AI Analysis of Cancer Mutations may Improve Therapy

Cancer has many faces - no wonder, then, that the range of cancer-causing mutations is huge as well. The totality of such genomic alterations in an individual is what experts call a "mutational landscape." These landscapes differ from one another depending on the type of cancer. And even people suffering from the same cancer often have different mutation patterns.

Researchers have already catalogued the mutational landscapes of numerous types of cancer. Somatic structural variants (SVs) have been shown to account for more than half of all cancer-driving mutations. These are those mutations in cells that emerge over the course of life - such as when copying errors creep into the DNA during cell division - and thereby alter the chromosome structure. They are not inherited and are found only in affected cells and in their daughter cells. As we age, such genomic alterations become more numerous, and a person's mutational landscape increasingly comes to resemble a unique mosaic.

Although somatic SVs play a crucial role in cancer development, relatively little is known about them. "There is a lack of methods that analyze their effects on cell function," explains Dr. Ashley Sanders, who heads the Genome Stability and Somatic Mosaicism Lab at the Max Delbrück Center. That's changing thanks to new research findings, which Sanders recently published in the journal Nature Biotechnology along with the European Molecular Biology Laboratory (EMBL). "We developed a computational analysis method to detect and identify the functional effects of somatic SVs," she reports. This enabled the team to understand the molecular consequences of individual somatic mutations in different leukemia patients, giving them new insights into the mutation-specific alterations. Sanders says it may also be possible to use these findings to develop therapies that target the mutated cells, adding that “they open up exciting new avenues for personalized medicine."

Their calculations are based on data from Strand-seq - a special single-cell sequencing method that Sanders played an instrumental role in developing and that was first introduced to the scientific community in 2012. This technique can examine a cell’s genome in much greater detail than conventional single-cell sequencing technologies. Thanks to a sophisticated experimental protocol, the Strand-seq method can independently analyze the two parental DNA strands (one from the father and one from the mother). With conventional sequencing methods, distinguishing such homologs - chromosomes that are similar in shape and structure but not identical - is nearly impossible. "By resolving the individual homologs within a cell, somatic SVs can be identified much better than with other methods," explains Sanders. The approach used for doing this was described by the researcher and her colleagues in a paper that appeared in Nature Biotechnology in 2020.

The research team is part of the joint research focus “Single-Cell Approaches for Personalized Medicine” of the Berlin Institute of Health at Charité (BIH), Charité - Universitätsmedizin Berlin, and the Max Delbrück Center.

Building on this work, they are now able to also determine the positions of nucleosomes in each cell. Nucleosomes are units of DNA wrapped around protein complexes called histones, and play a crucial role in organizing chromosomes. The position of nucleosomes can change during gene expression, with the type of wrapping revealing whether or not a gene is active. Sanders and her colleagues developed a self-learning algorithm to compare the gene activity of patient cells with and without somatic SV mutations, allowing them to determine the molecular impact of the structural variants.

"We can now take a sample from a patient, look for the mutations that led to the disease, and also learn the signaling pathways that the disease-causing mutations disrupt," explains Sanders. For example, the team was able to identify a rare but very aggressive mutation in a leukemia patient. The nucleosome analysis provided the researchers with information about the signaling pathways involved, which they used to specifically inhibit the growth of cells containing the mutation. "This means that a single test tells us something about the cellular mechanisms involved in cancer formation," says Sanders. "We can eventually use this knowledge to develop personalized treatments, guided by each patient’s unique condition."

Jeong H, Grimes K, Rauwolf KK, Bruch PM, Rausch T, Hasenfeld P, Benito E, Roider T, Sabarinathan R, Porubsky D, Herbst SA, Erarslan-Uysal B, Jann JC, Marschall T, Nowak D, Bourquin JP, Kulozik AE, Dietrich S, Bornhauser B, Sanders AD, Korbel JO.
Functional analysis of structural variants in single cells using Strand-seq.
Nat Biotechnol. 2022 Nov 24. doi: 10.1038/s41587-022-01551-4

Most Popular Now

Philips and Medtronic Advocacy Partnersh…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Medtronic Neurovascular, a leading innovator in neurovascular therapies, today announced a strategic advocacy partnership. Delivering timely stroke...

New AI Tool Predicts Protein-Protein Int…

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool...

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

New Research Shows Promise and Limitatio…

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

Hampshire Emergency Departments Digitise…

Emergency departments in three hospitals across Hampshire Hospitals NHS Foundation Trust have deployed Alcidion's Miya Emergency, digitising paper processes, saving clinical teams time, automating tasks, and providing trust-wide visibility of...

MEDICA HEALTH IT FORUM: Success in Maste…

11 - 14 November 2024, Düsseldorf, Germany. How can innovations help to master the great challenges and demands with which healthcare is confronted across international borders? This central question will be...

A "Chemical ChatGPT" for New M…

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model - a kind of...

Siemens Healthineers co-leads EU Project…

Siemens Healthineers is joining forces with more than 20 industry and public partners, including seven leading stroke hospitals, to improve stroke management for patients all over Europe. With a total...

MEDICA and COMPAMED 2024: Shining a Ligh…

11 - 14 November 2024, Düsseldorf, Germany. Christian Grosser, Director Health & Medical Technologies, is looking forward to events getting under way: "From next Monday to Thursday, we will once again...

In 10 Seconds, an AI Model Detects Cance…

Researchers have developed an AI powered model that - in 10 seconds - can determine during surgery if any part of a cancerous brain tumor that could be removed remains...