Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma / El valor de ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico del glioma

Background: Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. Methods: The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan–Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. Results: HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis.Conclusions: Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients.(AU)

Introducción: Los gliomas presentan una alta incidencia y un mal pronóstico, por lo que es necesario un tratamiento más efectivo. Algunos estudios han confirmado que los ARN no codificantes de cadena larga (ARNncl) regulan diferentes enfermedades, entre las que se incluyen los gliomas. Se ha postulado que HAS2-AS1 actúa como un ARNncl, con un efecto oncogénico en diferentes tipos de cáncer. Este estudio tiene como objetivo analizar el valor del ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico de glioma. Métodos: Descargamos los datos clínicos y de expresión de micro-ARN de la base de datos del Atlas del Genoma del Cáncer (TCGA) para realizar el análisis diferencial y de supervivencia. También analizamos la expresión de HAS2-AS1 en muestras patológicas y muestras de tejido adyacente normal de 80 pacientes con glioma. Para analizar la capacidad diagnóstica y el valor pronóstico de HAS2-AS1 en el glioma, recurrimos a la curva ROC. También utilizamos curvas de Kaplan-Meier para evaluar la supervivencia de los pacientes con glioma con diferentes niveles de expresión de HAS2-AS1. Resultados: La expresión de HAS2-AS1 era significativamente mayor en las muestras patológicas que en el tejido normal. Las curvas de supervivencia demostraron que la sobreexpresión de HAS2-AS1 estaba relacionada con una menor supervivencia general y supervivencia libre de progresión. Algunos factores clínico-patológicos de los pacientes con glioma, como el tamaño del tumor y su grado, según la clasificación de la OMS, mostraron una correlación significativa con la expresión de HAS2-AS1 en los tejidos afectados. La curva ROC mostró un área bajo la curva de 0,863, lo que indica que la expresión de HAS2-AS1 posee un importante valor diagnóstico. El área bajo la curva de la supervivencia general estimada fue de 0,906; para la supervivencia libre de progresión estimada, de 0,88. Ambos valores muestran que la sobreexpresión de HAS2-AS1 se asocia con un mal pronóstico...(AU)

Prognostic significance of the chemerin level in coronavirus disease 2019 patients.

Increased serum chemerin levels have been reported in several inflammatory diseases. Few studies have investigated the relationship between chemerin and clinical features of COVID-19. Thus, chemerin may modulate the development and progression of COVID-19. We compared the serum chemerin concentration between patients with and without SARS-CoV-2 infection and its association with the severity and prognosis of COVID-19 pneumonia. This is a prospective, single-center, cross-sectional study. We enrolled COVID-19 patients who presented to our tertiary hospital and healthy controls. The COVID-19 patients were conducted and the dates of symptom onset were recorded. After admission to the hospital and stabilization, blood samples were obtained for routine hemogram, biochemistry, and chemerin. The chemerin level was 37.93 ±â€…17.3 ng/mL in patients followed in the ICU, 29.41 ±â€…12.79 ng/mL in inpatients, 30.48 ±â€…10.86 ng/mL in outpatients, and 25.12 ±â€…9.82 ng/mL in healthy controls. The difference between patients treated in the ICU and healthy controls was significant (P < .001). The high-sensitivity C-reactive protein (hs-CRP), ferritin, procalcitonin (PCT), and D-dimer levels were significantly higher in the intensive care unit (ICU) group (P < .001). Moreover, the chemerin level of patients who died was significantly higher than that of those who survived (P < .001). The chemerin level was increased in COVID-19 patients and also increased with increasing disease severity. The chemerin level was higher in the COVID-19 patients than healthy controls and was significantly higher in patients who died compared to those who did not.

Identification of fibronectin type III domain containing 3B as a potential prognostic and therapeutic target for pancreatic cancer: a preliminary analysis.

BACKGROUND: Fibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated. METHODS: In this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan-Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored. RESULTS: The study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan-Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells. CONCLUSION: Despite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.

GGT5 facilitates migration and invasion through the induction of epithelial-mesenchymal transformation in gastric cancer.

