Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy

Meng, Jialin; Lu, Xiaofan; Zhou, Yujie; Zhang, Meng; Ge, Qintao; Zhou, Jun; Hao, Zongyao; Gao, Shenglin; Yan, Fangrong; Liang, Chaozhao

doi:10.1016/j.omto.2021.02.001

Cited by 49 publications

(34 citation statements)

References 64 publications

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“…As expected, the patients in the low-risk group have a better response to anti-PD1 therapy than those in the high-risk group. Group with high TIDE score is more likely to induce immune evasion, indicating a lower response to immunotherapy (74), which is consistent with our findings.…”

Section: Discussionsupporting

confidence: 92%

Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Chen

Lan

et al. 2021

Front. Immunol.

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BackgroundOvarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).ResultsWe identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.ConclusionsIn this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.

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Section: Discussionsupporting

confidence: 92%

Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Chen

Lan

et al. 2021

Front. Immunol.

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“…The NMF algorithm, a multiplicative update algorithm, can be used to dissect substantial volumes of data using a limited number of components 50 . Emerging evidence has suggested NMF to be a promising method for classifying tumor molecular subtypes 51 . Using the NMF algorithm, we identified an immune pattern in the training cohort.…”

Section: Discussionmentioning

confidence: 99%

Identification of immune-related subtypes of colorectal cancer to improve antitumor immunotherapy

Zheng

Gao

et al. 2021

Sci Rep

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Immunotherapy involving immune checkpoint inhibitors (ICIs) for enhancing immune system activation is promising for tumor management. However, the patients’ responses to ICIs are different. Here, we applied a non-negative matrix factorization algorithm to establish a robust immune molecular classification system for colorectal cancer (CRC). We obtained data of 1503 CRC patients (training cohort: 488 from The Cancer Genome Atlas; validation cohort: 1015 from the Gene Expression Omnibus). In the training cohort, 42.8% of patients who exhibited significantly higher immunocyte infiltration and enrichment of immune response-associated signatures were subdivided into immune classes. Within the immune class, 53.1% of patients were associated with a worse overall prognosis and belonged to the immune-suppressed subclass, characterized by the activation of stroma-related signatures, genes, immune-suppressive cells, and signaling. The remaining immune class patients belonged to the immune-activated subclass, which was associated with a better prognosis and response to anti-PD-1 therapy. Immune-related subtypes were associated with different copy number alterations, tumor-infiltrating lymphocyte enrichment, PD-1/PD-L1 expression, mutation landscape, and cancer stemness. These results were validated in patients with microsatellite instable CRC. We described a novel immune-related class of CRC, which may be used for selecting candidate patients with CRC for immunotherapy and tailoring optimal immunotherapeutic treatment.

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“…The mean of the enrichment score for each subtype was used in the visualization of the heatmap. The gene sets of immune signatures and stromal signatures were obtained from a previous study[25], and the NES score was calculated in order to compare the different immune activated statuses among the different subtypes.…”

Section: Methodsmentioning

confidence: 99%

Molecular classification reveals the diverse genetic features and prognosis of gastric cancer: a multi-omics consensus ensemble clustering

Wang

et al. 2021

Preprint

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Background: Gastric cancer (GC) is the fifth most common tumor around the world, it is necessary to reveal novel molecular subtypes to guide the selection of patients who may benefit from specific target therapy. Methods: Multi-omics data, including RNA-sequence of transcriptomics (mRNA, LncRNA, miRNA), DNA methylation and gene mutation of TCGA-STAD cohort was used for the clustering. Ten classical clustering algorithms were applied to recognize patients with different molecular features via the R package MOVICS. The activated signaling pathways were evaluated using the single-sample gene set enrichment analysis. The difference distribution of gene mutations, copy number alterations and tumor mutation burden was compared, and potential response to immunotherapy and chemotherapy was assessed as well. Results: Two molecular subtypes (CS1 and CS2) were recognized by ten clustering algorithms with further consensus ensembles. Patients in the CS1 group were found to contain a shorter average overall survival time (28.5 vs. 68.9 months, P = 0.016), and progression-free survival (19.0 vs. 63.9 months, P = 0.008) compared to the CS2 group. CS1 group contained more activation of extracellular associated biological process, while CS2 group displayed the activation of cell cycle associated pathways. The significantly higher total mutation numbers and neo antigens were observed in CS2 group, along with the specific mutation of TTN, MUC16 and ARID1A. Higher infiltration of immunocytes were also observed in CS2 group, reflected to the potential benefit from immunotherapy. Moreover, CS2 group also can response to 5-fluorouracil, cisplatin, and paclitaxel. The similar diverse of clinical outcome of CS1 and CS2 groups were successfully validation in external cohorts of GSE62254, GSE26253, GSE15459, and GSE84437. Conclusion: Novel insight into the GC subtypes was obtained via integrative analysis of five omics data by ten clustering algorithms, which can provide the idea to the clinical target therapy based on the specific molecular features.

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Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy

Cited by 49 publications

References 64 publications

Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

Identification of immune-related subtypes of colorectal cancer to improve antitumor immunotherapy

Molecular classification reveals the diverse genetic features and prognosis of gastric cancer: a multi-omics consensus ensemble clustering

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