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Adipogenesis is essential in in vitro experimentation to assess differentiation capability of stem cells, and therefore, its accurate measurement is important. Quantitative analysis of adipogenic levels, however, is challenging and often susceptible to errors due to non-specific reading or manual estimation by observers. To this end, we developed a novel adipocyte quantification algorithm, named Fast Adipogenesis Tracking System (FATS), based on computer vision libraries. The FATS algorithm is versatile and capable of accurately detecting and quantifying percentage of cells undergoing adipogenic and browning differentiation even under difficult conditions such as the presence of large cell clumps or high cell densities. The algorithm was tested on various cell lines including 3T3-L1 cells, adipose-derived mesenchymal stem cells (ASCs), and induced pluripotent stem cell (iPSC)-derived cells. The FATS algorithm is particularly useful for adipogenic measurement of embryoid bodies derived from pluripotent stem cells and was capable of accurately distinguishing adipogenic cells from false-positive stains. We then demonstrate the effectiveness of the FATS algorithm for screening of nuclear receptor ligands that affect adipogenesis in the high-throughput manner. Together, the FATS offer a universal and automated image-based method to quantify adipocyte differentiation of different cell lines in both standard and high-throughput workflows. Electronic supplementary material The online version of this article (10.1186/s13287-019-1141-0) contains supplementary material, which is available to authorized users.

Obesity increases the risk of hepatocellular carcinoma (HCC), but precise identification and characterization of druggable oncogenic pathways that contribute to the progression of NAFLD to HCC, and hence to the increased incidence and aggressiveness of HCC in obese individuals is lacking. In this regard, we demonstrate that the Indian Hedgehog (Ihh) signaling pathway is upregulated in the fatty livers of mice consuming a high fat diet, and furthermore sustained in HCC tumors specifically within the context of a NAFLD microenvironment. Using a diet-induced mouse model of HCC wherein only obese mice develop HCC, targeted ablation of hepatocyte-secreted Ihh results in a decreased tumor burden and lower grade tumors. Ihh activation regulates the transdifferentiation of ciliated stellate cells and proliferation of Epcam+ ductal cells to promote fibrosis. Mechanistically, increased expression of hitherto uncharacterized effectors of Hh pathway, namely Myc and Tgf-β2 is critical to the observed physiology. This pro-tumorigenic response is driven by increased expression of Wnt5a to effect a poorly-differentiated and invasive tumor phenotype. Wnt5a secreted from activated stellate cells act on Ror2-expressing hepatocytes. We further demonstrate that Wnt5a expression is also elevated in poorly-differentiated HCC cells, suggesting that these ligands are also able to function in an autocrine positive feedback manner to sustain poorly-differentiated tumors. Taken together, our study provides a mechanistic understanding for how Ihh signaling promotes HCC tumorigenesis specifically in obese mice. We propose that therapeutic targeting of the Hh pathway offers benefit for patients with dietary / NAFLD-driven steatotic HCC. Refereed/Peer-reviewed