Proteomics and metabolomics identify molecular mechanisms of aging potentially predisposing for chronic lymphocytic leukemia

Single-cell analysis of a bi-clonal chronic lymphocytic leukemia reveals two clones with distinct gene expression pattern

Dual productive B-cell receptor (BCR) rearrangements have been repeatedly reported for chronic lymphocytic leukemia (CLL), but the standard population-based PCR analyses cannot distinguish whether these are bi-clonal CLL, or a monoclonal CLL with bi-allelic productive rearrangements. We investigated CLL cells by combined single-cell RNA and BCR sequencing. We identified two CLL clones using different immunoglobulin (Ig) heavy-chain V region genes (IGHV) genes and distinct Ig λ light chains. One clone is classified as Ig unmutated the other as mutated. The two CLL clones have distinct transcriptomes: Numerous genes were differentially expressed, with genes typical for unmutated or mutated CLL showing the expected representation in the two clones. Using PCR, cloning and Sanger sequencing of the IGHV rearrangements we detected both CLL clones over a period of three years without clinical progression of the CLL and thus giving insights into the disease biology of multi-clonal CLL.

Acute Myeloid Leukaemia and Acute Lymphoblastic Leukaemia Classification and Metabolic Characteristics for Informing and Advancing Treatment

Acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL) remain significant challenges in haematological oncology. This review examines the pathophysiology, classification, and risk stratification of these aggressive malignancies, emphasising their impact on treatment strategies and prognosis. We discuss current standard-of-care treatments, including chemotherapy regimens and targeted therapies, while addressing the associated adverse effects and hypersensitivity reactions. Delving into the metabolic characteristics and vulnerabilities of leukaemia cells, the review highlights the key differences between lymphoid and myeloid leukaemia and how metabolic insights can be utilised for therapeutic purposes, with special focus on asparaginase therapy and its potential for improvement in both ALL and AML treatment. The review conveys the importance of personalised medicine approaches based on individual metabolic profiles and the challenges posed by metabolic heterogeneity and plasticity in leukaemia cells. Combining molecular and metabolic profiling can enhance and refine treatment strategies for acute leukaemia, potentially improving patient outcomes and quality of life. However, integrating these into routine clinical practice requires overcoming various practical, technical, and logistical issues.

Identification of DLAT as a potential therapeutic target via a novel cuproptosis-related gene signature for the prediction of liver cancer prognosis

BACKGROUND

The prognosis for liver cancer (LC) is dismal. Researchers recently discovered cuproptosis, a novel form of controlled cell death whose expression in LC and prognosis are unclear. This study reveals a gene signature to predict LC prognosis.

METHODS

RNA and clinical data for 371 LC patients were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were identified by comparing cancerous and normal samples. Genes linked to overall survival (OS) were found using univariate Cox regression and least absolute shrinkage and selection operator (LASSO). The gene signature was validated across all patients. Gene expression and clinical traits were analyzed, and Kaplan-Meier (KM) curves were generated for high- and low-risk groups. DEGs were used for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), immune infiltration, and drug prediction analyses. DLAT's functions were assessed using real-time polymerase chain reaction (RT-PCR), transwell invasion, Cell Counting Kit-8 (CCK-8), colony formation, and drug resistance assays.

RESULTS

A total of 12 cuproptosis regulators were discovered in LC and normal liver tissues. A 3-gene signature based on LASSO Cox regression was utilized to categorize TCGA LC patients into low- and high-risk categories. Low-risk patients exhibited better survival than high-risk patients (P<0.05). Tumor grade, stage, and T stage differed between high- and low-risk groups. Long-term prognosis was well predicted by male subgroup survival studies. We predicted LC patient survival using sex, tumor grade, tumor stage, and risk score. Functional enrichment showed that extracellular matrix (ECM) architecture, channel function, and tumor-associated pathways were enriched in LC, suggesting that cancer related functions were collected. Immune microenvironment inhibition was found in the high-risk group suggesting that immunosuppression was closely related. We also discovered five small molecules that could be potentially useful for LC treatment. DLAT was discovered to promote the migration and proliferation of LC cells and is connected to drug resistance as a prognostic marker.

CONCLUSIONS

Cuproptosis-related genes contribute to tumor development and can aid the prediction of LC patient prognosis. DLAT is a potential LC prognostic and therapeutic target.

Metabolomics for hematologic malignancies: Advances and perspective

With the use of advanced technology, metabolomics allows for a thorough examination of metabolites and other small molecules found in biological specimens, blood, and tissues. In recent years, metabolomics has been recognized that is closely related to the development of malignancies in the hematological system. Alterations in metabolomic pathways and networks are important in the pathogenesis of hematologic malignancies and can also provide a theoretical basis for early diagnosis, efficacy evaluation, accurate staging, and individualized targeted therapy. In this review, we summarize the progress of metabolomics, including glucose metabolism, amino acid metabolism, and lipid metabolism in lymphoma, myeloma, and leukemia through specific mechanisms and pathways. The research of metabolomics gives a new insight and provides therapeutic targets for the treatment of patients with hematologic malignancies.

Integrative Analysis of Multi-Omics Data to Identify Deregulated Molecular Pathways and Druggable Targets in Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia (CLL) is the most common B-cell malignancy in the Western world, characterized by frequent relapses despite temporary remissions. Our study integrated publicly available proteomic, transcriptomic, and patient survival datasets to identify key differences between healthy and CLL samples. We exposed approximately 1000 proteins that differentiate healthy from cancerous cells, with 608 upregulated and 415 downregulated in CLL cases. Notable upregulated proteins include YEATS2 (an epigenetic regulator), PIGR (Polymeric immunoglobulin receptor), and SNRPA (a splicing factor), which may serve as prognostic biomarkers for this disease. Key pathways implicated in CLL progression involve RNA processing, stress resistance, and immune response deficits. Furthermore, we identified three existing drugs-Bosutinib, Vorinostat, and Panobinostat-for potential further investigation in drug repurposing in CLL. We also found limited correlation between transcriptomic and proteomic data, emphasizing the importance of proteomics in understanding gene expression regulation mechanisms. This generally known disparity highlights once again that mRNA levels do not accurately predict protein abundance due to many regulatory factors, such as protein degradation, post-transcriptional modifications, and differing rates of translation. These results demonstrate the value of integrating omics data to uncover deregulated proteins and pathways in cancer and suggest new therapeutic avenues for CLL.

Targeting sphingolipid metabolism in chronic lymphocytic leukemia

Elevated levels of circulating C16:0 glucosylceramides (GluCer) and increased mRNA expression of UDP-glucose ceramide glycosyltransferase (UGCG), the enzyme responsible for converting ceramides (Cer) to GluCer, represent unfavorable prognostic markers in chronic lymphocytic leukemia (CLL) patients. To evaluate the therapeutic potential of inhibiting GluCer synthesis, we genetically repressed the UGCG pathway using in vitro models of leukemic B cells, in addition to UGCG pharmacological inhibition with approved drugs such as eliglustat and ibiglustat, both individually and in combination with ibrutinib, assessed in cell models and primary CLL patient cells. Cell viability, apoptosis, and proliferation were evaluated in vitro, and survival and apoptosis were examined ex vivo. UGCG inhibition efficacy was confirmed by quantifying intracellular sphingolipid levels through targeted lipidomics using mass spectrometry. Other inhibitors of sphingolipid biosynthesis pathways were similarly assessed. Blocking UGCG significantly decreased cell viability and proliferation, highlighting the oncogenic role of UGCG in CLL. The efficient inhibition of UGCG was confirmed by a significant reduction in GluCer intracellular levels. The combination of UGCG inhibitors with ibrutinib demonstrated synergistic effect. Inhibitors that target alternative pathways within sphingolipid metabolism, like sphingosine kinases inhibitor SKI-II, also demonstrated promising therapeutic effects both alone and when used in combination with ibrutinib, reinforcing the oncogenic impact of sphingolipids in CLL cells. Targeting sphingolipid metabolism, especially the UGCG pathway, represents a promising therapeutic strategy and as a combination therapy for potential treatment of CLL patients, warranting further investigation.

Bioinformatics prediction and experimental verification identify a cuproptosis-related gene signature as prognosis biomarkers of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) of which its prognostic prediction is still unclarified is a highly heterogeneous disease. Cuproptosis is a form of cell death that depends on copper regulation. Whether the cuproptosis-related genes can be the prognostic indicators of HCC is yet to be elucidated. The aim of this study is to investigate whether cuproptosis-related genes play a role in HCC and can be used as a diagnostic index to predict the occurrence of liver cancer.

