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The recommended treatment for patients with high-risk non–muscle-invasive bladder cancer (HR-NMIBC) is tumor resection followed by adjuvant Bacillus Calmette-Guérin (BCG) bladder instillations. However, only 50% of patients benefit from this therapy. If progression to advanced disease occurs, then patients must undergo a radical cystectomy with risks of substantial morbidity and poor clinical outcome. Identifying tumors unlikely to respond to BCG can translate into alternative treatments, such as early radical cystectomy, targeted therapies, or immunotherapies. Here, we conducted molecular profiling of 132 patients with BCG-naive HR-NMIBC and 44 patients with recurrences after BCG (34 matched), which uncovered three distinct BCG response subtypes (BRS1, 2 and BRS3). Patients with BRS3 tumors had a reduced recurrence-free and progression-free survival compared with BRS1/2. BRS3 tumors expressed high epithelial-to-mesenchymal transition and basal markers and had an immunosuppressive profile, which was confirmed with spatial proteomics. Tumors that recurred after BCG were enriched for BRS3. BRS stratification was validated in a second cohort of 151 BCG-naive patients with HR-NMIBC, and the molecular subtypes outperformed guideline-recommended risk stratification based on clinicopathological variables. For clinical application, we confirmed that a commercially approved assay was able to predict BRS3 tumors with an area under the curve of 0.87. These BCG response subtypes will allow for improved identification of patients with HR-NMIBC at the highest risk of progression and have the potential to be used to select more appropriate treatments for patients unlikely to respond to BCG.

Supplementary Figure from Ovarian Cancers with Low CIP2A Tumor Expression Constitute an APR-246–Sensitive Disease Subtype

Identification of ovarian cancer patient subpopulations with increased sensitivity to targeted therapies could offer significant clinical benefit. We report that 22% of the high-grade ovarian cancer tumors at diagnosis express CIP2A oncoprotein at low levels. Furthermore, regardless of their significantly lower likelihood of disease relapse after standard chemotherapy, a portion of relapsed tumors retain their CIP2A-deficient phenotype. Through a screen for therapeutics that would preferentially kill CIP2A-deficient ovarian cancer cells, we identified reactive oxygen species inducer APR-246, tested previously in ovarian cancer clinical trials. Consistent with CIP2A-deficient ovarian cancer subtype in humans, CIP2A is dispensable for development of MISIIR-Tag–driven mouse ovarian cancer tumors. Nevertheless, CIP2A-null ovarian cancer tumor cells from MISIIR-Tag mice displayed APR-246 hypersensitivity both in vitro and in vivo. Mechanistically, the lack of CIP2A expression hypersensitizes the ovarian cancer cells to APR-246 by inhibition of NF-κB activity. Accordingly, combination of APR-246 and NF-κB inhibitor compounds strongly synergized in killing of CIP2A-positive ovarian cancer cells. Collectively, the results warrant consideration of clinical testing of APR-246 for CIP2A-deficient ovarian cancer tumor subtype patients. Results also reveal CIP2A as a candidate APR-246 combination therapy target for ovarian cancer.

Supplementary Table from Ovarian Cancers with Low CIP2A Tumor Expression Constitute an APR-246–Sensitive Disease Subtype

Supplementary Data from Ovarian Cancers with Low CIP2A Tumor Expression Constitute an APR-246–Sensitive Disease Subtype

PDF file, 134K, Model covariates and results from simulation experiment and probabilistic categorization.

PDF file, 933K, Full model formulation and details of its estimation, inference and validation.

PDF file, 1943K, Data on real and simulated tumor growth experiments and power and precision analyses.

Purpose: Preclinical tumor growth experiments often result in heterogeneous datasets that include growing, regressing, or stable growth profiles in the treatment and control groups. Such confounding intertumor variability may mask the true treatment effects especially when less aggressive treatment alternatives are being evaluated.Experimental design: We developed a statistical modeling approach in which the growing and poorly growing tumor categories were automatically detected by means of an expectation-maximization algorithm coupled within a mixed-effects modeling framework. The framework is implemented and distributed as an R package, which enables model estimation and statistical inference, as well as statistical power and precision analyses.Results: When applied to four tumor growth experiments, the modeling framework was shown to (i) improve the detection of subtle treatment effects in the presence of high within-group tumor variability; (ii) reveal hidden tumor subgroups associated with established or novel biomarkers, such as ERβ expression in a MCF-7 breast cancer model, which remained undetected with standard statistical analysis; (iii) provide guidance on the selection of sufficient sample sizes and most informative treatment periods; and (iv) offer flexibility to various cancer models, experimental designs, and treatment options. Model-based testing of treatment effect on the tumor growth rate (or slope) was shown as particularly informative in the preclinical assessment of treatment alternatives based on dietary interventions.Conclusions: In general, the modeling framework enables identification of such biologically significant differences in tumor growth profiles that would have gone undetected or had required considerably higher number of animals when using traditional statistical methods. Clin Cancer Res; 18(16); 4385–96. ©2012 AACR.

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or unstandardized. Here, we present thecuratedPCaDataR package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights.curatedPCaDatais an open and accessible community resource with code made available for reproducibility.

