Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

7.5K
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...
7.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The Oncology Research Information Exchange Network (ORIEN) - Building a Real-World Collaborative, Patient-driven Infrastructure for Discovery Research and Precision Oncology.

Research square·2026
Same author

The Queen and the Dark Twin: Heme, Protoporphyrin IX, and State Transitions in Liver Metabolism.

Molecules (Basel, Switzerland)·2026
Same author

Russian Dolls of Heme Metabolism in Malaria-Infected Red Blood Cells: Nested Vulnerabilities and Therapeutic Opportunities.

Pathogens (Basel, Switzerland)·2026
Same author

Targeting Infected Host Cell Heme Metabolism to Kill Malaria Parasites.

Pharmaceuticals (Basel, Switzerland)·2026
Same author

Medium-Chain Fatty Acid Receptor GPR84 Modulates Cytotoxic CD8 T-cell Antitumor Immunity through Metabolic Reprogramming.

Cancer immunology research·2026
Same author

ShinyEvents: harmonizing longitudinal data for real-world survival estimation.

NPJ precision oncology·2026

Related Experiment Video

Updated: May 7, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.4K

Spatial Transcriptomics Reveals Distinct Architectures but Shared Vulnerabilities in Primary and Metastatic Liver

Swamy R Adapa1,2, Sahanama Porshe3, Divya Priyanka Talada3,4

  • 1USF Genomics Program, College of Public Health, University of South Florida, Tampa, FL 33612, USA.

Cancers
|October 16, 2025
PubMed
Summary

Primary liver cancer (hepatocellular carcinoma) and metastatic liver tumors have distinct spatial structures and cell types. Both tumor types, however, share a common metabolic rewiring program, offering potential therapeutic targets.

Keywords:
cancer metabolismheme metabolismplasticityporphyrin metabolismprostaglandintumor microenvironment

More Related Videos

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
07:43

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

Published on: May 3, 2024

4.3K
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

649

Related Experiment Videos

Last Updated: May 7, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.4K
Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics
07:43

Author Spotlight: Exploring Advanced Therapeutic Targets in Osteosarcoma Through Spatial Transcriptomics

Published on: May 3, 2024

4.3K
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

649

Area of Science:

  • Oncology
  • Molecular Biology
  • Systems Biology

Background:

  • Hepatocellular carcinoma (HCC) and liver metastases have different origins and responses to therapy.
  • A high-resolution spatial comparison of their tumor microenvironments (TMEs) has been lacking.

Purpose of the Study:

  • To spatially compare the TMEs of primary HCC and liver metastases using high-definition spatial transcriptomics.
  • To identify distinct cellular compartments, cell states, and metabolic pathways in each tumor type.

Main Methods:

  • Applied high-definition spatial transcriptomics to one HCC and one liver metastasis specimen.
  • Analyzed gene expression, cell states, and pathway alterations.
  • Cross-validated findings with human proteomics and patient survival data.

Main Results:

  • HCC exhibited an ordered lineage architecture with dispersed tumor cells.
  • Liver metastases displayed compartmentalized domains: an invasion zone and a plasticity zone with germline-like cells.
  • Both tumor types shared a conserved metabolic program termed "porphyrin overdrive."

Conclusions:

  • HCC and liver metastases possess fundamentally different spatial architectures.
  • Liver metastases uniquely feature a germline/neural-like plasticity hub.
  • Convergent metabolic rewiring in both tumor types suggests shared therapeutic targets.