Molecular Fingerprinting in Human Lung Cancer

Recent advances in single-cell MALDI mass spectrometry imaging and potential clinical impact

Single-cell analysis is gaining popularity in the field of mass spectrometry as a method for analyzing protein and peptide content in cells. The spatial resolution of MALDI mass spectrometry (MS) imaging is by a large extent limited by the laser focal diameter and the displacement of analytes during matrix deposition. Owing to recent advancements in both laser optics and matrix deposition methods, spatial resolution on the order of a single eukaryotic cell is now achievable by MALDI MS imaging. Provided adequate instrument sensitivity, a lateral resolution of approximately 10 µm is currently attainable with commercial instruments. As a result of these advances, MALDI MS imaging is poised to become a transformative clinical technology. In this article, the crucial steps needed to obtain single-cell resolution are discussed, as well as potential applications to disease research.

International comparisons of survival from lung cancer: pitfalls and warnings

Population-based survival data can provide valuable comparative data on outcome but should be interpreted with caution. Differences in data collection and analysis, patient and tumor characteristics and treatment options can have an impact on reported results. Ideally, data from the whole population, including clinical-only diagnoses, should be reported and the methods of case identification described. The relative survival rates should preferably be given. Data on patient characteristics such as age, sex, ethnicity and socioeconomic deprivation should be described, together with tumor details such as pathology and clinical stage. Whenever possible, details on the use of treatments should be reported.

Lung cancer staging in the genomics era

The search for clinically applicable biologic markers or tumor signatures sufficiently powered as prognosticators of tumor behaviors or responses to therapeutic interventions has significantly advanced in scope and sophistication in the last 10 years. The TNM system, examining of tumor tissues to identify histopathologic features that could be correlated with tumor biology and outcome, could be improved by the immunohistochemical assessment of individual marker proteins or painstaking sequencing of candidate genes (one at a time) from tumor tissues. Large-scale investigation of the gene or protein expression profiles using genomics or proteomics technology may further improve risk stratification and assessment of therapeutic response. Although the gene expression profiling studies summarized in this article are exciting and initially serve as proofs of concept that large-scale mining of the genome and the transcriptome yields clinically useful data, the technology is still evolving and standardization is still needed for large-scale studies and data validation. As a proof of principle, studies have been performed to demonstrate that it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study, and to demonstrate significant, albeit incomplete, agreement of gene expression patterns related to lung cancer biology and predictive of treatment outcomes via cross-study comparative analysis. Leading the concerted efforts of molecular characterization of lung cancer is the National Cancer Institute Director's Challenge Program: Toward A Molecular Classification of Cancer. The ultimate goal of molecular staging, envisioned as a combination of traditional TNM classification bolstered with gene/protein unique expression signatures, is to classify patients who have lung cancer on the basis of tumor biology, for better risk stratification and treatment using targeted patient-tailored therapeutics based on unique genotypes of individual tumors.

Two-step matrix application technique to improve ionization efficiency for matrix-assisted laser desorption/ionization in imaging mass spectrometry

A novel matrix application protocol for direct tissue mass spectrometry is presented. Matrix-assisted laser desorption/ionization is a popular ionization procedure for direct tissue analysis and imaging mass spectrometry. Usually, matrixes are applied by dispensing droplets through either pipettes or automated dispensing machines, or by airbrushing. These techniques are very simple, but it was difficult to obtain uniform matrix crystals on the tissue surface, and nonuniform crystals degrade the spectrum qualities. Here we report a new matrix application protocol, which is a combination of spraying and dispensing droplets, and we have succeeded in overcoming these problems in conventional matrix applications on tissue surfaces. We call our new technique the "spray-droplet method". In this technique, tiny matrix crystals formed by spraying act as seeds for crystal growth. Our technique leads to matrix spots that are filled homogeneously with minute crystals. Such matrix crystals dramatically improve peak intensity and signal-to-noise ratio. In an example on a rat brain section, the number of detectable peaks was increased and signal intensity of m/z 5440 in our method was approximately 30.6 times higher than that in conventional methods. We used this spray-droplet method with a chemical ink-jet technology for matrix deposition to succeed in MALDI imaging of signals, which were undetectable from the conventional matrix applications.

