Upregulation of SPP1 Is a Marker for Poor Lung Cancer Prognosis and Contributes to Cancer Progression and Cisplatin Resistance

SPP1 represents a therapeutic target that promotes the progression of oesophageal squamous cell carcinoma by driving M2 macrophage infiltration

BACKGROUND

Tumour-associated macrophages (TAMs) are an important component of the tumour microenvironment (TME). However, the crosstalk between oesophageal squamous cell carcinoma (ESCC) cells and TAMs remains largely unexplored.

METHODS

Clinical samples and the TCGA database were used to evaluate the relevance of SPP1 and TAM infiltration in ESCC. Mouse models were constructed to investigate the roles of macrophages educated by SPP1 in ESCC. Macrophage phenotypes were determined using qRT‒PCR and immunohistochemical staining. RNA sequencing was performed to elucidate the mechanism.

RESULTS

Increasing expression of SPP1 correlated with M2-like TAM accumulation in ESCC, and they both predicted poor prognosis in the ESCC cohort. Knockdown of SPP1 significantly inhibited the infiltration of M2 TAMs in xenograft tumours. In vivo mouse model experiments showed that SPP1-mediated education of macrophages plays an essential role in the progression of ESCC. Mechanistically, SPP1 recruited macrophages and promoted M2 polarisation via CD44/PI3K/AKT signalling activation and then induced VEGFA and IL6 secretion to sustain ESCC progression. Finally, blockade of SPP1 with RNA aptamer significantly inhibited tumour growth and M2 TAM infiltration in xenograft mouse models.

CONCLUSIONS

This study highlights SPP1-mediated crosstalk between ESCC cells and TAMs in ESCC. SPP1 could serve as a potential target in ESCC therapy.

Macrophage diversity in human cancers: New insight provided by single-cell resolution and spatial context

M1/M2 paradigm of macrophage plasticity has existed for decades. Now it becomes clear that this dichotomy doesn't adequately reflect the diversity of macrophage phenotypes in tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are a major population of innate immune cells in the TME that promotes tumor cell proliferation, angiogenesis and lymphangiogenesis, invasion and metastatic niche formation, as well as response to anti-tumor therapy. However, the fundamental restriction in therapeutic TAM targeting is the limited knowledge about the specific TAM states in distinct human cancer types. Here we summarized the results of the most recent studies that use advanced technologies (e.g. single-cell RNA sequencing and spatial transcriptomics) allowing to decipher novel functional subsets of TAMs in numerous human cancers. The transcriptomic profiles of these TAM subsets and their clinical significance were described. We emphasized the characteristics of specific TAM subpopulations - TREM2+, SPP1+, MARCO+, FOLR2+, SIGLEC1+, APOC1+, C1QC+, and others, which have been most extensively characterized in several cancers, and are associated with cancer prognosis. Spatial transcriptomics technologies defined specific spatial interactions between TAMs and other cell types, especially fibroblasts, in tumors. Spatial transcriptomics methods were also applied to identify markers of immunotherapy response, which are expressed by macrophages or in the macrophage-abundant regions. We highlighted the perspectives for novel techniques that utilize spatial and single cell resolution in investigating new ligand-receptor interactions for effective immunotherapy based on TAM-targeting.

A programmed cell death-related gene signature to predict prognosis and therapeutic responses in liver hepatocellular carcinoma

BACKGROUND

Programmed cell death (PCD) functions critically in cancers and PCD-related genes are associated with tumor microenvironment (TME), prognosis and therapeutic responses of cancer patients. This study stratified hepatocellular carcinoma (HCC) patients and develop a prognostic model for predicting prognosis and therapeutic responses.

METHODS

Consensus clustering analysis was performed to subtype HCC patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) among the subtypes were filtered and subjected to the least absolute shrinkage and selection operator (LASSO) regression analysis and univariate Cox regression analysis to filter prognostic genes. A PCD-related prognostic gene signature in TCGA was constructed and validated in ICGC-LIRI-JP and GSE14520 datasets. TME was analyzed using CIBERSORT, MCP-counter, TIMER and EPIC algorithms. Drug sensitivity was predicted by oncoPredict package. Spearman analysis was used to detect correlation.

RESULTS

Four molecular subtypes were categorized based on PCD-related genes. Subtype C1 showed the poorest prognosis, the most infiltration of Fibroblasts, dentritic cell (DC) and cancer-associated fibroblasts (CAFs), and the highest TIDE score. C4 had a better prognosis survival outcome, and lowest immune cell infiltration. The survival outcomes of C2 and C3 were intermediate. Next, a total of 69 co-DEGs were screened among the four subtypes and subsequently we identified five prognostic genes (MCM2, SPP1, S100A9, MSC and EPO) for developing the prognostic model. High-risk patients not only had unfavorable prognosis, higher clinical stage and grade, and more inflammatory pathway enrichment, but also possessed higher possibility of immune escape and were more sensitive to Cisplatin and 5. Fluorouracil. The robustness of the prognostic model was validated in external datasets.

CONCLUSION

This study provides new insights into clinical subtyping and the PCD-related prognostic signature may serve as a useful tool to predict prognosis and guide treatments for patients with HCC.

Overexpression of SPP1 is a prognostic indicator of immune infiltration in lung adenocarcinoma

OBJECTIVE

The extracellular phosphoprotein, secreted phosphoprotein 1 (SPP1), plays a crucial role in various tumors and regulating the immune system. This study aimed to evaluate its prognostic value and relationship to immune infiltration in lung adenocarcinoma (LUAD).

