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12 pages, 8669 KiB

Open AccessArticle

Pharmacological Inhibition of PIP4K2 Potentiates Venetoclax-Induced Apoptosis in Acute Myeloid Leukemia

by Keli Lima, Maria Fernanda Lopes Carvalho, Diego Antonio Pereira-Martins, Frederico Lisboa Nogueira, Lívia Bassani Lins de Miranda, Mariane Cristina do Nascimento, Rita de Cássia Cavaglieri, Jan Jacob Schuringa, João Agostinho Machado-Neto and Eduardo Magalhães Rego

Int. J. Mol. Sci. 2023, 24(23), 16899; https://doi.org/10.3390/ijms242316899 - 29 Nov 2023

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Abstract

Phosphatidylinositol-5-phosphate 4-kinase type 2 (PIP4K2) protein family members (PIP4K2A, PIP4K2B, and PIP4K2C) participate in the generation of PIP4,5P₂, which acts as a secondary messenger in signal transduction, a substrate for metabolic processes, and has structural functions. In [...] Read more.

Phosphatidylinositol-5-phosphate 4-kinase type 2 (PIP4K2) protein family members (PIP4K2A, PIP4K2B, and PIP4K2C) participate in the generation of PIP4,5P₂, which acts as a secondary messenger in signal transduction, a substrate for metabolic processes, and has structural functions. In patients with acute myeloid leukemia (AML), high PIP4K2A and PIP4K2C levels are independent markers of a worse prognosis. Recently, our research group reported that THZ-P1-2 (PIP4K2 pan-inhibitor) exhibits anti-leukemic activity by disrupting mitochondrial homeostasis and autophagy in AML models. In the present study, we characterized the expression of PIP4K2 in the myeloid compartment of hematopoietic cells, as well as in AML cell lines and clinical samples with different genetic abnormalities. In ex vivo assays, PIP4K2 expression levels were related to sensitivity and resistance to several antileukemia drugs and highlighted the association between high PIP4K2A levels and resistance to venetoclax. The combination of THZ-P1-2 and venetoclax showed potentiating effects in reducing viability and inducing apoptosis in AML cells. A combined treatment differentially modulated multiple genes, including TAp73, BCL2, MCL1, and BCL2A1. In summary, our study identified the correlation between the expression of PIP4K2 and the response to antineoplastic agents in ex vivo assays in AML and exposed vulnerabilities that may be exploited in combined therapies, which could result in better therapeutic responses. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Figure 1
Expression of PIP4K2A, PIP4K2B, and PIP4K2C in normal and malignant hematopoietic cells. (A) Graphical legend for the myeloid differentiation hierarchy illustrating the analyzed cell subpopulations used in the analysis (<a href="https://mindthegraph.com/" target="_blank">https://mindthegraph.com/</a> (accessed on 2 August 2023)). Abbreviations: HSC, hematopoietic stem cells; CMP, common myeloid progenitor; GMP, granulocyte macrophage progenitor; MEP, megakaryocyte/erythrocyte progenitor; ERY, erythrocytes; MEGA, megakaryocytes; META, metamyelocytes; NEU, neutrophils; EOS, eosinophils; BASO, basophils; and MONO, monocytes. (B–D) Gene expression profile of PIP4K2A (probe 205570_at), PIP4K2B (probe 201080_at), and PIP4K2C (probe 218942_at) in myeloid cell subpopulations (GSE24759). The p-values and cell lineages are indicated in the graphs: * p < 0.05 cell lineage vs. HSC1, # p < 0.01 cell lineage vs. HSC2; ANOVA and Bonferroni post hoc test. (E) Schematic representation of PIP4K2A, PIP4K2B, and PIP4K2C expression in the different molecular subtypes of AML obtained from the BloodSpot Database (<a href="https://servers.binf.ku.dk/bloodspot/" target="_blank">https://servers.binf.ku.dk/bloodspot/</a> (accessed on 2 August 2023)). (F) PIP4K2A, PIP4K2B, and PIP4K2C mRNA levels in normal CD34+ cells and AML cell lines. ACTB and HPRT1 were used as the reference genes, and CD34+ cells were used as a calibrator. (G) Western blot analysis of the PIP4K2A, PIP4K2B, and PIP4K2C levels in the total cell extracts from CD34+ cells and AML cell lines; the membranes were re-probed with the antibody for the detection of actin and developed with the SuperSignal™ West Dura Extended Duration Substrate system using a G: BOX Chemi XX6 gel document system. Full article ">Figure 2
PIP4K2A, PIP4K2B, and PIP4K2C impact on drug sensitivity in ex vivo assays of acute myeloid leukemia cells. (A) Drug sensitivity according to PIP4K2A, PIP4K2B, and PIP4K2C expression in ex vivo assays of acute myeloid leukemia. Drugs with p < 0.05 are indicated using the Spearman correlation test. (B) The molecular targets (proteins/genes) of the identified drugs are listed and analyzed using Venn diagrams (<a href="http://bioinformatics.psb.ugent.be/" target="_blank">http://bioinformatics.psb.ugent.be/</a> (accessed on 2 August 2023)). Full article ">Figure 3
THZ-P1-2 potentiates venetoclax-induced apoptosis in acute myeloid leukemia cells. (A) Dose–response cytotoxicity for combined treatment was analyzed using a MTT assay for Kasumi-1, NB4, and U-937 cells treated with vehicle or graded concentrations of THZ-P1-2 (0.3, 0.6, 1.2, 2.5, and 5 µM) and venetoclax (1.6, 3.2, 6.4, 12.5, and 25 µM) alone or in combination with each other for 48 h, as indicated. The values are expressed as the percentage of viable cells for each condition relative to the vehicle-treated cells. The results are shown as the mean of at least three independent experiments. The bar graphs represent the cell viability for the selected concentrations. The p-values and cell lines are indicated as follows: * p < 0.05 treatment versus vehicle and # p < 0.05 monotherapy versus combined therapy; ANOVA test and Bonferroni post-test. (B) The apoptosis was detected using flow cytometry in Kasumi-1, NB4, and U-937 cells treated with THZ-P1-2 and/or venetoclax for 48 h using an APC-annexin V/PI staining method. Representative dot plots are shown for each condition; the upper and lower right quadrants (Q2 plus Q3) cumulatively contain the apoptotic population (annexin V+ cells). The bar graphs represent the mean ± SD of at least three independent experiments. The p values and cell lines are indicated in the graphs as follows: * p < 0.05 for THZ-P1-2- and/or venetoclax-treated cells vs. vehicle-treated cells and # p < 0.05 for THZ-P1-2- or venetoclax-treated cells versus the combination treatment at the corresponding doses; ANOVA and Bonferroni post-test. (C) Western blot analysis PARP1 (total and cleaved) and γH2AX levels in the total cell extracts from Kasumi-1, NB4, and U-937 cells treated with vehicle, THZ-P1-2, and/or venetoclax at the indicated concentrations; the membranes were re-probed with the antibody for the detection of α-tubulin and developed with the SuperSignal™ West Dura Extended Duration Substrate system (Thermo Fisher Scientific, Cleveland, OH, USA) using a G: BOX Chemi XX6 gel document system. Full article ">Figure 4
Effects of THZ-P1-2 alone or in combination with venetoclax on the gene expression profile of Kasumi-1 cells. (A) Heatmap for the gene expression analysis in Kasumi-1 cells treated with vehicle, THZ-P1-2 (3.2 µM), and/or venetoclax (1.2 µM) for 24 h. The data represent the fold change of the vehicle-treated cells, and the downregulated and upregulated genes are shown in blue and red, respectively. The fold-change (FC), standard deviation (SD), and p-values are indicated, with * p < 0.05, ** p < 0.01, *** p < 0.001, using Student t-test. (B) The network for the genes modulated with THZ-P1-2 and/or venetoclax was constructed using the GeneMANIA database (<a href="https://genemania.org/" target="_blank">https://genemania.org/</a> (accessed on 2 August 2023)). The genes significantly modulated are illustrated as crosshatched circles; the interacting genes included by modeling the software are indicated using circles without crosshatching. The main biological interactions and the associated functions are described. FDR, false discover rate. (C) The mitochondrial membrane potential (ΔΨM) analysis was evaluated using the JC-1 staining method and flow cytometry. Kasumi-1 cells were treated with vehicle, THZ-P1-2 (3.2 μM), and/or venetoclax (1.2 μM) for 24 h. Representative dot plots are shown for each condition; the gate FL-2 contains cells with intact mitochondria and the gate FL-2/FL-1 contains cells with damaged mitochondria. The bar graphs represent the mean ± SD of at least five independent experiments and the p values are indicated as follows: * p < 0.05 treatment versus vehicle and # p < 0.05 monotherapy versus combined therapy; ANOVA test and Bonferroni post-test. Full article ">

