A roadmap to generate renewable protein binders to the human proteome

Plasma Proteomics to Identify Drug Targets and Potential Drugs for Retinal Artery Occlusion: An Integrated Analysis in the UK Biobank

Retinal artery occlusion (RAO), which is positively correlated with acute ischemic stroke (IS) and results in severe visual impairment, lacks effective intervention drugs. This study aims to perform integrated analysis using UK Biobank plasma proteome data of RAO and IS to identify potential targets and preventive drugs. A total of 7191 participants (22 RAO patients, 1457 IS patients, 8 individuals with both RAO and IS, and 5704 healthy age-gender-matched controls) were included in this study. Unique 1461 protein expression profiles of RAO, IS, and the combined data set, extracted from UK Biobank Plasma proteomics projects, were analyzed using both differential expression analysis and elastic network regression (Enet) methods to identify shared key proteins. Subsequent analyses, including single cell type expression assessment, pathway enrichment, and druggability analysis, were conducted for verifying shared key proteins and discovery of new drugs. Five proteins were found to be shared among the samples, with all of them showing upregulation. Notably, adhesion G-protein coupled receptor G1 (ADGRG1) exhibited high expression in glial cells of the brain and eye tissues. Gene set enrichment analysis revealed pathways associated with lipid metabolism and vascular regulation and inflammation. Druggability analysis unveiled 15 drug candidates targeting ADGRG1, which demonstrated protective effects against RAO, especially troglitazone (-8.5 kcal/mol). Our study identified novel risk proteins and therapeutic drugs associated with the rare disease RAO, providing valuable insights into potential intervention strategies.

Stemness subtypes in lower-grade glioma with prognostic biomarkers, tumor microenvironment, and treatment response

Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Bioreversible Anionic Cloaking Enables Intracellular Protein Delivery with Ionizable Lipid Nanoparticles

Protein-based therapeutics comprise a rapidly growing subset of pharmaceuticals, but enabling their delivery into cells for intracellular applications has been a longstanding challenge. To overcome the delivery barrier, we explored a reversible, bioconjugation-based approach to modify the surface charge of protein cargos with an anionic "cloak" to facilitate electrostatic complexation and delivery with lipid nanoparticle (LNP) formulations. We demonstrate that the conjugation of lysine-reactive sulfonated compounds can allow for the delivery of various protein cargos using FDA-approved LNP formulations of the ionizable cationic lipid DLin-MC3-DMA (MC3). We apply this strategy to functionally deliver RNase A for cancer cell killing as well as a full-length antibody to inhibit oncogenic β-catenin signaling. Further, we show that LNPs encapsulating cloaked fluorescent proteins distribute to major organs in mice following systemic administration. Overall, our results point toward a generalizable platform that can be employed for intracellular delivery of a wide range of protein cargos.

Pan-cancer analysis of the disulfidptosis-related gene RPN1 and its potential biological function and prognostic significance in gliomas

Background

Numerous studies have shown a strong correlation between disulfidptosis and various cancers. However, the expression and function of RPN1, a crucial gene in disulfidptosis, remain unclear in the context of cancer.

Methods

Gene expression and clinical information on lung adenocarcinoma were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. RPN1 expression was analyzed using the Timer2.0 and the Human Protein Atlas (HPA) databases. Prognostic significance was assessed using Cox regression analysis and Kaplan-Meier curves. Genetic mutations and methylation levels were examined using the cBioPortal and UALCAN platforms, respectively. The relationship between RPN1 and tumor mutation burden (TMB) and microsatellite instability (MSI) across different cancer types was analyzed using the Spearman correlation coefficient. The relationship between RPN1 and immune cell infiltration was analyzed using the Timer2.0 database, whereas variations in drug sensitivity were explored using the CellMiner database. Receiver operating characteristic curves validated RPN1's diagnostic potential in glioma, and its correlation with immune checkpoint inhibitors (ICIs) was assessed using Spearman's correlation coefficient. Single-sample gene set enrichment analysis elucidated a link between RPN1 and immune cells and pathways. In addition, a nomogram based on RPN1 was developed to predict patient prognosis. The functional impact of RPN1 on glioma cells was confirmed using scratch and Transwell assays.

Result

RPN1 was aberrantly expressed in various cancers and affected patient prognosis. The main mutation type of RPN1 in the cancer was amplified. RPN1 exhibited a positive correlation with myeloid-derived suppressor cells, neutrophils, and macrophages, and a negative correlation with CD8+ T cells and hematopoietic stem cells. RPN1 expression was associated with TMB and MSI in various cancers. The expression of RPN1 affected drug sensitivity in cancer cells. RPN1 was positively correlated with multiple ICIs in gliomas. RPN1 also affected immune cell infiltration into the tumor microenvironment. RPN1 was an independent prognostic factor for gliomas, and the nomogram demonstrated excellent predictive performance. Interference with RPN1 expression reduces the migratory and invasive ability of glioma cells.

Conclusion

RPN1 exerts multifaceted effects on different stages of cancer, including immune infiltration, prognosis, and treatment outcomes. RPN1 expression affects the prognosis and immune microenvironment infiltration in patients with glioma, making RPN1 a potential target for the treatment of glioma.

Identification of PANoptosis-related genes as prognostic indicators of thyroid cancer

Background

Thyroid cancer (THCA) has become a common malignancy in recent years, with the mortality rate steadily increasing. PANoptosis is a unique kind of programmed cell death (PCD), including pyroptosis, necroptosis, and apoptosis, and is involved in the proliferation and prognosis of numerous cancers. This paper demonstrated the connection between PANoptosis-related genes and THCA based on the analyses of Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, which have not been evaluated yet.

Methods

We identified PANoptosis-related differentially expressed genes (PRDEGs) by multi-analyzing the TCGA-THCA and GEO datasets. To identify the significant PRDEGs, a prognostic model was constructed using least absolute shrinkage and selection operator regression (LASSO). The predictive values of the significant PRDEGs for THCA outcomes were determined using Cox regression analysis and nomograms. Gene enrichment analyses were performed. Finally, immunohistochemistry was carried out using the human protein atlas.

Results

A LASSO regression model based on nine PRDEGs was constructed, and the prognostic value of key PRDEGs was explored via risk score. Univariate and multivariate Cox regression were implemented to identify further three significant PRDEGs closely related to distant metastasis, lymph node metastasis, and tumor stage. Then, a nomogram was constructed, which presented high predictive accuracy for 5 years survival of THCA patients. Gene enrichment analyses in THCA were strongly associated with PCD pathways. CASP6 presented significantly differential expression during clinical T stage, N stage, and PFI events (P < 0.05 for all) and demonstrated the highest degree of diagnostic efficacy in PRDEGs (HR: 2.060, 95 % CI: 1.170-3.628, P < 0.05). Immunohistochemistry showed CASP6 was more abundant in THCA tumor tissue.

Conclusion

A potential prognostic role for PRDEGs in THCA was identified, providing a new direction for treatment. CASP6 may be a potential therapeutic target and a novel prognostic biomarker for THCA.

Identification of disulfidptosis-associated genes and characterization of immune cell infiltration in thyroid carcinoma

OBJECTIVE

The primary objective of this study is to conduct a comprehensive screening and analysis of differentially expressed genes related to disulfidoptosis (DEDRGs) in thyroid carcinoma (THCA). This entails delving into the intricate characterization of immune cell infiltration within the THCA context and subsequently formulating and validating a novel prognostic model.

METHOD

To achieve our objectives, we first delineated two distinct subtypes of disulfidoptosis-related genes (DRGs) via consensus clustering methodology. Subsequently, employing the limma R package, we identified the DEDRGs critical for our investigation. These DEDRGs underwent meticulous validation across various databases, alongside an in-depth analysis of gene regulation. Employing functional enrichment techniques, we explored the potential molecular mechanisms underlying disulfidoptosis in THCA. Furthermore, we scrutinized the immune landscape within the two identified subtypes utilizing CIBERSORT and ESTIMATE algorithms. The construction of the prognostic model for THCA entailed intricate methodologies including univariate, multivariate Cox regression, and LASSO regression algorithms. The validity and efficacy of our prognostic model were corroborated through Kaplan-Meier survival curves and ROC curves. Additionally, a nomogram was meticulously formulated to facilitate the prediction of patient prognosis. To fortify our findings, we conducted a comprehensive Bayesian co-localization analysis coupled with rigorous in vitro experimentation, aimed at unequivocally establishing the validity of the identified DEDRGs.

RESULT

Our analyses unveiled Cluster C1, characterized by elevated expression levels of DEDRGs, as harboring a favorable prognosis accompanied by abundant immune cell infiltration. Correlation analyses underscored predominantly positive associations among the DEDRGs, further affirming their significance in THCA. Differential expression patterns of DEDRGs between tumor samples and normal tissues were evident across the GEPIA and HPA databases. Insights from the TIMER database underscored a robust correlation between DEDRGs and immune cell infiltration. KEGG analysis elucidated the enrichment of DEDRGs primarily in pivotal pathways including MAPK, PPAR signaling pathway, and Proteoglycans in cancer. Furthermore, analyses using CIBERSORT and ESTIMATE algorithms shed light on the crucial role played by DEDRGs in shaping the immune microenvironment. The prognostic model, anchored by five genes intricately associated with THCA prognosis, exhibited commendable predictive accuracy and was intricately linked to the tumor immune microenvironment. Notably, patients categorized with low-risk scores stood to potentially benefit more from immunotherapy. The validation of DEDRGs unequivocally underscores the protective role of INF2 in THCA.

CONCLUSION

In summary, our study delineates two discernible subtypes intricately associated with DRGs, revealing profound disparities in immune infiltration and survival prognosis within the THCA milieu. The implications of our findings extend to potential treatment strategies for THCA patients, which could entail targeted interventions directed towards DEDRGs and prognostic genes, thereby influencing disulfidptosis and the immune microenvironment. Moreover, the robust predictive capability demonstrated by our prognostic model, based on the five genes (ANGPTL7, FIRRE, ODAPH, PROKR1, SFRP5), underscores its potential clinical utility in guiding personalized therapeutic approaches for THCA patients.

