Biology subjects

La Ferlita, A.

Publications and source records attributed to La Ferlita, A..

10 recordsLinked to original sources

bioRxiv2026

Deciphering the Genomic Landscape of Renal Cell Carcinoma Brain Metastases

Brain metastases from renal cell carcinoma (RCC) remain a major cause of morbidity and mortality, yet the genomic features associated with metastatic dissemination remain poorly understood. Whole-exome sequencing was performed on 72 RCC brain metastasis samples with matched normal. To identify candidate genomic alterations associated with brain metastasis, the genomic alterations detected in the brain metastases were compared against alterations in extracranial metastases from the MSK-ECM cohort (n=137) and primary RCC tumors from TCGA (n=432) by case-control analyses. Candidate alterations were also identified through matched-pair analyses comparing brain metastases with matched primary tumors or extracranial metastases from the same patient (n=25). A random survival forest model incorporating the candidate CNA events was developed to predict overall survival. The candidate CNAs were further evaluated using functional experimental data from MetMap and DepMap. Survival analyses were conducted to assess the prognostic relevance of these alterations. We identified recurrent CNAs enriched in RCC brain metastases, including 4q loss, 7p gain, 7q gain, 8p loss, 8q gain, 9p21.3 deletion, 12q15 amplification, and 14q loss. These alterations were associated with significantly poorer patient survival among RCC patients. A random survival forest model based on these CNA events stratified TCGA-KIRC patients into prognostically distinct risk groups (C-index = 0.64). Among the recurrent CNAs, 8p loss, 8q gain, 9p21.3 deletion were associated with increased incidence of brain metastases across multiple primary cancer types in xenograft mouse models. These alterations were also strongly associated with metastatic progression and poor prognosis across RCC, lung adenocarcinoma, breast cancer, and melanoma. These findings indicate a shared genomic basis for brain tropism and highlight the potential utility of copy-number alterations as biomarkers for risk stratification and clinical decision-making.

genetics↗

bioRxiv2025

Upregulation of GREB1 in colorectal cancer ovarian metastases may be a potential therapeutic target

IntroductionClassification of ovarian metastases (OM) in colorectal cancer (CRC) as peritoneal metastasis (PM) remains controversial. OM demonstrate resistance to systemic therapy, suggesting distinct molecular tumorigenesis. Gene expression profiling and transcriptomic analysis were performed to distinguish OM, PM, and primary CRC (pCRC) and identify potential therapeutic targets. MethodsRNA sequencing data were obtained from the Total Cancer Care database. After filtering out low-expressed genes, raw counts of retained genes were normalized in trimmed mean of M-values and then log2-transformed. Genes with a |Log2FC|>0.58 and adjusted p-value <0.05 were considered dysregulated. In silico motif enrichment analysis of estrogen receptor 1 (ESR1) on growth regulating estrogen receptor binding 1 (GREB1) was conducted. ResultsThere were 115 patients with tissue from OM (n=6), PM (n=4), and pCRC (n=105). Among upregulated genes, LAMC3, SCUBE1, and GREB1 had the highest differential expression in OM compared to PM, and PEG3, C7, and GREB1 had the highest differential expression in OM compared to pCRC (all p<0.001). GREB1 was upregulated in OM compared to PM and pCRC. There are two estrogen response element (ERE) sites within the promoter region of GREB1. ESR1 transcription factor was shown to bind to these ERE (p<0.001). ConclusionsTranscriptomic analysis demonstrated clear molecular distinction between OM, PM and pCRC. We identified upregulation of GREB1 in OM compared to PM and pCRC. GREB1 contains both ERE and ESR1 in the upstream promoter regions implying potential upstream transcription regulation mediated by ESR1. GREB1 may represent a novel, hormonal target in treatment of OM in CRC.

cancer biology↗

bioRxiv2025

TWIST1 mediated transcriptional activation of SPON2 drives colorectal peritoneal metastasis through activation of cancer-associated fibroblast signaling network

