ASPSCR1-TFE3 reprograms transcription by organizing enhancer loops around hexameric VCP/p97.

The t(X,17) chromosomal translocation, generating the ASPSCR1::TFE3 fusion oncoprotein, is the singular genetic driver of alveolar soft part sarcoma (ASPS) and some Xp11-rearranged renal cell carcinomas (RCCs), frustrating efforts to identify therapeutic targets for these rare cancers. Here, proteomic analysis identifies VCP/p97, an AAA+ ATPase with known segregase function, as strongly enriched in co-immunoprecipitated nuclear complexes with ASPSCR1::TFE3. We demonstrate that VCP is a likely obligate co-factor of ASPSCR1::TFE3, one of the only such fusion oncoprotein co-factors identified in cancer biology. Specifically, VCP co-distributes with ASPSCR1::TFE3 across chromatin in association with enhancers genome-wide. VCP presence, its hexameric assembly, and its enzymatic function orchestrate the oncogenic transcriptional signature of ASPSCR1::TFE3, by facilitating assembly of higher-order chromatin conformation structures demonstrated by HiChIP. Finally, ASPSCR1::TFE3 and VCP demonstrate co-dependence for cancer cell proliferation and tumorigenesis in vitro and in ASPS and RCC mouse models, underscoring VCP's potential as a novel therapeutic target.

Surface and Global Proteome Analyses Identify ENPP1 and Other Surface Proteins as Actionable Immunotherapeutic Targets in Ewing Sarcoma.

PURPOSE: Ewing sarcoma is the second most common bone sarcoma in children, with 1 case per 1.5 million in the United States. Although the survival rate of patients diagnosed with localized disease is approximately 70%, this decreases to approximately 30% for patients with metastatic disease and only approximately 10% for treatment-refractory disease, which have not changed for decades. Therefore, new therapeutic strategies are urgently needed for metastatic and refractory Ewing sarcoma. EXPERIMENTAL DESIGN: This study analyzed 19 unique Ewing sarcoma patient- or cell line-derived xenografts (from 14 primary and 5 metastatic specimens) using proteomics to identify surface proteins for potential immunotherapeutic targeting. Plasma membranes were enriched using density gradient ultracentrifugation and compared with a reference standard of 12 immortalized non-Ewing sarcoma cell lines prepared in a similar manner. In parallel, global proteome analysis was carried out on each model to complement the surfaceome data. All models were analyzed by Tandem Mass Tags-based mass spectrometry to quantify identified proteins. RESULTS: The surfaceome and global proteome analyses identified 1,131 and 1,030 annotated surface proteins, respectively. Among surface proteins identified, both approaches identified known Ewing sarcoma-associated proteins, including IL1RAP, CD99, STEAP1, and ADGRG2, and many new cell surface targets, including ENPP1 and CDH11. Robust staining of ENPP1 was demonstrated in Ewing sarcoma tumors compared with other childhood sarcomas and normal tissues. CONCLUSIONS: Our comprehensive proteomic characterization of the Ewing sarcoma surfaceome provides a rich resource of surface-expressed proteins in Ewing sarcoma. This dataset provides the preclinical justification for exploration of targets such as ENPP1 for potential immunotherapeutic application in Ewing sarcoma. See related commentary by Bailey, p. 934.

ASPSCR1-TFE3 reprograms transcription by organizing enhancer loops around hexameric VCP/p97.

The t(X,17) chromosomal translocation, generating the ASPSCR1-TFE3 fusion oncoprotein, is the singular genetic driver of alveolar soft part sarcoma (ASPS) and some Xp11-rearranged renal cell carcinomas (RCC), frustrating efforts to identify therapeutic targets for these rare cancers. Proteomic analysis showed that VCP/p97, an AAA+ ATPase with known segregase function, was strongly enriched in co-immunoprecipitated nuclear complexes with ASPSCR1-TFE3. We demonstrate that VCP is a likely obligate co-factor of ASPSCR1-TFE3, one of the only such fusion oncoprotein co-factors identified in cancer biology. Specifically, VCP co-distributed with ASPSCR1-TFE3 across chromatin in association with enhancers genome-wide. VCP presence, its hexameric assembly, and its enzymatic function orchestrated the oncogenic transcriptional signature of ASPSCR1-TFE3, by facilitating assembly of higher-order chromatin conformation structures as demonstrated by HiChIP. Finally, ASPSCR1-TFE3 and VCP demonstrated co-dependence for cancer cell proliferation and tumorigenesis in vitro and in ASPS and RCC mouse models, underscoring VCP's potential as a novel therapeutic target.