METHODS

In the TCGA and GEO datasets, the information on clinic and transcriptome analysis of SPP1 in non-small-cell lung cancer (NSCLC) was examined accordingly. The association of SPP1 expression with overall survival and clinicopathologic characteristics was investigated by univariate and multivariate analysis. CancerSEA database was utilized to investigate the role of SPP1 at the cellular level by single-cell analysis. Additionally, the CIBERSORT algorithm was utilized to assess the correlation among the immune cells that infiltrated.

RESULTS

NSCLC tissues exhibited a notable rise in SPP1 expression compared with that of normal tissues. Furthermore, the overexpression of SPP1 was substantially associated with clinicopathological features and unfavorable survival outcomes in individuals with LUAD, whereas no such correlation was observed in lung squamous cell carcinoma. Immune cells that infiltrate tumors and their corresponding genes were associated with SPP1 expression levels in LUAD.

CONCLUSIONS

SPP1 is a reliable indicator for assessing LUAD immune infiltration status and prognosis. With this approach, SPP1 can help earlier LUAD diagnosis and act as a possible immunotherapy target.

SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies

NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment.

Integrating bulk-RNA sequencing and single-cell sequencing analyses to characterize adenosine-enriched tumor microenvironment landscape and develop an adenosine-related prognostic signature predicting immunotherapy in lung adenocarcinoma

The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.

Integrative bioinformatics analysis reveals ECM and nicotine-related genes in both LUAD and LUSC, but different lung fibrosis-related genes are involved in LUAD and LUSC

There are several bioinformatics studies related to lung cancer, but most of them have mainly focused on either microarray data or RNA-Seq data alone. In this study, we have combined both types of data to identify differentially expressed genes (DEGs) specific to lung cancer subtypes. We obtained six microarray datasets from the GEO and also the expression matrix of LUSC and LUAD from TCGA, which were analyzed by GEO2R tool and GEPIA2, respectively. Enrichment analyses of DEGs were performed using the Enrichr database. Protein module identification was done by MCODE plugin in cytoscape software. We identified 30 LUAD-specific, 17 LUSC-specific, and 17 DEGs shared between LUAD and LUSC. Enrichment analyses revealed that LUSC-specific DEGs are involved in lung fibrosis. In addition, DEGs shared between LUAD and LUSC are involved in extracellular matrix (ECM), nicotine metabolism, and lung fibrosis. We identified lung fibrosis-related genes, including SPP1, MMP9, and CXCL2, involved in both LUAD and LUSC, but SERPINA1 and PLAU genes involved only in LUSC. We also found an important module separately for LUAD-specific, LUSC-specific, and shared DEGs between LUSC and LUAD. S100P, GOLM, AGR2, AK1, TMEM125, SLC2A1, COL1A1, and GHR genes were significantly associated with survival. Our findings suggest that different lung fibrosis-related genes may play roles in LUSC and LUAD. Additionally, nicotine metabolism and ECM remodeling were found to be associated with both LUSC and LUAD, regardless of subtype, emphasizing the role of smoking in the development of lung cancer and ECM in the high aggressiveness and mortality of lung cancer.

Multi-Omics Reveals the Role of Osteopontin/Secreted Phosphoprotein 1 in Regulating Ovarian Aging

Secreted phosphoprotein 1 (SPP1), also known as osteopontin (OPN), is located on chromosome 4q22.1. This multifunctional secreted acidic glycoprotein is expressed intracellularly and extracellularly in various tissues, where it interacts with regulatory proteins and pro-inflammatory immune chemokines, contributing to the pathogenesis of multiple diseases. Nevertheless, the intricate genetic connections between SPP1 and ovarian aging remain largely unexplored. This study aims to bridge this knowledge gap by delving into ovarian aging and its associations with SPP1 using multi-omics data analysis. Our findings indicate that SPP1 is a potential gene related to ovarian aging. To comprehend the role of SPP1, we conducted spatial transcriptomic analyses on young and aged female mouse ovaries, revealing a significant decline in SPP1 expression in the aging group compared to the young group. Similarly, a significantly low level of SPP1 was found in the 73-year-old sample. Additionally, in-depth single-cell RNA-sequencing analysis identified associations between SPP1 and ITGAV, ITGB1, CD44, MMP3, and FN1. Notably, co-expression analysis highlighted a strong correlation between SPP1 and ITGB1. In summary, this study pioneers the identification of SPP1 as a gene implicated in ovarian aging. Further research into the role of SPP1 has the potential to advance precision medicine and improve treatment strategies for ovarian aging-related conditions.

[Role of SPP1 in acute kidney injury induced by renal ischemia-reperfusion in rats]

OBJECTIVE

To investigate the role of SPP1 gene in acute kidney injury induced by renal ischemia-reperfusion injury (IRI).

METHODS

Twelve Sprague-Dawley rats were randomly divided into sham group and IRI group (n=6) and subjected to sham operation and renal ischemia for 30 min induced by penal pedicle clamping using non-traumatic microvascular clamps, respectively.Serum creatinine and blood urea nitrogen levels were detected, and PAS staining was used for pathological examination of the kidneys in the two groups.The renal expressions of SPP1, α-SMA and caspase-3 were detected using immunohistochemistry and immunofluorescent staining.In cultured renal tubular epithelial cells (HK-2 cells), Western blotting was performed to detect the changes in expressions of SPP1, caspase-3, and Kim-1 proteins following hypoxiareoxygenation (H/R) and transfection with si-NC or si-SPP1;flow cytometry was employed to analyze apoptosis of the treated cells.

