Metastatic recurrence in colorectal cancer arises from residual EMP1+ cells.

Around 30-40% of patients with colorectal cancer (CRC) undergoing curative resection of the primary tumour will develop metastases in the subsequent years1. Therapies to prevent disease relapse remain an unmet medical need. Here we uncover the identity and features of the residual tumour cells responsible for CRC relapse. An analysis of single-cell transcriptomes of samples from patients with CRC revealed that the majority of genes associated with a poor prognosis are expressed by a unique tumour cell population that we named high-relapse cells (HRCs). We established a human-like mouse model of microsatellite-stable CRC that undergoes metastatic relapse after surgical resection of the primary tumour. Residual HRCs occult in mouse livers after primary CRC surgery gave rise to multiple cell types over time, including LGR5+ stem-like tumour cells2-4, and caused overt metastatic disease. Using Emp1 (encoding epithelial membrane protein 1) as a marker gene for HRCs, we tracked and selectively eliminated this cell population. Genetic ablation of EMP1high cells prevented metastatic recurrence and mice remained disease-free after surgery. We also found that HRC-rich micrometastases were infiltrated with T cells, yet became progressively immune-excluded during outgrowth. Treatment with neoadjuvant immunotherapy eliminated residual metastatic cells and prevented mice from relapsing after surgery. Together, our findings reveal the cell-state dynamics of residual disease in CRC and anticipate that therapies targeting HRCs may help to avoid metastatic relapse.

Autogenous Control of 5'TOP mRNA Stability by 40S Ribosomes.

Ribosomal protein (RP) expression in higher eukaryotes is regulated translationally through the 5'TOP sequence. This mechanism evolved to more rapidly produce RPs on demand in different tissues. Here we show that 40S ribosomes, in a complex with the mRNA binding protein LARP1, selectively stabilize 5'TOP mRNAs, with disruption of this complex leading to induction of the impaired ribosome biogenesis checkpoint (IRBC) and p53 stabilization. The importance of this mechanism is underscored in 5q− syndrome, a macrocytic anemia caused by a large monoallelic deletion, which we found to also encompass the LARP1 gene. Critically, depletion of LARP1 alone in human adult CD34+ bone marrow precursor cells leads to a reduction in 5'TOP mRNAs and the induction of p53. These studies identify a 40S ribosome function independent of those in translation that, with LARP1, mediates the autogenous control of 5'TOP mRNA stability, whose disruption is implicated in the pathophysiology of 5q− syndrome.

Bioactivity Profile Similarities to Expand the Repertoire of COVID-19 Drugs.

Until a vaccine becomes available, the current repertoire of drugs is our only therapeutic asset to fight the SARS-CoV-2 outbreak. Indeed, emergency clinical trials have been launched to assess the effectiveness of many marketed drugs, tackling the decrease of viral load through several mechanisms. Here, we present an online resource, based on small-molecule bioactivity signatures and natural language processing, to expand the portfolio of compounds with potential to treat COVID-19. By comparing the set of drugs reported to be potentially active against SARS-CoV-2 to a universe of 1 million bioactive molecules, we identify compounds that display analogous chemical and functional features to the current COVID-19 candidates. Searches can be filtered by level of evidence and mechanism of action, and results can be restricted to drug molecules or include the much broader space of bioactive compounds. Moreover, we allow users to contribute COVID-19 drug candidates, which are automatically incorporated to the pipeline once per day. The computational platform, as well as the source code, is available at https://sbnb.irbbarcelona.org/covid19.

Open Source Code Contributions to Global Health: The Case of Antimalarial Drug Discovery.

The discovery of treatments for infectious diseases that affect the poorest countries has been stagnant for decades. As long as expected returns on investment remain low, pharmaceutical companies' lack of interest in this disease area must be compensated for with collaborative efforts from the public sector. New approaches to drug discovery, inspired by the "open source" philosophy prevalent in software development, offer a platform for experts from diverse backgrounds to contribute their skills, enhancing reproducibility, progress tracking, and public discussion. Here, we present the first efforts of Ersilia, an initiative focused on attracting data scientists into contributing to global health, toward meeting the goals of Open Source Malaria, a consortium of medicinal chemists investigating antimalarial compounds using a purely open science approach. We showcase the chemical space exploration of a set of triazolopyrazine compounds with potent antiplasmodial activity and discuss how open source practices can serve as a common ground to make drug discovery more inclusive and participative.

