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PubMed2026

Integrative analysis identifies a glycosylation-related lncRNA signature associated with prognosis in kidney renal clear cell carcinoma.

BACKGROUND: Glycosylation and long non-coding RNAs (lncRNAs) play critical roles in tumor progression. However, the prognostic significance of glycosylation-related lncRNAs (GRLncs) in kidney renal clear cell carcinoma (KIRC) remains largely unclear. This study aimed to identify prognostic GRLncs and construct a predictive model for KIRC prognosis. METHODS: Transcriptomic and clinical data of KIRC patients were analyzed to identify GRLncs associated with overall survival (OS). A prognostic model was constructed based on selected GRLncs, and its predictive performance was evaluated using Kaplan-Meier (KM) survival analysis, receiver operating characteristic (ROC) curves, and univariate and multivariate Cox regression analyses. Patients were stratified into high- and low-risk groups according to the median risk score, and internal validation was performed using training and testing cohorts to assess the stability of the model. Tumor microenvironment characteristics, immune checkpoint expression, immunotherapy response, and drug sensitivity were further analyzed. In addition, the expression of three signature lncRNAs was validated by real-time quantitative polymerase chain reaction (RT-qPCR) in 10 paired KIRC tumor and adjacent normal tissues. Functional roles of selected lncRNAs were investigated using antisense oligonucleotides (ASOs)-mediated knockdown in KIRC cell lines, followed by Cell Counting Kit 8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU) incorporation, colony formation, and migration assays. RESULTS: Five GRLncs (AC093278.2, EPB41L4A-DT, DLGAP1-AS2, AC084876.1, and AC005261.3) were identified and used to construct a prognostic model. AC093278.2 and EPB41L4A-DT were protective factors, whereas DLGAP1-AS2, AC084876.1, and AC005261.3 were risk factors. KM analysis on GRLncs-based risk score stratification revealed patients in the high-risk group had significantly poorer OS than those in the low-risk group. ROC analysis and Cox regression demonstrated that the GRLnc-based risk score served as an independent predictor of KIRC prognosis and exhibited favorable predictive performance compared with conventional clinical variables. High- and low-risk groups also exhibited distinct immune microenvironment characteristics, immune checkpoint expression patterns, and predicted drug sensitivities. RT-qPCR detected significant downregulation of protective factor-EPB41L4A-DT in KIRC tissues, while risk factors-DLGAP1-AS2 and AC084876.1 showed expression trends consistent with their predicted risk attributes. Functional experiments further revealed that knockdown of DLGAP1-AS2 and AC084876.1 suppressed proliferation and migration of KIRC cells, whereas knockdown of EPB41L4A-DT promoted these processes, supporting the biological relevance of these three signature lncRNAs. CONCLUSIONS: This study establishes a novel prognostic model based on five GRLncs that showed promising performance in The Cancer Genome Atlas (TCGA)-based analyses of KIRC. The combined clinical expression analysis and functional validation of three constituent GRLncs (DLGAP1-AS2, EPB41L4A-DT, and AC084876.1) supports the biological plausibility of the model and suggest that GRLncs may serve as potential prognostic biomarkers and therapeutic targets for KIRC.

Kidney renal clear cell carcinoma (KIRC)↗
PubMed1998

Prognostic factors in metastatic germ cell tumors.

Metastatic germ cell cancer is a very heterogeneous group with respect to prognosis under cisplatinum-based chemotherapy. The main determinants of complete response and survival are not only the extension of the metastases but much more the biology of the underlying tumor which is represented by the location of the metastases (pulmonary versus nonpulmonary visceral metastases (liver, bone, central nervous system) and the level of the marker elevation (AFG, HCG, LDH). Using these parameters patients with seminoma can be in two or three prognostic divided groups, depending on the model used; nonseminomatous germ cell cancer can be divided in three prognostic groups (good, intermediate and poor prognosis) with a 5 year survival of 90%, 70%, and 50%, respectively. The rate of marker decline and AFP- "surge" are not proven to be significant indicators of prognosis after the start of chemotherapy. Also, molecular markers i12p, p53, Rb, DNA-repair-capacity, etc, currently do not contribute to the prognostic models. In conclusion, with the present available prognostic models the patients with seminomatous as well as nonseminomatous cancer can be attributed to different prognostic groups for first-line as well as salvage treatment. This allows to the selection of patients for a risk adapted treatment and for the investigation of less toxic regimen for good prognosis patients and more aggressive protocols for intermediate and in particular poor risk patients.

Biomarkers↗
PubMed2003

Ki-67 index enhances the prognostic accuracy of the urothelial superficial bladder carcinoma risk group classification.

