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Key Event: 2323

Key Event Title

A descriptive phrase which defines a discrete biological change that can be measured. More help

Over-expression of PD-L1 in cancer cells

Short name
The KE short name should be a reasonable abbreviation of the KE title and is used in labelling this object throughout the AOP-Wiki. More help
Over-expression of PD-L1 in cancer cells
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Biological Context

Structured terms, selected from a drop-down menu, are used to identify the level of biological organization for each KE. More help
Level of Biological Organization
Molecular

Cell term

The location/biological environment in which the event takes place.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help
Cell term
macrophage

Organ term

The location/biological environment in which the event takes place.The biological context describes the location/biological environment in which the event takes place.  For molecular/cellular events this would include the cellular context (if known), organ context, and species/life stage/sex for which the event is relevant. For tissue/organ events cellular context is not applicable.  For individual/population events, the organ context is not applicable.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help

Event Components

The KE, as defined by a set structured ontology terms consisting of a biological process, object, and action with each term originating from one of 14 biological ontologies (Ives, et al., 2017; https://aopwiki.org/info_pages/2/info_linked_pages/7#List). Biological process describes dynamics of the underlying biological system (e.g., receptor signalling).Biological process describes dynamics of the underlying biological system (e.g., receptor signaling).  The biological object is the subject of the perturbation (e.g., a specific biological receptor that is activated or inhibited). Action represents the direction of perturbation of this system (generally increased or decreased; e.g., ‘decreased’ in the case of a receptor that is inhibited to indicate a decrease in the signaling by that receptor).  Note that when editing Event Components, clicking an existing Event Component from the Suggestions menu will autopopulate these fields, along with their source ID and description.  To clear any fields before submitting the event component, use the 'Clear process,' 'Clear object,' or 'Clear action' buttons.  If a desired term does not exist, a new term request may be made via Term Requests.  Event components may not be edited; to edit an event component, remove the existing event component and create a new one using the terms that you wish to add.  Further information on Event Components and Biological Context may be viewed on the attached pdf. More help
Process Object Action
Abnormality of cellular immune system B7-related protein increased

Key Event Overview

AOPs Including This Key Event

All of the AOPs that are linked to this KE will automatically be listed in this subsection. This table can be particularly useful for derivation of AOP networks including the KE.Clicking on the name of the AOP will bring you to the individual page for that AOP. More help
AOP Name Role of event in AOP Point of Contact Author Status OECD Status
AhR activation leading to cancer progression KeyEvent Léo SPORTES-MILOT (send email) Under development: Not open for comment. Do not cite

Taxonomic Applicability

Latin or common names of a species or broader taxonomic grouping (e.g., class, order, family) that help to define the biological applicability domain of the KE.In many cases, individual species identified in these structured fields will be those for which the strongest evidence used in constructing the AOP was available in relation to this KE. More help
Term Scientific Term Evidence Link
human Homo sapiens High NCBI
mouse Mus musculus High NCBI

Life Stages

An indication of the the relevant life stage(s) for this KE. More help
Life stage Evidence
During development and at adulthood High

Sex Applicability

An indication of the the relevant sex for this KE. More help
Term Evidence
Mixed High

Key Event Description

A description of the biological state being observed or measured, the biological compartment in which it is measured, and its general role in the biology should be provided. More help

PD-L1 (Programmed Death-Ligand 1, or B7-H1/CD274) is known to be a promising therapeutic target in the development of anti-tumor treatments. This ligand can be expressed in several forms: cytoplasmic, membrane-bound, soluble, or in extracellular vesicles. Based on current knowledge, the membrane form is the most well-documented, particularly for inhibiting T cell activity (Lin et al., 2024). Its physiological role is to bind to PD1 (or CD279), its receptor on immune cells, giving it an essential immunosuppressive role (Butte et al., 2007). This is why this ligand is well studied for treatment related to immunosuppressive disease (Tomlins et al., 2023).

PD-L1 is a membrane protein belonging to the immunoglobulin family (IgSF). It has two main domains: an N-terminal variable immunoglobulin (IgV) domain and a C-terminal constant immunoglobulin (IgC) domain (Lin et al., 2008) (Jiang et al., 2019). It is the IgV domain that allows interaction with the PD-1 receptor, which is mainly expressed on T lymphocytes but also present in slightly lower levels on B lymphocytes.

In the context of cancer, tumor cells overexpress this ligand, which contributes to immune escape and the establishment of the Tumor MicroEnvironment (TME) (Riella et al., 2012).

How It Is Measured or Detected

A description of the type(s) of measurements that can be employed to evaluate the KE and the relative level of scientific confidence in those measurements.These can range from citation of specific validated test guidelines, citation of specific methods published in the peer reviewed literature, or outlines of a general protocol or approach (e.g., a protein may be measured by ELISA). Do not provide detailed protocols. More help

Multiple validated and widely used methods exist to measure PD-L1 expression on cancer cells :

1. Immunohistochemistry (IHC). This is the most clinically validated and standardized method. Several antibody clones such as 22C3, 28-8, SP142, and SP263, have been approved as companion or complementary diagnostics for anti-PD-L1 immunotherapies and are used routinely on formalin-fixed paraffin-embedded tumour sections (Martinez-Morilla et al., 2021). Expression is quantified as the Tumour Proportion Score (TPS), the percentage of viable tumour cells showing membranous staining, or as the Combined Positive Score (CPS), which also incorporates PD-L1-positive immune cells (Noordhof et al., 2023).

2. Flow cytometry. Used on dissociated tumour tissue or cultured cancer cell lines to quantify cell-surface PD-L1 via fluorochrome-conjugated antibodies; allows co-staining with other markers to characterise the PD-L1⁺ cell subpopulation (Chen et al., 2021) 34211855.

3. Quantitative RT-PCR / RNA sequencing. Used to measure CD274 (PD-L1 gene) mRNA transcript levels; mRNA levels correlate moderately-to-strongly with IHC protein scores (Noordhof et al., 2023).

4. Western blot. Used in cell-line-based mechanistic studies to confirm total cellular PD-L1 protein levels, often alongside pathway-specific inhibitors/activators (e.g., STAT1/STAT3 inhibition) (Alsaab et al., 2019).

5. ELISA (for soluble PD-L1, sPD-L1). Used to measure a shed/secreted form of PD-L1 in serum or culture supernatant as a surrogate, non-invasive biomarker, complementary to tissue-based assays.

Domain of Applicability

A description of the scientific basis for the indicated domains of applicability and the WoE calls (if provided).  More help

PD-L1 overexpression relative to normal tissue has been independently documented in non-small cell lung cancer, melanoma, breast cancer, ovarian cancer, colorectal cancer, hepatocellular carcinoma, prostate cancer, gastric cancer and renal cell carcinoma (Dermani et al., 2019, Kammerer-Jacquet et al., 2019, Payandeh et al., 2020, Matuschewski et al., 2025, Santoni et al., 2020).

The magnitude of overexpression and its clinical or functional threshold varies by tumour type.

References

List of the literature that was cited for this KE description. More help

Alsaab, Hashem O., Samaresh Sau, Rami Alzhrani, et al. 2017. « PD-1 and PD-L1 Checkpoint Signaling Inhibition for Cancer Immunotherapy: Mechanism, Combinations, and Clinical Outcome ». Frontiers in Pharmacology 8: 561. https://doi.org/10.3389/fphar.2017.00561.

Butte, Manish J., Mary E. Keir, Theresa B. Phamduy, Arlene H. Sharpe, et Gordon J. Freeman. 2007. « Programmed Death-1 Ligand 1 Interacts Specifically with the B7-1 Costimulatory Molecule to Inhibit T Cell Responses ». Immunity 27 (1): 11122. https://doi.org/10.1016/j.immuni.2007.05.016.

