SAA1 identified as a potential prediction biomarker for metastasis of hepatocellular carcinoma via multi-omics approaches

Background

Metastasis is the major cause of high recurrence and mortality of hepatocellular carcinoma (HCC). Unfortunately, there are few reports on effective biomarkers of HCC metastasis. Previous studies have reported that SAA1 may be a predictor and prognostic biomarker for multiple malignant tumors. However, the role of SAA1 in HCC has not yet been investigated.

Methods

We applied RNA sequencing and proteomics analysis to investigate the expression landscape of HCC cell lines and patient serum, respectively. SAA1 is a common key gene and listed as a candidate biomarker of HCC metastasis. It was validated in two cell lines, 107 participants serum, and 63 matched HCC and adjacent non-tumorous liver tissues. Human Protein Atlas (HPA), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) datasets were integrated to explore SAA1 expression among various cell types and organs. The diagnostic and prognostic value of SAA1 in HCC were determined through receiver operating characteristic (ROC) and Kaplan-Meier curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network were constructed for SAA1, as well as for its co-expressed genes. We further analyzed the correlation between SAA1 and co-expression genes.

Results

We found 7 differentially expressed genes (DEGs) and 14 differentially expressed proteins (DEPs) were related to HCC metastasis. SAA1, a key candidate biomarker, was highly enriched in hepatocytes and liver organ, and it was also highly expressed in HCC cells and the serum and tissues of HCC patients. The results of ROC curve analysis indicated that SAA1 had better predictive values for distinguishing HCC metastasis from non-metastasis. Kaplan-Meier curve analysis revealed that HCC patients with higher SAA1 expression had worse overall survival.

Conclusions

Our findings provide new insights into HCC metastasis by identifying candidate gene prediction biomarkers for HCC metastasis.

iTRAQ-Based Proteomic Analysis Reveals Potential Serum Biomarkers for Pediatric Non-Hodgkin's Lymphoma

Non-Hodgkin’s lymphoma (NHL) is the third most common malignant tumor among children. However, at initial NHL diagnosis, most cases are at an advanced stage because of nonspecific clinical manifestations and currently limited diagnostic methods. This study aimed to screen and verify potential serum biomarkers of pediatric NHL using isobaric tags for relative and absolute quantification (iTRAQ)-based proteomic analysis. Serum protein expression profiles from children with B-NHL (n=20) and T-NHL (n=20) and healthy controls (n=20) were detected by utilizing iTRAQ in combination with two-dimensional liquid chromatography-tandem mass spectrometry (2D LC–MS/MS) and analyzed by applying Ingenuity Pathway Analysis (IPA). The candidate biomarkers S100A8 and LRG1 were further validated by using enzyme-linked immunosorbent assays (ELISAs). Receiver operating characteristic (ROC) analysis based on ELISA data was used to evaluate diagnostic efficacy. In total, 534 proteins were identified twice using iTRAQ combined with 2D LC–MS/MS. Further analysis identified 79 and 73 differentially expressed proteins in B-NHL and T-NHL serum, respectively, compared with control serum according to our defined criteria; 34 proteins were overexpressed and 45 proteins underexpressed in B-NHL, whereas 45 proteins were overexpressed and 28 proteins underexpressed in T-NHL (p < 0.05). IPA demonstrated a variety of signaling pathways, including acute phase response signaling and liver X receptor/retinoid X receptor (LXR/RXR) activation, to be strongly associated with pediatric NHL. S100A8 and LRG1 were elevated in NHL patients compared to normal controls according to ELISA (p < 0.05), which was consistent with iTRAQ results. The areas under the ROC curves of S100A8, LRG1, and the combination of S100A8 and LRG1 were 0.873, 0.898 and 0.970, respectively. Our findings indicate that analysis of the serum proteome using iTRAQ combined with 2D LC–MS/MS is a feasible approach for biomarker discovery. Serum S100A8 and LRG1 are promising candidate biomarkers for pediatric NHL, and these differential proteins illustrate a novel pathogenesis and may be clinically helpful for NHL diagnosis in the future.

Experimental and computational modeling for signature and biomarker discovery of renal cell carcinoma progression

BACKGROUND

Renal Cell Carcinoma (RCC) is difficult to treat with 5-year survival rate of 10% in metastatic patients. Main reasons of therapy failure are lack of validated biomarkers and scarce knowledge of the biological processes occurring during RCC progression. Thus, the investigation of mechanisms regulating RCC progression is fundamental to improve RCC therapy.

METHODS

In order to identify molecular markers and gene processes involved in the steps of RCC progression, we generated several cell lines of higher aggressiveness by serially passaging mouse renal cancer RENCA cells in mice and, concomitantly, performed functional genomics analysis of the cells. Multiple cell lines depicting the major steps of tumor progression (including primary tumor growth, survival in the blood circulation and metastatic spread) were generated and analyzed by large-scale transcriptome, genome and methylome analyses. Furthermore, we performed clinical correlations of our datasets. Finally we conducted a computational analysis for predicting the time to relapse based on our molecular data.

RESULTS

Through in vivo passaging, RENCA cells showed increased aggressiveness by reducing mice survival, enhancing primary tumor growth and lung metastases formation. In addition, transcriptome and methylome analyses showed distinct clustering of the cell lines without genomic variation. Distinct signatures of tumor aggressiveness were revealed and validated in different patient cohorts. In particular, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. Machine learning and mathematical modeling confirmed the importance of CFB and SAA2 together, which had the highest impact on distant metastasis-free survival. From these data sets, a computational model predicting tumor progression and relapse was developed and validated. These results are of great translational significance.

