Identification of prognostic biomarkers for breast cancer brain metastases based on the bioinformatics analysis

PurposeThe prognosis of breast cancer (BC) patients who develop into brain metastases (BMs) is very poor. Thus, it is of great significance to explore the etiology of BMs in BC and identify the key genes involved in this process to improve the survival of BC patients with BMs.Patients and methodsThe gene expression data and the clinical information of BC patients were downloaded from TCGA and GEO database. Differentially expressed genes (DEGs) in TCGA-BRCA and GSE12276 were overlapped to find differentially expressed metastatic genes (DEMGs). The protein-protein interaction (PPI) network of DEMGs was constructed via STRING database. ClusterProfiler R package was applied to perform the gene ontology (GO) enrichment analysis of DEMGs. The univariate Cox regression analysis and the Kaplan-Meier (K-M) curves were plotted to screen DEMGs associated with the overall survival and the metastatic recurrence survival, which were identified as the key genes associated with the BMs in BC. The immune infiltration and the expressions of immune checkpoints for BC patients with brain relapses and BC patients with other relapses were analyzed respectively. The correlations among the expressions of key genes and the differently infiltrated immune cells or the differentially expressed immune checkpoints were calculated. The gene set enrichment analysis (GSEA) of each key gene was conducted to investigate the potential mechanisms of key genes involved in BC patients with BMs. Moreover, CTD database was used to predict the drug-gene interaction network of key genes.ResultsA total of 154 DEGs were identified in BC patients at M0 and M1 in TCGA database. A total of 667 DEGs were identified in BC patients with brain relapses and with other relapses. By overlapping these DEGs, 17 DEMGs were identified, which were enriched in the cell proliferation related biological processes and the immune related molecular functions. The univariate Cox regression analysis and the Kaplan-Meier curves revealed that CXCL9 and GPR171 were closely associated with the overall survival and the metastatic recurrence survival and were identified as key genes associated with BMs in BC. The analyses of immune infiltration and immune checkpoint expressions showed that there was a significant difference of the immune microenvironment between brain relapses and other relapses in BC. GSEA indicated that CXCL9 and GPR171 may regulate BMs in BC via the immune-related pathways.ConclusionOur study identified the key genes associated with BMs in BC patients and explore the underlying mechanisms involved in the etiology of BMs in BC. These findings may provide a promising approach for the treatments of BC patients with BMs.     

Differential expression patterns of phospholipase D isoforms 1 and 2 in the mammalian brain and retina

Phosphatidic acid is a key signaling molecule heavily implicated in exocytosis due to its protein-binding partners and propensity to induce negative membrane curvature. One phosphatidic acid-producing enzyme, phospholipase D (PLD), has also been implicated in neurotransmission. Unfortunately, due to the unreliability of reagents, there has been confusion in the literature regarding the expression of PLD isoforms in the mammalian brain which has hampered our understanding of their functional roles in neurons. To address this, we generated epitope-tagged PLD1 and PLD2 knockin mice using CRISPR/Cas9. Using these mice, we show that PLD1 and PLD2 are both localized at synapses by adulthood, with PLD2 expression being considerably higher in glial cells and PLD1 expression predominating in neurons. Interestingly, we observed that only PLD1 is expressed in the mouse retina, where it is found in the synaptic plexiform layers. These data provide critical information regarding the localization and potential role of PLDs in the central nervous system.     

Prediction of response and adverse drug reaction of pemetrexed plus platinum-based chemotherapy in lung adenocarcinoma by serum metabolomic profiling

