A nomogram incorporating treatment data for predicting overall survival in gastroenteropancreatic neuroendocrine tumors: a population-based cohort study.

BACKGROUND: Over the last few decades, the annual global incidence of gastroenteropancreatic neuroendocrine tumours (GEP-NETs) has steadily increased. Because of the complex and inconsistent treatment of GEP-NETs, the prognosis of patients with GEP-NETs is still difficult to assess. The study aimed to construct and validate the nomograms included treatment data for prediction overall survival (OS) in GEP-NETs patients. METHODS: GEP-NETs patients determined from the Surveillance, Epidemiology, and End Results (SEER)-13 registry database (1992-2018) and with additional treatment data from the SEER-18 registry database (1975-2016). In order to select independent prognostic factors that contribute significantly to patient survival and can be included in the nomogram, multivariate Cox regression analysis was performed using the minimum value of Akaike information criterion (AIC) and we analyzed the relationship of variables with OS by calculating hazard ratios (HRs) and 95% CIs. In addition, we also comprehensively compared the nomogram using to predict OS with the current 7th American Joint Committee on Cancer (AJCC) staging system. RESULTS: From 2004 to 2015, a total of 42 662 patients at diagnosis years with GEP-NETs were determined from the SEER database. The results indicated that the increasing incidence of GEP-NETs per year and the highest incidence is in patients aged 50-54. After removing cases lacking adequate clinicopathologic characteristics, the remaining eligible patients ( n =7564) were randomly divided into training (3782 patients) and testing sets (3782 patients). In the univariate analysis, sex, age, race, tumour location, SEER historic stage, pathology type, TNM, stage, surgery, radiation, chemotherapy, and CS tumour size were found to be significantly related to OS. Ultimately, the key factors for predicting OS were determined, involving sex, age, race, tumour location, SEER historic stage, M, N, grade, surgery, radiation, and chemotherapy. For internal validation, the C-index of the nomogram used to estimate OS in the training set was 0.816 (0.804-0.828). For external validation, the concordance index (C-index) of the nomogram used to predict OS was 0.822 (0.812-0.832). In the training and testing sets, our nomogram produced minimum AIC values and C-index of OS compared with AJCC stage. Decision curve analysis (DCA) indicated that the nomogram was better than the AJCC staging system because more clinical net benefits were obtained within a wider threshold probability range. CONCLUSION: A nomogram combined treatment data may be better discrimination in predicting overall survival than AJCC staging system. The authors highly recommend to use their nomogram to evaluate individual risks based on different clinical features of GEP-NETs, which can improve the diagnosis and treatment outcomes of GEP-NETs patients and improve their quality of life.

Immune checkpoints signature-based risk stratification for prognosis of patients with gastric cancer.

Until now, few researches have comprehensive explored the role of immune checkpoints (ICIs) and tumor microenvironment (TME) in gastric cancer (GC) patients based on the genomic data. RNA-sequence data and clinical information were obtained from The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) database, GSE84437 and GSE84433. Univariate Cox analysis identified 60 ICIs with prognostic values, and these genes were then subjected to NMF cluster analysis and the GC samples (n = 804) were classified into two distinct subtypes (Cluster 1: n = 583; Cluster 2: n = 221). The Kaplan-Meier curves for OS analysis indicated that C1 predicted a poorer prognosis. The C2 subtype illustrated a relatively better prognosis and characteristics of "hot tumors," including high immune score, overexpression of immune checkpoint molecules, and enriched tumor-infiltrated immune cells, indicating that the NMF clustering in GC was robust and stable. Regarding the patient's heterogeneity, an ICI-score was constructed to quantify the ICI patterns in individual patients. Moreover, the study found that the low ICI-score group contained mostly MSI-low events, and the high ICI-score group contained predominantly MSI-high events. In addition, the ICI-score groups had good responsiveness to CTLA4 and PD-1 based on The Cancer Immunome Atlas (TCIA) database. Our research firstly constructed ICIs signature, as well as identified some hub genes in GC patients.

The impact of surgery and survival prediction in patients with gastroenteropancreatic neuroendocrine tumors: a population-based cohort study.

