Identification Of Tumor Markers Research Articles

Diagnóstico de câncer oral através de biomarcadores, uma proposta não invasiva

The present study aimed to identify, through scientific literature, the use of biomarkers that help in the diagnosis of cancer in the oral cavity. This is a narrative review study with a qualitative and descriptive approach. To investigate the data, the databases of Periódicos Capes, PubMed and Sciencedirect were used, on the use of scientific articles, published during the time frame from 2019 to 2023, in Portuguese, English and Spanish, available online and free of charge, with expanded summary and in full text format. After applying filters, selecting descriptors and including review studies, meta-analysis, controlled and randomized tests, 52 articles were identified, among which 27 were from PubMed, 14 from Periódicos Capes and 11 from Science direct, in addition considering suitability, only 17 articles were registered for review. In this important study, it became evident that despite advances in the identification of tumor markers, they still do not have sufficient capacity to diagnose cancer in the oral cavity. However, it highlights its influence as an important tool for the prognosis of clinical conditions. Furthermore, it appears as a less invasive alternative, with more accessible samples such as saliva and promising results.

Drug screening and biomarker gene investigation in cancer therapy through the human transcriptional regulatory network

A complex and vast biological network regulates all biological functions in the human body in a sophisticated manner, and abnormalities in this network can lead to disease and even cancer. The construction of a high-quality human molecular interaction network is possible with the development of experimental techniques that facilitate the interpretation of the mechanisms of drug treatment for cancer. We collected 11 molecular interaction databases based on experimental sources and constructed a human protein-protein interaction (PPI) network and a human transcriptional regulatory network (HTRN). A random walk-based graph embedding method was used to calculate the diffusion profiles of drugs and cancers, and a pipeline was constructed by using five similarity comparison metrics combined with a rank aggregation algorithm, which can be implemented for drug screening and biomarker gene prediction. Taking NSCLC as an example, curcumin was identified as a potentially promising anticancer drug from 5450 natural small molecules, and combined with differentially expressed genes, survival analysis, and topological ranking, we obtained BIRC5 (survivin), which is both a biomarker for NSCLC and a key target for curcumin. Finally, the binding mode of curcumin and survivin was explored using molecular docking. This work has a guiding significance for antitumor drug screening and the identification of tumor markers.

Abstract 2944: Rapid and accurate variant calling of FFPE samples with the Genexus System

Abstract Next-Generation Sequencing technology has enhanced oncology research by enabling the detection of all cancer related variants into one assay for research and drug discovery programs. The Oncomine࣪ Comprehensive Assay v3, a pan-cancer panel, used with the Ion Torrent࣪ Genexus࣪ System allows for formalin-fixed paraffin embedded (FFPE) samples to be examined across 161 unique genes in an automated sample to result workflow in 30hrs. This study demonstrates ≥ 95% Sensitivity and PPV for detecting SNV, Indel, and Copy Number variants of clinical FFPE samples along with fusions. When tested using analytical controls, the Genexus System achieves ≥ 98% Sensitivity for hotspot variants, ≥ 95% for de novo variants, and 100% Sensitivity for fusion variants. The Ion Torrent࣪ Genexus࣪ System is fully automated and consists of two software linked instruments, the Ion Torrent࣪ Genexus࣪ Purification System and the Ion Torrent࣪ Genexus࣪ Integrated Sequencer. For this study, the purification system was used to sequentially extract and quantify DNA & RNA samples from human colon and lung FFPE tumor tissue. The purification instrument provides minimal hands-on-time, ease of use and compatibility with the integrated sequencer. It extracts and quantifies the nucleic acids, records the quantitation values and transfers the nucleic acids to an output plate. The plate is transferred from the purification instrument directly to the sequencer for sample dilution, library preparation, and sequencing using the Oncomine࣪ Comprehensive Assay v3 panel. Variant calling analysis of the DNA & RNA pairs is completed immediately following sequencing. Results show that the variants are detected reproducibly with ≥ 95% Sensitivity and PPV when compared to the Ion GeneStudio࣪ S5 System as an orthogonal method. All variants in the report were correct with p-values ≤ 10-5. Additionally, a subset of the extracted samples was evaluated using Sanger Sequencing to verify hotspot mutations found in samples sequenced on both the Genexus࣪ System and GeneStudio࣪ S5 System. Results show that all expected hotspot variants were detected. In summary, the Ion Torrent࣪ Genexus࣪ System is a reliable and fast turnaround solution for sample-to-variant calling results. When used with the Oncomine࣪ Comprehensive Assay v3 panel, the system provides accurate identification of tumor markers for oncology research. Citation Format: Iris Casuga, Frances Chan, Milton Huynh, Gregory R. Govoni, Kayla Zochowski, Thilanka Jayaweera, Janice Au-Young. Rapid and accurate variant calling of FFPE samples with the Genexus System [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2944.

