An integrated genome-wide approach to discover tumor-specific antigens as potential immunologic and clinical targets in cancer

Non-immune cell components in tumor microenvironment influencing lung cancer Immunotherapy

Lung cancer (LC) is one of the leading causes of cancer-related deaths worldwide, with a significant morbidity and mortality rate, endangering human life and health. The introduction of immunotherapies has significantly altered existing cancer treatment strategies and is expected to improve immune responses, objective response rates, and survival rates. However, a better understanding of the complex immunological networks of LC is required to improve immunotherapy efficacy further. Tumor-associated antigens (TAAs) and tumor-specific antigens (TSAs) are significantly expressed by LC cells, which activate dendritic cells, initiate antigen presentation, and activate lymphocytes to exert antitumor activity. However, as tumor cells combat the immune system, an immunosuppressive microenvironment forms, enabling the enactment of a series of immunological escape mechanisms, including the recruitment of immunosuppressive cells and induction of T cell exhaustion to decrease the antitumor immune response. In addition to the direct effect of LC cells on immune cell function, the secreting various cytokines, chemokines, and exosomes, changes in the intratumoral microbiome and the function of cancer-associated fibroblasts and endothelial cells contribute to LC cell immune escape. Accordingly, combining various immunotherapies with other therapies can elicit synergistic effects based on the complex immune network, improving immunotherapy efficacy through multi-target action on the tumor microenvironment (TME). Hence, this review provides guidance for understanding the complex immune network in the TME and designing novel and effective immunotherapy strategies for LC.

Molecular and Circulating Biomarkers of Gastric Cancer

Gastric cancer (GC)—a common tumor that affects humans worldwide—is highly malignant with a poor prognosis. GC is frequently not diagnosed until a relatively advanced stage. Early detection and efficient monitoring of tumor dynamics are prerequisites for reducing disease burden and mortality. Minimally invasive methods are needed to establish a diagnosis or monitoring the response to treatment of gastric cancer. Blood-based biomarker assays for the detection of early-stage GC could be of great relevance both for the risk group or for population-wide based screening programs, The currently used tumor marker assays for detecting GC are simple and rapid, but their use is limited by their low sensitivity and specificity. In recent years, several markers have been identified and tested for their clinical relevance in the management of gastric cancer. Here we review the available literature on plasma classical tumor markers, circulating free microRNAs (cfmiRNAs), circulating cell-free DNA (cfDNA), circulating tumor cells (CTCs), autoantibodies against tumor associated antigens (TAAs), and circulating extracellular vesicles (EVs) for diagnosis and monitoring of gastric cancer. This review summarizes the present status and approaches for these biomarkers, which could be potentially used for early diagnosis and accurate prediction of therapeutic approaches. We also discuss the future perspective and challenges in the search for new biomarkers of gastric 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.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Knockdown of m6A methyltransferase METTL3 in gastric cancer cells results in suppression of cell proliferation

N6-methyladenosine (m6A) RNA modification regulates multiple biological functions. Methyltransferase like 3 (METTL3), one of the major N6-methyltransferases, is highly expressed in gastric cancer, but its potential role in disease is unclear. The current study knocked out METTL3 (METTL3-KO) in human gastric cancer AGS cells using CRISPR/Cas9. METTL3-KO AGS cells exhibited decreased m6A methylation levels. A significant inhibition of cell proliferation was observed in METTL3-KO AGS cells. Silencing METTL3 in AGS cells altered the expression profile of many effector molecules that were previously demonstrated to serve key roles in AGS cell proliferation, including the suppressor of cytokine signaling (SOCS) family of proteins. The results further demonstrated that SOCS2 upregulation in METTL3-KO AGS cells was associated with a decreased RNA decay rate. Furthermore, SOCS2 KO or SOCS2 overexpression caused a significant increase and decrease in AGS cell proliferation, respectively. The current data suggested that METTL3-KO in gastric cancer cells resulted in the suppression of cell proliferation by inducing SOCS2, suggesting a potential role of elevated METTL3 expression in gastric cancer progression.

Role of Regenerating Islet-Derived Protein 3A in Gastrointestinal Cancer

Regenerating islet-derived protein 3A (Reg3A), a protein mainly expressed in the digestive system, has been found over-expressed in many kinds of gastrointestinal cancer, including hepatocellular carcinoma, pancreatic cancer, gastric cancer, and colorectal cancer, therefore has been considered as a promising tumor marker. In recent years, considerable attention has been focused on the tumorigenesis effects of Reg3A, which were mainly manifested as cell proliferation promotion, cell apoptosis inhibition, the regulation of cancer cell migration and invasion. In particular, based on the significant up-regulation of Reg3A during pancreatic inflammation as well as its tumorigenic potential, Reg3A has been considered to play a key role in inflammation-linked pancreatic carcinogenesis. In addition, we here systematically generalized the reported Reg3A-related signaling molecules, which included JAK2-STAT3- NF-κB, SOCS3, EXTL3-PI3K-Akt, GSK3β, Wnt/β-catenin as well as some invasion and migration-related genes (Snail, MMP-2, MMP-9, E-cadherin, RhoC, and MTA1). And gp130, EGFR, EXTL3, and Fibronectin 1 might act as potential receptors for Reg3A.

Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Immunotherapy can revolutionize anti-cancer therapy if specific targets are available. Immunogenic peptides encoded by cancer-specific genes (CSGs) may enable targeted immunotherapy, even of oligo-mutated cancers, which lack neo-antigens generated by protein-coding missense mutations. Here, we describe an algorithm and user-friendly software named RAVEN (Rich Analysis of Variable gene Expressions in Numerous tissues) that automatizes the systematic and fast identification of CSG-encoded peptides highly affine to Major Histocompatibility Complexes (MHC) starting from transcriptome data. We applied RAVEN to a dataset assembled from 2,678 simultaneously normalized gene expression microarrays comprising 50 tumor entities, with a focus on oligo-mutated pediatric cancers, and 71 normal tissue types. RAVEN performed a transcriptome-wide scan in each cancer entity for gender-specific CSGs, and identified several established CSGs, but also many novel candidates potentially suitable for targeting multiple cancer types. The specific expression of the most promising CSGs was validated in cancer cell lines and in a comprehensive tissue-microarray. Subsequently, RAVEN identified likely immunogenic CSG-encoded peptides by predicting their affinity to MHCs and excluded sequence identity to abundantly expressed proteins by interrogating the UniProt protein-database. The predicted affinity of selected peptides was validated in T2-cell peptide-binding assays in which many showed binding-kinetics like a very immunogenic influenza control peptide. Collectively, we provide an exquisitely curated catalogue of cancer-specific and highly MHC-affine peptides across 50 cancer types, and a freely available software (https://github.com/JSGerke/RAVENsoftware) to easily apply our algorithm to any gene expression dataset. We anticipate that our peptide libraries and software constitute a rich resource to advance anti-cancer immunotherapy.

Epigenetic activation of HORMAD1 in basal-like breast cancer: role in Rucaparib sensitivity

Basal-like breast cancer (BLBC) is an aggressive breast cancer subtype with features similar to the basal cells surrounding the mammary ducts. Treatment of patients with BLBC has been challenging due to the lack of well-defined molecular targets. Due to the clinical and pathological similarities of BLBC with BRCA-deficient breast cancers, the effectiveness of Poly (ADP-ribose) polymerase inhibitors (PARPi) has been tested in early phase clinical trials for patients with advanced BLBC, with limited clinical responses. Recently, it was reported that HORMAD1 overexpression sensitizes BLBC to HR-targeting agents by suppressing homologous recombination. Our independent analysis suggests that HORMAD1 is aberrantly overexpressed in about 80% of BLBC, and its expression in normal tissues is restricted to testis. Our experimental data suggests that HORMAD1 overexpression correlates with focal hypomethylation in BLBC. On the other hand, investigation of the Genomics of Drug Sensitivity in Cancer dataset revealed significantly reduced sensitivity of HORMAD1-overexpressing BLBC cell lines to Rucaparib, a commonly used PARPi. To further assess the role of HORMAD1 in PARPi sensitivity, we generated three HORMAD1-overexpressing xenograft models using the HORMAD1-low BLBC cell lines HCC1954, HCC1806, and BT20; we then subjected these xenograft models to Rucaparib treatment. Ectopic expression of HORMAD1 enhances tumor formations in two of these models, and significantly reduces sensitivity to Rucaparib in the HCC1954 model. Taken together, our data suggest that epigenetic activation of HORMAD1 by hypomethylation in BLBC may endow reduced sensitivity to Rucaparib treatment in some tumor models.

