Autoantibody biomarkers for the detection of serous ovarian cancer

An electrochemical immunosensor based on MXene-GQD/AuNPs for the detection of trace amounts of CA-125 as specific tracer of ovarian cancer

An electrochemical immunoassay system was developed to detect CA-125 using a glassy carbon electrode (GCE) modified with MXene, graphene quantum dots (GQDs), and gold nanoparticles (AuNPs). The combined MXene-GQD/AuNPs modification displayed advantageous electrochemical properties due to the synergistic effects of MXene, GQDs, and AuNPs. The MXene-GQD composite in the modified layer provided strong mechanical properties and a large specific surface area. Furthermore, the presence of AuNPs significantly improved conductivity and facilitated the binding of anti-CA-125 on the modified GCE, thereby enhancing sensitivity. Various analytical techniques such as FE-SEM and EDS were utilized to investigate the structural and morphological characteristics as well as the elemental composition. The performance of the developed immunosensor was assessed using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), square wave voltammetry (SWV), and differential pulse voltammetry (DPV). Under optimized conditions in a working potential range of -0.2 to 0.6 V (vs. Ag/AgCl), the sensitivity, linear range (LR), limit of detection (LOD), and correlation coefficient (R2) were determined to be 315.250 µA pU.mL-1/cm2, 0.1 to 1 nU/mL, 0.075 nU/mL, and 0.9855, respectively. The detection of CA-125 in real samples was investigated using the developed immunoassay platform, demonstrating satisfactory results including excellent selectivity and reproducibility.

Autoantibodies, antigen-autoantibody complexes and antigens complement CA125 for early detection of ovarian cancer

BACKGROUND

Multiple antigens, autoantibodies (AAb), and antigen-autoantibody (Ag-AAb) complexes were compared for their ability to complement CA125 for early detection of ovarian cancer.

METHODS

Twenty six biomarkers were measured in a single panel of sera from women with early stage (I-II) ovarian cancers (n = 64), late stage (III-IV) ovarian cancers (186), benign pelvic masses (200) and from healthy controls (502), and then split randomly (50:50) into a training set to identify the most promising classifier and a validation set to compare its performance to CA125 alone.

RESULTS

Eight biomarkers detected ≥ 8% of early stage cases at 98% specificity. A four-biomarker panel including CA125, HE4, HE4 Ag-AAb and osteopontin detected 75% of early stage cancers in the validation set from among healthy controls compared to 62% with CA125 alone (p = 0.003) at 98% specificity. The same panel increased sensitivity for distinguishing early-stage ovarian cancers from benign pelvic masses by 25% (p = 0.0004) at 95% specificity. From 21 autoantibody candidates, 3 AAb (anti-p53, anti-CTAG1 and annt-Il-8) detected 22% of early stage ovarian cancers, potentially lengthening lead time prior to diagnosis.

CONCLUSION

A four biomarker panel achieved greater sensitivity at the same specificity for early detection of ovarian cancer than CA125 alone.

UHMK1 promotes lung adenocarcinoma oncogenesis by regulating the PI3K/AKT/mTOR signaling pathway

BACKGROUND

Effective targeted therapy for lung adenocarcinoma (LUAD), the number one cancer killer worldwide, continues to be a difficult problem because of the limitation of number of applicable patients and acquired resistance. Identifying more promising drug targets for LUAD treatment holds immense clinical significance. Recent studies have revealed that the U2 auxiliary factor (U2AF) homology motif kinase 1 (UHMK1) is a robust pro-oncogenic factor in many cancers. However, its biological functions and the underlying molecular mechanisms in LUAD have not been investigated.

METHODS

The UHMK1 expression in LUAD cells and tissues was evaluated by bioinformatics analysis, immunohistochemistry (IHC), western blotting (WB), and real time quantitative polymerase chain reaction (RT-qPCR) assays. A series of gain- and loss-of-function experiments for UHMK1 were carried out to investigate its biological functions in LUAD in vitro and in vivo. The mechanisms underlying UHMK1's effects in LUAD were analyzed by transcriptome sequencing and WB assays.

RESULTS

UHMK1 expression was aberrantly elevated in LUAD tumors and cell lines and positively correlated with tumor size and unfavorable patient prognosis. Functionally, UHMK1 displayed robust pro-oncogenic capacity in LUAD and mechanistically exerted its biological effects via the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway.

CONCLUSION

UHMK1 is a potent oncogene in LUAD. Targeting UHMK1 may significantly improve the effect of LUAD treatment via inhibiting multiple biological ways of LUAD progression.

Research progress in protein microarrays: Focussing on cancer research

Although several effective treatment modalities have been developed for cancers, the morbidity and mortality associated with cancer continues to increase every year. As one of the most exciting emerging technologies, protein microarrays represent a powerful tool in the field of cancer research because of their advantages such as high throughput, small sample usage, more flexibility, high sensitivity and direct readout of results. In this review, we focus on the research progress in four types of protein microarrays (proteome microarray, antibody microarray, lectin microarray and reversed protein array) with emphasis on their application in cancer research. Finally, we discuss the current challenges faced by protein microarrays and directions for future developments. We firmly believe that this novel systems biology research tool holds immense potential in cancer research and will become an irreplaceable tool in this field.

Molecular Biomarkers for the Early Detection of Ovarian Cancer

Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.

A novel prognostic 7-methylguanosine signature reflects immune microenvironment and alternative splicing in glioma based on multi-omics analysis

Glioma is the most common type of central nervous system tumor with increasing incidence. 7-methylguanosine (m7G) is one of the diverse RNA modifications that is known to regulate RNA metabolism and its dysregulation was associated with various cancers. However, the expression pattern of m7G regulators and their roles in regulating tumor immune microenvironments (TIMEs) as well as alternative splicing events (ASEs) in glioma has not been reported. In this study, we showed that m7G regulators displayed a close correlation with each other and most of them were differentially expressed between normal and glioma tissues. Two m7G signatures were then constructed to predict the overall survival of both GBM and LGG patients with moderate predictive performance. The risk score calculated from the regression coefficient and expression level of signature genes was proved to be an independent prognostic factor for patients with LGG, thus, a nomogram was established on the risk score and other independent clinical parameters to predict the survival probability of LGG patients. We also investigated the correlation of m7G signatures with TIMEs in terms of immune scores, expression levels of HLA and immune checkpoint genes, immune cell composition, and immune-related functions. While exploring the correlation between signature genes and the ASEs in glioma, we found that EIF4E1B was a key regulator and might play dual roles depending on glioma grade. By incorporating spatial transcriptomic data, we found a cluster of cells featured by high expression of PTN exhibited the highest m7G score and may communicate with adjacent cancer cells via SPP1 and PTN signaling pathways. In conclusion, our work brought novel insights into the roles of m7G modification in TIMEs and ASEs in glioma, suggesting that evaluation of m7G in glioma could predict prognosis. Moreover, our data suggested that blocking SPP1 and PTN pathways might be a strategy for combating glioma.

