Extended Essay
Title: The analysis of the density of CD8+ T-lymphocytes, PD-1 and TIGIT expressing T-lymphocytes in tumorous and healthy lymph nodes and the implications on possible cancer immunotherapies.
Research question: To what extent is the difference in the density of CD8+ lymphocytes, TIGIT and PD-1 checkpoint expression between tumorous and healthy lymph node tissue significant?
Subject: Biology
Word count:
Table of Contents
1.0 Personal Engagement 3
2.0 Background 3
3.0 Introduction 4
3.1 CD8+ T-Cells 6
3.2 PD-1 6
3.3 TIGIT 8
3.4 Immunohistochemistry 10
4.0 Research Questions 11
5.0 Predictions/Hypotheses 11
6.0 Samples 11
7.0 Method 12
7.1 Analysis 12
8.0 Results and t-Test analysis 13
9.0 Evaluation 16
10.0 Conclusion 16
11.0 Appendix 17
12.0 Bibliography 18
1.0 Personal Engagement
I chose this topic due to my interest in molecular biology and biomedicine underlying the mechanisms of action of medication. New treatments are constantly being developed in the hope for more efficient and specific cure of diseases. I wish to explore the impact of checkpoints on immunity inhibition and cancer development in more detail
2.0 Background
Cancer remains one of the main causes of human death; with 9.6 million mortalities worldwide in 2018 . Thus great efforts and resources are continually undertaken and invested to develop cancer treatments. Cancer cells are infamous in their resistance to chemotherapy, a standard approach for treating cancer. However, an enormous body of research strongly suggests that drug-resistant cancer cells that remain alive after chemotherapy are responsible for the reappearance of tumours and the poor prognosis for patients.
Different types of treatment, other than chemotherapy have therefore been an arising field of research in the continuous battle against cancer.
Unlike when faced with other diseases, the human immune system is often incapable of eradicating cancer as tumour cells use a variety of complex techniques to evade the immune system and avoid clearance.
T-cells recognize tumour antigens expressed by tumour cells but often fail to promote tumour regression in humans. Evidence shows that tumour antigen–specific (TA-specific) CD8+ T-cells (cytotoxic T-cells) become dysfunctional and exhausted upon chronic antigen exposure, losing their capacity to proliferate (to grow and divide), produce cytokines (signalling molecules that help in cell communication in immune responses), and lyse (breakdown) tumour cells. Dysfunctional TA-specific CD8+ T cells upregulate a number of inhibitory receptors including PD-1, which binds to their respective ligands expressed by antigen-presenting cells (APCs) and tumour cells, inhibiting T cell survival and functions in the tumour microenvironment. Blocking ligands targeting these inhibitory receptors successfully improve T cell responses in vitro and promote tumour regression in vivo in animals.
In contrast to traditional cytotoxic chemotherapy agents which interfere with cell proliferation and division non-specifically, destroying both healthy and tumour cells, such immunotherapies act on cancer cells indirectly through the regulation of the immune system.
Immunotherapies, like immune checkpoint blockade have reformed cancer treatment in recent years and are an established approach in the treatment of malignancies, cancerous tumours, such as melanoma, squamous and non-squamous non-small cell lung cancer, renal cell carcinoma, urothelial carcinoma, and head and neck squamous cell carcinoma.
Studies have proven a significant impact of immunotherapy versus standard care on patient outcomes, including extended survival and durable response.
Identifying the suitable therapy for individual cancer patients has become increasingly important as new immunotherapy treatments are approved and cancer care costs continue to rise.
3.0 Introduction
Immune checkpoint blockade is a rapidly developing innovative and has great potential to treat cancer and prevent future relapse by activating the immune system to recognize and kill cancer cells. It is an efficient treatment for cancer due to its antitumor effects induced by stimulating host immune responses for cytotoxic lymphocyte activities against cancer cells in the microenvironment. Molecular mechanisms that inhibit systemic metastasis of cancer would be a novel therapeutic candidate for patients affected. Cellular immunotherapy exhibits immense potential to be a highly-targeted alternative to traditional treatments, which possesses very low to zero toxicity to normal cells, unlike chemotherapy, and demonstrates notable capability to eradicate tumour cells.
