Nikon, Japan) with 4X, 10X, and 20X magnifications. Based on the images, a qualitative assessment of protein expression was conducted, which included the area of positive staining in the epithelium and connective tissue, the intensity of positive staining, and the types of positively stained cells.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll values from proteomics were logarithmized (base 2). The Student\u0026acute;s paired t-test was used to assess differences between groups. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn the OL and OSCC samples 5530 proteins were identified. The number of deregulated proteins between the different OL groups and OSCC are displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B (full list of proteins in Supplementary file 1). The highest number of DEPs was between OSCC and leuko-nonca and the lowest number was between LD-leuko-ca and SD-leuko-ca (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Including all proteins present in \u0026gt;\u0026thinsp;58% of samples showed that 87 proteins were in common between leuko-nonca \u003cem\u003evs.\u003c/em\u003e SD-leuko-ca and leuko-nonca \u003cem\u003evs.\u003c/em\u003e OSCC and 229 proteins were in common between leuko-nonca \u003cem\u003evs.\u003c/em\u003e OSCC and SD-leuko-ca \u003cem\u003evs.\u003c/em\u003e OSCC but only 2 proteins were in common between leuko-nonca \u003cem\u003evs.\u003c/em\u003e SD-leuko-ca and SD-leuko-ca \u003cem\u003evs.\u003c/em\u003e OSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSD-leuko-ca vs. leuko-nonca\u003c/h2\u003e\u003cp\u003eIn SD-leuko-ca 130 proteins were upregulated and 102 proteins were down-regulated compared with leuko-nonca (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B). Including the top 40 DEPs in String analysis identified Collagen fibril organization, Regulation of very-low-density lipoprotein particle remodeling, Phospholipid efflux, Negative regulation of cholesterol transport, Extracellular matrix organization and Reverse cholesterol transport as enriched biological pathways in SD-leuko-ca compared with leuko-nonca (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA; full list presented in Supplementary file 2). Including all DEPs (absolute fold-change 0.12\u0026ndash;1.19) identified Cytoplasmic translation, Gene expression, Ribosomal large subunit, Acute-phase response, Negative regulation of blood coagulation and Reverse cholesterol transport as top enriched biological pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-D; full list in Supplementary file 2). In SD-leuko-ca compared to leuko-nonca, proteins regulating cytoplasmic translation, gene expression and ribosomal large subunit were upregulated, while proteins regulating acute-phase response, negative regulation of blood coagulation, reverse cholesterol and collagen fibril organization were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eKininogen-1, apoE, collagen alpha-1(XVIII) chain, sortilin, basement-membrane-specific heparan sulfate proteoglycan core protein, histone-lysine N-methyltransferase EHMT1, lanC-like protein 2, chloride intracellular channel protein 6, serine/threonine-protein phosphatase PGAM5, mitochondrial, elongation factor 1-delta, ATP-binding cassette sub-family F member 2 and apolipoprotein CII were the proteins significantly changed and the most distant from the origo on the volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among these potential biomarkers, collagen alpha-1(VII) chain, sortilin, basement-membrane-specific heparan sulfate proteoglycan core protein and apolipoprotein CII were also significantly down-regulated and lanC-like protein 2, serine/threonine-protein phosphatase PGAM5, mitochondrial and ATP-binding cassette sub-family F member 2 were significantly up-regulated in OSCC compared with leuko-nonca (data not shown). Kininogen-1 tended to be down-regulated in SD-leuko-ca compared with leuko-nonca (p\u0026thinsp;=\u0026thinsp;0.097).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eOSCC vs. leuko-nonca\u003c/h2\u003e\u003cp\u003eIn OSCC 1284 proteins were upregulated and 184 proteins were down-regulated compared with leuko-nonca. By including the top 40 DEPs in String analysis we identified Collagen fibril organization, Skin development, External encapsulating structure organization, Collagen biosynthetic process, Supramolecular fiber organization and Extracellular matrix organization\u003c/p\u003e\u003cp\u003eas enriched biological pathways in OSCC compared with leuko-nonca (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA; full list in Supplementary file 2). Including instead all DEPs (absolute fold-change\u0026thinsp;\u0026gt;\u0026thinsp;0.7) in