Methods

We downloaded HCC patients' gene expression profiles and their corresponding clinical data from a public database. To screen data, we used single factor Cox regression analysis, meanwhile, polymerase chain reaction (PCR) was used for the verification. After that, the risk score was calculated and the relationship between risk score and clinical factors was analyzed. Besides, a nomogram map was constructed for predicting the prognosis of HCC, and calibration map and decision curve analysis (DCA) map were used to test the model.

Results

Compared to the high expression group of four cuproptosis-related genes, the low expression group showed better overall survival (OS) [hazard ratio (HR) =2.58; 95% confidence interval (CI): 1.72-3.89, P<0.01]. The expression of the four cuproptosis-relate genes increased in liver cancer cell lines compared to liver cell lines (P<0.05). Based on these four genes, we calculated the risk score and divided them into two groups as high-risk group and low-risk group. The risk factor map showed the high-risk group had shorter survival time and the four genes were highly expressed. The area under curve (AUC) of receiver operating characteristic (ROC) prediction curve for the first year was 0.726. Risk scores were closely related to clinical factors and immune cells. Finally, we constructed a nomogram for predicting the prognosis of HCC.

Conclusions

The risk score for cuproptosis-related genes was established and involved in the construction of the nomogram, providing a new perspective on the prognosis and copper metabolism of HCC.

Multiple omics levels of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a lymphoproliferative malignancy characterized by the proliferation of functionally mature but incompetent B cells. It is the most prevalent type of leukemia in Western populations, accounting for approximately 25% of new leukemia cases. While recent advances, such as ibrutinib and venetoclax treatment have improved patient outlook, aggressive forms of CLL such as Richter transformation still pose a significant challenge. This discrepancy may be due to the heterogeneity of factors contributing to CLL development at multiple -omics levels. However, information on the omics of CLL is fragmented, hindering multi-omics-based research into potential treatment options. To address this, we aggregated and presented a selection of important aspects of various omics levels of the disease in this review. The purpose of the present literature analysis is to portray examples of CLL studies from different omics levels, including genomics, epigenomics, transcriptomics, epitranscriptomics, proteomics, epiproteomics, metabolomics, glycomics and lipidomics, as well as those identified by multi-omics approaches. The review includes the list of 102 CLL-associated genes with relevant genomics information. While single-omics studies yield substantial and useful data, they omit a significant level of complex biological interplay present in the disease. As multi-omics studies integrate several different layers of data, they may be better suited for complex diseases such as CLL and have thus far yielded promising results. Future multi-omics studies may assist clinicians in improved treatment choices based on CLL subtypes as well as allow the identification of novel biomarkers and targets for treatments.

Untargeted metabolomics identifies metabolic dysregulation of sphingolipids associated with aggressive chronic lymphocytic leukaemia and poor survival

BACKGROUND

Metabolic dependencies of chronic lymphocytic leukaemia (CLL) cells may represent new personalized treatment approaches in patients harbouring unfavourable features.

METHODS

Here, we used untargeted metabolomics and lipidomics analyses to isolate metabolomic features associated with aggressive CLL and poor survival outcomes. We initially focused on profiles associated with overexpression of the adverse metabolic marker glycosyltransferase (UGT2B17) associated with poor survival and drug resistance.

RESULTS

Leukaemic B-cell metabolomes indicated a significant perturbation in lipids, predominantly bio-active sphingolipids. Expression of numerous enzyme-encoding genes of sphingolipid biosynthesis pathways was significantly associated with shorter patient survival. Targeted metabolomics further exposed higher circulating levels of glucosylceramides (C16:0 GluCer) in CLL patients relative to healthy donors and an aggressive cancer biology. In multivariate analyses, C16:0 GluCer and sphinganine were independent prognostic markers and were inversely linked to treatment-free survival. These two sphingolipid species function as antagonistic mediators, with sphinganine being pro-apoptotic and GluCer being pro-proliferative, tested in leukemic B-CLL cell models. Blocking GluCer synthesis using ceramide glucosyltransferase inhibitors induced cell death and reduced the proliferative phenotype, which further sensitized a leukaemic B-cell model to the anti-leukaemics fludarabine and ibrutinib in vitro.

CONCLUSIONS

Specific sphingolipids may serve as prognostic markers in CLL, and inhibiting enzymatic pathways involved in their biosynthesis has potential as a therapaeutic approach.

Novel Molecular Subtyping Scheme Based on In Silico Analysis of Cuproptosis Regulator Gene Patterns Optimizes Survival Prediction and Treatment of Hepatocellular Carcinoma

BACKGROUND

The liver plays an important role in maintaining copper homeostasis. Copper ion accumulation was elevated in HCC tissue samples. Copper homeostasis is implicated in cancer cell proliferation and angiogenesis. The potential of copper homeostasis as a new theranostic biomarker for molecular imaging and the targeted therapy of HCC has been demonstrated. Recent studies have reported a novel copper-dependent nonapoptotic form of cell death called cuproptosis, strikingly different from other known forms of cell death. The correlation between cuproptosis and hepatocellular carcinoma (HCC) is not fully understood.

MATERIALS AND METHODS

The transcriptomic data of patients with HCC were retrieved from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and were used as a discovery cohort to construct the prognosis model. The gene expression data of patients with HCC retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) databases were used as the validation cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was used to construct the prognosis model. A principal component analysis (PCA) was used to evaluate the overall characteristics of cuproptosis regulator genes and obtain the PC1 and PC2 scores. Unsupervised clustering was performed using the ConsensusClusterPlus R package to identify the molecular subtypes of HCC. Cox regression analysis was performed to identify cuproptosis regulator genes that could predict the prognosis of patients with HCC. The receiver operating characteristics curve and Kaplan-Meier survival analysis were used to understand the role of hub genes in predicting the diagnosis and prognosis of patients, as well as the prognosis risk model. A weighted gene co-expression network analysis (WGCNA) was used for screening the cuproptosis subtype-related hub genes. The functional enrichment analysis was performed using Metascape. The 'glmnet' R package was used to perform the LASSO regression analysis, and the randomForest algorithm was performed using the 'randomForest' R package. The 'pRRophetic' R package was used to estimate the anticancer drug sensitivity based on the data retrieved from the Genomics of Drug Sensitivity in Cancer database. The nomogram was constructed using the 'rms' R package. Pearson's correlation analysis was used to analyze the correlations.

RESULTS

We constructed a six-gene signature prognosis model and a nomogram to predict the prognosis of patients with HCC. The Kaplan-Meier survival analysis revealed that patients with a high-risk score, which was predicted by the six-gene signature model, had poor prognoses (log-rank test p < 0.001; HR = 1.83). The patients with HCC were grouped into three distinct cuproptosis subtypes (Cu-clusters A, B, and C) based on the expression pattern of cuproptosis regulator genes. The patients in Cu-cluster B had poor prognosis (log-rank test p < 0.001), high genomic instability, and were not sensitive to conventional chemotherapeutic treatment compared to the patients in the other subtypes. Cancer cells in Cu-cluster B exhibited a higher degree of the senescence-associated secretory phenotype (SASP), a marker of cellular senescence. Three representative genes, CDCA8, MCM6, and NCAPG2, were identified in patients in Cu-cluster B using WGCNA and the "randomForest" algorithm. A nomogram was constructed to screen patients in the Cu-cluster B subtype based on three genes: CDCA8, MCM6, and NCAPG2.

CONCLUSION

Publicly available databases and various bioinformatics tools were used to study the heterogeneity of cuproptosis in patients with HCC. Three HCC subtypes were identified, with differences in the survival outcomes, genomic instability, senescence environment, and response to anticancer drugs. Further, three cuproptosis-related genes were identified, which could be used to design personalized therapeutic strategies for HCC.

Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation

Background

Anoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) is a malignant disease of the urinary tract and has a strong metastatic potential. To determine whether anoikis-associated genes can predict the prognosis of BLCA accurately, we evaluated the prognostic value of anoikis-associated genes in BLCA and constructed the best model to predict prognosis.

Method

The BLCA transcriptome data were downloaded from TCGA and GEO databases, and genes with differential expression were selected and then clustered using non-negative matrix factorization (NMF). The genes with the most correlation with anoikis were screened and identified using univariate Cox regression, lasso regression, and multivariate Cox regression. The GEO dataset was used for external validation. Nomograms were created based on risk characteristics in combination with clinical variants and the performance of the model was validated with receiver operating characteristic (ROC) curves. The immunotherapeutic significance of this risk score was assessed using the immune phenomenon score (IPS). IC50 values of predictive chemotherapeutic agents were calculated. Finally, we used RT-qPCR to determine the mRNA expression of four genes, CALR, FASN, CASP6, and RAD9A.

