ArticleClinical cancer research : an official journal of the American Association for Cancer Research2022
Data-Rich Spatial Profiling of Cancer Tissue: Astronomy Informs Pathology.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Multimodal spatial omics: From data acquisition to computational integration.Patterns (New York, N.Y.) · 2026Review
- Novel Predictive Spatial Biomarker in Non-Small Cell Lung Carcinoma: The Diversity of Niches Unlocking Treatment Sensitivity (DONUTS).bioRxiv : the preprint server for biology · 2025Article
- Spatial omics technology potentially promotes the progress of tumor immunotherapy.British journal of cancer · 2025Review
- Rapidly Evolving Pre- and Post-surgical Systemic Treatment of Melanoma.American journal of clinical dermatology · 2024Review
- Weakly supervised deep learning to predict recurrence in low-grade endometrial cancer from multiplexed immunofluorescence images.NPJ digital medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Astronomy was among the first disciplines to embrace Big Data and use it to characterize spatial relationships between stars and galaxies. Today, medicine, in particular pathology, has similar needs with regard to characterizing the spatial relationships between cells, with an emphasis on understanding the organization of the tumor microenvironment. In this article, we chronicle the emergence of data-intensive science through the development of the Sloan Digital Sky Survey and describe how analysis patterns and approaches similarly apply to multiplex immunofluorescence (mIF) pathology image exploration. The lessons learned from astronomy are detailed, and the new AstroPath platform that capitalizes on these learnings is described. AstroPath is being used to generate and display tumor-immune maps that can be used for mIF immuno-oncology biomarker development. The development of AstroPath as an open resource for visualizing and analyzing large-scale spatially resolved mIF datasets is underway, akin to how publicly available maps of the sky have been used by astronomers and citizen scientists alike. Associated technical, academic, and funding considerations, as well as extended future development for inclusion of spatial transcriptomics and application of artificial intelligence, are also addressed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.