Abstract
Objective
To compare circulating tumor DNA (ctDNA) levels between patients with oral squamous cell carcinoma (OSCC) and healthy controls.
Methods
A case-control study was conducted at Khyber College of Dentistry and Khyber Medical University, Peshawar. A total of 124 participants (94 OSCC patients and 30 healthy controls) were recruited using a non-probability consecutive sampling technique after obtaining the written informed consent. ctDNA was extracted from plasma and quantified using Qubit fluorometry and Nanodrop spectrophotometry. Real-time polymerase chain reaction (PCR) with TaqMan probes was used for detection. Independent t-tests compared ctDNA levels between OSCC patients and controls, and linear regression was conducted to assess the influence of age, gender, tumor site, and histopathological grade on ctDNA levels.
Results
The mean age of OSCC patients (56.82 ± 11.92 years) was significantly higher than that of controls (31.93 ± 7.10 years, p < 0.001). The most common tumor site was the buccal mucosa (20.16%), and moderately differentiated OSCC was the most prevalent histopathological grade (38.71%). The mean ctDNA level was significantly higher in OSCC cases (37.52 ± 8.71 ng/ml) compared to controls (11.00 ± 6.39 ng/ml, p < 0.001). Linear regression analysis confirmed significantly elevated ctDNA levels in OSCC cases (β = 28.13, 95% CI: 19.67–36.60, p < 0.001). Age, gender, tumor site, and histopathological grade did not significantly influence ctDNA levels.
Conclusion
OSCC patients exhibited significantly higher ctDNA levels than healthy controls. ctDNA quantification may serve as a promising non-invasive biomarker, though further validation is needed.
Keywords: Oral squamous cell carcinoma, Circulating tumor DNA, CtDNA, Biomarker, Case-control study
Introduction
Oral squamous cell carcinoma (OSCC) makes up about 90% of all oral cancers and is a major health concern worldwide, though its prevalence varies by region [1]. In North America, OSCC accounts for 10% of head and neck squamous cell carcinoma (HNSCC), with an age standardized incidence rate (ASIR) of 4.2 in men and 3.1 in women per 100,000. Rates are higher in Europe (12.1 in men, 7.4 in women) and India (9.4 in men, 5.5 in women) [2]. In Pakistan, OSCC is the most common cancer among males, with an age-standardized incidence rate (ASIR) of 88.1 per 100,000, and the third most common among females [3].
Early detection and prediction of prognosis of OSCC can aid effective management. Conventional diagnostic approaches primarily involve clinical evaluation and histopathological assessment [4]. However, recent advancements have identified less invasive biomarkers that improve the diagnostic and prognostic accuracy. Various biomarkers, including Cyclin D1, p53, Ki-67, p16, and vascular endothelial growth factors (VEGFs), play a role in determining the prognostic value of OSCC [5].
ctDNA has emerged as a valuable non-invasive biomarker for various malignancies, including OSCC. It consists of fragmented DNA released by tumor cells into the bloodstream, reflecting the genetic alterations present within the tumor microenvironment [6]. The detection and quantification of ctDNA provide critical insights into tumor burden, mutational profiles, and therapeutic response. In OSCC, ctDNA holds significant potential for early detection, real-time monitoring of disease progression, and the assessment of minimal residual disease following treatment [7]. Several studies have investigated the role of ctDNA in OSCC. Research has demonstrated that ctDNA can be detected in the plasma of OSCC patients and correlates with tumor stage and burden [8, 9].
Despite significant progress in the diagnosis and treatment of oral squamous cell carcinoma (OSCC), survival rates remain low, largely due to late-stage detection and disease recurrence. Circulating tumor DNA (ctDNA) presents a promising solution, as it provides insight into the genetic profile of tumors through a simple blood test. By analyzing ctDNA levels and associated genetic alterations, this study aims to evaluate its potential as a non-invasive tool for detecting and monitoring OSCC. This study is novel in that it is the first to investigate circulating tumor DNA (ctDNA) levels in OSCC patients within the Pakistani population, where no prior data currently exist. Unlike conventional diagnostic techniques such as tissue biopsy or imaging, which are often invasive, costly, and limited in detecting early or residual disease, ctDNA offers a minimally invasive approach that allows real-time monitoring of tumor dynamics through a simple blood sample. Its potential to reflect tumor burden and genetic alterations makes it a promising tool for earlier detection and better disease management.
