(searched for: Discovery of Novel Prognostic Biomarkers and Therapeutic Targets for Esophageal Cancer)
Frontiers in Oncology, Volume 10; doi:10.3389/fonc.2020.596963
Editorial on the Research TopicImpact of Cancer Plasticity on Drug Resistance and Treatment in Solid Tumors The Research Topic “Impact of Cancer Plasticity on Drug Resistance and Treatment in Solid Tumors” consists of 32 articles contributed by more than 270 authors in the field of oncology, pharmacology, and translational research. Our aim was to provide a collaborative discussion on molecular and cellular regulators of cancer cell plasticity contributing to tumor progression and drug resistance for the future direction of biomarker discovery and therapeutic strategies. Cancer stem cells, tumor microenvironment, stroma/cancer cells interactions, changes in metabolism and epithelial-mesenchymal transition offer explanation for tumor plasticity. The current state of art in this era was elegantly reviewed by Fanelli et al., Yang et al., and Lin X. et al., who discussed the clinical relevance of cancer cell plasticity, the novel approaches for monitoring tumor plasticity and the current advances for therapeutic targeting. Yu et al. found that the FAP-a+GOLPH3+ immunophenotype, combining the expression of both the fibroblast activation protein-alpha and the oncogenic Golgi phosphoprotein 3 protein predict the recurrence and progression of ductal carcinoma in-situ (DCIS) into invasive breast cancer. Yao et al. demonstrated in mouse experiments that the levels of MTA3 and SOX2 decreased and increased, respectively, during the progression of tongue squamous cell cancer (TSCC), and that MTA3low/SOX2high can serve as an independent prognostic factor for TSCC patients. Chen et al. confirmed that overexpression of PD-L1 occurred predominantly in highly aggressive glioma cells, and Akt binding/activation prevented autophagic cytoskeleton collapse, thus facilitating glioma cell invasion upon starvation stress. Sun et al. showed that SIRT5, a mitochondrial class III NAD-dependent deacetylase, contributes to cisplatin resistance in ovarian cancer by suppressing cisplatin-induced DNA damage in a reactive oxygen species (ROS)-dependent manner, via the regulation of the nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase 1 (HO-1) pathway. The study from Tang et al. suggested that the Pigment epithelium-derived factor (PEDF) participates the carcinogenesis of human esophageal squamous cell carcinoma and might be a candidate therapeutic target. Finally, analyses conducted by Zhang J. et al. on single-cell sequencing datasets of several human cancers indicated a tumor suppression function of the ZNF671 transcription factor. Fahs et al. demonstrated that the PAX3-FOXO1 fusion protein modulates exosome cargo to confer a protective effect on recipient cells against oxidative stress and to promote plasticity and survival, potentially contributing to the known aggressive phenotype of the fusion gene-positive subtype of Rhabdomyosarcoma. Guo T. et al. reported a clinical case showing change of pathological type to metaplastic squamous cell carcinoma of the breast during disease recurrence. Epigenetic reprogramming favors cancer plasticity. The discovery of non-coding RNA such as microRNA (miR), Long non-coding RNA (LncRNA) and circular RNA (circ-RNA) is propelling the future advancement of biomarker development and offers opportunities to understand their role in the hallmarks of cancer, including signaling pathways involved in cell proliferation, cell invasion, metabolic plasticity and drug resistance. Wan et al. deciphered the functional domains of the channel-kinase transient receptor