Dataset Information

Transcriptional Profiling of Advanced Urothelial Cancer Predicts Prognosis and Response to Immunotherapy.

ABSTRACT: Recent investigations reported that some subtypes from the Lund or The Cancer Genome Atlas (TCGA) classifications were most responsive to PD-L1 inhibitor treatment. However, the association between previously reported subtypes and immune checkpoint inhibitor (ICI) therapy responsiveness has been insufficiently explored. Despite these contributions, the ability to predict the clinical applicability of immune checkpoint inhibitor therapy in patients remains a major challenge. Here, we aimed to re-classify distinct subtypes focusing on ICI responsiveness using gene expression profiling in the IMvigor 210 cohort (n = 298). Based on the hierarchical clustering analysis, we divided advanced urothelial cancer patients into three subgroups. To confirm a prognostic impact, we performed survival analysis and estimated the prognostic value in the IMvigor 210 and TCGA cohort. The activation of CD8+ T effector cells was common for patients of classes 2 and 3 in the TCGA and IMvigor 210 cohort. Survival analysis showed that patients of class 3 in the TCGA cohort had a poor prognosis, while patients of class 3 showed considerably prolonged survival in the IMvigor 210 cohort. One of the distinct characteristics of patients in class 3 is the inactivation of the TGF? and YAP/TAZ pathways and activation of the cell cycle and DNA replication and DNA damage (DDR). Based on our identified transcriptional patterns and the clinical outcomes of advanced urothelial cancer patients, we constructed a schematic summary. When comparing clinical and transcriptome data, patients with downregulation of the TGF? and YAP/TAZ pathways and upregulation of the cell cycle and DDR may be more responsive to ICI therapy.

SUBMITTER: Baek SW

PROVIDER: S-EPMC7084828 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Transcriptional Profiling of Advanced Urothelial Cancer Predicts Prognosis and Response to Immunotherapy.

Baek Seung-Woo SW Jang In-Hwan IH Kim Seon-Kyu SK Nam Jong-Kil JK Leem Sun-Hee SH Chu In-Sun IS

International journal of molecular sciences 20200308 5

Recent investigations reported that some subtypes from the Lund or The Cancer Genome Atlas (TCGA) classifications were most responsive to PD-L1 inhibitor treatment. However, the association between previously reported subtypes and immune checkpoint inhibitor (ICI) therapy responsiveness has been insufficiently explored. Despite these contributions, the ability to predict the clinical applicability of immune checkpoint inhibitor therapy in patients remains a major challenge. Here, we aimed to re- ...[more]

PMID: 32182655

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Project description:BackgroundImmune checkpoint blockade is effective against many cancer types, but few patients achieve a complete response (OR). Therefore, effective prognostic biomarkers are needed for metastatic gastric cancer (GC) patients after immune treatment. The present study assessed the value of hematological parameters as markers of the effectiveness of immune checkpoint blockade among metastatic GC patients.MethodsThis retrospective study included patients with metastatic GC who underwent multiline chemotherapy including at least two courses of immunotherapy between September 2018 and December 2020. Patient and tumor characteristics were tested for prognostic significance by analysis of variance or chi-square test. Kaplan-Meier and Cox analyses were performed to identify factors associated with progression-free survival (PFS).ResultsSixty-one GC patients (mean age 55.61±11.97 years, range 23-80 years, 24 females, and 37 males) were included, and 27, 9 and 25 cases had organ only, peritoneum only, and simultaneous organ and peritoneum metastasis, respectively. Gastrectomy was performed in 24 cases, and there was no operative treatment in the other 37 cases, while all patients received two or more lines of chemotherapy. After immune treatment, 13 patients achieved a partial response (PR), 16 stable disease (SD), and 32 progressive disease (PD). The median PFS was 4.93±3.47 months. An alkaline phosphatase (ALP) level >225 U/L, a lactate dehydrogenase level (LDH) >299 U/L, and a body mass index (BMI) >24 kg/m2 were associated with a short PFS (P=0.01, P=0.008, and P=0.039, respectively). A Cox multivariate proportional hazard model indicated that higher ALP level was a significant prognostic indicator for adverse PFS.ConclusionsOur data show an ALP cutoff of 225 U/L offered good prognostic sensitivity for HER2-negative metastatic GC. ALP measurement represents a convenient, cost-effective, and relatively sensitive screening tool, and prospective studies involving its evaluation in addition to other biomarkers in metastatic GC patients are indicated.

Project description:Objective: This study used homologous recombination (HR) related signatures to develop a clinical prediction model for screening immune checkpoint inhibitors (ICIs) advantaged populations and identify hub genes in advanced metastatic urothelial carcinoma. Methods: The single-sample gene enrichment analysis and weighted gene co-expression network analysis were applied to identify modules associated with immune response and HR in IMvigor210 cohort samples. The principal component analysis was utilized to determine the differences in HR-related module gene signature scores across different tissue subtypes and clinical variables. Risk prediction models and nomograms were developed using differential gene expression analysis associated with HR scores, least absolute shrinkage and selection operator, and multivariate proportional hazards model regression. Additionally, hub genes were identified by analyzing the contribution of HR-related genes to principal components and overall survival analysis. Finally, clinical features from GSE133624, GSE13507, the TCGA, and other data sets were analyzed to validate the relationship between hub genes and tumor growth and mutation. Results: The HR score was significantly higher in the complete/partial response group than in the stable/progressive disease group. The majority of genes associated with HR were discovered to be involved in the cell cycle and others. Genomically unstable, high tumor level, and high immune level samples all exhibited significantly higher HR score than other sample categories, and higher HR scores were related to improved survival following ICIs treatment. The risk scores for AUNIP, SEPT, FAM72D, CAMKV, CXCL9, and FOXN4 were identified, and the training and verification groups had markedly different survival times. The risk score, tumor neoantigen burden, mismatch repair, and cell cycle regulation were discovered to be independent predictors of survival time following immunotherapy. Patients with a high level of expression of hub genes such as EME1, RAD51AP1, and RAD54L had a greater chance of surviving following immunotherapy. These genes are expressed at significantly higher levels in tumors, high-grade cancer, and invasive cancer than other categories, and are associated with TP53 and RB1 mutations. Conclusion: HR-related genes are upregulated in genomically unstable samples, the survival time of mUC patients after treatment with ICIs can be predicted using a normogram model based on HR signature.

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Transcriptional Profiling of Advanced Urothelial Cancer Predicts Prognosis and Response to Immunotherapy.

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Transcriptional Profiling of Advanced Urothelial Cancer Predicts Prognosis and Response to Immunotherapy.

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