Kian Kani

A Cross-platform Toolkit for Mass Spectrometry and Proteomics

Mass-spectrometry-based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2, and characterize protein complexes3. Despite successes, the interpretation of vast proteomics datasets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we have developed the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, non-commercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.

Functional isolation of activated and unilaterally phosphorylated heterodimers of ERBB2 and ERBB3 as scaffolds in ligand-dependent signaling

The EGFR (ERBB) family provides a model system for receptor signaling, oncogenesis, and the development of targeted therapeutics. Heterodimers of the ligand-binding–deficient ERBB2 (HER2) receptor and the kinase impaired ERBB3 (HER3) create a potent mitogenic signal, but the phosphorylation of ERBB2 in this context presents a challenge to established models of phosphorylation in trans. Higher order complexes of ERBB receptors have been observed biophysically and offer a theoretical route for ERBB2 phosphorylation, but it is not clear whether such complexes provide functionality beyond the constituent dimers. We now show that a previously selected inhibitory RNA aptamer that targets the extracellular domain (ECD) of ERBB3 acts by sterically disrupting these higher order interactions. Ligand binding, heterodimerization, phosphorylation of ERBB3, and AKT signaling are only minimally affected, whereas ERBB2 phosphorylation and MAPK signaling are selectively inhibited. The mapping of the binding site and creation of aptamer-resistant point mutants are consistent with a model of side-by-side oriented heterodimers to facilitate proxy phosphorylation, even at very low endogenous levels of receptors (below 10,000 receptors per cell). Additional modes of signaling with relevance to pathological ERBB expression states emerge at high receptor levels. Hence, higher order complexes of nonoverexpressed ERBB receptors are an integral and qualitatively distinct part of normal ERBB2/ERBB3 signaling. This mechanism of activation has implications for models of allosteric control, specificity of interactions, possible mechanisms of cross-talk, and approaches to therapeutic intervention that at present often generate experimental and clinical outcomes that do not reconcile with purely canonical, dimer-based models.

Precursor-ion mass re-estimation improves peptide identification on hybrid instruments.

Mass spectrometry-based proteomics experiments have become an important tool for studying biological systems. Identifying the proteins in complex mixtures by assigning peptide fragmentation spectra to peptide sequences is an important step in the proteomics process. The 1-2 ppm mass-accuracy of hybrid instruments, like the LTQ-FT, has been cited as a key factor in their ability to identify a larger number of peptides with greater confidence than competing instruments. However, in replicate experiments of an 18-protein mixture, we note parent masses deviate 171 ppm, on average, for ion-trap data directed identifications and 8 ppm, on average, for preview Fourier transform (FT) data directed identifications. These deviations are neither caused by poor calibration nor by excessive ion-loading and are most likely due to errors in parent mass estimation. To improve these deviations, we introduce msPrefix, a program to re-estimate a peptides parent mass from an associated high-accuracy full-scan survey spectrum. In 18-protein mixture experiments, msPrefix parent mass estimates deviate only 1 ppm, on average, from the identified peptides. In a cell lysate experiment searched with a tolerance of 50 ppm, 2295 peptides were confidently identified using native data and 4560 using msPrefixed data. Likewise, in a plasma experiment searched with a tolerance of 50 ppm, 326 peptides were identified using native data and 1216 using msPrefixed data. msPrefix is also able to determine which MS/MS spectra were possibly derived from multiple precursor ions. In complex mixture experiments, we demonstrate that more than 50% of triggered MS/MS may have had multiple precursor ions and note that spectra with multiple candidate ions are less likely to result in an identification using TANDEM. These results demonstrate integration of msPrefix into traditional shotgun proteomics workflows significantly improves identification results.

Anterior gradient 2 (AGR2): Blood-based biomarker elevated in metastatic prostate cancer associated with the neuroendocrine phenotype

Anterior gradient 2 (AGR2) is associated with metastatic progression in prostate cancer cells as well as other normal and malignant tissues. We investigated AGR2 expression in patients with metastatic prostate cancer.

