Proteomic Studies on the Management of High-Grade Serous Ovarian Cancer Patients: A Mini-Review

Teixit cancerígen; Càncer d'ovaris; ProteòmicaTejido canceroso; Cáncer de ovarios; ProteómicaCancer tissue; Ovarian cancer; ProteomicsHigh-grade serous ovarian cancer (HGSC) remains the most common and deadly subtype of ovarian cancer. It is characterized by its late diagnosis and frequent relapse despite standardized treatment with cytoreductive surgery and platinum-based chemotherapy. The past decade has seen significant advances in the clinical management and molecular understanding of HGSC following the publication of the Cancer Genome Atlas (TCGA) researchers and the introduction of targeted therapies with anti-angiogenic drugs and poly(ADP-ribose) polymerase inhibitors in specific subgroups of patients. We provide a comprehensive review of HGSC, focusing on the most important molecular advances aimed at providing a better understanding of the disease and its response to treatment. We emphasize the role that proteomic technologies are now playing in these two aspects of the disease, through the identification of proteins and their post-translational modifications in ovarian cancer tumors. Finally, we highlight how the integration of proteomics with genomics, exemplified by the work performed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), can guide the development of new biomarkers and therapeutic targets.This work was supported by the PhD4MD collaborative research program between the Vall d’Hebron Research Institute (VHIR) and the Centre for Genomic Regulation (CRG). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by grant PT17/0019 of the PE I + D + i 2013–2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science and Innovation (CTQ2016-80364-P) and “Centro de Excelencia Severo Ochoa 2013–2017”, SEV-2012-0208; the “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2017SGR595 and 2017SGR1661), from the Instituto de Salud Carlos III (PI15/02238, PI18/01017, CPII18/00027) and from the Ministerio de Economia y Competitividad y Fondos FEDER (RTC-2015-3821). We also acknowledge the support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme/Generalitat de Catalunya

BRCA1 mutations in high-grade serous ovarian cancer are associated with proteomic changes in DNA repair, splicing, transcription regulation and signaling

Ovarian cancer; ProteomicsCáncer de ovarios: ProteómicaCàncer d'ovaris; ProteòmicaDespite recent advances in the management of BRCA1 mutated high-grade serous ovarian cancer (HGSC), the physiology of these tumors remains poorly understood. Here we provide a comprehensive molecular understanding of the signaling processes that drive HGSC pathogenesis with the addition of valuable ubiquitination profiling, and their dependency on BRCA1 mutation-state directly in patient-derived tissues. Using a multilayered proteomic approach, we show the tight coordination between the ubiquitination and phosphorylation regulatory layers and their role in key cellular processes related to BRCA1-dependent HGSC pathogenesis. In addition, we identify key bridging proteins, kinase activity, and post-translational modifications responsible for molding distinct cancer phenotypes, thus providing new opportunities for therapeutic intervention, and ultimately advance towards a more personalized patient care.This work was supported by the PhD4MD collaborative research program between the Vall d’Hebron Research Institute (VHIR) and the Centre for Genomic Regulation (CRG). The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is a member of the ProteoRed PRB3 consortium which is supported by grant PT17/0019 of the PE I+D+i 2013-2016 from the Instituto de Salud Carlos III (ISCIII) and ERDF. We acknowledge support from the Spanish Ministry of Science, Innovation and Universities, (CTQ2016-80364-P and “Centro de Excelencia Severo Ochoa 2013-2017”, SEV-2012-0208), and “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2017SGR595 and 2017SGR1661). This project has also received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 823839 (EPIC-XS). It has also been supported by grants from the Instituto Carlos III (PI15/00238, PI18/01017, PI21/00977), the Miguel Servet Program (CP13/00158 and CPII18/00027) and the Ministerio de Economía y Competitividad y Fondos FEDER (RTC-2015-3821-1). The authors are grateful to the team members of the Proteomics Unit at the Centre for Genomic Regulation, the Biomedical Research Group in Gynecology at the Vall d’Hebron Institute, the Gynecological Oncology Unit at the Vall d’Hebron Hospital and the Biomedical Research Group in Urology at the Vall d’Hebron Institute for their assistance

