Isoforms of MUC16 activate oncogenic signaling through EGF receptors to enhance the progression of pancreatic cancer

Redefining phenotypic intratumor heterogeneity of pancreatic ductal adenocarcinoma: a bottom-up approach

Pancreatic ductal adenocarcinoma (PDAC) tumor interpatient heterogeneity has been well described with two major prognostic subtypes (classical and basal-like). An important intrapatient heterogeneity has been reported but has not yet been studied extensively due to the lack of standardized, reproducible, and easily accessible high-throughput methods. We built an immunohistochemical (IHC) tool capable of differentiating RNA-defined classical and basal-like tumors by selecting relevant antibodies using a multistep process. The successive stages of (i) an in silico selection from a literature review and a bulk transcriptome analysis of 309 PDACs, (ii) a tumor-specific selection from 30 patient-derived xenografts and single-cell data, followed by (iii) the validation on tissue microarrays in 50 PDAC were conducted. We used our final IHC panel on two independent cohorts of resected PDAC (n = 95, whole-slide, n = 148, tissue microarrays) for external validation. After digitization and registration of pathology slides, we performed a tile-based analysis in tumor areas to identify relevant marker combinations. Sequential marker selection led to the following panel: GATA6, CLDN18, TFF1, MUC16, S100A2, KRT17, PanBasal. Four different phenotypes were identified: one classical, one intermediate (KRT17+), and two basal-like (MUC16+ versus S100A2+) with specific biological properties. The presence of a minor basal contingent drastically reduced overall survival [hazard ratio (HR) = 1.90, p = 0.03], even in classical predominant PDACs. Analysis of preneoplastic lesions suggested that pancreatic carcinogenesis might follow a progressive evolution from classical toward a basal through an early intermediate phenotype. In conclusion, our IHC panel redefined and easily assessed the high degree of intra- and intertumoral heterogeneity of PDAC. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Humanized Anti-MUC16 Antibody-Conjugated Contrast Agents for Magnetic Resonance Imaging of Pancreatic Cancer

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) is diagnosed at a late stage with distant metastasis in an overwhelming 50% of cases, and the prognosis is poor. Treating this extremely aggressive disease with standard-of-care therapies has led to modest benefits in overall survival, mainly due to a lack of targeted early treatment modalities, as early detection has not yet been possible. Mucin-16 (MUC16) is a glycoprotein overexpressed in more than 60% of patients with PDAC and is a tumor-specific biomarker. Methods: In this study, a magnetic resonance imaging (MRI) probe to facilitate the detection of early and late lesions of PDAC is developed by conjugating a MUC16-targeted humanized antibody (huAR9.6) with gadolinium. Results: In preclinical mouse models, this MUC16-targeted MRI probe demonstrates effective contrast enhancement in early lesions of PDAC in the subcutaneous setting and allows for the detection of late-stage pancreatic cancer tumors in an orthotopic model. The probe did not induce any toxicity in vital organs at the administered doses. Conclusions: This study establishes that synthesizing a MUC16-targeted MRI probe is feasible and allows for the better high-resolution contrast enhancement of MUC16+ PDAC lesions to facilitate detection and possibly better treatment strategies.

MUC16/CA125 in cancer: new advances

MUC16/CA125 is a common diagnostic marker for many types of cancer. However, due to the widespread expression of MUC16 in cancer, its specificity and sensitivity as a target are poor, which severely limits its clinical application. In recent years, various studies have shown that the clinical application potential of MUC16/CA125 has been greatly improved. The update of detection technology improves the accuracy and range of detection, and improves the early diagnosis rate of cancer. Targeting MUC16/CA125 is an important strategy for tumor therapy. Targeting residual amino acids, n-glycoylation structures or other targets on the surface of MUC16 cells can greatly improve the accuracy of detection and therapy. The new drug delivery method broke through the original technical shackles, targeted MUC16 positive cells more specifically and improved the drug efficacy. In this paper, the technological advances in detecting and identifying MUC16 targets and the great progress in cancer screening and treatment based on MUC16 as a target are described in detail, revealing the great potential of MUC16 as a target in cancer screening and treatment, and illustrating the potential clinical application value of MUC16.

Pretargeted alpha therapy in MUC16-positive high-grade serous ovarian cancer

BACKGROUND

Peritoneal metastasis with micrometastatic cell clusters is a common feature of advanced ovarian cancer. Targeted alpha therapy (TAT) is an attractive approach for treating micrometastatic diseases as alpha particles release enormous amounts of energy within a short distance. A pretargeting approach - leveraging the inverse-electron-demand Diels-Alder reaction between tetrazines (Tz) and trans-cyclooctene (TCO) - can minimize off-target toxicity related to TAT, often associated with full-length antibodies. We hypothesized that a pretargeting strategy could effectively treat high-grade serous (HGS) ovarian tumors while minimizing toxicity.

METHODS

We utilized the humanized antibody, AR9.6, labeled with actinium-225 (225Ac). AR9.6 targets fully glycosylated and hypoglycosylated isoforms of MUC16. For biodistribution and radioimmunotherapy studies, AR9.6-TCO was injected into OVCAR3-bearing mice 72 h before administering [225Ac]Ac-mcp-PEG8-Tz, e.g. using a 1,2,4,5-tetrazine conjugated to the macropa chelator via a polyethylene glycol (PEG) linker.

RESULTS

Biodistribution data revealed that the pretargeting approach achieved substantial tumor uptake. Cerenkov luminescence imaging confirmed successful in vivo pretargeting during TAT studies. Compared to the control groups, TAT with AR9.6-TCO and [225Ac]Ac-mcp-PEG8-Tz significantly suppressed tumor growth and improved overall survival in OVCAR3 tumor-bearing mice. Renal and ovarian pathology compatible with toxicity was observed in mice in addition to transient hematologic toxicity.

