Evidence map›Paper›PMID 36110952›Full record

ArticleFrontiers in oncology2022

An emerging prognosis prediction model for multiple myeloma: Hypoxia-immune related microenvironmental gene signature.

Zhengyu Yu, Bingquan Qiu, Linfeng Li, Jing Xu, Hui Zhou, Ting Niu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

8 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
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

6 authors at 3 institutions in 1 country.

Zhengyu YuDepartment of Hematology, West China Hospital, Sichuan University, Chengdu, China.
Bingquan QiuDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
Linfeng LiDepartment of Hematology, West China Hospital, Sichuan University, Chengdu, China.
Jing XuDepartment of Hematology, West China Hospital, Sichuan University, Chengdu, China.
Hui ZhouDepartment of Hematology, West China Hospital, Sichuan University, Chengdu, China.
Ting NiuDepartment of Hematology, West China Hospital, Sichuan University, Chengdu, China.
Sichuan University · CNPeking University · CNWest China Hospital of Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple myeloma (MM), a hematologic malignancy, is characterized by malignant plasma cells clonal proliferation. Many evidences indicated the indirect interaction between hypoxic environment and immune state in MM tumorigenesis, but the underlying mechanism remains unclear. MM-related datasets were downloaded from the Gene Expression Omnibus (GEO) database. The R packages were applied for screening protective differentially expressed genes (DEGs) and risk DEGs. The signature was constructed based the most prognostic gene signature in the training and assessed in the validation cohorts. The immune cell infiltration, the expression of the HLA family and immune checkpoint genes inside the low- and high-risk groups were compared to determine the differences in immune infiltration and immunotherapy responses. Moreover, the expression of HLA families and immune checkpoints inside the low- and high-risk groups was markedly disordered. The results indicated hypoxia- and immune-related genes, including

Indexed as

hypoxiaimmuneimmunotherapymultiple myelomaprognosistumor microenvironment

Identifiers

PMID36110952
PMCPMC9468480
OpenAlexW4293661241

What Socratic holds

Textmetadata
LicenceCC BY
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.