Immune checkpoint alterations and their blockade in COVID-19 patients : Blood Science

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Review Article

Immune checkpoint alterations and their blockade in COVID-19 patients

Tan, Jiaxionga; Li, Yangqiub,*

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doi: 10.1097/BS9.0000000000000132
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Coronavirus disease 2019 (COVID-19) is a highly contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which can lead to an excessive inflammatory reaction and acute lung injury, leading to respiratory failure or death.1 Studies have shown that immune dysfunction, such as imbalance in the lymphocyte proportion, and the absolute decrease in T cells, which is caused by excessive apoptosis, are important characteristics of severe patients with poor prognosis.2–4 Recently, numerous studies have demonstrated that ICs, which are expressed on immune cells, play an important role in cancer immunosuppression and infectious diseases.5 The dysfunction in immune cells in COVID-19 may be associated with alterations in ICs.

As a “brake” for suppressing the immune system when the body is invaded by tumor antigens or pathogens for a long period of time, immune cells, particularly T/NK cells, pathologically express key ICs such as programmed death 1 (PD-1), cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) and T cell immunoglobin and mucin domain 3 (Tim-3).6–8 When these ICs bind to specific ligands, T cells enter a state of impotent exhaustion, thus inhibiting immune surveillance and clearance.9 IC blockade (ICB) have been widely studied and applied in many types of tumors, such as melanoma, non-small cell lung cancer, lymphoma, and other infectious diseases including hepatitis B virus, human immunodeficiency virus, and cytomegalovirus, and have been shown to significantly improving clinical outcome.10,11

Recently, increasing data have shown that up-regulation of ICs results in dysfunction in NK cells, monocytes, and B cells in patients with COVID-19 (Table 1, Figure 1)2,3 and an increase in specific or soluble ligands in tissue endothelium, antigen-presenting cells (APCs), and plasma (Table 2).12 However, the expression levels of the ICs can be maintained mostly at normal levels in mild non-hospitalized COVID-19 and convalescent patients.49 While, there are also reports indicating that the expression of major co-inhibitory receptors including PD-1, CTLA-4, and T cell immunoglobulin and ITIM domain (TIGIT) is not detected in samples from COVID-19 patients.3,21,25 In addition, it has been reported that the use of anti-PD-1/PD-L1 alone or in combination with anti-CTLA-4 immunotherapy increases the risk of overlapping lung injury and co-morbid mechanisms for COVID-19 in cancer patients.50 Here, we summarized recent research on the distribution characteristics and alterations of ICs in COVID-19 patients and discuss the role and clinical significance of ICB in disease control.

Table 1 - The distribution of immune checkpoints in patients with COVID-19.
ICs Expression Cell type/fluid Performance Sample style Sample size (n) Detection method Area Reference
PD-1 Up NK and T cells Death Lung, kidney 11 DSP, mIHC China 1
Up Plasma Severe case Plasma 109 FCM China 12
Up CD4+ and CD8+ T cells Severe case PB 100 FCM Iran 13
PB 522 FCM China 14
PBMC 76 FCM China 15
Up CD8+T cells Elderly mild cases PB 42 FCM Italy 16
PB 30 FCM Germany 17
Up CXCR3+CD4+ and CCR6+CD8+ T cells Severe cases BALF/PB 22(PB), 9(BALF) FCM Netherlands 18
Up CD57+T and CD38+TCM cells Unknown PB 39 FCM Italy 19
Up Treg cells Unknown PB 39 FCM Italy 19
Up CD56dim NK cells Unknown PB 35 FCM Italy 20
Down PB cells Severe cases PB 14 RNA-seq China 3
PBMC 33 CITE-seq USA 21
Up Memory T cells and CD38+SARS-CoV-2–specific T cells Acute severe cases PB 206 FCM Sweden 22
Up SARS-CoV-2–specific T cells Acute and convalescent cases PB 235 FCM Korea 23
Up B cells Unknown PB 20 FCM Germany 24
PB 85 FCM USA 25
Tim-3 Up Memory T cells and SARS-CoV-2–specific T cells Acute severe cases PB 206 FCM Sweden 22
Up SARS-CoV-2-reactive CD8+ T cells Unknown PB 39 scRNA-seq UK 26
Up Plasma Severe cases Serum 24 ELISA China 27
Plasma 39 EIA Norway 28
Plasma 55 ELISA China 29
Up NK and CD8+ T cells Severe cases PB 32 FCM Italy 30
PBMC 44 FCM Iran 31
Up NK and T cells Death Lung, Kidney 11 DSP, mIHC China 1
Up CD4+ and CD8+ T cells in Severe cases PBMC 76 FCM China 15
CD4+ T cells PBMC 44 FCM Iran 32
Tfh cells PB 11 FCM China 33
Up CD3+ T cells Acute severe cases PBMC 92 FCM Germany 34
Up Treg cells Convalescent cases PBMC 30 FCM China 35
Up CD4+ and CD8+ T cells Unknown Skin 8 IHC Italy 36
CTLA-4 Down PB cells Severe cases PB 14 RNA-seq China 3
Up SARS-CoV-2–specific T cells Severe cases PB 108 FCM Canada 37
Up Memory T cells and SARS-CoV-2–specific T cells Acute severe cases PB 206 FCM Sweden 22
Up CD4+ and CD8+ T cells Severe ARDS cases PB/BALF 4 FCM UK 38
Up Plasma Severe cases Plasma 109 FCM China 12
LAG-3 Up Memory T cells and SARS-CoV-2–specific T cells Acute severe cases PB 206 FCM Sweden 22
Up SARS-CoV-2-reactive CD8+ T cells Unknown PB 39 scRNA-seq UK 26
Up CD4+ and CD38+ HLA-DR+CD8+ T cells Severe cases PBMC 10 scRNA-seq, FCM USA 39
Up CD4+ and CD8+ T cells Unknown PBMC 20 FCM UK 2
TIGIT Down SARS-CoV-2–specific T cells Unknown PB 206 FCM Sweden 22
PB 108 FCM Canada 37
Down CD4+ and CD8+ T cells Unknown PB 50 FCM Germany 40
Down NK cells Unknown PB 50 FCM Germany 40
Down CD4+ and CD8+T cells Non-ICU cases PB 144 FCM Spain 41
Up CD4+ T cells Acute cases PB 85 FCM USA 25
Treg and CD4+TM cells PB 50 FCM Germany 40
BTLA Up CD8+TM and TEM cells Unknown PBMC 20 FCM UK 2
Up CD4+ and CD8+ T cells Active cases NPSs 430 RNA-seq United Arab Emirates 42
Lung/BALF 16 RNA-seq
Up Plasma Severe cases Plasma 109 FCM China 12
Up CD4+ and CD8+ T cells Active cases PB 50 FCM Germany 40
VISTA Up CD154+CD4+ and CD137+CD8+T cells Unknown PB 108 FCM Canada 37
Up CD4+ and CD8+T cells Mild cases PBMC 45 FCM USA 43
Up CD4+ and CD8+T cells Unknown PBMC 108 FCM Canada 37
NKG2A Up SARS-CoV-2–specific T cells Severe cases PB 108 FCM Canada 37
ARDS = acute respiratory distress syndrome, BALF = bronchoalveolar lavage fluid, CITE-seq = cellular indexing of transcriptomes and epitopes by sequencing, DSP = digital spatial profiling, EIA = enzyme immunoassays, ELISA = enzyme-linked immunosorbent assay, FCM = flow cytometer, mIHC = multiplex-immunohistochemistry, NPSs = nasopharyngeal swabs, PB = peripheral blood, PBMC = peripheral blood mononuclear cell, RNA-seq = RNA sequencing, scRNA-seq = single-cell RNA sequencing, TCM = central memory T cells, TEM = effector memory T cells, Tfh = follicular helper T cell, TM = transitional memory T cells, UK = United Kingdom, USA = United States of America.

