Grading Evolution and Contemporary Prognostic Biomarkers of Clinically Significant Prostate Cancer

Sopyllo, Konrad; Erickson, Andrew; Mirtti, Tuomas

doi:10.3390/cancers13040628

Cited by 7 publications

(7 citation statements)

References 107 publications

(118 reference statements)

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“…Cancer is a complex and heterogeneous disease, rarely detected at its initial stages [1] . Current methods rely on biomarker panels that contain several genes rather than a single specific biomarker to quickly and accurately detect cancers [2] , [3] , [4] . The advent of high-throughput technologies, such as whole/targeted exome sequencing, whole-genome sequencing, large-scale RNA sequencing, and chromatin immunoprecipitation followed by sequencing (ChIP-Seq) and mass spectrometry-based proteomics, has accelerated cancer research and has resulted in a large volume of publicly available data.…”

Section: Introductionmentioning

confidence: 99%

UALCAN: An update to the integrated cancer data analysis platform

et al. 2022

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Cancer genomic, transcriptomic, and proteomic profiling has generated extensive data that necessitate the development of tools for its analysis and dissemination. We developed UALCAN to provide a portal for easy exploring, analyzing, and visualizing these data, allowing users to integrate the data to better understand the gene, proteins, and pathways perturbed in cancer and make discoveries. UALCAN web portal enables analyzing and delivering cancer transcriptome, proteomics, and patient survival data to the cancer research community. With data obtained from The Cancer Genome Atlas (TCGA) project, UALCAN has enabled users to evaluate protein-coding gene expression and its impact on patient survival across 33 types of cancers. The web portal has been used extensively since its release and received immense popularity, underlined by its usage from cancer researchers in more than 100 countries. The present manuscript highlights the task we have undertaken and updates that we have made to UALCAN since its release in 2017. Extensive user feedback motivated us to expand the resource by including data on a) microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and promoter DNA methylation from TCGA and b) mass spectrometry-based proteomics from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). UALCAN provides easy access to pre-computed, tumor subgroup-based gene/protein expression, promoter DNA methylation status, and Kaplan-Meier survival analyses. It also provides new visualization features to comprehend and integrate observations and aids in generating hypotheses for testing. UALCAN is accessible at http://ualcan.path.uab.edu

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Section: Introductionmentioning

confidence: 99%

UALCAN: An update to the integrated cancer data analysis platform

et al. 2022

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“…In our study, the results showed that PSA level at diagnosis was not statistically related to CCMCCs expression. Gleason grade was another important biomarker in PC ( Sopyllo, Erickson & Mirtti, 2021 ; Moris et al, 2020 ). Recently, a meta-analysis found that Gleason grade was positively associated with recurrence after surgery ( John et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Prognostic values of the core components of the mammalian circadian clock in prostate cancer

Yue

Wang

et al. 2021

PeerJ

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Background Prostate cancer (PC) is one of the most common malignancies in males. Extensive and complex connections between circadian rhythm and cancer were found. Nonetheless, in PC, the potential role of the core components of the mammalian circadian clock (CCMCCs) in prognosis prediction has not been fully clarified. Methods We firstly collected 605 patients with PC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Survival analysis was carried out for each CCMCC. Then, we investigated the prognostic ability of CCMCCs by Cox regression analysis. Independent prognostic signatures were extracted for the establishment of the circadian clock-based risk score model. We explored the predictive performance of the risk score model in the TCGA training cohort and the independent GEO dataset. Finally, the relationships between risk score and clinicopathological parameters, biological processes, and signaling pathways were evaluated. Results The expression levels of CCMCCs were widely correlated with age, tumor status, lymph node status, disease-free survival (DFS), progression-free survival (PFS), and overall survival (OS). Nine circadian clock genes, including CSNK1D, BTRC, CLOCK, CSNK1E, FBXL3, PRKAA2, DBP, NR1D2, and RORB, were identified as vital prognostic factors in PC and were used to construct the circadian clock-based risk score model. For DFS, the area under the 3-year or 5-year receiver operating characteristic curves ranged from 0.728 to 0.821, suggesting better predictive performance. When compared with T3-4N1 stage, PC patients at T2N0 stage might be benefited more from the circadian clock-based risk score model. Furthermore, a high circadian clock-based risk score indicated shorter DFS (p < 0.0001), early progression (p < 0.0001), and higher 5-year death rate (p = 0.007) in PC. The risk score was related to tumor status (p < 0.001), lymph node status (p < 0.001), and ribosome-related biogenesis and pathways. Conclusions The vital roles of circadian clock genes in clinical outcomes were fully depicted. The circadian clock-based risk score model could reflect and predict the prognosis of patients with PC.

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“…Targeted and systematic cores were fixed, paraffin-embedded, and analyzed separately under the supervision of a dedicated uropathologist (AS) according to ISUP (International Society of Urological Pathology) standards [ 22 , 23 ]. sPC was defined as Gleason score (GS) ≥3+4.…”

Section: Methodsmentioning

confidence: 99%

Impact of Surgeon’s Experience in Rigid versus Elastic MRI/TRUS-Fusion Biopsy to Detect Significant Prostate Cancer Using Targeted and Systematic Cores

Görtz

Nyarangi‐Dix

Pursche

et al. 2022

Cancers

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Multiparametric magnetic resonance imaging (mpMRI) and MRI/ultrasound fusion-targeted prostate biopsy (FB) have excellent sensitivity in detecting significant prostate cancer (sPC). FB platforms can be distinguished by rigid (RTB) or elastic image registration (ETB). We compared RTB and ETB by analyzing sPC detection rates of both RTB and ETB at different stages of the surgeons’ learning curve. Patients undergoing RTB between 2015–2017 (n = 502) were compared to patients undergoing ETB from 2017–2019 (n = 437). SPC detection rates were compared by Chi-square-test on patient-basis. Combination of transperineal systematic biopsy and each TB served as reference and sub-analyses were performed for different grades of surgeon’s experience. In the RTB subgroup, 233 men (46%) had sPC, compared to 201 (46%) in the ETB subgroup. RTB alone detected 94% of men with sPC and ETB 87% (p = 0.02). However, for at least intermediate-experienced surgeons (>100 FB), no differences occurred between RTB and ETB. In the total cohort, at least intermediate-experienced surgeons detected significantly more sPC (10%, p = 0.008) than novices. Thus, targeted transperineal MRI/TRUS-FB with a RTB registration system showed a similar sPC detection rate to ETB in experienced surgeons but a superior sPC detection rate to ETB in the total cohort. Low-experienced surgeons seem to benefit from RTB.

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Grading Evolution and Contemporary Prognostic Biomarkers of Clinically Significant Prostate Cancer

Cited by 7 publications

References 107 publications

UALCAN: An update to the integrated cancer data analysis platform

UALCAN: An update to the integrated cancer data analysis platform

Prognostic values of the core components of the mammalian circadian clock in prostate cancer

Impact of Surgeon’s Experience in Rigid versus Elastic MRI/TRUS-Fusion Biopsy to Detect Significant Prostate Cancer Using Targeted and Systematic Cores

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