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Overview of Exosomes01:36

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Exosomes are stable, lipid bilayer-enclosed vesicles capable of crossing biological barriers. They can carry a wide range of molecules required for intercellular communication. Once exosomes are released from the cell where they originated, they enter a recipient cell through various pathways such as fusion, receptor-mediated endocytosis, macropinocytosis, and phagocytosis.
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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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Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
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Related Experiment Video

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Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool
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Exosome-related lncRNA score: A value-based individual treatment strategy for predicting the response to

Zhan Yang1, Xiaoting Zhang2, Ning Zhan2

  • 1Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.

Cancer Medicine
|May 29, 2024
PubMed
Summary

A new score based on exosomes-related long non-coding RNAs (lncRNAs) predicts clear cell renal cell carcinoma (ccRCC) patient survival and immunotherapy response. This score correlates with tumor characteristics and immune microenvironment, identifying EMX2OS as a potential therapeutic target.

Keywords:
ceRNA networkclear cell renal cell carcinomaexosomelncRNAmachine learningprecision medicinetumor microenvironment

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Area of Science:

  • Oncology
  • Molecular Biology
  • Immunotherapy

Background:

  • Exosomes mediate intercellular communication in clear cell renal cell carcinoma (ccRCC).
  • Long non-coding RNAs (lncRNAs) are involved in ccRCC tumorigenesis and progression.

Purpose of the Study:

  • To develop an exosomes-related lncRNA score for predicting immunotherapy response in ccRCC.
  • To construct a competing endogenous RNA (ceRNA) network for identifying potential targeted drugs in ccRCC.

Main Methods:

  • Utilized TCGA database for ccRCC patient data.
  • Identified exosomes-related lncRNAs (ERLRs) using Pearson correlation analysis.
  • Constructed a prognostic score using LASSO and multivariate Cox regression.
  • Analyzed immune microenvironment and drug susceptibility differences between risk groups.
  • Built a ceRNA network via machine learning to explore therapeutic targets.

Main Results:

  • A 4-ERLRs-based score was developed, with higher scores indicating poorer prognosis.
  • The score accurately predicted prognosis in training and validation cohorts.
  • High-score patients showed poor survival, advanced stage, higher tumor mutational burden, and increased immunosuppressive cells.
  • The EMX2OS/hsa-miR-31-5p/TLN2 axis was identified as a potential therapeutic pathway.

Conclusions:

  • A novel ERLRs-based score effectively predicts ccRCC patient survival and is linked to immune microenvironment and clinicopathological features.
  • The identified EMX2OS/hsa-miR-31-5p/TLN2 axis offers potential new avenues for ccRCC targeted therapy.