CONCLUSION

We confirmed that pretargeting with AR9.6-TCO and [225Ac]Ac-mcp-PEG8-Tz has durable antitumor effects in high MUC16-expressing tumors. These findings demonstrate great potential for using pretargeting in combination with TAT for the treatment of ovarian cancer.

CLASSIFICATION

Biological Sciences; Applied Biological Sciences.

Muc16CD is a novel CAR T cell target antigen for the treatment of pancreatic cancer

Pancreatic cancer is an aggressive malignancy with a 5-year survival rate of 13% that remains refractory to current immunotherapies, such as chimeric antigen receptor (CAR) T cells. These engineered cells can produce robust anti-tumor responses but require a reliable tumor-associated antigen (TAA) target. Here, we describe the retained ectodomain of Muc16, Muc16CD, as a novel TAA for targeting by CAR T cell therapy in pancreatic cancer. We establish clinically relevant, endogenous Muc16 and Muc16CD expression in pancreatic tumor tissues for CAR T cell targeting. Muc16CD-directed CAR T cells can both recognize and activate in a polyfunctional manner in response to patient-derived pancreatic tumor cells. Last, we demonstrate that Muc16CD-directed CAR T cells can elicit an anti-tumor response in vivo with significantly enhanced tumor control and survival benefits in a pancreatic tumor model. Overall, these findings demonstrate the utility of Muc16CD-targeted CAR T cell therapy in the novel setting of pancreatic cancer.

The glycogene alterations and potential effects in esophageal squamous cell carcinoma

BACKGROUND

Aberrant glycosylation is one of the hallmarks of cancer. The profile of glycoprotein expression caused by abnormal glycosylation has been revealed, while abnormal glycogenes that may disturb the structure of glycans have not yet been identified in esophageal squamous cell carcinoma (ESCC).

METHODS

Genomic alterations driven by differentially expressed glycogenes in ESCC were compared with matched normal tissues by multi-omics analysis. Immunohistochemistry, MTT, colony formation, transwell assays, subcutaneous tumor formation experiments and tail vein injection were used to study the expression and the effect on the proliferation and metastasis of the differentially expressed glycogenes POFUT1 and RPN1 in ESCC. In the alkyne fucose labeling experiment, AAL lectin affinity chromatography and immunoprecipitation were used to explore the mechanism of POFUT1 in ESCC.

RESULTS

The expression of the POFUT1 and RPN1 glycogenes were upregulated, as determined by genomic copy number gain and proteomics analysis. The overexpression of POFUT1 or RPN1 was associated with poor prognosis in ESCC patients and affected the proliferation and metastasis of ESCC in vivo and in vitro. The overexpression of POFUT1 increased the overall fucosylation level and activated the Notch signaling pathway, which partially mediated POFUT1 induced pro-migration in ESCC. The regulation of malignant progression of ESCC by RPN1 may be related to the TNF signaling pathway, p53 signaling pathway, etc. CONCLUSIONS: Our study fills a gap in the study of abnormal glycogenes and highlights the potential role of the POFUT1/Notch axis in ESCC. Moreover, our study identifies POFUT1 and RPN1 as promising anticancer targets in ESCC.

A signal-diffusion-based unsupervised contrastive representation learning for spatial transcriptomics analysis

MOTIVATION

Spatial transcriptomics allows for the measurement of high-throughput gene expression data while preserving the spatial structure of tissues and histological images. Integrating gene expression, spatial information, and image data to learn discriminative low-dimensional representations is critical for dissecting tissue heterogeneity and analyzing biological functions. However, most existing methods have limitations in effectively utilizing spatial information and high-resolution histological images. We propose a signal-diffusion-based unsupervised contrast learning method (SDUCL) for learning low-dimensional latent embeddings of cells/spots.

RESULTS

SDUCL integrates image features, spatial relationships, and gene expression information. We designed a signal diffusion microenvironment discovery algorithm, which effectively captures and integrates interaction information within the cellular microenvironment by simulating the biological signal diffusion process. By maximizing the mutual information between the local representation and the microenvironment representation of cells/spots, SDUCL learns more discriminative representations. SDUCL was employed to analyze spatial transcriptomics datasets from multiple species, encompassing both normal and tumor tissues. SDUCL performed well in downstream tasks such as clustering, visualization, trajectory inference, and differential gene analysis, thereby enhancing our understanding of tissue structure and tumor microenvironments.

AVAILABILITY AND IMPLEMENTATION

https://github.com/WeiMin-Li-visual/SDUCL.

Single-cell analysis of matrisome-related genes in breast invasive carcinoma: new avenues for molecular subtyping and risk estimation

Background

The incidence of breast cancer remains high and severely affects human health. However, given the heterogeneity of tumor cells, identifying additional characteristics of breast cancer cells is essential for accurate treatment.

Purpose

This study aimed to analyze the relevant characteristics of matrix genes in breast cancer through the multigroup data of a breast cancer multi-database.

Methods

The related characteristics of matrix genes in breast cancer were analyzed using multigroup data from the breast cancer multi database in the Cancer Genome Atlas, and the differential genes of breast cancer matrix genes were identified using the elastic net penalty logic regression method. The risk characteristics of matrix genes in breast cancer were determined, and matrix gene expression in different breast cancer cells was evaluated using real-time fluorescent quantitative polymerase chain reaction (PCR). A consensus clustering algorithm was used to identify the biological characteristics of the population based on the matrix molecular subtypes in breast cancer, followed by gene mutation, immune correlation, pathway, and ligand-receptor analyses.

