Modeling and prediction of advanced prostate cancer

Background: Prostate cancer (PCa) is the most commonly diagnosed cancer and second leading cause of cancer-related deaths for men in Western countries. The advanced form of the disease is life-threatening with few options for curative therapies. The development of novel therapeutic alternatives would greatly benefit from a more comprehensive and tailored mathematical and statistical methodology. In particular, statistical inference of treatment effects and the prediction of time-dependent effects in both preclinical and clinical studies remains a challenging yet interesting opportunity for applied mathematicians. Such methods are likely to improve the reproducibility and translatability of results and offer possibility for novel holistic insights into disease progression, diagnosis, and prognosis. Methods: Several novel statistical and mathematical techniques were developed over the course of this thesis work for the in vivo modeling of PCa treatment responses. A matching-based, blinded randomized allocation procedure for preclinical experiments was developed that provides assistance for the statistical design of animal intervention studies, e.g., through power analysis and accounting for the stratification of individuals. For the post-intervention testing of treatment effects, two novel mixed-effects models were developed that aim to address the characteristic challenges of preclinical longitudinal experiments, including the heterogeneous response profiles observed in animal studies. Subsequently, a Finnish clinical PCa hospital registry cohort was inspected with a strong emphasis on prostate-specific antigen (PSA), the most commonly used PCa marker. After exploring the PSA trends using penalized splines, a generalized mixed-effects prediction model was implemented with a focus on the ultra-sensitive range of the PSA assay. Finally, for metastatic, aggressive PCa, an ensemble Cox regression methodology was developed for overall survival prediction in the DREAM 9.5 mCRPC Challenge based on open datasets from controlled clinical trials. Results: The advantages of the improved experimental design and two proposed statistical models were demonstrated in terms of both increased statistical power and accuracy in simulated and real preclinical testing settings. Penalized regression models applied to the clinical patient datasets support the use of PSA in the ultra-sensitive range together with a model for relapse prediction. Furthermore, the novel ensemble-based Cox regression model that was developed for the overall survival prediction in advanced PCa outperformed the state-of-the-art benchmark and all other models submitted to the Challenge and provided novel predictors of disease progression and treatment responses. Conclusions: The methods and results provide preclinical researchers and clinicians with novel tools for comprehensive modeling and prediction of PCa. All methodology is available as open source R statistical software packages and/or web-based graphical user interfaces

Group polarisation among location-based game players: an analysis of use and attitudes towards game slang

Purpose – This 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/approach – The authors performed an exploratory data analysis on an original dataset of n 5 242,852 messages from five communication channels to find differences in game slang adoption between three teams in the location-based augmented reality game Pokemon 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 5 185). Finally, selected participants (n 5 25) were interviewed in person to discover any underlying reasons for the observed polarised attitudes. Findings – The 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 implications – Game 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/value – The 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. Keywords Location-based games, Polarisation, Social identity theory, Language, Slang Paper type Research paper</p

A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions

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.Peer reviewe

Label-free quantitative phosphoproteomics with novel pairwise abundance normalization reveals synergistic RAS and CIP2A signaling

Hyperactivated RAS drives progression of many human malignancies. However, oncogenic activity of RAS is dependent on simultaneous inactivation of protein phosphatase 2A (PP2A) activity. Although PP2A is known to regulate some of the RAS effector pathways, it has not been systematically assessed how these proteins functionally interact. Here we have analyzed phosphoproteomes regulated by either RAS or PP2A, by phosphopeptide enrichment followed by mass-spectrometry-based label-free quantification. To allow data normalization in situations where depletion of RAS or PP2A inhibitor CIP2A causes a large uni-directional change in the phosphopeptide abundance, we developed a novel normalization strategy, named pairwise normalization. This normalization is based on adjusting phosphopeptide abundances measured before and after the enrichment. The superior performance of the pairwise normalization was verified by various independent methods. Additionally, we demonstrate how the selected normalization method influences the downstream analyses and interpretation of pathway activities. Consequently, bioinformatics analysis of RAS and CIP2A regulated phosphoproteomes revealed a significant overlap in their functional pathways. This is most likely biologically meaningful as we observed a synergistic survival effect between CIP2A and RAS expression as well as KRAS activating mutations in TCGA pan-cancer data set, and synergistic relationship between CIP2A and KRAS depletion in colony growth assays.Peer reviewe

Adrenals Contribute to Growth of Castration-Resistant VCaP Prostate Cancer Xenografts

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.Peer reviewe

CIP2A Promotes T-Cell Activation and Immune Response to Listeria monocytogenes Infection

The oncoprotein Cancerous Inhibitor of Protein Phosphatase 2A ( CIP2A) is overexpressed in most malignancies and is an obvious candidate target protein for future cancer therapies. However, the physiological importance of CIP2A-mediated PP2A inhibition is largely unknown. As PP2A regulates immune responses, we investigated the role of CIP2A in normal immune system development and during immune response in vivo. We show that CIP2A-deficient mice (CIP2A(HOZ)) present a normal immune system development and function in unchallenged conditions. However when challenged with Listeria monocytogenes, CIP2A(HOZ) mice display an impaired adaptive immune response that is combined with decreased frequency of both CD4(+) T-cells and CD8(+) effector T-cells. Importantly, the cell autonomous effect of CIP2A deficiency for T-cell activation was confirmed. Induction of CIP2A expression during T-cell activation was dependent on Zap70 activity. Thus, we reveal CIP2A as a hitherto unrecognized mediator of T-cell activation during adaptive immune response. These results also reveal CIP2A(HOZ) as a possible novel mouse model for studying the role of PP2A activity in immune regulation. On the other hand, the results also indicate that CIP2A targeting cancer therapies would not cause serious immunological side-effects.Peer reviewe

