scholarly journals Differential methylation of G-protein coupled receptor signaling genes in gastrointestinal neuroendocrine tumors

2021 ◽  
Author(s):  
Seyoun Byun ◽  
Kajsa E. Affolter ◽  
Angela K. Snow ◽  
Karen Curtin ◽  
Austin R. Cannon ◽  
...  
Keyword(s):  
Small Intestine ◽  
Neuroendocrine Tumors ◽  
Patient Survival ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Treatment Strategies ◽  
Molecular Features ◽  
Differentially Methylated Genes ◽  
Chromosomal Changes ◽  
Approved Drugs

Abstract Neuroendocrine tumors (NETs) of the small intestine undergo large chromosomal and methylation changes. The objective of this study was to identify methylation differences in NETs and consider how the differentially methylated genes may impact patient survival. Whole genome methylation and chromosomal copy number varation (CNV) of NETs from the small intestine and appendix was measured Tumors were divided into three molecular subtypes according to CNV results: chromosome 18 loss (18LOH), MultiCNV, and NoCNV. Comparison of 18LOH tumors with MultiCNV and NoCNV tumors identified 901 differentially methylated genes which are over represented with sevenG-protein coupled receptor (GPCR) pathways and the gene encoding somatostatin (SST), a clinical target for NETs. Patient survival based on low versus high methylation in all samples identified four significant genes (p-<0.05) OR2S2, SMILR, RNU6-653P and AC010543.1. Within the 18LOH molecular subtype tumors, survival differences were identifiedin high versus low methylation of 24 genes. The most significant is TRHR (p < 0.01), a GPCR with multiple FDA-approved drugs. By separating NETs into different molecular subtypes based on chromosomal changes, we find that multiple GPCRs and their ligands appear to be regulated through methylation and correlated with survival. Opportunities for better treatment strategies based on molecular features exist for NETs.

scholarly journals Differential methylation of G-protein coupled receptor signaling genes in gastrointestinal neuroendocrine tumors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyoun Byun ◽  
Kajsa E. Affolter ◽  
Angela K. Snow ◽  
Karen Curtin ◽  
Austin R. Cannon ◽  
...  
Keyword(s):  
Small Intestine ◽  
G Protein ◽  
Neuroendocrine Tumors ◽  
Patient Survival ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
G Protein Coupled Receptor ◽  
Molecular Features ◽  
Differentially Methylated Genes ◽  
G Protein Coupled

AbstractNeuroendocrine tumors (NETs) of the small intestine undergo large chromosomal and methylation changes. The objective of this study was to identify methylation differences in NETs and consider how the differentially methylated genes may impact patient survival. Genome-wide methylation and chromosomal copy number variation (CNV) of NETs from the small intestine and appendix were measured. Tumors were divided into three molecular subtypes according to CNV results: chromosome 18 loss (18LOH), Multiple CNV, and No CNV. Comparison of 18LOH tumors with MultiCNV and NoCNV tumors identified 901 differentially methylated genes. Genes from the G-protein coupled receptor (GPCR) pathways are statistically overrepresented in the differentially methylated genes. One of the highlighted genes from the GPCR pathway is somatostatin (SST), a clinical target for NETs. Patient survival based on low versus high methylation in all samples identified four significant genes (p < 0.05) OR2S2, SMILR, RNU6-653P, and AC010543.1. Within the 18LOH molecular subtype tumors, survival differences were identified in high versus low methylation of 24 genes. The most significant is TRHR (p < 0.01), a GPCR with multiple FDA-approved drugs. By separating NETs into different molecular subtypes based on chromosomal changes, we find that multiple GPCRs and their ligands appear to be regulated through methylation and correlated with survival. These results suggest opportunities for better treatment strategies for NETs based on molecular features.

scholarly journals Building a Foundation for Precision Onco-Nutrition: Docosahexaenoic Acid and Breast Cancer

Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 157
Author(s):  
Henry J. Thompson ◽  
Elizabeth S. Neil ◽  
John N. McGinley ◽  
Vanessa K. Fitzgerald ◽  
Karam El Bayoumy ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Docosahexaenoic Acid ◽  
Anticancer Activity ◽  
Mammalian Cells ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Biological Activities ◽  
Treatment Strategies ◽  
Cell Number

