Integrated bioinformatics analysis of differentially expressed genes and immune cell infiltration characteristics in Esophageal Squamous cell carcinoma

SPP1 promotes tumor progression in esophageal carcinoma by activating focal adhesion pathway

Background

Recurrence and metastasis are the major obstacles affecting the therapeutic efficacy and clinical outcomes for patients with esophageal carcinoma (ESCA). Secreted phosphoprotein 1 (SPP1) is considered as a hub gene in ESCA and is negatively associated with disease-free survival (DFS) in ESCA. However, the exact roles and underlying mechanisms remain elusive. This study aims to examine the roles of SPP1 on ESCA, and elucidate the potential mechanisms.

Methods

Bioinformatics were used to analyze the expression of SPP1 in ESCA tissues, and its relations with clinicopathological characteristics and clinical prognosis in patients with ESCA based on The Cancer Genome Atlas (TCGA) dataset. Loss-of-function was conducted to examine the roles of SPP1 on malignant behaviors of ESCA cells by cell counting kit-8 (CCK8), plate clone, wound healing, and transwell assays. Gene set enrichment analysis (GSEA) was conducted to screen the pathways associated with SPP1 in ESCA. Then, the enriched pathway and the underlying mechanism were elucidated by western blotting, cell adhesion, and cell spreading assays. Lastly, Y15 [a specific inhibitor of focal adhesion kinase (FAK)] was used to examine its potential to inhibit tumor growth in ESCA cells.

Results

SPP1 was upregulated in ESCA tissues compared to the adjacent nontumorous tissues, which was closely associated with clinical stage, lymph node metastasis, histological subtype, and p53 mutation. A high expression of SPP1 indicated a poor clinical prognosis in patients with ESCA. The knockdown of SPP1 inhibited cell proliferative, migratory, and invasive capacities in ESCA cells. GSEA indicated that the focal adhesion pathway was closely related with SPP1 in ESCA. Further studies confirmed that the knockdown of SPP1 suppressed cell adhesion ability and reduced the expression of p-FAK and p-Erk in ESCA cells. In addition, Y15 inhibited FAK autophosphorylation and dramatically inhibited cell proliferation, migration, and invasion in ESCA cells.

Conclusions

SPP1 promotes tumor progression in ESCA by activating FAK/Erk pathway, and FAK is a potential therapeutic target to overcome tumor recurrence and metastasis of ESCA.

Identification and Validation of Immune Implication of R-Spondin 1 and an R-Spondin 1-Related Prognostic Signature in Esophagus Cancer

R-spondin 1 (RSPO1), which encodes a secretory-activating protein, is a promising therapeutic target for various tumors. The aim of this study was to establish a robust RSPO1-related signature specific to esophageal cancer (ESCA). Our comprehensive study involved meticulous analysis of RSPO1 expression in ESCA tissues and validation across ESCA cell lines and clinical samples using The Cancer Genome Atlas (TCGA) and GTEx databases. Using TCGA-ESCA dataset, we employed single-sample gene set enrichment analysis (ssGSEA) to elucidate the complex interaction between RSPO1 expression and the abundance of 22 specific immune cell types infiltrating ESCA. The biological significance of RSPO1 was further elucidated using KEGG, GO, and GSEA, demonstrating its relevance to pivotal tumor and immune pathways. This study culminated in the construction of prognostic nomograms enriched by calibration curves, facilitating the projection of individual survival probabilities at intervals of one, three, and five years. A substantial decrease in RSPO1 expression was observed within ESCA tissues and cell lines compared to their normal esophageal counterparts, and a significant decrease in the proportion of activated dendritic cells was evident within ESCA, accompanied by an augmented presence of macrophages and naive B cells relative to normal tissue. GSEA and KEGG analyses showed that RSPO1 was associated with tumor and immune pathways. Additionally, an independent prognostic risk score based on the RSPO1-related gene signature was developed and validated for patients with ESCA. Finally, RT-qPCR and western blotting were performed to confirm RSPO1 expression in normal and ESCA cell lines and tissue samples. In summary, our investigation underscores the pivotal role of RSPO1 in orchestrating tumor immunity and proposes RSPO1 as a prospective target for immunotherapeutic interventions in ESCA. Furthermore, the intricate profile of the two RSPO1-related genes has emerged as a promising predictive biomarker with notable potential for application in ESCA.

