MUC16 induced rapid G2/M transition via interactions with JAK2 for increased proliferation and anti-apoptosis in breast cancer cells. Oncogene. 2012;31:805-817. [PMID: 21785467 DOI: 10.1038/onc.2011.297]

ST6GalNAc-I regulates tumor cell sialylation via NECTIN2/MUC5AC-mediated immunosuppression and angiogenesis in non-small cell lung cancer

Glycosylation controls immune evasion, tumor progression, and metastasis. However, how tumor cell sialylation regulates immune evasion remains poorly characterized. ST6GalNAc-I, a sialyltransferase that conjugates sialic acid to the glycans in glycoproteins, was overexpressed in an aggressive-type KPA (KrasG12D/+ Trp53R172H/+ Ad-Cre) lung adenocarcinoma (LUAD) model and patient samples. Proteomic and biochemical analysis indicated that ST6GalNAc-I mediated NECTIN2 sialylation in LUAD cells. ST6GalNAc-I-deficient tumor cells cocultured with T cells were more susceptible to T cell-mediated tumor cell killing, indicating a key role for NECTIN2 in T cell dysfunction. Mice injected with St6galnac-I-knockdown syngeneic cells showed reduced lung tumor incidence and Nectin2/Tigit-associated immunosuppression. ST6GalNAc-I-deficient cells exhibited reduced P-DMEA metabolite levels, while administration of P-DMEA promoted LUAD cell proliferation via MUC5AC. MUC5AC interacted and colocalized with PRRC1 in the Golgi, suggesting a potential role for PRRC1 in MUC5AC glycosylation. Mice injected with ST6GalNAc-I/MUC5AC-deficient cells (human LUAD) exhibited reduced lung tumor incidence, angiogenesis, and liver metastases. Mechanistically, ST6GalNAc-I/MUC5AC regulates VCAN-V1, a key factor in tumor matrix remodeling during angiogenesis and metastasis. These findings demonstrate that ST6GalNAc-I-mediated sialylation of NECTIN2/MUC5AC is critical for immune evasion and tumor angiogenesis. Targeting this pathway may prevent LUAD development and/or metastasis.

Early-Stage Pancreatic Cancer Diagnosis: Serum Biomarkers and the Potential for Aptamer-Based Biosensors

Pancreatic cancer has a high mortality rate, and both the incidence and mortality are continuing to increase in many countries globally. The poor prognosis of pancreatic cancer is in part due to the challenges in early diagnosis. Improving early-stage pancreatic cancer diagnosis would improve survival outcomes. Aptamer-based biosensors provide an alternative technological approach for the analysis of serum biomarkers with several potential advantages. This review summarizes the major pancreatic cancer serum biomarkers, as well as discusses recent progress in biomarker exploration and aptasensor development. Here, we review both established and novel serum biomarkers identified recently, emphasizing their potential for early-stage pancreatic cancer diagnosis. We also propose strategies for further expanding multiplex biomarker panels beyond the established CA19-9 biomarker to enhance diagnostic performance. We discuss technological advancements in aptamer-based sensors for pancreatic cancer-related biomarkers over the last decade. Optical and electrochemical sensors are highlighted as two primary modalities in aptasensor design, each offering unique advantages. Finally, we propose steps towards clinical application using aptamer-based sensors with multiplexed biomarker detection for improved pancreatic cancer diagnostics.

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.

Whole exome-seq and RNA-seq data reveal unique neoantigen profiles in Kenyan breast cancer patients

Background

The immune response against tumors relies on distinguishing between self and non-self, the basis of cancer immunotherapy. Neoantigens from somatic mutations are central to many immunotherapeutic strategies and understanding their landscape in breast cancer is crucial for targeted interventions. We aimed to profile neoantigens in Kenyan breast cancer patients using genomic DNA and total RNA from paired tumor and adjacent non-cancerous tissue samples of 23 patients.

Methods

We sequenced the genome-wide exome (WES) and RNA, from which somatic mutations were identified and their expression quantified, respectively. Neoantigen prediction focused on human leukocyte antigens (HLA) crucial to cancer, HLA type I. HLA alleles were predicted from WES data covering the adjacent non-cancerous tissue samples, identifying four alleles that were present in at least 50% of the patients. Neoantigens were deemed potentially immunogenic if their predicted median IC50 (half-maximal inhibitory concentration) binding scores were ≤500nM and were expressed [transcripts per million (TPM) >1] in tumor samples.

Results

An average of 1465 neoantigens covering 10260 genes had ≤500nM median IC50 binding score and >1 TPM in the 23 patients and their presence significantly correlated with the somatic mutations (R 2 = 0.570, P=0.001). Assessing 58 genes reported in the catalog of somatic mutations in cancer (COSMIC, v99) to be commonly mutated in breast cancer, 44 (76%) produced >2 neoantigens among the 23 patients, with a mean of 10.5 ranging from 2 to 93. For the 44 genes, a total of 477 putative neoantigens were identified, predominantly derived from missense mutations (88%), indels (6%), and frameshift mutations (6%). Notably, 78% of the putative breast cancer neoantigens were patient-specific. HLA-C*06:01 allele was associated with the majority of neoantigens (194), followed by HLA-A*30:01 (131), HLA-A*02:01 (103), and HLA-B*58:01 (49). Among the genes of interest that produced putative neoantigens were MUC17, TTN, MUC16, AKAP9, NEB, RP1L1, CDH23, PCDHB10, BRCA2, TP53, TG, and RB1.

Conclusions

The unique neoantigen profiles in our patient group highlight the potential of immunotherapy in personalized breast cancer treatment as well as potential biomarkers for prognosis. The unique mutations producing these neoantigens, compared to other populations, provide an opportunity for validation in a much larger sample cohort.

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.

Production of CA125 with Tn antigens using a glycosylphosphatidylinositol anchoring system

Cancer antigen 125 (CA125) is a serum marker associated with ovarian cancer. Despite its widespread use, CA125 levels can also be elevated in benign conditions. Recent reports suggest that detecting serum CA125 that carries the Tn antigen, a truncated O-glycan containing only N-acetylgalactosamine on serine or threonine residues, can improve the specificity of ovarian cancer diagnosis. In this study, we engineered cells to express CA125 with a Tn antigen. To achieve this, we knocked out C1GALT1 and SLC35A1, genes encoding Core1 synthase and a transporter for cytidine-5'-monophospho-sialic acid respectively, in human embryonic kidney 293 (HEK293) cells. In ClGALT1-SLC35A1-knockout (KO) cells, the expression of the Tn antigen showed a significant increase, whereas the expression of the T antigen (galactose-β1,3-N-acetylgalactosamine on serine or threonine residues) was decreased. Due to the inefficient secretion of soluble CA125, we employed a glycosylphosphatidylinositol (GPI) anchoring system. This allowed for the expression of GPI-anchored CA125 on the cell surface of ClGALT1-SLC35A1-KO cells. Cells expressing high levels of GPI-anchored CA125 were then enriched through cell sorting. By knocking out the PGAP2 gene, the GPI-anchored form of CA125 was converted to a secretory form. Through the engineering of O-glycans and the use of a GPI-anchoring system, we successfully produced CA125 with Tn antigen modification.

