Transcriptional profiling of peripheral blood mononuclear cells in pancreatic cancer patients identifies novel genes with potential diagnostic utility

The potential of carbonic anhydrase enzymes as a novel target for anti-cancer treatment

Carbonic anhydrase (CA) is a zinc-dependent metal enzyme that maintains the pH and carbon dioxide (CO2) homeostasis in cells by catalyzing the reversible hydration and dehydration of CO2 and bicarbonate (HCO3-). In mammals, there are 16 isozymes of CA existed, namely CAI to CAXIV, but only 15 isozymes are found in humans except CAXV. Human CAs have highly conserved catalytic domains, all of which are distributed in different tissues and play important physiological roles. Changes in their functions may disrupt the typical distribution of CAs throughout human body and therefore CAs can be used as diagnostic biomarkers for many diseases. Furthermore, the expression of CAs is correlated to the progression of numerous tumors, therapeutic sensitivity and patient prognosis. In this review, we discuss thoroughly the structure of CAs, their functional activities in human physiology, dysregulations and diseases related to CAs, and different types of CA inhibitors that can reverse their dysregulation.

Pharmacological Activation of SIRT3 Modulates the Response of Cancer Cells to Acidic pH

Cancer cells modulate their metabolism, creating an acidic microenvironment that, in turn, can favor tumor progression and chemotherapy resistance. Tumor cells adopt strategies to survive a drop in extracellular pH (pHe). In the present manuscript, we investigated the contribution of mitochondrial sirtuin 3 (SIRT3) to the adaptation and survival of cancer cells to a low pHe. SIRT3-overexpressing and silenced breast cancer cells MDA-MB-231 and human embryonic kidney HEK293 cells were grown in buffered and unbuffered media at pH 7.4 and 6.8 for different times. mRNA expression of SIRT3 and CAVB, was measured by RT-PCR. Protein expression of SIRT3, CAVB and autophagy proteins was estimated by western blot. SIRT3-CAVB interaction was determined by immunoprecipitation and proximity ligation assays (PLA). Induction of autophagy was studied by western blot and TEM. SIRT3 overexpression increases the survival of both cell lines. Moreover, we demonstrated that SIRT3 controls intracellular pH (pHi) through the regulation of mitochondrial carbonic anhydrase VB (CAVB). Interestingly, we obtained similar results by using MC2791, a new SIRT3 activator. Our results point to the possibility of modulating SIRT3 to decrease the response and resistance of tumor cells to the acidic microenvironment and ameliorate the effectiveness of anticancer therapy.

A human-specific insertion promotes cell proliferation and migration by enhancing TBC1D8B expression

Human-specific insertions play important roles in human phenotypes and diseases. Here we reported a 446-bp insertion (Insert-446) in intron 11 of the TBC1D8B gene, located on chromosome X, and traced its origin to a portion of intron 6 of the EBF1 gene on chromosome 5. Interestingly, Insert-446 was present in the human Neanderthal and Denisovans genomes, and was fixed in humans after human-chimpanzee divergence. We have demonstrated that Insert-446 acts as an enhancer through binding transcript factors that promotes a higher expression of human TBC1D8B gene as compared with orthologs in macaques. In addition, over-expression TBC1D8B promoted cell proliferation and migration through "a dual finger" catalytic mechanism (Arg538 and Gln573) in the TBC domain in vitro and knockdown of TBC1D8B attenuated tumorigenesis in vivo. Knockout of Insert-446 prevented cell proliferation and migration in cancer and normal cells. Our results reveal that the human-specific Insert-446 promotes cell proliferation and migration by upregulating the expression of TBC1D8B gene. These findings provide a significant insight into the effects of human-specific insertions on evolution.

Pan-cancer scRNA-seq analysis reveals immunological and diagnostic significance of the peripheral blood mononuclear cells

Peripheral blood mononuclear cells (PBMCs) reflect systemic immune response during cancer progression. However, a comprehensive understanding of the composition and function of PBMCs in cancer patients is lacking, and the potential of these features to assist cancer diagnosis is also unclear. Here, the compositional and status differences between cancer patients and healthy donors in PBMCs were investigated by single-cell RNA sequencing (scRNA-seq), involving 262,025 PBMCs from 68 cancer samples and 14 healthy samples. We observed an enhanced activation and differentiation of most immune subsets in cancer patients, along with reduction of naïve T cells, expansion of macrophages, impairment of NK cells and myeloid cells, as well as tumor promotion and immunosuppression. Based on characteristics including differential cell type abundances and/or hub genes identified from weight gene co-expression network analysis (WGCNA) modules of each major cell type, we applied logistic regression to construct cancer diagnosis models. Furthermore, we found that the above models can distinguish cancer patients and healthy donors with high sensitivity. Our study provided new insights into using the features of PBMCs in non-invasive cancer diagnosis.

Xenopus Ssbp2 is required for embryonic pronephros morphogenesis and terminal differentiation

The nephron, functional unit of the vertebrate kidney, is specialized in metabolic wastes excretion and body fluids osmoregulation. Given the high evolutionary conservation of gene expression and segmentation patterning between mammalian and amphibian nephrons, the Xenopus laevis pronephric kidney offers a simplified model for studying nephrogenesis. The Lhx1 transcription factor plays several roles during embryogenesis, regulating target genes expression by forming multiprotein complexes with LIM binding protein 1 (Ldb1). However, few Lhx1-Ldb1 cofactors have been identified for kidney organogenesis. By tandem- affinity purification from kidney-induced Xenopus animal caps, we identified single-stranded DNA binding protein 2 (Ssbp2) interacts with the Ldb1-Lhx1 complex. Ssbp2 is expressed in the Xenopus pronephros, and knockdown prevents normal morphogenesis and differentiation of the glomus and the convoluted renal tubules. We demonstrate a role for a member of the Ssbp family in kidney organogenesis and provide evidence of a fundamental function for the Ldb1-Lhx1-Ssbp transcriptional complexes in embryonic development.

Improved predictability of pancreatic ductal adenocarcinoma diagnosis using a blood immune cell biomarker panel developed from bulk mRNA sequencing and single-cell RNA-sequencing

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) remains a devastating cancer due to its poor survival rate, early detection, and resectability. This study aimed to determine the peripheral blood mononuclear cell (PBMC) immune biomarkers in patients with PDAC and investigate the PDAC-specific peripheral blood biomarker panel and validate its clinical performance.

METHODS

In this prospective, blinded, case-control study, a biomarker panel formula was generated using a development cohort-including healthy controls, patients at high risk of PDAC, and patients with benign pancreatic disease, PDAC, or other gastrointestinal malignancies-and its diagnostic performance was verified using a validation cohort, including patients with ≥ 1 lesion suspected as PDAC on computed tomography (CT).

RESULTS

RNA-sequencing of PBMCs from patients with PDAC identified three novel immune cell markers, IL-7R, PLD4, and ID3, as specific markers for PDAC. Regarding the diagnostic performance of the regression formula for the three biomarker panels, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.0%, 78.8%, 47.2%, 95.6%, and 79.8%, respectively. Based on the formula scores for the biomarker panel, the false-negative rate (FNR) of the biomarkers was 8% (95% confidence interval [CI] 3.0-13.0), which was significantly lower than that based on CT in the validation cohort (29.2%, 95% CI 20.8-37.6).

CONCLUSIONS

The regression formula constructed using three PBMC biomarkers is an inexpensive, rapid, and convenient method that shows clinically useful performance for the diagnosis of PDAC. It aids diagnoses and differential diagnoses of PDAC from pancreatic disease by lowering the FNR compared to CT. Clinical trial registration Clinical Research Information Service, KCT0004614 (08 January 2020).

ANKRD29, as a new prognostic and immunological biomarker of non-small cell lung cancer, inhibits cell growth and migration by regulating MAPK signaling pathway

BACKGROUND

The predominant cancer-related deaths worldwide are caused by lung cancer, particularly non-small cell lung cancer (NSCLC), despite the fact that numerous therapeutic initiatives have been devised to improve the outcomes. Ankyrin repeat domain (ANKRD) is one of the widespread protein structural motifs in eukaryotes but the functions of ANKRD proteins in NSCLC progression remains unclear.

