Identification of an immunotherapy-responsive molecular subtype of bladder cancer

Song, Bicna; Kim, Seon‐Kyu; Mun, Jeong-Yeon; Choi, Young Deuk; Leem, Sun‐Hee; Chu, In-Sun

doi:10.1016/j.ebiom.2019.10.058

Cited by 61 publications

(69 citation statements)

References 36 publications

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“…Recently, considerable effort has been devoted to elucidating the molecular characteristics of bladder cancer [6][7][8][9]. It has been reported that the GU subtype of the Lund classification and the neuronal subtype of the TCGA classification respond best to anti-PD-L1 treatment [10,11].…”

Section: Discussionmentioning

confidence: 99%

“…Recently, immunotherapy studies have focused on a way to improve efficacy in individual patients. Numerous studies reported several molecular subtypes in bladder cancer, including immunotherapy-associated subgroups, the genomically unstable (GU) subtype of the Lund classification and the neuronal subtype in The Cancer Genome Atlas (TCGA) classification [6][7][8][9][10]. PD-L1 protein expression on immune cells, tumor mutation burden (TMB), and the TGFβ pathway have been shown to correlate with the clinical outcome of immune checkpoint inhibitor (ICI) therapy for advanced urothelial cancer [11].…”

Section: Introductionmentioning

confidence: 99%

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

Baek

Jang

Kim

et al. 2020

IJMS

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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 TGFβ 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 TGFβ and YAP/TAZ pathways and upregulation of the cell cycle and DDR may be more responsive to ICI therapy.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Baek

Jang

Kim

et al. 2020

IJMS

Self Cite

View full text Add to dashboard Cite

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“…as well as noncellular components (cytokines, etc.). Notably, the complex interplay between tumor cells and their surrounding microenvironment plays a pivotal role during tumor development and has significant effects on the OS and immunotherapeutic efficacy in tumors [6][7][8]. Here, we investigated the immune landscape between patients in the high-risk and lowrisk groups using two bioinformatic methods to infer specific immune cell infiltration.…”

Section: Discussionmentioning

confidence: 99%

“…ovarian clear cell carcinoma [7], and bladder cancer [8]. However, the limitations of immunecheckpoint inhibitors (ICIs) in metastatic melanoma require a deep understanding of the definitive mechanisms within the tumor microenvironment and a more reliable biomarker to predict patient prognosis or response to ICIs.…”

mentioning

confidence: 99%

Identification of an Immune-Related Prognostic Signature Associated with Immune Infiltration in Melanoma

Liu

et al. 2020

Preprint

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Background: Melanoma is the leading cause of cancer-related death among skin tumors, with an increasing incidence worldwide. Few studies have effectively investigated the significance of an immune-related genes (IRGs) signature for melanoma prognosis. Methods: Here, we constructed an IRGs prognostic signature using bioinformatics methods and evaluated and validated its predictive capability. Then, immune cell infiltration and tumor mutation burden (TMB) landscapes associated with this signature in melanoma were analyzed comprehensively. Results: With the 10-IRG prognostic signature, melanoma patients in the low-risk group showed better survival with distinct features of high immune cell infiltration and TMB. Importantly, melanoma patients in this subgroup were significantly responsive to MAGE-A3 in the validation cohort. Conclusions: This immune-related prognostic signature is thus a reliable tool to predict melanoma prognosis; as the underlying mechanism of this signature is associated with immune infiltration and mutation burden, it might reflect the benefit of immunotherapy to patients.

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“…Raw data normalization was carried out in different platforms with default setting. ( Supplementary Table 1) [5,[10][11][12][13][14][15][16][17][18]].…”

Section: Data Reprocessingmentioning

confidence: 99%

Machine Learning Prediction Models Based on Hub Genes Related to Immune Phenotypes in Muscle-Invasive Bladder Cancer Treated With Immune Checkpoint Blockade

Chen

Wang

et al. 2020

Preprint

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Background: Bladder cancer is one of the most frequent cancer in the world. Muscle-invasive bladder cancer (MIBC) is a more aggressive subtype with higher morbidity and mortality. ICB therapy has shown potential for treating MIBC, but is limited due to the lack of predictive biomarkers.Methods: 1601 MIBC transcriptomic profiles were obtained from 10 datasets. Unsupervised clustering of immune phenotypes in MIBC were performed based on immune-related signature genes. We analyzed the characteristics including immune microenvironments, metabolic pathways, and survival rates in different phenotypes. Multi-omic analysis and WGCNA were performed to identify hub genes distinguishing phenotypes related to prognosis. A model was established and CART was employed to predict the response of patients treated with ICB.Results: Of various immune phenotypes, cluster 3C was the most “inflamed” subcluster with the best prognosis, while cluster 1A was associated with “non-inflammation” and worse prognosis. WGCNA analysis identified 5 hub genes related to the survival rate of patients, IFNG, CXCR6, IL2RB, LCK, and PSMB10, which were utilized for prognostic score model and decision tree analysis. The areas under the curve (AUC) of the ROC curves predicting 5-year endpoint generated from the risk-based prediction model were 0.652. The mean accuracy, sensitivity, and specificity of CART for predicting stable disease/progressive disease were 70.1%, 70.0% and 71.7%.Conclusions: The 5 hub genes and generated models showed the potential for predicting the prognosis for patients receiving ICB therapy. The molecular mechanisms regulating the expression of the hub genes require further studies in the future.

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Identification of an immunotherapy-responsive molecular subtype of bladder cancer

Cited by 61 publications

References 36 publications

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

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

Identification of an Immune-Related Prognostic Signature Associated with Immune Infiltration in Melanoma

Machine Learning Prediction Models Based on Hub Genes Related to Immune Phenotypes in Muscle-Invasive Bladder Cancer Treated With Immune Checkpoint Blockade

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