Prognostic implication of TERT promoter mutation and circulating tumor cells in muscle-invasive bladder cancer

Purpose: Current clinical prognostic factors are not accurate enough to identify and monitor those muscle-invasive bladder cancer (MIBC) patients at high risk of progression after radical cystectomy (RC). Here, we determined genetic alterations in the tumor and circulating tumor cell (CTC) enumeration to find biomarkers useful for the management of MIBC after RC. Methods: Thirty-nine MIBC patients undergoing RC were included. Tumoral tissue DNA was analyzed by next generation sequencing. CTCs were isolated from blood collected before RC and one, four and 12 months later. Results: Sixteen (41%) patients progressed in a median time of 8.5 months and 11 (69%) of these patients harbored the TERT c.-124C > T mutation. All progressive patients harboring the TERT c.-124C > T mutation presented a significant increase in CTC number 12 months after RC compared to those without the mutation. Additionally, CTC number at 12 months was identified as an independent prognostic biomarker for tumor progression and cancer specific survival (CSS). Ten (63%) progressive patients showed an increment of CTC number with a median anticipation period of four months compared with imaging techniques. Conclusions: The TERT c.-124C > T mutation could be considered a biomarker of aggressivity. CTC enumeration is a useful tool for identifying MIBC patients at high risk of progression and CSS after RC and for detecting tumor progression earlier than imaging techniques

Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma

The inaccuracy of the current prognostic algorithms and the potential changes in the therapeutic management of localized ccRCC demands the development of an improved prognostic model for these patients. To this end, we analyzed whole-transcriptome profiling of 26 tissue samples from progressive and non-progressive ccRCCs using Illumina Hi-seq 4000. Differentially expressed genes (DEG) were intersected with the RNA-sequencing data from the TCGA. The overlapping genes were used for further analysis. A total of 132 genes were found to be prognosis-related genes. LASSO regression enabled the development of the best prognostic six-gene panel. Cox regression analyses were performed to identify independent clinical prognostic parameters to construct a combined nomogram which includes the expression of CERCAM, MIA2, HS6ST2, ONECUT2, SOX12, TMEM132A, pT stage, tumor size and ISUP grade. A risk score generated using this model effectively stratified patients at higher risk of disease progression (HR 10.79; p < 0.001) and cancer-specific death (HR 19.27; p < 0.001). It correlated with the clinicopathological variables, enabling us to discriminate a subset of patients at higher risk of progression within the Stage, Size, Grade and Necrosis score (SSIGN) risk groups, pT and ISUP grade. In summary, a gene expression-based prognostic signature was successfully developed providing a more precise assessment of the individual risk of progression

Cell-Free DNA as a Prognostic Biomarker for Monitoring Muscle-Invasive Bladder Cancer

Cell-free DNA (cfDNA) has recently emerged as a real-time biomarker for diagnosis, monitoring and prediction of therapy response in tumoral disease. Here, we evaluated cfDNA as a prognostic biomarker for monitoring muscle-invasive bladder cancer (MIBC) patients at different follow-up time points. Blood samples from 37 MIBC patients who underwent radical cystectomy (RC) were collected at cystectomy and 1, 4, 12 and 24 months later. Plasma cfDNA amount and fragmentation patterns were determined. Four mutations were analyzed in cfDNA to detect circulating tumor DNA (ctDNA) during patient follow-up. During a median follow-up of 36 months, 46% of patients progressed; median time to progression was 10 months. cfDNA levels and ctDNA status four months after RC were identified as independent prognostic biomarkers of tumor progression (HR 5.290; p = 0.033) and cancer-specific survival (HR 4.199; p = 0.038), respectively. Furthermore, ctDNA clearance four months after RC was significantly associated with patients’ clinical outcomes. In conclusion, cfDNA levels and ctDNA status four months after RC have prognostic implications in MIBC patients. In addition, cfDNA monitoring is useful to predict patient outcomes after RC. cfDNA analysis in the clinical setting could greatly improve MIBC patient management.This research was funded by the Instituto de Salud Carlos III (ISCIII) through the Plan Estatal de Investigación Científica y Técnica y de Innovación 2018–2020, project reference number PI17/01343, and co-funded by the European Regional Development Fund (ERDF)

Application of Artificial Intelligence Algorithms Within the Medical Context for Non-Specialized Users: the CARTIER-IA Platform

