The role of CD47 in immune escape of colon cancer and its correlation with heterogeneity of tumor immune microenvironment

Background

Cluster of differentiation 47 (CD47), a transmembrane protein, plays a critical role in regulating cellular functions and maintaining immune homeostasis. Its expression has been shown to influence cancer prognosis. In this study, we investigated the role of CD47 in tumor progression in colon adenocarcinoma (COAD) and evaluated its potential as a target for immunotherapy.

Materials and Methods

We analyzed surgical samples from 96 COAD patients. Immunohistochemical analysis was performed on 90 samples, while the remaining 6 were subjected to multiplex immunofluorescence. To explore the association between CD47 expression and clinicopathological characteristics, we integrated transcriptome data from The Cancer Genome Atlas and the Gene Expression Omnibus using R software. The Tumor Immune Estimation Resource and Kaplan-Meier plotter were utilized to assess the relationship between CD47 expression, patient prognosis, and immune infiltration. Furthermore, the single-cell Tumor Immune System Interaction Database was used to examine the correlation between CD47 expression and the tumor microenvironment (TME). All included patients gave oral and written informed consent. The study was approved by the Ethics Committee of 3201 Hospital (full name: Medical Ethics Committee of 3201 Hospital).

Results

CD47 was found to be overexpressed in various tumors, including COAD. Higher CD47 expression was significantly associated with more advanced tumor stages, including TNM staging, T staging, and N staging (P < 0.05). A robust correlation was observed between CD47 expression and immune cell infiltration in COAD. Patients with elevated CD47 expression tended to have longer disease-free intervals, although this benefit was diminished in cases with high infiltration of M1 macrophages. The immunosuppressive function of CD47 primarily acted through the CD47/SIRPα pathway. Additionally, distinct cellular compositions and distributions were identified between primary and metastatic COAD, underscoring the heterogeneity of the TME. CD47 also influenced the TME by modulating cytokine and cytokine receptor interactions.

Conclusion

CD47 represents a promising prognostic biomarker and a potential target for immunotherapy in COAD. These findings provide new insights into therapeutic strategies aimed at modulating the TME and improving patient outcomes.

Gene-expression profile analysis to disclose diagnostics and therapeutics biomarkers for thyroid carcinoma

The most frequent endocrine cancer of the head and neck is thyroid carcinoma (THCA). Although there is increasing evidence linking THCA to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. There is still much to learn about THCA's molecular roots and genetic biomarkers. Though drug therapies are the best choice after metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving them for a few years. Therefore, multi-targeted different variants of therapeutic drugs may be essential for effective treatment against THCA. To understand molecular mechanisms of THCA development and progression and explore multi-targeted different variants of therapeutic drugs, we detected 80 common differentially expressed genes (cDEGs) between THCA and non-THCA samples from six microarray gene expression datasets using the statistical LIMMA approach. Through protein-protein interaction (PPI) network analysis, we identified the top-ranked eight differentially expressed genes (TIMP1, FN1, THBS1, RUNX2, SHANK2, TOP2A, LRP2, and ACTN1) as the THCA-causing key genes (KGs), where 6 KGs (TIMP1, TOP2A, FN1, ACTN1, RUNX2, THBS1) are upregulated and 2 KGs (LRP2, SHANK2) are downregulated. The expression pattern analysis of KGs with the independent TCGA database by Box plots also confirmed their upregulated and downregulated patterns. The expression analysis of KGs in different stages of THCA development indicated that these KGs might be utilized as early diagnostic and prognostic biomarkers. The pan-cancer analysis of KGs indicated a substantial correlation of KGs with multiple cancers, including THCA. Some transcription factors (TFs) and microRNAs were detected as the key transcriptional and post-transcriptional regulators of KGs using gene regulatory network (GRN) analysis. The enrichment analysis of the cDEGs revealed several key molecular functions, biological processes, cellular components, and pathways significantly associated with THCA. These findings highlight critical mechanisms influenced by the identified key genes (KGs), providing deeper insight into their roles in THCA development. Then we detected 6 repurposable drug molecules (Entrectinib, Imatinib, Ponatinib, Sorafenib, Retevmo, and Pazopanib) by molecular docking with KGs-mediated receptor proteins, ADME/T analysis, and cross-validation with the independent receptors. Therefore, these findings might be useful resources for wet lab researchers and clinicians to consider an effective treatment strategy against THCA.

KLK7, KLK10, and KLK11 in Papillary Thyroid Cancer: Bioinformatic Analysis and Experimental Validation

Despite many studies on papillary thyroid carcinoma (PTC) in the past few decades, some critical and significant genes remain undiscovered. To explore genes that may play crucial roles in PTC, a detailed analysis of the expression levels, mutations, and clinical significance of Kallikrein-related peptidases (KLKs) family genes in PTC was undertaken to provide new targets for the precise treatment of the disease. A comprehensive analysis of KLK family genes was performed using various online tools, such as GEPIA, Kaplan-Meier Plotter, LinkedOmics, GSCA, TIMER, and Cluego. KLK7, KLK10, and KLK11 were critical factors of KLK family genes. Then, functional assays were carried out on KLK7/10/11 to determine their proliferation, migration, and invasion capabilities in PTC. The mRNA expression levels of KLK7, KLK10, KLK11, and KLK13 were significantly elevated in thyroid carcinoma, while KLK1, KLK2, KLK3 and KLK4 mRNA levels were decreased compared to normal tissues. Correlations between KLK2/7-12/15 expression levels and tumor stage were also observed in thyroid carcinoma. Survival analysis demonstrated that KLK4/5/7/9-12/14 was associated with overall survival in patients with thyroid cancer. Not only were KLK genes strongly associated with cancer-related pathways, but also KLK7/10/11 was associated with immune-cell infiltration. Finally, silencing KLK7/10/11 impaired human papillary thyroid carcinoma cells' growth, migration ability, and invasiveness. The increased expression of KLK7, KLK10, and KLK11 may serve as molecular markers to identify PTC patients. KLK7, KLK10, and KLK11 could be potential prognostic indicators and targets for precision therapy against PTC.

Bioinformatics analysis and experimental validation of the oncogenic role of COL11A1 in pan-cancer

The intricate expression patterns and oncogenic attributes of COL11A1 across different cancer types remain largely elusive. This study used several public databases (TCGA, GTEx, and CCLE) to investigate the pan-cancer landscape of COL11A1 expression, its prognostic implications, interplay with the immune microenvironment, and enriched signaling cascades. Concurrently, western blot analyses were performed to verify COL11A1 expression in lung adenocarcinoma (LUAD) cell lines and clinical samples. In addition, COL11A1 knockout cell lines were generated to scrutinize the functional consequences of COL11AI expression on cancer cell behavior by use MTT, colony formation, and scratch wound healing assays. A comprehensive database investigation revealed that COL11A1 was upregulated in a majority of tumor tissues and its expression was highly correlated with a patient's prognosis. Notably, genetic alterations in COL11A1 predominantly occurred as mutations, while its DNA methylation status inversely mirrored gene expression levels across multiple promoter regions. Our findings suggest that COL11A1 helps to modulate the tumor immune landscape and potentially acts through the epithelial-mesenchymal transition (EMT) pathway to exert its oncogenic function. Western blot analyses further substantiated the specific upregulation of COL11A1 in LUAD cell lines and tissues, suggesting a close association with the EMT process. Ablation of COL11A1 in cancer cells significantly reduced their proliferative, clonogenic, and migratory abilities, underscoring the functional significance of COL11A1 in tumor cell behavior. Collectively, this research revealed the prevalent overexpression of COL11A1 in pan-cancer tissues, its profound prognostic and microenvironmental correlations, and the mechanistic underpinnings of its tumor-promoting effects as mediated via EMT signaling. Our findings suggest that COL11A1 could serve as a prognostic and diagnostic biomarker and therapeutic target for cancer.

A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer

Comprehensive action patterns of programmed cell death (PCD) in bladder cancer (BLCA) have not yet been thoroughly investigated. Here, we collected 19 different PCD patterns, including 1911 PCD-related genes, and developed a multiple programmed cell death index (MPCDI) based on a machine learning computational framework. We found that in the TCGA-BLCA training cohort and the independently validated GSE13507 cohort, the patients with high-MPCDI had a worse prognosis, whereas patients with low-MPCDI had a better prognosis. By combining clinical characteristics with the MPCDI, we constructed a nomogram. The C-index demonstrated that the nomogram was significantly more accurate compared to other variables, including MPCDI, age, gender, and clinical stage. The results of the decision curve analysis demonstrated that the nomogram had a better net clinical benefit compared to other clinical variables. Subsequently, we revealed the heterogeneity of BLCA patients, with significant differences in terms of overall immune infiltration abundance, immunotherapeutic response, and drug sensitivity in the two MPCDI groups. Encouragingly, the high-MPCDI patients showed better efficacy for commonly used chemotherapeutic drugs than the low-MPCDI patients, which suggests that MPCDI scores have a guiding role in chemotherapy for BLCA patients. In conclusion, the MPCDI developed and verified in this study is not only an emerging clinical classifier for BLCA patients, but it also serves as a reliable forecaster for both chemotherapy and immunotherapy, which can guide clinical management and clinical decision-making for BLCA patients.

