Metastatic Gene Research Articles

CNSC-46. GLIOBLASTOMA INITIATION, MIGRATION, AND CELL TYPES ARE REGULATED BY CORE BHLH TRANSCRIPTION FACTORS ASCL1 AND OLIG2

Abstract Glioblastomas (GBMs) are highly aggressive, infiltrative, and heterogeneous brain tumors driven by complex genetic alterations. The neurodevelopmental transcription factors ASCL1 and OLIG2 are highly co-expressed in GBMs. However, their combinatorial roles in regulating the hierarchy and heterogeneity of GBM cells are unknown. Here, we show that induction of somatic mutations in neural progenitor cells lead to the dysregulation of ASCL1 and OLIG2, which then function redundantly and are required for brain tumor formation in a mouse model of GBM. Subsequently, the binding of ASCL1 and OLIG2 to each other’s loci and to downstream target genes then determine the cell types and degree of migration of tumor cells. Notably, single-cell RNA sequencing (scRNA-seq) reveals that a high level of ASCL1 is key in promoting neural stem cell (NSC)/astrocyte-like tumor cell types, which are highly proliferative, migratory, and are marked by upregulation of ribosomal protein, oxidative phosphorylation, cancer metastasis, and therapeutic resistance genes.

PATH-61. GENOMIC SIGNATURE IN NON-SMALL CELL LUNG CANCER PATIENTS METASTATIC TO BRAIN-A SINGLE INSTITUTION EXPERIENCE

Abstract BACKGROUND Lung cancer is leading cause of cancer-related death in US, with 10-30 % of NSCLC patients developing brain metastasis, which challenges curative treatment and life expectancy. Somatic mutations in KRAS and EGFR genes have been commonly implicated with brain metastasis. Other studies have shown higher amplification frequencies in MYC, YAP1, and MMP13 and deletions in CDKN2A/B. METHODS We conducted a retrospective study on observational cohort of NSCLC patients from January 2022 to July 2023, using IRB-approved data in patients with confirmed brain metastasis (CBS). Beyond demographic information, data on genomic signatures was obtained from maximum parallel/next-generation sequencing on tumor biopsy samples. Comparative analysis was conducted to predict commonalities in brain metastasis gene signatures. RESULTS The study involved 143 newly diagnosed lung cancer patients, with 29 having CBS. Genomic data was available in 24 patients. Most common abnormality was noted in TP53 gene in about 47% of patients, followed by LRP1B (12%). Mutations in KRAS, EGFR, NF1, MET, SMARCA4, KEAP1, and STK11 genes were seen in two patients each. Interestingly, 3 of 4 patients with LRP1B had brain metastasis. Actionable mutations/rearrangements were significantly lower compared to general prevalence of these mutations (KRAS gene 8% and EGFR gene 5%). CONCLUSIONS Lung cancer with brain metastasis has an abysmal prognosis due to poor CNS penetration of chemotherapeutic agents. Surgical resection and RT remain cornerstones of treatment, but certain TKI has shown some potential. Our study uncovered a notably higher prevalence of TP53 mutation among patients with brain metastasis. While patient cohort was small, those harboring an LRP1B mutation exhibited significantly higher incidence of brain metastasis. Contrary to prevalent epidemiological data, our patient population demonstrated a lower frequency of targetable mutations (specifically in EGFR and KRAS genes). We hypothesize that this observation is due to a markedly higher smoking prevalence in our region.

Representing ECM composition and EMT pathways in gastric cancer using a new metastatic gene signature

IntroductionGastric cancer (GC) is an aggressive and heterogeneous malignancy marked by cellular and molecular diversity. In GC, cancer cells invade locally in the stomach at stage I and can progress to metastasis in distant organs by stage IV, where it often becomes fatal.MethodsWe analyzed gene expression profiles from 719 stage I and stage IV GC patients across seven public datasets, conducting functional enrichment analysis to identify a gene signature linked to disease progression. Additionally, we developed an in vitro model of a simplified extracellular matrix (ECM) for cell-based assays.ResultsOur analysis identified a progression-associated gene signature (APOD, COL1A2, FSTL1, GEM, LUM, and SPARC) that characterizes stage IV GC. This signature is associated with ECM organization and epithelial-to-mesenchymal transition (EMT), both of which influence the tumor microenvironment by promoting cell invasion and triggering EMT.DiscussionThis gene signature may help identify stage I GC patients at higher risk, offering potential utility in early-stage patient management. Furthermore, our experimental ECM model may serve as a platform for investigating molecular mechanisms underlying metastatic spread in gastric cancer.