The use of advanced algorithms and models such as Machine Learning, Deep Learning and other related approaches of Artificial Intelligence have grown in their use given their benefits in different contexts. One of these contexts is the medical domain, as these algorithms can support disease detection, image segmentation and other multiple tasks. However, it is necessary to organize and arrange the different data resources involved in these scenarios and tackle the heterogeneity of data sources. This work presents the CARTIER-IA platform: a platform for the management of medical data and imaging. The goal of this project focuses on providing a friendly and usable interface to organize structured data, to visualize and edit medical images, and to apply Artificial Intelligence algorithms on the stored resources. One of the challenges of the platform design is to ease these complex tasks in a way that non-AI-specialized users could benefit from the application of AI algorithms without further training. Two use cases of AI application within the platform are provided, as well as a heuristic evaluation to assess the usability of the first version of CARTIER-IA. Year of Publication 2021 Journal International Journal of Interactive Multimedia and Artificial Intelligence Volume 6 Issue Regular Issue Number 6 Number of Pages 46-53 Date Published 06/2021 ISSN Number 1989-1660 URL https://www.ijimai.org/journal/sites/default/files/2021-05/ijimai_6_6_5.pdf DOI 10.9781/ijimai.2021.05.005 DOI Google Scholar BibTeX EndNote X3 XML EndNote 7 XML Endnote tagged Marc RIS Attachment ijimai_6_6_5.pdf 932.11 K

KoopaML, a Machine Learning platform for medical data analysis

Machine Learning allows facing complex tasks related to data analysis with big datasets. This Artificial Intelligence branch allows not technical contexts to get benefits related to data processing and analysis. In particular, in medicine, medical professionals are increasingly interested in Machine Learning to identify patterns in clinical cases and make predictions regarding health issues. However, many do not have the necessary programming or technological skills to perform these tasks. Many different tools focus on developing Machine Learning pipelines, from libraries for developers and data scientists to visual tools for experts or platforms to learn. However, we have identified some requirements in the medical context that raise the need to create a customized platform adapted to end-user found in this context. This work describes the design process and the first version of KoopaML, an ML platform to bridge the data science gaps of physicians while automatizing Machine Learning pipelines. The platform is focused on enhanced interactivity to improve the engagement of physicians while still providing all the benefits derived from the introduction of Machine Learning pipelines in medical departments, as well as integrated ongoing training during the use of the tool’s features

Cell-Free DNA as a Prognostic Biomarker for Monitoring Muscle-Invasive Bladder Cancer

Cell-free DNA (cfDNA) has recently emerged as a real-time biomarker for diagnosis, monitoring and prediction of therapy response in tumoral disease. Here, we evaluated cfDNA as a prognostic biomarker for monitoring muscle-invasive bladder cancer (MIBC) patients at different follow-up time points. Blood samples from 37 MIBC patients who underwent radical cystectomy (RC) were collected at cystectomy and 1, 4, 12 and 24 months later. Plasma cfDNA amount and fragmentation patterns were determined. Four mutations were analyzed in cfDNA to detect circulating tumor DNA (ctDNA) during patient follow-up. During a median follow-up of 36 months, 46% of patients progressed; median time to progression was 10 months. cfDNA levels and ctDNA status four months after RC were identified as independent prognostic biomarkers of tumor progression (HR 5.290; p = 0.033) and cancer-specific survival (HR 4.199; p = 0.038), respectively. Furthermore, ctDNA clearance four months after RC was significantly associated with patients' clinical outcomes. In conclusion, cfDNA levels and ctDNA status four months after RC have prognostic implications in MIBC patients. In addition, cfDNA monitoring is useful to predict patient outcomes after RC. cfDNA analysis in the clinical setting could greatly improve MIBC patient management

Differential gene expression profile between progressive and de novo muscle invasive bladder cancer and its prognostic implication

This study aimed to ascertain gene expression profle diferences between progressive muscle-invasive bladder cancer (MIBC) and de novo MIBC, and to identify prognostic biomarkers to improve patients' treatment. Retrospective multicenter study in which 212 MIBC patients who underwent radical cystectomy between 2000 and 2019 were included. Gene expression profles were determined in 26 samples using Illumina microarrays. The expression levels of 94 genes were studied by quantitative PCR in an independent set of 186 MIBC patients. In a median follow-up of 16 months, 46.7% patients developed tumor progression after cystectomy. In our series, progressive MIBC patients show a worse tumor progression (p= 0.024) and cancer-specifc survival (CSS) (p= 0.049) than the de novo group. A total of 480 genes were found to be diferently expressed between both groups. Diferential expression of 24 out of the 94 selected genes was found in an independent cohort. RBPMC2 and DSC3 were found as independent prognostic biomarkers of tumor progression and CALD1 and LCOR were identifed as prognostic biomarkers of CSS between both groups. In conclusion, progressive and de novo MIBC patients show diferent clinical outcome and gene expression profles. Gene expression patterns may contribute to predict high-risk of progression to distant metastasis or CSS

