MUC16 as a novel target for cancer therapy

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.

Characteristic of molecular subtype based on lysosome-associated genes reveals clinical prognosis and immune infiltration of gastric cancer

Background

Lysosome are involved in nutrient sensing, cell signaling, cell death, immune responses and cell metabolism, which play an important role in the initiation and development of multiple tumors. However, the biological function of lysosome in gastric cancer (GC) has not been revealed. Here, we aim to screen lysosome-associated genes and established a corresponding prognostic risk signature for GC, then explore the role and underlying mechanisms.

Methods

The lysosome-associated genes (LYAGs) were obtained from MSigDB database. Differentially expressed lysosome-associated genes (DE-LYAGs) of GC were acquired based on the TCGA database and GEO database. According to expression profiles of DE-LYAGs, we divided the GC patients into different subgroups and then explored tumor microenvironment (TME) landscape and immunotherapy response in LYAG subtypes using GSVA, ESTIMATE and ssGSEA algorithms. Univariate Cox regression analysis, LASSO algorithm and multivariate Cox regression analysis were adopted to identify the prognostic LYAGs and then establish a risk model for patients with GC. The Kaplan-Meier analysis, Cox regression analysis and ROC analysis were utilized to evaluate the performance of the prognostic risk model. Clinical GC specimens were also used to verify the bioinformatics results by qRT-PCR assay.

Results

Thirteen DE-LYAGs were obtained and utilized to distinguish three subtypes in GC samples. Expression profiles of the 13 DE-LYAGs predicted prognosis, tumor-related immunological abnormalities and pathway dysregulation in these three subtypes. Furthermore, we constructed a prognostic risk model for GC based on DEG in the three subtypes. The Kaplan-Meier analysis suggested that higher risk score related to short OS rate. The Cox regression analysis and ROC analysis indicated that risk model had independent and excellent ability in predicting prognosis of GC patients. Mechanistically, a remarkable difference was observed in immune cell infiltration, immunotherapy response, somatic mutation landscape and drug sensitivity. qRT-PCR results showed that compared with corresponding adjacent normal tissues, most screened genes showed significant abnormal expressions and the expression change trends were consistent with the bioinformatics results.

Conclusions

We established a novel signature based on LYAGs which could be served as a prognostic biomarker for GC. Our study might provide new insights into individualized prognostication and precision treatment for GC.

In silico Screening and Validation of Achyranthes aspera as a Potential Inhibitor of BRAF and NRAS in Controlling Thyroid Cancer

BACKGROUND

Thyroid carcinoma (THCA) is one of the most prevalent endocrine tumors, accounting for 3.4% of all cancers diagnosed annually. Single Nucleotide Polymorphisms (SNPs) are the most prevalent genetic variation associated with thyroid cancer. Understanding thyroid cancer genetics will enhance diagnosis, prognosis, and treatment.

METHODS

This TCGA-based study analyzes thyroid cancer-associated highly mutated genes through highly robust in silico techniques. Pathway, gene expression, and survival studies were performed on the top 10 highly mutated genes (BRAF, NRAS, TG, TTN, HRAS, MUC16, ZFHX3, CSMD2, EIFIAX, SPTA1). Novel natural compounds from Achyranthes aspera Linn were discovered to target two highly mutated genes. The natural compounds and synthetic drugs used to treat thyroid cancer were subjected to comparative molecular docking against BRAF and NRAS targets. The ADME characteristics of Achyranthes aspera Linn compounds were also investigated.

RESULTS

The gene expression analysis revealed that the expression of ZFHX3, MCU16, EIF1AX, HRAS, and NRAS was up-regulated in tumor cells while BRAF, TTN, TG, CSMD2, and SPTA1 were down-regulated in tumor cells. In addition, the protein-protein interaction network demonstrated that HRAS, BRAF, NRAS, SPTA1, and TG proteins have strong interactions with each other as compared to other genes. The ADMET analysis shows that seven compounds have druglike properties. These compounds were further studied for molecular docking studies. The compounds MPHY012847, IMPHY005295, and IMPHY000939 show higher binding affinity with BRAF than pimasertib. In addition, IMPHY000939, IMPHY000303, IMPHY012847, and IMPHY005295 showed a better binding affinity with NRAS than Guanosine Triphosphate.

CONCLUSION

The outcomes of docking experiments conducted on BRAF and NRAS provide insight into natural compounds with pharmacological characteristics. These findings indicate that natural compounds derived from plants as a more promising cancer treatment option. Thus, the results of docking investigations conducted on BRAF and NRAS substantiate the conclusions that the molecule possesses the most suited drug-like qualities. Compared to other compounds, natural compounds are superior, and they are also druggable. This demonstrates that natural plant compounds can be an excellent source of potential anti-cancer agents. The preclinical research will pave the road for a possible anti-cancer agent.

