Head & Neck, 2024; 0:1–7
https://doi.org/10.1002/hed.27945
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Head & Neck
ORIGINAL ARTICLE OPEN ACCESS
Tumor Microenvironment- Based Risk Stratification of 
Oropharyngeal Squamous Cell Carcinoma
Alhadi Almangush1,2,3,4  |  Lauri Jouhi5  |  Caj Haglund6,7 |  Jaana Hagström1,6,8 |  Antti A. Mäkitie2,5,9  |  Ilmo Leivo10,11
1Department of Pathology, University of Helsinki, Helsinki, Finland | 2Research Program in Systems Oncology, Faculty of Medicine, University 
of Helsinki, Helsinki, Finland | 3Department of Pathology, University of Turku, Turku, Finland | 4Faculty of Dentistry, Misurata University, 
Misurata, Libya | 5Department of Otorhinolaryngology – Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, 
Finland | 6Research Programs Unit, Translational Cancer Medicine, University of Helsinki, Helsinki, Finland | 7Department of Surgery, University of 
Helsinki and Helsinki University Hospital, Helsinki, Finland | 8Department of Oral Pathology and Radiology, University of Turku, Turku University 
Hospital, Turku, Finland | 9Division of Ear, Nose and Throat Diseases, Department of Clinical Sciences, Intervention and Technology, Karolinska Institutet 
and Karolinska University Hospital, Stockholm, Sweden | 10Institute of Biomedicine, Pathology, University of Turku, Turku, Finland | 11Turku University 
Central Hospital, Turku, Finland
Correspondence: Alhadi Almangush (alhadi.almangush@helsinki.fi)
Received: 13 May 2024 | Revised: 1 September 2024 | Accepted: 17 September 2024
Section Editor: Nicole Schmitt 
Funding: This work was supported by Finnish Cancer Society, Turku University Hospital Fund, Finska Läkaresällskapet, Maritza and Reino Salonen 
Foundation, K. Albin Johansson Foundation, the Finnish Dental Society Apollonia, Helsinki University Hospital Research Fund, and Sigrid Jusélius 
Foundation.
Keywords: oropharyngeal squamous cell carcinoma | prognosis | tumor microenvironment | tumor- infiltrating lymphocytes | tumor- stroma ratio
ABSTRACT
Background: Evaluation of the prognostic impact of tumor microenvironment (TME) has received attention in recent years. We 
introduce a TME- based risk stratification for oropharyngeal squamous cell carcinoma (OPSCC).
Material and Methods: A total of 182 patients treated for OPSCC at the Helsinki University Hospital were included. TME- 
based risk stratification was designed combining tumor- stroma ratio and stromal tumor- infiltrating lymphocytes assessed in 
hematoxylin and eosin- stained sections.
Results: In multivariable analysis, TME- based risk stratification associated with poor disease- free survival with a hazard ratio 
(HR) of 2.68 (95% CI 1.11– 6.48, p = 0.029). In addition, the proposed risk stratification was associated with poor disease- specific 
survival (HR 2.687, 95% CI 1.28– 5.66, p = 0.009) and poor overall survival (HR 2.21, 95% CI 1.23– 3.99, p = 0.008).
Conclusion: Our TME- based risk stratification provides a powerful prognostic tool that can be used in daily treatment planning 
of OPSCC together with tumor- related prognostic markers.
1   |   Introduction
Oropharyngeal squamous cell carcinoma (OPSCC) is one 
of the most commonly occurring malignancies in the head 
and neck region. There is an increasing incidence of human 
papillomavirus- associated (HPV+) OPSCC tumors [1, 2]. In 
general, HPV+ OPSCC is associated with a better prognosis 
than HPV− OPSCC, however many HPV+ cases present also 
with a poor survival [3]. HPV+ OPSCC patients who are at 
high risk of recurrence (about 15% of the cases), would require 
more intensive therapy, but their identification is challenging 
[2]. Therefore, there is a need for additional prognostic mark-
ers beyond the HPV status to predict the clinical behavior 
of OPSCC.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is 
properly cited.
