Bioinformatics for cancer management in the post-genome era

Comprehensive characterization of adipogenesis-related genes in colorectal cancer for clinical significance and immunogenomic landscape analyses

OBJECTIVE

Colorectal cancer (CRC) is a major global health concern, necessitating the identification of biomarkers and molecular subtypes for improved clinical management. This study aims to evaluate the clinical value of adipogenesis-related genes and molecular subtypes in CRC.

METHODS

A comprehensive analysis of adipogenesis-related genes in CRC was performed using publicly available datasets (TCGA and GEO database) and bioinformatics tools. Unsupervised cluster analysis was employed to identify the molecular subtypes of CRC, while LASSO regression analysis was utilized to develop a risk prognostic model. The immunogenomic patterns and immunotherapy analysis were used to predict patient response to immunotherapy. Furthermore, qPCR analysis was conducted to confirm the expression of the identified key genes in vitro.

RESULTS

Through the analysis of RNAseq data from normal and tumor tissues, we identified 50 differentially expressed genes. Unsupervised cluster analysis identified two subtypes (Cluster A and Cluster B) with significantly different survival outcomes. Cluster A and B displayed differential immune cell compositions and enrichment in specific biological pathways, providing insights into potential therapeutic targets. A risk-scoring model was developed using five ARGs, which successfully classified patients into high and low-risk groups, showing distinct survival outcomes. The model was validated and showed robust predictive performance. High-risk patients exhibited altered immune cell proportions and gene expression patterns compared to low-risk patients. In qPCR validation, four out of the five key genes were consistent with the results of bioinformatics analysis.

CONCLUSION

Overall, the findings of our investigation offer valuable understanding regarding the clinical relevance of ARGs and molecular subtypes in CRC, laying the groundwork for improved precision medicine applications and personalized treatment modalities.

TIGIT and PD-1 may serve as potential prognostic biomarkers for gastric cancer

Gastric Cancer (GC) is the fifth leading cause of cancer-related death in the world, and in urgent need of specific therapeutic targets to acquire prominent effectiveness. T-cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif (ITIM) domain (TIGIT) and programmed cell death protein 1 (PD-1) are identified to be abnormally overexpressed in various types of cancers including GC. This study aimed to investigate whether TIGIT and PD-1 could serve as potential prognostic biomarkers for GC. Firstly, TCGA GC dataset analysis and correlation analysis were utilized to inspect the relationship between expression of TIGIT, PD-1 and CD8 + T cells in GC and adjacent normal tissues. Then, flow cytometry was used to verify the data after collecting the peripheral blood, GC and adjacent normal tissues from 150 GC patients. Lastly, quantitative RT-PCR was performed to detect the expression of CD155, CD113, CD112 and TIGIT in six human GC cell lines and 631 GC patients in KM Plotter Database to conduct prognostic analysis. As results, we found that TIGIT and PD-1 were upregulated in GC tissues with high CD8 + T cells infiltration, while correlation analysis indicated they were in high-positive correlation. In addition, the flow cytometry analysis further showed that the high-expression of TIGIT in tumor microenvironment of GC could suppress the function of infiltrative CD8 + T cells, which leads to the escape of GC cells from immune killing. Furthermore, CD155 and CD112 were found abnormally upregulated in GC tissues and cell lines and the high expression of CD155, CD112 and TIGIT demonstrated poor prognosis results. In conclusion, these results provided potential therapeutic targets and prognostic biomarkers for treatment of GC in clinic.

Creating a common language: defining individualized, personalized and precision prevention in public health

Background

Because of the limited success of population-based prevention methods and due to developments in genomic screening, public health professionals and health policy makers are increasingly interested in more individualized prevention strategies. However, the terminology applied in this field is still ambiguous and thus has the potential to create misunderstandings.

Methods

A narrative literature review was conducted to identify how individualized, personalized and precision prevention are used in research papers and documents. Based on the findings a set of definitions were created that distinguish between these activities in a meaningful way.