CONCLUSION

A combination of experimental and mathematical modeling was able to generate meaningful data for the prediction of the clinical evolution of RCC.

High SAA1 Expression Predicts Advanced Tumors in Renal Cancer

Renal cell carcinoma (RCC) is the most frequent malignant tumor of the kidney. 30% of patients with RCC are diagnosed at an advanced stage. Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of RCC. Currently, advanced ccRCC lacks reliable diagnostic and prognostic markers. We explored the potential of SAA1 as a diagnostic and prognostic marker for advanced ccRCC. In this study, we mined and analyzed the public cancer databases (TCGA, UALCAN and GEPIA) to conclude that SAA1 was up-regulated at mRNA and protein levels in advanced ccRCC. We further found that hypomethylation of SAA1 promoter region was responsible for its high expression in ccRCC. Receiver operating characteristic curve (ROC) indicated that high SAA1 levels could distinguish advanced ccRCC patients from normal subjects (p < 0.0001). Kaplan-Meier curve analysis showed that high SAA1 levels predicted poor overall survival time (p < 0.0001) and poor disease-free survival time (p = 0.0003). Finally, the functional roles of SAA1 were examined using a si-SAA1 knockdown method in RCC cell lines. Our results suggest that SAA1 may possess the potential to serve as a diagnostic and prognostic biomarker for advanced ccRCC patients. Moreover, targeting SAA1 may represent as a novel therapeutic target for advanced ccRCC patients.

Serum metabolomic profiling correlated with ISS and clinical outcome for multiple myeloma patients treated with high-dose melphalan and autologous stem cell transplantation

The metabolome, which is the final down-stream global product of metabolic processes in organisms, is not sufficiently described in multiple myeloma (MM) patients. The aim of this study was, therefore, to study the serum metabolomic profile using proton nuclear magnetic resonance (¹H-NMR) spectroscopy, and its relationship to clinical characteristics and patient outcome. Serum samples, which were taken at diagnosis, from 201 MM patients who underwent high-dose melphalan followed by autologous stem cell transplantation as the first-line therapy, were analyzed. We found that the metabolomic profile differed between patients with different MM International Staging System (ISS) stages. The profile revealed increased levels of cholesterol, phospholipids, high-density lipoprotein, low-density lipoprotein, apolipoproteins A1 and A2, valine, and leucine in ISS I patients compared with ISS III patients. The metabolomic profile also differed between patients with IgA and IgG paraproteins, predominantly because of higher levels of high- and low-density lipoprotein subfractions in IgA patients. The exact pathway of metabolism leading to accumulation of these metabolites is still elusive, but this study indicates an area of interest for further investigation in the search for new therapy targets and prognostic markers for this disease.

Screening and identification of key genes between liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) by bioinformatic analysis

BACKGROUND

Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are common primary liver cancers worldwide. Liver stem cells have biopotential to differentiate into either hepatocytes and cholangiocytes, the phenotypic overlap between LIHC and CHOL has been acceptable as a continuous liver cancer spectrum. However, few studies directly investigated the underlying molecular mechanisms between LIHC and CHOL.

METHOD

To identify the candidate genes between LIHC and CHOL, three data series including GSE31370, GSE15765 and GSE40367 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape.

RESULTS

A total of 171 DEGs were identified, consisting of 49 downregulated genes and 122 upregulated genes. Compared with CHOL, the enriched functions of the DEGs mainly included steroid metabolic process, acute inflammatory response, coagulation. Meanwhile, the pathway of KEGG enrichment analyses showed that the upregulated gene(s) were mainly enriched complement and coagulation cascades, cholesterol metabolism and PPAR signaling pathway, while the downregulated gene(s) were mainly enriched in ECM-receptor interaction, focal adhesion, bile secretion. Similarly, the most significant module was identified and biological process analysis revealed that these genes were mainly enriched in regulation of blood coagulation, acute inflammatory response, complement and coagulation cascades. Finally, two (ITIH2 and APOA2) of 10 hub genes had been screened out to help differential diagnosis.

CONCLUSION

171 DEGs and two (ITIH2 and APOA2) of 10 hub genes identified in the present study help us understand the different molecular mechanisms between LIHC and CHOL, and provide candidate targets for differential diagnosis.

Prognostic role of pretreatment lactate dehydrogenase in patients with metastatic renal cell carcinoma: A systematic review and meta-analysis

BACKGROUND

To date, there remain uncertainties over the prognostic role of serum lactate dehydrogenase (LDH) in patients with metastatic renal cell carcinoma (mRCC). A systematic review and meta-analysis was performed.

MATERIALS AND METHODS

Eligible studies were retrieved from PubMed, Embase, Cochrane Library and Web of Science databases up to October 2019. The endpoints included overall survival (OS) and progression-free survival (PFS). Multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were used to evaluate each endpoint.

RESULTS

Thirty observational studies of low to moderate risk of bias embracing 6754 patients with mRCC were included. The results showed that patients with a high pretreatment serum LDH had an inferior OS (HR: 2.15, 95% CI: 1.85-2.51; P < 0.001) and PFS (HR: 1.76, 95% CI: 1.49-2.10; P < 0.001). Subgroup analyses according to year of publication, study design, patient population, geographic region, sample size and NOS score did not alter the direction of results. There was significant publication bias for OS, but not for PFS. Sensitivity analyses further confirmed the robustness of the results.

