Exploring the potential of mucin 13 (MUC13) as a biomarker for carcinomas and other diseases

Breaking the Mucin Barrier: A New Affinity Chromatography-Mass Spectrometry Approach to Unveil Potential Cell Markers and Pathways Altered in Pseudomyxoma Peritonei

BACKGROUND

Pseudomyxoma peritonei (PMP) is a rare peritoneal mucinous carcinomatosis with largely unknown underlying molecular mechanisms. Cytoreductive surgery combined with hyperthermic intraperitoneal chemotherapy is the only therapeutic option; however, despite its use, recurrence with a fatal outcome is common. The lack of molecular characterisation of PMP and other mucinous tumours is mainly due to the physicochemical properties of mucin.

RESULTS

This manuscript describes the first protocol capable of breaking the mucin barrier and isolating proteins from mucinous tumours. Briefly, mucinous tumour samples were homogenised and subjected to liquid chromatography using two specific columns to reduce mainly glycoproteins, albumins and immunoglobulin G. The protein fractions were then subjected to mass spectrometry analysis and the proteomic profile obtained was analysed using various bioinformatic tools. Thus, we present here the first proteome analysed in PMP and identified a distinct mucin isoform profile in soft compared to hard mucin tumour tissues as well as key biological processes/pathways altered in mucinous tumours. Importantly, this protocol also allowed us to identify MUC13 as a potential tumour cell marker in PMP.

CONCLUSIONS

In sum, our results demonstrate that this protein isolation protocol from mucin will have a high impact, allowing the oncology research community to more rapidly advance in the knowledge of PMP and other mucinous neoplasms, as well as develop new and effective therapeutic strategies.

Deciphering cellular and molecular mechanism of MUC13 mucin involved in cancer cell plasticity and drug resistance

There has been a surge of interest in recent years in understanding the intricate mechanisms underlying cancer progression and treatment resistance. One molecule that has recently emerged in these mechanisms is MUC13 mucin, a transmembrane glycoprotein. Researchers have begun to unravel the molecular complexity of MUC13 and its impact on cancer biology. Studies have shown that MUC13 overexpression can disrupt normal cellular polarity, leading to the acquisition of malignant traits. Furthermore, MUC13 has been associated with increased cancer plasticity, allowing cells to undergo epithelial-mesenchymal transition (EMT) and metastasize. Notably, MUC13 has also been implicated in the development of chemoresistance, rendering cancer cells less responsive to traditional treatment options. Understanding the precise role of MUC13 in cellular plasticity, and chemoresistance could pave the way for the development of targeted therapies to combat cancer progression and enhance treatment efficacy.

Diagnostic efficacy of combining diffusion-weighted magnetic resonance imaging with serum Mucin 1, Mucin 13, and Mucin 16 in distinguishing borderline from malignant epithelial ovarian tumors

AIMS

To enhance ovarian tumor diagnosis beyond conventional methods, this study explored combining diffusion-weighted magnetic resonance imaging (DWI-MRI) and serum biomarkers (Mucin 1 [MUC1], MUC13, and MUC16) for distinguishing borderline from malignant epithelial ovarian tumors.

METHODS

A total of 126 patients, including 71 diagnosed with borderline (BEOTs) and 55 with malignant epithelial ovarian tumors (MEOTs), underwent preoperative DWI-MRI. Region of interest (ROI) was manually drawn along the solid component's boundary of the largest tumor, focusing on areas with potentially the lowest apparent diffusion coefficient (ADC). For entirely cystic tumors, a free-form ROI enclosed the maximum number of septa while targeting the lowest ADC. Serum biomarkers were determined using enzyme-linked immunosorbent assay.

RESULTS

Basic morphological traits proved inadequate for malignancy diagnosis, warranting this investigation. BEOTs had an ADC mean of (1.670 ± 0.250) × 103 mm2 /s, while MEOTs had a lower ADC mean of (1.332 ± 0.481) × 103 mm2 /s, with a sensitivity of 63.6% and specificity of 90.1%. Median MUC1 (167.0 U/mL vs. 87.3 U/mL), MUC13 (12.44 ng/mL vs. 7.77 ng/mL), and MUC16 (180.6 U/mL vs. 36.1 U/mL) levels were higher in MEOTs patients. The biomarker performance was: MUC1, sensitivity 50.9%, specificity 100%; MUC13, sensitivity 56.4%, specificity 78.9%; MUC16, sensitivity 83.64%, specificity 100%. Combining serum biomarkers and ADC mean resulted in a sensitivity of 96.4% and specificity of 100%.

