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Tuesday & Wednesday, February 14 – 15, 2023

Integrating Environmental Data with Other Omics for Cancer Epidemiology Abstract

 

Virtual Workshop

Purpose

The purpose of this two-day virtual workshop was to identify the challenges and opportunities related to the integration of environmental exposure data with other omics data for human cancer population studies and to inform future supported research directions for the National Institute of Environmental Health Sciences (NIEHS) and the National Cancer Institute (NCI). This workshop was part of the NCI/NIEHS Cancer and the Environment Working Group’s effort to promote research into the effects of environmental exposures on cancer risk and etiology.

Goals

  1. To understand the challenges and opportunities in integrating environmental data with other omics.
  2. To identify the possible approaches and best practices for multi-omic integration including environmental data.
  3. To identify special considerations for using environmental and multi-omic data for cancer epidemiology.
  4. To determine how experimental models integrating environmental exposures and genomic (or other Omic) effects can be used to inform cancer risk assessment.

Workshop Recordings

Day 1: Tuesday, February 14, 2023

Setting the Stage and Purpose and Outcomes

Speakers:

  • Trevor Archer, Ph.D., Deputy Director, National Institute of Environmental Health Sciences (NIEHS); National Institutes of Health (NIH) Distinguished Investigator
  • Gary Ellison, Ph.D., M.P.H., Deputy Director, Division of Cancer Control and Population Sciences, National Cancer Institute (NCI)
  • Kimberly McAllister, Ph.D., NIEHS
  • Leah Mechanic, Ph.D., M.P.H., NCI

Session I: Specific Cancer Considerations

This session examined specific considerations about performing integration of environmental exposure data with other -omics data for cancer epidemiology studies. Topics that were explored include:

  • the role of tumor and normal tissue in disease biology
  • the long latency periods of cancer
  • the timing of exposures during particular susceptibility windows
  • the distinguishment between the role of exposure on cancer initiation and promotion.

Moderator

  • Ulrike Peters, Ph.D., M.P.H., University of Washington, Fred Hutchinson Cancer Center

Speakers

  • Mary Beth Terry, Ph.D., Columbia University, Mailman School of Public Health
  • Genevieve Leyden, Ph.D., University of Bristol, Bristol Medical School

Panelists

  • Catherine Metayer, M.D., Ph.D., University of California, Berkeley, School of Public Health
  • Sophia Wang, Ph.D., City of Hope Comprehensive Cancer Center
  • Peter Kraft, Ph.D., Harvard University, T.H. Chan School of Public Health
  • Cathrine Hoyo, Ph.D., North Carolina State University

Session II: Computational Approaches

This session delved into challenges and considerations for computational methods for integrating environmental exposure data with other -omics measures in cancer, including methods to deal with:

  • the heterogeneity of environmental data
  • the differences in data scales
  • the high dimensionality of environmental data

The group discussed possible methodology and computational needs and identified current best practices for these approaches.

Moderator

  • Andrea Baccarelli, M.D., Ph.D., Columbia University, Mailman School of Public Health

Speakers

  • James Gauderman, Ph.D., University of Southern California, Keck School of Medicine
  • Cristian Coarfa, Ph.D., Baylor University, Baylor College of Medicine

Panelists

  • Marylyn Ritchie, Ph.D., University of Pennsylvania, Perelman School of Medicine
  • Nilanjan Chatterjee, Ph.D., Johns Hopkins University, Bloomberg School of Public Health
  • Marina Sirota, Ph.D., University of California, San Francisco, Bakar Computational Health Sciences Institute

Open Discussion and Closing

Moderators

  • Kimberly McAllister, Ph.D., NIEHS
  • Leah Mechanic, Ph.D., M.P.H., NCI

Day 2: Wednesday, February 15, 2023

Introduction

Session III: Integration of Environmental Data With Other Data Types

This session explored the research gaps and needs for integrating a variety of diverse environmental data (toxicant measures from biological samples, high dimensional environmental data from wearable devices or GIS systems, etc.) with other omics data to inform our understanding of environmentally-relevant cancer outcomes. The session addressed how to better inform environmentally-relevant biomarkers for cancer outcomes by addressing the unique challenges with the incorporation of heterogenous environmental data including:

