Identification novel prognostic signatures for Head and Neck Squamous Cell Carcinoma based on ceRNA network construction and immune infiltration analysis

PRKAA2 Promotes Tumor Growth and Inhibits Ferroptosis through SLC7A11/GSH/GPX4 Pathway in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) is the most pervasive sort of lung cancer with deadly outcome. According to recent studies, a number of neoplastic disorders and ferroptosis are intimately connected. This study aims to identify the role of key ferroptosis-related gene (protein kinase AMP-activated catalytic subunit alpha 2, PRKAA2) and explore new directions for the diagnosis and treatment of NSCLC. The PRKAA2 expression and its influence on survival were analyzed in multiple public databases (TCGA, TIMER2.0, and GEPIA). And PRKAA2 mRNA level in NSCLC cells were examined by qRT-PCR. Silencing of PRKAA2 (sh-PRKAA2) were used to cell transfection. CCK-8, EdU, and flow cytometry assays were used to measure cell proliferation and apoptosis. The protein levels of ferroptosis markers (SLC7A11, GPX4, and NRF2) were determined by western blotting. Meanwhile, the related ferroptosis analysis, such as malondialdehyde (MDA) and glutathione (GSH), reactive oxygen species (ROS), iron, and Fe2+ levels were also detected in the transfected cells. Moreover, the relationship between PRKAA2 expression and SLC7A11 was analyzed. NSCLC xenograft mouse models were used for in vivo verification of the PRKAA2 function. Here, our data revealed that PRKAA2 was upregulated in NSCLC cells. Additionally, PRKAA2 strengthened cell proliferation and attenuated apoptosis and ferroptosis of NSCLC cells. The depletion of PRKAA2 enhanced the erastin-induced inhibition effect on cell growth, and notably increased the levels of MDA, ROS, iron, and Fe2+, while decreased GSH level in NSCLC cells. In the mechanism exploration, we discovered that PRKAA2 could activate the SLC7A11/GSH/GPx4 antioxidant pathway. The rescue experiments showed that SLC7A11 abrogated the inhibitive impacts of PRKAA2 repression on cellular proliferation, cell apoptosis, and ferroptosis in NSCLC. Besides, animal experiments proved that PRKAA2 enhanced NSCLC tumor growth in vivo. The results discovered that PRKAA2 accelerated the malignant progression, diminished apoptosis and ferroptosis in NSCLC through SLC7A11/GSH/GPX4 pathway. This study provide a novel target in the application of PRKAA2 for NSCLC treatment.

Prognostic Value of Pentraxin3 Protein Expression in Human Malignancies: A Systematic Review and Meta-Analysis

BACKGROUND/OBJECTIVES

Pentraxin 3 (PTX3), a member of the pentraxin superfamily, plays diverse roles in immunity and inflammation. Its dual role in tumorigenesis, exhibiting both protumoral and antitumoral effects, has been the subject of conflicting reports. High PTX3 expression levels in serum and tumor tissues have been associated with poor prognosis in various malignancies, suggesting its potential as a prognostic biomarker. Through this meta-analysis, we aim to comprehensively assess the prognostic significance of PTX3 protein expression in human malignancies and evaluate its potential as a pan-cancer prognostic marker.

METHODS

A systematic literature search was conducted across the PubMed, Embase, Web of Science, MEDLINE, and Cochrane Library databases. Studies were included if they assessed the association between PTX3 protein expression and overall survival (OS) in cancer patients. Hazard ratios (HRs) were pooled using a random-effects model. Subgroup analyses were performed based on the method of PTX3 assessment, and publication bias was evaluated using Egger's and Begg's tests.

RESULTS

Nine studies encompassing 1215 patients were included in the analysis. High PTX3 expression was significantly associated with poorer OS (HR = 1.89, 95% CI = 1.55-2.32, p < 0.01) with no significant heterogeneity (I2 = 0%). Subgroup analysis revealed consistent results across different assessment methods (immunohistochemistry: HR = 1.93, p < 0.01; immunoassay: HR = 1.86, p < 0.01). However, publication bias was detected (Egger's test, p = 0.03).

