Abstract
Immune-checkpoint inhibitors (ICIs) have improved clinical outcomes across several solid tumour types. Prominent efforts have focused on understanding the anticancer mechanisms of these agents, identifying biomarkers of response and uncovering resistance mechanisms to develop new immunotherapeutic approaches. This research has underscored the crucial roles of the tumour microenvironment and, particularly, tumour-infiltrating lymphocytes (TILs) in immune-mediated tumour elimination. Numerous studies have evaluated the prognostic and predictive value of TILs and the mechanisms that govern T cell dysfunction, fuelled by technical developments in single-cell transcriptomics, proteomics, high-dimensional spatial platforms and advanced computational models. However, questions remain regarding the definition of TILs, optimal strategies to study them, specific roles of different TIL subpopulations and their clinical implications in different treatment contexts. Additionally, most studies have focused on the abundance of major TIL subpopulations but have not developed standardized quantification strategies or analysed other crucial aspects such as their functional profile, spatial distribution and/or arrangement, tumour antigen-reactivity, clonal diversity and heterogeneity. In this Review, we discuss a conceptual framework for the systematic study of TILs and summarize the evidence regarding their biological properties and biomarker potential for ICI therapy. We also highlight opportunities, challenges and strategies to support future developments in this field.
Key points
-
A clear and widely accepted definition of tumour-infiltrating lymphocytes (TILs) has not yet been established and TILs are not systematically used as biomarkers in current oncology practice.
-
TILs comprise a spectrum of numerous lymphocyte subsets with dissimilar abundance, functional states, marker profiles, antigen specificity, clonal expansion, spatial distribution and dynamics; resolving the relative contribution of different TIL features and/or integration of these diverse parameters is key to exploiting their clinical value.
-
Cytotoxic T cells mediate tumour elimination induced by immune-checkpoint inhibitors (ICIs), the role of other T cell subsets and B cells in the recognition and eradication of malignant cells is less clear.
-
The abundance of intratumoural T cells and/or B cells (typically forming tertiary lymphoid structures) is positively associated with prognosis across most solid tumour types and might be predictive of sensitivity to ICIs and other immunotherapies.
-
The functional (or dysfunctional) profile of TILs determines their capacity to eliminate cancer cells and has prominent biomarker potential. Spatial features of TILs such as their location within the tumour microenvironment, distribution and/or clustering, infiltration patterns and topographical heterogeneity can also affect their biological responses, association with immunotherapy outcomes and might inform therapeutic avenues.
-
The application of modern technologies such as multiparametric single-cell molecular analysis, spatially resolved immunoprofiling tools and deep learning or other artificial intelligence platforms is redefining our understanding of the composition and analysis of TILs.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
24,99 € / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
195,33 € per year
only 16,28 € per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Balkwill, F. & Mantovani, A. Inflammation and cancer: back to Virchow? Lancet 357, 539–545 (2001).
Clemente, C. G. et al. Prognostic value of tumor infiltrating lymphocytes in the vertical growth phase of primary cutaneous melanoma. Cancer 77, 1303–1310 (1996).
Galon, J. et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313, 1960–1964 (2006).
Zou, W. & Chen, L. Inhibitory B7-family molecules in the tumour microenvironment. Nat. Rev. Immunol. 8, 467–477 (2008).
Elder, D. E., Massi, D., Scolyer, R. A. & Willemze, R. (eds) WHO Classification of Skin Tumours 4th edn, Vol. 11 (WHO, 2018).
WHO Classification of Tumours Editorial Board. Digestive System Tumours 5th edn, Vol. 1 (WHO, 2019).
Salgado, R. et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann. Oncol. 26, 259–271 (2015).
Salgado, R. & AbdulJabbar, K. Artificial intelligence biomarkers for digital oncology: a case study of tumor-infiltrating lymphocytes in melanoma. EBioMedicine 96, 104796 (2023).
Fridman, W. H., Zitvogel, L., Sautes-Fridman, C. & Kroemer, G. The immune contexture in cancer prognosis and treatment. Nat. Rev. Clin. Oncol. 14, 717–734 (2017).
Petitprez, F., Meylan, M., de Reynies, A., Sautes-Fridman, C. & Fridman, W. H. The tumor microenvironment in the response to immune checkpoint blockade therapies. Front. Immunol. 11, 784 (2020).
Bruni, D., Angell, H. K. & Galon, J. The immune contexture and Immunoscore in cancer prognosis and therapeutic efficacy. Nat. Rev. Cancer 20, 662–680 (2020).
Paijens, S. T., Vledder, A., de Bruyn, M. & Nijman, H. W. Tumor-infiltrating lymphocytes in the immunotherapy era. Cell Mol. Immunol. 18, 842–859 (2021).
Lowery, F. J. et al. Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers. Science 375, 877–884 (2022).
Klein, S. et al. Tumor infiltrating lymphocyte clusters are associated with response to immune checkpoint inhibition in BRAF V600E/K mutated malignant melanomas. Sci. Rep. 11, 1834 (2021).
Wong, P. F. et al. Multiplex quantitative analysis of tumor-infiltrating lymphocytes and immunotherapy outcome in metastatic melanoma. Clin. Cancer Res. 25, 2442–2449 (2019).
Petitprez, F. et al. B cells are associated with survival and immunotherapy response in sarcoma. Nature 577, 556–560 (2020).
Keung, E. Z. et al. Correlative analyses of the SARC028 trial reveal an association between sarcoma-associated immune infiltrate and response to pembrolizumab. Clin. Cancer Res. 26, 1258–1266 (2020).
Ayers, M. et al. IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade. J. Clin. Invest. 127, 2930–2940 (2017).
