Abstract 5145: Integrative analysis of multidimensional colorectal cancer molecular profiles reveals an aggressive subpopulation characterized by specific gene methylation/expression patterns.

Abstract Context Adipose tissue inflammation and dysregulated energy homeostasis are key mechanisms linking obesity and cancer. Distinct adipose tissue depots strongly differ in their metabolic profiles; however, comprehensive studies of depot-specific perturbations among patients with cancer are lacking. Objective We compared transcriptome profiles of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) from patients with colorectal cancer and assessed the associations of different anthropometric measures with depot-specific gene expression. Design Whole transcriptomes of VAT and SAT were measured in 233 patients from the ColoCare Study, and visceral and subcutaneous fat area were quantified via CT. Results VAT compared with SAT showed elevated gene expression of cytokines, cell adhesion molecules, and key regulators of metabolic homeostasis. Increased fat area was associated with downregulated lipid and small molecule metabolism and upregulated inflammatory pathways in both compartments. Comparing these patterns between depots proved specific and more pronounced gene expression alterations in SAT and identified unique associations of integrins and lipid metabolism–related enzymes. VAT gene expression patterns that were associated with visceral fat area poorly overlapped with patterns associated with self-reported body mass index (BMI). However, subcutaneous fat area and BMI showed similar associations with SAT gene expression. Conclusions This large-scale human study demonstrates pronounced disparities between distinct adipose tissue depots and reveals that BMI poorly correlates with fat mass–associated changes in VAT. Taken together, these results provide crucial evidence for the necessity to differentiate between distinct adipose tissue depots for a correct characterization of gene expression profiles that may affect metabolic health of patients with colorectal cancer.

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Expression and methylation profiles associated with recurrent mutations in stage II colorectal cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.e14613 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. e14613-e14613

Author(s):

Laia Pare-Brunet ◽

Rebeca Sanz-Pamplona ◽

Adriana Lopez-Doriga ◽

Antoni Berenguer-Llergo ◽

Susanna Ausso ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Methylation ◽

Molecular Subtypes ◽

Expression Patterns ◽

Stage Ii ◽

Molecular Heterogeneity ◽

Rna Expression ◽

Gene Methylation ◽

Recurrent Mutations ◽

Combining Data

e14613 Background: Aberration of normal genetic and epigenetic patterns occurs at early stages of colorectal cancer (CRC) and accumulates throughout cancer progression. To characterize pre-metastatic tumors, a series of stage II, microsatellite stable, colon tumors and their paired mucosa were profiled on RNA expression and DNA methylation microarrays ( www.colonomics.org ). Our aim is to define molecular subtypes based on recurrent gene mutations, methylation and expression profiles, and explore if these molecular subtypes are associated to patients’ prognosis. Methods: We have sequenced exomes (Illumina Genome Analyzer) of a subset of 42 COLONOMICS normal-tumor paired samples (21 good and 21 bad prognosis). Variants identified in normal tissue were used to filter SNPs. DNA methylation (Infinium Human Methylation 450k) and RNA expression (Affymetrix U219) data from those samples were used in this analysis. Correlation was used to assess the association between tumor mutations and differentially expressed/methylated genes. Significant genes were subsequently used to perform tumor clustering. Results: Exome analysis revealed a mean of 150 somatic mutations per sample. From these, 12 variants were recurrently mutated (KRAS, TP53, etc) in more than 3 tumors that were used to define tumor subtypes based on gene methylation/expression patterns. We obtained 12 profiles that clearly identified the cluster of mutated samples. For some profiles, the cluster only includes those tumors with the mutation. Interestingly, some clusters included the mutated samples and additional tumors showing the same phenotype despite not having the mutation. For each mutation, the overlapping between the differently methylated/expressed genes ranged from 14 to 200 common genes. When combining data from the three platforms two main CRC molecular subtypes emerge; each of which shows molecular heterogeneity but no association with prognosis. Conclusions: Mutational status is associated with gene methylation and expression patterns in CRC patients. Although none of these clusters was associated with prognosis, different groups of tumors could be related to distinctive pathways, which may reveal useful as therapeutic targets.