15 pages, 539 KiB

Open AccessArticle

Characterization of Potential Melanoma Predisposition Genes in High-Risk Brazilian Patients

by Bianca Costa Soares de Sá, Luciana Facure Moredo, Giovana Tardin Torrezan, Felipe Fidalgo, Érica Sara Souza de Araújo, Maria Nirvana Formiga, João Pereira Duprat and Dirce Maria Carraro

Int. J. Mol. Sci. 2023, 24(21), 15830; https://doi.org/10.3390/ijms242115830 - 31 Oct 2023

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Abstract

Increased genetic risk for melanoma can occur in the context of germline pathogenic variants in high-penetrance genes, such as CDKN2A and CDK4, risk variants in low- to moderate-penetrance genes (MC1R and MITF), and possibly due to variants in emerging genes, [...] Read more.

Increased genetic risk for melanoma can occur in the context of germline pathogenic variants in high-penetrance genes, such as CDKN2A and CDK4, risk variants in low- to moderate-penetrance genes (MC1R and MITF), and possibly due to variants in emerging genes, such as ACD, TERF2IP, and TERT. We aimed to identify germline variants in high- and low- to moderate-penetrance melanoma risk genes in Brazilian patients with clinical criteria for familial melanoma syndrome. We selected patients with three or more melanomas or melanoma patients from families with three tumors (melanoma and pancreatic cancer) in first- or second-degree relatives. Genetic testing was performed with a nine-gene panel (ACD, BAP1, CDK4, CDKN2A, POT1, TERT, TERF2IP, MC1R, and MITF). In 36 patients, we identified 2 (5.6%) with germline pathogenic variants in CDKN2A and BAP1 and 4 (11.1%) with variants of uncertain significance in the high-penetrance genes. MC1R variants were found in 86.5%, and both red hair color variants and unknown risk variants were enriched in patients compared to a control group. The low frequency of germline pathogenic variants in the high-penetrance genes and the high prevalence of MC1R variants found in our cohort show the importance of the MC1R genotype in determining the risk of melanoma in the Brazilian melanoma-prone families. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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11 pages, 2380 KiB

Open AccessArticle

The Clinical and Molecular Profile of Lung Cancer Patients Harboring the TP53 R337H Germline Variant in a Brazilian Cancer Center: The Possible Mechanism of Carcinogenesis

by Carlos D. H. Lopes, Fernanda F. Antonacio, Priscila M. G. Moraes, Paula F. Asprino, Pedro A. F. Galante, Denis L. Jardim, Mariana P. de Macedo, Renata L. Sandoval, Artur Katz, Gilberto de Castro, Jr. and Maria Isabel Achatz

Int. J. Mol. Sci. 2023, 24(20), 15035; https://doi.org/10.3390/ijms242015035 - 10 Oct 2023

Cited by 3 | Viewed by 1400

Abstract

In southern and southeastern Brazil, the TP53 founder variant c.1010G>A (R337H) has been previously documented with a prevalence of 0.3% within the general population and linked to a heightened incidence of lung adenocarcinomas (LUADs). In the present investigation, we cover clinical and molecular [...] Read more.

In southern and southeastern Brazil, the TP53 founder variant c.1010G>A (R337H) has been previously documented with a prevalence of 0.3% within the general population and linked to a heightened incidence of lung adenocarcinomas (LUADs). In the present investigation, we cover clinical and molecular characterizations of lung cancer patients from the Brazilian Li-Fraumeni Syndrome Study (BLISS) database. Among the 175 diagnosed malignant neoplasms, 28 (16%) were classified as LUADs, predominantly occurring in females (68%), aged above 50 years, and never-smokers (78.6%). Significantly, LUADs manifested as the initial clinical presentation of Li-Fraumeni Syndrome in 78.6% of cases. Molecular profiling was available for 20 patients, with 14 (70%) revealing EGFR family alterations. In total, 23 alterations in cancer driver genes were identified, comprising 7 actionable mutations and 4 linked to resistance against systemic treatments. In conclusion, the carriers of TP53 R337H demonstrate a predisposition to LUAD development. Furthermore, our results indicate that environmental pollution potentially impacts the carcinogenesis of lung tumors in the carriers of TP53 R337H. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Patients included in the BLISS database: (A) proportion of patients with cancer diagnosis; (B) proportion of lung cancer from all tumors. Full article ">Figure 2
Genomic landscape of lung adenocarcinomas. Genomic profile of the 20 patients submitted to tumoral multigenic next-generation sequencing (NGS) platforms or real-time PCR (rtPCR) for EGFR and ALK. NGS was performed in 16 patients and rtPCR was performed in 4 (indicated by *). Most cases indicated mutations in driver genes. A total of 23 alterations, comprising 7 actionable and 4 related to systemic treatment resistance, were described. In horizontal lines, individual characteristics of the patients are listed, such as average levels of exposure to PM2.5, gender, smoking, and evaluated genes. Each column indicates an individual patient. On the right, the genetic alterations are described and illustrated with colored squares. Abbreviations: del—deletion; indel—insertion or deletion; inser—insertion; PM2.5—particulate matter < 2.5mm of diameter. Full article ">Figure 3
Clinical outcomes of 16 patients with early disease submitted to surgery: (a) median disease-free survival of the sixteen patients assessed; (b) overall survival of these patients. None of them had died due to LC. Abbreviation: NR—not reached. Full article ">Figure 4
Clinical outcomes in 11 patients with advanced disease treated with EGFR inhibitors: (a) median progression-free survival on first-generation EGFR inhibitor treatment (n = 6; median follow-up of 15.7 months); (b) median progression-free survival on third-generation EGFR inhibitor treatment (n = 5; median of follow-up of 12 months); (c) median overall survival on first-generation EGFR inhibitor treatment (n = 6; median of follow-up of 50.3 months); (d) median overall survival on third-generation EGFR inhibitor treatment (n = 5; median of follow-up of 67.6 months). Full article ">Figure 5
Clinical evolution on systemic treatments of patients #6 and #11: (a) a 41-year-old man with metastatic LC to bone and lungs with EGFR exon 20 insertion was submitted to six lines of treatment with clinical and radiologic benefit until multisystemic progression after seven months of an experimental EGFR oral inhibitor for exon 20 alterations; (b) a 33-year-old man with previous resected LC harboring, HER 2 exon 20 insertion, and submitted to four cycles of platinum doublet experienced a hepatic recurrence 13 months after. Then, he received three lines of systemic treatment, as represented above, with clinical and radiographic benefits for 25 months until CNS progression. Abbreviations: carbo—carboplatin; CDDP—cisplatin; pmtx—pemetrexed; TDM-1—trastuzumab–emtansine; x followed by a number indicates the number of treatment cycles. Full article ">Figure 6
Distribution of cases in Brazil and average daily values of PM2.5: (a) location of patients diagnosed with LC according to the PM2.5 heat map obtained via satellite (the redder the colors, the higher the PM2.5 value); (b) daily mean values are represented in box plots of cities with cases and comparison with the value established by the European Society for the Environment as poor air quality (EAQI poor). We applied logarithmic scaling to the values for better graphical representation. Note that most values are above the levels designated as EAQI poor. Full article ">

16 pages, 3296 KiB

Open AccessArticle

Aspirin Affects MDA-MB-231 Vesicle Production and Their Capacity to Induce Fibroblasts towards a Pro-Invasive State

by Rafaela de Assiz Louback, Karina Martins-Cardoso, Luzineide W. Tinoco, Federica Collino, Ana Paula D. N. de Barros, Anneliese Fortuna-Costa, Robson Q. Monteiro, Maria Isabel Doria Rossi and Rafael Soares Lindoso

Int. J. Mol. Sci. 2023, 24(15), 12020; https://doi.org/10.3390/ijms241512020 - 27 Jul 2023

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Abstract

Long-term administration of aspirin (ASA, acetylsalicylic acid) in oncogenic patients has been related to a reduction in cancer risk incidence, but its precise mechanism of action is unclear. The activation of cancer-associated fibroblasts (CAFs) is a key element in tumor progression and can [...] Read more.

