Max Gong

Dr. Max Gong

Allen School of Engineering and Computing, Trine University, Angola, IN 46703, USA
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Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 June 2017 in Chemical Reviews
Verified
Journal Article
Closed access
Max GongMax Gong
Max Gong
DSDavid Sinton
David Sinton

12 December 2018 in OncoImmunology
Verified
Journal Article
Closed access
JAJose Ayuso
Jose Ayuso
RTRegan Truttschel
Regan Truttschel
Max GongMax Gong
Max Gong
MHMouhita Humayun
Mouhita Humayun
MVMaria Virumbrales-Munoz
Maria Virumbrales-Munoz
MSMelissa C. Skala
Melissa C. Skala
Immunotherapies against solid tumors face additional challenges compared with hematological cancers. In solid tumors, immune cells and antibodies need to extravasate from vasculature, find the tumor, and migrate through a dense mass of cells. These multiple steps pose significant obstacles for solid tumor immunotherapy and their study has remained difficult using classic in vitro models based on Petri dishes. In this work, a microfluidic model has been developed to study natural killer cell response. The model includes a 3D breast cancer spheroid in a 3D extracellular matrix, and two flanking lumens lined with endothelial cells, replicating key structures and components during the immune response. Natural Killer cells and antibodies targeting the tumor cells were either embedded in the matrix or perfused through the lateral blood vessels. Antibodies that were perfused through the lateral lumens extravasated out of the blood vessels and rapidly diffused through the matrix. However, tumor cell-cell junctions hindered antibody penetration within the spheroid. On the other hand, natural killer cells were able to detect the presence of the tumor spheroid several hundreds of microns away and penetrate the spheroid faster than the antibodies. Once inside the spheroid, natural killer cells were able to destroy tumor cells at the spheroid periphery and, importantly, also at the innermost layers. Finally, the combination of antibody-cytokine conjugates and natural killer cells led to an enhanced cytotoxicity located mostly at the spheroid periphery. Overall, these results demonstrate the utility of the model for informing immunotherapy of solid tumors.

20 October 2015 in Journal of the American Chemical Society
Verified
Journal Article
Closed access
Max GongMax Gong
Max Gong
RNReza Nosrati
Reza Nosrati
MGMaria C. San Gabriel
Maria C. San Gabriel
AZArmand Zini
Armand Zini
DSDavid Sinton
David Sinton

6 May 2020 in Cancers
Verified
Journal Article
Open access
PDF file
KLKarina M. Lugo-Cintrón
Karina M. Lugo-Cintrón
Max GongMax Gong
Max Gong
JAJose Ayuso
Jose Ayuso
LTLucas A. Tomko
Lucas A. Tomko
DBDavid Beebe
David Beebe
SPSuzanne Ponik
Suzanne Ponik
The extracellular matrix (ECM) composition greatly influences cancer progression, leading to differential invasion, migration, and metastatic potential. In breast cancer, ECM components, such as fibroblasts and ECM proteins, have the potential to alter cancer cell migration. However, the lack of in vitro migration models that can vary ECM composition limits our knowledge of how specific ECM components contribute to cancer progression. Here, a microfluidic model was used to study the effect of 3D heterogeneous ECMs (i.e., fibroblasts and different ECM protein compositions) on the migration distance of a highly invasive human breast cancer cell line, MDA-MB-231. Specifically, we show that in the presence of normal breast fibroblasts, a fibronectin-rich matrix induces more cancer cell migration. Analysis of the ECM revealed the presence of ECM tunnels. Likewise, cancer-stromal crosstalk induced an increase in the secretion of metalloproteinases (MMPs) in co-cultures. When MMPs were inhibited, migration distance decreased in all conditions except for the fibronectin-rich matrix in the co-culture with human mammary fibroblasts (HMFs). This model mimics the in vivo invasion microenvironment, allowing the examination of cancer cell migration in a relevant context. In general, this data demonstrates the capability of the model to pinpoint the contribution of different components of the tumor microenvironment (TME).

1 September 2019 in Biomaterials
Verified
Journal Article
Closed access
Max GongMax Gong
Max Gong
KLKarina M. Lugo-Cintron
Karina M. Lugo-Cintron
BWBridget R. White
Bridget R. White
SKSheena C. Kerr
Sheena C. Kerr
PHPaul M. Harari
Paul M. Harari
DBDavid Beebe
David Beebe

21 July 2014 in Analytical Chemistry
Verified
Journal Article
Closed access
Max GongMax Gong
Max Gong
PZPei Zhang
Pei Zhang
BMBrendan Macdonald
Brendan Macdonald
DSDavid Sinton
David Sinton