First fully-automated AI/ML virtual screening cascade implemented at a drug discovery centre in Africa.

Streamlined data-driven drug discovery remains challenging, especially in resource-limited settings. We present ZairaChem, an artificial intelligence (AI)- and machine learning (ML)-based tool for quantitative structure-activity/property relationship (QSAR/QSPR) modelling. ZairaChem is fully automated, requires low computational resources and works across a broad spectrum of datasets. We describe an end-to-end implementation at the H3D Centre, the leading integrated drug discovery unit in Africa, at which no prior AI/ML capabilities were available. By leveraging in-house data collected over a decade, we have developed a virtual screening cascade for malaria and tuberculosis drug discovery comprising 15 models for key decision-making assays ranging from whole-cell phenotypic screening and cytotoxicity to aqueous solubility, permeability, microsomal metabolic stability, cytochrome inhibition, and cardiotoxicity. We show how computational profiling of compounds, prior to synthesis and testing, can inform progression of frontrunner compounds at H3D. This project is a first-of-its-kind deployment at scale of AI/ML tools in a research centre operating in a low-resource setting.

Machine Learning Approaches Identify Chemical Features for Stage-Specific Antimalarial Compounds.

Efficacy data from diverse chemical libraries, screened against the various stages of the malaria parasite Plasmodium falciparum, including asexual blood stage (ABS) parasites and transmissible gametocytes, serve as a valuable reservoir of information on the chemical space of compounds that are either active (or not) against the parasite. We postulated that this data can be mined to define chemical features associated with the sole ABS activity and/or those that provide additional life cycle activity profiles like gametocytocidal activity. Additionally, this information could provide chemical features associated with inactive compounds, which could eliminate any future unnecessary screening of similar chemical analogs. Therefore, we aimed to use machine learning to identify the chemical space associated with stage-specific antimalarial activity. We collected data from various chemical libraries that were screened against the asexual (126 374 compounds) and sexual (gametocyte) stages of the parasite (93 941 compounds), calculated the compounds' molecular fingerprints, and trained machine learning models to recognize stage-specific active and inactive compounds. We were able to build several models that predict compound activity against ABS and dual activity against ABS and gametocytes, with Support Vector Machines (SVM) showing superior abilities with high recall (90 and 66%) and low false-positive predictions (15 and 1%). This allowed the identification of chemical features enriched in active and inactive populations, an important outcome that could be mined for essential chemical features to streamline hit-to-lead optimization strategies of antimalarial candidates. The predictive capabilities of the models held true in diverse chemical spaces, indicating that the ML models are therefore robust and can serve as a prioritization tool to drive and guide phenotypic screening and medicinal chemistry programs.

Mex3a marks drug-tolerant persister colorectal cancer cells that mediate relapse after chemotherapy.

Colorectal cancer (CRC) patient-derived organoids predict responses to chemotherapy. Here we used them to investigate relapse after treatment. Patient-derived organoids expand from highly proliferative LGR5+ tumor cells; however, we discovered that lack of optimal growth conditions specifies a latent LGR5+ cell state. This cell population expressed the gene MEX3A, is chemoresistant and regenerated the organoid culture after treatment. In CRC mouse models, Mex3a+ cells contributed marginally to metastatic outgrowth; however, after chemotherapy, Mex3a+ cells produced large cell clones that regenerated the disease. Lineage-tracing analysis showed that persister Mex3a+ cells downregulate the WNT/stem cell gene program immediately after chemotherapy and adopt a transient state reminiscent to that of YAP+ fetal intestinal progenitors. In contrast, Mex3a-deficient cells differentiated toward a goblet cell-like phenotype and were unable to resist chemotherapy. Our findings reveal that adaptation of cancer stem cells to suboptimal niche environments protects them from chemotherapy and identify a candidate cell of origin of relapse after treatment in CRC.

