Molecular markers in prostate cancer. Part I: predicting lethality.
Ontology highlight
ABSTRACT:
SUBMITTER: Agrawal S
PROVIDER: S-EPMC3735212 | biostudies-literature | 2009 Jan
REPOSITORIES: biostudies-literature
Publications
Molecular markers in prostate cancer. Part I: predicting lethality.
Agrawal Sachin S Dunsmuir William D WD
Asian journal of andrology 20081201 1
Assessing the lethality of 'early,' potentially organ-confined prostate cancer (PCa) is one of the central controversies in modern-day urological clinical practice. Such cases are often considered for radical 'curative' treatment, although active surveillance may be equally appropriate for many men. Moreover, the balance between judicious intervention and overtreatment can be difficult to judge. The patient's age, comorbidities, family history and philosophy of self-health care can be weighed ag ...[more]
Similar Datasets
Project description:Predicting treatment responses in advanced prostate cancer (PCa) currently centres on prostate-specific antigen (PSA) kinetics and on being able to visualize measurable changes in imaging modalities. New molecular markers have emerged as potential diagnostic and prognostic indicators; these were summarized in Part I of this review in the Asian Journal of Andrology. A number of molecular markers are now being used to enhance PCa imaging and staging. However, management options for advanced and hormone-resistant PCa (HRPC) are limited and additional therapeutic options are needed. Molecular markers have been proposed as potential therapeutic targets using gene therapy and immunomodulation. Additionally, markers identified in early PCa and precursor lesions may offer novel targets for chemoprevention and vaccine development. This review summarizes the current advances regarding the roles of these markers in the management of PCa.
| S-EPMC3735215 | biostudies-literature
Project description:Background: Prostate cancer (PCa) is the second most frequent cause of cancer-related death in men worldwide. It is a heterogeneous disease at molecular and clinical levels which makes its prognosis and treatment outcome hard to predict. The epithelial-to-mesenchymal transition (EMT) marks a key step in the invasion and malignant progression of PCa. We sought to assess the co-expression of epithelial cytokeratin 8 (CK8) and mesenchymal vimentin (Vim) in locally-advanced PCa as indicators of EMT and consequently predictors of the progression status of the disease. Methods: Co-expression of CK8 and Vim was evaluated by immunofluorescence (IF) on paraffin-embedded tissue sections of 122 patients with PCa who underwent radical prostatectomies between 1998 and 2016 at the American University of Beirut Medical Center (AUBMC). EMT score was calculated accordingly and then correlated with the patients' clinicopathological parameters and PSA failure. Results: The co-expression of CK8/Vim (EMT score), was associated with increasing Gleason group. A highly significant linear association was detected wherein higher Gleason group was associated with higher mean EMT score. In addition, the median estimated biochemical recurrence-free survival for patients with < 25% EMT score was almost double that of patients with more than 25%. The validity of this score for prediction of prognosis was further demonstrated using cox regression model. Our data also confirmed that the EMT score can predict PSA failure irrespective of Gleason group, pathological stage, or surgical margins. Conclusion: This study suggests that assessment of molecular markers of EMT, particularly CK8 and Vim, in radical prostatectomy specimens, in addition to conventional clinicopathological prognostic parameters, can aid in the development of a novel system for predicting the prognosis of locally-advanced PCa.
| S-EPMC6421270 | biostudies-literature
Project description:BackgroundKey challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation.MethodsProstatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively.ResultsUsing a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error.ConclusionsOur results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.
| S-EPMC4453845 | biostudies-literature
Project description:Blackspot bruising is the tuber discoloration resulting from mechanical damage in susceptible crops and is a major quality and environmental problem for the potato industry. The present study is aimed at identifying differences in gene expression which are correlated with the development of bruise susceptibility or resistance in tubers. This may produce markers or diagnostic tests for use in predicting enhanced bruise susceptibility in field grown potato crops. Different potato cultivars were grown in field plots at ADAS Gleadthorpe, Nottinghamshire, UK during three growing seasons – 2003, 2004 and 2005. Random samples of tubers (8) were harvested by hand and cores excised from the subdermal tissues of the stolon end of the tubers and immediately frozen and stored in liquid nitrogen for RNA isolations. The remainder of the crops were stored at 4oC for bruise susceptibility testing - samples of tubers (30) from each crop were impacted and incubated for 48h at 30oC. Bruise susceptibility was scored, according to the intensity of pigmentation and the volume of tuber tissue affected, on a scale of 0 (very resistant) – 10 (very susceptible). Crops representing 'very susceptible', 'susceptible', 'moderate' and 'resistant' to bruising, were selected for RNA isolation. Total RNA’s were isolated from frozen cores by the TIGR hot phenol extraction method, precipitated by LiCl and treated with DNase. RNA concentrations were adjusted to ~2ug/ul and analysed on 1% TBE gels after formamide treatment. Any RNA’s which were not pure enough or showed degradation were discarded. Total RNA’s were pooled and 25ul samples aliquotted according to the required hybridisations indicated in the Excel spreadsheet and the on-line information form. Keywords: Direct comparison 32 hybs total
2007-09-01 | E-GEOD-8274 | biostudies-arrayexpress
