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BMC Cancer

, 19:467 | Cite as

A novel integrated platform for the identification of surgical margins in oral squamous cell carcinoma: results from a prospective single-institution series

  • Alessandro Baj
  • Nicola Fusco
  • Alessandro Bolzoni
  • Daniela Carioli
  • Camilla Mazzucato
  • Alice Faversani
  • Lorenzo Bresciani
  • Marco Maggioni
  • Pasquale CapaccioEmail author
Open Access
Research article
  • 108 Downloads
Part of the following topical collections:
  1. Surgical oncology, cancer imaging, and interventional therapeutics

Abstract

Background

The optimal surgical margins assessment is capital in oral squamous cell carcinoma (OSCC) management. We evaluated the clinical benefits of integrating intraoperative macroscopic margin (MM) assessment and narrow band imaging (NBI).

Methods

Sixteen OSCC patients eligible for surgery were prospectively enrolled. For each patient, 2 to 6 bioptic samples of MM and NBI margins were obtained and histologically analyzed for the presence of dysplasia and lymphocytes. Microvessel density was investigated by CD34 immunohistochemistry.

Results

Taken together, 104 specimens were analyzed, including 15% tumors, 33% MM, 33% NBI margins, and 19% MM-NBI overlapping margins. The NBI margins were closer to the lesion in 50% cases, while the same number of MM were more conservative than NBI, irrespective of the tumor site. The rate of histologically positive margins was similar among the two methods, akin to the microvessel density.

Conclusions

MM assessment should be integrated but not replaced with the NBI technology to allow for more conservative surgery.

Keywords

Oral squamous cell carcinoma NBI Narrow band imaging Microvascular density Surgical margins 

Abbreviations

ENE

Extranodal extension

ENT

Ears, nose and throat

H&E

Hematoxylin and eosin

IHC

Immunohistochemistry

MD

Microvessel density

MM

Macroscopic margins

NBI

Narrow band imaging

OSCC

Oral squamous cell carcinoma

TILs

Tumor infiltrating lymphocytes

Background

Oral squamous cell carcinoma (OSCC) is the most frequent histological type of head and neck cancer and one of the most prevalent malignant neoplasms worldwide [1]. Despite the recent achievements in the diagnosis and treatment of these patients, OSCC is showing increasingly high recurrence rates [2, 3]. Due to its clinical and biological complexity, therapeutic decision-making is not an easy task, even in multidisciplinary settings. Anatomical site, clinical stage, and pathological features of the primary tumor are the foremost elements to guide OSCC treatment, which remains surgically-based either in single or in combined therapeutic settings [4]. During surgical removal, the visible neoplastic area should be resected with a threshold of normal tissue, whose edge represents the mucosal margin [5]. To improve patient’s outcome, the surgical radicality (i.e. histologically-proved negativity of the mucosal margin) is fundamental [6]. Indeed, there are multiple lines of evidence to suggest that failure to reach clear margins in OSCC is related to an increased risk of local recurrence and, subsequently, reduced chances of survival. However, there are no widely adopted guidelines for pre- and intra-operative margins identification. To date, finding the “golden strategy” for the optimal assessment of the surgical margins remains one of the most critical issues in OSCC management [7, 8].

Several approaches have been proposed to enhance the traditional white-light macroscopic margins (MM) identification in OSCC. Among them, the Narrow Band Imaging (NBI) technology have shown good performance and is currently employed in several Centers [9, 10]. This augmented reality tool increases the contrast between the epithelial surface and the subjacent vascular network, allowing for the visualization of the mucosal and submucosal (micro) vascular patterns. The principle by which NBI can be employed for surgical margin assessment is based on the evidence that neoangiogenesis is a crucial step in tumor growth and metastatic spread. Therefore, the in vivo analysis of blood-specific light traces could help identifying oral potentially malignant disorders or even overt malignant conditions at the periphery of the resected tumor. Furthermore, several studies have demonstrated that microvessel density (MD) assessed by histological and immunohistochemical analysis can be employed as a prognostic biomarker for OSCC [11, 12, 13].

Our work aims to evaluate the potential surgical benefits of mucosal margin assessment for OSCC using a platform which integrates intraoperative MM and NBI.