Table 2 - Distribution of immune checkpoint ligands in COVID-19.
IC ligands Expression Cell type/fluid Performance Sample style Sample size (n) Detection method Area Reference
PD-L1 Up MON and DCs Severe cases PBMC 19 FCM Czech Republic 44
PB 20 FCM Portugal 45
Gal-1, -3 Up Plasma Severe cases Plasma 84 ELISA Turkey 46
Gal-3, -9 Up Plasma Severe cases Plasma 55 ELISA China 29
Gal-9 Up HLA-DR+ and CD80+ monocyte Unknown PB 146 FCM Canada 47
Up Neutrophils Unknown PB 146 FCM Canada 47
CD155 Up Plasma and pulmonary epithelial cells Severe cases Serum/lung 46 Proteomics/IHC China 48
DCs = dendritic cells, ELISA = enzyme-linked immunosorbent assay, FCM = flow cytometer, Gal = galectin, IC = immune checkpoint, IHC = immunohistochemistry, MON = monocytes, PB = peripheral blood, PBMC = peripheral blood mononuclear cell, PD-L1 = programmed death-ligand 1.

Figure 1.:
Summary of the increased expression of immunosuppressive receptors on immune cells.

2. PD-1

PD-1 is a co-inhibitory receptor expressed on a variety of immune cells.7 After the TCR recognizes an antigen, it forms a specific cross-link with the ligand PD-L1\PD-L2, which plays a negative regulatory role.7,51 Based on the effectiveness of a monoclonal antibody directed against the PD-1/PD-L1 axis in reversing T cell function,10 the role of anti-PD-1 therapy in the clearance of SARS-CoV-2 was investigated.52

With regards to the relationship between ICs and COVID-19, the earliest research came from pathological examination data from autopsies of COVID-19 patients. It was found that there was an abnormal distribution of T cells in lung, kidney, and bronchoalveolar lavage fluid (BALF). PD-1 and Tim-3 were the signs of severe immunosuppression in COVID-19, and they were mainly correlated with males and the elderly.1,18 Based on the theory that soluble checkpoint molecules are produced by membrane-bound protein cleavage or mRNA expression, Kong Y et al detected 13 soluble co-inhibitory molecules, including sPD-1 and sPD-L1, in plasma samples of severe or critical patients, and these were significantly higher than that in mild and asymptomatic infected patients, and they maintained a continuous increasing trend upon dynamic analysis, with the exception of PD-L2.12 Correspondingly, a series of descriptive reports demonstrated that PD-1 was up-regulated in T cells, NK cells, and B cells from the PB of COVID-19 patients.20,24 Subgroup studies of PB samples almost consistently concluded that PD-1 expression was higher and immunosuppression was more severe in critically ill patients, hospitalized patients, and the elderly, particularly those over 80 years old.14,17,53 While, the percentage of PD-1+CD4+ and PD-1+CD8+ T cells decreased gradually after treatment.49 However, some studies have not found a difference in PD-1 and PD-L1 expression and CD8+ T cell dysfunction.3,21,54 The reason for the difference in reports may be due to ignoring the distinction in immune cell function. Not all T cells are virus-specific immune cells, and there is a lack of data supporting effector function.

