Joshua D. Campbell, PhD
Associate Professor
Boston University Chobanian & Avedisian School of Medicine
Medicine
Computational Biomedicine

PhD, Boston University
BS, Anderson University

Pronouns: he/him/his



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.

Diversity, Equity, Inclusion and Accessibility

Our research group supports trainees from diverse and underrepresented groups by fostering career development experiences in preparation for an independent career in computational biology and biomedical research. We welcome all trainees including individuals who are first generation college students, LGBTQ+, disabled, or are from underrepresented/minoritized races and ethnicities. Our group values diversity of thought and perspective which can only be obtained by having representation from people with a wide range of experiences and backgrounds. We are specifically looking to train undergraduate and graduate students from minority groups in computational skills and techniques as they are vastly underrepresented in STEM fields.

We are also interested in understanding the mechanisms underlying health disparities in cancer. Some disease such as prostate cancer high higher incidence and mortality rates in African Americans compared to other populations. Many things contribute to this disparity including access to health care and other socioeconomic factors. Our group is determining if underlying biological differences in tumors from African Americans also contributes to cancer disparities. We are characterizing and comparing somatic mutational profiles and transcriptomic states of cancer cells from different ancestral backgrounds. These types of studies will be important for understanding when certain therapies may preferentially benefit African American patients who continue to remain underrepresented in clinical trials.

Member
Boston University
BU-BMC Cancer Center


Member
Boston University
Evans Center for Interdisciplinary Biomedical Research


Member
Boston University
Genome Science Institute




Investigating the mechanisms of driver genes associated with ancestry and aggressiveness in prostate cancer
05/10/2021 - 04/30/2026 (PI)
NIH/National Cancer Institute
5R01CA248920-03

Lung Pre-Cancer Atlas (PCA) Cohort Registry
01/01/2019 - 12/31/2024 (Multi-PI)
PI: Joshua D. Campbell, PhD
Johnson & Johnson


An Atlas of Human Prostate Across Ancestries to develop a comprehensive atlas of the human prostate at single-cell resolution with a community engagement plan to maximize impact for the public and cli
12/01/2021 - 11/30/2024 (Subcontract PI)
The Regents of the University of California Silicon Valley C Fdn


Utilizing Bayesian modeling to improve mutational signature inference in large-scale datasets (Restricted Holding Account for 50209293)
09/01/2023 - 08/31/2024 (PI)
NIH/National Cancer Institute
5U01CA253500-03

Utilizing Bayesian modeling to improve mutational signature inference in large-scale datasets
09/17/2021 - 08/31/2024 (Multi-PI)
PI: Joshua D. Campbell, PhD
NIH/National Cancer Institute
5U01CA253500-03

The Lung PCA: A Multi-Dimensional Atlas of Pulmonary Premalignancy
09/30/2018 - 08/31/2024 (Multi PI of Sub-Project / SP)
PI: Avrum Spira, MD
NIH/National Cancer Institute
3U2CCA233238-01S2

Integrative clustering of cells and samples using multi-modal single-cell data
08/01/2019 - 07/31/2024 (Multi-PI)
PI: Joshua D. Campbell, PhD
NIH/National Library of Medicine
5R01LM013154-03

Novel approaches to characterize the microenvironment of lung cancers and lymph nodes to improve overall staging and survival of cancer patients
01/01/2023 - 06/30/2024 (PI)
Johnson & Johnson Enterprise Innovation, Inc.


Robust, scalable, and accurate discovery of mutational signatures
09/20/2021 - 06/30/2024 (Multi-PI)
PI: Joshua D. Campbell, PhD
NIH/National Institute of General Medical Sciences
5R01GM144963-03

Methods and software for decontamination of single-cell data
07/01/2022 - 12/31/2023 (PI)
Silicon Valley Community Foundation


Showing 10 of 19 results. Show All Results


Title


Yr Title Project-Sub Proj Pubs

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

iCite Analysis       Copy PMIDs To Clipboard

  1. Yin Y, Yajima M, Campbell JD. Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro. Nucleic Acids Res. 2024 Jan 11; 52(1):e4. PMID: 37973397; PMCID: PMC10783508; DOI: 10.1093/nar/gkad1032;
     
