ELUCIDATING THE ROLES OF T-HELPER AND T-REGULATORY CELLS IN SARCOMA PATIENTS

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(1)M al. ay a. ELUCIDATING THE ROLES OF T-HELPER AND T-REGULATORY CELLS IN SARCOMA PATIENTS. U. ni. ve. rs i. ty. of. SARMINI A/P MUNISAMY. FACULTY OF MEDICINE UNIVERSITY OF MALAYA KUALA LUMPUR 2019.

(2) M al. ay a. ELUCIDATING THE ROLES OF T-HELPER AND T-REGULATORY CELLS IN SARCOMA PATIENTS. rs i. ty. of. SARMINI A/P MUNISAMY. U. ni. ve. DISSERTATION SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF MEDICAL SCIENCES. FACULTY OF MEDICINE UNIVERSITY OF MALAYA KUALA LUMPUR. 2019.

(3) UNIVERSITY OF MALAYA ORIGINAL LITERARY WORK DECLARATION. Name of Candidate: SARMINI A/P MUNISAMY Matric No: MGN 130055 Name of Degree: MASTER OF MEDICAL SCIENCE Title of Project Paper/Research Report/Dissertation/Thesis (“this Work”): CELLS IN SARCOMA PATIENTS Field of Study: TUMOUR IMMUNOLOGY. M al. I do solemnly and sincerely declare that:. ay a. ELUCIDATING THE ROLES OF T-HELPER AND T-REGULATORY. U. ni. ve. rs i. ty. of. (1) I am the sole author/writer of this Work; (2) This Work is original; (3) Any use of any work in which copyright exists was done by way of fair dealing and for permitted purposes and any excerpt or extract from, or reference to or reproduction of any copyright work has been disclosed expressly and sufficiently and the title of the Work and its authorship have been acknowledged in this Work; (4) I do not have any actual knowledge nor do I ought reasonably to know that the making of this work constitutes an infringement of any copyright work; (5) I hereby assign all and every rights in the copyright to this Work to the University of Malaya (“UM”), who henceforth shall be owner of the copyright in this Work and that any reproduction or use in any form or by any means whatsoever is prohibited without the written consent of UM having been first had and obtained; (6) I am fully aware that if in the course of making this Work I have infringed any copyright whether intentionally or otherwise, I may be subject to legal action or any other action as may be determined by UM. Candidate’s Signature. Date:. Subscribed and solemnly declared before, Witness’s Signature. Date:. Name: Designation:. ii.

(4) ELUCIDATING THE ROLES OF T-HELPER AND T-REGULATORY CELLS IN SARCOMA PATIENTS ABSTRACT Tumour cells can create microenvironments that suppress effective anti-tumour activity and interact with host defence mechanisms to support tumour development. The immune system is known to inhibit tumour growth. However, some immune cells could. ay a. promote tumour growth; i.e. T-regulatory (Treg) cells which play a vital role in tumour promotion and progression. Sarcomas are heterogeneous tumours of connective tissues. M al. which depend on angiogenesis for growth and metastasis, with slow progression and local aggressiveness. Those younger than 20-years old are more susceptible to sarcoma, which accounts for 1% of adult cancers; 11% of young adult cancers and 15% of childhood. of. cancers. 50% of sarcoma patients succumb to metastasis during disease progression. This study aims to elucidate the mechanism(s) of sarcomas’ modulation of the host immune. ty. system by studying the T – helper cells (Th), Treg cells, and associated cytokines.. rs i. Peripheral blood leucocytes (PBL) from sarcoma patients were used for flow cytometry. ve. analysis, gene expression studies, and analysis of cytokines. Flow cytometry analysis showed a reduction in the total population of CD4+ T-lymphocytes and Treg. ni. (CD4+CD25+FoxP3+) in sarcoma patients compared to healthy volunteers, but only the. U. former was statistically significant (p < 0.05). PBL from sarcoma and healthy volunteers were cultured in the presence of mitogen for cytokine analysis as plasma levels of cytokines were almost undetectable. Tumour necrosis factor-alpha (TNFα), interferongamma (IFNγ) (p < 0.05), interleukin-17A (IL-17A) were markedly decreased in sarcoma patients’ PBL compared to healthy volunteers. LAP-transforming growth factor-beta1 (LAP-TGF-β1) was significantly reduced (p < 0.05) in sarcoma patients compared to healthy volunteers despite giving higher yield. The quantitative polymerase chain reaction (qPCR) array used was annotated with primers for 84 genes involved in the iii.

(5) differentiation of CD4+ T-lymphocytes. qPCR analysis showed differential expression (p < 0.05) of five important genes involved in T-cell differentiation, namely homeobox A10 (HOXA10), C-C chemokine receptor type 3 (CCR3), GATA3, prostaglandin D2 receptor (PTDGR2) and thymocyte selection-associated high mobility group box (TOX) genes. HOXA10 expression was significantly (p < 0.05) upregulated in sarcoma patients whilst expressions of CCR3, GATA3, PTDGR2 and TOX were distinctly reduced (p <. ay a. 0.05). Expression of these genes with two others [T-cell-specific T-box transcription factor T-Bet (TBX21) and tumour necrosis factor superfamily member 11 (TNFSF11)] were validated using real-time polymerase chain reaction (RT-PCR) and it showed up-. M al. regulation (p > 0.05) of HOXA10 and TBX21 expression in sarcoma patients. Meanwhile, GATA3 and TNFSF1 expression were down-regulated in sarcoma patients. In conclusion,. of. Th cells and its associated cytokines were reduced in sarcoma patients compared to healthy volunteers. This finding suggests possible suppression of the host immune. ty. system in sarcoma patients, contributing to ineffective anti-tumour immune responses.. rs i. This hypothesis is further supported by the imbalance between the numbers of Th and Treg cells (p > 0.05) in sarcoma patients in this study. Expression of some genes. ve. responsible for the development and differentiation of CD4+ T-cells were also. ni. differentially expressed in sarcomas. Further studies are essential to conclude if the. U. regulation of these genes in immune cells has any significant impact on survival and progression of sarcomas.. Keywords: sarcoma, flow-cytometry, gene expression, enzyme-linked immunosorbent assay. iv.

(6) MENJELASKAN PERANAN SEL T-HELPER DAN T-REGULATOR DALAM PESAKIT SARKOMA ABSTRAK Perkembangan sel-sel tumor berpotensi mewujudkan persekitaran mikro yang menjejaskan keberkesanan fungsi anti-tumor dan menyumbang kepada kelangsungan hidup tumor melalui interaksi dengan mekanisme pertahanan tuan rumah. Walaupun. ay a. sistem imun mampu menyekat tumbesaran tumor, terdapat komponen yang menggalakkan pertumbuhan tumor, seperti sel T-regulator (Treg) yang berperanan penting dalam perkembangan tumor. Sarkoma adalah sejenis tumor heterogen yang. M al. terbentuk daripada tisu penghubung dan terdiri daripada 100 jenis. Kanser ini bergantung kepada proses angiogenesis untuk berkembang dan metastasis, dan berkembang secara. of. perlahan, dan agresif lokal/setempat. Pesakit berumur kurang dari 20 tahun lebih berisiko untuk mendapat penyakit ini. Kelaziman penyakit ini dalam populasi adalah seperti. ty. berikut: 1% daripada kes kanser dewasa; 11% daripada kes kanser remaja, dan 15%. rs i. daripada kes kanser kanak-kanak. 50% daripada pesakit sarkoma akhirnya meninggal dunia disebabkan oleh metastasis. Kajian ini bertujuan untuk mengkaji mekanisme. ve. modulasi sistem imuniti oleh sel T-pembantu/T-“helper” (Th), Treg, dan sitokin yang. ni. relevan dalam pesakit sarkoma. Leukosit darah periferal (LDP) dari pesakit sarkoma digunakan untuk menjalankan analisa “flow cytometry”, kajian ekspresi gen, dan analisis. U. sitokin. Analisis “flow cytometry” menunjukkan kekurangan ketara dalam jumlah populasi CD4+ T-limfosit dan Treg (CD4+ CD25+ FoxP3+) dalam pesakit sarkoma berbanding subjek normal, tetapi pengurangan T-limfosit sahaja signifikan (p < 0.05). LDP pesakit sarkoma dan subjek normal diperkembangbiakan dengan kehadiran mitogen untuk menganalisis perembesan sitokin kerana kadar sitokin utama dalam plasma hampir tidak dapat dikesan.. Keputusan analsis menunjukkan bahawa perembesan nekrosis. tumor-alpha (TNF), interferon-gamma (IFN) dan interleukin-17A (IL-17A) menurun. v.

