MUC16 as a novel target for cancer therapy

MUC16 as a serum-based prognostic indicator of prometastatic gastric cancer

Metastatic gastric cancer (GC) presents significant clinical challenges due to its poor prognosis and limited treatment options. To address this, we conducted a targeted protein biomarker discovery study to identify markers predictive of metastasis in advanced GC (AGC). Serum samples from 176 AGC patients (T stage 3 or higher) were analyzed using the Olink Proteomics Target panels. Patients were retrospectively categorized into nonmetastatic, metastatic, and recurrence groups, and differential protein expression was assessed. Machine learning and gene set enrichment analysis (GSEA) methods were applied to discover biomarkers and predict prognosis. Four proteins (MUC16, CAIX, 5'-NT, and CD8A) were significantly elevated in metastatic GC patients compared to the control group. Additionally, GSEA indicated that the response to interleukin-4 and hypoxia-related pathways were enriched in metastatic patients. Random forest classification and decision-tree modeling showed that MUC16 could be a predictive marker for metastasis in GC patients. Additionally, ELISA validation confirmed elevated MUC16 levels in metastatic patients. Notably, high MUC16 levels were independently associated with metastatic progression in T3 or higher GC. These findings suggest the potential of MUC16 as a clinically relevant biomarker for identifying GC patients at high risk of metastasis.

MUC21: a new target for tumor treatment

MUC21, also known as Epiglycanin, is a high-molecular-weight glycoprotein with transmembrane mucin properties. It consists of a tandem repeat domain, a stem domain, a transmembrane domain and a cytoplasmic tail. MUC21 is expressed is observed in normal tissues in organs like the thymus, testes, lungs, and large intestine. Research has shown that MUC21 is expressed in esophageal squamous cell carcinoma, lung adenocarcinoma, glioblastoma, thyroid cancer, melanoma, and various other malignant tumors in distinctive manner. Additionally, tumor invasion, metastasis, and poor prognosis are linked to it. Some researchers believe that MUC21 has the potential to become a new target in cancer treatment. This review aims to deliver a comprehensive overview of the glycosylation, function, and research progress of MUC21 in multiple types of cancer and infectious diseases.

Structural Basis for Multivalent MUC16 Recognition and Robust Anti-Pancreatic Cancer Activity of Humanized Antibody AR9.6

Mucin-16 (MUC16) is a target for antibody-mediated immunotherapy in pancreatic ductal adenocarcinoma (PDAC) among other malignancies. The MUC16-specific monoclonal antibody AR9.6 has shown promise for PDAC immunotherapy and imaging. Here, we report the structural and biological characterization of the humanized AR9.6 antibody (huAR9.6). The structure of huAR9.6 was determined in complex with a MUC16 SEA (Sea urchin sperm, Enterokinase, Agrin) domain. Binding of huAR9.6 to recombinant, shed, and cell-surface MUC16 was characterized, and anti-PDAC activity was evaluated in vitro and in vivo. HuAR9.6 bound a discontinuous, SEA domain epitope with an overall affinity of 88 nmol/L. Binding affinity depended on the specific SEA domain(s) present, and glycosylation modestly enhanced affinity driven by favorable entropy and enthalpy and via distinct transition state thermodynamic pathways. Treatment with huAR9.6 reduced the in vitro growth, migration, invasion, and clonogenicity of MUC16-positive PDAC cells and patient-derived organoids (PDO). HuAR9.6 blocked MUC16-mediated ErbB and AKT activation in PDAC cells, PDOs, and patient-derived xenografts and induced antibody-dependent cellular cytotoxicity and complement-dependent cytotoxicity. More importantly, huAR9.6 treatment caused substantial PDAC regression in subcutaneous and orthotopic tumor models. The mechanism of action of huAR9.6 may depend on dense avid binding to homologous SEA domains on MUC16. The results of this study validate the translational therapeutic potential of huAR9.6 against MUC16-positive PDACs.

Construction and analysis of a reliable five-gene prognostic signature for colon adenocarcinoma associated with the wild-type allelic state of the COL6A6 gene

Background

Tumors emerge by acquiring a number of mutations over time. The first mutation provides a selective growth advantage compared to adjacent epithelial cells, allowing the cell to create a clone that can outgrow the cells that surround it. Subsequent mutations determine the risk of the tumor progressing to metastatic cancer. Some secondary mutations may inhibit the aggressiveness of the tumor while still increasing the survival of the clone. Meaningful mutations in genes may provide a strong molecular foundation for developing novel therapeutic strategies for cancer.

Methods

The somatic mutation and prognosis in colon adenocarcinoma (COAD) were analyzed. The copy number variation (CNV) and differentially expressed genes (DEGs) between the collagen type VI alpha 6 chain (COL6A6) mutation (COL6A6-MUT) and the COL6A6 wild-type (COL6A6-WT) subgroups were evaluated. The independent prognostic signatures based on COL6A6-allelic state were determined to construct a Cox model. The biological characteristics and the immune microenvironment between the two risk groups were compared.

Results

COL6A6 was found to be highly mutated in COAD at a frequency of 9%. Patients with COL6A6-MUT had a good overall survival (OS) compared to those with COL6A6-WT, who had a different CNV pattern. Significant differences in gene expression were established for 593 genes between the COL6A6-MUT and COL6A6-WT samples. Among them, MUC16, ASNSP1, PRR18, PEG10, and RPL26P8 were determined to be independent prognostic factors. The internally validated prognostic risk model, constructed using these five genes, demonstrated its value by revealing a significant difference in patient prognosis between the high-risk and low-risk groups. Specifically, patients in the high-risk group exhibited a considerably worse prognosis than did those in the low-risk group. The high-risk group had a significantly higher proportion of patients over 60 years of age and patients in stage III. Moreover, the tumor immune dysfunction and exclusion (TIDE) score and the expression of human leukocyte antigen (HLA) family genes were all higher in the high-risk group than that in the low-risk group.

Conclusions

The allelic state of COL6A6 and the five associated DEGs were identified as novel biomarkers for the diagnosis and prognosis of COAD and may be therapeutic targets in COAD.

CAR-T-Cell-Based Cancer Immunotherapies: Potentials, Limitations, and Future Prospects

Cancer encompasses various elements occurring at the cellular and genetic levels, necessitating an immunotherapy capable of efficiently addressing both aspects. T cells can combat cancer cells by specifically recognizing antigens on them. This innate capability of T cells has been used to develop cellular immunotherapies, but most of them can only target antigens through major histocompatibility complexes (MHCs). New gene-editing techniques such as clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 9 (CRISPR-cas9) can precisely edit the DNA sequences. CRISPR-cas9 has made it possible to generate genetically engineered chimeric antigen receptors (CARs) that can overcome the problems associated with old immunotherapies. In chimeric antigen receptor T (CAR-T) cell therapy, the patient's T cells are isolated and genetically modified to exhibit synthetic CAR(s). CAR-T cell treatment has shown remarkably positive clinical outcomes in cancers of various types. Nevertheless, there are various challenges that reduce CAR-T effectiveness in solid tumors. It is required to address these challenges in order to make CAR-T cell therapy a better and safer option. Combining CAR-T treatment with other immunotherapies that target multiple antigens has shown positive outcomes. Moreover, recently generated Boolean logic-gated advanced CARs along with artificial intelligence has expanded its potential to treat solid tumors in addition to blood cancers. This review aims to describe the structure, types, and various methods used to develop CAR-T cells. The clinical applications of CAR-T cells in hematological malignancies and solid tumours have been described in detail. In addition, this discussion has addressed the limitations associated with CAR-T cells, explored potential strategies to mitigate CAR-T-related toxicities, and delved into future perspectives.

MUC16: clinical targets with great potential

Mucin 16 (MUC16) is a membrane-bound mucin that is abnormally expressed or mutated in a variety of diseases, especially tumors, while being expressed in normal body epithelium. MUC16 and its extracellular components are often important cancer-related biomarkers. Abnormal expression of MUC16 promotes tumor progression through mesenchymal protein, PI3K/AKT pathway, JAK2/STAT3 pathway, ERK/FBW7/c-Myc, and other mechanisms, and plays an important role in the occurrence and development of tumors. In addition, MUC16 also helps tumor immune escape by inhibiting T cells and NK cells. Many drugs and trials targeting MUC16 have been developed, and MUC16 may be a new direction for future treatments. In this paper, the mechanism of action of MUC16 in the development of cancer, especially in the immune escape of tumor, is introduced in detail, indicating the potential of MUC16 in clinical treatment.