Background: Antibiotic treatment may reduce the efficacy of cancer immunotherapy by disrupting gut microbiome. We aimed to study the association of antibiotics and survival outcomes in advanced cutaneous melanoma and non–small-cell lung cancer (NSCLC) patients who had received anti-PD-1/L1 monotherapy. Patients and Methods: A total of 222 melanoma and 199 NSCLC patients had received anti-PD-1/L1 monotherapy in 5 Finnish hospitals between January 2014 and December 2020. Clinical characteristics, antibiotic and corticosteroid treatment, and survival outcomes were retrospectively collected from hospital and national medical records. Results: There were 32% of melanoma and 31% of NSCLC patients who had received antibiotic treatment (ABT) 3 months before to 1 month after the first anti-PD-1/L1 antibody infusion. In survival analyses, early antibiotic treatment was associated with inferior overall survival (OS) (ABT 19.2 [17.6-43.7] vs. no ABT 35.6 [29.3-NA] months, P = .033) but not with inferior progression-free survival (PFS) (ABT 5.8 [3.0-12.6] vs. no ABT 10.2 [7.7-15.3] months, P = .3) in melanoma patients and with inferior OS (ABT 8.6 [6.4-12.3] vs. no ABT 18.5 [15.1-21.6] months, P < .001) and PFS (ABT 2.8 [2.1-4.5] vs. no ABT 5.6 [4.4-8.0] months, P = .0081) in NSCLC patients. In multivariable analyses, ABT was not an independent risk-factor for inferior OS and PFS in melanoma but was associated with inferior OS (hazard ratio [HR] 2.12 [1.37-3.28]) and PFS (HR 1.65 [1.10-2.47]) in NSCLC after adjusted for other risk factors. Conclusions: Early ABT was an independent poor risk factor in NSCLC patients who had received anti-PD-1/L1 monotherapy but not in melanoma patients. The weight of ABT as a poor risk factor might depend on other prognostic factors in different cancers. publishedVersion

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti–PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC.MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials.ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression–based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1.ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy.Context summaryKey objectiveNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC.Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response.Relevance

PurposeThis study investigates how game design, which divides players into static teams, can reinforce group polarisation. The authors study this phenomenon from the perspective of social identity in the context of team-based location-based games, with a focus on game slang.Design/methodology/approachThe authors performed an exploratory data analysis on an original dataset of n = 242,852 messages from five communication channels to find differences in game slang adoption between three teams in the location-based augmented reality game Pokémon GO. A divisive word “jym” (i.e. a Finnish slang derivative of the word “gym”) was discovered, and players' attitudes towards the word were further probed with a survey (n = 185). Finally, selected participants (n = 25) were interviewed in person to discover any underlying reasons for the observed polarised attitudes.FindingsThe players' teams were correlated with attitudes towards “jym”. Face-to-face interviews revealed association of the word to a particular player subgroup and it being used with improper grammar as reasons for the observed negative attitudes. Conflict over (virtual) territorial resources reinforced the polarisation.Practical implicationsGame design with static teams and inter-team conflict influences players' social and linguistic identity, which subsequently may result in divisive stratification among otherwise cooperative or friendly player-base.Originality/valueThe presented multi-method study connecting linguistic and social stratification is a novel approach to gaining insight on human social interactions, polarisation and group behaviour in the context of location-based games.

SummaryThe recommended treatment for patients with high-risk non-muscle invasive bladder cancer (HR-NMIBC) is tumor resection followed by adjuvant Bacillus Calmette-Guérin (BCG) bladder instillations. However, only 50% of patients benefit from this therapy. In case of progression to advanced disease, patients must undergo a radical cystectomy with significant morbidity and have a poor clinical outcome. Identifying tumors least likely to respond to BCG can translate into alternative treatments, such as early radical cystectomy or novel targeted or immunotherapies. Here we present molecular profiling of 132 BCG-naive, HR-NMIBC patients, and 44 post-BCG recurrences (34 matched), which uncovered three distinct BCG Response Subtypes (BRS1-3). Patients with BRS3 tumors have reduced recurrence and progression-free survival compared to BRS1-2. BRS3 tumors expressed high EMT-basal markers and had an immunosuppresive profile, which was confirmed with spatial proteomics. Tumors which recurred post-BCG were enriched for BRS3. BRS stratification was validated in a second cohort of 151 BCG-naive HR-NMIBC patients and the molecular subtypes outperformed guideline recommended risk stratification based on clinicopathological variables. For clinical application, we validated that a commercially approved assay was able to accurately predict BRS3 tumors (AUROC 0.86). Our findings provide a potential clinical tool for improved identification of HR-NMIBC patients at the highest risk of progression, which can be used to select patients for early radical cystectomy or novel subtype-directed therapies.One Sentence SummaryMolecular subtypes are predictive of response to intravesical Bacillus Calmette-Guérin immunotherapy in non-muscle invasive bladder cancer.

Background The cancer antigen 125 (CA125) immunoassay (IA) does not distinguish epithelial ovarian cancer (EOC) from benign disease with the sensitivity needed in clinical practice. In recent studies, glycoforms of CA125 have shown potential as biomarkers in EOC. Here, we assessed the diagnostic abilities of two recently developed CA125 glycoform assays for patients with a pelvic mass. Detailed analysis was further conducted for postmenopausal patients with marginally elevated conventionally measured CA125 levels, as this subgroup presents a diagnostic challenge in the clinical setting. Methods Our study population contained 549 patients diagnosed with EOC, benign ovarian tumors, and endometriosis. Of these, 288 patients were postmenopausal, and 98 of them presented with marginally elevated serum levels of conventionally measured CA125 at diagnosis. Preoperative serum levels of conventionally measured CA125 and its glycoforms (CA125-MGL and CA125-STn) were determined. Results The CA125-STn assay identified EOC significantly better than the conventional CA125-IA in postmenopausal patients (85% vs. 74% sensitivity at a fixed specificity of 90%, P = 0.0009). Further, both glycoform assays had superior AUCs compared to the conventional CA125-IA in postmenopausal patients with marginally elevated CA125. Importantly, the glycoform assays reduced the false positive rate of the conventional CA125-IA. Conclusions The results indicate that the CA125 glycoform assays markedly improve the performance of the conventional CA125-IA in the differential diagnosis of pelvic masses. This result is especially valuable when CA125 is marginally elevated.

