Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is a heterogeneous and dynamic disease in which cells can evade treatment through various mechanisms, including pathway rewiring, altered protein expression, and interactions with the tumor microenvironment.
The more molecular information we can collect, the better researchers can understand these mechanisms, and this is where multiomics is transforming cancer research.
Seeing resistance cell by cell: single‑cell multiomics
One of cancer’s defining features is its heterogeneity. Every cancer contains very diverse cell populations with distinct molecular profiles, functions, and thus responses to treatment. Single-cell analysis allows researchers to study cancer cell by cell, while multiomics provides the high-resolution they need to distinguish one population from another.
Two complementary approaches to single-cell multiomics are advancing the field: deep single‑cell proteomics, metabolomics, and lipidomics by mass spectrometry; and sequencing‑based multiomics that integrate RNA, chromatin, and protein in the same cells.
Deep single‑cell proteomics, metabolomics and lipidomics by mass spectrometry
Single‑cell and low‑input mass spectrometry give information on the functional consequences of drug exposure through proteomics, metabolomics, and lipidomics. And Thermo Fisher Scientific is working to bring these molecular layers on a single platform, as we discussed with Aaron Robitaille, Senior Director, Product & Vertical Marketing of Mass Spectrometry at Thermo Fisher Scientific.
As Robitaille mentioned: “Orbitrap-based platforms like the Orbitrap Tribrid Apex MultiOmics and Orbitrap Astral Zoom mass spectrometers are built to provide deep proteome coverage with post-translational modifications and glycopeptide characterization, metabolomics, and lipidomics.”
This gives researchers a systems-level understanding of drug resistance. “A tumor may not acquire a new mutation, but it may reactivate a pathway downstream, switch receptor signaling, change kinase activity, or alter protein degradation,” explained Robitaille. This makes proteomics and phosphoproteomics key, especially as proteins are where many drug mechanisms actually play out.
How metabolic rewiring drives cancer drug resistance
Metabolomics adds more details to the story. In response to treatment-induced stress, cancer cells can adopt alternative metabolic pathways to overcome it, a phenomenon known as metabolic rewiring.
For instance, in a recent study in lung cancer, tumor cells resistant to EGFR inhibitors showed a noncanonical glucose pathway driven by GLUT6, which produced the by-product methylglyoxal, ultimately activating a stress-response program that makes cells resistant to treatment.
Identifying new targets for endocrine resistance through lipidomics
A similar reasoning applies to drug resistance in luminal breast cancer. A recent study found that resistance is linked to decreased sensitivity to ferroptosis, a type of cell death driven by peroxidation of cell membrane lipids.
By integrating lipidomics with transcriptomics, copy-number alteration data, and proteomics, the authors found that the lipase DDHD2 showed higher expression in resistant cells, depleting polyunsaturated lipids that are needed for lipid peroxidation and ferroptosis and reducing sensitivity to endocrine therapy. This makes DDHD2 a new potential target for developing new drugs that help patients overcome resistance.
Sequencing‑based single‑cell—integrating gene expression, epigenetics, and protein data in the same cell
Compared to mass spectrometry platforms, sequencing-based single-cell multiomics approaches typically measure a smaller panel of proteins but offer the advantage of reading gene expression and protein markers together in the same cell.
This can be achieved with 10x Genomics’ Flex Apex, a platform that’s pushing the field toward higher cell throughput and lower prices. By fixing cells and using DNA‑barcoded antibodies, this platform can capture both surface-level and intracellular proteins coupled with gene expression.
Kristopher Nazor, Vice President of Corporate Strategy at 10x Genomics, stresses: “This matters a great deal in cancer pathways and resistance, making it possible to ask not only whether resistance has appeared, but which nodes in the pathway are driving it in specific clones or immune cell subsets, including key phosphoproteins in pathways like MEK.”
Integrating epigenetics in single-cell analysis reveals resistance biomarkers and guides stratification
Other 10x single‑cell platforms, like Epi Multiome, integrate whole‑transcriptome data with chromatin accessibility. This approach was used to study how patients with aggressive T-cell leukaemia and lymphoma respond to valemetostat in clinical trials. Valemotastat acts at the epigenetic level, blocking the enzymes that silence tumor-suppressor genes through histone modifications.
