Joshua D. Campbell, PhD

Associate Professor, Boston University Chobanian & Avedisian School of Medicine

Biography

Computational biology and bioinformatics.
High-throughput genomic technologies are rapidly evolving including the areas of DNA and RNA sequencing. Novel types of complex data are being rapidly generated and require novel methods for quality control and analysis. We are currently focused on developing and/or applying methods for identifying genomic alterations in cancer, quantifying the mutagenic effect of carcinogens, and characterizing cellular heterogeneity using single cell RNA sequencing. We are applying these methods in the areas of lung cancer development and premalignancy as well as COPD pathogenesis as described below.

Identifying early drivers of lung cancer.
Lung adenocarcinomas and lung squamous cell carcinomas are the most common types of lung cancer and remain major causes of death worldwide despite advances in smoking cessation, early detection, and targeted and immunological therapies. Many patients have lung cancers that do not harbor a known activating mutation and therefore cannot be given targeted therapies. In collaboration with labs from Dana-Farber Cancer Institute, the Broad Institute, and The Cancer Genome Atlas (TCGA) consortium, we analyze next-generation sequencing data to identify novel drivers of lung tumorigenesis. Targeting these genes with novel therapies will hopefully lead to a reduction in overall lung cancer mortality. In collaboration with the Spira/Lenburg lab at BUSM, we are identifying the genomic alterations in premalignant lesions for squamous cell carcinoma with the ultimate goal of defining strategies for early detection.

Therapeutic development and pathogenesis of COPD.
Chronic Obstructive Pulmonary Disease (COPD) is the 4th leading cause of death in the world. Our understanding of the molecular mechanisms responsible for the initiation and progression of this disease are limited. By examining expression differences between individuals with and without COPD or differences within a person along a gradient of disease, we hope to elucidate the molecular mechanisms that responsible for disease initiation. Utilizing publicly available resources such as the Connectivity Map, we are also using gene expression data to predict novel therapeutics for the treatment of COPD.

Publications

  • Published 2/25/2025

    Soucy AM, Brune JE, Jayaraman A, Shenoy AT, Korkmaz FT, Etesami NS, Hiller BE, Martin IM, Goltry WN, Ha CT, Crossland NA, Campbell JD, Beach TG, Traber KE, Jones MR, Quinton LJ, Bosmann M, Frevert CW, Mizgerd JP. Transcriptomic responses of lung mesenchymal cells during pneumonia. JCI Insight. 2025 Feb 25; 10(7). PMID: 39998887.

    Read at: PubMed

  • Published 1/3/2025

    Bandyadka S, Lebo DPV, Mondragon AA, Serizier SB, Kwan J, Peterson JS, Chasse AY, Jenkins VK, Calikyan A, Ortega AJ, Campbell JD, Emili A, McCall K. Multi-modal comparison of molecular programs driving nurse cell death and clearance in Drosophila melanogaster oogenesis. PLoS Genet. 2025 Jan; 21(1):e1011220. PMID: 39752622.

    Read at: PubMed

  • Published 10/1/2024

    Faupel-Badger J, Kohaar I, Bahl M, Chan AT, Campbell JD, Ding L, De Marzo AM, Maitra A, Merrick DT, Hawk ET, Wistuba II, Ghobrial IM, Lippman SM, Lu KH, Lawler M, Kay NE, Tlsty TD, Rebbeck TR, Srivastava S. Defining precancer: a grand challenge for the cancer community. Nat Rev Cancer. 2024 Nov; 24(11):792-809. PMID: 39354069.

    Read at: PubMed

  • Published 8/1/2024

    Sarfraz I, Wang Y, Shastry A, Teh WK, Sokolov A, Herb BR, Creasy HH, Virshup I, Dries R, Degatano K, Mahurkar A, Schnell DJ, Madrigal P, Hilton J, Gehlenborg N, Tickle T, Campbell JD. MAMS: matrix and analysis metadata standards to facilitate harmonization and reproducibility of single-cell data. Genome Biol. 2024 Aug 01; 25(1):205. PMID: 39090672.

    Read at: PubMed

  • Published 7/31/2024

    Sun Y, Benmhammed H, Al Abdullatif S, Habara A, Fu E, Brady J, Williams C, Ilinski A, Sharma A, Mahdaviani K, Alekseyev YO, Campbell JD, Steinberg MH, Cui S. PGC-1a agonism induces fetal hemoglobin and exerts antisickling effects in sickle cell disease. Sci Adv. 2024 Aug 02; 10(31):eadn8750. PMID: 39083598.

    Read at: PubMed

Other Positions

  • Member, BU-BMC Cancer Center
    Boston University
  • Member, Evans Center for Interdisciplinary Biomedical Research
    Boston University
  • Member, Genome Science Institute
    Boston University

Education

  • Boston University, PhD
  • Anderson University, BS