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.

Pathological Implications of Mucin Signaling in Metastasis

The dynamic mucosal layer provides a selective protective barrier for the epithelial cells lining the body cavities. Diverse human malignancies exploit their intrinsic role to protect and repair epithelia for promoting growth and survival. Aberrant expression of mucin has been known to be associated with poor prognosis of many cancers. However, the emergence of new paradigms in the study of metastasis recognizes the involvement of MUC1, MUC4, MUC5AC, MUC5B, and MUC16 during metastasis initiation and progression. Hence mucins can be used as an attractive target in future diagnostic and therapeutic strategies. In this review, we discuss in detail about mucin family and its domains and the role of different mucins in regulating cancer progression and metastasis. In addition, we briefly discuss insights into mucins as a therapeutic agent.

Nanotechnology-Based Nucleic Acid Vaccines for Treatment of Ovarian Cancer

Anticancer vaccines represent a promising approach for effective treatment of cancer and along with recent advantages of nucleic acid-based vaccines for other diseases form a prospective and potentially efficacious direction of the research, development and clinical applications. Despite the ongoing several clinical trials of mRNA vaccines for the treatment of various types of cancer, to-date no cancer vaccines were approved by the US Food and Drug Administration. The present review analyzes and summarizes major approaches for treating of different forms of ovarian cancer including mRNA-based vaccines as well as nanotechnology-based approaches for their delivery.

Integrative Multi-OMICs Identifies Therapeutic Response Biomarkers and Confirms Fidelity of Clinically Annotated, Serially Passaged Patient-Derived Xenografts Established from Primary and Metastatic Pediatric and AYA Solid Tumors

Establishment of clinically annotated, molecularly characterized, patient-derived xenografts (PDXs) from treatment-naïve and pretreated patients provides a platform to test precision genomics-guided therapies. An integrated multi-OMICS pipeline was developed to identify cancer-associated pathways and evaluate stability of molecular signatures in a panel of pediatric and AYA PDXs following serial passaging in mice. Original solid tumor samples and their corresponding PDXs were evaluated by whole-genome sequencing, RNA-seq, immunoblotting, pathway enrichment analyses, and the drug−gene interaction database to identify as well as cross-validate actionable targets in patients with sarcomas or Wilms tumors. While some divergence between original tumor and the respective PDX was evident, majority of alterations were not functionally impactful, and oncogenic pathway activation was maintained following serial passaging. CDK4/6 and BETs were prioritized as biomarkers of therapeutic response in osteosarcoma PDXs with pertinent molecular signatures. Inhibition of CDK4/6 or BETs decreased osteosarcoma PDX growth (two-way ANOVA, p < 0.05) confirming mechanistic involvement in growth. Linking patient treatment history with molecular and efficacy data in PDX will provide a strong rationale for targeted therapy and improve our understanding of which therapy is most beneficial in patients at diagnosis and in those already exposed to therapy.

A review of recent advances on single use of antibody-drug conjugates or combination with tumor immunology therapy for gynecologic cancer

Immune checkpoint inhibitors have made significant progress in the treatment of various cancers. However, due to the low ICI responsive rate for the gynecologic cancer, ICI two-drug combination therapy tends to be a predominant way for clinical treatment. Antibody-drug conjugates, a promising therapeutic modality for cancer, have been approved by the FDA for breast cancer, lymphoma, multiple myeloma and gastric cancer. On September 2021, the FDA granted accelerated approval to tisotumab vedotin for patients with recurrent or metastatic cervical cancer. Currently, the role of therapy of ADCs on gynecologic tumors was also included in medication regimens. Now more than 30 ADCs targeting for 20 biomarkers are under clinical trials in the field, including monotherapy or combination with others for multiple lines of therapy. Some ADCs have been proved to enhance the antitumor immunity effect on both pre-clinical models and clinical trials. Therefore, combination of ADCs and ICIs are expected in clinical trials. In this review, we discuss current development of ADCs in gynecologic oncology and the combination effects of ICIs and ADCs.

