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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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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
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The Ras-gene-encoded proteins are regulators of signaling pathways controlling cell proliferation, differentiation, or cell survival. The Ras-gene family in humans constitutes three primary members—the HRas, NRas, and KRas. These genes code for four functionally distinct yet closely related proteins—the HRas, NRas, KRas4A, and KRas4B. The involvement of mutant Ras genes in human cancer was first discovered in 1982 and is among the most common causes of human tumorigenesis.
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Under normal conditions, most adult cells remain in a non-proliferative state unless stimulated by internal or external factors to replace lost cells. Abnormal cell proliferation is a condition in which the cell's growth exceeds and is uncoordinated with normal cells. In such situations, cell division persists in the same excessive manner even after cessation of the stimuli, leading to persistent tumors. The tumor arises from the damaged cells that replicate to pass the damage to the...
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Tumor suppressor genes are normal genes that can slow down cell division, repair DNA mistakes, or program the cells for apoptosis in case of irreparable damage. Hence, they play an essential role in preventing the proliferation of damaged cells.
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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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  9. Predictive And Prognostic Markers
  11. Unraveling The Role Of Low-density Lipoprotein-related Genes In Lung Adenocarcinoma: Insights Into Tumor Microenvironment And Clinical Prognosis

Unraveling the role of low-density lipoprotein-related genes in lung adenocarcinoma: Insights into tumor microenvironment and clinical prognosis

Pengpeng Zhang1, Xinyi Wu1, Dingli Wang1

  • 1Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.

Environmental Toxicology
|March 15, 2024

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Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
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Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

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Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma
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Network Pharmacology Prediction and Experimental Validation of Trichosanthes-Fritillaria thunbergii Action Mechanism Against Lung Adenocarcinoma

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View abstract on PubMed

Summary
This summary is machine-generated.

This study reveals how low-density lipoprotein (LDL) genes impact lung adenocarcinoma (LUAD) and introduces an LDL-associated signature (LAS) for patient prognostication and targeted therapy selection.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • The link between low-density lipoprotein (LDL) and cancer (oncogenesis) is of significant interest.
  • However, its specific role in lung adenocarcinoma (LUAD) requires further investigation.
  • This study explores the function of LDL-related genes (LRGs) in LUAD.

Purpose of the Study:

  • To investigate the role of LDL-related genes (LRGs) in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD).
  • To develop an LDL-associated signature (LAS) for predicting patient outcomes and guiding treatment decisions.

Main Methods:

  • Single-cell transcriptomics and computational analyses (AUCell, UCell, singscore, ssGSEA, AddModuleScore) were used to examine LRG expression.
  • CellChat analyzed cellular interactions in LDL_low and LDL_high groups.
Keywords:
LDL‐associated signature (LAS)LDL‐related genes (LRGs)low‐density lipoprotein (LDL)prognosis

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  • A machine learning framework (CoxBoost+Ridge) developed the LAS.
  • Genomic, pathway, immune, and drug sensitivity analyses were performed on LAS stratifications.

    • Main Results:

    • Increased cellular crosstalk was observed in the LDL_high group.
    • The developed LAS demonstrated superior prognostic accuracy compared to existing LUAD models.
    • Higher LAS indices correlated with poorer outcomes, reduced immune surveillance, and increased pathways promoting tumor growth.
    • Patients with high LAS showed increased susceptibility to paclitaxel and gemcitabine.

    Conclusions:

    • LRGs play a significant role in the LUAD TME.
    • The novel LAS serves as a valuable prognostic tool for LUAD patients.
    • Findings highlight potential therapeutic targets and the clinical utility of the LAS.