Results

This study reveals the genetic characteristics of cell matrix related to breast cancer. It is found that 18.1% of stromal genes are related to the prognosis of breast cancer, and these genes are mostly concentrated in the biological processes related to metabolism and cytokines in protein. Five different matrix-related molecular subtypes were identified by using the algorithm, and it was found that the five molecular subtypes were obviously different in prognosis, immune infiltration, gene mutation and drug-making gene analysis.

Conclusions

This study involved analyzing the characteristics of cell-matrix genes in breast cancer, guiding the precise prevention and treatment of the disease.

Molecular Subtypes Defined by Cuproptosis-Associated Genes, Prognostic Model Development, and Tumor Immune Microenvironment Characterization in Adrenocortical Carcinoma

Introduction

This study aims to explore the role of cuproptosis-related genes in ACC, utilizing data from TCGA and GEO repositories, and to develop a predictive model for patient stratification.

Methods

A cohort of 123 ACC patients with survival data was analyzed. RNA-seq data of 17 CRGs were examined, and univariate Cox regression identified prognostic CRGs. A cuproptosis-related network was constructed to show interactions between CRGs. Consensus clustering classified ACC into three subtypes, with transcriptional and survival differences assessed by PCA and survival analysis. Gene set variation analysis (GSVA) and ssGSEA evaluated functional and immune infiltration characteristics across subtypes. Differentially expressed genes (DEGs) were identified, and gene clusters were established. A risk score (CRG_score) was generated using LASSO and multivariate Cox regression, validated across datasets. Tumor microenvironment, stem cell index, mutation status, drug sensitivity, and hormone synthesis were examined in relation to the CRG_score. Protein expression of key genes was validated, and functional studies on ASF1B and NDRG4 were performed.

Results

Three ACC subtypes were identified with distinct survival outcomes. Subtype B showed the worst prognosis, while subtype C had the best. We identified 214 DEGs linked to cell proliferation and classified patients into three gene clusters, confirming their prognostic value. The CRG_score predicted patient outcomes, with high-risk patients demonstrating worse survival and possible resistance to immunotherapy. Drug sensitivity analysis suggested higher responsiveness to doxorubicin and etoposide in high-risk patients.

Conclusion

This study suggests the potential prognostic value of CRGs in ACC. The CRG_score model provides a robust tool for risk stratification, with implications for treatment strategies.

Predicting recurrent glioblastoma clinical outcome to immune checkpoint inhibition and low-dose bevacizumab with tumor in situ fluid circulating tumor DNA analysis

OBJECTIVE

Most recurrent glioblastoma (rGBM) patients do not benefit from immune checkpoint inhibition, emphasizing the necessity for response biomarkers. This study evaluates whether tumor in situ fluid (TISF) circulating tumor DNA (ctDNA) could serve as a biomarker for response to low-dose bevacizumab (Bev) plus anti-PD-1 therapy in rGBM patients, aiming to enhance systemic responses to immunotherapy.

METHODS

In this phase II trial, 32 GBM patients with first recurrence after standard therapy were enrolled and then received tislelizumab plus low-dose Bev each cycle. TISF samples were analyzed for ctDNA using a 551-gene panel before each treatment.

RESULTS

The median progression-free survival (mPFS) and overall survival (mOS) were 8.2 months (95% CI, 5.2-11.1) and 14.3 months (95% CI, 6.5-22.1), respectively. The 12-month OS was 43.8%, and the objective response rate was 56.3%. Patients with more than 20% reduction in the mutant allele fraction and tumor mutational burden after treatment were significantly associated with better prognosis compared to baseline TISF-ctDNA. Among detectable gene mutations, patients with MUC16 mutation, EGFR mutation & amplification, SRSF2 amplification, and H3F3B amplification were significantly associated with worse prognosis.

CONCLUSIONS

Low-dose Bev plus anti-PD-1 therapy significantly improves OS in rGBM patients, offering guiding significance for future individualized treatment strategies. TISF-ctDNA can monitor rGBM patients' response to combination therapy and guide treatment.

CLINICAL TRIAL REGISTRATION

This trial is registered with ClinicalTrials.gov, NCT05540275.

GDNF-induced phosphorylation of MUC21 promotes pancreatic cancer perineural invasion and metastasis by activating RAC2 GTPase

Perineural invasion (PNI) is an adverse prognostic feature of pancreatic ductal adenocarcinoma (PDAC). However, the understanding of the interactions between tumors and neural signaling within the tumor microenvironment is limited. In the present study, we found that MUC21 servers as an independent risk factor for poor prognosis in PDAC. Furthermore, we demonstrated that MUC21 promoted the metastasis and PNI of PDAC cells by activating JNK and inducing epithelial-mesenchymal transition (EMT). Mechanistically, glial cell-derived neurotrophic factor, secreted by Schwann cells, phosphorylates the intracellular domain S543 of MUC21 via CDK1 in PDAC cells, facilitating the interaction between MUC21 and RAC2. This interaction leads to membrane anchoring and activation of RAC2, which in turn activates the JNK/ZEB1/EMT axis, ultimately enhancing the metastasis and PNI of PDAC cells. Our results present a novel mechanism of PNI, suggesting that MUC21 is a potential prognostic marker and therapeutic target for PDAC.

Novel progressive deep learning algorithm for uncovering multiple single nucleotide polymorphism interactions to predict paclitaxel clearance in patients with nonsmall cell lung cancer

Background

The rate at which the anticancer drug paclitaxel is cleared from the body markedly impacts its dosage and chemotherapy effectiveness. Importantly, paclitaxel clearance varies among individuals, primarily because of genetic polymorphisms. This metabolic variability arises from a nonlinear process that is influenced by multiple single nucleotide polymorphisms (SNPs). Conventional bioinformatics methods struggle to accurately analyze this complex process and, currently, there is no established efficient algorithm for investigating SNP interactions.