CONCLUSION

The integration of DWI-MRI with serum biomarkers (MUC1, MUC13, and MUC16) achieves exceptional diagnostic accuracy, offering a powerful tool for the precise differentiation between borderline and malignant epithelial ovarian tumors.

MUC13 promotes the development of esophageal cancer by upregulating the expression of O-glycan process-related molecules

BACKGROUND

Esophageal cancer is one of the most common malignant tumors in the world, which is characterized by poor prognosis, aggressiveness, and poor survival. Mucin 13 (MUC13) is a member of the membrane-bound mucin and located on chromosome 3q21.2 and consists of α and β subunits. It has been found that MUC13 is overexpressed in a variety of tumor cells and acts a vital role in the invasiveness and malignant progression of several types of tumors. However, the role and regulatory mechanism of MUC13 in the progression of esophageal cancer remain unclear.

METHODS

The expression level of MUC13 was detected in 15 esophageal cancer tissues and 15 pairs of adjacent nontumor tissues by immunohistochemistry (IHC). In addition, the expression of MUC13 mRNA level in human esophageal cancer cell lines (EC9706 and ECA109 and TE-1) was measured by qRT-PCR. In vitro, after silencing MUC13 with lentiviral interference technology, CCK8 assay, clone formation assay, and flow cytometry were applied to investigate the proliferation activity, clone formation ability and anti-apoptosis ability of EC9706 and ECA109 cells. The tumor xenograft growth assay was used to confirm the influence of MUC13 knockdown on the growth of esophageal tumors in vivo. The qRT-PCR assay and western blot experiments were taken to study the mechanism of MUC13 regulating the proproliferation and antiapoptotic of esophageal cancer.

RESULTS

The results showed that MUC13 was overexpressed in esophageal cancer tissues and cell lines (EC9706 and ECA109 and TE-1), especially in EC9706 and ECA109 cells, but low expressed in human esophageal epithelial cell line (HEEC). Next, silencing MUC13 inhibits proliferation, blocks cell cycle progression, and promotes cell apoptosis in vitro, and restrains the growth of esophageal cancer tissues in vivo. Finally, MUC13 affects the proproliferation and antiapoptotic by regulating the expression of GLANT14, MUC3A, MUC1, MUC12, and MUC4 that closely related to O-glycan process.

CONCLUSIONS

This study proved that MUC13 is an important molecule that regulates the O-glycan process and then affects the progress of esophageal cancer. MUC13 may be a novel therapeutic target for patients with esophageal cancer.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Mucin 13 (MUC13) as a candidate biomarker for ovarian cancer detection: potential to complement CA125 in detecting non-serous subtypes

OBJECTIVES

Ovarian cancer is the most lethal gynecological malignancy in developed countries. One of the key associations with the high mortality rate is diagnosis at late stages. This clinical limitation is primarily due to a lack of distinct symptoms and detection at the early stages. The ovarian cancer biomarker, CA125, is mainly effective for identifying serous ovarian carcinomas, leaving a gap in non-serous ovarian cancer detection. Mucin 13 (MUC13) is a transmembrane, glycosylated protein with aberrant expression in malignancies, including ovarian cancer. We explored the potential of MUC13 to complement CA125 as an ovarian cancer biomarker, by evaluating its ability to discriminate serous and non-serous subtypes of ovarian cancer at FIGO stages I-IV from benign conditions.

METHODS

We used our newly developed, high sensitivity ELISA to measure MUC13 protein in a large, well-defined cohort of 389 serum samples from patients with ovarian cancer and benign conditions.

RESULTS

MUC13 and CA125 serum levels were elevated in malignant compared to benign cases (p<0.0001). Receiver-operating characteristic (ROC) curve analysis showed similar area under the curve (AUC) of 0.74 (MUC13) and 0.76 (CA125). MUC13 concentrations were significantly higher in mucinous adenocarcinomas compared to benign controls (p=0.0005), with AUC of 0.80. MUC13 and CA125 showed significant elevation in early-stage cases (stage I-II) in relation to benign controls (p=0.0012 and p=0.014, respectively).

CONCLUSIONS

We report the novel role of MUC13 as a serum ovarian cancer biomarker, where it could complement CA125 for detecting some subtypes of non-serous ovarian carcinoma and early-stage disease.