Integrating Multiple Database Resources to Elucidate the Gene Flow in Southeast Asian Pig Populations

The domestic pig (Sus scrofa) and its subfamilies have experienced long-term and extensive gene flow, particularly in Southeast Asia. Here, we analyzed 236 pigs, focusing on Yunnan indigenous, European commercial, East Asian, and Southeast Asian breeds, using the Pig Genomics Reference Panel (PGRP v1) of Pig Genotype-Tissue Expression (PigGTEx) to investigate gene flow and associated complex traits by integrating multiple database resources. In this study, we discovered evidence of admixtures from European pigs into the genome of Yunnan indigenous pigs. Additionally, we hypothesized that a potential conceptual gene flow route that may have contributed to the genetic composition of the Diannan small-ear pig is a gene exchange from the Vietnamese pig. Based on the most stringent gene introgression scan using the fd statistic, we identified three specific loci on chromosome 8, ranging from 51.65 to 52.45 Mb, which exhibited strong signatures of selection and harbored the NAF1, NPY1R, and NPY5R genes. These genes are associated with complex traits, such as fat mass, immunity, and litter weight, in pigs, as supported by multiple bio-functionalization databases. We utilized multiple databases to explore the potential dynamics of genetic exchange in Southeast Asian pig populations and elucidated specific gene functionalities.

The cuproptosis-related gene UBE2D2 functions as an immunotherapeutic and prognostic biomarker in pan-cancer

BACKGROUND

Cuproptosis, as a unique modality of regulated cell death, requires the involvement of ubiquitin-binding enzyme UBE2D2. However, the prognostic and immunotherapeutic values of UBE2D2 in pan-cancer remain largely unknown.

METHODS

Using UCSC Xena, TIMER, Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA) databases, we aimed to explore the differential expression pattern of UBE2D2 across multiple cancer types and to evaluate its association with patient prognosis, clinical features, and genetic variations. The association between UBE2D2 and immunotherapy response was assessed by gene set enrichment analysis, tumor microenvironment, immune gene co-expression and drug half maximal inhibitory concentration (IC50) analysis.

RESULTS

The mRNA and protein levels of UBE2D2 were markedly elevated in most cancer types, and UBE2D2 exhibited prognostic significance in liver hepatocellular carcinoma (LIHC), kidney chromophobe (KICH), uveal melanomas (UVM), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and kidney renal papillary cell carcinoma (KIRP). UBE2D2 expression was correlated with clinical features, tumor mutation burden, microsatellite instability, and anti-tumor drug resistance in several tumor types. Gene enrichment analysis showed that UBE2D2 was significantly associated with immune-related pathways. The expression level of UBE2D2 was correlated with immune cell infiltration, including CD4 + T cells、Macrophages M2、CD8 + T cells in pan-cancer. PDCD1, CD274 and CTLA4 expression levels were positively correlated with UBE2D2 level in multiple cancers.

CONCLUSIONS

We comprehensively investigated the potential value of UBE2D2 as a prognostic and immunotherapeutic predictor for pan-cancer, providing a novel insight for cancer immunotherapy.

Pan-Cancer Analysis Identifies BCLAF1 as a Potential Biomarker for Renal Cell Carcinoma

B-cell lymphoma-2-associated transcription factor 1 (BCLAF1) is a versatile protein involved in the regulation of gene transcription and post-transcriptional processing. Although BCLAF1 exerts a broad tumor suppressor effect or tumor promoter effect in many cancer types, the specific roles concerning its expression levels, and its impact on tumorigenesis in Renal cell carcinoma (RCC) remain unclear. Here, we utilized the Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) datasets alongside R software and online tools to unravel the specific roles of BCLAF1 in 33 cancer types, including its expression levels, tumor immune and molecular subtypes, and its correlation with prognosis, diagnosis, DNA methylation, and immune microenvironment. Additionally, we carried out cell biology experiments to independently investigate the expression of BCLAF1 in RCC and its effects on tumor progression. BCLAF1 was differentially expressed in tumor tissues compared to normal tissues across various cancer types and was also differentially expressed in different immune and molecular subtypes. In RCC, patients with high BCLAF1 expression had a better prognosis and BCLAF1 was tightly correlated with the stage, gender, and histological grade of patients. Furthermore, BCLAF1 had higher DNA methylation levels and higher immune infiltration levels in tumor tissues. Additionally, cell functional experiments confirmed the low expression of BCLAF1 in RCC and that BCLAF1 significantly inhibited the proliferation, migration, and invasion, while inducing apoptosis and cell cycle arrest in RCC cells in vitro. Our study under-scored the potential of BCLAF1 as an important actor in tumorigenesis, especially concerning RCC where it may serve as an effective prognostic marker.

Bioinformatics Analysis of the Genetic and Epigenetic Alterations of Bone Morphogenetic Protein Receptors in Metastatic Breast Cancer

The leading cause of mortality in patients with breast cancer is metastasis, and bone morphogenetic protein (BMP) signaling activation regulates metastasis in breast cancer. This study explored the genetic and epigenetic modification of BMP receptor genes associated with metastatic breast cancer cells using bioinformatics. The genetic and epigenetic alterations of BMP receptors (BMPR1A, BMPR1B, BMPR2, ACVR2A, ACVR1, ACVR2B, ACVR1B, HJV, and ENG) were examined using cBioportal and methSurv, respectively. mRNA expression was analyzed using TNM plot and bcgenex, and protein expression was studied using Human Protein Atlas. Prognostic value and ROC were investigated using Kaplan-Meier (KM) and ROC plot, respectively. Finally, mutant function was predicted using several databases, including PolyPhen-2, FATHMM, Mutation Assessor, and PredictSNP. Oncoprint analysis showed genetic alterations in BMPR1A (39%), BMPR1B (13%), BMPR2 (34%), ACVR2A (14%), ACVR1 (7%), ACVR2B (13), ACVR1B (35%), HJV (40%), and ENG (33%) across the patients with breast cancer in The Metastatic Breast Cancer Project. The mRNA and protein levels of BMPR2 were increased in metastatic breast tumor tissues compared with those in normal and breast tumor tissues. BMPR1A and BMPR2 showed the highest and lowest levels of epigenetic alterations among the BMP receptors, respectively. The patients with breast cancer who had low levels of BMPR2 had a better overall survival (OS) than those with high levels of BMPR2. Functional mutation prediction showed that mutants in BMPR2 (R272L, E274K, and L685F), ACVR2A (S127L), and ACVR1B (R484H), are deleterious, probably damaging, and possess a cancer phenotype. ROC plot revealed no BMP receptors correlated with endocrine therapy sensitivity. BMPR1B, BMPR2, and ACVR2A levels were significantly linked as moderate prediction of anti-HER2, BMPR2, and ACVR1B demonstrated moderate predictive potential for chemotherapy sensitivity. This study contributed in fully comprehending the significance of genetic and epigenetic alterations in BMP receptors and BMP signaling in metastatic breast cancer cells for the development of breast cancer treatment plans.

Pan-cancer analysis of DDIT4 identifying its prognostic value and function in acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is a hematological malignancy derived from the accumulation of abnormal proliferation of infantile leukocytes in the hematopoietic system. DNA-damage-inducible transcript 4 (DDIT4) acting as a negative regulator of rapamycin inhibitor is involved in various cellular functions. Many studies have suggested that DDIT4 plays a key role in tumorigenesis. However, the role of DDIT4 in AML has been poorly studied.

METHOD

In this study, we analyzed the expression of DDIT4 in AML patients using The Cancer Genome Atlas and real-time polymerase chain reaction. The Chi-square test was used to assess the correlation between DDIT4 and clinical characters in AML patients. Loss-of-function experiments were implemented to investigate the role of DDIT4 in AML carcinogenesis. The R package was applied to evaluate the correlation between DDIT4 expression and immune cells.

RESULTS

Results showed that the expression of DDIT4 was associated with Age, Cytogenetic risk, Cytogenetics and OS event. Moreover, high expression of DDIT4 led to a terrible prognosis. KEGG analysis showed that differently expressed genes (DEGs) were involved in the PI3-Akt signaling pathway. GSEA enrichment analysis displayed DEGs were correlated with apoptosis. Functional experiments presented that knocking down DDIT4 suppressed cell cycle transition/proliferation and facilitated apoptosis. In addition, DDIT4 is associated with immune infiltration.

CONCLUSION

Our research verified that DDIT4 can be used as a prognostic marker and a potential therapeutic target for AML.

SpyMask enables combinatorial assembly of bispecific binders

Bispecific antibodies are a successful and expanding therapeutic class. Standard approaches to generate bispecifics are complicated by the need for disulfide reduction/oxidation or specialized formats. Here we present SpyMask, a modular approach to bispecifics using SpyTag/SpyCatcher spontaneous amidation. Two SpyTag-fused antigen-binding modules can be precisely conjugated onto DoubleCatcher, a tandem SpyCatcher where the second SpyCatcher is protease-activatable. We engineer a panel of structurally-distinct DoubleCatchers, from which binders project in different directions. We establish a generalized methodology for one-pot assembly and purification of bispecifics in 96-well plates. A panel of binders recognizing different HER2 epitopes were coupled to DoubleCatcher, revealing unexpected combinations with anti-proliferative or pro-proliferative activity on HER2-addicted cancer cells. Bispecific activity depended sensitively on both binder orientation and DoubleCatcher scaffold geometry. These findings support the need for straightforward assembly in different formats. SpyMask provides a scalable tool to discover synergy in bispecific activity, through modulating receptor organization and geometry.

Banxia-Shengjiang drug pair inhibits gastric cancer development and progression by improving body immunity

To investigate the mechanism of action of Banxia-Shengjiang drug pair on the inhibition of gastric cancer (GC) using network pharmacology and bioinformatics techniques. The action targets of the Banxia (Pinellia ternata (Thunb.) Makino) -Shengjiang (Zingiber officinale Roscoe) drug pair obtained from the TCMSP database were intersected with differentially expressed genes (DEGs) and GC-related genes, and the intersected genes were analyzed for pathway enrichment to identify the signaling pathways and core target genes. Subsequently, the core target genes were analyzed for clinical relevance gene mutation analysis, methylation analysis, immune infiltration analysis and immune cell analysis. Finally, by constructing the PPI network of hub genes and corresponding active ingredients, the key active ingredients of the Banxia-Shengjiang drug pair were screened for molecular docking with the hub genes. In this study, a total of 557 target genes of Banxia-Shengjiang pairs, 7754 GC-related genes and 1799 DEGs in GC were screened. Five hub genes were screened, which were PTGS2, MMP9, PPARG, MMP2, and CXCR4. The pathway enrichment analyses showed that the intersecting genes were associated with RAS/MAPK signaling pathway. In addition, the clinical correlation analysis showed that hub genes were differentially expressed in GC and was closely associated with immune infiltration and immunotherapy. The results of single nucleotide variation (SNV) and copy number variation (CNV) indicated that mutations in the hub genes were associated with the survival of gastric cancer patients. Finally, the PPI network and molecular docking results showed that PTGS2 and MMP9 were potentially important targets for the inhibition of GC by Banxia-Shengjiang drug pair, while cavidine was an important active ingredient for the inhibition of GC by Banxia-Shengjiang drug pair. Banxia-Shengjiang drug pair may regulate the immune function and inhibit GC by modulating the expression of core target genes such as RAS/MAPK signaling pathway, PTGS2 and MMP9.

