scholarly journals MR Imaging Distinguishes Tumor Hypoxia Levels of Different Prognostic and Biological Significance in Cervical Cancer

2020 ◽  
Author(s):  
Tiril Hillestad ◽  
Tord Hompland ◽  
Christina S. Fjeldbo ◽  
Vilde E. Skingen ◽  
Unn Beate Salberg ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Epithelial To Mesenchymal Transition ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Tumor Hypoxia ◽  
Biological Significance ◽  
Gene Expression Profiles ◽  
Interferon Response ◽  
Moderate Hypoxia ◽  
Mesenchymal Transition

AbstractTumor hypoxia levels range from mild to severe and have different biological and therapeutical consequences, but are not easily assessable in patients. We present a method based on diagnostic dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) that visualizes a continuous range of hypoxia levels in tumors of cervical cancer patients. Hypoxia images were generated using an established approach based on pixel-wise combination of the DCE-MRI parameters νe and Ktrans, reflecting oxygen consumption and supply, respectively. An algorithm to retrieve hypoxia levels from the images was developed and validated in 28 xenograft tumors, by comparing the MRI-defined levels with hypoxia levels derived from pimonidazole stained histological sections. We further established an indicator of hypoxia levels in patient tumors based on expression of nine hypoxia responsive genes. A strong correlation was found between these indicator values and the MRI-defined hypoxia levels in 63 patients. Chemoradiotherapy outcome of 74 patients was most strongly predicted by moderate hypoxia levels, whereas more severe or milder levels were less predictive. By combining gene expression profiles and MRI-defined hypoxia levels in cancer hallmark analysis, we identified a distribution of levels associated with each hallmark; oxidative phosphorylation and G2/M checkpoint were associated with moderate hypoxia, and epithelial-to-mesenchymal transition and inflammatory responses with significantly more severe levels. At the mildest levels, interferon response hallmarks, together with stabilization of HIF1A protein by immunohistochemistry, appearred significant. Thus, our method visualizes the distribution of hypoxia levels within patient tumors and has potential to distinguish levels of different prognostic and biological significance.

scholarly journals Stromal-derived interleukin 6 drives epithelial-to-mesenchymal transition and therapy resistance in esophageal adenocarcinoma

2019 ◽  
Vol 116 (6) ◽  
pp. 2237-2242 ◽  
Author(s):  
Eva A. Ebbing ◽  
Amber P. van der Zalm ◽  
Anne Steins ◽  
Aafke Creemers ◽  
Simone Hermsen ◽  
...  
Keyword(s):  
Esophageal Adenocarcinoma ◽  
Epithelial To Mesenchymal Transition ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Treatment Resistance ◽  
Serum Levels ◽  
Therapy Resistance ◽  
Mesenchymal Transition ◽  
Dismal Prognosis ◽  
Organoid Cultures

Esophageal adenocarcinoma (EAC) has a dismal prognosis, and survival benefits of recent multimodality treatments remain small. Cancer-associated fibroblasts (CAFs) are known to contribute to poor outcome by conferring therapy resistance to various cancer types, but this has not been explored in EAC. Importantly, a targeted strategy to circumvent CAF-induced resistance has yet to be identified. By using EAC patient-derived CAFs, organoid cultures, and xenograft models we identified IL-6 as the stromal driver of therapy resistance in EAC. IL-6 activated epithelial-to-mesenchymal transition in cancer cells, which was accompanied by enhanced treatment resistance, migratory capacity, and clonogenicity. Inhibition of IL-6 restored drug sensitivity in patient-derived organoid cultures and cell lines. Analysis of patient gene expression profiles identified ADAM12 as a noninflammation-related serum-borne marker for IL-6–producing CAFs, and serum levels of this marker predicted unfavorable responses to neoadjuvant chemoradiation in EAC patients. These results demonstrate a stromal contribution to therapy resistance in EAC. This signaling can be targeted to resensitize EAC to therapy, and its activity can be measured using serum-borne markers.

