General keynote: proteomic patterns in sera serve as biomarkers of ovarian cancer

Proteomic Strategies and their Application in Cancer Research

The understanding of carcinogenesis and tumor progression on a molecular basis needs a detailed study of proteins as effector molecules and as critical components of the multiple interconnected signaling pathways that drive the neoplastic phenotype. Thus, the proteomic approach represents a powerful tool for the challenge of the post-genomic era. The term “cancer proteome” refers to the collection of proteins expressed by a given cancer cell and should be considered as a highly dynamic entity within the cell, which affects a variety of cellular activities. The emerging proteomic analysis platforms including 2D-PAGE, mass spectrometry technologies, and protein microarrays represent powerful tools to study and understand cancer. These systems aim to not only identify, catalogue, and characterize cancer proteins, but also to unveil how they interact to affect overall tumor progression. Moreover, recent studies on various cancers have reported promising results concerning the detection of novel molecular biomarkers useful in the early diagnosis of cancer and in drug discovery. Thus, a new subdiscipline named clinical proteomics, concomitant with new molecular technologies that are developed, demonstrates promise to discover new cancer biomarkers. The early diagnosis of cancer, even in a premalignant state, is crucial for the successful treatment of this disease. For these reasons, it is clear that the identification of biomarkers for the early diagnosis of cancer should represent one of the main goals of this emerging field of study.

Conventional and Proteomic Technologies for the Detection of Early Stage Malignancies: Markers for Ovarian Cancer

Our understanding of the tumor microenvironment continues to evolve and allows for the identification of biomarkers that should detect the presence of early stage malignancies. Recent advances in computational analysis and biomedical technologies have come together to elucidate signatures associated with cancer and that are capable of identifying unique tumor-specific proteins. Within the tumor microenvironment, we continue to characterize the proteophysiology of the different steps associated with tumor progression. The urgent need for biomarkers accurately detecting early-stage epithelial ovarian cancer has prompted us, and others, to engage in a search for specific peptide signatures that may discriminate transformed cells from those of the normal ovarian microenvironment. This endeavor also provides new insights into the biology of the disease, which may not only be applicable to detection but may also help to initiate new therapies and optimize patient care.

Biomarker discovery in lung cancer--promises and challenges of clinical proteomics

Lung cancer is a devastating illness with an overall poor prognosis. To effectively address this disease, early detection and novel therapeutics are required. Early detection of lung cancer is challenging, in part because of the lack of adequate tumor biomarkers. The goal of this review is to summarize the knowledge of current biomarkers in lung cancer, with a focus on important serum biomarkers. The current knowledge on the known serum cytokines and tumor biomarkers of lung cancer will be presented. Emerging trends and new findings in the search for novel diagnostic and therapeutic tumor biomarkers using proteomics technologies and platforms are emphasized, including recent advances in mass spectrometry to facilitate tumor biomarker discovery program in lung cancer. It is our hope that validation of these new research platforms and technologies will result in improved early detection, prognostication, and finally the treatment of lung cancer with potential novel molecularly targeted therapeutics.

Proteomic search for potential diagnostic markers and therapeutic targets for ovarian clear cell adenocarcinoma

Clear cell adenocarcinoma (CCA) has a highly malignant potential in human epithelial ovarian cancer. The serum CA-125 is widely used as a marker for ovarian cancer, but the level is relatively low in CCA. Therefore, new sensitive biomarkers are required. In this report, we describe a promising proteomic analysis that is differentially expressed in CCA when compared to mucinous adenocarcinoma, using the ovarian cultured cell lines OVISE, OVTOKO, and MCAS. The disease-associated proteins were identified by 2-D differential gel electrophoresis (2-D DIGE) and MS. In this analysis, 18 up-regulated and 31 down-regulated spots were observed that had at least two-fold differences in the two CCA cell lines than in MCAS as control cells. Some of the proteins differentially expressed in CCA were previously observed as alternative expression levels in ovarian and/or other cancers in clinical samples. In a subsequent preliminary differential study using surgical specimens from patients with CCA, it was demonstrated that the identified proteins were expressed differentially in actual tissues, as well as in the CCA culture cells. The results from this investigation show the potentiality of a proteomic approach for identifying disease-associated proteins, which may eventually serve as diagnostic markers or therapeutic targets in CCA.