CONCLUSION

Our findings indicated that a high level of pretreatment serum LDH was associated with an inferior OS and DFS in patients with mRCC. Methodological limitations should be considered while interpreting these results.

Serum Derived Exosomes From Pancreatic Cancer Patients Promoted Metastasis: An iTRAQ-Based Proteomic Analysis

Background

Pancreatic cancer (PC) is one of the most aggressive malignancies and has a poor prognosis despite being extensively researched. The role of serum-derived exosomes in tumorigenesis and the development of PC is still unclear.

Method

The present study employed iTRAQ-based proteomic analysis to search for differences between the serum exosomes of PC patients and those from control patients. Then, bioinformatics methods were used to analyze the functions of the identified proteins, and the possible functions were verified through cell culture experiments.

Results

A total of 611 proteins were identified from exosomes, and 141 proteins were differentially expressed, with 91 up- and 50 down regulated proteins in PC cancer compared to healthy controls. Further analysis indicated that APOE serves as an important hub in the network. In addition, CRP, VWF, APOA2, NIN, and GSK3B potentially interact with many other proteins. We then tested the effect of patient serum-derived exosomes on pancreatic cancer cells and found that patient serum-derived exosomes, but not those from healthy controls, induced cell proliferation, migration, and EMT, supporting the role of exosomes in metastasis.

Conclusion

Our data suggest that exosomes derived from PC patients may promote PC metastasis.

The prognostic value of serum amyloid A in solid tumors: a meta-analysis

BACKGROUND

Previous studies have demonstrated that serum amyloid A (SAA) levels are correlated with the clinical outcomes of solid tumors. However, the available data have not been systematically evaluated. The objective of the present meta-analysis was to explore the prognostic value of SAA levels in solid tumors.

METHODS

Eligible studies were identified from the PubMed, EMBASE and Science Citation Index electronic databases. The clinical characteristics, disease/progression-free survival (DFS/PFS) and overall survival (OS) were extracted from the eligible studies. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated with Stata 12.0 software. We also performed subgroup, meta-regression and sensitivity analyses.

RESULTS

In total, 12 eligible studies including 2749 patients were enrolled in the present meta-analysis. The pooled HRs with 95% CIs showed that elevated levels of SAA were significantly associated with poor OS (HR = 3.01, 95% CI 1.96-4.63) and DFS/PFS (HR = 1.67, 95% CI 1.31-2.12) in patients with solid tumors. Although publication bias was seem found in the studies with regard to OS, a further trim and fill analysis revealed that the adjusted HR was 3.02 (95% CI 1.96-4.63), which was close to the original HR. Subgroup analysis confirmed an elevated level of SAA as a strong prognostic marker in patients with solid tumors, regardless of tumor type, detection method, cut-off value, sample size, area and variance analyses.

CONCLUSION

Our meta-analysis indicated that elevated levels of SAA might be an unfavorable prognostic marker for OS in patients with solid tumors.

Pyranocoumarin Tissue Distribution, Plasma Metabolome and Prostate Transcriptome Impacts of Sub-Chronic Exposure to Korean Angelica Supplement in Mice

Herbal products containing Korean Angelica gigas Nakai (AGN) root extract are marketed as dietary supplements for memory enhancement, pain killing, and female menopausal symptom relief. We have shown the anticancer activities of AGN supplements in mouse models. To facilitate human anticancer translational research, we characterized the tissue distribution of AGN marker pyranocoumarin compounds decursin (D) and decursinol angelate (DA) ([Formula: see text]% in AGN) and their metabolite decursinol (DOH), assessed the safety of sub-chronic AGN dietary exposure in mice, and explored its impact on plasma aqueous metabolites and the prostate transcriptome. The data show that after a gavage dose, plasma contained readily detectable DOH, but little D and DA, mirroring patterns in the liver. Extra-hepatic tissues retained greater levels of DA and D than the liver did. For sub-chronic exposures, male mice were provided ad libitum AIN93M-pellet diets with 0.5 and 1% AGN for six weeks. No adverse effects were observed on the plasma biochemistry markers of liver and kidney integrity in spite of their enlargement. Histopathological examinations of the liver, kidney and other visceral organs did not reveal tissue abnormalities. Metabolomic assessment of plasma from mice fed the 1%-AGN diet suggested metabolic shifts of key amino acids especially in the methionine-cysteine cycle, purine cycle, and glycolysis-citrate cycle. Prostate transcriptomic profiling identified gene signature changes in the metabolisms of drugs, lipids and cellular energetics, neuro-muscular features, immunity and inflammation, and tumor suppressor/oncogene balance. The safety profile was corroborated with a daily [Formula: see text] injection of AGN extract (100-300[Formula: see text]mg/kg) for four weeks, which resulted in much greater systemic pyranocoumarin exposure than the dietary route did.

