FAIM2 Promotes Non-Small Cell Lung Cancer Cell Growth and Bone Metastasis by Activating the Wnt/β-Catenin Pathway

Unravelling key signaling pathways for the therapeutic targeting of non-small cell lung cancer

Lung cancer (LC) remains the foremost cause of cancer-related mortality across the globe. Non-small cell lung cancer (NSCLC) is a type of LC that exhibits significant heterogeneity at histological and molecular levels. Genetic alterations in upstream signaling molecules activate cascades affecting apoptosis, proliferation, and differentiation. Disruption of these signaling pathways leads to the proliferation of cancer-promoting cells, progression of cancer, and resistance to its treatment. Recent insights into the function of signaling pathways and their fundamental mechanisms in the onset of various diseases could pave the way for new therapeutic approaches. Recently, numerous drug molecules have been created that target these cell signaling pathways and could be used alongside other standard therapies to achieve synergistic effects in mitigating the pathophysiology of NSCLC. Additionally, many researchers have identified several predictive biomarkers, and alterations in transcription factors and related pathways are employed to create new therapeutic strategies for NSCLC. Findings suggest using specific inhibitors to target cellular signaling pathways in tumor progression to treat NSCLC. This review investigates the role of signaling pathways in NSCLC development and explores novel therapeutic strategies to enhance clinical treatment options for NSCLC.

Lung cancer exosomal Gal3BP promotes osteoclastogenesis with potential connotation in osteolytic metastasis

New insights into cellular interactions and key biomolecules involved in lung cancer (LC) bone metastasis could offer remarkable therapeutic benefits. Using a panel of four LC cells, we investigated LC-bone interaction by exposing differentiating osteoclasts (OCs) to LC cells (LC-OC interaction) directly in a co-culture setting or indirectly via treatment with LC secretomes (conditioned media or exosomes). LC-OC interaction facilitated the production of large-sized OCs (nuclei > 10) coupled with extensive bone resorption pits. Proteomic analysis of LC exosomes identified galectin-3-binding protein (Gal3bp) as a potential biomarker which was released primarily by most of LC-derived exosomes. The facilitation of OC differentiation and function by LC-exosomal Gal3bp was supported by the application of recombinant Gal3bp and anti-Gal3bp in OC treatment. Further, our results exhibited a dysregulation of crucial OC markers (TRAF6, p-SAPK/JNK, p-44/42 MAPK, NFAT2 and CD9) during LC-OC interaction that possibly contributed to the facilitation of osteoclastogenesis. Simulation of bone metastasis via intratibial injection of LC cells revealed Gal3bp's possible roles in enhancing OC activation leading to osseous tissue resorption. Overall, this work implicated LC-exosomal Gal3bp in osteolytic metastasis of LC which warrants further studies to assess its potential prognostic and therapeutic relevance.

New insights into non-small cell lung cancer bone metastasis: mechanisms and therapies

Bone metastasis is a common cause of death in patients with non-small cell lung cancer (NSCLC), with approximately 30-40% of NSCLC patients eventually developing bone metastases. Bone metastasis, especially the occurrence of skeletal-related events (SREs), significantly reduces overall survival (OS) and quality of life (QoL) in patients. Although bone-targeting agents (BTAs) have been shown to reduce SREs and improve QoL in NSCLC patients with bone metastases, the prognosis for these patients remains poor. Understanding the underlying molecular pathways of bone metastasis is crucial for the development of novel therapeutic approaches. Bone metastasis is a complex, multistep process that involves interactions between tumor cells and the bone microenvironment. The bone microenvironment provides a fertile soil for tumor cells, and crosstalk among various signaling pathways and secreted factors also plays a role in regulating the occurrence and progression of bone metastasis in NSCLC. In this article, we provide a comprehensive review of the process, regulatory mechanisms, and clinical treatment in NSCLC bone metastasis, with the hope of assisting with clinical treatment.

Comprehensive analysis and experimental verification of the mechanism of anoikis related genes in pancreatic cancer

Background

Pancreatic cancer (PC), characterized by its aggressive nature and low patient survival rate, remains a challenging malignancy. Anoikis, a process inhibiting the spread of metastatic cancer cells, is closely linked to cancer progression and metastasis through anoikis-related genes. Nonetheless, the precise mechanism of action of these genes in PC remains unclear.

