The African Swine Fever Virus IAP Homolog Is a Late Structural Polypeptide

AbstractThe analysis of the complete nucleotide sequence of the African swine fever virus genome has revealed the existence of a number of genes potentially capable of modifying the host's response to the virus infection. In this report, we describe the results of the characterization of the A224L gene that encodes a novel member of the family of apoptosis inhibitors known as IAP proteins. A224L is expressed during the late phase of the infectious cycle, and its polypeptide product is assembled into virus particles

Tracking the antibody immunome in sporadic colorectal cancer by using antigen self-assembled protein arrays

© 2021 by the authors.Sporadic Colorectal Cancer (sCRC) is the third leading cause of cancer death in the Western world, and the sCRC patients presenting with synchronic metastasis have the poorest prognosis. Genetic alterations accumulated in sCRC tumor cells translate into mutated proteins and/or abnormal protein expression levels, which contribute to the development of sCRC. Then, the tumor-associated proteins (TAAs) might induce the production of auto-antibodies (aAb) via humoral immune response. Here, Nucleic Acid Programmable Protein Arrays (NAPPArray) are employed to identify aAb in plasma samples from a set of 50 sCRC patients compared to seven healthy donors. Our goal was to establish a systematic workflow based on NAPPArray to define differential aAb profiles between healthy individuals and sCRC patients as well as between non-metastatic (n = 38) and metastatic (n = 12) sCRC, in order to gain insight into the role of the humoral immune system in controlling the development and progression of sCRC. Our results showed aAb profile based on 141 TAA including TAAs associated with biological cellular processes altered in genesis and progress of sCRC (e.g., FSCN1, VTI2 and RPS28) that discriminated healthy donors vs. sCRC patients. In addition, the potential capacity of discrimination (between non-metastatic vs. metastatic sCRC) of 7 TAAs (USP5, ML4, MARCKSL1, CKMT1B, HMOX2, VTI2, TP53) have been analyzed individually in an independent cohort of sCRC patients, where two of them (VTI2 and TP53) were validated (AUC ~75%). In turn, these findings provided novel insights into the immunome of sCRC, in combination with transcriptomics profiles and protein antigenicity characterizations, wich might lead to the identification of novel sCRC biomarkers that might be of clinical utility for early diagnosis of the tumor. These results explore the immunomic analysis as potent source for biomarkers with diagnostic and prognostic value in CRC. Additional prospective studies in larger series of patients are required to confirm the clinical utility of these novel sCRC immunomic biomarkers.We gratefully acknowledge financial support from the Spanish Health Institute Carlos III (ISCIII) for the grants: FIS PI14/01538, FIS PI17/01930 and CB16/12/00400. We also acknowledge Fondos FEDER (EU) “Una manera de hacer Europa” and Junta Castilla-León (COVID19 grant COV20EDU/00187). Fundación Solórzano FS/38-2017. The Proteomics Unit belongs to ProteoRed, PRB3-ISCIII, supported by grant PT17/0019/0023, of the PE I + D + I 2017-2020, funded by ISCIII and FEDER. CNPq-National Council for Scientific and Technological Development (Brazil) (306258/2019-6) and FAPERJ-Foundation for Research Support of Rio de Janeiro State for the financial support (E-26/201.670/2017 and 210.379/2018). M. González-González is supported by MINECOPTA2019-017870-I.A. Landeira-Viñuela is supported by VIII Centenario-USAL PhD Program. P.J.-V. is supported by JCYL PhD Program and scholarship JCYL-EDU/601/2020. P.D. and E.B. are supported by a JCYL-EDU/346/2013 Ph.D. scholarship

Neurosurgical emergency management during the lockdown period in health care regions in Spain with different COVID-19 impact: lessons learned to improve outcomes on the future waves