Methods

Patients and tissue specimens

This pilot prospective non-randomized study was approved by the local ethics committee (approval #19_2018bis). A total of 16 patients (10 males, 6 females) with OSCC eligible for surgical treatment were enrolled. Informed consent was obtained from all patients. Only patients diagnosed and managed in IRCCS Ca′ Granda Foundation – Policlinico Maggiore Hospital, Milan, Italy, > 18 years old, chemotherapy- and radiotherapy-naïve, with no history of cancer were included. All patients underwent surgical treatment with a program established according to the guidelines of the American Joint Committee on Cancer (7th edition) [2].

Macroscopic and narrow band imaging surgical margins assessment in vivo

The MM was assessed by a craniofacial surgeon at a distance of 1,5–2 cm from the tumor, as described (Fig. 1a) [7, 14]. Subsequently, two ears, nose and throat (ENT) surgeons performed intraoperative NBI endoscopic evaluation using a scope of 4 mm outside diameter (Olympus Visera Pro system, Center Valley, PA America, with OTV-S7Pro camera and CLV-S40Pro light source). This intraoperative analysis allowed for the identification of the interface between the likely neoplastic/dysplastic and likely healthy areas, i.e. NBI margin. Next, the maxillofacial surgeon performed multiple biopsies of both the MM and the NBI margins. For each patient, from 2 to 6 bioptic samples were obtained. The NBI margins were then classified as overlapping, external, or internal, compared to the MM. In case of overlap between the MM and NBI margins, only one biopsy was performed (Fig. 1).
Fig. 1

a Schematic overview of the study. TILs are highlighted by stars. Original magnification of the micrographs 100X. b Schematic image of MM and NBI margins for the 16 OSCC patients. Red dots represent the cardinal points related to the biopsies performed for the excision of the mucosal margins

Histopathological analysis and pathologic surgical margins assessment

Hematoxylin and eosin (H&E) stained frozen sections of the MM margins were intraoperatively analyzed by a pathologist as part of the standard protocol to drive the surgical intervention. All surgical samples, including the tumor, the MM and NBI margins, were then analyzed after tissue processing by two pathologists (NF and MM), as shown in Fig. 1a. Specifically, all cases were classified and graded following the latest World Health Organization criteria [15]. Pathologic staging was assessed according to the current TNM staging system [16]. The presence of tumor infiltrating lymphocytes (TILs) was assessed as described [17]. The MM and NBI surgical margins were defined as positive in the presence of OSCC and/or dysplasia; otherwise, they were marked as negative.

Immunohistochemistry and microvessel density analysis

MD was investigated by immunohistochemistry (IHC) in the MM and NBI surgical margins. Representative 4-μm-thick sections were cut from the MM, NBI, and tumor blocks and subjected to IHC using pre-diluted antibodies against CD34 as previously described [18]. Positive and negative controls were included in each slide run. Briefly, the protocols use an automated staining system (Dako Omnis) and anti-human prediluted antibodies [19]. Protein expression was analyzed in all different samples by two independent pathologists (NF and SF). Discordant results were resolved during dedicated consensus sessions. Sections were first observed at low magnification (40x) to identify the areas with the higher concentration of vessels. Then, the vessels count was performed at 200x by means of a customized digital image analysis algorithm using the Aperio CS2 instrument (Leica Microsystems Srl) [20]. The MD value was expressed as a percentage. Each CD34-positive structure (round, oval, and irregular) separated from other profiles or tissue elements was counted as a single vessel, regardless of the presence of a clear lumen.

Statistical analysis

Data were analyzed using Prism 4.0 (GraphPad Inc., La Jolla, CA, USA). Differences among sample groups were analyzed using the unpaired Student’s t-test as previously described [21]. The association between positive margins was evaluated by Fisher’s exact test according to the classification proposed by Piazza and collaborators [22]. Statistical significance was assumed for a probability value (p) less than 0.05.

