Biomarker potential of the LEF1/TCF family members in breast cancer: Bioinformatic investigation on expression and clinical significance.

The LEF1/TCF transcription factor family is related to the development of diverse tissue types, including the mammary tissue, and dysregulation of its expression and function has been described to favor breast tumorigenesis. However, the clinical and biological relevance of this gene family in breast cancer is still poorly understood. Here, we used bioinformatics approaches aiming to reduce this gap. We investigated its expression patterns in molecular and immune breast cancer subtypes; its correlation with immune cell infiltration, and its prognostic values in predicting outcomes. Also, through regulons construction, we determined the genes whose expression is influenced by these transcription factors, and the pathways in which they are involved. We found that LEF1 and TCF3 are over-expressed in breast tumors regarding non-tumor samples, while TCF4 and TCF7 are down-expressed, with the gene's methylation status being associated with its expression dysregulation. All four transcription factors presented significance at the diagnostic and prognostic levels. LEF1, TCF4, and TCF7 presented a significant correlation with immune cell infiltration, being associated with the immune subtypes of less favorable outcomes. Altogether, this research contributes to a more accurate understanding of the expression and clinical and biomarker significance of the LEF1/TCF transcription factors in breast cancer.

So alike yet so different. Differential expression of the long non-coding RNAs NORAD and HCG11 in breast cancer subtypes.

Breast cancer (BC) is a heterogeneous disease, and it is the leading cause of death among women. NORAD and HCG11 are highly similar lncRNAs that present binding sites for PUMILIO proteins. PUMILIO acts on hundreds of mRNA targets, contributing to the modulation of gene expression. We analyzed the expression levels of NORAD and HCG11 in the BC subtypes luminal A (LA) and basal-like (BL), and the regulatory networks associated with these lncRNAs. In the analysis of TCGA cohort (n=329) and Brazilian BC samples (n=44), NORAD was up-regulated in LA while HCG11 was up-regulated in BL subtype. An increased expression of NORAD is associated with reduced disease-free survival in basal-like patients (p = 0.002), which suggests that its prognostic value could be different in specific subtypes. The biological pathways observed for the HCG11 network are linked to the epithelial-to-mesenchymal transition; while NORAD associated pathways appear to be related to luminal epithelial cell transformation. NORAD and HCG11 regulons respectively present 36% and 21.5% of PUMILIO targets, which suggests that these lncRNAs act as a decoy for PUMILIO. These lncRNAs seem to work as players in the differentiation process that drives breast cells to acquire distinct phenotypes related to a specific BC subtype.

Integrated analysis of label-free quantitative proteomics and bioinformatics reveal insights into signaling pathways in male breast cancer.

Male breast cancer (MBC) is a rare malignancy that accounts for about 1.8% of all breast cancer cases. In contrast to the high number of the "omics" studies in breast cancer in women, only recently molecular approaches have been performed in MBC research. High-throughput proteomics based methodologies are promisor strategies to characterize the MBC proteomic signatures and their association with clinico-pathological parameters. In this study, the label-free quantification-mass spectrometry and bioinformatics approaches were applied to analyze the proteomic profiling of a MBC case using the primary breast tumor and the corresponding axillary metastatic lymph nodes and adjacent non-tumor breast tissues. The differentially expressed proteins were identified in the signaling pathways of granzyme B, sirtuins, eIF2, actin cytoskeleton, eNOS, acute phase response and calcium and were connected to the upstream regulators MYC, PI3K SMARCA4 and cancer-related chemical drugs. An additional proteomic comparative analysis was performed with a primary breast tumor of a female patient and revealed an interesting set of proteins, which were mainly involved in cancer biology. Together, our data provide a relevant data source for the MBC research that can help the therapeutic strategies for its management.

COVID-19: The question of genetic diversity and therapeutic intervention approaches.

Coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), is the largest pandemic in modern history with very high infection rates and considerable mortality. The disease, which emerged in China's Wuhan province, had its first reported case on December 29, 2019, and spread rapidly worldwide. On March 11, 2020, the World Health Organization (WHO) declared the COVID-19 outbreak a pandemic and global health emergency. Since the outbreak, efforts to develop COVID-19 vaccines, engineer new drugs, and evaluate existing ones for drug repurposing have been intensively undertaken to find ways to control this pandemic. COVID-19 therapeutic strategies aim to impair molecular pathways involved in the virus entrance and replication or interfere in the patients' overreaction and immunopathology. Moreover, nanotechnology could be an approach to boost the activity of new drugs. Several COVID-19 vaccine candidates have received emergency-use or full authorization in one or more countries, and others are being developed and tested. This review assesses the different strategies currently proposed to control COVID-19 and the issues or limitations imposed on some approaches by the human and viral genetic variability.

