A single-cell atlas of non-haematopoietic cells in human lymph nodes and lymphoma reveals a landscape of stromal remodelling

The activities of non-haematopoietic cells (NHCs), including mesenchymal stromal cells and endothelial cells, in lymphomas are reported to underlie lymphomagenesis. However, our understanding of lymphoma NHCs has been hampered by unexplained NHC heterogeneity, even in normal human lymph nodes (LNs). Here we constructed a single-cell transcriptome atlas of more than 100,000 NHCs collected from 27 human samples, including LNs and various nodal lymphomas, and it revealed 30 distinct subclusters, including some that were previously unrecognized. Notably, this atlas was useful for comparative analyses with lymphoma NHCs, which revealed an unanticipated landscape of subcluster-specific changes in gene expression and interaction with malignant cells in follicular lymphoma NHCs. This facilitates our understanding of stromal remodelling in lymphoma and highlights potential clinical biomarkers. Our study largely updates NHC taxonomy in human LNs and analysis of disease status, and provides a rich resource and deeper insights into LN and lymphoma biology to advance lymphoma management and therapy.

The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of all covariates tested A description of any assumptions or corrections, such as tests of normality and adjustment for multiple comparisons A full description of the statistical parameters including central tendency (e.g. means) or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or associated estimates of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of freedom and P value noted Give P values as exact values whenever suitable.

For Bayesian analysis, information on the choice of priors and Markov chain Monte Carlo settings
For hierarchical and complex designs, identification of the appropriate level for tests and full reporting of outcomes Estimates of effect sizes (e.g. Cohen's d, Pearson's r), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of computer code Data collection FACSAria II and III (BD Biosciences) were used for acquisition of flow cytometry data. Chromium Single Cell 3' Reagent kits (V3) (10X Genomics) were used for single-cell RNA library preparation. Libraries were sequenced on an Illumina HiSeq X Ten system, mapped to the human genome (build GRCh38), and demultiplexed using CellRanger pipelines (10x Genomics, version 3.1.0).
The codes for key computational analyses are available on GitHub at http://github.com/yoshiakiabe1018/Stroma01. For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

April 2020
Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability scRNA-seq data that support the findings of this study have been deposited at the European Genome-Phenome Archive (https://ega-archive.org) database and can be retrieved using the accession number EGAD00001008311. For survival analysis, a DNA microarray dataset from Leich et al66 was downloaded from the Gene Expression Omnibus (GEO) (accession number: GSE16131). For mapping of scRNA-seq data, GRCh38 (https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.39) was used. All other data are available from the corresponding authors on reasonable request. Source data are provided with this paper.

Field-specific reporting
Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative.

Sample size
No statistical method was used to determine sample size a priori. The number of human lymph node and lymphoma samples was highly restricted due to the limited availability of these samples in clinical settings.
Data exclusions Pre-processed single-cell data from each sample were further processed and analysed individually using R package Seurat on RStudio. After removing ribosomal genes, genes expressed in fewer than 3 cells, and cells expressing fewer than 200 genes, we filtered out cells with less than 200 unique feature counts (low quality cells). Cells with unique feature counts greater than three times the median value (possible doublets) and/or cells with more than twice the median number of mitochondrial genes (possible apoptotic or lysed cells) were also removed. After the data integration and clustering analysis, we removed data of NHC subclusters considered possible doublets as characterized by high expressions of marker genes for different NHC components and incongruously high unique feature counts.

Replication
All experiments were independently replicated at least once to verify reproducibility.
Randomization Not relevant -no treatment group.

Blinding
Not relevant -no treatment group.

Reporting for specific materials, systems and methods
We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.

April 2020
Recombinant protein binding assay: PE-anti-human IgG Fc (R&D systems, FAB110P). The dilution is described in the Methods section of the manuscript.
Antibodies used for immunofluorescence staining were listed in Supplementary Table 9.

Validation
All the antibodies used in this study have been tested by the manufacturer and have been cited by other authors and references are available on the manufacturer's websites. We provide catalog numbers for all the antibodies in the Methods section of the manuscript or in Supplementary Table 9 as readers can retrieve the information of the antibodies. We have further evaluated the specificity of the antibodies in our samples by analyzing the distribution of the antibody signals and the absence of the antibody signals in the regions where the target protein was not supposed to be expressed.

Human research participants
Policy information about studies involving human research participants

Population characteristics
Supplementary Table 1 summarises the characteristics of patients in metastasis-free lymph node and follicular lymphoma cohorts. Metastasis-free lymph node cohort consists of neoplasm-bearing patients (n = 9) who had undergone surgical LN dissection. The median age of the patients in this cohort is 66 years old. Follicular lymphoma cohort consists of 10 patients with the median age of 59. Among the follicular lymphoma patients, six patients were newly diagnosed cases. Most of the follicular lymphoma patients (n = 9) were with pathological grade of 1-2. Supplementary Table 7 summarises the characteristics of patients in peripheral T-cell lymphoma cohort and diffuse large Bcell lymphoma transformed from follicular lymphoma cohort. Peripheral T-cell lymphoma cohort consists of five newly diagnosed patients with various subtypes of lymphoma with the median age of 78. Diffuse large B-cell lymphoma transformed from follicular lymphoma cohort consists of three patients. Additional follicular lymphoma samples for functional experiments were collected from eight patients. Characteristics of follicular lymphoma patients in the additional cohort is summarised in Supplementary Table 10.

Recruitment
Samples were prospectively collected from patients who agreed to participate in the study. There were no other criteria for patient selection. There is no self-selection bias or other biases in recruitment.

Ethics oversight
This study was approved by the Ethics Committee of the University of Tsukuba Hospital and the review boards of associated institutions that provided human samples (Kameda Medical Center, NTT Medical Center Tokyo, and Mito Medical Center) and conducted according to all relevant ethical regulations regarding human patients. Written informed consent was obtained from all participating patients. The participants were not compensated for their participation.
Note that full information on the approval of the study protocol must also be provided in the manuscript.

Flow Cytometry
Plots Confirm that: The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.
Single-cell isolation of FL haematopoietic cells: After thawing, cell suspensions were filtered through a 70 μm mesh and incubated with 7-AAD Viability Staining Solution for 10 min in the dark.