Significance of p16 in Site-Specific Human Papillomavirus-Positive and Negative Head and Neck Squamous Cell Carcinoma (HNSCC).

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) represents a group of cancers characterized by diverse origins and changing epidemiological patterns. The significance of high-risk human papillomavirus (HPV) infection in certain HNSCC cases has gained attention for its impact on the disease's behavior. Our current research focused on exploring the importance of using p16 as an HNSCC biomarker, particularly in the context of HPV infection, assessing its value in prognosis, and examining its variation across different tumor locations. MATERIALS AND METHODS: A retrospective analysis was carried out on 100 HNSCC patients from a tertiary care center, with particular attention paid to p16 expression, HPV status, clinic-pathological characteristics, and prognosis. HPV was detected using polymerase chain reaction (PCR) techniques, and p16 expression was evaluated by immunohistochemistry. According to the ethical guidelines outlined in the Declaration of Helsinki, multivariate analysis assessed the prognostic value of p16. RESULTS: Our analysis demonstrated a significant correlation between HPV status and p16 expression in HNSCC cases. A vast majority of 58 (96.7%) HPV-+ cases exhibited p16 overexpression, contrasting sharply with only two (5%) in the HPV-- group. Patients with tumors that were both p16+ and HPV+ exhibited more favorable overall survival rates. In contrast, those with p16- and HPV- tumors experienced the poorest survival outcomes. Notably, having a p16-- status in HPV+ cases emerged as an independent factor for reduced survival. Additionally, the study revealed distinct variations in p16 expression based on tumor location, particularly within the oropharyngeal area. CONCLUSION: The study established that p16 is a dependable indication for the existence of HPV in HNSCC and highlights its significant role as a prognostic factor, particularly in cases that are p16-- yet HPV-+. These findings underscore the importance of adopting site-specific treatment approaches in HNSCC management and contribute to a deeper understanding of p16's role in the disease, thereby aiding in more effective risk assessment and treatment planning.

Immune landscape of hepatocellular carcinoma: The central role of TP53-inducible glycolysis and apoptosis regulator.

Objective: This study aims to address the substantive issue of lacking reliable prognostic biomarkers in hepatocellular carcinoma (HCC) by investigating the relationship between TP53-inducible glycolysis and apoptosis regulator (TIGAR) and HCC prognosis using The Cancer Genome Atlas database. Methods: (1) Integrated statistical analyses, including logistic regression, Wilcoxon signed-rank test, and Kruskal-Wallis test, were conducted to explore the association between TIGAR expression and clinical-pathological features of HCC. (2) The Kaplan-Meier method combined with univariate and multivariate Cox regression models underscored TIGAR as a prognostic factor in HCC. (3) Gene set enrichment analysis (GSEA) revealed key pathways associated with TIGAR, while single-sample gene set enrichment analysis (ssGSEA) determined its relevance to cancer immune infiltration. Results: (1) Elevated TIGAR expression was significantly correlated with decreased survival outcomes in HCC patients. (2) GSEA highlighted the significant link between TIGAR and humoral immunity. (3) ssGSEA revealed a positive correlation between TIGAR expression and infiltration of Th1 and Th2 cells and a negative correlation with Th17 cell infiltration. Conclusion: TIGAR, as a potential prognostic biomarker for HCC, holds significant value in immune infiltration. Understanding the role of TIGAR could contribute to improved prognostic predictions and personalized treatment strategies for HCC patients.

Influence of tumour grade on disease survival in male breast cancer patients: a systematic review.

PURPOSE: Histological grading of tumours is a well-established biomarker used to guide treatment in female breast cancer. However, its significance in male breast cancer remains unclear. This systematic review investigates the prognostic significance of tumour grade in relation to breast cancer-specific survival (BCSS) in male breast cancer patients undergoing surgery. METHODS: MEDLINE, PUBMED Central and EMBASE databases were searched to identify randomised trials and observational studies related to male breast neoplasms, tumour grading, recurrence, and survival. RESULTS: A total of fifteen observational type studies were included in the review. A significant association between tumour grade and BCSS was reported in a majority of studies. This association was most evident with regard to high-grade (grade III) compared to low grade (grade I) tumours, with a significant relationship in 4 out of 4 studies. For intermediate-grade II tumours an association was demonstrated in a minority of studies. CONCLUSIONS: This study confirms an association between high-grade male breast cancers and poorer disease-specific survival, however, the significance of intermediate-grade tumours remains unclear. Further research is required to investigate the biology of male breast cancer in relation to histological grade and optimally define intermediate-grade disease.

CCND1 as a Prognostic and Diagnostic Biomarker and the Impact of Its Epigenetic Alterations on Cancer Survival.

