Hypercoagulation and complement: Connected players in tumor development and metastases

GJA4 expressed on cancer associated fibroblasts (CAFs)-A 'promoter' of the mesenchymal phenotype

BACKGROUND

Colorectal cancer (CRC) is the third most common cancer worldwide. Connexin is a transmembrane protein involved in gap junctions (GJs) formation. Our previous study found that connexin 37 (Cx37), encoded by gap junction protein alpha 4 (GJA4), expressed on fibroblasts acts as a promoter of CRC and is closely related to epithelial-mesenchymal transition (EMT) and tumor immune microenvironment. However, to date, the mechanism concerning the malignancy of GJA4 in tumor stroma has not been studied.

METHODS

Hematoxylin-eosin (HE) and immunohistochemical (IHC) staining were used to validate the expression and localization of GJA4. Using single-cell analysis, enrichment analysis, spatial transcriptomics, immunofluorescence staining (IF), Sirius red staining, wound healing and transwell assays, western blotting (WB), Cell Counting Kit-8 (CCK8) assay and in vivo experiments, we investigated the possible mechanisms of GJA4 in promoting CRC.

RESULTS

We discovered that in CRC, GJA4 on fibroblasts is involved in promoting fibroblast activation and promoting EMT through a fibroblast-dependent pathway. Furthermore, GJA4 may act synergistically with M2 macrophages to limit T cell infiltration by stimulating the formation of an immune-excluded desmoplasic barrier. Finally, we found a significantly correlation between GJA4 and pathological staging (P < 0.0001) or D2 dimer (R = 0.03, P < 0.05).

CONCLUSION

We have identified GJA4 expressed on fibroblasts is actually a promoter of the tumor mesenchymal phenotype. Our findings suggest that the interaction between GJA4+ fibroblasts and M2 macrophages may be an effective target for enhancing tumor immunotherapy.

Assessment of Hidden Blood Loss in Spinal Metastasis Surgery: A Comprehensive Approach with MRI-Based Radiomics Models

BACKGROUND

Patients undergoing surgery for spinal metastasis are predisposed to hidden blood loss (HBL), which is associated with poor surgical outcomes but unpredictable.

PURPOSE

To evaluate the role of MRI-based radiomics models for assess the risk of HBL in patients undergoing spinal metastasis surgery.

STUDY TYPE

Retrospective.

SUBJECTS

202 patients (42.6% female) operated on for spinal metastasis with a mean age of 58 ± 11 years were divided into a training (n = 162) and a validation cohort (n = 40).

FIELD STRENGTH/SEQUENCE

1.5T or 3.0T scanners. Sagittal T1-weighted and fat-suppressed T2-weighted imaging sequences.

ASSESSMENT

HBL was calculated using the Gross formula. Patients were classified as low and high HBL group, with 1000 mL as the threshold. Radiomics models were constructed with radiomics features. The radiomics score (Radscore) was obtained from the optimal radiomics model. Clinical variables were accessed using univariate and multivariate logistic regression analyses. Independent risk variables were used to build a clinical model. Clinical variables combined with Radscore were used to establish a combined model.

STATISTICAL TESTS

Predictive performance was evaluated using area under the curve (AUC), accuracy, sensitivity, specificity, and F1 score. Calibration curves and decision curves analyses were produced to evaluate the accuracy and clinical utility.

RESULTS

Among the radiomics models, the fusion (T1WI + FS-T2WI) model demonstrated the highest predictive efficacy (AUC: 0.744, 95% confidence interval [CI]: 0.576-0.914). The Radscore model (AUC: 0.809, 95% CI: 0.664-0.954) performs slightly better than the clinical model (AUC: 0.721, 95% CI: 0.524-0.918; P = 0.418) and the combined model (AUC: 0.752, 95% CI: 0.593-0.911; P = 0.178).

DATA CONCLUSION

A radiomics model may serve as a promising assessment tool for the risk of HBL in patients undergoing spinal metastasis surgery, and guide perioperative planning to improve surgical outcomes.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

PLP2 Could Be a Prognostic Biomarker and Potential Treatment Target in Glioblastoma Multiforme

Objective

This study aimed to discern the association between PLP2 expression, its biological significance, and the extent of immune infiltration in human GBM.

Methods

Utilizing the GEPIA2 and TCGA databases, we contrasted the expression levels of PLP2 in GBM against normal tissue. We utilized GEPIA2 and LinkedOmics for survival analysis, recognized genes co-expressed with PLP2 via cBioPortal and GEPIA2, and implemented GO and KEGG analyses. The STRING database facilitated the construction of protein-protein interaction networks. We evaluated the relationship of PLP2 with tumor immune infiltrates using ssGSEA and the TIMER 2.0 database. An IHC assay assessed PLP2 and PDL-1 expression in GBM tissue, and the Drugbank database aided in identifying potential PLP2-targeting compounds. Molecular docking was accomplished using Autodock Vina 1.2.2.

Results

PLP2 expression was markedly higher in GBM tissues in comparison to normal tissues. High PLP2 expression correlated with a decrease in overall survival across two databases. Functional analyses highlighted a focus of PLP2 functions within leukocyte. Discrepancies in PLP2 expression were evident in immune infiltration, impacting CD4+ T cells, neutrophils, myeloid dendritic cells, and macrophages. There was a concomitant increase in PLP2 and PD-L1 expression in GBM tissues, revealing a link between the two. Molecular docking with ethosuximide and praziquantel yielded scores of -7.441 and -4.295 kcal/mol, correspondingly.

Conclusion

PLP2's upregulation in GBM may adversely influence the lifespan of GBM patients. The involvement of PLP2 in pathways linked to leukocyte function is suggested. The positive correlation between PLP2 and PD-L1 could provide insights into PLP2's role in glioma modulation. Our research hints at PLP2's potential as a therapeutic target for GBM, with ethosuximide and praziquantel emerging as potential treatment candidates, especially emphasizing the potential of these compounds in GBM treatment targeting PLP2.

The prognostic role of coagulation markers in the progression and metastasis of laryngeal squamous cell carcinoma

BACKGROUND

The application of coagulation-related markers in laryngeal squamous cell carcinoma(LSCC) remains unclear. This study explored the prognostic role of coagulation markers in the progression and metastasis of LSCC.

METHODS

Coagulation markers of patients with LSCC receiving surgery in the Second Affiliated Hospital of Fujian Medical University in China, from January 2013 to May 2022 were retrospectively analyzed and compared with those of contemporary patients with benign laryngeal diseases. The relationship between clinicopathological features of LSCC and coagulation markers was analyzed with the chi-square and rank sum tests. The ROC curve analysis was utilized to evaluate the diagnostic efficacy of seven coagulation markers for LSCC and its different clinicopathological features, and to find the optimal cutoff value of each coagulation marker.

RESULTS

303 patients with LSCC and 533 patients with benign laryngeal diseases were included in the present analysis. Compared to the control group, prothrombin time (PT) (p < 0.001), activated partial thromboplastin time (APTT) (p = 0.001), and Fib (p < 0.001) in patients with LSCC were significantly higher, while mean platelet volume (MPV) (p < 0.001) was significantly shorter. Significant increases were detected in PT (Z = 14.342, p = 0.002), Fib (Z = 25.985, p < 0.001), platelet count (PC) (Z = 12.768, p = 0.005), PCT (Z = 9.178, p = 0.027), MPV (F = 2.948, p = 0.033) in T4 stage. Fib had the highest prognostic value among the seven coagulation markers in different T stages (AUC = 0.676, p < 0.001), N stages (AUC = 0.717, p < 0.001), tumor stage (AUC = 0.665, p < 0.001), differentiation degree (AUC = 0.579, p = 0.022), and neurovascular invasion (AUC = 0.651, p = 0.007). Fib (Z = 25.832, p < 0.001), PC (Z = 23.842, p < 0.001), and PCT (Z = 20.15, p < 0.001) in N1 and N3 stages were significantly higher than in N0 stage. PT (Z = 12.174, p = 0.007), Fib (Z = 23.873, p < 0.001), PC (Z = 17.785, p < 0.001), and PCT (Z = 14.693, p = 0.002) were significantly higher in stage IV than in stage I and II. APTT (Z=-1.983, p = 0.047), Fib (Z=-2.68, p = 0.007), PC (Z=-2.723, p = 0.006), and PCT (Z=-2.592, p = 0.01) increased significantly when the tumor invaded neurovascular tissue.

