Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This limitation hampers the full realization of the potential offered by shotgun phosphoproteomics. Here we present DeepRescore2, a computational workflow that leverages deep learning-based retention time and fragment ion intensity predictions to improve phosphopeptide identification and phosphosite localization. Using a state-of-the-art computational workflow as a benchmark, DeepRescore2 increases the number of correctly identified peptide-spectrum matches by 17% in a synthetic dataset and identifies 19% to 46% more phosphopeptides in biological datasets. In a liver cancer dataset, 30% of the significantly altered phosphosites between tumor and normal tissues and 60% of the prognosis-associated phosphosites identified from DeepRescore2-processed data could not be identified based on the state-of-the-art workflow. Notably, DeepRescore2-processed data uniquely identifies EGFR hyperactivation as a new target in poor-prognosis liver cancer, which is validated experimentally. Integration of deep learning prediction in DeepRescore2 improves phosphopeptide identification and facilitates biological discoveries.

Kinase inhibitor pulldown assay (KiP) for clinical proteomics

Protein kinases are frequently dysregulated and/or mutated in cancer and represent essential targets for therapy. Accurate quantification is essential. For breast cancer treatment, the identification and quantification of the protein kinase ERBB2 is critical for therapeutic decisions. While immunohistochemistry (IHC) is the current clinical diagnostic approach, it is only semiquantitative. Mass spectrometry-based proteomics offers quantitative assays that, unlike IHC, can be used to accurately evaluate hundreds of kinases simultaneously. The enrichment of less abundant kinase targets for quantification, along with depletion of interfering proteins, improves sensitivity and thus promotes more effective downstream analyses. Multiple kinase inhibitors were therefore deployed as a capture matrix for kinase inhibitor pulldown (KiP) assays designed to profile the human protein kinome as broadly as possible. Optimized assays were initially evaluated in 16 patient derived xenograft models (PDX) where KiP identified multiple differentially expressed and biologically relevant kinases. From these analyses, an optimized single-shot parallel reaction monitoring (PRM) method was developed to improve quantitative fidelity. The PRM KiP approach was then reapplied to low quantities of proteins typical of yields from core needle biopsies of human cancers. The initial prototype targeting 100 kinases recapitulated intrinsic subtyping of PDX models obtained from comprehensive proteomic and transcriptomic profiling. Luminal and HER2 enriched OCT-frozen patient biopsies subsequently analyzed through KiP-PRM also clustered by subtype. Finally, stable isotope labeled peptide standards were developed to define a prototype clinical method. Data are available via ProteomeXchange with identifiers PXD044655 and PXD046169.

Targeting eIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A with zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages toward an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon (IFN) response uniformly across models. The induction of an IFN response is partially due to the inhibition of Sox4 translation by zotatifin. A similar induction of IFN-stimulated genes was observed in breast cancer patient biopsies following zotatifin treatment. Surprisingly, zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened IFN response, resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for zotatifin, and provide a rationale for new combination regimens consisting of zotatifin and chemotherapy or immunotherapy as treatments for TNBC.

Targeting EIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A by Zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages towards an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that Zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon response uniformly across models. The induction of an interferon response is partially due to the inhibition of Sox4 translation by Zotatifin. A similar induction of interferon-stimulated genes was observed in breast cancer patient biopsies following Zotatifin treatment. Surprisingly, Zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened interferon response resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for Zotatifin, and provide a rationale for new combination regimens comprising Zotatifin and chemotherapy or immunotherapy as treatments for TNBC.

A defective mechanosensing pathway affects fibroblast-to-myofibroblast transition in the old male mouse heart

The cardiac fibroblast interacts with an extracellular matrix (ECM), enabling myofibroblast maturation via a process called mechanosensing. Although in the aging male heart, ECM is stiffer than in the young mouse, myofibroblast development is impaired, as demonstrated in 2-D and 3-D experiments. In old male cardiac fibroblasts, we found a decrease in actin polymerization, α-smooth muscle actin (α-SMA), and Kindlin-2 expressions, the latter an effector of the mechanosensing. When Kindlin-2 levels were manipulated via siRNA interference, young fibroblasts developed an old-like fibroblast phenotype, whereas Kindlin-2 overexpression in old fibroblasts reversed the defective phenotype. Finally, inhibition of overactivated extracellular regulated kinases 1 and 2 (ERK1/2) in the old male fibroblasts rescued actin polymerization and α-SMA expression. Pathological ERK1/2 overactivation was also attenuated by Kindlin-2 overexpression. In contrast, old female cardiac fibroblasts retained an operant mechanosensing pathway. In conclusion, we identified defective components of the Kindlin/ERK/actin/α-SMA mechanosensing axis in aged male fibroblasts.

