Grant: Project Grant
Centre hospitalier de l'Université de Montréal (CHUM)
$707,626.00
Artificial intelligence-based Development and Validation of a New Approach to Predict Efficacy of Treatment for Surgical Head and Neck Squamous Cell Carcinoma using Multi-omics (ADVANCE)
FY 2025-26
Summary
Head and neck cancers affect thousands of people in Canada each year. The usual treatment involves surgery to remove the tumor, followed by radiation therapy and sometimes chemotherapy. This can cure many patients, but the treatment is very hard on the body and can cause long-term side effects like difficulty swallowing, changes in speech, and fatigue. At the same time, some people still see their cancer come back, especially in the first two years. Right now, doctors decide how aggressive the treatment should be based mostly on what they see at diagnosis, such as the size of the tumor and whether it has spread to the lymph nodes. But this information is not always precise-so some people end up getting more treatment than they need, while others might not get enough.
Our project, called ADVANCE, will use artificial intelligence to help solve this problem. We will bring together many different types of information about each patient. This includes medical imaging like CT and MRI scans, genetic information from the tumor to see what mutations are present, special analysis of tissue samples under the microscope to look at how the cancer cells interact with the immune system, and even simple blood tests that can detect traces of tumor DNA after surgery. By combining all these pieces into one picture, we hope to build a tool that can tell doctors which patients need stronger treatments, such as new immune-based drugs, and which patients can safely receive less treatment to avoid side effects.
We will start by using information from 350 patients treated at the Centre hospitalier de l'Université de Montréal to develop and test this tool. Then we will try it out in real time with 50 new patients to see if it can fit smoothly into routine care. If it works, this approach could lead to future clinical trials and, ultimately, to a new era where cancer treatment is more personalized-stronger treatment for those who truly need it, and fewer side effects for everyone else.
Department
Program
Project Grant
Location
Quebec, Canada
Recipient Type
Not-for-profit organization or charity
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
535549
Name
Bahig Houda
Region
Québec
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Cancer Research
Theme2
Biomedical
Prcname2
Tri-Agency Interdisciplinary - CIHR TIR
Projecttitle
Artificial intelligence-based Development and Validation of a New Approach to Predict Efficacy of Treatment for Surgical Head and Neck Squamous Cell Carcinoma using Multi-omics (ADVANCE)
Programtype2
Operating Grants
Orgnameinp2
Centre hospitalier de l'Université de Montréal (CHUM)
Cihramount2
$707,626
Cihrequipment2
$0
Programname2
Project Grant
Keyworddelim
Artificial Intelligence; Genomics; Head And Neck Cancer; Immunotherapy; Multi-Omic; Oncology; Precision; Radiomics; Radiotherapy; Surgery
Abstract
Head and neck cancers affect thousands of people in Canada each year. The usual treatment involves surgery to remove the tumor, followed by radiation therapy and sometimes chemotherapy. This can cure many patients, but the treatment is very hard on the body and can cause long-term side effects like difficulty swallowing, changes in speech, and fatigue. At the same time, some people still see their cancer come back, especially in the first two years. Right now, doctors decide how aggressive the treatment should be based mostly on what they see at diagnosis, such as the size of the tumor and whether it has spread to the lymph nodes. But this information is not always precise-so some people end up getting more treatment than they need, while others might not get enough.
Our project, called ADVANCE, will use artificial intelligence to help solve this problem. We will bring together many different types of information about each patient. This includes medical imaging like CT and MRI scans, genetic information from the tumor to see what mutations are present, special analysis of tissue samples under the microscope to look at how the cancer cells interact with the immune system, and even simple blood tests that can detect traces of tumor DNA after surgery. By combining all these pieces into one picture, we hope to build a tool that can tell doctors which patients need stronger treatments, such as new immune-based drugs, and which patients can safely receive less treatment to avoid side effects.
We will start by using information from 350 patients treated at the Centre hospitalier de l'Université de Montréal to develop and test this tool. Then we will try it out in real time with 50 new patients to see if it can fit smoothly into routine care. If it works, this approach could lead to future clinical trials and, ultimately, to a new era where cancer treatment is more personalized-stronger treatment for those who truly need it, and fewer side effects for everyone else.
Competitiondate
202509
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Bahig, Houda
Approvedterm
3 ans 0 mois
Cihrcontribution2
~ $707,626~ $0~