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Poster Display

30P - CD4+ T cells within the tumor microenvironment are an independent predictor of recurrence, but do not improve the performance of a predictive model in oral squamous cell carcinoma

Date

07 Dec 2023

Session

Poster Display

Presenters

Sangeeta Bisheshar

Citation

Annals of Oncology (2023) 20 (suppl_1): 100412-100412. 10.1016/iotech/iotech100412

Authors

S.K. Bisheshar1, M. van der Kamp2, J. de Vries2, L. Slagter-Menkema2, E. Schuuring2, G. Lunter2, G. Halmos2, B. van der Vegt2

Author affiliations

  • 1 The University Medical Center - UMCG, Groningen/NL
  • 2 UMCG - University Medical Center Groningen, Groningen/NL

Resources

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Abstract 30P

Background

The recurrence risk of patients diagnosed with oral squamous cell carcinoma (OSCC) is currently insufficiently predicted by conventional clinicopathological characteristics. This study investigates the added predictive value of the tumor microenvironment immune cell composition (TMICC) in addition to conventional clinicopathologic characteristics.

Methods

Primary tumor samples of 290 OSCC patients were immunohistochemically stained for TMICC, consisting of CD4, CD8, CD20, CD68, CD163, CD57, FoxP3 and Programmed cell Death Ligand 1 (PD-L1). Additionally, clinicopathologic characteristics were obtained from patients’ medical files. Predictive models were trained and validated by conducting Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses with cross-validation. To quantify the added predictive power of TMICC within models, receiver operating characteristic (ROC) analyses were used. Recurrence was defined to include locoregional recurrences and distant metastasis.

Results

Recurrence occurred in 74 (25.5%) of patients. Conventional clinicopathologic characteristics consisting of tumor localization, pathological T-stage, pathological N-stage, extracapsular spread, resection margin, differentiation grade, perineural invasion, lymph angioinvasion and treatment modality, were used to build a LASSO logistic regression-based predictive model. Addition of TMICC to the model resulted in a comparable AUC of respectively 0.79 (± 0.01) and 0.76 (± 0.1) in the training and test sets. The model showed that high numbers of CD4+ T cells and absence of lymph node metastasis, extracapsular spread and perineural invasion protected against recurrence. Positive surgical margins and reception of adjuvant treatment increased the risk for recurrence.

Conclusions

CD4+ T cells are the strongest predictor within the TMICC, however, addition to conventional clinicopathologic characteristics does not improve the performance of a predictive model for recurrence in OSCC treated with curative intent.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

E. Schuuring: Financial Interests, Institutional, Advisory Board, Unrelated to the publication of this article: AstraZeneca, Bayer, BMS, Roche, Pfizer, Novartis, Amgen, Lilly, BioCartis, Illumina, Astellas Pharma, Agena Biosciences, MSD/Merck, CC Diagnostics, Janssen Cilag (Johnson&Johnson), Diaceutics; Financial Interests, Institutional, Invited Speaker, Unrelated to the publication of this article: Bio-Rad, Abbott, Roche, Biocartis, Illumina, Pfizer, AstraZeneca, Agena Biosciences; Financial Interests, Institutional, Research Grant, Unrelated to the publication of this article: Pfizer, Biocartis, AstraZeneca, Bayer/Invitae, Biocartis, Cancer-ID, BMS, Bio-Rad, Roche, Agena Biosciences, Promega, Qiagen, CC Diagnostics, Boehringer Ingelheim. B. van der Vegt: Financial Interests, Institutional, Speaker, Consultant, Advisor, Unrelated to the publication of this article: Visiopharm; Financial Interests, Institutional, Advisory Board, Unrelated to the publication of this article: Phillips, AstraZeneca, Daiichi Sankyo; Financial Interests, Institutional, Invited Speaker, Unrelated to the publication of this article: Diaceutics, MSD, MSD. All other authors have declared no conflicts of interest.

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