OBJECTIVE: This study aimed at assessing the impact of surgical treatments in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs). METHODS: A propensity score-matched analysis based on data in the Surveillance, Epidemiology, and End Results database was used to assess the efficacy of surgical treatment in patients with GEP-NETs. RESULTS: A total of 7515 patients diagnosed with GEP-NETs from 2004 to 2015 were evaluated from the Surveillance, Epidemiology, and End Results database. There were 1483 patients in the surgery group and 6032 patients in the nonsurgery group. Compared with patients in the surgery group, patients in the nonsurgery group were inclined to receive chemotherapy (50.8 vs. 16.7%) and radiation (12.9 vs. 3.7%) as treatment options. Multivariate Cox regression analysis revealed higher rates of overall survival (OS) outcomes for GEP-NETs patients who had been subjected to surgery (hazard ratio=0.483, 95% CI=0.439-0.533, P <0.001). Then, to reduce the impact of bias, a 1 : 1 propensity score-matched analysis was performed for the two groups of patients. A total of 1760 patients were assessed and each subgroup included 880 patients. In the matched population, the patients exhibited the ability to significantly benefit from surgery (hazard ratio=0.455, 95% CI=0.439-0.533, P <0.001). The OS outcomes for radiation or chemotherapy patients who had been treated with surgery were better than those of patients who had not been treated with surgery ( P <0.001). In addition, it was found that the OS of patients was not significant after rectum and small intestine surgery, whereas there was a significant difference in OS after colon, pancreas, and stomach surgery on the patients. Patients who had been subjected to surgery in the rectum and small intestines exhibited better therapeutic benefits. CONCLUSION: Patients with GEP-NETs who are treated with surgery have better OS outcomes. Therefore, surgery is recommended for specified selected patients with metastatic GEP-NETs.

Epigenetic and Tumor Microenvironment for Prognosis of Patients with Gastric Cancer.

BACKGROUND: Epigenetics studies heritable or inheritable mechanisms that regulate gene expression rather than altering the DNA sequence. However, no research has investigated the link between TME-related genes (TRGs) and epigenetic-related genes (ERGs) in GC. METHODS: A complete review of genomic data was performed to investigate the relationship between the epigenesis tumor microenvironment (TME) and machine learning algorithms in GC. RESULTS: Firstly, TME-related differential expression of genes (DEGs) performed non-negative matrix factorization (NMF) clustering analysis and determined two clusters (C1 and C2). Then, Kaplan-Meier curves for overall survival (OS) and progression-free survival (PFS) rates suggested that cluster C1 predicted a poorer prognosis. The Cox-LASSO regression analysis identified eight hub genes (SRMS, MET, OLFML2B, KIF24, CLDN9, RNF43, NETO2, and PRSS21) to build the TRG prognostic model and nine hub genes (TMPO, SLC25A15, SCRG1, ISL1, SOD3, GAD1, LOXL4, AKR1C2, and MAGEA3) to build the ERG prognostic model. Additionally, the signature's area under curve (AUC) values, survival rates, C-index scores, and mean squared error (RMS) curves were evaluated against those of previously published signatures, which revealed that the signature identified in this study performed comparably. Meanwhile, based on the IMvigor210 cohort, a statistically significant difference in OS between immunotherapy and risk scores was observed. It was followed by LASSO regression analysis which identified 17 key DEGs and a support vector machine (SVM) model identified 40 significant DEGs, and based on the Venn diagram, eight co-expression genes (ENPP6, VMP1, LY6E, SHISA6, TMEM158, SYT4, IL11, and KLK8) were discovered. CONCLUSION: The study identified some hub genes that could be useful in predicting prognosis and management in GC.

Identification of a Cancer Stem Cells Signature of Head and Neck Squamous Cell Carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) ranks as the sixth most widespread and deadly cancer. In recent times, it has been determined that undifferentiated cell populations with stem cell-like properties in HNSCC are major factors influencing recurrence and progression. Method: In this study, we determine key genes related to stemness by merging WGCNA with HNSCC mRNAsi based on the online database. Results: We first download the mRNA expression-based stemness index (mRNAsi) data and contrast the expression levels of mRNAsi in cancers and control samples; we found significantly elevated mRNAsi expressions in HNSCC tissues (p = 0.002). Moreover, the brown module showed a relatively high negative correlation with mRNAsi (cor = -0.8). Thus, we selected the brown module as the interesting module and used it for following analysis. We screened 20 key genes (PDGFRB, PLPP4, CALU, ADAMTS14, COL5A3, KCNE4, LOXL1, CLEC11A, PODN,BGN, AEBP1, COL1A2, LAMA4, LOXL2, LRRC15, THY1, SPON2, COL1A1, NID2, and AC134312.5) including and as to decide the neighbor genes biological interaction network of these 20 stemness-related genes in HNSCC. The top 10 frequent alterations were PIK3CA, FGF3, FGF19, FGF4, DVL3, P3H2, GNB4, COL22A1, COL14A1, and PLOD2. Conclusion: This study showed the critical role of stemness-related genes in HNSCC. However, more related studies are needed to confirm these results.

