Identification of novel early pancreatic cancer biomarkers KIF5B and SFRP2 from “first contact” interactions in the tumor microenvironment

Single cell analysis revealed SFRP2 cancer associated fibroblasts drive tumorigenesis in head and neck squamous cell carcinoma

Understanding the mechanisms of invasion and metastasis in head and neck squamous cell carcinoma (HNSCC) is crucial for effective treatment, particularly in metastatic cases. In this study, we analyzed multicenter bulk sequencing and comprehensive single-cell data from 702,446 cells, leading to the identification of a novel subtype of cancer-associated fibroblasts (CAFs), termed Secreted Frizzled-Related Protein2 CAFs (SFRP2_CAFs). These cells, originating from smooth muscle cells, display unique characteristics resembling both myofibroblastic CAFs and inflammatory CAFs, and are linked to poorer survival outcomes in HNSCC patients. Our findings reveal significant interactions between SFRP2_CAFs and SPP1 tumor-associated macrophages, which facilitate tumor invasion and metastasis. Moreover, our research identifies Nuclear factor I/X (NFIX) as a key transcription factor regulating SFRP2_CAFs behavior, confirmed through gene regulatory network analysis and simulation perturbation.

Down-regulation of RTEL1 Improves M1/M2 Macrophage Polarization by Promoting SFRP2 in Fibroblasts-derived Exosomes to Alleviate COPD

Chronic obstructive pulmonary disease (COPD) is a common chronic respiratory disease worldwide. Macrophage polarization plays a substantial role in the pathogenesis of COPD. This study is aimed to explore the regulatory mechanism of regulator of telomere elongation 1 (RTEL1) in COPD. COPD model mouse was conducted by cigarette smoke (CS). The pathological features of lung in mice were observed by histological staining. After extracting exosomes, macrophages were co-cultured with fibroblasts-derived exosomes. Then, the effects of RTEL1 and exosomal secreted frizzled-related protein 2 (SFRP2) on macrophage proliferation, inflammation, apoptosis, and M1, M2 macrophage polarization (iNOS and CD206) were evaluated by cell counting kit-8, EdU assay, enzyme-linked immuno sorbent assay, and western blotting, respectively. CS-induced COPD model mouse was successfully constructed. Through in vitro experiments, knockdown of RTEL1 inhibited macrophage proliferation, inflammation (MMP9, IL-1β and TNF-α), and promoted apoptosis (Bax, cleaved-caspase3, Bcl-2) in CS extract-induced lung fibroblasts. Meanwhile, RTEL1 knockdown promoted M1 and suppressed M2 macrophage polarization in COPD. Additionally, silencing SFRP2 in fibroblasts-derived exosomes reversed the effects of RTEL1 knockdown on proliferation, inflammation, apoptosis, and M1, M2 macrophage polarization. Collectively, down-regulation of RTEL1 improved M1/M2 macrophage polarization by promoting SFRP2 in fibroblasts-derived exosomes to alleviate CS-induced COPD.

Mass spectrometry–based proteomics technology in pancreatic cancer research

Pancreatic ductal adenocarcinoma (PDAC) has become a significant health concern with increasing incidence and mortality rates over the past few decades. Researchers have turned their attention to cutting-edge mass spectrometry (MS) technology due to its high-throughput and accurate detection capacity, which plays a vital role in understanding the mechanisms and discovering biomarkers for pancreatic diseases. In this review, we comprehensively investigate various methodologies of quantitative and qualitative proteomics MS technologies, alongside bioinformatical platforms employed in pancreatic cancer research. The integration of these optimized approaches provides novel insights into the molecular mechanisms underlying tumorigenesis and disease progression, ultimately facilitating the discovery of potential diagnostic, prognostic biomarkers, and therapeutic targets. The robust MS-based strategy shows promise in paving the way for early diagnosis and personalized medicine for pancreatic cancer patients.

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

Thinking small to win big? A critical review on the potential application of extracellular vesicles for biomarker discovery and new therapeutic approaches in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly form of cancer, with limited progress in 5-year survival rates despite significant research efforts. The main challenges in treating PDAC include difficulties in early detection, and resistance to current therapeutic approaches due to aggressive molecular and microenvironment features. These challenges emphasize the importance of identifying clinically validated biomarkers for early detection and clinical management. Extracellular vesicles (EVs), particularly exosomes, have emerged as crucial mediators of intercellular communication by transporting molecular cargo. Recent research has unveiled their role in initiation, metastasis, and chemoresistance of PDAC. Consequently, utilizing EVs in liquid biopsies holds promise for the identification of biomarkers for early detection, prognosis, and monitoring of drug efficacy. However, numerous limitations, including challenges in isolation and characterization of homogeneous EVs populations, as well as the absence of standardized protocols, can affect the reliability of studies involving EVs as biomarkers, underscoring the necessity for a prudent approach. EVs have also garnered considerable attention as a promising drug delivery system and novel therapy for tumors. The loading of biomolecules or chemical drugs into exosomes and their subsequent delivery to target cells can effectively impede tumor progression. Nevertheless, there are obstacles that must be overcome to ensure the accuracy and efficacy of therapies relying on EVs for the treatment of tumors. In this review, we examine both recent advancements and remaining obstacles, exploring the potential of utilizing EVs in biomarker discovery as well as for the development of drug delivery vehicles.