The feasibility of using an autologous GM-CSF-secreting breast cancer vaccine to induce immunity in patients with stage II-III and metastatic breast cancers

PURPOSE

The antigenic targets of immunity and the role of vaccination in breast cancer are unknown. We performed a phase I study of an autologous GM-CSF-secreting breast cancer vaccine in patients with metastatic and stage II-III breast cancer.

METHODS

Tumor cells from patients with metastatic (n = 15) and stage II-III (n = 7) disease were transduced with a replication-defective adenoviral vector encoding GM-CSF, and then irradiated. Twelve and seven patients with metastatic and stage II-III disease, respectively, received weekly vaccination for three weeks, followed by every other week until disease progression or vaccine supply was exhausted (metastatic) or until six total vaccine doses were administered (stage II-III).

RESULTS

Among those patients with metastatic disease who received vaccinations, eight had progressive disease at two months, three had stable disease for 4-13 months, and one has had no evidence of disease for 13 years. Of the patients with stage II-III disease, five died of metastatic disease between 1.16 and 8.49 years after the start of vaccinations (median 6.24 years) and two are alive as of September 2021. Toxicities included injection site reactions, fatigue, fever, upper respiratory symptoms, joint pain, nausea, and edema. Four of five evaluable patients with metastatic disease developed a skin reaction with immune cell infiltration after the fifth injection of unmodified, irradiated tumor cells.

CONCLUSION

We conclude that tumor cells can be harvested from patients with metastatic or stage II-III breast cancer to prepare autologous GM-CSF-secreting vaccines that induce coordinated immune responses with limited toxicity. TRIAL REGISTRATION AND DATE OF REGISTRATION: clinicaltrials.gov, NCT00317603 (April 25, 2006) and NCT00880464 (April 13, 2009).

Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review

With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.

Serum autoantibodyome reveals that healthy individuals share common autoantibodies

Autoantibodies are a hallmark of both autoimmune disease and cancer, but they also occur in healthy individuals. Here, we perform a meta-analysis of nine datasets and focus on the common autoantibodies shared by healthy individuals. We report 77 common autoantibodies based on the protein microarray data obtained from probing 182 healthy individual sera on 7,653 human proteins and an additional 90 healthy individual sera on 1,666 human proteins. There is no gender bias; however, the number of autoantibodies increase with age, plateauing around adolescence. We use a bioinformatics pipeline to determine possible molecular-mimicry peptides that can contribute to the elicitation of these common autoantibodies. There is enrichment of intrinsic properties of proteins like hydrophilicity, basicity, aromaticity, and flexibility for common autoantigens. Subcellular localization and tissue-expression analysis reveal that several common autoantigens are sequestered from the circulating autoantibodies.

Shome et al. performed a meta-analysis to discover the common autoantibodies found in healthy individuals. These common autoantibodies appear and increase during youth and plateau at adolescence. Bioinformatics techniques demonstrate the potential role of molecular mimicry in their production as well as several common intrinsic biochemical properties.

Anti-POSTN and Anti-TIMP1 Autoantibodies as Diagnostic Markers in Esophageal Squamous Cell Carcinoma

Esophageal cancer is one of the most commonly diagnosed malignant gastrointestinal tumors. The aim of the study was to explore the diagnostic values of anti-POSTN and anti-TIMP1 autoantibodies in esophageal squamous cell carcinoma (ESCC). Differentially expressed genes (DEGs) associated with esophageal cancer were screened out by the LIMMA method in the Gene Expression Profiling Interactive Analysis (GEPIA) platform. Search Tool for the Retrieval of Interacting Genes (STRING) was used to construct the protein-protein interaction (PPI) based on highly DEGs. The candidate hub genes were the intersection genes calculated based on degree and Maximal Clique Centrality (MCC) algorithms via Cytoscape. A total of 370 participants including 185 ESCC patients and 185 matched normal controls were enrolled in enzyme-linked immunosorbent assay (ELISA) to detect the expression levels of autoantibodies corresponding to POSTN and TIMP1 proteins. A total of 375 DEGs with high expression were obtained in esophageal cancer. A total of 20 hub genes were acquired using the cytoHubba plugin by degree and MCC algorithms. The expression levels of anti-POSTN and anti-TIMP1 autoantibodies were higher in the sera of ESCC patients (p < 0.05). Anti-POSTN autoantibody can diagnose ESCC patients with an AUC of 0.638 at the specificity of 90.27% and sensitivity of 27.57%, and anti-TIMP1 autoantibody can diagnose ESCC patients with an AUC of 0.585 at the specificity of 90.27% and sensitivity of 20.54% (p < 0.05). In addition, anti-POSTN and anti-TIMP1 autoantibodies can distinguish ESCC patients from normal controls in most clinical subgroups (p < 0.05). In conclusion, anti-POSTN and anti-TIMP1 autoantibodies may be considered the potential biomarkers in the clinical diagnosis of ESCC.

Temporal reproducibility of IgG and IgM autoantibodies in serum from healthy women

Autoantibodies are present in healthy individuals and altered in chronic diseases. We used repeated samples collected from participants in the NYU Women's Health Study to assess autoantibody reproducibility and repertoire stability over a one-year period using the HuProt array. We included two samples collected one year apart from each of 46 healthy women (92 samples). We also included eight blinded replicate samples to assess laboratory reproducibility. A total of 21,211 IgG and IgM autoantibodies were interrogated. Of those, 86% of IgG (n = 18,303) and 34% of IgM (n = 7,242) autoantibodies showed adequate lab reproducibility (coefficient of variation [CV] < 20%). Intraclass correlation coefficients (ICCs) were estimated to assess temporal reproducibility. A high proportion of both IgG and IgM autoantibodies with CV < 20% (76% and 98%, respectively) showed excellent temporal reproducibility (ICC > 0.8). Temporal reproducibility was lower after using quantile normalization suggesting that batch variability was not an important source of error, and that normalization removed some informative biological information. To our knowledge this study is the largest in terms of sample size and autoantibody numbers to assess autoantibody reproducibility in healthy women. The results suggest that for many autoantibodies a single measurement may be used to rank individuals in studies of autoantibodies as etiologic markers of disease.

UHMK1 Is a Novel Marker for Personalized Prediction of Pancreatic Cancer Prognosis

Pancreatic ductal adenocarcinoma (PDAC) is among the leading causes of cancer mortality, and new therapeutic options are urgently needed. Long noncoding RNA H19 (H19) is known to promote PDAC progression, but the downstream genes of H19 are largely unknown. Five PDAC cell lines, nonmalignant pancreatic cells, TCGA, GEO-derived pancreatic tissues (malignant, n=413; nonmalignant, n=234), a pancreatic tissue array (n=96), and pancreatic tissues from our clinic (malignant, n=20; nonmalignant, n=20) were examined by a gene array, RT-qPCR, Western blotting, MTT, colony formation, wound-healing, siRNA-mediated gene silencing, bioinformatics, xenotransplantation, and immunohistochemistry assays. The cell cycle inhibitor, UHMK1, was identified to have the strongest correlation with H19. UHMK1 expression was enhanced in PDAC, and high UHMK1 expression correlated with tumor stage, and lower overall survival. siRNA-mediated UHMK1 downregulation inhibited progression signaling. siRNA-mediated downregulation of H19 or UHMK1 inhibited tumor proliferation and xenograft growth. Based on the correlation between UHMK1 expression and clinical parameters, we developed a nomogram that reliably predicts patient prognosis and overall survival. Together, we characterized UHMK1 as an H19-induced oncogene and verified it as a novel PDAC prognostic marker for overall survival.

