Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article


Doctor of Philosophy


Pathology and Laboratory Medicine


Nichols, Anthony C.


A better understanding of the pathophysiology and molecular heterogeneity underlying response to treatment may lead to improved biomarkers and more robust treatment responses. In my thesis, I will discuss three diseases of the head and neck: human papillomavirus-associated oropharyngeal squamous cell carcinoma, idiopathic subglottic stenosis, and anaplastic thyroid cancer. Using these three diseases, I demonstrate the power of translational molecular profiling to understand these diseases at the genetic, transcriptomic, and/or cellular levels. First, I describe our UWO3 prognostic biomarker that may allow personalized treatment decision making in HPV-associated oropharyngeal cancer. Next, I defined the clinical, transcriptional, and cellular landscape of the human epiglottis and subglottis in healthy and diseased states. By studying the disease idiopathic subglottic stenosis, I catalogued the cellular population within the subglottis associated with disease status and clinical outcomes. I uncovered unappreciated plasticity within the subglottis microenvironment and identified potential therapeutics to reverse disease. Furthermore, I unraveled the genomic and evolutionary landscape of anaplastic thyroid cancer (ATC). Subclonal reconstruction provided unambiguous evidence that ATC diverged early from its related but indolent differentiated thyroid cancers. Finally, using biological insights from an ATC patient undergoing therapy, I present evidence that the type II RAF inhibitor naporafenib can overcome treatment resistance in ATC in vitro and in patient-derived xenograft models. I further uncover the mechanisms of innate and acquired resistance. Together, these molecular portraits have provided tremendous insights on disease drivers, discovered biomarkers, nominated drug targets, and presented new opportunities for clinical translation.

Summary for Lay Audience

Medicine is becoming increasingly personalized for each patient. However, our lack of understanding of diseases in the head and neck region has hampered the development of more individualized treatments. In my thesis, I will study three diseases in detail: human papillomavirus associated-oropharyngeal cancer, idiopathic subglottic stenosis, and anaplastic thyroid cancer. I will use these three diseases that exhibit distinct properties in terms of etiology, anatomy, malignancy, and patient outcomes to demonstrate the power of understanding them at the molecular level. Using this knowledge, I discovered biomarkers that can predict patient trajectory and identified new treatments that may be more effective or long-lasting. Specifically, I studied the differences at the DNA, RNA, protein, and/or cell level to understand why these diseases develop and elucidate why patients respond differently to treatment. In the first study, I developed a biomarker that may allow clinicians to identify human papillomavirus-driven oropharyngeal cancer patients at low, medium, or high risk of relapse. In the second study, I studied epiglottis and subglottis samples from patients suffering from idiopathic subglottic stenosis to identify cells that may be driving disease. In the third study, I catalogued changes in the DNA of tumour cells that lead to the development of lethal anaplastic thyroid cancer. Finally, in the fourth study I elucidated why anaplastic thyroid cancer cells are resistant to treatment, and identified a drug called naporafenib that anaplastic thyroid cancer cells are vulnerable to. Together, my work has uncovered important mechanisms governing the development of diseases in the head and neck and provided important groundwork for future investigations in the lab and clinic.

SupplementaryTable01.UWO3_clinical_characteristics.xlsx (10 kB)

SupplementaryTable02.Treatment_received_in_UWO3_study.xlsx (11 kB)

SupplementaryTable03.Patient_Characteristics.xlsx (11 kB)

SupplementaryTable04.Sample_Characteristics.xlsx (10 kB)

SupplementaryTable05.Transcript_disease_tissue_interaction.xlsx (1263 kB)

SupplementaryTable06.cell_composition_analysis.xlsx (29 kB)

SupplementaryTable07.ConnecitivityMap_Fibroblast.xlsx (62 kB)

SupplementaryTable08.Variants_associated_with_cell_type_abundance.xlsx (58 kB)

SupplementaryTable09_SampleSummary.xlsx (115 kB)

SupplementaryTable10_SeqSig_results.xlsx (20 kB)

SupplementaryTable11_RNA_abundance_TPM.xlsx (11077 kB)

SupplementaryTable12_GermlineSNVs_DriverGenes.xlsx (23 kB)

SupplementaryTable13_CNA_subtype_association.xlsx (9 kB)

SupplementaryTable14_RNA_fusions.xlsx (221 kB)

SupplementaryTable15_SNV_SurvivalAssociations.xlsx (31 kB)

SupplementaryTable16_CNA_SurvivalAssociations.xlsx (38 kB)

SupplementaryTable17_StudyComparison_CNAs.xlsx (3250 kB)

SupplementaryTable18_CNA_RNA_correlation.xlsx (19 kB)

SupplementaryTable19_StudyComparison_SNVs.xlsx (1636 kB)

SupplementaryTable20_SNVOverlap.xlsx (13 kB)

SupplementaryTable21_CNAOverlap.xlsx (15 kB)

Available for download on Saturday, May 23, 2026