A Survey of Computer-Aided Tumor Diagnosis Based on Convolutional Neural Network.

Simple SummaryOne of the hottest areas in deep learning is computerized tumor diagnosis and treatment. The identification of tumor markers, the outline of tumor growth activity, and the staging of various tumor kinds are frequently included. There are several deep learning models based on convolutional neural networks that have high performance and accurate identification, with the potential to improve medical tasks. Breakthroughs and updates in computer algorithms and hardware devices, and intelligent algorithms applied in medical images have a diagnostic accuracy that doctors cannot match in some diseases. This paper reviews the progress of tumor detection from traditional computer-aided methods to convolutional neural networks and demonstrates the potential of the practical application of convolutional neural networks from practical cases to transform the detection model from experiment to clinical application.Tumors are new tissues that are harmful to human health. The malignant tumor is one of the main diseases that seriously affect human health and threaten human life. For cancer treatment, early detection of pathological features is essential to reduce cancer mortality effectively. Traditional diagnostic methods include routine laboratory tests of the patient’s secretions, and serum, immune and genetic tests. At present, the commonly used clinical imaging examinations include X-ray, CT, MRI, SPECT scan, etc. With the emergence of new problems of radiation noise reduction, medical image noise reduction technology is more and more investigated by researchers. At the same time, doctors often need to rely on clinical experience and academic background knowledge in the follow-up diagnosis of lesions. However, it is challenging to promote clinical diagnosis technology. Therefore, due to the medical needs, research on medical imaging technology and computer-aided diagnosis appears. The advantages of a convolutional neural network in tumor diagnosis are increasingly obvious. The research on computer-aided diagnosis based on medical images of tumors has become a sharper focus in the industry. Neural networks have been commonly used to research intelligent methods to assist medical image diagnosis and have made significant progress. This paper introduces the traditional methods of computer-aided diagnosis of tumors. It introduces the segmentation and classification of tumor images as well as the diagnosis methods based on CNN to help doctors determine tumors. It provides a reference for developing a CNN computer-aided system based on tumor detection research in the future.

Early cancer diagnosis using lab-on-a-chip devices : A bibliometric and network analysis

In the future, early diagnosis of cancers may be performed using labon-a-chip devices. Yet, very little is known about the research obtained so far, who are the leading institutions, and how they collaborate. We address this gap by mapping the global research on early cancer diagnosis and labs-on-a-chip. Bibliometrics and network analysis were applied to analyze data of 301 articles collected in the Web of Science Core Collection, published between 2010 and 2020. The two most frequent tumor markers are the prostate-specific antigen and the carcinoembryonic antigen; the USA and China are the most relevant countries, and the Chinese Academy of Sciences and the Massachusetts Institute of Technology are the most publishing institutions; they also established the greatest research collaborations. This study identifies research trends on lab-on-a-chip for tumor marker identification, and the most publishing countries and institutions, which can be helpful to stakeholders working on this research topic.

Expression of Hippo signaling pathway and Aurora kinase genes in chronic myeloid leukemia.

