A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Widespread dysregulation of mRNA splicing implicates RNA processing in the development and progression of Huntington's disease.

BACKGROUND: In Huntington's disease (HD), a CAG repeat expansion mutation in the Huntingtin (HTT) gene drives a gain-of-function toxicity that disrupts mRNA processing. Although dysregulation of gene splicing has been shown in human HD post-mortem brain tissue, post-mortem analyses are likely confounded by cell type composition changes in late-stage HD, limiting the ability to identify dysregulation related to early pathogenesis. METHODS: To investigate gene splicing changes in early HD, we performed alternative splicing analyses coupled with a proteogenomics approach to identify early CAG length-associated splicing changes in an established isogenic HD cell model. FINDINGS: We report widespread neuronal differentiation stage- and CAG length-dependent splicing changes, and find an enrichment of RNA processing, neuronal function, and epigenetic modification-related genes with mutant HTT-associated splicing. When integrated with a proteomics dataset, we identified several of these differential splicing events at the protein level. By comparing with human post-mortem and mouse model data, we identified common patterns of altered splicing from embryonic stem cells through to post-mortem striatal tissue. INTERPRETATION: We show that widespread splicing dysregulation in HD occurs in an early cell model of neuronal development. Importantly, we observe HD-associated splicing changes in our HD cell model that were also identified in human HD striatum and mouse model HD striatum, suggesting that splicing-associated pathogenesis possibly occurs early in neuronal development and persists to later stages of disease. Together, our results highlight splicing dysregulation in HD which may lead to disrupted neuronal function and neuropathology. FUNDING: This research is supported by the Lee Kong Chian School of Medicine, Nanyang Technological University Singapore Nanyang Assistant Professorship Start-Up Grant, the Singapore Ministry of Education under its Singapore Ministry of Education Academic Research Fund Tier 1 (RG23/22), the BC Children's Hospital Research Institute Investigator Grant Award (IGAP), and a Scholar Award from the Michael Smith Health Research BC.

Molecular Subgroups of Intrahepatic Cholangiocarcinoma Discovered by Single-Cell RNA Sequencing-Assisted Multiomics Analysis.

Intrahepatic cholangiocarcinoma (ICC) is a relatively rare but highly aggressive tumor type that responds poorly to chemotherapy and immunotherapy. Comprehensive molecular characterization of ICC is essential for the development of novel therapeutics. Here, we constructed two independent cohorts from two clinic centers. A comprehensive multiomics analysis of ICC via proteomic, whole-exome sequencing (WES), and single-cell RNA sequencing (scRNA-seq) was performed. Novel ICC tumor subtypes were derived in the training cohort (n = 110) using proteomic signatures and their associated activated pathways, which were further validated in a validation cohort (n = 41). Three molecular subtypes, chromatin remodeling, metabolism, and chronic inflammation, with distinct prognoses in ICC were identified. The chronic inflammation subtype was associated with a poor prognosis. Our random forest algorithm revealed that mutation of lysine methyltransferase 2D (KMT2D) frequently occurred in the metabolism subtype and was associated with lower inflammatory activity. scRNA-seq further identified an APOE+C1QB+ macrophage subtype, which showed the capacity to reshape the chronic inflammation subtype and contribute to a poor prognosis in ICC. Altogether, with single-cell transcriptome-assisted multiomics analysis, we identified novel molecular subtypes of ICC and validated APOE+C1QB+ tumor-associated macrophages as potential immunotherapy targets against ICC.

Topological analysis of hepatocellular carcinoma tumour microenvironment based on imaging mass cytometry reveals cellular neighbourhood regulated reversely by macrophages with different ontogeny.

OBJECTIVE: Hepatocellular carcinoma (HCC) tumour microenvironment (TME) is highly complex with diverse cellular components organising into various functional units, cellular neighbourhoods (CNs). And we wanted to define CN of HCC while preserving the TME architecture, based on which, potential targets for novel immunotherapy could be identified. DESIGN: A highly multiplexed imaging mass cytometry (IMC) panel was designed to simultaneously quantify 36 biomarkers of tissues from 134 patients with HCC and 7 healthy donors to generate 562 highly multiplexed histology images at single-cell resolution. Different function units were defined by topological analysis of TME. CN relevant to the patients' prognosis was identified as specific target for HCC therapy. Transgenic mouse models were used to validate the novel immunotherapy target for HCC. RESULTS: Three major types of intratumour areas with distinct distribution patterns of tumorous, stromal and immune cells were identified. 22 cellular metaclusters and 16 CN were defined. CN composed of various types of cells formed regional function units and the regional immunity was regulated reversely by resident Kupffer cells and infiltrating macrophages with protumour and antitumour function, respectively. Depletion of Kupffer cells in mouse liver largely enhances the T cell response, reduces liver tumour growth and sensitises the tumour response to antiprogrammed cell death protein-1 treatment. CONCLUSION: Our findings reveal for the first time the various topological function units of HCC TME, which also presents the largest depository of pathological landscape for HCC. This work highlights the potential of Kupffer cell-specific targeting rather than overall myeloid cell blocking as a novel immunotherapy for HCC treatment.

