Product introduction

Clinical application

Multigene transcriptomic profiling assesses recurrence risk in patients with lung cancer and helps physicians develop individualized treatment plans.

Four characteristics used to group patients

1. Whether patients receive chemotherapy.
2. Normal and abnormal expression subtypes of gene clusters for nine driver genes of lung cancer, namely ALK, BRAF, EGFR, MET, NTRK, RAS, RET, ROS1, TP53, and two immunotherapy target genes, PDCD1 and CTLA4;
3. Pathological subgroups, including stage I and stages II–IV.
4. Age group (65 years or younger, or over 65).

Recurrence risk assessment model

The recurrence model accurately classifies cancer patients into about 33,000 combinations based on 4 features taken from the population. Using big data AI algorithms, corresponding to each feature taken, we developed 30 recurrence risk assessment models for different populations for research, and for each patient, personalized matching 15 recurrence models, resulting in 15 recurrence scores, comprehensive recurrence risk, and finally recommending 1 personalized treatment plan.

Treatment protocol recommendation

1. To determine whether or not to have chemotherapy:
   1. a. The risk of recurrence is divided into low, medium and high risk groups.
   2. b. Low-risk groups do not require chemotherapy; medium- to high-risk groups require chemotherapy; and high-risk groups require more aggressive treatment.
2. To guide targeted drug usage (further clinical validation required):
   1. a. For people at high risk of abnormal expression of the driver gene cluster: try the targeted drug corresponding to that gene.
   2. b. For people at high risk of abnormal expression of the immune gene cluster: try the immunotherapy corresponding to that gene.

Technical advantages

1. U.S. scientists

The technology leader is a core member of Genomic Health’s "Breast Cancer 21-Gene Recurrence Score", which has achieved significant success in the United States and Europe.

2. Independent patents

Years of research and development, in-house patented genetic screening and modeling algorithms.

3. Based on NGS sequencing

This approach uses next-generation sequencing (NGS). Other products use qPCR or gene chips.

4. 20+ years of industrial research results

Using big data from the latest scientific research in the field of lung cancer molecules over the last 20 years.

Tests and performance

1. Chemotherapy regimen assessment

2. Driver gene, immunotherapy target gene expression

3. Pathological staging population

4. Different age groups