Cancer Research

In line with the revolutionary ASPIRE Precision Medicine initiative in Abu Dhabi, our focus extends to a dedicated exploration into the realms of cancer research and treatment. This pivotal segment accentuates the application of personalized medicine in the context of cancer, fostering an environment where diagnostics and treatments are precisely tailored to the individual characteristics of each patient.

Stay tuned for new updates and exciting content on this page.

Chronic Complex Disease

Cancer is a chronic complex disease that can be caused by specific hereditary genetic variations and different genetic analysis tools have been helpful in determining these variations, therefore enabling precision medicine for most common cancer types.

Cancer Diagnostics

Cancer's complexity, marked by variable intra-tumoral heterogeneity and evolving cancer cells, complicates early diagnosis. Early detection of biomarkers, however, could improve diagnosis accuracy and treatment effectiveness, thereby enhancing patient outcomes.

Personalized Therapy

Cancer patients typically receive standardized therapy, such as uniform doses of radiotherapy or chemotherapy. This approach can modestly extend survival, but often cancer adapts and spreads, resulting in poor outcomes and mortality. Understanding the cellular pathways behind therapy resistance is crucial for developing personalized treatments tailored to each patient's genetic and physical characteristics.

Tumour Immune Microenvironment

The immune system, adaptable to environmental factors like infections or injuries, uses inflammation to defend against these issues by localizing and eliminating harmful elements, thus starting the healing process. The Tumor Immune Microenvironment (TIME) consists of tumor cells, immune cells, cytokines, and chemokines, with their interactions influencing anti-tumor immunity. Through single-cell OMICs analysis of TIME, clinicians can gain insights into cancer development and the mechanisms of immunotherapy in cancer patients.

Unexplored Populations

Most research, however, is carried on Caucasian, African or Far Eastern populations, and little is known on the genetic makeup of cancer in Middle Eastern populations. In Specific, the Emirati population that is a mix of different ethnicities with the local community comprising of only 11.27%, outnumbered by expats.

The Unique Genetic Makeup

The local Emirati population are unique in their genetic makeup which can be exploited to track the genetic causes of the common cancers in these populations by identifying diagnostic and prognostic biomarkers for cancers prevalent in the UAE and putative therapeutic targets by understanding the role these biomarkers play in the pathogenesis of the various cancers.

Molecular Genetics

Cancer in the UAE, characterized by low esophageal but high breast, colorectal, and lung cancer rates, arises from DNA mutations. Studying the molecular genetics of these cancers is crucial for developing tailored treatments for UAE patients and gaining insights into organ-specific DNA programming, which is key to understanding cancer progression and metastasis.

The Emirati population in the UAE

Dementia risk from lifestyle & environment

AImS

How We Plan To Solve Challenges

Identify the key cancer-causing mutations prevalent in the UAE population

Determine the pathogenic mechanism of these gene mutations for cancers in the UAE

Application of big data analytics in cancer classification and prediction

Identify diagnostic and prognostic biomarkers for cancer and develop targeted personalized interventions

Identify predictive biomarkers for patients undergoing cancer therapy including radio, chemo, and immunotherapy

Understanding the tumour immune microenvironment in cancer

Understanding the molecular genetics of cancer in UAE

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)

Natural History of GM1-gangliosidosis in Emirati patients

delves into the complex processes of protein cellular trafficking, specifically focusing on understanding the role and implications of misfolded proteins within the endoplasmic reticulum (ER), a critical aspect in several genetic diseases including cystic fibrosis and familial hypercholesterolemia. Through deep research, we aim to develop novel therapies targeting these intricate cellular processes.

Investigate the role of the ER-associated degradation (ERAD) pathway in the handling of misfolded proteins in single-gene disorders

Explore the recognition processes of luminal misfolded lesions of membrane proteins in the canonical ERAD pathway

Determine the functions of ERAD components such as SEL1, HRD, and Derlin 1 & 2 in managing membrane proteins with misfolded luminal lesions

Evaluate the potential of pharmacological inhibitors like Kifunensine and Eeyarestatin in restoring the functionality of membrane proteins with misfolded luminal lesions

Diagnostic and prognostic biomarkers in cancer

will be initially on discovering early biomarkers to provide more accurate prognosis for cancer patients in the UAE.