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the second leading cause of cancer-related mortality in the United States. Peritoneal metastasis (PM), a malignant dissemination within the peritoneal cavity, affects approximately 20% of CRC patients and accounts for 25-35% of stage IV cases. CRC PM is associated with dismal outcomes, with a median overall survival of only 16 months on systemic chemotherapy and an almost 0% five-year survival rate, largely due to frequent treatment resistance and limited therapeutic options. Despite advances in understanding CRC metastasis, the molecular mechanisms driving CRC PM remain poorly defined. CRC heterogeneity is classified into four Consensus Molecular Subtypes (CMS1-4), with CRC PM tumors predominantly exhibiting the CMS4 signature--characterized by stromal enrichment, high mesenchymal gene expression, and enhanced cellular plasticity--features linked to aggressive disease progression and resistance to standard chemotherapy. In this study, we identify TWIST1, a basic helix-loop-helix transcription factor, as significantly upregulated in CRC PM. We establish TWIST1-SPON2 as a novel transcriptional axis driving CRC PM tumorigenesis, mediating tumor-stroma interactions between tumor epithelium and cancer-associated fibroblasts (CAFs). Additionally, we identify SPP1, secreted by CAFs, as an upstream regulator of the TWIST1-SPON2 cascade via AKT activation in tumor cells. This newly defined SPP1-TWIST1-SPON2 signaling circuit plays a pivotal role in shaping the tumor microenvironment and promoting CRC PM progression. The findings establish the SPP1-TWIST1-SPON2 axis as a potential biomarker and a promising therapeutic target in CRC PM. Keyword: Colorectal cancer, peritoneal metastasis, epithelial-mesenchymal transition, cancer-associated fibroblast

cancer biology↗

bioRxiv2024

KDM2B is required for ribosome biogenesis and its depletion unequally affects mRNA translation

KDM2B is a JmjC domain lysine demethylase, which promotes cell immortalization, stem cell self-renewal and tumorigenesis. Here we employed a multi-omics strategy to address its role in ribosome biogenesis and mRNA translation. These processes are required to sustain cell proliferation, an important cancer hallmark. Contrary to earlier observations, KDM2B promotes ribosome biogenesis by stimulating the transcription of genes encoding ribosome biogenesis factors and ribosomal proteins, particularly those involved in the biogenesis of the 40S ribosomal subunits. Knockdown of KDM2B impaired the assembly of the small and large subunit processomes, as evidenced by specific defects in pre-ribosomal RNA processing. The final outcome was a decrease in the rate of ribosome assembly and in the abundance of ribosomes, and inhibition of mRNA translation. The inhibition of translation was distributed unequally among mRNAs with different features, suggesting that mRNA-embedded properties influence how mRNAs interpret ribosome abundance. This study identified a novel mechanism contributing to the regulation of translation and provided evidence for a rich biology elicited by a pathway that depends on KDM2B, and perhaps other regulators of translation.

cancer biology↗

bioRxiv2023

METTL3 alters capping enzyme expression and its activity on ribosomal proteins

The 5 cap, catalyzed by RNA guanylyltransferase and 5-phosphatase (RNGTT), is a vital mRNA modification for the functionality of mRNAs. mRNA capping occurs in the nucleus for the maturation of the functional mRNA and in the cytoplasm for fine-tuning gene expression. Given the fundamental importance of RNGTT in mRNA maturation and expression there is a need to further investigate the regulation of RNGTT. N6-methyladenosine (m6A) is one of the most abundant RNA modifications involved in the regulation of protein translation, mRNA stability, splicing, and export. We sought to investigate whether m6A could regulate the expression and activity of RNGTT. A motif for the m6A writer methyltransferase 3 (METTL3) in the 3UTR of RNGTT mRNA was identified. Knockdown of METTL3 resulted in destabilizing RNGTT mRNA, and reduced protein expression. Sequencing of capped mRNAs identified an underrepresentation of ribosomal protein mRNA overlapping with 5 terminal oligopyrimidine (TOP) mRNAs and genes are dysregulated when cytoplasmic capping is inhibited. Pathway analysis identified disruptions in the mTOR and p70S6K pathways. A reduction in RPS6 mRNA capping, protein expression, and phosphorylation was detected with METTL3 knockdown.

