Novel transcripts associated with lymph node metastasis in triple negative breast cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE61725 | GEO | 2015/12/01
SECONDARY ACCESSION(S): PRJNA261956
REPOSITORIES: GEO
Similar Datasets
Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with the worst prognosis and no targeted treatments. TNBC patients are more likely to develop metastases and relapse than patients with other breast cancer subtypes. We aimed to identify TNBC-specific genes and genes associated with lymph node metastasis, one of the first signs of metastatic spread. A total of 33 TNBCs were used; 17 of which had matched normal adjacent tissues available, and 15 with matched lymph node metastases. Gene expression microarray analysis was used to reveal genes that were differentially expressed between these groups. We identified and validated 66 genes that are significantly altered when comparing tumours to normal adjacent samples. Further, we identified 83 genes that are associated with lymph node metastasis and correlated these with miRNA-expression. Pathway analysis revealed their involvement in DNA repair, recombination and cell death, chromosomal instability and other known cancer-related pathways. Finally, four genes were identified that were specific for TNBC, of which one was associated with overall survival. This study has identified novel genes involved in LN metastases in TNBC and genes that are TNBC specific that may be used as treatment targets or prognostic indicators in the future.
| S-EPMC4633580 | biostudies-literature
Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with the worst prognosis. It is characterised by the absence of hormone receptors for estrogen, progesterone, and human epidermal growth factor 2, and as a consequence there are no targeted endocrine treatments available. TNBC patients are more likely to develop metastases and disease relapse than patients with other breast cancer subtypes. The identification of biomarkers that can be used to predict which patient is likely to develop metastatic disease remains a priority since this is the major cause of cancer-related death in these women.
2015-12-02 | GSE61724 | GEO
Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with the worst prognosis. It is characterised by the absence of hormone receptors for estrogen, progesterone, and human epidermal growth factor 2, and as a consequence there are no targeted endocrine treatments available. TNBC patients are more likely to develop metastases and disease relapse than patients with other breast cancer subtypes. The identification of biomarkers that can be used to predict which patient is likely to develop metastatic disease remains a priority since this is the major cause of cancer-related death in these women.
2015-12-02 | GSE61723 | GEO
Project description:Novel transcripts associated with lymph node metastasis in triple negative breast cancer
| PRJNA261956 | ENA
Project description:Triple negative breast cancer (TNBC) is a highly metastatic and aggressive subtype of breast cancer and cases presenting with lymph node involvement have worse outcomes. This study aimed to determine the regions of copy number variation (CNV) associated with lymph node metastasis in TNBC patients. CNV analyses were performed in a study cohort of 23 invasive ductal carcinomas (IDCs), 12 lymph node metastases (LNmets), and 7 normal adjacent tissues (NATs); as well as in an independent cohort containing 70 TNBC IDCs and the same 7 NATs. CNV-associated genes were analyzed using GO-enrichment and Pathway analysis. The prognostic role for genes showing CNV-based changes in messenger RNA expression was determined using the Kaplan-Meier plotter database. For the IDCs, there were a number of variations that were common in both the study and independent cohorts in the amplified regions of 1q, 8q, 19 (p and q), 2p, 5p and the deleted regions in 8p followed by 5q, and 19p. The most frequently amplified regions in the LNmets of the study cohort were 4q28.3, 2p, 3q24, 1q21.2, 10p, 12p11.1, 8q, 20p11.22-20p11.21, 21q22.13, 6p22.1 and the most frequently deleted regions were in 1p36.23, 4q21.1 and 5q. A total of 686 (441 amplified and 245 deleted) genes were associated with LNmets. The LNmet-associated genes were highly enriched for "regulation of complement activation," "regulation of protein activation cascade," "regulation of humoral immune response," "oxytocin signalling pathway," and "TRAIL binding" pathways. Moreover, 6/686 LNmet-associated genes showed CNV-based changes in their mRNA expression of which, high expression of ASPM and KIF14 was significantly associated with worse relapse-free survival. This study has identified several CNV regions in TNBC that could play a major role in metastasis to the lymph node.