Kinase Inhibitor Pulldown Assay Identifies a Chemotherapy Response Signature in Triple-negative Breast Cancer Based on Purine-binding Proteins

Triple-negative breast cancer (TNBC) constitutes 10%-15% of all breast tumors. The current standard of care is multiagent chemotherapy, which is effective in only a subset of patients. The original objective of this study was to deploy a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) to identify kinases elevated in non-pCR (pathologic complete response) cases for therapeutic targeting. Frozen optimal cutting temperature compound-embedded core needle biopsies were obtained from 43 patients with TNBC before docetaxel- and carboplatin-based neoadjuvant chemotherapy. KIPA was applied to the native tumor lysates that were extracted from samples with high tumor content. Seven percent of all identified proteins were kinases, and none were significantly associated with lack of pCR. However, among a large population of "off-target" purine-binding proteins (PBP) identified, seven were enriched in pCR-associated samples (P < 0.01). In orthogonal mRNA-based TNBC datasets, this seven-gene "PBP signature" was associated with chemotherapy sensitivity and favorable clinical outcomes. Functional annotation demonstrated IFN gamma response, nuclear import of DNA repair proteins, and cell death associations. Comparisons with standard tandem mass tagged-based discovery proteomics performed on the same samples demonstrated that KIPA-nominated pCR biomarkers were unique to the platform. KIPA is a novel biomarker discovery tool with unexpected utility for the identification of PBPs related to cytotoxic drug response. The PBP signature has the potential to contribute to clinical trials designed to either escalate or de-escalate therapy based on pCR probability.

Significance

The identification of pretreatment predictive biomarkers for pCR in response to neoadjuvant chemotherapy would advance precision treatment for TNBC. To complement standard proteogenomic discovery profiling, a KIPA was deployed and unexpectedly identified a seven-member non-kinase PBP pCR-associated signature. Individual members served diverse pathways including IFN gamma response, nuclear import of DNA repair proteins, and cell death.

Abstract P6-11-10: Investigating the role of mitochondrial protein translation in the metabolic adaptation of chemoresistant triple negative breast cancer