METHODS

We performed integrative bioinformatical analysis to determine the dysregulated expression of ANKRDs in multiple tumors and the association between ANKRD29 expression and the NSCLC tumor environment. Quantitative real-time PCR (qRT-PCR), western blot, immunohistochemistry (IHC), and tissue microarray (TMA) assays were used to investigate the expression of ANKRD29 in NSCLC cell lines. The role of ANKRD29 in NSCLC cell proliferation and migration in vitro was deteceted by 5-bromodeoxyuridine (BrdU) incorporation, colony formation, flow cytometry, would-healing, trans-well, and western blot experiment. RNA-seq technology was applied to deciper the molecular mechanism regulated by ANKRD29 in NSCLC.

RESULTS

We constructed a valuable risk-score system for predicting the overall survival outcomes of NSCLC patients based on the expression of five hub ANKRD genes. And we found that the hub gene ANKRD29 was remarkedly decreased in NSCLC tissues and cell lines due to the promoter hypermethylation, and revealed that high ANKRD29 expression obviously correlated with patients' better clinical outcome. Overexpression of ANKRD29 significantly inhibited cell proliferation and migration, promoted the cancerous cells' sensitivity to carboplatin and enhanced the killing ability of T cells in NSCLC cells. Interestingly, ANKRD29 can be served as a biomarker to predict the response to immunotherapy in NSCLC. Mechanically, RNA-seq results showed that ANKRD29 could regulate MAPK signaling pathway. Moreover, we screened two potential agonists for ANKRD29.

CONCLUSIONS

ANKRD29 functions as a new tumor suppressor in NSCLC tumorigenesis and could be developed as a biomarker for prognostic prediction, immunotherapy response, and drug susceptibility evaluation of NSCLC in the future.

Xenopus Ssbp2 is required for embryonic pronephros morphogenesis and terminal differentiation

The nephron, functional unit of the vertebrate kidney, is specialized in metabolic wastes excretion and body fluids osmoregulation. Given the high evolutionary conservation of gene expression and segmentation patterning between mammalian and amphibian nephrons, the Xenopus laevis pronephric kidney offers a simplified model for studying nephrogenesis. The Lhx1 transcription factor plays several roles during embryogenesis, regulating target genes expression by forming multiprotein complexes with LIM binding protein 1 (Ldb1). However, few Lhx1-Ldb1 cofactors have been identified for kidney organogenesis. By tandem-affinity purification from kidney-induced Xenopus animal caps, we identified s ingle- s tranded DNA b inding p rotein 2 (Ssbp2) interacts with the Ldb1-Lhx1 complex. Ssbp2 is expressed in the Xenopus pronephros, and knockdown prevents normal morphogenesis and differentiation of the glomus and the convoluted renal tubules. We demonstrate a role for a member of the Ssbp family in kidney organogenesis and provide evidence of a fundamental function for the Ldb1-Lhx1-Ssbp transcriptional complexes in embryonic development.

SWEET: a single-sample network inference method for deciphering individual features in disease

Recently, extracting inherent biological system information (e.g. cellular networks) from genome-wide expression profiles for developing personalized diagnostic and therapeutic strategies has become increasingly important. However, accurately constructing single-sample networks (SINs) to capture individual characteristics and heterogeneity in disease remains challenging. Here, we propose a sample-specific-weighted correlation network (SWEET) method to model SINs by integrating the genome-wide sample-to-sample correlation (i.e. sample weights) with the differential network between perturbed and aggregate networks. For a group of samples, the genome-wide sample weights can be assessed without prior knowledge of intrinsic subpopulations to address the network edge number bias caused by sample size differences. Compared with the state-of-the-art SIN inference methods, the SWEET SINs in 16 cancers more likely fit the scale-free property, display higher overlap with the human interactomes and perform better in identifying three types of cancer-related genes. Moreover, integrating SWEET SINs with a network proximity measure facilitates characterizing individual features and therapy in diseases, such as somatic mutation, mut-driver and essential genes. Biological experiments further validated two candidate repurposable drugs, albendazole for head and neck squamous cell carcinoma (HNSCC) and lung adenocarcinoma (LUAD) and encorafenib for HNSCC. By applying SWEET, we also identified two possible LUAD subtypes that exhibit distinct clinical features and molecular mechanisms. Overall, the SWEET method complements current SIN inference and analysis methods and presents a view of biological systems at the network level to offer numerous clues for further investigation and clinical translation in network medicine and precision medicine.

Protocol for Classification Single-Cell PBMC Types from Pathological Samples Using Supervised Machine Learning

Peripheral blood mononuclear cells (PBMC) are mixed subpopulations of blood cells composed of five cell types. PBMC are widely used in the study of the immune system, infectious diseases, cancer, and vaccine development. Single-cell transcriptomics (SCT) allows the labeling of cell types by gene expression patterns from biological samples. Classifying cells into cell types and states is essential for single-cell analyses, especially in the classification of diseases and the assessment of therapeutic interventions, and for many secondary analyses. Most of the classification of cell types from SCT data use unsupervised clustering or a combination of unsupervised and supervised methods including manual correction. In this chapter, we describe a protocol that uses supervised machine learning (ML) methods with SCT data for the classification of PBMC cell types in samples representing pathological states. This protocol has three parts: (1) data preprocessing, (2) labeling of reference PBMC SCT datasets and training supervised ML models, and (3) labeling new PBMC datasets from disease samples. This protocol enables building classification models that are of high accuracy and efficiency. Our example focuses on 10× Genomics technology but applies to datasets from other SCT platforms.

Development of a Molecular Blood-Based Immune Signature Classifier as Biomarker for Risks Assessment in Lung Cancer Screening

BACKGROUND

Low-dose CT (LDCT) screening trials have shown that lung cancer early detection saves lives. However, a better stratification of the screening population is still needed. In this respect, we generated and prospectively validated a plasma miRNA signature classifier (MSC) able to categorize screening participants according to lung cancer risk. Here, we aimed to deeply characterize the peripheral immune profile and develop a diagnostic immune signature classifier to further implement blood testing in lung cancer screening.

METHODS

Peripheral blood mononuclear cell (PBMC) samples collected from 20 patients with LDCT-detected lung cancer and 20 matched cancer-free screening volunteers were analyzed by flow cytometry using multiplex panels characterizing both lymphoid and myeloid immune subsets. Data were validated in PBMC from 40 patients with lung cancer and 40 matched controls and in a lung cancer specificity set including 27 subjects with suspicious lung nodules. A qPCR-based gene expression signature was generated resembling selected immune subsets.

RESULTS

Monocytic myeloid-derived suppressor cell (MDSC), polymorphonuclear MDSC, intermediate monocytes and CD8+PD-1+ T cells distinguished patients with lung cancer from controls with AUCs values of 0.94/0.72/0.88 in the training, validation, and lung cancer specificity set, respectively. AUCs raised up to 1.00/0.84/0.92 in subgroup analysis considering only MSC-negative subjects. A 14-immune genes expression signature distinguished patients from controls with AUC values of 0.76 in the validation set and 0.83 in MSC-negative subjects.

CONCLUSIONS

An immune-based classifier can enhance the accuracy of blood testing, thus supporting the contribution of systemic immunity to lung carcinogenesis.

IMPACT

Implementing LDCT screening trials with minimally invasive blood tests could help reduce unnecessary procedures and optimize cost-effectiveness.

RNA-sequencing for transcriptional profiling of whole blood in early stage and metastatic pancreatic cancer patients

We investigated the transcriptional profile of whole blood in early and metastatic stages of pancreatic cancer (PaC) patients to identify potential diagnostic factors for early diagnosis. Blood samples from 18 participants (6 healthy individuals, 6 patients in early stage (I/II) PaC, and 6 patients in metastatic PaC) were analyzed by RNA-sequencing. The expression levels of identified genes were subsequently compared with their expression in pancreatic tumor tissues based on TCGA data reported in UALCAN and GEPIA2 databases. Overall, 331 and 724 genes were identified as differentially expressed genes in early and metastatic stages, respectively. Of these, 146 genes were shared by early and metastatic stages. Upregulation of PTCD3 and UBA52 genes and downregulation of A2M and ARID1B genes in PaC patients were observed from early stage to metastasis. TCGA database showed increasing trend in expression levels of these genes from stage I to IV in pancreatic tumor tissue. Finally, we found that low expression of PTCD3, A2M, and ARID1B genes and high expression of UBA52 gene were positively correlated with PaC patients survival. We identified a four-gene set (PTCD3, UBA52, A2M, and ARID1B) expressed in peripheral blood of early stage and metastatic PaC patients that may be useful for PaC early diagnosis.

Regulated cell death (RCD) in cancer: key pathways and targeted therapies

Regulated cell death (RCD), also well-known as programmed cell death (PCD), refers to the form of cell death that can be regulated by a variety of biomacromolecules, which is distinctive from accidental cell death (ACD). Accumulating evidence has revealed that RCD subroutines are the key features of tumorigenesis, which may ultimately lead to the establishment of different potential therapeutic strategies. Hitherto, targeting the subroutines of RCD with pharmacological small-molecule compounds has been emerging as a promising therapeutic avenue, which has rapidly progressed in many types of human cancers. Thus, in this review, we focus on summarizing not only the key apoptotic and autophagy-dependent cell death signaling pathways, but the crucial pathways of other RCD subroutines, including necroptosis, pyroptosis, ferroptosis, parthanatos, entosis, NETosis and lysosome-dependent cell death (LCD) in cancer. Moreover, we further discuss the current situation of several small-molecule compounds targeting the different RCD subroutines to improve cancer treatment, such as single-target, dual or multiple-target small-molecule compounds, drug combinations, and some new emerging therapeutic strategies that would together shed new light on future directions to attack cancer cell vulnerabilities with small-molecule drugs targeting RCD for therapeutic purposes.

PBMCs: a new source of diagnostic and prognostic biomarkers

There are various types of molecular biomarkers that are derived from distinct starting materials. Although many indirect biomarkers are found in blood, their detection remains a challenging issue because of the high degree of fragmentation, minute quantity and a vast amount of non-specific background. The present review points out the sensitivity and specificity of peripheral blood mononuclear cells (PBMCs) as an intact source of biomarkers in a variety of diseases. Multiple recent studies that have used PBMCs as a source of biomarkers reveal the alteration of mRNAs/microRNAs (miRNAs) signature and methylation profile in many kinds of disorders; for instance, dysregulation of mRNAs/miRNAs in schizophrenia, diabetes and different types of cancers and change in the methylation status of LINE-1 in neoplasms. In conclusion with a strong probability, PBMCs mimic conditions of some tissues which are in contact with them like the tumour cells, hence providing a non-invasive and suitable source of biomarkers.

Poorer survival outcomes in patients with multiple versus single primary melanoma

BACKGROUND

Given equivocal results related to overall survival (OS) for patients with multiple primary melanomas (MPMs) compared with those with single primary melanomas (SPMs) in previous reports, the authors sought to determine whether OS differs between these 2 cohorts in their center using their UPCI-96-99 database. Secondary aims were to assess the differences in recurrence-free survival (RFS). In a subset of patients, transcriptomic profiling of peripheral blood mononuclear cells (PBMCs) was performed to assess disease-associated genes of interest.

METHODS

This retrospective case-controlled study included patients with MPMs and age-, sex-, and stage-matched controls with SPMs at a 1:1 ratio. Cox regression models were used to evaluate the effect of the presence of MPMs on death and recurrence. NanoString PanCancer Immune Profiling was used to assess peripheral blood immune status in patients.

RESULTS

In total, 320 patients were evaluated. The mean patient age was 47 years; 43.8% were male. Patients with MPMs had worse RFS and OS (P = .023 and P = .0019, respectively). The presence of MPMs was associated with an increased risk of death (hazard ratio [HR], 4.52, P = .0006), and increased risk of disease recurrence (HR, 2.17; P = .004) after adjusting for age, sex, and stage. The degree of tumor-infiltrating lymphocytes (TILs) was different between the first melanoma of MPMs and SPMs. Expression of CXCL6 and FOXJ1 was increased in PBMCs isolated from patients with MPMs.

CONCLUSIONS

Patients with MPMs had worse RFS and OS compared with patients with SPMs. Immunologic differences were also observed, including TIL content and expression of CXCL6/FOXJ1 in PBMCs of patients with MPMs, which warrant further investigation.

Selection of RNA-based evaluation methods for tumor microenvironment by comparing with histochemical and flow cytometric analyses in gastric cancer

Understanding the tumor microenvironment (TME) and anti-tumor immune responses in gastric cancer are required for precision immune-oncology. Taking advantage of next-generation sequencing technology, the feasibility and reliability of transcriptome-based TME analysis were investigated. TME of 30 surgically resected gastric cancer tissues was analyzed by RNA-Seq, immunohistochemistry (IHC) and flow cytometry (FCM). RNA-Seq of bulk gastric cancer tissues was computationally analyzed to evaluate TME. Computationally analyzed immune cell composition was validated by comparison with cell densities established by IHC and FCM from the same tumor tissue. Immune cell infiltration and cellular function were also validated with IHC and FCM. Cell proliferation and cell death in the tumor as assessed by RNA-Seq and IHC were compared. Computational tools and gene set analysis for quantifying CD8⁺ T cells, regulatory T cells and B cells, T cell infiltration and functional status, and cell proliferation and cell death status yielded an excellent correlation with IHC and FCM data. Using these validated transcriptome-based analyses, the immunological status of gastric cancer could be classified into immune-rich and immune-poor subtypes. Transcriptome-based TME analysis is feasible and is valuable for further understanding the immunological status of gastric cancer.

Annexin A3, a Calcium-Dependent Phospholipid-Binding Protein: Implication in Cancer

Annexin A3 (ANXA3), also known as lipocortin III and placental anticoagulant protein III, has been reported to be dysregulated in tumor tissues and cancer cell lines, and harbors pronounced diagnostic and prognostic value for certain malignancies, such as breast, prostate, colorectal, lung and liver cancer. Aberrant expression of ANXA3 promotes tumor cell proliferation, invasion, metastasis, angiogenesis, and therapy resistance to multiple chemotherapeutic drugs including platinum-based agents, fluoropyrimidines, cyclophosphamide, doxorubicin, and docetaxel. Genetic alterations on the ANXA3 gene have also been reported to be associated with the propensity to form certain inherited, familial tumors. These diverse functions of ANXA3 in tumors collectively indicate that ANXA3 may serve as an attractive target for novel anticancer therapies and a powerful diagnostic and prognostic biomarker for early tumor detection and population risk screening. In this review, we dissect the role of ANXA3 in cancer in detail.

The calcimedin annexin A3 displays tumor-promoting effect in esophageal squamous cell carcinoma by activating NF-κB signaling

Esophageal squamous cell carcinoma (ESCC) is one of the lethal malignancies commonly found in the eastern world, with overall five-year survival rates less than 25%. The present study aimed to investigate the biological function of annexin A3 (ANXA3) in ESCC cell proliferation. The mRNA and protein levels of ANXA3 in ESCC tissues and cell lines were determined by real-time PCR and Western blot, respectively. Lentiviral transduction was applied to overexpress or reduce ANXA3 expression in ESCC cell lines. The effect of ANXA3 on ESCC cell proliferation was evaluated by cell-counting kit-8 assay in vitro and tumor-bearing animal model in vivo. We found that ANXA3 was substantially upregulated in ESCC tissues compared to adjacent normal tissues as well as ESCC cell lines compared to normal esophageal endothelial cells. Suppression of ANXA3 significantly inhibited ESCC cell proliferation in vitro and tumor growth in vivo. We further revealed that NF-κB was involved in ANXA3-mediated ESCC cell proliferation. Our results suggest that ANXA3 acts as an oncogene in ESCC, and targeting ANXA3 or NF-κB may serve as potential therapeutic strategies for patients with ESCC.