Sorafenib and SIAIS361034, a novel PROTAC degrader of BCL-xL, display synergistic antitumor effects on hepatocellular carcinoma with minimal hepatotoxicity

The overexpression of BCL-xL is closely associated with poor prognosis in hepatocellular carcinoma (HCC). While the strategy of combination of BCL-xL and MCL-1 for treating solid tumors has been reported, it presents significant hepatotoxicity. SIAIS361034, a novel proteolysis targeting chimera (PROTAC) agent, selectively induces the ubiquitination and subsequent proteasomal degradation of BCL-xL through the CRBN-E3 ubiquitin ligase. When combined with sorafenib, SIAIS361034 showed a potent synergistic effect in inhibiting hepatocellular carcinoma development both in vitro and in vivo. Since SIAIS361034 exhibits a high degree of selectivity for degrading BCL-xL in hepatocellular carcinoma, the hepatotoxicity typically associated with the combined inhibition of BCL-xL and MCL-1 is significantly reduced, thereby greatly enhancing safety. Mechanistically, BCL-xL and MCL-1 sequester the BH3-only protein BIM on mitochondria at baseline. Treatment with SIAIS361034 and sorafenib destabilizes BIM/BCL-xL and BIM/MCL1 association, resulting in the liberation of more BIM proteins to trigger apoptosis. Additionally, we discovered a novel compensatory regulation mechanism in hepatocellular carcinoma cells. BIM can rapidly respond to changes in the balance between BCL-xL and MCL-1 through their co-transcription factor MEF2C to maintain apoptosis resistance. In summary, the combination therapy of SIAIS361034 and sorafenib represents an effective and safe approach for inhibiting hepatocellular carcinoma progression. The novel balancing mechanism may also provide insights for combination and precision therapies in the treatment of hepatocellular carcinoma.

Integrating machine learning and multi-omics analysis to develop an asparagine metabolism immunity index for improving clinical outcome and drug sensitivity in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignancy affecting the respiratory system. Most patients are diagnosed with advanced or metastatic lung cancer due to the fact that most of their clinical symptoms are insidious, resulting in a bleak prognosis. Given that abnormal reprogramming of asparagine metabolism (AM) has emerged as an emerging therapeutic target for anti-tumor therapy. However, the clinical significance of abnormal reprogramming of AM in LUAD patients is unclear. In this study, we collected 864 asparagine metabolism-related genes (AMGs) and used a machine-learning computational framework to develop an asparagine metabolism immunity index (AMII) for LUAD patients. Through the utilization of median AMII scores, LUAD patients were segregated into either a low-AMII group or a high-AMII group. We observed outstanding performance of AMII in predicting survival prognosis in LUAD patients in the TCGA-LUAD cohort and in three externally independently validated GEO cohorts (GSE72094, GSE37745, and GSE30219), and poorer prognosis for LUAD patients in the high-AMII group. The results of univariate and multivariate analyses showed that AMII can be used as an independent risk factor for LUAD patients. In addition, the results of C-index analysis and decision analysis showed that AMII-based nomograms had a robust performance in terms of accuracy of prognostic prediction and net clinical benefit in patients with LUAD. Excitingly, LUAD patients in the low-AMII group were more sensitive to commonly used chemotherapeutic drugs. Consequently, AMII is expected to be a novel diagnostic tool for clinical classification, providing valuable insights for clinical decision-making and personalized management of LUAD patients.

Clinical relevance and function of HMGB1 gene polymorphism and expression in colorectal cancer

High HMGB1 levels contribute to the development and metastasis of tumors such as colorectal cancer (CRC). The current investigation sought to evaluate the association of a functional InDel polymorphism (rs34000982) on the HMGB1 gene with CRC susceptibility and tumor stage and the clinical relevance of HMGB1 gene expression. A total of 600 CRC patients and 600 healthy control individuals were genotyped by a polymerase chain reaction-polyacrylamide gel electrophoresis assay. The findings demonstrated that the rs34000982 Ins allele or Ins/Ins genotype was associated not only with reduced susceptibility to CRC, especially stage III-IV CRC (Ins vs. Del: OR = 0.65, 95%CI = 0.51-0.82, p < 0.001; Ins/Ins vs. Del/Del: OR = 0.29, 95%CI = 0.14- 0.60, p < 0.001), but also with tumor stage. CRC patients carrying the Ins allele or Ins/Ins genotype had a significantly lower risk of stage III-IV tumors (Ins vs. Del: OR = 0.69, 95%CI = 0.53- 0.91; Ins/Ins vs. Del/Del: OR = 0.41, 95%CI = 0.18-0.94). Functional research revealed that the rs34000982 Ins allele enabled hsa-miR-944 to interact with the 3' untranslated region of HMGB1. In addition, HMGB1 gene expression levels were associated not only with multiple immune cell infiltration, but also with multiple anti-CRC drug sensitivities. The current findings suggest that the HMGB1 rs34000982 polymorphism may serve as a marker of CRC susceptibility and progression in the Chinese population, and HMGB1 levels may serve as an anti-CRC drug sensitivity marker.

Towards simplified graph neural networks for identifying cancer driver genes in heterophilic networks

The identification of cancer driver genes is crucial for understanding the complex processes involved in cancer development, progression, and therapeutic strategies. Multi-omics data and biological networks provided by numerous databases enable the application of graph deep learning techniques that incorporate network structures into the deep learning framework. However, most existing methods do not account for the heterophily in the biological networks, which hinders the improvement of model performance. Meanwhile, feature confusion often arises in models based on graph neural networks in such graphs. To address this, we propose a Simplified Graph neural network for identifying Cancer Driver genes in heterophilic networks (SGCD), which comprises primarily two components: a graph convolutional neural network with representation separation and a bimodal feature extractor. The results demonstrate that SGCD not only performs exceptionally well but also exhibits robust discriminative capabilities compared to state-of-the-art methods across all benchmark datasets. Moreover, subsequent interpretability experiments on both the model and biological aspects provide compelling evidence supporting the reliability of SGCD. Additionally, the model can dissect gene modules, revealing clearer connections between driver genes in cancers. We are confident that SGCD holds potential in the field of precision oncology and may be applied to prognosticate biomarkers for a wide range of complex diseases.

Bioinformatics-based analysis of the role of immune-related genes in acute rejection after kidney transplantation and renal cancer development

Acute rejection (AR) is a common complication in the early stage after kidney transplantation. Some studies have shown that the occurrence of AR after kidney transplantation may further affect the development of tumors, and both AR and tumor development are related to immune cells and immune genes, so it is particularly important to diagnose the occurrence of AR at an early stage and to analyze the correlation between AR and tumors. In this study, we applied bioinformatics techniques for differential expression analysis and weighted gene co-expression network analysis analysis of AR patients to obtain differentially expressed genes and modular genes significantly associated with AR, respectively, so as to obtain their intersecting genes with immune-related genes; 21 intersecting genes were screened by lasso regression and Boruta algorithm to obtain the genes, and finally, the feature genes that were significantly associated with the dependent variable were further obtained by single-factor and multi-factor logistic regression. Then the best diagnostic model for AR was screened by 10 machine learning methods, and we evaluated the model in various aspects, such as receiver operator characteristic curve, decision curve analysis. We then focused on the role of FAM3C in renal cancer. We finally screened 4 feature genes (CD1D, FPR2, FAM3C, and HMOX1) to construct the AR diagnostic model; through comparative evaluation, we believe that logistic regression shows a better advantage in the construction of diagnostic models for AR. FAM3C may become a potential biological marker for AR diagnosis and plays an important role in the development of renal cancer. In summary, immune-related genes play an important role in the diagnosis of AR after kidney transplantation, and the gene FAM3C may be a potential therapeutic target for AR and renal cancer.

Pan-cancer analysis of oncogenic role of CEP55 and experiment validation in clear cell renal cell carcinoma

Immunotherapy has emerged as a vital component in the contemporary landscape of cancer treatment. Recent studies have indicated that CEP55 plays an oncogenic role; however, its specific mechanisms in promoting tumor proliferation and its potential value in prognosis and immunotherapy prediction across various cancers remain to be elucidated. CEP55 was significantly overexpressed in 22 cancer types compared with their adjacent normal tissues. Elevated CEP55 expression was positively correlated with younger onset age, worse tumor stage, lower response rate to the first treatment, lower tumor-free survival rate, and poorer overall survival (OS) and disease-free survival (DFS) prognosis in most cancers. Moreover, CEP55 expression was positively correlated with its binding and related genes, such as KIF11 (R = 0.83, P < 0.001), CDK1 (R = 0.77, P < 0.001) and CCNA2 (R = 0.76, P < 0.001), and the classic proliferation markers, including MKI67 and PCNA. Enrichment analyses indicated that CEP55 was predominantly associated with cell division, cell cycle activities and proliferation. Immune cell infiltration analysis by TIMER2.0 revealed that CEP55 expression was positively correlated with many kinds of infiltrating cells, such as Th2 cells and some CD4+ T cell subsets. The CEP55 expression was positively associated with increased MSI and TMB in various cancers. Our analyzation indicated that the CEP55 expression level in patients with complete remission (CR) or partial remission (PR) to anti-PDL1 therapy was significantly higher than patients with stable disease (SD) or progressive disease (PD) based on IMvigor210 cohort. We also used Gene Set Cancer Analysis (GSCA) to predict a serious of small molecule CEP55 targeted drugs, such as AZ628, SB52334, SB590885, A-770,041, AZD7762, Elesclomol, panobinostat, BRD-A94377914, and LRRK2-IN-1. Furthermore, the patients with high level of CEP55-posivie tumor epithelial cells had inferior overall survival in ccRCC according to single-cell analysis. Finally, our wet lab experiments verified that the CEP55-positive rate in ccRCC tissues (19/30, 63.3%) was significantly higher than that in renal adjacent tissues (10/30, 33.3%). The clinicopathologic analysis revealed that CEP55 protein level was significantly associated with tumor size (P = 0.044), histology grade (P < 0.001) and stage (P = 0.034). Our study indicated that CEP55 overexpression in most caner types was associated with poor prognosis. Notably, CEP55 was closely relevant to immune cell infiltration and impacted the response to immunotherapy and small molecule drugs against cancers.

