A Regulatory Circuit Controlling the Dynamics of NFκB cRel Transitions B Cells from Proliferation to Plasma Cell Differentiation.

Humoral immunity depends on efficient activation of B cells and their subsequent differentiation into antibody-secreting cells (ASCs). The transcription factor NFκB cRel is critical for B cell proliferation, but incorporating its known regulatory interactions into a mathematical model of the ASC differentiation circuit prevented ASC generation in simulations. Indeed, experimental ectopic cRel expression blocked ASC differentiation by inhibiting the transcription factor Blimp1, and in wild-type (WT) cells cRel was dynamically repressed during ASC differentiation by Blimp1 binding the Rel locus. Including this bi-stable circuit of mutual cRel-Blimp1 antagonism into a multi-scale model revealed that dynamic repression of cRel controls the switch from B cell proliferation to ASC generation phases and hence the respective cell population dynamics. Our studies provide a mechanistic explanation of how dysregulation of this bi-stable circuit might result in pathologic B cell population phenotypes and thus offer new avenues for diagnostic stratification and treatment.

N-cadherin: A diagnostic marker to help discriminate primary liver carcinomas from extrahepatic carcinomas.

Distinguishing primary liver cancer (PLC), namely hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), from liver metastases is of crucial clinical importance. Histopathology remains the gold standard, but differential diagnosis may be challenging. While absent in most epithelial, the expression of the adherens junction glycoprotein N-cadherin is commonly restricted to neural and mesenchymal cells, or carcinoma cells that undergo the phenomenon of epithelial-to-mesenchymal transition (EMT). However, we recently established N- and E-cadherin expression as hallmarks of normal hepatocytes and cholangiocytes, which are also preserved in HCC and iCCA. Therefore, we hypothesized that E- and/or N-cadherin may distinguish between carcinoma derived from the liver vs carcinoma of other origins. We comprehensively evaluated E- and N-cadherin in 3359 different tumors in a multicenter study using immunohistochemistry and compared our results with previously published 882 cases of PLC, including 570 HCC and 312 iCCA. Most carcinomas showed strong positivity for E-cadherin. Strong N-cadherin positivity was present in HCC and iCCA. However, except for clear cell renal cell carcinoma (23.6% of cases) and thyroid cancer (29.2%), N-cadherin was only in some instances faintly expressed in adenocarcinomas of the gastrointestinal tract (0%-0.5%), lung (7.1%), pancreas (3.9%), gynecological organs (0%-7.4%), breast (2.2%) as well as in urothelial (9.4%) and squamous cell carcinoma (0%-5.6%). As expected, N-cadherin was detected in neuroendocrine tumors (25%-75%), malignant melanoma (46.2%) and malignant mesothelioma (41%). In conclusion, N-cadherin is a useful marker for the distinction of PLC vs liver metastases of extrahepatic carcinomas (P < .01).

NF-κB responds to absolute differences in cytokine concentrations.

Cells receive a wide range of dynamic signaling inputs during immune regulation, but how gene regulatory networks measure such dynamic inputs is not well understood. Here, we used microfluidic single-cell analysis and mathematical modeling to study how the NF-κB pathway responds to immune inputs that vary over time such as increasing, decreasing, or fluctuating cytokine signals. We found that NF-κB activity responded to the absolute difference in cytokine concentration and not to the concentration itself. Our analyses revealed that negative feedback by the regulatory proteins A20 and IκBα enabled differential responses to changes in cytokine dose by providing a short-term memory of previous cytokine concentrations and by continuously resetting kinase cycling and receptor abundance. Investigation of NF-κB target gene expression showed that cells exhibited distinct transcriptional responses under different dynamic cytokine profiles. Our results demonstrate how cells use simple network motifs and transcription factor dynamics to efficiently extract information from complex signaling environments.