Quantitative proteomic landscape of metaplastic breast carcinoma pathological subtypes and their relationship to triple-negative tumors

A precise microdissection strategy enabled spatial heterogeneity analysis on the targeted region of formalin-fixed paraffin-embedded tissues

In recent years, the development of spatial transcriptomic technologies has enabled us to gain an in-depth understanding of the spatial heterogeneity of gene expression in biological tissues. However, a simple and efficient tool is required to analyze multiple spatial targets, such as mRNAs, miRNAs, or genetic mutations, at high resolution in formalin-fixed paraffin-embedded (FFPE) tissue sections. In this study, we developed hydrogel pathological sectioning coupled with the previously reported Sampling Junior instrument (HPSJ) to assess the spatial heterogeneity of multiple targets in FFPE sections at a scale of 180 μm. The HPSJ platform was used to demonstrate the spatial heterogeneity of 9 ferroptosis-related genes (TFRC, NCOA4, FTH1, ACSL4, LPCAT3, ALOX12, SLC7A11, GLS2, and GPX4) and 2 miRNAs (miR-185-5p and miR522) in FFPE tissue samples from patients with triple-negative breast cancer (TNBC). The results validated the significant heterogeneity of ferroptosis-related mRNAs and miRNAs. In addition, HPSJ confirmed the spatial heterogeneity of the L858R mutation in 7 operation-sourced and 4 needle-biopsy-sourced FFPE samples from patients with lung adenocarcinoma (LUAD). The successful detection of clinical FFPE samples indicates that HPSJ is a precise, high-throughput, cost-effective, and universal platform for analyzing spatial heterogeneity, which is beneficial for elucidating the mechanisms underlying drug resistance and guiding the prescription of mutant-targeted drugs in patients with tumors.

Analysis of Protein Cysteine Acylation Using a Modified Suspension Trap (Acyl-Trap)

Proteins undergo reversible S-acylation via a thioester linkage in vivo. S-palmitoylation, modification by C16:0 fatty acid, is a common S-acylation that mediates critical protein-membrane and protein-protein interactions. The most widely used S-acylation assays, including acyl-biotin exchange and acyl resin-assisted capture, utilize blocking of free Cys thiols, hydroxylamine-dependent cleavage of the thioester and subsequent labeling of nascent thiol. These assays generally require >500 μg of protein input material per sample and numerous reagent removal and washing steps, making them laborious and ill-suited for high throughput and low input applications. To overcome these limitations, we devised "Acyl-Trap", a suspension trap-based assay that utilizes a thiol-reactive quartz to enable buffer exchange and hydroxylamine-mediated S-acyl enrichment. We show that the method is compatible with protein-level detection of S-acylated proteins (e.g., H-Ras) as well as S-acyl site identification and quantification using "on trap" isobaric labeling and LC-MS/MS from as little as 20 μg of protein input. In mouse brain, Acyl-Trap identified 279 reported sites of S-acylation and 1298 previously unreported putative sites. Also described are conditions for long-term hydroxylamine storage, which streamline the assay. More generally, Acyl-Trap serves as a proof-of-concept for PTM-tailored suspension traps suitable for both traditional protein detection and chemoproteomic workflows.

Analysis of Protein Cysteine Acylation Using a Modified Suspension Trap (Acyl-Trap)

Proteins undergo reversible S-acylation via a thioester linkage in vivo. S-palmitoylation, modification by C16:0 fatty acid, is a common S-acylation that mediates critical protein-membrane and protein-protein interactions. The most widely used S-acylation assays, including acyl-biotin exchange and acyl resin-assisted capture, utilize blocking of free Cys thiols, hydroxylamine-dependent cleavage of the thioester and subsequent labeling of nascent thiol. These assays generally require >500 micrograms of protein input material per sample and numerous reagent removal and washing steps, making them laborious and ill-suited for high throughput and low input applications. To overcome these limitations, we devised "Acyl-Trap", a suspension trap-based assay that utilizes a thiol-reactive quartz to enable buffer exchange and hydroxylamine-mediated S-acyl enrichment. We show that the method is compatible with protein-level detection of S-acylated proteins (e.g. H-Ras) as well as S-acyl site identification and quantification using "on trap" isobaric labeling and LC-MS/MS from as little as 20 micrograms of protein input. In mouse brain, Acyl-Trap identified 279 reported sites of S-acylation and 1298 previously unreported putative sites. Also described are conditions for long-term hydroxylamine storage, which streamlines the assay. More generally, Acyl-Trap serves as a proof-of-concept for PTM-tailored suspension traps suitable for both traditional protein detection and chemoproteomic workflows.

Koina: Democratizing machine learning for proteomics research

Recent developments in machine-learning (ML) and deep-learning (DL) have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML/DL models for various applications and peptide properties are frequently published, the rate at which these models are adopted by the community is slow, which is mostly due to technical challenges. We believe that, for the community to make better use of state-of-the-art models, more attention should be spent on making models easy to use and accessible by the community. To facilitate this, we developed Koina, an open-source containerized, decentralized and online-accessible high-performance prediction service that enables ML/DL model usage in any pipeline. Using the widely used FragPipe computational platform as example, we show how Koina can be easily integrated with existing proteomics software tools and how these integrations improve data analysis.

Comprehensive proteogenomic characterization of rare kidney tumors

Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.

A comprehensive overview of metaplastic breast cancer: Features and treatments

Metaplastic breast cancer is a rare, aggressive, and chemotherapy-resistant subtype of breast cancers, accounting for less than 1% of invasive breast cancers, characterized by adenocarcinoma with spindle cells, squamous epithelium, and/or mesenchymal tissue differentiation. The majority of metaplastic breast cancers exhibit the characteristics of triple-negative breast cancer and have unfavorable prognoses with a lower survival rate. This subtype often displays gene alterations in the PI3K/AKT pathway, Wnt/β-catenin pathway, and cell cycle dysregulation and demonstrates epithelial-mesenchymal transition, immune response changes, TP53 mutation, EGFR amplification, and so on. Currently, the optimal treatment of metaplastic breast cancer remains uncertain. This article provides a comprehensive review on the clinical features, molecular characteristics, invasion and metastasis patterns, and prognosis of metaplastic breast cancer, as well as recent advancements in treatment strategies.

Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets

Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal cancer and is characterized by an unfavorable prognosis. To elucidate the distinct molecular alterations in ESCC and investigate therapeutic targets, we performed a comprehensive analysis of transcriptomics, proteomics, and phosphoproteomics data derived from 60 paired treatment-naive ESCC and adjacent nontumor tissue samples. Additionally, we conducted a correlation analysis to describe the regulatory relationship between transcriptomic and proteomic processes, revealing alterations in key metabolic pathways. Unsupervised clustering analysis of the proteomics data stratified patients with ESCC into 3 subtypes with different molecular characteristics and clinical outcomes. Notably, subtype III exhibited the worst prognosis and enrichment in proteins associated with malignant processes, including glycolysis and DNA repair pathways. Furthermore, translocase of inner mitochondrial membrane domain containing 1 (TIMMDC1) was validated as a potential prognostic molecule for ESCC. Moreover, integrated kinase-substrate network analysis using the phosphoproteome nominated candidate kinases as potential targets. In vitro and in vivo experiments further confirmed casein kinase II subunit α (CSNK2A1) as a potential kinase target for ESCC. These underlying data represent a valuable resource for researchers that may provide better insights into the biology and treatment of ESCC.