CONCLUSIONS

High PTX3 protein expression is associated with a poor prognosis in various malignancies, supporting its potential as a prognostic biomarker.

Role of long pentraxin PTX3 in cancer

Cancer has become a leading cause of death and disease burden worldwide, closely related to rapid socioeconomic development. However, the fundamental reason is the lack of comprehensive understanding of the mechanism of cancer, accurate identification of preclinical cancer, and effective treatment of the disease. Therefore, it is particularly urgent to study specific mechanisms of cancer and develop effective prediction and treatment methods. Long Pentraxin PTX3 is a soluble pattern recognition molecule produced by various cells in inflammatory sites, which plays a role as a promoter or suppressor of cancer in multiple tumors through participating in innate immune response, neovascularization, energy metabolism, invasion, and metastasis mechanisms. Based on this, this article mainly reviews the role of PTX3 in various cancers.

Integrated bioinformatics and validation reveal SOX12 as potential biomarker in colon adenocarcinoma based on an immune infiltration-related ceRNA network

PURPOSE

The primary objective of this study was to construct competing endogenous RNA (ceRNA) networks and evaluate the prognostic significance of tumor-infiltrating immune cells (TIICs) and key biomarkers within the ceRNA networks in colon adenocarcinoma (COAD) patients.

METHODS

Comprehensive bioinformatics tools were used to screen differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs) related to COAD, leading to the creation of ceRNA networks. The CIBERSORT technique was employed to assess the significance of TIICs in COAD, and an immune-related prognosis prediction model was subsequently developed. Co-expression analyses were conducted to determine the relationship between key genes in ceRNA networks and immunologically significant TIICs. The study also utilized 5 GEO datasets and web-based databases to externally validate the findings.

RESULTS

The study revealed a statistically significant relationship between key hub genes and immune cells, as determined through co-expression analysis. Two hub regulators (SOX12 and H19) demonstrated significant prognostic value in the ceRNA-related prognostic model, and their elevated expression levels were verified across multiple CRC cell lines. Additionally, the knockdown of SOX12 led to a suppression of proliferation, migration, and invasion in colon cancer cells.

CONCLUSION

Through the construction of ceRNA networks and evaluation of TIICs, the study successfully established two risk score models and nomograms. These models serve as valuable tools for understanding the molecular processes and predicting the prognosis of COAD patients. Further validation of hub regulators SOX12 and H19 substantiates their potential role as key biomarkers in COAD.

MiR-148a-3p Promotes Colorectal Cancer Cell Ferroptosis by Targeting SLC7A11

Ferroptosis, an iron-dependent form of cell death, and dysregulated microRNA (miRNA) expression correlate with colorectal cancer (CRC) development and progression. The tumor suppressor ability of miR-148a-3p has been reported for several cancers. Nevertheless, the role of miR-148a-3p in CRC remains largely undetermined. Here, we aim at investigating the molecular mechanisms and regulatory targets of miR-148a-3p in the CRC cell death mechanism(s). To this end, miR-148a-3p expression was evaluated in SW480 and SW620 cells and normal colon epithelial CCD 841 CoN cells with quantitative real-time polymerase chain reaction (qRT-PCR). Data reported a reduction of miR-148a-3p expression in SW480 and SW620 cells compared to non-tumor cells (p < 0.05). Overexpression of miR-148a selectively inhibited CRC cell viability (p < 0.001), while weakly affecting normal CCD 841 CoN cell survival (p < 0.05). At the cellular level, miR-148a-3p mimics promoted apoptotic cell death via caspase-3 activation (p < 0.001), accumulation of mitochondrial reactive oxygen species (ROS) (p < 0.001), and membrane depolarization (p < 0.001). Moreover, miR-148a-3p overexpression induced lipid peroxidation (p < 0.01), GPX4 downregulation (p < 0.01), and ferroptosis (p < 0.01), as revealed by intracellular and mitochondrial iron accumulation and ACSL4/TFRC/Ferritin modulation. In addition, levels of SLC7A11 mRNA and protein, the cellular targets of miR-148a-3p predicted by bioinformatic tools, were suppressed by miR-148a-3p's overexpression. On the contrary, the downregulation of miR-148a-3p boosted SLC7A11 gene expression and suppressed ferroptosis. Together, these in vitro findings reveal that miR-148a-3p can function as a tumor suppressor in CRC by targeting SLC7A11 and activating ferroptosis, opening new perspectives for the rationale of therapeutic strategies through targeting the miR-148a-3p/SLC7A11 pathway.