String analysis identified Antigen processing and presentation of endogenous antigen, Skin development, Antigen processing and presentation of endogenous peptide antigen, Antigen processing and presentation of peptide antigen, Supramolecular fiber organization and Peptide cross-linking as enriched biological pathways in OSCC compared with leuko-nonca (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-D; full list in Supplementary file 2). In OSCC compared to leuko-nonca, proteins regulating antigen processing and presentation were upregulated, while proteins regulating skin development and peptide cross-linking were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eOSCC vs. Leuko-ca\u003c/h2\u003e\u003cp\u003eSerpin B9, cytosol aminopeptidase, small ubiquitin-related modifier 2, coactosin-like protein, interferon regulatory factor 9, cleavage stimulation factor subunit 2, tapasin, heat shock protein 105 kDa, damage-control phosphatase ARMT1, N-myc interactor, synembryn-A and sequestome-1 were the twelve DEPs the most significantly increased in OSCC compared with leuko-ca and the most distant from the origo of the volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIncluding the top 40 DEPs in String analysis identified Establishment of skin barrier, Skin development, Epidermis development, Antigen processing and presentation of endogenous peptide antigen, Defense response to other organism and Keratinocyte differentiation as enriched biological pathways in OSCC compared with leuko-ca (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA; full list in Supplementary file 2). Including all DEPs (absolute fold-change\u0026thinsp;\u0026gt;\u0026thinsp;0.7) in String analysis identified Skin development, Antigen processing and presentation of endogenous peptide antigen, Epidermis development, Keratinocyte differentiation, Antigen processing and presentation of peptide antigen via MHC class Ib, Antigen processing and presentation of peptide antigen and Immune response as enriched biological pathways in OSCC compared with leuko-ca (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-D; full list in Supplementary file 2). In OSCC compared to leuko-ca, proteins regulating antigen processing and presentation and immune responses were upregulated, while proteins regulating skin and epidermis development and keratinocyte differentiation were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eImmunohistochemical expression of kininogen-1, apolipoprotein E, perlecan, and EEF1D in OL and OSCC\u003c/h2\u003e\u003cp\u003eAmong the top ten proteins identified with proteomic analysis distinguishing SD-leuko-ca from leuko-nonca, kininogen-1, apolipoprotein E (ApoE), basement-membrane-specific heparan sulfate proteoglycan core protein (perlecan), and eukaryotic elongation factor 1 delta (EEF1D) were selected to be assessed by immunohistochemistry on the same tissue specimens that were used for proteomics. Immunohistochemical staining demonstrated the presence of all four proteins identified in the proteomic analysis. Positive kininogen-1 staining was present in the epithelium in OLs with and without malignant transformation as well as in OSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-D). The epithelial cells displayed cytoplasmic staining in the majority of samples, and with occasional membrane staining. In the connective tissue, kininogen-1-positive endothelial cells and striated muscle cells were observed. In some areas, cells resembling lymphocytes and fibroblasts were positive.\u003c/p\u003e\u003cp\u003eWeak ApoE staining was observed in the connective tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE-H). In the epithelium of leuko-nonca, there were some focal areas of membranous staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). In general, a very weak cytoplasmic staining was found in OSCC (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003ePositive perlecan cytoplasmic staining was seen in the epithelium of leuko-nonca, leuko-ca, and OSCC specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eI-L). Particularly, the cytoplasm of OSCC cells in tumor islands was positive (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eL). Granular cytoplasmic staining was identified in two of the four LD-leuko-ca samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eJ). SD-leuko-ca samples exhibited weak cytoplasmic staining of the keratinocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eK).\u003c/p\u003e\u003cp\u003eEEF1D staining was hardly present in the epithelium of leuko-nonca and LD-leuko-ca specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eM-N). In SD-leuko-ca, very weak cytoplasmic staining was identified in the epithelial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eO). In OSCC cells, EEF1D-staining dominated in the nuclei (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eP).