Correlation between prognostic indicator AHNAK2 and immune infiltrates in lung adenocarcinoma

Comprehensive analysis indicates DDX46 as a novel biomarker for the prognosis of lung adenocarcinoma

The expression levels of DEAD-box 46 (DDX46) are elevated in several malignancies; however, the function of DDX46 in lung adenocarcinoma (LUAD), including its expression patterns and functional implications, has not been fully elucidated. The present study primarily explores the potential role and underlying mechanism of DDX46 in the malignant progression of LUAD. The present study analyzed both publicly available databases and clinical specimens to assess DDX46 expression in LUAD and explore its prognostic significance. The findings demonstrated that elevated DDX46 expression was associated with a worse prognosis in patients with LUAD in comparison with a low DDX46 expression. Functional assays, including Cell Counting Kit-8, colony formation, 5-ethynyl-2'-deoxyuridine incorporation, flow cytometry, wound healing and Transwell assays, indicated that silencing DDX46 suppressed cancer cell migration, enhanced apoptosis, and induced G0/G1 phase cell cycle arrest. Moreover, DDX46 expression was correlated with the infiltration of T cells, natural killer cells and monocytes, as well as with several immune checkpoints and chemokines. Additionally, the results identified a marked association between DDX46 and the Wnt signaling pathway in LUAD. Low DDX46 expression was also demonstrated to be associated with increased drug responsiveness in patients. In conclusion, DDX46 holds promise as a dual-purpose marker for the diagnosis and therapy of patients with LUAD.

Hydrazone copper(II) complexes suppressed lung adenocarcinoma by activating multiple anticancer pathway

Activating multiple anti-cancer pathways has great potential for tumor treatment. Herein, we synthesized two binuclear Cu(II) hydrazone complexes ([Cu2(HL1)2Cl2] 1 and [Cu2(HL1)2Br2] 2) and two mononuclear hydrazone-Cu(II) complexes ([Cu(HL2)Cl]·CH3OH 3 and [Cu(HL2)(H2O)Br]·2H2O 4), to evaluate their anti-lung cancer activities. MTT assays revealed that the Cu(II) complexes demonstrate superior anticancer activity compared to cisplatin. Among them, complex 3 exhibited selective toxicity towards A549 cancer cells in comparison to normal cells and demonstrated hemolytic activity comparable to cisplatin. The low toxicity and effective antitumor capabilities of complex 3 have been confirmed in xenograft experiments using A549 tumor-bearing mice. Interestingly, complex 3 eradicates lung tumor cells both in vivo and in vitro by initiating multiple anticancer pathways, including cuproptosis. Our research extends the study of hydrazone copper complexes and provides strategies for the treatment of lung cancer.

Identification of a Novel Signature Based on Ferritinophagy-Related Genes to Predict Prognosis in Lung Adenocarcinoma: Focus on AHNAK2

BACKGROUND

Lung adenocarcinoma (LUAD) accounts for over 40% of all non-small cell lung cancer (NSCLC) cases and continues to be difficult to treat despite advancements in diagnostics and therapies. Ferritinophagy, a newly recognized autophagy process linked to ferroptosis, has been associated with LUAD development. Recent studies have shown a dysregulation of genes related to ferritinophagy in LUAD, indicating its potential as a therapeutic target.

METHODS

We constructed a predictive model using seven genes associated with ferritinophagy. The model's accuracy was evaluated across three independent gene expression datasets. We analyzed the biological functions, immune environment, mutations, and drug sensitivities in groups with high and low risk. Utilizing a single-cell sequencing (scRNA-seq) dataset, we confirmed the expression of the model genes and identified a subtype of epithelial cells expressing AHNAK2. We further investigated the impact of the ferritinophagy-related gene AHNAK2 on LUAD cell proliferation, invasion, migration, and ferroptosis in vitro.

RESULTS

Our prediction model, comprising seven genes (AHNAK2, ARNTL2, CD27, LTB, SLC15A1, SLC2A1, and SYT1), has shown potential in predicting the prognosis of individuals diagnosed with LUAD. Notably, AHNAK2 impedes ferroptosis, promoting LUAD progression in vitro.