scholarly journals Cancer-Associated Fibroblasts Modulate Transcriptional Signatures Involved in Proliferation, Differentiation and Metastasis in Head and Neck Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3361
Author(s):  
Emilia Wiechec ◽  
Mustafa Magan ◽  
Natasa Matic ◽  
Anna Ansell-Schultz ◽  
Matti Kankainen ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Tumor Cells ◽  
Epithelial To Mesenchymal Transition ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
In Vitro Models ◽  
Cancer Associated Fibroblasts ◽  
Mesenchymal Transition ◽  
2D And 3D

Cancer-associated fibroblasts (CAFs) are known to increase tumor growth and to stimulate invasion and metastasis. Increasing evidence suggests that CAFs mediate response to various treatments. HNSCC cell lines were co-cultured with their patient-matched CAFs in 2D and 3D in vitro models, and the tumor cell gene expression profiles were investigated by cDNA microarray and qRT-PCR. The mRNA expression of eight candidate genes was examined in tumor biopsies from 32 HNSCC patients and in five biopsies from normal oral tissue. Differences in overall survival (OS) were tested with Kaplan–Meier long-rank analysis. Thirteen protein coding genes were found to be differentially expressed in tumor cells co-cultured with CAFs in 2D and 81 in 3D when compared to tumor cells cultured without CAFs. Six of these genes were upregulated both in 2D and 3D (POSTN, GREM1, BGN, COL1A2, COL6A3, and COL1A1). Moreover, two genes upregulated in 3D, MMP9 and FMOD, were significantly associated with the OS. In conclusion, we demonstrated in vitro that CAF-derived signals alter the tumor cell expression of multiple genes, several of which are associated with differentiation, epithelial-to-mesenchymal transition (EMT) phenotype, and metastasis. Moreover, six of the most highly upregulated genes were found to be overexpressed in tumor tissue compared to normal tissue.

scholarly journals Pooled CRISPR screening in pancreatic cancer cells implicates co-repressor complexes as a cause of multiple drug resistance via regulation of epithelial-to-mesenchymal transition

2019 ◽  
Author(s):  
Ryne C. Ramaker ◽  
Andrew A. Hardigan ◽  
Emily R. Gordon ◽  
Carter A. Wright ◽  
Richard M. Myers ◽  
...  
Keyword(s):  
Epithelial To Mesenchymal Transition ◽  
Efflux Pump ◽  
Multiple Drug Resistance ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Ductal Adenocarcinoma ◽  
Multiple Drug ◽  
Knock Out ◽  
Mesenchymal Transition ◽  
Pancreatic Cancer Cells

ABSTRACTPancreatic ductal adenocarcinoma (PDAC) patients suffer poor outcomes in part due to therapeutic resistance. We conducted four genome-wide CRISPR activation (CRISPRact) and CRISPR knock out (CRISPRko) screens to identify novel resistance mechanisms to four cytotoxic chemotherapies (gemcitabine, 5-fluorouracil, irinotecan, and oxaliplatin). ABCG2, a well-described efflux pump was the strongest mediator of resistance. We showed that overexpressing HDAC1 altered promoter occupancy and expression of genes involved in the epithelial-to-mesenchymal transition. Using the results of our CRISPR screens, we predicted drug sensitivity for patients and cell lines based on gene expression profiles. These predictions could be clinically useful for treatment selection.

scholarly journals Bioinformatics analysis of differentially expressed genes and pathways in the development of cervical cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Baojie Wu ◽  
Shuyi Xi
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Targets ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Kegg Pathways

Abstract Background This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis. Methods Three gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets. Results A total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained. Conclusions These findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.

scholarly journals Integrative machine learning analysis of multiple gene expression profiles in cervical cancer

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5285 ◽  
Author(s):  
Mei Sze Tan ◽  
Siow-Wee Chang ◽  
Phaik Leng Cheah ◽  
Hwa Jen Yap
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cervical Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
Multiple Gene ◽  
Cervical Cancers ◽  
Learning Analysis

