Biomarker For Carcinoma Research Articles

Investigating surface proteins and antibody combinations for detecting circulating tumor cells of various sarcomas

Circulating tumor cells (CTCs) have gathered attention as a biomarker for carcinomas. However, CTCs in sarcomas have received little attention. In this work, we investigated cell surface proteins and antibody combinations for immunofluorescence detection of sarcoma CTCs. A microfluidic device that combines filtration and immunoaffinity using gangliosides 2 and cell surface vimentin (CSV) antibodies was employed to capture CTCs. For CTC detection, antibodies against cytokeratins 7 and 8 (CK), pan-cytokeratin (panCK), or a combination of panCK and CSV were used. Thirty-nine blood samples were collected from 21 patients of various sarcoma subtypes. In the independent samples study, samples were subjected to one of three antibody combination choices. Significant difference in CTC enumeration was found between CK and panCK + CSV, and between panCK and panCK + CSV. Upon stratification of CK+ samples, those of metastatic disease had a higher CTC number than those of localized disease. In the paired samples study involving cytokeratin-positive sarcoma subtypes, using panCK antibody detected more CTCs than CK. Similarly, for osteosarcoma, using panCK + CSV combination resulted in a higher CTC count than panCK. This study emphasized deliberate selection of cell surface proteins for sarcoma CTC detection and subtype stratification for studying cancers as heterogeneous as sarcomas.

The elevated expression of serum glutathione reductase in hepatocellular carcinoma and its role in assessing the therapeutic efficacy and prognosis of transarterial chemoembolization

BackgroundCurrently, there is a scarcity of reliable biomarkers that can accurately forecast the outcome and prognosis of transarterial chemoembolization (TACE). In this study, we assessed the diagnostic efficacy of serum glutathione reductase (GR) as a biomarker for hepatocellular carcinoma (HCC) and its practicality in predicting TACE treatment response. MethodsThe baseline positive rate and level of serum GR were analyzed and compared between HCC group and control group. Serum GR levels were assessed at three specific time points in 181 patients with unresectable HCC who underwent TACE (HCC-TACE). The correlation between serum GR levels and clinical pathological factors, tumor reactivity, and prognosis was investigated. The modified Response Evaluation Criteria in Solid Tumors (mRECIST) was utilized for assessing the treatment response to TACE. A nomogram for predicting the response to TACE treatment efficacy was developed. ResultsSerum GR demonstrated superior diagnostic performance in HCC patients. The baseline levels of serum GR were associated with the patient's age, tumor size, BCLC staging, and tumor thrombi of the portal vein (TTPV) (p < 0.05). Elevated baseline levels of serum GR were also identified as independent prognostic factors for predicting lower overall survival (OS) and shorter time to radiological progression (TTP) (p < 0.001). Moreover, it is worth noting that non-responders group exhibited a substantial increase in median GR level in the fourth week following TACE treatment (p < 0.0001), whereas the median GR level of responders group did not display a significant augmentation (p > 0.05). Lastly, the changes in serum GRt1-t3 were negatively correlated with TTP (p < 0.001). The nomogram developed to predict the risk of mRECIST responsiveness in patients with HCC-TACE demonstrated excellent discriminatory ability. ConclusionSerum GR can serve as a valuable biomarker for the diagnosis of HCC and for predicting the therapeutic efficacy and prognosis of TACE treatment.

MiR-4429 inhibits ccRCC proliferation, migration, and invasion by directly targeting CD274

Clear cell renal cell carcinoma (ccRCC) is one of the most aggressive urological malignancies and a highly immunogenic cancer. Yet, its pathogenesis is still not fully understood. This study analyzed the role of the miR-320 family in ccRCC using bioinformatics algorithms and a series of in vitro experiments. miR-4429 was found to be significantly down-regulated in ccRCC tissues and cell lines, while overexpression of miR-4429 significantly inhibited renal cancer cell proliferation, migration, and invasion in vitro. In addition, the UALCAN database, immunohistochemistry, and protein blotting results showed that CD274 expression was up-regulated in ccRCC tissues and correlated with higher histologic grading. Dual luciferase assay indicated that CD274 was a direct target of miR-4429. Overexpression of miR-4429 in 786-O, Caki-2 cells significantly inhibited CD274 expression. KEGG results indicated that the potential target function of miR-4429 was associated with the PI3K/AKT signaling pathway, and protein blotting verified the results. In summary, this data shows that miR-4429 targets CD274 and inhibits ccRCC proliferation, migration, and invasion by regulating PI3K/AKT signaling, thus potentially providing a promising therapeutic target and prognostic biomarker for renal cell carcinoma patients.Graphical