BackgroundPemetrexed plus platinum doublet chemotherapy regimen remains to be the standard first-line treatment for lung adenocarcinoma patients. However, few biomarkers can be used to identify potential beneficiaries with maximal efficacy and minimal toxicity. This study aimed to explore potential biomarker models predictive of efficacy and toxicity after pemetrexed plus platinum chemotherapy based on metabolomics profiling.MethodsA total of 144 patients who received at least two cycles of pemetrexed plus platinum chemotherapy were enroled in the study. Serum samples were collected before initial treatment to perform metabolomics profiling analysis. Logistic regression analysis was performed to establish prediction models.Results157 metabolites were found to be differentially expressed between the response group and the nonresponse group. A panel of Phosphatidylserine 20:4/20:1, Sphingomyelin d18:1/18:0, and Phosphatidic Acid 18:1/20:0 could predict pemetrexed and platinum chemotherapy response with an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.7968. 76 metabolites were associated with hematological toxicity of pemetrexed plus platinum chemotherapy. A panel incorporating triglyceride 14:0/22:3/22:5, 3-(3-Hydroxyphenyl) Propionate Acid, and Carnitine C18:0 was the best predictive ability of hematological toxicity with an AUROC of 0.7954. 54 differential expressed metabolites were found to be associated with hepatotoxicity of pemetrexed plus platinum chemotherapy. A model incorporating stearidonic acid, Thromboxane B3, l-Homocitrulline, and phosphoinositide 20:3/18:0 showed the best predictive ability of hepatotoxicity with an AUROC of 0.8186.ConclusionsThis study established effective and convenient models that can predict the efficacy and toxicity of pemetrexed plus platinum chemotherapy in lung adenocarcinoma patients before treatment delivery.     

Spatiotemporal expression of sonic hedgehog signalling molecules in the embryonic mesencephalic dopaminergic neurons

Midbrain dopaminergic neurons (mDA) play an important role in controlling the voluntary motor movement, reward, and emotion-based behaviour. Differentiation of mDA neurons from progenitors depends on several secreted proteins, such as sonic hedgehog (SHH). The present study attempted to elucidate the possible role(s) of some SHH signaling components (Ptch1, Gli1, Gli2 and Gli3) in the spatiotemporal development of mDA neurons along the rostrocaudal axis of the midbrain and their possible roles in differentiation and survival of mDA neurons and the significance of using in vitro models for studying the development of mDA neurons. At E12 and E14, only Ptch1 and Gli1 were expressed in ventrolateral midbrain domains. All examined SHH signalling molecules were not detected in mDA area. Whereas, in MN9D cells, many SHH signalling molecules were expressed and co-localized with the dopaminergic marker; tyrosine hydroxylase (TH), and their expression were upregulated with SHH treatment of the MN9D cells. These results suggest that mDA neurons differentiation and survival might be independent of SHH in the late developmental stages (E12-18). Besides, MN9D cell line is not the ideal in vitro model for investigating the differentiation of mDA and hence, the ventral midbrain primary culture might be favored over MN9D line.     

Spatiotemporal heterogeneity and clinical challenge of pancreatic neuroendocrine tumors

During the course of pancreatic neuroendocrine tumors (NETs), they generally become more heterogeneous with individual cells exhibiting distinct molecular fingerprints. This heterogeneity manifests itself through an unequal distribution of genetically-variant, tumor cell subpopulations within disease locations (i.e., spatial heterogeneity) or changes in the genomic landscape over time (i.e., temporal heterogeneity); these characteristics complicate clinical diagnosis and treatment. Effective, feasible tumor heterogeneity detection and eradication methods are essential to overcome the clinical challenges of pancreatic NETs. This review explores the molecular fingerprints of pancreatic NETs and the spectrum of tumoral heterogeneity. We then describe the challenges of assessing heterogeneity by liquid biopsies and imaging modalities and the therapeutic challenges for pancreatic NETs. In general, navigating these challenges, refining approaches for translational research, and ultimately improving patient care are available once we have a better understanding of intratumoral spatiotemporal heterogeneity.     

