Elevated serum antibodies against insulin-like growth factor-binding protein-2 allow detecting early-stage cancers: evidences from glioma and colorectal carcinoma studies

Positive regulators of T cell functions as predictors of prognosis and microenvironment characteristics of low-grade gliomas

Background

Low-grade gliomas (LGG) are one of the most prevalent types of brain cancers. The efficacy of immunotherapy in LGG is limited compared to other cancers. Immunosuppression in the tumor microenvironment (TME) of LGG is one of the main reasons for the low efficacy of immunotherapy. Recent studies have identified 33 positive regulators of T cell functions (TPRs) that play a critical role in promoting the proliferation, activity, and functions of multiple immunocytes. However, their role in the TME of LGG has not been investigated. This study aimed to construct a risk model based on these TPRs and to detect the significance of immunotypes in predicting LGG prognosis and immunotherapy efficacy.

Methods

A total of 688 LGGs and 202 normal brain tissues were extracted from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases. The NMF R package was used to identify TRP-related subtypes. The TPR prognostic model was established using the least absolute shrinkage and selection operator (LASSO) algorithm to predict the overall survival of LGG samples.

Results

The Subtype 2 patients had worse survival outcomes, suppressed immune function, and higher immune cell infiltration. A risk regression model consisting of 14 TPRs was established, and its performance was validated in CGGA325 cohorts. The low-risk group exhibited better overall survival, immune microenvironment, and immunotherapy response, as determined via the TIDE algorithm, indicating that increasing the level of immune infiltration can effectively improve the response to immunotherapy in the low-risk group. The risk score was determined to be an independent hazard factor (p<0.001) although other clinical features (age, sex, grade, IDH status, 1p19q codel status, MGMT status, and accepted radiotherapy) were considered. Lastly, high-risk groups in both cohorts revealed optimal drug responses to rapamycin, paclitaxel, JW-7-52-1, and bortezomib.

Conclusions

Our study identified two distinct TPR subtypes and built a TPR signature to elucidate the characteristics of T cell proliferation in LGG and its association with immune status and prognosis. These findings shed light on possible immunotherapeutic strategies for LGGs.

Spatial Transcriptomic Analysis of Ovarian Cancer Precursors Reveals Reactivation of IGFBP2 during Pathogenesis

Elucidating the earliest pathogenic steps in cancer development is fundamental to improving its early detection and prevention. Ovarian high-grade serous carcinoma (HGSC), a highly aggressive cancer, mostly originates from the fallopian tube epithelium through a precursor stage, serous tubal intraepithelial carcinoma (STIC). In this study, we performed spatial transcriptomic analysis to compare STICs, carcinoma, and their matched normal fallopian tube epithelium. Several differentially expressed genes in STICs and carcinomas were involved in cancer metabolism and detected in a larger independent transcriptomic dataset of ovarian HGSCs. Among these, insulin-like growth factor binding protein-2 (IGFBP2) was found to undergo DNA hypomethylation and to be increased at the protein level in STICs. Pyrosequencing revealed an association of IGFBP2 expression with the methylation state of its proximal enhancer, and 5-azacytidine treatment increased IGFBP2 expression. In postmenopausal fallopian tubes, where most STICs are detected, IGFBP2 immunoreactivity was detected in all 38 proliferatively active STICs but was undetectable in morphologically normal tubal epithelia, including those with TP53 mutations. In premenopausal fallopian tubes, IGFBP2 expression was limited to the secretory epithelium at the proliferative phase, and estradiol treatment increased IGFBP2 expression levels. IGFBP2 knockdown suppressed the growth of IGFBP2-expressing tubal epithelial cells via inactivation of the AKT pathway. Taken together, demethylation of the proximal enhancer of IGFBP2 drives tumor development by maintaining the increased IGFBP2 required for proliferation in an otherwise estrogen-deprived, proliferation-quiescent, and postmenopausal tubal microenvironment.

SIGNIFICANCE

Molecular studies of the earliest precursor lesions of ovarian cancer reveal a role of IGFBP2 in propelling tumor initiation, providing new insights into ovarian cancer development.