potential ion channel subfamily M, member 7 (TRPM7) involved in glioma cell growth or migration/invasion. TRPM7 was found to regulate miR-28-5p expression, which suppresses cell proliferation and invasion in glioma cells by targeting the Rap1b signaling. Guo J. et al. demonstrated that miR-204-3p, whose down-regulation was significantly associated with poor prognosis in bladder cancer patients, negatively modulated the proliferation of bladder cancer cells via targeting the lactate dehydrogenase (LDHA)-mediated glycolysis. Huang et al. elegantly provided evidence that LncRNA AFAP1-S1 up-regulates the RRM2 protein levels by sponging miR-139-5, then activating an RRM2/EGFR/Akt axis that promotes chemoresistance in non-small cell lung cancer. Supportive in vivo experiments further demonstrated that knockdown of AFAP1-AS1 significantly suppressed tumor growth and chemoresistance. Li W. et al. proved that miR-199a, by directly regulating K-RAS and thus the downstream AKT and ERK signaling, inhibits glioma cell proliferation in vitro, tumor growth in vivo and increases sensitivity to telozomide, a drug used in first line treatment of glioma. Lin X.-J. et al. highlighted the role of miR-936 in sensitizing laryngeal squamous cancer cells to doxorubicin and cisplatin. Liu C. et al. experiments suggested that miR-34a-5p, by directly targeting thymidine kinase 1 (TKI), may be part of the mechanisms negatively regulating TKI-driven thyroid carcinoma cell aggressiveness. Growing body of evidence indicate that circRNAs play a role in disease progression, partly by sponging miRNA, and may be used as biomarkers. Gao et al. identified a candidate circRNA associated with poor prognosis in multiple myeloma. Finally, the review by Guo Q. et al. elegantly depicted and discussed the role of exosomal miRNA as a regulators and biomarkers in cancer drug resistance. It is of utmost importance to decipher how chronic exposure to environmental carcinogens contribute to cell plasticity and tumor progression. The identification of such molecular mechanisms may help in the discovery of human biomarkers of environmental carcinogen exposure and the development of candidate preventive strategies. Using an in vitro model for malignant transformation of normal lung cells upon long-term exposure to cigarette smoke, Wang et al. deciphered complex miRNA-mRNA networks associated with cancer-related signaling pathways, in particular those...
Archives of Clinical and Biomedical Research, Volume 4, pp 426-440; doi:10.26502/acbr.501700115
Esophageal cancer is one of the most common and lethal malignant tumors. Previous studies revealed the importance of microRNA (miRNA) and their targets in the occurrence, metastasis and prognosis of esophageal cancer. With the availability of The Cancer Genome Atlas (TCGA) database and the development of analytical tools, it is efficient and convenient to identify new biomarkers and key target genes associated with esophageal cancer prognosis through bioinformatic data mining. Five differentially expressed microRNA genes were identified to have significant association with the survival of the esophageal patients. Seven differentially expressed mRNA targets were selected to have significant association with the poor outcomes. These microRNA and mRNA genes could be the candidate biomarkers for tumor prognosis and/or therapeutic targets to improve the survival of esophageal cancer patients.
Cancer Chemistry, Volume 78, pp 2691-2691; doi:10.1158/1538-7445.am2018-2691
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SSRN Electronic Journal; doi:10.2139/ssrn.3253307
The publisher has not yet granted permission to display this abstract.