Long-term administration of aspirin (ASA, acetylsalicylic acid) in oncogenic patients has been related to a reduction in cancer risk incidence, but its precise mechanism of action is unclear. The activation of cancer-associated fibroblasts (CAFs) is a key element in tumor progression and can be triggered by cancer-derived extracellular vesicles (EVs). Targeting the communication between cancer cells and the surrounding tumor microenvironment (TME) may control cancer progression. Our aim was to investigate the effect of ASA on breast cancer cells, focusing on EV secretion and their effect on the biological properties of CAFs. As a result, ASA was shown to reduce the amount and alter the size distribution of EVs produced by MDA-MB-231 tumor cells. Fibroblasts stimulated with EVs derived from MDA-MB-231 treated with ASA (EV-ASA) showed a lower expression of alpha-smooth muscle actin (α-SMA), matrix metalloproteinase-2 (MMP2) but not fibroblast activation protein (FAP) in respect to the ones stimulated with EVs from untreated breast cancer cells (EV-CTR). Furthermore, invasion assays using a three-dimensional (3D) fibroblast spheroid model showed reduced MDA-MB-231 invasion towards fibroblast spheroids pretreated with EV-ASA as compared to spheroids prepared with EV-CTR-stimulated fibroblasts. This suggests that ASA partially inhibits the ability of tumor EVs to stimulate CAFs to promote cancer invasion. In conclusion, ASA can interfere with tumor communication by reducing EV secretion by breast tumor cells as well as by interfering with their capacity to stimulate fibroblasts to become CAFs. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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ASA reduces cell viability at high concentrations. Breast cancer tumor cell lines MCF-7 (A), T-47D (B), and MDA-MB-231 (C,D) were treated for up to 72 h with different concentrations (0.695–5.56 mM) of ASA. T-47D (B) MDA-MB-231 (C) cells were also treated for 24 h with different concentrations (0.695–5.56 mM) of ASA and then maintained for 24 h in the absence of ASA (24 + 24). (A–C) The percentage of inhibition of formazan crystal formation following reduction by MTT was calculated in relation to control cells incubated with vehicle (D) The percentage of MDA-MB-231 cells positive for Annexin V/PI (cell death) was evaluated by FACS analysis. Data show mean ± SEM of three independent experiments. * p < 0.05; ** p < 0.001. Full article ">Figure 2
ASA promotes changes in EV production by breast cancer cells. MDA-MB-231 derived EVs were isolated from the conditioned medium (CM) of cells incubated in the presence, or not, of 2.78 mM of ASA for 24 h (24 h). The EVs were collected 24 h after ASA removal. (A) Quantification of EVs secreted by cells treated (EV-ASA) or not (EV-CTR) with ASA. Data represent mean ± SEM of 5 (CTR) and 13 (ASA) independent experiments. * p = 0.0002. (B,C) Distribution and average size profile of EV-CTR (B) and EV-ASA (C) isolated from CM. Data show a median, maximum, and minimum of six independent experiments. (D,E) Pie chart showing the size distribution of each particle fraction secreted by control (D) and ASA-treated (E) cells. (F) Data represent the frequency of the different range size concentrations of EVs in CTR (white) and ASA (grey) conditions. The difference in the percentage of the 45 nm fraction was significant (* p < 0.05). Full article ">Figure 3
ASA modifies the profile of EV-stimulated fibroblasts. Human fibroblasts were stimulated with EVs released from MDA-MB-231 treated with 2.78 mM of ASA (EV-ASA) or not (EV-CTR) (24 + 24 h treatment). Expression of FAP (A–C, green) and α-SMA (D–F, green) in control (CTR) unstimulated cells (A,D) and EV-CTR (B,E) or EV-ASA (C,F) stimulated cells. (G) Secondary antibody control. Nuclei were stained with DAPI (blue). Bar = 20 µm. Representative images of three independent experiments. (H) Fluorescence intensity of α-SMA and FAP in regions of interest, adjusted to the percentage of control. (I,J) Gene expression of metalloproteinases-2 (MMP-2; I) and 14 (MMP-14; J) were analyzed by quantitative RT-PCR. GAPDH was used as the reference gene. Relative expression of mRNA was calculated using the ΔΔCT method. Data represent mean ± SEM of three independent experiments. * p < 0.05 ** p < 0.001. Full article ">Figure 4
EVs derived from ASA-treated breast tumor cells block the phenotypical switch of fibroblasts into CAF and their tumor pro-invasive properties. Spheroids made of unstimulated (CTR), EV-CTR, or EV-ASA stimulated fibroblasts were cultured for 24 h with CFSE-labeled MDA-MB-231 cells. The supernatant was harvested, and the spheroids were enzymatically dissociated. The amount of CFSE + events was evaluated by flow cytometry, with time as the acquisition parameter. (A–I) Dot plots showing (A,C,E,G) selected CFSE + events and (B,D,F,H) its distribution over the acquisition time in (A–D) supernatants and (E–H) spheroids. (I) Dot plot of spheroids maintained in the absence of labeled tumor cells, showing no CFSE + events. (J) Quantification of invasion, calculated as the percentage of CFSE + events inside the spheroids in relation to the total of CFSE + events (supernatant + spheroid). Data show mean ± SEM of the average of five independent experiments conducted in duplicate or triplicate. *, # p < 0.05 vs. EV-CTR and CTR, respectively. Full article ">

12 pages, 1322 KiB

Open AccessArticle

Rectal Cancer Tissue Lipidome Differs According to Response to Neoadjuvant Therapy

by Salvador Sánchez-Vinces, Gustavo Henrique Bueno Duarte, Marcia Cristina Fernandes Messias, Caroline Fernanda Alves Gatinoni, Alex Ap. Rosini Silva, Pedro Henrique Godoy Sanches, Carlos Augusto Real Martinez, Andreia M. Porcari and Patricia de Oliveira Carvalho

Int. J. Mol. Sci. 2023, 24(14), 11479; https://doi.org/10.3390/ijms241411479 - 14 Jul 2023

Cited by 1 | Viewed by 1333

Abstract

Rectal cancer (RC) is a gastrointestinal cancer with a poor prognosis. While some studies have shown metabolic reprogramming to be linked to RC development, it is difficult to define biomolecules, like lipids, that help to understand cancer progression and response to therapy. The [...] Read more.

Rectal cancer (RC) is a gastrointestinal cancer with a poor prognosis. While some studies have shown metabolic reprogramming to be linked to RC development, it is difficult to define biomolecules, like lipids, that help to understand cancer progression and response to therapy. The present study investigated the relative lipid abundance in tumoral tissue associated with neoadjuvant therapy response using untargeted liquid chromatography–mass spectrometry lipidomics. Locally advanced rectal cancer (LARC) patients (n = 13), clinically staged as T3–4 were biopsied before neoadjuvant chemoradiotherapy (nCRT). Tissue samples collected before nCRT (staging) and afterwards (restaging) were analyzed to discover lipidomic differences in RC cancerous tissue from Responders (n = 7) and Non-responders (n = 6) to nCRT. The limma method was used to test differences between groups and to select relevant feature lipids from tissue samples. Simple glycosphingolipids and differences in some residues of glycerophospholipids were more abundant in the Non-responder group before and after nCRT. Oxidized glycerophospholipids were more abundant in samples of Non-responders, especially those collected after nCRT. This work identified potential lipids in tissue samples that take part in, or may explain, nCRT failure. These results could potentially provide a lipid-based explanation for nCRT response and also help in understanding the molecular basis of RC and nCRT effects on the tissue matrix. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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16 pages, 5579 KiB

Open AccessArticle

2-Methoxyestradiol-3,17-O,O-bis-sulfamate (STX140) Inhibits Proliferation and Invasion via Senescence Pathway Induction in Human BRAFi-Resistant Melanoma Cells

by Ylana Adami Franco, Manoel Oliveira de Moraes, Jr., Larissa A. C. Carvalho, Wolfgang Dohle, Renaira Oliveira da Silva, Isabella Harumi Yonehara Noma, Keli Lima, Barry V. L. Potter, João A. Machado-Neto and Silvya Stuchi Maria-Engler

Int. J. Mol. Sci. 2023, 24(14), 11314; https://doi.org/10.3390/ijms241411314 - 11 Jul 2023

Cited by 1 | Viewed by 1495

Abstract

The endogenous estradiol derivative 2-Methoxyestradiol (2-ME) has shown good and wide anticancer activity but suffers from poor oral bioavailability and extensive metabolic conjugation. However, its sulfamoylated derivative, 2-methoxyestradiol-3,17-O,O-bis-sulfamate (STX140), has superior potential as a therapeutic agent, acts by disrupting [...] Read more.