Syöpäkasvatuskokeiden analysointi sekamalleilla

Tumor growth experiments used in pre-clinical cancer drug development often result in challenging response profiles. An implanted human cancer cell line inside a genetically standardized, immune-deficient mouse can shrink spontaneously in a control group or grow aggressively in a treatment group, even if the treatment otherwise appears to block the effective growth of the implanted cancer cells. Such experiments have previously been analysed using simple statistical methods such as comparison of the end-point tumor volume between the treatment and control groups through a t-test. We designed a mixed-effects modelling framework that explores hidden subgroups of the data and seeks to connect the identified groups to established tumor biomarkers. Suitable response and model transformations were proposed to be able to model a wide range of tumor growth experiments. Cross-validation as well as other model validation and diagnostic tools were utilized for motivating the suggested model choice. In addition, various approaches were proposed for the purposes of developing better experiment protocols in the future. The modelling procedure and conclusions made from the statistical inference were shown to be coherent with the previously published studies and the model parameters were assessed to have meaningful interpretation. The biological motivation of the identified categories was shown to be feasible through several biomarkers. The current work provides a fruitful base for future model development.Esikliiniset syöpäkokeet johtavat usein heterogeenisiin kasvuprofiileihin. Istutettu syöpäsolukasvain saattaa spontaanisti pienentyä immunokatoisissa geneettisesti standardoiduissa kontrollihiirissä ja toisaalta yksittäinen tuumori saattaa kasvaa aggressiivisesti hoitoryhmässä, vaikka hoito vaikuttaisi muuten pysäyttävän syöpäkasvainten suurentumisen. Tällaisten kasvatuskokeiden tilastollinen analyysi on suoritettu monissa julkaisuissa yksinkertaisilla menetelmillä, esimerkiksi vertailemalla viimeisen aikapisteen tuumorivolyymeja t-testillä eri hoitoryhmien yli. Kehitimme sekamalleihin perustuvan menetelmän, joka etsii syöpien alatyyppejä niiden kasvuprofiilien perusteella. Menetelmä pyrkii yhdistämään löydetyt alatyypit alalla käytettyihin biomarkkereihin. Mallin muokkausta ja vasteiden muunnoksia esitetään erilaisiin tilanteisiin, jotta mahdollisimman monenlaisia syöpäkokeita pystyttäisiin analysoimaan kehitetyllä lähestymistavalla. Ristiinvalidointia sekä muuta mallin diagnostiikkaa käytetään hyväksi perusteltaessa valittua mallin määrittelyä. Lisäksi testataan erilaisia menetelmiä parantaa käytettyä koeasetelmaa sovitetun mallin perusteella. Malliin perustuva päättely rinnastetaan aiempiin julkaisuihin. Sovitetun mallin parametreja tutkitaan biologisen esitiedon perusteella sekä osoitetaan mallilla olevan järkevä yhteys käytettyyn koeasetelmaan sekä kasvatuskokeisiin liittyviin hypoteeseihin. löydetyt kategoriat linkitetään alan biomarkkereihin ja esitetään erilaisia tulevaisuuden näkökulmia syöpäkokeiden mallinkehitykseen

Female doping: observations from a data lake study in the Hospital District of Helsinki and Uusimaa, Finland

BackgroundDoping is a well-recognized risk factor for several potentially severe health effects. Scientific literature concerning the need for medical treatment for such adversities is still sparse. This is especially true for women, due to lower doping use prevalence compared to men. Our study explored the nature of medical contacts and deviance in red blood cell parameters of female patients with doping use in Finnish specialized health care.MethodsThis was a retrospective register study. The study sample was gathered from the Hospital District of Helsinki and Uusimaa, Finland (HUS) Datalake. An exhaustive search for doping related terms was performed to find patients with doping use documentation within free-text patient records. Medical record data was supplemented with laboratory data and medical diagnoses covering a total observation time of two decades. Statistical analysis included Fisher's Exact Test and one-way ANOVA.ResultsWe found 39 female patients with history of doping use and specialized health care contacts in the HUS-area between 2002-2020. At initial contact (i.e., the first documentation of doping use), the mean age of these patients was 33.6 years (min 18.1, max 63.5, SD 10.6). The most frequently used doping agents were anabolic androgenic steroids (AAS). The initial contacts were significantly more often acute in nature among patients with active doping use than among patients with only previous use (no use within one year; p = 0.002). Psychiatric and substance use disorder (SUD) morbidity was high (46.2% and 30.8%, respectively). Eight patients (20.5%) had received specialized health care for acute poisoning with alcohol or drugs, and nine (23.1%) for bacterial skin infections. Less than 45% of patients with active AAS use presented with off-range red blood cell parameters.ConclusionsOur findings suggest that female patients with a history of doping use encountered in specialized health care may exhibit high psychiatric and SUD related morbidity. Also, majority of patients with AAS use had red blood cell parameters within-range. Further studies are required to assess the generalizability of these findings to patients within primary health care services, and to determine the usefulness of hematological parameters as indicators of AAS use in female patients.Peer reviewe