BACKGROUND: Gamma-glutamyltransferase 5 (GGT5), one of the two members in the GGT family (GGT1 and GGT5), plays a crucial role in oxidative regulation, inflammation promotion, and drug metabolism. Particularly in the tumorigenesis of various cancers, its significance has been recognized. Nevertheless, GGT5's role in gastric cancer (GC) remains ambiguous. This study delves into the function and prognostic significance of GGT5 in GC through a series of in vitro experiments. METHODS: Employing online bioinformatics analysis tools such as The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Kaplan-Meier plotter, and cBioPortal, we explored GGT5 characteristics and functions in GC. This encompassed aberrant expression, prognostic value, genomic alterations and mutations, immune cell infiltration, and associated signaling pathways. Immunohistochemistry was conducted to assess GGT5 expression in GC and adjacent normal tissues. Subsequently, univariate and multivariate logistic regression analyses were applied to investigate the associations between GGT5 and clinical characteristics. CCK8, wound healing, and migration assays were utilized to evaluate the impact of GGT5 on cell viability and migration. Additionally, Gene Set Enrichment Analysis (GSEA) and Western blot analysis were performed to scrutinize the activity of the epithelial-mesenchymal transformation (EMT) signaling pathway under GGT5 regulation. RESULTS: GGT5 exhibits upregulation in gastric cancer, with its overexpression significantly linked to histological differentiation in GC patients (P < 0.05). Multivariate analysis indicates that elevated GGT5 expression is an independent risk factor associated with poorer overall survival in gastric cancer patients (P < 0.05). In vitro experiments reveal that downregulation of GGT5 hampers the proliferation and migration of GC cell lines. Finally, GSEA using TCGA data highlights a significant correlation between GGT5 expression and genes associated with EMT, a finding further confirmed by Western blot analysis. CONCLUSIONS: GGT5 emerges as a promising prognostic biomarker and potential therapeutic target for GC.

Prognostic utility and characteristics of MIB-1 labeling index as a proliferative activity marker in childhood low-grade glioma: a retrospective observational study.

PURPOSE: The prognostic utility of MIB-1 labeling index (LI) in pediatric low-grade glioma (PLGG) has not yet conclusively been described. We assess the correlation of MIB-1 LI and tumor growth velocity (TGV), aiming to contribute to the understanding of clinical implications and the predictive value of MIB-1 LI as an indicator of proliferative activity and progression-free survival (PFS) in PLGG. METHODS: MIB-1 LI of a cohort of 172 nonependymal PLGGs were comprehensively characterized. Correlation to TGV, assessed by sequential MRI-based three-dimensional volumetry, and PFS was analyzed. RESULTS: Mean MIB-1 LI accounted for 2.7% (range: < 1-10) and showed a significant decrease to 1.5% at secondary surgery (p = .0013). A significant difference of MIB-1 LI in different histopathological types and a correlation to tumor volume at diagnosis could be shown. Linear regression analysis showed a correlation between MIB-1 LI and preoperative TGV (R2 = .55, p < .0001), while correlation to TGV remarkably decreased after incomplete resection (R2 = .08, p = .013). Log-rank test showed no association of MIB-1 LI and 5-year PFS after incomplete (MIB-1 LI > 1 vs ≤ 1%: 48 vs 46%, p = .73) and gross-total resection (MIB-1 LI > 1 vs ≤ 1%: 89 vs 95%, p = .75). CONCLUSION: These data confirm a correlation of MIB-1 LI and radiologically detectable TGV in PLGG for the first time. Compared with preoperative TGV, a crucially decreasing correlation of MIB-1 LI and TGV after surgery may result in limited prognostic capability of MIB-1 LI in PLGG.

Nicotinamide in Combination with EGFR-TKIs for the Treatment of Stage IV Lung Adenocarcinoma with EGFR Mutations: A Randomized Double-Blind (Phase IIb) Trial.

