Dual targeting of ErbB-2/ErbB-3 results in enhanced antitumor activity in preclinical models of pancreatic cancer

Ghasemi, Reza; Rapposelli, Ilario Giovanni; Capone, Emily; Rossi, Cosmo; Lattanzio, Rossano; Piantelli, Mauro; Sala, Gianluca; Iacobelli, Stéfano

doi:10.1038/oncsis.2014.31

Cited by 15 publications

(10 citation statements)

References 27 publications

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“…This pathway included lots of pathways which were related to cancers such as Wnt signaling pathway, mapk signaling pathway, vega signaling pathway and so on[ 52 , 53 ]. Besides, our biomarkers also were annotated in many other cancer-related pathways, for example, “ErbB signaling pathway”, “Chemokine signaling pathway”, “Natural killer cell mediated cytotoxicity” and “Focal adhesion” [ 54 – 56 ]. The result of annotation indicated that the potential biomarkers participated in many progresses of cancers, and acted as an important role in cancers.…”

Section: Resultsmentioning

confidence: 99%

The Identification of Specific Methylation Patterns across Different Cancers

Zhang

Zhao

et al. 2015

PLoS ONE

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Abnormal DNA methylation is known as playing an important role in the tumorgenesis. It is helpful for distinguishing the specificity of diagnosis and therapeutic targets for cancers based on characteristics of DNA methylation patterns across cancers. High throughput DNA methylation analysis provides the possibility to comprehensively filter the epigenetics diversity across various cancers. We integrated whole-genome methylation data detected in 798 samples from seven cancers. The hierarchical clustering revealed the existence of cancer-specific methylation pattern. Then we identified 331 differentially methylated genes across these cancers, most of which (266) were specifically differential methylation in unique cancer. A DNA methylation correlation network (DMCN) was built based on the methylation correlation between these genes. It was shown the hubs in the DMCN were inclined to cancer-specific genes in seven cancers. Further survival analysis using the part of genes in the DMCN revealed high-risk group and low-risk group were distinguished by seven biomarkers (PCDHB15, WBSCR17, IGF1, GYPC, CYGB, ACTG2, and PRRT1) in breast cancer and eight biomarkers (ZBTB32, OR51B4, CCL8, TMEFF2, SALL3, GPSM1, MAGEA8, and SALL1) in colon cancer, respectively. At last, a protein-protein interaction network was introduced to verify the biological function of differentially methylated genes. It was shown that MAP3K14, PTN, ACVR1 and HCK sharing different DNA methylation and gene expression across cancers were relatively high degree distribution in PPI network. The study suggested that not only the identified cancer-specific genes provided reference for individual treatment but also the relationship across cancers could be explained by differential DNA methylation.

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Section: Resultsmentioning

confidence: 99%

The Identification of Specific Methylation Patterns across Different Cancers

Zhang

Zhao

et al. 2015

PLoS ONE

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“…ErbB-1 (also known as EGFR, epidermal growth factor receptor) and ErbB-2 (also known as HER2, human epidermal growth factor receptor 2), are famous therapeutic targets for cancer treatment and their excessive signaling play critical roles in the development and malignancy of many tumors. For example, in preclinical models of pancreatic cancer, targeting of ErbB results in enhanced antitumor activity [40]. In addition, HIF-1 signaling pathway plays an integral role in the body’s response to low oxygen concentrations, and involves in tumor proliferation due to its role in hypoxia [41].…”

Section: Discussionmentioning

confidence: 99%

Differentially Expressed microRNAs in MIA PaCa-2 and PANC-1 Pancreas Ductal Adenocarcinoma Cell Lines are Involved in Cancer Stem Cell Regulation