(7) (p < 0.05) dalam pesakit sarkoma berbanding subjek normal. Perembesan LAP-TGF-β1 berkurang (p < 0.05) dalam pesakit sarkoma berbanding subjek normal walaupun kadar penghasilannya lebih tinggi. Kit “Quantitative Polymerase Chain Reaction” (qPCR) dalam kajian ini menggunakan primer untuk 84 gen yang terlibat dalam perkembangan CD4+ T-limfosit. Analisis qPCR menunjukkan perbezaan expresi (p < 0.05) lima gen utama dalam perkembangan sel T, iaitu homeobox A10 (HOXA10), C-C chemokine. ay a. receptor type 3 (CCR3), GATA3, prostaglandin D2 receptor (PTDGR2), dan thymocyte selection-associated high mobility group box (TOX). Ekspresi gen HOXA10 meningkat secara signifikan (p < 0.05) dalam pesakit sarkoma manakala ekspresi gen CCR3, GATA3,. M al. PTDGR2 dan TOX berkurang secara ketara (p < 0.05). Ekspresi gen – gen ini dan dua lagi gen [T-cell-specific T-box transcription factor T-Bet (TBX21) and tumour necrosis. of. factor superfamily member 11 (TNFSF11)] disahkan melalui “real-time polymerase chain reaction” (RT-PCR). Keputusan RT-PCR menunjukkan peningkatan (p > 0.05) ekspresi. ty. gen HOXA10 dan TBX21 dan pengurangan ekspresi gen GATA3 dan TNFSF11 dalam. rs i. pesakit sarkoma. Secara kesimpulan, sel Th dan sitokin yang berkaitan berkurang dalam pesakit sarkoma berbanding subjek normal. Hasil kajian ini mendapati bahawa sistem. ve. imuniti pesakit sarkoma terjejas, justeru menyumbang kepada pengurangan keberkesanan. ni. sistem imuniti anti - tumor. Hipotesis ini disokong oleh ketidakseimbangan (p > 0.05) antara sel Th dan T-reg dalam pesakit sarkoma dalam kajian ini. Ekspresi beberapa gen. U. yang terlibat dalam perkembangan CD4+ T-sel juga didapati berbeza dalam pesakit sarkoma. Kajian lanjut adalah disarankan untuk lebih mendalami kesan aktiviti gen – gen dalam sel imun ini ke atas perkembangan sarkoma dan kelangsungan hidup pesakit sarkoma. Kata kunci: sarkoma, “flow-cytometry”, expresi gen, “enzyme-linked immunosorbent assay”. vi.

(8) ACKNOWLEDGEMENTS. First and foremost, I would like to thank the Almighty for His continuous shower of blessing during this journey.. To Professor Dr Vivek Ajit Singh, my supervisor, I am very grateful for the opportunity given to me to pursue my Master’s degree under him. I am thankful for the. ay a. patience, guidance, advice, understanding, financial support, and knowledge rendered by him throughout this research.. M al. To Professor Dr Ammu Kutty Radhakrishnan, my co-supervisor, I would like to extend my gratitude for giving me an opportunity to join her research team to pursue this degree.. of. I would also like to thank her for her immense guidance, advice, emotional support, understanding as well as help in acquiring new knowledge in tumour immunology. This. ty. dissertation would not be possible without her guidance and support.. rs i. To Associate Professor Dr Puteri Shafinaz Akmar Abdul Rahman from Department of. ve. Molecular Medicine, UM, thank you for your kindness to spare me a small space in your. ni. lab to carry out the initial stage of my project.. U. To all staff from the Department of Molecular Medicine and Research Lab Office,. IMU, thank you for your kindness and assistance in need of help. Not forgetting staff from Department of Orthopaedic Surgery, UM, thank you for your support.. To all sarcoma patients and healthy volunteers who have donated their precious blood for this research and special thanks to all the doctors and housemen posted to Orthopaedic Oncology Unit, who helped with the blood sample collection for my project.. vii.

(9) I also would like to take this opportunity to gratefully acknowledge the funding received from University of Malaya, University Malaya Research Grant (UMRG RG376/11HTM), Higher Education of Malaysia (MyBrain15), University of Malaya (SBUM) and Miss Malaysia Indian Care Association (Gift Her with Life Education Grant) to pursue my Master’s degree.. ay a. To all my wonderful friends, colleagues and lab mates from UM and IMU; Bavani, Thanes, Priscilla, Haema Ng, Shonia, Jeya Seela, Vaani, Geetha, Premdass, Rupini, Venotha, Saravana, Kak Iz, Lee, Ann, Aizat, Kak Aty, Pariviny, and Dr. Sangeetha, thank. kept me going and motivated.. M al. you for your invaluable guidance, help, and support during my hard times which always Not forgetting Timah, Chor Yin, Shanta, Ramona,. Puvanes, Jaime, Li Zhe, Rathi, and Kasturi for being very encouraging, supportive, and. of. helpful whenever possible. Without all of you, this project will not have been completed.. ty. Last but not least, a special thanks and appreciation goes to my mother, Madam. rs i. Paramayswari who was always there to encourage, motivate, and provide me with. ve. financial support throughout my Master’s journey. Thank you to my family members, for. U. ni. their warmth of love, encouragement, and motivation both emotionally and financially.. Sarmini Munisamy 2019. viii.

(10) TABLE OF CONTENTS. Abstract ...................................................................................................................... iii Abstrak ......................................................................................................................... v Acknowledgements ..................................................................................................... vii Table of Contents ......................................................................................................... ix List of Figures ............................................................................................................ xiv. ay a. List of Tables ............................................................................................................. xvi List of Symbols and Abbreviations ........................................................................... xvii. M al. List of Appendices .................................................................................................... xxii. CHAPTER 1: INTRODUCTION............................................................................... 1 Background ......................................................................................................... 1. 1.2. Research Question ............................................................................................... 4. 1.3. Research Hypothesis ............................................................................................ 4. 1.4. Research Objectives ............................................................................................. 5 General Objective ................................................................................... 5. ve. 1.4.1. rs i. ty. of. 1.1. Specific Objectives ................................................................................. 5. ni. 1.4.2. U. CHAPTER 2: REVIEW OF LITERATURE ............................................................. 6 2.1. Overview of Sarcoma .......................................................................................... 6. 2.2. Bone Tumours ..................................................................................................... 9. 2.3. 2.2.1. Osteosarcoma .......................................................................................... 9. 2.2.2. Chondrosarcoma ................................................................................... 10. 2.2.3. Ewing’s sarcoma ................................................................................... 11. Soft Tissue Sarcoma .......................................................................................... 12 2.3.1. Pleomorphic sarcoma ............................................................................ 12. ix.

(11) 2.3.2. Liposarcoma ......................................................................................... 13. 2.3.3. Synovial sarcoma .................................................................................. 14. 2.3.4. Extra-skeletal osteosarcoma .................................................................. 15. 2.4. Management of Sarcoma ................................................................................... 15. 2.5. Overview of Immune System ............................................................................. 18. 2.6. T-lymphocytes Cells .......................................................................................... 21 Th cells ................................................................................................. 23. ay a. 2.6.1. 2.6.1.1 Th1 cells ................................................................................. 24 2.6.1.2 Th2 cells ................................................................................. 25. M al. 2.6.1.3 Th17 cells ............................................................................... 25 2.6.1.4 Th9 cells ................................................................................. 27. of. 2.6.1.5 Th22 cells ............................................................................... 27 2.6.1.6 T-follicular helper cells........................................................... 28 Treg cells .............................................................................................. 28. ty. 2.6.2. rs i. 2.6.2.1 Natural Treg cells ................................................................... 30 2.6.2.2 Peripheral induced Treg cells .................................................. 31. T-cell plasticity ..................................................................................... 32. ve. 2.6.3. Tumour Immunoregulation ................................................................................ 35. ni. 2.7. U. 2.7.1. Cancer Immunoediting .......................................................................... 35. 2.7.2. Anti-Tumour Immune Response ........................................................... 39. 2.7.3. Tumour Promoting Immune Response .................................................. 40. 2.7.4. Tumour Immunoregulation in Sarcoma …………………………………40. CHAPTER 3: MATERIALS AND METHODS ...................................................... 42 3.1. Materials ............................................................................................................ 42 3.1.1. Collection of Blood and Plasma Samples .............................................. 42. x.

(12) 3.1.2. Cell Culture .......................................................................................... 42. 3.1.3. Gene Expression Studies ....................................................................... 42. 3.1.4. Flow-cytometry Analysis ...................................................................... 43. 3.1.5. Enzyme-linked Immunosorbent Assay Analysis .................................... 43. 3.1.6. General Consumables............................................................................ 44. Instrumentation .................................................................................................. 44. 3.3. Methods ............................................................................................................. 46. ay a. 3.2. Recruitment of Patients ......................................................................... 46. 3.3.2. Recruitment of Healthy Volunteers ....................................................... 48. 3.3.3. Sample Size .......................................................................................... 48. 3.3.4. Sample Collection ................................................................................. 49. 3.3.5. Sample Transport and Storage ............................................................... 50. 3.3.6. Flow-Cytometry Analysis ..................................................................... 50. of. M al. 3.3.1. ty. 3.3.6.1 Preparation of buffers ............................................................. 50. rs i. 3.3.6.2 Preparation of mononuclear cells ............................................ 51 3.3.6.3 Cell count using haemocytometer ........................................... 51. ve. 3.3.6.4 Staining cells with FoxP3 ....................................................... 52. ni. 3.3.6.5 Analysis using flow cytometer ................................................ 54. U. 3.3.7. Gene Expression Study ......................................................................... 54 3.3.7.1 Extraction of total RNA from peripheral blood leucocytes ...... 54 3.3.7.2 Integrity and quality of RNA .................................................. 56 3.3.7.3 PCR array............................................................................... 56 3.3.7.4 Validation of gene expression by quantitative Real-time PCR. 59. 3.3.8. Culturing of Human Peripheral Mononuclear Cells ............................... 62 3.3.8.1 Isolation of PBMCs ................................................................ 62 3.3.8.2 Cell counting .......................................................................... 62. xi.