Construction and analysis of a conjunctive diagnostic model of HNSCC with random forest and artificial neural network

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous tumor that is highly aggressive and ranks fifth among the most common cancers worldwide. Although, the researches that attempted to construct a diagnostic model were deficient in HNSCC. Currently, the gold standard for diagnosing head and neck tumors is pathology, but this requires a traumatic biopsy. There is still a lack of a noninvasive test for such a high-incidence tumor. In order to screen genetic markers and construct diagnostic model, the methods of random forest (RF) and artificial neural network (ANN) were utilized. The data of HNSCC gene expression was accessed from Gene Expression Omnibus (GEO) database; we selected three datasets totally, and we combined 2 datasets (GSE6631 and GSE55547) for screening differentially expressed genes (DEGs) and chose another dataset (GSE13399) for validation. Firstly, the 6 DEGs (CRISP3, SPINK5, KRT4, MMP1, MAL, SPP1) were screened by RF. Subsequently, ANN was applied to calculate the weights of 6 genes. Besides, we created a diagnostic model and nominated it as neuralHNSCC, and the performance of neuralHNSCC by area under curve (AUC) was verified using another dataset. Our model achieved an AUC of 0.998 in the training cohort, and 0.734 in the validation cohort. Furthermore, we used the Cell-type Identification using Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm to investigate the difference in immune cell infiltration between HNSCC and normal tissues initially. The selected 6 DEGs and the constructed novel diagnostic model of HNSCC would make contributions to the diagnosis.

Clinical implication and immunological landscape analyses of ANLN in pan-cancer: A new target for cancer research

BACKGROUND

Anillin is a F-actin binding protein (ANLN) mainly involved in the process of cytokinesis and known to be dysregulated in diverse cancers. However, the role of ANLN in pan-cancer prognosis and tumor immunity remains unclear.

METHODS

Gene expression profiles of 31 solid tumors were downloaded from The Cancer Genome Atlas (TCGA) database. ANLN mRNA and protein expression were quantified using quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC). Protein expression of ANLN was further confirmed in Human Protein Atlas (HPA) database. Cox regression and Kaplan-Meier analysis were utilized to assess the prognostic value of ANLN in pan-cancer. The correlation between ANLN and different immune gene markers and infiltration cells was analyzed via ESTIMATE and CIBERSORT. A BLCA immunotherapy cohort: IMvigor (210) was used to confirm the role of ANLN in immune response.

RESULTS

ANLN upregulation was detected in 21 types of cancers and was associated with poor overall survival (OS), disease-free interval (DFI), and progression-free interval (PFI) in most cancers except in THYM (Thymoma). Additionally, correlation analysis revealed a significantly positive association between ANLN expression and tumor mutation burden (TMB), microsatellite instability (MSI), immune cells infiltration. and immune checkpoint genes in various cancers. The BLCA immunotherapy cohort confirmed that patients with higher ANLN level had better immune responses and longer OS.

CONCLUSION

ANLN may serve as a prognostic biomarker for pan-cancer. ANLN upregulation is associated with higher TMB, MSI, and immune cell infiltration in multiple types of tumors, shedding new light for cancer treatment.

