Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning.

Spatially resolved transcriptomics (SRT) has enabled precise dissection of tumor-microenvironment (TME) by analyzing its intracellular molecular networks and intercellular cell-cell communication (CCC). However, lacking computational exploration of complicated relations between cells, genes, and histological regions, severely limits the ability to interpret the complex structure of TME. Here, we introduce stKeep, a heterogeneous graph (HG) learning method that integrates multimodality and gene-gene interactions, in unraveling TME from SRT data. stKeep leverages HG to learn both cell-modules and gene-modules by incorporating features of diverse nodes including genes, cells, and histological regions, allows for identifying finer cell-states within TME and cell-state-specific gene-gene relations, respectively. Furthermore, stKeep employs HG to infer CCC for each cell, while ensuring that learned CCC patterns are comparable across different cell-states through contrastive learning. In various cancer samples, stKeep outperforms other tools in dissecting TME such as detecting bi-potent basal populations, neoplastic myoepithelial cells, and metastatic cells distributed within the tumor or leading-edge regions. Notably, stKeep identifies key transcription factors, ligands, and receptors relevant to disease progression, which are further validated by the functional and survival analysis of independent clinical data, thereby highlighting its clinical prognostic and immunotherapy applications.

Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics.

Spatially resolved transcriptomics (SRT) has emerged as a powerful tool for investigating gene expression in spatial contexts, providing insights into the molecular mechanisms underlying organ development and disease pathology. However, the expression sparsity poses a computational challenge to integrate other modalities (e.g. histological images and spatial locations) that are simultaneously captured in SRT datasets for spatial clustering and variation analyses. In this study, to meet such a challenge, we propose multi-modal domain adaption for spatial transcriptomics (stMDA), a novel multi-modal unsupervised domain adaptation method, which integrates gene expression and other modalities to reveal the spatial functional landscape. Specifically, stMDA first learns the modality-specific representations from spatial multi-modal data using multiple neural network architectures and then aligns the spatial distributions across modal representations to integrate these multi-modal representations, thus facilitating the integration of global and spatially local information and improving the consistency of clustering assignments. Our results demonstrate that stMDA outperforms existing methods in identifying spatial domains across diverse platforms and species. Furthermore, stMDA excels in identifying spatially variable genes with high prognostic potential in cancer tissues. In conclusion, stMDA as a new tool of multi-modal data integration provides a powerful and flexible framework for analyzing SRT datasets, thereby advancing our understanding of intricate biological systems.

TET2-STAT3-CXCL5 nexus promotes neutrophil lipid transfer to fuel lung adeno-to-squamous transition.

Phenotypic plasticity is a rising cancer hallmark, and lung adeno-to-squamous transition (AST) triggered by LKB1 inactivation is significantly associated with drug resistance. Mechanistic insights into AST are urgently needed to identify therapeutic vulnerability in LKB1-deficient lung cancer. Here, we find that ten-eleven translocation (TET)-mediated DNA demethylation is elevated during AST in KrasLSL-G12D/+; Lkb1L/L (KL) mice, and knockout of individual Tet genes reveals that Tet2 is required for squamous transition. TET2 promotes neutrophil infiltration through STAT3-mediated CXCL5 expression. Targeting the STAT3-CXCL5 nexus effectively inhibits squamous transition through reducing neutrophil infiltration. Interestingly, tumor-infiltrating neutrophils are laden with triglycerides and can transfer the lipid to tumor cells to promote cell proliferation and squamous transition. Pharmacological inhibition of macropinocytosis dramatically inhibits neutrophil-to-cancer cell lipid transfer and blocks squamous transition. These data uncover an epigenetic mechanism orchestrating phenotypic plasticity through regulating immune microenvironment and metabolic communication, and identify therapeutic strategies to inhibit AST.

Multicellular ecotypes shape progression of lung adenocarcinoma from ground-glass opacity toward advanced stages.

