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Poster Display

422P - CD8Teff distinguished tumor immunotyping heterogeneity and enables precision immunotherapy

Date

02 Dec 2023

Session

Poster Display

Presenters

luhui Mao

Citation

Annals of Oncology (2023) 34 (suppl_4): S1623-S1631. 10.1016/annonc/annonc1387

Authors

L. Mao1, Y. Yu2, C.Y. Jian3, W. Ouyang4, Z. Wang5, R. Lin6, Y. Tan7, W. Ren4, Z. He4, Z. Zhang4, T. li4, H. Yao4

Author affiliations

  • 1 Medical Oncology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 854054 - Guangzhou/CN
  • 2 Medical Oncology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510308 - Guangzhou/CN
  • 3 Dermatology And Venereology Division, Department of Medicine Solna, Center for Molecular Medicine, Karolinska Institutet, Stockholm/SE
  • 4 Medical Oncology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 510120 - Guangzhou/CN
  • 5 Faculty Of Science And Technology, Beijing Normal University-Hong Kong Baptist University United International College, zhuhai/HK
  • 6 School Of Computer And Information Engineering, Guangzhou Huali College, China, Guangzhou/CN
  • 7 Medical Oncology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou/CN

Resources

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Abstract 422P

Background

Tumor patients exhibit distinct immune microenvironments known as cold and hot tumors, with the drug resistance mechanisms of cold tumors remaining less understood. We endeavored to discern the pivotal cells that set apart hot and cold tumors so as to improve the efficacy of immunotherapy by interfering target cells and switching tumor subtypes.

Methods

Single-cell analysis was conducted on tumor tissues and peripheral blood samples collected before neoadjuvant treatment with immune checkpoint inhibitors (ICIs) at Sun Yat-sen Memorial Hospital, Sun Yat-sen University to identify key immune resistance cells. Multi-omics analysis utilizing pan-cancer immunotherapy cohorts was employed to validate the crucial role of CD8Teff in distinguishing hot and cold tumors. Deep learning was further utilized to analyze whole slide images of pathological sections, constructing an artificial intelligence (AI) model for identifying CD8Teff and seamless clinical implementation. Lastly, co-culture involving DC and T cells was employed to verify CD8Teff activation.

Results

CD8Teff was revealed to function as a crucial immunotherapeutic marker by directly determining the hot and cold tumor immune microenvironment. The ICIs sensitivity of hot tumor with high-CD8Teff attributable to activation of the tumor antigen presentation-related pathway and pronounced expression of cytotoxic cytokines CXCL13 and CXCL10. Conversely, the ICIs resistance of cold tumor with low-D8Teff due to escalated activation of angiogenesis and epithelial-mesenchymal transition pathway. The pathology AI model enabled quantitative prediction of CD8Teff and exhibited excellent performance with AUC values of 0.823 and 0.805 in training and validation cohorts. Augmenting CD52+DC expression with CXCL9 or CXCL10 straight activated CD8T transcription factors and elevated CD8Teff cell populations, thus inducing switching from cold to hot tumors.

Conclusions

The multi-omics study has discerned CD8Teff as a critical discriminator characterizing cold and hot tumors. Moreover, the pathological AI quantification of CD8Teff guides ICIs application. Intervening with CD52+DC-CD8T enables directly toggling from cold to hot tumors by activating CD8Teff.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

This study was supported by grants 2023YFE0204000 from National Key R&D Program of China, grants 82273204 and 81972471 from the National Natural Science Foundation of China, grant 2023A1515012412 and 2023A1515011214 GuangDong Basic and Applied Basic Research Foundation, grant 2023A03J0722, 202206010078 and 202201020574 from the Guangzhou Science and Technology Project, grant 2018007 from the Sun Yat-Sen University Clinical Research 5010 Program, grant SYS-C-201801 from the Sun Yat-Sen Clinical Research Cultivating Program, grant A2020558 from the Guangdong Medical Science and Technology Program, grant 7670020025 from Tencent Charity Foundation, grant YXQH202209 from the Sun Yat-sen Pilot Scientific Research Fund.

Disclosure

All authors have declared no conflicts of interest.

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