Inhibition of NPC1 suppresses cell proliferation and β-catenin signaling activation of liver cancer

Niemann-Pick Type C1 (NPC1) plays a significant role in the development of liver diseases and liver cancer. Our objective was to investigate the involvement of NPC1 in regulating liver cancer development. We observed that high levels of NPC1 expression in tumor tissues from patients with liver cancer were associated with a poor prognosis. Through in vitro experiments, we found that inhibiting NPC1 expression reduced the proliferation, invasion, and migration of liver cancer cells, while also inducing apoptosis in these cells. Additionally, the inhibition of NPC1 led to decreased activation of Wnt/β-catenin signaling. In vivo studies further supported our findings by demonstrating that the suppression of liver cancer cell growth was effectively achieved through the inhibition of NPC1. Overall, our results strongly indicate that the inhibition of NPC1 suppresses liver cancer cell proliferation. Targeting NPC1 is a promising potential therapeutic strategy for liver cancer.

Expression of HECTD2 predicts peritoneal metastasis of gastric cancer and reconstructs immune microenvironment

Peritoneal metastasis (PM) is a common metastasis site and death cause of gastric cancer, which is a complex biological process, but there is currently a lack of effective prediction and treatment targets. In this study, we first analyzed the differential gene expression of gastric cancer patients with or without peritoneal metastasis, and identified the HECT domain E3 ubiquitin protein ligase 2 (HECTD2) as the core gene of PM in gastric cancer. The current study shows that the role of HECTD2 in tumor is contradictory. In this study, our results show that the low expression of HECTD2 indicates that the survival rate of overall survival (OS), progression-free survival (PFS), disease-specific survival (DSS), and disease-free survival (DFS) are better, and can be used as an important component of prognostic indicators. In addition, through pathway enrichment analysis, we found that HECTD2 was mainly involved in metastasis related pathways such as extracellular matrix remodeling and cell adhesion in gastric cancer, and high expression of HECTD2 could activate epithelial-mesenchymal transition (EMT) metastasis related pathways in gastric cancer. In regulating the metastasis of gastric cancer cells, HECTD2 can also change the surrounding microenvironment, induce the enrichment of interstitial components and build an immune microenvironment conducive to tumor progression, while patients with low expression of HECTD2 may be more likely to benefit from immunotherapy. In conclusion, HECTD2 may be a novel biomarker for the diagnosis and prognosis of peritoneal metastasis of gastric cancer, providing basis for the mechanism of peritoneal metastasis of cancer and clinical medication.

PLAC1 augments the malignant phenotype of cervical cancer through the mTOR/HIF-1α/snail signaling pathway

AIMS

This study investigated the molecular mechanisms of placenta-specific protein 1 (PLAC1) in cervical cancer (CCa), aiming to elucidate its role in tumorigenesis through in vitro and in vivo experiments.

MATERIALS AND METHODS

CCa cell lines with overexpressed or silenced PLAC1 were established to evaluate its impact on cell cycle, apoptosis and the expression of key proteins in the PLAC1/mTOR/HIF-1α/Snail signaling pathways. Functional assays were conducted to assess the influence of the PLAC1/mTOR/HIF-1α/Snail regulatory pathway on cell proliferation, migration and invasion. The role of the mTOR signaling pathway in PLAC1-mediated modulation of CCa characteristics was validated using a mTOR activator (MHY1485) and a mTOR inhibitor (Rapamycin) respectively. HIF1A siRNA was introduced to confirm the role of HIF1A. Furthermore, an in vivo nude mouse model was constructed to confirm PLAC1's influence on tumorigenesis and metastasis in CCa.

KEY FINDINGS

PLAC1 upregulated hypoxia-inducible factor (HIF)-1α and Snail, promoting CCa cell proliferation, migration, and invasion via the mTOR/HIF-1α/Snail pathway. Enrichment analysis of PLAC1-associated differentially expressed genes implicated their involvement in CCa and tumor promotion. In a xenograft mouse model, PLAC1 exhibited a pro-tumorigenic effect, which can be reversed by siRNA targeting HIF1A.

SIGNIFICANCE

This study enhances our understanding of PLAC1's role and molecular mechanisms in CCa progression, highlighting its potential as a diagnostic, prognostic, and therapeutic marker for the management of CCa.

Pan-cancer analysis of STAT3 indicates its potential prognostic value and correlation with immune cell infiltration in prostate cancer

BACKGROUND

Targeting the STAT3 signaling pathway is a promising therapeutic approach for cancer patients. However, the association between STAT3 expression, the tumor immune microenvironment, and genetic variation remains unclear across human cancers, especially prostate cancer.

METHODS

We used R software and other tools to analyze pan-cancer and mutation data from publicly available databases statistically. A comprehensive investigation was performed to assess the genetic heterogeneity and clinical relevance of STAT3 in various malignancies, with a specific focus on its role in the immune landscape and prognostic significance in prostate cancer. The findings were validated through immunohistochemistry (IHC) and multiplex immunofluorescence (mIF).

RESULTS

STAT3 expression is abnormal in the majority of cancer tissues, which is strongly correlated with these patients' prognosis. Eight measures of tumor heterogeneity and six measures of tumor stemness of multiple tumor types showed a strong correlation with STAT3 expression. Furthermore, in individuals with prostate cancer, STAT3 expression indicated the degree of immune cell infiltration and the advancement of the disease. IHC analysis revealed that STAT3 was down-regulated in prostate tumor tissues, while mIF analysis demonstrated that STAT3 signaling (p-STAT3) was extensively active in tumor tissues and positive lymph node tissues.

CONCLUSION

STAT3 may serve as a valuable prognostic biomarker and therapeutic target across various cancers, with particular relevance to prostate cancer.

An integrated bioinformatics approach to early diagnosis, prognosis and therapeutics of non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the most deadly tumors characterized by poor survival rates. Advances in therapeutics and precise identification of biomarkers can potentially reduce the mortality rate. Thus, this study aimed to identify a set of common and stable gene biomarkers through integrated bioinformatics approaches that might be effective for NSCLC early diagnosis, prognosis, and therapies. Four gene expression profiles (GSE19804, GSE19188, GSE10072, and GSE32863) downloaded from the Gene Expression Omnibus database to identify common differential expressed genes (DEGs). A total of 213 overlapping DEGs (oDEGs) between NSCLC and healthy samples were identified by using statistical LIMMA method. Then 6 common top-ranked key genes (KGs) (CENPF, CAV1, ASPM, CCNB2, PRC1, and KIAA0101) were selected by using four network-measurer methods in the protein- protein interaction network. The GO functional and KEGG pathway enrichment analysis were performed to reveal some significant functions and pathways associated with NSCLC progression. Transcriptional and post-transcriptional factors of KGs were identified through the regulatory interaction network. The prognostic power and expression level of KGs were validated by using the independent data through the Kaplan-Meier and Box plots, respectively. Finally, 4 KGs-guided repositioning candidate drugs (ZSTK474, GSK2126458, Masitinib, and Trametinib) were proposed. The stability of three top-ranked drug-target interactions (CAV1 vs. ZSTK474, CAV1 vs. GSK2126458, and ASPM vs. Trametinib) were investigated by computing their binding free energies for 140 ns MD-simulation based on MM-PBSA approach. Therefore, the findings of this computational study may be useful for early prognosis, diagnosis and therapies of NSCLC.

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches

Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM.

Multi-omics analysis of the biological function of the VEGF family in colon adenocarcinoma

The vascular endothelial growth factor (VEGF) family plays a crucial role in cancer progression, but the prognostic significance and biological functions of VEGF family members in colon adenocarcinoma (COAD) remain unclear. Using data from The Cancer Genome Atlas, Gene Expression Omnibus, Gene Set Cancer Analysis, cBioPortal, GeneMANIA, String, MethSurv and starBase database, we identified vascular endothelial growth factor B (VEGFB) as a key gene associated with COAD prognosis, with its abnormal expression linked to methylation dysregulation. In vitro experiments confirmed VEGFB expression was significantly higher in colon cancer tissues compared to normal tissues, as shown by Real-time quantitative PCR and immunohistochemistry. Cell Counting Kit-8 and colony formation assay showed that decreased VEGFB expression in SW480 cells resulted in decreased cell viability and proliferation ability. Scratch assay showed that VEGFB downregulation impaired SW480 cell migration. In addition, our research suggests that VEGFB not only promotes angiogenesis but is also involved in the tumor microenvironment and immune regulation. The SHNG17-miR-375-VEGFB regulatory axis provides a potential therapeutic target for COAD, highlighting VEGFB's role in immune activation during anti-angiogenic therapy and potential reversal of drug resistance.