In vivo evidence of heterogeneous effects of n-3 fatty acids (N3FA) on cell signaling pathways associated with the reduced growth of breast cancer has been reported and is consistent with the expectation that N3FA will not exert uniform effects on all molecular subtypes of the disease. Similarly, available evidence indicates that many metabolites of N3FA are synthesized by mammalian cells and that they exert metabolite-specific biological activities. To begin to unravel the complex relationships among molecular subtypes and effects exerted by specific N3FA metabolites on those pathways, proof-of-concept experiments were conducted using cell lines representative of common molecular subtypes of human breast cancer. N3FA differed in anticancer activity with docosahexaenoic acid (DHA) having greater anticancer activity than eicosapentaenoic acid. 4-oxo-docosahexaenoic (4-oxo-DHA), a penultimate metabolite of 5-lipoxygenase mediated DHA metabolism, induced dose-dependent inhibition of cell number accumulation with apoptosis as a primary effector mechanism. Interrogation of protein expression data using the Ingenuity Pathway Analysis (IPA) bioinformatics platform indicated that 4-oxo-DHA differentially impacted six canonical pathways and the cellular functions they regulate across common molecular subtypes of breast cancer. This included the endocannabinoid pathway for cancer inhibition that has not been previously reported. These findings provide a rationale for juxtaposing molecular subtype targeted treatment strategies with the adjuvant use of specific N3FA metabolites as an example of precision onco-nutrition (PON) for the management and control of breast cancer.

ColotypeR: A tool to classify colon cancers by consensus molecular subtype and subtype-specific risk of recurrence.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 632-632
Author(s):  
Steven Allen Buechler ◽  
Sunil S. Badve ◽  
Yesim Gokmen-Polar ◽  
Emily Herring ◽  
Katelyn Ludwig ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Prognostic Significance ◽  
Response To Treatment ◽  
Training Set ◽  
Risk Of Recurrence ◽  
Molecular Features ◽  
Colon Cancers ◽  
Specific Risk

632 Background: Colon cancer is highly heterogeneous in prognosis and response to treatment. The consensus molecular subtypes (CMS1-4, and mixed) partition colon cancers into distinct groups. CMS4 tumors, a mesenchymal subtype, have the worst prognosis and poor response to standard chemotherapies. There is a critical need for accurate molecular subtyping, and subtype-specific management. Methods: Affymetrix microarrays colon cancer datasets (N = 813; GSE39582, GSE14333) were partitioned into training (AT; N = 370) and validation sets (AV; N = 443) balanced for clinical traits. A novel multistate gene methodology was used to predict CMS, and prognosticate subtype-specific relapse-free survival (RFS) in the training set. Accuracy of CMS prediction and prognostic significance was validated in the AV and TCGA colon cancer (COAD; N = 458) sets. Results: In the training set, a 20-gene panel (ColotypeR-CMS) predicts CMS subtype. Mean accuracy for CMS1-4 prediction was 0.87 in AV and 0.81 in COAD. In AV, 5-year RFS is 0.52 (95%CI 0.43 – 0.63) in the predicted CMS4, and 0.70 (95%CI 0.65 – 0.77) in the non-CMS4 samples. The risk of relapse for non-CMS4 samples was refined by a genomic score (ColotypeR-Risk) computed using expression of 25 genes in the training set. ColotypeR-Risk was prognostic of RFS (p = 0.0004) among the AV non-CMS4 samples, and also prognostic (p = 0.0001) among the stage II non-CMS4 AV samples not treated with chemotherapy. The prognostic significance of ColotypeR-Risk among non-CMS4 samples is independent of tumor location (right or left) and CMS subtype (CMS1-3 or mixed). ColotypeR-Risk was also prognostic of RFS in non-CMS4 samples in COAD (p = 0.005). Conclusions: ColotypeR identifies the consensus molecular subtypes (CMS1, CMS2, CMS3, CMS4, or mixed), and assesses subtype-specific risk of recurrence of colon cancer. ColotypeR identifies prognostic risk and molecular features that could help guide the management of colon cancer patients.

scholarly journals Breast Cancer—Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies—An Updated Review

Cancers ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 4287
Author(s):  
Sergiusz Łukasiewicz ◽  
Marcin Czeczelewski ◽  
Alicja Forma ◽  
Jacek Baj ◽  
Robert Sitarz ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Wide Spectrum ◽  
Tnm Classification ◽  
Treatment Strategies ◽  
Cancer Registration ◽  
Luminal A ◽  
Modifiable Factors

