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Cancer Genomics & Proteomics 2024Uveal melanoma is an ocular malignancy whose prognosis severely worsens following metastasis. In order to improve the understanding of molecular physiology of metastatic...
BACKGROUND/AIM
Uveal melanoma is an ocular malignancy whose prognosis severely worsens following metastasis. In order to improve the understanding of molecular physiology of metastatic uveal melanoma, we identified genes and pathways implicated in metastatic vs non-metastatic uveal melanoma.
PATIENTS AND METHODS
A previously published dataset from Gene Expression Omnibus (GEO) was used to identify differentially expressed genes between metastatic and non-metastatic samples as well as to conduct pathway and perturbagen analyses using Gene Set Enrichment Analysis (GSEA), EnrichR, and iLINCS.
RESULTS
In male metastatic uveal melanoma samples, the gene LOC401052 is significantly down-regulated and FHDC1 is significantly up-regulated compared to non-metastatic male samples. In female samples, no significant differently expressed genes were found. Additionally, we identified many significant up-regulated immune response pathways in male metastatic uveal melanoma, including "T cell activation in immune response". In contrast, many top up-regulated female pathways involve iron metabolism, including "heme biosynthetic process". iLINCS perturbagen analysis identified that both male and female samples have similar discordant activity with growth factor receptors, but only female samples have discordant activity with progesterone receptor agonists.
CONCLUSION
Our results from analyzing genes, pathways, and perturbagens demonstrate differences in metastatic processes between sexes.
Topics: Humans; Uveal Neoplasms; Melanoma; Female; Male; Gene Expression Profiling; Neoplasm Metastasis; Gene Expression Regulation, Neoplastic; Transcriptome; Sex Factors
PubMed: 38944422
DOI: 10.21873/cgp.20452 -
Cancer Genomics & Proteomics 2024It has been recently demonstrated that a methionine-restricted diet increases the response to immune checkpoint inhibitors (ICIs) via an increase in PD-L1 in a syngeneic...
BACKGROUND/AIM
It has been recently demonstrated that a methionine-restricted diet increases the response to immune checkpoint inhibitors (ICIs) via an increase in PD-L1 in a syngeneic mouse colorectal-cancer model. Our laboratory has developed recombinant methioninase (rMETase) to restrict methionine. The aim of the present study was to determine if rMETase can increase PD-L1 expression in a human colorectal cancer cell line in vitro.
MATERIALS AND METHODS
We evaluated the half-maximal inhibitory concentration (IC) value of rMETase on HCT-116 human colorectal cancer cells. HCT-116 cells were treated with rMETase at the IC Western immunoblotting was used to compare PD-L1 expression in HCT-116 cells treated with and without rMETase.
RESULTS
The IC value of rMETase on HCT-116 was 0.79 U/ml. Methionine restriction using rMETase increased PD-L1 expression compared to the untreated control (p<0.05).
CONCLUSION
Methionine restriction with rMETase up-regulates PD-L1 expression in human colorectal cancer cells and the combination of rMETase and ICIs may have the potential to improve immunotherapy in human colorectal cancer.
Topics: Humans; Carbon-Sulfur Lyases; Methionine; B7-H1 Antigen; Colorectal Neoplasms; Recombinant Proteins; HCT116 Cells
PubMed: 38944421
DOI: 10.21873/cgp.20457 -
Cancer Genomics & Proteomics 2024Aggressive breast cancer (BC) cells show high expression of Rho GTPase activating protein 29 (ARHGAP29), a negative regulator of RhoA. In breast cancer cells in which...
ARHGAP29 Is Involved in Increased Invasiveness of Tamoxifen-resistant Breast Cancer Cells and its Expression Levels Correlate With Clinical Tumor Parameters of Breast Cancer Patients.
BACKGROUND/AIM
Aggressive breast cancer (BC) cells show high expression of Rho GTPase activating protein 29 (ARHGAP29), a negative regulator of RhoA. In breast cancer cells in which mesenchymal transformation was induced, ARHGAP29 was the only one of 32 GTPase-activating enzymes whose expression increased significantly. Therefore, we investigated whether there is a correlation between expression of ARHGAP29 and tumor progression in BC. Since tamoxifen-resistant BC cells exhibit increased mesenchymal properties and invasiveness, we additionally investigated the relationship between ARHGAP29 and increased invasion rate in tamoxifen resistance. The question arises as to whether ARHGAP29 is a suitable prognostic marker for the progression of BC.
