β2-spectrin (SPTBN1) as a therapeutic target for diet-induced liver disease and preventing cancer development

Rao, Shuyun; Yang, Xiaochun; Ohshiro, Kazufumi; Zaidi, Sobia; Wang, Zhanhuai; Shetty, Kirti; Xiang, Xiyan; Hassan, Md. Imtaiyaz; Latham, Patricia S.; Nguyen, Bao-Ngoc; Yu, Herbert; Al‐Abed, Yousef; Mishra, Bibhuti; Vacca, Michèle; Guenigault, Gareth; Allison, Michael; Vidal-Puig, António; Benhammou, Jihane N.; Alvarez, Marcus; Pajukanta, Päivi; Pisegna, Joseph R.; Mishra, Lopa

doi:10.1126/scitranslmed.abk2267

Cited by 26 publications

(36 citation statements)

References 96 publications

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“…Significantly upregulated genes include CLDN4, TM4SF1, ZFAS1 each of which have been implicated GC (28,41). Significantly downregulated genes across these six cultures, included LYZ and TFF2, which modulate mucin production underscoring the general decrease in mucosal phenotypes in TP53 deficient gastric organoids and SPTBN1, a cytoskeletal protein involved in TGF-β signaling (42).…”

Section: Longitudinal Single Cell Profiling Reveals Transcriptional D...mentioning

confidence: 94%

Deterministic evolution and stringent selection during pre-neoplasia

Karlsson

Przybilla

et al. 2022

Preprint

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The earliest events during human tumor initiation are poorly characterized but may hold clues as to how to detect and prevent malignancy. Here we model this occult process by engineering TP53 deficiency in primary human gastric organoids and performing experimental evolution in multiple clonally derived cultures over two years, thereby defining causal relationships between this common initiating genetic lesion and resulting phenotypes. TP53 loss elicited progressive aneuploidy, including copy number alterations and complex structural variants that are common in gastric cancers and which follow preferred temporal orders. Longitudinal single cell sequencing of TP53 deficient gastric organoids similarly indicates progression towards malignant transcriptional programs. Moreover, lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programs repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference and a striking degree of phenotypic convergence in pre-malignant epithelial organoids, implying that the earliest stages of tumorigenesis may be predictable while illuminating evolutionary constraints and barriers to malignant transformation.

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Section: Longitudinal Single Cell Profiling Reveals Transcriptional D...mentioning

confidence: 94%

Deterministic evolution and stringent selection during pre-neoplasia

Karlsson

Przybilla

et al. 2022

Preprint

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“…To identify cell-types associated with HCC and its survival outcomes, we first analyzed three liver single cell level data sets from an existing snRNA-seq cohort of NAFLD-related HCC [ 25 ], an existing scRNA-seq cohort of HCC from various etiologies [ 8 ], and a healthy liver scRNA-seq cohort [ 7 ] to identify and characterize their cell-types. Next, we leveraged these liver cell-type reference data to decompose cell-type proportions in the liver bulk RNA-seq data from the Cancer Genome Atlas (TCGA) cohort [ 26 ] and subsequently tested the estimated cell-type proportions for associations with HCC and survival outcomes.…”

Section: Methodsmentioning

confidence: 99%

“…We identified NAFLD-related HCC cases among patients undergoing surgical resection for HCC treatment at the Dumont-UCLA Liver Cancer Center [ 25 ]. The 3 patients with NAFLD-related HCC were women with a mean age of 77.9 ± 3.1 years and a mean body mass index of 25.3 ± 2.9 kg/m 2 , who had components of the metabolic syndrome (hypertension, dyslipidemia and insulin resistance).…”