RESULTS

Renal IRI caused significant elevations of serum creatinine and blood urea nitrogen levels (P<0.05) and induced severe shedding and necrosis of the renal tubular epithelial cells in the rats, resulting also in significantly up-regulated renal expressions of SPP1, α-SMA and caspase-3(P<0.05).In HK-2 cells, H/R significantly increased the protein expression levels of SPP1, caspase-3, and Kim-1(P<0.05), and compared si-NC transfection, transfection with SPP1 obviously reduced caspase-3 and Kim-1 expressions and lowered apoptosis rate of the cells with H/R exposure (P<0.05).

CONCLUSION

SPP1 is up-regulated in the kidneys of rats with renal IRI, and down-regulation of SPP1 expression can inhibit H/R-induced apoptosis of renal tubular epithelial cells.

Biomarkers of lung cancer for screening and in never-smokers-a narrative review

Background and Objective

Lung cancer is the leading cause of cancer-related mortality worldwide, partially attributed to late-stage diagnoses. In order to mitigate this, lung cancer screening (LCS) of high-risk patients is performed using low dose computed tomography (CT) scans, however this method is burdened by high false-positive rates and radiation exposure for patients. Further, screening programs focus on individuals with heavy smoking histories, and as such, never-smokers who may otherwise be at risk of lung cancer are often overlooked. To resolve these limitations, biomarkers have been posited as potential supplements or replacements to low-dose CT, and as such, a large body of research in this area has been produced. However, comparatively little information exists on their clinical efficacy and how this compares to current LCS strategies.

Methods

Here we conduct a search and narrative review of current literature surrounding biomarkers of lung cancer to supplement LCS, and biomarkers of lung cancer in never-smokers (LCINS).

Key Content and Findings

Many potential biomarkers of lung cancer have been identified with varying levels of sensitivity, specificity, clinical efficacy, and supporting evidence. Of the markers identified, multi-target panels of circulating microRNAs, lipids, and metabolites are likely the most clinically efficacious markers to aid current screening programs, as these provide the highest sensitivity and specificity for lung cancer detection. However, circulating lipid and metabolite levels are known to vary in numerous systemic pathologies, highlighting the need for further validation in large cohort randomised studies.

Conclusions

Lung cancer biomarkers is a fast-expanding area of research and numerous biomarkers with potential clinical applications have been identified. However, in all cases the level of evidence supporting clinical efficacy is not yet at a level at which it can be translated to clinical practice. The priority now should be to validate existing candidate markers in appropriate clinical contexts and work to integrating these into clinical practice.

Identification of Hub Genes in Idiopathic Pulmonary Fibrosis and Their Association with Lung Cancer by Bioinformatics Analysis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and irreversible disease with a high mortality rate worldwide. However, the etiology and pathogenesis of IPF have not yet been fully described. Moreover, lung cancer is a significant complication of IPF and is associated with increased mortality. Nevertheless, identifying common genes involved in developing IPF and its progression to lung cancer remains an unmet need. The present study aimed to identify hub genes related to the development of IPF by meta-analysis. In addition, we analyzed their expression and their relationship with patients' progression in lung cancer.

METHOD

Microarray datasets GSE24206, GSE21369, GSE110147, GSE72073, and GSE32539 were downloaded from Gene Expression Omnibus (GEO). Next, we conducted a series of bioinformatics analysis to explore possible hub genes in IPF and evaluated the expression of hub genes in lung cancer and their relationship with the progression of different stages of cancer.

RESULTS

A total of 1888 differentially expressed genes (DEGs) were identified, including 1105 upregulated and 783 downregulated genes. The 10 hub genes that exhibited a high degree of connectivity from the PPI network were identified. Analysis of the KEGG pathways showed that hub genes correlate with pathways such as the ECM-receptor interaction. Finally, we found that these hub genes are expressed in lung cancer and are associated with the progression of different stages of lung cancer.

CONCLUSIONS

Based on the integration of GEO microarray datasets, the present study identified DEGs and hub genes that could play an essential role in the pathogenesis of IPF and its association with the development of lung cancer in these patients, which could be considered potential diagnostic biomarkers or therapeutic targets for the disease.

Role of SPP1 in the diagnosis of gastrointestinal cancer

Recently, the incidence rate of digestive system tumors has increased in China and these tumors occur in a younger population. The present study aimed to determine the expression levels and potential clinical value of secreted phosphoprotein 1 (SPP1) in gastrointestinal cancer. The microarray datasets GSE104836, GSE189830 and GSE103236, obtained from the gene expression omnibus database, were analyzed to determine differentially expressed genes in patients with colorectal cancer (CRC), gastric cancer (GC) and esophageal cancer (EC). A total of 42 patients with CRC, GC or EC and 21 healthy controls were recruited to obtain blood and tissues samples. SPP1 expression levels were detected using reverse transcription-quantitative PCR. Moreover, levels of significance of SPP1 in patients with CRC, GC and EC were analyzed using receiver operating characteristic analysis. Potential correlations between SPP1 and carcinoembryonic antigen (CEA) were assessed using Pearson's correlation coefficient. SPP1 was significantly upregulated in the serum, plasma and tissue of patients with CRC, GC or EC. In addition, the area under the curve of SPP1 was >0.5 in the plasma, serum and cancer tissue of patients with early and late CRC, GC or EC. The present study further demonstrated that the specificity and sensitivity of SPP1 was higher in patients with late CRC, GC or EC compared with patients with early CRC, GC or EC. Moreover, SPP1 and CEA were significantly positively correlated in serum of patients with CRC, GC or EC. In conclusion, the current study demonstrated that SPP1 exhibited significant diagnostic value for gastrointestinal tumors, which suggested that SPP1 may exhibit potential as a diagnostic marker of CRC, GC and EC. The present study provided a novel theoretical basis for the role of SPP1 as a diagnostic marker of digestive system tumors.