Exploring the genetic control of sweat gland characteristics in beef cattle for enhanced heat tolerance

BACKGROUND

Thermal stress in subtropical regions is a major limiting factor in beef cattle production systems with around $369 million being lost annually due to reduced performance. Heat stress causes numerous physiological and behavioral disturbances including reduced feed intake and decreased production levels. Cattle utilize various physiological mechanisms such as sweating to regulate internal heat. Variation in these traits can help identify genetic variants that control sweat gland properties and subsequently allow for genetic selection of cattle with greater thermotolerance.

METHODS

This study used 2,401 Brangus cattle from two commercial ranches in Florida. Precise phenotypes that contribute to an animal's ability to manage heat stress were calculated from skin biopsies and included sweat gland area, sweat gland depth, and sweat gland length. All animals were genotyped with the Bovine GGP F250K, and BLUPF90 software was used to estimate genetic parameters and for Genome Wide Association Study.

RESULTS

Sweat gland phenotypes heritability ranged from 0.17 to 0.42 indicating a moderate amount of the phenotypic variation is due to genetics, allowing producers the ability to select for favorable sweat gland properties. A weighted single-step GWAS using sliding 10 kb windows identified multiple quantitative trait loci (QTLs) explaining a significant amount of genetic variation. QTLs located on BTA7 and BTA12 explained over 1.0% of genetic variance and overlap the ADGRV1 and CCDC168 genes, respectively. The variants identified in this study are implicated in processes related to immune function and cellular proliferation which could be relevant to heat management. Breed of Origin Alleles (BOA) were predicted using local ancestry in admixed populations (LAMP-LD), allowing for identification of markers' origin from either Brahman or Angus ancestry. A BOA GWAS was performed to identify regions inherited from particular ancestral breeds that might have a significant impact on sweat gland phenotypes.

CONCLUSIONS

The results of the BOA GWAS indicate that both Brahman and Angus alleles contribute positively to sweat gland traits, as evidenced by favorable marker effects observed from both genetic backgrounds. Understanding and utilizing genetic traits that confer better heat tolerance is a proactive approach to managing the impacts of climate change on livestock farming.

Clinical value of combined detection of Carcinoembryonic Antigen and CA125 in the diagnosis of non-small cell lung cancer combined with Malignant Pleural Effusion

Objective

To investigate the clinical value of combined detection of carcinoembryonic antigen(CEA) and CA125 in the diagnosis of non-small cell lung cancer(NSCLC) combined with malignant pleural effusion.

Methods

This was retrospective research. Fifty-six NSCLC patients combined with malignant pleural effusion in Baoding No.1 Hospital, China, from January 2020 to January 2022 were recruited as the malignant group, and another 56 NSCLC patients combined with pleural effusion in the same period were recruited as the benign group. Pleural effusion and serum specimens were collected from both groups and their carcinoembryonic antigen (CEA), carbohydrate antigen 125(CA125) and SP70 antigen levels were measured respectively. The differences in index levels between the two groups were compared, and the value of the index in diagnosing NSCLC combined with malignant pleural effusion was analyzed.

Results

The positive rates of CEA, CA125 and SP70 antigen in pleural effusion were higher in the malignant group than in the benign group (p>0.05); The positive rates of CEA and CA125 in the malignant group were higher than those in the benign group (p>0.05), with no statistically significant difference between the two groups in the positive rates of SP70 antigen (p>0.05). ROC curve analysis revealed the value of serum CEA and CA12 in the diagnosis of NSCLC combined with malignant pleural effusion, while serum SP70 antigen had no diagnostic value (p>0.05).

Conclusion

The combined detection of CEA, CA125 and SP70 antigen boasts a higher diagnostic value for NSCLC-mediated pleural effusion, with higher diagnostic value than the combined detection of serum indexes.

A Comprehensive Analysis of HOXB13 Expression in Hepatocellular Carcinoma

Background and objectives: Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and is caused by multiple factors. To explore novel targets for HCC treatment, we comprehensively analyzed the expression of HomeoboxB13 (HOXB13) and its role in HCC. Materials and Methods: The clinical significance of HCC was investigated using open gene expression databases, such as TIMER, UALCAN, KM, OSlihc, and LinkedOmics, and immunohistochemistry analysis. We also analyzed cell invasion and migration in HCC cell lines transfected with HOXB13-siRNA and their association with MMP9, E2F1, and MEIS1. Results: HOXB13 expression was higher in fibrolamellar carcinoma than in other histological subtypes. Its expression was associated with lymph node metastasis, histological stage, and tumor grade. It was positively correlated with immune cell infiltration of B cells (R = 0.246), macrophages (R = 0.182), myeloid dendritic cells (R = 0.247), neutrophils (R = 0.117), and CD4+ T cells (R = 0.258) and negatively correlated with immune cell infiltration of CD8+ T cells (R = -0.107). A positive correlation was observed between HOXB13, MMP9 (R = 0.176), E2F1 (R = 0.241), and MEIS1 (R = 0.189) expression (p < 0.001). The expression level of HOXB13 was significantly downregulated in both HepG2 and PLC/PFR/5 cell lines transfected with HOXB13-siRNA compared to that in cells transfected with NC siRNA (p < 0.05). Additionally, HOXB13 significantly affected cell viability and wound healing. Conclusions: HOXB13 overexpression may lead to poor prognosis in patients with HCC. Additional in vivo studies are required to improve our understanding of the biological role and the exact mechanism of action of HOXB13 in HCC.

Relevance of glyco-biomakers and glycan profiles in cancer stem cells

Altered and aberrant glycosylation signatures have been linked to being a hallmark in a variety of human disorders including cancer. Cancer stem cells (CSCs), capable of self-renewal and differentiation, have recently been credited with a unique notion of disease genesis and implicated as the cause for initiation and recurrence of the disease in a new regime of neoplastic transformations hypothesis. Many biomarkers relating to diagnostic and prognostic intents have been discovered using the ubiquitous and abundant surface glycan patterns on CSCs. Various technological advancements have been developed to identify and determine concerns with glycosylation structure. However, the nature and purpose of the glycan moiety on these glycosylation pattern have not yet been thoroughly investigated. This review, thus, summarizes the process of glycosylation in CSCs, variations in glycosylation patterns in various stem cells, aberrant glycosylation patterns in cancer, the role of glycosylation in tumor cell adhesion, cell-matrix interactions, and signaling, as well as cancer detection and treatment. The function of carbohydrates as prospective serum biomarkers, some clinically authorized biomarkers, and potential novel biomarkers relating to cancer disease diagnosis and prognosis are also discussed in the review.

Mesothelin-based CAR-T cells exhibit potent antitumor activity against ovarian cancer

BACKGROUND

Ovarian cancer (OC) is characterized by its rapid growth and spread which, accompanied by a low 5-year survival rate, necessitates the development of improved treatments. In ovarian cancer, the selective overexpression of Mucin-16 (MUC16, CA125) in tumor cells highlights its potential as a promising target for developing anti-tumor therapies. However, the potential effectiveness of CAR-T cell therapy that targets MUC16 in ovarian cancer cells is unknown.

METHODS

The expression of MUC16 in viable OC cells was detected using immunofluorescence and flow cytometry techniques. A MSLN-CAR construct, comprising the MUC16-binding polypeptide region of mesothelin (MSLN), a CD8 hinge spacer and transmembrane domain, 4-1BB, and CD3ζ endo-domains; was synthesized and introduced into T cells using lentiviral particles. The cytotoxicity of the resultant CAR-T cells was evaluated in vitro using luciferase assays. Cytokine release by CAR-T cells was measured using enzyme-linked immunosorbent assays. The anti-tumor efficacy of the CAR-T cells was subsequently assessed in mice through both systemic and local administration protocols.

RESULTS

MSLN-CAR T cells exhibited potent cytotoxicity towards OVCAR3 cells and their stem-like cells that express high levels of MUC16. Also, MSLN-CAR T cells were inefficient at killing SKOV3 cells that express low levels of MUC16, but were potently cytotoxic to such cells overexpressing MUC16. Moreover, MSLN-CAR T cells delivered via tail vein or peritoneal injection could shrink OVCAR3 xenograft tumors in vivo, with sustained remission observed following peritoneal delivery of MSLN-CAR T cells.

CONCLUSIONS

Collectively, these results suggested that MSLN-CAR T cells could potently eliminate MUC16- positive ovarian cancer tumor cells both in vitro and in vivo, thereby providing a promising therapeutic intervention for MUC16-positive patients.