CONCLUSIONS

Coagulation markers have the potential to act as biomarkers for predicting pathological features of LSCC. The high level of Fib was helpful for the diagnosis of LSCC and the detection of advanced LSCC.

TRIAL REGISTRATION

Not applicable.

Regulatory T cells are associated with the tumor immune microenvironment and immunotherapy response in triple-negative breast cancer

Introduction

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with a high risk of distant metastasis, an extremely poor prognosis, and a high risk of death. Regulatory T cells (Tregs) contribute to the formation of a tumor immunosuppressive microenvironment, which plays an important role in the progression and treatment resistance of TNBC.

Methods

A public single-cell sequencing dataset demonstrated increased infiltration of Tregs in TNBC tissues relative to normal breast tissue. Weighted gene co-expression network analysis was used to identify Treg infiltration-related modules for METABRIC TNBC samples. Subsequently, we obtained two Treg infiltration-associated clusters of TNBC by applying consensus clustering and further constructed a prognostic model based on this Treg infiltration-associated gene module. The ability of the selected gene in the prognostic model, thymidine kinase-1 (TK1), to promote the progression of TNBC was evaluated in vitro.

Results

We concluded that two Treg infiltration-associated clusters had different prognoses and sensitivities to drugs commonly used in breast cancer treatment, and multi-omics analysis revealed that the two clusters had different copy number variations of key tumor progression genes. The 7-gene risk score based on TNBC Treg infiltration was a reliable prognostic indicator both in the training and validation cohorts. Moreover, patients with TNBC with high Treg infiltration-related scores lacked the activation of immune activation pathways and exhibited resistance to anti-PD1 immunotherapy. Knocking down TK1 led to impaired proliferation, migration, and invasion of TNBC cells in vitro. In addition, specimens from patients with TNBC with high TK1 expression showed significantly higher Treg infiltration in tumors. Results of spatial transcriptome analysis showed that TK1 positive cells mainly localize in tumor area, and Treg cell infiltration in TNBC tissues was associated with high expression of TK1. Pan-cancer analysis also demonstrated that TK1 is associated with poor prognosis and activation of proliferation pathways in multiple cancers.

Discussion

We established a prognostic model related to Treg infiltration and this model can be used to establish a clinically relevant classification of TNBC progression. Additionally, our work revealed the underestimable potential of TK1 as a tumor biomarker and immunotherapeutic target.

Integrated models of blood protein and metabolite enhance the diagnostic accuracy for Non-Small Cell Lung Cancer

BACKGROUND

For early screening and diagnosis of non-small cell lung cancer (NSCLC), a robust model based on plasma proteomics and metabolomics is required for accurate and accessible non-invasive detection. Here we aim to combine TMT-LC-MS/MS and machine-learning algorithms to establish models with high specificity and sensitivity, and summarize a generalized model building scheme.

METHODS

TMT-LC-MS/MS was used to discover the differentially expressed proteins (DEPs) in the plasma of NSCLC patients. Plasma proteomics-guided metabolites were selected for clinical evaluation in 110 NSCLC patients who were going to receive therapies, 108 benign pulmonary diseases (BPD) patients, and 100 healthy controls (HC). The data were randomly split into training set and test set in a ratio of 80:20. Three supervised learning algorithms were applied to the training set for models fitting. The best performance models were evaluated with the test data set.

RESULTS

Differential plasma proteomics and metabolic pathways analyses revealed that the majority of DEPs in NSCLC were enriched in the pathways of complement and coagulation cascades, cholesterol and bile acids metabolism. Moreover, 10 DEPs, 14 amino acids, 15 bile acids, as well as 6 classic tumor biomarkers in blood were quantified using clinically validated assays. Finally, we obtained a high-performance screening model using logistic regression algorithm with AUC of 0.96, sensitivity of 92%, and specificity of 89%, and a diagnostic model with AUC of 0.871, sensitivity of 86%, and specificity of 78%. In the test set, the screening model achieved accuracy of 90%, sensitivity of 91%, and specificity of 90%, and the diagnostic model achieved accuracy of 82%, sensitivity of 77%, and specificity of 86%.

CONCLUSIONS

Integrated analysis of DEPs, amino acid, and bile acid features based on plasma proteomics-guided metabolite profiling, together with classical tumor biomarkers, provided a much more accurate detection model for screening and differential diagnosis of NSCLC. In addition, this new mathematical modeling based on plasma proteomics-guided metabolite profiling will be used for evaluation of therapeutic efficacy and long-term recurrence prediction of NSCLC.

Protein Biomarker Discovery Studies on Urinary sEV Fractions Separated with UF-SEC for the First Diagnosis and Detection of Recurrence in Bladder Cancer Patients

Urinary extracellular vesicles (EVs) are an attractive source of bladder cancer biomarkers. Here, a protein biomarker discovery study was performed on the protein content of small urinary EVs (sEVs) to identify possible biomarkers for the primary diagnosis and recurrence of non-muscle-invasive bladder cancer (NMIBC). The sEVs were isolated by ultrafiltration (UF) in combination with size-exclusion chromatography (SEC). The first part of the study compared healthy individuals with NMIBC patients with a primary diagnosis. The second part compared tumor-free patients with patients with a recurrent NMIBC diagnosis. The separated sEVs were in the size range of 40 to 200 nm. Based on manually curated high quality mass spectrometry (MS) data, the statistical analysis revealed 69 proteins that were differentially expressed in these sEV fractions of patients with a first bladder cancer tumor vs. an age- and gender-matched healthy control group. When the discriminating power between healthy individuals and first diagnosis patients is taken into account, the biomarkers with the most potential are MASP2, C3, A2M, CHMP2A and NHE-RF1. Additionally, two proteins (HBB and HBA1) were differentially expressed between bladder cancer patients with a recurrent diagnosis vs. tumor-free samples of bladder cancer patients, but their biological relevance is very limited.

Transcriptome-based network analysis related to M2-like tumor-associated macrophage infiltration identified VARS1 as a potential target for improving melanoma immunotherapy efficacy

RATIONALE

The M2-like tumor-associated macrophages (TAMs) are independent prognostic factors in melanoma.

METHODS

We performed weighted gene co-expression network analysis (WGCNA) to identify the module most correlated with M2-like TAMs. The Cancer Genome Atlas (TCGA) patients were classified into two clusters that differed based on prognosis and biological function, with consensus clustering. A prognostic model was established based on the differentially expressed genes (DEGs) of the two clusters. We investigated the difference in immune cell infiltration and immune response-related gene expression between the high and low risk score groups.

RESULTS

The risk score was defined as an independent prognostic value in melanoma. VARS1 was a hub gene in the M2-like macrophage-associated WGCNA module that the DepMap portal demonstrated was necessary for melanoma growth. Overexpressing VARS1 in vitro increased melanoma cell migration and invasion, while downregulating VARS1 had the opposite result. VARS1 overexpression promoted M2 macrophage polarization and increased TGF-β1 concentrations in tumor cell supernatant in vitro. VARS1 expression was inversely correlated with immune-related signaling pathways and the expression of several immune checkpoint genes. In addition, the VARS1 expression level helped predict the response to anti-PD-1 immunotherapy. Pan-cancer analysis demonstrated that VARS1 expression negatively correlated with CD8 T cell infiltration and the immune response-related pathways in most cancers.