Identifying kinase targets of PPARγ in human breast cancer

Breast cancer is the most common cancer in women. Despite advances in screening women for genetic predisposition to breast cancer and risk stratification, a majority of women carriers remain undetected until they become affected. Thus, there is a need to develop a cost-effective, rapid, sensitive and non-invasive early-stage diagnostic method. Kinases are involved in all fundamental cellular processes and mutations in kinases have been reported as drivers of cancer. PPARγ is a ligand-activated transcription factor that plays important roles in cell proliferation and metabolism. However, the complete set of kinases modulated by PPARγ is still unknown. In this study, we identified human kinases that are potential PPARγ targets and evaluated their differential expression and gene pair correlations in human breast cancer patient dataset TCGA-BRCA. We further confirmed the findings in human breast cancer cell lines MCF7 and SK-BR-3 using a kinome array. We observed that gene pair correlations are lost in tumours as compared to healthy controls and could be used as a supplement strategy for diagnosis and prognosis of breast cancer.

Development of an optimized method for processing peripheral blood mononuclear cells for 1H-nuclear magnetic resonance-based metabolomic profiling

Human peripheral blood mononuclear cells (PBMCs) are part of the innate and adaptive immune system, and form a critical interface between both systems. Studying the metabolic profile of PBMC could provide valuable information about the response to pathogens, toxins or cancer, the detection of drug toxicity, in drug discovery and cell replacement therapy. The primary purpose of this study was to develop an improved processing method for PBMCs metabolomic profiling with nuclear magnetic resonance (NMR) spectroscopy. To this end, an experimental design was applied to develop an alternative method to process PBMCs at low concentrations. The design included the isolation of PBMCs from the whole blood of four different volunteers, of whom 27 cell samples were processed by two different techniques for quenching and extraction of metabolites: a traditional one using organic solvents and an alternative one employing a high-intensity ultrasound probe, the latter with a variation that includes the use of deproteinizing filters. Finally, all the samples were characterized by 1H-NMR and the metabolomic profiles were compared by the method. As a result, two new methods for PBMCs processing, called Ultrasound Method (UM) and Ultrasound and Ultrafiltration Method (UUM), are described and compared to the Folch Method (FM), which is the standard protocol for extracting metabolites from cell samples. We found that UM and UUM were superior to FM in terms of sensitivity, processing time, spectrum quality, amount of identifiable, quantifiable metabolites and reproducibility.

Identification of potential biomarkers of peripheral blood mononuclear cell in hepatocellular carcinoma using bioinformatic analysis: A protocol for systematic review and meta-analysis

BACKGROUND

Hepatocellular carcinoma (HCC) is the cause of an overwhelming number of cancer-related deaths across the world. Developing precise and noninvasive biomarkers is critical for diagnosing HCC. Our research was designed to explore potentially useful biomarkers of host peripheral blood mononuclear cell (PBMC) in HCC by integrating comprehensive bioinformatic analysis.

METHODS

Gene expression data of PBMC in both healthy individuals and patients with HCC were extracted from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to annotate the function of DEGs. Protein-protein interaction analysis was performed to screen the hub genes from DEGs. cBioportal database analysis was performed to assess the prognostic significance of hub genes. The Cancer Cell Line Encyclopedia (CCLE) and The Human Protein Atlas (HPA) database analyses were performed to confirm the expression levels of the hub genes in HCC cells and tissue.

RESULTS

A total of 95 DEGs were screened. Results of the GO analysis revealed that DEGs were primarily involved in platelet degranulation, cytoplasm, and protein binding. Results of the KEGG analysis indicated that DEGs were primarily enriched in focal adhesion. Five genes, namely, myosin light chain kinase (MYLK), interleukin 1 beta (IL1B), phospholipase D1 (PLD1), cortactin (CTTN), and moesin (MSN), were identified as hub genes. A search in the CCLE and HPA database showed that the expression levels of these hub genes were remarkably increased in the HCC samples. Survival analysis revealed that the overexpression of MYLK, IL1B, and PLD1 may have a significant effect on HCC survival. The aberrant high expression levels of MYLK, IL1B, and PLD1 strongly indicated worse prognosis in patients with HCC.

CONCLUSIONS

The identified hub genes may be closely linked with HCC tumorigenicity and may act as potentially useful biomarkers for the prognostic prediction of HCC in PBMC samples.

33-kDa ANXA3 isoform contributes to hepatocarcinogenesis via modulating ERK, PI3K/Akt-HIF and intrinsic apoptosis pathways

Introduction

As a member of annexin family proteins, annexin A3 (ANXA3) has 36-kDa and 33-kDa isoforms. ANXA3 plays crucial roles in the tumorigenesis, aggressiveness and drug-resistance of cancers. However, previous studies mainly focused on the role of total ANXA3 in cancers without distinguishing the distinction between the two isoforms, the role of 33-kDa ANXA3 in cancer remains unclear.

Objectives

Current work aimed to investigate the function and regulation mechanism of 33-kDa ANXA3 in hepatocarcinoma.

Methods

The expressions of ANXA3, CRKL, Rac1, c-Myc and pAkt were analyzed in hepatocarcinoma specimens by Western blotting. The biological function of 33-kDa ANXA3 in the growth, metastasis, apoptosis, angiogenesis, chemoresistance of hepatocarcinoma cells with the underlying molecular mechanism were investigated using gain-of-function strategy in vitro or in vivo.

Results

33-kDa ANXA3 was remarkably upregulated in tumor tissues compared with corresponding normal liver tissues of hepatocarcinoma patients. Its stable knockdown decreased the in vivo tumor growing velocity and malignancy of hepatocarcinoma HepG2 cells transplanted in nude mice. The in vitro experimental results indicated 33-kDa ANXA3 knockdown suppressed the proliferation, colony forming, migration and invasion abilities of HepG2 cells through downregulating CRKL, Rap1b, Rac1, pMEK, pERK2 and c-Myc in ERK pathway; inhibited angiogenesisability of HepG2 cells through inactivating PI3K/Akt-HIF pathway; induced apoptosis and enhanced chemoresistance of HepG2 cells through increasing Bax/decreasing Bcl-2 expressions and inactivating caspase 9/caspase 3 in intrinsic apoptosis pathway. Accordingly, CRKL, Rac1, c-Myc and pAkt were also upregulated in hepatocarcinoma patients ’ tumor tissues compared with corresponding normal liver tissues.

Conclusions

The overexpression of 33-kDa ANXA3 is involved in the clinical progression of hepatocarcinoma and in the malignancy, angiogenesis and apoptosis of hepatocarcinoma cells. It is of potential use in hepatocarcinoma diagnosis and treatment.

Dynamic edge-based biomarker non-invasively predicts hepatocellular carcinoma with hepatitis B virus infection for individual patients based on blood testing

Hepatitis B virus (HBV)-induced hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths in Asia and Africa. Developing effective and non-invasive biomarkers of HCC for individual patients remains an urgent task for early diagnosis and convenient monitoring. Analyzing the transcriptomic profiles of peripheral blood mononuclear cells from both healthy donors and patients with chronic HBV infection in different states (i.e. HBV carrier, chronic hepatitis B, cirrhosis, and HCC), we identified a set of 19 candidate genes according to our algorithm of dynamic network biomarkers. These genes can both characterize different stages during HCC progression and identify cirrhosis as the critical transition stage before carcinogenesis. The interaction effects (i.e. co-expressions) of candidate genes were used to build an accurate prediction model: the so-called edge-based biomarker. Considering the convenience and robustness of biomarkers in clinical applications, we performed functional analysis, validated candidate genes in other independent samples of our collected cohort, and finally selected COL5A1, HLA-DQB1, MMP2, and CDK4 to build edge panel as prediction models. We demonstrated that the edge panel had great performance in both diagnosis and prognosis in terms of precision and specificity for HCC, especially for patients with alpha-fetoprotein-negative HCC. Our study not only provides a novel edge-based biomarker for non-invasive and effective diagnosis of HBV-associated HCC to each individual patient but also introduces a new way to integrate the interaction terms of individual molecules for clinical diagnosis and prognosis from the network and dynamics perspectives.

