Tumor immune archetypes at single cell resolution
How would you propose to identify immune archetypes in the tumor microenvironment using single cell and spatial omics data, leveraging advances in data science and AI?
Youli Xia
Sr. Scientist
Computational Biology & Data Science
Bino John
Director
Computational Biology & Data Science
Abhi Kashyap
Director
Oncology Research
Call for proposals: All incoming answers accompanied by a collaboration proposal will be evaluated by a scientific jury, and, upon selection, chosen proposals are pursued through a joint collaboration with the successful applicants. Initial funding of up to 250,000 euros will be available for each selected proposal.
More information
Cancers are intricate ecosystems comprising tumor cells and a multitude of non-cancerous cells, embedded in an altered extracellular matrix. The tumor microenvironment (TME) consists of diverse immune cell types, stroma cells, and various tissue-resident cell types. These host cells are now recognized as playing critical roles in the pathogenesis and progression of cancer as well as resistance to standard of care treatments. The cellular composition and functional state of the TME can differ greatly depending on the organ in which the tumor arises, the intrinsic features of cancer cells, the tumor stage, patient characteristics, and treatment regimen. Better understanding of the whole tumor ecosystem is crucial for developing effective oncology drugs.
Immune archetype is an intriguing concept where it aims to define common patterns of the TME across different tumor types1,2. This poses benefit for drug discovery as it enables identification of unique and universal mechanisms across cancer types. For example, in 2022, Combes et al reported in Cell the identification of 12 immune archetypes using tumor bulk-RNA seq data, which can be further aggregated into five major categories: immune dessert, immune rich, immune stroma, T cell centric and myeloid centric3,4. These immune archetypes are tied closely to tumor biology and disease outcome.
With the development of single cell and spatial transcriptomic technology, there have been vast amount of high-resolution omics data published, facilitating more precise characterization of TME components. Various single cell atlases have been published focusing on a certain tumor type, or a certain cell type. Furthermore, the advent in machine learning and AI approaches provides unprecedented opportunities to leverage such data to infer new TME characteristics. However, there have been no studies to our knowledge integrating all the information to interrogate common patterns of tumor TME. Thus, we ask: Can we validate bulk RNA-seq derived immune archetypes in single cell and spatial data? Can we characterize the cellular and molecular mechanisms underlying immune archetypes? Can we discover novel immune archetypes? Can we link immune archetypes to patient response?
The aim of this proposal is to identify and invite research collaborators with shared interests in immune archetypes and expertise in single cell and spatial data analysis to investigate on this exciting topic with a potential to uncover common and unique entry points for the discovery of novel precision-based anti-cancer therapeutics, leveraging our understanding of immune archetypes.
In summary, using existing public (or proprietary) single cell and spatial omics data, leveraging advances in data science and AI, how would you propose to identify and characterize immune archetypes in depth?
- The successful proposal will feature a novel computational method developed to analyze single cell and spatial omics data towards the understanding of immune archetypes, including but not limited to: analysis of previously characterized Combes et al. 12 immune archetypes3 in single cell resolution and/or spatial data to validate/de-validate previous findings, de novo discovery of novel immune archetypes, characterization of cellular and molecular networks underlying each immune archetype.
- A proposal to leverage existing public or proprietary single cell and spatial omics data.
- A proposal seeking to identify and characterize common and/or unique immune archetypes across different solid tumors, including but not limited to, HNSCC, Sq/Non Sq NSCLC, PDAC, CRC, GBM, BrCa, PCa), or provide a deep dive analysis on unique immune archetype dynamic across disease progression and treatment course.
- Significant new data generation (>10% of total funding)
- Analysis of non-solid tumor indications e.g., lymphomas
- Analyzing data in other therapeutic areas
If your project is selected, you will have the opportunity to directly collaborate and publish with the Global Computational Biology and Data Science and Oncology Research teams of Boehringer Ingelheim. Through this, you would benefit from the vast experience of both teams in machine learning and human disease, in particular cancer.
You can expect appropriate funding for the prospective collaboration period. Your exact funding request should be outlined in your proposal. As a framework, we suggest that your initial funding request is structured in milestone and does not exceed 250,000 euros per submitted project in total (including direct, indirect, overhead costs) over a maximum period of 2 years.
Our collaboration agreement will provide full transparency about each partner’s rights & obligations (including intellectual property rights). As part of the agreement, you will be encouraged to publish following the collaboration agreement (to be negotiated in good faith).
We are seeking research collaboration proposals that address our question. Proposals that flag existing data and results regarding to single cell immune archetype analysis would be prioritized (please only share non-confidential information as part of your application). Additional success criteria are:
- Interest in and understanding of immune archetypes.
- Proven track record in the field of expertise, i.e. single cell and spatial omics data analysis.
- Existing access or outlined clear plans to access public or proprietary single cell and spatial omics data is required.
- The proposal should include at minimum a plan to examine the previously characterized Combes et al. 12 immune archetypes in single cell and spatial resolution. Preliminary results are encouraged to be included and proposals with compelling preliminary results will be prioritized.
- Optimally the proposal would include both validation/de-validation of the previously published Combes et al. 12 immune archetypes and novel computational methods for de novo discovery of immune archetypes.
- The proposal will include an analysis plan to characterize the detailed cellular and molecular mechanisms underlying immune archetypes.
- Proposals that include a plan to link immune archetype to disease biology and/or treatment response are strongly encouraged.
- Data analysis can/will be a collaborative effort with Boehringer Ingelheim computational biologists.
- A two-year plan for using opnMe funds to propel the project including proposed aims, budget, timeline estimate and risk mitigation plans. Your exact funding request should be outlined in your proposal based on a well-thought-through project that is structured in milestones and planned with key decision points (clear Go/No-Go criteria). The funding request for the initial milestones resulting in a Go/No-Go decision should not exceed 250,000 euros for a maximum duration of two years per submitted project in total.
- Be able to start immediately (within 3 months) after collaboration commences.
Please use our answer submission template to provide a 2–3 page non-confidential proposal (available for download here).
If confidential data exists that would strengthen the proposal, please indicate that information is available to share under a Confidential Disclosure Agreement (CDA). If we find the non-confidential concept proposal sufficiently interesting, we will execute a CDA for confidential discussions.
We are currently seeking answers for the following scientific question: How would you propose to identify immune archetypes in the tumor microenvironment using single cell and spatial omics data, leveraging advances in data science and AI?
All incoming answers accompanied by a collaboration proposal will be evaluated by a scientific jury, and, upon selection, chosen proposals are pursued through a joint collaboration with the successful applicants. Initial funding of up to 250,000 euros will be available for proposals that will receive support by our review team.
We can only accept research proposals if they arrive no later than February 11, 2025, 11:59 pm PST.
Discovering dominant tumor immune archetypes in a pan-cancer census
Combes A. J., Samad B., Tsui J., Chew N. W., Yan P., Reeder G. C., Kushnoor D., Shen A., Davidson B., Barczak A. J., Adkisson M., Edwards A., Naser M., Barry K. C., Courau T., Hammoudi T., Argüello R. J., Rao A. A., Olshen A. B., Cai C., Zhan J., Davis K. C., Kelley R. K., Chapman J. S., Atreya C. E., Patel A., Daud A. I., Ha P., Diaz A. A., Kratz J. R., Collisson E. A., Fragiadakis G. K., Erle D. J., Boissonnas A., Asthana S., Chan V., Krummel M. F.
Cell. 2022, 185(1):184-203.e19.