The endogenous estradiol derivative 2-Methoxyestradiol (2-ME) has shown good and wide anticancer activity but suffers from poor oral bioavailability and extensive metabolic conjugation. However, its sulfamoylated derivative, 2-methoxyestradiol-3,17-O,O-bis-sulfamate (STX140), has superior potential as a therapeutic agent, acts by disrupting microtubule polymerization, leading to cell cycle arrest and apoptosis in cancer cells and possesses much better pharmaceutical properties. This study investigated the antiproliferative and anti-invasive activities of STX140 in both SKMEL-28 naïve melanoma (SKMEL28-P) cells and resistant melanoma cells (SKMEL-28R). STX140 inhibited cell proliferation in the nanomolar range while having a less pronounced effect on human melanocytes. Additionally, STX140 induced cell cycle arrest in the G2/M phase and sub-G1, reduced migration, and clonogenic potential in monolayer models, and inhibited invasion in a 3D human skin model with melanoma cells. Furthermore, STX140 induced senescence features in melanoma and activated the senescence machinery by upregulating the expression of senescence genes and proteins related to senescence signaling. These findings suggest that STX140 may hold potential as a therapeutic agent for melanoma treatment. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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16 pages, 3087 KiB

Open AccessArticle

Cathepsin B Is Not an Intrinsic Factor Related to Asparaginase Resistance of the Acute Lymphoblastic Leukemia REH Cell Line

by Iris Munhoz Costa, Brian Effer, Tales Alexandre Costa-Silva, Chen Chen, Michael F. Ciccone, Adalberto Pessoa, Camila O. dos Santos and Gisele Monteiro

Int. J. Mol. Sci. 2023, 24(13), 11215; https://doi.org/10.3390/ijms241311215 - 7 Jul 2023

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Abstract

L-Asparaginase (ASNase) is a biopharmaceutical used as an essential drug in the treatment of acute lymphoblastic leukemia (ALL). Yet, some cases of ALL are naturally resistant to ASNase treatment, which results in poor prognosis. The REH ALL cell line, used as a model [...] Read more.

L-Asparaginase (ASNase) is a biopharmaceutical used as an essential drug in the treatment of acute lymphoblastic leukemia (ALL). Yet, some cases of ALL are naturally resistant to ASNase treatment, which results in poor prognosis. The REH ALL cell line, used as a model for studying the most common subtype of ALL, is considered resistant to treatment with ASNase. Cathepsin B (CTSB) is one of the proteases involved in the regulation of in vivo ASNase serum half-life and it has also been associated with the progression and resistance to treatment of several solid tumors. Previous works have shown that, in vitro, ASNase is degraded when incubated with REH cell lysate, which is prevented by a specific CTSB inhibitor, suggesting a function of this protease in the ASNase resistance of REH cells. In this work, we utilized a combination of CRISPR/Cas9 gene targeting and enzymatic measurements to investigate the relevance of CTSB on ASNase treatment resistance in the ALL model cell line. We found that deletion of CTSB in REH ALL cells did not confer ASNase treatment sensitivity, thus suggesting that intrinsic expression of CTSB is not a mechanism that drives the resistant nature of these ALL cells to enzymes used as the first-line treatment against leukemia. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Monitoring of REHcas9 cell infection and CTSB edition. (A) Representative image of REHcas9 infection using lentivirus particles sgRNA-Rosa26. The same procedure was carried out for all lentiviruses produced (sgRNA-1–5 for CTSB gene and sgRNA-RPA3). The infection was confirmed by GFP expression in inverted fluorescence microscope. The figure shows the uninfected cells and infected cells with sgRNA-Rosa26 lentivirus expressing GFP under bright light and green channel excitation at 488 nm. Scale bar, 100 µm. (B) Schematic representation of gene and qPCR-based assay to estimate gene editing efficiency using CRISPR/Cas9 editing tool. Five different primers pairs were designed to flank the target region for the knockout of each sgRNA to validate the editing of the CTSB gene by qPCR. (C) Confirmation of CTSB gene editing by qPCR. Derivate melting curves from qPCR of REHcas9 cells infected with different sgRNAs. The genomic DNA of each cell was used for CTSB editing validation. Uninfected REHcas9 cells and REHcas9 cells infected with sgRNA-Rosa26 (REHcas9 + sgRNA-Rosa26) were used as a negative control (no editing in CTSB gene). The specific primer for the cyclin-dependent kinase 7 (CDKL7) gene was used as an internal control. Full article ">Figure 2
Evaluation of CTSB protein amount and activity in REHcas9 + sgRNAs. (A) Western blotting assay image using REHcas9 + sgRNAs. Uninfected REHcas9 and REHcas9 + sgRNAs cells were lysed, 150 µg of total protein was used in each sample, and the film was exposed for 2.5 and 5 min. α-Tubulin protein (60 kDa) was used as a total protein load control. (B) Cathepsin B activity assay of uninfected (in the presence or absence of CTSB inhibitor) and infected cells with sgRNAs (1–5) and Rosa26 using the Cathepsin B Activity Fluorometric Assay Kit (BioVision, Waltham, MA, USA). (C) CTSB activity assay using Sigma-Aldrich reagents (see <a href="#sec4-ijms-24-11215" class="html-sec">Section 4</a>) for analysis of lysates of REHcas9 cells and cells infected with sgRNAs-1, 2, and 4 and Rosa26. Results represent the mean ± standard deviation of experiments performed in triplicate. One-way ANOVA statistical analysis followed by Tukey’s post hoc test showed a significant difference (p < 0.05) between the CTSB activities of sgRNA-infected cells (1–5) when compared to the uninfected control REHcas9 cells (*) or when compared to cells treated with CTSB inhibitor (#). Full article ">Figure 3
Analysis of CTSB gene editing in confirmed REHcas9 cells with CTSB knockout by sequencing. (A) Analysis of gene editing by sequencing of REHcas9 + sgRNA-1 and REHcas9 + sgRNA-4. The plasmids obtained from TOPO + PCR constructs were sequenced using the TOPO M13 vector primer and aligned with the CTSB gene sequence (NG_009217.2) using Geneious® 11.1.5 software. (B) Human CTSB protein sequence (Uniprot code: P07858). The signal peptide sequence is identified in red; the propeptide sequence is identified in blue; the mature protein sequence is identified in black; the C-terminal propeptide sequence is identified in green. The arrows represent the position at the beginning of the changes in the amino-acid sequence caused by the editing of sgRNA-1 (orange arrow) and sgRNA-4 (purple arrow). Full article ">Figure 4
Monitoring of REHcas9-sgRNA cell proliferation by flow cytometry. (A) Cells infected with different sgRNAs were monitored by flow cytometer MACSQuant® (Miltenyi Biotec) for 27 days. (B) After 27 days, cells were sorted by fluorescence-activated cell sorting (FACS) and monitored for additional 15 days. Full article ">Figure 5
Purification and activity assay of ASNases. (A) Evaluation of purity of ErA_WT, ErA_DM, and EcA_WT proteoforms by 12% SDS-PAGE gel electrophoresis. ErA_WT and ErA_DM proteins have ~37 kDa and the EcA_WT protein has ~35 kDa. MW indicates the molecular weight Dual Color Standards TM (Bio-Rad). (B) Specific activity of ErA_WT, ErA_DM, and EcA_ WT proteoforms measured by Nessler’s reagent. Graph of reaction speed in μmol/min as a function of the amount of protein in milligram. The slope of the line equation represents the specific activity for each enzyme given in U/mg. One unit (U) is equal to 1 µmol of ammonium produced per minute at 37 °C. The points represent the mean ± standard error (n = 3). Full article ">Figure 6
In vitro cytotoxicity assay of CTSB KO cells in the presence of ASNase. REHcas9 (uninfected) and REHcas + sgRNA-1 cells were treated with different concentrations of EcA_WT, ErA_WT, and ErA_DM enzymes for 72 h. Cells without treatment and with the addition of the buffer in which the enzymes were diluted are named “control”. The assay was performed in analytical triplicate, and the data represent the mean ± standard deviation (n = 3). Full article ">