The current study was aimed to compare the levels of ctDNA between OSCC patients and healthy controls.
Methods
This case control study was conducted at Khyber College of Dentistry and Khyber Medical University Peshawar from January 1, 2022 to January 1 2025 on 94 OSCC and 30 healthy control by non-probability consecutive sample technique.
Ethical approval
The ethical approval was obtained from Khyber medical university Pakistan No KMU/IPDM/IEC/2022 03. We declare that our research has strictly adhered to the ethical principles of Helsinki declaration and written informed consent was taken from all the participants after fully explaining the study and to ensure that their rights are fully protected.
Sample size
The sample size was determined using OpenEpi to be 86 participants (64 OSCC patients and 22 controls) based on 80% power and a 95% confidence level. This calculation was based on previously reported proportions of high ctDNA levels, 64.5% in OSCC patients and 30% in the control group [10]. However, to further increase the power of the study, we included a total of 124 participants (94 OSCC patients and 30 controls).
Inclusion criteria
Patients diagnosed with oral squamous cell carcinoma (OSCC) who had not undergone any cancer treatment, such as surgery, chemotherapy, or radiotherapy, and had adequate blood samples for ctDNA analysis were included as cases. The control group consisted of healthy individuals with no history of cancer, oral potentially malignant disorders like leukoplakia or oral submucous fibrosis, or chronic illnesses that could have affected ctDNA levels. Participants were Pakistani nationals of any gender who provided informed consent.
Exclusion criteria
Individuals with recurrent or metastatic OSCC, secondary cancers, recent major infections, significant inflammatory conditions, or serious systemic diseases were excluded. Pregnant or breastfeeding individuals and those with poor-quality blood samples for ctDNA testing were also excluded.
All individuals in the control group underwent a thorough intraoral examination performed by a trained dental professional using a mouth mirror and proper lighting. All areas of the oral cavity—including the buccal mucosa, tongue, floor of the mouth, palate, and gingiva—were carefully inspected to confirm the absence of any visible premalignant, malignant, or suspicious lesions. In addition, a brief medical history was recorded to identify any previous surgeries, ongoing medical conditions, or prior consultations related to oral health, ensuring the selection of clinically healthy individuals for the control group.
Outcome measures
For each patient, we collected key demographic and clinical data, including age, gender, tumor site, and the histopathological grade of OSCC. The tumor site was documented based on clinical and biopsy reports, categorizing lesions by their specific location in the oral cavity. The histopathological grade of OSCC was classified as well-differentiated, moderately differentiated, or poorly differentiated, based on the analysis of biopsy reports. Well-differentiated tumors showed cells that closely resembled normal squamous cells, with significant keratin production and minimal cell variation. Moderately differentiated tumors had some features of normal cells but with more variation and less keratinization. Poorly differentiated tumors were characterized by marked abnormality in cell structure, minimal keratin production, and significant variations in cell size and shape. These classifications were determined by experienced pathologists following the established WHO guidelines.
Laboratory procedure
Blood samples were collected from all participants. Each 10 mL blood sample was drawn into ethylenediaminetetraacetic acid (EDTA) tubes (BOLTON scientific limited EDTA, K3) and processed within an hour. Plasma was separated through a two-step centrifugation process and stored at -80 °C until analysis. ctDNA was extracted using a column-based (Nucleospin XS extraction kit), and its concentration was measured using Qubit fluorometry and Nanodrop spectrophotometry, reported in nanograms per microliter (ng/µL). To detect ctDNA, we used specific primers and a TaqMan probe based on previously published sequences [11]. Real-time PCR (QuantStudio5 applied biosystems by thermos fisher scientific) was performed using TaqMan Universal Master Mix, and Ct values were calculated to determine the copy number of ctDNA. A melting curve analysis was done to confirm the accuracy of amplification. Figure 1.
Fig. 1.
