Here’s how RNA Analysis can Help Predict Cancer at a very Nascent Stage

RNA Analysis

Predicting cancer at a very nascent stage could play a very crucial role in treatment and prevention. Cancer has been identified as a life-threatening disease which accounts for 13% of all deaths in the world. It has further been predicted that in the next two decades, cancer levels will rise. As a result, it has become imminent to come up with effective ways to detect and treat cancer at a very nascent stage. Traditional methods of cancer detection, which include imaging procedures, biopsies, and lab tests have not proved effective in the early detection of cancer.

In addition, they have proven to be expensive and time-consuming. However, all hope is not lost as new methods of cancer detection are proving to be more effective in early detection. RNA analysis is one of the latest technologies that are not only effective in early detection but also useful in the development of treatments and prevention. RNA plays the biological functions of genetic transmission and regulatory factor.  Compared to other biomarkers, RNA is more effective because it can detect disease at low abundance. Also, as compared to DNA, it lowers the cost of detection because it does not rely on proteins which require a specific antibody. More importantly, RNA has multiple copies in a cell which provides more insights than DNA.

RNA analysis can help predict cancer at a very nascent stage through certain clinical significance in cancer prediction and treatment. They include diagnostic, prognostic and predictive. Diagnostic involves early prediction, identifying the origins of tumors, and the classification of cancer type. Conversely, prognostic consists of the determination of the outcomes and risks assessments associated with cancer. Lastly, predictive revolves around the responses of treatments. RNA has a powerful diagnostic and prognostic significance. Firstly, it is easy to detect cancer through RNA analysis.

This is because different types of RNA are found in biofluids, which include breast milk, saliva, urine, bile, serum, plasma, and cerebrospinal fluid. The fluids have been used in the early detection of various types of cancer, which include Prostate, Pancreatic, Gastric, Brain and Liver cancer. Secondly, RNA analysis can easily identify adverse cell defects such as mutations, deletions, insertions, translocations, and exon-skipping, which indicate the presence of cancer. 

Cancer is described by genetic lesions that affect genes which can lead to mutation, gene fusion, translocation, and deletion. RNA analysis can help predict cancer at a very nascent stage by identifying the genetic lesions. In addition, RNA analysis indicates the expression levels of the mutant genes. It is effective in identifying the stages of progression of cancer, providing information on the diagnosis.

This is indicated by how various types of RNA biomarkers in cancer are used to identify different types of cancer. The first one is the mRNA which has been used to predict breast cancer, as well as, the recurrence and risk of prostate cancer. The second one is the microRNAs (miRNAs). miRNA plays a central role in cell differentiation and proliferation. As a result, they can be used to classify poorly differentiated types of tumor. The third one is the Piwi-interacting RNA (piRNA).

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piRNA is involved in cell proliferation and invasion. Thus, low expression of them indicates a low survival rate for lymphoma patients. The fourth one is the small nucleolar RNA (snoRNA), which is involved in gene silencing. The expression profile of the snoRNA is useful in the early detection of lung cancer.

RNA analysis has further played an important role in the classification of cancer subtypes. The immune-associated genes through RNA sequencing can be used to identify tumor-associated cancers. The immune system of cancer patients of breast cancer, glioblastoma, and colorectal is suppressed, especially in the cancer adjacent cells. As a result, it is possible to use immune genes to classify the cancer types depending on the places the immune system is suppressed. The classification of cancer subtypes is critical in the correct prediction of the type of cancer and treatment.

Various studies have been conducted to show how RNA analysis helps predict cancer at a very nascent stage. One of the studies focused on the use of RNA sequencing in the detection of gene fusion in tumors. The study used a total of 76 specimens out of which 15 were normal tissues, and the remaining 61 were tumor specimens (Siegel et al., 2018). The study concluded that RNA sequencing is a powerful method for detecting gene fusion’s tumors.

The second study explored how RNA sequencing can be used to predict ovarian cancer recurrence. The study used 391 RNA sequencing profiles out of which 220 were recurrence and 171 were non-recurrence (Wang et al., 2018). The study concluded that low expression of IncRNAs was associated with recurrent ovarian cancer. These are just among the many studies that have proven the effectiveness of RNA analysis in predicting cancer at a very nascent stage, which then increases the chances of a patient to survive.


RNA analysis has a lot of potential in enhancing early detection and treatment of cancer. RNA analysis has already proved to be effective in the prediction of cancer at a very nascent stage. You can analyze data here with Basepair, who is an expert in this field. The expression of various types of RNA has been useful in the prediction of Prostate, Breast, Liver, and Lung cancer. More studies are currently being conducted on the applications of RNA. Thus, in the future, there will be more discoveries in RNA analysis that will enhance cancer prediction at a very nascent stage.

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