The DOI matches its Crossref record; 90 of the 90 references it cites were found in a registry or an index.
Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma
Open accessAbstract
Hepatocellular carcinoma (HCC) has high relapse and low 5-year survival rates. Single-cell profiling in relapsed HCC may aid in the design of effective anticancer therapies, including immunotherapies. We profiled the transcriptomes of ∼17,000 cells from 18 primary or early-relapse HCC cases. Early-relapse tumors have reduced levels of regulatory T cells, increased dendritic cells (DCs), and increased infiltrated CD8+ T cells, compared with primary tumors, in two independent cohorts. Remarkably, CD8+ T cells in recurrent tumors overexpressed KLRB1 (CD161) and displayed an innate-like low cytotoxic state, with low clonal expansion, unlike the classical exhausted state observed in primary HCC. The enrichment of these cells was associated with a worse prognosis. Differential gene expression and interaction analyses revealed potential immune evasion mechanisms in recurrent tumor cells that dampen DC antigen presentation and recruit innate-like CD8+ T cells. Our comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse.
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
Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., & Jemal, A. (2018) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21492 · Cited by 84,109
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
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
fastp: an ultra-fast all-in-one FASTQ preprocessor
Chen, S., Zhou, Y., Chen, Y., & Gu, J. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty560 · Cited by 29,721
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179
GSVA: gene set variation analysis for microarray and RNA-Seq data
Hänzelmann, S., Castelo, R., & Guinney, J. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-7 · Cited by 15,440
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,621
EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma
Galle, P. R., Forner, A., Llovet, J. M., Mazzaferro, V., Piscaglia, F., Raoul, J.-L., Schirmacher, P., & Vilgrain, V. (2018) · Journal of Hepatology · doi:10.1016/j.jhep.2018.03.019 · Cited by 11,406
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Research works printed but not linked: 1
- Zheng, 2017, Actual 10-Year Survivors After Resection of Hepatocellular Carcinoma, Ann. Surg. Oncol., 24, 1358, 10.1245/s10434-016-5713-2 · DOI
Cited by
Immunotherapies for hepatocellular carcinoma
Llovet, J. M., Castet, F., Heikenwalder, M., Maini, M. K., Mazzaferro, V., Pinato, D. J., Pikarsky, E., Zhu, A. X., & Finn, R. S. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-021-00573-2 · Cited by 1,843
Molecular pathogenesis and systemic therapies for hepatocellular carcinoma
Llovet, J. M., Pinyol, R., Kelley, R. K., El-Khoueiry, A., Reeves, H. L., Wang, X. W., Gores, G. J., & Villanueva, A. (2022) · Nature Cancer · doi:10.1038/s43018-022-00357-2 · Cited by 498
Self-citationBiomarkers for immunotherapy of hepatocellular carcinoma
Greten, T. F., Villanueva, A., Korangy, F., Ruf, B., Yarchoan, M., Ma, L., Ruppin, E., & Wang, X. W. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00816-4 · Cited by 227
Self-citationXCR1+ type 1 conventional dendritic cells drive liver pathology in non-alcoholic steatohepatitis
Deczkowska, A., David, E., Ramadori, P., Pfister, D., Safran, M., Li, B., Giladi, A., Jaitin, D. A., Barboy, O., Cohen, M., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01344-3 · Cited by 197
Intratumor microbiome features reveal antitumor potentials of intrahepatic cholangiocarcinoma
Chai, X., Wang, J., Li, H., Gao, C., Li, S., Wei, C., Huang, J., Tian, Y., Yuan, J., Lu, J., et al. (2023) · Gut Microbes · doi:10.1080/19490976.2022.2156255 · Cited by 152
Self-citation
Metadata
- Authors
- Sun, Y., Wu, L., Zhong, Y., Zhou, K., Hou, Y., Wang, Z., Zhang, Z., Xie, J., Wang, C., Chen, D., Huang, Y., Wei, X., Shi, Y., Zhao, Z., Li, Y., Guo, Z., Yu, Q., Xu, L., Volpe, G., Qiu, S., Zhou, J., Ward, C., Sun, H., Yin, Y., Xu, X., Wang, X., Esteban, M. A., Yang, H., Wang, J., Dean, M., Zhang, Y., Liu, S., Yang, X., & Fan, J.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 184
- Issue
- 2
- Pages
- 404-421.e16
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W3118017075
- Cited by
- 895
- References
- 90
- FWCI
- 32.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 385 d)
- Funders
- Shanghai Association for Science and Technology
- Chinese Academy of Sciences
- Science and Technology Planning Project of Guangdong Province
- Natural Science Foundation of Guangdong Province
- Science, Technology and Innovation Commission of Shenzhen Municipality
- Shanghai Municipal Health and Family Planning Commission
- National Natural Science Foundation of China
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: Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma. https://app.cochat.ai/papers/10.1016/j.cell.2020.11.041
- The paper
- Sun, Y., Wu, L., Zhong, Y., Zhou, K., Hou, Y., Wang, Z., Zhang, Z., Xie, J., Wang, C., Chen, D., Huang, Y., Wei, X., Shi, Y., Zhao, Z., Li, Y., Guo, Z., Yu, Q., Xu, L., Volpe, G., . . . Fan, J. (2021). Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma. Cell. https://doi.org/10.1016/j.cell.2020.11.041
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.