The CINSARC signature predicts the clinical outcome in patients with Luminal B breast cancer.
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ABSTRACT:
SUBMITTER: Goncalves A
PROVIDER: S-EPMC8099860 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDifferential expression of chemokines/chemokine receptors in colorectal cancer (CRC) may enable molecular characterization of patients' tumors for predicting clinical outcome.ObjectiveTo evaluate the prognostic ability of these molecules in a CRC cohort and the CRC TCGA-dataset.MethodsChemokine (CXCL-12α, CXCL-12β, IL-17A, CXCL-8, GM-CSF) and chemokine receptor (CXCR-4, CXCR-7) transcripts were analyzed by RT-qPCR in 76 CRC specimens (normal: 27, tumor: 49; clinical cohort). RNA-Seq data was analyzed from the TCGA-dataset (n= 375). Transcript levels were correlated with outcome; analyses: univariate, multivariable, Kaplan-Meier.ResultsIn the clinical cohort, chemokine/chemokine receptor levels were elevated 3-10-fold in CRC specimens (P⩽ 0.004) and were higher in patients who developed metastasis (P= 0.03 - < 0.0001). CXCR-4, CXCR-7, CXCL-12α, CXCL-8, IL-17 and GM-CSF levels predicted metastasis (P⩽ 0.0421) and/or overall survival (OS; P⩽ 0.0373). The CXCR-4+CXCR-7+CXCL-12 marker (CXCR-4/7+CXCL-12 (α/b) signature) stratified patients into risk for metastasis (P= 0.0014; OR, 2.72) and OS (P= 0.0442; OR, 2.7); sensitivity: 86.67%, specificity: 97.06%. In the TCGA-dataset, the CXCR-4/7+CXCL-12 signature predicted metastasis (P= 0.011; OR, 2.72) and OS (P= 0.0006; OR: 4.04). In both datasets, the signature was an independent predictor of clinical outcome.ConclusionsResults of 451 specimens from both cohorts reveal that the CXCR-4/7+CXCL-12 signature potentially predicts outcome in CRC patients and may allow earlier intervention.
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Project description:Background: Genetic classification of breast cancer based on the coding mRNA suggests the evolution of distinct subtypes. Whether the non-coding genome is altered concordantly with the coding genome and the mechanism by which the cell cycle directly controls the non-coding genome is poorly understood. Methods: Herein, the miRNA signature maintained by endogenous cyclin D1 in human breast cancer cells was defined. In order to determine the clinical significance of the cyclin D1-mediated miRNA signature, we defined a miRNA expression superset from 459 breast cancer samples. We compared the coding and non-coding genome of breast cancer subtypes. Results: Hierarchical clustering of human breast cancers defined four distinct miRNA clusters (G1-G4) associated with distinguishable relapse-free survival by Kaplan-Meier analysis. The cyclin D1-regulated miRNA signature included several oncomirs, was conserved in multiple breast cancer cell lines, was associated with the G2 tumor miRNA cluster, ER?+ status, better outcome and activation of the Wnt pathway. The coding and non-coding genome were discordant within breast cancer subtypes. Seed elements for cyclin D1-regulated miRNA were identified in 63 genes of the Wnt signaling pathway including DKK. Cyclin D1 restrained DKK1 via the 3'UTR. In vivo studies using inducible transgenics confirmed cyclin D1 induces Wnt-dependent gene expression. Conclusion: The non-coding genome defines breast cancer subtypes that are discordant with their coding genome subtype suggesting distinct evolutionary drivers within the tumors. Cyclin D1 orchestrates expression of a miRNA signature that induces Wnt/?-catenin signaling, therefore cyclin D1 serves both upstream and downstream of Wnt/?-catenin signaling.
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Project description:BackgroundOne of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively.Methods and findingsOur results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER- patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome.ConclusionsThe 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer.
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Project description:The inositol hexakisphosphate kinase (IP6K) 1 and 2 genes are localized at 3p21.31, a highly altered gene-dense chromosomal region in cancer. The IP6Ks convert IP6 to IP7, which inhibits activation of the tumor-promoting PI3K/Akt/mTOR signaling pathway. IP6K2 has been suggested to be involved in p53-induced apoptosis, while IP6K1 may stimulate tumor growth and migration. The present study aimed to elucidate the role of the two IP6Ks in predicting outcome in patients with breast cancer. To the best of our knowledge, the role of IP6K was analyzed for the first time in tumors from three cohorts of patients with breast cancer; one Swedish low-risk cohort, one Dutch cohort and the TCGA dataset. Analyses of gene -and protein expression and subcellular localization were included. IP6K2 gene expression was associated with ER positivity and nuclear p-Akt. Improved prognosis was detected with high IP6K2 gene expression compared with low IP6K2 gene expression in systemically untreated patients in the Swedish low-risk and Dutch cohorts. In the TCGA dataset, IP6K2 prognostic value was significant when selecting for tumors with wild-type TP53. A multivariable analysis testing IP6K2 against other cancer-related genes at 3p.21.31, including IP6K1 and clinical biomarkers, revealed that IP6K2 was associated with decreased risk of distant recurrence. IP6K1 was associated with increased risk of distant recurrence in the multivariable test and protein analysis revealed trends of worse prognosis with high IP6K1 in the cytoplasm. The expression levels of IP6K1 and IP6K2 were associated to a high extent; however, a diverging prognostic value of the two genes was observed in breast cancer. The present data suggest that IP6K2 can be a favorable prognostic factor, while IP6K1 may not be.
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Project description:BackgroundLuminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment.MethodsWe conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H's (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels.ResultsWe found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression.ConclusionsThe GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.
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