Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology

BACKGROUND

Colorectal Cancer (CRC) is a prevalent form of cancer, and the effectiveness of the main postoperative chemotherapy treatment, FOLFOX, varies among patients. In this study, we aimed to identify potential biomarkers for predicting the prognosis of CRC patients treated with FOLFOX through plasma proteomic characterization.

METHODS

Using a fully integrated sample preparation technology SISPROT-based proteomics workflow, we achieved deep proteome coverage and trained a machine learning model from a discovery cohort of 90 CRC patients to differentiate FOLFOX-sensitive and FOLFOX-resistant patients. The model was then validated by targeted proteomics on an independent test cohort of 26 patients.

RESULTS

We achieved deep proteome coverage of 831 protein groups in total and 536 protein groups in average for non-depleted plasma from CRC patients by using a Orbitrap Exploris 240 with moderate sensitivity. Our results revealed distinct molecular changes in FOLFOX-sensitive and FOLFOX-resistant patients. We confidently identified known prognostic biomarkers for colorectal cancer, such as S100A4, LGALS1, and FABP5. The classifier based on the biomarker panel demonstrated a promised AUC value of 0.908 with 93% accuracy. Additionally, we established a protein panel to predict FOLFOX effectiveness, and several proteins within the panel were validated using targeted proteomic methods.

CONCLUSIONS

Our study sheds light on the pathways affected in CRC patients treated with FOLFOX chemotherapy and identifies potential biomarkers that could be valuable for prognosis prediction. Our findings showed the potential of mass spectrometry-based proteomics and machine learning as an unbiased and systematic approach for discovering biomarkers in CRC.

Deep spatial proteomics reveals region-specific features of severe COVID-19-related pulmonary injury

As a primary target of severe acute respiratory syndrome coronavirus 2, lung exhibits heterogeneous histopathological changes following infection. However, comprehensive insight into their protein basis with spatial resolution remains deficient, which hinders further understanding of coronavirus disease 2019 (COVID-19)-related pulmonary injury. Here, we generate a region-resolved proteomic atlas of hallmark pathological pulmonary structures by integrating histological examination, laser microdissection, and ultrasensitive proteomics. Over 10,000 proteins are quantified across 71 post-mortem specimens. We identify a spectrum of pathway dysregulations in alveolar epithelium, bronchial epithelium, and blood vessels compared with non-COVID-19 controls, providing evidence for transitional-state pneumocyte hyperplasia. Additionally, our data reveal the region-specific enrichment of functional markers in bronchiole mucus plugs, pulmonary fibrosis, airspace inflammation, and alveolar type 2 cells, uncovering their distinctive features. Furthermore, we detect increased protein expression associated with viral entry and inflammatory response across multiple regions, suggesting potential therapeutic targets. Collectively, this study provides a distinct perspective for deciphering COVID-19-caused pulmonary dysfunction by spatial proteomics.

High-throughput drug target discovery using a fully automated proteomics sample preparation platform

Drug development is plagued by inefficiency and high costs due to issues such as inadequate drug efficacy and unexpected toxicity. Mass spectrometry (MS)-based proteomics, particularly isobaric quantitative proteomics, offers a solution to unveil resistance mechanisms and unforeseen side effects related to off-targeting pathways. Thermal proteome profiling (TPP) has gained popularity for drug target identification at the proteome scale. However, it involves experiments with multiple temperature points, resulting in numerous samples and considerable variability in large-scale TPP analysis. We propose a high-throughput drug target discovery workflow that integrates single-temperature TPP, a fully automated proteomics sample preparation platform (autoSISPROT), and data independent acquisition (DIA) quantification. The autoSISPROT platform enables the simultaneous processing of 96 samples in less than 2.5 hours, achieving protein digestion, desalting, and optional TMT labeling (requires an additional 1 hour) with 96-channel all-in-tip operations. The results demonstrated excellent sample preparation performance with >94% digestion efficiency, >98% TMT labeling efficiency, and >0.9 intra- and inter-batch Pearson correlation coefficients. By automatically processing 87 samples, we identified both known targets and potential off-targets of 20 kinase inhibitors, affording over a 10-fold improvement in throughput compared to classical TPP. This fully automated workflow offers a high-throughput solution for proteomics sample preparation and drug target/off-target identification.

DeKinomics pulse-chases kinase functions in living cells

Cellular context is crucial for understanding the complex and dynamic kinase functions in health and disease. Systematic dissection of kinase-mediated cellular processes requires rapid and precise stimulation ('pulse') of a kinase of interest, as well as global and in-depth characterization ('chase') of the perturbed proteome under living conditions. Here we developed an optogenetic 'pulse-chase' strategy, termed decaging kinase coupled proteomics (DeKinomics), for proteome-wide profiling of kinase-driven phosphorylation at second-timescale in living cells. We took advantage of the 'gain-of-function' feature of DeKinomics to identify direct kinase substrates and further portrayed the global phosphorylation of understudied receptor tyrosine kinases under native cellular settings. DeKinomics offered a general activation-based strategy to study kinase functions with high specificity and temporal resolution under living conditions.

Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation

Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .

Target deconvolution with matrix-augmented pooling strategy reveals cell-specific drug-protein interactions

Target deconvolution is a crucial but costly and time-consuming task that hinders large-scale profiling for drug discovery. We present a matrix-augmented pooling strategy (MAPS) which mixes multiple drugs into samples with optimized permutation and delineates targets of each drug simultaneously with mathematical processing. We validated this strategy with thermal proteome profiling (TPP) testing of 15 drugs concurrently, increasing experimental throughput by 60x while maintaining high sensitivity and specificity. Benefiting from the lower cost and higher throughput of MAPS, we performed target deconvolution of the 15 drugs across 5 cell lines. Our profiling revealed that drug-target interactions can differ vastly in targets and binding affinity across cell lines. We further validated BRAF and CSNK2A2 as potential off-targets of bafetinib and abemaciclib, respectively. This work represents the largest thermal profiling of structurally diverse drugs across multiple cell lines to date.

Chemical Proteomic Approach for In-Depth Glycosylation Profiling of Plasma Carcinoembryonic Antigen in Cancer Patients

Carcinoembryonic antigen (CEA) of human plasma is a biomarker of many cancer diseases, and its N-glycosylation accounts for 60% of molecular mass. It is highly desirable to characterize its glycoforms for providing additional dimension of features to increase its performance in prognosis and diagnosis of cancers. However, to systematically characterize its site-specific glycosylation is challenging because of its low abundance. Here, we developed a highly sensitive strategy for in-depth glycosylation profiling of plasma CEA through chemical proteomics combined with multienzymatic digestion. A trifunctional probe was utilized to generate covalent bond of plasma CEA and its antibody upon UV irradiation. As low as 1 ng/ml CEA in plasma could be captured and digested with trypsin and chymotrypsin for intact glycopeptide characterization. Twenty six of 28 potential N-glycosylation sites were well identified, which were the most comprehensive N-glycosylation site characterization of CEA on intact glycopeptide level as far as we known. Importantly, this strategy was applied to the glycosylation analysis of plasma CEA in cancer patients. Differential site-specific glycoforms of plasma CEA were observed in patients with colorectal cancers (CRCs) and lung cancer. The distributions of site-specific glycoforms were different as the progression of CRC, and most site-specific glycoforms were overexpressed in stage II of CRC. Overall, we established a highly sensitive chemical proteomic method to profile site-specific glycosylation of plasma CEA, which should generally applicable to other well-established cancer glycoprotein biomarkers for improving their cancer diagnosis and monitoring performance.

