BID expression determines the apoptotic fate of cancer cells after abrogation of the spindle assembly checkpoint by AURKB or TTK inhibitors

BACKGROUND

Drugs targeting the spindle assembly checkpoint (SAC), such as inhibitors of Aurora kinase B (AURKB) and dual specific protein kinase TTK, are in different stages of clinical development. However, cell response to SAC abrogation is poorly understood and there are no markers for patient selection.

METHODS

A panel of 53 tumor cell lines of different origins was used. The effects of drugs were analyzed by MTT and flow cytometry. Copy number status was determined by FISH and Q-PCR; mRNA expression by nCounter and RT-Q-PCR and protein expression by Western blotting. CRISPR-Cas9 technology was used for gene knock-out (KO) and a doxycycline-inducible pTRIPZ vector for ectopic expression. Finally, in vivo experiments were performed by implanting cultured cells or fragments of tumors into immunodeficient mice.

RESULTS

Tumor cells and patient-derived xenografts (PDXs) sensitive to AURKB and TTK inhibitors consistently showed high expression levels of BH3-interacting domain death agonist (BID), while cell lines and PDXs with low BID were uniformly resistant. Gene silencing rendered BID-overexpressing cells insensitive to SAC abrogation while ectopic BID expression in BID-low cells significantly increased sensitivity. SAC abrogation induced activation of CASP-2, leading to cleavage of CASP-3 and extensive cell death only in presence of high levels of BID. Finally, a prevalence study revealed high BID mRNA in 6% of human solid tumors.

CONCLUSIONS

The fate of tumor cells after SAC abrogation is driven by an AURKB/ CASP-2 signaling mechanism, regulated by BID levels. Our results pave the way to clinically explore SAC-targeting drugs in tumors with high BID expression.

Pipeline for transferring annotations between proteins beyond globular domains

BACKGROUND

DisProt is the primary repository of Intrinsically Disordered Proteins (IDPs). This database is manually curated and the annotations there have strong experimental support. Currently, DisProt contains a relatively small number of proteins highlighting the importance of transferring annotations regarding verified disorder state and corresponding functions to homologous proteins in other species. In such a way, providing them with highly valuable information to better understand their biological roles. While the principles and practicalities of homology transfer are well-established for globular proteins, these are largely lacking for disordered proteins.

METHODS

We used DisProt to evaluate the transferability of the annotation terms to orthologous proteins. For each protein, we looked for their orthologs, with the assumption that they will have a similar function. Then, for each protein and their orthologs we made multiple sequence alignments (MSAs). Disordered sequences are fast evolving and can be hard to align: Therefore we implemented alignment quality control steps ensuring robust alignments before mapping the annotations.

RESULTS

We have designed a pipeline to obtain good quality MSAs and to transfer annotations from any protein to their orthologs. Applying the pipeline to DisProt proteins, from the 1,731 entries with 5,623 annotations we can reach 97,555 orthologs and transfer a total of 301,190 terms by homology. We also provide a web server for consulting the results of DisProt proteins and execute the pipeline for any other protein. The server Homology Transfer IDP (HoTIDP) is accessible at http://hotidp.leloir.org.ar. This article is protected by copyright. All rights reserved.

Abstract 1032: Development of a plasma circRNA signature for the discrimination of malign lung nodules using the nCounter platform

Introduction: The evaluation of suspicious lung nodules detected by imaging techniques is currently being performed by invasive methods, such as surgical biopsy or fine-needle aspiration (FNA). Liquid biopsies could offer a minimally invasive alternative in this setting. Some circRNAs have recently been investigated as biomarkers for the early detection of lung cancer and other solid tumors. In this project, we are evaluating the levels of whole plasma circRNAs using the nCounter technology in order to develop a prognostic signature that can aid the clinician to differentiate benign vs. malign nodules.

Methods: Plasma samples from patients with malign lung nodules (n=135) and controls (n=149), including patients with benign nodules (n=66/149) have been collected. RNA was purified using the QIAsymphony DSP Virus/Pathogen Midi Kit in a QIAsymphony robot (Qiagen). The nCounter Low RNA Input Amplification Kit (NanoString) was used to retrotranscribe and pre-amplify 4 μL of plasma RNA. Overnight hybridization and posterior nCounter processing (NanoString) steps were carried out following the manufacturer’s instructions. Differential expression and machine learning (ML) methods were performed for the development of a lung cancer signature.

