Similar Datasets
Project description:The lack of prognostic biomarkers and therapeutic targets in triple-negative breast cancer (TNBC) underscores an urgent need for the identification of novel biomarkers and effective treatment targets. In this study, we collected tumor and adjacent normal samples of four TNBC and four non-TNBC patients for whole-exome sequencing (WES).Comparative WES analysis uncovered the distinct landscape of somatic mutations and driver genes in TNBC.
2025-10-07 | GSE267443 | GEO
Project description:The lack of prognostic biomarkers and therapeutic targets in triple-negative breast cancer (TNBC) underscores an urgent need for the identification of novel biomarkers and effective treatment targets. In this study, we collected tumor and adjacent normal samples of four TNBC and four non-TNBC patients for RNA sequencing.TNBC exhibited distinguished gene expression and splicing patterns in contrast to non-TNBC. Notably, we identified four genes that were exclusively responsive and significantly correlated with prognosis in TNBC, but not non-TNBC. Immunohistochemical analysis confirmed the preferential expression of Chloride Intracellular Channel 3 (CLIC3) in TNBC, proposing CLIC3 as a potential prognostic biomarker for TNBC.
2025-10-07 | GSE267442 | GEO
Project description:Identification of CLIC3 as a novel prognostic biomarker in triple-negative breast cancer via characteristic analysis
| PRJNA1111516 | ENA
Project description:Identification of CLIC3 as a novel prognostic biomarker in triple-negative breast cancer via characteristic analysis (WES)
| PRJNA1111519 | ENA
Project description:Identification of CLIC3 as a novel prognostic biomarker in triple-negative breast cancer via characteristic analysis (RNA-Seq)
| PRJNA1111520 | ENA
Project description:PurposeTriple-negative breast cancer (TNBC) has aggressive characteristics and fewer treatment options than other subtypes. The purpose of this study was to explore prognostic biomarkers for TNBC that can be easily detected from the blood samples.MethodsMDA-MB-231 and MDA-MB-231BR, a brain metastatic variant of the human TNBC cell line MDA-MB-231, were used as less and more aggressive models of TNBC, respectively. The extent to which the candidate gene/protein identified by RNA sequencing correlated well with aggressiveness of TNBC and how much protein was detected from the blood of tumor-bearing mice were evaluated.ResultsBoth the in vitro proliferation and in vivo tumor growth of MDA-MB-231BR were more rapid than those of MDA-MB-231. RNA sequencing identified ESM1 as a gene that was expressed significantly more in MDA-MB-231BR than in MDA-MB-231, and qRT-PCR confirmed a significantly higher expression of ESM1 in MDA-MB-231BR xenograft in vivo. Furthermore, Kaplan-Meier analysis of relapse-free survival demonstrated that TNBC patients with high ESM1 expression had clearly worse relapse-free survival than those with low ESM1 expression, which was consistent with our preclinical findings. Endocan, a protein of ESM1 gene product, was successfully detected in both conditioned medium from MDA-MB-231BR and plasma samples from mice bearing MDA-MB-231BR xenograft, which showed a significantly distinct pattern from less aggressive MDA-MB-231. Moreover, bisulfite sequence analysis revealed that overexpression of ESM1 in MDA-MB-231BR might be attributed to DNA demethylation in an upstream region of the ESM1 gene.ConclusionThis study indicates that endocan could be used as a blood-based prognostic biomarker in TNBC patients.
| S-EPMC5225208 | biostudies-literature
Project description:BackgroundMethylenetetrahydrofolate dehydrogenase 2 (MTHFD2) is a mitochondrial bifunctional enzyme encoded in the nucleus. It plays a significant role in the regulation of glucose, nucleic acid, and folate metabolism, and maintains redox balance in the cells. The present study aimed at elucidating the potential function and mechanisms of MTHFD2 and explored the correlation between ferroptosis and MTHFD2 in triple-negative breast cancer.MethodsMTHFD2 expression, survival analysis, and clinical correlation were performed using data from various online databases including TCGA, GEO, HPA, GTEX, Kaplan-Meier Plotter, PrognoScan, and UALCAN databases. Genomic alterations and CNV analysis were performed using the cBioPortal and GSCA databases. Potential functions and mechanisms were explored by enrichment analysis. The tumor microenvironment was identified by the TIMER database. In vitro, RT-qPCR and western blot assays were utilized to identify the MTHFD2 expression and the knockdown effects in breast cancer. CCK8, cell wound healing, transwell, and flow cytometry assays were used to identify the potential function of MTHFD2 in TNBC cells. MDA, GSH detection, and flow cytometry assays were performed to identify ferroptosis. Western blot assays were performed to measure the protein expression of all target genes.ResultsMTHFD2 expression levels were up-regulated in the majority of cancers and particularly in TNBC, in which higher expression levels indicated a poorer prognosis. Enrichment analyses showed that MTHFD2 is involved in various tumor-related biological processes. MTHFD2 expression was found to strongly correlate with multiple immune cell infiltration. In vitro, the knockdown of MTHFD2 suppresses the proliferation, apoptosis, migration, and invasion in TNBC cells. In addition, the MTHFD2 knockdown significantly enhanced intracellular ROS and lipid peroxidation and decreased intracellular GSH. The expressions of SLC7A11, GPX4, and NRF2 were down-regulated by the MTHFD2 knockdown.ConclusionMTHFD2 could be a crucial molecular biomarker for predicting patient prognosis and a novel therapeutic target in TNBC. In addition, MTHFD2 is a potential ferroptosis regulatory gene in TNBC.