Cachexia and efficiency of trifluridine/thymidine phosphorylase inhibitor + bevacizumab in metastatic colorectal cancer

In later-line treatment of metastatic colorectal cancer (mCRC), there may be large differences in treatment efficacy depending on cancer cachexia. Recently, the cachexia index (CXI), which was calculated from the skeletal muscle mass index (SMI), serum albumin concentration, and neutrophil-to-lymphocyte ratio, was developed to evaluate cancer cachexia. We retrospectively examined the CXI of 80 patients who were treated with trifluridine/thymidine phosphorylase inhibitor (FTD/TPI) + bevacizumab (Bmab) therapy as a later-line treatment for mCRC, and assessed the impact of cancer cachexia on chemotherapeutic efficacy using CXI. Progression-free and overall survival rates were significantly worse in the low CXI group than in the high CXI group, although there were no marked differences in tumor factors, such as the number of metastatic organs or gene mutations, between the two groups. As the cross-sectional area of the iliopsoas muscle was significantly associated with that of the skeletal muscle, the accuracy of the CXI based on the psoas mass index (P-CXI), which is easier to calculate than the SMI, in predicting treatment outcomes was equivalent to that of the CXI based on the SMI (S-CXI). Cancer cachexia is an important factor related to treatment efficacy in later-line treatments, such as FTD/TPI + Bmab therapy.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq revealed key genes for bone metastasis and chemoresistance in prostate cancer.

Prostate cancer (PCa) is a serious malignancy. The main causes of PCa aggravation and death are unexplained resistance to chemotherapy and bone metastases. This study aimed to investigate the molecular mechanisms associated with the dynamic processes of progression, bone metastasis, and chemoresistance in PCa. Through comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data, Gene Expression Omnibus (GEO) tumor progression and metastasis-related genes were identified. These genes were subjected to lasso regression modeling using the Cancer Genome Atlas (TCGA) database. Tartrate-resistant acid phosphatase (TRAP) staining and real-time quantitative PCR (RT-qPCR) were used to evaluate osteoclast differentiation. CellMiner was used to confirm the effect of LDHA on chemoresistance. Finally, the relationship between LDHA and chemoresistance was verified using doxorubicin-resistant PCa cell lines. 7928 genes were identified as genes related to tumor progression and metastasis. Of these, 7 genes were found to be associated with PCa prognosis. The scRNA-seq and TCGA data showed that the expression of LDHA was higher in tumors and associated with poor prognosis of PCa. In addition, upregulation of LDHA in PCa cells induces osteoclast differentiation. Additionally, high LDHA expression was associated with resistance to Epirubicin, Elliptinium acetate, and doxorubicin. Cellular experiments demonstrated that LDHA knockdown inhibited doxorubicin resistance in PCa cells. LDHA may play a potential contributory role in PCa initiation and development, bone metastasis, and chemoresistance. LDHA is a key target for the treatment of PCa.

Proof of Concept for Genome Profiling of the Neurofibroma/Sarcoma Sequence in Neurofibromatosis Type 1.