Engineering of a Fully Human Anti-MUC-16 Antibody and Evaluation as a PET Imaging Agent

Antibodies that recognize cancer biomarkers, such as MUC16, can be used as vehicles to deliver contrast agents (imaging) or cytotoxic payloads (therapy) to the site of tumors. MUC16 is overexpressed in 80% of epithelial ovarian cancer (EOC) and 65% of pancreatic ductal adenocarcinomas (PDAC), where effective ‘theranostic’ probes are much needed. This work aims to develop fully human antibodies against MUC16 and evaluate them as potential immuno-PET imaging probes for detecting ovarian and pancreatic cancers. We developed a fully human monoclonal antibody, M16Ab, against MUC16 using phage display. M16Ab was conjugated with p-SCN-Bn-DFO and radiolabeled with 89Zr. 89Zr-DFO-M16Ab was then evaluated for binding specificity and affinity using flow cytometry. In vivo evaluation of 89Zr-DFO-M16Ab was performed by microPET/CT imaging at different time points at 24−120 h post injection (p.i.) and ex vivo biodistribution studies in mice bearing MUC16-expressing OVCAR3, SKOV3 (ovarian) and SW1990 (pancreatic) xenografts. 89Zr-DFO-M16Ab bound specifically to MUC16-expressing cancer cells with an EC50 of 10nM. 89Zr-DFO-M16Ab was stable in serum and showed specific uptake and retention in tumor xenografts even after 120 h p.i. (microPET/CT) with tumor-to-blood ratios > 43 for the SW1990 xenograft. Specific tumor uptake was observed for SW1990/OVCAR3 xenografts but not in MUC16-negative SKOV3 xenografts. Pharmacokinetic study shows a relatively short distribution (t1/2α) and elimination half-life (t1/2ß) of 4.4 h and 99 h, respectively. In summary, 89Zr-DFO-M16Ab is an effective non-invasive imaging probe for ovarian and pancreatic cancers and shows promise for further development of theranostic radiopharmaceuticals.

Experimental drugs for fallopian cancer: promising agents in the clinical trials and key stumbling blocks for researchers

INTRODUCTION

Fallopian tube carcinoma (FC) as a single entity is a rare disease. Although its diagnosis is increasing thanks to the widespread use of prophylactic salpingectomy, there are no clinical trials exclusively designed for FC.

AREAS COVERED

This review aims at identifying the most promising trials and future therapeutic pathways in the setting of FC.

EXPERT OPINION

Hot topics in FC treatment include the consequences of using PARP inhibitors (PARPi) as first-line therapy, ways to overcome platinum resistance, and the role of immunotherapy. Patient selection is a key point for future development of target therapies. Next-generation sequencing (NGS) is one of the most investigated technologies both for drug discovery and identification of reverse mutations, involved in resistance to PARPi and platinum. New, promising molecular targets are emerging. Notwithstanding the disappointing outcomes when used by itself, immunotherapy in FC treatment could still have a role in combination with other agents, exploiting synergistic effects at the molecular level. The development of cancer vaccines is currently hampered by the high variability of tumor neoantigens in FC. Genomic profiling could be a solution, allowing the synthesis of individualized vaccines.

The Potential Role of MUC16 (CA125) Biomarker in Lung Cancer: A Magic Biomarker but with Adversity

Lung cancer is the second most commonly diagnosed cancer in the world. In terms of the diagnosis of lung cancer, combination carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125) detection had higher sensitivity, specificity, and diagnostic odds ratios than CEA detection alone. Most individuals with elevated serum CA125 levels had lung cancer that was either in stage 3 or stage 4. Serum CA125 levels were similarly elevated in lung cancer patients who also had pleural effusions or ascites. Furthermore, there is strong evidence that human lung cancer produces CA125 in vitro, which suggests that other clinical illnesses outside of ovarian cancer could also be responsible for the rise of CA125. MUC16 (CA125) is a natural killer cell inhibitor. As a screening test for lung and ovarian cancer diagnosis and prognosis in the early stages, CA125 has been widely used as a marker in three different clinical settings. MUC16 mRNA levels in lung cancer are increased regardless of gender. As well, increased expression of mutated MUC16 enhances lung cancer cells proliferation and growth. Additionally, the CA125 serum level is thought to be a key indicator for lung cancer metastasis to the liver. Further, CA125 could be a useful biomarker in other cancer types diagnoses like ovarian, breast, and pancreatic cancers. One of the important limitations of CA125 as a first step in such a screening technique is that up to 20% of ovarian tumors lack antigen expression. Each of the 10 possible serum markers was expressed in 29-100% of ovarian tumors with minimal or no CA125 expression. Therefore, there is a controversy regarding CA125 in the diagnosis and prognosis of lung cancer and other cancer types. In this state, preclinical and clinical studies are warranted to elucidate the clinical benefit of CA125 in the diagnosis and prognosis of lung cancer.