A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management

Biomarker; Prediction; ProteomicsBiomarcador; Predicción; ProteómicaBiomarcador; Predicció; ProteòmicaBackground High-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR). Methods A total of 109 ready-available formalin-fixed paraffin-embedded HGSC tissues obtained at the time of HGSC diagnosis were selected for proteomic analysis. Clinical data, treatment approach and outcomes were collected for all patients. An initial discovery cohort (n = 21) were divided into chemoresistant and chemosensitive groups and evaluated using discovery mass-spectrometry (MS)-based proteomics. Proteins showing differential abundance between groups were verified in a verification cohort (n = 88) using targeted MS-based proteomics. A logistic regression model was used to select those proteins able to correctly classify patients into chemoresistant and chemosensitive. The classification performance of the protein and clinical data combinations were assessed through the generation of receiver operating characteristic (ROC) curves. Results Using the HGSC-1LTR strategy we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data (patients’ age, menopausal status, serum CA125 levels, and treatment approach) is able to predict patient response to first-line treatment with an AUC: 0.82 (95% CI 0.72–0.92). Conclusions We have established a new strategy that combines molecular and clinical parameters to predict the response to first-line treatment in HGSC patients (HGSC-1LTR). This strategy can allow the identification of chemoresistance at the time of diagnosis providing the optimization of therapeutic decision making and the evaluation of alternative treatment strategies. Thus, advancing towards the improvement of patient outcome and the individualization of HGSC patients’ care.This work was supported by the PhD4MD collaborative research program between the Vall d’Hebron Research Institute (VHIR) and the Centre for Genomic Regulation (CRG). It has been supported by grants from the Instituto Carlos III (PI18/01017), the Miguel Servet Program (CPII18/00027) and the Ministerio de Economía y Competitividad y Fondos FEDER (RTC-2015-3821-1 to AS and CTQ2016-80364-P to ES). This project has also received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 823839 (EPIC-XS).The CRG/UPF Proteomics Unit is part of the Spanish Infrastructure for Omics Technologies (ICTS OmicsTech) and it is supported by “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya” (2017SGR595 and 2017SGR1661). We also acknowledge support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme / Generalitat de Catalunya

Comparative Analysis of PSA Density and an MRI-Based Predictive Model to Improve the Selection of Candidates for Prostate Biopsy

Clinically significant prostate cancer; Predictive model; Prostate-specific antigenCàncer de pròstata clínicament significatiu; Model predictiu; Antigen específic de la pròstataCáncer de próstata clínicamente significativo; Modelo predictivo; Antígeno específico de la próstataThis study is a head-to-head comparison between mPSAD and MRI-PMbdex. The MRI-PMbdex was created from 2432 men with suspected PCa; this cohort comprised the development and external validation cohorts of the Barcelona MRI predictive model. Pre-biopsy 3-Tesla multiparametric MRI (mpMRI) and 2 to 4-core transrectal ultrasound (TRUS)-guided biopsies for suspicious lesions and/or 12-core TRUS systematic biopsies were scheduled. Clinically significant PCa (csPCa), defined as Gleason-based Grade Group 2 or higher, was detected in 934 men (38.4%). The area under the curve was 0.893 (95% confidence interval [CI]: 0.880–0.906) for MRI-PMbdex and 0.764 (95% CI: 0.774–0.783) for mPSAD, with p < 0.001. MRI-PMbdex showed net benefit over biopsy in all men when the probability of csPCa was greater than 2%, while mPSAD did the same when the probability of csPCa was greater than 18%. Thresholds of 13.5% for MRI-PMbdex and 0.628 ng/mL2 for mPSAD had 95% sensitivity for csPCa and presented 51.1% specificity for MRI-PMbdex and 19.6% specificity for mPSAD, with p < 0.001. MRI-PMbdex exhibited net benefit over mPSAD in men with prostate imaging report and data system (PI-RADS) <4, while neither exhibited any benefit in men with PI-RADS 5. Hence, we can conclude that MRI-PMbdex is more accurate than mPSAD for the proper selection of candidates for prostate biopsy among men with suspected PCa, with the exception of men with a PI-RAD S 5 score, for whom neither tool exhibited clinical guidance to determine the need for biopsy.This research was funded by Instituto de Salut Carlos III (ESP), grant number PI20/01666

Who with suspected prostate cancer can benefit from Proclarix after multiparametric magnetic resonance imaging?

