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HMBOX1 reverses autophagy mediated 5-fluorouracil resistance through promoting HACE1-induced ubiquitination and degradation of ATG5 in colorectal cancer.
Chemotherapy remains the primary treatment for unresectable or advanced postoperative colorectal cancers. However, its effectiveness is compromised by chemoresistance, which adversely affects patient outcomes. Dysregulated macroautophagy/autophagy is a proposed mechanism behind this resistance, with ubiquitination playing a key regulatory role. In this study, we identify the transcription factor HMBOX1 (homeobox containing 1) as a critical regulator of chemoresistance in colorectal cancer. RNA sequencing revealed that HMBOX1 is downregulated in drug-resistant colorectal cancer cells and tissues, with its low expression linked to poor prognosis. An integrated analysis of genes associated with autophagy and 5-fluorouracil (5-FU) resistance was conducted, verified in the colorectal cancer tissues of patients by single-cell RNA sequencing and immunostaining. Mass-spectrometry-based proteomics and RNA sequencing were used to elucidate the underlying molecular mechanisms. Functionally, upregulation of HMBOX1 enhances the sensitivity of colorectal cancer cells to the first-line treatment with 5-FU by inhibiting autophagy. Mechanistically, HMBOX1 promotes the transcription of the E3 ubiquitin ligase HACE1, which in turn enhances ATG5 K63-ubiquitination and subsequent proteasome-mediated degradation. This results in decreased ATG5 levels, inhibiting autophagy and thus reducing 5-FU resistance in colorectal cancer cells both in vitro and in vivo. Furthermore, we confirm that HMBOX1 expression positively correlates with HACE1 expression and inversely correlates with autophagy levels in clinical colorectal cancer tissues. Our findings suggest that HMBOX1 downregulation drives 5-FU resistance through autophagy enhancement in colorectal cancer, highlighting HMBOX1 as a potential target for improving chemosensitivity and patient prognosis.Abbreviation: 3-MA: 3-methyladenine; 5-FU: 5-fluorouracil; ATG: autophagy related; CASP3: caspase 3; C-CASP3: cleaved caspase 3; C-PARP: cleaved PARP; CCK8: cell counting kit-8; ChIP: chromatin immunoprecipitation; CHX: cycloheximide; CNV: copy number variation; co-IP: co-immunoprecipitation; COAD: colorectal adenocarcinoma; CQ: chloroquine; CRC: colorectal cancer; CR: complete response; FHC: fetal human colon; GEO: Gene Expression Omnibus; HACE1: HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1; HMBOX1: homeobox containing 1; IHC: immunohistochemistry; LC-MS/MS: liquid chromatography-tandem mass spectrometry; mIHC: multiplexed immunohistochemistry; MUT: mutant; NC: negative control; OS: overall survival; PBS: phosphate-buffered saline; PD: progressive disease; PFA: paraformaldehyde; PFS: progression-free survival; PR: partial response; qPCR: quantitative polymerase chain reaction; RAPA: rapamycin; SD: stable disease; TCGA: The Cancer Genome Atlas; TEM: transmission electron microscopy; TF: translation factor; USP22: ubiquitin specific peptidase 22; WT: wild type.
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An atlas of healthy and injured cell states and niches in the human kidney.
Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
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Transcriptomic analysis identifies enrichment of cAMP/PKA/CREB signaling in invasive lobular breast cancer.