Prognostic and predictive blood biomarkers in gastric cancer and the potential application of circulating tumor cells

Gastric cancer (GC), with its high incidence and mortality rates, is a highly fatal cancer that is common in East Asia particularly in China. Its recurrence and metastasis are the main causes of its poor prognosis. Circulating tumor cells (CTCs) or other blood biomarkers that are released into the circulating blood stream by tumors are thought to play a crucial role in the recurrence and metastasis of gastric cancer. Therefore, the detection of CTCs and other blood biomarkers has an important clinical significance; in fact, they can help predict the prognosis, assess the staging, monitor the therapeutic effects and determine the drug susceptibility. Recent research has identified many blood biomarkers in GC, such as various serum proteins, autoantibodies against tumor associated antigens, and cell-free DNAs. The analysis of CTCs and circulating cell-free tumor DNA (ctDNA) in the peripheral blood of patients with gastric cancer is called as liquid biopsy. These blood biomarkers provide the disease status for individuals and have clinical meaning. In this review, we focus on the recent scientific advances regarding CTCs and other blood biomarkers, and discuss their origins and clinical meaning.

Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) promotes lung tumorigenesis via attenuating p53 stability

Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3/IMP3/KOC), initially identified as an RNA-binding protein, is highly expressed in embryonic tissues and a variety of cancers. Previously, our group reported that IGF2BP3 may serve as a potential diagnostic marker for lung cancer. However, little is known about the function of IGF2BP3 in lung cancer development. Here we demonstrate that IGF2BP3 expression was markedly increased in lung cancer tissues compared to normal tissues at both mRNA and protein levels. Overexpression of IGF2BP3 in lung cancer cells promoted cell proliferation, tumor migration and invasion in vitro and in vivo, whereas knockdown of IGF2BP3 exhibited opposite effects. Notably IGF2BP3 was directly associated with a deubiquitinase Ubiquitin specific peptidase 10 (USP10) and attenuated its function in stabilizing p53 protein. Silencing IGF2BP3 expression in lung cancer cells consistently increased the half-life and protein level of p53 and induced G0/G1 arrest. Thus, our data together demonstrate that IGF2BP3 promotes lung tumorigenesis via attenuating p53 protein stability.

Combination of OipA, BabA, and SabA as candidate biomarkers for predicting Helicobacter pylori-related gastric cancer

Helicobacter pylori (H. pylori ) infection is a major cause of chronic gastritis and is highly related to duodenal ulcer (DU) and gastric cancer (GC). To identify H. pylori-related GC biomarkers with high seropositivity in GC patients, differences in levels of protein expression between H. pylori from GC and DU patients were analyzed by isobaric tag for relative and absolute quantitation (iTRAQ). In total, 99 proteins showed increased expression (>1.5-fold) in GC patients compared to DU patients, and 40 of these proteins were categorized by KEGG pathway. The four human disease-related adhesin identified, AlpA, OipA, BabA, and SabA, were potential GC-related antigens, with a higher seropositivity in GC patients (n = 76) than in non-GC patients (n = 100). Discrimination between GC and non-GC patients was improved using multiple antigens, with an odds ratio of 9.16 (95% CI, 2.99-28.07; p < 0.0001) for three antigens recognized. The optimized combination of OipA, BabA, and SabA gave a 77.3% correct prediction rate. A GC-related protein microarray was further developed using these antigens. The combination of OipA, BabA, and SabA showed significant improvement in the diagnostic accuracy and the protein microarray containing above antigens should provide a rapid and convenient diagnosis of H. pylori-associated GC.