(13) 3.3.8.3 Preparation of Concanavalin A stock solution ......................... 63 3.3.8.4 Cell Proliferation Assay (MTT Assay) .................................... 63 3.3.8.5 Effect of Con A on T-lymphocyte Cells ................................. 63 3.3.8.6 Culturing of peripheral blood lymphocytes ............................. 63 3.3.9. Quantification of Cytokines .................................................................. 65 3.3.9.1 Preparation of coating buffer .................................................. 65. ay a. 3.3.9.2 Preparation of wash buffer ...................................................... 65 3.3.9.3 Preparation of assay diluent .................................................... 65 3.3.9.4 Preparation of capture antibody .............................................. 66. M al. 3.3.9.5 Preparation of detection antibody ........................................... 66 3.3.9.6 Preparation of avidin-horseradish peroxidase .......................... 66. of. 3.3.9.7 Preparation of stop solution .................................................... 66 3.3.9.8 Enzyme-linked immunosorbent assay ..................................... 67. rs i. ty. 3.3.9.9 Statistical analysis .................................................................. 68. CHAPTER 4: RESULTS .......................................................................................... 69 Demographic Data ............................................................................................. 69. 4.2. Flow Cytometry Analysis .................................................................................. 71. ni. ve. 4.1. 4.2.1. Gene Expression ................................................................................................ 80. U. 4.3. 4.4. Level of Treg Cells in Peripheral Blood ............................................... 75. 4.3.1. Human Th Cell Differentiation Array .................................................... 81. 4.3.2. Validating Differentially Expressed Genes in Sarcoma Patients ............ 87. Cytokine Analysis .............................................................................................. 93 4.4.1. Effect of Con A on the Viability of Peripheral Blood T-lymphocytes..... 93. 4.4.2. Production of Cytokines ........................................................................ 95 4.4.2.1 IL-17A levels ......................................................................... 99. xii.

(14) 4.4.2.2 TNFα levels ............................................................................ 99 4.4.2.3 IFNγ levels ........................................................................... 104 4.4.2.4 LAP-TGF-β1 levels .............................................................. 104. CHAPTER 5: DISCUSSION .................................................................................. 110 Flow-cytometry Analysis ................................................................................. 110. 5.2. Gene Expression Study .................................................................................... 116. 5.3. Quantification of Cytokines ............................................................................. 127. ay a. 5.1. M al. CHAPTER 6: CONCLUSION ............................................................................... 136 6.1. Conclusion....................................................................................................... 136. 6.2. Limitations of the Study................................................................................... 138. Proposal for Future Studies .............................................................................. 141. ty. 6.3. Sample Size Variation for Downstream Analysis ................................ 139. of. 6.2.1. rs i. References ................................................................................................................ 143 List of Publications and Papers Presented ................................................................. 165. U. ni. ve. Appendix .................................................................................................................. 167. xiii.

(15) LIST OF FIGURES. Figure 2.1: Host defence mechanism of the immune system and types of cells responsible for innate and adaptive immunities ............................................................................. 20 Figure 2.2: Development and survival of T-lymphocytes ........................................... 23 Figure 2.3: Differentiation of naïve CD4+ T cells into different effector T-lymphocyte subsets ....................................................................................................................... 24. ay a. Figure 2.4: Development of nTreg and iTreg cells and their associated cytokines ....... 33 Figure 2.5: CD4+ T cell lineage differentiation plasticity ............................................ 35. M al. Figure 2.6: Three phases of immunoediting; Elimination phase, Equilibrium phase, and Escape phase .............................................................................................................. 37 Figure 3.1: Flow chart of the study.............................................................................. 47 Figure 4.1: Representative flow-cytometry results of PBMCs from a healthy subject . 72. ty. of. Figure 4.2: Comparing the mean percentage of CD4+ T-cells in (a) sarcomas patients with healthy volunteers and in (b) bone and soft tissue sarcoma patients with healthy volunteers . .................................................................................................................................. 74. ve. rs i. Figure 4.3: Comparing the mean percentage of Th cells in (a) sarcomas patients with healthy volunteers and in (b) bone and soft tissue sarcoma patients with healthy volunteers. .................................................................................................................. 76. ni. Figure 4.4: Representative flow cytometry results of PBMCs from a healthy volunteer showing (a) Total CD4+ T-cell population and (b) Treg cells ...................................... 77. U. Figure 4.5: Comparing the mean percentage of Treg cells in (a) sarcomas patients with healthy volunteers and in (b) bone and soft tissue sarcoma patients with healthy volunteers ................................................................................................................................... 79 Figure 4.6: Representative melt curves of RNA from (a) healthy volunteers and (b) sarcoma patients following quantitative PCR array .................................................... 83 Figure 4.7: Scatter plot comparing the normalised expression of all genes in human Thelper cell differentiation PCR array .......................................................................... 84 Figure 4.8: Differentially expressed genes in peripheral blood leucocytes of soft tissue sarcoma patients compared to healthy volunteers . ...................................................... 85 Figure 4.9: Representative amplification plots from quantitative real-time PCR ......... 88. xiv.

(16) Figure 4.10: Scatter plot showing selected genes of interest from qPCR array used for validation using real-time quantitative PCR method ................................................... 90 Figure 4.11: Comparing expressions of selected genes in (a) soft tissue sarcoma patients, (b) bone sarcoma patients and (c) sarcoma patients against healthy volunteers . .......... 92 Figure 4.12: Effect of different concentrations of Concanavalin A on the proliferation of human T-lymphocyte cells from peripheral blood ...................................................... 94 Figure 4.13: Comparing concentration of IL-17A in the culture supernatant of PBMCs from sarcoma patients and healthy volunteers . ......................................................... 100. ay a. Figure 4.14: Comparing concentration of TNFα in the culture supernatant of PBMCs from sarcoma patients and healthy volunteers . .................................................................. 102. M al. Figure 4.15: Comparing concentration of IFNγ in the culture supernatant of PBMCs from sarcoma patients and healthy volunteers ................................................................... 105 Figure 4.16: Comparing concentration of LAP TGF-β1 in the culture supernatant of PBMCs from sarcoma patients and healthy volunteers . ............................................ 107. of. Figure 4.17: Comparing plasma levels of LAP TGF-β1 from sarcoma patients and healthy volunteers . ............................................................................................................... 109. rs i. ty. Figure 5.1: Gene network of human Th cell differentiation generated using STRING CONSORTIUM 2019 software for sarcoma patients versus healthy volunteers . ....... 119. U. ni. ve. Figure 5.2: Gene network of epigenetically regulated genes in T-cell subsets generated using STRING CONSORTIUM 2019 software for sarcoma patients versus healthy volunteers. ................................................................................................................ 120. xv.

(17) LIST OF TABLES. Table 2.1: Summary of cytokines, transcriptional factors and functions of T-cells ....... 34 Table 3.1: List of major equipment used in this study .................................................. 45 Table 3.2: Inclusion and exclusion criteria used in patient selection ............................ 46 Table 3.3: Types of blood tubes used in the study ....................................................... 49. ay a. Table 3.4: Transport and storage of blood samples ...................................................... 50 Table 3.5: Genomic DNA elimination reaction mix..................................................... 57. M al. Table 3.6: Reverse-transcriptase reaction mix ............................................................. 57 Table 3.7: PCR reaction mix ....................................................................................... 58 Table 3.8: PCR cycling programme ............................................................................ 59. of. Table 3.9: Forward and reverse primers used in this study........................................... 59 Table 3.10: The real-time PCR reaction master mix .................................................... 61. rs i. ty. Table 3.11: Real-time cycling program for Bio-Rad CFX96TM Touch Real-Time PCR Detection System ........................................................................................................ 61 Table 4.1: Demographic data of sarcoma patients and healthy volunteers .................... 69. ve. Table 4.2: Demographic data of sarcoma patients and healthy volunteers according to analysis ....................................................................................................................... 70. U. ni. Table 4.3: Shapiro – Wilk Normality test for peripheral blood CD4+ T-cells and Th cells ................................................................................................................................... 73 Table 4.4: Shapiro – Wilk Normality test for peripheral blood Treg cells .................... 78 Table 4.5: Quality, quantity and integrity of RNA used for PCR array ........................ 81 Table 4.6: The grouping and types of genes differentially regulated in sarcoma patients ................................................................................................................................... 86 Table 4.7: Shapiro – Wilk Normality test for four different key cytokines concentration related to T-lymphocytes in culture supernatant and blood plasma .............................. 96. xvi.

