High Expression of Complement 3 Enhances the Efficacy of Neoadjuvant Chemotherapy Prior to Oncoplastic Surgery for HER2-Positive Breast Cancer

Background: Neoadjuvant chemotherapy for breast cancer (BC) improves patient prognosis, but its efficacy is hindered by the disease's high heterogeneity. This study enhances effectiveness of targeted therapy to improve clinical outcomes. Methods: This study enrolled 335 patients from three centers. Differentially expressed genes were identified using DESeq2, and Venn analysis was applied to identify hub Complement genes. Hub gene expression was validated through public databases and IHC in real-world samples. In addition, associations between these genes and clinical factors were evaluated. Survival analysis, using the log-rank test, assessed overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) as end points. The authors also locate hub Complement 3 gene position by immunofluorescence. Results: The study identified C3 as a hub Complement gene associated with trastuzumab sensitivity. C3 shows higher expression in normal than tumor tissues. C3 was highly expressed in HER2-negative and early-stage BC, but showed no differences in lymph node or metastasis subgroups. High C3 expression correlated with better OS, DSS, and PFI, particularly in HER2+ patients. IHC analysis confirmed higher C3 expression in normal tissues with the lowest in triple-negative BC. Immunofluorescence findings suggest that C3 recruits complement receptor 2 to enhance trastuzumab efficacy in HER2+ patients. Conclusions: This finding highlights the potential of complement 3 to improve therapeutic outcomes and pave the way for more personalized treatment strategies in BC.

Potential applications of dual haptoglobin expression in the reclassification and treatment of hepatocellular carcinoma

HCC is a malignancy characterized by high incidence and mortality rates. Traditional classifications of HCC primarily rely on tumor morphology, phenotype, and multicellular molecular levels, which may not accurately capture the cellular heterogeneity within the tumor. This study integrates scRNA-seq and bulk RNA-seq to spotlight HP as a critical gene within a subgroup of HCC malignant cells. HP is highly expressed in HCC malignant cells and lowly expressed in T cells. Within malignant cells, elevated HP expression interacts with C3, promoting Th1-type responses via the C3/C3AR1 axis. In T cells, down-regulating HP expression favors the expression of Th1 cell-associated marker genes, potentially enhancing Th1-type responses. Consequently, we developed a "HP-promoted Th1 response reclassification" gene set, correlating higher activity scores with improved survival rates in HCC patients. Additionally, four predictive models for neoadjuvant treatment based on HP and C3 expression were established: 1) Low HP and C3 expression with high Th2 cell infiltration; 2) High HP and low C3 expression with high Th2 cell infiltration; 3) High HP and C3 expression with high Th1 cell infiltration; 4) Low HP and high C3 expression with high Th1 cell infiltration. In conclusion, the HP gene selected from the HCC malignant cell subgroup (Malignant_Sub 6) might serve as a potential ally against the tumor by promoting Th1-type immune responses. The establishment of the "HP-promoted Th1 response reclassification" gene set offers predictive insights for HCC patient survival prognosis and neoadjuvant treatment efficacy, providing directions for clinical treatments.

Association of complement components with risk of colorectal cancer: A systematic review and meta-analysis

BACKGROUND

Complement components could contribute to the tumor microenvironment and the systemic immune response. Nevertheless, their role in colorectal cancer (CRC) remains a contentious subject.

AIM

To elucidate the relationship between complement components and CRC risk and clinical characteristics.

METHODS

Searches were conducted in PubMed, the Cochrane Library, and the China National Knowledge Infrastructure database until June 1, 2023. We included cohort studies encompassing participants aged ≥ 18 years, investigating the association between complement components and CRC. The studies were of moderate quality or above, as determined by the Agency for Healthcare Research and Quality. The meta-analysis employed fixed-effects or random-effects models based on the I² test, utilizing risk ratio (RR) and their corresponding 95% confidence interval (CI) for outcomes. Sensitivity and subgroup analyses were performed to validate the robustness of the collective estimates and identify the source of heterogeneity.

RESULTS

Data from 15 studies, comprising 1631 participants that met the inclusion criteria, were included in the meta-analysis. Our findings indicated that protein levels of cluster of differentiation 46 (CD46) (RR = 3.66, 95%CI: 1.75-7.64, P < 0.001), CD59 (RR = 2.86, 95%CI: 1.36-6.01, P = 0.005), and component 1 (C1) (RR = 5.88, 95%CI: 1.75-19.73, P = 0.004) and serum levels of C3 (standardized mean difference = 1.82, 95%CI: 0.06-3.58, P = 0.040) were significantly elevated in patients with CRC compared to healthy controls. Strong expression of CD55 or CD59 was associated with a higher incidence of lymph node metastasis, whereas strong CD46 expression correlated with a higher incidence of tumor differentiation compared to low CD46 expression (P < 0.05 for all). Although specific pooled results demonstrated notable heterogeneity, subgroup analyses pointed to regional differences as the primary source of inconsistency among the studies.

CONCLUSION

Our analysis underscores that increased levels of specific complement components are associated with a heightened risk of CRC, emphasizing the potential significance of monitoring elevated complement component levels.

Integrated Transcriptomics-Proteomics Analysis Identifies Molecular Phenotypic Alterations Associated with Colorectal Cancer

Understanding the pathogenesis and finding diagnostic markers for colorectal cancer (CRC) are the key to its diagnosis and treatment. Integrated transcriptomics and proteomics analysis can be used to characterize alterations of molecular phenotypes and reveal the hidden pathogenesis of CRC. This study employed a novel strategy integrating transcriptomics and proteomics to identify pathological molecular pathways and diagnostic biomarkers of CRC. First, differentially expressed proteins and coexpressed genes generated from weighted gene coexpression network analysis (WGCNA) were intersected to obtain key genes of the CRC phenotype. In total, 63 key genes were identified, and pathway enrichment analysis showed that the process of coagulation and peptidase regulator activity could both play important roles in the development of CRC. Second, protein-protein interaction analysis was then conducted on these key genes to find the central genes involved in the metabolic pathways underpinning CRC. Finally, Itih3 and Lrg1 were further screened out as diagnostic biomarkers of CRC by applying statistical analysis on central genes combining transcriptomics and proteomics data. The deep involvement of central genes in tumorigenesis demonstrates the accuracy and reliability of this novel transcriptomics-proteomics integration strategy in biomarker discovery. The identified candidate biomarkers and enriched metabolic pathways provide insights for CRC diagnosis and treatment.

Protein Biomarker Discovery Studies on Urinary sEV Fractions Separated with UF-SEC for the First Diagnosis and Detection of Recurrence in Bladder Cancer Patients

Urinary extracellular vesicles (EVs) are an attractive source of bladder cancer biomarkers. Here, a protein biomarker discovery study was performed on the protein content of small urinary EVs (sEVs) to identify possible biomarkers for the primary diagnosis and recurrence of non-muscle-invasive bladder cancer (NMIBC). The sEVs were isolated by ultrafiltration (UF) in combination with size-exclusion chromatography (SEC). The first part of the study compared healthy individuals with NMIBC patients with a primary diagnosis. The second part compared tumor-free patients with patients with a recurrent NMIBC diagnosis. The separated sEVs were in the size range of 40 to 200 nm. Based on manually curated high quality mass spectrometry (MS) data, the statistical analysis revealed 69 proteins that were differentially expressed in these sEV fractions of patients with a first bladder cancer tumor vs. an age- and gender-matched healthy control group. When the discriminating power between healthy individuals and first diagnosis patients is taken into account, the biomarkers with the most potential are MASP2, C3, A2M, CHMP2A and NHE-RF1. Additionally, two proteins (HBB and HBA1) were differentially expressed between bladder cancer patients with a recurrent diagnosis vs. tumor-free samples of bladder cancer patients, but their biological relevance is very limited.

