Citations

Background and Aims: Acute-on-chronic liver failure (ACLF) is a complication of cirrhosis characterized by multiple organ failure and high short-term mortality. The pathophysiology of ACLF involves elevated systemic inflammation leading to organ failure, along with immune dysfunction that heightens susceptibility to bacterial infections. However, it is unclear how these aspects are associated with recovery and nonrecovery in ACLF. Approach and Results: Here, we mapped the single-cell transcriptome of circulating immune cells from patients with ACLF and acute decompensated (AD) cirrhosis and healthy individuals. We further interrogate how these findings, as well as immunometabolic and functional profiles, associate with ACLF-recovery (ACLF-R) or nonrecovery (ACLF-NR). Our analysis unveiled 2 distinct states of classical monocytes (cMons). Hereto, ACLF-R cMons were characterized by transcripts associated with immune and stress tolerance, including anti-inflammatory genes such as RETN and LGALS1. Additional metabolomic and functional validation experiments implicated an elevated oxidative phosphorylation metabolic program as well as an impaired ACLF-R cMon functionality. Interestingly, we observed a common stress-induced tolerant state, oxidative phosphorylation program, and blunted activation among lymphoid populations in patients with ACLF-R. Conversely, ACLF-NR cMon featured elevated expression of inflammatory and stress response genes such as VIM, LGALS2, and TREM1, along with blunted metabolic activity and increased functionality. Conclusions: This study identifies distinct immunometabolic cellular states that contribute to disease outcomes in patients with ACLF. Our findings provide valuable insights into the pathogenesis of ACLF, shedding light on factors driving either recovery or nonrecovery phenotypes, which may be harnessed as potential therapeutic targets in the future.

Abstract Molecular drivers of metastasis in patients with high-risk localized prostate cancer are poorly understood. Therefore, we aim to study molecular drivers of metastatic progression in patients with high-risk prostate cancer. A retrospective matched case-control study of two clinico-pathologically identical groups of patients with high-risk prostate cancer was undertaken. One group developed metastatic recurrence (n = 19) while the other did not (n = 25). The primary index tumor was identified by a uro-pathologist, followed by DNA and RNA extraction for somatic copy-number aberration (SCNA) analysis and whole-transcriptome gene expression analysis. In vitro and in vivo studies included cell line manipulation and xenograft models. The integrative CNA and gene expression analyses identified an increase in Antizyme Inhibitor 1 (AZIN1) gene expression within a focal amplification of 8q22.3, which was associated with metastatic recurrence of patients with high-risk prostate cancer in four independent cohorts. The effects of AZIN1 knockdown were evaluated, due to its therapeutic potential. AZIN1 knockdown effected proliferation and metastatic potential of prostate cancer cells and xenograft models. RNA sequencing after AZIN1 knockdown in prostate cancer cells revealed upregulation of genes coding for collagen subunits. The observed effect on cell migration after AZIN1 knockdown was mimicked when exposing prostate cancer cells to bio-active molecules deriving from COL4A1 and COL4A2. Our integrated CNA and gene expression analysis of primary high-risk prostate cancer identified the AZIN1 gene as a novel driver of metastatic progression, by altering collagen subunit expression. Future research should further investigate its therapeutic potential in preventing metastatic recurrence. Implications: AZIN1 was identified as driver of metastatic progression in high-risk prostate cancer through matrikine regulation.

AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast cancer.