Novel prognostic biomarkers in nasopharyngeal carcinoma unveiled by mega-data bioinformatics analysis

Nasopharyngeal carcinoma (NPC) is commonly diagnosed at an advanced stage with a high incidence rate in Southeast Asia and Southeast China. However, the limited availability of NPC patient survival data in public databases has resulted in less rigorous studies examining the prediction of NPC survival through construction of Kaplan-Meier curves. These studies have primarily relied on small samples of NPC patients with progression-free survival (PFS) information or data from head and neck squamous cell carcinoma (HNSCC) studies almost without NPC patients. Thus, we coanalyzed RNA expression profiles in eleven datasets (46 normal (control) vs 160 tumor (NPC)) downloaded from the Gene Expression Omnibus (GEO) database and survival data provided by Jun Ma from Sun Yat-sen University. Then, differential analysis, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and network analysis were performed using STRING database. After that, 2142 upregulated differentially expressed genes (DEGs) and 3857 downregulated DEGs were screened. Twenty-five of them were identified as hub genes, which were enriched in several pathways (cilium movement, extracellular matrix structural constituent, homologous recombination and cell cycle). Utilizing the comprehensive dataset we amassed from GEO database, we conducted a survival analysis of DEGs and subsequently constructed survival models. Seven DEGs (RASGRP2, MOCOS, TTC9, ARHGAP4, DPM3, CD37, and CD72) were identified and closely related to the survival prognosis of NPC. Finally, qRT-PCR, WB and IHC were performed to confirm the elevated expression of RASGRP2 and the decreased expression of TTC9, CD37, DPM3 and ARHGAP4, consistent with the DEG analysis. Conclusively, our findings provide insights into the novel prognostic biomarkers of NPC by mega-data bioinformatics analysis, which suggests that they may serve special targets in the treatment of NPC.

Plasma CD24 level as a promising prognostic biomarker of hepatocellular carcinoma

BackgroundHepatocellular carcinoma constitutes the most common primary hepatic cancer and remains a major medical burden in both developing and developed world. It ranks fifth in terms of global cases and second in terms of deaths for males.CD24 is known as a heavily glycosylated cell surface molecule that is highly expressed in a wide variety of human malignancies. It plays an important role in self-renewal, proliferation, migration, invasion, and drug resistance. The aim of this work was to evaluate the potential role of serum CD24 in the diagnosis and prediction of response to interventional therapy among hepatocellular carcinomas.MethodsThis study included 40 adult Egyptian patients who had liver cirrhosis and hepatocellular carcinoma (HCC group). Another group of 20 patients with liver cirrhosis only served as controls (Cirrhosis group). All patients underwent standard laboratory tests and abdominal ultrasound. For HCC patients, a triphasic CT scan, alpha-fetoprotein was done. CD24 levels were measured in all patients, and in HCC patients at baseline and one month after intervention.ResultsBaseline CD24 was significantly higher among HCC group in comparison to cirrhosis group (19.463 ± 8.573 vs. 0.725 ± 0.125 mg/L) with an overall p value < 0.001. Serum CD24 levels significantly declined after locoregional treatment from 19.463 ± 8.573 mg/L to 3.569 ± 1.248 mg/L (p < 0.001). Baseline CD24 was a useful marker in eligibility for HCC intervention with 80% sensitivity and 74.29% specificity at a cutoff of ≤ 23 mg/L, and it also had 62.96% sensitivity and 100% specificity in prediction of cure after locoregional treatment at a cutoff of ≤ 19.5 mg/L.ConclusionCD24 could be a helpful diagnostic and prognostic marker for HCC, as its baseline level is useful in predicting both eligibility for intervention and cure after locoregional treatment.

