Dataset Information

Mutation of the PTCH1 gene predicts recurrence of breast cancer.

ABSTRACT: Breast cancer is the most common cancer in women, and some patients develop recurrence after standard therapy. Effective predictors are urgently needed to detect recurrence earlier. The activation of Hedgehog signaling in breast cancer is correlated with poor prognosis. PTCH1 is an essential membrane receptor of Hedgehog. However, there are few reports about mutations in Hedgehog genes in breast cancer. We conducted a comprehensive study via an experimental and bioinformatics approach to detect mutated genes in breast cancer. Twenty-two breast cancer patients who developed recurrence within 24 months postoperatively were enrolled with 22 control cancer patients. Targeted deep sequencing was performed to assess the mutations among individuals with breast cancer using a panel of 143 cancer-associated genes. Bioinformatics and public databases were used to predict the protein functions of the mutated genes. Mutations were identified in 44 breast cancer specimens, and the most frequently mutated genes were BRCA2, APC, ATM, BRCA1, NF1, TET2, TSC1, TSC2, NOTCH1, MSH2, PTCH1, TP53, PIK3CA, FBXW7, and RB1. Mutation of these genes was correlated with protein phosphorylation and autophosphorylation, such as peptidyl-tyrosine and protein kinase C phosphorylation. Among these highly mutated genes, mutations of PTCH1 were associated with poor prognosis and increased recurrence of breast cancer, especially mutations in exons 22 and 23. The public sequencing data from the COSMIC database were exploited to predict the functions of the mutations. Our findings suggest that mutation of PTCH1 is correlated with early recurrence of breast cancer patients and will become a powerful predictor for recurrence of breast cancer.

SUBMITTER: Wang CY

PROVIDER: S-EPMC6841698 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mutation of the PTCH1 gene predicts recurrence of breast cancer.

Wang Chih-Yang CY Chang Yung-Chieh YC Kuo Yao-Lung YL Lee Kuo-Ting KT Chen Pai-Sheng PS Cheung Chun Hei Antonio CHA Chang Chih-Peng CP Phan Nam Nhut NN Shen Meng-Ru MR Hsu Hui-Ping HP

Scientific reports 20191108 1

Breast cancer is the most common cancer in women, and some patients develop recurrence after standard therapy. Effective predictors are urgently needed to detect recurrence earlier. The activation of Hedgehog signaling in breast cancer is correlated with poor prognosis. PTCH1 is an essential membrane receptor of Hedgehog. However, there are few reports about mutations in Hedgehog genes in breast cancer. We conducted a comprehensive study via an experimental and bioinformatics approach to detect ...[more]

PMID: 31704974

Similar Datasets

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.

Project description:PurposeT-cell-mediated cytotoxicity is suppressed when programmed cell death-1 (PD-1) is bound by PD-1 ligand-1 (PD-L1) or PD-L2. Although PD-1 inhibitors have been approved for triple-negative breast cancer, the lower response rates of 25%-30% in estrogen receptor-positive (ER+) breast cancer will require markers to identify likely responders. The focus of this study was to evaluate whether PD-L2, which has higher affinity than PD-L1 for PD-1, is a predictor of early recurrence in ER+ breast cancer.MethodsPD-L2 protein levels in cancer cells and stromal cells of therapy-naive, localized or locoregional ER+ breast cancers were measured retrospectively by quantitative immunofluorescence histocytometry and correlated with progression-free survival (PFS) in the main study cohort (n = 684) and in an independent validation cohort (n = 273). All patients subsequently received standard-of-care adjuvant therapy without immune checkpoint inhibitors.ResultsUnivariate analysis of the main cohort revealed that high PD-L2 expression in cancer cells was associated with shorter PFS (hazard ratio [HR], 1.8; 95% CI, 1.3 to 2.6; P = .001), which was validated in an independent cohort (HR, 2.3; 95% CI, 1.1 to 4.8; P = .026) and remained independently predictive after multivariable adjustment for common clinicopathological variables (HR, 2.0; 95% CI, 1.4 to 2.9; P < .001). Subanalysis of the ER+ breast cancer patients treated with adjuvant chemotherapy (n = 197) revealed that high PD-L2 levels in cancer cells associated with short PFS in univariate (HR, 2.5; 95% CI, 1.4 to 4.4; P = .003) and multivariable analyses (HR, 3.4; 95% CI, 1.9 to 6.2; P < .001).ConclusionUp to one third of treatment-naive ER+ breast tumors expressed high PD-L2 levels, which independently predicted poor clinical outcome, with evidence of further elevated risk of progression in patients who received adjuvant chemotherapy. Collectively, these data warrant studies to gain a deeper understanding of PD-L2 in the progression of ER+ breast cancer and may provide rationale for immune checkpoint blockade for this patient group.

Project description:ObjectiveNecroptosis, a type of programmed necrotic cell death, has been implicated in cancer biology and therapeutics. Improved risk stratification is required for prostate carcinoma in individuals. In view of the importance of necroptosis, this work proposed a necroptosis-based genetic model for recurrence prediction, and clarified its characteristics.MethodsA least absolute shrinkage and selection operator (LASSO) regression analysis was conducted based upon transcriptome data of necroptosis genes with clinical information in the Cancer Genome Atlas (TCGA) prostate carcinoma samples, which were externally verified in the GSE116918 cohort. Somatic mutation was characterized by Maftools method. The drug sensitivity was estimated via OncoPredict algorithm. T-cell inflammation score and tumor mutational burden (TMB) score were computed for inferring immunotherapy response. CIBERSORT was adopted for scoring the infiltration of immune cell compositions.ResultsThe necroptosis gene model was defined, composed of BCL2, BCL2L11, BNIP3, CASP8, CYLD, HDAC9, IDH2, IPMK, MYC, PLK1, TNF, TNFRSF1A, and TSC1. Considering external verification, this model effectively predicted recurrence-free survival, notably within one year (area under the curve (AUC) = 0.841, 0.706, 0.776, and 0.893 in the discovery, verification, total and external independent sets, respectively). Patients who had a risk score > median value were defined as high risk, while those who had risk score ≤ median value were defined as low risk. Older age, more advanced T, N, M stage, shorter disease-free survival, and more recurred/progressed statuses were found in high-risk patients (all P<0.05). Moreover, the signature independently predicted patient recurrence (P<0.05). High-risk specimens had more frequent somatic mutation, especially of TP53, BSN, APC, TRANK1, DNAH9, and SALL1 (all P<0.05). The heterogeneity in sensitivity to small-molecule compounds was investigated in low- and high-risk patients. Also, high-risk individuals responded better to immunotherapy (P<0.05).ConclusionAltogether, the necroptosis gene signature may effectively predict prostatic carcinoma recurrence and therapeutic responses, but its clinical feasibility must be verified.

Dataset Information

Mutation of the PTCH1 gene predicts recurrence of breast cancer.

Publications

Mutation of the PTCH1 gene predicts recurrence of breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets