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关键词： Donor lymphocyte infusion   HLA-haploidentical hematopoietic   transplantation   Adult T -cell leukemia/lymphoma  

摘要： Donor lymphocyte infusion (DLI) combined with chemotherapy is an effective therapy for relapsed adult T-cell leukemia/lymphoma (ATL) after allogeneic hematopoietic stem cell transplantation from a human leukocyte antigen (HLA)-matched related donor or matched unrelated donor. The 1-year incidence of ATL relapse is 28 % after HLA-haploidentical hematopoietic stem cell transplantation (haplo-HSCT) with post-transplant cyclophosphamide. However, the efficacy of DLI for relapsed ATL after haplo-HSCT remains unclear. Here, we present the case of a 61-year-old woman diagnosed with ATL who underwent haplo-HSCT from an HLA-haploidentical relative donor. On day +164 after transplantation, the patient experienced ATL relapse. Tacrolimus was tapered and discontinued on day +216;however, ATL progressed. Since the patient did not develop graft-versus-host disease (GVHD) after the discontinuation of tacrolimus, DLI following chemotherapy was performed for relapsed ATL. The patient achieved complete remission without severe GVHD after the 6th DLI treatment. This remission has been sustained for over 15 months with 13 DLI treatments. These results suggest the potential of DLI combined with chemotherapy as a treatment option for patients with relapsed ATL after haplo-HSCT.

关键词： ESR1   Hotspot mutations   Neoepitopes   HLA-A2   Immunotherapy  

摘要： Endocrine therapy has shown significant clinical efficacy in estrogen receptor alpha (ER alpha)-positive breast cancer management, but the emergence of therapy-resistant mutations significantly undermines treatment outcomes, frequently leading to disease progression and metastasis. Among these resistance mechanisms, mutations in the ESR1 gene are particularly prevalent, detectable in 76% of endocrine therapy-resistant tumor specimens. The identification of immunogenic neoepitopes derived from mutant ESR1 offers a promising therapeutic avenue for patients with endocrine therapy-resistant breast cancer. In this study, we systematically investigated the mutational landscape of ESR1 across various cancer types, with particular emphasis on mutation frequency and spectrum analysis. Our findings revealed that non-synonymous ESR1 mutations predominantly occurred in breast cancer, clustering at four distinct hotspot sites: K303, E380, Y537 and D538. We further characterized the mutation prevalence at these hotspots across different breast cancer subtypes. Through comprehensive screening, we identified eight human leukocyte antigen (HLA)-A*0201 restricted immunogenic neoepitopes derived from ESR1 hotspot mutations. These neoepitopes demonstrated the capacity to elicit specific cytotoxic T lymphocytes (CTLs) responses both in vitro and in vivo. The induced CTLs exhibited specific recognition and cytotoxic activity against both T2A2 cells loaded with mutant neoepitopes and HLA-A*0201-positive breast cancer cells transfected with minigene encoding mutant neoepitopes. Notably, adoptive transfer of T cells primed with a peptide pool containing these eight neoepitopes significantly suppressed tumor growth and enhanced CD8+ T cells infiltration within tumor tissue. These findings suggest that the identified neoepitopes represent promising candidates for the development of tumor shared neoantigen vaccines.

关键词： gastric cancer   growth   interleukin-21 receptor   long non-coding RNA MALAT1   miR-125a-3p  

摘要： Following the publication of the above article, an interested reader drew to the authors' attention that their paper was found to contain data with a previous article that had been published in the journal (Figs. 2C and 4B), and in a paper that appeared subsequently in the journal Molecular Cancer. All cases involved the sharing of Transwell assay data, and the other papers in question were published by the same authors/the same research group. After having examined their original data, the authors realized that Figs. 2 and 4 had been inadvertently assembled incorrectly in the above paper. Specifically, Figs. 2C and D, and 4B and D, showing the results of Transwell assay experiments indicating the effects of IL‑21R knockdown or co‑transfection with IL‑21R and miR‑125a mimic on cell invasion in HGC‑27 and MKN‑45 cell lines, contained erroneous images. The revised versions of Figs. 2 and 4, featuring replacement data for Figs. 2C and D and 4B and D, showing the correct data obtained for the effects of IL‑21R knockdown or co‑transfection with IL‑21R and miR‑125a mimic on cell invasion, are shown on the next page. All authors confirm that the errors made in Figs. 2C and D and 4B and D did not influence the final conclusions reported in the above article, and they thank the Editor of for granting them the opportunity to publish a Corrigendum. All the authors agree to the publication of this Corrigendum, and apologize for the inconvenience to the readers. [International Journal of Oncology 54: 7‑16, 2019; DOI: 10.3892/ijo.2018.4612].