Methods

Study data were acquired from the Cancer Genome Atlas (TCGA) database, with validation data accessed at the Gene Expression Omnibus (GEO) database. Differential expression analysis and univariate Cox analysis were performed to determine prognostically relevant differentially expressed genes (DEGs) associated with anoikis. Unsupervised cluster analysis was then employed to categorize cancer samples. Subsequently, a least absolute shrinkage and selection operator (LASSO) Cox regression analysis was conducted on the identified DEGs to establish a clinical prognostic gene signature. Using risk scores derived from this signature, patients with cancer were stratified into high-risk and low-risk groups, with further assessment conducted via survival analysis, immune infiltration analysis, and mutation analysis. External validation data were employed to confirm the findings, and Western blot and immunohistochemistry were utilized to validate risk genes for the clinical prognostic gene signature.

Results

A total of 20 prognostic-related DEGs associated with anoikis were obtained. The TCGA dataset revealed two distinct subgroups: cluster 1 and cluster 2. Utilizing the 20 DEGs, a clinical prognostic gene signature comprising two risk genes (CDKN3 and LAMA3) was constructed. Patients with pancreatic adenocarcinoma (PAAD) were classified into high-risk and low-risk groups per their risk scores, with the latter exhibiting a superior survival rate. Statistically significant variation was noted across immune infiltration and mutation levels between the two groups. Validation cohort results were consistent with the initial findings. Additionally, experimental verification confirmed the high expression of CDKN3 and LAMA3 in tumor samples.

Conclusion

Our study addresses the gap in understanding the involvement of genes linked to anoikis in PAAD. The clinical prognostic gene signature developed herein accurately stratifies patients with PAAD, contributing to the advancement of precision medicine for these patients.

Anoikis resistance regulates immune infiltration and drug sensitivity in clear-cell renal cell carcinoma: insights from multi omics, single cell analysis and in vitro experiment

Background

Anoikis is a form of programmed cell death essential for preventing cancer metastasis. In some solid cancer, anoikis resistance can facilitate tumor progression. However, this phenomenon is underexplored in clear-cell renal cell carcinoma (ccRCC).

Methods

Using SVM machine learning, we identified core anoikis-related genes (ARGs) from ccRCC patient transcriptomic data. A LASSO Cox regression model stratified patients into risk groups, informing a prognostic model. GSVA and ssGSEA assessed immune infiltration, and single-cell analysis examined ARG expression across immune cells. Quantitative PCR and immunohistochemistry validated ARG expression differences between immune therapy responders and non-responders in ccRCC.

Results

ARGs such as CCND1, CDKN3, PLK1, and BID were key in predicting ccRCC outcomes, linking higher risk with increased Treg infiltration and reduced M1 macrophage presence, indicating an immunosuppressive environment facilitated by anoikis resistance. Single-cell insights showed ARG enrichment in Tregs and dendritic cells, affecting immune checkpoints. Immunohistochemical analysis reveals that ARGs protein expression is markedly elevated in ccRCC tissues responsive to immunotherapy.

Conclusion

This study establishes a novel anoikis resistance gene signature that predicts survival and immunotherapy response in ccRCC, suggesting that manipulating the immune environment through these ARGs could improve therapeutic strategies and prognostication in ccRCC.

Wnt/β-catenin signaling in the development and therapeutic resistance of non-small cell lung cancer

Wnt/β-catenin signaling is a critical pathway that influences development and therapeutic response of non-small cell lung cancer (NSCLC). In recent years, many Wnt regulators, including proteins, miRNAs, lncRNAs, and circRNAs, have been found to promote or inhibit signaling by acting on Wnt proteins, receptors, signal transducers and transcriptional effectors. The identification of these regulators and their underlying molecular mechanisms provides important implications for how to target this pathway therapeutically. In this review, we summarize recent studies of Wnt regulators in the development and therapeutic response of NSCLC.

Prognostic correlation between specialized capillary endothelial cells and lung adenocarcinoma

Background

In-depth analysis of the functional changes occurring in endothelial cells (ECs) involved in capillary formation can help to elucidate the mechanism of tumour vascular growth.

Methods

Appropriate datasets were retrieved from the GEO database to obtain single-cell data on LUAD samples and adjacent normal tissue samples. ECs were selected by an automatic annotation program in R and further subdivided based on reported EC marker genes. Functional changes in different types of capillary ECs were then visualized, and the concrete expression was classified by genetic data in the TCGA. Finally, a prognostic model was constructed to predict immunoinfiltration status, survival and drug therapy effects.

Results

The LUAD data contained in the GSE183219 dataset were suitable for our analysis. After dimensionality reduction analysis and cell annotation, EC general capillary and EC aerocyte subsets as capillary specialized phenotypes showed a series of functional changes in tumour samples, with a total of 108 genes found to undergo functional changes. Use of CellPhoneDB revealed a close interaction of activity between ECs. After integration of TCGA, GSE68465 and GSE11969 datasets, the genes obtained were analysed by cluster analysis and risk model construction, identifying 8 genes. Drug sensitivity, immune cell and molecular differences can be accurately predicted.

Conclusions

EC general capillary and EC aerocyte subsets are recognized capillary ECs in the tumour microenvironment, and the functional changes between them are relevant to the prognosis and treatment of LUAD patients and have the potential to be used in target therapy.

Digital spatial profiling of segmental outflow regions in trabecular meshwork reveals a role for ADAM15

In this study we used a spatial transcriptomics approach to identify genes specifically associated with either high or low outflow regions in the trabecular meshwork (TM) that could potentially affect aqueous humor outflow in vivo. High and low outflow regions were identified and isolated from organ cultured human anterior segments perfused with fluorescently-labeled 200 nm FluoSpheres. The NanoString GeoMx Digital Spatial Profiler (DSP) platform was then used to identified genes in the paraffin embedded tissue sections from within those regions. These transcriptome analyses revealed that 16 genes were statistically upregulated in high outflow regions and 57 genes were statistically downregulated in high outflow regions when compared to low outflow regions. Gene ontology enrichment analysis indicated that the top three biological categories of these differentially expressed genes were ECM/cell adhesion, signal transduction, and transcription. The ECM/cell adhesion genes that showed the largest differential expression (Log2FC ±1.5) were ADAM15, BGN, LDB3, and CRKL. ADAM15, which is a metalloproteinase that can bind integrins, was upregulated in high outflow regions, while the proteoglycan BGN and two genes associated with integrin signaling (LDB3, and CRKL) were downregulated. Immunolabeling studies supported the differential expression of ADAM15 and showed that it was specifically upregulated in high outflow regions along the inner wall of Schlemm's canal and in the juxtacanalicular (JCT) region of the TM. In addition to these genes, the studies showed that genes for decorin, a small leucine-rich proteoglycan, and the α8 integrin subunit were enriched in high outflow regions. These studies identify several novel genes that could be involved in segmental outflow, thus demonstrating that digital spatial profiling could be a useful approach for understanding segmental flow through the TM. Furthermore, this study suggests that changes in the expression of genes involved in regulating the activity and/or organization of the ECM and integrins in the TM are likely to be key players in segmental outflow.

Identification of hypoxia-related gene signatures based on multi-omics analysis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and one of the malignancies with the highest incidence rate and mortality worldwide. Hypoxia is a typical feature of tumour microenvironment (TME), which affects the progression of LUAD from multiple molecular levels. However, the underlying molecular mechanisms behind LUAD hypoxia are not fully understood. In this study, we estimated the level of hypoxia by calculating a score based on 15 hypoxia genes. The hypoxia scores were relatively high in LUAD patients with poor prognosis and were bound up with tumour node metastasis (TNM) stage, tumour size, lymph node, age and gender. By comparison of high hypoxia score group and low hypoxia score group, 1820 differentially expressed genes were identified, among which up-regulated genes were mainly about cell division and proliferation while down-regulated genes were primarily involved in cilium-related biological processes. Besides, LUAD patients with high hypoxia scores had higher frequencies of gene mutations, among which TP53, TTN and MUC16 had the highest mutation rates. As for DNA methylation, 1015 differentially methylated probes-related genes were found and may play potential roles in tumour-related neurobiological processes and cell signal transduction. Finally, a prognostic model with 25 multi-omics features was constructed and showed good predictive performance. The area under curve (AUC) values of 1-, 3- and 5-year survival reached 0.863, 0.826 and 0.846, respectively. Above all, our findings are helpful in understanding the impact and molecular mechanisms of hypoxia in LUAD.

Development of a prognostic signature based on anoikis-related genes in hepatocellular carcinoma with the utilization of LASSO-cox method

To develop a signature based on anoikis-related genes (ARGs) for predicting the prognosis of patients with hepatocellular carcinoma (HCC), and to elucidate the molecular mechanisms involved. In this study, bioinformatic algorithms were applied to integrate and analyze 777 HCC RNA-seq samples from the cancer genome atlas and international cancer genome consortium repositories. A prognostic signature was developed via the least absolute shrinkage and selection operator-cox regression method. To evaluate the accuracy of the signature in predicting events, multi-type technical means, such as Kaplan-Meier plots, receiver operating characteristic curve analysis, nomogram construction, and univariate and multivariate Cox regression studies were performed. We investigated the underlying molecular biological mechanisms and immune mechanisms of the signature using gene set enrichment analysis and the CIBERSORT R package, respectively. Meanwhile, immunohistochemical staining acquired from the human protein atlas was used to confirm the differential expression levels of hub genes involved in the prognostic signature. We developed an HCC prognostic signature with a collection of 5 ARGs, and the prognostic value was successfully assessed and verified in both the test and validation cohorts. The risk scores calculated by the prognostic signature were proved to be an independent negative prognostic factor for overall survival. A set of nomograms based on risk scores was established and found to be effective in predicting OS. Further investigation of the underlying molecular biological mechanisms and immune mechanisms indicated that the signature may be relevant to metabolic dysregulation and infiltration of gamma delta T cells in the tumor. The survival prognosis of HCC patients can be predicted by the anoikis-related prognostic signature, and it serves as a valuable reference for individualized HCC therapy.