Antibodies as biomarkers for cancer risk: a systematic review

Increasing evidence has linked the humoral immune response with the development of various cancers. Therefore, there is growing interest in investigating the predictive value of antibodies to assess overall and tissue site-specific cancer risk. Given the large amount of antibody types and the broad scope of the search (i.e. cancer risk), the primary aim of this systematic review was to present an overview of the most researched antibodies (i.e. immunoglobulin (Ig) isotypes (IgG, IgM, IgA, and IgE), tumour and self-antigen-reactive antibodies, infection-related antibodies) in relation to overall and site-specific cancer risk. We identified various antibody types that have been associated with the risk of cancer. While no significant associations were found for IgM serum levels, studies found an inconsistent association among IgE, IgA, and IgG serum levels in relation to cancer risk. When evaluating antibodies against infectious agents, most studies reported a positive link with specific cancers known to be associated with the specific agent recognized by serum antibodies (i.e. helicobacter pylori and gastric cancer, hepatitis B virus and hepatocellular carcinoma, and human papillomavirus and cervical cancer). Several reports identified autoantibodies, as single biomarkers (e.g. anti-p53, anti-MUC1, and anti-CA125) but especially in panels of multiple autoantibodies, to have potential as diagnostic biomarkers for specific cancer types. Overall, there is emerging evidence associating certain antibodies to cancer risk, especially immunoglobulin isotypes, tumour-associated antigen-specific, and self-reactive antibodies. Further experimental studies are necessary to assess the efficacy of specific antibodies as markers for the early diagnosis of cancer.

Autoantibodies in the diagnosis, prognosis, and prediction of colorectal cancer

Colorectal cancer (CRC) is the second-most commonly diagnosed cancer worldwide. Early diagnosis improves prognosis and long-term outcomes. Several studies have found tumor-associated autoantibodies in CRC patients. We aimed to provide an overview on CRC-associated autoantibodies and their reported diagnostic, prognostic, and predictive performance when used singly or in combination. We systematically reviewed studies on CRC-related autoantibodies published till March 2018 and critically analyzed the role of these autoantibodies in CRC. In general, autoantibodies were of low sensitivity when tested individually and the diagnostic characteristics improved when tested in combination. Autoantibodies against CCD83, carcinoembryonic antigen, MAPKAPK3, RPH 3AL, SEC61b, and SPAG9 showed high sensitivity and specificity when tested alone. When tested in combination, autoantibodies against three antigens (PIM1, MAPKAPK3, and ACVR2B) showed high sensitivity and specificity. So far, most CRC-associated autoantibodies have been evaluated in single or in a small number of studies. In contrast, anti-p53 antibodies have been studied in a larger number of CRC studies, but, so far, none of them have high diagnostic characteristics. CRC-associated autoantibodies are detectable from the early stages of malignancy, pointing to their possible use in the early detection of CRC. Some studies suggest that CRC-associated autoantibodies may be a guide to prognosis in CRC.

Immunization with a Plasmid DNA Vaccine Encoding the N-Terminus of Insulin-like Growth Factor Binding Protein-2 in Advanced Ovarian Cancer Leads to High-level Type I Immune Responses

BACKGROUND

Cancer vaccines targeting nonmutated proteins elicit limited type I T-cell responses and can generate regulatory and type II T cells. Class II epitopes that selectively elicit type I or type II cytokines can be identified in nonmutated cancer-associated proteins. In mice, a T-helper I (Th1) selective insulin-like growth factor binding protein-2 (IGFBP-2) N-terminus vaccine generated high levels of IFNγ secreting T cells, no regulatory T cells, and significant antitumor activity. We conducted a phase I trial of T-helper 1 selective IGFBP-2 vaccination in patients with advanced ovarian cancer.

METHODS

Twenty-five patients were enrolled. The IGFBP-2 N-terminus plasmid-based vaccine was administered monthly for 3 months. Toxicity was graded by NCI criteria and antigen-specific T cells measured by IFNγ/IL10 ELISPOT. T-cell diversity and phenotype were assessed.

RESULTS

The vaccine was well tolerated, with 99% of adverse events graded 1 or 2, and generated high levels of IGFBP-2 IFNγ secreting T cells in 50% of patients. Both Tbet⁺ CD4 (P = 0.04) and CD8 (P = 0.007) T cells were significantly increased in immunized patients. There was no increase in GATA3⁺ CD4 or CD8, IGFBP-2 IL10 secreting T cells, or regulatory T cells. A significant increase in T-cell clonality occurred in immunized patients (P = 0.03, pre- vs. post-vaccine) and studies showed the majority of patients developed epitope spreading within IGFBP-2 and/or to other antigens. Vaccine nonresponders were more likely to have preexistent IGFBP-2 specific immunity and demonstrated defects in CD4 T cells, upregulation of PD-1, and downregulation of genes associated with T-cell activation, after immunization.

