Myofibroblasts are a main cell-type of collagen-producing cells during tissue fibrosis, but their origins remains controversial. While bone marrow-derived myofibroblasts in renal fibrosis has been reported, the cell origin and mechanisms regulating their transition into myofibroblasts remain undefined. In the present study, cell lineage tracing studies by adoptive transfer of GFP+ or dye-labelled macrophages identified that monocyte/macrophages from bone marrow can give rise to myofibroblasts via the process of macrophage-myofibroblast transition (MMT) in a mouse model of unilateral ureteric obstruction. The MMT cells were a major source of collagen-producing fibroblasts in the fibrosing kidney, accounting for more than 60% of α-SMA+ myofibroblasts. The MMT process occurred predominantly within M2-type macrophages and was regulated by TGF-β/Smad3 signalling as deletion of Smad3 in the bone marrow compartment of GFP+ chimeric mice prevented the M2 macrophage transition into the MMT cells and progressive renal fibrosis. In vitro studies in Smad3 null bone marrow macrophages also showed that Smad3 was required for TGF-β1-induced MMT and collagen production. In conclusion, we have demonstrated that bone marrow-derived fibroblasts originate from the monocyte/macrophage population via a process of MMT. This process contributes to progressive renal tissue fibrosis and is regulated by TGF-β/Smad3 signalling.

Background While enumeration of circulating tumor cells (CTCs) has shown some clinical value, the pool of CTCs contains a mixture of cells which contains additional information that can be extracted. Our group sub-classified CTCs by shape features focusing on nuclear size and related this to clinical information. Methods A total of 148 blood samples were obtained from 57 PC patients across the spectrum of metastatic states: no metastasis, non-visceral metastasis, and visceral metastasis. CTCs captured and enumerated on NanoVelcro Chips were subjected to pathologic review including nuclear size. The distribution of nuclear sizes was analyzed using a Gaussian Mixture Model. Correlations were made between CTC subpopulations and metastatic status. Results Statistical modeling of nuclear size distribution revealed 3 distinct subpopulations: large-nuclear (lnCTC), small-nuclear (snCTC), and very-small-nuclear CTCs (vsnCTCs). snCTC + vsnCTC identified patients with metastatic disease. vsnCTC counts alone, however, were elevated in patients with visceral metastases when compared to those without (0.36 ± 0.69 vs. 1.95 ± 3.77 cells/mL blood, p < 0.001). Serial enumerations suggested the emergence of vsnCTCs occurred prior to the detection of visceral metastases. Conclusions There are morphologic subsets of CTCs that can be identified by fundamental pathologic approaches, such as nuclear size measurement. This observational study strongly suggests that they contain relevant information on disease status. In particular, the detection of vsnCTCs correlated with the presence of visceral metastases and should be formally explored as a putative blood-borne biomarker to identify patients at risk for developing this clinical evolution of PC.

Motivation: Protein domains are subunits that can fold and evolve independently. Identification of domain boundary locations is often the first step in protein folding and function annotations. Most of the current methods deduce domain boundaries by sequence-based analysis, which has low accuracy. There is no efficient method for predicting discontinuous domains that consist of segments from separated sequence regions. As template-based methods are most efficient for protein 3D structure modeling, combining multiple threading alignment information should increase the accuracy and reliability of computational domain predictions.Result: We developed a new protein domain predictor, ThreaDom, which deduces domain boundary locations based on multiple threading alignments. The core of the method development is the derivation of a domain conservation score that combines information from template domain structures and terminal and internal alignment gaps. Tested on 630 non-redundant sequences, without using homologous templates, ThreaDom generates correct single- and multi-domain classifications in 81% of cases, where 78% have the domain linker assigned within ±20 residues. In a second test on 486 proteins with discontinuous domains, ThreaDom achieves an average precision 84% and recall 65% in domain boundary prediction. Finally, ThreaDom was examined on 56 targets from CASP8 and had a domain overlap rate 73, 87 and 85% with the target for Free Modeling, Hard multiple-domain and discontinuous domain proteins, respectively, which are significantly higher than most domain predictors in the CASP8. Similar results were achieved on the targets from the most recently CASP9 and CASP10 experiments.Availability: http://zhanglab.ccmb.med.umich.edu/ThreaDom/.Contact: zhng@umich.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Colorectal cancer (CRC) represents the third most common cancer in males and second in females worldwide. Here, we performed a quantitative 8-plex iTRAQ proteomics analysis of the secreted proteins from five colonic fibroblast cultures and three colon cancer epithelial cell lines. We identified 1114 proteins at 0% FDR, including 587 potential secreted proteins. We further recognized 116 fibroblast-enriched proteins which were significantly associated with cell movement, angiogenesis, proliferation and wound healing, and 44 epithelial cell-enriched proteins. By interrogation of Oncomine database, we found that 20 and 8 fibroblast-enriched proteins were up- and downregulated in CRC, respectively. Western blots confirmed the fibroblast-specific secretion of filamin C, COL6A3, COL4A1 and spondin-2. Upregulated mRNA and stroma expression of COL6A3 in CRC, which were revealed by Oncomine analyses and tissue-microarray-immunohistochemistry, indicated poor prognosis. COL6A3 expression was significantly associated with Dukes stage, T stage, stage, recurrence and smoking status. Circulating plasma COL6A3 in CRC patients was upregulated significantly comparing with healthy peoples. Receiver operating characteristic curve analysis revealed that COL6A3 has better predictive performance for CRC with an area under the curve of 0.885 and the best sensitivity/specificity of 92.9%/81.3%. Thus we demonstrated that COL6A3 was a potential diagnosis and prognosis marker of CRC.

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