© 2024 The Author(s). Head & Neck published by Wiley Periodicals LLC.
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The tumor stroma as part of the tumor microenvironment 
(TME) has a prominent role in the progression of many cancer 
types including those of various subsites of head and neck re-
gion, as widely reported recently [4]. Tumor stroma consists of 
fibroblasts, myofibroblasts, endothelial cells, and immune cells. 
The stromal tissue serves as a supporting framework where the 
tumor cells are embedded [5].
Assessment of the quantity of stromal compartment has been re-
cently introduced in the form of tumor- stroma ratio (TSR) using 
hematoxylin and eosin (HE)- stained sections and it has shown 
to have a powerful prognostic value [6– 9]. Moreover, immune 
cells may infiltrate tumor tissue, and their organization within 
the TME is tightly connected with the clinical behavior of many 
solid cancers [10]. Of note, the combination of TSR and immune 
status in TME has also been studied in some tumor types includ-
ing head and neck cancer [11, 12].
Up to date, there are no TME- related classifiers included in 
the prognostication of OPSCC. TME- based stratification could 
improve accuracy in the assessment of the clinical behav-
ior of OPSCC. Therefore, the aim of this study was to intro-
duce a TME- based risk stratification for the prognostication 
of OPSCC.
2   |   Material and Methods
All cases treated for OPSCC at the Helsinki University Hospital 
(Helsinki, Finland) in the period between January 2000 and 
December 2009 were included in this study. This research 
project was approved by the Research Ethics Committee of 
the Helsinki University Hospital. The following patients were 
excluded: those with palliative treatment intent (n = 44), with 
treatment for previous head and neck cancer (n = 11), with 
concurrent head and neck cancer (n = 5), other histology than 
squamous cell carcinoma (n = 18), and those in whom a suffi-
cient tumor- host interface was not available (n = 71). A total of 
182 cases of OPSCC were eligible for this study. We used both 
tumor resection specimens and representative incisional diag-
nostic specimens. All unrepresentative samples were excluded. 
Both p16 immunohistochemistry and Ventana Inform DNA in 
situ hybridization assay were performed on tissue samples and 
used to determine HPV status based on the algorithm described 
by Smeets et al. [13].
All representative HE- stained cancer specimens were as-
sessed. TME- based risk stratification was designed based 
on the abundance of tumor stroma and the stromal TILs 
(Figure 1). TSR and stromal TILs were combined as follows: 
category I in which the stromal component was less than 50% 
and TILs more than or equal to 30%, and category III in which 
the stromal component was more than or equal to 50% and 
TILs less than 30%. All other tumors were assigned to cate-
gory II.
The evaluation of TSR and TILs was performed by two observ-
ers (AA and IL) as described in the recent guidelines [14– 17]. 
In brief, the assessment of TSR started with scanning of the 
whole slide with ×5 objective to select the area with the highest 
amount of tumor- associated stroma, and then with ×10 objective 
to assess the amount of tumor- associated stroma in a chosen mi-
croscopic field with cancer cells present in all four sides [14, 15]. 
In any heterogenous tumor with areas of both high and low 
amounts of tumor- associated stroma, the stroma- high area was 
considered decisive for scoring the case, as recommended in the 
guidelines [14, 15]. For the assessment of TILs, the whole tumor 
section was evaluated at low magnification using ×5 or ×10 ob-
jective, and then at higher magnification using ×20 objective. 
The percentage of stromal area occupied by TILs was assessed 
for scoring. To obtain an average score of TILs this assessment 
was carried out in multiple stromal areas. Stromal areas not ad-
jacent to the tumor, tonsillar lymphatic tissue and areas of ne-
crosis were excluded.
2.1   |   Statistical Method
All statistical analyses was conducted using IBM SPSS Statistics 
(version 27). The prognostic impact of the TME- based risk 
stratification was assessed with univariable and multivariable 
FIGURE 1    |    Tumor microenvironment- based risk stratification of 
oropharyngeal squamous cell carcinoma. (A) Category I: Tumor with 
low stroma (< 50%) and high infiltration of TILs (≥ 30%). (B) Example of 
category II: High stroma (≥ 50%) and high infiltration of TILs (≥ 30%). 