Lung adenocarcinoma is a type of cancer that exhibits a wide range of clinical radiological manifestations, from ground-glass opacity (GGO) to pure solid nodules, which vary greatly in terms of their biological characteristics. Our current understanding of this heterogeneity is limited. To address this gap, we analyze 58 lung adenocarcinoma patients via machine learning, single-cell RNA sequencing (scRNA-seq), and whole-exome sequencing, and we identify six lung multicellular ecotypes (LMEs) correlating with distinct radiological patterns and cancer cell states. Notably, GGO-associated neoantigens in early-stage cancers are recognized by CD8+ T cells, indicating an immune-active environment, while solid nodules feature an immune-suppressive LME with exhausted CD8+ T cells, driven by specific stromal cells such as CTHCR1+ fibroblasts. This study also highlights EGFR(L858R) neoantigens in GGO samples, suggesting potential CD8+ T cell activation. Our findings offer valuable insights into lung adenocarcinoma heterogeneity, suggesting avenues for targeted therapies in early-stage disease.

Mutant U2AF1-Induced Mis-Splicing of mRNA Translation Genes Confers Resistance to Chemotherapy in Acute Myeloid Leukemia.

Patients with primary refractory acute myeloid leukemia (AML) have a dismal long-term prognosis. Elucidating the resistance mechanisms to induction chemotherapy could help identify strategies to improve AML patient outcomes. Herein, we retrospectively analyzed the multiomics data of more than 1,500 AML cases and found that patients with spliceosome mutations had a higher risk of developing refractory disease. RNA splicing analysis revealed that the mis-spliced genes in refractory patients converged on translation-associated pathways, promoted mainly by U2AF1 mutations. Integrative analyses of binding and splicing in AML cell lines substantiated that the splicing perturbations of mRNA translation genes originated from both the loss and gain of mutant U2AF1 binding. In particular, the U2AF1S34F and U2AF1Q157R mutants orchestrated the inclusion of exon 11 (encoding a premature termination codon) in the eukaryotic translation initiation factor 4A2 (EIF4A2). This aberrant inclusion led to reduced eIF4A2 protein expression via nonsense-mediated mRNA decay. Consequently, U2AF1 mutations caused a net decrease in global mRNA translation that induced the integrated stress response (ISR) in AML cells, which was confirmed by single-cell RNA sequencing. The induction of ISR enhanced the ability of AML cells to respond and adapt to stress, contributing to chemoresistance. A pharmacologic inhibitor of ISR, ISRIB, sensitized U2AF1 mutant cells to chemotherapy. These findings highlight a resistance mechanism by which U2AF1 mutations drive chemoresistance and provide a therapeutic approach for AML through targeting the ISR pathway. SIGNIFICANCE: U2AF1 mutations induce the integrated stress response by disrupting splicing of mRNA translation genes that improves AML cell fitness to enable resistance to chemotherapy, which can be targeted to improve AML treatment.

Adeno-to-squamous transition drives resistance to KRAS inhibition in LKB1 mutant lung cancer.

KRASG12C inhibitors (adagrasib and sotorasib) have shown clinical promise in targeting KRASG12C-mutated lung cancers; however, most patients eventually develop resistance. In lung patients with adenocarcinoma with KRASG12C and STK11/LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRASG12C and KrasG12D lung cancer mouse models and organoids treated with KRAS inhibitors reveal tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. Transcriptomic and epigenomic analyses reveal ΔNp63 drives AST and modulates response to KRAS inhibition. We identify an intermediate high-plastic cell state marked by expression of an AST plasticity signature and Krt6a. Notably, expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

EML4-ALK fusions drive lung adeno-to-squamous transition through JAK-STAT activation.

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, exhibits strong cancer plasticity. We find that ALK rearrangement is detectable in 5.1-7.5% of human LUAS, and transgenic expression of EML4-ALK drives lung adenocarcinoma (LUAD) formation initially and squamous transition at late stage. We identify club cells as the main cell-of-origin for squamous transition. Through recapitulating lineage transition in organoid system, we identify JAK-STAT signaling, activated by EML4-ALK phase separation, significantly promotes squamous transition. Integrative study with scRNA-seq and immunostaining identify a plastic cell subpopulation in ALK-rearranged human LUAD showing squamous biomarker expression. Moreover, those relapsed ALK-rearranged LUAD show notable upregulation of squamous biomarkers. Consistently, mouse squamous tumors or LUAD with squamous signature display certain resistance to ALK inhibitor, which can be overcome by combined JAK1/2 inhibitor treatment. This study uncovers strong plasticity of ALK-rearranged tumors in orchestrating phenotypic transition and drug resistance and proposes a potentially effective therapeutic strategy.