Flow diagram of steps involved in ctDNA quantification
Statistical analysis
All data analysis was performed using R software version 4.3.1. The mean and SD were computed for continuous data, such as ctDNA levels and age. Categorical data, including gender, site, and grade of the tumor, were presented as percentages with frequencies. An independent two-sample t-test was conducted to compare ctDNA levels between the OSCC and control groups. To control for confounders, linear regression analysis was performed using ctDNA as the dependent variable and the type of participant (healthy versus OSCC), gender, age, site, and grade of OSCC as independent variables. A p-value of < 0.05 was set as the threshold to detect significant differences.
Results
The mean age of participants with OSCC (56.82 ± 11.92 years) was significantly higher than that of healthy controls (31.93 ± 7.10 years, p < 0.001). Gender distribution did not differ significantly between groups (p = 0.21), with males comprising 68.09% of the OSCC group and 80% of the healthy controls, while females accounted for 31.91% and 20.00%, respectively. (Table 1)
Table 1.
Distribution of age and gender of the participants
| Characteristic | OSCC, N = 94 | healthy, N = 30 | p-value |
|---|---|---|---|
| Age (years), Mean ± SD | 56.82 ± 11.92 | 31.93 ± 7.10 | < 0.001* |
| Gender, n (%); | 0.21 | ||
| female | 30 (31.91) | 6 (20.00) | |
| male | 64 (68.09) | 24 (80.00) |
OSSC; Oral squamous cell carcinoma, *Welch Two Sample t-test; **Pearson’s Chi-squared test
The most common tumour site was the buccal mucosa (20.16%), followed by the lip (12.90%), floor of the mouth (12.10%), and tongue (11.29%). In terms of tumour differentiation, moderately differentiated OSCC was the most prevalent (38.71%), followed by well-differentiated (28.23%) and poorly differentiated tumours (8.87%). (Fig. 2)
Fig. 2.
Distribution of grade and site of tumor
The mean ctDNA level was significantly higher in OSCC cases (37.52 ± 8.71ng/ml) compared to healthy controls (11.00 ± 6.39 ng/ml, p < 0.001). (Fig. 3)
Fig. 3.
ctDNA level among healthy versus OSCC cases
The linear regression analysis showed that ctDNA levels were significantly higher in OSCC cases compared to healthy controls (β = 28.13, 95% CI: 19.67–36.60, p < 0.001). Age (β = -0.09, p = 0.195) and gender (β = 3.09 for females, p = 0.076) were not significant predictors. Tumour differentiation did not show a significant effect, with well-differentiated (β = 2.18, p = 0.458) and moderately differentiated tumours (β = 0.84, p = 0.763) showing no substantial differences compared to poorly differentiated tumours. Tumour site also had no significant impact on ctDNA levels. The model explained 69.7% of the variance in ctDNA levels (adjusted R² = 0.667). (Table 2)
Table 2.
Linear regression for ctdna level by group, gender age, grade and site of tumor
| Predictors | characteristics | ctDNA | ||
|---|---|---|---|---|
| Estimates | CI | p | ||
| (Intercept) | (Intercept) | 13.38 | 7.84–18.92 | < 0.001 |
| Group | Healthy control | ref | ref | |
| OSSC | 28.13 | 19.67–36.60 | < 0.001 | |
| Age (years) | -0.09 | -0.24–0.05 | 0.195 | |
| Gender | Male | ref | ref | |
| Female | 3.09 | -0.33–6.50 | 0.076 | |
| Grade of tumour | Poorly differentiated | ref | ref | |
| well differentiated | 2.18 | -3.61–7.97 | 0.458 | |
| moderately differentiated | 0.84 | -4.65–6.32 | 0.763 | |
| Tumour site | Alveolar mucosa | ref | ref | |
| Buccal mucosa | -0.64 | -6.34–5.07 | 0.825 | |
| Floor of mouth | -2.63 | -8.77–3.51 | 0.398 | |
| Lip | -1.57 | -7.87–4.73 | 0.623 | |
| Palate | 2.55 | -6.09–11.20 | 0.56 | |
| Retromolar | -6.75 | -14.98–1.49 | 0.107 | |
| Tongue | 1.84 | -4.47–8.14 | 0.565 | |
Observations 124
R2 / R2 adjusted 0.697 / 0.667
Discussion
ctDNA holds great promise as a non-invasive biomarker for the early detection and management of oral squamous cell carcinoma (OSCC). Unlike traditional biopsies, ctDNA can be obtained through a simple blood draw, allowing for real-time monitoring of tumor genetics. Studies have shown that higher ctDNA levels often correlate with tumor size and disease progression, making it useful not only for detecting cancer earlier but also for tracking response to treatment and identifying recurrence [12]. ctDNA analysis has been effective in detecting minimal residual disease and predicting relapse in several cancers, highlighting its role in improving patient outcomes [13]. Further research is needed to fully establish ctDNA’s clinical utility in OSCC, especially across diverse patient populations.
