Petar Ozretić

The risk of developing some types of head and neck squamous cell carcinoma (HNSCC) is seven times higher in males, and such disparities may not be associated only with tobacco and alcohol consumption or HPV infection. Therefore, the endocrine microenvironment is considered another risk factor, as epidemiologic studies have unequivocally shown the protective effect of estrogen in women. This research was focused on progesterone receptors (PRs), the least-studied sex hormone receptors in HNSCC. Our study included fresh tissue samples from 95 primary tumors, 25 metastatic lymph nodes and 40 healthy oral mucosa. Gene expression of nuclear (PGR) and seven membrane PRs (PAQR5, PAQR6, PAQR7, PAQR8, PAQR9, PGRMC1 and PGRMC2) was analyzed by qRT-PCR and associated with clinicopathological characteristics. The results showed that, compared to control tissue, PGR was increased in metastatic lymph nodes, while PAQR5, PAQR7, PAQR8 and PAQR9 were decreased in primary tumors (all p < 0.05). The expression of almost all PRs was greater in older patients and showed moderate to strong positive mutual correlations in both tumors and controls. PARQ8 and PAQR9 were increased in females and pT4 tumors (all p < 0.05). Survival analysis showed that higher PAQR5 (hazard ratio (HR) 2.8, 95% confidence interval (CI) 1.19–6.57, p = 0.019) and PAQR7 (HR 2.0, 95% CI 1.01–3.81, p = 0.048) were associated with worse overall survival, but their independence was not proven in multivariate analysis. Although most PRs were reduced in primary tumors, an increased PAQR5 expression, also associated with tumor invasion markers, could likely mark a specific aggressive, advanced stage of primary tumors and potentially serve as a negative prognostic biomarker for HNSCC.

An individual's risk of DVT in colorectal cancer patients. Given the prevalence of DVT and that traditional risk assessments may not be accurate indicators of true risk, they showed that the XGBoost model (2) has strong potential for improving early detection and treatment in clinical settings.Identifying novel biomarkers for predicting patient survival time is of crucial practical clinical significance, since it could lead to better patient stratification and treatment decisions. Li et al. (3) used the reactive oxygen species (ROS)-related signature genes, which they identified using the TCGA data, to predict the prognosis and chemotherapy response of patients with bladder cancer. They did not only identify 17 ROS-related genes that exhibited good overall survival in bladder cancer patients, but also 11 potential small molecular drugs that target these ROS-related genes using the Connectivity Map (CMap) database (4).Using ML models to predict response to treatment could lead to the development of more personalized treatment, leading to significant improvement in patient outcomes. Guo et al. (5) developed the Artificial Intelligence-Derived Anoikis Signature (AIDAS), a novel machine learning-based prognostic tool for breast cancer. AIDAS identifies key gene expression patterns related to anoikis, a form of programmed cell death triggered by detachment from the extracellular matrix. Using AIDAS, the authors found they could more accurately predict breast cancer outcomes compared to existing prognostic models. They discovered that patients with low AIDAS levels may be more responsive to immunotherapy, while those with high AIDAS levels are more susceptible to certain chemotherapies like methotrexate. Zhu et al. (6) showed the crucial role of autophagy in acute myeloid leukemia (AML) prognosis, identifying essential autophagy genes that correlate with patient survival. Using ML, they developed a predictive model that aids risk stratification and suggested potential therapeutic targets. Their findings also reveal a link between autophagy and the immune microenvironment, offering insights for future research and clinical applications.Due to the large difference in survival of patients with moderately differentiated gastric adenocarcinoma (MDGA) with distant metastases and without metastases, it becomes important to predict the occurrence of distant metastases after surgical treatment, after morphological examination of all removed lymph nodes, and after final staging of the disease. Yang et al. (7) collected data from MDGA patients from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2019, as well as data from MDGA patients in China. Based on these data they conducted univariate and multivariate analyses, and factors were identified that contribute to the occurrence of distant metastases and worsen the prognosis of the disease.Prostate cancer is a highly metastatic tumor, and it is estimated that about 50% of patients with advanced disease will develop bone metastases. Once bone metastasis occurs, it is incurable and is significantly associated with mortality. The STING signaling pathway is an important transduction mechanism in innate immunity and viral defense, and it has been demonstrated that this pathway plays a key role in tumorigenesis and metastasis (8). In their study, Li et al. ( 8) extrapolated three key STING pathway genes related to bone metastasis based on a machine learning algorithm. After comprehensive analysis, it was verified that these three genes have key roles in prostate cancer development, metastasis, and tumor immunity, while RELA or transcription factor p65 is a highly potential therapeutic target.Ding et al. (10) explored the role of FAT1, which is crucial for cellular adhesion and cell signaling, in lung cancer cell lines. The authors identified FAT1 mutations in five out of thirty-seven individuals diagnosed with non-small cell lung cancer (NSCLC), using next-generation sequencing (NGS) technology. These mutations included four missense mutations and one splice variant. The frequency of FAT1 mutations was the third highest, following those in EGFR and TP53 genes. The study further demonstrated correlations between FAT1 expression and methylation with the malignancy of certain cancer types. Knockdown of FAT1 in A549 and H1299 lung cancer cell lines led to downregulated PD-L1 expression. Additionally, FAT1 knockdown significantly inhibited cell proliferation, colony formation, and migration. It also affected the cell cycle and the FAK-YAP/TAZ signaling pathway, ultimately inhibiting the proliferation of lung cancer cells in vivo.In their retrospective study, Huang et 12) conducted an in-depth study on immune-related genes in hepatocellular carcinoma (HCC) using extensive datasets and robust bioinformatics methods, leading to the development of the Subtype-specific and Immune-Related Prognostic Signatures (SIR-PS) model. The SIR-PS model effectively predicted survival outcomes and immunotherapy responses in HCC patients, providing meaningful guidance for personalized immunotherapy.High serum levels of hepatitis B surface antigen (HBsAg) increase the risk of developing HCC and have a worse prognosis for patients who have already developed HCC. Xiong et al. (13) compared the effects of high and low levels of HBsAg in HCC patients undergoing transarterial chemoembolization (TACE) and sequential ablation and utilized propensity score matching to minimize selection bias. In addition, they created a nomogram to predict the prognosis of HCC patients with high levels of HBsAg after local treatment to more accurately guide the clinical decision.Cancer incidence rises with aging, even though there are more senescent cells that have stopped dividing as we age. In their bioinformatics study, Ru et al. (14) explored the molecular and immune landscape of cellular senescence in lung adenocarcinoma using publicly available TCGA and GEO datasets to...

Proliferative verrucous leukoplakia (PVL) is a rare and aggressive oral potentially malignant disorder (OPMD) characterized by multifocal keratotic plaques, progressive expansion, high recurrence, and a strong risk of malignant transformation. Although its etiology remains unclear, recent evidence emphasizes the role of the oral microbiome as a key factor in disease progression. Alterations in microbial diversity and ecological balance create a shift toward dysbiosis, supporting a chronic inflammatory microenvironment that favors epithelial transformation. Specific taxa, including Fusobacterium and Porphyromonas, have been implicated in biofilm formation, immune evasion, and modulation of epithelial signaling pathways. These interactions highlight the potential of microbial communities to drive oncogenic processes through host–microbe crosstalk. Advanced methodological approaches such as metagenomics, functional microbiome profiling, and multi-omics integration provide novel opportunities to unravel the mechanisms of dysbiosis in PVL. Beyond pathogenesis, microbiome research opens perspectives for the identification of predictive biomarkers, targeted prevention, and microbiome-based therapeutics. This review synthesizes current insights into the microbial basis of PVL and outlines future directions aimed at improving understanding of host–microbe interactions and their role in oral carcinogenesis. Relevant literature was identified through PubMed and Web of Science searches (1985–2025) using terms related to PVL, oral leukoplakia, OPMD, oral microbiome, and oral squamous cell carcinoma. In conclusion, current evidence suggests that while microbial dysbiosis is not an isolated driver, it likely synergizes with genetic, epigenetic, and immunological factors in PVL progression, offering opportunities for biomarker discovery and novel therapeutic strategies. This study also provides a potential direction for the early diagnosis of PVL and the development of microecologically targeted interventions.

