About

Joshua D. Campbell is an Associate Professor in the Department of Medicine and the Faculty of Computing & Data Sciences at Boston University. He serves as the director of the Bioinformatics Program and is the co-scientific director of the Boston University Medical Campus Single Cell Sequencing core. His interdisciplinary research focuses on the intersection of data science and translational medicine, with particular emphasis on understanding human diseases such as cancer. Dr. Campbell's background includes postdoctoral work at the Dana-Farber Cancer Institute and the Broad Institute of Harvard and MIT, where he performed comprehensive genomic characterization of lung cancers within The Cancer Genome Atlas (TCGA) consortium and investigated somatic mutation differences across ancestral groups. His lab develops novel Bayesian methods and software for analyzing diverse biological data, including single-cell and spatial omics data, as well as mutational signatures in cancer. In collaboration with clinical and experimental colleagues, his group conducts translational research by generating multi-omic datasets from patient samples at Boston Medical Center to facilitate new discoveries.

Research topics

• Biology
• Genetics
• Computational biology
• Computer Science
• Medicine
• Pathology
• Data Mining
• Artificial Intelligence
• Bioinformatics
• Virology
• Immunology
• Cancer research
• Mathematics
• Database
• Internal medicine
• Oncology
• Chemistry
• Cell biology
• World Wide Web

Selected publications

• The evolving role of the immune microenvironment of tumor draining lymph nodes in the development of biomarkers of non-small cell lung cancer

  Frontiers in Oncology · 2026-05-15

  articleOpen access

  Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality, and a substantial fraction of patients with resected early-stage disease experience recurrence despite curative-intent surgery. Current pathologic staging does not completely capture the biological heterogeneity that supports metastasis and drives relapse in node-negative patients. Development of robust prognostic and predictive biomarkers are needed to predict which early-stage patients are likely to progress and require additional treatment. Increasing evidence indicates that antitumor immunity is a major determinant of clinical outcome and therapeutic responsiveness. This is particularly relevant in the era of neoadjuvant, adjuvant, and perioperative immune checkpoint blockade where harnessing the potential antitumor properties of the immune system is essential. While most biomarker efforts have focused on the primary tumor alone, antitumor immune responses are orchestrated across multiple compartments, including tumor-surrounding lymph nodes, where antigen presentation, germinal center reactions including T and B cell priming and memory formation occur contributing to immunologic remodeling that can precede overt metastasis. Here, we review the cellular, transcriptional, and spatial architecture of the tumor–immune microenvironment (TIME) and lymph node immune microenvironment (LIME) in human NSCLC, emphasizing how immune cell composition, cell state, clonal dynamics, and spatial organization influence progression, recurrence risk, and response to immunomodulatory therapies. This review highlights the current technical and translational advantages and limitations of multimodal single cell technologies and discuss potential directions for early-stage NSCLC staging and optimizing therapy timing through leveraging TIME–LIME assessment utilizing multimodal technologies.

  PublisherDOI

• Figure S11 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S11. Analysis of IMC data from the non-epithelial tissue.</p>

  PublisherDOI

• Figure S1 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S1. Correlation between GSVA scores of miRNAs and gene modules from the miRNA-gene network.</p>

  PublisherDOI

• Figure S4 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S4. Expression of hsa-miR-149-5p was up-regulated and expression of <i>NLRC5</i> was downregulated in LUSC tumor compared to adjacent benign tissue.</p>

  PublisherDOI

• Figure S10 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S10. Analysis of IMC data from the epithelial tissue.</p>

  PublisherDOI

• PGC-1α Agonism via Oral Administration of ZLN005 Induces Fetal Hemoglobin and is Anti-Sickling in Sickle Mice

  Blood Advances · 2026-04-23

  articleOpen access

  Sickle cell disease (SCD) caused by a point mutation in the β-globin gene results in the production of sickle hemoglobin (HbS). DeoxyHbS polymerizes, deforming red blood cells (RBCs) and leading to a cascade of clinical complications, including vaso-occlusion, hemolysis, inflammation, and progressive organ damage. An effective strategy to mitigate disease severity is the reactivation of fetal hemoglobin (HbF), which interferes with HbS polymerization. We explored the therapeutic potential of ZLN005, a small-molecule activator of the transcriptional coactivator PGC-1α, by evaluating its impact on HbF induction in CD34⁺ hematopoietic progenitor cells derived from SCD patients, in β-YAC transgenic mice carrying a normal human β-globin gene cluster, and in SCD mice. ZLN005 increased γ-globin expression and F-cells without impairing erythroid differentiation of CD34+ cells. Oral administration of ZLN005 to sickle mice increased F-cells, reduced sickled RBCs, increased hemoglobin levels, lowered reticulocyte counts, and decreased sickle cell-related spleen and liver pathology. ZLN005 or related compounds could represent a promising new class of orally available HbF-inducing therapeutics.

