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PubMed2026

Development and Validation of a Prognostic Signature Based on Transcription Factors Associated with Endoplasmic Reticulum Stress in Pancreatic Adenocarcinoma.

BACKGROUND: Endoplasmic reticulum stress (ER stress) plays a crucial role in influencing the malignant behaviors of various tumors. Targeting the expression or degradation of transcription factors (TFs) offers a promising avenue for cancer treatment. However, a detailed understanding of how ER stress affects TF function and their interactions remains limited. This study aims to develop a prognostic model and identify TFs associated with ER stress in pancreatic ductal adenocarcinoma (PDAC). METHODS: We obtained gene expression profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA). To develop a prognostic signature, we performed several analyses, including unsupervised clustering, enrichment analysis, immune infiltration assessment, as well as univariate, LASSO, and multivariate Cox regression analyses. Four transcription factors-STAT1, IRF6, NRF1, and RXRA-were incorporated into a risk model, which was subsequently validated using the GSE dataset. Additionally, we examined IRF6 through quantitative PCR, western blotting, flow cytometry, and immunohistochemistry in vitro using pancreatic cancer cell lines and a tissue microarray. RESULTS: The high-risk group identified by the model exhibited significant associations with immune cell infiltration and poorer survival outcomes, though there was no significant correlation with tumor purity (p = 0.19). Furthermore, IRF6 downregulation in vitro was found to inhibit pancreatic cancer cell proliferation and promote apoptosis. IRF6 depletion also increased the expression of key molecules involved in ER stress at both the transcriptional and translational levels. Immunohistochemical analysis revealed marked differences in IRF6 expression between tumor and adjacent non-tumor tissues (59.29±29.88 vs. 95.22±40.80, p<0.001). CONCLUSION: This study provides evidence that the constructed risk model can effectively predict prognosis in PDAC patients. Transcription factors related to ER stress, such as IRF6, show promise as both prognostic biomarkers and potential therapeutic targets for PDAC.

Humans↗

PubMed2004

Treatment of malignant gliomas: radiotherapy, chemotherapy and integration of new targeted agents.

Progress in the biological and molecular characterization of gliomas and studies of factors associated with tumor growth and progression have led to translational research projects and the development of rational new approaches regarding prognostic models, better prediction of response to treatment and innovative therapeutic strategies. This review summarizes the available data on established and emerging prognostic factors and prognostic scores, and discusses their limitations as well as their potential influence on future therapeutic efforts. Recent developments in standard treatment options (i.e., surgery, radiotherapy and chemotherapy) are reviewed. Experimental data indicate that inhibition of several signaling pathways (e.g., epidermal growth factor, transforming growth factor-beta and phosphatidylinositol 3 kinase) may represent a promising therapeutic strategy. Some inhibitory agents (i.e., drugs, antibodies and antisense oligonucleotides) have now entered clinical trials, mainly for recurrent gliomas and a small number are being tested in combination with radiotherapy. Early results of such approaches are presented.

Antineoplastic Agents↗

PubMedDate not supplied

[The chronological structure of the population count of the taiga tick in the Maritime Territory].

A time series analysis of 23-years observations of the Ixodes persulcatus imago dynamics was carried out. The tick were counted in forests of the western Sikhote-Alin' foothills near Ussuriysk. The fluctuations of the ticks number are quasiperiodical. They are formed by near 3-years oscillations, long-term non linear trend and accidental component. The observed process was described by means of a statistic model. This model combines the harmonic regression analysis with linear regression analysis. The determination coefficients are 90.8% and 92.7% for the descriptive and prognostic models respectively. The difference between two groups of environmental factors, which influence on the tick number, is discussed. These factors are: 1) the directly influencing factors (functional factors), 2) the factors influencing by dint of natural rhythms being general for a biocoenosis (synchronizing factors).

Animals↗

PubMed2026

An immune exhaustion signature predicts prognosis and identifies patients with diffuse large B-cell lymphoma (DLBCL) who derive preferential benefit from chimeric antigen receptor (CAR)-T cell therapy.

