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The proto-oncogene function of Mdm2 in bone.
Olivos DJ, Perrien DS, Hooker A, Cheng YH, Fuchs RK, Hong JM, Bruzzaniti A, Chun K, Eischen CM, Kacena MA, Mayo LD
(2018) J Cell Biochem 119: 8830-8840
MeSH Terms: Analysis of Variance, Animals, Bone Density, Bone Remodeling, Calcification, Physiologic, Cancellous Bone, Cell Line, Tumor, Female, Humans, Male, Mice, Mice, Inbred C57BL, Mice, Inbred DBA, Osteoblasts, Osteoclasts, Osteogenesis, Osteosarcoma, Proto-Oncogene Proteins c-mdm2, Proto-Oncogenes
Show Abstract · Added April 1, 2019
Mouse double minute 2 (Mdm2) is a multifaceted oncoprotein that is highly regulated with distinct domains capable of cellular transformation. Loss of Mdm2 is embryonically lethal, making it difficult to study in a mouse model without additional genetic alterations. Global overexpression through increased Mdm2 gene copy number (Mdm2 ) results in the development of hematopoietic neoplasms and sarcomas in adult animals. In these mice, we found an increase in osteoblastogenesis, differentiation, and a high bone mass phenotype. Since it was difficult to discern the cell lineage that generated this phenotype, we generated osteoblast-specific Mdm2 overexpressing (Mdm2 ) mice in 2 different strains, C57BL/6 and DBA. These mice did not develop malignancies; however, these animals and the MG63 human osteosarcoma cell line with high levels of Mdm2 showed an increase in bone mineralization. Importantly, overexpression of Mdm2 corrected age-related bone loss in mice, providing a role for the proto-oncogenic activity of Mdm2 in bone health of adult animals.
© 2018 Wiley Periodicals, Inc.
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19 MeSH Terms
Simple staging system for osteosarcoma performs equivalently to the AJCC and MSTS systems.
Cates JMM
(2018) J Orthop Res 36: 2802-2808
MeSH Terms: Adolescent, Adult, Bone Neoplasms, Bone and Bones, Female, Humans, Male, Neoplasm Metastasis, Neoplasm Staging, Osteosarcoma, Prognosis, Retrospective Studies, SEER Program, United States, Young Adult
Show Abstract · Added November 1, 2018
Both the American Joint Committee on Cancer (AJCC) and Musculoskeletal Tumor Society (MSTS) staging systems for skeletal sarcomas have major weaknesses. A revised staging system for osteosarcoma (the Vanderbilt system) was developed based on exploratory analyses of the relative prognostic impacts of histologic grade, tumor size, local tumor extension, and specific anatomic sites of metastasis using case records from the National Cancer Database (N = 4,285). AJCC, MSTS, and Vanderbilt staging schemes were then compared using a separate, population-based cancer registry (the Surveillance, Epidemiology, and End Results database; N = 2,246) as a validation dataset. Predictive accuracy for 5-year sarcoma-specific survival was evaluated by comparing areas under receiver-operating characteristic curves generated from logistic regression. Three different concordance indices and Bayesian information criteria were also calculated for model comparisons. The Vanderbilt staging system showed comparable predictive accuracy for 5-year disease-specific survival (65%) compared to the AJCC (67%) and MSTS (67%) staging systems. Most cross-comparisons of model concordance were not significantly different either. Bayesian information criterion was lowest for the MSTS staging system. Substaging osteosarcoma by current anatomical criteria is ineffectual. A simplified staging system based only on histologic grade and the presence of distant metastasis to any anatomic site performs similarly to the current AJCC and MSTS staging systems by multiple statistical criteria and is proposed for clinical and pathological staging of osteosarcomas of the non-pelvic appendicular and non-spinal axial skeleton. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:2802-2808, 2018.
© 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.
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Modeling Continuous Prognostic Factors in Survival Analysis: Implications for Tumor Staging and Assessing Chemotherapy Effect in Osteosarcoma.