A prospective study of HER3 expression pre and post neoadjuvant therapy of different breast cancer subtypes: implications for HER3 imaging therapy guidance

PURPOSE

HER3, a member of the EGFR receptor family, plays a central role in driving oncogenic cell proliferation in breast cancer. Novel HER3 therapeutics are showing promising results while recently developed HER3 PET imaging modalities aid in predicting and assessing early treatment response. However, baseline HER3 expression, as well as changes in expression while on neoadjuvant therapy, have not been well-characterized. We conducted a prospective clinical study, pre- and post-neoadjuvant/systemic therapy, in patients with newly diagnosed breast cancer to determine HER3 expression, and to identify possible resistance mechanisms maintained through the HER3 receptor.

EXPERIMENTAL DESIGN

The study was conducted between May 25, 2018 and October 12, 2019. Thirty-four patients with newly diagnosed breast cancer of any subtype (ER ± , PR ± , HER2 ±) were enrolled in the study. Two core biopsy specimens were obtained from each patient at the time of diagnosis. Four patients underwent a second research biopsy following initiation of neoadjuvant/systemic therapy or systemic therapy which we define as neoadjuvant therapy. Molecular characterization of HER3 and downstream signaling nodes of the PI3K/AKT and MAPK pathways pre- and post-initiation of therapy was performed. Transcriptional validation of finings was performed in an external dataset (GSE122630).

RESULTS

Variable baseline HER3 expression was found in newly diagnosed breast cancer and correlated positively with pAKT across subtypes (r = 0.45). In patients receiving neoadjuvant/systemic therapy, changes in HER3 expression were variable. In a hormone receptor-positive (ER +/PR +/HER2-) patient, there was a statistically significant increase in HER3 expression post neoadjuvant therapy, while there was no significant change in HER3 expression in a ER +/PR +/HER2+ patient. However, both of these patients showed increased downstream signaling in the PI3K/AKT pathway. One subject with ER +/PR -/HER2- breast cancer and another subject with ER +/PR +/HER2 + breast cancer showed decreased HER3 expression. Transcriptomic findings, revealed an immune suppressive environment in patients with decreased HER3 expression post therapy.

CONCLUSION

This study demonstrates variable HER3 expression across breast cancer subtypes. HER3 expression can be assessed early, post-neoadjuvant therapy, providing valuable insight into cancer biology and potentially serving as a prognostic biomarker. Clinical translation of neoadjuvant therapy assessment can be achieved using HER3 PET imaging, offering real-time information on tumor biology and guiding personalized treatment for breast cancer patients.

Potential and application of abortive transcripts as a novel molecular marker of cancers

Abortive transcript (AT) is a 2-19 nt long non-coding RNA that is produced in the abortive initiation stage. Abortive initiation was found to be closely related to RNA polymerase through in vitro experiments. Therefore, the distribution of AT length and the scale of abortive initiation are correlated to the promoter, discriminator, and transcription initiation sequence, and can be affected by transcription elongation factors. AT plays an important role in the occurrence and development of various diseases. Here we summarize the discovery of AT, the factors responsible for AT formation, the detection methods and biological functions of AT, to provide new clues for finding potential targets in the early diagnosis and treatment of cancers.

Evaluating Ovarian Cancer Chemotherapy Response Using Gene Expression Data and Machine Learning

Background

Ovarian cancer (OC) is the most lethal gynecological cancer in the United States. Among the different types of OC, serous ovarian cancer (SOC) stands out as the most prevalent. Transcriptomics techniques generate extensive gene expression data, yet only a few of these genes are relevant to clinical diagnosis.

Methods

Methods for feature selection (FS) address the challenges of high dimensionality in extensive datasets. This study proposes a computational framework that applies FS techniques to identify genes highly associated with platinum-based chemotherapy response on SOC patients. Using SOC datasets from the Gene Expression Omnibus (GEO) database, LASSO and varSelRF FS methods were employed. Machine learning classification algorithms such as random forest (RF) and support vector machine (SVM) were also used to evaluate the performance of the models.

Results

The proposed framework has identified biomarkers panels with 9 and 10 genes that are highly correlated with platinum-paclitaxel and platinum-only response in SOC patients, respectively. The predictive models have been trained using the identified gene signatures and accuracy of above 90% was achieved.

Conclusions

In this study, we propose that applying multiple feature selection methods not only effectively reduces the number of identified biomarkers, enhancing their biological relevance, but also corroborates the efficacy of drug response prediction models in cancer treatment.

Deciphering the role of apoptosis signature on the immune dynamics and therapeutic prognosis in breast cancer: Implication for immunotherapy

Background: In breast cancer oncogenesis, the precise role of cell apoptosis holds untapped potential for prognostic and therapeutic insights. Thus, it is important to develop a model predicated for breast cancer patients' prognosis and immunotherapy response based on apoptosis-related signature. Methods: Our approach involved leveraging a training dataset from The Cancer Genome Atlas (TCGA) to construct an apoptosis-related gene prognostic model. The model's validity was then tested across several cohorts, including METABRIC, Sun Yat-sen Memorial Hospital Sun Yat-sen University (SYSMH), and IMvigor210, to ensure its applicability and robustness across different patient demographics and treatment scenarios. Furthermore, we utilized Quantitative Polymerase Chain Reaction (qPCR) analysis to explore the expression patterns of these model genes in breast cancer cell lines compared to immortalized mammary epithelial cell lines, aiming to confirm their differential expression and underline their significance in the context of breast cancer. Results: Through the development and validation of our prognostic model based on seven apoptosis-related genes, we have demonstrated its substantial predictive power for the survival outcomes of breast cancer patients. The model effectively stratified patients into high and low-risk categories, with high-risk patients showing significantly poorer overall survival in the training cohort and across all validation cohorts. Importantly, qPCR analysis confirmed that the genes constituting our model indeed exhibit differential expression in breast cancer cell lines when contrasted with immortalized mammary epithelial cell lines. Conclusion: Our study establishes a groundbreaking prognostic model using apoptosis-related genes to enhance the precision of breast cancer prognosis and treatment, particularly in predicting immunotherapy response.

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.

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

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

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

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

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

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.

High expression of the RET receptor tyrosine kinase and its ligand GDNF identifies a high-risk subset of estrogen receptor positive breast cancer

PURPOSE

Resistance to endocrine therapy is the primary cause of treatment failure and death in patients with ER-positive (ER +)/luminal breast cancer. Expression and activation of the RET receptor tyrosine kinase may be driving poor outcomes. We aim to identify high-risk patients and druggable pathways for biomarker-based clinical trials.

METHODS

We obtained batch-normalized mRNA expression data from Breast Invasive Carcinoma-The Cancer Genome Atlas, PanCancer Atlas (BRCA-TCGA). To determine clinically significant cutoffs for RET expression, patients were grouped at different thresholds for Kaplan-Meier plotting. Differential gene expression (DGE) analysis and enrichment for gene sets was performed. transcriptomic dataset of antiestrogen-treated ER + tumors stratified by clinical response was then analyzed.