BACKGROUND: Cyclin D1 (CCND1) plays a crucial role in cell cycle regulation and has been implicated in various cancers. As is well known, cancer is caused by the accumulation of detrimental variations in the genome. In this study, we shed light on the role of CCND1 in the diagnosis and progression of cancer and aimed to provide a comprehensive analysis of CCND1 across multiple cancer types, focusing on its expression, clinical correlations, DNA methylation status, prognostic implications, genetic alterations, and immune infiltration. METHODS: Gene expression analysis of CCND1 was conducted across 33 cancer types using the TIMER, GEPIA, and UALCAN databases. Clinical parameters were investigated to assess their correlations with CCND1 expression. Methylation analysis was performed using the UALCAN and GSCA databases to investigate the relationship between CCND1 promoter methylation and gene expression and their association with survival. Immune infiltration and survival analyses were performed to explore the prognostic implications of CCND1 expression in various cancers. Statistical tests, such as the Cox proportional hazards model and the Kaplan-Meier analysis, were used to assess survival outcomes. Additionally, genetic alteration analysis was performed using the cBioPortal database to examine the prevalence and types of CCND1 alterations across different cancer types. RESULTS: CCND1 expression was significantly elevated in 13 cancers compared to normal tissues, with distinct patterns observed across different cancer types. It is highly expressed in BLCA, CHOL, COAD, ESCA, GBM, HNSC, KIRC, PAAD, RRAD, READ, STAD, THCA, and UCEC. The investigation of clinical parameters revealed associations between CCND1 expression and factors such as age, gender, race, and cancer stage. The methylation analysis highlighted hypomethylation of CCND1 across the 13 selected cancer types. The survival analysis identified both favorable and unfavorable prognostic implications of CCND1 expression in different cancers and revealed that a high expression of CCND1 was associated with a poor prognosis in HNSC and PAAD, while a high expression of CCND1 was associated with a good prognosis in KIRC, STAD, THCA, and UCEC. In the immune infiltration analysis of various cancers, many statistically significant correlations were observed between the immune cell types and tumor purity. For example, in BLCA, neutrophils and dendritic cells showed statistically significant positive correlations and a negative correlation with macrophages. While in CHOL patients, none of the immune cell types showed a significant correlation. Similar statistical significance was observed in other cancer types, such as COAD, HNSC, GBM, KIRC, PAAD, PRAD, READ, and STAD, with different immune cell types. The genetic alteration analysis revealed that amplification was the predominant genetic alteration type in CCND1, with specific patterns observed in different cancer types. CONCLUSION: The findings of this study provide valuable insights into the role of CCND1 in cancer diagnosis and progression, and its potential for targeted therapies. CCND1 could be used as a potential diagnostic biomarker for the COAD, ESCA, KIRC, READ, STAD, and THCA stages. Furthermore, CCND1 could be used as a potential prognostic biomarker for HNSC, KIRC, and PAAD. Also, the correlation between CCND1 methylation and expression could be used as a potential diagnostic and prognostic biomarker for ESCA, HNSC, and STAD.

Prognostic value of a novel myeloid-to-lymphoid ratio biomarker in advanced gastric cancer.

BACKGROUND: Currently, immune checkpoint inhibitors (ICIs) have excellent performance in the clinical treatment of advanced gastric cancer (AGC). However, precisely selecting AGC patients who can benefit from immunotherapy is an urgent difficulty. In this study, we investigated the immunoprognostic role of myeloid-to-lymphocyte ratio (M:L) in AGC patients. METHODS: We collected information on 268 AGC patients who were hospitalized in the Department of Medical Oncology of PLA General Hospital from December 2014 to May 2021. The patients were divided into low M: L group (< 3.76) and high M:L group (≥ 3.76). Survival differences between different M: L level groups at baseline and after treatment were analyzed by methods such as Kaplan-Meier, Cox or Logistic regression model. RESULTS: Progression free survival (PFS) (5.8 months vs. 3.4 months, p = 0.001) and overall survival (OS) (14.1 months vs. 9.0 months, p = 0.001) were significantly longer in the low M:L group than in the high M:L group. After analyses of Cox regression modeling it was concluded that M:L was an independent prognostic factor for PFS (HR 1.371 95%CI 1.057-1.777 p = 0.017) and OS (HR 1.352 95%CI 1.003-1.824 p = 0.048), respectively. Subsequent subgroup analyses performed across immunotherapy lines, regimens, PD-1 inhibitor agents, and age groups revealed a poorer prognosis in the high M:L group. Notably, an increase in the value of M:L after treatment significantly increased the risk of poor prognosis. CONCLUSIONS: M:L ≥ 3.76 is associated with poor prognostic outcomes in AGC patients receiving immunotherapy and may be a predictive biomarker of prognosis. This result needs to be confirmed by larger prospective studies.

Clinical Applications of Radiomics and Deep Learning in Breast and Lung cancer: a Narrative Literature Review on Current Evidence and Future Perspectives.

Radiomics, analysing quantitative features from medical imaging, has rapidly become an emerging field in translational oncology. Radiomics has been investigated in several neoplastic malignancies as it might allow for a non-invasive tumour characterization and for the identification of predictive and prognostic biomarkers. Over the last few years, evidence has been accumulating regarding potential clinical applications of machine learning in many crucial moments of cancer patients' history. However, the incorporation of radiomics in clinical decision-making process is still limited by low data reproducibility and study variability. Moreover, the need for prospective validations and standardizations is emerging. In this narrative review, we summarize current evidence regarding radiomic applications in high-incidence cancers (breast and lung) for screening, diagnosis, staging, treatment choice, response, and clinical outcome evaluation. We also discuss pro and cons of the radiomic approach, suggesting possible solutions to critical issues which might invalidate radiomics studies and propose future perspectives.