By integrating ATAC-seq (to see which regions of DNA are open) with RNA-seq, the researchers could follow how some cells switched these genes off again during treatment and find what specific mutations were responsible for this. This translates into a better basis for future stratification and more effective combination strategies.
How single‑cell multiomics is used in oncology today
The previous results are a great example of how single-cell multiomics is already being applied in oncology. As Nazor noted, most current uses are still retrospective, analyzing clinical trial samples where outcomes are known.
“Researchers compare what was happening in patients who responded to a drug versus those who did not to tease apart mechanisms of failure, refine patient stratification in follow‑up trials, or design better drugs.” These assays are not yet used to directly decide treatment options in real time in the clinic, but Nazor sees that as a realistic future goal once the field has generated enough “data and proof of concept to move on safely.”
Understanding the tumor microenvironment
The power of single-cell analysis for understanding drug resistance in cancer is clear, but by disaggregating tissues, they miss one crucial aspect: the tumor microenvironment.
Spatial technologies come to solve this problem, helping understand where resistant cells live in the tumor, what their environment is in terms of vascularization, and whether they interact with immune cells. Ultimately, this leads to understanding resistance-promoting niches and heterogeneous response to treatment.
The next frontier in spatial biology is multiomics
Integrating spatial information with the specificity brought by multiomics is what many researchers are looking for. Dr. Ania Piskorz, Head of Genomics at Cancer Research UK Cambridge Institute and University of Cambridge, is one of them: “Integrating single-cell whole-genome, transcriptomic, epigenomic, proteomic, and metabolomic data within a spatial context is critical to understanding the mechanisms of drug resistance and driving more precise and effective clinical outcomes.”
Dr. Piskorz is one of the first people to have tried the new spatial technology from Illumina, StrataMap. This platform offers whole‑transcriptome maps over large capture areas, which are useful for profiling big tumor sections and their microenvironments.
StrataMap is not multiomic by itself yet, but it integrates with the Illumina Connected Multiomics ecosystem, allowing researchers to combine these RNA maps with genomic, epigenetic, and proteomic datasets. As Dr. Piskorz stresses, these steps are key to working toward an unbiased understanding of cancer biology.
At the same time, 10x Genomics is planning to expand its spatial technology beyond transcriptomics with Atera. This recently announced platform aims to remove the traditional breadth-versus-depth trade-off in spatial biology, as Nazor explained, by combining whole-transcriptome analysis with high spatial resolution. 10x Genomics’ roadmap includes adding proteomics in a future release, advancing its vision for spatial multiomics.
What’s next for spatial and single-cell multi-omics in cancer research
Spatial transcriptomics, not to mention multiomics, is an emerging field. And thus, there is still a need for more datasets that validate and provide clear benchmarks. The challenge is as big as the amount of data these technologies deliver, and new computational methods need to be tailored to their scale.
As Dr. Piskorz mentioned, “Spatial data holds immense potential for discovering tumor resistance mechanisms and identifying novel targets or biomarkers. In clinic applications, it could serve as a discovery platform where findings are later translated into more cost-effective clinical assays, or it could become a foundational clinical assay itself.”
Looking ahead, the real power of multiomics will come from treating single‑cell, spatial, and blood‑based readouts as parts of the same picture. A clear example is 10x, which has announced a collaboration with Cleveland Clinic on advanced bladder cancer, using single‑cell and spatial platforms, including Flex Apex and Xenium, with planned expansion to Atera, to identify biomarkers that predict response and resistance to antibody–drug conjugates (ADCs) and immunotherapy.
About the author: Nuria M. Wentzien got her Ph.D. from the University of Granada in 2023. After finishing her Ph.D., she discovered that science communication brings together her two favorite worlds: science and writing. Her career reflects her passion for learning and exploring new topics, from a Bachelor's degree in Biochemistry (with a strong focus on human sciences) to a Ph.D. in sustainable agriculture. She brings this same curiosity to every project, making readers feel as inspired by science as she does. Now dedicated to helping life-science companies communicate rigorous science in an engaging way, she is the co-founder of Helixa Communications.