Kurtulus, S. et al. Checkpoint blockade immunotherapy induces dynamic changes in PD-1− CD8+ tumor-infiltrating T cells. Immunity 50, 181–194 (2019).
Lopez de Rodas, M. et al. Role of tumor infiltrating lymphocytes and spatial immune heterogeneity in sensitivity to PD-1 axis blockers in non-small cell lung cancer. J. Immunother. Cancer https://doi.org/10.1136/jitc-2021-004440 (2022).
Hendry, S. et al. Assessing tumor-infiltrating lymphocytes in solid tumors: a practical review for pathologists and proposal for a standardized method from the International Immunooncology Biomarkers Working Group: part 1: assessing the host immune response, TILs in invasive breast carcinoma and ductal carcinoma in situ, metastatic tumor deposits and areas for further research. Adv. Anat. Pathol. 24, 235–251 (2017).
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V. & Madabhushi, A. Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology. Nat. Rev. Clin. Oncol. 16, 703–715 (2019).
Corredor, G. et al. Spatial architecture and arrangement of tumor-infiltrating lymphocytes for predicting likelihood of recurrence in early-stage non-small cell lung cancer. Clin. Cancer Res. 25, 1526–1534 (2019).
Saltz, J. et al. Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images. Cell Rep. 23, 181–193 (2018).
Harder, N. et al. Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma. Sci. Rep. 9, 7449 (2019).
Li, T. et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 48, W509–W514 (2020).
Newman, A. M. et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat. Biotechnol. 37, 773–782 (2019).
June, C. H., O’Connor, R. S., Kawalekar, O. U., Ghassemi, S. & Milone, M. C. CAR T cell immunotherapy for human cancer. Science 359, 1361–1365 (2018).
Leko, V. & Rosenberg, S. A. Identifying and targeting human tumor antigens for T cell-based immunotherapy of solid tumors. Cancer Cell 38, 454–472 (2020).
Rohaan, M. W., Wilgenhof, S. & Haanen, J. Adoptive cellular therapies: the current landscape. Virchows Arch. 474, 449–461 (2019).
Milone, M. C. et al. Engineering enhanced CAR T-cells for improved cancer therapy. Nat. Cancer 2, 780–793 (2021).
Provencio, M. et al. Neoadjuvant chemotherapy and nivolumab in resectable non-small-cell lung cancer (NADIM): an open-label, multicentre, single-arm, phase 2 trial. Lancet Oncol. 21, 1413–1422 (2020).
Emens, L. A. et al. Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer: biomarker evaluation of the IMpassion130 Study. J. Natl Cancer Inst. 113, 1005–1016 (2021).
Brummel, K., Eerkens, A. L., de Bruyn, M. & Nijman, H. W. Tumour-infiltrating lymphocytes: from prognosis to treatment selection. Br. J. Cancer 128, 451–458 (2023).
Hegi-Johnson, F. et al. Imaging immunity in patients with cancer using positron emission tomography. NPJ Precis. Oncol. 6, 24 (2022).
Sabdyusheva Litschauer, I. et al. 3D histopathology of human tumours by fast clearing and ultramicroscopy. Sci. Rep. 10, 17619 (2020).
Uhlen, P. & Tanaka, N. Improved pathological examination of tumors with 3D light-sheet microscopy. Trends Cancer 4, 337–341 (2018).
Simoni, Y. et al. Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates. Nature 557, 575–579 (2018).
Thommen, D. S. et al. A transcriptionally and functionally distinct PD-1+ CD8+ T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade. Nat. Med. 24, 994–1004 (2018).
Li, H. et al. Dysfunctional CD8 T cells form a proliferative, dynamically regulated compartment within human melanoma. Cell 176, 775–789 (2019).
Lee, Y. J. et al. CD39+ tissue-resident memory CD8+ T cells with a clonal overlap across compartments mediate antitumor immunity in breast cancer. Sci. Immunol. 7, eabn8390 (2022).
Krieg, C. et al. High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nat. Med. 24, 144–153 (2018).
Beyrend, G. et al. PD-L1 blockade engages tumor-infiltrating lymphocytes to co-express targetable activating and inhibitory receptors. J. Immunother. Cancer 7, 217 (2019).
Lu, S. et al. Comparison of biomarker modalities for predicting response to PD-1/PD-L1 checkpoint blockade: a systematic review and meta-analysis. JAMA Oncol. 5, 1195–1204 (2019).
Hudson, W. H. & Sudmeier, L. J. Localization of T cell clonotypes using the Visium spatial transcriptomics platform. Star. Protoc. 3, 101391 (2022).
Liu, S. et al. Spatial maps of T cell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response. Immunity 55, 1940–1952 (2022).
Gao, J. et al. Neoadjuvant PD-L1 plus CTLA-4 blockade in patients with cisplatin-ineligible operable high-risk urothelial carcinoma. Nat. Med. 26, 1845–1851 (2020).
Loupakis, F. et al. Prediction of benefit from checkpoint inhibitors in mismatch repair deficient metastatic colorectal cancer: role of tumor infiltrating lymphocytes. Oncologist 25, 481–487 (2020).
Mastracci, L. et al. Response to ipilimumab therapy in metastatic melanoma patients: potential relevance of CTLA-4+ tumor infiltrating lymphocytes and their in situ localization. Cancer Immunol. Immunother. 69, 653–662 (2020).
Datar, I. et al. Expression analysis and significance of PD-1, LAG-3, and TIM-3 in human non-small cell lung cancer using spatially resolved and multiparametric single-cell analysis. Clin. Cancer Res. 25, 4663–4673 (2019).
