FELLOWSHIP IN ONCOPATHOLOGY
Explore the Fellowship in Oncopathology through our practical-focused Postgraduate Diploma program. Designed for medical professionals passionate about excelling in diagnostics, this course provides clinical training and expert mentorship to master the intricacies of oncopathological diagnosis and care.
Batch starts on
Jan to Dec/ May to June
Course Duration
12 Months
Multimodal Program
Hybrid Mode & Clinical Attachment
Flexible payment
financing options available
Program Overview
The Medical Global Academy’s Fellowship in Oncopathology is a clinically-oriented program for physicians interested in specializing in cancer diagnosis using the latest histopathological and molecular diagnostic procedures. This fellowship program aims to impart profound understanding of tumor biology, cancer pathology, molecular oncology, and precision diagnostics of cancer. The program will be a mix of lectures and clinical exposure, to enable the students to gain an understanding of the various types of cancers, such as breast, lung, gastrointestinal malignancies, haematological cancers and gynecological tumours, along with their diagnosis and classification. Advanced histopathology, advanced immunohistochemistry (IHC) and molecular pathology are included, as well as next generation sequencing (NGS), fluorescence in situ hybridization (FISH), liquid biopsy technologies, and digital pathology. Other specializations of the fellowship include personalized medicine, cancer genomics, biomarker analysis, artificial intelligence for pathology, studies of the tumor microenvironment, and advanced molecular diagnostics. Participants will have the opportunity to develop clinical experience with case-based learning, multidisciplinary tumor board discussions, research projects, and working with oncology teams. It is designed based on the latest standards of oncology, and is intended to increase the accuracy of diagnosis and help improve patient results in cancer treatment.
What Skills You Will Gain
Detailed understanding of cancer biology, tumor classification and oncopathology principles
A knowledge of the histopathological diagnosis and interpretation of malignant tumors.
Practical experience in Immunohistochemistry (IHC), molecular diagnostics and genomic testing.
Expert knowledge of application of advanced technologies like NGS, PCR, FISH, liquid biopsy and digital pathology
Knowledge of tumour grading, tumour staging and tumour prognostic factors.
Diagnostic and Analytical Skills in the study of breast, lung, gastrointestinal, hematologic, and gynecologic cancers.
Understanding of precision oncology, targeted therapies and cancer genomics
Exposure to AI and Machine learning applications in Oncopathology
Clinical experience in inter-disciplinary tumor board discussions and analysis of cancer cases
Research skills in Oncopathology – clinical studies, data interpretation, scientific presentations.
Enhanced patient skills – patient communication, family counselling and oncology team communication
Knowledge of ethical issues and contemporary standards in cancer diagnostics and pathology
Career Outcomes After the Fellowship
Upon completing this fellowship, physicians have the opportunity to broaden their skills and advance into higher-level, cancer-related careers with the Healthcare sector.
Develop a career in oncopathology and molecular cancer diagnostics.
Perform duties in cancer hospitals, diagnostic labs, research centers, and multispecialty medical facilities.
Enhance the skills in precision oncology and personalised cancer treatment
Learn opportunities in histopathology, molecular pathology and advanced diagnostics in oncology
Participate on multidisciplinary oncology teams for diagnosis and treatment planning of cancer
Improve cancer pathologists’ professional value and recognition in modern diagnostic technologies
Engage in clinical research, clinical trials and university education programs
Gain proficiency in AI-powered diagnostic platforms and state-of-the-art genomic diagnostics.
Improve career prospects in healthcare leadership, pathology consultation and oncology research.
Keep abreast of new developments in cancer diagnosis, targeted therapy and molecular medicine.
What you'll learn
Introduction to Oncopathology
Histopathological Techniques
Tumor Types and Their Pathological Features
Diagnostic Criteria and Reporting
Molecular Pathology and Genomics
Clinical Correlation and Multidisciplinary Approach
Key Features
- Attending /Non-Attending Classes
- Clinical Training in Nearest Hospital/Clinics.
- Free Study Material with recorded lectures
- Best Faculties (Super Specialists) of India
5. Library Access & Question & Answer Session
6. NAAC A+ University
7. 1 Year of Mentorship
8. Updated Curriculum
Course Curriculum
- Summary of Oncopathology: History, range and changing role in cancer diagnosis.
- Fundamentals of Cancer Biology: Cellular changes, genetic mutations and tumor microenvironment.
- Tumor Classification: Histological, molecular and genetic classification systems.
- Oncology Terminology: Major terms and names used in oncopathology.
- Tumor Grading and Staging principles: TNM system, prognostic indicators.
- Tumor Histopathology: Histological characteristics of typical malignancies ( lung, breast, gastrointestinal, hematologic).
- Cellular Patterns of Malignant Tumors: Cytological alterations in malignant cells, mitosis, necrosis and invasion.
- Special Staining Techniques: H&E, PAS, trichrome, and special stains that can be used to diagnose a specific type of cancer.
- Immunohistochemistry (IHC): Tumor diagnosis, interpretation of IHC markers of tissue of origin, and receptor status.
- Tumor Microenvironment: The importance of stroma, vasculature and immune cells to tumor progression.
- Genomic Alterations in Cancer: mutations, gene rearrangements, amplifications, deletions, and their diagnostic implications.
- Next-Generation sequencing (NGS): Principles, uses, and interpretation in cancer.
- Fluorescence In Situ Hybridization (FISH): Uses in the diagnosis of chromosomal abnormalities.
- Polymerase Chain Reaction (PCR): Applications in the identification of particular gene mutations and molecular markers.
- Liquid Biopsy: Circulating tumor DNA (ctDNA) and its use in cancer monitoring.
- Breast Cancer Pathology: Histological subtypes, molecular classification, hormone receptors, HER2/neu, and prognostic markers.
