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Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear.Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA-seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease-free status was the primary endpoint assessed.SSIGN and RS were calculated for 428 patients with non-metastatic ccRCC. SSIGN low-, intermediate-, and high-risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3-year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease-free status (sub-distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00-1.43)], p = 0.05). By risk groups, RS further risk stratified the SSIGN intermediate-risk group (sHR 2.22 [95% CI 1.10-4.50], p = 0.03). SSIGN intermediate-risk patients with low and high RS had a 3-year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination.Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate-risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted.

BACKGROUND & AIMSPrimary sclerosing cholangitis (PSC) is a rare chronic cholestatic liver disease characterized by multi-focal bile duct strictures. To date, underlying molecular mechanisms of PSC remain unclear and therapeutic options for PSC patients are limited. We performed cell-free messenger RNA (cf-mRNA) next generation sequencing (RNA-Seq) to characterize the circulating transcriptome of PSC and non-invasively investigate potentially bioactive signals that are associated with PSC.METHODSSerum cf-mRNA profiles were compared among 50 individuals with PSC, 20 healthy controls, and 235 individuals with non-alcoholic fatty liver disease (NAFLD). Tissue and cell type-of-origin genes that are dysregulated in subjects with PSC were evaluated. Subsequently, diagnostic classifiers were built using PSC dysregulated cf-mRNA genes.RESULTSDifferential expression analysis of the cf-mRNA transcriptomes of PSC and healthy controls resulted in identification of 1407 dysregulated genes. Furthermore, differentially expressed genes between PSC and the liver diseases (NAFL and Non-Alcohol Steatohepatitis (NASH)) or healthy controls shared common genes known to be involved in liver pathophysiology. In particular, genes from liver- and specific cell type-origin, including hepatocyte, hepatic stellate cells and Kupffer cells, were highly abundant in cf-mRNA of subjects with PSC. Gene cluster analysis revealed that liver-specific genes dysregulated in PSC form a distinct cluster which corresponded to a subset of the PSC subject population. Finally, we developed a cf-mRNA classifier using liver-specific genes which discriminated PSC from healthy control subjects using gene transcripts of liver origin.CONCLUSIONSBlood-based whole transcriptome cf-mRNA profiling revealed high abundance of liver-specific genes in PSC subject sera which may be used to diagnose PSC patients. We identified several unique cf-mRNA profiles of subjects with PSC. These findings may also have utility for non-invasive molecular stratification of subjects with PSC for pharmacotherapy safety and response studies.Graphical Abstract

Inflammatory and immune responses are essential and dynamic biological processes that protect the body against acute and chronic adverse stimuli. While conventional protein markers have been used to evaluate systemic inflammatory response, the immunological response to stimulation is complex and involves modulation of a large set of genes and interacting signaling pathways of innate and adaptive immune systems. Therefore, there is a need for a non-invasive tool that can comprehensively evaluate and monitor molecular dysregulations associated with inflammatory and immune responses. Here we utilized cell-free messenger RNA (cf-mRNA) RNA-Seq whole transcriptome profiling to assess lipopolysaccharide (LPS) induced and JAK inhibitor modulated inflammatory and immune responses in mouse plasma samples. Considering that, both organspecific recruitment of immune cells and organ resident bespoke immune cells contributes to restoration of organ homeostasis, we also examined LPS-induced gene-expression dysregulation of multiple organs to shed light on organ crosstalk. Cf-mRNA profiling displayed a pattern of systemic immune responses elicited by LPS and dysregulation of associated pathways. Moreover, attenuation of several inflammatory pathways, including STAT and interferon pathways, were observed following the treatment of JAK inhibitor. Lastly, we identified the dysregulation of liverspecific transcripts in cf-mRNA which reflected changes in the gene-expression pattern in this biological compartment. Collectively, using a preclinical model, we demonstrated the potential of plasma cf-mRNA profiling for systemic and organ-specific characterization of drug-induced molecular alterations that are associated with inflammatory and immune responses.Abstract Figure