Xiaofan Liu

BACKGROUND: Various studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA. METHODS: We first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance. FINDINGS: We identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928). INTERPRETATION: This study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP. FUNDING: National Natural Science Foundation of China, and The National Key Basic Research Program (973 program).

Abstract Small amplitude or short period geomagnetic anomalies known as “tiny wiggles” (TWs) are often hard to identify because of magnetic signal smoothing in the marine record of geomagnetic reversals. We report here the late Miocene record of geomagnetic reversals in the aeolian red clay sediments of Linxia Basin in China that enables us to identify two TWs. We performed magnetostratigraphy dating and used spectral analysis to distinguish orbital cycles in the records of magnetic susceptibility (MS) and sedimentary grain size (GS) and develop an orbitally tuned age model. The presence of two TWs in the study section, that correspond to C5n.2n‐3 and C5r.2r‐1, is confirmed by orbital calibration of our age model through recognition of eccentricity, obliquity and precession in MS and GS records.

ABSTRACT Genes that drive the proliferation, survival, invasion and metastasis of malignant cells have been identified for many human cancers 1–6 . Independent studies have identified cell death pathways that eliminate cells for the good of the organism 7–10 . The coexistence of the cell death pathways with the driver mutations suggest that the cancer driver could be rewired to activate cell death. We have invented a new class of molecules: TCIPs (Transcriptional/Epigenetic Chemical Inducers of Proximity) that recruit the endogenous cancer driver, or a downstream transcription factor, to the promoters of cell death genes thereby activating their expression. To develop this concept, we have focused on diffuse large B cell lymphoma (DLBCL), in which BCL6 is amplified or mutated 11 . BCL6 binds to the promoters of cell death genes and epigenetically suppresses their expression 12 . We produced the first TCIPs by chemically linking BCL6 inhibitors to small molecules that bind transcriptional activators. Several of these molecules robustly kill DLBCL at single-digit nanomolar concentrations, including chemotherapy-resistant, TP53-mutant lines. The dominant gain-of-function approach provided by TCIPs captures the combinatorial specificity inherit to transcription and can thereby accesses new therapeutic space. TCIPs are relatively non-toxic to normal cells and mice, apparently reflecting their need for coincident expression of both target proteins for effective killing. The general TCIP concept has applications in elimination of senescent cells, enhancing expression of therapeutic genes, treatment of diseases produced by haploinsufficiency, and activation of immunogens for immunotherapy.

BACKGROUND: Cell-free RNAs (cfRNAs) can be detected in biofluids and have emerged as valuable disease biomarkers. Accurate identification of the fragmented cfRNA signals, especially those originating from pathological cells, is crucial for understanding their biological functions and clinical value. However, many challenges still need to be addressed for their application, including developing specific analysis methods and translating cfRNA fragments with biological support into clinical applications. RESULTS: We present cfPeak, a novel method combining statistics and machine learning models to detect the fragmented cfRNA signals effectively. When test in real and artificial cfRNA sequencing (cfRNA-seq) data, cfPeak shows an improved performance compared with other applicable methods. We reveal that narrow cfRNA peaks preferentially overlap with protein binding sites, vesicle-sorting sites, structural sites, and novel small non-coding RNAs (sncRNAs). When applied in clinical cohorts, cfPeak identified cfRNA peaks in patients' plasma that enable cancer detection and are informative of cancer types and metastasis. CONCLUSIONS: Our study fills the gap in the current small cfRNA-seq analysis at fragment-scale and builds a bridge to the scientific discovery in cfRNA fragmentomics. We demonstrate the significance of finding low abundant tissue-derived signals in small cfRNA and prove the feasibility for application in liquid biopsy.