RESULTS

High RET expression was associated with worse outcomes in patients with ER + tumors, and stratification was enhanced by incorporating GDNF expression. High RET/GDNF patients had significantly lower overall survival (HR = 2.04, p = 0.012), progression-free survival (HR = 2.87, p < 0.001), disease-free survival (HR = 2.67, p < 0.001), and disease-specific survival (HR = 3.53, p < 0.001) than all other ER + patients. High RET/GDNF tumors were enriched for estrogen-independent signaling and targetable pathways including NTRK, PI3K, and KRAS. Tumors with adaptive resistance to endocrine therapy were enriched for gene expression signatures of high RET/GDNF primary tumors.

CONCLUSION

Expression and activation of the RET receptor tyrosine kinase may be driving poor outcomes in some patients with ER + breast cancer. ER + patients above the 75th percentile may benefit from clinical trials with tyrosine kinase inhibitors.

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.

Elevated PAF1-RAD52 axis confers chemoresistance to human cancers

Cisplatin- and gemcitabine-based chemotherapeutics represent a mainstay of cancer therapy for most solid tumors; however, resistance limits their curative potential. Here, we identify RNA polymerase II-associated factor 1 (PAF1) as a common driver of cisplatin and gemcitabine resistance in human cancers (ovarian, lung, and pancreas). Mechanistically, cisplatin- and gemcitabine-resistant cells show enhanced DNA repair, which is inhibited by PAF1 silencing. We demonstrate an increased interaction of PAF1 with RAD52 in resistant cells. Targeting the PAF1 and RAD52 axis combined with cisplatin or gemcitabine strongly diminishes the survival potential of resistant cells. Overall, this study shows clinical evidence that the expression of PAF1 contributes to chemotherapy resistance and worse clinical outcome for lethal cancers.

Exploration of prognostic biomarkers in head and neck squamous cell carcinoma microenvironment from TCGA database

Background

Immune checkpoint blockade (ICB) therapies have redefined human cancer treatment, including for head and neck squamous cell carcinoma (HNSCC). However, clinical responses to various immune checkpoint inhibitors are often accompanied by immune-related adverse events (irAEs). Therefore, it is crucial to obtain a comprehensive understanding of the association between different immune tumor microenvironments (TMEs) and the immunotherapeutic response.

Methods

The research data were obtained from The Cancer Genome Atlas (TCGA) database. We applied RNA-seq genomic data from tumor biopsies to assess the immune TME in HNSCC. As the TME is a heterogeneous system that is highly associated with HNSCC progression and clinical outcome, we relied on the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm to calculate immune and stromal scores that were evaluated based on the immune or stromal components in the TME. Then, the Tumor Immune Dysfunction and Exclusion algorithm (TIDE) was used to predict the benefits of ICB to each patient. Finally, we identified specific prognostic tumor-infiltrating immune cells (TIICs) by quantifying the cellular composition of the immune response in HNSCC and its association to survival outcome, using the CIBERSORT algorithm.

Results

Utilizing the HNSCC cohort of the TCGA database and TIDE and ESTIMATE algorithm-derived immune scores, we obtained a list of microenvironment-associated lncRNAs that predicted different clinical outcomes in HNSCC patients. We validated these correlations in a different HNSCC cohort available from the TCGA database and provided insight into the prediction of response to ICB therapies in HNSCC.

Conclusions

This study confirmed that CD8⁺ T cells were significantly associated with better survival in HNSCC and verified that the top five significantly mutated genes (SMGs) in the TCGA HNSCC cohort were TP53, TTN, FAT1, CDKN2A, and MUC16. A high level of CD8⁺ T cells and high immune and stroma scores corresponded to a better survival probability in HNSCC.

The role of IL-6/JAK2/STAT3 signaling pathway in cancers

Interleukin-6 (IL-6) is a pleiotropic cytokine involved in immune regulation. It can activate janus kinase 2 (JAK2)-signal transducer and activator of transcription 3 (STAT3) signaling pathway. As one of the important signal transduction pathways in cells, JAK2/STAT3 signaling pathway plays a critical role in cell proliferation and differentiation by affecting the activation state of downstream effector molecules. The activation of JAK2/STAT3 signaling pathway is involved in tumorigenesis and development. It contributes to the formation of tumor inflammatory microenvironment and is closely related to the occurrence and development of many human tumors. This article focuses on the relationship between IL-6/JAK2/STAT3 signaling pathway and liver cancer, breast cancer, colorectal cancer, gastric cancer, lung cancer, pancreatic cancer and ovarian cancer, hoping to provide references for the research of cancer treatment targeting key molecules in IL-6/JAK2/STAT3 signaling pathway.

Muc16 depletion diminishes KRAS-induced tumorigenesis and metastasis by altering tumor microenvironment factors in pancreatic ductal adenocarcinoma

MUC16, membrane-bound mucin, plays an oncogenic role in pancreatic ductal adenocarcinoma (PDAC). However, the pathological role of MUC16 in the PDAC progression, tumor microenvironment, and metastasis in cooperation with KrasG12D and Trp53R172H mutations remains unknown. Deletion of Muc16 with activating mutations KrasG12D/+ and Trp53R172H/+ in mice significantly decreased progression and prolonged overall survival in KrasG12D/+; Trp53R172H/+; Pdx-1-Cre; Muc16-/- (KPCM) and KrasG12D/+; Pdx-1-Cre; Muc16-/- (KCM), as compared to KrasG12D/+; Trp53R172H/+; Pdx-1-Cre (KPC) and KrasG12D/+; Pdx-1-Cre (KC) mice, respectively. Muc16 knockout pancreatic tumor (KPCM) displays decreased tumor microenvironment factors and significantly reduced incidence of liver and lung metastasis compared to KPC. Furthermore, in silico data analysis showed a positive correlation of MUC16 with activated stroma and metastasis-associated genes. KPCM mouse syngeneic cells had significantly lower metastatic and endothelial cell binding abilities than KPC cells. Similarly, KPCM organoids significantly decreased the growth rate compared to KPC organoids. Interestingly, RNA-seq data revealed that the cytoskeletal proteins Actg2, Myh11, and Pdlim3 were downregulated in KPCM tumors. Further knockdown of these genes showed reduced metastatic potential. Overall, our results demonstrate that Muc16 alters the tumor microenvironment factors during pancreatic cancer progression and metastasis by changing the expression of Actg2, Myh11, and Pdlim3 genes.

Expression of MUC16/CA125 Is Associated with Impaired Survival in Patients with Surgically Resected Cholangiocarcinoma

MUC16/CA125 is associated with cancer proliferation in several tumor entities. The data on MUC16 expression in cholangiocarcinoma (CCA) tissue are very limited. The aim of this study was to assess the MUC16 status and its impact on survival in CCA patients. All the patients with surgically resected CCA that were diagnosed between August 2005 and December 2021 at the University Hospital Frankfurt were retrospectively analyzed. A 7-Mucin biomarker panel was assessed by immunohistochemistry. For overall survival (OS), Kaplan−Meier curves and Cox-regression analyses were performed. Randomly selected intrahepatic cholangiocarcinoma (iCCA) were further processed for differential expression profiling. A total of 168 patients with CCA were classified as MUC16 (−) (66%, n = 111) and MUC16 (+) (34%, n = 57). Subgroup analyses revealed a median OS of 56.1 months (95% CI = 42.4−69.9 months) and 27.4 months (95% CI = 15.8−39.1 months) for MUC16 (−) and MUC16 (+), respectively (p < 0.001). In multivariate analysis, MUC16 (+) (HR = 1.6, 95% CI = 1−2.6, p = 0.032) was an independent risk factor for poor prognosis. Prominently deregulated pathways have been identified following MUC16 expression, overrepresented in cell cycle and immune system exhaustion processes. These findings suggest including MUC16 in clinical routine diagnostics as well as studying its molecular pathways to identify further mechanistic key players.