  • Temporality of exposures
  • Dose
  • Environmental mixtures

Moderator

  • Gary Miller, Ph.D., Columbia University, Mailman School of Public Health

Speakers

  • Dean Jones, Ph.D., Emory University, Winship Cancer Institute
  • Carmen Marsit, Ph.D., Emory University, Rollins School of Public Health

Panelists

  • Scarlett Gomez, Ph.D., M.P.H., University of California, San Francisco, Helen Diller Family Comprehensive Cancer Center
  • Thomas Metz, Ph.D., Pacific Northwest National Laboratory
  • Douglas Walker, Ph.D., Emory University, Rollins School of Public Health
  • Ivana Yang, Ph.D., University of Colorado, Anschutz Medical Campus
  • Nathaniel Rothman, M.D., M.P.H., M.H.S., NCI

Session IV: Experimental Models and Functional Approaches

This session examined how the expansion of in vitro functional genomics advances (CRISPR, organoids, etc.) and model organisms might be utilized to inform multi-omics human studies related to environmentally-sensitive cancers.

Moderator

  • Stephen Montgomery, Ph.D., Stanford University

Speakers

  • Stephen Montgomery, Ph.D., Stanford University
  • William Hill, Ph.D., The Francis Crick Institute
  • Matthew Devall, Ph.D., University of Virginia

Panelists

  • David Reif, Ph.D., NIEHS
  • Rebecca Fry, Ph.D., University of North Carolina at Chapel Hill, Gillings School of Global Public Health
  • Francesca Luca, Ph.D., Wayne State University
  • Justin Colacino, Ph.D., University of Michigan, School of Public Health

Closing Session: Integration of All Four Themes and Future Directions: Key Recommendations for Moving the Field Forward

Moderator

  • Kari Nadeau, M.D., Ph.D., Harvard University, T.H. Chan School of Public Health

Speakers

  • Chirag Patel, Ph.D., Harvard University, Harvard Medical School
  • Kimberly McAllister, Ph.D., NIEHS
  • Leah Mechanic, Ph.D., M.P.H., NCI