Zonation of Ribosomal DNA Transcription Defines a Stem Cell Hierarchy in Colorectal Cancer.

Colorectal cancers (CRCs) are composed of an amalgam of cells with distinct genotypes and phenotypes. Here, we reveal a previously unappreciated heterogeneity in the biosynthetic capacities of CRC cells. We discover that the majority of ribosomal DNA transcription and protein synthesis in CRCs occurs in a limited subset of tumor cells that localize in defined niches. The rest of the tumor cells undergo an irreversible loss of their biosynthetic capacities as a consequence of differentiation. Cancer cells within the biosynthetic domains are characterized by elevated levels of the RNA polymerase I subunit A (POLR1A). Genetic ablation of POLR1A-high cell population imposes an irreversible growth arrest on CRCs. We show that elevated biosynthesis defines stemness in both LGR5+ and LGR5- tumor cells. Therefore, a common architecture in CRCs is a simple cell hierarchy based on the differential capacity to transcribe ribosomal DNA and synthesize proteins.

ENABLE 2017, the First EUROPEAN PhD and Post-Doc Symposium. Session 4: From Discovery to Cure: The Future of Therapeutics.

The EUROPEAN ACADEMY FOR BIOMEDICAL SCIENCE (ENABLE) is an initiative funded by the European Union Horizon 2020 program involving four renowned European Research Institutes (Institute for Research in Biomedicine-IRB Barcelona, Spain; Radboud Institute for Molecular Life Sciences-RIMLS, the Netherlands; Novo Nordisk Foundation Center for Protein Research-NNF CPR, Denmark; European School of Molecular Medicine-SEMM, Italy) and an innovative science communication agency (Scienseed). With the aim of promoting biomedical science of excellence in Europe, ENABLE organizes an annual three-day international event. This gathering includes a top-level scientific symposium bringing together leading scientists, PhD students, and post-doctoral fellows; career development activities supporting the progression of young researchers and fostering discussion about opportunities beyond the bench; and outreach activities stimulating the interaction between science and society. The first European PhD and Postdoc Symposium, entitled "Breaking Down Complexity: Innovative Models and Techniques in Biomedicine", was hosted by the vibrant city of Barcelona. The scientific program of the conference was focused on the most recent advances and applications of modern techniques and models in biomedical research and covered a wide range of topics, from synthetic biology to translational medicine. Overall, the event was a great success, with more than 200 attendees from all over Europe actively participating in the symposium by presenting their research and exchanging ideas with their peers and world-renowned scientists.

ENABLE 2017, the First EUROPEAN PhD and Post-Doc Symposium. Session 3: In Vitro to In Vivo: Modeling Life in 3D.

The EUROPEAN ACADEMY FOR BIOMEDICAL SCIENCE (ENABLE) is an initiative funded by the European Union Horizon 2020 program involving four renowned European research institutes (Institute for Research in Biomedicine-IRB Barcelona, Spain; Radboud Institute for Molecular Life Sciences-RIMLS, the Netherlands; Novo Nordisk Foundation Center for Protein Research-NNF CPR, Denmark; European School of Molecular Medicine-SEMM, Italy) and an innovative science communication agency (Scienseed). With the aim to promote biomedical science of excellence in Europe, ENABLE organizes an annual three-day international event. This gathering includes a top-level scientific symposium bringing together leading scientists, PhD students, and post-doctoral fellows; career development activities supporting the progression of young researchers and fostering discussion about opportunities beyond the bench; outreach activities stimulating the interaction between science and society. The first European PhD and Postdoc Symposium, entitled "Breaking Down Complexity: Innovative models and techniques in biomedicine", was hosted by the vibrant city of Barcelona. The scientific program of the conference was focused on the most recent advances and applications of modern techniques and models in biomedical research and covered a wide range of topics, from synthetic biology to translational medicine. Overall, the event was a great success, with more than 200 attendees from all over Europe actively participating in the symposium by presenting their research and exchanging ideas with their peers and world-renowned scientists.