Integrated stress response plasticity governs normal cell adaptation to chronic stress via the PP2A-TFE3-ATF4 pathway

The integrated stress response (ISR) regulates cell fate during conditions of stress by leveraging the cell's capacity to endure sustainable and efficient adaptive stress responses. Protein phosphatase 2A (PP2A) activity modulation has been shown to be successful in achieving both therapeutic efficacy and safety across various cancer models; however, the molecular mechanisms driving its selective antitumor effects remain unclear. Here, we show for the first time that ISR plasticity relies on PP2A activation to regulate drug response and dictate cellular fate under conditions of chronic stress. We demonstrate that genetic and chemical modulation of the PP2A leads to chronic proteolytic stress and triggers an ISR to dictate cell fate. More specifically, we uncovered that the PP2A-TFE3-ATF4 pathway governs ISR cell plasticity during endoplasmic reticular and cellular stress independent of the unfolded protein response. We further show that normal cells reprogram their genetic signatures to undergo ISR-mediated adaptation and homeostatic recovery thereby successfully avoiding toxicity following PP2A-mediated stress. Conversely, oncogenic specific cytotoxicity induced by chemical modulation of PP2A is achieved by activating chronic and irreversible ISR in cancer cells. Our findings propose that a differential response to chemical modulation of PP2A is determined by intrinsic ISR plasticity, providing a novel biological vulnerability to selectively induce cancer cell death and improve targeted therapeutic efficacy.

Starfysh integrates spatial transcriptomic and histologic data to reveal heterogeneous tumor-immune hubs

Spatially resolved gene expression profiling provides insight into tissue organization and cell-cell crosstalk; however, sequencing-based spatial transcriptomics (ST) lacks single-cell resolution. Current ST analysis methods require single-cell RNA sequencing data as a reference for rigorous interpretation of cell states, mostly do not use associated histology images and are not capable of inferring shared neighborhoods across multiple tissues. Here we present Starfysh, a computational toolbox using a deep generative model that incorporates archetypal analysis and any known cell type markers to characterize known or new tissue-specific cell states without a single-cell reference. Starfysh improves the characterization of spatial dynamics in complex tissues using histology images and enables the comparison of niches as spatial hubs across tissues. Integrative analysis of primary estrogen receptor (ER)-positive breast cancer, triple-negative breast cancer (TNBC) and metaplastic breast cancer (MBC) tissues led to the identification of spatial hubs with patient- and disease-specific cell type compositions and revealed metabolic reprogramming shaping immunosuppressive hubs in aggressive MBC.

Illuminating the Dark Cancer Phosphoproteome Through a Machine-Learned Co-Regulation Map of 26,280 Phosphosites

Mass spectrometry-based phosphoproteomics offers a comprehensive view of protein phosphorylation, but limited knowledge about the regulation and function of most phosphosites restricts our ability to extract meaningful biological insights from phosphoproteomics data. To address this, we combine machine learning and phosphoproteomic data from 1,195 tumor specimens spanning 11 cancer types to construct CoPheeMap, a network mapping the co-regulation of 26,280 phosphosites. Integrating network features from CoPheeMap into a machine learning model, CoPheeKSA, we achieve superior performance in predicting kinase-substrate associations. CoPheeKSA reveals 24,015 associations between 9,399 phosphosites and 104 serine/threonine kinases, including many unannotated phosphosites and under-studied kinases. We validate the accuracy of these predictions using experimentally determined kinase-substrate specificities. By applying CoPheeMap and CoPheeKSA to phosphosites with high computationally predicted functional significance and cancer-associated phosphosites, we demonstrate the effectiveness of these tools in systematically illuminating phosphosites of interest, revealing dysregulated signaling processes in human cancer, and identifying under-studied kinases as putative therapeutic targets.

Analysis and visualization of quantitative proteomics data using FragPipe-Analyst

The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.

Proteometabolomics of initial and recurrent glioblastoma highlights an increased immune cell signature with altered lipid metabolism

BACKGROUND

There is an urgent need to better understand the mechanisms associated with the development, progression, and onset of recurrence after initial surgery in glioblastoma (GBM). The use of integrative phenotype-focused -omics technologies such as proteomics and lipidomics provides an unbiased approach to explore the molecular evolution of the tumor and its associated environment.

METHODS

We assembled a cohort of patient-matched initial (iGBM) and recurrent (rGBM) specimens of resected GBM. Proteome and metabolome composition were determined by mass spectrometry-based techniques. We performed neutrophil-GBM cell coculture experiments to evaluate the behavior of rGBM-enriched proteins in the tumor microenvironment. ELISA-based quantitation of candidate proteins was performed to test the association of their plasma concentrations in iGBM with the onset of recurrence.

RESULTS

Proteomic profiles reflect increased immune cell infiltration and extracellular matrix reorganization in rGBM. ASAH1, SYMN, and GPNMB were highly enriched proteins in rGBM. Lipidomics indicates the downregulation of ceramides in rGBM. Cell analyses suggest a role for ASAH1 in neutrophils and its localization in extracellular traps. Plasma concentrations of ASAH1 and SYNM show an association with time to recurrence.

CONCLUSIONS

We describe the potential importance of ASAH1 in tumor progression and development of rGBM via metabolic rearrangement and showcase the feedback from the tumor microenvironment to plasma proteome profiles. We report the potential of ASAH1 and SYNM as plasma markers of rGBM progression. The published datasets can be considered as a resource for further functional and biomarker studies involving additional -omics technologies.

Pan-cancer proteogenomics characterization of tumor immunity

Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.

Chemotherapy is of prognostic significance to metaplastic breast cancer

This study aimed to evaluate the significance of chemotherapy (CT) among metaplastic breast cancer (MpBC), and to compare the survival outcomes between triple negative MpBC (MpBC-TNBC) and triple negative invasive ductal carcinoma (IDC-TNBC). SEER database was indexed to identify female unilateral primary MpBC diagnosed from 2010 to 2017. Patients were classified into neoadjuvant chemotherapy (NAC) with response (NAC-response), NAC-no response, adjuvant chemotherapy, and no CT. Breast cancer-specific survival (BCSS) and overall survival (OS) was estimated using the Kaplan-Meier method and compared by log-rank test. Cox regression was used to evaluate the independent prognostic factors. A 1:4 propensity score matching method was adopted to balance baseline differences. Altogether 1186 MpBC patients were enrolled, among them 181 received NAC, 647 received adjuvant CT and 358 did not receive any CT. Chemotherapy was an independent favorable prognostic factor. NAC-response and adjuvant CT had a significant or an obvious trend of survival improvement compared with NAC-no response or no CT. MpBC-TNBC was an independent unfavorable prognostic factor compared with IDC-TNBC. Among them, there was significant or trend of survival improvement among all TNBCs receiving NAC or adjuvant CT compared with no CT. Chemotherapy was of important significance to MpBC prognosis and should be integrated in comprehensive treatment for MpBC.