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disorder characterized by the predisposition to develop tumors such as malignant peripheral nerve sheath tumors (MPNSTs) which represents the primary cause of death for NF1-affected patients. Regardless of the high incidence and mortality, the molecular mechanisms underneath MPNST growth and metastatic progression remain poorly understood. In this proof-of-concept study, we performed somatic whole-exome sequencing (WES) to profile the genomic alterations in four samples from a patient with NF1-associated MPNST, consisting of a benign plexiform neurofibroma, a primary MPNST, and metastases from lung and skin tissues. By comparing genomic patterns, we identified a high level of variability across samples with distinctive genetic changes which allow for the definition of profiles of the early phase with respect to the late metastatic stages. Pathogenic and likely pathogenic variants were abundant in the primary tumor, whereas the metastatic samples exhibited a high level of copy-number variations (CNVs), highlighting a possible genomic instability in the late phases. The most known MPNST-related genes, such as TP53 and SUZ12, were identified in CNVs observed within the primary tumor. Pathway analysis of altered early genes in MPNST pointed to a potential role in cell motility, division and metabolism. Moreover, we employed survival analysis with the TCGA sarcoma genomic dataset on 262 affected patients, in order to corroborate the predictive significance of the identified early and metastatic MPNST driver genes. Specifically, the expression changes related to the mutated genes, such as in RBMX, PNPLA6 and AGAP2, were associated with reduced patient survival, distinguishing them as potential prognostic biomarkers. This study underlines the relevance of integrating genomic results with clinical information for early diagnosis and prognostic understanding of tumor aggressiveness.

Multi-scale transcriptomics reveals that specific tumor cells promote lung adenocarcinoma metastasis through crosstalk with the microenvironment

Most advanced lung adenocarcinoma (LUAD) patient deaths are attributed to metastasis. However, the complete understanding of the metastatic mechanism in LUAD remains elusive. Single-cell RNA-seq (scRNA-seq), spatial RNA-seq (stRNA-seq) and bulk RNA-seq of primary LUAD were integrated to investigate metastatic driver genes, cell–cell interactions, and spatial colocalization of cells and ligand-receptor pairs. A lung adenocarcinoma metastasis risk scoring model (LMRS) was established to estimate the risk of metastasis in LUAD. Forty-two metastasis driver genes were identified and tumor epithelial cells were classified into two subtypes. Epithelial cell subclass characterized by susceptibility to metastasis are referred to as Epithelial_LM, and the remaining as Epithelial_LL. Epithelial_LM subtype has intimate ligand-receptor interactions with inflammatory endothelial cells (iendo), inflammatory cancer-associated fibroblasts (iCAF), and NKT cells. Epithelial_LM cells have a spatial colocalization relationship with these three types of cells. The LMRS was established and its efficacy was verified in bulk RNA-seq. We identified a subclass of epithelial cells prone to metastasis and demonstrated the contribution of inflammatory stromal cells and NKT cells in facilitating tumor metastasis.Graphical

Gasdermin C promotes Stemness and Immune Evasion in Pancreatic Cancer via Pyroptosis-Independent Mechanism.

Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic and lethal disease. Gasdermins are primarily associated with necrosis via membrane permeabilization and pyroptosis, a lytic pro-inflammatory type of cell death. In this study, GSDMC upregulation during PDAC progression is reported. GSDMC directly induces genes related to stemness, EMT, and immune evasion. Targeting Gsdmc in murine PDAC models reprograms the immunosuppressive tumor microenvironment, rescuing the recruitment of anti-tumor immune cells through CXCL9. This not only results in diminished tumor initiation, growth and metastasis, but also enhances the response to KRASG12D inhibition and PD-1 checkpoint blockade, respectively. Mechanistically, it is discovered that ADAM17 cleaves GSDMC, releasing nuclear fragments binding to promoter regions of stemness, metastasis, and immune evasion-related genes. Pharmacological inhibition of GSDMC cleavage or prevention of its nuclear translocation is equally effective in suppressing GSDMC's downstream targets and inhibiting PDAC progression. The findings establish GSDMC as a potential therapeutic target for enhancing treatment response in this deadly disease.