Cellular immunotherapy often employs active immunization with immune cells, including infiltrating T-cells, effector T-cells and cytotoxic T cells, using adoptive transfer of T-cells from the patients themselves to directly target antigens on malignant tumour cells.
Immune checkpoint blockade focuses on the termination of immune responses by inhibiting immune suppressor molecules and increases activation of the immune system, which is needed for successful destruction of cancer. It thus prevents the termination of immune responses or even awakes cytotoxic T-lymphocytes that have become exhausted during an immune response. Therefore, blocking negatively regulating immune checkpoints restores the capacity of exhausted cytotoxic T-lymphocytes to kill the cancer they infiltrate. In addition, they drive surviving cancer cells into a still poorly defined state of dormancy.
PD-1 and TIGIT are both checkpoints, which inhibit T-cell activation and reduce the ability of the human immune system to attack tumour cells; their significance on tumour growth and development will be further investigated to evaluate whether immune checkpoint blockers targeted against these checkpoints could be valuable as treatment for cancer.
Whereas TIGIT is still in research as a possible checkpoint inhibitor, which could be used in future, PD-1 inhibitors are already in use.
Improvements in median overall survival associated with immune checkpoint blockers versus other therapies have been reported in several cancer types, including renal cell carcinoma treated with nivolumab (PD-1 inhibitor) versus the targeted agent everolimus, an immunosuppressant, a signal transduction inhibitor, which slows down tumour cell growth and division.
Use of immune checkpoint blockades has improved survival in melanoma over standard chemotherapy and has shown to significantly improve objective response rate when compared with standard therapies, for example in patients with melanoma, renal cell carcinoma, and non-small cell lung cancer with high PD-L1 (the ligand to PD-1) expression. Immune checkpoint blockers have also been shown to prolong duration of response when compared with standard therapies.
However, successful immunotherapy ultimately depends on the host immune cells, the tumour microenvironment and other characteristics which are not explicitly reflected in the tumour cells’ genetics. In addition, the efficiency of immunotherapies has been restricted by the lack of understanding regarding the processes underlying immune regulation and due to different exhibition of immunological fingerprints in different cancer types, which indicates that individually tailored immunotherapies for different cancer types, or even patients are needed. Much more efforts therefore need to be invested in the research of immunotherapies against cancer to develop cost-efficient and effective therapies.
3.1 CD8+ T-Cells
CD8+ T-cells are one of the main types of tumour infiltrating lymphocytes in cell-mediated immunity and play a central role in the induction of efficient immune responses against tumours due to their ability to kill malignant cells upon recognition of specific antigenic peptides presented on the surface of target cells by T-cell receptors. CD8+ T-cells can recognize tumour antigens bound to major histocompatibility complex class I (MHC I) molecules, which display fragments of foreign proteins from within the foreign cell (tumour cells) to cytotoxic T-cells on the tumour cells for these to directly kill them.
(Patient 10)
3.2 PD-1
Programmed cell death protein 1 has been gaining high attention, as inhibition of PD-1 provides the first immune therapy that significantly improves survival of patients with metastatic solid cancers. The PD-1 receptor is expressed on activated T cells, B cells, macrophages, regulatory T cells (Tregs) and natural killer (NK) cells.
PD-1 engagement through its B7 family of ligands, such as programmed death ligand 1 (PD-L1), negatively regulates T-cell mediated immune responses and results in suppression of proliferation and immune response of T-cells.
As PD-1 attaches to programmed death ligand (PD-L1), an antigen found on normal and tumour cells, cytotoxic T-cells are inhibited and then remain inactivated within the tumour microenvironment. Activation of PD-1/PD-L1 signalling serves as a principal mechanism by which tumours evade antigen specific T-cell immunologic responses.
By inhibiting natural killer cells, which can prevent spontaneous cancer cell metastasis, migration and invasion of cancer cells and activate other immune cells and thus inhibit tumour growth, high PD-1 expression can be fatal and have a significant negative impact on prognosis.
