Biostatistics & Computational Biology Branch

Benedict N. Anchang, Ph.D.
Benedict N. Anchang, Ph.D.
Stadtman Investigator
Tel 984-287-3350
[email protected]
Curriculum Vitae (125KB)
P.O. Box 12233
Mail Drop A3-03
Durham, NC 27709

Research Summary

Benedict Anchang, MSc. Ph.D. is a Stadtman Tenure-Track Investigator in the Biostatistics and Computational Biology Branch. He also holds a joint appointment at the National Cancer Institute in Bethesda, Maryland. Computational biology brings order to our understanding of life, ensures the rigor and testability of biological concepts, and provides a reference map for individual insights. Anchang's Computational and Systems Biology Group performs multi-scale modeling, visualization, and integration of dynamic perturbation effects of complex biological processes, such as cancer, drug response and toxicity with personalized and precision health as a desired goal.

Most of Dr. Anchang’s past work focused on understanding cellular heterogeneity during normal cellular function and cancer development using mostly single-cell analysis, especially as it relates to the immune and reproductive systems. He is currently interested to improve understanding of how celltype-specific extracellular and intracellular receptors such as enzyme-linked receptors and glucocorticoid receptors are affected by drugs, endocrine disruptors, viruses, and environmental chemicals/agents. These disruptions are known to cause cancerous tumors, birth defects, neurological and other developmental disorders. Given the role of intratumor heterogeneity in drug resistance, drug combination optimization at the single-cell level is key for individualized therapy. He was able to address this computational challenge by developing a drug nested effects model (DRUG-NEM) on single-cell CyTOF drug perturbation data to examine drug combination effects that account for intratumor heterogeneity. He has also developed and published sophisticated computational tools, e.g., PHENOtypic STAte MaP (PHENOSTAMP) based on neural networks, Dynamic Spanning Forest mixtures (DSFMix) and Multiscale Multicellular Quantitative Evaluator (MMQE) to visualize protein and gene expression single-cell profiles at multiscale levels. These algorithms are particularly optimized for characterizing, benchmarking, and modeling normal and disease temporal biological processes in single-cell and multicellular systems.

Dr. Anchang recently received an award from the Chan Zuckerberg Initiative (CZI) as part of the Human Cell Atlas project to develop the first map of placental cells from women in different ethnic groups in Nigeria. The project will shed light on gene expression patterns during pregnancy and potentially reveal how genes, pathogens, age, ethnicity, and cultural activities affect fetal-maternal short and long-term health outcomes. This project will also allow Dr Anchang’s group to develop innovative, robust, and scalable methods for:

  • Visualizing and modelling temporal and spatial high-dimensional single-cell data.
  • Perturbation Network Analysis including optimizing drug response synergy in mixtures.
  • Integration of molecular and pathological features to differentiate between chemically-induced, adverse biological processes in neoplastic and non-neoplastic lesions.

