HOXB7 acts as an oncogenic biomarker in head and neck squamous cell carcinoma

Unveiling HOXB7 as a novel diagnostic and prognostic biomarker through pan-cancer computer screening

We attempted to investigate the role of HOXB7 in tumor progression and evolution by means of an extensive computer screening analysis of various cancer types. We performed univariate Cox regression and Kaplan-Meier survival analyses to assess the impact of HOXB7 on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in different types of cancer. Furthermore, we examined the relationship between HOXB7 and several clinical features: tumor microenvironment, immune regulatory genes, immune checkpoints, tumor mutational burden (TMB), and microsatellite instability (MSI). We performed gene set enrichment analysis to gain deeper insights into the potential molecular mechanisms of HOXB7, and validated our findings through functional assays in cells, including methyl thiazolyl tetrazolium cytotoxicity and Transwell invasion assays. HOXB7 expression was associated with different clinical characteristics in numerous malignancies. Higher HOXB7 expression was associated with worse OS, DSS, and PFI in some cancer types. In particular, HOXB7 expression was favorably associated with immune cell infiltration, immune regulatory genes, immunological checkpoints, TMB, and MSI in malignancies. Furthermore, we identified a strong link between copper death-associated gene expression and HOXB7 expression. According to the findings of this study, HOXB7 might serve as an appealing focus for tumor diagnosis and immunotherapy and a prospective indicator of prognosis.

The biomarkers for maintenance Cancer stem cell features can be applicable in precision medicine of head and neck squamous cell carcinoma

Cancer stem cells (CSCs) play a crucial role in tumor relapse, proliferation, invasion, and drug resistance in head and neck squamous cell carcinoma (HNSCC). This narrative review aims to synthesize data from articles published between 2019 and 2023 on biomarkers for detecting CSCs in HNSCC and changes in molecular pathways, genetics, epigenetics, and non-coding RNAs (ncRNAs) in CSCs relevant to precision medicine approaches in HNSCC management. The search encompassed 41 in vitro studies and 22 clinical studies. CSCs exhibit diverse molecular profiles and unique biomarker expression patterns, offering significant potential for HNSCC diagnosis, treatment, and prognosis, thereby enhancing patient survival. Their remarkable self-renewal ability and adaptability are closely linked to tumorigenicity development and maintenance. Assessing biomarkers before and after therapy can aid in identifying various cell types associated with cancer progression and relapse. Screening for CSCs, senescent tumor cells, and cells correlated with the senescence process post-treatment has proven highly beneficial. However, the clinical application of precision medicine in HNSCC management is hindered by the lack of specific and definitive CSC biomarkers. Furthermore, our limited understanding of CSC plasticity, governed by genomic, transcriptomic, and epigenomic alterations during tumorigenesis, as well as the bidirectional interaction of CSCs with the tumor microenvironment, underscores the need for further research. Well-designed studies involving large patient cohorts are, therefore, essential to establish a standardized protocol and address these unresolved queries.

Case report: Squamous cell carcinoma of the prostate-a clinicopathological and genomic sequencing-based investigation

Squamous differentiation of prostate cancer, which accounts for less than 1% of all cases, is typically associated with androgen deprivation treatment (ADT) or radiotherapy. This entity is aggressive and exhibits poor prognosis due to limited response to traditional treatment. However, the underlying molecular mechanisms and etiology are not fully understood. Previous findings suggest that squamous cell differentiation may potentially arise from prostate adenocarcinoma (AC), but further validation is required to confirm this hypothesis. This paper presents a case of advanced prostate cancer with a combined histologic pattern, including keratinizing SCC and AC. The study utilized whole-exome sequencing (WES) data to analyze both subtypes and identified a significant overlap in driver gene mutations between them. This suggests that the two components shared a common origin of clones. These findings emphasize the importance of personalized clinical management for prostate SCC, and specific molecular findings can help optimize treatment strategies.

