A combined biomarker pattern improves the discrimination of lung cancer

Identifying a combined biomarker for bisphosphonate-related osteonecrosis of the jaw

BACKGROUND

For this study, the aim was to identify combined biomarkers associated with bisphosphonate-related osteonecrosis of the jaw (BRONJ).

MATERIALS AND METHODS

Microarray data for GSE7116 were downloaded from the Gene Expression Omnibus database, which contains 26 samples, including without ONJ, and 5 healthy volunteers. The combined biomarkers were identified using principal component analysis, and the pathway enrichment analyses were performed using the DAVID online tool.

RESULTS

Two hundred differently expressed genes between groups were detected according to the significances. From functional annotation, Y-box binding protein 1 and heterogeneous nuclear ribonucleoprotein C were found to be included in the most significant 10 pathways. Ten combined gene sets were identified that were effective in classifying multiple myeloma (MM) with ONJ and MM without ONJ.

CONCLUSION

Identifying combined gene expression profiles is expected to contribute to more personalized management of BRONJ and to improve existing therapies, and it will be helpful in finding new therapies by identifying more predictive biomarkers.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

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.

Transthyretin as a potential biomarker for the differential diagnosis between lung cancer and lung infection

Satisfactory biomarkers for screening and early diagnosis of lung cancer remain scarce and require further investigation. The aim of the present study was to examine the changes of the biochemical and protein composition in the serum and pleural effusion from lung cancer and lung infection (bacterial pneumonia) patients. A total of 92 patients with lung cancer, 38 with bacterial pneumonia and 42 healthy controls were enrolled in the study. The serum levels of cholesterol, apolipoprotein A and transthyretin (TTR) in the lung cancer patients were higher than that of the lung infection patients (P<0.05). The levels of TTR were higher, whereas the activity of adenosine deaminase (ADA) was lower in the pleural effusion from the lung cancer patients compared to the lung infection patients (P<0.05). Furthermore, the pleural effusion/serum TTR ratios in the lung cancer patients were higher, whereas the ratios of ADA were lower (P<0.05). By matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis, four major peaks corresponding to native TTR, Sul-TTR, Cys-TTR and Cysgly-TTR were observed in the serum of the lung cancer and lung infection patients. A significant increase was found in the proportion of Cysgly-TTR in the pleural effusion from the patients with lung cancer. The data indicated that a combination of pleural effusion/serum TTR ratios and modified TTR may be beneficial for the differential diagnosis between lung cancer and lung infection.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

A primary proteomic analysis of serum from patients with nonfunctioning pituitary adenoma

OBJECTIVE

The early diagnosis of nonfunctioning pituitary adenoma (NFPA) is difficult. The objective of this study was to find specific protein biomarkers to aid in the early detection of NFPA.

METHODS

Serum samples from 34 patients with NFPA and 34 age- and sex-matched healthy control subjects were analysed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. The spectra were generated, protein peak clustering was performed and classification analyses were carried out using a decision tree classification algorithm.

RESULTS

Nine differentially expressed serum proteins were identified in the patients with NFPA compared with the control subjects. Both the sensitivity and specificity of the decision tree classification algorithm were 82.4% for NFPA.

CONCLUSIONS

Nine new serum protein biomarkers for NFPA were identified. SELDI-TOF-MS coupled with data mining tools might provide a novel approach for the early diagnosis of NFPA and population screening for the disease.

Screening and identification of serum proteomic biomarkers for gastric adenocarcinoma

The aim of the present study was to screen for possible serum biomarkers for gastric adenocarcinoma. Surface-enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) was used to screen serum samples from 109 cases of gastric adenocarcinoma and 106 control subjects (60 healthy subjects, 30 patients with chronic superficial gastritis and 16 cases of chronic atrophic gastritis). The differentially expressed protein peaks were selected and isolated using high performance liquid chromatography (HPLC) and processed with enzyme prior to liquid chromatography-mass spectrometry tandem mass spectrometry (LC-MS/MS) analysis and data mining with software XCalibur program components BioWorks 3.2. Among the gastric cancer cases, three differentially expressed protein peaks were selected as potential serum biomarkers: the m/z peaks at 5,906.5 showed increased expression (8.53±4.33 in the cancer group, and 0.88±0.31 in the control group); the m/z peaks at 6,635.7 and 8,716.3 showed decreased expression (6.54±2.44 and 0.93±0.29, respectively, in the cancer group and 17.56±4.43 and 2.16±0.98, respectively, in the control group) (P<0.01). The m/z peaks at 5,906.5, 6,635.7 and 8,716.3, were identified as fibrinogen α-chain, apolipo-protein A-II and apolipoprotein C-I. The combined use of the three biomarkers distinguished the cancer group patients from the control group samples at a sensitivity of 93.85% (61/65) and a specificity of 94.34% (50/53). In conclusion, fibrinogen α-chain, apolipoprotein A-II and apolipoprotein C-I were identified as potential markers for gastric cancer and appear to have diagnostic value for clinical applications.

Human urine proteomics: building a list of human urine cancer biomarkers

In the last decade, several reports have focused on the identification and characterization of proteins present in urine. In an effort to build a list of proteins of interest as biomarkers, we reviewed the largest urine proteomes and built two updated lists of proteins of interest (available as supplementary tables). The first table includes a consensus list of 443 proteins found in urine by independent laboratories and reported on the top three largest urine proteomes currently published. This consensus list of proteins could serve as biomarkers to diagnose, monitor and manage a number of diseases. Here, we focus on a reduced list of 35 proteins with potential interest as cancer biomarkers in urine following two criteria: first, proteins previously detected in urine using bottom-up proteomic experiments, and second, those suggested as cancer protein biomarkers in human plasma. In an effort to standardize the information presented and its use in future studies, here we include the updated International Protein Index (v. 3.80) and primary Swiss-Prot accession numbers, official gene symbols and recommended full names. The main variables that influence urine proteomic experiments are also discussed.