Background COVID-19 has overloaded health care systems, testing the capacity and response in every European region. Concerns were raised regarding the impact of resources’ reorganization on certain emergency pathology management. The aim of the present study was to assess the impact of the outbreak (in terms of reduction of neurosurgical emergencies) during lockdown in different regions of Spain. Methods We analyzed the impact of the outbreak in four different affected regions by descriptive statistics and univariate comparison with same period of two previous years. These regions differed in their incidence level (high/low) and in the time of excess mortality with respect to lockdown declaration. That allowed us to analyze their influence on the characteristics of neurosurgical emergencies registered for every region. Results 1185 patients from 18 neurosurgical centers were included. Neurosurgical emergencies that underwent surgery dropped 24.41% and 28.15% in 2020 when compared with 2019 and 2018, respectively. A higher reduction was reported for the most affected regions by COVID-19. Non-traumatic spine experienced the most significant decrease in number of cases. Life-threatening conditions did not suffer a reduction in any health care region. Conclusions COVID-19 affected dramatically the neurosurgical emergency management. The most significant reduction in neurosurgical emergencies occurred on those regions that were hit unexpectedly by the pandemic, as resources were focused on fighting the virus. As a consequence, life-threating and non-life-threatening conditions’ mortality raised. Results in regions who had time to prepare for the hit were congruent with an organized and sensible neurosurgical decision-making.Peer reviewe

Detection of High Level of Co-Infection and the Emergence of Novel SARS CoV-2 Delta-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia

Recombination is an evolutionary strategy to quickly acquire new viral properties inherited from the parental lineages. The systematic survey of the SARS-CoV-2 genome sequences of the Andalusian genomic surveillance strategy has allowed the detection of an unexpectedly high number of co-infections, which constitute the ideal scenario for the emergence of new recombinants. Whole genome sequence of SARS-CoV-2 has been carried out as part of the genomic surveillance programme. Sample sources included the main hospitals in the Andalusia region. In addition to the increase of co-infections and known recombinants, three novel SARS-CoV-2 delta-omicron and omicron-omicron recombinant variants with two break points have been detected. Our observations document an epidemiological scenario in which co-infection and recombination are detected more frequently. Finally, we describe a family case in which co-infection is followed by the detection of a recombinant made from the two co-infecting variants. This increased number of recombinants raises the risk of emergence of recombinant variants with increased transmissibility and pathogenicity

Table_4_Unravelling soluble immune checkpoints in chronic lymphocytic leukemia: Physiological immunomodulators or immune dysfunction.xlsx [Dataset]

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm characterized by the accumulation of mature B cells. The diagnosis is established by the detection of monoclonal B lymphocytes in peripheral blood, even in early stages [monoclonal B-cell lymphocytosis (MBLhi)], and its clinical course is highly heterogeneous. In fact, there are well-characterized multiple prognostic factors that are also related to the observed genetic heterogenicity, such as immunoglobulin heavy chain variable region (IGHV) mutational status, del17p, and TP53 mutations, among others. Moreover, a dysregulation of the immune system (innate and adaptive immunity) has been observed in CLL patients, with strong impact on immune surveillance and consequently on the onset, evolution, and therapy response. In addition, the tumor microenvironment is highly complex and heterogeneous (i.e., matrix, fibroblast, endothelial cells, and immune cells), playing a critical role in the evolution of CLL. In this study, a quantitative profile of 103 proteins (cytokines, chemokines, growth/regulatory factors, immune checkpoints, and soluble receptors) in 67 serum samples (57 CLL and 10 MBLhi) has been systematically evaluated. Also, differential profiles of soluble immune factors that discriminate between MBLhi and CLL (sCD47, sCD27, sTIMD-4, sIL-2R, and sULBP-1), disease progression (sCD48, sCD27, sArginase-1, sLAG-3, IL-4, and sIL-2R), or among profiles correlated with other prognostic factors, such as IGHV mutational status (CXCL11/I-TAC, CXCL10/IP-10, sHEVM, and sLAG-3), were deciphered. These results pave the way to explore the role of soluble immune checkpoints as a promising source of biomarkers in CLL, to provide novel insights into the immune suppression process and/or dysfunction, mostly on T cells, in combination with cellular balance disruption and microenvironment polarization leading to tumor escape.Peer reviewe

