Cells are the building blocks of life. But they don’t just operate in isolation. In our bodies, they’re often connected with each other to form tissues and organs. Healthy cells within these tissues perform many functions to keep the organs working. Others, such as tumour cells, can wreak havoc in various ways by disrupting normal organ functions. Characterizing these cells provides massive potential for understanding how our bodies work and how we can treat diseases when they arise.
Single-cell and spatial ‘omics techniques can isolate and characterize these cells at unprecedented resolution. These datasets can produce beautiful atlases that depict the differences in traits that distinguish each cell type within a tissue sample. However, our previous interview with Catia Moutinho helped me see just how difficult it can be to obtain useful single-cell data, let alone spatial ‘omics data. It was then to my delight that amid our media partnership with SLAS 2025, one of the AveNEW companies specialized in automating spatial ‘omics pipelines.
To explore how automating spatial ‘omics workflows can generate reproducible data, I interviewed Amos Lee, CEO of Meteor Biotech. He was instrumental in developing CosmoSort, the company’s flagship product. With over a decade of experience in spatial ‘omics research, he is set to scale up the production of CosmoSort to move beyond tissue atlasing and into target discovery. With such an approach, Meteor Biotech is set to help researchers pinpoint actionable molecular targets and pathways that can directly inform therapeutic strategies.
Read on to get a taste of what’s to come in spatial ‘omics research with Meteor Biotech!
The Interview
About Spatial Omics
PN: Thanks for joining us today, Amos. SLAS 2025 has a whole track dedicated to spatial ‘omics, but for those who may not know, give us a primer on what spatial ‘omics is.
AL: Spatial omics takes a sample from its native environment, such as the human body, and determines what and where individual cells are located. It’s like preparing a map of the sample down to the subcellular level. The map would tell you what features to watch out for and where the cellular features are located relative to each other. Anything from RNA to proteins can be mapped with spatial ‘omics. However, getting an accurate map from your spatial ‘omics data requires many tools that work together:
- Preserved tissue samples: For us to understand how cells are arranged within tissues and tumours, we need to retain their structure from its origin. From a biopsy, we can freeze a tissue block and section it. We can also fix samples and section them. Regardless of the approach, the preservation method must not lose who the cells were from the sample. This requires significant effort from both physicians and patients, and the various samples collected must be made universally accessible for broader use.
- Capable instrumentation:Â The systems and tools needed to profile cells within a sample are highly sophisticated. Preserving spatial information while acquiring diverse omics data such as DNA, RNA, and proteins is extremely challenging. Moreover, these capabilities must be applicable to a wide range of sample types, including FFPE, FF, and pre-stained samples. CosmoSort is a device that can achieve all of this.
- Freedom in Molecular Analysis: One of the key advantages of modern spatial omics tools, such as CosmoSort, is the ability to isolate cells directly from preserved tissue samples and transfer them into any desired molecular analysis pipeline. This feature provides researchers with unparalleled flexibility in how they process and analyze the isolated molecular information. Whether it’s RNA sequencing, DNA analysis, proteomics, or other multi-omics approaches, this adaptability ensures that the data generated can be tailored to meet the specific needs of the study. This freedom significantly expands the scope of spatial omics research, enabling scientists to explore molecular details with precision and versatility.
- Robust data analysis tools:Â Spatial omics studies inherently encompass spatial information along with various cell types, time-dependent changes, multiple disease groups, and diverse omics data. To understand and interpret these complexities and contribute to new diagnostics, pharmaceuticals, and biotechnology research, an experienced and dedicated bioinformatics team, along with a globally accessible data bank that can be shared among researchers worldwide, is essential.
When scientists can combine these three into a unified, reproducible pipeline, they can generate data that unlocks many possibilities for treating diseases and understanding how our bodies work.
PN: You spend considerable time with heterogenous cell types and how they affect the progression of diseases such as cancer. How does heterogeneity do so, and how can spatial ‘omics illuminate those dynamics?