CRISPR/Cas9-mediated target validation of the splicing inhibitor Pladienolide B

CRISPR/Cas9 system confers molecular immunity in archeal and bacterial species against invading foreign nucleic acids. CRISPR/Cas9 system is used for genome engineering applications across diverse eukaryotic species. In this study, we demonstrate the utility of the CRISPR/Cas9 genome engineering system for drug target validation in human cells. Pladienolide B is a natural macrolide with antitumor activities mediated through the inhibition of pre-mRNA splicing. To validate the spliceosomal target of Pladienolide B, we employed the CRSIPR/Cas9 system to introduce targeted mutations in the subunits of the SF3B complex in the HEK293T cells. Our data reveal that targeted mutagenesis of the SF3b1 subunit exhibited higher levels of resistance to Pladienolide B. Therefore, our data validate the spliceosomal target of Pladienolide B and provide a proof of concept on using the CRISPR/Cas9 system for drug target identification and validation.

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CRISPR/Cas9 system serves as an excellent tool for drug target validation.

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Pladienolide B an antitumor macrolide known to bind to the SF3b complex and inhibit pre-mRNA splicing.

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Use of CRISPR/Cas9 system to confirm and validate the Pladienolide B spliceosomal target.

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Our data confirm that the SF3b1 is a specific target for Pladienolide B.

Emerging blood-based biomarkers for detection of gastric cancer

Early detection and efficient monitoring of tumor dynamics are prerequisites for reducing disease burden and mortality, and for improving the management of patients with gastric cancer (GC). Blood-based biomarker assays for the detection of early-stage GC could be of great relevance both for population-wide or risk group-based screening programs, while circulating biomarkers that reflect the genetic make-up and dynamics of the tumor would allow monitoring of treatment efficacy, predict recurrences and assess the genetic heterogeneity of the tumor. Recent research to identify blood-based biomarkers of GC has resulted in the identification of a wide variety of cancer-associated molecules, including various proteins, autoantibodies against tumor associated antigens, cell-free DNA fragments, mRNAs and various non-coding RNAs, circulating tumor cells and cancer-derived extracellular vesicles. Each type of these biomarkers provides different information on the disease status, has different advantages and disadvantages, and distinct clinical usefulness. In the current review, we summarize the recent developments in blood-based GC biomarker discovery, discuss the origin of various types of biomarkers and their clinical usefulness and the technological challenges in the development of biomarker assays for clinical use.

Antigen-specific bacterial vaccine combined with anti-PD-L1 rescues dysfunctional endogenous T cells to reject long-established cancer

Immunogenic tumors grow progressively even when heavily infiltrated by CD8(+) T cells. We investigated how to rescue CD8(+) T cell function in long-established immunogenic melanomas that contained a high percentage of endogenous PD-1(+) tumor-specific CD8(+) T cells that were dysfunctional. Treatment with αPD-L1 and αCTLA-4 blocking antibodies did not prevent tumors from progressing rapidly. We then tested exogenous tumor-specific antigen delivery into tumors using Salmonella Typhimurium A1-R to increase antigen levels and generate a proinflammatory tumor microenvironment. Antigen-producing A1-R rescued the endogenous tumor-specific CD8(+) T cell response: proliferation was induced in the lymphoid organs and effector function was recovered in the tumor. Treatment with antigen-producing A1-R led to improved mouse survival and resulted in 32% rejection of long-established immunogenic melanomas. Following treatment with antigen-producing A1-R, the majority of tumor-specific CD8(+) T cells still expressed a high level of PD-1 in the tumor. Combining antigen-producing A1-R with αPD-L1 blocking antibody enhanced the expansion of tumor-specific CD8(+) T cells and resulted in 80% tumor rejection. Collectively, these data demonstrate a powerful new therapeutic approach to rescue dysfunctional endogenous tumor-specific CD8(+) T cells and eradicate advanced immunogenic tumors.