Gettinger, S. N. et al. A dormant TIL phenotype defines non-small cell lung carcinomas sensitive to immune checkpoint blockers. Nat. Commun. 9, 3196 (2018).
Sanmamed, M. F. et al. A burned-out CD8+ T-cell subset expands in the tumor microenvironment and curbs cancer immunotherapy. Cancer Discov. 11, 1700–1715 (2021).
Sade-Feldman, M. et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 175, 998–1013 (2018).
Schad, S. E. et al. Tumor-induced double positive T cells display distinct lineage commitment mechanisms and functions. J. Exp. Med. https://doi.org/10.1084/jem.20212169 (2022).
Chaput, N. et al. Identification of CD8+ CD25+ Foxp3+ suppressive T cells in colorectal cancer tissue. Gut 58, 520–529 (2009).
Ruf, B. et al. Activating mucosal-associated invariant T cells induces a broad antitumor response. Cancer Immunol. Res. 9, 1024–1034 (2021).
Mauri, C. & Menon, M. The expanding family of regulatory B cells. Int. Immunol. 27, 479–486 (2015).
Monette, A. et al. Biomarker development for PD-(L)1 axis inhibition: a consensus view from the SITC Biomarkers Committee. J. Immunother. Cancer https://doi.org/10.1136/jitc-2024-009427 (2024).
Vikas, P. et al. Mismatch repair and microsatellite instability testing for immune checkpoint inhibitor therapy: ASCO endorsement of College of American Pathologists guideline. J. Clin. Oncol. 41, 1943–1948 (2023).
US Food & Drug Administration. Approval package for ipilimumab. FDA https://www.accessdata.fda.gov/drugsatfda_docs/nda/2011/125377Orig1s000Approv.pdf (2011).
US Food & Drug Administration. Clinical pharmacology and biopharmaceutics review for pembrolizumab. FDA https://www.accessdata.fda.gov/drugsatfda_docs/nda/2014/125514Orig1s000ClinPharmR.pdf?form=MG0AV3 (2014).
Sharma, P. et al. Immune checkpoint therapy-current perspectives and future directions. Cell 186, 1652–1669 (2023).
US Food & Drug Administration. FDA approves Opdualag for unresectable or metastatic melanoma. FDA https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-opdualag-unresectable-or-metastatic-melanoma?form=MG0AV3 (2022).
Haslam, A. & Prasad, V. Estimation of the percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs. JAMA Netw. Open. 2, e192535 (2019).
Lei, Y., Li, X., Huang, Q., Zheng, X. & Liu, M. Progress and challenges of predictive biomarkers for immune checkpoint blockade. Front. Oncol. 11, 617335 (2021).
Jardim, D. L., Goodman, A., de Melo Gagliato, D. & Kurzrock, R. The challenges of tumor mutational burden as an immunotherapy biomarker. Cancer Cell 39, 154–173 (2021).
Davis, A. A. & Patel, V. G. The role of PD-L1 expression as a predictive biomarker: an analysis of all US Food and Drug Administration (FDA) approvals of immune checkpoint inhibitors. J. Immunother. Cancer 7, 278 (2019).
Aguiar, P. N. Jr. et al. The role of PD-L1 expression as a predictive biomarker in advanced non-small-cell lung cancer: a network meta-analysis. Immunotherapy 8, 479–488 (2016).
Mehra, R. et al. Efficacy and safety of pembrolizumab in recurrent/metastatic head and neck squamous cell carcinoma: pooled analyses after long-term follow-up in KEYNOTE-012. Br. J. Cancer 119, 153–159 (2018).
Herbst, R. S. et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 515, 563–567 (2014).
Taube, J. M. et al. Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci. Transl. Med. 4, 127ra137 (2012).
Topalian, S. L. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2454 (2012).
Li, K., Luo, H., Huang, L., Luo, H. & Zhu, X. Microsatellite instability: a review of what the oncologist should know. Cancer Cell Int. 20, 16 (2020).
Bredel, D. et al. Immune checkpoints are predominantly co-expressed by clonally expanded CD4+ FoxP3+ intratumoral T-cells in primary human cancers. J. Exp. Clin. Cancer Res. 42, 333 (2023).
Erdag, G. et al. Immunotype and immunohistologic characteristics of tumor-infiltrating immune cells are associated with clinical outcome in metastatic melanoma. Cancer Res. 72, 1070–1080 (2012).
Gide, T. N. et al. Close proximity of immune and tumor cells underlies response to anti-PD-1 based therapies in metastatic melanoma patients. Oncoimmunology 9, 1659093 (2020).
Hamid, O. et al. Safety, clinical activity, and biological correlates of response in patients with metastatic melanoma: results from a phase I trial of atezolizumab. Clin. Cancer Res. 25, 6061–6072 (2019).
Amaria, R. N. et al. Neoadjuvant immune checkpoint blockade in high-risk resectable melanoma. Nat. Med. 24, 1649–1654 (2018).
Uryvaev, A., Passhak, M., Hershkovits, D., Sabo, E. & Bar-Sela, G. The role of tumor-infiltrating lymphocytes (TILs) as a predictive biomarker of response to anti-PD1 therapy in patients with metastatic non-small cell lung cancer or metastatic melanoma. Med. Oncol. 35, 25 (2018).
Cabrita, R. et al. Tertiary lymphoid structures improve immunotherapy and survival in melanoma. Nature 577, 561–565 (2020).
van Duin, I. A. J. et al. Baseline tumor-infiltrating lymphocyte patterns and response to immune checkpoint inhibition in metastatic cutaneous melanoma. Eur. J. Cancer 208, 114190 (2024).
