Prostate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies,... Show moreProstate cancer (PCa) is a highly prevalent cancer type with a heterogeneous prognosis. An accurate assessment of tumor aggressiveness can pave the way for tailored treatment strategies, potentially leading to better outcomes. While tumor aggressiveness is typically assessed based on invasive methods (e.g., biopsy), radiogenomics, combining diagnostic imaging with genomic information can help uncover aggressive (imaging) phenotypes, which in turn can provide non-invasive advice on individualized treatment regimens. In this study, we carried out a parallel analysis on both imaging and transcriptomics data in order to identify features associated with clinically significant PCa (defined as an ISUP grade ≥ 3), subsequently evaluating the correlation between them. Textural imaging features were extracted from multi-parametric MRI sequences (T2W, DWI, and DCE) and combined with DCE-derived parametric pharmacokinetic maps obtained using magnetic resonance dispersion imaging (MRDI). A transcriptomic analysis was performed to derive functional features on transcription factors (TFs), and pathway activity from RNA sequencing data, here referred to as transcriptomic features. For both the imaging and transcriptomic features, different machine learning models were separately trained and optimized to classify tumors in either clinically insignificant or significant PCa. These models were validated in an independent cohort and model performance was used to isolate a subset of relevant imaging and transcriptomic features to be further investigated. A final set of 31 imaging features was correlated to 33 transcriptomic features obtained on the same tumors. Five significant correlations (p < 0.05) were found, of which, three had moderate strength (|r| ≥ 0.5). The strongest significant correlations were seen between a perfusion-based imaging feature—MRDI A median—and the activities of the TFs STAT6 (−0.64) and TFAP2A (−0.50). A higher-order T2W textural feature was also significantly correlated to the activity of the TF STAT6 (−0.58). STAT6 plays an important role in controlling cell proliferation and migration. Loss of the AP2alpha protein expression, quantified by TFAP2A, has been strongly associated with aggressiveness and progression in PCa. According to our findings, a combination of texture features extracted from T2W and DCE, as well as perfusion-based pharmacokinetic features, can be considered for the prediction of clinically significant PCa, with the pharmacokinetic MRDI A feature being the most correlated with the underlying transcriptomic information. These results highlight a link between quantitative imaging features and the underlying transcriptomic landscape of prostate tumors. Show less
Almekinders, M.M.M.; Schaapveld, M.; Thijssen, B.; Visser, L.L.; Bismeijer, T.; Sanders, J.; ... ; Grand Challenge PRECISION Consort 2021
Although Ductal Carcinoma In Situ (DCIS) is a non-obligate precursor to ipsilateral invasive breast cancer (iIBC), most DCIS lesions remain indolent. Hence, overdiagnosis and overtreatment of DCIS... Show moreAlthough Ductal Carcinoma In Situ (DCIS) is a non-obligate precursor to ipsilateral invasive breast cancer (iIBC), most DCIS lesions remain indolent. Hence, overdiagnosis and overtreatment of DCIS is a major concern. There is an urgent need for prognostic markers that can distinguish harmless from potentially hazardous DCIS. We hypothesized that features of the breast adipose tissue may be associated with risk of subsequent iIBC. We performed a case-control study nested in a population-based DCIS cohort, consisting of 2,658 women diagnosed with primary DCIS between 1989-2005, uniformly treated with breast conserving surgery (BCS) alone. We assessed breast adipose features with digital pathology (HALO®, Indica Labs) and related these to iIBC risk in 108 women that developed subsequent iIBC (cases) and 168 women who did not (controls) by conditional logistic regression, accounting for clinicopathological and immunohistochemistry variables. Large breast adipocyte size was significantly associated with iIBC risk (Odds Ratio (OR) 2.75, 95% confidence interval (95%CI)= 1.25 to 6.05). High Cyclooxygenase (COX)-2 protein expression in the DCIS cells was also associated with subsequent iIBC (OR 3.70 (95%CI= 1.59 to 8.64). DCIS with both high COX-2 expression and large breast adipocytes was associated with a 12-fold higher risk (OR 12.0, 95%CI= 3.10 to 46.3, P<.001) for subsequent iIBC compared with women with smaller adipocyte size and low COX-2 expression. Large breast adipocytes combined with high COX-2 expression in DCIS is associated with a high risk of subsequent iIBC. Besides COX-2, adipocyte size has the potential to improve clinical management in patients diagnosed with primary DCIS. Show less
The androgen receptor (AR) is the master regulator of prostate cancer (PCa) development, and inhibition of AR signalling is the most effective PCa treatment. AR is expressed in PCa cells and also... Show moreThe androgen receptor (AR) is the master regulator of prostate cancer (PCa) development, and inhibition of AR signalling is the most effective PCa treatment. AR is expressed in PCa cells and also in the PCa-associated stroma, including infiltrating macrophages. Macrophages have a decisive function in PCa initiation and progression, but the role of AR in macrophages remains largely unexplored. Here, we show that AR signalling in the macrophage-like THP-1 cell line supports PCa cell line migration and invasion in culture via increased Triggering Receptor Expressed on Myeloid cells-1 (TREM-1) signalling and expression of its downstream cytokines. Moreover, AR signalling in THP-1 and monocyte-derived macrophages upregulates IL-10 and markers of tissue residency. In conclusion, our data suggest that AR signalling in macrophages may support PCa invasiveness, and blocking this process may constitute one mechanism of anti-androgen therapy. Show less
Brain mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs) respond to the same glucocorticoid hormones but can have differential effects on cellular function. Several lines of... Show moreBrain mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs) respond to the same glucocorticoid hormones but can have differential effects on cellular function. Several lines of evidence suggest that MR-specific target genes must exist and might underlie the distinct effects of the receptors. The present study aimed to identify MR-specific target genes in the hippocampus, a brain region where MR and GR are co-localised and play a role in the stress response. Using genome-wide binding of both receptor types, we previously identified MR-specific, MR-GR overlapping and GR-specific putative target genes. We now report altered gene expression levels of such genes in the hippocampus of forebrain MR knockout (fbMRKO) mice, killed at the time of their endogenous corticosterone peak. Of those genes associated with MR-specific binding, the most robust effect was a 50% reduction in Jun dimerization protein 2 (Jdp2) mRNA levels in fbMRKO mice. Down-regulation was also observed for the MR-specific Nitric oxide synthase 1 adaptor protein (Nos1ap) and Suv3 like RNA helicase (Supv3 l1). Interestingly, the classical glucocorticoid target gene FK506 binding protein 5 (Fkbp5), which is associated with MR and GR chromatin binding, was expressed at substantially lower levels in fbMRKO mice. Subsequently, hippocampal Jdp2 was confirmed to be up-regulated in a restraint stress model, posing Jdp2 as a bona fide MR target that is also responsive in an acute stress condition. Thus, we show that MR-selective DNA binding can reveal functional regulation of genes and further identify distinct MR-specific effector pathways. Show less
Schunselaar, L.M.; Monkhorst, K.; Noort, V. van der; Wijdeven, R.; Peters, D.; Zwart, W.; ... ; Baas, P. 2018