Immune microenvironment analysis and novel biomarkers of early-stage lung adenocarcinoma evolution

Background

Lung cancer is the deadliest and most diagnosed type of cancer worldwide. The 5-year survival rate of lung adenocarcinoma (LUAD) dropped significantly when tumor stages advanced. Patients who received surgically resecting at the pre-invasive stage had a 5-year survival rate of nearly 100%. However, the study on the differences in gene expression profiles and immune microenvironment among pre-invasive LUAD patients is still lacking.

Methods

In this study, the gene expression profiles of three pre-invasive LUAD stages were compared using the RNA-sequencing data of 10 adenocarcinoma in situ (AIS) samples, 12 minimally invasive adenocarcinoma (MIA) samples, and 10 invasive adenocarcinoma (IAC) samples.

Results

The high expression levels of PTGFRN (Hazard Ratio [HR] = 1.45; 95% Confidence Interval [CI]: 1.08-1.94; log-rank P = 0.013) and SPP1 (HR = 1.44; 95% CI: 1.07-1.93; log-rank P = 0.015) were identified to be associated with LUAD prognosis. Moreover, the early LUAD invasion was accompanied by the enhancement of antigen presentation ability, reflected by the increase of myeloid dendritic cells infiltration rate (Cuzick test P < 0.01) and the upregulation of seven important genes participating in the antigen presentation, including HLA-A (Cuzick test P = 0.03), MICA (Cuzick test P = 0.01), MICB (Cuzick test P = 0.01), HLA-DPA1 (Cuzick test P = 0.04), HLA-DQA2 (Cuzick test P < 0.01), HLA-DQB1 (Cuzick test P = 0.03), and HLA-DQB2 (Cuzick test P < 0.01). However, the tumor-killing ability of the immune system was inhibited during this process, as there were no rising cytotoxic T cell activity (Cuzick test P = 0.20) and no increasing expression in genes encoding cytotoxic proteins.

Conclusion

In all, our research elucidated the changes in the immune microenvironment during early-stage LUAD evolution and may provide a theoretical basis for developing novel early-stage lung cancer therapeutic targets.

Important oncogenic and immunogenic roles of SPP1 and CSF1 in hepatocellular carcinoma

The treatment and prognosis of liver cancer remain the focus of medical research. Studies have shown that SPP1 and CSF1 play important roles in cell proliferation, invasion, and metastasis. Therefore, this study analyzed the oncogenic and immunologic roles of SPP1 and CSF1 in hepatocellular carcinoma (HCC). We found that the expression levels of SPP1 and CSF1 in HCC were markedly increased and positively correlated. High SPP1 expression was significantly associated with poor OS, DSS, PFS, and RFS. It was not affected by gender, alcohol use, HBV, or race, whereas CSF1 was affected by these factors. Higher expression levels of SPP1 and CSF1 indicated higher levels of immune cell infiltration and a higher immune score with the R software package ESTIMATE. Further analysis revealed that many genes work co-expressed between SPP1 and CSF1 with the LinkedOmics database, which were mainly involved in signal transduction, the integral components of the membrane, protein binding, and osteoclast differentiation. In addition, we screened ten hub genes using cytoHubba, among which the expression of four genes was significantly associated with the prognosis of HCC patients. Finally, we demonstrated the oncogenic and immunologic roles of SPP1 and CSF1 using the vitro experiments. Reducing the expression of either SPP1 or CSF1 could significantly reduce the proliferation of HCC cells and the expression of CSF1, SPP1, and the other four hub genes. This study suggested that SPP1 and CSF1 interact with each other and have the potential to be therapeutic and prognostic targets for HCC.

Construction and analysis of a conjunctive diagnostic model of HNSCC with random forest and artificial neural network

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous tumor that is highly aggressive and ranks fifth among the most common cancers worldwide. Although, the researches that attempted to construct a diagnostic model were deficient in HNSCC. Currently, the gold standard for diagnosing head and neck tumors is pathology, but this requires a traumatic biopsy. There is still a lack of a noninvasive test for such a high-incidence tumor. In order to screen genetic markers and construct diagnostic model, the methods of random forest (RF) and artificial neural network (ANN) were utilized. The data of HNSCC gene expression was accessed from Gene Expression Omnibus (GEO) database; we selected three datasets totally, and we combined 2 datasets (GSE6631 and GSE55547) for screening differentially expressed genes (DEGs) and chose another dataset (GSE13399) for validation. Firstly, the 6 DEGs (CRISP3, SPINK5, KRT4, MMP1, MAL, SPP1) were screened by RF. Subsequently, ANN was applied to calculate the weights of 6 genes. Besides, we created a diagnostic model and nominated it as neuralHNSCC, and the performance of neuralHNSCC by area under curve (AUC) was verified using another dataset. Our model achieved an AUC of 0.998 in the training cohort, and 0.734 in the validation cohort. Furthermore, we used the Cell-type Identification using Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm to investigate the difference in immune cell infiltration between HNSCC and normal tissues initially. The selected 6 DEGs and the constructed novel diagnostic model of HNSCC would make contributions to the diagnosis.

