The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma
Open accessAbstract
Immune checkpoint blockade (ICB) of PD-1 and CTLA-4 to treat metastatic melanoma (MM) has variable therapeutic benefit. To explore this in peripheral samples, we characterized CD8+ T cell gene expression across a cohort of patients with MM receiving anti-PD-1 alone (sICB) or in combination with anti-CTLA-4 (cICB). Whereas CD8+ transcriptional responses to sICB and cICB involve a shared gene set, the magnitude of cICB response is over fourfold greater, with preferential induction of mitosis- and interferon-related genes. Early samples from patients with durable clinical benefit demonstrated overexpression of T cell receptor–encoding genes. By mapping T cell receptor clonality, we find that responding patients have more large clones (those occupying >0.5% of repertoire) post-treatment than non-responding patients or controls, and this correlates with effector memory T cell percentage. Single-cell RNA-sequencing of eight post-treatment samples demonstrates that large clones overexpress genes implicated in cytotoxicity and characteristic of effector memory T cells, including CCL4, GNLY and NKG7. The 6-month clinical response to ICB in patients with MM is associated with the large CD8+ T cell clone count 21 d after treatment and agnostic to clonal specificity, suggesting that post-ICB peripheral CD8+ clonality can provide information regarding long-term treatment response and, potentially, facilitate treatment stratification. Transcriptomic analysis of peripheral CD8+ T cells in a cohort of patients with metastatic melanoma receiving checkpoint inhibitors shows that the number of large clones early post-treatment is strongly associated with six-month clinical outcome.
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
Fitting Linear Mixed-Effects Models Using lme4
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
WGCNA: an R package for weighted correlation network analysis
Langfelder, P., & Horvath, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-559 · Cited by 27,252
HISAT: a fast spliced aligner with low memory requirements
Kim, D., Langmead, B., & Salzberg, S. L. (2015) · Nature Methods · doi:10.1038/nmeth.3317 · Cited by 24,112
HTSeq—a Python framework to work with high-throughput sequencing data
Anders, S., Pyl, P. T., & Huber, W. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu638 · Cited by 21,464
Comprehensive Integration of Single-Cell Data
Stuart, T., Butler, A., Hoffman, P., Hafemeister, C., Papalexi, E., Mauck, W. M., Hao, Y., Stoeckius, M., Smibert, P., & Satija, R. (2019) · Cell · doi:10.1016/j.cell.2019.05.031 · Cited by 15,453
VEGAN, a package of R functions for community ecology
Dixon, P. (2003) · Journal of Vegetation Science · doi:10.1111/j.1654-1103.2003.tb02228.x · Cited by 6,824
PD-1 blockade induces responses by inhibiting adaptive immune resistance
Tumeh, P. C., Harview, C. L., Yearley, J. H., Shintaku, I. P., Taylor, E. J. M., Robert, L., Chmielowski, B., Spasic, M., Henry, G., Ciobanu, V., et al. (2014) · Nature · doi:10.1038/nature13954 · Cited by 6,609
Orchestrating high-throughput genomic analysis with Bioconductor
Huber, W., Carey, V. J., Gentleman, R., Anders, S., Carlson, M., Carvalho, B. S., Bravo, H. C., Davis, S., Gatto, L., Girke, T., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3252 · Cited by 3,608
Cited by
Hiam-Galvez, K. J., Allen, B. M., & Spitzer, M. H. (2021) · Nature Reviews Cancer · doi:10.1038/s41568-021-00347-z · Cited by 1,400
A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer
Bassez, A., Vos, H., Van Dyck, L., Floris, G., Arijs, I., Desmedt, C., Boeckx, B., Vanden Bempt, M., Nevelsteen, I., Lambein, K., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01323-8 · Cited by 867
Ott, P. A., Hu-Lieskovan, S., Chmielowski, B., Govindan, R., Naing, A., Bhardwaj, N., Margolin, K., Awad, M. M., Hellmann, M. D., Lin, J. J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.053 · Cited by 738
Rahim, M. K., Okholm, T. L. H., Jones, K. B., McCarthy, E. E., Liu, C. C., Yee, J. L., Tamaki, S. J., Marquez, D. M., Tenvooren, I., Wai, K., et al. (2023) · Cell · doi:10.1016/j.cell.2023.02.021 · Cited by 455
A blood atlas of COVID-19 defines hallmarks of disease severity and specificity
Ahern, D. J., Ai, Z., Ainsworth, M., Allan, C., Allcock, A., Angus, B., Ansari, M. A., Arancibia-Cárcamo, C. V., Aschenbrenner, D., Attar, M., et al. (2022) · Cell · doi:10.1016/j.cell.2022.01.012 · Cited by 328
Self-citation
Metadata
- Authors
- Fairfax, B. P., Taylor, C. A., Watson, R. A., Nassiri, I., Danielli, S., Fang, H., Mahé, E. A., Cooper, R., Woodcock, V., Traill, Z., Al-Mossawi, M. H., Knight, J. C., Klenerman, P., Payne, M., & Middleton, M. R.
- Venue
- Nature Medicine
- Published
- 2020-02
- Volume
- 26
- Issue
- 2
- Pages
- 193-199
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W3005134677
- Cited by
- 341
- References
- 42
- FWCI
- 15.96
- Type
- journal article
- Language
- en
- Open access
- green
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: Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma. https://app.cochat.ai/papers/10.1038/s41591-019-0734-6
- The paper
- Fairfax, B. P., Taylor, C. A., Watson, R. A., Nassiri, I., Danielli, S., Fang, H., Mahé, E. A., Cooper, R., Woodcock, V., Traill, Z., Al-Mossawi, M. H., Knight, J. C., Klenerman, P., Payne, M., & Middleton, M. R. (2020). Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma. Nature Medicine. https://doi.org/10.1038/s41591-019-0734-6
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.