Results

Definitions were found only for precision prevention, not for individualized or personalized prevention. The definitions of individualized, personalized and precision medicine were therefore used to create the definitions for their prevention counterparts. By these definitions, individualized prevention consists of all types of prevention that are individual-based; personalized prevention also consists of at least one form of -omic screening; and precision prevention further includes psychological, behavioral and socioeconomic data for each patient.

Conclusions

By defining these three key terms for different types of individual-based prevention both researchers and health policy makers can differentiate and use them in their proper context.

Application of genome editing technologies in gastrointestinal cancers

Genome editing is a site-directed modification technology for gene targeting and a powerful tool to edit the target DNA by site-specific DNA knockout or knockin. Genome editing has achieved a considerable success from lower microbes to human in the past years and may play a very important role in tumor staging, precision medicine as well as prognosis evaluation in gastrointestinal cancers. This review discusses the mechanisms of different genome-editing strategies and describes each of the common nuclease-based platforms, including transcription activator-like effector nucleases, zinc finger nucleases and the CRISPR/Cas9 system. We also summarize the progress made in applying genome editing to the research of gastrointestinal cancers.

Classical MALDI-MS versus CE-based ESI-MS proteomic profiling in urine for clinical applications

Human urine is an attractive and informative biofluid for medical diagnosis, which has been shown to reflect the (patho)-physiology of not only the urogenital system, but also others such as the cardiovascular system. For this reason, many studies have concentrated on the study of the urine proteome, aiming to find relevant biomarkers that could be applied in a clinical setting. However, this goal can only be achieved after reliable quantitative and qualitative analysis of the urinary proteome. In the last two decades, MS-based platforms have evolved to become indispensable tools for biomarker research. In this review, we will present and compare two of the most clinically relevant analytical platforms that have been used for the study of the urinary proteome, namely CE-based ESI-MS and classical MALDI-MS. These platforms, although not directly comparable, have been extensively used in proteomic profiling and therefore their comparison is fundamentally relevant to this field.

A practical data processing workflow for multi-OMICS projects

Multi-OMICS approaches aim on the integration of quantitative data obtained for different biological molecules in order to understand their interrelation and the functioning of larger systems. This paper deals with several data integration and data processing issues that frequently occur within this context. To this end, the data processing workflow within the PROFILE project is presented, a multi-OMICS project that aims on identification of novel biomarkers and the development of new therapeutic targets for seven important liver diseases. Furthermore, a software called CrossPlatformCommander is sketched, which facilitates several steps of the proposed workflow in a semi-automatic manner. Application of the software is presented for the detection of novel biomarkers, their ranking and annotation with existing knowledge using the example of corresponding Transcriptomics and Proteomics data sets obtained from patients suffering from hepatocellular carcinoma. Additionally, a linear regression analysis of Transcriptomics vs. Proteomics data is presented and its performance assessed. It was shown, that for capturing profound relations between Transcriptomics and Proteomics data, a simple linear regression analysis is not sufficient and implementation and evaluation of alternative statistical approaches are needed. Additionally, the integration of multivariate variable selection and classification approaches is intended for further development of the software. Although this paper focuses only on the combination of data obtained from quantitative Proteomics and Transcriptomics experiments, several approaches and data integration steps are also applicable for other OMICS technologies. Keeping specific restrictions in mind the suggested workflow (or at least parts of it) may be used as a template for similar projects that make use of different high throughput techniques. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Fibroblast growth factor receptor 2: expression, roles, and potential as a novel molecular target for colorectal cancer