Single-Cell RNA Sequencing Analysis of Gene Regulatory Network Changes in the Development of Lung Adenocarcinoma

Lung cancer is a highly heterogeneous disease. Cancer cells and other cells within the tumor microenvironment interact to determine disease progression, as well as response to or escape from treatment. Understanding the regulatory relationship between cancer cells and their tumor microenvironment in lung adenocarcinoma is of great significance for exploring the heterogeneity of the tumor microenvironment and its role in the genesis and development of lung adenocarcinoma. This work uses public single-cell transcriptome data (distant normal, nLung; early LUAD, tLung; advanced LUAD, tL/B), to draft a cell map of lung adenocarcinoma from onset to progression, and provide a cell-cell communication view of lung adenocarcinoma in the different disease stages. Based on the analysis of cell populations, it was found that the proportion of macrophages was significantly reduced in the development of lung adenocarcinoma, and patients with lower proportions of macrophages exhibited poor prognosis. We therefore constructed a process to screen an intercellular gene regulatory network that reduces any error generated by single cell communication analysis and increases the credibility of selected cell communication signals. Based on the key regulatory signals in the macrophage-tumor cell regulatory network, we performed a pseudotime analysis of the macrophages and found that signal molecules (TIMP1, VEGFA, SPP1) are highly expressed in immunosuppression-associated macrophages. These molecules were also validated using an independent dataset and were significantly associated with poor prognosis. Our study provides an effective method for screening the key regulatory signals in the tumor microenvironment and the selected signal molecules may serve as a reference to guide the development of diagnostic biomarkers for risk stratification and therapeutic targets for lung adenocarcinoma.

Critical transition and reversion of tumorigenesis

Cancer is caused by the accumulation of genetic alterations and therefore has been historically considered to be irreversible. Intriguingly, several studies have reported that cancer cells can be reversed to be normal cells under certain circumstances. Despite these experimental observations, conceptual and theoretical frameworks that explain these phenomena and enable their exploration in a systematic way are lacking. In this review, we provide an overview of cancer reversion studies and describe recent advancements in systems biological approaches based on attractor landscape analysis. We suggest that the critical transition in tumorigenesis is an important clue for achieving cancer reversion. During tumorigenesis, a critical transition may occur at a tipping point, where cells undergo abrupt changes and reach a new equilibrium state that is determined by complex intracellular regulatory events. We introduce a conceptual framework based on attractor landscapes through which we can investigate the critical transition in tumorigenesis and induce its reversion by combining intracellular molecular perturbation and extracellular signaling controls. Finally, we present a cancer reversion therapy approach that may be a paradigm-changing alternative to current cancer cell-killing therapies.

Lipopolysaccharide and lipoteichoic acid regulate the PI3K/AKT pathway through osteopontin/integrin β3 to promote malignant progression of non-small cell lung cancer

Background

Lung cancer (LC) is a malignancy with one of the highest mortality rates. Respiratory microbiota is considered to play a key role in the development of LC, but the molecular mechanisms are rarely studied.

Methods

We used lipopolysaccharide (LPS) and lipoteichoic acid (LTA) to study human lung cancer cell lines PC9 and H1299. The gene expression of CXC chemokine ligand (CXCL)1/6, interleukin (IL)-6, IL-8, and tumor necrosis factor (TNF)-α were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). The Cell-Counting Kit 8 (CCK-8) was used to analyze cell proliferation. Transwell assays were performed to analyze cell migration ability. Flow cytometry was used to observe cell apoptosis. Western blot and qRT-PCR were used to analyze the expression of secreted phosphoprotein 1 (SPP1), toll-like receptor (TLR)-2/4, and NLR family pyrin domain containing 3 (NLRP3) to determine the mechanism of LPS + LTA. We evaluated the effect of LPS + LTA on cisplatin sensibility by analyzing cell proliferation, apoptosis, and caspase-3/9 expression levels. We observed the proliferation activity, apoptosis, and migration ability of cells in which SPP1 had been transfected small interfering (si) negative control (NC) and integrin β3 siRNA. Then the mRNA expression level and protein expression of PI3K, AKT, and ERK were analyzed. Finally, the nude mouse tumor transplantation model was conducted to verify.

Results

We studied that in two cell lines, the expression level of inflammatory factors in LPS+LTA group was significantly higher than that in single treatment group (P<0.001). We explored LPS + LTA combined treatment group significantly increased the expression of NLRP3 and genes and proteins. LPS + LTA + Cisplatin group could significantly reduce the inhibitory effect of LPS on cell proliferation (P<0.001), reduce the apoptosis rate (P<0.001) and significantly reduce the expression levels of caspase-3/9 (P<0.001) compared with Cisplatin group. Finally, we verified that LPS and LTA could increase osteopontin (OPN)/integrin β3 expression and activate the PI3K/AKT pathway to promote malignant progression of LC in vitro studies.

Conclusions

This study provides a theoretical basis for further exploration of the influence of lung microbiota on NSCLC and the optimization of LC treatment in the future.

Clinical features and molecular genetics associated with brain metastasis in suspected early-stage non-small cell lung cancer

Introduction

Regarding whether brain magnetic resonance imaging (MRI) should be routine in patients with suspected early-stage lung cancer, guideline recommendations are inconsistent. Therefore, we performed this study to evaluate the incidence of and risk factors for brain metastasis (BM) in patients with suspected early-stage non-small-cell lung cancer (NSCLC).

Methods

A review of the medical charts of consecutive NSCLC patients diagnosed between January 2006 and May 2020 was performed. We identified 1,382 NSCLC patients with clinical staging of T1/2aN0M0 (excluding BM), and investigated the incidence, clinical predictors, and prognosis of BM in the cohort. We also performed RNA-sequencing differential expression analysis using transcriptome of 8 patients, using DESeq2 package (version 1.32.0) with R (version 4.1.0).

