LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer.

BACKGROUND: Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach. METHODS: In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels. RESULTS: There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965. CONCLUSION: This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Discovery of a proliferation essential gene signature and actin-like 6A as potential biomarkers for predicting prognosis and neoadjuvant chemotherapy response in triple-positive breast cancer.

BACKGROUND: Patients with triple-positive breast cancer (TPBC) have a higher risk of recurrence and lower survival rates than patients with other luminal breast cancers. However, there are few studies on the predictive biomarkers of prognosis and treatment responses in TPBC. METHODS: Proliferation essential genes (PEGs) were acquired from clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR-Cas9) technology, and cohorts of patients with TPBC were obtained from public databases and our cohort. To develop a TPBC-PEG signature, Cox regression and least absolute shrinkage and selection operator regression analyses were applied. Functional analyses were performed with gene set enrichment analysis. The relationship between candidate genes and neoadjuvant chemotherapy (NACT) sensitivity was explored via real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) on the basis of clinical samples. RESULTS: Among 900 TPBC-PEGs, 437 showed significant differential expression between TPBC and normal tissues. Three prognostic PEGs (actin-like 6A [ACTL6A], chaperonin containing TCP1 subunit 2 [CCT2], and threonyl-TRNA synthetase [TARS]) were identified and used to construct the PEG signature. Patients with high PEG signature scores exhibited a worse overall survival and lower sensitivity to NACT than patients with low PEG signature scores. RT-qPCR results indicated that ACTL6A and CCT2 expression were significantly upregulated in patients who lacked sensitivity to NACT. IHC results showed that the ACTL6A protein was highly expressed in patients with NACT resistance and nonpathological complete responses. CONCLUSIONS: This efficient PEG signature prognostic model can predict the outcomes of TPBC. Furthermore, ACTL6A expression level was associated with the response to NACT, and could serve as an important factor in predicting prognosis and drug sensitivity of patients with TPBC.

Assessing the role of programmed cell death signatures and related gene TOP2A in progression and prognostic prediction of clear cell renal cell carcinoma.

Kidney Clear Cell Carcinoma (KIRC), the predominant form of kidney cancer, exhibits a diverse therapeutic response to Immune Checkpoint Inhibitors (ICIs), highlighting the need for predictive models of ICI efficacy. Our study has constructed a prognostic model based on 13 types of Programmed Cell Death (PCD), which are intertwined with tumor progression and the immune microenvironment. Validated by analyses of comprehensive datasets, this model identifies seven key PCD genes that delineate two subtypes with distinct immune profiles and sensitivities to anti-PD-1 therapy. The high-PCD group demonstrates a more immune-suppressive environment, while the low-PCD group shows better responses to PD-1 treatment. In particular, TOP2A emerged as crucial, with its inhibition markedly reducing KIRC cell growth and mobility. These findings underscore the relevance of PCDs in predicting KIRC outcomes and immunotherapy response, with implications for enhancing clinical decision-making.

NLISA versus enzyme-linked immunosorbent assay: Nanozyme-linked immunosorbent array based on platinum sub-nanocluster nanozyme for α-fetoprotein detection.

Rapid and accurate identification of tumor metabolic markers is important for early tumor diagnosis and individualized treatment. Here, a stable monodisperse sub-nanometer platinum (Pt) material was developed as a highly efficient nanozyme with a specific activity of peroxidase as high as 20.86 U mg-1 through the growth of in situ domain-limited Pt quantum dots via the polymer polyvinylpyrrolidone. Further, the synthesis of large quantities of Pt-loaded SiO2 (Pt-SiO2 ) was determined by silylation reaction and used for naked eye colorimetric testing of human alpha-fetoprotein (AFP). In particular, the immunization incubation process occurred in preprepared microplates. A nanozyme-based immunomodel was constructed in the presence of the target AFP, and a chromogenic reaction occurred with exogenous hydrogen peroxide and the chromogenic substrate tetramethylbenzidine. On optimization of experimental conditions, the dynamic working response range for AFP was found to be 0.05-20 ng mL-1 , with a limit of detection of 38.7 pg mL-1 . This work provides a new strategy to design efficient nanozyme-based enzyme-linked immunochromatographic platforms to meet the practical use of replacing natural enzymes.