HEPA and PARSE: Systematic discovery of clinically relevant tumor-specific antigens

The effective discovery of tumor-specific antigens (TSAs) holds the key for the development of new diagnostic assays and immunotherapeutic approaches against cancer. Here, we discuss our recently developed technologies, HEPA and PARSE, which allow for the systematic identification of TSAs, generating a reservoir of immunologically and clinically relevant targets.

IQGAP3 promotes EGFR-ERK signaling and the growth and metastasis of lung cancer cells

Proteins of the IQGAP family display complicated and often contradictory activities in tumorigenesis. IQGAP1 has well documented oncogenic potential and IQGAP2 has putative tumor-suppressive function. IQGAP3 is the latest addition to this family and its role in cancer development remains to be defined. Here we demonstrate IQGAP3 expression is markedly increased in lung cancer tissues at both mRNA and protein levels. Overexpression of IQGAP3 promoted tumor cell growth, and migration and invasion, whereas knockdown of IQGAP3 exhibited opposite effects. Moreover, suppression of IQGAP3 in a lung cancer cell line caused a reduction in the tumorigenicity of these cells in lung tissue after intravenous injection. Furthermore, we showed that IQGAP3 is able to interact with ERK1 and enhance its phosphorylation following treatment with EGF. These data suggest that IQGAP3 may contribute to the pathogenesis of lung cancer by modulating EGFR-ERK signaling.

Systematic review: serum autoantibodies in the early detection of gastric cancer

Antibodies against tumor-associated antigens have been found in serum of patients with various types of cancers and may serve as biomarkers for early detection of gastric cancer as well. This systematic review aims to give an overview about known autoantibodies and their diagnostic value in gastric cancer. We conducted a systematic literature search in two databases to identify studies which performed serological testing for autoantibodies in gastric cancer patients and controls. Data on study characteristics and results were extracted independently by two reviewers. Overall, 39 articles reporting the detection of 34 different autoantibodies met the inclusion criteria for this review. The most common antibody detection method was enzyme-linked immunosorbent assay and the most frequently assessed autoantibody was anti-p53, which was tested in 13 studies. Most antibodies were assessed in only one study and only few authors have evaluated the diagnostic value of combinations of multiple autoantibodies. For single autoantibodies, specificity was generally very high (median: 99.15%), but sensitivity was mostly rather low (median: 12.35%). For some autoantibody combinations, substantially higher sensitivity at reasonably high levels of specificity could be achieved. Development of extended and optimized multimarker panels of autoantibodies might be a promising approach for gastric cancer early detection.

Early diagnosis of complex diseases by molecular biomarkers, network biomarkers, and dynamical network biomarkers

Many studies have been carried out for early diagnosis of complex diseases by finding accurate and robust biomarkers specific to respective diseases. In particular, recent rapid advance of high-throughput technologies provides unprecedented rich information to characterize various disease genotypes and phenotypes in a global and also dynamical manner, which significantly accelerates the study of biomarkers from both theoretical and clinical perspectives. Traditionally, molecular biomarkers that distinguish disease samples from normal samples are widely adopted in clinical practices due to their ease of data measurement. However, many of them suffer from low coverage and high false-positive rates or high false-negative rates, which seriously limit their further clinical applications. To overcome those difficulties, network biomarkers (or module biomarkers) attract much attention and also achieve better performance because a network (or subnetwork) is considered to be a more robust form to characterize diseases than individual molecules. But, both molecular biomarkers and network biomarkers mainly distinguish disease samples from normal samples, and they generally cannot ensure to identify predisease samples due to their static nature, thereby lacking ability to early diagnosis. Based on nonlinear dynamical theory and complex network theory, a new concept of dynamical network biomarkers (DNBs, or a dynamical network of biomarkers) has been developed, which is different from traditional static approaches, and the DNB is able to distinguish a predisease state from normal and disease states by even a small number of samples, and therefore has great potential to achieve "real" early diagnosis of complex diseases. In this paper, we comprehensively review the recent advances and developments on molecular biomarkers, network biomarkers, and DNBs in particular, focusing on the biomarkers for early diagnosis of complex diseases considering a small number of samples and high-throughput data (or big data). Detailed comparisons of various types of biomarkers as well as their applications are also discussed.