The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer
Open accessAbstract
In triple-negative breast cancer (TNBC), the benefit of combining chemotherapy with checkpoint inhibitors is still not very clear. We utilize single-cell RNA- and ATAC-sequencing to examine the immune cell dynamics in 22 patients with advanced TNBC treated with paclitaxel or its combination with the anti-PD-L1 atezolizumab. We demonstrate that high levels of baseline CXCL13 + T cells are linked to the proinflammatory features of macrophages and can predict effective responses to the combination therapy. In responsive patients, lymphoid tissue inducer (LTi) cells, follicular B (Bfoc) cells, CXCL13 + T cells, and conventional type 1 dendritic cells (cDC1) concertedly increase following the combination therapy, but instead decrease after paclitaxel monotherapy. Our data highlight the importance of CXCL13 + T cells in effective responses to anti-PD-L1 therapies and suggest that their reduction by paclitaxel regimen may compromise the clinical outcomes of accompanying atezolizumab for TNBC treatment.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These cell subsets show different responses to anti-PD(L)-1 therapies,”
From Contrasting cytotoxic and regulatory T cell responses underlying distinct clinical outcomes to anti-PD-1 plus lenvatinib therapy in cancer (2025) · cites this paper as [19]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Applying ICB and combination therapies as neoadjuvant treatments provides an opportunity to observe immune cell dynamics in tumor microenvironment (TME) with temporal samples.”
From Contrasting cytotoxic and regulatory T cell responses underlying distinct clinical outcomes to anti-PD-1 plus lenvatinib therapy in cancer (2025) · cites this paper as [19]
Experimental — accuracy not yet measured
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
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
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)
Eisenhauer, E. A., Therasse, P., Bogaerts, J., Schwartz, L. H., Sargent, D., Ford, R., Dancey, J., Arbuck, S., Gwyther, S., Mooney, M., et al. (2009) · European Journal of Cancer · doi:10.1016/j.ejca.2008.10.026 · Cited by 29,534
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
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,724
The blockade of immune checkpoints in cancer immunotherapy
Pardoll, D. M. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3239 · Cited by 13,838
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,457
SCANPY: large-scale single-cell gene expression data analysis
Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology · doi:10.1186/s13059-017-1382-0 · Cited by 8,881
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013) · Science · doi:10.1126/science.1235122 · Cited by 7,863
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X. Y., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al. (2017) · Nature Communications · doi:10.1038/ncomms14049 · Cited by 7,353
Cancer immunotherapy using checkpoint blockade
Ribas, A., & Wolchok, J. D. (2018) · Science · doi:10.1126/science.aar4060 · Cited by 6,791
From Louvain to Leiden: guaranteeing well-connected communities
Traag, V. A., Waltman, L., & van Eck, N. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-41695-z · Cited by 5,635
Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq
Tirosh, I., Izar, B., Prakadan, S. M., Wadsworth, M. H., Treacy, D., Trombetta, J. J., Rotem, A., Rodman, C., Lian, C., Murphy, G., et al. (2016) · Science · doi:10.1126/science.aad0501 · Cited by 4,944
Hafemeister, C., & Satija, R. (2019) · Genome Biology · doi:10.1186/s13059-019-1874-1 · Cited by 4,479
Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer
Schmid, P., Adams, S., Rugo, H. S., Schneeweiss, A., Barrios, C. H., Iwata, H., Diéras, V., Hegg, R., Im, S.-A., Shaw Wright, G., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1809615 · Cited by 4,350
Innate and adaptive immune cells in the tumor microenvironment
Gajewski, T. F., Schreiber, H., & Fu, Y.-X. (2013) · Nature Immunology · doi:10.1038/ni.2703 · Cited by 4,148
Wherry, E. J. (2011) · Nature Immunology · doi:10.1038/ni.2035 · Cited by 4,062
Salgado, R., Denkert, C., Demaria, S., Sirtaine, N., Klauschen, F., Pruneri, G., Wienert, S., den Eynden, G. V., Baehner, F. L., Penault-Llorca, F. M., et al. (2014) · Annals of Oncology · doi:10.1093/annonc/mdu450 · Cited by 3,142
Triple-negative breast cancer: challenges and opportunities of a heterogeneous disease
Bianchini, G., Balko, J. M., Mayer, I. A., Sanders, M. E., & Gianni, L. (2016) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.66 · Cited by 3,079
Scrublet: computational identification of cell doublets in single-cell transcriptomic data
Wolock, S. L., Lopez, R., & Klein, A. M. (2018) · doi:10.1101/357368 · Cited by 2,758
Scrublet: computational identification of cell doublets in single-cell transcriptomic data
Wolock, S. L., Lopez, R., & Klein, A. M. (2019) · Cell Systems · doi:10.1016/j.cels.2018.11.005 · Cited by 2,758
B cells and tertiary lymphoid structures promote immunotherapy response
Helmink, B. A., Reddy, S. M., Gao, J., Zhang, S., Basar, R., Thakur, R., Yizhak, K., Sade-Feldman, M., Blando, J., Han, G., et al. (2020) · Nature · doi:10.1038/s41586-019-1922-8 · Cited by 2,731
Tertiary lymphoid structures improve immunotherapy and survival in melanoma
Cabrita, R., Lauss, M., Sanna, A., Donia, M., Skaarup Larsen, M., Mitra, S., Johansson, I., Phung, B., Harbst, K., Vallon-Christersson, J., et al. (2020) · Nature · doi:10.1038/s41586-019-1914-8 · Cited by 2,374
Immune checkpoint targeting in cancer therapy: toward combination strategies with curative potential
Sharma, P., & Allison, J. P. (2015) · Cell · doi:10.1016/j.cell.2015.03.030 · Cited by 2,345
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
NicheNet: Modeling intercellular communication by linking ligands to target genes
Browaeys, R., Saelens, W., & Saeys, Y. (2020) · Nature Methods · doi:10.1038/s41592-019-0667-5 · Cited by 2,192
Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing
Zheng, C., Zheng, L., Yoo, J.-K., Guo, H., Zhang, Y., Guo, X., Kang, B., Hu, R., Huang, J. Y., Zhang, Q., et al. (2017) · Cell · doi:10.1016/j.cell.2017.05.035 · Cited by 2,152
Self-citationSingle-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment
Azizi, E., Carr, A. J., Plitas, G., Cornish, A. E., Konopacki, C., Prabhakaran, S., Nainys, J., Wu, K., Kiseliovas, V., Setty, M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.060 · Cited by 1,976
B cells are associated with survival and immunotherapy response in sarcoma
Petitprez, F., de Reyniès, A., Keung, E. Z., Chen, T. W.-W., Sun, C.-M., Calderaro, J., Jeng, Y.-M., Hsiao, L.-P., Lacroix, L., Bougoüin, A., et al. (2020) · Nature · doi:10.1038/s41586-019-1906-8 · Cited by 1,942
Fast and SNP-tolerant detection of complex variants and splicing in short reads
Wu, T. D., & Nacu, S. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq057 · Cited by 1,894
Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing
Guo, X., Zhang, Y., Zheng, L., Zheng, C., Song, J., Zhang, Q., Kang, B., Liu, Z., Jin, L., Xing, R., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0045-3 · Cited by 1,651
Self-citationLandscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma
Zhang, Q., He, Y., Luo, N., Patel, S. J., Han, Y., Gao, R., Modak, M., Carotta, S., Haslinger, C., Kind, D., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.003 · Cited by 1,624
Self-citationSingle-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer
Zhang, L., Li, Z., Skrzypczynska, K. M., Fang, Q., Zhang, W., O’Brien, S. A., He, Y., Wang, L., Zhang, Q., Kim, A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.03.048 · Cited by 1,620
Self-citationBlank, C. U., Haining, W. N., Held, W., Hogan, P. G., Kallies, A., Lugli, E., Lynn, R. C., Philip, M., Rao, A., Restifo, N. P., et al. (2019) · Nature Reviews Immunology · doi:10.1038/s41577-019-0221-9 · Cited by 1,603
A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells
Cheng, S., Li, Z., Gao, R., Xing, B., Gao, Y., Yang, Y., Qin, S., Zhang, L., Ouyang, H., Du, P., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.010 · Cited by 1,601
Self-citationStrelka: accurate somatic small-variant calling from sequenced tumor–normal sample pairs
Saunders, C. T., Wong, W. S. W., Swamy, S., Becq, J., Murray, L. J., & Cheetham, R. K. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts271 · Cited by 1,589
Clonal replacement of tumor-specific T cells following PD-1 blockade
Yost, K. E., Satpathy, A. T., Wells, D. K., Qi, Y., Wang, C., Kageyama, R., McNamara, K. L., Granja, J. M., Sarin, K. Y., Brown, R. A., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0522-3 · Cited by 1,534
Lineage tracking reveals dynamic relationships of T cells in colorectal cancer
Zhang, L., Yu, X., Zheng, L., Zhang, Y., Li, Y., Fang, Q., Gao, R., Kang, B., Zhang, Q., Huang, J. Y., et al. (2018) · Nature · doi:10.1038/s41586-018-0694-x · Cited by 1,505
Self-citationPembrolizumab in Patients With Advanced Triple-Negative Breast Cancer: Phase Ib KEYNOTE-012 Study
Nanda, R., Chow, L. Q. M., Dees, E. C., Berger, R., Gupta, S., Geva, R., Pusztai, L., Pathiraja, K., Aktan, G., Cheng, J. D., et al. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2015.64.8931 · Cited by 1,477
Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates
Simoni, Y., Becht, E., Fehlings, M., Loh, C. Y., Koo, S.-L., Teng, K. W. W., Yeong, J. P. S., Nahar, R., Zhang, T., Kared, H., et al. (2018) · Nature · doi:10.1038/s41586-018-0130-2 · Cited by 1,370
Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing
Cusanovich, D. A., Daza, R., Adey, A., Pliner, H. A., Christiansen, L., Gunderson, K. L., Steemers, F. J., Trapnell, C., & Shendure, J. (2015) · Science · doi:10.1126/science.aab1601 · Cited by 1,248
Hargadon, K. M., Johnson, C. E., & Williams, C. J. (2018) · International Immunopharmacology · doi:10.1016/j.intimp.2018.06.001 · Cited by 1,211
Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses
Lavin, Y., Kobayashi, S., Leader, A., Amir, E.-A. D., Elefant, N., Bigenwald, C., Remark, R., Sweeney, R., Becker, C. D., Levine, J. H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.04.014 · Cited by 1,209
A rapid and robust method for single cell chromatin accessibility profiling
Chen, X., Miragaia, R. J., Natarajan, K. N., & Teichmann, S. A. (2018) · Nature Communications · doi:10.1038/s41467-018-07771-0 · Cited by 1,147
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
Arbour, K. C., Mezquita, L., Long, N., Rizvi, H., Auclin, E., Ni, A., Martínez-Bernal, G., Ferrara, R., Lai, W. V., Hendriks, L. E. L., et al. (2018) · Journal of Clinical Oncology · doi:10.1200/jco.2018.79.0006 · Cited by 1,071
Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab), Savas, P., Virassamy, B., Ye, C., Salim, A., Mintoff, C. P., Caramia, F., Salgado, R., Byrne, D. J., Teo, Z. L., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0078-7 · Cited by 992
The epigenetic landscape of T cell exhaustion
Sen, D. R., Kaminski, J., Barnitz, R. A., Kurachi, M., Gerdemann, U., Yates, K. B., Tsao, H.-W., Godec, J., LaFleur, M. W., Brown, F. D., et al. (2016) · Science · doi:10.1126/science.aae0491 · Cited by 986
Systemic Immunity Is Required for Effective Cancer Immunotherapy
