Building a reproducible single-cell experimental workflow to capture tumour cell persistence

Projektinformationen

PERSIST-SEQ

ID Finanzhilfevereinbarung: 101007937

DOI

10.3030/101007937

EK-Unterschriftsdatum 28 Juni 2021

Startdatum 1 Juli 2021

Enddatum 31 Dezember 2027

Finanziert unter

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Gesamtkosten

€ 14 989 292,00

EU-Beitrag

€ 7 057 980,00

Koordiniert durch

STICHTING ONCODE INSTITUTE
Netherlands

Periodic Reporting for period 3 - PERSIST-SEQ (Building a reproducible single-cell experimental workflow to capture tumour cell persistence)

Berichtszeitraum: 2024-01-01 bis 2024-12-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

PERSIST-SEQ’s mission is to develop a standardised approach to single-cell sequencing workflows for the study of cells pre-treatment, at minimal residual disease (‘drug tolerant persister cells’) and at relapse. In so doing, we will create a connected community of researchers and industry parties skilled in the generation and interpretation of single- cell RNA-sequencing data. PERSIST-SEQ’s gold standard operating procedures and centralised European data infrastructure are envisioned to be sustained and built upon in an open access model, reducing duplication of effort, promoting collaboration across disciplines, and ensuring efficient adoption of state-of-the-art single cell technologies.

O1. Design and evaluate a reproducible single-cell sequencing workflow that can robustly extract and disentangle genetic, epigenetic and expression signatures that determine inherent and acquired resistance at the single-cell level, in the context of tumour cell populations of any level of diversity and the tumour microenvironment. This workflow will include the following steps: (1) Experimental design (2) Sampling, coding, storage and logistics, (3) Single-cell extraction and barcoding, (4) Single-cell & spatial sequencing, (5) Data storage, analysis, integration and interpretation and (6) Guidance on follow-up experiments.
O2. Incorporate beyond-state-of-the-art single-cell sequencing approaches and where necessary refine and improve them to handle complex biological samples (see Box 1 above for details).
O3. Develop novel PDO and/or PDX-based approaches to study the biology of plasticity in drug tolerant persister cells (DTPs).
O4. Select and analyse at the single cell level, tumour samples from patients affected by solid tumours (e.g. CRC) at baseline, on response and at progression to specific treatments.
O5. Devise blueprints (SOPs, guidelines, technical requirements, and quality assurance measures) of the developed sequencing workflow and experimental approaches to enable their reproducibility across academic and industrial research settings.
O6. Expand existing data infrastructures to provide wide access to single-cell sequencing data (Open Data) and ensure FAIRness of results, in line with parallel initiatives such as the Human Cell Atlas and COSMIC.
O7. Identify and replicate the molecular signatures of DTPs in clinical samples, cell lines, and 3D models (PDOs and PDXs).

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

WP1
• Organization of regular project meetings, including monthly Management Team meetings and bi-monthly Steering Committee meetings. In September 2024 we held our 3rd Annual Consortium Meeting which was hosted by Lygature in Utrecht, The Netherlands.
• Creation of bi-monthly internal newsletter with key updates for all consortium members
• The Scientific Advisory Board has held a meeting together with the Management Team, and they are regularly consulted when needed. We have also finalized the instalment of the Multi-stakeholder Advisory Board in this period.
• The first project results were analysed on patentability


WP2
• The Management team has created a Study Technical Plan that describes the proposed samples for submission for single-cell sequencing and that must be completed by each partner and approved by the team before the samples can be submitted. This Study Technical Plan includes experimental design information, whether any ethical constraints on data sharing, suitable QC metrics generated and analysis plans.
• The Management Team meets on a monthly basis to review projects, technology development, coordinate activity, review budget spend, ethical issues and communications.
• In total WP2 has reviewed and approved 21 Study Technical Plans


WP3, WP4, WP5
• The work performed by this group has led to the creation of the first SOPs for dissociating cancer cell lines or 3D organoids, Fixation of cells and nuclei and tissue and cryopreservation prior to shipping for single-cell sequencing at Single Cell Discoveries, Netherlands. These SOPs have been uploaded to the PERSIST-SEQ SharePoint for all partners to access
• WP5 has processed, sequenced and prepared data for downstream analysis of 374 samples among 37 different studies
• Overall, we have sequenced so far around 1.8 Million cells of which 407,000 are expected to be persister cells (note, 500K of these single cells are from a pilot spatial transcriptomics study using the 10X Visium HD platform).
• We have processed 6 different types of samples: cell lines, organoids, patient derived xenografts, cell derived xenografts, patient biopsies and genetically modified mouse models (GEMM).


WP6
• At present we have limited activity in this WP given the focus initially on establishing robust single cell sequencing protocols using the 10X Genomics platform – we anticipate that this WP will be most relevant for clinical sample studies or in vivo mouse models.
• We are actively exploring how we access spatial transcriptomics as a capability to offer to the consortium partners (specifically for GEMM and clinical samples).

WP7
• Established a monthly WP7 meeting that includes the lead Bioinformatician for each Efpia and non-Efpia partner to identify and prioritise single cell analysis algorithms that should be incorporated into the analysis pipeline that will be used to analyse all samples and is web-accessible to the bioinformaticians of each partner.
• This WP7 meeting is a forum to identify and prioritise single cell analysis algorithms that should be incorporated into the analysis pipeline that will be used to analyse all samples and is web-accessible to the bioinformaticians of each partner.
• WP7 previously agreed to use an established Galaxy workflow created to support the Human Cell Atlas at the European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus and to part fund a position in the EBI lab of Irene Papatheodorou (Gene Expression Team Leader, EMBL-EBI) – using an established platform as the foundation for PERSIST-SEQ (rather than building as new) will allow us to start analyses quickly. The Galaxy workflow is ideal to add additional modules for data analysis as we identify these from publications/conferences as part of the WP7 monthly meetings. Since the previous Periodic Report we have used this cloud-based Galaxy workflow to build a suite of analysis tools for single cell data. As a web-based platform, this is accessible to all the consortium members and a video tutorial for less expert users has been created to improve the accessibility of the platform.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

The project will deliver (a) a state-of-the-art single cell analysis pipeline in a cloud-based environment that is specific to the analysis of cancer models and (b) insights into the biology of cancer persister cells made from analysis of single cells from a range of cancer models and drug treatments using this analysis workflow. The project will generate among the largest such single-cell data from cancer models and we will constantly publish such data as we make new discoveries in this field. Both of these outputs will have impacts in the field of cancer research (providing new cancer targets and identification of the pathways that persister cells use to avoid cell death) and in the socio-economic arena (new drug targets will accelerate drug discovery programs in this area and ultimately lead to more effective treatments for cancer patients).

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