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Background: Gleason scores for prostate cancer correlates with an increased recurrence risk after radiotherapy (RT). Furthermore, higher Gleason scores correlates with decreasing apparent diffusion coefficient (ADC) data from diffusion weighted MRI (DWI-MRI). Based on these observations, we present a formalism for dose painting prescriptions of prostate volumes based on ADC images mapped to Gleason score driven dose-responses.

Methods: The Gleason score driven dose-responses were derived from a learning data set consisting of pre-RT biopsy data and post-RT outcomes for 122 patients treated with a homogeneous dose to the prostate. For a test data set of 18 prostate cancer patients with pre-RT ADC images, we mapped the ADC data to the Gleason driven dose-responses by using probability distributions constructed from published Gleason score correlations with ADC data. We used the Gleason driven dose-responses to optimize dose painting prescriptions that maximize the tumor control probability (TCP) with equal average dose as for the learning sets homogeneous treatment dose.

Results: The dose painting prescriptions increased the estimated TCP compared to the homogeneous dose by 0–51% for the learning set and by 4–30% for the test set. The potential for individual TCP gains with dose painting correlated with increasing Gleason score spread and larger prostate volumes. The TCP gains were also found to be larger for patients with a low expected TCP for the homogeneous dose prescription.

Conclusions: We have from retrospective treatment data demonstrated a formalism that yield ADC driven dose painting prescriptions for prostate volumes that potentially can yield significant TCP increases without increasing dose burdens as compared to a homogeneous treatment dose. This motivates further development of the approach to consider more accurate ADC to Gleason mappings, issues with delivery robustness of heterogeneous dose distributions, and patient selection criteria for design of clinical trials.

Improved prediction of progression to Alzheimer's Disease (AD) among older individuals with mild cognitive impairment (MCI) is of high clinical and societal importance. We recently developed a polygenic hazard score (PHS) that predicted age of AD onset above and beyond APOE. Here, we used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to further explore the potential clinical utility of PHS for predicting AD development in older adults with MCI. We examined the predictive value of PHS alone and in combination with baseline structural magnetic resonance imaging (MRI) data on performance on the Mini-Mental State Exam (MMSE). In survival analyses, PHS significantly predicted time to progression from MCI to AD over 120 months (p = 1.07e-5), and PHS was significantly more predictive than APOE alone (p = 0.015). Combining PHS with baseline brain atrophy score and/or MMSE score significantly improved prediction compared to models without PHS (three-factor model p = 4.28e-17). Prediction model accuracies, sensitivities and area under the curve were also improved by including PHS in the model, compared to only using atrophy score and MMSE. Further, using linear mixed-effect modeling, PHS improved the prediction of change in the Clinical Dementia Rating—Sum of Boxes (CDR-SB) score and MMSE over 36 months in patients with MCI at baseline, beyond both APOE and baseline levels of brain atrophy. These results illustrate the potential clinical utility of PHS for assessment of risk for AD progression among individuals with MCI both alone, or in conjunction with clinical measures of prodromal disease including measures of cognitive function and regional brain atrophy.

Prostate cancer is one of the most common types of cancer in men in Western countries. Chronic inflammation in the prostate, regulated by a complex network of factors including inflammatory cytokines, is one of the established risk factors for development of prostate cancer. Interleukin-6 (IL-6) is a well-known promoter of inflammation-induced carcinogenesis and disease progression in prostate cancer. Presence in the prostate and possible roles in tumor development by other members of the IL-6 family of cytokines have, however, been less studied. Here we show that the IL-6-type cytokine oncostatin M (OSM) indeed induce cellular properties associated with tumorigenesis and disease progression in non-transformed human prostate epithelial cells, including morphological changes, epithelial-to-mesenchymal transition (EMT), enhanced migration and pro-invasive growth patterns. The effects by OSM were partly mediated by activation of signal transducer and activator of transcription 3 (STAT3), a transcription factor established as driver of cancer progression and treatment resistance in numerous types of cancer. The findings presented here further consolidate IL-6-type cytokines and STAT3 as promising future treatment targets for prostate cancer.