Characterization of the function and clinical value of ERCC family genes in lung adenocarcinoma

Introduction

ERCC genes, responsible for encoding enzymes involved in base excision repair, have been implicated in various cancers, contributing to chemoresistance. However, a comprehensive analysis of the prognostic and therapeutic significance of this gene family in lung adenocarcinoma (LUAD) is lacking.

Methods

This study conducted a multidimensional assessment of ERCC family genes in LUAD using bioinformatic approaches, including mRNA expression level, gene methylation, and copy number variation (CNV), as well as their correlations with clinical outcome, gene set variations, and tumor-infiltrating lymphocytes (TILs). In addition, We evaluated the anti-tumor effects of ERCC8 in cell lines, demonstrating its clinical potential on an experimental level.

Results

Overall, the expression of ERCC genes exhibited a negative correlation with good prognosis, with ERCC6L and ERCC8 demonstrating the most reliable predictive performance. Gene methylation level and CNV increases of ERCC genes generally displayed negative and positive associations with their expression levels, respectively. Additionally, GSVA analysis suggested that ERCC expression was positively correlated with cell cycle and apoptosis pathways but negatively correlated to the TSC/mTOR pathway. Furthermore, the expression of ERCC genes exhibited a complex relationship with TILs and the response to anti-tumor drugs. The results of in vitro cellular experiments show that inhibiting ERCC8 can alleviate the malignant phenotype of LUAD cells.

Discussion

Our study revealed the multifaceted biological and clinical significance of ERCC family members in LUAD. These findings provide new insights into the function of ERCC family genes in LUAD and their potential clinical applications.

Elevated ITGA3 expression serves as a novel prognostic biomarker and regulates tumor progression in cervical cancer

Patients with advanced and recurrent cervical cancer often lack satisfactory treatment outcomes. Thus, it is necessary to seek reliable biomarkers that provide the ability to identify the disease at an early stage and predict the patient prognosis, providing new strategies for the treatment of cervical cancer. The sequencing data of ITGA3 were retrieved from public datasets. Immune infiltration and sensitivity of potential immunotherapy and chemotherapy have been analyzed between two subgroups. Functional analysis was applied to excavate the related pathways of ITGA3 in cervical cancer. Furthermore, the impact of ITGA3 in tumor progression has been verified in vitro. The results revealed that the level of ITGA3 was upregulated in cervical cancer, and was positively correlated with worse prognosis. The tumor microenvironment of patients in the high-risk group was immunosuppressed. Patients in high-risk group may not benefit from immunotherapy, but be may be sensitive to several chemotherapy drugs. Notably, the angiogenesis, epithelial mesenchymal transition, and PI3K pathway were increased in high-risk group. Collectively, ITGA3 is a marker of poor prognosis and promotes tumor progression by regulating PI3K/AKT pathway in cervical cancer. Our results provide new insights for potential molecular targeted therapy and prognostic prediction of cervical cancer.

Comprehensive Pan-Cancer Analysis of the Prognostic Role of KLF Transcription Factor 2 (KLF2) in Human Tumors

Background

KLF2 is a transcription factor expressed early in mammalian development that plays a role in many processes of development and disease. Recently, increasing studies revealed that KLF2 plays a key role in the occurrence and progression of cancer.

Purpose

The aim of this study was to explore the role of KLF2 in various tumor types using the Cancer Genome Atlas dataset.

Methods

Here, we set out to explore the role of KLF2 in 33 tumor types using TCGA (The Cancer Genome Atlas), GEO (Gene Expression Omnibus) dataset, Human Protein Atlas (HPA), UALCAN database, CancerSEA, GSCALite and several bioinformatic tools. Furthermore, we also performed immunohistochemistry and qPCR to further validate the role of KLF2 in multiple cancers and its correlation with prognosis.

Results

We found that KLF2 was underexpressed in most tumors and generally predicted poor OS in tumor patients. We found that amplification of KLF2 may be a risk factor for patients with OV (Ovarian serous cystadenocarcinoma). We also analyzed the abundance of checkpoints and markers of specific immune subsets including CD8+ T lymphocytes (T cells), CD4+ T cells, macrophages, and endothelial cells that significantly correlated with the expression level of KLF2 in pan-carcinoma tissues. In some cancers, KLF2 expression levels are positively correlated with gene promoter DNA methylation and drug sensitivity. In addition, we found that KLF2 is involved in single-cell level cell invasion in some cancers. In addition, KLF2 is co-expressed with several intracellular signal transduction genes involved in immune system processes. Immunohistochemistry and qPCR confirmed the low expression of KLF2 in STAD (stomach adenocarcinoma) and renal cancer.

Conclusion

Our pan-cancer analysis provides a comprehensive overview of the oncogenic roles of KLF2 in multiple human cancers and can be regarded as a potential prognostic marker and a novel target for cancer immunotherapy.

Ribosomal proteins in hepatocellular carcinoma: mysterious but promising

Ribosomal proteins (RPs) are essential components of ribosomes, playing a role not only in ribosome biosynthesis, but also in various extra-ribosomal functions, some of which are implicated in the development of different types of tumors. As universally acknowledged, hepatocellular carcinoma (HCC) has been garnering global attention due to its complex pathogenesis and challenging treatments. In this review, we analyze the biological characteristics of RPs and emphasize their essential roles in HCC. In addition to regulating related signaling pathways such as the p53 pathway, RPs also act in proliferation and metastasis by influencing cell cycle, apoptosis, angiogenesis, and epithelial-to-mesenchymal transition in HCC. RPs are expected to unfold new possibilities for precise diagnosis and individualized treatment of HCC.

A computational analysis of the oncogenic and anti-tumor immunity role of P4HA3 in human cancers

Prolyl-4-hydroxylase subunit alpha3 (P4HA3) is a triple helical procollagen synthesis protein. The role of P4HA3 in cancer development is not well known and lacks comprehensive analyses among human cancers. This study aimed to investigate the relationship between P4HA3 expression and anti-tumor immunity and its prognostic value in pan-cancer. P4HA3 expression was analyzed from TIMER2.0, GTEx, GEPIA2.0 and TCGA databases. Genetic and DNA methylation alterations, survival analysis and proteins co-expression analysis of P4HA3 in cBio Cancer Genomics Portal, TCGA, GSCA and TIMER2.0. The correlation between P4HA3 expression and immune infiltration was analyzed by TIDE, XCELL, MCPCOUNTER, and EPIC. We performed EdU and transwell experiments to evaluate the influence of P4HA3 on the proliferation, migration and invasion abilities of different tumors. Patients derived xenograft (PDX) and subcutaneous transplantation models were utilized to explore the correlation between P4HA3 and immunotherapy response in triple-negative breast cancer (TNBC). Among 33 types of cancers, P4HA3 had generally different expression between different tumors, further analysis showed that the expression of P4HA3 was correlated with the cells infiltration of the tumor microenvironment (TME). The expression of P4HA3 was positively with the cell proliferation markers and epithelial-mesenchymal transition (EMT) markers. Moreover, P4HA3 deficiency inhibited the proliferation, migration and invasion abilities of tumor cells, and promoted anti-tumor immunotherapy of PD-1/PD-L1 inhibitor. This pan-cancer analysis of P4HA3 provides a comprehensive understanding of its oncogenic and prognosis role in different cancers, P4HA3 abnormal expression could be a useful biomarker for predicting the effectiveness of immunotherapy in cancer patients.

The cellular signaling and regulatory role of protein phosphatase in tumor diagnosis: Upstream miRNAs of PTEN

Protein phosphatases have demonstrated considerable promise in the realm of early tumor diagnosis across various malignancies. These enzymes play a critical role in modulating the PI3K-Akt signaling pathway, which is integral to cellular processes such as proliferation, survival, and migration. When the activity of protein phosphatases becomes abnormal, it can disrupt these essential signaling pathways, potentially leading to the initiation and progression of tumors. Consequently, monitoring for abnormal expression and activity levels of protein phosphatases could serve as a vital biomarker for early cancer detection. By identifying these alterations, clinicians may be better equipped to diagnose tumors at an earlier stage, significantly improving patient outcomes.In summary, our study highlights the multifaceted and significant role of PTEN in various forms of cancer, including esophageal squamous cell carcinoma (ESCA). Further analysis showed that the expression levels of protein phosphatase and PTEN protein were significantly associated with the early diagnosis of tumors, especially in the early stage of tumors, and their detection sensitivity and specificity were high. Therefore, by detecting the expression of protein phosphatase and PTEN protein, the early diagnosis of tumor can be achieved, and the therapeutic effect and prognosis of patients can be improved.

