Replication Study: Biomechanical remodeling of the microenvironment by stromal caveolin-1 favors tumor invasion and metastasis

Harmonizing the Generation and Pre-publication Stewardship of FAIR bioimage data

Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured bioimage data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable bioimage data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled "Enabling Global Image Data Sharing in the Life Sciences," which is published in parallel and addresses the need to build the cyberinfrastructure for sharing bioimage data (arXiv:2401.13023 [q-bio.OT], https://doi.org/10.48550/arXiv.2401.13023). Here, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse bioimage data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made generating community standard practices for imaging Quality Control (QC) and metadata (Faklaris et al., 2022; Hammer et al., 2021; Huisman et al., 2021; Microscopy Australia, 2016; Montero Llopis et al., 2021; Rigano et al., 2021; Sarkans et al., 2021). We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges and democratize access to common practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.

Community-developed checklists for publishing images and image analyses

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.

Toward a common standard for data and specimen provenance in life sciences

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by the quality of the samples, the experimental methods, and the data analysis. Therefore, a comprehensive and precise documentation of the pre-analytical conditions, the analytical procedures, and the data processing are essential to be able to assess the validity of the research results. With the increasing importance of the exchange, reuse, and sharing of data and samples, procedures are required that enable cross-organizational documentation, traceability, and non-repudiation. At present, this information on the provenance of samples and data is mostly either sparse, incomplete, or incoherent. Since there is no uniform framework, this information is usually only provided within the organization and not interoperably. At the same time, the collection and sharing of biological and environmental specimens increasingly require definition and documentation of benefit sharing and compliance to regulatory requirements rather than consideration of pure scientific needs. In this publication, we present an ongoing standardization effort to provide trustworthy machine-actionable documentation of the data lineage and specimens. We would like to invite experts from the biotechnology and biomedical fields to further contribute to the standard.

Community-developed checklists for publishing images and image analyses

Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality and explanatory power of microscopy data is in publications.

Tumor-derived Cav-1 promotes pre-metastatic niche formation and lung metastasis in breast cancer

Rationale: Breast cancer (BC), as one of the most frequently diagnosed cancer, has a poor prognosis due to the development of distant metastasis. Among the BC metastatic sites, lung is one of the most common sites. Caveolin-1 (Cav-1) is a functional membrane protein that plays a vital role in tumor metastasis. Although studies have revealed that Cav-1 levels were elevated in patients with advanced cancer, whether Cav-1 affects BC lung metastasis by influencing the formation of pre-metastatic niche (PMN) through exosomes has not been explored. Methods: Differential ultracentrifugation, transmission electron microscopy and nanoparticle tracking analysis were used to verify the presence of exosomes. Transwell assays were used to examine the biological effects of exosomes containing Cav-1. Both in vitro cell cultures and mammary tumor cell-induced mouse models were used to assess the lung metastasis. The regulatory mechanisms of PMN formation were revealed using western blot, flow cytometry, RT-qPCR, immunofluorescence assays, gene overexpression assays and RNA interference assays. Results: Exosomes have critical functions in transporting Cav-1 between primary BC and metastatic organ microenvironments. Cav-1 in BC-derived exosomes can act as a signaling molecule to mediate intercellular communication and regulate the PMN before lung metastasis by regulating the expression of PMN marker genes and inflammatory chemokines in lung epithelial cells, promoting the secretion of tenascin-C (TnC) in lung fibroblasts to cause extracellular matrix (ECM) deposition, and inhibiting the PTEN/CCL2/VEGF-A signaling pathway in lung macrophages to facilitate their M2-type polarization and angiogenesis. Conclusion: Our study investigated the mechanisms of lung PMN formation induced by Cav-1 in BC-derived exosomes. Our data may provide new directions for exploring the mechanisms and developing treatment strategies of BC lung metastasis.

Overexpression of pressure-responsive miRNA-5703 inhibits pressure-induced growth and metastasis of liver cancer

A vast majority of liver cancers coexist with cirrhosis and/or portal hypertension. A high-pressure tumour microenvironment may lead to malignant progression of liver cancer. Through quantitative reverse transcription-polymerase chain reaction, we found that miRNA-5703 was expressed at low levels in HepG2 and Huh-7 cells and pressure-treated MHCC97H implanted mouse cancer tissues, while its potential target gene, sarcoma gene (SRC), was highly expressed. The expression of miRNA-5703 was higher in liver cancer tissues from Barcelona Clinic Liver Cancer (BCLC) stage A1 patients than those from BCLC stage A2-D patients, whereas SRC showed the opposite expression pattern. Bioinformatics analysis, luciferase reporter assay, and western blotting were performed to verify the relationship between miRNA-5703 and its potential target SRC. Using intravital imaging and immunohistochemistry, we demonstrated that pressure promotes tumour growth in subcutaneous tumourigenesis nude mice, and overexpression of miRNA-5703 significantly downregulated Ki67 and upregulated NM23 in tumour tissues of mice, implying the blockage of tumour growth and metastasis. The activation of proliferation, migration, and invasion of HepG2 and Huh-7 cells by pressure, and inhibition by overexpressing miRNA-5703 were observed by cell counting kit-8 assay, flow cycle assay, transwell assay, and wound healing assay. After the intervention of pressure, inhibitor, and lentivirus to hepatoma cells, SRC, focal adhesion kinase (FAK), phosphatidylinositol 3-kinase (PI3K), serum/glucocorticoid regulated kinase-3 (SGK3), phosphoinositide dependent protein kinase 1 (PDK1), and paxillin were upregulated, and forkhead box O1 (FOXO1) and cyclin dependent kinase inhibitor 1B (P27^Kip1) were downregulated in pressure-loaded hepatoma cells, which could be reversed by overexpression of miRNA-5703 or SRC knockdown. In conclusion, upregulation of miRNA-5703 inhibited pressure-induced growth and metastasis by suppressing the SRC-FAK-FOXO1 axis and SRC-paxillin axis. This novel perspective may be conducive to the mechano-inspired anticancer drugs of liver cancer.