Efficient CAR T cell targeting of the CA125 extracellular repeat domain of MUC16

BACKGROUND

Ovarian cancer (OC) is the leading cause of death from gynecologic malignancies in the Western world. Contributing factors include a high frequency of late-stage diagnosis, the development of chemoresistance, and the evasion of host immune responses. Currently, debulking surgery and platinum-based chemotherapy are the treatment cornerstones, although recurrence is common. As the clinical efficacy of immune checkpoint blockade is low, new immunotherapeutic strategies are needed. Chimeric antigen receptor (CAR) T cell therapy empowers patients' own T cells to fight and eradicate cancer, and has been tested against various targets in OC. A promising candidate is the MUC16 ectodomain. This ectodomain remains on the cell surface after cleavage of cancer antigen 125 (CA125), the domain distal from the membrane, which is currently used as a serum biomarker for OC. CA125 itself has not been tested as a possible CAR target. In this study, we examined the suitability of the CA125 as a target for CAR T cell therapy.

METHODS

We tested a series of antibodies raised against the CA125 extracellular repeat domain of MUC16 and adapted them to the CAR format. Comparisons between these candidates, and against an existing CAR targeting the MUC16 ectodomain, identified K101 as having high potency and specificity. The K101CAR was subjected to further biochemical and functional tests, including examination of the effect of soluble CA125 on its activity. Finally, we used cell lines and advanced orthotopic patient-derived xenograft (PDX) models to validate, in vivo, the efficiency of our K101CAR construct.

RESULTS

We observed a high efficacy of K101CAR T cells against cell lines and patient-derived tumors, in vitro and in vivo. We also demonstrated that K101CAR functionality was not impaired by the soluble antigen. Finally, in direct comparisons, K101CAR, which targets the CA125 extracellular repeat domains, was shown to have similar efficacy to the previously validated 4H11CAR, which targets the MUC16 ectodomain.

CONCLUSIONS

Our in vitro and in vivo results, including PDX studies, demonstrate that the CA125 domain of MUC16 represents an excellent target for treating MUC16-positive malignancies.

Molecular mechanisms underlying the regulation of tumour suppressor genes in lung cancer

Tumour suppressor genes play a cardinal role in the development of a large array of human cancers, including lung cancer, which is one of the most frequently diagnosed cancers worldwide. Therefore, extensive studies have been committed to deciphering the underlying mechanisms of alterations of tumour suppressor genes in governing tumourigenesis, as well as resistance to cancer therapies. In spite of the encouraging clinical outcomes demonstrated by lung cancer patients on initial treatment, the subsequent unresponsiveness to first-line treatments manifested by virtually all the patients is inherently a contentious issue. In light of the aforementioned concerns, this review compiles the current knowledge on the molecular mechanisms of some of the tumour suppressor genes implicated in lung cancer that are either frequently mutated and/or are located on the chromosomal arms having high LOH rates (1p, 3p, 9p, 10q, 13q, and 17p). Our study identifies specific genomic loci prone to LOH, revealing a recurrent pattern in lung cancer cases. These loci, including 3p14.2 (FHIT), 9p21.3 (p16INK4a), 10q23 (PTEN), 17p13 (TP53), exhibit a higher susceptibility to LOH due to environmental factors such as exposure to DNA-damaging agents (carcinogens in cigarette smoke) and genetic factors such as chromosomal instability, genetic mutations, DNA replication errors, and genetic predisposition. Furthermore, this review summarizes the current treatment landscape and advancements for lung cancers, including the challenges and endeavours to overcome it. This review envisages inspired researchers to embark on a journey of discovery to add to the list of what was known in hopes of prompting the development of effective therapeutic strategies for lung cancer.

Structural basis for antibody recognition of the proximal MUC16 ectodomain

BACKGROUND

Mucin 16 (MUC16) overexpression is linked with cancer progression, metastasis, and therapy resistance in high grade serous ovarian cancer and other malignancies. The cleavage of MUC16 forms independent bimodular fragments, the shed tandem repeat sequence which circulates as a protein bearing the ovarian cancer biomarker (CA125) and a proximal membrane-bound component which is critical in MUC16 oncogenic behavior. A humanized, high affinity antibody targeting the proximal ectodomain represents a potential therapeutic agent against MUC16 with lower antigenic potential and restricted human tissue expression.

RESULTS

Here, we demonstrate the potential therapeutic versatility of the humanized antibody as a monoclonal antibody, antibody drug conjugate, and chimeric antigen receptor. We report the crystal structures of 4H11-scFv, derived from an antibody specifically targeting the MUC16 C-terminal region, alone and in complex with a 26-amino acid MUC16 segment resolved at 2.36 Å and 2.47 Å resolution, respectively. The scFv forms a robust interaction with an epitope consisting of two consecutive β-turns and a β-hairpin stabilized by 2 hydrogen bonds. The VH-VL interface within the 4H11-scFv is stabilized through an intricate network of 11 hydrogen bonds and a cation-π interaction.

CONCLUSIONS

Together, our studies offer insight into antibody-MUC16 ectodomain interaction and advance our ability to design agents with potentially improved therapeutic properties over anti-CA125 moiety antibodies.

Arming oncolytic viruses with bispecific T cell engagers: The evolution and current status

Oncolytic viruses (OVs) are emerging as therapeutically relevant anticancer agents as contemporary immunotherapy gains traction. Furthermore, OVs are an ideal platform for genetic modification to express therapeutic transgenes. Bispecific T cell engagers (BiTEs) can redirect T cells to tumor cells, resulting in targeted cytotoxicity. BiTEs have demonstrated success in hematological cancers but are rarely used in solid tumors. The drawbacks of BiTEs, including inadequate delivery and on-target-off-tumor activity have limited their efficacy. Combining OVs with BiTEs is a prospective area to investigate. This combined strategy can benefit from the best qualities of both therapies while overcoming the limitations.

Progress in the treatment of malignant ascites

Malignant ascites occurs as a symptom of the terminal stage of cancer, affecting the quality of life through abdominal distension, pain, nausea, anorexia, dyspnea and other symptoms. We describe the current main drug treatments in addition to surgery according to the traditional and new strategies. Traditional treatments were based on anti-tumor chemotherapy and traditional Chinese medicine treatments, as well as diuretics to relieve the patient's symptoms. New treatments mainly involve photothermal therapy, intestinal therapy and targeted immunity. This study emphasizes that both traditional and new therapies have certain advantages and disadvantages, and medication should be adjusted according to different periods of use and different patients. In conclusion, this article reviews the literature to systematically describe the primary treatment modalities for malignant ascites.

An exploration of the effect of Chinese herbal compound on the occurrence and development of large intestine cancer and intestinal flora

This study was conducted to observe the effect of Chinese herbal compound on the treatment of colon cancer using AOM/DSS-induced C57BL/6J colon cancer mice and to validate potential influence on intestinal flora of mice. A colorectal cancer (CRC) mouse model was built with a total of 50 C57BL/6J mice that were induced by administrating AOM/DSS. These experimental animals were split up into 5 groups, a control group, a model group, and low-, medium- and high-dose Chinese herbal compound groups. All mice were given Chinese herbal compound treatment, and the colon tissues of each group were harvested with the length measured and the number of colon polyps accounted. The Ki-67 expression in the colon tissues was detected via immuno-histochemistry. Relative quantification of the expression of genes and proteins was determined through qPCR and WB assays. Contents of IL-6, TNF-α, IFN-γ, and IL-10 in serum and colon tissues of mice were determined by ELISA. An additional 16S rRNA sequencing analysis was implemented for the identification of mouse intestinal flora. The results suggested that all low-, medium- or high-dose Chinese herbal compound could markedly inhibit the shortening of colon length and significant number reduction of colon polyps in the model group. The relative expression of genes and proteins (PCNA, Muc16, and MMP-9) associated with proliferation in mouse colon tissues were inhibited. In addition, compared with the model group, the contents of IL-6, TNF-α, and IFN-γ in serum and colon tissues were substantially decreased in the high-dose Chinese herbal compound group, thereby reducing the structure damage in colon tissues and the infiltration degree of inflammatory cells. Besides, the expression of TLR4/MyD88/NF-κB protein was markedly decreased. The 16S rRNA sequencing analysis demonstrated that mice in the model group had decreased intestinal flora diversity, and there were significant changes in flora abundance and amino acid metabolism between the control group and the model group. Taken together, the treatment of Chinese herbal compound against CRC in this study might be regulated by the TLR4/MyD88/NF-κB signaling pathway, and the imbalance in intestinal flora was also closely related to CRC occurrence.

