RESUMO

It is well established that microRNA-21 (miR-21) targets phosphatase and tensin homolog (PTEN), facilitating epithelial-to-mesenchymal transition (EMT) and drug resistance in cancer. Recent evidence indicates that PTEN activates its pseudogene-derived long non-coding RNA, PTENP1, which in turn inhibits miR-21. However, the dynamics of PTEN, miR-21, and PTENP1 in the DNA damage response (DDR) remain unclear. Thus, we propose a dynamic Boolean network model by integrating the published literature from various cancers. Our model shows good agreement with the experimental findings from breast cancer, hepatocellular carcinoma (HCC), and oral squamous cell carcinoma (OSCC), elucidating how DDR activation transitions from the intra-S phase to the G2 checkpoint, leading to a cascade of cellular responses such as cell cycle arrest, senescence, autophagy, apoptosis, drug resistance, and EMT. Model validation underscores the roles of PTENP1, miR-21, and PTEN in modulating EMT and drug resistance. Furthermore, our analysis reveals nine novel feedback loops, eight positive and one negative, mediated by PTEN and implicated in DDR cell fate determination, including pathways related to drug resistance and EMT. Our work presents a comprehensive framework for investigating cellular responses following DDR, underscoring the therapeutic potential of targeting PTEN, miR-21, and PTENP1 in cancer treatment.

Assuntos

Dano ao DNA , Resistencia a Medicamentos Antineoplásicos , Transição Epitelial-Mesenquimal , MicroRNAs , PTEN Fosfo-Hidrolase , RNA Longo não Codificante , PTEN Fosfo-Hidrolase/metabolismo , PTEN Fosfo-Hidrolase/genética , MicroRNAs/genética , MicroRNAs/metabolismo , Humanos , Transição Epitelial-Mesenquimal/genética , Resistencia a Medicamentos Antineoplásicos/genética , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , Regulação Neoplásica da Expressão Gênica , Neoplasias/genética , Neoplasias/metabolismo , Neoplasias/patologia , Neoplasias/tratamento farmacológico , Linhagem Celular Tumoral , Apoptose/efeitos dos fármacos , Apoptose/genética , Transdução de Sinais

RESUMO

Most protocols used to study the dynamics of calcium (Ca2+) in the malaria parasite are based on dyes, which are invasive and do not allow discrimination between the signal from the host cell and the parasite. To avoid this pitfall, we have generated a parasite line expressing the genetically encoded calcium sensor GCaMP3. The PfGCaMP3 parasite line is an innovative tool for studying spontaneous intracellular Ca2+ oscillations without external markers. Using this parasite line, we demonstrate the occurrence of spontaneous Ca2+ oscillations in the ring, trophozoite, and schizont stages in Plasmodium falciparum. Using the Fourier transform to fluorescence intensity data extracted from different experiments, we observe cytosolic Ca2+ fluctuations. These spontaneous cytosolic Ca2+ oscillations occur in the three intraerythrocytic stages of the parasite, with most oscillations occurring in the ring and trophozoite stages. A control parasite line expressing only a GFP control did not reveal such fluctuations, demonstrating the specificity of the observations. Our results clearly show dynamic, spontaneous Ca2+ oscillations during the asexual stage in P. falciparum, independent from external stimuli.

RESUMO

Patients with non-small cell lung cancer (NSCLC) are often treated with chemotherapy. Poor clinical response and the onset of chemoresistance limit the anti-tumor benefits of drugs such as cisplatin. According to recent research, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a long non-coding RNA related to cisplatin resistance in NSCLC. Furthermore, MALAT1 targets microRNA-145-5p (miR-145), which activates Krüppel-like factor 4 (KLF4) in associated cell lines. B lymphoma Mo-MLV insertion region 1 homolog (BMI1), on the other hand, inhibits miR-145 expression, which stimulates Specificity protein 1 (Sp1) to trigger the epithelial-mesenchymal transition (EMT) process in pemetrexed-resistant NSCLC cells. The interplay between these molecules in drug resistance is still unclear. Therefore, we propose a dynamic Boolean network that can encapsulate the complexity of these drug-resistant molecules. Using published clinical data for gain or loss-of-function perturbations, our network demonstrates reasonable agreement with experimental observations. We identify four new positive circuits: miR-145/Sp1/MALAT1, BMI1/miR-145/Myc, KLF4/p53/miR-145, and miR-145/Wip1/p38MAPK/p53. Notably, miR-145 emerges as a central player in these regulatory circuits, underscoring its pivotal role in NSCLC drug resistance. Our circuit perturbation analysis further emphasizes the critical involvement of these new circuits in drug resistance for NSCLC. In conclusion, targeting MALAT1 and BMI1 holds promise for overcoming drug resistance, while activating miR-145 represents a potential strategy to significantly reduce drug resistance in NSCLC.

