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Related Concept Videos

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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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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The Tumor Microenvironment02:17

The Tumor Microenvironment

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Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...
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MicroRNAs01:22

MicroRNAs

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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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Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

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Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
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Regulation of Angiogenesis and Blood Supply01:24

Regulation of Angiogenesis and Blood Supply

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Rapidly dividing tumors, embryos, and wounded tissues require more oxygen than usual, lowering the oxygen concentration in the blood. At low oxygen or hypoxic conditions, an oxygen-sensitive transcription factor called the hypoxia-inducible factor 1 or HIF1 is activated. HIF1 is a dimeric protein of alpha (ɑ) and beta (β) subunits.  Under optimal oxygen conditions, HIF1β is present in the nucleus while HIF1ɑ remains in the cytosol. HIF1ɑ is hydroxylated by prolyl...
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  9. Predictive And Prognostic Markers
  11. Hypoxia-related Lncrna Correlates With Prognosis And Immune Microenvironment In Uveal Melanoma.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Hypoxia-related Lncrna Correlates With Prognosis And Immune Microenvironment In Uveal Melanoma.

Related Experiment Video

Repression of Multiple Myeloma Cell Growth In Vivo by Single-wall Carbon Nanotube SWCNT-delivered MALAT1 Antisense Oligos
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Repression of Multiple Myeloma Cell Growth In Vivo by Single-wall Carbon Nanotube SWCNT-delivered MALAT1 Antisense Oligos

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Hypoxia-related lncRNA correlates with prognosis and immune microenvironment in uveal melanoma.

Yu Chen1,2, Shen Chen3, Zhenkai Wu4

  • 1Department of Ophthalmology, Hunan Key Laboratory of Ophthalmology, Xiangya Hospital, Central South University, Changsha, China.

Cancer Cell International
|October 9, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study identifies hypoxia-related long non-coding RNAs (HRLs) as potential biomarkers for uveal melanoma (UVM) prognosis. A novel HRL signature can predict patient outcomes and guide immunotherapy strategies for UVM.

Keywords:
Immune microenvironmentPrognosisRNA-seqRisk signature

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Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • Hypoxia-related genes influence solid tumor prognosis.
  • The role of hypoxia-related long non-coding RNAs (HRLs) in uveal melanoma (UVM) is not well understood.
  • Identifying prognostic HRLs in UVM is crucial for improving patient outcomes.

Purpose of the Study:

  • To identify HRLs associated with UVM prognosis.
  • To develop a novel risk signature for predicting UVM patient outcomes.
  • To explore the association between HRLs and immune features in UVM.

Main Methods:

  • Utilized The Cancer Genome Atlas data from 80 UVM samples.
  • Screened prognostic HRLs using Cox univariate and Pearson correlation analyses.
  • Constructed an HRL signature with Lasso analysis and performed gene enrichment analysis.
Uveal melanoma
  • Assessed cell proliferation, invasion, migration, inflammatory factors, and macrophage polarization in vitro.

    • Main Results:

    • Identified 12 prognostic HRLs, forming a risk signature significantly correlated with UVM patient survival.
    • Found HRLs associated with immune checkpoints, suggesting potential immunotherapy targets.
    • Observed enrichment of immune-related pathways in the high-risk group.
    • LINC02367, a protective HRL, impacted UVM cell proliferation, migration, and macrophage polarization, influencing the immune microenvironment.

    Conclusions:

    • Developed a novel HRL signature for predicting UVM prognosis.
    • HRLs represent promising biomarkers and therapeutic targets for UVM treatment.