Association Analysis of PRKAA2 and MSMB Polymorphisms and Growth Traits of Xiangsu Hybrid Pigs

In this study, Xiangsu hybrid pig growth traits were evaluated via PRKAA2 and MSMB as candidate genes. Sanger sequencing revealed three mutation sites in PRKAA2, namely, g.42101G>T, g.60146A>T, and g.61455G>A, and all these sites were intronic mutations. Moreover, six mutation sites were identified in MSMB: intronic g.4374G>T, exonic g.4564T>C, exonic g.6378G>A, exonic g.6386C>T, intronic g.8643G>A, and intronic g.8857A>G. Association analysis revealed that g.42101G>T, g.60146A>T, g.61455G>A, g.4374G>T, g.4564T>C, g.6378G>A, g.6386C>T, g.8643G>A, and g.8857A>G showed different relationship patterns among body weight, body length, body height, chest circumference, abdominal circumference, tube circumference, and chest depth. Real-time polymerase chain reaction results revealed that the expression of PRKAA2 was highest in the longissimus dorsi muscle, followed by that in the heart, kidney, liver, lung, and spleen. The expression of MSMB was highest in the spleen, followed by that in the liver, kidney, lung, heart, and longissimus dorsi muscle. These results suggest that PRKAA2 and MSMB can be used in marker-assisted selection to improve growth related traits in Xiangsu hybrid pigs, providing new candidate genes for Pig molecular breeding.

High eukaryotic initiation factor 5A2 expression predicts poor prognosis and may participate in the SNHG16/miR-10b-5p/EIF5A2 regulatory axis in head and neck squamous cell carcinoma

BACKGROUND

This study attempted to investigate the significance of eukaryotic initiation factor 5A2 (EIF5A2) in the prognosis and regulatory network of head and neck squamous cell carcinoma (HNSCC).

METHODS

EIF5A2 expression, prognostic information, and methylation levels of HNSCC were collected from the Cancer Genome Atlas (TCGA) database. Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot analyses were performed to determine EIF5A2 levels in HNSCC and normal tissue samples. R software was employed for expression analysis and prognosis assessment of EIF5A2 in HNSCC. A competing endogenous RNA (ceRNA) network was generated with the starBase database. Gene set enrichment analysis (GSEA) was used to determine the enriched physiological functions and network related to high expression of EIF5A2 in HNSCC. Immune infiltration-related outcomes were acquired from the CIBERSORT and Tumor Immune Estimation Resource (TIMER) database.

RESULTS

EIF5A2 overexpression was observed in HNSCC and linked to poor progression-free survival and overall survival time. Cox regression analyses showed that EIF5A2 level was a stand-alone indicator of HNSCC patients' prognosis. A ceRNA network analysis highlighted the SNHG16/miR-10b-5p/EIF5A2 axis in EIF5A2 regulation. The GSEA results indicated that EIF5A2 was involved in complex signaling pathways. The CIBERSORT and TIMER databases revealed significant associations between EIF5A2 expression and immune cell infiltration.

CONCLUSION

EIF5A2 overexpression may be a risk factor for prognosis in HNSCC and may be regulated by the SNHG16/miR-10b-5p/EIF5A2 axis.

Identification of the prognostic, diagnostic, and biological significance of the miR-148a-3p/cathepsin A axis in hepatocellular carcinoma

A comprehensive analysis of the prognostic, diagnostic, and biological significance of miR-148a-3p and cathepsin A (CTSA) in hepatocellular carcinoma (HCC) was performed using bioinformatics algorithms with The Cancer Genome Atlas (TCGA) data. miR-148a-3p and CTSA gene expression in HCC tissues and nontumor specimens was analyzed using TCGA database with R software. CTSA staining analysis was validated using the Human Protein Atlas database. Prognostic, diagnostic, gene set enrichment, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and immune infiltration analyses were implemented using the TCGA database with R software. Based on TCGA data and our cohort populations, CTSA expression was significantly elevated in HCC tissues compared with nontumor specimens. A significant negative correlation between miR-148a-3p and CTSA was observed in the TCGA data and our cohort population. Mechanistically, CTSA was a direct gene target of miR-148a-3p. Both CTSA and miR-148a-3p could serve as prognostic and diagnostic indicators in HCC. miR-148a-3p expression was significantly and negatively correlated with the StromalScore, ImmuneScore, and ESTIMATEScore in patients with liver cancer. miR-148a-3p mimic-mediated apoptosis and the inhibition of HCC cell growth and migration were counteracted by CTSA overexpression. The miR-148a-3p/CTSA axis was implicated in immune cell infiltration and carcinogenesis of HCC. miR-148a-3p and CTSA might be prospective molecular targets to enhance the potency of immunotherapy in HCC.