Network pharmacology and experimental verification study on the mechanism of Hedyotis diffusa Willd in treating colorectal cancer

This study aimed to evaluate the pharmacological mechanism of Hedyotis diffusa Willd against CRC (colorectal cancer) using network pharmacological analysis combined with experimental validation. The active components and potential targets of Hedyotis diffusa Willd were screened from the tax compliance management program public database using network pharmacology. The core anti-CRC targets were screened using a protein-protein interaction (PPI) network. The mRNA and protein expression of core target genes in normal colon and CRC tissues and their relationship with overall CRC survival were evaluated using The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Functional and pathway enrichment analyses of the potential targets were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The first six core targets with stable binding were molecular-docked with the active components quercetin and β-sitosterol. Finally, the results of network pharmacology were verified using in vitro experiments. In total, 149 potential targets were identified by searching for seven types of active components and the intersection of all potential and CRC targets. PPI network analysis showed that ten target genes, including tumor protein p53 (TP53) and recombinant cyclin D1 (CCND1), were pivotal genes. GO enrichment analysis involved 2043 biological processes, 52 cellular components, and 191 molecular functions. KEGG enrichment analysis indicated that the anticancer effects of H. alba were mediated by tumor necrosis factor, interleukin-17, and nuclear factor-κB (NF-κB) signaling pathways. Validation of key targets showed that the validation results for most core genes were consistent with those in this study. Molecular docking revealed that the ten core target proteins could be well combined with quercetin and β-sitosterol and the structure remained stable after binding. The results of the in vitro experiment showed that β-sitosterol inhibited proliferation and induced apoptosis in SW620 cells. This study identified a potential target plant for CRC through network pharmacology and in vitro validation.

Mycobacterium tuberculosis infection associated immune perturbations correlate with antiretroviral immunity

Infection with Mycobacterium tuberculosis (MTB) remains one of the most important opportunistic infections in people with HIV-1 (PWH). While active Tuberculosis (TB) leads to rapid progression of immunodeficiency in PWH, the interaction between MTB and HIV-1 during the asymptomatic phase of both infections remains poorly understood. In a cohort of individuals with HIV (PWH) with and without suppressed HIV-1 viral load, the transcriptomic profiles of peripheral blood mononuclear cells (PBMC) clustered in individuals infected with Mycobacterium tuberculosis (MTB) compared to carefully matched controls. Subsequent functional annotation analysis disclosed alterations in the IL-6, TNF, and KRAS pathways. Notably, MTB-associated genes demonstrated an inverse correlation with HIV-1 viremia, evident at both on individual gene level and when employed as a gene score. In sum, our data show that MTB infection in PWH is associated with a shift in the activation state of the immune system, displaying an inverse relationship with HIV-1 viral load. These results could provide an explanation for the observed increased antiretroviral control associated with MTB infection in PWH.

Hsa_circ_0086414/transducer of ERBB2 (TOB2) axis-driven lipid elimination and tumor suppression in clear cell renal cell cancer via perilipin 3

BACKGROUND

Renal cell cancer (RCC) is characterized by abnormal lipid accumulation. However, the specific mechanism by which such lipid deposition is eliminated remains unclear. Circular RNAs (circRNAs) widely regulate various biological processes, but the effect of circRNAs on lipid metabolism in cancers, especially clear cell renal cell carcinoma (ccRCC), remains poorly understood.

METHODS

The downregulated circRNA, hsa_circ_0086414, was identified from high-throughput RNA-sequencing data of human ccRCC and pair-matched normal tissues. The target relationship between circRNA_0086414 and miR-661, and the transducer of ERBB2 (TOB2) was predicted using publicly available software programs and verified by luciferase reporter assays. The clinical prognostic value of TOB2 was evaluated by bioinformatic analysis. The expression levels of circRNA_0086414, miR-661, TOB2, and perilipin 3 (PLIN3) were measured by quantitative reverse-transcription polymerase chain reaction or western blot analysis. Cell Counting Kit-8, transwell assays, and xenograft models were employed to assess the biological behaviors of the hsa_circ_0086414/TOB2 axis. Oil Red staining and triglyceride assay was conducted to assess lipid deposition.

RESULTS

Herein, we identified a downregulated circRNA, hsa_circ_0086414. Functionally, the restored hsa_circ_0086414 inhibited ccRCC proliferation, metastasis, and lipid accumulation in vitro and in vivo. Furthermore, the downregulated TOB2 predicted adverse prognosis and promoted cancer progression and lipid deposition in ccRCC. Mechanically, the binding of hsa_circ_0086414 to miR-661, as a miRNA sponge, upregulates the expression of TOB2, wielding an anti-oncogene effect. Importantly, the restored hsa_circ_0086414/TOB2 axis significantly contributed to the elimination of lipid deposition by inhibiting the lipid metabolism regulator PLIN3 in ccRCC cells.

CONCLUSIONS

Our data highlight the importance of the hsa_circ_0086414/TOB2/PLIN3 axis as a tumor suppressor and lipid eliminator in ccRCC. The positive modulation of the hsa_circ_0086414/TOB2 axis might lead to the development of novel treatment strategies for ccRCC.

DLGAP5 promotes lung adenocarcinoma growth via upregulating PLK1 and serves as a therapeutic target

BACKGROUND

Human discs large-associated protein 5 (DLGAP5) is reported to play a pivotal role in regulating the cell cycle and implicate in tumorigenesis and progression of various cancers. Our current research endeavored to explore the prognostic value, immune implication, biological function and targeting strategy of DLGAP5 in LUAD through approaches including bioinformatics, network pharmacology analysis and experimental study.

METHODS

Multiple databases, including TCGA, GEO, CPTAC and Human Protein Atlas, were utilized to explore the expression and clinical significance of DLGAP5 in LUAD. The genetic alterations of DLGAP5 were assessed through cBioPortal and COSMIC databases. The relationship between DLGAP5 expression and genetic abnormalities of driver genes in LUAD was analyzed through TIMER2.0 database. CancerSEA database was utilized to explore the function of DLGAP5 in 14 different states in LUAD at single-cell resolution. GDSC database was utilized to analyze the impact of DLGAP5 on IC50 of frequently-used anti-LUAD drugs. CIBERSORT method and TIMER2.0 database was utilized to explore the relationship between DLGAP5 and tumor immune infiltration. Network pharmacology was applied to screen potential DLGAP5 inhibitor. In vitro and in vivo experiments were utilized to evaluate biological function and downstream targets of DLGAP5, and the effect of screened DLGAP5 inhibitor on LUAD growth.

RESULTS

High DLGAP5 expression was commonly observed in LUAD and associated with mutation of major driver genes, poor prognosis, high IC50 values of frequently-used anti-LUAD drugs, increasing immune infiltration and elevated immune checkpoint blockade-related genes in LUAD. PLK1 was revealed as a potential DLGAP5 downstream target in LUAD. DLGAP5 overexpression or knockdown significantly promoted or inhibited LUAD cell proliferation and PLK1 expression. PLK1 overexpression well rescued DLGAP5 knockdown-induced cell proliferation inhibition, or vice versa. Furthermore, by virtual screening of an investigational drug library from the DrugBank database, AT9283 was screened and identified as a novel DLGAP5 inhibitor. AT9283 effectively suppressed growth of LUAD cells both in vitro and in vivo. DLGAP5 overexpression significantly reversed AT9283-induced proliferation inhibition. Moreover, AT9283 significantly suppressed DLGAP5 and PLK1 expression, while DLGAP5 overexpression significantly reversed AT9283-induced PLK1 suppression.

CONCLUSION

Our research has demonstrated that DLGAP5 is upregulated in LUAD and exhibits a strong correlation with unfavorable prognosis. Furthermore, DLGAP5 assumes a significant function in the regulation of tumor immunity and treatment outcome of immune checkpoint inhibitors. Of note, we found that DLGAP5 promotes cell proliferation of LUAD via upregulating PLK1. Targeting DLGAP5 by AT9283, our newly identified DLGAP5 inhibitor, suppresses LUAD growth. DLGAP5 may become a promising prognostic biomarker and therapeutic target for patients with LUAD.

Mechanism exploration and biomarker identification of glycemic deterioration in patients with diseases of the exocrine pancreas

The damage to the endocrine pancreas among patients with diseases of the exocrine pancreas (DP) leads to reduced glycemic deterioration, ultimately resulting in diabetes of the exocrine pancreas (DEP). The present research aims to investigate the mechanism responsible for glycemic deterioration in DP patients, and to identify useful biomarkers, with the ultimate goal of enhancing clinical practice awareness. Gene expression profiles of patients with DP in this study were acquired from the Gene Expression Omnibus database. The original study defines DP patients to belong in one of three categories: non-diabetic (ND), impaired glucose tolerance (IGT) and DEP, which correspond to normoglycemia, early and late glycemic deterioration, respectively. After ensuring quality control, the discovery cohort included 8 ND, 20 IGT, and 12 DEP, while the validation cohort included 27 ND, 15 IGT, and 20 DEP. Gene set enrichment analysis (GSEA) employed differentially expressed genes (DEGs), while immunocyte infiltration was determined using single sample gene set enrichment analysis (ssGSEA). Additionally, correlation analysis was conducted to establish the link between clinical characteristics and immunocyte infiltration. The least absolute shrinkage and selection operator regression and random forest combined to identify biomarkers indicating glycemic deterioration in DP patients. These biomarkers were further validated through independent cohorts and animal experiments. With glycemic deterioration, biological processes in the pancreatic islets such as nutrient metabolism and complex immune responses are disrupted in DP patients. The expression of ACOT4, B2M, and ACKR2 was upregulated, whereas the expression of CACNA1F was downregulated. Immunocyte infiltration in the islet microenvironment showed a significant positive correlation with the age, body mass index (BMI), HbA1c and glycemia at the 2-h of patients. It was a crucial factor in glycemic deterioration. Additionally, B2M demonstrated a significant positive correlation with immunocyte infiltration and clinical features. Quantitative real-time PCR (qRT-PCR) and western blotting confirmed the upregulation in B2M. Immunofluorescent staining suggested the alteration of B2M was mainly in the alpha cells and beta cells. Overall, the study showed that gradually increased immunocyte infiltration was a significant contributor to glycemic deterioration in patients with DP, and it also highlighted B2M as a biomarker.