Results

Among 1,382 patients, nine hundred forty-nine patients (68.7%) underwent brain MRI during staging, and 34 patients (3.6%) were shown to have BM. Firth's bias-reduced logistic regression showed that tumor size (OR 1.056; 95% CI 1.009-1.106, p=0.018) was the only predictor of BM, and pathologic type was not a predictor of BM in our cohort (p>0.05). The median overall survival for patients with brain metastasis was 5.5 years, which is better than previously reported in the literature. RNA-sequencing differential expression analysis revealed the top 10 significantly upregulated genes and top 10 significantly downregulated genes. Among the genes involved in BM, Unc-79 homolog, non-selective sodium leak channel (NALCN) channel complex subunit (UNC79) was the most highly expressed gene in the lung adenocarcinoma tissues from the BM group, and an in vitro assay using A549 cells revealed that the NALCN inhibitor suppressed lung cancer cell proliferation and migration.

Conclusions

Given the incidence and favorable outcome of BM in patients with suspected early-stage NSCLC, selective screening with brain MRI may be considered, especially in patients with high-risk features.

Autoencoder Networks Decipher the Association between Lung Cancer and Alzheimer’s Disease

Lung cancer is the most common malignancy and is responsible for the largest cancer-related mortality worldwide. Alzheimer’s disease is a degenerative neurological disease that burdens healthcare worldwide. While the two diseases are distinct, several transcriptomic studies have demonstrated they are linked. However, no concordant conclusion on how they are associated has been drawn. Since these studies utilized conventional bioinformatics methods, such as the differentially expressed gene (DEG) analysis, it is naturally expected that the proportion of DEGs having either the same or inverse directions in lung cancer and Alzheimer’s disease is substantial. This raises the inconsistency. Therefore, a novel bioinformatics method capable of determining the direction of association is desirable. In this study, the moderated t-tests were first used to identify DEGs that are shared by the two diseases. For the shared DEGs, separate autoencoder (AE) networks were trained to extract a one-dimensional representation (pseudogene) for each disease. Based on these pseudogenes, the association direction between lung cancer and Alzheimer’s disease was inferred. AE networks based on 266 shared DEGs revealed a comorbidity relationship between Alzheimer’s disease and lung cancer. Specifically, Spearman’s correlation coefficient between the predicted values using the two AE networks for the Alzheimer’s disease test set was 0.825 and for the lung cancer test set was 0.316. Novel bioinformatics methods such as an AE network may help decipher how distinct diseases are associated by providing the refined representations of dysregulated genes.

SPP1 facilitates cell migration and invasion by targeting COL11A1 in lung adenocarcinoma

Background

Secreted phosphoprotein 1 (SPP1), an extracellular secreted glycol phosphoprotein, is closely related to tumor biologies, such as proliferation, migration, and invasion. However, the role and biological function of SPP1 in lung adenocarcinoma (LUAD) was still ambiguous.

Methods

SPP1 expression in LUAD tissues and its associations with clinical features and prognosis was investigated using meta-analysis, immunohistochemistry (IHC) staining methods, and quantitative real-time polymerase chain reaction (qRT-PCR). Moreover, the potential mechanism related to SPP1 was identified by using the Gene Set Enrichment Analysis (GSEA) method. A series of function assays were conducted to determine the biological role of SPP1 in LUAD cell migration and invasion in vitro and vivo. The co-expressed genes of SPP1 were obtained and verified by western blot assays. The influence of SPP1 on Collagen type XI alpha 1 (COL11A1) expression and epithelial-mesenchymal transition (EMT) markers was analyzed using western blot assays.

Results

The expression of SPP1 in LUAD tissues and cells was significantly higher than that in normal tissues and cells. And positively associations of SPP1 expression with TNM stage, lymph node metastasis, and invasion depth were observed. Patients with high SPP1 expression had unfavorable survival. The multivariable Cox regression analysis revealed that SPP1 expression was an independent prognostic factor of LUAD patients. Furthermore, downregulation of SPP1 could inhibit cell migration and invasion both in vitro and vivo, reduce the expression of epithelial marker (E-cadherin), and increase the expression of mesenchymal markers (N-cadherin and vimentin). Using bioinformatics and western blot assays, we confirmed that COL11A1 acted as the downstream of SPP1, and SPP1 knockdown could significantly downregulate the COL11A1 expression. Importantly, suppression of cell migration and invasion and the expression changes of EMT markers induced by SPP1 downregulation could be reversed by COL11A1 overexpression.

Conclusions

SPP1 facilitates cell migration and invasion by upregulating COL11A1 expression and that acts as a potential biomarker of metastasis and prognosis for LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02749-x.

The small molecule chemical compound cinobufotalin attenuates resistance to DDP by inducing ENKUR expression to suppress MYH9-mediated c-Myc deubiquitination in lung adenocarcinoma

The small molecule chemical compound cinobufotalin (CB) is reported to be a potential antitumour drug that increases cisplatin (DDP) sensitivity in nasopharyngeal carcinoma. In this study, we first found that CB decreased DDP resistance, migration and invasion in lung adenocarcinoma (LUAD). Mechanistic studies showed that CB induced ENKUR expression by suppressing PI3K/AKT signalling to downregulate c-Jun, a negative transcription factor of ENKUR. Furthermore, ENKUR was shown to function as a tumour suppressor by binding to β-catenin to decrease c-Jun expression, thus suppressing MYH9 transcription. Interestingly, MYH9 is a binding protein of ENKUR. The Enkurin domain of ENKUR binds to MYH9, and the Myosin_tail of MYH9 binds to ENKUR. Downregulation of MYH9 reduced the recruitment of the deubiquitinase USP7, leading to increased c-Myc ubiquitination and degradation, decreased c-Myc nuclear translocation, and inactivation of epithelial-mesenchymal transition (EMT) signalling, thus attenuating DDP resistance. Our data demonstrated that CB is a promising antitumour drug and may be a candidate chemotherapeutic drug for LUAD patients.