Cates JMM
(2018) Am J Surg Pathol 42: 485-491
MeSH Terms: Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Bone Neoplasms, Chemotherapy, Adjuvant, Child, Databases, Factual, Decision Support Techniques, Female, Humans, Male, Middle Aged, Models, Statistical, Necrosis, Neoadjuvant Therapy, Neoplasm Staging, Orthopedic Procedures, Osteosarcoma, Predictive Value of Tests, Risk Assessment, Risk Factors, Time Factors, Treatment Outcome, Tumor Burden, United States, Young Adult
Show Abstract · Added November 1, 2018
Extent of response to neoadjuvant chemotherapy, tumor size, and patient age are important prognostic variables for patients with osteosarcoma, but applying information from these continuous variables in survival models is difficult. Dichotomization is usually inappropriate and alternative statistical techniques should be considered instead. Nonlinear multivariable regression methods (restricted cubic splines and fractional polynomials) were applied to data from the National Cancer Database to model continuous prognostic factors for overall survival from localized, high-grade osteosarcoma of the appendicular and nonspinal skeleton following neoadjuvant chemotherapy and surgical resection (N=2493). The assumption that log hazard ratios were linear in relation to these continuous prognostic factors was tested using likelihood ratio tests of model deviance and Wald tests of spline coefficients. Log hazard ratios for increasing patient age were linear over the range of 4 to 80 years, but showed evidence for variation in the coefficient over elapsed follow-up time. Tumor size also showed a linear relationship with log hazard over the range of 1 to 30 cm. Hazard ratios for chemotherapy effect profoundly deviated from log-linear (P<0.004), with significantly decreased hazard for death from baseline for patients with ≥90% tumor necrosis (hazard ratio, 0.32; 95% confidence interval, 0.20-0.52; P<0.0001). Important implications of these results include: (1) ≥90% tumor necrosis defines good chemotherapy response in a clinically useful manner; (2) staging osteosarcoma by dichotomizing tumor size is inappropriate; and (3) patient age can be modeled as a linear effect on the log hazard ratio in prognostic models with the caveat that risk may change over duration of the analysis.
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28 MeSH Terms
Comparison of the AJCC, MSTS, and Modified Spanier Systems for Clinical and Pathologic Staging of Osteosarcoma.
Cates JM
(2017) Am J Surg Pathol 41: 405-413
MeSH Terms: Adult, Aged, Bone Neoplasms, Female, Follow-Up Studies, Humans, Logistic Models, Male, Middle Aged, Neoplasm Staging, Osteosarcoma, Prognosis, Retrospective Studies, Survival Analysis
Show Abstract · Added November 1, 2018
The prognostic performance of the 2 most commonly used staging systems for skeletal sarcoma (the American Joint Committee on Cancer [AJCC] and Musculoskeletal Tumor Society [MSTS] systems) have never been compared analytically. Another staging system originally proposed by Spanier has not yet been validated. Given the recent release of the 8th edition of the AJCC Cancer Staging Manual, this study was designed to directly compare these anatomic staging systems in a series of 153 high-grade, intramedullary osteosarcomas. Kaplan-Meier curves were plotted and pairwise comparisons between each stage category were performed. Predictive accuracy of each staging system for determining 5-year disease-free survival was evaluated by comparing areas under receiver-operating characteristic curves generated from logistic regression analysis. Multiple concordance indices were calculated using bootstrapping methods (200 replications). ρk and R were estimated as measures of the variation in survival outcomes explained by the regression models. The AJCC, MSTS, and a modified version of the Spanier staging systems showed similar discriminatory abilities and no significant differences in the levels of contrast between different tumor stages across staging systems. Addition of T-category information from each staging system contributed significant prognostic information compared with a Cox proportional hazard regression model consisting only of the presence or absence of metastatic disease as a measure of disease extent. Concordance indices and predictive accuracy for 5-year disease-free survival were not significantly different among the different staging systems either. Similar findings were observed after accounting for other important prognostic variables. Additional studies are necessary to determine performance parameters of each staging system for other types of skeletal sarcoma. Prognostic performance of osteosarcoma staging systems would also be improved by incorporating nonanatomic prognostic variables into staging algorithms.
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Reporting Surgical Resection Margin Status for Osteosarcoma: Comparison of the AJCC, MSTS, and Margin Distance Methods.