MUC16 Promotes Liver Metastasis of Pancreatic Ductal Adenocarcinoma by Upregulating NRP2-Associated Cell Adhesion

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal types of cancer, as it commonly metastasizes to the liver resulting in an overall poor prognosis. However, the molecular mechanism involved in liver metastasis remains poorly understood. Here, we aimed to identify the MUC16-mediated molecular mechanism of PDAC-liver metastasis. Previous studies demonstrated that MUC16 and its C-terminal (Cter) domain are involved in the aggressiveness of PDAC. In this study, we observed MUC16 and its Cter expression significantly high in human PDAC tissues, PDAC organoids, and metastatic liver tissues, while no expression was observed in normal pancreatic tissues using IHC and immunofluorescence (IFC) analyses. MUC16 knockdown in SW1990 and CD18/HPAF PDAC cells significantly decreased the colony formation, migration, and endothelial/p-selectin binding. In contrast, MUC16-Cter ectopic overexpression showed significantly increased colony formation and motility in MiaPaCa2 pancreatic cancer cells. Interestingly, MUC16 promoted cell survival and colonization in the liver, mimicking an ex vivo environment. Furthermore, MUC16 enhanced liver metastasis in the in vivo mouse model. Our integrated analyses of RNA-sequencing suggested that MUC16 alters Neuropilin-2 (NRP2) and cell adhesion molecules in pancreatic cancer cells. Furthermore, we identified that MUC16 regulated NRP2 via JAK2/STAT1 signaling in PDAC. NRP2 knockdown in MUC16-overexpressed PDAC cells showed significantly decreased cell adhesion and migration. Overall, the findings indicate that MUC16 regulates NRP2 and induces metastasis in PDAC.

IMPLICATIONS

This study shows that MUC16 plays a critical role in PDAC liver metastasis by mediating NRP2 regulation by JAK2/STAT1 axis, thereby paving the way for future therapy efforts for metastatic PDAC.

Human Malignant Rhabdoid Tumor Antigens as Biomarkers and Potential Therapeutic Targets

INTRODUCTION

Atypical teratoid rhabdoid tumor (ATRT) is a lethal type of malignant rhabdoid tumor in the brain, seen mostly in children under two years old. ATRT is mainly linked to the biallelic inactivation of the SMARCB1 gene. To understand the deadly characteristics of ATRT and develop novel diagnostic and immunotherapy strategies for the treatment of ATRT, this study investigated tumor antigens, such as alpha-fetoprotein (AFP), mucin-16 (MUC16/CA125), and osteopontin (OPN), and extracellular matrix modulators, such as matrix metalloproteinases (MMPs), in different human malignant rhabdoid tumor cell lines. In addition, the roles of MMPs were also examined.

MATERIALS AND METHODS

Five human cell lines were chosen for this study, including two ATRT cell lines, CHLA-02-ATRT and CHLA-05-ATRT; a kidney malignant rhabdoid tumor cell line, G401; and two control cell lines, human embryonic kidney HEK293 and HEK293T. Both ATRT cell lines were treated with a broad-spectrum MMP inhibitor, GM6001, to investigate the effect of MMPs on cell proliferation, viability, and expression of tumor antigens and biomarkers. Gene expression was examined using a reverse transcription polymerase chain reaction (RT-PCR), and protein expression was characterized by immunocytochemistry and flow cytometry.

RESULTS

All the rhabdoid tumor cell lines tested had high gene expression levels of MUC16, OPN, AFP, and MSLN. Low expression levels of neuron-specific enolase (ENO2) by the two ATRT cell lines demonstrated their lack of neuronal genotype. Membrane-type 1 matrix metalloproteinase (MT1-MMP/MMP-14) and tissue inhibitor of metalloproteinases-2 (TIMP-2) were highly expressed in these malignant rhabdoid tumor cells, indicating their invasive phenotypes. GM6001 significantly decreased ATRT cell proliferation and the gene expression of MSLN, OPN, and several mesenchymal markers, suggesting that inhibition of MMPs may reduce the aggressiveness of rhabdoid cancer cells.

CONCLUSION

The results obtained from this study may advance our knowledge of the molecular landscapes of human malignant rhabdoid tumors and their biomarkers for effective diagnosis and treatment. This work analyzed the expression of human malignant rhabdoid tumor antigens that may serve as biomarkers for the development of novel therapeutic strategies, such as cancer vaccines and targeted and immunotherapies targeting osteopontin and mesothelin, for the treatment of patients with ATRT and other malignant rhabdoid tumors.

[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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Mucin 16 Promotes Colorectal Cancer Development and Progression Through Activation of Janus Kinase 2

BACKGROUND

Mucin 16 (MUC16), a cell surface-associated mucin, has been implicated to be upregulated in a large repertoire of malignances. However, its function in the pathogenesis of colorectal cancer (CRC) is unknown.

AIMS

Here, we explored the regulatory role of MUC16 in CRC.

METHODS

First, tumor and paracancerous tissues, and serum samples from 162 CRC patients, peripheral blood samples from 48 healthy volunteers and 72 benign colorectal patients were collected. The correlation between the MUC16 expression and the clinical phenotypes of the patients was analyzed. Subsequently, HCT116 and SW480 cells with deletion of MUC16 were established to detect changes in the growth and metastatic capacities of CRC cells. The genes with the highest correlation with MUC16 were predicted by bioinformatics, and their binding relationships were detected by Co-IP and double-labeled immunofluorescence, followed by functional rescue experiments.

RESULTS

Overexpression of MUC16 in CRC patients was positively correlated with serum biomarkers and poor prognosis of patients. It was demonstrated by in vitro and in vivo experiments that knocking-down the expression of MUC16 could significantly inhibit the growth and metastasis of CRC cells. MUC16 activated janus kinase 2 (JAK2)/signal transducer and activator of transcription 3 (STAT3) by interacting with JAK2. Further overexpression of JAK2 in cells with poor expression of MUC16 revealed a significant increase in the proliferative and metastatic capacities of CRC cells.

CONCLUSIONS

MUC16 contributes to the development and progression of CRC by binding to JAK2, thereby promoting phosphorylation of JAK2 and further activating STAT3 phosphorylation.

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.