A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody-antigen system

Hepatocellular carcinoma (HCC) is a malignancy with a dismal survival rate. The novel autoantibodies panel may provide new insights for the diagnosis of HCC. Biomarkers screened by two methods (bioinformatics and the antigen‐antibody system) were taken as candidate tumor‐associated antigens (TAAs). Enzyme‐linked immunosorbent assay was used to detect the corresponding autoantibodies in 888 samples of verification and validation cohorts. The verification cohort was used to verify the autoantibodies. Samples in the validation cohort were randomly divided into a train set and a test set with the ratio of 6:4. A diagnostic model was established by support vector machines within the train set. The test set further verified the model. Eleven TAAs were selected (AAGAB, C17orf75, CDC37L1, DUSP6, EID3, PDIA2, RGS20, PCNA, TAF7L, TBC1D13, and ZIC2). The titer of six autoantibodies (PCNA, AAGAB, CDC37L1, TAF7L, DUSP6, and ZIC2) had a significant difference in any of the pairwise comparisons among the HCC, liver cirrhosis, and normal control groups. The titer of these autoantibodies had an increasing tendency. Finally, an optimum diagnostic model was constructed with the six autoantibodies. The AUCs were 0.826 in the train set and 0.773 in the test set. The area under the curve (AUC) of this panel for diagnosing early HCC was 0.889. The diagnostic ability of the panel reduced with the progress of HCC. The positive rate of the panel in diagnosing alpha‐fetoprotein (AFP)‐negative patients was 75.6%. For early HCC, the sensitivity of the combination of AFP with the panel was 90.9% and superior to 53.2% of AFP alone. The novel immunodiagnosis panel combining AFP may be a new approach for the diagnosis of HCC, especially for early‐HCC cases.

Identification of Tumor Antigens in Ovarian Cancers Using Local and Circulating Tumor-Specific Antibodies

Ovarian cancers include several disease subtypes and patients often present with advanced metastatic disease and a poor prognosis. New biomarkers for early diagnosis and targeted therapy are, therefore, urgently required. This study uses antibodies produced locally in tumor-draining lymph nodes (ASC probes) of individual ovarian cancer patients to screen two separate protein microarray platforms and identify cognate tumor antigens. The resulting antigen profiles were unique for each individual cancer patient and were used to generate a 50-antigen custom microarray. Serum from a separate cohort of ovarian cancer patients encompassing four disease subtypes was screened on the custom array and we identified 28.8% of all ovarian cancers, with a higher sensitivity for mucinous (50.0%) and serous (40.0%) subtypes. Combining local and circulating antibodies with high-density protein microarrays can identify novel, patient-specific tumor-associated antigens that may have diagnostic, prognostic or therapeutic uses in ovarian cancer.

Mapping Epitopes Recognised by Autoantibodies Shows Potential for the Diagnosis of High-Grade Serous Ovarian Cancer and Monitoring Response to Therapy for This Malignancy

Simple Summary

Most women are diagnosed with high-grade serous ovarian cancer (HGSOC) at stage III, when the cancer has already spread, contributing to poor survival outcomes. However, while earlier diagnosis increases survival rates, there is a lack of early diagnosis biomarkers. Previously, autoantibodies specific for phosphorylated heat shock factor 1 (HSF1-PO4) were suggested as a potential diagnostic biomarker for early-stage HGSOC. In the present study, specific regions within HSF1 were identified, tested and confirmed as useful biomarkers, with comparable diagnostic potential to the full protein, across two separate clinical cohorts. Additionally, antibody responses to HSF1-PO4 and the corresponding peptides were found to increase following a round of standard first-line chemotherapy. Together, our data suggest that the identified short peptide sequences could be used as practical alternatives to support early diagnosis or monitor responses to chemotherapy.

Abstract

Autoantibodies recognising phosphorylated heat shock factor 1 (HSF1-PO4) protein are suggested as potential new diagnostic biomarkers for early-stage high-grade serous ovarian cancer (HGSOC). We predicted in silico B-cell epitopes in human and murine HSF1. Three epitope regions were synthesised as peptides. Circulating immunoglobulin A (cIgA) against the predicted peptide epitopes or HSF1-PO4 was measured using ELISA, across two small human clinical trials of HGSOC patients at diagnosis. To determine whether chemotherapy would promote changes in reactivity to either HSF1-PO4 or the HSF-1 peptide epitopes, IgA responses were further assessed in a sample of patients after a full cycle of chemotherapy. Anti-HSF1-PO4 responses correlated with antibody responses to the three selected epitope regions, regardless of phosphorylation, with substantial cross-recognition of the corresponding human and murine peptide epitope variants. Assessing reactivity to individual peptide epitopes, compared to HSF1-PO4, improved assay sensitivity. IgA responses to HSF1-PO4 further increased significantly post treatment, indicating that HSF1-PO4 is a target for immunity in response to chemotherapy. Although performed in a small cohort, these results offer potential insights into the interplay between autoimmunity and ovarian cancer and offer new peptide biomarkers for early-stage HGSOC diagnosis, to monitor responses to chemotherapy, and widely for pre-clinical HGSOC research.

Comparative analysis of triple-negative breast cancer transcriptomics of Kenyan, African American and Caucasian Women

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The current study determined the molecular fingerprints of TNBCs of women from kenya (KE) and compared them with those of African–American (AA) and Caucasian (CA) women.

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RNA sequencing analysis highlights the role of molecular alterations in TNBCs and the potential benefit of targeting pathways in this disease for the KE population as compared to AAs and CAs.

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The dysregulated genes and signaling pathways could contributes to the aggressive phenotypes of TNBCs of KE women.

Purpose

: Triple-negative breast cancer (TNBC) patients of various ethnic groups often have discrete clinical presentations and outcomes. Women of African descent have a disproportionately higher chance of developing TNBCs. The aim of the current study was to establish the transcriptome of TNBCs from Kenyan (KE) women of Bantu origin and compare it to those TNBCs of African-Americans (AA) and Caucasians (CA) for identifying KE TNBC-specific molecular determinants of cancer progression and potential biomarkers of clinical outcomes.

Patients and Methods

: Pathology-confirmed TNBC tissues from Kenyan women of Bantu origin (n = 15) and age and stage range matched AA (n = 19) and CA (n = 23) TNBCs of patients from Alabama were included in this study. RNA was isolated from paraffin-embedded tissues, and expression was analyzed by RNA sequencing.