The fibroblast growth factor receptor (FGFR) family consists of four members, named FGFR1, 2, 3, and 4. All 4 FGFRs and their ligands, fibroblast growth factors (FGFs), are expressed in colorectal cancer (CRC). Recent studies have shown that FGFR2 plays important roles in cancer progression; therefore, it is of great interest as a novel target for cancers. Expression of FGFR2 regulates migration, invasion, and growth in CRC. Expression of the FGFR2 isoform FGFR2 IIIb was associated with well-differentiated histological types, and its specific ligand, FGF7, enhanced angiogenesis and adhesion to type-IV collagen via FGFR2 IIIb in CRC. FGFR2 IIIc is detected in CRC, but its roles have not been well elucidated. Interactions between FGFR2 IIIb and IIIc and FGFs may play important roles in CRC via autocrine and/or paracrine signaling. Several kinds of molecular-targeting agents against FGFR2 have been developed; however, it is not clear how a cancer treatment can most effectively inhibit FGFR2 IIIb or FGFR2 IIIc, or both isoforms. The aim of this paper is to summarize the roles of FGFR2 and its isoforms in CRC and clarify whether they are potent therapeutic targets for CRC.

Receptor tyrosine kinases and targeted cancer therapeutics

The majority of growth factor receptors are composed of extracellular, transmembrane, and cytoplasmic tyrosine kinase (TK) domains. Receptor tyrosine kinase (RTK) activation regulates many key processes including cell growth and survival. However, dysregulation of RTK has been found in a wide range of cancers, and it has been shown to correlate with the development and progression of numerous cancers. Therefore, RTK has become an attractive therapeutic target. One way to effectively block signaling from RTK is inhibition of its catalytic activity with small-molecule inhibitors. Low-molecular-weight TK inhibitors (TKIs), such as imatinib, targeting tumors with mutant c-Kit, and gefitinib, targeting non-small cell lung cancer with mutant epidermal growth factor receptor (EGFR), have received marketing approval in Japan. MET, fibroblast growth factor receptor (FGFR), and insulin-like growth factor-I receptor (IGF-IR) are frequently genetically altered in advanced cancers. TKIs of these receptors have not yet appeared on the market, but many anticancer drug candidates are currently undergoing clinical trials. Most of these TKIs were designed to compete with ATP at the ATP-binding site within the TK domain. This review will focus on small-molecule TKIs targeting MET, FGFR, and IGF-IR and discuss the merits and demerits of two types of agents, i.e., those with only one or a few targets and those directed at multiple targets. Targeting agents specifically inhibiting the target kinase were previously searched for based on the hypothesis that a narrow target window might reduce unexpected side effects, but agents with multiple targets have been recently developed to overcome tumors resistant against a single-targeting agent.

An integrated study of aberrant gene copy number and gene expression in GIST and LMS

Increased chromosomal instability that alters the gene copy numbers throughout the genome is known to have a role in molecular pathogenesis of tumors. The impact of gene dosage effect to the expression levels of genes in GIST and LMS is unknown. In this paper, we used a combination of array comparative genomic hybridization (aCGH) and gene expression data to gain insights into the interplay of structural and functional changes of the genome in GIST and LMSs. We identified specific target genes that change their expression due to the gene dosage effect. Statistical analysis identified four chromosomal regions, 1p, 14q, 15q, and 22q, where both copy number and mRNA expression were significantly different between the tumor types. Multi-dimensional scaling (MDS) analysis showed that the gene expression profiles of these four regions accurately distinguish GIST and LMS. In addition, the gene dosage sensitive genes in these regions are differently involved in several tumor growth promoting pathways, implying that there are different mechanisms underlying the GIST and LMS carcinogenesis. Integration of aCGH and gene expression data has not only provided insights into how DNA copy number variations affect the gene expression patterns in these cancers, but also proves to be a promising method to choose biologically relevant biomarkers.

APEX1 Gene Amplification and Its Protein Overexpression in Osteosarcoma: Correlation with Recurrence, Metastasis, and Survival