Methods

We developed a novel machine-learning approach called GEP-CSIs data mining algorithm. This algorithm, an advanced version of GEP, uses linear algebra computations to handle discrete variables. The GEP-CSI algorithm calculates a fitness function score based on paclitaxel clearance data and genetic polymorphisms in patients with nonsmall cell lung cancer. The data were divided into a primary set and a validation set for the analysis.

Results

We identified and validated 1184 three-SNP combinations that had the highest fitness function values. Notably, SERPINA1, ATF3 and EGF were found to indirectly influence paclitaxel clearance by coordinating the activity of genes previously reported to be significant in paclitaxel clearance. Particularly intriguing was the discovery of a combination of three SNPs in genes FLT1, EGF and MUC16. These SNPs-related proteins were confirmed to interact with each other in the protein-protein interaction network, which formed the basis for further exploration of their functional roles and mechanisms.

Conclusion

We successfully developed an effective deep-learning algorithm tailored for the nuanced mining of SNP interactions, leveraging data on paclitaxel clearance and individual genetic polymorphisms.

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.

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.

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.

Targeted and Self-Adjuvated Nanoglycovaccine Candidate for Cancer Immunotherapy

Advanced-stage solid primary tumors and metastases often express mucin 16 (MUC16), carrying immature glycans such as the Tn antigen, resulting in specific glycoproteoforms not found in healthy human tissues. This presents a valuable approach for designing targeted therapeutics, including cancer glycovaccines, which could potentially promote antigen recognition and foster the immune response to control disease spread and prevent relapse. In this study, we describe an adjuvant-free poly(lactic-co-glycolic acid) (PLGA)-based nanoglycoantigen delivery approach that outperforms conventional methods by eliminating the need for protein carriers while exhibiting targeted and adjuvant properties. To achieve this, we synthesized a library of MUC16-Tn glycoepitopes through single-pot enzymatic glycosylation, which were then stably engrafted onto the surface of PLGA nanoparticles, generating multivalent constructs that better represent cancer molecular heterogeneity. These glycoconstructs demonstrated affinity for Macrophage Galactose-type Lectin (MGL) receptor, known to be highly expressed by immature antigen-presenting cells, enabling precise targeting of immune cells. Moreover, the glycopeptide-grafted nanovaccine candidate displayed minimal cytotoxicity and induced the activation of dendritic cells in vitro, even in the absence of an adjuvant. In vivo, the formulated nanovaccine candidate was also nontoxic and elicited the production of IgG specifically targeting MUC16 and MUC16-Tn glycoproteoforms in cancer cells and tumors, offering potential for precise cancer targeting, including targeted immunotherapies.

Interrogating the Theranostic Capacity of a MUC16-Targeted Antibody for Ovarian Cancer

Aberrantly expressed glycans on mucins such as mucin-16 (MUC16) are implicated in the biology that promotes ovarian cancer (OC) malignancy. Here, we investigated the theranostic potential of a humanized antibody, huAR9.6, targeting fully glycosylated and hypoglycosylated MUC16 isoforms. Methods: In vitro and in vivo targeting of the diagnostic radiotracer [89Zr]Zr-DFO-huAR9.6 was investigated via binding experiments, immuno-PET imaging, and biodistribution studies on OC mouse models. Ovarian xenografts were used to determine the safety and efficacy of the therapeutic version, [177Lu]Lu-CHX-A″-DTPA-huAR9.6. Results: In vivo uptake of [89Zr]Zr-DFO-huAR9.6 supported in vitro-determined expression levels: high uptake in OVCAR3 and OVCAR4 tumors, low uptake in OVCAR5 tumors, and no uptake in OVCAR8 tumors. Accordingly, [177Lu]Lu-CHX-A″-DTPA-huAR9.6 displayed strong antitumor effects in the OVCAR3 model and improved overall survival in the OVCAR3 and OVCAR5 models in comparison to the saline control. Hematologic toxicity was transient in both models. Conclusion: PET imaging of OC xenografts showed that [89Zr]Zr-DFO-huAR9.6 delineated MUC16 expression levels, which correlated with in vitro results. Additionally, we showed that [177Lu]Lu-CHX-A″-DTPA-huAR9.6 displayed strong antitumor effects in highly MUC16-expressing tumors. These findings demonstrate great potential for 89Zr- and 177Lu-labeled huAR9.6 as theranostic tools for the diagnosis and treatment of OC.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

Background

Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer.

Methods

The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool.

Results

BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans.

Conclusion

The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Advancements in Preclinical Models of Pancreatic Cancer

ABSTRACT

Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.

MUC1 and MUC16: critical for immune modulation in cancer therapeutics

The Mucin (MUC) family, a range of highly glycosylated macromolecules, is ubiquitously expressed in mammalian epithelial cells. Such molecules are pivotal in establishing protective mucosal barriers, serving as defenses against pathogenic assaults. Intriguingly, the aberrant expression of specific MUC proteins, notably Mucin 1 (MUC1) and Mucin 16 (MUC16), within tumor cells, is intimately associated with oncogenesis, proliferation, and metastasis. This association involves various mechanisms, including cellular proliferation, viability, apoptosis resistance, chemotherapeutic resilience, metabolic shifts, and immune surveillance evasion. Due to their distinctive biological roles and structural features in oncology, MUC proteins have attracted considerable attention as prospective targets and biomarkers in cancer therapy. The current review offers an exhaustive exploration of the roles of MUC1 and MUC16 in the context of cancer biomarkers, elucidating their critical contributions to the mechanisms of cellular signal transduction, regulation of immune responses, and the modulation of the tumor microenvironment. Additionally, the article evaluates the latest advances in therapeutic strategies targeting these mucins, focusing on innovations in immunotherapies and targeted drugs, aiming to enhance customization and accuracy in cancer treatments.

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.

