ProSAP: a GUI software tool for statistical analysis and assessment of thermal stability data.

The Cellular Thermal Shift Assay (CETSA) plays an important role in drug-target identification, and statistical analysis is a crucial step significantly affecting conclusion. We put forward ProSAP (Protein Stability Analysis Pod), an open-source, cross-platform and user-friendly software tool, which provides multiple methods for thermal proteome profiling (TPP) analysis, nonparametric analysis (NPA), proteome integral solubility alteration and isothermal shift assay (iTSA). For testing the performance of ProSAP, we processed several datasets and compare the performance of different algorithms. Overall, TPP analysis is more accurate with fewer false positive targets, but NPA methods are flexible and free from parameters. For iTSA, edgeR and DESeq2 identify more true targets than t-test and Limma, but when it comes to ranking, the four methods show not much difference. ProSAP software is available at https://github.com/hcji/ProSAP and https://zenodo.org/record/5763315.

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.

Malignancy-associated generalised exfoliative dermatitis: A retrospective study in a single-centre Asian cohort.

BACKGROUND: Erythroderma is an inflammatory skin condition that causes extensive erythema and skin scaling amounting ≥90% of the body surface area. This retrospective cohort study describes the prevalence of malignancy-associated erythroderma in a single centre where there was concerted effort to systematically offer malignancy screens to all adult erythroderma patients above the age of 65 years. METHODS: Clinical charts were reviewed for all adult inpatients and outpatients with erythroderma who attended the National University Hospital (NUH) from 1 July 2019 to 31 December 2021. Data collected included patient demographics, clinical findings, laboratory investigations, disease-specific investigations such as endoscopic procedures and biopsies, follow-up duration and mortality data. RESULTS: Seventy-four patients were analysed. The median age of the patients was 73 years old (interquartile range: 59-81 years old). An underlying dermatosis was the most common cause of erythroderma-63 patients having atopic dermatitis/asteatotic eczema or psoriasis. Three patients had erythroderma from drug eruptions, and 1 patient had chronic actinic dermatitis. Four patients had associated malignancies (5.4%). Half of our patients completed further evaluation for malignancy (52.7%). The rest had either declined or were eventually unable to complete the investigations. There was a higher prevalence of associated malignancy (7.8%) in elderly patients above 65 years old. CONCLUSION: When compared to existing literature, our cohort reflects a higher observed occurrence of malignancy in association with erythroderma. As delays in evaluation for underlying malignancy could result in potentially deleterious outcomes, it is prudent to consider systematic screening for malignancy in high-risk populations such as elderly erythroderma patients.

Recent progress in mass spectrometry-based strategies for elucidating protein-protein interactions.

Protein-protein interactions are fundamental to various aspects of cell biology with many protein complexes participating in numerous fundamental biological processes such as transcription, translation and cell cycle. MS-based proteomics techniques are routinely applied for characterising the interactome, such as affinity purification coupled to mass spectrometry that has been used to selectively enrich and identify interacting partners of a bait protein. In recent years, many orthogonal MS-based techniques and approaches have surfaced including proximity-dependent labelling of neighbouring proteins, chemical cross-linking of two interacting proteins, as well as inferring PPIs from the co-behaviour of proteins such as the co-fractionating profiles and the thermal solubility profiles of proteins. This review discusses the underlying principles, advantages, limitations and experimental considerations of these emerging techniques. In addition, a brief account on how MS-based techniques are used to investigate the structural and functional properties of protein complexes, including their topology, stoichiometry, copy number and dynamics, are discussed.

Supportive oncodermatology-a narrative review of its utility and the way forward.

Supportive oncodermatology is an interdisciplinary field, emerging due to increasing dermatological morbidity in patients with cancer and the recognition of the need for greater collaborative and integrated care to improve patient outcomes. These two unique fields (Oncology and Dermatology) may be integrated in various ways, such as through specialised combined clinics, protocols for expedited access, multidisciplinary groups and meetings, and the development of best practices guidelines. This narrative review consolidates the small but growing literature surrounding supportive oncodermatology; discusses the potential benefit and disadvantages, and areas for future research; and suggests a framework for implementation.

Efficacy of targeted education in reducing topical steroid phobia: A randomized clinical trial.

