scholarly journals Response to FEC Chemotherapy and Oncolytic HSV-1 Is Associated with Macrophage Polarization and Increased Expression of S100A8/A9 in Triple Negative Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5590
Author(s):  
Alyssa Vito ◽  
Nader El-Sayes ◽  
Omar Salem ◽  
Yonghong Wan ◽  
Karen L. Mossman

The era of immunotherapy has seen an insurgence of novel therapies driving oncologic research and the clinical management of the disease. We have previously reported that a combination of chemotherapy (FEC) and oncolytic virotherapy (oHSV-1) can be used to sensitize otherwise non-responsive tumors to immune checkpoint blockade and that tumor-infiltrating B cells are required for the efficacy of our therapeutic regimen in a murine model of triple-negative breast cancer. In the studies herein, we have performed gene expression profiling using microarray analyses and have investigated the differential gene expression between tumors treated with FEC + oHSV-1 versus untreated tumors. In this work, we uncovered a therapeutically driven switch of the myeloid phenotype and a gene signature driving increased tumor cell killing.

2017 ◽  
Vol 114 (52) ◽  
pp. 13792-13797 ◽  
Author(s):  
Mary R. Doherty ◽  
HyeonJoo Cheon ◽  
Damian J. Junk ◽  
Shaveta Vinayak ◽  
Vinay Varadan ◽  
...  

Triple-negative breast cancer (TNBC), the deadliest form of this disease, lacks a targeted therapy. TNBC tumors that fail to respond to chemotherapy are characterized by a repressed IFN/signal transducer and activator of transcription (IFN/STAT) gene signature and are often enriched for cancer stem cells (CSCs). We have found that human mammary epithelial cells that undergo an epithelial-to-mesenchymal transition (EMT) following transformation acquire CSC properties. These mesenchymal/CSCs have a significantly repressed IFN/STAT gene expression signature and an enhanced ability to migrate and form tumor spheres. Treatment with IFN-beta (IFN-β) led to a less aggressive epithelial/non–CSC-like state, with repressed expression of mesenchymal proteins (VIMENTIN, SLUG), reduced migration and tumor sphere formation, and reexpression of CD24 (a surface marker for non-CSCs), concomitant with an epithelium-like morphology. The CSC-like properties were correlated with high levels of unphosphorylated IFN-stimulated gene factor 3 (U-ISGF3), which was previously linked to resistance to DNA damage. Inhibiting the expression of IRF9 (the DNA-binding component of U-ISGF3) reduced the migration of mesenchymal/CSCs. Here we report a positive translational role for IFN-β, as gene expression profiling of patient-derived TNBC tumors demonstrates that an IFN-β metagene signature correlates with improved patient survival, an immune response linked with tumor-infiltrating lymphocytes (TILs), and a repressed CSC metagene signature. Taken together, our findings indicate that repressed IFN signaling in TNBCs with CSC-like properties is due to high levels of U-ISGF3 and that treatment with IFN-β reduces CSC properties, suggesting a therapeutic strategy to treat drug-resistant, highly aggressive TNBC tumors.


Oncotarget ◽  
2019 ◽  
Vol 10 (43) ◽  
pp. 4356-4368 ◽  
Author(s):  
Feng-Mao Lin ◽  
Susan E. Yost ◽  
Wei Wen ◽  
Paul H. Frankel ◽  
Daniel Schmolze ◽  
...  

2019 ◽  
Vol 39 (5) ◽  
Author(s):  
Tianzhi Zheng ◽  
Zhiyuan Pang ◽  
Zhao Zhao