Role of tumor cell sialylation in pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies and is currently the third leading cause of cancer death. The aggressiveness of PDAC stems from late diagnosis, early metastasis, and poor efficacy of current chemotherapies. Thus, there is an urgent need for effective biomarkers for early detection of PDAC and development of new therapeutic strategies. It has long been known that cellular glycosylation is dysregulated in pancreatic cancer cells, however, tumor-associated glycans and their cognate glycosylating enzymes have received insufficient attention as potential clinical targets. Aberrant glycosylation affects a broad range of pathways that underpin tumor initiation, metastatic progression, and resistance to cancer treatment. One of the prevalent alterations in the cancer glycome is an enrichment in a select group of sialylated glycans including sialylated, branched N-glycans, sialyl Lewis antigens, and sialylated forms of truncated O-glycans such as the sialyl Tn antigen. These modifications affect the activity of numerous cell surface receptors, which collectively impart malignant characteristics typified by enhanced cell proliferation, migration, invasion and apoptosis-resistance. Additionally, sialic acids on tumor cells engage inhibitory Siglec receptors on immune cells to dampen anti-tumor immunity, further promoting cancer progression. The goal of this review is to summarize the predominant changes in sialylation occurring in pancreatic cancer, the biological functions of sialylated glycoproteins in cancer pathogenesis, and the emerging strategies for targeting sialoglycans and Siglec receptors in cancer therapeutics.

Expression of Mucin Family Proteins in Non-Small-Cell Lung Cancer and its Role in Evaluation of Prognosis

Lung cancer is still the major contributor to cancer-related mortality. Over 85% of patients suffer from non-small-cell lung cancer (NSCLC). Mucins (MUCs) are large glycoproteins secreted or membrane-bound produced by epithelial cells in normal and malignant tissues. They are the major components of the mucous gel that covers the surface of the respiratory epithelium. Certain MUCs have been used or proposed to act as biomarkers for lung cancer. Nevertheless, the expression, messenger ribonucleic acid (mRNA) levels, and the prognostic value of MUCs in NSCLC are yet to be investigated systematically. In this research, the biological information of MUC proteins in patients with NSCLC was examined using a series of databases. The results based on gene expression profiling interactive analysis (GEPIA) illustrated that the expression of MUC3A, MUC4, MUC5B, MUC13, MUC16, and MUC21 mRNAs was remarkably upmodulated in lung adenocarcinoma (LUAD) patients, whereas the MUC1 expression was downregulated in lung squamous cell carcinoma (LUSC) patients. Kaplan–Meier plotter (KM Plotter) analysis revealed that elevated mRNA expression levels of MUC3A and MUC16 were linked to unfavourable overall survival (OS) in NSCLC, while increased mRNA expression of MUC1 and MUC15 was linked to good OS, especially in LUAD patients. In addition, differential expression of MUC1, MUC3A/3B, MUC8, MUC12, MUC15, and MUC16 mRNA was linked to the prognoses of NSCLC patients with varied clinical-pathological subtypes. Genetic alterations of MUCs in NSCLC primarily involved mutations, fusion, amplification, deep deletion, and multiple alterations according to cancer genomics (cBioPortal). Therefore, we propose that combinations of MUC proteins can act as prognostic biomarkers and demonstrate the therapeutic potential for NSCLC-related therapy.

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.

Prognostic Value of MUC16 Mutation and Its Correlation with Immunity in Hepatocellular Carcinoma Patients

Objective

Identifying gene mutation signatures will enable a better understanding for the occurrence, development, and prognosis of hepatocellular carcinoma (HCC) and provide some potential biomarkers for clinical practice. This study investigated the mutated genes in HCC patients and assessed their relationship with tumor mutation burden (TMB) and prognosis.

Methods

The somatic mutation annotation format (MAF) document, mRNA expression matrix, and clinical information of HCC patients were obtained from the International Cancer Genome Consortium (ICGC) and the Cancer Genome Atlas (TCGA) database. The differences of TMB between the mutant type and the wild-type genes were detected using the Mann–Whitney U test. The link of gene mutations with prognosis was explored by the Kaplan–Meier analysis. The proportion of 22 immune cells' composition was measured using CIBERSORT algorithm.

Results

The two databases screened 16 common mutated genes, which included TP53, TTN, LRP1B, ZFHX4, MUC16, OBSCN, CSMD3, FLG, CSMD1, SYNE1, SPTA1, USH2A, KMT2C, PCLO, HMCN1, and FAT3. After a series of analysis, MUC16 mutation was found to be highly correlated with TMB and was regarded as an independent factor predicting HCC. Furthermore, gene set enrichment analysis (GSEA) indicated that the MUC16 mutation was significantly involved in HCC cell metabolism.