Pyroptosis-Related Signature and Tumor Microenvironment Infiltration Characterization in Head and Neck Squamous Cell Carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most widespread and deadly cancer. Until now, very few studies have systematically evaluated the role of pyroptosis-related genes (PRGs) and lncRNAs in HNSCC patients. Methods: We integrated the genomic data to comprehensively assess the role of pyroptosis with the tumor microenvironment cell-infiltrating characteristics in HNSCC. In addition, we also constructed a set of the scoring system to calculate the pyroptosis dysfunction in each patient. Results: The analysis of the CNV alteration frequency displayed that CNV changes were common in 33 PRGs, and the frequency of copy number gain and loss was similar. CASP8 demonstrated the highest mutation frequency. Considering the individual heterogeneity, a scoring system to quantify the pyroptosis pattern in each patient was constructed based on these phenotypic-related genes, which we named as the PyroptosisScore. The results indicated that the low PyroptosisScore group experienced increased extensive TMB than the high group, with the most significant mutated genes being TP53 and TTN. Finally, we tried to find some useful pyroptosis-related lncRNAs, and 14 differentially expressed lncRNAs were selected as independent prognosis factors of HNSCC patients based on the multivariate Cox analysis. Conclusion: This work suggests the pyroptosis features and the potential mechanisms of the tumor microenvironment. The exploration may assist in identifying novel biomarkers and help patients predict prognosis, clinical diagnosis, and management.

Bioinformatics Study Revealed Significance of Exosome Transcriptome in Hepatocellular Carcinoma Diagnosis.

Background: Hepatocellular carcinoma (HCC) is one of the fifty most common cancers globally, having a high mortality rate being the second most common cause of cancer-related deaths. However, little attention has been paid to the involvement of exosomes and ceRNA in HCC. Method: The study aimed to explore exosome data from exoRBase database and a free online database to estimate possible binding miRNA from mRNA, lncRNA, and circRNA and discover useful exosome biomarkers for HCC therapy. Results: The results indicated that a total of 159 mRNAs, 60 lncRNAs, and 13 circRNAs were differentially expressed, with HIST2H3C exhibiting the highest log2FC change, CTD-2031P19 exhibiting the most relevant lncRNA, and CTD-2031P19 exhibiting the most relevant lncRNA. MARCH8, SH3PXD2A, has-circ-0014088, hsa-miR-186-5p, and hsa-miR-613 were identified as hub biomarkers used by Cytoscape. According to the KEGG pathway analysis results, the differentially expressed proteins were primarily enriched in the MAPK signaling network, central carbon metabolism in cancer, the glucagon signaling pathway, glutamatergic synapse, and spliceosome. Furthermore, immunohistochemical images from the Human Protein Atlas (HPA) online tool were used to directly evaluate the protein expression of SMARCA5, CDC42, and UBC between normal and cancer tissues, and the results showed that these three gene expressions were significantly higher in tumor tissues. Conclusion: This study discovered atypical signature exosomes for HCC prognostic prediction based on an online database. The signals could mimic exosome microenvironmental disorders providing potential biomarkers for exosome treatment.

Prognostic value and immune relevancy of a combined autophagy-, apoptosis- and necrosis-related gene signature in glioblastoma.

