PROstate CAncer Radiotherapy - Bowel Quality of Life (PROCAR-BQ)
Ontology highlight
ABSTRACT:
DISEASE(S): Prostatic Neoplasms,Radiotherapy Side Effect,Intestinal Diseases,Prostate Cancer,Malnutrition,Bowel Dysfunction
PROVIDER: 61671 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:The prophylactic irradiation of pelvic lymph-nodes by means of Whole-Pelvis Radiotherapy (WPRT) in the treatment of prostate cancer (PCa) is aimed at the timely eradication of microscopic lymph-nodal metastases. Nevertheless, even though delivered by means of modern Intensity-Modulated Radiotherapy (IMRT) techniques, WPRT may result in intestinal, hematologic and urinary toxicity (IT, HT, UT, respectively) severely affecting patients’ daily health-related quality-of-life (HRQoL) within the so-called and inadequately investigated Pelvic Radiation Disease.
The aim of this study is to develop sophisticated predictive models of IMRT-WPRT induced patient-reported HT, IT and UT in PCa. The possible correlation between several clinical factors and radiation doses received by various pelvic structures (i.e. pelvic bones subvolumes, intestinal loops, sigmoid, rectum and bladder) and risk and severity of patient-reported IT, UT and HT will be analyzed and robust multi-variable models will be developed and internally validated. A secondary end-point will be the identification of specific symptoms affecting patients’ HRQoL during irradiation and in the long term, overall and in different therapeutic settings (radical, adjuvant and salvage). Lastly, possible correlation between HT and UT/IT will be investigated.
| 2217512 | ecrin-mdr-crc
Project description:Prostate cancer (PCa) is the second most prevalent malignancy in Western countries and the fifth leading cause of cancer-related death in men. The risk factors for PCa include obesity, age, and family history. Visceral fat has been linked to PCa risk, which has prompted researchers to investigate the influence of body composition and fat distribution on PCa prognosis. This study investigated the correlation between the composition of pelvic adipose tissue (PAT) and PCa aggressiveness to understand the role played by this tissue in PCa progression. Moreover, we prepared a periprostatic adipose tissue (PPAT)-conditioned medium (CM) to determine the influence of the PPAT secretome on the pathophysiology of PCa. This study included 60 patients with localized PCa who received robot-assisted radical prostatectomy. Medical records were collected, and magnetic resonance imaging scans were analyzed, and body compositions were calculated to identify the correlations between adipose tissue volume and clinical PCa aggressiveness. CM was prepared using PPAT and perivesical adipose tissue (PVAT) collected from 25 patients during surgery, and its influence was investigated using the PCa cell lines C4-2 and LNCaP and the prostate epithelial cell line PZ-HPV-7. Cell proliferation assays and RNA sequencing were performed. The initial prostate-specific antigen level was significantly correlated with pelvic and perirectal adipose tissue volumes. PPAT volume was significantly higher in patients with extracapsular tumor extension. PCa cells proliferated was significantly slower when cultured in PPAT-CM compared with when cultured in control- and PVAT-CM. RNA sequencing revealed that immune responses and the cell death and apoptosis pathways were enriched in PPAT-CM-cultured cells. The cytokines or other secreted factors in PPAT-CM induced PCa cell apoptosis. This in vitro study revealed that the PPAT secretome inhibits PCa cells proliferation by activating immune responses and promoting cancer cell apoptosis. This mechanism may act as a first-line defense during the early stages of PCa.
2024-05-15 | GSE267084 | GEO
Project description:Prostate cancer (PCa) is one of the most prevalent cancers among men and the fifth leading cause of cancer-related death in men. Currently, PCa suspicion is based on abnormal digital rectal examination and/or raised PSA serum levels, with prostate needle biopsy being required for a definitive diagnosis. Histopathological classification of tumours based on GS grading, cancer staging and PSA levels are used to predict the indolent or aggressive progression of the tumour as well as the likelihood of disease recurrence. These diagnosis and prognosis tools for PCa have revealed limited usefulness, especially PSA testing, which despite organ-specificity is not cancer-specific, being associated with low specificity. In this vein, new markers have been proposed in order to increase the accuracy of PCa detection, most of them proteins. Despite the significant efforts that have been undertaken for discovering other biomarkers for PCa management, few were translated into clinical practice. The simple and non-invasive nature of urine collection along with its proteome stability and storing many secreted proteins of prostate origin, makes the identification of PCa urinary biomarkers an attractive approach. With this in mind, we aimed to compare the urinary proteome profile of PCa patients with non-cancer patients in order to identify non-invasive candidate biomarkers for PCa prediction. To fulfil this task, we followed a shotgun LC-MS/MS approach using an Orbitrap instrument. A combination of two different software packages, MaxQuant and Proteome Discover was used to increase the robustness of analysis and enhance the search for new biomarkers. Proteins quantification was based on a label-free quantification approach (false discovery rate (FDR) 1%). The present dataset was used to disclosure potential markers in PCa management.