Desquamative gingivitis (DG) is a clinical presentation characterized by erythema, epithelial desquamation, and mucosal fragility, commonly associated with immune-mediated diseases such as oral lichen planus (OLP), mucous membrane pemphigoid (MMP), and pemphigus vulgaris (PV). While traditionally viewed as a manifestation of immune dysregulation, growing evidence suggests that the oral microbiome may modulate disease onset, persistence, and severity. This review summarizes current knowledge on the oral microbiota in DG and its underlying diseases, explores mechanistic links between dysbiosis and immune activation, and discusses clinical and research implications. A narrative literature review was conducted using PubMed and Scopus, focusing on studies analyzing the oral microbiome in OLP, MMP, and PV. Emphasis was placed on molecular microbiology techniques, immune profiling, and functional or longitudinal approaches. In OLP, microbial dysbiosis is consistently reported, including reduced diversity and increased abundance of pro-inflammatory genera such as Fusobacterium, Prevotella, and Capnocytophaga. These shifts correlate with epithelial barrier disruption and inflammatory cytokine production. Although data on MMP and PV are limited, early findings suggest microbial involvement in sustaining inflammation, delaying healing, and possibly amplifying autoimmune responses. Dysbiosis may activate Toll-like receptors, skew T cell responses, and contribute to the breakdown of immune tolerance. DG may reflect a dynamic interplay between immune mechanisms and microbial ecology. While evidence is strongest for OLP, preliminary data suggest broader microbial contributions across DG-associated diseases. Microbiome-informed approaches could enhance diagnostic accuracy and support the development of adjunctive therapies.

Inflammatory facial dermatoses (atopic dermatitis [AD], acne vulgaris, contact dermatitis, seborrheic dermatitis, rosacea, perioral dermatitis, and demodicosis, etc.) often profoundly impact patients’ appearance and psychological well-being. In this narrative review, we wanted to present the current knowledge on the role of skin microbiota in common facial dermatoses. Skin keratinocytes are the primary producers of antimicrobial peptides (AMPs) and express Toll-like receptors (TLRs), which stimulate the T helper (Th1) immune response, with the production of interferon (IFN). They can also produce certain pro-inflammatory cytokines, namely IL-1β, IL-18, IL-6, IL-10, and the tumor necrosis factor (TNF). In healthy infants, the bacterial skin microbiota is predominantly composed of Firmicutes (genera Staphylococcus and Streptococcus), as well as Actinobacteria, Proteobactera, and Bacteroidota. The genera Cutibacterium and Staphylococcus, which have antimicrobial effects and compete with pathogens for nutrients/ecological niches, coexist symbiotically on the skin and can reduce the expression of TLR2 and TLR4. In patients with AD, lesional/non-lesional skin was found to have increased colonization by Staphylococcus aureus which reduces effector T lymphocytes’ ability to produce cytokines, such as IL-17A and IFN-γ, leading to decreased AMP production and impaired skin microbiota immune functionality. In patients with rosacea, the overexpression of TLR2 may stimulate elevated pro-inflammatory cytokine production (IL-8, IL-1β, and TNF-α, etc.), exacerbating the inflammatory response. Also, increased colonization by Malassezia yeasts triggers a Th2 immune response and cytokine secretion (IL-1α, IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, TNF-α, beta-defensin, IFN-γ, nitric oxide, and histamine), and participates in signaling pathways. Insight into these factors may further improve clinical approaches to patients with facial dermatoses.

This study aims to evaluate the potential benefits and challenges of integrating oral microbiome research into the clinical management of oral potentially malignant disorders (OPMD) and oral squamous cell carcinoma (OSCC). The oral microbiome has gained significant attention for its role in the pathogenesis and progression of these conditions, with emerging evidence suggesting its value as a diagnostic and prognostic tool. By critically analyzing current evidence and methodological considerations, this manuscript examines whether microbiome analysis in biopsy samples can aid in the early detection, prognosis, and management of OPMD and OSCC. The complexity and dynamic nature of the oral microbiome require a multifaceted approach to fully understand its clinical utility. Based on this review, we conclude that studying the oral microbiome in this context holds significant promise but also faces notable challenges, including methodological variability and the need for standardization. Ultimately, this manuscript addresses the question, “Should such research be undertaken, given the intricate interactions of various factors and the inherent obstacles involved?”, and also emphasizes the importance of further research to optimize clinical applications and improve patient outcomes.

