ALK-positive NSCLC patients demonstrate initial responses to ALK tyrosine kinase inhibitor (TKI) treatments, but eventually develop resistance, causing rapid tumor relapse and poor survival rates. Growing evidence suggests that the combination of drug and immune therapies greatly improves patient survival; however, due to the low immunogenicity of the tumors, ALK-positive patients do not respond to currently available immunotherapies. Tumor-associated macrophages (TAMs) play a crucial role in facilitating lung cancer growth by suppressing tumoricidal immune activation and absorbing chemotherapeutics. However, they can also be programmed toward a pro-inflammatory tumor suppressive phenotype, which represents a highly active area of therapy development. Iron loading of TAMs can achieve such reprogramming correlating with an improved prognosis in lung cancer patients. We previously showed that superparamagnetic iron oxide nanoparticles containing core-cross-linked polymer micelles (SPION-CCPMs) target macrophages and stimulate pro-inflammatory activation. Here, we show that SPION-CCPMs stimulate TAMs to secrete reactive nitrogen species and cytokines that exert tumoricidal activity. We further show that SPION-CCPMs reshape the immunosuppressive Eml4-Alk lung tumor microenvironment (TME) toward a cytotoxic profile hallmarked by the recruitment of CD8(+) T cells, suggesting a multifactorial benefit of SPION-CCPM application. When intratracheally instilled into lung cancer-bearing mice, SPION-CCPMs delay tumor growth and, after first line therapy with a TKI, halt the regrowth of relapsing tumors. These findings identify SPIONs-CCPMs as an adjuvant therapy, which remodels the TME, resulting in a delay in the appearance of resistant tumors.

Precision oncology has revolutionized the treatment of ALK-positive lung cancer with targeted therapies. However, an unmet clinical need still to address is the treatment of refractory tumors that contain drug-induced resistant mutations in the driver oncogene or exhibit resistance through the activation of diverse mechanisms. In this study, we established mouse tumor-derived cell models representing the two most prevalent EML4-ALK variants in human lung adenocarcinomas and characterized their proteomic profiles to gain insights into the underlying resistance mechanisms. We showed that Eml4-Alk variant 3 confers a worse response to ALK inhibitors, suggesting its role in promoting resistance to targeted therapy. In addition, proteomic analysis of brigatinib-treated cells revealed the upregulation of SRC kinase, a protein frequently activated in cancer. Co-targeting of ALK and SRC showed remarkable inhibitory effects in both ALK-driven murine and ALK-patient-derived lung tumor cells. This combination induced cell death through a multifaceted mechanism characterized by profound perturbation of the (phospho)proteomic landscape and a synergistic suppressive effect on the mTOR pathway. Our study demonstrates that the simultaneous inhibition of ALK and SRC can potentially overcome resistance mechanisms and enhance clinical outcomes in ALK-positive lung cancer patients.One Sentence SummaryCo-targeting ALK and SRC enhances ALK inhibitor response in lung cancer by affecting the proteomic profile, offering hope for overcoming resistance and improving clinical outcomes.

Human plasma is routinely collected during clinical care and constitutes a rich source of biomarkers for diagnostics and patient stratification. Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is a key method for plasma biomarker discovery, but the high dynamic range of plasma proteins poses significant challenges for MS analysis and data processing. To benchmark the quantitative performance of neat plasma analysis, we generated a multispecies sample set based on a human tryptic plasma digest containing varying low level spike-ins of yeast and E. coli tryptic proteome digests, termed PYE. The sample set was distributed across twelve different sites and analysed on state-of-the-art LC-MS platforms in data-dependent (DDA) and data-independent acquisition (DIA) modes, resulting in a total of 1,116 individual LC-MS runs. Centralized data analysis showed that DIA methods outperform DDA-based approaches regarding identifications, data completeness, accuracy, and precision. DIA achieved excellent technical reproducibility, as demonstrated by coefficients of variation (CVs) between 1.5% and 4.6% at protein level. Comparative analysis of different setups clearly shows a high overlap in identified proteins and proves that accurate and precise quantitative measurements are feasible across multiple sites, even in a complex matrix such as plasma, using state-of-the-art instrumentation. The collected dataset, including the PYE sample set and strategy presented, serves as a valuable resource for optimizing the accuracy and reproducibility of LC-MS and bioinformatic workflows for clinical plasma proteome analysis.

