PD-1/PD-L1, Treg-related proteins, and tumour-infiltrating lymphocytes are associated with the development of oral squamous cell carcinoma

Pathology ◽  
2021 ◽  
Author(s):  
Omar Kujan ◽  
Muhamed Agag ◽  
Monika Smaga ◽  
Yash Vaishnaw ◽  
Majdy Idrees ◽  
...  
1997 ◽  
Vol 45 (1) ◽  
pp. 61-61
Author(s):  
Takefumi Mouri ◽  
Seiji Nakamura ◽  
Yukiko Ohyama ◽  
Goro Matsuzaki ◽  
Masanori Shinohara ◽  
...  

2019 ◽  
Vol 70 (4) ◽  
pp. 277-285
Author(s):  
Mariusz Książek ◽  
Bogumił Lewandowski ◽  
Robert Brodowski ◽  
Paweł Pakla ◽  
Marta Kawalec-Książek ◽  
...  

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Muhammad Shaban ◽  
Syed Ali Khurram ◽  
Muhammad Moazam Fraz ◽  
Najah Alsubaie ◽  
Iqra Masood ◽  
...  

Abstract Oral squamous cell carcinoma (OSCC) is the most common type of head and neck (H&N) cancers with an increasing worldwide incidence and a worsening prognosis. The abundance of tumour infiltrating lymphocytes (TILs) has been shown to be a key prognostic indicator in a range of cancers with emerging evidence of its role in OSCC progression and treatment response. However, the current methods of TIL analysis are subjective and open to variability in interpretation. An automated method for quantification of TIL abundance has the potential to facilitate better stratification and prognostication of oral cancer patients. We propose a novel method for objective quantification of TIL abundance in OSCC histology images. The proposed TIL abundance (TILAb) score is calculated by first segmenting the whole slide images (WSIs) into underlying tissue types (tumour, lymphocytes, etc.) and then quantifying the co-localization of lymphocytes and tumour areas in a novel fashion. We investigate the prognostic significance of TILAb score on digitized WSIs of Hematoxylin and Eosin (H&E) stained slides of OSCC patients. Our deep learning based tissue segmentation achieves high accuracy of 96.31%, which paves the way for reliable downstream analysis. We show that the TILAb score is a strong prognostic indicator (p = 0.0006) of disease free survival (DFS) on our OSCC test cohort. The automated TILAb score has a significantly higher prognostic value than the manual TIL score (p = 0.0024). In summary, the proposed TILAb score is a digital biomarker which is based on more accurate classification of tumour and lymphocytic regions, is motivated by the biological definition of TILs as tumour infiltrating lymphocytes, with the added advantages of objective and reproducible quantification.


2021 ◽  
Author(s):  
Yuri Noda ◽  
Mitsuaki Ishida ◽  
Yasuhiro Ueno ◽  
Takuo Fujisawa ◽  
Hiroshi Iwai ◽  
...  

Abstract Background: Extranodal extension (ENE) is a poor prognostic factor for oral squamous cell carcinoma (OSCC). Identifying ENE by clinical and/or radiological examination is difficult, thereby leading to unnecessary neck dissections. Currently, no definitive predictors are available for ENE. Thus, we aimed to determine the histological predictors of ENE by routine histopathological examination using biopsy and surgically resected specimens.Methods: This retrospective study included 186 surgically resected OSCC and 83 matched biopsy specimens. Clinical features associated with the tumor microenvironment, including desmoplastic reaction (DR), tumor budding (TB), and tumor-infiltrating lymphocytes (TILs), were evaluated using hematoxylin and eosin-stained primary OSCC and neck dissection specimens. These histological features were divided into two groups: DR-immature (DR-I) and DR-mature (DR-M); TB-high (TB-H) and TB-low (TB-L); and TILs-low (TILs-L) and TILs-high (TILs-H). Clinical depth of invasion (cDOI) and pathological DOI (pDOI) were adapted for biopsies and resections, respectively; DOI was evaluated as DOI >10 mm and DOI ≤10 mm. The clinicopathological relationships between these histopathological features and ENE and the independent risk factors for ENE were analyzed. The histological predictors of ENE were evaluated.Results:The histological status of DR, TILs, and TB present in biopsy and resection specimens showed high accuracy with that of ENE. DR-I, TILs-L, and TB-H were significantly associated with lymph node metastasis, cDOI, and pDOI. Bivariate and multivariate analyses revealed that TB-H and pDOI >10 mm in resections were independent factors for the presence of ENE (ENE+). The combination of TB-H/pDOI >10 mm in resection specimens showed high specificity (91%) and accuracy (83%) regarding ENE+. Although there proved to be no independent factors in biopsies, DR-I and TILs-L were significantly associated with ENE+ (p<0.001). The combination of DR-I/TILs-L/cDOI >10 mm in biopsies exhibited high sensitivity and specificity with ENE+ (70% and 77%, respectively, p<0.001). These histological predictors could detect even minor ENE (<2 mm).Conclusions:The tumor microenvironment status in primary OSCC was significantly associated with that of ENE, and TB-H was an independent risk factor for ENE. The histological status of DR-I/TILs-L/cDOI >10 mm in biopsy specimens and TB-H/pDOI >10 mm in resection specimens is a useful predictor of ENE.


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