molecular biology↗

bioRxiv2023

Transcriptional regulation of amino acid metabolism by KDM2B, in the context of ncPRC1.1 and in concert with MYC and ATF4

IntroductionKDM2B encodes a JmjC domain-containing histone lysine demethylase, which functions as an oncogene in several types of tumors, including TNBC. This study was initiated to address the cancer relevance of the results of our earlier work, which had shown that overexpression of KDM2B renders mouse embryonic fibroblasts (MEFs) resistant to oxidative stress by regulating antioxidant mechanisms. MethodsWe mainly employed a multi-omics strategy consisting of RNA-Seq, quantitative TMT proteomics, Mass-spectrometry-based global metabolomics, ATAC-Seq and ChIP-seq, to explore the role of KDM2B in the resistance to oxidative stress and intermediary metabolism. These data and data from existing patient datasets were analyzed using bioinformatic tools, including exon-intron-split analysis (EISA), FLUFF and clustering analyses. The main genetic strategy we employed was gene silencing with shRNAs. ROS were measured by flow cytometry, following staining with CellROX and various metabolites were measured with biochemical assays, using commercially available kits. Gene expression was monitored with qRT-PCR and immunoblotting, as indicated. ResultsThe knockdown of KDM2B in basal-like breast cancer cell lines lowers the levels of GSH and sensitizes the cells to ROS inducers, GSH targeting molecules, and DUB inhibitors. To address the mechanism of GSH regulation, we knocked down KDM2B in MDA-MB-231 cells and we examined the effects of the knockdown, using a multi-omics strategy. The results showed that KDM2B, functioning in the context of ncPRC1.1, regulates a network of epigenetic and transcription factors, which control a host of metabolic enzymes, including those involved in the SGOC, glutamate, and GSH metabolism. They also showed that KDM2B enhances the chromatin accessibility and expression of MYC and ATF4, and that it binds in concert with MYC and ATF4, the promoters of a large number of transcriptionally active genes, including many, encoding metabolic enzymes. Additionally, MYC and ATF4 binding sites were enriched in genes whose accessibility depends on KDM2B, and analysis of a cohort of TNBCs expressing high or low levels of KDM2B, but similar levels of MYC and ATF4 identified a subset of MYC targets, whose expression correlates with the expression of KDM2B. Further analyses of basal-like TNBCs in the same cohort, revealed that tumors expressing high levels of all three regulators exhibit a distinct metabolic signature that carries a poor prognosis. ConclusionsThe present study links KDM2B, ATF4, and MYC in a transcriptional network that regulates the expression of multiple metabolic enzymes, including those that control the interconnected SGOC, glutamate, and GSH metabolic pathways. The co-occupancy of the promoters of many transcriptionally active genes, by all three factors, the enrichment of MYC binding sites in genes whose chromatin accessibility depends on KDM2B, and the correlation of the levels of KDM2B with the expression of a subset of MYC target genes in tumors that express similar levels of MYC, suggest that KDM2B regulates both the expression and the transcriptional activity of MYC. Importantly, the concerted expression of all three factors also defines a distinct metabolic subset of TNBCs with poor prognosis. Overall, this study identifies novel mechanisms of SGOC regulation, suggests novel KDM2B-dependent metabolic vulnerabilities in TNBC, and provides new insights into the role of KDM2B in the epigenetic regulation of transcription. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=122 HEIGHT=200 SRC="FIGDIR/small/548031v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1bac894org.highwire.dtl.DTLVardef@1c6977eorg.highwire.dtl.DTLVardef@103d73corg.highwire.dtl.DTLVardef@127b1ff_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsThe knockdown of KDM2B in basal-like breast cancer cell lines lowers the levels of GSH and sensitizes the cells to ROS inducers, GSH targeting molecules, and DUB inhibitors. KDM2B regulates intermediary metabolism by targeting the expression of a host of metabolic enzymes, including those in the SGOC, glutamate, and GSH metabolism. KDM2B enhances chromatin accessibility of MYC and ATF4 and promotes their expression. MYC and ATF4 binding sites are enriched in the promoters of genes whose accessibility depends on KDM2B. KDM2B functioning in the context of ncPRC1.1, binds the promoters of transcriptionally active genes, including those encoding KDM2B-regulated metabolic enzymes, in concert with MYC and ATF4. Basal-like TNBCs expressing high levels of all three regulators, exhibit a distinct metabolic signature that is associated with poor prognosis.

