Differences in somatic TP53 mutation type in breast tumors by race and receptor status

Outcomes of De Novo Oligometastatic Breast Cancer Treated With Surgery of Primary and Metastasis Directed Radiotherapy

OBJECTIVES

With sensitive imaging for breast cancer, the question arises whether present-day oncologists treat dOMBC with palliative systemic therapy (ST), which, a few years earlier, would have been treated with curative intent. We retrospectively analyzed outcomes of dOMBC treated with curative intent using a combination of surgery, metastasis-directed radiotherapy (RT), and adjuvant/neoadjuvant ST and have also explored the possible role of total lesional glycolysis of metastases and p53 immunohistochemistry in predicting outcomes.

METHODS

Data were collected from a prospectively maintained database using electronic medical records and Radiation Oncology Information System. In the study, dOMBC was defined as up to 3 metastatic sites, all amenable to treatment with ablative RT and primary and axillary disease amenable to curative surgery. Patients were treated with surgery, ST, and RT.

RESULTS

Patients underwent either breast conservation surgery or modified radical mastectomy. Patients were treated with 6 to 8 cycles of chemotherapy in the neoadjuvant and/or adjuvant setting. Hormone receptor-positive patients received either tamoxifen or aromatase inhibitors. Trastuzumab was offered to Her-2-neu receptor-positive patients. RT included locoregional RT and metastases-directed ablative body RT. The median progression-free survival was 39 months (95% CI: -28.7 to 50.1 mo). Two and 3 year estimated disease-free survival (DFS) was 79% and 60.5%, respectively. The median overall survival was not reached. The estimated 3-year overall survival was 87.3%. Total lesional glycolysis of metastases score and p53 status did not affect DFS.

CONCLUSION

Combination treatment of surgery, metastases-directed ablative RT, and ST may provide prolonged DFS in dOMBC.

Association of ESR1 Germline Variants with TP53 Somatic Variants in Breast Tumors in a Genome-wide Study

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency.

SIGNIFICANCE

Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences.

ASAH1 facilitates TNBC by DUSP5 suppression-driven activation of MAP kinase pathway and represents a therapeutic vulnerability

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that is prone to metastasis and therapy resistance. Owing to its aggressive nature and limited availability of targeted therapies, TNBC is associated with higher mortality as compared to other forms of breast cancer. In order to develop new therapeutic options for TNBC, we characterized the factors involved in TNBC growth and progression. Here, we demonstrate that N-acylsphingosine amidohydrolase 1 (ASAH1) is overexpressed in TNBC cells and is regulated via p53 and PI3K-AKT signaling pathways. Genetic knockdown or pharmacological inhibition of ASAH1 suppresses TNBC growth and progression. Mechanistically, ASAH1 inhibition stimulates dual-specificity phosphatase 5 (DUSP5) expression, suppressing the mitogen-activated protein kinase (MAPK) pathway. Furthermore, pharmacological cotargeting of the ASAH1 and MAPK pathways inhibits TNBC growth. Collectively, we unmasked a novel role of ASAH1 in driving TNBC and identified dual targeting of the ASAH1 and MAPK pathways as a potential new therapeutic approach for TNBC treatment.

A ten long noncoding RNA-based prognostic risk model construction and mechanism study in the basal-like immune-suppressed subtype of triple-negative breast cancer

Background

According to the Fudan University Shanghai Cancer Center (FUSCC) system, triple-negative breast cancer (TNBC) is divided into four stable subtypes: (I) luminal androgen receptor, (II) immunomodulatory, (III) basal-like immune-suppressed (BLIS), and (IV) mesenchymal-like. However, the treatment outcomes of the corresponding targeted therapies are unsatisfactory, especially for the BLIS subtype. Therefore, we aimed to identify the key long noncoding RNAs (lncRNAs) to construct a prognostic model for BLIS subtype and discover potential targets to explore potential therapeutic strategies in this study.

Methods

The FUSCC cohort was used to establish a prognostic risk model via least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The Cancer Genome Atlas (TCGA) cohort was then used to evaluate and verify the model. To understand the functional aspects of the model, functional, immune landscape, mutation, and drug sensitivity analyses were performed between high- and low-risk groups.

Results

Ten prognostic-related lncRNAs identified, including C5ORF66-AS2, DIO3OS, FZD10-DT, LINC00393, LNC-ERI1-32, LNC-FOXO1-2, LNC-SPARCL1-1, HCG23, LNC-MMD-4 and LNC-TMEM106C-6, were selected for risk score system construction. The results showed that the model constructed could divide the patients with BLIS subtype into two groups of high and low risk, and patients with higher risk scores had shorter recurrence-free survival. In addition, drug sensitivity analysis identified 3 compounds, including BMS-754807, cytochalasin b, and linifanib, that could have a potential therapeutic effect on patients with the BLIS subtype.

