Genetic Testing Enhances the Precision Diagnosis and Treatment of Breast Cancer

Korean patients with hereditary cancer: a prospective multicentre cohort study protocol exploring psychosocial and health outcomes

INTRODUCTION

Although genetic testing for hereditary cancers is increasing, data on health attitudes based on genetic pathogenicity are limited. This cohort study aims to establish three subcohorts based on genetic testing results to assess the health impact of genetic variations. This study evaluates changes in participant quality of life (QoL), unmet needs and mental health over time based on their genetic variant status.

METHODS AND ANALYSIS

This prospective cohort study will recruit 1435 patients with suspected hereditary cancer who have undergone BRCA1/2 or next-generation sequencing (NGS) testing. The study began in July 2023 and will continue until December 2027. By 2026, participants will be surveyed up to four times annually during their outpatient visits. The survey consists of 342 items across 5 domains: comorbidities (96), health behaviours (80), QoL (41), unmet needs (75) and mental health (50). Data were collected using 11 validated surveys. In addition, information on the chronic diseases, cancer diagnoses, medical history and treatment history of participants will be extracted from their electronic medical records to analyse their health status and cancer treatment experiences. Genetic variant data from BRCA1/2 and NGS will be used to classify participants into three subcohorts: pathogenic variants, variants of uncertain significance and undetectable mutations. A three-generation pedigree that includes details such as the year of cancer diagnosis, age at diagnosis, cancer type, survival status of family members and age at death will be constructed for each participant. The collected data will be linked to secondary sources such as cancer registries and National Health Insurance Service data to provide a comprehensive analysis of the impact of hereditary cancer on health and survival.

ETHICS AND DISSEMINATION

The study protocol was approved by all the Ethics Committees: the National Cancer Center IRB (NCC2023-0179), the Samsung Medical Center IRB (SMC2023-09-057), the Yonsei University Health System, Severance Hospital IRB (4-2023-0627), the Hanyang University Guri Hospital IRB (GURI2023-08-021) and the Keimyung University IRB (DSMC IRB 2024-05-048). The study outcomes will be disseminated through conference presentations, peer-reviewed publications and social media.

TRIAL REGISTRATION NUMBER

KCT0009460.

On integrative analysis of multi-level gene expression data in Kidney cancer subgrouping

Kidney cancer is one of the most dangerous cancer mainly targeting men. In 2020, around 430, 000 people were diagnosed with this disease worldwide. It can be divided into three prime subgroups such as kidney renal cell carcinoma (KIRC), kidney renal papilliary cell carcinoma (KIRP) and kidney chromophobe (KICH). Correct identification of these subgroups on time is crucial for the initiation and determination of proper treatment. On-time identification of this disease and its subgroup can help both the clinicians and patients to improve the situation. Hence, this study checks the possibility of using multi-omics data in the kidney cancer subgrouping, whether integrating multiple omics data will increase the subgrouping accuracy or not. Four different molecular data such as genomics, proteomics, epigenomics and miRNA from The Cancer Genome Atlas (TCGA) are used in this study. As the data is in a very high dimension world, this study starts with selecting the relevant features of the study using Pearson's correlation coefficient. Those selected features are used with three different classification algorithms such as k-nearest neighbor (KNN), supporting vector machines (SVMs) and random forest. Performances are compared to see whether the integration of multi-omics data can improve the accuracy of kidney cancer subgrouping. This study shows that integration of multi-omics data can improve the performance of the kidney cancer subgrouping. The highest performance (accuracy value of 0.98±0.03) is gained by top 400 features selected from integrated multi-omics data, with support vector machines.

Triple-Negative Breast Cancer: Tumor Immunogenicity and Beyond

Triple-negative breast cancer (TNBC) is a breast malignancy with a poor prognosis and limited therapeutic options. Many studies show that TNBC exhibits heterogeneity across clinical, histopathological, and molecular levels. In this review, we discuss the immunogenic features of TNBC with a focus on immunotherapy and the current standard of care in the neoadjuvant, adjuvant, and metastatic setting. In addition, we address the ongoing research on immunotherapy, antibody-drug conjugates (ADCs), poly ADP-ribose polymerase (PARP) inhibitors, and future challenges in the treatment of this entity.

Epithelial cell-related prognostic risk model in breast cancer based on single-cell and bulk RNA sequencing

Objective

This study aims to construct an epithelial cell-related prognostic risk model for breast cancer (BRCA) and explore its significance.

Methods

GSE42568, GSE10780, GSE245601, and TCGA-BRCA datasets were sourced from public databases. Epithelial cell-related differentially expressed genes were identified using single-cell data analysis. Venn diagrams determined the intersecting genes between epithelial cell-related and BRCA-related genes. Batch Kaplan-Meier (K-M) survival analysis identified core intersecting genes for BRCA overall survival. Consensus clustering, enrichment, LASSO, and COX regression analyses were performed on the core intersecting genes, and then a prognostic risk model was constructed. The diagnostic and prognostic effectiveness of the risk model was subsequently evaluated and immune infiltration analysis was conducted. Finally, qRT-PCR was used to verify the expression of genes in the risk model.

Results

There were 374 intersecting genes between epithelial cell-related and BRCA-related genes, among which 51 core intersecting genes were associated with BRCA prognosis. Consensus clustering categorized TCGA-BRCA into C1 and C2, with shared regulation of the estrogen signaling pathway. Three genes (DIRC3, SLC6A2, TUBA3D) were independent predictors of BRCA prognosis, forming the basis for a risk model. Except for exhibiting satisfactory diagnostic efficacy, the risk score elevation correlated with poor prognosis, elevated matrix, immune, and ESTIMATE scores, and negative correlation with microsatellite instability. The in vitro results confirmed the differential expression levels of DIRC3, SLC6A2, and TUBA3D.

Conclusion

The prognostic risk model associated with epithelial cells demonstrates effective diagnostic performance in BRCA, serving as an independent prognostic factor for BRCA patients. Additionally, it exhibits a correlation with immune scores.

Utilization and outcomes of the 21-gene recurrence score in de novo metastatic breast cancer

BACKGROUND

Limited data exist regarding the utility and validity of the 21-gene recurrence score (RS) in patients with de novo metastatic breast cancer (dnMBC). This study aimed to investigate the practice patterns as well as associated survival outcomes based on 21-gene RS in dnMBC.

RESEARCH DESIGN AND METHODS

The Surveillance, Epidemiology, and End Results Oncotype database was queried for women with hormone receptor-positive and Her2-negative dnMBC.

RESULTS

A total of 153 patients were identified, including 62.7% and 37.3% of patients who had RS < 26 and ≥ 26, respectively. Patients with RS ≥ 26 were more likely to receive chemotherapy compared to those with RS < 26 (61.4% vs. 28.1%, p < 0.001). Patients with RS ≥ 26 had an inferior breast cancer-specific survival (BCSS) (2-year BCSS: 84.3% vs. 89.5, p = 0.067) and overall survival (OS) compared to those with RS < 26 (2-year OS: 76.9% vs. 87.4%, p = 0.018). The multivariate Cox proportional hazard models showed that those with RS ≥ 26 had a significantly inferior BCSS (hazard ratio [HR] 2.251, 95% confidence interval [CI] 1.056-4.799, p = 0.036) and OS (HR 2.151, 95%CI 1.123-4.120, p = 0.021) compared to those with RS < 26.

CONCLUSIONS

The 21-gene RS assay is an important prognostic factor in patients with dnMBC.