BACKGROUND: The tumor microenvironment (TME) is a key determinant of prognosis in diffuse large B-cell lymphoma (DLBCL). While T-cell exhaustion is implicated in therapeutic failure, its precise molecular hallmarks and utility for predicting response to modern immunotherapies, such as chimeric antigen receptor (CAR)-T cell therapy, remain unclear. METHODS: We performed an integrative analysis of transcriptomic and clinical data from multiple DLBCL cohorts (The Cancer Genome Atlas [TCGA], GSE181063, GSE10846, GSE248835, GSE182434). We used unsupervised clustering, exploratory analysis of single-cell RNA sequencing data, and the least absolute shrinkage and selection operator for variable selection (LASSO-Cox) regression to characterize the exhausted TME, construct a prognostic model, and evaluate its predictive value for CAR-T cell therapy. The model's dynamic behavior was assessed in a proof-of-concept longitudinal cohort of patients treated with the T-cell-engaging bispecific antibody glofitamab. RESULTS: We identified a "high-exhaustion" subtype associated with significantly poorer overall survival (OS; log-rank P = 0.016). Based on this, we developed a five-gene immune exhaustion-Related Prognostic Score (IERPS) that served as a robust independent predictor of poor OS across multiple cohorts. Critically, in a cohort of 256 relapsed/refractory patients, the IERPS was strongly prognostic for event-free survival (EFS) in the standard-of-care (SOC) arm (HR = 2.02, 95% confidence interval [95% CI]: 1.07-3.81, P = 0.029) but lost prognostic significance in the CAR-T arm (HR = 0.70, 95 % CI: 0.35-1.40, P = 0.314). This significant interaction suggests that CAR-T cell therapy may abrogate the poor prognosis associated with a high IERPS. Biologically, exploratory single-cell analysis (n = 4 samples) defined the high-IERPS state by hallmarks of classical T-cell exhaustion, and a descriptive case study showed the score dynamically tracked clinical response to glofitamab. CONCLUSIONS: A state of active T-cell exhaustion and a suppressive TME drive the adverse immune phenotype in DLBCL. Our IERPS model captures this dysfunctional state, acting as a powerful prognostic tool and, more importantly, as a potential predictive biomarker to identify high-risk patients who appear to overcome their inherently poor prognosis through CAR-T cell therapy.

Biomarkers↗

PubMed2026

Imaging‑based models for predicting cerebrovascular complications of carotid stenosis.

This is a protocol for a Cochrane review (prognosis). The objectives are as follows: Primary objective To systematically review and critically appraise multivariable prognostic models developed for adults (≥ 18 years) with carotid stenosis in which imaging biomarkers (e.g. plaque characteristics derived from magnetic resonance imaging (MRI), computed tomography (CT), or ultrasound) constitute the core predictors. The primary focus is to evaluate the predictive performance of these models for cerebrovascular complications - specifically ipsilateral ischaemic stroke and transient ischaemic attack (TIA) - which are the clinical outcomes to be predicted. Where feasible, we will summarise and compare the models' discrimination (C‑statistic/area under the curve (AUC)) and calibration (calibration‑in‑the‑large, calibration slope, observed‑to‑expected ratio) across studies, and assess their potential for clinical application and external validation. For the purpose of defining symptomatic carotid stenosis as an eligibility criterion and subgroup variable, we will include studies that also considered retinal ischaemia (e.g. retinal embolism, amaurosis fugax) as a qualifying event. Secondary objectives To describe the combinations of imaging markers, modelling techniques, sample sizes, and variable‑selection strategies used in the development of the included models To evaluate the performance of these models for additional secondary clinical outcomes: plaque progression or regression, incident high‑risk imaging features, and the transition from asymptomatic to symptomatic disease To explore whether predictive performance differs according to imaging modality (MRI versus CT versus contrast‑enhanced ultrasound (CEUS)) or technical protocol (e.g. 3 T versus 1.5 T, spectral CT versus conventional CT) For studies that report both cerebrovascular and broader cardiovascular outcomes (major adverse cardiovascular events, myocardial infarction, etc.), we will only extract the performance metrics relating to cerebrovascular events for the primary analysis. Performance metrics for cardiovascular outcomes will be considered exploratory and will not form part of the main synthesis.