DPHL v.2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v.1, a previous pan-human library built from 1,096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying of 10,943 proteins. Here, we generated DPHL v.2 from 1,608 DDA-MS data. The data included 586 DDA-MS data acquired from 18 tissue types, while 1,022 files were derived from DPHL v.1. DPHL v.2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v.2 to include semi-tryptic peptides and protein isoforms. DPHL v.2 was then applied to two colorectal cancer cohorts. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v.1. Our findings show that the increased human proteome coverage of DPHL v.2 provides larger pools of potential protein biomarkers.

FAIM2 is correlated with metastasis of medulloblastoma through bioinformatics analysis

Medulloblastoma (MB) is one of the most frequent malignant brain tumors in children. The metastasis of MB outside the nervous system is associated with a poor prognosis. Our study aimed to explore the genes correlated with metastasis in MB. Using the data downloaded from the gene expression omnibus database, the differentially expressed genes were identified between the metastatic and nonmetastatic samples in MB, which were undergone functional enrichment. Prognosis related genes were identified using univariate Cox regression analysis. The gene set enrichment analysis was conducted to find MB metastasis related pathways. A total of 196 differentially expressed genes were identified between metastatic and nonmetastatic samples in MB patients, and these genes were significantly enriched in 483 gene ontology terms and 29 Kyoto encyclopedia of genes and genomes pathways. In addition, univariate Cox regression analysis screened the top 10 genes (CEMIP, GLCE, ART3, GABRA5, COLEC12, LIN28B, ZNF521, IL17RB, Fas apoptotic inhibitory molecule 2 (FAIM2), RCBTB2) that were significantly associated with survival of MB, among which FAIM2 was prominently expressed in cerebral cortex, cerebellum and hippocampus. The expression of FAIM2 was decreased in metastatic MB samples, and FAIM2 harbored missense mutations, amplifications and deep deletions in metastatic samples of MB. Moreover, a total of 25 pathways were significantly activated and 41 pathways were significantly inhibited in FAIM2 high expression group compared to FAIM2 low expression group in MB patients. FAIM2 was tightly correlated with metastasis in MB patients, and the low expression of FAIM2 was associated with poor prognosis.

Anoikis resistance of small airway epithelium is involved in the progression of chronic obstructive pulmonary disease

Background

Anoikis resistance is recognized as a crucial step in the metastasis of cancer cells. Most epithelial tumors are distinguished by the ability of epithelial cells to abscond anoikis when detached from the extracellular matrix. However, no study has investigated the involvement of anoikis in the small airway epithelium (SAE) of chronic obstructive pulmonary disease (COPD).

Methods

Anoikis-related genes (ANRGs) exhibiting differential expression in COPD were identified using microarray datasets obtained from the Gene Expression Omnibus (GEO) database. Unsupervised clustering was performed to classify COPD patients into anoikis-related subtypes. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used to annotate the functions between different subtypes. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were leveraged to identify key molecules. The relative proportion of infiltrating immune cells in the SAE was quantified using the CIBERSORT and ssGSEA computational algorithms, and the correlation between key molecules and immune cell abundance was analyzed. The expression of key molecules in BEAS-2B cells exposed to cigarette smoke extract (CSE) was validated using qRT-PCR.

Results

A total of 25 ANRGs exhibited differential expression in the SAE of COPD patients, based on which two subtypes of COPD patients with distinct anoikis patterns were identified. COPD patients with anoikis resistance had more advanced GOLD stages and cigarette consumption. Functional annotations revealed a different immune status between COPD patients with pro-anoikis and anoikis resistance. Tenomodulin (TNMD) and long intergenic non-protein coding RNA 656 (LINC00656) were subsequently identified as key molecules involved in this process, and a close correlation between TNMD and the infiltrating immune cells was observed, such as activated CD4+ memory T cells, M1 macrophages, and activated NK cells. Further enrichment analyses clarified the relationship between TNMD and the inflammatory and apoptotic signaling pathway as the potential mechanism for regulating anoikis. In vitro experiments showed a dramatic upregulation of TNMD and LINC00656 in BEAS-2B cells when exposed to 3% CSE for 48 hours.

Conclusion

TNMD contributes to the progression of COPD by inducing anoikis resistance in SAE, which is intimately associated with the immune microenvironment.