BACKGROUND: Nearly 50% of patients with triple negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NACT) retain residual tumors resulting in high rates of metastatic relapse and poor overall survival. Residual tumors surviving NACT (Adriamycin plus cyclophosphamide; AC) were found to undergo a metabolic transition to heightened mitochondrial oxidative phosphorylation (oxphos; PMID: 30996079). Pharmacologic inhibition of mitochondrial electron transport chain (ETC) complex I with IACS-010759 (PMID: 29892070) had enhanced efficacy in residual, rather than treatment-naïve, tumors of orthotopic patient-derived xenograft (PDX) models. Our analyses of mitochondrial structure and function in human TNBC cell lines revealed differing adaptations in residual cells surviving treatment with conventional NACT agents. While DNA-damaging chemotherapies (e.g.Adriamycin, carboplatin) induced mitochondrial fusion and oxphos, taxanes (e.g.paclitaxel, docetaxel) induced mitochondrial fragmentation and reduced oxphos (Baek et al., Biorxiv Doi 10.1101/2022.02.25.481996). The mechanistic basis of these mitochondrial adaptations is not yet understood. The mitochondrial ETC consists of 92 proteins, 13 of which are encoded in the mitochondrial genome (mtDNA) and translated by the mitoribosome, while the remaining are encoded by the nuclear genome (nDNA), translated by the cytoribosome, and inserted into the inner mitochondrial membrane by accessory proteins, namely Oxidase (Cytochrome C) Assembly 1-Like (OXA1L). Disruption of OXA1L in mammalian cells has been shown to affect the levels and activity of ETC complexes I, III, IV, and V, and thus diminish oxphos. We aim to determine whether mitochondrial translation and OXA1L activity represent therapeutic vulnerabilities to overcome pro-survival metabolic adaptations in chemoresistant TNBC thereby augmenting treatment response. METHODS: Weare evaluating the effects of conventional TNBC chemotherapies singly, and in standard combinations, on mitochondrial translation and ETC formation in human TNBC cells and PDX models(PIM001-P, WHIM14, BCM15116) using metabolomic and proteomic profiling. To perturb these processes genetically, we knocked down (KD) OXA1Lwith siRNA. We are complementing these studies pharmacologically using conventional antibiotics, such as tigecycline, as previous studies showed they inhibit mitochondrial translation in breast and other cancers (PMID: 25625193). These studies will reveal whether OXA1L and mitochondrial translation are required for metabolic adaption and chemotherapy resistance of residual TNBC cells. PDX preclinical trials based on our published residual tumor testing schema (PMID: 30996079), will reveal whether the sequential combination of NACT followed by tigecycline can effectively perturb residual tumor relapse. RESULTS: Proteomic profiling of longitudinally harvested PDX tumors demonstrates substantial disruption of mitochondria-and nuclear-encoded ETC components in residual vs. treatment-naïve tumors. Interestingly, these patterns are distinct between different chemotherapy treatments, with an increase of ETC components in carboplatin-treated residual tumors compared to a decrease in docetaxel-treated residual tumors. Western blot analyses of human cell lines show OXA1LKD perturbs levels of both nuclear-and mitochondria-encoded ETC components. Preliminary findings suggest OXA1LKD increases sensitivity to chemotherapies in human TNBC cell lines. Finally, tigecycline effectively inhibits TNBC cell growth. We next will evaluate whether residual cells not killed by conventional chemotherapies have enhanced tigecycline susceptibility. CONCLUSION: These data suggest targeting mitochondrial translation may be a promising approach to overcome pro-survival metabolic adaptations in residual TNBC cells not killed by conventional chemotherapies.

Citation Format: Mariah J. Berner, Lily Baek, Junegoo Lee, Philip L. Lorenzi, Mei Leng, Alexander B. Saltzman, Anna Malovannaya, Lacey E. Dobrolecki, Christina Sallas, Michael T. Lewis, Gloria V. Echeverria. Investigating the role of mitochondrial protein translation in the metabolic adaptation of chemoresistant triple negative breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-11-10.

Abstract P2-23-01: Patient-derived xenografts allow deconvolution of single agent and combination chemotherapy responses in triple-negative breast cancer