Selected Publications

  1. Atitey K, Motsinger-Reif AA, Anchang B. 2023. Model-based evaluation of spatiotemporal data reduction methods with unknown ground truth through optimal visualization and interpretability metrics. Brief Bioinform. 25(1):bbad455. doi: 10.1093/bib/bbad455. [Abstract]
  2. Joy A, Aimola I, Hanneda FA, Samson RB, Kudan ZB, Abubakar HH, Kana M, and Anchang B. 2023. Non-Enzymatic Generation of Placenta Single Cells from Third Trimester Human Placenta. protocols.io. doi: 10.17504/protocols.io.yxmvm3b99l3p/v1. [Abstract]
  3. Anchang B, Mendez-Giraldez R, Xu X, Archer TK, Chen Q, Hu G, Plevritis SK, Motsinger-Reif AA, Li JL. 2022. Visualization, Benchmarking and Characterization of Nested Single-cell Heterogeneity as Dynamic Forest Mixtures. Brief Bioinform. bbac017. doi: 10.1093/bib/bbac017. Epub ahead of print. PMID: 35192692. [Abstract Anchang B, Mendez-Giraldez R, Xu X, Archer TK, Chen Q, Hu G, Plevritis SK, Motsinger-Reif AA, Li JL. 2022. Visualization, Benchmarking and Characterization of Nested Single-cell Heterogeneity as Dynamic Forest Mixtures. Brief Bioinform. 2022 Feb 22:bbac017. doi: 10.1093/bib/bbac017. Epub ahead of print. PMID: 35192692.]
  4. Atitey K, Anchang B. 2022. Mathematical Modeling of Proliferative Immune Response Initiated by Interactions Between Classical Antigen-Presenting Cells Under Joint Antagonistic IL-2 and IL-4 Signaling. Front. Mol. Biosci. 9:777390. [Abstract Atitey K, Anchang B. 2022. Mathematical Modeling of Proliferative Immune Response Initiated by Interactions Between Classical Antigen-Presenting Cells Under Joint Antagonistic IL-2 and IL-4 Signaling. Front. Mol. Biosci. 9:777390.]
  5. Bushel P R, Ward J, Burkholder A, Jianying Li, Anchang B. 2022. Mitochondrial-nuclear epistasis underlying phenotypic variation in breast cancer pathology. Sci Rep 12, 1393. [Abstract Bushel P R, Ward J, Burkholder A, Jianying Li, Anchang B. 2022. Mitochondrial-nuclear epistasis underlying phenotypic variation in breast cancer pathology. Sci Rep 12, 1393.]
  6. Rezaee M, Verde A, Anchang B, Mattonen SA, Garcia-Diaz J, Daldrup-Link H. 2022. Disparate participation by gender of conference attendants in scientific discussions. PLoS ONE 17(1): e0262639. [Abstract Rezaee M, Verde A, Anchang B, Mattonen SA, Garcia-Diaz J, Daldrup-Link H. 2022. Disparate participation by gender of conference attendants in scientific discussions. PLoS ONE 17(1): e0262639.]
  7. Green AJ, Anchang B, Akhtari FS, Reif DM, Motsinger-Reif A. 2021. Extending the lymphoblastoid cell line model for drug combination pharmacogenomics. Pharmacogenomics. Jun. 22(9):543-551. doi:10.2217/pgs-2020-0160. Epub 2021 May 28. PMID: 34044623. [Abstract Green AJ, Anchang B, Akhtari FS, Reif DM, Motsinger-Reif A. 2021. Extending the lymphoblastoid cell line model for drug combination pharmacogenomics. Pharmacogenomics. Jun. 22(9):543-551. doi:10.2217/pgs-2020-0160. Epub 2021 May 28. PMID: 34044623.]
  8. Salahudeen A, Choi S, Rustagi A, Zhu J, van Unen V, de la O S, Flynn R, Margalef-Català M, Santos A, Ju J, Batish A, Usui T, Zheng G, Edwards C, Wagar L, Luca V, Anchang B, Nagendran M, Nguyen K, Hart D, Terry J, Belgrader P, Ziraldo S, Mikkelsen T, Harbury P, Glenn J, Garcia K, Davis M, Baric R, Sabatti C, Amieva M, Blish C, Desai T, Kuo C. 2020. Progenitor identification and SARS-CoV-2 infection in human distal lung organoids. Nature. Nov 25. doi: 10.1038/s41586-020-3014-1. [Abstract Salahudeen A, Choi S, Rustagi A, Zhu J, van Unen V, de la O S, Flynn R, Margalef-Català M, Santos A, Ju J, Batish A, Usui T, Zheng G, Edwards C, Wagar L, Luca V, Anchang B, Nagendran M, Nguyen K, Hart D, Terry J, Belgrader P, Ziraldo S, Mikkelsen T, Harbury P, Glenn J, Garcia K, Davis M, Baric R, Sabatti C, Amieva M, Blish C, Desai T, Kuo C. 2020. Progenitor identification and SARS-CoV-2 infection in human distal lung organoids. Nature. Nov 25. doi: 10.1038/s41586-020-3014-1.]