Identification of a novel ceRNA network related to prognosis and immunity in HNSCC based on integrated bioinformatic investigation

Head and neck squamous cell carcinoma (HNSCC) is characterized by an immunosuppression environment and necessitates the development of new immunotherapy response predictors. The study aimed to build a prognosis-related competing endogenous RNA (ceRNA) network based on immune-related genes (IRGs) and analyze its immunological signatures. Differentially expressed IRGs were identified by bioinformatics analysis with Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and ImmPort databases. Finally, via upstream prognosis-related microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) prediction and co-expression analysis, we built an immune-related ceRNA network (LINC00052/hsa-miR-148a-3p/PLAU) related to HNSCC patient prognosis. CIBERSORT analysis demonstrated that there were substantial differences in 11 infiltrating immune cells in HNSCC, and PLAU was closely correlated with 10 type cells, including T cells CD8+ (R =  - 0.329), T cells follicular helper (R = - 0.342) and macrophage M0 (R = 0.278). Methylation and Tumor Immune Dysfunction and Exclusion (TIDE) analyses revealed that PLAU upregulation was most likely caused by hypomethylation and that high PLAU expression may be associated with tumor immune evasion in HNSCC, respectively.

A multifaceted and feasible prognostic model of amino acid metabolism-related genes in the immune response and tumor microenvironment of head and neck squamous cell carcinomas

We investigated the role of amino acid metabolism (AAM) in head and neck squamous cell carcinoma (HNSCC) tissues to explore its prognostic value and potential therapeutic strategies. A risk score based on four AAM-related genes (AMG) was constructed that could predict the prognosis of HNSCC. These four genes were up-regulated in HNSCC tissues and might act as oncogenes. Internal validation in The Cancer Genome Atlas (TCGA) by bootstrapping showed that patients with high-risk scores had a poorer prognosis than patients with low-risk scores, and this was confirmed in the Gene Expression Omnibus (GEO) cohort. There were also differences between the high-risk and low-risk groups in clinical information and different anatomical sites such as age, sex, TNM stage, grade stage, surgery or no surgery, chemotherapy, radiotherapy, no radiotherapy, neck lymph node dissection or not, and neck lymphovascular invasion, larynx, overlapping lesion of lip, and oral cavity and pharynx tonsil of overall survival (OS). Immune-related characteristics, tumor microenvironment (TME) characteristics, and immunotherapy response were significantly different between high- and low-risk groups. The four AMGs were also found to be associated with the expression of markers of various immune cell subpopulations. Therefore, our comprehensive approach revealed the characterization of AAM in HNSCC to predict prognosis and guide clinical therapy.

Exploration of a predictive model based on genes associated with fatty acid metabolism and clinical treatment for head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent malignant tumors of the head and neck and presents high risks of recurrence and poor prognosis postoperatively. The aim of this study was to establish a predictive model based on fatty acid metabolism (FAM) genes to forecast the prognosis of HNSCC patients and the subsequent treatment strategies.

METHODS

We accessed the TCGA and GEO databases for HNSCC genes and clinical data. The FAM risk score model was created and validated using a combination of univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Combining risk scores and clinical characteristics, a nomogram was established and assessed. Subsequently, the function, gene mutation, immune difference, and chemotherapeutic drug sensitivity of the groups with high- and low-risk scores were analyzed. Consequently, the mode's validity was evaluated comprehensively by combining single gene analysis.

RESULTS

The FAM risk score model for predicting HNSCC prognosis had certain validity. Patients in the high- and low-risk groups had genetic mutations, and the prognosis was the poorest for the high-risk groups with high genetic mutations. The patients with low-risk scores were suitable for immunotherapy since they had increased infiltration of immune cells. In contrast, the patients in the other groups were more suitable for chemotherapy.

