Evidence map›Paper›PMID 39310123›Full record

ArticleAmerican journal of clinical and experimental immunology2024

Characterization of tumor suppressors and oncogenes evaluated from TCGA cancers.

Claire Shen, Richard Geng, Sissi Zhu, Michael Huang, Jeffrey Liang, Binze Li, Yongsheng Bai

Abstract read
In one paragraph

Article in American journal of clinical and experimental immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

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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

7 authors.

Claire ShenJohns Hopkins University Baltimore, MD 21218, USA.
Richard GengCarmel High School Carmel, IN 46032, USA.
Sissi ZhuShady Side Academy Pittsburgh, PA 15238, USA.
Michael HuangJames E. Taylor High School Katy, TX 77450, USA.
Jeffrey LiangDaniel Hand High School Madison, CT 06443, USA.
Binze LiThe University of California, Los Angeles Los Angeles, CA 90095, USA.
Yongsheng BaiNext-Gen Intelligent Science Training Ann Arbor, MI 48105, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations in oncogenes and tumor suppressor genes can significantly impact cellular function during cancer development. A comprehensive analysis of their mutation patterns and significant gene ontology terms can provide insights into cancer emergence and suggest potential targets for drug development. This study analyzes twelve cancer subtypes by focusing on significant genetic and molecular factors. Two common genetic mutations associated with cancer are single nucleotide variants (SNVs) and copy number alterations (CNAs). Oncogenes, derived from mutated proto-oncogenes, disrupt normal cell functions and promote cancer, while tumor suppressor genes, often inactivated by mutations, regulate cell processes like proliferation and DNA damage response. This study analyzed datasets from The Cancer Genome Atlas (TCGA), which provides extensive genomic data across various cancers. In our analysis results, many genes with significant

Indexed as

cancercomputational biologyoncogenesThe Cancer Genome Atlastumor suppressors

Identifiers

PMID39310123
PMCPMC11411158

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.