The pan-cancer landscape presented ITGA7 as a prognostic determinant, tumor suppressor, and oncogene in multiple tumor types

Integrin α7 (ITGA7) is an extracellular matrix-binding protein. Integrins are the main type of cell adhesive molecules in mammals, playing a role in many biological pathways. Although various studies have shown correlations between ITGA7 and various types of cancer, a comprehensive study at a pan-cancer level has not yet been conducted. In this study, we investigated the function of ITGA7 in distinct tumor types using the multi-omics relevant information, then two CeRNA regulatory network was drawn to identify the ITGA7 hub regulatory RNAs. The results indicated that the expression of ITGA7 varies in different tumors. Overexpression of ITGA7 was correlated with a worse OS in BLCA, LGG, and UVM, and the downregulation of ITGA7 was related to a worse OS in PAAD. In addition, BLCA, and UVM showed poor PFS in association with ITGA7 overexpression, and PAAD, SARC, and THCA indicated poor PFS in correlation with ITGA7 under expression. Further analyses of ITGA7 gene alteration data showed that ITGA7 amplifications may have an impact on Kidney Chromophobe prognosis. In 20 types of tumors, ITGA7 expression was linked to cancer-associated fibroblast infiltration. ITGA7 expression was linked to cancer-associated fibroblast infiltration. ITGA7-Related Gene Enrichment Analysis indicated that ITGA7 expression-correlated and functional binding genes were enriched in homotypic cell-cell adhesion, focal adhesion, and ECM-receptor interaction. This pan-cancer study found that abnormal expression of ITGA7 was correlated with poor prognosis and metastasis in different types of tumors. Thus, the ITGA7 gene may prove to be a promising biomarker for the prognosis and complication prevention of different cancers.

Exploring the role of ADAMTSL2 across multiple cancer types: A pan-cancer analysis and validated in colorectal cancer

BACKGROUND

Recent studies have established a correlation between ADAMTSL2 (ADAMTS-like 2) and the development of various cancers. This study aims to conduct a comprehensive pan-cancer analysis in 37 cancer types and investigate its potential role in colon and rectal adenocarcinoma (COADREAD).

METHOD

Pan-cancer and mutation data were sourced from The Cancer Genome Atlas (TCGA) database and analyzed using Sangerbox analysis platform. We explored the expression patterns and prognostic implications of ADAMTSL2, and investigated its relationships with tumor heterogeneity, stemness, immune checkpoint genes, immune cell infiltration, RNA modifications, and mutational profiles across different cancers. Additionally, with Ethics Committee approval, we conducted immunohistochemical (IHC) analysis on 120 COADEAD samples to evaluate ADAMTSL2 expression and its association with clinicopathological parameters.

RESULTS

ADAMTSL2 expression was positively correlated with the hazard ratio of OS, DSS, DFI and PFI for ESCA and COADREAD. A negative correlation was observed between ADAMTSL2 expression and NEO levels in COAD. Gene alterations in ADAMTSL2 were observed, with a mutation frequency of 5.0% in COAD. There is a significant correlation between ADAMTSL2 expression and immune cell infiltration in a variety of cancers. The expression level of ADAMTSL2 protein was associated with T stage, N stage, M stage (p < 0.05). Kaplan‒Meier survival curves demonstrated that the high ADAMTSL2 group had a shorter OS time (p = 0.047) and progression free survival time (p = 0.026) than the low ADAMTSL2 group.

CONCLUSION

In summary, we conducted a comprehensive pan-cancer analysis of ADAMTSL2 and we demonstrated that ADAMTSL2 may serve as a novel prognostic biomarker and immunotherapy target in COADREAD.

Pan-cancer analysis and experimental validation of FPR3 as a prognostic and immune infiltration-related biomarker for glioma

Formyl peptide receptor 3 (FPR3) is known to have implications in the progression of various cancer types. Despite this, its biological significance within pan-cancer datasets has yet to be investigated. In this investigation, we scrutinized FPR3's expression profiles, genetic alterations, prognostic significance, immune-related characteristics, methylation status, tumor mutation burden (TMB), and microsatellite instability (MSI) across different types of cancer. We utilized TISCH's single-cell data to identify immune cells closely associated with FPR3. The predictive significance of FPR3 was evaluated independently in gliomas using data from TCGA and CGGA datasets, leading to the development of a prognostic nomogram. Immunohistochemistry and Western blot analysis confirmed FPR3 expression in gliomas. Lastly, the CCK-8 and wound-healing assays were employed to assess the impact of FPR3 on the proliferation and metastasis of GBM cell lines. In numerous cancer types, heightened FPR3 expression correlated with adverse outcomes, immune cell infiltration, immune checkpoints, TMB, and MSI. In glioma, FPR3 emerged as a notable risk factor, with the prognostic model effectively forecasting patient results. The potential biological relevance of FPR3 was confirmed in glioma, and it was shown to have significant involvement in the processes of glioma growth, immune infiltration, and metastasis. Our results imply a potential association of FPR3 with tumor immunity, indicating its viability as a prognostic indicator in glioma.

KNSTRN Is a Prognostic Biomarker That Is Correlated with Immune Infiltration in Breast Cancer and Promotes Cell Cycle and Proliferation

Kinetochore-localized astrin/SPAG5-binding protein (KNSTRN) promotes the progression of bladder cancer and lung adenocarcinoma. However, its expression and biological function in breast cancer remain largely unknown. Therefore, this study aimed to analyze KNSTRN expression, prognoses, correlation with immune infiltration, expression-associated genes, and regulated signaling pathways to characterize its role in regulating the cell cycle using both bioinformatics and in vitro functional experiments. Analyses of The Cancer Genome Atlas, Gene Expression Omnibus, TIMER, and The Human Protein Atlas databases revealed a significant upregulation of KNSTRN transcript and protein levels in breast cancer. Kaplan-Meier survival analyses demonstrated a significant association between high expression of KNSTRN and poor overall survival, relapse-free survival, post-progression survival, and distant metastases-free survival in patients with breast cancer. Furthermore, multivariate Cox regression analyses confirmed that KNSTRN is an independent prognostic factor for breast cancer. Immune infiltration analysis indicated a positive correlation between KNSTRN expression and T regulatory cell infiltration while showing a negative correlation with Tgd and natural killer cell infiltration. Gene set enrichment analysis along with single-cell transcriptome data analysis suggested that KNSTRN promoted cell cycle progression by regulating the expression of key cell cycle proteins. The overexpression and silencing of KNSTRN in vitro, respectively, promoted and inhibited the proliferation of breast cancer cells. The overexpression of KNSTRN enhanced the expression of key cell cycle regulators, including CDK4, CDK6, and cyclin D3, thereby accelerating the G1/S phase transition and leading to aberrant proliferation of breast cancer cells. In conclusion, our study demonstrates that KNSTRN functions as an oncogene in breast cancer by regulating immune response, promoting G1/S transition, and facilitating breast cancer cell proliferation. Moreover, KNSTRN has potential as a molecular biomarker for diagnostic and prognostic prediction in breast cancer.

NFKBIE is a predictive factor of survival and is correlated with immune infiltration and antigen processing and presentation in hepatocellular carcinoma

The important role of the nuclear factor κB (NFκB) pathway in tumour development has long been recognized; however, the role of the NFκB inhibitor family in liver cancer has not been elucidated. Hepatocellular carcinoma (HCC) is a serious public health burden with a high incidence, poor prognosis, and early detection, especially in Asia, where hepatitis is prevalent. In the present study, the mRNA expression level of the NFκB inhibitor family was assessed in HCC and normal tissues using the Metabolic Gene Rapid Visualizer, University of Alabama at Birmingham Cancer Data Analysis Portal, and the Tumor Immune Estimation Resource database (TIMER). Survival curves of nuclear factor of κ light polypeptide gene enhancer in B-cells inhibitor (NFKBI)E were obtained using the Kaplan-Meier method. Genes co-expressed with NFKBIE in HCC samples were studied using data from the LinkedOmics and the Hepatocellular Carcinoma Databases. Protein-protein interaction networks, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment pathway analyses were used to assess the NFKBIE mechanism in HCC. Using the TIMER database, the association between immune infiltration and NFKBIE was determined. RNA-sequencing (RNA-seq) was used to evaluate the function of NFKBIE in HCC and its impact on proliferation and migration. Western blotting was used to confirm the expression of NFKBIE in HCC cell lines. In addition, NFKBIE overexpression in HCC was demonstrated using tissue microarrays encompassing 80 pairs of HCC and normal liver tissues. NFKBIE was the only NFκB inhibitor with high expression and an improved prognosis in HCC compared with other NFκB inhibitors. NFKBIE was correlated with clinical characteristics, such as tumour grade, tumour protein P53 mutation status and tumour stage. Data obtained from Gene Set Cancer Analysis suggested that NFKBIE may inhibit the PI3K/AKT, RAS/MAPK, RTK and TSC/mTOR pathways. In addition, NFKBIE was significantly associated with B-cell immune infiltration and the RNA-seq data demonstrated that knockdown of NFKBIE significantly affected 'Antigen processing and presentation' and 'hepatocellular carcinoma' pathways. Immunohistochemistry of microarrays of tissue samples revealed that NFKBIE was overexpressed in several stages of HCC. Finally, inhibition of NFKBIE decreased the proliferation and migration of HCC cells. In conclusion, due to its prognostic value and overexpression in HCC, NFKBIE distinguished itself from other NFκB inhibitors. As such, it may provide a novel prognostic indicator and immunotherapeutic target for HCC.