Results

Sixteen patients (10 males and 6 females) who underwent surgery for OSCC were included in this study (age 23 to 92 years old, mean 68 years). Tumor sites included the tongue (n = 6), lower alveolar ridge/mandible (n = 3), hard palate (n = 2), cheek (n = 2), floor of mouth (n = 2), and upper alveolar ridge/maxilla (n = 1). Clinicopathologic data are summarized in Table 1.
Table 1

Demographic and clinicopathologic features of the study group

Features

Number of cases (%)

Sex

 Male

10 (62.5)

 Female

6 (37.5)

Age

 Mean

68.25

Smoking

 Yes

3 (19)

 No

4 (25)

 Ex smoker

9 (56)

Alcohol

 Yes

12 (75)

 No

3 (19)

 Ex drinker

1 (6)

Site

 Tongue

6 (37.5)

 Mandible

3 (19)

 Palate

2 (12.5)

 Cheek

2 (12.5)

 Floor of the mouth

2 (12.5)

 Maxilla

1 (6)

T Staging

 T1

6 (37.5)

 T2

5 (31.25)

 T3

1 (6.25)

 T4

4 (25)

N Staging

 Nx

3 (18.75)

 N0

7 (43.75)

 N1

3 (18.75)

 N2

3 (18.75)

Grading

 G1

2 (12.5)

 G2

13 (76.4)

 G3

1 (6.25)

Vascular invasion

 Yes

0

 No

9 (56.25)

Perineural invasion

 Yes

5 (31.25)

 No

11 (68.75)

Integration of MM and NBI margins is superior to MM and NBI alone

Taken together, 104 specimens were analyzed, including 16 (15.4%) tumors, 34 (32.7%) MM, 34 (32.7%) NBI margins, and 20 (19.2%) MM-NBI overlapping margins (Fig. 1b). The NBI margins were closer to the lesion in 17 (50%) cases (Fig. 1b) compared to the MM assessment. However, this method showed no propensity to allow for a more conservative resection, given that in the same number of margins (n = 17, 50%) was the MM the more conservative approach. Furthermore, this heterogeneity was irrespective of the tumor site and was not present at a single-patient level. At the histological examination, the margins collected with the MM intraoperative assessment revealed dysplasia in 3 (8.8%) cases and OSCC in 1 (2.9%) case, while 30 (88.2%) samples were negative as represented in Table 2 and Fig. 2a. The analysis of the NBI margins showed dysplasia and OSCC in 2 (5.9%) and 1 (2.9%) cases; respectively, while 31 (91.2%) margins were negative, as confirmed by histological examination (Table 2 and Fig. 2b). Among the 20 overlapping MM-NBI margins, 2 (10%) cases were positive. In particular, positive margins showed a significant association with thick and thin non-keratinized epithelial cells [23] (p = 0.027). These data suggest that the intraoperative integration of MM and NBI analysis might allow for a more conservative excision of OSCC compared to each of the two methods alone.
Table 2

Demographic, clinicopathologic characteristics, and surgical margins status of the patients included in this study. NBI, narrow-band imaging; MM, macroscopic margin, AU, alcohol units; n.a., not available; RT, radiotherapy; CT, chemotherapy. When NBI and MM were overlapping, only one biopsy was performed

Case

Age (range)

Smoking

Alcohol

Site

Piazza et al. Classification [23]

Staging TNM

Grading

Lympho-vascular/Perineural invasion

Sample 1 NBI/MM

Sample 2 NBI/ MM

Sample 3 NBI/ MM

Sample 4 NBI/ MM

Adjuvant Therapy

1

50–60

No

Yes (2 AU/die)

Lateral Tongue

2b

T1Nx

G2

No/No

−/−

No

2

70–80

Ex

Yes (2 AU/die)

Floor of mouth

2a

T2 N0

G2

No/Yes

−/−

n.a.

n.a.

RT

3

50–60

Yes

Yes (2 AU/die)

Ventral Tongue

2a

T2 N0

G2

No/Yes

−/−

−/−

n.a.

n.a.

RT

4

50–60

Ex

Yes (1 AU/die)

Floor of mouth

2a

T1(m)Nx

n.a.

No/No

+/−

−/−

−/−

n.a.

CT + RT

5

50–60

Ex

Yes (1 AU/die)

Maxilla/Alveolar Mucosa

1

T4aNx

G1

No/No

−/−

−/−

n.a.

n.a.

No

6

> 80

No

Yes (1 AU/die)

Mandible/Alveolar Mucosa

1

T4aN0

G1

No/No

−/−

−/−

−/−

−/−

No

7

60–70

Ex

Yes (1 AU/die)

Lateral Tongue

2b

T1 N1(E-)R1

G2

No/No

n.a.