Table_3_Unravelling soluble immune checkpoints in chronic lymphocytic leukemia: Physiological immunomodulators or immune dysfunction.xlsx [Dataset]

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm characterized by the accumulation of mature B cells. The diagnosis is established by the detection of monoclonal B lymphocytes in peripheral blood, even in early stages [monoclonal B-cell lymphocytosis (MBLhi)], and its clinical course is highly heterogeneous. In fact, there are well-characterized multiple prognostic factors that are also related to the observed genetic heterogenicity, such as immunoglobulin heavy chain variable region (IGHV) mutational status, del17p, and TP53 mutations, among others. Moreover, a dysregulation of the immune system (innate and adaptive immunity) has been observed in CLL patients, with strong impact on immune surveillance and consequently on the onset, evolution, and therapy response. In addition, the tumor microenvironment is highly complex and heterogeneous (i.e., matrix, fibroblast, endothelial cells, and immune cells), playing a critical role in the evolution of CLL. In this study, a quantitative profile of 103 proteins (cytokines, chemokines, growth/regulatory factors, immune checkpoints, and soluble receptors) in 67 serum samples (57 CLL and 10 MBLhi) has been systematically evaluated. Also, differential profiles of soluble immune factors that discriminate between MBLhi and CLL (sCD47, sCD27, sTIMD-4, sIL-2R, and sULBP-1), disease progression (sCD48, sCD27, sArginase-1, sLAG-3, IL-4, and sIL-2R), or among profiles correlated with other prognostic factors, such as IGHV mutational status (CXCL11/I-TAC, CXCL10/IP-10, sHEVM, and sLAG-3), were deciphered. These results pave the way to explore the role of soluble immune checkpoints as a promising source of biomarkers in CLL, to provide novel insights into the immune suppression process and/or dysfunction, mostly on T cells, in combination with cellular balance disruption and microenvironment polarization leading to tumor escape.Peer reviewe

Real-World Data on Adult T-Cell Leukemia/Lymphoma in Latin America: A Study From the Grupo de Estudio Latinoamericano de Linfoproliferativos

PURPOSE Adult T-cell leukemia/lymphoma (ATLL) is an aggressive disease caused by the human T-cell leukemia virus type 1. Real-world data of ATLL in Latin America are lacking. PATIENTS AND METHODS We analyzed patients with ATLL (acute, lymphomatous, chronic, and smoldering) encountered in 11 Latin American countries between 1995 and 2019. Treatment response was assessed according to the 2009 consensus report. Survival curves were estimated using the Kaplan-Meier method and log-rank test. RESULTS We identified 253 patients; 226 (lymphomatous: n = 122, acute: n = 73, chronic: n = 26, and smoldering: n = 5) had sufficient data for analysis (median age 57 years). Most patients with ATLL were from Peru (63%), Chile (17%), Argentina (8%), and Colombia (7%). Hypercalcemia was positively associated with acute type (57% v lymphomatous 27%, P = .014). The median survival times (months) were 4.3, 7.9, 21.1, and not reached for acute, lymphomatous, chronic, and smoldering forms, with 4-year survival rates of 8%, 22%, 40%, and 80%, respectively. First-line zidovudine (AZT)-interferon alfa (IFN) resulted in an overall response rate of 63% (complete response [CR] 24%) for acute. First-line chemotherapy yielded an overall response rate of 41% (CR 29%) for lymphomatous. CR rate was 42% for etoposide, cyclophosphamide, vincristine, doxorubicin, and prednisone versus 12% for cyclophosphamide, vincristine, doxorubicin, and prednisone–like regimen ( P < .001). Progression-free survival at 1 year for acute type patients treated with AZT-IFN was 67%, whereas 2-year progression-free survival in lymphomatous type patients who achieved CR after chemotherapy was 77%. CONCLUSION This study confirms Latin American ATLL presents at a younger age and has a high incidence of lymphomatous type, low incidence of indolent subtypes, and worse survival rates as compared with Japanese patients. In aggressive ATLL, chemotherapy remains the preferred choice for lymphomatous favoring etoposide-based regimen (etoposide, cyclophosphamide, vincristine, doxorubicin, and prednisone), whereas AZT-IFN remains a good first-line option for acute subtype