The expression of apurinic/apyrimidinic exonuclease 1 (APEX1) in tumors has been linked with chemoresistance, radioresistance, and shorter patient survival times. We sought to gain insight into the role of APEX1 in human osteosarcoma by evaluation of gene copy number alterations and its protein expression in osteosarcoma patients treated at the Sarcoma Center of Tianjin Cancer Hospital (Tianjin, China). To evaluate the gene copy number alterations of APEX1, we acquired 10 fresh tissue samples from 9 patients and performed whole-genome array-based comparative genomic hybridization (aCGH). We next acquired formalin-fixed and paraffin embedded tissues from 57 well-annotated osteosarcoma cases and performed immunohistochemical analyses for APEX1. APEX1 gene amplification was observed in 50% (5/10) of the osteosarcoma samples. The overexpression of APEX1 protein was detected in 64.9% (37/57) of the osteosarcomas ranging from negative (35.1%, 20/57), weakly positive (35.1%, 20/57), moderate (14%, 8/57) and strongly positive (15.8%, 9/57). The APEX1 expression had significant correlation with osteosarcoma local recurrence and/or metastasis. Moreover, multivariate analysis showed that APEX1 expression was an independent molecular predictor for disease-free survival of patients with osteosarcomas. Our study for the first time showed that APEX1 gene was amplified in osteosarcomas and that APEX1 expression was an independent predictor of the osteosarcoma local recurrence and/or metastasis. Thus, APEX1 may serve as a prognostic marker and potential therapeutic target for osteosarcoma.

Toxicity testing in the 21st century: a vision and a strategy

With the release of the landmark report Toxicity Testing in the 21st Century: A Vision and a Strategy, the U.S. National Academy of Sciences, in 2007, precipitated a major change in the way toxicity testing is conducted. It envisions increased efficiency in toxicity testing and decreased animal usage by transitioning from current expensive and lengthy in vivo testing with qualitative endpoints to in vitro toxicity pathway assays on human cells or cell lines using robotic high-throughput screening with mechanistic quantitative parameters. Risk assessment in the exposed human population would focus on avoiding significant perturbations in these toxicity pathways. Computational systems biology models would be implemented to determine the dose-response models of perturbations of pathway function. Extrapolation of in vitro results to in vivo human blood and tissue concentrations would be based on pharmacokinetic models for the given exposure condition. This practice would enhance human relevance of test results, and would cover several test agents, compared to traditional toxicological testing strategies. As all the tools that are necessary to implement the vision are currently available or in an advanced stage of development, the key prerequisites to achieving this paradigm shift are a commitment to change in the scientific community, which could be facilitated by a broad discussion of the vision, and obtaining necessary resources to enhance current knowledge of pathway perturbations and pathway assays in humans and to implement computational systems biology models. Implementation of these strategies would result in a new toxicity testing paradigm firmly based on human biology.

Initial study of microRNA expression profiles of colonic cancer without lymph node metastasis

OBJECTIVE

To investigate the difference of microRNA expression profiles between colonic cancer without lymph node metastasis and the para-cancerous control, to identify the specific microRNA associated with the cancer and to predict the carcinogenetic mechanism of microRNA on the basis of these results.

METHODS

The microRNA (miRNA) were extracted and isolated from six specimens, including colonic cancerous and para-cancerous ones, all of which were confirmed to be without lymph node metastasis. Agilent microRNA microarrays consisting of 723 probes were used for screening the expression differences of microRNA. Data were analyzed using feature extraction software. The expression level of differentially expressed microRNA using quantitative real-time polymerase chain reaction (RT-PCR) was validated.

RESULTS

A total of 14 miRNAs were found to be associated with colonic cancer, in which the expression of miR-106b, miR-135b, miR-18a, miR-18b, miR-196b, miR-19a, miR-224, miR-335, miR-424, miR-20a*, miR-301b and miR-374a were up-regulated and the expression of miR-378 and miR-378* were downregulated in colonic cancer tissues, compared with the para-cancerous control. The expression level of miR-18a and miR-135b were validated in accordance with the results of RT-PCR.

CONCLUSION

The miRNAs are differentially expressed between colonic tumor tissues and para-cancerous tissues. Many of these miRNAs are expected to participate in the process of multiple tumorigenesis. These miRNAs could play an important role in the carcinogenesis of colon. These results provide new insights in human colorectal cancer genesis.

