Dilution of Molecular-Pathologic Gene Signatures by Medically Associated Factors Might Prevent Prediction of Resection Status After Debulking Surgery in Patients With Advanced Ovarian Cancer.

PURPOSE: Predicting surgical outcome could improve individualizing treatment strategies for patients with advanced ovarian cancer. It has been suggested earlier that gene expression signatures (GES) might harbor the potential to predict surgical outcome. EXPERIMENTAL DESIGN: Data derived from high-grade serous tumor tissue of FIGO stage IIIC/IV patients of AGO-OVAR11 trial were used to generate a transcriptome profiling. Previously identified molecular signatures were tested. A theoretical model was implemented to evaluate the impact of medically associated factors for residual disease (RD) on the performance of GES that predicts RD status. RESULTS: A total of 266 patients met inclusion criteria, of those, 39.1% underwent complete resection. Previously reported GES did not predict RD in this cohort. Similarly, The Cancer Genome Atlas molecular subtypes, an independent de novo signature and the total gene expression dataset using all 21,000 genes were not able to predict RD status. Medical reasons for RD were identified as potential limiting factors that impact the ability to use GES to predict RD. In a center with high complete resection rates, a GES which would perfectly predict tumor biological RD would have a performance of only AUC 0.83, due to reasons other than tumor biology. CONCLUSIONS: Previously identified GES cannot be generalized. Medically associated factors for RD may be the main obstacle to predict surgical outcome in an all-comer population of patients with advanced ovarian cancer. If biomarkers derived from tumor tissue are used to predict outcome of patients with cancer, selection bias should be focused on to prevent overestimation of the power of such a biomarker.See related commentary by Handley and Sood, p. 9.

Thoracic paravertebral block versus thoracic epidural analgesia for post-operative pain control in open pancreatic surgery: A randomized controlled trial.

STUDY OBJECTIVE: The purpose of this study was to compare the efficacy of bilateral ultrasound guided thoracic paravertebral catheters to a thoracic epidural after open pancreatic surgery. DESIGN: This was a prospective non-blinded randomized controlled trial. SETTING: Academic hospital operating room, postoperative recovery area, and ward. PATIENTS: 53 patients aged 18 and above who had open pancreatic surgery. INTERVENTIONS: Patients received either bilateral thoracic paravertebral block at T8 with an infusion of 0.2% ropivacaine or thoracic epidural analgesia at T7/8 with an infusion of 0.125% bupivacaine with hydromorphone 6 µg/mL. MEASUREMENTS: Pain scores, opioid use, length of recovery room and hospital stay, adverse events, and incidence of nausea and vomiting. MAIN RESULTS: There was no difference in baseline demographics between the two groups. There were no significant differences in pain scores between the two groups in each of the first five days after surgery. There was no difference in length of stay nor nausea and vomiting. There was significantly less modality related adverse events in the paravertebral group compared to the epidural group (p = 0.02). CONCLUSIONS: The use of thoracic paravertebral catheters provided comparable analgesia and less modality related adverse events when compared to a thoracic epidural in patients undergoing open pancreaticoduodenectomy.

Dorsolateral Prefrontal Cortex GABA Concentration in Humans Predicts Working Memory Load Processing Capacity.

The discovery of neural mechanisms of working memory (WM) would significantly enhance our understanding of complex human behaviors and guide treatment development for WM-related impairments found in neuropsychiatric conditions and aging. Although the dorsolateral prefrontal cortex (DLPFC) has long been considered critical for WM, we still know little about the neural elements and pathways within the DLPFC that support WM in humans. In this study, we tested whether an individual's DLPFC gamma-aminobutryic acid (GABA) content predicts individual differences in WM task performance using a novel behavioral approach. Twenty-three healthy adults completed a task that measured the unique contribution of major WM components (memory load, maintenance, and distraction resistance) to performance. This was done to address the possibility that components have differing GABA dependencies and the failure to parse WM into components would lead to missing true associations with GABA. The subjects then had their DLPFC GABA content measured by single-voxel proton magnetic spectroscopy. We found that individuals with lower DLPFC GABA showed greater performance degradation with higher load, accounting for 31% of variance, p(corrected) = 0.015. This relationship was component, neurochemical, and brain region specific. DLPFC GABA content did not predict performance sensitivity to other components tested; DLPFC glutamate + glutamine and visual cortical GABA content did not predict load sensitivity. These results confirm the involvement of DLPFC GABA in WM load processing in humans and implicate factors controlling DLPFC GABA content in the neural mechanisms of WM and its impairments. SIGNIFICANCE STATEMENT: This study demonstrated for the first time that the amount of gamma-aminobutryic acid (GABA), the major inhibitory neurotransmitter of the brain, in an individual's prefrontal cortex predicts working memory (WM) task performance. Given that WM is required for many of the most characteristic cognitive and behavioral capabilities in humans, this finding could have a significant impact on our understanding of the neural basis of complex human behavior. Furthermore, this finding suggests that efforts to preserve or increase brain GABA levels could be fruitful in remediating WM-related deficits associated with neuropsychiatric conditions.

Delay Period Activity of the Substantia Nigra during Proactive Control of Response Selection as Determined by a Novel fMRI Localization Method.

The ability to proactively control motor responses, particularly to overcome overlearned or automatic actions, is an essential prerequisite for adaptive, goal-oriented behavior. The substantia nigra (SN), an element of the BG, has figured prominently in current models of response selection. However, because of its small size and proximity to functionally distinct subcortical structures, it has been challenging to test the SN's involvement in response selection using conventional in vivo functional neuroimaging approaches. We developed a new fMRI localization method for directly distinguishing, on echo-planar images, the SN BOLD signal from that of neighboring structures, including the subthalamic nucleus (STN). Using this method, we tested the hypothesis that the SN supports the proactive control of response selection. We acquired high-resolution EPI volumes at 3 T from 16 healthy participants while they completed the Preparing to Overcome Prepotency task of proactive control. There was significantly elevated delay period signal selectively during high- compared with low-control trials in the SN. The STN did not show delay period activity in either condition. SN delay period signal was significantly inversely associated with task performance RTs across participants. These results suggest that our method offers a novel means for measuring SN BOLD responses, provides unique evidence of SN involvement in cognitive control in humans, and suggests a novel mechanism for proactive response selection.