TFPI2 suppresses breast cancer progression through inhibiting TWIST-integrin α5 pathway

Tissue factor pathway inhibitor-2 inhibits integrin β1 activation and focal adhesion formation and suppresses peritoneal ovarian cancer dissemination in mice

Tissue factor pathway inhibitor-2 (TFPI2) is a Kunitz-type serine protease inhibitor and an ovarian clear cell carcinoma (CCC) biomarker. TFPI2 is expressed in several cancers and exerts tumor-suppressive effects; however, the role of TFPI2 in the CCC cell phenotype remains unclear. Therefore, in this study, we investigated the function of TFPI2 by establishing a gene knockout (KO) in ES-2 CCC cells and observed the change in phenotypes in vitro and in vivo. TFPI2 KO inhibited ES-2 cell proliferation, increased extracellular matrix protein adhesion, enhanced focal adhesion formation and activated integrin β1 cell surface clustering in vitro, and markedly increased ES-2 tumor growth and dissemination in the peritoneal cavity of a mouse xenograft model. These findings suggest a novel function of TFPI2 expression in suppressing the formation of focal adhesions in CCC cells, potentially by activating integrin β1. This function plays a role in the peritoneal growth characteristics of CCC cells.

Tissue factor pathway inhibitor-2 (TFPI-2)-an underappreciated partaker in cancer and metastasis

The coagulation system is known to play an important role in cancer development and metastasis, but the precise mechanisms by which it does so remain incompletely understood. With this in mind, we provide an updated overview of the effects of TFPI-2, a protease inhibitor, on cancer development and metastasis. TFPI-2 interacts with the thrombin cascade and also employs other mechanisms to suppress cancer growth and dissemination, which include extracellular matrix stabilization, promotion of caspase-mediated cell apoptosis, inhibition of angiogenesis and transduction of intracellular signals. Down-regulation of TFPI-2 expression is well documented in numerous types of neoplasms, mainly via promoter methylation. However, the exact role of TFPI-2 in cancer progression and possible approaches to up-regulate TFPI-2 expression warrant further studies. Strategies to reactivate TFPI-2 may represent a promising direction for future anticancer studies and therapy development.

Tissue factor pathway inhibitor 2 (TFPI2) is a potential serum biomarker for clear cell renal carcinoma

Renal and ovarian clear cell carcinoma (CCC) are both characterized by a clear cytoplasm and exhibit similar genomic alterations and clinical characteristics. We hypothesized that both CCCs may share clinical biomarker. Tissue factor pathway inhibitor 2 (TFPI2), a serine protease inhibitor, has emerged as a promising serum biomarker for ovarian CCC, and we evaluated the efficacy of TFPI2 as a biomarker for renal cell carcinoma (RCC). Serum samples were collected from patients with RCC and healthy volunteers, and TFPI2 levels were measured. Expression of TFPI2 in each cell type was evaluated using single-cell RNA sequencing. Survival analyses according to TFPI2 expression levels were performed based on publicly available databases. Serum TFPI2 was significantly elevated in patients with RCC compared to healthy volunteers, particularly those with clear cell histology. Metastatic RCC tumors exhibited higher TFPI2 than localized RCCs. Moreover, higher TFPI2 correlated with higher Fuhrman grades in clear cell RCC. Publicly available databases showed an association between TFPI2 expression and overall survival, particularly in clear cell RCC. Single-cell RNA sequencing confirmed TFPI2 expression in clear cell RCC and normal kidney tubular epithelial cells. TFPI2 has emerged as a potential serum biomarker for RCC, offering avenues for improved detection and prognostication.

Identification of new subtypes of breast cancer based on vasculogenic mimicry related genes and a new model for predicting the prognosis of breast cancer

