Submitted:
26 March 2025
Posted:
27 March 2025
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Methodology
2.1. Tumour Samples, Histology and Other Metadata
2.2. Silver/Gold (S/G) Staining of Paraffin Embedded Tissue
2.3. Tissue Preparation for Immune-Fluorescence Microscopy
2.4. Immunohistochemistry with Counter-Staining
2.5. Cell Isolation, Culture and Immunophenotyping
2.6. Cell Cycle Analysis from Paraffin Fixed Tissue
2.7. Statistical Analysis
3. Results
3.1. Histopathological Findings and MRI Metadata
3.2. GFAP Showed Distinct Variability in Glial Cell Population
3.3. Ki67 and Propedium Iodide (PI) Displayed Graded Variation of Proliferation
3.4. Expression of Total MMP2 Indicated Variable Invasive Property
3.5. VEGFR2 and DNMT1 Showed Neo-Vasculogenesis and Epigenetic Modification Patterns
3.6. S/G Staining with CD11b and Iba1 Expression Showed the Association of Macrophage/Microglia Within Tumour Types
4. Discussion
5. Conclusion
Authors’ Contribution
Ethical Approval
Grant Information
Availability of Data and Materials
Acknowledgments
Competing Interest
References
- Dasgupta A, Gupta T, Jalali R. Indian data on central nervous tumors: A summary of published work. South Asian J Cancer. 2016;5:147-53. [CrossRef]
- Ghosh A, Sarkar S, Begum Z et al. The first cross sectional survey on intracranial malignancy in Kolkata, India: Reflection of the state of the art in southern West Bengal. Asian Pac J Cancer Prev. 2004;5:259-267.
- Jalali R, Datta D. Prospective analysis of incidence of central nervous tumors presenting in a tertiary cancer hospital from India. J Neurooncol. 2008;87:111-4. [CrossRef]
- Paul M, Goswami S, Raj G, Bora G. Clinico-epidemiological Profile of Primary Brain Tumours in North-Eastern Region of India: A Retrospective Single Institution Study. Asian Pac J Cancer Care. 2023;8(2):333-336. [CrossRef]
- Yeole BB. Trends in the Brain Cancer Incidence in India. Asian Pacific J Cancer Prev. 2008;9:267-270.
- Miller KD, Ostrom QT, Kruchko C et al. Brain and other central nervous system tumor statistics, 2021. CA Cancer J Clin. 2021;71:381-406. [CrossRef]
- Gao H, Jiang X. Progress on the diagnosis and evaluation of brain tumors. Cancer Imaging. 2013;13(4):466-481. [CrossRef]
- Park SH, Won J, Kim SI et al. Molecular Testing of Brain Tumor. J Pathol Transl Med. 2017;51(3):205-223. [CrossRef]
- Louis DN, Perry A, Reifenberger G et al. World Health Organization classification of tumours of the central nervous system: a summary. Acta Neuropathol. 2016;131:803-820. [CrossRef]
- Louis DN, Perry A, Wesseling P. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary. Neuro-Oncol. 2021;23(8):1231-1251. [CrossRef]
- Bready D, Placantonakis DG. Molecular pathogenesis of low-grade glioma. Neurosurg Clin N Am. 2019;30(1):17-25. [CrossRef]
- Yrysov K, Arstanbekov N, Mamytov M. Postoperative complications in patients with intracranial meningiomas who underwent surgery. Biomedicine. 2023;43(3):1023-1026. [CrossRef]
- Chang JH, Chang JW, Choi JY, Park YG, Chung SS. Complications after gamma knife radiosurgery for benign meningiomas. J Neurol Neurosurg Psychiatry. 2003;74:226–230. [CrossRef]
- Bertrand KC, Kliom P. Recent Advancements in Ependymoma: Challenges and Therapeutic Opportunities. Pediatr Neurosurg. 2023;58,307–312.
- Thotakura M, Tirumalasetti N, Krishna R. Role of Ki-67 labeling index as an adjunct to the histopathological diagnosis and grading of astrocytomas. J Can Res Ther. 2014;10:641-645. [CrossRef]
- Shivaprasad NV, Satish S, Ravishankar S, Vimalambike MG. Ki-67 immunostaining in astrocytomas: Association with histopathological grade – A South Indian study. J Neurosci Rural Pract. 2016;7:510-514. [CrossRef]
- Akyurek S, Chang EL, Yu TK et al. Spinal myxopapillary ependymoma outcomes in patients treated with surgery and radiotherapy at MD Anderson Cancer Center. J Neuro Oncol. 2006;80:177-183. [CrossRef]
- Huang H, Held-Feindt J, Buhl R, Mehdorn HM, Mentlein R. Expression of VEGF and its receptors in different brain tumours. Neurol Res. 2005;27:371-377. [CrossRef]
- Snuderl M, Chi SN, DeSantis SM et al. Prognostic value of tumour microinvasion and metalloproteinases expression in intracranial paediatric ependymomas. J Neuropath Exp Neurol. 2008;67:911-920.