Potential prognostic and predictive value of UBE2N, IMPDH1, DYNC1LI1 and HRASLS2 in colorectal cancer stool specimens

Colorectal cancer (CRC) is the most common gastrointestinal malignancy worldwide. The poor specificity and sensitivity of the fecal occult blood test has prompted the development of CRC-related genetic markers for CRC screening and treatment. Gene expression profiles in stool specimens are effective, sensitive and clinically applicable. Herein, a novel advantage of using cells shed from the colon is presented for cost-effective CRC screening. Molecular panels were generated through a series of leave-one-out cross-validation and discriminant analyses. A logistic regression model following reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry was used to validate a specific panel for CRC prediction. The panel, consisting of ubiquitin-conjugating enzyme E2 N (UBE2N), inosine monophosphate dehydrogenase 1 (IMPDH1), dynein cytoplasmic 1 light intermediate chain 1 (DYNC1LI1) and phospholipase A and acyltransferase 2 (HRASLS2), accurately recognized patients with CRC and could thus be further investigated as a potential prognostic and predictive biomarker for CRC. UBE2N, IMPDH1 and DYNC1LI1 expression levels were upregulated and HRASLS2 expression was downregulated in CRC tissues. The predictive power of the panel was 96.6% [95% confidence interval (CI), 88.1-99.6%] sensitivity and 89.7% (95% CI, 72.6-97.8%) specificity at a predicted cut-off value at 0.540, suggesting that this four-gene panel testing of stool specimens can faithfully mirror the state of the colon. On the whole, the present study demonstrates that screening for CRC or cancer detection in stool specimens collected non-invasively does not require the inclusion of an excessive number of genes, and colonic defects can be identified via the detection of an aberrant protein in the mucosa or submucosa.

Presurgery Adhesion Molecules and Angiogenesis Biomarkers Are Differently Associated with Outcomes in Colon and Rectal Cancer: Results from the ColoCare Study

BACKGROUND

Cell-to-cell adhesion and angiogenesis are hallmarks of cancer. No studies have examined associations of adhesion molecules and angiogenesis biomarkers with clinical outcomes in colorectal cancer.

METHODS

In presurgery serum from n = 426 patients with colorectal cancer (stage I-III), we investigated associations of CRP, SAA, adhesion molecules (sICAM-1, sVCAM-1), and angiogenesis markers (VEGF-A and VEGF-D) with overall survival (OS), disease-free survival (DFS), and risk of recurrence. We computed HRs and 95% confidence intervals; adjusted for age, sex, BMI, stage, site, and study site, stratified by tumor site in exploratory analyses.

RESULTS

N = 65 (15%) were deceased, and 39 patients (14%) had a recurrence after a median follow-up of 31 months. We observed significant associations of biomarkers with OS, DFS, and risk of recurrence on a continuous scale and comparing top to bottom tertile, with HRs ranging between 1.19 and 13.92. CRP was associated with risk of death and recurrence in patients in the top tertile compared with patients in the bottom tertile, for example, risk of recurrence HRQ3-Q1: 13.92 (1.72-112.56). Significant heterogeneity between biomarkers and clinical outcomes was observed in stratified analysis by tumor site for CRP, SAA, sICAM-1, sVCAM-1, and VEGF-D. VEGF-D was associated with a 3-fold increase in risk of death for rectal cancer (HRlog2: 3.26; 95% CI, 1.58-6.70) compared with no association for colon cancer (HRlog2: 0.78; 95% CI, 0.35-1.73; Pheterogenity = 0.01).

CONCLUSIONS

Adhesion molecules and angiogenesis biomarkers are independent prognostic markers for colorectal cancer, with differences by tumor site.

IMPACT

There is need for tailored treatment for colon and rectal cancer.

Comparative analysis of protein-protein interaction networks in metastatic breast cancer

Metastatic lesions leading causes of the majority of deaths in patients with the breast cancer. The present study aimed to provide a comprehensive analysis of the differentially expressed genes (DEGs) in the brain (MDA-MB-231 BrM2) and lung (MDA-MB-231 LM2) metastatic cell lines obtained from breast cancer patients compared with those who have primary breast cancer. We identified 981 and 662 DEGs for brain and lung metastasis, respectively. Protein-protein interaction (PPI) analysis revealed seven shared (PLCB1, FPR1, FPR2, CX3CL1, GABBR2, GPR37, and CXCR4) hub genes between brain and lung metastasis in breast cancer. Moreover, GNG2 and CXCL8, C3, and PTPN6 in the brain and SAA1 and CCR5 in lung metastasis were found as unique hub genes. Besides, five co-regulation of clusters via seven important co-expression genes (COL1A2, LUM, SPARC, THBS2, IL1B, CXCL8, THY1) were identified in the brain PPI network. Clusters screening followed by biological process (BP) function and pathway enrichment analysis for both metastatic cell lines showed that complement receptor signalling, acetylcholine receptor signalling, and gastric acid secretion pathways were common between these metastases, whereas other pathways were site-specific. According to our findings, there are a set of genes and functional pathways that mark and mediate breast cancer metastasis to the brain and lungs, which may enable us understand the molecular basis of breast cancer development in a deeper levele to the brain and lungs, which may help us gain a more complete understanding of the molecular underpinnings of breast cancer development.

Circulating Clusterin Levels and Cancer Risk: A Systematic Review and Meta-Analysis

Introduction

The previous reports on clusterin (CLU) levels in various types of cancer have been controversial and heterogeneous. The present meta-analysis has aimed to evaluate the association between soluble CLU levels and the risk of different human cancers based on observational studies.

Methods

A systematic literature review was conducted to determine the relevant eligible studies in English language from health-related electronic databases up to January 2021. Random effects models were used to calculate the summary standard mean difference (SMD) with 95% confidence intervals (CIs) to identify the correlation between CLU levels and cancer risk. The meta-regression, sensitivity, Galbraith, and subgroup analyses were performed to explore the source of between-study heterogeneity. Furthermore, the funnel plot and Egger’s linear regression tests were carried out to evaluate the risk of publication bias.

Results

According to 16 eligible articles, 3331 patients and 839 healthy controls were included in our meta-analysis. Overall, the CLU levels were significantly higher in various cancer cases compared to the healthy groups (SMD = 1.50, 95% CI = 0.47–2.53). Moreover, subgroup analysis based on types of cancer showed a significant correlation between CLU levels and the risk of digestive system cancers (SMD = 1.54, 95% CI = 0.91–2.18, P <0.001), especially in HCC (SMD = 1.89, 95% CI = 0.76–3.03, P = 0.001), and CRC (SMD = 1.63, 95% CI = 0.0–3.23, P = 0.048).

Conclusion

The present meta-analysis indicates a significant association of CLU levels with the risk of digestive system cancers such as hepatocellular carcinoma and colorectal cancer. Therefore, CLU can be monitored as a novel molecular biomarker for the prognosis and diagnosis of various types of cancers particularly in the digestive system.

Identification of C3 and FN1 as potential biomarkers associated with progression and prognosis for clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most lethal urological malignancies, but the pathogenesis and prognosis of ccRCC remain obscure, which need to be better understand.