Approximately 80% of bladder tumors are urothelial superficial papillary carcinomas (USPC). Despite a generally good prognosis, these tumors have a strong propensity to recur and about 1/3 of them compared to disease progression. Histological assessment of these superficial tumors is not sufficiently discriminator in predicting prognosis; therefore, we decided to evaluate the prognostic significance of p53 and Ki-67 immunoexpression in low-grade (GI-II) USPC in order to predict the potential outcome of these tumors. P53 and Ki-67 immunoexpression were studied in function of recurrence-free and progression-free survival in 159 primary superficial bladder tumors. A prognostic risk model based on grade, stage and multifocality was also evaluated. P53 accumulation was significantly related to tumor progression (p=0.006). High Ki-67 index (>/=18%) and multifocality were significantly related to recurrence (both p=0.0001) and progression-free survival (both p=0.0001) and were independent prognostic factors in the multivariate analysis. The prognostic risk model based on grade, stage and multifocality was not an efficient discriminator of outcome. Adding the Ki-67 index into the risk model, single pTa/T1-GI Ki-67 positive tumors, usually classified as low risk, were reclassified as of intermediate risk. After this reclassification, the risk group model identified a subgroup of pTa/T1-G1 with a high risk of recurrence and progression. Ki-67 index is a reliable prognostic marker in urothelial superficial bladder carcinoma and, when included into a risk profile classification of the low-grade USPC, the accuracy of the prognostic discrimination is enhanced.

Biomarkers, Tumor↗
PubMed2025

The MTORC1 signaling pathway related gene POLR3G serves as a potential prognostic biomarker in Hepatocellular Carcinoma.

This study aims to investigate the prognostic significance and potential biological functions of the MTORC1 signaling pathway-associated gene POLR3G in Hepatocellular carcinoma (HCC). A prognostic risk model for HCC was developed by integrating HCC-related datasets and associated clinical data obtained from The Cancer Genome Atlas (TCGA) database. The GSVA website was employed to analyze the model genes across pan-cancer datasets, focusing on copy number variations (CNV), single nucleotide variations (SNV), methylation differences, drug sensitivity and immune cell infiltration profiles. Subsequently, we examined the expression levels and prognostic significance of POLR3G in HCC. Utilizing Spearman correlation analysis, we identified genes associated with POLR3G. Furthermore, Gene Set Enrichment Analysis (GSEA) was employed to elucidate the potential signaling pathways in which POLR3G may be involved. The relationship between POLR3G expression and immune cell abundance in HCC samples was assessed using the ssGSEA algorithm. Finally, the impact of POLR3G on HCC cell proliferation was validated through CCK-8 and EDU cell proliferation assays. Through univariate Cox regression analysis and LASSO regression analysis, we established a prognostic risk model for HCC comprising 13 genes. The analysis revealed that individuals categorized in the low-risk group had a markedly improved overall survival probability relative to those in the high-risk group. POLR3G exhibited a markedly elevated expression in HCC tissues when compared to adjacent normal tissues. The expression of POLR3G was correlated with tumor grade, and elevated POLR3G expression was associated with poor prognosis in HCC patients. Furthermore, the expression level of POLR3G was found to be correlated with the level of immune cell infiltration. Knockdown of POLR3G significantly inhibited the proliferative capacity of hepatocellular carcinoma cells. The findings suggest that POLR3G may serve as a potential biomarker influencing the prognosis of hepatocellular carcinoma patients by modulating the tumor immune microenvironment.

Humans↗
PubMed2026

Integrative analysis of the roles and prognostic value of RNA-binding proteins in papillary renal cell carcinoma.