De Biasi S et al found that PD-1 was mainly overexpressed on CD38+ central memory T cells, effector memory T cells, and primitive regulatory T (Treg) cells in the COVID-19 activated phenotype, but there was no difference in the expression levels of the terminal TEM and stem cell memory T cells subsets.19 Saris A et al pointed out that the high expression of PD-1 in CXCR3+CD4+ and CCR6+CD8+ T cells was the reason for the decrease in the TH1 cell proportion and insufficient secretion of granzyme and perforin by cytotoxic CD8+ T cells (CTLs) in severe COVID-19 patients.18 This result was supported by the finding of up-regulated PD-1, Tim-3, and lymphocyte activation gene 3 (LAG-3) on SARS-CoV-2–specific T cells in the acute stage of COVID-19, and it was negatively correlated with the time after the onset of symptoms.22 However, Rha MS et al found that PD-1+, SARS-CoV-2–specific CD8+ T cells could still produce interferon (IFN)-γ in the acute phase and convalescence.23 It was suggested that up-regulation of PD-1, CTLA-4, Tim-3, and V-domain Ig suppressor of T cell activation (VISTA) on SARS-CoV-2–specific T cells may be related to the over activation of T cells.37 Overall, the findings suggested that transient expression of co-inhibitory receptors on activated T cells prevent a harmful overactive immune response in COVID-19.55

3. Tim-3

Another important co-inhibitory receptor, Tim-3 was initially found to be expressed in CD4+ type 1 helper T cells (TH1 cells) and CTLs.6 Subsequently, Tim-3 was detected on Tregs, myeloid cells, NK cells, and tumor cells.6 At present, it is considered that blockade of Tim-3 signaling can be used as a supplement to the failure of anti-PD-1/PD-L1 therapy.

Pathologists have found a higher level of Tim-3 in the center of the pulmonary inflammatory storm in cadaver samples of COVID-19 patients, which is consistent with a report from a multi-center, single-cell sequencing study where Tim-3 expression was increased and a high concentration of sTim-3 was detected in the plasma of critically ill patients.1,28,56 Interestingly, the proportion of Tim-3+ and PD-1+Tim-3+ cells among T cells and NK cells in male lung tissue is significantly higher than that in females, which is related to a local high viral load, suggesting that high expression of Tim-3 in male immune cells has a poor prognosis.1 A case report from Spain confirmed the above findings.57 In this report of a couple who live together, close in age, and were infected with the same load of SARS-CoV-2 virus, it was demonstrated that the husband gradually developed severe pneumonia, showed progressive respiratory failure, and became hospitalized on the 10th day after onset. In contrast, his wife only displayed mild to moderate tolerable symptoms. Dynamic data display that the male patient maintained a high proportion of Tim-3+CD4+ and Tim-3+CD8+ T cells throughout the course of the disease, and sGal-9 had a significant concentration difference that was detected in the plasma 2 days before the disease became worse.57

A number of studies have reported that Tim-3 was detected in CD4+ and CD8+ T and NK cells in the PB of COVID-19 patients accompanied by immune dysfunction.32 Diao B et al found that the expression of the Tim-3 and PD-1 genes in T cells gradually increased with the progression of clinical symptoms.14 These findings may explain the higher level of Tim-3 detected in PB samples of critically ill COVID-19 patients.15 However, a high proportion of Tim-3+ Treg and Tim-3+ CD8 cells was still detected in convalescent patients, but the secretion of granzyme B was limited.35 In addition, it is known that CD4+ T cells can regulate the immune response of CTLs through TH1 cells and Tregs and activate B cells through T follicular helper (Tfh) cells to promote the production of virus-specific antibodies. In contrast, a recent study found that the decrease in CD4+ T cells in COVID-19 patients was accompanied by up-regulation of Tim-3 in TH1, Treg, Tfh cells, and they may reduce the functions described above.32,33,35 In addition, Herrmann et al2 found the expression of LAG-3 and TIM-3 in all subsets of CD8+ and CD4+ T cells (including naive, CM, TM, EM, EMRA, and SARS-CoV-2–specific T cells) of critical COVID-19 patients increased significantly.

More interestingly, Cazzato et al found that TIM-3 was accompanied by the expression of another ligand, high mobility group box 1(HMGB-1), in CD4+ and CD8+ T cells from skin biopsy samples of COVID-19 patients. Suggesting that in addition to the respiratory tract, the skin, the “sentinel” of the immune system, is also affected.36

4. CTLA-4

CTLA-4 induces inhibitory signals in regulatory or effector T cells by competitively binding to B-7 ligand, which is an important protective mechanism to prevent a super-immune response. Although higher concentrations of soluble CTLA-4 can be detected in the plasma of critical COVID-19 patients compared to mild and healthy individuals,12 CTLA-4 was only slightly expressed on T cells in PB from critical patients.38 There was no difference in CTLA-4 gene expression by RNA-seq in PB samples between COVID-19 patients and healthy controls.3 However, a higher proportion of CTLA-4+CD4+ and CTLA-4+CD8+ T cells was detected in BALF compared with the PB of critical COVID-19 patients with acute respiratory distress syndrome.38 Overall, it was reported that CTLA-4 was still highly expressed on CD4+ T cells including SARS-CoV-2–specific CD4+T cells 1 year after recovery.58


B and T lymphocyte attenuator (BTLA), a co-inhibitory receptor mainly expressed on B and T cells, has been found to have abnormal expression and may be an indicator for late lymphocyte exhaustion. The ligand for BTLA, herpes virus entry mediator was found to play an auxiliary role in immune escape in PD-L1-deficient lung tumors.59 Transcriptome data from nasopharyngeal swabs (NPSs) and lung autopsy samples from COVID-19 cases have been published, demonstrating a pattern of upregulation of the mRNA levels of 8 ICs, including BTLA, LAG-3, CTLA-4, and PDCD1 during acute COVID-19.42 The above results are consistent with the findings that high concentrations of soluble BTLA can be detected in the plasma of critically ill COVID-19 patients.12 Interestingly, 1 report showed that COVID-19 is very similar to malaria infection, and higher levels of BTLA expression can be detected on TM and EM CD8+ T cells.2


