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Oncology Commons

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Full-Text Articles in Oncology

Numerical Chromosomal Instability Mediates Susceptibility To Radiation Treatment, Samuel F. Bakhoum, Lilian Kabeche, Matthew D. Wood, Christopher D. Laucius Jul 2015

Numerical Chromosomal Instability Mediates Susceptibility To Radiation Treatment, Samuel F. Bakhoum, Lilian Kabeche, Matthew D. Wood, Christopher D. Laucius

Dartmouth Scholarship

The exquisite sensitivity of mitotic cancer cells to ionizing radiation (IR) underlies an important rationale for the widely used fractionated radiation therapy. However, the mechanism for this cell cycle-dependent vulnerability is unknown. Here we show that treatment with IR leads to mitotic chromosome segregation errors in vivo and long-lasting aneuploidy in tumour-derived cell lines. These mitotic errors generate an abundance of micronuclei that predispose chromosomes to subsequent catastrophic pulverization thereby independently amplifying radiation-induced genome damage. Experimentally suppressing whole-chromosome missegregation reduces downstream chromosomal defects and significantly increases the viability of irradiated mitotic cells. Further, orthotopically transplanted human glioblastoma tumours in which …


Role Of A Genetic Variant On The 15q25.1 Lung Cancer Susceptibility Locus In Smoking-Associated Nasopharyngeal Carcinoma, Xuemei Ji, Weidong Zhang, Jiang Gui, Xia Fan, Weiwei Zhang, Yafang Li, Guangyu An, Dakai Zhu, Qiang Hu Oct 2014

Role Of A Genetic Variant On The 15q25.1 Lung Cancer Susceptibility Locus In Smoking-Associated Nasopharyngeal Carcinoma, Xuemei Ji, Weidong Zhang, Jiang Gui, Xia Fan, Weiwei Zhang, Yafang Li, Guangyu An, Dakai Zhu, Qiang Hu

Dartmouth Scholarship

Background: The 15q25.1 lung cancer susceptibility locus, containing CHRNA5, could modify lung cancer susceptibility and multiple smoking related phenotypes. However, no studies have investigated the association between CHRNA5 rs3841324, which has been proven to have the highest association with CHRNA5 mRNA expression, and the risk of other smoking-associated cancers, except lung cancer. In the current study we examined the association between rs3841324 and susceptibility to smoking-associated nasopharyngeal carcinoma (NPC).

Methods: In this case-control study we genotyped the CHRNA5 rs3841324 polymorphism with 400 NPC cases and 491 healthy controls who were Han Chinese and frequency-matched by age (±5 years), gender, and …


Feasibility Of Tomotherapy-Based Image-Guided Radiotherapy To Reduce Aspiration Risk In Patients With Non-Laryngeal And Non-Pharyngeal Head And Neck Cancer, Nam P. Nguyen, Lexie Smith-Raymond, Vincent Vinh-Hung, Paul Vos, Rick Davis, Anand Desai, Thomas Sroka Mar 2013

Feasibility Of Tomotherapy-Based Image-Guided Radiotherapy To Reduce Aspiration Risk In Patients With Non-Laryngeal And Non-Pharyngeal Head And Neck Cancer, Nam P. Nguyen, Lexie Smith-Raymond, Vincent Vinh-Hung, Paul Vos, Rick Davis, Anand Desai, Thomas Sroka

Dartmouth Scholarship

Purpose: The study aims to assess the feasibility of Tomotherapy-based image-guided radiotherapy (IGRT) to reduce the aspiration risk in patients with non-laryngeal and non-hypopharyngeal cancer. A retrospective review of 48 patients undergoing radiation for non-laryngeal and non-hypopharyngeal head and neck cancers was conducted. All patients had a modified barium swallow (MBS) prior to treatment, which was repeated one month following radiotherapy. Mean middle and inferior pharyngeal dose was recorded and correlated with the MBS results to determine aspiration risk.


Building A Statistical Model For Predicting Cancer Genes, Ivan P. Gorlov, Christopher J. Logothetis, Shenying Fang, Olga Y. Gorlova, Christopher Amos Nov 2012

Building A Statistical Model For Predicting Cancer Genes, Ivan P. Gorlov, Christopher J. Logothetis, Shenying Fang, Olga Y. Gorlova, Christopher Amos

Dartmouth Scholarship

More than 400 cancer genes have been identified in the human genome. The list is not yet complete. Statistical models predicting cancer genes may help with identification of novel cancer gene candidates. We used known prostate cancer (PCa) genes (identified through KnowledgeNet) as a training set to build a binary logistic regression model identifying PCa genes. Internal and external validation of the model was conducted using a validation set (also from KnowledgeNet), permutations, and external data on genes with recurrent prostate tumor mutations. We evaluated a set of 33 gene characteristics as predictors. Sixteen of the original 33 predictors were …