Methods

Differentially expressed genes were identified and function enrichment analyses were performed using three publicly available ccRCC gene expression profiles downloaded from the Gene Expression Omnibus database. The protein-protein interaction and the competing endogenous RNA (ceRNA) networks were visualized by Cytoscape. Multivariate Cox analysis was used to predict an optimal risk mode, and the survival analysis was performed with the Kaplan-Meier curve and log-rank test. Protein expression data were downloaded from Clinical Proteomic Tumor Analysis Consortium database and Human Protein Atlas database, and the clinical information as well as the corresponding lncRNA and miRNA expression data were obtained via The Cancer Genome Atlas database. The co-expressed genes and potential function of candidate genes were explored using data exacted from the Cancer Cell Line Encyclopedia database.

Results

Of the 1044 differentially expressed genes shared across the three datasets, 461 were upregulated, and 583 were downregulated, which significantly enriched in multiple immunoregulatory-related biological process and tumor-associated pathways, such as HIF-1, PI3K-AKT, P53 and Rap1 signaling pathways. In the most significant module, 36 hub genes were identified and were predominantly enriched in inflammatory response and immune and biotic stimulus pathways. Survival analysis and validation of the hub genes at the mRNA and protein expression levels suggested that these genes, particularly complement component 3 (C3) and fibronectin 1 (FN1), were primarily responsible for ccRCC tumorigenesis and progression. Increased expression of C3 or FN1 was also associated with advanced clinical stage, high pathological grade, and poor survival in patients with ccRCC. Univariate and multivariate Cox regression analysis qualified the expression levels of the two genes as candidate biomarkers for predicting poor survival. FN1 was potentially regulated by miR-429, miR-216b and miR-217, and constructed a bridge to C3 and C3AR1 in the ceRNA network, indicating a critical position of FN1.

Conclusions

The biomarkers C3 and FN1 could provide theoretical support for the development of a novel prognostic tool to advance ccRCC diagnosis and targeted therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08818-0.

Transcriptomic Analysis Identifies Complement Component 3 as a Potential Predictive Biomarker for Chemotherapy Resistance in Colorectal Cancer

Objective: 5-fluorouracil- and oxaliplatin-based FOLFOX regimens are mainstay chemotherapeutics for colorectal cancer (CRC) but drug resistance represents a major therapeutic challenge. To improve patient survival, there is a need to identify resistance genes to better understand the mechanisms underlying chemotherapy resistance. Methods: Transcriptomic datasets were retrieved from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and combined with our own microarray data. Weighted gene co-expression network analysis (WGCNA) was used to dissect the functional networks and hub genes associated with FOLFOX resistance and cancer recurrence. We then conducted analysis of prognosis, profiling of tumor infiltrating immune cells, and pathway overrepresentation analysis to comprehensively elucidate the biological impact of the identified hub gene in CRC. Results: WGCNA analysis identified the complement component 3 (C3) gene as the only hub gene associated with both FOLFOX chemotherapy resistance and CRC recurrence after FOLFOX chemotherapy. Subsequent survival analysis confirmed that high C3 expression confers poor progression-free survival, disease-free survival, and recurrence-free survival. Further correlational analysis revealed significant negative association of C3 expression with sensitivity to oxaliplatin, but not 5-fluorouracil. Moreover, in silico analysis of tumor immune cell infiltration suggested the change of C3 expression could affect tumor microenvironment. Finally, gene set enrichment analysis (GSEA) revealed a hyperactivation of pathways contributing to invasion, metastasis, lymph node spread, and oxaliplatin resistance in CRC samples with C3 overexpression. Conclusion: Our results suggest that high C3 expression is a debilitating factor for FOLFOX chemotherapy, especially for oxaliplatin sensitivity, and C3 may represent a novel biomarker for treatment decision of CRC.

Molecular Origin of Blood-Based Infrared Spectroscopic Fingerprints*

Infrared spectroscopy of liquid biopsies is a time- and cost-effective approach that may advance biomedical diagnostics. However, the molecular nature of disease-related changes of infrared molecular fingerprints (IMFs) remains poorly understood, impeding the method's applicability. Here we probe 148 human blood sera and reveal the origin of the variations in their IMFs. To that end, we supplemented infrared spectroscopy with biochemical fractionation and proteomic profiling, providing molecular information about serum composition. Using lung cancer as an example of a medical condition, we demonstrate that the disease-related differences in IMFs are dominated by contributions from twelve highly abundant proteins-that, if used as a pattern, may be instrumental for detecting malignancy. Tying proteomic to spectral information and machine learning advances our understanding of the infrared spectra of liquid biopsies, a framework that could be applied to probing of any disease.

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.

Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

Skin problems are often overlooked due to a lack of robust and patient-friendly monitoring tools. Herein, we report a rapid, noninvasive, and high-throughput analytical chemical methodology, aiming at real-time monitoring of skin conditions and early detection of skin disorders. Within this methodology, adhesive sampling and laser desorption ionization mass spectrometry are coordinated to record skin surface molecular mass in minutes. Automated result interpretation is achieved by data learning, using similarity scoring and machine learning algorithms. Feasibility of the methodology has been demonstrated after testing a total of 117 healthy, benign-disordered, or malignant-disordered skins. Remarkably, skin malignancy, using melanoma as a proof of concept, was detected with 100% accuracy already at early stages when the lesions were submillimeter-sized, far beyond the detection limit of most existing noninvasive diagnosis tools. Moreover, the malignancy development over time has also been monitored successfully, showing the potential to predict skin disorder progression. Capable of detecting skin alterations at the molecular level in a nonsurgical and time-saving manner, this analytical chemistry platform is promising to build personalized skin care.

Gastric perforation caused by secondary systemic amyloidosis

Amyloid A amyloidosis secondary to chronic inflammation involves systemic organs and tissues, including the gastrointestinal tract. In the present case, massive amyloid deposit caused gastric perforation. IgM co-deposition in the glomeruli was another finding of note.

Identification of potential salivary biomarker panels for oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide with the maximum number of incidences and deaths reported from India. One of the major causes of poor survival rate associated with OSCC has been attributed to late presentation due to non-availability of a biomarker. Identification of early diagnostic biomarker will help in reducing the disease morbidity and mortality. We validated 12 salivary proteins using targeted proteomics, identified initially by relative quantification of salivary proteins on LC-MS, in OSCC patients and controls. Salivary AHSG (p = 0.0041**) and KRT6C (p = 0.002**) were upregulated in OSCC cases and AZGP1 (p ≤ 0.0001***), KLK1 (p = 0.006**) and BPIFB2 (p = 0.0061**) were downregulated. Regression modelling resulted in a significant risk prediction model (p < 0.0001***) consisting of AZGP1, AHSG and KRT6C for which ROC curve had AUC, sensitivity and specificity of 82.4%, 78% and 73.5% respectively for all OSCC cases and 87.9%, 87.5% and 73.5% respectively for late stage (T3/T4) OSCC. AZGP1, AHSG, KRT6C and BPIFB2 together resulted in ROC curve (p < 0.0001***) with AUC, sensitivity and specificity of 94%, 100% and 77.6% respectively for N0 cases while KRT6C and AZGP1 for N+ cases with ROC curve (p < 0.0001***) having AUC sensitivity and specificity of 76.8%, 73% and 69.4%. Our data aids in the identification of biomarker panels for the diagnosis of OSCC cases with a differential diagnosis between early and late-stage cases.