Conclusions

MUC16 mutation seems to be a valuable potential biomarker for HCC development and its overall survival.

Liquid Biopsy and Circulating Biomarkers for the Diagnosis of Precancerous and Cancerous Oral Lesions

Oral cancer is one of the most common malignancies worldwide, accounting for 2% of all cases annually and 1.8% of all cancer deaths. To date, tissue biopsy and histopathological analyses are the gold standard methods for the diagnosis of oral cancers. However, oral cancer is generally diagnosed at advanced stages with a consequent poor 5-year survival (~50%) due to limited screening programs and inefficient physical examination strategies. To address these limitations, liquid biopsy is recently emerging as a novel minimally invasive tool for the early identification of tumors as well as for the evaluation of tumor heterogeneity and prognosis of patients. Several studies have demonstrated that liquid biopsy in oral cancer could be useful for the detection of circulating biomarkers including circulating tumor DNA (ctDNA), microRNAs (miRNAs), proteins, and exosomes, thus improving diagnostic strategies and paving the way to personalized medicine. However, the application of liquid biopsy in oral cancer is still limited and further studies are needed to better clarify its clinical impact. The present manuscript aims to provide an updated overview of the potential use of liquid biopsy as an additional tool for the management of oral lesions by describing the available methodologies and the most promising biomarkers.

[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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Urine CA125 and HE4 for the Triage of Symptomatic Women with Suspected Endometrial Cancer

A simple, noninvasive and accurate detection tool that can triage women with suspected endometrial cancer for definitive testing will transform patient care. The aim of this study was to evaluate urine CA125 and HE4 levels for the detection of endometrial cancer in symptomatic women. This was a cross-sectional diagnostic accuracy study of 153 symptomatic women who underwent urgent diagnostic investigations for suspected endometrial cancer at a large gynecological cancer center. Urine samples were collected prior to routine clinical procedures. Urine CA125 and HE4 levels were determined using automated chemiluminescent enzyme immunoassays. Univariate and multivariable receiver operating characteristic (ROC) curve analyses were performed. Urine CA125 and HE4 were discovered to be significantly elevated in women with endometrial cancer, compared to controls (p < 0.001 and p = 0.01, respectively). Urine CA125 and HE4 detected endometrial cancer with an area under the ROC curve (AUC) of 0.89 (0.81, 0.98) and 0.69 (0.55, 0.83), respectively. CA125 exhibited good discriminatory potential for Type I and early-stage tumors (AUC 0.93 and 0.90, respectively). A diagnostic model that combined urine CA125 and transvaginal ultrasound-measured endometrial thickness predicted endometrial cancer with an AUC of 0.96 (0.91, 1.00). Urine CA125 displays potential as a diagnostic tool for symptomatic women with suspected endometrial cancer. When combined with transvaginal ultrasound-measured endometrial thickness, this patient-friendly, urine-based test could help triage women for invasive diagnostics or safe reassurance, reducing costs and improving patient experience.

Multifunctional Magnetic Nanoparticles for MRI-guided Co-delivery of Erlotinib and L-Asparaginase to Ovarian Cancer

AIM(S)

The use of magnetic nanoparticles (MNPs) in biomedical applications has been wildly opted due to their unique properties. The objective of this study was to evaluate the effects of aptamer-armed MNPs in ovarian cancer treatment and as T2 weighted MRI contrast agent.

METHODS

Here, we designed MNPs loaded with erlotinib (ERL/SPION-Val-PEG) and conjugated them with anti-mucin16 (MUC16) aptamer to introduce new image-guided nanoparticles (NPs) for targeted drug delivery as well as non-invasive magnetic resonance imaging (MRI) contrast agents. Also, the combination of our nanosystem (NS) along with L-Asparaginase (L-ASPN) led to synergistic effects in terms of reducing cell viability in ovarian cancer cells, which could suggest a novel combination therapy.

RESULTS

The mean size of our NS was about 63.4 ± 3.4 nm evaluated by DLS analysis and its morphology was confirmed using TEM. Moreover, the functional groups, as well as magnetic properties of our NS, were examined by FT-IR and VSM tests, respectively. The loading efficacy of erlotinib on MNPs was about 80% and its release reached 70.85% over 7 days in the pH value of 5.4. The MR images and flow cytometry results revealed that the cellular uptake of ERL/SPION-Val-PEG-MUC16 NPs in cells with MUC16 overexpression was considerably higher than unarmed NPs. In addition, T2-weight MR images of ovarian cancer-bearing mice indicated significant signal intensity changes at the tumor site 4 h after intravenous injection compared to the non-target MNPs.