(18) %. :. percentage. >. :. more than. ≥. :. more or equal to. º. :. degree. ºC. :. degree Celsius. γδ. :. gamma-delta. 260/230. :. absorbance ratio of 260/230. 260/280. :. absorbance ratio of 260/280. exclusion/elimination, equilibrium, and escape :. absorbance at 230 nm. A280. :. absorbance at 280 nm. A450/450nm. :. absorbance at 450 nm. A570/570nm. :. absorbance at 570 nm. AHR. :. aryl Hydrocarbon Receptor. Ags. :. antigens. APC. :. allophycocyanin. APCs. :. antigen presenting cells. B2M. :. beta-2-microglobulin. BC3 Bcl-6. of. reverse transcription buffer 3. :. B-lymphocytes. :. B-cell lymphoma 6 protein. :. Becton Dickinson. :. base pair. BTLA. :. B- and T-lymphocyte attenuator. CBA/H. :. radiation-induced acute myeloid leukaemia sensitivity 1. CCR. :. C-C chemokine receptor. CD. :. cluster of differentiation. CD40-CD40L. :. CD40 – CD40 ligand. CD62L. :. L-selectin. cDNA. :. complementary deoxyribonucleic acid. cells/mL. :. cells per millilitre. c-Maf. :. transcription factor Maf. CO2. :. carbon dioxide. Con A. :. Concanavalin A. CPT. :. cell preparation tube. CRTh2. :. prostaglandin D2 receptor 2. ni. bp. U. ve. BD. :. rs i. B-cells. M al. A230. ty. 3Es. ay a. LIST OF SYMBOLS AND ABBREVIATIONS. xvii.

(19) :. threshold cycle. CT. :. computer tomography. CTL. :. cytotoxic T-lymphocytes. CTLA-4. :. cytotoxic T-lymphocyte associated protein 4. CXCL. :. Chemokine (C-X-C motif) ligand. CXCR. :. CXC chemokine receptor. CXR. :. chest X-ray. DC. :. dendrite cells. dH2O. :. double distilled water. DMSO. :. dimethyl-54-sulfoxide. DNA. :. deoxyribonucleic acid. EBV. :. Epstein-Barr virus. EL. :. erythrocyte lysis. ELISA. :. enzyme-linked immunoabsorbent assay. ESR. :. erythrocyte sedimentation rate. et al.. :. Et alia (and others). FACS. :. fluorescence-activated cell sorting. FITC. :. fluorescein isothiocyanate. Foxp3. :. forkhead box P3. g. :. gram. GAPDH. ty. GM-CSF. M al. of. glyceraldehyde 3-phosphate dehydrogenase. :. gDNA elimination. :. sranulocyte-macrophage colony-stimulating factor. :. sulphuric acid. ve. H2SO4. :. rs i. GE. ay a. CT. :. null hypothesis. HA. :. research hypothesis. HEPES. :. 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid. HIV. :. human immunodeficiency virus. HOXA10. :. homeobox A10. HRP. :. horseradish peroxidase. ICAM-1. :. intracellular adhesion molecule 1. ICOS. :. inducible co-stimulatory molecule. IFNγ. :. interferon-gamma. Ig. :. immunoglobulin. IgG1. :. immunoglobulin G1. IL. :. interleukin. IL-1β. :. interleukin-1 beta. IL-4Rα. :. Interleukin-4 receptor alpha. U. ni. H0. xviii.

(20) :. interferon regulatory factor 4. iTregs. :. induced T-regulatory cells. kD. :. kilodalton. KSHV. :. Kaposi’s sarcoma-associated herpes virus. L. :. litre. LAP. :. latency-associated peptide. LDH. :. lactose dehydrogenase. LPS. :. lipopolysaccharides. LSS. :. limb-sparing surgery. MCA. :. methyl-cholantherene. MDSCs. :. myeloid-derived suppressor cells. µg. :. microgram(s). µg/ml. :. micrograms per millilitre. µl. :. microliter(s). µL/well. :. microliters per well. µM. :. micrometre(s). mg. :. milligram. mg/mL. :. milligrams per millilitre. MHC. :. major histocompatibility complex. ml. :. millilitre. mm. ty. MRI. M al. of. millimetre. :. mononuclear cells. :. magnetic resonance imaging. :. 3-(4,5-Dimethyl-2-thiozolyl)-2,5-diphenyl-2H-tetrazolium bromide. :. National Center for Biotechnology Information. ng. :. nanogram. nm. :. nanometre. nM. :. nanomolar. NK. :. natural killer. NKT. :. natural killer T-cells. NPC. :. nasopharyngeal carcinoma. nTregs. :. naturally occurring T-regulatory cells. PAMP. :. pathogen-associated molecular-pattern. PBMC. :. peripheral blood mononuclear cells. PBS. :. phosphate-buffered saline. PCR. :. polymerase chain reaction. PD-1. :. programmed cell death protein 1. PE. :. phycoerythrin. ni. NCBI. U. ve. MTT. :. rs i. MNC. ay a. IRF-4. xix.

(21) Pen-Strep. :. penicillin and ptreptomycin. pg. :. picogram. pg/ml. :. picograms per millilitre prostaglandin E2. :. potential of hydrogen. PRRs. :. pattern-recognition receptors. pMHC. :. peptide major histocompatibility complex. p-STAT3. :. phospho-Stat3. PTDGR2. :. prostaglandin D2 receptor. PU.1.. :. haematopoietic Transcription Factor. qPCR. :. quantitative polymerase chain reaction. qRT-PCR. :. quantitative real-time polymerase chain reaction. RBC. :. red blood cell. RE3. :. reverse transcriptase enzyme mix 3. RNA. :. ribonucleic acid. ROR-α. :. retinoic acid-related orphan receptor α. ROR-γt. :. retinoic acid-related orphan receptor-γ-t. ROX. :. carboxy-X-rhodamine. rpm. :. revolution per minute. RPMI. :. Roswell Park Memorial Institute. RT SAP. M al. of. reverse transcriptase. :. second. :. SLAM-associated protein. :. Surveillance, Epidemiology, and End Result. :. signalling lymphocytic activation molecule. SSX1. :. synovial sarcoma, X break point 1 (homo sapiens). SSX2. :. synovial sarcoma, X break point 2 (homo sapiens). SSX4. :. synovial sarcoma, X break point 4 (homo sapiens). STAT. :. signal transducer and activator of transcription. STS. :. soft tissue sarcoma. SYBR. :. Synergy Brands, Incorporated. SYT. :. Synovial sarcoma translocation, chromosome 18 (homo sapiens). TA. :. Tumour antigens. TAMs. :. Tumour-associated macrophages. T-bet. :. T-box transcription factor. TBX21. :. T-box transcription factor 21. T-cells. :. T-lymphocytes. TCR. :. T-cell receptors. ni. SLAM. U. ve. SEER. :. rs i. sec. ay a. pH. ty. PGE2. xx.

(22) :. follicular helper T-cells. Th. :. T-helper. TGF-β. :. transforming growth factor-beta. TLRs. :. toll-like receptors. TNFα. :. tumour necrosis factor-alpha. TNFSF11. :. tumour necrosis factor superfamily member 11. Tr1. :. type-1 regulatory T-cells. Treg. :. T-regulatory. TOX. :. T-box. U/mL. :. units per millilitre. US. :. United States. VEGF. :. vascular endothelial growth factor. WBC. :. white blood cells. WHO. :. World Health Organisation. xg. :. acceleration due to gravity. U. ni. ve. rs i. ty. of. M al. ay a. Tfh. xxi.

(23) LIST OF APPENDICES Appendix A: Sample Size Determination Table ……………………………….... 166. Appendix B: Medical Ethics Committee Approval Letter ……………………… 167 170. Appendix D: Study Consent Form ………………………………………………. 174. U. ni. ve. rs i. ty. of. M al. ay a. Appendix C: Participation Information Sheet ………………………………….... xxii.

