Cancer Res Treat.  2024 Oct;56(4):1113-1125. 10.4143/crt.2024.100.

A 10-Gene Signature to Predict the Prognosis of Early-Stage Triple-Negative Breast Cancer

• Kim CM
• Park KH
• Yu YS
• Kim JW
• Park JY
• Park K
• Yu JH
• Lee JE
• Sim SH
• Seo BK
• Kim JK
• Lee ES
• Park YH
• Kong SY

• KMID: 2560246
• DOI: http://doi.org/10.4143/crt.2024.100

Abstract

Purpose
Triple-negative breast cancer (TNBC) is a particularly challenging subtype of breast cancer, with a poorer prognosis compared to other subtypes. Unfortunately, unlike luminal-type cancers, there is no validated biomarker to predict the prognosis of patients with early-stage TNBC. Accurate biomarkers are needed to establish effective therapeutic strategies.
Materials and Methods
In this study, we analyzed gene expression profiles of tumor samples from 184 TNBC patients (training cohort, n=76; validation cohort, n=108) using RNA sequencing.
Results
By combining weighted gene expression, we identified a 10-gene signature (DGKH, GADD45B, KLF7, LYST, NR6A1, PYCARD, ROBO1, SLC22A20P, SLC24A3, and SLC45A4) that stratified patients by risk score with high sensitivity (92.31%), specificity (92.06%), and accuracy (92.11%) for invasive disease-free survival. The 10-gene signature was validated in a separate institution cohort and supported by meta-analysis for biological relevance to well-known driving pathways in TNBC. Furthermore, the 10-gene signature was the only independent factor for invasive disease-free survival in multivariate analysis when compared to other potential biomarkers of TNBC molecular subtypes and T-cell receptor β diversity. 10-gene signature also further categorized patients classified as molecular subtypes according to risk scores.
Conclusion
Our novel findings may help address the prognostic challenges in TNBC and the 10-gene signature could serve as a novel biomarker for risk-based patient care.

Keyword

Triple-negative breast neoplasms; Biomarkers; Prognostic diagnosis; Gene signature

Figure

• 

  Fig. 1. Selected prognostic gene signature evaluation of clinical performance. The clinical performance of the prognostic gene signature was evaluated using receiver operating characteristic (ROC) analysis, cross validation, and Cox regression analysis. (A) ROC analysis of the prognostic gene signature to predict the recurrence of triple-negative breast cancer. (B) Clinical performance of the gene signature in Cox regression analysis, cross-validation, and ROC analysis. AUC, area under the curve; CI, confidence interval; DGKH, diacylglycerol kinase eta; GADD45B, growth arrest and DNA damage inducible beta; KLF7, Kruppel-like factor 7; LYST, lysosomal trafficking regulator; NR6A1, nuclear receptor subfamily 6 group A member 1; PYCARD, PYD and CARD domain containing; ROBO1, roundabout guidance receptor 1; SLC22A20P, solute carrier family 22 member 20, pseudogene; SLC24A3, solute carrier family 24 member 3; SLC45A4, solute carrier family 45 member 4.

• 

  Fig. 2. Invasive disease-free survival in high risk and low-risk groups. The invasive disease-free survival was analyzed in different cases. (A) Kaplan-Meier curves for all patients. (B) Kaplan-Meier curves of patients treated with adjuvant chemotherapy. (C) Kaplan-Meier curves of patients treated with neoadjuvant chemotherapy.

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  Fig. 3. Prognostic validation of the gene signature in the validation cohort. The prognostic gene signature was validated by invasive disease-free survival analysis in various cases. (A) Kaplan-Meier curves for all patients. (B) Kaplan-Meier curves in primary tumor specimens (surgical specimens of adjuvant patients and biopsy specimens of neoadjuvant patients). (C) Kaplan-Meier curves of patients treated with adjuvant chemotherapy. (D) Kaplan-Meier curves in biopsies of patients treated with neoadjuvant chemotherapy. (E) Kaplan-Meier curves for invasive disease-free survival in residual tumors of patients treated with neoadjuvant chemotherapy.

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  Fig. 4. TNBC-type-4 analysis with gene signature. TNBC-type-4 was analyzed by invasive disease-free survival analysis in various cases. (A) Pie charts of TNBC-type-4 for total patients, high-risk patients and low-risk patients. (B) Kaplan-Meier curves of patients classified with TNBC-type-4. (C) Kaplan-Meier curves of patients classified with TNBC-type-4 and gene signature. (D) Kaplan-Meier curves of patients classified into BL1 subtype. (E) Kaplan-Meier curves of patients classified into BL2 subtype. (F) Kaplan-Meier curves of patients classified into M subtype. (G) Kaplan-Meier curves of patients classified into LAR subtype. BL1, basal-like 1; BL2, basal-like 2; LAR, luminal androgen receptor; M, mesenchymal; UNS, unspecified.

Reference

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