FUSE-ML: development and external validation of a clinical prediction model for mid-term outcomes after lumbar spinal fusion for degenerative disease

Background: Indications and outcomes in lumbar spinal fusion for degenerative disease are notoriously heterogenous. Selected subsets of patients show remarkable benefit. However, their objective identification is often difficult. Decision-making may be improved with reliable prediction of long-term outcomes for each individual patient, improving patient selection and avoiding ineffective procedures. Methods: Clinical prediction models for long-term functional impairment [Oswestry Disability Index (ODI) or Core Outcome Measures Index (COMI)], back pain, and leg pain after lumbar fusion for degenerative disease were developed. Achievement of the minimum clinically important difference at 12 months postoperatively was defined as a reduction from baseline of at least 15 points for ODI, 2.2 points for COMI, or 2 points for pain severity. Results: Models were developed and integrated into a web-app (https://neurosurgery.shinyapps.io/fuseml/) based on a multinational cohort [N = 817; 42.7% male; mean (SD) age: 61.19 (12.36) years]. At external validation [N = 298; 35.6% male; mean (SD) age: 59.73 (12.64) years], areas under the curves for functional impairment [0.67, 95% confidence interval (CI): 0.59–0.74], back pain (0.72, 95%CI: 0.64–0.79), and leg pain (0.64, 95%CI: 0.54–0.73) demonstrated moderate ability to identify patients who are likely to benefit from surgery. Models demonstrated fair calibration of the predicted probabilities. Conclusions: Outcomes after lumbar spinal fusion for degenerative disease remain difficult to predict. Although assistive clinical prediction models can help in quantifying potential benefits of surgery and the externally validated FUSE-ML tool may aid in individualized risk–benefit estimation, truly impacting clinical practice in the era of “personalized medicine” necessitates more robust tools in this patient population

FUSE-ML: development and external validation of a clinical prediction model for mid-term outcomes after lumbar spinal fusion for degenerative disease

Background: Indications and outcomes in lumbar spinal fusion for degenerative disease are notoriously heterogenous. Selected subsets of patients show remarkable benefit. However, their objective identification is often difficult. Decision-making may be improved with reliable prediction of long-term outcomes for each individual patient, improving patient selection and avoiding ineffective procedures. Methods: Clinical prediction models for long-term functional impairment [Oswestry Disability Index (ODI) or Core Outcome Measures Index (COMI)], back pain, and leg pain after lumbar fusion for degenerative disease were developed. Achievement of the minimum clinically important difference at 12 months postoperatively was defined as a reduction from baseline of at least 15 points for ODI, 2.2 points for COMI, or 2 points for pain severity. Results: Models were developed and integrated into a web-app (https://neurosurgery.shinyapps.io/fuseml/) based on a multinational cohort [N = 817; 42.7% male; mean (SD) age: 61.19 (12.36) years]. At external validation [N = 298; 35.6% male; mean (SD) age: 59.73 (12.64) years], areas under the curves for functional impairment [0.67, 95% confidence interval (CI): 0.59–0.74], back pain (0.72, 95%CI: 0.64–0.79), and leg pain (0.64, 95%CI: 0.54–0.73) demonstrated moderate ability to identify patients who are likely to benefit from surgery. Models demonstrated fair calibration of the predicted probabilities. Conclusions: Outcomes after lumbar spinal fusion for degenerative disease remain difficult to predict. Although assistive clinical prediction models can help in quantifying potential benefits of surgery and the externally validated FUSE-ML tool may aid in individualized risk–benefit estimation, truly impacting clinical practice in the era of “personalized medicine” necessitates more robust tools in this patient population