Heterogeneity in tumors is recognized as a key contributor to drug resistance and spread of advanced disease, but deep characterization of genetic variation within tumors has only recently been quantifiable with the advancement of next generation sequencing and single cell technologies. These data have been essential in developing molecular models of how tumors develop, evolve, and respond to environmental changes, such as therapeutic intervention. A deeper understanding of tumor evolution has subsequently opened up new research efforts to develop mathematical models that account for evolutionary dynamics with the goal of predicting drug response and resistance in cancer. This study describes recent advances and limitations of how models of tumor evolution can impact treatment strategies for cancer patients.

INTRODUCTION AND OBJECTIVE:Intravesical Bacillus Calmette-Guerin (BCG) is the recommended treatment option in high-risk non-muscle invasive bladder cancer (HR-NMIBC). However, disease recurrence oc...

After surgery of localized renal cell carcinoma, over 20% of the patients will develop distant metastases. Our aim was to develop an easy-to-use prognostic model for predicting metastasis-free survival after radical or partial nephrectomy of localized clear cell RCC. Model training was performed on 196 patients. Right-censored metastasis-free survival was analysed using LASSO-regularized Cox regression, which identified three key prediction features. The model was validated in an external cohort of 714 patients. 55 (28%) and 134 (19%) patients developed distant metastases during the median postoperative follow-up of 6.3 years (interquartile range 3.4–8.6) and 5.4 years (4.0–7.6) in the training and validation cohort, respectively. Patients were stratified into clinically meaningful risk categories using only three features: tumor size, tumor grade and microvascular invasion, and a representative nomogram and a visual prediction surface were constructed using these features in Cox proportional hazards model. Concordance indices in the training and validation cohorts were 0.755 ± 0.029 and 0.836 ± 0.015 for our novel model, which were comparable to the C-indices of the original Leibovich prediction model (0.734 ± 0.035 and 0.848 ± 0.017, respectively). Thus, the presented model retains high accuracy while requiring only three features that are routinely collected and widely available.

Identification of ovarian cancer (OvCa) patient subpopulations with increased sensitivity to targeted therapies could offer significant clinical benefit. We report that 22% of the high grade OvCa tumors at diagnosis express CIP2A oncoprotein at low levels. CIP2Alow OvCa tumors have significantly lower likelihood of disease relapse after standard chemotherapy, but yet a portion of relapsed tumors retain their CIP2Alow phenotype. We further discover that reactive oxygen species (ROS) inducing compound APR-246 (PRIMA-1Met/Eprenetapopt), currently in clinical development, preferentially kill CIP2Alow OvCa cells across multiple chemotherapy resistant cell lines. Consistent with CIP2Alow OvCa subtype in humans, CIP2A is dispensable for development of MISIIR-TAg-driven mouse OvCa tumors. Nevertheless, CIP2A deficient OvCa tumor cells from MISIIR-TAg mice displayed APR-246 hypersensitivity both in vitro and in vivo. Mechanistically, the lack of CIP2A expression hypersensitizes the OvCa cells to APR-246 by inhibition of NF-kB activity. Accordingly, combination of APR-246 and Nf-kB inhibitor compounds strongly synergized in killing of CIP2A positive OvCa cells. Collectively, we discover low CIP2A expression as a vulnerability for APR-246 in OvCa. The results warrant consideration of clinical testing of APR-246 for CIP2Alow OvCa tumor subtype patients, and reveal CIP2A as a candidate APR-246 combination therapy target.

Despite routine platinum-based chemotherapeutic use in cancer treatment, there remains a need to improve efficacy and patient selection. Using multi-omic assessment of cisplatin responsive and resistant human bladder cancer cell lines and whole-genome CRISPR screens, we identified NPEPPS, the puromycin-sensitive aminopeptidase as a novel driver of cisplatin resistance. Volume-regulated anion channels (VRACs) have been shown to directly import the majority of intracellular cisplatin. Here, we show that the mechanism of NPEPPS-mediated cisplatin resistance is by binding to VRACs and blocking the import of cisplatin into the cell. We show that NPEPPS depletion increased intracellular cisplatin and made cisplatin-resistant cells more responsive to cisplatin in vitro and in vivo. Overexpression of NPEPPS in cisplatin-sensitive cells decreased intracellular cisplatin and resulted in increased treatment resistance. The same results also hold for carboplatin. Our findings describe the first mechanism by which VRACs can be targeted to control the import of cisplatin and carboplatin.