Identification and validation of anoikis-associated gene SNCG as a prognostic biomarker in gastric cancer

Anoikis is a newly discovered form of apoptosis that was originally identified in the extracellular matrix (ECM). Recent studies have reported that anoikis is central to cancer metastasis. Here, SNCG was identified as hub anoikis-associated gene in GC and associated with prognosis of patients with GC. To screen the hub anoikis-associated genes connected to GC, the database of Cancer Genome Atlas (TCGA) was employed. For further validating these identified genes, the Gene Expression Omnibus (GEO) dataset was applied, and Western blotting and quantitative Real-Time PCR were carried out. To identify hub genes, we conducted the analyses of univariate Cox regression, differential expression, and weighted gene co-expression network analysis (WGCNA). According to the identified hub genes, we constructed a model of prognosis. Following complex analysis, SNCG was finally identified as hub anoikis-associated gene in GC. Indeed, K-M and receiver operating characteristic analyses suggested that the expression patterns of SNCG can be used as prognostic factors for GC survival. The expression and survival trends of SNCG were verified in the validation cohort and in vitro experimental analyses. The analysis of immune cell infiltration showed that the infiltrated immune cells varied among patients with GC and gene SNCG. Furthermore, due to the significant association of the constructed risk signature with patient age and survival, this risk signature can be used to predict the prognosis of GC. We suggest that SNCG was served as hub anoikis-associated gene in GC. Meanwhile, SNCG may have prognostic potential for overall patient survival.

Establishment and validation of a novel anoikis-related prognostic signature of clear cell renal cell carcinoma

Background

Despite progression in its treatment, the clinical outcome of patients with clear cell renal cell carcinoma (ccRCC) remains not ideal. Anoikis is a unique form of programmed apoptosis, owing to insufficient cell-matrix interactions. Anoikis plays a crucial role in tumor migration and invasion, and tumor cells could protect themselves through the capacity of anoikis resistance.

Methods

Anoikis-related genes (ARGs) were obtained from Genecards and Harmonizome portals. The ARGs related to ccRCC prognosis were identified through univariate Cox regression analysis, then we utilized these ARGs to construct a novel prognostic model for ccRCC patients. Moreover, we explored the expression profile of ARGs in ccRCC using the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database. We also conducted Real-Time Polymerase Chain Reaction (RT-PCR) to probe ARGs expression of the risk score. Finally, we performed correlation analysis between ARGs and tumor immune microenvironment.

Results

We identified 17 ARGs associated with ccRCC survival, from which 7 genes were chosen to construct a prognostic model. The prognostic model was verified as an independent prognostic indicator. The expression of most ARGs was higher in ccRCC samples. These ARGs were closely correlated with immune cell infiltration and immune checkpoint members, and had independent prognostic value respectively. Functional enrichment analysis demonstrated that these ARGs were significantly associated with multiple types of malignances.

Conclusion

The prognostic signature was identified to be highly efficient in predicting ccRCC prognosis, and these ARGs were closely related to tumor microenvironment.

Oncogenic zinc finger protein ZNF687 accelerates lung adenocarcinoma cell proliferation and tumor progression by activating the PI3K/AKT signaling pathway

BACKGROUND

Zinc finger protein 687 (ZNF687) has previously been discovered as a potential oncogene in individuals with giant cell tumors of the bone, acute myeloid leukemia, and hepatocellular carcinoma. However, its role and mechanism in lung adenocarcinoma (LUAD) remain unclear.

METHODS

In LUAD cells, tumor, and matched adjacent tissue specimens, quantitative real-time RT- polymerase chain reaction (qRT-PCR), western blotting analyses, and immunohistochemistry staining (IHC) were conducted. Cell counting kit-8 (CCK8) assay, clonogenicity analysis, flow cytometry, and transwell assays were utilized to detect ZNF687 overexpression and knockdown impacts on cell growth, colony formation, cell cycle, migration, and invasion. Bioinformatic studies, qRT-PCR and western blotting studies were employed to validate the underlying mechanisms and signaling pathways implicated in the oncogenic effect of ZNF687.

RESULTS

This study demonstrated that ZNF687 expression was elevated in LUAD cells and tissues. Individuals with upregulated ZNF687 had a poorer prognosis than those with downregulatedZNF687 (p < 0.001). ZNF687 overexpression enhanced LUAD growth, migration, invasion and colony formation, and the cell cycle G1-S transition; additionally, it promoted the epithelial-mesenchymal transition (EMT). In contrast, knocking down ZNF687 showed to have the opposite impact. Moreover, these effects were associated with the activity of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling mechanism.

CONCLUSION

ZNF687 was upregulated in LUAD, and high ZNF687 expression levels are associated with poor prognoses. The activation of the PI3K/AKT signaling pathway by upregulated ZNF687 increased the proliferation of LUAD cells and tumor progression. ZNF687 may be a beneficial predictive marker and a therapeutic target in LUAD.

Development of anoikis-related genes signature to predict the prognosis in gastric cancer patients

Background

It is well known that the prognosis of Gastric cancer (GC) patient is affected by many factors. However, the latent impact of anoikis on the prognosis of GC patients is insufficient understood.

Methods

According to the Cancer Genome Atlas (TCGA) database, we elected discrepantly expressed anoikis-related genes (ARGs). Univariate cox and the least absolute shrinkage and selection operator (lasso) analysis were applied to build the ARGs signature. The prognostic effect of the ARGs signature was also evaluated. A series of algorithms were performed to evaluate the discrepancies in the immune microenvironment. Moreover, the correlation between drug sensitivity and ARGs signature was analyzed. We also performed Real-Time Polymerase Chain Reaction (RT-PCR) to probe the signature.

Results

The ARGs signature of 9 genes was constructed, which was apparently interrelated with the prognosis. The nomogram was established by combining the ARGs signature with clinicopathological characteristics. We found that the predictive power was noteworthily superior to other individual predictors. The immune microenvironment analysis indicated that ESTIMATEscore, ImmuneScores, StromalScores, tumor immune dysfunction and exclusion (TIDE) score were lower in the low-risk group, while immunophenoscore (IPS) was on the contrary. The infiltrated immune cells and immune checkpoint (ICP) expression levels were significantly different between the two groups. Furthermore, nine drugs were positively associated with the ARGs signature score. The results of RT-PCR analysis were consistent with our previous differential expression analysis.

Conclusion

The developed ARGs signature could act as the biomarker and provide a momentous reference for Individual therapy of GC patients.

DNA methylome in pancreatic cancer identified novel promoter hyper-methylation in NPY and FAIM2 genes associated with poor prognosis in Indian patient cohort

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading cancers worldwide and has a poor survival, with a 5-year survival rate of only 8.5%. In this study we investigated altered DNA methylation associated with PDAC severity and prognosis.

METHODS

Methylome data, generated using 450 K bead array, was compared between paired PDAC and normal samples in the TCGA cohort (n = 9) and our Indian cohort (n = 7). The total Indian Cohort (n = 75) was split into cohort 1 (n = 7), cohort 2 (n = 22), cohort 3 (n = 26) and cohort 4 (n = 20).Validation of differential methylation (6 selected CpG loci) and associated gene expression for differentially methylated genes (10 selected gDMs) were carried out in separate validation cohorts, using MSP, RT-PCR and IHC correlations between methylation and gene expression were observed in TCGA, GTEx cohorts and in validation cohorts. Kaplan-Meier survival analysis was done to study differential prognosis, during 2-5 years of follow-up.

RESULTS

We identified 156 DMPs, mapped to 91 genes (gDMs), in PDAC; 68 (43.5%) DMPs were found to be differentially methylated both in TCGA cohort and our cohort, with significant concordance at hypo- and hyper-methylated loci. Enrichments of "regulation of ion transport", "Interferon alpha/beta signalling", "morphogenesis and development" and "transcriptional dysregulation" pathways were observed among 91 gDMs. Hyper-methylation of NPY and FAIM2 genes with down-regulated expression in PDAC, were significantly associated with poor prognosis in the Indian patient cohort.

CONCLUSIONS

Ethnic variations among populations may determine the altered epigenetic landscape in the PDAC patients of the Indian cohort. Our study identified novel differentially methylated genes (mainly NPY and FAIM2) and also validated the previously identified differentially methylated CpG sites associated with PDAC cancer patient's survival. Comparative analysis of our data with TCGA and CPTAC cohorts showed that both NPY and FAIM2 hyper-methylation and down-regulations can be novel epigenetically regulated genes in the Indian patient population, statistically significantly associated with poor survival and advanced tumour stages.

Anoikis-Associated Lung Cancer Metastasis: Mechanisms and Therapies

Simple Summary

Anoikis is a programmed cell death process resulting from the loss of interaction between cells and the extracellular matrix. Therefore, it is necessary to overcome anoikis when tumor cells acquire metastatic potential. In lung cancer, the composition of the extracellular matrix, cell adhesion-related membrane proteins, cytoskeletal regulators, and epithelial–mesenchymal transition are involved in the process of anoikis, and the initiation of apoptosis signals is a critical step in anoikis. Inversely, activation of growth signals counteracts anoikis. This review summarizes the regulators of lung cancer-related anoikis and explores potential drug applications targeting anoikis.