Abstract Triple-negative breast cancer (TNBC) accounts for approximately 15% of all breast cancer cases. TNBC is highly aggressive and associated with poor prognosis. The present study aimed to compare gene expression between TNBC patients with pathological complete response (pCR) and those with not complete response (nCR) to neoadjuvant chemotherapy. Microarray data of 16 TNBC patients received neoadjuvant chemotherapy were identified from the Gene Expression Omnibus database and 10 patients of them had pCR. We found that 250 coding genes and 155 long noncoding RNAs (lncRNAs) were statistically differentially expressed between patients with pCR and nCR. Receiver operator characteristic curve and area under the curve (AUC) were calculated to assess predictive value of differentially expressed genes. A gene signature of three coding genes and two lncRNA was developed: 2.318*TCF3 + 7.349*CREB1 + 0.891*CEP44 + 0.091*NR_023392.1 + 1.424*NR_048561.1 − 106.682. The gene signature was further validated and had an AUC = 0.829. In summary, we profiled gene expression in pCR patients and developed a gene signature, which was effective to predict pCR among TNBC patients received neoadjuvant chemotherapy.


2020 ◽  
Author(s):  
Ana T. Matias ◽  
Ana Jacinta-Fernandes ◽  
Ana-Teresa Maia ◽  
Sofia Braga ◽  
António Jacinto ◽  
...  

AbstractPurposeTriple-negative breast cancer (TNBC) has a higher incidence, a younger age of onset, and a more aggressive behavior in African-ancestry women. Biological disparities have been suggested as an important factor influencing the ancestry-associated TNBC discrepancy. In this study, we sought to identify ancestry-associated differential gene and protein expression between African-ancestry and White TNBC patients, controlling for patients’ menopause status and pathological staging at diagnosis.MethodsDifferential gene expression analyses (DGEA) were performed using RNA-sequencing data from The Cancer Genome Atlas (TCGA). Gene set enrichment analysis (GSEA) and Ingenuity Pathway Analysis (IPA), with focus on network design, were performed to highlight candidate genes for further validation through immunohistochemistry of TNBC samples from patients followed in Portugal.ResultsWith 52 African-American and 90 White TNBC patients included, TCGA’s data corroborate that African-American patients have a higher TNBC incidence (28.42% vs 11.89%, p<0.0001). Particularly, premenopausal and stage II disease African-American patients also have significantly lower survival probability, comparing with White patients (log-rank p=0.019 and 0.0038, respectively). DGEA results suggest that expression profile differences are more associated with TNBC staging than with patient’s menopause status. Hippo pathway and cellular community gene sets are downregulated, while breast cancer gene set is upregulated in African-Americans, comparing with White TNBC patients. Furthermore, MAPK pathway gene set is upregulated when controlling for stage II disease. Due to their central role in highly scored networks resulted from IPA’s network design, EGFR, Myc and Bcl2 genes were selected for further validation through immunohistochemistry. We also included β-Catenin in the validation study as it is consensually reported to be required in TNBC tumorigenesis. Although patients used in the DGEA and in the immunohistochemistry experiments are geographically and culturally distinct, both groups of African-ancestry patients are mostly of western-African ancestry and, interesting, differential gene and protein expression matched.ConclusionsWe found ancestry-associated gene expression patterns between African-ancestry and White TNBCs, particularly when controlling for menopause status or staging. EGFR, Myc, Bcl2 and β-catenin gene and protein differential expression matching results in distinct populations suggest these markers as being important indicators of TNBC’s ancestry-associated development.


2021 ◽  
Author(s):  
Yunfei Ye ◽  
Jungang Ma ◽  
Qin Zhang ◽  
Kai Xiong ◽  
Zhimin Zhang ◽  
...  