Identification of several plasma proteins whose levels in colorectal cancer patients differ depending on outcome

Colorectal cancer (CRC) stands for 10% of the worldwide cancer burden and has recently become the second most common cause of cancer death. The 5-year survival rate depends mainly on stage at diagnosis. Mass spectrometric proteomic analysis is widely used to study the plasma proteome, which is complex and contains multitudes of proteins. In this study, we have used Ultra Performance Liquid Chromatography-Ultra Definition Mass Spectrometry (UPLC-UDMSE)-based proteomics to analyze plasma samples from 76 CRC patients. We identified several plasma proteins, such as CP, TVP23C, FETUB, and IGFBP3, of which altered levels led to significant differences in survival, as seen by Cox regression and Kaplan-Meier analysis. Additionally, during Cox regression analysis, samples were adjusted for age and/or tumor stage, enabling stringent analysis. These proteins, although in need of further validation, could be of use during patient follow-up, as their levels can non-invasively be measured from blood samples, and could be of use in predicting patient outcome. Several of these proteins additionally have roles in metabolism and inflammation, two processes central to the development and progression of cancer, further indicating their importance in cancer.

Identification of protein changes in the blood plasma of lung cancer patients subjected to chemotherapy using a 2D-DIGE approach

A comparative analysis of blood samples (depleted of albumin and IgG) obtained from lung cancer patients before chemotherapy versus after a second cycle of chemotherapy was performed using two-dimensional difference gel electrophoresis (2D-DIGE). The control group consisted of eight patients with non-cancerous lung diseases, and the experimental group consisted of four adenocarcinoma (ADC) and four squamous cell carcinoma (SCC) patients. Analyses of gels revealed significant changes in proteins and/or their proteoforms between control patients and lung cancer patients, both before and after a second cycle of chemotherapy. Most of these proteins were related to inflammation, including acute phase proteins (APPs) such as forms of haptoglobin and transferrin, complement component C3, and clusterin. The variable expression of APPs can potentially be used for profiling lung cancer. The greatest changes observed after chemotherapy were in transferrin and serotransferrin, which likely reflect disturbances in iron turnover after chemotherapy-induced anaemia. Significant changes in plasma proteins between ADC and SCC patients were also revealed, suggesting use of plasma vitronectin as a potential marker of SCC.

A comparative proteomic study of plasma in Colombian childhood acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Owing to the incorporation of risk-adapted therapy and the arrival of new directed agents, the cure rate and survival of patients with ALL have improved dramatically, get near to 90%. In Latin American countries, the mortality rates of ALL are high, for example in Colombia, during the last decade, ALL has been the most prevalent cancer among children between 0–14 years of age. In the face of this public health problem and coupled with the fact that the knowledge of the proteome of the child population is little, our investigation proposes the study of the plasma proteome of Colombian children diagnosed with B-cell ALL (B-ALL) to determine potential disease markers that could reflect processes altered by the presence of the disease or in response to it. A proteomic study by LC-MS/MS and quantification by label-free methods were performed in search of proteins differentially expressed between healthy children and those diagnosed with B-ALL. We quantified a total of 472 proteins in depleted blood plasma, and 25 of these proteins were differentially expressed (fold change >2, Bonferroni-adjusted P-values <0.05). Plasma Aggrecan core protein, alpha-2-HS-glycoprotein, coagulation factor XIII A chain and gelsolin protein were examined by ELISA assay and compared to shotgun proteomics results. Our data provide new information on the plasma proteome of Colombian children. Additionally, these proteins may also have certain potential as illness markers or as therapeutic targets in subsequent investigations.

Acute phase proteins and biomarkers of oxidative status in feline spontaneous malignant mammary tumours

Acute phase proteins (APP) and biomarkers of oxidative status change in human and canine mammary tumours, however, they have not been studied in feline mammary tumours. The aims of this study were to investigate the APP and antioxidant responses in feline malignant mammary tumours, to evaluate their relation with tumour features, and to assess their prognostic value. Serum amyloid A (SAA), haptoglobin (Hp), albumin, butyrylcholinesterase (BChE), insulin-like growth factor1 (IGF1), paraoxonase1 (PON1), total serum thiols (Thiol), glutathione peroxidase (GPox) and total antioxidant capacity determined by different assays, including trolox equivalent antioxidant capacity assessed by two different methodologies (TEAC1/2), ferric reducing ability of plasma (FRAP), and cupric reducing antioxidant capacity (CUPRAC), were determined in serum of 50 queens with spontaneous mammary carcinomas and of 12 healthy female cats. At diagnosis, diseased queens presented significantly higher SAA and Hp, and lower albumin, BChE, GPox, TEAC1, TEAC2 and CUPRAC than controls. Different tumour features influenced concentrations of APP and antioxidants. Increases in serum Hp, and decreases in albumin, Thiol and FRAP were significantly associated with neoplastic vascular emboli, metastasis in regional lymph nodes and/or in distant organs. Distant metastasis development during the course of the disease was associated with increases in SAA and TEAC1. At diagnosis, decreased albumin was associated with a longer survival, and BChE <1.15 μmoL/mL.minute was associated with a shorter survival time on multivariate analysis. Feline malignant mammary tumours are associated with an APP response and oxidative stress, and different tumour features influence the inflammatory response and the oxidative damage. Furthermore, some of these analytes proved to have prognostic value.

Serum amyloid A expression in the breast cancer tissue is associated with poor prognosis

Background

Serum amyloid A (SAA), an acute-phase protein, is expressed primarily in the liver, and recently found also expressed in cancer tissues. However, its expression and prognostic value in breast cancer have not been described.

Results

SAA protein was found expressed in tumor cells in 44.2% cases and in TAM in 62.5% cases. FISH showed more frequent SAA mRNA expression in TAM than in tumor cells (76% versus 12%, p < 0.001), and a significant association between the frequencies of SAA mRNA expression in TAM and tumor cells (r_s = 0.603, p < 0.001). The immunoreactivities of SAA protein in TAM and tumor cells were both associated with lymphovascular invasion and lymph node metastasis. Moreover, SAA-positivity in TAMs was associated with larger tumor-size, higher histological-grade, negative estrogen-receptor and progesterone-receptor statuses, and HER-2 overexpression. It was also linked to worse recurrence-free survival in a multivariable regression model.

Methods

Immunohistochemistry was applied on the tumor tissues from 208 breast cancer patients to evaluate the local SAA-protein expression with additional CD68 stain to identify the tumor-associated macrophage (TAM) on the serial tissue sections. Fluorescent in situ hybridization (FISH) was conducted on serial tissue sections from 25 of the 208 tumors to examine the expression and location of SAA mRNA.

Conclusions

Our results suggested that the TAMs may be a pivotal and main source of SAA production in tumor microenvironment of breast cancer. SAA immunoreactivity in TAM is associated with worse recurrence-free survival, and is therefore a biomarker candidate for postoperative surveillance and perhaps a therapeutic target for breast cancer.

Single nucleotide polymorphisms of the haptoglobin gene in non-small cell lung cancer treated with personalized peptide vaccination

The present study analyzed polymorphisms of the 5' flanking region (from nt -840 to +151) of the haptoglobin gene in 120 patients with advanced non-small cell lung cancer (NSCLC) receiving personalized peptide vaccinations. In the region, six single nucleotide polymorphisms (SNPs) were confirmed, of which two, rs5472 and rs9927981, were completely linked to each other. The minor allele frequencies of rs5472/rs9927981 and rs4788458 were higher than those of the other three SNPs. The genotype frequencies of rs5472 or rs9927981 were A/A or C/C (42.5%, n=51), A/G or C/T (40.8%, n=49), and G/G or T/T (16.7%, n=20), respectively; and those of rs4788458 were T/T (34.2%, n=41), T/C (40.0%, n=48), and C/C (25.8%, n=31). The association between polymorphism rs5472/rs9927981 and prognosis, or between rs4788458 and prognosis, was analyzed further. However, no correlation was found between these SNPs and overall survival, regardless of subgroup analysis of gender, histology or concurrent therapy. These results suggest that the polymorphisms rs5472/rs9927981 and rs4788458 are not useful prognostic tools for patients with NSCLC treated with personalized peptide vaccination.