Cathepsin D; Magnetic resonance imaging; ProclarixCatepsina D; Imatges per ressonància magnètica; ProclarixCatepsina D; Imágenes por resonancia magnética; ProclarixProclarix is a new blood-based test to assess the likelihood of clinically significant prostate cancer (csPCa) defined as >2 grade group. In this study, we analyzed whether Proclarix and PSA density (PSAD) could improve the selection of candidates for prostate biopsy after multiparametric magnetic resonance imaging (mpMRI). Proclarix and PSAD were assessed in 567 consecutive men with suspected PCa in whom pre-biopsy 3 Tesla mpMRI, scoring with Prostate Imaging-Report and Data System (PI-RADS) v.2, and guided and/or systematic biopsies were performed. Proclarix and PSAD thresholds having csPCa sensitivity over 90% were found at 10% and 0.07 ng/(mL*cm3), respectively. Among 100 men with negative mpMRI (PI-RADS <3), csPCa was detected in 6 cases, which would have been undetected if systematic biopsies were avoided. However, Proclarix suggested performing a biopsy on 70% of men with negative mpMRI. In contrast, PSAD only detected 50% of csPCa and required 71% of prostate biopsies. In 169 men with PI-RADS 3, Proclarix avoided 21.3% of prostate biopsies and detected all 25 cases of csPCa, while PSAD avoided 26.3% of biopsies, but missed 16% of csPCa. In 190 men with PI-RADS 4 and 108 with PI-RADS 5, Proclarix avoided 12.1% and 5.6% of prostate biopsies, but missed 4.8% and 1% of csPCa, respectively. PSAD avoided 18.4% and 9.3% of biopsies, but missed 11.4% and 4.2% csPCa, respectively. We conclude that Proclarix outperformed PSAD in the selection of candidates for prostate biopsy, especially in men with PI-RADS <3.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Instituto de Salud Carlos III, (grant number PI20/01666)

The Efficacy of Proclarix to Select Appropriate Candidates for Magnetic Resonance Imaging and Derived Prostate Biopsies in Men with Suspected Prostate Cancer

Diagnosis; Proclarix; Prostate cancerDiagnóstico; Proclarix; Cáncer de próstataDiagnòstic; Proclarix; Càncer de pròstataPurpose To analyze how Proclarix is valuable to appropriately select candidates for multiparametric magnetic resonance imaging (mpMRI) and derived biopsies, among men with suspected prostate cancer (PCa). Proclarix is a new marker computing the clinically significant PCa (csPCa) risk, based on serum thosmbospondin-1, cathepsin D, prostate-specific antigen (PSA) and percent free PSA, in addition to age, that has been developed in men with serum PSA 2 to 10 ng/mL, prostate volume ≥35 mL, and normal digital rectal examination (DRE). Materials and Methods Proclarix score (0%–100%) is analyzed in a prospective frozen serum collection of 517 correlative men scheduled for guided and/or systematic biopsies after mpMRI. Outcome variables were csPCa detection (grade group ≥2), insignificant PCa (iPCa) overdetection and avoided mpMRIs. Results The area under the curve of Proclarix was 0.701 (95% CI 0.637–0.765) among 281 men with serum PSA 2 to 10 ng/mL, prostate volume ≥35 mL, and -normal DRE, and 0.754 (95% CI 0.701–0.807) in the others, p=0.038. Net benefit of Proclarix existed in all men. After selecting 10% threshold, Proclarix was integrated in an algorithm which also used the serum PSA level and DRE. A reduction of 25.4% of mpMRIs request was observed and 17.7% of prostate biopsies. Overdetection of iPCa was reduced in 18.2% and 2.6% of csPCa were misdiagnosed. Conclusions Proclarix is valuable in all men with suspected PCa. An algorithm integrating Proclarix score, serum PSA, and DRE can avoid mpMRI requests, unnecessary prostate biopsies and iPCa overdetection, with minimal loss of csPCa detection

