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Join the world to find immune features in breast cancer!

Research

Welcome to "Node Code Breakers: looking for patterns in lymph nodes" project

Who are we, what are we studying, and why?

The science team behind 'Node Code Breakers: looking for patterns in lymph nodes' is working at King's College London . We are mainly computational scientists, trying to identify patterns in many different biological systems that are associated with breast cancer. One major focus of our work is a type of bean-like structure called lymph nodes.

The human body contains around 500-600 of these bean-shaped organs which make up the so-called lymphatic system. These nodes, mostly located in our neck or under our arms, contain specialised cells that help us to sense and attack foreign invaders like viruses or cancer cells that do not belong in a healthy body.

When a lymph node senses something foreign, it undergoes structural changes. Several small or large dots become visible within the lymph node, signalling a location where new immune cells are produced. These patches are called germinal centres. Some immune cells derived from these germi nal centres will produce markers called Immunoglobulins, which they will use to label foreign molecules. This labelling tactic allows killer immune cells to easily track down and destroy their prey. Another type of immune cell produced in the germinal centres helps the immune system to remember which molecules are foreign. So, if in future our immune system encounters these foreign molecules again, it can then act immediately to produce labels and eliminate the invader much more rapidly.

We have found that the appearance of these dots (germinal centres) in lymph nodes can help to identify breast cancer patients who will overall live longer. Over the years, our hospitals have collected many lymph nodes from many breast cancer patients. This is very useful for our research, as we can study the differences in number, shape and the location of these dots in large numbers of lymph nodes. All this information helps us to understand more about a patient's disease, and how the lymph node reacts to the presence of foreign molecules.

If you want to know more about our research, please look at our two publications, Grigoriadis et al, 2018. Liu et al, 2021.

Our team, consisting of many computational scientists, have written sophisticated computer programs to capture the information related to size, number and locations of these dots in images of lymph nodes from breast cancer patients.

Why we need help and how you can help?

Recent technological advances enable us to perform our research much faster, however we still need to assess carefully how much we can rely on these computer programs. Are these computer programs as good as the human eye in spotting these dots? Can the computer programs find something that the human eye would miss? This is why we need your help!

We have collected a series of lymph node images and now we need your help to identify the germinal centres within them. Germinal centres can be identified as shallow pink circles as you can see in the "FIELD GUIDE" on the right hand side.

What can we do through your help?

We are interested to learn from our audiences how difficult it is to spot these germinal centres in lymph nodes. This information will help us on several levels:
(1) we will compare the results amongst our audiences;
(2) we will compare the results from the audiences with the results from pathologists, doctors specialised in looking at tissue structure, and the computer programs;
(3) we will study the similarities and the differences which will help us to further improve our computer programs.

How artificial intelligence (AI) can help our doctors?

The process of manual assessment of cancerous tissue is very time-consuming. Each pathologist can annotate 30-40 images a day. Due to increasing numbers of patients, we need to find new ways to support our pathologists.

Nowadays, AI works well on detecting patterns in images. By creating computer programs to detect germinal centres in lymph nodes, our work will support the pathological diagnoses of breast cancer patients.

With thanks to the support from