Oncogenic drivers in 11q13 associated with prognosis and response to therapy in advanced oropharyngeal carcinomas
M C Barros-Filho1, L A Reis-Rosa2, M Hatakeyama1
1International Research Center (CIPE), A. C. Camargo Cancer Center, São Paulo, Brazil.
Objectives:
To identify potential molecular drivers associated with prognosis and response to treatment in advanced oropharyngeal squamous cell carcinomas (OPSCC).
Materials And Methods:
Thirty-three OPSCC biopsies from untreated Brazilian patients were evaluated for human papilloma virus genotyping, genome wide copy number alterations and gene expression profiling. Data were integrated using CONEXIC algorithm. Validation with TCGA dataset and confirmation by RT-qPCR of candidate genes were performed.
Results:
High-risk HPV positive cases, detected in 55% of advanced OPSCC, were associated with better outcome. Losses of 8p11.23-p11.22, 14q11.1-q11.2 and 15q11.2, and gains of 11q13.2 and 11q13.2-q13.3 were detected as recurrent alterations. Gains of 3q26.31 and 11q13.2 and losses of 9p21.3 were exclusively detected in HPV-negative tumors. Two clusters of expression profiles were observed, being one composed mostly by HPV positive cases (83%). HPV-positive enriched cluster showed predominantly immune response-related pathways. Integrative analysis identified 10 modulators mapped in 11q13, which were frequently cancer-related. These 10 genes showed copy number gains, overexpression and an association with worse survival, further validated by TCGA database analyses. Overexpression of four genes (ORAOV1, CPT1A, SHANK2 and PPFIA1) evaluated by RT-qPCR confirmed their association with poor survival. Multivariate analysis showed that PPFIA1 overexpression and HPV status are independent prognostic markers. Moreover, SHANK2 overexpression was significantly associated with incomplete response to treatment.
Conclusion:
The integrative genomic and transcriptomic data revealed potential driver genes mapped in 11q13 associated with worse prognosis and response to treatment, giving fundamentals for the identification of novel therapeutic targets in OPSCC.
More Related Videos
07:32Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
Published on: April 12, 2024
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
Related Concept Videos
01:25Suctioning the Oropharyngeal Airway
After assembling the equipment, the nurse should practice hand hygiene and don appropriate PPE according to infection control guidelines to avoid the...
01:33Cancer-Critical Genes I: Proto-oncogenes
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
00:59Gene Therapy
02:22Overview of Advanced Functional Groups
Functional groups are groups of atoms with specific chemical properties that occur within organic molecules and are sometimes denoted as “R”. Functional groups can “functionalize” a compound by enabling it to adopt different physical and chemical properties.
Types of Advanced Functional Groups
The table below summarizes some of the major functional groups in organic chemistry.
00:56Extraction: Advanced Methods
01:26Group Therapy