Construction of shared gene signature between rheumatoid arthritis and lung adenocarcinoma helps to predict the prognosis and tumor microenvironment of the LUAD patients

Introduction: Rheumatoid arthritis (RA) is a common chronic autoimmune disease with high incidence rate and high disability rate. One of the top complications is cancer, especially lung adenocarcinoma (LUAD). However, the molecular mechanisms linking RA and LUAD are still not clear. Therefore, in this study, we tried to identify the shared genetic signatures and local immune microenvironment between RA and LUAD and construct a clinical model for survival prediction. Methods: We obtained gene expression profiles and clinical information of patients with RA and LUAD from GEO and TCGA datasets. We performed differential analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to discover the shared genes between RA and LUAD. Then, COX regression and LASSO analysis were employed to figure out genes significantly associated with survival. qRT-PCR and Western blot were utilized to validate the expression level of candidate genes. For clinical application, we constructed a nomogram, and also explored the value of RALUADS in characterizing immune infiltration features by CIBERSORT and xCell. Finally, responses to different drug therapy were predicted according to different RALUADS. Results: Our analysis identified two gene sets from differentially expressed genes and WGCNA gene modules of RA and LUAD. Filtered by survival analysis, three most significant shared genes were selected, CCN6, CDCA4 and ERLIN1, which were all upregulated in tumors and associated with poor prognosis. The three genes constituted RA and LUAD score (RALUADS). Our results demonstrated that RALUADS was higher in tumor patients and predicted poor prognosis in LUAD patients. Clinical nomogram combining RALUADS and other clinicopathological parameters had superior performance in survival prediction (AUC = 0.722). We further explored tumor immune microenvironment (TME) affected by RALUADS and observed RALUADS was closely related to the sensitivity of multiple immune blockades, chemotherapy and targeted drugs. Conclusion: Our findings suggest that there are shared physiopathologic processes and molecular profiles between RA and LUAD. RALUADS represents an excellent prognosis predictor and immune-related biomarker, which can be applied to select potential effective drugs and for LUAD patients with RA.

Quantitative Proteomics of Tissue-Infiltrating T Cells From CRC Patients Identified Lipocalin-2 Induces T-Cell Apoptosis and Promotes Tumor Cell Proliferation by Iron Efflux

T cells play the most pivotal roles in antitumor immunity; the T-cell proteome and the differentially expressed proteins in the tumor immune microenvironment have rarely been identified directly from the clinical samples, especially for tumors that lack effective immunotherapy targets, such as colorectal cancer (CRC). In this study, we analyzed the protein expression pattern of the infiltrating T cells isolated from CRC patients using quantitative proteomics. CD4+ and CD8+ T cells were isolated from clinical samples and labeled by tandem mass tag reagents, and the differentially expressed proteins were quantified by mass spectrometry. The T-cell proteome profiling revealed dysfunctions in these tumor-infiltrating T cells. Specifically, antitumor immunity was suppressed because of differentially expressed metal ion transporters and immunity regulators. For the first time, lipocalin-2 (LCN2) was shown to be significantly upregulated in CD4+ T cells. Quantitative proteomic analysis of LCN2-overexpressed Jurkat cells showed that LCN2 damaged T cells by changes in iron transport. LCN2 induced T-cell apoptosis by reducing cellular iron concentration; moreover, the iron that was transported to the tumor microenvironment aided tumor cell proliferation, promoting tumor development. Meanwhile, LCN2 also influenced tumor progression through immune cytokines and cholesterol metabolism. Our results demonstrated that LCN2 has immunosuppressive functions that can promote tumor development; therefore, it is a potential immunotherapy target for CRC.

Epithelial to mesenchymal transition (EMT) in metaplastic breast cancer and phyllodes breast tumors

Epithelial-mesenchymal transition (EMT), a transdifferentiation program whereby epithelial cells acquire mesenchymal phenotype, is essential during embryonic development. EMT has also been implicated in cancer progression by conferring migratory and metastatic potential, as well as cell plasticity and stem cell like traits, to cancer cells. Metaplastic breast carcinoma (MBC) is a rare aggressive type of breast cancer characterized by the presence of heterologous elements, typically by the existence of epithelial and mesenchymal components. Phyllodes tumors (PTs) are uncommon fibroepithelial neoplasms consisting of epithelial and mesenchymal elements. Although various hypotheses have been proposed on the pathogenesis of these biphasic tumors, there is growing evidence supporting the theory that PTs and MBC could both correlate with cancer related EMT. This review summarizes the existing literature on the emerging role of EMT in the pathogenesis of MBC and PTs. Both malignant PTs and MBC are characterized by poor prognosis. Therefore, several anti-EMT targeting strategies such as blocking upstream signaling pathways, targeting the molecular drivers of EMT and targeting mesenchymal cells and the extracellular matrix, could potentially represent a promising therapeutic approach for patients suffering from these aggressive neoplasms.

Proteomics protocol for obtaining extracellular vesicle from human plasma using asymmetrical flow field-flow fractionation technology

Plasma extracellular vesicles (EVs) represent a potential resource for biomarkers of multiple diseases. Here, we present a protocol for obtaining EVs from human plasma using asymmetrical flow field-flow fractionation technology. We describe steps for using tandem mass tags to perform comparative proteomic studies of a large clinical cohort. We then detail targeted quantitative analysis of differential proteins based on a parallel reaction monitoring technique. For complete details on the use and execution of this protocol, please refer to Wu et al. (2020)1 and Li et al. (2023).2.

Identification of LMAN1- and SURF4-Dependent Secretory Cargoes

Most proteins secreted into the extracellular space are first recruited from the endoplasmic reticulum into coat protein complex II (COPII)-coated vesicles or tubules that facilitate their transport to the Golgi apparatus. Although several secreted proteins have been shown to be actively recruited into COPII vesicles and tubules by the cargo receptors LMAN1 and SURF4, the full cargo repertoire of these receptors is unknown. We now report mass spectrometry analysis of conditioned media and cell lysates from HuH7 cells CRISPR targeted to inactivate the LMAN1 or SURF4 gene. We found that LMAN1 has limited clients in HuH7 cells, whereas SURF4 traffics a broad range of cargoes. Analysis of putative SURF4 cargoes suggests that cargo recognition is governed by complex mechanisms rather than interaction with a universal binding motif..