Recent Pre-Clinical Advancements in Nuclear Medicine: Pioneering the Path to a Limitless Future

The theranostic approach in oncology holds significant importance in personalized medicine and stands as an exciting field of molecular medicine. Significant achievements have been made in this field in recent decades, particularly in treating neuroendocrine tumors using 177-Lu-radiolabeled somatostatin analogs and, more recently, in addressing prostate cancer through prostate-specific-membrane-antigen targeted radionuclide therapy. The promising clinical results obtained in these indications paved the way for the further development of this approach. With the continuous discovery of new molecular players in tumorigenesis, the development of novel radiopharmaceuticals, and the potential combination of theranostics agents with immunotherapy, nuclear medicine is poised for significant advancements. The strategy of theranostics in oncology can be categorized into (1) repurposing nuclear medicine agents for other indications, (2) improving existing radiopharmaceuticals, and (3) developing new theranostics agents for tumor-specific antigens. In this review, we provide an overview of theranostic development and shed light on its potential integration into combined treatment strategies.

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.

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.

Mucins as contrast agent targets for fluorescence-guided surgery of pancreatic cancer

Pancreatic cancer is difficult to resect due to its unique challenges, often leading to incomplete tumor resections. Fluorescence-guided surgery (FGS), also known as intraoperative molecular imaging and optical surgical navigation, is an intraoperative tool that can aid surgeons in complete tumor resection through an increased ability to detect the tumor. To target the tumor, FGS contrast agents rely on biomarkers aberrantly expressed in malignant tissue compared to normal tissue. These biomarkers allow clinicians to identify the tumor and its stage before surgical resection and provide a contrast agent target for intraoperative imaging. Mucins, a family of glycoproteins, are upregulated in malignant tissue compared to normal tissue. Therefore, these proteins may serve as biomarkers for surgical resection. Intraoperative imaging of mucin expression in pancreatic cancer can potentially increase the number of complete resections. While some mucins have been studied for FGS, the potential ability to function as a biomarker target extends to the entire mucin family. Therefore, mucins are attractive proteins to investigate more broadly as FGS biomarkers. This review summarizes the biomarker traits of mucins and their potential use in FGS for pancreatic cancer.

MUC16 mutation is associated with tumor grade, clinical features, and prognosis in glioma patients

MUC16 is a member of the attached mucin family that encodes cancer antigen 125 (CA-125), but the association of MUC16 status with grade and subtypes of glioma patients has not yet been established. Data for MUC16 mRNA expression in 37 different cancer types were considered, and genomic data from the Cancer Genome Atlas (TCGA) from 1051 low-grade glioma (LGG) patients and 833 glioblastoma (GBM) patients were analyzed. LGG and GBM has low expression of MUC16, but it is frequently mutated in GBM. Kaplan-Meier survival analysis, glioma subtypes, methylation, and isocitrate dehydrogenase (IDH1) status were all performed. We found that mutated-MUC16 in LGG patients is associated with better prognosis considering overall survival (OS), IDH1, methylation, 1p/19q, and 10q status. Conversely, MUC16 mutation were related with worse prognosis in GBM patients upon analyzing those same parameters. Therefore, MUC16 mutations may assist in glioma diagnosis and prognosis and should be further studied in this tumor type.

Challenges in precision medicine in pancreatic cancer: A focus in cancer stem cells and microbiota

Pancreatic cancer adenocarcinoma (PDAC) is a lethal disease, with the lowest 5-years survival rate of all cancers due to late diagnosis. Despite the advance and success of precision oncology in gastrointestinal cancers, the frequency of molecular-informed therapy decisions in PDAC is currently neglectable. The reasons for this dismal situation are mainly the absence of effective early diagnostic biomarkers and therapy resistance. PDAC cancer stem cells (PDAC-SC), which are regarded as essential for tumor initiation, relapse and drug resistance, are highly dependent on their niche i.e. microanatomical structures of the tumor microenvironment. There is an altered microbiome in PDAC patients embedded within the highly desmoplastic tumor microenvironment, which is known to determine therapeutic responses and affecting survival in PDAC patients. We consider that understanding the communication network that exists between the microbiome and the PDAC-SC niche by co-culture of patient-derived organoids (PDOs) with TME microbiota would recapitulate the complexity of PDAC paving the way towards a precision oncology treatment-response prediction.

METTL3 suppresses anlotinib sensitivity by regulating m6A modification of FGFR3 in oral squamous cell carcinoma

Background

N6-methyladenosine (m⁶A) is an abundant nucleotide modification in mRNA, but there were few studies on its role in cancer drug sensitivity and resistance. Anlotinib has been proved to have effective antitumor effects in oral squamous cell carcinoma (OSCC) in our previous study. Here, we sought to investigate the treatment target of anlotinib and the function and mechanisms of m⁶A modification in regulating anlotinib effect in OSCC.

Methods

Anlotinib treatment in a dose-dependent manner, western blotting, qRT-PCR and cell lost-of-function assays were used to study the treatment target of anlotinib in OSCC. RNA m⁶A dot blot assays, the m⁶A MeRIP-seq and MeRIP-qPCR, RNA and protein stability assays were used to explore the m⁶A modification of the treatment target of anlotinib. Cell lost-of-function assays after METTL3 depletion were conducted to investigate the effect of m⁶A modification level on the therapeutic effect of anlotinib in OSCC. Patient-derived tumor xenograft (PDX) models and immunohistochemistry staining were performed to study the relationship of METTL3 and antitumor sensitivity of anlotinib in vivo.