RNA-binding proteins (RBPs) serve essential roles in various cancer types, but their functions in papillary renal cell carcinoma (pRCC) have not been elucidated to date. In our work, differentially expressed RBPs in pRCC were identified after acquisition of RNA-sequencing and clinical data related to pRCC from The Cancer Genome Atlas database(TCGA). Functional enrichment analysis and protein interaction network analysis, along with univariate and multivariate Cox regression analyses, were performed to uncover potential biological effects of the identified RBPs and screen the hub RBPs for pRCC prognosis. We identified 251 up-regulated and 129 down-regulated RBPs, and filtered out seven hub RBPs, namely, SRSF8, CD3EAP, HBS1L, ELAC2, MRPL34, NOP2 and IGF2BP2, for their prognostic relevance. A prognostic risk score model for overall survival of pRCC patients was constructed based on the seven hub RBPs. Further analysis showed that the low-risk group had higher survival rate than the high-risk group in both training and validation cohorts. The predictive accuracy was verified in the Human Protein Atlas database.In addition, we introduced the GSE15641 dataset from the Gene Expression Omnibus (GEO) database for independent external validation, and confirmed the expression levels of HBS1L, MRPL34 and IGF2BP2 through real-time quantitative PCR (RT-qPCR) and Western blotting (WB) using human renal tubular epithelial cell line HK-2 and human papillary renal cell carcinoma cell line Caki-2. In pRCC, CD3EAP was significantly elevated, while ELAC2, IGF2BP2, MRPL34, SRSF8 and HBS1L were significantly reduced. There was no significant difference between tumor and normal tissues in NOP2 expression. Risk score and tumor grade were independent prognostic factors associated with overall survival. In addition, we established a nomogram based on the seven prognostic RBPs to help predict overall survival at 1-3 years. In conclusion, seven differentially expressed hub RBPs were identified as potential prognostic biomarkers for pRCC. Our prognostic model might serve as a support for better treatment decision-making. Our work could provide potential new ideas for diagnosis and research on targeted drugs for pRCC.

Bioinformatics↗
PubMedDate not supplied

The bootstrap and identification of prognostic factors via Cox's proportional hazards regression model.

This paper describes the use of the bootstrap, a new computer-based statistical methodology, to help validate a regression model resulting from the fitting of Cox's proportional hazards model to a set of censored survival data. As an example, we define a prognostic model for outcome in childhood acute lymphocytic leukemia with the Cox model and use of a training set of 224 patients. To validate the accuracy of the model, we use a bootstrap resampling technique to mimic the population under study in two stages. First, we select the important prognostic factors via a stepwise regression procedure with 100 bootstrap samples. Secondly we estimate the corresponding regression parameters for these important factors with 400 bootstrap samples. The bootstrap result suggests that the model constructed from the training set is reasonable.

Child↗
PubMed1991

An evaluation of potential prognostic indicators in cardiac patients.

Cardiovascular disease results in more deaths and higher medical costs than any other medical problem. Cardiac patients may be transported to centers for specialized care. We evaluated historical, current event, and physiologic items (n = 32) for ability to predict use of specialized care and hospital costs. For 199 patients studied, seven items were prognostic. A model classifying patients by presence of predictors was developed. For the group without predictors and the group with multiple predictors, sensitivity and specificity were respectively very good. For 125 (63%) of the patients in middle categories, the model was not sufficiently sensitive to be prognostic. A scoring system for all cardiac patients could not be developed. Patients requiring only diagnostics were responsible for financial deficits, as were all Medicare patient groups. Patients staying longer than seven days, or having surgery, or both, were responsible for the largest deficits (if on Medicare) and the highest profits (if not on Medicare). Advance validation of the need to transport is difficult, with far-reaching medical and financial implications.

Adult↗
PubMed1992

Vibrations--discriminant models and possibilities for prognosticating specific and non-specific effects on the organism.

The present study involved 290 workers from branches of industry in which they were exposed to intense vibration and 102 patients suffering from disease due to vibration. Some specific (physiological) indices for exposure to vibration, such as the sensation of vibration, cold provocation test, Doppler-ultrasound, etc., and some non-specific (biochemical) indices, such as blood lipids, electrolytes and trace elements were studied. A discriminant analysis was made and 17 discriminant models (including different numbers of physiological and biochemical indices, age, and length of service) were elaborated. These models were used to predict the presence or absence of concomitant diseases, such as hypertension, coronary heart disease and arthritic lesions in persons exposed to vibrations; the stage of the vibration disease; the occurrence of exposure to vibration or of vibration disease. It was shown that physiological (specific) and biochemical (non-specific) indices affected by the exposure to vibration were interrelated, and that their estimation by means of the discriminant analysis revealed the distinction between the states mentioned above.

Adult↗
PubMed1998

[Neuron-specific enolase (NSE) in the surveillance of small cell cancers. An evaluation of the prognostic information using Markov's model].