TIGIT is an inhibitory molecule that is expressed on NK/T cells, and it was found to be up-regulated to induce T cell exhaustion in leukemia patients. TIGIT mainly competes with DNAM-1 and CD96 for CD155 to induce immunosuppression. Studies have shown high expression of CD155 in SARS-CoV-2 infected cells48; however, the findings of TIGIT alteration in COVID-19 remain controversial. Although many studies have found that TIGIT is up-regulated in patients with acute COVID-19, ICU patients, and the deceased, the Treg, CD4+ TM cell, and CD8+ T cell subgroups are up-regulated and recovered in the rehabilitation cohort.40 Reports also have shown a decrease in TIGIT in NK cells2 and normal TIGIT expression on CTLs from COVID-19 patients regardless of the need for hospitalization.22,25

7. LAG-3

LAG-3 is a marker for NK cell dysfunction. All CD8+ and CD4+ T cells (including naive, CM, TM, EM, and EMRA) in patients with COVID-19 demonstrated an increase in the expression of LAG-3.2 Multi-omic single-cell analysis has also found up-regulation of LAG-3 on most T/NK cells, with the exception of Tregs, in samples from advanced COVID-19 patients.39 In addition, it was also found that LAG-3+CD4+ T cells are negatively correlated with activated monocytes. Thus, LAG-3 may play a regulatory role after the activation of immune cells.39,60


VISTA is an immune checkpoint protein with suppressive effects on CD4+ and CD8+ T cells.61 In chronic viral diseases (including chronic SARS-CoV-2 infection), exhausted T cells with high expression of VISTA may appear.19 Rendeiro et al found that VISTA was significantly up-regulated in CD4+ and CD8+ T cells in mild and moderate COVID-19 patients. Interestingly, the frequency of VISTA expression in severe patients was decreased, but it was still higher than that in healthy controls and the convalescent.43 In addition, a study from Canada also found that the SARS-CoV-2–specific T cells (CD154+CD4+, CD137+CD8+ T cells) stimulated by antigens significantly increased VISTA molecules.37 Recent studies of VISTA on T cells, monocytes, and myeloid cells have highlighted its potential significance in driving cytokine storms after viral infection.62


CD47 is a glycoprotein widely expressed in the immunoglobulin superfamily. CD47 interacts with signal regulatory protein α (SIRP α) to transmit an anti-phagocytic “don’t eat me” signal to mediate immune escape.63 The CD47 gene is up-regulated in human bronchial epithelial A549 lung cancer cells, Caco2 colorectal carcinoma cells, and Calu-3 lung cancer cells infected with SARS-CoV-2 accompanied by an increase in SIRPα in monocyte infected cells.64 It was found that CD47 may be related to COVID-19 pulmonary fibrosis, which can be reversed by an anti-CD47 antibody in a mouse model study.65,66

NKG2A, identified as another novel IC protein, was also found to be overexpressed on CTLs and NK cells in the early stage of SARS-CoV-2 infection, resulting in decreased NK cell activity and increased T cell exhaustion.67–69 The recovery of NK and CD8+ T cell function was accompanied by the recovery of NKG2A.70


ICs rely on binding with their corresponding ligands for different immune signal ligand expression, the greater the possibility of affecting the occurrence and development of diseases through these pathways.71,72 Currently, inhibitors designed to target ligands have been widely used in the treatment of solid tumors eg, PD-L1 inhibitors.73 Several studies have also reported the alteration of IC ligands in COVID-19 patients.

11. PD-L1

PD-L1 and indoleamine 2,3-dioxygenase were strongly and diffusely expressed in COVID-19 lung parenchymal lesions.74 Early studies have found high concentrations of PD-L1 in monocytes/ macrophages and the plasma of BALF.75 In addition, PD-L1 expression in basophils and eosinophils correlates with COVID-19 severity.72 The expression of PD-L1 gradually increased with the progression of the disease and gradually returned to normal after treatment.44,45 Under the stimulation of SARS-CoV-2, the proportion of PD-L1+DC cells increases, indicating that COVID-19 can induce dendritic cells (DCs) to differentiate into an anti-infective phenotype.76


Galectin plays an important role in the regulation of the immune and inflammatory response. Based on different structures, galectin can be divided into Gal-1, Gal-3, and Gal-9.77 All of the Gal proteins can be detected in APC cells (macrophages, monocytes, and DCs) and plasma from COVID-19 patients, which are considered to be associated with “cytokine storm syndrome” and severe disease course.29 Interestingly, Gal-9 appears to have higher expression in activated HLA-DR+ and CD80+ monocytes, whereas Gal-9 is down-regulated in activated neutrophils.78

In addition, CD155 and CD112 can be detected in APC cells as specific TIGIT ligands on T cells and NK cells. Abnormal expression of CD155, nectin-4, and CD112 has been detected in SARS-CoV-2 infected cells.48 These ligands and the opposite ligands, such as DNAM-1, play a role in balancing and maintaining immune cell homeostasis.48,79


Beyond the understanding that increased IC expression may result on T cell exhaustion in COVID-19 patients, several studies also showed that such T cells have can recognize SARS-CoV-2 peptide and produce associate cytokine. An in vitro antigen co-stimulation study confirmed that SARS-CoV-2 antigen can induce T cells from critical patients to express higher levels of co-inhibitory receptors such as CTLA-4, PD-1, VISTA, and Tim-3, which is related to the production of high levels of TNF-α and IFN-γ.37 Moreover, it was reported that CTLA-4 was still highly expressed on CD4+ T cells (including SARS-CoV-2–specific CD4+T cells) 1 year after recovery.58 Schultheiss C et al found that COVID-19 patients secreted high concentrations of the inflammatory factors IL-6, IL-10, TNF-α, and TNF-β at the acute stage of infection accompanied by an increase in BTLA expression of CD4+ and CD8+ T cells.40 Under the stimulation of SARS-CoV-2, the proportion of PD-L1+DC cells increases, indicating that COVID-19 can induce DCs to differentiate into an anti-infective phenotype.76 Thus, the researchers thought that increased IC expression may play potentiate the hyperinflammatory response in COVID-19 patients. At least, it may either play a protective or detrimental role in COVID-19 patients.37 Therefore, how to balance the effect of ICs is an open question to the clinicians.