Tumor Treatment Response Assessed During the Concurrent Chemoradiotherapy for Nasopharyngeal Patients

PURPOSE/OBJECTIVE(S)

To evaluate intratumoral treatment response distribution with using FDG-PET/CT during the chemoradiotherapy of nasopharyngeal patients (NPC).

MATERIALS/METHODS

A total of 5 of 30 patients with stage III-IVA NPC were enrolled in the institutional protocol for induction/concurrent chemoradiotherapy with radiation dose of 70 Gy in 33 fractions. For each patient, a pre-radiation treatment FDG-PET/MRI image (SUV0) and a mid-treatment image (SUVm) at the treatment dose of 31.8 Gy were obtained. Followed by deformable PET/MRI registration between SUV0 and SUVm, the tumor voxel SUV reduction ratio was obtained to construct a tumor dose response matrix (DRM). Tumor SUVavid was also constructed by limiting tumor voxel SUVm > a given value. Spatial correlations of the tumor SUV0, SUVm, SUVavid and DRM were determined.

RESULTS

The mean and coefficient variation (CV) of the SUV0, SUVm and DRM for all tumors were 5.05 (52%), 2.72 (49%) and 0.64 (63%) (Table contains the individual data), which were smaller than those on the SUVs of head-n-neck HPV+ patients reported previously due to the induction chemotherapy, but had much larger DRM mean and CV. The inter-tumoral CVs of SUV0 and DRM were 29% and 27%, which were much lower than those of the intra-tumoral CVs 43% and 57%. Meanwhile, the intra-tumoral variations on SUV0 was smaller than the one of head-neck HPV+ patients, but the DRM intra-variation was much larger. There was a weak correlation between SUV0 and SUVm with the correlation coefficient 0.13, a medium correlation of -0.55 between SUV0 and DRM, but a strong correlation, 0.72, between SUVm and DRM. However, the spatial correlation between tumor DRM and SUVavid was getting weaker as the SUVavid value increasing and equal 0.47 with SUVavid value > 3.

CONCLUSION

The spatial dose response DRM for NPC in the concurrent chemoradiotherapy was relatively high, while had relatively low baseline tumor metabolic activity SUV0. It was most likely due to the induction chemotherapy. In addition, the tumor dose response showed vary large intra-tumoral variation. The high correlations between DRM and SUVm imply that SUVavid could be used partially to guide adaptive modification of NPC treatment with carefully selected boundary value.

Tumor Treatment Response Assessed During the Chemo-Radiotherapy for Locally Advanced NSCLC

PURPOSE/OBJECTIVE(S)

To evaluate the capability of assessing intratumoral treatment response distribution with using FDG-PET/CT during the chemoradiotherapy of locally advanced NSCLC.

MATERIALS/METHODS

Twelve of total 50 patients with stage III NSCLC were enrolled in the institutional protocol for concurrent chemoradiotherapy with treatment dose of 54-60 Gy in 27-30 fractions. For each patient, a pre-treatment FDG-PET/CT image (SUV0) and a mid-treatment image (SUVm) obtained within the treatment dose of 24 ∼ 46 Gy were obtained. Followed by deformable PET/CT registration between SUV0 and SUVm, the tumor voxel SUV reduction ratio was obtained to construct a tumor dose response matrix (DRM). Tumor SUVavid was also constructed by limiting tumor voxel SUVm > a given value. Spatial correlations of the tumor SUV0, SUVm, SUVavid and DRM were determined.

RESULTS

The mean and coefficient variation (CV) of the SUV0, SUVm and DRM for all tumors were 6.56(64%), 2.82(59%) and 0.52(70%) (Table contains the individual data), which were like those on the SUVs and the mean DRM of head-neck HPV- patients reported previously, but much larger on the DRM variation. The inter-tumoral CVs of SUV0 and DRM were 17% and 43%, which were much smaller than those of the intra-tumoral CVs 61% and 55%. Meanwhile, the intra-tumoral variations on both SUV0 and DRM were much larger than those of head-neck HPV- patients. There was a weak correlation between SUV0 and SUVm with the correlation coefficient 0.32, a medium correlation of -0.51 between SUV0 and DRM; 0.58 between SUVm and DRM. It implies that the rule of tumor dose response DRM on treatment modification decision cannot be fully replaced by either SUV0 or SUVm. The spatial correlation between tumor DRM and SUVavid was 0.23 with SUVavid value > 3, which was getting weaker when increasing SUVavid value.

CONCLUSION

Spatial dose response for NSCLC assessed using FDG-PET/CT feedback demonstrated high treatment resistant patterns, which had a large intra-tumoral variation. In addition, the medium correlations of DRM vs SUV0 and DRM vs SUVm imply that all these factors could be used to guide adaptive modification of NSCLC treatment.

Scaled-Down Thermal Profiling and Coaggregation Analysis of the Proteome for Drug Target and Protein Interaction Analysis

Thermal proteome profiling (TPP), an experimental technique combining the cellular thermal shift assay (CETSA) with quantitative protein mass spectrometry (MS), identifies interactions of drugs and chemicals with endogenous proteins. Thermal proximity coaggregation (TPCA) profiling extended TPP to study the intracellular dynamics of protein complexes. In TPP and TPCA, samples are subjected to multiple denaturing temperatures, each requiring over 100 μg of proteins, which restricts their applications for rare cells and precious clinical samples. We developed a workflow termed STASIS (scaled-down thermal profiling and coaggregation analysis with SISPROT) that scales down the required protein to as low as 1 μg per temperature. This is achieved by heating and centrifugation using the same PCR tube, processing samples with the SISPROT technology (simple and integrated spintip-based proteomics technology), and tip-based manual fractionation of TMT-labeled peptides. We evaluate the STASIS workflow with starting protein quantities of 10, 5, and 1 μg per temperature prior to heating, identifying between 4000 and 5000 proteins with 6 h of acquisition time. Importantly, we observed a high correlation in the Tm of proteins with minimal difference in TPCA performance for predicting protein complexes. Moreover, STASIS could identify the targets of methotrexate and panobinostat with high precision with 1 μg of proteins per temperature. In conclusion, STASIS is a robust cost-effective technique for target deconvolution and extended TPCA to rare primary cells and precious clinical samples for the analysis of protein complexes.

Kindlin-2 enhances c-Myc translation through association with DDX3X to promote pancreatic ductal adenocarcinoma progression

Rationale: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive solid tumor, with extremely low survival rates. Identifying key signaling pathways driving PDAC progression is crucial for the development of therapies to improve patient response rates. Kindlin-2, a multi-functional protein, is involved in numerous biological processes including cell proliferation, apoptosis and migration. However, little is known about the functions of Kindlin-2 in pancreatic cancer progression in vivo. Methods: In this study, we employ an in vivo PDAC mouse model to directly investigate the role of Kindlin-2 in PDAC progression. Then, we utilized RNA-sequencing, the molecular and cellular assays to determine the molecular mechanisms by which Kindlin-2 promotes PDAC progression. Results: We show that loss of Kindlin-2 markedly inhibits KrasG12D-driven pancreatic cancer progression in vivo as well as in vitro. Furthermore, we provide new mechanistic insight into how Kindlin-2 functions in this process, A fraction of Kindlin-2 was localized to the endoplasmic reticulum and associated with the RNA helicase DDX3X, a key regulator of mRNA translation. Loss of Kindlin-2 blocked DDX3X from binding to the 5'-untranslated region of c-Myc and inhibited DDX3X-mediated c-Myc translation, leading to reduced c-Myc-mediated glucose metabolism and tumor growth. Importantly, restoration of the expression of either the full-length Kindlin-2 or c-Myc, but not that of a DDX3X-binding-defective mutant of Kindlin-2, in Kindlin-2 deficient PDAC cells, reversed the inhibition of glycolysis and pancreatic cancer progression induced by the loss of Kindlin-2. Conclusion: Our studies reveal a novel Kindlin-2-DDX3X-c-Myc signaling axis in PDAC progression and suggest that inhibition of this signaling axis may provide a promising therapeutic approach to alleviate PDAC progression.