Background: Triple-negative breast cancer (TNBC) patients frequently receive combination chemotherapy treatment, but a direct comparison of response to carboplatin, docetaxel, and their combination in 50 TNBC patient-derived xenografts (PDXs) showed that combination treatment was largely ineffective at generating enhanced responses over the best single agent. This suggests de-escalation of chemotherapy may be possible if molecular mechanisms and biomarkers underlying response to individual treatments can be identified. To this end, we performed multi-omics profiling for the 50 TNBC PDXs. Methods: Orthotopic TNBC PDXs were treated with four weekly cycles of docetaxel, carboplatin, or the combination. Changes in tumor volume after 4 weeks of treatment were assessed quantitatively and by modified RECIST criteria. Genomic, transcriptomic, and mass-spectrometry-based proteomic profiling were performed on baseline tumors prior to treatments to identify associations with chemotherapy response at the gene and pathway level. ProMS was used to integrate both RNA and protein data to select a 5 RNA feature combination for optimized prediction of carboplatin response in a logistic regression model. Publicly available neoadjuvant chemotherapy clinical datasets with transcriptomic data and response information used for validation/testing included TNBC samples from: GSE18864, I-SPY2 (GSE194040), and BrighTNess (GSE164458). Results: Proteogenomic profiles revealed distinct genes associated with response to each agent and their combination, respectively, suggesting distinct molecular mechanisms underlying response to each treatment. A substantial number of genes associated with single agent and combination treatment were validated in multiple independent patient cohorts receiving platinum and taxane containing neoadjuvant therapy, confirming clinical relevance of our PDX panel. For the same treatment, different types of molecular data identified distinct sets of associated genes, providing highly complementary information. At the pathway level, RNA and protein data converged to metabolic and E2F/G2M related pathways which were upregulated in PDXs resistant or responsive to all treatment types, respectively, while variable levels of MYC-related proliferation pathways were observed across all treatments suggesting pathways that are common across and unique to different treatments. Several individual genes found to be higher in PDXs with better response to either single-agent had discriminatory power in external clinical TNBC datasets treated with similar neoadjuvant chemotherapy regimens. In addition, a logistic regression-based carboplatin response prediction model trained to select a group of 5 RNA markers (TKT, MAGI2, ATF6B, MCM7, LRP6) using both RNA and protein data performed the best in predicting response to cisplatin in a clinical TNBC dataset vs predicting response to other datasets with taxane and platinum + taxane combination containing chemotherapy regimens, demonstrating specificity of the prediction model. These results suggest potential individual biomarkers or biomarker combinations to select TNBC tumors that may respond to either single agent carboplatin, docetaxel, or their combination. PDXs refractory to all treatment arms had higher levels of proteostasis-related pathways including proteasome degradation and the unfolded protein response (UPR) related to endoplasmic reticulum stress and altered levels of chromatin regulation. Subsequent pharmacological targeting of the UPR pathway and targeting HDACs enhanced chemotherapy response. Conclusion: Proteogenomic characterization identifies molecular mechanisms and putative biomarkers for stratifying TNBC tumors for single or combination chemotherapy treatments, suggests targeted therapies to augment chemotherapy response, and provides a valuable resource for researchers and clinicians.

Citation Format: Jonathan T. Lei, Chen Huang, Ramakrishnan R. Srinivasan, Suhas Vasaikar, Lacey E. Dobrolecki, Alaina N. Lewis, Na Zhao, Jin Cao, Susan G. Hilsenbeck, C. Kent Osborne, Mothaffar Rimawi, Matthew J. Ellis, Varduhi Petrosyan, Alexander B. Saltzman, Anna Malovannaya, John D. Landua, Bo Wen, Antrix Jain, Gerburg M. Wulf, Shunqiang Li, Daniel C. Kraushaar, Tao Wang, Xi Chen, Gloria V. Echeverria, Meenakshi Anurag, Bing Zhang, Michael T. Lewis. Patient-derived xenografts allow deconvolution of single agent and combination chemotherapy responses in triple-negative breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-23-01.

Mutations in Hcfc1 and Ronin result in an inborn error of cobalamin metabolism and ribosomopathy

Combined methylmalonic acidemia and homocystinuria (cblC) is the most common inborn error of intracellular cobalamin metabolism and due to mutations in Methylmalonic Aciduria type C and Homocystinuria (MMACHC). Recently, mutations in the transcriptional regulators HCFC1 and RONIN (THAP11) were shown to result in cellular phenocopies of cblC. Since HCFC1/RONIN jointly regulate MMACHC, patients with mutations in these factors suffer from reduced MMACHC expression and exhibit a cblC-like disease. However, additional de-regulated genes and the resulting pathophysiology is unknown. Therefore, we have generated mouse models of this disease. In addition to exhibiting loss of Mmachc, metabolic perturbations, and developmental defects previously observed in cblC, we uncovered reduced expression of target genes that encode ribosome protein subunits. We also identified specific phenotypes that we ascribe to deregulation of ribosome biogenesis impacting normal translation during development. These findings identify HCFC1/RONIN as transcriptional regulators of ribosome biogenesis during development and their mutation results in complex syndromes exhibiting aspects of both cblC and ribosomopathies.

Combined methylmalonic acidemia (MMA) and hyperhomocysteinemias are inborn errors of vitamin B12 metabolism, and mutations in the transcriptional regulators HCFC1 and RONIN (THAP11) underlie some forms of these disorders. Here the authors generated mouse models of a human syndrome due to mutations in RONIN (THAP11) and HCFC1, and show that this syndrome is both an inborn error of vitamin B12 metabolism and displays some features of ribosomopathy.

