Evidence map›Paper›PMID 38816397›Full record

ArticleScientific reports2024

Mutational landscape of HSP family on human breast cancer.

Juan Manuel Fernandez-Muñoz, Martin Eduardo Guerrero-Gimenez, Leonardo Andrés Ciocca, María José Germanó, Felipe Carlos Martin Zoppino

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Juan Manuel Fernandez-MuñozLaboratory of Data Science and Genomics, IMBECU CONICET UNCuyo, 5500, Mendoza, Argentina.
Martin Eduardo Guerrero-GimenezLaboratory of Data Science and Genomics, IMBECU CONICET UNCuyo, 5500, Mendoza, Argentina.
Leonardo Andrés CioccaHospital Italiano de Mendoza, Mendoza, 5519, Argentina.
María José GermanóLaboratory of Data Science and Genomics, IMBECU CONICET UNCuyo, 5500, Mendoza, Argentina.
Felipe Carlos Martin ZoppinoLaboratory of Data Science and Genomics, IMBECU CONICET UNCuyo, 5500, Mendoza, Argentina. mzoppino@gmail.com.

Funding

Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación PICT 2019-04617National Research Council of Argentina (CONICET) PIP 2918Universidad Nacional de Cuyo SIIP J038-T1Universidad Nacional de Cuyo SIIP J096
6 · The paper itself

Abstract

Breast cancer (BRCA) is a prevalent malignancy with the highest incidence among females. BRCA can be categorized into five intrinsic molecular subtypes (LumA, LumB, HER2, Basal, and Normal), each characterized by varying molecular and clinical features determined by the expression of intrinsic genes (PAM50). The Heat Shock Protein (HSP) family is composed of 95 genes evolutionary conservated, they have critical roles in proteostasis in both normal and cancerous processes. Many studies have linked HSP to the development and spread of cancer. They modulate the activity of multiple proteins expressed by oncogenes and anti-oncogenes through a range of interactions. In this study, we evaluate the mutational changes that HSP undergoes in BRCA mainly from the TCGA database. We observe that Copy Number Variations (CNV) are the more frequent events analyzed surpassing the occurrence of point mutations, indels, and translation start site mutations. The Basal subtype showcased the highest count of amplified CNV, including subtype-specific changes, whereas the Luminals tumors accumulated the greatest number of deletion CNV. Meanwhile, the HER2 subtype exhibited a comparatively lower frequency of CNV alterations when compared to the other subtypes. This study integrates CNV and expression data, finding associations between these two variables and the influence of CNV on the deregulation of HSP expression. To enhance the role of HSP as a risk predictor in BRCA, we succeeded in identifying CNV profiles as a prognostic marker. We included Artificial Intelligence to improve the clustering of patients, and we achieved a molecular CNV signature as a significant risk factor independent of known classic markers, including molecular subtypes PAM50. This research enhances the comprehension of HSP DNA alterations in BRCA and its relation with predicting the risk of affected individuals providing insights to develop guide personalized treatment strategies.

Indexed as

Breast NeoplasmsDNA Copy Number VariationsHeat-Shock ProteinsMutationBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansBiomarkers, TumorHeat-Shock Proteins

Identifiers

PMID38816397
PMCPMC11139924

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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.