Results: Preliminary analysis of the 88 samples first included in the study shown a cluster of 6 circRNAs differentially expressed in lung cancer. Among these circRNAs, circSMAD2, circCOL11A1, circCHST15, and circFUT8 were upregulated, while circACP3 and circLYPLAL1 were found downregulated in plasma of lung cancer patients. In addition, a 64-circRNA signature selected by ML was able to differentiate NSCLC patients from controls, including those with benign nodules, The algorithm assigned signature scores to samples, which ranged from 0 to 1. Using a cut-off value of 0.5, preliminary signature was able to classify samples with an AUC ROC of 0.90 and accuracy of 78.41% (CI = 68.35% - 86.47%) with the final model.

Conclusion: Using ML on nCounter analysis of 88 samples, we have generated a preliminary 64-circRNA signature in plasma predictive of early-stage NSCLC. Final results in the entire cohort of 294 samples will be presented at the meeting.

Citation Format: Carlos Pedraz Valdunciel, Giovanna Casagrande, Elizabeth Martínez-Pérez, Ana Gimenez-Capitán, Joselyn Valarezo, Pablo Rubinstein, Andrés Aguilar-Hernández, Leticia Ferro-Leal, Cristina Marino-Buslje, Rui Reis, Rafael Rosell, Miguel Ángel Molina-Vila. Development of a plasma circRNA signature for the discrimination of malign lung nodules using the nCounter platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1032.

DisPhaseDB: an integrative database of diseases related variations in liquid-liquid phase separation proteins

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Phase separation proteins involved in membraneless organelles are increasingly implicated in several complex human diseases.

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DisPhaseDB integrates ten repositories for analyzing clinically relevant mutations in phase separation proteins.

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Contains over a million disease-related mutations mapped onto the protein sequences along with extensive metadata.

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It is a comprehensive meta-database, implemented in an user-friendly web with visualization tools and downloadable datasets.

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DisPhaseDB will contribute deciphering still not fully understood human disease mechanisms under the lens of phase separation.

Motivation

Proteins involved in liquid–liquid phase separation (LLPS) and membraneless organelles (MLOs) are recognized to be decisive for many biological processes and also responsible for several diseases. The recent explosion of research in the area still lacks tools for the analysis and data integration among different repositories. Currently, there is not a comprehensive and dedicated database that collects all disease-related variations in combination with the protein location, biological role in the MLO, and all the metadata available for each protein and disease. Disease-related protein variants and additional features are dispersed and the user has to navigate many databases, with a different focus, formats, and often not user friendly.

Results

We present DisPhaseDB, a database dedicated to disease-related variants of liquid–liquid phase separation proteins. It integrates 10 databases, contains 5,741 proteins, 1,660,059 variants, and 4,051 disease terms. It also offers intuitive navigation and an informative display. It constitutes a pivotal starting point for further analysis, encouraging the development of new computational tools.

The database is freely available at http://disphasedb.leloir.org.ar.

Panels and models for accurate prediction of tumor mutation burden in tumor samples

Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.

PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs.

Short linear motif candidates in the cell entry system used by SARS-CoV-2 and their potential therapeutic implications

The first reported receptor for SARS-CoV-2 on host cells was the angiotensin-converting enzyme 2 (ACE2). However, the viral spike protein also has an RGD motif, suggesting that cell surface integrins may be co-receptors. We examined the sequences of ACE2 and integrins with the Eukaryotic Linear Motif (ELM) resource and identified candidate short linear motifs (SLiMs) in their short, unstructured, cytosolic tails with potential roles in endocytosis, membrane dynamics, autophagy, cytoskeleton, and cell signaling. These SLiM candidates are highly conserved in vertebrates and may interact with the μ2 subunit of the endocytosis-associated AP2 adaptor complex, as well as with various protein domains (namely, I-BAR, LC3, PDZ, PTB, and SH2) found in human signaling and regulatory proteins. Several motifs overlap in the tail sequences, suggesting that they may act as molecular switches, such as in response to tyrosine phosphorylation status. Candidate LC3-interacting region (LIR) motifs are present in the tails of integrin β3 and ACE2, suggesting that these proteins could directly recruit autophagy components. Our findings identify several molecular links and testable hypotheses that could uncover mechanisms of SARS-CoV-2 attachment, entry, and replication against which it may be possible to develop host-directed therapies that dampen viral infection and disease progression. Several of these SLiMs have now been validated to mediate the predicted peptide interactions.