A MYCN-independent mechanism mediating secretome reprogramming and metastasis in MYCN-amplified neuroblastoma.

MYCN amplification (MNA) is a defining feature of high-risk neuroblastoma (NB) and predicts poor prognosis. However, whether genes within or in close proximity to the MYCN amplicon also contribute to MNA+ NB remains poorly understood. Here, we identify that GREB1, a transcription factor encoding gene neighboring the MYCN locus, is frequently coexpressed with MYCN and promotes cell survival in MNA+ NB. GREB1 controls gene expression independently of MYCN, among which we uncover myosin 1B (MYO1B) as being highly expressed in MNA+ NB and, using a chick chorioallantoic membrane (CAM) model, as a crucial regulator of invasion and metastasis. Global secretome and proteome profiling further delineates MYO1B in regulating secretome reprogramming in MNA+ NB cells, and the cytokine MIF as an important pro-invasive and pro-metastatic mediator of MYO1B activity. Together, we have identified a putative GREB1-MYO1B-MIF axis as an unconventional mechanism promoting aggressive behavior in MNA+ NB and independently of MYCN.

Multi-Omic Analysis of CIC's Functional Networks Reveals Novel Interaction Partners and a Potential Role in Mitotic Fidelity.

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CIC's interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, as well as novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines, predominantly at 3' and 5' untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CIC's functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CIC's potential roles in cancer. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts.

Tandem mass tag-based thermal proteome profiling for the discovery of drug-protein interactions in cancer cells.

Identification of effector targets is imperative to the characterization of the mechanisms of action of novel small molecules. Here, we describe steps to identify effector drug-protein interactions in lysates derived from cancer cell lines using a thermal proteome profiling (TPP) protocol. Building on existing TTP approaches, we detail the use of an in-solution trypsin digestion technique to streamline sample preparation, a nonparametric analysis to rank proteins for prioritization, and a follow-up strategy for identifying effector interactors. For complete details on the use and execution of this protocol, please refer to Johnson et al. (2022).1.

Proteomic analysis of archival breast cancer clinical specimens identifies biological subtypes with distinct survival outcomes.

Despite advances in genomic classification of breast cancer, current clinical tests and treatment decisions are commonly based on protein level information. Formalin-fixed paraffin-embedded (FFPE) tissue specimens with extended clinical outcomes are widely available. Here, we perform comprehensive proteomic profiling of 300 FFPE breast cancer surgical specimens, 75 of each PAM50 subtype, from patients diagnosed in 2008-2013 (n = 178) and 1986-1992 (n = 122) with linked clinical outcomes. These two cohorts are analyzed separately, and we quantify 4214 proteins across all 300 samples. Within the aggressive PAM50-classified basal-like cases, proteomic profiling reveals two groups with one having characteristic immune hot expression features and highly favorable survival. Her2-Enriched cases separate into heterogeneous groups differing by extracellular matrix, lipid metabolism, and immune-response features. Within 88 triple-negative breast cancers, four proteomic clusters display features of basal-immune hot, basal-immune cold, mesenchymal, and luminal with disparate survival outcomes. Our proteomic analysis characterizes the heterogeneity of breast cancer in a clinically-applicable manner, identifies potential biomarkers and therapeutic targets, and provides a resource for clinical breast cancer classification.

Not4 and Not5 modulate translation elongation by Rps7A ubiquitination, Rli1 moonlighting, and condensates that exclude eIF5A.

In this work, we show that Not4 and Not5 from the Ccr4-Not complex modulate translation elongation dynamics and change ribosome A-site dwelling occupancy in a codon-dependent fashion. These codon-specific changes in not5Δ cells are very robust and independent of codon position within the mRNA, the overall mRNA codon composition, or changes of mRNA expression levels. They inversely correlate with codon-specific changes in cells depleted for eIF5A and positively correlate with those in cells depleted for ribosome-recycling factor Rli1. Not5 resides in punctate loci, co-purifies with ribosomes and Rli1, but not with eIF5A, and limits mRNA solubility. Overexpression of wild-type or non-complementing Rli1 and loss of Rps7A ubiquitination enable Not4 E3 ligase-dependent translation of polyarginine stretches. We propose that Not4 and Not5 modulate translation elongation dynamics to produce a soluble proteome by Rps7A ubiquitination, dynamic condensates that limit mRNA solubility and exclude eIF5A, and a moonlighting function of Rli1.