Development and characterization of a 68Ga-labeled A20FMDV2 peptide probe for the PET imaging of αvβ6 integrin-positive pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is known to be one of the most lethal cancers. Since the majority of patients are diagnosed at an advanced stage, development of a detection method for PDAC at an earlier stage of disease progression is strongly desirable. Integrin α_Vβ6 is a promising target for early PDAC detection because its expression increases during precancerous changes. The present study aimed to develop an imaging probe for positron emission tomography (PET) which targets α_Vβ6 integrin-positive PDAC. We selected A20FMDV2 peptide, which binds specifically to αvβ6 integrin, as a probe scaffold, and ⁶⁸Ga as a radioisotope. A20FMDV2 peptide has not been previously labeled with ⁶⁸Ga. A cysteine residue was introduced to the N-terminus of the probe at a site-specific conjugation of maleimide-NOTA (mal-NOTA) chelate. Different numbers of glycine residues were also introduced between cysteine and the A20FMDV2 sequence as a spacer in order to reduce the steric hindrance of the mal-NOTA on the binding probe to αVβ6 integrin. In vitro, the competitive binding assay revealed that probes containing a 6-glycine linker ([^natGa]CG6 and [^natGa]Ac-CG6) showed high affinity to αVβ6 integrin. Both probes could be labeled by ^67/68Ga with high radiochemical yield (>50%) and purity (>98%). On biodistribution analysis, [⁶⁷Ga]Ac-CG6 showed higher tumor accumulation, faster blood clearance, and lower accumulation in the surrounding organs of pancreas than did [⁶⁷Ga]CG6. The α_Vβ6 integrin-positive xenografts were clearly visualized by PET imaging with [⁶⁸Ga]Ac-CG6. The intratumoral distribution of [⁶⁸Ga]Ac-CG6 coincided with the α_Vβ6 integrin-positive regions detected by immunohistochemistry. Thus, [⁶⁸Ga]Ac-CG6 is a useful peptide probe for the imaging of α_Vβ6 integrin in PDAC.     

The role of amino acid metabolism alterations in pancreatic cancer: From mechanism to application

The incidence of pancreatic cancer is increasing in both developed and developing Nations. In recent years, various research evidence suggested that reprogrammed metabolism may play a key role in pancreatic cancer tumorigenesis and development. Therefore, it has great potential as a diagnostic, prognostic and therapeutic target. Amino acid metabolism is deregulated in pancreatic cancer, and changes in amino acid metabolism can affect cancer cell status, systemic metabolism in malignant tumor patients and mistakenly involved in different biological processes including stemness, proliferation and growth, invasion and migration, redox state maintenance, autophagy, apoptosis and even tumor microenvironment interaction. Generally, the above effects are achieved through two pathways, energy metabolism and signal transduction. This review aims to highlight the current research progress on the abnormal alterations of amino acids metabolism in pancreatic cancer, how they affect tumorigenesis and development of pancreatic cancer and the application prospects of them as diagnostic, prognostic and therapeutic targets.     

Comprehensive genomics and expression analysis of eceriferum (CER) genes in sunflower (Helianthus annuus)

Sunflower occupies the fourth position among oilseed crops the around the world. Eceriferum (CER) is an important gene family that plays critical role in very-long-chain fatty acids elongation and biosynthesis of epicuticular waxes under both biotic and abiotic stress conditions. The aim of present study was to investigate the effect of sunflower CER genes during drought stress condition. Thus, comparative analysis was undertaken for sunflower CER genes with Arabidopsis genome to determine phylogenetic relationship, chromosomal mapping, gene structures, gene ontology and conserved motifs. Furthermore, we subjected the sunflower cultivars under drought stress and used qRT-PCR analysis to explore the expression pattern of CER genes during drought conditions. We identified thirty-seven unevenly distributed CER genes in the sunflower genome. The phylogenetic analysis revealed that CER genes were grouped into seven clades in Arabidopsis, Helianthus annuus, and Gossypium hirsutum. Expression analysis showed that genes CER10 and CER60 were upregulated in sunflower during drought conditions, indicating that these genes are activated during drought stress. The results obtained will serve to characterize the CER gene family in sunflower and exploit the role of these genes in wax biosynthesis under limited water conditions.Key messageCuticular waxes protect the plants from drought stress, so we observed the expression of wax bio synthesis genes in recently sequences genome of Helianthus annuus. We observed that expression of wax biosynthesis genes CER10 and CER60 was upregulated when the plants were subjected to drought stress.     

