The metabolic heterogeneity, and metabolic interplay between cells have been known as significant contributors to disease treatment resistance. However, with the lack of a mature high-throughput single cell metabolomics technology, we are yet to establish systematic understanding of the intra-tissue metabolic heterogeneity and cooperative mechanisms. To mitigate this knowledge gap, we developed a novel computational method, namely scFEA (single cell Flux Estimation Analysis), to infer cell-wise fluxome from single cell RNA-sequencing (scRNA-seq) data. scFEA is empowered by a systematically reconstructed human metabolic map as a factor graph, a novel probabilistic model to leverage the flux balance constraints on scRNA-seq data, and a novel graph neural network based optimization solver. The intricate information cascade from transcriptome to metabolome was captured using multi-layer neural networks to capitulate the non-linear dependency between enzymatic gene expressions and reaction rates. We experimentally validated scFEA by generating an scRNA-seq dataset with matched metabolomics data on cells of perturbed oxygen and genetic conditions. Application of scFEA on this dataset demonstrated the consistency between predicted flux and the observed variation of metabolite abundance in the matched metabolomics data. We also applied scFEA on five publicly available scRNA-seq and spatial transcriptomics datasets and identified context and cell group specific metabolic variations. The cell-wise fluxome predicted by scFEA empowers a series of downstream analysis including identification of metabolic modules or cell groups that share common metabolic variations, sensitivity evaluation of enzymes with regards to their impact on the whole metabolic flux, and inference of cell-tissue and cell-cell metabolic communications.

Most patients with pancreatic adenocarcinoma (PDAC) suffer cachexia; some do not. To model heterogeneity, we used patient-derived orthotopic xenografts. These phenocopied donor weight loss. Furthermore, muscle wasting correlated with mortality and murine IL-6, and human IL-6 associated with the greatest murine cachexia. In cell culture and mice, PDAC cells elicited adipocyte IL-6 expression and IL-6 plus IL-6 receptor (IL6R) in myocytes and blood. PDAC induced adipocyte lipolysis and muscle steatosis, dysmetabolism, and wasting. Depletion of IL-6 from malignant cells halved adipose wasting and abolished myosteatosis, dysmetabolism, and atrophy. In culture, adipocyte lipolysis required soluble (s)IL6R, while IL-6, sIL6R, or palmitate induced myotube atrophy. PDAC cells activated adipocytes to induce myotube wasting and activated myotubes to induce adipocyte lipolysis. Thus, PDAC cachexia results from tissue crosstalk via a feed-forward, IL-6 trans-signaling loop. Malignant cells signal via IL-6 to muscle and fat, muscle to fat via sIL6R, and fat to muscle via lipids and IL-6, all targetable mechanisms for treatment of cachexia.

The salient features of this study are that SLC6A14 is markedly up-regulated in pancreatic cancer and that pharmacological blockade of this transporter interferes with amino acid nutrition and reduces growth and proliferation of pancreatic cancer cells. These findings identify SLC6A14 as a novel druggable target for pancreatic cancer.

AimsIn addition to giving optimal medical and device therapy, promoting self‐care of chronic heart failure (CHF) patients also plays an important role in comprehensive disease management for better outcomes. The study was aimed to investigate whether short message service (SMS) would help to improve death or readmission‐free survival and self‐care behaviour in CHF patients.Methods and resultsThis was a randomized controlled trial. Between December 2011 and September 2015, patients admitted with decompensated CHF in a tertiary referral hospital who fulfilled the inclusion criteria were enrolled and randomized to receive SMS, structured telephone support (STS), or usual care after discharge. All patients were followed up to 180 days after discharge by phone call or clinic visit. Primary endpoint was the 180 day composite event, defined as all‐cause mortality or readmission. Secondary endpoints included self‐care behaviour and quality of life. Seven hundred sixty‐seven patients (61 ± 15 years, 56.5% male) were finally randomized to receive SMS (n = 252), STS (n = 255), or usual care (n = 260). Baseline characteristics were similar among the three groups. Five hundred twenty‐five (68.4%) patients were in New York Heart Association Class III or IV, and 472 (61.5%) patients had an ejection fraction of <50%. During a 180 day follow‐up, 76 (9.9%) patients died and 274 (35.7%) patients experienced at least one readmission. In a short‐term follow‐up of 30 days, there was no difference in mortality and the composite endpoint among the three groups (SMS vs. STS vs. usual care: 2.8% vs. 3.1% vs. 3.8% for mortality, P = 0.786; 12.3% vs. 14.5% vs. 15.4% for the composite endpoint, P = 0.588). The 180 day composite event rate was significantly lower in the SMS and STS groups (50.4% vs. 41.3% and 36.5%, both P < 0.05) than in the usual care group, but no difference was observed between the two phone‐based intervention groups (P = 0.268). Although there was no difference between the two groups, better self‐care behaviour was reported in the SMS and STS groups than in the control group (medication compliance, 78.9% vs. 81.4% vs. 69.5%, P = 0.011; water restriction, 70.8% vs. 74.5% vs. 61.5%, P = 0.013). Quality‐of‐life score was similar among the three groups at 180 days (P = 0.526).ConclusionsIn CHF patients, post‐discharge SMS, which appeared as efficient as STS, reduced the 180 day composite event and improved self‐care behaviour. SMS intervention could be integrated into CHF management.