We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
PURITAN MEDICAL

Download Mobile App




AI Predicts Tumor-Killing Cells with High Accuracy

By LabMedica International staff writers
Posted on 16 May 2024

Cellular immunotherapy involves extracting immune cells from a patient's tumor, potentially enhancing their cancer-fighting capabilities through engineering, and then expanding and reintroducing them into the body. More...

T cells, a primary type of white blood cell or lymphocyte, circulate in the blood and monitor for virally infected or cancerous cells. Among these, T cells that infiltrate solid tumors are known as tumor-infiltrating lymphocytes, or TILs. However, not all TILs effectively recognize and attack tumor cells. To address this, scientists have now employed artificial intelligence (AI) to create a predictive model that can identify the most effective TILs for use in cancer immunotherapy.

The new AI-driven predictive model, called TRTpred developed by scientists at Ludwig Cancer Research (New York, NY, USA) ranks T cell receptors (TCRs) according to their tumor reactivity. To create TRTpred, the researchers utilized 235 TCRs from patients with metastatic melanoma, already categorized as tumor-reactive or non-reactive. They input the global gene-expression profiles of the T cells harboring each TCR into a machine learning model to identify patterns distinguishing tumor-reactive T cells from their inactive counterparts. This model, enhanced with additional algorithms, supports personalized cancer treatments tailored to the unique cellular composition of each patient’s tumors.

The TRTpred model was used to analyze TILs from 42 patients with melanoma, gastrointestinal, lung, and breast cancer, pinpointing tumor-reactive TCRs with about 90% accuracy. The selection process was further refined using a secondary algorithmic filter to isolate those T cells with “high avidity”—meaning they bind strongly to tumor antigens. It was observed that T cells identified by TRTpred and this secondary filter as both tumor-reactive and high avidity were predominantly located within the tumors rather than in the surrounding stromal tissue. This aligns with previous studies suggesting that effective T cells often deeply penetrate tumor islets.

A third filter was then introduced to enhance the identification of TCRs recognizing a diverse array of tumor antigens. This filter groups TCRs based on similar physical and chemical characteristics, assuming TCRs in each group recognize the same antigen. This enhanced system, named MixTRTpred, was then tested by growing human tumors in mice, extracting TCRs from their TILs, and employing MixTRTpred to identify T cells that were tumor-reactive, had high avidity, and targeted multiple tumor antigens. The researchers then engineered mouse T cells to express these TCRs and demonstrated that these modified cells could effectively eradicate tumors when reintroduced into the mice.

“The implementation of artificial intelligence in cellular therapy is new and may be a game-changer, offering new clinical options to patients,” said Ludwig Lausanne’s Alexandre Harari, who led the study published on May 7, 2024 in Nature Biotechnology.

Related Links:
Ludwig Cancer Research


New
Gold Member
Quality Control Material
iPLEX Pro Exome QC Panel
Serological Pipet Controller
PIPETBOY GENIUS
New
Pan-Cancer Panel
TruSight Oncology 500
New
Automated Biochemical Analyzer
iBC 900
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








DIASOURCE (A Biovendor Company)

Channels

Molecular Diagnostics

view channel
Image: Combining rapid diagnostic tests with conventional serology proves to be a useful strategy for diagnosing Chagas disease (Courtesy of Adobe Stock)

Rapid Tests for Chagas Disease Improves Diagnostic Access

Chagas disease, caused by the parasite Trypanosoma cruzi, affects between six and seven million people across the Americas. It is primarily transmitted by insect vectors and remains largely underdiagnosed,... Read more

Hematology

view channel
Image: CitoCBC is the world first cartridge-based CBC to be granted CLIA Waived status by FDA (Photo courtesy of CytoChip)

Disposable Cartridge-Based Test Delivers Rapid and Accurate CBC Results

Complete Blood Count (CBC) is one of the most commonly ordered lab tests, crucial for diagnosing diseases, monitoring therapies, and conducting routine health screenings. However, more than 90% of physician... Read more

Pathology

view channel
Image: A tool uses artificial intelligence and high-resolution imaging to track senescent cells (Courtesy of Adobe Stock)

AI-Assisted Technique Tracks Cells Damaged from Injury, Aging and Disease

Senescent cells, which stop growing and reproducing due to injury, aging, or disease, play a critical role in wound repair and aging-related diseases like cancer and heart disease. These cells, however,... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.