» Articles » PMID: 31526717

Generation of in Situ Sequencing Based OncoMaps to Spatially Resolve Gene Expression Profiles of Diagnostic and Prognostic Markers in Breast Cancer

Overview
Journal EBioMedicine
Date 2019 Sep 19
PMID 31526717
Citations 18
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Gene expression analysis of breast cancer largely relies on homogenized tissue samples. Due to the high degree of cellular and molecular heterogeneity of tumor tissues, bulk tissue-based analytical approaches can only provide very limited system-level information about different signaling mechanisms and cellular interactions within the complex tissue context.

Methods: We describe an analytical approach using in situ sequencing (ISS), enabling highly multiplexed, spatially and morphologically resolved gene expression profiling. Ninety-one genes including prognostic and predictive marker profiles, as well as genes involved in specific cellular pathways were mapped within whole breast cancer tissue sections, covering luminal A/B-like, HER2-positive and triple negative tumors. Finally, all these features were combined and assembled into a molecular-morphological OncoMap for each tumor tissue.

Findings: Our in situ approach spatially revealed intratumoral heterogeneity with regard to tumor subtype as well as to the OncotypeDX recurrence score and even uncovered areas of minor cellular subpopulations. Since ISS-resolved molecular profiles are linked to their histological context, a deeper analysis of the core and periphery of tumor foci enabled identification of specific gene expression patterns associated with these morphologically relevant regions.

Interpretation: ISS generated OncoMaps represent useful tools to extend our general understanding of the biological processes behind tumor progression and can further support the identification of novel therapeutical targets as well as refine tumor diagnostics. FUND: Swedish Cancerfonden, UCAN, Vetenskapsrådet, Cancer Genomics Netherlands, Iris, Stig och Gerry Castenbäcks Stiftelse, BRECT, PCM Program, King Gustaf V Jubilee Fund, BRO, KI and Stockholm County Council, Alice Wallenberg Foundation.

Citing Articles

Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy.

An J, Lu Y, Chen Y, Chen Y, Zhou Z, Chen J Front Immunol. 2025; 15:1499301.

PMID: 39749323 PMC: 11693744. DOI: 10.3389/fimmu.2024.1499301.


Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review).

Ren L, Huang D, Liu H, Ning L, Cai P, Yu X Oncol Lett. 2024; 27(4):152.

PMID: 38406595 PMC: 10885005. DOI: 10.3892/ol.2024.14285.


Mapping cancer biology in space: applications and perspectives on spatial omics for oncology.

Lee S, Kim G, Lee J, Lee A, Kwon S Mol Cancer. 2024; 23(1):26.

PMID: 38291400 PMC: 10826015. DOI: 10.1186/s12943-024-01941-z.


Novel insights from spatial transcriptome analysis in solid tumors.

Du J, An Z, Huang Z, Yang Y, Zhang M, Fu X Int J Biol Sci. 2023; 19(15):4778-4792.

PMID: 37781515 PMC: 10539699. DOI: 10.7150/ijbs.83098.


A unified pipeline for FISH spatial transcriptomics.

Cisar C, Keener N, Ruffalo M, Paten B Cell Genom. 2023; 3(9):100384.

PMID: 37719153 PMC: 10504669. DOI: 10.1016/j.xgen.2023.100384.


References
1.
Leung S, Nielsen T, Zabaglo L, Arun I, Badve S, Bane A . Analytical validation of a standardized scoring protocol for Ki67: phase 3 of an international multicenter collaboration. NPJ Breast Cancer. 2017; 2:16014. PMC: 5515324. DOI: 10.1038/npjbcancer.2016.14. View

2.
Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M . A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004; 351(27):2817-26. DOI: 10.1056/NEJMoa041588. View

3.
McGranahan N, Swanton C . Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future. Cell. 2017; 168(4):613-628. DOI: 10.1016/j.cell.2017.01.018. View

4.
Yates L, Desmedt C . Translational Genomics: Practical Applications of the Genomic Revolution in Breast Cancer. Clin Cancer Res. 2017; 23(11):2630-2639. DOI: 10.1158/1078-0432.CCR-16-2548. View

5.
Demeulemeester J, Kumar P, Moller E, Nord S, Wedge D, Peterson A . Tracing the origin of disseminated tumor cells in breast cancer using single-cell sequencing. Genome Biol. 2016; 17(1):250. PMC: 5146893. DOI: 10.1186/s13059-016-1109-7. View