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Related Concept Videos

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Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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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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Related Experiment Video

Updated: Jun 14, 2025

Looking for Driver Pathways of Acquired Resistance to Targeted Therapy: Drug Resistant Subclone Generation and Sensitivity Restoring by Gene Knock-down
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Data mining reveals novel gene drivers of lenvatinib resistance in hepatocellular carcinoma.

Cyrollah Disoma1, Claudio Tiribelli2, Caecilia Sukowati3

  • 1Doctoral School of Molecular Biomedicine, Department of Life Sciences, University of Trieste, 34149 Trieste, Italy; Liver Cancer Unit, Fondazione Italiana Fegato ONLUS (Italian Liver Foundation NPO), AREA Science Park Basovizza, 34149 Trieste, Italy.

Annals of Hepatology
|June 3, 2025
PubMed
Summary
This summary is machine-generated.

This study identifies five novel genes, including SECTM1 and IFI6, associated with lenvatinib resistance in liver cancer. These findings may lead to new therapeutic strategies for hepatocellular carcinoma (HCC) patients.

Keywords:
Data miningDrug resistanceHepatocellular carcinomaLenvatinib resistance

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Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms
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Area of Science:

  • Oncology
  • Genetics
  • Bioinformatics

Background:

  • Liver cancer, particularly hepatocellular carcinoma (HCC), is a major global health concern with high mortality.
  • Lenvatinib is a first-line treatment for advanced HCC, but resistance often leads to treatment failure.
  • Lenvatinib resistance is complex and multifactorial, necessitating the identification of novel therapeutic targets.

Purpose of the Study:

  • To identify novel genes driving lenvatinib resistance in hepatocellular carcinoma (HCC).
  • To explore potential new therapeutic targets for overcoming lenvatinib resistance in HCC.

Main Methods:

  • Analysis of four public RNA-sequencing datasets (GEO database).
  • Bioinformatic analyses of differentially expressed genes, including Gene Ontology (GO) and KEGG pathway enrichment.
  • In vitro validation using HCC cell lines (Huh7 and Hep3B) treated with lenvatinib.

Main Results:

  • Five candidate genes associated with lenvatinib resistance were identified: SEZ6L2, SECTM1, FBLN7, IFI6, and NPC1L1.
  • Prognostic associations of these genes were evaluated using The Cancer Genome Atlas (TCGA) database.
  • In vitro validation confirmed increased mRNA expression of SECTM1 and IFI6 in lenvatinib-treated HCC cells.

Conclusions:

  • This research highlights the importance of identifying novel genes contributing to lenvatinib resistance in HCC.
  • The identified genes, particularly SECTM1 and IFI6, represent potential targets for future therapeutic interventions against lenvatinib-resistant HCC.