(24) CHAPTER 1: INTRODUCTION. 1.1. Background. Based on research findings over the last few decades; the dual role of the immune. ay a. system in promoting and suppressing tumour growth in order to maintain equilibrium between immune recognition and tumour development is well-established. In addition, the interplay between cancer cells, normal stromal cells, and host defence mechanisms. M al. gives rise to tumour development and survival (Vinay et al., 2015). Naturally, the immune system prevents tumours either by resolving inflammation, eliminating and suppressing oncogenic viral infections or immune surveillance (Prestwich et al., 2008; Swann &. of. Smyth, 2007). Immune surveillance is a process through which the immune system can. ty. detect, recognize, and destroy cancer cells (Zaenker, Gray, & Ziman, 2016). However,. rs i. many cancer patients, despite having a functioning immune system, succumb to cancer (Prestwich et al., 2008). The immune escape mechanisms used by cancer cells to evade. ve. the immune system can be explained using the immunoediting concept (Mittal, Gubin,. ni. Schreiber, & Smyth, 2014).. U. There are three important stages in immunoediting, known as the “3E”; which are (i). exclusion or elimination; (ii) equilibrium and (iii) escape (Yuying Liu et al., 2017). In the exclusion stage, cancer cells are excluded or eliminated in accordance with immune surveillance, whereby the immune system detects and destroys cancer cells. Following this, equilibrium is achieved when new tumour variants that lack tumour antigens (TA) are generated despite the elimination process. At this stage, tumours with reduced TA remain dormant, thus, falling out of the surveillance radar of the host immune system; subsequently leading to tumour escape (Nouroz, Bibi, Noreen, & Masood, 2016; Swann 1.

(25) & Smyth, 2007; Vinay et al., 2015). There is also evidence that tumours produce a broad array of immune inhibitory factors, which exert either local or systemic effects on the host anti-tumour immune responses (Whiteside, 2010). Depending on the nature of tumour-host interactions, these inhibitory factors might cause the resulting immune responses to be weak, inefficient or even absent in patients with cancer.. ay a. The adaptive immune system plays a vital role in the elimination and prevention of cancer cells development and progression (den Haan, Arens, & van Zelm, 2014). The adaptive immune response is mediated by T-lymphocytes (T-cells) and B-lymphocytes The T-cells are reported to engage in mediating cell-mediated immune. M al. (B-cells).. responses, whilst B-cells are involved in producing humoral cell responses (Nouroz et al., 2016). The T-cells that express the glycoprotein CD4 on its cell surface are known as. of. CD4+ T-cells, which differentiate into several types of T-cells such as Th1 and Th2 and. ty. others, which possess specific biological functions. In cancer development, the Th1 cells provide the stimulus that boosts anti-tumour immune responses through activation of. rs i. tumour-specific cytotoxic T-lymphocytes (CTL) (Bailey et al., 2014).. The CTLs. ve. expresses the glycoprotein CD8 on its’ cell surface and are also known as CD8+ T-cells. Both Th1 cells and CTLs control cancer growth through the production of interferon-. U. ni. gamma (IFNγ) and cytotoxins (Vinay et al., 2015).. There is another subset of T-cells known as the Treg cells. These cells express CD4. and CD25 glycoprotein on the cell surface as well as express the transcription factor FoxP3 (Vinay et al., 2015). These cells are also known as CD4+CD25+FoxP3+. The Treg cells can function as immune suppressors by inhibiting the actions of CTLs (Bailey et al., 2014; Vinay et al., 2015). The Tregs can be found in the tumour microenvironments. Studies have shown that tumour-derived Tregs has a higher suppressive effect compared to naturally occurring Treg (nTreg) (Vinay et al., 2015). 2.

(26) More recently, another subset of CD4+ have been reported (Langrish et al., 2005). This subset is known as Th17. The Th17 cells also appear to play a role in tumour immunity (Zamarron & Chen, 2011). Some studies have reported that Th17 cells can help to destroy tumours (Bailey et al., 2014) whilst other studies have found that Th17 cells promote cancer progression (Tosolini et al., 2011). The results appear to contradict each other. However, more recently, researchers have concluded that the role of Th17 cells in tumour. microenvironment (Bailey et al., 2014).. ay a. immunity is strongly influenced by several factors faced by these cells in the tumour. M al. Innate immune responses against tumours able to activate adaptive immune response through distinctive signals. For instance, natural killer (NK) cells play a significant role in immune surveillance by inhibiting tumour development (Turvey & Broide, 2010). The. of. activities of T-cells and dendritic cells (DC) can be regulated by NK cells through. ty. production of IFNγ (Dunn, Koebel, & Schreiber, 2006). New findings showed that NK cell-derived IFNγ leads macrophages to cancer cells and protect the host from. rs i. tumourigenesis (Nouroz et al., 2016). The T-cells, which are part of the adaptive immune. ve. response also secrete a broad array of cytokines, which affect the immune environment (Torok et al., 2015). Recently, some cytokines have been linked to cancer progression. U. ni. due to their ability to stimulate cell growth and induce metastasis (Filho et al., 2014).. In the literature, there are only a few studies looking into the relationship between the. host immune system and sarcomas. Sarcomas are a heterogeneous group of malignant tumours arising from mesenchymal cells (DuBois & Demetri, 2007), muscles, tendons, and bones. In general, sarcomas account for approximately 1% of all adult tumours and 12-15% of paediatric malignancies (Foster et al., 2003; Olmos, Tan, Jones, & Judson, 2010). Most sarcomas are slow growing and aggressive locally. Since sarcomas are of mesenchymal origin, they depend on angiogenesis for growth and metastasis (DuBois & 3.

(27) Demetri, 2007). Sarcomas tend to metastasize to nodules (3-10%) and other organs (28%). Common sites for metastases include lungs, bone, liver, and central nervous system, especially in high-grade sarcomas (Salcedo-Hernández, Lino-Silva, MosquedaTaylor, & Luna-Ortiz, 2014).. Despite the advancement in surgical and treatment. modalities, the survival rate of sarcoma patients, especially those with advanced and metastatic disease are very poor (Olmos et al., 2010). Most of the patients with distance. ay a. metastases eventually pass away due to disease progression (Schuetze & Patel, 2009).. Hence, this study is designed to investigate the mechanism(s) through which the. M al. sarcomas may modulate host immune system, and to find a correlation (if any) between the immune status of the sarcoma patients and their prognosis. The outcome from this study may provide newer insights into the progression of disease in sarcoma patients and. of. pave a path to the discovery of new treatment modalities that can tap into the host immune. ty. system to promote host anti-tumour responses which may help to prolong the survival. Research Question. ve. 1.2. rs i. rate of sarcoma patients.. ni. The research question of this study is:. U. What is the difference between the proportion of Th and Treg cells in sarcoma patients compared to healthy individuals?. 1.3. Research hypothesis. The null (H0) and research (HA) hypothesis of this study are:. 4.

(28) H01:. There will not be higher levels of Treg cells in blood taken from sarcoma patients versus normal healthy individuals.. HA1:. There will be higher levels of Treg cells in blood taken from sarcoma patients versus normal healthy individuals.. H02:. There will be no reduction in the Th 1 immune response in sarcoma patients versus normal healthy individuals. There will be a reduction in the Th 1 immune response in sarcoma patients. Research Objectives. 1.4.1. General Objective:. of. 1.4. M al. versus normal healthy individuals.. ay a. HA2:. The primary aim of this study is to elucidate the role of the host immune system in. rs i. Specific Objectives:. ve. 1.4.2. ty. providing anti-cancer effects in sarcoma patients.. ni. The specific objectives of this study are to:. U. a) To compare the proportion of Th and Treg cells between sarcoma patients and healthy individuals.. b) To identify genes that are differentially regulated in T-lymphocytes isolated from sarcoma patients compared to healthy individuals. c) To compare the levels of key cytokines [TNFα, IFN, TGF-β1 and IL-17A] produced by PBMC isolated from sarcoma patients and healthy individuals.. 5.

(29) CHAPTER 2: REVIEW OF LITERATURE. 2.1. Overview of Sarcoma. Sarcomas are distinct group of tumours originating from connective tissues. To date,. ay a. there are more than 100 subtypes described in the literature (A van der Graaf, Orbach, Judson, & Ferrari, 2017; Olmos et al., 2010; Romeo, Dei Tos, & Hogendoorn, 2012). The term “sarcoma” is derived from the Greek word “sarcoma”, which means fleshy. M al. growth (Beckingsale & Gerrand, 2009). Sarcomas are most prevalent in patients younger than 20-years old (Herzog, 2005) and represent about 1% of all adult cancers; 11% of. of. young adult cancers and 15% of childhood cancers (A van der Graaf et al., 2017; Olmos et al., 2010; Thway, Noujaim, Jones, & Fisher, 2017). These tumours rely on the. Generally, sarcomas include both benign and malignant tumours. rs i. Demetri, 2007).. ty. formation of new blood vessels i.e. angiogenesis for growth and progression (DuBois &. (Romeo et al., 2012). These are further divided into tumours of soft tissues and bone.. ve. Prognosis of sarcoma differs with age; with children showing better prognosis compared. ni. to adults (A van der Graaf et al., 2017).. U. Bone tumours account for 0.2% of all cancers (Ramaswamy, Bharat, Sameer, Sachin,. & Agarwal, 2016; Zarkavelis, Petrakis, Fotopoulos, & Mitrou, 2016). Osteosarcoma and Ewing’s sarcoma are the most common types of bone tumours in young adults and children (Lee, 2014), while chondrosarcoma is the most frequently occurring malignant bone tumour in adults (Fletcher, Unni, & Mertens, 2002). Fibrosarcoma, chordomas, and undifferentiated pleomorphic sarcoma account for other uncommon subtypes. In young adults, bone sarcomas are the third most prevalent cause of death in sarcoma patients (Ramaswamy et al., 2016). Soft tissue sarcomas (STS) account for about 1% of adult 6.