Vitronectin and dermcidin serum levels predict the metastatic progression of AJCC I-II early-stage melanoma

Like many cancers, an early diagnosis of melanoma is fundamental to ensure a good prognosis, although an important proportion of stage I-II patients may still develop metastasis during follow-up. The aim of this work was to discover serum biomarkers in patients diagnosed with primary melanoma that identify those at a high risk of developing metastasis during the follow-up period. Proteomic and mass spectrophotometry analysis was performed on serum obtained from patients who developed metastasis during the first years after surgery for primary tumors and compared with that from patients who remained disease-free for more than 10 years after surgery. Five proteins were selected for validation as prognostic factors in 348 melanoma patients and 100 controls by ELISA: serum amyloid A and clusterin; immune system proteins; the cell adhesion molecules plakoglobin and vitronectin and the antimicrobial protein dermcidin. Compared to healthy controls, melanoma patients have high serum levels of these proteins at the moment of melanoma diagnosis, although the specific values were not related to the histopathological stage of the tumors. However, an analysis based on classification together with multivariate statistics showed that tumor stage, vitronectin and dermcidin levels were associated with the metastatic progression of patients with early-stage melanoma. Although melanoma patients have increased serum dermcidin levels, the REPTree classifier showed that levels of dermcidin <2.98 μg/ml predict metastasis in AJCC stage II patients. These data suggest that vitronectin and dermcidin are potent biomarkers of prognosis, which may help to improve the personalized medical care of melanoma patients and their survival.

Favorable prognostic influence of T-box transcription factor Eomesodermin in metastatic renal cell cancer patients

T-box transcription factors, T-box expressed in T cells (T-bet) encoded by Tbx21 and Eomesodermin (Eomes), drive the differentiation of effector/memory T cell lineages and NK cells. The aim of the study was to determine the prognostic influence of the expression of these transcription factors in peripheral blood (pB) in a cohort of 41 metastatic (m) RCC patients before receiving sorafenib treatment and to analyze their association with the immunophenotype in pB. In contrast to Tbx21, in the multivariate analysis including clinical features, Eomes mRNA expression was identified as an independent good prognostic factor for progression-free survival (PFS, p = 0.042) and overall survival (OS, p = 0.001) in addition to a favorable ECOG performance status (p = 0.01 and p = 0.008, respectively). Eomes expression correlated positively not only with expression of Tbx21 and TGFβ1 mRNA, but also with mRNA expression of the activation marker ICOS, and with in vivo activated HLA-DR(+) T cells. Eomes expression was negatively associated with TNFα-producing T cells. On protein level, Eomes was mainly expressed by CD56(+)CD3(-) NK cells in pB. In conclusion, we identified a higher Eomes mRNA expression as an independent good prognostic factor for OS and PFS in mRCC patients treated with sorafenib.

Prognostic role of lactate dehydrogenase in solid tumors: a systematic review and meta-analysis of 76 studies

BACKGROUND

In cancer cells, metabolism is shifted to aerobic glycolysis with lactate production coupled with a higher uptake of glucose as the main energy source. Lactate dehydrogenase (LDH) catalyzes the reduction of pyruvate to form lactate, and serum level is often raised in aggressive cancer and hematological malignancies. We have assessed the prognostic value of LDH in solid tumors.

MATERIAL AND METHODS

A systematic review of electronic databases was conducted to identify publications exploring the association of LDH with clinical outcome in solid tumors. Overall survival (OS) was the primary outcome, and cancer-specific survival (CSS), progression-free survival (PFS), and disease-free survival (DFS) were secondary outcomes. Data from studies reporting a hazard ratio (HR) and 95% confidence interval (CI) were pooled in a meta-analysis. Pooled HRs were computed and weighted using generic inverse-variance and random-effect modeling. All statistical tests were two-sided.

RESULTS

Seventy-six studies comprising 22 882 patients, mainly with advanced disease, were included in the analysis. Median cut-off of serum LDH was 245 U/L. Overall, higher LDH levels were associated with a HR for OS of 1.7 (95% CI 1.62-1.79; p < 0.00001) in 73 studies. The prognostic effect was highest in renal cell, melanoma, gastric, prostate, nasopharyngeal and lung cancers (all p < 0.00001). HRs for PFS was 1.75 (all p < 0.0001).

CONCLUSIONS

A high serum LDH level is associated with a poor survival in solid tumors, in particular melanoma, prostate and renal cell carcinomas, and can be used as a useful and inexpensive prognostic biomarker in metastatic carcinomas.

Multimarker proteomic profiling for the prediction of cardiovascular mortality in patients with chronic heart failure

Risk stratification of patients with systolic chronic heart failure (HF) is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was performed in a case/control discovery population of 198 patients with systolic HF (left ventricular ejection fraction <45%): 99 patients who died from cardiovascular cause within 3 years and 99 patients alive at 3 years. Proteomic scores predicting cardiovascular death were developed using 3 regression methods: support vector machine, sparse partial least square discriminant analysis, and lasso logistic regression. Forty two ion m/z peaks were differentially intense between cases and controls in the discovery population and were used to develop proteomic scores. In the validation population, score levels were higher in patients who subsequently died within 3 years. Similar areas under the curves (0.66 - 0.68) were observed for the 3 methods. After adjustment on confounders, proteomic scores remained significantly associated with cardiovascular mortality. Use of the proteomic scores allowed a significant improvement in discrimination of HF patients as determined by integrated discrimination improvement and net reclassification improvement indexes. In conclusion, proteomic analysis of plasma proteins may help to improve risk prediction in HF patients.

DNA methylation profiling reveals novel diagnostic biomarkers in renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is the tenth most commonly diagnosed cancer in the United States. While it is usually lethal when metastatic, RCC is successfully treated with surgery when tumors are confined to the kidney and have low tumor volume. Because most early stage renal tumors do not result in symptoms, there is a strong need for biomarkers that can be used to detect the presence of the cancer as well as to monitor patients during and after therapy.

METHODS

We examined genome-wide DNA methylation alterations in renal cell carcinomas of diverse histologies and benign adjacent kidney tissues from 96 patients.