A genetic variant in microRNA-146a is associated with sporadic breast cancer in a Southern Brazilian Population.

MicroRNAs (miRNAs) play an essential role in gene expression and affect the development of tumours, including breast cancer (BC). Polymorphisms in miRNA genes can affect the interaction of miRNAs with their target messenger RNA by interfering, creating or disrupting target sites. The single nucleotide polymorphism (SNP) rs2910164, located in the seed region of miR146a, was shown to be associated with BC among different populations. In the present study, we investigated whether rs2910164 is associated with BC in 326 patients and 411 controls from a Brazilian population of predominantly European ancestry. The presence of the allele rs2910164*C was associated with an increased risk of BC (OR=1.4, 95% CI=1.03-1.85, p = 0.03). We also analysed publicly available RNA-seq data to evaluate if miR146a is differentially expressed in different subtypes of BC. Genotyping was performed by polymerase chain reaction with sequence-specific primers (PCR-SSP). By leveraging public data from TCGA database, we analysed 461 patients and found that miR146a is significantly more expressed in BC than in non-tumor tissue (1.47 fold, p = 0.02) and is expressed to a greater degree in aggressive BC subtypes.

Association of FOSL1 copy number alteration and triple negative breast tumors.

Copy number alterations (CNAs) are a frequent feature in human breast cancer, and one of the hallmarks of genomic instability. The FOSL1, GSTP1 and CCND1 genes are located at 11q13, a cytoband commonly affected by CNA in breast cancer, with relevant function in progression and invasion. Our main goal was to analyze CNAs of these genes and determine their association with breast cancer subtypes. Seventy-three cases of invasive breast tumors [52 Luminal, 7 HER2+ and 14 triple negative (TNBC) subtypes] were analyzed by TaqMan assays. CNAs were observed for all genes, with gains more frequently observed. Gains of the FOSL1 gene were observed in 71% of the cases. This gene was the only one with a statistically significant difference (p<0.001) among tumor subtypes, with increased copy number in TNBC compared to luminal and HER2+. No significant association of CNA and clinical and histopathological parameters from the patients was observed. Additional studies in larger breast cancer patient cohorts based on more refined molecular subtypes are necessary to confirm the observed association of FOSL1 gain with aggressive breast tumors phenotypes.

Stress-induced phosphoprotein 1: how does this co-chaperone influence the metastasis steps?

In several cancer types, metastasis is associated with poor prognosis, survival, and quality of life, representing a life risk more significant than the primary tumor itself. Metastasis is a multi-step process that spreads tumor cells from primary sites to surrounding or distant organs, originating secondary tumors. The interconnected steps that drive metastasis depend of several capabilities that enable cells to detach from the primary tumor, acquire motility and migrate through the basal membrane; invade and spread through the vascular system, and finally settle and originate a new tumor. Recently, stress-induced phosphoprotein 1 (STIP1) has emerged as a protein capable of driving tumor cells through these metastasis steps by mediating several biological processes and signaling pathways. This protein is mainly known for its function as a co-chaperone, acting as a scaffold for the interaction of its client heat-shock proteins Hsp70/90 chaperones; however, it is also known that STIP1 can act independently of chaperones to activate downstream phosphorylation pathways. The over-expression of STIP1 has been reported across various cancer types, identifying it as a potential biomarker for predicting patient prognosis and monitoring the progression of metastasis. Here, we present a discussion on how this co-chaperone mediates the initial steps of metastasis (cell adhesion loss, epithelial-to-mesenchymal transition, and angiogenesis), highlighting the biological mechanisms in which STIP1 plays a vital role, also presenting an overview of the current knowledge regarding its clinical relevance.

Lnc-uc.147 Is Associated with Disease Stage of Liver, Gastric, and Renal Cancer.

Lnc-uc.147, a long non-coding RNA derived from a transcribed ultraconserved region (T-UCR), was previously evidenced in breast cancer. However, the role of this region in other tumor types was not previously investigated. The present study aimed to investigate lnc-uc.147 in different types of cancer, as well as to suggest lnc-uc.147 functional and regulation aspects. From solid tumor datasets analysis of The Cancer Genome Atlas (TCGA), deregulated lnc-uc.147 expression was associated with the histologic grade of hepatocellular carcinoma, and with the tumor stage of clear cell renal and gastric adenocarcinoma. Considering the epidemiologic relevance of liver cancer, silencing lnc-uc.147 reduced the viability and clonogenic capacity of HepG2 cell lines. Additionally, we suggest a relation between the transcription factor TEAD4 and lnc-uc.147 in liver and breast cancer cells.