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Identification of colorectal cancer, adenoma, and inflammatory bowel disease specific gene expression patterns using whole genomic oligonucleotide microarray system

Orvosi Hetilap ◽

10.1556/oh.2007.28157 ◽

2007 ◽

Vol 148 (44) ◽

pp. 2067-2079 ◽

Cited By ~ 6

Author(s):

Orsolya Galamb ◽

Balázs Győrffy ◽

Ferenc Sipos ◽

Sándor Spisák ◽

Anna Mária Németh ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Inflammatory Bowel Disease ◽

Expression Patterns ◽

Gene Expression Patterns ◽

Specific Gene ◽

Affymetrix Microarray ◽

Inflammatory Bowel ◽

Leave One Out ◽

Disease Specific

A vastagbél-biopsziák nagy teljesítményű oligonukleotid microarray-vizsgálata segítségünkre lehet a helyi patofiziológiai eltérések megértésében, valamint elősegítheti a colorectalis adenomák, karcinómák és gyulladásos bélbetegségek funkcionális klasszifikációját. Módszerek: 15 vastagbélrákos, 15 adenomás, 14 gyulladásos bélbetegségben szenvedő beteg biopsziás mintájából teljes ribonukleinsav izolálását, amplifikációját és biotinos jelölését végeztük. A teljes genomszintű génexpressziós mintázat meghatározása Human Genome U133 Plus 2.0 microarray-ken történt. Két független normalizációs módszert követően a diagnosztikus génmintázat meghatározására „Prediction Analysis of Microarrays” módszert használtunk. Leave one-out lépésenkénti diszkriminanciaelemzést végeztünk. Az expressziós eredményeket valós idejű polimeráz láncreakcióval igazoltuk. Eredmények: Adenomában a „top” igazolt gének a következők voltak: CD44-antigén, met proto-onkogén, kemokin ligand-12, ADAM-szerű decizin-1 és az ATP-kötő kazetta-A8; vastagbélrákban a kollagén-IVα1, lipokalin-2, kalumenin, akvaporin-8; és gyulladásos bélbetegségben a lipokalin-2, ubikvitin D és az interferon indukálta transzmembrán-fehérje-2. A diszkriminanciaelemzéssel kapott elkülönítő gének expressziója alapján átlagosan 96,2%-os pontossággal csoportosíthatók a minták. A Taqman valós idejű polimeráz láncreakcióval vizsgált, 52 kiválasztott gén 94%-ának expressziós szintje szignifikánsan korrelált az Affymetrix microarray vizsgálatban kapott eredményekkel ( p < 0,05). Következtetések: Biopsziás minták felhasználásával sikeresen végeztünk teljes genomszintű expressziós microarray-vizsgálatot, amely alkalmasnak bizonyult elkülönítő génmintázatok azonosítására. Eredményeink további elemzésekre felhasználható génexpressziós adattárat biztosítanak.

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Integrative Analysis of Fecal Metagenomics and Metabolomics in Colorectal Cancer

SSRN Electronic Journal ◽

10.2139/ssrn.3520024 ◽

2020 ◽

Author(s):

Marc Clos-Garcia ◽

Koldo Garcia ◽

Cristina Alonso ◽

Marta Iruarrizaga-Lejarreta ◽

Mauro D’Amato ◽

...

Keyword(s):

Colorectal Cancer ◽

Integrative Analysis

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A Global Vista of the Epigenomic State of the Mouse Submandibular Gland

Journal of Dental Research ◽

10.1177/00220345211012000 ◽

2021 ◽

pp. 002203452110120

Author(s):

C. Gluck ◽

S. Min ◽

A. Oyelakin ◽

M. Che ◽

E. Horeth ◽

...

Keyword(s):

Gene Expression ◽

Transcriptional Control ◽

Expression Patterns ◽

Global Gene Expression ◽

Regulatory Elements ◽

Specific Gene ◽

Submandibular Salivary Gland ◽

Data Sets ◽

Control Mechanisms ◽

Chromatin Immunoprecipitation Sequencing

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.

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A tumor microenvironment-specific gene expression signature predicts chemotherapy resistance in colorectal cancer patients

npj Precision Oncology ◽

10.1038/s41698-021-00142-x ◽

2021 ◽

Vol 5 (1) ◽

Author(s):

Xiaoqiang Zhu ◽

Xianglong Tian ◽

Linhua Ji ◽

Xinyu Zhang ◽

Yingying Cao ◽

...