Results

Anlotinib targeted FGFR3 in the treatment of OSCC and inhibited tumor cell proliferation and promoted apoptosis by inactivating the FGFR3/AKT/mTOR signaling pathway. METTL3 was identified to target and modify FGFR3 m⁶A methylation and then decrease the stability of mRNA. METTL3 expression level was related to the anlotinib sensitivity in OSCC cells in vitro and METTL3 knockdown promoted anlotinib sensitivity of OSCC cells by inhibiting the FGFR3 expression. PDX models samples furthermore showed that METTL3 and FGFR3 levels were tightly correlated with the anlotinib efficacy in OSCC.

Conclusions

In summary, our work revealed that FGFR3 was served as the treatment target of anlotinib and METTL3-mediated FGFR3 m⁶A modification played a critical function in the anlotinib sensitivity in OSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02715-7.

Bioinformatics Analysis Based on TCGA: MUC16 Mutation Correlates with Clinical Outcome in Gastric Cancer

The prognosis of gastric cancer (GC) is difficult to predict due to the disease's complex genetic and phenotypic characteristics. MUC16 has been reported to be involved in the progression of several tumors. In this study, we aimed to explore whether MUC16 mutation had any impact on the prognosis or treatments of GC patients. Additionally, this analysis uncovered possible critical pathways related with these systems. On the cBioPortal, we were able to locate the pertinent data of patients with MUC16 mutations. And then, GSEA analysis identified differences in mRNA levels between mutant and wild-type MUC16 patients in terms of biological function annotation and pathways. The KEGG and GO analyses were also performed using the differentially expressed genes (DEGs). There were 139 individuals with GC who had the MUC16 mutation, which accounts for 32 percent, and the remaining patients had the MUC16 wild type. Survival assays revealed that patients with the MUC16 mutation had longer overall survival and disease-free survival. GSEA analysis revealed that cell cycle, cysteine and methionine metabolism, Huntington's disease, one carbon pool by folate, pyrimidine metabolism, pyruvate metabolism, RNA degradation, spliceosome, and valine leucine and isoleucine degradation were distinctly enriched in patients with MUC16 mutation type. Moreover, we identified 323 DEGs. Among them, 162 genes were upregulated, and 161 genes were downregulated. GO and KEGG assays indicated DEGs as enriched in pancreatic secretion, neuroactive ligand-receptor interaction, protein digestion and absorption, fat digestion and absorption, and glycerolipid metabolism. Overall, our data revealed that the MUC16 mutation in GC may affect the development of patients by altering several genes and pathways, indicating the importance of MUC16 mutation in the treatments of GC on an individual basis.

[MUC16: The Novel Target for Tumor Therapy]

Mucin16 (MUC16), also known as carbohydrate antigen 125 (CA125), is a glycoprotein antigen that can be recognized by the monoclonal antibody OC125 detected from epithelial ovarian carcinoma antigen by Bast et al in 1981. CA125 is not present in normal ovarian tissue but is usually elevated in the serum of epithelial ovarian carcinoma patients. CA125 is the most commonly used serologic biomarker for the diagnosis and recurrence monitoring of epithelial ovarian carcinoma. MUC16 is highly expressed in varieties of tumors. MUC16 can interact with galectin-1/3, mesothelin, sialic acid-binding immunoglobulin-type lectins-9 (Siglec-9), and other ligands. MUC16 plays an important role in tumor genesis, proliferation, migration, invasion, and tumor immunity through various signaling pathways. Besides, therapies targeting MUC16 have some significant achievements. Related preclinical studies and clinical trials are in progress. MUC16 may be a potential novel target for tumor therapy. This article will review the mechanism of MUC16 in tumor genesis and progression, and focus on the research actuality of MUC16 in tumor therapy. This article also provides references for subsequent tumor therapy studies targeting MUC16.
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Genomic Landscape, Clinical Features and Outcomes of Non-Small Cell Lung Cancer Patients Harboring BRAF Alterations of Distinct Functional Classes

BACKGROUND

In non-small cell lung cancer (NSCLC), BRAF class 1 alterations are effectively targeted by BRAF inhibitors. Conversely, targeted therapies have very low or absent activity in patients carrying class 2 and 3 alterations. The spectrum of BRAF alterations in NSCLC patients, and their accompanying clinical features, genomic landscape and treatment outcomes have been poorly reported.

PATIENTS AND METHODS

We identified BRAF alterations of defined functional class across different tumors through a systematic review. Then, we selected NSCLC patients carrying BRAF alterations, according to the systematic review, in the cBioPortal (cBioPortal cohort) to collect and analyze clinical, biomolecular and survival data. Finally, we identified NSCLC patients carrying BRAF non-V600 mutations enrolled in POPLAR and OAK trials (POPLAR/OAK cohort), extracting clinical and survival data for survival analyses.

RESULTS

100 different BRAF non-V600 alterations were identified through the systematic review. In the cBioPortal cohort (n = 139), patients harboring class 2 and 3 alterations were more frequently smokers and had higher tumor mutational burden compared to those carrying class 1 alterations. The spectrum of most frequently co-altered genes was significantly different between BRAF alterations classes, including SETD2, STK11, POM121L12, MUC16, KEAP1, TERT, TP53 and other genes. In the POPLAR/OAK cohort, patients carrying non-V600 BRAF alterations were characterized by poor prognosis compared to BRAF wild-type patients.

CONCLUSIONS

Different classes of BRAF alterations confer distinctive clinical features, biomolecular signature and disease behavior to NSCLC patients. Non-V600 alterations are characterized by poor prognosis, but key gene co-alterations involved in cancer cell survival and immune pathways may suggest their potential sensitivity to tailored treatments.