Uracil as a biomarker for spatial pyrimidine metabolism in the development of gingivobuccal oral squamous cell carcinoma

No biomarker has yet been identified that allows accurate diagnosis and prognosis of oral cancers. In this study, we investigated the presence of key metabolites in oral cancer using proton nuclear magnetic resonance (NMR) spectroscopy to identify metabolic biomarkers of gingivobuccal oral squamous cell carcinoma (GB-OSCC). NMR spectroscopy revealed that uracil was expressed in 83.09% of tumor tissues and pyrimidine metabolism was active in GB-OSCC; these results correlated well with immunohistochemistry (IHC) and RNA sequencing data. Based on further gene and protein analyses, we proposed a pathway for the production of uracil in GB-OSCC tissues. Uridinetriphosphate (UTP) is hydrolyzed to uridine diphosphate (UDP) by CD39 in the tumor microenvironment (TME). We hypothesized that UDP enters the cell with the help of the UDP-specific P2Y6 receptor for further processing by ENTPD4/5 to produce uracil. As the ATP reserves diminish, the weakened immune cells in the TME utilize pyrimidine metabolism as fuel for antitumor activity, and the same mechanism is hijacked by the tumor cells to promote their survival. Correspondingly, the differential expression of ENTPD4 and ENTPD5 in immune and tumor cells, respectively, indicatedtheir involvement in disease progression. Furthermore, higher uracil levels were detected in patients with lymph node metastasis, indicating that metastatic potential is increased in the presence of uracil. The presence of uracil and/or expression patterns of intermediate molecules in purine and pyrimidine pathways, such asCD39, CD73, and P2Y6 receptors together with ENTPD4 and ENTPD5, hold promise as biomarker(s) for oral cancer diagnosis and prognosis.

Evaluating the diagnostic accuracy of heat shock proteins and their combination with Alpha-Fetoprotein in the detection of hepatocellular carcinoma: a meta-analysis

BackgroundA growing body of research suggests that heat shock proteins (HSPs) may serve as diagnostic biomarkers for hepatocellular carcinoma (HCC), but their results are still controversial. This meta-analysis endeavors to evaluate the diagnostic accuracy of HSPs both independently and in conjunction with alpha-fetoprotein (AFP) as novel biomarkers for HCC detection.MethodsPooled statistical indices, including sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) with 95% confidence intervals (CI), were computed to assess the diagnostic accuracy of HSPs, AFP, and their combinations. Additionally, the area under the summary receiver operating characteristic (SROC) curve (AUC) was determined.ResultsA total of 2013 HCC patients and 1031 control subjects from nine studies were included in this meta-analysis. The summary estimates for HSPs and AFP are as follows: sensitivity of 0.78 (95% CI: 0.69–0.85) compared to 0.73 (95% CI: 0.65–0.80); specificity of 0.89 (95% CI: 0.81–0.95) compared to 0.86 (95% CI: 0.77–0.91); PLR of 7.4 (95% CI: 3.7–14.9) compared to 5.1 (95% CI: 3.3–8.1); NLR of 0.24 (95% CI: 0.16–0.37) compared to 0.31 (95% CI: 0.24–0.41); DOR of 30.19 (95% CI: 10.68–85.37) compared to 16.34 (95% CI: 9.69–27.56); and AUC of 0.90 (95% CI: 0.87–0.92) compared to 0.85 (95% CI: 0.82–0.88). The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.90 (95% CI: 0.82–0.95), 0.94 (95% CI: 0.82–0.98), 14.5 (95% CI: 4.6–45.4), 0.11 (95% CI: 0.06–0.20), 133.34 (95% CI: 29.65–599.61), and 0.96 (95% CI: 0.94–0.98) for the combination of HSPs and AFP.ConclusionOur analysis suggests that HSPs have potential as a biomarker for clinical use in the diagnosis of HCC, and the concurrent utilization of HSPs and AFP shows notable diagnostic effectiveness for HCC.