Project description:Blackspot bruising is the tuber discoloration resulting from mechanical damage in susceptible crops and is a major quality and environmental problem for the potato industry. The present study is aimed at identifying differences in gene expression which are correlated with the development of bruise susceptibility or resistance in tubers. This may produce markers or diagnostic tests for use in predicting enhanced bruise susceptibility in field grown potato crops. Different potato cultivars were grown in field plots at ADAS Gleadthorpe, Nottinghamshire, UK during three growing seasons – 2003, 2004 and 2005. Random samples of tubers (8) were harvested by hand and cores excised from the subdermal tissues of the stolon end of the tubers and immediately frozen and stored in liquid nitrogen for RNA isolations. The remainder of the crops were stored at 4oC for bruise susceptibility testing - samples of tubers (30) from each crop were impacted and incubated for 48h at 30oC. Bruise susceptibility was scored, according to the intensity of pigmentation and the volume of tuber tissue affected, on a scale of 0 (very resistant) – 10 (very susceptible). Crops representing 'very susceptible', 'susceptible', 'moderate' and 'resistant' to bruising, were selected for RNA isolation. Total RNA’s were isolated from frozen cores by the TIGR hot phenol extraction method, precipitated by LiCl and treated with DNase. RNA concentrations were adjusted to ~2ug/ul and analysed on 1% TBE gels after formamide treatment. Any RNA’s which were not pure enough or showed degradation were discarded. Total RNA’s were pooled and 25ul samples aliquotted according to the required hybridisations indicated in the Excel spreadsheet and the on-line information form. Keywords: Direct comparison
2007-09-01 | GSE8274 | GEO
Project description:BackgroundThe derivation of molecular signatures indicative of disease status and predictive of subsequent behavior could facilitate the optimal choice of treatment for prostate cancer patients.MethodsIn this study, we conducted a computational analysis of gene expression profile data obtained from 79 cases, 39 of which were classified as having disease recurrence, to investigate whether advanced computational algorithms can derive more accurate prognostic signatures for prostate cancer.ResultsAt the 90% sensitivity level, a newly derived prognostic genetic signature achieved 85% specificity. This is the first reported genetic signature to outperform a clinically used postoperative nomogram. Furthermore, a hybrid prognostic signature derived by combination of the nomogram and gene expression data significantly outperformed both genetic and clinical signatures, and achieved a specificity of 95%.ConclusionsOur study demonstrates the feasibility of utilizing gene expression information for highly accurate prostate cancer prognosis beyond the current clinical systems, and shows that more advanced computational modeling of tissue-derived microarray data is warranted before clinical application of molecular signatures is considered.
| S-EPMC3425355 | biostudies-literature
Project description:Cholesterol metabolism has been implicated in prostate cancer pathogenesis. Here, we assessed the association of intratumoral mRNA expression of cholesterol synthesis enzymes, transporters, and regulators in tumor specimen at diagnosis and lethal prostate cancer, defined as mortality or metastases from prostate cancer in contrast to nonlethal disease without evidence of metastases after at least 8 years of follow-up. We analyzed the prospective prostate cancer cohorts within the Health Professionals Follow-up Study (n = 249) and the Physicians' Health Study (n = 153) as well as expectantly managed patients in the Swedish Watchful Waiting Study (n = 338). The expression of squalene monooxygenase (SQLE) was associated with lethal cancer in all three cohorts. Men with high SQLE expression (>1 standard deviation above the mean) were 8.3 times (95% confidence interval, 3.5 to 19.7) more likely to have lethal cancer despite therapy compared with men with the mean level of SQLE expression. Absolute SQLE expression was associated with lethal cancer independently from Gleason grade and stage, as was a SQLE expression ratio in tumor versus surrounding benign prostate tissue. Higher SQLE expression was tightly associated with increased histologic markers of angiogenesis. Collectively, this study establishes the prognostic value of intratumoral cholesterol synthesis as measured via SQLE, its second rate-limiting enzyme. SQLE expression at cancer diagnosis is prognostic for lethal prostate cancer both after curative-intent prostatectomy and in a watchful waiting setting, possibly by facilitating micrometastatic disease. Cancer Res; 76(16); 4785-90. ©2016 AACR.
| S-EPMC4987257 | biostudies-literature
Project description:Current prostate cancer prognostic models are based on pre-treatment prostate-specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict clinical disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. We analyzed a Swedish Watchful Waiting cohort (1977â1999) with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer or developed metastases and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. We reasoned that tumor sampling might preclude the identification of the dominant metastatic nodule. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Thus the determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses preventing the development of molecular biomarkers for prostate cancer progression. 281 cases from the population-based Swedish-Watchful Waiting cohort. The cohort consists of men with localized prostate cancer (clinical stage T1-T2, Mx, N0); Training set: first 186 samples; Validation cohort: remaining 95 cases from the same population.
2010-05-07 | E-GEOD-16560 | biostudies-arrayexpress
Project description:Current prostate cancer prognostic models are based on pre-treatment prostate-specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict clinical disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. We analyzed a Swedish Watchful Waiting cohort (1977–1999) with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer or developed metastases and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. We reasoned that tumor sampling might preclude the identification of the dominant metastatic nodule. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. Thus the determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses preventing the development of molecular biomarkers for prostate cancer progression.
2010-03-05 | GSE16560 | GEO
Project description:Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models.We analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases.Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors.The determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging.
| S-EPMC2855514 | biostudies-literature