Cates JM
(2017) Am J Surg Pathol 41: 633-642
MeSH Terms: Adolescent, Adult, Area Under Curve, Bone Neoplasms, Decision Support Techniques, Disease-Free Survival, Female, Humans, Kaplan-Meier Estimate, Logistic Models, Male, Margins of Excision, Multivariate Analysis, Neoplasm Grading, Neoplasm Recurrence, Local, Neoplasm, Residual, Osteosarcoma, Osteotomy, Predictive Value of Tests, Proportional Hazards Models, ROC Curve, Risk Assessment, Risk Factors, Time Factors, Treatment Outcome, Young Adult
Show Abstract · Added November 1, 2018
Multiple different schemes are used to assess surgical resection margins in orthopedic pathology, but which is optimal for reporting resection margin status of osteosarcoma is uncertain. Moreover, the minimum tumor clearance (metric width of resection margin) necessary for local control is not well defined. In this investigation, the American Joint Committee on Cancer (AJCC) R system, Musculoskeletal Tumor Society (MSTS) system, and margin distance method for reporting resection margin status were compared in a series of 186 high-grade osteosarcomas. Hazard ratios for local recurrence for each resection margin category were compared with other categories within each margin assessment scheme to assess discriminatory ability. Cross-model comparisons of regression coefficients from parametric survival and logistic regression models were also performed. Predictive accuracy of each margin assessment scheme for determining 2-year local recurrence-free survival was evaluated by comparing the areas under receiver-operating characteristic curves generated from logistic regression analyses. Concordance with clinical outcomes was also calculated. Both the MSTS and margin distance schemes showed significantly greater predictive accuracy and concordance with observed outcomes than the AJCC R system. A margin distance of ≥2 mm significantly decreased the risk of local recurrence. Results were similar after adjustment for confounding prognostic factors (anatomic site, macroscopic lymphovascular invasion, and chemotherapy status). Therefore, surgical resection margins for osteosarcoma should be reported using either the MSTS or margin distance method instead of the AJCC R system.
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Cytologic anaplasia is a prognostic factor in osteosarcoma biopsies, but mitotic rate or extent of spontaneous tumor necrosis are not: a critique of the College of American Pathologists Bone Biopsy template.
Cates JM, Dupont WD
(2017) Mod Pathol 30: 52-59
MeSH Terms: Adolescent, Adult, Anaplasia, Biopsy, Bone Neoplasms, Child, Disease-Free Survival, Female, Humans, Male, Mitosis, Necrosis, Osteosarcoma, Prognosis, Retrospective Studies, Survival Rate, Young Adult
Show Abstract · Added November 1, 2018
The current College of American Pathologists cancer template for reporting biopsies of bone tumors recommends including information that is of unproven prognostic significance for osteosarcoma, such as the presence of spontaneous tumor necrosis and mitotic rate. Conversely, the degree of cytologic anaplasia (degree of differentiation) is not reported in this template. This retrospective cohort study of 125 patients with high-grade osteosarcoma was performed to evaluate the prognostic impact of these factors in diagnostic biopsy specimens in predicting the clinical outcome and response to neoadjuvant chemotherapy. Multivariate Cox regression was performed to adjust survival analyses for well-established prognostic factors. Multivariate logistic regression was used to determine odds ratios for good chemotherapy response (≥90% tumor necrosis). Osteosarcomas with severe anaplasia were independently associated with increased overall and disease-free survival, but mitotic rate and spontaneous necrosis had no prognostic impact after controlling for other confounding factors. Mitotic rate showed a trend towards increased odds of a good histologic response, but this effect was diminished after controlling for other predictive factors. Neither spontaneous necrosis nor the degree of cytologic anaplasia observed in biopsy specimens was predictive of a good response to chemotherapy. Mitotic rate and spontaneous tumor necrosis observed in pretreatment biopsy specimens of high-grade osteosarcoma are not strong independent prognostic factors for clinical outcome or predictors of response to neoadjuvant chemotherapy. Therefore, reporting these parameters for osteosarcoma, as recommended in the College of American Pathologists Bone Biopsy template, does not appear to have clinical utility. In contrast, histologic grading schemes for osteosarcoma based on the degree of cytologic anaplasia may have independent prognostic value and should continue to be evaluated.