Based on the understanding that ICs can mediate the immune escape of pathogens and studies of the abnormal expression of ICs on immune cells of patients with COVID-19, ICB may contribute to virus clearance. This idea has attracted the attention of clinical oncologists because IC inhibitors (ICIs) are primarily used for cancer immunotherapy. Patients with cancer in the context of the COVID-19 epidemic have higher infection rates and risk for serious complications.79 The clinical response of cancer patients with COVID-19 during ICI treatment is an important reference for guiding ICI use for COVID-19 patients. This is based on the concern that there may be potential synergistic effects for ICB and COVID-19 pathogenesis that leads to aggravated lung injury. However, according to the German working group of a dermato-oncology database, a study involving 13 melanoma patients with COVID-19 demonstrated that only 2 cases developed disease progression and needed hospitalization when using anti-PD-1 antibody alone or in combination with CTLA-4 blocking therapy.50 One case was an 83-year-old patient with multiple organ dysfunction who received nivolumab + ipilimumab.50 Another case was hospitalized due to fever and diarrhea after nivolumab.50 Klebanov et al conducted a retrospective study of 1545 cancer patients who received ICI treatment during the SARS-CoV-2 epidemic.80 The results demonstrated that ICI treatment did not increase the risk of COVID-19.80 Another report presented data from 41 patients who received PD-1 inhibitors and demonstrated that PD-1 blockade did not increase the risk of progression for COVID-19.81 A report from Pala L et al also supported this result where a patient with SARS-CoV-2 and metastatic melanoma was cured by anti-PD-1 therapy.82 However, it has been reported that approximately 3 to 5% of patients have an immune-mediated lung injury, which proves that there are synergistic effects between ICB and SARS-CoV-2–related immune pneumonia.23,83 Clinical trials are also evaluating the safety and efficacy of PD-1 blockade strategies in COVID-19 patients without cancers (eg, NCT04356508, NCT04335305, NCT04413838, and NCT04343144) (Table 3). Overall, the above data provide the possibility of targeted IC therapy for COVID-19 patients.

Table 3 - Immune checkpoint blockade in clinical trials for COVID-19 patients.
Trials No. Condition or disease Interventions Primary outcome measures Secondary outcome measures Research status
NCT04356508 COVID-19; SARS-CoV-2; pneumonia Nivolumab + best supportive care Viral clearance kinetics (1) Treatment related adverse events of nivolumab
(2) Lymphocyte kinetics
(3) Cytokine kinetics
(4) Length of inpatient stay due to COVID-19. etc
Not yet recruiting
NCT04335305 COVID-19; pneumonia Tocilizumab plus Pembrolizumab Percentage of patients with normalization of SpO2 ≥96% on room air (1) Proportion of patients discharged from the emergency department and classified as low risk
(2) Number of days of patient hospitalization
(3) Change from baseline in organ failure parameters
(4) Incidence of adverse events. etc
NCT04413838 COVID-19 Nivolumab+ nursing routine Patient’s clinical state (1) Proportion of death at D7 and D15
(2) Oxygen flow needs
(3) Adverse events
(4) Discharge from hospital. etc
Not yet recruiting
NCT04343144 COVID-19 Nivolumab Time to clinical improvement (1) Overall survival (D28, D90)
(2) Cumulative incidence of ICU admission
(3) Length of hospital stay
(4) Incidence of adverse events. etc
Not yet recruiting


Significant alterations in ICs have been characterized in immune cells from patients with COVID-19 or those with SARS-CoV-2 infection, and these interfere the balance of activation and proliferation of various immune cells. These alterations may be associated with disease progression and poor prognosis, particularly in the elderly with more complications. Data from cancer patients with COVID-19 who are undergoing ICI treatment demonstrate that ICB may have defensive functions against COVID-19. However, the possibility of synergistic immune lung injury also needs to be considered when managing and optimizing ICB for COVID-19 patients. Nevertheless, the differences in IC expression in different populations and immune cell subsets and the advantages and disadvantages of IC proteins in different stages of COVID-19 as well as the benefits and risks of ICB in treating different cancers and non-cancer COVID-19 patients still need to be thoroughly research and discussed.