Abstract 2992: Proteogenomic characterization of triple-negative breast cancer patient-derived xenografts reveals molecular correlates of differential chemotherapy response and potential therapeutic targets to overcome resistance

Background: Chemotherapy is essential for the management of patients with triple-negative breast cancer (TNBC). Identification of biomarkers that may indicate treatment efficacy will be critical to improve patient stratification prior to treatment. To elucidate molecular determinants underlying chemotherapy response, we conducted a proteogenomic study using TNBC patient-derived xenografts (PDXs) treated with chemotherapy.

Approach: 50 TNBC PDXs were treated with either docetaxel or carboplatin. Changes in tumor volume after 4 weeks from baseline were evaluated. Genomic, transcriptomic, and mass-spectrometry-based proteomic profiling were performed on baseline tumors prior to treatment to identify associations with chemotherapy response. Fisher's exact tests were used to test for significant enrichment of mutation and copy number events (p&lt;0.05). Gene Set Enrichment Analysis was performed for pathway analyses.

Results: At the DNA level, genomic aberrations in BRCA2 and BCL2 were enriched in carboplatin-responsive PDXs, while ARID1B aberrations were enriched in docetaxel-responsive PDXs. Gene-drug response correlations supported by both mRNA and protein-based measurements, but not mRNA or protein alone, for both carboplatin and docetaxel treatment in PDXs were associated with prognosis from basal and claudin-low human breast tumors in receipt of any chemotherapy from the METABRIC dataset. These data suggest that the combination of mRNA and protein data increased power to identify genes related to clinical outcome in TNBC. Some of the top genes overexpressed at both mRNA and protein levels in chemoresistant PDXs are targets of approved drugs, many of which have not been evaluated for their ability to augment response to taxane- or platinum-based chemotherapies. These genes are being investigated as therapeutic targets as well as markers of chemotherapy response. At the pathway level, both RNA and protein data associated models resistant to both agents with enhanced oxidative phosphorylation and translation regulation. Protein data further associated resistant models with elevated cytoplasmic ribosomal proteins. In contrast, both RNA and protein data associated tumors sensitive to both agents with genes involved in the E2F-Rb axis and cell cycle progression. Moreover, DNA mismatch repair and mRNA processing pathways were uniquely associated with carboplatin and docetaxel sensitivity, respectively, while amino acid metabolism and MAPK signaling pathways were uniquely associated with carboplatin and docetaxel resistance, respectively.

Conclusion: Taken together, proteogenomic analysis of PDX tumors identifies diverse genes and pathways associated with chemotherapy response and further suggests potential therapeutic opportunities in TNBC.

Citation Format: Jonathan T. Lei, Chen Huang, Ramakrishnan R. Srinivasan, Suhas Vasaikar, Lacey E. Dobrolecki, Alaina N. Lewis, Christina Sallas, Susan G. Hilsenbeck, C Kent Osborne, Mothaffar F. Rimawi, Matthew J. Ellis, Varduhi Petrosyan, Alexander B. Saltzman, Anna Malovannaya, Gerburg Wulf, Daniel C. Kraushaar, Tao Wang, Gloria V. Echeverria, Bing Zhang, Michael T. Lewis. Proteogenomic characterization of triple-negative breast cancer patient-derived xenografts reveals molecular correlates of differential chemotherapy response and potential therapeutic targets to overcome resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2992.

Spliceosome-targeted therapies trigger an antiviral immune response in triple-negative breast cancer

Many oncogenic insults deregulate RNA splicing, often leading to hypersensitivity of tumors to spliceosome-targeted therapies (STTs). However, the mechanisms by which STTs selectively kill cancers remain largely unknown. Herein, we discover that mis-spliced RNA itself is a molecular trigger for tumor killing through viral mimicry. In MYC-driven triple-negative breast cancer, STTs cause widespread cytoplasmic accumulation of mis-spliced mRNAs, many of which form double-stranded structures. Double-stranded RNA (dsRNA)-binding proteins recognize these endogenous dsRNAs, triggering antiviral signaling and extrinsic apoptosis. In immune-competent models of breast cancer, STTs cause tumor cell-intrinsic antiviral signaling, downstream adaptive immune signaling, and tumor cell death. Furthermore, RNA mis-splicing in human breast cancers correlates with innate and adaptive immune signatures, especially in MYC-amplified tumors that are typically immune cold. These findings indicate that dsRNA-sensing pathways respond to global aberrations of RNA splicing in cancer and provoke the hypothesis that STTs may provide unexplored strategies to activate anti-tumor immune pathways.