BACKGROUND: Glioblastoma (GBM) is considered the most malignant and devastating intracranial tumor without effective treatment. Autophagy, apoptosis, and necrosis, three classically known cell death pathways, can provide novel clinical and immunological insights, which may assist in designing personalized therapeutics. In this study, we developed and validated an effective signature based on autophagy-, apoptosis- and necrosis-related genes for prognostic implications in GBM patients. METHODS: Variations in the expression of genes involved in autophagy, apoptosis and necrosis were explored in 518 GBM patients from The Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox analysis were performed to construct a combined prognostic signature. Kaplan-Meier survival, receiver-operating characteristic (ROC) curves and Cox regression analyses based on overall survival (OS) and progression-free survival (PFS) were conducted to estimate the independent prognostic performance of the gene signature. The Chinese Glioma Genome Atlas (CGGA) dataset was used for external validation. Finally, we investigated the differences in the immune microenvironment between different prognostic groups and predicted potential compounds targeting each group. RESULTS: A 16-gene cell death index (CDI) was established. Patients were clustered into either the high risk or the low risk groups according to the CDI score, and those in the low risk group presented significantly longer OS and PFS than the high CDI group. ROC curves demonstrated outstanding performance of the gene signature in both the training and validation groups. Furthermore, immune cell analysis identified higher infiltration of neutrophils, macrophages, Treg, T helper cells, and aDCs, and lower infiltration of B cells in the high CDI group. Interestingly, this group also showed lower expression levels of immune checkpoint molecules PDCD1 and CD200, and higher expression levels of PDCD1LG2, CD86, CD48 and IDO1. CONCLUSION: Our study proposes that the CDI signature can be utilized as a prognostic predictor and may guide patients' selection for preferential use of immunotherapy in GBM.

The impact of particulate matter 2.5 on the risk of hepatocellular carcinoma: a meta-analysis.

OBJECTIVE: The convoluted element of PM2.5 may cause various biological reactions. Nowadays, few studies have indicated the long-term health effects of PM2.5 on HCC. Therefore, this meta-analysis first aims to obtain more precise estimates of the effects of PM2.5 exposure on HCC to assess the strength of the evidence. METHODS: A combination of computer and manual retrieval was used to search in Medline through PubMed, EMBASE and Web of Science. Review Manager 5.3 software was used to examine the heterogeneity among the studies. RESULTS: Finally, 8 qualified articles meet the inclusion criteria. The results were I2 = 0%, P > 0.1 indicating that there was no heterogeneity. The results showed that the concentration of PM2.5 increased by 10 µg/m3 was significantly correlated with liver cancer, and HR was 1.22 (95% CI 1.14-1.30, P < 0.05), indicating that maternal exposure to PM2.5 was positively correlated with liver cancer. CONCLUSIONS: Our meta-analysis showed that the patients with HCC significance related to PM2.5 exposure. However, more studies investigating the combined effects of different air pollutants on HCC incidence are warranted to provide more comprehensive evidence for assessing the different levels impacts of PM2.5 exposure on HCC incidence.

Development and Validation of a Pyroptosis-Related Long Non-coding RNA Signature for Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma (HCC) is a highly aggressive malignant disease, and numerous studies have demonstrated that an inflammatory environment can induce normal cells to transform into cancerous. Methods: We integrated genomic data to comprehensively assess the association between pyroptosis and tumor microenvironment (TME) cell-infiltrating characteristics in HCC, as well as the potential molecular function and clinical significance of lncRNA. Results: The analysis of CNV alteration frequency displayed that CNV changes were common in 33 PRGs, and most were focused on copy number amplification. As a result of lasso regression analysis, nine differentially expressed lncRNAs (AL031985.3, NRAV, OSMR-AS1, AC073611.1, MKLN1-AS, AL137186.2, AL049840.4, MIR4435-2HG, and AL118511.1) were selected as independent prognosis factors of HCC patients. Patients at high risk have poorer survival than those in the low-risk group in training and testing cohorts. A low-risk score was significantly associated with an IC50 of chemotherapeutics such as bortezomib (p < 0.001), but a high-risk score was significantly linked to docetaxel (p < 0.001), implying that signature served as a prospective predictor for chemosensitivity. Conclusion: This work suggests pyroptosis-related lncRNAs features and their potential mechanisms on tumor microenvironment. The exploration may assist in identifying novel biomarkers and assist patients in predicting their prognosis, clinical diagnosis, and management.

Epigenetic and Immune-Cell Infiltration Changes in the Tumor Microenvironment in Hepatocellular Carcinoma.