2022-05-19 | PXD017902 | Pride
Project description:Interventions: Plan of Investigation
The primary objective of Phase IV of the study will be to test the scale structure, reliability and validity and cross-cultural applicability of the proctitis module (EORTC QLQ-PRT23) to be used alone or together with the EORTC Quality of Life Questionnaire (EORTC QLQ-C30) in patients who are receiving radiation therapy to their pelvic region.
Participants
Patients will be recruited from collaborating hospitals in Australia, Norway, Germany, Italy and France. This will enable the testing of the questionnaire in Anglo-Saxon countries, Northern Europe and Southern Europe.
We aim to recruit patients who have received a curative dose of radiation therapy to their pelvic region (50-70Gy). This will include tumours located in the following sites: prostate, cervix and rectum. Patients will be eligible for the study if they are receiving a radical course of pelvic irradiation (50-70 Gy) and able to converse freely in the language that the questionnaire is written. Participants will be ineligible for the study if they have previously received radiation therapy, the radiation dose prescribed is less than 50 Gy and they are participating in other Quality of Life trials that might interfere with this study.
Trial Design
This is a cross-sectional longitudinal descriptive study, which collects Quality of Life data alongside socio-demographic and clinical background data at three time points during the patients’ radiation therapy treatment. The following time points will be used to test for acute proctitis:
1.At least two (2) weeks prior to radiotherapy treatment (when they see their clinician);
2.During the first (1st) week of treatment;
3.At the end of treatment;
4.At the three (3) to six (6) months scheduled
Primary outcome(s): Proctitis symptoms will be measured using the proctitis module developed (EORTC PRT-23)
Proctitis is an unpleasant recurrent clinical syndrome that is manifest by bouts of the following symptoms: anorectal pain, profuse rectal bleeding or blood clots, explosive bowel urgency, frequent diarrhoea, profuse mucous discharge, faecal and/or mucous incontinence[Prior to radiation therapy
During first week of treatment
Completion of treatment
Post treatment (3-6 months)]
Study Design: Purpose: Screening;Duration: Longitudinal;Selection: Defined population;Timing: Prospective
| 2455292 | ecrin-mdr-crc
Project description:Due to heterogeneous multifocal nature of prostate cancer (PCa), there is currently a lack of biomarkers that stably distinguish it from benign prostatic hyperplasia (BPH), predict clinical outcome and guide the choice of optimal treatment. In this study, RNA-seq analysis was applied to formalin-fixed paraffin-embedded (FFPE) tumor and matched normal tissue samples collected from Russian patients with PCa and BPH. We identified 3384 genes differentially expressed (DE) (FDR < 0.05) between tumor tissue of PCa patients and adjacent normal tissue as well as both tissue types from BPH patients. Overexpression of four of the genes previously not associated with PCa (ANKRD34B, NEK5, KCNG3, and PTPRT) was validated by RT-qPCR. Furthermore, the enrichment analysis of overrepresented microRNA and transcription factor (TF) recognition sites within DE genes revealed common regulatory elements of which 13 microRNAs and 53 TFs were thus linked to PCa for the first time. Moreover, 8 of these TFs (FOXJ2, GATA6, NFE2L1, NFIL3, PRRX2, TEF, EBF2 and ZBTB18) were found to be differentially expressed in this study, making them not only candidate biomarkers of prostate cancer but also potential therapeutic targets.