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we identified a panel of potential biomarkers that could identify OL with risk of malignant transformation. Furthermore, our findings provide additional evidence that the immune system might play a key role in the progression of OL to OSCC.\u003c/p\u003e\u003cp\u003eWe had a time span of 5 months to 54 months from diagnosis of OL to the diagnosis of OSCC in the current cohort of patients. Since we hypothesized that OL with short duration till OSCC diagnosis would be closer genetically to OSCC than OL with longer duration to OSCC diagnosis, we divided the cohort into two groups depending on the duration till OSCC diagnosis. In fact, more proteins were differently expressed compared with the leuko-nonca in the SD-leuko-ca compared with the LD-leuko-ca. This supports the idea that OL undergoes dynamic genetic changes during its transformation into OSCC.\u003c/p\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eBiomarkers discriminating SD-leuko-ca from leuko-nonca\u003c/h2\u003e\u003cp\u003eAmong the top twelve biomarkers that distinguished SD-leuko-ca from leuko-nonca, the expression of four biomarkers\u0026mdash;collagen alpha-1(VII) chain, sortilin, basement-membrane-specific heparan sulfate proteoglycan core protein, and apolipoprotein CII\u0026mdash;were significantly decreased in OSCC compared to leuko-nonca (similar to SD-leuko-ca). Meanwhile, three others\u0026mdash;lanC-like protein 2, serine/threonine-protein phosphatase PGAM5, mitochondrial, and ATP-binding cassette sub-family F member 2\u0026mdash;were significantly increased in OSCC, following the same pattern as SD-leuko-ca. Previous studies have shown that collagen alpha-1(VII) chain encoded by the COL7A1 gene is up-regulated in esophageal squamous cell carcinoma, lung squamous cell carcinoma, pancreatic cancer and clear cell renal cell carcinoma and that such up-regulation is associated with poor overall survival \u003csup\u003e\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Moreover, COL7A1 is often mutated in microsatellite-instable high gastric adenocarcinoma \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn our study we observed a down-regulation of kininogen-1 in SD-leuko-ca and a tendency to a down-regulation in OSCC compared with leuko-nonca. Kininogen-1 is expressed in different cancer types including clear cell renal cell carcinoma, colorectal cancer and laryngeal squamous cell carcinoma \u003csup\u003e\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Protein-protein interaction analysis has suggested that kininogen-1 constitutes a hub-bottleneck protein for OSCC \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Based on salivary proteomics, kininogen-1 has been put forward as a biomarker identifying patients with OSCC from healthy controls \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Microarray studies demonstrated that kininogen-1 levels are positively correlated with shorter overall survival and recurrence-free survival in OSCC \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Moreover, among the top identified biomarkers we found collagen alpha-1 (XVIII)-chain. Endostatin is a cleavage product of the collagen alpha-1 (XVIII)-chain and treatment with endostatin may inhibit angiogenesis and inhibit growth of various forms of cancer including renal cell carcinoma \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAmong biomarkers discriminating SD-leuko-ca from leuko-nonca, ApoE and apolipoprotein C-II (ApoC-II) were identified among the twelve top potential biomarkers. Regulation of very-low-density lipoprotein particle remodeling and reverse cholesterol transport were identified as pathways in the top of activated biological pathways in leuko-ca \u003cem\u003evs.\u003c/em\u003e leuko-nonca. The lipidome is changed in OSCC where up-regulation occurs in cholesterol and glycerophospholipids in OSCC compared to healthy oral tongue mucosa \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Apolipoproteins have important and various roles in cancer development including regulation of authophagy, oxidative stress and drug resistance \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Serum levels of ApoC-II is a prognosticator for pancreatic cancer \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. ApoE is increased in OSCC and a regulator of cancer invasion \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAmong potential biomarkers distinguishing SD-leuko-ca from leuko-nonca, elongation factor 1-delta and sortilin were found. Elongation factor 1-delta is a regulator of various cancer forms and it is overexpressed in mesenchymal stem cells derived from malignant salivary gland tumours \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Sortilin is the receptor to the precursor to nerve growth factor (proNGF) and it is abundantly expressed in the nervous system but also involved in tumorigenesis and overexpressed in different cancer forms, \u003cem\u003ee.g.