Matrix-Associated Gene Expression and Annotated Tumor–Stroma Composition of Transcriptomically Defined Cold Regions in Triple-Negative Breast Cancer
- 1Department of Transdisciplinary Science & Technology, Siddha Vetha Multiversity, Newark, NJ 07103, USA
- 2NFInnovations, Renton, WA 170129, USA
- 3Centro de Investigación Biomédica (CENBIO), Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Av. Mariscal Sucre s/n y Mariana de Jesús, Quito 170129, Ecuador
Abstract
Background/Objectives: Regional transcriptomic labels can reflect cell mixtures and expression states. We examined how transcriptomically defined cold regions in triple-negative breast cancer relate to matrix-associated expression, annotated composition, spatial neighborhoods, and cell-type attribution. Methods: We reanalyzed public data from 43 discovery sections (22 patients) and 11 cancer captures of a secondary dataset with discovery-derived labels. Computational spot labels included desert (D), excluded (E), inflamed (I), and ambiguous-cold. Hierarchical models estimated E−D contrasts and E−I gene contrasts with and without sequencing-depth and estimated tumor-abundance adjustment; tests underwent Holm correction. Further analyses addressed annotated composition, neighborhoods, and pooled exploratory cell-type attribution. Results: Estimated cancer-associated fibroblast (CAF) abundance was higher in E- than D-labeled regions (standardized within-section effect 0.78; 95% confidence interval 0.55–1.00), as was expression of PDGFRB, COL3A1, COL5A1, and COL6A1; the three collagen genes remained higher than in D- and I-labeled regions after adjustment. Across 11 captures, the median within-capture difference in tumor-annotated spot fraction (E minus D) was −14.1 percentage points (95% bootstrap interval −33.5 to −10.7; nine negative, two ties; interval reached zero without in situ annotations). In discovery, 330 of 822 ambiguous cold spots neighbored both D- and E-labeled spots, exceeding two null models. Pooled models estimated positive COL3A1 and COL5A1 differences within CAFs; immune readouts depended on scoring and adjustment. Conclusions: We characterized a stromal–transcriptomic contrast: E-labeled regions showed higher matrix-associated expression and estimated CAF abundance than D-labeled regions and, in the secondary dataset, lower annotated tumor fraction. These measurements refine interpretation without implying functional immune exclusion.
Related
- Constitutive Expression of AtVTE2 in Flax Is Associated with Changes in Isoprenoid Metabolism and Stem Cell-Wall Composition
- Overexpression of BnaA08.NDPK Enhances Seed Oil Content and Modulates Fatty Acid Composition in Transgenic Arabidopsis: Insights from Comparative Transcriptomics and Co-Expression Network Analysis
- MYBL1 is a super-enhancer-associated transcription factor that regulates cell proliferation in triple-negative breast cancer
- Deoxythymidylate Kinase (DTYMK)-Driven Pyrimidine Hypermetabolism Is Associated with a Folate-Dependent Macrophage Programme in Triple-Negative Breast Cancer
- Common-Garden Transcriptomes Distinguish Leaf-Form-Associated from Site-Associated Expression in Zygophyllum xanthoxylum
BibTeX
@article{litumagonzalez2026matrixassociated,
title = {{Matrix-Associated Gene Expression and Annotated Tumor–Stroma Composition of Transcriptomically Defined Cold Regions in Triple-Negative Breast Cancer}},
author = {William D. Lituma-Gonzalez and Amogh V. Arunprasad and Hugo Chancay and Varshithaa Jayavelan and Meenakshi Chakravadhanula and Santiago Ballaz and Shanmugamurthy Lakshmanan},
journal = {Cancers},
year = {2026},
month = oct,
doi = {10.3390/cancers18213476},
url = {https://www.mdpi.com/2072-6694/18/21/3476},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Matrix-Associated Gene Expression and Annotated Tumor–Stroma Composition of Transcriptomically Defined Cold Regions in Triple-Negative Breast Cancer
AU - William D. Lituma-Gonzalez
AU - Amogh V. Arunprasad
AU - Hugo Chancay
AU - Varshithaa Jayavelan
AU - Meenakshi Chakravadhanula
AU - Santiago Ballaz
AU - Shanmugamurthy Lakshmanan
PY - 2026
DA - 2026/10/28
JO - Cancers
DO - 10.3390/cancers18213476
UR - https://www.mdpi.com/2072-6694/18/21/3476
AB - Background/Objectives: Regional transcriptomic labels can reflect cell mixtures and expression states. We examined how transcriptomically defined cold regions in triple-negative breast cancer relate to matrix-associated expression, annotated composition, spatial neighborhoods, and cell-type attribution. Methods: We reanalyzed public data from 43 discovery sections (22 patients) and 11 cancer captures of a secondary dataset with discovery-derived labels. Computational spot labels included desert (D), excluded (E), inflamed (I), and ambiguous-cold. Hierarchical models estimated E−D contrasts and E−I gene contrasts with and without sequencing-depth and estimated tumor-abundance adjustment; tests underwent Holm correction. Further analyses addressed annotated composition, neighborhoods, and pooled exploratory cell-type attribution. Results: Estimated cancer-associated fibroblast (CAF) abundance was higher in E- than D-labeled regions (standardized within-section effect 0.78; 95% confidence interval 0.55–1.00), as was expression of PDGFRB, COL3A1, COL5A1, and COL6A1; the three collagen genes remained higher than in D- and I-labeled regions after adjustment. Across 11 captures, the median within-capture difference in tumor-annotated spot fraction (E minus D) was −14.1 percentage points (95% bootstrap interval −33.5 to −10.7; nine negative, two ties; interval reached zero without in situ annotations). In discovery, 330 of 822 ambiguous cold spots neighbored both D- and E-labeled spots, exceeding two null models. Pooled models estimated positive COL3A1 and COL5A1 differences within CAFs; immune readouts depended on scoring and adjustment. Conclusions: We characterized a stromal–transcriptomic contrast: E-labeled regions showed higher matrix-associated expression and estimated CAF abundance than D-labeled regions and, in the secondary dataset, lower annotated tumor fraction. These measurements refine interpretation without implying functional immune exclusion.
SN - 2072-6694
ER -