Result

We screened 406 tumor samples and 19 normal tissue samples from the TCGA database. Based on anoikis-associated genes, we classified patients into two subtypes (C1 and C2) using NMF method. Subsequently, nine core genes were screened by multiple methods after analysis, which were used to construct risk profiles. The design of nomograms based on risk profiles and clinical variables, ROC, and calibration curves confirmed that the model could well have the ability to predict the survival of BLCA patients at 1, 3, and 5 years. By predicting the IC50 values of chemotherapeutic drugs, it was learned that the high-risk group (HRG) was more susceptible to paclitaxel, gemcitabine, and cisplatin, and the low-risk group (LRG) was more susceptible to veriparib and afatinib.

Conclusion

In summary, the risk score of anoikis-associated genes can be applied as a predictor to predict the prognosis of BLCA in clinical practice.

The evolving use of measurable residual disease in chronic lymphocytic leukemia clinical trials

Measurable residual disease (MRD) status in chronic lymphocytic leukemia (CLL), assessed on and after treatment, correlates with increased progression-free and overall survival benefit. More recently, MRD assessment has been included in large clinical trials as a primary outcome and is increasingly used in routine practice as a prognostic tool, a therapeutic goal, and potentially a trigger for early intervention. Modern therapy for CLL delivers prolonged remissions, causing readout of traditional trial outcomes such as progression-free and overall survival to be inherently delayed. This represents a barrier for the rapid incorporation of novel drugs to the overall therapeutic armamentarium. MRD offers a dynamic and robust platform for the assessment of treatment efficacy in CLL, complementing traditional outcome measures and accelerating access to novel drugs. Here, we provide a comprehensive review of recent major clinical trials of CLL therapy, focusing on small-molecule inhibitors and monoclonal antibody combinations that have recently emerged as the standard frontline and relapse treatment options. We explore the assessment and reporting of MRD (including novel techniques) and the challenges of standardization and provide a comprehensive review of the relevance and adequacy of MRD as a clinical trial endpoint. We further discuss the impact that MRD data have on clinical decision-making and how it can influence a patient's experience. Finally, we evaluate how upcoming trial design and clinical practice are evolving in the face of MRD-driven outcomes.

Cuproptosis-related gene signature stratifies lower-grade glioma patients and predicts immune characteristics

Cuproptosis is the most recently discovered type of regulated cell death and is mediated by copper ions. Studies show that cuproptosis plays a significant role in cancer development and progression. Lower-grade gliomas (LGGs) are slow-growing brain tumors. The majority of LGGs progress to high-grade glioma, which makes it difficult to predict the prognosis. However, the prognostic value of cuproptosis-related genes (CRGs) in LGG needs to be further explored. mRNA expression profiles and clinical data of LGG patients were collected from public sources for this study. Univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model were used to build a multigene signature that could divide patients into different risk groups. The differences in clinical pathological characteristics, immune infiltration characteristics, and mutation status were evaluated in risk subgroups. In addition, drug sensitivity and immune checkpoint scores were estimated in risk subgroups to provide LGG patients with precision medication. We found that all CRGs were differentially expressed in LGG and normal tissues. Patients were divided into high- and low-risk groups based on the risk score of the CRG signature. Patients in the high-risk group had a considerably lower overall survival rate than those in the low-risk group. According to functional analysis, pathways related to the immune system were enriched, and the immune state differed across the two risk groups. Immune characteristic analysis showed that the immune cell proportion and immune scores were different in the different groups. High-risk group was characterized by low sensitivity to chemotherapy but high sensitivity to immune checkpoint inhibitors. The current study revealed that the novel CRG signature was related to the prognosis, clinicopathological features, immune characteristics, and treatment perference of LGG.

Proteogenomics refines the molecular classification of chronic lymphocytic leukemia

Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.

Single-Cell Metabolomics in Hematopoiesis and Hematological Malignancies

Aberrant metabolism contributes to tumor initiation, progression, metastasis, and drug resistance. Metabolic dysregulation has emerged as a hallmark of several hematologic malignancies. Decoding the molecular mechanism underlying metabolic rewiring in hematological malignancies would provide promising avenues for novel therapeutic interventions. Single-cell metabolic analysis can directly offer a meaningful readout of the cellular phenotype, allowing us to comprehensively dissect cellular states and access biological information unobtainable from bulk analysis. In this review, we first highlight the unique metabolic properties of hematologic malignancies and underscore potential metabolic vulnerabilities. We then emphasize the emerging single-cell metabolomics techniques, aiming to provide a guide to interrogating metabolism at single-cell resolution. Furthermore, we summarize recent studies demonstrating the power of single-cell metabolomics to uncover the roles of metabolic rewiring in tumor biology, cellular heterogeneity, immunometabolism, and therapeutic resistance. Meanwhile, we describe a practical view of the potential applications of single-cell metabolomics in hematopoiesis and hematological malignancies. Finally, we present the challenges and perspectives of single-cell metabolomics development.

Deciphering Metabolic Adaptability of Leukemic Stem Cells

Therapeutic targeting of leukemic stem cells is widely studied to control leukemia. An emerging approach gaining popularity is altering metabolism as a potential therapeutic opportunity. Studies have been carried out on hematopoietic and leukemic stem cells to identify vulnerable pathways without impacting the non-transformed, healthy counterparts. While many metabolic studies have been conducted using stem cells, most have been carried out in vitro or on a larger population of progenitor cells due to challenges imposed by the low frequency of stem cells found in vivo. This creates artifacts in the studies carried out, making it difficult to interpret and correlate the findings to stem cells directly. This review discusses the metabolic difference seen between hematopoietic stem cells and leukemic stem cells across different leukemic models. Moreover, we also shed light on the advancements of metabolic techniques and current limitations and areas for additional research of the field to study stem cell metabolism.

Targeting metabolic reprogramming in chronic lymphocytic leukemia

Metabolic reprogramming, fundamentally pivotal in carcinogenesis and progression of cancer, is considered as a promising therapeutic target against tumors. In chronic lymphocytic leukemia (CLL) cells, metabolic abnormalities mediate alternations in proliferation and survival compared with normal B cells. However, the role of metabolic reprogramming is still under investigation in CLL. In this review, the critical metabolic processes of CLL were summarized, particularly glycolysis, lipid metabolism and oxidative phosphorylation. The effects of T cells and stromal cells in the microenvironment on metabolism of CLL were also elucidated. Besides, the metabolic alternation is regulated by some oncogenes and tumor suppressor regulators, especially TP53, MYC and ATM. Thus, the agents targeting metabolic enzymes or signal pathways may impede the progression of CLL. Both the inhibitor of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) statins and the lipoprotein lipase inhibitor orlistat induce the apoptosis of CLL cells. In addition, a series of oxidative phosphorylation inhibitors play important roles in decreasing the proliferation of CLL cells. We epitomized recent advancements in metabolic reprogramming in CLL and discussed their clinical potentiality for innovative therapy options. Metabolic reprogramming plays a vital role in the initiation and progression of CLL. Therapeutic approaches targeting metabolism have their advantages in improving the survival of CLL patients. This review may shed novel light on the metabolism of CLL, leading to the development of targeted agents based on the reshaping metabolism of CLL cells.

Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the main pathological subtype of non-small-cell lung cancer. Endoplasmic reticulum stress (ERS) has been found to be involved in multiple tumor-related biological processes. At present, a comprehensive analysis of ERS-related genes in LUAD is still lacking. A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. Then, LASSO Cox regression was used to construct a prognostic signature. Taking the median of signature score as the threshold, patients were separated into high-risk (HR) group and low-risk (LR) group. Tumor mutation burden (TMB), immune cell infiltration, cancer stem cell infiltration, expression of HLA, and immune checkpoints of the two risk groups were analyzed. TIDE score was used to evaluate the response of the two risk groups to immunotherapy. Finally, the gene expression was verified in clinical tissues with RT-qPCR. An eight-gene signature (ADRB2, AGER, CDKN3, GJB2, SFTPC, SLC2A1, SLC6A4, and SSR4) was constructed. TMB and cancer stem cell infiltration were higher in the HR group than the LR group. TIDE score and expression level of HLA were higher in the LR group than the HR group. Expression level of immune checkpoints, including CD28, CD27, IDO2, and others, were higher in the LR group. Multiple drugs approved by FAD, targeting ERS-related genes, were available for the treatment of LUAD. In summary, we established a stable prognostic model based on ERS-related genes to help the classification of LUAD patients and looked for new treatment strategies from aspects of immunity, tumor mutation, and tumor stem cell infiltration.