Mitchell-Riley syndrome iPSCs exhibit reduced pancreatic endoderm differentiation due to a mutation in RFX6.

Mitchell-Riley syndrome (MRS) is caused by recessive mutations in the regulatory factor X6 gene (RFX6) and is characterised by pancreatic hypoplasia and neonatal diabetes. To determine why individuals with MRS specifically lack pancreatic endocrine cells, we micro-CT imaged a 12-week-old foetus homozygous for the nonsense mutation RFX6 c.1129C>T, which revealed loss of the pancreas body and tail. From this foetus, we derived iPSCs and show that differentiation of these cells in vitro proceeds normally until generation of pancreatic endoderm, which is significantly reduced. We additionally generated an RFX6HA reporter allele by gene targeting in wild-type H9 cells to precisely define RFX6 expression and in parallel performed in situ hybridisation for RFX6 in the dorsal pancreatic bud of a Carnegie stage 14 human embryo. Both in vitro and in vivo, we find that RFX6 specifically labels a subset of PDX1-expressing pancreatic endoderm. In summary, RFX6 is essential for efficient differentiation of pancreatic endoderm, and its absence in individuals with MRS specifically impairs formation of endocrine cells of the pancreas head and tail.

Reprogramming roadmap reveals route to human induced trophoblast stem cells.

The reprogramming of human somatic cells to primed or naive induced pluripotent stem cells recapitulates the stages of early embryonic development1-6. The molecular mechanism that underpins these reprogramming processes remains largely unexplored, which impedes our understanding and limits rational improvements to reprogramming protocols. Here, to address these issues, we reconstruct molecular reprogramming trajectories of human dermal fibroblasts using single-cell transcriptomics. This revealed that reprogramming into primed and naive pluripotency follows diverging and distinct trajectories. Moreover, genome-wide analyses of accessible chromatin showed key changes in the regulatory elements of core pluripotency genes, and orchestrated global changes in chromatin accessibility over time. Integrated analysis of these datasets revealed a role for transcription factors associated with the trophectoderm lineage, and the existence of a subpopulation of cells that enter a trophectoderm-like state during reprogramming. Furthermore, this trophectoderm-like state could be captured, which enabled the derivation of induced trophoblast stem cells. Induced trophoblast stem cells are molecularly and functionally similar to trophoblast stem cells derived from human blastocysts or first-trimester placentas7. Our results provide a high-resolution roadmap for the transcription-factor-mediated reprogramming of human somatic cells, indicate a role for the trophectoderm-lineage-specific regulatory program during this process, and facilitate the direct reprogramming of somatic cells into induced trophoblast stem cells.

Oligonucleotide-directed STAT3 alternative splicing switch drives anti-tumorigenic outcomes in MCF10 human breast cancer cells.

Signal transducer and activator of transcription 3 (STAT3), a transcription factor responsive to the activation of cytokine receptors, is known for its oncogenic actions. Whilst STAT3α is the predominant spliceform in most tissues, alternative splicing of the STAT3 gene can generate a shorter STAT3ß spliceform. Redirecting splicing to enhance STAT3ß levels can result in tumor suppression in vivo, and so we evaluated the cellular basis underlying the anti-tumorigenic properties of STAT3ß. To investigate the impact of increased STAT3ß levels in cancer cells, we implemented a Morpholino-based antisense oligonucleotide strategy to modulate STAT3 spliceform expression in the MCF10CA1h cancer cells of the MCF10 series of human breast cancer cells. We employed nonsense-mediated decay (NMD) oligonucleotides and STAT3α-to-ß expression switching (SWI) oligonucleotides to successfully induce STAT3 knockdown and redirect alternative splicing to increase STAT3ß levels in MCF10CA1h cells, respectively. Importantly, assessment of the impacts of STAT3 splicing modulation on tumor cell biology showed that the SWI treatment significantly reduced MCF10CA1h cell growth, viability, and migration, whereas NMD treatment was without significant impact, although neither NMD nor SWI oligonucleotides significantly inhibited MCF10CA1h cell invasion through a semi-solid matrix. In conclusion, our data demonstrate that reduced breast cancer cell growth, viability and migration, but not invasion, follow the redirection of STAT3α-to-ß expression switching to favour STAT3ß expression.

TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets.

BACKGROUND: A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57-74, 2012; Nat 507:462-70, 2014; Nat 507:455-61, 2014; Nat 518:317-30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. RESULTS: We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563-5, 2007; Nat Protoc 5:323-34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. CONCLUSIONS: TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au .