Modulation of protease expression in prostate cancer cells after androgen deprivation

Understanding mechanisms associated with the emergence of castration resistant prostate cancer cells (CRPC) after androgen deprivation therapy (ADT) is essential to create new therapeutic agents to counteract this aggressive form of prostate cancer (PCa). Because proteases are involved in almost all cancer associated mechanisms such as cell proliferation, invasion and metastasis, we are interested in their modulation in PCa after ADT and their involvement in CRPC.

Extracellular vesicles mediate paracrine signalling in androgen deprived prostate cancer

The androgen receptor (AR) is the main therapeutic target for advanced prostate cancer (PCa). Current treatments have focused on inhibiting the transcriptional activity of the AR, however androgens can also induce non-genomic effects by facilitating the initiation of kinase signaling cascades in PCa. Cells, including PCa, secrete extracellular vesicles (EV), which are able to mediate communication between cells and can also contribute towards these processes.

A 3D in vitro model reflecting the androgen deprivation state in prostate cancer bone metastasis

In castrate-resistant prostate cancer (CRPC), the prevailing organ for metastasis is bone, where the survival of cancer cells is regulated by the permissive metastatic niche offered by the bone marrow. The tumour microenvironment and cellular interactions with the matrix and bone cells enable metastasis and lead to cancer cells becoming androgen resistant. Hence, 3D models that mimic CRPC in terms of an androgen deprivation state (ADS) are needed to identify the mechanisms for CPRC growth in bone and further develop therapeutic strategies.

Investigating the role of neuroendocrine transdifferentiation in the progression to castration resistant prostate cancer

Androgen targeted therapies (ATT) are the most commonly used treatments in prostate cancer (PCa).While these therapies are initially effective, PCa cells are able to activate adaptive response pathways to survive these therapies and progress to castration resistant PCa (CRPC), a highly aggressive and ultimately lethal stage of the disease. Neuroendocrine transdifferentiation (NEtD), a process whereby PCa cells gain neuroendocrinelike characteristics, has been implicated in the development of CRPC. The objective of this study is to develop and characterise models of therapy-induced NEtD to investigate the role of this adaptive plasticity in the progression to CRPC.

Targeting neuropilin-1 to inhibit prostate cancer invasion and metastasis

Recent reports provide evidence that the epithelial-to-mesenchymal transition (EMT) plays a key role in prostate cancer (PCa) metastasis and therapy resistance. We have recently identified the cell surface receptor, Neuropilin-1 (NRP1) to be increased during epithelial-mesenchymal transition (EMT) and this study aims to determine whether the inhibition of NRP1 will be a feasible therapeutic strategy for blocking PCa metastasis and therapy resistance.

The mesenchymal-to-epithelial reverting transition is enriched in metastatic castration resistant prostate cancer and correlates with poor survival

Despite recent recognition that the epithelial-mesenchymal transition (EMT) program acts in a dynamic manner (termed Epithelial to Mesenchymal Plasticity or EMP) during carcinoma metastasis, it has largely been ignored in the discovery and development of EMT-targeted therapies. In part, this has stemmed from a lack of preclinical models that can mimic the full dynamic nature of EMP and the perception that the EMT-reverting transition [or mesenchymal-epithelial reverting transition; (MErT)] is a mere antithesis of EMT. The objective of this study was to develop the first PCa model capable of recapitulating the dynamic nature of EMP.

Critical lattice size limit for synchronized chaotic state in one- and two-dimensional diffusively coupled map lattices

We consider diffusively coupled map lattices with P neighbors (where P is arbitrary) and study the stability of the synchronized state. We show that there exists a critical lattice size beyond which the synchronized state is unstable. This generalizes earlier results for nearest neighbor coupling. We confirm the analytical results by performing numerical simulations on coupled map lattices with logistic map at each node. The above analysis is also extended to two-dimensional P-neighbor diffusively coupled map lattices.

