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Cloud P Paweletz

Publications and source records attributed to Cloud P Paweletz.

15 recordsLinked to original sources

EGFR-mutant transformed small cell lung cancer harbors intratumoral heterogeneity targetable with MEK inhibitor combination therapy.

Small cell lung cancer (SCLC) transformation is an incompletely characterized mechanism of resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in EGFR-mutant cancers, limiting development of optimal treatment approaches. Through single-cell RNA sequencing of malignant pleural effusions from patients who underwent SCLC transformation, we identified heterogeneity and diversity, including distinct neuroendocrine (NE) and mesenchymal non-NE cancer cell subsets, which were maintained in patient-derived cell lines. We demonstrate that EZH2 regulates EGFR expression in NE cells where EGFR expression is silenced at baseline. Although neither epigenetic derepression nor exogenous overexpression of mutant EGFR sensitized the cells to EGFR inhibition, non-NE cells exhibited selective sensitivity to MEK inhibitors. Combined MEK inhibitor and chemotherapy effectively inhibited growth of both NE and non-NE cells in vitro and in vivo. Our findings demonstrate that EGFR-mutant SCLC is composed of mixed cell states with distinct therapeutic vulnerabilities and offer a therapeutic strategy to target tumor heterogeneity in highly plastic and treatment-resistant malignancies such as transformed SCLC.

Humans↗

Quantitative analysis of complex peptide mixtures using FTMS and differential mass spectrometry.

Label-free LC-MS profiling is a powerful quantitative proteomic method to study relative peptide abundances between two or more biological samples. Here we demonstrate the use of a previously described comparative LC-MS method, differential mass spectrometry (dMS), to analyze high-resolution Fourier transform mass spectrometry (FTMS) data for detection and quantification of known peptide differences between two sets of complex mixtures. Six standard peptides were spiked into a processed plasma background at fixed ratios from 1.25:1 to 4:1 to make two sets of samples. The resulting mixtures were analyzed by microcapillary LC-FTMS and dMS. dMS successfully identified five out of the six peptides as statistically significant differences (p <or= 0.005). In this experiment, the smallest fold change reliably detected by our method was 1.5:1, and the errors of estimated ratios of concentrations were less than 20% for peptides spiked at 1.5:1 to 4:1. We conclude that LC-FTMS coupled with dMS is a useful label-free quantitative MS method that can be used to detect subtle yet statistically significant peptide differences in complex protein mixtures, including plasma samples.

Amino Acid Sequence↗

Surface enhanced laser desorption ionization spectrometry reveals biomarkers for drug treatment but not dose.

Here we describe the use of SELDI-MS to detect dose-dependent peptide changes in plasma from mice treated with vehicle or rosiglitazone at one of two doses (10 and 30 mg/kg). SELDI features differentiating spectra from the three conditions were found and used to train classifiers. Samples treated with vehicle could be reliably distinguished from samples treated with either dose, but samples treated with the different doses could not be reliably distinguished from one another. We conclude that while SELDI-TOF mass spectra can be used to distinguish treated from untreated samples, the reproducibility and information content of SELDI-TOF are currently not sufficient as a pharmacodynamic readout to distinguish between mice treated with 10 or 30 mg/kg of rosiglitazone. This raises more general questions about whether SELDI's sensitivity is sufficient for detecting dose-dependent changes in plasma.

Animals↗

Identification and characterization of SSTK, a serine/threonine protein kinase essential for male fertility.

Here we describe and characterize a small serine/threonine kinase (SSTK) which consists solely of the N- and C-lobes of a protein kinase catalytic domain. SSTK protein is highly conserved among mammals, and no close homologues were found in the genomes of nonmammalian organisms. SSTK specifically interacts with HSP90-1beta, HSC70, and HSP70 proteins, and this association appears to be required for SSTK kinase activity. The SSTK transcript was most abundant in human and mouse testes but was also detected in all human tissues tested. In the mouse testis, SSTK protein was localized to the heads of elongating spermatids. Targeted deletion of the SSTK gene in mice resulted in male sterility due to profound impairment in motility and morphology of spermatozoa. A defect in DNA condensation in SSTK null mutants occurred in elongating spermatids at a step in spermiogenesis coincident with chromatin displacement of histones by transition proteins. SSTK phosphorylated histones H1, H2A, H2AX, and H3 but not H2B or H4 or transition protein 1 in vitro. These results demonstrate that SSTK is required for proper postmeiotic chromatin remodeling and male fertility. Abnormal sperm chromatin condensation is common in sterile men, and our results may provide insight into the molecular mechanisms underlying certain human infertility disorders.

Amino Acid Sequence↗

Proteomic analysis of human bladder tissue using SELDI approach following microdissection techniques.

Lysing of a complete biopsy sample results in a mixture of desired and undesired proteins, reflecting the originating cell types. Therefore microdissecting tissue material is mandatory prior to sample lysis and all downstream applications of protein analysis (proteomics). The two most important dissecting methods for bladder tissue specimens are manual microdissection and laser microdissection. Sample transfer can further be separated into manual laser pressure catapulting (LPC) and laser capture microdissection (LCM). One of the possible downstream applications of protein analysis is surface-enhanced laser desorption ionization (SELDI) time-of-flight mass spectrometry. The small quantities of tissue obtained by microdissection are sufficient for use in the SELDI technique.

