关键词: cancer vaccine clinical response machine learning peptide potential factors

Mesh : Adjuvants, Immunologic Cancer Vaccines Humans Melanoma Mineral Oil Peptides Vaccines, Subunit

来  源:   DOI:10.3389/fimmu.2022.931612   PDF(Pubmed)

Abstract:
Peptide-based cancer vaccines have been shown to boost immune systems to kill tumor cells in cancer patients. However, designing an effective T cell epitope peptide-based cancer vaccine still remains a challenge and is a major hurdle for the application of cancer vaccines. In this study, we constructed for the first time a library of peptide-based cancer vaccines and their clinical attributes, named CancerVaccine (https://peptidecancervaccine.weebly.com/). To investigate the association factors that influence the effectiveness of cancer vaccines, these peptide-based cancer vaccines were classified into high (HCR) and low (LCR) clinical responses based on their clinical efficacy. Our study highlights that modified peptides derived from artificially modified proteins are suitable as cancer vaccines, especially for melanoma. It may be possible to advance cancer vaccines by screening for HLA class II affinity peptides may be an effective therapeutic strategy. In addition, the treatment regimen has the potential to influence the clinical response of a cancer vaccine, and Montanide ISA-51 might be an effective adjuvant. Finally, we constructed a high sensitivity and specificity machine learning model to assist in designing peptide-based cancer vaccines capable of providing high clinical responses. Together, our findings illustrate that a high clinical response following peptide-based cancer vaccination is correlated with the right type of peptide, the appropriate adjuvant, and a matched HLA allele, as well as an appropriate treatment regimen. This study would allow for enhanced development of cancer vaccines.
摘要:
基于肽的癌症疫苗已被证明可以增强免疫系统以杀死癌症患者的肿瘤细胞。然而,设计一种有效的基于T细胞表位肽的癌症疫苗仍然是一个挑战,也是癌症疫苗应用的主要障碍。在这项研究中,我们首次构建了基于肽的癌症疫苗及其临床属性的文库,命名为癌症疫苗(https://peptidecancervaccine。weebly.com/)。探讨影响癌症疫苗有效性的相关因素,这些基于肽的癌症疫苗根据其临床疗效分为高临床应答(HCR)和低临床应答(LCR).我们的研究强调,来自人工修饰蛋白的修饰肽适合作为癌症疫苗,尤其是黑色素瘤。通过筛选HLAII类亲和肽可能是一种有效的治疗策略,可以促进癌症疫苗的发展。此外,治疗方案有可能影响癌症疫苗的临床反应,MontanideISA-51可能是一种有效的佐剂。最后,我们构建了高灵敏度和特异性的机器学习模型,以帮助设计能够提供高临床应答的基于肽的癌症疫苗.一起,我们的研究结果表明,基于肽的癌症疫苗接种后的高临床反应与正确的肽类型相关,适当的佐剂,和一个匹配的HLA等位基因,以及适当的治疗方案。这项研究将有助于增强癌症疫苗的开发。
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