The Global Burden of Leukemia and Its Attributable Factors in 204 Countries and Territories: Findings from the Global Burden of Disease 2019 Study and Projections to 2030

Background. Leukemia is a common malignancy that has four main subtypes and is a threat to human health. Understanding the epidemiological status of leukemia and its four main subtypes globally is important for allocating appropriate resources, guiding clinical practice, and furthering scientific research. Methods. Average annual percentage changes (AAPCs) were calculated to estimate the change trends of age-standardized rates (ASRs) from 1990 to 2019 in 204 countries and territories. The risk factors for leukemia death and disability-adjusted life-year (DALY) were also analyzed. In addition, the future trends in ASRs were projected through 2030. Results. The total number of incident cases, deaths, and DALYs from leukemia in 2019 was 0.64, 0.33, and 11.66 million, respectively. Decreasing trends in age-standardized incidence rate (ASIR), the age-standardized death rate (ASDR), and age-standardized DALY rate were detected on a global level while increasing trends in ASIR were detected in the high-sociodemographic index (SDI) regions. The leukemia burden was heavier in males than in females. By cause, acute myeloid leukemia (AML), chronic myeloid leukemia (CML), and chronic lymphocytic leukemia (CLL) were more likely to impose a burden on the elderly, while acute lymphoblastic leukemia (ALL) showed a greater impact in the younger population. A significant positive correlation was observed between SDI and AAPC in ASIR, while SDI was negatively correlated with AAPCs in both ASDR and age-standardized DALY rate. Smoking remained the most significant risk factor associated with leukemia-related death and DALY, especially in males. Similar deaths and DALYs were caused by smoking and high body mass index (BMI) in females. Future projections through 2030 estimated that ASIR and ASDR will continue to increase, while the DALY rate is predicted to decline. Conclusions. Patterns and trends of leukemia burden are correlated with SDI. The estimated contributions to leukemia deaths indicate that timely measures are needed to reduce smoking and obesity.

Proteomic profiling based classification of CLL provides prognostication for modern therapy and identifies novel therapeutic targets

Protein expression for 384 total and post-translationally modified proteins was assessed in 871 CLL and MSBL patients and was integrated with clinical data to identify strategies for improving diagnostics and therapy, making this the largest CLL proteomics study to date. Proteomics identified six recurrent signatures that were highly prognostic of survival and time to first or second treatment at three levels: individual proteins, when grouped into 40 functionally related groups (PFGs), and systemically in signatures (SGs). A novel SG characterized by hairy cell leukemia like proteomics but poor therapy response was discovered. SG membership superseded other prognostic factors (Rai Staging, IGHV Status) and were prognostic for response to modern (BTK inhibition) and older CLL therapies. SGs and PFGs membership provided novel drug targets and defined optimal candidates for Watch and Wait vs. early intervention. Collectively proteomics demonstrates promise for improving classification, therapeutic strategy selection, and identifying novel therapeutic targets.

Human intestinal bitter taste receptors regulate innate immune responses and metabolic regulators in obesity

Bitter taste receptors (taste 2 receptors, TAS2Rs) serve as warning sensors in the lingual system against the ingestion of potentially poisonous food. Here, we investigated the functional role of TAS2Rs in the human gut and focused on their potential to trigger an additional host defense pathway in the intestine. Human jejunal crypts, especially those from individuals with obesity, responded to bitter agonists by inducing the release of antimicrobial peptides (α-defensin 5 and regenerating islet–derived protein 3 α [REG3A]) but also regulated the expression of other innate immune factors (mucins, chemokines) that affected E. coli growth. We found that the effect of aloin on E. coli growth and on the release of the mucus glycoprotein CLCA1, identified via proteomics, was affected by TAS2R43 deletion polymorphisms and thus confirmed a role for TAS2R43. RNA-Seq revealed that denatonium benzoate induced an NRF2-mediated nutrient stress response and an unfolded protein response that increased the expression of the mitokine GDF15 but also ADM2 and LDLR, genes that are involved in anorectic signaling and lipid homeostasis. In conclusion, TAS2Rs in the intestine constitute a promising target for treating diseases that involve disturbances in the innate immune system and body weight control. TAS2R polymorphisms may be valuable genetic markers to predict therapeutic responses.

Is Myelodysplasia a Consequence of Normal Aging?

PURPOSE OF REVIEW

To review available data on the relationship of MDS and aging and to address the question if biological changes of (premature) aging are a prerequisite for the development of MDS.

RECENT FINDINGS

Whereas the association of MDS with advanced age and some common biologic features of aging and MDS are well established, additional evidence for both, especially on the role of stem cells, the stem cell niche, and inflammation, has been recently described. Biologically, many but not all drivers of aging also play a role in the development and propagation of MDS and vice versa. As a consequence, aging contributes to the development of MDS which can be seen as an interplay of clonal disease and normal and premature aging. The impact of aging may be different in specific MDS subtypes and risk groups.

Epithelial Cell Line Derived from Endometriotic Lesion Mimics Macrophage Nervous Mechanism of Pain Generation on Proteome and Metabolome Levels

Endometriosis is a benign disease affecting one in ten women of reproductive age worldwide. Although the pain level is not correlated to the extent of the disease, it is still one of the cardinal symptoms strongly affecting the patients' quality of life. Yet, a molecular mechanism of this pathology, including the formation of pain, remains to be defined. Recent studies have indicated a close interaction between newly generated nerve cells and macrophages, leading to neurogenic inflammation in the pelvic area. In this context, the responsiveness of an endometriotic cell culture model was characterized upon inflammatory stimulation by employing a multi-omics approach, including proteomics, metabolomics and eicosanoid analysis. Differential proteomic profiling of the 12-Z endometriotic cell line treated with TNFα and IL1β unexpectedly showed that the inflammatory stimulation was able to induce a protein signature associated with neuroangiogenesis, specifically including neuropilins (NRP1/2). Untargeted metabolomic profiling in the same setup further revealed that the endometriotic cells were capable of the autonomous production of 7,8-dihydrobiopterin (BH2), 7,8-dihydroneopterin, normetanephrine and epinephrine. These metabolites are related to the development of neuropathic pain and the former three were found up-regulated upon inflammatory stimulation. Additionally, 12-Z cells were found to secrete the mono-oxygenated oxylipin 16-HETE, a known inhibitor of neutrophil aggregation and adhesion. Thus, inflammatory stimulation of endometriotic 12-Z cells led to specific protein and metabolite expression changes suggesting a direct involvement of these epithelial-like cells in endometriosis pain development.

The function and mechanism of the JARID2/CCND1 axis in modulating glioma cell growth and sensitivity to temozolomide (TMZ)

A maximal surgical resection followed by radiotherapy and chemotherapy with temozolomide (TMZ) as the representative agent is the standard therapy for gliomas. However, tumor cell resistance to radiotherapy and chemotherapy leads to poor prognosis and high mortality in patients with glioma. In the present study, we demonstrated that JARID2 was downregulated and CCND1 was upregulated within glioma tissues of different grades and glioma cells. In tissue samples, JARID2 was negatively correlated with CCND1. JARID2 overexpression significantly inhibited glioma cell viability, promoted glioma cell apoptosis upon TMZ treatment, and increased p21, cleaved-PARP, and cleaved-caspase3 in TMZ-treated glioma cells. JASPAR tool predicted the possible binding sites between JARID2 and CCND1 promoter regions; through direct binding to CCND1 promoter region, JARID2 negatively regulated CCND1 expression. Under TMZ treatment, JARID2 overexpression inhibited CCND1 expression, promoted glioma cell apoptosis, and increased p21, cleaved-PARP, and cleaved-caspase3 in glioma cells treated with TMZ; meanwhile, CCND1 overexpression exerted opposite effects on glioma cells treated with TMZ and partially reversed the effects of JARID2 overexpression. In conclusion, JARID2 targets and inhibits CCND1. The JARID2/CCND1 axis modulates glioma cell growth and glioma cell sensitivity to TMZ.

Proteomics and Drug Repurposing in CLL towards Precision Medicine

Simple Summary

Despite continued efforts, the current status of knowledge in CLL molecular pathobiology, diagnosis, prognosis and treatment remains elusive and imprecise. Proteomics approaches combined with advanced bioinformatics and drug repurposing promise to shed light on the complex proteome heterogeneity of CLL patients and mitigate, improve, or even eliminate the knowledge stagnation. In relation to this concept, this review presents a brief overview of all the available proteomics and drug repurposing studies in CLL and suggests the way such studies can be exploited to find effective therapeutic options combined with drug repurposing strategies to adopt and accost a more “precision medicine” spectrum.

Abstract

CLL is a hematological malignancy considered as the most frequent lymphoproliferative disease in the western world. It is characterized by high molecular heterogeneity and despite the available therapeutic options, there are many patient subgroups showing the insufficient effectiveness of disease treatment. The challenge is to investigate the individual molecular characteristics and heterogeneity of these patients. Proteomics analysis is a powerful approach that monitors the constant state of flux operators of genetic information and can unravel the proteome heterogeneity and rewiring into protein pathways in CLL patients. This review essences all the available proteomics studies in CLL and suggests the way these studies can be exploited to find effective therapeutic options combined with drug repurposing approaches. Drug repurposing utilizes all the existing knowledge of the safety and efficacy of FDA-approved or investigational drugs and anticipates drug alignment to crucial CLL therapeutic targets, leading to a better disease outcome. The drug repurposing studies in CLL are also discussed in this review. The next goal involves the integration of proteomics-based drug repurposing in precision medicine, as well as the application of this procedure into clinical practice to predict the most appropriate drugs combination that could ensure therapy and the long-term survival of each CLL patient.