Networking of WNT, FGF, Notch, BMP, and Hedgehog signaling pathways during carcinogenesis

The biological functions of some orthologs within the human genome and model-animal genomes are evolutionarily conserved, but those of others are divergent due to protein evolution and promoter evolution. Because WNT signaling molecules play key roles during embryogenesis, tissue regeneration and carcinogenesis, the author's group has carried out a human WNT-ome project for the comprehensive characterization of human genes encoding WNT signaling molecules. From 1996 to 2002, we cloned and characterized WNT2B/WNT13, WNT3, WNT3A, WNT5B, WNT6, WNT7B, WNT8A, WNT8B, WNT9A/WNT14, WNT9B/WNT14B, WNT10A, WNT10B, WNT11, FZD1, FZD2, FZD3, FZD4, FZD5, FZD6, FZD7, FZD8, FZD10, FRAT1, FRAT2, NKD1, NKD2, VANGL1, RHOU/ARHU, RHOV/ARHV, GIPC2, GIPC3, FBXW11/betaTRCP2, SOX17, TCF7L1/TCF3, and established a cDNA-PCR system for snap-shot and dynamic analyses on the WNT-transcriptome. In 2003, we identified and characterized PRICKLE1, PRICKLE2, DACT1/DAPPER1, DACT2/DAPPER2, DAAM2, and BCL9L. After completion of the human WNT-ome project, we have been working on the stem cell signaling network. WNT signals are transduced to beta-catenin, NLK, NFAT, PKC, JNK and RhoA signaling cascades. FGF20, JAG1 and DKK1 are target genes of the WNT-beta-catenin signaling cascade. Cross-talk of WNT and FGF signaling pathways potentiates beta-catenin and NFAT signaling cascades. BMP signals induce IHH upregulation in co-operation with RUNX. Hedgehog signals induce upregulation of SFRP1, JAG2 and FOXL1, and then FOXL1 induces BMP4 upregulation. The balance between WNT-FGF-Notch and BMP-Hedgehog signaling networks is important for the maintenance of homoestasis among stem and progenitor cells. Disruption of the stem cell signaling network results in pathological conditions, such as congenital diseases and cancer.

BioShuttle-mediated plasmid transfer

An efficient gene transfer into target tissues and cells is needed for safe and effective treatment of genetic diseases like cancer. In this paper, we describe the development of a transport system and show its ability for transporting plasmids. This non-viral peptide-based BioShuttle-mediated transfer system consists of a nuclear localization address sequence realizing the delivery of the plasmid phNIS-IRES-EGFP coding for two independent reporter genes into nuclei of HeLa cells. The quantification of the transfer efficiency was achieved by measurements of the sodium iodide symporter activity. EGFP gene expression was measured with Confocal Laser Scanning Microscopy and quantified with biostatistical methods by analysis of the frequency of the amplitude distribution in the CLSM images. The results demonstrate that the "BioShuttle"-Technology is an appropriate tool for an effective transfer of genetic material carried by a plasmid.