HIGD1B, as a novel prognostic biomarker, is involved in regulating the tumor microenvironment and immune cell infiltration; its overexpression leads to poor prognosis in gastric cancer patients.

Background: HIGD1B (HIG1 Hypoxia Inducible Domain Family Member 1B) is a protein-coding gene linked to the occurrence and progression of various illnesses. However, its precise function in gastric cancer (GC) remains unclear. Methods: The expression of HIGD1B is determined through the TCGA and GEO databases and verified using experiments. The association between HIGD1B and GC patients' prognosis was analyzed via the Kaplan-Meier (K-M) curve. Subsequently, the researchers utilized ROC curves to assess the diagnostic capacity of HIGD1B and employed COX analysis to investigate risk factors for GC. The differentially expressed genes (DEGs) were then subjected to functional enrichment analysis, and a nomogram was generated to forecast the survival outcome and probability of GC patients. Additionally, we evaluated the interaction between HIGD1B and the immune cell infiltration and predicted the susceptibility of GC patients to therapy. Results: HIGD1B is markedly elevated in GC tissue and cell lines, and patients with high HIGD1B expression have a poorer outcome. In addition, HIGD1B is related to distinct grades, stages, and T stages. The survival ROC curves of HIGD1B and nomogram for five years were 0.741 and 0.735, suggesting appropriate levels of diagnostic efficacy. According to Cox regression analysis, HIGD1B represents a separate risk factor for the prognosis of gastric cancer (p<0.01). GSEA analysis demonstrated that the HIGD1B is closely related to cancer formation and advanced pathways. Moreover, patients with high HIGD1B expression exhibited a higher level of Tumor-infiltration immune cells (TIICs) and were more likely to experience immune escape and drug resistance after chemotherapy and immunotherapy. Conclusion: This study explored the potential mechanisms and diagnostic and prognostic utility of HIGD1B in GC, as well as identified HIGD1B as a valuable biomarker and possible therapeutic target for GC.

Pretreatment pulmonary tumor necrosis is a promising prognostic imaging biomarker for first-line anti-PD-1/PD-L1 therapy in advanced lung squamous cell carcinoma: a multi-institutional, propensity score-matching cohort analysis.

Background: Tumor necrosis (TN) is a common feature in lung squamous cell carcinoma (LSCC), which could provide useful predictive and prognostic information. Objectives: This study aimed to investigate the effect of pretreatment pulmonary TN (PTN) on the prognosis of first-line anti-programmed cell death 1 (PD-1)/PD ligand 1 (PD-L1) inhibitor in advanced LSCC. Design: We conducted a retrospective study to analyze the association between the presence of PTN and clinical outcomes in advanced LSCC patients treated with anti-PD-1/PD-L1 inhibitors. Methods: Data from 240 eligible patients were collected from 27 hospitals across China between 2016 and 2020. The presence of PTN was assessed using contrast-enhanced chest computed tomography (CT) imaging at baseline. We utilized the Cox proportional-hazards regression model to analyze the association between PTN and clinical outcomes. In addition, to account for potential confounding factors and ensure comparability between groups, we employed propensity score-matching (PSM) analysis. Results: In the overall patient cohort, the presence of PTN was 39.6%. The median follow-up duration was 20.3 months. The positive PTN group exhibited a notably inferior median progression-free survival (PFS; 6.5 months vs 8.6 months, p = 0.012) compared to the negative PTN group. Within the Cox proportional-hazards regression model, PTN emerged as an independent predictor of unfavorable PFS (hazard ratio (HR) = 1.354, 95% confidence interval (CI): 1.002-1.830, p = 0.049). After PSM, the median PFS for the positive PTN group (6.5 months vs 8.0 months, p = 0.027) remained worse than that of the negative PTN group. Multivariate analyses also further underscored that the presence of PTN independently posed a risk for shorter PFS (HR = 1.494, 95% CI: 1.056-2.112, p = 0.023). However, no statistically significant difference in overall survival was observed between the two groups. Conclusion: Our study suggests that the presence of PTN on baseline contrast-enhanced chest CT is a potential negative prognostic imaging biomarker for the outcome of anti-PD-1/PD-L1 inhibitor therapy in advanced LSCC. Further studies are warranted to validate these findings and explore the underlying mechanisms.

