Prognosis Stratification for pT4bN0M0 Colorectal Cancer Following Multivisceral Resection
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer,Colorectal Neoplasms
PROVIDER: 116743 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Hypertension in pregnancy is the leading cause of morbidity and mortality in pregnancy, affecting up to 10% of all gestations1. Hypertensive disorders of pregnancy include chronic hypertension, gestational hypertension, eclampsia and pre-eclampsia, all of which increase the risk of complications in both mothers and babies during gestation. Preeclampsia, in particular, is characterised by the new-onset of gestational hypertension in the presence of proteinuria or other organ damage. It affects 5-7% of pregnancies and causes approximately 76,000 maternal deaths and 500,000 foetal deaths worldwide each year2. The classification of preeclampsia has been evolving over the last decade. In 2013, American College of Obstetricians and Gynecologists (ACOG) and International Society for the Study of Hypertension in Pregnancy (ISSHP) in the absence of proteinuria included other symptoms/features including liver dysfunction, thrombocytopenia, cerebrovascular events or foetal growth restriction (FGR) in the diagnosis of preeclampsia 1,3,4. Despite the fact that preeclampsia is a multifactorial and heterogeneous disorder, it is now widely accepted that preeclampsia is stratified depending on the time of onset into: i) early-onset PE (EOPE) manifested before 34 weeks of gestation, and ii) late-onset PE (LOPE) manifested from 34 weeks of gestation. Although EOPE and LOPE share the same diagnostic criteria, these two phenotypes of preeclampsia lead to different outcomes. EOPE is commonly associated with FGR, abnormal uterine artery Doppler often leading to preterm birth and higher risk of post-pregnancy morbidities5,6. On the other hand, LOPE appears to be a less severe disorder, often with normal or slightly increased uterine resistance index and a low rate of FGR6,7. Distinct delineation between EOPE and LOPE is still not well understood, with most patients with preeclampsia presenting elements of both pathologies proposing a clinical spectrum for preeclampsia. The lack of untargeted discovery studies involving ‘omics’ analyses has impeded understanding of the molecular differences between these two phenotypes of preeclampsia. Notably, a study from 20058 utilised a proteomics approach using urine samples from a cohort of pregnant women with EOPE and healthy controls, however the differences between EOPE and LOPE were not elucidated. Another more recent bioinformatics study, identified overlapping pathogenic mechanisms between preeclampsia, hypertension and heart disease but could not stratify between EOPE and LOPE due to underreported of data related to individual phenotypes9. In this study, we conducted an unbiased, comprehensive proteomics investigation using plasma samples collected from patients with EOPE (n=17) and LOPE (n=11), compared with age- and BMI-matched normotensive controls (n=18). The use of plasma samples is able to better reflect the pathogenesis of EOPE and LOPE as systemic conditions centred by widespread endothelial dysfunction.
2023-03-11 | PXD026931 | Pride
Project description:Neuroblastoma (NB) is the most common extracranial malignant tumor in children. Although the survival rate of NB has improved over the years, the outcome of NB still remains poor for over 30% of cases. A more accurate risk stratification remains a key point in the study of NB and the availability of novel prognostic biomarkers of 'high-risk' at diagnosis could help improving patient stratification and predicting outcome. In this paper we show a biomarker discovery approach applied to the plasma of 172 NB patients. Plasma samples from a first cohort of NB patients and age-matched healthy controls were used for untargeted metabolomics analysis based on high-resolution mass spectrometry (HRMS). Differential expression analysis highlighted a number of metabolites annotated with a high degree of identification. Among them, 3-O-methyldopa (3-O-MD) was validated in a second cohort of NB patients using a targeted metabolite profiling approach and its prognostic potential was also analyzed by survival analysis on patients with 3 years follow-up. High expression of 3-O-MD was associated with worse prognosis in the subset of patients with stage M tumor (log-rank p < 0.05) and, among them, it was confirmed as a prognostic factor able to stratify high-risk patients older than 18 months. 3-O-MD might be thus considered as a novel prognostic biomarker of NB eligible to be included at diagnosis among catecholamine metabolite panels in prospective clinical studies. Further studies are warranted to exploit other potential biomarkers highlighted using our approach.