Selection of Aptamers for Use as Molecular Probes in AFM Detection of Proteins

Currently, there is great interest in the development of highly sensitive bioanalytical systems for diagnosing diseases at an early stage, when pathological biomarkers are present in biological fluids at low concentrations and there are no clinical manifestations. A promising direction is the use of molecular detectors-highly sensitive devices that detect signals from single biomacromolecules. A typical detector in this class is the atomic force microscope (AFM). The high sensitivity of an AFM-based bioanalysis system is determined by the size of the sensing element of an atomic force microscope-the cantilever-the radius of the curvature of which is comparable to that of a biomolecule. Biospecific molecular probe-target interactions are used to ensure detection system specificity. Antibodies, aptamers, synthetic antibodies, and peptides can be used as molecular probes. This study has demonstrated the possibility of using aptamers as molecular probes for AFM-based detection of the ovarian cancer biomarker CA125. Antigen detection in a nanomolar solution was carried out using AFM chips with immobilized aptamers, commercially available or synthesized based on sequences from open sources. Both aptamer types can be used for antigen detection, but the availability of sequence information enables additional modeling of the aptamer structure with allowance for modifications necessary for immobilization of the aptamer on an AFM chip surface. Information on the structure and oligomeric composition of aptamers in the solution was acquired by combining small-angle X-ray scattering and molecular modeling. Modeling enabled pre-selection, before the experimental stage, of aptamers for use as surface-immobilized molecular probes.

Assessing genomic diversity and selective pressures in Bashan cattle by whole-genome sequencing data

Specific ecological environments and domestication have continuously influenced the physiological characteristics of Chinese indigenous cattle. Among them, Bashan cattle belongs to one of the indigenous breeds. However, the genomic diversity of Bashan cattle is still unknown. Published whole-genome sequencing (WGS) data of 13 Bashan cattle and 48 worldwide cattle were used to investigate the genetic composition and selection characteristics of Bashan cattle. The population structure analysis revealed that Bashan cattle harbored ancestries with East Asian taurine and Chinese indicine. Genetic diversity analysis implied the relatively high genomic diversity in Bashan cattle. Through the identification of containing >5 nsSNPs or frameshift mutations genes in Bashan cattle, a large number of pathways related to sensory perception were discovered. CLR, θπ ratio, FST, and XP-EHH methods were used to detect the candidate signatures of positive selection in Bashan cattle. Among the identified genes, most of the enriched signal pathways were related to environmental information processing, biological systems, and metabolism. We mainly reported genes related to the nervous system (HCN1, KATNA1, FSTL1, GRIK2, and CPLX2), immune (CD244, SLAMF1, LY9, and CD48), and reproduction (AKR1C1, AKR1C3, AKR1C4, and TUSC3). Our findings will be significant in understanding the molecular basis underlying phenotypic variation of breed-related traits and improving productivity in Bashan cattle.

MUC15 is an independent prognostic factor that promotes metastases of MYCN non-amplified neuroblastoma

Background: Neuroblastoma (NB) is a cancer that arises from neural-crest-derived sympathoadrenal lineage. Less is known about the pathogenesis and molecular characteristics of MYCN non-amplified (MYCN-NA) NB. Methods: We constructed a signature model targeting mucin family according to RNA sequencing data from GSE49710 dataset, and validated the prognostic performance. We also analyzed the gene expression matrix using DESeq2 R packages to screen the most differential mucin in high-risk NB samples. We further assessed its prognostic value, particularly in MYCN-NA NB samples. Moreover, we performed functional experiments to evaluate the impact of MUC15 overexpression on the migration of MYCN-NA NB cell lines. Results: The 8-mucin signature model showed good prognostic performance in the GSE49710 dataset. Among the mucin genes, MUC15 was significantly upregulated in the high-risk NB cohort and was associated with poor prognosis, especially in MYCN-NA NB samples. Furthermore, MUC15 overexpression and exogenous MUC15 protein enhanced the migration of MYCN-NA NB cell lines. Mechanistically, MUC15 promoted the phosphorylation of focal adhesion kinase (FAK) by inhibiting the expression of MYCT1, a target of c-Myc. Conclusions: Our findings suggested a potential network in controlling NB cell metastasis. Targeting MUC15 in MYCN-NA NB patients could be a promising therapeutic strategy.

Albumin Nanoparticles Surface Decorated with a Tumor-Homing Peptide Help in Selective Killing of Triple-Negative Breast Cancer Cells

In this article, we describe a method of delivery of doxorubicin using a novel tumor-homing peptide-based albumin nanoparticle system to triple-negative breast cancer cells (TNBC). The absence and reduced expression of the hormone (estrogen, progesterone) and HER2 (human epidermal growth factor 2) receptors, respectively, render TNBC patients nonsusceptible to different available targeted therapies. These peptide-modified nanoparticles could be taken up by TNBC cells more effectively than their bare counterparts. The drug-loaded peptide-modified nanoparticles achieved an optimal but crucial balance between cell killing in cancerous cells and cell survival in the noncancerous ones. This appears to be because of different routes of entry and subsequent fate of the bare and peptide-modified nanoparticles in cancerous and noncancerous cells. In a TNBC mouse model, the peptide-modified system fared better than the free drug in mounting an antitumor response while not being toxic systemically.

Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer

Endoplasmic reticulum stress (ERS) is caused by the accumulation of intracellular misfolded or unfolded proteins and is associated with cancer development. In this study, pan-cancer analysis revealed complex genetic variations, including copy number variation, methylation, and somatic mutations for ERS-related genes (ERGs) in 33 kinds of cancer. Consensus clustering divided pancreatic cancer (PC) patients from TCGA and GEO databases into two ERS-related subtypes: ERGcluster A and B. Compared with ERGcluster A, ERGcluster B had a more active ERS state and worse prognosis. Subsequently, the ERS-related prognostic model was established to quantify the ERS score for a single sample. The patient with a low ERS score had remarkably longer survival times. ssGSEA and CIBERSORT algorithms revealed that activated B cells and CD8+ T cells had higher infiltration in the low ERS score group, but higher infiltration of activated CD4+ T cells, activated dendritic cells, macrophages, and neutrophils in the high ERS score group. Drug sensitivity analysis indicated the low ERS score group had a better response to gemcitabine, paclitaxel, 5-fluorouracil, oxaliplatin, and irinotecan. RT-qPCR validated that MET, MUC16, and KRT7 in the model had higher expression levels in pancreatic tumour tissues. Single-cell analysis further revealed that MET, MUC16, and KRT7 were mainly expressed in cancer cells in PC tumour microenvironment. In all, we first constructed the ERS-related molecular subtypes and prognostic model in PC. Our research highlighted the vital role of ERS in PC and contributed to further research on molecular mechanisms and novel therapeutic strategies for PC in the future.

Identification and validation of a prognostic risk-scoring model based on the level of TIM-3 expression in acute myeloid leukemia

Acute myeloid leukemia (AML) is characterized by an unfavorable prognosis due to the presence of self-renewing leukemic stem cells (LSCs). The presence of T-cell immunoglobulin mucin-3 (TIM-3) on the surface of LSCs has been observed in various types of human AML, exerting an impact on the prognostic outcome. Exploring the hub genes associated with varying levels of TIM-3 expression offers a valuable approach to enhance our understanding of the underlying mechanisms involving TIM-3 and to identify potential prognostic indicators in AML. Nevertheless, to date, no research studies have reported a prognostic model that relies on the level of TIM-3 expression. In our study, we screen the hub-genes based on different expression level of TIM-3 through WGCNA. The prognostic risk-scoring model was constructed based on hub-genes. The results show the risk prognostic model has extraordinary ability to predict prognosis in both the training and validation sets. The high-risk group present poor prognosis with mutation of NPM1, TP53 (Multiple Hit) and FLT3(multiple hit), while IDH2 (Missense Mutation), MUC16 (Multiple Hit/Missense Mutation) occur mutation in low-risk group presenting favorite prognosis than high-risk group. Leukocyte cell-cell adhesion, regulation of T cell activation and I-κB kinase/NF-κB signaling enriched in high-risk group, involving in HSCs or LSCs anchoring to BM, which implicated in LSCs survival and chemotherapy resistance. B7-H3 (CD276) and CD276 would be the potential immune targets in high-risk group. The risk score model may help in distinguishing immune and molecular characteristics, predicting patient outcomes.

Meigs Syndrome and Elevated CA-125: Case Report and Literature Review of an Unusual Presentation Mimicking Ovarian Cancer

Background and Objectives: Meigs syndrome is represented by a benign adnexal tumor, ascites, and hydrothorax. Even though the ovarian mass is often characterized by a fibroma-like origin, cancer antigen-125 (CA-125) serum levels could be elevated as in the development of ovarian cancer. Here, we present the case of a patient with Meigs syndrome and increased CA-125. Materials and Methods: We performed systematic research for articles including similar cases in PubMed, EMBASE, and Scopus in February 2023, adopting the string of idioms: "Meigs syndrome AND Cancer antigen 125", and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Results: Eligible records were 25. Hydrothorax was right-sided in 10 cases over 25; left-sided in two patients over 25. Concerning ascites, two patients showed more than 6 L of ascitic fluid, whereas three patients had 6 L or less. CA-125 elevation ranged from 149 IU/mL to 3803 IU/mL. Adnexal mass histotypes were: struma ovarii (12 cases), thecomas (two cases), fibrothecomas (five cases), fibromas (five cases), and one sclerosing stromal tumor (SST). Conclusions: In postmenopausal women with elevated CA-125 serum levels and an adnexal mass suspicious for malignancy at ultrasound (US), ascites and pleural effusion, surgery, and histopathological examination are necessary. MS is a diagnostic option, with an excellent prognosis after exeresis of the mass.