Primary polyestradiol phosphate versus orchiectomy for advanced prostate cancer : Studies on the efficacy, cardiovascular complications and prognostic factors

Paikallisesti levinnyttä (T3-4 M0) ja luustoon levinnyttä (T1-4 M1) eturauhassyöpää sairastaneet potilaat satunnaistettiin kirurgiseen kastraatioon (orkiektomia) tai lääkkeelliseen kastraatioon lihaksensisäisellä polyestradiolifosfaatilla (PEP) annoksella 240 mg/kk. Verrattiin hoitojen kliinistä tehoa sekä sydän- ja verisuonikomplikaatioita (SV-komplikaatioita). Verrattiin myös hoitoa edeltäviä plasman testosteroni (T) ja estradioli (E2) pitoisuuksia T3-4 M0 ja T1-4 M1 potilaiden välillä sekä selvitettiin potilaiden yleistilan vaikutusta näihin hormonitasoihin. Lopuksi luotiin T1-4 M1 potilaille eturauhassyövän aiheuttaman kuoleman ennusteellinen riskiluokittelu kolmeen riskiryhmään käyttämällä hoitoa edeltäviä ennustetekijöitä. Kliinisessä tehossa ei orkiektomian ja PEP-hoidon välillä todettu tilastollisesti merkitsevää eroa. Odotetusti T1-4 M1 potilaiden ennuste oli huonompi kuin T3-4 M0 potilaiden. T1-4 M1 potilailla ei ollut SV-kuolemissa hoitoryhmien välillä tilastollista eroa, mutta ei-tappavia SV-komplikaatioita oli PEP ryhmässä (5.9%) enemmän kuin orkiektomia ryhmässä (2.0%). T3-4 M0 potilailla PEP-hoitoon liittyi tilastollisesti merkitsevä SV-kuolleisuus riski orkiektomiaan verrattuna (p = 0.001). PEP ryhmässä 67% kuolemista oli akuutteja sydäninfarkteja. Tämä PEP hoitoon liittyvä sydäninfarktiriski (mukaan lukien myös ei-tappavat sydäninfarktit) oli merkitsevästi pienempi potilailla, joiden hoitoa edeltävä E2 taso oli vähintään 93 pmol/l (p = 0.022). E2 taso oli merkitsevästi matalampi T1-4 M1 potilailla (74.7 pmol/l) kuin T3-4 M0 potilailla (87.9 pmol/l), mutta vastaavaa eroa ei ollut T tasoissa. Sekä T3-4 M0 että T1-4 M1 potilailla yleistilan lasku osittain selitti yksilöllisen T ja E2 tasojen laskun. Eturauhassyövän aiheuttaman kuoleman riskiryhmäluokittelu (Rg) kolmeen ryhmään luotiin käyttämällä alkalista fosfataasia (AFOS), prostata spesifistä antigeenia (PSA), laskoa (La) ja potilaan ikää. Yksi riskipiste annettiin, jos AFOS > 180 U/l (tällä hetkellä käytössä olevalla menetelmällä AFOS > 83 U/l), PSA > 35 µg/l, La > 80 mm/h ja ikä < 60 vuotta. Lopuksi pisteet laskettiin yhteen. Muodostettiin seuraavat ryhmät: Rg-a (0 -1 riskipistettä), Rg-b (2 riskipistettä) ja Rg-c (3 – 4 riskipistettä). Eturauhassyövän aiheuttama kuoleman riski lisääntyi merkitsevästi siirryttäessä riskiryhmästä seuraavaan (p < 0.001). Rg-luokittelu oli kliinisesti käytännöllinen ja hyvä havaitsemaan huonon ennusteen potilaat.

Novel flutamide regulated genes in the rat ventral prostate: differential modulation of their expression by castration and flutamide treatments

Aim: To identify flutamide regulated genes in the rat ventral prostate. Methods: Total RNA from ventral prostates control and flutamide treated rats were isolated. Differentially expressed transcripts were identified using display reverse transcriptase polymerase chain reaction. The effect of castration on the expression of regulated transcripts was studied. Results: We have identified beta 2-microglobulin, cytoplasmic FMR1 protein 2 and pumilio 1 as flutamide induced and spermine binding protein and ribophorin II as flutamide targets in the rat ventral prostate. Although flutamide treatment caused an induction of pumilio I mRNA, had no effect. Conclusion: Castration and flutamide treatments exert differential effects on gene expression. might also have direct AR independent effects, which might have implications in the emergence of androgen dent prostate cancer and the failure of flutamide therapy.