ENABLE 2017, the First European PhD and Post-Doc Symposium. Session 1: Building the Foundations of Biology: Synthetic and Cellular Research.

The European Academy for Biomedical Science (ENABLE) is an initiative funded by the European Union Horizon 2020 program involving four renowned European Research Institutes (Institute for Research in Biomedicine—IRB Barcelona, Spain; Radboud Institute for Molecular Life Sciences—RIMLS, the Netherlands; Novo Nordisk Foundation Center for Protein Research—NNF CPR, Denmark; European School of Molecular Medicine—SEMM, Italy) and an innovative science communication agency (Scienseed). With the aim of promoting biomedical science of excellence in Europe, ENABLE organizes an annual three-day international event. This gathering includes a top-level scientific symposium bringing together leading scientists, PhD students, and post-doctoral fellows; career development activities supporting the progression of young researchers and fostering discussion about opportunities beyond the bench; and outreach activities stimulating the interaction between science and society. The first European PhD and Postdoc Symposium, entitled “Breaking Down Complexity: Innovative Models and Techniques in Biomedicine”, was hosted by the vibrant city of Barcelona. The scientific program of the conference was focused on the most recent advances and applications of modern techniques and models in biomedical research and covered a wide range of topics, from synthetic biology to translational medicine. Overall, the event was a great success, with more than 200 attendees from all over Europe actively participating in the symposium by presenting their research and exchanging ideas with their peers and world-renowned scientists.

ENABLE 2017, the First European PhD and Post-Doc Symposium. Session 2: The OMICS Revolution.

The European Academy for Biomedical Science (ENABLE) is an initiative funded by the European Union Horizon 2020 program involving four renowned European Research Institutes (Institute for Research in Biomedicine-IRB Barcelona, Spain; Radboud Institute for Molecular Life Sciences-RIMLS, The Netherlands; Novo Nordisk Foundation Center for Protein Research-NNF CPR, Denmark; European School of Molecular Medicine-SEMM, Italy) and an innovative science communication agency (Scienseed). With the aim of promoting biomedical science of excellence in Europe, ENABLE organizes an annual three-day international event. This gathering includes a top-level scientific symposium bringing together leading scientists, PhD students, and post-doctoral fellows; career development activities supporting the progression of young researchers and fostering discussion about opportunities beyond the bench; and outreach activities stimulating the interaction between science and society. The first European PhD and Post-Doc Symposium, entitled "Breaking Down Complexity: Innovative Models and Techniques in Biomedicine", was hosted by the vibrant city of Barcelona. The scientific program of the conference was focused on the most recent advances and applications of modern techniques and models in biomedical research and covered a wide range of topics, from synthetic biology to translational medicine. Overall, the event was a great success, with more than 200 attendees from all over Europe actively participating in the symposium by presenting their research and exchanging ideas with their peers and world-renowned scientists.

A genome editing approach to study cancer stem cells in human tumors.

The analysis of stem cell hierarchies in human cancers has been hampered by the impossibility of identifying or tracking tumor cell populations in an intact environment. To overcome this limitation, we devised a strategy based on editing the genomes of patient-derived tumor organoids using CRISPR/Cas9 technology to integrate reporter cassettes at desired marker genes. As proof of concept, we engineered human colorectal cancer (CRC) organoids that carry EGFP and lineage-tracing cassettes knocked in the LGR5 locus. Analysis of LGR5-EGFP+ cells isolated from organoid-derived xenografts demonstrated that these cells express a gene program similar to that of normal intestinal stem cells and that they propagate the disease to recipient mice very efficiently. Lineage-tracing experiments showed that LGR5+ CRC cells self-renew and generate progeny over long time periods that undergo differentiation toward mucosecreting- and absorptive-like phenotypes. These genetic experiments confirm that human CRCs adopt a hierarchical organization reminiscent of that of the normal colonic epithelium. The strategy described herein may have broad applications to study cell heterogeneity in human tumors.