Single-cell profiling of response to neoadjuvant chemo-immunotherapy in surgically resectable esophageal squamous cell carcinoma

BACKGROUND

The efficacy of neoadjuvant chemo-immunotherapy (NAT) in esophageal squamous cell carcinoma (ESCC) is challenged by the intricate interplay within the tumor microenvironment (TME). Unveiling the immune landscape of ESCC in the context of NAT could shed light on heterogeneity and optimize therapeutic strategies for patients.

METHODS

We analyzed single cells from 22 baseline and 24 post-NAT treatment samples of stage II/III ESCC patients to explore the association between the immune landscape and pathological response to neoadjuvant anti-PD-1 combination therapy, including pathological complete response (pCR), major pathological response (MPR), and incomplete pathological response (IPR).

RESULTS

Single-cell profiling identified 14 major cell subsets of cancer, immune, and stromal cells. Trajectory analysis unveiled an interesting link between cancer cell differentiation and pathological response to NAT. ESCC tumors enriched with less differentiated cancer cells exhibited a potentially favorable pathological response to NAT, while tumors enriched with clusters of more differentiated cancer cells may resist treatment. Deconvolution of transcriptomes in pre-treatment tumors identified gene signatures in response to NAT contributed by specific immune cell populations. Upregulated genes associated with better pathological responses in CD8 + effector T cells primarily involved interferon-gamma (IFNγ) signaling, neutrophil degranulation, and negative regulation of the T cell apoptotic process, whereas downregulated genes were dominated by those in the immune response-activating cell surface receptor signaling pathway. Natural killer cells in pre-treatment tumors from pCR patients showed a similar upregulation of gene expression in response to IFNγ but a downregulation of genes in the neutrophil-mediated immunity pathways. A decreased cellular contexture of regulatory T cells in ESCC TME indicated a potentially favorable pathological response to NAT. Cell-cell communication analysis revealed extensive interactions between CCL5 and its receptor CCR5 in various immune cells of baseline pCR tumors. Immune checkpoint interaction pairs, including CTLA4-CD86, TIGIT-PVR, LGALS9-HAVCR2, and TNFSF4-TNFRSF4, might serve as additional therapeutic targets for ICI therapy in ESCC.

CONCLUSIONS

This pioneering study unveiled an intriguing association between cancer cell differentiation and pathological response in esophageal cancer patients, revealing distinct subgroups of tumors for which neoadjuvant chemo-immunotherapy might be effective. We also delineated the immune landscape of ESCC tumors in the context of clinical response to NAT, which provides clinical insights for better understanding how patients respond to the treatment and further identifying novel therapeutic targets for ESCC patients in the future.

Developing a novel necroptosis-related signature to evaluate the prognostic and therapeutic characteristics of esophageal cancer

BACKGROUND

The prognostic assessment and therapeutic interventions of esophageal cancer (ESCA) require novel molecular targets. The prognostic value of necroptosis, a specific mode of programmed cell death strongly linked to cancer progression, remains largely unexplored in ESCA. The primary goal of this research is to develop a necroptosis-based prognostic signature, which will represent the microenvironmental characteristics and prognosis of individuals diagnosed with ESCA.

METHODS

Transcriptome data of ESCA samples from The Cancer Genome Atlas were utilized to screen for necroptosis-related long non-coding RNAs (NR-lncRNAs) and genes (NRGs). The research employed the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression analysis to identify prognostic candidates. Based on these analyses, a signature was developed in the training set and subsequently verified in the testing and entire sets. A clinicopathologic relevance assessment was carried out, after which a nomogram was established. The features of the immune microenvironment, functional pathways, mutational burden, checkpoint expression, and stemness of tumors were analyzed. Moreover, the sensitivity of individuals to immunotherapy and chemotherapy was compared for therapeutic guidance.

RESULTS

A necroptosis-associated signature comprising two genes and eleven lncRNAs was constructed. High-risk patients showed worse prognosis and clinicopathologic features, with more tumor-infiltrating naïve B cells, CD4+ memory resting T cells, and regulatory T cells. Furthermore, stromal and ESTIMATE scores were decreased along with increased stemness scores and tumor mutational burden in high-risk individuals. For the quantitative prediction of the outcomes of individuals, a nomogram was established. High-risk individuals showed greater sensitivity to immunotherapy while low-risk individuals benefited more from conventional chemotherapeutic or targeted therapy.