(30) tumours and 15% of paediatric malignancies. The STS are heterogeneous tumours with more than 50 different types of tumour subsets where undifferentiated pleomorphic sarcoma, gastrointestinal stromal sarcoma (GIST), liposarcoma, leiomyosarcoma and synovial sarcoma are the most prevalent subtypes (Ramaswamy et al., 2016).. The aetiological agent for sarcomas is still not known. However, there are several risk. ay a. factors that have been linked to the development of sarcoma, such as exposure to radiation, viral infection, occupational factors, genetic syndrome and hormones (Amankwah, Conley, & Reed, 2013). Radiation-induced sarcomas can occur in 0.16%. M al. of cancer patients treated with radiation therapy (Di Marco, Kaci, Orcel, Nizard, & Laredo, 2016). In these patients, cancers are more prone to appear in bones compared to soft tissues due to their superior absorption nature (Amankwah et al., 2013; Velaj &. of. DeLuca, 1987). For instance, bone sarcomas were mainly reported in patients receiving. ty. radiation therapy for tuberculous arthritis, giant-cell tumour, and aneurysmal bone cyst (Velaj & DeLuca, 1987). Similar findings have been reported in post-radiation therapy. rs i. patients with nasopharyngeal carcinoma (NPC) or pelvic sarcoma (Di Marco et al., 2016;. ve. Chen, Li, Li, & Yang, 2005).. ni. Epstein-Barr virus (EBV) (Thorley-lawson, 2001) and Kaposi’s sarcoma-associated. U. herpesvirus (KSHV) (Rezaee, Cunningham, Davison, & Blackbourn, 2006) are two types of viruses that have been reported to be able to suppress immune responses. For instance, EBV infection is commonly associated with the development of leiomyosarcoma in immunocompromised patients such as HIV-infected or transplant patients (Amankwah et al., 2013). Some of the known risk factors of osteosarcoma include, genetic defects such as the Li-Fraumeni syndrome (Porter et al., 1992), retinoblastoma (Hansen et al., 1985), Werner. syndrome. (Ishikawa,. Miller,. Machinami,. Sugano,. & Goto, 2000),. neurofibromatosis (Hatori et al., 2006), enchondromatosis (Lee, 2014), and Rothmund7.

(31) Thomson syndrome (Amankwah et al., 2013). Studies have also shown that Paget’s disease and Diamond’s disease can increase the risk of developing osteosarcoma (Amankwah et al., 2013). Sarcomas have also been linked to karyotype changes such as point mutation or translocation in Ewing’s sarcoma (Lee, 2014).. Sarcomas are diagnosed through analysing the clinical history, mainly personal and. ay a. family history of malignancy, followed by clinical examination. Radiological examinations including X-rays can be used to detect bone abnormalities and local bone involvement. The biopsy is crucial for histological diagnosis and planning of treatment. M al. (Stamatoukou & Grimer, 2006). Magnetic resonance imaging (MRI) and computed tomography (CT) scan are imaging techniques used by clinicians to help them to plan for the right type of biopsy that needs to be performed (Singer, Demetri, Baldini, & Fletcher,. of. 2000) in a certain clinical condition, i.e. whether to use core needle, incisional or. ty. excisional biopsies. In addition, chest X-rays (CXR), chest CT scans and isotope bone scans (whole body technetium-99m bone scan) can also be carried out on sarcoma patients. rs i. to stage their tumours and to detect the presence of metastases (Lee, 2014). These are. ve. crucial for determining prognosis and disease monitoring during the course of treatment. ni. (Beckingsale & Gerrand, 2009).. U. Approximately 50% of sarcoma patients would be expected to succumb to metastasis. during the course of the disease (Falk et al., 2015). Pulmonary metastasis is the most common type of metastasis, (Beckingsale & Gerrand, 2009; Dossett et al., 2015; Nakamura et al., 2013) occurring in over 50% of sarcoma patients (Dossett et al., 2015), with some types of sarcoma metastasizing to lymph nodes, soft tissues (Beckingsale & Gerrand, 2009), and bones (Hoch, Ali, Agrawal, Wang, & Khurana, 2013). Moreover, pulmonary metastasis remains the leading cause of death among these patients (Schur et. 8.

(32) al., 2014). To address this issue, surgical resection of the lung nodules remains as the only option feasible to extend the survival of sarcoma patients.. 2.2. Bone Tumours. 2.2.1. Osteosarcoma. ay a. Osteosarcoma is also known as the tumour of growing bone (Lee, 2014). It is a malignant skeletal neoplasm (Lamonaca, Vasile, & Nastro, 2016) distinguished by direct formation of immature bones or osteoid tissue by the tumour cells (Picci, 2007). It is. M al. reported to be the most prevalent primary malignant bone sarcoma in adolescents and young adults (Biteau et al., 2016; Buddingh et al., 2011; Lamonaca et al., 2016; Sun,. of. Yang, Li, & Wang, 2015). The World Health Organization (WHO) estimated that osteosarcoma occurs in 4-5 per million populations and is frequently observed in 60% of. ty. patients below 25-years-old and 30% of patients above 40-years-old (Fletcher et al.,. rs i. 2002). Males are more commonly affected by osteosarcoma than females (1.5:1) (Picci,. ve. 2007) but it is reported to occur early in girls compared to boys (Lee, 2014).. Osteosarcoma tends to develop in the metaphysis of long bones (Biteau et al., 2016;. ni. Lamonaca et al., 2016; Mathkour et al., 2016; Stamatoukou & Grimer, 2006) with 70%. U. of osteosarcoma emerging in the proximal tibia and distal femur (Lamonaca et al., 2016; Stamatoukou & Grimer, 2006). Osteosarcoma occurs less frequently in the proximal femur, proximal humerus and pelvis (Stamatoukou & Grimer, 2006).. Although. osteosarcoma frequently favours long bones, its relative incidence in non-long bones such as jaws, pelvis, spine, and skull tends to increase with age (Fletcher et al., 2002). Osteosarcoma is an aggressive tumour that grows rapidly (Sun et al., 2015) while destroying the surrounding normal tissues in the process (Liu, Li, Wu, Shi, & Zhao, 2016). It is known for its high metastatic potential (Han et al., 2008), regionally or 9.

(33) systemically (Lamonaca et al., 2016), with the more common being metastasis to the lungs (Salinas-Souza et al., 2013) and bones (Lee, 2014).. Generally, 20% of. osteosarcoma patients present with lung metastasis upon diagnosis (Lee, 2014; SalinasSouza et al., 2013) and 40% of patients present with metastasis at later stages (SalinasSouza et al., 2013).. ay a. Despite the advancement in treatment modalities over the past 15 years, the survival rate for osteosarcoma patients are still poor (Buddingh et al., 2011). The five-year survival rate is reported to average around 65% (Hönicke, Ender, & Radons, 2012;. M al. Ramaswamy et al., 2016). In patients with metastatic osteosarcoma, the five-year survival rate is less than 30% (Han et al., 2008).. In general, about 20% of the. osteosarcoma patients survive upon primary tumour resection whilst 80% of generally. of. succumb to metastatic lung disease within two years (Lee, 2014).. ty. Chondrosarcoma. rs i. 2.2.2. Chondrosarcoma is a malignant bone tumour with pure hyaline cartilage. ve. differentiation, diverse morphological features, and clinical behaviour. It can be divided. ni. into primary, secondary, and periosteal chondrosarcoma with more than 90% of incidences being the primary type (Fletcher et al., 2002). Chondrosarcoma is the second. U. most frequently occurring primary bone sarcoma of cartilage (Liang et al., 2014) and accounts for nearly 20% of malignant bone tumours (Fletcher et al., 2002). It is a tumour of old age in which the majority of the patients are above the age of 40. Chondrosarcoma frequently involves pelvis, axial skeleton and proximal femur, and humerus (Zarkavelis et al., 2016).. Chondrosarcoma is a type of sarcoma which is less sensitive to chemotherapy and radiotherapy. Thus, surgical resection is the only treatment option currently available for 10.

