NAIRscore as a biomarker for the quality of immune response to neoantigens is related with an increased overall survival in multiple myeloma

Jian, Xingxing; Xu, Linfeng; Zhao, Jingjing; Wang, Yanhui; Zhou, Wen; Xie, Lu

doi:10.1016/j.omtn.2022.07.006

Cited by 6 publications

(6 citation statements)

References 41 publications

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“…spike protein (S), membrane protein (M), envelope protein (E), and nucleocapsid protein (N), have been integrated as well. As we have known, based on the amino-acid sequences of these proteins, there were four probable mutation types, including single amino acid variation (SAAV), insertion and deletion of amino acids (InDelAA), insertion of amino acids (InAA), deletion of amino acids (DelAA) [35] .…”

Section: Resultsmentioning

confidence: 99%

CoV2-TCR: A web server for screening TCR CDR3 from TCR immune repertoire of COVID-19 patients and their recognized SARS-CoV-2 epitopes

Jian

Zhao

et al. 2023

Computational and Structural Biotechnology Journal

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Section: Resultsmentioning

confidence: 99%

CoV2-TCR: A web server for screening TCR CDR3 from TCR immune repertoire of COVID-19 patients and their recognized SARS-CoV-2 epitopes

Jian

Zhao

et al. 2023

Computational and Structural Biotechnology Journal

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“…They also recognized shared neoantigens among many patients in three driver oncogenic genes in MM (KRAS, NRAS, and IRF4), indicating the likely presence of shared neoantigens in MM. Jian et al [35] characterized the quality of immune response to neoantigens, and for this reason they developed an immune response score (NAIRscore), taking in consideration the neoantigen load, the cytolytic score, and the HLA-I score. They studied 478 patients and found that a high NAIRscore was associated with increased OR, reflecting the underlying lower driver-gene mutations and downregulated immune response.…”

Section: Neoantigens and Neoantigen Vaccination Strategiesmentioning

confidence: 99%

Identification and Targeting of Mutant Neoantigens in Multiple Myeloma Treatment

et al. 2023

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Multiple myeloma (MM) is malignant disease characterized by the clonal proliferation of plasma cells in the bone marrow, leading to anemia, immunosuppression, and other symptoms, that is generally hard to treat. In MM, the immune system is likely exposed to neoplasia-associated neoantigens for several years before the tumor onset. Different types of neoantigens have been identified. Public or shared neoantigens derive from tumor-specific modifications often reported in several patients or across diverse tumors. They are intriguing therapeutic targets because they are frequently observed, and they have an oncogenic effect. Only a small number of public neoantigens have been recognized. Most of the neoantigens that have been identified are patient-specific or “private”, necessitating a personalized approach for adaptive cell treatment. It was demonstrated that the targeting of a single greatly immunogenic neoantigen may be appropriate for tumor control. The purpose of this review was to analyze the neoantigens present in patients with MM, and to evaluate the possibility of using their presence as a prognostic factor or as a therapeutic target. We reviewed the most recent literature on neoantigen treatment strategies and on the use of bispecific, trispecific, and conjugated antibodies for the treatment of MM. Finally, a section was dedicated to the use of CAR-T in relapsed and refractory patients.

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“…Researching shared neoantigens offers the advantage of reducing resource and time consumption compared with specific neoantigen therapies. Given that specific neoantigens are patient‐specific, they are not applicable for a broad patient population 16–20 …”

Section: Introductionmentioning

confidence: 99%

“…Given that specific neoantigens are patient-specific, they are not applicable for a broad patient population. [16][17][18][19][20] In this study, we delved into the mechanisms underlying the role of tumor neoantigen-related genes in BLCA and their impact on prognosis. Our analysis utilized both single-cell sequencing data and bulk sequencing data from publicly available databases.…”

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confidence: 99%

Unraveling neoantigen‐associated genes in bladder cancer: An in‐depth analysis employing 101 machine learning algorithms

Lv,

Xiong,

et al. 2024

Environmental Toxicology

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The therapeutic outcomes for bladder cancer (BLCA) remain suboptimal. Concurrently, there is a growing appreciation for the role of neoantigens in tumors. In this study, we explored the mechanisms underlying the involvement of neoantigen‐associated genes in BLCA and their impact on prognosis. Our analysis incorporated both single‐cell sequencing and bulk sequencing data sourced from publicly available databases. By employing a comprehensive set of 10 machine learning algorithms, we generated 101 algorithm combinations. The optimal combination, determined based on consistency indices, was utilized to construct a prognostic model comprising nine genes (CAPG, ACTA2, PDIA6, AKNA, PTMS, SNAP23, ID2, CD3G, SP140). Subsequently, we validated this model in an independent cohort, demonstrating its robust testing efficacy. Moreover, we explored the correlations between various clinical traits, model scores, and genes. Leveraging extensive public data resources, we conducted a drug sensitivity analysis to provide insights for targeted drug screening. Additionally, consensus clustering analysis and immune infiltration analysis were performed on bulk sequencing datasets and immunotherapy cohorts. These analyses yield valuable insights into the role of neoantigens in BLCA, guiding future research endeavors.

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NAIRscore as a biomarker for the quality of immune response to neoantigens is related with an increased overall survival in multiple myeloma

Cited by 6 publications

References 41 publications

CoV2-TCR: A web server for screening TCR CDR3 from TCR immune repertoire of COVID-19 patients and their recognized SARS-CoV-2 epitopes

CoV2-TCR: A web server for screening TCR CDR3 from TCR immune repertoire of COVID-19 patients and their recognized SARS-CoV-2 epitopes

Identification and Targeting of Mutant Neoantigens in Multiple Myeloma Treatment

Unraveling neoantigen‐associated genes in bladder cancer: An in‐depth analysis employing 101 machine learning algorithms

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