High-throughput proteomics of breast cancer subtypes: Biological characterization and multiple candidate biomarker panels to patients' stratification.

BACKGROUND AND AIMS: The actual classification of breast tumors in subtypes represents an attempt to stratify patients into clinically cohesive groups, nevertheless, clinicians still lack reproducible and reliable protein biomarkers for breast cancer subtype discrimination. In this study, we aimed to access the differentially expressed proteins between these tumors and its biological implications, contributing to the subtype's biological and clinical characterization, and with protein panels for subtype discrimination. METHODS: In our study, we applied high-throughput mass spectrometry, bioinformatic, and machine learning approaches to investigate the proteome of different breast cancer subtypes. RESULTS: We identified that each subtype depends on different protein expression patterns to sustain its malignancy, and also alterations in pathways and processes that can be associated with each subtype and its biological and clinical behaviors. Regarding subtype biomarkers, our panels achieved performances with at least 75% of sensibility and 92% of specificity. In the validation cohort, the panels obtained acceptable to outstanding performances (AUC = 0.740 to 1.00). CONCLUSIONS: In general, our results expand the accuracy of breast cancer subtypes' proteomic landscape and improve the understanding of its biological heterogeneity. In addition, we identified potential protein biomarkers for the stratification of breast cancer patients, improving the repertoire of reliable protein biomarkers. SIGNIFICANCE: Breast cancer is the most diagnosed cancer type worldwide and the most lethal cancer in women. As a heterogeneous disease, breast cancer tumors can be classified into four major subtypes, each presenting particular molecular alterations, clinical behaviors, and treatment responses. Thus, a pivotal step in patient management and clinical decisions is accurately classifying breast tumor subtypes. Currently, this classification is made by the immunohistochemical detection of four classical markers (estrogen receptor, progesterone receptor, HER2 receptor, and the Ki-67 index); however, it is known that these markers alone do not fully discriminate the breast tumor subtypes. Also, the poor understanding of the molecular alterations of each subtype leads to a challenging decision-making process regarding treatment choice and prognostic determination. This study, through high-throughput label-free mass-spectrometry data acquisition and downstream bioinformatic analysis, advances in the proteomic discrimination of breast tumors and achieves an in-depth characterization of the subtype's proteomes. Here, we indicate how the variations in the subtype's proteome can influence the tumor's biological and clinical differences, highlighting the variation in the expression pattern of oncoproteins and tumor suppressor proteins between subtypes. Also, through our machine-learning approach, we propose multi-protein panels with the potential to discriminate the breast cancer subtypes. Our panels achieved high classification performance in our cohort and in the independent validation cohort, demonstrating their potential to improve the current tumor discrimination system as complements to the classical immunohistochemical classification.

PD-1/PD-L1 Inhibitors Response in Triple-Negative Breast Cancer: Can Long Noncoding RNAs Be Associated?

As immune checkpoint inhibitors (ICI) emerge as a paradigm-shifting treatment option for patients with advanced or metastatic cancer, there is a growing demand for biomarkers that can distinguish which patients are likely to benefit. In the case of triple-negative breast cancer (TNBC), characterized by a lack of therapeutic targets, pembrolizumab approval for high-risk early-stage disease occurred regardless of PD-L1 status, which keeps the condition in a biomarker limbus. In this review, we highlight the participation of long non-coding RNAs (lncRNAs) in the regulation of the PD-1/PD-L1 pathway, as well as in the definition of prognostic immune-related signatures in many types of tumors, aiming to shed light on molecules that deserve further investigation for a potential role as biomarkers. We also conducted a bioinformatic analysis to investigate lncRNAs already investigated in PD-1/PDL-1 pathways in other cancer types, considering the TNBC molecular context. In this sense, from the generated data, we evidence here two lncRNAs, UCA1 and HCP5, which have not yet been identified in the context of the tumoral immune response in breast cancer. These candidates can be further explored to verify their use as biomarkers for ICI response. In this article, we present an updated review regarding the use of lncRNA as biomarkers of response to ICI, highlighting the versatility of using these molecules.

The Potential of NORAD-PUMILIO-RALGAPB Regulatory Axis as a Biomarker in Breast Cancer.