(34) this type of sarcoma (Liang et al., 2014; Lin et al., 2014; Zarkavelis et al., 2016). The five-year survival rate is more than 90% for chondrosarcoma Grade 1 but this drops to 25% for Grade 3 (Zarkavelis et al., 2016). Chondrosarcoma also tends to metastasize to lungs and liver; and patients with metastasis have a very poor prognosis (Lin et al., 2014).. 2.2.3. Ewing’s sarcoma. ay a. Ewing’s sarcoma is a round cell sarcoma that shows different degrees of neuroectodermal differentiation (Fletcher et al., 2002) and the second most common. M al. sarcoma after osteosarcoma (Bernstein et al., 2006; Jürgens & Dirksen, 2011). Although Ewing’s sarcoma can affect all age groups, ranging from infants to adults (Iwamoto, 2007; Jürgens & Dirksen, 2011); 80% of Ewing’s sarcoma diagnosis are made for patients. of. younger than 20-years of age (Bernstein et al., 2006; Iwamoto, 2007). This condition is. ty. observed more in males and is more prevalent among Caucasians (Lee, 2014).. rs i. Ewing’s sarcoma commonly occurs in the axial skeleton, diaphysis of long bones (Bernstein et al., 2006; Lee, 2014) and ribs (Bernstein et al., 2006; Fletcher et al., 2002;. ve. Jürgens & Dirksen, 2011). However, Ewing’s sarcoma can occur anywhere in the body. ni. (Erkizan et al., 2009), with the prevalence being in the bones and less than 10% in soft tissues (Toomey, Schiffman, & Lessnick, 2010). About 85% of Ewing’s tumours present. U. with genetic characters of reciprocal chromosomal translocation of chromosome 11 and 12, t(11;22) (q24;q12) (Bernstein et al., 2006; Lee, 2014). In addition, these gene rearrangements were reported to also correlate with high CD99MIC2 expression (Bernstein et al., 2006).. Ewing’s sarcoma patients may present with non-specific signs of inflammation such as increased erythrocyte sedimentation rate (ESR) values, moderate anaemia, leukocytosis, and increased serum lactate dehydrogenase (LDH) (Bernstein et al., 2006; 11.

(35) Lee, 2014). This cancer also has the potential to metastasize to lungs, bone, or bone marrow. About 15-20% of Ewing patients have detectable metastasis at diagnosis (Amankwah et al., 2013; Bernstein et al., 2006; Jürgens & Dirksen, 2011; Lee, 2014). Some patients tend to have a recurrence with distance metastasis after surgical resection (Toomey et al., 2010). Bone marrow aspiration, trephines and stem cells harvest are. ay a. required as part of Ewing’s treatment due to bone marrow involvement (Lee, 2014).. The five-year survival rate for these patients is below 65% for local tumours and 35% for patients with metastasis. Bone and bone marrow metastasis have the worst prognosis. M al. with a three-year survival rate at 15%, while it is 22% for other metastatic sites. In addition, patients who responded well to chemotherapy with a 90% necrosis, showed a 10-years survival rate of 70% compared to 47% for poor responders of chemotherapy. of. (Lee, 2014).. Soft Tissue Sarcoma. 2.3.1. Pleomorphic sarcoma. ve. rs i. ty. 2.3. Pleomorphic sarcoma was previously known as malignant fibrous histiocytoma (Tos,. ni. 2006; Weiss & Enzinger, 1978). It is a type of sarcoma composed of spindle and. U. pleomorphic cells and accounts for 10-15% of all adult soft tissue sarcomas. Most of the pleomorphic sarcoma cases are high-grade and aggressive (Guillou, 2008). It is common in patients aged above 40 years and favours males compared to females (1.2:1) (Fletcher et al., 2002; Weiss & Enzinger, 1978).. Undifferentiated high-grade pleomorphic sarcomas occur mainly in extremities; especially in the lower limb and deep soft tissues (Fletcher et al., 2002; Nascimento & Raut, 2008). Other rare subtypes of these tumours include undifferentiated pleomorphic 12.

(36) sarcoma with giant cells and undifferentiated pleomorphic sarcoma with prominent inflammation, occurring primarily in distal extremities and trunk of the body, and retroperitoneum/abdomen respectively (Nascimento & Raut, 2008). About 5% of these patients were reported to have metastases at presentation, mainly to the lungs (Fletcher et al., 2002); and also in the lymph nodes (Tos, 2006), liver (Nascimento & Raut, 2008) and bone (Nascimento & Raut, 2008). Moreover, metastasis in pleomorphic sarcoma occurs. ay a. commonly in the more deeply-seated tumours compared to the superficial tumours (Weiss & Enzinger, 1978).. Liposarcoma. M al. 2.3.2. Liposarcoma is a common malignant adult soft tissue sarcoma, which occurs mainly. of. in the extremities (24%) and retroperitoneum (45%) (Amankwah et al., 2013; Choi, Kim, & Jin, 2010; Keung, Hornick, Bertagnolli, Baldini, & Raut, 2014; Shih et al., 2014). This. ty. type of tumour commonly occurs in adults aged between 40 and 60 years old (Zarkavelis. rs i. et al., 2016). Liposarcoma accounts for 10% of all type sarcomas (Stevenson et al., 2016). ve. and is classified into five histological subtypes; dedifferentiated, well-differentiated,. ni. myxoid, round cell and pleomorphic (Keung et al., 2014; Shih et al., 2014).. Well-differentiated liposarcoma is the largest subgroup of adipocytic neoplasms,. U. which account for nearly 45% of all liposarcomas (Fletcher et al., 2002). Dedifferentiated liposarcoma is an aggressive type of high-grade tumour with a systemic metastasis of up to 24%, with poor prognosis (Keung et al., 2014).. Both well-differentiated and. dedifferentiated liposarcomas affect middle-aged adults. Myxoid/round cell liposarcoma is the second most common subtype of liposarcoma that accounts for more than one-third of all liposarcomas and 10% of all adult soft tissue sarcomas. It occurs in younger adults and most commonly in patients younger than 20-years-old. The pleomorphic subtype. 13.

(37) occurs in 5% of all liposarcomas and in 20% of all pleomorphic sarcomas. It affects patients above 50-years of age. To date, there is no gender preference reported for all subtypes of liposarcoma (Fletcher et al., 2002). However, liposarcomas are known to metastasize to lungs, extra-pulmonary skeletal, and soft tissue sites (Stevenson et al., 2016).. Synovial sarcoma. ay a. 2.3.3. Synovial sarcoma is a commonly occurring high-grade sarcoma (Baheti et al., 2015),. et al.,. M al. which accounts for relatively 5-10% of all soft tissue sarcomas (Baheti et al., 2015; Naing 2015; Vlenterie et al., 2016).. Synovial sarcoma usually presents with a. chromosomal translocation between the SYT gene (X chromosome) and SSX1, SSX2 or. of. SSX4 genes (chromosome 18) (Amankwah et al., 2013). Synovial sarcoma may occur throughout the body, but more commonly at the extremities in young adults (Vlenterie et. ty. al., 2016). Synovial sarcomas occur more commonly in males with 90% of incidences. rs i. occurring before 50-years of age and between 15 to 35-years of age (Fletcher et al., 2002).. ve. The US Surveillance, Epidemiology, and End Result (SEER) data show approximately 10% cases of newly diagnosed synovial sarcoma, with 70% affecting patients below 40-. ni. years-old.. U. For newly diagnosed synovial sarcoma patients, around 20% presents with clinically. detectable lymph node metastasis and 6% present with lung metastasis. Moreover, it is a type of sarcoma with a high risk of recurrence, with a local recurrence rate of 12% and distant recurrence rate of 39% at five years, with a median survival of 22 months from the onset of metastatic disease (Amankwah et al., 2013). The SEER data also shows that children and adolescents with synovial sarcoma have a better prognosis with a five-year cancer-specific survival rate of 83% to 62% for their older counterparts (A van der Graaf. 14.

(38) et al., 2017). In contrast, a long follow-up study of synovial sarcoma patients showed recurrence after 3.7 years and metastasis after 5.7 years (Vlenterie et al., 2016).. 2.3.4. Extra-skeletal osteosarcoma. Extra-skeletal osteosarcoma or soft tissue osteosarcoma is a rare malignant mesenchymal neoplasm of soft tissues (Fletcher et al., 2002; Narayanan, Gopalakrishnan,. ay a. Ibrahim, & Sankar, 2016). It is a type of soft tissue sarcoma that grows outside the bone and may secondarily involve the periosteum, cortex or medullary canal (Fletcher et al.,. M al. 2002). It tends to grow at the soft tissues of the thigh, upper extremity, retro-peritoneum, and in any other parts of the body. Extra-skeletal osteosarcoma accounts for 1-2% of all soft tissue sarcomas and approximately 2-4% of all osteosarcomas (Fletcher et al., 2002;. of. Hoch et al., 2013; Narayanan et al., 2016).. ty. Soft tissue sarcomas mainly affect patients in the middle and/or later ages. Males are. rs i. reported to be more susceptible than females; with a ratio of 1.9:1 (Fletcher et al., 2002; Hoch et al., 2013). In addition, 10% of the extra-skeletal osteosarcoma cases appear to. ve. be related to previous radiation or well-documented injuries (Fletcher et al., 2002; Hoch. ni. et al., 2013; Narayanan et al., 2016). Nearly 90% of these patients succumb to local recurrences and metastases to lungs and bones (Hoch et al., 2013). The overall five-year. U. survival rate for extra-skeletal osteosarcoma is reported to be 25% (Tos, 2006).. 2.4. Management of Sarcoma. There is more than one treatment option available for sarcomas. Combination treatment has greatly improved the prognosis of patients with bone or soft tissue sarcomas (Ueda et al., 2008).. 15.