Breast cancer (BC) is the most frequently diagnosed cancer in women worldwide with more than 2 million new cases in 2020. Its incidence and death rates have increased over the last three decades due to the change in risk factor profiles, better cancer registration, and cancer detection. The number of risk factors of BC is significant and includes both the modifiable factors and non-modifiable factors. Currently, about 80% of patients with BC are individuals aged >50. Survival depends on both stage and molecular subtype. Invasive BCs comprise wide spectrum tumors that show a variation concerning their clinical presentation, behavior, and morphology. Based on mRNA gene expression levels, BC can be divided into molecular subtypes (Luminal A, Luminal B, HER2-enriched, and basal-like). The molecular subtypes provide insights into new treatment strategies and patient stratifications that impact the management of BC patients. The eighth edition of TNM classification outlines a new staging system for BC that, in addition to anatomical features, acknowledges biological factors. Treatment of breast cancer is complex and involves a combination of different modalities including surgery, radiotherapy, chemotherapy, hormonal therapy, or biological therapies delivered in diverse sequences.

scholarly journals miRNA profiling of small intestinal neuroendocrine tumors defines novel molecular subtypes and identifies miR-375 as a biomarker of patient survival

2018 ◽  
Vol 31 (8) ◽  
pp. 1302-1317 ◽  
Author(s):  
Yvonne Arvidsson ◽  
Anna Rehammar ◽  
Anders Bergström ◽  
Ellinor Andersson ◽  
Gülay Altiparmak ◽  
...  
Keyword(s):  
Neuroendocrine Tumors ◽  
Patient Survival ◽  
Molecular Subtypes ◽  
Mirna Profiling ◽  
Small Intestinal

scholarly journals Predicting Endometrial Cancer Subtypes and Molecular Features from Histopathology Images Using Multi-resolution Deep Learning Models

2020 ◽  
Author(s):  
Runyu Hong ◽  
Wenke Liu ◽  
Deborah DeLair ◽  
Narges Razavian ◽  
David Fenyö
Keyword(s):  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Characteristic Curve ◽  
The Cancer Genome Atlas ◽  
Diagnostic Process ◽  
Histological Subtypes ◽  
Neural Network Models ◽  
Molecular Subtyping ◽  
Cancer Subtypes ◽  
Molecular Features

AbstractThe determination of endometrial carcinoma histological subtypes is a critical diagnostic process that directly affects patients’ prognosis and treatment options. Recently, molecular subtyping and mutation status are increasingly utilized in clinical practice as they offer better inform prognosis and offer the possibility of individualized therapies. Compared to the histopathological approach, however, the availability of molecular subtyping is limited as it can only be obtained by genomic sequencing, which may be cost prohibitive. Here, we implemented deep convolutional neural network models that predict not only the histological subtypes, but also molecular subtypes and 18 common gene mutations based on digitized H&E stained pathological images. Taking advantage of the multi-resolution nature of the whole slide images, we introduced a customized architecture, Panoptes, to integrate features of different magnification. The model was trained and evaluated with images from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium. Our models achieved an area under the receiver operating characteristic curve (AUROC) of 0.969 in predicting histological subtype and 0.934 to 0.958 in predicting the copy number high (CNV-H) molecular subtype. The prediction tasks of 4 mutations and microsatellite high (MSI-H) molecular subtype also achieved a high performance with AUROC ranging from 0.781 to 0.873. Panoptes showed a significantly better performance than InceptionResnet in most of these top predicted tasks by up to 18%. Feature extraction and visualization revealed that the model relied on human-interpretable patterns. Our results suggest that Panoptes can help pathologists determine molecular subtypes and mutations without sequencing, and our models are generalizable to independent datasets.

Beyond Adenocarcinoma: Current Treatments and Future Directions for Squamous, Small Cell, and Rare Lung Cancer Histologies

2015 ◽  
pp. 147-162 ◽  
Author(s):  
David E. Gerber ◽  
Paul K. Paik ◽  
Afshin Dowlati
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Neuroendocrine Tumors ◽  
Cell Lung Cancer ◽  
Somatostatin Analogs ◽  
Treatment Strategies ◽  
Small Cell ◽  
Cytotoxic Agents ◽  
Small Cell Lung ◽  
Molecular Features