Proteomic Screens for Suppressors of Anoikis Identify IL1RAP as a Promising Surface Target in Ewing Sarcoma.

Cancer cells must overcome anoikis (detachment-induced death) to successfully metastasize. Using proteomic screens, we found that distinct oncoproteins upregulate IL1 receptor accessory protein (IL1RAP) to suppress anoikis. IL1RAP is directly induced by oncogenic fusions of Ewing sarcoma, a highly metastatic childhood sarcoma. IL1RAP inactivation triggers anoikis and impedes metastatic dissemination of Ewing sarcoma cells. Mechanistically, IL1RAP binds the cell-surface system Xc - transporter to enhance exogenous cystine uptake, thereby replenishing cysteine and the glutathione antioxidant. Under cystine depletion, IL1RAP induces cystathionine gamma lyase (CTH) to activate the transsulfuration pathway for de novo cysteine synthesis. Therefore, IL1RAP maintains cyst(e)ine and glutathione pools, which are vital for redox homeostasis and anoikis resistance. IL1RAP is minimally expressed in pediatric and adult normal tissues, and human anti-IL1RAP antibodies induce potent antibody-dependent cellular cytotoxicity of Ewing sarcoma cells. Therefore, we define IL1RAP as a new cell-surface target in Ewing sarcoma, which is potentially exploitable for immunotherapy. SIGNIFICANCE: Here, we identify cell-surface protein IL1RAP as a key driver of metastasis in Ewing sarcoma, a highly aggressive childhood sarcoma. Minimal expression in pediatric and adult normal tissues nominates IL1RAP as a promising target for immunotherapy.See related commentary by Yoon and DeNicola, p. 2679.This article is highlighted in the In This Issue feature, p. 2659.

HACE1 blocks HIF1α accumulation under hypoxia in a RAC1 dependent manner.

Uncovering the mechanisms that underpin how tumor cells adapt to microenvironmental stress is essential to better understand cancer progression. The HACE1 (HECT domain and ankyrin repeat-containing E3 ubiquitin-protein ligase) gene is a tumor suppressor that inhibits the growth, invasive capacity, and metastasis of cancer cells. However, the direct regulatory pathways whereby HACE1 confers this tumor-suppressive effect remain to be fully elucidated. In this report, we establish a link between HACE1 and the major stress factor, hypoxia-inducible factor 1 alpha (HIF1α). We find that HACE1 blocks the accumulation of HIF1α during cellular hypoxia through decreased protein stability. This property is dependent on HACE1 E3 ligase activity and loss of Ras-related C3 botulinum toxin substrate 1 (RAC1), an established target of HACE1 mediated ubiquitinylation and degradation. In vivo, genetic deletion of Rac1 reversed the increased HIF1α expression observed in Hace1-/- mice in murine KRasG12D-driven lung tumors. An inverse relationship was observed between HACE1 and HIF1α levels in tumors compared to patient-matched normal kidney tissues, highlighting the potential pathophysiological significance of our findings. Together, our data uncover a previously unrecognized function for the HACE1 tumor suppressor in blocking HIF1α accumulation under hypoxia in a RAC1-dependent manner.

Proteomic analysis of transitional cell carcinoma-like variant of tubo-ovarian high-grade serous carcinoma.

