Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/037531

Exploring genes of rectal cancer for new treatments based on protein interaction network

wenjing Teng·Yan Li·Chao Zhou
View original source ↗Export metadata ↓

Abstract

ObjectiveTo develop a protein-protein interaction network of rectal cancer, which is based on genetic genes as well as to predict biological pathways underlying the molecular complexes in the network. In order to analyze and summarize genetic markers related to diagnosis and prognosis of rectal cancer.\n\nMethodsthe genes expression profile was downloaded from OMIM (Online Mendelian Inheritance in Man) database; the protein-protein interaction network of rectal cancer was established by Cytoscape; the molecular complexes in the network were detected by Clusterviz plugin and the pathways enrichment of molecular complexes were performed by DAVID online and Bingo (The Biological Networks Gene Ontology tool).\n\nResults and DiscussionA total of 127 rectal cancer genes were identified to differentially express in OMIM Database. The protein-protein interaction network of rectal cancer was contained 966 nodes (proteins), 3377 edges (interactive relationships) and 7 molecular complexes (score>7.0). Regulatory effects of genes and proteins were focused on cell cycle, transcription regulation and cellular protein metabolic process. Genes of DDK1, sparcl1, wisp2, cux1, pabpc1, ptk2 and htral were significant nodes in PPI network. The discovery of featured genes which were probably related to rectal cancer, has a great significance on studying mechanism, distinguishing normal and cancer tissues, and exploring new treatments for rectal cancer.

Explore related subjects

Cancer BiologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

wenjing Teng, Yan Li, Chao Zhou. 2016-01-21. Exploring genes of rectal cancer for new treatments based on protein interaction network. https://doi.org/10.1101/037531

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Stepwise Evolution and Epistatic Interaction of Driver Mutations from Endometrial Hyperplasia to Carcinoma

To characterize early oncogenesis, pathologically identified pre-cancerous tissue can be analyzed for the presence of cancer drivers. Here, we argue that in such studies, analyses of the driver status of variants, of the association between step-specific prevalence and progression through tumorigenesis, and of driver co-occurrence and mutual exclusivity should be accompanied by estimates of inherent mutation rate of variants and presented within an evolutionary framework of selective epistasis. To illustrate this point, we examine the transition of endometrial tissue from atypical hyperplasia to carcinoma. We apply a step-specific analysis, demonstrating that the strength of selection on somatic driver mutations promoting cell division and survival differs between hyperplasia to carcinoma. We demonstrate that mutations of PTEN, which are highly prevalent in carcinomas and have been argued to exert substantial driver effects, exhibit an even larger effect of increasing cellular division and survival within developing hyperplasias. A determination of cooccurrence or mutual exclusivity may be a product of genes sharing or differing in underlying sources of mutation, as opposed to a product of biological interaction and selection. By accounting for tumor-specific mutational processes that influence co-occurrence, we calculate epistatic selective intensities between pairs of drivers. Mutations of KRAS and FGFR2 are often mutually exclusive and were indeed found to exhibit significant antagonistic selective epistasis. However, mutations of PIK3CA and PIK3R1, which also have been identified as showing mutual exclusivity, do not demonstrate significant antagonistic selective epistasis. Thus, evidence of mutually exclusivity is insufficient to determine epistasis. Accordingly, the application of quantitative approaches that distinctly analyze mutation and selection on cancer variants has the potential to substantially illuminate the trajectory of tumorigenesis and cancer progression.

Cancer Biology↗
bioRxiv2026

Comprehensive transcriptome data of melittin- and un-treated murine hepatoma Hepa 1-6 cells

Melittin, the principal bioactive peptide of bee venom, exerts potent antitumor activity against hepatocellular carcinoma (HCC). However, the comprehensive transcriptomic alterations it elicits in hepatoma cells remain poorly characterized. Here, we present an integrated transcriptome dataset from melittin- and un-treated murine Hepa 1-6 hepatoma cells, encompassing messenger RNA (mRNA) and microRNA (miRNA) expression profiles. Cells were exposed to 4 g/mL melittin in serum-free DMEM for 20 min, and total RNA was subjected to ribosomal RNA-depleted strand-specific RNA sequencing on an Illumina NovaSeq6000 platform (paired-end 150 bp) and small RNA sequencing on an Illumina HiSeq2500 platform (single-end 50 bp). Raw data were processed using Cutadapt to remove adapters and low-quality reads, yielding clean datasets with Q20 [≥] 99.85%, Q30 [≥] 98.48%, and valid data ratios exceeding 85%. All raw and processed sequencing data are publicly available. This transcriptomic resource provides a valuable resource and basis for elucidating the regulatory networks underlying melittin-induced anti-hepatoma effects. DatasetThe dataset can be accessed through the National Genomics Data Center, China National Center website by searching with the BioProject accession number PRJCA065485 Reviewers may use this link for anonymous access during the review process. Direct URL to data: Genome Sequence Archive-CNCB-NGDC. Dataset LicenseCC BY 4.0

Cancer Biology↗
bioRxiv2026

LDB1-dependent enhancer connectivity defines T-cell leukemia identities and masks metabolic vulnerabilities

Spatial enhancer connectivity is fundamental to proper gene regulation. Enhancer dysregulation has emerged as a hallmark of cancers, including T-cell acute lymphoblastic leukemias (T-ALL). T-ALL are aggressive malignancies characterized by marked transcriptional heterogeneity driven by distinct stages of developmental arrest and diverse noncoding alterations. How these cancers co-opt nuclear architecture to rewire enhancer connectivity remains poorly understood. Here, we report that the LDB1 chromatin architectural complex is an essential mediator of enhancer-oncogene looping that sustains oncogenic transcriptional programs across multiple T-ALL subtypes. Integrating bulk and single-cell transcriptomic data from patients with T-ALL and healthy hematopoietic controls, we show that the LDB1-dependent regulatory circuitry defines the molecular identities of distinct T-ALL subtypes while restricting plasticity toward alternative cell states. LDB1 loss dismantles chromatin looping among cell state-defining enhancers liberating them to form promiscuous interactions with nearby genes. This enhancer rewiring stimulates expression of key metabolic genes, creating a mevalonate pathway dependency exploitable with statin treatment. Our study establishes LDB1 as a central executor of T-ALL regulatory circuitry and more broadly illustrates chromatin rewiring as a source of targetable dependencies in cancer.

Cancer Biology↗