Supplementary Figure 5. The relative fungi abundance of melanoma and healthy samples at different taxonomical levels: (A) Phylum (B) Class (C) Order (D) Family.

Supplementary Table 1. Melanoma patients and healthy controls data.

Supplementary Figure Legends and Tables 2-9

Supplementary Figure 11. Relative abundance of selected species in responders and non responders (R vs. NR).

Supplementary Figure 6. Gut microbiota richness.

Supplementary Figure 10. Relative abundance of selected species in patients that exhibited benefits during anti-PD-1 treatment and patients who did not show benefits (CB vs. NB).

Supplementary Figure 1. Baseline characteristics of the study populations with respect to (A) age groups, (B) BMI groups, and (C) sex.

Supplementary Figure 7. Relative abundance of selected species during anti-PD-1 treatment.

Supplementary Figure 2. (A) Shannon diversity of patients with normal (n=102) and elevated level of serum LDH (n=16). Kruskal–Wallis test was performed to compare groups, p<0.05. Horizontal line shows median. The lower and upper hinges correspond to the first and third quartiles. The upper and the lower whiskers extend from the hinge to the largest and smallest value, respectively, no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles). Dots represent potential outliers. (B) Relative abundance of Neurospora crassa and Sugiyamaella lignohabitans in patients with normal serum LDH level (n=102) and patients with elevated level of serum LDH (LDH>1.5x, what corresponds to >375 U/L, n=16). Welch Two Sample t-test was performed to compare groups, padj<0.05 (FDR). Horizontal line shows median. Red dot shows mean. Dots represent individual samples.

Supplementary Figure 4. Phylogenetic trees of mycobiota in (A) healthy and (B) melanoma subjects.

Supplementary Figure 8. Relative abundance of statistically significant gut fungi species in overweight and normal BMI patients (A) before anti-PD-1 treatment, and (B) in the third month of anti-PD-1 treatment.

Supplementary Figure 9. Relative abundance of Yarrowia lipolytica in overweight patients during anti-PD-1 treatment.

Supplementary Figure 3. Relative abundance of Candida glabrata in normal (18.5

The gut microbiota is recognized as one of the extrinsic factors that modulate the clinical outcomes of immune checkpoint inhibitors (ICIs), such as inhibitors targeting programmed cell death protein 1 (PD-1), in cancer patients. However, the link between intestinal barrier, which mutually interacts with the gut microbiota, and therapeutic effects has not been extensively studied so far. Therefore, the primary goal of this study was to investigate the relationship between intestinal barrier functionality and clinical outcomes of anti-PD-1 therapy in patients with advanced melanoma. Fecal samples were collected from 64 patients before and during anti-PD-1 therapy. The levels of zonulin, calprotectin, and secretory immunoglobulin A (SIgA), which reflect intestinal permeability, inflammation, and immunity, respectively, were measured in fecal samples (n = 115) using an Enzyme-Linked Immunosorbent Assay (ELISA). Moreover, the composition of the immunoglobulin (Ig)-bound (n = 108) and total stool microbiota (n = 117) was determined by the V3-V4 region of 16S rRNA gene sequencing. ELISA indicated a higher baseline concentration of fecal SIgA in patients with favorable clinical outcomes than those with unfavorable ones. Moreover, high baseline concentrations of intestinal barrier state biomarkers correlated with survival outcomes. In the cases of fecal zonulin and fecal SIgA, there was a positive correlation, while in the case of fecal calprotectin, there was a negative correlation. Furthermore, there were differences in the microbial profiles of the Ig-bound stool microbiota between patients with favorable and unfavorable clinical outcomes and their changes during treatment. Collectively, these findings indicate an association between intestinal barrier functionality and clinical outcomes of anti-PD-1 therapy in advanced melanoma patients.

Background: High-risk human papillomavirus (HPV) contributes to oropharyngeal cancers through mechanisms involving the deregulation of host cell functions by oncoproteins E6 and E7. Changes in the epigenome, particularly involving long non-coding RNAs (lncRNAs), are crucial for understanding HPV-related carcinogenesis. Methods: This study aimed to analyze the expression levels of lncRNAs in HPV-related head and neck squamous cell carcinoma (HNSCC) to determine their biological and clinical significance, addressing the current gap in clinically validated biomarkers for early screening and therapeutic interventions. Results: The study highlights the significant overexpression of the EGOT gene in HPV-positive HNSCC samples, suggesting its potential as a marker to distinguish between HPV-negative and HPV-positive cases. Furthermore, high EGOT expression correlates with better overall survival (OS) and indicates possible resistance to therapy, making it a valuable prognostic factor. Conclusions: These findings underscore the potential of incorporating EGOT expression analysis in clinical practice for improved patient stratification and treatment outcomes in HNSCC.

Atherosclerosis, previously regarded as a lipid storage disease, has now been classified as a chronic inflammatory disease. The hardening of arterial vessels characterizes atherosclerosis due to the accumulation of lipids in the arterial walls, eliciting an inflammatory response. The development of atherosclerosis occurs in various stages and is facilitated by many clinical factors, such as hypertension, hyperlipidemia, and inflammatory status. A large arsenal of cells has been implicated in its development. This review will summarize the phases of atherosclerotic formation and all the cells involved in either promoting or inhibiting its development.