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Utility of Examination of Biopsy Tracts in Osteosarcoma Resection Specimens.
Cates JM
(2016) Am J Clin Pathol 146: 324-7
MeSH Terms: Biopsy, Bone Neoplasms, Humans, Neoplasm, Residual, Osteosarcoma
Show Abstract · Added November 1, 2018
OBJECTIVES - To determine the utility and necessity of submitting tissue sections from the biopsy tracts of osteosarcoma resection specimens.
METHODS - The prevalence of residual tumor in representative sections of osteosarcoma biopsy tracts was assessed in a series of 97 osteosarcoma resection specimens.
RESULTS - No residual tumor cells were identified in 97 sampled biopsy tracts (0%; 95% confidence interval, 0%-2.5%).
CONCLUSIONS - Pathologists do not need to submit sections of resected biopsy tracts unless there is clinical or gross evidence that would warrant further examination.
© American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Proximal location in extremity long bones is a poor prognostic factor for osteosarcoma: A retrospective cohort study of 153 patients.
Cates JM, Schoenecker JG
(2016) Acta Oncol 55: 1036-9
MeSH Terms: Adolescent, Adult, Bone Neoplasms, Cohort Studies, Disease-Free Survival, Female, Humans, Humerus, Male, Neoadjuvant Therapy, Osteosarcoma, Prognosis, Proportional Hazards Models, Retrospective Studies, Tibia, Young Adult
Show Abstract · Added November 1, 2018
BACKGROUND - Osteosarcomas arising in the proximal femur, humerus, and tibia appear to have poorer outcomes than those arising in distal long bones. However, the strength of this association is uncertain, particularly in light of other prognostic factors. Therefore, this retrospective cohort study was performed to compare patient outcomes between proximal and distal tumor location within extremity long bones.
MATERIAL AND METHODS - A total of 153 patients with conventional high-grade osteosarcoma of the extremity long bones, pelvis, or axial skeleton who had undergone neoadjuvant chemotherapy and surgical resection between 1985 and 2010 were identified in the Surgical Pathology files at Vanderbilt Medical Center. Effect of anatomic location within a proximal long bone was assessed using multivariable Cox proportional hazard regression.
RESULTS - Proximal tumor location was a strong predictor of poor prognosis in univariate survival analysis. Multivariate regression analysis showed that after controlling for American Joint Committee on Cancer (AJCC) stage, histologic response to chemotherapy, surgical resection margin status, and histologic type, location in the proximal femur, tibia, and humerus were independent risk factors for death due to osteosarcoma, but not event-free survival.
CONCLUSION - Osteosarcomas of the proximal extremity long bones are associated with decreased disease-specific survival compared to tumors of the distal long bones, even after accounting for other key prognostic covariates.
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Pathologic fracture a poor prognostic factor in osteosarcoma: Misleading conclusions from meta-analyses?
Cates JM
(2016) Eur J Surg Oncol 42: 883-8
MeSH Terms: Bone Neoplasms, Disease-Free Survival, Fractures, Spontaneous, Humans, Osteosarcoma, Prognosis, Retrospective Studies
Show Abstract · Added November 1, 2018
AIM - Recently published meta-analyses have concluded that pathologic fracture is a negative prognostic factor in osteosarcoma. But several confounding variables were not accounted for in the index studies, thereby compromising internal validity.
METHODS - A multivariable survival analysis of a retrospective cohort of 131 patients with conventional, high-grade osteosarcoma of the extremity long bones treated with neoadjuvant chemotherapy and surgical resection was performed.
RESULTS - There were no significant differences in clinicopathologic variables between the 21 patients who suffered pathologic fracture and the 110 patients who did not in standard bivariable statistical tests. Hazard ratios for decreased overall and disease-free survival of patients with pathologic fracture failed to reach statistical significance in univariable Cox proportional hazard regression. Furthermore, pathologic fracture did not significantly affect patient outcome (hazard ratio for overall survival, 1.15 [95% CI 0.56-2.38], P = 0.71 or disease-free survival, 1.01 [95% CI 0.53-1.91], P = 0.98) after controlling for confounding factors not accounted for in prior meta-analyses, such as tumor size, chemotherapy response, and proximal tumor location.