Tissue expression of miR-449a as risk factor for occult neck metastasis in patients with cT3-T4 N0 laryngeal cancer. A pilot study.

To explore the potential role of miR-449a as biomarker for laryngeal squamous cell carcinoma (LSCC), especially in the decision strategy of neck dissection (ND). Each patient underwent total laryngectomy and bilateral ND (levels II-IV); during surgery, tissue samples of around 1 × 0.5cm were extracted from both healthy tissue adjacent to the tumor and the visibly affected tumor tissue. The extraction of total RNA, encompassing miRNA, was performed using a mirVana PARIS kit. To detect miR449a, cDNA was synthesized from 200ng of RNA using a TaqMan miRNA reverse transcription kit. The study group was formed of 66 patients (62 males, and 4 females) with LSCC, aged between 39 and 77years (mean 60 + 14.56yr). MiR-449a was up-regulated in twenty-eight tumors (42%), while it was down-regulated in 38 samples (58%). In the present study, there was a statistical relevance for miR-449a tissue expression for pN staging (p = 0.017), and PNI (p = 0.005). Eight tumors (12%) cN0 became pN + showing occult cervical lymph node metastases at the final histopathological examination, and all of these patients showed miR-449a downregulation. Super-selective ND (sparing the sub evels IIb and IV) might be the approach to cT3-T4 N0 LSCCs with upregulation of miR-449a; on the other hand, to ensure and effective control of occult neck metastases it would be appropriate to reserve elective ND (including sublevels IIb and IV) for cT3-T4 N0 LSCCs with miR-449a downregulation. Although promising, due to the small size of the cohort, the results of this work can be considered preliminary and need to be confirmed by prospective and larger studies.

Discovering novel prognostic biomarkers of hepatocellular carcinoma using eXplainable Artificial Intelligence

Hepatocellular carcinoma (HCC) remains a global health challenge with high mortality rates, largely due to late diagnosis and suboptimal efficacy of current therapies. With the imperative need for more reliable, non-invasive diagnostic tools and novel therapeutic strategies, this study focuses on the discovery and application of novel genetic biomarkers for HCC using explainable artificial intelligence (XAI). Despite advances in HCC research, current biomarkers like Alpha-fetoprotein (AFP) exhibit limitations in sensitivity and specificity, necessitating a shift towards more precise and reliable markers. This paper presents an innovative multi-model XAI and a probabilistic causal inference framework to identify and validate key genetic biomarkers for HCC prognosis. Our methodology involved analyzing clinical and gene expression data to identify potential biomarkers with prognostic significance. The study utilized robust AI models validated against extensive gene expression datasets, demonstrating not only the predictive accuracy but also the clinical relevance of the identified biomarkers through explainable metrics. The findings highlight the importance of biomarkers such as TOP3B, SSBP3, and COX7A2L, which were consistently influential across multiple models, suggesting their role in improving the predictive accuracy for HCC prognosis beyond AFP. Notably, the study also emphasizes the relevance of these biomarkers to the Hispanic population, aligning with the larger goal of demographic-specific research. The application of XAI in biomarker discovery represents a significant advancement in HCC research, offering a more nuanced understanding of the disease and laying the groundwork for improved diagnostic and therapeutic strategies.

Angiopoietin-2 as a diagnostic biomarker for Liver cirrhosis and Hepatocellular Carcinoma

Angiopoietin-2 as a diagnostic biomarker for Liver cirrhosis and Hepatocellular Carcinoma

Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis

Background & AimsThe effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of the screening modalities. MethodsWe developed a multicenter prospective cohort of cirrhotic patients undergoing surveillance with MRI, and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up. ResultsWe identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who didn’t develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine, had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, patatin-like phospholipase domain-containing protein 3 (PNPLA3) and transmembrane 6 superfamily member 2 (TMS6SF2) SNPs, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top 6 variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC=0.88 [0.83-0.93]). Finally, 23 metabolites distinguished Cases with Liver Imaging Reporting and Data System (LI-RADS)-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases-LR3. ConclusionsThis study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as main biomarkers of HCC risk, and microbiota-derived metabolites as main contributors to HCC development. Impact and ImplicationsThe effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited. There is an urgent need for improvement in risk stratification and new screening modalities, blood biomarkers in particular. Longitudinal collection of paired blood samples and MRI images from cirrhotic patients is particularly valuable in assessing how early blood and imaging markers become positive during the period when lesions are observed to obtain a diagnosis of HCC. We generated a multicenter prospective cohort of patients with cirrhosis under surveillance with contrast MRI, applied untargeted metabolomics on 612 serum samples from 203 patients and identified metabolites associated with risk of HCC development. Such biomarkers may significantly improve early stage HCC detection for cirrhotic patients undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality.