2023-07-14 | MTBLS4294 | MetaboLights
Project description:Purpose Survival of patients with multiple myeloma is highly heterogeneous from periods of few weeks to more than ten years. We used gene-expression profiles of myeloma cells obtained at diagnosis to identify broadly applicable prognostic markers. Methods In a training set of 182 patients, we used supervised methods to identify individual genes associated with length of survival. A survival model was built from these genes. The validity of our model was assessed in our test set of 68 patients and in three independent cohorts comprising 853 multiple myeloma patients. Results The 15 strongest genes associated with the length of survival were used to calculate a risk score and to stratify patients in low-risk and high-risk. The survival-predictor score was significantly associated with survival in both the training and test sets and in the external validation cohorts. The Kaplan Meier estimates of rates of survival at 3 years were 90.5 percent (95 percent CI, 85.6 – 95.3), and 47.4 (95 percent CI, 33.5 - 60.1) respectively in our patients having a low-risk or high-risk, independently of traditional prognostic factors. High-risk patients constituted a homogeneous biological entity characterized by the overexpression of genes involved in cell cycle progression and its surveillance, while low-risk patients were heterogeneous and displayed hyperdiploid signatures. Conclusion Gene expression-based survival prediction and molecular features associated with high-risk patients may be useful for developing prognostic markers and may provide basis to treat these patients with new targeted anti-mitotics. Keywords: Gene-expression profiling
2008-08-05 | GSE7039 | GEO
Project description:BackgroundThe effectiveness of adjuvant transarterial chemoembolization (TACE) for intrahepatic cholangiocarcinoma (ICC) after hepatectomy remains unclear. This study was performed to identify ICC patients who would benefit from adjuvant TACE.Patients and methodsThe study included 553 patients who underwent hepatectomy for ICC between January 2008 and February 2011 at the Eastern Hepatobiliary Surgery Hospital and who were treated with or without TACE (122 with TACE and 431 without TACE). Survival risk stratification was performed using the established prognostic nomogram (ICC nomogram). The predictive performance was evaluated by concordance index and calibration. The tumor recurrence and overall survival (OS) rates were analyzed by the Kaplan-Meier method before and after propensity score matching (PSM).ResultsThe predictive performance of the ICC nomogram was demonstrated by the well-fitted calibration curves and an optimal c-index of 0.71 for OS prediction. In the whole cohort, the 5-year recurrence and OS rates between the TACE and non-TACE groups were significantly different (5-year recurrence: 72.9% vs. 78.1%; OS: 38.4% vs. 29.7%). After 1:1 PSM, the TACE and non-TACE groups (122 patients each) had similar 5-year recurrence and OS rates (5-year recurrence: 72.9% vs. 74.2%; OS: 38.4% vs. 36.0%). By survival risk stratification based on ICC nomogram, only the patients in the lowest tertile (nomogram scores ?77) benefited from adjuvant TACE (TACE vs. non-TACE groups: 90.4% vs. 95.9% for 5-year recurrence; 21.3% vs. 6.2% for 5-year OS).ConclusionAdjuvant TACE following liver resection might be suitable for ICC patients with high ICC nomogram scores (?77).Implications for practiceThe accurate predictive performance of the established prognostic nomogram for intrahepatic cholangiocarcinoma (ICC) following liver resection was reconfirmed in an independent cohort with 553 patients. Based on the survival risk stratification using the nomogram, adjuvant transarterial chemoembolization following liver resection might be suitable only for ICC patients with high scores from the nomogram.
| S-EPMC4571785 | biostudies-literature
Project description:No consensus treatment regime exists beyond surgery for malignant peripheral nerve sheath tumours (MPNST), and the purpose of the present study was to find new approaches to stratify patients with good and poor prognosis and to better guide therapeutic intervention for this aggressive soft tissue cancer. Genome-wide RNA expression was analysed for 30 MPNSTs and eight neurofibromas from Scandinavian patients, and the overall gene expression in these two groups were compared in order to identify prognostic markers.