Our results indicate that OSCC patients were, on average, significantly older than the healthy controls. Lin et al. [10] found higher plasma cell-free DNA (cfDNA) levels in OSCC patients compared to controls, with correlation between elevated cfDNA and older age. Our study found no significant difference between male and female OSCC patients and healthy controls, which aligns with existing research [14]. While OSCC is more common in males, studies show that gender does not affect ctDNA levels. Lin et al. [10] studied a younger Taiwanese cohort with a higher proportion of females, differing from our male-dominated sample. On the other hand, Hamana et al. [15] studied older Japanese patients with a more balanced gender distribution, while Kakimoto et al. [16] observed a similar male-to-female ratio to the current study. These differences may be due to geographic, genetic, and lifestyle factors. Variations in environmental exposures, such as tobacco and alcohol use, as well as genetic factors, could contribute to these discrepancies.
The most common tumor site in our study was the buccal mucosa, followed by the lip, floor of the mouth, and tongue. A study in Swat on OSCC found that the most common site was the alveolar ridge, followed by the buccal mucosa and hard palate [17]. Another study in the United Arab Emirates reported that the most common site of OSCC was the anterior two-thirds of the tongue (57.6%), followed by the cheek (28.1%) [18]. A study conducted in India found that the most common site of recurrent OSCC was the buccal mucosa, while the least common sites were the submandibular region and the gingivobuccal sulcus [19].
Our study showed that tumor differentiation; moderately differentiated OSCC was most prevalent, followed by well-differentiated and poorly differentiated tumors. Another study from Swat showed that most common was well-differentiated followed by moderately differentiated OSSC [17]. Another study from Lahore reported that 49% of OSCC cases were well-differentiated, 40.8% were moderately differentiated, and the remaining were poorly differentiated [8].
In our study, the mean ctDNA level observed in healthy individuals was 11 ng/mL, which falls slightly above the previously reported range of 1–10 ng/mL for healthy populations (Wan et al. [13]). This finding aligns with existing literature suggesting that low levels of ctDNA may be detectable even in individuals without a diagnosed malignancy, potentially due to background biological processes such as apoptosis, inflammation, or clonal hematopoiesis. Importantly, the ctDNA level in OSCC patients (37.52 ng/mL) was significantly higher, supporting its relevance as a hallmark of cancer and reinforcing its potential role as a non-invasive biomarker for early detection and disease monitorin.
Our study identified significantly elevated mean ctDNA levels in OSCC patients compared to healthy controls, a finding consistently reported in previous research. Lin et al. [10] and Desai et al. [9] similarly observed increased plasma cfDNA concentrations in OSCC patients, with levels positively correlated with tumor size and disease stage. This elevation in ctDNA can be attributed to several oncogenic processes. OSCC is characterized by accelerated cellular proliferation and turnover, leading to increased cell death through apoptosis and necrosis. Apoptotic pathways predominantly generate shorter, fragmented DNA, whereas necrotic cell death—often induced by hypoxia and inflammatory responses in the tumor microenvironment—results in the release of larger, more heterogeneous DNA fragments into circulation. Tumors exhibiting high genomic instability further contribute to increased ctDNA shedding due to the accumulation of chromosomal aberrations and mitotic errors [20]. Moreover, the extensive neovascularization observed in OSCC facilitates the dissemination of ctDNA into the bloodstream. As tumor expansion disrupts normal tissue architecture, the associated inflammatory and immune responses further augment the release of tumor-derived genetic material [21].