Abstract

Tumor metastasis occurs in lung cancer, resulting in tumor progression and therapy failure. Anoikis is a mechanism of apoptosis that combats tumor metastasis; it inhibits the escape of tumor cells from the native extracellular matrix to other organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat lung cancer. Several natural and synthetic products exhibit the pro-anoikis potential in lung cancer cells and in vivo models. These products include artonin E, imperatorin, oroxylin A, lupalbigenin, sulforaphane, renieramycin M, avicequinone B, and carbenoxolone. This review summarizes the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in lung cancer metastasis and discusses the therapeutic potential of targeting anoikis in the treatment of lung cancer metastasis.

FAIM2 is a potential pan-cancer biomarker for prognosis and immune infiltration

Fas apoptosis inhibitory molecule 2 (FAIM2) is an important member of the transmembrane BAX inhibitor motif containing (TMBIM) family. However, the role of FAIM2 in tumor prognosis and immune infiltration has rarely been studied. Here, we conducted a pan-cancer analysis to explore the role of FAIM2 in various tumors and further verified the results in glioma through molecular biology experiment. FAIM2 expression and clinical stages in tumor samples and para-cancerous samples were analyzed by TIMER2 database, GEPIA database, and the TISIDB database. The role of FAIM2 on prognosis was analyzed via GEPIA2. We utilized the ESTIMATE algorithm to evaluate the ImmuneScore and StromalScore of various tumors. In addition, we explored the correlation between FAIM2 expression and tumor immune cell infiltration by the TIMER2 database. The immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methylation related to FAIM2 were analyzed based on the TCGA database. The correlation between FAIM2 expression with Copy number variations (CNV) and methylation is explored by GSCA database. Protein-Protein Interaction (PPI) analysis was obtained from the STRING database and the CellMiner database was used to explore the association between FAIM2 expression and drug response. FAIM2 co-expression genes were studied by the LinkedOmics database. Immunohistochemistry, Western Blotting Analysis, Cell Viability Assay, Colony Formation Assay, and Edu staining assay were used in the molecular biology experiments section. The FAIM2 expression was down-regulated in most tumors and highly expressed FAIM2 was associated with a better prognosis in several cancers. FAIM2 plays an essential role in the tumor microenvironment and is closely associated with immune Infiltration in various tumors. The expression of FAIM2 was closely correlated to TMB, MSI, MMR, CNV, and DNA methylation. Furthermore, FAIM2 related genes in the PPI network and its co-expression genes in glioma are involved in a large number of immune-related pathways. Molecular biology experiments verified a cancer suppressor role for FAIM2 in glioma. FAIM2 may serve as a potential pan-cancer biomarker for prognosis and immune infiltration, especially in glioma. Moreover, this study might provide a potential target for tumor immunotherapy.

Osteoporosis in Patients With Respiratory Diseases

Climate change, environmental pollution, and virus epidemics have sharply increased the number of patients suffering from respiratory diseases in recent years. Prolonged periods of illness and drug use increase the occurrence of complications in these patients. Osteoporosis is the common bone metabolism disease with respiratory disturbance, which affects prognosis and increases mortality of patients. The problem of osteoporosis in patients with respiratory diseases needs more attention. In this review, we concluded the characteristics of osteoporosis in some respiratory diseases including COPD, asthma, COVID-19, tuberculosis, and lung cancer. We revealed that hypoxia was the common pathogenesis of osteoporosis secondary to respiratory diseases, with malnutrition and corticosteroid abuse driving the progression of osteoporosis. Hypoxia-induced ROS accumulation and activated HIF-1α lead to attenuated osteogenesis and enhanced osteoclastogenesis in patients with respiratory diseases. Tuberculosis and cancer also invaded bone tissue and reduced bone strength by direct infiltration. For the treatment of osteoporosis in respiratory patients, oral-optimized bisphosphonates were the best treatment modality. Vitamin D was a necessary supplement, both for calcium absorption in osteogenesis and for improvement of respiratory lesions. Reasonable adjustment of the dose and course of corticosteroids according to the etiology and condition of patients is beneficial to prevent the occurrence and development of osteoporosis. Additionally, HIF-1α was a potential target for the treatment of osteoporosis in respiratory patients, which could be activated under hypoxia condition and involved in the process of bone remodeling.