Analysis of differential protein expression in Acidithiobacillus ferrooxidans grown under different energy resources respectively using SELDI-ProteinChip technologies

Surface-enhanced laser desorption/ionization (SELDI)-time of flight is an affinity-based mass spectrometric method in which proteins of interest are selectively absorbed to a chemically modified surface on a chip, which allows proteomic analysis with limited material requirements. This characteristic makes it a valuable technique for microbiologists handling problematic samples, such as low cell number cultures. In this study, we explored differential-expressed proteome of Acidithiobacillus ferrooxidans cultivated with Fe(2+) and elemental sulfur separately by adopting the protein biochip SELDI approach. The cell lysates of A. ferrooxidans were applied onto Ciphergen ProteinChip WCX2, SAX2 and IMAC-Cu arrays. Proteins bound to the chips were analyzed on a ProteinChip Reader Model PBS II. A summary of the molecular masses of the differentially regulated proteins found on WCX2, IMAC-Cu and SAX2 was obtained and 28 differentially expressed proteins were found on the molecular weight range of 5.0 to 25 kDa.

Liver tumors in wild flatfish: a histopathological, proteomic, and metabolomic study

Fish play host to viral, bacterial, and parasitic diseases in addition to non-infectious conditions such as cancer. The National Marine Monitoring Programme (NMMP) provides information to the U.K. Government on the health status of marine fish stocks. An aspect of this work relates to the presence of tumors and other pathologies in the liver of the offshore sentinel flatfish species, dab (Limanda limanda). Using internationally agreed quality assurance criteria, tumors and pre-tumors are diagnosed using histopathology. The current study has expanded upon this work by integrating these traditional diagnostic approaches with ones utilizing modern technologies for analysis of proteomic and metabolomic profiles of selected lesions. We have applied SELDI and FT-ICR technologies (for proteomic and metabolomic analyses, respectively) to tumor and non-tumor samples resected from the liver of dab. This combined approach has demonstrated how these technologies are able to identify protein and metabolite profiles that are specific to liver tumors. Using histopathology to classify "analysis groups" is key to the success of such an approach since it allows for elimination of spurious samples (e.g., those containing parasite infections) that may confuse interpretation of "omic" data. As such, the pathology laboratory plays a central role in collating information relating to particular specimens and in establishing sampling groups relative to specific diagnostic questions. In this study, we present pilot data, which illustrates that proteomics and metabolomics can be used to discriminate fish liver tumors and suggest future directions for work of this type.

A Chronic Fatigue Syndrome - related proteome in human cerebrospinal fluid

BACKGROUND

Chronic Fatigue Syndrome (CFS), Persian Gulf War Illness (PGI), and fibromyalgia are overlapping symptom complexes without objective markers or known pathophysiology. Neurological dysfunction is common. We assessed cerebrospinal fluid to find proteins that were differentially expressed in this CFS-spectrum of illnesses compared to control subjects.

METHODS

Cerebrospinal fluid specimens from 10 CFS, 10 PGI, and 10 control subjects (50 mul/subject) were pooled into one sample per group (cohort 1). Cohort 2 of 12 control and 9 CFS subjects had their fluids (200 mul/subject) assessed individually. After trypsin digestion, peptides were analyzed by capillary chromatography, quadrupole-time-of-flight mass spectrometry, peptide sequencing, bioinformatic protein identification, and statistical analysis.

RESULTS

Pooled CFS and PGI samples shared 20 proteins that were not detectable in the pooled control sample (cohort 1 CFS-related proteome). Multilogistic regression analysis (GLM) of cohort 2 detected 10 proteins that were shared by CFS individuals and the cohort 1 CFS-related proteome, but were not detected in control samples. Detection of >or=1 of a select set of 5 CFS-related proteins predicted CFS status with 80% concordance (logistic model). The proteins were alpha-1-macroglobulin, amyloid precursor-like protein 1, keratin 16, orosomucoid 2 and pigment epithelium-derived factor. Overall, 62 of 115 proteins were newly described.

CONCLUSION

This pilot study detected an identical set of central nervous system, innate immune and amyloidogenic proteins in cerebrospinal fluids from two independent cohorts of subjects with overlapping CFS, PGI and fibromyalgia. Although syndrome names and definitions were different, the proteome and presumed pathological mechanism(s) may be shared.

Proteomic approaches in colon cancer: promising tools for new cancer markers and drug target discovery

Novel technologies are needed from which to identify new and more efficient biomarkers and improved molecular targets for the expedient and accurate diagnosis and treatment of colorectal cancer. Many advances have been made in direct and virtual imaging for detection of polyps and malignant-type lesions. These require tissue verification before definitive intervention. Inclusion of a simple serum test, more accurate than CEA, especially for early cancer detection, would make virtual imaging much more successful. Proteomics, the study of the proteins and protein pathways involved in disease, is a new dimension in preclinical and clinical development. Mass spectrometric analysis of serum proteins has been shown to be a fast and simple approach yielding a large datastream of information to mine for biomarker patterns. Preliminary studies in a variety of cancers has shown this to be a promising direction. Protein arrays of tumor lysates allows assessment of expression and activation of proteins that may be specific colorectal cancer targets or targets that are shown to be universally important in cancer, such as those proteins involved in angiogenesis. Small quantities of tumor are needed for this technique and allow direct analysis of the biochemical events ongoing in the tumor and/or the stroma. This provides insight into the biology of the disease and can be used to identify targets for therapeutic intervention as well as to monitor the ability to successfully attack those targets. Together, these 2 technologies have been shown to advance the field and may be important new steps in diagnosis, prognosis, and treatment of colorectal cancer.