Our multivariate analysis found that ctDNA levels were significantly higher in OSCC patients compared to healthy individuals. However, factors like age, gender, tumor differentiation, and tumor site did not significantly influence ctDNA levels. These findings align with previous research, suggesting that ctDNA is more reflective of tumor burden and disease progression rather than patient demographics or specific tumor characteristics [10]. A study involving 121 OSCC patients and 50 healthy controls found that cfDNA levels were markedly higher in OSCC cases. Moreover, higher cfDNA levels were linked to larger tumors, lymph node involvement, and advanced disease stages rather than factors like age or gender [10]. Similarly, a study on 418 cancer patients showed that the total number of ctDNA alterations was a strong predictor of survival. Interestingly, it found no meaningful association between ctDNA levels and demographic variables like age or gender, reinforcing the idea that ctDNA serves as a marker of tumor progression rather than patient characteristics [22].
In this study we used non-probability sampling. Due to the hospital-based nature of this study, non-probability sampling was employed, as a defined sampling frame of OSCC patients and healthy individuals was not available. While this approach may introduce selection bias, efforts were made to apply clear inclusion and exclusion criteria to ensure consistency across groups. Furthermore, to account for potential confounding variables and strengthen the validity of the comparisons, linear regression analysis was performed during data analysis.
This study has some limitations. The sample size, especially for the control group, was relatively small, which may affect how well the results apply to a broader population. Since all participants were recruited from a single hospital using non-probability sampling, there is a chance of selection bias. Additionally, the OSCC patients were generally older than the controls, which could influence ctDNA levels despite adjustments in the analysis. Finally, we measured overall ctDNA levels but did not analyze specific genetic changes that might provide more detailed information about the tumors. Future studies with larger groups from multiple centers and more detailed genetic testing are needed to confirm and build on these results.
Conclusion
OSCC patients exhibited significantly higher ctDNA levels than healthy controls. ctDNA quantification may serve as a valuable biomarker for OSCC detection. Further studies with long term are required to validate its clinical efficacy for prognostic purpose.
Abbreviations
- OSCC
Oral Squamous Cell Carcinoma
- ctDNA
Circulating Tumor DNA
- PCR
Polymerase Chain Reaction
- HNSCC
Head and Neck Squamous Cell Carcinoma
- EDTA
Ethylenediaminetetraacetic acid
- ASIR
Age Standardized Incidence Rate
- VEGF
Vascular Endothelial Growth Factor
Author contributions
Samrina mohammad: Original draft, Writing- review and editing; Asif Ali: Conceptualization, Supervision; Ihsan Ullah: Methodology; Zainab Jan: Writing, Review & Editing; Muslim Khan: Data Analysis, Review & Editing.
Funding
This research is funded by ICRG-46 Higher Education Commission Pakistan.
Data availability
The data is available from the corresponding author on reasonable request.
Declarations
Ethical approval and consent to participate
The ethical approval was obtained from Khyber medical university Pakistan No KMU/IPDM/IEC/2022 03. We declare that our research has strictly adhered to the ethical principles of Helsinki declaration and written informed consent was taken from the participants and ensure that their rights are fully protected.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Samrina Mohammad, Email: drsamrina@hotmail.com.
Ihsan Ullah, Email: drihsan.ibms@kmu.edu.pk.
References
- 1.Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2021;71(3):209–49. [DOI] [PubMed] [Google Scholar]
- 2.Saberian E, Jenča A, Petrášová A, Jenčová J, Jahromi RA, Seiffadini R. Oral cancer at a glance. Asian Pac J Cancer Biol. 2023;8(4):379–86. [Google Scholar]