Balatoni, T. et al. Tumor-infiltrating immune cells as potential biomarkers predicting response to treatment and survival in patients with metastatic melanoma receiving ipilimumab therapy. Cancer Immunol. Immunother. 67, 141–151 (2018).
Chen, P. L. et al. Analysis of immune signatures in longitudinal tumor samples yields insight into biomarkers of response and mechanisms of resistance to immune checkpoint blockade. Cancer Discov. 6, 827–837 (2016).
Tumeh, P. C. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568–571 (2014).
Prat, A. et al. Immune-related gene expression profiling after PD-1 blockade in non-small cell lung carcinoma, head and neck squamous cell carcinoma, and melanoma. Cancer Res. 77, 3540–3550 (2017).
Madonna, G. et al. PD-L1 expression with immune-infiltrate evaluation and outcome prediction in melanoma patients treated with ipilimumab. Oncoimmunology 7, e1405206 (2018).
Daud, A. I. et al. Tumor immune profiling predicts response to anti-PD-1 therapy in human melanoma. J. Clin. Invest. 126, 3447–3452 (2016).
Helmink, B. A. et al. B cells and tertiary lymphoid structures promote immunotherapy response. Nature 577, 549–555 (2020).
Homet Moreno, B. et al. Response to programmed cell death-1 blockade in a murine melanoma syngeneic model requires costimulation, CD4, and CD8 T Cells. Cancer Immunol. Res. 4, 845–857 (2016).
Fumet, J. D. et al. Prognostic and predictive role of CD8 and PD-L1 determination in lung tumor tissue of patients under anti-PD-1 therapy. Br. J. Cancer 119, 950–960 (2018).
Hashemi, S. et al. Surprising impact of stromal TIL’s on immunotherapy efficacy in a real-world lung cancer study. Lung Cancer 153, 81–89 (2021).
Niemeijer, A. N. et al. Association of tumour and stroma PD-1, PD-L1, CD3, CD4 and CD8 expression with DCB and OS to nivolumab treatment in NSCLC patients pre-treated with chemotherapy. Br. J. Cancer 123, 392–402 (2020).
Hurkmans, D. P. et al. Tumor mutational load, CD8+ T cells, expression of PD-L1 and HLA class I to guide immunotherapy decisions in NSCLC patients. Cancer Immunol. Immunother. 69, 771–777 (2020).
Hu-Lieskovan, S. et al. Tumor characteristics associated with benefit from pembrolizumab in advanced non-small cell lung cancer. Clin. Cancer Res. 25, 5061–5068 (2019).
Kaira, K. et al. Prognostic significance of tumor infiltrating lymphocytes on first-line pembrolizumab efficacy in advanced non-small cell lung cancer. Discov. Oncol. 14, 6 (2023).
Rakaee, M. et al. Association of machine learning-based assessment of tumor-infiltrating lymphocytes on standard histologic images with outcomes of immunotherapy in patients with NSCLC. JAMA Oncol. 9, 51–60 (2023).
Althammer, S. et al. Automated image analysis of NSCLC biopsies to predict response to anti-PD-L1 therapy. J. Immunother. Cancer 7, 121 (2019).
Schalper, K. A. et al. Objective measurement and clinical significance of TILs in non-small cell lung cancer. J. Natl Cancer Inst. https://doi.org/10.1093/jnci/dju435 (2015).
Velcheti, V. et al. Programmed death ligand-1 expression in non-small cell lung cancer. Lab. Invest. 94, 107–116 (2014).
Cascone, T. et al. Neoadjuvant durvalumab alone or combined with novel immuno-oncology agents in resectable lung cancer: the phase II NeoCOAST platform trial. Cancer Discov. 13, 2394–2411 (2023).
Cascone, T. et al. Neoadjuvant chemotherapy plus nivolumab with or without ipilimumab in operable non-small cell lung cancer: the phase 2 platform NEOSTAR trial. Nat. Med. 29, 593–604 (2023).
Emens, L. A. et al. Long-term clinical outcomes and biomarker analyses of atezolizumab therapy for patients with metastatic triple-negative breast cancer: a phase 1 study. JAMA Oncol. 5, 74–82 (2019).
Voorwerk, L. et al. Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial. Nat. Med. 25, 920–928 (2019).
Bachelot, T. et al. Durvalumab compared to maintenance chemotherapy in metastatic breast cancer: the randomized phase II SAFIR02-BREAST IMMUNO trial. Nat. Med. 27, 250–255 (2021).
Adams, S. et al. Atezolizumab plus nab-paclitaxel in the treatment of metastatic triple-negative breast cancer with 2-year survival follow-up: a phase 1b clinical trial. JAMA Oncol. 5, 334–342 (2019).
Dieci, M. V. et al. Neoadjuvant chemotherapy and immunotherapy in luminal B-like breast cancer: results of the phase II GIADA trial. Clin. Cancer Res. 28, 308–317 (2022).
Andre, T. et al. Pembrolizumab in microsatellite-instability-high advanced colorectal cancer. N. Engl. J. Med. 383, 2207–2218 (2020).
Le, D. T. et al. PD-1 blockade in tumors with mismatch-repair deficiency. N. Engl. J. Med. 372, 2509–2520 (2015).
Rosenberg, J. E. et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet 387, 1909–1920 (2016).
Deng, B. et al. CD8 lymphocytes in tumors and nonsynonymous mutational load correlate with prognosis of bladder cancer patients treated with immune checkpoint inhibitors. Cancer Rep. 1, e1002 (2018).
Mariathasan, S. et al. TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature 554, 544–548 (2018).
Wang, L. et al. EMT- and stroma-related gene expression and resistance to PD-1 blockade in urothelial cancer. Nat. Commun. 9, 3503 (2018).