Deciphering intercellular signaling complexes by interaction-guided chemical proteomics

Indirect cell-cell interactions mediated by secreted proteins and their plasma membrane receptors play essential roles for regulating intercellular signaling. However, systematic profiling of the interactions between living cell surface receptors and secretome from neighboring cells remains challenging. Here we develop a chemical proteomics approach, termed interaction-guided crosslinking (IGC), to identify ligand-receptor interactions in situ. By introducing glycan-based ligation and click chemistry, the IGC approach via glycan-to-glycan crosslinking successfully captures receptors from as few as 0.1 million living cells using only 10 ng of secreted ligand. The unparalleled sensitivity and selectivity allow systematic crosslinking and identification of ligand-receptor complexes formed between cell secretome and surfaceome in an unbiased and all-to-all manner, leading to the discovery of a ligand-receptor interaction between pancreatic cancer cell-secreted urokinase (PLAU) and neuropilin 1 (NRP1) on pancreatic cancer-associated fibroblasts. This approach is thus useful for systematic exploring new ligand-receptor pairs and discovering critical intercellular signaling events.

Functional and Clinical Proteomic Exploration of Pancreatic Cancer

Pancreatic cancer, most cases being pancreatic ductal adenocarcinoma (PDAC), is one of the most lethal cancers with a median survival time of less than 6 months. Therapeutic options are very limited for PDAC patients, and surgery is still the most effective treatment, making improvements in early diagnosis critical. One typical characteristic of PDAC is the desmoplastic reaction of its stroma microenvironment, which actively interacts with cancer cells to orchestrate key components in tumorigenesis, metastasis, and chemoresistance. Global exploration of cancer-stroma crosstalk is essential to decipher PDAC biology and design intervention strategies. Over the past decade, the dramatic improvement of proteomics technologies has enabled profiling of proteins, post-translational modifications (PTMs), and their protein complexes at unprecedented sensitivity and dimensionality. Here, starting with our current understanding of PDAC characteristics, including precursor lesions, progression models, tumor microenvironment, and therapeutic advancements, we describe how proteomics contributes to the functional and clinical exploration of PDAC, providing insights into PDAC carcinogenesis, progression, and chemoresistance. We summarize recent achievements enabled by proteomics to systematically investigate PTMs-mediated intracellular signaling in PDAC, cancer-stroma interactions, and potential therapeutic targets revealed by these functional studies. We also highlight proteomic profiling of clinical tissue and plasma samples to discover and verify useful biomarkers that can aid early detection and molecular classification of patients. In addition, we introduce spatial proteomic technology and its applications in PDAC for deconvolving tumor heterogeneity. Finally, we discuss future prospects of applying new proteomic technologies in comprehensively understanding PDAC heterogeneity and intercellular signaling networks. Importantly, we expect advances in clinical functional proteomics for exploring mechanisms of cancer biology directly by high-sensitivity functional proteomic approaches starting from clinical samples.

Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling

Data-dependent liquid chromatography-tandem mass spectrometry (LC-MS/MS) is widely used in proteomic analyses. A well-performed LC-MS/MS workflow, which involves multiple procedures and interdependent metrics, is a prerequisite for deep proteome profiling. Researchers have previously evaluated LC-MS/MS performance mainly based on the number of identified peptides and proteins. However, this is not a comprehensive approach. This motivates us to develop MSRefine, which aims to evaluate and optimize the performance of the LC-MS/MS workflow for data-dependent acquisition (DDA) proteomics. It extracts 47 kinds of metrics, scores the metrics, and reports visual results, assisting users in evaluating the workflow, locating problems, and providing optimizing strategies. In this study, we compared and analyzed multiple pairs of datasets spanning different samples, methods, and instruments and demonstrated that the comprehensive visual metrics and scores in MSRefine enable us to evaluate the performance of the various experiments and provide optimal strategies for the identification of more peptides and proteins.

Integrated mass spectrometry strategy for functional protein complex discovery and structural characterization

The discovery of functional protein complex and the interrogation of the complex structure-function relationship (SFR) play crucial roles in the understanding and intervention of biological processes. Affinity purification-mass spectrometry (AP-MS) has been proved as a powerful tool in the discovery of protein complexes. However, validation of these novel protein complexes as well as elucidation of their molecular interaction mechanisms are still challenging. Recently, native top-down MS (nTDMS) is rapidly developed for the structural analysis of protein complexes. In this review, we discuss the integration of AP-MS and nTDMS in the discovery and structural characterization of functional protein complexes. Further, we think the emerging artificial intelligence (AI)-based protein structure prediction is highly complementary to nTDMS and can promote each other. We expect the hybridization of integrated structural MS with AI prediction to be a powerful workflow in the discovery and SFR investigation of functional protein complexes.

[Biological function and clinical significance of long non-coding RNA LINC00342 in head and neck squamous carcinoma]

Objective: To investigate the relationship between the long-non-coding RNA LINC00342 expression and the clinicopathological parameters of head and neck squamous cell carcinoma (HNSCC) and the biological function of LINC00342 in HNSCC cells. Methods: The expression level of LINC00342 in the HNSCC was analyzed using transcriptome sequencing data from TCGA (The Cancer Genome Atlas) database, and the expressions of LINC00342 in laryngeal squamous cell carcinoma tissues (LSCC) of 27 patients in the First Hospital of Shanxi Medical University were detected by transcriptome sequencing. The expression levels of LINC00342 in human embryonic lung diploid cells 2BS, HNSCC cell lines FD-LSC-1, CAL-27 and Detroit562 were determined by real-time quantitative polymerase chain reaction (qPCR). RNAi (RNA interference) was used for LINC00342 knockdown in HNSCC cell lines, and the changes of malignant phenotype in the tumor cells after LINC00342 knockdown were examined by cell counting kit-8 (CCK-8), colony formation, flow cytometry, transwell invasion and migration assays. Bioinformatics analysis was performed to construct a LINC00342-centered competing endogenous RNA (ceRNA) regulatory network, and GO (Gene Ontology) enrichment analysis was performed. Statistical analysis and graphing were performed using SPSS 25.0 software and GraphPad Prism 6 software. Results: Mean LINC00342 levels in HNSCC tissues and TCGA database were higher than that in normal control tissues, but with no significantly statistical difference (P=0.522). LINC00342 expression levels were positively correlated with cervical lymph node metastasis and pathological grade in patients with HNSCC, with higher expression in male patients than in female patients (P<0.05). Transcriptome sequencing analysis showed that mean expression level of LINC00342 in LSCC tissues of 27 patients was significantly higher than that in the paired adjacent normal mucosa tissues (t=1.56, P=0.036). LINC00342 expression was significantly upregulated in HNSCC cell lines FD-LSC-1, CAL-27 and Detroit562 (t-values of -12.17, -23.26 and -388.57, respectively; all P<0.001). Knockdown of LINC00342 by transfecting si-LINC00342-1 and si-LINC00342-2 inhibited HNSCC cell proliferation (t-values of 8.95 and 4.84, 2.70 and 5.55, 2.02 and 3.70, respectively), colony formation (t-values of 6.66 and 6.17, 7.38 and 11.65, 4.90 and 5.79, respectively), migration (t-values of 8.21 and 7.19, 5.76 and 6.46, 6.28 and 9.92, respectively) and invasion abilities (t-values of 9.29 and 10.25, 11.30 and 11.36, 8.02 and 8.66, respectively), but promoting apoptosis in cell lines FD-LSC-1 and CAL-27 (t-values of -2.21 and -5.83, -3.05 and -5.25 respectively) (all P-values<0.05). The LINC00342-centered ceRNA network consists of 10 downregulated microRNA and 647 upregulated mRNA nodes. GO analysis results indicated that LINC00342-regulated mRNAs were enriched in 22 biological processes, 32 molecular functions, and 12 cellular components. Conclusion: High level of LINC00342 is associated with the malignant progression of HNSCC. LINC00342 promotes the proliferation, migration, invasion, and antagonizes apoptosis of HNSCC cells, which serves as a potential molecular marker in HNSCC.