Gastric cancer peritoneal metastasis related signature predicts prognosis and sensitivity to immunotherapy in gastric cancer.

Gastric cancer peritoneal metastases (GCPM) is a leading cause of GC-related death. Early detection of GCPM is critical for improving the prognosis of advanced GC. Differentially expressed genes (DEGs) were identified in the GSE62254 database to distinguish between GCPM and non-GCPM. The gastric cancer peritoneal metastases signature (GCPMs) was developed using DEGs. We analysed the effectiveness of GCPMs as indicators for prognosis, chemotherapy, and immune therapy response in GC patients. Subsequently, we analysed the correlation between GCPMs and immune microenvironment as well as immune escape in GC patients. Random forest model and immunohistochemistry was utilized to identify the crucial genes that can aid in the diagnosis of GCPM. We identified five DEGs and utilized their expression to construct GCPMs. Patients with high GCPMs had a higher likelihood of a poor prognosis, while those with low GCPMs appeared to potentially benefit more from chemotherapy. GCPMs were a dependable marker for predicting the response to immunotherapy. Additionally, GCPMs was found to be significantly linked to stromal score and cancer-associated fibroblasts. SYNPO2 has been identified as the gene with the highest significance in the diagnosis of GCPM. Immunohistochemistry suggests that SYNPO2-positive expression in tumour cells, fibroblasts, inflammatory cell may be associated with promoting peritoneal metastasis in GC. GCPMs have shown to be a promising biomarker for predicting the prognosis and response of GC patients to chemotherapy and immunotherapy. The use of GCPMs for individual tumour evaluation may pave the way for personalized treatment for GC patients in the future.

Identification of LARS as an essential gene for osteosarcoma proliferation through large-Scale CRISPR-Cas9 screening database and experimental verification.

BACKGROUND: Osteosarcoma is one of the most malignant tumors, and it occurs mostly in children and adolescents. Currently, surgery and chemotherapy are the main treatments. The recurrence rate is high and the prognosis is often poor. Finding an effective target gene therapy for osteosarcoma may effectively improve its prognosis. METHOD: In this study, genes essential for the survival of osteosarcoma cells were identified by genome-wide screening of CRISPR-Cas9 based on the DepMap database. The expression of these essential genes in osteosarcoma patients' tissues and normal tissues was identified in the GSE19276 database. Functional pathway enrichment analysis, protein interaction network construction, and LASSO were performed to construct a prognostic risk model based on these essential genes. CCK8 assay was used to detect the effect of essential gene-LARS (Leucyl-TRNA Synthetase 1) on the proliferation of osteosarcoma. RESULTS: In this study, 785 genes critical for osteosarcoma cell proliferation were identified from the DepMap. Among these 785 essential genes, 59 DEGs were identified in osteosarcoma tissues. In the functional enrichment analysis, these 59 essential genes were mainly enriched in cell cycle-related signaling pathways. Furthermore, we established a risk score module, including LARS and DNAJC17, screened from these 59 genes, and this module could divide osteosarcoma patients into the low-risk and high-risk groups. In addition, knockdown of LARS expression inhibited the proliferative ability of osteosarcoma cells. A significant correlation was found between LARS expression and Monocytic lineage, T cells, and Fibroblasts. CONCLUSION: In conclusion, LARS was identified as an essential gene for survival in osteosarcoma based on the DepMap database. Knockdown of LARS expression significantly inhibited the proliferation of osteosarcoma cells, suggesting that it is involved in the formation and development of osteosarcoma. The results are useful as a foundation for further studies to elucidate a potential osteosarcoma diagnostic index and therapeutic targets.