Active surveillance (AS) of prostate cancer (PC) has increased in popularity to address overtreatment.To determine whether a novel metric, cumulative cancer locations (CCLO), can predict AS outcomes in a group of AS patients with low and very low risk.CCLO is obtained by summing the total number of histological cancer-positive locations in both diagnostic and confirmatory biopsies (Bx). The retrospective study cohort comprised three prospective AS cohorts (Helsinki University Hospital: n=316; European Institute of Oncology: n=204; and University of Münster: n=89).We analyzed whether risk stratification based on CCLO predicts different AS outcomes: protocol-based discontinuation (PBD), Gleason upgrading (GU) during AS, and adverse findings in radical prostatectomy (RP) specimens.In Kaplan Meier analyses, patients in the CCLO high-risk group experienced significantly shorter event-free survival for all outcomes (PBD, GU, and adverse RP findings; all p0.002). In multivariable Cox regression analysis, patients in the CCLO high-risk group had a significantly higher risk of experiencing PBD (hazard ratio [HR] 12.15, 95% confidence interval [CI] 6.18-23.9; p0.001), GU (HR 6.01, 95% CI 2.16-16.8; p=0.002), and adverse RP findings (HR 9.144, 95% CI 2.27-36.9; p=0.006). In receiver operating characteristic analyses, the area under the curve for CCLO outperformed the number of cancer-positive Bxs in confirmatory Bx in predicting PBD (0.734 vs 0.682), GU (0.655 vs 0.576) and adverse RP findings (0.662 vs 0.561) and the added value was supported by decision curve analysis.CCLO is distinct from the number of positive Bx cores. Higher CCLO predicts AS outcomes and may aid in selection of patients for AS.For patients on active surveillance for prostate cancer, the cumulative number of cancer-positive locations in diagnostic and confirmatory biopsies is a predictor of active surveillance outcomes.

Aims: Low-density lipoprotein (LDL) particles cause atherosclerotic cardiovascular disease (ASCVD) through their retention, modification, and accumulation within the arterial intima. High plasma concentrations of LDL drive this disease, but LDL quality may also contribute. Here, we focused on the intrinsic propensity of LDL to aggregate upon modification. We examined whether inter-individual differences in this quality are linked with LDL lipid composition and coronary artery disease (CAD) death, and basic mechanisms for plaque growth and destabilization. Methods and results: We developed a novel, reproducible method to assess the susceptibility of LDL particles to aggregate during lipolysis induced ex vivo by human recombinant secretory sphingomyelinase. Among patients with an established CAD, we found that the presence of aggregation-prone LDL was predictive of future cardiovascular deaths, independently of conventional risk factors. Aggregation-prone LDL contained more sphingolipids and less phosphatidylcholines than did aggregation-resistant LDL. Three interventions in animal models to rationally alter LDL composition lowered its susceptibility to aggregate and slowed atherosclerosis. Similar compositional changes induced in humans by PCSK9 inhibition or healthy diet also lowered LDL aggregation susceptibility. Aggregated LDL in vitro activated macrophages and T cells, two key cell types involved in plaque progression and rupture. Conclusion: Our results identify the susceptibility of LDL to aggregate as a novel measurable and modifiable factor in the progression of human ASCVD.

Objective. In clinical practise, prognostication of endometrial cancer is based on clinicopathological risk factors. The use of immunohistochemistry-based markers as prognostic tools is generally not recommended and a systematic analysis of their utility as a panel is lacking. We evaluated whether an immunohistochemical marker panel could reliably assess endometrioid endometrial cancer (EEC) outcome independent of clinicopathological information. Methods. A cohort of 306 EEC specimens was profiled using tissue microarray (TMA). Cost- and time-efficient immunohistochemical analysis of well-established tissue biomarkers (ER, PR, HER2, Ki-67, MLH1 and p53) and two new biomarkers (L1CAM and ASRGL1) was carried out. Statistical modelling with embedded variable selection was applied on the staining results to identify minimal prognostic panels with maximal prognostic accuracy without compromising generalizability. Results. A panel including p53 and ASRGL1 immunohistochemistry was identified as the most accurate predictor of relapse-free and disease-specific survival. Within this panel, patients were allocated into high- (5.9%), intermediate- (295%) and low- (64.6%) risk groups where high-risk patients had a 30-fold risk (P

The role of adrenal androgens as drivers for castration-resistant prostate cancer (CRPC) growth in humans is generally accepted; however, the value of preclinical mouse models of CRPC is debatable, because mouse adrenals do not produce steroids activating the androgen receptor. In this study, we confirmed the expression of enzymes essential for de novo synthesis of androgens in mouse adrenals, with high intratissue concentration of progesterone (P-4) and moderate levels of androgens, such as androstenedione, testosterone, and dihydrotestosterone, in the adrenal glands of both intact and orchectomized (ORX) mice. ORX alone had no effect on serum P-4 concentration, whereas orchectomized and adrenalectomized (ORX + ADX) resulted in a significant decrease in serum P-4 and in a further reduction in the Low levels of serum androgens (androstenedione, testosterone, and dihydrotestosterone), measured by mass spectrometry. In line with this, the serum prostate-specific antigen and growth of VCaP xenografts in mice after ORX + ADX were markedly reduced compared with ORX alone, and the growth difference was not abolished by a glucocorticoid treatment. Moreover, ORX + ADX altered the androgen-dependent gene expression in the tumors, similar to that recently shown for the enzalutamide treatment. These data indicate that in contrast to the current view, and similar to humans, mouse adrenals synthesize significant amounts of steroids that contribute to the androgen receptor dependent growth of CRPC.