BACKGROUND: Fear of adverse effects of corticosteroids is common in dermatology and results in medication nonadherence. OBJECTIVE: To study the efficacy of targeted education in reducing topical steroid phobia. METHODS: In this double-blinded, randomized controlled trial, participants in the intervention arm were presented with an educational video and patient information leaflet targeting common misconceptions of topical corticosteroids. Steroid phobia was assessed with the topical corticosteroid phobia (TOPICOP) scale, medication adherence with the Elaboration d'un outil d'evaluation de l'observance des traitements medicamenteux (ECOB) score, and quality of life with the Dermatology Life Quality Index (DLQI). RESULTS: The study randomized 275 patients. The mean TOPICOP score in the intervention arm decreased (improved) from 41.9 (SD, 17.4) to 37.1 (SD, 20.0) and to 33.8 (SD, 19.0) at 1 month and 3 months, respectively, with the reduction arising from the knowledge domain but not the fears and behaviors domain. This remained statistically significant after adjusting for demographic confounding with an expected reduction of 4.22 points (P = .031). After accounting for demographic factors, there was no statistical difference in medication adherence and quality of life. Limitations include the exclusion of non-English-speaking patients. CONCLUSION: Targeted education at a single time point improved the TOPICOP score primarily in the knowledge domain but not in the fear domain.

Proteome-wide drug and metabolite interaction mapping by thermal-stability profiling.

Thermal stabilization of proteins after ligand binding provides an efficient means to assess the binding of small molecules to proteins. We show here that in combination with quantitative mass spectrometry, the approach allows for the systematic survey of protein engagement by cellular metabolites and drugs. We profiled the targets of the drugs methotrexate and (S)-crizotinib and the metabolite 2'3'-cGAMP in intact cells and identified the 2'3'-cGAMP cognate transmembrane receptor STING, involved in immune signaling.

The RNA-binding protein HuR/ELAVL1 regulates IFN-ß mRNA abundance and the type I IFN response.

Secretion of type I interferon (IFN) is the first cellular reaction to invading pathogens. Despite the protective function of these cytokines, an excessive response to their action can contribute to serious pathologies, such as autoimmune diseases. Transcripts of most cytokines contain adenylate-uridylate (A/U)-rich elements (AREs) that make them highly unstable. RNA-binding proteins (RBPs) are mediators of the regulatory mechanisms that determine the fate of mRNAs containing AREs. Here, we applied an affinity proteomic approach and identified lethal, abnormal vision, drosophila-like 1 (ELAVL1)/Hu antigen R (HuR) as the predominant RBP of the IFN-ß mRNA ARE. Reduced expression or chemical inhibition of HuR severely hampered the type I IFN response in various cell lines and fibroblast-like synoviocytes isolated from joints of rheumatoid arthritis patients. These results define a role for HuR as a potent modulator of the type I IFN response. Taken together, HuR could be used as therapeutic target for diseases where type I IFN production is exaggerated.

Does PEEK/HA Enhance Bone Formation Compared With PEEK in a Sheep Cervical Fusion Model?

BACKGROUND: Polyetheretherketone (PEEK) has a wide range of clinical applications but does not directly bond to bone. Bulk incorporation of osteoconductive materials including hydroxyapatite (HA) into the PEEK matrix is a potential solution to address the formation of a fibrous tissue layer between PEEK and bone and has not been tested. QUESTIONS/PURPOSES: Using in vivo ovine animal models, we asked: (1) Does PEEK-HA improve cortical and cancellous bone ongrowth compared with PEEK? (2) Does PEEK-HA improve bone ongrowth and fusion outcome in a more challenging functional ovine cervical fusion model? METHODS: The in vivo responses of PEEK-HA Enhanced and PEEK-OPTIMA® Natural were evaluated for bone ongrowth in the form of dowels implanted in the cancellous and cortical bone of adult sheep and examined at 4 and 12 weeks as well as interbody cervical fusion at 6, 12, and 26 weeks. The bone-implant interface was evaluated with radiographic and histologic endpoints for a qualitative assessment of direct bone contact of an intervening fibrous tissue later. Gamma-irradiated cortical allograft cages were evaluated as well. RESULTS: Incorporating HA into the PEEK matrix resulted in more direct bone apposition as opposed to the fibrous tissue interface with PEEK alone in the bone ongrowth as well as interbody cervical fusions. No adverse reactions were found at the implant-bone interface for either material. Radiography and histology revealed resorption and fracture of the allograft devices in vivo. CONCLUSIONS: Incorporating HA into PEEK provides a more favorable environment than PEEK alone for bone ongrowth. Cervical fusion was improved with PEEK-HA compared with PEEK alone as well as allograft bone interbody devices. CLINICAL RELEVANCE: Improving the bone-implant interface with a PEEK device by incorporating HA may improve interbody fusion results and requires further clinical studies.