GPNMB contributes to a vicious circle for chronic obstructive pulmonary disease

Osteoporosis (OP) is significant and debilitating comorbidity of chronic obstructive pulmonary disease (COPD). We hypothesize that genetic variance identified with OP may also play roles in COPD. We have conducted a large-scale relation data analysis to explore the genes implicated with either OP or COPD, or both. Each gene linked to OP but not to COPD was further explored in a mega-analysis and partial mega-analysis of 15 independently collected COPD RNA expression datasets, followed by gene set enrichment analysis (GSEA) and literature-based pathway analysis to explore their functional linked to COPD. A multiple linear regression (MLR) model was built to study the possible influence of sample size, population region, and study date on the gene expression data in COPD. At the first step of the analysis, we have identified 918 genes associated with COPD, 581 with OP, and a significant overlap (P<2.30e-140; 210 overlapped genes). Partial mega-analysis showed that, one OP gene, GPNMB presented significantly increased expression in COPD patients (P-value = 0.0018; log fold change = 0.83). GPNMB was enriched in multiple COPD pathways and plays roles as a gene hub formulating multiple vicious COPD pathways included gene MMP9 and MYC. GPNMB could be a novel gene that plays roles in both COPD and OP. Partial mega-analysis is valuable in identify case-specific genes for COPD.

Identification of hub genes in peripheral blood mononuclear cells for the diagnosis of hepatocellular carcinoma using a weighted gene co-expression network analysis

Human hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive tract that is prevalent worldwide. Improving diagnosis methods for HCC helps to improve patient survival rate. The present study aimed to identify novel HCC biomarkers for the diagnosis of HCC through analyzing gene changes on peripheral blood mononuclear cells (PBMCs) and verifying these in additional samples. The gene expression profiles GSE49515 (including 10 specimens from normal patients and 10 specimens from patients with HCC) and GSE58208 (including 5 specimens from normal patients and 10 specimens from patients with HCC) were downloaded from the online Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) in PBMCs between healthy controls and patients with HCC were identified using R software. A total of 935 DEGs, including 686 upregulated DEGs and 249 downregulated DEGs, were identified in the present study. In order to identify any internal associations, these DEGs were used to construct weighted gene co-expression networks (WGCNA). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of genes in each module were conducted using the online database DAVID. Furthermore, hub genes with high module membership were identified in a co-expression network and receiver operating characteristic curves were used to verify the diagnostic values of these eight hub genes. Furthermore, the expression and diagnosis value of the eight hub genes were also verified in additional samples. The results of the present study suggested that secreted protein acidic and cysteine rich(SPARC), transmembrane protein 40 (TMEM40), solute carrier family 25 member 44, formyl peptide receptor 2 (FPR2), complement C8 β chain, N-myristoyltransferase 1, protein kinase C δ(PRKCD) and protein phosphatase, Mg²⁺/Mn²⁺ dependent 1M(PPM1M) were hub genes. SPARC, TMEM40, FPR2, PRKCD and PPM1M had prominent diagnostic value according to the results from the GEO data and the additional samples. The present study demonstrated that these hub genes may help to improve the diagnosis of HCC.

TFPI2 and NDRG4 gene promoter methylation analysis in peripheral blood mononuclear cells are novel epigenetic noninvasive biomarkers for colorectal cancer diagnosis

BACKGROUND

As a result of the growing prevalence of colorectal cancer (CRC), new screening and early detection methods are required. Among the novel biomarkers, DNA methylation has emerged as a high-potential diagnosis/screening molecular marker. The present study aimed to assess non-invasive early diagnosis of CRC by examining promoter methylation of TFPI2 and NDRG4 genes in peripheral blood mononuclear cells (PBMCs).

METHODS

Fifty CRC patients and 50 normal controls were recruited to the present study. Quantitative methylation of the promoter region of the TFPI2 and NDRG4 genes was analyzed in DNA extracted from PBMCs of all cases and control subjects using a methylation-quantification endonuclease-resistant DNA (MethyQESD) method.

RESULTS

The sensitivity and specificity of the TFPI2 gene for the diagnosis of CRC was 88% and 92%, respectively, and, for the NDRG4 gene, it was 86% and 92%, respectively. The methylation range for the TFPI2 gene was 43.93% and 11.56% in patients and controls, respectively, and, for the NDRG4 gene, it was 38.8% in CRC patients and 12.23% in healthy controls (p < 0.001). In addition, we observed that a higher percentage of methylation was correlated with the higher stage of CRC.

CONCLUSIONS

The results of the present study reveal that PBMCs are reliable sources of methylation analysis for CRC screening. Furthermore, the TFPI2 and NDRG4 genes provide sufficiently high sensitivity and specificity to be nominated for use in a novel noninvasive CRC screening method in PBMCs.

Comprehensive Benchmarking and Integration of Tumor Microenvironment Cell Estimation Methods

Various computational approaches have been developed for estimating the relative abundance of different cell types in the tumor microenvironment (TME) using bulk tumor RNA data. However, a comprehensive comparison across diverse datasets that objectively evaluates the performance of these approaches has not been conducted. Here, we benchmarked seven widely used tools and gene sets and introduced ConsensusTME, a method that integrates gene sets from all the other methods for relative TME cell estimation of 18 cell types. We collected a comprehensive benchmark dataset consisting of pan-cancer data (DNA-derived purity, leukocyte methylation, and hematoxylin and eosin-derived lymphocyte counts) and cell-specific benchmark datasets (peripheral blood cells and tumor tissues). Although none of the methods outperformed others in every benchmark, ConsensusTME ranked top three in all cancer-related benchmarks and was the best performing tool overall. We provide a Web resource to interactively explore the benchmark results and an objective evaluation to help researchers select the most robust and accurate method to further investigate the role of the TME in cancer (www.consensusTME.org). SIGNIFICANCE: This work shows an independent and comprehensive benchmarking of recently developed and widely used tumor microenvironment cell estimation methods based on bulk expression data and integrates the tools into a consensus approach.

Two Distinct Subtypes Revealed in Blood Transcriptome of Breast Cancer Patients With an Unsupervised Analysis

Background: Breast cancer (BC) is a highly heterogeneous cancer. The interaction between immune system and BC is complex, widespread yet unclear. In this study, we aimed to reveal the heterogeneity of host systemic immune response to BC and understand the possible mechanisms that may drive the heterogeneity using transcriptomic data from peripheral blood mononuclear cells (PBMCs). Methods: Transcriptome-wide gene expressions of PBMCs in 33 BC patients were generated by RNA sequencing. An unsupervised clustering algorithm was employed to discover PBMC transcriptome subtypes among BC patients. Association analysis between PBMC subtypes and age, clinical stage, abundance of immune cells, and other clinical factors was performed to understand the underlying biological processes that may drive this heterogeneity. Immune gene signature identification and in silico survival analysis were performed to investigate the potential clinical implications of these PBMC subtypes. The findings were validated using the whole blood transcriptomes of an independent cohort. Results: We observed that established BC subtypes were not associated with PBMC gene expression profiles. Instead, we discovered and validated two new BC subtypes using PBMC transcriptome, which have distinct immune cell proportions, especially for lymphocytes (P = 5.22 × 10^-12) and neutrophils (P = 1.13 × 10^-14). Enrichment analysis of differentially expressed genes revealed that these two subtypes had distinct patterns of immune responses, including osteoclast differentiation and interleukin-10 signaling pathway. We developed two immune gene signatures that can differentiate these two BC PBMC subtypes. Further analysis suggested they had the ability to predict the clinical outcome of BC patients. Conclusions: PBMC transcriptome profiles can classify BC patients into two distinct subtypes. These two subtypes are mainly shaped by different immune cell abundance, which may have implications on clinical outcomes.

Ibrutinib as a potential therapeutic option for HER2 overexpressing breast cancer - the role of STAT3 and p21

Treatment response rates to current anticancer therapies for HER2 overexpressing breast cancer are limited and are associated with severe adverse drug reactions. Tyrosine kinases perform crucial roles in cellular processes by mediating cell signalling cascades. Ibrutinib is a recently approved Tyrosine Kinase Inhibitor (TKI) that has been shown be an effective therapeutic option for HER2 overexpressing breast cancer. The molecular mechanisms, pathways, or genes that are modulated by ibrutinib and the mechanism of action of ibrutinib in HER2 overexpressing breast cancer remain obscure. In this study, we have performed a kinome array analysis of ibrutinib treatment in two HER2 overexpressing breast cancer cell lines. Our analysis shows that ibrutinib induces changes in nuclear morphology and causes apoptosis via caspase-dependent extrinsic apoptosis pathway with the activation of caspases-8, caspase-3, and cleavage of PARP1. We further show that phosphorylated STAT3^Y705 is upregulated and phosphorylated p21^T145 is downregulated upon ibrutinib treatment. We propose that STAT3 upregulation is a passive response as a result of induction of DNA damage and downregulation of phosphorylated p21 is promoting cell cycle arrest and apoptosis in the two HER2 overexpressing cell lines. These results suggest that inhibitors of STAT3 phosphorylation may be potential options for combination therapy to help increase the efficacy of ibrutinib against HER2-overexpressing tumors.