Functional Antagonism of Junctional Adhesion Molecule-A (JAM-A), Overexpressed in Breast Ductal Carcinoma In Situ (DCIS), Reduces HER2-Positive Tumor Progression

Simple Summary

Specific drug targets for breast ductal carcinoma in situ (DCIS) remain elusive, despite increasing disease prevalence and burden to healthcare services. Estrogen receptor (ER)-negative HER2-positive DCIS, associated with the poorest patient prognosis, is in particular need of novel therapeutic avenues. This report provides the first evidence that a cell surface protein called JAM-A is upregulated on human DCIS patient tissues and can be readily targeted by a novel JAM-A-binding peptide inhibitor in separate in vivo models of DCIS. The anti-tumor efficacy and lack of systemic toxicity of this lead inhibitor, coupled with early indications of potential signaling pathways implicated, support the value of future studies investigating JAM-A as a novel drug target in DCIS patients.

Abstract

Breast ductal carcinoma in situ (DCIS) is clinically challenging, featuring high diagnosis rates and few targeted therapies. Expression/signaling from junctional adhesion molecule-A (JAM-A) has been linked to poor prognosis in invasive breast cancers, but its role in DCIS is unknown. Since progression from DCIS to invasive cancer has been linked with overexpression of the human epidermal growth factor receptor-2 (HER2), and JAM-A regulates HER2 expression, we evaluated JAM-A as a therapeutic target in DCIS. JAM-A expression was immunohistochemically assessed in patient DCIS tissues. A novel JAM-A antagonist (JBS2) was designed and tested alone/in combination with the HER2 kinase inhibitor lapatinib, using SUM-225 cells in vitro and in vivo as validated DCIS models. Murine tumors were proteomically analyzed. JAM-A expression was moderate/high in 96% of DCIS patient tissues, versus 23% of normal adjacent tissues. JBS2 bound to recombinant JAM-A, inhibiting cell viability in SUM-225 cells and a primary DCIS culture in vitro and in a chick embryo xenograft model. JBS2 reduced tumor progression in in vivo models of SUM-225 cells engrafted into mammary fat pads or directly injected into the mammary ducts of NOD-SCID mice. Preliminary proteomic analysis revealed alterations in angiogenic and apoptotic pathways. High JAM-A expression in aggressive DCIS lesions and their sensitivity to treatment by a novel JAM-A antagonist support the viability of testing JAM-A as a novel therapeutic target in DCIS.

Effect of MUC16 mutations on tumor mutation burden and its potential prognostic significance for cutaneous melanoma

OBJECTIVES

MUC16, a mucin marker with a high mutation probability, is closely related to the occurrence, development, response to treatment, and prognosis of melanoma. As melanoma has high immunogenicity, immunotherapy has become a routine treatment. Tumor mutation burden (TMB) is the most common indicator for determining appropriate immunotherapy. The relationship between the mutation and expression of MUC16 and the prognosis, TMB, level of immune infiltration, and drug sensitivity in melanoma was investigated in this study.

METHODS

Melanoma data were downloaded from the Cancer Genome Atlas and the International Cancer Genome Consortium database, and the "GenVisR" package was used to visualize the gene mutation types and frequencies. Intersections of the top 30 genes with the highest mutation frequencies were determined. Thereafter, we investigated the effects of MUC16 mutations on overall survival (OS) and TMB of melanoma patients by multivariate Cox regression and multivariate logistic analyses. Related pathways that were enriched by MUC16 and BRAF were investigated using gene-set enrichment analysis and gene-set variation analysis. The CIBERSORT calculation method was used to analyze the proportion of tumor-infiltrating immune subsets. The relationship between MUC16 expression and drug sensitivity was also discussed.

RESULTS

Twenty-two genes with high mutation frequencies were identified in both datasets. MUC16 and ADGRV1 mutations were associated with higher TMB and good clinical prognosis (P<0.05). Multivariate Cox regression analysis showed that age, clinical stage, and MUC16 mutations were independent prognostic factors affecting OS of melanoma patients. Multivariate logistic analysis showed that gender and MUC16 mutations were independent prognostic factors affecting the TMB. MUC16 mutations and high-expression groups were primarily enriched in immune-related pathways. Furthermore, T-cell CD4 memory activation and T-cell CD8 were positively correlated with MUC16 expression and activated dendritic cells were significantly enriched in the MUC16 mutant group. Abnormal MUC16 expression may be related to abnormal methylation and drug resistance.

CONCLUSION

MUC16 was found to have a higher mutation frequency in melanoma patients, which is associated with a higher TMB. The mutation and/or expression of MUC16 may affect immune-related pathways and tumor-infiltrating immune cell subsets, which may improve the prognosis for melanoma patients.

Computational Prediction of the Pathogenic Status of Cancer-Specific Somatic Variants

In-silico classification of the pathogenic status of somatic variants is shown to be promising in promoting the clinical utilization of genetic tests. Majority of the available classification tools are designed based on the characteristics of germline variants or the combination of germline and somatic variants. Significance of somatic variants in cancer initiation and progression urges for development of classifiers specialized for classifying pathogenic status of cancer somatic variants based on the model trained on cancer somatic variants. We established a gold standard exclusively for cancer somatic single nucleotide variants (SNVs) collected from the catalogue of somatic mutations in cancer. We developed two support vector machine (SVM) classifiers based on genomic features of cancer somatic SNVs located in coding and non-coding regions of the genome, respectively. The SVM classifiers achieved the area under the ROC curve of 0.94 and 0.89 regarding the classification of the pathogenic status of coding and non-coding cancer somatic SNVs, respectively. Our models outperform two well-known classification tools including FATHMM-FX and CScape in classifying both coding and non-coding cancer somatic variants. Furthermore, we applied our models to predict the pathogenic status of somatic variants identified in young breast cancer patients from METABRIC and TCGA-BRCA studies. The results indicated that using the classification threshold of 0.8 our "coding" model predicted 1853 positive SNVs (out of 6,910) from the TCGA-BRCA dataset, and 500 positive SNVs (out of 1882) from the METABRIC dataset. Interestingly, through comparative survival analysis of the positive predictions from our models, we identified a young-specific pathogenic somatic variant with potential for the prognosis of early onset of breast cancer in young women.

Disruption of FDPS/Rac1 axis radiosensitizes pancreatic ductal adenocarcinoma by attenuating DNA damage response and immunosuppressive signalling

Background

Radiation therapy (RT) has a suboptimal effect in patients with pancreatic ductal adenocarcinoma (PDAC) due to intrinsic and acquired radioresistance (RR). Comprehensive bioinformatics and microarray analysis revealed that cholesterol biosynthesis (CBS) is involved in the RR of PDAC. We now tested the inhibition of the CBS pathway enzyme, farnesyl diphosphate synthase (FDPS), by zoledronic acid (Zol) to enhance radiation and activate immune cells.

Methods

We investigated the role of FDPS in PDAC RR using the following methods: in vitro cell-based assay, immunohistochemistry, immunofluorescence, immunoblot, cell-based cholesterol assay, RNA sequencing, tumouroids (KPC-murine and PDAC patient-derived), orthotopic models, and PDAC patient's clinical study.