[1]. Wu H, He P, Ren Y, et al. Postmortem high-dimensional immune profiling of severe COVID-19 patients reveals distinct patterns of immunosuppression and immune activation. Nat Commun. 2022;13(1):269.
[2]. Herrmann M, Schulte S, Wildner NH, et al. Analysis of co-inhibitory receptor expression in COVID-19 infection compared to acute plasmodium falciparum Malaria: LAG-3 and TIM-3 correlate with T cell activation and course of disease. Front Immunol. 2020;11:1870.
[3]. Zhou Y, Liao X, Song X, et al. Severe adaptive immune suppression may be why patients with severe COVID-19 cannot be discharged from the ICU even after negative viral tests. Front Immunol. 2021;12:755579.
[4]. Liu L, Xu L, Lin C. T cell response in patients with COVID-19. Blood Science. 2020;2(3):76–78.
[5]. Amodio V, Mauri G, Reilly NM, et al. Mechanisms of immune escape and resistance to checkpoint inhibitor therapies in mismatch repair deficient metastatic colorectal cancers. Cancers. 2021;13(11):26382638.
[6]. Rezaei M, Tan J, Zeng C, Li Y, Ganjalikhani-Hakemi M. TIM-3 in leukemia; immune response and beyond. Front Oncol. 2021;11:753677.
[7]. Tan J, Yu Z, Huang J, et al. Increased PD-1+Tim-3+ exhausted T cells in bone marrow may influence the clinical outcome of patients with AML. Biomark Res. 2020;8:6.
[8]. Huang J, Tan J, Chen Y, et al. A skewed distribution and increased PD-1+Vbeta+CD4+/CD8+ T cells in patients with acute myeloid leukemia. J Leukoc Biol. 2019;106(3):725–732.
[9]. Wherry EJ, Ha SJ, Kaech SM, et al. Molecular signature of CD8+ T cell exhaustion during chronic viral infection. Immunity. 2007;27(4):670–684.
[10]. Liu SY, Wu YL. Tislelizumab: an investigational anti-PD-1 antibody for the treatment of advanced non-small cell lung cancer (NSCLC). Expert Opin Investig Drugs. 2020;29(12):1355–1364.
[11]. Murata T. Human herpesvirus and the immune checkpoint PD-1/PD-L1 pathway: disorders and strategies for survival. Microorganisms. 2021;9(4):778.
[12]. Kong Y, Wang Y, Wu X, et al. Storm of soluble immune checkpoints associated with disease severity of COVID-19. Signal Transduct Target Ther. 2020;5(1):192.
[13]. Mahmoodpoor A, Hosseini M, Soltani-Zangbar S, et al. Reduction and exhausted features of T lymphocytes under serological changes, and prognostic factors in COVID-19 progression. Mol Immunol. 2021;138:121–127.
[14]. Diao B, Wang C, Tan Y, et al. Reduction and functional exhaustion of T Cells in patients with coronavirus disease 2019 (COVID-19). Front Immunol. 2020;11:827.
[15]. Liu Y, Pan Y, Hu Z, et al. Thymosin alpha 1 reduces the mortality of severe coronavirus disease 2019 by restoration of lymphocytopenia and reversion of exhausted T cells. Clin Inf Dis: An Off Pub Infect Dis Soc Am. 2020;71(16):2150–2157.
[16]. Bellesi S, Metafuni E, Hohaus S, et al. Increased CD95 (Fas) and PD-1 expression in peripheral blood T lymphocytes in COVID-19 patients. Br J Haematol. 2020;191(2):207–211.
[17]. Westmeier J, Paniskaki K, Karakose Z, et al. Impaired cytotoxic CD8(+) T cell response in elderly COVID-19 patients. mBio. 2020;11(5):e02243–e02220.
[18]. Saris A, Reijnders TDY, Reijm M, et al. Enrichment of CCR6(+) CD8(+) T cells and CCL20 in the lungs of mechanically ventilated patients with COVID-19. Eur J Immunol. 2021;51(6):1535–1538.
[19]. De Biasi S, Meschiari M, Gibellini L, et al. Marked T cell activation, senescence, exhaustion and skewing towards TH17 in patients with COVID-19 pneumonia. Nat Commun. 2020;11(1):3434.
[20]. Bergantini L, d’Alessandro M, Cameli P, et al. NK and T cell immunological signatures in hospitalized patients with COVID-19. Cells. 2021;10(11):31823182.
[21]. Liu C, Martins AJ, Lau WW, et al. Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19. Cell. 2021;184(7):1836–1857.e22.
[22]. Sekine T, Perez-Potti A, Rivera-Ballesteros O, et al. Robust T cell immunity in convalescent individuals with asymptomatic or mild COVID-19. Cell. 2020;183(1):158–168.e14.
[23]. Rha MS, Jeong HW, Ko JH, et al. PD-1-expressing SARS-CoV-2-specific CD8(+) T cells are not exhausted, but functional in patients with COVID-19. Immunity. 2021;54(1):44–52.e3.
[24]. Wildner NH, Ahmadi P, Schulte S, et al. B cell analysis in SARS-CoV-2 versus malaria: increased frequencies of plasmablasts and atypical memory B cells in COVID-19. J Leukoc Biol. 2021;109(1):77–90.
[25]. Files JK, Boppana S, Perez MD, et al. Sustained cellular immune dysregulation in individuals recovering from SARS-CoV-2 infection. J Clin Invest. 2021;131(1):e140491.
[26]. Kusnadi A, Ramirez-Suastegui C, Fajardo V, et al. Severely ill COVID-19 patients display impaired exhaustion features in SARS-CoV-2-reactive CD8(+) T cells. Sci Immunol. 2021;6(55):eabe4782.
[27]. Huang W, Li M, Luo G, et al. The inflammatory factors associated with disease severity to predict COVID-19 progression. J Immunol. 2021;206(7):1597–1608.
[28]. Ueland T, Heggelund L, Lind A, et al. Elevated plasma sTIM-3 levels in patients with severe COVID-19. J Allergy Clin Immunol. 2021;147(1):92–98.
