The Science Behind Measuring Bcl-2 Protein Expression
In the microscopic universe within our cells, a delicate dance between life and death plays out continuously. At the center of this dance is B-cell lymphoma 2 (Bcl-2), a protein that functions as a master regulator of cellular survival. Discovered in 1984 as the gene involved in a chromosomal translocation found in most follicular lymphomas, Bcl-2 represented a breakthrough in cancer biology—the first example of an oncogene that promotes cancer not by accelerating cell division but by preventing programmed cell death (apoptosis) 1 .
Maintains tissue homeostasis by preventing excessive cell death
Contributes to cancer development and resistance to therapy
When scientists talk about "measuring protein expression," they're often actually measuring messenger RNA (mRNA) levels—the genetic blueprint that cells use to produce proteins. This is because mRNA levels generally correlate with the amount of protein a cell produces, and mRNA is much easier to quantify than proteins themselves.
The gold standard for mRNA quantification is quantitative polymerase chain reaction (qPCR), a technique that allows researchers to amplify and detect specific DNA sequences with incredible sensitivity. The key to qPCR's specificity lies in the primers—short sequences of single-stranded DNA that are designed to match perfectly with the target gene 3 .
Designing effective primers for Bcl-2 presents unique challenges. The BCL2 gene produces multiple splice isoforms (different versions of the mRNA), with the membrane-bound BCL2α and the less studied soluble BCL2β being the most prominent. Most commercially available primers amplify only BCL2α or larger amplicons, potentially leading to incomplete measurement of the gene's expression profile 3 .
The human BCL2 gene is located on chromosome 18 and consists of three exons that code for a 239-amino acid protein. The primers most commonly used for human BCL2 qPCR analysis target the NM_000633 transcript variant, which encodes the canonical Bcl-2 protein 2 .
These primers produce an amplicon of approximately 100-200 base pairs, ideal for qPCR amplification efficiency 2 .
One significant challenge in Bcl-2 measurement is selecting appropriate reference genes for normalization. Reference genes, sometimes called "housekeeping genes," are genes whose expression is presumed to remain constant across different conditions and cell types. They serve as internal controls to ensure that differences in mRNA levels reflect actual biological changes rather than variations in sample preparation or loading.
Common reference genes like GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and RPL32 (ribosomal protein L32) have been shown to vary significantly across different tissue types and experimental conditions, making them unsuitable for many studies 3 . Surprisingly, research has revealed that Bcl-2 itself shows remarkably stable expression in certain contexts, such as human colon cancer cells treated with various compounds, making it a potential reference gene for studies in these systems 5 .
In 2020, researchers embarked on an ambitious project to identify the most stable reference genes for quantifying BCL2 mRNA in diagnostic applications, particularly for hematological malignancies 3 . This was crucial because inaccurate normalization could lead to misinterpretation of BCL2 expression levels, potentially affecting treatment decisions.
The researchers began with an extensive literature search to identify reference genes commonly used in studies of hematological malignancies.
They analyzed four RNA-seq datasets containing gene expression data from various blood cancers, including acute myeloid leukemia (AML), diffuse large B-cell lymphoma (DLBCL), and multiple myeloma.
Using statistical measures including coefficient of variation (CV), median absolute deviation (MAD), and normality testing, they evaluated the expression stability of over 60,000 genes.
The top candidate genes were tested using qPCR on samples from various haematological malignancies.
BCL2 mRNA levels normalized using the novel reference genes were compared with those normalized using GAPDH, the most commonly cited reference gene.
| Measure | Calculation | Interpretation |
|---|---|---|
| Coefficient of Variation (CV) | Standard deviation / Mean | Lower values indicate greater stability |
| Median Absolute Deviation (MAD) | Median(|X - median(X)|) | Less sensitive to outliers than standard deviation |
| Normality p-value | Shapiro-Wilk test | Higher p-values indicate more normal distribution |
The study revealed that commonly used reference genes like GAPDH showed significant variation across samples, while genes such as PTCD2, PPP1R3B and FBXW9 demonstrated much greater stability. When BCL2 mRNA levels were normalized using these stable reference genes, they showed consistently higher expression in hematological malignancy patients compared to normalization with GAPDH 3 .
This finding has profound implications for diagnostic applications, as it suggests that previous studies using suboptimal reference genes may have underestimated BCL2 overexpression in certain cancers.
| Sample Type | BCL2 Expression (GAPDH-normalized) | BCL2 Expression (Novel RG-normalized) | Fold Difference |
|---|---|---|---|
| Lymph Node #1 | 1.0 | 3.2 | 3.2x |
| Lymph Node #2 | 1.5 | 4.1 | 2.7x |
| Bone Marrow #1 | 0.8 | 2.6 | 3.3x |
| Bone Marrow #2 | 1.2 | 3.3 | 2.8x |
In a surprising twist, a 2022 study investigating cottonseed-derived compounds found that Bcl-2 mRNA was the most stably expressed among 55 genes analyzed in human colon cancer cells (COLO 205) treated with various compounds 5 . This stability was consistent across different treatments including gossypol, lipopolysaccharides (LPS), and cottonseed extracts, regardless of treatment duration.
The researchers generated an impressive 10,560 Cq values from 64 treatments with triplicate measurements for each gene. The stability of Bcl-2 expression suggests that its regulation may occur primarily at the post-transcriptional level rather than through changes in mRNA production 5 .
Research has revealed that different anti-apoptotic Bcl-2 family members show distinct expression patterns across cancer types. A comprehensive survey of 68 human cancer cell lines found that 4 :
Shows the highest expression in lung, prostate, breast, ovarian, renal, and glioma cancer lines
Dominate in leukemia/lymphoma and melanoma cell lines, respectively
| Cancer Type | Predominant Anti-Apoptotic Protein | Response to BCL-2 Inhibitors |
|---|---|---|
| Leukemia/Lymphoma | BCL-2 | Strong |
| Melanoma | Bfl-1 | Limited |
| Breast Cancer | Mcl-1 | Limited |
| Lung Cancer | Mcl-1 | Limited |
| Ovarian Cancer | Mcl-1 | Limited |
Successful Bcl-2 expression analysis requires careful selection of research reagents. Here are the key components:
Designed to target the appropriate BCL2 transcript variant without cross-reacting with similar sequences 2 .
Essential for obtaining undegraded, pure RNA without genomic DNA contamination.
High-efficiency enzymes for converting RNA to complementary DNA (cDNA).
Optimized mixtures containing DNA polymerase, nucleotides, buffers, and fluorescent dyes.
Appropriate for the specific tissue and experimental conditions being studied 3 .
Samples with known BCL2 expression levels to validate assay performance.
The humble primer pair—a few dozen nucleotides of synthesized DNA—serves as the key that unlocks our understanding of Bcl-2 expression. Through careful design, validation, and application of these specific sequences, researchers and clinicians can accurately measure the expression of a protein that plays a crucial role in cancer development and treatment response.
As research continues to reveal the complexities of Bcl-2 biology and its interactions with family members, the tools for measuring its expression will continue to evolve. From basic research to clinical diagnostics, these advances promise to improve our ability to target the Bcl-2 family for therapeutic benefit, ultimately leading to more effective and personalized cancer treatments.
The story of Bcl-2 measurement exemplifies how methodological advances in basic science can translate into clinical improvements, highlighting the interconnectedness of basic research and medical application in the ongoing effort to combat cancer.
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