Findings

FDPS overexpression in PDAC tissues and cells (P < 0.01 and P < 0.05) is associated with poor RT response and survival (P = 0.024). CRISPR/Cas9 and pharmacological inhibition (Zol) of FDPS in human and mouse syngeneic PDAC cells in conjunction with RT conferred higher PDAC radiosensitivity in vitro (P < 0.05, P < 0.01, and P < 0.001) and in vivo (P < 0.05). Interestingly, murine (P = 0.01) and human (P = 0.0159) tumouroids treated with Zol+RT showed a significant growth reduction. Mechanistically, RNA-Seq analysis of the PDAC xenografts and patients-PBMCs revealed that Zol exerts radiosensitization by affecting Rac1 and Rho prenylation, thereby modulating DNA damage and radiation response signalling along with improved systemic immune cells activation. An ongoing phase I/II trial (NCT03073785) showed improved failure-free survival (FFS), enhanced immune cell activation, and decreased microenvironment-related genes upon Zol+RT treatment.

Interpretation

Our findings suggest that FDPS is a novel radiosensitization target for PDAC therapy. This study also provides a rationale to utilize Zol as a potential radiosensitizer and as an immunomodulator in PDAC and other cancers.

Funding

National Institutes of Health (P50, P01, and R01).

The evolving role of MUC16 (CA125) in the transformation of ovarian cells and the progression of neoplasia

MUC16 (the cancer antigen CA125) is the most commonly used serum biomarker in epithelial ovarian cancer, with increasing levels reflecting disease progression. It is a transmembrane glycoprotein with multiple isoforms, undergoing significant changes through the metastatic process. Aberrant glycosylation and cleavage with overexpression of a small membrane-bound fragment consist MUC16-related mechanisms that enhance malignant potential. Even MUC16 knockdown can induce an aggressive phenotype but can also increase susceptibility to chemotherapy. Variable MUC16 functions help ovarian cancer cells avoid immune cytotoxicity, survive inside ascites and form metastases. This review provides a comprehensive insight into MUC16 transformations and interactions, with description of activated oncogenic signalling pathways, and adds new elements on the role of its differential glycosylation. By following the journey of the molecule from pre-malignant states to advanced stages of disease it demonstrates its behaviour, in relation to the phenotypic shifts and progression of ovarian cancer. Additionally, it presents proposed differences of MUC16 structure in normal/benign conditions and epithelial ovarian malignancy.

Impact of Neoantigen Expression and T-Cell Activation on Breast Cancer Survival

Simple Summary

Neoantigens are novel proteins presented on the cell surface and derived from the accumulation of somatic mutations in tumor cells. They can be recognized by the immune system and may play a crucial role in boosting immune responses against tumor cells. The impact of neoantigen expression and T-cell activation status on overall survival was investigated in a breast cancer cohort. We found that high neoantigen expression and T-cell activation status was correlated with improved patient survival in the study population. This result supports that neoantigens are promising to serve as immunogenic agents for immunotherapy in breast cancer.

Abstract

Neoantigens are derived from tumor-specific somatic mutations. Neoantigen-based synthesized peptides have been under clinical investigation to boost cancer immunotherapy efficacy. The promising results prompt us to further elucidate the effect of neoantigen expression on patient survival in breast cancer. We applied Kaplan–Meier survival and multivariable Cox regression models to evaluate the effect of neoantigen expression and its interaction with T-cell activation on overall survival in a cohort of 729 breast cancer patients. Pearson’s chi-squared tests were used to assess the relationships between neoantigen expression and clinical pathological variables. Spearman correlation analysis was conducted to identify correlations between neoantigen expression, mutation load, and DNA repair gene expression. ERCC1, XPA, and XPC were negatively associated with neoantigen expression, while BLM, BRCA2, MSH2, XRCC2, RAD51, CHEK1, and CHEK2 were positively associated with neoantigen expression. Based on the multivariable Cox proportional hazard model, patients with a high level of neoantigen expression and activated T-cell status showed improved overall survival. Similarly, in the T-cell exhaustion and progesterone receptor (PR) positive subgroups, patients with a high level of neoantigen expression showed prolonged survival. In contrast, there was no significant difference in the T-cell activation and PR negative subgroups. In conclusion, neoantigens may serve as immunogenic agents for immunotherapy in breast cancer.

Knockdown of MUC16 (CA125) Enhances the Migration and Invasion of Hepatocellular Carcinoma Cells

As an important global medical problem, hepatocellular carcinoma (HCC) has been recognized as the most frequent primary liver cancer and a leading cause of death among patients with cirrhosis. Surveillance of HCC using serum markers aims to reduce the disease-related mortality of HCC. MUC16 (mucin 16, also known as carbohydrate antigen 125, CA125) has been predicted as a tumor biomarker for many cancer types. Based on the high frequency mutation rate in a database from the Cancer Genome Atlas (TCGA), we investigated the effects of MUC16 knockdown and the regulatory profile of MUC16 in HepG2 and Huh7 cell lines. Knockdown of MUC16 was conducted via siRNA transfection, and the proliferation of cells was not affected by CCK8 assay results. Moreover, decreasing the expression of MUC16 enhanced the migration and invasion of cells, as shown by wound healing and transwell assays. Furthermore, RNA-seq was used to investigate the effect of MUC16 knockdown on the gene expression profile of HepG2 and Huh7 cells. Our study demonstrated the significant role of MUC16 in the inhibition of the migration and invasion of HepG2 and Huh7 cells.

Spatial Distribution of Private Gene Mutations in Clear Cell Renal Cell Carcinoma

Simple Summary

Tumours consist of multiple groups of similar cells resulting from differing evolutionary trajectories, i.e., subclones. These subclones are prevalent in clear cell renal cell carcinoma (ccRCC). The aim of this study is to determine how similar or dissimilar the subclones in 89 ccRCC tumours are from one another regarding their gene mutations and expression profiles, i.e., the extent of intra-tumour heterogeneity. The implications of these alterations with respect to signalling pathways is also assessed. Deep sequencing allows for the identification of mutations with low-allele frequencies, providing a more comprehensive view of the heterogeneity present in the tumours. With an average of 62% of mutations having been identified in only one of the two biopsies, some of which in turn are found to impact gene expression, the complex makeup of ccRCC tumours is evident, and this can drastically influence treatment outcome.

Abstract

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average, 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction and might explain the clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

Predictive effects of preoperative serum CA125 and AFP levels on post-hepatectomy survival in patients with hepatitis B-related hepatocellular carcinoma

The association between the serum levels of cancer antigen 125 (CA125; also termed MUC16) and the prognosis of patients with hepatocellular carcinoma (HCC) has not been widely reported to date. The aim of the present study was to determine the association between preoperative serum CA125 levels and prognosis of patients with hepatitis B virus (HBV)-related HCC after hepatectomy. The study included 306 patients with HBV-related HCC who underwent liver resection and were classified into four subgroups based on their baseline CA125 and α-fetoprotein (AFP) levels. The perioperative clinical data were compared and analyzed. Kaplan-Meier and Cox regression analyses were performed to determine the associations between patient clinicopathological characteristics and survival. The results revealed that the median follow-up time was 35 months. Patients with low preoperative serum CA125 levels presented with improved 3-year disease-free survival (DFS) (79.3 vs. 75.7%; P=0.278) and overall survival (OS) (84.4 vs. 77.1%; P=0.001) rates compared with those among patients with high preoperative serum CA125 levels. High preoperative serum CA125 levels were a risk factor associated with short DFS and OS rates in all patients. In patients with baseline AFP levels >100 ng/ml, low preoperative serum CA125 levels were significantly associated with prolonged DFS and OS rates (log-rank test P=0.002 and P=0.005, respectively). In patients with AFP levels ≤100 ng/ml, no significant differences were observed in DFS or OS rates between the high and low preoperative serum CA125 groups. Patients with high preoperative serum CA125 and AFP levels exhibited the worst prognosis (low DFS and OS rates). In conclusion, high baseline CA125 levels may be associated with a poor prognosis in patients with HBV-related HCC.