RATIONALE: An elevated serum NSE concentration is generally a bad prognostic sign when a diagnosis of small cell lung cancer is made. However, the marker may vary from time to time crossing the discriminant threshold (12.5 ng/ml) in one direction or the other. These variations are presumed to reflect the progress of the disease but it has not been shown that the risk of death from the disease is changed by alterations in the serum concentration of NSE. To resolve this question we have used Markov's mathematical model (homogeneous over time and in three states). METHOD: A prospective study has included 52 patients suffering from small cell cancer and treated with chemotherapy based on cisplatin. The NSE was measured following each treatment and three monthly in subsequent follow up. Markov's model was studying the intensities of transition and the risks of death between the two following transient states: living with an NSE concentration of < or = to 12.5 ng/ml, living with an NSE concentration of > 12.5 ng/ml, and an absorbing state: death. RESULTS: When a level of > 12.5 ng/ml was noted the mean time of maintaining in this state was short (123 days). During this time when a transfer was effected in 44 per cent of cases there is turn towards the opposite state (living with a concentration < 12.5 ng/ml) showing the real reversibility between the two transient states. When a patient had an elevated concentration of serum NSE the risk of death was 2.23 times greater than in the opposite state (living with a low NSE; P < 0.01). CONCLUSION: The observation of an elevated NSE concentration at any time in the follow up of patients suffering from small cell cancer was strongly associated with an elevated risk of death but a return from this state towards a state of less risk (living with a low NSE level) remains possible. This works suggests that the NSE levels may be useful in the follow up of small cell lung cancer.

Antineoplastic Agents↗
PubMed1999

Clinical application of proliferating cell nuclear antigen, oncoprotein p53 and tumor front grading analysis in patients operated on for laryngeal cancer.

The authors assessed proliferating cell nuclear antigen (PCNA), p-53 oncoprotein and morphologic tumor front grading (TFG) in patients with advanced squamous cell carcinoma (SCC), of the larynx and a poor prognosis and tried to find a correlation with tumor stage, the Broders grading system, local and neck lymph node metastases, as well as nodal and local recurrences. In addition, utility of the parameters investigated was evaluated in developing a prognostic factor model, using uni- and multivariate Cox regression analysis. Included in this study were 54 patients (mean age 57 years +/- 8.6). PCNA-positive staining was found in all but one patient with advanced disease, while p-53 stained positively in only 24 subjects (44.4%). The PCNA index ranged from 4.6 to 59.0% (mean, 23.4 +/- 11. 0) and the p-53 index varied from 4.0 to 42.0% (mean, 17.2 +/- 8.6). The TFG score ranged from 9 to 23 points (mean, 15.1 +/- 3.2). PCNA, p-53 and TFG were found to be the markers that provided significant additional information about the biological behavior of tumor cells. The high variability of the results (PCNA, p-53) and high percentage of negatively stained cells (p-53) reduced their application in clinical use. PCNA correlated with tumor grade, G (r = 0.38; P < 0. 01), but negatively with nodal (N) disease(r = -0.37; P < 0.01). The mean values of PCNA and p-53 index were higher in the subgroup with local recurrences. Our present attempt to develop a useful prognostic factor model failed.

Adult↗
PubMed2026

SERPINE1-centric inflammatory signature associates with treatment resistance and survival in laryngeal squamous cell carcinoma.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) prognosis remains poor despite treatment advances. More accurate prognostic assessment models can help guide individualized treatment and improve prognosis. Chronic inflammation contributes to tumorigenesis, yet inflammatory response-related genes (IRGs) in LSCC prognosis are underexplored. This study aimed to construct an IRG prognostic signature for LSCC and further dissect core IRG-mediated mechanisms of immune escape and chemoresistance. METHODS: Transcriptional profiles and clinical data from LSCC patients were retrieved from The Cancer Genome Atlas (TCGA). IRGs were sourced from Gene Set Enrichment Analysis (GSEA) hallmark gene set. We identified differentially expressed IRGs linked to survival outcomes in LSCC. Key IRGs were subsequently selected using least absolute shrinkage and selection operator (LASSO) Cox regression analysis to establish an inflammatory risk score model. This model underwent internal validation within the TCGA cohort and external validation using independent Gene Expression Omnibus (GEO) datasets. We further assessed the model's association with the tumor immune microenvironment and the impact of IRGs on chemotherapy response. Finally, the functional roles of interested signature IRG were experimentally validated in LSCC cell lines. RESULTS: Four significant IRGs (AQP9, ITGA5, LCK, SERPINE1) were identified to build the risk score model. The model stratified LSCC patients into distinct prognostic groups: TCGA cohort: 5-year area under the curve (AUC) =0.836, P<0.001; GSE25727 cohort: 5-year AUC =0.706, P=0.02; GSE27020 cohort: 5-year AUC =0.798, P<0.01. Multivariate analysis confirmed the risk score as an independent prognostic factor (P<0.05). High-risk patients showed reduced immune cell infiltration (CD8+ T cells, dendritic cells) and suppressed immune pathways. Multi-algorithm immune analysis further revealed defective antigen presentation and reduced anti-tumor immune infiltration in high-risk LSCC, promoting tumor immune escape. GSEA/Gene Ontology (GO) enrichment combined with drug sensitivity prediction further revealed that high-risk tumors activate invasive signaling and acquire broad chemoresistance alongside impaired anti-tumor immunity. SERPINE1 might be associated with chemotherapy resistance and exhibited the highest alteration frequency (predominantly amplification) and overexpression in LSCC tissues. Its knockdown significantly suppressed proliferation, migration, invasion and chemoresistance in LSCC cells. Immunohistochemistry (IHC) confirmed tumor SERPINE1 overexpression (P=0.002 vs. normal tissues), correlating with poor survival (P<0.001). CONCLUSIONS: The 4-IRG risk signature is a reliable prognostic indicator reflecting immune dysfunction in LSCC. SERPINE1 is validated as a therapeutic target and biomarker, enriching our understanding of gene regulation dynamics in LSCC.