Humans↗

PubMed1988

Development and validation of a multivariate predictor of mortality in very low birth weight.

Accurate prognosis is critical to the design of all prospective research aimed at improving survival. Predictions based on birth weight, gestational age, or any other single variable, fail to take into account the potentially important contribution of other factors. In order to develop a practical and accurate multivariate model, we studied all singleton pregnancies resulting in viable liveborn infants who weighed less than or equal to 1500 g at birth during 1984 and 1985 at the New York Hospital-Cornell Medical Center. When gestational age, birth weight, and/or crown-heel length were considered, no maternal characteristics were significant predictors of mortality. The model with the maximal predictive accuracy (84.5%) used birth weight and 5-minute Apgar score to calculate a probability of mortality. This prognostic model was then validated in a separate cohort of singletons born in 1986. We conclude that clinical trials should require stratification before randomization, using the calculated probability of mortality, rather than birth weight or gestational age alone. Given the ability of models, such as the one presented here, to generate reasonable estimates of mortality, this information might also be used in the clinical setting to assist parents and physicians in individualized decision-making processes for a given infant.

Adult↗

PubMed2006

Molecular profiling of breast cancer.

PURPOSE OF REVIEW: This review is a comprehensive survey of molecular-profiling literature published since 2004. RECENT FINDINGS: More microarray-based gene-expression profiles that are prognostic for breast cancer have been published, strengthening the possibility that the microarray gene-expression profile may indeed provide clinically meaningful results. Requirement for snap-frozen tissue, however, will continue to be a limiting factor in clinical application. Results from a multicenter validation study were less spectacular than the original findings. A prognostic model based on classical markers performed well in a comparative study. Further clinical validation, with a large sample size, is needed. A prognostic gene-expression profile of 21 genes, which can be assayed using routinely processed formalin-fixed paraffin-embedded tumor tissue, has been introduced and this assay has also been shown to correlate with degree of benefit from chemotherapy. Two large clinical trials to validate gene-expression-based assays are to be launched in North America (TAILORx) and the European Union (MINDACCT). The usefulness of these genomic tools is still being debated, because clinicopathologic factors also are still important. SUMMARY: Gene-expression-based prognostic tests are now available as commercial reference laboratory tests. Their successful implementation will depend on the seamless integration with existing clinicopathologic markers.

Antineoplastic Agents↗

PubMed1995

Survival after surgery for spinal and extremity metastases. Prognostication in 241 patients.

We assessed the survival after surgery in 153 patients with extremity metastases and 88 with spinal metastases. The survival rate for the whole series of 241 patients was 0.30 at 1 year, 0.15 at 2, and 0.08 at 3 years. The 1-year survival rate was the same for the extremity metastases group and the spinal group. Univariate analysis showed that 1-year survival was related to metastatic load, site of primary tumor, and presence of pathologic fracture. Multivariate regression analysis showed that pathologic fracture, visceral or brain metastases, and lung cancer were negative prognostic variables. Solitary skeletal metastases, breast and kidney cancer, myeloma, and lymphoma were positive variables. A prognostication model based on these variables stratified the patients into 3 groups with a 1-year survival ranging from 0.5 to 0.0. These prognostic variables can be used for differentiating the treatment of cancer patients with pathologic fracture or epidural compression.

Adult↗

PubMed2003

Relapse risk assessment of transplantation for patients with chronic myeloid leukaemia.