The N-terminal Domains of Neuregulin 1 Confer Signal Attenuation

Degradation of activated ERBB receptors is an important mechanism for signal attenuation. However, compared with epidermal growth factor (EGF) receptor, the ERBB2/ERBB3 signaling pair is considered to be attenuation-deficient. The ERBB2/ERBB3 ligands of the neuregulin family rely on an EGF-like domain for signaling and are generated from larger membrane-bound precursors. In contrast to EGF, which is processed to yield a 6-kDa peptide ligand, mature neuregulins retain a variety of segments N-terminal to the EGF-like domain. Here we evaluate the role of the N-terminal domain of neuregulin 1 in signaling and turnover of ERBB2/ERBB3. Our data suggest that whereas the EGF-like domain of neuregulin 1 is required and sufficient for the formation of active receptor heterodimers, the presence of the N-terminal Ig-like domain is required for efficient signal attenuation. This manifests itself for both ERBB2 and ERBB3 but is more pronounced and coupled directly to degradation for ERBB3. When stimulated with only the EGF-like domain, ERBB3 shows degradation rates comparable with constitutive turnover, but stimulation with full-length neuregulin 1 resulted in receptor degradation at rates that are comparable with activated EGF receptor. Most of the enhancement in down-regulation was maintained after replacing the Ig-like domain with a thioredoxin protein of comparable size but different amino acid composition, suggesting that the physical presence but not specific properties of the Ig-like domain are needed. This sequence-independent effect of the N-terminal domain correlates with an enhanced ability of full-size neuregulin 1 to disrupt higher order oligomers of the ERBB3 extracellular domains in vitro.

Impact of Protein Stability, Cellular Localization, and Abundance on Proteomic Detection of Tumor-Derived Proteins in Plasma

Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a proteins stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models. A statistical analysis of this data revealed protein properties indicative of the detection level in plasma. Though 20% of the proteins identified in plasma were tumor-derived, only 5% of the proteins observed in the tumor tissue were found in plasma. Both intracellular and extracellular tumor proteins were observed in plasma; however, after normalizing for tumor abundance, extracellular proteins were seven times more likely to be detected. Although proteins that were more abundant in the tumor were also more likely to be observed in plasma, the relationship was nonlinear: Doubling the spectral count increased detection rate by only 50%. Many secreted proteins, even those with relatively low spectral count, were observed in plasma, but few low abundance intracellular proteins were observed. Proteins predicted to be stable by dipeptide composition were significantly more likely to be identified in plasma than less stable proteins. The number of tryptic peptides in a protein was not significantly related to the chance of a protein being observed in plasma. Quantitative comparison of large versus small tumors revealed that the abundance of proteins in plasma as measured by spectral count was associated with the tumor size, but the relationship was not one-to-one; a 3-fold decrease in tumor size resulted in a 16-fold decrease in protein abundance in plasma. This study provides quantitative support for a tumor-derived marker prioritization strategy that favors secreted and stable proteins over all but the most abundant intracellular proteins.

Quantitative Proteomic Profiling Identifies Protein Correlates to EGFR Kinase Inhibition

Clinical oncology is hampered by lack of tools to accurately assess a patients response to pathway-targeted therapies. Serum and tumor cell surface proteins whose abundance, or change in abundance in response to therapy, differentiates patients responding to a therapy from patients not responding to a therapy could be usefully incorporated into tools for monitoring response. Here, we posit and then verify that proteomic discovery in in vitro tissue culture models can identify proteins with concordant in vivo behavior and further, can be a valuable approach for identifying tumor-derived serum proteins. In this study, we use stable isotope labeling of amino acids in culture (SILAC) with proteomic technologies to quantitatively analyze the gefitinib-related protein changes in a model system for sensitivity to EGF receptor (EGFR)-targeted tyrosine kinase inhibitors. We identified 3,707 intracellular proteins, 1,276 cell surface proteins, and 879 shed proteins. More than 75% of the proteins identified had quantitative information, and a subset consisting of 400 proteins showed a statistically significant change in abundance following gefitinib treatment. We validated the change in expression profile in vitro and screened our panel of response markers in an in vivo isogenic resistant model and showed that these were markers of gefitinib response and not simply markers of phospho-EGFR downregulation. In doing so, we also were able to identify which proteins might be useful as markers for monitoring response and which proteins might be useful as markers for a priori prediction of response. Mol Cancer Ther; 11(5); 1071–81. ©2012 AACR.