Results

: At clinical presentation, young KE TNBC patients have tumors of higher stages. Differential expression analysis identified 160 up-regulated and 178 down-regulated genes in KE TNBCs compared to AA and CA TNBCs. Validation analyses of the TCGA breast cancer data identified 45 KE TNBC-specific genes that are involved in the apoptosis (ACTC1, ERCC6 and CD14), cell proliferation (UHRF2, KDM4C, UHMK1, KCNH5, KRT18, CSF1R and S100A13), and Wnt signaling (BCL9L) pathways.

Conclusions

: In this study, we identified biomarkers that are specific for KE TNBC patients of Bantu origin. Further study with a larger sample size of matched tumors could confirm our findings. If biologically confirmed, these molecular determinants could have clinical and biological implications and serve as targets for development of personalized therapeutics for KE TNBC patients.

Anti-Cancer Auto-Antibodies: Roles, Applications and Open Issues

Auto-antibodies are classically associated with autoimmune diseases, where they are an integral part of diagnostic panels. However, recent evidence is accumulating on the presence of auto-antibodies against single or selected panels of auto-antigens in many types of cancer. Auto-antibodies might initially represent an epiphenomenon derived from the inflammatory environment induced by the tumor. However, their effect on tumor evolution can be crucial, as is discussed in this paper. It has been demonstrated that some of these auto-antibodies can be used for early detection and cancer staging, as well as for monitoring of cancer regression during treatment and follow up. Interestingly, certain auto-antibodies were found to promote cancer progression and metastasis, while others contribute to the body's defense against it. Moreover, auto-antibodies are of a polyclonal nature, which means that often several antibodies are involved in the response to a single tumor antigen. Dissection of these antibody specificities is now possible, allowing their identification at the genetic, structural, and epitope levels. In this review, we report the evidence available on the presence of auto-antibodies in the main cancer types and discuss some of the open issues that still need to be addressed by the research community.

Using protein microarray to identify and evaluate autoantibodies to tumor-associated antigens in ovarian cancer

The aim of this study was to develop a noninvasive serological diagnostic approach in identifying and evaluating a panel of candidate autoantibodies to tumor‐associated antigens (TAAs) based on protein microarray technology for early detection of ovarian cancer (OC). Protein microarray based on 154 proteins encoded by 138 cancer driver genes was used to screen candidate anti‐TAA autoantibodies in a discovery cohort containing 17 OC and 27 normal controls (NC). Indirect enzyme‐linked immunosorbent assay (ELISA) was used to detect the content of candidate anti‐TAA autoantibodies in sera from 140 subjects in the training cohort. Differential anti‐TAA autoantibodies were further validated in the validation cohort with 328 subjects. Subsequently, 112 sera from the patients with ovarian benign diseases with 104 OC sera and 104 NC sera together were recruited to identify the specificity of representative autoantibodies to OC among ovarian diseases. Five TAAs (GNAS, NPM1, FUBP1, p53, and KRAS) were screened out in the discovery phase, in which four of them presented higher levels in OC than controls (P < .05) in the training cohort, which was consistent with the result in the subsequent validation cohort. An optimized panel of three anti‐TAA (GNAS, p53, and NPM1) autoantibodies was identified to have relatively high sensitivity (51.2%), specificity (86.0%), and accuracy (68.6%), respectively. This panel can identify 51% of OC patients with CA125 negative. This study supports our assumption that anti‐TAA autoantibodies can be considered as potential diagnostic biomarkers for detection of OC; especially a panel of three anti‐TAA autoantibodies could be a good tool in immunodiagnosis of OC.

Upfront debulking surgery for high-grade serous ovarian carcinoma: current evidence

High-grade serous ovarian carcinoma (HGSOC) is a leading cause of mortality among women worldwide. Currently, there is no clear consensus over the regime these patients should receive. The main two options are upfront debulking surgery with adjuvant chemotherapy or neoadjuvant chemotherapy followed by interval debulking surgery (IDS). The former approach is proposed to be accompanied by lower chemoresistance rates but could lead to severe surgical comorbidities and lower quality of life (QoL). Optimizing patient’s selection for upfront debulking surgery might offer higher progression-free and overall survival rates. Further studies need to be conducted in order to elucidate the predictive factors, which are favorable for patients undergoing upfront debulking surgery in cases of high-grade serous ovarian cancer.

Evaluation of paraneoplastic antigens reveals TRIM21 autoantibodies as biomarker for early detection of ovarian cancer in combination with autoantibodies to NY-ESO-1 and TP53

BACKGROUND

The majority of ovarian cancer cases are diagnosed at an advanced stage with poor prognosis. This study evaluates autoantibodies against tumor antigens to identify candidate biomarkers for early detection of ovarian cancer in women at increased risk.

OBJECTIVE

To assess the immunoreactivity of paraneoplastic antigens and tumor associated antigens with high-grade serous ovarian cancer (HGSOC) samples.

METHODS

Five paraneoplastic antigens along with three tumor-associated antigens were evaluated with HGSOC patient serum samples. Validation screening was performed with n= 164 serum samples consisting of: 50 late stage HGSOC, 14 early stage HGSOC, 50 benign ovarian cyst, and 50 healthy control samples on ELISA and western blot. The four markers TRIM21, NY-ESO-1, TP53, and PAX8 were evaluated on a second validation serum set, n= 150.

RESULTS

TRIM21 achieved the highest sensitivity in the first validation screening of 33% with 100% specificity. Combining TRIM21 with NY-ESO-1, TP53, and PAX8 provided 67% sensitivity with 94% specificity, and 56% sensitivity at 98% specificity. These four markers resulted in 46% sensitivity with 98% specificity in the second validation cohort; TRIM21 achieved the highest individual sensitivity of 36%.

CONCLUSIONS

Autoantibodies to TRIM21, NY-ESO-1, and TP53 may complement CA125 in screening of women at genetic risk for ovarian cancer.

Protein anabolism is key to long-term survival in high-grade serous ovarian cancer

This study aimed to identify the biological processes associated with long-term survival in high-grade serous ovarian cancer (HGSOC). HGSOC cases obtained from The Cancer Genome Atlas Ovarian Cancer (TCGA-OV) database were divided into long-term survivors (LTS) and normal-term survivors (NTS) based on survival cutoffs defined by the HGSOC cohort in the SEER database. Differentially expressed genes (DEGs) were screened using the generalized linear modeling (GLM) method. Gene Ontology (GO) functional and KEGG pathway enrichment analyses were performed using DAVID Bioinformatics Resources. DEG-related protein-protein interactions (PPI) were extracted from the STRING database and hub genes were identified using CytoHubba in the Cytoscape program. In total, 157 DEGs, including 155 upregulated and 2 downregulated genes, were identified. Upregulated genes were statistically enriched in 80 GO terms and 11 KEGG pathways related to energy and substrate metabolism, such as protein absorption, digestion, and metabolism as well as signaling pathways, including chromatin silencing, regulation of ERK1 and ERK2 cascade, and regulation of MAPKKK. ALB and POMC were the common hub genes. These findings reveal that protein anabolism is crucial to long-term survival, regulated by activation of the MAPK/ERK signaling pathway and chromatin silencing. Comprehensive understanding of the molecular mechanisms via further exploration may contribute toward an effective treatment for ovarian cancer.