MAD2L2, a key regulator in ovarian cancer and promoting tumor progression

Ovarian cancer (OVCA), a prevalent gynecological malignancy, ranks as the fourth most common cancer among women. Mitotic Arrest Deficient 2 Like 2 (MAD2L2), a chromatin-binding protein and a component of DNA polymerase ζ, has been previously identified as an inhibitor of tumor growth in colorectal cancer. However, the roles of MAD2L2 in OVCA, including its expression, impact, and prognostic significance, remain unclear. We employed bioinformatics tools, Cox Regression analysis, and in vitro cell experiments to investigate its biological functions. Our findings reveal that MAD2L2 typically undergoes genomic alterations, such as amplifications and deep deletions. Moreover, we observed an overexpression of MAD2L2 mRNA in OVCA patients, correlating with reduced survival rates, particularly in those with Grade IV tumors. Furthermore, analysis of mRNA biofunctions indicated that MAD2L2 is predominantly localized in the organellar ribosome, engaging mainly in NADH dehydrogenase activity. This was deduced from the results of gene ontology enrichment analysis, which also identified its role as a structural constituent in mitochondrial translation elongation. These findings were corroborated by KEGG pathway analysis, further revealing MAD2L2's involvement in tumor metabolism and the cell death process. Notably, MAD2L2 protein expression showed significant associations with various immune cells, including CD4+T cells, CD8+T cells, B cells, natural killer cells, and Myeloid dendritic cells. Additionally, elevated levels of MAD2L2 were found to enhance cell proliferation and migration in OVCA cells. The upregulation of MAD2L2 also appears to inhibit the ferroptosis process, coinciding with increased mTOR signaling activity in these cells. Our study identifies MAD2L2 as a novel regulator in ovarian tumor progression and offers new insights for treating OVCA.

Can antibodies be "vegan"? A guide through the maze of today's antibody generation methods

There is no doubt that today's life sciences would look very different without the availability of millions of research antibody products. Nevertheless, the use of antibody reagents that are poorly characterized has led to the publication of false or misleading results. The use of laboratory animals to produce research antibodies has also been criticized. Surprisingly, both problems can be addressed with the same technology. This review charts today's maze of different antibody formats and the various methods for antibody production and their interconnections, ultimately concluding that sequence-defined recombinant antibodies offer a clear path to both improved quality of experimental data and reduced use of animals.

Intratumor APOL3 delineates a distinctive immunogenic ferroptosis subset with prognosis prediction in colorectal cancer

With the essential role of lipid transporting signaling in cancer-related immunity, apolipoprotein L3 (APOL3), a member of the apolipoprotein L gene family, demonstrated significant modulation ability in immunity. However, the expression profile and critical role of APOL3 in colorectal cancer (CRC) remain unclear. This study aimed to investigate the prognostic significance of APOL3 expression and its biological predictive value in CRC. The study enrolled multiple cohorts, consisting of 911 tumor microarray specimens of CRC patients from Zhongshan Hospital, 412 transcriptional data from The Cancer Genome Atlas, and 30 single-cell RNA sequencing (scRNA-seq) from internal and external CRC patients. APOL3 mRNA expression was directly acquired from public datasets, and APOL3 protein expression was detected using immunohistochemistry. Finally, the associations of APOL3 expression with clinical outcomes, immune context, and genomic and ferroptotic features were analyzed. Low APOL3 expression predicted poor prognosis and inferior responsiveness to 5-fluorouracil-based adjuvant chemotherapy (ACT) and targeted therapy. APOL3 fosters an immune-active microenvironment characterized by the promotion of ferroptosis, downregulation of macrophages, and upregulation of CD8+ T cell infiltration. Moreover, the expression of APOL3 in CD8+ T cells is intrinsically linked to ferroptosis and immune activation in CRC. In summary, APOL3 serves as an independent prognosticator and predictive biomarker for immunogenic ferroptosis, ACT, and targeted therapy in CRC. Furthermore, the APOL3 signaling activator could be a novel agent alone or in combination with current therapeutic strategies for CRC.

FTY720 requires vitamin B12-TCN2-CD320 signaling in astrocytes to reduce disease in an animal model of multiple sclerosis

Vitamin B12 (B12) deficiency causes neurological manifestations resembling multiple sclerosis (MS); however, a molecular explanation for the similarity is unknown. FTY720 (fingolimod) is a sphingosine 1-phosphate (S1P) receptor modulator and sphingosine analog approved for MS therapy that can functionally antagonize S1P1. Here, we report that FTY720 suppresses neuroinflammation by functionally and physically regulating the B12 pathways. Genetic and pharmacological S1P1 inhibition upregulates a transcobalamin 2 (TCN2)-B12 receptor, CD320, in immediate-early astrocytes (ieAstrocytes; a c-Fos-activated astrocyte subset that tracks with experimental autoimmune encephalomyelitis [EAE] severity). CD320 is also reduced in MS plaques. Deficiency of CD320 or dietary B12 restriction worsens EAE and eliminates FTY720's efficacy while concomitantly downregulating type I interferon signaling. TCN2 functions as a chaperone for FTY720 and sphingosine, whose complex induces astrocytic CD320 internalization, suggesting a delivery mechanism of FTY720/sphingosine via the TCN2-CD320 pathway. Taken together, the B12-TCN2-CD320 pathway is essential for the mechanism of action of FTY720.

Comprehensive analysis of the potential biological significance of cuproptosis-related gene LIPT2 in pan-cancer prognosis and immunotherapy

Lipoyltransferase 2 (LIPT2) acts as a key enzyme involved in fatty acid metabolism and cell membrane synthesis. However, the biological function of LIPT2 in various cancer types and its potential significance in prognosis continue to be unresolved. For this analysis, we evaluated the expression levels and the significance of prognosis of LIPT2 gene in all cancers by various bioinformatics methods. The results found that LIPT2 was dramatically overexpressed in the vast majority of cancers. The upregulated LIPT2 was related to bad prognosis in Brain Lower Grade Glioma (LGG), Glioma (GBMLGG), Glioblastoma multiforme (GBM), Kidney Chromophobe (KICH), and High-Risk Wilms Tumor (WT), while it had a favorable prognosis in Kidney renal clear cell carcinoma (KIRC), and Ovarian serous cystadenocarcinoma (OV), Pan-kidney cohort (KIPAN). Furthermore, we assessed the mutation status, methylation levels, and immune status of LIPT2 in pan-cancer. Single-cell sequencing results revealed the correlation of LIPT2 expression with various biological characteristics such as DNA lesion, tumor angiogenesis, cell apoptosis, metastasis, and invasion. Enrichment analysis unveiled potential molecular regulatory mechanisms. In conclusion, our research reveals a detailed key role of LIPT2 in the progression, prognosis, and immune efficacy of various forms of cancer. Therefore, we have reason to believe that LIPT2 has the potential to be a candidate biomarker for tumors.

Multidimensional analysis to elucidate the possible mechanism of bone metastasis in breast cancer

BACKGROUND

Breast cancer (BC) patients tend to suffer from distant metastasis, especially bone metastasis.

METHODS

All the analysis based on open-accessed data was performed in R software, dependent on multiple algorithms and packages. The RNA levels of specific genes were detected using quantitative Real-time PCR as a method of detecting the RNA levels. To assess the ability of BC cells to proliferate, we utilized the CCK8 test, colony formation, and the 5-Ethynyl-20-deoxyuridine assay. BC cells were evaluated for invasion and migration by using Transwell assays and wound healing assays.

RESULTS

In our study, we identified the molecules involved in BC bone metastasis based on the data from multiple BC cohorts. Then, we comprehensively investigated the effect pattern and underlying biological role of these molecules. We found that in the identified molecules, the EMP1, ACKR3, ITGA10, MMP13, COL11A1, and THY1 were significantly correlated with patient prognosis and mainly expressed in CAFs. Therefore, we explored the CAFs in the BC microenvironment. Results showed that CAFs could activate multiple carcinogenic pathways and most of these pathways play an important role in cancer metastasis. Meanwhile, we noticed the interaction between CAFs and malignant, endothelial, and M2 macrophage cells. Moreover, we found that CAFs could induce the remodeling of the BC microenvironment and promote the malignant behavior of BC cells. Then, we identified MMP13 for further analysis. It was found that MMP13 can enhance the malignant phenotype of BC cells. Meanwhile, biological enrichment and immune infiltration analysis were conducted to present the effect pattern of MMP13 in BC.

CONCLUSIONS

Our result can improve the understanding of researchers on the underlying mechanisms of BC bone metastasis.

Construction and Validation of a Prognostic Model Based on Novel Senescence-Related Genes in Non-Small Cell Lung Cancer Patients with Drug Sensitivity and Tumor Microenvironment

Cellular senescence contributes to cancer pathogenesis and immune regulation. Using the LASSO Cox regression, we developed a 12-gene prognostic signature for lung adenocarcinoma (LUAD) from The Cancer Genome Atlas (TCGA) and a Gene Expression Omnibus (GEO) dataset. We assessed gene expression, drug sensitivity, immune infiltration, and conducted cell line experiments. High-risk LUAD patients showed increased mortality risk and shorter survival (P < 0.001). Senescence-related gene analysis indicated differences in protein phosphorylation and DNA methylation between normal individuals and LUAD patients. The high-risk group showed a positive association with PD-L1 expression (P = 0.003). Single-cell sequencing data suggested PEBP1 might significantly impact T cell infiltration. We predicted potential sensitive compounds for 12 senescence genes and found GAPDH promoted cell line proliferation. We established a novel prognostic system based on a newly identified senescence gene. High-risk patients had elevated immunosuppressive markers, and PEBP1 might influence T cell infiltration significantly. GAPDH, expressed at higher levels in tumors, could affect cancer progression. Our drug prediction model may guide treatment selection.