\u003c/em\u003e, lung cancer and cervical cancer \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Interestingly, in head and neck squamous cell carcinoma (HNSCC), sortilin seems to regulate epidermal growth factor receptor (EGFr) expression and the expression is associated with worse prognosis \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eBiomarkers distinguishing OSCC from leuko-nonca\u003c/h2\u003e\u003cp\u003eOf the top twelve biomarkers distinguishing OSCC from leuko-nonca, all have been identified previously as biomarkers in cancer. Serpin B9 has been demonstrated to have multiple roles in cancer development. Studies show that serpin B9 seems to be a positive prognosticator for overall survival in colorectal cancer and melanoma \u003csup\u003e\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Cytosol aminopeptidase constitutes a prognosticator in diffuse large B cell lymphoma \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. The coding gene LAP3 for cytosol aminopeptidase constitutes a hub gene in Epstein-Barr virus-associated gastric carcinoma \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. SUMOylation is a post-translational modification regulating a number of biological processes and involved in carcinogenesis \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. The small ubiquitin-related modifier (SUMO)1\u0026ndash;4 proteins resemble the ubiquitin proteins in structure and SUMO1 and SUMO2 have been suggested to play a role in OSCC \u003csup\u003e\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCoactosin-like protein is involved in carcinogenesis and is significantly overexpressed in HNSCC and breast cancer compared to healthy breast tissue \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Interferon regulatory family proteins including interferon regulatory factor 9 (IRF9) are up-regulated in HNSCC and IRF9 is correlated with better overall survival in HNSCC \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Cleavage stimulation factor subunit 2 is a prognosticator for poor overall survival in hepatocellular carcinoma and OSCC \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Decreased expression of tapasin and increased expression of heat shock protein 105 kDa are correlated with poor survival in OSCC \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Damage-control phosphatase ARMT1 methylates proliferating cell nuclear antigen (PCNA) in breast cancer cell lines and modulates their sensitivity to chemotherapy and ultraviolet light \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. N-myc interactor modulates proliferation, migration and invasion of the cervical cancer cell line HeLa \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. The gene encoding synembryn-A, RIC8A, is more often mutated in metastatic breast cancer compared to early breast cancer \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Sequestome-1 is up-regulated in OSCC and correlated with EGFR expression, and sequestome-1 and EGFR expressions are positively correlated with poor survival in OSCC \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Taken together, the proteins identified in this study have earlier been shown to be of importance in established cancers, and our results point to an involvement also in the precancer stage. This raises possibilities for future use of these biomarker in predicting cancer development.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eProteins involved in epithelial differentiation in OSCC transformation\u003c/h2\u003e\u003cp\u003eAs a result of the loss of epithelial differentiation, biological pathways involved in skin development, epidermal development, and keratinocyte differentiation were downregulated in OSCC compared to leuko-ca. Among the downregulated proteins were keratin 1, keratin 10, keratin 76, cystatin-A, and corneodesmosin. Previous studies have shown that keratin 1 and keratin 10 are downregulated in OSCC compared to normal mucosa, and that keratin 76 is expressed at lower levels in OSCC than in OL \u003csup\u003e\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eCSTA\u003c/em\u003e (cystatin-A) and \u003cem\u003eCDSN\u003c/em\u003e (corneodesmosin) are important hub genes in OSCC, and their reduced expression is associated with poor prognosis \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e,\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. These observations indicate that deregulation of epithelial differentiation is more pronounced in OSCC as compared to the leuko-ca.