ArticleOmics : a journal of integrative biology2012
Identifying grade/stage-related active modules in human co-regulatory networks: a case study for breast cancer.
Article in Omics : a journal of integrative biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The histological grade/stage of tumor is widely acknowledged as an important clinical prognostic factor for cancer progression. Recent experimental studies have explored the following two topics at the molecular level: (1) whether or not gene expression levels vary by different degrees among different tumor grades/stages, and (2) whether some well-defined modules could distinguish one grade/stage from another. In this article, using breast cancer as an example, we investigated this topic and identified grade/stage-related active modules under the framework of a weighted network integrated from a human protein interaction network and a transcriptional regulatory network. Our results enabled us to draw the conclusion that the gene expression profile could provide more clues about tumor grade, but reveals less evidence about tumor stage. In addition, we found that our modular biomarker method had additional advantages in identifying some tumor grade/stage-related genes with slightly altered expression. According to our case study, the framework we introduced could be used for other cancers to identify their modules during grading or staging.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.