Signaling networks and the feasibility of computational analysis in gastroenteropancreatic neuroendocrine tumors.

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare diseases with a prevalence that has been increasing over the past three decades. The unsatisfactory outcome of these diseases has encouraged a great amount of research attention and discussion. Currently, to the best of our knowledge, studies on transcriptome screening and molecular mechanisms of the pathogenesis of GEP-NETs are limited. In this review, we have summarized the signaling network of GEP-NETs and the recent meta-analysis-related studies, and we have discussed the potential research direction for GEP-NETs, especially based on computational analysis.

Death-associated protein kinase 1 suppresses hepatocellular carcinoma cell migration and invasion by upregulation of DEAD-box helicase 20.

Death-associated protein kinase 1 (DAPK) is a calcium/calmodulin kinase that plays a vital role as a suppressor gene in various cancers. Yet its role and target gene independent of p53 is still unknown in hepatocellular carcinoma (HCC). In this study, we discovered that DAPK suppressed HCC cell migration and invasion instead of proliferation or colony formation. Using a proteomics approach, we identified DEAD-box helicase 20 (DDX20) as an important downstream target of DAPK in HCC cells and critical for DAPK-mediated inhibition of HCC cell migration and invasion. Using integrin inhibitor RGD and GTPase activity assays, we discovered that DDX20 suppressed HCC cell migration and invasion through the CDC42-integrin pathway, which was previously reported as an important downstream pathway of DAPK in cancer. Further research using cycloheximide found that DAPK attenuates the proteasomal degradation of DDX20 protein, which is dependent on the kinase activity of DAPK. Our results shed light on new functions and regulation for both DAPK and DDX20 in carcinogenesis and identifies new potential therapeutic targets for HCC.

Evaluation of MiR-1908-3p as a novel serum biomarker for breast cancer and analysis its oncogenic function and target genes.

BACKGROUND: Breast cancer is one of the most common tumors for women globally. Various miRNAs have been reported to play a crucial role in breast cancer, however the clinical significance of miR-1908-3p in breast cancer remains unclear. The present study aimed to explore the role of miR-1908-3p in breast cancer. METHODS: The expression of miR-1908-3p was detected in 50 pairs of breast cancer tissues and adjacent normal tissues, 60 breast cancer patient serum and 60 healthy volunteer serum. The functional roles of miR-1908-3p in breast cancer cells such as proliferation, migration and invasion were evaluated using CCK8, SRB, wound healing and transwell chambers. In addition, bioinformatics tools were used to identify potential targets of miR-1908-3p. RESULTS: The results showed that the expression of miR-1908-3p were increased in breast cancer tissues and serum compared with normal breast tissues and serum of healthy volunteers respectively. Furthermore, the young breast cancer patients and HER2-positive patients had a higher level of tissues' miR-1908-3p than elder breast cancer patients and HER2-negative patients, respectively. The young breast cancer patients had a higher level of serum miR-1908-3p than elder breast cancer patients, ROC analysis suggested that miR-1908-3p had the potential as a promising serum diagnostic biomarker of breast cancer. Up-regulation of miR-1908-3p promoted the cells proliferation, migration and invasion while knockdown of miR-1908-3p inhibited these processes in breast cancer cell MCF-7 and MDA-MB-231. The potential target genes of miR-1908-3p in breast cancer included ID4, LTBP4, GPM6B, RGMA, EFCAB1, ALX4, OSR1 and PPARA. Higher expression of these eight genes correlated with a better prognosis for breast cancer patients. CONCLUSIONS: These results suggest that miR-1908-3p may exert its oncogenic functions via suppression of these eight genes in breast cancer.

Distance-dependent visual fluorescence immunoassay on CdTe quantum dot-impregnated paper through silver ion-exchange reaction.