A Cross-Linking-Aided Immunoprecipitation/Mass Spectrometry Workflow Reveals Extensive Intracellular Trafficking in Time-Resolved, Signal-Dependent Epidermal Growth Factor Receptor Proteome

Ligand binding to the cell surface receptors initiates signaling cascades that are commonly transduced through a protein-protein interaction (PPI) network to activate a plethora of response pathways. However, tools to capture the membrane PPI network are lacking. Here, we describe a cross-linking-aided mass spectrometry workflow for isolation and identification of signal-dependent epidermal growth factor receptor (EGFR) proteome. We performed protein cross-linking in cell culture at various time points following EGF treatment, followed by immunoprecipitation of endogenous EGFR and analysis of the associated proteins by quantitative mass spectrometry. We identified 140 proteins with high confidence during a 2 h time course by data-dependent acquisition and further validated the results by parallel reaction monitoring. A large proportion of proteins in the EGFR proteome function in endocytosis and intracellular protein transport. The EGFR proteome was highly dynamic with distinct temporal behavior; 10 proteins that appeared in all time points constitute the core proteome. Functional characterization showed that loss of the FYVE domain-containing proteins altered the EGFR intracellular distribution but had a minor effect on EGFR proteome or signaling. Thus, our results suggest that the EGFR proteome include functional regulators that influence EGFR signaling and bystanders that are captured as the components of endocytic vesicles. The high-resolution spatiotemporal information of these molecules facilitates the delineation of many pathways that could determine the strength and duration of the signaling, as well as the location and destination of the receptor.

MiR-146a wild-type 3' sequence identity is dispensable for proper innate immune function in vivo

The prevailing model of microRNA function is that the "seed region" (nt 2-8) is sufficient to mediate target recognition and repression. However, numerous recent studies have challenged this model, either by demonstrating extensive 3' pairing between physically defined miRNA-mRNA pairs or by showing in Caenorhabditis elegans that disrupted 3' pairing can result in impaired function in vivo. To test the importance of miRNA 3' pairing in a mammalian system in vivo, we engineered a mutant murine mir-146a allele in which the 5' half of the mature microRNA retains its wild-type sequence, but the 3' half's sequence has been altered to robustly disrupt predicted pairing to this latter region. Mice homozygous or hemizygous for this mutant allele are phenotypically indistinguishable from wild-type controls and do not recapitulate any of the immunopathology previously described for mir-146a-null mice. Our results indicate that 3' pairing is dispensable for the established myeloid function of this key mammalian microRNA.

gpGrouper: A Peptide Grouping Algorithm for Gene-Centric Inference and Quantitation of Bottom-Up Proteomics Data

In quantitative mass spectrometry, the method by which peptides are grouped into proteins can have dramatic effects on downstream analyses. Here we describe gpGrouper, an inference and quantitation algorithm that offers an alternative method for assignment of protein groups by gene locus and improves pseudo-absolute iBAQ quantitation by weighted distribution of shared peptide areas. We experimentally show that distributing shared peptide quantities based on unique peptide peak ratios improves quantitation accuracy compared with conventional winner-take-all scenarios. Furthermore, gpGrouper seamlessly handles two-species samples such as patient-derived xenografts (PDXs) without ignoring the host species or species-shared peptides. This is a critical capability for proper evaluation of proteomics data from PDX samples, where stromal infiltration varies across individual tumors. Finally, gpGrouper calculates peptide peak area (MS1) based expression estimates from multiplexed isobaric data, producing iBAQ results that are directly comparable across label-free, isotopic, and isobaric proteomics approaches.