Date: 30th September 2024 | Issue #2
The RNA revolution, now beyond its infancy, is in an exciting phase of evolution with vast potential in cancer diagnosis and treatment. The science of RNA, which begins with understanding the central dogma (DNA to RNA to proteins), is driving innovative medical approaches and improved patient outcomes in cancer. In the previous issue, ‘The power of your RNA in cancer,’ we have elucidated the myriad spectra of RNAs that can be used in detecting and monitoring cancer, citing specific examples of these RNAs, which demonstrate how RNA is transforming the cancer landscape and engaging the audience in the potential of RNA from diagnosis to treatment.
In this new issue, we explore the advent and power of RNA technology and its revolution. We focus on the technology that makes these advancements possible. We aim to explain why this technology is considered the gold standard for discovering new ways to diagnose and treat cancer by looking at a widely used technique in clinical and research settings.
Have you ever wondered how scientists classify cancers? How do they identify the genes to target in cancer treatments? For instance, how do doctors classify the subtype of breast cancer? This classification is crucial because it helps doctors select the most effective treatments. The classification of breast cancer types has been significantly advanced by a technology known as RNA-sequencing (RNA-seq). This technique examines the expression of thousands of genes at once providing scientists with a detailed understanding of which genes are turned on or off in a cell. In the context of breast cancer, RNA-seq plays a crucial role in identifying specific patterns that distinguish different subtypes of tumors, thereby aiding in developing personalized therapies.
How does RNA sequencing work? The process begins with collecting tumor/tissue samples from breast cancer patients. The doctors/scientists extract the RNA from the sample and prepare it for ‘sequencing’. Sequencing is a process that scientists use to determine the order of the building blocks of your DNA/RNA. Our genome is very long, made up of sentences with millions of letters. Just like reading a long sentence letter by letter, sequencing is like figuring out the order of the letters in a book to understand the message. Figuring out this message helps you to understand the story. In this case, your genome (DNA or RNA), is the book made up of letters called ‘nucleotides,’ which are the building blocks of your DNA and RNA. These nucleotides form a sequence that carries important information (the message) regarding your biological element, known as a gene. A gene instructs your body on how to make everything they need to function (the story). Therefore, by reading the information about these nucleotides, scientists learn a lot about your genes, how they work, and if they are involved in diseases like cancer. Therefore, sequencing allows us to understand the expression and function of various genes.
After sequencing, we use computational tools to assemble these genes into patterns usable for understanding their functions and quantifying their expression levels. It is through these analyses that various genes are identified as overexpressed or under-expressed. The presence of overexpressed genes in cancer indicates the cancer-promoting properties of those genes, and depending on their known functions, they are implicated in causing and/or promoting cancer. Moreover, identifying these over-expressed genes by RNA sequencing has contributed to classifying cancer and cancer stages, prompting accurate and unique ways of approaching the disease treatment and response to therapies. For example, the well-known breast cancer type is Luminal A, which is known for its high activity of hormone-related genes but has a good prognosis and responds well to hormone therapy. In contrast, Luminal B, has higher activity of genes linked to cell growth, is more aggressive than Luminal A, and may need additional treatments like chemotherapy. On the other hand, HER2-breast cancer is more aggressive, with high activity of the HER2 gene, but has better responses to HER2-targeted therapies such as Herceptin. Basal-like breast cancer has hyperactivity of genes found in basal cells (all types of cells in the breast), such as TP53 (tumor protein p53) genes that are normally mutated in basal-like breast cancer. This leads to loss of tumor suppressive function and enhances uncontrollable cell growth and resistance to apoptosis (natural cell death).
RNA sequencing has improved our understanding of genetic events that underpin cancer consequently informing personalized therapy. With the advent of precision (individualized or personalized medicine), RNA-seq analysis has enabled the study of millions of cancer samples available in The Cancer Genome Atlas (TCGA) database, providing valuable data for ongoing research for the development of better personalized treatments for cancer patients. From technology to practical applications at the point of care (POC) of patients, RNA sequencing has transformed how we understand and treat many types of cancers. It provides comprehensive insights into an individual’s genes and the genetic and molecular mechanisms underlying different cancers. The technology has paved the way for opportunities for not only categorizing cancers but also early detection of these cancers with improved prognosis and timely interventions, treatment monitoring, and personalized medicine while minimizing adverse side effects. All these advancements in RNA-seq have transformed the cancer research landscape, contributing to improved patient outcomes.
Faith Mokobi Zablon is a researcher at ICRF Kenya and a Ph.D. candidate in Nanoengineering (Synthetic Biology) at the Joint School of Nanoscience and Nanoengineering, North Carolina A&T State University.