OBJECTIVE: Invasive lobular breast cancer (ILC) is the most common special type of breast cancer and has unique clinicopathological and molecular hallmarks that differentiate it from the more common invasive carcinoma-no special type (NST). Despite these differences, ILC and NST are treated as a single entity and there is a lack of ILC-targeted therapies. To fill this gap, we sought to identify novel molecular alterations in ILC that could be exploited for targeted therapies. METHODS: Differential gene expression and Geneset Enrichment and Variation analyses were performed on RNA-seq data from three large public breast cancer databases-the Sweden Cancerome Analysis Network-Breast (SCAN-B; luminal A ILC N = 263, luminal A NST N = 1162), The Cancer Genome Atlas (TCGA; luminal A ILC N = 157, luminal A NST N = 307) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; luminal A ILC N = 65, luminal A NST N = 533). Pathways enriched in overlapping differentially expressed genes from these datasets were clustered using Jaccard similarity to identify pathways enriched in ILC. The cAMP/PKA/CREB signaling was studied in ILC, ILC-like and NST cell lines and patient-derived organoids (PDOs) using forskolin, an activator of the pathway. RESULTS: Clinicopathological features of patients with ILC and NST in SCAN-B were similar to prior population-based studies. There was a consistent pattern of up-regulation of cAMP/PKA/CREB related signaling in ILC compared to NST in SCAN-B, TCGA and METABRIC. Treatment with forskolin resulted in a greater increase in phospho-CREB in ILC cell lines and organoids than NST. CRISPR deletion of CDH1 in NST cell lines did not alter response of cells to forskolin as measured by phospho-CREB. Forskolin treatment caused growth inhibition in ILC and NST, with ILC cell lines being more sensitive to forskolin-mediated growth inhibition. CONCLUSION: In three separate datasets, cAMP/PKA/CREB signaling was identified to be higher in ILC than NST. This in silico finding was validated in cell line and organoid models. Loss of CDH1 was not sufficient to mediate this phenotype. Future studies should investigate the mechanisms for differential cAMP/PKA/CREB signaling and the potential for therapeutic targeting in patients with ILC.
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Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.
Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.
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Targeting tumor cell-to-macrophage communication by blocking Vtn-C1qbp interaction inhibits tumor progression via enhancing macrophage phagocytosis.
Background: Cancer cells are capable of evading clearance by macrophages through overexpression of anti-phagocytic surface proteins known as "don't eat me" signals. Monoclonal antibodies that antagonize the "don't-eat-me" signaling in macrophages and tumor cells by targeting phagocytic checkpoints have shown therapeutic promises in several cancer types. However, studies on the responses to these drugs have revealed the existence of other unknown "don't eat me" signals. Moreover, identification of key molecules and interactions regulating macrophage phagocytosis is required for tumor therapy. Methods: CRISPR screen was used to identify genes that impede macrophage phagocytosis. To explore the function of Vtn and C1qbp in phagocytosis, knockdown and subsequent functional experiments were conducted. Flow cytometry were performed to explore the phagocytosis rate, polarization of macrophage, and immune microenvironment of mouse tumor. To explore the underlying molecular mechanisms, RNA sequencing, immunoprecipitation, mass spectrometry, and immunofluorescence were conducted. Then, in vivo experiments in mouse models were conducted to explore the probability of Vtn knockdown combined with anti-CD47 therapy in breast cancer. Single-cell sequencing data from the Gene Expression Omnibus from The Cancer Genome Atlas database were analyzed. Results: We performed a genome-wide CRISPR screen to identify genes that impede macrophage phagocytosis, followed by analysis of cell-to-cell interaction databases. We identified a ligand-receptor pair of Vitronectin (Vtn) and complement C1Q binding protein (C1qbp) in tumor cells or macrophages, respectively. We demonstrated tumor cell-secreted Vtn interacts with C1qbp localized on the cell surface of tumor-associated macrophages, inhibiting phagocytosis of tumor cells and shifting macrophages towards the M2-like subtype in the tumor microenvironment. Mechanistically, the Vtn-C1qbp axis facilitated FcγRIIIA/CD16-induced Shp1 recruitment, which reduced the phosphorylation of Syk. Furthermore, the combination of Vtn knockdown and anti-CD47 antibody effectively enhanced phagocytosis and infiltration of macrophages, resulting in a reduction of tumor growth in vivo. Conclusions: This work has revealed that the Vtn-C1qbp axis is a new anti-phagocytic signal in tumors, and targeting Vtn and its interaction with C1qbp may sensitize cancer to immunotherapy, providing a new molecular target for the treatment of triple-negative breast cancer.