Prognostic clinical phenotypes associated with tumor stemness in the immune microenvironment of T-cell exhaustion for hepatocellular carcinoma

T-cell exhaustion (TEX) and high heterogeneity of cancer stem cells (CSCs) are associated with progression, metastasis, and treatment resistance in hepatocellular carcinoma (HCC). Here, we aim to characterize TEX-stemness-related genes (TEXSRGs) and screen for HCC patients who are more sensitive to immunotherapy. The immune cell abundance identifier (ImmuCellAI) was utilized to precisely evaluate the abundance of TEX and screen TEX-related genes. The stemness index (mRNAsi) of samples was analyzed through the one-class logistic regression (OCLR) algorithm. Application of the non-negative matrix decomposition algorithm (NMF) for subtype identification of HCC samples. The different subtypes were assessed for differences in prognosis, tumor microenvironment (TME) landscape, and immunotherapy treatment response. Then, the TEXSRGS-score, which can accurately forecast the survival outcome of HCC patients, was built by LASSO-Cox and multivariate Cox regression, and experimentally validated for the most important TEXSRGs. We also analyzed the expression of TEXSRGs and the infiltration of CD8+ T cells in clinical samples using qRT-PCR and immunohistochemistry (IHC). Based on 146 TEXSRGs, we found two distinct clinical phenotypes with different TEX infiltration abundance, tumor stemness index, enrichment pathways, mutational landscape, and immune cell infiltration through the non-negative matrix decomposition algorithm (NMF), which were confirmed in the ICGC dataset. Utilizing eight TEXSRGs linked to clinical outcome, we created a TEXSRGs-score model to further improve the clinical applicability. Patients can be divided into two groups with substantial differences in the characteristics of immune cell infiltration, TEX infiltration abundance, and survival outcomes. The results of qRT-PCR and IHC analysis showed that PAFAH1B3, ZIC2, and ESR1 were differentially expressed in HCC and normal tissues and that patients with high TEXSRGs-scores had higher TEX infiltration abundance and tumor stemness gene expression. Regarding immunotherapy reaction and immune cell infiltration, patients with various TEXSRGs-score levels had various clinical traits. The outcome and immunotherapy efficacy of patients with low TEXSRGs-score was favorable. In conclusion, we identified two clinical subtypes with different prognoses, TEX infiltration abundance, tumor cell stemness index, and immunotherapy response based on TEXSRGs, and developed and validated a TEXSRGs-score capable of accurately predicting survival outcomes in HCC patients by comprehensive bioinformatics analysis. We believe that the TEXSRGs-score has prospective clinical relevance for prognostic assessment and may help physicians select prospective responders in preference to current immune checkpoint inhibitors (ICIs).

Pan-cancer analysis revealing that PTPN2 is an indicator of risk stratification for acute myeloid leukemia

The non-receptor protein tyrosine phosphatases gene family (PTPNs) is involved in the tumorigenesis and development of many cancers, but the role of PTPNs in acute myeloid leukemia (AML) remains unclear. After a comprehensive evaluation on the expression patterns and immunological effects of PTPNs using a pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas, the most valuable gene PTPN2 was discovered. Further investigation of the expression patterns of PTPN2 in different tissues and cells showed a robust correlation with AML. PTPN2 was then systematically correlated with immunological signatures in the AML tumor microenvironment and its differential expression was verified using clinical samples. In addition, a prediction model, being validated and compared with other models, was developed in our research. The systematic analysis of PTPN family reveals that the effect of PTPNs on cancer may be correlated to mediating cell cycle-related pathways. It was then found that PTPN2 was highly expressed in hematologic diseases and bone marrow tissues, and its differential expression in AML patients and normal humans was verified by clinical samples. Based on its correlation with immune infiltrates, immunomodulators, and immune checkpoint, PTPN2 was found to be a reliable biomarker in the immunotherapy cohort and a prognostic predictor of AML. And PTPN2'riskscore can accurately predict the prognosis and response of cancer immunotherapy. These findings revealed the correlation between PTPNs and immunophenotype, which may be related to cell cycle. PTPN2 was differentially expressed between clinical AML patients and normal people. It is a diagnostic biomarker and potentially therapeutic target, providing targeted guidance for clinical treatment.

The comprehensive analysis of the prognostic and functional role of N-terminal methyltransferases 1 in pan-cancer

Background

NTMT1, a transfer methylase that adds methyl groups to the N-terminus of proteins, has been identified as a critical player in tumor development and progression. However, its precise function in pan-cancer is still unclear. To gain a more comprehensive understanding of its role in cancer, we performed a thorough bioinformatics analysis.

Methods

To conduct our analysis, we gathered data from multiple sources, including RNA sequencing and clinical data from the TCGA database, protein expression data from the UALCAN and HPA databases, and single-cell expression data from the CancerSEA database. Additionally, we utilized TISIDB to investigate the interaction between the tumor and the immune system. To assess the impact of NTMT1 on the proliferation of SNU1076 cells, we performed a CCK8 assay. We also employed cellular immunofluorescence to detect DNA damage and used flow cytometry to measure tumor cell apoptosis.

Results

Our analysis revealed that NTMT1 was significantly overexpressed in various types of tumors and that high levels of NTMT1 were associated with poor survival outcomes. Functional enrichment analysis indicated that NTMT1 may contribute to tumor development and progression by regulating pathways involved in cell proliferation and immune response. In addition, we found that knockdown of NTMT1 expression led to reduced cell proliferation, increased DNA damage, and enhanced apoptosis in HNSCC cells.

Conclusion

High expression of NTMT1 in tumors is associated with poor prognosis. The underlying regulatory mechanism of NTMT1 in cancer is complex, and it may be involved in both the promotion of tumor development and the inhibition of the tumor immune microenvironment.

Systematic analysis of glutamine metabolism family genes and exploration of the biological role of GPT in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a malignancy of the digestive system with high incidence rate and mortality, and reliable diagnostic and prognostic markers for CRC are still lacking. Glutamine metabolism is crucial to the occurrence and development of CRC. However, no research has systematically analyzed the biological role of glutamine metabolism-related genes (GMRGs) in CRC.

METHODS

We downloaded gene expression data and clinical data of CRC patients from the TCGA database. The UCSC database downloads pan-cancer gene expression data and prognosis data. Characteristic GMRGs were screened out using differential analysis and two types of machine learning (SVM-REF and RandomForest). Single-cell RNA-sequencing data from CRC patients were downloaded from GEO data. ROC curve was used to evaluate the diagnostic value. Kaplan-Meier method and univariate Cox regression analysis were used to evaluate the prognostic value. The oncopredict package is used to calculate IC50 values for common drugs in CRC patients.

RESULTS

A total of 31 differentially expressed GMRGs were identified, 9 of which were identified as characteristic GMRGs. Further evaluation of diagnostic and prognostic value finally identified GPT as the most important GMRGs in CRC. scRNA-seq analysis revealed that GPT is almost exclusively expressed in epithelial cells. GPT expression is closely related to the tumor microenvironment and can effectively distinguish the sensitivity of different CRC patients to clinical drugs. In addition, pan-cancer analysis showed that GPT is an excellent diagnostic and prognostic marker for multiple cancers.

CONCLUSIONS

GPT is a reliable diagnostic, prognostic marker and therapeutic target in CRC.

Circulating miRNAs as Noninvasive Biomarkers for PDAC Diagnosis and Prognosis in Mexico

Among malignant neoplasms, pancreatic ductal adenocarcinoma (PDAC) has one of the highest fatality rates due to its late detection. Therefore, it is essential to discover a noninvasive, early, specific, and sensitive diagnostic method. MicroRNAs (miRNAs) are attractive biomarkers because they are accessible, highly specific, and sensitive. It is crucial to find miRNAs that could be used as possible biomarkers because PDAC is the eighth most common cause of cancer death in Mexico. With the help of microRNA microarrays, differentially expressed miRNAs (DEmiRNAs) were found in PDAC tissues. The presence of these DEmiRNAs in the plasma of Mexican patients with PDAC was determined using RT-qPCR. Receiver operating characteristic curve analysis was performed to determine the diagnostic capacity of these DEmiRNAs. Gene Expression Omnibus datasets (GEO) were employed to verify our results. The Prisma V8 statistical analysis program was used. Four DEmiRNAs in plasma from PDAC patients and microarray tissues were found. Serum samples from patients with PDAC were used to validate their overexpression in GEO databases. We discovered a new panel of the two miRNAs miR-222-3p and miR-221-3p that could be used to diagnose PDAC, and when miR-221-3p and miR-222-3p were overexpressed, survival rates decreased. Therefore, miR-222-3p and miR-221-3p might be employed as noninvasive indicators for the diagnosis and survival of PDAC in Mexican patients.

The Role of NCS1 in Immunotherapy and Prognosis of Human Cancer

The Neural Calcium Sensor1 (NCS1) is a crucial protein that binds to Ca2+ and is believed to play a role in regulating tumor invasion and cell proliferation. However, the role of NCS1 in immune infiltration and cancer prognosis is still unknown. Our study aimed to explore the expression profile, immune infiltration pattern, prognostic value, biological function, and potential compounds targeting NCS1 using public databases. High expression of NCS1 was detected by immune histochemical staining in LIHC (Liver hepatocellular carcinoma), BRCA (Breast invasive carcinoma), KIRC (Kidney renal clear cell carcinoma), and SKCM (Skin Cutaneous Melanoma). The expression of NCS1 in cancer was determined by TCGA (The Cancer Genome Atlas Program), GTEx (The Genotype-Tissue Expression), the Kaplan-Meier plotter, GEO (Gene Expression Omnibus), GEPIA2.0 (Gene Expression Profiling Interactive Analysis 2.0), HPA (The Human Protein Atlas), UALCAN, TIMER2.0, TISIDB, Metascape, Drugbank, chEMBL, and ICSDB databases. NCS1 has genomic mutations as well as aberrant DNA methylation in multiple cancers compared to normal tissues. Also, NCS1 was significantly different in the immune microenvironment, tumor mutational burden (TMB), microsatellite instability (MSI), and immune infiltrate-associated cells in different cancers, which could be used for the typing of immune and molecular subtypes of cancer and the presence of immune checkpoint resistance in several cancers. Univariate regression analysis, multivariate regression analysis, and gene enrichment analysis to construct prognostic models revealed that NCS1 is involved in immune regulation and can be used as a prognostic biomarker for SKCM, LIHC, BRCA, COAD, and KIRC. These results provide clues from a bioinformatic perspective and highlight the importance of NCS1 in a variety of cancers.