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eInvolvement of the immune system in OSCC transformation\u003c/h2\u003e\u003cp\u003eImportantly, our study provides further evidence that the immune system is involved in the development of OSCC from OL. Antigen processing and presentation of endogenous peptide antigen, Antigen processing and presentation of peptide antigen via MHC class Ib, Antigen processing and presentation of peptide antigen and Immune response were in top of up-regulated biological pathways in OSCC compared with leuko-ca. Previous studies showed that the numbers of T cells, NK cells, macrophages and Langerhans cells increase in dysplastic OL and are associated with OSCC development \u003csup\u003e\u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. The numbers of CD8\u0026thinsp;+\u0026thinsp;T cells and T regulatory (Treg) cells are increased in proliferative OL compared with localized OL independently of the degree of dysplasia \u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. Thus, activation of different branches of the immune system occurs, which also our results confirm.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eImmunohistochemical expression of biomarkers\u003c/h2\u003e\u003cp\u003eAmong the top ten proteins identified from proteomics distinguishing SD-leuko-ca vs. leuko-nonca we selected kininogen-1, ApoE, perlecan and EEF1D to assess the expression in all tissue specimens with immunohistochemistry. All four proteins were expressed in the examined tissues; however, a quantitative analysis of the immunohistochemical results was not possible to conduct primarily due to insufficient number of samples across the four groups of tissues to support the objectivity of the statistical analysis. Nevertheless, we provided a qualitative description of the staining pattern of the proteins, which could serve as a basis for future research.\u003c/p\u003e\u003cp\u003eThe strength of our study is that we have longitudinally followed patients with OL to OSCC development and identified potential biomarkers identifying OL at risk of transformation to OSCC. However, our study has limitations since we studied only a low number of patients with OL. There was also a mixture of dysplastic and non-dysplastic lesions in the leuko-nonca and the leuko-ca groups. However, the limited number of patients did not allow consideration of dysplasia grade.\u003c/p\u003e\u003cp\u003eIn conclusion, biomarkers may discriminate OL with high risk of developing to OSCC. The immune system is involved in the pathogenesis of OL to OSCC. Future studies, validating the present identified panel discriminating OL with high risk of developing to OSCC from OL with low risk of developing to OSCC are warranted.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the Proteomics Core Facility, Sahlgrenska academy at the University of Gothenburg (with financial support from SciLifeLab and BioMS), for help with proteomics and analysis. We also would like to thank Olaf Schreurs at the Department of Oral Biology, University of Oslo, for valuable contribution in performing immunohistochemistry. The present study was sponsored by TUA (TUAGBG-978132; given to Professor Bengt Hass\u0026eacute;us) and King Gustav V Jubilee Clinic Cancer Research Foundation (2021:352; given to Associate Professor Daniel Giglio).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026acute; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDaniel Giglio: conceptualization, study design, planning, analyzed and interpreted data and drafted the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDivya Ganesh: retrieved tissue specimens and characterized patients\u0026acute; clinical data. Took part in analysis, interpretation of data and co-drafted the manuscript.\u003c/p\u003e\n\u003cp\u003eBishwa Prakash Bhattarai: performed and evaluated immunohistochemistry analyses, took part in analysis, interpretation of data and co-drafted the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTine Merete S\u0026oslash;land: evaluation of histopathological diagnoses and immunohistochemistry analyses, interpretation of data and co-drafted the manuscript.