CONCLUSION

The results of this study demonstrated that the FAM risk score model may predict the prognosis of HSNCC and has a certain therapeutic guidance value.

Immune Infiltration-Related ceRNA Network Revealing Potential Biomarkers for Prognosis of Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC.

Materials and Methods

ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed.

Results

Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress.

Conclusion

In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

MiRNA-148a inhibits cell growth and drug resistance by regulating WNT10a expression in renal cell carcinoma

Background

We aimed to explore miR-148a exerts a tumor suppressor effect and arsenic trioxide (As₂O₃) sensitivity on renal cell carcinoma (RCC).

Methods

We performed polymerase chain reaction (PCR) on 42 pairs of tumor and paracancerous samples collected from RCC patients to investigate the miR-148a expression; meanwhile, we analyzed the interplay between clinical indicators and miR-148a expression of RCC. Then, the influence of miR-148a overexpression on the functions of RCC cells were analyze using transwell migration assay, Cell Counting Kit-8 (CCK-8), and cell wound healing assay. Furthermore, the ability of miR-148a to sensitize Caki-1 cells treated with As₂O₃ were detected using flow cytometry. Finally, the relevant mechanism of miR-148a on the downstream gene Wnt family member 10A (WNT10a) was explored by cell reverse method.

Results

The results from RCC patients indicated a significantly lower miR-148a level than adjacent tissues. The low miR-148a expression increased prevalence of distant metastasis and decreased survival rate compared to those with high expression in patients. In the RCC cell lines, the proliferation and metastasis ability of the miR-148a mimic group was remarkably lower than the miR-NC group. At the same time, it was verified that WNT10a was remarkably higher cell lines and RCC tissues; and negatively related to miR-148a expression. In addition, miR-148a mimics were found to remarkably reduce the protein expression of WNT10a. In the cell reverse experiment, overexpression of WNT10a was confirmed to offset the miR-148a mimics effect on metastasis and proliferation of RCC cells. In addition, an increase in relative apoptosis was detected in As₂O₃ treated with/without miR-148a mimics for 48 hours, and apoptosis was significantly reduced after transfection with WNT10a in the Caki-1 cell line and significantly reduced after combined treatment.

Conclusions

The study revealed that miR-148a is associated with distant metastases and leads to poor prognosis in RCC patients. Moreover, miR-148a inhibit the malignant progression and increase the sensitivity of RCC cells to As₂O₃ by regulating WNT10a.

STAT3 Activates the Pentraxin 3 Gene in Chronic Lymphocytic Leukemia Cells

Pentraxin-related protein 3 (PTX3), commonly produced by myeloid and endothelial cells, is a humoral pattern recognition protein of the innate immune system. Because PTX3 plasma levels of patients with chronic lymphocytic leukemia (CLL) are high and most circulating cells in patients with CLL are CLL cells, we reasoned that CLL cells produce PTX3. Western immunoblotting revealed that low-density cells from seven of seven patients with CLL produce high levels of PTX3, flow cytometry analysis revealed that the PTX3-producing cells are B lymphocytes coexpressing CD19 and CD5, and confocal microscopy showed that PTX3 is present in the cytoplasm of CLL cells. Because STAT3 is constitutively activated in CLL cells, and because we identified putative STAT3 binding sites within the PTX3 gene promoter, we postulated that phosphorylated STAT3 triggers transcriptional activation of PTX3. Immunoprecipitation analysis of CLL cells' chromatin fragments showed that STAT3 Abs precipitated PTX3 DNA. STAT3 knockdown induced a marked reduction in PTX3 expression, indicating a STAT3-induced transcriptional activation of the PTX3 gene in CLL cells. Using an EMSA, we established and used a dual-reporter luciferase assay to confirm that STAT3 binds the PTX3 gene promoter. Downregulation of PTX3 enhanced apoptosis of CLL cells, suggesting that inhibition of PTX3 might benefit patients with CLL.