Introduction: Long non-coding RNAs (LncRNA) represent a heterogeneous family of RNAs that have emerged as regulators of various biological processes through their association with proteins in ribonucleoproteins complexes. The dynamic of these interactions can affect cell metabolism, including cancer development. Annually, breast cancer causes thousands of deaths worldwide, and searching for new biomarkers is pivotal for better diagnosis and treatment. Methods: Based on in silico prediction analysis, we focus on LncRNAs that have binding sites for PUMILIO, an RBP family involved in post-transcriptional regulation and associated with cancer progression. We compared the expression levels of these LncRNAs in breast cancer and non-tumor samples from the TCGA database. We analyzed the impact of overall and disease-free survival associated with the expression of the LncRNAs and co-expressed genes and targets of PUMILIO proteins. Results: Our results found NORAD as the most relevant LncRNA with a PUMILIO binding site in breast cancer, differently expressed between Luminal A and Basal subtypes. Additionally, NORAD was co-expressed in a Basal-like subtype (0.55) with the RALGAPB gene, a target gene of PUMILIO related to chromosome stability during cell division. Conclusion: These data suggest that this molecular axis may provide insights for developing novel therapeutic strategies for breast cancer.

Comprehensive analysis of the large and small ribosomal proteins in breast cancer: Insights on proteomic and transcriptomic expression patterns, regulation, mutational landscape, and prognostic significance.

Several evidence has demonstrated the involvement of the ribosomal proteins (RPs) in many malignancies, however, the function and clinical relevance of the RPs in breast cancer remains unclear. The present study aims to contribute to the understanding of the role of the RPs in breast tumorigenesis and its clinical implications in the field of biomarker discovery and outcome prediction. We investigated the proteomic and transcriptomic expression of the RPs in non-tumor and tumor tissues of different breast cancer subtypes, and integrated bioinformatics approaches and online databases to comprehensively evaluate the potential functions, regulatory networks, mutational landscape, and prognostic values of the ribosomal proteins in breast cancer. Our results show that 33 RPs have deregulated expression in breast cancer and its subtypes and that 26 RPs have potential as prognostic markers in a subtype-dependent way, with mutations in RP genes being frequent in breast tumors and related to overall survival and relapse-free status. Our RP gene regulatory network indicates the transcription factors MYC, ETS1, and SPI1, and the miRNAs has-let-7c-5p, has-mir-20b-5p, and has-mir-4668-3p as regulators of the RPs expression in breast cancer. The RPs were associated with several clinicopathological parameters of breast cancer and predicted to be involved in ribosomal-independent mechanisms such as regulation of the SLITS-ROBO pathway. This study comprehensively investigated the ribosomal proteins in breast cancer, suggesting that the RPs have clinical potential as biomarkers of diagnostic and prognostic, also providing an in-depth view of the RPs significance in breast cancer.

MicroRNAs miR-142-5p, miR-150-5p, miR-320a-3p, and miR-4433b-5p in Serum and Tissue: Potential Biomarkers in Sporadic Breast Cancer.

Breast cancer (BC) is a heterogeneous disease, and establishing biomarkers is essential to patient management. We previously described that extracellular vesicle-derived miRNAs (EV-miRNAs) miR-142-5p, miR-150-5p, miR-320a, and miR-4433b-5p in serum discriminated BC from control samples, either alone or combined in a panel. Using these previously described markers, we intend to evaluate whether the same markers identified in EVs are also potential biomarkers in tissue and serum. Expression analysis using RT-qPCR was performed using serum of 67 breast cancer patients (BC-S), 19 serum controls (CT), 83 fresh tumor tissues (BC-T), and 29 adjacent nontumor tissue samples (NT). In addition, analysis from The Cancer Genome Atlas (TCGA) data (832 BC-T and 136 NT) was performed. In all comparisons, we found concordant high expression levels of miR-320a and miR-4433b-5p in BC-S compared to CT in both EVs and cell-free miRNAs (cf-miRNAs). Although miR-150-5p and miR-142-5p were not found to be differentially expressed in serum, panels including these miRNAs improved sensitivity and specificity, supporting our previous findings in EVs. Fresh tissue and data from the TCGA database had, in most comparisons, an opposite behavior when compared to serum and EVs: lower levels of all miRNAs in BC-T than those in NT samples. TCGA analyses revealed reduced expression levels of miR-150-5p and miR-320a-3p in BC-T than those in NT samples and the overexpression of miR-142-5p in BC-T, unlike our RT-qPCR results from tissue in the Brazilian cohort. The fresh tissue analysis showed that all miRNAs individually could discriminate between BC-T and NT in the Brazilian cohort, with high sensitivity and sensibility. Furthermore, combining panels showed higher AUC values and improved sensitivity and specificity. In addition, lower levels of miR-320a-3p in serum were associated with poor overall survival in BC Brazilian patients. In summary, we observed that miR-320a and miR-4433b-5p distinguished BC from controls with high specificity and sensibility, regardless of the sample source. In addition, lower levels of miR-150-5p and higher levels of miR-142-5p were statistically significant biomarkers in tissue, according to TCGA. When combined in panels, all combinations could distinguish BC patients from controls. These results highlight a potential application of these miRNAs as BC biomarkers.