Bioinformatic Approaches for the Identification of Novel Tumor Suppressor Genes and Cancer Pathways in Renal Clear Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC, KIRC) is the most prevalent subtype of RCC, and even with different available therapies, the average progression-free survival is worse. Therefore, the identification of new molecular targets could be helpful for its therapeutic purposes.

Materials and Methods

We used the Cancer Genome Atlas to perform bioinformatic analyses for genes with possible tumor suppressor roles in KIRC.

Objective

This research aims to identify new prognostic biomarkers and potential therapeutic targets for this type of cancer.

Results

We identified 14 down-regulated genes in KIRC that had not previously been studied or poorly studied, with the majority of them impacted by increased promoter methylation. Eight genes showed shorter overall survival and worse prognosis, indicating their function as tumor suppressors, and six genes revealed good prognosis. From the 8 genes, C7ORF41 and CTXN3 revealed only downregulation in most cancers, proposing them as highly potential tumor suppressors. Among these 8 genes, the function of CTXN3 in cancers is unknown. Moreover, we identified the CWH43 gene as the major signature of KIRC. In addition, we found different genes as signatures of KIRC tumor stages and grades.

Conclusions

Our results may shed light on identifying KIRC pathogenesis and developing effective therapeutic targets for renal cancers, mainly KIRC.

A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome

Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.

Identification and Verification of Key Genes Associated with Temozolomide Resistance in Glioblastoma Based on Comprehensive Bioinformatics Analysis

Background

Glioblastoma (GBM) is the most aggressive form of brain cancer, with poor prognosis despite treatments like temozolomide (TMZ). Resistance to TMZ is a significant clinical challenge, and understanding the genes involved is crucial for developing new therapies and prognostic markers. This study aims to identify key genes associated with TMZ resistance in GBM, which could serve as valuable biomarkers for predicting patient outcomes and potential targets for treatment.

Objectives

This study aimed to identify genes involved in TMZ resistance in GBM and to assess the value of these genes in GBM treatment and prognosis evaluation.

Materials and Methods

Bioinformatics analysis of Gene Expression Omnibus (GEO) datasets (GSE113510 and GSE199689) and The Chinese Glioblastoma Genome Atlas (CGGA) database was performed to identify differentially expressed genes (DEGs) between GBM cell lines with and without TMZ resistance. Subsequently, the key modules associated with GBM patient prognosis were identified by weighted gene coexpression network analysis (WGCNA). Furthermore, hub genes related to TMZ resistance were accurately screened and confirmed using three machine learning algorithms. In addition, immune cell infiltration analysis, TF-miRNA coregulatory network analysis, drug sensitivity prediction, and gene set enrichment analysis (GSEA) were also performed for temozolomide resistance-specific genes. Finally, the expression levels of key genes were validated in our constructed TMZ-resistant cell lines by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting (WB).

Results

Integrated analysis of the GEO and CGGA datasets revealed 769 differentially expressed genes (DEGs), comprising 350 downregulated and 419 upregulated genes, between GBM patients and normal controls. Among these DEGs, three key genes, namely, PITX1, TNFRSF11B, and IGFBP2, exhibited significant differences in expression between groups and were prioritized via machine learning algorithms. The expression levels of these genes were found to be closely related to adverse clinical features and immune cell infiltration levels in GBM patients. These genes were also found to participate in several biological pathways and processes. RT‒qPCR and WB confirmed the differential expression of these genes in vitro, indicating that they play vital roles in GBM patients with TMZ resistance.

Conclusions

PITX1, TNFRSF11B, and IGFBP2 are key genes associated with the prognosis of GBM patients with TMZ resistance. The differential expression of these genes correlates with adverse outcomes in GBM patients, suggesting that they are valuable biomarkers for predicting patient prognosis and that they could serve as diagnostic biomarkers or treatment targets.

Exploring the prognostic and therapeutic value of HIF1A in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains a challenge within the realm of non-small cell lung cancer (NSCLC), demanding innovative diagnostic and therapeutic solutions. In this study, we systematically detected the correlation between the expression of hypoxia-induced factor 1A (HIF1A) and the clinical characteristics of LUAD, alongside lung squamous cell carcinoma (LUSC). Our bioinformatic analysis reveals that HIF1A mRNA expression is significantly upregulated in both LUAD and LUSC samples compared to non-tumorous lung tissues. The overexpression is positively correlated with increased copy number variation and negatively associated with promoter methylation. However, meta-analysis and survival analyses revealed a pronounced association between elevated HIF1A expression and poor clinical outcome specifically within the LUAD subset, with no such correlation evident in LUSC. Additionally, we explored the interplay between HIF1A expression, leukocyte infiltration, and the presence of immunosuppressive markers, revealing HIF1A's suppressive role in cytotoxicity against cancer cells. Furthermore, we performed in silico prediction to explore the correlations between HIF1A and its interacting proteins, associated pathways, glycolysis, and m6A modification, and the feasibility of targeting HIF1A with specific drugs. In summary, our study revealed the prognostic significance and therapeutic potential of HIF1A in LUAD.

Novel Oncogenic Value of C10orf90 in Colon Cancer Identified as a Clinical Diagnostic and Prognostic Marker

C10orf90, a tumor suppressor, can inhibit the occurrence and development of tumors. Therefore, we investigated the gene function of C10orf90 in various tumors using multiple pan-cancer datasets. Pan-cancer analysis results reveal that the expression levels of C10orf90 vary across different tumors and hold significant value in the clinical diagnosis and prognosis of patients with various tumors. In some cancers, the expression level of C10orf90 is correlated with CNV, DNA methylation, immune subtypes, immune cell infiltration, and drug sensitivity in the tumors. In particular, in COAD, the C10orf90 gene is implicated in multiple processes associated with COAD. Cell experiments demonstrate that C10orf90 suppresses the proliferation and migration of colon cancer cells while promoting apoptosis. In summary, C10orf90 plays a role in the onset and progression of various cancers and could potentially serve as an effective diagnostic and prognostic marker for cancer patients. Notably, in COAD, C10orf90 inhibits the proliferation and migration of colon cancer cells, induces apoptosis, and is linked to the advancement of colon cancer.

Actin like 6A is a prognostic biomarker and associated with immune cell infiltration in cancers

PURPOSE

To investigate the role of Actin like 6 A (ACTL6A) in cancer and explore the potential mechanism of its function.

METHODS

Differential expression of ACTL6A was analyzed using Oncomine and TIMER database. Then, we downloaded data sets from TCGA database. The correlation between ACTL6A expression and survival in pan-cancer were analyzed by "survival", "survminer" R package and PrognoScan database. STRING (v 11.0) and stringAPP for Cytoscape v3.7.2 were used to predict ACTL6A associated genes. Copy number and methylation alterations of ACTL6A were analyzed using cBioPortal and GSCALite. Transcription factors were downloaded from The Human Transcription Factors Database and analyzed using "limma" R package, JASPAR and PROMO database. Correlations analysis between ACTL6A and immune cells were performed using TIMER and GEPIA database.

RESULTS

In our studies, we found that ACTL6A was widely upregulated in cancers, which might be attributed to its gene amplifications. Moreover, ACTL6A might regulated by transcription factors (TFs), including E2F1, YY1, CDX2 and HOXD10. In addition, high ACTL6A expression was associated with poor prognosis in most cancers. Meanwhile, ACTL6A was associated with the infiltration of immune cells, especially in liver hepatocellular carcinoma and brain lower grade glioma.

CONCLUSION

Amplification of ACTL6A is correlated with poor prognosis and contribute to immune cells infiltration in LIHC and LGG, which may provide immune-related therapeutic targets to guide clinical strategies.

SSCI: Self-Supervised Deep Learning Improves Network Structure for Cancer Driver Gene Identification

The pathogenesis of cancer is complex, involving abnormalities in some genes in organisms. Accurately identifying cancer genes is crucial for the early detection of cancer and personalized treatment, among other applications. Recent studies have used graph deep learning methods to identify cancer driver genes based on biological networks. However, incompleteness and the noise of the networks will weaken the performance of models. To address this, we propose a cancer driver gene identification method based on self-supervision for graph convolutional networks, which can efficiently enhance the structure of the network and further improve predictive accuracy. The reliability of SSCI is verified by the area under the receiver operating characteristic curves (AUROC), the area under the precision-recall curves (AUPRC), and the F1 score, with respective values of 0.966, 0.964, and 0.913. The results show that our method can identify cancer driver genes with strong discriminative power and biological interpretability.

