Gene cluster expression analysis for personalized lung cancer therapy

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Gene cluster expression analysis for personalized lung cancer therapy
ImmunotherapyCancerGene Expression
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About 30% of lung cancer patients are accessible to targeted therapy or immunotherapy based on the current criteria.

May 23 2024Xia & He Publishing Inc. Background and objectives In this study, a novel gene cluster expression analysis was introduced with a goal to potentially expand the treatments to more patients based on the proposed criteria.

Methods Selected gene expression omnibus data sets were downloaded, normalized, and analyzed. A univariate recurrence prediction model was built based on the receiver operating characteristic, for which an optimal cutoff was determined to set abnormality status, called the gene cluster expression index . Recurrence and survival risks were calculated and compared between two subgroups indexed by the GCEI.

Results The recurrence risks of the patient subgroups with abnormally expressed clusters with GCEI=1 were much higher than for the corresponding normal subgroup with GCEI=0. The higher risks ranged from 120–300% that of the corresponding lower-risk group. Conclusions Gene cluster expression index can be used to classify lung cancers with dramatically different recurrence risks and the recurrence risk of the patient group with index 1 is typically 20% to 200% higher than the group with index 0. We expect that the higher risk group of index 1 may also be suitable for the corresponding targeted therapy or immunotherapy. Therefore, it may be used to guide targeted therapy or immunotherapy when the conventional companion tests give no recommendation.

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Immunotherapy Cancer Gene Expression Lung Cancer

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