Pain is often one of the first signs of head and neck cancer. Head and neck cancer pain may be due to the disease itself (tumor) or as a consequence of therapy. Up to 80% of patients with head and neck cancer report pain during treatment and for some 36%, pain persists beyond treatment. Chronic pain leads to prolonged suffering and reduced quality of life. Neuropathic pain, in particular, remains a major clinical problem since existing analgesics are often ineffective and with serious side-effects. Therefore, the goal of this proposal is to perform genome-wide (730,525SNPs) analyses on 2400 patients with head and neck cancer to determine the molecular/genetic basis of chronic pain, with a specific emphasis on validating the role of genetic mechanisms in the transition from acute pain to chronic pain (nociceptive versus neuropathic).
The specific aims are;
AIM 1 : To perform genetic analyses on 2400 patients with squamous cell carcinoma of the head and neck in order to identify potentially novel gene variants associated with the development of chronic pain (neuropathic versus nociceptive). Hypothesis 1: Potentially novel genetic variants that may also serve as therapeutic targets for pain will be identified using a genome-wide SNP scan.
AIM 2 : To establish a cohort of head and neck cancer patients and determine the independent influence of behavioral, epidemiological, biological, and clinical factors in predicting the development of chronic pain (neuropathic/nociceptive) in these patients. Hypothesis 1: The development of chronic pain will vary by cancer treatment (surgery, chemotherapy, radiotherapy) and behavioral, epidemiological, and clinical factors.
AIM 3 : To perform exploratory gene-gene and gene-treatment (type of cancer treatment) interaction analyses that will help identify individuals at highest risk for the development of chronic pain (neuropathic versus nociceptive) on the basis of their genetic risk profiles and treatment (e.g. we will test th risk allele of each SNP for its association with detailed treatment information). Pain will be longitudinally assessed by self-report and quantitative sensory testing along with assessment of behavioral, genetic, clinical and epidemiological factors. We expect that new findings from this proposal will provide insight into the genetic mechanisms of chronic pain development and may provide novel information, which could lead to the development of new therapeutic agents for chronic neuropathic pain.

Public Health Relevance

Our study will provide critical information on the epidemiological, clinical, behavioral, and biological/genetic determinants for the development of chronic pain. Importantly, the genome-wide component of the grant may yield potential novel genes as therapeutic target for neuropathic pain, a disabling condition that is hard to treat with available analgesics.

National Institute of Health (NIH)
National Institute of Dental & Craniofacial Research (NIDCR)
Research Project (R01)
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Special Emphasis Panel (ZDE1-VH (09))
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Kusiak, John W
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University of Texas MD Anderson Cancer Center
Public Health & Prev Medicine
Schools of Medicine
United States
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Talluri, Rajesh; Shete, Sanjay (2018) An approach to estimate bidirectional mediation effects with application to body mass index and fasting glucose. Ann Hum Genet 82:396-406
Wang, Jian; Shete, Sanjay (2018) Estimation of indirect effect when the mediator is a censored variable. Stat Methods Med Res 27:3010-3025
Reyes-Gibby, Cielito C; Wang, Jian; Yeung, Sai-Ching J et al. (2018) Genome-wide association study identifies genes associated with neuropathy in patients with head and neck cancer. Sci Rep 8:8789
Reyes-Gibby, Cielito C; Melkonian, Stephanie C; Hanna, Ehab Y et al. (2017) Cohort study of oncologic emergencies in patients with head and neck cancer. Head Neck 39:1195-1204
Wang, Jian; Talluri, Rajesh; Shete, Sanjay (2017) Selection of X-chromosome Inactivation Model. Cancer Inform 16:1176935117747272
Dai, Tianjiao; Shete, Sanjay (2016) Time-varying SMART design and data analysis methods for evaluating adaptive intervention effects. BMC Med Res Methodol 16:112
Zhu, Xuan; Wang, Jian; Peng, Bo et al. (2016) Empirical estimation of sequencing error rates using smoothing splines. BMC Bioinformatics 17:177
Talluri, Rajesh; Shete, Sanjay (2016) Using the weighted area under the net benefit curve for decision curve analysis. BMC Med Inform Decis Mak 16:94
Reyes-Gibby, Cielito C; Wang, Jian; Silvas, Mary Rose T et al. (2016) Genome-wide association study suggests common variants within RP11-634B7.4 gene influencing severe pre-treatment pain in head and neck cancer patients. Sci Rep 6:34206
Reyes-Gibby, Cielito C; Wang, Jian; Silvas, Mary Rose T et al. (2016) MAPK1/ERK2 as novel target genes for pain in head and neck cancer patients. BMC Genet 17:40

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