Proteomic and Phosphoproteomic Reprogramming in Epithelial Ovarian Cancer Metastasis

Epithelial ovarian cancer (EOC) is a high-risk cancer presenting with heterogeneous tumors. The high incidence of EOC metastasis from primary tumors to nearby tissues and organs is a major driver of EOC lethality. We used cellular models of spheroid formation and readherence to investigate cellular signaling dynamics in each step toward EOC metastasis. In our system, adherent cells model primary tumors, spheroid formation represents the initiation of metastatic spread, and readherent spheroid cells represent secondary tumors. Proteomic and phosphoproteomic analyses show that spheroid cells are hypoxic and show markers for cell cycle arrest. Aurora kinase B abundance and downstream substrate phosphorylation are significantly reduced in spheroids and readherent cells, explaining their cell cycle arrest phenotype. The proteome of readherent cells is most similar to spheroids, yet greater changes in the phosphoproteome show that spheroid cells stimulate Rho-associated kinase 1 (ROCK1)-mediated signaling, which controls cytoskeletal organization. In spheroids, we found significant phosphorylation of ROCK1 substrates that were reduced in both adherent and readherent cells. Application of the ROCK1-specific inhibitor Y-27632 to spheroids increased the rate of readherence and altered spheroid density. The data suggest ROCK1 inhibition increases EOC metastatic potential. We identified novel pathways controlled by Aurora kinase B and ROCK1 as major drivers of metastatic behavior in EOC cells. Our data show that phosphoproteomic reprogramming precedes proteomic changes that characterize spheroid readherence in EOC metastasis.

A hybrid breast cancer/mesenchymal stem cell population enhances chemoresistance and metastasis

Patients with triple-negative breast cancer remain at risk for metastatic disease despite treatment. The acquisition of chemoresistance is a major cause of tumor relapse and death, but the mechanisms are far from understood. We have demonstrated that breast cancer cells (BCCs) can engulf mesenchymal stem/stromal cells (MSCs), leading to enhanced dissemination. Here, we show that clinical samples of primary invasive carcinoma and chemoresistant breast cancer metastasis contain a unique hybrid cancer cell population coexpressing pancytokeratin and the MSC marker fibroblast activation protein-α. We show that hybrid cells form in primary tumors and that they promote breast cancer metastasis and chemoresistance. Using single-cell microfluidics and in vivo models, we found that there are polyploid senescent cells within the hybrid cell population that contribute to metastatic dissemination. Our data reveal that Wnt Family Member 5A (WNT5A) plays a crucial role in supporting the chemoresistance properties of hybrid cells. Furthermore, we identified that WNT5A mediates hybrid cell formation through a phagocytosis-like mechanism that requires BCC-derived IL-6 and MSC-derived C-C Motif Chemokine Ligand 2. These findings reveal hybrid cell formation as a mechanism of chemoresistance and suggest that interrupting this mechanism may be a strategy in overcoming breast cancer drug resistance.

A proteogenomics data-driven knowledge base of human cancer

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.

Stromal heterogeneity may explain increased incidence of metaplastic breast cancer in women of African descent

The biologic basis of genetic ancestry-dependent variability in disease incidence and outcome is just beginning to be explored. We recently reported enrichment of a population of ZEB1-expressing cells located adjacent to ductal epithelial cells in normal breasts of women of African ancestry compared to those of European ancestry. In this study, we demonstrate that these cells have properties of fibroadipogenic/mesenchymal stromal cells that express PROCR and PDGFRα and transdifferentiate into adipogenic and osteogenic lineages. PROCR + /ZEB1 + /PDGFRα+ (PZP) cells are enriched in normal breast tissues of women of African compared to European ancestry. PZP: epithelial cell communication results in luminal epithelial cells acquiring basal cell characteristics and IL-6-dependent increase in STAT3 phosphorylation. Furthermore, level of phospho-STAT3 is higher in normal and cancerous breast tissues of women of African ancestry. PZP cells transformed with HRasG12V ± SV40-T/t antigens generate metaplastic carcinoma suggesting that these cells are one of the cells-of-origin of metaplastic breast cancers.

Integrative multi-omic cancer profiling reveals DNA methylation patterns associated with therapeutic vulnerability and cell-of-origin

DNA methylation plays a critical role in establishing and maintaining cellular identity. However, it is frequently dysregulated during tumor development and is closely intertwined with other genetic alterations. Here, we leveraged multi-omic profiling of 687 tumors and matched non-involved adjacent tissues from the kidney, brain, pancreas, lung, head and neck, and endometrium to identify aberrant methylation associated with RNA and protein abundance changes and build a Pan-Cancer catalog. We uncovered lineage-specific epigenetic drivers including hypomethylated FGFR2 in endometrial cancer. We showed that hypermethylated STAT5A is associated with pervasive regulon downregulation and immune cell depletion, suggesting that epigenetic regulation of STAT5A expression constitutes a molecular switch for immunosuppression in squamous tumors. We further demonstrated that methylation subtype-enrichment information can explain cell-of-origin, intra-tumor heterogeneity, and tumor phenotypes. Overall, we identified cis-acting DNA methylation events that drive transcriptional and translational changes, shedding light on the tumor's epigenetic landscape and the role of its cell-of-origin.

Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling

Repeated measures experimental designs, which quantify proteins in biological subjects repeatedly over multiple experimental conditions or times, are commonly used in mass spectrometry-based proteomics. Such designs distinguish the biological variation within and between the subjects and increase the statistical power of detecting within-subject changes in protein abundance. Meanwhile, proteomics experiments increasingly incorporate tandem mass tag (TMT) labeling, a multiplexing strategy that gains both relative protein quantification accuracy and sample throughput. However, combining repeated measures and TMT multiplexing in a large-scale investigation presents statistical challenges due to unique interplays of between-mixture, within-mixture, between-subject, and within-subject variation. This manuscript proposes a family of linear mixed-effects models for differential analysis of proteomics experiments with repeated measures and TMT multiplexing. These models decompose the variation in the data into the contributions from its sources as appropriate for the specifics of each experiment, enable statistical inference of differential protein abundance, and recognize a difference in the uncertainty of between-subject versus within-subject comparisons. The proposed family of models is implemented in the R/Bioconductor package MSstatsTMT v2.2.0. Evaluations of four simulated datasets and four investigations answering diverse biological questions demonstrated the value of this approach as compared to the existing general-purpose approaches and implementations.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Nuclear lamina erosion-induced resurrection of endogenous retroviruses underlies neuronal aging

The primate frontal lobe (FL) is sensitive to aging-related neurocognitive decline. However, the aging-associated molecular mechanisms remain unclear. Here, using physiologically aged non-human primates (NHPs), we depicted a comprehensive landscape of FL aging with multidimensional profiling encompassing bulk and single-nucleus transcriptomes, quantitative proteome, and DNA methylome. Conjoint analysis across these molecular and neuropathological layers underscores nuclear lamina and heterochromatin erosion, resurrection of endogenous retroviruses (ERVs), activated pro-inflammatory cyclic GMP-AMP synthase (cGAS) signaling, and cellular senescence in post-mitotic neurons of aged NHP and human FL. Using human embryonic stem-cell-derived neurons recapitulating cellular aging in vitro, we verified the loss of B-type lamins inducing resurrection of ERVs as an initiating event of the aging-bound cascade in post-mitotic neurons. Of significance, these aging-related cellular and molecular changes can be alleviated by abacavir, a nucleoside reverse transcriptase inhibitor, either through direct treatment of senescent human neurons in vitro or oral administration to aged mice.