Binding of PD-1 to its B7 family of ligands, PD-L1 or B7-H1 or PD-L2 (B7-DC) results in suppression of proliferation and immune response of T-cells. Activation of PD-1/PD-L1 signalling serves as a principal mechanism by which tumours evade antigen specific T-cell immunologic responses. Antibody blockade of PD-1 or PD-L1 reverses this process and enhances antitumor immune activity and can prevent the inhibitory interaction and decrease tumour progression and therefore has been suggested to be an effective cancer immunotherapy.
PD-1 checkpoint inhibitors are now already approved for clinical practice in the treatment against unresectable or metastatic melanoma, metastatic non-small cell lung carcinoma, advanced renal cancer, relapsed or refractory classical Hodgkin lymphoma (adult patients), recurrent or metastatic head and neck squamous-cell carcinoma, locally advanced or metastatic urothelial cancer, metastatic, MSI-H or dMMR colorectal carcinoma (adult and paediatric patients) with nivolumab and pembrolizumab being the earliest PD-1 inhibitors.
Immune checkpoint blockade with anti–PD-1 antibodies has provided persistent clinical benefits for approximately 30% to 40% of patients with advanced melanoma in multiple clinical trials. In addition, dual PD-1 and CTLA-4 (a different immune checkpoint expressed in regulatory T-cells) blockade appears to further improve clinical outcome in patients. It is therefore expected that targeting multiple inhibitory pathways in the tumour microenvironment will prove useful for the majority of patients with advanced cancers, why two different immune checkpoints are investigated.
(Patient 10)
3.3 TIGIT
TIGIT, an antigen expressed by T- and natural killer cells (NK cells), natural killer T cells, CD8+, T regulatory and CD4+ memory cells, binds to PVR and other PVR-like (PVRL2 but not PVRL3) receptors and inhibits T-cell activity indirectly through the manipulation of dendritic cell activity.
TIGIT inhibits NK-mediated killing of tumour cells and protects normal cells from NK-mediated cytotoxicity thus providing an ‘’alternative self’’ mechanism for MHC I inhibition. TIGIT, through its ITIM motif (immunoreceptor tyrosine- based inhibitory motif), which decreases the activation of molecules involved in cell signalling through phosphorylation, can also directly inhibit NK cytotoxicity, which can prove fatal for patients affected by cancer as NK cells have been shown to inhibit systematic metastasis of cancer.
Through previous studies, it has been determined that TIGIT is upregulated on tumour antigen–specific (TA-specific) CD8+ T cells and CD8+ tumour-infiltrating lymphocytes from patients with melanoma, and these TIGIT-expressing CD8+ T cells often also coexpress the inhibitory receptor PD-1 and so experience a double inhibitory effect. Thus only targeting TIGIT or PD-1 would not necessarily be effective as cancer immunotherapy; only if both checkpoints are targeted under such circumstances would immunotherapy be effective.
In the presence of TIGIT ligand–expressing cells, TIGIT and PD-1 blockade have been found to additively increase proliferation, cytokine production, and degranulation of both tumour antigen specific CD8+ T cells and CD8+ tumour-infiltrating lymphocytes.
Collectively TIGIT and PD-1 regulate the expansion and function of tumour antigen-specific CD8+ T cells and CD8+ tumour infiltrating lymphocytes in patients with melanoma and suggest that dual TIGIT and PD-1 blockade should be further explored to provoke potent antitumor CD8+ T cell responses in patients with advanced melanoma and other cancer types.
TIGIT might therefore be a vital immunomodulator protein, able to control the activities of both NK and T-cells.
Elevated TIGIT expression appears to correlate with CD8 and PD-1 expression. TIGIT expression on CD8+ tumour infiltrating lymphocytes was observed several tumour samples.
TIGIT blockade synergized with PD-L1 blockade to enhance CD8+ tumour infiltrating lymphocytes functions in mice and promoted the rejection of transplanted tumours, while single-agent blockade had no effect, correlating with the suggestion, that blockade of only either TIGIT or PD-L1 has no beneficial effect on tumour regression. In addition, its role in regulating the expansion and function of tumour antigen-specific CD8+ T-cells in melanoma patients has not yet been investigated. TIGIT is upregulated and co-expressed with PD-1 on the majority of circulating tumour antigen-specific CD8+ T cells directed against cancer antigens.