Identification of mutation gene prognostic biomarker in multiple myeloma through gene panel exome sequencing and transcriptome analysis in Chinese population

BACKGROUND

The 5-year survival rate of multiple myeloma (MM) in China is less than 40%, with considerable individual heterogeneity. Gene mutations are important predictive biomarkers that influence MM treatment decision. The aim of our study was to uncover the clinical significance of mutated genes in MM in the Chinese population.

METHODS

Targeted exon panel sequencing was performed of 400 genes to detect the gene mutation status in plasma cells from 50 patients with MM. DAVID was used to explore the functions and pathways of mutated genes. Detection of mutant gene expression, prognosis and immune cell infiltration with GSE6477. GEO2R was utilized to identify differentially expressed genes (DEGs). Kaplan-Meier and CIBERSORT were applied to compare survival distributions and evaluate the gene expression associated with immune cell infiltration, respectively.

RESULTS

Mutations of 337 genes were identified in MM. The mutation types included SNP, INS, and DEL, but the dominant mutation type was SNP. Function and pathway analysis of mutant genes were performed to elucidate DNA modifications. We identified a total number of 660 downregulated and 587 upregulated genes from the GSE6477 dataset. Thirty-three common genes were present in both the mutant genes and DEGs. The functions and pathways of the mutated genes were enriched in myeloid cell differentiation, regulation of hemopoiesis, etc. Moreover, we found that the low expression of BCL6, BIRC3, HLA-DQA1, and VCAN was correlated with poor prognosis in MM.

CONCLUSIONS

The mutations and low expression of BCL6, BIRC3, HLA-DQA1, and VCAN were correlated with poor prognosis and immune cell infiltration in MM. This study is the first to reveal the spectrum of mutations in the Chinese population by the use of an NGS panel.

Inaugurating High-Throughput Profiling of Extracellular Vesicles for Earlier Ovarian Cancer Detection

Detecting early cancer through liquid biopsy is challenging due to the lack of specific biomarkers for early lesions and potentially low levels of these markers. The current study systematically develops an extracellular-vesicle (EV)-based test for early detection, specifically focusing on high-grade serous ovarian carcinoma (HGSOC). The marker selection is based on emerging insights into HGSOC pathogenesis, notably that it arises from precursor lesions within the fallopian tube. This work thus establishes murine fallopian tube (mFT) cells with oncogenic mutations and performs proteomic analyses on mFT-derived EVs. The identified markers are then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood of tumor-bearing mice, mFT-EV markers increase with tumor initiation, supporting their potential use in early cancer detection. A pilot clinical study (n = 51) further narrows EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. The combined expression of these markers distinguishes HGSOC from non-cancer with 89% sensitivity and 93% specificity. The same markers are also effective in classifying three groups (non-cancer, early-stage HGSOC, and late-stage HGSOC). The developed approach, for the first time inaugurated in fallopian tube-derived EVs, could be a minimally invasive tool to monitor women at high risk of ovarian cancer for timely intervention.

Whole-Exome Sequencing Reveals High Mutational Concordance between Primary and Matched Recurrent Triple-Negative Breast Cancers

PURPOSE

Triple-negative breast cancer (TNBC) is a molecularly complex and heterogeneous breast cancer subtype with distinct biological features and clinical behavior. Although TNBC is associated with an increased risk of metastasis and recurrence, the molecular mechanisms underlying TNBC metastasis remain unclear. We performed whole-exome sequencing (WES) analysis of primary TNBC and paired recurrent tumors to investigate the genetic profile of TNBC.

METHODS

Genomic DNA extracted from 35 formalin-fixed paraffin-embedded tissue samples from 26 TNBC patients was subjected to WES. Of these, 15 were primary tumors that did not have recurrence, and 11 were primary tumors that had recurrence (nine paired primary and recurrent tumors). Tumors were analyzed for single-nucleotide variants and insertions/deletions.

RESULTS

The tumor mutational burden (TMB) was 7.6 variants/megabase in primary tumors that recurred (n = 9); 8.2 variants/megabase in corresponding recurrent tumors (n = 9); and 7.3 variants/megabase in primary tumors that did not recur (n = 15). MUC3A was the most frequently mutated gene in all groups. Mutations in MAP3K1 and MUC16 were more common in our dataset. No alterations in PI3KCA were detected in our dataset.

CONCLUSIONS

We found similar mutational profiles between primary and paired recurrent tumors, suggesting that genomic features may be retained during local recurrence.

Chimeric antibody targeting unique epitope on onco-mucin16 reduces tumor burden in pancreatic and lung malignancies

Aberrantly expressed onco-mucin 16 (MUC16) and its post-cleavage generated surface tethered carboxy-terminal (MUC16-Cter) domain are strongly associated with poor prognosis and lethality of pancreatic (PC) and non-small cell lung cancer (NSCLC). To date, most anti-MUC16 antibodies are directed towards the extracellular domain of MUC16 (CA125), which is usually cleaved and shed in the circulation hence obscuring antibody accessibility to the cancer cells. Herein, we establish the utility of targeting a post-cleavage generated, surface-tethered oncogenic MUC16 carboxy-terminal (MUC16-Cter) domain by using a novel chimeric antibody in human IgG1 format, ch5E6, whose epitope expression directly correlates with disease severity in both cancers. ch5E6 binds and interferes with MUC16-associated oncogenesis, suppresses the downstream signaling pFAK(Y397)/p-p70S6K(T389)/N-cadherin axis and exert antiproliferative effects in cancer cells, 3D organoids, and tumor xenografts of both PC and NSCLC. The robust clinical correlations observed between MUC16 and N-cadherin in patient tumors and metastatic samples imply ch5E6 potential in targeting a complex and significantly occurring phenomenon of epithelial to mesenchymal transition (EMT) associated with disease aggressiveness. Our study supports evaluating ch5E6 with standard-of-care drugs, to potentially augment treatment outcomes in malignancies inflicted with MUC16-associated poor prognosis.

Genetic analysis of familial predisposition in the pathogenesis of malignant pleural mesothelioma

PURPOSE

Mesothelioma is the primary tumor of the mesothelial cell membrane. The most important etiology is asbestos exposure. The development of malignant mesothelioma in very few of the population exposed to asbestos and its frequent occurrence in some families may be significant in terms of genetic predisposition. Again, the presence of relatives with mesothelioma who did not have asbestos contact strengthens this argument. This disease, which has limited treatment options and has a poor prognosis, revealing a genetic predisposition, if any, may prolong survival with early diagnosis and effective treatment.

METHODS

Based on the genetic predisposition idea, we diagnosed and followed a total of ten individuals of relatives with mesothelioma. DNA was isolated from peripheral blood and whole genome sequencing analysis was done. Common gene mutations in ten individuals were filtered using bioinformatics. After this filter, from the remaining variants, very rare in the population and damaging mutations are selected.

RESULTS

Eight thousand six hundred and twenty-two common variants have been identified in ten individuals with this analysis. In total, 120 variants were found on 37 genes in 15 chromosomes. These genes are PIK3R4, SLC25A5, ITGB6, PLK2, RAD17, HLA-B, HLA-DRB1, HLA-DQB1, GRM, IL20RA, MAP3K7, RIPK2, and MUC16.

CONCLUSION

Our finding, PIK3R4 gene, is directly associated with mesothelioma development. Twelve genes, which are associated with cancer, were detected in literature. Additional studies, which scan first-degree relatives of individual, are needed to find the specific gene region.