Cryoablation triggers type I interferon-dependent antitumor immunity and potentiates immunotherapy efficacy in lung cancer.

BACKGROUND: Cryoablation is a minimally invasive option for patients with medically inoperable non-small cell lung cancer (NSCLC) and can trigger abscopal immune-regulatory effects. However, it remains unclear how cryoablation affects the host-level immune response in NSCLC. In this study, we investigated the local and systemic immunological effects of cryoablation and the potential of combining cryoablation with programmed cell death protein 1 (PD-1) blockade to boost immunotherapy efficacy in NSCLC. METHODS: We first investigated systemic immunological effects induced by cryoablation in patients with early-stage NSCLC. Subsequently, we explored cryoablation-induced antitumor immunity and the underlying biological mechanisms using KP (Kras G12D/+, Tp53 -/-) mutant lung cancer cell allograft mouse models. Moreover, the synergistic efficacy of cryoablation and PD-1 blockade was explored in both mouse models and patients with unresectable NSCLC. RESULTS: We found that cryoablation significantly increased circulating CD8+ T cell subpopulations and proinflammatory cytokines in patients with early-stage NSCLC. In lung cancer cell allograft mouse models, we demonstrated that cryoablation resulted in abscopal growth inhibition of contralateral, non-ablated tumors. Integrated analysis of bulk, single-cell RNA and T cell receptor (TCR) sequencing data revealed that cryoablation reprogrammed the intratumoral immune microenvironment and increased CD8+ T cell infiltration with higher effector signature, interferon (IFN) response, and cytolytic activity. Mechanistically, cryoablation promoted antitumor effect through the STING-dependent type I IFN signaling pathway, and type I IFN signaling blockade attenuated this antitumor effect. We also found that the combination of PD-1 blockade with cryoablation further inhibited tumor growth compared with either treatment alone in an allograft mouse model. Moreover, the combination therapy induced notable tumor suppression and CD8+ T cell infiltration in patients with unresectable NSCLC. CONCLUSIONS: Our results provide mechanistic insights into how cryoablation triggers the antitumor immune effect in lung cancer, thereby potentiating programmed cell death ligand 1 (PD-L1)/PD-1 blockade efficacy in the clinical treatment of NSCLC.

Integrated characterization of hepatobiliary tumor organoids provides a potential landscape of pharmacogenomic interactions.

Despite considerable efforts to identify human liver cancer genomic alterations that might unveil druggable targets, the systematic translation of multiomics data remains challenging. Here, we report success in long-term culture of 64 patient-derived hepatobiliary tumor organoids (PDHOs) from a Chinese population. A divergent response to 265 metabolism- and epigenetics-related chemicals and 36 anti-cancer drugs is observed. Integration of the whole genome, transcriptome, chromatin accessibility profiles, and drug sensitivity results of 64 clinically relevant drugs defines over 32,000 genome-drug interactions. RUNX1 promoter mutation is associated with an increase in chromatin accessibility and a concomitant gene expression increase, promoting a cluster of drugs preferentially sensitive in hepatobiliary tumors. These results not only provide an annotated PDHO biobank of human liver cancer but also suggest a systematic approach for obtaining a comprehensive understanding of the gene-regulatory network of liver cancer, advancing the applications of potential personalized medicine.

Correction to: Identification of TAZ as the essential molecular switch in orchestrating SCLC phenotypic transition and metastasis.

[This corrects the article DOI: 10.1093/nsr/nwab232.].

Revealing Tissue Heterogeneity and Spatial Dark Genes from Spatially Resolved Transcriptomics by Multiview Graph Networks.

