Western blotting is a decades-old laboratory technique that is used to detect specific proteins from cell culture, tissue, or blood specimen. The term “western blot” is a twist on the Southern blotting method developed by Edwin Southern, which is used to detect DNA and shares methodological similarities with western blotting.
Western blotting is a decades-old laboratory technique that is used to detect specific proteins from cell culture, tissue, or blood specimen. The term “western blot” is a twist on the Southern blotting method developed by Edwin Southern, which is used to detect DNA and shares methodological similarities with western blotting. The western blot method was first described by Harry Towbin in 1979 but the term “western blot” was coined by W. Neal Burnette in 1981[1],[2]. Since its initial description, the application of western blotting to all fields of biological and biomedical research has been broad because it is a straightforward and robust method for detecting specific proteins. Here we provide an overview of the western blot method and highlight the current application of western blotting in preclinical oncology research.
The western blot technique can be used to separate and identify a specific protein using three major steps:
1. Size separation using gel electrophoresis,
2. Transfer to a solid membrane, and
3. Detection with a specific antibody.
Most western blot methods begin with a lysate of cells or tissue, which releases a mix of proteins that are separated by molecular weight using gel electrophoresis. Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) is the most common type of gel electrophoresis for western blotting and includes a protein denaturation step prior to gel electrophoresis such that proteins are separated by molecular weight. The SDS buffer causes proteins to become negatively charged so electrophoresis allows for migration of proteins from smallest to largest weight towards a positive charge. After gel electrophoresis, proteins are transferred to a solid membrane, usually polyvinylidene difluoride or nitrocellulose, using electroblotting or a slower alternative method based on capillary action. This membrane can now be probed with a primary antibody specific to a protein of interest and the primary antibody is visualized using a secondary antibody that recognizes a species-specific region of the primary antibody and is conjugated with a chemiluminescence substrate for visualization. Other less common visualization methods use colorimetric substrates or radioactive labels on secondary antibodies.
Why is western blotting a method that is still used after more than forty years since its development? Western blotting remains a reliable, affordable, and practical method for detecting specific proteins. The application of western blotting in preclinical oncology research allows to validate high throughput single-cell RNA sequencing or proteomics methods that detect elevated proteins associated with specific cancers[3]. Western blotting can also validate tissue microarray and immunohistochemistry findings with respect to specific proteins that are overexpressed in tumor tissue. Together these data can be used toward developing prognostic biomarkers for cancers, such as measuring overexpression of Kin of IRRE-like Protein 1 (KIRREL) in breast cancer and precancerous tissue[4]. Western blotting is also a useful tool for understanding molecular mechanisms that drive cancer progression by measuring expression of critical proteins such as HMGB1, cyclins, and various oncogenes[5],[6].
Western blot has made a leap into the twenty-first century with advancements in process workflow and sensitivity using new platforms like ProteinSimple’s JESS System. Western blot will continue to be a workhorse for detecting and monitoring specific protein expression and the application of western blotting continues to be broad in preclinical and clinical oncology studies related to understanding oncogenesis and defining potential tumor biomarkers.
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In vivo models for numerous diseases and conditions have endpoints that have involved animals being gravely ill or dying. As researchers have sought to utilize animal models in more humane and practical ways, surrogate endpoints have been developed that prevent animals from suffering and provide critical research data. Flow cytometry has been instrumental to these advances. Consider these aspects of preclinical flow cytometry endpoint analysis as you develop new protocols.
Flow cytometry provides the most useful data when the cell subsets of interest are well-defined and robust. You may need to analyze existing research literature or do pilot studies to define the immune cell subsets of interest for a particular disease state, be it changes in regulatory T cells in the tumor microenvironment, or the proliferation of plasmablasts in different leukemias. You must identify which profound changes in different cell populations are most closely correlated with morbidity and mortality in your animal model.