MATERIALS AND METHODS
Tissue microarrays were used to investigate expression of ARHGAP29 in BC and adjacent normal breast tissues. Knockdown experiments using siRNA were performed to investigate the influence of ARHGAP29 and the possible downstream actors RhoC and pAKT1 on invasive growth of tamoxifen-resistant BC spheroids in vitro.
RESULTS
Expression of ARHGAP29 was frequently increased in BC tissues compared to adjacent normal breast tissues. In addition, there was evidence of a correlation between high ARHGAP29 expression and advanced clinical tumor stage. Tamoxifen-resistant BC cells show a significantly higher expression of ARHGAP29 compared to their parental wild-type cells. After knockdown of ARHGAP29 in tamoxifen-resistant BC cells, expression of RhoC was significantly reduced. Further, expression of pAKT1 decreased significantly. Invasive growth of three-dimensional tamoxifen-resistant BC spheroids was reduced after knockdown of ARHGAP29. This could be partially reversed by AKT1 activator SC79.
CONCLUSION
Expression of ARHGAP29 correlates with the clinical tumor parameters of BC patients. In addition, ARHGAP29 is involved in increased invasiveness of tamoxifen-resistant BC cells. ARHGAP29 alone or in combination with its downstream partners RhoC and pAKT1 could be suitable prognostic markers for BC progression.
Topics: Humans; Tamoxifen; Breast Neoplasms; GTPase-Activating Proteins; Female; Drug Resistance, Neoplasm; Neoplasm Invasiveness; Middle Aged; Gene Expression Regulation, Neoplastic; Prognosis; Antineoplastic Agents, Hormonal; Biomarkers, Tumor; Cell Line, Tumor; rhoC GTP-Binding Protein
PubMed: 38944420
DOI: 10.21873/cgp.20454 -
Cancer Genomics & Proteomics 2024Metastatic prostate cancer (mPCa) results in high morbidity and mortality. Visceral metastases in particular are associated with a shortened survival. Our aim was to...
BACKGROUND/AIM
Metastatic prostate cancer (mPCa) results in high morbidity and mortality. Visceral metastases in particular are associated with a shortened survival. Our aim was to unravel the molecular mechanisms that underly pulmonary spread in mPCa.
MATERIALS AND METHODS
We performed a comprehensive transcriptomic analysis of PCa lung metastases, followed by functional validation of candidate genes. Digital gene expression analysis utilizing the NanoString technology was performed on mRNA extracted from formalin-fixed, paraffin-embedded (FFPE) tissue from PCa lung metastases. The gene expression data from primary PCa and PCa lung metastases were compared, and several publicly available bioinformatic analysis tools were used to annotate and validate the data.
RESULTS
In PCa lung metastases, 234 genes were considerably up-regulated, and 78 genes were significantly down-regulated when compared to primary PCa. Carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) was identified as suitable candidate gene for further functional validation. CEACAM6 as a cell adhesion molecule has been implicated in promoting metastatic disease in several solid tumors, such as colorectal or gastric cancer. We showed that siRNA knockdown of CEACAM6 in PC-3 and LNCaP cells resulted in decreased cell viability and migration as well as enhanced apoptosis. Comprehensive transcriptomic analyses identified several genes of interest that might promote metastatic spread to the lung.
CONCLUSION
Functional validation revealed that CEACAM6 might play an important role in fostering metastatic spread to the lung of PCa patients via enhancing proliferation, migration and suppressing apoptosis in PC-3 and LNCaP cells. CEACAM6 might pose an attractive therapeutic target to prevent metastatic disease.
Topics: Humans; Male; Apoptosis; Cell Adhesion Molecules; Cell Proliferation; Cell Movement; Lung Neoplasms; Antigens, CD; Prostatic Neoplasms; GPI-Linked Proteins; Gene Expression Regulation, Neoplastic; Cell Line, Tumor
PubMed: 38944419
DOI: 10.21873/cgp.20459 -
Insect Biochemistry and Molecular... Jun 2024The larvae of the moth Hyalophora cecropia spin silk cocoons with morphologically distinct layers. We investigated the expression of the individual silk protein...