Predicting anti-PD-1/PD-L1 inhibitor treatment outcomes: pulmonary tumor necrosis in lung squamous cell carcinoma Our study focused on lung squamous cell carcinoma (LSCC) patients receiving first-line anti-PD-1/PD-L1 therapy. We explored the impact of a feature called pretreatment pulmonary tumor necrosis (PTN) on their prognosis. PTN was identified in 39.6% of patients using baseline chest CT scans. Results revealed that patients with PTN had a shorter time without disease progression (median PFS of 6.5 months compared to 8.6 months) and a higher risk of unfavorable outcomes. This suggests that PTN may serve as a negative prognostic imaging marker for anti-PD-1/PD-L1 therapy in advanced LSCC. Further research is needed to confirm and understand these findings better.

UBR1 is a prognostic biomarker and therapeutic target associated with immune cell infiltration in gastric cancer.

BACKGROUND: Ubiquitination is a targeted protein modification process mediated by intracellular molecules. UBR1 encodes a protein that binds to unstable N-terminal residues of substrate proteins and contributes to the formation of substrate-linked polyubiquitin chains. However, the function and cellular pathways of UBR1 in tumors have received inadequate attention. This study aimed to investigate the potential of UBR1 as a prognostic biomarker and immunotherapy target for stomach adenocarcinoma (STAD) as well as its biological function and molecular mechanism in relation to the disease. METHODS: Differential expression and pan-cancer gene set enrichment analysis (GSEA) were conducted using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) datasets. The Human Protein Atlas (HPA) database was utilized to identify UBR1-enriched pathways in AGS cells and to compare immunohistochemical differences between cancerous and adjacent non-cancerous tissues in gastric cancer. Quantitative Polymerase Chain Reaction (QPCR) and Western blot (WB) analyses were employed to validate these findings in both cancerous and adjacent non-cancerous tissues of gastric cancer. UBR1 expression in GES-1 and four gastric cancer cell lines was assessed using QPCR and WB. Kaplan-Meier curves, univariate and multivariate Cox regression analyses, and receiver operating characteristic (ROC) curve analyses were performed to evaluate the prognostic and diagnostic roles of UBR1. Additionally, the correlation between UBR1 expression and clinical parameters was analyzed using TCGA and GEO databases. UBR1 mutation data were obtained from the cBioPortal database. The mutation landscape, mutation-associated genes, protein structure, tumor mutation burden (TMB), and microsatellite instability (MSI) correlations were analyzed and illustrated. The biological functions of UBR1 were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The correlation between UBR1 and immune infiltration was assessed using TIMER and EPIC computational methods. Protein expression levels of UBR1 in gastric cancer cell lines were determined by immunohistochemistry (IHC) and WB analysis. Quantitative real-time PCR (qRT-PCR) was employed to analyze mRNA expression. Immunoprecipitation (IP) assays were conducted to detect protein-protein interactions between UBR1 and PDL1, while cellular immunofluorescence was used to observe the co-localization of these proteins. Cell proliferation was evaluated using CCK8 and colony formation assays. Cell migration was assessed using Transwell and wound healing assays. Finally, apoptosis was analyzed using flow cytometry, and WB was used to detect changes in apoptotic proteins and NF-κB P65 pathway proteins. RESULTS: UBR1 was upregulated in 28 cancer types, including STAD, and its overexpression was validated in gastric cancer cell lines and tissues. UBR1 expression was associated with advanced pathological characteristics. High UBR1 expression was linked to poor prognostic outcomes, including overall survival (OS), progression-free interval (PFI), disease-specific survival (DSS), as well as responses to surgery, chemotherapy, and HER2 expression. UBR1 expression showed significant correlations with clinical parameters such as age, gender, TNM stage, pathological stage, tumor resection, and anti-reflux therapy. Amplifications and deletions were the most frequent genetic alterations associated with UBR1. According to KEGG and GSEA analyses, UBR1 was significantly associated with several cancer pathways, oxidative phosphorylation, and the TNF-NFκB pathway. UBR1 also exhibited a significant correlation with immune cell infiltration and immunotherapy, including a direct interaction with PDL1. Knockdown of UBR1 inhibited the proliferation, migration, and invasion of STAD cells and promoted apoptosis. CONCLUSIONS: UBR1 is overexpressed in STAD, promoting its progression and positively correlating with immune cell infiltration and immunotherapeutic responses. Therefore, UBR1 could be a promising biomarker for the prognosis and immunotherapy of STAD.

Early evaluation of the effectiveness and cost-effectiveness of ctDNA-guided selection for adjuvant chemotherapy in stage II colon cancer.