PURPOSE: RUNX3 is a tumor suppressor gene, which is inactivated in approximately 70% of lung adenocarcinomas. Nicotinamide, a sirtuin inhibitor, has demonstrated potential in re-activating epigenetically silenced RUNX3 in cancer cells. This study assessed the therapeutic benefits of combining nicotinamide with first-generation EGFR-tyrosine kinase inhibitors (TKI) for patients with stage IV lung cancer carrying EGFR mutations. PATIENTS AND METHODS: We assessed the impact of nicotinamide on carcinogen-induced lung adenocarcinomas in mice and observed that nicotinamide increased RUNX3 levels and inhibited lung cancer growth. Subsequently, 110 consecutive patients with stage IV lung cancer who had EGFR mutations were recruited: 70 females (63.6%) and 84 never-smokers (76.4%). The patients were randomly assigned to receive either nicotinamide (1 g/day, n = 55) or placebo (n = 55). The primary and secondary endpoints were progression-free survival (PFS) and overall survival (OS), respectively. RESULTS: After a median follow-up of 54.3 months, the nicotinamide group exhibited a median PFS of 12.7 months [95% confidence interval (CI), 10.4-18.3], while the placebo group had a PFS of 10.9 months (9.0-13.2; P = 0.2). The median OS was similar in the two groups (31.0 months with nicotinamide vs. 29.4 months with placebo; P = 0.2). Notably, subgroup analyses revealed a significant reduction in mortality risk for females (P = 0.01) and never-smokers (P = 0.03) treated with nicotinamide. CONCLUSIONS: The addition of nicotinamide with EGFR-TKIs demonstrated potential improvements in PFS and OS, with notable survival benefits for female patients and those who had never smoked (ClinicalTrials.gov Identifier: NCT02416739).

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells.

Background: The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD. Method: Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2. Results: Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment. Conclusion: The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Computational identification and experimental verification of a novel signature based on SARS-CoV-2-related genes for predicting prognosis, immune microenvironment and therapeutic strategies in lung adenocarcinoma patients.

Background: Early research indicates that cancer patients are more vulnerable to adverse outcomes and mortality when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, the specific attributes of SARS-CoV-2 in lung Adenocarcinoma (LUAD) have not been extensively and methodically examined. Methods: We acquired 322 SARS-CoV-2 infection-related genes (CRGs) from the Human Protein Atlas database. Using an integrative machine learning approach with 10 algorithms, we developed a SARS-CoV-2 score (Cov-2S) signature across The Cancer Genome Atlas and datasets GSE72094, GSE68465, and GSE31210. Comprehensive multi-omics analysis, including assessments of genetic mutations and copy number variations, was conducted to deepen our understanding of the prognosis signature. We also analyzed the response of different Cov-2S subgroups to immunotherapy and identified targeted drugs for these subgroups, advancing personalized medicine strategies. The expression of Cov-2S genes was confirmed through qRT-PCR, with GGH emerging as a critical gene for further functional studies to elucidate its role in LUAD. Results: Out of 34 differentially expressed CRGs identified, 16 correlated with overall survival. We utilized 10 machine learning algorithms, creating 101 combinations, and selected the RFS as the optimal algorithm for constructing a Cov-2S based on the average C-index across four cohorts. This was achieved after integrating several essential clinicopathological features and 58 established signatures. We observed significant differences in biological functions and immune cell statuses within the tumor microenvironments of high and low Cov-2S groups. Notably, patients with a lower Cov-2S showed enhanced sensitivity to immunotherapy. We also identified five potential drugs targeting Cov-2S. In vitro experiments revealed a significant upregulation of GGH in LUAD, and its knockdown markedly inhibited tumor cell proliferation, migration, and invasion. Conclusion: Our research has pioneered the development of a consensus Cov-2S signature by employing an innovative approach with 10 machine learning algorithms for LUAD. Cov-2S reliably forecasts the prognosis, mirrors the tumor's local immune condition, and supports clinical decision-making in tumor therapies.

Hazard function analysis of prognosis after recurrent colorectal cancer.

BACKGROUND AND OBJECTIVES: Mean survival time (MST) is used as the indicator of prognosis in patients with a colorectal cancer (CRC) recurrence. The present study aimed to visualize the changes in death risk after a CRC recurrence using hazard function analysis (HFA) to provide an alternative prognostic indicator to MST. METHODS: The medical records of 725 consecutive patients with a recurrence following R0 radical surgery for CRC were retrospectively reviewed. RESULTS: The five-year, post-recurrence survival rate was 37.8%, and the MST was 3.5 years while the risk of death peaked at 2.9 years post-recurrence. Seven variables were found to predict short-term survival, including the number of metastatic organs ≥ 2, non-surgical treatment for the recurrence, and a short interval before recurrence. In patients with a recurrence in one organ, the MST was four years, the peak time of death predicted by HFA was 2.9 years, and the five-year survival rate was 45.8%. In patients with a surgical resection of the recurrence, the MST was 8 years, the peak time of death was 3.3 years, and the five-year survival rate was 62%. CONCLUSIONS: The present study established a novel method of assessing changes in mortality risk over time using HFA in patients with a CRC recurrence.