Metaplastic Carcinoma of the Breast: Case Series of a Single Institute and Review of the Literature

Metaplastic carcinoma of the breast (MpBC) is a very rare and aggressive type of breast cancer. Data focusing on MpBC are limited. The aim of this study was to describe the clinicopathological features of MpBC and evaluate the prognosis of patients with MpBC. Eligible articles about MpBC were identified by searching CASES SERIES gov and the MEDLINE bibliographic database for the period of 1 January 2010 to 1 June 2021 with the keywords metaplastic breast cancer, mammary gland cancer, neoplasm, tumor, and metaplastic carcinoma. In this study, we also report 46 cases of MpBC stemming from our hospital. Survival rates, clinical behavior, and pathological characteristics were analyzed. Data from 205 patients were included for analysis. The mean age at diagnosis was 55 (14.7) years. The TNM stage at diagnosis was mostly stage II (58.5%) and most tumors were triple negative. The median overall survival was 66 (12-118) months, and the median disease-free survival was 56.8 (11-102) months. Multivariate Cox regression analysis revealed that surgical treatment was associated with decreased risk of death (hazard ratio 0.11, 95% confidence interval 0.02-0.54, p = 0.01) while advanced TNM stage was associated with increased risk of death (hazard ratio 1.5, 95% confidence interval 1.04-2.28, p = 0.03). Our results revealed that surgical treatment and TNM stage were the only independent risk factors related to patients' overall survival.

CCN proteins: opportunities for clinical studies-a personal perspective

The diverse members of the CCN family now designated as CCN1(CYR61), CCN2 (CTGF), CCN3(NOV), CCN4(WISP1), CCN5(WISP2), CCN6(WISP3) are a conserved matricellular family of proteins exhibiting a spectrum of functional properties throughout all organs in the body. Interaction with cell membrane receptors such as integrins trigger intracellular signaling pathways. Proteolytically cleaved fragments (constituting the active domains) can be transported to the nucleus and perform transcriptional relevant functional activities. Notably, as also found in other protein families some members act opposite to others creating a system of functionally relevant checks and balances. It has become apparent that these proteins are secreted into the circulation, are quantifiable, and can serve as disease biomarkers. How they might also serve as homeostatic regulators is just becoming appreciated. In this review I have attempted to highlight the most recent evidence under the subcategories of cancer and non-cancer relevant that could lead to potential therapeutic approaches or ideas that can be factored into clinical advances. I have added my own personal perspective on feasibility.

Identification of LMAN1 and SURF4 dependent secretory cargoes

Most proteins secreted into the extracellular space are first recruited from the endoplasmic reticulum into coat protein complex II (COPII)-coated vesicles or tubules that facilitate their transport to the Golgi apparatus. Although several secreted proteins have been shown to be actively recruited into COPII vesicles/tubules by the cargo receptors LMAN1 and SURF4, the full cargo repertoire of these receptors is unknown. We now report mass spectrometry analysis of conditioned media and cell lysates from HuH7 cells CRISPR targeted to inactivate the LMAN1 or SURF4 gene. We found that LMAN1 has limited clients in HuH7 cells whereas SURF4 traffics a broad range of cargoes. Analysis of putative SURF4 cargoes suggests that cargo recognition is governed by complex mechanisms rather than interaction with a universal binding motif.

Metaplastic breast cancer: A review

Metaplastic breast cancer (MpBC) is an uncommon aggressive malignancy that is associated with a poor prognosis. Due to its rarity, the relationships between the clinical and pathological features of MpBC, treatment approach, and clinical outcomes remain underexplored. In the following review article, we synthesize the existing data on the clinical, pathological and genomic features, management, and outcomes of MpBC. We also identify potential targets for future clinical trials.

Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics

There is a growing demand to develop high-throughput and high-sensitivity mass spectrometry methods for single-cell proteomics. The commonly used isobaric labeling-based multiplexed single-cell proteomics approach suffers from distorted protein quantification due to co-isolated interfering ions during MS/MS fragmentation, also known as ratio compression. We reasoned that the use of MS3-based quantification could mitigate ratio compression and provide better quantification. However, previous studies indicated reduced proteome coverages in the MS3 method, likely due to long duty cycle time and ion losses during multilevel ion selection and fragmentation. Herein, we described an improved MS acquisition method for MS3-based single-cell proteomics by employing a linear ion trap to measure reporter ions. We demonstrated that linear ion trap can increase the proteome coverages for single-cell-level peptides with even higher gain obtained via the MS3 method. The optimized real-time search MS3 method was further applied to study the immune activation of single macrophages. Among a total of 126 single cells studied, over 1200 and 1000 proteins were quantifiable when at least 50 and 75% nonmissing data were required, respectively. Our evaluation also revealed several limitations of the low-resolution ion trap detector for multiplexed single-cell proteomics and suggested experimental solutions to minimize their impacts on single-cell analysis.

Transcriptomic alterations underlying metaplasia into specific metaplastic components in metaplastic breast carcinoma

BACKGROUND

Metaplastic breast carcinoma (MpBC) typically consists of carcinoma of no special type (NST) with various metaplastic components. Although previous transcriptomic and proteomic studies have reported subtype-related heterogeneity, the intracase transcriptomic alterations between metaplastic components and paired NST components, which are critical for understanding the pathogenesis underlying the metaplastic processes, remain unclear.

METHODS

Fifty-nine NST components and paired metaplastic components (spindle carcinomatous [SPS], matrix-producing, rhabdoid [RHA], and squamous carcinomatous [SQC] components) were microdissected from specimens obtained from 27 patients with MpBC for gene expression profiling using the NanoString Breast Cancer 360 Panel on a NanoString nCounter FLEX platform. BC360-defined signatures were scored using nSolver software.

RESULTS

Hierarchical clustering and principal component analysis revealed a heterogeneous gene expression profile (GEP) corresponding to the NST components, but the GEP of metaplastic components exhibited subtype dependence. Compared with the paired NST components, the SPS components demonstrated the upregulation of genes related to stem cells and epithelial-mesenchymal transition and displayed enrichment in claudin-low and macrophage signatures. Despite certain overlaps in the enriched functions and signatures between the RHA and SPS components, the specific differentially expressed genes differed. We observed the RHA-specific upregulation of genes associated with vascular endothelial growth factor signaling. The chondroid matrix-producing components demonstrated the upregulation of hypoxia-related genes and the downregulation of the immune-related MHC2 signature and the TIGIT gene. In the SQC components, TGF-β and genes associated with cell adhesion were upregulated. The differentially expressed genes among metaplastic components in the 22 MpBC cases with one or predominantly one metaplastic component clustered paired NST samples into clusters with correlation with their associated metaplastic types. These genes could be used to separate the 31 metaplastic components according to respective metaplastic types with an accuracy of 74.2%, suggesting that intrinsic signatures of NST may determine paired metaplastic type. Finally, the EMT activity and stem cell traits in the NST components were correlated with specimens displaying lymph node metastasis.

CONCLUSIONS

We presented the distinct transcriptomic alterations underlying metaplasia into specific metaplastic components in MpBCs, which contributes to the understanding of the pathogenesis underlying morphologically distinct metaplasia in MpBCs.

Identifying Associations between DCE-MRI Radiomic Features and Expression Heterogeneity of Hallmark Pathways in Breast Cancer: A Multi-Center Radiogenomic Study

BACKGROUND

To investigate the relationship between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic features and the expression activity of hallmark pathways and to develop prediction models of pathway-level heterogeneity for breast cancer (BC) patients.

METHODS

Two radiogenomic cohorts were analyzed (n = 246). Tumor regions were segmented semiautomatically, and 174 imaging features were extracted. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to identify significant imaging-pathway associations. Random forest regression was used to predict pathway enrichment scores. Five-fold cross-validation and grid search were used to determine the optimal preprocessing operation and hyperparameters.

RESULTS

We identified 43 pathways, and 101 radiomic features were significantly related in the discovery cohort (p-value < 0.05). The imaging features of the tumor shape and mid-to-late post-contrast stages showed more transcriptional connections. Ten pathways relevant to functions such as cell cycle showed a high correlation with imaging in both cohorts. The prediction model for the mTORC1 signaling pathway achieved the best performance with the mean absolute errors (MAEs) of 27.29 and 28.61% in internal and external test sets, respectively.

CONCLUSIONS

The DCE-MRI features were associated with hallmark activities and may improve individualized medicine for BC by noninvasively predicting pathway-level heterogeneity.

Comparative Evaluation of Proteome Discoverer and FragPipe for the TMT-Based Proteome Quantification

Isobaric labeling-based proteomics is widely applied in deep proteome quantification. Among the platforms for isobaric labeled proteomic data analysis, the commercial software Proteome Discoverer (PD) is widely used, incorporating the search engine CHIMERYS, while FragPipe (FP) is relatively new, free for noncommercial purposes, and integrates the engine MSFragger. Here, we compared PD and FP over three public proteomic data sets labeled using 6plex, 10plex, and 16plex tandem mass tags. Our results showed the protein abundances generated by the two software are highly correlated. PD quantified more proteins (10.02%, 15.44%, 8.19%) than FP with comparable NA ratios (0.00% vs. 0.00%, 0.85% vs. 0.38%, and 11.74% vs. 10.52%) in the three data sets. Using the 16plex data set, PD and FP outputs showed high consistency in quantifying technical replicates, batch effects, and functional enrichment in differentially expressed proteins. However, FP saved 93.93%, 96.65%, and 96.41% of processing time compared to PD for analyzing the three data sets, respectively. In conclusion, while PD is a well-maintained commercial software integrating various additional functions and can quantify more proteins, FP is freely available and achieves similar output with a shorter computational time. Our results will guide users in choosing the most suitable quantification software for their needs.

Investigating pathological epigenetic aberrations by epi-proteomics

Epigenetics includes a complex set of processes that alter gene activity without modifying the DNA sequence, which ultimately determines how the genetic information common to all the cells of an organism is used to generate different cell types. Dysregulation in the deposition and maintenance of epigenetic features, which include histone posttranslational modifications (PTMs) and histone variants, can result in the inappropriate expression or silencing of genes, often leading to diseased states, including cancer. The investigation of histone PTMs and variants in the context of clinical samples has highlighted their importance as biomarkers for patient stratification and as key players in aberrant epigenetic mechanisms potentially targetable for therapy. Mass spectrometry (MS) has emerged as the most powerful and versatile tool for the comprehensive, unbiased and quantitative analysis of histone proteoforms. In recent years, these approaches-which we refer to as "epi-proteomics"-have demonstrated their usefulness for the investigation of epigenetic mechanisms in pathological conditions, offering a number of advantages compared with the antibody-based methods traditionally used to profile clinical samples. In this review article, we will provide a critical overview of the MS-based approaches that can be employed to study histone PTMs and variants in clinical samples, with a strong focus on the latest advances in this area, such as the analysis of uncommon modifications and the integration of epi-proteomics data into multi-OMICs approaches, as well as the challenges to be addressed to fully exploit the potential of this novel field of research.

Integrative analysis of KRAS wildtype metastatic pancreatic ductal adenocarcinoma reveals mutation and expression-based similarities to cholangiocarcinoma

Oncogenic KRAS mutations are absent in approximately 10% of patients with metastatic pancreatic ductal adenocarcinoma (mPDAC) and may represent a subgroup of mPDAC with therapeutic options beyond standard-of-care cytotoxic chemotherapy. While distinct gene fusions have been implicated in KRAS wildtype mPDAC, information regarding other types of mutations remain limited, and gene expression patterns associated with KRAS wildtype mPDAC have not been reported. Here, we leverage sequencing data from the PanGen trial to perform comprehensive characterization of the molecular landscape of KRAS wildtype mPDAC and reveal increased frequency of chr1q amplification encompassing transcription factors PROX1 and NR5A2. By leveraging data from colorectal adenocarcinoma and cholangiocarcinoma samples, we highlight similarities between cholangiocarcinoma and KRAS wildtype mPDAC involving both mutation and expression-based signatures and validate these findings using an independent dataset. These data further establish KRAS wildtype mPDAC as a unique molecular entity, with therapeutic opportunities extending beyond gene fusion events.

KRAS wildtype metastatic pancreatic ductal adenocarcinoma (mPDAC) could represent a distinct molecular entity from other PDACs. Here, the authors analyse KRAS wildtype mPDAC tumours using genomics and transcriptomics and find molecular similarities with cholangiocarcinomas.

Nanomaterial-assisted CRISPR gene-engineering - A hallmark for triple-negative breast cancer therapeutics advancement

Triple-negative breast cancer (TNBC) is the most violent class of tumor and accounts for 20–24% of total breast carcinoma, in which frequently rare mutation occurs in high frequency. The poor prognosis, recurrence, and metastasis in the brain, heart, liver and lungs decline the lifespan of patients by about 21 months, emphasizing the need for advanced treatment. Recently, the adaptive immunity mechanism of archaea and bacteria, called clustered regularly interspaced short palindromic repeats (CRISPR) combined with nanotechnology, has been utilized as a potent gene manipulating tool with an extensive clinical application in cancer genomics due to its easeful usage and cost-effectiveness. However, CRISPR/Cas are arguably the efficient technology that can be made efficient via organic material-assisted approaches. Despite the efficacy of the CRISPR/Cas@nano complex, problems regarding successful delivery, biodegradability, and toxicity remain to render its medical implications. Therefore, this review is different in focus from past reviews by (i) detailing all possible genetic mechanisms of TNBC occurrence; (ii) available treatments and gene therapies for TNBC; (iii) overview of the delivery system and utilization of CRISPR-nano complex in TNBC, and (iv) recent advances and related toxicity of CRISPR-nano complex towards clinical trials for TNBC.

Systematic molecular profiling of acute leukemia cancer stem cells allows identification of druggable targets

Acute myeloid leukemia (AML) is one of the most prevalent and acute blood cancers with a poor prognosis and low overall survival rate, especially in the elderly. Although several new AML markers and drug targets have been recently identified, the rate of long-term cancer eradication has not improved significantly due to the presence and drug resistance of AML cancer stem cells (CSCs). Here we develop a novel computational pipeline to analyze the transcriptomic profiles of AML cancer (stem) cells and identify novel candidate AML CSC markers and drug targets. In our novel pipeline we apply a top-down meta-analysis strategy to integrate The Cancer Genome Atlas data with CSC datasets to infer cell stemness features. As a result, a set of genes termed the "AML key CSC genes" along with all the available drugs/compounds that could target them were identified. Overall, our novel computational pipeline could retrieve known cancer drugs (Carfilzomib) and predicted novel drugs such as Zonisamide, Amitriptyline, and their targets amongst the top ranked drugs and drug targets for targeting AML. Additionally, the pipeline applied in this study could be used for the identification of CSC-specific markers, drivers and their respective targeting drugs in other cancer types.

Proteogenomic analysis of cancer aneuploidy and normal tissues reveals divergent modes of gene regulation across cellular pathways

How cells control gene expression is a fundamental question. The relative contribution of protein-level and RNA-level regulation to this process remains unclear. Here, we perform a proteogenomic analysis of tumors and untransformed cells containing somatic copy number alterations (SCNAs). By revealing how cells regulate RNA and protein abundances of genes with SCNAs, we provide insights into the rules of gene regulation. Protein complex genes have a strong protein-level regulation while non-complex genes have a strong RNA-level regulation. Notable exceptions are plasma membrane protein complex genes, which show a weak protein-level regulation and a stronger RNA-level regulation. Strikingly, we find a strong negative association between the degree of RNA-level and protein-level regulation across genes and cellular pathways. Moreover, genes participating in the same pathway show a similar degree of RNA- and protein-level regulation. Pathways including translation, splicing, RNA processing, and mitochondrial function show a stronger protein-level regulation while cell adhesion and migration pathways show a stronger RNA-level regulation. These results suggest that the evolution of gene regulation is shaped by functional constraints and that many cellular pathways tend to evolve one predominant mechanism of gene regulation at the protein level or at the RNA level.

Nomogram for the prediction of triple-negative breast cancer histological heterogeneity based on multiparameter MRI features: A preliminary study including metaplastic carcinoma and non- metaplastic carcinoma

Objectives

Triple-negative breast cancer (TNBC) is a heterogeneous disease, and different histological subtypes of TNBC have different clinicopathological features and prognoses. Therefore, this study aimed to establish a nomogram model to predict the histological heterogeneity of TNBC: including Metaplastic Carcinoma (MC) and Non-Metaplastic Carcinoma (NMC).

Methods

We evaluated 117 patients who had pathologically confirmed TNBC between November 2016 and December 2020 and collected preoperative multiparameter MRI and clinicopathological data. The patients were randomly assigned to a training set and a validation set at a ratio of 3:1. Based on logistic regression analysis, we established a nomogram model to predict the histopathological subtype of TNBC. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve. According to the follow-up information, disease-free survival (DFS) survival curve was estimated using the Kaplan-Meier product-limit method.

Results

Of the 117 TNBC patients, 29 patients had TNBC-MC (age range, 29–65 years; median age, 48.0 years), and 88 had TNBC-NMC (age range, 28–88 years; median age, 44.5 years). Multivariate logistic regression analysis demonstrated that lesion type (p = 0.001) and internal enhancement pattern (p = 0.001) were significantly predictive of TNBC subtypes in the training set. The nomogram incorporating these variables showed excellent discrimination power with an AUC of 0.849 (95% CI: 0.750−0.949) in the training set and 0.819 (95% CI: 0.693−0.946) in the validation set. Up to the cutoff date for this analysis, a total of 66 patients were enrolled in the prognostic analysis. Six of 14 TNBC-MC patients experienced recurrence, while 7 of 52 TNBC-NMC patients experienced recurrence. The DFS of the two subtypes was significantly different (p=0.035).

Conclusions

In conclusion, we developed a nomogram consisting of lesion type and internal enhancement pattern, which showed good discrimination ability in predicting TNBC-MC and TNBC-NMC.

EZH2 T367 phosphorylation activates p38 signaling through lysine methylation to promote breast cancer progression

Triple-negative breast cancers (TNBCs) are frequently poorly differentiated with high propensity for metastasis. Enhancer of zeste homolog 2 (EZH2) is the lysine methyltransferase of polycomb repressive complex 2 that mediates transcriptional repression in normal cells and in cancer through H3K27me3. However, H3K27me3-independent non-canonical functions of EZH2 are incompletely understood. We reported that EZH2 phosphorylation at T367 by p38α induces TNBC metastasis in an H3K27me3-independent manner. Here, we show that cytosolic EZH2 methylates p38α at lysine 139 and 165 leading to enhanced p38α stability and that p38 methylation and activation require T367 phosphorylation of EZH2. Dual inhibition of EZH2 methyltransferase and p38 kinase activities downregulates pEZH2-T367, H3K27me3, and p-p38 pathways in vivo and reduces TNBC growth and metastasis. These data uncover a cooperation between EZH2 canonical and non-canonical mechanisms and suggest that inhibition of these pathways may be a potential therapeutic strategy.

Identification of secreted proteins by comparison of protein abundance in conditioned media and cell lysates

Analysis of the full spectrum of secreted proteins in cell culture is complicated by leakage of intracellular proteins from damaged cells. To address this issue, we compared the abundance of individual proteins between the cell lysate and the conditioned medium, reasoning that secreted proteins should be relatively more abundant in the conditioned medium. Marked enrichment for signal-peptide-bearing proteins with increasing conditioned media to cell lysate ratio, as well loss of this signal following brefeldin A treatment, confirmed the sensitivity and specificity of this approach. The subset of proteins demonstrating increased conditioned media to cell lysate ratio in the presence of Brefeldin A identified candidates for unconventional secretion via a pathway independent of ER to Golgi trafficking.

Oxidative stress differentially impacts apical and basolateral secretion of angiogenic factors from human iPSC-derived retinal pigment epithelium cells

The retinal pigment epithelium (RPE) is a polarized monolayer that secretes growth factors and cytokines towards the retina apically and the choroid basolaterally. Numerous RPE secreted proteins have been linked to the pathogenesis of age-related macular degeneration (AMD). The purpose of this study was to determine the differential apical and basolateral secretome of RPE cells, and the effects of oxidative stress on directional secretion of proteins linked to AMD and angiogenesis. Tandem mass tag spectrometry was used to profile proteins in human iPSC-RPE apical and basolateral conditioned media. Changes in secretion after oxidative stress induced by H2O2 or tert-butyl hydroperoxide (tBH) were investigated by ELISA and western analysis. Out of 926 differentially secreted proteins, 890 (96%) were more apical. Oxidative stress altered the secretion of multiple factors implicated in AMD and neovascularization and promoted a pro-angiogenic microenvironment by increasing the secretion of pro-angiogenic molecules (VEGF, PTN, and CRYAB) and decreasing the secretion of anti-angiogenic molecules (PEDF and CFH). Apical secretion was impacted more than basolateral for PEDF, CRYAB and CFH, while basolateral secretion was impacted more for VEGF, which may have implications for choroidal neovascularization. This study lays a foundation for investigations of dysfunctional RPE polarized protein secretion in AMD and other chorioretinal degenerative disorders.

