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Biostatistics & Computational Biology Branch

Benedict N. Anchang, M.Sc., Ph.D.
Benedict N. Anchang, M.Sc., Ph.D.
Stadtman Investigator
Tel 984-287-3350
[email protected]
NIH Intramural Profile Benedict N. Anchang, M.Sc., Ph.D.
P.O. Box 12233
Mail Drop A3-03
Durham, NC 27709

Research Summary

Benedict Anchang, M.Sc. Ph.D. is a Stadtman Tenure-Track Investigator at the Biostatistics and Computational Biology Branch, with a joint appointment at the National Cancer Institute in Bethesda, Maryland. His research harnesses computational biology to bring clarity to the complexity of life, ensuring rigor in biological insights and building reference maps for understanding individual health and disease variability.

The Computational and Systems Biology Group, led by Dr. Anchang, focuses on multi-scale modeling, visualization, and integration of dynamic perturbation effects in complex biological systems. His work spans cancer biology, immune responses, drug interactions, environmental exposures, and reproductive health, all aimed at advancing personalized and precision medicine.

Dr. Anchang’s earlier research emphasized cellular heterogeneity in normal physiology and cancer, with particular focus on the immune and reproductive systems. He is now expanding this framework to investigate how extracellular and intracellular receptors such as enzyme-linked receptors and glucocorticoid receptors, respond to various perturbations from drugs, endocrine-disrupting chemicals (EDCs), viruses, and environmental agents. These disruptions contribute to diseases including cancers, birth defects, neurological disorders, and developmental abnormalities.

Recognizing that intratumor heterogeneity drives drug resistance, Dr. Anchang developed DRUG-NEM, a computational approach leveraging single-cell CyTOF drug perturbation data to optimize drug combinations at the cellular level. This method models drug effects while accounting for tumor complexity, paving the way for individualized therapies.

Currently, his research also explores how ancestry, maternal age, and environmental exposures (like tobacco smoke, industrial chemicals, and endocrine disruptors) shape placental function and pregnancy outcomes. In breast cancer and asthma, he investigates how EDCs can modulate the transcriptional response to drugs such as dexamethasone, potentially enhancing or suppressing therapeutic effects.

In cancer progression, his team is building digital twin models that incorporate genetic, epigenetic, and microenvironmental data, aiming to predict tumor evolution and treatment response. Special attention is given to breast cancer, as well as maternal and fetal health, using placenta research to understand how environmental factors drive genomic instability and influence disease susceptibility. These models integrate high-resolution single-cell and spatial sequencing data to better understand maternal-fetal immune dynamics and improve patient-specific predictions.

Dr. Anchang's long-term vision is to integrate dynamic modeling and comprehensive data integration to create full-scale digital twins of biological systems, simulating immune system behavior and cancer driver dynamics to advance prevention, early diagnosis, and precision treatment. He was recently awarded two grants from the Chan Zuckerberg Initiative (CZI) through the Human Cell Atlas project: one to build a single-cell atlas of placental development during pregnancy to improve birth outcomes across diverse ancestries and exposures, and another to investigate spatiotemporal interactions between maternal blood and the placenta throughout pregnancy in diverse populations.

Software Packages

The group actively develops open-source computational tools to empower the broader scientific community in the analysis of complex biological data. These tools are applicable across multiple biological contexts, from cancer research to developmental biology.

Spatiotemporal Modeling and Visualization

  • DSFMix (Dynamic Spanning Forest Mixture) 
    Extension of the popular SPADE algorithm to enhance hierarchical clustering and phenotypic discovery in scRNA-seq and flow cytometry data. DSFMix improves dynamic phenotypic characterization and structure detection. 
    GitHub | SPADE Bioconductor | Cytobank SPADE
  • MIBCOVIS 
    Provides a unified benchmarking framework for optimizing and comparing data reduction methods, facilitating the dynamic and spatial visualization of complex biological systems. 
    GitHub
  • GIBOOST 
    Enhances visualization and interpretation of high-dimensional data by integrating feature selection with boosting algorithms, improving insights into complex biological landscapes. 
    GitHub
  • Perturb-STNet 
    Models and visualizes perturbation effects in spatial and temporal interactions within complex disease microenvironments. Integrates mesh optimization and clustering to construct cell-type neighborhood graphs, offering insights into cellular communications and disease progression. 
    GitHub

Selected Publications

  1. Book chapter on decoding drug resistance at a single-cell level using systems-level approaches, Oxford University Press. Publication date in May 2025.
  2. Rachel Church R. Anchang B., Bennett BD, Bushel PR, Watkins PB. (2025). Blood Toxicogenomics Reveals Potential Biomarkers for Management of Idiosyncratic Drug-Induced Liver Injury. 2025, Frontiers in Genetics, section Toxicogenomics, 16:1524433. [Full Text]
  3. Artur Szałata, Andrew Benz [et al. Including Anchang B], "A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types." In Proceedings of the Thirty-eighth Conference on Neural Information Processing Systems Datasets and Benchmarks Track, 2024. OpenReview. [Abstract]
  4. Motsinger-Reif AA, Reif DM, Akhtari FS, House JS, Campbell CR, Messier KP, Fargo DC, Bowen TA, Nadadur SS, Schmitt CP, Pettibone KG, Balshaw DM, Lawler CP, Newton SA, Collman GW, Miller AK, Merrick BA, Cui Y, Anchang B, Harmon QE, McAllister KA, Woychik R. Gene-environment interactions within a precision environmental health framework. Cell Genom. 2024 Jul 10;4(7):100591. PMID: 38925123. PMCID: PMC8791930 [Abstract]
  5. Karacosta, L.G., Bhattacharyya, S., Stewart, A., Victorian, A., Lujan, E.F., Ehsan, S., Kim, S., Duarte, A., Wang, R., Anchang, B. and Wang, J., 2024. Abstract PR005: Leveraging mass cytometry for phenotyping CTCs in SCLC liquid biopsies: Tracking therapy resistance at a personalized level. Clinical Cancer Research, 30(21_Supplement), pp.PR005-PR005. [Abstract]
  6. Hemberg, Martin, Federico Marini, Shila Ghazanfar, Ahmad Al Ajami, Najla Abassi, Benedict Anchang, Bérénice A. Benayoun et al. "Insights, opportunities and challenges provided by large cell atlases." arXiv preprint arXiv:2408.06563 (2024). [Abstract]
  7. 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]
  8. 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]
  9. 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.]
  10. Gabrielle Dewson, Benedict Anchang, Rosalie Sears, Daniel F. Liefwalker. Evasion of apoptosis in MYC dependent T-ALL through epigenetic control [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl): Abstract nr 825. [Abstract]
  11. 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.]
  12. 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.]
  13. 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.]
  14. 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.]
  15. 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.]
  16. 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.]
  17. 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.]
  18. 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.]
  19. 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.]
  20. 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.
  21. 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.]
  22. 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.]
  23. 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.]
  24. 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.]
  25. 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.]
  26. 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].]
  27. 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.]