−/−

−/+

CT + RT

8

> 80

No

No

Cheek

2b

T2N1R0

G2

No/Yes

n.a.

−/+

−/−

No

9

> 80

No

Ex Drinker

Hard Palate

1

T4aN2b (E-) R0

G2

No/No

−/−

No

10

70–80

Ex

No

Mandible/Retromolar Trigone

2b

T2 N1 (E-) R0

G3

No/No

+/−

−/−

−/−

RT

11

< 30

Ex

Yes (1 AU/die)

Lateral Tongue

2b

T2N2b

G2

No/Yes

+/+

−/−

+

−/−

CT + RT

12

60–70

Ex

Yes (1 AU/die)

Mandible/Alveolar Mucosa

1

T2 N0R0

G2

No/Yes

−/−

No

13

> 80

Yes

No

Lateral Tongue

2b

T1N2b

G2

No/No

−/+

No

14

> 80

Ex

Yes (1 AU/die)

Cheek

2b

T1 N0

G2

No/No

+

−/−

−/−

−/−

No

15

70–80

Ex

Yes (1 AU/die)

Hard Palate

1

T4aN0

G2

No/No

−/−

−/−

−/−

No

16

50–60

Yes

Yes (1 AU/die)

Floor of mouth

2a

T1 N0

G2

No/No

−/−

n.a.

−/−

No

Fig. 2

a Representative histological micrographs of the primary tumor, NBI and MM margins in a case (#7) where NBI margins are negative and a MM shows low-grade dysplasia. b Representative histological micrographs of the primary tumor, NBI and MM margins in a case (#4) were an NBI margin is positive for high-grade dysplasia, while MM are negative. Original magnification is 100X. c CD34 protein levels in positive (red) and negative (cyan) margins. p < 0.0001 by unpaired Student’s t-test

High levels of microvessel density are related to positive mucosal margins irrespective of the method used for their assessment

MD has been investigated in 83 margins and matched OSCCs. This analysis showed significantly high CD34 levels in pathological margins compared to the normal ones (p < 0.0001, Fig. 2c). This observation was unrelated to the intraoperative method of surgical margins assessment (i.e. MM and NBI). Internal and external margins didn’t show a statistically significant different MD, akin to the tumor site.

Discussion

The use of new technologies to investigate tumor behavior and microenvironment is of great interest in this era of precision medicine. Several studies unraveled the role of molecular biomarkers for the diagnostic and therapeutic process in patients with OSCC [24, 25, 26]. The application of “biologic endoscopy” to intraoperative surgical procedures represents another step forward towards the realization of the potentials of customized surgery [9, 10, 27, 28]. Autofluorescence detection and NBI technology have already been tested in the definition of resection margins in OSCC and demonstrated to be reliable and cost-effective [9, 29]. Poh et al. [29] described the ability of autofluorescence to identify malignant and pre-malignant lesions. Tirelli et al. [10] reported an overall diagnostic gain of 8.5% using NBI, allowing a better definition of the tumor extension. They observed adequate resection margins in 74.2% of cases. Moreover, a resection enlargement of 11 ± 3 mm was performed consequently for intraoperative NBI evaluation [9], which revealed moderate dysplasia and cancer in 25 and 75% of samples respectively.

In this study, we performed a comparison between the mucosal margins assessment by MM and NBI, using their histological counterparts as "gold standard". Overall, we have observed that 50% of NBI margins were external or internal to the traditional surgical (i.e. MM) ones. These results confirm previous observations that NBI margins are usually wider than MM margins [9]. Interestingly, we observed that in approximately 30% of cases the NBI technology coupled with traditional surgical assessment is able to reduce the extent of the resection, as confirmed by the histological analysis. Moreover, NBI and MM specimens revealed 2 and 3 mild dysplasia, respectively. In particular, positive margins were significantly localized in thick and thin non-keratinized epithelia with a low papillary density [23]. These data confirm the safety of the NBI technique and provide previously unavailable data that the integration of MM and NBI margins is superior to MM and NBI alone in OSCC surgical management [23, 30].