Clinical proteomics: from biomarker discovery and cell signaling profiles to individualized personal therapy

The discovery of new highly sensitive and specific biomarkers for early disease detection and risk stratification coupled with the development of personalized "designer" therapies holds the key to future treatment of complex diseases such as cancer. Mounting evidence confirms that the low molecular weight (LMW) range of the circulatory proteome contains a rich source of information that may be able to detect early stage disease and stratify risk. Current mass spectrometry (MS) platforms can generate a rapid and high resolution portrait of the LMW proteome. Emerging novel nanotechnology strategies to amplify and harvest these LMW biomarkers in vivo or ex vivo will greatly enhance our ability to discover and characterize molecules for early disease detection, subclassification and prognostic capability of current proteomics modalities. Ultimately genetic mutations giving rise to disease are played out and manifested on a protein level, involving derangements in protein function and information flow within diseased cells and the interconnected tissue microenvironment. Newly developed highly sensitive, specific and linearly dynamic reverse phase protein microarray systems are now able to generate circuit maps of information flow through phosphoprotein networks of pure populations of microdissected tumor cells obtained from patient biopsies. We postulate that this type of enabling technology will provide the foundation for the development of individualized combinatorial therapies of molecular inhibitors to target tumor-specific deranged pathways regulating key biologic processes including proliferation, differentiation, apoptosis, immunity and metastasis. Hence future therapies will be tailored to the specific deranged molecular circuitry of an individual patient's disease. The successful transition of these groundbreaking proteomic technologies from research tools to integrated clinical diagnostic platforms will require ongoing continued development, and optimization with rigorous standardization development and quality control procedures.

Combined Fourier transform infrared and Raman spectroscopic approach for identification of multidrug resistance phenotype in cancer cell lines

Cancer cells escape cytotoxic effects of anticancer drugs by a process known as multidrug resistance (MDR). Identification of cell status by less time-consuming methods can be extremely useful in patient management and treatment. This study aims at evaluating the potentials of vibrational spectroscopic methods to perform cell typing and to differentiate between sensitive and resistant human cancer cell lines, in particular those that exhibit the MDR phenotype. Micro-Raman and Fourier transform infrared (FTIR) spectra have been acquired from the sensitive promyelocytic HL60 leukemia cell line and two of its subclones resistant to doxorubicin (HL60/DOX) and daunorubicin (HL60/DNR), and from the sensitive MCF7 breast cancer cell line and its MDR counterpart resistant to verapamil (MCF7/VP). Principal components analysis (PCA) was employed for spectral comparison and classification. Our data show that cell typing was feasible with both methods, giving two distinct clusters for HL60- and MCF7-sensitive cells. In addition, phenotyping of HL60 cells, i.e., discriminating between the sensitive and MDR phenotypes, was attempted by both methods. FTIR could not only delineate between the sensitive and resistant HL60 cells, but also gave two distinct clusters for the resistant cells, which required a two-step procedure with Raman spectra. In the case of MCF7 cell lines, both the sensitive and resistant phenotypes could be differentiated very efficiently by PCA analysis of their FTIR and Raman point spectra. These results indicate the prospective applicability of FTIR and micro-Raman approaches in the differentiation of cell types as well as characterization of the cell status, such as the MDR phenotype exhibited in resistant leukemia cell lines like HL60 and MCF7.

[The NOLA2 and RPS3A genes as highly informative markers for human squamous cell lung cancer]

cDNA libraries enriched with sequences that are differentially transcribed in normal and tumor tissues were prepared using the subtractive hybridization of mixtures of cDNAs from ten patients with squamous cell lung cancer and the corresponding mixtures of cDNAs from normal tissues of the same patients. An analysis of the libraries revealed two genes, NOLA2 and RPS3A, whose expression in patients with squamous cell lung cancer increased by 70%. A high frequency of enhanced expression of these genes in the cancer makes them highly informative markers of squamous cell lung cancer, which, together with other markers, can be used for reliable diagnosis of the disease.

