Integrated multi-omics data reveals the molecular subtypes and the contruction of novel signature to aid Immunotherapy

Abstract

AbstractMalignant cancer exhibits a severe imbalance between the active of immune response and tolerance. And the different and connection between the establishment and deficiency of the tumor immune response is still unknown entirely. Here, we used ten clustering algorithms based on five immune cells infiltration matrix to identified two specific molecular subtypes and determine its potential clinical outcomes and immune response effect. The cluster A subtype can be called the cold inflammatory subtype, which revealed the worst prognosis. And the cluster B can be identified as hot inflammatory subtype with high activated immune-related pathways. Then we used the WGCNA algorithms and limma to confirm the driven genes between the cluster A and B. 67 genes were identified the cluster A signature genes, and based on that we used the ssgsea algorithm to quantize the two subtypes. We confirmed the high score group had high activated level of immune activity pathways and better survival rate. The tumorigenesis-associated pathways were analysed in low score group, indicating active cell proliferation may be associated with poor prognosis. An in-silico drug screen predicted the erlotinib can be an effective compound in low score group based on the lung cancer cell line. Our research confirmed that the score can worked as an effective immunotherapy index, which provide a promising therapeutic strategies on immune therapeutics for lung adenocarcinoma.