Keyword(s):

Colorectal Cancer ◽

Tumor Microenvironment ◽

Drug Sensitivity ◽

Chemotherapy Resistance ◽

Gene Expression Signature ◽

Prediction Algorithm ◽

Specific Gene ◽

Chemotherapy Response ◽

Rna Seq ◽

Mesenchymal Transition

AbstractStudies have shown that tumor microenvironment (TME) might affect drug sensitivity and the classification of colorectal cancer (CRC). Using TME-specific gene signature to identify CRC subtypes with distinctive clinical relevance has not yet been tested. A total of 18 “bulk” RNA-seq datasets (total n = 2269) and four single-cell RNA-seq datasets were included in this study. We constructed a “Signature associated with FOLFIRI resistant and Microenvironment” (SFM) that could discriminate both TME and drug sensitivity. Further, SFM subtypes were identified using K-means clustering and verified in three independent cohorts. Nearest template prediction algorithm was used to predict drug response. TME estimation was performed by CIBERSORT and microenvironment cell populations-counter (MCP-counter) methods. We identified six SFM subtypes based on SFM signature that discriminated both TME and drug sensitivity. The SFM subtypes were associated with distinct clinicopathological, molecular and phenotypic characteristics, specific enrichments of gene signatures, signaling pathways, prognosis, gut microbiome patterns, and tumor lymphocytes infiltration. Among them, SFM-C and -F were immune suppressive. SFM-F had higher stromal fraction with epithelial-to-mesenchymal transition phenotype, while SFM-C was characterized as microsatellite instability phenotype which was responsive to immunotherapy. SFM-D, -E, and -F were sensitive to FOLFIRI and FOLFOX, while SFM-A, -B, and -C were responsive to EGFR inhibitors. Finally, SFM subtypes had strong prognostic value in which SFM-E and -F had worse survival than other subtypes. SFM subtypes enable the stratification of CRC with potential chemotherapy response thereby providing more precise therapeutic options for these patients.

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Genome-wide analysis and expression profile of the bZIP gene family in poplar

BMC Plant Biology ◽

10.1186/s12870-021-02879-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Kai Zhao ◽

Song Chen ◽

Wenjing Yao ◽

Zihan Cheng ◽

Boru Zhou ◽

...

Keyword(s):

Salt Stress ◽

Systems Biology ◽

Gene Family ◽

Stress Responses ◽

Metal Ion ◽

Gene Networks ◽

Expression Patterns ◽

Gene Set Enrichment Analysis ◽

Specific Gene ◽

Biological Processes

Abstract Background The bZIP gene family, which is widely present in plants, participates in varied biological processes including growth and development and stress responses. How do the genes regulate such biological processes? Systems biology is powerful for mechanistic understanding of gene functions. However, such studies have not yet been reported in poplar. Results In this study, we identified 86 poplar bZIP transcription factors and described their conserved domains. According to the results of phylogenetic tree, we divided these members into 12 groups with specific gene structures and motif compositions. The corresponding genes that harbor a large number of segmental duplication events are unevenly distributed on the 17 poplar chromosomes. In addition, we further examined collinearity between these genes and the related genes from six other species. Evidence from transcriptomic data indicated that the bZIP genes in poplar displayed different expression patterns in roots, stems, and leaves. Furthermore, we identified 45 bZIP genes that respond to salt stress in the three tissues. We performed co-expression analysis on the representative genes, followed by gene set enrichment analysis. The results demonstrated that tissue differentially expressed genes, especially the co-expressing genes, are mainly involved in secondary metabolic and secondary metabolite biosynthetic processes. However, salt stress responsive genes and their co-expressing genes mainly participate in the regulation of metal ion transport, and methionine biosynthetic. Conclusions Using comparative genomics and systems biology approaches, we, for the first time, systematically explore the structures and functions of the bZIP gene family in poplar. It appears that the bZIP gene family plays significant roles in regulation of poplar development and growth and salt stress responses through differential gene networks or biological processes. These findings provide the foundation for genetic breeding by engineering target regulators and corresponding gene networks into poplar lines.

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Comprehensive analysis of single cell ATAC-seq data with SnapATAC

Nature Communications ◽

10.1038/s41467-021-21583-9 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Rongxin Fang ◽

Sebastian Preissl ◽

Yang Li ◽

Xiaomeng Hou ◽

Jacinta Lucero ◽

...

Keyword(s):

Single Cell ◽

Single Cell Analysis ◽

Expression Patterns ◽

Regulatory Elements ◽

Cellular Heterogeneity ◽

Specific Gene ◽

Open Chromatin ◽

Cell Type ◽

Process Data ◽

Cell Type Specific

AbstractIdentification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

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