Endometriosis is a common inflammatory estrogen-dependent gynecological disorder, associated with pelvic pain and reduced fertility in women. Several aspects of this disorder and its cellular and molecular etiology remain unresolved. We have analyzed the global gene expression patterns in the endometrium, peritoneum and in endometriosis lesions of endometriosis patients and in the endometrium and peritoneum of healthy women. In this report, we present the EndometDB, an interactive web-based user interface for browsing the gene expression database of collected samples without the need for computational skills. The EndometDB incorporates the expression data from 115 patients and 53 controls, with over 24000 genes and clinical features, such as their age, disease stages, hormonal medication, menstrual cycle phase, and the different endometriosis lesion types. Using the web-tool, the end-user can easily generate various plot outputs and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format. Availability and implementationThe web-based user interface is implemented using HTML5, JavaScript, CSS, Plotly and R. It is freely available from https://endometdb.utu.fi/., Measurement(s) RNA • differential expression analysis data • endometriosis Technology Type(s) Microarray Analysis • digital curation Factor Type(s) age • disease stage • menstrual cycle phase • hormonal medication • endometriosis lesion type • endometrium Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12800642

Intravesical instillations with Bacillus Calmette-Guérin (BCG) are the recommended treatment in T1 high-grade (HG) bladder cancer (BC) patients. However, even with BCG treatment, 50% of patients develop a HG recurrence or progression to advanced disease. Current risk stratification is insufficient to identify patients at risk of BCG failure. We aimed to identify molecular predictors of BCG failure in T1HG BC patients with the objective to improve clinical decision-making. Primary T1HG BC patients treated with ≥5/6 BCG induction instillations were retrospectively included. RNA-sequencing (50 million paired-end reads, ≥80% tumor) was performed on centrally reviewed tumors from: 1) BCG-naïve tumors and recurrent tumors from patients that failed BCG therapy (BCG non-responders), matched to an equal number of 2) patients who had an ongoing complete response until study inclusion (BCG responders). Endpoints were HG recurrence-free survival defined as BCG-failure (RFS) and progression-free survival (PFS), assessed by survival analyses. BCG-failure was defined as development of a biopsy-proven HG recurrence or progression to muscle-muscle invasion. Using RNA-seq, we sought to identify genes, pathways and signatures that stratified patients with respect to these endpoints. 132 BCG-naïve T1HG tumors were sequenced and 45 post-BCG tumors. Median follow-up for all patients was 75 months (IQR 48-106), 99 months for n=63 BCG-responders (IQR 74-120) and 49 months for n=69 BCG-non-responders (IQR 25-79). Three molecular subtypes were identified: BCG1 (32%), BCG2 (40%) and BCG3 (28%). BCG3 patients had a significantly worse RFS (HR 2.4 p Citation Format: Florus C. De Jong, Teemu D. Laajala, Robert F. Hoedemaeker, Sébastien Rinaldetti, Jolien T. Mensink, Angelique C. Van der Made, Deric K. Van der Schoot, Egbert R. Boevé, Ellen C. Zwarthoff, Joost L. Boormans, Dan Theodorescu, James C. Costello, Tahlita C. Zuiverloon. Transcriptomic analysis of BCG-treated T1HG bladder cancer patients identifies an EMT-basal subgroup with immune suppressive characteristics at high risk of BCG-failure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 614.

Intravesical instillations with Bacillus Calmette-Guérin (BCG) is the recommended treatment for T1 high-grade (HG) bladder cancer (BC) patients. Unfortunately, risk stratification is insufficient to identify patients at risk of BCG treatment failure. Another challenge is the worldwide BCG-shortage, which emphasizes the need for alternative therapeutic strategies. Thus, we aimed to investigate molecular signal transduction pathway activities using Philips' OncoSignal consumer-ready test in BCG treated T1HG BC in order to identify differentially expressed pathways that may predict clinical outcome or provide a rationale for alternative therapeutic strategies. Primary T1HG BC patients treated with ≥5/6 BCG induction instillations were retrospectively included. RNA-sequencing (50 million paired-end reads, containing ≥80% tumor) was performed on: 1) BCG-naïve tumors from patients with complete response to BCG at study inclusion (BCG-responders) and 2) BCG-naïve tumors with matching muscle-invasive bladder cancer (MIBC) recurrences during BCG therapy (BCG-failures). Philips OncoSignal analysis was performed to quantify functional signal transduction pathway activities. Molecular subtyping was performed using non-muscle invasive and muscle-invasive classifiers. Clinical and molecular subtyping results were combined with Philips OncoSignal to explore differences between BCG responders and BCG failures and between molecular subtypes. OncoSignal was performed in 20 tumors: 14 BCG-naïve (7 BCG-responders vs 7 BCG-failures) and 6 MIBC recurrences. Median follow-up for BCG-responders was 99 months (IQR 74-120); median follow-up for BCG-failures was 49 months (IQR 25-79), with a median time to progression of 14 months (IQR 10-41). Based on pilot data, MAPK and TGFβ pathway activity was significantly higher in tumors from BCG failures vs BCG-responders (both p Citation Format: Florus C. De Jong, Teemu D. Laajala, Robert F. Hoedemaeker, Sébastien Rinaldetti, Jolien T. Mensink, Angelique C. Van Der Made, Deric K. Van der Schoot, Egbert R. Boevé, Ellen C. Zwarthoff, Joost L. Boormans, Dan Theodorescu, James C. Costello, Tahlita C. Zuiverloon. Differential pathway analyses of BCG-treated T1HG bladder cancer using Philips OncoSignal: A pilot study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 615.