Stem cell research points the way to the cell of origin for intracranial germ cell tumours.

Germ cell tumours found in the brain (intracranial GCTs) are a very unusual class of tumour for two reasons. First, they include a very diverse range of histological subtypes classified together due to their proposed common cell of origin. Second, this proposed cell of origin, the germ cell progenitor, would not normally be found in the tissue where these tumours arise. This is in contrast to all other primary brain tumours, in which the cell of origin is believed to be a brain cell. Indeed, no other class of primary cancer arises from a cell from a distant organ. This theory for the origins of intracranial GCTs has been in place for many decades, but recent data arising from studies of induced pluripotency for regenerative medicine raise serious questions about this dogma. Here we review the cellular origins of intracranial GCTs in the light of these new data and reanalyse the existing data on the biology of this unusual class of tumours. Together, these considerations lead us to conclude that the evidence now falls in favour of a model in which these tumours arise from the transformation of endogenous brain cells. This theory should inform future studies of the aetiology of these tumours and so lead the way to animal models in which to study their development and potential biological therapeutics.

Protein painting for structural and binding site analysis via intracellular lysine reactivity profiling with o-phthalaldehyde.

The three-dimensional structure and the molecular interaction of proteins determine their roles in many cellular processes. Chemical protein painting with protein mass spectrometry can identify changes in structural conformations and molecular interactions of proteins including their binding sites. Nevertheless, most current protein painting techniques identify protein targets and binding sites of drugs in vitro using a cell lysate or purified protein. Here, we tested 11 membrane-permeable lysine-reactive chemical probes for intracellular covalent labeling of endogenous proteins, which reveals ortho-phthalaldehyde (OPA) as the most reactive probe in the intracellular environment. An MS workflow and a new data analysis strategy termed RAPID (Reactive Amino acid Profiling by Inverse Detection) was developed to enhance detection sensitivity. RAPID with OPA successfully identified structural changes induced by the allosteric drug TEPP-46 on its target protein PKM2 and was applied to profile the conformation change of the proteome occurring in cells during thermal denaturation. The application of RAPID-OPA on cells treated with geldanamycin, selumetinib, and staurosporine successfully revealed their binding sites on target proteins. Thus, RAPID-OPA for cellular protein painting enables the identification of ligand-binding sites and detection of protein structural changes occurring in cells.

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.

Iron-(Fe3+) dependent reactivation of telomerase drives colorectal cancers.

Over-consumption of iron-rich red meat and hereditary or genetic iron overload are associated with increased risk of colorectal carcinogenesis, yet the mechanistic basis of how metal-mediated signaling leads to oncogenesis remains enigmatic. Using fresh colorectal cancer (CRC) samples we identify Pirin, an iron sensor, that overcomes a rate-limiting step in oncogenesis, by re-activating the dormant human-reverse-transcriptase (hTERT) subunit of telomerase holoenzyme in an iron-(Fe3+)-dependent-manner and thereby drives CRCs. Chemical genetic screens combined with isothermal-dose response fingerprinting and mass-spectrometry identified a small molecule SP2509, that specifically inhibits Pirin-mediated hTERT reactivation in CRCs by competing with iron-(Fe3+) binding. Our findings, first to document how metal ions reactivate telomerase, provide a molecular mechanism for the well-known association between red meat, and increased incidence of CRCs. Small molecules like SP2509 represent a novel modality to target telomerase that acts as driver of 90% human cancers and is yet to be targeted in clinic.