The role of histological subtype and chemotherapy on prognosis of ureteral cancer.

OBJECTIVE: To date, there have been few studies examining the prognostic implications of histological subtypes in ureteral cancer. And chemotherapy plays a crucial role in the treatment of ureteral cancer, while many factors influence the efficacy of chemotherapy. This study aimed to utilize the Surveillance, Epidemiology and End Results database to assess the impact of histological type on ureteral cancer prognostic outcomes and discovered how histological type and T-stage influence the efficacy of chemotherapy. METHODS: Based on Surveillance, Epidemiology, and End Results Program, we reviewed 8915 records of patients with primary ureteral cancer from 18 centers between 2000 and 2018. We focused on the overall survival and cancer-specific survival of the records and used Kaplan‒Meier method to calculate survival curves. RESULTS: In the comparison of prognostic outcomes, atypical subtypes exhibited a less favorable prognosis compared to typical ureteral carcinoma. Notably, patients diagnosed with papillary urothelial carcinoma demonstrated the most favorable overall survival (p = 0.005). Statistically significant benefits were observed in the prognosis of patients with non-papillary urothelial carcinoma who received chemotherapy (HR = 0.860, 95% CI 0.764-0.966, p = 0.011), while chemotherapy did not yield a statistically significant effect on the prognosis of patients with papillary urothelial carcinoma (HR = 1.055, 95% CI 0.906-1.228, p = 0.493). Chemotherapy had an adverse impact on the prognosis of patients with T1 ureteral cancer (HR = 1.235, 95% CI 1.016-1.502, p = 0.034), whereas it exhibited a positive prognostic effect for T3/T4 cases (HR = 0.739, 95% CI 0.654-0.835, p < 0.001). CONCLUSIONS: Histological type affects the prognosis of ureteral cancer. And evaluation of cancer histological type and T stage in ureteral cancer patients prior to chemotherapy is mandatory.

PSAT1 enhances the efficacy of the prognosis estimation nomogram model in stage-based clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is associated with a high prevalence of cancer-related deaths. The survival rates of patients are significantly lower in late-stage ccRCC than in early-stage ccRCC, due to the spread and metastasis of late-stage ccRCC, surgery has not reached the goal of radical cure, and the effect of traditional radiotherapy and chemotherapy is poor. Thus, it is crucial to accurately assess the prognosis and provide personalized treatment at an early stage in ccRCC. This study aims to develop an efficient nomogram model for stratifying and predicting the survival of ccRCC patients based on tumor stage. METHODS: We first analyzed the microarray expression data of ccRCC patients from the Gene Expression Omnibus (GEO) database and categorized them into two groups based on the disease stage (early and late stage). Subsequently, the GEO2R tool was applied to screen out the genes that were highly expressed in all GEO datasets. Finally, the clinicopathological data of the two patient groups were obtained from The Cancer Genome Atlas (TCGA) database, and the differences were compared between groups. Survival analysis was performed to evaluate the prognostic value of candidate genes (PSAT1, PRAME, and KDELR3) in ccRCC patients. Based on the screened gene PSAT1 and clinical parameters that were significantly associated with patient prognosis, we established a new nomogram model, which was further optimized to a single clinical variable-based model. The expression level of PSAT1 in ccRCC tissues was further verified by qRT-PCR, Western blotting, and immunohistochemical analysis. RESULTS: The datasets GSE73731, GSE89563, and GSE150404 identified a total of 22, 89, and 120 over-expressed differentially expressed genes (DEGs), respectively. Among these profiles, there were three genes that appeared in all three datasets based on different stage groups. The overall survival (OS) of late-stage patients was significantly shorter than that of early-stage patients. Among the three candidate genes (PSAT1, PRAME, and KDELR3), PSAT1 was shown to be associated with the OS of patients with late-stage ccRCC. Multivariate Cox regression analysis showed that age, tumor grade, neoadjuvant therapy, and PSAT1 level were significantly associated with patient prognosis. The concordance indices were 0.758 and 0.725 for the 3-year and 5-year OS, respectively. The new model demonstrated superior discrimination and calibration compared with the single clinical variable model. The enhancer PSAT1 used in the new model was shown to be significantly overexpressed in tissues from patients with late-stage ccRCC, as demonstrated by the mRNA level, protein level, and pathological evaluation. CONCLUSION: The new prognostic prediction nomogram model of PSAT1 and clinicopathological variables combined was thus established, which may provide a new direction for individualized treatment for different-stage ccRCC patients.

Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma.

BACKGROUND: Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. METHODS: The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan-Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. RESULTS: HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis. CONCLUSIONS: Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma.

Investigating the level of vitamin D receptor gene expression in two tumoral and healthy breast tissues in breast cancer patients and its association with prognostic factors.

BACKGROUND: Breast cancer is one of the most common cancers known among women. This study aimed to investigate the level of vitamin D receptor gene expression in two tumoral and healthy breast tissues in breast cancer patients and its association with prognostic factors. METHODS: This descriptive cross-sectional study was conducted in 2022 on 50 patients with high suspicion of breast cancer who were candidates for mastectomy and lumpectomy in a learning hospital. From the patients, two tissue samples were prepared, and there was a total of 100 samples. The samples were subjected to H/E staining and evaluated by a pathologist. The presence or absence of malignancy in each sample was confirmed by two pathologists, and HER2/ER/PR indices were determined. Descriptive and analytical statistical methods and SPSS version 22 software were used. RESULTS: The average age of the patients was 51.60 ± 11.22 years old, and the average tumor size was 3.17 ± 1.28. Most tumors were grade 2 (48%). The expression of HER2, ER, and PR was positive in 24, 64, and 54%, respectively. The largest number of cases were in stage 2A. The expression level of vitamin D receptor (VDR) gene in healthy tissue (2.08 ± 1.01) was higher than tumoral tissue (0.25 ± 1.38) (P = 0.001). In tumoral and healthy tissue, VDR expression was not significant according to tumor grade, HER2, ER, PR, LVI, LN, disease stage, age, and tumor size. CONCLUSIONS: The expression level of VDR in healthy tissue was significantly higher than tumoral tissue. However, there was no significant relationship between VDR and tumor grade, HER2, ER, PR, LVI, LN, disease stage, age, and tumor size.

The Expression and Prognostic Significance of ICOS in NSCLC Integrated Pan-Cancer and Multi-Omics Analyses.

Background: Inducible co-stimulator (ICOS) shows great potential in the regulation of innate and adaptive immunity. However, previous studies of ICOS have often been limited to one or two levels. Methods: Using the data from the online database, the immunohistochemistry, and enzyme-linked immunosorbent assays, we investigated the role of ICOS / PD-L1 on patients with NSCLC at the mRNA, protein, and serum levels. Results: Our data revealed that unlike most solid tumors, the mRNA expression of ICOS was down-regulated in NSCLC. In addition, our data also showed that mRNA expression levels in ICOS are negatively associated with poor clinicopathologic grading but positively associated with better prognostic outcomes and higher Tregs infiltration level. Immunohistochemistry showed that ICOS correlated negatively with the T stage; while PD-L1 levels correlated positively with the N stage and FOXP3 levels. Serological biomarker analysis showed that patients with NSCLC had lower sICOS levels, which increased significantly post-surgery, and combined sICOS and sPD-L1 diagnosis improved efficacy and accuracy of disease diagnosis. Conclusion: Our findings support that ICOS suggests lower pathological staging and better prognosis. ICOS is a potential diagnostic and prognostic biomarker for NSCLC.

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication.

BACKGROUND: Liver cancer is one of the deadliest malignant tumors worldwide. Immunotherapy has provided hope to patients with advanced liver cancer, but only a small fraction of patients benefit from this treatment due to individual differences. Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies, thereby improving patient survival rates. Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer, the impact of cell-cell interactions in the tumor microenvironment has not been adequately considered. AIM: To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy. METHODS: Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways. Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells. The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features, and a least absolute shrinkage and selection operator (LASSO) regression model was constructed to screen for diagnostic-related features. Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model. Finally, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified and used to construct an immune-related gene signature. RESULTS: The immune-related gene signature composed of stathmin 1, cofilin 1, and C-C chemokine ligand 5 was identified through cell-cell communication. The effectiveness of the identified gene signature was validated based on experimental results of predictive immunotherapy response, tumor mutation burden analysis, immune cell infiltration analysis, survival analysis, and expression analysis. CONCLUSION: The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment, providing insights for personalized treatment strategies.

Efficacy of radiofrequency ablation combined with sorafenib for treating liver cancer complicated with portal hypertension and prognostic factors.

