Secretory IgA (SIgA) is the dominant antibody class in mucosal secretions. The majority of plasma cells producing IgA are located within mucosal membranes lining the intestines. SIgA protects against the adhesion of pathogens and their penetration into the intestinal barrier. Moreover, SIgA regulates gut microbiota composition and provides intestinal homeostasis. In this review, we present mechanisms of SIgA generation: T cell-dependent and -independent; in different non-organized and organized lymphoid structures in intestinal lamina propria (i.e., Peyer’s patches and isolated lymphoid follicles). We also summarize recent advances in understanding of SIgA functions in intestinal mucosal secretions with focus on its role in regulating gut microbiota composition and generation of tolerogenic responses toward its members.

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Background Keratoconus (KTCN) is a progressive eye disease, characterized by changes in the shape and thickness of the cornea that results in loss of visual acuity. While numerous KTCN candidate genes have been identified, the genetic etiology of the disease remains undetermined. To further investigate and verify the contribution of particular genetic factors to KTCN, we assessed 45 candidate genes previously indicated as involved in KTCN etiology based on transcriptomic and genomic data. Methods The RealTime ready Custom Panel, covering 45 KTCN candidate genes and two reference transcripts, has been designed. Then, the expression profiles have been assessed using the RT-qPCR assay in six KTCN and six non-KTCN human corneas, obtained from individuals undergoing a penetrating keratoplasty procedure. Results In total, 35 genes exhibiting differential expression between KTCN and non-KTCN corneas have been identified. Among these genes were ones linked to the extracellular matrix formation, including collagen synthesis or the TGF-β, Hippo, and Wnt signaling pathways. The most downregulated transcripts in KTCN corneas were CTGF, TGFB3, ZNF469, COL5A2, SMAD7, and SPARC, while TGFBI and SLC4A11 were the most upregulated ones. Hierarchical clustering of expression profiles demonstrated almost clear separation between KTCN and non-KTCN corneas. The gene expression levels determined using RT-qPCR showed a strong correlation with previous RNA sequencing (RNA-Seq) results. Conclusions A strong correlation between RT-qPCR and earlier RNA-Seq data confirms the possible involvement of genes from collagen synthesis and the TGF-β, Hippo, and Wnt signaling pathways in KTCN etiology. Our data also revealed altered expression of several genes, such as LOX, SPARC, and ZNF469, in which single nucleotide variants have been frequently identified in KTCN. These findings further highlight the heterogeneous nature of KTCN.

Allogeneic whole cell gene modified therapeutic melanoma vaccine (AGI-101H) comprising of two melanoma cell lines transduced with cDNA encoding fusion protein composed of IL-6 linked with the soluble IL-6 receptor (sIL-6R), referred to as H6 was developed. H6 served as a molecular adjuvant, however, it has altered vaccine cells phenotype towards melanoma stem cells (MSC)-like with high activity of aldehyde dehydrogenase isoenzyme (ALDH1A1). AGI-101H was applied in advanced melanoma patients with non-resected and resected disease. In the adjuvant setting, it was combined with surgery in case of recurring metastases, which were surgically removed and vaccination continued. A significant fraction of AGI-101H treated melanoma patients is still alive (11–19 years). Out of 106 living patients, 39 were HLA-A2 positive and were the subject of the study. Immunization of melanoma patients resulted in the generation of cytotoxic CD8+ T cells specific for ALDH1A1, which were detected in circulation by HLA-A0201 MHC dextramers loaded with ALDH1A188-96(LLYKLADLI) peptide. Phenotypically they were central memory CD8+ T cells. Re-stimulation with ALDH1A188-96 ex vivo resulted in IFN-γ secretion and cells degranulation. Following each vaccine dose administration, the number of ALDH1A1-CD8+ T cells increased in circulation and returned to the previous level until next dose injection (one month). ALDH1A1-CD8+ T cells were also found, however in the lower number than in vaccinated patients, in the circulation of untreated melanoma with stage IV but were not found in stage II or III and healthy donors. Specific anti-ALDH1 antibodies were present in treated patients. Long-term survival suggests immuno-targeting of MSC in treated patients.

The human gut is inhabited by many organisms, including bacteria and fungi, that may affect human health. However, research on human gut mycobiome is still rare.