RESULTS

We observed widespread methylation differences between tumors and benign adjacent tissues, particularly in immune-, G-protein coupled receptor-, and metabolism-related genes. Additionally, we identified a single panel of DNA methylation biomarkers that reliably distinguishes tumor from benign adjacent tissue in all of the most common kidney cancer histologic subtypes, and a second panel does the same specifically for clear cell renal cell carcinoma tumors. This set of biomarkers were validated independently with excellent performance characteristics in more than 1,000 tissues in The Cancer Genome Atlas clear cell, papillary, and chromophobe renal cell carcinoma datasets.

CONCLUSIONS

These DNA methylation profiles provide insights into the etiology of renal cell carcinoma and, most importantly, demonstrate clinically applicable biomarkers for use in early detection of kidney cancer.

Genes associated with metabolic syndrome predict disease-free survival in stage II colorectal cancer patients. A novel link between metabolic dysregulation and colorectal cancer

Studies have recently suggested that metabolic syndrome and its components increase the risk of colorectal cancer. Both diseases are increasing in most countries, and the genetic association between them has not been fully elucidated. The objective of this study was to assess the association between genetic risk factors of metabolic syndrome or related conditions (obesity, hyperlipidaemia, diabetes mellitus type 2) and clinical outcome in stage II colorectal cancer patients. Expression levels of several genes related to metabolic syndrome and associated alterations were analysed by real-time qPCR in two equivalent but independent sets of stage II colorectal cancer patients. Using logistic regression models and cross-validation analysis with all tumour samples, we developed a metabolic syndrome-related gene expression profile to predict clinical outcome in stage II colorectal cancer patients. The results showed that a gene expression profile constituted by genes previously related to metabolic syndrome was significantly associated with clinical outcome of stage II colorectal cancer patients. This metabolic profile was able to identify patients with a low risk and high risk of relapse. Its predictive value was validated using an independent set of stage II colorectal cancer patients. The identification of a set of genes related to metabolic syndrome that predict survival in intermediate-stage colorectal cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy and avoid the toxic and unnecessary chemotherapy in patients classified as low risk. Our results also confirm the linkage between metabolic disorder and colorectal cancer and suggest the potential for cancer prevention and/or treatment by targeting these genes.

Mass spectrometry-based serum and plasma peptidome profiling for prediction of treatment outcome in patients with solid malignancies

INTRODUCTION

Treatment selection tools are needed to enhance the efficacy of targeted treatment in patients with solid malignancies. Providing a readout of aberrant signaling pathways and proteolytic events, mass spectrometry-based (MS-based) peptidomics enables identification of predictive biomarkers, whereas the serum or plasma peptidome may provide easily accessible signatures associated with response to treatment. In this systematic review, we evaluate MS-based peptide profiling in blood for prompt clinical implementation.

METHODS

PubMed and Embase were searched for studies using a syntax based on the following hierarchy: (a) blood-based matrix-assisted or surface-enhanced laser desorption/ionization time-of-flight MS peptide profiling (b) in patients with solid malignancies (c) prior to initiation of any treatment modality, (d) with availability of outcome data.

RESULTS

Thirty-eight studies were eligible for review; the majority were performed in patients with non-small cell lung cancer (NSCLC). Median classification prediction accuracy was 80% (range: 66%-93%) in 11 models from 14 studies reporting an MS-based classification model. A pooled analysis of 9 NSCLC studies revealed clinically significant median progression-free survival in patients classified as "poor outcome" and "good outcome" of 2.0 ± 1.06 months and 4.6 ± 1.60 months, respectively; median overall survival was also clinically significant at 4.01 ± 1.60 months and 10.52 ± 3.49 months, respectively.

CONCLUSION

Pretreatment MS-based serum and plasma peptidomics have shown promising results for prediction of treatment outcome in patients with solid tumors. Limited sample sizes and absence of signature validation in many studies have prohibited clinical implementation thus far. Our pooled analysis and recent results from the PROSE study indicate that this profiling approach enables treatment selection, but additional prospective studies are warranted.

Molecular marker for predicting treatment response in advanced renal cell carcinoma: does the promise fulfill clinical need?

Renal cell carcinoma (RCC) is largely diagnosed incidentally on imaging taken for unrelated reasons. The management of localized lesions is primarily extirpative with excellent results. Treatment of advanced RCC has evolved over recent years with the use of targeted therapies such as tyrosine kinase inhibitors, mammalian target of rapamycin inhibitors, and antibody-mediated therapies. The treatment response to these targeted therapies is highly variable, with no clear clinical method of identifying patients who will benefit from or not tolerate therapy. The field of molecular markers has evolved significantly in the last decade, with a multitude of markers identified that predict treatment response and drug toxicity. The following review critically evaluates those molecular markers that have been assessed for their utility in predicting treatment response in patients with advanced/metastatic renal cell carcinoma (mRCC). Identifying the ideal treatment for these patients will improve responses to therapy, minimize morbidity, and save significant healthcare dollars.

Gene expression profile is associated with chemoradiation resistance in rectal cancer

AIM

Patients with rectal cancer who achieve a complete pathological response after preoperative chemoradiation (CRT) have an improved oncological outcome. Identifying factors associated with a lack of response could help our understanding of the underlying biology of treatment resistance. This study aimed to develop a gene expression signature for CRT-resistant rectal cancer using high-throughput nucleotide microarrays.