Spatially resolved transcriptomics (SRT) is capable of comprehensively characterizing gene expression patterns and providing an unbiased image of spatial composition. To fully understand the organizational complexity and tumor immune escape mechanism, we propose stMGATF, a multiview graph attention fusion model that integrates gene expression, histological images, spatial location, and gene association. To better extract information, stMGATF exploits SimCLRv2 for visual feature exaction and employs edge feature enhanced graph attention networks for the learning potential embedding of each view. A global attention mechanism is used to adaptively integrate 3 views to obtain low-dimensional representation. Applied to diverse SRT datasets, stMGATF is robust and outperforms other methods in detecting spatial domains and denoising data even with different resolutions and platforms. In particular, stMGATF contributes to the elucidation of tissue heterogeneity and extraction of 3-dimensional expression domains. Importantly, considering the associations between genes in tumors, stMGATF can identify the spatial dark genes ignored by traditional methods, which can be used to predict tumor-driving transcription factors and reveal tumor immune escape mechanisms, providing theoretical evidence for the development of new immunotherapeutic strategies.

Metabolic classification suggests the GLUT1/ALDOB/G6PD axis as a therapeutic target in chemotherapy-resistant pancreatic cancer.

Metabolic reprogramming is known as an emerging mechanism of chemotherapy resistance, but the metabolic signatures of pancreatic ductal adenocarcinomas (PDACs) remain unclear. Here, we characterize the metabolomic profile of PDAC organoids and classify them into glucomet-PDAC (high glucose metabolism levels) and lipomet-PDAC (high lipid metabolism levels). Glucomet-PDACs are more resistant to chemotherapy than lipomet-PDACs, and patients with glucomet-PDAC have a worse prognosis. Integrated analyses reveal that the GLUT1/aldolase B (ALDOB)/glucose-6-phosphate dehydrogenase (G6PD) axis induces chemotherapy resistance by remodeling glucose metabolism in glucomet-PDAC. Increased glycolytic flux, G6PD activity, and pyrimidine biosynthesis are identified in glucomet-PDAC with high GLUT1 and low ALDOB expression, and these phenotypes could be reversed by inhibiting GLUT1 expression or by increasing ALDOB expression. Pharmacological inhibition of GLUT1 or G6PD enhances the chemotherapy response of glucomet-PDAC. Our findings uncover potential metabolic heterogeneity related to differences in chemotherapy sensitivity in PDAC and develop a promising pharmacological strategy for patients with chemotherapy-resistant glucomet-PDAC through the combination of chemotherapy and GLUT1/ALDOB/G6PD axis inhibitors.

A single-cell transcriptional landscape of immune cells shows disease-specific changes of T cell and macrophage populations in human achalasia.

Achalasia is a rare motility disorder of the esophagus caused by the gradual degeneration of myenteric neurons. Immune-mediated ganglionitis has been proposed to underlie the loss of myenteric neurons. Here, we measure the immune cell transcriptional profile of paired lower esophageal sphincter (LES) tissue and blood samples in achalasia and controls using single-cell RNA sequencing (scRNA-seq). In achalasia, we identify a pattern of expanded immune cells and a specific transcriptional phenotype, especially in LES tissue. We show C1QC+ macrophages and tissue-resident memory T cells (TRM), especially ZNF683+ CD8+ TRM and XCL1+ CD4+ TRM, are significantly expanded and localized surrounding the myenteric plexus in the LES tissue of achalasia. C1QC+ macrophages are transcriptionally similar to microglia of the central nervous system and have a neurodegenerative dysfunctional phenotype in achalasia. TRM also expresses transcripts of dysregulated immune responses in achalasia. Moreover, inflammation increases with disease progression since immune cells are more activated in type I compared with type II achalasia. Thus, we profile the immune cell transcriptional landscape and identify C1QC+ macrophages and TRM as disease-associated immune cell subsets in achalasia.

HLA-I Evolutionary Divergence Confers Response to PD-1 Blockade plus Chemotherapy in Untreated Advanced Non-Small Cell Lung Cancer.