27 pages, 5292 KiB

Open AccessArticle

Impairment of SK-MEL-28 Development—A Human Melanoma Cell Line—By the Crataeva tapia Bark Lectin and Its Sequence-Derived Peptides

by Kathleen Chwen Ming Lie, Camila Ramalho Bonturi, Bruno Ramos Salu, Juliana Rodrigues de Oliveira, Márcia Bonini Galo, Patrícia Maria Guedes Paiva, Maria Tereza dos Santos Correia and Maria Luiza Vilela Oliva

Int. J. Mol. Sci. 2023, 24(13), 10617; https://doi.org/10.3390/ijms241310617 - 25 Jun 2023

Cited by 3 | Viewed by 1768

Abstract

Melanoma is difficult to treat with chemotherapy, prompting the need for new treatments. Protease inhibitors have emerged as promising candidates as tumor cell proteases promote metastasis. Researchers have developed a chimeric form of the Bauhinia bauhinioides kallikrein inhibitor, rBbKIm, which has shown negative [...] Read more.

Melanoma is difficult to treat with chemotherapy, prompting the need for new treatments. Protease inhibitors have emerged as promising candidates as tumor cell proteases promote metastasis. Researchers have developed a chimeric form of the Bauhinia bauhinioides kallikrein inhibitor, rBbKIm, which has shown negative effects on prostate tumor cell lines DU145 and PC3. Crataeva tapia bark lectin, CrataBL, targets sulfated oligosaccharides in glycosylated proteins and has also demonstrated deleterious effects on prostate and glioblastoma tumor cells. However, neither rBbKIm nor its derived peptides affected the viability of SK-MEL-28, a melanoma cell line, while CrataBL decreased viability by over 60%. Two peptides, Pep. 26 (Ac-Q-N-S-S-L-K-V-V-P-L-NH2) and Pep. 27 (Ac-L-P-V-V-K-L-S-S-N-Q-NH2), were also tested. Pep. 27 suppressed cell migration and induced apoptosis when combined with vemurafenib, while Pep. 26 inhibited cell migration and reduced nitric oxide and the number of viable cells. Vemurafenib, a chemotherapy drug used to treat melanoma, was found to decrease the release of interleukin 8 and PDGF-AB/BB cytokines and potentiated the effects of proteins and peptides in reducing these cytokines. These findings suggest that protease inhibitors may be effective in blocking melanoma cells and highlight the potential of CrataBL and its derived peptides. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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22 pages, 2903 KiB

Open AccessArticle

Analysis of the Mutational Landscape of Osteosarcomas Identifies Genes Related to Metastasis and Prognosis and Disrupted Biological Pathways of Immune Response and Bone Development

by Sara Ferreira Pires, Juliana Sobral de Barros, Silvia Souza da Costa, Gabriel Bandeira do Carmo, Marília de Oliveira Scliar, André van Helvoort Lengert, Érica Boldrini, Sandra Regini Morini da Silva, Daniel Onofre Vidal, Mariana Maschietto and Ana Cristina Victorino Krepischi

Int. J. Mol. Sci. 2023, 24(13), 10463; https://doi.org/10.3390/ijms241310463 - 21 Jun 2023

Cited by 2 | Viewed by 1957

Abstract

Osteosarcoma (OS) is the most prevalent type of bone tumor, but slow progress has been achieved in disentangling the full set of genomic events involved in its initiation and progression. We assessed by NGS the mutational spectrum of 28 primary OSs from Brazilian [...] Read more.

Osteosarcoma (OS) is the most prevalent type of bone tumor, but slow progress has been achieved in disentangling the full set of genomic events involved in its initiation and progression. We assessed by NGS the mutational spectrum of 28 primary OSs from Brazilian patients, and identified 445 potentially deleterious SNVs/indels and 1176 copy number alterations (CNAs). TP53 was the most recurrently mutated gene, with an overall rate of ~60%, considering SNVs/indels and CNAs. The most frequent CNAs (~60%) were gains at 1q21.2q21.3, 6p21.1, and 8q13.3q24.22, and losses at 10q26 and 13q14.3q21.1. Seven cases presented CNA patterns reminiscent of complex events (chromothripsis and chromoanasynthesis). Putative RB1 and TP53 germline variants were found in five samples associated with metastasis at diagnosis along with complex genomic patterns of CNAs. PTPRQ, KNL1, ZFHX4, and DMD alterations were prevalent in metastatic or deceased patients, being potentially indicative of poor prognosis. TNFRSF11B, involved in skeletal system development and maintenance, emerged as a candidate for osteosarcomagenesis due to its biological function and a high frequency of copy number gains. A protein–protein network enrichment highlighted biological pathways involved in immunity and bone development. Our findings reinforced the high genomic OS instability and heterogeneity, and led to the identification of novel disrupted genes deserving further evaluation as biomarkers due to their association with poor outcomes. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Figure 1
Characterization of the 445 coding non-synonymous somatic variants detected in the group of 28 primary osteosarcomas from Brazilian patients. (a) Genomic distribution of the identified SNV/indel variants across all chromosomes, indicated from 1 to 22 and X; red indicates SNVs and yellow, indels. The symbols of the recurrently mutated genes (with SNVs/indel variants detected in >1 patient) are depicted on the left side of the ideograms. (b) Characterization of the variants, according to their types: SNV—single nucleotide variant; indel—small insertion or deletion. (c) Characterization of the variants, according to their effects: missense—amino acid changes; LoF—loss-of-function. Full article ">Figure 2
Overlapping genomic information between our study and previous genomic OS studies. (a) Venn diagram showing the genes common to the set of mutated genes in the Brazilian OS group and those reported in the literature. (b) Distribution of point mutations across 29 genes from our dataset and previously reported in the literature to be mutated in OS. The identified alterations are color-coded by type (missense or loss-of-function). Each row indicates a gene; each column indicates a tumor sample. The asterisk indicates the occurrence of more than one mutation in the same sample. Full article ">Figure 3
Distribution of point mutations across genes recurrently mutated in patients presenting clinical particularities. Full article ">Figure 4
Global CNA profile of the 28 osteosarcomas cohort, with the respective frequencies of detected copy number gains and losses. On the x-axis, the chromosomes are indicated from 1 to 22 and X. The y-axis shows the detection frequency (%) of gains (in blue) and losses (in red) in the OS group. In the boxes below the graph, we highlighted specific CNAs, with the log2 sample/reference ratio thresholds indicated on the left of each figure: 0.25 for gains and 1.2 for high copy gains (blue lines), 0 for no differences in copy number (black line), −0.25 for losses and −1.2 for homozygous copy losses (red lines). In the same boxes, each dot represents one probe, and the colors of the dots are a way of representing different chromosomes. In the yellow boxes above the graph, we indicate the genes that, among those affected by SNV/indels, were the most recurrently affected by CNAs. The genes highlighted in bold, within these boxes, are the ones with the highest number of amplifications or homozygous copy losses. Images were obtained from Nexus Copy Number software version 9.0. Full article ">Figure 5
Complex chromosomal rearrangements revealed by CNA events identified in osteosarcomas. The type of event, chromoanasynthesis or chromothripsis, is indicated, as well as the affected chromosomes and sample IDs (x-axis), together with the log2 sample/reference ratio thresholds (y-axis): 0.25 for gains and 1.2 for high copy gains (blue lines), 0 for no differences in copy number (black line), −0.25 for losses and −1.2 for homozygous copy losses (red lines). Each dot represents one probe, and the colors of the dots are a way of representing different chromosomes. Images were obtained from Nexus Copy Number software version 9.0. Full article ">