Identification of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising.MethodsRNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models.ResultsAn initial cluster analysis of RNA-seq expression data showed separation by the subjects’ gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091).ConclusionsOur study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

PCDHGA10 as a Potential Biomarker of Lung Squamous Cell Carcinoma Based on Bioinformatics and Experimental Verification.

Procalcitonin gamma subfamily A, 10 (PCDHGA10) is a member of the procalcitonin gamma gene cluster, which is associated with neuronal synapse development. However, there are lack of studies on the role and potential prognostic value of PCDHGA10 in lung squamous cell carcinoma (LUSC). We analyzed the RNAseq data of PCDHGA10 to compare their expression differences. Then survival analysis, tumor microenvironment (TME) analysis, and mutation analysis were carried out. Additionally, we performed gene ontology (GO) and kyoto gene encyclopedia (KEGG) enrichment analyses to explore potential signal pathways. PCDHGA10 protein expression was evaluated using immunohistochemistry (IHC) on tissue microarrays (HLugS180Su02). By microarray analysis and database analysis, we found that PCDHGA10 was significantly highly expressed in LUSC. Sufferers with elevated PCDHGA10 levels exhibited a worse prognosis, according to the survival analysis. The PCDHGA10 mutation was also linked to LUSC patient prognosis. Besides, PCDHGA10 was closely related to tumor immune cell infiltration andimmunecheckpoints. In conclusion, PCDHGA10 is expected to become a new molecular marker for LUSC.

EnsemBic: An effective ensemble of biclustering to identify potential biomarkers of esophageal squamous cell carcinoma

The development of functionally enriched and biologically competent biclustering algorithm is essential for extracting hidden information from massive biological datasets. This paper presents a novel biclustering ensemble called EnsemBic based on p-value, which calculates the functional similarity of genetic associations. To validate the effectiveness and robustness of EnsemBic, we apply three well-known biclustering techniques, viz. Laplace Prior, iBBiG, and xMotif to implement EnsemBic and have been compared using different leading parameters. It is observed that the EnsemBic outperforms its competing algorithms in several prominent functional and biological measures. Next, the biclusters obtained from EnsemBic are used to identify potential biomarkers of Esophageal Squamous Cell Carcinoma (ESCC) by exploring topological and biological relevance with reference to the elite genes, attained from genecards. Finally, we discover that the genes F2RL3, APPL1, CALM1, IFNGR1, LPAR1, ANGPT2, ARPC2, CGN, CLDN7, ATP6V1C2, CEACAM1, FTL, PLAU,PSMB4, and EPHB2 carry both the topological and biological significance of previously established ESCC elite genes. Therefore, we declare the aforementioned genes as potential biomarkers of ESCC.

Lipid Identification of Biomarkers in Esophageal Squamous Cell Carcinoma by Lipidomic Analysis

Lipids participate in many important biological functions through energy storage, membrane structure stabilization, signal transduction, and molecular recognition. Previous studies have shown that patients with esophageal squamous cell carcinoma (ESCC) have abnormal lipid metabolism. However, studies characterizing lipid metabolism in ESCC patients through lipidomics are limited. Plasma lipid profiles of 65 ESCC patients and 42 healthy controls (HC) were characterized by lipidomics-based ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Single-factor and multi-factor statistical analysis were used to screen the differences in blood lipids between groups, and combined with component ratio analysis and receiver operating characteristic (ROC) curve diagnostic efficiency assessment, to reveal the potential mechanisms and biomarkers of ESCC. There were significant differences in lipid profiles between the ESCC and HC groups. Thirty-six differential lipids (11 up-regulated and 25 down-regulated) were selected based on the criteria of p < .05 and fold change > 1.3 or < 0.77. Glycerophospholipids were the major differential lipids, suggesting that these lipid metabolic pathways exhibit a significant imbalance that may contribute to the development of esophageal squamous cell carcinoma. Among them, the seven candidate biomarkers for esophageal squamous cell carcinoma with the highest diagnostic value are three phosphatidylserine (PS), three fatty acids (FA) and one phosphatidylcholine (PC).