Background: Epigenetics regulate gene expression without altering the DNA sequence. Epigenetics targeted chemotherapeutic approach can be used to overcome treatment resistance and low response rate in HCC. However, a comprehensive review of genomic data was carried out to determine the role of epigenesis in the tumor microenvironment (TME), immune cell-infiltration characteristics in HCC is still insufficient. Methods: The association between epigenetic-related genes (ERGs), inflammatory response-related genes (IRRGs) and CRISPR genes was determined by merging genomic and CRISPR data. Further, characteristics of immune-cell infiltration in the tumor microenvironment was evaluated. Results: Nine differentially expressed genes (ANP32B, ASF1A, BCORL1, BMI1, BUB1, CBX2, CBX3, CDK1, and CDK5) were shown to be independent prognostic factors based on lasso regression in the TCGA-LIHC and ICGC databases. In addition, the results showed significant differences in expression of PDCD-1 (PD-1) and CTLA4 between the high- and low-epigenetic score groups. The CTRP and PRISM-derived drug response data yielded four CTRP-derived compounds (SB-743921, GSK461364, gemcitabine, and paclitaxel) and two PRISM-derived compounds (dolastatin-10 and LY2606368). Patients with high ERGs benefited more from immune checkpoint inhibitor (ICI) therapy than patients with low ERGs. In addition, the high ERGs subgroup had a higher T cell exclusion score, while the low ERGs subgroup had a higher T cell dysfunction. However, there was no difference in microsatellite instability (MSI) score among the two subgroups. Further, genome-wide CRISPR-based loss-of function screening derived from DepMap was conducted to determine key genes leading to HCC development and progression. In total, 640 genes were identified to be essential for survival in HCC cell lines. The protein-protein interaction (PPI) network demonstrated that IRRGs PSEN1 was linked to most ERGs and CRISPR genes such as CDK1, TOP2A, CBX2 and CBX3. Conclusion: Epigenetic alterations of cancer-related genes in the tumor microenvironment play a major role in carcinogenesis. This study showed that epigenetic-related novel biomarkers could be useful in predicting prognosis, clinical diagnosis, and management in HCC.

Integrated analysis of the functions and prognostic values of RNA binding proteins in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC), one of the most common malignant tumors worldwide, ranks as the fifth most common cancer and has been the second most frequent cause of cancer-related death. RNA binding proteins (RBPs) are proteins that interact with different classes of RNA and are commonly detected in cells. METHODS: We used RNA sequencing data from TCGA to display dysfunctional RBPs microenvironments and provide potential useful biomarkers for HCC diagnosis and prognosis. RESULTS: 330 differently expressed RBPs (208 upregulated and 122 downregulated) were identified. KEGG were mainly enriched in RNA degradation, Influenza A, Hepatitis C, RIG-I-like receptor signaling pathway, Herpes simplex virus 1 infection and RNA transport. CBioPortal results demonstrated that these genes were altered in 50 samples out of 357 HCC patients (14%) and the amplification of BRCA1 was the largest frequent copy-number alteration. CONCLUSION: Based on the online database, we identified novel RBPs markers for the prognosis of hepatocellular carcinoma.

Single sample scoring of hepatocellular carcinoma: A study based on data mining.

Hepatocellular carcinoma (HCC) is a high mortality malignancy and the second leading cause of cancer-related deaths. Because the immune system plays a dual role by assisting the host barrier and tumor progression, there are complex interactions with considerable prognostic significance. Herein, we performed single-sample gene set enrichment (ssGSEA) to explore the tumor microenvironment (TME) and quantify the tumor-infiltrating immune cell (TIIC) subgroups of immune responses based on the HCC cohort of The Cancer Genome Atlas (TCGA) database. We evaluate molecular subpopulations, survival, function, and expression differential associations, as well as reveal potential targets, and biomarkers for immunotherapy. We combined the TME score and the 29 immune cell types in the low, medium, and high immunity groups. The stromal score, immune score, and ESTIMATE score were positively correlated with immune activity but negatively correlated with the tumor purity. There were 23 human leukocyte antigen (HLA)-related genes that were significantly different. However, KIAA1429 was not significant among the different immunity groups. Besides, programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression increased with the increase of immune activity. This may provide valuable information for HCC immunotherapy. We also found that there was no significant difference in naïve B cells, macrophages M1, activated mast cells, resting natural killer (NK) cells, and T cells gamma delta among the different immunity groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the differential proteins were mainly enriched in alpha-linolenic acid (ALA) metabolism, cytokine-cytokine receptor interaction, glycosaminoglycan biosynthesis-heparan sulfate/heparin, glycosphingolipid biosynthesis-ganglio series and proteasome. Our findings provide a deeper understanding of the immune scene, uncovering remarkable immune infiltration patterns of various subtypes of HCC using ssGSEA. This study advances the understanding of immune response and provides a basis for research to enhance immunotherapy.