CONCLUSION

We established an M2-like TAM-related prognostic model for melanoma and explored the role of VARS1 in melanoma progression, M2 macrophage polarization, and the development of immunotherapy resistance.

Blood Stasis Syndrome Accelerates the Growth and Metastasis of Breast Cancer by Promoting Hypoxia and Immunosuppressive Microenvironment in Mice

Blood stasis syndromes (BSSs) are closely related to the occurrence and development of tumors, although the mechanism is still unclear. This study was aimed at exploring the effect and mechanism underlying different BSSs on tumor growth and metastasis. We established four BSS mouse models bred with breast cancer: qi deficiency and blood stasis (QDBS), cold coagulation blood stasis (CCBS), heat toxin and blood stasis (HTBS), and qi stagnation and blood stasis (QSBS). The results showed that microcirculation in the lower limb, abdominal wall, and tumor in situ decreased by varying degrees in the BSS groups. In addition, BSS promoted tumor growth and lung metastasis. The ratio of regulatory T cells in the tumor microenvironment was downregulated. Moreover, hypoxia-inducible factor 1-α, Wnt1, β-catenin, vascular endothelial growth factor, and Cyclin D1 levels increased in the tumors of BSS mice. In conclusion, BSS not only promoted the formation of a hypoxic and immunosuppressive microenvironment but also promoted the neovascularization.

Establishing a Prognostic Model Based on Ulceration and Immune Related Genes in Melanoma Patients and Identification of EIF3B as a Therapeutic Target

Ulceration and immune status are independent prognostic factors for survival in melanoma patients. Herein univariate Cox regression analysis revealed 53 ulcer-immunity-related DEGs. We performed consensus clustering to divide The Cancer Genome Atlas (TCGA) cohort (n = 467) into three subtypes with different prognosis and biological functions, followed by validation in three merged Gene Expression Omnibus (GEO) cohorts (n = 399). Multiomics approach was used to assess differences among the subtypes. Cluster 3 showed relatively lesser amplification and expression of immune checkpoint genes. Moreover, Cluster 3 lacked immune-related pathways and immune cell infiltration, and had higher proportion of non-responders to immunotherapy. We also constructed a prognostic model based on ulceration and immune related genes in melanoma. EIF3B was a hub gene in the intersection between genes specific to Cluster 3 and those pivotal for melanoma growth (DepMap, https://depmap.org/portal/download/). High EIF3B expression in TCGA and GEO datasets was related to worst prognosis. In vitro models revealed that EIF3B knockdown inhibited melanoma cell migration and invasion, and decreased TGF-β1 level in supernatant compared with si-NC cells. EIF3B expression was negatively correlated with immune-related signaling pathways, immune cell gene signatures, and immune checkpoint gene expression. Moreover, its low expression could predict partial response to anti-PD-1 immunotherapy. To summarize, we established a prognostic model for melanoma and identified the role of EIF3B in melanoma progression and immunotherapy resistance development.

Distant Metastasis Pattern and Prognostic Prediction Model of Colorectal Cancer Patients Based on Big Data Mining

Aims

This study aimed to investigate the distant metastasis pattern from newly diagnosed colorectal cancer (CRC) and also construct and validate a prognostic nomogram to predict both overall survival (OS) and cancer-specific survival (CSS) of CRC patients with distant metastases.

Methods

Primary CRC patients who were initially diagnosed from 2010 to 2016 in the SEER database were included in the analysis. The independent risk factors affecting the OS, CSS, all-cause mortality, and CRC-specific mortality of the patients were screened by the Cox regression and Fine–Gray competitive risk model. The nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index) and calibration curve. The gene chip GSE41258 was downloaded from the GEO database, and differentially expressed genes (DEGs) were screened by the GEO2R online tool (p < 0.05, |logFC|>1.5). The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway and Gene Ontology (GO) annotation and String website were used for enrichment analysis and protein–protein interaction (PPI) analysis of DEGs, respectively, and Cytoscape software was used to construct PPI network and screen function modules and hub genes.

Results

A total of 57,835 CRC patients, including 47,823 without distant metastases and 10,012 (17.31%) with metastases, were identified. Older age, unmarried status, poorly differentiated or undifferentiated grade, right colon site, larger tumor size, N2 stage, more metastatic sites, and elevated carcinoembryonic antigen (CEA) might lead to poorer prognosis (all p < 0.01). The independent risk factors of OS and CSS were included to construct a prognosis prediction model for predicting OS and CSS in CRC patients with distant metastasis. C-index and calibration curve of the training group and validation group showed that the models had acceptable predictive performance and high calibration degree. Furthermore, by comparing CRC tissues with and without liver metastasis, 158 DEGs and top 10 hub genes were screened. Hub genes were mainly concentrated in liver function and coagulation function.

Conclusion

The big data in the public database were counted and transformed into a prognostic evaluation tool that could be applied to the clinic, which has certain clinical significance for the formulation of the treatment plan and prognostic evaluation of CRC patients with distant metastasis.

N7-Methylguanosine-Related lncRNAs: Integrated Analysis Associated With Prognosis and Progression in Clear Cell Renal Cell Carcinoma

N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely reported to play an important role in cancer. However, there is little known about the relationship between m7G-related lncRNAs and clear cell renal cell carcinoma (ccRCC). To find new potential biomarkers and construct an m7G-related lncRNA prognostic signature for ccRCC, we retrieved transcriptome data and clinical data from The Cancer Genome Atlas (TCGA), and divided the entire set into train set and test set with the ratio of 1:1 randomly. The m7G-related lncRNAs were identified by Pearson correlation analysis (|coefficients| &gt; 0.4, and p &lt; 0.001). Then we performed the univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a 12 m7G-related lncRNA prognostic signature. Next, principal component analysis (PCA), the Kaplan–Meier method, time-dependent receiver operating characteristics (ROC) were made to verify and evaluate the risk signature. A nomogram based on the risk signature and clinical parameters was developed and showed high accuracy and reliability for predicting the overall survival (OS). Functional enrichment analysis (GO, KEGG and GSEA) was used to investigate the potential biological pathways. We also performed the analysis of tumor mutation burden (TMB), immunological analysis including immune scores, immune cell infiltration (ICI), immune function, tumor immune escape (TIE) and immunotherapeutic drug in our study. In conclusion, using the 12 m7G-related lncRNA risk signature as a prognostic indicator may offer us insight into the oncogenesis and treatment response prediction of ccRCC.

Platelets as Key Factors in Inflammation: Focus on CD40L/CD40

Platelets are anucleate cytoplasmic fragments derived from the fragmentation of medullary megakaryocytes. Activated platelets adhere to the damaged endothelium by means of glycoproteins on their surface, forming the platelet plug. Activated platelets can also secrete the contents of their granules, notably the growth factors contained in the α-granules, which are involved in platelet aggregation and maintain endothelial activation, but also contribute to vascular repair and angiogenesis. Platelets also have a major inflammatory and immune function in antibacterial defence, essentially through their Toll-like Receptors (TLRs) and Sialic acid-binding immunoglobulin-type lectin (SIGLEC). Platelet activation also contributes to the extensive release of anti- or pro-inflammatory mediators such as IL-1β, RANTES (Regulated on Activation, Normal T Expressed and Secreted) or CD154, also known as the CD40-ligand. Platelets are involved in the direct activation of immune cells, polynuclear neutrophils (PNNs) and dendritic cells via the CD40L/CD40 complex. As a general rule, all of the studies presented in this review show that platelets are capable of covering most of the stages of inflammation, primarily through the CD40L/CD40 interaction, thus confirming their own role in this pathophysiological condition.