DisProt: intrinsic protein disorder annotation in 2020

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.

Comutation and exclusion analysis in human tumors: A tool for cancer biology studies and for rational selection of multitargeted therapeutic approaches

Malignant tumors originate from somatic mutations and other genomic and epigenomic alterations, which lead to loss of control of the cellular circuitry. These alterations present patterns of co-occurrence and mutual exclusivity that can influence prognosis and modify response to drugs, highlighting the need for multitargeted therapies. Studies in this area have generally focused in particular malignancies and considered whole genes instead of specific mutations, ignoring the fact that different alterations in the same gene can have widely different effects. Here, we present a comprehensive analysis of co-dependencies of individual somatic mutations in the whole spectrum of human tumors. Combining multitesting with conditional and expected mutational probabilities, we have discovered rules governing the codependencies of driver and nondriver mutations. We also uncovered pairs and networks of comutations and exclusions, some of them restricted to certain cancer types and others widespread. These pairs and networks are not only of basic but also of clinical interest, and can be of help in the selection of multitargeted antitumor therapies. In this respect, recurrent driver comutations suggest combinations of drugs that might be effective in the clinical setting, while recurrent exclusions indicate combinations unlikely to be useful.

Uncommon renal masses: Perirenal extramedullary hematopoiesis and multiple lymphangiomatosis with a perirenal lymphangioma

OBJECTIVE

To present two cases of infrequent renal masses, trying to achieve the diagnosis before surgery.

METHODS

We describe a case referred from the Department of Hematology in which bilateral perirrenal masses were described in the CT scan; after biopsy they where classified as extramedullary hematopoietic tissue. The other case was a patient presenting to the emergency room with dyspnea. CT Scan showed lungs with multiple cysts, chylothorax and a cystic-solid mass in the left perirenal space. In the lung biopsy they reported lung lymphangiomatosis, so we didn't perform renal biopsy.

RESULTS

Most renal masses are renal carcinomas (856%). The less common diagnosis are sarcomas, lymphomas, upper urinary tract transitional cell carcinomas, metastases of other primary tumors, the Erdheim-Chester disease, the Castleman disease and benign tumors. All these diseases might show similar images in the CT scan and MRI, being the biopsy and histological study necessary for the diagnosis

CONCLUSIONS

Perirenal extramedullary hematopoiesis and perirenal lymphangioma are rare diseases that need a pathologic study for their diagnosis.

Homologous chromosome pairing in wheat

Bread wheat is a hexaploid (AABBDD, 2n=6x=42) containing three related ancestral genomes, each having 7 chromosomes, giving 42 chromosomes in diploid cells. During meiosis true homologues are correctly associated in wild-type wheat, but a degree of association of related chromosomes (homoeologues) occurs in a mutant (ph1b). We show that the centromeres are associated in non-homologous pairs in all floral tissues studied, both in wild-type wheat and the ph1b mutant. The non-homologous centromere associations then become homologous premeiotically in wild-type wheat in both meiocytes and the tapetal cells, but not in the mutant. In wild-type wheat, the homologues are colocalised along their length at this stage, but the telomeres remain distinct. A single telomere cluster (bouquet) is formed in the meiocytes only by the onset of leptotene. The sub-telomeric regions of the homologues associate as the telomere cluster forms. The homologous associations at the telomeres and centromeres are maintained through meiotic prophase, although, during leptotene, the two homologues and also the sister chromatids within each homologue are separate along the rest of their length. As meiosis progresses, first the sister chromatids and then the homologues associate intimately. In wild-type wheat, first the centromere grouping, then the bouquet disperse by the end of zygotene.