Comprehensive Proteomic Analysis Reveals Distinct Features and a Diagnostic Biomarker Panel for Early Pregnancy Loss in Histological Subtypes.

Early pregnancy loss (EPL) is a common event in human reproduction and is classified into histological subtypes such as hydropic abortion (HA) and hydatidiform moles, including complete hydatidiform moles (CHMs) and partial hydatidiform moles (PHMs). However, accurate diagnosis and improved patient management remain challenging due to high rates of misdiagnosis and diverse prognostic risks. Therefore, diagnostic biomarkers for EPL are urgently needed. Our study aimed to identify biomarkers for EPL through comprehensive proteomic analysis. Ten CHMs, six PHMs, ten HAs, and 10 normal control products of conception were used to obtain a proteomic portrait. Parallel reaction monitoring-targeted proteomic and regression analyses were used to verify and select the diagnostic signatures. Finally, 14 proteins were selected and a panel of diagnostic classifiers (DLK1, SPTB/COL21A1, and SAR1A) was built to represent the CHM, PHM, and normal control groups (area under the receiver operating characteristic curve = 0.900, 0.804/0.885, and 0.991, respectively). This high diagnostic power was further validated in another independent cohort (n = 148) by immunohistochemistry (n = 120) and Western blot analyses (n = 28). The protein SPTB was selected for further biological behavior experiments in vitro. Our data suggest that SPTB maintains trophoblast cell proliferation, angiogenesis, cell motility, and the cytoskeleton network. This study provides a comprehensive proteomic portrait and identifies potential diagnostic biomarkers. These findings enhance our understanding of EPL pathogenesis and offer novel targets for diagnosis and therapeutic interventions.

Metabolomics, Transcriptome and Single-Cell RNA Sequencing Analysis of the Metabolic Heterogeneity between Oral Cancer Stem Cells and Differentiated Cancer Cells.

Understanding the distinct metabolic characteristics of cancer stem cells (CSC) may allow us to better cope with the clinical challenges associated with them. In this study, OSCC cell lines (CAL27 and HSC3) and multicellular tumor spheroid (MCTS) models were used to generate CSC-like cells. Quasi-targeted metabolomics and RNA sequencing were used to explore altered metabolites and metabolism-related genes. Pathview was used to display the metabolites and transcriptome data in a KEGG pathway. The single-cell RNA sequencing data of six patients with oral cancer were analyzed to characterize in vivo CSC metabolism. The results showed that 19 metabolites (phosphoethanolamine, carbamoylphosphate, etc.) were upregulated and 109 metabolites (2-aminooctanoic acid, 7-ketocholesterol, etc.) were downregulated in both MCTS cells. Integration pathway analysis revealed altered activity in energy production (glycolysis, citric cycle, fatty acid oxidation), macromolecular synthesis (purine/pyrimidine metabolism, glycerophospholipids metabolism) and redox control (glutathione metabolism). Single-cell RNA sequencing analysis confirmed altered glycolysis, glutathione and glycerophospholipid metabolism in in vivo CSC. We concluded that CSCs are metabolically inactive compared with differentiated cancer cells. Thus, oral CSCs may resist current metabolic-related drugs. Our result may be helpful in developing better therapeutic strategies against CSC.

Single-cell RNA sequencing highlights epithelial and microenvironmental heterogeneity in malignant progression of pancreatic ductal adenocarcinoma.

Intraductal papillary mucinous neoplasms (IPMNs) of the pancreas are bona fide precursor lesions of pancreatic ductal adenocarcinoma (PDAC). Single-cell transcriptomics provides a unique perspective for dissecting the epithelial and microenvironmental heterogeneity that accompanies progression from benign IPMNs to invasive PDAC. Single-cell RNA sequencing was performed through droplet-based sequencing on 35 693 cells from three high-grade IPMNs and two IPMN-derived PDACs (all surgically resected). Analysis of single-cell transcriptomes revealed heterogeneous alterations within the epithelium and the tumor microenvironment during the progression of noninvasive dysplasia to invasive cancer. For epithelial cells, we identified acinar-ductal cells and isthmus-pit cells enriched in IPMN lesions and profiled three types of PDAC-unique ductal cells. Notably, a proinflammatory immune component was distinctly observed in IPMNs, comprising CD4+ T cells, CD8+ T cells, and B cells, whereas M2 macrophages were significantly accumulated in PDAC. Through the analysis of cellular communication, the osteopontin gene (SPP1)-CD44 pathway between macrophages and epithelial cells were particularly strengthened in the PDAC group. Further prognostic analysis revealed that SPP1 is a biomarker of IPMN carcinogenesis for surveillance. This study demonstrates the ability to perform high-resolution profiling of single cellular transcriptomes during the progression of high-grade IPMNs to cancer. Notably, single-cell analysis provides an unparalleled insight into both epithelial and microenvironmental heterogeneity associated with early cancer pathogenesis and provides practical markers for surveillance and targets for cancer interception.

ARIH1 activates STING-mediated T-cell activation and sensitizes tumors to immune checkpoint blockade.

Despite advances in cancer treatment, immune checkpoint blockade (ICB) only achieves complete response in some patients, illustrating the need to identify resistance mechanisms. Using an ICB-insensitive tumor model, here we discover cisplatin enhances the anti-tumor effect of PD-L1 blockade and upregulates the expression of Ariadne RBR E3 ubiquitin-protein ligase 1 (ARIH1) in tumors. Arih1 overexpression promotes cytotoxic T cell infiltration, inhibits tumor growth, and potentiates PD-L1 blockade. ARIH1 mediates ubiquitination and degradation of DNA-PKcs to trigger activation of the STING pathway, which is blocked by the phospho-mimetic mutant T68E/S213D of cGAS protein. Using a high-throughput drug screen, we further identify that ACY738, less cytotoxic than cisplatin, effectively upregulates ARIH1 and activates STING signaling, sensitizing tumors to PD-L1 blockade. Our findings delineate a mechanism that tumors mediate ICB resistance through the loss of ARIH1 and ARIH1-DNA-PKcs-STING signaling and indicate that activating ARIH1 is an effective strategy to improve the efficacy of cancer immunotherapy.

Detection of aberrant splicing events in RNA-seq data using FRASER.

Aberrant splicing is a major cause of rare diseases.  However, its prediction from genome sequence alone remains in most cases inconclusive. Recently, RNA sequencing has proven to be an effective complementary avenue to detect aberrant splicing. Here, we develop FRASER, an algorithm to detect aberrant splicing from RNA sequencing data. Unlike existing methods, FRASER captures not only alternative splicing but also intron retention events. This typically doubles the number of detected aberrant events and identified a pathogenic intron retention in MCOLN1 causing mucolipidosis. FRASER automatically controls for latent confounders, which are widespread and affect sensitivity substantially. Moreover, FRASER is based on a count distribution and multiple testing correction, thus reducing the number of calls by two orders of magnitude over commonly applied z score cutoffs, with a minor loss of sensitivity. Applying FRASER to rare disease diagnostics is demonstrated by reprioritizing a pathogenic aberrant exon truncation in TAZ from a published dataset. FRASER is easy to use and freely available.