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Diagnostics Digital and computational pathology, Microscopy and imaging, Oncology

Staying Ahead of the Rest with Spatial Phenotyping

sponsored by Akoya Biosciences

The use of immunohistochemistry (IHC) and immunofluorescence (IF) has grown rapidly over the past decade – especially in recent years. Though research capabilities and technologies have advanced alongside them, for some labs, the choices can be overwhelming. “Beginners in the field may be caught between excitement for a bright future – and confusion,” says Joe Poh sheng Yeong, a research immunopathologist at Singapore General Hospital. But one clear route to that bright future lies in multiplex IF.

Multiplex IF opens the door to spatial phenotyping, which enables labs 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,” says Matt Humphries, scientific lead for Tissue Hybridization and Digital Pathology at Queen’s University Belfast. “This high level of cell profiling could hold significant prognostic information at a basic diagnostic level, while addressing the failures of treatment regimens in clinical trials – particularly in immuno-oncology.” 

An unmet need 
Current immunotherapy response rates are poor – fewer than 20 percent across several cancer types. “This could be improved with personalized medicine, which is what we strive for as a community of immuno-oncology researchers,” says Yeong. “But resource-limited areas still face accessibility and technical challenges, slow turnaround times, and cost limitations.”

That’s not all; prior to the rise of spatial phenotyping, predicting treatment response relied mostly on next-generation sequencing (NGS) and transcriptomic analysis. “Though these techniques are essential for gaining high quality subvisual data, the loss of spatial arrangement of influential cell types is a significant drawback,” says Humphries. “Retaining the morphological landscape can help us identify key phenotypes that can impact tumor progression or patient survival – even with phenotypes that are expressed at very low levels.”

Big data challenges 
Big data generation in biomarker research also presents a challenge. Clinicians are expected to analyze hundreds to thousands of samples, with single whole-slide multiplex IF images sometimes as large as 100 GB. “It is unrealistic to expect the human eye to assess and quantify an image containing hundreds of thousands of data points and report these with a high degree of accuracy and reproducibility,” says Humphries, “especially within the timeframe that diagnosticians have to assess a single slide.”

There is a growing need to simplify this wave of big data.

There is a growing need to simplify this wave of big data that will inform biomarker discoveries in cancer research. “Accurately quantifying the number of cells expressing two biomarkers within a certain proximity to tumor cells could take a clinician many hours to complete – but this is something computational pathology can do rapidly and reliably,” says Humphries. But where does the responsibility for driving it forward lie? “Laboratory medicine professionals will need to authorize such analysis – but this high-level information could be invaluable to an oncologist deciding on a patient’s treatment course.”

Clear advantages 
Predicting immunotherapy outcome is fundamental for providing patients with the best possible treatment and, although there are various methods to choose from, spatial phenotyping is particularly advantageous because of the reduced need for larger numbers of tissue slides. Humphries highlights that “human tissue – whether used for research or clinical diagnosis – is precious and can be a finite resource if predicting immunotherapy response requires the assessment of several biomarkers.”

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) but, because each successive slide is stained and reviewed, the topography of the tissue changes as you progress through a specimen.”

How can multiplex IF overcome this? “Spatial phenotyping can capture all these biomarkers and their cellular landscape in one slide,” says Humphries. “Furthermore, multiplex IF can identify cell types that co-express biomarkers with potential prognostic value. It is in the proximity of these phenotypes where spatial analysis is valuable – this level of data could strongly indicate immunotherapy response.”

“The advantages are tremendous,” agrees Yeong. “I doubt anyone working in cancer immunotherapy can deny that. We can investigate phenotypes that require us to identify more than one marker and save the tissue for investigating two markers on one slide – and do so in a way that is compatible with most digital pathology analytical software for comprehensive interpretation, such as high-dimensional and spatial analysis. It also has strong potential and compatibility for clinical translation.” 

Leading the charge
When considering what the future may hold for early adopters of spatial phenotyping with multiplex IF, Yeong believes they have much to look forward to. “Labs will not have to outsource to a third-party lab – just like those who adopted molecular testing and NGS all those years ago. Instead, their in-house researchers will have the knowledge to understand and interpret the data.” On the other hand, he says, “If the lab is a part of an Academic Medical Center or National Cancer Centre, oncologists and surgeons will no longer need to worry about this part of immunopathological monitoring – which, nowadays, is like having an indispensable arm in most large trials and studies.”

Humphries adds, “Laboratories undertaking spatial phenotyping with multiplex IF will quickly realize the huge wealth of information contained within a humble tissue slide. As the possibility for more nuanced data extraction grows, so too will the need for clear, objective analysis goals to have a meaningful impact on patient survival.”

Don’t get left behind 

Labs that do not incorporate spatial phenotyping into their research risk stunting their growth.

Labs that do not incorporate spatial phenotyping into their research risk stunting their growth. “They will continue to deliver the high-quality diagnoses and reporting they are currently capable of – and only that,” says Humphries. Although he understands that caution is to be expected when new technology challenges the status quo, he says, “The laboratories that push the envelope with these new methods will truly reap the benefits, and there will be a point of critical mass when industry, national health agencies, and patient needs will drive adoption. This can already be seen in recent medical history with the introduction of techniques and technologies such as IHC, high-throughput auto-staining platforms, and digital pathology.”

But it’s not all doom and gloom for those not yet making the leap – there are groups dedicated to helping labs adapt. “I am a part of a task force called the JEDI council. Our goal is to make the knowledge of standardization and quality control of staining, imaging, troubleshooting, analysis, interpreting, and reporting more accessible,” highlights Yeong. “And there are more – many other global task forces and committees are already helping in this effort.”

Moreover, labs can start small on their path to spatial phenotyping. “We started tentatively with small panels that we designed to confirm our observations in single-plex analysis – one of these was in an esophageal adenocarcinoma cohort demonstrating a dual-positive phenotype that could have prognostic value,” says Humphries. “But, as our panels have grown, so too has our in-house technical proficiency and our confidence in panel design and application.”

Parting wisdom 
For pathologists and laboratory medicine professionals out there – wherever they may be in their spatial phenotyping journey – Yeong and Humphries have a key message. “We have seen the field of oncology evolve from the ‘H&E-only’ era to IHC, molecular testing, and now cancer immunotherapy – but there is more to come,” says Yeong. “We need collective effort and shared wisdom to use multiplex IHC and IF to move the field forward and overcome cost limitations and slow turnaround times.”

Humphries agrees that now is the time for labs to adopt spatial phenotyping and set an example for others to follow. “Don’t forget to engage in conversations around new technologies as early as possible. Without your expert and uniquely placed opinion, early adoption of new technologies will take far longer,” he says. “As a translational scientist, my goal is to support pathologists and laboratory medicine professionals in the brilliant job they are doing. If new ways of working can augment specialist clinical skills, save time, and improve patient care, I would hope this is a positive pathway that all scientists would want to embrace.”


Joe Poh sheng Yeong is Research Immunopathologist at Singapore General Hospital, Singapore. 

Matt Humphries is Scientific Lead for Tissue Hybridization and Digital Pathology at Queen’s University Belfast, Belfast, Ireland.
 

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