Breast cancer is a malignant tumor that poses a serious threat to women's health, and vasculogenic mimicry (VM) is strongly associated with bad prognosis in breast cancer. However, the relationship between VM and immune infiltration in breast cancer and the underlying mechanisms have not been fully studied. On the basis of the Cancer Genome Atlas (TCGA), Fudan University Shanghai Cancer Center (FUSCC) database, GSCALite database, and gene set enrichment analysis (GSEA) datasets, we investigated the potential involvement of VM-related genes in the development and progression of breast cancer. We analyzed the differential expression, mutation status, methylation status, drug sensitivity, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoints, tumor microenvironment (TME), and immune cell infiltration levels associated with VM-related genes in breast cancer. We created two VM subclusters out of breast cancer patients using consensus clustering, and discovered that patients in Cluster 1 had better survival outcomes compared to those in Cluster 2. The infiltration levels of T cells CD4 memory resting and T cells CD8 were higher in Cluster 1, indicating an immune-active state in this cluster. Additionally, we selected three prognostic genes (LAMC2, PIK3CA, and TFPI2) using Lasso, univariate, and multivariate Cox regression and constructed a risk model, which was validated in an external dataset. The prognosis of patients is strongly correlated with aberrant expression of VM-related genes, which advances our knowledge of the tumor immune milieu and enables us to identify previously unidentified breast cancer subtypes. This could direct more potent immunotherapy approaches.

Non-apoptotic regulatory cell death scoring system to predict the clinical outcome and drug choices in breast cancer

Background

Breast cancer (BC), the most common cancer among women globally, has been shown by numerous studies to significantly involve non-apoptotic regulatory cell death (RCD) in its pathogenesis and progression.

Methods

We obtained the RNA sequences and clinical data of BC patients from The Cancer Genome Atlas (TCGA) database for the training set, while datasets GSE96058, GSE86166, and GSE20685 from The Gene Expression Omnibus (GEO) database were utilized as validation cohorts. Initially, we performed non-negative matrix factorization (NMF) clustering analysis on the BC samples from the TCGA database to discern non-apoptotic RCD-related molecular subtypes. To identify prognostically-relevant non-apoptotic RCD genes (NRGs) and construct a prognostic model, we implemented three machine learning algorithms: lasso regression, random forest, and XGBoost analysis. The expression of selected genes was verified using real-time quantitative polymerase chain reaction (RT-qPCR), single-cell RNA-sequencing (scRNA-seq) analysis, and The Human Protein Atlas (HPA) database. The risk signature was evaluated concerning clinical characteristics and drug sensitivity. Furthermore, we developed a nomogram to predict BC patient survival.

Results

The NMF method successfully compartmentalized patients from the TCGA database into three distinct non-apoptotic RCD-related subtypes, with significant variations observed in immune characteristics and prognostic stratification across these subtypes. We identified 5 differentially expressed NRGs used in establishing the risk signature. Patients with different risk groups exhibited distinct clinicopathological features, drug sensitivity, and prognostic outcomes. A nomogram was subsequently developed, incorporating the NRGs-related risk signature, age, T stage, and N stage, to aid clinical decision-making.

Conclusion

We identified a novel NRGs-related risk signature, which was expected to become a potential prognostic marker in BC.

Transcriptomics Studies Reveal Functions of Transglutaminase 2 in Breast Cancer Cells Using Membrane Permeable and Impermeable Inhibitors

Transglutaminase 2 (TG2) performs many functions both under physiological and pathological conditions. In cancer, its expression is associated with aggressiveness, propensity to epithelial-mesenchymal transition, and metastasis. Since TG2 performs key functions both outside and inside the cell, using inhibitors with different membrane permeability we analyzed the changes in the transcriptome induced in two triple-negative cell lines (MDA-MB-436 and MDA-MB-231) with aggressive features. By characterizing pathways and gene networks, we were able to define the effects of TG2 inhibitors (AA9, membrane-permeable, and NCEG2, impermeable) in relation to the roles of the enzyme in the intra- and extracellular space within the context of breast cancer. The deregulated genes revealed p53 and integrin signaling to be the common pathways with some genes showing opposite changes in expression. In MDA-MB-436, AA9 induced apoptosis, modulated cadherin, Wnt, gastrin and cholecystokinin receptors (CCKR) mediated signaling, with RHOB and GNG2 playing significant roles, and affected the Warburg effect by decreasing glycolytic enzymes. In MDA-MB-231 cells, AA9 strongly impacted HIF-mediated hypoxia, including AKT and mTOR pathway. These effects suggest an anti-tumor activity by blocking intracellular TG2 functions. Conversely, the use of NCEG2 stimulated the expression of ATP synthase and proteins involved in DNA replication, indicating a potential promotion of cell proliferation through inhibition of extracellular TG2. To effectively utilize these molecules as an anti-tumor strategy, an appropriate delivery system should be evaluated to target specific functions and avoid adverse effects. Additionally, considering combinations with other pathway modulators is crucial.