CONCLUSIONS

Our research suggests that ferritinophagy-associated genes are promising prognostic markers for LUAD and lay the groundwork for further exploration of ferritinophagy's role in LUAD. Furthermore, we present AHNAK2 as a novel regulator of ferroptosis, which requires further investigation to understand its mechanism.

The Novel-B-Cell-Related Gene Signature Predicts the Prognosis and Immune Status of Patients with Esophageal Carcinoma

BACKGROUND

The current understanding of the prognostic significance of B cells and their role in the tumor microenvironment (TME) in esophageal carcinoma (ESCA) is limited.

METHODS

We conducted a screening for B-cell-related genes through the analysis of single-cell transcriptome data. Subsequently, we developed a B-cell-related gene signature (BRGrisk) using LASSO regression analysis. Patients from The Cancer Genome Atlas cohort were divided into a training cohort and a test cohort. Patients were categorized into high- and low-risk groups based on their median BRGrisk scores. The overall survival was assessed using the Kaplan-Meier method, and a nomogram based on BRGrisk was constructed. Immune infiltration profiles between the risk groups were also compared.

RESULTS

The BRGrisk prognostic model indicated significantly worse outcomes for patients with high BRGrisk scores (p < 0.001). The BRGrisk-based nomogram exhibited good prognostic performance. Analysis of immune infiltration revealed that patients in the high-BRGrisk group had notably higher levels of immune cell infiltration and were more likely to be in an immunoresponsive state. Enrichment analysis showed a strong correlation between the prognostic gene signature and cancer-related pathways. IC50 results indicated that patients in the low-BRGrisk group were more responsive to common drugs compared to those in the high-BRGrisk group.

CONCLUSIONS

This study presents a novel BRGrisk that can be used to stratify the prognosis of ESCA patients and may offer guidance for personalized treatment strategies aimed at improving prognosis.

Gene Expression Profiles of AHNAK2, DCSTAMP, FN1, and TERT Correlate With Mutational Status and Recurrence in Papillary Thyroid Carcinoma

Papillary thyroid carcinoma (PTC), the most common malignancy of follicular cell derivation, is generally associated with good prognosis. Nevertheless, it is important to identify patients with aggressive PTCs and unfavorable outcome. Molecular markers such as BRAFV600E mutation and TERT promoter mutations have been proposed for risk stratification. While TERT promoter mutations have been frequently associated with aggressive PTCs, the association of BRAFV600E mutation with increased recurrence and mortality is less clear and has been controversially discussed. The aim of the present study was to analyze whether differentially expressed genes can predict BRAFV600E mutations as well as TERT promoter mutations in PTCs. RNA sequencing identified a large number of differentially expressed genes between BRAFV600E and BRAFwildtype PTCs. Of those, AHNAK2, DCSTAMP, and FN1 could be confirmed in a larger cohort (n = 91) to be significantly upregulated in BRAFV600E mutant PTCs using quantitative RT-PCR. Moreover, individual PTC expression values of DCSTAMP and FN1 were able to predict the BRAFV600E mutation status with high sensitivity and specificity. The expression of TERT was detected in all PTCs harboring TERT promoter mutations and in 19% of PTCs without TERT promoter mutations. Tumors with both TERT expression and TERT promoter mutations were particularly associated with aggressive clinicopathological features and a shorter recurrence-free survival. Altogether, it will be interesting to explore the biological function of AHNAK2, DCSTAMP, and FN1 in PTC in more detail. The analysis of their expression patterns could allow the characterization of PTC subtypes and thus enabling a more individualized surgical and medical treatment.

Genomic alterations in oral multiple primary cancers

Oral squamous cell carcinoma (OSCC) is the predominant type of oral cancer, while some patients may develop oral multiple primary cancers (MPCs) with unclear etiology. This study aimed to investigate the clinicopathological characteristics and genomic alterations of oral MPCs. Clinicopathological data from patients with oral single primary carcinoma (SPC, n = 202) and oral MPCs (n = 34) were collected and compared. Copy number alteration (CNA) analysis was conducted to identify chromosomal-instability differences among oral MPCs, recurrent OSCC cases, and OSCC patients with lymph node metastasis. Whole-exome sequencing was employed to identify potential unique gene mutations in oral MPCs patients. Additionally, CNA and phylogenetic tree analyses were used to gain preliminary insights into the molecular characteristics of different primary tumors within individual patients. Our findings revealed that, in contrast to oral SPC, females predominated the oral MPCs (70.59%), while smoking and alcohol use were not frequent in MPCs. Moreover, long-term survival outcomes were poorer in oral MPCs. From a CNA perspective, no significant differences were observed between oral MPCs patients and those with recurrence and lymph node metastasis. In addition to commonly mutated genes such as CASP8, TP53 and MUC16, in oral MPCs we also detected relatively rare mutations, such as HS3ST6 and RFPL4A. Furthermore, this study also demonstrated that most MPCs patients exhibited similarities in certain genomic regions within individuals, and distinct differences of the similarity degree were observed between synchronous and metachronous oral MPCs.

BLCA prognostic model creation and validation based on immune gene-metabolic gene combination

BACKGROUND

Bladder cancer (BLCA) is a prevalent urinary system malignancy. Understanding the interplay of immunological and metabolic genes in BLCA is crucial for prognosis and treatment.

METHODS

Immune/metabolism genes were extracted, their expression profiles analyzed. NMF clustering found prognostic genes. Immunocyte infiltration and tumor microenvironment were examined. Risk prognostic signature using Cox/LASSO methods was developed. Immunological Microenvironment and functional enrichment analysis explored. Immunotherapy response and somatic mutations evaluated. RT-qPCR validated gene expression.

RESULTS

We investigated these genes in 614 BLCA samples, identifying relevant prognostic genes. We developed a predictive feature and signature comprising 7 genes (POLE2, AHNAK, SHMT2, NR2F1, TFRC, OAS1, CHKB). This immune and metabolism-related gene (IMRG) signature showed superior predictive performance across multiple datasets and was independent of clinical indicators. Immunotherapy response and immune cell infiltration correlated with the risk score. Functional enrichment analysis revealed distinct biological pathways between low- and high-risk groups. The signature demonstrated higher prediction accuracy than other signatures. qRT-PCR confirmed differential gene expression and immunotherapy response.

CONCLUSIONS

The model in our work is a novel assessment tool to measure immunotherapy's effectiveness and anticipate BLCA patients' prognosis, offering new avenues for immunological biomarkers and targeted treatments.

Genomic analysis and filtration of novel prognostic biomarkers based on metabolic and immune subtypes in pancreatic cancer

PURPOSE

Patients with pancreatic cancer (PC) can be classified into various molecular subtypes and benefit from some precise therapy. Nevertheless, the interaction between metabolic and immune subtypes in the tumor microenvironment (TME) remains unknown. We hope to identify molecular subtypes related to metabolism and immunity in pancreatic cancer METHODS: Unsupervised consensus clustering and ssGSEA analysis were utilized to construct molecular subtypes related to metabolism and immunity. Diverse metabolic and immune subtypes were characterized by distinct prognoses and TME. Afterward, we filtrated the overlapped genes based on the differentially expressed genes (DEGs) between the metabolic and immune subtypes by lasso regression and Cox regression, and used them to build risk score signature which led to PC patients was categorized into high- and low-risk groups. Nomogram were built to predict the survival rates of each PC patient. RT-PCR, in vitro cell proliferation assay, PC organoid, immunohistochemistry staining were used to identify key oncogenes related to PC RESULTS: High-risk patients have a better response for various chemotherapeutic drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. We built a nomogram with the risk group, age, and the number of positive lymph nodes to predict the survival rates of each PC patient with average 1-year, 2-year, and 3-year areas under the curve (AUCs) equal to 0.792, 0.752, and 0.751. FAM83A, KLF5, LIPH, MYEOV were up-regulated in the PC cell line and PC tissues. Knockdown of FAM83A, KLF5, LIPH, MYEOV could reduce the proliferation in the PC cell line and PC organoids CONCLUSION: The risk score signature based on the metabolism and immune molecular subtypes can accurately predict the prognosis and guide treatments of PC, meanwhile, the metabolism-immune biomarkers may provide novel target therapy for PC.