- Gastrointestinal Malignancies: Colorectal cancer, gastric, pancreatic and liver cancers – pathology, molecular markers and staging.
- Lung Cancer: NSCLC histopathology, small cell lung cancer, and molecular profiling.
- Hematologic Malignancies Leukemias, lymphoma, and myeloma; histopathology, cytogenetics, and molecular aspects.
- Gynecologic Tumors: Endometrial, ovarian, and cervical cancer; pathology and molecular markers.
- Oncopathology Artificial Intelligence: Image analysis, diagnostic performance, and automated interpretation.
- Digital Pathology: Virtual microscopy, telepathology, whole slide imaging.
- Molecular Imaging Techniques: PET scans, CT, MRI and their application in oncopathology diagnostics.
- Biomarkers in Cancer: Current and emerging biomarkers in diagnosis, prognosis, and treatment response.
- Artificial Intelligence and Deep Learning: Application in cancer diagnostics, images recognition, and predictive modeling.
- Cancer Genomics and Precision Oncology: Genetic and Genomic Profiling – Use in treatment decision-making, e.g. targeted therapies, immunotherapies.
- Predictive and Prognostic Biomarkers: Evaluation of biomarkers in treatment and clinical outcome.
- Immunohistochemistry and Molecular Subtyping: Tumor testing of HER2, EGFR, ALK, PD-L1, and other molecular markers to select treatment.
- Oncology Therapy and Resistance Mechanisms: The responses and resistance to therapy in tumors.
- Precision Oncopathology Case Studies: How to understand complex cases and use molecular discoveries to make clinical decisions.
- Practical Case Analysis: A wide range of exposure to cancer cases, including unusual and complicated tumors.
- Case-based Learning: Multidisciplinary teams, weekly tumor board conferences with pathologists, oncologists, and multidisciplinary teams.
- Autopsy and Postmortem Pathology: Oncopathology Role in postmortem diagnosis and cancer related death.
- Research and Diagnostic Innovations: Fellows will report on their own research in oncopathology.
- Interdisciplinary Tumor Board Involvement: Multidisciplinary tumor boards with oncologists, surgeons and radiologists.
- Research Design Oncopathology: The design, data collection, and ethical aspects of an oncological study.
- Statistics in Pathology: The use of statistics in analyzing oncological data.
- Dissertation and Research Paper: Fellows will prepare and carry out a research project on an issue of interest in oncopathology.
- Presentation and Defense: Making the research findings present before a committee of experts.
- Publication and Peer Review: Advice on how to submit research results to reputable medical journals.
- Multi-disciplinary Clinical Rounds: Fellows will attend daily/weekly Clinical Rounds with oncologists, surgeons, radiologists, and geneticists.
- Patient Interaction and Family Counseling: Understanding how to report complex oncological diagnoses to patients and their families.
- Ethics in Oncopathology: Finding your way through the ethical dilemmas of cancer diagnosis, genetic counseling and therapeutic interventions.
- Onward Professional Development: Participation in on-going education by taking seminars, webinars and international conference attendance on oncopathology.
- Molecular Diagnostics in Solid Tumors: PCR, NGS, and FISH to identify the most important genetic mutations, chromosomal abnormalities and driver mutations.
- Liquid Biopsy Technologies: ctDNA, miRNA and exosomes as diagnostic and prognostic in cancer management.
- Targeted Therapy and Companion Diagnostics: Discovering therapeutic targets like EGFR, ALK, BRAF and PD-L1 and matching them with molecular testing.
- Cancer Immunotherapy: Immune checkpoint inhibitors, CAR-T Therapies and immunotherapy response predictive biomarkers.
- Pharmacogenomics in Oncology: Oncology Pharmacogenomics Oncology Pharmacogenomics evaluates genetic predispositions to drug responses and resistance during oncology treatments.
- Tumor Clonal Evolution: How cancers evolve at both cellular and molecular scales and what is the contribution of genetic instability?
- Intratumoral Heterogeneity: Therapy resistance mechanisms and the role of clonal heterogeneity in tumor recurrence and metastasis.
- Pathophysiology of Metastasis: Metastasis mechanisms, such as EMT (epithelial-mesenchymal transition) and important genes.
- Tumor Microenvironment and Immune Escape: The part of the immune system in tumor progression and immune escape strategies adapted by cancer cells.
- Single-Cell Sequencing: Methods and uses of single-cell sequencing to investigate tumor heterogeneity and microenvironment.
- Epigenetics in Cancer Introduction: The role of DNA methylation, histone modification, and non-coding RNA in oncogenesis.
- RNA Modifications and Cancer: The RNA modifications (m6A, pseudouridine) are involved in cancer progression and resistance to therapy.
- Chromatin Remodeling in Cancer: Chromatin Dynamics and their role in cancer cell proliferation and metastasis.
- Cancer Stem Cells and Epigenetic Reprogramming: Epigenetic roles in cancer stem cell behavior, resistance to therapy, and relapse.
- Treatment of Epigenetic alterations Targeting Epigenetic Pathways: Therapeutic intervention of epigenetic alterations and its clinical use.
- Pathology Introduction AI and ML Introduction AI and ML The principles of artificial intelligence and machine learning, and their application to pathology.
- Deep Learning in Image Analysis: Image recognition, tumor detection, and grading in histopathology images.
- AI-Driven Diagnostics: AI tools in molecular diagnostics, genomic data interpretation, and workflow automation in pathology labs.
- Predictive Models of Cancer Prognosis: Machine learning algorithms predict patient outcomes using histopathological and molecular data.
- Ethical and Legal Aspects of AI in Oncopathology: How to deal with the ethical issues, data privacy, and legal regulations surrounding AI in cancer diagnostics.
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