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

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

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.

Tumor neoantigens derived from RNA editing events show significant clinical relevance in melanoma patients treated with immunotherapy

This study aimed to investigate the clinical significance of RNA editing (RE) and RNA editing derived (RED-) neoantigens in melanoma patients treated with immunotherapy. Vardict and VEP were used to identify the somatic mutations. RE events were identified by Reditools2 and filtered by the custom pipeline. miRTar2GO was implemented to predict the RE whether located in miRNA targets within the 3' UTR region. NetMHCpan and NetCTLpan were used to identify and characterize RED-neoantigens. In total, 7116 RE events were identified, most of which were A-to-I events. Using our custom pipeline, 631 RED-neoantigens were identified that show a significantly greater peptide-MHC affinity, and facilitate epitope processing and presentation than wild-type peptides. The OS of the patients with high RED-neoantigens burden was significantly longer ( P  = 0.035), and a significantly higher RED-neoantigens burden was observed in responders ( P  = 0.048). The area under the curve of the RED-neoantigen was 0.831 of OS. Then, we validated the reliability of RED-neoantigens in predicting the prognosis in an independent cohort and found that patients with high RED-neoantigens exhibited a longer OS ( P  = 0.008). To our knowledge, this is the first study to systematically assess the clinical relevance of RED-neoantigens in melanoma patients treated with immunotherapy.

Therapeutic strategies to enhance immune response induced by multiple myeloma cells

Multiple myeloma (MM)as a haematological malignancy is still incurable. In addition to the presence of somatic genetic mutations in myeloma patients, the presence of immunosuppressive microenvironment greatly affects the outcome of treatment. Although the discovery of immunotherapy makes it possible to break the risk of high toxicity and side effects of traditional chemotherapeutic drugs, there are still obstacles of ineffective treatment or disease recurrence. In this review, we discuss therapeutic strategies to further enhance the specific anti-tumor immune response by activating the immunogenicity of MM cells themselves. New ideas for future myeloma therapeutic approaches are provided.

Identification and Targeting of Mutant Neoantigens in Multiple Myeloma Treatment

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.

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

Although multiple vaccines have been developed and widely administered, several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have been reported to evade immune responses and spread diffusely. Here, 108 RNA-seq files from coronavirus disease 2019 (COVID-19) patients and healthy donors (HD) were downloaded to extract their TCR immune repertoire by MiXCR. Those extracted TCR repertoire were compared and it was found that disease progression was related negatively with diversity and positively with clonality. Specifically, greater proportions of high-abundance clonotypes were observed in active and severe COVID-19 samples, probably resulting from strong stimulation of SARS-CoV-2 epitopes and a continued immune response in host. To investigate the specific recognition between TCR CDR3 and SARS-CoV-2 epitopes, we constructed an accurate classifier CoV2-TCR with an AUC of 0.967 in an independent dataset, which outperformed several similar tools. Based on this model, we observed a huge range in the number of those TCR CDR3 recognizing those different peptides, including 28 MHC-I epitopes from SARS-CoV-2 and 22 immunogenic peptides from SARS-CoV-2 variants. Interestingly, their proportions of high-abundance, low-abundance and rare clonotypes were close for each peptide. To expand the potential application of this model, we established the webserver, CoV2-TCR, in which users can obtain those recognizing CDR3 sequences from the TCR repertoire of COVID-19 patients based on the 9-mer peptides containing mutation site(s) on the four main proteins of SARS-CoV-2 variants. Overall, this study provides preliminary screening for candidate antigen epitopes and the TCR CDR3 that recognizes them, and should be helpful for vaccine design on SARS-CoV-2 variants.