Assessment of aggressive bladder cancer mutations in plasma cell-free DNA

Background and aimsThe spatial and temporal genetic heterogeneity of bladder cancer (BC) makes challenging to find specific drivers of metastatic disease, thus preventing to determine those BC patients at high risk of tumor progression. Our aim was to identify DNA mutations providing aggressive behavior to bladder tumors and analyze them in patients’ cell-free DNA (cfDNA) during their follow-up after radical cystectomy (RC) in order to monitor tumor evolution.MethodsSix BC patients who underwent RC and presented disease progression during their follow-up were included. Next-generation sequencing was used to determine somatic mutations in several primary tumor and metastatic specimens from each patient. Shared DNA mutations between primary bladder tumor and metastatic sites were identified in cfDNA samples through droplet digital PCR.ResultsBesides BC genetic heterogeneity, specific mutations in at least one of these genes —TERT, ATM, RB1, and FGFR3— were found in primary tumors and their metastases in all patients. These mutations were also identified in the patients’ cfDNA at different follow-up time points. Additionally, the dynamic changes of these mutations in cfDNA allowed us to determine tumor evolution in response to treatment.ConclusionThe analysis of BC mutations associated with poor prognosis in plasma cfDNA could be a valuable tool to monitor tumor evolution, thus improving the clinical management of BC patients

Changes in total plasma and serum N-glycome composition and patient-controlled analgesia after major abdominal surgery

Systemic inflammation participates to the complex healing process occurring after major surgery, thus directly affecting the surgical outcome and patient recovery. Total plasma N-glycome might be an indicator of inflammation after major surgery, as well as an anti-inflammatory therapy response marker, since protein glycosylation plays an essential role in the inflammatory cascade. Therefore, we assessed the effects of surgery on the total plasma N-glycome and the association with self-administration of postoperative morphine in two cohorts of patients that underwent major abdominal surgery. We found that plasma N-glycome undergoes significant changes one day after surgery and intensifies one day later, thus indicating a systemic physiological response. In particular, we observed the increase of bisialylated biantennary glycan, A2G2S[3,6]2, 12 hours after surgery, which progressively increased until 48 postoperative hours. Most changes occurred 24 hours after surgery with the decrease of most core-fucosylated biantennary structures, as well as the increase in sialylated tetraantennary and FA3G3S[3,3,3]3 structures. Moreover, we observed a progressive increase of sialylated triantennary and tetraantennary structures two days after surgery, with a concomitant decrease of the structures containing bisecting N-acetylglucosamine along with bi- and trisialylated triantennary glycans. We did not find any statistically significant association between morphine consumption and plasma N-glycome

Markers of Tissue Deterioration and Pain on Earth and in Space

Madalina Patron,1,2,&ast; Mattias Neset,1,2,&ast; Mariia Mielkozorova,2,&ast; Daniel G Bisson,1,3,&ast; Marie Vigouroux,4 Juan Pablo Cata,5,6 Pablo M Ingelmo,4,7,8 Jean A Ouellet,1,3 Lisbet Haglund,1,3,&ast; Svetlana V Komarova1,2,&ast; 1Shriners Hospital for Children, Montreal, Canada; 2Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Canada; 3Orthopaedic Research Laboratory, Department of Surgery, McGill University, Montreal, Canada; 4Edwards Family Interdisciplinary Center for Complex Pain, Montreal Children’s Hospital, Montreal, QC, Canada; 5Department of Anesthesia and Perioperative Medicine, The University of Texas – MD Anderson Cancer Center, Houston, TX, USA; 6Anesthesiology and Surgical Oncology Research Group, Houston, TX, USA; 7Alan Edwards Centre for Research on Pain, McGill University, Montreal, QC, Canada; 8Research Institute, McGill University Health Center, Montreal, Canada&ast;These authors contributed equally to this workCorrespondence: Svetlana V Komarova, Shriners Hospital for Children, 1003 Decarie Boulevard, Montreal, Quebec, H4A 0A9, Canada, Tel +1 514 282-7153, Email [email protected]: Pain is an understudied physiological effect of spaceflight. Changes in inflammatory and tissue degradation markers are often associated with painful conditions. Our aim was to evaluate the changes in markers associated with tissue deterioration after a short-term spaceflight.Patients and Methods: Plasma levels of markers for systemic inflammation and tissue degeneration markers were assessed in two astronauts before and within 24 h after the 17-day Axiom Space AX-1 mission.Results: After the spaceflight, C-reactive protein (CRP) was reduced in both astronauts, while INFγ, GM-CSF, TNFα, BDNF, and all measured interleukins were consistently increased. Chemokines demonstrated variable changes, with consistent positive changes in CCL3, 4, 8, 22 and CXCL8, 9, 10, and consistent negative change in CCL8. Markers associated with tissue degradation and bone turnover demonstrated consistent increases in MMP1, MMP13, NTX and OPG, and consistent decreases in MMP3 and MMP9.Conclusion: Spaceflight induced changes in the markers of systemic inflammation, tissue deterioration, and bone resorption in two astronauts after a short, 17-day, which were often consistent with those observed in painful conditions on Earth. However, some differences, such as a consistent decrease in CRP, were noted. All records for the effect of space travel on human health are critical for improving our understanding of the effect of this unique environment on humans.Keywords: spaceflight, astronaut, cytokine, interleukin, chemokine, bone turnove