ABSTRACT
The tumor microenvironment (TME) plays an important role in the progression of head
and neck squamous cell carcinoma (HNSCC). Currently, pathological assessment of TME
is non-standardized and subject to observer bias. Genome-wide transcriptomic approaches
to understanding the TME, while less subject to bias, are expensive and not currently
part of standard of care for HNSCC. To identify pathology-based biomarkers that correlate
with genomic and transcriptomic signatures of TME in HNSCC, cytometric feature maps
were generated in a publicly available cohort of patients with HNSCC with available
whole-slide tissue images and genomic and transcriptomic phenotyping (N=49). Cytometric
feature maps were generated based on whole-slide nuclear detection, using a deep learning
algorithm trained for StarDist nuclear segmentation. Cytometric features were measured
for each patient and compared to transcriptomic measurements, including Estimation
of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE)
scores, as well as stemness scores. When corrected for multiple comparisons, one feature
(nuclear circularity) demonstrated a significant linear correlation with ESTIMATE
stromal score. Two features (nuclear maximum and minimum diameter) correlated significantly
with ESTIMATE immune score. Three features (nuclear solidity, nuclear minimum diameter,
and nuclear circularity) correlated significantly with transcriptomic stemness score.
This study provides preliminary evidence that observer-independent, automated tissue
slide analysis can provide insights into the HNSCC TME which correlate with genomic
and transcriptomic assessments.
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Article Info
Publication History
Accepted:
June 2,
2022
Received in revised form:
May 26,
2022
Received:
April 1,
2022
Publication stage
In Press Journal Pre-ProofFootnotes
Grant support: Research reported in this publication was supported by the National Center For Advancing Translational Sciences of the National Institutes of Health under Award Number TL1 TR002555.
Disclosures: The authors indicate no financial or personal conflicts to disclose with regards to this work.
AUTHOR CONTRIBUTIONS
S.J.B, J.I.E., and Y.M.M. contributed to study conception and design; S.J.B, J.C., J.I.E., W.M.A., T.L.W., and Y.M.M. contributed to data analysis and interpretation; S.J.B., J.I.E., T.L.W., and Y.M.M. contributed to manuscript drafting and major revisions. All authors provided feedback on manuscript drafts, and approved the final version for submission.
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© 2022 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