Secreted phosphoprotein 1 promotes angiogenesis of glioblastoma through upregulating PSMA expression via transcription factor HIF-1&alpha;

Glioblastoma multiforme (GBM) is a highly vascularized malignant brain tumor. Our previous study showed that prostate-specific membrane antigen (PSMA) promotes angiogenesis of GBM. However, the specific mechanism underlying GBM-induced PSMA upregulation remains unclear. In this study, we demonstrate that the GBM-secreted cytokine phosphoprotein 1 (SPP1) can regulate the expression of PSMA in human umbilical vein endothelial cells (HUVECs). Our mechanistic study further reveals that SPP1 regulates the expression of PSMA through the transcription factor HIF1α. Moreover, SPP1 promotes HUVEC migration and tube formation. In addition, HIF1α knockdown reduces the expression of PSMA in HUVECs and blocks the ability of SPP1 to promote HUVEC migration and tube formation. We further confirm that SPP1 is abundantly expressed in GBM, is associated with poor prognosis, and has high clinical diagnostic value with considerable sensitivity and specificity. Collectively, our findings identify that the GBM-secreted cytokine SPP1 upregulates PSMA expression in endothelial cells via the transcription factor HIF1α, providing insight into the angiogenic process and promising candidates for targeted GBM therapy.

Single Cell RNA-Seq Identifies Immune-Related Prognostic Model and Key Signature-SPP1 in Pancreatic Ductal Adenocarcinoma

There are no reliable biomarkers for early diagnosis or prognosis evaluation in pancreatic ductal adenocarcinoma (PDAC). Multiple scRNA-seq datasets for PDAC were retrieved from online databases and combined with scRNA-seq results from our previous study. The malignant ductal cells were identified through calculating copy number variation (CNV) scores. The robust markers of malignant ductal cells in PDAC were found. Five immune-related signatures, including SPP1, LINC00683, SNHG10, LINC00237, and CASC19, were used to develop a risk score formula to predict the overall survival of PDAC patients. We also constructed an easy-to-use nomogram, combining risk score, N stage, and margin status. The expression level of SPP1 was related to the prognosis and immune regulators. We found that SPP1 was mainly expressed in ductal cells and macrophages in PDAC. In conclusion, we constructed a promising prognostic model based on immune-related signatures for PDAC using scRNA-seq and TCGA_PAAD datasets.

Serum anti-SPP1 autoantibody as a potential novel biomarker in detection of esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) has poor prognosis mainly due to lacking of effective diagnostic biomarkers. Aberrant expression of secreted phosphoprotein 1 (SPP1) protein has been observed in several cancers. The purpose of this study is to assess the feasibility of serum autoantibody to SPP1 in detection of ESCC.

Methods

The SPP1 protein levels in 108 ESCC tissues and 72 adjacent normal tissues were analyzed by immunohistochemistry. Discovery group containing 62 serum samples from ESCC patients and 62 serum samples from normal controls (NC) were used to detect the levels of anti-SPP1 autoantibody by enzyme-linked immunosorbent assay (ELISA). Validation group containing another 100 ESCC and 100 NC serum samples were tested to confirm the levels of autoantibody to SPP1. Western blotting was performed to further confirm the results of ELISA.

Results

SPP1 protein was significantly overexpressed in ESCC tissues compared to adjacent normal tissues. ELISA results showed that serum autoantibody to SPP1 was significantly increased in ESCC compared to NC in both discovery and validation groups. Autoantibody to SPP1 could discriminate patients with ESCC from NC with the area under curve (AUC) values of 0.653 and 0.739 in discovery and validation group, respectively. The results of ELISA and the occurrence of immunoreactivity to SPP1 in ESCC sera were confirmed by western blotting.

Conclusion

Our study indicated the potential significance of anti-SPP1 autoantibody as a novel biomarker for detection of ESCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10012-9.

Comprehensive Analysis of Histone Modifications in Hepatocellular Carcinoma Reveals Different Subtypes and Key Prognostic Models

Histone modification, an important epigenetic mechanism, is related to the carcinogenesis of hepatocellular carcinoma (HCC). In three datasets, we screened 88 epigenetic-dysregulated PCGs (epi-PCGs) , which were significantly associated with HCC survival and could cluster HCC into three molecular subtypes. These subtypes were associated with prognosis, immunomodulatory alterations, and response to different treatment strategies. Based on 88 epi-PCGs in the TCGA training set, a risk prediction model composed of 4 epi-PCGs was established. The model was closely related to the clinicopathological features and showed a strong predictive ability in different clinical subgroups. In addition, the risk prediction model was an independent prognostic factor for patients with HCC. The significance of epi-PCGs in HCC is revealed by our data analysis.

An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

Simple Summary

Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology.

Abstract

Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.