Pixel-Level Classification of Five Histologic Patterns of Lung Adenocarcinoma

Lung adenocarcinoma is the most common histologic type of lung cancer. The pixel-level labeling of histologic patterns of lung adenocarcinoma can assist pathologists in determining tumor grading with more details than normal classification. We manually annotated a dataset containing a total of 1000 patches (200 patches for each pattern) of 512 × 512 pixels and 420 patches (contains test sets) of 1024 × 1024 pixels according to the morphological features of the five histologic patterns of lung adenocarcinoma (lepidic, acinar, papillary, micropapillary, and solid). To generate an even large amount of data patches, we developed a data stitching strategy as a data augmentation for classification in model training. Stitched patches improve the Dice similarity coefficient (DSC) scores by 24.06% on the whole-slide image (WSI) with the solid pattern. We propose a WSI analysis framework for lung adenocarcinoma pathology, intelligently labeling lung adenocarcinoma histologic patterns at the pixel level. Our framework contains five branches of deep neural networks for segmenting each histologic pattern. We test our framework with 200 unclassified patches. The DSC scores of our results outpace comparing networks (U-Net, LinkNet, and FPN) by up to 10.78%. We also perform results on four WSIs with an overall accuracy of 99.6%, demonstrating that our network framework exhibits better accuracy and robustness in most cases.

Measuring quality of reporting in systematic reviews of diagnostic test accuracy studies in medical imaging: comparison of PRISMA-DTA and PRISMA

OBJECTIVES

To compare the reporting quality measured by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy studies (PRISMA-DTA) vs the original PRISMA checklist for systematic reviews of diagnostic test accuracy studies in imaging and survey the use of PRISMA-DTA by researchers and endorsement by journals.

METHODS

Systematic reviews of DTA studies published in 2020 and 2021 in Quartile 1 and Quartile 3 medical imaging journals (defined by Journal Citation Reports) were identified through PubMed. The reporting of each systematic review was assessed using PRISMA-DTA, PRISMA-2009 and PRISMA-2020. The item scores and overall score were compared among the three checklists. We also examined checklist adoption by the included systematic reviews and surveyed checklist endorsement from author instructions of included journals.

RESULTS

A total of 173 systematic reviews from 66 journals were included. The use of PRISMA-DTA, compared with PRISMA-2009 and PRISMA-2020, identified more issues in the reporting of title (proportion of systematic reviews with proper reporting, 27.2% vs 98.8% vs 98.8%), abstract (39.3% vs 97.1% vs 64.7%), eligibility criteria (67.6% vs 94.2% vs 94.2%), search (28.9% vs 72.3% vs 28.9%), definitions for data extraction (14.5% vs 91.9% vs 91.9%), diagnostic accuracy measures (38.2% vs 93.6% vs 93.6%), synthesis of results (28.9% vs 89.6% vs 73.4%) and results of individual studies (40.5% vs 80.3% vs 80.3%). The overall median reporting score measured by PRISMA-DTA (72.0% (interquartile range (IQR), 66.7-77.8%)) was lower than that measured by PRISMA-2009 (88.9% (IQR, 84.0-92.6%)) and similar to that measured by PRISMA-2020 (74.1% (IQR, 66.7-77.8%)). Additionally, PRISMA-DTA was used by only 43 (24.9%) systematic reviews and endorsed by two (3.0%) journals. These trends remained consistent for reviews published in journals with diverse scientific impact.

CONCLUSIONS

The use of PRISMA-DTA may identify more reporting inadequacies compared with the original PRISMA checklists when assessing diagnostic test accuracy systematic reviews, especially in critical sections such as title, abstract and methods. However, this tool is not commonly used by researchers and is inadequately endorsed by imaging journals. Our findings suggest a strong need to use PRISMA-DTA for reporting of diagnostic test accuracy systematic reviews by authors and its endorsement by journals. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Combination of automated sample preparation and micro-flow LC-MS for high-throughput plasma proteomics

BACKGROUND

Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis.

METHODS

We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC-MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups.

RESULTS

This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC-MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers.

CONCLUSIONS

This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups.

Hearing Impairment and Incident Frailty in Later Life: The Health in Men Study (HIMS)

OBJECTIVES

This study is designed to determine if hearing loss is associated with increased risk of frailty in later life.

DESIGN

A prospective cohort study.

SETTING AND PARTICIPANTS

We retrieved data of a community sample of men aged 70 years and above living in the metropolitan region of Perth, Western Australia. 3,285 participants who were free of frailty at the beginning of the study were followed for up to 17 years. Data were retrieved from the Health in Men Study (HIMS) and the Western Australian Data Linkage System (WADLS).

MEASUREMENTS

Hearing loss was defined by self-report or by diagnosis recorded in the WADLS. Incident frailty was assessed using the Hospital Frailty Risk Score (HFRS).

RESULTS

A total of 2,348 (71.5%) men developed frailty during follow up. The adjusted hazard ratio was 1.03 (95% CI: 0.95-1.12). The majority of the participants became frail by age 90 regardless of hearing condition. The time point where half of the group become frail was delayed by 14.4 months for men without hearing loss compared with hearing impaired men.

CONCLUSIONS

Hearing loss is not associated with incident frailty in men aged 70 years or older when frailty was measured by HFRS. However, this statistically non-significant result could be due to the low sensitivity of study measures. Also, we found a trend that men with hearing loss were more likely to develop frailty compared with their normal-hearing peers, suggesting a potential association between hearing loss and frailty.

Integrated and High-Throughput Approach for Sensitive Analysis of Tyrosine Phosphoproteome

Tyrosine phosphorylation (pTyr) regulates various signaling pathways under normal and cancerous states. Due to their low abundance and transient and dynamic natures, systematic profiling of pTyr sites is challenging. Antibody and engineered binding domain-based approaches have been well applied to pTyr peptide enrichment. However, traditional methods have the disadvantage of a long sample preparation process, which makes them unsuitable for processing limited amount of samples, especially in a high-throughput manner. In this study we developed a 96-well microplate-based approach to integrate all the sample preparation steps starting from cell culture to MS-compatible pTyr peptide enrichment in three consecutive 96-well microplates. By assembling an engineered SH2 domain onto a microplate, nonspecific adsorption of phosphopeptides is greatly reduced, which allows us to remove the Ti-IMAC purification and three C18 desalting steps (after digestion, pTyr enrichment, and Ti-IMAC purification) and, therefore, greatly simplifies the entire pTyr peptide enrichment workflow, especially when processing a large number of samples. Starting with 96-well microplate-cultured, pervanadate-stimulated cells, our approach could enrich 21% more pTyr sites than the traditional serial pTyr enrichment approach and showed good sensitivity and reproducibility in the range of 200 ng to 200 μg peptides. Importantly, we applied this approach to profile tyrosine kinase inhibitor-mediated EGFR signaling pathway and could well differentiate the distinct response of different pTyr sites. Collectively, the integrated 96-well microplate-based approach is valuable for profiling pTyr sites from limited biological samples and in a high-throughput manner.

[Construction of zebrafish models for screening intracranial hemorrhage associated genes]

Objective: To construct zebrafish models for the screening of intracranial hemorrhage (ICH) associated genes. Methods: ICH zebrafish models were constructed through morpholino oligonucleotides (MOs) technique and microinjection technique, and multiple verification was performed from macro and micro perspectives. First, the normal wild-type AB strain zebrafish injected with control MO was used as the control group, and AB zebrafish embryos microinjected with MOs of genes related to development of neural crest-derived cells (NCDCs) were used as the study group, such as col8a1 MO, tfap2α MO, msx1a MO, msx2 MO, and dkk1a MO. Preliminary verification of the model was conducted under a white-light optical microscope. Then, the model was verified by Tg (flk1: gfp; gata1: dsRed) double transgenic zebrafish, with vascular endothelial cells labeled by green fluorescent protein (GFP) and red blood cell labeled by fluorescent protein (dsRed), and thus the location of cerebral hemorrhage can be observed more clearly. Specifically, zebrafish embryos were microinjected with Control MO as the control group and those microinjected with col8a1 MO as the study group. Then the embryos were cultured until 48 hours post-fertilization to observe the leakage of red blood cells under the confocal laser scanning microscope. Finally, Tg (flk1: gfp) transgenic zebrafish was used to verify the model based on the blood-brain barrier (BBB). Through the leakage of dextran-rhodamine and DAPI dyes, the destruction of BBB and the occurrence of cerebral hemorrhage in zebrafish were further clarified, and quantitative statistics were carried out to verify the relationship between NCDCs development related genes and cerebral hemorrhage phenotype, which proved that the modeling was effective. Results: The zebrafish with col8a1, tfap2α, and msx1 mutations in the study group had apparent ICH compared with wildtype zebrafish, and the prevalence of ICH was 18.18% (52/286), 23.04% (62/251), and 35.94% (23/64), respectively. While, the zebrafish with msx2 and dkk1a mutations rarely had ICH, with the ICH prevalence of 1.03% (1/97) and 1.15% (1/87), respectively. The prevalence of red blood cells leakage in Tg (flk1:gfp; gata1:dsred) double transgenic zebrafish injected with Control Mo and col8a1 Mo was 0.37% (1/273) and 18.18% (52/286) (P<0.001). The number of DAPI positive nuclei of Tg (flk1: gfp) transgenic zebrafish injected with Control Mo and col8a1 Mo was 10.05±5.27 and 60.35±3.96 (P<0.001), and the fluorescent intensity of midbrain parenchymal induced by dextran-rhodamin leakage was 2.54±4.70 and 5.13±3.52 (P<0.001). Conclusion: This study successfully constructs the ICH zebrafish models, and ICH-related genes are screened out, such as col8a1, tfap2α, msx1, and so on.

Robust Capillary- and Micro-Flow Liquid Chromatography-Tandem Mass Spectrometry Methods for High-Throughput Proteome Profiling

Capillary- and micro-flow liquid chromatography-tandem mass spectrometry (capLC-MS/MS and μLC-MS/MS) is becoming a valuable alternative to nano-flow LC-MS/MS due to its high robustness and throughput. The systematic comparison of capLC-MS/MS and μLC-MS/MS systems for global proteome profiling has not been reported yet. Here, the capLC-MS/MS (150 μm i.d. column, 1 μL/min) and μLC-MS/MS (1 mm i.d. column, 50 μL/min) systems were both established based on UltiMate 3000 RSLCnano coupled to an Orbitrap Exploris 240 by integrating with different flowmeters. We evaluated both systems in terms of sensitivity, analysis throughput, separation efficiency, and robustness. capLC-MS/MS was about 10 times more sensitive than μLC-MS/MS at different gradient lengths. Compared with capLC-MS/MS, μLC-MS/MS was able to achieve higher analysis throughput and separation efficiency. During the 7 days' long-term performance test, both systems showed good reproducibility of chromatographic full width (RSD < 3%), retention time (RSD < 0.4%), and protein identification (RSD < 3%). These results demonstrate that capLC-MS/MS is more suitable for high-throughput analysis of clinical samples with a limited starting material. When enough samples are available, μLC-MS/MS is preferred. Together, capLC and μLC coupled to Orbitrap Exploris 240 with moderate sensitivity should well meet the needs of large-cohort clinical proteomic analysis.

[Effect of D-dimer on the prognosis of patients with aneurysmal subarachnoid hemorrhage based on propensity score matching]

Objective: To evaluate the effect of D-dimer on the prognosis of patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods: A total of 1 658 patients who were first diagnosed with aSAH in West China Hospital of Sichuan University from December 2013 to June 2019 were retrospectively analyzed. All patients were divided into four groups according to the median and quartiles of D-dimer level, including 415 cases, 414 cases, 414 cases, and 415 cases in groups Q₁, Q₂, Q₃, and Q₄, respectively. Groups Q₂, Q₃, Q_4, and group Q₁ were matched by propensity score matching (PSM), and the correlation between D-dimer and each outcome was analyzed by logistic regression. Since there is no general clinical classification standard for D-dimer, this study attempted to reclassify patients into groups q1 (<0.55 mg/L, 94 cases), q2 (0.55-1.65 mg/L, 435 cases), q3 (1.65-5.50 mg/L, 650 cases) and q4 (>5.50 mg/L, 303 cases) based on 1, 3, 5, 10 times of the upper limit of the current clinical reference value. Results: The age of 1 658 aSAH patients were (57±12) years, including 1 068 males and 590 females. After PSM based on the median and quartiles of D-dimer level, there were 318 cases, 318 cases, 251 cases, and 229 cases in groups Q₁, Q₂, Q₃, and Q₄, respectively. Compared with group Q₁ (<1.23 mg/L), the risk of in-hospital infection (OR=2.14, 95%CI: 1.47-3.11, P<0.001), pneumonia (OR=2.22, 95%CI: 1.51-3.28, P<0.001), urinary tract infection (OR=1.75, 95%CI: 1.12-2.75, P=0.014) and intracranial rebleeding (OR=3.59, 95%CI: 1.30-9.91, P=0.013) group Q₄ (>4.95 mg/L) was higher. Likewise, the risk of adverse outcomes in group Q₄ was also higher than that in group Q₁, including unfavorable outcome at discharge (OR=2.12, 95%CI: 1.43-3.14, P<0.001), mortality during hospitalization (OR=3.03, 95%CI: 1.26-7.33, P=0.014), mortality within 90 days (OR=2.33, 95%CI:1.29-4.22, P=0.005), mortality within 180 days (OR=1.92, 95%CI: 1.12-3.29, P=0.018), mortality within 1 year (OR=2.07, 95%CI:1.23-3.47, P=0.006) and mortality during the longest follow-up period (OR=1.97, 95%CI:1.26-3.09, P=0.003). After secondary grouping and PSM based on current clinical reference values, there were 90 cases, 87 cases, 90 cases, and 43 cases, respectively in groups q1, q2, q3 and q4. The risk of nosocomial infection (OR=2.26, 95%CI: 1.14-4.45, P=0.019), blood-borne infection (OR=8.86, 95%CI:1.08-72.78, P=0.042), poor prognosis at discharge (OR=4.92, 95%CI: 2.18-11.07, P<0.001), death within 180 days (OR=3.39, 95%CI: 1.04-11.08, P=0.043), death within 1 year (OR=3.23, 95%CI: 1.10-9.49, P=0.033), and death within the longest follow-up period (OR=3.28, 95%CI: 1.34-8.01, P=0.009) was still higher in group q4 than that in group q1. Conclusion: aSAH patients with high D-dimer level have a higher risk of complications and mortality during hospitalization and worse clinical prognosis.