Simple Summary Approximately 1 in 8 men will be diagnosed with prostate cancer (PCa) at some point in their lifetime. Five-year survival rate for patients with local or regionally spread disease is near 100%, but this drops to 30% when the cancer has spread to distant sites. Androgen receptor (AR) signaling plays a pivotal role in normal prostate development and PCa cell survival. Therapies targeting the AR pathway are mainline treatments, but resistance is a major clinical problem. From the literature and our own meta-analysis of PCa databases, we aimed to review the connections between PCa genetic alterations and the AR signaling axis at the primary stage. Assessing how combinations of PCa genetic drivers that arise in patients affect AR signaling will aid in stratifying patients who will likely respond to AR-directed therapies, and those who will require other therapeutic agents upfront in order to prevent disease progression. Abstract While many prostate cancer (PCa) cases remain indolent and treatable, others are aggressive and progress to the metastatic stage where there are limited curative therapies. Androgen receptor (AR) signaling remains an important pathway for proliferative and survival programs in PCa, making disruption of AR signaling a viable therapy option. However, most patients develop resistance to AR-targeted therapies or inherently never respond. The field has turned to PCa genomics to aid in stratifying high risk patients, and to better understand the mechanisms driving aggressive PCa and therapy resistance. While alterations to the AR gene itself occur at later stages, genomic changes at the primary stage can affect the AR axis and impact response to AR-directed therapies. Here, we review common genomic alterations in primary PCa and their influence on AR function and activity. Through a meta-analysis of multiple independent primary PCa databases, we also identified subtypes of significantly co-occurring alterations and examined their combinatorial effects on the AR axis. Further, we discussed the subsequent implications for response to AR-targeted therapies and other treatments. We identified multiple primary PCa genomic subtypes, and given their differing effects on AR activity, patient tumor genetics may be an important stratifying factor for AR therapy resistance.

G-Protein Coupled Receptor (GPCR), Class C, Group 5, Member A (GPRC5A) has been implicated in several malignancies. The underlying mechanisms, however, remain poorly understood. Using a panel of human cell lines, we demonstrate that CRISPR/Cas9-mediated knockout and RNAi-mediated depletion of GPRC5A impairs cell adhesion to integrin substrates: collagens I and IV, fibronectin, as well as to extracellular matrix proteins derived from the Engelbreth-Holm-Swarm (EHS) mouse sarcoma (Matrigel). Consistent with the phenotype, knock-out of GPRC5A correlated with a reduced integrin beta 1 (ITGB1) protein expression, impaired phosphorylation of the focal adhesion kinase (FAK), and lower activity of small GTPases RhoA and Rac1. Furthermore, we provide the first evidence for a direct interaction between GPRC5A and a receptor tyrosine kinase EphA2, an upstream regulator of FAK, although its contribution to the observed adhesion phenotype is unclear. Our findings reveal an unprecedented role for GPRC5A in regulation of the ITGB1-mediated cell adhesion and it's downstream signaling, thus indicating a potential novel role for GPRC5A in human epithelial cancers.

Background: Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interestnamely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trialENTHUSE M1in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0·791; Bayes factor >5) and surpassed the reference model (iAUC 0·743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3·32, 95% CI 2·394·62, p, European Union within the ERC grant LatentCauses supported the work of C.F and I.K. German Research Foundation (DFG) within the Collaborative Research Centre 1243, subproject A17 awarded to C.F. German Federal Ministry of Education and Research (BMBF) through the Research Consortium e:AtheroMED (Systems medicine of myocardial infarction and stroke) under the auspices of the e:Med Programme (grant # 01ZX1313C) supported the work of D.P.A., P.D., C.F., C.K., I.K., N.K., M.L., H.S. and J.F.S. at the Institute of Computational Biology. NIH Grants RR025747-01, MH086633 and 1UL1TR001111, and NSF Grants SES-1357666, DMS-14-07655 and BCS0826844 supported the work of C.H., J.I., E.L., Y.W., H.Y., H.Z. and J.Z. NSFC Grant Nos. 61332013, 61572139 supported the work of X.L, Y.L, Y.Z., and S.Z. National Natural Science Foundation of China grants [Nos. 61422309, 61379092] was awarded to S.Z. The Patrick C. Walsh Prostate Research Fund and the Johns Hopkins Individualized Health Initiative supported the work of R.Y.C., D.D., Y.D., Z.J., K.R., Z.W. and Y.Z. FCT Ph.D. Grant SFRH/BD/80925/2011 was awarded to S.C. Clinical Persona Inc., East Palo Alto, CA supported the work of L.B. and D.K. The Finnish Cultural Foundation and the Drug Research Doctoral Programme (DRDP) at the University of Turku supported T.D.L. The National Research Foundation Singapore and the Singapore Ministry of Education, under its Research Centres of Excellence initiative, supported the work of J.G. and K.T. A grant from the Russian Science Foundation 14-24-00155 was awarded to M.D.K. A*MIDEX grant (no. ANR-11-IDEX-0001-02) was awarded to P.J.B. NSERC supported the work of R.G. The Israeli Centers of Research Excellence (I-CORE) program (Center No. 4/11) supported the work of E.G. Academy of Finland (grants 292611, 269862, 272437, 279163, 295504), National Cancer Institute (16X064), and Cancer Society of Finland supported the work of T.A. Academy of Finland (grant 268531) supported the work of T.M