Analysis of a large cohort of pancreatic cancer transcriptomic profiles to reveal the strongest prognostic factors

Pancreatic adenocarcinoma remains a leading cause of cancer-related deaths. In order to develop appropriate therapeutic and prognostic tools, a comprehensive mapping of the tumor's molecular abnormalities is essential. Here, our aim was to integrate available transcriptomic data to uncover genes whose elevated expression is simultaneously linked to cancer pathogenesis and inferior survival. A comprehensive search was performed in GEO to identify clinical studies with transcriptome-level gene expression data of pancreatic carcinoma with overall survival data and normal pancreatic tissues. After quantile normalization, the entire database was used to identify genes with altered expression. Cox proportional hazard regression was employed to uncover genes most strongly correlated with survival with a Bonferroni corrected p < 0.01. Perturbed biological processes and molecular pathways were identified to enable the understanding of underlying processes. A total of 16 available datasets were combined. The aggregated database comprised data of 1640 samples for 20,443 genes. When comparing with normal pancreatic tissues, a total of 2612 upregulated and 1977 downregulated genes were uncovered in pancreatic carcinoma. Among these, we found 24 genes with higher expression which significantly correlated with overall survival length also. The most significant genes were ANXA8, FAM83A, KRT6A, MET, MUC16, NT5E, and SLC2A1. These genes remained significant after a multivariate analysis also including grade and stage. Here, we assembled a large-scale database of pancreatic carcinoma samples and used this cohort to identify carcinoma-specific genes linked to altered survival outcomes. As our analysis focused on genes with higher expression, these could serve as future therapy targets.

Aberrant Glycosylation as Immune Therapeutic Targets for Solid Tumors

Glycosylation occurs at all major types of biomolecules, including proteins, lipids, and RNAs to form glycoproteins, glycolipids, and glycoRNAs in mammalian cells, respectively. The carbohydrate moiety, known as glycans on glycoproteins and glycolipids, is diverse in their compositions and structures. Normal cells have their unique array of glycans or glycome which play pivotal roles in many biological processes. The glycan structures in cancer cells, however, are often altered, some having unique structures which are termed as tumor-associated carbohydrate antigens (TACAs). TACAs as tumor biomarkers are glycan epitopes themselves, or glycoconjugates. Some of those TACAs serve as tumor glyco-biomarkers in clinical practice, while others are the immune therapeutic targets for treatment of cancers. A monoclonal antibody (mAb) to GD2, an intermediate of sialic-acid containing glycosphingolipids, is an example of FDA-approved immune therapy for neuroblastoma indication in young adults and many others. Strategies for targeting the aberrant glycans are currently under development, and some have proceeded to clinical trials. In this review, we summarize the currently established and most promising aberrant glycosylation as therapeutic targets for solid tumors.

Sequencing Analysis of MUC6 and MUC16 Gene Fragments in Patients with Oropharyngeal Squamous Cell Carcinoma Reveals Novel Mutations: A Preliminary Study

The growing incidence of oropharyngeal squamous cell carcinoma (OPSCC) calls for better understanding of the mutational landscape of such cases. Mucins (MUCs) are multifunctional glycoproteins expressed by the epithelial cells and may be associated with the epithelial tumour invasion and progression. The present study aimed at the analysis of the sequence of selected MUC6 and MUC16 gene fragments in the tumour, as well as the margin, samples obtained from 18 OPSCC patients. Possible associations between the detected mutations and the clinicopathological and demographic characteristics of the study group were analysed. Sanger sequencing and bioinformatic data analysis of the selected MUC6 and MUC16 cDNA fragments were performed. Our study found 13 and 3 mutations in MUC6 and MUC16, respectively. In particular, one novelty variant found that the MUC6 gene (chr11:1018257 A>T) was the most frequent across our cohort, in both the tumour and the margin samples, and was then classified as a high impact, stop-gain mutation. The current study found novel mutations in MUC6 and MUC16 providing new insight into the genetic alternation in mucin genes among the OPSCC patients. Further studies, including larger cohorts, are recommended to recognise the pattern in which the mutations affect oropharyngeal carcinogenesis.

Update value and clinical application of MUC16 (cancer antigen 125)

INTRODUCTION

The largest transmembrane mucin, mucin 16 (MUC16), contains abundant glycosylation sites on the molecular surface, allowing it to participate in various molecular pathways. When cells lose polarity and become cancerous, MUC16 is overexpressed, and more of the extracellular region (cancer antigen [CA]125) is released into serum and possibly, promote the development of diseases. Thus, MUC16 plays an indispensable role in clinical research and application.

AREAS COVERED

This review summarizes the update proposed role of MUC16 in carcinogenesis and metastasis. Most importantly, we prospect its potential value in targeted therapy after screening 1226 articles published within the last 10 years from PubMed. Two reviewers screened each record and each report retrieved independently. We have summarized the progress of MUC16/CA125 in basic research and clinical application, and predicted its possible future development directions.

EXPERT OPINION

As an important noninvasive co-factor in the diagnosis of gynecological diseases, MUC16 has been used for a long time, especially in the diagnosis and treatment of ovarian cancer. The overexpression of MUC16 plays a very obvious role in regulating inflammatory response, supporting immune suppression, and promoting the proliferation, division, and metastasis of cancer cells. In the next 20 years, there will be a luxuriant clinical application of MUC16 as a target for immune monitoring and immunotherapy.

Capitalizing glycomic changes for improved biomarker-based cancer diagnostics

Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.

Precision-engineered biomimetics: the human fallopian tube

The fallopian tube has an essential role in several physiological and pathological processes from pregnancy to ovarian cancer. However, there are no biologically relevant models to study its pathophysiology. The state-of-the-art organoid model has been compared to two-dimensional tissue sections and molecularly assessed providing only cursory analyses of the model's accuracy. We developed a novel multi-compartment organoid model of the human fallopian tube that was meticulously tuned to reflect the compartmentalization and heterogeneity of the tissue's composition. We validated this organoid's molecular expression patterns, cilia-driven transport function, and structural accuracy through a highly iterative platform wherein organoids are compared to a three-dimensional, single-cell resolution reference map of a healthy, transplantation-quality human fallopian tube. This organoid model was precision-engineered to match the human microanatomy.

One sentence summary

Tunable organoid modeling and CODA architectural quantification in tandem help design a tissue-validated organoid model.

Deciphering Protein O-GalNAcylation: Method Development and Disease Implication

Mucin-type O-glycosylation is an important protein post-translational modification that is abundantly expressed on cell surface proteins. Protein O-glycosylation plays a variety of roles in cellular biological functions including protein structure and signal transduction to the immune response. Cell surface mucins are highly O-glycosylated and are the main substance of the mucosal barrier that protects the gastrointestinal or respiratory tract from infection by pathogens or microorganisms. Dysregulation of mucin O-glycosylation may impair mucosal protection against pathogens that can invade cells to trigger infection or immune evasion. Truncated O-glycosylation, also known as Tn antigen or O-GalNAcylation, is highly upregulated in diseases such cancer, autoimmune disorders, neurodegenerative diseases, and IgA nephropathy. Characterization of O-GalNAcylation helps decipher the role of Tn antigen in physiopathology and therapy. However, the analysis of O-glycosylation, specifically the Tn antigen, remains challenging due to the lack of reliable enrichment and identification assays compared to N-glycosylation. Here, we summarize recent advances in analytical methods for O-GalNAcylation enrichment and identification and highlight the biological role of the Tn antigen in various diseases and the clinical implications of identifying aberrant O-GalNAcylation.

Altered Glycosylation in Progression and Management of Bladder Cancer

Bladder cancer (BC) is the 10th most common malignancy worldwide, with an estimated 573,000 new cases and 213,000 deaths in 2020. Available therapeutic approaches are still unable to reduce the incidence of BC metastasis and the high mortality rates of BC patients. Therefore, there is a need to deepen our understanding of the molecular mechanisms underlying BC progression to develop new diagnostic and therapeutic tools. One such mechanism is protein glycosylation. Numerous studies reported changes in glycan biosynthesis during neoplastic transformation, resulting in the appearance of the so-called tumor-associated carbohydrate antigens (TACAs) on the cell surface. TACAs affect a wide range of key biological processes, including tumor cell survival and proliferation, invasion and metastasis, induction of chronic inflammation, angiogenesis, immune evasion, and insensitivity to apoptosis. The purpose of this review is to summarize the current information on how altered glycosylation of bladder cancer cells promotes disease progression and to present the potential use of glycans for diagnostic and therapeutic purposes.

Whole-exome mutational landscape and molecular marker study in mucinous and clear cell ovarian cancer cell lines 3AO and ES2

BACKGROUND

Ovarian cancer is one of the most lethal cancers in women because it is often diagnosed at an advanced stage. The molecular markers investigated thus far have been unsatisfactory.

METHODS

We performed whole-exome sequencing on the human ovarian cancer cell lines 3AO and ES2 and the normal ovarian epithelial cell line IOSE-80. Molecular markers of ovarian cancer were screened from shared mutation genes and copy number variation genes in the 6q21-qter region.