A paper-based visual fluorescence immunoassay is presented for the detection of matrix metalloproteinase-7 (MMP7) that is related to renal cancer. The method is based on the distance-dependent fluorescence quenching of CdTe quantum dots (QDs) on a nitrocellulose membrane by Ag+ following a sandwich-type immunoreaction on microtiter wells using silver nanoparticle (AgNP)-labeled secondary antibody- and primary antibody-coated microtiter wells. The silver nanoparticles captured in the well are dissolved with HNO3, while the quenching effect of QDs is based on silver ion-exchange reaction under 365-nm excitation light irradiation. Increasing concentration of released Ag+, thus higher concentration of the protein, leads to an increased distance of quenching on the nitrocellulose membrane. The paper-based immunoassay by combination of AgNP-assisted ion-exchange reaction with QD gives good distance-dependent responses and allows the detection of MMP7 at a concentration as low as 7.3 pg mL-1. The coefficients of variation are less than 6.9% and 12.4% for intra-assay and inter-assay, respectively. High specificity and long-term stability are achieved during the assay. Importantly, the testing of human serum samples using our strategy shows well-matched results with commercial human MMP7 ELISA kits. Graphical abstract A distance-dependent visual immunoassay is developed for the determination of serum matrix metalloproteinase-7 on CdTe quantum dot-impregnated paper with silver ion-exchange reaction.

A nanohybrid composed of Prussian Blue and graphitic C3N4 nanosheets as the signal-generating tag in an enzyme-free electrochemical immunoassay for the neutrophil gelatinase-associated lipocalin.

An enzyme-free electrochemical immunoassay is described for the neutrophil gelatinase-associated lipocalin (NGAL; a biomarker of kidney disease). Prussian Blue (PB) nanoparticles with redox activity were deposited on graphitic C3N4 nanosheets (g-C3N4) by in-situ reduction. A screen printed electrode (SPCE) was modified with antibody against NGAL, and the PB-g-C3N4 nanohybrid was used as the signal-generating tag for the secondary antibody against NGAL. Upon addition of target NGAL and of secondary antibody, a sandwich is formed on the SPCE. At an applied potential of typically 0.13 V (vs. Ag/AgCl), a well-defined voltammetric peak is observed that results from the presence of PB on the secondary antibody. Under optimal conditions, the peak current increases linearly in the 0.01 to 10 ng·mL-1 NGAL concentration range, and the detection limit is 2.8 pg·mL-1. An average precision of <12% was accomplished in the batch-to-batch mode. Other disease-related biomarkers do not interfere. The accuracy and inter-laboratory validation of this method were evaluated for target NGAL detection in spiked human serum by using a commercial ELISA. The results obtained by the two methods are in good accordance. Graphical abstract An enzyme-free electrochemical immunoassay was used for detection of neutrophil gelatinase-associated lipocalin by Prussian blut/graphitic-C3N4 nanohybrids as the signal-generation tags.

The Roles of microRNAs in Regulating the Expression of PD-1/PD-L1 Immune Checkpoint.

Engagement of programmed death-ligand 1 (PD-L1) with its receptor programmed death 1 (PD-1) on T cells has been speculated to play a major role in suppressing the immune system, which helps tumor cells evade anti-tumor immunity. With the development of whole genome sequencing technologies, microRNAs have gained more attention as an important new layer of molecular regulation. Recent studies have revealed that altered expression of microRNAs play a pivotal role in immune checkpoint and various cellular processes in cancer. In this review, we focused on the latest progress about microRNAs research which involves the regulation of PD-1/PD-L1 immune checkpoint.

Method for RNA extraction and cDNA library construction from microbes in crop rhizosphere soil.