Conclusions

The risk prognosis model showed good prognostic value for the BLIS subtype patients, and the ten lncRNAs may be potential therapeutic targets.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study

Background

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

Methods

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

Results

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

Conclusions

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

The heterogeneous impact of targeted therapy on the prognosis of stage III/IV colorectal cancer patients with different subtypes of TP53 mutations

BACKGROUND

The relationship between molecular characteristics and the prognosis of colorectal cancer (CRC) patients has not been fully understood. This study explored the impact of targeted therapy on the prognosis of CRC patients with different TP53 mutations, in the context of comprehensive treatment.

METHODS

This study included patients with stage III/IV primary CRC from the electronic medical record system. TP53 mutations were detected via next-generation sequencing (NGS) using formalin-fixed paraffin-embedded (FFPE) tissues. Applying two methods, we classified TP53 mutations as gain of function (GOF)/non-GOF mutations or known/likely loss of function (LOF) mutations. Kaplan-Meier plot and parametric survival analysis were performed to evaluate the prognosis of CRC patients and identify potential predictors.

RESULTS

There were 286 patients included, of which 166 (58.04%) patients received targeted therapy and 120 (41.96%) did not. There were 286 patients in the TP53 GOF classification set and 247 in the TP53 LOF classification set. Parametric survival analysis, adjusted for sex, onset, KRAS mutation, sidedness, stage, and surgery, showed that receiving targeted therapy predicted better overall survival (OS) among patients who harbored TP53 GOF mutations (HR 0.40, 95% confidence interval (CI) [0.21, 0.76], p = 0.005) or known LOF mutations (HR 0.21, 95% CI [0.07, 0.60], p = 0.002). However, there was no significant impact of receiving targeted therapy on OS among patients harboring TP53 non-GOF mutations (HR 1.68, 95% CI [0.50, 5.63], p = 0.403) or likely LOF mutations (HR 0.90, 95% CI [0.34, 2.39], p = 0.837).

CONCLUSIONS

Receiving targeted therapy had a heterogeneous impact on the prognosis of CRC patients harboring different TP53 mutations. These results provide promising value for future personalized treatment and precision medicine.

A novel immune checkpoint-related signature for prognosis and immune analysis in breast cancer

Breast cancer is one of the most prevailing forms of cancer globally. Immunotherapy has demonstrated efficacy in improving the overall survival of breast cancer. The aim of us was to formulate a novel signature predicated on immune checkpoint-related genes (ICGs) that could anticipate the prognosis and further analyze the immune status of patients with breast cancer. After acquiring data, we pinpointed the definitive ICGs for constructing the prognostic model of breast cancer. We constructed a novel prognostic model and created a fresh risk score called Immune Checkpoint-related Risk Score in breast cancer (ICRSBC). The nomogram was constructed to evaluate the accuracy of the model, and the new web-based tool was created to be more intuitive for predicting prognosis. We also investigated immunotherapy responsiveness and analyzed the tumor mutational burden (TMB) in ICRSBC subgroups. The ICRSBC was found to have significant correlations with the immune environment, immunotherapy responsiveness, and TMB. The expression levels of the 9 ICGs that construct the prognostic model and their promoter methylation levels are significantly different between breast cancer and normal tissues. Furthermore, the mutation profiles, the copy number alterations, and the levels of protein expression also exhibit marked disparities among the 9 ICGs. We have identified and validated a novel signature related to ICGs that is strongly associated with breast cancer progression. This signature enables us to create a risk score for prognosticating the survival and assessing the immune status of individuals affected by breast cancer.

Mutational Landscape and In-Silico Analysis of TP53, PIK3CA, and PTEN in Patients with Breast Cancer from Khyber Pakhtunkhwa