The current World Health Organization classification does not distinguish transitional cell carcinoma of the ovary (TCC) from conventional tubo-ovarian high-grade serous carcinoma (HGSC), despite evidence suggesting improved prognosis for patients with TCC; instead, it is considered a morphologic variant of HGSC. The immunohistochemical (IHC) markers applied to date do not distinguish between TCC and HGSC. Therefore, we sought to compare the proteomic profiles of TCC and conventional HGSC to identify proteins enriched in TCC. Prognostic biomarkers in HGSC have proven to be elusive, and our aim was to identify biomarkers of TCC as a way of reliably and reproducibly identifying patients with a favorable prognosis and better response to chemotherapy compared with those with conventional HGSC. Quantitative global proteome analysis was performed on archival material of 12 cases of TCC and 16 cases of HGSC using SP3 (single-pot, solid phase-enhanced, sample preparation)-Clinical Tissue Proteomics, a recently described protocol for full-proteome analysis from formalin-fixed paraffin-embedded tissues. We identified 430 proteins that were significantly enriched in TCC over HGSC. Unsupervised co-clustering perfectly distinguished TCC from HGSC based on protein expression. Pathway analysis showed that proteins associated with cell death, necrosis, and apoptosis were highly expressed in TCCs, whereas proteins associated with DNA homologous recombination, cell mitosis, proliferation and survival, and cell cycle progression pathways had reduced expression. From the proteomic analysis, three potential biomarkers for TCC were identified, claudin-4 (CLDN4), ubiquitin carboxyl-terminal esterase L1 (UCHL1), and minichromosome maintenance protein 7 (MCM7), and tested by IHC analysis on tissue microarrays. In agreement with the proteomic analysis, IHC expression of those proteins was stronger in TCC than in HGSC (p < 0.0001). Using global proteomic analysis, we are able to distinguish TCC from conventional HGSC. Follow-up studies will be necessary to confirm that these molecular and morphologic differences are clinically significant.

Class I HDAC inhibitors enhance YB-1 acetylation and oxidative stress to block sarcoma metastasis.

Outcomes for metastatic Ewing sarcoma and osteosarcoma are dismal and have not changed for decades. Oxidative stress attenuates melanoma metastasis, and melanoma cells must reduce oxidative stress to metastasize. We explored this in sarcomas by screening for oxidative stress sensitizers, which identified the class I HDAC inhibitor MS-275 as enhancing vulnerability to reactive oxygen species (ROS) in sarcoma cells. Mechanistically, MS-275 inhibits YB-1 deacetylation, decreasing its binding to 5'-UTRs of NFE2L2 encoding the antioxidant factor NRF2, thereby reducing NFE2L2 translation and synthesis of NRF2 to increase cellular ROS. By global acetylomics, MS-275 promotes rapid acetylation of the YB-1 RNA-binding protein at lysine-81, blocking binding and translational activation of NFE2L2, as well as known YB-1 mRNA targets, HIF1A, and the stress granule nucleator, G3BP1. MS-275 dramatically reduces sarcoma metastasis in vivo, but an MS-275-resistant YB-1K81-to-alanine mutant restores metastatic capacity and NRF2, HIF1α, and G3BP1 synthesis in MS-275-treated mice. These studies describe a novel function for MS-275 through enhanced YB-1 acetylation, thus inhibiting YB-1 translational control of key cytoprotective factors and its pro-metastatic activity.

The FUS-DDIT3 Interactome in Myxoid Liposarcoma.

Myxoid liposarcoma is a malignant lipogenic tumor that develops in deep soft tissues. While local control rates are good, current chemotherapy options remain ineffective against metastatic disease. Myxoid liposarcoma is characterized by the FUS-DDIT3 fusion oncoprotein that is proposed to function as an aberrant transcription factor, but its exact mechanism of action has remained unclear. To identify the key functional interacting partners of FUS-DDIT3, this study utilized immunoprecipitation-mass spectrometry (IP-MS) to identify the FUS-DDIT3 interactome in whole cell lysates of myxoid liposarcoma cells, and results showed an enrichment of RNA processing proteins. Further quantitative MS analyses of FUS-DDIT3 complexes isolated from nuclear lysates showed that members of several chromatin regulatory complexes were present in the FUS-DDIT3 interactome, including NuRD, SWI/SNF, PRC1, PRC2, and MLL1 COMPASS-like complexes. Co-immunoprecipitation validated the associations of FUS-DDIT3 with BRG1/SMARCA4, BAF155/SMARCC1, BAF57/SMARCE1, and KDM1A. Data from this study provides candidates for functional validation as potential therapeutic targets, particularly for emerging epigenetic drugs.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry.

The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

Single-pot, solid-phase-enhanced sample preparation for proteomics experiments.

A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead-based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration.

RawTools: Rapid and Dynamic Interrogation of Orbitrap Data Files for Mass Spectrometer System Management.