RESUMO

Long non-coding RNA (lncRNA) distal-less homeobox 6 antisense RNA 1 (DLX6-AS1) is elevated in a variety of cancers, including non-small cell lung cancer (NSCLC) and cervical cancer. Although it was found that the microRNA-16-5p (miR-16), which is known to regulate autophagy and apoptosis, had been downregulated in similar cancers. Recent research has shown that in tumors with similar characteristics, DLX6-AS1 acts as a sponge for miR-16 expression. However, the cell death-related molecular mechanism of the DLX6-AS1/miR-16 axis has yet to be investigated. Therefore, we propose a dynamic Boolean model to investigate gene regulation in cell death processes via the DLX6-AS1/miR-16 axis. We found the finest concordance when we compared our model to many experimental investigations including gain-of-function genes in NSCLC and cervical cancer. A unique positive circuit involving BMI1/ATM/miR-16 is also something we predict. Our results suggest that this circuit is essential for regulating autophagy and apoptosis under stress signals. Thus, our Boolean network enables an evident cell-death process coupled with NSCLC and cervical cancer. Therefore, our results suggest that DLX6-AS1 targeting may boost miR-16 activity and thereby restrict tumor growth in these cancers by triggering autophagy and apoptosis.

RESUMO

Cell fate determination is a complex process that is frequently described as cells traveling on rugged pathways, beginning with DNA damage response (DDR). Tumor protein p53 (p53) and phosphatase and tensin homolog (PTEN) are two critical players in this process. Although both of these proteins are known to be key cell fate regulators, the exact mechanism by which they collaborate in the DDR remains unknown. Thus, we propose a dynamic Boolean network. Our model incorporates experimental data obtained from NSCLC cells and is the first of its kind. Our network's wild-type system shows that DDR activates the G2/M checkpoint, and this triggers a cascade of events, involving p53 and PTEN, that ultimately lead to the four potential phenotypes: cell cycle arrest, senescence, autophagy, and apoptosis (quadra-stable dynamics). The network predictions correspond with the gain-and-loss of function investigations in the additional two cell lines (HeLa and MCF-7). Our findings imply that p53 and PTEN act as molecular switches that activate or deactivate specific pathways to govern cell fate decisions. Thus, our network facilitates the direct investigation of quadruplicate cell fate decisions in DDR. Therefore, we concluded that concurrently controlling PTEN and p53 dynamics may be a viable strategy for enhancing clinical outcomes.

Assuntos

Dano ao DNA , PTEN Fosfo-Hidrolase , Proteína Supressora de Tumor p53 , Humanos , Apoptose , Pontos de Checagem do Ciclo Celular , Células HeLa , PTEN Fosfo-Hidrolase/genética , PTEN Fosfo-Hidrolase/metabolismo , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismo

RESUMO

The lncRNA GAS5 acts as a tumor suppressor and is downregulated in gastric cancer (GC). In contrast, E2F1, an important transcription factor and tumor promoter, directly inhibits miR-34c expression in GC cell lines. Furthermore, in the corresponding GC cell lines, lncRNA GAS5 directly targets E2F1. However, lncRNA GAS5 and miR-34c remain to be studied in conjunction with GC. Here, we present a dynamic Boolean network to classify gene regulation between these two non-coding RNAs (ncRNAs) in GC. This is the first study to show that lncRNA GAS5 can positively regulate miR-34c in GC through a previously unknown molecular pathway coupling lncRNA/miRNA. We compared our network to several in-vivo/in-vitro experiments and obtained an excellent agreement. We revealed that lncRNA GAS5 regulates miR-34c by targeting E2F1. Additionally, we found that lncRNA GAS5, independently of p53, inhibits GC proliferation through the ATM/p38 MAPK signaling pathway. Accordingly, our results support that E2F1 is an engaging target of drug development in tumor growth and aggressive proliferation of GC, and favorable results can be achieved through tumor suppressor lncRNA GAS5/miR-34c axis in GC. Thus, our findings unlock a new avenue for GC treatment in response to DNA damage by these ncRNAs.