  PublisherDOI

• Figure S12 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S12. Representative IMC images.</p>

  PublisherDOI

• Figure 4 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>hsa-miR-149-5p is highly expressed within the epithelium and associates with PML progression. <b>A,</b> Bubble plot showing the correlation between the residual expression level of hsa-miR-149-5p and cell type marker genes, including <i>CD3G</i> (T cells), <i>CD19</i> (B cells), <i>CD68</i> (macrophages), <i>KRT5</i> (basal cells), <i>FOXJ1</i> (ciliated cells), <i>MUC5AC</i> (goblet cells), <i>SCGB1A1</i> (club cells), <i>MUC5B</i> (secretory cells), and <i>CEACAM5</i> (peri-goblet cells). Correlation results for hsa-miR-34b-5p, hsa-miR-449c-5p, and hsa-miR-150-5p are shown as controls. <b>B,</b> Enrichment of hsa-miR-149-5p across cell type compartments in the FANTOM5 project. Bar chart shows the normalized expression levels of hsa-miR-149-5p in the FANTOM5 samples (<i>n</i> = 399) (top). Vertical bars indicate the position of FANTOM5 samples derived from the epithelial (red) or immune (orange) cell compartments (bottom). <b>C,</b> Scatter plot of the Pearson correlation between the normalized expression levels of hsa-miR-149-5p and <i>NLRC5</i> within the FANTOM5 samples derived from the epithelial cell compartment (<i>n</i> = 87). The dashed red line represents the linear regression fit and the shaded region indicates the 95% confidence interval. <b>D–F,</b> The hsa-miR-149-5p density was detected by miRNA-ISH from proliferative-subtype PMLs (<i>n</i> = 19; 10 progressive/persistent and nine regressive). <b>D,</b> Boxplot showing the hsa-miR-149-5p density per area between the epithelium and nonepithelium regions. <b>E,</b> hsa-miR-149-5p density per nucleus between the progressive/persistent and regressive PMLs within regions of normal epithelium, regions with hyperplasia or metaplasia (hyper-metaplasia), and regions of bronchial dysplasia. <b>F,</b> Representative miRNA-ISH staining of hsa-miR-149-5p for progressive/persistent PMLs (top) and regressive PMLs (bottom). Arrows indicate stained hsa-miR-149-5p within epithelium. Boxplots indicate median with IQR and whiskers indicate minimum and maximum measurement in (<b>D</b>) and (<b>E</b>). <i>P</i> values were FDR (Benjamini and Hochberg) adjusted and determined by Pearson correlation coefficients (<b>A</b>), the two-sided paired Wilcoxon test (<b>D</b>), and a linear mixed-effects model (<b>E</b>). *, <i>P</i> ≤ 0.05; **, <i>P</i> ≤ 0.01; ***, <i>P</i> ≤ 0.001; ****, <i>P</i> ≤ 0.0001; ns, no significance.</p>

  PublisherDOI

• Figure S7 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S7. Performance of the hsa-miR-149-5p spot detection classifier.</p>

  PublisherDOI

• Figure S9 from Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions

  2026-04-02

  articleOpen access

  <p>Supplementary Figure S9. Identification of broad cell types in IMC data.</p>

  PublisherDOI

Recent grants

• Integrative clustering of cells and samples using multi-modal single-cell data

  NIH · $1.1M · 2019–2024

Frequent coauthors

• Avrum Spira

  Boston University

  140 shared

• Marc E. Lenburg

  Boston University

  128 shared

• Jennifer Beane

  Boston University

  88 shared

• Matthew Meyerson

  Dana-Farber Cancer Institute

  81 shared

• Gang Liu

  Boston University

  54 shared

• Andrew D. Cherniack

  52 shared

• Sarah A. Mazzilli

  Boston University

  49 shared

• Juliann Shih

  University of Nevada, Las Vegas

  47 shared

Education

• Ph.D. in Bioinformatics, Engineering

  Boston University

  2012

• Bachelor of Arts, Biology, Computer Science, Mathematics

  Anderson University

  2007