CONCLUSION

A necroptosis-related prognostic signature was developed to study the tumor microenvironment, mutational burden, clinical features, and the treatment response of ESCA patients. This may contribute to precision medicine for ESCA.

The Clinical Significance and Role of CXCL1 Chemokine in Gastrointestinal Cancers

One area of cancer research is the interaction between cancer cells and immune cells, in which chemokines play a vital role. Despite this, a comprehensive summary of the involvement of C-X-C motif ligand 1 (CXCL1) chemokine (also known as growth-regulated gene-α (GRO-α), melanoma growth-stimulatory activity (MGSA)) in cancer processes is lacking. To address this gap, this review provides a detailed analysis of CXCL1's role in gastrointestinal cancers, including head and neck cancer, esophageal cancer, gastric cancer, liver cancer (hepatocellular carcinoma (HCC)), cholangiocarcinoma, pancreatic cancer (pancreatic ductal adenocarcinoma), and colorectal cancer (colon cancer and rectal cancer). This paper presents the impact of CXCL1 on various molecular cancer processes, such as cancer cell proliferation, migration, and invasion, lymph node metastasis, angiogenesis, recruitment to the tumor microenvironment, and its effect on immune system cells, such as tumor-associated neutrophils (TAN), regulatory T (T_reg) cells, myeloid-derived suppressor cells (MDSCs), and macrophages. Furthermore, this review discusses the association of CXCL1 with clinical aspects of gastrointestinal cancers, including its correlation with tumor size, cancer grade, tumor-node-metastasis (TNM) stage, and patient prognosis. This paper concludes by exploring CXCL1's potential as a therapeutic target in anticancer therapy.

The identification of a two-gene prognostic model based on cisplatin resistance-related ceRNA network in small cell lung cancer

BACKGROUND

Small cell lung cancer (SCLC) is a very malignant tumor with rapid growth and early metastasis. Platinum-based chemo-resistance is the major issue for SCLC treatment failure. Identifying a new prognostic model will help to make an accurate treatment decision for SCLC patients.

METHODS

Using the genomics of drug sensitivity in cancer (GDSC) database, we identified cisplatin resistance-related lncRNAs in SCLC cells. Based on the competing endogenous RNA (ceRNA) network, we identified the mRNAs correlated with the lncRNAs. Using Cox and LASSO regression analysis, a prognostic model was established. The survival prediction accuracy was evaluated by receiver operating characteristic (ROC) curve and Kaplan-Meier analysis. GSEA, GO, KEGG and CIBERSORT tools were used for functional enrichment and immune cells infiltration analysis.

RESULTS

We first screened out 10 differentially expressed lncRNAs between cisplatin resistant and sensitive SCLC cells from GDSC database. Based on ceRNA network, 31 mRNAs were identified with a correlation with the 10 lncRNAs. Furthermore, two genes (LIMK2 and PI4K2B) were identified by Cox and LASSO regression analysis to construct a prognostic model. Kaplan-Meier analysis indicated that the high-risk group had a poor overall survival compared with the low-risk group. The predicted area under the ROC curve (AUC) was 0.853 in the training set, and the AUC was 0.671 in the validation set. In the meanwhile, the low expression of LIMK2 or the high expression of PI4K2B in SCLC tumors was also significantly associated with poor overall survival in both training and validation sets. Functional enrichment analysis showed that the low-risk group was enriched in the apoptosis pathway and high immune infiltration of T cells. Finally, an apoptosis-related gene Cathepsin D (CTSD) was identified to be up-regulated in the low-risk group, and its higher expression correlated with better overall survival in SCLC.

CONCLUSION

We established a prognostic model and potential biomarkers (LIMK2, PI4K2B and CTSD), which could help to improve the risk stratification of SCLC patients.

Ion channel gene GJB2 influences the intercellular communication by Up-regulating the SPP1 signaling pathway identified by the single-cell RNA sequencing in lung adenocarcinoma

Objective

Firstly, observe the prognostic significance and the biological functional effects of gap junction protein beta 2 (GJB2 or Cx26) in lung adenocarcinoma (LUAD). Subsequently, explore the role played by GJB2 in intercellular communication by single-cell RNA sequencing.

Method

We made a differential analysis of GJB2 expression through public databases and investigated the clinical characteristics and prognostic significance. ESTIMATE analysis and Tumor Immune Estimation Resource (TIMER) database were utilized to illustrate the association of GJB2 with immune infiltration and components of the tumor microenvironment. Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), and Gene set enrichment analysis (GSEA) were performed to study the biological function of GJB2. Cell-cell communication was analyzed using the CellChat R package through sc-RNA data.

