Recurrence-Associated Spatial Niches and Tumor–Stroma Interface Architecture in Colorectal Cancer
Eesha Vanamala
Lay Summary:
Even after successful surgery, up to 3 in 10 colon cancer patients see their cancer come back. I built a framework that automatically discovers recurring patterns of cells within colon tumor tissue and rigorously tests whether any of these neighborhoods are linked to the cancer coming back.
Abstract:
Colorectal cancer (CRC) recurs in up to 30% of Stage II patients despite complete surgical resection. Current staging systems such as TNM classification and Immunoscore rely on biomarker expression or broad T-cell infiltration counts and do not capture the spatial organization of the tumor microenvironment (TME). This analysis used single-cell resolution G4X spatial transcriptomics data from the ColoCare cohort (126 patients, 151 slides, 13.4 million cells) to test whether recurrence is associated with interface-localized stromal–myeloid architecture that spatially excludes cytotoxic and interferon-active immune populations from the tumor margin. Three spatial endpoints were prespecified- myeloid–CD8 T-cell contact, myeloid–plasma-cell contact, and IFN-high plasma-cell localization, all measured within a ±100 µm band around a classifier-derived tumor boundary, each tested against a permutation-centered null and Bonferroni-corrected across the three. None of the three primary endpoints reached significance after Bonferroni correction. Exploratory, non-prespecified analyses, including a niche-discovery approach, generated candidate hypotheses but did not survive correction for multiple comparisons.
Q&A:
Bios: Eesha Vanamala
Program Track: Advanced Research
GitHub Username:
VEesha28 -Eesha Vanamala
What was your favorite seminar? Why?
My favorite seminar was the talk on Bayesian Spatial Transcriptomics because it showed how virtual RNA inference can predict gene expression from H&E slides while separating biological noise from reducible model uncertainty. This approach is really interesting to me because mapping epistemic uncertainty tells researchers exactly which rare tissue morphologies or cell states they need to collect next to improve the model! -Eesha Vanamala
If you were to summarize your summer internship experience in one sentence, what would it be?
I learned so much this summer, from the seminars to my own research project and the helpful advice I was able to receive from my mentors. -Eesha Vanamala