CONCLUSIONS

IGFBP-2 N-terminus Th1 selective vaccination safely induces type I T cells without evidence of regulatory responses.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Lower Gastrointestinal Cancers: A Systematic Review and Meta-Analysis

INTRODUCTION

Lower gastrointestinal (GI) cancers are a major cause of cancer deaths worldwide. Prognosis improves with earlier diagnosis, and non-invasive biomarkers have the potential to aid with early detection. Substantial investment has been made into the development of biomarkers; however, studies are often carried out in specialist settings and few have been evaluated for low-prevalence populations.

METHODS

We aimed to identify novel biomarkers for the detection of lower GI cancers that have the potential to be evaluated for use in primary care. MEDLINE, Embase, Emcare and Web of Science were systematically searched for studies published in English from January 2000 to October 2019. Reference lists of included studies were also assessed. Studies had to report on measures of diagnostic performance for biomarkers (single or in panels) used to detect colorectal or anal cancers. We included all designs and excluded studies with fewer than 50 cases/controls. Data were extracted from published studies on types of biomarkers, populations and outcomes. Narrative synthesis was used, and measures of specificity and sensitivity were meta-analysed where possible.

RESULTS

We identified 142 studies reporting on biomarkers for lower GI cancers, for 24,844 cases and 45,374 controls. A total of 378 unique biomarkers were identified. Heterogeneity of study design, population type and sample source precluded meta-analysis for all markers except methylated septin 9 (mSEPT9) and pyruvate kinase type tumour M2 (TuM2-PK). The estimated sensitivity and specificity of mSEPT9 was 80.6% (95% CI 76.6-84.0%) and 88.0% (95% CI 79.1-93.4%) respectively; TuM2-PK had an estimated sensitivity of 81.6% (95% CI 75.2-86.6%) and specificity of 80.1% (95% CI 76.7-83.0%).

CONCLUSION

Two novel biomarkers (mSEPT9 and TuM2-PK) were identified from the literature with potential for use in lower-prevalence populations. Further research is needed to validate these biomarkers in primary care for screening and assessment of symptomatic patients.

Prognostic Value of Circulating IGFBP2 and Related Autoantibodies in Children with Metastatic Rhabdomyosarcomas

Insulin-like growth factor-binding protein 2 (IGFBP2) is a tumor-associated protein measurable in patients’ biopsies and blood samples. Increased IGFBP2 expression correlates with tumor severity in rhabdomyosarcoma (RMS). Thus, we examined the plasmatic IGFBP2 levels in 114 RMS patients and 15 healthy controls by ELISA assay in order to evaluate its value as a plasma biomarker for RMS. Additionally, we looked for the presence of a humoral response against IGBFP2 protein measurable by the production of anti-IGFBP2 autoantibodies. We demonstrated that both circulating IGFBP2 protein and autoantibodies were significantly higher in RMS patients with respect to controls and their combination showed a better discriminative capacity. IGFBP2 protein identified metastatic patients with worse event-free survival, whereas both IGFBP2 and anti-IGFBP2 antibodies negatively correlated with overall survival. Our study suggests that IGFBP2 and anti-IGFBP2 antibodies are useful for diagnostic and prognostic purposes, mainly as independent negative prognostic markers in metastatic patients. This is the first study that reports a specific humoral response in RMS plasma samples and proves the value of blood-based biomarkers in improving risk assessment and outcome of metastatic RMS patients.

Autoantibodies as biomarkers for colorectal cancer: A systematic review, meta-analysis, and bioinformatics analysis