Results

GJB2 has an outstanding prognosis value in LUAD and a close relationship was found between GJB2 and immune infiltration in LUAD. GJB2 could participate in several tumor biological processes, including extracellular matrix remodeling and upregulation of multiple cancer-related active pathways. GJB2 related hub-genes influence intercellular communication through the SPP1 signaling pathway.

Conclusion

Our study illustrates one mechanism by which GJB2 exerts its cancer-specific relevant effects, that is, causing changes in intercellular communication through the SPP1 signaling pathway. Blockade of this pathway may limit the functional role of GJB2 and provide us with promising new perceptions for LUAD treatment.

Transcriptomic analysis of esophageal cancer reveals hub genes and networks involved in cancer progression

Esophageal carcinoma (ESCA) has a 5-year survival rate of fewer than 20%. The study aimed to identify new predictive biomarkers for ESCA through transcriptomics meta-analysis to address the problems of ineffective cancer therapy, lack of efficient diagnostic tools, and costly screening and contribute to developing more efficient cancer screening and treatments by identifying new marker genes. Nine GEO datasets of three kinds of esophageal carcinoma were analyzed, and 20 differentially expressed genes were detected in carcinogenic pathways. Network analysis revealed four hub genes, namely RAR Related Orphan Receptor A (RORA), lysine acetyltransferase 2B (KAT2B), Cell Division Cycle 25B (CDC25B), and Epithelial Cell Transforming 2 (ECT2). Overexpression of RORA, KAT2B, and ECT2 was identified with a bad prognosis. These hub genes modulate immune cell infiltration. These hub genes modulate immune cell infiltration. Although this research needs lab confirmation, we found interesting biomarkers in ESCA that may aid in diagnosis and treatment.

Intratumoral microbiome impacts immune infiltrates in tumor microenvironment and predicts prognosis in esophageal squamous cell carcinoma patients

Background

Different intratumoral microbiotaexist in different tumors and play a crucial function in carcinogenesis. However, whether they impact clinical outcomes in esophageal squamous cell carcinoma (ESCC) and their mechanism remain unclear.

Methods

16S rDNA amplicon sequencing was performed on surgically resected samples from 98 ESCC patients to analyze intratumoral microbiome abundance and composition. Multiplex fluorescent immunohistochemistry staining was used to profile the phenotypes of immune infiltrates in the tumor microenvironment (TME).

Results

Patients with higher intratumoral Shannon index had significantly worse surgical outcomes. When patients were divided into short-term survivors and long-term survivors based on the median survival time, both intratumoral alpha-diversity and beta-diversity were found to be significantly inconsistent, and the relative abundance of Lactobacillus and Leptotrichia emerged as the two microorganisms that probably influenced the survival of ESCC patients. Only Lactobacillus in ESCC was validated to significantly worsen patients' prognoses and to be positively correlated with the Shannon index. Multivariate analysis revealed that the intratumoral Shannon index, the relative abundance of Lactobacillus, and the pathologic tumor-node-metastasis (pTNM) stage were independently associated with patients' overall survival. Furthermore, the relative abundance of both Lactobacillus and Shannon index was positively correlated with the proportions of PD-L1⁺ epithelial cells (ECs) and tumor-associated macrophages (TAMs). The Shannon index was negatively correlated with the proportions of natural killer (NK) cells in the TME.

Conclusions

A high abundance of intratumoral Lactobacillus and bacterial alpha-diversity was associated with the formation of the immunosuppressive TME and predicted poor long-term survival in ESCC patients.

A more novel and robust gene signature predicts outcome in patients with esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The tumor microenvironment (TME) mainly comprises tumor cells and tumor-infiltrating immune cells mixed with stromal components. The latest research has displayed that tumor immune cell infiltration (ICI) is closely connected with the ESCC patients' clinical prognosis. This study was designed to construct a gene signature based on the ICI of ESCC to predict prognosis.