[Role of COX-2/PGE2/EP4 Axis-induced Macrophage Functional Activation in NSCLC Development]

BACKGROUND

Tumor microenvironment (TME) is one of the important factors in tumorigenesis and progression, in which tumor-associated macrophages (TAMs) play an important role in non-small cell lung cancer (NSCLC) progression. However, the mechanism of TAMs in NSCLC progression remains unclear, so this study aimed to investigate the role of TAMs in NSCLC progression and to find potential therapeutic targets.

METHODS

Gene Expression Profiling Interactive Analysis (GEPIA) database was used to analyze the expression of prostaglandin E2 receptor 4 (EP4) mRNA in NSCLC and normal lung tissues; the protein expression levels of cyclooxygenase-2 (COX-2), EP4, cluster of differentiation 86 (CD86), CD163 and CD31 were detected by immunohistochemistry (IHC) in 120 NSCLC tissues and 24 paracancerous tissues specimens. The nude mouse lung adenocarcinoma cell A549 and macrophage RAW264.7 co-transplanted tumor model was established. And the samples were collected by gavage with EP4 inhibitor E7046, and then stained with hematoxylin-eosin (HE), IHC, and immunofluorescence (IF), and then detected by Western blot for the epithelial mesenchymal transformation (EMT) of the tumor tissues of the nude mice in each group. Western blot was used to detect the expressions of EMT related protiens in each group of nude mice; full-length transcriptome sequencing was used to screen the key genes causing liver metastasis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed.

RESULTS

EP4 mRNA expression level in NSCLC tissues was generally lower than that in normal lung tissues (P<0.05); COX-2, EP4, CD163, CD31 proteins were differentially expressed in NSCLC tissues and adjacent tissues, and differences were observed in many clinicopathological parameters of NSCLC patients; RAW264.7 shortened the latency period of tumorigenesis of A549 and promoted the proliferation of tumors and liver metastasis of tumors, and E7046 could reduce tumor cell proliferation activity, tumor tissue vascular density and M2-type macrophage infiltration in nude mice; IF staining showed that macrophages were mainly distributed around the metastatic foci of tumors; Western blot results showed that compared with A549 alone transplantation group, the relative expression of E-cadherin protein in tumor tissues of mice in A549 and RAW264.7 co-transplantation group was significantly decreased, and the difference was statistically significant (P<0.05), while the relative expression of N-cadherin protein was up-regulated, but the difference was not statistically significant (P>0.05); the main pathways enriched in the differential genes of the full-length transcriptome were the PI3K-AKT and MAPK signaling pathways.

CONCLUSIONS

During NSCLC development, the COX-2/PGE2/EP4 axis may promote tumor progression by inducing macrophage functional activation, and EP4 may be a potential new target for tumor immunotherapy. This study provides new perspectives and ideas for in-depth exploration of the mechanisms of NSCLC development, as well as a theoretical basis for the development of new therapeutic strategies for NSCLC.

PathExpSurv: pathway expansion for explainable survival analysis and disease gene discovery

BACKGROUND

In the field of biology and medicine, the interpretability and accuracy are both important when designing predictive models. The interpretability of many machine learning models such as neural networks is still a challenge. Recently, many researchers utilized prior information such as biological pathways to develop neural networks-based methods, so as to provide some insights and interpretability for the models. However, the prior biological knowledge may be incomplete and there still exists some unknown information to be explored.

RESULTS

We proposed a novel method, named PathExpSurv, to gain an insight into the black-box model of neural network for cancer survival analysis. We demonstrated that PathExpSurv could not only incorporate the known prior information into the model, but also explore the unknown possible expansion to the existing pathways. We performed downstream analyses based on the expanded pathways and successfully identified some key genes associated with the diseases and original pathways.

CONCLUSIONS

Our proposed PathExpSurv is a novel, effective and interpretable method for survival analysis. It has great utility and value in medical diagnosis and offers a promising framework for biological research.