Colorectal cancer is a very common cancer worldwide. Serum tumor-associated autoantibodies (TAAbs), especially the anti-p53 autoantibody, may be promising biomarkers to detect early-stage colorectal cancer. This study aimed to identify all known autoantibodies and their value in colorectal cancer diagnosis, as well as exploring the underlying connections and mechanisms through a bioinformatics analysis. Databases were used to select available articles of TAAbs in colorectal cancer. In a meta-analysis of the anti-p53 autoantibody, the diagnostic odds ratio and area under the curve (AUC) of the summary receiver-operating characteristic (SROC) curve were calculated using Stata 12.0 and Meta-Disc 1.4. We identified 73 articles including 199 single autoantibodies and 42 multiple autoantibodies. The maximum value of Youden's index was 0.76, combining c-MYC, p53, cyclin B1, p62, Koc, IMP1, and survivin. The diagnostic odds ratio for anti-p53 autoantibody at all stages was 10.86 (95% CI 8.40, 14.06) with low heterogeneity (I² = 40.3%) and the AUC of the SROC curve was 0.82. For the anti-p53 autoantibody in early-stage colorectal cancer, the diagnostic odds ratio was 4.82 (95% CI 2.95, 7.87) with heterogeneity (I² = 7.9%) and the AUC of the SROC curve was 0.72. Eighty-seven autoantibodies were selected for bioinformatics analyses. We found that the most enriched functional terms and protein-protein interactions may relate to the mechanism of autoantibody generation. In summary, our study summarized the diagnostic value of TAAbs in colorectal cancer, either as single molecules or in combination. Bioinformatics analyses may be a new approach to explore the mechanism of autoantibody generation.

Identification of a five B cell-associated gene prognostic and predictive signature for advanced glioma patients harboring immunosuppressive subtype preference

High grade gliomas contribute to most brain tumor mortality. A few studies reported that the immune system affected glioma development, and immune biomarkers helped understand the disease and formulate effective immunotherapy for patients. Currently, no B lymphocyte-based prognostic signature was reported in gliomas. By applying 78 B cell lineage-specific genes, we conducted a whole-genome gene expression analysis in 782 high grade gliomas derived from three independent datasets by Cox regression analysis and risk score method for signature identification, and then used Gene Ontology, Gene Set Enrichment Analysis, and other statistical methods for functional annotations of the signature-defined differences. We developed a five B cell-associated gene signature for prognosis of high grade glioma patients, which is independent of clinicopathological and genetic features. The signature identified high risk patients suitable for chemoradiotherapy, whereas low risk patients should rule out chemotherapy with radiotherapy only. We found that tumors of TCGA Mesenchymal subtype and wild type IDH1 were preferentially stratified to the high risk group, which bore strong immunosuppressive microenvironment, while tumors of TCGA Proneural subtype and mutated IDH1 were significantly accumulated to the low risk group, which exhibited less immunosuppressive state. The five B cell-associated gene signature predicts poor survival of high risk patients bearing strong immunosuppression and helps select optimal therapeutic regimens for glioma patients.

Immune heterogeneity and clinicopathologic characterization of IGFBP2 in 2447 glioma samples

Glioblastoma is an immunosuppressive, deadly brain tumor. IGFBP2, a circulating biomarker for cancer diagnosis and a potential immunotherapeutic target, is attracting more and more attention from oncologists and clinicians. Thus, it is urgent to thoroughly investigate the immune biological process of IGFBP2 to understand tumor immune complexity and provide potential evidence for anti-IGFBP2 therapy. Through authoritative public databases, we enrolled a total of 2447 glioma samples with gene expression profiles. Then, the clinical characteristics and immunosuppressive status of IGFBP2 in the glioma samples were analyzed. Immunohistochemical staining detected the expression of immunosuppressive biomarkers. We found that IGFBP2 expression was upregulated in high-grade glioma and GBM and downregulated in IDH mutant glioma. Increased IGFBP2 accompanied PTEN loss and EGFR amplification. Bioinformatic analysis revealed that IGFBP2 is related to immunological processes. We further selected specific immunologic related gene sets and found IGFBP2 predominated immunosuppressive activities in GBM. Furthermore, we explored the relationship between IGFBP2 and genes that were well-characterized glioma-mediated immunosuppressive molecules to investigate the potential effect of IGFBP2. We discovered that IGFBP2 was correlated with CHI3L1, TNFRSF1A, LGALS1, TIMP1, VEGFA, ANXA1 and LGALS3, which were classic immunosuppressive biomarkers. Higher IGFBP2 expression predicted unfavorable survival for patients with GBM. Our findings implied that IGFBP2 is involved in immunosuppressive activities and is an independent unfavorable prognostic biomarker for patients with GBM. IGFBP2 is a potential immunotherapeutic target for GBM in future clinical trials.

Development of a multiplexed tumor-associated autoantibody-based blood test for the detection of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most common malignancies worldwide, and early diagnosis is vital to improving prognoses. We explored the diagnostic potential of a multiplex autoantibody panel as a biomarker for the detection of CRC by ELISA.