All in all, recent evidence supports the use of TIGIT blockade in combination with PD-1 blockade to enhance CD8+ T cell responses to melanoma and improve the clinical efficiency of PD-1 blockade for patients with advanced melanoma and other cancer types.
(Patient 10)
3.4 Immunohistochemistry
Immunohistochemistry is a microscopy-based technique used to visualize cellular components, such as proteins or other macromolecules in tissue samples and to reveal the presence and localization of target-proteins in the context of different cell types, and subcellular localization within complex tissues.
4.0 Research Questions
To confirm the impact of PD-1 and TIGIT expression on the inhibition of immune activity, this investigation aims to determine a significant difference in the expression of these receptors between healthy and tumorous lymph nodes tissue.
Only by determining if a significant difference in expression of these both checkpoints between tumorous and healthy tissue exists, it can be suggested that PD-1 and TIGIT have an effect on tumour growth and therefore targeting these antigens will be beneficial in slowing down or stopping tumour growth.
In addition, by determining a significant difference of CD8+ T-cells density, it can be established that T lymphocytes are able to recognize antigens on tumour cells and are only unable to perform their cytotoxic functions, but might be stimulated to proliferate. Thus a basic immune response exists against tumour cells, although tumour cells are able to avoid lysing by CD8+ cells.
5.0 Predictions/Hypotheses
The density of TIGIT and PD-1 checkpoints will be higher in tumorous lymph node tissue. Due to inhibition of T-lymphocyte activity, immune cells are unable to kill tumour cells and allow faster growth and spreading of tumour cells, as these are able to evade antigen specific T-cell mediated responses.
As previously demonstrated, the density of CD8+ T-cells is higher in tumorous tissue than in healthy tissue (breast cancer).
Furthermore, regardless of significant difference in densities of CD8+ and PD-1, as well as TIGIT expression, it is expected that elevated TIGIT expression correlates with CD8 and PD-1 expression and vice versa.
Null Hypothesis: No significant difference in the density of CD8+ lymphocytes, TIGIT and PD-1 checkpoint expression between tumorous and healthy lymph nodes exists.
Alternative Hypothesis: A significant difference in the density of CD8+ lymphocytes, TIGIT and PD-1 checkpoint expression between tumorous and healthy lymph nodes exists.
6.0 Samples
Lymph node samples were chosen over other tissues because battling tumour cells in lymph nodes should especially be the centre of interest as the lymphatic system cause lymph node spread and are also the preferential site of initial tumour metastases. Moreover, lymph nodes are also the major components of the lymphatic system and crucial sites for the initiation of the immune responses.
Samples were collected from patients, with written and informed consent, affected by Hodgkin lymphoma (cancer originating in lymph nodes) (n=5), admitted to the Universitätsklinikum Hamburg. Prior to surgery, patients were asked for their consent and all required legal documents can be are stored in and can be provided by the Universitätsklinikum. Because I haven’t been given information about the patient number of the samples, confidential information about patients (overall survival, age, name, gender) has not been leaked, as this also was not of interest in the investigation.
Healthy lymph nodes were obtained from patients (n=5) having undergone a biopsy or other preventative removal (e.g. extensive swelling), but whose lymph nodes have not shown invasion by tumour cells.
A total of 4 cuts were taken from each lymph node sample and stained by the haematoxylin and eosin stain, stained for CD8+ (membrane stain), PD-1 (membrane stain) and TIGIT (membrane stain).
The samples from the patients were numbered 1-10, with patients 1-5 having healthy lymph nodes and patients 6-10 with tumorous lymph node tissue.
7.0 Method
Immunohistochemistry was used to analyse the slides for this investigation with an antibody concentration of 1:100.
Lymph node samples from the archive of the pathology institute were used and pre-cut as well as pre-stained as both processes involve hazardous chemicals (e.g. formaldehyde) and equipment not suitable to be handled by a inexperienced student without professional training.
The stained slides were then scanned in a pathology scanner.