Prognostic analyses of genes associated with anoikis in breast cancer

Breast cancer (BRCA) is the most diagnosed cancer worldwide and is responsible for the highest cancer-associated mortality among women. It is evident that anoikis resistance contributes to tumour cell metastasis, and this is the primary cause of treatment failure for BRCA. However, anoikis-related gene (ARG) expression profiles and their prognostic value in BRCA remain unclear. In this study, a prognostic model of ARGs based on The Cancer Genome Atlas (TCGA) database was established using a least absolute shrinkage and selection operator analysis to evaluate the prognostic value of ARGs in BRCA. The risk factor graph demonstrated that the low-risk group had longer survival than the high-risk group, implying that the prognostic model had a good performance. We identified 11 ARGs that exhibited differential expression between the two risk groups in TCGA and Gene Expression Omnibus databases. Through Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analyses, we revealed that the screened ARGs were associated with tumour progression and metastasis. In addition, a protein-protein interaction network showed potential interactions among these ARGs. Furthermore, gene set enrichment analysis suggested that the Notch and Wnt signalling pathways were overexpressed in the high-risk group, and gene set variation analysis revealed that 38 hallmark genes differed between the two groups. Moreover, Kaplan-Meier survival curves and receiver operating characteristic curves were used to identify five ARGs (CD24, KRT15, MIA, NDRG1, TP63), and quantitative polymerase chain reaction was employed to assess the differential expression of these ARGs. Univariate and multivariate Cox regression analyses were then performed for the key ARGs, with the best prediction of 3 year survival. In conclusion, ARGs might play a crucial role in tumour progression and serve as indicators of prognosis in BRCA.

Development of a thyroid cancer prognostic model based on the mitophagy-associated differentially expressed genes

BACKGROUND

The prevalence of thyroid cancer (ThyC), a frequent malignant tumor of the endocrine system, has been rapidly increasing over time. The mitophagy pathway is reported to play a critical role in ThyC onset and progression in many studies. This research aims to create a mitophagy-related survival prediction model for ThyC patients.

METHODS

Genes connected to mitophagy were found in the GeneCards database. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases provided information on the expression patterns of ThyC-related genes. To identify differentially expressed genes (DEGs), R software was employed. The prognostic significance of each DEG was assessed using the prognostic K-M curve. The prognostic model was built using LASSO, ROC, univariate, and multivariate Cox regression analyses. Finally, a nomogram model was developed to predict the survival outcome of ThyC patients in the clinical setting.

RESULTS

Through differential analysis, functional enrichment analysis, and protein-protein interaction (PPI) network analysis, we screened 10 key genes related to mitophagy in ThyC. The risk model was eventually developed using LASSO and Cox regression analyses based on the six DEGs related to mitophagy. An altered expression level of a mitophagy-related prognostic gene, GGCT, was found to be the most significant one, according to the KM survival curve analysis. An immunohistochemical (IHC) investigation revealed that ThyC tissues expressed higher levels of GGCT than normal thyroid tissues. The ROC curve verified the satisfactory performance of the model in survival prediction. Multivariate Cox regression analysis showed that the pathological grade, residual tumor volume, and initial tumor lesion type were significantly linked to the prognosis. Finally, we created a nomogram to predict the overall survival rate of ThyC patients at 3-, 5-, and 7- year time points.

CONCLUSION

The nomogram risk prediction model was developed to precisely predict the survival rate of ThyC patients. The model was validated based on the most significant DEG GGCT gene expression in ThyC. This model may serve as a guide for the creation of precise treatment plans for ThyC patients.

Prognostic value and potential molecular mechanism of ITGB superfamily members in hepatocellular carcinoma

We analyzed the prognostic value and potential molecular mechanisms of the members of integrin β (ITGB)superfamily in hepatocellular carcinoma (HCC) using data from The Cancer Genome Atlas (TCGA), cBioPortal, Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) HPA, Search Tool for the Retrieval of Interacting Genes/Proteins, GeneMANIA, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), TIMER and Gene set enrichment analysis (GSEA) databases. ITGB4/5 mRNA was upregulated in HCC tissues in contrast to the normal liver tissues, whereas ITGB2/3/8 levels were lower in the former. ITGB4 was the most frequently mutated ITGB gene in HCC. Receiver operating characteristic curve (ROC) analysis showed that the expression levels of ITGB2/3/4/5/7/8 had significant diagnostic value in distinguishing HCC tissues from healthy liver tissues, ITGB8 had the highest diagnostic efficacy. The ITGB1/3/6/8 were also upregulated in the HCC tissues in contrast to healthy liver tissues. The expression of ITGB8 was verified by immunohistochemistry (IHC). Furthermore, ITGB6 and ITGB7 expression levels were strongly associated with the overall survival (OS) of HCC patients. The ITGB superfamily members exhibited homology and interactions in protein structure. In addition, ITGB6 together with ITGB7 were negatively related to the infiltration of multiple immune cell populations. GSEA results showed that ITGB6 was enriched in HCC migration and recurrence, whereas ITGB7 was significantly enriched in HIPPO, TOLL and JAK-STAT signaling pathways. In conclusion, ITGB6 and ITGB7 genes are possible to be prognostic biomarkers for HCC.

Systematic establishment and verification of an epithelial-mesenchymal transition gene signature for predicting prognosis of oral squamous cell carcinoma

Objective: Epithelial-mesenchymal transition (EMT) is linked to an unfavorable prognosis in oral squamous cell carcinoma (OSCC). Here, we aimed to develop an EMT gene signature for OSCC prognosis. Methods: In TCGA dataset, prognosis-related EMT genes with p < 0.05 were screened in OSCC. An EMT gene signature was then conducted with LASSO method. The efficacy of this signature in predicting prognosis was externally verified in the GSE41613 dataset. Correlations between this signature and stromal/immune scores and immune cell infiltration were assessed by ESTIMATE and CIBERSORT algorithms. GSEA was applied for exploring significant signaling pathways activated in high- and low-risk phenotypes. Expression of each gene was validated in 40 paired OSCC and normal tissues via RT-qPCR. Results: A prognostic 9-EMT gene signature was constructed in OSCC. High risk score predicted poorer clinical outcomes than low risk score. ROCs confirmed the well performance on predicting 1-, 3- and 5-year survival. Multivariate cox analysis revealed that this signature was independently predictive of OSCC prognosis. The well predictive efficacy was validated in the GSE41613 dataset. Furthermore, this signature was distinctly related to stromal/immune scores and immune cell infiltration in OSCC. Distinct pathways were activated in two subgroups. After validation, AREG, COL5A3, DKK1, GAS1, GPX7 and PLOD2 were distinctly upregulated and SFRP1 was downregulated in OSCC than normal tissues. Conclusion: Our data identified and verified a robust EMT gene signature in OSCC, which provided a novel clinical tool for predicting prognosis and several targets against OSCC therapy.

Integrative analysis illustrates the role of PCDH7 in lung cancer development, cisplatin resistance, and immunotherapy resistance: an underlying target

Background: Cisplatin resistance is a common clinical problem in lung cancer. However, the underlying mechanisms have not yet been fully elucidated, highlighting the importance of searching for biological targets. Methods: Bioinformatics analysis is completed through downloaded public data (GSE21656, GSE108214, and TCGA) and specific R packages. The evaluation of cell proliferation ability is completed through CCK8 assay, colony formation, and EdU assay. The evaluation of cell invasion and migration ability is completed through transwell and wound-healing assays. In addition, we evaluated cell cisplatin sensitivity by calculating IC50. Results: Here, we found that PCDH7 may be involved in cisplatin resistance in lung cancer through public database analysis (GSE21656 and GSE108214). Then, a series of in vitro experiments was performed, which verified the cancer-promoting role of PCDH7 in NSCLC. Moreover, the results of IC50 detection showed that PCDH7 might be associated with cisplatin resistance of NSCLC. Next, we investigated the single-cell pattern, biological function, and immune analysis of PCDH7. Importantly, we noticed PCDH7 may regulate epithelial-mesenchymal transition activity, and the local infiltration of CD8+ T and activated NK cells. Furthermore, we noticed that patients with high PCDH7 expression might be more sensitive to bortezomib, docetaxel, and gemcitabine, and resistant to immunotherapy. Finally, a prognosis model based on three PCDH7-derived genes (GPX8, BCAR3, and TNS4) was constructed through a machine learning algorithm, which has good prediction ability on NSCLC patients' survival. Conclusion: Our research has improved the regulatory framework for cisplatin resistance in NSCLC and can provide direction for subsequent related research, especially regarding PCDH7.

The Genomic and Proteomic Profiles of NTRK Genes and Trk Receptors in Liver Hepatocellular Carcinoma

Background

The neurotrophic tyrosine kinase (NTRK) gene family includes NTRK1, NTRK2, and NTRK3, which encode tropomyosin receptor kinases TrkA, TrkB, and TrkC, respectively. This study aimed to initially assess the genomic and proteomic profiles of NTRK genes and Trk receptors in liver hepatocellular carcinoma (LIHC).

Methods

The ONCOMINE, UALCAN, GEPIA, cBioPortal, FusionGDB, SurvivalMeth, and the Human Protein Atlas databases were searched for NTRK gene expression and protein data in LIHC. Immunohistochemistry was used to detect pan-Trk expression across a commercial microarray containing 96 hepatocellular carcinoma (HCC) and 94 para-cancerous tissue spots. A modified histological score (H-score) with a maximum score of 300 was used to quantify immunohistochemical staining for pan-Trk. Student's t- and chi-square tests were the main statistical analyses used.