Powles, T. et al. Clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial. Nat. Med. 25, 1706–1714 (2019).
van Dijk, N. et al. Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer: the NABUCCO trial. Nat. Med. 26, 1839–1844 (2020).
Pignon, J. C. et al. irRECIST for the evaluation of candidate biomarkers of response to nivolumab in metastatic clear cell renal cell carcinoma: analysis of a phase II prospective clinical trial. Clin. Cancer Res. 25, 2174–2184 (2019).
Ficial, M. et al. Expression of T-cell exhaustion molecules and human endogenous retroviruses as predictive biomarkers for response to nivolumab in metastatic clear cell renal cell carcinoma. Clin. Cancer Res. 27, 1371–1380 (2021).
Motzer, R. J. et al. Avelumab plus axitinib versus sunitinib in advanced renal cell carcinoma: biomarker analysis of the phase 3 JAVELIN Renal 101 trial. Nat. Med. 26, 1733–1741 (2020).
Braun, D. A. et al. Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma. Nat. Med. 26, 909–918 (2020).
Hanna, G. J. et al. Frameshift events predict anti-PD-1/L1 response in head and neck cancer. JCI Insight https://doi.org/10.1172/jci.insight.98811 (2018).
Hecht, M. et al. Safety and efficacy of single cycle induction treatment with cisplatin/docetaxel/ durvalumab/tremelimumab in locally advanced HNSCC: first results of CheckRad-CD8. J. Immunother. Cancer https://doi.org/10.1136/jitc-2020-001378 (2020).
Vanhersecke, L. et al. Mature tertiary lymphoid structures predict immune checkpoint inhibitor efficacy in solid tumors independently of PD-L1 expression. Nat. Cancer 2, 794–802 (2021).
Tong, G. et al. Intratumoral CD8+ T cells as a potential positive predictor of chemoimmunotherapy response in PD-L1-negative advanced gastric cancer patients: a retrospective cohort study. J. Gastrointest. Oncol. 13, 1668–1678 (2022).
Kato, K. et al. Long-term efficacy and predictive correlates of response to nivolumab in Japanese patients with esophageal cancer. Cancer Sci. 111, 1676–1684 (2020).
Tay, R. E., Richardson, E. K. & Toh, H. C. Revisiting the role of CD4+ T cells in cancer immunotherapy-new insights into old paradigms. Cancer Gene Ther. 28, 5–17 (2021).
Bennett, S. R., Carbone, F. R., Karamalis, F., Miller, J. F. & Heath, W. R. Induction of a CD8+ cytotoxic T lymphocyte response by cross-priming requires cognate CD4+ T cell help. J. Exp. Med. 186, 65–70 (1997).
Theisen, D. & Murphy, K. The role of cDC1s in vivo: CD8 T cell priming through cross-presentation. F1000Res 6, 98 (2017).
Agarwal, P. et al. Gene regulation and chromatin remodeling by IL-12 and type I IFN in programming for CD8 T cell effector function and memory. J. Immunol. 183, 1695–1704 (2009).
Oh, S. et al. IL-15 as a mediator of CD4+ help for CD8+ T cell longevity and avoidance of TRAIL-mediated apoptosis. Proc. Natl Acad. Sci. USA 105, 5201–5206 (2008).
Bedoui, S., Heath, W. R. & Mueller, S. N. CD4+ T-cell help amplifies innate signals for primary CD8+ T-cell immunity. Immunol. Rev. 272, 52–64 (2016).
Cui, C. et al. Neoantigen-driven B cell and CD4 T follicular helper cell collaboration promotes anti-tumor CD8 T cell responses. Cell 184, 6101–6118 (2021).
Walker, L. S. & Sansom, D. M. The emerging role of CTLA4 as a cell-extrinsic regulator of T cell responses. Nat. Rev. Immunol. 11, 852–863 (2011).
Vignali, D. A., Collison, L. W. & Workman, C. J. How regulatory T cells work. Nat. Rev. Immunol. 8, 523–532 (2008).
Rudensky, A. Y. Regulatory T cells and Foxp3. Immunol. Rev. 241, 260–268 (2011).
Peggs, K. S., Quezada, S. A., Chambers, C. A., Korman, A. J. & Allison, J. P. Blockade of CTLA-4 on both effector and regulatory T cell compartments contributes to the antitumor activity of anti-CTLA-4 antibodies. J. Exp. Med. 206, 1717–1725 (2009).
Sharma, A. et al. Anti-CTLA-4 immunotherapy does not deplete FOXP3+ regulatory T cells (Tregs) in human cancers. Clin. Cancer Res. 25, 1233–1238 (2019).
Italiano, A. et al. Pembrolizumab in soft-tissue sarcomas with tertiary lymphoid structures: a phase 2 PEMBROSARC trial cohort. Nat. Med. 28, 1199–1206 (2022).
Fridman, W. H. et al. B cells and tertiary lymphoid structures as determinants of tumour immune contexture and clinical outcome. Nat. Rev. Clin. Oncol. 19, 441–457 (2022).
Cyster, J. G. & Allen, C. D. C. B cell responses: cell interaction dynamics and decisions. Cell 177, 524–540 (2019).
Liu, B. et al. Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer. Nat. Cancer 3, 108–121 (2022).
Shen, P. & Fillatreau, S. Antibody-independent functions of B cells: a focus on cytokines. Nat. Rev. Immunol. 15, 441–451 (2015).
Patil, N. S. et al. Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer. Cancer Cell 40, 289–300 (2022).
Cottrell, T. R. et al. Pathologic features of response to neoadjuvant anti-PD-1 in resected non-small-cell lung carcinoma: a proposal for quantitative immune-related pathologic response criteria (irPRC). Ann. Oncol. 29, 1853–1860 (2018).