BACKGROUND: Patients with liver cancer complicated by portal hypertension present complex challenges in treatment. AIM: To evaluate the efficacy of radiofrequency ablation in combination with sorafenib for improving liver function and its impact on the prognosis of patients with this condition. METHODS: Data from 100 patients with liver cancer complicated with portal hypertension from May 2014 to March 2019 were analyzed and divided into a study group (n = 50) and a control group (n = 50) according to the treatment regimen. The research group received radiofrequency ablation (RFA) in combination with sorafenib, and the control group only received RFA. The short-term efficacy of both the research and control groups was observed. Liver function and portal hypertension were compared before and after treatment. Alpha-fetoprotein (AFP), glypican-3 (GPC-3), and AFP-L3 levels were compared between the two groups prior to and after treatment. The occurrence of adverse reactions in both groups was observed. The 3-year survival rate was compared between the two groups. Basic data were compared between the survival and non-surviving groups. To identify the independent risk factors for poor prognosis in patients with liver cancer complicated by portal hypertension, multivariate logistic regression analysis was employed. RESULTS: When comparing the two groups, the research group's total effective rate (82.00%) was significantly greater than that of the control group (56.00%; P < 0.05). Following treatment, alanine aminotransferase and aspartate aminotransferase levels increased, and portal vein pressure decreased in both groups. The degree of improvement for every index was substantially greater in the research group than in the control group (P < 0.05). Following treatment, the AFP, GPC-3, and AFP-L3 levels in both groups decreased, with the research group having significantly lower levels than the control group (P < 0.05). The incidence of diarrhea, rash, nausea and vomiting, and fatigue in the research group was significantly greater than that in the control group (P < 0.05). The 1-, 2-, and 3-year survival rates of the research group (94.00%, 84.00%, and 72.00%, respectively) were significantly greater than those of the control group (80.00%, 64.00%, and 40.00%, respectively; P < 0.05). Significant differences were observed between the survival group and the non-surviving group in terms of Child-Pugh grade, history of hepatitis, number of tumors, tumor size, use of sorafenib, stage of liver cancer, histological differentiation, history of splenectomy and other basic data (P < 0.05). Logistic regression analysis demonstrated that high Child-Pugh grade, tumor size (6-10 cm), history of hepatitis, no use of sorafenib, liver cancer stage IIIC, and previous splenectomy were independent risk factors for poor prognosis in patients with liver cancer complicated with portal hypertension (P < 0.05). CONCLUSION: Patients suffering from liver cancer complicated by portal hypertension benefit from the combination of RFA and sorafenib therapy because it effectively restores liver function and increases survival rates. The prognosis of patients suffering from liver cancer complicated by portal hypertension is strongly associated with factors such as high Child-Pugh grade, tumor size (6-10 cm), history of hepatitis, lack of sorafenib use, liver cancer at stage IIIC, and prior splenectomy.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery.

BACKGROUND: Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer, the prognostic value of hematocrit for colorectal cancer (CRC) patients has not been determined. The prognostic value of red blood cell distribution width (RDW) for CRC patients was controversial. AIM: To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery. METHODS: Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included. The short-term outcomes, overall survival (OS) and disease-free survival (DFS) were compared among the different groups. Cox analysis was also conducted to identify independent risk factors for OS and DFS. RESULTS: There were 4258 CRC patients who underwent radical surgery included in our study. A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group. There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group, respectively. Patients in the higher RDW group had more intraoperative blood loss (P < 0.01) and more overall complications (P < 0.01) than did those in the lower RDW group. Similarly, patients in the lower hematocrit group had more intraoperative blood loss (P = 0.012), longer hospital stay (P = 0.016) and overall complications (P < 0.01) than did those in the higher hematocrit group. The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis (TNM) stage I (OS, P < 0.05; DFS, P = 0.001) and stage II (OS, P = 0.004; DFS, P = 0.01) than the lower RDW group; the lower hematocrit group had worse OS and DFS for TNM stage II (OS, P < 0.05; DFS, P = 0.001) and stage III (OS, P = 0.001; DFS, P = 0.001) than did the higher hematocrit group. Preoperative hematocrit was an independent risk factor for OS [P = 0.017, hazard ratio (HR) = 1.256, 95% confidence interval (CI): 1.041-1.515] and DFS (P = 0.035, HR = 1.194, 95%CI: 1.013-1.408). CONCLUSION: A higher preoperative RDW and lower hematocrit were associated with more postoperative complications. However, only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery, while RDW was not.

