Alice Chin

ST2 as a Marker for Risk of Therapy-Resistant Graft-versus-Host Disease and Death

BACKGROUND No plasma biomarkers are associated with the response of acute graft-versus-host disease (GVHD) to therapy after allogeneic hematopoietic stem-cell transplantation. METHODS We compared 12 biomarkers in plasma obtained a median of 16 days after therapy initiation from 10 patients with a complete response by day 28 after therapy initiation and in plasma obtained from 10 patients with progressive GVHD during therapy. The lead biomarker, suppression of tumorigenicity 2 (ST2), was measured at the beginning of treatment for GVHD in plasma from 381 patients and during the first month after transplantation in three independent sets totaling 673 patients to determine the association of this biomarker with treatment-resistant GVHD and 6-month mortality after treatment or transplantation. RESULTS Of the 12 markers, ST2 had the most significant association with resistance to GVHD therapy and subsequent death without relapse. As compared with patients with low ST2 values at therapy initiation, patients with high ST2 values were 2.3 times as likely to have treatment-resistant GVHD (95% confidence interval [CI], 1.5 to 3.6) and 3.7 times as likely to die within 6 months after therapy (95% CI, 2.3 to 5.9). Patients with low ST2 values had lower mortality without relapse than patients with high ST2 values, regardless of the GVHD grade (11% vs. 31% among patients with grade I or II GVHD and 14% vs. 67% among patients with grade III or IV GVHD, P<0.001 for both comparisons). Plasma ST2 values at day 14 after transplantation were associated with 6-month mortality without relapse, regardless of the intensity of the conditioning regimen. CONCLUSIONS ST2 levels measured at the initiation of therapy for GVHD and during the first month after transplantation improved risk stratification for treatment-resistant GVHD and death without relapse after transplantation. (Funded by the National Institutes of Health.)

Regenerating islet-derived 3-alpha is a biomarker of gastrointestinal graft-versus-host disease

There are no plasma biomarkers specific for GVHD of the gastrointestinal (GI) tract, the GVHD target organ most associated with nonrelapse mortality (NRM) following hematopoietic cell transplantation (HCT). Using an unbiased, large-scale, quantitative proteomic discovery approach to identify candidate biomarkers that were increased in plasma from HCT patients with GI GVHD, 74 proteins were increased at least 2-fold; 5 were of GI origin. We validated the lead candidate, REG3α, by ELISA in samples from 1014 HCT patients from 3 transplantation centers. Plasma REG3α concentrations were 3-fold higher in patients at GI GVHD onset than in all other patients and correlated most closely with lower GI GVHD. REG3α concentrations at GVHD onset predicted response to therapy at 4 weeks, 1-year NRM, and 1-year survival (P ≤ .001). In a multivariate analysis, advanced clinical stage, severe histologic damage, and high REG3α concentrations at GVHD diagnosis independently predicted 1-year NRM, which progressively increased with higher numbers of onset risk factors present: 25% for patients with 0 risk factors to 86% with 3 risk factors present (P < .001). REG3α is a plasma biomarker of GI GVHD that can be combined with clinical stage and histologic grade to improve risk stratification of patients.

Elafin is a biomarker of graft-versus-host disease of the skin.

Plasma elafin concentrations correlate with graft-versus-host disease of the skin and long-term survival. Progress toward biomarker commercialization requires the discovery, qualification, verification, optimization, and clinical validation of a candidate before it is incorporated into existing therapeutic diagnostic platforms. The tremendous value that could be derived from the advancement of methods to detect disease at earlier and more treatable stages puts this pipeline approach at the forefront of biomarker development. However, to date there are no clear success stories in which discovery proteomics has led to a deployed protein biomarker. There is no polymerase chain reaction equivalent available to detect, quantify, and amplify proteins. Rather, proteomics-based biomarker discovery across a wide assortment of diseases is enabled by technologies such as mass spectrometry to sift through a large span of complex analytes at variable concentrations. Now, Paczesny and colleagues use a mass spectrometry–based technique to unambiguously identify candidate plasma biomarkers of skin acute graft-versus-host disease (GVHD)—the primary cause of nonrelapse mortality after bone marrow transplantation (BMT). Rashes are common after BMT and can be caused by a variety of reasons, but because the consequences of GVHD are serious, physicians initiate treatment of suspected GVHD without a bona fide confirmed diagnosis. In the discovery set of this work, the authors examined plasma samples from patients who had received BMT with and without clinical diagnosis of skin GVHD, and found that in patients with skin GVHD, the concentration of one lead marker, elafin, was three times as high. In a follow-up independent validation of 492 BMT patients, skin biopsies stained with elafin stratified the patients consistently according to GVHD parameters, and elafin plasma concentrations were concordantly higher in patients with GVHD. The specificity and sensitivity of elafin relative to other markers revealed that it was the single best discriminator for the diagnosis of GVHD in BMT patients with a rash, and was correlated with the severity of the disease. Elafin concentrations also correlated with the eventual maximum grade of GVHD and with nonrelapse mortality. These results show that elafin concentrations may serve as a noninvasive diagnostic test as well as a prognostic marker in determining GVHD grading in the clinic. Graft-versus-host disease (GVHD), the major complication of allogeneic bone marrow transplantation, affects the skin, liver, and gastrointestinal tract. There are no plasma biomarkers specific for any acute GVHD target organ. We used a large-scale quantitative proteomic discovery procedure to identify biomarker candidates of skin GVHD and validated the lead candidate, elafin, with enzyme-linked immunosorbent assay in samples from 492 patients. Elafin was overexpressed in GVHD skin biopsies. Plasma concentrations of elafin were significantly higher at the onset of skin GVHD, correlated with the eventual maximum grade of GVHD, and were associated with a greater risk of death relative to other known risk factors (hazard ratio, 1.78). We conclude that elafin has significant diagnostic and prognostic value as a biomarker of skin GVHD.

