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Noah F. Greenwald

@noahgreenwald.bsky.social
156 followers 130 following 15 posts

Current postdoc at UCSF with @willowcoyote.bsky.social‬ studying membrane proteins; PhD at Stanford developing spatial tools to study breast cancer with Mike Angelo & Christina Curtis

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Reposted by Noah F. Greenwald
Erin McCaffrey, PhD @erin-mccaffrey.bsky.social · 24/02/2025
Happy to share a preprint from the Angelo lab many years in the making. Read on for a saga of multiplexed imaging, immunometabolism, and TB granulomas with some fun side quests into the realms of geographical information sciences and transcriptomics… (1/20) doi.org/10.1101/2025...
doi.org
The immunometabolic topography of tuberculosis granulomas governs cellular organization and bacterial control
Despite being heavily infiltrated by immune cells, tuberculosis (TB) granulomas often subvert the host response to Mycobacterium tuberculosis (Mtb) infection and support bacterial persistence. We prev...
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Noah F. Greenwald @noahgreenwald.bsky.social · 07/02/2025
We developed a dedicated pipeline for mibi data: github.com/angelolab/to..., but for other data modalities I’m not as familiar what people generally do. Right now there isn’t a good cross platform solution for data normalization, at least not that we’ve found
github.com
GitHub - angelolab/toffy: Scripts for interacting with and generating data from the commercial MIBIScope
Scripts for interacting with and generating data from the commercial MIBIScope - angelolab/toffy
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Noah F. Greenwald @noahgreenwald.bsky.social · 30/01/2025
Great point. We spent a lot of effort addressing batch effects earlier in our processing pipeline so that SpaceCat wouldn't have to deal with them. In general, I would say the earlier you can address your batch correction issues, the better, but there aren't as many options for spatial data
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Reposted by Noah F. Greenwald
Katie Houlahan @khoulahan.bsky.social · 08/01/2025
The Curtis Lab’s latest study on the genomic architecture of breast cancer from the pre-invasive to metastatic setting is now out in Nature! www.nature.com/articles/s41...
nature.com
Complex rearrangements fuel ER+ and HER2+ breast tumours - Nature
A study identifies three dominant genomic archetypes of breast cancer induced by discrete mutational processes, describing a continuum of genomic profiles and detailing the mechanisms underlying the p...
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
Thanks Kieran!
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
If you run into any problems getting the codebase to work, have questions about what we found, or want to chat, please don’t hesitate to reach out (/end) bsky.app/profile/noah...
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
This wouldn’t have been possible without an amazing team (most of whom have not migrated over to the good place yet!), including Iris, Cami, Seongyeol, Manon, as well as Christina, Marleen and Mike (9/x)
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
This was just a sampling of what we found; for the full details, please check out the paper, as well as our github, where we’ve made all the underlying code open source and available (8/x) github.com/angelolab/Sp...
github.com
GitHub - angelolab/SpaceCat: Generate a spatial catalogue from multiplexed imaging data
Generate a spatial catalogue from multiplexed imaging data - angelolab/SpaceCat
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
Finally, to look at how these features could be combined together, as well as to compare modalities, we built multivariate models to predict outcome from each data type at each timepoint. We found large differences across both assay types and sample timepoints! (7/x)
Evaluation of multivariate models trained on different timepoints (x axis) and data types (colors) to predict patient outcome.
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
When we looked at the specific features we defined, we found some that were temporally dependent, with good predictive power at one timepoint but poor predictive power at another timepoint (6/x)
The same feature (T / Cancer Ratio) has no association with outcome when looking at the primary tumor, but very strong association with outcome when looking at the on treatment (on-nivo) sample
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
We then tested which of the 800+ features from SpaceCat could predict response to immunotherapy, finding numerous strong predictors. Interestingly, features defined in specific regions of the tumor did an especially good job at predicting outcome (5/x)
Volcano plot on the left showing association with outcome for each of the SpaceCat features. Barplot on the right shows the enrichment in top predictive features for those defined within specific regions (compartments) of the tumor
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
To help us make sense of this spatially-resolved data, we built SpaceCat, an algorithm to quantify and summarize the key features from spatial datasets. SpaceCat can be applied to processed imaging data from any multiplexed imaging platform! (4/x)
Summary of the types of features that SpaceCat generates, with representative images from four of the categories
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
We then generated highly multiplexed imaging data using an antibody panel of 37 antibodies. This allowed us to identify 22 cell types across the more than 650 TMA cores we imaged from 117 total patients (3/x)
Heatmap showing the cell types identified in our study. Each row is a cell type, and each column is a different marker on the antibody panel
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
Our awesome collaborators at NKI put together a unique cohort spanning primary disease, pre-treatment metastases, and on-treatment metastases from triple negative breast cancer patients enrolled in the TONIC clinical trial (2/x)
Cartoon overview of the samples collected from patients at each timepoint, as well as the number of different modalities (MIBI, DNA, RNA) collected from each.
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Noah F. Greenwald @noahgreenwald.bsky.social · 29/01/2025
I’m super excited to share what I’ve been working on for the last (many) years: a spatial + genomic + transcriptomic characterization of how the breast cancer microenvironment evolves through immunotherapy! (1/x) 🧪🧬 🖥️ #AcademicSky #MLSky #ImmunoSky www.biorxiv.org/content/10.1...
biorxiv.org
Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition
Immune checkpoint inhibition (ICI) has fundamentally changed cancer treatment. However, only a minority of patients with metastatic triple negative breast cancer (TNBC) benefit from ICI, and the deter...
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Reposted by Noah F. Greenwald
Anshul Kundaje @anshulkundaje.bsky.social · 24/01/2025
I wanted to write briefly about a very pleasant experience we recently had coordinating and collaborating closely on competing publications with 2 other teams. 1/
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Noah F. Greenwald @noahgreenwald.bsky.social · 24/01/2025
Hi Erik, I work on tissue imaging, spatial biology, and cancer research. Could you please add me to the feed? Thanks!https://scholar.google.com/citations?user=ajvnimEAAAAJ&hl=en
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Reposted by Noah F. Greenwald
Arjun Raj @arjunraj.bsky.social · 12/12/2023
Reposting our Penn Postdoctoral Fellowship in Genetics! www.med.upenn.edu/apps/my/bpp_...
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Noah F. Greenwald @noahgreenwald.bsky.social · 01/10/2023
Hi all, I just joined! I’m a PhD student at Stanford studying tumor immunology. Excited to try this thing out #HiSciSky #AcademicSky
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