Upregulation of FasL by LPA on ovarian cancer cell surface leads to apoptosis of activated lymphocytes

OBJECTIVE

Constitutive expression and upregulation of FasL by malignant epithelial cells counterattack infiltrating natural killer (NK) cells and cytotoxic T lymphocytes (CTLs) and induce apoptosis of normal cells within the tumor, which may induce metastasis. As little is known about the mechanisms that regulate expression of Fas ligand and the subsequent release of FasL in epithelial ovarian cancer cells (EOC), we investigated the effects of lysophosphatidic acid (LPA) on FasL expression and associated signaling pathways.

METHODS

We used established EOC cell lines that were incubated with or without LPA and FasL expression was detected by flow cytometry. Cells were additionally lysed and detected for total protein expression. Activated CD4+ T cells, after coculture with or without EOC, were collected for apoptosis staining and analysis by flow cytometry.

RESULTS

Flow cytometry showed that LPA strongly upregulated FasL expression on the OVCAR3 cell surface (P < 0.01), yet in Dov13 cells, LPA significantly upregulated FasL expression only in the presence of the general matrix metalloproteinase (MMP) inhibitors GM6001 and MMP inhibitor II (P < 0.01). The MEK/ERK1/2 kinase cascade is required for FasL upregulation, since the MEK inhibitor PD98059 significantly inhibited FasL upregulation induced by LPA (P < 0.01). Type II secretory phospholipase A2 (sPLA2-II), which promotes protein exocytosis from secretory vesicles and gelatinase granules, affects FasL translocation from intracellular to the cell surface. Pretreatment of Dov13 cells with LPA increased activated T cell apoptosis in cocultures.

CONCLUSIONS

These data suggest that upregulation of FasL by LPA provides EOC immune-privilege and leads to apoptosis of activated T lymphocytes.

Improved targeting of pancreatic cancer: experimental studies of a new bispecific antibody, pretargeting enhancement system for immunoscintigraphy

PURPOSE

The early detection and diagnosis of pancreatic cancer remains a major clinical challenge in which imaging procedures have a central role. The purpose of this study was to evaluate a pretargeting method with a bispecific PAM4 (bsPAM4; anti-MUC1) antibody for radioimmunoscintigraphy of experimental human pancreatic cancer.

EXPERIMENTAL DESIGN

A bispecific F(ab')(2) antibody was generated from chimeric PAM4 Fab' and murine 734 (anti-indium-diethylenetriaminepentaacetic acid) Fab' fragments and then used in conjunction with 2 peptide haptens ((111)In-IMP-156 and (99m)Tc-IMP-192). Biodistribution studies and radioimmunoscintigraphic imaging properties of the radiolabeled bsPAM4, and pretargeted, radiolabeled peptides were examined in the CaPan1 human pancreatic tumor grown as s.c. xenografts in athymic nude mice. Tumor uptake and tumor:nontumor ratios were compared with a nontargeting irrelevant anti-CD20, bispecific rituximab, radiolabeled peptides alone, and with directly labeled PAM4.

RESULTS

Biodistribution results indicated significantly greater tumor uptake of radiolabeled peptides at 3 h after injection when pretargeting was performed with bsPAM4 as compared with the bispecific rituximab [20.2 +/- 5.5 percentage of injected dose per gram of tissue (%ID/g) versus 0.9 +/- 0.1%ID/g, respectively, for (111)In-IMP-156, and 16.8 +/- 4.8%ID/g versus 1.1 +/- 0.2%ID/g, respectively, for (99m)Tc-IMP-192]. Similar results were obtained at the 24-h time point. Tumor:nontumor ratios were >30 for all of the tissues except the kidneys, where a ratio of 7.8 +/- 2.8 was observed. By immunoscintigraphy, tumors could be visualized as early as 30 min after injection of the radiolabeled peptide.

CONCLUSIONS

These studies demonstrate the feasibility of using the pretargeted, bispecific antibody technology for nuclear imaging of pancreatic cancer. The advantage of pretargeted bsPAM4 antibody as an imaging platform is the high specificity for pancreatic cancer as compared with the physicochemical parameters identified by current imaging technologies.

Proteomic analysis for early detection of ovarian cancer: a realistic approach?