WNT signaling pathway and stem cell signaling network

WNT signals are transduced to the canonical pathway for cell fate determination, and to the noncanonical pathway for control of cell movement and tissue polarity. Canonical WNT signals are transduced through Frizzled family receptors and LRP5/LRP6 coreceptor to the beta-catenin signaling cascade. Microtubule affinity-regulating kinase (PAR-1) family kinases, casein kinase I epsilon (CKI epsilon), and FRAT are positive regulators of the canonical WNT pathway, whereas APC, AXIN1, AXIN2, CKI alpha, NKD1, NKD2, beta TRCP1, beta TRCP2, ANKRD6, Nemo-like kinase (NLK), and peroxisome proliferator-activated receptor gamma (PPAR gamma) are negative regulators. Nuclear complex, consisting of T-cell factor/lymphoid enhancer factor, beta-catenin, BCL9/BCL9L, and PYGO, activates transcription of canonical WNT target genes such as FGF20, DKK1, WISP1, MYC, CCND1, and Glucagon (GCG). Noncanonical WNT signals are transduced through Frizzled family receptors and ROR2/RYK coreceptors to the Dishevelled-dependent (Rho family GTPases and c-jun NH(2)-terminal kinase) or the Ca(2+)-dependent (NLK and nuclear factor of activated T cells) signaling cascades. WNT signals are context-dependently transduced to both pathways based on the expression profile of WNT, SFRP, WIF, DKK, Frizzled receptors, coreceptors, and the activity of intracellular WNT signaling regulators. Epigenetic silencing and loss-of-function mutation of negative regulators of the canonical WNT pathway occur in a variety of human cancer. WNT, fibroblast growth factor (FGF), Notch, Hedgehog, and transforming growth factor beta/bone morphogenetic protein signaling network are implicated in the maintenance of tissue homeostasis by regulating self-renewal of normal stem cells as well as proliferation or differentiation of progenitor (transit-amplifying) cells. Breakage of the stem cell signaling network leads to carcinogenesis. Nonsteroidal anti-inflammatory drugs and PPAR gamma agonists with the potential to inhibit the canonical WNT signaling pathway are candidate agents for chemoprevention. ZTM000990 and PKF118-310 are lead compounds targeted to the canonical WNT signaling cascade. Anti-WNT1 and anti-WNT2 monoclonal antibodies show in vitro effects in cancer treatment. After the optimization, derivatives of small-molecule compound and human monoclonal antibody targeted to the WNT signaling pathway could be used in cancer medicine.

Proteomic approach to studying the cytotoxicity of YC-1 on U937 leukemia cells and antileukemia activity in orthotopic model of leukemia mice

To evaluate the effects of YC-1 on leukemia cell lines, PI incorporation was used to determine cell viability. YC-1 induced a dose- and time-dependent decrease in viability and apoptosis in YC-1-treated U937 cells. YC-1-induced apoptosis is a cyclic guanosine monophosphate (cGMP)-independent pathway. Proteomic analysis showed that the altered proteins include the significant regulation of HSP70, chaperonin, ATP synthase beta chains, and Chain F. Western blotting and immuno-cytochemistry stain showed that YC-1 treatment caused a time-dependent increase in cytosolic Cytochrome c, pro-caspase-9, Apaf-1, and the activation of caspase-9 and -3. Importantly, the in vivo antileukemia effects of YC-1 were evaluated in BALB/c mice inoculated with WEHI-3B orthotopic model. YC-1 enhanced survival rate and prevented the body weight loss in leukemia mice. The enlargement of spleen and lymph nodes were reduced in YC-1 treated than that in leukemia mice. H-E stain of spleen sections revealed that infiltration of immature myeloblastic cells into red pulp was reduced in YC-1-treated group. The apoptotic cells of splenocyte were significantly increased in YC-1 treated than that in leukemia mice by Tdt-mediated deoxyuridine triphosphate nick end labeling (TUNEL) assay. Taken together, we conclude that YC-1 acted against U937 cells in vitro via a mitochondrial-dependent apoptosis pathway, and in orthotopic leukemia model, YC-1 administered antileukemia activity.

Cancer immunomics and application of 'omics' for cancer management

Several 'omics' sciences have been launched. The outstanding diversity of immune system components, together with the complexity of the regulatory pathways and network-type interactions, makes immunology a combinatorial science. Cancer immonomics is a branch of immunomics. The present cancer immunomics project aims at diagnostics and therapy. Comparative and structural genomics can be applied for understanding the underlying tumorogenesis process. For diagnostic purposes, in order to develop a new marker, gene expression analysis technologies, such as DNA microarray, differential display, cDNA subtraction, serial analysis of gene expression and serological proteome analysis, which enable investigators to obtain comprehensive data with respect to gene expression profiles, are progressing rapidly. For therapeutic purposes, vaccine candidate finding, gene therapy and drug-tumor interaction modeling can be clarified by the advance immunomics techniques. In this article, the author will present the basic concepts on cancer immunomics and application for basic study of the pathogenesis, diagnosis and treatment of cancer.

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.