Results

The transcriptional levels of NTRK genes in LIHC were not significantly different from healthy controls. Using UALCAN and GEPIA, only high expression of NTRK2 was significantly associated with longer disease-free survival (P = 0.004). The alteration frequencies were low (7% in NTRK1, 1.7% in NTRK2, and 2% in NTRK3). The methylation levels of NTRK genes were all significantly different as analyzed by UALCAN; the high-risk group displayed an unfavorable prognosis compared with the low-risk group for NTRK1 (P = 0.033) and NTRK3 (P = 0.005). The median H-score of pan-Trk in HCC and para-cancerous tissues was not statistically different (186.31 ± 23.86 and 192.38 ± 21.06, P = 0.065). No differences were observed in clinicopathological features of HCC with the median H-score for pan-Trk expression (p > 0.05). The survival rate of patients with pan-Trk expression was also not significantly different.

Conclusion

The alteration frequency was low in NTRK genes, including gene fusion and methylation levels. Therefore, pan-Trk expression in HCC tissue has limited value in clinicopathological features and prognosis.

Telomere-related prognostic biomarkers for survival assessments in pancreatic cancer

Human telomeres are linked to genetic instability and a higher risk of developing cancer. Therefore, to improve the dismal prognosis of pancreatic cancer patients, a thorough investigation of the association between telomere-related genes and pancreatic cancer is required. Combat from the R package "SVA" was performed to correct the batch effects between the TCGA-PAAD and GTEx datasets. After differentially expressed genes (DEGs) were assessed, we constructed a prognostic risk model through univariate Cox regression, LASSO-Cox regression, and multivariate Cox regression analysis. Data from the ICGC, GSE62452, GSE71729, and GSE78229 cohorts were used as test cohorts for validating the prognostic signature. The major impact of the signature on the tumor microenvironment and its response to immune checkpoint drugs was also evaluated. Finally, PAAD tissue microarrays were fabricated and immunohistochemistry was performed to explore the expression of this signature in clinical samples. After calculating 502 telomere-associated DEGs, we constructed a three-gene prognostic signature (DSG2, LDHA, and RACGAP1) that can be effectively applied to the prognostic classification of pancreatic cancer patients in multiple datasets, including TCGA, ICGC, GSE62452, GSE71729, and GSE78229 cohorts. In addition, we have screened a variety of tumor-sensitive drugs targeting this signature. Finally, we also found that protein levels of DSG2, LDHA, and RACGAP1 were upregulated in pancreatic cancer tissues compared to normal tissues by immunohistochemistry analysis. We established and validated a telomere gene-related prognostic signature for pancreatic cancer and confirmed the upregulation of DSG2, LDHA, and RACGAP1 expression in clinical samples, which may provide new ideas for individualized immunotherapy.

Multi-omics analysis of DNA replication-associated primase polymerase (PRIMPOL) in pan-cancer: a potential target for prognosis and immune response

BACKGROUND

It is critical to understand the mechanisms of human cancers in order to develop the effective anti-cancer therapeutic strategies. Recent studies indicated that primase polymerase (PRIMPOL) is strongly associated with the development of human cancers. Nevertheless, a systematic pan-cancer analysis of PRIMPOL remains to be further clarified.

METHOD

Comprehensive multi-omics bioinformatics algorithms, such as TIMER2.0, GEPIA2.0 and cBioPortal, were utilized to evaluate the biological roles of PRIMPOL in pan-cancer, including the expression profiles, genomic alterations, prognostic values and immune regulation.

RESULTS

PRIMPOL was upregulated in glioblastoma multiforme and kidney renal clear cell carcinoma. The brain lower grade glioma patients with enhanced PRIMPOL expression displayed poor prognostic values. We also demonstrated the PRIMPOL's immunomodulating effects on pan-cancer as well as its genomic changes and methylation levels. The aberrant expression of PRIMPOL was linked to various cancer-associated pathways, including DNA damage response, DNA repair, and angiogenesis, according to single-cell sequencing and function enrichment.

CONCLUSIONS

This pan-cancer analysis offers a thorough review of the functional roles of PRIMPOL in human cancers, suggesting PRIMPOL as a potentially important biomarker for the progression and immunotherapy of various cancers.

Intrinsic Immunogenic Tumor Cell Death Subtypes Delineate Prognosis and Responsiveness to Immunotherapy in Lung Adenocarcinoma

Recent studies have highlighted the combination of activation of host immunogenic cell death (ICD) and tumor-directed cytotoxic strategies. However, overall multiomic analysis of the intrinsic ICD property in lung adenocarcinoma (LUAD) has not been performed. Therefore, the aim of this study was to develop an ICD-based risk scoring system to predict overall survival (OS) and immunotherapeutic efficacy in patients. In our study, both weighted gene co-expression network analysis (WGCNA) and LASSO-Cox analysis were utilized to identify ICDrisk subtypes (ICDrisk). Moreover, we identify genomic alterations and differences in biological processes, analyze the immune microenvironment, and predict the response to immunotherapy in patients with pan-cancer. Importantly, immunogenicity subgroup typing was performed based on the immune score (IS) and microenvironmental tumor neoantigens (meTNAs). Our results demonstrate that ICDrisk subtypes were identified based on 16 genes. Furthermore, high ICDrisk was proved to be a poor prognostic factor in LUAD patients and indicated poor efficacy of immune checkpoint inhibitor (ICI) treatment in patients with pan-cancer. The two ICDrisk subtypes displayed distinct clinicopathologic features, tumor-infiltrating immune cell patterns, and biological processes. The IS^lowmeTNA^high subtype showed low intratumoral heterogeneity (ITH) and immune-activated phenotypes and correlated with better survival than the other subtypes within the high ICDrisk group. This study suggests effective biomarkers for the prediction of OS in LUAD patients and immunotherapeutic response across Pan-cancer and contributes to enhancing our understanding of intrinsic immunogenic tumor cell death.

Combining WGCNA and machine learning to construct basement membrane-related gene index helps to predict the prognosis and tumor microenvironment of HCC patients and verifies the carcinogenesis of key gene CTSA

Hepatocellular carcinoma (HCC) is a malignant tumor with high recurrence and metastasis rates and poor prognosis. Basement membrane is a ubiquitous extracellular matrix and is a key physical factor in cancer metastasis. Therefore, basement membrane-related genes may be new targets for the diagnosis and treatment of HCC. We systematically analyzed the expression pattern and prognostic value of basement membrane-related genes in HCC using the TCGA-HCC dataset, and constructed a new BMRGI based on WGCNA and machine learning. We used the HCC single-cell RNA-sequencing data in GSE146115 to describe the single-cell map of HCC, analyzed the interaction between different cell types, and explored the expression of model genes in different cell types. BMRGI can accurately predict the prognosis of HCC patients and was validated in the ICGC cohort. In addition, we also explored the underlying molecular mechanisms and tumor immune infiltration in different BMRGI subgroups, and confirmed the differences in response to immunotherapy in different BMRGI subgroups based on the TIDE algorithm. Then, we assessed the sensitivity of HCC patients to common drugs. In conclusion, our study provides a theoretical basis for the selection of immunotherapy and sensitive drugs in HCC patients. Finally, we also considered CTSA as the most critical basement membrane-related gene affecting HCC progression. In vitro experiments showed that the proliferation, migration and invasion abilities of HCC cells were significantly impaired when CTSA was knocked down.

Protocol to identify novel immunotherapy biomarkers based on transcriptomic data in human cancers

Immune checkpoint inhibitors have transformed the management of advanced cancers, but biomarkers for the prediction of therapeutic responses have not been fully uncovered. Here, we provide a step-by-step approach for the identification of novel biomarkers from public transcriptomic datasets. We comprehensively summarize the available transcriptomic datasets containing immunotherapy information and describe the necessary procedures to evaluate the effectiveness of a novel immunotherapy biomarker, which may accelerate the identification of novel immunotherapy biomarkers. For complete details on the use and execution of this protocol, please refer to Mei et al.¹.

Combined analysis of bulk and single-cell RNA sequencing reveals novel natural killer cell-related prognostic biomarkers for predicting immunotherapeutic response in hepatocellular carcinoma

Introduction

Natural killer (NK) cells play an irreplaceable and important role as a subtype of innate immune cells in the contemporary setting of antitumor immunity.

Methods

We chose a total of 1,196 samples for this analysis from the public dataset’s six separate cohorts. To identify 42 NK cell marker genes, we first carried out a thorough study of single-cell RNA sequencing data from the GSE149614 cohort of hepatocellular carcinoma (HCC).

Results

Using the NK cell marker genes in the TCGA cohort, we next created a seven-gene prognostic signature, separating the patients into two categories with distinct survival patterns. This signature’s prognostic prediction ability was well verified across several validation cohorts. Patients with high scores had higher TIDE scores but lower immune cell infiltration percentages. Importantly, low-scoring patients had superior immunotherapy response and prognosis than high-scoring patients in an independent immunotherapy cohort (IMvigor210). Finally, we used CD56 and TUBA1B antibodies for immunohistochemical labeling of HCC tissue sections, and we discovered a lower number of CD56+ cells in the HCC tissue sections with high TUBA1B expression.

Discussion

In summary, our research created a unique prognostic profile based on NK cell marker genes that may accurately predict how well immunotherapy would work for HCC patients.

The prognostic value and immunological role of SULF2 in adrenocortical carcinoma

Background

Adrenocortical carcinoma (ACC) represents the rare urological epithelial cancer of urinary tract, which has a large mass and is usually diagnosed at the advanced stage, thus inducing the poor prognosis. As a result, early detection and diagnosis are more important for the prognosis rather than the treatment of ACC. There is evidence supporting the association of Sulfatase2 (SULF2) with bladder cancer. However, the relationships of SULF2 with the clinical features and immune infiltration of ACC remain unclear.

Methods

This work comprehensively investigated the different expression levels of SULF2 within ACC and its prognostic significance through various databases including Gene Expression Profiling Interaction Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Kaplan-Meier (KM) plotter and UALCAN. Besides, SULF2 levels within different tumor and paraneoplastic tissues were examined based on Human Protein Atlas (HPA) and TIMER. Afterwards, this study identified differentially expressed genes (DEGs) in high-compared with low-SULF2-expression groups. To predict the possible interaction between SULF2 and its targets, a protein-protein interaction (PPI) network was constructed based on relevant data collected in STRING database. Besides, the SULF2 functional annotation was carried out, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and GSEA. In addition, gene mutation analysis was also performed based on the cBioPortal database. The relation of SULF2 with immune infiltration was analyzed from various aspects by using the resources of various databases including TIMER, TISIDB, and GEPIA, which was first reported in this work. Finally, R package was utilized to plot the receiver operating characteristic (ROC) curves of diagnosis, time-dependent survival, and the association of SULF2 with cancer stage and the nomogram model. Finally, CellMiner dataset was adopted for SULF2 correlation as well as drug sensitivity analysis.