[29]. Chen PK, Lan JL, Huang PH, et al. Interleukin-18 is a potential biomarker to discriminate active adult-onset still’s disease from COVID-19. Front Immunol. 2021;12:719544.
[30]. Varchetta S, Mele D, Oliviero B, et al. Unique immunological profile in patients with COVID-19. Cell Mol Immunol. 2021;18(3):604–612.
[31]. Shahbazi M, Moulana Z, Sepidarkish M, et al. Pronounce expression of Tim-3 and CD39 but not PD1 defines CD8 T cells in critical Covid-19 patients. Microb Pathog. 2021;153:104779.
[32]. Modabber Z, Shahbazi M, Akbari R, Bagherzadeh M, Firouzjahi A, Mohammadnia-Afrouzi M. TIM-3 as a potential exhaustion marker in CD4(+) T cells of COVID-19 patients. Immun Inflammation Dis. 2021;9(4):1707–1715.
[33]. Yan L, Cai B, Li Y, et al. Dynamics of NK, CD8 and Tfh cell mediated the production of cytokines and antiviral antibodies in Chinese patients with moderate COVID-19. J Cell Mol Med. 2020;24(24):14270–14279.
[34]. Bonifacius A, Tischer-Zimmermann S, Dragon AC, et al. COVID-19 immune signatures reveal stable antiviral T cell function despite declining humoral responses. Immunity. 2021;54(2):340–354.e6.
[35]. Liu J, Yang X, Wang H, et al. Analysis of the long-term impact on cellular immunity in COVID-19-recovered individuals reveals a profound NKT cell impairment. mBio. 2021;12(2):e00085–e00021.
[36]. Cazzato G, Colagrande A, Cimmino A, et al. HMGB1-TIM3-HO1: a new pathway of inflammation in skin of SARS-CoV-2 patients? a retrospective pilot study. Biomolecules. 2021;11(8):1219.
[37]. Shahbaz S, Xu L, Sligl W, et al. The quality of SARS-CoV-2-specific T cell functions differs in patients with mild/moderate versus severe disease, and T cells expressing coinhibitory receptors are highly activated. J Immunol. 2021;207(4):1099–1111.
[38]. Ronit A, Berg RMG, Bay JT, et al. Compartmental immunophenotyping in COVID-19 ARDS: a case series. J Allergy Clin Immunol. 2021;147(1):81–91.
[39]. Unterman A, Sumida TS, Nouri N, et al. Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19. Nat Commun. 2022;13(1):440.
[40]. Schultheiss C, Paschold L, Simnica D, et al. Next-generation sequencing of T and B cell receptor repertoires from COVID-19 patients showed signatures associated with severity of disease. Immunity. 2020;53(2):442–455.
[41]. Gutierrez-Bautista JF, Rodriguez-Nicolas A, Rosales-Castillo A, et al. Negative clinical evolution in COVID-19 patients is frequently accompanied with an increased proportion of undifferentiated Th cells and a strong underrepresentation of the Th1 subset. Front Immunol. 2020;11:596553.
[42]. Saheb Sharif-Askari N, Saheb Sharif-Askari F, Mdkhana B, et al. Enhanced expression of immune checkpoint receptors during SARS-CoV-2 viral infection. Mol Ther Methods Clin Dev. 2021;20:109–121.
[43]. Rendeiro AF, Casano J, Vorkas CK, et al. Profiling of immune dysfunction in COVID-19 patients allows early prediction of disease progression. Life Sci Alliance. 2021;4(2):e202000955.
[44]. Parackova Z, Zentsova I, Bloomfield M, et al. Disharmonic inflammatory signatures in COVID-19: augmented neutrophils’ but impaired monocytes’ and dendritic cells’ responsiveness. Cells. 2020;9(10):22062206.
[45]. Trombetta AC, Farias GB, Gomes AMC, et al. Severe COVID-19 recovery is associated with timely acquisition of a myeloid cell immune-regulatory phenotype. Front Immunol. 2021;12:691725.
[46]. Kazancioglu S, Yilmaz FM, Bastug A, et al. Assessment of Galectin-1, Galectin-3, and Prostaglandin E2 levels in patients with COVID-19. Jpn J Infect Dis. 2021;74(6):530–536.
[47]. Bozorgmehr N, Mashhouri S, Perez Rosero E, et al. Galectin-9, a player in cytokine release syndrome and a surrogate diagnostic biomarker in SARS-CoV-2 infection. mBio. 2021;12(3):e00384–e00321.
[48]. Hsieh WC, Lai EY, Liu YT, et al. NK cell receptor and ligand composition influences the clearance of SARS-CoV-2. J Clin Invest. 2021;131(21):e146408.
[49]. Yang J, Zhong M, Zhang E, et al. Broad phenotypic alterations and potential dysfunction of lymphocytes in individuals clinically recovered from COVID-19. J Mol Cell Biol. 2021;13(3):197–209.
[50]. Moritz RKC, Gutzmer R, Zimmer L, et al. SARS-CoV-2 infections in melanoma patients treated with PD-1 inhibitors: a survey of the German ADOREG melanoma registry. Eur J Cancer. 2021;144:382–385.
[51]. Ai L, Xu A, Xu J. Roles of PD-1/PD-L1 pathway: signaling, cancer, and beyond. Adv Exp Med Biol. 2020;1248:33–59.
[52]. Vivarelli S, Falzone L, Torino F, et al. Immune-checkpoint inhibitors from cancer to COVID19: a promising avenue for the treatment of patients with COVID19 (Review). Int J Oncol. 2021;58(2):145–157.
[53]. Song JW, Zhang C, Fan X, et al. Immunological and inflammatory profiles in mild and severe cases of COVID-19. Nat Commun. 2020;11(1):3410.
[54]. Wilk AJ, Rustagi A, Zhao NQ, et al. A single-cell atlas of the peripheral immune response in patients with severe COVID-19. Nat Med. 2020;26(7):1070–1076.
[55]. Chamoto K, Al-Habsi M, Honjo T. Role of PD-1 in immunity and diseases. Curr Top Microbiol Immunol. 2017;410:75–97.
[56]. Yang J, Chang T, Tang L, et al. Increased expression of Tim-3 is associated with depletion of NKT cells in SARS-CoV-2 infection. Front Immunol. 2022;13:796682.