Clinical Translatability of "Identified" Circulating miRNAs for Diagnosing Breast Cancer: Overview and Update

The effective management of patients with breast cancer (BC) depends on the early diagnosis of the disease. Currently, BC diagnosis is based on diagnostic imaging and biopsy, while the use of non-invasive circulating biomarkers for diagnosis remains an unmet need. Among the plethora of proposed non-invasive biomarkers, circulating microRNAs (miRNAs) have been considered promising diagnostic molecules because they are very stable in biological fluids and easily detectable. Although the discovery of miRNAs has opened a new avenue for their clinical application, the clinical translatability of these molecules remains unclear. This review analyses the role of circulating miRNAs as BC diagnostic biomarkers and focuses on two essential requirements to evaluate their clinical validity: i) Specificity and ii) consistent expression between the blood and tissue. These two issues were analyzed in depth using the Human miRNA Disease Database (HMDD v3.0) and the free search engine PubMed. One hundred and sixty three BC-associated miRNAs were selected and analyzed for their specificity among all human pathologies that shared deregulation (291) and consistent expression in the bloodstream and the tissue. In addition, we provide an overview of the current clinical trials examining miRNAs in BC. In conclusion, we highlight pitfalls in the translatability of circulating miRNAs into clinical practice due to the lack of specificity and a consistent expression pattern between the tissue and blood.

Carbonic anhydrases as disease markers

INTRODUCTION

The physiologic importance of fast CO₂/HCO₃^- interconversion in various tissues requires the presence of carbonic anhydrase (CA, EC 4.2.1.1). Fourteen CA isozymes are present in humans, all of them being used as biomarkers.

AREAS COVERED

A great number of patents and articles were focused on the use of CA isozymes as biomarkers for various diseases and syndromes in the recent years, in an ascending trend over the last decade. The review highlights the most important studies related with each isozyme and covers the most recent patent literature.

EXPERT OPINION

The CAs biomarker research area expanded significantly in recent years, shifting from the predominant use of CA IX and CA XII in cancer diagnostic, staging, and prognosis towards a wider use of CA isozymes as disease biomarkers. CA isozymes are currently used either alone, in tandem with other CA isozymes and/or in combination with other proteins for the detection, staging, and prognosis of a huge repertoire of human dysfunctions and diseases, ranging from mild transformation of the normal tissues to extreme shifts in tissue organization and function. The techniques used for their detection/quantitation and the state-of-the-art in each clinical application are presented through relevant clinical examples and corresponding statistical data.

Gene expression analysis in peripheral blood cells of patients with hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC): identification of NRF2 pathway activation

Hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC) is a very rare disease that is inherited in an autosomal dominant manner. Affected patients may develop from cutaneous and uterine leiomyomas to type 2 papillary renal cell carcinoma (Schmidt and Linehan, Int J Nephrol Renovasc Dis 7:253-260, 2014). HLRCC is caused by germline mutations in the FH gene, which produces the fumarate hydratase protein that participates in the tricarboxylic acid cycle during the conversion of fumarate to malate. In FH-deficient cells, high concentrations of fumarate lead to a series of intricate events, which seem to be responsible for the malignant transformation (Yang et al., J Clin Invest 123(9):3652-3658, 2013) (Bardella et al., J Pathol 225(1):4-11, 2011). Among these events, one that is gaining attention is the pathological activation of the nuclear factor erythroid 2-related factor 2 (NRF2) pathway, which has been found in several types of cancer and is implicated in the expression of genes associated with antioxidant responses (Linehan and Rouault, Clin Cancer Res 19(13):3345-3352, 2013). In this article, we present the results of a gene expression analysis performed on peripheral blood cells from patients with HLRCC syndrome, where upregulation of numerous NRF2 targets and the differential expression of two key genes, Jun dimerization protein 2 (JDP2) and Phosphoglycerate mutase family member 5 (PGAM5), which are involved in the control of this pathway, was observed.

Phenotypic and functional stability of leukocytes from human peripheral blood samples: considerations for the design of immunological studies

Background

Human peripheral blood mononuclear cells (PBMCs) are extensively used for research of immune cell functions, identification of biomarkers and development of diagnostics and therapeutics for human diseases, among others. The assumption that “old blood samples” are not appropriate for isolation of PBMCs for functional assays has been a dogma in the scientific community. However, partial data on the impact of time after phlebotomy on the quality and stability of human PBMCs preparations impairs the design of studies in which time-controlled blood sampling is challenging such as field studies involving multiple sampling centers/sites. In this study, we evaluated the effect of time after phlebotomy over a 24 h time course, on the stability of human blood leukocytes used for immunological analyses. Blood samples from eight healthy adult volunteers were obtained and divided into four aliquots, each of which was left in gentle agitation at room temperature (24 °C) for 2 h (control), 7 h, 12 h and 24 h post phlebotomy. All samples at each time point were independently processed for quantification of mononuclear cell subpopulations, cellular viability, gene expression and cytokine secretion.

Results

A 24 h time delay in blood sample processing did not affect the viability of PBMCs. However, a significantly lower frequency of CD3+ T cells (p < 0.05) and increased LPS-induced CXCL10 secretion were observed at 12 h post-phlebotomy. Alterations in TNFα, CCL8, CCR2 and CXCL10 gene expression were found as early as 7 h after blood sample procurement.

Conclusions

These data reveal previously unrecognized early time-points for sample processing control, and provide an assay-specific time reference for the design of studies that involve immunological analyses of human blood samples.

Electronic supplementary material

The online version of this article (10.1186/s12865-019-0286-z) contains supplementary material, which is available to authorized users.

Gene expression profile of peripheral blood mononuclear cells may contribute to the identification and immunological classification of breast cancer patients

BACKGROUND

It has been reported that the gene expression profile of peripheral blood mononuclear cells (PBMCs) exhibits a unique gene expression signature in several types of cancer. In this study, we aimed to explore the breast cancer patient-specific gene expression profile of PBMCs and discuss immunological insight on host antitumor immune responses.

METHODS

We comprehensively analyzed the gene expression of PBMCs by RNA sequencing in the breast cancer patients as compared to that of healthy volunteers (HVs). Pathway enrichment analysis was performed on MetaCore^tm to search the molecular pathways associated with the gene expression profile of PBMCs in cancer patients compared with HVs.

RESULTS

We found a significant unique gene expression signature, such as the Toll-like receptor (TLR) 3- and TLR4-induced Toll/interleukin-1 receptor domain-containing adapter molecule 1 (TICAM1)-specific signaling pathway in the breast cancer patients as compared to that of healthy volunteers. Distinctive immunological gene expression profiles also showed the possibility of classifying breast cancer patients into subgroups such as T-cell inhibitory and monocyte-activating groups independent of known phenotypes of breast cancer.

CONCLUSIONS

These preliminary findings suggest that evaluation of gene expression patterns of PBMCs might be both a less invasive diagnostic procedure and a useful way to reveal immunological insight of breast cancer, including biomarkers for cancer immunotherapy, such as immune checkpoint inhibitor therapy.