Lung cancer encompasses a diverse spectrum of histologic subtypes. Until recently, the majority of therapeutic advances were limited to the minority of patients with adenocarcinoma. With the advent of comprehensive genomic profiling of squamous and small cell lung cancers, new therapeutic targets have emerged. For squamous tumors, the most promising of these include fibroblast growth factor receptor (FGFR), the phosphatidylinositol 3-kinase (PI3K) pathway, discoidin domain receptor 2 (DDR2), and G1/S checkpoint regulators. In 2014, the antiangiogenic agent ramucirumab was approved for all non–small cell lung cancer (NSCLC) histologies, including squamous tumors. Immunotherapeutic approaches also appear to be promising for these cases. Genomic analysis of small cell lung cancer has revealed a high mutation burden, but relatively few druggable driver oncogenic alterations. Current treatment strategies under investigation are focusing on targeting mitotic, cell cycle, and DNA repair regulation, as well as immunotherapy. Pulmonary neuroendocrine tumors represent a diverse spectrum of diseases that may be treated with somatostatin analogs, cytotoxic agents, and molecularly targeted therapies. Radiolabeled somatostatin analogs and combinations with mammalian target of rapamycin (mTOR) inhibitors also show potential. Large cell neuroendocrine tumors share numerous clinical, pathologic, and molecular features with small cell lung cancer; however, whether they should be treated similarly or according to a NSCLC paradigm remains a matter of debate.

Intrauterine Growth Restriction Alters the Genome-Wide DNA Methylation Profiles in Small Intestine, Liver and Longissimus Dorsi Muscle of Newborn Piglets

2019 ◽  
Vol 20 (7) ◽  
pp. 713-726 ◽  
Author(s):  
Shiyu Tao ◽  
Tianjiao Zhou ◽  
Perot Saelao ◽  
Ying Wang ◽  
Yuhua Zhu ◽  
...  
Keyword(s):  
Small Intestine ◽  
Birth Weight ◽  
Intrauterine Growth Restriction ◽  
Longissimus Dorsi ◽  
Intrauterine Growth ◽  
Longissimus Dorsi Muscle ◽  
Newborn Piglets ◽  
Dorsi Muscle ◽  
Genome Wide ◽  
Differentially Methylated Genes

Intrauterine growth restriction (IUGR) remains a major problem in swine production since the associated low birth weight leads to high rates of pre-weaning morbidity and mortality, and permanent retardation of growth and development. The underlying regulatory mechanisms from the aspects of epigenetic modification has received widespread attention. Studies explore the changes in genome wide methylation in small intestine (SI), liver and longissimus dorsi muscle (LDM) between IUGR and normal birth weight (NBW) newborn piglets using a methylated DNA immunoprecipitation-sequencing (MeDIP-Seq) approach. The data demonstrated that methylated peaks were prominently distributed in distal intergenic regions and the quantities of peaks in IUGR piglets were more than that of NBW piglets. IUGR piglets had relatively high methylated level in promoters, introns and coding exons in all the three tissues. Through KEGG pathway analysis of differentially methylated genes found that 33, 54 and 5 differentially methylated genes in small intestine, liver and longissimus dorsi muscle between NBW and IUGR piglets, respectively, which are related to development and differentiation, carbohydrate and energy metabolism, lipid metabolism, protein turnover, immune response, detoxification, oxidative stress and apoptosis pathway. The objective of this review is to assess the impact of differentially methylation status on developmental delay, metabolic disorders and immune deficiency of IUGR piglets.

scholarly journals CSIG-03. RECONCILING TUMOR HETEROGENEITY IN GLIOBLASTOMA USING A PATHWAY-BASED APPROACH

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii28-ii28
Author(s):  
Alvaro Alvarado ◽  
Kaleab Tessema ◽  
Kunal Patel ◽  
Riki Kawaguchi ◽  
Richard Everson ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Patient Survival ◽  
Molecular Subtype ◽  
Gene List ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Molecular Architecture ◽  
Survival Pathways ◽  
Cancer Genome Atlas

Abstract Despite efforts to gain a deeper understanding of its molecular architecture, glioblastoma (GBM) remains uniformly fatal. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has yielded little progress towards extending patient survival. In particular, the great phenotypic heterogeneity of GBM – both inter and intratumorally – has hindered therapeutic efforts. To this end, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. Gene set enrichment analysis (GSEA) was applied to gene expression data and used to provide an overview of each sample that can be compared to other samples by generating sample clusters based on overall patterns of enrichment. The Cancer Genome Atlas (TCGA) samples were clustered using the canonical and oncogenic signatures and in both cases the clustering was distinct from the molecular subtype previously reported and clusters were informative of patient survival. We also analyzed single cell RNA sequencing datasets and uniformly found two clusters of cells enriched for cell cycle regulation and survival pathways. We have validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity when E2F1, out top target, was silenced and when treated with fulvestrant and calcitriol, which were identified as potential drugs targeting this genelist. Conversely, no changes were observed in samples not enriched for this gene list. Finally, we interrogated spatial heterogeneity and found higher enrichment of the proliferative signature in contrast enhancing compared with non-enhancing regions. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

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