Evidence map›Paper›PMID 38321554›Full record

ArticleBiomarker research2024

A patient with multiple primary malignant neoplasms with high variant allele frequencies of RB1, TP53, and TERT.

Mingyang Ma, Kun Shang, Jiewei Wang, Xiaojing Teng, Peng Li, Jing Wang

Abstract readLetter
In one paragraph

Article in Biomarker research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Mingyang MaDepartment of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Kun ShangDepartment of Oncology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Jiewei WangDepartment of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Xiaojing TengDepartment of Pathology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Peng LiDepartment of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Jing WangDepartment of Oncology, Beijing Friendship Hospital, Capital Medical University, Beijing, China. wangjing1981@ccmu.edu.cn.

Funding

Beijing Municipal Administration of Hospitals Incubating Program PZ2023001
6 · The paper itself

Abstract

Multiple primary malignant neoplasms are a rare disease with tumors of different histology or morphology arising in various sites. Next-generation sequencing is essential in the etiology, diagnosis, treatment, and surveillance of this disease. No eight primary malignant neoplasm cases with high variant allele frequencies of RB1, TP53, and TERT have been reported. Herein, we report a 65-year-old male who exhibited eight primary malignancies of the vocal cord, pharynx, kidney, mouth floor, esophagus, and urinary bladder with different pathological types. The first seven tumors were early-stage tumors; the last tumor, small cell carcinoma of urinary bladder, showed liver metastasis at diagnosis. Next-generation sequencing results revealed extremely high somatic variant allele frequencies of RB1 c.1472 T > C, TP53 c.576A > G, and TERT c.-58-u66C > T (95.5%, 95.1%, and 51.0%, respectively). No germline mutations were detected. These findings denoted a heavy tumor burden and poor prognosis. This is the first report of eight primary malignant neoplasm cases with high variant allele frequencies of RB1, TP53, and TERT.

Indexed as

Multiple primary malignant neoplasmsNext-generation sequencingRB1Small cell carcinoma of urinary bladderTERTTP53Variant allele frequency

Identifiers

PMID38321554
PMCPMC10845515

What OpenQuestion 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 OpenQuestion graph.