Abstract Purpose This study aimed to develop and validate a prognostic model for metastasis-free survival (MFS) based on genes that may functionally interact with cytotoxic T lymphocytes (CTLs) and M2 macrophages in patients with triple-negative breast cancer (TNBC) who underwent adjuvant radiotherapy.Methods The transcriptional profiles and phenotypical files of TNBC and other subtypes of breast cancer were downloaded from the Gene Expression Omnibus (GEO). The abundance of infiltrated immune cells was evaluated through CIBERSORTx or MCP-counter. A weighted linear model, the score for MFS (SMFS), was developed by using least absolute shrinkage and selection operator (LASSO) in GSE58812 and validated in GSE2034 and GSE12276. The biological implication of SMFS was explored by evaluating its associations with TNBC molecular subtypes and other radiosensitivity- or immune-related signatures. Results A model consisting of the gene expression ratios of PCDH12/ELP3, PCDH12/MSRA and FAM160B2/MSRA with nonzero coefficients finally selected by LASSO was developed in GSE58812. In GSE2034 (treatment with adjuvant radiotherapy), SMFS was significantly associated with MFS in TNBC patients (HR=8.767, 95% CI: 1.856-41.408, P=0.006) and, to a lesser extent, in non-TNBC patients (HR=2.888, 95% CI: 1.076-7.750, P=0.035). However, the interaction of subtype (TNBC vs non-TNBC) and SMFS tended to be significant (Pinteraction=0.081). In contrast, SMFS was not significantly associated with MFS in either TNBC patients (P=0.499) or non-TNBC patients (P=0.536) in GSE12276 (treatment without radiotherapy). Among the four TNBC molecular subtypes, the c1 and c4 subtypes exhibited higher CTL infiltration and lower SMFS values than the c2 and c3 subtypes. In addition, SMFS was positively correlated with the abundance of endothelial cells (r=0.413, P<0.001).Conclusions The proposed model has the potential to predict MFS in TNBC patients after adjuvant radiotherapy. SMFS may represent a measurement of tumor immune suppression.


Author(s):  
Sung Gwe Ahn ◽  
Seon-Kyu Kim ◽  
Jonathan H. Shepherd ◽  
Yoon Jin Cha ◽  
Soong June Bae ◽  
...  

Abstract Purpose The SP142 PD-L1 assay is a companion diagnostic for atezolizumab in metastatic triple-negative breast cancer (TNBC). We strove to understand the biological, genomic, and clinical characteristics associated with SP142 PD-L1 positivity in TNBC patients. Methods Using 149 TNBC formalin-fixed paraffin-embedded tumor samples, tissue microarray (TMA) and gene expression microarrays were performed in parallel. The VENTANA SP142 assay was used to identify PD-L1 expression from TMA slides. We next generated a gene signature reflective of SP142 status and evaluated signature distribution according to TNBCtype and PAM50 subtypes. A SP142 gene expression signature was identified and was biologically and clinically evaluated on the TNBCs of TCGA, other cohorts, and on other malignancies treated with immune checkpoint inhibitors (ICI). Results Using SP142, 28.9% of samples were PD-L1 protein positive. The SP142 PD-L1-positive TNBC had higher CD8+ T cell percentage, stromal tumor-infiltrating lymphocyte levels, and higher rate of the immunomodulatory TNBCtype compared to PD-L1-negative samples. The recurrence-free survival was prolonged in PD-L1-positive TNBC. The SP142-guided gene expression signature consisted of 94 immune-related genes. The SP142 signature was associated with a higher pathologic complete response rate and better survival in multiple TNBC cohorts. In the TNBC of TCGA, this signature was correlated with lymphocyte-infiltrating signature scores, but not with tumor mutational burden or total neoantigen count. In other malignancies treated with ICIs, the SP142 genomic signature was associated with improved response and survival. Conclusions We provide multi-faceted evidence that SP142 PDL1-positive TNBC have immuno-genomic features characterized as highly lymphocyte-infiltrated and a relatively favorable survival.


2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Erica M. Stringer-Reasor ◽  
Jori E. May ◽  
Eva Olariu ◽  
Valerie Caterinicchia ◽  
Yufeng Li ◽  
...  

