Evidence map›Paper›PMID 35581624›Full record

ArticleGenome medicine2022

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

Marcus Alvarez, Jihane N Benhammou, Nicholas Darci-Maher, Samuel W French, Steven B Han, Janet S Sinsheimer, Vatche G Agopian, Joseph R Pisegna, Päivi Pajukanta

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
7.5field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

60 citing papers in PubMed, 90 citations in OpenAlex.

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  8. Computational analysis of multi-omics data reveals CXCL10Cellular and molecular life sciences : CMLS · 2026
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  9. F13A1-Mediated Macrophage Activation Promotes MASH Progression via the PKM2/HIF1A Pathway.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Marcus Alvarez *Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.ORCID 0000-0002-6369-5028
Jihane N Benhammou *Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Nicholas Darci-MaherDepartment of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Samuel W FrenchDepartment of Pathology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Steven B HanDepartment of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Janet S SinsheimerDepartment of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Vatche G AgopianDumont-UCLA Transplant and Liver Cancer Centers, Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Joseph R PisegnaDepartment of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Päivi PajukantaDepartment of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. ppajukanta@mednet.ucla.edu.
University of California, Los Angeles · US

Funding

Systems genomics of metabolic syndrome traitsP01HL028481 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PAJUKANTA, PAIVI · 1985 to 2019
$50.2M
Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
Integrated analysis of HCC CTCs for Liver Transplant Candidate SelectionR01CA246304 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AGOPIAN, VATCHE, TSENG, HSIAN-RONG · 2020 to 2024
$2.8M
Modeling, Inference, and Optimization for Genomic and Biomedical Big DataR35GM141798 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LANGE, KENNETH L · 2021 to 2025
$2.7M
Methods for Genomic Analysis in Heterogeneous TissuesR01HG010505 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HALPERIN, ERAN · 2019 to 2022
$2.6M
Functional genetic variants for type 2 diabetesU01DK105561 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MOHLKE, KAREN L. · 2015 to 2019
$2.3M
Integrative approaches for mapping the genetic risk of complex traitsR01HG009120 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PASANIUC, BOGDAN · 2017 to 2021
$2.3M
Analysis of HCC CTC Phenotype for Liver Transplant Candidate SelectionR21CA216807 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AGOPIAN, VATCHE · 2018 to 2019
$368k
Molecular Mechanisms of Stellate Cell Activation in Liver FibrosisI01BX001991 · VA · VA GREATER LOS ANGELES HEALTHCARE SYSTEM · PI HIDEKAZU TSUKAMOTO · 2014 to 2026
–
BLRD VA I01 BX004560Howard Hughes Medical InstituteNCI NIH HHS R01 CA246304NCI NIH HHS R21 CA216807NHLBI NIH HHS P01 HL028481NIDDK NIH HHS U01 DK105561NIH HHS R01HG006139NIH HHS R01HG009120NIH HHS R01HG010505NIH HHS R35GM141798NIH HHS U01DK105561
6 · The paper itself

Abstract

backgroundHepatocellular 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.

methodsWe 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.

resultsWe 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.

conclusionsBy 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.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkers, TumorGene Expression Regulation, NeoplasticHumansPrognosisSequence Analysis, RNABiomarkers, Tumor

Identifiers

PMID35581624
PMCPMC9115949
OpenAlexW4280503962

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.