Exploring the dermotoxicity of the mycotoxin deoxynivalenol: combined morphologic and proteomic profiling of human epidermal cells reveals alteration of lipid biosynthesis machinery and membrane structural integrity relevant for skin barrier function

Deoxynivalenol (vomitoxin, DON) is a secondary metabolite produced by Fusarium spp. fungi and it is one of the most prevalent mycotoxins worldwide. Crop infestation results not only in food and feed contamination, but also in direct dermal exposure, especially during harvest and food processing. To investigate the potential dermotoxicity of DON, epidermoid squamous cell carcinoma cells A431 were compared to primary human neonatal keratinocytes (HEKn) cells via proteome/phosphoproteome profiling. In A431 cells, 10 µM DON significantly down-regulated ribosomal proteins, as well as mitochondrial respiratory chain elements (OXPHOS regulation) and transport proteins (TOMM22; TOMM40; TOMM70A). Mitochondrial impairment was reflected in altered metabolic competence, apparently combined with interference of the lipid biosynthesis machinery. Functional effects on the cell membrane were confirmed by live cell imaging and membrane fluidity assays (0.1–10 µM DON). Moreover, a common denominator for both A431 and HEKn cells was a significant downregulation of the squalene synthase (FDFT1). In sum, proteome alterations could be traced back to the transcription factor Klf4, a crucial regulator of skin barrier function. Overall, these results describe decisive molecular events sustaining the capability of DON to impair skin barrier function. Proteome data generated in the study are fully accessible via ProteomeXchange with the accession numbers PXD011474 and PXD013613.

Mass Spectrometry: A Powerful Method for Monitoring Various Type of Leukemia, Especially MALDI-TOF in Leukemia's Proteomics Studies Review

Recent success in studying the proteome, as a source of biomarkers, has completely changed our understanding of leukemia (blood cancer). The identification of differentially expressed proteins, such as relapse and drug resistance proteins involved in leukemia by using various ionization sources and mass analyzers of mass spectrometry techniques, has helped scientists find better diagnosis, prognosis, and treatment strategies. With the aid of this powerful analytical technique, we can investigate the qualification/quantification of proteins, protein-protein interactions, post-translational modifications, and find the correlation between proteins and their genes with the hope of finding the missing parts of the successful therapy puzzle. In this review, we followed different MS sources and analyzers which used for monitoring various type of leukemia, then focused on MALDI-TOF MS as a quick and reliable method for studying proteins. Due to several review published for other techniques, the present review is the first work in this field. Also, by classifying more than 400 proteins, we have found 42 proteins are involved in two or three different stages of leukemia. Finally, we have suggested six specific biomarkers for AML, one for ALL, three biomarkers with a role in the etiology of leukemia and 13 markers with the potential for further studies.

Gene Expression and Resistance to Glucocorticoid-Induced Apoptosis in Acute Lymphoblastic Leukemia: A Brief Review and Update

BACKGROUND

Resistance to glucocorticoid (GC)-induced apoptosis in Acute Lymphoblastic Leukemia (ALL), is considered one of the major prognostic factors for the disease. Prednisolone is a corticosteroid and one of the most important agents in the treatment of acute lymphoblastic leukemia. The mechanics of GC resistance are largely unknown and intense ongoing research focuses on this topic.

AIM

The aim of the present study is to review some aspects of GC resistance in ALL, and in particular of Prednisolone, with emphasis on previous and present knowledge on gene expression and signaling pathways playing a role in the phenomenon.

METHODS

An electronic literature search was conducted by the authors from 1994 to June 2019. Original articles and systematic reviews selected, and the titles and abstracts of papers screened to determine whether they met the eligibility criteria, and full texts of the selected articles were retrieved.

RESULTS

Identification of gene targets responsible for glucocorticoid resistance may allow discovery of drugs, which in combination with glucocorticoids may increase the effectiveness of anti-leukemia therapies. The inherent plasticity of clinically evolving cancer justifies approaches to characterize and prevent undesirable activation of early oncogenic pathways.

CONCLUSION

Study of the pattern of intracellular signal pathway activation by anticancer drugs can lead to development of efficient treatment strategies by reducing detrimental secondary effects.

Cell signaling and the aging of B cells

The uniqueness of each B cell lies in the structural diversity of the B-cell antigen receptor allowing the virtually limitless recognition of antigens, a necessity to protect individuals against a range of challenges. B-cell development and response to stimulation are exquisitely regulated by a group of cell surface receptors modulating various signaling cascades and their associated genetic programs. The effects of these signaling pathways in optimal antibody-mediated immunity or the aberrant promotion of immune pathologies have been intensely researched in the past in young individuals. In contrast, we are only beginning to understand the contribution of these pathways to the changes in B cells of old organisms. Thus, critical transcription factors such as E2A and STAT5 show differential expression or activity between young and old B cells. As a result, B-cell physiology appears altered, and antibody production is impaired. Here, we discuss selected phenotypic changes during B-cell aging and attempt to relate them to alterations of molecular mechanisms.

Tumor mutation burden and JARID2 gene alteration are associated with short disease-free survival in locally advanced triple-negative breast cancer

Background

In locally advanced triple-negative breast cancer (TNBC), patients who did not achieve pathologic complete response (non-pCR) after neoadjuvant chemotherapy develop rapid tumor metastasis. Tumor mutation burden (TMB) is a potential biomarker of cancer therapy, though whether it is applicable to TNBC is still unclear.

Methods

A total of 14 non-pCR TNBC patients were enrolled, and tissue samples from radical operation were collected. Of these, 7 cases developed disease progression within 12 months after operation [short disease-free survival (short DFS)], while others showed longer DFS over 1 year (long DFS). Next generation sequencing (NGS) analysis targeting 422 cancer-related genes and in vitro studies were performed.

Results

A total of 72 mutations were detected within 14 patients, which ranged from 1 to 8 per patient with a median mutations number of 5. The median number of mutations in the short-DFS group was higher than that in the long-DFS group (6.0 vs. 4.3; P=0.094). Furthermore, 6 gene mutation types were detected, with missense mutations displayed in the majority (36/72, 50.0%). No correlation between mutation type and DFS was found. Among 422 cancer-related genes, alterations in 30 genes were detected. TP53 (12/14, 85.7%) was the most common mutation gene in the entire cohort. RB1 mutations significantly occurred in patients with high Ki-67 scores (P=0.013). Additionally, 4 mutations of PTPN13 (57.1%, 4/7) and 3 of JARID2 (42.9%, 3/7) were only detected in the short-DFS group, while patients with JARID2 mutation had a significantly shorter DFS period (P=0.026). Experiments in vitro confirmed that JARID2 gene was widely expressed in various breast cancer cell lines. Knockdown of JARID2 in MD-MBA-231 cells by small interfering RNA (siRNA) decreased the expression of E-cadherin, and increased the levels of vimentin, MMP7, and MMP9.

Conclusions

In non-pCR TNBC, JARID2 mutation and TMB elevated in patients with short-DFS, indicating the potential prognostic biomarkers and therapeutic molecular targets for locally advanced TNBC.