Section: Methodsmentioning

confidence: 99%

“…Along with the snRNA-seq data [ 25 ], we also incorporated liver scRNA-seq data from two previously published cohorts into our single cell level analysis [ 1 ]: HCC patients with viral origin of HCC ( n = 4), HCC patients with unspecific origin of HCC ( n = 10), and adjacent control liver samples ( n = 14), as well as a healthy normal donor, collected in the Singapore General Hospital and National University Hospital [ 8 ], and [ 2 ] normal liver samples ( n = 9), collected in the Strasbourg University Hospital [ 7 ]. Data from Sharma et al [ 8 ] were downloaded from https://data.mendeley.com/datasets/6wmzcskt6k/1 .…”

Section: Methodsmentioning

confidence: 99%

“…We hypothesized that snRNA-seq can complement the existing scRNA and bulk expression data from liver HCC and normal liver cohorts and that these data can be integrated to identify currently unknown HCC-associated cell-types that affect survival when their proportions expand in the tumor tissue. To this end, we first used a liver snRNA-seq data set that we previously generated from HCC tumor and adjacent non-tumor liver biopsies from patients with NAFLD-related HCC [ 25 ], and then integrated these data with two existing liver scRNA-seq data sets, representing multiple etiologies of HCC and normal liver [ 7 , 8 ]. Thus, we generated a powerful reference data set, comprising both viral and non-viral origin HCC, adjacent non-tumor, and normal liver samples at the single cell resolution.…”

Section: Introductionmentioning

confidence: 99%

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Human liver single nucleus and single cell RNA sequencing identify a hepatocellular carcinoma-associated cell-type affecting survival

et al. 2022

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Background Hepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival. Methods We combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort (n = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort (n = 1 non-HCC, n = 14 HCC-tumor, and n = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort (n = 3 HCC-tumor and n = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients’ tumor (n = 361) and adjacent non-tumor tissue (n = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University. Results We discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC. Conclusions By integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.

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Regulation and targeting of SREBP-1 in hepatocellular carcinoma

Su,

Koeberle

2023

Cancer Metastasis Rev

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Hepatocellular carcinoma (HCC) is an increasing burden on global public health and is associated with enhanced lipogenesis, fatty acid uptake, and lipid metabolic reprogramming. De novo lipogenesis is under the control of the transcription factor sterol regulatory element-binding protein 1 (SREBP-1) and essentially contributes to HCC progression. Here, we summarize the current knowledge on the regulation of SREBP-1 isoforms in HCC based on cellular, animal, and clinical data. Specifically, we (i) address the overarching mechanisms for regulating SREBP-1 transcription, proteolytic processing, nuclear stability, and transactivation and (ii) critically discuss their impact on HCC, taking into account (iii) insights from pharmacological approaches. Emphasis is placed on cross-talk with the phosphatidylinositol-3-kinase (PI3K)-protein kinase B (Akt)-mechanistic target of rapamycin (mTOR) axis, AMP-activated protein kinase (AMPK), protein kinase A (PKA), and other kinases that directly phosphorylate SREBP-1; transcription factors, such as liver X receptor (LXR), peroxisome proliferator-activated receptors (PPARs), proliferator-activated receptor γ co-activator 1 (PGC-1), signal transducers and activators of transcription (STATs), and Myc; epigenetic mechanisms; post-translational modifications of SREBP-1; and SREBP-1-regulatory metabolites such as oxysterols and polyunsaturated fatty acids. By carefully scrutinizing the role of SREBP-1 in HCC development, progression, metastasis, and therapy resistance, we shed light on the potential of SREBP-1-targeting strategies in HCC prevention and treatment.

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β2-spectrin (SPTBN1) as a therapeutic target for diet-induced liver disease and preventing cancer development

Abstract: Targeting SBPTN1 with siRNA has the potential to treat NASH and prevent HCC.

Cited by 26 publications

References 96 publications

Deterministic evolution and stringent selection during pre-neoplasia

Deterministic evolution and stringent selection during pre-neoplasia

Human liver single nucleus and single cell RNA sequencing identify a hepatocellular carcinoma-associated cell-type affecting survival

Regulation and targeting of SREBP-1 in hepatocellular carcinoma

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