(39) The management of bone sarcomas is divided into three stages i.e. pre-operative, local, and post-operative disease control. Pre-operative chemotherapy is given in order to reduce the symptoms, size, and neurovascular bundle involvement prior to surgical resection (Lee, 2014). This step would help to preserve most of the function of the affected bone. For example, in high-grade osteosarcoma, therapy consists of neoadjuvant chemotherapy, followed by surgical resection (Ramaswamy et al., 2016). In general,. ay a. patients who respond well i.e. have 90% necrosis rate or more, appear to show significant positive prognosis compared to patients with lower necrosis rates (Ramaswamy et al., 2016). Local control involves surgery followed by radiotherapy. Surgery may involve. M al. full limb resection, with reconstruction using endoprosthesis, rotationplasty, and sometimes even amputation. Post-operative disease control involves chemotherapy,. of. immunotherapy, radiotherapy, and surgical resection of metastatic disease (Lee, 2014). There is evidence which shows that patients with pulmonary metastasis who are treated. ty. with surgical treatment correlate with increased survival (Beckingsale & Gerrand, 2009).. rs i. In soft tissue sarcoma (STS), surgical resection is the first-line therapy for localized. ve. tumours with or without radiotherapy (Beckingsale & Gerrand, 2009). Surgery in combination with radiation therapy is used for tumours with incomplete excisional. ni. margin or those of high - grade subtypes (Amankwah et al., 2013; Beckingsale &. U. Gerrand, 2009). Chemotherapy is given for intermediate, high-grade, unresectable, large, or metastatic tumours. Compared to other STS subtypes, synovial sarcoma responds better to high-dose ifosfamide. Neoadjuvant chemotherapy is given to large and highgrade liposarcomas such as myxoid and pleomorphic liposarcoma. Some STS may also be treated using combination therapy (Amankwah et al., 2013). In some STS cases involving extremities, limb-sparing surgery (LSS) with radiotherapy approach is frequently used as an alternative to amputation in order to save the limb function and. 16.

(40) minimize the risk of local recurrence (Rydholm et al., 1991; Yang et al., 1998). A few studies have found that the combinatory treatment approach of using LSS with radiotherapy could achieve 80% local control rates in some STS patients (B. J. C. Yang et al., 1998). Amputation will only be considered as a final resort when tumours were found to have invaded considerably important sections of the body, including the neurovascular network. Furthermore, studies comparing LSS with amputations did not. individuals (Beckingsale & Gerrand, 2009).. ay a. show significant differences in the general health and quality of life scores of affected. M al. Pulmonary metastasectomy is the well-established standard management for sarcoma patients with pulmonary metastasis and has been implemented since 40-years ago (Dossett et al., 2015; Schur et al., 2014). This approach is found to offer a long-term. of. survival advantage. A recent study, involving 120 adult sarcoma patients who underwent. ty. pulmonary metastasectomy reports the five-year survival rate was reported to be 44% (Dossett et al., 2015). Another useful and safe therapeutic alternative for elderly patients. rs i. with non-resectable lung metastases is the minimally invasive pulmonary radiofrequency. ve. (RF) ablation approach (Nakamura et al., 2013).. ni. In Malaysia, differences in the demographics, which includes culture, race, belief and. U. religion may contribute to the disparity in the survival rate of patients with sarcoma. Moreover, the epidemiology of sarcoma is lacking in this country. Nevertheless, there are few institutes that have reported on the survival rate of Malaysians with sarcomas. Eleven years of retrospective record review study of 127 osteosarcoma patients in Hospital Universiti Sains Malaysia (HUSM) revealed limb salvage surgery and neoadjuvant with adjuvant chemotherapy reported the highest survival rate at 70.6% and 80.5%, respectively but the overall survival rate was quite low (48.94%) (Wahidah, Khattak, Wan-Arfah, & Naing, 2018). In a separate study in the same institute, 13 17.

(41) patients with pelvic sarcoma showed medial survival of 19 months in 6 patients who underwent limb salvage and 9 months in 7 patients with amputation. Overall, the survival rates are very poor in these patients despite the treatment rendered (Ariff, Zulmi, Faisham, Nor Azman, & Nawaz, 2013).. 2.5. Overview of the Immune System. ay a. The immune system is a complex network involving cells and soluble substances, which protects the host from many assaults, including pathogenic microorganisms and. M al. tumours. One of the inherent functions of the immune system is its ability to differentiate between “self” (own proteins) and “non-self” (foreign) antigens (Jonuleit & Schmitt, 2003). This role ensures that the immune system does not engage in self-destructive. of. pursuits. An effective defence mechanism is achieved by regulating both innate and. rs i. Littman, 2009).. ty. adaptive arms of the immune systems via complex signalling networks (Zhou, Chong, &. Cells that play a key role in immune responses are collectively known as leucocytes. ve. or white blood cells (WBC). Leucocytes that play a key role in innate immune response. ni. include granulocytes (neutrophils, eosinophils, basophils and mast cells), macrophages, dendritic cells (DC), and natural killer (NK) cells whilst T-lymphocytes and B-cells are. U. the main players of adaptive immune responses. Three types of leucocytes can be classified under the lymphocyte family; i.e. the thymus-derived T-lymphocytes, bone marrow-derived B-cells and natural killer (NK) cells (Luckheeram, Zhou, Verma, & Xia, 2012).. An immune response is triggered when the host immune system encounters infectious microbes that induce activation and differentiation of CD4+ T-lymphocytes or Th cells (O’Shea et al., 2009; Coffman & Mosmann, 1986). As shown in Figure 2.1, host defence 18.

(42) involves three levels of protection; (1) anatomical and physiological barriers, (2) innate immunity, and (3) adaptive immunity. Skin, mucociliary clearance mechanisms, low stomach pH, and bacteriolytic lysozymes in several body secretions (tears, saliva and etc.) act as the first line of defence against pathogens. The first line of defence is strengthened by the second level of protection, i.e. innate immunity (Turvey & Broide, 2010). Innate immunity creates a protective inflammatory response to pathogen exposure and. ay a. subsequently activates the antigen-specific adaptive immune system (Takeda & Akira, 2005; Turvey & Broide, 2010). Upon activation, the adaptive immune system increases. M al. receptor variation that can better identify antigen (Turvey & Broide, 2010).. The defence mechanisms provided by the immune system can be classified as cellular and humoral immune responses.. Cellular defence consists of leucocytes such as. of. neutrophils, macrophages, lymphocytes, dendritic cells (DC), eosinophils, basophils, and. ty. mast cells natural killer (NK) cells. The humoral arm consists of soluble factors such as cytokines, chemokines, acute phase proteins [e.g. C-reactive proteins (CRP)],. rs i. complement proteins, and lipopolysaccharide (LPS) binding proteins (Dranoff, 2004;. ve. Turvey & Broide, 2010).. ni. The skin and epithelium lining of the respiratory, gastrointestinal, and genitourinary. U. tracts also contribute to the protective actions of the innate immune system (Turvey & Broide, 2010).. The cells that provide innate immunity express germ-line-encoded. pattern-recognition receptors (PRRs) and other cell-surface molecules to help these cells identify invading pathogens so that these can be eradicated via activation of immediate inflammatory responses (Bonilla & Oettgen, 2010; Dranoff, 2004; Medzhitov & Janeway, 1997; Turvey & Broide, 2010). The toll-like receptors (TLRs) are a type of PRRs expressed by cells that provide innate immunity. These receptors help the innate immune cells to recognise different types of microbial molecular structures, collectively 19.

(43) known as pathogen-associated molecular-patterns (PAMPs) (Medzhitov & Janeway,. of. M al. ay a. 1997; Turvey & Broide, 2010).. Host defence mechanism of the immune system and types of cells. ty. Figure 2.1:. rs i. responsible for innate and adaptive immunities (adapted from Turvey & Broide, 2010).. ve. The innate immune system has the ability to provide appropriate signals to activate. ni. adaptive immune responses when foreign antigens are encountered in order to induce. U. relevant effector responses (Medzhitov & Janeway, 1997). The thymus-derived Tlymphocytes and bone marrow-derived B-cells are the two important players of adaptive immunity (Bonilla & Oettgen, 2010; Fearon & Locksley, 1996; Turvey & Broide, 2010). The B-cells express membrane-bound forms of immunoglobulin (Ig) on its surface as the B-cell receptor (BCR) (Lebien & Tedder, 2008) whilst T-lymphocytes express T-cell receptors (TCRs) on the cell surface (Bonilla & Oettgen, 2010). The diversity of TCR and BCR is achieved due to the genes that code for TCR and BCR, which allow the generation of T- and B-cells with antigen-specific receptors (Fearon & Locksley, 1996).. 20.