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A novel risk signature based on liquid-liquid phase separation-related genes reveals prognostic and tumour microenvironmental features in clear cell renal cell carcinoma.
BACKGROUND: Clear cell renal cell carcinoma(ccRCC) is one of the most common malignancies. However, there are still many barriers to its underlying causes, early diagnostic techniques and therapeutic approaches. MATERIALS AND METHODS: The Cancer Genome Atlas (TCGA)- Kidney renal clear cell (KIRC) cohort differentially analysed liquid-liquid phase separation (LLPS)-related genes from the DrLLPS website. Univariate and multivariate Cox regression analyses and LASSO regression analyses were used to construct prognostic models. The E-MTAB-1980 cohort was used for external validation. Then, potential functions, immune infiltration analysis, and mutational landscapes were analysed for the high-risk and low-risk groups. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) experiments as well as single-cell analyses validated the genes key to the model. RESULTS: We screened 174 LLPS-related genes in ccRCC and constructed a risk signature consisting of five genes (CLIC5, MXD3, NUF2, PABPC1L, PLK1). The high-risk group was found to be associated with worse prognosis in different subgroups. A nomogram constructed by combining age and tumour stage had a strong predictive power for the prognosis of ccRCC patients. In addition, there were differences in pathway enrichment, immune cell infiltration, and mutational landscapes between the two groups. The results of qRT-PCR in renal cancer cell lines and renal cancer tissues were consistent with the biosignature prediction. Three single-cell data of GSE159115, GSE139555, and GSE121636 were analysed for differences in the presence of these five genes in different cells. CONCLUSIONS: We developed a risk signature constructed based on the five LLPS-related genes and can have a high ability to predict the prognosis of ccRCC patients, further providing a strong support for clinical decision-making.
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Integrated bulk and single-cell transcriptomic analysis unveiled a novel cuproptosis-related lipid metabolism gene molecular pattern and a risk index for predicting prognosis and antitumor drug sensitivity in breast cancer.
Breast cancer is the second most prevalent malignant tumor worldwide and is highly heterogeneous. Cuproptosis, a newly identified form of cell death, is intimately connected to lipid metabolism. This study investigated breast cancer heterogeneity through the lens of cuproptosis-related lipid metabolism genes (CLMGs), with the goal of predicting patient prognosis, immunotherapy efficacy, and sensitivity to anticancer drugs. By utilizing transcriptomic data from The Cancer Genome Atlas (TCGA) for breast cancer, we identified 682 CLMGs and applied the nonnegative matrix factorization (NMF) method to categorize breast cancer patients into four distinct clusters: cluster 1, ''immune-cold and stroma-poor''; cluster 2, ''immune-infiltrated''; cluster 3, ''stroma-rich''; and cluster 4, ''moderate infiltration''. We subsequently developed a risk model based on CLMGs that incorporates ACSL1, ATP2B4, ATP7B, ENPP6, HSPH1, PIP4K2C, SRD5A3, and ULBP1. This model demonstrated excellent prognostic predictive performance in both the internal (testing and entire sets) and external (GSE20685 and Kaplan-Meier Plotter sets) validation sets. High-risk patients presented lower expression levels of immune checkpoint-related genes and lower immunophenoscores (IPSs), whereas low-risk patients presented higher CD8+ T-cell infiltration levels and IPSs. Furthermore, the risk index was positively correlated with tumor cell stemness and could predict sensitivity to anticancer drugs. We also confirmed that SRD5A3 was highly expressed in breast cancer and participated in promoting the proliferation and migration of breast cancer cells. In conclusion, the results of this study provide new insights and strategies for assessing prognosis and implementing precision treatment for breast cancer through the lens of CLMGs.
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A factor-based analysis of individual human microglia uncovers regulators of an Alzheimer-related transcriptional signature.