Using a Machine Learning Approach to Identify Key Biomarkers for Renal Clear Cell Carcinoma

Background

The most common and deadly subtype of renal carcinoma is kidney renal clear cell carcinoma (KIRC), which accounts for approximately 75% of renal carcinoma. However, the main cause of death in KIRC patients is tumor metastasis. There are no obvious clinical features in the early stage of kidney cancer, and 25–30% of patients have already metastasized when they are first diagnosed. Moreover, KIRC patients whose local tumors have been removed by nephrectomy are still at high risk of metastasis and recurrence and are not sensitive to chemotherapy and radiotherapy, leading to poor prognosis. Therefore, early diagnosis and treatment of this disease are very important.

Methods

KIRC-related patient datasets were downloaded from the GEO database and TCGA database. DEG screening and GO, KEGG and GSEA enrichment analysis was firstly conducted and then the LASSO and support vector machine (SVM) RFE algorithms were adopted to identify KIRC-associated key genes in training sets and validate them in the test set. The clinical prognostic analysis including the association between the expression of key genes and the overall survival, stage, grade across KIRC, the immune infiltration difference between normal samples and cancer samples, the correlation between the key genes and immune cells, immunomodulator, immune subtypes of KIRC were investigated in this research.

Results

We finally screened out 4 key genes, including ACPP, ANGPTL4, SCNN1G, SLC22A7. The expression of key genes show difference among normal samples and tumor samples, SCNN1G and SLC22A7 could be predictor of prognosis of patients. The expression of key genes was related with the abundance of tumor infiltration immune cells and the gene expression of immune checkpoint.

Conclusion

This study screened the 4 key genes, which contributed to early diagnosis, prognosis assessment and immune target treatment of patients with KIRC.

Modulation of the Complement System by Neoplastic Disease of the Central Nervous System

The complement system is a highly conserved component of innate immunity that is involved in recognizing and responding to pathogens. The system serves as a bridge between innate and adaptive immunity, and modulation of the complement system can affect the entire host immune response to a foreign insult. Neoplastic diseases have been shown to engage the complement system in order to evade the immune system, gain a selective growth advantage, and co-opt the surrounding environment for tumor proliferation. Historically, the central nervous system has been considered to be an immune-privileged environment, but it is now clear that there are active roles for both innate and adaptive immunity within the central nervous system. Much of the research on the role of immunological modulation of neoplastic disease within the central nervous system has focused on adaptive immunity, even though innate immunity still plays a critical role in the natural history of central nervous system neoplasms. Here, we review the modulation of the complement system by a variety of neoplastic diseases of the central nervous system. We also discuss gaps in the current body of knowledge and comment on future directions for investigation.

Ceruloplasmin overexpression is associated with oncogenic pathways and poorer survival rates in clear-cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is the most prevalent renal malignancy. The pathogenesis of the disease is currently poorly understood, and the prognosis is poor. Therefore, in this study, we focused on exploring and identifying genes and signal transduction pathways that are closely related to ccRCC. Differentially expressed genes (DEGs) were analyzed using the renal cell oncogene expression profiles GSE100666 and GSE68417. DAVID evaluation of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses was used. We constructed a protein-protein interaction (PPI) network of DEGS using Cytoscape software and analyzed the submodules with the CytoHubba plugin. Finally, we performed western blot, immunohistochemistry, and PCR validation by collecting tissues, and also utilized cells for in vitro functional analysis of ceruloplasmin (CP). In total, 202 DEGs (52 upregulated and 150 downregulated genes) were identified. Upregulated DEGs are significantly rich in angiogenesis, cell adhesion, and response to hypoxia, whereas downregulated DEGs are involved in intracellular pH regulation, excretion, coagulation, and chloride transmembrane transport. We selected the interactions of the top 20 hub genes provided by the PPI network, all of which are involved in important physiological pathways in vivo, such as complement and coagulation cascades. Tissue protein assays demonstrated that renal cancer highly expressed CP, while in vitro experiments showed that CP could promote the invasion of renal cancer cells. Our study suggests that ALB, C3, LOX, HRG, CXCR4, GPC3, SLC12A3, CP, and CASR may be involved in the development of ccRCC, and is expected to provide theoretical support for future studies on the diagnosis and targeted therapy of ccRCC.

Neutrophil extracellular traps in cancer

Beyond their well-known functions in the acute phases of the immune response, neutrophils play important roles in the various phases of tumor initiation and progression, through the release of their stored or newly synthesized mediators. In addition to reactive oxygen species, cytokines, chemokines, granule proteins and lipid mediators, neutrophil extracellular traps (NETs) can also be released upon neutrophil activation. NET formation can be achieved through a cell-death process or in association with the release of mitochondrial DNA from viable neutrophils. NETs are described as extracellular fibers of DNA and decorating proteins responsible for trapping and killing extracellular pathogens, playing a protective role in the antimicrobial defense. There is increasing evidence, however, that NETs play multiple roles in the scenario of cancer-related inflammation. For instance, NETs directly or indirectly promote tumor growth and progression, fostering tumor spread at distant sites and shielding cancer cells thus preventing the effects of cytotoxic lymphocytes. NETs can also promote tumor angiogenesis and cancer-associated thrombosis. On the other hand, there is some evidence that NETs may play anti-inflammatory and anti-tumorigenic roles. In this review, we focus on the main mechanisms underlying the emerging effects of NETs in cancer initiation and progression.

Development and Validation of a Practical Prognostic Coagulation Index for Patients with Esophageal Squamous Cell Cancer

BACKGROUND

This study aimed to establish an effective and practical prognostic index for esophageal squamous cell cancer (ESCC) based on the coagulation factors.

METHODS

The training cohort of 965 patients with ESCC was retrospectively collected at Sichuan Cancer Hospital from 2012 to 2014, along with clinical characteristics and follow-up information. Risk factors of coagulation status, including 11 blood parameters (platelet [PLT], mean platelet volume [MPV], platelet distribution width [PDW], plateletocrit [PCT], thrombin time [TT], prothrombin time [PT], international normalized ratio [INR], activated partial thromboplastin time [APTT], fibrinogen, D-dimer, and fibrinogen degradation product [FDP]), were studied by least absolute shrinkage and selection operator (LASSO) Cox regression and the Coagulation Index was established. The index was validated in a cohort of 848 patients with ESCC at the same institution, from 2015 to 2016.

RESULTS

Three variables of PLT, MPV, and fibrinogen were identified by selecting features with coefficients in the LASSO algorithm, and a Coagulation Index was established as follows: Coagulation Index = 0.0005 × PLT (10⁹/L) - 0.0384 × MPV (fL) + 0.1148 × fibrinogen (g/L). A higher Coagulation Index score was significantly associated with higher pT stage and pN stage (p < 0.05). With this prognostic index, patients could be stratified into three risk groups. The 3-year overall survival (OS) rates of the low-, middle- and high-risk groups in the training cohort were 63.5%, 55.5% and 43.1%, respectively (log-rank p < 0.001). Similarly, in the validation set, the respective 3-year OS for each risk group was significantly different across the three risk groups. Multivariate analysis indicated that the Coagulation Index remained a significant factor for predicting OS, independently of pathological TNM stage.

CONCLUSIONS

The Coagulation Index is an independent predictor of survival for patients with ESCC.