Investigation of LGALS2 expression in the TCGA database reveals its clinical relevance in breast cancer immunotherapy and drug resistance

Breast cancer (BRCA) is known as the leading cause of death in women worldwide and has a poor prognosis. Traditional therapeutic strategies such as surgical resection, radiotherapy and chemotherapy can cause adverse reactions such as drug resistance. Immunotherapy, a new treatment approach with fewer side effects and stronger universality, can prolong the survival of BRCA patients and even achieve clinical cure. However, due to population heterogeneity and other reasons, there are still certain factors that limit the efficacy of immunotherapy. Therefore, the importance of finding new tumor immune biomarker cannot be emphasized enough. Studies have reported that LGALS2 was closely related to immunotherapy efficacy, however, it is unclear whether it can act as an immune checkpoint for BRCA immunotherapy. In the current study, changes in LGALS2 expression were analyzed in public datasets such as TCGA-BRCA. We found that LGALS2 expression was associated with immune infiltration, drug resistance and other characteristics of BRCA. Moreover, high LGALS2 expression was closely related to immunotherapy response, and was associated with methylation modifications and clinical resistance for the first time. These findings may help to elucidate the role of LGALS2 in BRCA for the development and clinical application of future immunotherapy strategies against BRCA.

Analysis of myosin genes in HNSCC and identify MYL1 as a specific poor prognostic biomarker, promotes tumor metastasis and correlates with tumor immune infiltration in HNSCC

Head neck squamous cell carcinoma (HNSCC) is one of the most common malignant tumors which ranks the sixth incidence in the world. Although treatments for HNSCC have improved significantly in recent years, its recurrence rate and mortality rate remain high. Myosin genes have been studied in a variety of tumors, however its role in HNSCC has not been elucidated. GSE58911 and GSE30784 gene expression profile analysis were performed to detect significantly dys-regulated myosin genes in HNSCC. The Cancer Genome Atlas (TCGA) HNSCC database was used to verify the dys-regulated myosin genes and study the relationship between these genes and prognosis in HNSCC. The results showed that MYL1, MYL2, MYL3, MYH2, and MYH7 were down-regulated, while MYH10 was up-regulated in patients with HNSCC. Interestingly, MYL1, MYL2, MYH1, MYH2, and MYH7 were shown to be unfavorable prognostic markers in HNSCC. It is also worth noting that MYL1 was a specific unfavorable prognostic biomarker in HNSCC. MYL1, MYL2, MYL3, MYH2, MYH7, and MYH10 promoted CD4 + T cells activation in HNSCC. MYL1 was proved to be down-regulated in HNSCC tissues compared to normal tissues at protein levels. MYL1 overexpression had no effect on proliferation, but significantly promoted migration of Fadu cells. MYL1 increased EGF and EGFR protein expression levels. Moreover, there is a positive correlation between MYL1 expression and Tcm CD8 cells, Tcm CD4 + cells, NK cells, Mast cells, NKT cells, Tfh cells and Treg cells in HNSCC. Overall, MYL1 facilitates tumor metastasis and correlates with tumor immune infiltration in HNSCC and these effects may be associated with the EGF/EGFR pathway.

Differentially Expressed Genes, miRNAs and Network Models: A Strategy to Shed Light on Molecular Interactions Driving HNSCC Tumorigenesis

Head and neck squamous cell carcinoma (HNSCC) is among the most common cancer worldwide, accounting for hundreds thousands deaths annually. Unfortunately, most patients are diagnosed in an advanced stage and only a percentage respond favorably to therapies. To help fill this gap, we hereby propose a retrospective in silico study to shed light on gene-miRNA interactions driving the development of HNSCC. Moreover, to identify topological biomarkers as a source for designing new drugs. To achieve this, gene and miRNA profiles from patients and controls are holistically reevaluated using protein-protein interaction (PPI) and bipartite miRNA-target networks. Cytoskeletal remodeling, extracellular matrix (ECM), immune system, proteolysis, and energy metabolism have emerged as major functional modules involved in the pathogenesis of HNSCC. Of note, the landscape of our findings depicts a concerted molecular action in activating genes promoting cell cycle and proliferation, and inactivating those suppressive. In this scenario, genes, including VEGFA, EMP1, PPL, KRAS, MET, TP53, MMPs and HOXs, and miRNAs, including mir-6728 and mir-99a, emerge as key players in the molecular interactions driving HNSCC tumorigenesis. Despite the heterogeneity characterizing these HNSCC subtypes, and the limitations of a study pointing to relationships that could be context dependent, the overlap with previously published studies is encouraging. Hence, it supports further investigation for key molecules, both those already and not correlated to HNSCC.