Zheng

et al. 2019

IJMS

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Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, and thus better understanding of its molecular pathology is crucial for us to devise more effective treatment of this deadly disease. As cancer cell line remains a convenient starting point for discovery and proof-of-concept studies, here we report the miRNA expression characteristics of two cell lines, MIA PaCa-2 and PANC-1, and discovered three miRNAs (miR-7-5p, let-7d, and miR-135b-5p) that are involved in cancer stem cells (CSCs) suppression. After transfection of each miRNA’s mimic into PANC-1 cells which exhibits higher stemness feature than MIA-PaCa-2 cells, partial reduction of CSC surface markers and inhibition of tumor sphere formation were observed. These results enlighten us to consider miRNAs as potential therapeutic agents for pancreatic cancer patients via specific and effective inhibition of CSCs.

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“… 67 , 68 A similar function of ErbB signaling was reported in previous studies, and targeting the regulation of the ErbB pathway by sex-determining region Y-related high mobility group box 9 was involved in pancreatic tumorigenesis; dual targeting of ErbB-2 and ErbB-3 increases the therapeutic efficacy of trastuzumab. 69 , 70 Similar anti-tumor drugs in PC target the JAK-STAT pathway and may have a potential application in chemotherapy and immunotherapy. 71 , 72 Therefore, we can hypothesize that these prognostic miRNAs are involved in biological processes and signaling pathways by regulating their target genes and affecting PC tumorigenesis and treatment.…”

Section: Discussionmentioning

confidence: 99%

Genome-scale analysis to identify prognostic microRNA biomarkers in patients with early stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy

Liao¹,

Wang²,

Huang³

et al. 2018

CMAR

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BackgroundThe aim of the study was to investigate potential prognostic microRNA (miRNA) biomarkers for patients with early stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy using a miRNA-sequencing (miRNA-seq) data set from The Cancer Genome Atlas (TCGA). A miRNA expression-based prognostic signature was generated, and the potential role of target genes in overall survival (OS) in patients with PDAC was examined.MethodsA miRNA-seq data set of 112 PDAC patients who underwent pancreaticoduodenectomy was obtained from TCGA. Survival analysis was performed to identify potential prognostic biomarkers.ResultsEleven miRNAs (hsa-mir-501, hsa-mir-4521, hsa-mir-5091, hsa-mir-24-1, hsa-mir-126, hsa-mir-30e, hsa-mir-3157, hsa-let-7a-3, hsa-mir-133a-1, hsa-mir-4709, and hsa-mir-421) were used to construct a prognostic signature using the step function. The 11-miRNA prognostic signature showed good performance for prognosis prediction (adjusted P<0.0001, adjusted hazard ratio =4.285, 95% confidence interval =2.146–8.554), and the time-dependent receiver operating characteristic analysis showed an area under the curve of 0.864, 0.877, and 0.787 for 1-, 2-, and 3-year PDAC OS predictions, respectively. Comprehensive survival analysis suggested that the prognostic signature could serve as an independent prognostic factor for PDAC OS and performs better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of the miRNAs indicated that they were significantly enriched in multiple biological processes and pathways, including cell proliferation, cell cycle biological processes, the forkhead box O, mitogen-activated protein kinase, Janus kinase/signal transducers and activators of transcription signaling pathways, pathways in cancer, and the ErbB signaling pathway. Several target genes of these miRNAs were also associated with PDAC OS.ConclusionThe present study identified a novel miRNA expression signature that showed potential as a prognostic biomarker for PDAC after pancreaticoduodenectomy.

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Dual targeting of ErbB-2/ErbB-3 results in enhanced antitumor activity in preclinical models of pancreatic cancer

Cited by 15 publications

References 27 publications

The Identification of Specific Methylation Patterns across Different Cancers

The Identification of Specific Methylation Patterns across Different Cancers

Differentially Expressed microRNAs in MIA PaCa-2 and PANC-1 Pancreas Ductal Adenocarcinoma Cell Lines are Involved in Cancer Stem Cell Regulation

Genome-scale analysis to identify prognostic microRNA biomarkers in patients with early stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy

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