- 3.Shamsi U, Khan MAA, Qadir MS, Rehman SSU, Azam I, Idress R. Factors associated with the survival of oral cavity cancer patients: a single institution experience from karachi, Pakistan. BMC Oral Health. 2024;24(1):1427. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Almangush A, Heikkinen I, Mäkitie AA, Coletta RD, Läärä E, Leivo I, et al. Prognostic biomarkers for oral tongue squamous cell carcinoma: a systematic review and meta-analysis. Br J Cancer. 2017;117(6):856–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Pekarek L, Garrido-Gil MJ, Sánchez-Cendra A, Cassinello J, Pekarek T, Fraile-Martinez O, et al. Emerging histological and serological biomarkers in oral squamous cell carcinoma: applications in diagnosis, prognosis evaluation and personalized therapeutics. Oncol Rep. 2023;50(6):213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Sánchez-Herrero E, Serna-Blasco R, Robado de Lope L, González-Rumayor V, Romero A, Provencio M. Circulating tumor DNA as a cancer biomarker: an overview of biological features and factors that May impact on ctdna analysis. Front Oncol. 2022;12:943253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Lauritano D, Lucchese A, Contaldo M, Serpico R, Lo Muzio L, Biolcati F, et al. Moral squamous cell carcinoma: diagnostic markers and prognostic indicators. J Biol Regulat Homeos Agent. 2016;30(2):169–76. [PubMed] [Google Scholar]
- 8.Khan NR, Naseem N, Riaz N, Anjum R, Khalid S, Iqbal A, et al. Oral squamous cell carcinoma Clinico-pathological features in relation to tumor stage; AJCC 2018 perspective. Pak J Med Sci. 2023;39(2):395. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Desai A, Kallianpur S, Mani A, Tijare MS, Khan S, Jain M, et al. Quantification of Circulating plasma cell free DNA fragments in patients with oral cancer and precancer. Gulf J Oncol. 2018;1(27):11–7. [PubMed] [Google Scholar]
- 10.Lin L-H, Chang K-W, Kao S-Y, Cheng H-W, Liu C-J. Increased plasma Circulating cell-free DNA could be a potential marker for oral cancer. Int J Mol Sci. 2018;19(11):3303. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Asiyah B, Zahid K, Asif A, Nighat N. Comparison of methods of isolation and quantification of cell free DNA from plasma of patients with breast Cancer. Pak-Euro J Med Life Sci. 2021;4(4):359–66. 10.31580/pjmls.v4i4.2435. [Google Scholar]
- 12.Yang R, Li T, Zhang S, Shui C, Ma H, Li C. The effect of Circulating tumor DNA on the prognosis of patients with head and neck squamous cell carcinoma: a systematic review and meta-analysis. BMC Cancer. 2024;24(1):1434. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Wan JC, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, et al. Liquid biopsies come of age: towards implementation of Circulating tumour DNA. Nat Rev Cancer. 2017;17(4):223–38. [DOI] [PubMed] [Google Scholar]
- 14.Huang X, Duijf PH, Sriram S, Perera G, Vasani S, Kenny L, et al. Circulating tumour DNA alterations: emerging biomarker in head and neck squamous cell carcinoma. J Biomed Sci. 2023;30(1):65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Hamana K, Uzawa K, Ogawara K, Shiiba M, Bukawa H, Yokoe H, et al. Monitoring of Circulating tumour-associated DNA as a prognostic tool for oral squamous cell carcinoma. Br J Cancer. 2005;92(12):2181–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Kakimoto Y, Yamamoto N, Shibahara T. Microsatellite analysis of serum DNA in patients with oral squamous cell carcinoma. Oncol Rep. 2008;20(5):1195–200. [PubMed] [Google Scholar]
- 17.Shah A, Uddin Z, Masooma S, Akhtar R, Kumar T. Pattern and site distribution of oral squamous cell carcinoma. J Saidu Med Coll. 2025;15(1):44–9. [Google Scholar]
- 18.Al-Rawi NH, Hachim IY, Hachim MY, Salmeh A, Uthman AT, Marei H. Anatomical landscape of oral squamous cell carcinoma: A single cancer center study in UAE. Heliyon. 2023;9(5):e15884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Reichal P, Ramani P, Kizhakkoottu S. Association of site and recurrence in oral squamous cell carcinoma patients visiting private hospital in chennai: a retrospective study. Cureus. 2024;16(1):e52774. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Stejskal P, Goodarzi H, Srovnal J, Hajdúch M, van’t Veer LJ, Magbanua MJM. Circulating tumor nucleic acids: biology, release mechanisms, and clinical relevance. Mol Cancer. 2023;22(1):15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ghiyasimoghaddam N, Shayan N, Mirkatuli HA, Baghbani M, Ameli N, Ashari Z, et al. Does Circulating tumor DNA apply as a reliable biomarker for the diagnosis and prognosis of head and neck squamous cell carcinoma? Discover Oncol. 2024;15(1):427. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Vu P, Khagi Y, Riviere P, Goodman A, Kurzrock R. Total number of alterations in liquid biopsies is an independent predictor of survival in patients with advanced cancers. JCO Precision Oncol. 2020;4:192–201. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data is available from the corresponding author on reasonable request.