OBJECTIVE: To analyse the risk factors of relapse before bone marrow transplantation (BMT) and to present the prognostic information as good as possible. METHODS: A total of 3142 patients, who underwent the allogeneic blood or bone marrow transplantation between 1989 and 1997 and were documented in the European Group for Blood and Marrow transplantation (EBMT), were included. Six possible risk factors including type of donor, stage of disease, age, gender, donor-recipient sex combination and the waiting time from diagnosis to transplantation of relapse were considered. The time to relapse was analysed by Kaplan-Meier curves and Cox regression with stratification on prognostic factors that did not satisfy the Proportional Hazard Assumption. RESULTS: An amount of 447 patients relapsed out of all 3142 patients. The relapse rate was 14.2%. Type of donor and stage of disease showed a clear prognostic effect, but failed the proportional hazard assumption. Therefore, the data were stratified on the combination of type of donor and stage of disease. Within these strata an additional significant effect of age could be observed. Relative risk of age > or = 40 vs age < 40 was 1.32 (95% confidence interval 1.09 - 1.59). The prognostic model is summarized graphically. CONCLUSIONS: The combination of type of donor, stage of disease and age of recipient at transplantation are important prognostic factors for relapse after BMT.

Adult↗

PubMed2006

[Model of prognosis of outcome of burn trauma on the basis of probit-analysis].

On the basis of probit-analysis of results of treatment of 10,670 burned patients a prognostic model of the trauma outcome was created as a coordinate network. The model is very accurate, sensitive, specific and simple in use that allows it to be applied for prognosis of burn trauma outcomes in the early period after trauma, especially in organization of medical-evacuation work in places of appearance of mass burns. The model is a standard for the assessment of new protocols of treatment and can serve a criterion of the efficiency of work of intensive care units in burn centers.

Adolescent↗

PubMed2005

Prognostic factors for survival in patients with early-intermediate hepatocellular carcinoma undergoing non-surgical therapy: comparison of Okuda, CLIP, and BCLC staging systems in a single Italian centre.

BACKGROUND: Several prognostic models have been developed to stage hepatocellular carcinoma (HCC) but there is no general consensus on which is the most reliable. We compared three prognostic indices (Okuda, CLIP, and BCLC scoring systems) in a large series of cirrhotic patients with HCC undergoing non-surgical treatment in terms of their ability to classify patients into different risk groups METHODS: We retrospectively studied 268 Italian patients with HCC. A total of 146 patients were treated with ablation, 132 with percutaneous ethanol injection, and 14 with radiofrequency ablation; 103 underwent transcatheter arterial chemoembolisation and 19 had supportive care alone. Factors determining survival were analysed by univariate and multivariate analysis using the Kaplan-Meier method and Cox proportional hazard regression models. Okuda, CLIP, and BCLC scores evaluated before treatment were applied. RESULTS: Median survival was 25.7 months. In a multivariate analysis, portal vein thrombosis, alpha fetoprotein, total bilirubin, and tumour size were significant predictors of survival. Okuda, CLIP, and BCLC scores were all able to predict survival (p<0.001). They identified two, four, and six risk groups, respectively, with a median survival ranging from 27 to 19 months for Okuda, 30 to 5 months for CLIP, and 43 to 7 months for BCLC. CONCLUSIONS: Both CLIP and BCLC scores were more effective than the Okuda score in stratifying patients into different risk groups with early-intermediate HCC. However, the BCLC scoring system gave a better prediction of prognosis in patients with disease diagnosis at a very early stage.

Adult↗

PubMed1996

Neoplastic progression and prognosis in melanoma.

Most melanomas evolve through an initial stage known as radial growth phase (RGP), encompassing in situ and microinvasive malignancies in which the probability of cure approaches 100%. At the present time, despite a shift toward earlier recognition of melanoma, by the time of diagnosis roughly 70% of melanomas have evolved to a point, known as vertical growth phase (VGP) or tumorigenic melanoma, at which cure is not certain, and prognosis depends upon certain attributes of the neoplasm and the host. Attempts have been made to assemble these attributes into prognostic models to permit estimation of the probability of cure for individuals and for groups of patients. Attributes that have been identified as independent prognostic variables include thickness of the primary neoplasm, the numbers of mitotic figures, and the presence of tumor-infiltrating lymphocytes (TIL). Other biologically important prognostic variables are on the horizon, and some will likely be based on molecules (markers) expressed on neoplastic cells that show functional significance in mechanisms of metastasis.