Although most of the cervical cancer cases are reported to be closely related to the Human Papillomavirus (HPV) infection, there is a need to study genes that stand up differentially in the final actualization of cervical cancers following HPV infection. In this study, we proposed an integrative machine learning approach to analyse multiple gene expression profiles in cervical cancer in order to identify a set of genetic markers that are associated with and may eventually aid in the diagnosis or prognosis of cervical cancers. The proposed integrative analysis is composed of three steps: namely, (i) gene expression analysis of individual dataset; (ii) meta-analysis of multiple datasets; and (iii) feature selection and machine learning analysis. As a result, 21 gene expressions were identified through the integrative machine learning analysis which including seven supervised and one unsupervised methods. A functional analysis with GSEA (Gene Set Enrichment Analysis) was performed on the selected 21-gene expression set and showed significant enrichment in a nine-potential gene expression signature, namely PEG3, SPON1, BTD and RPLP2 (upregulated genes) and PRDX3, COPB2, LSM3, SLC5A3 and AS1B (downregulated genes).

LncRNA-CTS promotes metastasis and epithelial-to-mesenchymal transition through regulating miR-505/ZEB2 axis in cervical cancer

2019 ◽  
Vol 465 ◽  
pp. 105-117 ◽  
Author(s):  
Shujun Feng ◽  
Wei Liu ◽  
Xiaoxu Bai ◽  
Wenjing Pan ◽  
Zhaoyang Jia ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Epithelial To Mesenchymal Transition ◽  
Mesenchymal Transition

scholarly journals Alleviation of Multidrug Resistance by Flavonoid and Non-Flavonoid Compounds in Breast, Lung, Colorectal and Prostate Cancer

2020 ◽  
Vol 21 (2) ◽  
pp. 401 ◽  
Author(s):  
Teodora Costea ◽  
Oana Cezara Vlad ◽  
Luminita-Claudia Miclea ◽  
Constanta Ganea ◽  
János Szöllősi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Multidrug Resistance ◽  
Phenolic Compounds ◽  
Epithelial To Mesenchymal Transition ◽  
Inflammatory Responses ◽  
Inhibition Of Proliferation ◽  
Mesenchymal Transition ◽  
Beneficial Effects ◽  
Different Types ◽  
Phenolcarboxylic Acids

The aim of the manuscript is to discuss the influence of plant polyphenols in overcoming multidrug resistance in four types of solid cancers (breast, colorectal, lung and prostate cancer). Effective treatment requires the use of multiple toxic chemotherapeutic drugs with different properties and targets. However, a major cause of cancer treatment failure and metastasis is the development of multidrug resistance. Potential mechanisms of multidrug resistance include increase of drug efflux, drug inactivation, detoxification mechanisms, modification of drug target, inhibition of cell death, involvement of cancer stem cells, dysregulation of miRNAs activity, epigenetic variations, imbalance of DNA damage/repair processes, tumor heterogeneity, tumor microenvironment, epithelial to mesenchymal transition and modulation of reactive oxygen species. Taking into consideration that synthetic multidrug resistance agents have failed to demonstrate significant survival benefits in patients with different types of cancer, recent research have focused on beneficial effects of natural compounds. Several phenolic compounds (flavones, phenolcarboxylic acids, ellagitannins, stilbens, lignans, curcumin, etc.) act as chemopreventive agents due to their antioxidant capacity, inhibition of proliferation, survival, angiogenesis, and metastasis, modulation of immune and inflammatory responses or inactivation of pro-carcinogens. Moreover, preclinical and clinical studies revealed that these compounds prevent multidrug resistance in cancer by modulating different pathways. Additional research is needed regarding the role of phenolic compounds in the prevention of multidrug resistance in different types of cancer.

Sign in / Sign up

Export Citation Format

Share Document