Publications

Reviews

  1. Adkins-Jackson PB, Chantarat T, Bailey ZD, Ponce NA. Measuring Structural Racism: A Guide for Epidemiologists and Other Health Researchers. Am J Epidemiol. 2022 Mar 24;191(4):539-547. doi: 10.1093/aje/kwab239. PMID: 34564723; PMCID: PMC9077112. [Abstract]
  2. Everson TM, Marsit CJ. Integrating -Omics Approaches into Human Population-Based Studies of Prenatal and Early-Life Exposures. Curr Environ Health Rep. 2018 Sep;5(3):328-337. doi: 10.1007/s40572-018-0204-1. PMID: 30054820; PMCID: PMC6187081. [Abstract]
  3. Ghosh D, Bernstein JA, Khurana Hershey GK, Rothenberg ME, Mersha TB. Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine. Front Immunol. 2018 Dec 12;9:2727. doi: 10.3389/fimmu.2018.02727. PMID: 30631320; PMCID: PMC6315155. [Abstract]
  4. Gillette MA, Satpathy S, Cao S, Dhanasekaran SM, Vasaikar SV, Krug K, Petralia F, Li Y, Liang WW, Reva B, Krek A, Ji J, Song X, Liu W, Hong R, Yao L, Blumenberg L, Savage SR, Wendl MC, Wen B, Li K, Tang LC, MacMullan MA, Avanessian SC, Kane MH, Newton CJ, Cornwell M, Kothadia RB, Ma W, Yoo S, Mannan R, Vats P, Kumar-Sinha C, Kawaler EA, Omelchenko T, Colaprico A, Geffen Y, Maruvka YE, da Veiga Leprevost F, Wiznerowicz M, Gümüş ZH, Veluswamy RR, Hostetter G, Heiman DI, Wyczalkowski MA, Hiltke T, Mesri M, Kinsinger CR, Boja ES, Omenn GS, Chinnaiyan AM, Rodriguez H, Li QK, Jewell SD, Thiagarajan M, Getz G, Zhang B, Fenyö D, Ruggles KV, Cieslik MP, Robles AI, Clauser KR, Govindan R, Wang P, Nesvizhskii AI, Ding L, Mani DR, Carr SA; Clinical Proteomic Tumor Analysis Consortium. Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma. Cell. 2020 Jul 9;182(1):200-225.e35. doi: 10.1016/j.cell.2020.06.013. PMID: 32649874; PMCID: PMC7373300. [Abstract]
  5. Graw S, Chappell K, Washam CL, Gies A, Bird J, Robeson MS 2nd, Byrum SD. Multi-omics data integration considerations and study design for biological systems and disease. Mol Omics. 2021 Apr 19;17(2):170-185. doi: 10.1039/d0mo00041h. PMID: 33347526; PMCID: PMC8058243. [Abstract]
  6. Gruszecka-Kosowska A, Ampatzoglou A, Aguilera M. Integration of Omics Approaches Enhances the Impact of Scientific Research in Environmental Applications. Int J Environ Res Public Health. 2022 Jul 19;19(14):8758. doi: 10.3390/ijerph19148758. PMID: 35886610; PMCID: PMC9317225. [Abstract]
  7. López de Maturana E, Alonso L, Alarcón P, Martín-Antoniano IA, Pineda S, Piorno L, Calle ML, Malats N. Challenges in the Integration of Omics and Non-Omics Data. Genes (Basel). 2019 Mar 20;10(3):238. doi: 10.3390/genes10030238. PMID: 30897838; PMCID: PMC6471713. [Abstract]
  8. Noble AJ, Purcell RV, Adams AT, Lam YK, Ring PM, Anderson JR, Osborne AJ. A Final Frontier in Environment-Genome Interactions? Integrated, Multi-Omic Approaches to Predictions of Non-Communicable Disease Risk. Front Genet. 2022 Feb 8;13:831866. doi: 10.3389/fgene.2022.831866. PMID: 35211161; PMCID: PMC8861380. [Abstract]