Disease Progression↗

PubMed2004

mRNA microarray analysis in lymphoma and leukemia.

We have reviewed the ability of gene expression microarrays to characterize subgroups of lymphoma and leukemia, identify expression profiles that correlate with known cytogenetic abnormalities, demonstrate that expression profiles can predict prognosis, new proteins identified for diagnosis and followup, and provided new therapeutic targets for chemotherapy. We can expect that new prognostic models will be designed and tested, incorporating the pathologic diagnosis based on morphology, the molecular gene expression profile, and the clinical assessment (e.g. International prognostic index). In addition, the gene expression profiles will be used to generate correlative and ultimately predictive data for response to particular chemotherapeutic regimens. Translation for clinical usage is likely in a diagnostic fashion in both lymphoma and leukemia.

Animals↗

PubMed1989

The clinical and renal biopsy predictors of long-term outcome in lupus nephritis: a study of 87 patients and review of the literature.

The prognostic markers in 87 consecutive patients with lupus nephritis who underwent renal biopsy are reported for five clinically relevant long-term outcomes--renal insufficiency, renal failure, death due to renal systemic lupus erythematosus, death due to non-renal SLE and death due to SLE, both renal and non-renal. We have demonstrated that a number of previously neglected or rarely studied predictors were important prognostic markers. These included the duration of renal disease before biopsy, overall severity of SLE, as well as the presence of vasculitis, hypertension or a comorbid ailment. Furthermore, the study confirms the predictive importance of serum creatinine, 24-h urinary excretion of protein, C3, and of the activity and chronicity indices on biopsy. However, overall a simple measure of tubulointerstitial disease was the best predictor obtained from biopsy. Prognostic models based on clinical data alone were developed for each of the five outcomes. The models amplify our clinical understanding of lupus nephritis. Markers of renal severity were most important in predicting renal outcomes such as renal insufficiency and renal failure. Prognostic factors less directly related to renal disease (comorbidity and vasculitis) were important predictors of fatality. A marker of immunologic disease activity (C3) was a valuable predictor for many of the outcomes. Thus markers of disease severity reflecting organ damage due to SLE and other comorbid conditions could be combined with markers of immunologic activity to predict a variety of outcomes of relevance to a clinician. When biopsy data obtained by light or electron microscopy were evaluated for their ability to add new predictive information to the clinical models, only a limited value for biopsy was noted. It is likely that this reflected the close correlational relationships between clinical and biopsy variables, the strong clinical models generated, and the inclusion in the clinical models of the previously neglected clinical variables, duration of renal disease before biopsy and the presence of vasculitis or comorbid disease.

Adolescent↗

PubMed2006

Retention of chromosome arm 5q in stage II colon cancers identifies 83% of liver metastasis occurrences.

The decision to use chemotherapy in the treatment of colon cancer patients depends on the risk of developing metastases, as estimated by clinicopathological staging combining body imaging and pathological findings. The aim of this study was to identify all chromosome arms that, when allelotyped, correlate with the metastatic process, add prognostic information to pathology, and are of relevance for predicting metachronous metastases. A 5-year follow-up survey enrolled 401 MSS (microsatellite stable) colon cancer patients who were divided into three groups. Staging was performed with and without imaging data (called tumor and patient staging, respectively). The first 192 patients were used to construct a model prognosticating metastases. The subsequent 146 patients were used to validate this model. The third group evaluated its consistency by comparing the status of the relevant chromosome arms in 63 liver metastases and primary tumors that did or did not metastasize. The first group identified three factors: tumor staging (P < 0.0001), 5q status (P = 0.003), and gender (P = 0.02). The second group confirmed 5q as a marker of metastasis occurrence (P = 0.004). Merged data predicted that, when both 5q arms are retained, metastatic risk increases 4.3-fold in stage II patients. The third group corroborated these findings, with a 5q retention rate in metastases comparable to that of primary tumors that metastasize, but significantly higher than that observed in nonmetastatic tumors (one-tail, P = 0.0005). Long arm of chromosome 5 allelotyping detects high-risk stage II tumors. This simple, easily implemented, and inexpensive test increases the power of randomized studies that evaluate chemotherapy.