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm resulting from clonal expansion of hematopoietic stem cells positive for the Philadelphia chromosome. The CML pathogenesis is associated with expression of the BCR-ABL1 oncogene, which encodes the Bcr-Abl protein with tyrosine kinase activity, promoting the leukemic cell exacerbated myeloproliferation and resistance to apoptosis. CML patients are usually treated with tyrosine kinase inhibitors (TKI), but some of them acquire resistance or are refractory to TKI. Thus, it is still relevant to elucidate the CML pathogenesis and seek new therapeutic targets, such as the Hippo signaling pathway and cell cycle regulatory genes fromtheAurora kinase family. The present study quantified the expression level of genes encoding components of the Hippo signaling pathway (LATS1, LATS2, YAP, and TAZ), AURKA and AURKB in CML patients at different stages of the disease, who were resistant or sensitive to imatinib mesylate therapy, and in healthy individuals. The expression levels of the target genes were correlated with the CML Sokal's prognostic score. The most striking results were the LATS2 and AURKA overexpression in CML patients, the overexpression of TAZ and AURKB in CML patients at advanced phasesand TAZ in CML IM-resistant. The development of drugs and/or identification of tumor markers for the Hippo signaling pathway and the Aurora kinase family, either alone or in combination, can optimize CML treatment by enhancing the susceptibility of leukemic cells to apoptosis and leading to a better disease prognosis.

Melanoma-associated antigen A2 is overexpressed in glioma and associated with poor prognosis in glioma patients.

Malignant glioma is the most common and aggressive primary brain tumor and the overall prognosis for glioma patients remains poor. Clarification of the molecular mechanism responsible for glioma progression is critical for the effective treatment of glioma. Melanoma antigen gene (MAGE)-A2 (MAGEA2) is a member of the MAGE-A family proteins widely studied for cancer vaccine development and identification of tumor markers. However, MAGEA2 clinical significance and biological function in glioma remain unclear, especially for the prognosis of glioma patients. This study investigates MAGEA2 expression in glioma tissue samples and its significance in predicting glioma patient prognosis. MAGEA2 protein expression in tissue samples was measured by immunohistochemistry and western blotting, and MAGEA2 mRNA expression was determined by real-time polymerase chain reaction. Our results confirmed that MAGEA2 mRNA and protein expression levels were upregulated in glioma tissues, compared with normal brain tissue. The high expression of MAGEA2 in glioma tissues significantly correlated with World Health Organization advanced grade. Univariate and multivariate analyses revealed that high MAGEA2 expression is an independent prognostic factor for glioma patient poor overall survival. The P53 mRNA expression levels were downregulated in glioma tissues compared to noncancerous brain tissue and MAGEA2 expression negatively correlated with P53 expression. Taken together, our results suggest that MAGEA2 plays an oncogenic role in glioma progression, and they provide insight into MAGEA2 application as a novel predictor of clinical outcomes and a potential glioma biomarker.

Spatial-resolved dual-signal-output electrochemiluminescent ratiometric strategy for accurate and sensitive immunoassay

The identification of tumor markers is of great importance for clinical diagnosis but accurate detection with high sensitivity is still a great challenge. In present work, a spatial-resolved dual-signal-output electrochemiluminescent (ECL) ratiometric assay platform was constructed for sensitive detection of prostate specific antigen (PSA) on a dual-disk glassy carbon electrode. To fabricate the platform, flower-like CdS three-dimensional (3D) assemblies and Ru(bpy)32+-conjugated silica nanoparticles (Ru(bpy)32+@RuSi NPs), were immobilized onto the two disks as cathodic and anodic ECL emitters, respectively. After the stepwise modification of the gold nanoparticles, antibody for PSA, and bovine serum albumin onto the two disks respectively, the Ru(bpy)32+@RuSi NPs-based disk were incubated with varied concentration of PSA as working electrode, whereas the flower-like CdS 3D assemblies-based disk with fixed concentration of PSA were taken as internal reference electrode. The label free assay of PSA was realized by the ratio of anodic ECL signal from working electrode to the cathodic ECL signal from the internal reference electrode (ECLanode/ECLcathode). On the basis of the spatial-resolved dual-signal-output ratiometric ECL sensor, the PSA can be detected accurately with a linear range of 0.001 – 50ng/mL at a concentration as low as 0.34pg/mL. Furthermore, the proposed method was applied for PSA determination in human serum samples with satisfying results. Thanks to the same modified process of the two disks, this universal design well avoids environmental errors including the interference caused in the biological recognition process, which effectively reduces the false positive or negative errors, exhibiting a greatly improved accuracy, reliability and sensitivity.