CONCLUSIONS

Our data suggest ERL/SPION-Val-PEG NPs as an image-guided co-drug delivery system for ovarian cancer.

Genomic Features of Solid Tumor Patients Harboring ALK/ROS1/NTRK Gene Fusions

The fusions of receptor tyrosine kinase (RTK) involving anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1), and neurotrophic receptor tyrosine kinase (NTRK) represent the potential targets of therapeutic intervention for various types of solid tumors. Here, the genomic features of 180 Chinese solid tumor patients with ALK, ROS1, and NTRK fusions by next generation sequencing (NGS) were comprehensively characterized, and the data from 121 patients in Memorial Sloan Kettering Cancer Center (MSKCC) database were used to compare. We found that ALK, ROS1, and NTRK fusions were more common in younger female patients (p&lt;0.001) and showed a higher expression of programmed death ligand 1 (PD-L1). The gene-intergenic fusion and the fusion with rare formation directions accounted for a certain proportion in all samples and 62 novel fusions were discovered. Alterations in TP53 and MUC16 were common in patients with RTK fusions. The mutational signatures of patients were mainly distributed in COSMIC signature 1, 2, 3, 15 and 30, while had a higher frequency in copy number variations (CNVs) of individual genes, such as IL-7R. In the MSKCC cohort, patients with fusions and CNVs showed shorter overall survival than those with only fusions. Furthermore, the differentially mutated genes between fusion-positive and -negative patients mainly concentrated on MAPK signaling and FOXO signaling pathways. These results may provide genomic information for the personalized clinical management of solid tumor patients with ALK, ROS1, and NTRK fusions in the era of precision medicine.

Bispecific Antibody-Based Immune-Cell Engagers and Their Emerging Therapeutic Targets in Cancer Immunotherapy

Cancer is the second leading cause of death worldwide after cardiovascular diseases. Harnessing the power of immune cells is a promising strategy to improve the antitumor effect of cancer immunotherapy. Recent progress in recombinant DNA technology and antibody engineering has ushered in a new era of bispecific antibody (bsAb)-based immune-cell engagers (ICEs), including T- and natural-killer-cell engagers. Since the first approval of blinatumomab by the United States Food and Drug Administration (US FDA), various bsAb-based ICEs have been developed for the effective treatment of patients with cancer. Simultaneously, several potential therapeutic targets of bsAb-based ICEs have been identified in various cancers. Therefore, this review focused on not only highlighting the action mechanism, design and structure, and status of bsAb-based ICEs in clinical development and their approval by the US FDA for human malignancy treatment, but also on summarizing the currently known and emerging therapeutic targets in cancer. This review provides insights into practical considerations for developing next-generation ICEs.

HSP90 N-terminal inhibitors target oncoprotein MORC2 for autophagic degradation and suppress MORC2-driven breast cancer progression

Aims

MORC family CW‐type zinc finger 2 (MORC2), a GHKL‐type ATPase, is aberrantly upregulated in multiple types of human tumors with profound effects on cancer aggressiveness, therapeutic resistance, and clinical outcome, thus making it an attractive drug target for anticancer therapy. However, the antagonists of MORC2 have not yet been documented.

Methods and Results

We report that MORC2 is a relatively stable protein, and the N‐terminal homodimerization but not ATP binding and hydrolysis is crucial for its stability through immunoblotting analysis and Quantitative real‐time PCR. The N‐terminal but not C‐terminal inhibitors of heat shock protein 90 (HSP90) destabilize MORC2 in multiple cancer cell lines, and strikingly, this process is independent on HSP90. Mechanistical investigations revealed that HSP90 N‐terminal inhibitors disrupt MORC2 homodimer formation without affecting its ATPase activities, and promote its lysosomal degradation through the chaperone‐mediated autophagy pathway. Consequently, HSP90 inhibitor 17‐AAG effectively blocks the growth and metastatic potential of MORC2‐expressing breast cancer cells both in vitro and in vivo, and these noted effects are not due to HSP90 inhibition.

Conclusion

We uncover a previously unknown role for HSP90 N‐terminal inhibitors in promoting MORC2 degradation in a HSP90‐indepentent manner and support the potential application of these inhibitors for treating MORC2‐overexpressing tumors, even those with low or absent HSP90 expression. These results also provide new clue for further design of novel small‐molecule inhibitors of MORC2 for anticancer therapeutic application.

