Research Interests
[NEWS] Our lab will move to Mayo Clinic in Florida starting Oct. 2021. Tae Hyun Hwang, PhD will hold an endowed chair position with the designation of Florida Department of Health Cancer Chair to build a nationally recognized program in Artificial Intelligence in Cancer at Mayo Clinic Florida! New positions for AI/Data Scientists and Bioinformatician are available and please send an email to us.
We focus on advancing the understanding of complex biological systems through the innovative use of artificial intelligence (AI), machine learning, and computational methods, combined with experimental approaches. Our interdisciplinary research encompasses spatial biology, single-cell biology, digital pathology, biomarker discovery, and therapeutic development, including novel immunotherapy and cellular therapy strategies. A key aspect of our research is the creation and analysis of subcellular-resolution 3D tumor atlas models, which enable us to gain unprecedented insights into the tumor immune microenvironment (TIME) and its role in various cancer types. This comprehensive approach allows us to investigate the intricate relationships between cellular and molecular components, ultimately guiding the identification of novel biomarkers and personalized therapeutic interventions.
The followings are the areas that our group are actively working:
AI and Machine Learning-driven Spatial Biology and Single-Cell Analysis: We develop and apply cutting-edge AI, machine learning, and computational techniques to decode the spatial organization of cells, tissues, and organs, as well as to characterize individual cell states and their interactions within the tumor immune microenvironment. We also use experimental methods to validate our computational findings, generating high-resolution molecular and phenotypic maps of complex biological systems to unravel the mechanisms underlying cellular heterogeneity, tissue organization, and disease progression.
Subcellular-Resolution 3D Tumor Atlas Models empowered by AI and Machine Learning algorithms: We harness the power of advanced imaging technologies, AI, machine learning, and computational methods to create subcellular-resolution 3D tumor atlas models for in-depth analysis of the tumor immune microenvironment (TIME) in pancreatic cancer. This approach enables us to investigate the complex interplay between cellular and molecular components, offering unprecedented insights into treatment resistance mechanisms. Our research in this area focuses on developing robust AI and ML algorithms and computational tools to identify novel biomarkers, predict patient outcomes, and guide personalized therapeutic interventions using 3D Tumor Atlas Models.
Therapeutic Development, Immunotherapy, and Cellular Therapy:: Our lab is committed to designing and optimizing innovative therapeutic strategies, including novel immunotherapies and cellular therapies, to combat a wide range of diseases, such as cancer and autoimmune disorders. We leverage AI, machine learning, and computational modeling, along with experimental validation, to identify potential drug targets, predict therapeutic responses, and guide the rational design of personalized treatment regimens targeting the tumor immune microenvironment. Our work also includes developing and refining cellular therapy approaches, such as chimeric antigen receptor (CAR) T cell therapy, to enhance their efficacy and minimize their toxicity.
By synergistically combining state-of-the-art AI, machine learning, computational approaches, experimental methodologies, and subcellular-resolution 3D tumor atlas models, the Hwang Lab strives to unravel the complex mechanisms governing health and disease, with a particular focus on the tumor immune microenvironment, ultimately driving innovations in personalized medicine and therapeutic development.
Talks!
News!
03/15/2023: Our work made Clinical Cancer Research’s March 15th edition COVER image “ACTA2 expression predicts survival and is associated with response to immune checkpoint inhibitors in gastric cancer”
03/07/2023: We are honored to receive a fund from Eric and Wendy Schmidt Foundation to improve immunotherapy efficacy in Gastric Cancer. This is a great accomplishment and a testament to the importance and impact of our lab’s research. Big congrats to Hwang lab members!
03/06/2023: Our collaborative work with Dr. Koga from Mayo Clinic to identify neurodegenerative disorders “Diagnosis of Alzheimer’s Disease and Tauopathies on Whole Slide Histopathology Images Using a Weakly Supervised Deep Learning Algorithm” is accepted in Laboratory Investigation.