There are several lines of evidence that the activation of neoangiogenesis pathways represents a founder molecular event in OSCC initiation and progression [31]. Previous studies have demonstrated that high levels of MD are associated with a more aggressive clinical course in head and neck cancers [31, 32, 33, 34, 35]. In the present study, MD was quantified by the measurement of the areas lined by elements expressing CD34, which is a transmembrane protein encoded by the homonymous gene located at chromosome 1q. Taken together, we detected significant higher levels of MD in the positive margins compared to the normal mucosa. In several solid tumors, neoangiogenesis carries heavy traffic of non-malignant cells, especially B and T lymphocytes. These data confirm crucial role of the immune surveillance in head and neck cancer [36, 37].

Here, we evaluated the surgical margins status in OSCC by means of NBI endoscopy and the pathological identification of neoangiogenesis and intratumor immune response. This pilot study highlights that the surgical and NBI margins are comparable in terms of reliability. This notion, however, should be considered in the context of the small sample size investigated in the present work. An intrinsic limitation of this study is represented by absence of deep margin assessment, given that the NBI technology allows only for the evaluation of the perimetral margins. Further prospective studies embracing larger cohorts of patients are warranted to define the operational implications of our observations. This would lead to standardized intraoperative employment of this novel integrated strategy.

Conclusion

The integration of the traditional MM assessment with the NBI technology can allow for more conservative surgical interventions in OSCC.

Notes

Acknowledgments

The Authors would like to thank Prof. Alto Gianni’, Prof. Stefano Ferrero, and Prof. Lorenzo Pignataro for fostering this study.

Funding

Not applicable.

Availability of data and materials

The dataset used and analysed during the present study is available from the corresponding author upon reasonable request.

Authors’ contributions

Study concept, design, and supervision by ABa and NF. Acquisition, analysis, and interpretation of data: AB, NF, ABa, DC, and CM. ABo, DC, CM and LB reviewed the clinical records. Clinicopathologic correlations were performed by ABa, NF, and PC, with the substantial contribution of ABo and AF. Initial histologic review of the cases was performed by NF and MM. The statistical analysis was carried out by NF and AF. Iconography and image processing by CM, AF, and NF. CM wrote the first draft of the manuscript, which was initially reviewed by Aba, AF, and NF. Subsequently, all authors edited and approved the final draft.