Humans↗

Mitochondrial proteome: altered cytochrome c oxidase subunit levels in prostate cancer.

Laser capture microdissection was combined with reverse phase protein lysate arrays to quantitatively analyze the ratios of mitochondrial encoded cytochrome c oxidase subunits to nuclear encoded cytochrome c oxidase subunits, and to correlate the ratios with malignant progression in human prostate tissue specimens. Cytochrome c oxidase subunits I-III comprise the catalytic core of the enzyme and are all synthesized from mitochondrial DNA. The remaining subunits (IV-VIII) are synthesized from cellular nuclear DNA. A significant (P < 0.001, 30/30 prostate cases) shift in the relative concentrations of nuclear encoded cytochrome c oxidase subunits IV, Vb, and VIc compared to mitochondrial encoded cytochrome c oxidase subunits I and II was noted during the progression of prostate cancer from normal epithelium through premalignant lesions to invasive carcinoma. Significantly, this shift was discovered to begin even in the premalignant stage. Reverse phase protein lysate array-based observations were corroborated with immunohistochemistry, and extended to a few human carcinomas in addition to prostate. This analysis points to a role for nuclear DNA encoded mitochondrial proteins in carcinogenesis; underscoring their potential as targets for therapy while highlighting the need for full characterization of the mitochondrial proteome.

Blotting, Western↗

Signal pathway profiling of prostate cancer using reverse phase protein arrays.

Reverse phase protein arrays represent a new proteomics microarray technology with which to study the fluctuating state of the proteome in minute quantities of cells. The activation status of cell signaling pathways controls cellular fate and deregulation of these pathways underpins carcinogenesis. Changes in pathway activation that occur between early stage prostatic epithelial lesions, prostatic stroma and the extracellular matrix can be analyzed by obtaining pure populations of cell types by laser capture microdissection (LCM) and analyzing the relative states of several key phosphorylation points within the cellular circuitry. We have applied reverse phase protein array technology to analyze the status of key points in cell signaling involved in pro-survival, mitogenic, apoptotic and growth regulation pathways in the progression from normal prostate epithelium to invasive prostate cancer. Using multiplexed reverse phase protein arrays coupled with LCM, the states of signaling changes during disease progression from prostate cancer study sets were analyzed. Focused analysis of phospho-specific endpoints revealed changes in cellular signaling events through disease progression and between patients. We have used a new protein array technology to study specific molecular pathways believed to be important in cell survival and progression from normal epithelium to invasive carcinoma directly from human tissue specimens. With the advent of molecular targeted therapeutics, the identification, characterization and monitoring of the signaling events within actual human biopsies will be critical for patient-tailored therapy.

Antigens, Neoplasm↗

Proteomic approaches to the diagnosis, treatment, and monitoring of cancer.

The field of proteomics holds promise for the discovery of new biomarkers for the early detection and diagnosis of disease, molecular targets for therapy and markers for therapeutic efficacy and toxicity. A variety of proteomics approaches may be used to address these goals. Two-dimensional gel electrophoresis (2D-PAGE) is the cornerstone of many discovery-based proteomics studies. Technologies such as laser capture microdissection (LCM) and highly sensitive MS methods are currently being used together to identify greater numbers of lower abundance proteins that are differentially expressed between defined cell populations. Newer technologies such as reverse phase protein arrays will enable the identification and profiling of target pathways in small biopsy specimens. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) analysis enables the high throughput characterization of lysates from very few tumor cells or body fluids and may be best suited for diagnosis and monitoring of disease. Such technologies are expected to supplement our arsenal of mRNA-based assays, and we believe that in the future, entire cellular networks and not just a single deregulated protein will be the target of therapeutics and that we will soon be able to monitor the status of these pathways in diseased cells before, during and after therapy.

Biomarkers, Tumor↗

Serum-derived protein S binds to phosphatidylserine and stimulates the phagocytosis of apoptotic cells.

Rapid phagocytosis of apoptotic cells is thought to limit the development of inflammation and autoimmune disease. Serum enhances macrophage phagocytosis of apoptotic cells. Here we identified protein S as the factor responsible for serum-stimulated phagocytosis of apoptotic cells. Protein S is best known for its anti-thrombotic activity, serving as a cofactor for protein C. Purified protein S was equivalent to serum in its ability to stimulate macrophage phagocytosis of apoptotic lymphoma cells, and immunodepletion of protein S eliminated the prophagocytic activity of serum. Protein S acted by binding to phosphatidylserine expressed on the apoptotic cell surface. Protein S is thus a multifunctional protein that can facilitate clearance of early apoptotic cells in addition to regulating blood coagulation.

Apoptosis↗

Serum proteomic patterns for detection of prostate cancer.

