Universal concept signature analysis: genome-wide quantification of new biological and pathological functions of genes and pathways.

Identifying new gene functions and pathways underlying diseases and biological processes are major challenges in genomics research. Particularly, most methods for interpreting the pathways characteristic of an experimental gene list defined by genomic data are limited by their dependence on assessing the overlapping genes or their interactome topology, which cannot account for the variety of functional relations. This is particularly problematic for pathway discovery from single-cell genomics with low gene coverage or interpreting complex pathway changes such as during change of cell states. Here, we exploited the comprehensive sets of molecular concepts that combine ontologies, pathways, interactions and domains to help inform the functional relations. We first developed a universal concept signature (uniConSig) analysis for genome-wide quantification of new gene functions underlying biological or pathological processes based on the signature molecular concepts computed from known functional gene lists. We then further developed a novel concept signature enrichment analysis (CSEA) for deep functional assessment of the pathways enriched in an experimental gene list. This method is grounded on the framework of shared concept signatures between gene sets at multiple functional levels, thus overcoming the limitations of the current methods. Through meta-analysis of transcriptomic data sets of cancer cell line models and single hematopoietic stem cells, we demonstrate the broad applications of CSEA on pathway discovery from gene expression and single-cell transcriptomic data sets for genetic perturbations and change of cell states, which complements the current modalities. The R modules for uniConSig analysis and CSEA are available through https://github.com/wangxlab/uniConSig.

HPV Integration in HNSCC Correlates with Survival Outcomes, Immune Response Signatures, and Candidate Drivers.

The incidence of human papillomavirus (HPV)-related oropharynx cancer has steadily increased over the past two decades and now represents a majority of oropharyngeal cancer cases. Integration of the HPV genome into the host genome is a common event during carcinogenesis that has clinically relevant effects if the viral early genes are transcribed. Understanding the impact of HPV integration on clinical outcomes of head and neck squamous cell carcinoma (HNSCC) is critical for implementing deescalated treatment approaches for HPV+ HNSCC patients. RNA sequencing (RNA-seq) data from HNSCC tumors (n = 84) were used to identify and characterize expressed integration events, which were overrepresented near known head and neck, lung, and urogenital cancer genes. Five genes were recurrent, including CD274 (PD-L1) A significant number of genes detected to have integration events were found to interact with Tp63, ETS, and/or FOX1A. Patients with no detected integration had better survival than integration-positive and HPV- patients. Furthermore, integration-negative tumors were characterized by strongly heightened signatures for immune cells, including CD4+, CD3+, regulatory, CD8+ T cells, NK cells, and B cells, compared with integration-positive tumors. Finally, genes with elevated expression in integration-negative specimens were strongly enriched with immune-related gene ontology terms, while upregulated genes in integration-positive tumors were enriched for keratinization, RNA metabolism, and translation.Implications: These findings demonstrate the clinical relevancy of expressed HPV integration, which is characterized by a change in immune response and/or aberrant expression of the integration-harboring cancer-related genes, and suggest strong natural selection for tumor cells with expressed integration events in key carcinogenic genes. Mol Cancer Res; 16(1); 90-102. ©2017 AACR.

Subtypes of HPV-Positive Head and Neck Cancers Are Associated with HPV Characteristics, Copy Number Alterations, PIK3CA Mutation, and Pathway Signatures.

PURPOSE: There is substantial heterogeneity within human papillomavirus (HPV)-associated head and neck cancer (HNC) tumors that predispose them to different outcomes; however, the molecular heterogeneity in this subgroup is poorly characterized due to various historical reasons. EXPERIMENTAL DESIGN: We performed unsupervised gene expression clustering on deeply annotated (transcriptome and genome) HPV(+) HNC samples from two cohorts (84 total primary tumors), including 18 HPV(-) HNC samples, to discover subtypes and characterize the differences between subgroups in terms of their HPV characteristics, pathway activity, whole-genome somatic copy number alterations, and mutation frequencies. RESULTS: We identified two distinct HPV(+) subtypes (namely HPV-KRT and HPV-IMU). HPV-KRT is characterized by elevated expression of genes in keratinocyte differentiation and oxidation-reduction process, whereas HPV-IMU has strong immune response and mesenchymal differentiation. The differences in expression are likely connected to the differences in HPV characteristics and genomic changes. HPV-KRT has more genic viral integration, lower E2/E4/E5 expression levels, and higher ratio of spliced to full-length HPV oncogene E6 than HPV-IMU; the subgroups also show differences in copy number alterations and mutations, in particular the loss of chr16q in HPV-IMU and gain of chr3q and PIK3CA mutation in HPV-KRT. CONCLUSIONS: Our characterization of two subtypes of HPV(+) HNC tumors provides valuable molecular level information that point to two main carcinogenic paths. Together, these results shed light on stratifications of the HPV(+) HNCs and will help to guide personalized care for HPV(+) HNC patients. Clin Cancer Res; 22(18); 4735-45. ©2016 AACR.