Cancer Secretome May Influence BSP and DSP Expression in Human Salivary Gland Cells

One of the biggest challenges in managing head and neck cancers, especially salivary gland cancers, is the identification of secreted biomarkers of the disease that can be evaluated noninvasively. A relevant source of enriched tumor markers could potentially be found in the tumor secretome. Although numerous studies have evaluated secretomes from various cancers, the influence of the cancer secretome derived from salivary gland cancers on the behavior of normal cells has not yet been elucidated. Our data indicate that secretome derived from salivary gland cancer cells can influence the expression of two potential biomarkers of oral cancer-namely, bone sialoprotein (BSP) and dentin sialoprotein (DSP)-in normal salivary gland cells. Using routine immunohistochemistry, immunofluorescence, and immunoblotting techniques, we demonstrate an enrichment of BSP and DSP in human salivary gland (HSG) cancer tissue, unique localizations of BSP and DSP in HSG cancer cells, and enriched expression of BSP and DSP in normal salivary gland cells exposed to a cancer secretome. The secretome domain of the cancer microenvironment could alter signaling cascades responsible for normal cell proliferation, migration, and invasion, thus enhancing cancer cell survival and the potential for cancer progression. The cancer secretome may be critical in maintaining and stimulating "cancer-ness," thus potentially promoting specific hallmarks of metastasis.

Increased serum amyloid A as potential diagnostic marker for lung cancer: a meta-analysis based on nine studies

BACKGROUND

Previous studies have disclosed that serum amyloid A (SAA) is likely involved in the lung cancer pathogenesis and progression. We performed a systematic evaluation and meta-analysis to disclose the correlation between the expression of SAA and lung cancer and to evaluate its value for lung cancer diagnosis.

METHODS

We searched the relevant articles from the databases of Medline, Embase, Cochrance Library and Web of Science and calculated the standardized mean difference (SMD) with 95 % confidence interval (CI) to assess the expression difference of SAA between lung cancer and normal patients. Moreover, we counted the positive rate, sensitivity and specificity and drew a summary receiver operating characteristic curve (SROC) to evaluate the diagnostic value of SAA for lung cancer.

RESULTS

A total of nine studies with 1392 individuals were included in this analysis. The results showed an increased SAA was correlated with the incidence of lung cancer (P < 0.001), especially with the lung squamous cell carcinoma (LSCC) (p = 0.012). The overall sensitivity and specificity of SAA for discerning lung cancer was 0.59 (95 % CI: 0.54-0.63) and 0.92 (95 % CI: 0.88-0.95), respectively. The area under the SROC curve was 0.9066 (SE = 0.0437).

CONCLUSIONS

Increased SAA in lung cancer was intimately correlated with the development and progression of lung cancer. A higher specificity of SAA suggested that it should be a significant biomarker for discerning lung cancer from normal individuals, especially for LSCC (p = 0.012).

Building the Evidence Base of Blood-Based Biomarkers for Early Detection of Cancer: A Rapid Systematic Mapping Review

BACKGROUND

The Early Cancer Detection Consortium is developing a blood-test to screen the general population for early identification of cancer, and has therefore conducted a systematic mapping review to identify blood-based biomarkers that could be used for early identification of cancer.

METHODS

A mapping review with a systematic approach was performed to identify biomarkers and establish their state of development. Comprehensive searches of electronic databases Medline, Embase, CINAHL, the Cochrane library and Biosis were conducted in May 2014 to obtain relevant literature on blood-based biomarkers for cancer detection in humans. Screening of retrieved titles and abstracts was performed using an iterative sifting process known as "data mining". All blood based biomarkers, their relevant properties and characteristics, and their corresponding references were entered into an inclusive database for further scrutiny by the Consortium, and subsequent selection of biomarkers for rapid review. This systematic review is registered with PROSPERO (no. CRD42014010827).

FINDINGS

The searches retrieved 19,724 records after duplicate removal. The data mining approach retrieved 3990 records (i.e. 20% of the original 19,724), which were considered for inclusion. A list of 814 potential blood-based biomarkers was generated from included studies. Clinical experts scrutinised the list to identify miss-classified and duplicate markers, also volunteering the names of biomarkers that may have been missed: no new markers were identified as a result. This resulted in a final list of 788 biomarkers.

INTERPRETATION

This study is the first to systematically and comprehensively map blood biomarkers for early detection of cancer. Use of this rapid systematic mapping approach found a broad range of relevant biomarkers allowing an evidence-based approach to identification of promising biomarkers for development of a blood-based cancer screening test in the general population.

COPD and squamous cell lung cancer: aberrant inflammation and immunity is the common link

Cigarette smoking has reached epidemic proportions within many regions of the world and remains the highest risk factor for chronic obstructive pulmonary disease (COPD) and lung cancer. Squamous cell lung cancer is commonly detected in heavy smokers, where the risk of developing lung cancer is not solely defined by tobacco consumption. Although therapies that target common driver mutations in adenocarcinomas are showing some promise, they are proving ineffective in smoking-related squamous cell lung cancer. Since COPD is characterized by an excessive inflammatory and oxidative stress response, this review details how aberrant innate, adaptive and systemic inflammatory processes can contribute to lung cancer susceptibility in COPD. Activated leukocytes release increasing levels of proteases and free radicals as COPD progresses and tertiary lymphoid aggregates accumulate with increasing severity. Reactive oxygen species promote formation of reactive carbonyls that are not only tumourigenic through initiating DNA damage, but can directly alter the function of regulatory proteins involved in host immunity and tumour suppressor functions. Systemic inflammation is also markedly increased during infective exacerbations in COPD and the interplay between tumour-promoting serum amyloid A (SAA) and IL-17A is discussed. SAA is also an endogenous allosteric modifier of FPR2 expressed on immune and epithelial cells, and the therapeutic potential of targeting this receptor is proposed as a novel strategy for COPD-lung cancer overlap.

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

INTRODUCTION

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

METHOD

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

RESULTS

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

CONCLUSIONS

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.

Insights into immune responses in oral cancer through proteomic analysis of saliva and salivary extracellular vesicles

The development and progression of oral cavity squamous cell carcinoma (OSCC) involves complex cellular mechanisms that contribute to the low five-year survival rate of approximately 20% among diagnosed patients. However, the biological processes essential to tumor progression are not completely understood. Therefore, detecting alterations in the salivary proteome may assist in elucidating the cellular mechanisms modulated in OSCC and improve the clinical prognosis of the disease. The proteome of whole saliva and salivary extracellular vesicles (EVs) from patients with OSCC and healthy individuals were analyzed by LC-MS/MS and label-free protein quantification. Proteome data analysis was performed using statistical, machine learning and feature selection methods with additional functional annotation. Biological processes related to immune responses, peptidase inhibitor activity, iron coordination and protease binding were overrepresented in the group of differentially expressed proteins. Proteins related to the inflammatory system, transport of metals and cellular growth and proliferation were identified in the proteome of salivary EVs. The proteomics data were robust and could classify OSCC with 90% accuracy. The saliva proteome analysis revealed that immune processes are related to the presence of OSCC and indicate that proteomics data can contribute to determining OSCC prognosis.