Background: Current patient selection for adjuvant chemotherapy (ACT) after curative surgery for stage II colon cancer (CC) is suboptimal, causing overtreatment of high-risk patients and undertreatment of low-risk patients. Postoperative circulating tumor DNA (ctDNA) could improve patient selection for ACT. Objectives: We conducted an early model-based evaluation of the (cost-)effectiveness of ctDNA-guided selection for ACT in stage II CC in the Netherlands to assess the conditions for cost-effective implementation. Methods: A validated Markov model, simulating 1000 stage II CC patients from diagnosis to death, was supplemented with ctDNA data. Five ACT selection strategies were evaluated: the current guideline (pT4, pMMR), ctDNA-only, and three strategies that combined ctDNA status with pT4 and pMMR status in different ways. For each strategy, the costs, life years, quality-adjusted life years (QALYs), recurrences, and CC deaths were estimated. Sensitivity analyses were performed to assess the impact of the costs of ctDNA testing, strategy adherence, ctDNA as a predictive biomarker, and ctDNA test performance. Results: Model predictions showed that compared to current guidelines, the ctDNA-only strategy was less effective (+2.2% recurrences, -0.016 QALYs), while the combination strategies were more effective (-3.6% recurrences, +0.038 QALYs). The combination strategies were not cost-effective, since the incremental cost-effectiveness ratio was €67,413 per QALY, exceeding the willingness-to-pay threshold of €50,000 per QALY. Sensitivity analyses showed that the combination strategies would be cost-effective if the ctDNA test costs were lower than €1500, or if ctDNA status was predictive of treatment response, or if the ctDNA test performance improved substantially. Conclusion: Adding ctDNA to current high-risk clinicopathological features (pT4 and pMMR) can improve patient selection for ACT and can also potentially be cost-effective. Future studies should investigate the predictive value of post-surgery ctDNA status to accurately evaluate the cost-effectiveness of ctDNA testing for ACT decisions in stage II CC.

Effectiveness and cost-effectiveness of circulating tumour DNA-guided selection for adjuvant chemotherapy in patients with stage II colon cancer Most patients with stage II colon cancer (CC) are cured by surgery. Therefore, guidelines recommend to only offer adjuvant chemotherapy to patients who have a tumor with high-risk features. However, current selection is suboptimal, leading to recurrence of cancer in 13% of low-risk patients and unnecessary administration of chemotherapy in some high-risk patients. Previous studies indicate that a biomarker, so-called circulating tumour DNA (ctDNA), could improve the selection of high-risk patients for adjuvant chemotherapy, as patients who have detectable ctDNA in their blood after surgery are likely to develop a recurrence. Despite its potential, implementation is still pending. Our study assessed the long-term effectiveness and costs associated with various ctDNA-guided strategies for selecting high-risk patients for adjuvant chemotherapy in stage II CC. We used an health-economic model to simulate a cohort of 1000 Dutch patients with stage II CC from diagnosis to death. Next, we compared the health outcomes and costs of the ctDNA-guided strategies to those when selection is based on the Dutch guideline. We found that a combination of the Dutch guideline and ctDNA was the most effective strategy, but not cost-effective. Additional analyses showed that ctDNA-guided selection were cost-effective if the costs of the ctDNA test were below 1500 euros, if the ctDNA test performed significantly better, or if patients with detectable ctDNA responded better to chemotherapy. Thus, while post-surgery ctDNA status is a good indicator for recurrence risk, specific criteria related to ctDNA test performance and costs, in addition to combining ctDNA with current high-risk features, should be met to achieve cost-effective implementation. Looking ahead, future studies should explore how patients with detectable ctDNA respond to chemotherapy for next assessments of the cost-effectiveness of ctDNA-guided strategies in selecting patients with stage II CC for adjuvant chemotherapy.

Comprehensive pan-cancer analysis of ZNF337 as a potential diagnostic, immunological, and prognostic biomarker.

BACKGROUND: Zinc Finger Protein 337 (ZNF337) is a novel Zinc Finger (ZNF) protein family member. However, the roles of ZNF337 in human cancers have not yet been investigated. METHODS: In this study, with the aid of TCGA databases, GTEx databases, and online websites, we determined the expression levels of ZNF337 in pan-cancer and its potential value as a diagnostic and prognostic marker for pan-cancer and analyzed the relationship between ZNF337 expression and immune cell infiltration and immune checkpoint genes. We then focused our research on the potential of ZNF337 as a biomarker for diagnostic and prognostic in KIRC (kidney renal clear cell carcinoma) and validated in the E-MTAB-1980 database. Moreover, the expression of ZNF337 was detected through qRT-PCR and Western blotting (WB). CCK-8 experiment, colony formation experiment, and EDU experiment were performed to evaluate cell proliferation ability. Wound healing assay and transwell assay were used to analyze its migration ability. The qRT-PCR and WB were used to detect the expression of ZNF337 in tumor tissues and paracancerous tissues of KIRC patients. RESULTS: The pan-cancer analysis revealed that abnormal ZNF337 expression was found in multiple human cancer types. ZNF337 had a high diagnostic value in pan-cancer and a significant association with the prognosis of certain cancers, indicating that ZNF337 may be a valuable prognostic biomarker for multiple cancers. Further analysis demonstrated that the expression level of ZNF337 displayed significant correlations with cancer-associated fibroblasts, immune cell infiltration, and immune checkpoint genes in many tumors. Additionally, ZNF337 was observed to have a high expression in KIRC. Its expression was significantly associated with poor prognosis [overall survival (OS), disease-specific survival (DSS)], age, TNM stage, histologic grade, and pathologic stage. The high ZNF337 expression was associated with poor prognosis in the E-MTAB-1980 validation cohort. The in vitro experiments suggested that the expression of ZNF337 in KIRC tumor tissues was higher than in adjacent tissues, and ZNF337 knockdown inhibited the proliferation and migration of KIRC cells, whereas overexpression of ZNF337 had the opposite effects. CONCLUSIONS: ZNF337 might be an important prognostic and immunotherapeutic biomarker for pan-cancer, especially in KIRC.