METHODS

In total, 192 serum samples (92 CRC and 100 matched controls) were tested against a panel of 12 tumor-associated antigens (TAAs): RPH3AL, RPL36, SLP2, p53, survivin, ANAXA4, SEC61B, CCCAP, NYCO16, NMDAR, PLSCR1, and HDAC5. Individual and combined autoantibody signatures were examined.

RESULTS

Compared to individual autoantibody markers, the combinations of TAAs provided better discrimination between tumorous and normal sera. The overall sensitivity of a selected panel of four antibodies (anti-SLP2, -p53, -SEC61B, and -PLSCR1) was 64.1%, with a specificity of 80% that increased to 83.7% when carcinoembryonic antigen (CEA) measurement was added. Furthermore, the sensitivity of the panel of four antibodies for early and advanced stages of CRC was 66.7% and 62%, increasing to 88.3% and 84%, respectively, when CEA was added.

CONCLUSIONS

We identified a panel of four antibodies as a promising diagnostic biomarker for the detection of CRC.

FBLN4 as candidate gene associated with long-term and short-term survival with primary glioblastoma

Background

Glioblastoma multiforme (GBM) is the most common malignant and lethal type of primary central nervous system tumor in humans. In spite of its high lethality, a small percentage of patients have a relatively good prognosis, with median survival times of 36 months or longer. The identification of clinical subsets of GBM associated with distinct molecular genetic profiles has made it possible to design therapies tailored to treat individual patients.

Methods

We compared microarray data sets from long-term survivors (LTSs) and short-term survivors (STSs) to screen for prognostic biomarkers in GBM patients using the WebArrayDB platform. We focused on FBLN4, IGFBP-2, and CHI3L1, all members of a group of 10 of the most promising, differentially regulated gene candidates. Using formalin-fixed paraffin-embedded GBM samples, we corroborated the relationship between these genes and patient outcomes using methylation-specific polymerase chain reaction (PCR) for MGMT methylation status and quantitative reverse transcription PCR for expression of these genes.

Results

Expression levels of the mRNAs of these 3 genes were higher in the GBM samples than in normal brain samples and these 3 genes were significantly upregulated in STSs compared to the levels in LTS samples (P<0.01). Furthermore, Kaplan–Meier analysis showed that the expression patterns of FBLN4 and IGFBP-2 serve as independent prognostic indicators for overall survival (P<0.01 and P<0.05, respectively).

Conclusion

To our knowledge, this is the first report describing FBLN4 as a prognostic factor for GBM patient survival, demonstrating that increased GBM survival time correlates with decreased FBLN4 expression. Understanding FBLN4 expression patterns could aid in the creation of powerful tools to predict clinical prognoses of GBM patients.

Combined detection of serum Dickkopf-1 and its autoantibodies to diagnose esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) can be treated effectively if diagnosed at an early stage. We evaluated whether measurement of Dickkopf-1 (DKK-1) in combination of DKK-1 autoantibodies in serum may benefit early diagnosis of ESCC. Serum DKK-1 and DKK-1 autoantibodies were measured by enzyme-linked immunosorbent assay in a training cohort (185 ESCC samples vs. 97 normal controls) and validated in a validation cohort (104 ESCC samples vs. 53 normal controls). Receiver operating characteristic (ROC) was applied to calculate diagnostic accuracy. Testing of DKK-1 and DKK-1 autoantibodies together could differentiate ESCC from normal controls (area under the ROC curve [AUC] 0.769, 95% confidence interval (CI), 0.715-0.823, 50.3% sensitivity, and 90.7% specificity in the training cohort; AUC 0.752, 95% CI, 0.675-0.829, 50.0% sensitivity, and 84.9% specificity in the validation cohort). Importantly, the diagnostic performance of the combination of DKK-1 and DKK-1 autoantibodies persisted in early ESCC patients (AUC 0.780, 95% CI, 0.699-0.862, 50.0% sensitivity, and 90.7% specificity in the training cohort; AUC 0.745, 95% CI, 0.626-0.865, 53.8% sensitivity, and 84.9% specificity in the validation cohort). Furthermore, the levels of serum DKK-1 or DKK-1 autoantibody after surgical resection were lower, respectively, compared with the corresponding preoperative samples (P < 0.05). Our results suggest that measurement of DKK-1 combined with DKK-1 autoantibodies is a potentially valuable tool for the early detection of ESCC.