7.1 Analysis
Select equal numbers of slides with lymph node tissue from healthy lymph nodes and tumour affected tissue
Clean slides using 70% Ethanol
Use brightfield digital pathology scanner and insert slides of interest to be scanned with 40x magnification (Aperio AT2 was used in this investigation)
Prior to scanning, name slides with organ_patient number_antibody
Scan slides
Open scanned slides in a pathology slide viewing software; use the same software for all slides
Use pen tool to mark areas to be analysed
Use negative pen tool to mark areas to be excluded from analysis (e.g. germinal centres, poor staining, dirt, air spaces, sparse areas. (Use HE slides do differentiate between healthy tissue and tumorous tissue) (Fig. 1)
Select suitable macro program for antibody to analyse slides
Open analysed slides and open analysis layer
Check the area analysed by macro program by adding up the areas included in analysis and subtracting the areas excluded from analysis
Copy values of interest into excel sheet: Cytoplasm: Percent (1+), Number of Cells, Area of Analysis (mm2) (Fig.2)
Find number of positive cells = Cytoplasm: Percent (1+)/100*Number of Cells
Find density in cells/mm2 = number of positive cells/Area of Analysis (mm2)
Use t-test to find significance between density of positive cells in tumorous and healthy lymph nodes (tail: 2, type: 3)
8.0 Results and t-Test analysis
I use the two-tailed t-Test to determine the variance between the average density of CD8+, PD-1 or TIGIT expression in healthy and tumorous lymph node tissue. The t-Test compares the average values from both samples and examines if both samples are taken from the same population. In this investigation the type 3 t-Test was used due to the different variance between the two samples.
CD8+ – Healthy lymph nodes
Patient 1 Patient 2 Patient 3 Patient 4 Patient 5
Cytoplasm: Percent (1+) 17.6538 27.672 37.2204 35.8196 26.873
Number of Cells 99633 194796 81982 48225 82514
Area of Analysis (mm2) 17.5663031 34.4133619 14.4328977 11.3342224 12.9415035
Number of CD8 positive cells 17589.0106 53903.9491 30514.0283 17274.0021 22173.9872
Density (cells/mm2) 1001.29267 1566.36684 2114.19973 1524.0571 1713.40117
Average Density (cells/mm2) 1583.8635
STDEV 358.136352
CD8+ – Tumorous lymph nodes
Patient 6 Patient 7 Patient 8 Patient 9 Patient 10
Cytoplasm: Percent (1+) 44.7176 37.4835 23.3242 26.7913 37.7306
Number of Cells 24080 583209 354658 55436 237380
Area of Analysis (mm2) 4.2374522 131.813268 73.0462311 7.71794015 37.1406651
Number of CD8 positive cells 10767.9981 218607.146 82721.1412 14852.0251 89564.8983
Density (cells/mm2) 2541.14915 1658.46086 1132.44914 1924.3509 2411.50497
Average Density (cells/mm2) 1933.583
STDEV 512.862346
t-Test: 0.29965011
PD-1 – Healthy lymph nodes
Patient 1 Patient 2 Patient 3 Patient 4 Patient 5
Cytoplasm: Percent (1+) 12.193 6.57796 8.74067 6.99797 3.49034
Number of Cells 686500 746523 283834 180195 342775
Area of Analysis (mm2) 37.1946265 42.6173308 14.1238208 11.1688143 20.2545555
Number of PD-1 positive cells 83704.945 49105.9843 24808.9933 12609.992 11964.0129
Density (cells/mm2) 2250.45801 1152.25387 1756.53555 1129.03588 590.682572
Average Density (cells/mm2) 1375.79318
STDEV 572.234387
PD-1 – Tumorous lymph nodes
Patient 6 Patient 7 Patient 8 Patient 9 Patient 10
Cytoplasm: Percent (1+) 2.0741 3.99508 57.7602 7.32521 7.22497
Number of Cells 69476 2169892 1223803 183353 817609
Area of Analysis (mm2) 3.7959839 124.827485 74.339562 8.31609139 47.935038
Number of PD-1 positive cells 1441.00172 86688.9213 706871.06 13430.9923 59072.005
Density (cells/mm2) 379.612178 694.469821 9508.67938 1615.06069 1232.33458
Average Density (cells/mm2) 2686.03133
STDEV 3437.86635
t-Test: 0.49187082
TIGIT – Healthy lymph nodes
Patient 1 Patient 2 Patient 3 Patient 4 Patient 5
Cytoplasm: Percent (1+) 8.7748 1.11632 1.3867 6.29E-02 0.260023
Number of Cells 83170 408306 194563 82620 47688
