Molecular determinants of response to PD-L1 blockade across tumor types

Banchereau, Romain; Leng, Ning; Zill, Oliver A.; Sokol, Ethan S.; Liu, Gengbo; Pavlick, Dean; Maund, Sophia L.; Liu, Lifen; Kadel, Edward E.; Baldwin, Nicole; Jhunjhunwala, Suchit; Nickles, Dorothee; Assaf, Zoe June; Bower, Daniel; Patil, Namrata; McCleland, Mark L.; Shames, David S.; Molinero, Luciana; Huseni, Mahrukh; Sanjabi, Shomyseh; Cummings, Craig; Mellman, Ira; Mariathasan, Sanjeev; Hegde, Priti S.; Powles, Thomas

doi:10.1038/s41467-021-24112-w

Cited by 99 publications

(110 citation statements)

References 43 publications

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“…On the basis of results obtained in other tumors, clearly indicating that non-immune pathways could impact response to ICI therapy, an additional combination therapy that can be proposed for STS will envisage the use of drugs targeting CDKs [ 69 ]. In fact, CDK activation pathways are drivers of sarcomagenesis, but they also have an active role in limiting immune surveillance in human tumors and likely in sarcomas, as well.…”

Section: Genetic/immunological Diversity In Stss and Response To Icismentioning

confidence: 99%

“…In fact, CDK activation pathways are drivers of sarcomagenesis, but they also have an active role in limiting immune surveillance in human tumors and likely in sarcomas, as well. Moreover, it has been recently reported that CDK4/6 axis is a tumor-intrinsic resistance mechanism to anti PD1 therapy in melanoma [ 70 ] and increased activity of the CDK4/6 inhibitor CDKN2A correlates with response to PD-L1 blockage in RCC and NSCLC patients [ 69 ].…”

Section: Genetic/immunological Diversity In Stss and Response To Icismentioning

confidence: 99%

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Molecular Determinants of Soft Tissue Sarcoma Immunity: Targets for Immune Intervention

Tazzari

Bergamaschi

Vita

et al. 2021

IJMS

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Soft tissue sarcomas (STSs) are a family of rare malignant tumors encompassing more than 80 histologies. Current therapies for metastatic STS, a condition that affects roughly half of patients, have limited efficacy, making innovative therapeutic strategies urgently needed. From a molecular point of view, STSs can be classified as translocation-related and those with a heavily rearranged genotype. Although only the latter display an increased mutational burden, molecular profiles suggestive of an “immune hot” tumor microenvironment are observed across STS histologies, and response to immunotherapy has been reported in both translocation-related and genetic complex STSs. These data reinforce the notion that immunity in STSs is multifaceted and influenced by both genetic and epigenetic determinants. Cumulative evidence indicates that a fine characterization of STSs at different levels is required to identify biomarkers predictive of immunotherapy response and to discover targetable pathways to switch on the immune sensitivity of “immune cold” tumors. In this review, we will summarize recent findings on the interplay between genetic landscape, molecular profiling and immunity in STSs. Immunological and molecular features will be discussed for their prognostic value in selected STS histologies. Finally, the local and systemic immunomodulatory effects of the targeted drugs imatinib and sunitinib will be discussed.

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Section: Genetic/immunological Diversity In Stss and Response To Icismentioning

confidence: 99%

Section: Genetic/immunological Diversity In Stss and Response To Icismentioning

confidence: 99%

Molecular Determinants of Soft Tissue Sarcoma Immunity: Targets for Immune Intervention

Tazzari

Bergamaschi

Vita

et al. 2021

IJMS

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“…Some targeted therapeutic agents targeting vascular endothelial growth factor (VEGF) signaling, such as sunitinib and pazopanib, have greatly improved the prognosis of ccRCC patients. Additionally, immune checkpoint inhibitor alone or combined strategies were also identified as a promising therapeutic target for those patients ( 5 , 6 ). Revealing comprehensive genomic features is of great importance for understanding ccRCC and developing new therapeutic lines for patients with ccRCC ( 7 ).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Genomic Landscape in Chinese Clear Cell Renal Cell Carcinoma Patients