Challenges for assessing replicability in preclinical cancer biology

We conducted the Reproducibility Project: Cancer Biology to investigate the replicability of preclinical research in cancer biology. The initial aim of the project was to repeat 193 experiments from 53 high-impact papers, using an approach in which the experimental protocols and plans for data analysis had to be peer reviewed and accepted for publication before experimental work could begin. However, the various barriers and challenges we encountered while designing and conducting the experiments meant that we were only able to repeat 50 experiments from 23 papers. Here we report these barriers and challenges. First, many original papers failed to report key descriptive and inferential statistics: the data needed to compute effect sizes and conduct power analyses was publicly accessible for just 4 of 193 experiments. Moreover, despite contacting the authors of the original papers, we were unable to obtain these data for 68% of the experiments. Second, none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments, so we had to seek clarifications from the original authors. While authors were extremely or very helpful for 41% of experiments, they were minimally helpful for 9% of experiments, and not at all helpful (or did not respond to us) for 32% of experiments. Third, once experimental work started, 67% of the peer-reviewed protocols required modifications to complete the research and just 41% of those modifications could be implemented. Cumulatively, these three factors limited the number of experiments that could be repeated. This experience draws attention to a basic and fundamental concern about replication – it is hard to assess whether reported findings are credible.

Challenges for assessing replicability in preclinical cancer biology

We conducted the Reproducibility Project: Cancer Biology to investigate the replicability of preclinical research in cancer biology. The initial aim of the project was to repeat 193 experiments from 53 high-impact papers, using an approach in which the experimental protocols and plans for data analysis had to be peer reviewed and accepted for publication before experimental work could begin. However, the various barriers and challenges we encountered while designing and conducting the experiments meant that we were only able to repeat 50 experiments from 23 papers. Here we report these barriers and challenges. First, many original papers failed to report key descriptive and inferential statistics: the data needed to compute effect sizes and conduct power analyses was publicly accessible for just 4 of 193 experiments. Moreover, despite contacting the authors of the original papers, we were unable to obtain these data for 68% of the experiments. Second, none of the 193 experiments were described in sufficient detail in the original paper to enable us to design protocols to repeat the experiments, so we had to seek clarifications from the original authors. While authors were extremely or very helpful for 41% of experiments, they were minimally helpful for 9% of experiments, and not at all helpful (or did not respond to us) for 32% of experiments. Third, once experimental work started, 67% of the peer-reviewed protocols required modifications to complete the research and just 41% of those modifications could be implemented. Cumulatively, these three factors limited the number of experiments that could be repeated. This experience draws attention to a basic and fundamental concern about replication - it is hard to assess whether reported findings are credible.

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model

Rigorous record-keeping and quality control are required to ensure the quality, reproducibility and value of imaging data. The 4DN Initiative and BINA here propose light Microscopy Metadata specifications that extend the OME data model, scale with experimental intent and complexity, and make it possible for scientists to create comprehensive records of imaging experiments.

QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy

A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated , quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70% of researchers have tried and failed to repeat another scientist's experiments, while more than half have even failed to reproduce their own experiments. One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique. Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g. DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common standards and guidelines for quality assessment and reproducibility. In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models and tools, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper (1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; (2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists, bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers and observers of such; (3) outlines the current actions of the QUAREP-LiMi initiative and (4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.

Micro-Meta App: an interactive tool for collecting microscopy metadata based on community specifications

For quality, interpretation, reproducibility and sharing value, microscopy images should be accompanied by detailed descriptions of the conditions that were used to produce them. Micro-Meta App is an intuitive, highly interoperable, open-source software tool that was developed in the context of the 4D Nucleome (4DN) consortium and is designed to facilitate the extraction and collection of relevant microscopy metadata as specified by the recent 4DN-BINA-OME tiered-system of Microscopy Metadata specifications. In addition to substantially lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training purposes.

Rethinking research into metastasis

The partial success of an attempt to repeat findings in cancer biology highlights the need to improve study designs for preclinical research into metastasis and the targeting of cancer cells.