Liquid biopsy for breast cancer using extracellular vesicles and cell-free microRNAs as biomarkers.

Improvement of breast cancer (BC) patient's outcome is directly related to early detection. However, there is still a lack of reliable biomarkers for diagnosis, prognosis and, treatment follow up in BC, leading researchers to study the potential of liquid biopsy based on circulating microRNAs (c-miRNAs). These c-miRNAs can be cell-free or associated with extracellular vesicles (EVs), and have great advantages such as stability in biofluids, noninvasive accessibility compared to current techniques (core-biopsy and surgery), and expression associated with pathogenic conditions. Recently, a new promising field of EV-derived miRNAs (EV-miRNAs) as cancer biomarkers has emerged, receiving special attention due to their selective vesicle sorting which makes them accurate for disease detection. In this review, we discuss new findings about c-miRNA and their potential as biomarkers for BC diagnosis, prognosis, and therapy. Additionally, we address the impact of limitations associated with the standardization of analysis techniques and methods on the implementation of these biomarkers in the clinical setting.

High-throughput mass spectrometry and bioinformatics analysis of breast cancer proteomic data.

Data present here describe a comparative proteomic analysis among the malignant [primary breast tumor (PT) and axillary metastatic lymph nodes (LN)], and the non-tumor [contralateral (NCT) and adjacent (ANT)] breast tissues. Protein identification and quantification were performed through label-free mass spectrometry using a nano-liquid chromatography coupled to an electrospray ionization-mass spectrometry (nLC-ESI-MS/MS). The mass spectrometry proteomic data have been deposited to the ProteomeXchange Consortium via PRIDE partner repository with the dataset identifier PXD012431. A total of 462 differentially expressed proteins was identified among these tissues and was analyzed in six groups' comparisons (named NCTxANT, PTxNCT, PTxANT, LNxNCT, LNxANT and PTxLN). Proteins at 1.5 log2 fold change were submitted to the Ingenuity® Pathway Analysis (IPA) software version 2.3 (QIAGEN Inc.) to identify biological pathways, disease and function annotation, and interaction networks related to cancer biology. The detailed data present here provides information about the proteome alterations and their role on breast tumorigenesis. This information can lead to novel biological insights on cancer research. For further interpretation of these data, please see our research article 'Quantitative label-free mass spectrometry using contralateral and adjacent breast tissues reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer' [2].

Quantitative label-free mass spectrometry using contralateral and adjacent breast tissues reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer.

Proteins play an essential role in the biological processes associated with cancer. Their altered expression levels can deregulate critical cellular pathways and interactive networks. In this study, the mass spectrometry-based label-free quantification followed by functional annotation was performed to investigate the most significant deregulated proteins among tissues of primary breast tumor (PT) and axillary metastatic lymph node (LN) and corresponding non-tumor tissues contralateral (NCT) and adjacent (ANT) from patients diagnosed with invasive ductal carcinoma. A total of 462 proteins was observed as differentially expressed (DEPs) among the groups analyzed. A high level of similarity was observed in the proteome profile of both non-tumor breast tissues and DEPs (n = 12) were mainly predicted in the RNA metabolism. The DEPs among the malignant and non-tumor breast tissues [n = 396 (PTxNCT) and n = 410 (LNxNCT)] were related to pathways of the LXR/RXR, NO, eNOS, eIF2 and sirtuins, tumor-related functions, fatty acid metabolism and oxidative stress. Remarkable similarity was observed between both malignant tissues, which the DEPs were related to metastatic capabilities. Altogether, our findings revealed differential proteomic profiles that affected cancer associated and interconnected signaling processes. Validation studies are recommended to demonstrate the potential of individual proteins and/or pathways as biological markers in breast cancer. SIGNIFICANCE: The proteomic analysis of this study revealed high similarity in the proteomic profile of the contralateral and adjacent non-tumor breast tissues. Significant differences were identified among the proteome of the malignant and non-tumor tissue groups of the same patients, providing relevant insights into the hallmarks, signaling pathways, biological functions, and interactive protein networks that act during tumorigenesis and breast cancer progression. These proteins are suggested as targets of relevant interest to be explored as potential biological markers related to tumor development and metastatic progression in the breast cancer disease.