Serum amyloid A is a novel prognostic biomarker in hepatocellular carcinoma

PURPOSE

To investigate the prognostic value of serum amyloid A (SAA) in patients with hepatocellular carcinoma (HCC) undergoing surgery.

MATERIALS AND METHODS

Preoperative serum samples of 328 patients with HCC who underwent curative resection and of 47 patients with benign liver lesion were assayed. Serum levels of SAA were measured by enzyme-linked immunosorbent assay and its correlations with clinicopathological characteristics and survival were explored.

RESULTS

Levels of SAA were significantly higher in patients with HCC than those with benign liver lesion. There were strong correlations between preoperative serum SAA level and tumor size and more advanced BCLC stage. On univariate analysis, elevated SAA was associated with reduced disease-free survival and overall survival (p=0.001 and 0.03, respectively). Multivariate analyses showed that serum SAA level was an independent prognostic factor for overall survival (hazard ratio 2.80, p=0.01).

CONCLUSIONS

High SAA serum level is a novel biomarker for the prognosis of HCC patients.

Plasma fetuin-A concentration, genetic variation in the AHSG gene and risk of colorectal cancer

Fetuin-A, also referred to as α2-Heremans-Schmid glycoprotein (AHSG), is a liver protein known to inhibit insulin actions. Hyperinsulinemia is a possible risk factor for colorectal cancer; however, the role of fetuin-A in the development of colorectal cancer is unclear. We investigated the association between circulating fetuin-A and colorectal cancer risk in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition. Fetuin-A concentrations were measured in prediagnostic plasma samples from 1,367 colorectal cancer cases and 1,367 matched controls. In conditional logistic regression models adjusted for potential confounders, the estimated relative risk (95% confidence interval) of colorectal cancer per 40 µg/mL higher fetuin-A concentrations (approximately one standard deviation) was 1.13 (1.02-1.24) overall, 1.21 (1.05-1.39) in men, 1.06 (0.93-1.22) in women, 1.13 (1.00-1.27) for colon cancer and 1.12 (0.94-1.32) for rectal cancer. To improve causal inference in a Mendelian Randomization approach, five tagging single nucleotide polymorphisms of the AHSG gene were genotyped in a subset of 456 case-control pairs. The AHSG allele-score explained 21% of the interindividual variation in plasma fetuin-A concentrations. In instrumental variable analysis, genetically raised fetuin-A was not associated with colorectal cancer risk (relative risk per 40 µg/mL genetically determined higher fetuin-A was 0.98, 95% confidence interval: 0.73-1.33). The findings of our study indicate a modest linear association between fetuin-A concentrations and risk of colorectal cancer but suggest that fetuin-A may not be causally related to colorectal cancer development.

Metabolic serum biomarkers for the prediction of cancer: a follow-up of the studies conducted in the Swedish AMORIS study

The Swedish Apolipoprotein MOrtality RISk study (AMORIS) contains information on more than 500 biomarkers collected from 397,443 men and 414,630 women from the greater Stockholm area during the period 1985–1996. Using a ten-digit personal identification code, this database has been linked to Swedish national registries, which provide data on socioeconomic status, vital status, cancer diagnosis, comorbidity, and emigration. Within AMORIS, 18 studies assessing risk of overall and site-specific cancers have been published, utilising a range of serum markers representing glucose and lipid metabolism, immune system, iron metabolism, liver metabolism, and bone metabolism. This review briefly summarises these findings in relation to more recently published studies and provides an overview of where we are today and the challenges of observational studies when studying cancer risk prediction.

Overall, more recent observational studies supported previous findings obtained in AMORIS, although no new results have been reported for serum fructosamine and inorganic phosphate with respect to cancer risk. A drawback of using serum markers in predicting cancer risk is the potential fluctuations following other pathological conditions, resulting in non-specificity and imprecision of associations observed. Utilisation of multiple combination markers may provide more specificity, as well as give us repeated instead of single measurements. Associations with other diseases may also necessitate further analytical strategies addressing effects of serum markers on competing events in addition to cancer. Finally, delineating the role of serum metabolic markers may generate valuable information to complement emerging clinical studies on preventive effects of drugs and supplements targeting metabolic disorders against cancer.

Identification of genes involved in breast cancer and breast cancer stem cells

Breast cancer is the most frequent type of cancer in women. Great progress has been made in its treatment but relapse is common. One hypothesis to account for the high recurrence rates is the presence of cancer stem cells (CSCs), which have the ability to self-renew and differentiate into multiple malignant cell types. This study aimed to determine genes that are expressed in breast cancer and breast CSCs and to investigate their correlation with stemness. RNA was extracted from established breast cancer cell lines and from CSCs derived from five different breast cancer patients. DNA microarray analysis was performed and any upregulated genes were also studied in other cancer types, including colorectal and lung cancer. For genes that were expressed only in breast cancer, knockdown-based experiments were performed. Finally, the gene expression levels of stemness transcription factors were measured. The outcome of the analysis indicated a group of genes that were aberrantly expressed mainly in breast cancer cells with stemness properties. Knockdown experiments confirmed the impact of several of these on NANOG, OCT3/4, and SOX2 transcription factors. It seems that several genes that are not directly related with hormone metabolism and basic signal transduction pathways might have an important role in relapse and disease progression and, thus, can be targeted for new treatment approaches for breast cancer.

Clinical predictive circulating peptides in rectal cancer patients treated with neoadjuvant chemoradiotherapy

Preoperative chemoradiotherapy is worldwide accepted as a standard treatment for locally advanced rectal cancer. Current standard of treatment includes administration of ionizing radiation for 45-50.4 Gy in 25-28 fractions associated with 5-fluorouracil administration during radiation therapy. Unfortunately, 40% of patients have a poor or absent response and novel predictive biomarkers are demanding. For the first time, we apply a novel peptidomic methodology and analysis in rectal cancer patients treated with preoperative chemoradiotherapy. Circulating peptides (Molecular Weight <3 kDa) have been harvested from patients' plasma (n = 33) using nanoporous silica chip and analyzed by Matrix-Assisted Laser Desorption/Ionization-Time of Flight mass spectrometer. Peptides fingerprint has been compared between responders and non-responders. Random Forest classification selected three peptides at m/z 1082.552, 1098.537, and 1104.538 that were able to correctly discriminate between responders (n = 16) and non-responders (n = 17) before therapy (T0) providing an overall accuracy of 86% and an area under the receiver operating characteristic (ROC) curve of 0.92. In conclusion, the nanoporous silica chip coupled to mass spectrometry method was found to be a realistic method for plasma-based peptide analysis and we provide the first list of predictive circulating biomarker peptides in rectal cancer patients underwent preoperative chemoradiotherapy.