Lung Cancer Signatures in Plasma Based on Proteome Profiling of Mouse Tumor Models

We investigated the potential of in-depth quantitative proteomics to reveal plasma protein signatures that reflect lung tumor biology. We compared plasma protein profiles of four mouse models of lung cancer with profiles of models of pancreatic, ovarian, colon, prostate, and breast cancer and two models of inflammation. A protein signature for Titf1/Nkx2-1, a known lineage-survival oncogene in lung cancer, was found in plasmas of mouse models of lung adenocarcinoma. An EGFR signature was found in plasma of an EGFR mutant model, and a distinct plasma signature related to neuroendocrine development was uncovered in the small-cell lung cancer model. We demonstrate relevance to human lung cancer of the protein signatures identified on the basis of mouse models.

Molecular Portraits of Epithelial, Mesenchymal, and Hybrid States in Lung Adenocarcinoma and Their Relevance to Survival

Epithelial-to-mesenchymal transition (EMT) is a key process associated with tumor progression and metastasis. To define molecular features associated with EMT states, we undertook an integrative approach combining mRNA, miRNA, DNA methylation, and proteomic profiles of 38 cell populations representative of the genomic heterogeneity in lung adenocarcinoma. The resulting data were integrated with functional profiles consisting of cell invasiveness, adhesion, and motility. A subset of cell lines that were readily defined as epithelial or mesenchymal based on their morphology and E-cadherin and vimentin expression elicited distinctive molecular signatures. Other cell populations displayed intermediate/hybrid states of EMT, with mixed epithelial and mesenchymal characteristics. A dominant proteomic feature of aggressive hybrid cell lines was upregulation of cytoskeletal and actin-binding proteins, a signature shared with mesenchymal cell lines. Cytoskeletal reorganization preceded loss of E-cadherin in epithelial cells in which EMT was induced by TGFβ. A set of transcripts corresponding to the mesenchymal protein signature enriched in cytoskeletal proteins was found to be predictive of survival in independent datasets of lung adenocarcinomas. Our findings point to an association between cytoskeletal and actin-binding proteins, a mesenchymal or hybrid EMT phenotype and invasive properties of lung adenocarcinomas.

Tumor Microenvironment-Derived Proteins Dominate the Plasma Proteome Response During Breast Cancer Induction and Progression

Tumor development relies upon essential contributions from the tumor microenvironment and host immune alterations. These contributions may inform the plasma proteome in a manner that could be exploited for cancer diagnosis and prognosis. In this study, we employed a systems biology approach to characterize the plasma proteome response in the inducible HER2/neu mouse model of breast cancer during tumor induction, progression, and regression. Mass spectrometry data derived from approximately 1.6 million spectra identified protein networks involved in wound healing, microenvironment, and metabolism that coordinately changed during tumor development. The observed alterations developed prior to cancer detection, increased progressively with tumor growth and reverted toward baseline with tumor regression. Gene expression and immunohistochemical analyses suggested that the cancer-associated plasma proteome was derived from transcriptional responses in the noncancerous host tissues as well as the developing tumor. The proteomic signature was distinct from a nonspecific response to inflammation. Overall, the developing tumor simultaneously engaged a number of innate physiologic processes, including wound repair, immune response, coagulation and complement cascades, tissue remodeling, and metabolic homeostasis that were all detectable in plasma. Our findings offer an integrated view of tumor development relevant to plasma-based strategies to detect and diagnose cancer.