  9. Karacosta LG, Anchang B, Ignatiadis N, Kimmey SC, Benson JA, Shrager JB, Tibshirani R, Bendall SC, Plevritis SK. 2019. Mapping Lung Cancer Epithelial-mesenchymal Transition States and Trajectories With Single-cell Resolution. Nature Communications 10, 5587 doi:10.1038/s41467-019-13441-6. [Abstract Karacosta LG, Anchang B, Ignatiadis N, Kimmey SC, Benson JA, Shrager JB, Tibshirani R, Bendall SC, Plevritis SK. 2019. Mapping Lung Cancer Epithelial-mesenchymal Transition States and Trajectories With Single-cell Resolution. Nature Communications 10, 5587 doi:10.1038/s41467-019-13441-6.]
  10. Menden MP, Wang D, Mason MJ, Szalai B, Bulusu KC, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslaskiy M, AstraZeneca-Sanger Drug Combination DREAM Consortium, Jang IS, Ghazoui Z, Ahsen ME, Vogel R, Neto EC, Norman T, Tang EKY, Garnett MJ, Veroli GYD, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J. 2019. Community Assessment to Advance Computational Prediction of Cancer Drug Combinations in a Pharmacogenomic Screen. Nature Communications 10(1):2674. [Abstract Menden MP, Wang D, Mason MJ, Szalai B, Bulusu KC, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslaskiy M, AstraZeneca-Sanger Drug Combination DREAM Consortium, Jang IS, Ghazoui Z, Ahsen ME, Vogel R, Neto EC, Norman T, Tang EKY, Garnett MJ, Veroli GYD, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J. 2019. Community Assessment to Advance Computational Prediction of Cancer Drug Combinations in a Pharmacogenomic Screen. Nature Communications 10(1):2674.]
  11. Anchang B, Davis KL, Fienberg HG, Williamson BD, Bendall SC, Karacosta LG, Tibshirani R, Nolan GP, Plevritis SK. 2018. DRUG-NEM: Optimizing Drug Combinations Using Single-cell Perturbation Response to Account for Intratumoral Heterogeneity. Proceedings of the National Academy of Sciences of the USA 115(18):E4294-E4303. [Abstract Anchang B, Davis KL, Fienberg HG, Williamson BD, Bendall SC, Karacosta LG, Tibshirani R, Nolan GP, Plevritis SK. 2018. DRUG-NEM: Optimizing Drug Combinations Using Single-cell Perturbation Response to Account for Intratumoral Heterogeneity. Proceedings of the National Academy of Sciences of the USA 115(18):E4294-E4303.]
  12. Yan KS, Gevaert O, Zheng GXY, Anchang B, Probert CS, Larkin KA, Davies PS, Cheng ZF, Kaddis JS, Han A, Roelf K, Calderon RI, Cynn E, Hu X, Mandleywala K, Wilhelmy J, Grimes SM, Corney DC, Boutet SC, Terry JM, Belgrader P, Ziraldo SB, Mikkelsen TS, Wang F, von Furstenberg RJ, Smith NR, Chandrakesan P, May R, Chrissy MAS, Jain R, Cartwright CA, Niland JC, Hong YK, Carrington J, Breault DT, Epstein J, Houchen CW, Lynch JP, Martin MG, Plevritis SK, Curtis C, Ji HP, Li L, Henning SJ, Wong MH, Kuo CJ. 2017. Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity. Cell Stem Cell 21(1):78-90.e6. [Abstract Yan KS, Gevaert O, Zheng GXY, Anchang B, Probert CS, Larkin KA, Davies PS, Cheng ZF, Kaddis JS, Han A, Roelf K, Calderon RI, Cynn E, Hu X, Mandleywala K, Wilhelmy J, Grimes SM, Corney DC, Boutet SC, Terry JM, Belgrader P, Ziraldo SB, Mikkelsen TS, Wang F, von Furstenberg RJ, Smith NR, Chandrakesan P, May R, Chrissy MAS, Jain R, Cartwright CA, Niland JC, Hong YK, Carrington J, Breault DT, Epstein J, Houchen CW, Lynch JP, Martin MG, Plevritis SK, Curtis C, Ji HP, Li L, Henning SJ, Wong MH, Kuo CJ. 2017. Intestinal Enteroendocrine Lineage Cells Possess Homeostatic and Injury-Inducible Stem Cell Activity. Cell Stem Cell 21(1):78-90.e6.]