Assuntos

MicroRNAs , RNA Longo não Codificante , Neoplasias Gástricas , Humanos , Linhagem Celular Tumoral , Proliferação de Células/genética , Dano ao DNA/genética , Regulação Neoplásica da Expressão Gênica , MicroRNAs/genética , MicroRNAs/metabolismo , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , Neoplasias Gástricas/patologia

RESUMO

The long non-coding RNA X inactivate-specific transcript (lncRNA XIST) has been verified as an oncogenic gene in non-small cell lung cancer (NSCLC) whose regulatory role is largely unknown. The important tumor suppressors, microRNAs: miR-449a and miR-16 are regulated by lncRNA XIST in NSCLC, these miRNAs share numerous common targets and experimental evidence suggests that they synergistically regulate the cell-fate regulation of NSCLC. LncRNA XIST is known to sponge miR-449a and miR-34a, however, the regulatory network connecting all these non-coding RNAs is still unknown. Here we propose a Boolean regulatory network for the G1/S cell cycle checkpoint in NSCLC contemplating the involvement of these non-coding RNAs. Model verification was conducted by comparison with experimental knowledge from NSCLC showing good agreement. The results suggest that miR-449a regulates miR-16 and p21 activity by targeting HDAC1, c-Myc, and the lncRNA XIST. Furthermore, our circuit perturbation simulations show that five circuits are involved in cell fate determination between senescence and apoptosis. The model thus allows pinpointing the direct cell fate mechanisms of NSCLC. Therefore, our results support that lncRNA XIST is an attractive target of drug development in tumor growth and aggressive proliferation of NSCLC, and promising results can be achieved through tumor suppressor miRNAs.

RESUMO

Transfection of tumor suppressor miRNAs such as miR-34a, miR-449a, and miR-16 with DNA damage can regulate apoptosis and senescence in cancer cells. miR-16 has been shown to influence autophagy in cervical cancer. However, the function of miR-34a and miR-449a in autophagy remains unknown. The functional and persistent G1/S checkpoint signaling pathways in HeLa cells via these three miRNAs, either synergistically or separately, remain a mystery. As a result, we present a synthetic Boolean network of the functional G1/S checkpoint regulation, illustrating the regulatory effects of these three miRNAs. To our knowledge, this is the first synthetic Boolean network that demonstrates the advanced role of these miRNAs in cervical cancer signaling pathways reliant on or independent of p53, such as MAPK or AMPK. We compared our estimated probability to the experimental data and found reasonable agreement. Our findings indicate that miR-34a or miR-16 may control senescence, autophagy, apoptosis, and the functional G1/S checkpoint. Additionally, miR-449a can regulate just senescence and apoptosis on an individual basis. MiR-449a can coordinate autophagy in HeLa cells in a synergistic manner with miR-16 and/or miR-34a.

Assuntos

MicroRNAs , Neoplasias do Colo do Útero , Apoptose/genética , Autofagia/genética , Linhagem Celular Tumoral , Feminino , Regulação Neoplásica da Expressão Gênica , Células HeLa , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , Transdução de Sinais , Neoplasias do Colo do Útero/genética

RESUMO

Long non-coding RNA (lncRNA) such as ANRIL and UFC1 have been verified as oncogenic genes in non-small cell lung cancer (NSCLC). It is well known that the tumor suppressor microRNA-34a (miR-34a) is downregulated in NSCLC. Furthermore, miR-34a induces senescence and apoptosis in breast, glioma, cervical cancer including NSCLC by targeting Myc. Recent evidence suggests that these two lncRNAs act as a miR-34a sponge in corresponding cancers. However, the biological functions between these two non-coding RNAs (ncRNAs) have not yet been studied in NSCLC. Therefore, we present a Boolean model to analyze the gene regulation between these two ncRNAs in NSCLC. We compared our model to several experimental studies involving gain- or loss-of-function genes in NSCLC cells and achieved an excellent agreement. Additionally, we predict three positive circuits involving miR-34a/E2F1/ANRIL, miR-34a/E2F1/UFC1, and miR-34a/Myc/ANRIL. Our circuit- perturbation analysis shows that these circuits are important for regulating cell-fate decisions such as senescence and apoptosis. Thus, our Boolean network permits an explicit cell-fate mechanism associated with NSCLC. Therefore, our results support that ANRIL and/or UFC1 is an attractive target for drug development in tumor growth and aggressive proliferation of NSCLC, and that a valuable outcome can be achieved through the miRNA-34a/Myc pathway.