Monitoring Protein Import into the Endoplasmic Reticulum in Living Cells with Proximity Labeling

The proper trafficking of eukaryotic proteins is essential to cellular function. Genetic, environmental, and other stresses can induce protein mistargeting and, in turn, threaten cellular protein homeostasis. Current methods for measuring protein mistargeting are difficult to translate to living cells, and thus the role of cellular signaling networks in stress-dependent protein mistargeting processes, such as ER pre-emptive quality control (ER pQC), is difficult to parse. Herein, we use genetically encoded peroxidases to characterize protein import into the endoplasmic reticulum (ER). We show that the ^ERHRP/^cytAPEX pair provides good selectivity and sensitivity for both multiplexed protein labeling and for identifying protein mistargeting, using the known ER pQC substrate transthyretin (TTR). Although ^ERHRP labeling induces formation of detergent-resistant TTR aggregates, this is minimized by using low ^ERHRP expression, without loss of labeling efficiency. ^cytAPEX labeling recovers TTR that is mistargeted as a consequence of Sec61 inhibition or ER stress-induced ER pQC. Furthermore, we discover that stress-free activation of the ER stress-associated transcription factor ATF6 recapitulates the TTR import deficiency of ER pQC. Hence, proximity labeling is an effective strategy for characterizing factors that influence ER protein import in living cells.

Molecular Characterization and Prospective Evaluation of Pathologic Response and Outcomes with Neoadjuvant Therapy in Metaplastic Triple-Negative Breast Cancer

PURPOSE

Metaplastic breast cancer (MpBC) is a rare subtype of breast cancer that is commonly triple-negative and poorly responsive to neoadjuvant therapy in retrospective studies.

EXPERIMENTAL DESIGN

To better define clinical outcomes and correlates of response, we analyzed the rate of pathologic complete response (pCR) to neoadjuvant therapy, survival outcomes, and genomic and transcriptomic profiles of the pretreatment tumors in a prospective clinical trial (NCT02276443). A total of 211 patients with triple-negative breast cancer (TNBC), including 39 with MpBC, received doxorubicin-cyclophosphamide-based neoadjuvant therapy.

RESULTS

Although not meeting the threshold for statistical significance, patients with MpBCs were less likely to experience a pCR (23% vs. 40%; P = 0.07), had shorter event-free survival (29.4 vs. 32.2 months, P = 0.15), metastasis-free survival (30.3 vs. 32.4 months, P = 0.22); and overall survival (32.6 vs. 34.3 months, P = 0.21). This heterogeneity is mirrored in the molecular profiling. Mutations in PI3KCA (23% vs. 9%, P = 0.07) and its pathway (41% vs. 18%, P = 0.02) were frequently observed and enriched in MpBCs. The gene expression profiles of each histologically defined subtype were distinguishable and characterized by distinctive gene signatures. Among nonmetaplastic (non-Mp) TNBCs, 10% possessed a metaplastic-like gene expression signature and had pCR rates and survival outcomes similar to MpBC.

CONCLUSIONS

Further investigations will determine if metaplastic-like tumors should be treated more similarly to MpBC in the clinic. The 23% pCR rate in this study suggests that patients with MpBC should be considered for NAT. To improve this rate, a pathway analysis predicted enrichment of histone deacetylase (HDAC) and RTK/MAPK pathways in MpBC, which may serve as new targetable vulnerabilities.

Presentation and treatment of aggressive, Triple‐Negative carcinosarcoma of the breast

An extremely rare form of breast cancer, breast carcinosarcoma accounts for less than a percent of all breast malignancies and is highly aggressive. Composed of both cancerous epithelial and mesenchymal cell types, breast carcinosarcoma is associated with a poor prognosis compared to more common breast cancers, and typically lack the receptors typical of other breast carcinomas, which minimize potential targets for treatment. In this case report, we discuss a 56‐year‐old patient affected by carcinosarcoma of the breast at a T2N1 stage, and the decision‐making process that factored into her treatment plan.

Correlation Between Plasma Proteomics and Adverse Outcomes Among Older Men With Chronic Coronary Syndrome

Background

Chronic coronary syndrome (CCS) is a newly proposed concept and is hallmarked by more long-term major adverse cardiovascular events (MACEs), calling for accurate prognostic biomarkers for initial risk stratification.

Methods

Data-independent acquisition liquid chromatography tandem mass spectrometry (DIA LC-MS/MS) quantitative proteomics was performed on 38 patients with CCS; 19 in the CCS events group and 19 in the non-events group as the controls. We also developed a machine-learning-based pipeline to identify proteins as potential biomarkers and validated the target proteins by enzyme-linked immunosorbent assay in an independent prospective cohort.

Results

Fifty-seven differentially expressed proteins were identified by quantitative proteomics and three final biomarkers were preliminarily selected from the machine-learning-based pipeline. Further validation with the prospective cohort showed that endothelial protein C receptor (EPCR) and cholesteryl ester transfer protein (CETP) levels at admission were significantly higher in the CCS events group than they were in the non-events group, whereas the carboxypeptidase B2 (CPB2) level was similar in the two groups. In the Cox survival analysis, EPCR and CETP were independent risk factors for MACEs. We constructed a new prognostic model by combining the Framingham coronary heart disease (CHD) risk model with EPCR and CETP levels. This new model significantly improved the C-statistics for MACE prediction compared with that of the Framingham CHD risk model alone.

Conclusion

Plasma proteomics was used to find biomarkers of predicting MACEs in patients with CCS. EPCR and CETP were identified as promising prognostic biomarkers for CCS.

Multiomic characterization of pancreatic cancer-associated macrophage polarization reveals deregulated metabolic programs driven by the GM-CSF-PI3K pathway

The pancreatic ductal adenocarcinoma microenvironment is composed of a variety of cell types and marked by extensive fibrosis and inflammation. Tumor-associated macrophages (TAMs) are abundant, and they are important mediators of disease progression and invasion. TAMs are polarized in situ to a tumor promoting and immunosuppressive phenotype via cytokine signaling and metabolic crosstalk from malignant epithelial cells and other components of the tumor microenvironment. However, the specific distinguishing features and functions of TAMs remain poorly defined. Here, we generated tumor-educated macrophages (TEMs) in vitro and performed detailed, multiomic characterization (i.e., transcriptomics, proteomics, metabolomics). Our results reveal unique genetic and metabolic signatures of TEMs, the veracity of which were queried against our in-house single-cell RNA sequencing dataset of human pancreatic tumors. This analysis identified expression of novel, metabolic TEM markers in human pancreatic TAMs, including ARG1, ACLY, and TXNIP. We then utilized our TEM model system to study the role of mutant Kras signaling in cancer cells on TEM polarization. This revealed an important role for granulocyte–macrophage colony-stimulating factor (GM-CSF) and lactate on TEM polarization, molecules released from cancer cells in a mutant Kras-dependent manner. Lastly, we demonstrate that GM-CSF dysregulates TEM gene expression and metabolism through PI3K–AKT pathway signaling. Collectively, our results define new markers and programs to classify pancreatic TAMs, how these are engaged by cancer cells, and the precise signaling pathways mediating polarization.