Prerequisite for a successful proteomics experiment is a high-quality lysis of the sample of interest, resulting in a large number of identified proteins as well as a high coverage of protein sequences. Therefore, the choice of suitable lysis conditions is crucial. Many buffers were previously employed in proteomics studies, yet a comprehensive comparison of lysate preparation conditions was so far missing. In this study, we compared the efficiency of four commonly used lysis buffers, containing the agents NP40, SDS, urea or GdnHCl, in four different types of biological samples (suspension and adherent cell lines, primary mouse cells and mouse liver tissue). After liquid chromatography-mass spectrometry (LC-MS) measurement and MaxQuant analysis, we compared chromatograms, intensities, number of identified proteins and the localization of the identified proteins. Overall, SDS emerged as the most reliable reagent, ensuring stable performance and reproducibility across diverse samples. Furthermore, our data advocated for a dual-sample lysis approach, including that the resulting pellet is lysed again after the initial lysis with a urea lysis buffer and subsequently both lysates are combined for a single LC-MS run to maximize the proteome coverage. However, none of the investigated lysis buffers proved to be superior in every category, indicating that the lysis buffer of choice depends on the proteins of interest and on the biological question. Further, we demonstrated with our systematic studies the establishment of conditions that allows to perform global proteomics and affinity purification-based interactome characterization from the same lysate. In sum our results provide guidance for the best-suited lysis buffer for mass spectrometry-based proteomics depending on the question of interest.### Competing Interest StatementThe authors have declared no competing interest.

Chronic liver diseases are worldwide on the rise. Due to the rapidly increasing incidence, in particular in Western countries, metabolic dysfunction-associated steatotic liver disease (MASLD) is gaining importance as the disease can develop into hepatocellular carcinoma. Lipid accumulation in hepatocytes has been identified as the characteristic structural change in MASLD development, but molecular mechanisms responsible for disease progression remained unresolved. Here, we uncover in primary hepatocytes from a preclinical model fed with a Western diet (WD) an increased basal MET phosphorylation and a strong downregulation of the PI3K-AKT pathway. Dynamic pathway modeling of hepatocyte growth factor (HGF) signal transduction combined with global proteomics identifies that an elevated basal MET phosphorylation rate is the main driver of altered signaling leading to increased proliferation of WD-hepatocytes. Model-adaptation to patient-derived hepatocytes reveal patient-specific variability in basal MET phosphorylation, which correlates with patient outcome after liver surgery. Thus, dysregulated basal MET phosphorylation could be an indicator for the health status of the liver and thereby inform on the risk of a patient to suffer from liver failure after surgery.

The human liver has a remarkable capacity to regenerate and thus compensate over decades for fibrosis caused by toxic chemicals, drugs, alcohol, or malnutrition. To date, no protective mechanisms have been identified that help the liver tolerate these repeated injuries. In this study, we revealed dysregulation of lipid metabolism and mild inflammation as protective mechanisms by studying longitudinal multi-omic measurements of liver fibrosis induced by repeated CCl4 injections in mice (n = 45). Based on comprehensive proteomics, transcriptomics, blood- and tissue-level profiling, we uncovered three phases of early disease development-initiation, progression, and tolerance. Using novel multi-omic network analysis, we identified multi-level mechanisms that are significantly dysregulated in the injury-tolerant response. Public data analysis shows that these profiles are altered in human liver diseases, including fibrosis and early cirrhosis stages. Our findings mark the beginning of the tolerance phase as the critical switching point in liver response to repetitive toxic doses. After fostering extracellular matrix accumulation as an acute response, we observe a deposition of tiny lipid droplets in hepatocytes only in the Tolerant phase. Our comprehensive study shows that lipid metabolism and mild inflammation may serve as biomarkers and are putative functional requirements to resist further disease progression.