Clinical significance of PNO1 as a novel biomarker and therapeutic target of hepatocellular carcinoma.

The RNA-binding protein PNO1 plays an essential role in ribosome biogenesis. Recent studies have shown that it is involved in tumorigenesis; however, its role in hepatocellular carcinoma (HCC) is not well understood. The purpose of this study was to examine whether PNO1 can be used as a biomarker of HCC and also examine the therapeutic potential of PNO1 knockout for the treatment of HCC. PNO1 expression was upregulated in HCC and associated with poor prognosis. PNO1 expression was positively associated with tumour stage, lymph node metastasis and poor survival. PNO1 expression was significantly higher in HCC compared to that in fibrolamellar carcinoma or normal tissues. Furthermore, HCC tissues with mutant Tp53 expressed higher PNO1 than those with wild-type Tp53. PNO1 knockout suppressed cell viability, colony formation and EMT of HCC cells. Since activation of Notch signalling pathway promotes HCC, we measured the effects of PNO1 knockout on the components of Notch pathway and its targets. PNO1 knockout suppressed Notch signalling by modulating the expression of Notch ligands and their receptors, and downstream targets. PNO1 knockout also inhibited genes involved in surface adhesion, cell cycle, inflammation and chemotaxis. PNO1 knockout also inhibited colony and spheroid formation, cell migration and invasion, and markers of stem cells, pluripotency and EMT in CSCs. Overall, our data suggest that PNO1 can be used as a diagnostic and prognostic biomarker of HCC, and knockout of PNO1 by CRISPR/Cas9 can be beneficial for the management of HCC by targeting CSCs.

Construction of a TP53 mutation-associated ceRNA network as prognostic biomarkers in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) continues to endanger human health worldwide. Regulatory networks of competing endogenous RNAs (ceRNAs) play important roles in HCC. TP53 is the second most often altered gene in HCC and has a significant role in regulating target genes such as miRNAs and lncRNAs. MethodsData from patients with TP53 mutation were collected through the cBioPortal database and differential analysis was performed to screen RNAs related to TP53 mutation. The lncRNA-miRNA–mRNA relationship was predicted by the miRcode, miRDB, and TargetScan databases. The ceRNA networks were screened and visualized by Cytoscape. Core ceRNA networks were generated by differential analysis, coexpression analysis, prognostic analysis and subcellular localization. Finally, methylation, mutation, PPI, GSEA, immunity and drug sensitivity analyses of MEX3A were performed to determine the role of MEX3A in HCC. ResultsWe identified 1508 DEmRNAs, 85 DEmiRNAs and 931 DElncRNAs and obtained a ceRNA network including 28 lncRNAs, 4 miRNAs and 31 mRNAs. Twenty hub DERNAs in the TP53-altered-related ceRNA network were screened out by Cytoscape and the core ceRNA network (LINC00491/TCL6-hsa-miR-139-5p-MEX3A) was obtained by multiple analyses. In addition, we discovered that the methylation level of MEX3A was decreased and the mutation frequency was raised in HCC. Furthermore, elevated MEX3A expression was associated with alterations in the HCC immunological microenvironment. ConclusionWe successfully constructed a reciprocal ceRNA network, which could provide new ideas for exploring HCC mechanisms and therapeutic approaches.

Plasma-based lipidomics reveals potential diagnostic biomarkers for esophageal squamous cell carcinoma: a retrospective study.

