Immune checkpoint inhibitors: a promising anticancer therapy

Singh, Sima; Hassan, Daniel; Aldawsari, Hibah M; Molugulu, Nagashekhara; Shukla, Rahul; Kesharwani, Prashant

doi:10.1016/j.drudis.2019.11.003

Cited by 124 publications

(84 citation statements)

References 58 publications

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“…The human TCR repertoire refers to the whole range of different TCRs present in an organism. The genetic diversification mechanisms acting on a small set of genes that encode the TCR (recombination, random insertion, and deletion) have the potential to create 10 14 -10 19 new genetic configuration of TCRα/β, according to probabilistic models of TCR rearrangement, where diversity is largely dominated by the CDR3 [6,35].…”

Section: The Immune Repertoirementioning

confidence: 99%

“…In a seminal paper in 1996, Leach et al showed for the first time that antibodies against CTLA4 could help reject pre-established tumors in mice [17]. Since then, immune checkpoints inhibitors have been considered as novel targets for cancer immunotherapy, and several antibodies targeting CTLA4, PD-1, and PD-L1 are currently approved for use in a variety of different cancers (reviewed in [18,19]). Several clinical trials have demonstrated that CBI improves the overall survival and long-term safety in a number of different cancers, as well provoking fewer metastases and adverse effects as compared with traditional cancer treatments such as chemotherapy and radiation therapy [1,[20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…Several clinical trials have demonstrated that CBI improves the overall survival and long-term safety in a number of different cancers, as well provoking fewer metastases and adverse effects as compared with traditional cancer treatments such as chemotherapy and radiation therapy [1,[20][21][22][23][24]. Multiple additional trials using CBI drugs either as single agents or in combination with other agents are ongoing to extend their indication areas [18,19].…”

Section: Introductionmentioning

confidence: 99%

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Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Aversa

Malanga

Fiume

et al. 2020

IJMS

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The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a “footprint” of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.

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Section: The Immune Repertoirementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Aversa

Malanga

Fiume

et al. 2020

IJMS

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“…The success of ICIs has emerged from a deep understanding of the functions of the immune system and immunosuppressive conditions that are generated in the tumor microenvironment (TME). 7,8 In the TME, T cells help distinguish cancer cells from healthy cells and initiate subsequent attacks. Before the attack, the naïve T cells need two signals to be active.…”

Section: Introductionmentioning

confidence: 99%

Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma

Zhang

Sun

et al. 2020

OncoImmunology

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Background: Costimulatory molecules play significant roles in mounting anti-tumor immune responses, and antibodies targeting these molecules are recognized as promising adjunctive cancer immunotherapies. Here, we aim to conduct a first full-scale exploration of costimulatory molecules from the B7-CD28 and TNF families in patients with lung adenocarcinoma (LUAD) and generated a costimulatory moleculebased signature (CMS) to predict survival and response to immunotherapy. Methods: We enrolled 1549 LUAD cases across 10 different cohorts and included 502 samples from TCGA for discovery. The validation set included 970 cases from eight different Gene Expression Omnibus (GEO) datasets and 77 frozen tumor tissues with qPCR data. The underlying mechanisms and predictive immunotherapy capabilities of the CMS were also explored. Results: A five gene-based CMS (CD40LG, TNFRSF6B, TNFSF13, TNFRSF13C, and TNFRSF19) was initially constructed using the bioinformatics method from TCGA that classifies cases as high-vs. low-risk groups per OS. Multivariable Cox regression analysis confirmed that the CMS was an independent prognostic factor. As expected, CMS exhibited prognostic significance in the stratified cohorts and different validation cohorts. Additionally, the prognostic meta-analysis revealed that CMS was superior to the previous signature. Samples in high-and low-risk groups exhibited significantly different tumor-infiltrating leukocytes and inflammatory activities. Importantly, we found that the CMS scores were closely related to multiple immunotherapy biomarkers. Conclusion: We conducted the first and most comprehensive costimulatory molecule landscape analysis of patients with LUAD and built a clinically feasible CMS for prognosis and immunotherapy response prediction, which will be helpful for further optimize immunotherapies for cancer.

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“…The success of ICIs has emerged from a deep understanding of the functions of the immune system and immunosuppressive conditions that are generated in the tumor microenvironment (TME). [7,8] In the TME, T cells help distinguish cancer cells from healthy cells and initiate subsequent attacks.…”

Section: Introductionmentioning

confidence: 99%

Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma

Zhang

Sun

et al. 2020

Preprint

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Background Costimulatory molecules play significant roles in mounting anti-tumor immune responses, and antibodies targeting these molecules are recognized as promising adjunctive cancer immunotherapies. Here, we aim to conduct a first full-scale exploration of costimulatory molecules from the B7-CD28 and TNF families in patients with lung adenocarcinoma (LUAD) and generated a costimulatory molecule-based signature (CMS) to predict survival and response to immunotherapy. Methods We enrolled 1549 LUAD cases across 10 different cohorts and included 502 samples from TCGA for discovery. The validation set included 970 cases from eight different Gene Expression Omnibus (GEO) datasets and 77 frozen tumor tissues with qPCR data. The underlying mechanisms and predictive immunotherapy capabilities of the CMS were also explored. Results A five gene-based CMS (CD40LG, TNFRSF6B, TNFSF13, TNFRSF13C, and TNFRSF19) was initially constructed using the bioinformatics method from TCGA that classifies cases as high- vs. low-risk groups per OS. Multivariable Cox regression analysis confirmed that the CMS was an independent prognostic factor. As expected, CMS exhibited prognostic significance in the stratified cohorts and different validation cohorts. Additionally, the prognostic meta-analysis revealed that CMS was superior to the previous signature. Samples in high- and low-risk groups exhibited significantly different tumor-infiltrating leukocytes and inflammatory activities. Importantly, we found that signature high-risk patients were optimal candidates for immunotherapy. Conclusion We conducted the first and most comprehensive costimulatory molecule landscape analysis of patients with LUAD and built a clinically feasible CMS for prognosis and immunotherapy response prediction, which will be helpful for further optimize immunotherapies for cancer.

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Immune checkpoint inhibitors: a promising anticancer therapy

Cited by 124 publications

References 58 publications

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma

Identification of a costimulatory molecule-based signature for predicting prognosis risk and immunotherapy response in patients with lung adenocarcinoma

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