Synthetic Reader-Actuators Targeted to Polycomb-Silenced Genes Block Triple-Negative Breast Cancer Proliferation and Invasion

Scientists have used pharmacological inhibitors of polycomb proteins to restore the expression of tumor suppressor genes and stop cancer proliferation and invasion. A major limitation of this approach is that key transcriptional activators, such as TP53 and BAF SWI/SNF, are often mutated in cancer. Poor clinical results for polycomb-targeting therapies in solid cancers, including triple-negative breast cancer (TNBC), could discourage the further development of epigenetic monotherapies. Here, we performed epigenome actuation with a synthetic reader-actuator (SRA) that binds trimethylated histone H3 lysine 27 in polycomb chromatin and modulates core transcriptional activators. In SRA-expressing TNBC BT-549 cells, 122 genes become upregulated ≥2-fold, including the genes involved in cell death, cell cycle arrest, and migration inhibition. The SRA-expressing spheroids showed reduced size in Matrigel and loss of invasion. Therefore, targeting Mediator-recruiting regulators to silenced chromatin can activate tumor suppressors and stimulate anti-cancer phenotypes, and further development of robust gene regulators might benefit TNBC patients.

Downregulated DUXAP8 lncRNA impedes trophoblast cell proliferation and migration by epigenetically upregulating TFPI2 expression

BACKGROUND

Preeclampsia (PE), a pregnancy complication characterized by new-onset hypertension and proteinuria during the second trimester, is the leading cause of neonatal and maternal morbidity and mortality. In the etiology of PE, failure of uterine spiral artery remodeling may be related to functioning abnormally of trophoblast cells, leading to the occurrence and progression of PE. Recently, long noncoding RNAs (lncRNAs) have been reported to play critical roles in PE nowadays. This study aimed to investigate the expression and functions of the TFPI2 pathway-related lncRNA DUXAP8.

METHODS

DUXAP8 expression in the placenta from pregnancies was examined using qPCR. Then, the in vitro functions of DUXAP8 were investigated through MTT, EdU, colony, transwell, and flow cytometry experiments. The downstream gene expression profiles were assessed using RNA transcriptome sequencing analysis and verified using qPCR and western blot. Furthermore, Immunoprecipitation (RIP), chromatin immunoprecipitation (CHIP) and fluorescence in situ hybridization (FISH) were used to detect the interaction between lncDUXAP8/EZH2/TFPI2.

RESULTS

The expression of lncRNA DUXAP8 in placenta of patients with eclampsia was significantly decreased. After knockout of DUXAP8, the proliferation and migration of trophoblasts were significantly decreased, and the percentage of apoptosis was increased. Flow cytometry showed that low expression of DUXAP8 increased the accumulation of cells in G2/M phase, while overexpression of DUXAP8 had the opposite effect. We also proved that DUXAP8 epigenetically inhibited TFPI2 expression by recruiting EZH2 and mediating H3K27me3 modification.

CONCLUSION

Together, these resulting data clarify that aberrant expression of DUXAP8 is involved in the potential PE development and progress. Unraveling the role of DUXAP8 will provide novel insights into the pathogenesis of PE.

Colon cancer transcriptome

Over the last four decades, methodological innovations have continuously changed transcriptome profiling. It is now feasible to sequence and quantify the transcriptional outputs of individual cells or thousands of samples using RNA sequencing (RNA-seq). These transcriptomes serve as a connection between cellular behaviors and their underlying molecular mechanisms, such as mutations. This relationship, in the context of cancer, provides a chance to unravel tumor complexity and heterogeneity and uncover novel biomarkers or treatment options. Since colon cancer is one of the most frequent malignancies, its prognosis and diagnosis seem to be critical. The transcriptome technology is developing for an earlier and more accurate diagnosis of cancer which can provide better protectivity and prognostic utility to medical teams and patients. A transcriptome is a whole set of expressed coding and non-coding RNAs in an individual or cell population. The cancer transcriptome includes RNA-based changes. The combined genome and transcriptome of a patient may provide a comprehensive picture of their cancer, and this information is beginning to affect treatment decision-making in real-time. A full assessment of the transcriptome of colon (colorectal) cancer has been assessed in this review paper based on risk factors such as age, obesity, gender, alcohol use, race, and also different stages of cancer, as well as non-coding RNAs like circRNAs, miRNAs, lncRNAs, and siRNAs. Similarly, they have been examined independently in the transcriptome study of colon cancer.