02/08/2023: Our work to identify biomarkers that predict overall survival (OS) and response to immune checkpoint inhibitors (ICI) for patients with gastric cancer “ACTA2 expression predicts survival and is associated with response to immune checkpoint inhibitors in gastric cancer” is accepted in Clinical Cancer Research.
02/02/2023: [AACR 2023] Thrilled to share that six abstracts are accepted at AACR 2023 this April!
07/16/2022: Tae Hyun Hwang, PhD is invited to serve National Cancer Institute Gastric and Esophageal Cancers Subgroup on Multi-Omics Technology. He will provide insights into what is needed to advance Gastric and Esophageal Cancer prevention, diagnosis, and treatment, in particular the role of multi-comics technology in GE cancer, and help to identify the most promising translational research opportunities to ultimately help patients with GE cancers.
06/16/2022: Our work to identify TIGIT as predictive biomarker and potential therapeutic target to improve CD19 CAR-T cell therapy efficacy “Sequential Single-Cell Transcriptional and Protein Marker Profiling Reveals TIGIT as a Marker of CD19 CAR-T Cell Dysfunction in Patients with Non-Hodgkin Lymphoma” is accepted in Cancer Discovery. This is the first study show how TIGIT drives CAR-T cell dysfunction in Lymphoma and could be used as a therapeutic target to improve the efficacy of CD19 CAR-T cell treatment. We used large scale single cell sequencing from pre and post-infusion CAR-T cells empowered our own computational apporaches to investigate mechanisms of resistance to CD19 CAR-T cell therapy in Lymphoma.
05/21/2022: Our work to study spatial heterogeneity and organization of Tumor Mutation Burden (TMB) and Tumor Infiltrate Lymphocytes (TILs) as prognostic biomarker in bladder cancer “Spatial heterogeneity and organization of tumor mutation burden with immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer” is accepted in Journal of Pathology Informatics. This is the first study to explore spatial heterogeneity of TMB and their co-localization with TILs within tumors. Our findings suggest that tumors with less spatial TMB heterogeneity with high TILs show better overall survival. This indicates that not just patient level TMB and/or TILs important but also spatial TMB and TILs co-organization could further stratify patients with distinct survival outcome in Bladder Cancer.
04/28/2022: Our work about spatial analysis of Tumor Infiltrate Lymphocytes (TILs) based on H&E images to develop AI-based immune score “Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma” is accepted in the Journal of Pathology: Clinical Research. This is the first study to develop AI-based immune score based on H&E images in Colorectal Cancer. Our findings show that AI-based immune score combined with human TILs quantification further improve patient’s prognostication in Colorectal Cancer.
03/07/2022: Our collaborative work with Dr. Sam Wang from U of Texas Southwestern Medical Center “Lenvatinib inhibits the growth of gastric cancer patient-derived xenografts generated from a heterogeneous population” is accepted in Journal of Translational Medicine. This work shows the use of Patient-derived xenografts (PDX) by engrafting human tumors into immunodeficient mice to evaluate an efficacy of lenvatinib monotherapy.
03/05/2022: Our work to study microbiome and host-gene interaction in tumor immune microenvironment in stomach cancer “Multi-omics Reveals Microbiome, Host Gene Expression, and Immune Landscape in Gastric Carcinogenesis” is accepted in iScience. This is the first study how micro-organisms in addition to Helicobacter pylori could impact tumor immune microenvironment to develop gastritis and gastric cancer. Our findings indicate that micro-organisms in stomach could play important roles for immune invasion and development of gastric cancer.
02/28/2022: [AACR 2022] Happy to share that one oral presentation and four posters of AI and machine learning approaches utilizing digital pathology, single cell, microbiome, tissue immune microenvironment to predict patients’ prognosis and clinical outcome including immunotherapy respsone in blood and solid tumor are accepted at AACR 2022!
