Inflammatory breast cancer (IBC) is an aggressive form of locally advanced breast cancer with high metastatic potential. Most patients have lymph node involvement at the time of diagnosis and 1/3 of the patients have distant metastases. In a previous study, we demonstrated that IBC is a distinct form of breast cancer in comparison with non-IBC. The aim of this study was to investigate the presence of the different molecular subtypes in our data set of 16 IBC and 18 non-IBC specimen. Therefore, we selected an 'intrinsic gene set' of 144 genes, present on our cDNA chips and common to the 'intrinsic gene set' described by Sorlie et al. [PNAS, 2003]. This set of genes was tested for performance in the Norway/Stanford data set by unsupervised hierarchical clustering. Expression centroids were then calculated for the core members of each of the five subclasses in the Norway/Stanford data set and used to classify our own specimens by calculating Spearman correlations between each sample and each centroid. We identified the same cell-of-origin subtypes in IBC as those already described in non-IBC. The classification was in good agreement with immunohistochemical data for estrogen receptor protein expression and cytokeratin 5/6 protein expression. Confirmation was done by an alternative unsupervised hierarchical clustering method. The robustness of this classification was assessed by an unsupervised hierarchical clustering with an alternative gene set of 141 genes related to the cell-of-origin subtypes, selected using a discriminating score and iterative random permutation testing. The contribution of the different cell-of-origin subtypes to the IBC phenotype was investigated by principal component analysis. Generally, the combined ErbB2-overexpressing and basal-like cluster was more expressed in IBC compared to non-IBC, whereas the combined luminal A, luminal B and normal-like cluster was more pronounced in non-IBC compared to IBC. The presence of the same molecular cell-of-origin subtypes in IBC as in non-IBC does not exclude the specific molecular nature of IBC, since gene lists that characterize IBC and non-IBC are entirely different from gene lists that define the different cell-of-origin subtypes, as evidenced by principal component analysis.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s10549-005-9015-9DOI Listing

Publication Analysis

Top Keywords

cell-of-origin subtypes
20
breast cancer
16
data set
12
ibc non-ibc
12
unsupervised hierarchical
12
hierarchical clustering
12
subtypes ibc
12
ibc
10
inflammatory breast
8
presence molecular
8

Similar Publications

The Role of the Tumor Microenvironment in T-Cell Redirecting Therapies of Large B-Cell Lymphoma: Lessons Learned from CAR-T to Bispecific Antibodies.

Cancers (Basel)

January 2025

RM Gorbacheva Research Institute of Pediatric Oncology, Hematology and Transplantation, Pavlov University, 191144 St. Petersburg, Russia.

T-cell redirecting therapies, which include chimeric antigen receptor T-cells (CAR-Ts) and bispecific antibodies (BSAs), have revolutionized the treatment of relapsed\refractory large B-cell lymphoma (LBCL). Expanding clinical experience with these advanced therapies shows the potential for the optimization of their use with combination or consolidation strategies, which necessitates the prognostic stratification of patients. While traditional clinical prognostic factors identified in the era of chemotherapy are characterized by limited value, the tumor microenvironment (TME) is becoming a new prognostic cluster.

View Article and Find Full Text PDF

The cell of origin (COO) classification is an expression-based tumor algorithm identifying molecular subtypes of diffuse large B-cell lymphoma (DLBCL) with distinct prognostic characteristics. Traditional immunohistochemical methods for classifying COO subtypes have poor concordance and limited prognostic value in frontline DLBCL. In contrast, RNA-based metrics like the NanoString Lymphoma Subtyping Test (LST) define more robust subtypes with validated prognostic associations.

View Article and Find Full Text PDF

Cell of origin and expression profiles of pseudomyxoma peritonei derived from the appendix.

Pathol Res Pract

December 2024

Division of Clinical Genome Research, Institute of Medical Science, The University of Tokyo, Tokyo, Japan. Electronic address:

Article Synopsis
  • Pseudomyxoma peritonei (PMP) is a rare condition linked to mucin-producing tumors, usually starting in the appendix, leading to mucin buildup in the abdomen.
  • Researchers conducted RNA-seq analysis on ten PMP cases and their healthy tissue to reveal 32 differently expressed genes, indicating that PMP tumors arise from goblet cells.
  • The study found significant associations between PMP tumors and important biological processes like epithelial-mesenchymal transition, angiogenesis, and inflammation, with further analysis highlighting distinct gene expressions in different PMP types, suggesting more aggressive traits in peritoneal mucinous adenocarcinomas (PMCA).
View Article and Find Full Text PDF

Metabolic Analysis of Tumor Cells Within Ameloblastoma at the Single-Cell Level.

Oral Dis

December 2024

State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China.

Background: To meet their high energy needs, tumor cells undergo aberrant metabolic reprogramming. A tumor cell may expertly modify its metabolic pathways and the differential expression of the genes for metabolic enzymes. The physiological requirements of the host tissue and the tumor cell of origin mostly dictate metabolic adaptation.

View Article and Find Full Text PDF

Extracellular vesicles (EVs) are heterogeneous entities secreted by cells into their microenvironment and systemic circulation. Circulating EVs carry functional small RNAs and other molecular footprints from their cell of origin, and thus have evident applications in liquid biopsy, therapeutics, and intercellular communication. Yet, the complete transcriptomic landscape of EVs is poorly characterized due to critical limitations including variable protocols used for EV-RNA extraction, quality control, cDNA library preparation, sequencing technologies, and bioinformatic analyses.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!