Techniques to analyze the transcriptome of the soil rhizosphere are essential to reveal the interactions and communications between plants and microorganisms in the soil ecosystem. In this study, different volumes of Al2(SO4)3 were added to rhizosphere soil samples to precipitate humic substances, which interfere with most procedures of RNA and DNA analyses. After humic substances were precipitated, cells of soil microorganisms were broken by vortexing with glass beads, and then DNA and RNA were recovered using Tris-HCl buffer with LiCl, SDS, and EDTA. The crude extract was precipitated and dissolved in RNAse-free water, and then separated by agarose gel electrophoresis. We determined the optimum volume of Al2(SO4)3 for treating rhizosphere soil of rice, tobacco, sugarcane, Rehmannia glutinosa, and Pseudostellaria heterophylla. The crude nucleic acids extract from rice soil was treated with DNase I and then RNA was purified using a gel filtration column. The purified RNA was reverse-transcribed into single-strand cDNA and then ligated with an adaptor at each end before amplifying ds cDNA. The ds cDNA was sub-cloned for subsequent gene sequence analysis. We conducted qPCR to amplify 16S ribosomal DNA and observed highly efficient amplification. These results show that the extraction method can be optimized to isolate and obtain high-quality nucleic acids from microbes in different rhizosphere soils, suitable for genomic and post-genomic analyses.

Characterization of an endoplasmic reticulum stress-associated lncRNA prognostic signature and the tumor-suppressive role of RP11-295G20.2 knockdown in lung adenocarcinoma.

Endoplasmic reticulum stress (ERS) is commonly induced by accumulating misfolded or unfolded proteins in tumor microenvironment. Long non-coding RNAs (lncRNAs) play important roles in ERS response and lung adenocarcinoma (LUAD) progression. However, the role of ERS-related lncRNAs in LUAD remains unknown. In this study, we aimed to identify ERS-associated lncRNAs with prognostic value in LUAD and characterize their clinical implications. Cox and least absolute shrinkage and selection operator regression analyses identified nine ERS-related lncRNAs with independent prognostic abilities, including five protective factors (CROCCP2, KIAA0125, LINC0996, RPARP-AS1 and TBX5-AS1) and four risk factors (LINC0857, LINC116, RP11-21L23.2 and RP11-295G20.2). We developed an ERS-related lncRNA risk prediction model in predicting overall survival of LUAD patients, which classified TCGA cohorts into high-risk (HS) and low-risk (LS) groups. Comprehensive bioinformatic analyses revealed HS patients featured with late-stage tumors, greater mutation burdens, weaker anti-tumor immunity/responses, and lower sensitivity to targeted drugs compared to LS patients, contributing to tumor progression and a poor prognosis. Functional enrichment analysis implicated these ERS-related lncRNAs in cell migration, cell death, and immunity. Furthermore, expression of the most significantly upregulated risk lncRNA, RP11-295G20.2, was validated at the mRNA level using clinical LUAD samples. Knockdown of RP11-295G20.2 obviously reduced ERS and suppressed proliferation, invasion, and migration of LUAD cells. This novel ERS-related lncRNA signature provides a new biomarker for prognostic prediction, and ERS-associated RP11-295G20.2 serves as a potential therapeutic target in LUAD.

The prognosis, chemotherapy and immunotherapy efficacy of the SUMOylation pathway signature and the role of UBA2 in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors worldwide. Small Ubiquitin-like Modifier (SUMO)-ylation plays a crucial role in tumorigenesis. However, the SUMOylation pathway landscape and its clinical implications in LUAD remain unclear. Here, we analyzed genes involved in the SUMOylation pathway in LUAD and constructed a SUMOylation pathway signature (SUMOPS) using the LASSO-Cox regression model, validated in independent cohorts. Our analysis revealed significant dysregulation of SUMOylation-related genes in LUAD, comprising of favorable or unfavorable prognostic factors. The SUMOPS model was associated with established molecular and histological subtypes of LUAD, highlighting its clinical relevance. The SUMOPS stratified LUAD patients into SUMOPS-high and SUMOPS-low subtypes with distinct survival outcomes and adjuvant chemotherapy responses. The SUMOPS-low subtype showed favorable responses to adjuvant chemotherapy. The correlations between SUMOPS scores and immune cell infiltration suggested that patients with the SUMOPS-high subtype exhibited favorable immune profiles for immune checkpoint inhibitor (ICI) treatment. Additionally, we identified UBA2 as a key SUMOylation-related gene with an increased expression and a poor prognosis in LUAD. Cell function experiment confirmed the role of UBA2 in promoting LUAD cell proliferation, invasion, and migration. These findings provide valuable insights into the SUMOylation pathway and its prognostic implications in LUAD, paving the way for personalized treatment strategies and the development of novel therapeutic targets.

Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance.

Background: Bladder cancer (BLCA) is the most common genitourinary malignancy. Proliferation essential genes (PEGs) are crucial to the survival of cancer cells. This study aimed to build a PEG signature to predict BLCA prognosis and treatment efficacy. Methods: BLCA PEGs and differentially expressed PEGs were identified using DepMap and TCGA-BLCA datasets, respectively. Based on the prognostic analysis of the differentially expressed PEGs, a PEG model was constructed. Subsequently, we analyzed the relationship between the PEG signature and prognosis of BLCA patients as well as their response to chemotherapy. Finally, we performed random forest analysis to target and functional experiments to validate the most significant PEG which is associated with BLCA progression. CCK-8, invasion, migration, and chemosensitivity assays were performed to assess effects of gene knockdown on BLCA cell proliferation, invasion and migration abilities, and cisplatin chemosensitivity. Results: We screened 10 prognostic PEGs from 201 differentially expressed PEGs and used them to construct a PEG signature model. Patients with high PEG signature score (PEGs-high) exhibited worse OS and lower sensitivity to chemotherapy than those with PEGs-low. We also found significant correlations between the PEG score and previously defined BLCA molecular subtypes. This suggests that the PEG score may effectively predict the molecular subtypes which have distinct clinical outcomes. Random forest analysis revealed that POLE2 (DNA polymerase epsilon subunit 2) was the most significant PEG differentiating BLCA tissue and normal tissue. Bioinformatic analysis and an immunohistochemistry staining assay confirmed that POLE2 was significantly up-regulated in tumor tissues and was associated with poor survival in BLCA patients. Moreover, POLE2 knockdown inhibited the ability of cell clone formation, proliferation, invasion, immigration and IC50 of cisplatin. Conclusion: The PEG signature acts as a potential predictor for prognosis and chemotherapy response in BLCA patients. POLE2 is a key PEG and plays a remarkable role in promoting the malignant progression and cisplatin resistance of BLCA.

Target-triggered assembly of plasmon resonance nanostructures for quantitative detection of lncRNA in liver cancer cells via surface enhanced Raman spectroscopy.

Long-stranded non-coding RNAs (lncRNA) have important roles in disease as transcriptional regulators, mRNA processing regulators and protein synthesis factors. However, traditional methods for detecting lncRNA are time-consuming and labor-intensive, and the functions of lncRNA are still being explored. Here, we present a surface enhanced Raman spectroscopy (SERS) based biosensor for the detection of lncRNA associated with liver cancer (LC) as well as in situ cellular imaging. Using the dual SERS probes, quantitative detection of lncRNA (DAPK1-215) can be achieved with an ultra-low detection limit of 952 aM by the target-triggered assembly of core-satellite nanostructures. And the reliability of this assay can be further improved with the R2 value of 0.9923 by an internal standard probe that enables the signal dynamic calibration. Meanwhile, the high expression of DAPK1-215 mainly distributed in the cytoplasm was observed in LC cells compared with the normal ones using the SERS imaging method. Moreover, results of cellular function assays showed that DAPK1-215 promoted the migration and invasion of LC by significantly reducing the expression of the structural domain of death associated protein kinase. The development of this biosensor based on SERS can provide a sensitive and specific method for exploring the expression of lncRNA that would be a potential biomarker for the screening of LC.

Establishment of a SUMO pathway related gene signature for predicting prognosis, chemotherapy response and investigating the role of EGR2 in bladder cancer.