Dataset Papers in Science, Volume 2014, pp 1-3; doi:10.1155/2014/376541
Despite the undisputed importance of altered microRNA (miRNA) expression in various cancers, there is limited information on the clinicopathologic significance of cancer-related miRNAs in esophageal squamous cell carcinoma (ESCC). Previously, it was reported that the expression of several miRNAs was dysregulated in ESCC. However, the target genes of these miRNAs have not been identified. Furthermore, additional miRNAs in humans have been discovered recently, indicating that revised miRNA and gene expression profiling for ESCC are necessary. Here, we provide datasets from microarray analyses to identify miRNA and mRNA expression comprehensively in Het-1A, a normal human esophageal squamous cell line, and three human ESCC cell lines.1. IntroductionEsophageal cancer (EC) is the sixth most common cancer in the world that predominantly affects men and has a poor prognosis . EC is classified mainly into two types—squamous cell carcinoma and adenocarcinoma—which begin as flat cells lining the esophagus and as cells that produce and release mucus and other fluids, respectively. Despite recent medical advances, EC associated with distant metastasis and local invasion still leads to a poor prognosis. A recent statistical study revealed that the numbers of new EC cases and EC-related deaths worldwide in 2008 were estimated to be 482,300 and 406,800, respectively . This high mortality rate is largely due to poor subjective symptoms and difficulty with early diagnosis. Thus, EC is frequently diagnosed at late stages, leading to the unsatisfactory prognosis of affected patients, even though various therapeutic options such as surgery, chemotherapy, and radiotherapy are available. To date, endoscopic and radiologic examinations have been applied to detect EC at an early stage. Although the sensitivity and reliability of these diagnostic techniques have been improved, they do not always provide a satisfactory result. Furthermore, noninvasive diagnostic methods such as blood and urine tests for EC detection have not been established yet. Therefore, there is an urgent need to develop novel biomarkers for early detection and prognostic classification .MicroRNAs (miRNAs) are small, noncoding RNAs of about 18–25 nucleotides in length that negatively regulate protein translation and/or mRNA stability by binding to target mRNAs. Although many miRNAs are expressed ubiquitously, a few are known to exhibit cell type/organ-dependent and/or developmental stage-dependent expression patterns . Furthermore, aberrant miRNA expression has been found in various diseases, including many types of cancer . Functionally, miRNAs act as either oncogenes or tumor suppressors via gene regulation and are thus called “oncomirs” [5, 6]. In silico target prediction revealed that individual miRNAs potentially target multiple mRNAs, indicating their crucial roles physiologically and pathologically. Thus, efforts to identify the actual target mRNAs of miRNAs experimentally are necessary to understand how miRNAs are associated with the onset and progression of various diseases, including cancer, possibly leading to improvements in current diagnostic and prognostic indicators. To achieve this goal, we used microarray analysis, which is a powerful tool because it can analyze the expression of a number of mRNAs and miRNAs in multiple samples at once.Here, we present the datasets from our microarray experiments to analyze comprehensively and comparably mRNA and miRNA expression in normal and tumorous human esophageal squamous cell lines.2. MethodologyCell culture and RNA isolation were as follows. The ESCC-derived human cell lines used in this study were TE-1, TE-5, and TE-8, which are derived from well, poorly, and moderately differentiated tumors, respectively. These cell lines were purchased from RIKEN Cell Bank (Tsukuba, Japan) and cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum. Het-1A, an SV40 large T antigen-harboring normal human esophageal squamous cell line, was purchased from American Type Culture Collection (Manassas, VA, USA) and cultured using the BEGM kit (Lonza, Basel, Switzerland) but without the addition of the GA-1000 (gentamycin-amphotericin B mix) provided with the kit. Total RNA was isolated from these cells using ISOGEN reagent (Wako, Osaka, Japan) according to the manufacturer’s protocol. RNA purity was evaluated by the RNA integrity number (RIN), a representative index to assess RNA quality determined using the Agilent 2100 bioanalyzer (Agilent, Santa Clara, CA, USA). We confirmed RINs of more than 9.9 for all RNA samples used in this study (data not shown).Microarray study design for mRNA expression analysis was as follows. The RNA samples isolated from Het-1A and the ESCC cells were subjected to microarray-based expression analyses for mRNA using a SurePrint G3 Human Gene Expression 8 × 60 K v2 Array (Agilent). Cy3-labeled complementary RNA (cRNA) was prepared from 