02/08/2022: Our machine learning approaches to predict chemotherapy and immunotherapy response in stomach cancer, “Development and validation of a prognostic and predictive 32-gene signature for gastric cancer" is published in Nature Communication 2022. This is the first signature to select chemotherapy and immunotherapy response and resistant patients as well as risk stratification in stomach cancer.
08/03/2021: Our mini review article “Machine Learning and Artificial Intelligence–driven Spatial Analysis of the Tumor Immune Microenvironment in Pathology Slides” is published inEuropean Urology Focus.
07/13/2021: Our collaborative research sponsored by NASA Specialized Center of Research on Radiation, “Associations between lipids in selected brain regions, plasma miRNA, and behavioral and cognitive measures following 28Si ion irradiation“, published in Scientific Report.
07/09/2021: Our collaborative single cell research with David Wald’s lab at Case Western Reserve University, “Single cell RNA sequencing of AML initiating cells reveals RNA-based evolution during disease progression” is published in Leukemia journal.
05/28/2021: Our ongoing projects for 1) Machine Learning and Deep Learning driven Spatial Tumor Immune Microenvironment analysis in Bladder Cancer and 2) Single cell approaches for AML biomarker discovery are selected as a long oral presentation (20mins) and poster presentation at ISMB/ECCB 2021 conference! Big congrats to Jean Clemenceau and Robert Schauner, our PhD students at CCLCM and Case Western Reserve University!
01/01/2021: Our post-doc researcher Hongming Xu PhD accepted an associate professor position in the department of Biomedical Engineering at Dalian University of Technology in China. Big congrats to Hongming and look forward to continue to work together!
12/03/2020: Our research to study spatial tumor and immune microenvironment using H&E image and spatial transcriptome for biomarker discovery related to immune checkpoint inhibitor in gastric cancer presented at 7th Digital Pathology & AI congress: USA and Europe!
11/06/2020: Our very talented the first year Cleveland College Lerner College of Medicine MD program student, Monica Nair, is featured at Cold Spring Harbor Laboratory Biodata 2020 meeting. Big congratulations Monica and very proud of you! https://currentexchange.cshl.edu/blog/2020/11/visitor-of-the-week-186
7/16/2020: Hwang team won NanoString GeoMX Cancer Transcriptome Atlas Grant to study tumor and immune microenvironment using spatial transcriptome to identify biomarker and build a predictive model for immune checkpoint inhibitor in gastric cancer.
4/24/2020: Our collaborative work with Ting Lab “DNA Methylation Regulates Alternative Polyadenylation via CTCF and the Cohesin Complex” is published in Molecular Cell.
4/16/2020: Our collaborative work with Lathia Lab “Myeloid-derived suppressor cell subsets drive glioblastoma growth in a sex-specific manner” is published in Cancer Discovery.
4/09/2020: Our paper “Hispanic/Latino gastric adenocarcinoma patients have distinct molecular profiles including a high rate of germline CDHI mutations” is published in Cancer Research.
3/17/2020: Our Department Of Defense Translational Team Science Award with Omar Mian, Shilpa Gupta, Lily Wang, Marcela Diaz to discover biomarker and combinatory synergies to improve #BladderCancer immunotherapy is funded! Our group will develop novel machine learning and AI algorithms to integrate image/genomics/single cell and clinical data to identify predictive biomarker for bladder immunotherapy response.
3/01/2020: Hwang lab has six posters accepted at @AACR this April.
2/22/2020: Our collaborative Department Of Defense grant with Shilpa Gupta to identify biomarker for #BladderCancer immunotherapy is funded!
1/04/2020: Our new algorithm, Bayesian Semi-nonnegative Matrix Tri-factorization, is accepted to publish in Pacific Symposium on Biocomputing (PSB) 2020.
06/14/2023: We are selected to present two oral presentation at Immunotherapy Scientific Program at the 15th International Gastric Cancer Congress.