Herein, we report the mutational spectrum of three breast cancer candidate genes (TP53, PIK3CA, and PTEN) using WES for identifying potential biomarkers. The WES data were thoroughly analyzed using SAMtools for variant calling and identification of the mutations. Various bioinformatic tools (SIFT, PolyPhen-2, Mutation Taster, ISPRED-SEQ, SAAFEQ-SEQ, ConSurf, PROCHECK etc.) were used to determine the pathogenicity and nature of the SNVs. Selected interaction site (IS) mutations were visualized in PyMOL after building 3D structures in Swiss-Model. Ramachandran plots were generated by using the PROCHECK server. The selected IS mutations were subjected to molecular dynamic simulation (MDS) studies using Gromacs 4.5. STRING and GeneMANIA were used for the prediction of gene-gene interactions and pathways. Our results revealed that the luminal A molecular subtype of the breast cancer was most common, whereas a high percentage of was Her2 negatives. Moreover, the somatic mutations were more common as compared to the germline mutations in TP53, PIK3CA, and PTEN. 20% of the identified mutations are reported for the first time from Khyber Pakhtunkhwa. In the enrolled cohort, 23 mutations were nonsynonymous SNVs. The frequency of mutations was the highest in PIK3CA, followed by TP53 and PTEN. A total of 13 mutations were found to be highly pathogenic. Four novel mutations were identified on PIK3CA and one each on PTEN and TP53. SAAFEQ-SEQ predicted the destabilizing effect for all mutations. ISPRED-SEQ predicted 9 IS mutations (6 on TP53 and 3 on PIK3CA), whereas no IS mutation was predicted on PTEN. The TP53 IS mutations were TP53R43H, TP53Y73X, TP53K93Q, TP53K93R, TP53D149E, and TP53Q199X; whereas for PIK3CA, the IS mutations were PIK3CAL156V, PIK3CAM610K, and PIK3CAH1047R. Analysis from the ConSurf Web server revealed five SNVs with a highly conserved status (conservation score 9) across TP53 and PTEN. TP53P33R was found predominant in the grade 3 tumors, whereas PTENp.C65S was distributed on ER+, ER-, PR+, PR-, Her2+, and Her2- patients. TP53p.P33R mutation was found to be recurring in the 14/19 (73.6%) patients and, therefore, can be considered as a potential biomarker. Finally, these mutations were studied in the context of their potential association with different hormonal and social factors.

Prevalence of TP53 gene Pro72Arg (rs1042522) single nucleotide polymorphism among Egyptian breast cancer patients

Background

The P53 protein has an essential role in several cellular processes, including DNA repair, apoptosis, and cell cycle arrest. The pathophysiology of many cancer types has frequently been linked to polymorphisms in the TP53 locus. Over 200 single nucleotide polymorphisms (SNPs) have been identified in TP53. However, Pro72Arg (rs1042522) at codon 72, shows contradictory results in terms of cancer risk. In this study, we aimed to determine if the Pro72Arg (rs1042522) SNP in the TP53 gene would be linked to breast cancer (BC) risk among Egyptian patients.

Materials and Methods

Genomic DNA was extracted from blood samples of 100 healthy volunteers and 100 breast cancer patients (50 familial and 50 non-familial). TP53 Genotyping was performed using tetra-primer amplification refractory mutation (Tetra-ARMS) PCR. Data were analyzed using SNPstat software.

Results

The prevalence of TP53 (Pro72Arg) rs1042522 genotypes carrying the high-risk allele [Pro/Arg (CG) and Arg/Arg (GG)] were significantly higher in BC patients compared to healthy volunteers and were associated with BC susceptibility (OR 0.2; [95% CI 0.11–0.38]; P = 0.0001). However, there was no statistical significant difference in the prevalence of TP53 (Pro72Arg) rs1042522 genotypes carrying the high-risk allele between familial and non-familial BC patients. In addition, there was no association between the prevalence of TP53 (Pro72Arg) rs1042522 genotypes carrying the high-risk allele and BC patients’ clinical and pathological characteristics including tumor size, tumor grade, lymph node status, presence of lymphovascular invasion, expression of ER, PR and Her-2 in both of familial and non-familial BC patients.

Conclusions

TP53 (Pro72Arg) rs1042522 is more prevalent among BC patients but not associated with disease progression.

Schlafen 12 Slows TNBC Tumor Growth, Induces Luminal Markers, and Predicts Favorable Survival

The Schlafen 12 (SLFN12) protein regulates triple-negative breast cancer (TNBC) growth, differentiation, and proliferation. SLFN12 mRNA expression strongly correlates with TNBC patient survival. We sought to explore SLFN12 overexpression effects on in vivo human TNBC tumor xenograft growth and performed RNA-seq on xenografts to investigate related SLFN12 pathways. Stable SLFN12 overexpression reduced tumorigenesis, increased tumor latency, and reduced tumor volume. RNA-seq showed that SLFN12 overexpressing xenografts had higher luminal markers levels, suggesting that TNBC cells switched from an undifferentiated basal phenotype to a more differentiated, less aggressive luminal phenotype. SLFN12-overexpressing xenografts increased less aggressive BC markers, HER2 receptors ERBB2 and EGFR expression, which are not detectable by immunostaining in TNBC. Two cancer progression pathways, the NAD signaling pathway and the superpathway of cholesterol biosynthesis, were downregulated with SLFN12 overexpression. RNA-seq identified gene signatures associated with SLFN12 overexpression. Higher gene signature levels indicated good survival when tested on four independent BC datasets. These signatures behaved differently in African Americans than in Caucasian Americans, indicating a possible biological difference between these races that could contribute to the worse survival observed in African Americans with BC. These results suggest an increased SLFN12 expression modulates TNBC aggressiveness through a gene signature that could offer new treatment targets.