Prognostic Value of the TP53 Mutation Location in Metastatic Breast Cancer as Detected by Next-Generation Sequencing

Construction of a prognostic model for breast cancer based on moonlighting genes

Breast cancer (BRCA) is a highly heterogeneous disease, with significant differences in prognosis among patients. Existing biomarkers and prognostic models have limited ability to predict BRCA prognosis. Moonlighting genes regulate tumor progression and are associated with cancer prognosis. This study aimed to construct a moonlighting gene-based prognostic model for BRCA. We obtained differentially expressed genes (DEGs) in BRCA from The Cancer Genome Atlas and intersected them with moonlighting genes from MoonProt to acquire differential moonlighting genes. GO and KEGG results showed main enrichment of these genes in the response of BRCA cells to environmental stimuli and pentose phosphate pathway. Based on moonlighting genes, we conducted drug prediction and validated results through cellular experiments. After ABCB1 knockdown, viability and proliferation of BRCA cells were significantly enhanced. Based on differential moonlighting genes, BRCA was divided into three subgroups, among which cluster2 had the highest survival rate and immunophenoscore and relatively low tumor mutation burden. TP53 had the highest mutation frequency in cluster2 and cluster3, while PIK3CA had a higher mutation frequency in cluster1, with the majority being missense mutations. Subsequently, we established an 11-gene prognostic model in the training set based on DEGs among subgroups using univariate Cox regression, LASSO regression, and multivariable Cox regression analyses. Model prognostic performance was verified in GEO, METABRIC and ICGC validation sets. In summary, this study obtained three BRCA moonlighting gene-related subtypes and constructed an 11-gene prognostic model. The 11-gene BRCA prognostic model has good predictive performance, guiding BRCA prognosis for clinical doctors.

Prognostic significance of TP53 and PIK3CA mutations analyzed by next-generation sequencing in breast cancer

Breast cancer is one of the most prevalent malignant tumors affecting women globally. It is a heterogeneous disease characterized by mutations in several genes. Several gene panels have been applied to assess the risk of breast cancer and determine the appropriate treatment. As a powerful tool, Next-generation sequencing (NGS) has been widely utilized in cancer research due to its advantages, including high speed, high throughput, and high accuracy. In this study, we aim to analyze the correlation between somatic mutations in breast cancer, analyzed using NGS, and the prognosis of patients. Between May 2018 and May 2019, a total of 313 patients with breast cancer underwent surgical treatment, which included total mastectomy and breast-conserving surgery. Among these patients, 265 were diagnosed with invasive ductal carcinoma. In this study, we analyzed the NGS results, clinicopathological characteristics, and their correlation with prognosis. Using a gene panel, we examined 143 somatic mutations in solid cancers. Notably, the study population included patients who had received neoadjuvant chemotherapy. The mean age of the patients was 53.1 (±10.28) years, and the median follow-up time was 48 months (range, 8-54). Among the 265 patients, 68 had received prior systemic therapy. Of these, 203 underwent breast-conserving surgery, and 62 underwent a mastectomy. Various somatic mutations were observed in NGS, with the most frequent mutation being PIK3CA mutations, which accounted for 44% of all mutations. TP53 mutations were the second most frequent, and ERBB2 mutations were the third most frequent. TP53 mutations were associated with poor disease-free survival (P = .027), while PIK3CA mutations were associated with better disease-free survival (P = .035) than PIK3CA wild-type. In our study, we identified various somatic mutations in breast cancer. Particularly, we found that TP53 and PIK3CA mutations are potentially associated with the prognosis of breast cancer. These findings suggest that the presence of specific mutations may have implications for predicting the prognosis of breast cancer. Further research and validation are needed to gain a deeper understanding of the role of these mutations and their mechanisms in prognosis prediction.

Pathogenic variant profile in DNA damage response genes correlates with metastatic breast cancer progression-free survival in a Mexican-mestizo population

Introduction

Metastatic breast cancer causes the most breast cancer-related deaths around the world, especially in countries where breast cancer is detected late into its development. Genetic testing for cancer susceptibility started with the BRCA 1 and 2 genes. Still, recent research has shown that variations in other members of the DNA damage response (DDR) are also associated with elevated cancer risk, opening new opportunities for enhanced genetic testing strategies.