Sun, X. et al. Maturation and abundance of tertiary lymphoid structures are associated with the efficacy of neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer. J. Immunother. Cancer https://doi.org/10.1136/jitc-2022-005531 (2022).
Hammerl, D. et al. Spatial immunophenotypes predict response to anti-PD1 treatment and capture distinct paths of T cell evasion in triple negative breast cancer. Nat. Commun. 12, 5668 (2021).
Liu, Z., Meng, X., Tang, X., Zou, W. & He, Y. Intratumoral tertiary lymphoid structures promote patient survival and immunotherapy response in head neck squamous cell carcinoma. Cancer Immunol. Immunother. 72, 1505–1521 (2023).
Manzo, A., Bombardieri, M., Humby, F. & Pitzalis, C. Secondary and ectopic lymphoid tissue responses in rheumatoid arthritis: from inflammation to autoimmunity and tissue damage/remodeling. Immunol. Rev. 233, 267–285 (2010).
Moyron-Quiroz, J. E. et al. Role of inducible bronchus associated lymphoid tissue (iBALT) in respiratory immunity. Nat. Med. 10, 927–934 (2004).
Morissette, M. C. et al. Persistence of pulmonary tertiary lymphoid tissues and anti-nuclear antibodies following cessation of cigarette smoke exposure. Respir. Res. 15, 49 (2014).
Mosnier, J. F. et al. The intraportal lymphoid nodule and its environment in chronic active hepatitis C: an immunohistochemical study. Hepatology 17, 366–371 (1993).
Zajac, A. J. et al. Viral immune evasion due to persistence of activated T cells without effector function. J. Exp. Med. 188, 2205–2213 (1998).
Schietinger, A. et al. Tumor-specific T cell dysfunction is a dynamic antigen-driven differentiation program initiated early during tumorigenesis. Immunity 45, 389–401 (2016).
Scott-Browne, J. P. et al. Dynamic changes in chromatin accessibility occur in CD8+ T cells responding to viral infection. Immunity 45, 1327–1340 (2016).
van der Leun, A. M., Thommen, D. S. & Schumacher, T. N. CD8+ T cell states in human cancer: insights from single-cell analysis. Nat. Rev. Cancer 20, 218–232 (2020).
Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).
Oliveira, G. et al. Phenotype, specificity and avidity of antitumour CD8+ T cells in melanoma. Nature 596, 119–125 (2021).
Eberhardt, C. S. et al. Functional HPV-specific PD-1+ stem-like CD8 T cells in head and neck cancer. Nature 597, 279–284 (2021).
Caushi, J. X. et al. Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers. Nature 596, 126–132 (2021).
Han, J. et al. Resident and circulating memory T cells persist for years in melanoma patients with durable responses to immunotherapy. Nat. Cancer 2, 300–311 (2021).
Spassova, I. et al. Predominance of central memory T cells with high T-cell receptor repertoire diversity is associated with response to PD-1/PD-L1 inhibition in Merkel cell carcinoma. Clin. Cancer Res. 26, 2257–2267 (2020).
Enamorado, M. et al. Enhanced anti-tumour immunity requires the interplay between resident and circulating memory CD8+ T cells. Nat. Commun. 8, 16073 (2017).
Edwards, J. et al. CD103+ tumor-resident CD8+ T cells are associated with improved survival in immunotherapy-naive melanoma patients and expand significantly during anti-PD-1 treatment. Clin. Cancer Res. 24, 3036–3045 (2018).
Clarke, J. et al. Single-cell transcriptomic analysis of tissue-resident memory T cells in human lung cancer. J. Exp. Med. 216, 2128–2149 (2019).
Corgnac, S. et al. CD103+ CD8+ TRM cells accumulate in tumors of anti-PD-1-responder lung cancer patients and are tumor-reactive lymphocytes enriched with Tc17. Cell Rep. Med. 1, 100127 (2020).
Yeong, J. et al. Intratumoral CD39+ CD8+ T cells predict response to Programmed Cell Death Protein-1 or Programmed Death Ligand-1 blockade in patients with NSCLC. J. Thorac. Oncol. 16, 1349–1358 (2021).
Gide, T. N. et al. Distinct immune cell populations define response to anti-PD-1 monotherapy and anti-PD-1/anti-CTLA-4 combined therapy. Cancer Cell 35, 238–255 (2019).
Siddiqui, I. et al. Intratumoral Tcf1+ PD-1+ CD8+ T cells with stem-like properties promote tumor control in response to vaccination and checkpoint blockade immunotherapy. Immunity 50, 195–211 (2019).
Miller, B. C. et al. Subsets of exhausted CD8+ T cells differentially mediate tumor control and respond to checkpoint blockade. Nat. Immunol. 20, 326–336 (2019).
Chow, A., Perica, K., Klebanoff, C. A. & Wolchok, J. D. Clinical implications of T cell exhaustion for cancer immunotherapy. Nat. Rev. Clin. Oncol. 19, 775–790 (2022).
Zebley, C. C., Zehn, D., Gottschalk, S. & Chi, H. T cell dysfunction and therapeutic intervention in cancer. Nat. Immunol. 25, 1344–1354 (2024).
Li, Y. et al. Novel T cell exhaustion gene signature to predict prognosis and immunotherapy response in thyroid carcinoma from integrated RNA-sequencing analysis. Sci. Rep. 14, 8375 (2024).
Pauken, K. E. et al. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Science 354, 1160–1165 (2016).
Sen, D. R. et al. The epigenetic landscape of T cell exhaustion. Science 354, 1165–1169 (2016).