Mass spectrometry-based ganglioside profiling provides potential insights into Alzheimer's disease development

Gangliosides are a family of glycosphingolipids which are particularly enriched in the nervous system. They play crucial roles in neuroprotection and neurological diseases. Alzheimer's disease (AD) is a neurodegenerative disease with cognitive, judgment and memory dysfunction. In this study, a mass spectrometry-based data-dependent acquisition method assisted with fragmentation characteristics screening by computer algorithm was developed for qualitative and quantitative analysis of gangliosides at low concentration. The developed method was applied to obtain detailed ganglioside species content in hippocampus of model mice (APPswe/PS1dE9 transgenic mice) with AD at 3- to 8-month-old. Up-regulated acetylated and N-acetylgalactosaminylated ganglioside species, and the down-regulated major gangliosides were observed with the development of AD from early to late stage. We speculated that deterioration of AD may be related to the acetylation/N-acetylgalactosaminylation transformation of complex gangliosides due to the inhibition of GD3 synthase activity. Moreover, the ganglioside species di-O-Ac-GT1a (d36:1), O-Ac-GD1b (d36:1) and O-Ac-GD1b (d36:0) were considered as the time-coursed biomarkers, and O-Ac-GT1a (d36:2) could be a candidate for early diagnosis of AD.

[A nationalsurveyandresults analysisof seizure prophylaxis after aneurismal subarachnoid hemorrhage]

Investigate theclinical practice of seizure prophylaxis after aneurysmal subarachnoid hemorrhage in Chinese neurosurgeons.Aquestionnaire for this theme was designed and was sent to respondents through the internet.From July 2021 to October 2021, atotal of forty-three eligible questionnaires were collected. All responders come from affiliated hospitals of medical schools in China. Each of these hospitals admitted more than one hundred patients with aneurysmal subarachnoid hemorrhage per year. Only 9.3% (4/43) of responders disagree with the prophylactic use of anticonvulsants. 86.04% (37/43) of responders perform seizure prophylaxis in clinical practice. Sodium valproate is the most commonly used regimen; 94.59% (35/37) of responders who perform prophylaxis chose this drug. The medication period differs sharply fromlessthan 3 daystolongerthan 14 daysamong different hospitals. The use of EEG was insufficient in Chinese patients. A low seizure rate was reported according to the feedback from Chinese neurosurgeons.In China, seizure prophylaxis after subarachnoid hemorrhage was not yet standardized. Clinicians' mastery of relevant knowledge is still not enough. Carrying out high-quality clinical research can help justify the use of anticonvulsants, which could also positively impact rational drug use.

[A randomized double-blinded placebo-controlled clinical trial of minodronate tablet in postmenopausal Chinese women with osteoporosis]

Objective: To verify the efficacy and safety of daily oral minodronate in postmenopausal women with established osteoporosis. Methods: In this randomized, double-blinded, placebo-controlled trial, 262 postmenopausal women were enrolled. Patients were randomized to receive daily oral minodronate 1 mg with supplements of 500 mg calcium and 200 U vitamin D₃ (n=130) or placebo (n=132) with daily supplements of 500 mg calcium and 200 U vitamin D₃, for 48 weeks. The primary endpoint was the average bone mineral density (BMD) change in the lumbar vertebrae 48 weeks post-treatment. Secondary outcome measures was the incidence of vertebral fractures. Safety assessments included the rate of adverse events. Results: At the end of 48 weeks treatment, the average BMD change rate from baseline were: full analysis set results: (3.52±4.82)% in the minodronate group and (2.00±5.74)% in the placebo group; per-protocol set results: (3.99±5.05)% in the minodronate group and (2.07±6.20)% in the placebo group; the differences were all significant (all P<0.05). Vertebral fracture occured in 3 patients (2.3%, 3/132) in the placebo group, and 1 case (0.8%, 1/130) in the minodronate group (P>0.05). The incidence of adverse events was 71.5% (93/130) in the minodronate group and 78.0% (103/132) in the placebo group (P>0.05). Conclusion: Minodronate is effective and safe in the treatment of postmenopausal osteoporosis without severe side effects.

Kindlin-2 promotes Src-mediated tyrosine phosphorylation of androgen receptor and contributes to breast cancer progression

Androgen receptor (AR) signaling plays important roles in breast cancer progression. We show here that Kindlin-2, a focal adhesion protein, is critically involved in the promotion of AR signaling and breast cancer progression. Kindlin-2 physically associates with AR and Src through its two neighboring domains, namely F1 and F0 domains, resulting in formation of a Kindlin-2-AR-Src supramolecular complex and consequently facilitating Src-mediated AR Tyr-534 phosphorylation and signaling. Depletion of Kindlin-2 was sufficient to suppress Src-mediated AR Tyr-534 phosphorylation and signaling, resulting in diminished breast cancer cell proliferation and migration. Re-expression of wild-type Kindlin-2, but not AR-binding-defective or Src-binding-defective mutant forms of Kindlin-2, in Kindlin-2-deficient cells restored AR Tyr-534 phosphorylation, signaling, breast cancer cell proliferation and migration. Furthermore, re-introduction of phosphor-mimic mutant AR-Y534D, but not wild-type AR reversed Kindlin-2 deficiency-induced inhibition of AR signaling and breast cancer progression. Finally, using a genetic knockout strategy, we show that ablation of Kindlin-2 from mammary tumors in mouse significantly reduced AR Tyr-534 phosphorylation, breast tumor progression and metastasis in vivo. Our results suggest a critical role of Kindlin-2 in promoting breast cancer progression and shed light on the molecular mechanism through which it functions in this process.