Abstract C071: Transcription factor switching drives progression of the classical subtype of pancreatic cancer

Abstract Despite recent advances in the treatment of pancreatic adenocarcinoma (PDAC), the median survival remains <12 months. Patients typically present with late-stage disease and are often unable to tolerate drug combination regimens. Large-scale genomic approaches categorise PDAC into two distinct molecular subtypes, based on transcriptomic signatures, and these are termed the classical and squamous (or basal) subtypes. Although it is well-described that PDAC harbours gene mutations (i.e. KRAS G12D, p53 R172H) that initiate the disease, little is known about the influence of lineage-defining Transcription Factors (TF) on PDAC subtypes and their contribution to tumor progression. We took an unbiased approach to discover driving TFs in PDAC, we performed ChIP-seq of the active enhancer mark H3K27Ac from surplus tissue following resection of primary PDAC tumors (n=6) and normal adjacent tissue (n=4). Analysis of the H3K27Ac sites showed that the most enriched motifs within all experimentally mapped enhancer elements were HNF motifs (HNF4G & HNF4A) and Forkhead (i.e., FOXA1), confirming that these two classes of TFs constitute the lineage-defining factors in these clinical samples. Investigation of publicly available clinical datasets revealed HNF4G to be amplified in 9% of PDAC patients. Using Rapid Immunoprecipitation and Mass Spectrometry of Endogenous protein complexes (RIME), our method for unbiased discovery of endogenous protein complexes, we investigated the fundamental differences in the FOXA1 interactome between models of classical and squamous subtypes. HNF4A and HNF4G were only seen as FOXA1-interactors in models of the classical subtype. HNF4G Knockout (KO) clones injected orthotopically into the pancreas of mice, showed a significant increase (p-value<0.0006) in median survival and slower tumor growth compared to Control (Cas-9) (p-value <0.0001). HNF4G-KO dependent genes were specifically expressed in primary tumors (with decreased EMT signalling) versus metastatic samples (PanCRux dataset), implying that the HNF4G target genes were mostly limited to primary tumor contexts. We found Protein Arginine Methylate Transferase (PRMT1) to be a significant and reproducible interactor of FOXA1 and HNF4G. We observed a significant global reduction in PRMT1 chromatin binding in both the HNF4G-KO and FOXA1 depleted cells compared to the control. This data suggests a dependency on both HNF4G and FOXA1 for recruitment of PRMT1 to chromatin. We find HNF4G to be the key driver of classical subtype primary disease, in part by recruiting the methyltransferase PRMT1 to regulatory regions revealing a therapeutically exploitable opportunity. A molecular switch occurs in advanced disease, whereby HNF4G expression decreases, unmasking FOXA1’s transcriptional activity. De-repressed FOXA1 drives late-stage disease, by orchestrating metastasis-specific enhancer-promoter loops to direct metastatic gene regulation. We suggest the existence of stage-dependent TF activity, triggered by molecular compartmentalisation that mediates multistage progression of PDAC. Citation Format: Shalini Vasudev Rao, Lisa V Young, Danya Cheeseman, Stephanie V Mack, Dominique-Laurent Couturier, Sean V Flynn, Rebecca Brias, Amy Smith, Jill Temple, Duncan Jodrell, Alasdair Russell V Russell, Igor Chernukhin, Jason Carroll. Transcription factor switching drives progression of the classical subtype of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C071.

Exploring extrahepatic metastasis of hepatocellular carcinoma based on methylation driver genes and establishing a prognostic model for hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC), theseventh most common cancer worldwide, is characterized by a high mortality rate, advanced diagnosis, and susceptibility to extrahepatic metastasis. Numerous studies have shown that DNA methylation is a crucial factor in epigenetic modifications and regulation of carcinogenesis. MethodsHCC patient data were sourced from the TCGA dataset as a training set, while GSE116174 was used as an external validation set for verification. Differential methylation and expression analyses were performed on HCC samples with and without extrahepatic metastasis. In the intersecting genes, the relationship between methylation and expression levels of the intersecting genes was analyzed. Genes with a correlation coefficient≥|0.30| and P<0.05 were identified as methylation driver genes. Cox regression analysis was conducted to identify genes associated with HCC prognosis and establish a risk score. Subsequently, a prognostic model was established and validated using Cox regression analysis incorporating the risk score and other clinical factors. Using immunohistochemistry to evaluate the expression of DHX58 and EIF5A2 in HCC tissues with and without extrahepatic metastasis. Immunoinfiltration analysis was performed on the HCC samples using CIBERSORT. ResultsOur research identified eight methylation driver genes for HCC extrahepatic metastasis, of which two genes (DHX58 and EIF5A2) were associated with HCC patient prognosis. And the study further constructed and validated the risk score and prognostic model. Immunoinfiltration analysis showed that M0 macrophage abundance was correlated with the prognosis of HCC patients. Immunohistochemistry revealed differences in DHX58 and EIF5A2 expression between HCC tissues with and without extrahepatic metastasis, consistent with our bioinformatics findings.