PIC recruitment by synthetic reader-actuators to polycomb-silenced genes blocks triple-negative breast cancer invasion

Scientists have used small molecule inhibitors and genetic knockdown of gene-silencing polycomb repressive complexes (PRC1/2) to determine if restoring the expression of tumor suppressor genes can block proliferation and invasion of cancer cells. A major limitation of this approach is that inhibitors can not restore key transcriptional activators that are mutated in many cancers, such as p53 and members of the BRAF SWI/SNF complex. Furthermore, small molecule inhibitors can alter the activity of, rather than inhibit, the polycomb enzyme EZH2. While chromatin has been shown to play a major role in gene regulation in cancer, poor clinical results for polycomb chromatin-targeting therapies for diseases like triple-negative breast cancer (TNBC) could discourage further development of this emerging avenue for treatment. To overcome the limitations of inhibiting polycomb to study epigenetic regulation, we developed an engineered chromatin protein to manipulate transcription. The synthetic reader-actuator (SRA) is a fusion protein that directly binds a target chromatin modification and regulates gene expression. Here, we report the activity of an SRA built from polycomb chromodomain and VP64 modules that bind H3K27me3 and subunits of the Mediator complex, respectively. In SRA-expressing BT-549 cells, we identified 122 upregulated differentially expressed genes (UpDEGs, ≥ 2-fold activation, adjusted p < 0.05). On-target epigenetic regulation was determined by identifying UpDEGs at H3K27me3-enriched, closed chromatin. SRA activity induced activation of genes involved in cell death, cell cycle arrest, and the inhibition of migration and invasion. SRA-expressing BT-549 cells showed reduced spheroid size in Matrigel over time, loss of invasion, and activation of apoptosis. These results show that Mediator-recruiting regulators broadly targeted to silenced chromatin activate silenced tumor suppressor genes and stimulate anti-cancer phenotypes. Therefore further development of gene-activating epigenetic therapies might benefit TNBC patients.

Using publicly available datasets to identify population-based transcriptomic landscape contributing to the aggressiveness of breast cancer in young women

Introduction: Although the risk of breast cancer increases with advancing age, some regions have larger number of young breast cancer patients (≤45 years-old), such as the Middle East, Eastern Asia, and North Africa, with more aggressive and poorly differentiated tumors. We aimed to conduct an in-silico analysis in an attempt to understand the aggressive nature of early-onset breast cancer, and to identify potential drivers of early-onset breast cancer using gene expression profiling datasets in a population-dependent manner. Methods: Functional genomics experiments data were acquired from cBioPortal database for cancer genomics, followed by the stratification of patients based on the age at representation of breast cancer and race. Differential gene expression analysis and gene amplification status analysis were carried out, followed by hub gene, transcription factor, and signalling pathway identification. Results: PAM50 subtype analysis revealed that young patients (≤45 years-old) had four-fold more basal tumors and worst progression-free survival (median of 101 months), compared with the 45-65 years group (median of 168 months). Fourteen genes were amplified in more than 14% of patients with an early-onset breast cancer. Interestingly, FREM2, LINC00332, and LINC00366 were exclusively amplified in younger patients. Gene expression data from three different populations (Asian, White, and African) revealed a unique transcriptomic profile of young patients, which was also reflected on the PAM50 subtype analysis. Our data indicates a higher tendency of young African patients to develop basal tumors, while young Asian patients are more prone to developing Luminal A tumors. Most genes that were found to be upregulated in younger patients are involved in important signaling pathways that promote cancer progression and metastasis, such as MAPK pathway, Reelin pathway and the PI3K/Akt pathway. Conclusion: This study provides strong evidence that the molecular profile of tumors derived from young breast cancer patients of different populations is unique and may explain the aggressiveness of these tumors, stressing the need to conduct population- based multi-omic analyses to identify the potential drivers for tumorigenesis and molecular profiles of young breast cancer patients.