METHODS

Based on the selection criteria we set, the eligible ESCC cases from the GSE53625 and TCGA-ESCA datasets were chosen for the training cohort and the validation cohort, respectively. Unsupervised clustering detailed grouped ESCC cases of the training cohort based on the ICI profile. We determined the differential expression genes (DEGs) between the ICI clusters, and, subsequently, we adopted the univariate Cox analysis to recognize DEGs with prognostic potential. These screened DEGs underwent a Lasso regression, which then generated a gene signature. The harvested signature's predictive ability was further examined by the Kaplan-Meier analysis, Cox analysis, ROC, IAUC, and IBS. More importantly, we listed similar studies in the most recent year and compared theirs with ours. We performed the functional annotation, immune relevant signature correlation analysis, and immune infiltrating analysis to thoroughly understand the functional mechanism of the signature and the immune cells' roles in the gene signature's predicting capacity.

RESULTS

A sixteen-gene signature (ARSD, BCAT1, BIK, CLDN11, DLEU7-AS1, GGH, IGFBP2, LINC01037, LINC01446, LINC01497, M1AP, PCSK2, PCSK5, PPP2R2A, TIGD7, and TMSB4X) was generated from the Lasso model. We then confirmed the signature as having solid and stable prognostic capacity by several statistical methods. We revealed the superiority of our signature after comparing it to our predecessors, and the GSEA uncovered the specifically mechanism of action related to the gene signature. Two immune relevant signatures, including GZMA and LAG3 were identified associating with our signature. The immune-infiltrating analysis identified crucial roles of resting mast cells, which potentially support the sixteen-gene signature's prognosis ability.

CONCLUSIONS

We discovered a robust sixteen-gene signature that can accurately predict ESCC prognosis. The immune relevant signatures, GZMA and LAG3, and resting mast cells infiltrating were closely linked to the sixteen-gene signature's ability.

A Systems Biology and LASSO-Based Approach to Decipher the Transcriptome-Interactome Signature for Predicting Non-Small Cell Lung Cancer

The lack of precise molecular signatures limits the early diagnosis of non-small cell lung cancer (NSCLC). The present study used gene expression data and interaction networks to develop a highly accurate model with the least absolute shrinkage and selection operator (LASSO) for predicting NSCLC. The differentially expressed genes (DEGs) were identified in NSCLC compared with normal tissues using TCGA and GTEx data. A biological network was constructed using DEGs, and the top 20 upregulated and 20 downregulated hub genes were identified. These hub genes were used to identify signature genes with penalized logistic regression using the LASSO to predict NSCLC. Our model’s development involved the following steps: (i) the dataset was divided into 80% for training (TR) and 20% for testing (TD1); (ii) a LASSO logistic regression analysis was performed on the TR with 10-fold cross-validation and identified a combination of 17 genes as NSCLC predictors, which were used further for development of the LASSO model. The model’s performance was assessed on the TD1 dataset and achieved an accuracy and an area under the curve of the receiver operating characteristics (AUC-ROC) of 0.986 and 0.998, respectively. Furthermore, the performance of the LASSO model was evaluated using three independent NSCLC test datasets (GSE18842, GSE27262, GSE19804) and achieved high accuracy, with an AUC-ROC of >0.99, >0.99, and 0.95, respectively. Based on this study, a web application called NSCLCpred was developed to predict NSCLC.

Drug repositioning for esophageal squamous cell carcinoma

Esophageal cancer (EC) remains a significant challenge globally, having the 8th highest incidence and 6th highest mortality worldwide. Esophageal squamous cell carcinoma (ESCC) is the most common form of EC in Asia. Crucially, more than 90% of EC cases in China are ESCC. The high mortality rate of EC is likely due to the limited number of effective therapeutic options. To increase patient survival, novel therapeutic strategies for EC patients must be devised. Unfortunately, the development of novel drugs also presents its own significant challenges as most novel drugs do not make it to market due to lack of efficacy or safety concerns. A more time and cost-effective strategy is to identify existing drugs, that have already been approved for treatment of other diseases, which can be repurposed to treat EC patients, with drug repositioning. This can be achieved by comparing the gene expression profiles of disease-states with the effect on gene-expression by a given drug. In our analysis, we used previously published microarray data and identified 167 differentially expressed genes (DEGs). Using weighted key driver analysis, 39 key driver genes were then identified. These driver genes were then used in Overlap Analysis and Network Analysis in Pharmomics. By extracting drugs common to both analyses, 24 drugs are predicted to demonstrate therapeutic effect in EC patients. Several of which have already been shown to demonstrate a therapeutic effect in EC, most notably Doxorubicin, which is commonly used to treat EC patients, and Ixazomib, which was recently shown to induce apoptosis and supress growth of EC cell lines. Additionally, our analysis predicts multiple psychiatric drugs, including Venlafaxine, as repositioned drugs. This is in line with recent research which suggests that psychiatric drugs should be investigated for use in gastrointestinal cancers such as EC. Our study shows that a drug repositioning approach is a feasible strategy for identifying novel ESCC therapies and can also improve the understanding of the mechanisms underlying the drug targets.