21 pages, 3811 KiB

Open AccessArticle

Molecular BCR::ABL1 Quantification and ABL1 Mutation Detection as Essential Tools for the Clinical Management of Chronic Myeloid Leukemia Patients: Results from a Brazilian Single-Center Study

by Anelis Maria Marin, Denise Kusma Wosniaki, Heloisa Bruna Soligo Sanchuki, Eduardo Cilião Munhoz, Jeanine Marie Nardin, Gabriela Silva Soares, Dhienifer Caroline Espinace, João Samuel de Holanda Farias, Bruna Veroneze, Luiz Felipe Becker, Guilherme Lima Costa, Olair Carlos Beltrame, Jaqueline Carvalho de Oliveira, Geison Cambri, Dalila Luciola Zanette and Mateus Nóbrega Aoki

Int. J. Mol. Sci. 2023, 24(12), 10118; https://doi.org/10.3390/ijms241210118 - 14 Jun 2023

Cited by 3 | Viewed by 2478

Abstract

Chronic myeloid leukemia (CML) is a well-characterized oncological disease in which virtually all patients possess a translocation (9;22) that generates the tyrosine kinase BCR::ABL1 protein. This translocation represents one of the milestones in molecular oncology in terms of both diagnostic and prognostic evaluations. [...] Read more.

Chronic myeloid leukemia (CML) is a well-characterized oncological disease in which virtually all patients possess a translocation (9;22) that generates the tyrosine kinase BCR::ABL1 protein. This translocation represents one of the milestones in molecular oncology in terms of both diagnostic and prognostic evaluations. The molecular detection of the BCR::ABL1 transcription is a required factor for CML diagnosis, and its molecular quantification is essential for assessing treatment options and clinical approaches. In the CML molecular context, point mutations on the ABL1 gene are also a challenge for clinical guidelines because several mutations are responsible for tyrosine kinase inhibitor resistance, indicating that a change may be necessary in the treatment protocol. So far, the European LeukemiaNet and the National Comprehensive Cancer Network (NCCN) have presented international guidelines on CML molecular approaches, especially those related to BCR::ABL1 expression. In this study, we show almost three years’ worth of data regarding the clinical treatment of CML patients at the Erasto Gaertner Hospital, Curitiba, Brazil. These data primarily comprise 155 patients and 532 clinical samples. BCR::ABL1 quantification by a duplex-one-step RT-qPCR and ABL1 mutations detection were conducted. Furthermore, digital PCR for both BCR::ABL1 expression and ABL1 mutations were conducted in a sub-cohort. This manuscript describes and discusses the clinical importance and relevance of molecular biology testing in Brazilian CML patients, demonstrating its cost-effectiveness. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Figure 1
Linear regression of limit of quantification for BCR::ABL1 (A) and ABL1 (B) demonstrating that 500 copies for both targets show an r2 > 0.99. Linear regression for BCR::ABL1 (C) and ABL1 (D) quantification using RNA from KCL-22 cell line standard curve, where amplification efficiency was 90% and 87%, respectively. Full article ">Figure 2
CML clinical samples per patients, indicating that most patients had three and two clinical samples, while few patients had six or more. Full article ">Figure 3
(A) BCR::ABL1 quantification in CML patients that respond well to TKI treatment, as shown by it decreasing levels according to the sequence of analyzed samples. (B) BCR::ABL1 quantification in patients requiring a change in the TKI used. The arrow represents the last clinical samples before imatinib was discontinued. (C) Refractory CML patients where BCR::ABL1 expression are oscillating at a low level, where each color line represents one patient. Full article ">Figure 4
CML patients according to TFR distribution: 6 patients are actual under TFR—3.8%; 14 patients are in DMR or undetected BCR::ABL1 expression in one-year follow-up—9%; 19 patients presents TFR requirements and eligible for imatinib discontinuation—12.2%; 116 patients are under TKIs treatment and not eligible for TFR—75%. Full article ">Figure 5
Representative images from dPCR detection of BCR::ABL1 in three samples. (A) Signalmap of ABL1 and BCR::ABL1. Each green spot represents one of 26,000 partitions per well, in which amplification occurred; (B) Scatterplot. In the abscissa are the analyzed partitions, where each gray or blue spot represents one of 26,000 partitions per well (scale 0 to 26,000). The red line is the threshold that is automatically set by the analysis software QIAcuity Software Suite v2.1.7.182. The spots below this line (gray) are from the negative partitions, while the spots above (blue) represent the positives partitions for the target. Full article ">Figure 6
Representative images from dPCR detection of T315I from three samples. (A) Signalmap of C (wild type) and T (mutant) bases. Each green spot represents one of 26,000 partitions per well, in which amplification occurred: (B) Scatterplot. In the abscissa are the analyzed partitions, where each gray or blue spot represents one of 26,000 partitions per well (scale 0 to 26,000). The red line is the threshold that is automatically set by the analysis software QIAcuity Software Suite v2.1.7.182. The spots below this line are from the negative partitions, while the spots above represent the positives partitions for the target. Full article ">Figure 7
Cost-saving perspective with molecular BCR-ABL quantification in TFR patients for 10 years in Erasto Gaertner Hospital, reaching about $650,000.00 in 5 years and $1,200,000.00 in 10 years. Full article ">

15 pages, 2268 KiB

Open AccessArticle

Glyphosate and Aminomethylphosphonic Acid (AMPA) Modulate Glutathione S-Transferase in Non-Tumorigenic Prostate Cells

by Dayanne Silva Borges, Lara Vecchi, Deysse Carla Tolentino Barros, Vinícius Marques Arruda, Helen Soares Valença Ferreira, Matheus Fernandes da Silva, Joyce Ferreira da Costa Guerra, Raoni Pais Siqueira and Thaise Gonçalves Araújo

Int. J. Mol. Sci. 2023, 24(7), 6323; https://doi.org/10.3390/ijms24076323 - 28 Mar 2023

Viewed by 1653

Abstract

Glyphosate (GLY) was developed in the early 1970s and has become the most used broad-spectrum herbicide in the world so far. Its main metabolite is aminomethylphosphonic acid (AMPA), and the accumulation of GLY and its derivative compounds raises some concerns regarding possible health [...] Read more.