The larvae of the moth Hyalophora cecropia spin silk cocoons with morphologically distinct layers. We investigated the expression of the individual silk protein components of these cocoons in relation to the morphology of the silk gland and its affiliation to the different layers of the cocoon. The study used transcriptomic and proteomic analyses to identify 91 proteins associated with the silk cocoons, 63 of which have a signal peptide indicating their secretory nature. We checked the specificity of their expression in different parts of the SG and the presence of the corresponding protein products in each cocoon layer. Differences were observed among less abundant proteins with unclear functions. The representation of proteins in the inner envelope and intermediate space was similar, except for a higher proportion of probable contaminating proteins, mostly originating from the gut. On the other hand, the outer envelope contains a number of putative enzymes with unclear function. However, the protein most specific to the outer layer has sequence homology to putative serine/threonine kinase-like proteins and some adhesive proteins, and its closest homolog in Bombyx mori was found in the scaffold silk. This research provides valuable insights into the silk production of the cecropia moth, highlighting both similarities and differences to other moth species.
PubMed: 38944399
DOI: 10.1016/j.ibmb.2024.104152 -
Biotechnology Advances Jun 2024Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the interrelations between genotype, phenotype, and external environment. The recent... (Review)
Review
Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the interrelations between genotype, phenotype, and external environment. The recent advancement of high-throughput experimental approaches and multi-omics strategies has generated a plethora of new and precise information from wide-ranging biological domains. On the other hand, the continuously growing field of machine learning (ML) and its specialized branch of deep learning (DL) provide essential computational architectures for decoding complex and heterogeneous biological data. In recent years, both multi-omics and ML have assisted in the escalation of CBM. Condition-specific omics data, such as transcriptomics and proteomics, helped contextualize the model prediction while analyzing a particular phenotypic signature. At the same time, the advanced ML tools have eased the model reconstruction and analysis to increase the accuracy and prediction power. However, the development of these multi-disciplinary methodological frameworks mainly occurs independently, which limits the concatenation of biological knowledge from different domains. Hence, we have reviewed the potential of integrating multi-disciplinary tools and strategies from various fields, such as synthetic biology, CBM, omics, and ML, to explore the biochemical phenomenon beyond the conventional biological dogma. How the integrative knowledge of these intersected domains has improved bioengineering and biomedical applications has also been highlighted. We categorically explained the conventional genome-scale metabolic model (GEM) reconstruction tools and their improvement strategies through ML paradigms. Further, the crucial role of ML and DL in omics data restructuring for GEM development has also been briefly discussed. Finally, the case-study-based assessment of the state-of-the-art method for improving biomedical and metabolic engineering strategies has been elaborated. Therefore, this review demonstrates how integrating experimental and in silico strategies can help map the ever-expanding knowledge of biological systems driven by condition-specific cellular information. This multiview approach will elevate the application of ML-based CBM in the biomedical and bioengineering fields for the betterment of society and the environment.
PubMed: 38944218
DOI: 10.1016/j.biotechadv.2024.108400 -
The Journal of Biological Chemistry Jun 2024Iron-sulfur (Fe-S) clusters are required for essential biological pathways, including respiration and isoprenoid biosynthesis. Complex Fe-S cluster biogenesis systems...
Iron-sulfur (Fe-S) clusters are required for essential biological pathways, including respiration and isoprenoid biosynthesis. Complex Fe-S cluster biogenesis systems have evolved to maintain an adequate supply of this critical protein cofactor. In Escherichia coli, two Fe-S biosynthetic systems, the "housekeeping" Isc and "stress responsive" Suf pathways, interface with a network of cluster trafficking proteins, such as ErpA, IscA, SufA, and NfuA. GrxD, a Fe-S cluster-binding monothiol glutaredoxin, also participates in Fe-S protein biogenesis in both prokaryotes and eukaryotes. Previous studies in E. coli showed that the ΔgrxD mutation causes sensitivity to iron depletion, spotlighting a critical role for GrxD under conditions that disrupt Fe-S homeostasis. Here, we utilized a global chemoproteomic mass spectrometry (MS) approach to analyse the contribution of GrxD to the Fe-S proteome. Our results demonstrate that 1) GrxD is required for biogenesis of a specific subset of Fe-S proteins under iron-depleted conditions, 2) GrxD is required for cluster delivery to ErpA under iron limitation, 3) GrxD is functionally distinct from other Fe-S trafficking proteins and, 4) GrxD Fe-S cluster binding is responsive to iron limitation. All these results lead to the proposal that GrxD is required to maintain Fe-S cluster delivery to the essential trafficking protein ErpA during iron limitation conditions.