METHOD

Pretreatment biopsies of rectal adenocarcinomas were prospectively collected and freshly frozen according to an institutional review board-approved protocol. Total tumour mRNA was extracted and gene expression levels were measured using microarrays. Patients underwent proctectomy after completing standard long-course CRT and the resected specimens were graded for treatment response. Gene expression profiles for nonresponders were compared with those of responders. Differentially expressed genes were analyzed for functional significance using the Ingenuity Pathway Analysis (IPA) software.

RESULTS

Thirty-three patients treated between 2006 and 2009 were included. We derived 812-gene and 183-gene signatures separating nonresponders from responders. The classifiers were able to identify nonresponders with a sensitivity and specificity of 100% using the 812-gene signature, and sensitivity and specificity of 33% and 100% using the 183-gene signature. IPA canonical pathway analysis revealed a significant ratio of differentially expressed genes in the 'DNA double-strand break repair by homologous recombination' pathway.

CONCLUSION

Certain rectal cancer gene profiles are associated with poor response to CRT. Alterations in the DNA double-strand break repair pathway could contribute to treatment resistance and provides an opportunity for further studies.

MicroRNA expression profiling of peripheral blood samples predicts resistance to first-line sunitinib in advanced renal cell carcinoma patients

Anti-angiogenic therapy benefits many patients with advanced renal cell carcinoma (RCC), but there is still a need for predictive markers that help in selecting the best therapy for individual patients. MicroRNAs (miRNAs) regulate cancer cell behavior and may be attractive biomarkers for prognosis and prediction of response. Forty-four patients with RCC were recruited into this observational prospective study conducted in nine Spanish institutions. Peripheral blood samples were taken before initiation of therapy and 14 days later in patients receiving first-line therapy with sunitinib for advanced RCC. miRNA expression in peripheral blood was assessed using microarrays and L2 boosting was applied to filtered miRNA expression data. Several models predicting poor and prolonged response to sunitinib were constructed and evaluated by binary logistic regression. Blood samples from 38 patients and 287 miRNAs were evaluated. Twenty-eight miRNAs of the 287 were related to poor response and 23 of the 287 were related to prolonged response to sunitinib treatment. Predictive models identified populations with differences in the established end points. In the poor response group, median time to progression was 3.5 months and the overall survival was 8.5, whereas in the prolonged response group these values were 24 and 29.5 months, respectively. Ontology analyses pointed out to cancer-related pathways, such angiogenesis and apoptosis. miRNA expression signatures, measured in peripheral blood, may stratify patients with advanced RCC according to their response to first-line therapy with sunitinib, improving diagnostic accuracy. After proper validation, these signatures could be used to tailor therapy in this setting.

Apolipoprotein concentrations are elevated in malignant ovarian cyst fluids suggesting that lipoprotein metabolism is dysregulated in epithelial ovarian cancer

SELDI-TOF MS analysis of ovarian cyst fluids revealed that peaks m/z 8696 and 8825 discriminate malignant, borderline, and benign tumors. These peaks correspond to isoforms of apoA2. ELISA demonstrates that apoA1, A2, B, C2, C3, and E cyst fluid concentrations are uncorrelated and higher in malignant ovarian tumors, but only apoA2, apoE, and age are independent classifiers of malignant ovarian tumors, yielding 55.1% sensitivity, 95% specificity, and 88.1% accuracy to discern malignant from benign and borderline tumors. These data suggest that lipoprotein metabolism is dysregulated in ovarian cancer and that apoA2 and apoE warrant further investigation as ovarian tumor biomarkers.

Biochemical markers of bone turnover and clinical outcome in patients with renal cell and bladder carcinoma with bone metastases following treatment with zoledronic acid: The TUGAMO study

Background:

Levels of bone turnover markers (BTM) might be correlated with outcome in terms of skeletal-related events (SRE), disease progression, and death in patients with bladder cancer (BC) and renal cell carcinoma (RCC) with bone metastases (BM). We try to evaluate this possible correlation in patients who receive treatment with zoledronic acid (ZOL).

Methods:

This observational, prospective, and multicenter study analysed BTM and clinical outcome in these patients. Serum levels of bone alkaline phosphatase (BALP), procollagen type I amino-terminal propeptide (PINP), and beta-isomer of carboxy-terminal telopeptide of type I collagen (β-CTX) were analysed.

Results:

Patients with RCC who died or progressed had higher baseline β-CTX levels and those who experienced SRE during follow-up showed high baseline BALP levels. In BC, a poor rate of survival was related with high baseline β-CTX and BALP levels, and new SRE with increased PINP levels. Cox univariate analysis showed that β-CTX levels were associated with higher mortality and disease progression in RCC and higher mortality in BC. Bone alkaline phosphatase was associated with increased risk of premature SRE appearance in RCC and death in BC.

Conclusion:

Beta-isomer of carboxy-terminal telopeptide of type I collagen and BALP can be considered a complementary tool for prediction of clinical outcomes in patients with BC and RCC with BM treated with ZOL.

Proteomics: methodologies and applications to the study of human diseases

Proteomic approach has allowed large-scale studies of protein expression in different tissues and body fluids in discrete conditions and/or time points. Recent advances of methodologies in this field have opened new opportunities to obtain relevant information on normal and abnormal processes occurring in the human body. In the current report, the main proteomics techniques and their application to human disease study are reviewed.

Elevated levels of serum amyloid A indicate poor prognosis in patients with esophageal squamous cell carcinoma

BACKGROUND

Increase of Serum amyloid A (SAA) level has been observed in patients with a variety of cancers. The objective of this study was to determined whether SAA level could be used as a prognostic parameter in patients with esophageal squamous cell carcinoma (ESCC).

