The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Accumulation of long-chain fatty acids in the tumor microenvironment drives dysfunction in intrapancreatic CD8+ T cells
Open accessAbstract
CD8+ T cells are master effectors of antitumor immunity, and their presence at tumor sites correlates with favorable outcomes. However, metabolic constraints imposed by the tumor microenvironment (TME) can dampen their ability to control tumor progression. We describe lipid accumulation in the TME areas of pancreatic ductal adenocarcinoma (PDA) populated by CD8+ T cells infiltrating both murine and human tumors. In this lipid-rich but otherwise nutrient-poor TME, access to using lipid metabolism becomes particularly valuable for sustaining cell functions. Here, we found that intrapancreatic CD8+ T cells progressively accumulate specific long-chain fatty acids (LCFAs), which, rather than provide a fuel source, impair their mitochondrial function and trigger major transcriptional reprogramming of pathways involved in lipid metabolism, with the subsequent reduction of fatty acid catabolism. In particular, intrapancreatic CD8+ T cells specifically exhibit down-regulation of the very-long-chain acyl-CoA dehydrogenase (VLCAD) enzyme, which exacerbates accumulation of LCFAs and very-long-chain fatty acids (VLCFAs) that mediate lipotoxicity. Metabolic reprogramming of tumor-specific T cells through enforced expression of ACADVL enabled enhanced intratumoral T cell survival and persistence in an engineered mouse model of PDA, overcoming one of the major hurdles to immunotherapy for PDA.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009) · Science · doi:10.1126/science.1160809 · Cited by 16,197
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
Safety and activity of anti-PD-L1 antibody in patients with advanced cancer
Brahmer, J. R., Tykodi, S. S., Chow, L. Q. M., Hwu, W.-J., Topalian, S. L., Hwu, P., Drake, C. G., Camacho, L. H., Kauh, J., Odunsi, K., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200694 · Cited by 7,945
Molecular and cellular insights into T cell exhaustion
Wherry, E. J., & Kurachi, M. (2015) · Nature Reviews Immunology · doi:10.1038/nri3862 · Cited by 4,652
Cancer immunotherapy comes of age
Mellman, I., Coukos, G., & Dranoff, G. (2011) · Nature · doi:10.1038/nature10673 · Cited by 3,893
Genomic analyses identify molecular subtypes of pancreatic cancer
Bailey, P., Chang, D. K., Nones, K., Johns, A. L., Patch, A.-M., Gingras, M.-C., Miller, D. K., Christ, A. N., Bruxner, T. J. C., Quinn, M. C., et al. (2016) · Nature · doi:10.1038/nature16965 · Cited by 3,621 · cited 2×
“5 E) and PDA tumor cells (Bailey et al., 2016) adapt to the lipid-rich TME by up-regulating VLCAD.”
Self-citationMetabolic Competition in the Tumor Microenvironment Is a Driver of Cancer Progression
Chang, C.-H., Qiu, J., O’Sullivan, D., Buck, M. D., Noguchi, T., Curtis, J. D., Chen, Q., Gindin, M., Gubin, M. M., van der Windt, G. J. W., et al. (2015) · Cell · doi:10.1016/j.cell.2015.08.016 · Cited by 3,331
Molecular Imaging of Biological Samples: Localization of Peptides and Proteins Using MALDI-TOF MS
Caprioli, R. M., Farmer, T. B., & Gile, J. (1997) · Analytical Chemistry · doi:10.1021/ac970888i · Cited by 2,234
Self-citation
Cited by
Lipid metabolism in cancer: New perspectives and emerging mechanisms
Broadfield, L. A., Pane, A. A., Talebi, A., Swinnen, J. V., & Fendt, S.-M. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.04.013 · Cited by 758
Tumor-infiltrating regulatory T cells as targets of cancer immunotherapy
Tay, C., Tanaka, A., & Sakaguchi, S. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.02.014 · Cited by 580
Linoleic acid potentiates CD8+ T cell metabolic fitness and antitumor immunity
Nava Lauson, C. B., Tiberti, S., Corsetto, P. A., Conte, F., Tyagi, P., Machwirth, M., Ebert, S., Loffreda, A., Scheller, L., Sheta, D., et al. (2023) · Cell Metabolism · doi:10.1016/j.cmet.2023.02.013 · Cited by 291
Self-citationThe effects of age and systemic metabolism on anti-tumor T cell responses
Drijvers, J. M., Sharpe, A. H., & Haigis, M. C. (2020) · eLife · doi:10.7554/elife.62420 · Cited by 69
“Lipid accumulation in the TME of a pancreatic cancer model led to intracellular lipid accumulation in CD8 T cells, reducing their functionality (Manzo et al., 2020).”
Background
Metadata
- Authors
- Manzo, T., Prentice, B. M., Anderson, K. G., Raman, A., Schalck, A., Codreanu, G. S., Nava Lauson, C. B., Tiberti, S., Raimondi, A., Jones, M. A., Reyzer, M., Bates, B. M., Spraggins, J. M., Patterson, N. H., McLean, J. A., Rai, K., Tacchetti, C., Tucci, S., Wargo, J. A., Rodighiero, S., Clise-Dwyer, K., Sherrod, S. D., Kim, M., Navin, N. E., Caprioli, R. M., Greenberg, P. D., Draetta, G., & Nezi, L.
- Venue
- Journal of Experimental Medicine
- Publisher
- Rockefeller University Press
- Published
- 2020-06-03
- Volume
- 217
- Issue
- 8
- ISSN
- 0022-1007 (ISSN-L)
- 1540-9538
- OpenAlex
- W3028703234
- Cited by
- 342
- References
- 27
- FWCI
- 10.57
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Accumulation of long-chain fatty acids in the tumor microenvironment drives dysfunction in intrapancreatic CD8+ T cells. https://app.cochat.ai/papers/10.1084/jem.20191920
- The paper
- Manzo, T., Prentice, B. M., Anderson, K. G., Raman, A., Schalck, A., Codreanu, G. S., Nava Lauson, C. B., Tiberti, S., Raimondi, A., Jones, M. A., Reyzer, M., Bates, B. M., Spraggins, J. M., Patterson, N. H., McLean, J. A., Rai, K., Tacchetti, C., Tucci, S., Wargo, J. A., . . . Nezi, L. (2020). Accumulation of long-chain fatty acids in the tumor microenvironment drives dysfunction in intrapancreatic CD8+ T cells. Journal of Experimental Medicine. https://doi.org/10.1084/jem.20191920
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.