Purpose: Adenocarcinoma arises in Barrett's esophagus by progression from metaplasia to cancer through grades of dysplasia. Our aim in this exploratory study was to characterize the broad changes in gene expression that underlie this histologic progression to cancer and assess the potential for using these gene expression changes as a marker predictive of malignant progression in Barrett's epithelium.
Experimental Design: Microarray analysis was used to obtain individual gene expression profiles from endoscopic biopsies of nine esophageal adenocarcinomas and the Barrett's epithelia from which three of the cancers had arisen. Pooled samples from the Barrett's epithelia of six patients without cancer or dysplasia served as a reference.
Results: Barrett's epithelia from which cancer had arisen differed from the reference Barrett's epithelia primarily by underexpression of genes, many of which function in governing cell differentiation. These changes in gene expression were found even in those specimens of Barrett's epithelia from which cancer had arisen that lacked dysplasia. Each cancer differed from the Barrett's epithelium from which it had arisen primarily by an overexpression of genes, many of which were associated with tissue remodeling and invasiveness. Cancers without identifiable Barrett's epithelium differed from cancers that had arisen from a Barrett's epithelium by having an even greater number of these overexpressed genes.
Conclusions: Histologic progression from Barrett's epithelium to cancer is associated with a gradient of increasing changes in gene expression characterized by an early loss of gene function governing differentiation that begins before histologic change; gain in function of genes related to remodeling and invasiveness follows later. This correlation of histologic progression with increasing changes in gene expression suggests that gene expression changes in biopsies taken from Barrett's epithelium potentially could serve as a marker for neoplastic progression that could be used to predict risk for developing cancer.
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http://dx.doi.org/10.1158/1078-0432.CCR-04-1280 | DOI Listing |
Brief Bioinform
November 2024
Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, St Lucia, Brisbane, QLD 4072, Australia.
Regulatory genes are critical determinants of cellular responses in development and disease, but standard RNA sequencing (RNA-seq) analysis workflows, such as differential expression analysis, have significant limitations in revealing the regulatory basis of cell identity and function. To address this challenge, we present the TRIAGE R package, a toolkit specifically designed to analyze regulatory elements in both bulk and single-cell RNA-seq datasets. The package is built upon TRIAGE methods, which leverage consortium-level H3K27me3 data to enrich for cell-type-specific regulatory regions.
View Article and Find Full Text PDFBrief Bioinform
November 2024
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, 2 Sipailou, Xuanwu District, Nanjing 210096, China.
Spatial transcriptomics technologies have been extensively applied in biological research, enabling the study of transcriptome while preserving the spatial context of tissues. Paired with spatial transcriptomics data, platforms often provide histology and (or) chromatin images, which capture cellular morphology and chromatin organization. Additionally, single-cell RNA sequencing (scRNA-seq) data from matching tissues often accompany spatial data, offering a transcriptome-wide gene expression profile of individual cells.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Buk-gu, Gwangju 61005, Republic of Korea.
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex interactions among drugs and their wide-ranging effects. To address this issue, we introduce DD-PRiSM (Decomposition of Drug-Pair Response into Synergy and Monotherapy effect), a deep-learning pipeline that predicts the effects of combination therapy.
View Article and Find Full Text PDFBrief Bioinform
November 2024
Department of Electronic Engineering, Tsinghua University, 100084 Beijing, China.
Single-cell multi-omics techniques, which enable the simultaneous measurement of multiple modalities such as RNA gene expression and Assay for Transposase-Accessible Chromatin (ATAC) within individual cells, have become a powerful tool for deciphering the intricate complexity of cellular systems. Most current methods rely on motif databases to establish cross-modality relationships between genes from RNA-seq data and peaks from ATAC-seq data. However, these approaches are constrained by incomplete database coverage, particularly for novel or poorly characterized relationships.
View Article and Find Full Text PDFMol Biol Rep
January 2025
Goat Genetics and Breeding Division, ICAR-Central Institute for Research On Goats, Makhdoom, Farah, Mathura, 281 122, Uttar Pradesh, India.
Background: Extracellular matrix (ECM) proteins play a crucial role in regulating the biological properties of adherent cells. For cryopreserved fibroblasts, a favourable ECM environment can help restore their natural morphology and function more rapidly, minimizing post-thaw stress responses.
Methods And Results: This study explored the functional responses of cryopreserved enriched caprine adult dermal fibroblast (cadFibroblast) cells to structural [collagen-IV and rat tail collagen (RTC)] and adhesion ECM proteins (laminin, fibronectin, and vitronectin) under in vitro culture conditions.
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