Gastric Cancer Immune Subtypes and Prognostic Modeling: Insights from Aging-Related Gene Analysis.

Gastric cancer (GC) is highly heterogeneous and influenced by aging-related factors. This study aimed to improve individualized prognostic assessment of GC by identifying aging-related genes and subtypes. Immune scores of GC samples from GEO and TCGA databases were calculated using ESTIMATE and scored as high immune (IS_high) and low immune (IS_low). ssGSEA was used to analyze immune cell infiltration. Univariate Cox regression was employed to identify prognosis-related genes. LASSO regression analysis was used to construct a prognostic model. GSVA enrichment analysis was applied to determine pathways. CCK-8, wound healing, and Transwell assays tested the proliferation, migration, and invasion of the GC cell line (AGS). Cell cycle and aging were examined using flow cytometry, ß-galactosidase staining, and Western blotting. Two aging-related GC subtypes were identified. Subtype 2 was characterized as lower survival probability and higher risk, along with a more immune-responsive tumor microenvironment. Three genes (IGFBP5, BCL11B, and AKR1B1) screened from aging-related genes were used to establish a prognosis model. The AUC values of the model were greater than 0.669, exhibiting strong prognostic value. In vitro, IGFBP5 overexpression in AGS cells was found to decrease viability, migration, and invasion, alter the cell cycle, and increase aging biomarkers (SA-ß-galactosidase, p53, and p21). This analysis uncovered the immune characteristics of two subtypes and aging-related prognosis genes in GC. The prognostic model established for three aging-related genes (IGFBP5, BCL11B, and AKR1B1) demonstrated good prognosis performance, providing a foundation for personalized treatment strategies aimed at GC.

Integrating bulk and single-cell sequencing data to construct a Scissor+ dendritic cells prognostic model for predicting prognosis and immune responses in ESCC.

Esophageal squamous cell carcinoma (ESCC) is characterized by molecular heterogeneity with various immune cell infiltration patterns, which have been associated with therapeutic sensitivity and resistance. In particular, dendritic cells (DCs) are recently discovered to be associated with prognosis and survival in cancer. However, how DCs differ among ESCC patients has not been fully comprehended. Recently, the advance of single-cell RNA sequencing (scRNA-seq) enables us to profile the cell types, states, and lineages in the heterogeneous ESCC tissues. Here, we dissect the ESCC tumor microenvironment at high resolution by integrating 192,078 single cells from 60 patients, including 4379 DCs. We then used Scissor, a method that identifies cell subpopulations from single-cell data that are associated bulk samples with genomic and clinical information, to stratify DCs into Scissorhi and Scissorlow subtypes. We applied the Scissorhi gene signature to stratify ESCC scRNAseq patient, and we found that PD-L1, TIGIT, PVR and IL6 ligand-receptor-mediated cell interactions existed mainly in Scissorhi patients. Finally, based on the Scissor results, we successfully developed a validated prognostic risk model for ESCC and further validated the reliability of the risk prediction model by recruiting 40 ESCC clinical patients. This information highlights the importance of these genes in assessing patient prognosis and may help in the development of targeted or personalized therapies for ESCC.

Single cell analysis unveils B cell-dominated immune subtypes in HNSCC for enhanced prognostic and therapeutic stratification.

Head and neck squamous cell carcinoma (HNSCC) is characterized by high recurrence or distant metastases rate and the prognosis is challenging. There is mounting evidence that tumor-infiltrating B cells (TIL-Bs) have a crucial, synergistic role in tumor control. However, little is known about the role TIL-Bs play in immune microenvironment and the way TIL-Bs affect the outcome of immune checkpoint blockade. Using single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database, the study identified distinct gene expression patterns in TIL-Bs. HNSCC samples were categorized into TIL-Bs inhibition and TIL-Bs activation groups using unsupervised clustering. This classification was further validated with TCGA HNSCC data, correlating with patient prognosis, immune cell infiltration, and response to immunotherapy. We found that the B cells activation group exhibited a better prognosis, higher immune cell infiltration, and distinct immune checkpoint levels, including elevated PD-L1. A prognostic model was also developed and validated, highlighting four genes as potential biomarkers for predicting survival outcomes in HNSCC patients. Overall, this study provides a foundational approach for B cells-based tumor classification in HNSCC, offering insights into targeted treatment and immunotherapy strategies.