Ethics approval and consent to participate

The study was approved by the ethics committee of the Fondazione IRCCS Ca′ Granda under the vote #19_2018bis. All participants signed informed consent forms.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. 1.
    Marur S, Forastiere AA. Head and neck squamous cell carcinoma: update on epidemiology, diagnosis, and treatment. Mayo Clin Proc. 2016;91(3):386–96.CrossRefGoogle Scholar
  2. 2.
    Edge SB, Compton CC. The American joint committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010;17(6):1471–4.CrossRefGoogle Scholar
  3. 3.
    Garavello W, Bertuccio P, Levi F, et al. The oral cancer epidemic in central and eastern Europe. Int J Cancer. 2010;127(1):160–71.CrossRefGoogle Scholar
  4. 4.
    Adelstein D, Gillison ML, Pfister DG, et al. NCCN guidelines insights: head and neck cancers, version 2. J Natl Compr Canc Netw. 2017;15(6):761–70.CrossRefGoogle Scholar
  5. 5.
    Shah AK. Postoperative pathologic assessment of surgical margins in oral cancer: a contemporary review. J Oral Maxillofac Pathol. 2018;22(1):78–85.PubMedPubMedCentralGoogle Scholar
  6. 6.
    Loree TR, Strong EW. Significance of positive margins in oral cavity squamous carcinoma. Am J Surg. 1990;160(4):410–4.CrossRefGoogle Scholar
  7. 7.
    Hinni ML, Ferlito A, Brandwein-Gensler MS, et al. Surgical margins in head and neck cancer: a contemporary review. Head Neck. 2013;35(9):1362–70.CrossRefGoogle Scholar
  8. 8.
    Tirelli G, Zacchigna S, Boscolo Nata F, Quatela E, Di Lenarda R, Piovesana M. Will the mininvasive approach challenge the old paradigms in oral cancer surgery? Eur Arch Otorhinolaryngol. 2017;274(3):1279–89.CrossRefGoogle Scholar
  9. 9.
    Tirelli G, Piovesana M, Gatto A, Tofanelli M, Biasotto M, Boscolo Nata F. Narrow band imaging in the intra-operative definition of resection margins in oral cavity and oropharyngeal cancer. Oral Oncol. 2015;51(10):908–13.CrossRefGoogle Scholar
  10. 10.
    Tirelli G, Piovesana M, Gatto A, Torelli L, Di Lenarda R, Boscolo Nata F. NBI utility in the pre-operative and intra-operative assessment of oral cavity and oropharyngeal carcinoma. Am J Otolaryngol. 2017;38(1):65–71.CrossRefGoogle Scholar
  11. 11.
    Jalayer Naderi N, Tirgari F, Keshavarz Z. Vascular endothelial growth factor expression and vascular density in oral squamous cell carcinoma (OSCC): a study on clinical and histopathologic significance. Med J Islam Repub Iran. 2016 Apr 18;30:358.PubMedPubMedCentralGoogle Scholar
  12. 12.
    Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis--correlation in invasive breast carcinoma. N Engl J Med. 1991;324(1):1–8.CrossRefGoogle Scholar
  13. 13.
    Ingaleshwar PS, Pandit S, Desai D, Redder CP, Shetty AS, Mithun KM. Immunohistochemical analysis of angiogenesis by CD34 and mast cells by toluidine blue in different grades of oral squamous cell carcinoma. J Oral Maxillofac Pathol. 2016;20(3):467–73.CrossRefGoogle Scholar
  14. 14.
    Williams MD. Determining adequate margins in head and neck cancers: practice and continued challenges. Curr Oncol Rep. 2016;18(9):54.CrossRefGoogle Scholar
  15. 15.
    General Assembly of the World Medical Association. World medical association declaration of Helsinki: ethical principles for medical research involving human subjects. J Am Coll Dent. 2014 Summer;81(3):14–8.Google Scholar
  16. 16.
    Amin MB, Edge SB, Greene FL, et al. AJCC Cancer staging manual. Eighth ed. New York, NY: Springer; 2017.CrossRefGoogle Scholar
  17. 17.
    Klauschen F, Müller KR, Binder A, et al. International scoring of tumor-infiltrating lymphocytes: from visual estimation to machine learning. Semin Cancer Biol. 2018;52(Pt 2):151-157.Google Scholar
  18. 18.
    Ercoli G, Lopez G, Ciapponi C, et al. Building Up a High-throughput Screening Platform to Assess the Heterogeneity of HER2 Gene Amplification in Breast Cancers. J Vis Exp. 2017;5(130).Google Scholar
  19. 19.
    Sciarra A, Lopez G, Corti C, et al. Columnar cell lesion and apocrine hyperplasia of the breast: is there a common origin? The role of prolactin-induced protein. Appl Immunohistochem Mol Morphol. 2017 Oct 27.Google Scholar
  20. 20.
    Fusco N, Guerini-Rocco E, Del Gobbo A, et al. The contrasting role of p16Ink4A patterns of expression in neuroendocrine and non-neuroendocrine lung tumors: a comprehensive analysis with Clinicopathologic and molecular correlations. PLoS One. 2015;10(12):e0144923.CrossRefGoogle Scholar
  21. 21.
