Changing face of socio-economic vulnerability and COVID-19: An analysis of country wealth during the first two years of the pandemic.

There are numerous academic studies on the relationship between population wealth and the incidence of COVID-19. However, research developed shows contradictory results on their relationship. In accordance with this question, this work pursues two objectives: on the one hand, to check whether wealth and disease incidence have a unidirectional and stable relationship. And on the other hand, to find out if the country's statistical production capacity is masking the real incidence of the COVID-19 pandemic. In order to achieve this objective, an ecological study has been designed at international level with the countries established as study units. The analytical strategy utilized involves the consecutive application of cross-sectional analysis, specifically employing multivariate linear regression daily throughout the first two years of the pandemic (from 03/14/2020 to 03/28/2022). The application of multiple cross-sectional analysis has shown that country wealth has a dynamic relationship with the incidence of COVID-19. Initially, it appears as a risk factor and, in the long term, as a protective element. In turn, statistical capacity appears as an explanatory variable for the number of published COVID-19 cases and deaths. Therefore, the inadequate statistical production capacity of low income countries may be masking the real incidence of the disease.

Venetoclax improves CD20 immunotherapy in a mouse model of MYC/BCL2 double-expressor diffuse large B-cell lymphoma.

BACKGROUND: Approximately one-third of diffuse large B cell lymphoma (DLBCL) patients exhibit co-expression of MYC and BCL2 (double-expressor lymphoma, DEL) and have a dismal prognosis. Targeted inhibition of the anti-apoptotic protein BCL2 with venetoclax (ABT-199) has been approved in multiple B-cell malignancies and is currently being investigated in clinical trials for DLBCL. Whether BCL2 anti-apoptotic function represents a multifaceted vulnerability for DEL-DLBCL, affecting both lymphoma B cells and T cells within the tumor microenvironment, remains to be elucidated. METHODS: Here, we present novel genetically engineered mice that preclinically recapitulate DEL-DLBCL lymphomagenesis, and evaluate their sensitivity ex vivo and in vivo to the promising combination of venetoclax with anti-CD20-based standard immunotherapy. RESULTS: Venetoclax treatment demonstrated specific killing of MYC+/BCL2+ lymphoma cells by licensing their intrinsically primed apoptosis, and showed previously unrecognized immunomodulatory activity by specifically enriching antigen-activated effector CD8 T cells infiltrating the tumors. Whereas DEL-DLBCL mice were refractory to venetoclax alone, inhibition of BCL2 significantly extended overall survival of mice that were simultaneously treated with a murine surrogate for anti-CD20 rituximab. CONCLUSIONS: These results suggest that the combination of anti-CD20-based immunotherapy and BCL2 inhibition leads to cooperative immunomodulatory effects and improved preclinical responses, which may offer promising therapeutic opportunities for DEL-DLBCL patients.

Multivariate Analysis of Risk Factors of the COVID-19 Pandemic in the Community of Madrid, Spain.

It has been more than one year since Chinese authorities identified a deadly new strain of coronavirus, SARS-CoV-2. Since then, the scientific work regarding the transmission risk factors of COVID-19 has been intense. The relationship between COVID-19 and environmental conditions is becoming an increasingly popular research topic. Based on the findings of the early research, we focused on the community of Madrid, Spain, which is one of the world's most significant pandemic hotspots. We employed different multivariate statistical analyses, including principal component analysis, analysis of variance, clustering, and linear regression models. Principal component analysis was employed in order to reduce the number of risk factors down to three new components that explained 71% of the original variance. Cluster analysis was used to delimit the territory of Madrid according to these new risk components. An ANOVA test revealed different incidence rates between the territories delimited by the previously identified components. Finally, a set of linear models was applied to demonstrate how environmental factors present a greater influence on COVID-19 infections than socioeconomic dimensions. This type of local research provides valuable information that could help societies become more resilient in the face of future pandemics.

Long Noncoding RNA EGOT Responds to Stress Signals to Regulate Cell Inflammation and Growth.