Improving the Early Detection of Clinically Significant Prostate Cancer in Men in the Challenging Prostate Imaging-Reporting and Data System 3 Category

Clinically significant prostate cancer; Prostate Cancer predictive model; Multiparametric magnetic resonance imagingCáncer de próstata clínicamente significativo; Modelo predictivo de cáncer de próstata; Resonancia magnética multiparamétricaCàncer de pròstata clínicament significatiu; Model predictiu del càncer de pròstata; Imatge de ressonància magnètica multiparamètricaBackground Prostate Imaging-Reporting and Data System (PI-RADS) category 3 is a challenging scenario for detection of clinically significant prostate cancer (csPCa) and some tools can improve the selection of appropriate candidates for prostate biopsy. Objective To assess the performance of the European Randomized Study of Screening for Prostate Cancer (ERSPC) magnetic resonance imaging (MRI) model, the new Proclarix test, and prostate-specific antigen density (PSAD) in selecting candidates for prostate biopsy among men in the PI-RADS 3 category. Design, setting, and participants We conducted a head-to-head prospective analysis of 567 men suspected of having PCa for whom guided and systematic biopsies were scheduled between January 2018 and March 2020 in a single academic institution. A PI-RADS v.2 category 3 lesion was identified in 169 men (29.8%). Outcome measurement and statistical analysis csPCa, insignificant PCa (iPCa), and unnecessary biopsy rates were analysed. csPCa was defined as grade group ≥2. Receiver operating characteristic (ROC) curves, decision curve analysis curves, and clinical utility curves were plotted. Results and limitations PCa was detected in 53/169 men (31.4%) with a PI-RADS 3 lesion, identified as csPCa in 25 (14.8%) and iPCa in 28 (16.6%). The area under the ROC curve for csPCa detection was 0.703 (95% confidence interval [CI] 0.621–0.768) for Proclarix, 0.657 (95% CI 0.547–0.766) for the ERSPC MRI model, and 0.612 (95% CI 0.497–0.727) for PSAD (p = 0.027). The threshold with the highest sensitivity was 10% for Proclarix, 1.5% for the ERSPC MRI model, and 0.07 ng/ml/cm3 for PSAD, which yielded sensitivity of 100%, 91%, and 84%, respectively. Some 21.3%, 26.2%, and 7.1% of biopsies would be avoided with Proclarix, PSAD, and the ERSPC MRI model, respectively. Proclarix showed a net benefit over PSAD and the ERSPC MRI model. Both Proclarix and PSAD reduced iPCa overdetection from 16.6% to 11.3%, while the ERSPC MRI model reduced iPCa overdetection to 15.4%. Conclusions Proclarix was more accurate in selecting appropriate candidates for prostate biopsy among men in the PI-RADS 3 category when compared to PSAD and the ERSPC MRI model. Proclarix detected 100% of csPCa cases and would reduce prostate biopsies by 21.3% and iPCa overdetection by 5.3%

Comparison of Proclarix, PSA Density and MRI-ERSPC Risk Calculator to Select Patients for Prostate Biopsy after mpMRI