| S-EPMC9885267 | biostudies-literature
Project description:BackgroundThe clinical outcome of triple-negative breast cancer (TNBC) is poor. Finding more targets for the treatment of TNBC is an urgent need. SENPs are SUMO-specific proteins that play an important role in SUMO modification. Among several tumor types, SENPs have been identified as relevant biomarkers for progression and prognosis. The role of SENPs in TNBC is not yet clear.MethodsThe expression and prognosis of SENPs in TNBC were analyzed by TCGA and GEO data. SENP3 coexpression regulatory networks were determined by weighted gene coexpression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and Cox univariate analyses were used to develop a risk signature based on genes associated with SENP3. A time-dependent receiver operating characteristic (ROC) analysis was employed to evaluate a risk signature's predictive accuracy and sensitivity. Moreover, a nomogram was constructed to facilitate clinical application.ResultsThe prognostic and expression effects of SENP family genes were validated using the TCGA and GEO databases. SENP3 was found to be the only gene in the SENP family that was highly expressed and associated with an unfavorable prognosis in TNBC patients. Cell functional experiments showed that knockdown of SENP3 leads to growth, invasion, and migration inhibition of TNBC cells in vitro. By using WGCNA, 273 SENP3-related genes were identified. Finally, 11 SENP3-related genes were obtained from Cox univariate analysis and LASSO regression. Based on this, a prognostic risk prediction model was established. The risk signature of SENP3-related genes was verified as an independent prognostic marker for TNBC patients.ConclusionAmong SENP family genes, we found that SENP3 was overexpressed in TNBC and associated with a worse prognosis. SENP3 knockdown can inhibit tumor proliferation, invasion, and migration. In TNBC patients, a risk signature based on the expression of 11 SENP3-related genes may improve prognosis prediction. The established risk markers may be promising prognostic biomarkers that can guide the individualized treatment of TNBC patients.
| S-EPMC9868814 | biostudies-literature
Project description:Triple-negative breast cancer represents approximately 15–20% of all reported breast cancer cases, and is characterized by a shorter survival time and higher mortality rates compared to other breast cancer sub-types. Tumor microenvironment (TME) refers to the internal and external environment of tumor tissue. Increasing evidence indicates that a tumor’s microenvironment is tightly associated with the immunological surveillance and defense during the development of breast cancer. Although oncology studies employing digital dissection methodologies have provided some insight on the biological features of TME, the development of methods to investigate the cellular composition of the tumor microenvironment remain an important research priority. In this study, we extracted whole transcriptome from 30 Triple-negative breast cancer (TNBC) patients and then used bioinformatics approaches to characterize cell type content in tumor tissue compared with para-cancerous tissue. We identified 4 types of enriched immune cells and 6 types of downregulated immune cells in the tumor tissue samples. After comprehensive bioinformatics analyses, we developed an ‘immune infiltration score’ (IIS) to quantitatively model immune cell infiltration in TNBC. To demonstrate the utility of the IIS, we used 2 independent datasets for validation. We found that patients with a higher IIS showing a longer progression-free survival time and significantly better prognosis than those with a lower IIS value. In sum, we explored the immune infiltration landscape in 30 TNBC patients and provided a novel and reliable biomarker IIS to evaluate the progression-free survival and prognosis in the TNBC patients.
2021-10-18 | E-MTAB-10886 | biostudies-arrayexpress
Project description:Purpose: Oncology studies employing digital dissection methodologies have provided some insight on the biological features of tumor microenvironment of Triple-negative breast cancer (TNBC), but molecular diagnostics rarely have therapeutic impact. We aimed to identify a novel prognostic biomarker to investigate immune characteristics of TNBC using transcriptomic features.Patients and Methods: We extracted whole transcriptome from breast cancer tissue of 30 TNBC patients and then used bioinformatics approaches to characterize the different immune cell contents in tumor tissue and para-cancerous tissue. We extract 2 indicators to describe the major differences in immune infiltration in the microenvironment between tumor tissue and para-cancerous tissue. We then combined the 2 indicators that represent the levels of increased and decreased infiltration in each sample to obtain the Immune Infiltration Score (IIS). Then we compared the tumor-infiltrating immune cell contents and immune infiltrating status in TNBC samples with CIBERSORT and ESTIMATE score to validate the IIS. Finally, 132 TNBC patients from the Cancer Genome Atlas program (TCGA) dataset was used to validate the predictive power of IIS.Results: 4 types of upregulated and 4 types of downregulated immune cells were identified in the tumor tissue samples of the TNBC patients. Then we developed a novel biomarker, IIS. Results showed that IIS score can clearly separate cancer and para-cancerous tissue. Using the same cutoff value of 0 in the TNBC-TCGA cohort, we show that those patients with a higher IIS had significantly higher PD-L1 expression and shorter progression-free survival time than those with a lower IIS value, indicating IIS score can be generalized to other TNBC datasets.Conclusion: we explored the immune infiltration landscape in 30 TNBC patients and provided IIS as a novel and reliable biomarker to evaluate the progression-free survival and prognosis of the TNBC patients.
| S-EPMC9068007 | biostudies-literature