Expression of DNAJB9 and some other genes is more sensitive to SWCNTs in normal human astrocytes than glioblastoma cells

Objective. Single-walled carbon nanotubes (SWCNTs) are considered to be one of the nanomaterials attractive for biomedical applications, particularly in the health sciences as imaging probes and drug carriers, especially in the field of cancer therapy. The increasing exploitation of nanotubes necessitates a comprehensive evaluation of the potential impact of these nanomaterials, which purposefully accumulate in the cell nucleus, on the human health and the function of the genome in the normal and tumor tissues. The aim of this study was to investigate the sensitivity of the expression of DNAJB9 and some other genes associated with the endoplasmic reticulum (ER) stress and cell proliferation to low doses of SWCNTs in normal human astrocytes (NHA/TS) and glioblastoma cells (U87MG) with and without an inhibition of ERN1 signaling pathway of the ER stress. Methods. Normal human astrocytes, line NHA/TS and U87 glioblastoma cells stable transfected by empty vector or dnERN1 (dominant-negative construct of ERN1) were exposed to low doses of SWCNTs (2 and 8 ng/ml) for 24 h. RNA was extracted from the cells and used for cDNA synthesis. The expression levels of DNAJB9, TOB1, BRCA1, DDX58, TFPI2, CLU, and P4HA2 mRNAs were measured by a quantitative polymerase chain reaction and normalized to ACTB mRNA. Results. It was found that the low doses of SWCNTs up-regulated the expression of DNAJB9, TOB1, BRCA1, DDX58, TFPI2, CLU, and P4HA2 genes in normal human astrocytes in dose-dependent (2 and 8 ng/ml) and gene-specific manner. These nanotubes also increased the expression of most studied genes in control (transfected by empty vector) U87 glioblastoma cells, but with much lesser extent than in NHA/TS. However, the expression of CLU gene in control U87 glioblastoma cells treated with SWCNTs was down-regulated in a dose-dependent manner. Furthermore, the expression of TOB1 and P4HA2 genes did not significantly change in these glioblastoma cells treated by lower dose of SWCNTs only. At the same time, inhibition of ERN1 signaling pathway of ER stress in U87 glioblastoma cells led mainly to a stronger resistance of DNAJB9, TOB1, BRCA1, DDX58, TFPI2, and P4HA2 gene expression to both doses of SWCNTs. Conclusion. The data obtained demonstrate that the low doses of SWCNTs disturbed the genome functions by changing the levels of key regulatory gene expressions in gene-specific and dose-dependent manner, but their impact was much stronger in the normal human astrocytes in comparison with the tumor cells. It is possible that ER stress, which is constantly present in tumor cells and responsible for multiple resistances, also created a partial resistance to the SWCNTs action. Low doses of SWCNTs induced more pronounced changes in the expression of diverse genes in the normal human astrocytes compared to glioblastoma cells indicating for a possible both genotoxic and neurotoxic effects with a greater extent in the normal cells.

Identification of Glucose Metabolism-Related Genes in the Progression from Nonalcoholic Fatty Liver Disease to Hepatocellular Carcinoma

Nonalcoholic fatty liver disease (NAFLD) is a manifestation of hepatic metabolic syndrome that varies in severity. Hepatocellular carcinoma progresses from NAFLD when there is heterogeneity in the infiltration of immune cells and molecules. A precise molecular classification of NAFLD remains lacking, allowing further exploration of the link between NAFLD and hepatocellular carcinoma. In this work, a weighted gene coexpression network analysis was used to identify two coexpression modules based on multiple omics data used to differentiate NAFLD subtypes. Additionally, key genes in the process of glucose metabolism and NAFLD were used to construct a prognostic model in a cohort of patients with hepatocellular carcinoma. Furthermore, the specific expression of signature genes in hepatocellular carcinoma cells was analyzed using a single-cell RNA sequencing approach. A total of 19 liver tissues of NAFLD patients were obtained from the GEO database, and 81 glucose metabolism-related genes were downloaded from the CTD database. In addition, based on nine signature genes, we constructed a prognostic model to divide the HCC cohort into high and low-risk groups. We also demonstrated a significant correlation between prognostic models and clinical phenotypes. Furthermore, we integrated single-cell RNA-sequencing data and immunology data to assess potential relationships between different molecular subtypes and hepatocellular carcinoma. Finally, our study discovered that the glucose metabolism pathway may play an important role in the process of NAFLD-hepatocellular carcinoma. In addition, three glucose metabolism-related genes (SERPINE1, VCAN, and TFPI2) may be the potential targets for the immunotherapy of patients with NAFLD-hepatocellular carcinoma.

