Preexisting Skin-Resident CD8 and γδ T-cell Circuits Mediate Immune Response in Merkel Cell Carcinoma and Predict Immunotherapy Efficacy
Open accessPublished version of a preprint
Abstract
Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer with a ∼50% response rate to immune checkpoint blockade (ICB) therapy. To identify predictive biomarkers, we integrated bulk and single-cell RNA sequencing (RNA-seq) with spatial transcriptomics from a cohort of 186 samples from 116 patients, including bulk RNA-seq from 14 matched pairs pre- and post-ICB. In nonresponders, tumors show evidence of increased tumor proliferation, neuronal stem cell markers, and IL1. Responders have increased type I/II interferons and preexisting tissue resident (Trm) CD8 or Vδ1 γδ T cells that functionally converge with overlapping antigen-specific transcriptional programs and clonal expansion of public T-cell receptors. Spatial transcriptomics demonstrated colocalization of T cells with B and dendritic cells, which supply chemokines and costimulation. Lastly, ICB significantly increased clonal expansion or recruitment of Trm and Vδ1 cells in tumors specifically in responders, underscoring their therapeutic importance. These data identify potential clinically actionable biomarkers and therapeutic targets for MCC. Significance: MCC serves as a model of ICB response. We utilized the largest-to-date, multimodal MCC dataset (n = 116 patients) to uncover unique tumor-intrinsic properties and immune circuits that predict response. We identified CD8 Trm and Vδ1 T cells as clinically actionable mediators of ICB response in major histocompatibility complex–high and –low MCCs, respectively.
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
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.
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Top 10 Challenges in Cancer Immunotherapy
Hegde, P. S., & Chen, D. S. (2020) · Immunity · doi:10.1016/j.immuni.2019.12.011 · Cited by 2,238 · see citing works
Li, H., van der Leun, A. M., Yofe, I., Lubling, Y., Gelbard-Solodkin, D., van Akkooi, A. C. J., van den Braber, M., Rozeman, E. A., Haanen, J. B. A. G., Blank, C. U., et al. (2019) · Cell · doi:10.1016/j.cell.2018.11.043 · Cited by 1,101 · see citing works
γδ T cells are effectors of immunotherapy in cancers with HLA class I defects
de Vries, N. L., van de Haar, J., Veninga, V., Chalabi, M., Ijsselsteijn, M. E., van der Ploeg, M., van den Bulk, J., Ruano, D., van den Berg, J. G., Haanen, J. B., et al. (2023) · Nature · doi:10.1038/s41586-022-05593-1 · Cited by 311 · see citing works
PIRD: pan immune repertoire database
Zhang, W., Wang, L., Liu, K., Wei, X., Yang, K., Du, W., Wang, S., Guo, N., Ma, C., Luo, L., et al. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz614 · Cited by 166 · see citing works
Flagged first, then by citations
- Authors
- Reinstein, Z. Z., Zhang, Y., Ospina, O. E., Nichols, M. D., Chu, V. A., Pulido, A. D. M., Prieto, K., Nguyen, J. V., Yin, R., Moran Segura, C., Usman, A., Sell, B., Ng, S., de la Iglesia, J. V., Chandra, S., Sosman, J. A., Cho, R. J., Cheng, J. B., Ivanova, E., Koralov, S. B., Slebos, R. J. C., Chung, C. H., Khushalani, N. I., Messina, J. L., Sarnaik, A. A., Zager, J. S., Sondak, V. K., Vaske, C., Kim, S., Brohl, A. S., Mi, X., Pierce, B. G., Wang, X., Fridley, B. L., Tsai, K. Y., & Choi, J.
- Affiliations
- Northwestern University (US)
- Moffitt Cancer Center (US)
- Department of Tumor Metastasis and Microenvironment, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida. 6
- Institute for Bioscience and Biotechnology Research (US)
- Department of Pathology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida. 7
- University of California, San Francisco (US)
- San Francisco VA Medical Center (US)
- New York University (US)
- Clear Labs, Santa Cruz, California. 18
- Corresponding author
- Tsai, Kenneth Y.
- Choi, Jaehyuk
- ORCID
- Reinstein, Zachary Z.
- Zhang, Yue
- Ospina, Oscar E.
- Nichols, Matt D.
- Chu, Victoria A.
- Pulido, Alvaro de Mingo
- Prieto, Karol
- Nguyen, Jonathan V.
- Yin, Rui
- Moran Segura, Carlos
- Usman, Ahmed
- Sell, Brittney
- Ng, Spencer
- de la Iglesia, Janis V.
- Chandra, Sunandana
- Sosman, Jeffrey A.
- Cho, Raymond J.
- Cheng, Jeffrey B.
- Ivanova, Ellie
- Koralov, Sergei B.
- Slebos, Robbert J.C.
- Chung, Christine H.
- Khushalani, Nikhil I.
- Messina, Jane L.
- Sarnaik, Amod A.
- Zager, Jonathan S.
- Sondak, Vernon K.
- Vaske, Charles
- Kim, Sungjune
- Brohl, Andrew S.
- Mi, Xinlei
- Pierce, Brian G.
- Wang, Xuefeng
- Fridley, Brooke L.
- Tsai, Kenneth Y.
- Choi, Jaehyuk
- Venue
- Cancer Discovery
- Published
- 2024-07-26
- Volume
- 14
- Issue
- 9
- Pages
- 1631-1652
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- PMC
- PMC11954000
- OpenAlex
- W4401025146
- Cited by
- 33
- References
- 5
- Citations by year
- 2026: 15 · 2025: 16 · 2024: 2
- FWCI
- 5.65
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cancer Discovery (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- Funders
- Alpha Omega Alpha Honor Medical Society (2019 AOA Carolyn E Kuckein Fellowship)
- National Cancer Institute (P30-CA076292, T32 CA009560, F30CA278298, DP2 OD024475-01, R35 GM144083, T32CA233399)
- Leukemia and Lymphoma Society (1377-21)
- V Foundation for Cancer Research (T2021-019)
- National Comprehensive Cancer Network (NCCN-YIA 2019)
- Topics
- Health Sciences › Medicine › Oncology › Polyomavirus and related diseases
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- Merkel cell carcinoma, immune checkpoint blockade, predictive biomarkers, CD8+ T cells, Vδ1 γδ T cells, tissue-resident memory T cells, tumor-infiltrating lymphocytes, spatial transcriptomics, single-cell RNA sequencing, type I interferon, interleukin-1, T cell clonal expansion, MHC class I, MHC class II, immune response prediction
- MeSH terms
- Immune Checkpoint Inhibitors, Humans, Immunotherapy, Skin Neoplasms, Carcinoma, Merkel Cell, CD8-Positive T-Lymphocytes
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