Epitranscriptomics is the study of modifications of RNA molecules by small molecular residues, such as the methyl (-CH₃) group. These modifications are inheritable and reversible. A specific group of enzymes called “writers” introduces the change to the RNA; “erasers” delete it, while “readers” stimulate a downstream effect. Epitranscriptomic changes are present in every type of organism from single-celled ones to plants and animals and are a key to normal development as well as pathologic processes. Oncology is a fast-paced field, where a better understanding of tumor biology and (epi)genetics is necessary to provide new therapeutic targets and better clinical outcomes. Recently, changes to the epitranscriptome have been shown to be drivers of tumorigenesis, biomarkers, and means of predicting outcomes, as well as potential therapeutic targets. In this review, we aimed to give a concise overview of epitranscriptomics in the context of neoplastic disease with a focus on N¹-methyladenosine (m¹A) modification, in layman’s terms, to bring closer this omics to clinicians and their future clinical practice.

(1) Background: Periocular or periorbital dermatitis is a common term for all inflammatory skin diseases affecting the area of skin around the eyes. The clear etiopathogenesis of periocular dermatitis is still not fully understood. Advances in molecular techniques for studying microorganisms living in and on our bodies have highlighted the microbiome as a possible contributor to disease, as well as a promising diagnostic marker and target for innovative treatments. The aim of this study was to compare the composition and diversity of the skin microbiota in the periocular region between healthy individuals and individuals affected by the specific entity of periocular dermatitis. (2) Methods: A total of 35 patients with periocular dermatitis and 39 healthy controls were enrolled in the study. After a skin swab from the periocular region was taken from all participants, DNA extraction and 16S rRNA gene amplicon sequencing using Illumina NovaSeq technology were performed. (3) Results: Staphylococcus and Corynebacterium were the most abundant bacterial genera in the microbiota of healthy skin. Analysis of alpha diversity revealed a statistically significant change (p < 0.05) in biodiversity based on the Faith’s PD index between patients and healthy individuals. We did not observe changes in beta diversity. The linear discriminant analysis effect size (LEfSe) revealed that Rothia, Corynebacterium, Bartonella, and Paracoccus were enriched in patients, and Anaerococcus, Bacteroides, Porphyromonas, and Enhydrobacter were enriched in healthy controls. (4) Conclusions: According to the results obtained, we assume that the observed changes in the bacterial microbiota on the skin, particularly Gram-positive anaerobic cocci and skin commensals of the genus Corynebacterium, could be one of the factors in the pathogenesis of the investigated inflammatory diseases. The identified differences in the microbiota between healthy individuals and patients with periocular dermatitis should be further investigated.

Although not completely understood, the role of the Hedgehog-GLI (HH-GLI) signaling pathway in melanoma and epithelial skin tumors has been reported before. In this study, we confirmed in various melanoma cell line models that keratin 16 (KRT16) and S100 Calcium-Binding Protein A7 (S100A7) are transcriptional targets of GLI Family Zinc Finger (GLI) proteins. Besides their important role in protecting and maintaining the epidermal barrier, keratins are somehow tightly connected with the S100 family of proteins. We found that stronger expression of KRT16 indeed corresponds to stronger expression of S100A7 in our clinical melanoma samples. We also report a trend regarding staining of GLI1, which corresponds to stronger staining of GLI3, KRT16, and S100A7 proteins. The most interesting of our findings is that all the proteins are detected specifically in the epidermis overlying the tumor, but rarely in the tumor itself. The examined proteins were also not detected in the healthy epidermis at the edges of the sample, suggesting that the staining is specific to the epidermis overlaying the tumor mass. Of all proteins, only S100A7 demonstrated a statistically significant trend regarding tumor staging and staining intensity. Results from our clinical samples prove that immune infiltration is an important feature of melanoma. Pigmentophages and tumor-infiltrating lymphocytes (TIL) demonstrate a significant association with tumor stage, while mononuclear cells are equally present in all stages. For S100A7, we found an association between the number of TILs and staining intensity. Considering these new findings presented in our study, we suggest a more detailed examination of the possible role of the S100A7 protein as a biomarker in melanoma.