Identification of Novel Prognostic Markers Associated With Laryngeal Squamous Cell Carcinoma Using Comprehensive Analysis

Background

Laryngeal squamous cell carcinoma (LSCC) is a leading malignant cancer of the head and neck. Patients with LSCC, in which the cancer has infiltrated and metastasized, have a poor prognosis. Therefore, there is an urgent need to identify more potential targets for drugs and biomarkers for early diagnosis.

Methods

RNA sequence data from LSCC and patients’ clinical traits were obtained from the Gene Expression Omnibus (GEO) (GSE142083) and The Cancer Genome Atlas (TCGA) database. Differentially expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify hub genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, prognostic value analysis, receiver operating characteristic (ROC) curve analysis, gene mutation analysis, tumor-infiltrating immune cell abundance profile estimation, gene set variation analysis (GSVA), and gene set enrichment analysis (GSEA) were performed. Single-gene RNA sequencing data were obtained from the GSE150321 dataset. Cell proliferation and viability were confirmed by the CCK-8 assay and real-time PCR.

Results

A total of 701 DEGs, including 329 upregulated and 372 downregulated genes, were screened in the GSE142083 dataset. Using WGCNA, three modules were identified to be closely related to LSCC. After intersecting the DEGs and performing univariate and multivariate Cox analyses, a novel prognostic model based on three genes (SLC35C1, HOXB7, and TEDC2) for LSCC was established. Interfering TEDC2 expression inhibited tumor cell proliferation and migration.

Conclusions

Our results show that SLC35C1, HOXB7, and TEDC2 have the potential to become new therapeutic targets and prognostic biomarkers for LSCC.

The Role of Gut Microbiota and Microbiota-Related Serum Metabolites in the Progression of Diabetic Kidney Disease

Objective: Diabetic kidney disease (DKD) has become the major cause of end-stage renal disease (ESRD) associated with the progression of renal fibrosis. As gut microbiota dysbiosis is closely related to renal damage and fibrosis, we investigated the role of gut microbiota and microbiota-related serum metabolites in DKD progression in this study.

Methods: Fecal and serum samples obtained from predialysis DKD patients from January 2017 to December 2019 were detected using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry, respectively. Forty-one predialysis patients were divided into two groups according to their estimated glomerular filtration rate (eGFR): the DKD non-ESRD group (eGFR ≥ 15 ml/min/1.73 m²) (n = 22), and the DKD ESRD group (eGFR < 15 ml/min/1.73 m²) (n = 19). The metabolic pathways related to differential serum metabolites were obtained by the KEGG pathway analysis. Differences between the two groups relative to gut microbiota profiles and serum metabolites were investigated, and associations between gut microbiota and metabolite concentrations were assessed. Correlations between clinical indicators and both microbiota-related metabolites and gut microbiota were calculated by Spearman rank correlation coefficient and visualized by heatmap.

Results: Eleven different intestinal floras and 239 different serum metabolites were identified between the two groups. Of 239 serum metabolites, 192 related to the 11 different intestinal flora were mainly enriched in six metabolic pathways, among which, phenylalanine and tryptophan metabolic pathways were most associated with DKD progression. Four microbiota-related metabolites in the phenylalanine metabolic pathway [hippuric acid (HA), L-(−)-3-phenylactic acid, trans-3-hydroxy-cinnamate, and dihydro-3-coumaric acid] and indole-3 acetic acid (IAA) in the tryptophan metabolic pathway positively correlated with DKD progression, whereas L-tryptophan in the tryptophan metabolic pathway had a negative correlation. Intestinal flora g_Abiotrophia and g_norank_f_Peptococcaceae were positively correlated with the increase in renal function indicators and serum metabolite HA. G_Lachnospiraceae_NC2004_Group was negatively correlated with the increase in renal function indicators and serum metabolites [L-(−)-3-phenyllactic acid and IAA].

Conclusions: This study highlights the interaction among gut microbiota, serum metabolites, and clinical indicators in predialysis DKD patients, and provides new insights into the role of gut microbiota and microbiota-related serum metabolites that were enriched in the phenylalanine and tryptophan metabolic pathways, which correlated with the progression of DKD.