\u003c/p\u003e\n\u003cp\u003eJonas Sundberg: patient collection, evaluation, analyses and interpretation, critically reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003eAnnika Thorsell: study design, proteomics analyses of tissue specimens, evaluation, and interpretation of data, critically reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJenny \u0026Ouml;hman: patient collection, evaluation of clinical and histopathological diagnoses, analyses, interpretation of data and co-drafted the manuscript.\u003c/p\u003e\n\u003cp\u003eDipak Sapkota: evaluation of histopathological diagnoses and immunohistochemistry analyses, interpretation of data and co-drafted the manuscript.\u003c/p\u003e\n\u003cp\u003eBengt Hass\u0026eacute;us: conceptualization, study design, planning, patient collection, analyzed and interpreted data and co-drafted the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations and Competing Interests Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParts of the results have been presented at the European Association of Oral Medicine Conference 2023, London, UK. DG has been part of scientific advisory boards and/or has held scientific presentations for Merck, Roche and AstraZeneca. All other authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdditional data can be available upon request from the Institute of Clinical Sciences at the Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 3A SE-413 90 G\u0026ouml;teborg, Sweden. Email: [email protected].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was approved by the Regional Ethical Review Board in Gothenburg, Sweden (Dnr. 673\u0026ndash;10, T864-11).\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWarnakulasuriya, S. 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J.\u003cem\u003e et al.\u003c/em\u003e Comprehensive Immunoprofiling of High-Risk Oral Proliferative and Localized Leukoplakia. \u003cem\u003eCancer Res Commun\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 30-40, doi:10.1158/2767-9764.CRC-21-0060 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"oral potentially malignant disorder, oral squamous cell carcinoma, malignant transformation, proteomics","lastPublishedDoi":"10.21203/rs.3.rs-6688707/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6688707/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe here assessed protein biomarkers expressed in oral leukoplakia (OL) associated with the risk of transformation to oral squamous cell carcinoma (OSCC). Tissue specimen sections of OL transforming into OSCC (leuko-ca), the corresponding OSCC and OL not developing to OSCC (leuko-nonca) were analyzed with proteomics using nano-liquid chromatography-mass spectrometry, and immunohistochemistry was performed on identified biomarkers. The top enriched biological pathways in OL turning to OSCC within 5\u0026ndash;26 months from diagnosis (short duration (SD)-leuko-ca) \u003cem\u003evs.\u003c/em\u003e leuko-nonca were Cytoplasmic translation, Gene expression and Ribosomal large subunit biogenesis. Kininogen-1, apolipoprotein E (apoE), collagen alpha-1(XVIII) chain, sortilin and perlecan were top down-regulated candidate biomarkers, while EEF1D was the top up-regulated biomarker in SD-leuko-ca compared with leuko-nonca. The expressions in OL and OSCC of kininogen-1, apoE, perlecan and EEF1D were confirmed by immunohistochemistry. The top enriched biological pathways in OSCC compared with leuko-ca were Skin development, Antigen processing and presentation of endogenous peptide antigen, Epidermis development, Keratinocyte differentiation, Antigen processing and presentation of peptide antigen via MHC class Ib, Antigen processing and presentation of peptide antigen and Immune response. In conclusion, we have identified biomarkers in OL correlating with the risk of malignant transformation where the immune system seems to play an important role.\u003c/p\u003e","manuscriptTitle":"Biomarkers Correlating with the Development of Oral Squamous Cell Carcinoma from Leukoplakia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-10 15:32:07","doi":"10.21203/rs.3.rs-6688707/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e784534f-32e7-4128-9775-c21b6cf97332","owner":[],"postedDate":"July 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51266741,"name":"Biological sciences/Cancer/Oral cancer"},{"id":51266742,"name":"Biological sciences/Molecular biology/Proteomics"},{"id":51266743,"name":"Biological sciences/Cell biology/Mechanisms of disease"},{"id":51266744,"name":"Biological sciences/Cancer/Cancer screening"}],"tags":[],"updatedAt":"2026-02-04T11:26:03+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-10 15:32:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6688707","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6688707","identity":"rs-6688707","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}