Glycosylation spectral signatures for glioma grade discrimination using Raman spectroscopy

BACKGROUND

Gliomas are the most common brain tumours with the high-grade glioblastoma representing the most aggressive and lethal form. Currently, there is a lack of specific glioma biomarkers that would aid tumour subtyping and minimally invasive early diagnosis. Aberrant glycosylation is an important post-translational modification in cancer and is implicated in glioma progression. Raman spectroscopy (RS), a vibrational spectroscopic label-free technique, has already shown promise in cancer diagnostics.

METHODS

RS was combined with machine learning to discriminate glioma grades. Raman spectral signatures of glycosylation patterns were used in serum samples and fixed tissue biopsy samples, as well as in single cells and spheroids.

RESULTS

Glioma grades in fixed tissue patient samples and serum were discriminated with high accuracy. Discrimination between higher malignant glioma grades (III and IV) was achieved with high accuracy in tissue, serum, and cellular models using single cells and spheroids. Biomolecular changes were assigned to alterations in glycosylation corroborated by analysing glycan standards and other changes such as carotenoid antioxidant content.

CONCLUSION

RS combined with machine learning could pave the way for more objective and less invasive grading of glioma patients, serving as a useful tool to facilitate glioma diagnosis and delineate biomolecular glioma progression changes.

Recombinant mucin biotechnology and engineering

Mucins represent a largely untapped class of polymeric building block for biomaterials, therapeutics, and other biotechnology. Because the mucin polymer backbone is genetically encoded, sequence-specific mucins with defined physical and biochemical properties can be fabricated using recombinant technologies. The pendent O-glycans of mucins are increasingly implicated in immunomodulation, suppression of pathogen virulence, and other biochemical activities. Recent advances in engineered cell production systems are enabling the scalable synthesis of recombinant mucins with precisely tuned glycan side chains, offering exciting possibilities to tune the biological functionality of mucin-based products. New metabolic and chemoenzymatic strategies enable further tuning and functionalization of mucin O-glycans, opening new possibilities to expand the chemical diversity and functionality of mucin building blocks. In this review, we discuss these advances, and the opportunities for engineered mucins in biomedical applications ranging from in vitro models to therapeutics.

The diagnostic and prognostic potential of the EGFR/MUC4/MMP9 axis in glioma patients

Glioblastoma is the most aggressive form of brain cancer, presenting poor prognosis despite current advances in treatment. There is therefore an urgent need for novel biomarkers and therapeutic targets. Interactions between mucin 4 (MUC4) and the epidermal growth factor receptor (EGFR) are involved in carcinogenesis, and may lead to matrix metalloproteinase-9 (MMP9) overexpression, exacerbating cancer cell invasiveness. In this study, the role of MUC4, MMP9, and EGFR in the progression and clinical outcome of glioma patients was investigated. Immunohistochemistry (IHC) and immunofluorescence (IF) in fixed tissue samples of glioma patients were used to evaluate the expression and localization of EGFR, MMP9, and MUC4. Kaplan-Meier survival analysis was also performed to test the prognostic utility of the proteins for glioma patients. The protein levels were assessed with enzyme-linked immunosorbent assay (ELISA) in serum of glioma patients, to further investigate their potential as non-invasive serum biomarkers. We demonstrated that MUC4 and MMP9 are both significantly upregulated during glioma progression. Moreover, MUC4 is co-expressed with MMP9 and EGFR in the proliferative microvasculature of glioblastoma, suggesting a potential role for MUC4 in microvascular proliferation and angiogenesis. The combined high expression of MUC4/MMP9, and MUC4/MMP9/EGFR was associated with poor overall survival (OS). Finally, MMP9 mean protein level was significantly higher in the serum of glioblastoma compared with grade III glioma patients, whereas MUC4 mean protein level was minimally elevated in higher glioma grades (III and IV) compared with control. Our results suggest that MUC4, along with MMP9, might account for glioblastoma progression, representing potential therapeutic targets, and suggesting the 'MUC4/MMP9/EGFR axis' may play a vital role in glioblastoma diagnostics.

Biomarkers in the management of lung cancer: changing the practice of thoracic oncology

Lung cancer currently represents a leading cause of cancer death. Substantial progress achieved in the medical therapy of lung cancer during the last decade has been associated with the advent of targeted therapy, including immunotherapy. The targeted therapy has gradually shifted from drugs suppressing general mechanisms of tumor growth and progression to agents aiming at transforming mechanisms like driver mutations in a particular tumor. Knowledge of the molecular characteristics of a tumor has become an essential component of the more targeted therapeutic approach. There are specific challenges for biomarker determination in lung cancer, in particular a commonly limited size of tumor sample. Liquid biopsy is therefore of particular importance in the management of lung cancer. Laboratory medicine is an indispensable part of multidisciplinary management of lung cancer. Clinical Chemistry and Laboratory Medicine (CCLM) has played and will continue playing a major role in updating and spreading the knowledge in the field.