Glyphosate (GLY) was developed in the early 1970s and has become the most used broad-spectrum herbicide in the world so far. Its main metabolite is aminomethylphosphonic acid (AMPA), and the accumulation of GLY and its derivative compounds raises some concerns regarding possible health outcomes. In this study, we aimed to evaluate the effects of GLY and AMPA on prostate cell lines by evaluating cell viability, proliferation, gene and protein expression, and cellular pathways involved in the response to oxidative stress. Our results indicated that GLY and AMPA reduced the cell viability of tumorigenic and non-tumorigenic prostate cell lines only at higher concentrations (10 mM GLY and 20 mM AMPA). In contrast, both compounds increased the clonogenicity of non-tumorigenic PNT2 cells, mainly at concentrations below the IC₅₀ (5 mM GLY and 10 mM AMPA). Moreover, treatment of non-tumorigenic cells with low concentrations of GLY or AMPA for 48 h increased GSTM3 expression at both mRNA and protein levels. In contrast, the treatments decrease the GST activity and induced an increase in oxidative stress, mainly at lower concentrations. Therefore, both compounds can cause cellular damage even at lower concentrations in non-tumorigenic PNT2 cells, mainly affecting cell proliferation and oxidative stress. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
Effects of glyphosate (GLY) and aminomethylphosphonic acid (AMPA) on the viability and proliferation of prostate cell lines. (A) MTT assay was conducted for 24 and 48 h on PNT2 (non-tumorigenic), LNCaP (hormone-dependent tumorigenic), and PC-3 (hormone-independent tumorigenic) cell lines treated with GLY and AMPA. Lowercase letters over graph lines represent significant differences between cell lines: (a) PNT2 × Control (untreated cells), (b) LNCaP × Control, (c) PC-3 × Control, (d) PNT2 × LNCaP, (e) PNT2 × PC-3, (f) LNCaP × PC-3. The green-dashed line corresponds to 50% cell viability. (B) The colony formation assay was performed to evaluate the effect of GLY and AMPA on PNT2 cell proliferation (crystal violet staining). * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. Results (A,B) are expressed as means ± standard deviation of three independent tests performed in triplicate. Full article ">Figure 1 Cont.
Effects of glyphosate (GLY) and aminomethylphosphonic acid (AMPA) on the viability and proliferation of prostate cell lines. (A) MTT assay was conducted for 24 and 48 h on PNT2 (non-tumorigenic), LNCaP (hormone-dependent tumorigenic), and PC-3 (hormone-independent tumorigenic) cell lines treated with GLY and AMPA. Lowercase letters over graph lines represent significant differences between cell lines: (a) PNT2 × Control (untreated cells), (b) LNCaP × Control, (c) PC-3 × Control, (d) PNT2 × LNCaP, (e) PNT2 × PC-3, (f) LNCaP × PC-3. The green-dashed line corresponds to 50% cell viability. (B) The colony formation assay was performed to evaluate the effect of GLY and AMPA on PNT2 cell proliferation (crystal violet staining). * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. Results (A,B) are expressed as means ± standard deviation of three independent tests performed in triplicate. Full article ">Figure 2
Glutathione S-transferase mu 3 (GSTM3) expression and enzymatic activity in PNT2 (non-tumorigenic) cells treated with glyphosate (GLY) and aminomethylphosphonic acid (AMPA) for 48 h. (A) The protein expression levels of GSTM3 were detected using western blotting. β-actin was used as the loading control. (B) Enzymatic activity of GST in cell homogenates: 3 µg of protein was analyzed in 0.1 M phosphate buffer, pH 6.5, with 0.1% Triton X-100, 0.1 M reduced glutathione (GSH), and 0.1 M 1-chloro-2,4-dinitrobenzene (CDNB) at 25 °C. Results are expressed as means ± standard deviation of three independent tests performed in triplicate. * p < 0.05, ** p < 0.01, **** p < 0.0001. Full article ">Figure 3
Protein oxidation assay and quantification of transcriptional levels of the growth arrest specific 5 (GAS5) in PNT2 cells. (A) Analysis of oxidized proteins from the PNT2 prostate cell line exposed to glyphosate (GLY) and aminomethylphosphonic acid (AMPA) for 48 h. (B) Expression of GAS5 by qPCR. β-2 microglobulin (β2M) was used as the reference. Results are expressed as means ± standard deviation of three independent tests performed in triplicate. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. Full article ">

Review

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18 pages, 1262 KiB

Open AccessReview

Molecular Profile of Intrahepatic Cholangiocarcinoma

by Wellington Andraus, Francisco Tustumi, José Donizeti de Meira Junior, Rafael Soares Nunes Pinheiro, Daniel Reis Waisberg, Liliana Ducatti Lopes, Rubens Macedo Arantes, Vinicius Rocha Santos, Rodrigo Bronze de Martino and Luiz Augusto Carneiro D’Albuquerque

Int. J. Mol. Sci. 2024, 25(1), 461; https://doi.org/10.3390/ijms25010461 - 29 Dec 2023

Cited by 4 | Viewed by 1840

Abstract

Intrahepatic cholangiocarcinoma (ICC) is a relatively uncommon but highly aggressive primary liver cancer that originates within the liver. The aim of this study is to review the molecular profile of intrahepatic cholangiocarcinoma and its implications for prognostication and decision-making. This comprehensive characterization of [...] Read more.

Intrahepatic cholangiocarcinoma (ICC) is a relatively uncommon but highly aggressive primary liver cancer that originates within the liver. The aim of this study is to review the molecular profile of intrahepatic cholangiocarcinoma and its implications for prognostication and decision-making. This comprehensive characterization of ICC tumors sheds light on the disease’s underlying biology and offers a foundation for more personalized treatment strategies. This is a narrative review of the prognostic and therapeutic role of the molecular profile of ICC. Knowing the molecular profile of tumors helps determine prognosis and support certain target therapies. The molecular panel in ICC helps to select patients for specific therapies, predict treatment responses, and monitor treatment responses. Precision medicine in ICC can promote improvement in prognosis and reduce unnecessary toxicity and might have a significant role in the management of ICC in the following years. The main mutations in ICC are in tumor protein p53 (TP53), Kirsten rat sarcoma virus (KRAS), isocitrate dehydrogenase 1 (IDH1), and AT-rich interactive domain-containing protein 1A (ARID1A). The rate of mutations varies significantly for each population. Targeting TP53 and KRAS is challenging due to the natural characteristics of these genes. Different stages of clinical studies have shown encouraging results with inhibitors of mutated IDH1 and target therapy for ARID1A downstream effectors. Fibroblast growth factor receptor 2 (FGFR2) fusions are an important target in patients with ICC. Immune checkpoint blockade can be applied to a small percentage of ICC patients. Molecular profiling in ICC represents a groundbreaking approach to understanding and managing this complex liver cancer. As our comprehension of ICC’s molecular intricacies continues to expand, so does the potential for offering patients more precise and effective treatments. The integration of molecular profiling into clinical practice signifies the dawn of a new era in ICC care, emphasizing personalized medicine in the ongoing battle against this malignancy. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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29 pages, 3891 KiB

Open AccessReview

A Strategy Utilizing Protein–Protein Interaction Hubs for the Treatment of Cancer Diseases

by Nicolas Carels, Domenico Sgariglia, Marcos Guilherme Vieira Junior, Carlyle Ribeiro Lima, Flávia Raquel Gonçalves Carneiro, Gilberto Ferreira da Silva, Fabricio Alves Barbosa da Silva, Rafaela Scardini, Jack Adam Tuszynski, Cecilia Vianna de Andrade, Ana Carolina Monteiro, Marcel Guimarães Martins, Talita Goulart da Silva, Helen Ferraz, Priscilla Vanessa Finotelli, Tiago Albertini Balbino and José Carlos Pinto

Int. J. Mol. Sci. 2023, 24(22), 16098; https://doi.org/10.3390/ijms242216098 - 8 Nov 2023

Viewed by 2161

Abstract

We describe a strategy for the development of a rational approach of neoplastic disease therapy based on the demonstration that scale-free networks are susceptible to specific attacks directed against its connective hubs. This strategy involves the (i) selection of up-regulated hubs of connectivity [...] Read more.