Gene expression signature for detection of gastric cancer in peripheral blood

Gastric cancer (stomach cancer) is the fifth most common malignancy and the third leading cause of cancer-associated mortality worldwide. Identifying gastric cancer patients at an early and curable stage of the disease is essential if mortality rates for this disease are to decrease. A non-invasive blood-based test that is an indicator of gastric cancer risk would likely be of benefit in identifying gastric cancer patients at an early stage, and such a test may enhance clinical decision making. This study identified a four-gene expression signature in peripheral blood samples associated with gastric cancer. A total of 216 blood samples were collected, including those from 36 gastric cancer patients, 55 healthy controls and 125 patients with other carcinomas, and gene expression profiles were examined using an Affymetrix Gene Profiling microarray. Blood gene expression profiles were compared between patients with stomach cancer, healthy controls and patients affected with other malignancies. A four-gene panel was identified comprising purine-rich element binding protein B, structural maintenance of chromosomes 1A, DENN/MADD domain containing 1B and programmed cell death 4. The four-gene panel discriminated gastric cancer with an area under the receiver-operating-characteristic curve of 0.99, an accuracy of 95%, sensitivity of 92% and specificity of 96%. The non-invasive nature of the blood test, together with the relatively high accuracy of the four-gene panel may assist physicians in gastric cancer screening decision making.

Natural killer cells and their therapeutic role in pancreatic cancer: A systematic review

Pancreatic cancer is among the three deadliest cancers worldwide with the lowest 5-year survival of all cancers. Despite all efforts, therapeutic improvements have barely been made over the last decade. Even recent highly promising targeted and immunotherapeutic approaches did not live up to their expectations. Therefore, other horizons have to be explored. Natural Killer (NK) cells are gaining more and more interest as a highly attractive target for cancer immunotherapies, both as pharmaceutical target and for cell therapies. In this systematic review we summarise the pathophysiological adaptions of NK cells in pancreatic cancer and highlight possible (future) therapeutic NK cell-related targets. Furthermore, an extensive overview of recent therapeutic approaches with an effect on NK cells is given, including cytokine-based, viro- and bacteriotherapy and cell therapy. We also discuss ongoing clinical trials that might influence NK cells. In conclusion, although several issues regarding NK cells in pancreatic cancer remain unsolved and need further investigation, extensive evidence is already provided that support NK cell oriented approaches in pancreatic cancer.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses (‘gained’ genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Overexpression of ANXA3 is an independent prognostic indicator in gastric cancer and its depletion suppresses cell proliferation and tumor growth

Background

Gastric cancer (GC) is one of the most common malignancies worldwide. Tumour metastasis is one of the leading causes of death in GC patients. This study aims to investigate the significance of ANXA3 expression and the mechanism by which ANXA3 is involved in the epithelial–mensenchymal transition (EMT) of gastric cancer cells.

Results

Our results confirmed that ANXA3 was high expression at the mRNA and protein level in GC cancer tissues and the majority of GC cell lines. In clinicopathological analysis, we found that increased expression of ANXA3 in tumors was closely associated with a poor prognosis. Xogenous ANXA3 transduction promoted proliferation, clone formation, migration, and invasion. Small interfering RNA silencing of ANXA3 inhibited these processes. Silence of ANXA3 inhibited tumorigenicity in vivo. Additionally, ANXA3 expression is associated with the epithelial–mesenchymal transition.

Methods

Firstly, we investigated the ANXA3 expression on mRNA and protein level with RT-PCR and Western blot. Secondly, 183 GC patients tissues were used the to evaluate the clinicopathological characteristics and prognosis through immunohistochemistry. Furthermore, The functions of ANXA3 were analyzed in the cell proliferation, Colony Formation, migration, invasion and apoptosis of GC cell lines.

Conclusions

Our research suggests that ANXA3 plays important roles in gastric cancer carcinogenesis and metastasis, and provides a valuable prognostic marker and potential target for treatment of gastric cancer patients.

Proteomic Differences in Feline Fibrosarcomas Grown Using Doxorubicin-Sensitive and -Resistant Cell Lines in the Chick Embryo Model

Proteomic analyses are rapid and powerful tools that are used to increase the understanding of cancer pathogenesis, discover cancer biomarkers and predictive markers, and select and monitor novel targets for cancer therapy. Feline injection-site sarcomas (FISS) are aggressive skin tumours with high recurrence rates, despite treatment with surgery, radiotherapy, and chemotherapy. Doxorubicin is a drug of choice for soft tissue sarcomas, including FISS. However, multidrug resistance is one of the major causes of chemotherapy failure. The main aim of the present study was to identify proteins that differentiate doxorubicin-resistant from doxorubicin-sensitive FISS using two-dimensional gel electrophoresis (2DE), followed by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) analysis. Using the three-dimensional (3D) preclinical in ovo model, which resembles features of spontaneous fibrosarcomas, three significantly (p ≤ 0.05) differentially expressed proteins were identified in tumours grown from doxorubicin-resistant fibrosarcoma cell lines (FFS1 and FFS3) in comparison to the doxorubicin-sensitive one (FFS5): Annexin A5 (ANXA5), Annexin A3 (ANXA3), and meiosis-specific nuclear structural protein 1 (MNS1). Moreover, nine other proteins were significantly differentially expressed in tumours grown from the high doxorubicin-resistant cell line (FFS1) in comparison to sensitive one (FFS5). This study may be the first proteomic fingerprinting of FISS reported, identifying potential candidates for specific predictive biomarkers and research targets for doxorubicin-resistant FISS.

Integrating Circulating Immunological and Sputum Biomarkers for the Early Detection of Lung Cancer

We have demonstrated that assessments of microRNA (miRNA) expressions in circulating peripheral blood mononucleated cell (PBMC) and sputum specimens, respectively, may help diagnose lung cancer. To assess the individual and combined analysis of the miRNAs across the different body fluids for lung cancer early detection, we analyse a panel of 3 sputum miRNAs (miRs-21, 31, and 210) and a panel of 2 PBMC miRNAs (miRs-19b-3p and 29b-3p) in a discovery cohort of 68 patients with lung cancer and 66 cancer-free smokers. We find that integrating 2 sputum miRNAs (miRs-31 and 210) and 1 PBMC miRNA (miR-19b-3p) has higher sensitivity (86.8%) and specificity (92.4%) compared with the individual panels. The synergistic value of the integrated panel of 3 biomarkers is confirmed in a validation cohort, independent of stage and histological type of lung cancer, and patients' age, sex, and ethnicity. Integrating circulating immunological and sputum biomarkers could improve the early detection of lung cancer.

Perspectives on Systems Modeling of Human Peripheral Blood Mononuclear Cells

Human peripheral blood mononuclear cells (PBMCs) are the key drivers of the immune responses. These cells undergo activation, proliferation and differentiation into various subsets. During these processes they initiate metabolic reprogramming, which is coordinated by specific gene and protein activities. PBMCs as a model system have been widely used to study metabolic and autoimmune diseases. Herein we review various omics and systems-based approaches such as transcriptomics, epigenomics, proteomics, and metabolomics as applied to PBMCs, particularly T helper subsets, that unveiled disease markers and the underlying mechanisms. We also discuss and emphasize several aspects of T cell metabolic modeling in healthy and disease states using genome-scale metabolic models.

Association between preoperative peripheral blood mononuclear cell gene expression profiles, early postoperative organ function recovery potential and long-term survival in advanced heart failure patients undergoing mechanical circulatory support

BACKGROUND

Multiorgan dysfunction syndrome contributes to adverse outcomes in advanced heart failure (AdHF) patients after mechanical circulatory support (MCS) implantation and is associated with aberrant leukocyte activity. We tested the hypothesis that preoperative peripheral blood mononuclear cell (PBMC) gene expression profiles (GEP) can predict early postoperative improvement or non-improvement in patients undergoing MCS implantation. We believe this information may be useful in developing prognostic biomarkers.

METHODS & DESIGN

We conducted a study with 29 patients undergoing MCS-surgery in a tertiary academic medical center from 2012 to 2014. PBMC samples were collected one day before surgery (day -1). Clinical data was collected on day -1 and day 8 postoperatively. Patients were classified by Sequential Organ Failure Assessment score and Model of End-stage Liver Disease Except INR score (measured eight days after surgery): Group I = improving (both scores improved from day -1 to day 8, n = 17) and Group II = not improving (either one or both scores did not improve from day -1 to day 8, n = 12). RNA-sequencing was performed on purified mRNA and analyzed using Next Generation Sequencing Strand. Differentially expressed genes (DEGs) were identified by Mann-Whitney test with Benjamini-Hochberg correction. Preoperative DEGs were used to construct a support vector machine algorithm to predict Group I vs. Group II membership.