Apoptotic effect of melatonin on ER-positive breast cancer cell lines: ADGRL4 gene expression and promoter methylation.

Breast cancer (BC) is the second most common malignancy worldwide. ADGRL4, as a modulator of angiogenesis, undergoes various epigenetic modifications affecting its biological functions. In this study, we aimed to assess ADGRL4 promoter methylation status and its expression levels in primary breast tumors and to evaluate its potency as a plausible prognostic biomarker in BC. Furthermore, we evaluated the effect of melatonin on ADGRL4 expression and viability of BC cells in vitro. One hundred breast tumor tissue samples and adjacent non-tumor tissues were collected, followed by DNA isolation, bisulfite conversion, qRT-PCR, qMSP assay, and immunoblotting. In addition, four BC cell lines were treated with melatonin and subjected to ADGRL4 expression analysis and apoptosis assay. We found a significant correlation between ADGRL4 expression levels and HER2 status and stage of disease (P < 0.05). We observed a substantial attenuation in ADGRL4 promoter methylation in tumor samples compared to marginal non-tumor samples. A significantly lower expression of ADGRL4 was detected in two BC cell lines in the presence of melatonin. MCF-7 and BT474 melatonin-treated cell lines showed a significantly higher number of apoptotic cells than non-treated cells (P < 0.0001). Based on the receiver operating characteristic (ROC) curve analysis, ADGRL4 expression and ADGRL4 promoter methylation status showed moderate prognostic value. We found that melatonin has anti-cancer effects on BC cells. In addition, ADGRL4 expression can potentially be used as a prognostic biomarker in BC.

MZT2A serves as a prognostic biomarker and promotes the progression of kidney renal clear cell carcinoma.

MZT2A is a novel core component in the γ-tubulin ring complex and aberrantly expressed in some types of tumors. However, MZT2A expression pattern across different cancers and its role in kidney renal clear cell carcinoma have not been sufficiently investigated. A thorough analysis of MZT2A expression landscape across 33 cancer types was conducted, utilizing 712 normal samples and 9807 tumor samples from TCGA (version 37.0), as well as 5112 normal samples from the GTEx databases. MZT2A's impact on KIRC cell viability and proliferation were evaluated through BrdU assays and monitored by cell imaging readers in MZT2A-expressing plasmid or siRNA-transfected cells. Additionally, the effects of MZT2A on cell apoptosis and cell cycle were detected using flow cytometry and Western blot. WGCNA analysis was employed to construct a co-expression gene network associated with MZT2A expression in KIRC, and Pearson correlation coefficient was utilized to examine the relationships between pairs of genes. MZT2A is overexpressed in 25 out of 33 types of cancer, including KIRC. In KIRC, high level of MZT2A was associated with higher clinical stage progression and poorer patients' survival. Downregulation of MZT2A decreased KIRC cell proliferation, retarded cell cycle and promoted apoptosis, while upregulation of MZT2A produced the opposite effects. WGCNA analysis and in vitro experiments revealed that MZT2A activated PI3K/AKT signaling pathway in KIRC. In all, MZT2A was overexpressed in most types of tumors. MZT2A served as an oncogene in KIRC and might be a potential target for guiding future treatments.

Identification of POU4F1 as a novel prognostic biomarker and therapeutic target in esophageal squamous cell carcinoma.

BACKGROUND: Esophageal cancer is a significant global health concern, ranking seventh in incidence and sixth in mortality. It encompasses two pathological types: esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma, with ESCC being more prevalent globally and associated with higher mortality rates. The POU (Pit-Oct-Unc) domain family transcription factors, comprising 15 members, play important roles in embryonic development and organ formation. Aberrant expression of POUs has been observed in several human cancers, influencing cell proliferation, tumor invasion, and drug resistance. However, their specific role in ESCC remains unknown. METHODS: We analyzed TCGA and GEO databases to assess POUs expression in ESCC tissues. Kaplan-Meier and ROC analyses were used to evaluate the prognostic value of POUs. Gene Set Enrichment Analysis and Protein-Protein interaction network were used to explore the potential pathway. Functional assays (Cell Counting Kit-8, EdU Staining assay, and cloning formation assay) and mechanism analyses (RNA-seq, flow cytometry, and Western blot) were conducted to determine the effects of POU4F1 knockdown on ESCC cell phenotypes and signaling pathways. RESULTS: POU4F1 and POU6F2 were upregulated in various cancer tissues, including ESCC, compared to normal tissues. POU4F1 expression was significantly correlated with patient survival and superior to previous models (AUC = 0.776). Knockdown of POU4F1 inhibited ESCC cell proliferation and affected cell cycle, autophagy, and DNA damage pathways in ESCC cells. CONCLUSION: POU4F1 is a novel and promising prognostic and therapeutic target for ESCC patients, providing insights into potential treatment strategies.

