Evidence map›Paper›PMID 36230801›Full record

ArticleCancers2022

Subpathway Analysis of Transcriptome Profiles Reveals New Molecular Mechanisms of Acquired Chemotherapy Resistance in Breast Cancer.

Yang Huo, Shuai Shao, Enze Liu, Jin Li, Zhen Tian, Xue Wu, Shijun Zhang, Daniel Stover, Huanmei Wu, Lijun Cheng and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.1field-weighted citation impact, top 11% 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

21 citing papers in PubMed, 22 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

Yang HuoSchool of Informatics, Indiana University, Indianapolis, IN 46032, USA.
Shuai ShaoDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0002-8178-1421
Enze LiuDepartment of Medicine, School of Medicine, Indiana University, Indianapolis, IN 46032, USA.ORCID 0000-0003-3162-461X
Jin LiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Zhen TianDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Xue WuDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Shijun ZhangDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Daniel StoverDivision of Medical Oncology, Department of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Huanmei WuDepartment of Health Service Administration and Policy, College of Public Health, Temple University, Philadelphia, PA 19122, USA.
Lijun ChengDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
Lang LiDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA.
The Ohio State University · USIndiana University Indianapolis · USIndiana University – Purdue University Indianapolis · USTemple University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chemoresistance has been a major challenge in the treatment of patients with breast cancer. The diverse omics platforms and small sample sizes reported in the current studies of chemoresistance in breast cancer limit the consensus regarding the underlying molecular mechanisms of chemoresistance and the applicability of these study findings. Therefore, we built two transcriptome datasets for patients with chemotherapy-resistant breast cancers—one comprising paired transcriptome samples from 40 patients before and after chemotherapy and the second including unpaired samples from 690 patients before and 45 patients after chemotherapy. Subsequent conventional pathway analysis and new subpathway analysis using these cohorts uncovered 56 overlapping upregulated genes (false discovery rate [FDR], 0.018) and 36 downregulated genes (FDR, 0.016). Pathway analysis revealed the activation of several pathways in the chemotherapy-resistant tumors, including those of drug metabolism, MAPK, ErbB, calcium, cGMP-PKG, sphingolipid, and PI3K-Akt, as well as those activated by Cushing’s syndrome, human papillomavirus (HPV) infection, and proteoglycans in cancers, and subpathway analysis identified the activation of several more, including fluid shear stress, Wnt, FoxO, ECM-receptor interaction, RAS signaling, Rap1, mTOR focal adhesion, and cellular senescence (FDR < 0.20). Among these pathways, those associated with Cushing’s syndrome, HPV infection, proteoglycans in cancer, fluid shear stress, and focal adhesion have not yet been reported in breast cancer chemoresistance. Pathway and subpathway analysis of a subset of triple-negative breast cancers from the two cohorts revealed activation of the identical chemoresistance pathways.

Indexed as

breast cancer chemotherapy resistancepathway analysistranscriptome

Identifiers

PMID36230801
PMCPMC9563670
OpenAlexW4303622028

What OpenQuestion 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 OpenQuestion graph.