Neutrophil extracellular traps promote gastric cancer metastasis by inducing epithelial‑mesenchymal transition

The risks of tumor recurrence following the successful resection of the primary tumor have been known for decades; however, the precise mechanisms underlying treatment failures remain unknown. The formation of neutrophil extracellular traps (NETs) has increasingly been demonstrated to be associated with thrombi formation in cancer patients, as well as with the development and metastasis of cancer. The present study demonstrated that the level of peripheral blood NETs in patients with gastric cancer (GC) was associated with tumor progression, and patients with stage III/IV disease exhibited significant differences compared with the healthy controls and patients with stage I/II disease, which may be associated with an increased risk of metastasis. In addition, plasma from patients with stage III/IV GC was more prone to stimulate neutrophils to form NETs; thus, it was hypothesized that the formation of NETs may be affected by the tumor microenvironment. A higher deposition of NETs in GC tissues compared with normal resection margins was also identified. In vitro, following treatment with phorbol myristate acetate, which promotes the formation of NETs, or with DNAse-1/GSK-484, which inhibits the formation of NETs, it was found that the tumor migratory ability was altered; however, no significant changes were observed in cell proliferation and cell cycle progression. Epithelial-mesenchymal transition (EMT) is a key event associated with dissemination and metastasis in GC pathogenesis. Finally, the present study demonstrated that NETs promote a more aggressive mesenchymal phenotype and promote the progression of GC in vitro and in vivo. On the whole, to the best of our knowledge, the present study reports a previously unknown role of NETs in the regulation of GC, which is associated with EMT and migration. Therefore, targeting NETs may prove to be therapeutically beneficial.

The novel roles of virus infection-associated gene CDKN1A in chemoresistance and immune infiltration of glioblastoma

Chemoresistance is a common limitation for successful treatment of glioblastoma multiforme (GBM). Recently, virus infections have been demonstrated to be associated with tumorigenesis and chemoresistance in tumors. However, the role of infection-related genes in GBM haven’t been clearly demonstrated. Here, we explored the roles and mechanisms of human T-lymphotropic virus type-1 (HTLV-1) infections in tumorigenesis and chemoresistance in GBM. Four candidate genes, CDKN1A, MSX1, MYC and CHEK2, were identified to be the codifferentially expressed genes between three temozolomide (TMZ) chemotherapy datasets and one HTLV-1 infection gene set. Next, comprehensive bioinformatics data from several databases indicated that only CDKN1A was significantly upregulated in both GBM tissues and cells and showed the greatest prognostic value in GBM patients. Clinical data identified the correlations between CDKN1A expression and clinicopathological parameters of GBM patients. Moreover, CDKN1A was found to be involved in AKT-mediated TMZ resistance of glioma cells. In addition, KEGG analysis of CDKN1A-associated coexpression genes showed that CDKN1A was potentially involved in complement and coagulation cascades pathways in GBM. Finally, TISIDB database was used to investigate the role of CDKN1A in tumor-immune system interactions in GBM. These findings enhanced our understanding of the roles of CDKN1A in tumorigenesis and therapy response in GBM.

TMEM158 May Serve as a Diagnostic Biomarker for Anaplastic Thyroid Carcinoma: An Integrated Bioinformatic Analysis

Anaplastic thyroid carcinoma (ATC) is a rare but extremely lethal malignancy. However, little is known about the pathogenesis of ATC. Given its high mortality, it is critical to improve our understanding of ATC pathogenesis and to find new diagnostic biomarkers. In the present study, two gene microarray profiles (GSE53072 and GSE65144), which included 17 ATC and 17 adjacent non-tumorous tissues, were obtained. Bioinformatic analyses were then performed. Immunohistochemistry (IHC) and receiver operating characteristic (ROC) curves were then used to detect transmembrane protein 158 (TMEM158) expression and to assess diagnostic sensitivity. A total of 372 differentially expressed genes (DEGs) were identified. Through protein-protein interaction (PPI) analysis, we identified a significant module with 37 upregulated genes. Most of the genes in this module were related to cell-cycle processes. After co-expression analysis, 132 hub genes were selected for further study. Nine genes were identified as both DEGs and genes of interest in the weighted gene co-expression network analysis (WGCNA). IHC and ROC curves confirmed that TMEM158 was overexpressed in ATC tissue as compared with other types of thyroid cancer and normal tissue samples. We identified 8 KEGG pathways that were associated with high expression of TMEM158, including aminoacyl-tRNA biosynthesis and DNA replication. Our results suggest that TMEM158 may be a potential oncogene and serve as a diagnostic indicator for ATC.

Screening and identification of key genes and pathways in metastatic uveal melanoma based on gene expression using bioinformatic analysis

The current study aimed to elucidate the molecular mechanisms and identify the potential key genes and pathways for metastatic uveal melanoma (UM) using bioinformatics analysis.Gene expression microarray data from GSE39717 included 39 primary UM tissue samples and 2 metastatic UM tissue samples. Differentially expressed genes (DEGs) were generated using Gene Expression Omnibus 2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the online Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. The web-based STRING tool was adopted to construct a protein--protein interaction (PPI) network. The MCODE tool in Cytoscape was used to generate significant modules of the PPI network.A total of 213 DEGs were identified. GO and KEGG analyses revealed that the upregulated genes were mainly enriched in extracellular matrix organization and blood coagulation cascades, while the downregulated DEGs were mainly related to protein binding, negative regulation of ERK cascade, nucleus and chromatin modification, and lung and renal cell carcinoma. The most significant module was extracted from the PPI network. GO and KEGG enrichment analyses of the module revealed that the genes were mainly enriched in the extracellular region and space organization, blood coagulation process, and PI3K-Akt signaling pathway. Hub genes, including FN1, APOB, F2, SERPINC1, SERPINA1, APOA1, FGG, PROC, ITIH2, VCAN, TFPI, CXCL8, CDH2, and HP, were identified from DEGs. Survival analysis and hierarchical clustering results revealed that most of the hub genes were associated with prognosis and clinical progression.Results of this bioinformatics analysis may provide predictive biomarkers and potential candidate therapeutic targets for individuals with metastatic UM.

Identification of key differentially expressed mRNAs and microRNAs in non-small cell lung cancer using bioinformatics analysis

Non-small cell lung cancer (NSCLC) is a leading cause of mortality worldwide. However, the pathogenesis of NSCLC remains to be fully elucidated. Therefore, the present study aimed to explore the differential expression of mRNAs and microRNAs (miRNAs/miRs) in NSCLC and to determine how these RNA molecules interact with one another to affect disease progression. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified from the GSE18842, GSE32863 and GSE29250 datasets downloaded from the Gene Expression Omnibus (GEO database). Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. STRING, Cytoscape and MCODE were applied to construct a protein-protein interaction (PPI) network and to screen hub genes. The interactions between miRNAs and mRNAs were predicted using miRWalk 3.0 and a miRNA-mRNA regulatory network was constructed. The prognostic value of the identified hub genes was then evaluated via Kaplan-Meier survival analyses using datasets from The Cancer Genome Atlas. A total of 782 DEGs and 46 DEMs were identified from the 3 GEO datasets. The enriched pathways and functions of the DEGs and target genes of the DEMs included osteoclast differentiation, cell adhesion, response to a drug, plasma membrane, extracellular exosome and protein binding. A subnetwork composed of 11 genes was extracted from the PPI network and the genes in this subnetwork were mainly involved in the cell cycle, cell division and DNA replication. A miRNA-gene regulatory network was constructed with 247 miRNA-gene pairs based on 6 DEMs and 210 DEGs. Kaplan-Meier survival analysis indicated that the expression of ubiquitin E2 ligase C, cell division cycle protein 20, DNA topoisomerase IIα, aurora kinase A and B, cyclin B2, maternal embryonic leucine zipper kinase, slit guidance ligand 3, phosphoglucomutase 5, endomucin, cysteine dioxygenase type 1, dihydropyrimidinase-like 2, miR-130b, miR-1181 and miR-127 was significantly associated with overall survival of patients with lung adenocarcinoma. In the present study, a miRNA-mRNA regulatory network in NSCLC was established, which may provide future avenues for scientific exploration and therapeutic targeting of NSCLC.

