Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Tumor Progression

Tumor Progression

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.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...

You might also read

Related Articles

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

Sort by

Same author

Neoadjuvant sintilimab plus chemotherapy in EGFR-mutant non-small cell lung cancer (NEOTIDE/CTONG2104): phase II trial and correlative genomic analysis in China.

EClinicalMedicine·2026

Same author

The Role of PD-L1 in Treatment Decision-Making for Perioperative EGFR-Mutated Lung Cancer and its Genomic Analysis.

Annals of surgical oncology·2026

Same author

LAMPAD: An Integrated Circulating Tumor DNA-Based Model for Predicting Potential Cure in Patients With Resected NSCLC.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer·2026

Same author

Adjuvant immunotherapy may have no impact on survival in patients who received neoadjuvant immunotherapy for stage II-IIIB non-small cell lung cancer.

Lung cancer (Amsterdam, Netherlands)·2026

Same author

Tubeless strategy following thoracoscopic pulmonary wedge resection: a safe and beneficial option in selected patients.

Journal of thoracic disease·2026

Same author

Cellular dynamics in cerebrospinal fluid unveils the key regulators of intracranial response to immune checkpoint inhibitors in NSCLC brain metastases.

Journal for immunotherapy of cancer·2025

Search research articles

Related Experiment Video

Updated: Jan 11, 2026

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

Published on: February 27, 2020

Quantifying Early-Stage Lung Adenocarcinoma Progression with a Radiomic Trajectory.

Zhen-Bin Qiu^1,2,3, Jiaqi Li^4,5, Shihua Dou^6,7

¹Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

NPJ Digital Medicine

|November 18, 2025

Summary

RadioTrace, a novel deep learning framework, quantifies early-stage lung adenocarcinoma progression by integrating imaging and pathology data. It offers a more accurate prognosis than traditional methods, improving clinical decision-making.

More Related Videos

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Published on: May 20, 2016

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Related Experiment Videos

Last Updated: Jan 11, 2026

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

Detection of Lung Tumor Progression in Mice by Ultrasound Imaging

Published on: February 27, 2020

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer

Published on: May 20, 2016

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Area of Science:

Oncology
Radiology
Artificial Intelligence

Background:

Accurate tumor progression assessment is crucial for early-stage lung adenocarcinoma (esLUAD).
Current histopathology grading may not fully capture intra-tumor heterogeneity.
Need for advanced methods to quantify esLUAD progression beyond traditional pathology.

Purpose of the Study:

To introduce RadioTrace, a deep contrastive learning framework for quantifying esLUAD progression.
To integrate radiomic and pathological information for a comprehensive assessment.
To develop a radiomic trajectory for predicting tumor progression and patient outcomes.

Main Methods:

Developed RadioTrace, a deep contrastive learning framework.
Integrated radiomic features from CT scans with pathological data.
Validated the framework across four multi-institutional cohorts.
Performed survival analyses, genomic, transcriptomic, and longitudinal CT analyses.

Main Results:

RadioTrace accurately predicted tumor phenotypes like spread through air spaces (STAS) and lymph node metastasis (LNM).
It served as an independent prognostic factor, showing significant survival differences (p < 0.004).
Revealed significant survival heterogeneity within the same pathological grades (p < 0.02), highlighting limitations of current grading.

Conclusions:

RadioTrace provides a quantitative and interpretable assessment of esLUAD progression.
Offers insights beyond histopathology, aiding clinical decision-making.
Demonstrates potential for improved diagnosis and treatment planning in esLUAD.