Novel Methylation Biomarkers for Colorectal Cancer Prognosis

Colorectal cancer (CRC) comprises the third most common cancer worldwide and the second regarding number of deaths. In order to make a correct and early diagnosis to predict metastasis formation, biomarkers are an important tool. Although there are multiple signaling pathways associated with cancer progression, the most recognized are the MAPK pathway, p53 pathway, and TGF-β pathway. These pathways regulate many important functions in the cell, such as cell cycle regulation, proliferation, differentiation, and metastasis formation, among others. Changes in expression in genes belonging to these pathways are drivers of carcinogenesis. Often these expression changes are caused by mutations; however, epigenetic changes, such as DNA methylation, are increasingly acknowledged to play a role in the deregulation of oncogenic genes. This makes DNA methylation changes an interesting biomarkers in cancer. Among the newly identified biomarkers for CRC metastasis INHBB, SMOC2, BDNF, and TBRG4 are included, all of which are highly deregulated by methylation and closely associated with metastasis. The identification of such biomarkers in metastasis of CRC may allow a better treatment and early identification of cancer formation in order to perform better diagnostics and improve the life expectancy.

Toward an understanding of tissue factor pathway inhibitor-2 as a novel serodiagnostic marker for clear cell carcinoma of the ovary

AIMS

Tissue factor pathway inhibitor (TFPI)-2 has recently emerged as a serodiagnostic marker for patients with epithelial ovarian cancer (EOC), especially clear cell carcinoma (CCC). This review discusses the biological properties of TFPI-2 and why serum levels are elevated in CCC patients.

METHODS

A comprehensive literature search was conducted in PubMed up until March, 2021.

RESULTS

TFPI-2 is a Kunitz-type protease inhibitor and negatively regulates the enzymatic activities, such as plasmin. TFPI-2 has been characterized as a tumor suppressor gene and was frequently downregulated through promoter hypermethylation in various human cancers. In contrast, TFPI-2 was overexpressed only in CCC. TFPI-2 may be involved in the pathophysiology of CCC, possibly through regulation of coagulation system, stabilization of extracellular matrix (ECM), and induction of intracellular signal transduction. TFPI-2 suppresses tissue factor-induced hypercoagulation in a hypoxic environment. TFPI-2, secreted by CCC cells, platelets, and adjacent vascular endothelial cells, may suppress tumor growth and invasion through ECM remodeling. Nuclear TFPI-2 may suppress matrix metalloproteinase production via transcription factors and modulate caspase-mediated cell apoptosis. CCC cells may upregulate the TFPI-2 expression to adapt to survival in the demanding environment. TFPI-2 is secreted by CCC cells and enters the systemic circulation, resulting in elevated blood levels.

DISCUSSION

Serum TFPI-2 reflects the overexpression of TFPI-2 in CCC tissues and is a potential serodiagnostic marker. Further research is needed to explore the expression, clinical significance, biological function, and potential mechanism of TFPI-2 in CCC.

TFPI2 Promotes Perivascular Migration in an Angiotropism Model of Melanoma

Purpose

Angiotropism is the process by which cancer cells attach to and migrate along blood vessels to acquire vasculature, disseminate, and metastasize. However, the molecular basis for such vessel–tumor interactions has not been fully elucidated, partly due to limited experimental models. In this study, we aimed to observe and explore the molecular mechanism underlying angiotropism in melanoma.

Methods

To monitor the interactions of human melanoma cells with the vasculature in vivo, a murine coxenograft model was employed by co-injecting highly and poorly invasive melanoma cells subcutaneously. To identify key pathways and genes involved in the angiotropic phenotype of melanoma, analysis of differentially expressed genes (DEGs) and gene set enrichment analysis (GSEA) were performed. The role of tissue factor pathway inhibitor 2 (TFPI2) in angiotropism was evaluated by immunostaining, adhesion assay, shRNA, and in vivo tumorigenicity. Angiotropism and TFPI2 expression were examined in surgical specimens of melanoma by immunohistochemical staining. Data from The Cancer Genome Atlas (TCGA) were analyzed to explore the expression and prognostic implications of TFPI2 in uveal and cutaneous melanoma.

