Emily Newton, Contributing Writer05.24.22
Utilizing immunohistochemistry (IHC) for cancer diagnostics, neurology and research and development dates to the 1930s. Researchers didn’t complete the first IHC study until 1942, using FITC-labeled antibodies to identify pneumococcal antigens successfully. The rest, as they say, is history. The techniques may look different than they did back in the 1940s, but some of the same challenges remain.
Automation is beginning to emerge as an invaluable tool for multiple industries, including medicine. Can automation help optimize immunohistochemistry?
Alone, it is valuable for diagnostics. When paired with other analytical techniques, IHC can be used to monitor healthy tissue or pathological processes. It can also be an invaluable tool for tracking natural actions like cell death, cell repair and wound healing.
Today, IHC also makes appearances in drug development and biological research. The last 15 years or so have seen significant advances in technology. IHC is never easy, but the ability to prepare samples, understand multiple-parameter data and more has vastly improved.
In 2018, the vacancy rate for the histology specialty was 8.37%, up from the 5.6% reported in 2017. More than 18% of histology lab supervisors are expected to retire within the next three to five years, and IHC-centric labs are swiftly running out of people with the necessary skills to complete this invaluable lab work.
Automation could take some of the load off these already overwork laboratory technicians, either by completing mundane tasks or analyzing stained samples and comparing them to a database of collected images.
Antibody validation
Other forms of diagnostics, such as immunoblotting, can compare cell staining to an existing molecular weight ladder to verify the targeted protein. There is no such molecular weight ladder for IHC. Each primary antibody used in IHC needs to be validated using the western blot procedure or other similar practices for accurate diagnostics. Identifying the target protein without this antibody validation can be challenging, leading to inaccurate diagnostics.
Strong background staining
Things can go wrong even under ideal conditions. Problems with endogenous biotin or reporter enzymes can cause strong background staining. This makes it impossible to differentiate the background from the target protein. This problem can also occur because of antibody cross-reactivity in the primary or secondary antibody.
Weak target antigen staining
Diagnostics aren’t possible if the target antigens don’t stain sufficiently. Problems with enzyme activity or antibody potency can interfere with antigen staining.
Autofluorescence
Autofluorescence can occur naturally in some tissues, causing them to illuminate. In IHC, it can also be observed as an error caused by the fixation method.
Marker diversity
There are dozens or even hundreds of IHC markers to choose from, depending on the diagnostic criteria. This number does not include new markers being verified for diagnostic or R&D applications.
Could automation help optimize IHC in lab settings despite all these challenges?
Automation can be a boon for labs that focus on IHC. It isn’t currently possible to control all the variables that could negatively impact tissue collection or IHC staining, but automation could help mitigate some of them.
Automation can improve standardization and optimization in IHC testing. Studies suggest it could also guarantee labelling quality and improve operation traceability.
Many tasks previously relegated to lab employees could be automated. However, some qualifications are necessary to make automation suitable for IHC, including equipment capable of analytical flexibility. Low-cost automation would be ideal, but it isn’t always possible. Walkaway operation, user-friendly interface and biosafety capabilities are also essential for IHC applications.
Emily Newton is the Editor-in-Chief of Revolutionized. She’s always excited to learn how the latest industry trends will improve the world. She has over five years of experience covering stories in the science and tech sectors.
Automation is beginning to emerge as an invaluable tool for multiple industries, including medicine. Can automation help optimize immunohistochemistry?
New IHC applications
Immunohistochemistry has been around for decades, used primarily for cancer diagnosis or confirming the presence of specific types of cells. Researchers and scientists are discovering new applications for this technology. Stained samples can be observed either through a standard light microscope or more sophisticated electron microscopy.Alone, it is valuable for diagnostics. When paired with other analytical techniques, IHC can be used to monitor healthy tissue or pathological processes. It can also be an invaluable tool for tracking natural actions like cell death, cell repair and wound healing.
Today, IHC also makes appearances in drug development and biological research. The last 15 years or so have seen significant advances in technology. IHC is never easy, but the ability to prepare samples, understand multiple-parameter data and more has vastly improved.
Growing staff shortages
One of the biggest challenges facing IHC technicians isn’t the technology itself — it’s the lack of skilled hands to prepare samples and analyze them once stained. Histology laboratories are facing a historic shortage of qualified laboratory technicians.In 2018, the vacancy rate for the histology specialty was 8.37%, up from the 5.6% reported in 2017. More than 18% of histology lab supervisors are expected to retire within the next three to five years, and IHC-centric labs are swiftly running out of people with the necessary skills to complete this invaluable lab work.
Automation could take some of the load off these already overwork laboratory technicians, either by completing mundane tasks or analyzing stained samples and comparing them to a database of collected images.
Challenges of IHC
When done correctly, IHC can be one of the most accurate forms of diagnostics for various cancers and some neurological conditions. What are some of the most common challenges of IHC?Antibody validation
Other forms of diagnostics, such as immunoblotting, can compare cell staining to an existing molecular weight ladder to verify the targeted protein. There is no such molecular weight ladder for IHC. Each primary antibody used in IHC needs to be validated using the western blot procedure or other similar practices for accurate diagnostics. Identifying the target protein without this antibody validation can be challenging, leading to inaccurate diagnostics.
Strong background staining
Things can go wrong even under ideal conditions. Problems with endogenous biotin or reporter enzymes can cause strong background staining. This makes it impossible to differentiate the background from the target protein. This problem can also occur because of antibody cross-reactivity in the primary or secondary antibody.
Weak target antigen staining
Diagnostics aren’t possible if the target antigens don’t stain sufficiently. Problems with enzyme activity or antibody potency can interfere with antigen staining.
Autofluorescence
Autofluorescence can occur naturally in some tissues, causing them to illuminate. In IHC, it can also be observed as an error caused by the fixation method.
Marker diversity
There are dozens or even hundreds of IHC markers to choose from, depending on the diagnostic criteria. This number does not include new markers being verified for diagnostic or R&D applications.
Could automation help optimize IHC in lab settings despite all these challenges?
Incorporating automation in the lab
Laboratories, especially those working with limited funding, might be hesitant to adopt new technologies such as automation. Purchasing the necessary equipment can represent a significant initial investment and the expense of hiring individuals who know how to use and maintain it.Automation can be a boon for labs that focus on IHC. It isn’t currently possible to control all the variables that could negatively impact tissue collection or IHC staining, but automation could help mitigate some of them.
Automation can improve standardization and optimization in IHC testing. Studies suggest it could also guarantee labelling quality and improve operation traceability.
Many tasks previously relegated to lab employees could be automated. However, some qualifications are necessary to make automation suitable for IHC, including equipment capable of analytical flexibility. Low-cost automation would be ideal, but it isn’t always possible. Walkaway operation, user-friendly interface and biosafety capabilities are also essential for IHC applications.
IHC optimization for the future
Immunohistochemistry is an invaluable tool for various medical and scientific applications. Optimizing this practice for the future will help ensure its viability and efficacy as the industry continues to change and evolve. Automation is the key to improving drug development and advancement.