Feature selection method based on support vector machine and shape analysis for high-throughput medical data

Proteomics data analysis based on the mass-spectrometry technique can provide a powerful tool for early diagnosis of tumors and other diseases. It can be used for exploring the features that reflect the difference between samples from high-throughput mass spectrometry data, which are important for the identification of tumor markers. Proteomics mass spectrometry data have the characteristics of too few samples, too many features and noise interference, which pose a great challenge to traditional machine learning methods. Traditional unsupervised dimensionality reduction methods do not utilize the label information effectively, so the subspaces they find may not be the most separable ones of the data. To overcome the shortcomings of traditional methods, in this paper, we present a novel feature selection method based on support vector machine (SVM) and shape analysis. In the process of feature selection, our method considers not only the interaction between features but also the relationship between features and class labels, which improves the classification performance. The experimental results obtained from four groups of proteomics data show that, compared with traditional unsupervised feature extraction methods (i.e., Principal Component Analysis - Procrustes Analysis, PCA-PA), our method not only ensures that fewer features are selected but also ensures a high recognition rate. In addition, compared with the two kinds of multivariate filter methods, i.e., Max-Relevance Min-Redundancy (MRMR) and Fast Correlation-Based Filter (FCBF), our method has a higher recognition rate.

Trastuzumab stimulation of ribosomal protein S6 kinase 1 (S6K1) predicts de novo trastuzumab resistance

Breast cancer is a complex disease with at least five different molecular subtypes identified. The breast tumor molecular subtypes guide stratification of patients for specific targeted therapy regimens and each subtype is associated with significantly different patient outcomes. For example, patients with the HER2 positive molecular subtype benefit from the HER2 targeted therapy trastuzumab. Unfortunately, women with the HER2 positive molecular subtype have the worst overall prognosis and nearly 70% of women with HER2 positive breast cancer exhibit de novo or acquired resistance to trastuzumab. Identification of tumor markers predicting trastuzumab response can be used to further stratify patients for life-saving personalized therapeutic options. The aim of this study was to identify clinically useful tumor markers predicting de novo tumor cell resistance to trastuzumab treatment. To identify oncogenic signaling pathways activated in response to trastuzumab treatment, we performed a Human Phospho-Kinase Proteome Profiler Array analysis comparing trastuzumab sensitive MCF-7/HER2.2 and trastuzumab resistant MCF-7/HER2Δ16H cells following acute treatment with 20 μg/ml of trastuzumab for 2 h. We found that of the 43 phosphorylation activated human kinases represented on the array, S6K1 was the only kinase altered greater than 1.5-fold in response to trastuzumab treatment of the trastuzumab resistant MCF-7/HER2Δ16H cells. Trastuzumab activation of S6K1 was confirmed in the two trastuzumab resistant SUM190 and SUM225 cell lines. Significantly, trastuzumab failed to stimulate S6K1 activation in the trastuzumab sensitive MCF-7/HER2.2, BT474, and SKBR3 cell lines suggesting that trastuzumab activation of S6K1 is a tumor cell marker for trastuzumab resistance. Consistent with a role for mTORC1/S6K1 signaling promoting trastuzumab resistance, all cell lines were sensitive to S6K1 inactivation with significant growth inhibition following treatment with the mTORC1 inhibitor rapamycin. In conclusion, characterizing rapid trastuzumab induced molecular alterations resulted in the identification of activated S6K1 as an early breast tumor cell marker for trastuzumab resistance. Our results further suggest that trastuzumab resistant breast tumor cells are addicted to mTORC1/S6K1 oncogenic signaling and targeting mTORC1 with rapamycin reverses trastuzumab resistance.