  9. Price EJ, Vitale CM, Miller GW, David A, Barouki R, Audouze K, Walker DI, Antignac JP, Coumoul X, Bessonneau V, Klánová J. Merging the exposome into an integrated framework for "omics" sciences. iScience. 2022 Feb 24;25(3):103976. doi: 10.1016/j.isci.2022.103976. PMID: 35310334; PMCID: PMC8924626. [Abstract]
  10. Ritchie MD, Holzinger ER, Li R, Pendergrass SA, Kim D. Methods of integrating data to uncover genotype-phenotype interactions. Nat Rev Genet. 2015 Feb;16(2):85-97. doi: 10.1038/nrg3868. Epub 2015 Jan 13. PMID: 25582081. [Abstract]
  11. Tarazona S, Arzalluz-Luque A, Conesa A. Undisclosed, unmet and neglected challenges in multi-omics studies. Nat Comput Sci. 2021 Jun;1(6):395-402. doi: 10.1038/s43588-021-00086-z. Epub 2021 Jun 21. PMID: 38217236. [Abstract]
  12. Xiao Y, Bi M, Guo H, Li M. Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis. EBioMedicine. 2022 May;79:104001. doi: 10.1016/j.ebiom.2022.104001. Epub 2022 Apr 16. PMID: 35439677; PMCID: PMC9035645. [Abstract]
  13. Shah RV, Steffen LM, Nayor M, Reis JP, Jacobs DR, Allen NB, Lloyd-Jones D, Meyer K, Cole J, Piaggi P, Vasan RS, Clish CB, Murthy VL. Dietary metabolic signatures and cardiometabolic risk. Eur Heart J. 2023 Feb 14;44(7):557-569. doi: 10.1093/eurheartj/ehac446. PMID: 36424694; PMCID: PMC10169425. [Abstract]
  14. Davies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ. 2018 Jul 12;362:k601. doi: 10.1136/bmj.k601. PMID: 30002074; PMCID: PMC6041728. [Abstract]
  15. Fang Z, Song M, Lee DH, Giovannucci EL. The Role of Mendelian Randomization Studies in Deciphering the Effect of Obesity on Cancer. J Natl Cancer Inst. 2022 Mar 8;114(3):361-371. doi: 10.1093/jnci/djab102. PMID: 34021349; PMCID: PMC8902442. [Abstract]
  16. Zeinomar N, Oskar S, Kehm RD, Sahebzeda S, Terry MB. Environmental exposures and breast cancer risk in the context of underlying susceptibility: A systematic review of the epidemiological literature. Environ Res. 2020 Aug;187:109346. doi: 10.1016/j.envres.2020.109346. Epub 2020 Mar 12. PMID: 32445942; PMCID: PMC7314105. [Abstract]
  17. Terry MB, Michels KB, Brody JG, Byrne C, Chen S, Jerry DJ, Malecki KMC, Martin MB, Miller RL, Neuhausen SL, Silk K, Trentham-Dietz A; Breast Cancer and the Environment Research Program (BCERP). Environmental exposures during windows of susceptibility for breast cancer: a framework for prevention research. Breast Cancer Res. 2019 Aug 20;21(1):96. doi: 10.1186/s13058-019-1168-2. PMID: 31429809; PMCID: PMC6701090. [Abstract]
  18. Hüls A, Czamara D. Methodological challenges in constructing DNA methylation risk scores. Epigenetics. 2020 Jan-Feb;15(1-2):1-11. doi: 10.1080/15592294.2019.1644879. Epub 2019 Jul 22. PMID: 31318318; PMCID: PMC6961658. [Abstract]
  19. Yalcin GD, Danisik N, Baygin RC, Acar A. Systems Biology and Experimental Model Systems of Cancer. J Pers Med. 2020 Oct 19;10(4):180. doi: 10.3390/jpm10040180. PMID: 33086677; PMCID: PMC7712848. [Abstract]
  20. Pfohl U, Pflaume A, Regenbrecht M, Finkler S, Graf Adelmann Q, Reinhard C, Regenbrecht CRA, Wedeken L. Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed. Cells. 2021 Apr 17;10(4):928. doi: 10.3390/cells10040928. PMID: 33920536; PMCID: PMC8072767. [Abstract]

