ArticleJournal of experimental & clinical cancer research : CR2018
Classification of triple-negative breast cancers based on Immunogenomic profiling.
Article in Journal of experimental & clinical cancer research : CR, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 412 papers, 2 of them syntheses that pooled it.
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Who cites it
412 citing papers in PubMed, 2 syntheses or guidelines pooled it, 686 citations in OpenAlex.
- The translational chasm in machine learning for triple-negative breast cancer: a quantitative landscape assessment.Frontiers in oncology · 2026Pooled it
- Analyzing the associations between tertiary lymphoid structures and postoperative prognosis, along with immunotherapy response in gastric cancer: findings from pooled cohort studies.Journal of cancer research and clinical oncology · 2024Pooled it
- Transcriptomic and microenvironment characteristics of triple-negative breast cancer under three different neoadjuvant treatment regimens.Breast cancer research and treatment · 2025Trial
- Trial
- Genomic and transcriptomic features of HBV integration in treatment-naïve, HBeAg-positive children with chronic HBV infection.EBioMedicine · 2026Article
- IrMn-Cluster-Based Artificial Metalloenzymes with Radiosensitized Systemic Antitumor Responses to Prevent Malignant Tumor Metastasis and Recurrence.Nano-micro letters · 2026Article
- Multiomics reveals fatty acid metabolism and immune remodeling in retinal artery occlusion.iScience · 2026Article
- Complement system-related gene signatures implicated in the recurrence of glioma.Translational cancer research · 2026Article
- Tumor-infiltrating lymphocytes display prognostic signatures associated with chemotherapy response in TNBC patients.iScience · 2026Article
- Identification and Prognostic Analysis of Immune-Related Genes Co-Regulated by Key Histone Modifications in Breast Cancer.Current issues in molecular biology · 2026Article
- DNA damage response signature-based prognostic genes for intrahepatic cholangiocarcinoma: a combined analysis of machine learning and biological experiments.Cancer cell international · 2026Article
- ZNF831 suppresses triple-negative breast cancer progression through NLRP3-associated pyroptotic signaling and M1-like macrophage phenotypic remodeling.Breast cancer research : BCR · 2026Article
- Spatial remodeling of the tumor immune microenvironment in hepatocellular carcinoma with cirrhosis driven by Treg-CD8⁺T cell crosstalk via the SPP1-ITGA4 axis.Translational oncology · 2026Article
- Cuproptosis as a novel predictor of immunotherapy response and shapes the immune landscape in pan-cancer analysis.Discover oncology · 2026Article
- Loss of GGT6 promotes colorectal cancer progression and correlates with poor prognosis: a study based on multi-database mining and functional validation.Translational cancer research · 2026Article
- Robust transcriptomic hallmarks targeting intratumor heterogeneity in intrahepatic cholangiocarcinoma.Cell reports. Medicine · 2026Article
- Targeted Therapies for Each Subtype of Breast Cancer.MedComm · 2026Review
- Molecular classification and construction of prognostic risk model via machine learning based on metabolic-related genes in hepatocellular carcinoma.Translational cancer research · 2026Article
- Identification and validation of a sphingolipid metabolism-related prognostic signature for predicting prognosis and immune microenvironment-related characteristics in ovarian cancer.Translational cancer research · 2026Article
- Developing a Metabolic-Associated Prognostic Index for Risk Stratification and Therapeutic Guidance in Stage I Lung Adenocarcinoma via Multiomics Analysis.JCO precision oncology · 2026Article
352 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundAbundant evidence shows that triple-negative breast cancer (TNBC) is heterogeneous, and many efforts have been devoted to identifying TNBC subtypes on the basis of genomic profiling. However, few studies have explored the classification of TNBC specifically based on immune signatures that may facilitate the optimal stratification of TNBC patients responsive to immunotherapy.
methodsUsing four publicly available TNBC genomics datasets, we classified TNBC on the basis of the immunogenomic profiling of 29 immune signatures. Unsupervised and supervised machine learning methods were used to perform the classification.
resultsWe identified three TNBC subtypes that we named Immunity High (Immunity_H), Immunity Medium (Immunity_M), and Immunity Low (Immunity_L) and demonstrated that this classification was reliable and predictable by analyzing multiple different datasets. Immunity_H was characterized by greater immune cell infiltration and anti-tumor immune activities, as well as better survival prognosis compared to the other subtypes. Besides the immune signatures, some cancer-associated pathways were hyperactivated in Immunity_H, including apoptosis, calcium signaling, MAPK signaling, PI3K-Akt signaling, and RAS signaling. In contrast, Immunity_L presented depressed immune signatures and increased activation of cell cycle, Hippo signaling, DNA replication, mismatch repair, cell adhesion molecule binding, spliceosome, adherens junction function, pyrimidine metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, and RNA polymerase pathways. Furthermore, we identified a gene co-expression subnetwork centered around five transcription factor (TF) genes (CORO1A, STAT4, BCL11B, ZNF831, and EOMES) specifically significant in the Immunity_H subtype and a subnetwork centered around two TF genes (IRF8 and SPI1) characteristic of the Immunity_L subtype.
conclusionsThe identification of TNBC subtypes based on immune signatures has potential clinical implications for TNBC treatment.
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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.