Results

Relative to healthy people, SULF2 level markedly elevated within ACC tissues. Besides, SULF2 up-regulation significantly predicted the dismal prognostic outcome, which may be an important prognostic factor. Afterwards, the PPI network was constructed, and the possible link of SULF2 with the corresponding targets was predicted. Besides, up-regulated SULF2 expression was tightly related to immune regulation and tumor-infiltration immune cell (TIICs), including CD8⁺, CD4⁺ and mast cells. Finally, SULF2 expression was speculated to help determine the sensitivity of certain drugs.

Conclusions

SULF2 may offer a new therapeutic target for ACC patients and become an important potential prognostic biomarker.

Comprehensive analysis of fatty acid metabolism-related gene signatures for predicting prognosis in patients with prostate cancer

Fatty acid metabolism (FAM) is an important factor in tumorigenesis and development. However, whether fatty acid metabolism (FAM)-related genes are associated with prostate cancer (PCa) prognosis is not known. Therefore, we established a novel prognostic model based on FAM-related genes to predict biochemical recurrence in PCa patients. First, PCa sequencing data were acquired from TCGA as the training cohort and GSE21032 as the validation cohort. Second, a prostate cancer prognostic model containing 10 FAM-related genes was constructed using univariate Cox and LASSO. Principal component analysis and t-distributed stochastic neighbour embedding analysis showed that the model was highly effective. Third, PCa patients were divided into high- and low-risk groups according to the model risk score. Survival analysis, ROC curve analysis, and independent prognostic analysis showed that the high-risk group had short recurrence-free survival (RFS), and the risk score was an independent diagnostic factor with diagnostic value in PCa patients. External validation using GSE21032 also showed that the prognostic model had high reliability. A nomogram based on a prognostic model was constructed for clinical use. Fourth, tumor immune correlation analyses, such as the ESTIMATE, CIBERSORT algorithm, and ssGSEA, showed that the high-risk group had higher immune cell infiltration, lower tumour purity, and worse RFS. Various immune checkpoints were expressed at higher levels in high-risk patients. In summary, this prognostic model is a promising prognostic biomarker for PCa that should improve the prognosis of PCa patients. These data provide new ideas for antitumour immunotherapy and have good potential value for the development of targeted drugs.

KIF5A upregulation in hepatocellular carcinoma: A novel prognostic biomarker associated with unique tumor microenvironment status

Liver hepatocellular carcinoma (LIHC) is one of the most common liver malignancies with high mortality and morbidity. Thus, it is crucial to identify potential biomarker that is capable of accurately predicting the prognosis and therapeutic response of LIHC. Kinesin family member 5A (KIF5A) is a microtubule-based motor protein involved in the transport of macromolecules such as organelle proteins in cells. Recent studies have illustrated that the high expression of KIF5A was related to poor prognosis of solid tumors, including bladder cancer, prostate cancer, and breast cancer. However, little is currently known concerning the clinical significance of KIF5A expression in LIHC. Herein, by adopting multi-omics bioinformatics analysis, we comprehensively uncovered the potential function and the predictive value of KIF5A in stratifying clinical features among patients with LIHC, for which a high KIF5A level predicted an unfavorable clinical outcome. Results from KIF5A-related network and enrichment analyses illustrated that KIF5A might involve in microtubule-based process, antigen processing and presentation of exogenous peptide antigen via MHC class II. Furthermore, immune infiltration and immune function analyses revealed upregulated KIF5A could predict a unique tumor microenvironment with more CD8+T cells and a higher level of anti-tumor immune response. Evidence provided by immunohistochemistry staining (IHC) further validated our findings at the protein level. Taken together, KIF5A might serve as a novel prognostic biomarker for predicting immunotherapy response and could be a potential target for anti-cancer strategies for LIHC.

Prognostic Lysosome-Related Biomarkers for Predicting Drug Candidates in Hepatocellular Carcinoma: An Insilco Analysis

Background

Lysosomes play an important role in enhancing tumorigenesis and chemoresistance in hepatocellular carcinoma (HCC). Therefore, a detailed analysis of the role of lysosome-related genes could improve the poor prognosis of HCC patients.

Methods

Lysosome-associated genes were downloaded from the GO and Genome Enrichment Analysis (GSEA) databases. After analyzing lysosome-associated differentially expressed genes (DEGs) between the TCGA and GTEx cohorts, we used univariate Cox regression, LASSO-Cox regression, stepwise Cox regression, and multivariate Cox regression analyses to build a predictive risk model. The ICGC cohort was used as a test cohort for the prognostic signature's validation. It was also assessed how significantly the signature affected the tumor microenvironment (TME) and sensitivity to immune checkpoint inhibitors. To investigate the expression of this signature in clinical samples, qRT-PCR and immunohistochemistry (IHC) were carried out in 50 normal tissues and 59 HCC tissues.

Results

A total of 894 lysosome-associated genes were obtained. After identifying 113 lysosome-associated DEGs, we constructed a five-gene prognostic signature (RRAGD, AP1M2, CRHBP, NCSTN, and SLCO4C1) that can be effectively applied to the prognostic classification of HCC patients in TCGA and ICGC cohorts. Additionally, we discovered that this signature can affect the proportion of macrophage infiltration in TME. We also evaluated several tumor-sensitive medicines that affect this signature. Finally, we discovered that HCC tissues had lower amounts of CRHBP compared to normal tissues by the qRT-PCR and IHC assay.

Conclusion

We developed and validated a predictive signature of five lysosome-related genes for HCC patients and verified the downregulation of CRHBP expression in clinical samples, which may provide fresh perspectives for customized immunotherapy.

Identification of circRNA-lncRNA-miRNA-mRNA competitive endogenous RNA networks as prognostic bio-markers in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent neoplasms of malignancy. The pathogenesis of HNSCC is involved in the change of gene expression and the abnormal interaction between genes.

OBJECTIVE

The purpose of our research is to find genes that affect the survival time of patients and construct circRNA-lncRNA-miRNA-mRNA network. This paper aims to reveal the development mechanism of HNSCC and provide new ideas for clinical prognosis prediction.

METHODS

Transcriptome data were obtained from TCGA and GEO databases. A total of 556 samples were included. We screened the differentially expressed lncRNAs, circRNAs and mRNAs to predict interactions between lncRNA-miRNA, circRNA-miRNA and miRNA-mRNA. Then, we selected the hub mRNAs to predict the prognosis of patients.

RESULTS

We identified 8 hub prognostic mRNAs (FAM111A, IFIT2, CAV1, KLF9, OCIAD2, SLCO3A1, S100A16 and APOL3) by a series of bioinformatics analyses and established the prognostic ceRNA network of 8 mRNAs, 3 miRNAs, 2 circRNAs and 1 lncRNAs according to the targeting relationship by using databases.

CONCLUSION

We established the circRNA-lncRNA-miRNA-mRNA gene interaction network in HNSCC. We illuminated the molecular mechanism underlying the gene regulation associated with the pathogenesis of HNSCC and predicted the biomarkers related to prognosis.

Construction of a machine learning-based artificial neural network for discriminating PANoptosis related subgroups to predict prognosis in low-grade gliomas

The poor prognosis of gliomas necessitates the search for biomarkers for predicting clinical outcomes. Recent studies have shown that PANoptosis play an important role in tumor progression. However, the role of PANoptosis in in gliomas has not been fully clarified.Low-grade gliomas (LGGs) from TCGA and CGGA database were classified into two PANoptosis patterns based on the expression of PANoptosis related genes (PRGs) using consensus clustering method, followed which the differentially expressed genes (DEGs) between two PANoptosis patterns were defined as PANoptosis related gene signature. Subsequently, LGGs were separated into two PANoptosis related gene clusters with distinct prognosis based on PANoptosis related gene signature. Univariate and multivariate cox regression analysis confirmed the prognostic values of PANoptosis related gene cluster, based on which a nomogram model was constructed to predict the prognosis in LGGs. ESTIMATE algorithm, MCP counter and CIBERSORT algorithm were utilized to explore the distinct characteristics of tumor microenvironment (TME) between two PANoptosis related gene clusters. Furthermore, an artificial neural network (ANN) model based on machine learning methods was developed to discriminate distinct PANoptosis related gene clusters. Two external datasets were used to verify the performance of the ANN model. The Human Protein Atlas website and western blotting were utilized to confirm the expression of the featured genes involved the ANN model. We developed a machine learning based ANN model for discriminating PANoptosis related subgroups with drawing implications in predicting prognosis in gliomas.

A comprehensive analysis focusing on cuproptosis to investigate its clinical and biological relevance in uterine corpus endometrial carcinoma and its potential in indicating prognosis

Cuproptosis, a novel copper-dependent cell death involving mitochondrial respiration, is distinct from other known death mechanisms, which inspires us to study further in uterine corpus endometrial carcinoma (UCEC). Herein, leveraging comprehensive data from TCGA-UCEC, we conducted transcriptional and genetic analyses of 13 recently identified cuproptosis genes. We discovered severe genetic instability of cuproptosis genes, extensive positive correlations among those genes with each other at the mRNA level, and their involvement in oncogenic pathways in UCEC samples. Next, WGCNA was performed to identify a potential module regulating cuproptosis, in which the hub genes, in addition to 13 cuproptosis genes, were drawn to construct a scoring system termed Cu. Score. Furthermore, its clinical and biological relevance and tumor immune landscape, genetic alterations, as well as predicted sensitivity of chemotherapy drugs in different Cu. Score subgroups had been discussed extensively and in detail. Additionally, univariate Cox and LASSO regression were performed to identify 13 cuproptosis-related prognostic genes to establish a prognostic signature, the Risk. Score. Integrating the Risk. Score and clinical parameters, we established a nomogram with excellent performance to predict the 1-/3-/5-year survival probabilities of UCEC patients. To conclude, we conducted a comprehensive analysis encompassing cuproptosis and developed a cuproptosis scoring system and a prognostic prediction model for UCEC, which may offer help with individualized assessment and treatment for UCEC patients from the perspective of a novel death mechanism.