PTX3 modulates the immunoflogosis in tumor microenvironment and is a prognostic factor for patients with clear cell renal cell carcinoma

Pentraxin-3 (PTX3) belongs to the pentraxine family, innate immune regulators involved in angiogenesis, proliferation and immune escape in cancer. Here, we evaluated PTX3 tissue expression and serum levels as biomarkers of clear cell renal cell carcinoma (ccRCC) and analyzed the possible role of complement system activation on tumor site. A 10-year retrospective cohort study including patients undergoing nephrectomy for ccRCC was also performed. PTX3 expression was elevated in both neoplastic renal cell lines and tissues, while it was absent in both normal renal proximal tubular cells (HK2) and normal renal tissues. Analysis of complement system activation on tumor tissues showed the co-expression of PTX3 with C1q, C3aR, C5R1 and CD59, but not with C5b-9 terminal complex. RCC patients showed higher serum PTX3 levels as compared to non-neoplastic patients (p<0.0001). Higher PTX3 serum levels were observed in patients with higher Fuhrman grade (p<0.01), lymph node (p<0.0001), and visceral metastases (p<0.001). Patients with higher PTX3 levels also showed significantly lower survival rates (p=0.002). Our results suggest that expression of PTX3 can affect the immunoflogosis in the ccRCC microenvironment, by activating the classical pathway of CS (C1q) and releasing pro-angiogenic factors (C3a, C5a). The up-regulation of CD59 also inhibits the complement-mediated cellular lysis.

Clinicopathological value and underlying molecular mechanism of annexin A2 in 992 cases of thyroid carcinoma

BACKGROUND

Thyroid carcinoma (THCA) is one of the most frequent endocrine cancers and has increasing morbidity. Annexin A2 (ANXA2) has been found to be highly expressed in various cancers; however, its expression level and potential mechanism in THCA remain unknown. This study investigated the clinicopathological value and primary molecular machinery of ANXA2 in THCA.

MATERIAL AND METHODS

Public RNA-sequencing and microarray data were obtained and analyzed with ANXA2 expression in THCA and corresponding non-cancerous thyroid tissue. A Pearson correlation coefficient calculation was used for the acquisition of ANXA2 coexpressed genes, while edgR, limma, and Robust Rank Aggregation were employed for differentially expressed gene (DEG) in THCA. The probable mechanism of ANXA2 in THCA was predicted by gene ontology and pathway enrichment. A dual-luciferase reporter assay was employed to confirm the targeting relationships between ANXA2 and its predicted microRNA (miRNA).

RESULTS

Expression of ANXA2 was significantly upregulated in THCA tissues with a summarized standardized mean difference of 1.09 (P < 0.0001) based on 992 THCA cases and 589 cases of normal thyroid tissue. Expression of ANXA2 was related to pathologic stage. Subsequently, 1442 genes were obtained when overlapping 4542 ANXA2 coexpressed genes with 2248 DEGs in THCA; these genes were mostly enriched in pathways of extracellular matrix-receptor interaction, cell adhesion molecules, and complement and coagulation cascades. MiR-23b-3p was confirmed to target ANXA2 by dual-luciferase reporter assay.

CONCLUSIONS

Upregulated expression of ANXA2 may promote the malignant biological behavior of THCA by affecting the involving pathways or being targeted by miR-23b-3p.

Platelets and cancer-associated thrombosis: focusing on the platelet activation receptor CLEC-2 and podoplanin

Patients with cancer have an increased risk of thromboembolism, which is the second leading cause of death in these patients. Several mechanisms of the prothrombotic state in these patients have been proposed. Among them are a platelet activation receptor, C-type lectin-like receptor 2 (CLEC-2), and its endogenous ligand podoplanin, which are the focus of this review. CLEC-2 is almost specifically expressed in platelets/megakaryocytes in humans. A membrane protein, podoplanin is expressed in certain types of cancer cells, including squamous cell carcinoma, brain tumor, and osteosarcoma, in addition to several normal tissues, including kidney podocytes and lymphatic endothelial cells but not vascular endothelial cells. In the bloodstream, podoplanin induces platelet activation by binding to CLEC-2 and facilitates hematogenous cancer metastasis and cancer-associated thrombosis. In an experimental lung metastasis model, the pharmacological depletion of CLEC-2 from platelets in mice resulted in a marked reduction of lung metastasis of podoplanin-expressing B16F10 cells. Control mice with B16F10 orthotopically inoculated in the back skin showed massive thrombus formation in the lungs, but the cancer-associated thrombus formation in CLEC-2-depleted mice was significantly inhibited, suggesting that CLEC-2-podoplanin interaction stimulates cancer-associated thrombosis. Thromboinflammation induced ectopic podoplanin expression in vascular endothelial cells or macrophages, which may also contribute to cancer-associated thrombosis. CLEC-2 depletion in cancer-bearing mice resulted in not only reduced cancer-associated thrombosis but also reduced levels of plasma inflammatory cytokines, anemia, and sarcopenia, suggesting that cancer-associated thrombosis may cause thromboinflammation and cancer cachexia. Blocking CLEC-2-podoplanin interaction may be a novel therapeutic strategy in patients with podoplanin-expressing cancer.

Platelets and cancer-associated thrombosis: focusing on the platelet activation receptor CLEC-2 and podoplanin

Patients with cancer have an increased risk of thromboembolism, which is the second leading cause of death in these patients. Several mechanisms of the prothrombotic state in these patients have been proposed. Among them are a platelet activation receptor, C-type lectin-like receptor 2 (CLEC-2), and its endogenous ligand podoplanin, which are the focus of this review. CLEC-2 is almost specifically expressed in platelets/megakaryocytes in humans. A membrane protein, podoplanin is expressed in certain types of cancer cells, including squamous cell carcinoma, brain tumor, and osteosarcoma, in addition to several normal tissues, including kidney podocytes and lymphatic endothelial cells but not vascular endothelial cells. In the bloodstream, podoplanin induces platelet activation by binding to CLEC-2 and facilitates hematogenous cancer metastasis and cancer-associated thrombosis. In an experimental lung metastasis model, the pharmacological depletion of CLEC-2 from platelets in mice resulted in a marked reduction of lung metastasis of podoplanin-expressing B16F10 cells. Control mice with B16F10 orthotopically inoculated in the back skin showed massive thrombus formation in the lungs, but the cancer-associated thrombus formation in CLEC-2-depleted mice was significantly inhibited, suggesting that CLEC-2-podoplanin interaction stimulates cancer-associated thrombosis. Thromboinflammation induced ectopic podoplanin expression in vascular endothelial cells or macrophages, which may also contribute to cancer-associated thrombosis. CLEC-2 depletion in cancer-bearing mice resulted in not only reduced cancer-associated thrombosis but also reduced levels of plasma inflammatory cytokines, anemia, and sarcopenia, suggesting that cancer-associated thrombosis may cause thromboinflammation and cancer cachexia. Blocking CLEC-2-podoplanin interaction may be a novel therapeutic strategy in patients with podoplanin-expressing cancer.

The Interplay Between Blood Proteins, Complement, and Macrophages on Nanomedicine Performance and Responses

In the blood, depending on their physicochemical characteristics, nanoparticles attract a wide range of plasma biomolecules. The majority of blood biomolecules bind nonspecifically to nanoparticles. On the other hand, biomolecules such as pattern-recognition complement-sensing proteins may recognize some structural determinants of the pristine surface, causing complement activation. Adsorption of nonspecific blood proteins could also recruit natural antibodies and initiate complement activation, and this seems to be a global process with many preclinical and clinical nanomedicines. We discuss these issues, since complement activation has ramifications in nanomedicine stability and pharmacokinetics, as well as in inflammation and disease progression. Some studies have also predicted a role for complement systems in infusion-related reactions, whereas others show a direct role for macrophages and other immune cells independent of complement activation. We comment on these discrepancies and suggest directions for exploring the underlying mechanisms.