Pathologic states within the prostate may be reflected by changes in serum proteomic patterns. To test this hypothesis, we analyzed serum proteomic mass spectra with a bioinformatics tool to reveal the most fit pattern that discriminated the training set of sera of men with a histopathologic diagnosis of prostate cancer (serum prostate-specific antigen [PSA] > or =4 ng/mL) from those men without prostate cancer (serum PSA level <1 ng/mL). Mass spectra of blinded sera (N = 266) from a test set derived from men with prostate cancer or men without prostate cancer were matched against the discriminating pattern revealed by the training set. A predicted diagnosis of benign disease or cancer was rendered based on similarity to the discriminating pattern discovered from the training set. The proteomic pattern correctly predicted 36 (95%, 95% confidence interval [CI] = 82% to 99%) of 38 patients with prostate cancer, while 177 (78%, 95% CI = 72% to 83%) of 228 patients were correctly classified as having benign conditions. For men with marginally elevated PSA levels (4-10 ng/mL; n = 137), the specificity was 71%. If validated in future series, serum proteomic pattern diagnostics may be of value in deciding whether to perform a biopsy on a man with an elevated PSA level.

Biomarkers, Tumor↗

Clinical applications of proteomics: proteomic pattern diagnostics.

Clinical proteomics is an exciting new subdiscipline of proteomics that involves bedside application of proteomic technologies. A new and potentially revolutionary technology and approach for early disease detection, surveillance, and monitoring is proteomic pattern diagnostics. Using this approach, high throughput mass spectrometry generates a proteomic fingerprint of a given body fluid, such as serum or nipple fluid aspirants (NAF), in less than 30 s. This information archive is then used by new types of bioinformatic pattern recognition algorithms to identify patterns of protein changes that can discriminate cancer from healthy and unaffected individuals. This entire process can take place in less than a minute and requires only a droplet of blood, NAF, or ductal lavage washings. The new concept that is introduced by this platform is that the underlying identities of the proteins that comprise the patterns are not known and do not need to be known; the pattern itself becomes the diagnostic.

Algorithms↗

Utility of reverse phase protein arrays: applications to signalling pathways and human body arrays.

Protein microarrays offer a new means by which to conduct quantitative profiling of disease-associated proteins. The knowledge gained may provide novel strategies for early detection, diagnosis and therapeutic intervention. A variety of sophisticated approaches, including gene arrays, sequencing consortiums and large-scale two-dimensional gel electrophoresis, continue to generate lists of proteins potentially linked to disease aetiology and progression. The challenge is to evaluate quantitatively promising lead protein candidates using matched normal and diseased cell populations. In contrast to the antibody array, the reverse phase protein microarrays (RPPA) do not require labelling of cellular protein lysates, and constitute a sensitive high throughput platform for marker screening, pathophysiology investigation and therapeutic monitoring. In this paper, examples will be provided using RPPAs in the study of the apoptotic signalling cascade and in the evaluation of the expression of organ-specific protein makers using microdissected human organ cell lysates configured as 'human body arrays'.

Humans↗

Proteomic technologies to study diseases of the lymphatic vascular system.

Now that the human genome has been mapped, a new challenge has emerged: deciphering the various products of individual genes. Consequently, new proteomic technologies are being developed to monitor and identify protein function and interactions responsible for the total activities of the cell. The application of these new proteomic technologies to study cellular activities, will lead to a faster sample throughput and increased sensitivity for the detection of individual proteins, thus providing major opportunities for the discovery of new biomarkers for the early detection of protein alterations associated with the progression of the disease state.

Animals↗

Clinical proteomics for cancer biomarker discovery and therapeutic targeting.

As we emerge into the post-genome era, proteomics finds itself as the driving force field as we translate the nucleic acid information archive into understanding how the cell actually works and how disease processes operate. Even so, the traditionally held view of proteomics as simply cataloging and developing lists of the cellular protein repertoire of a cell are now changing, especially in the sub-discipline of clinical proteomics. The most relevant information archive to clinical applications and drug development involves the elucidation of the information flow of the cell; the "software" of protein pathway networks and circuitry. The deranged circuitry of the cell as the drug target itself as well as the effect of the drug on not just the target, but also the entire network, is what we now are striving towards. Clinical proteomics, as a new and most exciting sub-discipline of proteomics, involves the bench-to-bedside clinical application of proteomic tools. Unlike the genome, there are potentially thousands of proteomes: each cell type has its own unique proteome. Moreover, each cell type can alter its proteome depending on the unique tissue microenvironment in which it resides, giving rise to multiple permutations of a single proteome. Since there is no polymerase chain reaction equivalent to proteomics- identifying and discovering the "wiring diagram" of a human diseased cell in a biopsy specimen remains a daunting challenge. New micro-proteomic technologies are being and still need to be developed to drill down into the proteomes of clinically relevant material. Cancer, as a model disease, provides a fertile environment to study the application of proteomics at the bedside. The promise of clinical proteomics and the new technologies that are developed is that we will detect cancer earlier through discovery of biomarkers, we will discover the next generation of targets and imaging biomarkers, and we can then apply this knowledge to patient-tailored therapy.

Algorithms↗