Identification of a Gene Panel Predictive of Triple-Negative Breast Cancer Response to Neoadjuvant Chemotherapy Employing Transcriptomic and Functional Validation.

Int J Mol Sci

Translational Cancer and Immunity Center (TCIC), Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Doha P.O. Box 34110, Qatar.

Published: September 2022

AI Article Synopsis

  • Patients with triple-negative breast cancer (TNBC) who achieve a pathological complete response (pCR) have significantly better outcomes than those with residual disease (RD), highlighting the need for effective biomarkers.
  • A study identified a gene panel consisting of eight RD-derived genes that predict both RD and pCR, showing strong correlation with overall survival and relapse-free survival in larger breast cancer cohorts.
  • Further analysis demonstrated that depleting these genes in TNBC cell models inhibited proliferation, and the identified gene signatures could potentially improve clinical decision-making by accurately distinguishing between RD and pCR in patients.

Article Abstract

Triple-negative breast cancer (TNBC) patients exhibiting pathological complete response (pCR) have better clinical outcomes compared to those with residual disease (RD). Therefore, robust biomarkers that can predict pCR may help with triage and resource prioritization in patients with TNBC. Herein, we identified a gene panel predictive of RD and pCR in TNBC from the discovery ( = 90) treatment-naive tumor transcriptomic data. Eight RD-derived genes were identified as TNBC-essential genes, which were highly predicative of overall survival (OS) and relapse-free survival (RFS) in an additional cohort of basal breast cancer ( = 442). Mechanistically, targeted depletion of the eight genes reduced the proliferation potential of TNBC cell models, while most remarkable effects were for combined SLC39A7, TIMM13, BANF1, and MVD knockdown in conjunction with doxorubicin. Orthogonal partial least squares-discriminant analysis (OPLS-DA) and receiver operating characteristic curve (ROC) analyses revealed significant predictive power for the identified gene panels with an area under the curve (AUC) of 0.75 for the validation cohort ( = 50) to discriminate RD from pCR. Protein-Protein Interaction (PPI) network analysis of the pCR-derived gene signature identified an 87-immune gene signature highly predictive of pCR, which correlated with better OS, RFS, and distant-metastasis-free survival (DMFS) in an independent cohort of basal and, to a lesser extent, HER2+ breast cancer. Our data have identified gene signatures predicative of RD and pCR in TNBC with potential clinical implications.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9506546PMC
http://dx.doi.org/10.3390/ijms231810901DOI Listing

Publication Analysis

Top Keywords

breast cancer
16
identified gene
12
gene panel
8
panel predictive
8
triple-negative breast
8
predictive pcr
8
pcr tnbc
8
cohort basal
8
gene signature
8
pcr
6

Similar Publications

The emergence of self-propelling magnetic nanobots represents a significant advancement in the field of drug delivery. These magneto-nanobots offer precise control over drug targeting and possess the capability to navigate deep into tumor tissues, thereby addressing multiple challenges associated with conventional cancer therapies. Here, Fe-GSH-Protein-Dox, a novel self-propelling magnetic nanobot conjugated with a biocompatible protein surface and loaded with doxorubicin for the treatment of triple-negative breast cancer (TNBC), is reported.

View Article and Find Full Text PDF

LAG3 plays a regulatory role in immunity and emerged as an inhibitory immune checkpoint molecule comparable to PD-L1 and CTLA-4 and a potential target for enhancing anti-cancer immune responses. We generated 3D cancer cultures as a model to identify novel molecular biomarkers for the selection of patients suitable for α-LAG3 treatment and simultaneously the possibility to perform an early diagnosis due to its higher presence in breast cancer, also to achieve a theragnostic approach. Our data confirm the extreme dysregulation of LAG3 in breast cancer with significantly higher expression in tumor tissue specimens, compared to non-cancerous tissue controls.

View Article and Find Full Text PDF

This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.

View Article and Find Full Text PDF

T cell induced expression of Coronin-1A facilitates blood-brain barrier transmigration of breast cancer cells.

Sci Rep

December 2024

Department of Pathology, The Tumor Immuno-Pathology Laboratory, Erasmus University Medical Center, Wytemaweg 80, 3000 DR, Rotterdam, The Netherlands.

In previous work we discovered that T lymphocytes play a prominent role in the rise of brain metastases of ER-negative breast cancers. In the present study we explored how T lymphocytes promote breast cancer cell penetration through the blood brain barrier (BBB). An in vitro BBB model was employed to study the effects of T lymphocytes on BBB trespassing capacity of three different breast carcinoma cell lines.

View Article and Find Full Text PDF

Background: Benzodiazepines are the third most misused medication, with many patients having their first exposure during a surgical episode. We sought to characterize factors associated with new persistent benzodiazepine use (NPBU) among patients undergoing cancer surgery.

Patients And Methods: Patients who underwent cancer surgery between 2013 and 2021 were identified using the IBM-MarketScan database.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!