Lack of association among polymorphic xenobiotic-metabolizing enzyme genotypes and the occurrence and progression of oral carcinoma in a Brazilian population.

BACKGROUND: A case control association study was carried out to investigate polymorphisms in genes CYP1A1 (3801T > C), GSTM1, and GSTT1 (null genotypes) and oral squamous cell carcinoma (OSCC), including a correlation with some histopathological findings (tumor size, lymph node invasion and degree of tumor differentiation). PATIENTS AND METHODS: The patients (n = 91) and the controls (n = 81) were matched by age, sex, ethnicity and smoking habits. The molecular analysis was carried out using Polymerase Chain Reaction-Restrict Length Polymorphisms PCR-RFLP (CYP1A1) and Multiplex-PCR (GSTM1/GSTT1). RESULTS: No association was found for any of the studied genes: CYP1A1 (odds ratio (OR) = 1.24; 95% Confidence Interval (CI) = 0.67-2.31), GSTM1 (OR = 0.61; CI 95% = 0.33-1.11), and GSTT1 (OR = 1.24; CI 95% = 0.65-2.38). The analysis of combining genotypes also showed lack of association. Comparison with the histopathological findings did not, in general, detect any statistically significant differences. CONCLUSION: CYP1A1, GSTM1 and GSTT1 polymorphisms do not appear to influence the genetic susceptibility to OSCC or the progression to more advanced stages.

KIR-HLA distribution in a Vietnamese population from Hanoi.

The KIR (killer cell immunoglobulin-like receptors) gene family codifies a group of receptors that recognize human leukocyte antigens (HLA) and modulate natural killer (NK) cells response. Genetic diversity of KIR genes and HLA ligands has not yet been deeply investigated in South East Asia. Here, we characterized KIR gene presence and absence polymorphism of 14 KIR genes and two pseudogenes, as well as the frequencies of the ligands HLA-Bw4, HLA-C1 and HLA-C2 in a Vietnamese population from Hanoi (n = 140). Genotyping was performed by polymerase chain reaction with specific sequence primers (PCR-SSP). We compared KIR frequencies and performed principal component analysis with 43 worldwide populations of different ancestries. KIR carrier frequencies in Vietnamese were similar to those reported for Thai and Chinese Han, but differed significantly from other geographically close populations such as Japanese and South Korean. This similarity was also observed in KIR gene-content genotypes and is in accordance with the origin from Southern China and Thailand proposed for the Vietnamese population. The frequencies of HLA ligands observed in Vietnamese did not differ from those reported for other East-Asian populations (p > .05). Studies regarding KIR-HLA in populations are of prime importance to understand their evolution, function and role in diseases.

Characterization of MTAP Gene Expression in Breast Cancer Patients and Cell Lines.

MTAP is a ubiquitously expressed gene important for adenine and methionine salvage. The gene is located at 9p21, a chromosome region often deleted in breast carcinomas, similar to CDKN2A, a recognized tumor suppressor gene. Several research groups have shown that MTAP acts as a tumor suppressor, and some therapeutic approaches were proposed based on a tumors´ MTAP status. We analyzed MTAP and CDKN2A gene (RT-qPCR) and protein (western-blotting) expression in seven breast cancer cell lines and evaluated their promoter methylation patterns to better characterize the contribution of these genes to breast cancer. Cytotoxicity assays with inhibitors of de novo adenine synthesis (5-FU, AZA and MTX) after MTAP gene knockdown showed an increased sensitivity, mainly to 5-FU. MTAP expression was also evaluated in two groups of samples from breast cancer patients, fresh tumors and paired normal breast tissue, and from formalin-fixed paraffin embedded (FFPE) core breast cancer samples diagnosed as Luminal-A tumors and triple negative breast tumors (TNBC). The difference of MTAP expression between fresh tumors and normal tissues was not statistically significant. However, MTAP expression was significantly higher in Luminal-A breast tumors than in TNBC, suggesting the lack of expression in more aggressive breast tumors and the possibility of using the new approaches based on MTAP status in TNBC.