Abstract 2490: Integrative systems analysis of HPV+ and HPV- oropharyngeal carcinomas
Bibliographic record
Abstract
Abstract BACKGROUND: Over half of oropharyngeal carcinomas (OPCs) are linked to high-risk human papillomavirus (HPV) infection. As compared to their HPV-positive (HPV+) counterparts, HPV-negative (HPV-) OPCs are associated with significantly worse survival, inferior treatment response and a distinct molecular expression profile. There are currently considerable efforts underway to personalize treatment based on HPV status; however, this remains challenging as the current understanding of the different biological mechanisms in HPV+ vs. HPV- OPCs is limited. Hence, a comprehensive proteomic analysis was performed, utilizing archival OPC tissues, in order to acquire greater insights into the distinct biological pathways. METHODS: Global protein expression profiling was conducted on 26 HPV- and 27 HPV+ pre-treatment formalin-fixed paraffin-embedded (FFPE) OPCs using an automated 5-step Multidimensional Protein Identification Technology (MudPIT) procedure on a LTQ-Orbitrap XL. Protein quantification was achieved by adjusted spectral counting. Differentially expressed proteins (p<0.05) were classified into functionally enriched categories and interaction networks using GeneMania. Finally, differential expression of 4 proteins was evaluated by immunohistochemistry (IHC) on an independent cohort of 17 HPV- and 12 HPV+ pre-treatment FFPE OPC biopsies. RESULTS: Among the 2633 high confidence protein groups identified, 174 were significantly differentially expressed in HPV+ vs. HPV- OPCs. Functional enrichment analysis of these proteins demonstrated enrichment of cell cycle, DNA repair, cytokine signaling, apoptosis, DNA packaging, and metabolism proteins. These results were in concordance with a previous publication of pooled OPCs (Slebos et al, 2012). In addition, utilizing The Cancer Genome Atlas (TCGA) data, we determined that the relative expression levels of many of these proteins could be attributed to changes in copy number, methylation, mRNA, or mutation profiles. Next, the top 4 proteins were selected for verification based on concordance with these datasets and reported biological relevance. Selected proteins are involved in actin assembly, purine metabolism, differentiation, and cell migration and invasion. As a result, the differential expression of 2 proteins was successfully validated by IHC, while 2 additional proteins exhibited the same trend as in the discovery cohort. CONCLUSION: This study provides the most in-depth and integrated protein-centric view of HPV+ and HPV- OPC. As a key finding, we highlight the identification of an actin assembly oncoprotein reported to be involved in a targetable radioresistance pathway. We hypothesize that this pathway is preferentially activated in HPV- OPCs. Hence, future experiments will focus on validating the in vivo observed expression pattern of this protein in vitro, and manipulating its expression to overcome radioresistance in OPC models. Citation Format: Lusia Sepiashvili, Angela Hui, Wei Shi, Wei Xu, Daryl Waggot, Paul Boutros, Alex Ignatchenko, Vladimir Ignatchenko, Shao Hui (Sophie) Huang, John Waldron, Brian O'Sullivan, Jonathan C. Irish, Fei-Fei Liu, Thomas Kislinger. Integrative systems analysis of HPV+ and HPV- oropharyngeal carcinomas. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2490. doi:10.1158/1538-7445.AM2014-2490
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".