(C) Category III: High stroma (≥ 50%) and low infiltration of TILs 
(< 30%). [Color figure can be viewed at wileyonlinelibrary.com]
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analyses. Hazard radio (HR) with 95% confidence interval (CI) 
was reported for each variable. Cross- tabulation was used to an-
alyze the relationship between TME- based stratification and the 
clinicopathologic characteristics. Kaplan– Meier analyses were 
conducted for disease- free survival, disease- specific survival, 
and overall survival.
3   |   Results
A total of 140 (76.9%) males and 42 (23.1%) females were in-
cluded in the study. The median follow- up time was 4.48 years 
(range 3.51– 5.00 years). The clinicopathologic features of the 
cases and their relationship with the TME- based risk strat-
ification are summarized in Table  1. The TME- based strati-
fication had a total of 81 (44.5%) tumors categorized in the 
TME- based category I, 39 (21.4%) in category II, and 62 (34.1%) 
in category III.
There was a good inter- observer agreement in the assessment of 
TILs (Kappa value = 0.78) and TSR (Kappa value = 0.752), which 
indicates a good reproducibility of the proposed TME- based 
stratification. In the cross- tabulation (Table 1), we noted a sig-
nificant association was noted between the age of patients and 
the TME- based stratification (p = 0.006). On the other hand, no 
significant association (p > 0.05) was found between the TME- 
based risk stratification and other clinicopathologic factors 
including gender, HPV status, smoking history, TNM stage, his-
topathologic grade, and treatment.
In survival analyses using a cutoff point of 30% for TILs 
(Table 2), category III of the TME- based risk stratification was 
associated with significantly worse disease- free survival with 
a HR of 3.52 (95% CI 1.50– 8.22, p = 0.004) in univariable and 
multivariable analyses (HR 2.68, 95% CI 1.11– 6.48, p = 0.029). 
Similarly, category III of TME- based stratification was associ-
ated with significantly worse disease- specific survival with a 
HR of 3.43 (95% CI 1.67– 7.05, p < 0.001) in univariable and mul-
tivariable analyses (HR 2.687, 95% CI 1.28– 5.66, p = 0.009). In 
addition, category III of the TME- based risk stratification was 
associated with poor overall survival in univariable analysis 
with a HR of 2.83 (95% CI 1.60– 4.99, p < 0.001) as well as in mul-
tivariable analysis (HR 2.21, 95% CI 1.23– 3.99, p = 0.008). Our 
multivariable analyses included the routinely considered param-
eters of HPV- status and tumor stage. The results indicate the 
independence of the proposed TME- based risk stratification in 
predicting the prognosis of OPC. In addition, Kaplan– Meier sur-
vival curves (Figure 2A– C) indicated significantly worse prog-
nosis for category III of TME- based stratification in disease- free 
survival (p = 0.008), disease- specific survival (p = 0.002), and 
overall survival (p < 0.001).
When using a cutoff point of 20% for TILs in the TME- based 
risk stratification, a significant prognostic power was ob-
served for disease- free survival (HR 2.80, 95% CI 1.78– 6.66, 
p = 0.020). However, no significant prognostic power was 
reached for disease- specific survival (HR 1.45, 95% CI 
0.75– 2.81, p = 0.271) or overall survival (HR 1.47, 95% CI 
0.85– 2.52, p = 0.166). This indicates that the above described 
30% provides an optimal cutoff point for TILs in TME- based 
risk stratification. A 50% cutoff point was optimal for TSR in 
our TME- based risk stratification.
4   |   Discussion
Tumor microenvironment has a significant role in cancer pro-
gression [18]. Recently, stromal- related prognostic biomarkers 
have been introduced for risk assessment in head and neck 
cancers [9]. Identification of stromal markers can aid in tar-
geting tumor- associated stromal cells for cancer therapy [19]. 