A Machine-Learning Approach to Developing a Predictive Signature Based on Transcriptome Profiling of Ground-Glass Opacities for Accurate Classification and Exploring the Immune Microenvironment of Early-Stage LUAD

Screening for early-stage lung cancer with low-dose computed tomography is recommended for high-risk populations; consequently, the incidence of pure ground-glass opacity (pGGO) is increasing. Ground-glass opacity (GGO) is considered the appearance of early lung cancer, and there remains an unmet clinical need to understand the pathology of small GGO (&lt;1 cm in diameter). The objective of this study was to use the transcriptome profiling of pGGO specimens &lt;1 cm in diameter to construct a pGGO-related gene risk signature to predict the prognosis of early-stage lung adenocarcinoma (LUAD) and explore the immune microenvironment of GGO. pGGO-related differentially expressed genes (DEGs) were screened to identify prognostic marker genes with two machine learning algorithms. A 15-gene risk signature was constructed from the DEGs that were shared between the algorithms. Risk scores were calculated using the regression coefficients for the pGGO-related DEGs. Patients with Stage I/II LUAD or Stage IA LUAD and high-risk scores had a worse prognosis than patients with low-risk scores. The prognosis of high-risk patients with Stage IA LUAD was almost identical to that of patients with Stage II LUAD, suggesting that treatment strategies for patients with Stage II LUAD may be beneficial in high-risk patients with Stage IA LUAD. pGGO-related DEGs were mainly enriched in immune-related pathways. Patients with high-risk scores and high tumor mutation burden had a worse prognosis and may benefit from immunotherapy. A nomogram was constructed to facilitate the clinical application of the 15-gene risk signature. Receiver operating characteristic curves and decision curve analysis validated the predictive ability of the nomogram in patients with Stage I LUAD in the TCGA-LUAD cohort and GEO datasets.

Oligometastatic Disease in Non-Small-Cell Lung Cancer: An Update

Simple Summary

Approximately 7–50% of patients with non-small-cell lung cancer (NSCLC) develop oligometastases, which are new tumors found in another part of the body, arising from cancer cells of the original tumor that have travelled through the body. In recent years, these patients have been increasingly regarded as a distinct group that could benefit from treatment that intends to cure the disease, rather than palliative care, to achieve a better clinical outcome. Various treatment procedures have been developed for treating NSCLC patients with different oligometastatic sites. In addition, the newly proposed uniform definition for oligometastases as well as ongoing trials may lead to increased appropriate patient selection and evaluation of treatment effectiveness. The aim of this review article is to summarize the latest evidence regarding optimal management strategies for NSCLC patients with oligometastases.

Abstract

Oligometastatic non-small-cell lung cancer (NSCLC) is a distinct entity that is different from localized and disseminated diseases. The definition of oligometastatic NSCLC varies across studies in past decades owing to the use of different imaging modalities; however, a uniform definition of oligometastatic NSCLC has been proposed, and this may facilitate trial design and evaluation of certain interventions. Patients with oligometastatic NSCLC are candidates for curative-intent management, in which local ablative treatment, such as surgery or stereotactic radiosurgery, should be instituted to improve clinical outcomes. Although current guidelines recommend that local therapy for thoracic and metastatic lesions should be considered for patients with oligometastatic NSCLC with stable disease after systemic therapy, optimal management strategies for different oligometastatic sites have not been established. Additionally, the development of personalized therapies for individual patients with oligometastatic NSCLC to improve their quality of life and overall survival should also be addressed. Here, we review relevant articles on the management of patients with oligometastatic NSCLC and categorize the disease according to the site of metastases. Ongoing trials are also summarized to determine future directions and expectations for new treatment modalities to improve patient management.

Development of Biomarker Signatures Associated with Anoikis to Predict Prognosis in Endometrial Carcinoma Patients

Purpose

To generate a signature based on anoikis-related genes (ARGs) for endometrial carcinoma (EC) patients and elucidate the molecular mechanisms in EC.

Methods

On the basis of TCGA-UCEC dataset, we identified specific anoikis-related genes (ARGs) in EC. Cox-relative regression methods were used to generate an anoikis-related signature (ARS). The possible biological pathways of ARS-related genes were analyzed by GSEA. The clinical potency and immune status of ARS were analyzed by CIBERSORT method, ssGSEA algorithm, Tumor Immune Dysfunction and Exclusion (TIDE) analysis. Moreover, the expression patterns of ARS genes were verified by HPA database.

Results

Seven anoikis genes (CDKN2A, E2F1, ENDOG, EZH2, HMGA1, PLK1, and SLC2A1) were determined to develop a prognostic ARS. Both genes of ARS were closely bound up with the prognosis of EC patients. The ARS could accurately classify EC cases with different clinical outcome and mirror the specific immune status of EC. We observed that ARS-high patients could not benefit from immunotherapy. Finally, all the hub genes of ARS were proved to be upregulated in EC tissues by immunohistology.

Conclusion

ARS can be used to stratify the risk and forecast the survival outcome of EC patients and provide prominent reference for individualized treatment in EC.