Single-cell RNA-seq dissecting heterogeneity of tumor cells and comprehensive dynamics in tumor microenvironment during lymph nodes metastasis in gastric cancer

Lymph node metastasis is the common metastasis route of gastric cancer. However, until now, heterogeneities of tumor cells and tumor microenvironment in primary tumors (PT) and metastatic lymph nodes (MLN) of gastric cancer (GC) remains uncharacterized. In this study, scRNA-seq was performed on tissues from PT and MLN of gastric cancer. Trajectory analysis and function enrichment analyses were conducted to decode the underlying mechanisms contributing to LN metastasis of gastric cancer. Heterogeneous composition of immune cells and distant intercellular interactions in PT and MLN were analyzed. Based on the generated single cell transcriptome profiles, dynamics of gene expressions in cancer cells between PT and MLN were characterized. Moreover, we reconstructed the developmental trajectory of GC cells' metastasis to LN and identified two sub-types of GC cells with distinct potentials of having malignant biological behaviors. We characterized the repression of neutrophil polarization associated genes, like LCN2, which would contribute to LN metastasis, and histochemistry experiments validated our findings. Additionally, heterogeneity in neutrophils, rather than macrophages, was characterized. Immune checkpoint associated interaction of SPP1 was found active in MLN. In conclusion, we decode the dynamics of tumor cells during LN metastasis in GC and to identify a sub-type of GC cells with potentials of LN metastasis. Our data indicated that the disordering the neutrophils polarization and maturation and the activation of immune checkpoint SPP1 might contribute to LN metastasis in GC, providing a novel insight on the mechanism and potential therapeutic targets of LN metastasis in GC. This article is protected by copyright. All rights reserved.

mRNA Network: Solution for Tracking Chemotherapy Insensitivity in Small-Cell Lung Cancer

Background

Small-cell lung cancer (SCLC) has poor prognosis and is prone to drug resistance. It is necessary to search for possible influencing factors for SCLC chemotherapy insensitivity. Therefore, we proposed an mRNA network to track the chemotherapy insensitivity in SCLC.

Methods

Six samples of patients with SCLC were recruited for RNA sequencing. TopHat2 and Cufflinks were used to make differential analysis. Functional analysis was applied as well. Finally, multidimensional validation was applied for verifying the results we obtained by experiment.

Results

This study was a trial of drug resistance in 6 SCLC patients after first-line chemotherapy. The top 10 downregulated genes differentially expressed in the chemo-insensitive group were SERPING1, DRD5, PARVG, PRAME, NKX1-1, MCTP2, PID1, PLEKHA4, SPP1, and SLN. Cell-cell signaling by Wnt (p=6.98E - 21) was the most significantly enriched GO term in biological process, while systemic lupus erythematosus (p=6.97E - 10), alcoholism (p=1.01E - 09), and transcriptional misregulation in cancer (p=0.00227988) were the top three ones of KEGG pathways. In multiple public databases, we also highlighted and verified the vital role of glycolysis/gluconeogenesis pathway and corresponding genes in chemo-insensitivity in SCLC.

Conclusion

Our study confirmed some SCLC chemotherapy insensitivity-related genes, biological processes, and pathways, thus constructing the chemotherapy-insensitive network for SCLC.

Immune-Omics Networks of CD27, PD1, and PDL1 in Non-Small Cell Lung Cancer

To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. Major immune-checkpoint inhibitors (ICIs) have more DNA copy number variations (CNV) than mutations in The Cancer Genome Atlas (TCGA) NSCLC tumors. Nevertheless, CNV-mediated dysregulated gene expression in NSCLC is not well understood. Integrated CNV and transcriptional profiles in NSCLC tumors (n = 371) were analyzed using Boolean implication networks for the identification of a multi-omics CD27, PD1, and PDL1 network, containing novel prognostic genes and proliferation genes. A 5-gene (EIF2AK3, F2RL3, FOSL1, SLC25A26, and SPP1) prognostic model was developed and validated for patient stratification (p < 0.02, Kaplan-Meier analyses) in NSCLC tumors (n = 1163). A total of 13 genes (COPA, CSE1L, EIF2B3, LSM3, MCM5, PMPCB, POLR1B, POLR2F, PSMC3, PSMD11, RPL32, RPS18, and SNRPE) had a significant impact on proliferation in 100% of the NSCLC cell lines in both CRISPR-Cas9 (n = 78) and RNA interference (RNAi) assays (n = 92). Multiple identified genes were associated with chemoresponse and radiotherapy response in NSCLC cell lines (n = 117) and patient tumors (n = 966). Repurposing drugs were discovered based on this immune-omics network to improve NSCLC treatment.

Decreased Spp1 Expression in Acute Myocardial Infarction after Ischemia and Reperfusion Injury

BACKGROUND

With the progress of shock therapy and the establishment and promotion of methods such as thrombolytic therapy and percutaneous coronary intervention (PCI), many tissues and organs have been reperfused after ischemia which may cause even worse disorder called ischemia-reperfusion injury (IRI). mRNAs have been found to have significant impacts on ischemia-reperfusion through various mechanisms. In view of the accessibility of mRNAs from blood, we aimed to find the association between mRNA and ischemia-reperfusion.

METHODS

We used the GSE83472 dataset from the Gene Expression Omnibus (GEO) database to find differential RNA expression between ischemia-reperfusion tissue and control samples. In addition, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to find the biological property of 449 RNAs from GSE83472 via the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Besides, Gene Set Enrichment Analysis (GSEA), a tool to find the pathway orientation of a gene set, was used for further study in the four most significant KEGG pathways. Furthermore, we constructed a protein-protein interaction (PPI) network. In the end, we used quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting to measure and compare the expression of Spp1 in patients who accepted percutaneous coronary intervention.

RESULTS

The bioinformatics analyses suggested that Spp1 was a hub gene in reperfusion after ischemia. The qRT-PCR result showed that the Spp1 expression was significantly downregulated in ischemia-reperfusion cells after PCI compared with normal samples and so as the western blotting.

CONCLUSION

Spp1 might play an essential role in acute myocardial infarction after ischemia and reperfusion injury.