Targeting galectin-3 with a high-affinity antibody for inhibition of high-grade serous ovarian cancer and other MUC16/CA-125-expressing malignancies

The lectin, galectin-3 (Gal3), has been implicated in a variety of inflammatory and oncogenic processes, including tumor growth, invasion, and metastasis. The interactions of Gal3 and MUC16 represent a potential targetable pathway for the treatment of MUC16-expressing malignancies. We found that the silencing of Gal3 in MUC16-expressing breast and ovarian cancer cells in vitro inhibited tumor cell invasion and led to attenuated tumor growth in murine models. We therefore developed an inhibitory murine monoclonal anti-Gal3 carbohydrate-binding domain antibody, 14D11, which bound human and mouse Gal3 but did not bind human Galectins-1, -7, -8 or -9. Competition studies and a docking model suggest that the 14D11 antibody competes with lactose for the carbohydrate binding pocket of Gal3. In MUC16-expressing cancer cells, 14D11 treatment blocked AKT and ERK1/2 phosphorylation, and led to inhibition of cancer cell Matrigel invasion. Finally, in experimental animal tumor models, 14D11 treatment led to prolongation of overall survival in animals bearing flank tumors, and retarded lung specific metastatic growth by MUC16 expressing breast cancer cells. Our results provide evidence that antibody based Gal3 blockade may be a viable therapeutic strategy in patients with MUC16-expressing tumors, supporting further development of human blocking antibodies against Gal3 as potential cancer therapeutics.

MUC16 promotes EOC proliferation by regulating GLUT1 expression

As a common malignancy in females with a higher incidence rate, epithelial ovarian cancer (EOC) is a heterogeneous disease with complexity and diversity in histology and therapeutic response. Although great progress has been made in diagnosis and therapeutic strategies, novel therapeutic strategies are required to improve survival. Although the promoting effect of mucin 16 (MUC16) on tumour progression has been reported, the potential mechanisms remain unclear. In our study, we reported that overexpression of MUC16 was significantly related to cell proliferation and disease progression in EOC. Results from clinical specimen analysis and cell experiment support this conclusion. Patients with a high MUC16 expression usually had a worse prognosis that those with a low expression. Cell proliferation ability was significantly decreased in EOC cell lines when the knockdown of MUC16. Further study shows that the function of MUC16 in cell proliferation is based on the regulation of glucose transporter 1 (GLUT1) expression. MUC16 can control glucose uptake by regulating GLUT1 in EOC cells, thereby promoting glycogen synthesis, so that tumour cells produce more energy for proliferation. This conclusion is based on two findings. First, the significant correlation between MUC16 and GLUT1 was verified by clinical specimen and TCGA data analysis. Then, alteration of MUC16 expression levels can affect the expression of GLUT1 and glucose uptake was also verified. Finally, this conclusion is further verified in vivo by tumour‐bearing mice model. To summarize, our results suggest that MUC16 promotes EOC proliferation and disease progression by regulating GLUT1 expression.

A Novel Framework to Predict Breast Cancer Prognosis Using Immune-Associated LncRNAs

Background: Breast cancer (BC) is one of the most frequently diagnosed malignancies among females. As a huge heterogeneity of malignant tumor, it is important to seek reliable molecular biomarkers to carry out the stratification for patients with BC. We surveyed immune- associated lncRNAs that may be used as potential therapeutic targets in BC.

Methods: LncRNA expression data and clinical information of BC patients were downloaded from the TCGA database for a comprehensive analysis of candidate genes. A model consisting of immune-related lncRNAs enriched in BC cancerous tissues was established using the univariate Cox regression analysis and the iterative Lasso Cox regression analysis. The prognostic performance of this model was validated in two independent cohorts (GSE21653 and BC-KR), and compared with known prognostic biomarkers. A nomogram that integrated the immune-related lncRNA signature and clinicopathological factors was constructed to accurately assess the prognostic value of this signature. The correlation between the signature and immune cell infiltration in BC was also analyzed.

Results: The Kaplan-Meier analysis showed that the OS of Patients in the low-risk group had significantly better survival than those in the high-risk group, Clinical subgroup analysis showed that the predictive ability was independent of clinicopathological factors. Univariate/multivariate Cox regression analysis showed immune lncRNA signature is an important prognostic factor and an independent prognostic marker. In addition, GSEA and GSVA analysis as well as comprehensive analysis of immune cells showed that the signature was significantly correlated with the infiltration of immune cells.

Conclusion: We successfully constructed an immune-associated lncRNA signature that can accurately predict BC prognosis.

Single-pot enzymatic synthesis of cancer-associated MUC16 O-glycopeptide libraries and multivalent protein glycoconjugates: a step towards cancer glycovaccines

Glycosyltransferases and nucleotide sugars are combined in single-pot settings to synthesize a library of cancer-associated MUC16 O-glycopeptides and multivalent protein glycoconjugates foreseeing future development of cancer glycovaccines.

Targeting Glycans and Heavily Glycosylated Proteins for Tumor Imaging

Simple Summary

Distinguishing malignancy from healthy tissue is essential for oncologic surgery. Targeted imaging during an operation aids the surgeon to operate better. The present tracers for detecting cancer are directed against proteins that are overexpressed on the membrane of tumor cells. This review evaluates the use of tumor-associated sugar molecules as an alternative for proteins to image cancer tissue. These sugar molecules are present as glycans on glycosylated membrane proteins and glycolipids. Due to their location and large numbers per cell, these sugar molecules might be better targets for tumor imaging than proteins.

Abstract

Real-time tumor imaging techniques are increasingly used in oncological surgery, but still need to be supplemented with novel targeted tracers, providing specific tumor tissue detection based on intra-tumoral processes or protein expression. To maximize tumor/non-tumor contrast, targets should be highly and homogenously expressed on tumor tissue only, preferably from the earliest developmental stage onward. Unfortunately, most evaluated tumor-associated proteins appear not to meet all of these criteria. Thus, the quest for ideal targets continues. Aberrant glycosylation of proteins and lipids is a fundamental hallmark of almost all cancer types and contributes to tumor progression. Additionally, overexpression of glycoproteins that carry aberrant glycans, such as mucins and proteoglycans, is observed. Selected tumor-associated glyco-antigens are abundantly expressed and could, thus, be ideal candidates for targeted tumor imaging. Nevertheless, glycan-based tumor imaging is still in its infancy. In this review, we highlight the potential of glycans, and heavily glycosylated proteoglycans and mucins as targets for multimodal tumor imaging by discussing the preclinical and clinical accomplishments within this field. Additionally, we describe the major advantages and limitations of targeting glycans compared to cancer-associated proteins. Lastly, by providing a brief overview of the most attractive tumor-associated glycans and glycosylated proteins in association with their respective tumor types, we set out the way for implementing glycan-based imaging in a clinical practice.