PURPOSE: PD-1 blockade plus chemotherapy has become the new standard of care in patients with untreated advanced non-small cell lung cancer (NSCLC), whereas predictive biomarkers remain undetermined. EXPERIMENTAL DESIGN: We integrated clinical, genomic, and survival data of 427 NSCLC patients treated with first-line PD-1 blockade plus chemotherapy or chemotherapy from two phase III trials (CameL and CameL-sq) and investigated the predictive and prognostic value of HLA class I evolutionary divergence (HED). RESULTS: High HED could predict significantly improved objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) in those who received PD-1 blockade plus chemotherapy [in the CameL trial, ORR: 81.8% vs. 53.2%; P = 0.032; PFS: hazard ratio (HR), 0.47; P = 0.012; OS: HR, 0.40; P = 0.014; in the CameL-sq trial, ORR: 89.2% vs. 62.3%; P = 0.007; PFS: HR, 0.49; P = 0.005; OS: HR, 0.38; P = 0.002], but not chemotherapy. In multivariate analysis adjusted for PD-L1 expression and tumor mutation burden, high HED was independently associated with markedly better ORR, PFS, and OS in both trials. Moreover, the joint utility of HED and PD-L1 expression showed better performance than either alone in predicting treatment benefit from PD-1 blockade plus chemotherapy. Single-cell RNA sequencing of 58,977 cells collected from 11 patients revealed that tumors with high HED had improved antigen presentation and T cell-mediated antitumor immunity, indicating an inflamed tumor microenvironment phenotype. CONCLUSIONS: These findings suggest that high HED could portend survival benefit in advanced NSCLC treated with first-line PD-1 blockade plus chemotherapy. See related commentary by Dimou, p. 4706.

Counteracting lineage-specific transcription factor network finely tunes lung adeno-to-squamous transdifferentiation through remodeling tumor immune microenvironment.

Human lung adenosquamous cell carcinoma (LUAS), containing both adenomatous and squamous pathologies, harbors strong plasticity and is significantly associated with poor prognosis. We established an up-to-date comprehensive genomic and transcriptomic landscape of LUAS in 109 Chinese specimens and demonstrated LUAS development via adeno-to-squamous transdifferentiation. Unsupervised transcriptomic clustering and dynamic network biomarker analysis identified an inflammatory subtype as the critical transition stage during LUAS development. Dynamic dysregulation of the counteracting lineage-specific transcription factors (TFs), containing adenomatous TFs NKX2-1 and FOXA2, and squamous TFs TP63 and SOX2, finely tuned the lineage transition via promoting CXCL3/5-mediated neutrophil infiltration. Genomic clustering identified the most malignant subtype featured with STK11-inactivation, and targeting LSD1 through genetic deletion or pharmacological inhibition almost eradicated STK11-deficient lung tumors. These data collectively uncover the comprehensive molecular landscape, oncogenic driver spectrum and therapeutic vulnerability of Chinese LUAS.

Oxidative stress-triggered Wnt signaling perturbation characterizes the tipping point of lung adeno-to-squamous transdifferentiation.

Lkb1 deficiency confers the Kras-mutant lung cancer with strong plasticity and the potential for adeno-to-squamous transdifferentiation (AST). However, it remains largely unknown how Lkb1 deficiency dynamically regulates AST. Using the classical AST mouse model (Kras LSL-G12D/+;Lkb1flox/flox, KL), we here comprehensively analyze the temporal transcriptomic dynamics of lung tumors at different stages by dynamic network biomarker (DNB) and identify the tipping point at which the Wnt signaling is abruptly suppressed by the excessive accumulation of reactive oxygen species (ROS) through its downstream effector FOXO3A. Bidirectional genetic perturbation of the Wnt pathway using two different Ctnnb1 conditional knockout mouse strains confirms its essential role in the negative regulation of AST. Importantly, pharmacological activation of the Wnt pathway before but not after the tipping point inhibits squamous transdifferentiation, highlighting the irreversibility of AST after crossing the tipping point. Through comparative transcriptomic analyses of mouse and human tumors, we find that the lineage-specific transcription factors (TFs) of adenocarcinoma and squamous cell carcinoma form a "Yin-Yang" counteracting network. Interestingly, inactivation of the Wnt pathway preferentially suppresses the adenomatous lineage TF network and thus disrupts the "Yin-Yang" homeostasis to lean towards the squamous lineage, whereas ectopic expression of NKX2-1, an adenomatous lineage TF, significantly dampens such phenotypic transition accelerated by the Wnt pathway inactivation. The negative correlation between the Wnt pathway and AST is further observed in a large cohort of human lung adenosquamous carcinoma. Collectively, our study identifies the tipping point of AST and highlights an essential role of the ROS-Wnt axis in dynamically orchestrating the homeostasis between adeno- and squamous-specific TF networks at the AST tipping point.