The cell has several mechanisms to sense and neutralize stress. Stress-related stimuli activate pathways that counteract danger, support cell survival, and activate the inflammatory response. We use human cells to show that these processes are modulated by EGOT, a long noncoding RNA highly induced by viral infection, whose inhibition results in increased levels of antiviral IFN-stimulated genes (ISGs) and decreased viral replication. We now show that EGOT is induced in response to cell stress, viral replication, or the presence of pathogen-associated molecular patterns via the PI3K/AKT, MAPKs, and NF-κB pathways, which lead to cell survival and inflammation. Transcriptome analysis and validation experiments show that EGOT modulates PI3K/AKT and NF-κB responses. On the one hand, EGOT inhibition decreases expression of PI3K/AKT-induced cellular receptors and cell proliferation. In fact, EGOT levels are increased in several tumors. On the other hand, EGOT inhibition results in decreased levels of key NF-κB target genes, including those required for inflammation and ISGs in those cells that build an antiviral response. Mechanistically, EGOT depletion decreases the levels of the key coactivator TBLR1, essential for transcription by NF-κB. In summary, EGOT is induced in response to stress and may function as a switch that represses ISG transcription until a proper antiviral or stress response is initiated. EGOT then helps PI3K/AKT, MAPKs, and NF-κB pathways to activate the antiviral response, cell inflammation, and growth. We believe that modulation of EGOT levels could be used as a therapy for the treatment of certain viral infections, immune diseases, and cancer.

Whole exome sequencing characterization of individuals presenting extreme phenotypes of high and low risk of developing tobacco-induced lung adenocarcinoma.

BACKGROUND: Tobacco is the main risk factor for developing lung cancer. Yet, some heavy smokers do not develop lung cancer at advanced ages while others develop it at young ages. Here, we assess for the first time the genetic background of these clinically relevant extreme phenotypes using whole exome sequencing (WES). METHODS: We performed WES of germline DNA from heavy smokers who either developed lung adenocarcinoma at an early age (extreme cases, n=50) or did not present lung adenocarcinoma or other tumors at an advanced age (extreme controls, n=50). We selected non-synonymous variants located in exonic regions and consensus splice sites of the genes that showed significantly different allelic frequencies between both cohorts. We validated our results in all the additional extreme cases (i.e., heavy smokers who developed lung adenocarcinoma at an early age) available from The Cancer Genome Atlas (TCGA). RESULTS: The mean age for the extreme cases and controls was respectively 49.7 and 77.5 years. Mean tobacco consumption was 43.6 and 56.8 pack-years. We identified 619 significantly different variants between both cohorts, and we validated 108 of these in extreme cases selected from TCGA. Nine validated variants, located in relevant cancer related genes, such as PARP4, HLA-A or NQO1, among others, achieved statistical significance in the False Discovery Rate test. The most significant validated variant (P=4.48×10-5) was located in the tumor-suppressor gene ALPK2. CONCLUSIONS: We describe genetic variants associated with extreme phenotypes of high and low risk for the development of tobacco-induced lung adenocarcinoma. Our results and our strategy may help to identify high-risk subjects and to develop new therapeutic approaches.

Dynamic Intracellular Metabolic Cell Signaling Profiles During Ag-Dependent B-Cell Differentiation.

Human B-cell differentiation has been extensively investigated on genomic and transcriptomic grounds; however, no studies have accomplished so far detailed analysis of antigen-dependent maturation-associated human B-cell populations from a proteomic perspective. Here, we investigate for the first time the quantitative proteomic profiles of B-cells undergoing antigen-dependent maturation using a label-free LC-MS/MS approach applied on 5 purified B-cell subpopulations (naive, centroblasts, centrocytes, memory and plasma B-cells) from human tonsils (data are available via ProteomeXchange with identifier PXD006191). Our results revealed that the actual differences among these B-cell subpopulations are a combination of expression of a few maturation stage-specific proteins within each B-cell subset and maturation-associated changes in relative protein expression levels, which are related with metabolic regulation. The considerable overlap of the proteome of the 5 studied B-cell subsets strengthens the key role of the regulation of the stoichiometry of molecules associated with metabolic regulation and programming, among other signaling cascades (such as antigen recognition and presentation and cell survival) crucial for the transition between each B-cell maturation stage.

Characterization of complete lncRNAs transcriptome reveals the functional and clinical impact of lncRNAs in multiple myeloma.

Multiple myeloma (MM) is an incurable disease, whose clinical heterogeneity makes its management challenging, highlighting the need for biological features to guide improved therapies. Deregulation of specific long non-coding RNAs (lncRNAs) has been shown in MM, nevertheless, the complete lncRNA transcriptome has not yet been elucidated. In this work, we identified 40,511 novel lncRNAs in MM samples. lncRNAs accounted for 82% of the MM transcriptome and were more heterogeneously expressed than coding genes. A total of 10,351 overexpressed and 9,535 downregulated lncRNAs were identified in MM patients when compared with normal bone-marrow plasma cells. Transcriptional dynamics study of lncRNAs in the context of normal B-cell maturation revealed 989 lncRNAs with exclusive expression in MM, among which 89 showed de novo epigenomic activation. Knockdown studies on one of these lncRNAs, SMILO (specific myeloma intergenic long non-coding RNA), resulted in reduced proliferation and induction of apoptosis of MM cells, and activation of the interferon pathway. We also showed that the expression of lncRNAs, together with clinical and genetic risk alterations, stratified MM patients into several progression-free survival and overall survival groups. In summary, our global analysis of the lncRNAs transcriptome reveals the presence of specific lncRNAs associated with the biological and clinical behavior of the disease.

UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm.

The Human Proteome Project (HPP) is leading the international effort to characterize the human proteome. Although the main goal of this project was first focused on the detection of missing proteins, a new challenge arose from the need to assign biological functions to the uncharacterized human proteins and describe their implications in human diseases. Not only the proteins with experimental evidence (uPE1 proteins) but also the uncharacterized missing proteins (uMPs) were the objects of study in this challenge, neXt-CP50. In this work, we developed a new bioinformatic approach to infer biological annotations for the uPE1 proteins and uMPs based on a "guilt-by-association" analysis using public RNA-Seq data sets. We used the correlation of these proteins with the well-characterized PE1 proteins to construct a network. In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. All of the generated information was stored in a database. In addition, we implemented the web application UPEFinder (https://upefinder.proteored.org) to facilitate the access to this new resource. This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).

DeepMSPeptide: peptide detectability prediction using deep learning.

SUMMARY: The protein detection and quantification using high-throughput proteomic technologies is still challenging due to the stochastic nature of the peptide selection in the mass spectrometer, the difficulties in the statistical analysis of the results and the presence of degenerated peptides. However, considering in the analysis only those peptides that could be detected by mass spectrometry, also called proteotypic peptides, increases the accuracy of the results. Several approaches have been applied to predict peptide detectability based on the physicochemical properties of the peptides. In this manuscript, we present DeepMSPeptide, a bioinformatic tool that uses a deep learning method to predict proteotypic peptides exclusively based on the peptide amino acid sequences. AVAILABILITY AND IMPLEMENTATION: DeepMSPeptide is available at https://github.com/vsegurar/DeepMSPeptide. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MiTPeptideDB: a proteogenomic resource for the discovery of novel peptides.

MOTIVATION: The principal lines of research in MS/MS based Proteomics have been directed toward the molecular characterization of the proteins including their biological functions and their implications in human diseases. Recent advances in this field have also allowed the first attempts to apply these techniques to the clinical practice. Nowadays, the main progress in Computational Proteomics is based on the integration of genomic, transcriptomic and proteomic experimental data, what is known as Proteogenomics. This methodology is being especially useful for the discovery of new clinical biomarkers, small open reading frames and microproteins, although their validation is still challenging. RESULTS: We detected novel peptides following a proteogenomic workflow based on the MiTranscriptome human assembly and shotgun experiments. The annotation approach generated three custom databases with the corresponding peptides of known and novel transcripts of both protein coding genes and non-coding genes. In addition, we used a peptide detectability filter to improve the computational performance of the proteomic searches, the statistical analysis and the robustness of the results. These innovative additional filters are specially relevant when noisy next generation sequencing experiments are used to generate the databases. This resource, MiTPeptideDB, was validated using 43 cell lines for which RNA-Seq experiments and shotgun experiments were available. AVAILABILITY AND IMPLEMENTATION: MiTPeptideDB is available at http://bit.ly/MiTPeptideDB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identification of Coding and Long Noncoding RNAs Differentially Expressed in Tumors and Preferentially Expressed in Healthy Tissues.

The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets allow unprecedented gene expression analyses. Here, using these datasets, we performed pan-cancer and pan-tissue identification of coding and long noncoding RNA (lncRNA) transcripts differentially expressed in tumors and preferentially expressed in healthy tissues and/or tumors. Pan-cancer comparison of mRNAs and lncRNAs showed that lncRNAs were deregulated in a more tumor-specific manner. Given that lncRNAs are more tissue-specific than mRNAs, we identified healthy tissues that preferentially express lncRNAs upregulated in tumors and found that testis, brain, the digestive tract, and blood/spleen were the most prevalent. In addition, specific tumors also upregulate lncRNAs preferentially expressed in other tissues, generating a unique signature for each tumor type. Most tumors studied downregulated lncRNAs preferentially expressed in their tissue of origin, probably as a result of dedifferentiation. However, the same lncRNAs could be upregulated in other tumors, resulting in "bimorphic" transcripts. In hepatocellular carcinoma (HCC), the upregulated genes identified were expressed at higher levels in patients with worse prognosis. Some lncRNAs upregulated in HCC and preferentially expressed in healthy testis or brain were predicted to function as oncogenes and were significantly associated with higher tumor burden, and poor prognosis, suggesting their relevance in hepatocarcinogenesis and/or tumor evolution. Taken together, therapies targeting oncogenic lncRNAs should take into consideration the healthy tissue, where the lncRNAs are preferentially expressed, to predict and decrease unwanted secondary effects and increase potency. SIGNIFICANCE: Comprehensive analysis of coding and noncoding genes expressed in different tumors and normal tissues, which should be taken into account to predict side effects from potential coding and noncoding gene-targeting therapies.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/20/5167/F1.large.jpg.