DNA methylome and transcriptome profiling reveal key electrophysiology and immune dysregulation in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease. However, a detailed DNA methylation (DNAme) landscape has not yet been elucidated. Our study combined DNAme and transcriptome profiles for HCM myocardium and identify aberrant DNAme associated with altered myocardial function in HCM. The transcription of methylation-related genes did not significantly differ between HCM and normal myocardium. Nevertheless, the former had an altered DNAme profile compared with the latter. The hypermethylated and hypomethylated sites in HCM tissues had chromosomal distributions and functional enrichment of correlated genes differing from those of their normal tissue counterparts. The GO analysis of network underlying the genes correlated with DNAme alteration and differentially expressed genes (DEGs) shows functional clusters centred on immune cell function and muscle system processes. In KEGG analysis, only the calcium signalling pathway was enriched either by the genes correlated with changes in DNAme or DEGs. The protein-protein interactions (PPI) underlying the genes altered at both the DNAme and transcriptional highlighted two important functional clusters. One of these was related to the immune response and had the estrogen receptor-encoding ESR1 gene as its node. The other cluster comprised cardiac electrophysiology-related genes. Intelliectin-1 (ITLN1), a component of the innate immune system, was transcriptionally downregulated in HCM and had a hypermethylated site within 1500 bp upstream of the ITLN1 transcription start site. Estimates of immune infiltration demonstrated a relative decline in immune cell population diversity in HCM. A combination of DNAme and transcriptome profiles may help identify and develop new therapeutic targets for HCM.

AHNAKs roles in physiology and malignant tumors

The AHNAK family currently consists of two members, namely AHNAK and AHNAK2, both of which have a molecular weight exceeding 600 kDa. Homologous sequences account for approximately 90% of their composition, indicating a certain degree of similarity in terms of molecular structure and biological functions. AHNAK family members are involved in the regulation of various biological functions, such as calcium channel modulation and membrane repair. Furthermore, with advancements in biological and bioinformatics technologies, research on the relationship between the AHNAK family and tumors has rapidly increased in recent years, and its regulatory role in tumor progression has gradually been discovered. This article briefly describes the physiological functions of the AHNAK family, and reviews and analyzes the expression and molecular regulatory mechanisms of the AHNAK family in malignant tumors using Pubmed and TCGA databases. In summary, AHNAK participates in various physiological and pathological processes in the human body. In multiple types of cancers, abnormal expression of AHNAK and AHNAK2 is associated with prognosis, and they play a key regulatory role in tumor progression by activating signaling pathways such as ERK, MAPK, Wnt, and MEK, as well as promoting epithelial-mesenchymal transition.

Integrative profiling analysis reveals prognostic significance, molecular characteristics, and tumor immunity of angiogenesis-related genes in soft tissue sarcoma

Background

Soft tissue sarcoma (STS) is a class of malignant tumors originating from mesenchymal stroma with a poor prognosis. Accumulating evidence has proved that angiogenesis is an essential hallmark of tumors. Nevertheless, there is a paucity of comprehensive research exploring the association of angiogenesis-related genes (ARGs) with STS.

Methods

The ARGs were extracted from previous literature, and the differentially expressed ARGs were screened for subsequent analysis. Next, the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were conducted to establish the angiogenesis-related signature (ARSig). The predictive performance of the novel ARSig was confirmed using internal and external validation, subgroup survival, and independent analysis. Additionally, the association of the ARSig with the tumor immune microenvironment, tumor mutational burden (TMB), and therapeutic response in STS were further investigated. Notably, we finally conducted in vitro experiments to verify the findings from the bioinformatics analysis.

