Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comment
. 2021 Mar;18(3):515-517.
doi: 10.1038/s41423-020-00594-4. Epub 2020 Dec 14.

A machine learning approach to predict response to immunotherapy in type 1 diabetes

Georgia Fousteri  1 , Ely Montee Rodrigues  2 , Gian Maria Giamporcaro  2 , Marika Falcone  3
Affiliations
Comment

A machine learning approach to predict response to immunotherapy in type 1 diabetes

Georgia Fousteri et al. Cell Mol Immunol. 2021 Mar.
No abstract available

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
A Stratification of T1D patients based on immunological profiles. Edner et al. used comprehensive immunological profiling to stratify T1D patients into responders (blue) and non-responders (red). Blood samples of T1D patients treated with CTLA4-Ig (abatacept) were analyzed through a machine learning approach that identified immunological profiles (high ICOS+TFH, high CXCR5+ naive T cells), helping to stratify treated T1D patients into responders and non-responders. Responders were characterized by a reduction in TFH (T follicular helper), Tph (T peripheral helper), ICOS+PD-1+TFH, ICOS+PD-1− TFH, T regulatory, and ICOS+ memory and naive cells. B Possible mechanism of action for CTLA-4Ig (abatacept). Deactivation and dedifferentiation of TFH cells may be related to two mechanisms. 1. CTLA-4Ig inhibits crosstalk between the costimulatory molecules CD28 and CD80/CD86, altering TFH cell differentiation at two “decision” points in the germinal centers of secondary lymphoid organs and the T-cell zone. 2. CTLA-4Ig interferes with CD28–CD80/86-mediated activation of CD4 T cells by DCs at the T-cell zone or CD4 T-cell interactions with B cells at the T:B cell border, consequently preventing TFH cell differentiation, ICOS upregulation, and entry into B cell follicles. Once in the B cell follicle and the germinal center, abatacept neutralizes CD28–CD80/CD86 interaction among TFH cells, GC B cells and follicular DCs (FDCs), further weakening TFH cell differentiation and proliferation
See this image and copyright information in PMC

Comment on

References

    1. Edner NM, et al. Follicular helper T cell profiles predict response to costimulation blockade in type 1 diabetes. Nat. Immunol. 2020;21:1244–1255. doi: 10.1038/s41590-020-0744-z. - DOI - PMC - PubMed
    1. Todd JA. Etiology of type 1 diabetes. Immunity. 2010;32:457–467. doi: 10.1016/j.immuni.2010.04.001. - DOI - PubMed
    1. Fousteri G, Ippolito E, Ahmed R, Hamad ARA. Beta-cell specific autoantibodies: are they just an indicator of type 1 diabetes? Curr. Diabet. Rev. 2017;13:322–329. doi: 10.2174/1573399812666160427104157. - DOI - PMC - PubMed
    1. Chamberlain N, et al. Rituximab does not reset defective early B cell tolerance checkpoints. J. Clin. Invest. 2016;126:282–287. doi: 10.1172/JCI83840. - DOI - PMC - PubMed
    1. Crotty S. T follicular helper cell biology: a decade of discovery and diseases. Immunity. 2019;50:1132–1148. doi: 10.1016/j.immuni.2019.04.011. - DOI - PMC - PubMed

Publication types