Identification of novel autoantibodies based on the protein chip encoded by cancer-driving genes in detection of esophageal squamous cell carcinoma

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAbs) and explore the optimal diagnosis model based on the protein chip for detecting esophageal squamous cell carcinoma (ESCC). The human protein chip based on cancer-driving genes was customized to discover candidate TAAbs. Enzyme-linked immunosorbent assay was applied to verify and validate the expression levels of candidate TAAbs in the training cohort (130 ESCC and 130 normal controls) and the validation cohort (125 ESCC and 125 normal controls). Logistic regression analysis was adopted to construct the diagnostic model based on the expression levels of autoantibodies with diagnostic value. Twelve candidate autoantibodies were identified based on the protein chip according to the corresponding statistical methods. In both the training cohort and validation cohort, the expression levels of 10 TAAbs (GNA11, PTEN, P53, SRSF2, GNAS, ACVR1B, CASP8, DAXX, PDGFRA, and MEN1) in ESCC patients were higher than that in normal controls. The panel consisting of GNA11, ACVR1B and P53 demonstrated favorable diagnostic power. The sensitivity, specificity and accuracy of the model in the train cohort and the validation cohort were 71.5%, 93.8%, 79.6% and 77.6%, 81.6%, 70.8%, respectively. In either cohort, there was no correlation between positive rate of the autoantibody panel and clinicopathologic features for ESCC patients. Protein chip technology is an effective method to identify novel TAAbs, and the panel of 3 TAAbs (GNA11, ACVR1B, and P53) is promising for distinguishing ESCC patients from normal individuals.

Serological Biomarkers for Early Detection of Hepatocellular Carcinoma: A Focus on Autoantibodies against Tumor-Associated Antigens Encoded by Cancer Driver Genes

Substantial evidence manifests the occurrence of autoantibodies to tumor-associated antigens (TAAs) in the early stage of hepatocellular carcinoma (HCC), and previous studies have mainly focused on known TAAs. In the present study, protein microarrays based on cancer driver genes were customized to screen TAAs. Subsequently, autoantibodies against selected TAAs in sera were tested by enzyme-linked immunosorbent assays (ELISA) in 1175 subjects of three independent datasets (verification dataset, training dataset, and validation dataset). The verification dataset was used to verify the results from the microarrays. A logistic regression model was constructed within the training dataset; seven TAAs were included in the model and yielded an area under the receiver operating characteristic curve (AUC) of 0.831. The validation dataset further evaluated the model, exhibiting an AUC of 0.789. Remarkably, as the aggravation of HCC increased, the prediction probability (PP) of the model tended to decrease, the trend of which was contrary to alpha-fetoprotein (AFP). For AFP-negative HCC patients, the positive rate of this model reached 67.3% in the training dataset and 50.9% in the validation dataset. Screening TAAs with protein microarrays based on cancer driver genes is the latest, fast, and effective method for finding indicators of HCC. The identified anti-TAA autoantibodies can be potential biomarkers in the early detection of HCC.

Transcriptomic analysis of female and male gonads in juvenile snakeskin gourami (Trichopodus pectoralis)

The snakeskin gourami (Trichopodus pectoralis) exhibits sexual dimorphism, particularly in body size. Since the snakeskin gourami is usually marketed during sexual maturation, the sexual size dimorphism has become an economically important trait. Sex-biased gene expression plays a key role in phenotypic sexual dimorphism. Therefore, using high-throughput RNA sequencing (RNA-seq) technology, we aimed to explore the differentially expressed genes (DEGs) in ovary and testis during sex differentiation in juvenile snakeskin gourami. Our results revealed a number of DEGs were demonstrated to be overexpressed in ovary (11,625 unigenes) and testis (16,120 unigenes), and the top 10 female-biased (rdh7, dnajc25, ap1s3, zp4, polb, parp12, trim39, gucy2g, rtbs, and fdxr) and male-biased (vamp3, nbl1, dnah2, ccdc11, nr2e3, spats1, pih1d2, tekt3, fbxo36, and mybl2) DEGs were suggested to be mainly associated with ovary and testis differentiation, respectively. Additionally, using real-time reverse transcription polymerase chain reaction (qRT-PCR), validation of the differential expression of 21 genes that were previously shown to be related to gonad development was performed (ar, bHLH, cyp19a1, daz, dead-end, esrb, esrrg, gnrhr, gpa, gsg1l, hsd17B, mospd1, nanos-1, nanos-2, p53, piwi-1, piwi-2, rerg, rps6ka, tgf-beta, and VgR). The results showed a significantly positive correlation (0.84; P < 0.001) between the results of RNA-seq and qRT-PCR. Therefore, RNA-seq analysis in our study identified global genes that were associated with ovary and testis differentiation in the juvenile phase of the snakeskin gourami. Our findings provide valuable transcriptomic bioinformation for further investigation of reproductive biology and applications of sex manipulation.

UHMK1 promotes gastric cancer progression through reprogramming nucleotide metabolism

UHMK1 is a nuclear serine/threonine kinase recently implicated in carcinogenesis. However, the functions and action mechanisms of UHMK1 in the pathogenesis of human gastric cancer (GC) are unclear. Here, we observed that UHMK1 was markedly upregulated in GC. UHMK1 silencing strongly inhibited GC aggressiveness. Interestingly, UHMK1-induced GC progression was mediated primarily via enhancing de novo purine synthesis because inhibiting purine synthesis reversed the effects of UHMK1 overexpression. Mechanistically, UHMK1 activated ATF4, an important transcription factor in nucleotide synthesis, by phosphorylating NCOA3 at Ser (S) 1062 and Thr (T) 1067. This event significantly enhanced the binding of NCOA3 to ATF4 and the expression of purine metabolism-associated target genes. Conversely, deficient phosphorylation of NCOA3 at S1062/T1067 significantly abrogated the function of UHMK1 in GC development. Clinically, Helicobacter pylori and GC-associated UHMK1 mutation induced NCOA3-S1062/T1067 phosphorylation and enhanced the activity of ATF4 and UHMK1. Importantly, the level of UHMK1 was significantly correlated with the level of phospho-NCOA3 (S1062/T1067) in human GC specimens. Collectively, these results show that the UHMK1-activated de novo purine synthesis pathway significantly promotes GC development.