cancer biology↗

bioRxiv2020

IWS1 phosphorylation by AKT kinase controls the nucleocytoplasmic export of type I IFNs and the sensitivity of lung adenocarcinoma cells to oncolytic viral infection, through U2AF2 RNA splicing.

The authors have withdrawn their manuscript. While attempting to reproduce the data on the alternative splicing of exon 2 of U2AF2, they observed that the proposed splicing mechanism could not give rise to a functional U2AF2 protein. In addition, they observed evidence of manipulation in the electropherogram of the splicing junction between exons 1 and 3 and in the primary data on which this electropherogram was based, which were deposited in Mendeley by the first author. These observations raise questions on the integrity of the reported results. In light of this information, the authors have no confidence in the key findings of the paper, and therefore, do not wish it to be cited. If you have any questions, please contact the corresponding author.

cancer biology↗

bioRxiv2020

Divergent use of metabolic fluxes in breast cancer metastasis

Breast cancers can metastasize to many organs. But how do disseminated cells from a primary tumor adapt to distal tissues? Here we combined metabolomics, flux measurements, and mathematical modeling to study metabolic fluxes in breast cancer cells adapted to home to different organs. We found that lung-homing cells maintain high glycolytic flux despite low levels of glycolytic intermediates, by constitutively activating a pathway sink into lactate. Their distinct behavior--a strong Warburg effect--has a gene expression signature: a high ratio of lactate dehydrogenase to pyruvate dehydrogenase gene expression, which also correlates with lung metastases in patients with breast cancer. Surprisingly, this strong Warburg effect does not necessarily increase cellular growth rate, suggesting that lactate secretion may be a trait under selection in lung metastasis. Our results stress that metabolic fluxes may not correlate with metabolic intermediates, a finding relevant for metastatic tropism.

cancer biology↗

bioRxiv2020

IWS1 phosphorylation promotes cell proliferation and predicts poor prognosis in EGFR mutant lung adenocarcinoma patients, through the cell cycle-regulated U2AF2 RNA splicing.

cancer biology↗

bioRxiv2020

PHENSIM: Phenotype Simulator

Despite the unprecedented growth in our understanding of cell biology, it still remains challenging to connect it to experimental data obtained with cells and tissues physiopathological status under precise circumstances. This knowledge gap often results in difficulties in designing validation experiments, which are usually labor-intensive, expensive to perform, and hard to interpret. Here we propose PHENSIM, a computational tool using a systems biology approach in order to simulate how cell phenotypes are affected by the activation/inhibition of one or multiple biomolecules and does so by exploiting signaling pathways. Our tools applications include predicting the outcome of drug administration, knockdown experiments, gene transduction, and exposure to exosomal cargo. Importantly, PHENSIM enables the user to make inferences on well-defined cell lines and includes pathway maps from three different model organisms. To assess our approachs reliability, we built a benchmark from transcriptomics data gathered from NCBI GEO and performed four case studies on known biological experiments. Our results show high prediction accuracy, thus highlighting the capabilities of this methodology. PHENSIM standalone Java application is available at https://github.com/alaimos/phensim, along with all data and source codes for benchmarking. A web-based user interface is accessible at https://phensim.atlas.dmi.unict.it/.

bioinformatics↗