From histology stains to high-plex, whole-slide, single cell spatial imaging — the tools researchers can now use to interrogate tissues have reached new levels of precision and depth of detail. But how close are they to clinical utility? When will pathologists, oncologists and other healthcare professionals be able to harness the technology to directly impact patient lives?
Very soon, Dr. Arutha Kulasinghe (@aruthak), would argue.
Dr. Kulasinghe, leader of the Clinical-oMx Group at the Frazer Institute of the University of Queensland and founding scientific director of the Queensland Spatial Biology Centre, believes imaging data has become just as important in immunotherapy research as the more traditional molecular measurements, especially since tissues, not blood, are where immune cells function.
He shared several examples of functional insights gained into lung, skin, and head & neck cancer using spatial profiling — including a first-of-its-kind 100+plex protein panel — in the recent webinar, “Spatial Phenotyping: A Revolutionary Approach to Biomarker Discovery for Cancer Immunotherapy“.
Being able to bring different datasets together on one slide is a powerful way to integrate and understand the data better, he added. Delving into tumor architecture, cellular neighborhoods and phenotypes alongside metabolic profiles, for example, can be extremely valuable when studying complex cancer biology.
A traditional, two-channel dye histological stain of a head and neck cancer tumor sample, left, and a spatial visualization of the same sample highlighting five marker channels, from the PhenoCyler-Fusion system
Characterizing signs of future success – and failure – in skin cancer treatment
What does a pathological complete response to immunotherapy look like? Dr. Kulasinghe’s team was able to get a better idea by using the PhenoCycler-Fusion and 35 markers to examine 1.4 million cells in a pre-treatment sample from a skin cancer patient who later responded well to immune checkpoint inhibitor treatment.
“This panel starts to define what a pathological complete response looks like, channel by channel, where red is high and blue is low,” Dr. Kulasinghe said. “Theoretically, we can start to identify groups of markers that’ll define PET complete responders. And then can we start to identify minimal signatures that define these patient groups?”
A map of cell subtypes and marker expression (red is high, blue is low) in the tumor microenvironment of a pre-treatment sample of a skin cancer patient who later experienced a complete response to immunotherapy
The ultimate goal would be to gain enough insight to inform companion diagnostics.
“We’re not there yet, but I think in the future, using these multiomic data sets and defining what a PET CR looks like in a progressive phenotype, we can start to think about these really exciting companion diagnostic assays.”
The power of multiomics mapping in head and neck cancer
Genomics has moved well beyond ‘fruit smoothie’ bulk analysis processes with averaged expression counts of dissociated, mashed-up tissues to deep analysis of not only the composition, but also the location of each individual blueberry and strawberry in the mix.
Dr. Kulasinghe said the depth of detail achieved by single-cell analysis, and the level of context enabled by whole-slide scanning has become invaluable to his work.
As an example, he shared the results of 100-plex PhenoCycler-Fusion scans of tumor tissue from a head and neck cancer patient who was a partial responder to immunotherapy treatment, meaning the patient initially responded, but their cancer later progressed.
Their analysis of a variety of biomarkers from the hallmarks of cancer (including immune checkpoints, tumor-promoting inflammatory biomarkers, markers related to angiogenesis, invasion, and metastasis, as well as pathways implicated in the deregulation of cellular energetics, proliferation, and apoptosis) provided a comprehensive account of not only the tumor immune microenvironment, but also the metabolic state and biology of different regions within the tumor.
Their spatial metabolic map identified and profiled four distinct regions, including the likely ‘leading edge’ of the tumor – the metabolically active area that would ultimately kill the patient. The other three regions, in contrast, showed increased expression of pro-apoptotic pathways, with dead or necrotic tissue.
By creating a spatial metabolic map of a head and neck cancer sample, researchers were able to identify which regions were most likely to contribute to patient mortality
“This dichotomy of immune activation-induced death and tumor progression in the same sample demonstrates the heterogenous niches and competing microenvironments that underpin clinical responses of therapeutic resistance,” the researchers noted in their GEN Biotechnology paper, “Mapping the Spatial Proteome of Head and Neck Tumors: Key Immune Mediators and Metabolic Determinants in the Tumor Microenvironment“.
The researchers added another layer to their analysis: RNA content within the tumor. They examined 74 markers across lineage metabolic markers, stress and chemokines. Integrating spatial proteomics data, spatial transcriptomics data and neighborhood analyses, the team started to build an “omic cloud.”
“You really need to see the whole tissue to be able to understand the underlying biology that dictates response and resistance to therapy. We need to do these higher plex ‘omic assays to really figure out what is the underlying signal,” Dr. Kulasinghe said.
Magnifying what you cannot see with just H&E
There’s plenty of information that pathologists cannot see based on histology stains alone, and Dr. Kulasinghe hopes spatial multiomics will fill the gap.
“The data that we have obtained via antibody-based spatial phenotyping to detect protein expression and localization show a far greater depth of information than what is available via H&E staining, and they enable the exciting possibility of generating a holistic view of the tumor microenvironment and key cancer hallmarks in situ at single-cell resolution,” he wrote.
He sees future applications of high-plex discovery-based research tools to identify biomarkers of clinical significance. By screening large cohorts of patients with pathological complete responses and progressive disease, researchers could determine spatial signatures associated with therapy response and resistance, and possibly develop screening tools and/or companion diagnostic assays for predicting response to immunotherapies.
Imputing spatial multiomic information to H&E’s that is interpretable by pathologists could make the knowledge more accessible and actionable, “democratizing spatial” for the field, Dr. Kulasinghe said.
“It’s great to have these amazing images and these incredible data sets, but I think ultimately these assays need to move forward to the clinic,” Dr. Kulasinghe said. “Hopefully this moves the needle forward for precision medicine and we can start to use these really exciting data sets to individualize therapies for individual patients.”
For more information about Dr. Kulasinghe’s work and findings on cancer immunotherapy:
- Watch the on demand webinar, “Spatial Phenotyping: A Revolutionary Approach to Biomarker Discovery for Cancer Immunotherapy“.
- View the publication, “Mapping the Spatial Proteome of Head and Neck Tumors: Key Immune Mediators and Metabolic Determinants in the Tumor Microenvironment”.
- Read about the newly launched Queensland Spatial Biology Centre (QSBC) at the Wesley Research Institute in Brisbane Australia