Abstract Background Poly (ADP-ribose)-polymerase inhibitors (PARPi) have been approved for cancer patients with germline BRCA1/2 (gBRCA1/2) mutations, and efforts to expand the utility of PARPi beyond BRCA1/2 are ongoing. In preclinical models of triple-negative breast cancer (TNBC) with intact DNA repair, we have previously shown an induced synthetic lethality with combined EGFR inhibition and PARPi. Here, we report the safety and clinical activity of lapatinib and veliparib in patients with metastatic TNBC. Methods A first-in-human, pilot study of lapatinib and veliparib was conducted in metastatic TNBC (NCT02158507). The primary endpoint was safety and tolerability. Secondary endpoints were objective response rates and pharmacokinetic evaluation. Gene expression analysis of pre-treatment tumor biopsies was performed. Key eligibility included TNBC patients with measurable disease and prior anthracycline-based and taxane chemotherapy. Patients with gBRCA1/2 mutations were excluded. Results Twenty patients were enrolled, of which 17 were evaluable for response. The median number of prior therapies in the metastatic setting was 1 (range 0–2). Fifty percent of patients were Caucasian, 45% African–American, and 5% Hispanic. Of evaluable patients, 4 demonstrated a partial response and 2 had stable disease. There were no dose-limiting toxicities. Most AEs were limited to grade 1 or 2 and no drug–drug interactions noted. Exploratory gene expression analysis suggested baseline DNA repair pathway score was lower and baseline immunogenicity was higher in the responders compared to non-responders. Conclusions Lapatinib plus veliparib therapy has a manageable safety profile and promising antitumor activity in advanced TNBC. Further investigation of dual therapy with EGFR inhibition and PARP inhibition is needed. Trial registration ClinicalTrials.gov, NCT02158507. Registered on 12 September 2014


2021 ◽  
Vol 22 (4) ◽  
pp. 1820
Author(s):  
Anna Makuch-Kocka ◽  
Janusz Kocki ◽  
Anna Brzozowska ◽  
Jacek Bogucki ◽  
Przemysław Kołodziej ◽  
...  

The BIRC (baculoviral IAP repeat-containing; BIRC) family genes encode for Inhibitor of Apoptosis (IAP) proteins. The dysregulation of the expression levels of the genes in question in cancer tissue as compared to normal tissue suggests that the apoptosis process in cancer cells was disturbed, which may be associated with the development and chemoresistance of triple negative breast cancer (TNBC). In our study, we determined the expression level of eight genes from the BIRC family using the Real-Time PCR method in patients with TNBC and compared the obtained results with clinical data. Additionally, using bioinformatics tools (Ualcan and The Breast Cancer Gene-Expression Miner v4.5 (bc-GenExMiner v4.5)), we compared our data with the data in the Cancer Genome Atlas (TCGA) database. We observed diverse expression pattern among the studied genes in breast cancer tissue. Comparing the expression level of the studied genes with the clinical data, we found that in patients diagnosed with breast cancer under the age of 50, the expression levels of all studied genes were higher compared to patients diagnosed after the age of 50. We observed that in patients with invasion of neoplastic cells into lymphatic vessels and fat tissue, the expression levels of BIRC family genes were lower compared to patients in whom these features were not noted. Statistically significant differences in gene expression were also noted in patients classified into three groups depending on the basis of the Scarff-Bloom and Richardson (SBR) Grading System.


2021 ◽  
Vol 11 (2) ◽  
pp. 61
Author(s):  
Jiande Wu ◽  
Chindo Hicks

Background: Breast cancer is a heterogeneous disease defined by molecular types and subtypes. Advances in genomic research have enabled use of precision medicine in clinical management of breast cancer. A critical unmet medical need is distinguishing triple negative breast cancer, the most aggressive and lethal form of breast cancer, from non-triple negative breast cancer. Here we propose use of a machine learning (ML) approach for classification of triple negative breast cancer and non-triple negative breast cancer patients using gene expression data. Methods: We performed analysis of RNA-Sequence data from 110 triple negative and 992 non-triple negative breast cancer tumor samples from The Cancer Genome Atlas to select the features (genes) used in the development and validation of the classification models. We evaluated four different classification models including Support Vector Machines, K-nearest neighbor, Naïve Bayes and Decision tree using features selected at different threshold levels to train the models for classifying the two types of breast cancer. For performance evaluation and validation, the proposed methods were applied to independent gene expression datasets. Results: Among the four ML algorithms evaluated, the Support Vector Machine algorithm was able to classify breast cancer more accurately into triple negative and non-triple negative breast cancer and had less misclassification errors than the other three algorithms evaluated. Conclusions: The prediction results show that ML algorithms are efficient and can be used for classification of breast cancer into triple negative and non-triple negative breast cancer types.


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