et al. 2021

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Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). The genomic landscape in Chinese ccRCC needs to be elucidated. Herein, we investigated the molecular features of Chinese ccRCC patients. Genomic profiling of DNA was performed through next-generation sequencing (NGS) in Chinese patients with ccRCC between January 2017 and March 2020. Clinical information including age, gender, and tumor histology was collected. Immunohistochemistry (IHC) staining for PD-L1 expression was performed using PD-L1 IHC 22C3 pharmDx assay or Ventana PD-L1 SP263 assay. Data analyses were performed using R 3.6.1. A total of 880 Chinese ccRCC patients who have undergone NGS were included in this study. The most common somatic alterations were detected in VHL (59.7%), PBRM1 (18.0%), SETD2 (12.2%), BAP1 (10.2%), and TP53 (9.4%). Compared with The Cancer Genome Atlas (TCGA) database, a higher mutation frequency of VHL (59.7% vs. 50.0%, p < 0.001) and TP53 (9.4% vs. 3.5%, p < 0.001) and a lower mutation frequency of PBRM1 (18.0% vs. 31.0%, p < 0.001) were found in the Chinese cohort. Of the 460 patients who were evaluated for PD-L1 expression, 139 (30.2%) had positive PD-L1 expression. The median tumor mutational burden (TMB) value was 4.5 muts/Mb (range, 0–46.0). Five (0.7%) patients were identified as microsatellite instability-high (MSI-H). Furthermore, 52 (5.9%) patients were identified to carry pathogenic or likely pathogenic germline mutations in 22 cancer predisposition genes. This is the first large-scale comprehensive genomic analysis for Chinese ccRCC patients, and these results might provide a better understanding of molecular features in Chinese ccRCC patients, which can lead to an improvement in the personalized treatment for these patients.

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“…Collectively, lung adenocarcinoma patients with lower risk score or higher CDKN2A expression levels present more immune cells in TIME, suggesting an activated immune phenotype that results in longer overall survival. The correlation between CDKN2A expression and response to ICI treatment was also demonstrated in a recent study, highlighting the association of non-immune pathways to the outcome of ICI treatment (29). Nevertheless, further investigation is needed to explore the biological roles of CDKN2A.…”

Section: Discussionmentioning

confidence: 71%

A Prediction Model Using Alternative Splicing Events and the Immune Microenvironment Signature in Lung Adenocarcinoma

Zhu

Wang²,

Sun

et al. 2021

Front. Oncol.

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BackgroundAlternative splicing (AS) is a gene regulatory mechanism that drives protein diversity. Dysregulation of AS is thought to play an essential role in cancer initiation and development. This study aimed to construct a prognostic signature based on AS and explore the role in the tumor immune microenvironment (TIME) in lung adenocarcinoma.MethodsWe analyzed transcriptome profiling and clinical lung adenocarcinoma data from The Cancer Genome Atlas (TCGA) database and lists of AS-related and immune-related signatures from the SpliceSeq. Prognosis-related AS events were analyzed by univariate Cox regression analysis. Gene set enrichment analyses (GSEA) were performed for functional annotation. Prognostic signatures were identified and validated using univariate and multivariate Cox regression, LASSO regression, Kaplan–Meier survival analyses, and proportional hazards model. The context of TIME in lung adenocarcinoma was also analyzed. Gene and protein expression data of Cyclin-Dependent Kinase Inhibitor 2A (CDKN2A) were obtained from ONCOMINE and Human Protein Atlas. Splicing factor (SF) regulatory networks were visualized.ResultsA total of 19,054 survival-related AS events in lung adenocarcinoma were screened in 1,323 genes. Exon skip (ES) and mutually exclusive exons (ME) exhibited the most and fewest AS events, respectively. Based on AS subtypes, eight AS prognostic signatures were constructed. Patients with high-risk scores were associated with poor overall survival. A nomogram with good validity in prognostic prediction was generated. AUCs of risk scores at 1, 2, and 3 years were 0.775, 0.736, and 0.759, respectively. Furthermore, the prognostic signatures were significantly correlated with TIME diversity and immune checkpoint inhibitor (ICI)-related genes. Low-risk patients had a higher StromalScore, ImmuneScore, and ESTIMATEScore. AS-based risk score signature was positively associated with CD8+ T cells. CDKN2A was also found to be a prognostic factor in lung adenocarcinoma. Finally, potential functions of SFs were determined by regulatory networks.ConclusionTaken together, our findings show a clear association between AS and immune cell infiltration events and patient outcome, which could provide a basis for the identification of novel markers and therapeutic targets for lung adenocarcinoma. SF networks provide information of regulatory mechanisms.

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Molecular determinants of response to PD-L1 blockade across tumor types

Cited by 99 publications

References 43 publications

Molecular Determinants of Soft Tissue Sarcoma Immunity: Targets for Immune Intervention

Molecular Determinants of Soft Tissue Sarcoma Immunity: Targets for Immune Intervention

Comprehensive Genomic Landscape in Chinese Clear Cell Renal Cell Carcinoma Patients

A Prediction Model Using Alternative Splicing Events and the Immune Microenvironment Signature in Lung Adenocarcinoma

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