Differential pre-malignant programs and microenvironment chart distinct paths to malignancy in human colorectal polyps.

Colorectal cancers (CRCs) arise from precursor polyps whose cellular origins, molecular heterogeneity, and immunogenic potential may reveal diagnostic and therapeutic insights when analyzed at high resolution. We present a single-cell transcriptomic and imaging atlas of the two most common human colorectal polyps, conventional adenomas and serrated polyps, and their resulting CRC counterparts. Integrative analysis of 128 datasets from 62 participants reveals adenomas arise from WNT-driven expansion of stem cells, while serrated polyps derive from differentiated cells through gastric metaplasia. Metaplasia-associated damage is coupled to a cytotoxic immune microenvironment preceding hypermutation, driven partly by antigen-presentation differences associated with tumor cell-differentiation status. Microsatellite unstable CRCs contain distinct non-metaplastic regions where tumor cells acquire stem cell properties and cytotoxic immune cells are depleted. Our multi-omic atlas provides insights into malignant progression of colorectal polyps and their microenvironment, serving as a framework for precision surveillance and prevention of CRC.

Tumour evolution and microenvironment interactions in 2D and 3D space.

To study the spatial interactions among cancer and non-cancer cells1, we here examined a cohort of 131 tumour sections from 78 cases across 6 cancer types by Visium spatial transcriptomics (ST). This was combined with 48 matched single-nucleus RNA sequencing samples and 22 matched co-detection by indexing (CODEX) samples. To describe tumour structures and habitats, we defined 'tumour microregions' as spatially distinct cancer cell clusters separated by stromal components. They varied in size and density among cancer types, with the largest microregions observed in metastatic samples. We further grouped microregions with shared genetic alterations into 'spatial subclones'. Thirty five tumour sections exhibited subclonal structures. Spatial subclones with distinct copy number variations and mutations displayed differential oncogenic activities. We identified increased metabolic activity at the centre and increased antigen presentation along the leading edges of microregions. We also observed variable T cell infiltrations within microregions and macrophages predominantly residing at tumour boundaries. We reconstructed 3D tumour structures by co-registering 48 serial ST sections from 16 samples, which provided insights into the spatial organization and heterogeneity of tumours. Additionally, using an unsupervised deep-learning algorithm and integrating ST and CODEX data, we identified both immune hot and cold neighbourhoods and enhanced immune exhaustion markers surrounding the 3D subclones. These findings contribute to the understanding of spatial tumour evolution through interactions with the local microenvironment in 2D and 3D space, providing valuable insights into tumour biology.

Epigenetic regulation during cancer transitions across 11 tumour types.

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasis1-4. Although the genetic contributions to oncogenic transitions have been investigated, epigenetic drivers remain less understood. Here we constructed a pan-cancer epigenetic and transcriptomic atlas using single-nucleus chromatin accessibility data (using single-nucleus assay for transposase-accessible chromatin) from 225 samples and matched single-cell or single-nucleus RNA-sequencing expression data from 206 samples. With over 1 million cells from each platform analysed through the enrichment of accessible chromatin regions, transcription factor motifs and regulons, we identified epigenetic drivers associated with cancer transitions. Some epigenetic drivers appeared in multiple cancers (for example, regulatory regions of ABCC1 and VEGFA; GATA6 and FOX-family motifs), whereas others were cancer specific (for example, regulatory regions of FGF19, ASAP2 and EN1, and the PBX3 motif). Among epigenetically altered pathways, TP53, hypoxia and TNF signalling were linked to cancer initiation, whereas oestrogen response, epithelial-mesenchymal transition and apical junction were tied to metastatic transition. Furthermore, we revealed a marked correlation between enhancer accessibility and gene expression and uncovered cooperation between epigenetic and genetic drivers. This atlas provides a foundation for further investigation of epigenetic dynamics in cancer transitions.

Combinatorial Transcriptional Profiling of Mouse and Human Enteric Neurons Identifies Shared and Disparate Subtypes In Situ.