Preclinical studies with surrogate endpoints are valuable for screening potential therapeutic candidates. These drugs or biologics may have undesirable off target effects as well. In designing a flow cytometry assay for alternative endpoints, it is critical to identify the changes in immune cell subsets that reflect therapeutic improvements or indicate potential toxicity or off target effects.
Flow cytometry endpoint analysis not only advances the humane use of animal models but can be translated into informative clinical protocols that are critical for the evaluation of potential therapies.
Next-generation sequencing (NGS) technology has transformed the biomedical research landscape. Only a few years ago, high resolution genome or exome sequencing would be cumbersome and cost-restrictive, but current NGS technology platforms now allow for basic and clinical researchers to include these approaches for routine DNA and RNA sequencing needs. What are the different NGS sequencing approaches and how are they applied to oncology research?
1. Whole Genome Sequencing (WGS): NGS technology can be used for WGS of human genomes and tumor-specific genomes, as well as animal model and microbial genomes. WGS produces high resolution genomic sequences of expressed genomic regions as well as unexpressed regulatory regions. For preclinical oncology research, WGS is critical for characterizing genomic profiles associated with tumor progression or potential responsiveness to targeted drug therapies. WGS can detect single nucleotide variants, copy number variants, and insertions/deletions in tumor cells[1]. The comprehensive scope of WGS makes it well suited for detecting mutations in both coding and non-coding regions[2]. WGS is also useful for population level oncology studies that evaluate genetic susceptibility to specific cancers and potential heritability[3].
2. Whole Exome Sequencing (WES): WES techniques focus on sequencing the exome, which are comprised of protein expressing regions, or exons, within the genome. WES is an appropriate method for identifying genetic mutations that alter protein sequences, and WES data can be used toward measuring the tumor mutational burden (TMB) and predicting treatment efficacy[4]. WES data can also be used to identify potential new drug targets or mechanisms of drug resistance[5].
3. Targeted Sequencing: This method focuses on defined gene regions and is typically used in diagnostic applications or for validation of WGS or WES results. Targeted sequencing works well for screening tumor samples for well characterized mutations, such as those associated with BCL2, BRCA-1/2, BRAF, and EGFR, and can be used for identifying appropriate targeted therapies[6].
4. RNA sequencing: RNA sequencing is now emerging as a powerful tool that complements NGS DNA methods because the transcriptional profile of a single cell can be measured and used to bridge genomic data with cellular phenotypes. Single-cell RNA sequencing (scRNA-seq) has specifically emerged as a powerful method for understanding the heterogeneity of cell populations within a tumor. Together with histological data, scRNA-seq data can be used to distinguish between neoplastic cells, immune cells, and healthy cells from the surrounding tissue, and it can also be used to evaluate how experimental treatments alter the tumor microenvironment[7].
NGS methods are transforming both basic oncology research and clinical care, from identifying novel mutations to pinpointing personalized cancer therapies. Each method is suited to specific applications, so working with experts in NGS technology is critical to method selection and data analysis.
1 Bewicke-Copley F et al. Applications and Analysis of Targeted Genomic Sequencing in Cancer Studies. Comput. Struct. Biotechnol. 2019;17: 1348-1359.
2 Nakagawa H, Fujita M. Whole Genome Sequencing Analysis for Cancer Genomics and Precision Medicine. Cancer Sci. 2018;109(3):513-522.
3 Rotunno M et al. A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer. Cancer Epidemiology and Prevention Biomarkers. 2020;29(8):1519-34.
4 Klempner SJ et al. Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence. Oncologist. 2020 Jan;25(1): e147-e159.
5 Beltran H et al. Whole-Exome Sequencing of Metastatic Cancer and Biomarkers of Treatment Response. JAMA Oncol. 2015;1(4):466-474.
6 Vestergaard LK et al. Next Generation Sequencing Technology in the Clinic and Its Challenges. Cancers (Basel). 2021;13(8):1751.
7 Fan J et al. Single-Cell Transcriptomics in Cancer: Computational Challenges and Opportunities. Exp Mol Med. 2020; (52)1452–1465.
