Bile acids and liver cancer: Liver cancer is a leading cause of cancer-related deaths in the United States. The composition of the gut microbiome influences many human diseases, including liver inflammatory disorders. Ma et al. found that commensal gut bacteria can recruit the immune system to control the growth of liver tumors in mice (see the Perspective by Hartmann and Kronenberg). Clostridium species modified bile acids to signal liver sinusoidal endothelial cells to produce the chemokine CXCL16. This recruited natural killer T (NKT) immune cells to perform antitumor surveillance of the liver. Growth of both primary and metastatic cancer was reduced by NKT cell–driven killing. Science , this issue p. eaan5931 ; see also p. 858

T-cell exhaustion denotes a hypofunctional state of T lymphocytes commonly found in cancer, but how tumor cells drive T-cell exhaustion remains elusive. Here, we find T-cell exhaustion linked to overall survival in 675 hepatocellular carcinoma (HCC) patients with diverse ethnicities and etiologies. Integrative omics analyses uncover oncogenic reprograming of HCC methionine recycling with elevated 5-methylthioadenosine (MTA) and S-adenosylmethionine (SAM) to be tightly linked to T-cell exhaustion. SAM and MTA induce T-cell dysfunction in vitro. Moreover, CRISPR-Cas9-mediated deletion of MAT2A, a key SAM producing enzyme, results in an inhibition of T-cell dysfunction and HCC growth in mice. Thus, reprogramming of tumor methionine metabolism may be a viable therapeutic strategy to improve HCC immunity.

The long-term health outcome of prenatal exposure to arsenic has been associated with increased mortality in human populations. In this study, the extent to which maternal arsenic exposure impacts gene expression in the newborn was addressed. We monitored gene expression profiles in a population of newborns whose mothers experienced varying levels of arsenic exposure during pregnancy. Through the application of machine learning–based two-class prediction algorithms, we identified expression signatures from babies born to arsenic-unexposed and -exposed mothers that were highly predictive of prenatal arsenic exposure in a subsequent test population. Furthermore, 11 transcripts were identified that captured the maximal predictive capacity to classify prenatal arsenic exposure. Network analysis of the arsenic-modulated transcripts identified the activation of extensive molecular networks that are indicative of stress, inflammation, metal exposure, and apoptosis in the newborn. Exposure to arsenic is an important health hazard both in the United States and around the world, and is associated with increased risk for several types of cancer and other chronic diseases. These studies clearly demonstrate the robust impact of a mother's arsenic consumption on fetal gene expression as evidenced by transcript levels in newborn cord blood. Arsenic is an environmental pollutant and known human carcinogen. Chronic exposure to arsenic-contaminated water is an important public health hazard around the world, including the United States, with millions exposed to drinking water with levels that far exceed World Health Organization (WHO) guidelines. Given the implications of prenatal exposure on human health and the known public health hazard of chronic arsenic exposure, this study was aimed at establishing the extent to which maternal arsenic exposure in a human population affects newborn gene expression. The authors show that prenatal arsenic exposure in a human population results in alarming gene expression changes in newborn babies. The gene expression changes monitored in babies born to mothers exposed to arsenic during pregnancy are highly predictive of prenatal arsenic exposure in a subsequent test population. The study establishes a subset of just 11 transcripts that captured maximal predictive capability that could prove promising as genetic biomarkers of prenatal arsenic exposure. Pathway analysis of the genome-wide response in the babies exposed to arsenic in utero indicates robust activation of an integrated network of pathways involving NF-κB, inflammation, cell proliferation, stress, and apoptosis. This study contributes to our understanding of biological responses to arsenic exposure.

Intratumor heterogeneity may result from the evolution of tumor cells and their continuous interactions with the tumor microenvironment which collectively drives tumorigenesis. However, an appearance of cellular and molecular heterogeneity creates a challenge to define molecular features linked to tumor malignancy. Here we perform multiregional single-cell RNA sequencing (scRNA-seq) analysis of seven liver cancer patients (four hepatocellular carcinoma, HCC and three intrahepatic cholangiocarcinoma, iCCA). We identify cellular dynamics of malignant cells and their communication networks with tumor-associated immune cells, which are validated using additional scRNA-seq data of 25 HCC and 12 iCCA patients as a stable fingerprint embedded in a malignant ecosystem representing features of tumor aggressiveness. We further validate the top ligand-receptor interaction pairs (i.e., LGALS9-SLC1A5 and SPP1-PTGER4 between tumor cells and macrophages) associated with unique transcriptome in additional 542 HCC patients. Our study unveils stable molecular networks of malignant ecosystems, which may open a path for therapeutic exploration.