Cancer Theme: Projects
The current focus of the various projects within the cancer theme is aimed at generating experimental evidence for the qualitative improvement of therapy outcome in cancer patients. The combined approaches in cancer treatment has resulted in remakarable shift in overall patient survival compared to 20 years ago (graph). Whereas chemotherapy and targeted therapy agents helped to extend patient survival by 5-10 years, immune checkpoint therapy has shown that, for some cancers, we can achieve a complete cure of the disease. However, to date, this has been only realized in approximately 20% of patients. The challenge now is how to achieve a similar success rate for the majority of cancer patients. In order to accomplish this task, the current projects are aimed at deepening our understanding of the tumor-intrinsic as well as tumor-extrinsic factors that underpin the intricate relationship between the tumor microenvironment (TME) and the host immune system.
Sharma P and Allison JP. Immune Checkpoint Targeting in Cancer Therapy: Toward Combination Strategies with Curative Potential. Cell (2015)
Diagnostic and prognostic biomarkers in cancer
Focus will be initially on discovering early biomarkers to provide more accurate prognosis for cancer patients in the UAE. This will be carried out using combination of screening for biomarkers using multi-OMICs including genomics, transcriptomics and epigenetics on retrospective surgical biopsy cancer samples obtained from FFPE and prospective samples from blood, saliva, fresh frozen, and fine needle aspirates.
Understanding the role of cancer metabolism in response to treatment
Compared to normal cells, tumors utilize a unique mechanism to generate their enrgy needs, known as aerobic glycolysis. Over the past 2 decades, it has become evident that this metabolic process of cancer cells is essential for tumorigenesis. This metabolic reprogramming enables the creation of a tumor microenvironment (TME) that restrains immune responses, thus favoring unimpeded tumor growth. One of the key research aims of the cancer theme is to use a genetic approach to investigate the role of mitochondrial proteins in this process. Ultimately, this would lead to improved therapies for cancer patients.
Understanding the role of Tumor Immune Microenvironment in HER2-Breast Cancer Metastasis and resistance to Trastuzumab treatment
The activation of HER2, the Human epidermal growth factor, promotes oncogenesis and leads to the evaluation of HER2-directed drugs/therapeutics in cancers with HER2 variations, which is importantly characterized in the context of breast cancer (BC). The HER2 overexpression contributes to metastasis and patients’ poor survival. However, it has been demonstrated that trastuzumab-based therapy increases the survival of patients with HER2 overexpression. Hence, the identification of differentially expressed genes in HER2-overexpressing BC is important to understand the mechanistic basis of their increased metastatic potential.
Mutational screening of cancer-causing genes in UAE population
The UAE population is a mosaic of individuals from various ethnicities living within the same environment. Screening for DNA mutations of the common cancer-causing genes including KRAS, BRAF, EGFR, BRCA1, BRCA2, ATM, APC as well as others involved in cancer hallmark pathways is key in understanding some of reasons behind the high incidence of certain cancers within the UAE population. This can lead to the development of UAE cancer biomarker panel that may be used in screening the population and may prevent the onset of some of the aggressive cancers.
A hypothetical flow chart to highlight key steps involved in the identification of rational combinations for personalized therapies in cancer. The detailed analysis of a tumor biopsy by genomics, transcriptomics and other OMICS allows the initial characterization of the tumor type and its potential responsiveness to different treatments. The choice of agent is based on specific molecules and gene profiles identified on cells of the tumour microenvironment (TME). MDSC, myeloid-derived suppressor cells; Treg, regulatory T cells; APCs, antigen-presenting cells; poly-ICLC, polyinosinic-polycytidylic. Reference: Butterfield LH and Najjar YG. Immunotherapy combination approaches: mechanisms, biomarkers and clinical observations. Nat Rev Immunol (2023).
Development of integrative Advanced Computational Biology and Artificial intelligence algorithms in understanding some of the molecular mechanisms involved in cancer
Because of the inherent complexity of cancer due to its intra-tumoural heterogeneity, Artificial Intelligence (AI) alone is not able to mine the OMICs generated from cancer patients. Therefore this study will focus on developing explainable AI by guiding the AI algorithms through advanced computational biology algorithms to identify the important differentially activated cellular pathways and related differentially expressed genes involved in cancer pathogenesis and metastasis.
- Explore the application of advanced bioinformatics algorithms to multi-OMICs available data
- Explore the use of AI algorithms to mine multi-OMICs publicly available data
- Integrate advanced bioinformatics and AI algorithms to identify key molecular pathways and related genetic biomarkers involved in cancer pathogenesis and progression from publicly available multi-OMICs data
- Develop framework of novel algorithms to identify the key molecular mechanisms for cancer from multi-OMICs data with a view to identify potential therapeutic targets for cancer
- Validate the biomarkers identified from the novel algorithms using experimental data generated using bulk and single cell multi-OMICs approaches
- Leverage deep learning models and clinical data to develop predictive models for cancer