AI Prediction Model
AI Prediction Model: RNA-seq
analysis of patient tumors for predicting progression, therapeutic response and
outcome
Currently developing
tests for multiple
cancer indications
The clinical outcome of
the patient is
predicted based on 3
different scoring systems
- Immunogenicity Score is a measure of how
effectively a cancer therapy, such as immunotherapy, is able to stimulate the immune
system to recognize and attack cancer cells. It is often used to assess the likelihood
of a positive response to cancer immunotherapy. Our ImmunoInsightTM score is
calculated based on various
factors related to the interaction between the immune system and cancer cells,
including:
- Tumor
mutational burden
(TMB): TMB refers to the
number of mutations or
changes
in the DNA of cancer cells. Higher TMB generally indicates a higher likelihood
of generating neoantigens, which are unique proteins on the surface of cancer
cells that can trigger an immune response. A higher TMB is associated with a
higher immunogenicity score.
- Expression
of immune
checkpoint proteins: Immune
checkpoint proteins,
such as PD-1 and CTLA-4, are proteins that regulate the immune response. Cancer
cells can hijack these proteins to evade immune detection. Immunogenicity score
may take into consideration the expression levels of immune checkpoint proteins
on cancer cells, with higher expression levels indicating a higher likelihood of
response to immunotherapy.
- Inflammatory status of the
tumor microenvironment:
The tumor microenvironment, which consists of the surrounding cells and tissues,
can either promote or inhibit an immune response against cancer cells. An
inflamed tumor microenvironment with increased infiltration of immune cells,
such as T cells, is associated with higher immunogenicity score and better
response to immunotherapy.
- Presence of
pre-existing
immune response: Some
patients with cancer may already have an existing immune response against the
tumor. Immunogenicity score may take into consideration the presence of
pre-existing immune response, such as the presence of tumor-infiltrating
lymphocytes (TILs), which are immune cells that have infiltrated the tumor
tissue. Higher levels of TILs may indicate a higher immunogenicity score and
better response to immunotherapy.
- Therapeutic Response
Prediction
Cancer therapeutic response prediction involves using techniques to predict how well a
cancer patient is likely to respond to a particular treatment. These predictions can
help guide treatment decisions and optimize patient outcomes
- Overall Survival Prediction
Overall survival prediction is a key task in cancer prognosis. Predicting overall
survival can provide valuable information to clinicians for treatment planning, patient
counseling, and prognosis assessment.