BACKGROUND & AIMS: The enteric nervous system (ENS) coordinates essential intestinal functions through the concerted action of diverse enteric neurons (ENs). However, integrated molecular knowledge of EN subtypes is lacking. To compare human and mouse ENs, we transcriptionally profiled healthy ENS from adult humans and mice. We aimed to identify transcripts marking discrete neuron subtypes and visualize conserved EN subtypes for humans and mice in multiple bowel regions. METHODS: Human myenteric ganglia and adjacent smooth muscle were isolated by laser-capture microdissection for RNA sequencing. Ganglia-specific transcriptional profiles were identified by computationally subtracting muscle gene signatures. Nuclei from mouse myenteric neurons were isolated and subjected to single-nucleus RNA sequencing, totaling more than 4 billion reads and 25,208 neurons. Neuronal subtypes were defined using mouse single-nucleus RNA sequencing data. Comparative informatics between human and mouse data sets identified shared EN subtype markers, which were visualized in situ using hybridization chain reaction. RESULTS: Several EN subtypes in the duodenum, ileum, and colon are conserved between humans and mice based on orthologous gene expression. However, some EN subtype-specific genes from mice are expressed in completely distinct morphologically defined subtypes in humans. In mice, we identified several neuronal subtypes that stably express gene modules across all intestinal segments, with graded, regional expression of 1 or more marker genes. CONCLUSIONS: Our combined transcriptional profiling of human myenteric ganglia and mouse EN provides a rich foundation for developing novel intestinal therapeutics. There is congruency among some EN subtypes, but we note multiple species differences that should be carefully considered when relating findings from mouse ENS research to human gastrointestinal studies.

Succinate Produced by Intestinal Microbes Promotes Specification of Tuft Cells to Suppress Ileal Inflammation.

BACKGROUND & AIMS: Countries endemic for parasitic infestations have a lower incidence of Crohn's disease (CD) than nonendemic countries, and there have been anecdotal reports of the beneficial effects of helminths in CD patients. Tuft cells in the small intestine sense and direct the immune response against eukaryotic parasites. We investigated the activities of tuft cells in patients with CD and mouse models of intestinal inflammation. METHODS: We used microscopy to quantify tuft cells in intestinal specimens from patients with ileal CD (n = 19), healthy individuals (n = 14), and TNFΔARE/+ mice, which develop Crohn's-like ileitis. We performed single-cell RNA sequencing, mass spectrometry, and microbiome profiling of intestinal tissues from wild-type and Atoh1-knockout mice, which have expansion of tuft cells, to study interactions between microbes and tuft cell populations. We assessed microbe dependence of tuft cell populations using microbiome depletion, organoids, and microbe transplant experiments. We used multiplex imaging and cytokine assays to assess alterations in inflammatory response following expansion of tuft cells with succinate administration in TNFΔARE/+ and anti-CD3E CD mouse models. RESULTS: Inflamed ileal tissues from patients and mice had reduced numbers of tuft cells, compared with healthy individuals or wild-type mice. Expansion of tuft cells was associated with increased expression of genes that regulate the tricarboxylic acid cycle, which resulted from microbe production of the metabolite succinate. Experiments in which we manipulated the intestinal microbiota of mice revealed the existence of an ATOH1-independent population of tuft cells that was sensitive to metabolites produced by microbes. Administration of succinate to mice expanded tuft cells and reduced intestinal inflammation in TNFΔARE/+ mice and anti-CD3E-treated mice, increased GATA3+ cells and type 2 cytokines (IL22, IL25, IL13), and decreased RORGT+ cells and type 17 cytokines (IL23) in a tuft cell-dependent manner. CONCLUSIONS: We found that tuft cell expansion reduced chronic intestinal inflammation in mice. Strategies to expand tuft cells might be developed for treatment of CD.

Dual indexed library design enables compatibility of in-Drop single-cell RNA-sequencing with exAMP chemistry sequencing platforms.

BACKGROUND: The increasing demand of single-cell RNA-sequencing (scRNA-seq) experiments, such as the number of experiments and cells queried per experiment, necessitates higher sequencing depth coupled to high data quality. New high-throughput sequencers, such as the Illumina NovaSeq 6000, enables this demand to be filled in a cost-effective manner. However, current scRNA-seq library designs present compatibility challenges with newer sequencing technologies, such as index-hopping, and their ability to generate high quality data has yet to be systematically evaluated. RESULTS: Here, we engineered a dual-indexed library structure, called TruDrop, on top of the inDrop scRNA-seq platform to solve these compatibility challenges, such that TruDrop libraries and standard Illumina libraries can be sequenced alongside each other on the NovaSeq. On scRNA-seq libraries, we implemented a previously-documented countermeasure to the well-described problem of index-hopping, demonstrated significant improvements in base-calling accuracy on the NovaSeq, and provided an example of multiplexing twenty-four scRNA-seq libraries simultaneously. We showed favorable comparisons in transcriptional diversity of TruDrop compared with prior inDrop libraries. CONCLUSIONS: Our approach enables cost-effective, high throughput generation of sequencing data with high quality, which should enable more routine use of scRNA-seq technologies.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer (BC) is defined by distinct molecular subtypes with different cells of origin. The transcriptional networks that characterize the subtype-specific tumor-normal lineages are not established. In this work, we applied bulk, single-cell and single-nucleus multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 patients with BC to show characteristic links in gene expression and chromatin accessibility between BC subtypes and their putative cells of origin. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal BC and luminal mature cells and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like (SOX6 and KCNQ3) and luminal A/B (FAM155A and LRP1B) lineages. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like BC, suggesting an altered means of immune dysfunction. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single-cell level is a powerful tool for investigating cancer lineage and highlight transcriptional networks that define basal and luminal BC lineages.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

A contamination focused approach for optimizing the single-cell RNA-seq experiment.

