Please enter a gene
Late stages(stage IIA to IV)
Early stages(stage I to II)
KEGG pathway, GO function and target drug of the given gene.
KEGG pathway
GO function annotation
Drug target
Explore potential mechanism of immunotherapy resistance in LUSC
Althrough immunotherapy has revolutionized the treatment of lung squamous carcinoma, a significant proportion of patients which had high PDL1 expression showed resistance to immnotherapy. Based on gene expression profiles, we used virtual microdissection method to deconvolute the expression patterns and identify an immunosuppressive subtype which showed potential resistance to immune checkpoint blockade therapy. Then we defined this subtype as an Exhausted Immune class and developed an Exhausted Immune classifier to predict patients belonging to this class
Then we also constructed this database web app for clinical researchers to explore the mechanism of potential immunotherapy resistance at the multiomics level.This application consists of seven functional modules including signature expression, exhausted immune classifier, somatic mutation, microRNA, methylation, clinic and chemotherapy drugs. The dedailed usage of each module was described as below.
Signature expression
In this module,user can perfomed the co-expression analysis of given gene between exhausted immune class and rest class of LUSC cohort. The KEGG pathways, GO function and target drug of this given gene was listed in table. And user can investage expression correlation of two interested genes
Exhausted immune classifier
User can upload a lung squamous carcinoma expression matrix to predict exhausted immumne class with potential resistance to immunotherapy.
Somatic mutation
In this module,we developed 3 functional panels.Landscape of mutations panel enables user to explore overall mutation landscape of LUSC cohorts selected by tumor stages or exhausted immune class and to check amino acid changes information of individual gene among the cohort.Comparative analysis panel can make user to compare two cohorts to detect differentially mutated genes. Survival analysis panel enables user to check whether the mutation of given gene is associated with prognosis.
MicroRNA
User can browse differentially expressed microRNA between exhausted immune class and rest class, and the targeted genes of microRNA. And user can also perform correlaiton analysis of microRNA and target gene and functional enrichment analysis of the targeted genes.
Methylation
All differentially methylated CpGs between exhausted immune class and rest class can be queried by user. And the correlation between CpG methylation value and expression of corresponding gene can be performed.
Clinic
User can check association of exhausted immune class with the prognosis, gender, age, and clinical stage of LUSC patients, and can also explore whether the expression of given gene is associated with these clinical variables.
Chemotherapy drugs
User can predict chemotherapy sensitivity of patients based on expression profiles.
Please enter a gene
KEGG pathway, GO function and target drug of the given gene.
KEGG pathway
GO function annotation
Drug target
Predict exhausted immune class of patients with LUSC
Forest Plot
Differentially mutated genes between two cohorts
Explore microRNA related to immunotherapy resistance by correlating Exhausted Immune class(EIC)
Volcano plot
Differentially expressed microRNA between EIC and rest class
The experimentally validated miRNA-target genes from miRTarBase
Functional enrichment analysis
The correlation between gene expression and clinical information
Gender,tumor stage distribution of high and low gene expression groups
Gender
Tumor stages
Prediction of chemocherapy sensitive using 'pRRophetic' R package
This is an example: 61 LUSC patients from GSE30219
The generated data in this study can be downloaded.
Supplementary materials along with our study.
Early-stage(stage I to II) LUSC subtype information.
Late-stage(stage IIA to IV) LUSC subtype information.
Contact:Minglei Yang
Email:yangmlei3@mail2.sysu.edu.cn
Li Lab @Sun Yat-sen University