| S-EPMC8259224 | biostudies-literature
Project description:BackgroundThe prognosis of lymph node-negative triple-negative breast cancer (TNBC) is still worse than that of other subtypes despite adjuvant chemotherapy. Reliable prognostic biomarkers are required to identify lymph node-negative TNBC patients at a high risk of distant metastasis and optimize individual treatment.MethodsWe analyzed the RNA sequencing data of primary tumor tissue and the clinicopathological data of 202 lymph node-negative TNBC patients. The cohort was randomly divided into training and validation sets. Least absolute shrinkage and selection operator Cox regression and multivariate Cox regression were used to construct the prognostic model.ResultsA clinical prognostic model, seven-gene signature, and combined model were constructed using the training set and validated using the validation set. The seven-gene signature was established based on the genomic variables associated with distant metastasis after shrinkage correction. The difference in the risk of distant metastasis between the low- and high-risk groups was statistically significant using the seven-gene signature (training set: P < 0.001; validation set: P = 0.039). The combined model showed significance in the training set (P < 0.001) and trended toward significance in the validation set (P = 0.071). The seven-gene signature showed improved prognostic accuracy relative to the clinical signature in the training data (AUC value of 4-year ROC, 0.879 vs. 0.699, P = 0.046). Moreover, the composite clinical and gene signature also showed improved prognostic accuracy relative to the clinical signature (AUC value of 4-year ROC: 0.888 vs. 0.699, P = 0.029; AUC value of 5-year ROC: 0.882 vs. 0.693, P = 0.038). A nomogram model was constructed with the seven-gene signature, patient age, and tumor size.ConclusionsThe proposed signature may improve the risk stratification of lymph node-negative TNBC patients. High-risk lymph node-negative TNBC patients may benefit from treatment escalation.
| S-EPMC8481824 | biostudies-literature
Project description:BackgroundTriple-negative breast cancers (TNBCs) are the most deadly form of breast cancer (BC) subtypes. Axillary lymph node involvement (ALNI) has been described to be prognostic in BC taken as a whole, but its prognostic value in each subtype is unclear. We explored the prognostic impact of ALNI and especially of small size axillary metastases in early TNBCs.MethodsWe analysed in this multicentre study all patients treated for early TNBC in 12 French cancer centres. We explored the correlation between clinicopathological data and ALNI, with a specific focus on the dichotomisation between macrometastases and occult metastases, which is defined as the presence of isolated tumour cells or micrometastases. The prognostic value of ALNI both in terms of disease-free survival (DFS) and overall survival (OS) was also explored.ResultsWe included 1237 TNBC patients. Five-year DFS and OS were 83.7% and 88.5%, respectively. The identified independent prognostic features for DFS were tumour size >20?mm (hazard ratio (HR)=1.86; 95% CI: 1.11-3.10, P=0.018), lymphovascular invasion (HR=1.69; 95% CI: 1.21-2.34, P=0.002) and ALNI both in case of macrometastases (HR=1.97; 95% CI: 1.38-2.81, P<0.0001) and occult metastases (HR=1.72; 95% CI: 1.1-2.71, P=0.019). DFS and OS were similar between tumours with occult metastases and macrometastases. Tumours presenting at least two pejorative features (out of ALNI, lymphovascular invasion and large tumour size) displayed a significantly poorer DFS in both the training set and validation set, independently of chemotherapy administration. Tumours with no more than one of the above-cited pejorative features had a 5-year OS of ?90% vs 70% for other cases (P<0.0001).ConclusionsAxillary lymph node involvement is a key prognostic feature for early TNBC when isolated tumour cells were identified in lymph nodes. This impact is independent of chemotherapy use.
