<i>mdm2</i> gene amplification is associated with luminal breast cancer progression in humanized <scp>PDX</scp> mice and a worse outcome of estrogen receptor positive disease

Wege, Anja K.; Rom-Jurek, Eva-Maria; Jank, Paul; Denkert, Carsten; Ugocsai, Peter; Solbach, Christine; Blohmer, Jens-Uwe; Sinn, Bruno Valentin; Mackelenbergh, Marion van; Möbus, V.; Trumpp, Andreas; Marangoni, Elisabetta; Pfarr, Nicole; Irlbeck, Christoph; Warfsmann, Jens; Polzer, Bernhard; Weber, Florian; Ortmann, O.; Loibl, Sibylle; Vladimirova, Valentina; Brockhoff, Gero

doi:10.1002/ijc.33911

Cited by 7 publications

(5 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the METABRIC cohort, the Kaplan-Meier survival curves revealed that samples with MDM2 CN amplification or those with CDKN2A CN deep deletion presented worse prognosis (Figure 7A and B). The results of the samples with MDM2 CN amplification were consistent with those in previous reports (28,29). However, there were no statistically significant differences in the median cut-off values of MDM2 and CDKN2A mRNA expression levels (Supplementary Figure S2A-D).…”

Section: Samples With Mdm2 Cn Amplification or Those Withsupporting

confidence: 90%

TheMDM2andCDKN2ACopy-number-variation Influence theTP53-signature-score in Wild-typeTP53Luminal Type Breast Cancer

et al. 2022

View full text Add to dashboard Cite

Background/Aim: The TP53-signature is a multi-gene signature that can predict TP53 structural mutations. It has presented remarkable ability to predict the prognosis of earlystage breast cancer. However, some samples presented discordance with the signature status and structure status. We aimed to investigate whether the mRNA expression levels or copy number variation (CNV) of MDM2 and CDKN2A influence the TP53-signature-score, subtype classification, and prognosis prediction in TP53 wild-type, luminal type early-stage breast cancer samples. Materials and Methods: We selected TP53 wildtype, luminal type early-stage breast cancer samples from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohorts. Then, we analyzed the correlation between the TP53-signaturescore and mRNA expression levels or CNV of MDM2 and CDKN2A. Results: The samples with MDM2 copy number (CN) amplification or those with CDKN2A CN deep deletion presented higher TP53-signature-score. Moreover, samples with MDM2 CN amplification or those with CDKN2A CN deep deletion had more characteristics of the luminal B type. In addition, they showed lower estrogen response early score, which correlated with response to endocrine therapy in breast cancer. However, MDM2 and CDKN2A mRNA expression did not present the same tendency. Furthermore, samples with MDM2 CN amplification or those with CDKN2A CN deep deletion had a worse prognosis in METABRIC cohort. Conclusion: The MDM2 or CDKN2A CNV may be useful for classifying subtypes and predicting prognosis more accurately in TP53 wild-type, luminal type earlystage breast cancer patients.

show abstract

Section: Samples With Mdm2 Cn Amplification or Those Withsupporting

confidence: 90%

TheMDM2andCDKN2ACopy-number-variation Influence theTP53-signature-score in Wild-typeTP53Luminal Type Breast Cancer

et al. 2022

View full text Add to dashboard Cite

show abstract

“…It may be involved in preneoplastic processes, as it is detected in benign breast tumors [ 74 ]. Xu et al [ 75 ] had reported that NUF2 is overexpressed in breast cancer and significantly connected to multiple pathological features and prognosis of breast cancer. MDM2 from Cluster 4 is a cancer-related gene that encodes a nucleus-localized E3 ubiquitin ligase; such protein can promote tumor formation by targeting tumor suppressor proteins, e.g., p53, for proteasomal degradation.…”

Section: Discussionmentioning

confidence: 99%

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue

Mou

Liang

et al. 2023

Sensors

View full text Add to dashboard Cite

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

show abstract

“…NOD.Cg-Prkdc scid Il2rg tm1Wjl /SzJ (NSG) mice were obtained from Jackson Laboratories and housed and bred in a specialized pathogen-free facility at the University of Regensburg. Humanized tumor mice were generated as previously described [36]. In brief, newborn animals were irradiated with 1 Gy during the first 48 h of life span.…”

Section: Generation Of Humanized Patient-derived Tumor Mice (Hpdx)mentioning

confidence: 99%

Advanced Immune Cell Profiling by Multiparameter Flow Cytometry in Humanized Patient-Derived Tumor Mice

Bruß¹,

Kellner²,

Ortmann³

et al. 2022

Cancers

Self Cite

View full text Add to dashboard Cite

“Humanized” mice have been widely used for the characterization of human cancer progression and as a powerful preclinical model. Standardization of multicolor phenotyping could help to identify immune cell patterns involved in checkpoint-related complications. Therefore, we applied established protocols for immune cell profiling to our humanized Patient-Derived Xenograft (hPDX) model. hPDX are characterized by the co-existence of a human immune system and a patient-derived tumor transplant. These mice possess a human-like immune system after CD34+ stem cell transplantation while the reconstitution level of the immune system was not related to the quantity of transplanted CD34+ cells. Contamination ≤ 1.2% by CD3+ cells in the hematopoietic stem cell (HSC) transplant did not trigger abnormal T cell maturation. Different B and T cell differentiation stages were identified, as well as regulatory T cells (Tregs) and exhausted T cells that expressed TIGIT, PD-1, or KLRG1. Overall, the application of standardized protocols for the characterization of immune cells using flow cytometry will contribute to a better understanding of immune-oncologic processes.

show abstract

mdm2 gene amplification is associated with luminal breast cancer progression in humanized PDX mice and a worse outcome of estrogen receptor positive disease

Cited by 7 publications

References 55 publications

TheMDM2andCDKN2ACopy-number-variation Influence theTP53-signature-score in Wild-typeTP53Luminal Type Breast Cancer

TheMDM2andCDKN2ACopy-number-variation Influence theTP53-signature-score in Wild-typeTP53Luminal Type Breast Cancer

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue

Advanced Immune Cell Profiling by Multiparameter Flow Cytometry in Humanized Patient-Derived Tumor Mice

Contact Info

Product

Resources

About