METHODS

SAA levels were measured by rate nephelometry immunoassay in 167 healthy controls and 167 ESCC patients prior to surgical resection. Statistical associations between clinicopathological observations and SAA levels were determined using the Mann-Whitney U test. The clinical value of SAA level as a prognostic parameter was evaluated using the Cox's proportional hazards model.

RESULTS

SAA levels were significantly higher in patients with ESCC compared to levels in healthy controls (13.88 ± 15.19 mg/L vs. 2.26 ± 1.66 mg/L, P < 0.001). Elevation of SAA levels (≥ 8.0 mg/L) was observed in 54.5% (91/167) of patients with ESCC but not in healthy controls. SAA levels were associated with tumor size (P < 0.001), histological differentiation (P = 0.015), T classification (P < 0.001), clinical stage (P < 0.001), lymph node metastasis (P < 0.001) and distant metastasis (P < 0.001), but not with the age and gender of the patients or tumor location. Multivariate analysis revealed that patients with an elevated level of SAA (≥ 8.0 mg/L) had significantly lower 5-year survival rate than those with non-elevated SAA (< 8.0 mg/L, log-rank P < 0.0001).

CONCLUSIONS

An elevated level of preoperative SAA was found to associate with tumor progression and poor survival in patients with ESCC.

Validation of serum amyloid α as an independent biomarker for progression-free and overall survival in metastatic renal cell cancer patients

BACKGROUND

We recently identified apolipoprotein A2 (ApoA2) and serum amyloid α (SAA) as independent prognosticators in metastatic renal cell carcinoma (mRCC) patients, thereby improving the accuracy of the Memorial-Sloan Kettering Cancer Center (MSKCC) model.

OBJECTIVE

Validate these results prospectively in a separate cohort of mRCC patients treated with tyrosine kinase inhibitors (TKIs).

DESIGN, SETTING, AND PARTICIPANTS

For training we used 114 interferon-treated mRCC patients (inclusion 2001-2006). For validation we studied 151 TKI-treated mRCC patients (inclusion 2003-2009).

MEASUREMENTS

Using Cox proportional hazards regression analysis, SAA and ApoA2 were associated with progression-free survival (PFS) and overall survival (OS). In 72 TKI-treated patients, SAA levels were analyzed longitudinally as a potential early marker for treatment effect.

RESULTS AND LIMITATIONS

Baseline ApoA2 and SAA levels significantly predicted PFS and OS in the training and validation cohorts. Multivariate analysis identified SAA in both separate patient sets as a robust and independent prognosticator for PFS and OS. In contrast to our previous findings, ApoA2 interacted with SAA in the validation cohort and did not contribute to a better predictive accuracy than SAA alone and was therefore excluded from further analysis. According to the tertiles of SAA levels, patients were categorized in three risk groups, demonstrating accurate risk prognostication. SAA as a single biomarker showed equal prognostic accuracy when compared with the multifactorial MSKCC risk mode. Using receiver operating characteristic analysis, SAA levels >71 ng/ml were designated as the optimal cut-off value in the training cohort, which was confirmed for its significant sensitivity and specificity in the validation cohort. Applying SAA >71 ng/ml as an additional risk factor significantly improved the predictive accuracy of the MSKCC model in both independent cohorts. Changes in SAA levels after 6-8 wk of TKI treatment had no value in predicting treatment outcome.

CONCLUSIONS

SAA but not ApoA2 was shown to be a robust and independent prognosticator for PFS and OS in mRCC patients. When incorporated in the MSKCC model, SAA showed additional prognostic value for patient management.

Serum amyloid a protein in clinical cancer diagnosis

The serum amyloid A (SAA) protein is an acute phase protein that is synthesized under the regulation of inflammatory cytokines during both acute and chronic inflammation. It is suggested that the SAA increases correlate with many types of carcinogenesis and neoplastic diseases. Th changes in SAA in serum could therefore indicate the progress and malignancy of the disease, as well as the host responses. The present paper reviewed the rationale of using SAA as potential cancer biomarker in clinical diagnosis, including the contribution and involvement of SAA in cancer growth and development. Then we discussed the current applications of SAA in diagnosis and tracing of different types of cancers. Finally the proteomics techniques, especially the SELDI-TOF MS to identify SAA in serum from patients were appreciated as an important manner in clinical diagnosis.

Basic research in kidney cancer

CONTEXT

Advances in basic research will enhance prognosis, diagnosis, and treatment of renal cancer patients.

OBJECTIVE

To discuss advances in our understanding of the molecular basis of renal cancer, targeted therapies, renal cancer and immunity, and genetic factors and renal cell carcinoma (RCC).

EVIDENCE ACQUISITION

Data on recently published (2005-2011) basic science papers were reviewed.

EVIDENCE SYNTHESIS

Advances in basic research have shown that renal cancers can be subdivided based on specific genetic profiles. Now that this molecular basis has been established, it is becoming clear that additional events play a major role in the development of renal cancer. For example, aberrant chromatin remodelling appears to be a main driving force behind tumour progression in clear cell RCC. A large number of potential biomarkers have emerged using various high-throughput platforms, but adequate biomarkers for RCC are still lacking. To bring the potential biomarkers and biomarker profiles to the clinical arena is a major challenge for the field. The introduction of tyrosine kinase inhibitors (TKIs) for therapy has shifted the interest away from immunologic approaches. Nevertheless, a wealth of evidence supports immunotherapy for RCC. Interestingly, studies are now appearing that suggest a combination of TKI and immunotherapy may be beneficial. Thus far, little attention has been paid to patient-specific differences. With high-throughput methods becoming cheaper and with the advances in sequencing possibilities, this situation is expected to change rapidly.