Identification of the shared gene MXD3 signatures and biological mechanism in patients with hip pain and prostate cancer

Prostate cancer (PRAD) is recognized as having a significant effect on systemic illnesses. This study examined possible immune cells, metabolic pathways, and genes that may explain the interaction between PRAD and hip pain. We used information retrieved from the Cancer Genome Atlas and the Gene Expression Omnibus databases. To find common genes, we utilized differential expression analysis and weighted gene co-expression network analysis. The genes that were shared were subjected to pathway enrichment studies using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Additionally, hub genes were analyzed using LASSO regression, and a receiver operating characteristic curve was generated based on the screening outcomes. The genes for the nodes were chosen in a protein-protein interaction network that was built. Single-sample gene-set enrichment analysis was performed to identify the differentially expressed genes. Immunohistochemistry staining confirmed hub gene expression, and single-sample gene-set enrichment analysis assessed immune cell infiltration. We concluded by comparing MAX dimerization protein 3 (MXD3) and MAX interactor 1 (MXI1) expression in tumor tissues using Uniform Manifold Approximation and Projection and violin plots in the Tumor lmmune Single-cell Hub database. After analyzing the intersection of the differentially expressed genes and weighted gene co-expression network analysis-significant module genes, we determined that MXD3 was the best shared diagnostic biomarker for PRAD and hip pain. One potential predictor of PRAD development was the MXI1 node gene, which was found in the protein-protein interaction network. The analyses revealed that MXD3 had a relatively positive correlation with neutrophil and T-helper cell infiltration levels, whereas MXI1 had a negative correlation with mast and Tgd cell levels. Tumors had lower levels of MXI1 expression and higher levels of MXD3 expression compared to normal tissues. Endothelial cells, induced pluripotent stem cells, and smooth muscle cells were all found to express MXI1. This is the first study to investigate the close genetic link between hip pain and PRAD using bioinformatics technologies. The 2 most significant genes involved in crosstalk between PRAD and hip pain were MXD3 and MXI1. The immunological responses triggered by T cells, mast cells, and neutrophils may be crucial in the relationship between PRAD and hip pain.

A triple hormone receptor ER, AR, and VDR signature is a robust prognosis predictor in breast cancer

BACKGROUND

Despite evidence indicating the dominance of cell-of-origin signatures in molecular tumor patterns, translating these genome-wide patterns into actionable insights has been challenging. This study introduces breast cancer cell-of-origin signatures that offer significant prognostic value across all breast cancer subtypes and various clinical cohorts, compared to previously developed genomic signatures.

METHODS

We previously reported that triple hormone receptor (THR) co-expression patterns of androgen (AR), estrogen (ER), and vitamin D (VDR) receptors are maintained at the protein level in human breast cancers. Here, we developed corresponding mRNA signatures (THR-50 and THR-70) based on these patterns to categorize breast tumors by their THR expression levels. The THR mRNA signatures were evaluated across 56 breast cancer datasets (5040 patients) using Kaplan-Meier survival analysis, Cox proportional hazard regression, and unsupervised clustering.

RESULTS

The THR signatures effectively predict both overall and progression-free survival across all evaluated datasets, independent of subtype, grade, or treatment status, suggesting improvement over existing prognostic signatures. Furthermore, they delineate three distinct ER-positive breast cancer subtypes with significant survival in differences-expanding on the conventional two subtypes. Additionally, coupling THR-70 with an immune signature identifies a predominantly ER-negative breast cancer subgroup with a highly favorable prognosis, comparable to ER-positive cases, as well as an ER-negative subgroup with notably poor outcome, characterized by a 15-fold shorter survival.

CONCLUSIONS

The THR cell-of-origin signature introduces a novel dimension to breast cancer biology, potentially serving as a robust foundation for integrating additional prognostic biomarkers. These signatures offer utility as a prognostic index for stratifying existing breast cancer subtypes and for de novo classification of breast cancer cases. Moreover, THR signatures may also hold promise in predicting hormone treatment responses targeting AR and/or VDR.

Pan-cancer analysis of m1A writer gene RRP8: implications for immune infiltration and prognosis in human cancers

BACKGROUND

Ribosomal RNA Processing 8 (RRP8) is a gene associated with RNA modification and has been implicated in the development of several types of tumors in recent research. Nevertheless, the biological importance of RRP8 in pan-cancer has not yet been thoroughly and comprehensively investigated.

METHODS

In this study, we conducted an analysis of various public databases to investigate the biological functions of RRP8. Our analysis included examining its correlation with pan-cancer prognosis, heterogeneity, stemness, immune checkpoint genes, and immune cell infiltration. Furthermore, we utilized the GDSC and CTRP databases to assess the sensitivity of RRP8 to small molecule drugs.

RESULTS

Our findings indicate that RRP8 exhibits differential expression between tumor and normal samples, particularly impacting the prognosis of various cancers such as Adrenocortical carcinoma (ACC) and Kidney Chromophobe (KICH). The expression of RRP8 is intricately linked to tumor heterogeneity and stemness markers. Additionally, RRP8 shows a positive correlation with the presence of tumor-infiltrating cells, with TP53 being the predominant mutated gene in these malignancies.

CONCLUSION

Our findings suggest that RRP8 may serve as a potential prognostic marker and therapeutic target in a variety of cancer types.

Identification of two heterogeneous subtypes of hepatocellular carcinoma with distinct pathway activities and clinical outcomes based on gene set variation analysis

Background

High heterogeneity is an essential feature of malignant tumors. This study aims to reveal the drivers of hepatocellular carcinoma heterogeneity for prognostic stratification and to guide individualized treatment.

Methods

Omics data and clinical data for two HCC cohorts were derived from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Atlas (ICGC), respectively. CNV data and methylation data were downloaded from the GSCA database. GSVA was used to estimate the transcriptional activity of KEGG pathways, and consensus clustering was used to categorize the HCC samples. The pRRophetic package was used to predict the sensitivity of samples to anticancer drugs. TIMER, MCPcounter, quanTIseq, and TIDE algorithms were used to assess the components of TME. LASSO and COX analyses were used to establish a prognostic gene signature. The biological role played by genes in HCC cells was confirmed by in vitro experiments.

Results

We classified HCC tissues into two categories based on the activity of prognostic pathways. Among them, the transcriptional profile of cluster A HCC is similar to that of normal tissue, dominated by cancer-suppressive metabolic pathways, and has a better prognosis. In contrast, cluster B HCC is dominated by high proliferative activity and has significant genetic heterogeneity. Meanwhile, cluster B HCC is often poorly differentiated, has a high rate of serum AFP positivity, is prone to microvascular invasion, and has shorter overall survival. In addition, we found that mutations, copy number variations, and aberrant methylation were also crucial drivers of the differences in heterogeneity between the two HCC subtypes. Meanwhile, the TME of the two HCC subtypes is also significantly different, which offers the possibility of precision immunotherapy for HCC patients. Finally, based on the prognostic value of molecular subtypes, we developed a gene signature that could accurately predict patients' OS. The riskscore quantified by the signature could evaluate the heterogeneity of HCC and guide clinical treatment. Finally, we confirmed through in vitro experiments that RFPL4B could promote the progression of Huh7 cells.

Conclusion

The molecular subtypes we identified effectively exposed the heterogeneity of HCC, which is important for discovering new effective therapeutic targets.

FAM109B plays a tumorigenic role in low-grade gliomas and is associated with tumor-associated macrophages (TAMs)

BACKGROUND

Family with sequence similarity 109, member B (FAM109B) is involved in endocytic transport and affects genetic variation in brain methylation. It is one of the important genes related to immune cell-associated diseases. In the tumor immune system, methylation can regulate tumor immunity and influence the maturation and functional response of immune cells. Whether FAM109B is involved in tumor progression and its correlation with the tumor immune microenvironment has not yet been disclosed.

METHODS

A comprehensive pan-cancer analysis of FAM109B expression, prognosis, immunity, and TMB was conducted. The expression, clinical features, and prognostic value of FAM109B in low-grade gliomas (LGG) were evaluated using TCGA, CGGA, and Gravendeel databases. The expression of FAM109B was validated by qRT-PCR, immunohistochemistry (IHC), and Western blotting (WB). The relationship between FAM109B and methylation, Copy Number Variation (CNV), prognosis, immune checkpoints (ICs), and common chemotherapy drug sensitivity in LGG was explored through Cox regression, Kaplan-Meier curves, and Spearman correlation analysis. FAM109B levels and their distribution were studied using the TIMER database and single-cell analysis. The potential role of FAM109B in gliomas was further investigated through in vitro and in vivo experiments.

RESULTS

FAM109B was significantly elevated in various tumor types and was associated with poor prognosis. Its expression was related to aggressive progression and poor prognosis in low-grade glioma patients, serving as an independent prognostic marker for LGG. Glioma grade was negatively correlated with FAM109B DNA promoter methylation. Immune infiltration and single-cell analysis showed significant expression of FAM109B in tumor-associated macrophages (TAMs). The expression of FAM109B was closely related to gene mutations, immune checkpoints (ICs), and chemotherapy drugs in LGG. In vitro studies showed increased FAM109B expression in LGG, closely related to cell proliferation. In vivo studies showed that mice in the sh-FAM109B group had slower tumor growth, slower weight loss, and longer survival times.

CONCLUSIONS

FAM109B, as a novel prognostic biomarker for low-grade gliomas, exhibits specific overexpression in TAMs and may be a potential therapeutic target for LGG patients.