Discovery of Biomarker Candidates within Disease by Protein Profiling: Principles and Concepts†

Proteins and peptides present within clinical samples represent a valuable library of information regarding the ongoing processes within cells and tissues in health and disease. We have developed and validated novel technology applications that can be used to characterize the patterns of global protein expression in tissue and biofluids in either gel-based systems or by automated multidimensional nanocapillary liquid chromatography. Mass spectrophotometry platforms using MALDI MS and MS/MS or LTQ ion trap MS were capable of delivering sensitive and accurate identifications of hundreds of proteins contained in individual samples including individual forms of processing intermediates such as phospho peptides. The Systems Biology approach of integrating protein expression data with clinical data such as histopathology, clinical functional measurements, medical imaging scores, patient demographics, and clinical outcome provides a powerful tool for linking biomarker expression with biological processes that can be segmented and linked to disease presentation.

Proteomics in pathology research

Proteomics is a multifaceted approach to study various aspects of protein expression, post-translational modification, interactions, organization and function at a global level. While DNA constitutes the 'information archive of the genome', it is the proteins that actually serve as the functional effectors of cellular processes. Thus, analysis of protein derangements on a proteome-wide scale will reveal insights into deregulated pathways and networks involved in the pathogenesis of disease. Although the field of proteomics has advanced tremendously in recent years, there are significant technical challenges that pose limitations to the routine application of mass spectrometry to clinical research. Despite these challenges, proteomic studies have yielded unparalleled information and understanding of the cellular biology of diseased states. The application of mass spectrometry to the study of diseases will ultimately lead to identification of biomarkers that are critical for the detection, diagnosis, prognosis and treatment of specific disease entities.

Cancer proteomics: Serum diagnostics for tumor marker discovery

Cancer proteomics is an exciting field that is witnessing many new developments in recent years. It is hoped that these advances will result in decreased cancer death rates, which have not declined dramatically in the last several decades. Some of the problems with current tumor markers include the lack of sensitivity and specificity, factors that prevent their use in population-based screening of disease. Thus, there is an urgent need to identify novel biomarkers that can faithfully detect the disease state. As we are now in the post-genome era, many opportunities have been created. Genomic sequence data are available for human, as well as several other species. We are now poised to mine these data and to determine the functions of the encoded proteins constituting the human genome. Proteomics affords this opportunity by providing enhanced procedures and tools for discovery and also a framework for understanding these components in terms of pathogenesis. New technologies and improvements in existing methodologies will allow for the rapid growth in the identification and characterization of peptides and proteins that are unique to various clinical states. This technology can be successfully applied to clinical specimens for the identification of new tumor markers.

Detection of Cell-Free DNA in Bronchial Lavage Fluid Supernatants of Patients with Lung Cancer

Recently, it was shown that it is possible to isolate free circulating DNA from plasma/serum of patients with benign and malignant diseases. In addition, several groups were able to detect tumor-associated alterations in these nucleic acids. We wondered whether any nucleic acids are detectable in cell-free bronchial lavage supernatants, which until now have been discarded after cell harvest. Additionally, we wanted to find out if it is possible to detect tumor-associated alterations in these DNA molecules. DNA was isolated from cell-free lavage supernatants from 30 lung cancer patients, and the DNA was examined for microsatellite alterations. Intact DNA could be isolated from all cell-free bronchial lavage supernatants. Microsatellite alterations were found in lavage supernatants of 12 of 30 patients and in lavage cells of 6 of 30 patients. Altogether, alterations were found in 14 of 30 patients. Thus, we could demonstrate for the first time that it is possible to isolate intact DNA from cell-free bronchial lavage supernatants. Their quantity and quality are sufficient for further amplification via polymerase chain reaction. Altogether, tumor-associated changes were detected in the DNA of 47% of the patients that were analyzed.