Aged↗

PubMed1985

Prognosis of malignant melanoma.

Multiple factors appear to influence survival in patients with malignant melanoma. Although at present thickness appears to be the best individual prognostic factor, other variables such as anatomic site of the lesion, ulceration, and level consistently appear in multivariate prognostic models. These multivariate models enable the assessment of patient prognosis for the optimization of treatment as well as the evaluation of future therapeutic trials. Future study of these prognostic factors will hopefully help us to understand the pathophysiology of melanoma and, possibly, unlock the secrets of the biology of this disease.

Age Factors↗

PubMed2006

Biomarkers and neuroimaging of brain injury after cardiac arrest.

Unfortunately, it remains a difficult task to predict with certainty which patients will have a poor neurological outcome following cardiac arrest. Finding a quantitative prognostic model of outcome has become the objective of many intensivists to assist grieving families in making early difficult decisions regarding withdrawal of life support. An ideal prognostic test should be readily available, easily reproducible, and associated with a high degree of specificity for poor outcome. The goal is not to define which patients may recover, but rather which patients have no likelihood of meaningful neurological recovery at all to justify early withdrawal of support. The literature and the role of biochemical markers in the blood and in the cerebrospinal fluid will be evaluated as prognosticators following cardiac arrest. Radiological indicators of anoxic cerebral damage are reviewed. Each serum or radiological marker has its pros and cons. To accurately prognosticate following cardiac arrest, a multimodal scale or algorithm that incorporates serum markers, radiological markers, and the neurological exam is clearly needed. As these techniques are being evaluated more closely and as imaging modalities increase in sensitivity and portability, physicians will continue to assist families by providing some guidance as to which patients have no chance of meaningful recovery.

Biomarkers↗

PubMed2006

Patterns of p73 N-terminal isoform expression and p53 status have prognostic value in gynecological cancers.

The goal of this study was to determine whether patterns of expression profiles of p73 isoforms and of p53 mutational status are useful combinatorial biomarkers for predicting outcome in a gynecological cancer cohort. This is the first such study using matched tumor/normal tissue pairs from each patient. The median follow-up was over two years. The expression of all 5 N-terminal isoforms (TAp73, DeltaNp73, DeltaN'p73, Ex2p73 and Ex2/3p73) was measured by real-time RT-PCR and p53 status was analyzed by immunohistochemistry. TAp73, DeltaNp73 and DeltaN'p73 were significantly upregulated in tumors. Surprisingly, their range of overexpression was age-dependent, with the highest differences delta (tumor-normal) in the youngest age group. Correction of this age effect was important in further survival correlations. We used all 6 variables (five p73 isoform levels plus p53 status) as input into a principal component analysis with Varimax rotation (VrPCA) to filter out noise from non-disease related individual variability of p73 levels. Rationally selected and individually weighted principal components from each patient were then used to train a support vector machine (SVM) algorithm to predict clinical outcome. This SVM algorithm was able to predict correct outcome in 30 of the 35 patients. We use here a mathematical tool for pattern recognition that has been commonly used in e.g. microarray data mining and apply it for the first time in a prognostic model. We find that PCA/SVM is able to test a clinical hypothesis with robust statistics and show that p73 expression profiles and p53 status are useful prognostic biomarkers that differentiate patients with good vs. poor prognosis with gynecological cancers.

Age Factors↗