摘要： Antigenic noncanonical epitope and novel protein discovery are research areas with therapeutical applications, predominantly done via mass spectrometry. The latter should rely on a well-characterized proteogenomic search space. Its size is barely known for antigenic non-canonical peptides and novel proteins, and this could impact their identification. To address these issues, we here develop an automated workflow comprised of Sequoia for the creation of RNA sequencing-informed and exhaustive sequence search spaces for various noncanonical peptide origins, and SPIsnake for pre-filtering and exploration of sequence search space before mass spectrometry searches. We apply our workflow to characterize the exact sizes of tryptic and nonspecific peptide sequence search spaces in a variety of definitions, their reduction when using RNA expression, their inflation by post-translational modifications, and the frequency of peptide sequence multimapping to different noncanonical origins. Furthermore, we explore the application of Sequoia and SPIsnake on HLA-I immunopeptidomes, thereby rescuing sensitivity in peptide identification when confronted with inflated search spaces. Taken together, Sequoia and SPIsnake pave the way for an educated development of methods addressing large-scale exhaustive proteogenomic discovery by exposing the consequences of database size inflation and ambiguity of peptide and protein sequence identification.

关键词： hidradenitis suppurativa   medical dermatology   clinical research   biologic therapy   COVID-19   vaccines   SARS-CoV-2  

摘要： Background and Objectives: Tumour necrosis factor-alpha (TNF-alpha) inhibitors such as adalimumab and infliximab are commonly used in moderate-to-severe hidradenitis suppurativa (HS). While the impact of TNF-alpha inhibitors on outcomes after an active infection in patients with HS has been explored, their effect on the SARS-CoV-2 vaccine response remains unknown. We investigated the impact of TNF-alpha inhibitor therapy on the immunogenic response to the SARS-CoV-2 vaccine in patients with ***: This is a single-centre retrospective chart review of 120 patients with recorded levels of anti-SARS-CoV-2 spike antibody. This cohort was characterized descriptively by demographics, antibody levels, vaccine brand, number of doses, and days elapsed from vaccination. These variables were then compared by usage of anti-TNF therapy. Secondary analyses included comparison by biologic type, time on biologic, and biologic ***: We found no significant difference in seroconversion following SARS-CoV-2 vaccination while on anti-TNF therapy in HS patients;a finding that holds in comparisons between anti-TNF therapy type, time exposed to biologic, and anti-TNF ***: Patients with HS on anti-TNF therapy receiving the SARS-CoV-2 mRNA vaccine seroconvert similarly as those without anti-TNF therapy, indicating this population should receive the vaccine and expect a similar degree of protection against COVID-19 compared to HS patients who do not receive anti-TNF therapy.

关键词： Peptides   GSM   Feature extraction   Convolutional neural networks   Amino acids   Encoding   Data mining   Training   Prediction algorithms   Deep learning   immune system   MHC I molecules   deep learning   graph attention network  

摘要： The interaction between peptides and Major Histocompatibility Complex Class I (MHC-I) molecules plays a critical role in adaptive immune recognition. Although computational prediction algorithms have advanced over traditional experimental methods, challenges still remain. There is a scarcity of standardized datasets that provide comprehensive profiles of MHC-peptide structure. The polymorphism of MHC molecules introduces diverse binding patterns, complicating the characterization of specific amino acid interaction pairs. To address these issues, we introduce GSM, a novel deep learning model that combines a Graph Attention Neural Network with a Self-Attention Convolutional Neural Network to predict MHC-peptide binding affinities. By integrating self-attention mechanisms to capture global peptide-MHC interactions and graph-based modeling to represent local amino acid pairwise interactions, GSM provides a comprehensive understanding of binding mode. Compared to existing algorithms, GSM shows superior performance and greater stability across diverse allele datasets, as demonstrated on the benchmarks. Furthermore, by leveraging real 3D structural data and attention visualization, GSM is capacity of selecting interaction sites, offering valuable insights for vaccine design and advancing immunological research.