Proclarix; Clinically significant prostate cancer; Magnetic resonance imagingProclarix; Càncer de pròstata clínicament significatiu; Imatges per ressonància magnèticaProclarix; Cáncer de próstata clínicamente significativo; Imágenes por resonancia magnéticaTools to properly select candidates for prostate biopsy after magnetic resonance imaging (MRI) have usually been analyzed in overall populations with suspected prostate cancer (PCa). However, the performance of these tools can change regarding the Prostate Imaging-Reporting and Data System (PI-RADS) categories due to the different incidence of clinically significant PCa (csPCa). The objective of the study was to analyze PSA density (PSAD), MRI-ERSPC risk calculator (RC), and Proclarix to properly select candidates for prostate biopsy regarding PI-RADS categories. We performed a head-to-head analysis of 567 men with suspected PCa, PSA > 3 ng/mL and/or abnormal rectal examination, in whom two to four core transrectal ultrasound (TRUS) guided biopsies to PI-RADS ≥ three lesions and/or 12-core TRUS systematic biopsies were performed after 3-tesla mpMRI between January 2018 and March 2020 in one academic institution. The overall detection of csPCa was 40.9% (6% in PI-RADS 3, although none of them exhibited 100% sensitivity for csPCa in this setting. Therefore, tools to properly select candidates for prostate biopsy after MRI must be analyzed regarding the PI-RADS categories. While MRI-ERSPC RC outperformed PSAD and Proclarix in the overall population, Proclarix outperformed in PI-RADS ≤ 3, and no tool guaranteed 100% detection of csPCa in PI-RADS 4 and 5

Overcoming Paradoxical Kinase Priming by a Novel MNK1 Inhibitor

Inhibidor de MNK1; OncologíaInhibidor de MNK1; OncologiaMNK1 inhibitor; OncologyTargeting the kinases MNK1 and MNK2 has emerged as a valuable strategy in oncology. However, most of the advanced inhibitors are acting in an adenosine triphosphate (ATP)-competitive mode, precluding the evaluation of different binding modes in preclinical settings. Using rational design, we identified and validated the 4,6-diaryl-pyrazolo[3,4-b]pyridin-3-amine scaffold as the core for MNK inhibitors. Signaling pathway analysis confirmed a direct effect of the hit compound EB1 on MNKs, and in line with the reported function of these kinases, EB1 only affects the growth of tumor but not normal cells. Molecular modeling revealed the binding of EB1 to the inactive conformation of MNK1 and the interaction with the specific DFD motif. This novel mode of action appears to be superior to the ATP-competitive inhibitors, which render the protein in a pseudo-active state. Overcoming this paradoxical activation of MNKs by EB1 represents therefore a promising starting point for the development of a novel generation of MNK inhibitors.This work was supported by the Instituto de Salud Carlos III (PI17/02247), (PI20/01687), and CIBERONC (CB16/12/00363). S.R.y.C. acknowledges support from the Generalitat de Catalunya (2017-9015-385045). E. Bou-Petit thanks the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya (2017 FI_B2 00139) and the European Social Funds for her predoctoral fellowship

Multiparametric Magnetic Resonance Imaging Grades the Aggressiveness of Prostate Cancer

Aggressiveness; Magnetic resonance imaging; Prostate cancerAgresividad; Imágenes por resonancia magnética; Cáncer de próstataAgressivitat; Imatges per ressonància magnètica; Càncer de pròstataWe sought to find further evidence showing the increase in PCa aggressiveness as PI-RADS score increases from four surrogates of PCa aggressiveness: i. prostate biopsy GG (≤3 vs. >3), ii. type of pathology in surgical specimens (favourable vs. unfavourable), iii. clinical stage (localised vs. advanced), and risk of recurrence of localised PCa after primary treatment (low-intermediate vs. high). A group of 692 PCa patients were diagnosed after 3-T multiparametric MRI (mpMRI) and guided and/or systematic biopsies, showing csPCa (GG ≥ 2) in 547 patients (79%) and insignificant PCa (iPCa) in 145 (21%). The csPCa rate increased from 32.4% in PI-RADS 3 (p 3 (p = 0.030). Advanced disease was not observed in PCa with PI-RADS ≤ 3, while it existed in 12.7% of those with PI-RADS > 3 (p 3 (p = 0.001). The PI-RADS score was an independent predictor of all surrogates of PCa aggressiveness as PSA density. We confirmed that mpMRI grades PCa aggressiveness.This research was funded by Instituto de Salut Carlos III (ES) grant number PI20/01666