Using a combination of genomics, transcriptomics, and epigenetics in the multi-OMICs approach.

Analyzing retrospective surgical biopsy cancer samples from FFPE.

Examining 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.

Exploring the role of mitochondrial proteins in cancer metabolism using a genetic approach.

Develop more effective cancer therapies by understanding this process.

Understanding the role of Tumor Immune Microenvironment in HER2-Breast Cancer Metastasis and resistance to Trastuzumab treatment

explores how HER2 activation in breast cancer leads to metastasis and affects patient survival, and the impact of trastuzumab therapy on these processes.

HER2 activation promotes oncogenesis, especially in breast cancer with HER2 variations.

HER2 overexpression in breast cancer is linked to increased metastasis and poorer patient survival.

Trastuzumab-based therapy has improved survival in patients with HER2 overexpression.

Research focus: Identifying differentially expressed genes in HER2-overexpressing breast cancer to understand the mechanistic basis of their increased metastatic potential.

Mutational screening of cancer-causing genes in UAE population

Analyzing DNA mutations in key cancer-causing genes within the ethnically diverse UAE population to understand high cancer incidence and develop a UAE-specific cancer biomarker panel.

UAE population's diversity as a mix of various ethnicities in the same environment. Screening common cancer-causing genes like KRAS, BRAF, EGFR, BRCA1/2, ATM, APC, and others in cancer hallmark pathways.

Aim: To understand the reasons behind high cancer incidence in the UAE population.

Potential outcome: Creating a UAE-specific cancer biomarker panel for population screening and prevention of aggressive cancers.

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.

Families of inherited neurometabolic diseases

aims in uncovering the genetic basis of various IEMs prevalent in the region.

Patient clinical evaluation and description including phenotype, lab results, metabolic assessment, and/or neurological assessment.

Genetic pedigrees will be drawn, and causative genes and/or genetic variants will be identified using next-generation sequencing tools.

Perform pathogenicity assessment for the detected variant using different in-silico and modulation analyses.

Elucidate the molecular and cellular pathogenesis of the identified genetic variants using patient cells or in-vitro cellular models.

Available resources

In the pursuit of understanding the complex mysteries of genetic makeups, our Cancers theme is powered by advanced technological resources. These facilities and platforms are indispensable tools that accelerate our innovative research and breakthrough discoveries.

Biorad CFX 96 Real-Time PCR

Bio-Rad CFX96 Real-Time PCR System is a powerful and precise real-time polymerase chain reaction (PCR) system. It features advanced optical technology for detection of up to five different fluorescent dyes simultaneously in each well. This allows for multiplexing and precise quantification of nucleic acid sequences. It's widely used in molecular biology for applications like gene expression analysis, genetic variation detection, and DNA quantification.

Biosystems™ 3500 Genetic Analyser and ViiA™7 Real-Time PCR Systems

3500 Genetic Analyzer is a capillary electrophoresis instrument designed for DNA sequencing and fragment analysis. It's commonly used in genetic research, forensic analysis, and disease studies.
ViiA 7 Real-Time PCR System is an advanced real-time PCR platform offering high throughput capabilities and precise temperature control. It's ideal for gene expression analysis, SNP genotyping, and other molecular biology applications.

Illumina NGS Miseq and Novaseq Systems and Microarray

MiSeq System is a compact, all-in-one platform for a wide range of sequencing applications, including small genome sequencing, targeted gene sequencing, and metagenomics.
NovaSeq Systems offers high-throughput sequencing with scalability and flexibility, making it suitable for large-scale genomic projects like whole-genome sequencing, transcriptome analysis, and large-scale genotyping.
Illumina's microarray technology is used for genomic analysis, allowing for the simultaneous measurement of many genes or genetic variants. It's commonly used in genotyping, genome-wide association studies, and comparative genomic hybridization.

Data Collection