RESULTS

We found that missense mutations were the most common mutations in the gene (93%). The MUC12, FLG and MUC16 genes were highly mutated in 3AO and ES2 cells. Copy number amplification occurred mainly in 4p16.1 and 11q14.3, and copy number deletions occurred in 4q34.3 and 18p11.21. A total of 23 hub genes were screened, of which 16 were closely related to the survival of ovarian cancer patients. The three genes CCDC170, THBS2 and COL14A1 are most significantly correlated with the survival and prognosis of ovarian cancer. In particular, the overall survival of ovarian cancer patients with high CCDC170 gene expression was significantly prolonged (P < 0.001). The expression of CCDC170 in normal tissues was significantly higher than that in ovarian cancer tissues (P < 0.05), and its expression was significantly decreased in advanced ovarian cancer. Western blotting and immunofluorescence assays also showed that the expression of CCDC170 in ovarian cancer cells was significantly lower than that in normal cells (P < 0.001, P < 0.01).

CONCLUSIONS

CCDC170 is expected to become a new diagnostic molecular target and prognostic indicator for ovarian cancer patients, which can provide new ideas for the design of antitumor drugs.

Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes of lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD), the major lung cancer histotype, represents 40% lung cancers. Currently, outcomes are remarkably different in LUAD patients with similar AJCC/UICC-TNM features. T cell proliferation-related regulator genes (TPRGs) relate to the proliferation, activity and function of T cells and tumor progression. The values of TPRGs in classifying LUAD patients and predicting outcomes remain unknown.

Methods

Gene expression profile and corresponding clinical data were downloaded from TCGA and the GEO databases. We systematically analyzed the expression profile characteristics of 35 TPRGs in LUAD patients and investigated the differences in overall survival (OS), biology pathway, immunity and somatic mutation between different TPRGs-related subtypes. Subsequently, we constructed a TPRGs-related risk model in TCGA cohort to quantify risk scores using LASSO cox regression analysis and then validated this risk model in two GEO cohorts. LUAD patients were divided into high- and low-risk subtypes according to the median risk score. We systematically compared the biology pathway, immunity, somatic mutation and drug susceptibility between the two risk subtypes. Finally, we validate biological functions of two TPRGs-encoded proteins (DCLRE1B and HOMER1) in LUAD cells A549.

Results

We identified different TPRGs-related subtypes (including cluster 1/cluster A and its counterpart cluster 2/cluster B). Compared to the cluster 1/cluster A subtype, cluster 2/cluster B subtype tended to have a prominent survival advantage with an immunosuppressive microenvironment and a higher somatic mutation frequency. Then, we constructed a TPRGs-related 6-gene risk model. The high-risk subtype characterized by higher somatic mutation frequency and lower immunotherapy response had a worse prognosis. This risk model was an independent prognostic factor and showed to be reliable and accurate for LUAD classification. Furthermore, subtypes with different risk scores were significantly associated with drug sensitivity. DCLRE1B and HOMER1 suppressed cell proliferation, migration and invasion in LUAD cells A549, which was in line with their prognostic values.

Conclusion

We construed a novel stratification model of LUAD based on TPRGs, which can accurately and reliably predict the prognosis and might be used as a predictive tool for LUAD patients.

Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer

BACKGROUND

Cuproptosis, a novel form of programmed cell death, plays an essential role in various cancers. However, studies of the function of cuproptosis lncRNAs (CRLs) in colorectal cancer (CRC) remain limited. Thus, this study aims to identify the cuprotosis-related lncRNAs (CRLs) in CRC and to construct the potential prognostic CRLs signature model in CRC.

METHODS

First, we downloaded RNA-Seq data and clinical information of CRC patients from TCGA database and obtained the prognostic CRLs based on typical expression analysis of cuproptosis-related genes (CRGs) and univariate Cox regression. Then, we constructed a prognostic model using the Least Absolute Shrinkage and Selection Operator algorithm combined with multiple Cox regression methods (Lasso-Cox). Next, we generated Kaplan-Meier survival and receiver operating characteristic curves to estimate the performance of the prognostic model. In addition, we also analysed the relationships between risk signatures and immune infiltration, mutation, and drug sensitivity. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT -PCR) to verify the prognostic model.

RESULT

Lasso-Cox analysis revealed that four CRLs, SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, were related to CRC prognosis. Receiver operating characteristic (ROC) and Kaplan-Meier analysis curves indicated that this model performs well in prognostic predictions of CRC patients. The DCA results also showed that the model included four gene signatures was better than the traditional model. In addition, GO and KEGG analyses revealed that DE-CRLs are enriched in critical signalling pathway, such as chemical carcinogenesis-DNA adducts and basal cell carcinoma. Immune infiltration analysis revealed significant differences in immune infiltration cells between the high-risk and low-risk groups. Furthermore, significant differences in somatic mutations were noted between the high-risk and low-risk groups. Finally, we also validated the expression of four CRLs in FHCs cell lines and CRC cell lines using qRT-PCR.

CONCLUSION

The signature composed of SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, which has better performance in predicting colorectal cancer prognosis and are promising biomarkers for prognosis prediction of CRC.

Target Antigen Attributes and Their Contributions to Clinically Approved Antibody-Drug Conjugates (ADCs) in Haematopoietic and Solid Cancers

Antibody drug conjugates (ADCs) are powerful anti-cancer therapies comprising an antibody joined to a cytotoxic payload through a chemical linker. ADCs exploit the specificity of antibodies for their target antigens, combined with the potency of cytotoxic drugs, to selectively kill target antigen-expressing tumour cells. The recent rapid advancement of the ADC field has so far yielded twelve and eight ADCs approved by the US and EU regulatory bodies, respectively. These serve as effective targeted treatments for several haematological and solid tumour types. In the development of an ADC, the judicious choice of an antibody target antigen with high expression on malignant cells but restricted expression on normal tissues and immune cells is considered crucial to achieve selectivity and potency while minimising on-target off-tumour toxicities. Aside from this paradigm, the selection of an antigen for an ADC requires consideration of several factors relating to the expression pattern and biological features of the target antigen. In this review, we discuss the attributes of antigens selected as targets for antibodies used in clinically approved ADCs for the treatment of haematological and solid malignancies. We discuss target expression, functions, and cellular kinetics, and we consider how these factors might contribute to ADC efficacy.

MUC16 promotes triple-negative breast cancer lung metastasis by modulating RNA-binding protein ELAVL1/HUR

BACKGROUND

Triple-negative breast cancer (TNBC) is highly aggressive with an increased metastatic incidence compared to other breast cancer subtypes. However, due to the absence of clinically reliable biomarkers and targeted therapy in TNBC, outcomes are suboptimal. Hence, there is an urgent need to understand biological mechanisms that lead to identifying novel therapeutic targets for managing metastatic TNBC.

METHODS

The clinical significance of MUC16 and ELAVL1 or Hu antigen R (HuR) was examined using breast cancer TCGA data. Microarray was performed on MUC16 knockdown and scramble TNBC cells and MUC16-associated genes were identified using RNA immunoprecipitation and metastatic cDNA array. Metastatic properties of MUC16 were evaluated using tail vein experiment. MUC16 and HuR downstream pathways were confirmed by ectopic overexpression of MUC16-carboxyl-terminal (MUC16-Cter), HuR and cMyc as well as HuR inhibitors (MS-444 and CMLD-2) in TNBC cells.

RESULTS

MUC16 was highly expressed in TNBC and correlated with its target HuR. Depletion of MUC16 showed decreased invasion, migration, and colony formation abilities of human and mouse TNBC cells. Mice injected with MUC16 depleted cells were less likely to develop lung metastasis (P = 0.001). Notably, MUC16 and HuR were highly expressed in the lung tropic TNBC cells and lung metastases. Mechanistically, we identified cMyc as a HuR target in TNBC using RNA immunoprecipitation and metastatic cDNA array. Furthermore, MUC16 knockdown and pharmacological inhibition of HuR (MS-444 and CMLD-2) in TNBC cells showed a reduction in cMyc expression. MUC16-Cter or HuR overexpression models indicated MUC16/HuR/cMyc axis in TNBC cell migration.

CONCLUSIONS

Our study identified MUC16 as a TNBC lung metastasis promoter that acts through HuR/cMyc axis. This study will form the basis of future studies to evaluate the targeting of both MUC16 and HuR in TNBC patients.