Androgen receptor in cancer-associated fibroblasts influences stemness in cancer cells

Androgen receptor (AR) regulation pathways are essential for supporting the growth and survival of prostate cancer cells. Recently, sub-populations of prostate cancer cells have been identified with stem cell features and are associated with the emergence of treatment-resistant prostate cancer. Here, we explored the function of AR in prostate cancer-associated fibroblasts (CAFs) relative to growth and stem cell-associated characteristics. CAFs were isolated from the murine cPten-/-L prostate cancer model and cultured with human prostate cancer epithelial (hPCa) cells. A murine-specific AR antisense oligonucleotide (ASO) was used to suppress the expression of AR in the CAF cells. CAFs express low, but significant levels of AR relative to fibroblasts derived from non-malignant tissue. CAFs promoted growth and colony formation of hPCa cells, which was attenuated by the suppression of AR expression. Surprisingly, AR-depleted CAFs promoted increased stem cell marker expression in hPCa cells. Interferon gamma (IFN-γ) and macrophage colony-stimulating factor (M-CSF) were increased in AR-depleted CAF cells and exhibited similar effects on stem cell marker expression as seen in the CAF co-culture systems. Clinically, elevated IFN-γ expression was found to correlate with histologic grade in primary prostate cancer samples. In summary, AR and androgen-dependent signaling are active in CAFs and exert significant effects on prostate cancer cells. IFN-γ and M-CSF are AR-regulated factors secreted by CAF cells, which promote the expression of stem cell markers in prostate cancer epithelial cells. Understanding how CAFs and other constituents of stromal tissue react to anti-cancer therapies may provide insight into the development and progression of prostate cancer.

Simulation of the Protein-Shedding Kinetics of a Fully Vascularized Tumor

Circulating biomarkers are of significant interest for cancer detection and treatment personalization. However, the biophysical processes that determine how proteins are shed from cancer cells or their microenvironment, diffuse through tissue, enter blood vasculature, and persist in circulation remain poorly understood. Since approaches primarily focused on experimental evaluation are incapable of measuring the shedding and persistence for every possible marker candidate, we propose an interdisciplinary computational/experimental approach that includes computational modeling of tumor tissue heterogeneity. The model implements protein production, transport, and shedding based on tumor vascularization, cell proliferation, hypoxia, and necrosis, thus quantitatively relating the tumor and circulating proteomes. The results highlight the dynamics of shedding as a function of protein diffusivity and production. Linking the simulated tumor parameters to clinical tumor and vascularization measurements could potentially enable this approach to reveal the tumor-specific conditions based on the protein detected in circulation and thus help to more accurately manage cancer diagnosis and treatment.

Protein Mimetic and Anticancer Properties of Monocyte-Targeting Peptide Amphiphile Micelles

Monocyte chemoattractant protein-1 (MCP-1) stimulates the migration of monocytes to inflammatory sites, leading to the progression of many diseases. Recently, we described a monocyte-targeting peptide amphiphile micelle (MCP-1 PAM) incorporated with the chemokine receptor CCR2 binding motif of MCP-1, which has a high affinity for monocytes in atherosclerotic plaques. We further report here the biomimetic components of MCP-1 PAMs and the influence of the nanoparticle upon binding to monocytes. We report that MCP-1 PAMs have enhanced secondary structure compared to the MCP-1 peptide. As a result, MCP-1 PAMs displayed improved binding and chemoattractant properties to monocytes, which upregulated the inflammatory signaling pathways responsible for monocyte migration. Interestingly, when MCP-1 PAMs were incubated in the presence of prostate cancer cells in vitro, the particle displayed anticancer efficacy by reducing CCR2 expression. Given that monocytes play an important role in tumor cell migration and invasion, our results demonstrate that PAMs can improve the native biofunctional properties of the peptide and may be used as an effective inhibitor to prevent chemokine-receptor interactions that promote disease progression.