Area of Analysis (mm2) 14.9126189 24.9845674 13.3151391 12.5052721 10.8914987
Number of TIGIT positive cells 12402.8251 102013.488 25906.3341 10331.8558 5193.9379
Density (cells/mm2) 831.701327 4083.02874 1945.94981 826.491396 477.068353
Average Density (cells/mm2) 1632.84792
STDEV 1321.30935
TIGIT – Tumorous lymph nodes
Patient 6 Patient 7 Patient 8 Patient 9 Patient 10
Cytoplasm: Percent (1+) 8.16332 10.775 0.746762 15.1308 1.82808
Number of Cells 40143 2181751 810298 58305 26093
Area of Analysis (mm2) 3.66543731 119.470443 80.8600898 6.61846267 30.0948387
Number of TIGIT positive cells 1471.4165 2606547.58 655207.69 3858.89466 7852.64626
Density (cells/mm2) 401.341838 21817.582 8103.64459 583.137182 260.925024
Average Density (cells/mm2) 6233.32613
STDEV 8342.34229
t-Test: 0.33451275
Summary
Density (cells/mm2) STDEV TTEST
CD8 Non Tumorous 1583.8635 358.136352 0.29965011
Tumorous 1933.583 512.862346
PD-1 Non Tumorous 1375.79318 572.234387 0.49187082
Tumorous 2686.03133 3437.86635
TIGIT Non Tumorous 1632.84792 1321.30935 0.33451275
Tumorous 6233.32613 8342.34229
9.0 Evaluation
The significance level commonly used is =0,05. As the t-test used is two-tailed (testing for /2 difference in both directions of the reference value), I am looking for a t-test value greater than 0.975, as I compute 1-0.05/2, to reject the null hypothesis.
Although significant differences in densities of CD8+ T-lymphocytes between tumorous and healthy tissues have been detected previously ; such a result couldn’t be reproduced in this investigation. Furthermore, the use of PD-1 suppressor antibodies are already in clinical use, thus a significant difference of PD-1 expression between tumorous and healthy lymph nodes exists; this couldn’t be proved in this investigation either.
Against expectations, a significant difference in TIGIT expression between tumorous and healthy lymph nodes tissue could not been proved as well.
However, an apparent trend of higher density of CD8+ T-cells in tumorous tissue and also increased expression of PD-1 and TIGIT expression in tumorous tissue compared to healthy tissue is obvious, which correlates with the hypotheses. Moreover, TIGIT and PD-1 expression increased with CD8+ T-cell density overall, as average CD8+ density is higher in tumorous lymph nodes, together with PD-1 and TIGIT expression.
Moreover, a large standard deviation within samples leads me to the conclusion, that the expression of CD8+, PD-1 and TIGIT is not only affected by the presence of tumorous cells, but is also affected by lifestyle and genetic factors. As previous medical histories and lifestyle of the patients are unknown, these variables were not controlled and therefore decreases the level of reliability of the experiment.
10.0 Conclusion
Although the experiment is limited by significant weaknesses, with some alterations in the methodology (larger sample size and more careful cutting of tissue), more accurate and reliable results can be obtained.
The investigation is heavily limited by the reduced number of cases which has introduced inaccuracies and unreliability and should be repeated with a larger sample size. The small sample size limits the level to which healthy patients and patients affected by Hodgkin lymphoma are represented. Moreover, patients with similar lifestyle without previous medical incidences which could affect the expression of CD8+ cell, PD-1 and TIGIT should be used for future investigations.
Such research is especially important in the development of new immune checkpoint blockers for TIGIT, a relatively new area of interest (PD-1 immune checkpoint blockers are already in use) and new treatments for cancer.
11.0 Appendix
Fig. 1: Close up of analysed slide (Patient 1: each green cell is counted as positive for TIGIT)
Fig.1: Annotations (Patient 10: PD-1)
Fig.2:Macro analysis results (Patient 1: CD8+)
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