Droplet-based single-cell RNA-seq (scRNA-seq) data are plagued by ambient contaminations caused by nucleic acid material released by dead and dying cells. This material is mixed into the buffer and is co-encapsulated with cells, leading to a lower signal-to-noise ratio. Although there exist computational methods to remove ambient contaminations post-hoc, the reliability of algorithms in generating high-quality data from low-quality sources remains uncertain. Here, we assess data quality before data filtering by a set of quantitative, contamination-based metrics that assess data quality more effectively than standard metrics. Through a series of controlled experiments, we report improvements that can minimize ambient contamination outside of tissue dissociation, via cell fixation, improved cell loading, microfluidic dilution, and nuclei versus cell preparation; many of these parameters are inaccessible on commercial platforms. We provide end-users with insights on factors that can guide their decision-making regarding optimizations that minimize ambient contamination, and metrics to assess data quality.

Matrix stiffness enhances cancer-macrophage interactions and M2-like macrophage accumulation in the breast tumor microenvironment.

The role of intratumor heterogeneity is becoming increasingly apparent in part due to expansion in single cell technologies. Clinically, tumor heterogeneity poses several obstacles to effective cancer therapy dealing with biomarker variability and treatment responses. Matrix stiffening is known to occur during tumor progression and contribute to pathogenesis in several cancer hallmarks, including tumor angiogenesis and metastasis. However, the effects of matrix stiffening on intratumor heterogeneity have not been thoroughly studied. In this study, we applied single-cell RNA sequencing to investigate the differences in the transcriptional landscapes between stiff and compliant MMTV-PyMT mouse mammary tumors. We found similar compositions of cancer and stromal subpopulations in compliant and stiff tumors but differential intercellular communication and a significantly higher concentration of tumor-promoting, M2-like macrophages in the stiffer tumor microenvironments. Interestingly, we found that cancer cells seeded on stiffer substrates recruited more macrophages. Furthermore, elevated matrix stiffness increased Colony Stimulating Factor 1 (CSF-1) expression in breast cancer cells and reduction of CSF-1 expression on stiffer substrates reduced macrophage recruitment. Thus, our results demonstrate that tissue phenotypes were conserved between stiff and compliant tumors but matrix stiffening altered cell-cell interactions which may be responsible for shifting the phenotypic balance of macrophages residing in the tumor microenvironment towards a pro-tumor progression M2 phenotype. STATEMENT OF SIGNIFICANCE: Cells within tumors are highly heterogeneous, posing challenges with treatment and recurrence. While increased tissue stiffness can promote several hallmarks of cancer, its effects on tumor heterogeneity are unclear. We used single-cell RNA sequencing to investigate the differences in the transcriptional landscapes between stiff and compliant MMTV-PyMT mouse mammary tumors. We found similar compositions of cancer and stromal subpopulations in compliant and stiff tumors but differential intercellular communication and a significantly higher concentration of tumor-promoting, M2-like macrophages in the stiffer tumor microenvironments. Using a biomaterial-based platform, we found that cancer cells seeded on stiffer substrates recruited more macrophages, supporting our in vivo findings. Together, our results demonstrate a key role of matrix stiffness in affecting cell-cell communication and macrophage recruitment.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

Pollock: fishing for cell states.

Motivation: The use of single-cell methods is expanding at an ever-increasing rate. While there are established algorithms that address cell classification, they are limited in terms of cross platform compatibility, reliance on the availability of a reference dataset and classification interpretability. Here, we introduce Pollock, a suite of algorithms for cell type identification that is compatible with popular single-cell methods and analysis platforms, provides a set of pretrained human cancer reference models, and reports interpretability scores that identify the genes that drive cell type classifications. Results: Pollock performs comparably to existing classification methods, while offering easily deployable pretrained classification models across a wide variety of tissue and data types. Additionally, it demonstrates utility in immune pan-cancer analysis. Availability and implementation: Source code and documentation are available at https://github.com/ding-lab/pollock. Pretrained models and datasets are available for download at https://zenodo.org/record/5895221. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition. Mapping mutations and copy number events distinguished tumor populations from normal and transitional cells, including acinar-to-ductal metaplasia and pancreatic intraepithelial neoplasia. Pathology-assisted deconvolution of spatial transcriptomic data identified tumor and transitional subpopulations with distinct histological features. We showed coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin in tumor cells. Chemo-resistant samples contain a threefold enrichment of inflammatory cancer-associated fibroblasts that upregulate metallothioneins. Our study reveals a deeper understanding of the intricate substructure of pancreatic ductal adenocarcinoma tumors that could help improve therapy for patients with this disease.