Zwitter-ionic monolith-based spintip column coupled with Evosep One liquid chromatography for high-throughput proteomic analysis

A high-throughput proteomic workflow with good sensitivity and reproducibility is highly demanding for proteomic studies of large clinical cohorts. We present a workflow that seamlessly integrates the zwitter-ionic monolith-based spintip (ZIM-Tip) with the Evosep One liquid chromatography system to address this challenge. Disposable ZIM-Tips were prepared with satisfying permeability based on photo-initiated free radical polymerization. Sample preparation steps, including ion-exchange-based protein concentration, reduction, alkylation, and enzymatic digestion, were processed on the ZIM-Tips in 2 h with about 10% sample loss. The peptides recovered from ZIM-Tips were directly loaded on Evotips for desalting and proteomic data acquisition. In one-hour high performance liquid chromatography-MS/MS run, more than 4000 proteins were consistently identified from 1 µg of cell lysate using timsTOF Pro-mass spectrometer in data-dependent acquisition mode (DDA). At least 20 samples with protein amount of 1 µg could be processed each day. Good intra- and inter-day precision in quantification were demonstrated with median coefficient of variation (CV) values of less than 20% and 30%, respectively. The average Pearson correlation coefficients of each two sets of samples are 0.934 and 0.901, respectively. Collectively, the ZIM-Tip technology offers an useful solution for clinical cohort studies with demand for large sample amounts and low sample input while maintaining in-depth proteome coverage.

[Establishment of a rapid risk assessment system for imported COVID-19 cases]

Objective: To develop a rapid risk assessment tool for imported COVID-19 cases and provide reference evidences for prevention and control of COVID-19 at ports. Methods: The information about COVID-19 pandemic and control strategies of 12 concerned countries was collected during July to August 2021, and 12 indexes were selected to assess the importation risk of COVID-19 by risk matrix. Results: The risk for imported COVID-19 cases from 12 countries to China was high or extremely high, and the risk from Russia and the USA was highest. Conclusions: The developed rapid risk assessment tool based on the risk matrix method can be used to determine the risk level of countries for imported COVID-19 cases to China at ports, and the risk of imported COVID-19 was high at Beijing port in August 2021.

Generic Plug-and-Play Strategy for High-Throughput Analysis of PTM-Mediated Protein Complexes

Protein complexes mediated by various post-translational modifications (PTMs) play important roles in almost every aspect of biological processes. PTM-mediated protein complexes often have weak and transient binding properties, which limit their unbiased profiling especially in complex biological samples. Here, we developed a plug-and-play chemical proteomic approach for high-throughput analyis of PTM-mediated protein complexes. Taking advantage of the glutathione-S-transferase (GST) tag, which is the gold standard for protein purification and has wide access to a variety of proteins of interest (POIs), a glutathione (GSH) group- and photo-cross-linking group-containing trifunctional chemical probe was developed to tag POIs and assembled onto a streptavidin-coated 96-well plate for affinity purification, photo-cross-linking, and proteomics sample preparation in a fully integrated manner. Compared with the previously developed photo-pTyr-scaffold strategy, by assembling the tyrosine phosphorylation (pTyr) binding domain through covalent NHS chemistry, the new plug-and-play strategy using a noncovalent GST-GSH interaction has comparable enrichment efficiency for EGF stimulation-dependent pTyr protein complexes. To further prove its feasibility, we additionally assembled four pTyr-binding domains in the 96-well plate and selectively identified their pTyr-dependent interacting proteins. Importantly, we systematically optimized and applied the plug-and-play approach for exploring protein methylation-mediated protein complexes, which are difficult to be characterized due to their weak binding affinity and the lack of efficient enrichment strategies. We explored a comprehensive protein methylation-mediated interaction network assembled by five protein methylation binding domains including the chromo domain of MPP8, tandem tudor domain of KDM4A, full-length CBX1, PHD domain of RAG2, and tandem tudor domain of TP53BP1 and validated the chromo domain- and tudor domain-mediated interaction with histone H3. Collectively, this plug-and-play approach provides a convenient and generic strategy for exploring PTM-dependent protein complexes for any POIs with the GST tag.

Selective inhibition reveals the regulatory function of DYRK2 in protein synthesis and calcium entry

The dual-specificity tyrosine phosphorylation-regulated kinase DYRK2 has emerged as a critical regulator of cellular processes. We took a chemical biology approach to gain further insights into its function. We developed C17, a potent small-molecule DYRK2 inhibitor, through multiple rounds of structure-based optimization guided by several co-crystallized structures. C17 displayed an effect on DYRK2 at a single-digit nanomolar IC50 and showed outstanding selectivity for the human kinome containing 467 other human kinases. Using C17 as a chemical probe, we further performed quantitative phosphoproteomic assays and identified several novel DYRK2 targets, including eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and stromal interaction molecule 1 (STIM1). DYRK2 phosphorylated 4E-BP1 at multiple sites, and the combined treatment of C17 with AKT and MEK inhibitors showed synergistic 4E-BP1 phosphorylation suppression. The phosphorylation of STIM1 by DYRK2 substantially increased the interaction of STIM1 with the ORAI1 channel, and C17 impeded the store-operated calcium entry process. These studies collectively further expand our understanding of DYRK2 and provide a valuable tool to pinpoint its biological function.

A fully integrated sample preparation strategy for highly sensitive intact glycoproteomics

A fully integrated sample preparation technology, termed Intact GlycoSISPROT, was developed for the highly sensitive analysis of site-specific glycopeptides. Through integrating all glycoproteomic sample preparation steps into a single spintip, Intact GlycoSISPROT provided a tool for site-specific glycosylation analysis with low micrograms to even nanograms of protein sample.

Fully Integrated On-line strategy for Highly Sensitive Proteome Profiling of 10-500 Mammalian Cells

Recent development in proteomic sample preparation using nanofluidic devices has made single-cell proteome profiling possible. However, these nanofluidic devices require special expertise and costly nanopipetting instruments. They are also specially...

[Comparison of the performance of secretome analysis based on metabolic labeling by three unnatural sugars]

分泌蛋白质是调控细胞间信号转导的重要生物大分子。由于分泌蛋白的丰度相比于胞内蛋白以及培养基添加剂更低,因此分泌蛋白的高通量鉴定是目前蛋白质组学界研究的热点和难点。目前,基于生物质谱的分泌蛋白质组学分析一般均需要从无血清的条件培养基中获得分泌蛋白质,再对其进行富集和分析。该流程操作步骤繁琐,易造成分泌蛋白质的损失和降解。本工作采用基于生物正交化学生物学技术实现对分泌蛋白质的高选择性标记和高效富集。通过结合点击化学技术,综合评估了分泌蛋白质分析中用于代谢标记的不同糖类似物。采用3种最常用的商品化糖类似物,N-叠氮乙酰甘露糖胺(ManNAz)、N-叠氮乙酰半乳糖胺(GalNAz)和N-叠氮乙酰葡萄糖胺(GlcNAz)分别对HeLa细胞进行代谢标记,之后通过炔基生物素探针对条件培养基中的分泌蛋白进行富集,结合质谱分析来对比3种糖类似物对分泌蛋白的标记效率。最后通过无标定量蛋白质组学分析,系统评估了3种糖类似物用于分泌蛋白质组分析的性能。结果表明,基于ManNAz的分泌蛋白标记方法鉴定到了282个分泌蛋白、224个细胞质膜蛋白以及846个N-糖基化位点;对分泌蛋白的富集效率分别较GalNAz和GlcNAz提高了130%和67.2%;对细胞质膜蛋白的富集效率较GalNAz和GlcNAz分别提高了273.3%和148.7%,体现出了明显的优势。本研究的实验结果为分泌蛋白高选择性富集和系统分析提供了有益的对比分析和新技术策略。