Construction of miRNA-mRNA network for the identification of key biological markers and their associated pathways in IgA nephropathy by employing the integrated bioinformatics analysis

BackgroundAbout half-century ago, Immunoglobulin A nephropathy (IgAN) was discovered as a complicated disease with frequent clinical symptoms. Until now, exact mechanism underlying the pathogenesis of IgAN is poorly known. Therefore, current study was aimed to understand the molecular mechanism of IgAN by identifying the key miRNAs and their targeted hub genes. The key miRNAs might contribute to the diagnosis and therapy of IgAN, and could turn out to be a new star in the field of IgAN.MethodsThe microarray datasets were downloaded from Gene Expresssion Omnibus (GEO) database and analyzed using R package (LIMMA) in order to obtain differential expressed genes (DEGs). Then, the hub genes were identified using cytoHubba plugin of cytoscpae tool and other bioinformatics approaches including protein-protein interaction (PPI) network analysis, module analysis, and miRNA-hub gene network construction was also performed.ResultsA total of 348 DEGs were identified, of which 107 were upregulated genes and 241 were downregulated genes. Subsequently, the 12 overlapped genes were predicted from cytoHubba, and considered as hub genes. Moreover, a network among miRNA-hub genes was created to explore the correlation between the hub genes and their targeted miRNAs. Network construction ultimately lead to the identification of nine gene named FN1, EGR1, FOS, JUN, SERPINE1, MMP2, ATF3, MYC, and IL1B and one novel key miRNA namely, has-miR-144-3p as biomarker for diagnosis and therapy of IgAN.ConclusionThis study updates the information and yield a new perspective in context of understanding the pathogenesis and development of IgAN. In future, key miRNAs might be capable of improving the personalized detection and therapies for IgAN. In vivo and in vitro investigation of miRNAs and pathway interaction is essential to delineate the specific roles of the novel miRNAs, which may help to further reveal the mechanisms underlying IgAN.     

A novel PAK4 inhibitor suppresses pancreatic cancer growth and enhances the inhibitory effect of gemcitabine

Over 95% of Pancreatic ductal adenocarcinomas (PDA) carry mutations in the oncogene KRas which has been proven to be a difficult drug target. P21-activated kinase 4 (PAK4), acts downstream of KRas, and is overexpressed in PDA contributing to its growth and chemoresistance, and thus becomes an attractive therapeutic target. We have developed a new PAK4 inhibitor, PAKib and tested its effect on pancreatic cancer (PC) cell growth in vitro and in a syngeneic mouse model of PC. PAKib suppressed PC cell growth by inducing cell death and cycle arrest. PAKib inhibited PC growth and enhanced the inhibition by gemcitabine of PC in cell culture and in PC mouse model. PAKib acted through multiple signaling pathways involved in cell cycle checkpoints, apoptosis, cell junction, and focal adhesion. These proof-of-concept studies demonstrated the anti-cancer effect of PAKib alone and in combination with gemcitabine and warrant a further clinical investigation.     

Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer

Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein–protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.     

Concerted Antibody and Antigen Discovery by Differential Whole-cell Phage Display Selections and Multi-omic Target Deconvolution

Monoclonal antibody (mAb)-based biologics are well established treatments of cancer. Antibody discovery campaigns are typically directed at a single target of interest, which inherently limits the possibility of uncovering novel antibody specificities or functionalities. Here, we present a target-unbiased approach for antibody discovery that relies on generating mAbs against native target cell surfaces via phage display. This method combines a previously reported method for improved whole-cell phage display selections with next-generation sequencing analysis to efficiently identify mAbs with the desired target cell reactivity. Applying this method to multiple myeloma cells yielded a panel of >50 mAbs with unique sequences and diverse reactivities. To uncover the identities of the cognate antigens recognized by this panel, representative mAbs from each unique reactivity cluster were used in a multi-omic target deconvolution approach. From this, we identified and validated three cell surface antigens: PTPRG, ICAM1, and CADM1. PTPRG and CADM1 remain largely unstudied in the context of multiple myeloma, which could warrant further investigation into their potential as therapeutic targets. These results highlight the utility of optimized whole-cell phage display selection methods and could motivate further interest in target-unbiased antibody discovery workflows.     