Integrated mass spectrometry–based analysis of plasma glycoproteins and their glycan modifications

We present a protocol for the identification of glycosylated proteins in plasma followed by elucidation of their individual glycan compositions. The study of glycoproteins by mass spectrometry is usually based on cleavage of glycans followed by separate analysis of glycans and deglycosylated proteins, which limits the ability to derive glycan compositions for individual glycoproteins. The methodology described here consists of 2D HPLC fractionation of intact proteins and liquid chromatography–multistage tandem mass spectrometry (LC-MS/MSn) analysis of digested protein fractions. Protein samples are separated by 1D anion-exchange chromatography (AEX) with an eight-step salt elution. Protein fractions from each of the eight AEX elution steps are transferred onto the 2D reversed-phase column to further separate proteins. A digital ion trap mass spectrometer with a wide mass range is then used for LC-MS/MSn analysis of intact glycopeptides from the 2D HPLC fractions. Both peptide and oligosaccharide compositions are revealed by analysis of the ion fragmentation patterns of glycopeptides with an intact glycopeptide analysis pipeline.

Autoantibody Signatures Involving Glycolysis and Splicesome Proteins Precede a Diagnosis of Breast Cancer among Postmenopausal Women

We assessed the autoantibody repertoire of a mouse model engineered to develop breast cancer and the repertoire of autoantibodies in human plasmas collected at a preclinical time point and at the time of clinical diagnosis of breast cancer. In seeking to identify common pathways, networks, and protein families associated with the humoral response, we elucidated the dynamic nature of tumor antigens and autoantibody interactions. Lysate proteins from an immortalized cell line from a MMTV-neu mouse model and from MCF7 human breast cancers were spotted onto nitrocellulose microarrays and hybridized with mouse and human plasma samples, respectively. Immunoglobulin-based plasma immunoreactivity against glycolysis and spliceosome proteins was a predominant feature observed both in tumor-bearing mice and in prediagnostic human samples. Interestingly, autoantibody reactivity was more pronounced further away than closer to diagnosis. We provide evidence for dynamic changes in autoantibody reactivity with tumor development and progression that may depend, in part, on the extent of antigen-antibody interactions.

Detection of Elevated Plasma Levels of Epidermal Growth Factor Receptor Before Breast Cancer Diagnosis among Hormone Therapy Users

Applying advanced proteomic technologies to prospectively collected specimens from large studies is one means of identifying preclinical changes in plasma proteins that are potentially relevant to the early detection of diseases such as breast cancer. We conducted 14 independent quantitative proteomics experiments comparing pooled plasma samples collected from 420 estrogen receptor-positive (ER(+)) breast cancer patients ≤17 months before their diagnosis and matched controls. Based on the more than 3.4 million tandem mass spectra collected in the discovery set, 503 proteins were quantified, of which 57 differentiated cases from controls with a P value of <0.1. Seven of these proteins, for which quantitative ELISA assays were available, were assessed in an independent validation set. Of these candidates, epidermal growth factor receptor (EGFR) was validated as a predictor of breast cancer risk in an independent set of preclinical plasma samples for women overall [odds ratio (OR), 1.44; P = 0.0008] and particularly for current users of estrogen plus progestin (E + P) menopausal hormone therapy (OR, 2.49; P = 0.0001). Among current E + P users, the EGFR sensitivity for breast cancer risk was 31% with 90% specificity. Whereas the sensitivity and specificity of EGFR are insufficient for a clinically useful early detection biomarker, this study suggests that proteins that are elevated preclinically in women who go on to develop breast cancer can be discovered and validated using current proteomic technologies. Further studies are warranted to examine the role of EGFR and to discover and validate other proteins that could potentially be used for early detection of breast cancer.

Quantitative serum proteomics using dual stable isotope coding and nano LC-MS/MSMS.

Stable isotope coding technique in combination with mass spectrometry has emerged as a powerful tool to accurately identify and differentially quantify proteins within complex protein mixtures. We present a novel methodology to increase the yield of quantified proteins while maintaining a high stable-isotopic labeling efficacy. With this approach, intact proteins in complex biological sample such as sera are labeled with the designated dual stable isotope coding (DSIC) systems. In brief, intact proteins are coded sequentially with acrylamide to label Cysteine residues (Cys) and with succinic anhydride to label Lysine residues (Lys). Protein samples coded with this dual stable isotope are subjected to an online 2D-HPLC fractionation. The resolved protein fractions are individually digested with trypsin and analyzed with nano LC-MS/MSMS. Our results show that the DSIC labeling efficiency is 100% for Cysteine (Cys) labeled with acrylamide and 98% for Lysine (Lys) labeled with succinic anhydride. A comparative analysis of DSIC labeling and single labeling of Cysteine residues was made. Analysis of an entire anion-exchange chromatography subfraction of sera yielded 165 identified proteins (criteria: error rate <5% and unique peptides >or=2), 104 of which were quantified using the single labeling method (i.e., Cysteine acrylamide labeling only). In contrast, using same criteria for identification, a total 185 proteins were identified and 174 proteins were quantified using the DSIC labeling technique.