GBP5 and ACSS3: two potential biomarkers of high-grade ovarian cancer identified through downstream analysis of microarray data

Among all malignancies of the reproductive organs, ovarian cancer is the sixth leading cause of death for women. Several factors contribute to the uncontrolled expression of certain genes in cancer thus making them act as oncogenes or tumour suppressors. In this study, we have examined four microarray datasets of high-grade ovarian cancer cells to identify differentially expressed genes (DEGs). 362 and 94 common DEGs were identified as up-regulated and down-regulated, respectively from 119 disease and 31 control samples. The DEGs were further analysed for their gene ontologies (GO), pathway, protein-protein interactions and co-expression. Most of the biological processes were associated with cellular processes, biological regulation, metabolic processes, and developmental processes. Further, regulatory networks were constructed by the DEGs which are also co-expressed and the hub genes were identified. The hub genes targeted by a large number of microRNAs (miRNAs) were further analyzed to reveal their role in the overall survival of cancer patients. Finally, GBP5 and ACSS3 were highlighted as potential biomarkers for ovarian cancer research.Communicated by Ramaswamy H. Sarma.

Comprehensive Understanding and Evolutional Therapeutic Schemes for Pseudomyxoma Peritonei: A Literature Review

Pseudomyxoma peritonei is an infrequent solid tumor in clinical practice. The low morbidity and deficient understanding of this mucus-secreting malignant disease increase the risks of delayed identification or uncontrollable deterioration. In quite a lot cases, patients go through complete cytoreduction surgery and hyperthermic intraperitoneal chemotherapy could receive a long time survival over 5 years. But the recurrence rate is also hard to overlook. Unlike other types of cancer, the standard treatment for this considerable groups has not been confirmed yet. With the advanced medical progression, studies have been carrying out based on pathogenesis, biological characters, and mutated gene location. All but a few get statistical survival benefits, let alone the breaking progress on research or therapeutic practice in the field. We try to give a comprehensive exposition of pseudomyxoma peritonei around the epidemiology, radiologic features, clinical manifestation, present treatment and promising schemes, hoping to arise much attention and reflection on the feasible solutions, especially for the recrudescent part.

Ovarian Cancer Ascites Inhibits Transcriptional Activation of NK Cells Partly through CA125

Malignant ascites is a common clinical problem in ovarian cancer. NK cells are present in the ascites, but their antitumor activity is inhibited. The underlying mechanisms of the inhibition have yet to be fully elucidated. Using an Fcγ receptor-mediated NK cell activation assay, we show that ascites from ovarian cancer patients potently inhibits NK cell activation. Part of the inhibitory activity is mediated by CA125, a mucin 16 fragment shed from ovarian cancer tumors. Moreover, transcriptional analyses by RNA sequencing reveal upregulation of genes involved in multiple metabolic pathways but downregulation of genes involved in cytotoxicity and signaling pathways in NK cells purified from ovarian cancer patient ascites. Transcription of genes involved in cytotoxicity pathways are also downregulated in NK cells from healthy donors after in vitro treatment with ascites or with a CA125-enriched protein fraction. These results show that ascites and CA125 inhibit antitumor activity of NK cells at transcriptional levels by suppressing expression of genes involved in NK cell activation and cytotoxicity. Our findings shed light on the molecular mechanisms by which ascites inhibits the activity of NK cells and suggest possible approaches to reactivate NK cells for ovarian cancer immunotherapy.

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.

Expression of Mucins in Different Entities of Salivary Gland Cancer: Highest Expression of Mucin-1 in Salivary Duct Carcinoma : Mucin-1 - highest expression in Salivary Duct Carcinoma

Therapeutic options for advanced salivary gland cancer (SGC) are rare. Therefore, it was the aim of this study to investigate the extent and intensity of Mucin-1 (MUC1), Mucin-16 (MUC16), and Mucin-5AC (MUC5AC) as potential molecular targets using immunohistochemistry. The medical records of all patients who underwent primary surgery for salivary gland cancer with curative intent in a tertiary referral center between 1990 and 2018 were reviewed. Immunohistochemical staining for MUC1, MUC16, and MUC5AC was performed for all patients with sufficient formalin-fixed paraffin-embedded material, and a semi-quantitative combined score derived from the H-score for the cytoplasmatic, the membranous and the apical membrane was built for the most common entities of SGC. 107 patients with malignancies of the parotid (89.7%) and the submandibular gland (10.3%) were included. The most common entities were mucoepidermoid carcinoma (MuEp; n = 23), adenoid cystic carcinoma (AdCy; n = 22), and salivary duct carcinoma (SaDu; n = 21). The highest mean MUC1 combined score was found in SaDu with 223.6 (±91.7). The highest mean MUC16 combined score was found in MuEp with 177.0 (±110.0). The mean MUC5AC score was low across all entities. A higher MUC1 combined score was significantly associated with male gender (p = 0.03), lymph node metastasis (p < 0.01), lymphovascular invasion (p = 0.045), and extracapsular extension (p = 0.03). SaDu patients with MUC16 expression showed a significantly worse 5-year progression-free survival than those without MUC16 expression (p = 0.02). This is the first study to give a comprehensive overview of the expression of MUC1, MUC16, and MUC5AC in SGC. Since advanced SGCs lack therapeutic options in many cases, these results warrant in vitro research on therapeutic targets against MUC1 in SaDu cell lines and xenograft models.