The role of ferroptosis in breast cancer patients: a comprehensive analysis.

Breast cancer (BC) affects the breast tissue and is the second most common cause of mortalities among women. Ferroptosis is an iron-dependent cell death mode that is characterized by intracellular accumulation of reactive oxygen species (ROS). We constructed a prognostic multigene signature based on ferroptosis-associated differentially expressed genes (DEGs). Moreover, we comprehensively analyzed the role of ferroptosis-associated miRNAs, lncRNAs, and immune responses. A total of 259 ferroptosis-related genes were extracted. KEGG function analysis of these genes revealed that they were mainly enriched in the HIF-1 signaling pathway, NOD-like receptor signaling pathway, central carbon metabolism in cancer, and PPAR signaling pathway. Fifteen differentially expressed genes (ALOX15, ALOX15B, ANO6, BRD4, CISD1, DRD5, FLT3, G6PD, IFNG, NGB, NOS2, PROM2, SLC1A4, SLC38A1, and TP63) were selected as independent prognostic factors for BC patients. Moreover, T cell functions, including the CCR score, immune checkpoint, cytolytic activity, HLA, inflammation promotion, para-inflammation, T cell co-stimulation, T cell co-inhibition, and type II INF responses were significantly different between the low-risk and high-risk groups of the TCGA cohort. Immune checkpoints between the two groups revealed that the expressions of PDCD-1 (PD-1), CTLA4, LAG3, TNFSF4/14, TNFRSF4/8/9/14/18/25, and IDO1/2 among others were significantly different. A total of 1185 ferroptosis-related lncRNAs and 219 ferroptosis-related miRNAs were also included in this study. From the online database, we identified novel ferroptosis-related biomarkers for breast cancer prognosis. The findings of this study provide new insights into the development of new reliable and accurate cancer treatment options.

Ferroptosis-Related Long Non-Coding RNA signature predicts the prognosis of Head and neck squamous cell carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) are head and neck cancers. On the other hand, ferroptosis is a novel iron-dependent and ROS reliant type of cell death observed various disease conditions. Method: We constructed a prognostic multilncRNA signature based on ferroptosis-related differentially expressed lncRNAs in HNSCC. Results: We identified 25 differently expressed lncRNAs associated with prognosis of HNSCC. Kaplan-Meier analyses revealed the high-risk lncRNAs signature associated with poor prognosis of HNSCC. Moreover, the AUC of the lncRNAs signature was 0.782, underscoring their utility in prediction HNSCC prognosis. Indeed, our risk assessment model was superior to traditional clinicopathological features in predicting HNSCC prognosis. GSEA revealed the immune and tumor-related pathways in the low risk group individuals. Moreover, TCGA revealed T cell functions including cytolytic activity, HLA, regulation of inflammationp, co-stimulation, co-inhibition and coordination of type II INF response were significantly different between the low-risk and high-risk groups. Immune checkpoints such as PDCD-1 (PD-1), CTLA4 and LAG3, were also expressed differently between the two risk groups. Conclusion: A novel ferroptosis-related lncRNAs signature impacts on the prognosis of HNSCC.

Integrated analysis of the prognostic values of RNA-binding proteins in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma is a malignant tumor of the upper aerodigestive tract. These RNA-binding proteins (RBPs) influence post-transcriptional in cells and regulate cell physiology, participate in regulating RNA stability, alternative splicing, translation, modification, localization, and apoptosis. We used RNA sequencing data from The Cancer Genome Atlas to display dysfunctional RBPs microenvironments and provide potential useful biomarkers for head and neck squamous cell carcinoma (HNSCC) diagnosis and prognosis. Six RBPs (DNMT1, PCF11, EIF5A2, RNASE10, PSMA6, and IGF2BP2) were selected as independent prognosis factors of HNSCC patients. The Kyoto Encyclopedia of Genes and Genomes were mainly enriched in RNA transport, Spliceosome, RNA degradation, mRNA surveillance pathway, and Epstein-Barr virus infection. cBioPortal results demonstrated that these six genes were altered in 150 samples out of 504 HNSCC patients (30%) and the amplification of IGF2BP2 was the largest frequent copy-number alteration. Based on the online database, we identified novel RBPs markers for the prognosis of HNSCC.