CONCLUSIONS - Pathologic fracture is not a significant prognostic factor for extremity osteosarcoma after controlling for other established prognostic factors. Although a useful statistical method, meta-analysis can generate false conclusions if important confounding factors are ignored. Analysis of individual patient data, which would require collaboration among different groups, would circumvent this limitation of meta-analysis.
Copyright © 2016 Elsevier Ltd. All rights reserved.
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for Thirteen Cancer Types.
Sampson JN, Wheeler WA, Yeager M, Panagiotou O, Wang Z, Berndt SI, Lan Q, Abnet CC, Amundadottir LT, Figueroa JD, Landi MT, Mirabello L, Savage SA, Taylor PR, De Vivo I, McGlynn KA, Purdue MP, Rajaraman P, Adami HO, Ahlbom A, Albanes D, Amary MF, An SJ, Andersson U, Andriole G, Andrulis IL, Angelucci E, Ansell SM, Arici C, Armstrong BK, Arslan AA, Austin MA, Baris D, Barkauskas DA, Bassig BA, Becker N, Benavente Y, Benhamou S, Berg C, Van Den Berg D, Bernstein L, Bertrand KA, Birmann BM, Black A, Boeing H, Boffetta P, Boutron-Ruault MC, Bracci PM, Brinton L, Brooks-Wilson AR, Bueno-de-Mesquita HB, Burdett L, Buring J, Butler MA, Cai Q, Cancel-Tassin G, Canzian F, Carrato A, Carreon T, Carta A, Chan JK, Chang ET, Chang GC, Chang IS, Chang J, Chang-Claude J, Chen CJ, Chen CY, Chen C, Chen CH, Chen C, Chen H, Chen K, Chen KY, Chen KC, Chen Y, Chen YH, Chen YS, Chen YM, Chien LH, Chirlaque MD, Choi JE, Choi YY, Chow WH, Chung CC, Clavel J, Clavel-Chapelon F, Cocco P, Colt JS, Comperat E, Conde L, Connors JM, Conti D, Cortessis VK, Cotterchio M, Cozen W, Crouch S, Crous-Bou M, Cussenot O, Davis FG, Ding T, Diver WR, Dorronsoro M, Dossus L, Duell EJ, Ennas MG, Erickson RL, Feychting M, Flanagan AM, Foretova L, Fraumeni JF, Freedman ND, Beane Freeman LE, Fuchs C, Gago-Dominguez M, Gallinger S, Gao YT, Gapstur SM, Garcia-Closas M, García-Closas R, Gascoyne RD, Gastier-Foster J, Gaudet MM, Gaziano JM, Giffen C, Giles GG, Giovannucci E, Glimelius B, Goggins M, Gokgoz N, Goldstein AM, Gorlick R, Gross M, Grubb R, Gu J, Guan P, Gunter M, Guo H, Habermann TM, Haiman CA, Halai D, Hallmans G, Hassan M, Hattinger C, He Q, He X, Helzlsouer K, Henderson B, Henriksson R, Hjalgrim H, Hoffman-Bolton J, Hohensee C, Holford TR, Holly EA, Hong YC, Hoover RN, Horn-Ross PL, Hosain GM, Hosgood HD, Hsiao CF, Hu N, Hu W, Hu Z, Huang MS, Huerta JM, Hung JY, Hutchinson A, Inskip PD, Jackson RD, Jacobs EJ, Jenab M, Jeon HS, Ji BT, Jin G, Jin L, Johansen C, Johnson A, Jung YJ, Kaaks R, Kamineni A, Kane E, Kang CH, Karagas MR, Kelly RS, Khaw KT, Kim C, Kim HN, Kim JH, Kim JS, Kim YH, Kim YT, Kim YC, Kitahara CM, Klein AP, Klein RJ, Kogevinas M, Kohno T, Kolonel LN, Kooperberg C, Kricker A, Krogh V, Kunitoh H, Kurtz RC, Kweon SS, LaCroix A, Lawrence C, Lecanda F, Lee VH, Li D, Li H, Li J, Li