Background: Bladder cancer is a prevalent malignancy with significant clinical implications. Small Ubiquitin-like Modifier (SUMO) pathway related genes (SPRG) have been implicated in the development and progression of cancer. Methods: In this study, we conducted a comprehensive analysis of SPRG in bladder cancer. We analyzed gene expression and prognostic value of SPRG and developed a SPRG signature (SPRGS) prognostic model based on four genes (HDAC4, TRIM27, EGR2, and UBE2I) in bladder cancer. Furthermore, we investigated the relationship between SPRGS and genomic alterations, tumor microenvironment, chemotherapy response, and immunotherapy. Additionally, we identified EGR2 as a key SPRG in bladder cancer. The expression of EGR2 in bladder cancer was detected by immunohistochemistry, and the cell function experiment clarified the effect of knocking down EGR2 on the proliferation, invasion, and migration of bladder cancer cells. Results: Our findings suggest that SPRGS hold promise as prognostic markers and predictive biomarkers for chemotherapy response and immunotherapy efficacy in bladder cancer. The SPRGS prognostic model exhibited high predictive accuracy for bladder cancer patient survival. We also observed correlations between SPRG and genomic alterations, tumor microenvironment, and response to chemotherapy. Immunohistochemical results showed that EGR2 was highly expressed in bladder cancer tissues, and its overexpression was associated with poor prognosis. Knockdown of EGR2 inhibited bladder cancer cell proliferation, invasion, and migration. Conclusion: This study provides valuable insights into the landscape of SPRGS in bladder cancer and their potential implications for personalized treatment strategies. The identification of EGR2 as a key SPRG and its functional impact on bladder cancer cells further highlights its significance in bladder cancer development and progression. Overall, SPRGS may serve as important prognostic markers and predictive biomarkers for bladder cancer patients, guiding treatment decisions and improving patient outcomes.

SFPQ promotes the proliferation, migration and invasion of hepatocellular carcinoma cells and is associated with poor prognosis.

Liver cancer is a prevalent type of tumor worldwide. CRISPR-Cas9 technology can be utilized to identify therapeutic targets for novel therapeutic approaches. In this study, our goal was to identify key genes related to the survival of hepatocellular carcinoma (HCC) cells by analyzing the DepMap database based on CRISPR-Cas9. We screened candidate genes associated with HCC cell survival and proliferation from DepMap and identified their expression levels in HCC from the TCGA database. To develop a prognostic risk model based on these candidate genes, we performed WGCNA, functional pathway enrichment analysis, protein interaction network construction, and LASSO analysis. Our findings show that 692 genes were critical for HCC cell proliferation and survival, and among them, 571 DEGs were identified in HCC tissues. WGCNA categorized these 584 genes into three modules, and the blue module consisting of 135 genes was positively linked to the tumor stage. Using the MCODE approach in Cytoscape, we identified ten hub genes in the PPI network, and through Cox univariate analysis and Lasso analysis, we developed a prognostic model consisting of three genes (SFPQ, SSRP1, and KPNB1). Furthermore, knocking down SFPQ inhibited HCC cell proliferation, migration, and invasion. In conclusion, we identified three core genes (SFPQ, SSRP1, and KPNB1) that are essential for the proliferation and survival of HCC cells. These genes were used to develop a prognostic risk model, and knockdown of SFPQ was found to inhibit the proliferation, migration, and invasion of HCC cells.

Construction of a risk model based on N6 -methyladenosinerelated lncRNAs for predicting the prognosis of breast cancer.

N6-methyladenosine modification and lncRNAs are closely related to the prognosis and immunotherapy response of breast cancer patients. LncRNAs related to m6 A-associated genes were predicted based on coexpression analysis of the TCGA database. We established a novel 7-m6 A-associated lncRNA signature for predicting patient prognosis and validated it. The model was significantly correlated with survival time and survival status and was an independent predictor of overall survival (OS). Except for the M1 disease group, the model had good predictive value for OS in different subgroups. We constructed a prognostic model based on 7 m6 A-associated lncRNAs in breast cancer. This model could serve as an independent prognostic factor with tremendous predictive ability for breast cancer patients.