Challenges and Opportunities to Updating Prescribing Information for Longstanding Oncology Drugs.

A number of important drugs used to treat cancer-many of which serve as the backbone of modern chemotherapy regimens-have outdated prescribing information in their drug labeling. The Food and Drug Administration is undertaking a pilot project to develop a process and criteria for updating prescribing information for longstanding oncology drugs, based on the breadth of knowledge the cancer community has accumulated with the use of these drugs over time. This article highlights a number of considerations for labeling updates, including selecting priorities for updating; data sources and evidentiary criteria; as well as the risks, challenges, and opportunities for iterative review to ensure prescribing information for oncology drugs remains relevant to current clinical practice

Transforming growth factor beta-regulated gene expression in a mouse mammary gland epithelial cell line

BACKGROUND: Transforming growth factor beta (TGF-β) plays an essential role in a wide array of cellular processes. The most well studied TGF-β response in normal epithelial cells is growth inhibition. In some cell types, TGF-β induces an epithelial to mesenchymal transition (EMT). NMuMG is a nontransformed mouse mammary gland epithelial cell line that exhibits both a growth inhibitory response and an EMT response to TGF-β, rendering NMuMG cells a good model system for studying these TGF-β effects. METHOD: A National Institutes of Aging mouse 15,000 cDNA microarray was used to profile the gene expression of NMuMG cells treated with TGF-β1 for 1, 6, or 24 hours. Data analyses were performed using GenePixPro and GeneSpring software. Selected microarray results were verified by northern analyses. RESULTS: Of the 15,000 genes examined by microarray, 939 were upregulated or downregulated by TGF-β. This represents approximately 10% of the genes examined, minus redundancy. Seven genes previously not known to be regulated by TGF-β at the transcriptional level (Akt and RhoB) or not at all (IQGAP1, mCalpain, actinin α3, Ikki, PP2A-PR53), were identified and their regulation by TGF-β verified by northern blotting. Cell cycle pathway examination demonstrated downregulation of cyclin D(2), c-myc, Id2, p107, E2F5, cyclin A, cyclin B, and cyclin H. Examination of cell adhesion-related genes revealed upregulation of c-Jun, α-actinin, actin, myosin light chain, p120cas catenin (Catns), α-integrin, integrin β5, fibronectin, IQGAP1, and mCalpain. CONCLUSION: Using a cDNA microarray to examine TGF-β-regulated gene expression in NMuMG cells, we have shown regulation of multiple genes that play important roles in cell cycle control and EMT. In addition, we have identified several novel TGF-β-regulated genes that may mediate previously unknown TGF-β functions

Genotype tunes pancreatic ductal adenocarcinoma tissue tension to induce matricellular fibrosis and tumor progression

Fibrosis compromises pancreatic ductal carcinoma (PDAC) treatment and contributes to patient mortality yet anti-stromal therapies are controversial. We found that human PDACs with impaired epithelial transforming growth factor β (TGF-β) signaling have elevated epithelial Stat3 activity and develop a stiffer, matricellular-enriched fibrosis associated with high epithelial tension and shorter patient survival. In several Kras-driven mouse models, both the loss of TGF-β signaling and elevated β1-integrin mechanosignaling engaged a positive feedback loop whereby Stat3 signaling promotes tumor progression by increasing matricellular fibrosis and tissue tension. In contrast, epithelial Stat3 ablation attenuated tumor progression by reducing the stromal stiffening and epithelial contractility induced by loss of TGF-β signaling. In PDAC patient biopsies, higher matricellular protein and activated Stat3 associated with SMAD4 mutation and shorter survival. The findings implicate epithelial tension and matricellular fibrosis in the aggressiveness of SMAD4 mutant pancreatic tumors, and highlight Stat3 and mechanics as key drivers of this phenotype