YJ, Li Y, Liao LM, Liebow M, Lightfoot T, Lim WY, Lin CC, Lin D, Lindstrom S, Linet MS, Link BK, Liu C, Liu J, Liu L, Ljungberg B, Lloreta J, Di Lollo S, Lu D, Lund E, Malats N, Mannisto S, Le Marchand L, Marina N, Masala G, Mastrangelo G, Matsuo K, Maynadie M, McKay J, McKean-Cowdin R, Melbye M, Melin BS, Michaud DS, Mitsudomi T, Monnereau A, Montalvan R, Moore LE, Mortensen LM, Nieters A, North KE, Novak AJ, Oberg AL, Offit K, Oh IJ, Olson SH, Palli D, Pao W, Park IK, Park JY, Park KH, Patiño-Garcia A, Pavanello S, Peeters PH, Perng RP, Peters U, Petersen GM, Picci P, Pike MC, Porru S, Prescott J, Prokunina-Olsson L, Qian B, Qiao YL, Rais M, Riboli E, Riby J, Risch HA, Rizzato C, Rodabough R, Roman E, Roupret M, Ruder AM, Sanjose Sd, Scelo G, Schned A, Schumacher F, Schwartz K, Schwenn M, Scotlandi K, Seow A, Serra C, Serra M, Sesso HD, Setiawan VW, Severi G, Severson RK, Shanafelt TD, Shen H, Shen W, Shin MH, Shiraishi K, Shu XO, Siddiq A, Sierrasesúmaga L, Sihoe AD, Skibola CF, Smith A, Smith MT, Southey MC, Spinelli JJ, Staines A, Stampfer M, Stern MC, Stevens VL, Stolzenberg-Solomon RS, Su J, Su WC, Sund M, Sung JS, Sung SW, Tan W, Tang W, Tardón A, Thomas D, Thompson CA, Tinker LF, Tirabosco R, Tjønneland A, Travis RC, Trichopoulos D, Tsai FY, Tsai YH, Tucker M, Turner J, Vajdic CM, Vermeulen RC, Villano DJ, Vineis P, Virtamo J, Visvanathan K, Wactawski-Wende J, Wang C, Wang CL, Wang JC, Wang J, Wei F, Weiderpass E, Weiner GJ, Weinstein S, Wentzensen N, White E, Witzig TE, Wolpin BM, Wong MP, Wu C, Wu G, Wu J, Wu T, Wu W, Wu X, Wu YL, Wunder JS, Xiang YB, Xu J, Xu P, Yang PC, Yang TY, Ye Y, Yin Z, Yokota J, Yoon HI, Yu CJ, Yu H, Yu K, Yuan JM, Zelenetz A, Zeleniuch-Jacquotte A, Zhang XC, Zhang Y, Zhao X, Zhao Z, Zheng H, Zheng T, Zheng W, Zhou B, Zhu M, Zucca M, Boca SM, Cerhan JR, Ferri GM, Hartge P, Hsiung CA, Magnani C, Miligi L, Morton LM, Smedby KE, Teras LR, Vijai J, Wang SS, Brennan P, Caporaso NE, Hunter DJ, Kraft P, Rothman N, Silverman DT, Slager SL, Chanock SJ, Chatterjee N
(2015) J Natl Cancer Inst 107: djv279
MeSH Terms: Adult, Aged, Asian Continental Ancestry Group, Bone Neoplasms, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Kidney Neoplasms, Leukemia, Lymphocytic, Chronic, B-Cell, Lung Neoplasms, Lymphoma, Large B-Cell, Diffuse, Male, Middle Aged, Neoplasms, Osteosarcoma, Polymorphism, Single Nucleotide, Smoking, Testicular Neoplasms, Tissue Array Analysis, Urinary Bladder Neoplasms
Show Abstract · Added April 3, 2018
BACKGROUND - Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.
METHODS - Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.
RESULTS - GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl (2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.
CONCLUSION - Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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