[57]. Martin-Quiros A, Maroun-Eid C, Avendano-Ortiz J, et al. Potential role of the Galectin-9/TIM-3 axis in the disparate progression of SARS-CoV-2 in a married couple: a case report. Biomed Hub. 2021;6(1):48–58.
[58]. Hou H, Zhang Y, Tang G, et al. Immunologic memory to SARS-CoV-2 in convalescent COVID-19 patients at 1year postinfection. J Allergy Clin Immunol. 2021;148(6):1481–1492.e2.
[59]. Demerle C, Gorvel L, Olive D. BTLA-HVEM couple in health and diseases: insights for immunotherapy in lung cancer. Front Oncol. 2021;11:682007.
[60]. Stephenson E, Reynolds G, Botting RA, et al. Single-cell multi-omics analysis of the immune response in COVID-19. Nat Med. 2021;27(5):904–916.
[61]. Tao T, Bo L, Li T, et al. High-affinity anti-VISTA antibody protects against sepsis by inhibition of T lymphocyte apoptosis and suppression of the inflammatory response. Mediators Inflamm. 2021;8:6650329.
[62]. ElTanbouly MA, Zhao Y, Schaafsma E, et al. VISTA: a target to manage the innate cytokine storm. Front Immunol. 2020;11:595950.
[63]. Liu X, Kwon H, Li Z, Fu YX. Is CD47 an innate immune checkpoint for tumor evasion? J Hematol Oncol. 2017;10(1):12.
[64]. McLaughlin KM, Bojkova D, Kandler JD, et al. A potential role of the CD47/SIRP alpha axis in COVID-19 pathogenesis. Curr Issues Mol Biol. 2021;43(3):1212–1225.
[65]. Wernig G, Chen SY, Cui L, et al. Unifying mechanism for different fibrotic diseases. Proc Natl Acad Sci USA. 2017;114(18):4757–4762.
[66]. Leeming DJ, Genovese F, Sand JMB, et al. Can biomarkers of extracellular matrix remodeling and wound healing be used to identify high risk patients infected with SARS-CoV-2: lessons learned from pulmonary fibrosis. Respir Res. 2021;22(1):38.
[67]. Zheng M, Gao Y, Wang G, et al. Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cell Mol Immunol. 2020;17(5):533–535.
[68]. Cao X. COVID-19: immunopathology and its implications for therapy. Nat Rev Immunol. 2020;20(5):269–270.
[69]. Zheng HY, Zhang M, Yang CX, et al. Elevated exhaustion levels and reduced functional diversity of T cells in peripheral blood may predict severe progression in COVID-19 patients. Cell Mol Immunol. 2020;17(5):541–543.
[70]. Antonioli L, Fornai M, Pellegrini C, Blandizzi C. NKG2A and COVID-19: another brick in the wall. Cell Mol Immunol. 2020;17(6):672–674.
[71]. Xiong W, Gao Y, Wei W, Zhang J. Extracellular and nuclear PD-L1 in modulating cancer immunotherapy. Trends Cancer. 2021;7(9):837–846.
[72]. Vitte J, Diallo AB, Boumaza A, et al. A granulocytic signature identifies COVID-19 and its severity. J Infect Dis. 2020;222(12):1985–1996.
[73]. Doroshow DB, Bhalla S, Beasley MB, et al. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol. 2021;18(6):345–362.
[74]. Ravaglia C, Doglioni C, Chilosi M, et al. Clinical, radiological, and pathological findings in patients with persistent lung disease following SARS-CoV-2 infection. Eur Respir J. 2022;5:2102411.
[75]. Chilosi M, Poletti V, Ravaglia C, et al. The pathogenic role of epithelial and endothelial cells in early-phase COVID-19 pneumonia: victims and partners in crime. Mod Pathol: An Official J United States Canadian Acad Pathol, Inc. 2021;34(8):1444–1455.
[76]. Severa M, Diotti RA, Etna MP, et al. Differential plasmacytoid dendritic cell phenotype and type I interferon response in asymptomatic and severe COVID-19 infection. PLoS Pathog. 2021;17(9):e1009878.
[77]. Moar P, Tandon R. Galectin-9 as a biomarker of disease severity. Cell Immunol. 2021;361:104287.
[78]. Bai G, Furushima D, Niki T, et al. High levels of the cleaved form of Galectin-9 and osteopontin in the plasma are associated with inflammatory markers that reflect the severity of COVID-19 pneumonia. Int J Mol Sci. 2021;22(9):4978.
[79]. Wilk AJ, Lee MJ, Wei B, et al. Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19. J Exp Med. 2021;218(8):e20210582.
[80]. Klebanov N, Pahalyants V, Murphy WS, et al. Risk of COVID-19 in patients with cancer receiving immune checkpoint inhibitors. The Oncologist. 2021;26(5):e898–e901.
[81]. ICI impact on COVID-19 severity modest at best. Cancer Discov. 2020;10(10):1432–1433.
[82]. Pala L, Conforti F, Cocorocchio E, et al. Course of Sars-CoV2 infection in patients with cancer treated with anti-PD-1: a case presentation and review of the literature. Cancer Invest. 2021;39(1):9–14.
[83]. Suresh K, Naidoo J, Lin CT, Danoff S. Immune checkpoint immunotherapy for non-small cell lung cancer: benefits and pulmonary toxicities. Chest. 2018;154(6):1416–1423.
[84]. Tan J, Chen S, Lu Y, et al. Higher PD-1 expression concurrent with exhausted CD8+ T cells in patients with de novo acute myeloid leukemia. Chin J Cancer Res. 2017;29(5):463–470.
[85]. Kuipery A, Gehring AJ, Isogawa M. Mechanisms of HBV immune evasion. Antiviral Res. 2020;179:104816.
[86]. Tan J, Huang S, Huang J, et al. Increasing Tim-3+CD244+, Tim-3+CD57+, and Tim-3+PD-1+ T cells in patients with acute myeloid leukemia. Asia Pac J Clin Oncol. 2020;16(3):137–141.
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