Sun. Nov 10th, 2024

Over the past ten years, especially in the last few years, there has been a significant increase in the use of immunohistochemistry (IHC) and immunofluorescence (IF). For certain labs, there might be too many options, even as research capabilities and technology have progressed with them. According to Joe Poh sheng Yeong, a research immunopathologist at Singapore General Hospital, “newcomers in the field may be caught between excitement for a bright future – and confusion.” Multiplex IF offers a distinct path towards that promising future.

Read More: spatial phenotyping

Spatial phenotyping is made possible by multiplex IF, according to Matt Humphries, scientific lead for tissue hybridization and digital pathology at Queen’s University Belfast. This technique allows researchers to “not only identify several cell types within a single sample, but also categorize whether a particular cell is expressing several biomarkers – allowing us to recognize specific phenotypes.” In addition to addressing treatment regimen failures in clinical trials, particularly in immuno-oncology, this high degree of cell profiling may carry important prognostic information at a fundamental diagnostic level.

An unfulfilled desire

Less than 20% of cancer types now receiving immunotherapy respond well to current treatments. Yeong states, “Personalized medicine, which is what we as a community of immuno-oncology researchers strive for, could improve this.” “However, technical and accessibility issues, long turnaround times, and financial constraints still exist in resource-constrained areas.”

Not only that, but transcriptome analysis and next-generation sequencing (NGS) were the main methods used to predict therapy response until the advent of spatial phenotyping. The loss of influential cell types’ spatial arrangement is a major negative, according to Humphries, “even though these techniques are essential for gaining high quality subvisual data.” Even with traits that are expressed at extremely low levels, maintaining the morphological landscape can aid in the identification of important phenotypes that may have an influence on tumor growth or patient survival.

Big data difficulties

Generating big data in biomarker research is another difficulty. It is required of clinicians to evaluate hundreds or thousands of samples, with each whole-slide multiplex IF pictures up to 100 GB in size at times. Humphries states that it is impractical to expect the human eye to accurately and reproducibly evaluate and quantify a picture with hundreds of thousands of data points and report these, particularly in the short amount of time diagnosticians have to evaluate a single slide.

Simplifying this massive tsunami of data is becoming more and more important in order to help researchers find biomarkers for cancer. Humphries states, “Computational pathology can do this quickly and reliably, but it could take a clinician many hours to accurately quantify the number of cells expressing two biomarkers within a certain proximity to tumor cells.” However, who is really in charge of advancing it? “This high-level information could be invaluable to an oncologist deciding on a patient’s treatment course, but laboratory medicine professionals will need to authorize such analysis.”

Unmistakable benefits

For patients to get optimal treatment, it is essential to predict the result of immunotherapy. While there are several approaches available, spatial phenotyping offers a distinct benefit due to its lower requirement for a greater number of tissue slides. Humphries emphasizes that “human tissue can be a limited resource if multiple biomarkers need to be assessed in order to predict the response to immunotherapy, regardless of whether it is used for research or clinical diagnosis.”

“The topography of the tissue changes as you progress through a specimen because each successive slide is stained and reviewed,” he continues. “Not only does this require several slides to analyze individually (which may be limited if the tissue is a small diagnostic biopsy or a precious tissue microarray research resource).”

How can this be addressed by multiplex IF? According to Humphries, “all these biomarkers and their cellular landscape can be captured in one slide by spatial phenotyping.” Moreover, cell types with co-expressed biomarkers that may have prognostic significance can be identified with multiplex IF. Spatial analysis is useful in the vicinity of these traits since the data at this level may be highly indicative of an immunotherapy response.

Yeong concurs, saying “the benefits are enormous.” I doubt that anyone involved with immunotherapy for cancer could dispute that. We can study phenotypes where multiple marker identification is necessary, and preserve tissue for examining two markers on a single slide. We can accomplish this in a manner that works with the majority of digital pathology analytical software for thorough interpretation, including high-dimensional and spatial analysis. Additionally, there is a great chance that it will work well for clinical translation.

Taking the lead

Yeong thinks there is a lot for early adopters of spatial phenotyping with multiplex IF to look forward to in the future. “Labs won’t have to contract out to another lab, unlike those who implemented NGS and molecular testing years ago. Instead, the data will be understood and interpreted by their internal researchers. Nevertheless, he states that oncologists and surgeons won’t have to worry about this aspect of immunopathological monitoring if the lab is a member of an Academic Medical Center or National Cancer Center. This is because immunopathological monitoring is becoming necessary in the majority of big trials and research.

Humphries continues, “Researchers using multiplex IF for spatial phenotyping will rapidly discover the enormous amount of data that can be found on a simple tissue slide. The requirement for precise, objective analytical goals to significantly affect patient survival will increase along with the potential for more sophisticated data extraction.

Stay ahead of the curve.

Research labs running the danger of growth stunting are those that do not use spatial phenotyping in their work. According to Humphries, “They will only continue to provide the excellent diagnoses and reporting that they are currently capable of.” He acknowledges that when new technology challenges the status quo, caution is understandable, but he asserts, “There will be a point of critical mass when industry, national health agencies, and patient needs will drive adoption. The laboratories that push the envelope with these new methods will truly reap the benefits.” The advent of methods and tools like digital pathology, high-throughput auto-staining systems, and IHC in recent medical history is evidence of this.

For those who haven’t made the switch yet, there are organizations committed to assisting laboratories in adapting, so all is not lost. “I work on a task group known as the JEDI council. Yeong states, “We want to increase accessibility to staining, imaging, troubleshooting, analysis, interpretation, and reporting knowledge on standardization and quality control.” “And there’s more; numerous international task forces and committees are already contributing to this endeavor.”

Furthermore, laboratories might begin small before moving on to spatial phenotyping. “We began cautiously with small panels that we designed to validate our findings in single-plex analysis; one of these was in a cohort of esophageal adenocarcinomas showing a dual-positive phenotype that may be predictive of outcome,” adds Humphries. However, as our panels have expanded, so too have our technical expertise and self-assurance in panel design and application increased internally.

Parting insight

Yeong and Humphries have a crucial message for laboratory medicine and pathology practitioners, regardless of where they are in their spatial phenotyping journey. Yeong notes that although the discipline of oncology has advanced since the days of “H&E-only” treatment to IHC, molecular diagnostics, and cancer immunotherapy, there is still more work ahead of it. In order to advance the field and get past financial constraints and long turnaround times, multiplex IHC and IF will require teamwork and shared knowledge.

Humphries concurs that laboratories should embrace spatial phenotyping right now and lead by example. Remember to have talks as soon as possible about new technology. Early acceptance of new technology would take significantly longer without your knowledgeable and specialized advice, he claims. “As a translational scientist, my aim is to assist laboratory medicine specialists and pathologists in their outstanding work. I would expect that all scientists would wish to follow this beneficial route if new methods of working might enhance specialized clinical abilities, save time, and improve patient care.