Bioinformatics tools and resources for cancer and application

ABSTRACT

Tumor bioinformatics plays an important role in cancer research and precision medicine. The primary focus of traditional cancer research has been molecular and clinical studies of a number of fundamental pathways and genes. In recent years, driven by breakthroughs in high-throughput technologies, large-scale cancer omics data have accumulated rapidly. How to effectively utilize and share these data is particularly important. To address this crucial task, many computational tools and databases have been developed over the past few years. To help researchers quickly learn and understand the functions of these tools, in this review, we summarize publicly available bioinformatics tools and resources for pan-cancer multi-omics analysis, regulatory analysis of tumorigenesis, tumor treatment and prognosis, immune infiltration analysis, immune repertoire analysis, cancer driver gene and driver mutation analysis, and cancer single-cell analysis, which may further help researchers find more suitable tools for their research.

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

TIMM9 as a prognostic biomarker in multiple cancers and its associated biological processes

TIMM9 has been identified as a mediator of essential functions in mitochondria, but its association with pan-cancer is poorly understood. We herein employed bioinformatics, computational chemistry techniques and experiments to investigate the role of TIMM9 in pan-cancer. Our analysis revealed that overexpression of TIMM9 was significantly associated with tumorigenesis, pathological stage progression, and metastasis. Missense mutations (particularly the S49L variant), copy number variations (CNV) and methylation alterations in TIMM9 were found to be associated with poor cancer prognosis. Moreover, TIMM9 was positively related with cell cycle progression, mitochondrial and ribosomal function, oxidative phosphorylation, TCA cycle activity, innate and adaptive immunity. Additionally, we discovered that TIMM9 could be regulated by cancer-associated signaling pathways, such as the mTOR pathway. Using molecular simulations, we identified ITFG1 as the protein that has the strongest physical association with TIMM9, which show a promising structural complement.

DCS, a novel classifier system based on disulfidptosis reveals tumor microenvironment heterogeneity and guides frontline therapy for clear cell renal carcinoma

Background

Emerging evidence suggests that cell deaths are involved in tumorigenesis and progression, which may be treated as a novel direction of cancers. Recently, a novel type of programmed cell death, disulfidptosis, was discovered. However, the detailed biological and clinical impact of disulfidptosis and related regulators remains largely unknown.

Methods

In this work, we first enrolled pancancer datasets and performed multi-omics analysis, including gene expression, DNA methylation, copy number variation and single nucleic variation profiles. Then we deciphered the biological implication of disulfidptosis in clear cell renal cell carcinoma (ccRCC) by machine learning. Finally, a novel agent targeting at disulfidptosis in ccRCC was identified and verified.

Results

We found that disulfidptosis regulators were dysregulated among cancers, which could be explained by aberrant DNA methylation and genomic mutation events. Disulfidptosis scores were depressed among cancers and negatively correlated with epithelial mesenchymal transition. Disulfidptosis regulators could satisfactorily stratify risk subgroups in ccRCC, and a novel subtype, DCS3, owning with disulfidptosis depression, insensitivity to immune therapy and aberrant genome instability were identified and verified. Moreover, treating DCS3 with NU1025 could significantly inhibit ccRCC malignancy.

Conclusion

This work provided a better understanding of disulfidptosis in cancers and new insights into individual management based on disulfidptosis.

Identification of prognostic biomarkers for cholangiocarcinoma by combined analysis of molecular characteristics of clinical MVI subtypes and molecular subtypes

Cholangiocarcinoma (CCA) is widely noted for its high degree of malignancy, rapid progression, and limited therapeutic options. This study was carried out on transcriptome data of 417 CCA samples from different anatomical locations. The effects of lipid metabolism related genes and immune related genes as CCA classifiers were compared. Key genes were derived from MVI subtypes and better molecular subtypes. Pathways such as epithelial mesenchymal transition (EMT) and cell cycle were significantly activated in MVI-positive group. CCA patients were classified into three (four) subtypes based on lipid metabolism (immune) related genes, with better prognosis observed in lipid metabolism-C1, immune-C2, and immune-C4. IPTW analysis found that the prognosis of lipid metabolism-C1 was significantly better than that of lipid metabolism-C2 + C3 before and after correction. KRT16 was finally selected as the key gene. And knockdown of KRT16 inhibited proliferation, migration and invasion of CCA cells.

Clinical significance of LIN28A gene polymorphisms and expression in pan-cancer: a meta-analysis and bioinformatic analysis

Several studies have reported the relationship between LIN28A gene polymorphisms (rs3811463 T > C and rs34787247 G > A) and cancer susceptibility, but the results are inconsistent and need further clarification. The current study aimed to evaluate their relationship and also to explore the relationship between LIN28A gene expression and immune infiltration, tumor stage, survival prognosis, and drug sensitivity in pan-cancer. The meta-analysis and data mining were completed by STATA software and the GSCA platform, respectively. The meta-analysis showed that the rs3811463 polymorphism was not associated with cancer susceptibility, while the rs34787247 polymorphism was associated with cancer susceptibility in the Chinese population [AA vs. GG: Odd Ratio (OR)=1.98, 95% Confidence Interval (CI)=1.35-2.89, PZ<0.001; GA vs. GG: OR = 1.17, 95%CI= 1.01-1.36, PZ=0.04; (AA + GA) vs. GG: OR = 1.24, 95%CI = 1.07-1.43, PZ=0.004; AA vs. (GA + GG): OR = 1.90, 95%CI = 1.30- 2.78, PZ=0.001; A vs. G: OR = 1.27, 95%CI = 1.12-1.44, PZ<0.001]. LIN28A gene expression was associated not only with immune infiltration, pathological stage, and survival prognosis of certain cancers, but also with sensitivity to multiple anticancer drugs, such as cisplatin, pazopanib, olaparib, and selumetinib. In conclusion, the current study suggested that the rs34787247 G > A polymorphism might be used as a cancer risk marker in the Chinese population, and LIN28A might serve as a prognostic marker and therapeutic target for certain cancers.

Sevoflurane inhibits lung cancer development by promoting FUS1 transcription via downregulating IRF6

Lung cancer is a major contributor to cancer deaths worldwide and is on the rise. Although surgical resection has been widely used as a standard therapy for lung cancer patients, the relapse rate after surgery is high. It is still unclear whether there is a potential drug that can reduce the probability of postsurgical recurrence in lung cancer patients. We used 5 typical lung cancer cell lines as well as 41 lung cancer tissue samples and paracancer tissue samples to investigate the expression levels of interferon regulatory factor 6 (IRF6) and tumor suppressor candidate 2 (TUSC2, also known as FUS1). We also treated lung cancer cells (H322 and A549) with different concentrations of sevoflurane to study its influence on lung cancer cell tumorigenesis. Lentivirus-mediated gain-of-function studies of IRF6 and FUS1 were applied to validate the role of IRF6 and FUS1 in lung cancer. Next, we used short hairpin RNA-mediated loss of function of IRF6 and luciferase, chromatin immunoprecipitation assays to validate the regulatory role of IRF6 on FUS1. Our findings reported that IRF6 was upregulated in lung cancer tissues, while FUS1 was downregulated. Functional assays revealed that sevoflurane inhibits lung cancer development by downregulating IRF6 expression. Luciferase and chromatin immunoprecipitation-quantitative real-time PCR assays uncovered that IRF6 represses FUS1 transcriptional expression in lung cancer cells. We have shown that sevoflurane prevents lung cancer development by downregulating IRF6 to stimulate FUS1 transcription, indicating that sevoflurane can be used as the potential anesthetic drug in surgical resection to reduce postoperative tumor relapse in lung cancer patients.

Pan-cancer analysis and single-cell analysis reveals FAM110B as a potential target for survival and immunotherapy

Background: FAM110B belongs to the family that has a 110 sequence similarity (FAM110) and is located in the centrosome and mitotic spindle. FAM110B has been linked to tumor cell growth in earlier research. Uncertainty exists regarding FAM110B's function within the tumor microenvironment is unclear as well as pan-cancer. Methods: In order to assess the variation in FAM110B expression within normal and pan-cancer tissues, we combined the TCGA and GTEx databases. The cBioPortal database and the GSCALite platform were used to examine the variation in genome and methylation alteration of FAM110B. Cox regression, Kaplan-Meier, and SangerBox were employed to examine the clinical features and prognosis of FAM110B and pan-cancer. The purpose of the correlational research was to investigate the associations within immunerelated genes, tumor mutation burden, microsatellite instability, immune-related genes, and immunological checkpoints and FAM110B expression. ESTIMATE, EPIC, QUANTISEQ, and MCPCOUNTER methods were used to calculate the interaction among FAM110B expression as well as the tumor immune microenvironment. The immunoinfiltration and function of FAM110B were analyzed by single-cell databases (TISCH and CancerSEA). Finally, we evaluated the sensitivity of FAM110B to small-molecule medications through GDSC and CTRP databases. Results: The transcription and protein expression of FAM110B varies significantly throughout cancer types, and this has predictive value for the prognosis of some tumors; including brain lower grade glioma (LGG), stomach adenocarcinoma (STAD), pancreatic adenocarcinoma (PAAD), etc. In the tumor microenvironment, the expression level of FAM110B was associated with immune cell infiltration, immune checkpoint immune regulatory genes, tumor mutational burden, and microsatellite fragility to a certain extent. Conclusion: This work investigates the possibility of utility of FAM110B as a marker to forecast pan-cancer immunotherapy response, providing a theoretical basis for cancer therapy.