Results

Highly invasive melanoma cells spread along the branches of intratumor blood vessels to the leading edge of invasion in the coxenograft model, resembling angiotropic migration. Mechanisms underlying angiotropism were primarily associated with molecular function regulators, regulation of cell population proliferation, developmental processes, cell differentiation, responses to cytokines and cell motility/locomotion. TFPI2 downregulation weakened the perivascular migration of highly invasive melanoma cells. High levels of TFPI2 were correlated with worse and better survival in uveal and cutaneous melanoma, respectively.

Conclusion

These results provide a straightforward in vivo model for the observation of angiotropism and suggest that TFPI2 could inhibit the angiotropic phenotype of melanoma.

EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

BACKGROUND

Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.

METHODS

In this work, we study somatic mutation data consists of 450 metastatic breast tumor samples from cBio Cancer Genomics Portal. We use four software tools to extract features from this data. Then, an ensemble classifier (EC) learning algorithm called EARN (Ensemble of Artificial Neural Network, Random Forest, and non-linear Support Vector Machine) is proposed to evaluate plausible driver genes for metastatic breast cancer (MBCA). The decision-making strategy for the proposed ensemble machine is based on the aggregation of the predicted scores obtained from individual learning classifiers to be prioritized homo sapiens genes annotated as protein-coding from NCBI.

RESULTS

This study is an attempt to focus on the findings in several aspects of MBCA prognosis and diagnosis. First, drivers and passengers predicted by SVM, ANN, RF, and EARN are introduced. Second, biological inferences of predictions are discussed based on gene set enrichment analysis. Third, statistical validation and comparison of all learning methods are performed by some evaluation metrics. Finally, the pathway enrichment analysis (PEA) using ReactomeFIVIz tool (FDR < 0.03) for the top 100 genes predicted by EARN leads us to propose a new gene set panel for MBCA. It includes HDAC3, ABAT, GRIN1, PLCB1, and KPNA2 as well as NCOR1, TBL1XR1, SIRT4, KRAS, CACNA1E, PRKCG, GPS2, SIN3A, ACTB, KDM6B, and PRMT1. Furthermore, we compare results for MBCA to other outputs regarding 983 primary tumor samples of breast invasive carcinoma (BRCA) obtained from the Cancer Genome Atlas (TCGA). The comparison between outputs shows that ROC-AUC reaches 99.24% using EARN for MBCA and 99.79% for BRCA. This statistical result is better than three individual classifiers in each case.

CONCLUSIONS

This research using an integrative approach assists precision oncologists to design compact targeted panels that eliminate the need for whole-genome/exome sequencing. The schematic representation of the proposed model is presented as the Graphic abstract.

RNA-Seq Analysis of Cisplatin and the Monofunctional Platinum(II) Complex, Phenanthriplatin, in A549 Non-Small Cell Lung Cancer and IMR90 Lung Fibroblast Cell Lines

Phenanthriplatin is a new monofunctional platinum(II) complex that binds only one strand of DNA and acts by blocking gene transcription, but its effect on gene regulation has not been characterized relative to the traditional platinum-based complex, cisplatin. A549 non-small cell lung cancer and IMR90 lung fibroblast cells were treated with cisplatin, phenanthriplatin, or a control and then their RNA transcripts were subjected to next generation sequencing analysis. DESeq2 and CuffDiff2 were used to identify up- and downregulated genes and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used to identify pathways and functions. We found that phenanthriplatin may regulate the genes GPRC5a, TFF1, and TNFRSF10D, which act through p53 to control apoptosis, differently or to a greater extent than cisplatin, and that it, unlike cisplatin, could upregulate ATP5MD, a gene which signals through the Wnt/β catenin pathway. Furthermore, phenanthriplatin caused unique or enhanced effects compared to cisplatin on genes regulating the cytoskeleton, cell migration, and proliferation, e.g., AGAP1, DIAPH2, GDF15, and THSD1 (p < 0.05; q < 0.05). Phenanthriplatin may modulate some oncogenes differently than cisplatin potentially leading to improved clinical outcome, but this monofunctional complex should be carefully matched with cancer gene data to be successfully applied in chemotherapy.