Differential Proteome and Interactome Analysis Reveal the Basis of Pleiotropy Associated With the Histidine Methyltransferase Hpm1p

The methylation of histidine is a post-translational modification whose function is poorly understood. Methyltransferase histidine protein methyltransferase 1 (Hpm1p) monomethylates H243 in the ribosomal protein Rpl3p and represents the only known histidine methyltransferase in Saccharomyces cerevisiae. Interestingly, the hpm1 deletion strain is highly pleiotropic, with many extraribosomal phenotypes including improved growth rates in alternative carbon sources. Here, we investigate how the loss of histidine methyltransferase Hpm1p results in diverse phenotypes, through use of targeted mass spectrometry (MS), growth assays, quantitative proteomics, and differential crosslinking MS. We confirmed the localization and stoichiometry of the H243 methylation site, found unreported sensitivities of Δhpm1 yeast to nonribosomal stressors, and identified differentially abundant proteins upon hpm1 knockout with clear links to the coordination of sugar metabolism. We adapted the emerging technique of quantitative large-scale stable isotope labeling of amino acids in cell culture crosslinking MS for yeast, which resulted in the identification of 1267 unique in vivo lysine–lysine crosslinks. By reproducibly monitoring over 350 of these in WT and Δhpm1, we detected changes to protein structure or protein–protein interactions in the ribosome, membrane proteins, chromatin, and mitochondria. Importantly, these occurred independently of changes in protein abundance and could explain a number of phenotypes of Δhpm1, not addressed by expression analysis. Further to this, some phenotypes were predicted solely from changes in protein structure or interactions and could be validated by orthogonal techniques. Taken together, these studies reveal a broad role for Hpm1p in yeast and illustrate how crosslinking MS will be an essential tool for understanding complex phenotypes.     

Differential involvement of caspase-6 in amyloid-β-induced fragmentation of lamin A and B

Amyloid-β (Aβ), a peptide implicated in Alzheimer's disease, was shown to cause specific fragmentation of lamin proteins, which was mediated by an unidentified protease named nuclear scaffold protease (NSP) independently of caspase-6. Because caspase-6 is responsible for the fragmentation process in many other damage-induced apoptosis, here we further investigated possible involvement of caspase-6 in Aβ-induced lamin fragmentation under various conditions. We found that lamin A fragment generated by NSP (named fragment b) disappeared in cells incubated with Aβ42 for prolonged periods and this product was preserved by a caspase-6 inhibitor. Furthermore, caspase-6 could remove fragment b in nuclei isolated from Aβ42-treated cells (ANU). Lamin B in ANU was fragmented by caspase-6 only after treatment with an alkaline phosphatase. The caspase-mediated fragmentation of lamin B was also achieved with nuclei isolated from cells incubated with Aβ42 plus a Cdk5 inhibitor. The results indicate that Aβ42 induces NSP-mediated fragmentation of lamin A and the following removal process of fragment b by caspase-6 and an Aβ-induced phosphorylation prevents the fragmentation of lamin B by caspase-6. The pathway leading to lamin protein fragmentation in this investigation appears to be specific for Aβ and thus the data will provide novel insights into the toxicity of the peptide.     

Diagnostic Accuracy of Copeptin in the Differential Diagnosis of Patients With Diabetes Insipidus: A Systematic Review and Meta-analysis

ObjectiveAccurate diagnosis of diabetes insipidus (DI) is of significant importance for correct management. We aimed to evaluate the diagnostic accuracy of copeptin level measurements in the differential diagnosis between DI and primary polydipsia (PP).MethodsA literature search of electronic databases from January 1, 2005, to July 13, 2022, was performed. Primary studies that evaluated the diagnostic accuracy of copeptin concentration in patients with DI and PP were considered eligible. Two reviewers independently screened relevant articles and extracted data. The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the quality of the included studies. The hierarchical summary receiver operating characteristic model and bivariate method were used.ResultsSeven studies including 422 patients with polydipsia-polyuria syndrome were included; of the 422 patients, 189 (44.79%) presented with arginine vasopressin deficiency (AVP-D, cranial DI) and 212 (50.24%) with PP. The summary estimates of the diagnostic performance of stimulated copeptin to differentiate between PP and AVP-D were 0.93 (95% CI, 0.89-0.97) for sensitivity and 0.96 (95% CI, 0.88-1.00) for specificity. Baseline copeptin level showed high performance in identifying AVP resistance (nephrogenic DI), with a pooled sensitivity of 1.00 (95% CI, 0.82-1.00) and specificity of 1.00 (95% CI, 0.98-1.00); however, it showed little value in the differentiation between PP and AVP-D.ConclusionCopeptin level measurement is a useful tool for the differential diagnosis of patients with DI and PP. Stimulation before copeptin measurement is necessary in the diagnosis of AVP-D.     