Co-targeting NRF2 potentially enhances the in vitro anticancer effects of paclitaxel in gastric cancer cells

BackgroundGastric cancer (GC) is a highly chemoresistant malignancy with a poor prognosis. Paclitaxel’s low response rate as second-line chemotherapy for advanced GC has prompted intensive research into its molecular basis and prospective targeted therapies to enhance its therapeutic efficacy. The objective of this study was to investigate the synergistic effects of NRF2 silencing in combination with paclitaxel treatment on GC cell viability, apoptosis, proliferation, autophagy, and migration.Methods\\After the siRNA-mediated silencing of NRF2 in AGS cells, the transfection efficacy was evaluated by qRT-PCR. The MTT assay was then applied to assess cell viability, followed by flow cytometry analysis for apoptosis, proliferation, and autophagy in AGS cells treated with NRF2 siRNA, paclitaxel, or their combination. Thereafter, the migration of cells was measured using a wound-healing assay. Ultimately, the relative gene expression levels of apoptotic (Bax, Caspase-3, and Caspase-9), anti-apoptotic (Bcl-2), metastatic (MMP-2), and cell cycle (P53) genes were measured by qRT-PCR in all experiment groups to further assess the molecular basis for the combination therapy.ResultsNRF2 siRNA transfection significantly enhanced paclitaxel-induced apoptosis and sensitized AGS cells to paclitaxel via modulating the expression of apoptosis-related genes including Bcl-2, Bax, Caspase-3, and Caspase-9. Besides, NRF2 siRNA and paclitaxel synergistically induced cell cycle arrest at the G2 phase, promoted autophagy activation, and inhibited AGS cell migration via MMP-2 downregulation. Additionally, P53, a key regulator of cell growth, was significantly upregulated in the treated groups compared to the control group.ConclusionsOur findings suggest that paclitaxel combined with siRNA-mediated silencing of NRF2 might represent a promising therapeutic strategy for GC, however further translational and clinical research are warranted.

RCC1 depletion drives protein transport defects and rupture in micronuclei.

Micronuclei (MN) are a commonly used marker of chromosome instability that form when missegregated chromatin recruits its own nuclear envelope (NE) after mitosis. MN frequently rupture, which results in genome instability, upregulation of metastatic genes, and increased immune signaling. MN rupture is linked to NE defects, but the cause of these defects is poorly understood. Previous work from our lab found that chromosome identity correlates with rupture timing for small MN, i.e. MN containing a short chromosome, with more euchromatic chromosomes forming more stable MN with fewer nuclear lamina gaps. Here we demonstrate that histone methylation promotes rupture and nuclear lamina defects in small MN. This correlates with increased MN size, and we go on to find that all MN have a constitutive nuclear export defect that drives MN growth and nuclear lamina gap expansion, making the MN susceptible to rupture. We demonstrate that these export defects arise from decreased RCC1 levels in MN and that additional loss of RCC1 caused by low histone methylation in small euchromatic MN results in additional import defects that suppress nuclear lamina gaps and MN rupture. Through analysis of mutational signatures associated with early and late rupturing chromosomes in the Pan-Cancer Analysis of Whole Genomes (PCAWG) dataset, we identify an enrichment of APOBEC and DNA polymerase E hypermutation signatures in chromothripsis events on early and mid rupturing chromosomes, respectively, suggesting that MN rupture timing could determine the landscape of structural variation in chromothripsis. Our study defines a new model of MN rupture where increased MN growth, caused by defects in protein export, drives gaps in nuclear lamina organization that make the MN susceptible to membrane rupture with long-lasting effects on genome architecture.