Background: Macrophages play an important role in maintaining liver homeostasis and regeneration. However, it is not clear to what extent the different macrophage populations of the liver differ in terms of their activation state and which other liver cell populations may play a role in regulating the same. Methods: Reverse transcription PCR, flow cytometry, transcriptome, proteome, secretome, single cell analysis, and immunohistochemical methods were used to study changes in gene expression as well as the activation state of macrophages in vitro and in vivo under homeostatic conditions and after partial hepatectomy. Results: We show that F4/80 + /CD11b hi /CD14 hi macrophages of the liver are recruited in a C-C motif chemokine receptor (CCR2)–dependent manner and exhibit an activation state that differs substantially from that of the other liver macrophage populations, which can be distinguished on the basis of CD11b and CD14 expressions. Thereby, primary hepatocytes are capable of creating an environment in vitro that elicits the same specific activation state in bone marrow–derived macrophages as observed in F4/80 + /CD11b hi /CD14 hi liver macrophages in vivo . Subsequent analyses, including studies in mice with a myeloid cell–specific deletion of the TGF-β type II receptor, suggest that the availability of activated TGF-β and its downregulation by a hepatocyte-conditioned milieu are critical. Reduction of TGF-βRII-mediated signal transduction in myeloid cells leads to upregulation of IL-6, IL-10, and SIGLEC1 expression, a hallmark of the activation state of F4/80 + /CD11b hi /CD14 hi macrophages, and enhances liver regeneration. Conclusions: The availability of activated TGF-β determines the activation state of specific macrophage populations in the liver, and the observed rapid transient activation of TGF-β may represent an important regulatory mechanism in the early phase of liver regeneration in this context.

Type I interferons (IFNs) play a central role not only in innate immunity against viral infection, but also in the antitumour response, e.g. through a direct impact on cell proliferation. Particularly for cancer arising in the context of chronic inflammation, constant exposure to IFNs may constitute a strong selective pressure during tumour evolution. Expansion of neoplastic subclones resistant to the antiproliferative effects of IFNs may contribute to immunoediting of tumours, leading to more aggressive disease. Experimental evidence for this development of IFN-insensitivity has been scarce and its molecular mechanism is unclear. In this study we demonstrate that six weeks exposure of cells to IFN-β in vitro reduces their sensitivity to its antiproliferative effects, and that this phenotype was stable for up to four weeks. Furthermore, we observed substantial differences in cellular sensitivity to growth inhibition by IFN-β in a panel of ten different liver cancer cell lines, most prominently in a pair of highly dedifferentiated cell lines, and least in cells from well-differentiated tumours. In both, long-term IFN selection and in dedifferentiated tumour cell lines, we found IFNAR2 expression to be substantially reduced, suggesting the receptor complex to be a sensitive target amenable to immunoediting. Beyond new insights into possible molecular processes in tumour evolution, these findings might prove valuable for the development of biomarkers allowing to stratify tumours for their sensitivity to IFN treatment in the context of patient tailored therapies.