Chen, Zihang, Xueqin Deng, Yunxia Ye, Wenyan Zhang, Weiping Liu, et Sha Zhao. 2021. « Flow Cytometry-Assessed PD1/PDL1 Status in Tumor-Infiltrating Lymphocytes: A Link With the Prognosis of Diffuse Large B-Cell Lymphoma ». Frontiers in Oncology 11 (juin): 687911. https://doi.org/10.3389/fonc.2021.687911.

Dermani, Fatemeh K., Pouria Samadi, Golebagh Rahmani, Alisa K. Kohlan, et Rezvan Najafi. 2019. « PD-1/PD-L1 Immune Checkpoint: Potential Target for Cancer Therapy ». Journal of Cellular Physiology 234 (2): 131325. https://doi.org/10.1002/jcp.27172.

Jiang, Yongshuai, Ming Chen, Hong Nie, et Yuanyang Yuan. 2019. « PD-1 and PD-L1 in cancer immunotherapy: clinical implications and future considerations ». Human Vaccines & Immunotherapeutics 15 (5): 111122. https://doi.org/10.1080/21645515.2019.1571892.

Kammerer-Jacquet, Solène-Florence, Antoine Deleuze, Judikaël Saout, et al. 2019. « Targeting the PD-1/PD-L1 Pathway in Renal Cell Carcinoma ». International Journal of Molecular Sciences 20 (7): 1692. https://doi.org/10.3390/ijms20071692.

Lin, David Yin-wei, Yoshimasa Tanaka, Masashi Iwasaki, et al. 2008. « The PD-1/PD-L1 complex resembles the antigen-binding Fv domains of antibodies and T cell receptors ». Proceedings of the National Academy of Sciences of the United States of America 105 (8): 301116. https://doi.org/10.1073/pnas.0712278105.

Lin, Xin, Kuan Kang, Pan Chen, et al. 2024. « Regulatory Mechanisms of PD-1/PD-L1 in Cancers ». Molecular Cancer 23 (1): 108. https://doi.org/10.1186/s12943-024-02023-w.

Matuschewski, Nickolai J., Rabea Sobirey, Margarita Revzin, et al. 2025. « Noninvasive Tumor Profiling: Quantitative Contrast-Enhanced MRI Markers Predict PD-L1 and CTNNB1 Status in Hepatocellular Carcinoma ». Radiology 316 (2): e242750. https://doi.org/10.1148/radiol.242750.

Noordhof, A. L., R. a. M. Damhuis, L. E. L. Hendriks, et al. 2021. « Prognostic Impact of KRAS Mutation Status for Patients with Stage IV Adenocarcinoma of the Lung Treated with First-Line Pembrolizumab Monotherapy ». Lung Cancer (Amsterdam, Netherlands) 155 (mai): 16369. https://doi.org/10.1016/j.lungcan.2021.04.001.

Payandeh, Zahra, Saeed Khalili, Mohammad Hossein Somi, et al. 2020. « PD-1/PD-L1-Dependent Immune Response in Colorectal Cancer ». Journal of Cellular Physiology 235 (78): 546175. https://doi.org/10.1002/jcp.29494.

Riella, Leonardo V., Alison M. Paterson, Arlene H. Sharpe, et Anil Chandraker. 2012. « Role of the PD-1 Pathway in the Immune Response ». American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons 12 (10): 257587. https://doi.org/10.1111/j.1600-6143.2012.04224.x.

Santoni, Matteo, Francesco Massari, Liang Cheng, et al. 2020. « PD-L1 Inhibitors for the Treatment of Prostate Cancer ». Current Drug Targets 21 (15): 155865. https://doi.org/10.2174/1389450121666200609142219.

Tomlins, Scott A., Nickolay A. Khazanov, Benjamin J. Bulen, et al. 2023. « Development and Validation of an Integrative Pan-Solid Tumor Predictor of PD-1/PD-L1 Blockade Benefit ». Communications Medicine 3 (1): 14. https://doi.org/10.1038/s43856-023-00243-7.