Abdel-Hakeem, M. S. et al. Epigenetic scarring of exhausted T cells hinders memory differentiation upon eliminating chronic antigenic stimulation. Nat. Immunol. 22, 1008–1019 (2021).
Terranova-Barberio, M. et al. Exhausted T cell signature predicts immunotherapy response in ER-positive breast cancer. Nat. Commun. 11, 3584 (2020).
Cillo, A. R. et al. Blockade of LAG-3 and PD-1 leads to co-expression of cytotoxic and exhaustion gene modules in CD8+ T cells to promote antitumor immunity. Cell 187, 4373–4388 (2024).
Connolly, K. A. et al. A reservoir of stem-like CD8+ T cells in the tumor-draining lymph node preserves the ongoing antitumor immune response. Sci. Immunol. 6, eabg7836 (2021).
Spitzer, M. H. et al. Systemic immunity is required for effective cancer immunotherapy. Cell 168, 487–502 (2017).
Wu, T. D. et al. Peripheral T cell expansion predicts tumour infiltration and clinical response. Nature 579, 274–278 (2020).
Miggelbrink, A. M. et al. CD4 T-cell exhaustion: does it exist and what are its roles in cancer? Clin. Cancer Res. 27, 5742–5752 (2021).
Gajewski, T. F. The next hurdle in cancer immunotherapy: overcoming the non-T-cell-inflamed tumor microenvironment. Semin. Oncol. 42, 663–671 (2015).
Liu, Y. T. & Sun, Z. J. Turning cold tumors into hot tumors by improving T-cell infiltration. Theranostics 11, 5365–5386 (2021).
Chen, D. S. & Mellman, I. Elements of cancer immunity and the cancer-immune set point. Nature 541, 321–330 (2017).
Gajewski, T. F. et al. Cancer immunotherapy targets based on understanding the T cell-inflamed versus non-T cell-inflamed tumor microenvironment. Adv. Exp. Med. Biol. 1036, 19–31 (2017).
Clifton, G. T. et al. Developing a definition of immune exclusion in cancer: results of a modified Delphi workshop. J. Immunother. Cancer https://doi.org/10.1136/jitc-2023-006773 (2023).
Lopez de Rodas, M. et al. Objective analysis and clinical significance of the spatial tumor-infiltrating lymphocyte patterns in non-small cell lung cancer. Clin. Cancer Res. 30, 998–1008 (2024).
Zhang, T. et al. Up-regulated PLA2G10 in cancer impairs T cell infiltration to dampen immunity. Sci. Immunol. 9, eadh2334 (2024).
Francisco-Cruz, A. et al. Analysis of immune intratumor heterogeneity highlights immunoregulatory and coinhibitory lymphocytes as hallmarks of recurrence in stage I non-small cell lung cancer. Mod. Pathol. 36, 100028 (2023).
Chen, J. H. et al. Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy. Nat. Immunol. 25, 644–658 (2024).
Espinosa-Carrasco, G. et al. Intratumoral immune triads are required for immunotherapy-mediated elimination of solid tumors. Cancer Cell 42, 1202–1216 (2024).
Magen, A. et al. Intratumoral dendritic cell-CD4+ T helper cell niches enable CD8+ T cell differentiation following PD-1 blockade in hepatocellular carcinoma. Nat. Med. 29, 1389–1399 (2023).
Scheper, W. et al. Low and variable tumor reactivity of the intratumoral TCR repertoire in human cancers. Nat. Med. 25, 89–94 (2019).
Giraldo, N. A. et al. Orchestration and prognostic significance of immune checkpoints in the microenvironment of primary and metastatic renal cell cancer. Clin. Cancer Res. 21, 3031–3040 (2015).
Gupta, P. K. et al. CD39 expression identifies terminally exhausted CD8+ T cells. PLoS Pathog. 11, e1005177 (2015).
Yossef, R. et al. Phenotypic signatures of circulating neoantigen-reactive CD8+ T cells in patients with metastatic cancers. Cancer Cell 41, 2154–2165 (2023).
Liu, B., Zhang, Y., Wang, D., Hu, X. & Zhang, Z. Single-cell meta-analyses reveal responses of tumor-reactive CXCL13+ T cells to immune-checkpoint blockade. Nat. Cancer 3, 1123–1136 (2022).
Zhang, Y. et al. Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer. Cancer Cell 39, 1578–1593 (2021).
Tscharke, D. C., Croft, N. P., Doherty, P. C. & La Gruta, N. L. Sizing up the key determinants of the CD8+ T cell response. Nat. Rev. Immunol. 15, 705–716 (2015).
Purcarea, A. et al. Signatures of recent activation identify a circulating T cell compartment containing tumor-specific antigen receptors with high avidity. Sci. Immunol. 7, eabm2077 (2022).
Pasetto, A. et al. Tumor- and neoantigen-reactive T-cell receptors can be identified based on their frequency in fresh tumor. Cancer Immunol. Res. 4, 734–743 (2016).
Khunger, A., Rytlewski, J. A., Fields, P., Yusko, E. C. & Tarhini, A. A. The impact of CTLA-4 blockade and interferon-α on clonality of T-cell repertoire in the tumor microenvironment and peripheral blood of metastatic melanoma patients. Oncoimmunology 8, e1652538 (2019).
Yusko, E. et al. Association of tumor microenvironment T-cell repertoire and mutational load with clinical outcome after sequential checkpoint blockade in melanoma. Cancer Immunol. Res. 7, 458–465 (2019).
Inoue, H. et al. Intratumoral expression levels of PD-L1, GZMA, and HLA-A along with oligoclonal T cell expansion associate with response to nivolumab in metastatic melanoma. Oncoimmunology 5, e1204507 (2016).
