Clinical trial in a dish using iPSCs shows lovastatin improves endothelial dysfunction and cellular cross-talk in LMNA cardiomyopathy.

Mutations in LMNA, the gene that encodes lamin A and C, causes LMNA-related dilated cardiomyopathy (DCM) or cardiolaminopathy. LMNA is expressed in endothelial cells (ECs); however, little is known about the EC-specific phenotype of LMNA-related DCM. Here, we studied a family affected by DCM due to a frameshift variant in LMNA Human induced pluripotent stem cell (iPSC)-derived ECs were generated from patients with LMNA-related DCM and phenotypically characterized. Patients with LMNA-related DCM exhibited clinical endothelial dysfunction, and their iPSC-ECs showed decreased functionality as seen by impaired angiogenesis and nitric oxide (NO) production. Moreover, genome-edited isogenic iPSC lines recapitulated the EC disease phenotype in which LMNA-corrected iPSC-ECs showed restoration of EC function. Simultaneous profiling of chromatin accessibility and gene expression dynamics by combining assay for transposase-accessible chromatin using sequencing (ATAC-seq) and RNA sequencing (RNA-seq) as well as loss-of-function studies identified Krüppel-like factor 2 (KLF2) as a potential transcription factor responsible for the EC dysfunction. Gain-of-function studies showed that treatment of LMNA iPSC-ECs with KLF2 agonists, including lovastatin, rescued the EC dysfunction. Patients with LMNA-related DCM treated with lovastatin showed improvements in clinical endothelial dysfunction as indicated by increased reactive hyperemia index. Furthermore, iPSC-derived cardiomyocytes (iPSC-CMs) from patients exhibiting the DCM phenotype showed improvement in CM function when cocultured with iPSC-ECs and lovastatin. These results suggest that impaired cross-talk between ECs and CMs can contribute to the pathogenesis of LMNA-related DCM, and statin may be an effective therapy for vascular dysfunction in patients with cardiolaminopathy.

HIF1α Regulates Early Metabolic Changes due to Activation of Innate Immunity in Nuclear Reprogramming.

Innate immune signaling has recently been shown to play an important role in nuclear reprogramming, by altering the epigenetic landscape and thereby facilitating transcription. However, the mechanisms that link innate immune activation and metabolic regulation in pluripotent stem cells remain poorly defined, particularly with regard to key molecular components. In this study, we show that hypoxia-inducible factor 1α (HIF1α), a central regulator of adaptation to limiting oxygen tension, is an unexpected but crucial regulator of innate immune-mediated nuclear reprogramming. HIF1α is dramatically upregulated as a consequence of Toll-like receptor 3 (TLR3) signaling and is necessary for efficient induction of pluripotency and transdifferentiation. Bioenergetics studies reveal that HIF1α regulates the reconfiguration of innate immune-mediated reprogramming through its well-established role in throwing a glycolytic switch. We believe that results from these studies can help us better understand the influence of immune signaling in tissue regeneration and lead to new therapeutic strategies.

Paying the Toll in Nuclear Reprogramming.

The ability to reverse lineage-committed cells toward pluripotent stem cells or to another cell type is one of the ultimate goals in regenerative medicine. We recently discovered that activation of innate immunity, through Toll-like receptor 3, is required during this conversion of cell fate by causing global changes in the expression and activity of epigenetic modifiers. Here we discuss, in a comprehensive manner, the recent studies on the role of innate immunity in nuclear reprogramming and transdifferentiation, the underlying mechanisms, and its role in regenerative medicine.

Retinoic Acid Inducible Gene 1 Protein (RIG1)-Like Receptor Pathway Is Required for Efficient Nuclear Reprogramming.

We have revealed a critical role for innate immune signaling in nuclear reprogramming to pluripotency, and in the nuclear reprogramming required for somatic cell transdifferentiation. Activation of innate immune signaling causes global changes in the expression and activity of epigenetic modifiers to promote epigenetic plasticity. In our previous articles, we focused on the role of toll-like receptor 3 (TLR3) in this signaling pathway. Here, we define the role of another innate immunity pathway known to participate in response to viral RNA, the retinoic acid-inducible gene 1 receptor (RIG-1)-like receptor (RLR) pathway. This pathway is represented by the sensors of viral RNA, RIG-1, LGP2, and melanoma differentiation-associated protein 5 (MDA5). We first found that TLR3 deficiency only causes a partial inhibition of nuclear reprogramming to pluripotency in mouse tail-tip fibroblasts, which motivated us to determine the contribution of RLR. We found that knockdown of interferon beta promoter stimulator 1, the common adaptor protein for the RLR family, substantially reduced nuclear reprogramming induced by retroviral or by modified messenger RNA expression of Oct 4, Sox2, KLF4, and c-MYC (OSKM). Importantly, a double knockdown of both RLR and TLR3 pathway led to a further decrease in induced pluripotent stem cell (iPSC) colonies suggesting an additive effect of both these pathways on nuclear reprogramming. Furthermore, in murine embryonic fibroblasts expressing a doxycycline (dox)-inducible cassette of the genes encoding OSKM, an RLR agonist increased the yield of iPSCs. Similarly, the RLR agonist enhanced nuclear reprogramming by cell permeant peptides of the Yamanaka factors. Finally, in the dox-inducible system, RLR activation promotes activating histone marks in the promoter region of pluripotency genes. To conclude, innate immune signaling mediated by RLR plays a critical role in nuclear reprogramming. Manipulation of innate immune signaling may facilitate nuclear reprogramming to achieve pluripotency. Stem Cells 2017;35:1197-1207.

Targeted serum metabolite profiling and sequential metabolite ratio analysis for colorectal cancer progression monitoring.

Colorectal cancer (CRC) is one of the most prevalent cancers worldwide and a major cause of human morbidity and mortality. In addition to early detection, close monitoring of disease progression in CRC can be critical for patient prognosis and treatment decisions. Efforts have been made to develop new methods for improved early detection and patient monitoring; however, research focused on CRC surveillance for treatment response and disease recurrence using metabolomics has yet to be reported. In this proof of concept study, we applied a targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolic profiling approach focused on sequential metabolite ratio analysis of serial serum samples to monitor disease progression from 20 CRC patients. The use of serial samples reduces patient to patient metabolic variability. A partial least squares-discriminant analysis (PLS-DA) model using a panel of five metabolites (succinate, N2, N2-dimethylguanosine, adenine, citraconic acid, and 1-methylguanosine) was established, and excellent model performance (sensitivity = 0.83, specificity = 0.94, area under the receiver operator characteristic curve (AUROC) = 0.91 was obtained, which is superior to the traditional CRC monitoring marker carcinoembryonic antigen (sensitivity = 0.75, specificity = 0.76, AUROC = 0.80). Monte Carlo cross validation was applied, and the robustness of our model was clearly observed by the separation of true classification models from the random permutation models. Our results suggest the potential utility of metabolic profiling for CRC disease monitoring.

Colorectal cancer detection using targeted serum metabolic profiling.

Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.