The hydroxysteroid (17beta) dehydrogenase (HSD17B)12 gene belongs to the hydroxysteroid (17β) dehydrogenase superfamily, and it has been implicated in the conversion of estrone to estradiol as well as in the synthesis of arachidonic acid (AA). AA is a precursor of prostaglandins, which are involved in the regulation of female reproduction, prompting us to study the role of HSD17B12 enzyme in the ovarian function. We found a broad expression of HSD17B12 enzyme in both human and mouse ovaries. The enzyme was localized in the theca interna, corpus luteum, granulosa cells, oocytes, and surface epithelium. Interestingly, haploinsufficiency of the HSD17B12 gene in female mice resulted in subfertility, indicating an important role for HSD17B12 enzyme in the ovarian function. In line with significantly increased length of the diestrous phase, the HSD17B+/- females gave birth less frequently than wild-type females, and the litter size of HSD17B12+/- females was significantly reduced. Interestingly, we observed meiotic spindle formation in immature follicles, suggesting defective meiotic arrest in HSD17B12+/- ovaries. The finding was further supported by transcriptome analysis showing differential expression of several genes related to the meiosis. In addition, polyovular follicles and oocytes trapped inside the corpus luteum were observed, indicating a failure in the oogenesis and ovulation, respectively. Intraovarian concentrations of steroid hormones were normal in HSD17B12+/- females, whereas the levels of AA and its metabolites (6-keto prostaglandin F1alpha, prostaglandin D2, prostaglandin E2, prostaglandin F2α, and thromboxane B2) were decreased. In conclusion, our study demonstrates that HSD17B12 enzyme plays an important role in female fertility through its role in AA metabolism.

Gemcitabine and cisplatin (GC) combination neoadjuvant chemotherapy (NAC) is standard of care for patients with muscle-invasive bladder cancer (MIBC). This combination is preferred due to its favorable toxicity profile. Approximately 25% of NAC treated patients will experience complete pathological response (pT0) at time of radical cystectomy (RC). NAC-treated patients with residual disease at RC have poorer prognosis compared to those who achieved pT0. Here we systematically defined the in vitro functional determinants of resistance to gemcitabine and cisplatin in bladder cancer. To accomplish this, we performed molecular profiling and functional genomic screening on a panel of bladder cancer cell lines (KU-19-19, T24, TCCSUP, 253J and 5637), each having the parental cell line with matched gemcitabine-, cisplatin-, and dual GC-resistant derivatives. We performed whole exome sequencing, RNA sequencing, and phospho-proteomic profiling on these 20 cell lines. To identify chemogenetic interactions that govern sensitivity or resistance to these agents, we performed whole genome CRISPR knockout screening in the GC-resistant cells both in the presence and absence of GC. We identified several novel genes that when inactivated are capable of sensitizing GC resistant cell lines to the two agents. The majority of shared chemosensitizing genes fall into several DNA damage response pathways. This is consistent with the established mechanism of action of GC chemotherapy and observations that have been made from clinical cohorts, where loss-of-function mutations in these pathways correlate with response to platinum-based chemotherapy. Notably, our work has identified several druggable candidates that could serve as potential targets for enhancing responses rates to GC. Interestingly, comparing these candidate genes and pathways with those differentially expressed in the RNA sequencing and proteomic profiling showed limited overlap. This work provides a comprehensive view of the functional determinants of GC sensitivity in bladder cancer. In support of and expanding on previous studies, we identified additional DNA damage response genes that when lost enhance sensitivity to GC. These genes should be further explored for their utility as predictive biomarkers of response to GC-based therapy in clinical cohorts. Importantly, a number of these could be targeted in combination with GC-based NAC to potentially improve response. Citation Format: Robert T. Jones, Tahlita C. Zuiverloon, Hedvig Vekony, Andrew Goodspeed, Teemu D. Laajala, Molishree Joshi, Colin Sempeck, Annie Jean, Megan Tu, Julia D. Wulfkuhle, Emanuel F. Petricoin, James C. Costello, Dan Theodorescu. Functional genomic screening in gemcitabine and cisplatin resistant bladder cancer cell lines identifies DNA repair pathways as mediators of chemosensitivity [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4091.