Autoantibodies against tumor-associated antigens for detection of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide. The survival rate after the onset of symptoms is generally less than one year for the late presentation of HCC, and reliable tools for early diagnosis are lacking. Therefore, novel biomarkers for the early detection of HCC are urgently required. Recent studies show that the abnormal release of proteins by tumor cells can elicit humoral immune responses to self-antigens called tumor-associated antigens (TAAs). The corresponding autoantibodies can be detected before the clinical diagnosis of cancer. Therefore, there is growing interest in using serum autoantibodies as cancer biomarkers. In this review, we focus on the advances in research on autoantibodies against TAAs as serum biomarker for detection of HCC, the mechanism of the production of TAAs, and the association of autoantibodies with patients’ clinical characteristics.

BioMiner: Paving the Way for Personalized Medicine

Personalized medicine is promising a revolution for medicine and human biology in the 21st century. The scientific foundation for this revolution is accomplished by analyzing biological high-throughput data sets from genomics, transcriptomics, proteomics, and metabolomics. Currently, access to these data has been limited to either rather simple Web-based tools, which do not grant much insight or analysis by trained specialists, without firsthand involvement of the physician. Here, we present the novel Web-based tool “BioMiner,” which was developed within the scope of an international and interdisciplinary project (SYSTHER†) and gives access to a variety of high-throughput data sets. It provides the user with convenient tools to analyze complex cross-omics data sets and grants enhanced visualization abilities. BioMiner incorporates transcriptomic and cross-omics high-throughput data sets, with a focus on cancer. A public instance of BioMiner along with the database is available at http://systherDB.microdiscovery.de/, login and password: “systher”; a tutorial detailing the usage of BioMiner can be found in the Supplementary File.

Simulation predicts IGFBP2-HIF1α interaction drives glioblastoma growth

Tremendous strides have been made in improving patients’ survival from cancer with one glaring exception: brain cancer. Glioblastoma is the most common, aggressive and highly malignant type of primary brain tumor. The average overall survival remains less than 1 year. Notably, cancer patients with obesity and diabetes have worse outcomes and accelerated progression of glioblastoma. The root cause of this accelerated progression has been hypothesized to involve the insulin signaling pathway. However, while the process of invasive glioblastoma progression has been extensively studied macroscopically, it has not yet been well characterized with regards to intracellular insulin signaling. In this study we connect for the first time microscale insulin signaling activity with macroscale glioblastoma growth through the use of computational modeling. Results of the model suggest a novel observation: feedback from IGFBP2 to HIF1α is integral to the sustained growth of glioblastoma. Our study suggests that downstream signaling from IGFI to HIF1α, which has been the target of many insulin signaling drugs in clinical trials, plays a smaller role in overall tumor growth. These predictions strongly suggest redirecting the focus of glioma drug candidates on controlling the feedback between IGFBP2 and HIF1α.

Current treatment for glioblastoma patients is limited to nonspecific methods: surgery followed by a combination of radio- and chemotherapy. With these methods, glioma patient survival is less than one year post-diagnosis. Targeting specific protein signaling pathways offers potentially more potent therapies. One promising potential target is the insulin signaling pathway, which is known to contribute to glioblastoma progression. However, drugs targeting this pathway have shown mixed results in clinical trials, and the detailed mechanisms of how the insulin signaling pathway promotes glioblastoma growth remain to be elucidated. Here, we developed a computational model of insulin signaling in glioblastoma in order to study this pathway’s role in tumor progression. Using the model, we systematically test contributions of different insulin signaling protein interactions on glioblastoma growth. Our model highlights a key driver for the growth of glioblastoma: IGFBP2-HIF1α feedback. This interaction provides a target that could open the door for new therapies in glioma and other solid tumors.

Circulating glioma biomarkers

Validated biomarkers for patients suffering from gliomas are urgently needed for standardizing measurements of the effects of treatment in daily clinical practice and trials. Circulating body fluids offer easily accessible sources for such markers. This review highlights various categories of tumor-associated circulating biomarkers identified in blood and cerebrospinal fluid of glioma patients, including circulating tumor cells, exosomes, nucleic acids, proteins, and oncometabolites. The validation and potential clinical utility of these biomarkers is briefly discussed. Although many candidate circulating protein biomarkers were reported, none of these have reached the required validation to be introduced for clinical practice. Recent developments in tracing circulating tumor cells and their derivatives as exosomes and circulating nuclear acids may become more successful in providing useful biomarkers. It is to be expected that current technical developments will contribute to the finding and validation of circulating biomarkers.