Taking Advantage of the Selectivity of Histone Deacetylases and Phosphodiesterase Inhibitors to Design Better Therapeutic Strategies to Treat Alzheimer's Disease.

The discouraging results with therapies for Alzheimer's disease (AD) in clinical trials, highlights the urgent need to adopt new approaches. Like other complex diseases, it is becoming clear that AD therapies should focus on the simultaneous modulation of several targets implicated in the disease. Recently, using reference compounds and the first-in class CM-414, we demonstrated that the simultaneous inhibition of histone deacetylases [class I histone deacetylases (HDACs) and HDAC6] and phosphodiesterase 5 (PDE5) has a synergistic therapeutic effect in AD models. To identify the best inhibitory balance of HDAC isoforms and PDEs that provides a safe and efficient therapy to combat AD, we tested the compound CM-695 in the Tg2576 mouse model of this disease. CM-695 selectively inhibits HDAC6 over class I HDAC isoforms, which largely overcomes the toxicity associated with HDAC class 1 inhibition. Furthermore, CM-695 inhibits PDE9, which is expressed strongly in the brain and has been proposed as a therapeutic target for AD. Chronic treatment of aged Tg2576 mice with CM-695 ameliorates memory impairment and diminishes brain Aß, although its therapeutic effect was no longer apparent 4 weeks after the treatment was interrupted. An increase in the presence of 78-KDa glucose regulated protein (GRP78) and heat shock protein 70 (Hsp70) chaperones may underlie the therapeutic effect of CM-695. In summary, chronic treatment with CM-695 appears to reverse the AD phenotype in a safe and effective manner. Taking into account that AD is a multifactorial disorder, the multimodal action of these compounds and the different events they affect may open new avenues to combat AD.

Identification of mutations associated with acquired resistance to sunitinib in renal cell cancer.

Sunitinib is one of the most widely used targeted therapeutics for renal cell carcinoma (RCC), but acquired resistance against targeted therapies remains a major clinical challenge. To dissect mechanisms of acquired resistance and unravel reliable predictive biomarkers for sunitinib in RCC, we sequenced the exons of 409 tumor-suppressor genes and oncogenes in paired tumor samples from an RCC patient, obtained at baseline and after development of acquired resistance to sunitinib. From newly arising mutations, we selected, using in silico prediction models, six predicted to be deleterious, located in G6PD, LRP1B, SETD2, TET2, SYNE1, and DCC. Consistently, immunoblotting analysis of lysates derived from sunitinib-desensitized RCC cells and their parental counterparts showed marked differences in the levels and expression pattern of the proteins encoded by these genes. Our further analysis demonstrates essential roles for these proteins in mediating sunitinib cytotoxicity and shows that their loss of function renders tumor cells resistant to sunitinib in vitro and in vivo. Finally, sunitinib resistance induced by continuous exposure or by inhibition of the six proteins was overcome by treatment with cabozantinib or a low-dose combination of lenvatinib and everolimus. Collectively, our results unravel novel markers of acquired resistance to sunitinib and clinically relevant approaches for overcoming this resistance in RCC.

The Mechanism of Action of the Anti-CD38 Monoclonal Antibody Isatuximab in Multiple Myeloma.

PURPOSE: Knowledge about the mechanism of action (MoA) of monoclonal antibodies (mAb) is required to understand which patients with multiple myeloma (MM) benefit the most from a given mAb, alone or in combination therapy. Although there is considerable research about daratumumab, knowledge about other anti-CD38 mAbs remains scarce. EXPERIMENTAL DESIGN: We performed a comprehensive analysis of the MoA of isatuximab. RESULTS: Isatuximab induces internalization of CD38 but not its significant release from MM cell surface. In addition, we uncovered an association between levels of CD38 expression and different MoA: (i) Isatuximab was unable to induce direct apoptosis on MM cells with CD38 levels closer to those in patients with MM, (ii) isatuximab sensitized CD38hi MM cells to bortezomib plus dexamethasone in the presence of stroma, (iii) antibody-dependent cellular cytotoxicity (ADCC) was triggered by CD38lo and CD38hi tumor plasma cells (PC), (iv) antibody-dependent cellular phagocytosis (ADCP) was triggered only by CD38hi MM cells, whereas (v) complement-dependent cytotoxicity could be triggered in less than half of the patient samples (those with elevated levels of CD38). Furthermore, we showed that isatuximab depletes CD38hi B-lymphocyte precursors and natural killer (NK) lymphocytes ex vivo-the latter through activation followed by exhaustion and eventually phagocytosis. CONCLUSIONS: This study provides a framework to understand response determinants in patients treated with isatuximab based on the number of MoA triggered by CD38 levels of expression, and for the design of effective combinations aimed at capitalizing disrupted tumor-stroma cell protection, augmenting NK lymphocyte-mediated ADCC, or facilitating ADCP in CD38lo MM patients.See related commentary by Malavasi and Faini, p. 2946.