Results

A novel ARSig is successfully constructed and validated. The STS with a lower ARSig risk score in the training cohort has an improved prognosis. Also, consistent results were observed in the internal and external cohorts. The receiver operating characteristic (ROC) curve, subgroup survival, and independent analysis further indicate that the novel ARSig is a promising independent prognostic predictor for STS. Furthermore, it is proved that the novel ARSig is relevant to the immune landscape, TMB, immunotherapy, and chemotherapy sensitivity in STS. Encouragingly, we also validate that the signature ARGs are significantly dysregulated in STS, and ARDB2 and SRPK1 are closely connected with the malignant progress of STS cells.

Conclusion

In sum, we construct a novel ARSig for STS, which could act as a promising prognostic factor for STS and give a strategy for future clinical decisions, immune landscape, and personalized treatment of STS.

AHNAK2 is a biomarker and a potential therapeutic target of adenocarcinomas

Adenocarcinoma is the second largest histological type of cervical cancer, second only to cervical squamous cell carcinoma. At present, despite the clinical treatment strategies of cervical adenocarcinoma and cervical squamous cell carcinoma being similar, the outcome and prognosis of cervical adenocarcinoma are significantly poor. Therefore, it is urgent to find specific biomarker and therapeutic target for cervical adenocarcinoma. In this study, we aim to reveal and verify the potential biomarkers and therapeutic targets of cervical adenocarcinoma. Weighted correlation network analysis (WGCNA) reveals the differentially-expressed genes significantly related to the histological characteristics of the two cervical cancer subtypes. We select the genes with the top 20 significance for further investigation. Through microarray and immunohistochemical (IHC) analyses of a variety of tumor tissues, we find that among these 20 genes, AHNAK2 is highly expressed not only in cervical adenocarcinoma, but also in multiple of adenocarcinoma tissues, including esophagus, breast and colon, while not in normal gland tissues. In vitro, AHNAK2 knockdown significantly inhibits cell proliferation and migration of adenocarcinoma cell lines. In vivo, AHNAK2 knockdown significantly inhibits tumor progression and metastasis of various adenocarcinomas. RNA-sequencing and bioinformatics analyses suggest that the inhibitory effect of AHNAK2 knockdown on tumor progression is achieved by regulating DNA replication and upregulating Bim expression. Together, we demonstrate that AHNAK2 is a biomarker and a potential therapeutic target for adenocarcinomas.

Identification of Novel Imatinib-Resistant Genes in Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are common ICC precursor sarcomas, which are considered to be a potential malignant mesenchymal tumor driven by specific KIT or PDGFRA signals in the gastrointestinal tract. The standard treatment for GIST without metastasis is surgical resection. GIST with metastasis is usually treated with tyrosine kinase inhibitors (TKIs) only but cannot be cured. The TKI imatinib is the main drug of GIST drug therapy. In adjuvant therapy, the duration of imatinib adjuvant therapy is 3 years. It has been proved that imatinib can improve the overall survival time (OS). However, many GIST patients develop drug resistance due to the long-term use of imatinib. We were forced to look for new strategies to treat GIST. The purpose of the current academic work is to study the drug-resistant genes of imatinib and their potential mechanisms. A total of 897 differentially expressed genes (DEGs) were found between imatinib-sensitive cell line GIST882 and imatinib-resistant cell line GIST430 by RNA sequencing (RNA-seq). After analyzing the DEGs, 10 top genes were selected (NDN, FABP4, COL4A1, COLEC11, MEG3, EPHA3, EDN3, LMO3, RGS4, and CRISP2). These genes were analyzed by RT-PCR, and it was confirmed that the expression trend of FABP4, COL4A1, and RGS4 in different imatinib-resistant cell lines was in accord with the GEO database. It is suggested that these genes may play a potential role in the clinical diagnosis and treatment of imatinib resistance in GIST.