Alternative splicing events implicated in carcinogenesis and prognosis of thyroid gland cancer.

Alternative splicing (AS), a critical post-transcriptional regulatory mechanism, expands gene expression patterns, thereby leading to increased protein diversity. Indeed, more than 95% of human genes undergo alternative splicing events (ASEs). In this study, we drew an all-around AS profile of thyroid cancer cells based on RNA-seq data. In total, there were 45,150 AS in 10,446 thyroid cancer cell genes derived from 506 patients, suggesting that ASEs is a common process in TC. Moreover, 1819 AS signatures were found to be significantly associated with the overall survival (OS) of TC patients. Kaplan-Meier survival analyses suggested that seven types of ASEs were associated with poor prognosis of TC (P < 0.05). Among them, exon skipping (ES) was the most common, with alternate promoter (AP) and alternate terminator (AT) coming second and third, respectively. Our results indicated that acceptor sites (AA) (AUC: 0.937), alternate donor sites (AD) (AUC: 0.965), AT (AUC: 0.964), ES (AUC: 0.999), mutually exclusive exons (ME) (AUC: 0.999), and retained intron (RI) (AUC: 0.837) exhibited an AUC greater than 0.6. In addition, age and risk score (All) were risk factors for TC patients. We also evaluated whether TC-ASEs are regulated by various splicing factors (SFs). We found that the expression of 90 SFs was associated with 469 ASEs and OS of TC patients. Our findings provide an insight into the role of spliceosomes in TC, which may offer novel perspectives in tumor research.

DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients.

BACKGROUND: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation' However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. METHODS: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). RESULTS: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. CONCLUSIONS: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

Establishment and Validation of a Ferroptosis-Related Gene Signature to Predict Overall Survival in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the most common and lethal subtype of lung cancer. Ferroptosis, an iron-dependent form of regulated cell death, has emerged as a target in cancer therapy. However, the prognostic value of ferroptosis-related genes (FRGs)x in LUAD remains to be explored. Methods: In this study, we used RNA sequencing data and relevant clinical data from The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) dataset to construct and validate a prognostic FRG signature for overall survival (OS) in LUAD patients and defined potential biomarkers for ferroptosis-related tumor therapy. Results: A total of 86 differentially expressed FRGs were identified from LUAD tumor tissues versus normal tissues, of which 15 FRGs were significantly associated with OS in the survival analysis. Through the LASSO Cox regression analysis, a prognostic signature including 11 FRGs was established to predict OS in the TCGA tumor cohort. Based on the median value of risk scores calculated according to the signature, patients were divided into high-risk and low-risk groups. Kaplan-Meier analysis indicated that the high-risk group had a poorer OS than the low-risk group. The area under the curve of this signature was 0.74 in the TCGA tumor set, showing good discrimination. In the GEO validation set, the prognostic signature also had good predictive performance. Functional enrichment analysis showed that some immune-associated gene sets were significantly differently enriched in two risk groups. Conclusion: Our study unearthed a novel ferroptosis-related gene signature for predicting the prognosis of LUAD, and the signature may provide useful prognostic biomarkers and potential treatment targets.

miRNA biomarkers for predicting overall survival outcomes for head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract. The loss and gain of miRNA function promote cancer development through various mechanisms. RNA sequencing (RNA-seq) and miRNAs sequencing data from the Cancer Genome Atlas (TCGA) was used to show the dysfunctional miRNAs microenvironment and to provide useful biomarkers for miRNAs therapy. Seven miRNAs were found to be independent prognostic factors of HNSCC patients in the training cohort. A total of 60 target genes for these miRNAs were predicted. Nine target genes (CDCA4, CXCL14, FLNC, KLF7, NBEAL2, P4HA1, PFKM, PFN2 and SEPPINE1) were correlated with patient's overall survival (OS) outcomes. We identified novel miRNAs markers for the prognosis of head and neck squamous cell carcinoma.