Proteomic analysis of hypoxia and non-hypoxia secretome mesenchymal stem-like cells from human breastmilk

IntroductionBreastmilk contains proteins and cells which have stem cell properties. The human breastmilk stem cell mimick mesenchymal stem cells and expresses pluripotency genes. The protein level of breastmilk is high in colostrum and gradually subsides in the first year of lactation. The mesenchymal stem cells from breastmilk can be an alternative source of stem cells that can potentially affect cardiovascular therapy. This study aimed to identify the proteomic analysis of secretome mesenchymal stem-like cells under hypoxia compared to non-hypoxia from human breastmilk stem cells.Material and methodsThe human breastmilk was collected from six healthy breastfeeding women and transported to the laboratory under aseptic conditions. The breastmilk cells were isolated then cultured. After 72 h, the human breastmilk stem cells reached confluence then cleaned up and isolated in serum-free media (spheroid) to allow serial passaging every 48 h. The acquisition stem cell was made with flow cytometry. The cells were divided into hBSC secretomes under hypoxia (A) and non-hypoxia (B) and analyzed for LC-MS to identify the peptide structure.ResultsThe human breastmilk cells contained several mesenchymal stem-like cells in density 2.4 × 10⁶ cell/mL for hypoxia and 2 × 10⁶ cell/mL for non-hypoxia conditions. The human breastmilk stem cell surface markers derived from the third cell passage process were 93.77% for CD44, 98.69% for CD73, 88.45% for CD90, and 96.30% for CD105. The protein level of secretome mesenchymal stem -like cells under hypoxia was measured at 5.56 μg/mL and 4.28 μg/mL for non-hypoxia. The liquid chromatography-mass spectrometry analysis identified 130 and 59 peptides from hypoxia and non-hypoxia of the human breastmilk stem cell secretome sequentially. Some important proteomics structures were found in the hypoxic human breastmilk stem cell secretome, such as transforming growth factor-β, VE-cadherin, and caspase.ConclusionThe human breastmilk cells contain mesenchymal stem-like cells and a high concentration of CD44, CD73, CD90, and CD105 as surface markers at third passage culture. The hypoxic hBSC secretome produces a higher protein level compare to non-hypoxia. The transforming growth factor -β was found in the hypoxic hBSC secretome as a modulator of VEGF-mediated angiogenesis.     

Phosphoproteomic Analysis of FLCN Inactivation Highlights Differential Kinase Pathways and Regulatory TFEB Phosphoserines

In Birt–Hogg–Dubé (BHD) syndrome, germline loss-of-function mutations in the Folliculin (FLCN) gene lead to an increased risk of renal cancer. To address how FLCN inactivation affects cellular kinase signaling pathways, we analyzed comprehensive phosphoproteomic profiles of FLCN^POS and FLCN^NEG human renal tubular epithelial cells (RPTEC/TERT1). In total, 15,744 phosphorylated peptides were identified from 4329 phosphorylated proteins. INKA analysis revealed that FLCN loss alters the activity of numerous kinases, including tyrosine kinases EGFR, MET, and the Ephrin receptor subfamily (EPHA2 and EPHB1), as well their downstream targets MAPK1/3. Validation experiments in the BHD renal tumor cell line UOK257 confirmed that FLCN loss contributes to enhanced MAPK1/3 and downstream RPS6K1/3 signaling. The clinically available MAPK inhibitor Ulixertinib showed enhanced toxicity in FLCN^NEG cells. Interestingly, FLCN inactivation induced the phosphorylation of PIK3CD (Tyr524) without altering the phosphorylation of canonical Akt1/Akt2/mTOR/EIF4EBP1 phosphosites. Also, we identified that FLCN inactivation resulted in dephosphorylation of TFEB Ser109, Ser114, and Ser122, which may be linked to increased oxidative stress levels in FLCN^NEG cells. Together, our study highlights differential phosphorylation of specific kinases and substrates in FLCN^NEG renal cells. This provides insight into BHD-associated renal tumorigenesis and may point to several novel candidates for targeted therapies.