  13. Anchang B, Sylvia K. Plevritis. Systems and Methods for Targeted Therapy Based on Single-Cell Stimulus Perturbation Response. Patent, PCT/US2017/026243, 12/10/2017.
  14. Anchang B, Hart TD, Bendall SC, Qiu P, Bjornson Z, Linderman M, Nolan GP, Plevritis SK. 2016. Visualization and Cellular Hierarchy Inference of Single-cell Data Using SPADE. Nature Protocols 11(7):1264-1279. [Abstract Anchang B, Hart TD, Bendall SC, Qiu P, Bjornson Z, Linderman M, Nolan GP, Plevritis SK. 2016. Visualization and Cellular Hierarchy Inference of Single-cell Data Using SPADE. Nature Protocols 11(7):1264-1279.]
  15. Kearney AY, Anchang B, Plevritis S, Felsher DW. 2015. ARF: Connecting Senescence and Innate Immunity for Clearance. Aging (Albany NY) 7(9):613-615. [Abstract Kearney AY, Anchang B, Plevritis S, Felsher DW. 2015. ARF: Connecting Senescence and Innate Immunity for Clearance. Aging (Albany NY) 7(9):613-615.]
  16. Yetil A, Anchang B, Gouw AM, Adam SJ, Zabuawala T, Parameswaran R, van Riggelen J, Plevritis S, Felsher DW. 2015. p19ARF Is a Critical Mediator of Both Cellular Senescence and an Innate Immune Response Associated with Myc Inactivation in Mouse Model of Acute Leukemia. Oncotarget 6(6):3563-3577. [Abstract Yetil A, Anchang B, Gouw AM, Adam SJ, Zabuawala T, Parameswaran R, van Riggelen J, Plevritis S, Felsher DW. 2015. p19ARF Is a Critical Mediator of Both Cellular Senescence and an Innate Immune Response Associated with Myc Inactivation in Mouse Model of Acute Leukemia. Oncotarget 6(6):3563-3577.]
  17. Anchang B, Do MT, Zhao X, Plevritis SK. 2014. CCAST: A Model-based Gating Strategy to Isolate Homogeneous Subpopulations in a Heterogeneous Population of Single Cells. PLoS Computational Biology 10(7): e1003664. [Abstract Anchang B, Do MT, Zhao X, Plevritis SK. 2014. CCAST: A Model-based Gating Strategy to Isolate Homogeneous Subpopulations in a Heterogeneous Population of Single Cells. PLoS Computational Biology 10(7): e1003664.]
  18. Dümcke S, Bräuer J, Anchang B, Spang R, Beerenwinkel N, Tresch A. 2014. Exact Likelihood Computation in Boolean Networks with Probabilistic Time Delays, and Its Application in Signal Network Reconstruction. Bioinformatics 30(3):414-419. [Abstract Dümcke S, Bräuer J, Anchang B, Spang R, Beerenwinkel N, Tresch A. 2014. Exact Likelihood Computation in Boolean Networks with Probabilistic Time Delays, and Its Application in Signal Network Reconstruction. Bioinformatics 30(3):414-419.]
  19. Voloshanenko O, Erdmann G, Dubash TD, Augustin I, Metzig M, Moffa G, Hundsrucker C, Kerr G, Sandmann T, Anchang B, Demir K, Boehm C, Leible S, Ball CR, Glimm H, Spang R, Boutros M. 2013. Wnt Secretion Is Required to Maintain High Levels of Wnt Activity in Colon Cancer Cells. Nature Communications; doi: 10.1038/ncomms3610 [Online 28 October 2013]. [Abstract Voloshanenko O, Erdmann G, Dubash TD, Augustin I, Metzig M, Moffa G, Hundsrucker C, Kerr G, Sandmann T, Anchang B, Demir K, Boehm C, Leible S, Ball CR, Glimm H, Spang R, Boutros M. 2013. Wnt Secretion Is Required to Maintain High Levels of Wnt Activity in Colon Cancer Cells. Nature Communications; doi: 10.1038/ncomms3610 [Online 28 October 2013].]
  20. Anchang B, Sadeh MJ, Jacob J, Tresch A, Vlad MO, Oefner PJ, Spang R. 2009. Modeling the Temporal Interplay of Molecular Signaling and Gene Expression by Using Dynamic Nested Effects Models. Proceedings of the National Academy of Sciences of the USA 106(16):6447-6452. [Abstract Anchang B, Sadeh MJ, Jacob J, Tresch A, Vlad MO, Oefner PJ, Spang R. 2009. Modeling the Temporal Interplay of Molecular Signaling and Gene Expression by Using Dynamic Nested Effects Models. Proceedings of the National Academy of Sciences of the USA 106(16):6447-6452.]