MUC13 promotes lung cancer development and progression by activating ERK signaling

Mucin 13 (MUC13) is a glycoprotein that is expressed on the cell surface and participates in the tumorigenesis of multiple malignancies, including pancreatic cancer, colorectal cancer and renal cancer. However, to the best of our knowledge, the expression levels and function of MUC13 in lung cancer progression have not yet been demonstrated. Therefore, the present study examined the expression pattern and regulatory role of MUC13 in lung cancer tumorigenesis. The results demonstrated that MUC13 was highly expressed in lung cancer tissues and cell lines compared with that in normal tissues and cell lines. Functionally, knockdown of MUC13 inhibited cell proliferation and enhanced the apoptosis of A549 and NCI-H1650 lung cancer cells. Furthermore, silencing of MUC13 suppressed the migration and invasion of lung cancer cells. Additionally, a xenograft tumor model demonstrated that knockdown of MUC13 delayed the development of the lung cancer xenograft and suppressed the expression of proliferation marker Ki-67 in tumor tissues. Mechanistically, MUC13 activated the ERK signaling pathway by enhancing the phosphorylation of ERK, JNK and p38 in lung cancer tissues compared with that in normal tissues. Knockdown of MUC13 inhibited the phosphorylation of ERK/JNK/p38 in A549 and NCI-H1650 cells. Overall, these findings suggested that MUC13 could act as an oncogenic glycoprotein to accelerate the progression of lung cancer via abnormal activation of the ERK/JNK/p38 signaling pathway and might serve as a therapeutic target for lung cancer treatment.

Distinct Human Gut Microbial Taxonomic Signatures Uncovered With Different Sample Processing and Microbial Cell Disruption Methods for Metaproteomic Analysis

The use of metaproteomics for studying the human gut microbiota can shed light on the taxonomic profile and the functional role of the microbial community. Nevertheless, methods for extracting proteins from stool samples continue to evolve, in the pursuit of optimal protocols for moistening and dispersing the stool sample and for disrupting microbial cells, which are two critical steps for ensuring good protein recovery. Here, we evaluated different stool sample processing (SSP) and microbial cell disruption methods (CDMs). The combination of a longer disintegration period of the stool sample in a tube rotator with sonication increased the overall number of identified peptides and proteins. Proteobacteria, Bacteroidetes, Planctomycetes, and Euryarchaeota identification was favored by mechanical cell disruption with glass beads. In contrast, the relative abundance of Firmicutes, Actinobacteria, and Fusobacteria was improved when sonication was performed before bead beating. Tenericutes and Apicomplexa identification was enhanced by moistening the stool samples during processing and by disrupting cells with medium-sized glass beads combined with or without sonication. Human protein identifications were affected by sonication. To test the reproducibility of these gut metaproteomic analyses, we examined samples from six healthy individuals using a protocol that had shown a good taxonomic diversity and identification of proteins from Proteobacteria and humans. We also detected proteins involved in microbial functions relevant to the host and related mostly to specific taxa, such as B12 biosynthesis and short chain fatty acid (SCFA) production carried out mainly by members in the Prevotella genus and the Firmicutes phylum, respectively. The taxonomic and functional profiles obtained with the different protocols described in this work provides the researcher with valuable information when choosing the most adequate protocol for the study of certain pathologies under suspicion of being related to a specific taxon from the gut microbiota.

Development of Human Lung Induction Models for Air Pollutants' Toxicity Assessment

There is an urgent need for reliable and effective models to study air pollution health effects on human lungs. Here, we report the utilization of human pluripotent stem cell (hPSC) induction models for human lung progenitor cells (hLPs) and alveolar type 2 epithelial cell-like cells (ATLs) for the toxicity assessment of benzo(a)pyrene, nano-carbon black, and nano-SiO₂, as common air pollutants. We induced hPSCs to generate ATLs, which recapitulated key features of human lung type 2 alveolar epithelial cells, and tested the induction models for cellular uptake of nanoparticles and toxicity evaluations. Our findings reveal internalization of nano-carbon black, dose-dependent uptake of nano-SiO₂, and interference with surfactant secretion in ATLs exposed to benzo(a)pyrene/nano-SiO₂. Thus, hLP and ATL induction models could facilitate the evaluation of environmental pollutants potentially affecting the lungs. In conclusion, this is one of the first studies that managed to adopt hPSC pulmonary induction models in toxicology studies.