In daily practice of OPSCC, however, TME is not considered 
during the management of oropharyngeal cancer. In addi-
tion, it is sometimes challenging to select the most suitable 
treatment for OPSCC patients [20]. In the present study we 
have introduced for the first time in a large cohort of OPSCC 
a TME- based grading system that can be evaluated using rou-
tine hematoxylin and eosin (HE)- stained slides and, therefore, 
can be easily included in pathology reports without addi-
tional costs. Our proposed system combines features of stro-
mal microenvironment and immune microenvironment and 
has shown a powerful prognostic value in risk stratification 
of OPSCC.
Interactions of cancer cells with cells of tumor stroma are com-
plex and implicated as key players in cancer invasion. During 
cancer progression, cancer cells and other components modify 
stromal cells to form a phenotype that promotes tumor devel-
opment [19]. Tumor stroma can regulate tumor growth and it 
has the potential of regulating the aggressiveness of the tumor. 
Thus, research efforts on novel therapeutic strategies aim at tar-
geting anti- tumoral and anti- stromal agents [21].
Research efforts which have included immune parameters 
as prognostic classifiers have shown promising findings 
[10]. Importantly, the assessment of stromal TILs is the most 
widely used immune parameter and has been reported as a 
powerful prognosticator in recent studies on various tumors 
[22– 25]. It is necessary to point out that the prognostic value 
of intra- tumoral TILs was limited (p > 0.05), as also previ-
ously reported in oral cancer [23]. In the current study, the 
method used for the assessment of stromal TILs is standard-
ized, and it has shown a promising prognostic value and good 
inter- observer agreement [22– 25]. In addition, the method is 
cost- effective as the assessment of TILs is made on HE- stained 
sections which are already available as diagnostic samples. 
Similarly, the assessment of TSR is cost- effective and has 
shown a significant prognostic value and good reproducibil-
ity [6– 9].
Of note, recent research has proposed stromal- related char-
acteristics for risk stratification of different tumors to sup-
plement the currently used tumor- related features in risk 
stratification of cancer. Interestingly, two recent studies have 
reported the prognostic significance of stroma- based stratifi-
cation in oral squamous cell carcinoma [11, 12]. Our current 
study corroborates the results of these studies. Importantly, 
when using diagnostic biopsy sections for the assessment of 
TSR, it is necessary to have a representative sample including 
sufficient amounts of both tumor and stromal compartments. 
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In such samples, a good agreement on the TSR score in pre- 
treatment biopsies and surgical specimens has been reported 
in head and neck cancers [26, 27]. Interestingly, there is 
evidence indicating that TSR and response to neoadjuvant 
chemoradiotherapy are correlated so that in esophageal can-
cer stroma- low tumors show a better response to neoadjuvant 
TABLE 1    |    Relationship between tumor microenvironment- based risk stratification and clinicopathologic features in cases of oropharyngeal 
squamous cell carcinoma (n = 182).
Variable
Total
Stromal 
category I
Stromal 
category II
Stromal 
category III
p of Chi- 
square testTotal, N = 182
Number (%) Number (%) Number (%)
81 (44.5%) 39 (21.4%) 62 (34.1%)
Age 0.006
< 60 years 101 55 (54.5%) 15 (14.9%) 31 (30.7%)
≥ 60 years 81 26 (32.1%) 24 (29.6%) 31 (38.3%)
Gender 0.688
Male 140 61 (43.6%) 29 (20.7%) 50 (35.7%)
Female 42 20 (47.6%) 10 (23.8%) 12 (28.6%)
HPV status 0.252
Positive 91 46 (50.5%) 18 (19.8%) 27 (29.7%)
Negative 91 35 (38.5%) 21 (23.0%) 35 (38.5%)
Smoking 0.550
Never 20 9 (45.0%) 3 (15.0%) 8 (40.0%)
Former 46 21 (45.7%) 13 (28.3%) 12 (26.1%)
Current 85 33 (38.8%) 19 (22.4%) 33 (38.8%)
Stage 0.262
Early (I– II) 27 10 (37.0%) 9 (33.3%) 8 (29.6%)
Advanced 
(III– IV)
155 71 (45.8%) 30 (19.4%) 54 (34.8%)
T stage 0.174
T1 35 22 (62.9%) 7 (20.0%) 6 (17.1%)
T2 68 30 (44.1%) 15 (22.1%) 23 (33.8%)
T3 40 15 (37.5%) 10 (25.0%) 15 (37.5%)
T4 39 14 (35.9%) 7 (17.9%) 18 (46.2%)
N stage 0.601
N0 35 13 (37.1%) 9 (25.7%) 13 (37.1%)
N+ 147 68 (46.3%) 30 (20.4%) 49 (33.3%)
Grade 0.301
I 15 5 (33.3%) 6 (40.0%) 4 (26.7%)
II 70 29 (41.4%) 13 (18.6%) 28 (40.0%)
III 97 47 (48.5%) 20 (20.6%) 30 (30.9%)
Treatment 0.157
Sx ± (C)RT 120 58 (48.3%) 21 (17.5%) 41 (34.2%)
(C)RT ± Sx 62 23 (37.1%) 18 (29.0%) 21 (33.9%)
Abbreviations: CRT, chemoradiotherapy; RT, radiotherapy; Sx, surgery.