SOX11 as a prognostic biomarker linked to m6A modification and immune infiltration in renal clear cell carcinoma.

Background: The prognosis for patients with kidney renal clear cell carcinoma (KIRC) remains unfavorable, and the understanding of SRY-box transcription factor 11 (SOX11) in KIRC is still limited. The purpose of this paper is to explore the role of SOX11 in the prognosis of KIRC. Methods: We analyzed SOX11 expression in KIRC and adjacent normal tissues using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Our study aims to establish a correlation between SOX11 expression and clinical pathological features. Differentially expressed genes (DEGs) were assessed using R software. Furthermore, we conducted Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and gene set enrichment analysis (GSEA). Integration of data from the Tumor Immune Estimation Resource (TIMER) and TCGA databases allowed us to assess the association between SOX11 expression and immune infiltration in KIRC. Additionally, we analyzed the association between SOX11 gene expression and N6-methyladenosine (m6A) modification in KIRC using TCGA and GEO data. Results: Our findings revealed high SOX11 expression in KIRC, which showed a significant correlation with tumor staging and prognosis. GO/KEGG and GSEA analyses indicated that SOX11 was closely associated with sodium ion transport, synaptic vesicle circulation, and oxidative phosphorylation. Analysis of the TIMER and TCGA databases demonstrated correlations of SOX11 expression levels with the presence of CD8+ T lymphocytes, neutrophils, CD4+ T cells, as well as B cells. Moreover, both the TCGA and GEO datasets showed a substantial association between SOX11 and m6A modification-related genes, namely ZC3H13, FTO, METTL14, YTHDC1, IGF2BP1, and IGF2BP2. Conclusions: SOX11 exhibits a correlation with m6A modification and immune infiltration, suggesting its potential as a prognostic biomarker for KIRC.

MMP11 as a prognostic biomarker correlated with immune infiltrates in pancreatic adenocarcinoma.

Background: Matrix metalloproteinase 11 (MMP11) plays a vital role in cell proliferation, apoptosis, tumor angiogenesis, migration, and other basic processes. Currently, few studies have examined the value of MMP11 in pancreatic cancer in relation to prognostic risk, diagnostic indicators, and immunotherapy. This study aims to explore the association between MMP11 and the tumor immune microenvironment in pancreatic adenocarcinoma (PAAD). Methods: We selected clinical samples and data downloaded from The Cancer Genome Atlas and Genotype-Tissue Expression, in addition, we use other online data for further analysis. Through a comprehensive bioinformatics investigation, we systematically analyzed the clinical significance and expression level of MMP11 in pancreatic cancer. Results: MMP11 was overexpressed in many cancers, and a higher expression of MMP11 was associated with a poorer prognosis in pancreatic cancer. Conversely, the hypermethylation of MMP11 was associated with better overall survival. The MMP11 expression network had widespread effects on the prognosis and immune activation of PAAD. The expression of MMP11 was significantly associated with a variety of tumor-infiltrating immune cells. An association was also found between MMP11 expression and chemokines in PAAD. High MMP11 expression might be involved in immune cell migration to the tumor microenvironment. Conclusions: MMP11 is a prognostic biomarker for patients in pancreatic cancer and may regulate the tumor immune microenvironment. The potential effects and mechanisms of MMP11 in PAAD require further exploring.

The tumor-stroma ratio in giant cell tumor of bone: associations with the immune microenvironment and responsiveness to denosumab treatment.

BACKGROUND: Currently, there is limited understanding regarding the clinical significance of the tumor-stroma ratio (TSR) in giant cell tumor of bone (GCTB). Hence, we aimed to investigate the distribution of TSR in GCTB and explore its correlation with various clinicopathologic factors, immune microenvironment, survival prognosis, and denosumab treatment responsiveness. METHODS: We conducted a multicenter cohort study comprising 426 GCTB patients treated at four centers. TSR was evaluated on hematoxylin and eosin-stained and immunofluorescent sections of tumor specimens. Immunohistochemistry was performed to assess CD3+, CD4+, CD8+, CD20+, PD-1+, PD-L1+, and FoxP3+ TIL subtypes as well as Ki-67 expression levels in 426 tissue specimens. These parameters were then analyzed for their correlations with patient outcomes [local recurrence-free survival (LRFS) and overall survival (OS)], clinicopathological features, and denosumab treatment responsiveness. RESULTS: Low TSR was significantly associated with poor LRFS and OS in both cohorts. Furthermore, TSR was also correlated with multiple clinicopathological features, TIL subtype expression, and denosumab treatment responsiveness. TSR demonstrated similar predictive capabilities as the conventional Campanacci staging system for predicting patients' LRFS and OS. CONCLUSION: The results of this study provide evidence supporting the use of TSR as a reliable prognostic tool in GCTB and as a predictor of denosumab treatment responsiveness. These findings may aid in developing individualized treatment strategies for GCTB patients in the future.