The contribution of uncharted RNA sequences to tumor identity in lung adenocarcinoma

The identity of cancer cells is defined by the interplay between genetic, epigenetic transcriptional and post-transcriptional variation. A lot of this variation is present in RNA-seq data and can be captured at once using reference-free, k-mer analysis. An important issue with k-mer analysis, however, is the difficulty of distinguishing signal from noise. Here, we use two independent lung adenocarcinoma datasets to identify all reproducible events at the k-mer level, in a tumor versus normal setting. We find reproducible events in many different locations (introns, intergenic, repeats) and forms (spliced, polyadenylated, chimeric etc.). We systematically analyze events that are ignored in conventional transcriptomics and assess their value as biomarkers and for tumor classification, survival prediction, neoantigen prediction and correlation with the immune microenvironment. We find that unannotated lincRNAs, novel splice variants, endogenous HERV, Line1 and Alu repeats and bacterial RNAs each contribute to different, important aspects of tumor identity. We argue that differential RNA-seq analysis of tumor/normal sample collections would benefit from this type k-mer analysis to cast a wider net on important cancer-related events. The code is available at https://github.com/Transipedia/dekupl-lung-cancer-inter-cohort.

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.

Integrative Genomic Analyses of 1,145 Patient Samples Reveal New Biomarkers in Esophageal Squamous Cell Carcinoma

Due to the lack of effective diagnostic markers and therapeutic targets, esophageal squamous cell carcinoma (ESCC) shows a poor 5 years survival rate of less than 30%. To explore the potential therapeutic targets of ESCC, we integrated and reanalyzed the mutation data of WGS (whole genome sequencing) or WES (whole exome sequencing) from a total of 1,145 samples in 7 large ESCC cohorts, including 270 ESCC gene expression data. Two new mutation signatures and 20 driver genes were identified in our study. Among them, AP3S1, MUC16, and RPS15 were reported for the first time. We also discovered that the KMT2D was associated with the multiple clinical characteristics of ESCC, and KMT2D knockdown cells showed enhanced cell migration and cell invasion. Furthermore, a few neoantigens were shared between ESCC patients. For ESCC, compared to TMB, neoantigen might be treated as a better immunotherapy biomarker. Our research expands the understanding of ESCC mutations and helps the identification of ESCC biomarkers, especially for immunotherapy biomarkers.

Exome sequencing of glioblastoma-derived cancer stem cells reveals rare clinically relevant frameshift deletion in MLLT1 gene

BACKGROUND

Glioblastoma multiforme (GBM) is a heterogeneous CNS neoplasm which causes significant morbidity and mortality. One reason for the poor prognostic outcome of GBM is attributed to the presence of cancer stem cells (CSC) which confer resistance against standard chemo- and radiotherapeutics modalities. Two types of GBM-associated CSC were isolated from the same patient: tumor core- (c-CSC) and peritumor tissue-derived cancer stem cells (p-CSC). Our experiments are focused on glioblastoma-IDH-wild type, and no disease-defining alterations were present in histone, BRAF or other genes.

METHODS

In the present study, potential differences in genetic variants between c-CSC versus p-CSC derived from four GBM patients were investigated with the aims of (1) comparing the exome sequences between all the c-CSC or p-CSC to identify the common variants; (2) identifying the variants affecting the function of genes known to be involved in cancer origin and development.

RESULTS

By comparative analyses, we identified common gene single nucleotide variants (SNV) in all GBM c-CSC and p-CSC, a potentially deleterious variant was a frameshift deletion at Gln461fs in the MLLT1 gene, that was encountered only in p-CSC samples with different allelic frequency.

CONCLUSIONS

We discovered a potentially harmful frameshift deletion at Gln461fs in the MLLT1 gene. Further investigation is required to confirm the presence of the identified mutations in patient tissue samples, as well as the significance of the frameshift mutation in the MLLT1 gene on GBM biology and response to therapy based on genomic functional experiments.