AL: I’m glad you brought up cancer; it’s one of the best places to discuss the importance of cellular heterogeneity in disease progression. We often think of tumours as a single mass of cancer cells with identical traits. In reality, tumours are composed of many different cell types, each playing unique roles in how the cancer grows, spreads, and responds to treatments. You could encounter cancer stem cells that contribute to growth, immune cells that fight or support the tumour, or stromal cells that shape the tumour environment.
Spatial omics helps us understand this complexity by providing both a map of these different cell types and detailed molecular profiles of each one within their original location in the tumour. I can give you an illustration from our own research here. In our recent studies on triple-negative breast cancer (TNBC), we used spatial omics to identify and analyze cancer stem cell microniches. Microniches are small, specialized regions that harbor cancer stem cells. In these regions, we discovered a unique pattern of RNA editing in the GPX4 gene, specifically an adenosine-to-inosine (A-to-I) editing event. This modification is associated with ferroptosis — a type of cell death that can be harnessed as a potential therapy. Patients with higher A-to-I editing in GPX4 showed a worse prognosis, suggesting that GPX4 could be a valuable therapeutic target.
Spatial omics allows us to look at other types of cancer and connect previously unknown patterns in pathological images to their molecular profiles, opening doors for more targeted and personalized therapies. By mapping these cellular interactions, spatial omics provides insights into how different cell types within a tumour microenvironment contribute to cancer progression and resistance. By understanding these mechanisms more deeply with spatial omics, we can ultimately support the development of novel and more effective anti-cancer therapies.
PN: You’ve made clear here that the amount of data a scientist can get from spatial ‘omics is monumental. In fact, its potential has left spatial ‘omics notorious for having so many companies enter the space. What inspired you to enter it as well?
AL: We’ve known for a long time that cellular context is essential in how cells behave. For example, spatial ‘omics technology can help researchers focus on specific cellular regions that are relevant to disease mechanisms, instead of processing entire tissue samples. The way I see it, we would uncover novel cellular processes, reveal new therapeutic targets, and elucidate mechanisms of action (MOAs) within the complex tapestry of human disease by going beyond creating a human atlas.
However, as I ventured into spatial ‘omics research, I realized that we still had a long way to go in mapping where our cells are located relative to each other. We needed a targeted approach to spatial ‘omics, one that lets us focus on specific cell types at greater detail. That’s what inspired me to found Meteor Biotech. Now, we have a growing team that is committed to making spatial omics not just a mapping tool, but a powerful engine for identifying targets and advancing treatments in both research and clinical settings.
About Spatially-Resolved Laser-Activated Cell Sorting
PN: In your effort to add to the spatial ‘omics track, you developed Spatially-Resolved Laser-Activated Cell Sorting (SLACS). What is SLACS?
AL: SLACS is a tool that lets researchers observe specific cells of interest within a tissue section. It uses a unique laser-based targeting system to target and dislodge cells of interest without disturbing adjacent cells. Those cells are then processed to gain insights into what genes, transcripts, and proteins that the cells express. Our lasers can sort cells at one target per second We achieved such speed by using an algorithm that automatically analyzes the positions of specific cells of interest from stained tissues or cells, a hardware system that sequentially moves to those positions automatically, and Meteor Biotech’s proprietary laser separation technology.
PN: I imagine that sorting through the cells by oneself can be arduous and tedious.
AL: Absolutely. We developed CosmoSort to address those very issues. It uses AI-driven image processing to identify and select specific cells that are most relevant for a given study. End users can identify these regions by various traits, such as biomarker expression or cell appearance, before CosmoSort refines the selection process. This prevents important information about rare cells in bulk samples from being obscured and ensures that only the most relevant cells are isolated. With CosmoSort, researchers can home in on critical cells within their tissue specimens and perform deep molecular analyses.
PN: The ability to isolate single cells of interest this way surely comes with a lot of power for studying cells. Could you give me a few examples of CosmoSort at work?