LncRNA–miRNA–mRNA Networks of Gastrointestinal Cancers Representing Common and Specific LncRNAs and mRNAs

Gastrointestinal (GI) cancers are responsible for approximately half of cancer-related deaths, highlighting the need for the identification of distinct and common features in their clinicopathological characteristics. Long ncRNA (lncRNAs), which are involved in competitive endogenous RNA (ceRNA) networks with critical roles in biological processes, constitute a substantial number of non-coding RNAs. Therefore, our study aimed to investigate the similarities and differences in the ceRNA networks of The Cancer Genome Atlas (TCGA)-GI cancers. We performed a comprehensive bioinformatics analysis of ceRNA networks for TCGA-GI cancers in terms of the deferential mRNA, lncRNA, and miRNA expression levels, ceRNA networks, overall survival analysis, correlation analysis, pathological cancer stages, and gene set enrichment analysis. Our study revealed several common and distinct mRNAs and lncRNAs with prognostic values in these networks. It was specifically noteworthy that MAGI2-AS3 lncRNA was found to be shared in almost all GI cancers. Moreover, the most common shared mRNAs between GI cancers were MEIS1, PPP1R3C, ADAMTSL3, RIPOR2, and MYLK. For each cancer ceRNA network, we found that the expression level of a number of lncRNAs and mRNAs was specific. Furthermore, our study provided compelling evidence that several genes, most notably KDELC1, can act as novel proto-oncogenes in cancers. This, in turn, can highlight their role as new prognostic and therapeutic targets. Moreover, we found cell cycle and extracellular matrix structural constituent as the top shared KEGG and molecular function, respectively, among GI cancers. Our study revealed several known lncRNAs and known and unknown mRNAs in GI cancers with diagnostic and prognostic values.

Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

Objectives

Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients.

Methods and Results

Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis.

Conclusions

We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.

Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer

Aims: This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Methods: Based on the survival-related representation features yielded by BiDNNs through integrating transcriptomics and epigenomics data, K-means clustering analysis was performed to cluster tumor samples into different survival subgroups. The BiDNNs-based model was validated using tenfold cross-validation and in two independent confirmation cohorts. Results: Using the BiDNNs-based survival stratification model, patients were grouped into two survival subgroups with log-rank p-value = 9.05E-05. The subgroups classification was robustly validated in tenfold cross-validation (C-index = 0.65 ± 0.02) and in two confirmation cohorts (E-GEOD-26253, C-index = 0.609; E-GEOD-62254, C-index = 0.706). Conclusion: We propose and validate a robust and stable BiDNN-based survival stratification model in gastric cancer.

Immune infiltration and a ferroptosis-associated gene signature for predicting the prognosis of patients with endometrial cancer

Ferroptosis, a form of programmed cell death induced by excess iron-dependent lipid peroxidation product accumulation, plays a critical role in cancer. However, there are few reports about ferroptosis in endometrial cancer (EC). This article explores the relationship between ferroptosis-related gene (FRG) expression and prognosis in EC patients. One hundred thirty-five FRGs were obtained by mining the literature, retrieving GeneCards and analyzing 552 malignant uterine corpus endometrial carcinoma (UCEC) samples, which were randomly assigned to training and testing groups (1:1 ratio), and 23 normal samples from The Cancer Genome Atlas (TCGA). We established a signature using eight screened FRGs (MDM2, GPX4, PRKAA2, PRNP, SLC11A2, ATP5MC3, PHKG2 and ACO1) related to overall survival using LASSO regression analysis. The samples were divided into low- and high-risk subgroups according to the median risk score. Kaplan-Meier survival curves showed that the low-risk group had better OS. ROC curves showed that this signature performed well in predicting OS (1-, 2-, 3-, and 5-year AUCs of 0.676, 0.775, 0.797, and 0.826, respectively). We systematically analyzed the immune infiltrating profile in UCEC samples from TCGA. Overall, our study identified a novel prognostic signature of 8 FRGs that can potentially predict the prognosis of EC.