ArticleCancer biomarkers : section A of Disease markers2022
Machine learning analyses of highly-multiplexed immunofluorescence identifies distinct tumor and stromal cell populations in primary pancreatic tumors.
Article in Cancer biomarkers : section A of Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 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
8 citing papers in PubMed, 11 citations in OpenAlex.
- Intratumoral Three-Cell-Type Clusters Are a Conserved Feature of Endogenous Antitumor Immunity.Cancer immunology research · 2026Article
- Insights into artificial intelligence-based digital pathology in hepatobiliary and pancreatic cancer.Frontiers in oncology · 2026Review
- Spatial expression of fibroblast activation protein-α in clear cell renal cell carcinomas revealed by multiplex immunoprofiling analysis of the tumor microenvironment.Cancer immunology, immunotherapy : CII · 2025Article
- Characterization of Immune Infiltrate Along the Leading Edge of Differentiated Thyroid Cancer.Thyroid : official journal of the American Thyroid Association · 2024Article
- Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.The Journal of pathology · 2024Review
- An intravenous pancreatic cancer therapeutic: Characterization of CRISPR/Cas9n-modified Clostridium novyi-Non Toxic.PloS one · 2023Article
- Artificial intelligence in pancreatic cancer.Theranostics · 2022Review
- Using Single Cell Transcriptomics to Elucidate the Myeloid Compartment in Pancreatic Cancer.Frontiers in oncology · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPancreatic ductal adenocarcinoma (PDAC) is a formidable challenge for patients and clinicians.
objectiveTo analyze the distribution of 31 different markers in tumor and stromal portions of the tumor microenvironment (TME) and identify immune cell populations to better understand how neoplastic, non-malignant structural, and immune cells, diversify the TME and influence PDAC progression.
methodsWhole slide imaging (WSI) and cyclic multiplexed-immunofluorescence (MxIF) was used to collect 31 different markers over the course of nine distinctive imaging series of human PDAC samples. Image registration and machine learning algorithms were developed to largely automate an imaging analysis pipeline identifying distinct cell types in the TME.
resultsA random forest algorithm accurately predicted tumor and stromal-rich areas with 87% accuracy using 31 markers and 77% accuracy using only five markers. Top tumor-predictive markers guided downstream analyses to identify immune populations effectively invading into the tumor, including dendritic cells, CD4+ T cells, and multiple immunoregulatory subtypes.
conclusionsImmunoprofiling of PDAC to identify differential distribution of immune cells in the TME is critical for understanding disease progression, response and/or resistance to treatment, and the development of new treatment strategies.
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.