Evidence map›Paper›PMID 38347290›Full record

ArticleBiochemical genetics2024

Identifying an AML Prognostic Model Using 10 Marker Genes from Single-Cell Transcriptome and Bulk Transcriptome Analysis.

Fangyuan Zhang, Xiaohua Guo, Lihong Ye, Shicheng Yu

Abstract read
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In one paragraph

Article in Biochemical genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 98% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 4 institutions in 1 country.

Fangyuan Zhang *Department of Urology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, China.
Xiaohua Guo *Department of Gastroenterology, Peking University Third Hospital, Beijing, 100000, China.
Lihong Ye *Guangzhou Medical University, Xinzao, Panyu District, Guangzhou, 511436, China.
Shicheng YuGuangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, 510005, China. shyu@whu.edu.cn.
Guangzhou Institutes of Biomedicine and Health · CNGuangzhou Medical University · CNPeking University · CNTsinghua University · CN

Funding

Guangdong Provincial Postdoctoral Science Foundation O0390302
6 · The paper itself

Abstract

Fanconi anemia (FA) is the predominant hereditary syndrome of bone marrow failure (BMF), distinguished by impairments in DNA repair mechanisms. The deficiency in the FANC pathway, which governs DNA repair and replication rescue, results in aberrant responses to DNA damage in individuals with FA. The objective of this study is to examine the involvement of the FANC core complex in BMF and ascertain nucleolar homeostasis-related genes by conducting transcriptome analysis on primary hematopoietic stem cells obtained from FA patients with FANCA and FANCC variants. In the present study, we analyzed scRNA-seq data obtained from both healthy donors and individuals diagnosed with FA in order to investigate the phenomenon of cell-cell communication. Through the implementation of trajectory analysis, the differentiation pathways of several progenitor cell types, such as HSC cells transitioning into LMPP, N, M, B-prog, and E cells, were elucidated. Moreover, by scrutinizing the inferred interactions, notable disparities in cell-cell communication were observed between FA patients and their healthy counterparts. Our analysis has unveiled heightened interactions involving TNFSF13B, MIF, IL16, and COL4A2 in patients with FA. Furthermore, we have developed a prognostic model for predicting the outcome of acute myeloid leukemia (AML) which has exhibited remarkable predictive precision, with an AUC exceeding 0.83 at the 3- and 5-year intervals following the baseline assessment. In summary, the prognostic model that has been developed provides a valuable instrument for forecasting outcomes of AML by utilizing the genes identified through both single-cell and bulk transcriptome analyses.

Indexed as

Leukemia, Myeloid, AcuteSingle-Cell AnalysisTranscriptomeBiomarkers, TumorFanconi AnemiaFemaleGene Expression ProfilingHematopoietic Stem CellsHumansMalePrognosisBiomarkers, TumorCell–Cell communicationFANCFanconi anemiaPrognostic modelscRNA-seq

Identifiers

PMID38347290
OpenAlexW4391755786

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.