100 ng total RNA from each sample using the Low Input Quick Amp Labeling Kit, one color (Agilent). For each sample, 0.6 μg cRNA was hybridized using the Gene Expression Hybridization Kit (Agilent). The hybridized microarrays were subsequently washed using Gene Expression Wash Buffers Pack (Agilent) and subjected to fluorescent signal detection using a SureScan Microarray Scanner G4900DA (Agilent). The labeling, hybridization, and washing procedures were performed according to the manufacturer’s instructions.The intensities of the detected signals were quantified using Agilent Feature Extraction to generate raw data, which were registered in the Gene Expression Omnibus (GEO) database as accession number GSE61587. The quantified data were then normalized using GeneSpring GX12 (Agilent) to enable comparison of data from different microarrays.Microarray study design for miRNA expression analysis was as follows. The RNA samples isolated from the normal and tumorous esophageal squamous cells were subjected to microarray-based expression analyses for miRNA using the miRCURY LNA microRNA Array Kit 7th generation—human, mouse, and rat (Exiqon, Vedbaek, Denmark). Total RNA (250 ng) was 3′-labeled with Hy3 using the miRCURY LNA microRNA Hi-Power Labeling Kit (Exiqon) according to the manufacturer’s instructions. For this labeling reaction, a synthesized miRNA mimic supplied in the Spike-in microRNA Kit v2 (Exiqon) was added to the reaction mixture to assess the quality of the obtained microarray data. The hybridized microarrays were subsequently washed according to the manufacturer’s instructions and subjected to fluorescent signal detection using a SureScan Microarray Scanner G4900DA (Agilent).The intensities of the detected signals were quantified using Agilent Feature Extraction to generate raw data, which were registered as GEO accession number GSE61588. The quantified data were then normalized using ImaGene 9 and Nexus Expression 3.0 (BioDiscovery) to enable comparison of data from different microarrays.3. Dataset DescriptionThe dataset associated with this Dataset Paper consists of 2 items which are described as follows.Dataset Item 1 (Table). Normalized signal intensities from individual probes on SurePrint G3 Human Gene Expression 8 × 60 K v2 Arrays. The figures in the Signal Evaluation columns represent the significance of these signal intensities as follows: 2, detected; 1, difficult to judge; 0, not detected.Column 1: Feature Number Column 2: Probe ID Column 3: Gene Symbol Column 4: GenBank Accession Number Column 5: Description Column 6: Normalized Signal Intensity for Het-1A Column 7: Signal Evaluation for Het-1A Column 8: Normalized Signal Intensity for TE-1 Column 9: Signal Evaluation for TE-1 Column 10: Normalized Signal Intensity for TE-5 Column 11: Signal Evaluation for TE-5 Column 12: Normalized Signal Intensity for TE-8 Column 13: Signal Evaluation for TE-8 Column 14: GO Term Dataset Item 2 (Table). Normalized signal intensities from individual probes on miRCURY LNA microRNA Arrays.Column 1: Probe Number Column 2: miRNA Column 3: Normalized Signal Intensity for Het-1A Column 4: Normalized Signal Intensity for TE-1 Column 5: Normalized Signal Intensity for TE-5 Column 6: Normalized Signal Intensity for TE-8 4. Concluding RemarksMany recent studies have revealed that miRNAs could be promising biomarkers as well as therapeutic targets for cancer. This is particularly important for cancer types with a poor prognosis, including ESCC. In the present study, we conducted microarray analysis to analyze miRNA expression comprehensively in a normal human esophageal squamous cell line and in three types of human ESCC-derived cell lines to identify candidate miRNAs aberrantly expressed in ESCC. Furthermore, we performed microarray-based comprehensive gene expression analysis in these cell lines. Although it is generally believed that miRNAs suppress the translation of their target mRNAs into proteins, recent studies have revealed that miRNA-mediated gene silencing largely involves mRNA degradation [7, 8]. Thus, bioinformatic analyses of these microarray data, which include correlation analysis, miRNA target prediction, and ontology analysis, will provide an important clue to clarify how miRNAs are involved in the onset or progression of ESCC.Dataset AvailabilityThe dataset associated with this Dataset Paper is dedicated to the public domain using the CC0 waiver and is available at http://dx.doi.org/10.1155/2014/376541/dataset. In addition, the microarray data described herein (GSE61587 and GSE61588) were registered in GEO DataSets also as an integrated format as GSE61589. Deposited data are available at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE61589.Conflict of InterestsThe authors declare that they have no conflict of interests.AcknowledgmentsThis study was supported by Grant-in-Aid no. 24791449 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) and partly by the grant from Kurozumi Medical Foundation.