Platelet Inflammatory Response to Stress

Blood platelets play a central hemostatic role, (i) as they repair vascular epithelial damage, and (ii) they play immune defense roles, as they have the capacity to produce and secrete various cytokines, chemokines, and related products. Platelets sense and respond to local dangers (infectious or not). Platelets, therefore, mediate inflammation, express and use receptors to bind infectious pathogen moieties and endogenous ligands, among other components. Platelets contribute to effective pathogen clearance. Damage-associated molecular patterns (DAMPs) are danger signals released during inflammatory stress, such as burns, trauma and infection. Each pathogen is recognized by its specific molecular signature or pathogen-associated molecular pattern (PAMP). Recent data demonstrate that platelets have the capacity to sense external danger signals (DAMPs or PAMPs) differentially through a distinct type of pathogen recognition receptor (such as Toll-like receptors). Platelets regulate the innate immune response to pathogens and/or endogenous molecules, presenting several types of “danger” signals using a complete signalosome. Platelets, therefore, use complex tools to mediate a wide range of functions from danger sensing to tissue repair. Moreover, we noted that the secretory capacity of stored platelets over time and the development of stress lesions by platelets upon collection, processing, and storage are considered stress signals. The key message of this review is the “inflammatory response to stress” function of platelets in an infectious or non-infectious context.

Neutrophil extracellular traps enhance procoagulant activity in patients with oral squamous cell carcinoma

BACKGROUND

Hypercoagulability is a major cancer-associated complication linked to poor patient prognosis. The production of neutrophil extracellular traps (NETs) is increasingly found to be linked with the development and metastasis of cancer, as well as with thrombi formation in cancer patients. We hypothesized that the neutrophil NET release may be triggered by specific cytokines in oral squamous cell carcinoma (OSCC) patients, thereby predisposing them to a hypercoagulable state. Moreover, we have evaluated the interaction between NETs and endothelial cells (ECs).

METHODS

NET procoagulant activity was assessed based on fibrin and purified coagulation complex production assays, as well as by measuring coagulation time (CT). We further used confocal microscopy to quantify the exposure of phosphatidylserine (PS), fibrin strands, and cell FVa/Xa binding.

RESULTS

OSCC patients with stage III/IV exhibited elevated plasma NET levels compared to stage I/II or CTR (all P < 0.05). Neutrophils from OSCC patients are predisposed to amplified NET release compared to those from CTR. Furthermore, depleting IL-8, IL-6, and TNF-α led to a reduction in NET release in the plasma. OSCC NETs increased thrombin and fibrin generation and decreased CT significantly (P < 0.05). When NETs were isolated and used to treat ECs, these cells exhibited disrupted morphology by retracting from their cell-cell junctions and convert to a procoagulant phenotype. These effects could be attenuated by approximately 70% using DNase I.

CONCLUSIONS

Our findings are consistent with a model wherein OSCC drives a systemic inflammatory state, which, in turn, drives neutrophils to prime and release NETs, which drive the development of a hypercoagulable state. Intervening in this process may be a viable means of disrupting these undesirable coagulation dynamics in stage III/IV OSCC patients.

The Long Pentraxin PTX3 as a Link Between Innate Immunity, Tissue Remodeling, and Cancer

The innate immune system comprises a cellular and a humoral arm. Humoral pattern recognition molecules include complement components, collectins, ficolins, and pentraxins. These molecules are involved in innate immune responses by recognizing microbial moieties and damaged tissues, activating complement, exerting opsonic activity and facilitating phagocytosis, and regulating inflammation. The long pentraxin PTX3 is a prototypic humoral pattern recognition molecule that, in addition to providing defense against infectious agents, plays several functions in tissue repair and regulation of cancer-related inflammation. Characterization of the PTX3 molecular structure and biochemical properties, and insights into its interactome and multiple roles in tissue damage and remodeling support the view that microbial and matrix recognition are evolutionarily conserved functions of humoral innate immunity molecules.

Emodin regulates neutrophil phenotypes to prevent hypercoagulation and lung carcinogenesis

BACKGROUND

Hypercoagulation and neutrophilia are described in several cancers, however, whether they are involved in lung carcinogenesis is currently unknown. Emodin is the main bioactive component from Rheum palmatum and has many medicinal values, such as anti-inflammation and anticancer. This study is to investigate the contributions of neutrophils to the effects of emodin on hypercoagulation and carcinogenesis.

METHODS

The effects of emodin on neutrophil phenotypes were assessed by cell proliferation, morphological changes, phagocytosis and autophagy in vitro. The anti-coagulation and cancer-preventing actions of emodin were evaluated in the urethane-induced lung carcinogenic model. The expressions of Cit-H3 and PAD4 in lung sections were assessed by immunohistochemistry, CD66b⁺ neutrophils were distinguished by immunofluorescence, and cytokines and ROS were examined with ELISA. The neutrophils-regulating and hypercoagulation-improving efficacies of emodin were confirmed in a Lewis lung cancer allograft model. The related targets and pathways of emodin were predicted by network pharmacology.

RESULTS

In vitro, emodin at the dose of 20 µM had no effect on cell viability in HL-60N1 but increased ROS and decreased autophagy and thus induced apoptosis in HL-60N2 with the morphological changes. In the urethane-induced lung carcinogenic model, before lung carcinogenesis, urethane induced obvious hypercoagulation which was positively correlated with lung N2 neutrophils. There were the aggravated hypercoagulation and lung N2 neutrophils after lung carcinoma lesions. Emodin treatment resulted in the ameliorated hypercoagulation and lung carcinogenesis accompanied by the decreased N2 neutrophils (CD66b⁺) in the alveolar cavity. ELISA showed that there were more IFN-γ, IL-12 and ROS and less IL-6, TNF-α and TGF-β1 in the alveolar cavity in the emodin group than those in the control group. Immunohistochemical analysis showed that emodin treatment decreased Cit-H3 and PAD4 in lung sections. In the Lewis lung cancer allograft model, emodin inhibits tumor growth accompanied by the attenuated coagulation and intratumor N2 neutrophils. Network pharmacology indicated the multi-target roles of emodin in N2 neutrophil activation.

CONCLUSIONS

This study suggests a novel function of emodin, whereby it selectively suppresses N2 neutrophils to prevent hypercoagulation and lung carcinogenesis.

The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasets

Papillary renal cell carcinoma (PRCC) accounts for 15–20% of all kidney neoplasms and continually attracts attention due to the increase in the incidents in which it occurs. The molecular mechanism of PRCC remains unclear and the efficacy of drugs that treat PRCC lacks sufficient evidence in clinical trials. Therefore, it is necessary to investigate the underlying mechanism in the development of PRCC and identify additional potential anti-PRCC drugs for its treatment. The differently expressed genes (DEGs) of PRCC were identified, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for functional annotation. Then, potential drugs for PRCC treatment were predicted by Connectivity Map (Cmap) based on DEGs. Furthermore, the latent function of query drugs in PRCC was explored by integrating drug-target, drug-pathway and drug-protein interactions. In total, 627 genes were screened as DEGs, and these DEGs were annotated using KEGG pathway analyses and were clearly associated with the complement and coagulation cascades, amongst others. Then, 60 candidate drugs, as predicted based on DEGs, were obtained from the Cmap database. Vorinostat was considered as the most promising drug for detailed discussion. Following protein-protein interaction (PPI) analysis and molecular docking, vorinostat was observed to interact with C3 and ANXN1 proteins, which are the upregulated hub genes and may serve as oncologic therapeutic targets in PRCC. Among the top 20 metabolic pathways, several significant pathways, such as complement and coagulation cascades and cell adhesion molecules, may greatly contribute to the development and progression of PRCC. Following the performance of the PPI network and molecular docking tests, vorinostat exhibited a considerable and promising application in PRCC treatment by targeting C3 and ANXN1.