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TABLE 2    |    Disease- free survival, disease- specific survival, and overall survival analyses of the prognostic significance of tumor microenvironment 
(TME)- based risk stratification and clinicopathologic parameters of 182 patients treated for oropharyngeal squamous cell carcinoma.
Parameter
Univariable analysis
Disease- free survival Disease- specific survival Overall survival
HR (95% CI), p HR (95% CI), p HR (95% CI), p
Gender
Male Reference Reference Reference
Female 2.08 (0.80– 5.39), p = 0.13 2.19 (0.99– 4.88), p = 0.054 1.50 (0.85– 2.64), p = 0.16
Smoking
Never Reference Reference Reference
Former 1.69 (0.47– 6.15), p = 0.42 1.66 (0.46– 6.05), p = 0.44 1.24 (0.48– 3.21), p = 0.65
Current 1.89 (0.56– 6.42), p = 0.31 3.29 (1.01– 10.7), p = 0.048 2.36 (1.01– 5.53), p = 0.048
T stage
T1 Reference Reference Reference
T2 1.58 (0.51– 4.89), p = 0.43 1.97 (0.74– 5.27), p = 0.18 1.92 (0.84– 4.43), p = 0.12
T3 2.34 (0.74– 7.47), p = 0.15 1.79 (0.62– 5.26), p = 0.28 2.44 (1.03– 5.81), p = 0.044
T4 2.35 (0.69– 8.04), p = 0.17 3.62 (1.31– 9.96), p = 0.013 4.18 (1.79– 9.76), p = 0.001
N stage
N0– N1 Reference Reference Reference
N2– N3 1.55 (0.59– 4.01), p = 0.37 2.09 (1.05– 4.19), p = 0.037 1.49 (0.89– 2.48), p = 0.129
HPV status
Positive Reference Reference Reference
Negative 2.59 (1.26– 5.35), p = 0.010 2.51 (1.38– 4.56), p = 0.003 2.46 (1.52– 3.98), p < 0.001
Treatment
Sx ± (C)RT Reference Reference Reference
(C)RT ± Sx 1.24 (0.62– 2.49), p = 0.551 1.01 (0.56– 1.82), p = 0.98 1.13 (0.71– 1.81), p = 0.604
TME- based stratification
Category I Reference Reference Reference
Category II 1.79 (0.62– 5.14), p = 0.383 2.39 (1.04– 5.52), p = 0.041 1.65 (0.81– 3.34), p = 0.165
Category III 3.52 (1.50– 8.22), p = 0.004 3.43 (1.67– 7.05), p < 0.001 2.83 (1.60– 4.99), p < 0.001
Parameter
Multivariable analysis
Disease- free survival Disease- specific survival Overall survival
HR (95% CI), p HR (95% CI), p HR (95% CI), p
T stage
T1 Reference Reference Reference
T2 1.77 (0.54– 5.82), p = 0.35 2.22 (0.79– 6.22), p = 0.13 2.21 (0.88– 5.58), p = 0.09
T3 1.56 (0.46– 5.29), p = 0.47 1.43 (0.48– 4.25), p = 0.52 1.90 (0.73– 4.95), p = 0.19
T4 1.95 (0.55– 6.86), p = 0.30 2.76 (0.97– 7.89), p = 0.06 3.72 (1.47– 9.41), p = 0.006
HPV status
Positive Reference Reference Reference
(Continues)
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6 of 7 Head & Neck, 2024
chemoradiotherapy [28]. In agreement to that, in esophago-
gastric junction adenocarcinoma the assessment of TSR 
in preoperative biopsies has shown a predictive power for 
neoadjuvant therapy response [29]. Indeed, further studies are 
needed to compare TSR in tumor specimens before and after 
radiotherapy/chemo- radiotherapy.