Esophageal squamous cell carcinoma (ESCC) is highly prevalent and has a high mortality rate. Traditional diagnostic methods, such as imaging examinations and blood tumor marker tests, are not effective in accurately diagnosing ESCC due to their low sensitivity and specificity. Esophageal endoscopic biopsy, which is considered as the gold standard, is not suitable for screening due to its invasiveness and high cost. Therefore, this study aimed to develop a convenient and low-cost diagnostic method for ESCC using plasma-based lipidomics analysis combined with machine learning (ML) algorithms. Plasma samples from a total of 40 ESCC patients and 31 healthy controls were used for lipidomics study. Untargeted lipidomics analysis was conducted through liquid chromatography-mass spectrometry (LC-MS) analysis. Differentially expressed lipid features were filtered based on multivariate and univariate analysis, and lipid annotation was performed using MS-DIAL software. A total of 99 differential lipids were identified, with 15 up-regulated lipids and 84 down-regulated lipids, suggesting their potential as diagnostic targets for ESCC. In the single-lipid plasma-based diagnostic model, nine specific lipids (FA 15:4, FA 27:1, FA 28:7, FA 28:0, FA 36:0, FA 39:0, FA 42:0, FA 44:0, and DG 37:7) exhibited excellent diagnostic performance, with an area under the curve (AUC) exceeding 0.99. Furthermore, multiple lipid-based ML models also demonstrated comparable diagnostic ability for ESCC. These findings indicate plasma lipids as a promising diagnostic approach for ESCC.

Proteomics Identifies LUC7L3 as a Prognostic Biomarker for Hepatocellular Carcinoma.

Alternative splicing has been shown to participate in tumor progression, including hepatocellular carcinoma. The poor prognosis of patients with HCC calls for molecular classification and biomarker identification to facilitate precision medicine. We performed ssGSEA analysis to quantify the pathway activity of RNA splicing in three HCC cohorts. Kaplan-Meier and Cox methods were used for survival analysis. GO and GSEA were performed to analyze pathway enrichment. We confirmed that RNA splicing is significantly correlated with prognosis, and identified an alternative splicing-associated protein LUC7L3 as a potential HCC prognostic biomarker. Further bioinformatics analysis revealed that high LUC7L3 expression indicated a more progressive HCC subtype and worse clinical features. Cell proliferation-related pathways were enriched in HCC patients with high LUC7L3 expression. Consistently, we proved that LUC7L3 knockdown could significantly inhibit cell proliferation and suppress the activation of associated signaling pathways in vitro. In this research, the relevance between RNA splicing and HCC patient prognosis was outlined. Our newly identified biomarker LUC7L3 could provide stratification for patient survival and recurrence risk, facilitating early medical intervention before recurrence or disease progression.

Identification of SUMOylation-related biomarkers in papillary thyroid carcinoma

BackgroundSmall ubiquitin-like modifier (SUMO) modification is increasingly recognized as critical in tumorigenesis and progression. This study identifies biomarkers linked to SUMOylation in papillary thyroid carcinoma (PTC), aiming to advance therapeutic and prognostic strategies.MethodsEmploying PTC datasets and SUMO related genes (SRGs), we utilized univariate Cox regression for prognosis-related SRGs, conducted differential expression analyses, and integrated findings to pinpoint candidate genes. These genes underwent further validation through survival, gene set enrichment, immune infiltration, and drug sensitivity analyses, including external validation via quantitative RT-qPCR. In our final step, we conducted immunohistochemical staining on tumor samples from PTC patients at our center and integrated this with their clinical data to validate BMP8A’s effectiveness in predicting recurrence in PTC.ResultsThree biomarkers—BMP8A, RGS8, and SERPIND1—emerged as significant. Gene Set Enrichment Analysis (GSEA) showed their involvement in immune-related pathways, with differential immune infiltration patterns and drug response correlations observed, underscoring their potential for targeted therapy. Lastly, we validated the efficacy of BMP8A in predicting the recurrence of PTC in patients using clinical and pathological data from our center.ConclusionThe study identifies BMP8A, RGS8, and SERPIND1 as key biomarkers associated with SUMOylation in PTC. Their linkage to immune response and drug sensitivity highlights their importance as targets for therapeutic intervention and prognosis in PTC research.