We describe a strategy for the development of a rational approach of neoplastic disease therapy based on the demonstration that scale-free networks are susceptible to specific attacks directed against its connective hubs. This strategy involves the (i) selection of up-regulated hubs of connectivity in the tumors interactome, (ii) drug repurposing of these hubs, (iii) RNA silencing of non-druggable hubs, (iv) in vitro hub validation, (v) tumor-on-a-chip, (vi) in vivo validation, and (vii) clinical trial. Hubs are protein targets that are assessed as targets for rational therapy of cancer in the context of personalized oncology. We confirmed the existence of a negative correlation between malignant cell aggressivity and the target number needed for specific drugs or RNA interference (RNAi) to maximize the benefit to the patient’s overall survival. Interestingly, we found that some additional proteins not generally targeted by drug treatments might justify the addition of inhibitors designed against them in order to improve therapeutic outcomes. However, many proteins are not druggable, or the available pharmacopeia for these targets is limited, which justifies a therapy based on encapsulated RNAi. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Figure 1
Schematic diagram illustrating the hub diagnosis from RNA-seq data. Full article ">Figure 2
Circular layout of a sub-network consisting of differentially expressed genes between MDA-MB-231 (Triple-Negative) and MCF10A (non-tumoral). The nodes represent genes, while the links represent interactions between genes. We only clearly display the significant differentially regulated hubs with their gene symbols. Other vertices should not be taken into account and are shown according to their UniprotKB accession number. The size of the nodes corresponds to the degree of connectivity, and the colors (green for down-regulated and red for up-regulated) indicate the differential expression pattern of genes in tumoral versus non-tumoral breast cell lines. The network was visualized using Gephi (adapted with permission from ref. [<a href="#B8-ijms-24-16098" class="html-bibr">8</a>], Copyright is licensed under an open access Creative Commons CC BY 4.0). Full article ">Figure 3
In vitro validation of the hub-based theranostic concept. In comparison to MCF10A, the top five up-regulated hubs in MDA-MB-231 were HSP90AB1, CSNK2B, TK1, YWHAB, and VIM. When these five mRNA were silenced simultaneously through siRNA interference, the growth of MDA-MB-231 was halted while that of MCF10A remained unaffected (top panel). The increase in cell death was observed by 48 h (white rectangles) as depicted by flux cytometry (middle panel). Furthermore, the metastatic potential was eliminated (bottom panel) (adapted with permission from ref. [<a href="#B16-ijms-24-16098" class="html-bibr">16</a>], Copyright is licensed under an open access Creative Commons CC BY 4.0). Full article ">Figure 4
Correlation between number of targets and 5-year OS of each cancer type (Stomach adenocarcinoma: STAD, Lung adenocarcinoma: LUAD, Lung squamous cell carcinoma: LUSC, Liver hepatocellular carcinoma: LIHC, Kidney renal clear cell carcinoma: KIRC, Kidney renal papillary cell carcinoma: KIRP, Breast invasive carcinoma: BRCA, Thyroid cancer: THCA, Prostate cancer: PRAD) (adapted with permission from ref. [<a href="#B17-ijms-24-16098" class="html-bibr">17</a>], Copyright is licensed under an open access Creative Commons CC BY 4.0). Full article ">Figure 5
Principal component analysis (PCA) representation of the variance associated with cancer aggressiveness considering the WNT and cross-linked pathways showing a clear division of cancer types into H (red: STAD: stomach adenocarcinoma, LUSC: lung squamous cell carcinoma, LIHC: liver hepatocellular carcinoma) and L (green: KIRP: kidney renal papillary cell carcinoma, THCA: thyroid cancer, and PRAD: prostate cancer) classes according to PC3 (adapted with permission from ref. [<a href="#B23-ijms-24-16098" class="html-bibr">23</a>], Copyright is licensed under an open access Creative Commons CC BY 4.0). Full article ">Figure 6
Epigenetic landscape and attractors (adapted with permission from [<a href="#B30-ijms-24-16098" class="html-bibr">30</a>]). Full article ">Figure 7
A three-dimensional (A) and a two-dimensional grid (B) were used to plot an energy landscape depicting both control and tumor attractors, as well as samples (adapted with permission from ref. [<a href="#B27-ijms-24-16098" class="html-bibr">27</a>], Copyright is licensed under an open access Creative Commons CC BY 4.0). Full article ">Figure 8
Three-dimensional visualization of full trajectories in a three-subtype marker space of glioblastoma multiforme. Each axis shows the expression values of a specific marker gene, while each line corresponds to the complete time of the three trajectories analyzed. Each color or letter denotes the corresponding basin (adapted with permission from ref. [<a href="#B34-ijms-24-16098" class="html-bibr">34</a>], Copyright is licensed under an open access Creative Commons CC-BY-NC-ND 4.0). Full article ">

33 pages, 2916 KiB

Open AccessReview

Deciphering the Functional Status of Breast Cancers through the Analysis of Their Extracellular Vesicles

by Alexis Germán Murillo Carrasco, Andreia Hanada Otake, Janaina Macedo-da-Silva, Veronica Feijoli Santiago, Giuseppe Palmisano, Luciana Nogueira de Sousa Andrade and Roger Chammas

Int. J. Mol. Sci. 2023, 24(16), 13022; https://doi.org/10.3390/ijms241613022 - 21 Aug 2023

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Abstract

Breast cancer (BC) accounts for the highest incidence of tumor-related mortality among women worldwide, justifying the growing search for molecular tools for the early diagnosis and follow-up of BC patients under treatment. Circulating extracellular vesicles (EVs) are membranous nanocompartments produced by all human [...] Read more.

Breast cancer (BC) accounts for the highest incidence of tumor-related mortality among women worldwide, justifying the growing search for molecular tools for the early diagnosis and follow-up of BC patients under treatment. Circulating extracellular vesicles (EVs) are membranous nanocompartments produced by all human cells, including tumor cells. Since minimally invasive methods collect EVs, which represent reservoirs of signals for cell communication, these particles have attracted the interest of many researchers aiming to improve BC screening and treatment. Here, we analyzed the cargoes of BC-derived EVs, both proteins and nucleic acids, which yielded a comprehensive list of potential markers divided into four distinct categories, namely, (i) modulation of aggressiveness and growth; (ii) preparation of the pre-metastatic niche; (iii) epithelial-to-mesenchymal transition; and (iv) drug resistance phenotype, further classified according to their specificity and sensitivity as vesicular BC biomarkers. We discuss the therapeutic potential of and barriers to the clinical implementation of EV-based tests, including the heterogeneity of EVs and the available technologies for analyzing their content, to present a consistent, reproducible, and affordable set of markers for further evaluation. Full article

(This article belongs to the Special Issue State-of-the-Art Molecular Oncology in Brazil 2.0)

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Figure 1

Figure 1
Challenges and perspectives regarding omics research on BC-derived EVs. This review presents the current state of the art of the most-studied omics topics on EVs from BC, namely, transcriptomics and proteomics. However, we must fill omics-related gaps before proposing reliable EV-based tools for this disease. Here, we cited some challenges for future research. As vesicles are heterogeneous in terms of size, biogenesis, and cargo, authors must standardize the reporting of methods for the isolation, quantification, characterization, and profiling of EVs. Furthermore, consistent findings in relation to EVs are characterized by their ability to be replicated. Nevertheless, many studies use targeted analysis approaches, which can bias observations. In addition, such replicability must be related to characterizing different individuals of the same subgroup or cell lines of the same subtype. To evaluate this correctly, it is necessary to increase the number of studies comparing less-studied BC cell lines and include a translational approach between tumor cell markers and their vesicular pairs. Regarding associations with the subtype of BC patients, there are gaps produced by the lack of available information about the molecular or clinical profiles of these patients, which can complicate future secondary analysis. After conquering this challenge, we can promisingly combine data from different omics studies of BC-derived EVs and select potentially tumor-derived EVs via liquid biopsies from patients to debug or edit these vesicles and induce a beneficial effect in BC patients. Image created on BioRender.com. Full article ">Figure 2
Extracellular vesicle (EV) miRNAs in breast-cancer-related studies. Sankey plots show the number of studies mentioning each relevant vesicular miRNA from cell supernatant (A) or human bodily fluids (B). The cell lines in which the EV cargo was analyzed are classified into the main BC subtypes following the criteria given in Dai et al.’s (2017) study [<a href="#B124-ijms-24-13022" class="html-bibr">124</a>]. For studies on EVs collected from BC patients, the subtype information was retrieved from each study. H: Her2, TNA: Triple-Negative A, TNB: Triple-Negative B, LA: Luminal A, and LB: Luminal B. Full article ">Figure 3
Relevant putative markers in BC-derived EVs. Breast cancer cells produce a great diversity of EVs. These EVs can be classified into subpopulations based on their proteomic and transcriptomic cargo. In this review, we associate some BC-derived EV subpopulations with tumor-related functions. In addition, we include putative markers related to their types (miRNA, lncRNA, mRNA, circRNA, or protein) for each subpopulation. Image created on <a href="http://BioRender.com" target="_blank">BioRender.com</a>. Full article ">Figure 4
Extracellular vesicle (EVs) proteins in breast cancer proteome studies. (A) The most frequently identified proteins in the evaluated studies. The donut graph shows the corresponding subcellular locations. (B) Subcellular localization of proteins identified in EVs in at least two studies. (C) Cell-cycle-related and p53 pathways in which EV proteins participate. Full article ">

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