MULTIOMIC PATTERNS IN BODY FLUIDS: TECHNOLOGICAL CHALLENGE WITH A GREAT POTENTIAL TO IMPLEMENT THE ADVANCED PARADIGM OF 3P MEDICINE

Liquid biopsy (LB) is defined as a sample of any of body fluids (blood, saliva, tear fluid, urine, sweat, amniotic, cerebrospinal and pleural fluids, cervicovaginal secretion, and wound efflux, amongst others), which can be ex vivo analysed to detect and quantity the target(s) of interest. LB represents diagnostic approach relevant for organ-specific changes and systemic health conditions including both manifested diseases and their prestages such as suboptimal health. Further, experts emphasise that DNA-based analysis alone does not provide sufficient information for optimal diagnostics and effective treatments. Consequently, of great scientific and clinical utility are molecular patterns detected by hybrid technologies such as metabolomic tools and molecular imaging. Future proposed strategies utilise multiomic pillars (generally genome, tanscriptome, proteome, metabolome, epigenome, radiome, and microbiome), system-biological approach, and multivariable algorithms for diagnostic, prognostic, and therapeutic purposes. Current article analyses pros and cons of the mass spectrometry-based technologies, provides eminent examples of a success story "from discovery to clinical application," and demonstrates a "road-map" for the technology-driven paradigm change from reactive to predictive, preventive and personalised medical services as the medicine of the future benefiting the patient and healthcare at large. © 2019 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

Danon Disease-Associated LAMP-2 Deficiency Drives Metabolic Signature Indicative of Mitochondrial Aging and Fibrosis in Cardiac Tissue and hiPSC-Derived Cardiomyocytes

Danon disease is a severe X-linked disorder caused by deficiency of the lysosome-associated membrane protein-2 (LAMP-2). Clinical manifestations are phenotypically diverse and consist of hypertrophic and dilated cardiomyopathies, skeletal myopathy, retinopathy, and intellectual dysfunction. Here, we investigated the metabolic landscape of Danon disease by applying a multi-omics approach and combined structural and functional readouts provided by Raman and atomic force microscopy. Using these tools, Danon patient-derived cardiac tissue, primary fibroblasts, and human induced pluripotent stem cells differentiated into cardiomyocytes (hiPSC-CMs) were analyzed. Metabolic profiling indicated LAMP-2 deficiency promoted a switch toward glycolysis accompanied by rerouting of tryptophan metabolism. Cardiomyocytes' energetic balance and NAD+/NADH ratio appeared to be maintained despite mitochondrial aging. In turn, metabolic adaption was accompanied by a senescence-associated signature. Similarly, Danon fibroblasts appeared more stress prone and less biomechanically compliant. Overall, shaping of both morphology and metabolism contributed to the loss of cardiac biomechanical competence that characterizes the clinical progression of Danon disease.

Systematic review and analysis of human proteomics aging studies unveils a novel proteomic aging clock and identifies key processes that change with age

The development of clinical interventions that significantly improve human healthspan requires robust markers of biological age as well as thoughtful therapeutic targets. To promote these goals, we performed a systematic review and analysis of human aging and proteomics studies. The systematic review includes 36 different proteomics analyses, each of which identified proteins that significantly changed with age. We discovered 1,128 proteins that had been reported by at least two or more analyses and 32 proteins that had been reported by five or more analyses. Each of these 32 proteins has known connections relevant to aging and age-related disease. GDF15, for example, extends both lifespan and healthspan when overexpressed in mice and is additionally required for the anti-diabetic drug metformin to exert beneficial effects on body weight and energy balance. Bioinformatic enrichment analyses of our 1,128 commonly identified proteins heavily implicated processes relevant to inflammation, the extracellular matrix, and gene regulation. We additionally propose a novel proteomic aging clock comprised of proteins that were reported to change with age in plasma in three or more different studies. Using a large patient cohort comprised of 3,301 subjects (aged 18-76 years), we demonstrate that this clock is able to accurately predict human age.

Cancer-associated fibroblast-derived WNT2 increases tumor angiogenesis in colon cancer

WNT2 acts as a pro-angiogenic factor in placental vascularization and increases angiogenesis in liver sinusoidal endothelial cells (ECs) and other ECs. Increased WNT2 expression is detectable in many carcinomas and participates in tumor progression. In human colorectal cancer (CRC), WNT2 is selectively elevated in cancer-associated fibroblasts (CAFs), leading to increased invasion and metastasis. However, if there is a role for WNT2 in colon cancer, angiogenesis was not addressed so far. We demonstrate that WNT2 enhances EC migration/invasion, while it induces canonical WNT signaling in a small subset of cells. Knockdown of WNT2 in CAFs significantly reduced angiogenesis in a physiologically relevant assay, which allows precise assessment of key angiogenic properties. In line with these results, expression of WNT2 in otherwise WNT2-devoid skin fibroblasts led to increased angiogenesis. In CRC xenografts, WNT2 overexpression resulted in enhanced vessel density and tumor volume. Moreover, WNT2 expression correlates with vessel markers in human CRC. Secretome profiling of CAFs by mass spectrometry and cytokine arrays revealed that proteins associated with pro-angiogenic functions are elevated by WNT2. These included extracellular matrix molecules, ANG-2, IL-6, G-CSF, and PGF. The latter three increased angiogenesis. Thus, stromal-derived WNT2 elevates angiogenesis in CRC by shifting the balance towards pro-angiogenic signals.

Structural Similarity with Cholesterol Reveals Crucial Insights into Mechanisms Sustaining the Immunomodulatory Activity of the Mycotoxin Alternariol

The proliferation of molds in domestic environments can lead to uncontrolled continuous exposure to mycotoxins. Even if not immediately symptomatic, this may result in chronic effects, such as, for instance, immunosuppression or allergenic promotion. Alternariol (AOH) is one of the most abundant mycotoxins produced by Alternaria alternata fungi, proliferating among others in fridges, as well as in humid walls. AOH was previously reported to have immunomodulatory potential. However, molecular mechanisms sustaining this effect remained elusive. In differentiated THP-1 macrophages, AOH hardly altered the secretion of pro-inflammatory mediators when co-incubated with lipopolysaccharide (LPS), opening up the possibility that the immunosuppressive potential of the toxin could be related to an alteration of a downstream pro-inflammatory signaling cascade. Intriguingly, the mycotoxin affected the membrane fluidity in macrophages and it synergistically reacted with the cholesterol binding agent MβCD. In silico modelling revealed the potential of the mycotoxin to intercalate in cholesterol-rich membrane domains, like caveolae, and immunofluorescence showed the modified interplay of caveolin-1 with Toll-like Receptor (TLR) 4. In conclusion, we identified the structural similarity with cholesterol as one of the key determinants of the immunomodulatory potential of AOH.

The Challenge of Classifying Metastatic Cell Properties by Molecular Profiling Exemplified with Cutaneous Melanoma Cells and Their Cerebral Metastasis from Patient Derived Mouse Xenografts

The prediction of metastatic properties from molecular analyses still poses a major challenge. Here we aimed at the classification of metastasis-related cell properties by proteome profiling making use of cutaneous and brain-metastasizing variants from single melanomas sharing the same genetic ancestry. Previous experiments demonstrated that cultured cells derived from these xenografted variants maintain a stable phenotype associated with a differential metastatic behavior: The brain metastasizing variants produce more spontaneous micro-metastases than the corresponding cutaneous variants. Four corresponding pairs of cutaneous and metastatic cells were obtained from four individual patients, resulting in eight cell-lines presently investigated. Label free proteome profiling revealed significant differences between corresponding pairs of cutaneous and cerebellar metastases from the same patient. Indeed, each brain metastasizing variant expressed several apparently metastasis-associated proteomic alterations as compared with the corresponding cutaneous variant. Among the differentially expressed proteins we identified cell adhesion molecules, immune regulators, epithelial to mesenchymal transition markers, stem cell markers, redox regulators and cytokines. Similar results were observed regarding eicosanoids, considered relevant for metastasis, such as PGE2 and 12-HETE. Multiparametric morphological analysis of cells also revealed no characteristic alterations associated with the cutaneous and brain metastasis variants. However, no correct classification regarding metastatic potential was yet possible with the present data. We thus concluded that molecular profiling is able to classify cells according to known functional categories but is not yet able to predict relevant cell properties emerging from networks consisting of many interconnected molecules. The presently observed broad diversity of molecular patterns, irrespective of restricting to one tumor type and two main classes of metastasis, highlights the important need to develop meta-analysis strategies to predict cell properties from molecular profiling data. Such base knowledge will greatly support future individualized precision medicine approaches.

Anakoinosis: Correcting Aberrant Homeostasis of Cancer Tissue-Going Beyond Apoptosis Induction

The current approach to systemic therapy for metastatic cancer is aimed predominantly at inducing apoptosis of cancer cells by blocking tumor-promoting signaling pathways or by eradicating cell compartments within the tumor. In contrast, a systems view of therapy primarily considers the communication protocols that exist at multiple levels within the tumor complex, and the role of key regulators of such systems. Such regulators may have far-reaching influence on tumor response to therapy and therefore patient survival. This implies that neoplasia may be considered as a cell non-autonomous disease. The multi-scale activity ranges from intra-tumor cell compartments, to the tumor, to the tumor-harboring organ to the organism. In contrast to molecularly targeted therapies, a systems approach that identifies the complex communications networks driving tumor growth offers the prospect of disrupting or "normalizing" such aberrant communicative behaviors and therefore attenuating tumor growth. Communicative reprogramming, a treatment strategy referred to as anakoinosis, requires novel therapeutic instruments, so-called master modifiers to deliver concerted tumor growth-attenuating action. The diversity of biological outcomes following pro-anakoinotic tumor therapy, such as differentiation, trans-differentiation, control of tumor-associated inflammation, etc. demonstrates that long-term tumor control may occur in multiple forms, inducing even continuous complete remission. Accordingly, pro-anakoinotic therapies dramatically extend the repertoire for achieving tumor control and may activate apoptosis pathways for controlling resistant metastatic tumor disease and hematologic neoplasia.