Research has shown that the microbiome can influence how the immune system responds to melanoma cells, affecting the course of the disease and the outcome of the therapy. Here, we used the metagenomic approach and flow cytometry analyses of blood cells to discover correlations between gut fungi of metastatic melanoma patients enrolled in anti-PD-1 therapy and lymphocytes in their blood.We analyzed the patterns of associations before the first administration of anti-PD-1 therapy (BT, n = 61) and in the third month of the therapy (T3, n = 37), allowing us to track changes during treatment. To understand the possible impact of gut fungi on the efficacy of anti-PD-1 therapy, we analyzed the associations in clinical beneficiaries (CB, n = 37) and non-beneficiaries (NB, n = 24), as well as responders (R, n = 28) and non-responders (NR, n = 33).Patients with LDH < 338 units/L, overall survival (OS) > 12, CB, as well as R, had lower levels of Shannon diversity (p = 0.02, p = 0.05, p = 0.05, and p = 0.03, respectively). We found that the correlation pattern between intestinal fungi and lymphocytes was specific to the type of response, positive or negative. When comparing CB and NB groups, correlations with opposite directions were detected for C. albicans, suggesting a response-specific immune reaction. For CB, M. restricta exhibited a set of correlations with different types of lymphocytes, with prevalent positive correlations, suggesting a robust immune response in the CB group. This result extends our former research, where M. restricta and C. albicans were associated with an increased risk of melanoma progression and a poorer response to anti-PD-1 treatment.

Cutaneous melanoma is the deadliest form of skin cancer. Despite advancements in treatment, many patients still face poor outcomes. A deeper understanding of the mechanisms involved in melanoma pathogenesis is crucial for improving diagnosis and therapy. Non-coding RNAs, with their extensive regulatory roles, show promise as diagnostic biomarkers. This study focuses on evaluating the FER1L4 pseudogene and its potential role in melanoma. FER1L4 expression was analyzed in normal melanocytes and melanoma cell lines using qRT-PCR. Additionally, TCGA data and online prediction tools were employed to correlate expression levels with clinicopathological features. The relationship between FER1L4, patient phenotypes, and immune responses was further explored using REACTOME, GSEA, and immune deconvolution analyses. In vitro analysis revealed significant upregulation of FER1L4 in melanoma cells. Its expression levels were influenced by BRAF mutations and were markedly higher in metastatic compared to primary melanomas. Higher FER1L4 expression was associated with improved patient survival. Furthermore, miR-514a-5p, miR-330-5p, and miR-128-3p were identified as interacting with FER1L4. Dysregulated genes involved in immune signaling pathways were also identified as potential miRNA targets. This is the first study to demonstrate the association of FER1L4 with melanoma. Patients with elevated FER1L4 levels exhibited distinct phenotypes, altered immunological profiles, and improved survival rates. These findings suggest that FER1L4 could serve as a potential biomarker for melanoma.

The interplay between cancer and the immune system has captivated researchers for a long time. Recent developments in cancer immunotherapy have substantiated this interest with a significant benefit to cancer patients. Tumor and immune cells are regulated via a wide range of molecular mechanisms involving intricate transcriptional and epigenetic networks. Epigenetic processes influence chromatin structure and accessibility, thus governing gene expression, replication, and DNA damage repair. However, aberrations within epigenetic signatures are frequently observed in cancer. One of the key epigenetic marks is the trimethylation of histone 3 at lysine 9 (H3K9me3), confined mainly within constitutive heterochromatin to suppress DNA accessibility. It is deposited at repetitive elements, centromeric and telomeric loci, as well as at the promoters of various genes. Dysregulated H3K9me3 deposition disrupts multiple pathways, including immune signaling. Consequently, altered H3K9me3 dynamics may modify the efficacy of immunotherapy. Indeed, growing evidence highlights the pivotal roles of various proteins mediating H3K9me3 deposition (SETDB1/2, SUV39H1/2), erasure (KDM3, KDM4 families, KDM7B, LSD1) and interpretation (HP1 proteins, KAP1, CHD4, CDYL, UHRF1) in modulating immunotherapy effectiveness. Here, we review the existing literature to synthesize the available information on the influence of these H3K9me3 writers, erasers, and readers on the response to immunotherapy.

Melanoma is the most aggressive form of skin cancer. In the advanced stage of development, it is resistant to currently available therapeutic modalities. Increased invasiveness and metastatic potential depend on several proteins involved in various signal transduction pathways. Hippo signaling plays a vital role in malignant transformation. Dysfunctions of the Hippo pathway initiate the expression of tumor growth factors and are associated with tumor growth and metastasis formation. This review summarizes the recent achievements in studying the role of the Hippo pathway in melanoma pathogenesis and points to the potential specific targets for anti-melanoma therapy.