ABSTRACTThe liver has a remarkable capacity to regenerate and thus compensates for repeated injuries through toxic chemicals, drugs, alcohol or malnutrition for decades. However, largely unknown is how and when alterations in the liver occur due to tolerable damaging insults. To that end, we induced repeated liver injuries over ten weeks in a mouse model injecting carbon tetrachloride (CCl4) twice a week. We lost 10% of the study animals within the first six weeks, which was accompanied by a steady deposition of extracellular matrix (ECM) regardless of metabolic activity of the liver. From week six onwards, all mice survived, and in these mice ECM deposition was rather reduced, suggesting ECM remodeling as a liver response contributing to better coping with repeated injuries. The data of time-resolved paired transcriptome and proteome profiling of 18 mice was subjected to multi-level network inference, using Knowledge guided Multi-Omics Network inference (KiMONo), identified multi-level key markers exclusively associated with the injury-tolerant liver response. Interestingly, pathways of cancer and inflammation were lighting up and were validated using independent data sets compiled of 1034 samples from publicly available human cohorts. A yet undescribed link to lipid metabolism in this damage-tolerant phase was identified. Immunostaining revealed an unexpected accumulation of small lipid droplets (microvesicular steatosis) in parallel to a recovery of catabolic processes of the liver to pre-injury levels. Further, mild inflammation was experimentally validated. Taken together, we identified week six as a critical time point to switch the liver response program from an acute response that fosters ECM accumulation to a tolerant “survival” phase with pronounced deposition of small lipid droplets in hepatocytes potentially protecting against the repetitive injury with toxic chemicals. Our data suggest that microsteatosis formation plus a mild inflammatory state represent biomarkers and probably functional liver requirements to resist chronic damage.Graphical abstractThe datasets generated via transcriptomics, proteomics as well as blood, histopathological and biochemical analysis were analyzed in an independent and integrative manner. The independent analysis was performed via state-of-the-art statistical approaches i.e. differential and consistently regulated genes and proteins. Combining the results identified three fibrosis phases. Using the KiMONo algorithm, a fibrosis specific multi-omic network was inferred. Within this network we identified several nodes connecting phase III specific features forming 13 distinct multi-omic modules suggesting a tolerance scheme. Some of these modules were experimentally validated and compared to 11 independent human studies of various liver diseases.

Erythropoietin (Epo) ensures survival and proliferation of colony-forming unit erythroid (CFU-E) progenitor cells and their differentiation to hemoglobin-containing mature erythrocytes. A lack of Epo-induced responses causes embryonic lethality, but mechanisms regulating the dynamic communication of cellular alterations to the organismal level remain unresolved. By time-resolved transcriptomics and proteomics, we show that Epo induces in CFU-E cells a gradual transition from proliferation signature proteins to proteins indicative for differentiation, including heme-synthesis enzymes. In the absence of the Epo receptor (EpoR) in embryos, we observe a lack of hemoglobin in CFU-E cells and massive iron overload of the fetal liver pointing to a miscommunication between liver and placenta. A reduction of iron-sulfur cluster-containing proteins involved in oxidative phosphorylation in these embryos leads to a metabolic shift toward glycolysis. This link connecting erythropoiesis with the regulation of iron homeostasis and metabolic reprogramming suggests that balancing these interactions is crucial for protection from iron intoxication and for survival.

Changes that macrophage populations of the liver undergoes in terms of composition and activation state in the context of liver regeneration are incompletely understood. This and the question of what influence cell populations that significantly influence the microenvironment of the liver, such as hepatocytes, have on the activation state of liver macrophages and which mediators are relevant in this context was the aim of the present investigations.

Summary:Mass spectrometry-based proteomics is increasingly employed in biology and medicine. To generate reliable information from large datasets and ensure comparability of results, it is crucial to implement and standardize the quality control of the raw data, the data processing steps and the statistical analyses. MSPypeline provides a platform for importing MaxQuant output tables, generating quality control reports, data preprocessing including normalization and performing exploratory analyses by statistical inference plots. These standardized steps assess data quality, provide customizable figures and enable the identification of differentially expressed proteins to reach biologically relevant conclusions.Availability and implementation:The source code is available under the MIT license at https://github.com/siheming/mspypeline with documentation at https://mspypeline.readthedocs.io. Benchmark mass spectrometry data are available on ProteomeXchange (PXD025792).Supplementary information:Supplementary data are available at Bioinformatics Advances online.

Metabolomic and proteomic analyses of human plasma and serum samples harbor the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implementing a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4°C) are imperative for metabolic profiling, the analyzed proteomics data set showed variability when exposed to temperatures of 4°C for more than 2 h, highlighting the need for compromises in a combined analysis. We formalized a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonized standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies, we suggest keeping blood samples up to 2 h on ice (4°C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open-source R package allowing the systematic scoring of proteomics and metabolomics data sets to assess the stability of plasma and serum samples.