Hands-Free Proteomic Profiling of Urinary Extracellular Vesicles with a High-Throughput Automated Workflow

Extracellular vesicles (EVs) have emerged as a promising source of disease biomarkers for noninvasive early stage diagnoses, but a bottleneck in EV sample processing restricts their immense potential in clinical applications. Existing methods are limited by a low EV yield and integrity, slow processing speeds, low sample capacity, and poor recovery efficiency. We aimed to address these issues with a high-throughput automated workflow for EV isolation, EV lysis, protein extraction, and protein denaturation. The automation can process clinical urine samples in parallel, resulting in protein-covered beads ready for various analytical methods, including immunoassays, protein quantitation assays, and mass spectrometry. Compared to the standard manual lysis method for contamination levels, efficiency, and consistency of EV isolation, the automated protocol shows reproducible and robust proteomic quantitation with less than a 10% median coefficient of variation. When we applied the method to clinical samples, we identified a total 3,793 unique proteins and 40,380 unique peptides, with 992 significantly upregulated proteins in kidney cancer patients versus healthy controls. These upregulated proteins were found to be involved in several important kidney cancer metabolic pathways also identified with a manual control. This hands-free workflow represents a practical EV extraction and profiling approach that can benefit both clinical and research applications, streamlining biomarker discovery, tumor monitoring, and early cancer diagnoses.

Survival and Enrichment Analysis of Epithelial-Mesenchymal Transition Genes in Bladder Urothelial Carcinoma

The escalating prevalence of bladder cancer, particularly urothelial carcinoma, necessitates innovative approaches for prognosis and therapy. This study delves into the significance of genes related to epithelial-mesenchymal transition (EMT), a process inherently linked to carcinogenesis and comparatively better studied in other cancers. We examined 1184 EMT-related gene expression levels in bladder urothelial cancer cases through the TCGA dataset. Genes shown to be differentially expressed in relation to survival underwent further network and enrichment analysis to uncover how they might shape disease outcomes. Our in silico analysis revealed a subset of 32 genes, including those significantly represented in biological pathways such as VEGF signaling and bacterium response. In addition, these genes interact with genes involved in the JAK-STAT signaling pathway. Additionally, some of those 32 genes have been linked to immunomodulators such as chemokines CCL15 and CCL18, as well as to various immune cell infiltrates. Our findings highlight the prognostic utility of various EMT-related genes and identify possible modulators of their effect on survival, allowing for further targeted wet lab research and possible therapeutic intervention.

Functional and Clinical Proteomic Exploration of Pancreatic Cancer

Pancreatic cancer, most cases being pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancers with a median survival time of less than 6 months. Therapeutic options are very limited for PDAC patients, and surgery is still the most effective treatment, making improvements in early diagnosis critical. One typical characteristic of PDAC is the desmoplastic reaction of its stroma microenvironment, which actively interacts with cancer cells to orchestrate key components in tumorigenesis, metastasis, and chemoresistance. Global exploration of cancer-stroma crosstalk is essential to decipher PDAC biology and design intervention strategies. Over the past decade, the dramatic improvement of proteomics technologies has enabled profiling of proteins, post-translational modifications (PTMs), and their protein complexes at unprecedented sensitivity and dimensionality. Here, starting with our current understanding of PDAC characteristics, including precursor lesions, progression models, tumor microenvironment, and therapeutic advancements, we describe how proteomics contributes to the functional and clinical exploration of PDAC, providing insights into PDAC carcinogenesis, progression, and chemoresistance. We summarize recent achievements enabled by proteomics to systematically investigate PTMs-mediated intracellular signaling in PDAC, cancer-stroma interactions, and potential therapeutic targets revealed by these functional studies. We also highlight proteomic profiling of clinical tissue and plasma samples to discover and verify useful biomarkers that can aid early detection and molecular classification of patients. In addition, we introduce spatial proteomic technology and its applications in PDAC for deconvolving tumor heterogeneity. Finally, we discuss future prospects of applying new proteomic technologies in comprehensively understanding PDAC heterogeneity and intercellular signaling networks. Importantly, we expect advances in clinical functional proteomics for exploring mechanisms of cancer biology directly by high-sensitivity functional proteomic approaches starting from clinical samples.

Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson's disease

BACKGROUND

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson's disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.

METHODS

Utilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).

RESULTS

After efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.

CONCLUSIONS

These findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.

Extracellular vesicle proteomics and phosphoproteomics identify pathways for increased risk in patients hospitalized with COVID-19 and type 2 diabetes mellitus

Recent studies suggest that extracellular vesicles (EVs) play a role in the pathogenesis of SARS-CoV-2 infection and the severity of COVID-19. However, their role in the interaction between COVID-19 and type 2 diabetes (T2D) has not been addressed. Here, we characterized the circulating EV proteomic and phosphoproteomic landscape in patients with and without T2D hospitalized with COVID-19 or non-COVID-19 acute respiratory illness (RSP). We detected differentially expressed protein and phosphoprotein signatures that effectively characterized the study groups. The trio of immunomodulatory and coagulation proteins C1QA, C1QB, and C1QC appeared to be a central cluster in both the COVID-19 and T2D functional networks. PKCβ appeared to be retained in cells by being diverted from EV pathways and contribute to the COVID-19 and T2D interaction via a PKC/BTK/TEC axis. EV-shuttled CASP3 and ROCK1 appeared to be coregulated and likely contribute to disease interactions in patients with COVID-19 and T2D. Predicted activation of AMPK, MAPK, and SYK appeared to also play important roles driving disease interaction. These results suggest that activated cellular kinases (i.e., PKC, AMPK, MAPK, and SYK) and multiple EV-shuttled kinases (i.e., PKCβ, BTK, TEC, MAP2K2, and ROCK1) may play key roles in severe COVID-19, particularly in patients with comorbid diabetes.

Clinical diagnosis and management of pancreatic cancer: Markers, molecular mechanisms, and treatment options

Pancreatic cancer (PC) is the third-leading cause of cancer deaths. The overall 5-year survival rate of PC is 9%, and this rate for metastatic PC is below 3%. However, the PC-induced death cases will increase about 2-fold by 2060. Many factors such as genetic and environmental factors and metabolic diseases can drive PC development and progression. The most common type of PC in the clinic is pancreatic ductal adenocarcinoma, comprising approximately 90% of PC cases. Multiple pathogenic processes including but not limited to inflammation, fibrosis, angiogenesis, epithelial-mesenchymal transition, and proliferation of cancer stem cells are involved in the initiation and progression of PC. Early diagnosis is essential for curable therapy, for which a combined panel of serum markers is very helpful. Although some mono or combined therapies have been approved by the United States Food and Drug Administration for PC treatment, current therapies have not shown promising outcomes. Fortunately, the development of novel immunotherapies, such as oncolytic viruses-mediated treatments and chimeric antigen receptor-T cells, combined with therapies such as neoadjuvant therapy plus surgery, and advanced delivery systems of immunotherapy will improve therapeutic outcomes and combat drug resistance in PC patients. Herein, the pathogenesis, molecular signaling pathways, diagnostic markers, prognosis, and potential treatments in completed, ongoing, and recruiting clinical trials for PC were reviewed.

Analysis of exosomal competing endogenous RNA network response to paclitaxel treatment reveals key genes in advanced gastric cancer

BACKGROUND

Exosome is an important component of the tumor immune microenvironment and plays critical role in cancer pathogenesis. The exosome transcriptome of gastric cancer (GC) response to paclitaxel chemotherapy has not been investigated in the past.

METHODS

ceRNA microarrays were performed in exosomes from six advanced GC patients before and after paclitaxel treatment. Bioinformatics tools were used to identify differential expressing genes and construct competing endogenous RNA (ceRNA) networks. The importance of hub genes in the ceRNA network was confirmed by survival analysis and functional analysis.

RESULTS

A total of 213 differential mRNAs, 370 lncRNAs, and 376 circRNAs were identified, and hub genes in ceRNA networks were screened. The differential genes were associated with GO terms SNAP complex, gap junction, protein transporter activity, cytokine receptor, and KEGG pathways synaptic vesicle cycle, propanoate metabolism, Epstein-Barr virus infection, heparin, and steroid biosynthesis, and beta-alanine metabolism. ULK2, CYP2R1, BTLA, and miR-105-5p are prognostic genes for overall survival. Paclitaxel may target ULK2 which is involved in mitosis and cell cycle. miR-105-5p may target ULK2 3'UTR.

CONCLUSION

The work for the first time identified exosomal RNA biomarkers and constructed a ceRNA network in GC response to paclitaxel, revealed novel molecular mechanisms of GC, and provided new candidates for GC diagnosis and treatment.