In high- income countries, HPV- positive OPSCC is one of the 
most rapidly increasing cancers [2]. In addition, it is well doc-
umented that HPV status is a valuable prognostic parameter in 
classifying OPSCC into risk groups. Therefore, in the present 
study we have included HPV status as a prognostic parameter 
together with our proposed TME- based risk stratification in the 
multivariable analyses (Table 2), and both parameters showed a 
significant prognostic value indicating prognostic independence 
of each. This also indicates that our proposed TME- based risk 
stratification can provide a risk stratification beyond the HPV 
status. This is an important observation to support optimal 
treatment planning based on multiple prognostic indicators.
The clinical decision- making in OPSCC is sometimes challeng-
ing as cases that are usually considered as low risk (particu-
larly the HPV+ tumors), may still present with poor outcome 
[2]. Thus, additional prognostic factors are needed to optimize 
risk stratification to personalize the treatment and avoid both 
under- and over- treatment. The findings of our study indicate 
that category III tumors of the proposed TME- based risk strat-
ification carry a high risk of recurrence and mortality and thus 
require close follow- up. More importantly, they might require 
more aggressive treatment even when diagnosed at an early 
stage. In conclusion, the proposed TME- based risk stratification 
is cost- effective and has a valuable prognostic power in identify-
ing OPSCC cases at high risk of poor outcome. After validation 
studies, TME- based risk stratification can be incorporated in 
the routine pathology reports, and it can be considered for treat-
ment planning for OPSCC patients. It is a shortcoming of the 
present study that the patient cohort was limited to the period 
2000– 2009. Thus, further validation in a recent, preferably large 
multicenter cohort is desirable.
Acknowledgments
The authors acknowledge the funding of the Finnish Cancer Society, 
Turku University Hospital Fund, Finska Läkaresällskapet, Maritza and 
Reino Salonen Foundation, K. Albin Johansson Foundation, the Finnish 
Dental Society Apollonia, Helsinki University Hospital Research Fund, 
and Sigrid Jusélius Foundation.
Parameter
Multivariable analysis
Disease- free survival Disease- specific survival Overall survival
HR (95% CI), p HR (95% CI), p HR (95% CI), p
Negative 2.56 (1.18– 5.57), p = 0.02 2.98 (1.55– 5.71), p = 0.001 2.59 (1.52– 4.42), p < 0.001
TME- based stratification
Category I Reference Reference Reference
Category II 1.94 (0.66– 5.69), p = 0.225 2.696 (1.16– 6.29), p = 0.022 1.74 (0.85– 3.55), p = 0.127
Category III 2.68 (1.11– 6.48), p = 0.029 2.687 (1.28– 5.66), p = 0.009 2.21 (1.23– 3.99), p = 0.008
Note: Values in bold refers to the significant prognostic power of TME- Based stratification.
TABLE 2    |    (Continued)
FIGURE 2    |    Kaplan– Meier survival curves for oropharyngeal 
squamous cell carcinoma cases categorized by tumor 
microenvironment- based risk stratification. Cases with category III 
tumor microenvironment- based stratification are associated with poor 
disease- free survival (A), disease- specific survival (B), and overall 
survival (C). [Color figure can be viewed at wileyonlinelibrary.com]
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Conflicts of Interest
The authors declare no conflicts of interest.
Data Availability Statement
The data that support the findings of this study are available from the 
corresponding author upon reasonable request.
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