Serum Proteomics Identifies Biomarkers Associated With the Pathogenesis of Idiopathic Pulmonary Fibrosis.

The heterogeneity of idiopathic pulmonary fibrosis (IPF) limits its diagnosis and treatment. The association between the pathophysiological features and the serum protein signatures of IPF currently remains unclear. The present study analyzed the specific proteins and patterns associated with the clinical parameters of IPF based on a serum proteomic dataset by data-independent acquisition using MS. Differentiated proteins in sera distinguished patients with IPF into three subgroups in signal pathways and overall survival. Aging-associated signatures by weighted gene correlation network analysis coincidently provided clear and direct evidence that aging is a critical risk factor for IPF rather than a single biomarker. Expression of LDHA and CCT6A, which was associated with glucose metabolic reprogramming, was correlated with high serum lactic acid content in patients with IPF. Cross-model analysis and machine learning showed that a combinatorial biomarker accurately distinguished patients with IPF from healthy individuals with an area under the curve of 0.848 (95% CI = 0.684-0.941) and validated from another cohort and ELISA assay. This serum proteomic profile provides rigorous evidence that enables an understanding of the heterogeneity of IPF and protein alterations that could help in its diagnosis and treatment decisions.

Single-cell transcriptome highlights a multilayer regulatory network on an invasive trajectory within colorectal cancer progression.

PURPOSE: Colorectal cancer (CRC) is one of the most common and fatal gastrointestinal malignancies, in which cancer stem cells (CSCs) were identified to enable tumor heterogeneity and initiate tumor formation. However, the process from CSCs to invasion cells is unconfirmed. METHODS: Several bioinformatics methods, including clustering, pseudotime analysis, gene set variation analysis and gene ontology enrichment, were used to construct a path of gradual transformation of CSCs to invasive cells, called "stem-to-invasion path". A large amount of signaling interactions were collated to build the multilayer regulatory network. Kaplan-Meier curve and time-dependent ROC method were applied to reveal prognostic values. RESULTS: We validated the heterogeneity of cells in the tumor microenvironment and revealed the presence of malignant epithelial cells with high invasive potential within primary colonic carcinomas. Next, the "stem-to-invasion path" was identified through constructing a branching trajectory with cancer cells arranged in order. A multilayer regulatory network considered as the vital factor involved in acquiring invasion characteristics underlying the path was built to elucidate the interactions between tumor cell and tumor-associated microenvironment. Then we further identified a novel combinatorial biomarker that can be used to assess the prognosis for CRC patients, and validated its predictive robustness on the independent dataset. CONCLUSION: Our work provides new insights into the acquisition of invasive potential in primary tumor cells, as well as potential therapeutic targets for CRC invasiveness, which may be useful for the cancer research and clinical treatment.