| S-EPMC5117781 | biostudies-literature
Project description:BackgroundLymph node metastasis of triple-negative breast cancer (TNBC) is essential in treatment strategy formulation. This study aimed to build a nomogram that predicts lymph node metastasis in patients with TNBC.Materials and methodsA total of 28,966 TNBC patients diagnosed from 2010 to 2017 in the Surveillance, Epidemiology and End Results (SEER) database were enrolled, and randomized 1:1 into the training and validation sets, respectively. Univariate and multivariate logistic regression analysis were applied to identify the predictive factors, which composed the nomogram. The receiver operating characteristic curves showed the efficacy of the nomogram.ResultMultivariate logistic regression analyses revealed that age, race, tumor size, tumor primary site, and pathological grade were independent predictive factors of lymph node status. Integrating these independent predictive factors, a nomogram was successfully developed for predicting lymph node status, and further validated in the validation set. The areas under the receiver operating characteristic curves of the nomogram in the training and validation sets were 0.684 and 0.689 respectively, showing a satisfactory performance.ConclusionWe constructed a nomogram to predict the lymph node status in TNBC patients. After further validation in additional large cohorts, the nomogram developed here would do better in predicting, providing more information for staging and treatment, and enabling tailored treatment in TNBC patients.
| S-EPMC7747752 | biostudies-literature
Project description:Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype with no targeted treatment available. Our previous study identified 38 TNBC-specific genes with altered expression comparing tumour to normal samples. This study aimed to establish whether DNA methylation contributed to these expression changes in the same cohort as well as disease progression from primary breast tumour to lymph node metastasis associated with changes in the epigenome. We obtained DNA from 23 primary TNBC samples, 12 matched lymph node metastases, and 11 matched normal adjacent tissues and assayed for differential methylation profiles using Illumina HumanMethylation450 BeadChips. The results were validated in an independent cohort of 70 primary TNBC samples. The expression of 16/38 TNBC-specific genes was associated with alteration in DNA methylation. Novel methylation changes between primary tumours and lymph node metastases, as well as those associated with survival were identified. Altered methylation of 18 genes associated with lymph node metastasis were identified and validated. This study reveals the important role DNA methylation plays in altered gene expression of TNBC-specific genes and lymph node metastases. The novel insights into progression of TNBC to secondary disease may provide potential prognostic indicators for this hard-to-treat breast cancer subtype.
| S-EPMC5037364 | biostudies-literature
Project description:BackgroundTo avoid unnecessary postoperative complications, it is essential to select breast cancer patients without axillary lymph node (LN) metastasis who might be eligible for exemption from sentinel lymph node biopsy (SLNB). However, the lymph node metastasis (LNM) of triple-negative breast cancer (TNBC) is difficult to predict if only considering clinical parameters. Hence, by investigating the difference between LN positive and LN negative patients, we aimed to build a multi-omics model able to better predict LNM in TNBC.MethodsA total of 445 TNBC patients with lymph node status and multi-omics data were enrolled and divided into training and validation sets. We analyzed both clinicopathological characteristics and multi-omics data to search for robust biomarkers, which were used to establish a multi-omics model.ResultsCompared with LN negative patients, LN positive patients had an increasing number of mutational events, while the frequencies of both amplification and deletion in somatic copy number alterations (SCNAs) were lower in LN positive cases. After analyzing upregulated gene-related pathways, neutrophil-related pathways were found to be enriched in LN positive patients. Based on these omics analyses, 5 predictors were utilized to build a multi-omics model, and the area under the receiver operating characteristic curve was 0.790 in the training set and 0.807 in the validation set, showing a better performance than models using individual omics data.ConclusionsAfter analyzing the largest TNBC multi-omics cohorts, we identified the potential clinical and molecular characteristics that are related to LNM. A multi-omics model was developed and performed robustly in predicting LNM, with the potential assistance of tailoring unnecessary axillary LN management among TNBC patients.
| S-EPMC9263764 | biostudies-literature