IGF binding proteins in cancer: mechanistic and clinical insights

The six members of the family of insulin-like growth factor (IGF) binding proteins (IGFBPs) were originally characterized as passive reservoirs of circulating IGFs, but they are now understood to have many actions beyond their endocrine role in IGF transport. IGFBPs also function in the pericellular and intracellular compartments to regulate cell growth and survival - they interact with many proteins, in addition to their canonical ligands IGF-I and IGF-II. Intranuclear roles of IGFBPs in transcriptional regulation, induction of apoptosis and DNA damage repair point to their intimate involvement in tumour development, progression and resistance to treatment. Tissue or circulating IGFBPs might also be useful as prognostic biomarkers.

Multi-study integration of brain cancer transcriptomes reveals organ-level molecular signatures

We utilized abundant transcriptomic data for the primary classes of brain cancers to study the feasibility of separating all of these diseases simultaneously based on molecular data alone. These signatures were based on a new method reported herein – Identification of Structured Signatures and Classifiers (ISSAC) – that resulted in a brain cancer marker panel of 44 unique genes. Many of these genes have established relevance to the brain cancers examined herein, with others having known roles in cancer biology. Analyses on large-scale data from multiple sources must deal with significant challenges associated with heterogeneity between different published studies, for it was observed that the variation among individual studies often had a larger effect on the transcriptome than did phenotype differences, as is typical. For this reason, we restricted ourselves to studying only cases where we had at least two independent studies performed for each phenotype, and also reprocessed all the raw data from the studies using a unified pre-processing pipeline. We found that learning signatures across multiple datasets greatly enhanced reproducibility and accuracy in predictive performance on truly independent validation sets, even when keeping the size of the training set the same. This was most likely due to the meta-signature encompassing more of the heterogeneity across different sources and conditions, while amplifying signal from the repeated global characteristics of the phenotype. When molecular signatures of brain cancers were constructed from all currently available microarray data, 90% phenotype prediction accuracy, or the accuracy of identifying a particular brain cancer from the background of all phenotypes, was found. Looking forward, we discuss our approach in the context of the eventual development of organ-specific molecular signatures from peripheral fluids such as the blood.

From a multi-study, integrated transcriptomic dataset, we identified a marker panel for differentiating major human brain cancers at the gene-expression level. The ISSAC molecular signatures for brain cancers, composed of 44 unique genes, are based on comparing expression levels of pairs of genes, and phenotype prediction follows a diagnostic hierarchy. We found that sufficient dataset integration across multiple studies greatly enhanced diagnostic performance on truly independent validation sets, whereas signatures learned from only one dataset typically led to high error rate. Molecular signatures of brain cancers, when obtained using all currently available gene-expression data, achieved 90% phenotype prediction accuracy. Thus, our integrative approach holds significant promise for developing organ-level, comprehensive, molecular signatures of disease.

Autoantibodies against insulin-like growth factor‑binding protein-2 as a serological biomarker in the diagnosis of lung cancer

Insulin-like growth factor-binding protein-2 (IGFBP-2) is considered to be a human tumor antigen, and the tumor-specific immunity of IGFBP-2 has been reported in several types of cancer. The purpose of this study was to evaluate whether autoantibodies to IGFBP-2 can be used as diagnostic markers in lung cancer. The results demonstrated that serum anti-IGFBP-2 autoantibody levels were significantly elevated in lung cancer (mean, 1,633.318 ng/ml; median, 1,651.462 ng/ml; range, 342.732–4932.582 ng/ml) compared with benign lung disease (1,210.139, 1,035.900, 547.596–2,331.167 ng/ml) and normal controls (1,303.369, 1,194.800, 528.200–2140.500 ng/ml). The sensitivity and specificity of anti-IGFBP-2 autoantibodies in diagnosing lung cancer was 73.2 and 60.6%, respectively. When serum IGFBP-2 and anti-IGFBP-2 autoantibody were used together in the diagnosis of lung cancer, it can increase the discriminative power for lung cancer with a sensitivity of 85.7% and a specificity of 57.5%. In conclusion, this study demonstrates that circulating anti-IGFBP-2 autoantibodies can be used as a potential biomarker in diagnosing lung cancer.