Potentially Critical Roles of NDUFB5, TIMMDC1, and VDAC3 in the Progression of Septic Cardiomyopathy Through Integrated Bioinformatics Analysis

Septic cardiomyopathy (SC) is a rare and harmful cardiovascular disease with decreased left ventricular (LV) output and multiple organ failure, which poses a serious threat to human life. Despite the advances in SC, its diagnostic basis and treatment methods are limited, and the specific diagnostic biomarkers and its candidate regulatory targets have not yet been fully established. In this study, the GSE79962 gene expression profile was retrieved, with 20 patients with SC and 11 healthy donors as control. Weighted gene coexpression network analysis (WGCNA) was employed to investigate gene modules that were strongly correlated with clinical phenotypes. Blue module was found to be most significantly related to SC. Moreover, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the coexpression genes in blue module and showed that it was associated with metabolic pathways, oxidative phosphorylation, and cardiac muscle contraction. Furthermore, a total of 10 hub genes NDUFB5, TIMMDC1, VDAC3, COQ10A, MRPL16 (mitochondrial ribosomal protein L16), C3orf43, TMEM182, DLAT, NDUFA8, and PDHB (pyruvate dehydrogenase E1 beta subunit) in the blue module were identified at transcriptional level and further validated at translational level in myocardium of an lipopolysaccharide-induced septic cardiac dysfunction mouse model. Overall, the results of quantitative real-time polymerase chain reaction were consistent with most of the microarray analysis results. Intriguingly, we observed that the highest change was NDUFB5, TIMMDC1, and VDAC3. These identified and validated genes provided references that would advance the understanding of molecular mechanisms of SC. Taken together, using WGCNA, the hub genes NDUFB5, TIMMDC1, and VDAC3 might serve as potential biomarkers for diagnosis and/or therapeutic targets for precise treatment of SC in the future.

MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.

Quantitative proteomics of synaptosome S-nitrosylation in Alzheimer's disease

Increasing evidence suggests that both synaptic loss and neuroinflammation constitute early pathologic hallmarks of Alzheimer's disease. A downstream event during inflammatory activation of microglia and astrocytes is the induction of nitric oxide synthase type 2, resulting in an increased release of nitric oxide and the post-translational S-nitrosylation of protein cysteine residues. Both early events, inflammation and synaptic dysfunction, could be connected if this excess nitrosylation occurs on synaptic proteins. In the long term, such changes could provide new insight into patho-mechanisms as well as biomarker candidates from the early stages of disease progression. This study investigated S-nitrosylation in synaptosomal proteins isolated from APP/PS1 model mice in comparison to wild type and NOS2^-/- mice, as well as human control, mild cognitive impairment and Alzheimer's disease brain tissues. Proteomics data were obtained using an established protocol utilizing an isobaric mass tag method, followed by nanocapillary high performance liquid chromatography tandem mass spectrometry. Statistical analysis identified the S-nitrosylation sites most likely derived from an increase in nitric oxide (NO) in dependence of presence of AD pathology, age and the key enzyme NOS2. The resulting list of candidate proteins is discussed considering function, previous findings in the context of neurodegeneration, and the potential for further validation studies.

Tumor Metabolism as a Regulator of Tumor-Host Interactions in the B-Cell Lymphoma Microenvironment-Fueling Progression and Novel Brakes for Therapy

Tumor metabolism and its specific alterations have become an integral part of understanding functional alterations leading to malignant transformation and maintaining cancer progression. Here, we review the metabolic changes in B-cell neoplasia, focusing on the effects of tumor metabolism on the tumor microenvironment (TME). Particularly, innate and adaptive immune responses are regulated by metabolites in the TME such as lactate. With steadily increasing therapeutic options implicating or utilizing the TME, it has become essential to address the metabolic alterations in B-cell malignancy for therapeutic approaches. In this review, we discuss metabolic alterations of B-cell lymphoma, consequences for currently used therapy regimens, and novel approaches specifically targeting metabolism in the TME.

Bruton's tyrosine kinase is at the crossroads of metabolic adaptation in primary malignant human lymphocytes

In this work we explored metabolic aspects of human primary leukemic lymphocytes that hold a potential impact on the treatment of Bruton tyrosine kinase (BTK)-driven diseases. Our results suggest that there is crosstalk between Bruton tyrosine kinase (BTK) signaling and bioenergetic stress responses. In primary chronic lymphocytic leukemia (CLL) lymphocytes, pharmacological interference with mitochondrial ATP synthesis or glucose metabolism affects BTK activity. Conversely, an inhibitor of BTK used clinically (ibrutinib) induces bioenergetic stress responses that in turn affect ibrutinib resistance. Although the detailed molecular mechanisms are still to be defined, our work shows for the first time that in primary B cells, metabolic stressors enhance BTK signaling and suggest that metabolic rewiring to hyperglycemia affects ibrutinib resistance in TP53 deficient chronic lymphocytic leukemia (CLL) lymphocytes.

Proteome Analysis Reveals Distinct Mitochondrial Functions Linked to Interferon Response Patterns in Activated CD4+ and CD8+ T Cells

While genetic traits and epigenetic modifications mainly encode cell type-specific effector functions, the eventual outcome is also prone to modulation by post-transcriptional regulation mechanisms. T cells are a powerful model for the investigation of such modulatory effects, as common precursor cells may differentiate either to helper CD4⁺ T cells or cytotoxic CD8⁺ cells, which elicit distinct functionalities upon TCR-stimulation. Human primary CD4⁺ and CD8⁺ T cells were purified from three individual donors and activated with anti-CD3/CD28 antibodies. Associated proteome alterations were analyzed by high-resolution mass spectrometry using a label-free shotgun approach. Metabolic activation was indicated by upregulation of enzymes related to glycolysis, NADH production, fatty acid synthesis, and uptake as well as amino acid and iron uptake. Besides various inflammatory effector molecules, the mitochondrial proteins CLUH, TFAM, and TOMM34 were found specifically induced in CD4⁺ T cells. Investigation of overrepresented conserved transcription binding sites by the oPOSSUM software suggested interferon type I inducer IRF1 to cause many of the observed proteome alterations in CD4⁺ T cells. RT qPCR demonstrated the specific induction of IRF1 in CD4⁺ T cells only. While the interferon regulatory factor IRF4 was found induced in both T cell subtypes at protein and mRNA level, IRF9 and the type I interferon-induced proteins IFIT1, IFIT3, and MX1 were only found induced in CD4⁺ T cells. As oxidative stress enhances mitochondrial DNA-dependent type I interferon responses, the present data suggested that mitochondrial activities regulate those cell type-specific signaling pathways. Indeed, we detected mitochondrial superoxide formation predominantly in CD4⁺ T cells via FACS analysis with MitoSOX™ and confirmed this observation by live cell imaging with confocal microscopy. As interferon signaling regulates important features such as resistance regarding immune checkpoint blockade therapy, the present data may identify potential new targets for the efficient control of highly relevant immune cell properties.

Metabolic, Anti-apoptotic and Immune Evasion Strategies of Primary Human Myeloma Cells Indicate Adaptations to Hypoxia

Multiple Myeloma (MM) is an incurable plasma cell malignancy primarily localized within the bone marrow (BM). It develops from a premalignant stage, monoclonal gammopathy of undetermined significance (MGUS), often via an intermediate stage, smoldering MM (SMM). The mechanisms of MM progression have not yet been fully understood, all the more because patients with MGUS and SMM already carry similar initial mutations as found in MM cells. Over the last years, increased importance has been attributed to the tumor microenvironment and its role in the pathophysiology of the disease. Adaptations of MM cells to hypoxic conditions in the BM have been shown to contribute significantly to MM progression, independently from the genetic predispositions of the tumor cells. Searching for consequences of hypoxia-induced adaptations in primary human MM cells, CD138-positive plasma cells freshly isolated from BM of patients with different disease stages, comprising MGUS, SMM, and MM, were analyzed by proteome profiling, which resulted in the identification of 6218 proteins. Results have been made fully accessible via ProteomeXchange with identifier PXD010600. Data previously obtained from normal primary B cells were included for comparative purposes. A principle component analysis revealed three clusters, differentiating B cells as well as MM cells corresponding to less and more advanced disease stages. Comparing these three clusters pointed to the alteration of pathways indicating adaptations to hypoxic stress in MM cells on disease progression. Protein regulations indicating immune evasion strategies of MM cells were determined, supported by immunohistochemical staining, as well as transcription factors involved in MM development and progression. Protein regulatory networks related to metabolic adaptations of the cells became apparent. Results were strengthened by targeted analyses of a selected panel of metabolites in MM cells and MM-associated fibroblasts. Based on our data, new opportunities may arise for developing therapeutic strategies targeting myeloma disease progression.