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.

SPP1 promotes radiation resistance through JAK2/STAT3 pathway in esophageal carcinoma

BACKGROUND

Therapeutic resistance to radiotherapy is one of the major obstacles in clinical practice that significantly affect the therapeutic efficiency and prognosis of human esophageal carcinoma (ESCA). Thus, it is critical to understand the molecular mechanisms of radiation resistance in ESCA. Secreted phosphoprotein 1 (SPP1) plays an essential role in various human cancers, but its role in radiation resistance remains unclear.

METHOD

Cell culture and transfection; Cell Counting Kit-8 (CCK-8) assays; EdU incorporation assays; Patient sample collection and medical records review; Transwell assays; Colony formation assays; Wound healing assays; Western blot; Immunofluorescence; Immunohistochemistry; Irradiation; Flow cytometry; Animal studies; Human Apoptosis Array Kit; Bioinformatics.

RESULT

In the current study, we reported the novel phenomenon that radiation-treated human ESCA cells upregulated SPP1 expression, which in turn contributed to the ESCA resistance to radiotherapy. We also reported the tumor-promoting effect of SPP1 in ESCA systematically and comprehensively. Furthermore, subsequent studies by knocking down or overexpressing SPP1 in human ESCA cells showed that SPP1 could facilitate the repair of DNA damage and the survival of tumor cells post-radiation in ESCA, which might contribute to the development of radiation resistance during the radiotherapy process. More detailed investigations on the downstream molecular pathway suggested that radiation could increase the phosphorylation level of JAK2 and STAT3 by increasing SPP1 expression. Further in vivo validation using a mouse ESCA xenograft model showed that SPP1 overexpression significantly increased tumor volume while either SPP1 knockdown or pharmacological inhibition of the JAK2-STAT3 pathway reduced tumor volume in a synergistic manner with radiotherapy.

CONCLUSION

Collectively, these findings suggested that the SPP1/JAK2/STAT3 axis is a critical player in ESCA progression and radiation resistance, which is a potential therapeutic target for combined therapy with the standard radiotherapy regimen to improve curative effect and increase patients' survival with ESCA.

Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8+ T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis

BACKGROUND

Tuberculosis (TB) is a major infectious disease, where incomplete information about host genetics and immune responses is hindering the development of transformative therapies. This study characterized the immune cell landscape and blood transcriptomic profile of patients with pulmonary TB (PTB) to identify the potential therapeutic biomarkers.

METHODS

The blood transcriptome profile of patients with PTB and controls were used for fractionating immune cell populations with the CIBERSORT algorithm and then to identify differentially expressed genes (DEGs) with R/Bioconductor packages. Later, systems biology investigations (such as semantic similarity, gene correlation, and graph theory parameters) were implemented to prioritize druggable genes contributing to the immune cell alterations in patients with TB. Finally, real time-PCR (RT-PCR) was used to confirm gene expression levels.

RESULTS

Patients with PTB had higher levels of four immune subpopulations like CD8⁺ T cells (P = 1.9 × 10^-8), natural killer (NK) cells resting (P = 6.3 × 10^-5), monocytes (P = 6.4 × 10^-6), and neutrophils (P = 1.6 × 10^-7). The functional enrichment of 624 DEGs identified in the blood transcriptome of patients with PTB revealed major dysregulation of T cell-related ontologies and pathways (q ≤ 0.05). Of the 96 DEGs shared between transcriptome and immune cell types, 39 overlapped with TB meta-profiling genetic signatures, and their semantic similarity analysis with the remaining 57 genes, yielded 45 new candidate TB markers. This study identified 9 CD8⁺ T cell-associated genes (ITK, CD2, CD6, CD247, ZAP70, CD3D, SH2D1A, CD3E, and IL7R) as potential therapeutic targets of PTB by combining computational druggability and co-expression (r² ≥ |0.7|) approaches.

CONCLUSION

The changes in immune cell proportion and the downregulation of T cell-related genes may provide new insights in developing therapeutic compounds against chronic TB.