Laryngeal cancer↗
PubMed1987

Progress toward predictive models for the outcome of treatment for acute nonlymphocytic leukemia.

A prognostic factor model for "high risk" patients (those more than 70 years old or with secondary leukemia) which involves the serum albumin and platelet count has recently been reported. This model permits the division of the "high risk" patient group into those with an 80% likelihood of surviving high-dose cytosine arabinoside therapy and those with a greater than 70% likelihood of dying.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2004

Tree-based model for breast cancer prognostication.

PURPOSE: To define prognostic groups for recurrence-free survival in breast cancer, assess relative effects of prognostic factors, and examine the influence of treatment variations on recurrence-free survival in patients with similar prognostic-factor profiles. PATIENTS AND METHODS: We analyzed 1,055 patients diagnosed with stage I-III breast cancer between 1990 and 1996. Variables studied included socioeconomic factors, tumor characteristics, concurrent medical conditions, and treatment. The primary end point was recurrence-free survival (RFS). Multivariable analyses were performed using recursive partitioning and Cox proportional hazards regression. RESULTS: The most significant difference in prognosis was between patients with fewer than four and those with at least four positive nodes (P <.0001). Four distinct prognostic groups (5-year RFS, 97%, 78%, 58%, and 27%) were developed, defined by the number of positive nodes, tumor size, progesterone receptor (PR) status, differentiation, race, and marital status. Patients with fewer than four positive nodes and tumor < or = 2 cm, PR positive, and well or moderately differentiated had the best prognosis. RFS in this group was unaffected by type of adjuvant therapy (P =.38). Patients with at least four positive nodes and PR-negative tumors had the worst prognosis, and those treated with tamoxifen plus chemotherapy had the best outcome in this group (P =.0001). Among patients in the two intermediate-risk groups, those treated with tamoxifen or a combination of tamoxifen and chemotherapy had the best outcome. CONCLUSION: Lymph node status, PR status, tumor size, differentiation, race, and marital status are valuable for prognostication in breast cancer. The prognostic groups derived can provide guidance for clinical trial design, patient management, and future treatment policy.

Adult↗
PubMed2004

Selective prognostic impact of serum alpha-fetoprotein level in patients with hepatocellular carcinoma: analysis of 543 patients in a single center.

The prognostic impact of serum alpha-fetoprotein (AFP) level in patients with hepatocellular carcinoma (HCC) is controversial. This study aimed to investigate the predictive ability of serum AFP in HCC patients. A total of 543 patients undergoing surgical resection (258 patients) and non-surgical treatment (285 patients) including transarterial chemoembolization and percutaneous injection therapy were retrospectively studied. Overall, AFP level >400 ng/ml was an independent poor prognostic predictor [relative risk (RR): 1.4, 95% confidence interval (CI): 1.0-1.9, p=0.049]. Stratified analysis showed that there was a sharp contrast of predictive power of AFP level in treatment strategy and tumor size. In surgical patients, serum AFP >400 ng/ml was a tumor size-independent predictor of tumor recurrence (RR: 1.7, 95% CI: 1.2-2.5, p=0.006) and survival (RR: 2.3, 95% CI: 1.3-3.8, p=0.002). However, there was no association between AFP level and survival in the non-surgical group (p=0.597). Alternatively, among the 157 patients with large (>5 cm) HCCs, AFP >400 ng/ml independently predicted a poor survival (RR: 1.9, 95% CI: 1.2-2.5, p=0.012), whereas no clear relationship between AFP level and survival was found among the 386 patients with small (< or =5 cm) HCCs (p=0.685). There was no differential prognostic impact of serum AFP levels in other variables. In conclusion, serum AFP level is a weak prognostic predictor in HCC patients. Its predictive ability is highly selective and dependent on treatment strategy and tumor size. Incorporation of serum AFP level into any prognostic prediction model should be based on its distinctive selective prognostic power.

Aged↗