Recent advances and future perspectives on carbohydrate-based cancer vaccines and therapeutics

Carbohydrates are abundantly expressed on the surface of both eukaryotic and prokaryotic cells, often as post translational modifications of proteins. Glycoproteins are recognized by the immune system and can trigger both innate and humoral responses. This feature has been harnessed to generate vaccines against polysaccharide-encapsulated bacteria such as Streptococcus pneumoniae, Hemophilus influenzae type b and Neisseria meningitidis. In cancer, glycosylation plays a pivotal role in malignancy development and progression. Since glycans are specifically expressed on the surface of tumor cells, they have been targeted for the discovery of anticancer preventive and therapeutic treatments, such as vaccines and monoclonal antibodies. Despite the various efforts made over the last years, resulting in a series of clinical studies, attempts of vaccination with carbohydrate-based candidates have proven unsuccessful, primarily due to the immune tolerance often associated with these glycans. New strategies are thus deployed to enhance carbohydrate-based cancer vaccines. Moreover, lessons learned from glycan immunobiology paved the way to the development of new monoclonal antibodies specifically designed to recognize cancer-bound carbohydrates and induce tumor cell killing. Herein we provide an overview of the immunological principles behind the immune response towards glycans and glycoconjugates and the approaches exploited at both preclinical and clinical level to target cancer-associated glycans for the development of vaccines and therapeutic monoclonal antibodies. We also discuss gaps and opportunities to successfully advance glycan-directed cancer therapies, which could provide patients with innovative and effective treatments.

Altered glycosylation in pancreatic cancer and beyond

Pancreatic ductal adenocarcinoma (PDA) is one of the deadliest cancers and is projected to soon be the second leading cause of cancer death. Median survival of PDA patients is 6-10 mo, with the majority of diagnoses occurring at later, metastatic stages that are refractory to treatment and accompanied by worsening prognoses. Glycosylation is one of the most common types of post-translational modifications. The complex landscape of glycosylation produces an extensive repertoire of glycan moieties, glycoproteins, and glycolipids, thus adding a dynamic and tunable level of intra- and intercellular signaling regulation. Aberrant glycosylation is a feature of cancer progression and influences a broad range of signaling pathways to promote disease onset and progression. However, despite being so common, the functional consequences of altered glycosylation and their potential as therapeutic targets remain poorly understood and vastly understudied in the context of PDA. In this review, the functionality of glycans as they contribute to hallmarks of PDA are highlighted as active regulators of disease onset, tumor progression, metastatic capability, therapeutic resistance, and remodeling of the tumor immune microenvironment. A deeper understanding of the functional consequences of altered glycosylation will facilitate future hypothesis-driven studies and identify novel therapeutic strategies in PDA.

Truncated O-Glycan-Bearing MUC16 Enhances Pancreatic Cancer Cells Aggressiveness via α4β1 Integrin Complexes and FAK Signaling

Elevated levels of Mucin-16 (MUC16) in conjunction with a high expression of truncated O-glycans is implicated in playing crucial roles in the malignancy of pancreatic ductal adenocarcinoma (PDAC). However, the mechanisms by which such aberrant glycoforms present on MUC16 itself promote an increased disease burden in PDAC are yet to be elucidated. This study demonstrates that the CRISPR/Cas9-mediated genetic deletion of MUC16 in PDAC cells decreases tumor cell migration. We found that MUC16 enhances tumor malignancy by activating the integrin-linked kinase and focal adhesion kinase (ILK/FAK)-signaling axis. These findings are especially noteworthy in truncated O-glycan (Tn and STn antigen)-expressing PDAC cells. Activation of these oncogenic-signaling pathways resulted in part from interactions between MUC16 and integrin complexes (α4β1), which showed a stronger association with aberrant glycoforms of MUC16. Using a monoclonal antibody to functionally hinder MUC16 significantly reduced the migratory cascades in our model. Together, these findings suggest that truncated O-glycan containing MUC16 exacerbates malignancy in PDAC by activating FAK signaling through specific interactions with α4 and β1 integrin complexes on cancer cell membranes. Targeting these aberrant glycoforms of MUC16 can aid in the development of a novel platform to study and treat metastatic pancreatic cancer.

Hypoxia-reprogrammed regulatory group 2 innate lymphoid cells promote immunosuppression in pancreatic cancer

BACKGROUND

Previously, we uncovered a patient subgroup with highly malignant pancreatic cancer with serum markers CEA+/CA125+/CA19-9 ≥ 1000 U/mL (triple-positive, TP). However, the underlying immunosuppressive mechanism in the tumor immune microenvironment (TIME) of this subgroup is still unknown.

METHODS

Human tissues were analyzed by flow cytometry, mass cytometry, and immunofluorescence staining. Mouse pancreatic ILC2s were expanded in vivo and used for RNA sequencing, chromatin immunoprecipitation (ChIP), and chemotaxis assays.

FINDINGS

Through microarray data, we identified the accumulation of the hypoxia-induced factor-1α (HIF-1α) pathway in these TP patients. Via flow and mass cytometry, we discovered that a special subset of ILC2s were highly infiltrated in TP patients. Under the hypoxia microenvironment, ILC2s were found undergo a transition to a IL10+ regulatory phenotype, we named ILCregs which was correlated with pancreatic ductal adenocarcinoma (PDAC) progression. Further, neoadjuvant chemotherapy could ameliorate hypoxic tumor microenvironments so that significantly reverse the regulatory phenotype of ILCregs. Moreover, most tumor ILC2 were CD103-, which indicated its circulatory origin. The expression of Ccr2 was significantly upregulated on mouse ILCregs, and these cells selectively migrated to CCL2.

INTERPRETATION

Our results indicate that the hypoxia microenvironment creates an immunosuppressive TIME by inducing ILCregs from a population of circulating group 2 ILCs in TP PDAC patients.

FUNDING

This study was jointly supported by the National Natural Science Foundation of China (U21A20374, 82173091, and 81701630).