Integration of IgA and IgG Autoantigens Improves Performance of Biomarker Panels for Early Diagnosis of Lung Cancer

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. In our previous study, we surveyed both IgG and IgM-bound serological biomarkers and validated a panel of IgG-bound autoantigens for early LC diagnosis with 50% sensitivity at 90% specificity. To further improve the performance of these serological biomarkers, we surveyed HuProt arrays, comprised of 20,240 human proteins, for IgA-bound autoantigens because IgAs are a major immunoglobulin isotype in the lung. Integrating with IgG-bound autoantigens, we discovered and validated a combined biomarker panel using ELISA-format tests. Specifically, in Phase I, we obtained IgA-based autoimmune profiles of 69 early stage LC patients, 30 healthy subjects and 25 patients with lung benign lesions (LBL) on HuProt arrays and identified 28 proteins as candidate autoantigens that were significantly associated with early stage LC. In Phase II, we re-purified the autoantigens and converted them into an ELISA-format testing to profile an additional large cohort, comprised of 136 early stage LC patients, 58 healthy individuals, and 29 LBL patients. Integration of IgG autoimmune profiles allowed us to identify and validate a biomarker panel of three IgA autoantigens (i.e. BCL7A, and TRIM33 and MTERF4) and three IgG autoantigens (i.e. CTAG1A, DDX4 and MAGEC2) for diagnosis of early stage LC with 73.5% sensitivity at >85% specificity. In Phase III, the performance of this biomarker panel was confirmed with an independent cohort, comprised of 88 early stage LC patients, 18 LBL patients, and 36 healthy subjects. Finally, a blind test on 178 serum samples was conducted to confirm the performance of the biomarker panel. In summary, this study demonstrates for the first time that an integrated panel of IgA/IgG autoantigens can serve as valuable biomarkers to further improve the performance of early diagnosis of LC.

Proteome Profiling Uncovers an Autoimmune Response Signature That Reflects Ovarian Cancer Pathogenesis

Harnessing the immune response to tumor antigens in the form of autoantibodies, which occurs early during tumor development, has relevance to the detection of cancer at early stages. We conducted an initial screen of antigens associated with an autoantibody response in serous ovarian cancer using recombinant protein arrays. The top 25 recombinants that exhibited increased reactivity with cases compared to controls revealed TP53 and MYC, which are ovarian cancer driver genes, as major network nodes. A mass spectrometry based independent analysis of circulating immunoglobulin (Ig)-bound proteins in ovarian cancer and of ovarian cancer cell surface MHC-II bound peptides also revealed a TP53–MYC related network of antigens. Our findings support the occurrence of a humoral immune response to antigens linked to ovarian cancer driver genes that may have utility for early detection applications.

Discovery of an autoantibody signature for the early diagnosis of knee osteoarthritis: data from the Osteoarthritis Initiative

Objective

To find autoantibodies (AAbs) in serum that could be useful to predict incidence of radiographic knee osteoarthritis (KOA).

Design

A Nucleic-acid Programmable Protein Arrays (NAPPA) platform was used to screen AAbs against 2125 human proteins in sera at baseline from participants free of radiographic KOA belonging to the incidence and non-exposed subcohorts of the Osteoarthritis Initiative (OAI) who developed or not, radiographic KOA during a follow-up period of 96 months. NAPPA-ELISA were performed to analyse reactivity against methionine adenosyltransferase two beta (MAT2β) and verify the results in 327 participants from the same subcohorts. The association of MAT2β-AAb levels with KOA incidence was assessed by combining several robust biostatistics analysis (logistic regression, Receiver Operating Characteristic and Kaplan-Meier curves). The proposed prognostic model was replicated in samples from the progression subcohort of the OAI.

Results

In the screening phase, six AAbs were found significantly different at baseline in samples from incident compared with non-incident participants. In the verification phase, high levels of MAT2β-AAb were significantly associated with the future incidence of KOA and with an earlier development of the disease. The incorporation of this AAb in a clinical model for the prognosis of incident radiographic KOA significantly improved the identification/classification of patients who will develop the disorder. The usefulness of the model to predict radiographic KOA was confirmed on a different OAI subcohort.

Conclusions

The measurement of AAbs against MAT2β in serum might be highly useful to improve the prediction of OA development, and also to estimate the time to incidence.

MGMT autoantibodies as a potential prediction of recurrence and treatment response biomarker for glioma patients

Background

Cancer‐specific autoantibodies found in serum of cancer patients have been characterized as potential predictors of the high risk of recurrence and treatment response. The objective of this study is to investigate the clinical utility of serum O‐6‐methylguanine‐DNA methyltransferase (MGMT) autoantibodies as novel biomarkers for prediction of recurrence and treatment response for glioma through MGMT peptides microarray.

Methods

A total of 201 serum samples of glioma patients with various WHO grade and 311 serum samples of healthy donors were examined for the detection of MGMT autoantibodies by peptides microarray. The clinical value of MGMT autoantibodies was studied through univariable and multivariable analyses.

Results

Autoantibodies to MGMT peptides were detected in sera from glioma patients and five highly responsive autoantibodies to peptides were identified in the glioma group. The positive rate of MGMT autoantibody to 20 peptides in glioma groups is compared with healthy individuals, the positive rate of MGMT‐02 (45%), MGMT‐04 (27%), MGMT‐07 (21%), MGMT‐10 (13%), and MGMT‐18 (24%) were significantly elevated in patients with glioma. MGMT autoantibody and its protein expression exhibited a significant correlation. The levels of MGMT autoantibodies decreased on the 30th day after operation, reaching preoperative levels, similar to those when tumor recurrence developed. Univariable and multivariable analyses revealed that the only preoperative autoantibodies to MGMT‐02 peptide were independently correlated with recurrence‐free survival. Preoperative seropositive patients were more likely than seronegative patients to have shorter recurrence times and to be resistant to chemoradiotherapy or chemotherapy with temozolomide.

Conclusion

Monitoring the levels of preoperative serum autoantibodies to MGMT‐02 peptide was useful for predicting patients at high risk of recurrence and treatment response.

A decade of Nucleic Acid Programmable Protein Arrays (NAPPA) availability: News, actors, progress, prospects and access

Understanding the dynamic of the proteome is a critical challenge because it requires high sensitive methodologies in high-throughput formats in order to decipher its modifications and complexity. While molecular biology provides relevant information about cell physiology that may be reflected in post-translational changes, High-Throughput (HT) experimental proteomic techniques are essential to provide valuable functional information of the proteins, peptides and the interconnections between them. Hence, many methodological developments and innovations have been reported during the last decade. To study more dynamic protein networks and fine interactions, Nucleic Acid Programmable Protein Arrays (NAPPA) was introduced a decade ago. The tool is rapidly maturing and serving as a gateway to characterize biological systems and diseases thanks primarily to its accuracy, reproducibility, throughput and flexibility. Currently, NAPPA technology has proved successful in several research areas adding valuable information towards innovative diagnostic and therapeutic applications. Here, the basic and latest advances within this modern technology in basic, translational research are reviewed, in addition to presenting its exciting new directions. Our final goal is to encourage more scientists/researchers to incorporate this method, which can help to remove bottlenecks in their particular research or biomedical projects. SIGNIFICANCE: Nucleic Acid Programmable Protein Arrays (NAPPA) is becoming an essential tool for functional proteomics and protein-protein interaction studies. The technology impacts decisively on projects aiming massive screenings and the latest innovations like the multiplexing capability or printing consistency make this a promising method to be integrated in novel and combinatorial proteomic approaches.

