Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
INTEGRA BIOSCIENCES AG

Download Mobile App




Cancer Mutation ‘Fingerprints’ to Improve Prediction of Immunotherapy Response

By LabMedica International staff writers
Posted on 06 Mar 2026

Cancer cells accumulate thousands of genetic mutations, but not all mutations affect tumors in the same way. More...

Some make cancer cells more visible to the immune system, while others allow tumors to evade immune detection. Understanding how these mutations influence immune recognition is increasingly important for predicting which patients may benefit from immunotherapy. Researchers have now identified five dominant mutation patterns in cancer proteins that help determine how effectively the immune system can detect tumors.

Researchers from the HUN-REN Szeged Biological Research Centre (Szeged, Hungary) and the Hungarian Centre of Excellence for Molecular Medicine (HCEMM, Szeged, Hungary) analyzed nearly 9,300 cancer genomes from multiple cancer types to investigate how DNA mutations alter protein structures in tumors. When DNA is damaged by environmental factors such as ultraviolet radiation or tobacco smoke, or by internal replication errors, the resulting mutations can change amino acids—the building blocks of proteins. These changes can produce abnormal protein fragments known as neoantigens that the immune system may recognize as foreign.

The analysis revealed that most tumors are dominated by one of five recurring amino acid substitution signatures. These patterns represent distinct molecular fingerprints of how mutations alter proteins within cancer cells. Importantly, the substitution signatures also influence immune recognition. Some mutation patterns generate neoantigens that strongly activate immune responses, making tumors more visible to immune cells. Others produce weaker neoantigens, creating “cold” tumors that are harder for the immune system to detect.

The study also found that tumors dominated by a mutation pattern linked to DNA repair defects and chemical exposures often respond poorly to immune checkpoint inhibitor therapies, even when the tumors contain many mutations. The findings, published in Molecular Systems Biology, suggest that simply counting the number of mutations in a tumor may not be sufficient to predict response to immunotherapy. Instead, the specific protein-level effects of mutations may play a critical role in determining whether the immune system can recognize cancer cells.

Researchers also observed that certain immune system genes, particularly specific HLA class I variants, may improve the ability of immune cells to detect mutated tumor proteins. This means the same tumor could appear more visible to the immune system in one patient than in another. These insights may support the development of more personalized immunotherapy strategies that combine tumor genomic analysis with information about a patient’s immune genetics.

“Tumor visibility to the immune system is not determined by mutation numbers alone, but also by the protein-level patterns those mutations create,” said Dr. Máté Manczinger, senior author of the study. “These findings support a new framework for truly personalized immunotherapy, integrating tumor genomics with the patient’s immunogenetic background.”

Related Links:
HUN-REN Szeged BR
HCEMM


Platinum Member
Automated Coagulation Analyzer
Hemolumi H6
βeta-Hydroxybutyrate Reagent
β-Hydroxybutyrate LiquiColor®
Automated Urinalysis Solution
UN-9000
Gold Member
Blood-Based Protein Biomarker Solution for Alzheimer's Disease
BG-DTi2000.
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Molecular Diagnostics

view channel
Image: New findings demonstrate a blood RNA signal that may indicate ovarian cancer before conventional tests detect a tumor. (Image Credit: iStock)

Blood RNA Test May Detect Precursors to Ovarian Cancer

High-grade serous ovarian cancer is often diagnosed at an advanced stage, limiting opportunities for early intervention. The disease frequently originates in the fallopian tube as serous tubal intraepithelial... Read more

Hematology

view channel
Image: These new ANC reference ranges can help clinicians more accurately interpret neutrophil counts, reduce unnecessary testing and treatment interruptions, and help support more equitable care. (Photo courtesy of the American Society of Hematology)

New Reference Ranges Clarify Normal Neutrophil Counts in Duffy-Null Patients

Duffy-null status is a common genetic trait associated with naturally lower circulating white blood cell counts. It affects about 10% of the U.S. population and more than 66% of people with African or... Read more

Microbiology

view channel
Image: VITEK PRO combines microbial identification and antimicrobial susceptibility testing on a single platform to support routine microbiology workflows and antibiotic selection. (Photo courtesy of bioMérieux)

Automated Microbial Identification and Susceptibility System Gains FDA Clearance

Antimicrobial resistance (AMR) is a leading global public health threat, causing an estimated 1.27 million deaths annually. The growing challenge of diagnosing and treating resistant infections highlights... Read more

Pathology

view channel
AI: Artificial intelligence; CNN: Convolutional neural networks; ResNet: Residual neural network. (Xing-hua Gao from The First Hospital of China Medical University, China Image Source Link: https://www.ovid.com/jnls/cmj/fulltext/10.1097/cm9.0000000000004154~deep-learning-based-computational-pathology-technologies)

Review Highlights Progress and Validation Needs for AI in Digital Pathology

Pathology remains the gold standard for disease diagnosis, but clinical laboratories face growing demands for faster, more reproducible diagnostic and prognostic workflows. Digital pathology based on whole-slide... Read more

Industry

view channel
Image: The collaboration aims to expand access to the technology through a regulated clinical diagnostics pathway in Japan.

Partnership Aims to Bring Blood-Based Alzheimer’s Testing to Japan

Alzheimer’s disease remains a growing diagnostic challenge as populations age and cognitive impairment becomes more common. In Japan, government-supported estimates project that approximately 4.... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.