AL: From a transcriptomics perspective, there are many kinds of RNA that can be expressed from a single gene. We call them RNA isoforms. With CosmoSort, we can count those single genes accurately and perform full-length RNA sequencing on individual cell populations. That means we can tease apart the wealth of traits that cells express instead of obfuscating it by sequencing multiple cell types in a single preparation. Researchers across South Korea and the world have already benefitted from studying cells with CosmoSort in neurodegenerative diseases, proteomes in cancer progression, and single-cell epigenomics.
PN: I’m sure that making sure your data is reproducible is an important step for spatial ‘omics to be useful. And it’s a painstaking process given how much data is involved. How does SLACS and CosmoSort address potential reproducibility issues in spatial ‘omics?
AL: Issues with reproducibility often stem from the time and labour required to perform the menial and monotonous tasks. The task of characterizing the spatial heterogeneity of a tissue often involves analyzing the entire tissue sample. However, this method increases the risk of collecting noisy signals, reducing the resolution for the signals that we’re most interested in.
Both technologies together adopt a selective approach that reduces both by isolating only the cells of interest within a tissue section. Its integration of advanced AI and image processing means that researchers can determine which sets of cells are most relevant for their study’s goals. This controlled and precise targeting enhances the reproducibility and reliability of results, especially when studying complex disease environments.
SLACS and CosmoSort also doesn’t just provide selectivity. SLACS is highly flexible, being compatible with a wide range of single-cell and low-input biochemical assays. Some of these techniques include mass spectrometry, long-read sequencing, and other technologies that are typically done in PCR tubes. This broad compatibility enables researchers to capture a comprehensive molecular profile of targeted cells, from DNA and RNA sequencing to proteomics and metabolomics. With SLACS and CosmoSort, the possibilities extend far beyond conventional sequencing, offering an adaptable platform for integrating multiple high-resolution analyses in a single workflow. Â
The Future of Spatial Omics
PN: We’ve delved deep into spatial omics and how it advances medical research. Where do you see the discipline going in the future? Where does Meteor Biotech fit into that future?
AL: Spatial omics is rapidly advancing beyond simple tissue atlasing to become a powerful tool for identifying actionable therapeutic targets within complex cellular environments. While atlasing provides a valuable map of where different cells are located, the true potential of spatial omics lies in its ability to reveal targetable molecular interactions and mechanisms within specific cellular niches. This approach is particularly relevant for clinical applications, where understanding these interactions can guide the development of new treatments and improve patient outcomes.
At Meteor Biotech, we see spatial omics not just as a tool for mapping cells, but as a means to unlock deeper insights into disease mechanisms, particularly in cancer and immune diseases. By using our SLACS technology to isolate precise regions of interest, we’re able to analyze not only the cells’ positions but also their specific molecular profiles. This data enables researchers to find therapeutic targets directly related to the interactions between cancer cells and their surrounding microenvironment, rather than simply cataloguing cells.
For example, in cancer, spatial omics with SLACS allows us to identify unique features within cancer stem cell niches, which can reveal biomarkers and targets for precision therapies. This target-finding capability positions spatial omics as an essential tool in bridging the gap between research and the clinic, moving beyond basic research to identify actionable insights that directly inform therapeutic strategies.
Meteor Biotech is leading this shift by prioritizing target discovery through spatial context, making our technology highly relevant for both scientific discovery and clinical application. We believe this focus on actionable targets is what will set spatial omics apart and make it indispensable in advancing precision medicine.
PN: To end things off, congratulations on being selected as an Innovation AveNEW company. How will accessing SLAS’s resources through this award help you scale up your company?
AL: Being part of the Innovation AveNEW program is an exciting opportunity for us. SLAS provides a wealth of resources, from industry connections to mentorship, that will help us refine our strategy as we scale. We’re looking forward to accessing SLAS’s network of life sciences and automation experts, which will be invaluable as we continue to improve and expand CosmoSort’s capabilities.
The exposure SLAS offers through this award will also help us connect with potential partners and collaborators. The vast opportunities to connect with others across the life sciences is essential as we work to bring SLACS and CosmoSort to more researchers and institutions around the world. Altogether, we’re grateful for this recognition and look forward to leveraging SLAS’s resources to fuel Meteor Biotech’s growth and impact in the spatial omics space.