Spitzer, M. H., Carmi, Y., Reticker-Flynn, N. E., Kwek, S. S., Madhireddy, D., Martins, M. M., Gherardini, P. F., Prestwood, T. R., Chabon, J., Bendall, S. C., et al. (2017) · Cell · doi:10.1016/j.cell.2016.12.022 · Cited by 963
A conserved dendritic-cell regulatory program limits antitumour immunity
Maier, B. B., Leader, A. M., Chen, S. T., Tung, N., Chang, C., Bérichel, J. L., Chudnovskiy, A., Maskey, S., Walker, L. A., Finnigan, J. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2134-y · Cited by 939
Co-expression of CD39 and CD103 identifies tumor-reactive CD8 T cells in human solid tumors
Duhen, T., Duhen, R., Montler, R., Moses, J., Moudgil, T., de Miranda, N. F., Goodall, C. P., Blair, T. C., Fox, B. A., McDermott, J. E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05072-0 · Cited by 938
Chromatin states define tumour-specific T cell dysfunction and reprogramming
Philip, M., Fairchild, L., Sun, L., Horste, E. L., Camara, S., Shakiba, M., Scott, A. C., Viale, A., Lauer, P., Merghoub, T., et al. (2017) · Nature · doi:10.1038/nature22367 · Cited by 933
BBKNN: fast batch alignment of single cell transcriptomes
Polański, K., Young, M. D., Miao, Z., Meyer, K. B., Teichmann, S. A., & Park, J.-E. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz625 · Cited by 932
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
House, I. G., Savas, P., Lai, J., Chen, A. X. Y., Oliver, A. J., Teo, Z. L., Todd, K. L., Henderson, M. A., Giuffrida, L., Petley, E. V., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-1868 · Cited by 790
Dirix, L. Y., Takács, I., Jérusalem, G., Nikolinakos, P. G., Arkenau, H., Forero, A., Boccia, R. V., Lippman, M. E., Somer, R. A., Šmakal, M., et al. (2017) · Breast Cancer Research and Treatment · doi:10.1007/s10549-017-4537-5 · Cited by 762
Miles, D. W., Gligorov, J., André, F., Cameron, D., Schneeweiß, A., Barrios, C. H., Xu, B., Wardley, A. M., Kaen, D. L., Andrade, L., et al. (2021) · Annals of Oncology · doi:10.1016/j.annonc.2021.05.801 · Cited by 737
Self-citationHigh-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy
Krieg, C., Nowicka, M., Guglietta, S., Schindler, S., Hartmann, F. J., Weber, L. M., Dummer, R., Robinson, M. D., Levesque, M. P., & Becher, B. (2018) · Nature Medicine · doi:10.1038/nm.4466 · Cited by 735
TREM2 Modulation Remodels the Tumor Myeloid Landscape Enhancing Anti-PD-1 Immunotherapy
Molgora, M., Esaulova, E., Vermi, W., Hou, J., Chen, Y., Luo, J., Brioschi, S., Bugatti, M., Omodei, A. S., Ricci, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.07.013 · Cited by 656
cDC1 prime and are licensed by CD4(+) T cells to induce anti-tumour immunity
Ferris, S. T., Durai, V., Wu, R., Theisen, D. J., Ward, J. P., Bern, M. D., Davidson, J. T., Bagadia, P., Liu, T., Briseño, C. G., et al. (2020) · Nature · doi:10.1038/s41586-020-2611-3 · Cited by 611
Hollern, D. P., Xu, N., Thennavan, A., Glodowski, C. R., García‐Recio, S., Mott, K. R., He, X., Garay, J. P., Carey-Ewend, K., Marron, D. L., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.028 · Cited by 480
Roles of BCL6 in normal and transformed germinal center B cells
Basso, K., & Dalla‐Favera, R. (2012) · Immunological Reviews · doi:10.1111/j.1600-065x.2012.01112.x · Cited by 455
Massively multiplex chemical transcriptomics at single-cell resolution
Srivatsan, S. R., McFaline-Figueroa, J. L., Ramani, V., Saunders, L., Cao, J., Packer, J., Pliner, H. A., Jackson, D. L., Daza, R. M., Christiansen, L., et al. (2020) · Science · doi:10.1126/science.aax6234 · Cited by 401
Choudhuri, D., Srinivasan, S. G., Gibson, M. A., Zheng, Y., Jaeger, D. L., Fraser, H. L., & Banerjee, R. (2017) · Nature Communications · doi:10.1038/s41467-017-02112-z · Cited by 384
Are Conventional Type 1 Dendritic Cells Critical for Protective Antitumor Immunity and How?