Crystal structure of a human MUC16 SEA domain reveals insight into the nature of the CA125 tumor marker

MUC16 is a membrane bound glycoprotein involved in the progression and metastasis of pancreatic and ovarian cancer. The protein is shed into the serum and the resulting cancer antigen 125 (CA125) can be detected by immunoassays. The CA125 epitope is used for monitoring ovarian cancer treatment progression, and has emerged as a potential target for antibody mediated immunotherapy. The extracellular tandem repeat domain of the protein is composed of repeating segments of heavily glycosylated sequence intermixed with homologous SEA (Sperm protein, Enterokinase and Agrin) domains. Here we report the purification and the first X-ray structure of a human MUC16 SEA domain. The structure was solved by molecular replacement using a Rosetta generated structure as a search model. The SEA domain reacted with three different MUC16 therapeutic antibodies, confirming that the CA125 epitope is localized to the SEA domain. The structure revealed a canonical ferredoxin-like fold, and contained a conserved disulfide bond. Analysis of the relative solvent accessibility of side chains within the SEA domain clarified the assignment of N-linked and O-linked glycosylation sites within the domain. A model of the glycosylated SEA domain revealed two major accessible faces, which likely represent the binding sites of CA125 specific antibodies. The results presented here will serve to accelerate future work to understand the functional role of MUC16 SEA domains and antibody recognition of the CA125 epitope.

ImmunoPET of Ovarian and Pancreatic Cancer with AR9.6, a Novel MUC16-Targeted Therapeutic Antibody

PURPOSE

Advances in our understanding of the contribution of aberrant glycosylation to the pro-oncogenic signaling and metastasis of tumor cells have reinvigorated the development of mucin-targeted therapies. Here, we validate the tumor-targeting ability of a novel monoclonal antibody (mAb), AR9.6, that binds MUC16 and abrogates downstream oncogenic signaling to confer a therapeutic response.

EXPERIMENTAL DESIGN

The in vitro and ex vivo validation of the binding of AR9.6 to MUC16 was achieved via flow cytometry, radioligand binding assay (RBA), and immunohistochemistry (IHC). The in vivo MUC16 targeting of AR9.6 was validated by creating a 89Zr-labeled radioimmunoconjugate of the mAb and utilizing immunoPET and ex vivo biodistribution studies in xenograft models of human ovarian and pancreatic cancer.

RESULTS

Flow cytometry, RBA, and IHC revealed that AR9.6 binds to ovarian and pancreatic cancer cells in an MUC16-dependent manner. The in vivo radiopharmacologic profile of 89Zr-labeled AR9.6 in mice bearing ovarian and pancreatic cancer xenografts confirmed the MUC16-dependent tumor targeting by the radioimmunoconjugate. Radioactivity uptake was also observed in the distant lymph nodes (LNs) of mice bearing xenografts with high levels of MUC16 expression (i.e., OVCAR3 and Capan-2). IHC analyses of these PET-positive LNs highlighted the presence of shed antigen as well as necrotic, phagocytized, and actively infiltrating neoplastic cells. The humanization of AR9.6 did not compromise its ability to target MUC16-expressing tumors.

CONCLUSIONS

The unique therapeutic mechanism of AR9.6 combined with its excellent in vivo tumor targeting makes it a highly promising theranostic agent. huAR9.6 is poised for clinical translation to impact the management of metastatic ovarian and pancreatic cancers.

Glycans as Targets for Drug Delivery in Cancer

Simple Summary

Alterations in glycosylation are frequently observed in cancer cells. Different strategies have been proposed to increase drug delivery to the tumor site in order to improve the therapeutic efficacy of anti-cancer drugs and avoid collateral cytotoxicity. The exploitation of drug delivery approaches directed to cancer-associated glycans has the potential to pave the way for better and more efficient personalized treatment practices. Such strategies taking advantage of aberrant cell surface glycosylation patterns enhance the targeting efficiency and optimize the delivery of clinically used drugs to cancer cells, with major potential for the clinical applications.

Abstract

Innovative strategies have been proposed to increase drug delivery to the tumor site and avoid cytotoxicity, improving the therapeutic efficacy of well-established anti-cancer drugs. Alterations in normal glycosylation processes are frequently observed in cancer cells and the resulting cell surface aberrant glycans can be used as direct molecular targets for drug delivery. In the present review, we address the development of strategies, such as monoclonal antibodies, antibody–drug conjugates and nanoparticles that specific and selectively target cancer-associated glycans in tumor cells. The use of nanoparticles for drug delivery encompasses novel applications in cancer therapy, including vaccines encapsulated in synthetic nanoparticles and specific nanoparticles that target glycoproteins or glycan-binding proteins. Here, we highlight their potential to enhance targeting approaches and to optimize the delivery of clinically approved drugs to the tumor microenvironment, paving the way for improved personalized treatment approaches with major potential importance for the pharmaceutical and clinical sectors.

Heteromeric Amino Acid Transporters in Brain: from Physiology to Pathology

In humans, more than 50 transporters are responsible for the traffic and balance of amino acids within and between cells and tissues, and half of them have been associated with disease [1]. Covering all common amino acids, Heteromeric Amino acid Transporters (HATs) are one class of such transporters. This review first highlights structural and functional studies that solved the atomic structure of HATs and revealed molecular clues on substrate interaction. Moreover, this review focuses on HATs that have a role in the central nervous system (CNS) and that are related to neurological diseases, including: (i) LAT1/CD98hc and its role in the uptake of branched chain amino acids trough the blood brain barrier and autism. (ii) LAT2/CD98hc and its potential role in the transport of glutamine between plasma and cerebrospinal fluid. (iii) y⁺LAT2/CD98hc that is emerging as a key player in hepatic encephalopathy. xCT/CD98hc as a potential therapeutic target in glioblastoma, and (iv) Asc-1/CD98hc as a potential therapeutic target in pathologies with alterations in NMDA glutamate receptors.