Development of Triple-Negative Breast Cancer-Targeted Liposomes with MUC16 Binding Peptide Ligand in Triple-Negative Breast Cancer Cells

Triple-negative breast cancer (TNBC) is a highly malignant tumor that does not express the estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (HER-2). As molecular approaches to these targets have limited clinical utility in TNBC, novel strategies for the treatment of TNBC are urgently needed. MUC16 (Mucin-16) is a glycoprotein involved in cell proliferation and apoptosis and is overexpressed in breast cancer. To develop a clinically available strategy for TNBC treatment, we synthesized a MUC16 targeted peptide (EVQ)-grafted lipid derivative, EVQ-(SG)₅-lipid, and prepared EVQ-(SG)₅/PEGylated liposomes of 100 nm by size and a slightly negative ζ-potential value. Thus, we aimed at investigating the association between EVQ-(SG)₅/PEGylated and TNBC cell lines by interacting with MUC16 using an in vitro model. In addition, we aimed at exploring the intracellular distribution and cellular uptake pathway of EVQ-(SG)₅/PEGylated liposomes as novel drug delivery carriers for TNBC.

The hidden potential of glycomarkers: Glycosylation studies in the service of cancer diagnosis and treatment

Changes in the glycosylation process appear early in carcinogenesis and evolve with the growth and spread of cancer. The correlation of the characteristic glycosylation signature with the tumor stage and the appropriate therapy choice is an important issue in translational medicine. Oncologists also pay attention to extracellular vesicles as reservoirs of new cancer glycomarkers that can be potent for cancer diagnosis/prognosis. In this review, we recall glycomarkers used in oncology and show their new glycoforms of improved clinical relevance. We summarize current knowledge on the biological functions of glycoepitopes in cancer-derived extracellular vesicles and their potential use in clinical practice. Is glycomics a future of cancer diagnosis? It may be, but in combination with other omics analyses than alone.

Electrochemical immunosensing by carbon ink/carbon dot/ZnO-labeled-Ag@polypyrrole composite biomarker for CA-125 ovarian cancer detection

In this work, we demonstrated a novel cancer antigen 125 (CA125) biomarker detection based on electrochemical immunosensor. The biomarker on conductive composite materials of carbon ink/carbon dot/zine oxide (C-ink/CD/ZnO) was employed as an electrode platform by using ITO substrate to enhance the interaction of antibodies (Ab) with supporting catalytic performance of ZnO as a labeling signal molecule. They were a scientist attention for biosensor with chemical stability, strong biocompatibility, high conductive signal, and accuracy. Moreover, the nanocomposite of silver@polypyrrole (Ag@PPy) was used as a potential redox mediator. The labeled construction with Ag@PPy was more accuracy than that of a free-labeled. The created immunosensor was a wide linear range as 1 ag·mL^-1 - 100 ng·mL^-1 and a low limitation of detection as 0.1 fg·mL^-1 under the optimal condition. This suggested that the immunosensor is considered to be an accurate and efficient diagnostic tool for CA125 and other biomarkers detection in actual sample analysis for clinic.

A random forest-based metabolic risk model to assess the prognosis and metabolism-related drug targets in ovarian cancer

As one of the most common gynecologic malignant tumors, ovarian cancer is usually diagnosed at an advanced and incurable stage because of its early asymptomatic onset. Increasing research into tumor biology has demonstrated that abnormal cellular metabolism precedes tumorigenesis, therefore it has become an area of active research in academia. Cellular metabolism is of great significance in cancer diagnostic and prognostic studies. In this study, we integrated The Cancer Genome Atlas dataset with multiple Gene Expression Omnibus ovarian cancer datasets, identified 17 metabolic pathways with prognostic values using the random forest algorithm, constructed a metabolic risk scoring model based on metabolic pathway enrichment scores, and classified patients with ovarian cancer into two subtypes. Then, we systematically investigated the differences between different subtypes in terms of prognosis, differential gene expression, immune signature enrichment, Hallmark signature enrichment, and somatic mutations. As well, we successfully predicted differences in sensitivity to immunotherapy and chemotherapy drugs in patients with different metabolic risk subtypes. Moreover, we identified 5 drug targets associated with high metabolic risk and low metabolic risk ovarian cancer phenotypes through the weighted correlation network analysis and investigated their roles in the genesis of ovarian cancer. Finally, we developed an XGBoost classifier for predicting metabolic risk types in patients with ovarian cancer, producing a good predictive effect. In light of the above study, the research findings will provide valuable information for prognostic prediction and personalized medical treatment of patients with ovarian cancer.

Duplex-immunoassay of ovarian cancer biomarker CA125 and HE4 based carbon dot decorated dendritic mesoporous silica nanoparticles

Fluorescent lateral flow immunoassay (FLFIA) is widely used mainly because of its low cost and instant detection. Its limit of detection (LOD) is closely related to fluorescence signals, and the development of fluorescence signals with fine performance remains a challenge. In this work, dendritic mesoporous silica nanoparticles (DMSNs) were used as fine carriers due to their large pore size and stable performance. We successfully synthesized carbon dots (CDs) with a 560 nm maximum emission wavelength (CD₅₆₀) by the hydrothermal method. A new type of fluorescence signal for FLFIA was observed by loading CD₅₆₀ on DMSNs through the Si-O bond which is denoted as DMSNs@CD₅₆₀. Applying DMSNs@CD₅₆₀ to the FLFIA can eliminate the influence of interfacial background blue fluorescence thus improving its detection sensitivity. The formed DMSNs@CD₅₆₀-FLFIA achieved high sensitivity detection of ovarian cancer biomarkers carbohydrate antigen 125 (CA125) and human epididymal protein 4 (HE4). The LOD of CA125 is 0.5 U mL^-1 and the correlation coefficient R² = 0.985, and the LOD of HE4 reaches 0.05 ng mL^-1 and the correlation coefficient R² = 0.981. The DMSNs@CD₅₆₀-FLFIA is sensitive and efficient providing a new method for the early diagnosis of ovarian cancer.

Target Selection for T-Cell Therapy in Epithelial Ovarian Cancer: Systematic Prioritization of Self-Antigens

Adoptive T cell-receptor therapy (ACT) could represent a promising approach in the targeted treatment of epithelial ovarian cancer (EOC). However, the identification of suitable tumor-associated antigens (TAAs) as targets is challenging. We identified and prioritized TAAs for ACT and other immunotherapeutic interventions in EOC. A comprehensive list of pre-described TAAs was created and candidates were prioritized, using predefined weighted criteria. Highly ranked TAAs were immunohistochemically stained in a tissue microarray of 58 EOC samples to identify associations of TAA expression with grade, stage, response to platinum, and prognosis. Preselection based on expression data resulted in 38 TAAs, which were prioritized. Along with already published Cyclin A1, the TAAs KIF20A, CT45, and LY6K emerged as most promising targets, with high expression in EOC samples and several identified peptides in ligandome analysis. Expression of these TAAs showed prognostic relevance independent of molecular subtypes. By using a systematic vetting algorithm, we identified KIF20A, CT45, and LY6K to be promising candidates for immunotherapy in EOC. Results are supported by IHC and HLA-ligandome data. The described method might be helpful for the prioritization of TAAs in other tumor entities.

Profiling extracellular vesicles in circulation enables the early detection of ovarian cancer

Ovarian cancer is a heterogeneous group of tumors in both cell type and natural history. While outcomes are generally favorable when detected early, the most common subtype, high-grade serous carcinoma (HGSOC), typically presents at an advanced stage and portends less favorable prognoses. Its aggressive nature has thwarted early detection efforts through conventional detection methods such as serum CA125 and ultrasound screening and thus inspired the investigation of novel biomarkers. Here, we report the systematic development of an extracellular-vesicle (EV)-based test to detect early-stage HGSOC. Our study is based on emerging insights into HGSOC biology, notably that it arises from precursor lesions within the fallopian tube before traveling to ovarian and/or peritoneal surfaces. To identify HGSOC marker candidates, we established murine fallopian tube (mFT) cells with oncogenic mutations in Brca1/2, Tp53 , and Pten genes, and performed proteomic analyses on mFT EVs. The identified markers were then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood samples of tumor-bearing mice, mFT-EV markers increased with tumor initiation, supporting their potential use in early cancer detection. A pilot human clinical study ( n = 51) further narrowed EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. Combined expression of these markers achieved high OvCa diagnostic accuracy (cancer vs. non-cancer) with a sensitivity of 0.89 and specificity of 0.93. The same five markers were also effective in a three-group classification: non-cancer, early-stage (I & II) HGSOC, and late-stage (III & IV) HGSOC. In particular, they differentiated early-stage HGSOC from the rest with a specificity of 0.91. Minimally invasive and repeatable, this EV-based testing could be a versatile and serial tool for informing patient care and monitoring women at high risk for ovarian cancer.

Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning

BACKGROUND

Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough.

METHODS

The primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets.

RESULTS

Here we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75-1.0), sensitivity of 92% (95% CI 0.54-1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74-0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17-0.83, at 90% specificity).

CONCLUSIONS

The ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.