Metabolic shifts induced by human H460 cells in tumor‐bearing mice

Tumor markers are most popularly used in diagnosis of various cancers clinically. However, the confounding factors of individual background diversities, such as genetics, food preferences, living styles, physical exercises, etc., greatly challenge the identification of tumor markers. Study of the metabolic impact of inoculated tumors on model animals can facilitate the identification of metabolomic markers relevant to tumor insult. In this study, serum metabolites from nude mice (n = 14) inoculated with human H460 cells (human nonsmall cell lung carcinoma) were profiled using gas chromatography time-of-flight mass spectrometry. The mice with inoculated tumors showed an obviously different metabolic pattern from the control; identification of the discriminatory metabolites suggested the metabolic perturbation of free fatty acids, amino acids, glycolysis and tricarboxylic acid (TCA) cycle turnover. The significantly decreased TCA intermediates, free fatty acids, 3-hydroxybutyric acid and fluctuating amino acids (t-test, p < 0.05) in serum of tumor-bearing mice characterized the metabolic impact of local inoculated H460 tumor cells on the whole system. This indicates that they are candidate metabolomic markers for translational study of lung cancer, clinically.

UbcH10 expression can predict prognosis and sensitivity to the antineoplastic treatment for colorectal cancer patients.

Colorectal cancer (CRC) is one of the most frequent and deadly malignancies worldwide. Despite the progresses made in diagnosis and treatment, the identification of tumor markers is still a strong clinical need, because current treatments are efficacious only in a subgroup of patients. UbcH10 represents a potential candidate biomarker, whose expression levels could be employed to predict response or resistance to chemotherapy or targeted agents. UbcH10 mRNA and protein expression levels have been evaluated in a large group of CRC patients and correlated with clinico-pathological characteristics, including KRAS mutations. Moreover, the endogenous levels of UbcH10 and its role on cell growth have been evaluated in CRC cells. Finally, to investigate the impact of UbcH10 protein expression on the response to irinotecan, its active metabolite SN-38 and cetuximab treatment, UbcH10 silencing experiments were carried-out on two colon carcinoma cell lines, Caco-2, and DLD1. Overexpression of UbcH10 mRNA and protein was observed in the vast majority of patients analyzed. UbcH10 suppression decreased CRC cell growth rate (at least in part through deregulation of Cyclin B and ERK1) and sensitized them to pharmacological treatments with irinotecan, SN-38 and cetuximab (at least in part through a down-regulation of AKT). Taken together, these findings indicate that UbcH10 expression regulates CRC growth and could play an important role in the personalization of the therapy of CRC patients.

Immunohitochemical study of p53 protein expression in gastroesophageal reflux disease

ObjectiveThis study aimed to determine p53 protein expression by immunohistochemistry in the esophageal mucosa of patients with gastroesophageal reflux disease (GERD).BackgroundGERD is a common clinical disorder that can significantly impact the patient's quality of life and pose a significant burden on healthcare systems worldwide. The incidence of esophageal adenocarcinoma has been increasing rapidly over the past few decades. The major risk factors predisposing to the development of adenocarcinoma are long-standing GERD and Barrett's esophagus. P53 protein expression in esophageal carcinogenesis is still being studied. The identification of tumor markers in patients with GERD may enable recognition of subgroups of patients who are more at risk of developing dysplasia and/or cancer.Patients and methodsThis study was carried out on 200 patients with symptoms of GERD. They were recruited from the endoscopy unit of Menoufia University Hospital between August 2010 and March 2013, and were included in group 1. According to the results of upper endoscopy and histopathology, they were subdivided as follows: group 1a included patients with GERD with erosive esophagitis ( n = 180), group 1b included patients with GERD and Barrett's esophagus ( n = 20), and group 2 included 20 patients with other GIT symptoms with no reflux and normal esophageal squamous epithelium; this was the control group. Written valid consent was obtained from every patient for examination and upper endoscopy; the clinical sheet for every case was completed, including assessment of history, examination, and the investigations required.ResultsWe found negative reactivity for p53 in 20 histologically normal patients (0%), and positive p53 protein expression in 76 patients (40%) in the esophagitis group and in 14 patients (70%) with Barrett's metaplasia ( n = 20). According to the Los Angeles classification grade, p53 was overexpressed in 33.3% ( n = 24) of esophagitis grade A (mild esophagitis) patients, 46.3% ( n = 32) of esophagitis grade B (moderate esophagitis) patients, 56.4% ( n = 22) of esophagitis grade C patients, and 60% ( n = 12) of esophagitis grade D (severe esophagitis) patients.ConclusionGERD grades C and D were more prevalent in Barrett's esophagus. P53 expression was higher in Barrett's esophagus than in erosive esophagitis compared with the normal group. P53 protein expression increases gradually with the severity of esophagitis caused by GERD.