A cross-platform informatics system for the Gut Cell Atlas: integrating clinical, anatomical and histological data.

The Gut Cell Atlas (GCA), an initiative funded by the Helmsley Charitable Trust, seeks to create a reference platform to understand the human gut, with a specific focus on Crohn's disease. Although a primary focus of the GCA is on focusing on single-cell profiling, we seek to provide a framework to integrate other analyses on multi-modality data such as electronic health record data, radiological images, and histology tissues/images. Herein, we use the research electronic data capture (REDCap) system as the central tool for a secure web application that supports protected health information (PHI) restricted access. Our innovations focus on addressing the challenges with tracking all specimens and biopsies, validating manual data entry at scale, and sharing organizational data across the group. We present a scalable, cross-platform barcode printing/record system that integrates with REDCap. The central informatics infrastructure to support our design is a tuple table to track longitudinal data entry and sample tracking. The current data collection (by December 2020) is illustrated with types and formats of the data that the system collects. We estimate that one terabyte is needed for data storage per patient study. Our proposed data sharing informatics system addresses the challenges with integrating physical sample tracking, large files, and manual data entry with REDCap.

An interspecies translation model implicates integrin signaling in infliximab-resistant inflammatory bowel disease.

Anti-tumor necrosis factor (anti-TNF) therapy resistance is a major clinical challenge in inflammatory bowel disease (IBD), due, in part, to insufficient understanding of disease-site, protein-level mechanisms. Although proteomics data from IBD mouse models exist, data and phenotype discrepancies contribute to confounding translation from preclinical animal models of disease to clinical cohorts. We developed an approach called translatable components regression (TransComp-R) to overcome interspecies and trans-omic discrepancies between mouse models and human subjects. TransComp-R combines mouse proteomic data with patient pretreatment transcriptomic data to identify molecular features discernable in the mouse data that are predictive of patient response to therapy. Interrogating the TransComp-R models revealed activated integrin pathway signaling in patients with anti-TNF-resistant colonic Crohn's disease (cCD) and ulcerative colitis (UC). As a step toward validation, we performed single-cell RNA sequencing (scRNA-seq) on biopsies from a patient with cCD and analyzed publicly available immune cell proteomics data to characterize the immune and intestinal cell types contributing to anti-TNF resistance. We found that ITGA1 was expressed in T cells and that interactions between these cells and intestinal cell types were associated with resistance to anti-TNF therapy. We experimentally showed that the α1 integrin subunit mediated the effectiveness of anti-TNF therapy in human immune cells. Thus, TransComp-R identified an integrin signaling mechanism with potential therapeutic implications for overcoming anti-TNF therapy resistance. We suggest that TransComp-R is a generalizable framework for addressing species, molecular, and phenotypic discrepancies between model systems and patients to translationally deliver relevant biological insights.

Coregulator Sin3a Promotes Postnatal Murine ß-Cell Fitness by Regulating Genes in Ca2+ Homeostasis, Cell Survival, Vesicle Biosynthesis, Glucose Metabolism, and Stress Response.

Swi-independent 3a and 3b (Sin3a and Sin3b) are paralogous transcriptional coregulators that direct cellular differentiation, survival, and function. Here, we report that mouse Sin3a and Sin3b are coproduced in most pancreatic cells during embryogenesis but become much more enriched in endocrine cells in adults, implying continued essential roles in mature endocrine cell function. Mice with loss of Sin3a in endocrine progenitors were normal during early postnatal stages but gradually developed diabetes before weaning. These physiological defects were preceded by the compromised survival, insulin-vesicle packaging, insulin secretion, and nutrient-induced Ca2+ influx of Sin3a-deficient ß-cells. RNA sequencing coupled with candidate chromatin immunoprecipitation assays revealed several genes that could be directly regulated by Sin3a in ß-cells, which modulate Ca2+/ion transport, cell survival, vesicle/membrane trafficking, glucose metabolism, and stress responses. Finally, mice with loss of both Sin3a and Sin3b in multipotent embryonic pancreatic progenitors had significantly reduced islet cell mass at birth, caused by decreased endocrine progenitor production and increased ß-cell death. These findings highlight the stage-specific requirements for the presumed "general" coregulators Sin3a and Sin3b in islet ß-cells, with Sin3a being dispensable for differentiation but required for postnatal function and survival.