In recent years, the number of metagenomic studies increased significantly. Wide range of factors, including the tremendous community complexity and variability, is contributing to the challenge in reliable microbiome community profiling. Many approaches have been proposed to overcome these problems making hardly possible to compare results of different studies. The significant differences between procedures used in metagenomic research are reflected in a variation of the obtained results. This calls for the need for standardisation of the procedure, to reduce the confounding factors originating from DNA isolation, sequencing and bioinformatics analyses in order to ensure that the differences in microbiome composition are of a true biological origin. Although the best practices for metagenomics studies have been the topic of several publications and the main aim of the International Human Microbiome Standard (IHMS) project, standardisation of the procedure for generating and analysing metagenomic data is still far from being achieved. To highlight the difficulties in the standardisation of metagenomics methods, we thoroughly examined each step of the analysis of the human gut microbiome. We tested the DNA isolation procedure, preparation of NGS libraries for next-generation sequencing, and bioinformatics analysis, aimed at identifying microbial taxa. We showed that the homogenisation time is the leading factor impacting sample diversity, with the recommendation for a shorter homogenisation time (10 min). Ten minutes of homogenisation allows for better reflection of the bacteria gram-positive/gram-negative ratio, and the obtained results are the least heterogenous in terms of beta-diversity of samples microbial composition. Besides increasing the homogenisation time, we observed further potential impact of the library preparation kit on the gut microbiome profiling. Moreover, our analysis revealed that the choice of the library preparation kit influences the reproducibility of the results, which is an important factor that has to be taken into account in every experiment. In this study, a tagmentation-based kit allowed for obtaining the most reproducible results. We also considered the choice of the computational tool for determining the composition of intestinal microbiota, with Kraken2/Bracken pipeline outperforming MetaPhlAn2 in our in silico experiments. The design of an experiment and a detailed establishment of an experimental protocol may have a serious impact on determining the taxonomic profile of the intestinal microbiome community. Results of our experiment can be helpful for a wide range of studies that aim to better understand the role of the gut microbiome, as well as for clinical purposes.

There are various melanoma treatment strategies that are based on immunological responses, among which immune checkpoint inhibitors (ICI) are relatively novel form. Nowadays, anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and anti-programmed death-1 (PD-1) antibodies represent a standard treatment for metastatic melanoma. Although there are remarkable curative effects in responders to ICI therapy, up to 70% of melanoma patients show resistance to this treatment. This low response rate is caused by innate as well as acquired resistance, and some aspects of treatment resistance are still unknown. Growing evidence shows that gut microbiota and bacterial metabolites, such as short-chain fatty acids (SCFAs), affect the efficacy of immunotherapy. Various bacterial species have been indicated as potential biomarkers of anti-PD-1 or anti-CTLA-4 therapy efficacy in melanoma, next to biomarkers related to molecular and genetic tumor characteristics or the host immunological response, which are detected in patients’ blood. Here, we review the current status of biomarkers of response to ICI melanoma therapies, their pre-treatment predictive values, and their utility as on-treatment monitoring tools in order to select a relevant personalized therapy on the basis of probability of the best clinical outcome.

The gut microbiota is considered a key player modulating the efficacy of immune checkpoint inhibitor therapy. The study investigated the association between the response to anti-PD-1 therapy and the baseline gut microbiome in a Polish cohort of melanoma patients, alongside selected agents modifying the microbiome. Sixty-four melanoma patients enrolled for the anti-PD-1 therapy, and ten healthy subjects were recruited. The response to the treatment was assessed according to the response evaluation criteria in solid tumors, and patients were classified as responders or non-responders. The association between selected extrinsic factors and response was investigated using questionnaire-based analysis and the metataxonomics of the microbiota. In the responders, the Bacteroidota to Firmicutes ratio was higher, and the richness was decreased. The abundance of Prevotella copri and Bacteroides uniformis was related to the response, whereas the non-responders’ gut microbiota was enriched with Faecalibacterium prausnitzii and Desulfovibrio intestinalis and some unclassified Firmicutes. Dietary patterns, including plant, dairy, and fat consumption as well as gastrointestinal tract functioning were significantly associated with the therapeutic effects of the therapy. The specific gut microbiota along with diet were found to be associated with the response to the therapy in the population of melanoma patients.