Neoadjuvant platinum-based chemotherapy (NAC) followed by radical cystectomy is the preferred first-line option for treating patients diagnosed with muscle-invasive bladder cancer (MIBC). One of the two most commonly utilized chemotherapy regimens for MIBC consists of combination therapy with gemcitabine and cisplatin (GC). Importantly, cisplatin-based chemotherapy leads to complete response (pT0) in approximately 25% of patients, while the remaining 75% are left with residual disease. For MIBC patients, the presence of residual disease at cystectomy is associated with significantly poorer prognosis. Previous efforts to screen tumor-derived specimens have identified a number of mutational biomarkers associated with NAC response; however, to date these efforts have been limited by the number of patients profiled and the molecular and mutational heterogeneity intrinsic to bladder cancers. Moreover, these efforts have primarily relied on a single technology (e.g., whole-exome sequencing or transcriptome profiling), and were not designed to look at GC-resistance patterns in a way that integrates these data types. Therefore, we sought to systematically define the molecular phenotypes associated with chemoresistant bladder cancer cells, and to functionally interrogate these features to better define essential genes and pathways that govern chemoresponsiveness. To accomplish this, we have extensively characterized a panel of six bladder cancer cell lines (KU-19-19, T24, TCCSUP, 253J, 5637, and RT112), each of which has three derivative cell lines with acquired resistance to gemcitabine, cisplatin, and GC combination. For all of these cell lines we have performed whole-transcriptome mRNA sequencing, whole-exome sequencing, and reverse phase protein microarray. Additionally, we have performed functional genomic screening using whole-genome CRISPR knockout libraries, in the combination GC-resistant derivative cell lines. Using these data we identified multiple important chemoresistance genes and pathways, both previously known and novel. Interestingly, even though we found heterogeneous expression patterns seen across different –omic platforms, the functional genomic screens in GC-resistant cell lines converged on many genes and pathways that are essential to DNA damage response. These data suggest that functional genomic screens are perhaps more likely to identify genes and pathways that are directly linked to each of these drugs' specific mechanisms of action, as opposed to context-specific molecular differences seen across cell lines. Importantly, these results could enable improved prediction and personalization of therapy through identifying biomarkers that predict chemosensitivity and resistance. This study also suggests that identifying more generalizable strategies to overcome chemoresistance could increase the number of bladder cancer patients experiencing deeper and more complete responses to these common chemotherapeutic drugs. Citation Format: Robert T. Jones, Tahlita C. M. Zuiverloon, Hedvig Vekony, Andrew Goodspeed, Teemu D. Laajala, Molishree Joshi, Colin Sempeck, Annie Jean, Megan Tu, Julia D. Wulfkuhle, Emanuel F. Petricoin, James C. Costello, Dan Theodorescu. Multi-omic interrogation of gemcitabine and cisplatin-resistant bladder cancer cell lines identifies unique and shared mediators of chemosensitivity and resistance [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2019 May 18-21; Denver, CO. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(15_Suppl):Abstract nr B11.

Predictive survival modeling offers systematic tools for clinical decision-making and individualized tailoring of treatment strategies to improve patient outcomes while reducing overall healthcare costs. In 2015, a number of machine learning and statistical models were benchmarked in the DREAM 9.5 Prostate Cancer Challenge, based on open clinical trial data for metastatic castration resistant prostate cancer (mCRPC). However, applying these models into clinical practice poses a practical challenge due to the inclusion of a large number of model variables, some of which are not routinely monitored or are expensive to measure.To develop cost-specified variable selection algorithms for constructing cost-effective prognostic models of overall survival that still preserve sufficient model performance for clinical decision making.Penalized Cox regression models were used for the survival prediction. For the variable selection, we implemented two algorithms: (i) LASSO regularization approach; and (ii) a greedy cost-specified variable selection algorithm. The models were compared in three cohorts of mCRPC patients from randomized clinical trials (RCT), as well as in a real-world cohort (RWC) of advanced prostate cancer patients treated at the Turku University Hospital. Hospital laboratory expenses were utilized as a reference for computing the costs of introducing new variables into the models.Compared to measuring the full set of clinical variables, economic costs could be reduced by half without a significant loss of model performance. The greedy algorithm outperformed the LASSO-based variable selection with the lowest tested budgets. The overall top performance was higher with the LASSO algorithm.The cost-specified variable selection offers significant budget optimization capability for the real-world survival prediction without compromising the predictive power of the model.

Kinase inhibitor resistance constitutes a major unresolved clinical challenge in cancer. Furthermore, the role of serine/threonine phosphatase deregulation as a potential cause for resistance to kinase inhibitors has not been thoroughly addressed. We characterize protein phosphatase 2A (PP2A) activity as a global determinant of KRAS-mutant lung cancer cell resistance across a library of >200 kinase inhibitors. The results show that PP2A activity modulation alters cancer cell sensitivities to a large number of kinase inhibitors. Specifically, PP2A inhibition ablated mitogen-activated protein kinase kinase (MEK) inhibitor response through the collateral activation of AKT/mammalian target of rapamycin (mTOR) signaling. Combination of mTOR and MEK inhibitors induced cytotoxicity in PP2A-inhibited cells, but even this drug combination could not abrogate MYC up-regulation in PP2A-inhibited cells. Treatment with an orally bioavailable small-molecule activator of PP2A DT-061, in combination with the MEK inhibitor AZD6244, resulted in suppression of both p-AKT and MYC, as well as tumor regression in two KRAS-driven lung cancer mouse models. DT-061 therapy also abrogated MYC-driven tumorigenesis. These data demonstrate that PP2A deregulation drives MEK inhibitor resistance in KRAS-mutant cells. These results emphasize the need for better understanding of phosphatases as key modulators of cancer therapy responses.

During epididymal maturation, sperm acquire the ability to swim progressively by interacting with proteins secreted by the epididymal epithelium. Beta-defensin proteins, expressed in the epididymis, continue to regulate sperm motility during capacitation and hyperactivation in the female reproductive tract. We characterized the mouse beta-defensin 41 (DEFB41), by generating a mouse model with iCre recombinase inserted into the first exon of the gene. The homozygous Defb41(iCre/iCre) knock-in mice lacked Defb41 expression and displayed iCre recombinase activity in the principal cells of the proximal epididymis. Heterozygous Defb41(iCre/+) mice can be used to generate epididymis specific conditional knock-out mouse models. Homozygous Defb41(iCre/iCre) sperm displayed a defect in sperm motility with the flagella primarily bending in the pro-hook conformation while capacitated wild-type sperm more often displayed the anti-hook conformation. This led to a reduced straight line motility of Defb41(iCre/liCre) sperm and weaker binding to the oocyte. Thus, DEFB41 is required for proper sperm maturation. (C) 2016 Elsevier Ireland Ltd. All rights reserved.