Prediagnostic serum inflammatory markers in relation to breast cancer risk, severity at diagnosis and survival in breast cancer patients

Inflammation has been linked to cancer but its role in breast cancer is unclear. We investigated common serum markers of inflammation: C-reactive protein (CRP), albumin, haptoglobin and white blood cells (WBC) in relation to breast cancer incidence, severity and survival. A total of 155179 women aged 20 and older without any history of cancer were selected from a large Swedish cohort. Hazard ratios (HRs) for breast cancer were estimated with Cox regression, adjusting for potential confounders. Ordered and binomial logistic regression models were used to assess the associations of serum inflammatory markers with breast cancer severity and oestrogen receptor (ER) positivity at diagnosis, on the other. Cumulative incidence functions by levels of inflammatory markers were assessed for early death from breast cancer and all causes. During a mean follow-up of 18.3 years, 6606 women were diagnosed with breast cancer, of whom 1474 died. A positive association with incident breast cancer was seen for haptoglobin ≥ 1.4g/l [HR 1.09; 95% confidence interval (CI): 1.00-1.18] compared to lower levels. No association was observed between inflammatory markers and breast cancer severity or ER positivity. Higher haptoglobin was linked to risk of early death from breast cancer (HR: 1.27, 95% CI: 1.02-1.59), whereas higher risk of early death from all causes was additionally found with CRP ≥ 10mg/l (HR: 1.19, 95% CI: 1.04-1.36) and WBC ≥ 10×10(9)/l (HR: 1.57, 1.14-2.16). Our findings indicate that prediagnostic serum inflammatory markers were weakly linked to incident breast cancer but corresponded to worse survival after diagnosis.

Discovery and horizontal follow-up of an autoantibody signature in human prostate cancer

In response to an urgent need for improved diagnostic and predictive serum biomarkers for management of metastatic prostate cancer, we used phage display fingerprinting to analyze sequentially acquired serum samples from a patient with advancing prostate cancer. We identified a peptide ligand, CTFAGSSC, demonstrating an increased recovery frequency over time. Serum antibody reactivity to this peptide epitope increased in the index patient, in parallel with development of deteriorating symptoms. The antigen mimicking the peptide epitope was identified as alpha-2-Heremans-Schmid glycoprotein, also known as fetuin-A. Metastatic prostate cancer cell lines and bone metastasis samples displayed robust fetuin-A expression, and we demonstrated serum immune reactivity to fetuin-A with concomitant development of metastatic castrate-resistant disease in a large cohort of prostate cancer patients. Whereas fetuin-A is an established tumor antigen in several types of cancer, including breast cancer, glioblastoma, and pancreas cancer, this report is to our knowledge the first study implicating fetuin-A in prostate cancer and indicating that autoantibodies specific for fetuin-A show utility as a prognostic indicator for prostate cancer patients prone to progress to metastatic disease.

Identification of plasma protein markers common to patients with malignant tumour and Abnormal Savda in Uighur medicine: a prospective clinical study

Background

Traditional Uighur medicine shares an origin with Greco-Arab medicine. It describes the health of a human body as the dynamic homeostasis of four normal Hilits (humours), known as Kan, Phlegm, Safra, and Savda. An abnormal change in one Hilit may cause imbalance among the Hilits, leading to the development of a syndrome. Abnormal Savda is a major syndrome of complex diseases that are associated with common biological changes during disease development. Here, we studied the protein expression profile common to tumour patients with Abnormal Savda to elucidate the biological basis of this syndrome and identify potential biomarkers associated with Abnormal Savda.

Methods

Patients with malignant tumours were classified by the diagnosis of Uighur medicine into two groups: Abnormal Savda type tumour (ASt) and non-Abnormal Savda type tumour (nASt), which includes other syndromes. The profile of proteins that were differentially expressed in ASt compared with nASt and normal controls (NC) was analysed by iTRAQ proteomics and evaluated by bioinformatics using MetaCore™ software and an online database. The expression of candidate proteins was verified in all plasma samples by enzyme-linked immunosorbent assay (ELISA).

Results

We identified 31 plasma proteins that were differentially expressed in ASt compared with nASt, of which only 10 showed quantitatively different expression between ASt and NC. Bioinformatics analysis indicated that most of these proteins are known biomarkers for neoplasms of the stomach, breast, and lung. ELISA detection showed significant upregulation of plasma SAA1 and SPP24 and downregulation of PIGR and FASN in ASt compared with nASt and NC (p < 0.05).

Conclusions

Abnormal Savda may be causally associated with changes in the whole regulation network of protein expression during carcinogenesis. The expression of potential biomarkers might be used to distinguish Abnormal Savda from other syndromes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12906-015-0526-6) contains supplementary material, which is available to authorized users.

Lung Cancer Biomarkers

Lung cancer is the most frequently occurring cancer in the world and continually leads in mortality among cancers. The overall 5-year survival rate for lung cancer has risen only 4% (from 12% to 16%) over the past 4 decades, and late diagnosis is a major obstacle in improving lung cancer prognosis. Survival of patients undergoing lung resection is greater than 80%, suggesting that early detection and diagnosis of cancers before they become inoperable and lethal will greatly improve mortality. Lung cancer biomarkers can be used for screening, detection, diagnosis, prognosis, prediction, stratification, therapy response monitoring, and so on. This review focuses on noninvasive diagnostic and prognostic biomarkers. For that purpose, our discussion in this review will focus on biological fluid-based biomarkers. The body fluids include blood (serum or plasma), sputum, saliva, BAL, pleural effusion, and VOC. Since it is rich in different cellular and molecular elements and is one of the most convenient and routine clinical procedures, serum or plasma is the main source for the development and validation of many noninvasive biomarkers. In terms of molecular aspects, the most widely validated ones are proteins, some of which are used in the clinical sector, though in limited accessory purposes. We will also discuss the lung cancer (protein) biomarkers in clinical trials and currently in the validation phase with hundreds of samples. After proteins, we will discuss microRNAs, methylated DNA, and circulating tumor cells, which are being vigorously developed and validated as potential lung cancer biomarkers. The main aim of this review is to provide researchers and clinicians with an understanding of the potential noninvasive lung cancer biomarkers in biological fluids that have recently been discovered.

Senescence-associated-gene signature identifies genes linked to age, prognosis, and progression of human gliomas

BACKGROUND

Senescence-associated genes (SAGs) are responsible for the senescence-associated secretory phenotype, linked in turn to cellular aging, the aging brain, and the pathogenesis of cancer.

OBJECTIVE

We hypothesized that senescence-associated genes are overexpressed in older patients, in higher grades of glioma, and portend a poor prognosis.

METHODS

Forty-seven gliomas were arrayed on a custom version of the Affymetrix HG-U133+2.0 GeneChip, for expression of fourteen senescence-associated genes: CCL2, CCL7, CDKN1A, COPG, CSF2RB, CXCL1, ICAM-1, IGFBP-3, IL-6, IL-8, SAA4, TNFRSF-11B, TNFSF-11 and TP53. A combined "senescence score" was generated using principal component analysis to measure the combined effect of the senescence-associated gene signature.

RESULTS

An elevated senescence score correlated with older age (r=0.37; P=.01) as well as a higher degree of malignancy, as determined by WHO, histological grade (r=0.49; P<.001). There was a mild association with poor prognosis (P=.06). Gliosarcomas showed the highest scores. Six genes independently correlated with either age (IL-6, TNFRSF-11B, IGFBP-3, SAA4, and COPG), prognosis (IL-6, SAA4), or the grade of the glioma (IL-6, IL-8, ICAM-1, IGFBP-3, and COPG).

CONCLUSION

We report: 1) a novel molecular signature in human gliomas, based on cellular senescence, translating the concept of SAG to human cancer; 2) the senescence signature is composed of genes central to the pathogenesis of gliomas, defining a novel, aggressive subtype of glioma; and 3) these genes provide prognostic biomarkers, as well as targets, for drug discovery and immunotherapy.

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number of CPUs to tens of thousands of protein targets and millions of potential drug candidates.