Feedback control of PLK1 by Apolo1 ensures accurate chromosome segregation

Stable transmission of genetic material during cell division requires accurate chromosome segregation. PLK1 dynamics at kinetochores control establishment of correct kinetochore-microtubule attachments and subsequent silencing of the spindle checkpoint. However, the regulatory mechanism responsible for PLK1 activity in prometaphase has not yet been affirmatively identified. Here we identify Apolo1, which tunes PLK1 activity for accurate kinetochore-microtubule attachments. Apolo1 localizes to kinetochores during early mitosis, and suppression of Apolo1 results in misaligned chromosomes. Using the fluorescence resonance energy transfer (FRET)-based PLK1 activity reporter, we found that Apolo1 sustains PLK1 kinase activity at kinetochores for accurate attachment during prometaphase. Apolo1 is a cognate substrate of PLK1, and the phosphorylation enables PP1γ to inactivate PLK1 by dephosphorylation. Mechanistically, Apolo1 constitutes a bridge between kinase and phosphatase, which governs PLK1 activity in prometaphase. These findings define a previously uncharacterized feedback loop by which Apolo1 provides fine-tuning for PLK1 to guide chromosome segregation in mitosis.

Spatial proteomics for understanding the tissue microenvironment

The human body comprises rich populations of cells, which are arranged into tissues and organs with diverse functionalities. These cells exhibit a broad spectrum of phenotypes and are often organized as a heterogeneous but sophisticatedly regulated ecosystem - tissue microenvironment, inside which every cell interacts with and is reciprocally influenced by its surroundings through its life span. Therefore, it is critical to comprehensively explore the cellular machinery and biological processes in the tissue microenvironment, which is best exemplified by the tumor microenvironment (TME). The past decade has seen increasing advances in the field of spatial proteomics, the main purpose of which is to characterize the abundance and spatial distribution of proteins and their post-translational modifications in the microenvironment of diseased tissues. Herein, we outline the achievements and remaining challenges of mass spectrometry-based tissue spatial proteomics. Exciting technology developments along with important biomedical applications of spatial proteomics are highlighted. In detail, we focus on high-quality resources built by scalpel macrodissection-based region-resolved proteomics, method development of sensitive sample preparation for laser microdissection-based spatial proteomics, and antibody recognition-based multiplexed tissue imaging. In the end, critical issues and potential future directions for spatial proteomics are also discussed.

Stable and EGF-Induced Temporal Interactome Profiling of CBL and CBLB Highlights Their Signaling Complex Diversity

The epidermal growth factor receptor (EGFR) signal modulates cell proliferation, migration, and survival. Aberrant activation of EGFR constitutes the major cause of various cancers. Receptor ubiquitination and degradation mediated by CBL proteins play negative regulatory roles and control the intensity and duration of the signaling. With the construction of stable cell lines inducibly expressing FLAG-tagged CBL or CBLB, we identified 102 and 82 stable interacting proteins of CBL and CBLB, respectively, through the affinity purification followed by mass spectrometry (AP-MS) approach. Time-resolved profiling at six different time points combined with functional annotations of the temporal interactomes provides insights into the dynamic assembly of signal proteins upon EGFR signaling activation. Comparison between the interactomes of CBL and CBLB indicates their redundant but also complementary functions. Importantly, we validated the stable association of EPS15L1 and ITSN2 and temporal association of TNK2 to both CBL and CBLB through biochemical assays. Collectively, these results offer a useful resource for CBL and CBLB interactomes and highlight their prominent and diverse roles in the EGFR signaling network.

A robust and scalable active-matrix driven digital microfluidic platform based on printed-circuit board technology

Two-dimensional digital microfluidic platforms, on which droplets are actuated by electrowetting on dielectrics, have merits such as dynamic reconfigurability and ease for automation. However, concerns for digital microfluidic platforms based on low-cost printed circuit boards, such as the scalability of the electrode array and the reliability of the device operation, should be addressed before high throughput and fully automatic applications can be realized. In this work we report the progress in addressing those issues by using active-matrix circuitry to automatically drive a large electrode array with enhanced device reliability. We describe the design and the fabrication of a robust and scalable active-matrix driven digital microfluidic platform based on printed-circuit board technology. Reliable actuation of aqueous and organic droplets is achieved using a free-standing double-layer hydrophobic membrane. To demonstrate the versatility of the digital microfluidic platform, a pentapeptide is synthesized on the device within 30 minutes. With these improvements, a fully automatic, scalable, robust, reusable, and low-cost digital microfluidic platform capable of parallel manipulation of a large number of droplets can find numerous applications in chemical engineering, bioengineering and biomedical engineering.

Synergistic optimization of Liquid Chromatography and Mass Spectrometry parameters on Orbitrap Tribrid mass spectrometer for high efficient data-dependent proteomics

Steady improvement in Orbitrap-based mass spectrometry (MS) technologies has greatly advanced the peptide sequencing speed and depth. In-depth analysis of the performance of state-of-the-art MS and optimization of key parameters can improve sequencing efficiency. In this study, we first systematically compared the performance of two popular data-dependent acquisition approaches, with Orbitrap as the first-stage (MS1) mass analyzer and the same Orbitrap (high-high approach) or ion trap (high-low approach) as the second-stage (MS2) mass analyzer, on the Orbitrap Fusion mass spectrometer. High-high approach outperformed high-low approach in terms of better saturation of the scan cycle and higher MS2 identification rate. However, regardless of the acquisition method, there are still more than 60% of peptide features untargeted for MS2 scan. We then systematically optimized the MS parameters using the high-high approach. Increasing the isolation window in the high-high approach could facilitate faster scan speed, but decreased MS2 identification rate. On the contrary, increasing the injection time of MS2 scan could increase identification rate but decrease scan speed and the number of identified MS2 spectra. Dynamic exclusion time should be set properly according to the chromatography peak width. Furthermore, we found that the Orbitrap analyzer, rather than the analytical column, was easily saturated with higher loading amount, thus limited the dynamic range of MS1-based quantification. By using optimized parameters, 10 000 proteins and 110 000 unique peptides were identified by using 20 h of effective liquid chromatography (LC) gradient time. The study therefore illustrated the importance of synchronizing LC-MS precursor ion targeting, fragment ion detection, and chromatographic separation for high efficient data-dependent proteomics.

Phosphorylation-regulated HMGA1a-P53 interaction unveils the function of HMGA1a acidic tail phosphorylations via synthetic proteins

As a typical member of intrinsically disordered proteins (IDPs), HMGA1a carries many post-translational modifications (PTMs). To study the undefined function of acidic tail phosphorylations, seven HMGA1a proteins with site-specific modification(s) were chemically synthesized via Ser/Thr ligation. We found that the phosphorylations significantly inhibit HMGA1a-P53 interaction and the phosphorylations can induce conformational change of HMGA1a from an "open state" to a "close state." Notably, the positively charged lysine-arginine (KR) clusters are responsible for modulating HMGA1a conformation via electrostatic interaction with the phosphorylated acidic tail. Finally, we used a synthetic protein-affinity purification mass spectrometry (SP-AP-MS) methodology to profile the specific interactors, which further supported the function of HMGA1a phosphorylation. Collectively, this study highlights a mechanism for regulating IDPs' conformation and function by phosphorylation of non-protein-binding domain and showcases that the protein chemical synthesis in combination with mass spectrometry can serve as an efficient tool to study the IDPs' PTMs.