- Chen X, Li C, Che X, Chen H, Liu Z. Spinal myxopapillary ependymomas: a retrospective clinical and immunohistochemical study. Acta Neurochir. 2016;158:101-107. [CrossRef]
- Ghosh K, Ghosh S, Chatterjee U, Chaudhuri S, Ghosh A. Microglial contribution to glioma progression: An immunohistochemical study in Eastern India. Asian Pac J Cancer Prev, 2016;17:2767-2773.
- Sato K, Kuratsu JI, Takeshima H, Yoshimura T, Ushio Y. Expression of monocyte chemoattractant protein-1 in meningioma. J Neurosurg. 1995;82:874-878. [CrossRef]
- Kvisten M, Mikkelsen VE, Stensjøen AL et al. Microglia and macrophages in human glioblastomas: A morphological and immunohistochemical study. Mol Clin Oncol. 2019;11:31-36. [CrossRef]
- Gutmann DH, Kettenmann H. Microglia/Brain Macrophages as Central Drivers of Brain Tumour Pathobiology. Neuron. 2019;104(3):442-449. [CrossRef]
- Dubuc AM, Mack S, Unterberger A, Northcott PA, Taylor MD. The epigenetics of brain tumours. Methods Mol Biol. 2012;863:139-53.
- Ghosh K, Ghosh S, Chatterjee U, Bhattacharjee P, Ghosh A. Dichotomy in growth and invasion from low- to high-grade glioma cellular variants. Cell Mol Neurobiol. 2022;42:2219-2234. [CrossRef]
- Hanahan D, Weinberg RA. Hallmarks of Cancer: The Next Generation. Cell. 2011;144:646-74.
- Wang H, Diaz AK, Shaw TI. Deep multiomics profiling of brain tumours identifies signaling networks downstream of cancer driver genes. Nat Commun. 2019;10:3718. [CrossRef]
- Ghosh A, Chaudhuri S. Tissue-free non-invasive diagnostic methodology for brain tumour: Present scenario and future direction. Biomedicine. 2024;44(1):39-45. [CrossRef]




| Experimental Parameters | Defining Characteristics | WHO grade I Myxopapillary Ependymoma |
WHO grade I Fibrous Meningioma | WHO grade II Diffuse Astrocytoma |
|---|---|---|---|---|
| Site of Occurrence | Sub Region (as seen in MRI) | Extra dural, spinal, Involving spinal canal extending from L1-L5 | Extra cranial, mid line basifrontal region | Intracranial, left temporo-parietal region |
|
MRI |
T1 | Hypointense | Iso to hypointense | Hypointense |
| T2 | Overall iso to hyperintense | Iso to hyperintense | Markedly hyperintense | |
| Midline Shift | Mild to negligible | Mild | Vividly observed | |
| Mass Effect | Mild to negligible | Mild | Vividly observed | |
| MR Spectroscopy | Choline Peak | High | High | High |
| NAA Peak | Low | Very low | Low | |
|
Histopathology under Bright Field Microscopy |
H/E Staining (observed both in lower 10X and higher 40X magnification) | Lobulated islands, hyalinised fibrovascular core, perivascular pseudo-rosettes, lobulated blood islands, dystrophic micro-calcification | ‘Whorling’ inter crossing fascicles, vascular sprouting, dystrophic micro-calcification | Fibrillary astrocytic processes, pleomorphic nucleus, conspicuous neovascularization, dystrophic micro-calcification |
|
Astrocytic Glial Origin & Proliferation |
Fluorescence IHC with GFAP-Alexa Fluor 488 to measure expressional intensity | Moderate | Least | Maximum |
|
Gross Proliferation |
Proliferative index by IHC with Ki67-HRP + Haematoxylin counter staining | Minimum (index value 0.4±0.05) | Intermediate (index value 1.3±0.12) | Maximum (index value 1.9±0.26) |
| Tissue cell cycle analysis with PI | Total percentage of S+G2M is minimum (8.30%±0.02) | Total percentage of S+G2M is intermediate (12.80%±0.02) | Total percentage of S+G2M is maximum (21.20%±0.02) | |
| Fluorescence IHC with Ki67-FITC to measure expressional intensity | Minimum | Intermediate | Maximum | |
| Angiogenic Switching or Neovascularization | Fluorescence IHC with VEGFR2-TRITC to measure level of angiogenic receptor expression | Clustered/Patchy | Lowest | Highest |
| Metastatic Nature or Invasiveness | Cellular FC with MMP2-PE(MFI) | Highest | Intermediate | Lowest |
| Fluorescence IHC with MMP2-FITC | Regional intense expression | Low scattered expression | Diffused moderate expression | |
|
Association of Mononuclear Monocytic Lineage Immune Cells |
S/G staining on fixed tissue (positive cells) | Moderate (31±11) | Highest (58±13.9) | Lowest (18±2.5) |
| Fluorescence IHC with CD11b-FITC (intensity profiling) | Moderate (9.9±5.1) | Highest (26.7±4.9) | Lowest (6.6±1) | |
| Fluorescence IHC with Iba1-PE (intensity profiling) | Lowest (10.3±1.6) | Highest (18.9±3.8) | Moderate (18±4.8) | |
|
Epigenetic Alteration |
Global methylation pattern detection by IHC with DNMT1-HRP + Haematoxylin counter staining | Scarce | Patchy and moderate | Diffuse but intense |
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