Identification of RNMT as an immunotherapeutic and prognostic biomarker: From pan-cancer analysis to lung squamous cell carcinoma validation.

BACKGROUND: Dysregulation of RNA guanine-7 methyltransferase (RNMT) plays a crucial role in the tumor progression and immune responses. However, the detailed role of RNMT in pan-cancer is still unknown. METHODS: Bulk transcriptomic data of pan-cancer were obtained from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases. Single-cell transcriptomic and proteomics data of lung squamous cell carcinoma (LUSC) were analyzed in the Tumor Immune Single-cell Hub 2 (TISCH2) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, respectively. The correlation between RNMT expression and cancer prognosis was analyzed by Cox proportional hazards regression and Kaplan-Meier analyses. The correlation of RNMT expression with common immunoregulators, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) was analyzed. Additionally, the correlation between RNMT expression and immune infiltration level was evaluated. A total of 1287 machine learning combinations were used to construct prognostic models for LUSC. qRT-PCR and Western blot were used to validate the bioinformatics findings of RNMT upregulation in LUSC. RESULTS: RNMT was widely expressed across different cancers, with significant correlation to prognosis in cancers such as kidney chromophobe (KICH) (p = 0.0033, HR = 7.12), liver hepatocellular carcinoma (LIHC) (p = 0.01, HR = 1.41), and others. Notably, RNMT participates in the regulation of the tumor microenvironment. RNMT expression positively correlated with immune cell expression (Spearman's rank correlation, p < 0.05). Moreover, RNMT expression was strongly associated with immunoregulators, TMB, MSI, MMR, and DNMT in most cancer types. Notably, RNMT expression displayed excellent prognostic and immunological performance in LUSC. The expression of RNMT was mainly enriched in B cells of LUSC tissues. qRT-PCR and Western blot verified the high expression of RNMT in LUSC. CONCLUSION: RNMT expression widely correlated with prognosis and immune infiltration in various tumors, especially LUSC. The RNMT detection may provide a new idea for future tumor immune studies and treatment strategies.

Expression and Prognostic Value of a Novel B7-H3 (CD276) Antibody in Acute Myeloid Leukemia.

Despite recent advances in immunophenotyping, the prognosis of acute myeloid leukemia (AML) is still mainly estimated using age and genetic markers. As the genetic heterogeneity of AML patients is high, flow cytometry-based classification with appropriate biomarkers can efficiently complement risk stratification and treatment selection. An increased expression of B7-H3 (CD276), an immune checkpoint protein, has been reported and associated with poor prognosis. However, the available data are limited and heterogeneous. Here, we used a novel, proprietary murine anti-B7-H3 8H8 antibody for the flow cytometric analysis of B7-H3 expression in AML blasts from 77 patients. Our antibody reliably detected substantial B7-H3 expression in 62.3% of AML patients. B7-H3 expression was higher in the monocytic French-American-British (FAB) M5 group and in intermediate and poor risk patients according to the European Leukemia Network. Using receiver operating characteristics (ROCs), we identified a specific fluorescence intensity cut-off of 4.45 to discriminate between B7-H3high and B7-H3low expression. High B7-H3 expression was associated with shorter overall survival (OS) and progression-free survival (PFS). In conclusion, we have developed a novel B7-H3 antibody that serves as a new tool for the detection of B7-H3 expression in AML and may help to facilitate risk stratification and treatment selection in AML patients.

Constructing lncRNA-miRNA-mRNA networks specific to individual cancer patients and finding prognostic biomarkers.

BACKGROUND: The competitive endogenous RNA (ceRNA) hypothesis suggests that microRNAs (miRNAs) mediate a regulatory relation between long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) which share similar miRNA response elements (MREs) to bind to the same miRNA. Since the ceRNA hypothesis was proposed, several studies have been conducted to construct a network of lncRNAs, miRNAs and mRNAs in cancer. However, most cancer-related ceRNA networks are intended for representing a general relation of RNAs in cancer rather than for a patient-specific relation. Due to the heterogeneous nature of cancer, lncRNA-miRNA-mRNA interactions can vary in different patients. RESULTS: We have developed a new method for constructing a ceRNA network of lncRNAs, miRNAs and mRNAs, which is specific to an individual cancer patient and for finding prognostic biomarkers consisting of lncRNA-miRNA-mRNA triplets. We tested our method on extensive data sets of three types of cancer (breast cancer, liver cancer, and lung cancer) and obtained potential prognostic lncRNA-miRNA-mRNA triplets for each type of cancer. CONCLUSIONS: Analysis of expression patterns of the RNAs involved in the triplets and survival rates of cancer patients revealed several interesting findings. First, even for the same cancer type, prognostic lncRNA-miRNA-mRNA triplets can be different depending on whether lncRNA and mRNA show opposite or similar expression patterns. Second, prognostic lncRNA-miRNA-mRNA triplets are often more predictive of survival rates than RNA pairs or individual RNAs. Our approach will be useful for constructing patient-specific lncRNA-miRNA-mRNA networks and for finding prognostic biomarkers from the networks.