Methods

We sequenced BRCA1/2 and twelve other DDR genes from a Mexican-mestizo population of 40 metastatic breast cancer patients through semiconductor sequencing.

Results

Overall, we found 22 variants -9 of them reported for the first time- and a strikingly high proportion of variations in ARID1A. The presence of at least one variant in the ARID1A, BRCA1, BRCA2, or FANCA genes was associated with worse progression-free survival and overall survival in our patient cohort.

Discussion

Our results reflected the unique characteristics of the Mexican-mestizo population as the proportion of variants we found differed from that of other global populations. Based on these findings, we suggest routine screening for variants in ARID1A along with BRCA1/2 in breast cancer patients from the Mexican-mestizo population.

Association between TP53 mutation and high 21-gene recurrence score in estrogen receptor-positive/HER2-negative breast cancer

We investigated the association between TP53 mutation and 21-gene recurrence score (RS) in ER-positive/HER2-negative breast cancer (BC) using data from 141 patients who underwent TP53 sequencing and Oncotype DX^® tests. We detected TP53 mutations in 18 (12.8%) patients. Most patients with TP53 mutation had a high 21-gene RS (≥26). The average 21-gene RS was higher in TP53 mutant tumors. Multivariate analysis showed that mutated TP53 is an independent factor for a high 21-gene RS. Mutated TP53 remained closely associated with high 21-gene RS in patients with low pathological risk (n = 103). In the ER⁺/PR⁺/HER2-negative subset (n = 356) of The Cancer Genome Atlas, the non-luminal A intrinsic subtype was more prevalent in the group with mutant TP53. mRNA levels of p53-regulated senescence gatekeeper and cell cycle-related genes were increased in BC with mutated TP53. Mutational analysis of TP53 helped identify endocrine-resistant tumors.

Detection of genetic mutations in patients with breast cancer from Saudi Arabia using Ion AmpliSeq™ Cancer Hotspot Panel v.2.0

Next-Generation Sequencing allows for quick and precise sequencing of multiple genes concurrently. Recently, this technology has been employed for the identification of novel gene mutations responsible for disease manifestation among breast cancer (BC) patients, the most common type of cancer amongst Arabian women, and the major cause of disease-associated death in women worldwide. Genomic DNA was extracted from the peripheral blood of 32 Saudi Arabian BC patients with histologically confirmed invasive BC stages I-III and IV, as well from 32 healthy Saudi Arabian women using a QIAamp^® DNA Mini Kit. The isolated DNA was quantified using a Qubit™ dsDNA BR Assay Kit with a Qubit 2.0 Fluorometer. Ion semiconductor sequencing technology with an Ion S5 System and AmpliSeq™ Cancer Hotspot Panel v2 were utilized to analyze ~2,800 mutations described in the Catalogue of Somatic Mutations in Cancer from 50 oncogenes and tumor suppressor genes. Ion Reporter Software v.5.6 was used to evaluate the genomic alterations in all the samples after alignment to the hg19 human reference genome. The results showed that out of the 50 genes, 26 mutations, including 17 (65%) missense point mutations (single nucleotide variants), and 9 (35%) frameshift (insertion/deletion) mutations, were identified in 11 genes across the cohort in 61 samples (95%). Mutations were predominantly focused on two genes, PIK3CA and TP53, in the BC genomes of the sample set. PIK3CA mutation, c.1173A>G located in exon 9, was identified in 15 patients (46.9%). The TP53 mutations detected were a missense mutation (c.215C>G) in 26 patients (86.70%) and 1 frameshift mutation (c.215_216insG) in 1 patient (3.33%), located within exon 3 and 5, respectively. This study revealed specific mutation profiles for every BC patient, Thus, the results showed that Ion Torrent DNA Sequencing technology may be a possible diagnostic and prognostic method for developing personalized therapy based on the patient's individual BC genome.