The molecular basis of the anticancer effect of statins

Statins, widely used cardiovascular drugs that lower cholesterol by inhibiting HMG-CoA reductase, have been increasingly recognized for their potential anticancer properties. This study elucidates the underlying mechanism, revealing that statins exploit Synthetic Lethality, a principle where the co-occurrence of two non-lethal events leads to cell death. Our computational analysis of approximately 37,000 SL pairs identified statins as potential drugs targeting genes involved in SL pairs with metastatic genes. In vitro validation on various cancer cell lines confirmed the anticancer efficacy of statins. This data-driven drug repurposing strategy provides a molecular basis for the anticancer effects of statins, offering translational opportunities in oncology.

Hub metastatic gene signature and risk score of breast cancer patients with small tumor sizes using WGCNA

BackgroundBreast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices.MethodsWe integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression.ResultsABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72–0.76. The enriched pathways were immune regulation and cell–cell signaling. EGFR serves as the hub gene for the protein–protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3.ConclusionPrognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein–protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms.Graphical abstract

Targeted therapies in HER2-positive breast cancer with receptor-redirected Arazyme-linker-Herceptin as a novel fusion protein.

Targeted treatment of different types of cancers through highly expressed cancer cell surface receptors by fusion proteins is an efficient method for cancer therapy. The HER2 receptor is a member of the tyrosine kinase receptors family, which plays a notable role in breast cancer tumor development. About 25-30% of breast cancers overexpress human epidermal growth factor receptor 2 (HER2). In this study, we evaluated the particulars of a designed recombinant protein formed by HER2-specific Mab Herceptin linked with Arazyme on a HER2-overexpressing breast cancer cell line (SKBR3). Arazyme, a metalloprotease produced by Serratia proteamaculans was fused to the variable area of light and heavy chains of the Herceptin. The cytotoxic assay of the Arazyme-linker-Herceptin in the SKBR3 and MDA-MB-468 cells was evaluated by the MTT and flow cytometry techniques. The Caspase‑3 activity determination and adhesion assay were performed to evaluate the antitumor activity of the Arazyme-linker-Herceptin against SKBR3 cells. Furthermore, RT-PCR was used to measure the expression levels of the Bcl-2, Bax, MMP2, MMP9, and RIP3 genes. The Arazyme-linker-Herceptin showed higher cytotoxicity in SKBR3 cells compared to MDA-MB-468 cells. In addition, flow cytometry results revealed that the Arazyme-linker-Herceptin can significantly induce apoptosis in the HER2-overexpressing breast cancer cell line (SKBR3), which was confirmed by Bax upregulation and the decrease in adhesion of tumor cells and MMP2/MMP9. The findings of this study demonstrated that the Arazyme-linker-Herceptin induced apoptosis and decreased metastatic genes in SKBR3 cells; however, further research is required to confirm the effectiveness of the fusion protein.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and invitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through invitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration invitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Metastasis and basement membrane-related signature enhances hepatocellular carcinoma prognosis and diagnosis by integrating single-cell RNA sequencing analysis and immune microenvironment assessment