Optimizing the quality of proteomics data collected from a mass spectrometer (MS) requires careful selection of acquisition parameters and proper assessment of instrument performance. Software tools capable of extracting a broad set of information from raw files, including meta, scan, quantification, and identification data, are needed to provide guidance for MS system management. In this work, direct extraction and utilization of these data is demonstrated using RawTools, a standalone tool for extracting meta and scan data directly from raw MS files generated on Thermo Orbitrap instruments. RawTools generates summarized and detailed plain text outputs after parsing individual raw files, including scan rates and durations, duty cycle characteristics, precursor and reporter ion quantification, and chromatography performance. RawTools also contains a diagnostic module that includes an optional "preview" database search for facilitating informed decision-making related to optimization of MS performance based on a variety of metrics. RawTools has been developed in C# and utilizes the Thermo RawFileReader library and thus can process raw MS files with high speed and high efficiency on all major operating systems (Windows, MacOS, Linux). To demonstrate the utility of RawTools, the extraction of meta and scan data from both individual and large collections of raw MS files was carried out to identify problematic characteristics of instrument performance. Taken together, the combined rich feature-set of RawTools with the capability for interrogation of MS and experiment performance makes this software a valuable tool for proteomics researchers.

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant.

Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the "raw" MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS1, MS2, and MS3 metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags.

Extending the Compatibility of the SP3 Paramagnetic Bead Processing Approach for Proteomics.

The diversity in protein and peptide biochemistry necessitates robust protocols and reagents for efficiently handling and enriching these molecules prior to analysis with mass spectrometry (MS) or other techniques. Further exploration of the paramagnetic bead-based approach, single-pot solid-phase-enhanced sample preparation (SP3), is carried out toward updating and extending previously described conditions and experimental workflows. The SP3 approach was tested in a wide range of experimental scenarios, including (1) binding solvents (acetonitrile, ethanol, isopropanol, acetone), (2) binding pH (acidic vs neutral), (3) solvent/lysate ratios (50-200%, v/v), (4) mixing and rinsing conditions (on-rack vs off-rack rinsing), (5) Enrichment of nondenatured proteins, and (6) capture of individual proteins from noncomplex mixtures. These results highlight the robust handling of proteins in a broad set of scenarios while also enabling the development of a modified SP3 workflow that offers extended compatibility. The modified SP3 approach is used in quantitative in-depth proteome analyses to compare it with commercial paramagnetic bead-based HILIC methods (MagReSyn) and across multiple binding conditions (e.g., pH and solvent during binding). Together, these data reveal the extensive quantitative coverage of the proteome possible with SP3 independent of the binding approach utilized. The results further establish the utility of SP3 for the unbiased handling of peptides and proteins for proteomic applications.

Molecular characterization of ERBB2-amplified colorectal cancer identifies potential mechanisms of resistance to targeted therapies: a report of two instructive cases.

ERBB2 amplification has been identified in ∼5% of KRAS wild-type colorectal cancers (CRCs). A recent clinical trial showed response to HER2-directed therapy in a subset of ERBB2-amplified metastatic CRCs resistant to chemotherapy and EGFR-directed therapy. With the aim of better understanding mechanisms of resistance to HER2-directed and EGFR-directed therapies, we report the complete molecular characterization of two cases of ERBB2-amplified CRC. PCR-free whole-genome sequencing was used to identify mutations, copy-number alterations, structural variations, and losses of heterozygosity. ERBB2 copy number was also measured by fluorescence in situ hybridization. Single-stranded mRNA sequencing was used for gene expression profiling. Immunohistochemistry and protein mass spectrometry were used to quantify HER2 protein expression. The cases showed ERBB2 copy number of 86 and 92, respectively. Both cases were immunohistochemically positive for HER2 according to CRC-specific scoring criteria. Fluorescence in situ hybridization and protein mass spectrometry corroborated significantly elevated ERBB2 copy number and abundance of HER2 protein. Both cases were microsatellite stable and without mutation of RAS pathway genes. Additional findings included altered expression of PTEN, MET, and MUC1 and mutation of PIK3CA The potential effects of the molecular alterations on sensitivity to EGFR and HER2-directed therapies were discussed. Identification of ERBB2 amplification in CRC is necessary to select patients who may respond to HER2-directed therapy. An improved understanding of the molecular characteristics of ERBB2-amplified CRCs and their potential mechanisms of resistance will be useful for future research into targeted therapies and may eventually inform therapeutic decision-making.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PURPOSE: Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. EXPERIMENTAL DESIGN: To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. RESULTS: In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. CONCLUSION AND CLINICAL RELEVANCE: Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications.