Low expression of TBX4 predicts poor prognosis in patients with stage II pancreatic ductal adenocarcinoma

Multiomics2Targets identifies targets from cancer cohorts profiled with transcriptomics, proteomics, and phosphoproteomics

The availability of data from profiling of cancer patients with multiomics is rapidly increasing. However, integrative analysis of such data for personalized target identification is not trivial. Multiomics2Targets is a platform that enables users to upload transcriptomics, proteomics, and phosphoproteomics data matrices collected from the same cohort of cancer patients. After uploading the data, Multiomics2Targets produces a report that resembles a research publication. The uploaded matrices are processed, analyzed, and visualized using the tools Enrichr, KEA3, ChEA3, Expression2Kinases, and TargetRanger to identify and prioritize proteins, genes, and transcripts as potential targets. Figures and tables, as well as descriptions of the methods and results, are automatically generated. Reports include an abstract, introduction, methods, results, discussion, conclusions, and references and are exportable as citable PDFs and Jupyter Notebooks. Multiomics2Targets is applied to analyze version 3 of the Clinical Proteomic Tumor Analysis Consortium (CPTAC3) pan-cancer cohort, identifying potential targets for each CPTAC3 cancer subtype. Multiomics2Targets is available from https://multiomics2targets.maayanlab.cloud/.

Understanding the Conundrum of Pancreatic Cancer in the Omics Sciences Era

Pancreatic cancer (PC) is an increasing cause of cancer-related death, with a dismal prognosis caused by its aggressive biology, the lack of clinical symptoms in the early phases of the disease, and the inefficacy of treatments. PC is characterized by a complex tumor microenvironment. The interaction of its cellular components plays a crucial role in tumor development and progression, contributing to the alteration of metabolism and cellular hyperproliferation, as well as to metastatic evolution and abnormal tumor-associated immunity. Furthermore, in response to intrinsic oncogenic alterations and the influence of the tumor microenvironment, cancer cells undergo a complex oncogene-directed metabolic reprogramming that includes changes in glucose utilization, lipid and amino acid metabolism, redox balance, and activation of recycling and scavenging pathways. The advent of omics sciences is revolutionizing the comprehension of the pathogenetic conundrum of pancreatic carcinogenesis. In particular, metabolomics and genomics has led to a more precise classification of PC into subtypes that show different biological behaviors and responses to treatments. The identification of molecular targets through the pharmacogenomic approach may help to personalize treatments. Novel specific biomarkers have been discovered using proteomics and metabolomics analyses. Radiomics allows for an earlier diagnosis through the computational analysis of imaging. However, the complexity, high expertise required, and costs of the omics approach are the main limitations for its use in clinical practice at present. In addition, the studies of extracellular vesicles (EVs), the use of organoids, the understanding of host-microbiota interactions, and more recently the advent of artificial intelligence are helping to make further steps towards precision and personalized medicine. This present review summarizes the main evidence for the application of omics sciences to the study of PC and the identification of future perspectives.

Context-dependent T-BOX transcription factor family: from biology to targeted therapy

T-BOX factors belong to an evolutionarily conserved family of transcription factors. T-BOX factors not only play key roles in growth and development but are also involved in immunity, cancer initiation, and progression. Moreover, the same T-BOX molecule exhibits different or even opposite effects in various developmental processes and tumor microenvironments. Understanding the multiple roles of context-dependent T-BOX factors in malignancies is vital for uncovering the potential of T-BOX-targeted cancer therapy. We summarize the physiological roles of T-BOX factors in different developmental processes and their pathological roles observed when their expression is dysregulated. We also discuss their regulatory roles in tumor immune microenvironment (TIME) and the newly arising questions that remain unresolved. This review will help in systematically and comprehensively understanding the vital role of the T-BOX transcription factor family in tumor physiology, pathology, and immunity. The intention is to provide valuable information to support the development of T-BOX-targeted therapy.

Expression and prognosis analysis of TBX2 subfamily in human lung carcinoma

PURPOSE

Lung cancer has a high morbidity and mortality rate of all cancers worldwide. Therefore, there is an urgent need for reliable cancer markers for diagnosis and prognosis of patients with lung cancer.

METHODS

In this study, we used the bioinformatics database to compare the expression of the TBX2 subfamily at the transcriptional and protein levels in non-small cell lung cancer. Then, to confirm our bioinformatics analysis above, we used western bloting to determine the expression of TBX2, TBX3, TBX4 and TBX5 in human lung squamous carcinoma cell lines. Besides, low expression of TBX2 subfamily predicted a poor prognosis of patients with lung cancer. Finally, The methylation database was used to explore the relationship between the low expression of TBX2 subfamily and methylation of gene promoter region.

RESULTS

Our data showed a significant decrease of TBX2 subfamily expression in lung cancer tissues of several histological subtypes. Finally, the methylation of TBX2 subfamily members in the promoter region of NSCLC was significantly higher than that in normal tissues.

CONCLUSION

Our research provided sufficient evidence that TBX2 subfamily might play an inhibitory role in malignancy progression of lung cancer, which is promising to shed light on discovering a novel reliable cancer marker for prognosis of lung cancer patients.

DNA Methylation Biomarkers as Prediction Tools for Therapeutic Response and Prognosis in Intermediate-Stage Hepatocellular Carcinoma

INTRODUCTION

Alfa-fetoprotein (AFP), as the main serum tumor marker of hepatocellular carcinoma (HCC), is limited in terms of specificity and ability to predict outcomes. This study investigated the clinical utility of DNA methylation biomarkers to predict therapeutic responses and prognosis in intermediate-stage HCC.

METHODS

This study enrolled 72 patients with intermediate-stage HCC who underwent locoregional therapy (LRT) between 2020 and 2021. The immediate therapeutic response and disease status during a two-year follow-up were recorded. Analysis was performed on 10 selected DNA methylation biomarkers via pyrosequencing analysis of plasma collected before and after LRT.

RESULTS

Analysis was performed on 53 patients with complete responses and 19 patients with disease progression after LRT. The mean follow-up duration was 2.4 ± 0.6 years. A methylation prediction model for tumor response (MMTR) and a methylation prediction model for early progression (MMEP) were constructed. The area under the curve (AUC) for sensitivity and specificity of MMTR was 0.79 for complete response and 0.759 for overall survival. The corresponding AUCs for sensitivity and specificity of AFP and protein induced by vitamin K absence-II (PIVKA-II) were 0.717 and 0.708, respectively. Note that the MMTR index was the only significant predictor in multivariate analysis. The AUC for sensitivity and specificity of the MMEP in predicting early progression was 0.79. The corresponding AUCs for sensitivity and specificity of AFP and PIVKA-II were 0.758 and 0.714, respectively. Multivariate analysis revealed that platelet count, beyond up-to-7 criteria, and the MMEP index were strongly correlated with early tumor progression. Combining the indexes and serum markers further improved the predictive accuracy (AUC = 0.922). Multivariate analysis revealed the MMEP index was the only independent risk factor for overall survival.

DISCUSSION/CONCLUSIONS

This study indicates that these methylation markers could potentially outperform current serum markers in terms of accuracy and reliability in assessing treatment response and predicting outcomes. Combining methylation markers and serum markers further improved predictive accuracy, indicating that a multi-marker approach may be more effective in clinical practice. These findings suggest that DNA methylation biomarkers may be a useful tool for managing intermediate-stage HCC patients and guiding personalized treatment, particularly for those who are at high risk for close surveillance or adjuvant treatment after LRT.

Whole-genome DNA methylation and DNA methylation-based biomarkers in lung squamous cell carcinoma

Exploring early detection methods through comprehensive evaluation of DNA methylation for lung squamous cell carcinoma (LUSC) patients is of great significance. By using different machine learning algorithms for feature selection and model construction based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, five methylation biomarkers in LUSC (along with mapped genes) were identified including cg14823851 (TBX4), cg02772121 (TRIM15), cg10424681 (C6orf201), cg12910906 (ARHGEF4), and cg20181079 (OR4D11), achieving extremely high sensitivity and specificity in distinguishing LUSC from normal samples in independent cohorts. Pyrosequencing assay verified DNA methylation levels, meanwhile qRT-PCR and immunohistochemistry results presented their accordant methylation-related gene expression statuses in paired LUSC and normal lung tissues. The five methylation-based biomarkers proposed in this study have great potential for the diagnosis of LUSC and could guide studies in methylation-regulated tumor development and progression.

T-box transcription factor 19 promotes hepatocellular carcinoma metastasis through upregulating EGFR and RAC1

The effect of targeted therapy for metastatic hepatocellular carcinoma (HCC) is still unsatisfactory. Exploring the underlying mechanism of HCC metastasis is favorable to provide new therapeutic strategies. T-box (TBX) transcription factor family genes, which are crucial regulators in embryo and organ development, are vital for regulating tumor initiation, growth and metastasis. Here we explored the role of TBX19 in HCC metastasis, which is one of the most upregulated TBX family genes in human HCC tissues. TBX19 expression was markedly upregulated in HCC tissues and elevated TBX19 expression predicted poor prognosis. Overexpression of TBX19 enhanced HCC metastasis through upregulating epidermal growth factor receptor (EGFR) and Rac family small GTPase 1 (RAC1) expression. Downregulation of EGFR and RAC1 inhibited TBX19-mediated HCC metastasis, while upregulation of EGFR and RAC1 restored inhibition of HCC metastasis mediated by TBX19 knockdown. Furthermore, epidermal growth factor (EGF)/EGFR signaling upregulated TBX19 expression via the extracellular signal-regulated kinase (ERK)/nuclear factor (NF)-kB axis. Besides, the combined application of EGFR inhibitor Erlotinib and RAC1 inhibitor NSC23766 markedly inhibited TBX19-mediated HCC metastasis. In HCC cohorts, TBX19 expression was positively associated with EGFR and RAC1 expression. Patients with positive coexpression of TBX19/EGFR or TBX19/RAC1 displayed the poorest prognosis. In conclusion, EGF/EGFR signaling upregulated TBX19 expression via ERK/NF-kB pathway and TBX19 fostered HCC metastasis by enhancing EGFR and RAC1 expression, which formed an EGF-TBX19-EGFR positive feedback loop. Targeting this signaling pathway may offer a potential therapeutic strategy to efficiently restrain TBX19-mediated HCC metastasis.

Role of T-box genes in cancer, epithelial-mesenchymal transition, and cancer stem cells

Sharing a common DNA binding motif called T-box, transcription factor T-box gene family controls embryonic development and is also involved in cancer progression and metastasis. Cancer metastasis shows therapy resistance and involves complex processes. Among them, epithelial-mesenchymal transition (EMT) triggers cancer cell invasiveness and the acquisition of stemness of cancer cells, called cancer stem cells (CSCs). CSCs are a small fraction of tumor bulk and are capable of self-renewal and tumorsphere formation. Recent progress has highlighted the critical roles of T-box genes in cancer progression, EMT, and CSC function, and such regulatory functions of T-box genes have emerged as potential therapeutic candidates for cancer. Herein we summarize the current understanding of the regulatory mechanisms of T-box genes in cancer, EMT, and CSCs, and discuss the implications of targeting T-box genes as anticancer therapeutics.

Epigenetic changes in fibroblasts drive cancer metabolism and differentiation

Genomic changes that drive cancer initiation and progression contribute to the co-evolution of the adjacent stroma. The nature of the stromal reprogramming involves differential DNA methylation patterns and levels that change in response to the tumor and systemic therapeutic intervention. Epigenetic reprogramming in carcinoma-associated fibroblasts are robust biomarkers for cancer progression and have a transcriptional impact that support cancer epithelial progression in a paracrine manner. For prostate cancer, promoter hypermethylation and silencing of the RasGAP, RASAL3 that resulted in the activation of Ras signaling in carcinoma-associated fibroblasts. Stromal Ras activity initiated a process of macropinocytosis that provided prostate cancer epithelia with abundant glutamine for metabolic conversion to fuel its proliferation and a signal to transdifferentiate into a neuroendocrine phenotype. This epigenetic oncogenic metabolic/signaling axis seemed to be further potentiated by androgen receptor signaling antagonists and contributed to therapeutic resistance. Intervention of stromal signaling may complement conventional therapies targeting the cancer cell.

Male-Specific Long Noncoding RNA TTTY15 Inhibits Non-Small Cell Lung Cancer Proliferation and Metastasis via TBX4

Gender affects cancer susceptibility. Currently, there are only a few studies on Y chromosome-linked long noncoding RNAs (lncRNAs), and the potential association between lncRNAs and cancers in males has not been fully elucidated. Here, we examined the expression of testis-specific transcript Y-linked 15 (TTTY15) in 37 males with non-small cell lung cancer (NSCLC), and performed circular chromosome conformation capture with next-generation sequencing to determine the genomic interaction regions of the TTTY15 gene. Our results showed that the expression levels of TTTY15 were lower in NSCLC tissues. Lower TTTY15 expression levels were associated with Tumor-Node-Metastasis (TNM) stage. A TTTY15 knockdown promoted malignant transformation of NSCLC cells. Based on the bioinformatics analysis of circular chromosome conformation capture data, we found that T-box transcription factor 4 (TBX4) may be a potential target gene of TTTY15. The RNA immunoprecipitation and chromatin immunoprecipitation results showed that TTTY15 may interact with DNA (cytosine-5)-methyltransferase 3A (DNMT3A), and the TTTY15 knockdown increased the binding of DNMT3A to the TBX4 promoter. We concluded that low TTTY15 expression correlates with worse prognosis among patients with NSCLC. TTTY15 promotes TBX4 expression via DNMT3A-mediated regulation. The identification of lncRNAs encoded by male-specific genes may help to identify potential targets for NSCLC therapy.

TBX2 subfamily suppression in lung cancer pathogenesis: a high-potential marker for early detection

The TBX2 subfamily (TBXs 2, 3, 4 and 5) transactivates or represses genes involved in lung organogenesis. Yet TBX2 subfamily expression in pathogenesis of non-small cell lung cancer (NSCLC), the most common lung malignancy, remains elusive. We sought to probe the expression profile of the TBX2 subfamily in early phases of NSCLC. Expression of TBX2 subfamily was analyzed in datasets of pan-normal specimens as well as NSCLCs and normal lung tissues. TBX2 subfamily expression in matched normal lungs, premalignant hyperplasias and NSCLCs was profiled by transcriptome sequencing. TBX2 subfamily expression was evaluated in the cancerization field consisting of matched NSCLCs and adjacent cytologically-normal airways relative to distant normal lungs and in a dataset of normal bronchial samples from smokers with indeterminate nodules suspicious for malignancy. Statistical analysis was performed using R. TBX2 subfamily expression was markedly elevated in normal lungs relative to other organ-specific normal tissues. Expression of the TBXs was significantly suppressed in NSCLCs relative to normal lungs (P < 10⁻⁹). TBX2 subfamily was significantly progressively decreased across premalignant lesions and NSCLCs relative to normal lungs (P < 10⁻⁴). The subfamily was significantly suppressed in NSCLCs and adjacent normal-appearing airways relative to distant normal lung tissues (P < 10⁻¹⁵). Further, suppressed TBX2 subfamily expression in normal bronchi was associated with lung cancer status (P < 10⁻⁵) in smokers. Our findings suggest that the TBX2 subfamily is notably suppressed in human NSCLC pathogenesis and may serve as a high-potential biomarker for early lung cancer detection in high-risk smokers.

Systematic review of peri-operative prognostic biomarkers in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) continues to be associated with a poor prognosis. This systematic review aimed to summarize the literature regarding potential prognostic biomarkers to facilitate validation studies and clinical application.

METHODS

A systematic review was performed (2004-2014) according to PRISMA guidelines. Studies were ranked using REMARK criteria and the following outcomes were examined: overall/disease free survival, nodal involvement, tumour characteristics, metastasis, recurrence and resectability.

RESULTS

256 biomarkers were identified in 158 studies. 171 biomarkers were assessed with respect to overall survival: urokinase-type plasminogen activator receptor, atypical protein kinase C and HSP27 ranked the highest. 33 biomarkers were assessed for disease free survival: CD24 and S100A4 were the highest ranking. 17 biomarkers were identified for lymph node involvement: Smad4/Dpc4 and FOXC1 ranked highest. 13 biomarkers were examined for tumour grade: mesothelin and EGFR were the highest ranking biomarkers. 10 biomarkers were identified for metastasis: p16 and sCD40L were the highest ranking. 4 biomarkers were assessed resectability: sCD40L, s100a2, Ca 19-9, CEA.

CONCLUSION

This review has identified and ranked specific biomarkers that should be a primary focus of ongoing validation and clinical translational work in PDAC.

Biomarkers for pancreatic cancer: Recent achievements in proteomics and genomics through classical and multivariate statistical methods

Pancreatic cancer (PC) is one of the most aggressive and lethal neoplastic diseases. A valid alternative to the usual invasive diagnostic tools would certainly be the determination of biomarkers in peripheral fluids to provide less invasive tools for early diagnosis. Nowadays, biomarkers are generally investigated mainly in peripheral blood and tissues through high-throughput omics techniques comparing control vs pathological samples. The results can be evaluated by two main strategies: (1) classical methods in which the identification of significant biomarkers is accomplished by monovariate statistical tests where each biomarker is considered as independent from the others; and (2) multivariate methods, taking into consideration the correlations existing among the biomarkers themselves. This last approach is very powerful since it allows the identification of pools of biomarkers with diagnostic and prognostic performances which are superior to single markers in terms of sensitivity, specificity and robustness. Multivariate techniques are usually applied with variable selection procedures to provide a restricted set of biomarkers with the best predictive ability; however, standard selection methods are usually aimed at the identification of the smallest set of variables with the best predictive ability and exhaustivity is usually neglected. The exhaustive search for biomarkers is instead an important alternative to standard variable selection since it can provide information about the etiology of the pathology by producing a comprehensive set of markers. In this review, the most recent applications of the omics techniques (proteomics, genomics and metabolomics) to the identification of exploratory biomarkers for PC will be presented with particular regard to the statistical methods adopted for their identification. The basic theory related to classical and multivariate methods for identification of biomarkers is presented and then, the most recent applications in this field are discussed.

T-box transcription factors in cancer biology

The evolutionarily conserved T-box family of transcription factors have critical and well-established roles in embryonic development. More recently, T-box factors have also gained increasing prominence in the field of cancer biology where a wide range of cancers exhibit deregulated expression of T-box factors that possess tumour suppressor and/or tumour promoter functions. Of these the best characterised is TBX2, whose expression is upregulated in cancers including breast, pancreatic, ovarian, liver, endometrial adenocarcinoma, glioblastomas, gastric, uterine cervical and melanoma. Understanding the role and regulation of TBX2, as well as other T-box factors, in contributing directly to tumour progression, and especially in suppression of senescence and control of invasiveness suggests that targeting TBX2 expression or function alone or in combination with currently available chemotherapeutic agents may represent a therapeutic strategy for cancer.

Expression of novel tumor markers of pancreatic adenocarcinomas in intrahepatic cholangiocarcinomas

Intrahepatic cholangiocarcinomas (IHCCs) are morphologically and biologically similar to pancreatic ductal adenocarcinomas (PDACs), so newly identified PDAC-associated genes or proteins could provide clues for screening novel biomarkers for IHCC. In this study, the expression of three novel PDAC tumor markers (T-box transcription factor-4 [TBX4], heat shock protein-60 [HSP60], and Parkinson protein-7 [DJ-1]) identified in previous proteomic studies in IHCC tumors were immunohistochemically detected. The current study confirmed that three novel pancreatic cancer biomarkers TBX4, HSP60, and DJ-1 were also overexpressed in IHCC tumors, but with a relatively lower expression level than PDAC. No significant association was found between tumor marker expression and the clinicopathological characteristics of IHCC patients except that TBX4 expression correlated with tumor grades. Moreover, DJ-1 was demonstrated to be an independent prognostic factor for these patients. The current findings suggest that DJ-1 might play an important role in the malignant progression of IHCC, and its exact mechanism during IHCC progression deserves further investigation.