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Related Concept Videos

Cancer-Critical Genes II: Tumor Suppressor Genes01:05

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Cancer-Critical Genes I: Proto-oncogenes01:33

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Cancers Originate from Somatic Mutations in a Single Cell02:21

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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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MicroRNAs01:22

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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
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lncRNA - Long Non-coding RNAs02:39

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In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
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Updated: May 29, 2025

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
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Exploring genome-transcriptome correlations in cancer.

Michael Ronemus1, Daniel Bradford1, Zachary Laster1

  • 1Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, U.S.A.

Biochemical Society Transactions
|February 6, 2025
PubMed
Summary
This summary is machine-generated.

Genomic copy number variation (CNV) significantly impacts gene expression, especially in cancer. Understanding these complex interactions requires advanced multi-omic sequencing and computational analysis for better cancer research and therapies.

Keywords:
copy number variationsdosage compensationgenome-transcriptome relationshipstromal mutations

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Area of Science:

  • Genomics
  • Transcriptomics
  • Cancer Biology

Background:

  • Genomic copy number variation (CNV) influences gene expression.
  • Understanding these interactions is crucial for cancer biology.
  • Human cancers present a complex and heterogeneous landscape.

Purpose of the Study:

  • To examine the complex relationship between CNV and gene expression.
  • To highlight the relevance of CNV-gene expression links in cancer.
  • To discuss challenges and advances in studying these interactions.

Main Methods:

  • Review of historical genometranscriptome correlation studies.
  • Discussion of computational algorithms for genomic analysis.
  • Exploration of high-throughput single-cell multi-omic sequencing technologies.

Main Results:

  • CNV-gene expression relationships are complex and challenging to elucidate.
  • Single-cell multi-omic technologies offer potential for refined understanding.
  • Integrated genomic and transcriptomic analyses provide novel insights.

Conclusions:

  • Advancing cancer research necessitates integrated genomic and transcriptomic analyses.
  • Understanding tumor evolution and heterogeneity is key.
  • Improved insights can inform therapeutic strategies.