Mixed cerebrovascular disease in an elderly patient with mixed vascular risk factors: a case report

BACKGROUND

Mixed cerebrovascular disease is a diagnostic entity that presents with hemorrhagic and ischemic stroke clinically and/or subclinically. Here, we report a patient with mixed vascular risk factors, who presented with multiple intracerebral hemorrhages and a simultaneously occurring cerebral infarction with hemorrhagic transformation.

CASE PRESENTATION

A 63-year-old male with no history of trauma or prior neurological disease presented with a sudden onset of weakness in his right limbs, followed by an episode of focal seizure without impaired awareness. The patient had a 4-year history of deep vein thrombosis in the lower limbs, and a 2-year history of Raynaud's phenomenon in the hands. He also had a family history of hypertension and thrombophilia. Head computed tomography plain scans showed two high densities in the bilateral parietal lobes and one mixed density in the left frontal lobe. The patient was diagnosed with mixed cerebrovascular disease. In this report, we make a systematic clinical reasoning regarding the etiological diagnosis, and discuss the possible pathogenic mechanisms leading to mixed cerebrovascular disease. We exclude coagulopathy, endocarditis, atrial fibrillation, patent foramen ovale, brain tumor, cerebral venous thrombosis, cerebral vascular malformation, cerebral amyloid angiopathy and vasculitis as causative factors. We identify hypertension, hereditary protein S deficiency, hypercholesteremia and hyperhomocysteinemia as contributing etiologies in this case.

CONCLUSION

This case presents complex underlying mechanisms of mixed cerebrovascular disease, in which hypertension and hyperhomocysteinemia are considered to play a central role.

Identifying the key genes and microRNAs in colorectal cancer liver metastasis by bioinformatics analysis and in vitro experiments

Colorectal cancer (CRC) is one of the principal causes of cancer‑associated mortality worldwide. The high incidence of liver metastasis is the leading risk factor of mortality in patients with CRC, and the mechanisms of CRC liver metastasis are poorly understood. In the present study, 7 datasets, including 3 gene expression profile datasets and 4 microRNA (miRNA) expression profile datasets were downloaded from the NCBI Gene Expression Omnibus (GEO) database to identify potential key genes and miRNAs, which may be candidate biomarkers for CRC liver metastasis. Differentially expressed (DE) genes (DEGs) and DE miRNAs of primary CRC tumor tissues and liver metastatic CRC tumor tissues were selected using the GEO2R tool. Gene Ontology and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery online database. Furthermore, Cytoscape with cytoHubba and the Molecular Complex Detection (MCODE) plug‑in were used to visualize a protein‑protein interaction (PPI) network for these DEGs, and to screen hub genes and gene modules in the PPI network. In addition, the online databases, TargetScan, miRanda, PITA, miRWalk and miRDB, were used to identify the target genes of the DE miRNAs. In the present study, 141 DEGs (97 upregulated and 44 downregulated) and 3 DE miRNAs (2 upregulated and 1 downregulated) were screened from the 3 gene expression microarray datasets and 4 miRNA expression microarray datasets, respectively. In total, 10 hub genes with a high degree of connectivity were selected from the PPI network, including albumin (ALB), coagulation factor II (F2), thrombin, apolipoprotein H (APOH), serpin family C member 1 (SERPINC1), apolipoprotein A1 (APOA1), α‑1‑microglobulin/bikunin precursor (AMBP), apolipoprotein C3 (APOC3), plasminogen (PLG), α‑2 HS glycoprotein (AHSG) and apolipoprotein B (APOB). The most important module was detected in the PPI network using the MCODE plug‑in. A total of 20 DEGs were identified to be potential target genes of these DE miRNAs, and novel miRNA‑DEGs regulatory axes were constructed. In vitro experiments were performed to demonstrate that miR‑885 promoted CRC cell migration by, at least partially, decreasing the expression of von Willebrand factor (vWF) and insulin‑like growth factor binding protein 5 (IGFBP5). In conclusion, by using integrated bioinformatics analysis and in vitro experiments, key candidate genes were identified and novel miRNA‑mRNA regulatory axes in CRC liver metastasis were constructed, which may improve understanding of the molecular mechanisms underlying CRC liver metastasis.

Identification of genes and pathways in esophageal adenocarcinoma using bioinformatics analysis

Esophageal adenocarcinoma (EAC) is one of the most common subtypes of esophageal cancer, and is associated with a low 5-year survival rate. The present study aimed to identify key genes and pathways associated with EAC using bioinformatics analysis. The gene expression profiles of GSE92396, which includes 12 EAC samples and 9 normal esophageal samples, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the EAC and normal samples were identified using the limma package in R language. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the identified DEGs were conducted using the online analysis tool, the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. Finally, module analysis was conducted for the PPI network using the MCODE plug-in in Cytoscape. Of the 386 DEGs identified, the 150 upregulated genes were mainly enriched in the KEGG pathways of complement and coagulation cascades, maturity onset diabetes of the young and protein digestion and absorption; and the 236 downregulated genes were mainly enriched in amoebiasis, retinol metabolism and drug metabolism-cytochrome P450. Based on information from the STRING database, a PPI network comprising of 369 nodes and 534 edges was constructed in Cytoscape. The top 10 hub nodes with the highest degrees were determined as interleukin-8, involucrin, tissue inhibitor of metalloproteinase 1, fibronectin 1, serpin family E member 1, serpin family A member 1, cystic fibrosis transmembrane conductance regulator, secreted phosphoprotein 1, collagen type I alpha 1 chain and angiotensinogen. A total of 6 modules were detected from the PPI network that satisfied the criteria of MCODE score >4 and number of nodes >4. KEGG pathways enriched for the module DEGs were mainly within arachidonic acid metabolism, complement and coagulation cascades and rheumatoid arthritis. In conclusion, identification of these key genes and pathways may improve understanding of the mechanisms underlying the development of EAC, and may be used as diagnostic and therapeutic targets in EAC.

Neutrophils and neutrophil extracellular traps in the liver and gastrointestinal system

Neutrophil extracellular traps (NETs) have an important role during infection by helping neutrophils to capture and kill pathogens. However, evidence is accumulating that uncontrolled or excessive production of NETs is related to the exacerbation of inflammation and the development of autoimmunity, cancer metastasis and inappropriate thrombosis. In this Review, we focus on the role of NETs in the liver and gastrointestinal system, outlining their protective and pathological effects. The latest mechanistic insights in NET formation, interactions between microorganisms and NETs and the relationship between neutrophil subtypes and their functions are also discussed. Additionally, we describe the potential importance of NET-related molecules, including cell-free DNA and hypercitrullinated histones, as biomarkers and targets for therapeutic intervention in gastrointestinal diseases.

Pretreatment hematocrit is negatively associated with response to neoadjuvant chemotherapy in breast cancer

AIM

To explore the correlation between hematocrit (Hct) and response to neoadjuvant chemotherapy in breast cancer.

METHODS

The baseline clinicopathologic variables of included patients were retrospectively reviewed. Binary logistic regression analysis was performed to assess the predictive value of Hct on objective response.

RESULTS

Patients in Hct <0.396 group showed higher objective response rate (ORR) compared with patients in Hct ≥0.396 group (55.8 vs 39.3%; p = 0.049), especially in human epidermal growth factor receptor 2 (HER2) overexpression subtype (p = 0.045), premenopausal patients (p = 0.019) and HER2-positve patients (p = 0.021), respectively. And Hct (OR: 0.43; 95% CI: 0.20-0.90; p = 0.024) was independently associated with ORR in breast cancer patients.

CONCLUSION

Hct was negatively associated with ORR, and may serve as an independent predictive factor for ORR in breast cancer patients underwent neoadjuvant chemotherapy.