2017-03-27 | GSE89223 | GEO
Project description:miRNAs have been proven to be very useful biomarkers, readily detectable in body fluids, particularly urine may be a valuable source to identify changes in miRNA levels that contribute to better differentiate prostate cancer (PCa) from benign prostate hyperplasia (BPH) cases. In order to characterize microRNA expression in urine samples from PCa, we analyzed expression of 376 microRNAs in 9 samples of PCa and 9 of BPH. The Normalized Ct values were compared between PCa and BPH. Statistical comparisons were made using Mann-Whitney U test, considering two different distributions. We found statiscally differences n expression for 21 miRNAs (Fold change >2 and P value<0.05). For the initial screening of all the studied samples, we selected only those with a concentration above 100 ng/ml, for a total of 9 samples of group of PCa and 9 BPH group. The isolated RNA was evaluated by measuring the absorbance at 260 nm and 280 nm. RNA aliquots from specimens were pooled and reverse transcription (RT) reaction was pweformed. In total, we formed 3 pools from BPH specimens and 3 from PCa ones. The RT product was used to perform a preamplification reaction. The product of preamplification teaction was loaded into the Taqman Homo sapiens microRNA Low density arrays (TLDA) panel A and amplification signal was detected using the 7900 FAST real time thermal cycler (ABI).
2012-07-12 | E-GEOD-39314 | biostudies-arrayexpress
Project description:Predicting Outcomes of Prostate Cancer Immunotherapyby Personalized Mathematical Models
Natalie Kronik1¤, Yuri Kogan1, Moran Elishmereni1, Karin Halevi-Tobias1, Stanimir Vuk-Pavlovic ́2.,Zvia Agur1*.1Institute for Medical BioMathematics, Bene Ataroth, Israel,2College of Medicine, Mayo Clinic, Rochester, Minnesota, United States of America
Abstract
Background:Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients.We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simplemathematical models.Methodology/Principal Findings:We developed a general mathematical model encompassing the basic interactions of avaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cellvaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes inprostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were dividedinto each patient’s training set and his validation set. The training set, used for model personalization, contained thepatient’s initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized modelswere simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set.The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients(the coefficient of determination between the predicted and observed PSA values wasR2= 0.972). The model could notaccount for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validatedpersonalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccinationregimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Conclusions/Significance:Using a few initial measurements, we constructed robust patient-specific models of PCaimmunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value andfeasibility of individualized model-suggested immunotherapy protocols.
2020-01-13 | MODEL2001130003 | BioModels
Project description:This study presents a novel allograft model of high-risk, localised PCa. In characterising this model we have focused on its response to radiotherapy (RT).
2020-10-06 | GSE146790 | GEO
Project description:The present study describes a novel xenograft-based biomarker discovery platform and proves its usefulness in the discovery of novel serum markers for prostate cancer (PCa). By immunizing immuno-competent mice with serum from nude mice bearing PCa xenografts, an antibody response against xenograft-derived antigens was elicited. By probing protein microarrays with serum from immunized mice, several PCa-derived antigens were identified, of which a subset was successfully retrieved in serum from mice bearing PCa xenografts and validated in human serum samples of PCa patients. In conclusion, this novel method allows for the identification of low abundant cancer-derived serum proteins, circumventing dynamic range and host-response issues in standard patient cohort proteomics comparisons.
2011-12-16 | GSE16220 | GEO
Project description:It is well known that prostate cancer (PCa) is a progressive disease involving multiple gene alterations. The Gleason score (GS) is a morphologic feature of PCa used in the clinic to evaluate the risk of disease progression. However, GS often fail to clearly distinguish between indolent and aggressive disease. The aim of this study was to identify potential biomarkers for PCa risk stratification. An in-depth proteomics analysis (LC ESI-MS/MS) was performed on human PCa and BPH tissues. First, we identified differentially expressed proteins between PCa and BPH samples. We then filtered the proteins based on peptide spectrum matches and selected a panel of candidates. To assess and validate the clinical significance of these peptides we performed an integrative bioinformatics analysis using public database repositories. We identified YWHAZ, an androgen receptor downstream target, as one of the proteins enriched in PCa compared with BPH. We also found a strong association of YWHAZ expression with poor prognosis across different PCa datasets. Briefly, overall and relapse-free survival were significantly shorter in PCa cases expressing high vs. low YWHAZ expression. Further, multivariate analyses displayed high significant correlation with poor prognosis, independent from GS, age, PSA at diagnosis and TMPRSS2-ERG fusion. A multi-cancer screening for YWHAZ unveils amplification as the main alteration for this gene correlating with increased mRNA expression levels across all types of cancer through the cBioPortal platform. YWHAZ rises as a promising prognostic factor in PCa, independent from GS, aiding in disease risk stratification.
2021-09-08 | PXD014291 | Pride