05/22/2023: Tae Hyun Hwang will give an invited talk at HIMA Imaging Science Session and serve as a panelist at Pathology Informatics Summit 2023
05/14/2023: Tae Hyun Hwang will give a talk at Representation Learning and serve as a panelist at AI and Genomics at the 2023 Great Lakes Bioinformatics Conference
05/05/2023: 12th Annual Individualizing Medicine Conference: Direct-to-Patient Omics-Based Clinical Trials Tae Hyun Hwang will give a talk
04/14/2023: Our group will present 6 posters about AI, Machine Learning, Deep Learning based approaches utilizing single cell, spatial biology, and image data at AACR 2023 meeting.
11/31/2021: Tae Hyun Hwang gave a talk about machine learning and AI approaches developing clinically actionable biomarker for chemotherapy and immunotherapy in gastric cancer at TargetCancer Foundation.
04/21/2021: Tae Hyun Hwang gave an invited webinar about “Computational driven Spatial Transcriptome Analysis to Investigate Molecular Mechanisms present in Tumor Immune Microenvironment Associated With Immune Checkpoint Inhibitor Response in Gastric Cancer” at NanoString Webinar Series “Total Transcriptome Takeover”.
04/20/2021: Tae Hyun Hwang gave an invited talk about “Machine Learning driven Digital Pathology and Spatial Transcriptome Analyses to Predict Immune Directed Therapy Response in Bladder and Gastric Cancer” at Brigham and Women’s Hospital Computational Digital Pathology Symposium with >400 participants.
02/27/2021: Tae Hyun Hwang gave a seminar about our ongoing research "Spatial transcriptome, single cell and digital pathology approaches to understand mechanisms of response and resistance to Immunotherapy and cell therapy: Opportunities and challenges for machine learning and AI scientists" in the department of computational biology at Carnegie Melon University on March 5th.
1/13/2020: Tae Hyung Hwang gave a seminar at Cleveland Clinic-Yonsei Severance Joint AI and Data Science conference.
8/04/2019: Tae Hyun Hwang gave a keynote regarding AI in Healthcare at 24th ACM SIGKDD conference on Knowledge Discovery and Data Mining.
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RT @arnavmehta3: Excited to share our latest work uncovering the effects of sequential chemotherapy and immunotherapy on gastric can… https://t.co/qLs9NDFLH2
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1/4 📢 Belated posting about our work on ACTA2 as a potential predictive biomarker for gastric cancer immunotherapy… https://t.co/LtL0YCB8Fq
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Very grateful for the support from the Hoveida Family Foundation and leadership from @CherylWillmanMD to lead our… https://t.co/eIh8ezcH9q
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RT @KlempnerSam: Now online in @ESMO_Open Claudin18.who? Examining biomarker overlap and outcomes in claudin18.2-positive gastroes… https://t.co/a66mHbkxrB
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Finally our rapid CD19 CAR-T phase1 clinical trial is activated! If successful, this 20hr rapid CAR-T will revoluti… https://t.co/BBdFMFR5vm
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RT @CD_AACR: From the August issue: Sequential single-cell transcriptional and protein marker profiling reveals TIGIT as a marke… https://t.co/WfXhRZNLuC
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Excited to announce that our https://t.co/8fQusOju62's 20hour (one-day) Rapid CAR-T in Lymphoma IND was approved by… https://t.co/h4gAV2OwWl
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Thanks for covering our TIGIT and CD19 CAR-T work @PrecOncNews published in @CD_AACR. TIGIT Blockade Could Be Key t… https://t.co/XAaWuCrwTO
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RT @CD_AACR: #ICYMI: Sequential single-cell transcriptional and protein marker profiling reveals TIGIT as a marker of CD19 CAR-T… https://t.co/IWHjseUVBE
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Excited our work to discover #TIGIT as biomarker and combinatory therapeutic target to enhance CD19 CAR-T cell ther… https://t.co/w1XmfQNS4j