Hans algorithm

The Hans algorithm is a tool used by pathologists to classify diffuse large B cell lymphoma (DLBCL) into different subtypes based on the expression of specific proteins in the cancer cells. DLBCL is the most common type of non-Hodgkin lymphoma, and it can be divided into two main subtypes: germinal center B-cell-like (GCB) and activated B-cell-like (ABC). These subtypes behave differently, respond to treatment differently, and can affect a patient’s prognosis. The Hans algorithm helps pathologists make this distinction by examining specific proteins in the cancer cells.

How is the Hans algorithm used?

The Hans algorithm helps classify diffuse large B cell lymphoma into the GCB or ABC subtype. This classification is important because these two subtypes can have different outcomes and may respond to treatments differently. Knowing the subtype of DLBCL can help oncologists tailor treatment plans and give patients a better understanding of their disease. In some cases, one subtype may be associated with a better prognosis or response to certain therapies, while the other subtype may require more aggressive treatment.

How is the Hans algorithm performed?

The Hans algorithm is based on the results of a test called immunohistochemistry (IHC), which is used to look for specific proteins on the surface of the lymphoma cells. These proteins help determine the subtype of diffuse large B cell lymphoma. The Hans algorithm looks at the expression of three key proteins:

1. CD10: A protein found on the surface of some lymphoma cells.
2. BCL6: A protein that plays a role in the development of certain types of lymphomas.
3. MUM1: A protein involved in the regulation of cell growth and development.

The pathologist performs the test by treating the tissue sample with antibodies that bind to these proteins. When the antibodies bind, they cause the cells to change color, which the pathologist can see under a microscope. The pathologist can use the Hans algorithm to classify the diffuse large B cell lymphoma as either GCB or ABC subtype based on whether these proteins are present or absent.

What do the results mean?

The results of the Hans algorithm will classify the diffuse large B cell lymphoma into one of two subtypes:

• Germinal center B-cell-like (GCB): If the lymphoma cells express CD10 or a combination of CD10 and BCL6 but not MUM1, the lymphoma is classified as GCB subtype. This subtype tends to have a better prognosis and may respond more favorably to standard chemotherapy treatments.
• Activated B-cell-like (ABC): If the lymphoma cells express MUM1 and lack CD10 or have a combination of BCL6 and MUM1, the lymphoma is classified as ABC subtype. This subtype tends to be more aggressive and may have a poorer prognosis compared to the GCB subtype.

How does the Hans algorithm affect treatment for diffuse large B cell lymphoma?

The classification of diffuse large B cell lymphoma into GCB or ABC subtype using the Hans algorithm can influence treatment decisions. Patients with the GCB subtype often respond well to standard chemotherapy regimens, such as R-CHOP, which combines chemotherapy with a drug called rituximab. However, patients with the ABC subtype may require more aggressive treatments or additional targeted therapies, as this subtype is more resistant to standard treatments. In some cases, clinical trials may be recommended for patients with the ABC subtype to explore newer, more effective therapies.