Epigenomic profiling of myelofibrosis reveals widespread DNA methylation changes in enhancer elements and ZFP36L1 as a potential tumor suppressor gene that is epigenetically regulated.

In this study we interrogated the DNA methylome of myelofibrosis patients using high-density DNA methylation arrays. We detected 35,215 differentially methylated CpG, corresponding to 10,253 genes, between myelofibrosis patients and healthy controls. These changes were present both in primary and secondary myelofibrosis, which showed no differences between them. Remarkably, most differentially methylated CpG were located outside gene promoter regions and showed significant association with enhancer regions. This aberrant enhancer hypermethylation was negatively correlated with the expression of 27 genes in the myelofibrosis cohort. Of these, we focused on the ZFP36L1 gene and validated its decreased expression and enhancer DNA hypermethylation in an independent cohort of patients and myeloid cell-lines. In vitro reporter assay and 5'-azacitidine treatment confirmed the functional relevance of hyper-methylation of ZFP36L1 enhancer. Furthermore, in vitro rescue of ZFP36L1 expression had an impact on cell proliferation and induced apoptosis in SET-2 cell line indicating a possible role of ZFP36L1 as a tumor suppressor gene in myelofibrosis. Collectively, we describe the DNA methylation profile of myelofibrosis, identifying extensive changes in enhancer elements and revealing ZFP36L1 as a novel candidate tumor suppressor gene.

Proteogenomics in the context of the Human Proteome Project (HPP).

INTRODUCTION: The technological and scientific progress performed in the Human Proteome Project (HPP) has provided to the scientific community a new set of experimental and bioinformatic methods in the challenging field of shotgun and SRM/MRM-based Proteomics. The requirements for a protein to be considered experimentally validated are now well-established, and the information about the human proteome is available in the neXtProt database, while targeted proteomic assays are stored in SRMAtlas. However, the study of the missing proteins continues being an outstanding issue. Areas covered: This review is focused on the implementation of proteogenomic methods designed to improve the detection and validation of the missing proteins. The evolution of the methodological strategies based on the combination of different omic technologies and the use of huge publicly available datasets is shown taking the Chromosome 16 Consortium as reference. Expert commentary: Proteogenomics and other strategies of data analysis implemented within the C-HPP initiative could be used as guidance to complete in a near future the catalog of the human proteins. Besides, in the next years, we will probably witness their use in the B/D-HPP initiative to go a step forward on the implications of the proteins in the human biology and disease.

Deregulation of linc-PINT in acute lymphoblastic leukemia is implicated in abnormal proliferation of leukemic cells.

Long Non-Coding RNAs (lncRNAs) are functional RNAs longer than 200 nucleotides in length. Several lncRNAs are involved in cell proliferation and are deregulated in several human tumors. Few lncRNAs have been described to play a role in Acute Lymphoblastic Leukemia (ALL). In this study, we carried out a genome wide lncRNA expression profiling in ALL samples and peripheral blood samples obtained from healthy donors. We detected 43 lncRNAs that were aberrantly expressed in ALL. Interestingly, among them, linc-PINT showed a significant downregulation in T and B-ALL. Re-expression of linc-PINT in ALL cells induced inhibition of leukemic cell growth that was associated with apoptosis induction and cell cycle arrest in G2/M phase. linc-PINT induced the transcription of HMOX1 which reduced the viability of ALL cells. Intriguingly, we observed that treatment with anti-tumoral epigenetic drugs like LBH-589 (Panobinostat) and Curcumin induced the expression of linc-PINT and HMOX1 in ALL. These results indicate that the downregulation of linc-PINT plays a relevant role in the pathogenesis of ALL, and linc-PINT re-expression may be one of the mechanisms exerted by epigenetic drugs to reduce cell proliferation in ALL.