A mitotic phosphorylation feedback network connects Cdk1, Plk1, 53BP1, and Chk2 to inactivate the G(2)/M DNA damage checkpoint.

DNA damage checkpoints arrest cell cycle progression to facilitate DNA repair. The ability to survive genotoxic insults depends not only on the initiation of cell cycle checkpoints but also on checkpoint maintenance. While activation of DNA damage checkpoints has been studied extensively, molecular mechanisms involved in sustaining and ultimately inactivating cell cycle checkpoints are largely unknown. Here, we explored feedback mechanisms that control the maintenance and termination of checkpoint function by computationally identifying an evolutionary conserved mitotic phosphorylation network within the DNA damage response. We demonstrate that the non-enzymatic checkpoint adaptor protein 53BP1 is an in vivo target of the cell cycle kinases Cyclin-dependent kinase-1 and Polo-like kinase-1 (Plk1). We show that Plk1 binds 53BP1 during mitosis and that this interaction is required for proper inactivation of the DNA damage checkpoint. 53BP1 mutants that are unable to bind Plk1 fail to restart the cell cycle after ionizing radiation-mediated cell cycle arrest. Importantly, we show that Plk1 also phosphorylates the 53BP1-binding checkpoint kinase Chk2 to inactivate its FHA domain and inhibit its kinase activity in mammalian cells. Thus, a mitotic kinase-mediated negative feedback loop regulates the ATM-Chk2 branch of the DNA damage signaling network by phosphorylating conserved sites in 53BP1 and Chk2 to inactivate checkpoint signaling and control checkpoint duration.

Biomechanical Comparison of Cortical Lag Screws and Cortical Position Screws for Their Generation of Interfragmentary Compression and Area of Compression in Simulated Lateral Humeral Condylar Fractures.

OBJECTIVE: The aim of this study was to compare the interfragmentary compressive force and area of compression generated by cortical screws inserted as either a lag screw or position screw in simulated lateral humeral condylar fractures. STUDY DESIGN: Ex vivo biomechanical study. MATERIALS AND METHODS: Thirteen pairs of cadaveric humeri from skeletally mature Merinos with simulated lateral humeral condylar fractures were used. Pressure sensitive film was inserted into the interfragmentary interface prior to fracture reduction with fragment forceps. A cortical screw was inserted as a lag screw or a position screw and tightened to 1.8Nm. Interfragmentary compression and area of compression were quantified and compared between the two treatments groups at three time points. RESULTS: After fracture reduction using fragment forceps (Time point 1: T1), there was no significant difference in interfragmentary compression and area of compression between the two treatments. A combination of fragment forceps and a cortical screw inserted as a lag screw (Time point 2: T2) produced significantly greater interfragmentary compression and area of compression compared with the same screw inserted as a positional screw. After removal of the fragment forceps, leaving only the cortical screw (Time point 3: T3), both the interfragmentary compression and area of compression remain significantly greater in the lag screw group. CONCLUSION: Lag screws generate a greater force of compression and area of compression compared with position screws in this mature ovine humeral condylar fracture model.

A partially shared joint clustering framework for detecting protein complexes from multiple state-specific signed interaction networks.

Detecting protein complexes is critical for studying cellular organizations and functions. The accumulation of protein-protein interaction (PPI) data enables the identification of protein complexes computationally. Although a great number of computational methods have been proposed to identify protein complexes from PPI networks, most of them ignore the signs of PPIs that reflect the ways proteins interact (activation or inhibition). As not all PPIs imply co-complex relationships, taking into account the signs of PPIs can benefit the identification of protein complexes. Moreover, PPI networks are not static, but vary with the change of cell states or environments. However, existing methods are primarily designed for single-network clustering, and rarely consider joint clustering of multiple PPI networks. In this study, we propose a novel partially shared signed network clustering (PS-SNC) model for identifying protein complexes from multiple state-specific signed PPI networks jointly. PS-SNC can not only consider the signs of PPIs, but also identify the common and unique protein complexes in different states. Experimental results on synthetic and real datasets show that our PS-SNC model can achieve better performance than other state-of-the-art protein complex detection methods. Extensive analysis on real datasets demonstrate the effectiveness of PS-SNC in revealing novel insights about the underlying patterns of different cell lines.