Roh, W. et al. Integrated molecular analysis of tumor biopsies on sequential CTLA-4 and PD-1 blockade reveals markers of response and resistance. Sci. Transl Med. https://doi.org/10.1126/scitranslmed.aah3560 (2017).
Forde, P. M., Chaft, J. E. & Pardoll, D. M. Neoadjuvant PD-1 blockade in resectable lung cancer. N. Engl. J. Med. 379, e14 (2018).
Schalper, K. A. et al. Neoadjuvant nivolumab modifies the tumor immune microenvironment in resectable glioblastoma. Nat. Med. 25, 470–476 (2019).
Zhong, S. et al. T-cell receptor affinity and avidity defines antitumor response and autoimmunity in T-cell immunotherapy. Proc. Natl Acad. Sci. USA 110, 6973–6978 (2013).
Weiss, V. L. et al. Trafficking of high avidity HER-2/neu-specific T cells into HER-2/neu-expressing tumors after depletion of effector/memory-like regulatory T cells. PLoS ONE 7, e31962 (2012).
Allard, M. et al. TCR-ligand dissociation rate is a robust and stable biomarker of CD8+ T cell potency. JCI Insight https://doi.org/10.1172/jci.insight.92570 (2017).
Martinez-Usatorre, A., Donda, A., Zehn, D. & Romero, P. PD-1 blockade unleashes effector potential of both high- and low-affinity tumor-infiltrating T cells. J. Immunol. 201, 792–803 (2018).
Black, C. M., Armstrong, T. D. & Jaffee, E. M. Apoptosis-regulated low-avidity cancer-specific CD8+ T cells can be rescued to eliminate HER2/neu-expressing tumors by costimulatory agonists in tolerized mice. Cancer Immunol. Res. 2, 307–319 (2014).
Janicki, C. N., Jenkinson, S. R., Williams, N. A. & Morgan, D. J. Loss of CTL function among high-avidity tumor-specific CD8+ T cells following tumor infiltration. Cancer Res. 68, 2993–3000 (2008).
Bos, R., Marquardt, K. L., Cheung, J. & Sherman, L. A. Functional differences between low- and high-affinity CD8+ T cells in the tumor environment. Oncoimmunology 1, 1239–1247 (2012).
Caserta, S., Kleczkowska, J., Mondino, A. & Zamoyska, R. Reduced functional avidity promotes central and effector memory CD4 T cell responses to tumor-associated antigens. J. Immunol. 185, 6545–6554 (2010).
Gettinger, S. et al. Impaired HLA Class I antigen processing and presentation as a mechanism of acquired resistance to immune checkpoint inhibitors in lung cancer. Cancer Discov. 7, 1420–1435 (2017).
Liu, Z. et al. Progenitor-like exhausted SPRY1+ CD8+ T cells potentiate responsiveness to neoadjuvant PD-1 blockade in esophageal squamous cell carcinoma. Cancer Cell 41, 1852–1870 (2023).
Acknowledgements
The work of the authors is supported by NIH grants R37CA245154, R01CA262377, R01CA216579 and P50CA196530.
Author information
Authors and Affiliations
Contributions
M.L.d.R., M.V.-E. and K.A.S. researched data for the article and wrote the manuscript. All authors contributed substantially to discussion of the content and reviewed and/or edited the manuscript before submission.
Corresponding author
Ethics declarations
Competing interests
M.F.S. had received fees for consultancy from Bristol Myers Squibb, MSD, Numab and Roche; and his laboratory has received funding from Bristol Myers Squibb and Roche. L.C. has been a consultant for NextCure, OncoC4, Tcelltech and Zai Lab; is a scientific founder of DynamiCure, NextCure, Normunity and Tcelltech; and his laboratory has received funding from DynamiCure, NextCure and Normunity. D.L.R. has served as an adviser for Agendia, Amgen, AstraZeneca, Bristol Myers Squibb, Cell Signalling Technology, Cepheid, Danaher, Daiichi Sankyo, Genoptix/Novartis, GSK, Halda Biotherapeutics, Incendia, Konica Minolta, Merck, NanoString, PAIGE.AI, Perkin Elmer, Roche, Sanofi and Ventana; and his laboratory has received funding from Amgen, Cepheid, Navigate Biopharma, NextCure, Leica and Konica Minolta. K.A.S. has served as a consultant, adviser or speaker for Agenus, AstraZeneca, Bristol Myers Squibb, Clinica Alemana Santiago, CSRlife, Dynamicure, EMD Serono, Forefront Collaborative, Genmab, Indaptus, Merck, Merus, Moderna, Molecular Templates, OnCusp, Parthenon Therapeutics, PeerView, Physicians Education Resource, Roche, Sanofi, Shattuck Labs, Takeda and Torque/Repertoire Therapeutics; and his laboratory has received research funding from Akoya Biosciences, AstraZeneca, Boehringer-Ingelheim, Bristol Myers Squibb, Eli Lilly, Merck, NextPoint Therapeutics, Ribon Therapeutics, Roche, Surface Oncology, Takeda and Tesaro/GSK. M.L.d.R. and M.V.-E. declare no competing interests.
Peer review
Peer review information
Nature Reviews Clinical Oncology thanks M. Donia, C. Haymaker and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Lopez de Rodas, M., Villalba-Esparza, M., Sanmamed, M.F. et al. Biological and clinical significance of tumour-infiltrating lymphocytes in the era of immunotherapy: a multidimensional approach. Nat Rev Clin Oncol 22, 163–181 (2025). https://doi.org/10.1038/s41571-024-00984-x
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41571-024-00984-x