What mRNA Expression of Cancer Genes Means
mRNA expression of cancer genes refers to the measurement and quantification of messenger RNA molecules produced by specific genes in tumor tissue, which serves as a direct indicator of gene activity and protein production potential in cancer cells. 1
Basic Definition and Biological Function
mRNA (messenger ribonucleic acid) functions as the protein-coding template that is synthesized in the nucleus and exported to the cytosol for translation into proteins. 1 Mature mRNAs contain several key structural components including a 5′ methyl-7-guanosine cap, 5′ untranslated region, a coding region, a 3′ untranslated region, and a 3′ poly-A tail. 1
When we measure mRNA expression of cancer genes, we are essentially:
- Quantifying how actively specific genes are being transcribed in tumor cells 1
- Assessing the amount of mRNA template available for protein production 1
- Determining which genes are turned "on" or "off" in cancer versus normal tissue 2
Clinical Application in Cancer
Gene Expression Profiling Tests
Gene expression profiling identifies expression or activity of genes associated with disease prognosis by characterizing and quantifying cellular mRNA in tumor tissue. 1 This technology has moved from research into clinical practice through several FDA-cleared and CLIA-certified tests. 1
Clinically validated tests measure mRNA expression using two primary methods:
- Real-time reverse transcription polymerase chain reaction (RT-PCR) for detection and quantitation of mRNA in formalin-fixed, paraffin-embedded tissue 1
- Microarray technology where labeled patient mRNA is hybridized to DNA sequences from known genes on customized chips 1
Specific Clinical Examples
Oncotype DX® Colon examines 12 genes (7 cancer-related and 5 reference control genes) through RT-PCR to measure mRNA expression levels and predict the likelihood of cancer metastasis within 3 years after diagnosis. 1 The seven cancer-related genes include:
- BGN, INHBA, FAP (associated with activated stroma)
- MK167, MYBL2, MYC (associated with cell cycle activation)
- GADD45B (related to genotoxic stress) 1
Oncotype DX® Breast analyzes a 21-gene panel using mRNA expression to predict recurrence risk and guide chemotherapy decisions following surgical removal of primary tumors. 1
MammaPrint tests for 70 cancer-related genes plus approximately 1800 normative genes using microarray technology on fresh or frozen tumor tissue. 1
Why mRNA Expression Matters in Cancer
Reflects Functional Gene Activity
While mutations lie at the heart of cancer initiation, mRNA expression reveals the downstream functional consequences of these mutations and represents phenotypic changes many steps removed from the initiating mutation. 2 This is critical because:
- Cancer develops from both genetic mutations producing abnormal proteins AND dysregulation of translation leading to aberrant protein synthesis 3
- Changes in gene expression—upregulation of oncogenes and/or downregulation of tumor suppressor genes—can be generated by genetic, environmental, AND epigenetic factors 4
- Proteins are the functional molecules that determine cell types and function, making mRNA the critical intermediate step 3
Captures Multiple Cancer Processes
Genes involved in cancer affect normal functions of many cellular processes beyond just proliferation, including cell-cell and cell-matrix interactions, DNA repair, invasion and motility, angiogenesis, senescence, and apoptosis. 2 Measuring mRNA expression allows identification of genes affecting these diverse processes that might not be detected through mutation screening alone. 2
Types of RNA Involved in Cancer
Coding RNA (mRNA)
Both full-length and fragmented mRNA have been discovered in cancer cells and extracellular vesicles. 1 mRNAs from cancer cells can contain fragments ranging from 25 to 4000 nucleotides, whereas normal cellular mRNAs typically range from 400 to 12,000 nucleotides. 1
Non-Coding RNAs
MicroRNAs (miRNAs) are small non-coding RNAs (approximately 18-22 nucleotides) that can bind to mRNA to control protein expression and have unique profiles when comparing diseased versus normal tissue. 1 These molecules:
- Can modulate the function of tumor suppressors or dominant oncogenes by affecting transcription, translation rates, or mRNA/protein half-life 1
- May regulate up to two-thirds of the human genome based on computational analysis 1
- Have been implicated in all fundamental hallmarks of cancer initiation and progression 1
Long non-coding RNAs (lncRNAs) consist of >200 nucleotides and control gene transcription, mRNA production, protein translation, cellular senescence, and assembly of macromolecular structures. 1 Multiple specific lncRNAs are upregulated in circulating extracellular vesicles from liver, breast, and cervical cancers. 1
Clinical Utility
Prognostic Information
mRNA expression patterns can predict the likelihood that cancer cells will spread or metastasize, providing individualized recurrence scores that correlate with patient outcomes. 1 This information helps healthcare providers and patients make informed decisions about implementing additional chemotherapy treatment following surgery. 1
Diagnostic Applications
Because expression of many genes is lost during cancer progression, they may serve as useful tumor markers for diagnosis and prognosis. 2 Additionally, genes whose expression is altered but not mutated provide opportunities for pharmacological intervention by inducing their re-expression. 2
Important Caveats
mRNA expression analysis requires proper specimen handling, with specific protocols for evaluating tumor content, preparing mRNA samples, normalizing expression data, and computing summary indices. 1 Different assay platforms (RT-PCR versus microarray) have distinct requirements for tissue preparation—some require fresh or frozen tissue while others can use formalin-fixed, paraffin-embedded samples. 1
The interpretation of mRNA expression levels has been improved through approaches like Gene Set Enrichment Analysis (GSEA), which recognizes that mRNAs from genes in the same pathway tend to have relatively similar average expression levels and cluster together statistically. 1