Human microglial heterogeneity is only beginning to be appreciated at the molecular level. Here, we present a large, single-cell atlas of expression signatures from 441,088 live microglia broadly sampled across a diverse set of brain regions and neurodegenerative and neuroinflammatory diseases obtained from 161 donors sampled at autopsy or during a neurosurgical procedure. Using single-cell hierarchical Poisson factorization (scHPF), we derived a 23-factor model for continuous gene expression signatures across microglia which capture specific biological processes (e.g., metabolism, phagocytosis, antigen presentation, inflammatory signaling, disease-associated states). Using external datasets, we evaluated the aspects of microglial phenotypes that are encapsulated in various in vitro and in vivo microglia models and identified and replicated the role of two factors in human postmortem tissue of Alzheimer's disease (AD). Further, we derived a complex network of transcriptional regulators for all factors, including regulators of an AD-related factor enriched for the mouse disease-associated microglia 2 (DAM2) signature: ARID5B, CEBPA, MITF, and PPARG. We replicated the role of these four regulators in the AD-related factor and then designed a multiplexed MERFISH panel to assess our microglial factors using spatial transcriptomics. We find that, unlike cells with high expression of the interferon-response factor, cells with high expression of the AD DAM2-like factor are widely distributed in neocortical tissue. We thus propose a novel analytic framework that provides a taxonomic approach for microglia that is more biologically interpretable and use it to uncover new therapeutic targets for AD.
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Precancer Atlas to Drive Precision Prevention Trials.
Cancer development is a complex process driven by inherited and acquired molecular and cellular alterations. Prevention is the holy grail of cancer elimination, but making this a reality will take a fundamental rethinking and deep understanding of premalignant biology. In this Perspective, we propose a national concerted effort to create a Precancer Atlas (PCA), integrating multi-omics and immunity - basic tenets of the neoplastic process. The biology of neoplasia caused by germline mutations has led to paradigm-changing precision prevention efforts, including: tumor testing for mismatch repair (MMR) deficiency in Lynch syndrome establishing a new paradigm, combinatorial chemoprevention efficacy in familial adenomatous polyposis (FAP), signal of benefit from imaging-based early detection research in high-germline risk for pancreatic neoplasia, elucidating early ontogeny in BRCA1-mutation carriers leading to an international breast cancer prevention trial, and insights into the intricate germline-somatic-immunity interaction landscape. Emerging genetic and pharmacologic (metformin) disruption of mitochondrial (mt) respiration increased autophagy to prevent cancer in a Li-Fraumeni mouse model (biology reproduced in clinical pilot) and revealed profound influences of subtle changes in mt DNA background variation on obesity, aging, and cancer risk. The elaborate communication between the immune system and neoplasia includes an increasingly complex cellular microenvironment and dynamic interactions between host genetics, environmental factors, and microbes in shaping the immune response. Cancer vaccines are in early murine and clinical precancer studies, building on the recent successes of immunotherapy and HPV vaccine immune prevention. Molecular monitoring in Barrett's esophagus to avoid overdiagnosis/treatment highlights an important PCA theme. Next generation sequencing (NGS) discovered age-related clonal hematopoiesis of indeterminate potential (CHIP). Ultra-deep NGS reports over the past year have redefined the premalignant landscape remarkably identifying tiny clones in the blood of up to 95% of women in their 50s, suggesting that potentially premalignant clones are ubiquitous. Similar data from eyelid skin and peritoneal and uterine lavage fluid provide unprecedented opportunities to dissect the earliest phases of stem/progenitor clonal (and microenvironment) evolution/diversity with new single-cell and liquid biopsy technologies. Cancer mutational signatures reflect exogenous or endogenous processes imprinted over time in precursors. Accelerating the prevention of cancer will require a large-scale, longitudinal effort, leveraging diverse disciplines (from genetics, biochemistry, and immunology to mathematics, computational biology, and engineering), initiatives, technologies, and models in developing an integrated multi-omics and immunity PCA - an immense national resource to interrogate, target, and intercept events that drive oncogenesis. Cancer Res; 77(7); 1510-41. ©2017 AACR.
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Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses.
Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.