BackgroundHepatocellular carcinoma (HCC) is the most common type of primary liver cancer and second leading cause of cancer-related deaths worldwide. The heightened mortality associated with HCC is largely attributed to its propensity for metastasis, which cannot be achieved without remodeling or loss of the basement membrane (BM). Despite advancements in targeted therapies and immunotherapies, resistance and limited efficacy in late-stage HCC underscore the urgent need for better therapeutic options and early diagnostic biomarkers. Our study aimed to address these gaps by investigating and evaluating potential biomarkers to improve survival outcomes and treatment efficacy in patients with HCC.MethodIn this study, we collected the transcriptome sequencing, clinical, and mutation data of 424 patients with HCC from The Cancer Genome Atlas (TCGA) and 240 from the International Cancer Genome Consortium (ICGC) databases. We then constructed and validated a prognostic model based on metastasis and basement membrane-related genes (MBRGs) using univariate and multivariate Cox regression analyses. Five immune-related algorithms (CIBERSORT, QUANTISEQ, MCP counter, ssGSEA, and TIMER) were then utilized to examine the immune landscape and activity across high- and low-risk groups. We also analyzed Tumor Mutation Burden (TMB) values, Tumor Immune Dysfunction and Exclusion (TIDE) scores, mutation frequency, and immune checkpoint gene expression to evaluate immune treatment sensitivity. We analyzed integrin subunit alpha 3 (ITGA3) expression in HCC by performing single-cell RNA sequencing (scRNA-seq) analysis using the TISCH 2.0 database. Lastly, wound healing and transwell assays were conducted to elucidate the role of ITGA3 in tumor metastasis.ResultsPatients with HCC were categorized into high- and low-risk groups based on the median values, with higher risk scores indicating worse overall survival. Five immune-related algorithms revealed that the abundance of immune cells, particularly T cells, was greater in the high-risk group than in the low-risk group. The high-risk group also exhibited a higher TMB value, mutation frequency, and immune checkpoint gene expression and a lower tumor TIDE score, suggesting the potential for better immunotherapy outcomes. Additionally, scRNA-seq analysis revealed higher ITGA3 expression in tumor cells compared with normal hepatocytes. Wound healing scratch and transwell cell migration assays revealed that overexpression of the MBRG ITGA3 enhanced migration of HCC HepG2 cells.ConclusionThis study established a direct molecular correlation between metastasis and BM, encompassing clinical features, tumor microenvironment, and immune response, thereby offering valuable insights for predicting clinical outcomes and immunotherapy responses in HCC.

Bioinformatic analysis of differentially expressed genes in lung cancer bone metastasis and their implications for disease progression in lung cancer patients.

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related death worldwide. Moreover, it is highly susceptible to distant metastasis, which is the main cause of pain in advanced lung cancer, and frequently occurs in the bone. This study aimed to identify the differentially expressed genes (DEGs) related to metastatic bone disease in lung cancer using bioinformatics methods and to analyze the risk factors influencing the incidence of secondary bone metastasis in lung cancer. Gene expression profiles from the GSE175601 and GSE10799 datasets in the Gene Expression Omnibus (GEO) database were analyzed to screen for the DEGs associated with lung cancer bone metastasis. The STRING database was used to construct a protein-protein interaction (PPI) network, and the MCODE plugin was used to identify the key genes. The expression of these important genes in lung tumor tissues and their correlation with prognosis were validated in The Cancer Genome Atlas (TCGA) database. An examination of clinical data from patients diagnosed with stage IV lung adenocarcinoma treated at the Anhui No. 2 Provincial People's Hospital was conducted. Immunohistochemistry was used to examine the expression of key genes in lung cancer tumor tissues. A binary logistic regression analysis was conducted to examine the interactions in the expression of critical genes associated with bone metastasis in lung carcinoma patients. In total, 59 DEGs were identified in the GSE175601 and GSE10799 datasets through Venn diagram construction. The PPI network analysis revealed two significant modules and eight candidate genes (LAPTM5, LCP2, CD53, ARHGAP25, C1QA, DES, MYH11, and VIM). According to TCGA database analysis, in carcinogenic tissues of the lung, the expression of these eight critical genes is downregulated. Further, only the lung cancer patients who had high expressions of ARHGAP25 had an improved progress-free interval (PFI) (P<0.05), disease-specific survival (DSS), and overall survival (OS). Of the 49 with stage IV lung adenocarcinoma patients included in the study, 27 (55.10%) developed bone metastasis. The immunohistochemical (IHC) results indicated that the expression score of ARHGAP25 was significantly lower in the group with bone metastasis (3.93±2.95) than the group without bone metastasis (6.64±3.62) (P=0.006). The proportion of patients with low ARHGAP25 expression was significantly higher in the group with bone metastasis (70.37%, 19/27) than the group without bone metastasis (31.82%, 7/22) (P=0.007). The binary logistic regression analysis identified serum alkaline phosphatase (ALP) and ARHGAP25 expression levels as independent risk factors for the occurrence of secondary bone metastatic disease in lung carcinoma patients. The key gene ARHGAP25 identified through bioinformatics for lung cancer bone metastasis was significantly downregulated. Its low expression constitutes an independent risk factor for secondary bone metastatic disease in patients with lung carcinoma.

Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma

BackgroundAlthough there has been some progress in the treatment of primary uveal melanoma (UVM), distant metastasis remains the leading cause of death in patients. Monitoring, staging, and treatment of metastatic disease have not yet reached consensus. Although more than half of metastatic tumors (62%) are diagnosed within five years after primary tumor treatment, the remainder are only detected in the following 25 years. The mechanisms of UVM metastasis and its impact on prognosis are not yet fully understood.MethodsscRNA-seq data of UVM samples were obtained and processed, followed by cell type identification and characterization of macrophage subpopulations. High-dimensional weighted gene co-expression network analysis (HdWGCNA) was performed to identify key gene modules associated with metastatic protective macrophages (MPMφ) in primary samples, and functional analyses were conducted. Non-negative matrix factorization (NMF) clustering and immune cell infiltration analyses were performed using the MPMφ gene signatures. Machine learning models were developed using the identified metastatic protective macrophages related genes (MPMRGs) to distinguish primary from metastatic patients. A deep learning convolutional neural network (CNN) model was constructed based on MPMRGs and cell type associations. Lastly, a prognostic model was established using the MPMRGs and validated in independent cohorts.ResultsSingle-cell RNA-seq analysis revealed a unique immune microenvironment landscape in primary samples compared to metastatic samples, with an enrichment of macrophage cells. Using HdWGCNA, MPMφ and marker genes were identified. Functional analysis showed an enrichment of genes related to antigen processing progress and immune response. Machine learning and deep learning models based on key genes showed significant effectiveness in distinguishing between primary and metastatic patients. The prognostic model based on key genes demonstrated substantial predictive value for the survival of UVM patients.ConclusionOur study identified key macrophage subpopulations related to metastatic samples, which have a profound impact on shaping the tumor immune microenvironment. A prognostic model based on macrophage cell genes can be used to predict the prognosis of UVM patients.

Evaluation of Boric Acid Treatment on microRNA-127-5p and Metastasis Genes Orchestration of Breast Cancer Stem Cells.

Coregulation of microRNAs (miRNAs) and cancer stem cells (CSCs) is very important in carcinogenesis. miR-127-5p is known to be downregulated in breast cancer. In this study, we aimed to investigate how boric acid (BA), known for its previously unstudied anti-cancer properties, would affect the expression of miR127-5p and genes responsible for breast cancer stem cells (BC-SCs) metastasis. BC-SCs were isolated from human breast cancer cells (MCF-7) by immunomagnetic cell separation and characterized with flow cytometry and sphere formation. The viability of BC-SCs and the determination of its IC50 value in response to boric acid (BA) were assessed via the MTT assay. Boric acid exhibited dose- and time-dependent inhibition of cell viability in cells. The IC50 doses of boric acid in MCF-7 cells and BC-SCs were 45.69mM and 41.27mM, respectively. The impact of BA on the expression of metastatic genes and miR127-5p was elucidated through RT-qPCR analysis. While the expression of the COL1A1 (p < 0.05) and VIM (p < 0.01) was downregulated, the expression of the miR-127-5p, ZEB1 (p < 0.01), CDH1 (p < 0.05), ITGB1 (p < 0.05), ITGA5 (p < 0.05), LAMA5 (p < 0.01), and SNAIL (p < 0.05), was up-regulated in dose-treated BC-SCs (p < 0.001) to the RT-qPCR results. Our findings suggest that boric acid could induce miR-127-5p expression. However, it cannot be said that it improves the metastasis properties of breast cancer stem cells.