Blinded Comparator Study of Immunohistochemical Analysis versus a 92-Gene Cancer Classifier in the Diagnosis of the Primary Site in Metastatic Tumors

Accurate tumor classification is fundamental to inform predictive biomarker testing and optimize therapy. Gene expression-based tests are proposed as diagnostic aids in cases with uncertain diagnoses. This study directly compared the diagnostic accuracy of IHC analysis versus molecular classification using a 92-gene RT-PCR assay for determination of the primary tumor site. This prospectively defined blinded study of diagnostically challenging cases included 131 high-grade, primarily metastatic tumors. Cases were reviewed and reference diagnoses established through clinical correlation. Blinded FFPE sections were evaluated by either IHC/morphology analysis or the 92-gene assay. The final analysis included 122 cases. The 92-gene assay demonstrated overall accuracy of 79% (95% CI, 71% to 85%) for tumor classification versus 69% (95% CI, 60% to 76%) for IHC/morphology analysis (P = 0.019). Mean IHC use was 7.9 stains per case (median, 8; range, 2 to 15). IHC/morphology analysis accuracy was 79%, 80%, and 46% when 1 to 6 (n = 42), 7 to 9 (n = 41), and >9 (n = 39) IHC stains were used, respectively, versus 81%, 85%, and 69%, respectively, with the 92-gene assay. Results from this blinded series of high-grade metastatic cases demonstrate superior accuracy with the 92-gene assay versus standard-of-care IHC analysis and strongly support the diagnostic utility of molecular classification in difficult-to-diagnose metastatic cancer.

Identification of tumor markers and targets through integrative genomic analysis of cancer transcriptomes

Identification of tumor markers and targets through integrative genomic analysis of cancer transcriptomes

Author Reply: Follow-Up for Gastric Cancer: How Extensive and Intensive Should It Be?

We appreciate the comments by Drs. Bali, Roukos, and Dr. Ziogas regarding our recently published article in the Annals of Surgical Oncology. To date, there have been no definite diagnostic methods established for recurrent gastric cancer, and recurrence has mostly been diagnosed using a combinatory analysis of several methods including computed tomography (CT), positron emission tomography (PET), tumor marker evaluation, and even diagnostic laparoscopy. Of these, CT has been the most popular method for detecting recurrent gastric cancer without invasiveness, although several reports have shown that CT is not specific for diagnosing recurrent tumors following curative gastric cancer surgery. However, our results indicated that CT is an essential follow-up method. Additional studies such as PET-CT or tumor marker identification require more clinical studies of their diagnostic accuracy and costeffectiveness before they can be established as follow-up methods. Based on our survey, follow-up studies after curative gastric cancer surgery are performed every 3 to 12 months with a physical examination and imaging methods in Korea. However, a consensus has not been reached for the optimal frequency of follow-up studies. Although patients with recurrent gastric cancer have poor outcomes, their prognoses have been improved using state-of-the-art treatments, such as new chemotherapeutic agents and molecular target therapy. Specifically, our previous study showed that complete resection of the metastatic lesion could lead to a better prognosis than other treatments. Therefore, early detection of recurrence by intensive follow-up can be meaningful. In addition, meta-analysis results of the cost effectiveness of follow-up studies after curative colorectal cancer surgery have revealed that intensive follow-up schedules were economically justified in the United Kingdom. However, there have been no studies performed to evaluate those after gastric cancer surgery. Randomized controlled clinical trials (RCTs) are needed to identify follow-up schedules that are optimal for patient survival and cost effectiveness between conventional and intensive follow-up strategies. In the future, extensive and intensive follow-up studies after curative gastric cancer surgery will be used according to the stage of the patient. Searching for gene mutations and tissue biomarkers may help to decide how extensive and intensive the follow-up studies should be to improve the prognosis of patients with recurrent gastric cancer. However, those issues should be discussed after routine follow-up schedules are established through additional clinical studies and well-designed randomized controlled clinical trials.