Metabolic underpinnings of leukemia pathology and treatment

BACKGROUND

Carcinogenic transformation of white blood cells during hematopoiesis leads to the development of leukemia, a cancer characterized by incompetent immune cells and a disruption of normal bone marrow function. Leukemias are diverse in type, affected population, prognosis, and treatment regimen, yet a common theme in leukemia is the dysregulated metabolism of leukemic cells and leukemic stem cells with respect to their noncancerous counterparts.

RECENT FINDINGS

In this review, we highlight current findings that elucidate metabolic traits unique to the four major types of leukemia, which confer carcinogenic survival but can be potentially exploited for therapeutic intervention. These metabolic features can work in conjunction with or be independent of unique aspects of the bone marrow microenvironment that can also influence cell survival and proliferation, thus sustaining carcinogenesis.

CONCLUSION

Deepening our understanding of the interactions of leukemias with their niche environments in vivo will inform future treatments for leukemia, particularly for those that are refractive to tyrosine kinase inhibitors and other therapeutic mainstays.

Altered expression of metabolic pathways in CLL detected by unlabelled quantitative mass spectrometry analysis

Chronic lymphocytic leukaemia (CLL) remains the most common incurable malignancy of B cells in the western world. Patient outcomes are heterogeneous and can be difficult to predict with current prognostic markers. Here, we used a quantitative label-free proteomic technique to ascertain differences in the B-cell proteome from healthy donors and CLL patients with either mutated (M-CLL) or unmutated (UM-CLL) IGHV to identify new prognostic markers. In peripheral B-CLL cells, 349 (22%) proteins were differentially expressed between normal B cells and B-CLL cells and 189 (12%) were differentially expressed between M-CLL and UM-CLL. We also examined the proteome of proliferating CLL cells in the lymph nodes, and identified 76 (~8%) differentially expressed proteins between healthy and CLL lymph nodes. B-CLL cells show over-expression of proteins involved in lipid and cholesterol metabolism. A comprehensive lipidomic analysis highlighted large differences in glycolipids and sphingolipids. A shift was observed from the pro-apoptotic lipid ceramide towards the anti-apoptotic/chemoresistant lipid, glucosylceramide, which was more evident in patients with aggressive disease (UM-CLL). This study details a novel quantitative proteomic technique applied for the first time to primary patient samples in CLL and highlights that primary CLL lymphocytes display markers of a metabolic shift towards lipid synthesis and breakdown.

Metabolic rewiring beyond Warburg in chronic lymphocytic leukemia: How much do we actually know?

Chronic Lymphocytic Leukemia (CLL) is the most common adult leukemia in the western world. CLL consists of the accumulation of malignant B-cells in the blood stream and homing tissues. Although treatable, this disease is not curable, and resistance or relapse is often present. In many cancers, the study of metabolic reprograming has uncovered novel targets that are already being exploited in the clinic. However, CLL metabolism is still poorly understood. The ability of CLL lymphocytes to adapt to diverse microenvironments is accompanied by modifications in cell metabolism, revealing the challenge of targeting the CLL lymphocytes present in all different compartments. Despite this, the study of CLL metabolism led to an ongoing clinical trial using glucose uptake and mitochondrial respiration inhibitors. In contrast, glutamine and fatty acid metabolism remain to be further exploited in CLL. Here, we summarize the present knowledge of CLL metabolism, as well as the metabolic influence of Myc, ATM and p53 on CLL lymphocytes.

Clinical Efficacy of a Novel Therapeutic Principle, Anakoinosis

Classic tumor therapy, consisting of cytotoxic agents and/or targeted therapy, has not overcome therapeutic limitations like poor risk genetic parameters, genetic heterogeneity at different metastatic sites or the problem of undruggable targets. Here we summarize data and trials principally following a completely different treatment concept tackling systems biologic processes: the principle of communicative reprogramming of tumor tissues, i.e., anakoinosis (ancient greek for communication), aims at establishing novel communicative behavior of tumor tissue, the hosting organ and organism via re-modeling gene expression, thus recovering differentiation, and apoptosis competence leading to cancer control - in contrast to an immediate, "poisoning" with maximal tolerable doses of targeted or cytotoxic therapies. Therefore, we introduce the term "Master modulators" for drugs or drug combinations promoting evolutionary processes or regulating homeostatic pathways. These "master modulators" comprise a broad diversity of drugs, characterized by the capacity for reprogramming tumor tissues, i.e., transcriptional modulators, metronomic low-dose chemotherapy, epigenetically modifying agents, protein binding pro-anakoinotic drugs, such as COX-2 inhibitors, IMiDs etc., or for example differentiation inducing therapies. Data on 97 anakoinosis inducing schedules indicate a favorable toxicity profile: The combined administration of master modulators, frequently (with poor or no monoactivity) may even induce continuous complete remission in refractory metastatic neoplasia, irrespectively of the tumor type. That means recessive components of the tumor, successively developing during tumor ontogenesis, are accessible by regulatory active drug combinations in a therapeutically meaningful way. Drug selection is now dependent on situative systems characteristics, to less extent histology dependent. To sum up, anakoinosis represents a new substantive therapy principle besides novel targeted therapies.

Ibrutinib Resistance Is Reduced by an Inhibitor of Fatty Acid Oxidation in Primary CLL Lymphocytes

Chronic Lymphocytic Leukemia (CLL) is an incurable disease, characterized by the accumulation of malignant B-lymphocytes in the blood stream (quiescent state) and homing tissues (where they can proliferate). In CLL, the targeting of B-cell receptor signaling through a Burton's tyrosine kinase inhibitor (ibrutinib) has rendered outstanding clinical results. However, complete remission is not guaranteed due to drug resistance or relapse, revealing the need for novel approaches for CLL treatment. The characterization of metabolic rewiring in proliferative cancer cells is already being applied for diagnostic and therapeutic purposes, but our knowledge of quiescent cell metabolism—relevant for CLL cells—is still fragmentary. Recently, we reported that glutamine metabolism in primary CLL cells bearing the del11q deletion is different from their del11q negative counterparts, making del11q cells especially sensitive to glutaminase and glycolysis inhibitors. In this work, we used our primary CLL lymphocyte bank and compounds interfering with central carbon metabolism to define metabolic traits associated with ibrutinib resistance. We observe a differential basal metabolite uptake linked to ibrutinib resistance, favoring glutamine uptake and catabolism. Upon ibrutinib treatment, the redox balance in ibrutinib resistant cells is shifted toward NADPH accumulation, without an increase in glutamine uptake, suggesting alternative metabolic rewiring such as the activation of fatty acid oxidation. In accordance to this idea, the curtailing of fatty acid oxidation by CPT1 inhibition (etomoxir) re-sensitized resistant cells to ibrutinib. Our results suggest that fatty acid oxidation could be explored as a target to overcome ibrutinib resistance.

Identification of Distinct Unmutated Chronic Lymphocytic Leukemia Subsets in Mice Based on Their T Cell Dependency

Chronic lymphocytic leukemia (CLL) can be divided into prognostically distinct subsets with stereotyped or non-stereotyped, mutated or unmutated B cell receptors (BCRs). Individual subsets vary in antigen specificity and origin, but the impact of antigenic pressure on the CLL BCR repertoire remains unknown. Here, we employed IgH.TEμ mice that spontaneously develop CLL, expressing mostly unmutated BCRs of which ~35% harbor V_H11-2/Vκ14-126 and recognize phosphatidylcholine. Proportions of V_H11/Vκ14-expressing CLL were increased in the absence of functional germinal centers in IgH.TEμ mice deficient for CD40L or activation-induced cytidine deaminase. Conversely, in vivo T cell-dependent immunization decreased the proportions of V_H11/Vκ14-expressing CLL. Furthermore, CLL onset was accelerated by enhanced BCR signaling in Siglec-G^−/− mice or in mice expressing constitutively active Bruton's tyrosine kinase. Transcriptional profiling revealed that V_H11 and non-V_H11 CLL differed in the upregulation of specific pathways implicated in cell signaling and metabolism. Interestingly, principal component analyses using the 148 differentially expressed genes revealed that V_H11 and non-V_H11 CLL clustered with BCR-stimulated and anti-CD40-stimulated B cells, respectively. We identified an expression signature consisting of 13 genes that were differentially expressed in a larger panel of T cell-dependent non-V_H11 CLL compared with T cell-independent V_H11/Vκ14 or mutated IgH.TEμ CLL. Parallel differences in the expression of these 13 signature genes were observed between heterogeneous and stereotypic human unmutated CLL. Our findings provide evidence for two distinct unmutated CLL subsets with a specific transcriptional signature: one is T cell-independent and B-1 cell-derived while the other arises upon antigen stimulation in the context of T-cell help.