Cancel, J.-C., Crozat, K., Dalod, M., & Mattiuz, R. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00009 · Cited by 198
Xu, W., Zhao, X., Wang, X., Han, F., Gou, M., Jin, W., Wang, X., Liu, X., & Dong, C. (2019) · Immunity · doi:10.1016/j.immuni.2019.10.006 · Cited by 178
Effects of Systemically Administered Hydrocortisone on the Human Immunome
Olnes, M. J., Kotliarov, Y., Biancotto, A., Cheung, F., Chen, J., Shi, R., Zhou, H., Wang, E., Tsang, J. S., Nussenblatt, R. B., et al. (2016) · Scientific Reports · doi:10.1038/srep23002 · Cited by 172
MEF2B Instructs Germinal Center Development and Acts as an Oncogene in B Cell Lymphomagenesis
Brescia, P., Schneider, C., Holmes, A. B., Shen, Q. “., Hussein, S., Pasqualucci, L., Basso, K., & Dalla‐Favera, R. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.08.006 · Cited by 114
Miles, D. W., Gligorov, J., André, F., Cameron, D., Schneeweiß, A., Barrios, C. H., Xu, B., Wardley, A. M., Kaen, D. L., Andrade, L., et al. (2020) · Annals of Oncology · doi:10.1016/j.annonc.2020.08.2243 · Cited by 98
Self-citationPeperzak, V., Veraar, E. A. M., Xiao, Y., Bąbała, N., Thiadens, K. A. M. H., Brugmans, M., & Borst, J. G. (2013) · The Journal of Immunology · doi:10.4049/jimmunol.1202222 · Cited by 86
Challenges and Opportunities in Adapting Clinical Trial Design for Immunotherapies
Siu, L. L., Ivy, S. P., Dixon, E. L., Gravell, A. E., Reeves, S. A., & Rosner, G. L. (2017) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-3079 · Cited by 75
Qu, Y., Wen, J., Thomas, G. D., Yang, W., Prior, W., He, W., Sundar, P. D., Wang, X., Potluri, S., & Salek‐Ardakani, S. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108115 · Cited by 75
Qu, Y., Wen, J., Thomas, G. D., Yang, W., Prior, W., He, W., Sundar, P. D., Wang, X., Potluri, S., & Salek‐Ardakani, S. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107873 · Cited by 67
Wilczynska, A., Gillen, S. L., Schmidt, T., Meijer, H. A., Jukes-Jones, R., Langlais, C., Kopra, K., Lu, W.-T., Godfrey, J. D., Hawley, B. R., et al. (2019) · Genome Biology · doi:10.1186/s13059-019-1857-2 · Cited by 62
Litchfield, K., Reading, J. L., McGranahan, N., Quezada, S. A., & Swanton, C. (2020) · Annals of Oncology · doi:10.1016/j.annonc.2020.08.1321 · Cited by 4
Flagged first, then by citations
Cited by
Sorted by citations
Deciphering breast cancer: from biology to the clinic
Nolan, E., Lindeman, G. J., & Visvader, J. E. (2023) · Cell · doi:10.1016/j.cell.2023.01.040 · Cited by 792
Clinical relevance of tumour-associated macrophages
Pittet, M. J., Michielin, O. A., & Migliorini, D. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-022-00620-6 · Cited by 793
Long, Y., Ang, K. S., Li, M., Chong, K. L. K., Sethi, R., Zhong, C., Xu, H., Ong, Z., Sachaphibulkij, K., Chen, A., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36796-3 · Cited by 700
Fridman, W. H., Meylan, M., Petitprez, F., Sun, C., Italiano, A., & Sautès‐Fridman, C. (2022) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-022-00619-z · Cited by 710
Pan-cancer T cell atlas links a cellular stress response state to immunotherapy resistance
Chu, Y., Dai, E., Li, Y., Han, G., Pei, G., Ingram, D. R., Thakkar, K., Qin, J., Dang, M., Le, X., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02371-y · Cited by 518
Metadata
- Authors
- Zhang, Y., Chen, H., Mo, H., Hu, X., Gao, R., Zhao, Y., Liu, B., Niu, L., Sun, X., Yu, X., Wang, Y., Chang, Q., Gong, T., Guan, X., Hu, T., Qian, T., Xu, B., Ma, F., Zhang, Z., & Liu, Z.
- Affiliations
- Peking University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Cancer Hospital of Huanxing Chaoyang District Beijing (CN)
- Corresponding author
- Xu, Binghe
- Ma, Fei
- Zhang, Zemin
- Liu, Zhihua
- ORCID
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 39
- Issue
- 12
- Pages
- 1578-1593.e8
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W3205385275
- Cited by
- 783
- References
- 77
- Citations by year
- 2026: 135 · 2025: 206 · 2024: 183 · 2023: 158 · 2022: 93 · 2021: 8
- FWCI
- 41.16
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cancer Cell (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (31991171, 81988101, 82030089, 91942307)
- Chinese Academy of Meteorological Sciences (2016-I2M-1-001, 2017-I2M-3-004, 2019-I2M-1-003)
- Peking University
- Beijing Municipal Science and Technology Commission (Z201100005320014)
- National Key Research and Development Program of China (2018YFC1312101, 2020YFA0803300)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Life Sciences › Immunology and Microbiology › Immunology › Immune cells in cancer
- Keywords
- triple-negative breast cancer, PD-L1 blockade, atezolizumab, paclitaxel, immune cell dynamics, lymphoid tissue inducer cells, follicular B cells, conventional type 1 dendritic cells, single-cell RNA sequencing, single-cell ATAC-seq
- MeSH terms
- Immune Checkpoint Inhibitors, Female, Humans, Single-Cell Analysis, Triple Negative Breast Neoplasms
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