2015-03-11 | E-GEOD-66743 | biostudies-arrayexpress
Project description:The study entails novel bio-marker discovery of Tumor Aggressive Grade signature (TAGs) genes and their role in recurrence free survival of breast cancer (BC) patients. Current BC dataset was used for co-expression analysis of TAGs genes and their role in BC progression. Additionally, recent findings have suggested an importance of structural organization of sense-antisense gene pairs (SAGPs) for transcription, post-transcriptional and post-translational events and their associations with cancer and disease. We studied SAGPs in which both gene partners are protein encoding genes (coding-coding SAGPs), their role in human BC development and demonstrated their potential for BC stratification and prognosis. Based on gene expression and correlation analyses we identified the robust set of breast cancer-relevant SAGPs (BCR-SAGPs). We isolated and characterized the sense-antisense gene signature (SAGS) and evaluated its prognostic potential in various gene expression datasets comprising 1161 BC patients. The methods used included the Cox proportional survival analysis, statistical analysis of clinicopathologic parameters and differential gene expression. The SAGS was effective in identification of BC patients with the most aggressive disease. Independently, we validated the SAGS using 58 RNA samples of breast cancer tumors purchased from OriGene Technologies (Rockville, MD).
2015-05-10 | GSE61304 | GEO
Project description:The study entails novel bio-marker discovery of Tumor Aggressive Grade signature (TAGs) genes and their role in recurrence free survival of breast cancer (BC) patients. Current BC dataset was used for co-expression analysis of TAGs genes and their role in BC progression. Additionally, recent findings have suggested an importance of structural organization of sense-antisense gene pairs (SAGPs) for transcription, post-transcriptional and post-translational events and their associations with cancer and disease. We studied SAGPs in which both gene partners are protein encoding genes (coding-coding SAGPs, ccSAGPs), their role in human BC development and demonstrated their potential for BC stratification and prognosis. Based on gene expression and correlation analyses we identified the robust set of breast cancer-relevant ccSAGPs (BCR-ccSAGPs). We isolated and characterized the sense-antisense gene classifier (SAGC) and evaluated its prognostic potential in various gene expression datasets comprising 1161 BC patients. The methods used included the Cox proportional survival analysis, statistical analysis of clinicopathologic parameters and differential gene expression.The SAGC was effective in identification of BC patients with the most aggressive disease. Independently, we validated the SAGC using 58 RNA samples of breast cancer tumors purchased from OriGene Technologies (Rockville, MD). Sixty two total RNA samples from breast tumors and normal breast epithelium have been purchased from OriGene Technologies in March, 2011. Four RNA samples were obtained from normal individuals. Among 58 breast tumors (58 patients) 56 were diagnosed as ductal breast adenocarcinoma, 1 - as lobular breast adenocarcinoma and 1 - as squamous cell carcinoma. Gene expression data for all the samples were quantified by using whole-genome RNA microarrays (HG-U133 plus 2.0, Affymetrix).
2015-05-10 | E-GEOD-61304 | biostudies-arrayexpress
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2020-06-18 | PXD019864 |
Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication.
2014-08-18 | GSE54467 | GEO
Project description:In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features were evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients - gene, protein, and microRNA expression as well as clinical, pathologic and mutation information - to determine their relative impact on prognosis. We used classification frameworks based on pre-validation and bootstrap multiple imputation classification to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients, providing useful insights for ongoing developments in the individualized treatment of melanomas patients. SPECIAL NOTE: In this study, survival data were re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset (GSE53118: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53118). The current survival data are considered to be more accurate although the expression information has not changed. In addition, there were 5 samples (122, 144, 195, 264, and 358) for which gene expression information were not available at the time of analysis. However, the associated clinical information for these samples is provided since it was analysed elsewhere in the accompanying publication. Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. We previously analyzed the distribution of survival times in these samples and identified more favorable and less favorable groups as patients having time from surgery to death from melanoma greater than 4 years with no sign of relapse (n=25) or less than 1 year (n=22), respectively (Mann et al. 2013, PMID: 22931913). Since that publication, survival data have been re-extracted from the MIA research database for all patients and brought up to date, revealing discrepancies affecting survival class in the case of four patients compared with the previous dataset. The current survival data are considered to be more accurate. MRNA expression profiling and somatic mutation profiling, were performed as previously described in Mann et al. 2013 (PMID: 22931913).
2014-08-18 | E-GEOD-54467 | biostudies-arrayexpress