Diagnostic biomarker of asbestos‐related mesothelioma: Example of translational research

Mesothelioma is an aggressive tumor arising from the mesothelium, and is usually associated with previous exposure to asbestos. The incubation period of asbestos-related mesothelioma is estimated to be approximately 30-40 years. Once mesothelioma has occurred, there is no effective treatment. So, identification of tumor markers and a method for early diagnosis using such markers are urgently needed. Recently, several enzyme-linked immunosorbent assay systems for Erc/mesothelin have been developed, the reported usefulness of which has been assessed and demonstrated as a diagnostic tool. Asbestos-related mesothelioma should be ascribed as a typical environmental carcinogen. In this review, we will present asbestos-related mesothelioma for the study of problems in environmental carcinogenesis.

Identification of proteins released by follicular lymphoma-derived cells using a mass spectrometry-based approach

The recent advent of mass spectrometry-based methodologies for the analysis of complex protein mixtures opens new opportunities for the discovery of biomarkers that may aid in the diagnostic work-up of cancer. Follicular lymphoma (FL) is the most common form of low-grade non-Hodgkin lymphoma in the Western Hemisphere. Identification of tumor markers that facilitate early disease detection would be a significant advance in the management of FL. We have employed a strategy that entailed propagation of a follicular-derived cell line in serum-free media, protein extraction, and reverse-phase liquid chromatography, with subsequent electrospray ionization and tandem mass spectrometry analysis for the identification of proteins that are released by FL. Using a two-peptide minimum per protein and standard criteria, 209 proteins (5.6% maximum predicted error rate) released from the FL cells were identified. The released proteins included several growth factors, cytokines, acute phase reactants and cellular components previously known to be present in FL cells. Importantly, a greater proportion of proteins previously unassociated with FL were identified with high statistical confidence. Our studies provide a list of proteins, which may be candidates for early screening, diagnosis and therapeutic monitoring of patients with a suspected or biopsy-confirmed diagnosis of FL.

Identification of tumor markers and differentiation markers for molecular diagnosis of lung adenocarcinoma

To identify tumor markers and differentiation markers for lung adenocarcinoma (AdC), we analysed expression profiles of 14,500 genes against three cases of type II alveolar epithelial cells, bronchiolar epithelial cells, and bronchial epithelial cells, respectively, and 10 cases of AdC cells isolated by laser capture microdissection. Hierarchical clustering analysis indicated that AdC cells and noncancerous lung epithelial cells are significantly different in their expression profiles, and that different sets of differentiation markers are expressed among alveolar, bronchiolar and bronchial epithelial cells. Nine genes were identified as being highly expressed in AdC cells, but not expressed in noncancerous lung epithelial cells. Sixteen genes were identified as differentiation markers for lung epithelial cells. Real-time RT-PCR analysis of 45 lung AdC cases further revealed that expression of four tumor markers in AdC cells was significantly higher than that in noncancerous lung cells and that expression of ten differentiation markers was retained in a considerable fraction of lung AdC cases. Five tumor markers and seven differentiation markers were not expressed in peripheral blood cells. Similarities and differences in expression profiles between normal epithelial cells from different lung respiratory compartments and AdC cells demonstrated in this study will be informative for the molecular diagnosis of lung AdC.

Soluble mesothelin-related protein—A blood test for mesothelioma

Identification of tumor marker for mesothelioma (MM) might prove useful in diagnosis as well as for monitoring tumor in response to therapy and for screening at-risk individuals. We tested the hypothesis that soluble mesothelin-related protein (SMRP), a mesothelin family member, in the serum would be such a marker. Our data show that determination of SMRP in serum is a marker of MM with a sensitivity of sensitivity 83% and specificity 95% in the first 48 MM patients tested. Changes in serum SMRP levels parallel clinical course/tumor size and SMRP is elevated in 75% of patients at diagnosis. SMRP should also be useful for monitoring disease progression, and importantly, may prove useful for screening asbestos-exposed individuals for early MM.