Yin-and-yang bifurcation of opioidergic circuits for descending analgesia at the midbrain of the mouse.

In the descending analgesia pathway, opioids are known to disinhibit the projections from the periaqueductal gray (PAG) to the rostral ventromedial medulla (RVM), leading to suppression of pain signals at the spinal cord level. The locus coeruleus (LC) has been proposed to engage in the descending pathway through noradrenergic inputs to the spinal cord. Nevertheless, how the LC is integrated in the descending analgesia circuit has remained unknown. Here, we show that the opioidergic analgesia pathway is bifurcated in structure and function at the PAG. A knockout as well as a PAG-specific knockdown of phospholipase C ß4 (PLCß4), a signaling molecule for G protein-coupled receptors, enhanced swim stress-induced and morphine-induced analgesia in mice. Immunostaining after simultaneous retrograde labeling from the RVM and the LC revealed two mutually exclusive neuronal populations at the PAG, each projecting either to the LC or the RVM, with PLCß4 expression only in the PAG-LC projecting cells that provide a direct synaptic input to LC-spinal cord (SC) projection neurons. The PAG-LC projection neurons in wild-type mice turned quiescent in response to opiates, but remained active in the PLCß4 mutant, suggesting a possibility that an increased adrenergic function induced by the persistent PAG-LC activity underlies the enhanced opioid analgesia in the mutant. Indeed, the enhanced analgesia in the mutant was reversed by blocking α2-noradrenergic receptors. These findings indicate that opioids suppress descending analgesia through the PAG-LC pathway, while enhancing it through the PAG-RVM pathway, i.e., two distinct pathways with opposing effects on opioid analgesia. These results point to a therapeutic target in pain control.

Proteomic approach reveals FKBP4 and S100A9 as potential prediction markers of therapeutic response to neoadjuvant chemotherapy in patients with breast cancer.

Although doxorubicin (Doxo) and docetaxel (Docet) in combination are widely used in treatment regimens for a broad spectrum of breast cancer patients, a major obstacle has emerged in that some patients are intrinsically resistant to these chemotherapeutics. Our study aimed to discover potential prediction markers of drug resistance in needle-biopsied tissues of breast cancer patients prior to neoadjuvant chemotherapy. Tissues collected before chemotherapy were analyzed by mass spectrometry. A total of 2,331 proteins were identified and comparatively quantified between drug sensitive (DS) and drug resistant (DR) patient groups by spectral count. Of them, 298 proteins were differentially expressed by more than 1.5-fold. Some of the differentially expressed proteins (DEPs) were further confirmed by Western blotting. Bioinformatic analysis revealed that the DEPs were largely associated with drug metabolism, acute phase response signaling, and fatty acid elongation in mitochondria. Clinical validation of two selected proteins by immunohistochemistry found that FKBP4 and S100A9 might be putative prediction markers in discriminating the DR group from the DS group of breast cancer patients. The results demonstrate that a quantitative proteomics/bioinformatics approach is useful for discovering prediction markers of drug resistance, and possibly for the development of a new therapeutic strategy.