    Fusco N, Lopez G, Corti C, et al. Mismatch repair protein loss as a prognostic and predictive biomarker regardless of microsatellite instability. JNCI Cancer Spectrum. 2018 Nov;4(2):pky056.Google Scholar
  22. 22.
    Szafarowski T, Sierdzinski J, Szczepanski MJ, Whiteside TL, Ludwig N, Krzeski A. Microvessel density in head and neck squamous cell carcinoma. Eur Arch Otorhinolaryngol. 2018;275(7):1845–51.CrossRefGoogle Scholar
  23. 23.
    Piazza C, Del Bon F, Paderno A, et al. The diagnostic value of narrow band imaging in different oral and oropharyngeal subsites. Eur Arch Otorhinolaryngol. 2016;273(10):3347–53.CrossRefGoogle Scholar
  24. 24.
    Irimie AI, Braicu C, Cojocneanu-Petric R, Berindan-Neagoe I, Campian RS. Novel technologies for oral squamous carcinoma biomarkers in diagnostics and prognostics. Acta Odontol Scand. 2015;73(3):161–8.CrossRefGoogle Scholar
  25. 25.
    Retzbach EP, Sheehan SA, Nevel EM, et al. Podoplanin emerges as a functionally relevant oral cancer biomarker and therapeutic target. Oral Oncol. 2018;78:126–36.CrossRefGoogle Scholar
  26. 26.
    Song W, Sun Y, Lin J, Bi X. Current research on head and neck cancer-associated long noncoding RNAs. Oncotarget. 2017;9(1):1403–25.PubMedPubMedCentralGoogle Scholar
  27. 27.
    Sinha P, Bahadur S, Thakar A, et al. Significance of promoter hypermethylation of p16 gene for margin assessment in carcinoma tongue. Head Neck. 2009;31(11):1423–30.CrossRefGoogle Scholar
  28. 28.
    Tirelli G, Piovesana M, Marcuzzo AV, et al. Tailored resections in oral and oropharyngeal cancer using narrow band imaging. Am J Otolaryngol. 2018;39(2):197–203.CrossRefGoogle Scholar
  29. 29.
    Poh CF, Zhang L, Anderson DW, et al. Fluorescence visualization detection of field alterations in tumor margins of oral cancer patients. Clin Cancer Res. 2006;12(22):6716–22.CrossRefGoogle Scholar
  30. 30.
    Tirelli G, Piovesana M, Gatto A, Torelli L, Boscolo Nata F. Is NBI-guided resection a breakthrough for achieving adequate resection margins in Oral and oropharyngeal squamous cell carcinoma? Ann Otol Rhinol Laryngol. 2016;125(7):596–601.CrossRefGoogle Scholar
  31. 31.
    Naderi NJ, Tirgari F, Keshavarz Z. Vascular endothelial growth factor expression and vascular density in oral squamous cell carcinoma (OSCC): a study on clinical and histopathologic significance. Med J Islam Repub Iran. 2016;30(1):1–6.Google Scholar
  32. 32.
    Albo D, Granick M, Jhala N, Atkinson B, Solomon MP. The relationship of angiogenesis to biological activity in human squamous cell carcinomas of the head and neck. Ann Plast Surg. 1994;32(6):588–94.CrossRefGoogle Scholar
  33. 33.
    Ascani G, Balercia P, Messi M. Lupi et al. Angiogenesis in oral squamous cell carcinoma. Acta Otorhinolaryngol Ital. 2005;25(1):13–7.PubMedPubMedCentralGoogle Scholar
  34. 34.
    Shivamallappa SM, Venkatraman NT, Shreedhar B, Mohanty L, Shenoy S. Role of angiogenesis in oral squamous cell carcinoma development and metastasis: an immunohistochemical study. Int J Oral Sci. 2011;3(4):216–24.CrossRefGoogle Scholar
  35. 35.
    Li SH, Hung PH, Chou KC, Hsieh SHSY. Tumor angiogenesis in oral squamous cell carcinomas: the significance of endothelial markers and hotspot selection. J Med Sci. 2009;29:67–74.Google Scholar
  36. 36.
    Lei Y, Xie Y, Tan YS, et al. Telltale tumor infiltrating lymphocytes (TIL) in oral, head & neck cancer. Oral Oncol. 2016;61:159–65.CrossRefGoogle Scholar
  37. 37.
    Wolf GT, Chepeha DB, Bellile E, Nguyen A, Thomas D, McHugh J. University of Michigan head and neck SPORE program. Tumor infiltrating lymphocytes (TIL) and prognosis in oral cavity squamous carcinoma: a preliminary study. Oral Oncol. 2015;51(1):90–5.CrossRefGoogle Scholar

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Authors and Affiliations

  • Alessandro Baj
    • 1
    • 2
  • Nicola Fusco
    • 1
    • 3
  • Alessandro Bolzoni
    • 1
    • 2
  • Daniela Carioli
    • 4
  • Camilla Mazzucato
    • 2
  • Alice Faversani
    • 1
    • 3
  • Lorenzo Bresciani
    • 2
  • Marco Maggioni
    • 3
  • Pasquale Capaccio
    • 1
    • 4
    Email author
  1. 1.Department of Biomedical, Surgical, and Dental SciencesUniversity of MilanMilanItaly
  2. 2.Maxillo-Facial Surgery and Odontostomatology Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilanItaly
  3. 3.Division of PathologyFondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilanItaly
  4. 4.Otolaryngology Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoMilanItaly

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