Assuntos

Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , MicroRNAs , RNA Longo não Codificante , Apoptose/genética , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/patologia , Linhagem Celular Tumoral , Proliferação de Células/genética , Regulação Neoplásica da Expressão Gênica , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , MicroRNAs/genética , MicroRNAs/metabolismo , Oncogenes , RNA Longo não Codificante/genética , RNA Longo não Codificante/metabolismo , Enzimas de Conjugação de Ubiquitina/genética

RESUMO

According to the World Health Organization (WHO), Plasmodium falciparum is the deadliest parasite among all species. This parasite possesses the ability to sense molecules, including melatonin (MEL) and cAMP, and modulate its cell cycle accordingly. MEL synchronizes the development of this malaria parasite by activating several cascades, including the generation of the second messenger cAMP. Therefore, we performed RNA sequencing (RNA-Seq) analysis in P. falciparum erythrocytic stages (ring, trophozoite and schizont) treated with MEL and cAMP. To investigate the expression profile of P. falciparum genes regulated by MEL and cAMP, we performed RNA-Seq analysis in three P. falciparum strains (control, 3D7; protein kinase 7 knockout, PfPK7-; and PfPK7 complement, PfPK7C). In the 3D7 strain, 38 genes were differentially expressed upon MEL treatment; however, none of the genes in the trophozoite (T) stage PfPK7- knockout parasites were differentially expressed upon MEL treatment for 5 hours compared to untreated controls, suggesting that PfPK7 may be involved in the signaling leading to differential gene expression. Moreover, we found that MEL modified the mRNA expression of genes encoding membrane proteins, zinc ion-binding proteins and nucleic acid-binding proteins, which might influence numerous functions in the parasite. The RNA-Seq data following treatment with cAMP show that this molecule modulates different genes throughout the intraerythrocytic cycle, namely, 75, 101 and 141 genes, respectively, in the ring (R), T and schizont (S) stages. Our results highlight P. falciparum's perception of the external milieu through the signaling molecules MEL and cAMP, which are able to drive to changes in gene expression in the parasite.

RESUMO

Models of gene regulatory networks (GRN) have been proposed along with algorithms for inferring their structure. By structure, we mean the relationships among the genes of the biological system under study. Despite the large number of genes found in the genome of an organism, it is believed that a small set of genes is responsible for maintaining a specific core regulatory mechanism (small subnetworks). We propose an algorithm for inference of subnetworks of genes from a small initial set of genes called seed and time series gene expression data. The algorithm has two main steps: First, it grows the seed of genes by adding genes to it, and second, it searches for subnetworks that can be biologically meaningful. The seed growing step is treated as a feature selection problem and we used a thresholded Boolean network with a perturbation model to design the criterion function that is used to select the features (genes). Given that the reverse engineering of GRN is a problem that does not necessarily have one unique solution, the proposed algorithm has as output a set of networks instead of one single network. The algorithm also analyzes the dynamics of the networks which can be time-consuming. Nevertheless, the algorithm is suitable when the number of genes is small. The results showed that the algorithm is capable of recovering an acceptable rate of gene interactions and to generate regulatory hypotheses that can be explored in the wet lab.

Assuntos

Algoritmos , Biologia Computacional/métodos , Redes Reguladoras de Genes , Modelos Genéticos , Ciclo Celular/genética , Genes Fúngicos , Engenharia Genética , Modelos Estatísticos , Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/genética

RESUMO

BACKGROUND: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. METHODS: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. RESULTS AND CONCLUSIONS: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

Assuntos

Redes Reguladoras de Genes , Algoritmos , Bases de Dados Genéticas , Genoma , Plasmodium falciparum/genética , Mapas de Interação de Proteínas , Proteínas/metabolismo

RESUMO

BACKGROUND: A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. RESULTS: We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. CONCLUSIONS: The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.