Proteomic characterization of pediatric craniopharyngioma intracystic fluid by LC-MS top-down/bottom-up integrated approaches

The combination of top-down and bottom-up platforms was utilized for the LC-MS proteomic characterization of the intracystic fluid of adamantinomatous craniopharyngioma pediatric brain tumor disease. Proteins and peptides characterization was achieved by high-resolution LC-ESI-LTQ-Orbitrap-MS analysis while low-resolution LC-ESI-IT-MS was applied for the complete screening of the samples and the evaluation of the protein distribution within patients. Top-down analyses were applied to liquid/liquid extracted samples while bottom-up analyses were performed after trypsin digestion of both untreated and pretreated samples. The two proteomic approaches were complementary for the characterization of the proteome of craniopharyngioma intracystic fluid. Proteins and peptides involved in inflammation, mineralization processes and lipid transport were identified, in agreement with the calcium flecks, cholesterol granules and bone residues characteristic of this fluid. Apolipoprotein A-I, A-II, C-I and J, hemoglobin fragments, ubiquitin, α-2-HS-glycoprotein or fetuin A, α-1-antichymotrypsin, vitamin D binding protein, and α-1-acid glycoprotein were characterized. These data could be relevant for the comprehension of the processes involved in the pathogenesis of the disease and the development of the cyst and could contribute to the individuation of therapeutic targets for the reduction of the cyst volume delaying and/or avoiding invasive surgical treatments.

A1BG and C3 are overexpressed in patients with cervical intraepithelial neoplasia III

The present study aimed to analyze sera proteins in females with cervical intraepithelial neoplasia, grade III (CIN III) and in healthy control females, in order to identify a potential biomarker which detects lesions that have a greater probability of cervical transformation. The present study investigated five sera samples from females who were Human Papilloma Virus (HPV) 16⁺ and who had been histopathologically diagnosed with CIN III, as well as five sera samples from healthy control females who were HPV-negative. Protein separation was performed using two-dimensional (2D) gel electrophoresis and the proteins were stained with Colloidal Coommassie Blue. Quantitative analysis was performed using ImageMaster 2D Platinum 6.0 software. Peptide sequence identification was performed using a nano-LC ESIMS/MS system. The proteins with the highest Mascot score were validated using western blot analysis in an additional 55 sera samples from the control and CIN III groups. The eight highest score spots that were found to be overexpressed in the CIN III sera group were identified as α-1-B glycoprotein (A1BG), complement component 3 (C3), a pro-apolipoprotein, two apolipoproteins and three haptoglobins. Only A1BG and C3 were validated using western blot analysis, and the bands were compared between the two groups using densitometry analysis. The relative density of the bands of A1BG and C3 was found to be greater in all of the serum samples from the females with CIN III, compared with those of the individuals in the control group. In summary, the present study identified two proteins whose expression was elevated in females with CIN III, suggesting that they could be used as biomarkers for CIN III. However, further investigations are required in order to assess the expression of A1BG and C3 in different pre-malignant lesions.

SWATH™- and iTRAQ-based quantitative proteomic analyses reveal an overexpression and biological relevance of CD109 in advanced NSCLC

To identify cancer-related proteins, we used isobaric tags in a relative and absolute quantitation (iTRAQ) proteomic approach and SWATH™ quantification approach to analyze the secretome of an isogenic pair of highly metastatic and low metastatic non-small-cell lung cancer (NSCLC) cell lines. In addition, we compared two groups of pooled serum samples (12 early-stage and 12 late-stage patients) to mine data for candidates screened by iTRAQ-labeled proteomic analysis. A total of 110 proteins and 71 proteins were observed to be significantly differentially expressed in the cell line secretome and NSCLC sera, respectively. Among these proteins, CD109 was found to be highly expressed in both the highly metastatic cell line secretome and the group of late-stage patients. A sandwich ELISA assay also demonstrated an elevation of serum CD109 levels in individual NSCLC patients (n=30) compared with healthy subjects (n=19). Furthermore, CD109 displayed higher expression in lung cancer tissues compared with their matched noncancerous lung tissues (n=72). In addition, the knockdown of CD109 influenced several NSCLC cell bio-functions, for instance, depressing cell growth, affecting cell cycle phases. These phenomena suggest that CD109 plays a critical role in NSCLC progression.

BIOLOGICAL SIGNIFICANCE

We simultaneously applied two quantitative proteomic approaches-iTRAQ-labeling and SWATH™-to analyze the secretome of metastatic cell lines, in order to explore the cancer-associated proteins in conditioned media. In this study, our results indicate that CD109 plays a critical role in non-small-cell lung cancer (NSCLC) progression, and is overexpressed in advanced NSCLC.

Identification alpha-2-HS-glycoprotein precursor and tubulin beta chain as serology diagnosis biomarker of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient. Hence, the need for simple blood tests that could be used for the early detection is crucial for its ultimate control and prevention.

METHODS

The present work is a case-control study focused on proteomic analysis of serum of healthy volunteers and CRC patients by the ClinProt profiling technology based on mass spectrometry. This approach allowed to identifying a pattern of proteins/peptides able to differentiate the studied populations. Moreover, some of peptides differentially expressed in the serum of patients as compared to healthy volunteers were identified by LTQ Orbitrap XL.

RESULTS

A Quick Classifier Algorithm was used to construct the peptidome patterns (m/z 1208, 1467, 1505, 1618, 1656 and 4215) for the identification of CRC from healthy volunteers with accuracy close to 100% (>CEA, P < 0.05). Peaks at m/z 1505 and 1618 were identified as alpha-2-HS-glycoprotein precursor and tubulin beta chain, respectively.

CONCLUSIONS

Alpha-2-HS-glycoprotein precursor and tubulin beta chain could be involved in the pathogenesis of CRC and perform as potential serology diagnosis biomarker.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4796578761089186.

A penalized robust method for identifying gene-environment interactions

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model misspecification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example, with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications.

Expression of serum amyloid A in uterine cervical cancer

Background

As an acute-phase protein, serum amyloid A (SAA) is expressed primarily in the liver. However, its expression in extrahepatic tissues, especially in tumor tissues, was also demonstrated recently. In our study, we investigated the expression of SAA in uterine cervical carcinomas, and our results suggested its potential as a serum biomarker.

Methods

Quantitative real-time polymerase chain reaction (RT-PCR), immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA) were used to evaluate the SAA gene and protein expression levels in the tissues and sera of patients with non-neoplastic lesions (NNLs), cervical intraepithelial neoplasia (CIN) and cervical carcinoma (CC).

Results

Compared with NNLs, the SAA gene (SAA1 and SAA4) expression levels were significantly higher in uterine CC (mean copy numbers: 138.7 vs. 5.01, P < 0.000; and 1.8 vs. 0.079, P = 0.001, respectively) by real-time PCR. IHC revealed cytoplasmic SAA protein staining in tissues from adenocarcinoma and squamous cell carcinoma of the cervix. The median serum concentrations (μg/ml) of SAA were 6.02 in patients with NNLs and 10.98 in patients with CIN (P = 0.31). In contrast, the median serum SAA concentration was 23.7 μg/ml in uterine CC patients, which was significantly higher than the SAA concentrations of the NNL group (P = 0.002) and the CIN group (P = 0.024).

Conclusions

Our data suggested that SAA might be a uterine CC cell product. High SAA concentrations in the serum of CC patients may have a role in monitoring disease occurrence and could have therapeutic applications.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1433263219102962.