Tumor-associated autoantibodies as early detection markers for ovarian cancer? A prospective evaluation

Immuno-proteomic screening has identified several tumor-associated autoantibodies (AAb) that may have diagnostic capacity for invasive epithelial ovarian cancer, with AAbs to P53 proteins and cancer-testis antigens (CTAGs) as prominent examples. However, the early detection potential of these AAbs has been insufficiently explored in prospective studies. We performed ELISA measurements of AAbs to CTAG1A, CTAG2, P53 and NUDT11 proteins, for 194 patients with ovarian cancer and 705 matched controls from the European EPIC cohort, using serum samples collected up to 36 months prior to diagnosis under usual care. CA125 was measured using electrochemo-luminiscence. Diagnostic discrimination statistics were calculated by strata of lead-time between blood collection and diagnosis. With lead times ≤6 months, ovarian cancer detection sensitivity at 0.98 specificity (SE98) varied from 0.19 [95% CI 0.08-0.40] for CTAG1A, CTAG2 and NUDT1 to 0.23 [0.10-0.44] for P53 (0.33 [0.11-0.68] for high-grade serous tumors). However, at longer lead-times, the ability of these AAb markers to distinguish future ovarian cancer cases from controls declined rapidly; at lead times >1 year, SE98 estimates were close to zero (all invasive cases, range: 0.01-0.11). Compared to CA125 alone, combined logistic regression scores of AAbs and CA125 did not improve detection sensitivity at equal level of specificity. The added value of these selected AAbs as markers for ovarian cancer beyond CA125 for early detection is therefore limited.

Using a panel of multiple tumor-associated antigens to enhance autoantibody detection for immunodiagnosis of gastric cancer

Autoantibodies against tumor-associated antigens (TAAs) are attractive non-invasive biomarkers for detection of cancer due to their inherently stable in serum. Serum autoantibodies against 9 TAAs from gastric cancer (GC) patients and healthy controls were measured by enzyme-linked immunosorbent assay (ELISA). A logistic regression model predicting the risk of being diagnosed with GC in the training cohort (n = 558) was generated and then validated in an independent cohort (n = 372). Area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance. Finally, an optimal prediction model with 6 TAAs (p62, c-Myc, NPM1, 14-3-3ξ, MDM2 and p16) showed a great diagnostic performance of GC with AUC of 0.841 in the training cohort and 0.856 in the validation cohort. The proportion of subjects being correctly defined were 78.49% in the training cohort and 81.99% in the validation cohort. This prediction model could also differentiate early-stage (stage I-II) GC patients from healthy controls with sensitivity/specificity of 76.60%/72.34% and 80.56%/79.17% in the training and validation cohort, respectively, and the overall sensitivity/specificity for early-stage GC were 78.92%/74.70% when being combined with two cohorts. This prediction model presented no significant difference for the diagnostic accuracy between early-stage and late-stage (stage III - IV) GC patients. The model with 6 TAAs showed a high diagnostic performance for GC detection, particularly for early-stage GC. This study further supported the hypothesis that a customized array of multiple TAAs was able to enhance autoantibody detection in the immunodiagnosis of GC.

Preoperative Anti-Class III β-Tubulin Antibodies As Relevant Clinical Biomarkers in Ovarian Cancer

Class III β-tubulin (TUBB3) overexpression in ovarian cancer (OC) associates with poor prognosis. We investigated whether TUBB3 overexpression elicited anti-TUBB3 antibody production in OC patients and whether these antibodies may have diagnostic and prognostic impact. The presence of serum anti-TUBB3 antibodies was investigated in 49 untreated OC patients and 44 healthy individuals by an in-house developed ELISA that used recombinant TUBB3 as the antigen. Receiver operating characteristic (ROC) curves were generated to assess the diagnostic accuracy of the assay. Anti-TUBB3 antibodies discriminated OC patients and healthy individuals with excellent sensitivity and specificity (91.8% and 90.9%, respectively). In multivariate analysis, anti-TUBB3 antibody level emerged as an independent prognostic factor for progression free and overall survival. The ELISA was then optimized using a biotin-labeled TUBB3 C-terminal peptide_424-450 instead of recombinant TUBB3 as the antigen and streptavidin-coated plates. The diagnostic role of the anti-TUBB3 antibodies was studied in an independent series of 99 OC patients and 80 gynecological benign disease patients. ROC-curve analysis showed a valuable diagnostic potential for serum anti-TUBB3 antibodies to identify OC patients with higher sensitivity and specificity (95.3% and 97.6%, respectively). Overall, our results provide evidence that preoperative anti-TUBB3 antibody level is a promising diagnostic and prognostic biomarker for the management of OC patients.

A Combinatorial Proteomic Biomarker Assay to Detect Ovarian Cancer in Women

Ovarian cancer is often fatal and incidence in the general population is low, underscoring the necessity (and the challenges) for advancements in screening and early detection. The goal of this study was to design a serum-based biomarker panel and corresponding multivariate algorithm that can be used to accurately detect ovarian cancer. A combinatorial protein biomarker assay (CPBA) that uses CA125, HE4, and 3 tumor-associated autoantibodies resulted in an area under the curve of 0.98. The CPBA Ov algorithm was trained using subjects who were suspected to have gynecological cancer and were scheduled for surgery. As a surgical rule-out test, the clinical performance achieves 100% sensitivity and 83.7% specificity. Although sample size (n = 60) is a limiting factor, the CPBA Ov algorithm performed better than either CA-125 alone or the Risk of Ovarian Malignancy Algorithm.

Biodegradable nanoparticles as theranostics of ovarian cancer: an overview

Objectives

Above 10 million people are suffering from cancers every year. As per American Cancer Society, more than 22 440 new cases and 14 080 deaths were reported from ovarian cancer yearly worldwide. This review explores the current status, challenges and future perspectives of tumour-targeted theranostic nanoparticles (NPs).

Key findings

Most of the ovarian malignancy cases are uncovered after the disease is in a difficult state due to poor screening techniques and non-specific symptoms. In this manner, forceful and fruitful treatment is required that will indicate insignificant lethal impacts to solid tissue. In the current research, stealth biodegradable NPs are produced as vehicles for imaging and treatment of ovarian cancer as the controlled and targeted delivery of chemotherapeutic as well as imaging agents. To enhance the dependability of the colloidal suspension as well as to increase their circulation lifetime, NPs are introduced by incorporating the functional poly(ethylene glycol) on their surface, which also provides a site to conjugation of focusing on agents to ovarian tissue.

Summary

Biodegradable theranostic NPs can be fabricated and surface engineered without any alteration in drug-loading capacity, safety and efficacy. These NPs have shown promising results in imaging as well as treatment of ovarian cancer.