  2. Chevalier A, Guo T, Gurevich NQ, Xu J, Yajima M, Campbell JD. Characterization of highly active mutational signatures in tumors from a large Chinese population. medRxiv. 2023 Nov 04. PMID: 37961450; PMCID: PMC10635259; DOI: 10.1101/2023.11.03.23297964;
     
  3. Pavel AB, Garrison C, Luo L, Liu G, Taub D, Xiao J, Juan-Guardela B, Tedrow J, Alekseyev YO, Yang IV, Geraci MW, Sciurba F, Schwartz DA, Kaminski N, Beane J, Spira A, Lenburg ME, Campbell JD. Integrative genetic and genomic networks identify microRNA associated with COPD and ILD. Sci Rep. 2023 Aug 11; 13(1):13076.View Related Profiles. PMID: 37567908; PMCID: PMC10421936; DOI: 10.1038/s41598-023-39751-w;
     
  4. Wang Y, Sarfraz I, Pervaiz N, Hong R, Koga Y, Akavoor V, Cao X, Alabdullatif S, Zaib SA, Wang Z, Jansen F, Yajima M, Johnson WE, Campbell JD. Interactive analysis of single-cell data using flexible workflows with SCTK2. Patterns (N Y). 2023 Aug 11; 4(8):100814. PMID: 37602214; PMCID: PMC10436054; DOI: 10.1016/j.patter.2023.100814;
     
  5. Wang Y, Sarfraz I, 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. Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data. bioRxiv. 2023 Mar 07.View Related Profiles. PMID: 36945543; PMCID: PMC10028847; DOI: 10.1101/2023.03.06.531314;
     
  6. Wang Y, Sarfraz I, 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. Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data. bioRxiv. 2023 Mar 07. PMID: 36945543; PMCID: PMC10028847; DOI: 10.1101/2023.03.06.531314;
     
  7. Yin Y, Yajima M, Campbell JD. Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro. bioRxiv. 2023 Feb 24. PMID: 36865227; PMCID: PMC9979990; DOI: 10.1101/2023.01.27.525964;
     
  8. Xu K, Shi X, Husted C, Hong R, Wang Y, Ning B, Sullivan TB, Rieger-Christ KM, Duan F, Marques H, Gower AC, Xiao X, Liu H, Liu G, Duclos G, Platt M, Spira AE, Mazzilli SA, Billatos E, Lenburg ME, Campbell JD, Beane JE. Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways. Sci Rep. 2022 Oct 28; 12(1):18168.View Related Profiles. PMID: 36307504; PMCID: PMC9615627; DOI: 10.1038/s41598-022-17832-6;
     
  9. Vittoria MA, Kingston N, Kotynkova K, Xia E, Hong R, Huang L, McDonald S, Tilston-Lunel A, Darp R, Campbell JD, Lang D, Xu X, Ceol CJ, Varelas X, Ganem NJ. Inactivation of the Hippo tumor suppressor pathway promotes melanoma. Nat Commun. 2022 Jun 29; 13(1):3732.View Related Profiles. PMID: 35768444; PMCID: PMC9243107; DOI: 10.1038/s41467-022-31399-w;
     
  10. Chaudhary N, Jayaraman A, Reinhardt C, Campbell JD, Bosmann M. A single-cell lung atlas of complement genes identifies the mesothelium and epithelium as prominent sources of extrahepatic complement proteins. Mucosal Immunol. 2022 May; 15(5):927-939.View Related Profiles. PMID: 35672453; PMCID: PMC9173662; DOI: 10.1038/s41385-022-00534-7;
     
Showing 10 of 38 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 37 publications over 13 distinct years, with a maximum of 5 publications in 2022 and 2023

YearPublications
20112
20122
20133
20144
20153
20162
20181
20192
20203
20214
20225
20235
20241


New Method Removes Background Noise from CITE-Seq Data

AZO Life Sciences 11/20/2023

BU researchers develop new method to help with analysis of single cell data

ScienMag 11/17/2023

Biological Differences in Prostate Cancers of African American and European American Men

Cancer Network 8/22/2020

Genomic Profiles of Prostate Cancers Differ Between Men of African and European Ancestry

Medscape 8/11/2020

African American, European Ancestry Men Benefit from Same Targeted Prostate Cancer Therapies

Clinical OMICs 7/13/2020

Analysis identifies genomic treatment targets in African American men with prostate cancer

Urology Times 7/13/2020
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