PubMed: 38944118
DOI: 10.1016/j.jbc.2024.107506 -
Biochimie Jun 2024The Loxosceles genus represents one of the main arachnid genera of medical importance in Brazil. Despite the gravity of Loxosceles-related accidents, just a handful of...
The Loxosceles genus represents one of the main arachnid genera of medical importance in Brazil. Despite the gravity of Loxosceles-related accidents, just a handful of species are deemed medically important and only a few have undergone comprehensive venom characterization. Loxosceles amazonica is a notable example of a potentially dangerous yet understudied Loxosceles species. While there have been limited reports of accidents involving L. amazonica to date, accidents related to Loxosceles are increasing in the North and Northeast regions of Brazil, where L. amazonica has been reported. In this work, we provide a complementary biochemical and immunological characterization of L. amazonica venom, considering its most relevant enzymatic activities and its immunorecognition and neutralization by current therapeutic antivenoms. Additionally, a cDNA library enriched with phospholipase D (PLD) sequences from L. amazonica venom glands was built and subsequently sequenced. The results showed that L. amazonica venom is well immunorecognised by all the tested antibodies. Its venom also displayed proteolytic, hyaluronidase, and sphingomyelinase activities. These activities were at least partially inhibited by available antivenoms. With cDNA sequencing of PLDs, seven new putative isoforms were identified in the venom of L. amazonica. These results contribute to a better knowledge of the venom content and activities of a synanthropic, yet understudied, Loxosceles species. In vivo assays are essential to confirm the medical relevance of L. amazonica, as well as to assess its true toxic potential and elucidate its related pathophysiology.
PubMed: 38944106
DOI: 10.1016/j.biochi.2024.06.012 -
Biochimica Et Biophysica Acta. Proteins... Jun 2024In proteomic studies, the reliability and reproducibility of results hinge on well-executed protein extraction and digestion protocols. Here, we systematically compared...
In proteomic studies, the reliability and reproducibility of results hinge on well-executed protein extraction and digestion protocols. Here, we systematically compared three established digestion methods for macrophages, namely filter-assisted sample preparation (FASP), in-solution, and in-gel digestion protocols. We also compared lyophilization and manual lysis for liver tissue protein extraction, each of them tested using either sodium deoxycholate (SDC)- or RIPA-based lysis buffer. For the macrophage cell line, FASP using passivated filter units outperformed the other tested methods regarding the number of identified peptides and proteins. However, a careful standardization has shown that all three methods can yield robust results across a wide range of starting material (even starting with 1 μg of proteins). Importantly, inter and intra-day variances were determined for all sample preparation protocols. Thus, the median inter-day CVs for in-solution, in-gel and FASP protocols were respectively 10, 8 and 9%, very similar to the median CVs obtained for the intra-day analysis (9, 8 and 8%, respectively). Moreover, FASP digestion presented 80% of proteins with a CV lower than 25%, followed closely by in-gel digestion (78%) and in-solution sample preparation (72%) protocols. For tissue proteomics, both manual lysis and lyophilization presented similar proteome coverage and reproducibility, but the efficiency of protein extraction depended on the lysis buffer used, with RIPA buffer showing better results. In conclusion, although each sample preparation method has its own particularity, they are all suited for successful proteomic experiments if a careful standardization of the sample preparation workflow is carried out.
PubMed: 38944097
DOI: 10.1016/j.bbapap.2024.141030 -
Developmental Cell Jun 2024We describe a next-generation Drosophila protein interaction map-"DPIM2"-established from affinity purification-mass spectrometry of 5,805 baits, covering the largest...
We describe a next-generation Drosophila protein interaction map-"DPIM2"-established from affinity purification-mass spectrometry of 5,805 baits, covering the largest fraction of the Drosophila proteome. The network contains 32,668 interactions among 3,644 proteins, organized into 632 clusters representing putative functional modules. Our analysis expands the pool of known protein interactions in Drosophila, provides annotation for poorly studied genes, and postulates previously undescribed protein interaction relationships. The predictive power and functional relevance of this network are probed through the lens of the Notch signaling pathway, and we find that newly identified members of complexes that include known Notch modifiers can also modulate Notch signaling. DPIM2 allows direct comparisons with a recently published human protein interaction network, defining the existence of functional interactions conserved across species. Thus, DPIM2 defines a valuable resource for predicting protein co-complex memberships and functional associations as well as generates functional hypotheses regarding specific protein interactions.
PubMed: 38944040
DOI: 10.1016/j.devcel.2024.06.002