Abstract 5118: Proteogenomics characterization of HPV-negative head and neck squamous cell carcinomas

Abstract

Patients with head and neck squamous cell carcinomas (HNSCCs) are treated with surgery, radiation, chemotherapy, and limited targeted therapies. Compared to human papillomavirus (HPV)-positive HNSCCs, HPV-negative cases have worse treatment response and prognosis and represent an unmet clinical need. We performed comprehensive proteogenomic characterization of tumor specimens, matched normal adjacent tissues (NATs), and blood samples from 109 HPV-negative HNSCC patients. This cohort is dominated by tumors from oral cavity (45, 41%) and larynx (49, 45%). Somatic mutation and somatic copy number analyses validated previously reported genomic aberrations in HPV-negative HNSCC. Proteomics analysis linked p53 loss of heterozygosity to increased expression of EPCAM, a stemness marker. Additionally, FAT1 truncation mutations were associated with increased expression of proteins involved in keratinization, a key feature of SCC differentiation. Deletions of 3p and 9p led to the loss of genes encoding p16, chemokine receptors, and interferon/JAK/STAT signaling pathway proteins, whereas amplifications of 3q and 11q led to overexpression of proteins involved in cell proliferation and anti-apoptosis pathways. Comparative analysis of tumor and NAT proteomes and phosphoproteomes identified putative diagnostic biomarkers and druggable targets, and proteogenomic integration further identified putative neoantigens. Tumor site-specific characterization associated epigenetic silencing of neurofilaments with laryngeal but not oral cavity SCC. Protein targets of FDA approved or investigational drugs for HNSCC treatment showed high inter-tumor heterogeneity in their protein abundances. DNA copy number and RNA expression level were good surrogates of protein abundance for some targets, such as EGFR and PD-L1, but they failed to reflect protein levels or kinase activities for other targets, such as MMP9 and MTOR. Thus, there is a critical need for protein biomarker-driven treatment stratification. Deconvolution of bulk tumor gene expression data revealed an immune-hot subgroup and an immune-cold subgroup. Immune-hot tumors broadly overexpressed multiple immune checkpoints including PD-L1, IDO1, and CTLA4, underscoring the necessity of combination immune checkpoint inhibition to improve treatment efficacy. Immune-cold tumors were characterized by smoking, chromosomal instability, and activation of the CDK4/6-pRb axis, suggesting they could be targeted by CDK4/6 inhibitors. We also noted that EGFR-amplified tumors frequently harbor copy number aberrations of downstream signaling components of the EGFR pathway. This may explain the low response rate of EGFR-amplified tumors to EGFR inhibitors, and targeting multiple pathway components, including EGFR, PIK3CA and STAT3, may be required for these tumors. In summary, our integrative proteogenomic characterization revealed multiple novel insights into the pathogenesis and treatment of HPV-negative HNSCCs. Citation Format: Chen Huang, Lijun Chen, Yize Li, Sara Savage, Michael Schnaubelt, Felipe V. Leprevost, Marcin Cieslik, Yongchao Dou, Bo Wen, Jonathan T. Lei, Kai Li, Eric Jaehnig, Zhiao Shi, Meenakshi Anurag, Jianbo Pan, Yingwei Hu, Rodrigo V. Eguez, David J. Clark, Matthew Wyczalkowski, Saravana M. Dhanasekaran, Chandan Kumar, Antonio Colaprico, Karsten Krug, Michael Gillette, D. R. Mani, Seungyeul Yoo, Jiayi Ji, Xiaoyu Song, Weiping Ma, Xi Steven Chen, Alex Pico, Nathan J. Edwards, Scott D. Jewell, Mathangi Thiagarajan, Emily S. Boja, Henry Rodriguez, Andrew Sikora, Pei Wang, Matthew Ellis, Gilbert S. Omenn, Li Ding, Alexey I. Nesvizhskii, Adel K. EI-Naggar, Daniel W. Chan, Hui Zhang, Bing Zhang, Clinical Proteomic Tumor Analysis Consortium. Proteogenomics characterization of HPV-negative head and neck squamous cell carcinomas [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5118.

Immunosignatures associated with TP53 status and co-mutations classify prognostically head and neck cancer patients

“…In Fig. 1 , panel E, the prognostic value of the immune signature was further validated in the HNSCC CPTAC cohort, as described by Huang et al [ 11 ]. The cohort consisted of 108 HPV-negative patients.…”

Clinical applications of mass spectrometry‐based proteomics in cancer: Where are we?

“…These authors suggested that EGFR ligands, rather than the receptor, are the major activator of EGFR pathway activity in this cancer type. Ligand abundance may be a more appropriate biomarker to select patients for anti‐EGFR monoclonal antibodies, which have shown only modest activity in unselected patient populations with head and neck cancer [76–78].…”

“…Initial single‐tumor cohort discovery studies in colorectal, breast and ovarian cancers used label‐free quantification and iTRAQ [27, 72, 73]. Subsequent studies have utilized TMT labeling and DIA for orthogonal validation [74–76].…”

“…Phosphoproteomic analysis revealed interesting insights into EGFR pathway activation in HPV‐negative OPSCC [76]. Counterintuitively, EGFR pathway activity did not correlate with EGFR alterations but with EGFR ligand abundance.…”

GPnotebook: A pan-cancer glycoproteomic database and toolkit for analysis of protein glycosylation changes associated with cancer phenotypes

“…Using the mass spectrometry data sets from 10 tumor types characterized by CPTAC projects, we created a python package, named as 'cptac_glyco', to provide the unified access to identified glycopeptides of CPTAC cancer glycoproteomics data, containing 90,661 Nlinked glycopeptides from 2,194 proteins. The 10 cancer types include breast carcinoma (BRC) (Krug et al, 2020), clear cell renal cell carcinoma (ccRCC) (Clark et al, 2019), colorectal carcinoma (CRC) (Vasaikar et al, 2019), glioblastoma (GBM) (Wang, L. et al, 2021), head and neck squamous cell carcinoma (HNSCC) (Huang et al, 2021), lung squamous cell carcinoma (LSCC) (Satpathy et al, 2021), lung adenocarcinoma (LUAD) (Gillette et al, 2020), ovarian serous cystadenocarcinoma (OVC) (Hu et al, 2020), pancreatic ductal adenocarcinoma (PDAC) (Cao et al, 2021), and uterine corpus endometrial carcinoma (UCEC) (Dou et al, 2020). Based on the standardized expression matrices, we developed GPnotebook for the comprehensive glycoproteomic data analysis based on IGPs.…”