Deleterious AHNAK2 Mutation as a Novel Biomarker for Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer

Immune checkpoint inhibitors (ICIs) have exhibited promising efficacy in non-small cell lung cancer (NSCLC), but the response occurs in only a minority of patients. In clinic, biomarkers such as TMB (tumor mutation burden) and PD-L1 (programmed cell death 1 ligand 1) still have their limitations in predicting the prognosis of ICI treatment. Hence, reliable predictive markers for ICIs are urgently needed. A public immunotherapy dataset with clinical information and mutational data of 75 NSCLC patients was obtained from cBioPortal as the discovery cohort, and another immunotherapy dataset of 249 patients across multiple cancer types was collected as the validation. Integrated bioinformatics analysis was performed to explore the potential mechanism, and immunohistochemistry studies were used to verify it. AHNAK nucleoprotein 2 (AHNAK2) was reported to have pro-tumor growth effects across multiple cancers, while its role in tumor immunity was unclear. We found that approximately 11% of the NSCLC patients harbored AHNAK2 mutations, which were associated with promising outcomes to ICI treatments (ORR, p = 0.013). We further found that AHNAK2 deleterious mutation (del-AHNAK2^mut) possessed better predictive function in NSCLC than non-deleterious AHNAK2 mutation (PFS, OS, log-rank p < 0.05), potentially associated with stronger tumor immunogenicity and an activated immune microenvironment. This work identified del-AHNAK2^mut as a novel biomarker to predict favorable ICI response in NSCLC.

Construction of a Redox-Related Prognostic Model with Predictive Value in Survival and Therapeutic Response for Patients with Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) represents the most common histological subtype of lung cancer. Redox plays a significant role in oncogenesis and antitumor immunity. In this study, we aimed to investigate the prognostic redox-associated genes and construct a redox-based prognostic signature for LUAD.

Materials and Methods

A discovery cohort containing 479 LUAD samples from The Cancer Genome Atlas (TCGA) was analyzed. We identified prognostic redox-associated genes by weighted correlation network analysis (WGCNA) and univariate Cox regression analysis to construct a prognostic model via least absolute shrinkage and selection operator (LASSO)-multivariate Cox regression analyses. The performance of the redox-based model was validated in the TCGA cohort and an independent cohort of 456 samples by Cox regression analyses, log-rank test, and receiver operating characteristic (ROC) curves. Correlations of the model with clinicopathological variables and lymphocyte infiltration were assessed. Gene set enrichment analysis (GSEA) was used to clarify the underlying mechanism of the prognostic model. We constructed a nomogram based on the model and created calibration curves to show the accordance between actual survival and predicted survival of the nomogram.

Results

Stepwise analyses identified 6 prognostic redox-associated genes of LUAD and constructed a prognostic model that performed well in both the discovery and validation cohorts. The model was found to be associated with tumor stage, mutation of TP53 and EGFR, and lymphocyte infiltration. The model was mainly involved in the regulation of the cell cycle, DNA replication and repair, NADH metabolism, and the p53 signaling pathway. Calibration curves showed the high predictive accuracy of the nomogram.

Conclusions

This study explored the role of redox-associated genes in LUAD and constructed a prognostic model of LUAD. The signature was also associated with tumor progression and therapeutic response to immunotherapy. These findings contributed to uncovering the underlying mechanism and discovering novel prognostic predictor of LUAD.

The Obscure Potential of AHNAK2

Simple Summary

AHNAK2 is a relatively newly discovered protein. It can interact with many other proteins. This protein is increased in cells of variety of different cancers. AHNAK2 may play a vital role in cancer formation. AHNAK2 may have a role in early detection of cancer. This obscure potential of AHNAK2 is being studied.

Abstract

AHNAK2 is a protein discovered in 2004, with a strong association with oncogenesis in various epithelial cancers. It has a large 616 kDa tripartite structure and is thought to take part in the formation of large multi-protein complexes. High expression is found in clear cell renal carcinoma, pancreatic ductal adenocarcinoma, uveal melanoma, and lung adenocarcinoma, with a relation to poor prognosis. Little work has been done in exploring the function and relation AHNAK2 has with cancer, with early studies showing promising potential as a future biomarker and therapeutic target.