ERO1L promotes IL6/sIL6R signaling and regulates MUC16 expression to promote CA125 secretion and the metastasis of lung cancer cells

The abnormal secretion of CA125, a classic tumor marker, is usually related to a poor prognosis in various tumors. Thus, this study aimed to explore the potential mechanisms that promote CA125 secretion in lung cancer. By querying the database, the gene endoplasmic reticulum oxidoreductase 1L (ERO1L) was identified and chosen as the research subject. The antibody chips were used to screen the lung cancer cell supernatant and found that the most obvious secreted protein was CA125. ERO1L was found to promote the secretion of IL6R by affecting the formation of disulfide bonds. IL6R bound to IL6 and triggered the activation of the NF-κB signaling pathway. Then, NF-κB bound to the promoter of MUC16, resulting in overexpression of MUC16. The extracellular segment of MUC16 was cleaved to form CA125, while the C terminus of MUC16 promoted the EMT phenotype and the release of IL6, forming a positive feedback pathway. In conclusion, ERO1L might affect the secretion of CA125 through the IL6 signaling pathway and form a positive feedback loop to further promote the development of lung cancer. This might expand the application scope of CA125 in lung cancer.

Acinar transformed ductal cells exhibit differential mucin expression in a tamoxifen-induced pancreatic ductal adenocarcinoma mouse model

Pancreatic cancer (PC) is acquired postnatally; to mimic this scenario, we developed an inducible KrasG12D; Ptf1a-CreER™ (iKC) mouse model, in which Kras is activated postnatally at week 16 upon tamoxifen (TAM) administration. Upon TAM treatment, iKC mice develop pancreatic intraepithelial neoplasia (PanIN) lesions and PC with metastasis at the fourth and fortieth weeks, respectively, and exhibited acinar-to-ductal metaplasia (ADM) and transdifferentiation. Kras activation upregulated the transcription factors Ncoa3, p-cJun and FoxM1, which in turn upregulated expression of transmembrane mucins (Muc1, Muc4 and Muc16) and secretory mucin (Muc5Ac). Interestingly, knockdown of KrasG12D in multiple PC cell lines resulted in downregulation of MUC1, MUC4, MUC5AC and MUC16. In addition, iKC mice exhibited ADM and transdifferentiation. Our results show that the iKC mouse more closely mimics human PC development and can be used to investigate pancreatic ductal adenocarcinoma (PDAC) biomarkers, early onset of PDAC, and ADM. The iKC model can also be used for preclinical strategies such as targeting mucin axis alone or in combination with neo-adjuvant, immunotherapeutic approaches and to monitor chemotherapy response.

Combining the tumor abnormal protein test with tests for carcinoembryonic antigens, cancer antigen 15-3, and/or cancer antigen 125 significantly increased their diagnostic sensitivity for breast cancer

BACKGROUND

The tumor abnormal protein (TAP) test is used to screen for many cancers, but its use for breast cancer has not been studied.

METHODS

Tests for carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), cancer antigen 15-3 (CA15-3), and TAP were administered to 261 women with operable benign breast disease and 348 with breast cancer. The cutoff value used for TAP was the mean + 3 standard deviations for benign breast disease patients (275.64 μm). Sensitivities and specificities of single biomarker tests and combined tests were compared. The combined tests were defined as positive if any single biomarker was positive, and negative otherwise.

RESULTS

The single biomarker test sensitivities were similar: CEA, 7.18%; CA125, 4.89%; CA15-3, 7.47%; and TAP, 4.89%. For the combinations TAP + CEA + CA125, TAP + CEA + CA15-3, TAP + CA125 + CA15-3, and TAP + CEA + CA125 + CA15-3, the sensitivities were 16.67%, 17.82%, 16.38%, and 21.84%, respectively, and the specificities were 93.49%, 97.70%, 93.87%, and 92.72%.

CONCLUSIONS

The 4-test combination showed the highest sensitivity (21.84%) and may be auxiliary used in early screening. TAP + CEA + CA15-3 showed high specificity (97.70%) and so could be used for confirming breast cancer.

MUC15 promotes growth and invasion of glioma cells by activating Raf/MEK/ERK pathway

MUC15 is a novel mucin associated with the cell membrane that is overexpressed in human gliomas. Its function in glioma is unclear. In this study, high MUC15 levels were detected in glioma tissues and cells. We found that transfection with MUC15 siRNA in U251 and T98G cells reduced MUC15 expression and decreased cell proliferation, invasion, and migration (P < .05). After transfecting U251 and T98G cells with pcDNA3.1-myc-His-MUC15 plasmid to overexpress MUC15, MUC15 expression was significantly upregulated and cell proliferation, invasion, and migration were increased (P < .05). MUC15 activated the Raf/MEK/ERK signalling pathway and the ERK inhibitor PD98059 partly reversed MUC15-enhanced proliferation, invasion, and migration of glioma cells (P < .05). The results indicate that MUC15 plays a part in glioma tumorigenesis, and the Raf/MEK/ERK signalling is involved in the regulation of MUC15 on glioma cell activity.

P-STAT3 and IL-17 in tumor tissues enhances the prognostic value of CEA and CA125 in patients with lung adenocarcinoma

AIM

The present study aimed to examine the capability of p- signal transducer and activator of transcription (STAT)3 and interleukin-17 (IL-17), along with two known tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 125 (CA125), for disease prognosis. Moreover, the associations among biomarkers and clinicopathological parameters were evaluated to uncover the potential mechanisms responsible for their correlations with lung adenocarcinoma (LAD) prognosis.

METHODS

Five LAD-related parameters were used in the study: CEA, CA125, STAT3, p-STAT3, and IL-17. Spearman and chi-square correlation tests were used to explore the relationships between some clinicopathological variables and parameter expression levels and the associations among these five parameters.

RESULTS

The disease-specific survival decreased with the positive expression of CEA, CA125, p-STAT3, and IL-17, with no significant difference in the expression level of STAT3. Combinations of p-STAT3 and IL-17, CEA and p-STAT3, CEA and IL-17, CA125 and p-STAT3, and CA125 and IL-17 had higher predictive values in LAD prognosis. The correlation analyses indicated the synergic activities of STAT3, p-STAT3, and IL-17 and the coordinated expression of CEA, CA125, p-STAT3, and IL-17. The tumor-node-metastasis (TNM) stage significantly correlated with the levels of CA125 and p-STAT3.

CONCLUSIONS

Elevated levels of CEA, CA125, p-STAT3, and IL-17 alone and/or combinations of p-STAT3 and IL-17, CEA and p-STAT3, CEA and IL-17, CA125 and p-STAT3, and CA125 and IL-17 were recommended as the prognostic predictors of unfavorable clinical outcomes in patients with postoperative LAD. Also, p-STAT3 and IL-17 combined with CA125 and CEA helped in predicting the overall survival of patients with LAD and informing the TNM stage.