CONCLUSIONS

Great strides have been made in the understanding of molecular mechanisms of RCC. This has led this field to the enviable position of having a range of molecularly targeted therapies. Large sequencing efforts are now revealing more and more genes responsible for tumour development and progression, offering new targets for therapy. It is foreseen that through integration of high-throughput platforms, personalised cancer treatment for RCC patients will become possible.

Reproducibility of SELDI Spectra Across Time and Laboratories

This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.

The reproducibility of mass spectrometry (MS) data collected using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) has been questioned. This investigation was designed to test the reproducibility of SELDI data collected over time by multiple users and instruments. Five laboratories prepared arrays once every week for six weeks. Spectra were collected on separate instruments in the individual laboratories. Additionally, all of the arrays produced each week were rescanned on a single instrument in one laboratory. Lab-to-lab and array-to-array variability in alignment parameters were larger than the variability attributable to running samples during different weeks. The coefficient of variance (CV) in spectrum intensity ranged from 25% at baseline, to 80% in the matrix noise region, to about 50% during the exponential drop from the maximum matrix noise. Before normalization, the median CV of the peak heights was 72% and reduced to about 20% after normalization. Additionally, for the spectra from a common instrument, the CV ranged from 5% at baseline, to 50% in the matrix noise region, to 20% during the drop from the maximum matrix noise. Normalization reduced the variability in peak heights to about 18%. With proper processing methods, SELDI instruments produce spectra containing large numbers of reproducibly located peaks, with consistent heights.

Serum proteome analysis for profiling protein markers associated with lymph node metastasis in colorectal carcinoma

Colorectal cancer (CRC) is the second leading cause of cancer death in the human population worldwide. In China, CRC ranks fifth among cancer deaths, with a continuous increase in the incidence. Most CRC patients have lymph node metastasis (LNM) when first diagnosed. Two-dimensional (2D) serum proteome analysis may be useful in discovering new biomarkers that may aid in the diagnosis and therapy of CRC patients. To determine the tumour metastasis-specific antigen markers of CRC metastasis, sera from 32 patients with non-LNM CRC and 40 patients with LNM CRC were selected for screening using 2D serum proteome analysis combined with mass spectrometry (MS). Pretreatment strategies, including sonication and depletion of albumin and immunoglobulin (Ig) G, were adopted for screening differentially expressed proteins of low abundance in serum. By 2D image analysis and Matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF)-MS identification, eight protein spots were differentially expressed and successfully identified. The molecule transthyretin (TTR) was further studied in these sera by enzyme-linked immunosorbent assay. TTR appears to be a potential CRC metastasis-specific serum biomarker, which may be of value in the clinical detection and management of CRC.

Immunochemotherapy-associated protein patterns in tumour tissue and serum of patients with metastatic renal cell carcinoma

CONTEXT

Systemic treatment of metastatic renal cell carcinoma (mRCC) with targeted therapies became widely accepted; however, there are few patients who greatly benefit from immunochemotherapy (ICT). It is crucial to recognize these patients for individual treatment.

OBJECTIVES

Definition of protein patterns in tissue and serum from mRCC-patients to predict benefit from ICT.

MATERIALS AND METHODS

Twenty-five tissue samples and 59 sera were analysed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Protein peaks of interest were identified by 2D-PAGE and peptide mass fingerprinting. Validation was carried out by Western Blot and ELISA.

RESULTS

Protein patterns associated with therapy response were determined. Caveolin-1 (CAV-1) and plasminogen activator inhibitor 1 (PAI-1) were identified in tissue; serum amyloid A (SAA) and transthyretin (TTR) were found in serum.

CONCLUSION

Individual prediction of therapy benefit and selecting patients for ICT based on molecular biological profiles appear to be feasible in the future.

Serum amyloid A is elevated in the serum of lung cancer patients with poor prognosis

Background:

Lung cancer is known as the top cancer killer in most developed countries. However, there is currently no promising diagnostic or prognostic biomarker for lung cancer. This study aims to discover non-invasive differential markers in the serum of lung cancer patients, to determine the protein identity of the candidate biomarker(s), and to investigate any clinical implication of the biomarker(s) concerned.

Methods:

Blood specimens were collected from 154 pre-operative patients with lung cancer and 35 healthy blood donors with no evidence of lung cancer. Fractionated serum samples were processed by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (MS). Candidate biomarker was identified using sodium dodecyl sulphate polyacrylamide gel electrophoresis and tryptic digestion followed by tandem MS fragmentation analysis, which was subsequently validated with immunoassay.

Results:

A differential protein with m/z 11.6 kDa was detected and identified as an isoform of human serum amyloid A (SAA). It was significantly increased by 1822% in lung cancer patients when compared with the healthy controls, which gave an area under the receiver operator characteristic curve of 0.88. In addition, the protein was also significantly elevated by 77% in lung cancer patients with survival <5 years when compared with patients with survival ⩾5 years.

Conclusion:

There are several functions of the SAA protein, described in the context of inflammation, that are compatible with the mechanism of tumour invasion and metastasis. Our study not only detected increased SAA level in the serum of lung cancer patients but also identified that elevated SAA level may be a non-invasive biomarker useful for the prediction of lung cancer prognosis.