Human endoderm stem cells reverse inflammation-related acute liver failure through cystatin SN-mediated inhibition of interferon signaling.

Acute liver failure (ALF) is a life-threatening disease that occurs secondary to drug toxicity, infection or a devastating immune response. Orthotopic liver transplantation is an effective treatment but limited by the shortage of donor organs, the requirement for life-long immune suppression and surgical challenges. Stem cell transplantation is a promising alternative therapy for fulminant liver failure owing to the immunomodulatory abilities of stem cells. Here, we report that when transplanted into the liver, human endoderm stem cells (hEnSCs) that are germ layer-specific and nontumorigenic cells derived from pluripotent stem cells are able to effectively ameliorate hepatic injury in multiple rodent and swine drug-induced ALF models. We demonstrate that hEnSCs tune the local immune microenvironment by skewing macrophages/Kupffer cells towards an anti-inflammatory state and by reducing the infiltrating monocytes/macrophages and inflammatory T helper cells. Single-cell transcriptomic analyses of infiltrating and resident monocytes/macrophages isolated from animal livers revealed dramatic changes, including changes in gene expression that correlated with the change of activation states, and dynamic population heterogeneity among these cells after hEnSC transplantation. We further demonstrate that hEnSCs modulate the activation state of macrophages/Kupffer cells via cystatin SN (CST1)-mediated inhibition of interferon signaling and therefore highlight CST1 as a candidate therapeutic agent for diseases that involve over-activation of interferons. We propose that hEnSC transplantation represents a novel and powerful cell therapeutic treatment for ALF.

Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning.

Spatially resolved transcriptomics (SRT) technology enables us to gain novel insights into tissue architecture and cell development, especially in tumors. However, lacking computational exploitation of biological contexts and multi-view features severely hinders the elucidation of tissue heterogeneity. Here, we propose stMVC, a multi-view graph collaborative-learning model that integrates histology, gene expression, spatial location, and biological contexts in analyzing SRT data by attention. Specifically, stMVC adopting semi-supervised graph attention autoencoder separately learns view-specific representations of histological-similarity-graph or spatial-location-graph, and then simultaneously integrates two-view graphs for robust representations through attention under semi-supervision of biological contexts. stMVC outperforms other tools in detecting tissue structure, inferring trajectory relationships, and denoising on benchmark slices of human cortex. Particularly, stMVC identifies disease-related cell-states and their transition cell-states in breast cancer study, which are further validated by the functional and survival analysis of independent clinical data. Those results demonstrate clinical and prognostic applications from SRT data.

Identification of TAZ as the essential molecular switch in orchestrating SCLC phenotypic transition and metastasis.

Small-cell lung cancer (SCLC) is a recalcitrant cancer characterized by high metastasis. However, the exact cell type contributing to metastasis remains elusive. Using a Rb1 L/L /Trp53 L/L mouse model, we identify the NCAMhiCD44lo/- subpopulation as the SCLC metastasizing cell (SMC), which is progressively transitioned from the non-metastasizing NCAMloCD44hi cell (non-SMC). Integrative chromatin accessibility and gene expression profiling studies reveal the important role of the SWI/SNF complex, and knockout of its central component, Brg1, significantly inhibits such phenotypic transition and metastasis. Mechanistically, TAZ is silenced by the SWI/SNF complex during SCLC malignant progression, and its knockdown promotes SMC transition and metastasis. Importantly, ectopic TAZ expression reversely drives SMC-to-non-SMC transition and alleviates metastasis. Single-cell RNA-sequencing analyses identify SMC as the dominant subpopulation in human SCLC metastasis, and immunostaining data show a positive correlation between TAZ and patient prognosis. These data uncover high SCLC plasticity and identify TAZ as the key molecular switch in orchestrating SCLC phenotypic transition and metastasis.