0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Single-cell profiling of response to neoadjuvant chemo-immunotherapy in surgically resectable esophageal squamous cell carcinoma

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The efficacy of neoadjuvant chemo-immunotherapy (NAT) in esophageal squamous cell carcinoma (ESCC) is challenged by the intricate interplay within the tumor microenvironment (TME). Unveiling the immune landscape of ESCC in the context of NAT could shed light on heterogeneity and optimize therapeutic strategies for patients.

          Methods

          We analyzed single cells from 22 baseline and 24 post-NAT treatment samples of stage II/III ESCC patients to explore the association between the immune landscape and pathological response to neoadjuvant anti-PD-1 combination therapy, including pathological complete response (pCR), major pathological response (MPR), and incomplete pathological response (IPR).

          Results

          Single-cell profiling identified 14 major cell subsets of cancer, immune, and stromal cells. Trajectory analysis unveiled an interesting link between cancer cell differentiation and pathological response to NAT. ESCC tumors enriched with less differentiated cancer cells exhibited a potentially favorable pathological response to NAT, while tumors enriched with clusters of more differentiated cancer cells may resist treatment. Deconvolution of transcriptomes in pre-treatment tumors identified gene signatures in response to NAT contributed by specific immune cell populations. Upregulated genes associated with better pathological responses in CD8 + effector T cells primarily involved interferon-gamma (IFNγ) signaling, neutrophil degranulation, and negative regulation of the T cell apoptotic process, whereas downregulated genes were dominated by those in the immune response-activating cell surface receptor signaling pathway. Natural killer cells in pre-treatment tumors from pCR patients showed a similar upregulation of gene expression in response to IFNγ but a downregulation of genes in the neutrophil-mediated immunity pathways. A decreased cellular contexture of regulatory T cells in ESCC TME indicated a potentially favorable pathological response to NAT. Cell–cell communication analysis revealed extensive interactions between CCL5 and its receptor CCR5 in various immune cells of baseline pCR tumors. Immune checkpoint interaction pairs, including CTLA4-CD86, TIGIT-PVR, LGALS9-HAVCR2, and TNFSF4-TNFRSF4, might serve as additional therapeutic targets for ICI therapy in ESCC.

          Conclusions

          This pioneering study unveiled an intriguing association between cancer cell differentiation and pathological response in esophageal cancer patients, revealing distinct subgroups of tumors for which neoadjuvant chemo-immunotherapy might be effective. We also delineated the immune landscape of ESCC tumors in the context of clinical response to NAT, which provides clinical insights for better understanding how patients respond to the treatment and further identifying novel therapeutic targets for ESCC patients in the future.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13073-024-01320-9.

          Related collections

          Most cited references76

          • Record: found
          • Abstract: found
          • Article: not found

          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
                Bookmark

                Author and article information

                Contributors
                jiangtaochest@163.com
                minggao@fmmu.edu.cn
                luqiang@fmmu.edu.cn
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                2 April 2024
                2 April 2024
                2024
                : 16
                : 49
                Affiliations
                [1 ]GRID grid.417295.c, ISNI 0000 0004 1799 374X, Department of Digestive Surgery, , Xijing Hospital, Air Force Medical University, ; No. 169 Changle West Road, Xi’an, 710032 China
                [2 ]GRID grid.460007.5, ISNI 0000 0004 1791 6584, Precision Pharmacy & Drug Development Center, Department of Pharmacy, , Tangdu Hospital, Air Force Medical University, ; No. 569 Xinsi Road, Xi’an, 710038 China
                [3 ]GRID grid.518662.e, Geneseeq Research Institute, Nanjing Geneseeq Technology Inc, ; Nanjing, 210000 Jiangsu China
                [4 ]GRID grid.460007.5, ISNI 0000 0004 1791 6584, Department of Thoracic Surgery, , Tangdu Hospital, Air Force Medical University, ; No. 569 Xinsi Road, Xi’an, 710038 China
                [5 ]GRID grid.460007.5, ISNI 0000 0004 1791 6584, Department of Pathology, , Tangdu Hospital, Air Force Medical University, ; No. 569 Xinsi Road, Xi’an, 710038 China
                [6 ]Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Medical College, ( https://ror.org/00g3pqv36) Xi’an, 710000 China
                Article
                1320
                10.1186/s13073-024-01320-9
                10985969
                c51cbc4e-b0de-4188-a578-cbcb8e29c85a
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 16 June 2023
                : 21 March 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81671233
                Award ID: 81571218
                Award Recipient :
                Funded by: Shaanxi Provincial Key Project of Technological Innovation Guidance
                Award ID: 2021QFY01-03
                Award Recipient :
                Funded by: Major Clinical Research Project of Tangdu Hospital, Air Force Medical University
                Award ID: 2021LCYJ008
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Molecular medicine
                esophageal squamous cell carcinoma,neoadjuvant therapy,single-cell sequencing,pathological response

                Comments

                Comment on this article