Stage Dependence, Cell-Origin Independence, and Prognostic Capacity of Serum Glycan Fucosylation, β1-4 Branching, β1-6 Branching, and α2-6 Sialylation in Cancer

Glycans represent a promising but only marginally accessed source of cancer markers. We previously reported the development of a molecularly bottom-up approach to plasma and serum (P/S) glycomics based on glycan linkage analysis that captures features such as α2-6 sialylation, β1-6 branching, and core fucosylation as single analytical signals. Based on the behavior of P/S glycans established to date, we hypothesized that the alteration of P/S glycans observed in cancer would be independent of the tissue in which the tumor originated yet exhibit stage dependence that varied little between cancers classified on the basis of tumor origin. Herein, the diagnostic utility of this bottom-up approach as applied to lung cancer patients (n = 127 stage I; n = 20 stage II; n = 81 stage III; and n = 90 stage IV) as well as prostate (n = 40 stage II), serous ovarian (n = 59 stage III), and pancreatic cancer patients (n = 15 rapid autopsy) compared to certifiably healthy individuals (n = 30), nominally healthy individuals (n = 166), and risk-matched controls (n = 300) is reported. Diagnostic performance in lung cancer was stage-dependent, with markers for terminal (total) fucosylation, α2-6 sialylation, β1-4 branching, β1-6 branching, and outer-arm fucosylation most able to differentiate cases from controls. These markers behaved in a similar stage-dependent manner in other types of cancer as well. Notable differences between certifiably healthy individuals and case-matched controls were observed. These markers were not significantly elevated in liver fibrosis. Using a Cox proportional hazards regression model, the marker for α2-6 sialylation was found to predict both progression and survival in lung cancer patients after adjusting for age, gender, smoking status, and stage. The potential mechanistic role of aberrant P/S glycans in cancer progression is discussed.

The U2AF homology motif kinase 1 (UHMK1) is upregulated upon hematopoietic cell differentiation

UHMK1 (KIS) is a nuclear serine/threonine kinase that possesses a U2AF homology motif and phosphorylates and regulates the activity of the splicing factors SF1 and SF3b155. Mutations in these components of the spliceosome machinery have been recently implicated in leukemogenesis. The fact that UHMK1 regulates these factors suggests that UHMK1 might be involved in RNA processing and perhaps leukemogenesis. Here we analyzed UHMK1 expression in normal hematopoietic and leukemic cells as well as its function in leukemia cell line. In the normal hematopoietic compartment, markedly higher levels of transcripts were observed in differentiated lymphocytes (CD4⁺, CD8⁺ and CD19⁺) compared to the progenitor enriched subpopulation (CD34⁺) or leukemia cell lines. UHMK1 expression was upregulated in megakaryocytic-, monocytic- and granulocytic-induced differentiation of established leukemia cell lines and in erythrocytic-induced differentiation of CD34⁺ cells. No aberrant expression was observed in patient samples of myelodysplastic syndrome (MDS), acute myeloid (AML) or lymphoblastic (ALL) leukemia. Nonetheless, in MDS patients, increased levels of UHMK1 expression positively impacted event free and overall survival. Lentivirus mediated UHMK1 knockdown did not affect proliferation, cell cycle progression, apoptosis or migration of U937 leukemia cells, although UHMK1 silencing strikingly increased clonogenicity of these cells. Thus, our results suggest that UHMK1 plays a role in hematopoietic cell differentiation and suppression of autonomous clonal growth of leukemia cells.

Advances in cell-free protein array methods

INTRODUCTION

Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

Autoantibodies against HSF1 and CCDC155 as Biomarkers of Early-Stage, High-Grade Serous Ovarian Cancer

Background: Tumor-directed circulating autoantibodies (AAb) are a well-established feature of many solid tumor types, and are often observed prior to clinical disease manifestation. As such, they may provide a good indicator of early disease development. We have conducted a pilot study to identify novel AAbs as markers of early-stage HGSOCs.Methods: A rare cohort of patients with early (FIGO stage Ia-c) HGSOCs for IgG, IgA, and IgM-mediated AAb reactivity using high-content protein arrays (containing 9,184 individual proteins). AAb reactivity against selected antigens was validated by ELISA in a second, independent cohort of individual patients.Results: A total of 184 antigens were differentially detected in early-stage HGSOC patients compared with all other patient groups assessed. Among the six most highly detected "early-stage" antigens, anti-IgA AAbs against HSF1 and anti-IgG AAbs CCDC155 (KASH5; nesprin 5) were significantly elevated in patients with early-stage malignancy. Receiver operating characteristic (ROC) analysis suggested that AAbs against HSF1 provided better detection of early-stage malignancy than CA125 alone. Combined measurement of anti-HSF1, anti-CCDC155, and CA125 also improved efficacy at higher sensitivity.Conclusions: The combined measurement of anti-HSF1, anti-CCDC155, and CA125 may be useful for early-stage HGSOC detection.Impact: This is the first study to specifically identify AAbs associated with early-stage HGSOC. The presence and high frequency of specific AAbs in early-stage cancer patients warrants a larger scale examination to define their value for early disease detection at primary diagnosis and/or recurrence. Cancer Epidemiol Biomarkers Prev; 27(2); 183-92. ©2017 AACR.

Systematic review: Tumor-associated antigen autoantibodies and ovarian cancer early detection

OBJECTIVES

Tumor-associated autoantibodies (AAbs), produced as an immune response to tumor-associated antigens (TAAs), are a novel pathway of early detection markers.

METHODS

We conducted a systematic review on AAbs and ovarian cancer to summarize the diagnostic performance of individual AAbs and AAb panels. A total of 29 studies including 85 AAbs were included; 27 of the studies were conducted in prevalent cases and cancer-free controls and 2 investigations included pre-diagnosis samples. The majority of studies were hypothesis-driven, evaluating AAbs to target TAAs; 10 studies used screening approaches such as serological expression cloning (SEREX) and nucleic acid-programmable protein arrays (NAPPA).

RESULTS

The highest sensitivities for individual AAbs were reported for RhoGDI-AAbs (89.5%) and TUBA1C-AAbs (89%); however, specificity levels were relatively low (80% and 75%, respectively). High sensitivities at high specificities were reported for HOXA7-AAbs for detection of moderately differentiated ovarian tumors (66.7% sensitivity at 100% specificity) and IL8-AAbs in stage I-II ovarian cancer (65.5% sensitivity at 98% specificity). A panel of 11 AAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) provided 45% sensitivity at 98% specificity for serous ovarian cancer, when at least 2 AAbs were above a threshold of 95% specificity. Twelve of the AAbs identified in this review were investigated in more than one study. Data on diagnostic discrimination by tumor histology and stage at diagnosis are sparse. Limited data suggest select AAb markers improve diagnostic discrimination when combined with markers such as CA125 and HE4.

CONCLUSIONS

AAbs for ovarian cancer early detection is an emerging area, and large-scale, prospective investigations considering histology and stage are required for discovery and validation. However, data to date suggests panels of AAbs may eventually reach sufficient diagnostic discrimination to allow earlier detection of disease as a complement to existing markers and transvaginal ultrasound.