RESULTS

Out of 28 MCS-surgery patients alive 8 days postoperatively, one-year survival was 88% in Group I and 27% in Group II. We identified 28 preoperative DEGs between Group I and II, with an average 93% prediction accuracy. Out of 105 DEGs identified preoperatively between year 1 survivors and non-survivors, 12 genes overlapped with the 28 predictive genes.

CONCLUSIONS

In AdHF patients following MCS implantation, preoperative PBMC-GEP predicts early changes in organ function scores and correlates with long-term outcomes. Therefore, gene expression lends itself to outcome prediction and warrants further studies in larger longitudinal cohorts.

Tumor-Suppressing Effect of Silencing of Annexin A3 Expression in Breast Cancer

INTRODUCTION

Annexin A3 (ANXA3) participates in various tumor-associated biological processes, including tumor initiation, progression, and metastasis. The present study was designed to investigate the expression and function of ANXA3 in breast cancer cells.

MATERIALS AND METHODS

Annexin A3 protein expression in breast cancer cell lines was evaluated using Western blot analysis. ANXA3 expression in MDA-MB 231 breast cancer cells was silenced by RNA interference, and the effects of RNA silencing on cell proliferation, colony forming ability, wound-healing, and invasiveness were evaluated. Levels of ANXA3 expression in 30 primary breast cancers were assayed using immunohistochemistry and correlated with patient survival.

RESULTS

Levels of ANXA3 expression were higher in the basal subtype of breast cancer cells, such as MDA-MB 231, HCC-70, and HCC-1954 cells, than in other subtypes. ANXA3 silencing inhibited the activities of MDA-MB 231 and HCC-1954 cells, including their proliferation, invasion across transwell membranes, and wound-healing and colony forming abilities. ANXA3 small interfering RNA (siRNA) also reduced the expression of cycle-dependent kinase protein and increased the expression of E2F1 and p27 proteins compared with control siRNA. Expression of ANXA3 was closely correlated with tumor size, with higher ANXA3 expression associated with reduced disease-free survival in breast cancer patients.

CONCLUSION

These findings indicate that ANXA3 is associated with the natural progression of breast cancer and might be a potential prognostic marker of patient survival.

Whole Blood mRNA Expression-Based Prognosis of Metastatic Renal Cell Carcinoma

The Memorial Sloan Kettering Cancer Center (MSKCC) prognostic score is based on clinical parameters. We analyzed whole blood mRNA expression in metastatic clear cell renal cell carcinoma (mCCRCC) patients and compared it to the MSKCC score for predicting overall survival. In a discovery set of 19 patients with mRCC, we performed whole transcriptome RNA sequencing and selected eighteen candidate genes for further evaluation based on associations with overall survival and statistical significance. In an independent validation of set of 47 patients with mCCRCC, transcript expression of the 18 candidate genes were quantified using a customized NanoString probeset. Cox regression multivariate analysis confirmed that two of the candidate genes were significantly associated with overall survival. Higher expression of BAG1 [hazard ratio (HR) of 0.14, p < 0.0001, 95% confidence interval (CI) 0.04–0.36] and NOP56 (HR 0.13, p < 0.0001, 95% CI 0.05–0.34) were associated with better prognosis. A prognostic model incorporating expression of BAG1 and NOP56 into the MSKCC score improved prognostication significantly over a model using the MSKCC prognostic score only (p < 0.0001). Prognostic value of using whole blood mRNA gene profiling in mCCRCC is feasible and should be prospectively confirmed in larger studies.

Retinoid X receptor suppresses a metastasis-promoting transcriptional program in myeloid cells via a ligand-insensitive mechanism

Retinoid X receptor (RXR) regulates several key functions in myeloid cells, including inflammatory responses, phagocytosis, chemokine secretion, and proangiogenic activity. Its importance, however, in tumor-associated myeloid cells is unknown. In this study, we demonstrate that deletion of RXR in myeloid cells enhances lung metastasis formation while not affecting primary tumor growth. We show that RXR deficiency leads to transcriptomic changes in the lung myeloid compartment characterized by increased expression of prometastatic genes, including important determinants of premetastatic niche formation. Accordingly, RXR-deficient myeloid cells are more efficient in promoting cancer cell migration and invasion. Our results suggest that the repressive activity of RXR on prometastatic genes is mediated primarily through direct DNA binding of the receptor along with nuclear receptor corepressor (NCoR) and silencing mediator of retinoic acid and thyroid hormone receptor (SMRT) corepressors and is largely unresponsive to ligand activation. In addition, we found that expression and transcriptional activity of RXRα is down-modulated in peripheral blood mononuclear cells of patients with lung cancer, particularly in advanced and metastatic disease. Overall, our results identify RXR as a regulator in the myeloid cell-assisted metastatic process and establish lipid-sensing nuclear receptors in the microenvironmental regulation of tumor progression.

Molecular characterization of breast cancer cell lines through multiple omic approaches

BACKGROUND

Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated.

METHODS

We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer.

RESULTS

The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated in common or unique ways.

CONCLUSIONS

These two new kinase or "Kin-OMIC" analyses add another dimension of important data about these frequently used breast cancer cell lines. This will assist researchers in selecting the most appropriate cell lines to use for breast cancer studies and provide context for the interpretation of the emerging results.

Annexin A3 as a Prognostic Biomarker for Breast Cancer: A Retrospective Study

To validate the correlation between ANXA3 expression and prognosis in breast cancer, a retrospective study encompassing 309 breast cancer patients was performed. The expression of ANXA3 was determined by the immunohistochemical examination of tissue sections by the Max Vision™ method. The ANXA3 levels in the patient samples were validated for the prognosis based on age, menopause status, tumor size, tumor node, metastasis stage, the number of lymphatic metastases, oncology grade, and molecular subtyping. An elevated expression of ANXA3 was detected in breast cancer samples, compared to adjacent tissue samples, and significant correlation depending on the number of lymphatic metastases (P = 0.001) and histological grade (P = 0.004) was observed. The number of lymphatic metastases and ANXA3 expression were identified as independent risk factors affecting the disease-free survival and overall survival. Significantly (P < 0.002) higher level of ANXA3 was detected in triple-negative breast cancer compared to other subtypes. There was no significant (P > 0.05) change in the expression of ANXA3 with respect to age, menopausal status, tumor size, and clinical stage. The findings implicate the expression of ANXA3 with the natural progression of breast cancer and associate it with increased lymphatic metastasis. The study validates the use of ANXA3 as a potential prognosis biomarker for breast cancer.

A Prediction Model Based on Biomarkers and Clinical Characteristics for Detection of Lung Cancer in Pulmonary Nodules

Lung cancer early detection by low-dose computed tomography (LDCT) can reduce the mortality. However, LDCT increases the number of indeterminate pulmonary nodules (PNs), whereas 95% of the PNs are ultimately false positives. Modalities for specifically distinguishing between malignant and benign PNs are urgently needed. We previously identified a panel of peripheral blood mononucleated cell (PBMC)-miRNA (miRs-19b-3p and -29b-3p) biomarkers for lung cancer. This study aimed to evaluate efficacy of integrating biomarkers and clinical and radiological characteristics of smokers for differentiating malignant from benign PNs. We analyzed expression of 2 miRNAs (miRs-19b-3p and -29b-3p) in PBMCs of a training set of 137 individuals with PNs. We used multivariate logistic regression analysis to develop a prediction model based on the biomarkers, radiographic features of PNs, and clinical characteristics of smokers for identifying malignant PNs. The performance of the prediction model was validated in a testing set of 111 subjects with PNs. A prediction model comprising the two biomarkers, spiculation of PNs and smoking pack-year, was developed that had 0.91 area under the curve of the receiver operating characteristic for distinguishing malignant from benign PNs. The prediction model yielded higher sensitivity (80.3% vs 72.6%) and specificity (89.4% vs 81.9%) compared with the biomarkers used alone (all P < .05). The performance of the prediction model for malignant PNs was confirmed in the validation set. We have for the first time demonstrated that the integration of biomarkers and clinical and radiological characteristics could efficiently identify lung cancer among indeterminate PNs.