 

Applications

  1. Kehm RD, Oskar S, Tehranifar P, Zeinomar N, Rundle AG, Herbstman JB, Perera F, Miller RL, Terry MB. Associations of prenatal exposure to polycyclic aromatic hydrocarbons with pubertal timing and body composition in adolescent girls: Implications for breast cancer risk. Environ Res. 2021 May;196:110369. doi: 10.1016/j.envres.2020.110369. Epub 2020 Oct 22. PMID: 33131678; PMCID: PMC8552520. [Abstract]
  2. Shen J, Liao Y, Hopper JL, Goldberg M, Santella RM, Terry MB. Dependence of cancer risk from environmental exposures on underlying genetic susceptibility: an illustration with polycyclic aromatic hydrocarbons and breast cancer. Br J Cancer. 2017 Apr 25;116(9):1229-1233. doi: 10.1038/bjc.2017.81. Epub 2017 Mar 28. PMID: 28350789; PMCID: PMC5418454. [Abstract]
  3. Peng C, Wang J, Asante I, Louie S, Jin R, Chatzi L, Casey G, Thomas DC, Conti DV. A latent unknown clustering integrating multi-omics data (LUCID) with phenotypic traits. Bioinformatics. 2020 Feb 1;36(3):842-850. doi: 10.1093/bioinformatics/btz667. PMID: 31504184; PMCID: PMC7986585. [Abstract]
  4. Dixon HM, Armstrong G, Barton M, Bergmann AJ, Bondy M, Halbleib ML, Hamilton W, Haynes E, Herbstman J, Hoffman P, Jepson P, Kile ML, Kincl L, Laurienti PJ, North P, Paulik LB, Petrosino J, Points GL 3rd, Poutasse CM, Rohlman D, Scott RP, Smith B, Tidwell LG, Walker C, Waters KM, Anderson KA. Discovery of common chemical exposures across three continents using silicone wristbands. R Soc Open Sci. 2019 Feb 6;6(2):181836. doi: 10.1098/rsos.181836. PMID: 30891293; PMCID: PMC6408398. [Abstract]
  5. Samon SM, Rohlman D, Tidwell LG, Hoffman PD, Oluyomi AO, Anderson KA. Associating Increased Chemical Exposure to Hurricane Harvey in a Longitudinal Panel Using Silicone Wristbands. Int J Environ Res Public Health. 2022 May 30;19(11):6670. doi: 10.3390/ijerph19116670. PMID: 35682254; PMCID: PMC9180596. [Abstract]
  6. Oluyomi AO, Panthagani K, Sotelo J, Gu X, Armstrong G, Luo DN, Hoffman KL, Rohlman D, Tidwell L, Hamilton WJ, Symanski E, Anderson K, Petrosino JF, Walker CL, Bondy M. Houston hurricane Harvey health (Houston-3H) study: assessment of allergic symptoms and stress after hurricane Harvey flooding. Environ Health. 2021 Jan 19;20(1):9. doi: 10.1186/s12940-021-00694-2. PMID: 33468146; PMCID: PMC7816385. [Abstract]
  7. Dutta D, He Y, Saha A, Arvanitis M, Battle A, Chatterjee N. Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood. Nat Commun. 2022 Jul 26;13(1):4323. doi: 10.1038/s41467-022-31845-9. PMID: 35882830; PMCID: PMC9325868. [Abstract]
  8. Boye C, Kalita CA, Findley AS, Alazizi A, Wei J, Wen X, Pique-Regi R, Luca F. Characterization of caffeine response regulatory variants in vascular endothelial cells. Elife. 2024 Feb 9;13:e85235. doi: 10.7554/eLife.85235. PMID: 38334359; PMCID: PMC10901511. [Abstract]
  9. Balmain A. The critical roles of somatic mutations and environmental tumor-promoting agents in cancer risk. Nat Genet. 2020 Nov;52(11):1139-1143. doi: 10.1038/s41588-020-00727-5. Epub 2020 Oct 26. PMID: 33106632; PMCID: PMC8360498. [Abstract]
  10. Bissell MJ, Hines WC. Why don't we get more cancer? A proposed role of the microenvironment in restraining cancer progression. Nat Med. 2011 Mar;17(3):320-9. doi: 10.1038/nm.2328. PMID: 21383745; PMCID: PMC3569482. [Abstract]
  11. Freedman AN, Eaves LA, Rager JE, Gavino-Lopez N, Smeester L, Bangma J, Santos HP, Joseph RM, Kuban KC, O'Shea TM, Fry RC. The placenta epigenome-brain axis: placental epigenomic and transcriptomic responses that preprogram cognitive impairment. Epigenomics. 2022 Aug;14(15):897-911. doi: 10.2217/epi-2022-0061. Epub 2022 Sep 8. PMID: 36073148; PMCID: PMC9475498. [Abstract]
  12. Santos HP Jr, Bhattacharya A, Joseph RM, Smeester L, Kuban KCK, Marsit CJ, O'Shea TM, Fry RC. Evidence for the placenta-brain axis: multi-omic kernel aggregation predicts intellectual and social impairment in children born extremely preterm. Mol Autism. 2020 Dec 11;11(1):97. doi: 10.1186/s13229-020-00402-w. PMID: 33308293; PMCID: PMC7730750. [Abstract]
  13. Caipa Garcia AL, Arlt VM, Phillips DH. Organoids for toxicology and genetic toxicology: applications with drugs and prospects for environmental carcinogenesis. Mutagenesis. 2022 May 4;37(2):143-154. doi: 10.1093/mutage/geab023. PMID: 34147034; PMCID: PMC9071088. [Abstract]
  14. Cao ZJ, Gao G. Multi-omics single-cell data integration and regulatory inference with graph-linked embedding. Nat Biotechnol. 2022 Oct;40(10):1458-1466. doi: 10.1038/s41587-022-01284-4. Epub 2022 May 2. PMID: 35501393; PMCID: PMC9546775. [Abstract]

 

Questions?

For questions about the workshop content, please contact Kimberly McAllister, Ph.D. or Leah Mechanic, Ph.D., M.P.H..