Ovarian cancer is a multifaceted disease wherein most women are diagnosed with advanced stage disease. One of the most imperative issues in ovarian cancer is early detection. Biomarkers that allow cancer detection at stage I, a time when the disease is amenable to surgical and chemotherapeutic cure in over 90% of patients, can dramatically alter the horizon for women with this disease. Recent developments in mass spectroscopy and protein chip technology coupled with bioinformatics have been applied to biomarker discovery. The complexity of the proteome is a rich resource from which the patterns can be gleaned; the pattern rather than its component parts is the diagnostic. Serum is a key source of putative protein biomarkers, and, by its nature, can reflect organ-confined events. Pioneering use of mass spectroscopy coupled with bioinformatics has been demonstrated as being capable of distinguishing serum protein pattern signatures of ovarian cancer in patients with early- and late-stage disease. This is a sensitive, precise, and promising tool for which further validation is needed to confirm that ovarian cancer serum protein signature patterns can be a robust biomarker approach for ovarian cancer diagnosis, yielding improved patient outcome and reducing the death and suffering from ovarian cancer.

Phase II trial of carboxyamidotriazole in patients with relapsed epithelial ovarian cancer

PURPOSE

Carboxyamidotriazole (CAI) is a cytostatic inhibitor of nonvoltage-operated calcium channels and calcium channel-mediated signaling pathways. It inhibits angiogenesis, tumor growth, invasion, and metastasis. We hypothesized that CAI would promote disease stabilization lasting >/= 6 months in patients with relapsed ovarian cancer.

PATIENTS AND METHODS

Patients with epithelial ovarian cancer, good end-organ function, measurable disease, and three or fewer prior regimens were eligible. Oral CAI was given daily using a pharmacokinetic-dosing approach to maintain plasma concentrations between 2 and 4 microg/mL. Radiographic imaging to assess response was performed every 8 weeks. Positive outcome included stabilization or improvement of disease lasting >/= 6 months. Plasma vascular endothelial growth factor (VEGF), interleukin (IL)-8, and matrix metalloproteinase (MMP)-2 were measured.

RESULTS

Thirty-six patients were assessable for primary end point analysis, and 38 were assessable for toxicity. Forty-four percent of patients had three prior regimens, more than 50% had four or more disease sites, and 48% had liver metastases. Thirty-three patients reached the targeted concentration range during the first cycle. Eleven patients (31%) attained the >/= 6-month outcome end point, with one partial response (8 months) and three minor responses (8, 12+, and 13 months). Median time to progression was 3.6 months (range, 1.6 to 13.3 months). CAI was well tolerated, with mostly grade 1 to 2 toxicity. Grade 3 events included fatigue (5%), vomiting (2%), neutropenic fever (2%), and neutropenia (2%). There were no grade 4 adverse events. No associations between VEGF, IL-8, and MMP-2 with CAI concentration or clinical outcome were observed.

CONCLUSION

CAI is a potential agent for additional study in the stabilization of relapsed ovarian cancer. Given a limited toxicity profile, it may have utility as a maintenance therapeutic agent for this disease.

Rapid discovery and identification of a tissue-specific tumor biomarker from 39 human cancer cell lines using the SELDI ProteinChip platform

Useful biomarkers are needed for early detection of cancers. To demonstrate the potential diagnostic usefulness of a new proteomic technology, we performed Expression Difference Mapping analysis on 39 cancer cell lines from 9 different tissues using ProteinChip technology. A protein biomarker candidate of 12kDa was found in colon cancer cells. We then optimized the purification conditions for this biomarker by utilizing Retentate Chromatography mass spectrometry (RC-MS). The optimized purification conditions developed "on-chip" were directly transferred to conventional chromatography to purify the biomarker, which was identified as prothymosin-alpha by ProteinChip time-of-flight mass spectrometry (TOF MS) and ProteinChip-Tandem MS systems. The relative expression level of prothymosin-alpha between colon cancer cells and normal colon mucosal cells was evaluated on the same ProteinChip platform. Prothymosin-alpha expression in colon cancer cells was clearly higher than in normal colon cells. These results indicate that prothymosin-alpha could be a potential biomarker for colon cancer, and that the ProteinChip platform could perform the whole process of biomarker discovery from screening to evaluation of the identified marker.

Proteomics in biomarker discovery and drug development

Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time can be considered in an integrated way. Proteomic technology has been extensively used to tackle a wide variety of medical subjects including biomarker discovery and drug development. By complement with other new technique advances in genomics and bioinformatics, proteomics has a great potential to make considerable contribution to biomarker identification and to revolutionize drug development process. This article provides a brief overview of the proteomic technologies and their application in biomarker discovery and drug development.