The cancer genome anatomy project: online resources to reveal the molecular signatures of cancer

A systematic review of computational approaches to understand cancer biology for informed drug repurposing

Cancer is the second leading cause of death globally, trailing only heart disease. In the United States alone, 1.9 million new cancer cases and 609,360 deaths were recorded for 2022. Unfortunately, the success rate for new cancer drug development remains less than 10%, making the disease particularly challenging. This low success rate is largely attributed to the complex and poorly understood nature of cancer etiology. Therefore, it is critical to find alternative approaches to understanding cancer biology and developing effective treatments. One such approach is drug repurposing, which offers a shorter drug development timeline and lower costs while increasing the likelihood of success. In this review, we provide a comprehensive analysis of computational approaches for understanding cancer biology, including systems biology, multi-omics, and pathway analysis. Additionally, we examine the use of these methods for drug repurposing in cancer, including the databases and tools that are used for cancer research. Finally, we present case studies of drug repurposing, discussing their limitations and offering recommendations for future research in this area.

Multi-perspective quality control of Illumina RNA sequencing data analysis

Quality control (QC) is a critical step in RNA sequencing (RNA-seq). Yet, it is often ignored or conducted on a limited basis. Here, we present a multi-perspective strategy for QC of RNA-seq experiments. The QC of RNA-seq can be divided into four related stages: (1) RNA quality, (2) raw read data (FASTQ), (3) alignment and (4) gene expression. We illustrate the importance of conducting QC at each stage of an RNA-seq experiment and demonstrate our recommended RNA-seq QC strategy. Furthermore, we discuss the major and often neglected quality issues associated with the three major types of RNA-seq: mRNA, total RNA and small RNA. This RNA-seq QC overview provides comprehensive guidance for researchers who conduct RNA-seq experiments.

Public Databases and Software for the Pathway Analysis of Cancer Genomes

The study of pathway disruption is key to understanding cancer biology. Advances in high throughput technologies have led to the rapid accumulation of genomic data. The explosion in available data has generated opportunities for investigation of concerted changes that disrupt biological functions, this in turns created a need for computational tools for pathway analysis. In this review, we discuss approaches to the analysis of genomic data and describe the publicly available resources for studying biological pathways.

Chromosome-centric Human Proteome Project (C-HPP): Chromosome 12

Following an official announcement of the Chromosome-centric Human Proteome Project (C-HPP), the Chromosome 12 (Ch12) Consortium has been established by five representative teams from five Asian countries including Thailand (Siriraj Hospital, Mahidol University), Singapore (National University of Singapore), Taiwan (Academia Sinica), Hong Kong (The Chinese University of Hong Kong), and India (Institute of Bioinformatics). We have worked closely together to extensively and systematically analyze all missing and known proteins encoded by Ch12 for their tissue/cellular/subcellular localizations. The target organs/tissues/cells include kidney, brain, gastrointestinal tissues, blood/immune cells, and stem cells. In the later phase, post-translational modifications and functional significance of Ch12-encoded proteins as well as their associations with human diseases (i.e., immune diseases, metabolic disorders, and cancers) will be defined. We have collaborated with other chromosome teams, Human Kidney and Urine Proteome Project (HKUPP), AOHUPO Membrane Proteomics Initiative, and other existing HUPO initiatives in the Biology/Disease-Based Human Proteome Project (B/D-HPP) to delineate functional roles and medical implications of Ch12-encoded proteins. The data set to be obtained from this multicountry consortium will be an important piece of the jigsaw puzzle to fulfill the missions and goals of the C-HPP and the global Human Proteome Project (HPP).

Vitamin D and the RNA transcriptome: more than mRNA regulation

The GRCh37.p13 primary assembly of the human genome contains 20805 protein coding mRNA, and 37147 non-protein coding genes and pseudogenes that as a result of RNA processing and editing generate 196501 gene transcripts. Given the size and diversity of the human transcriptome, it is timely to revisit what is known of VDR function in the regulation and targeting of transcription. Early transcriptomic studies using microarray approaches focused on the protein coding mRNA that were regulated by the VDR, usually following treatment with ligand. These studies quickly established the approximate size, and surprising diversity of the VDR transcriptome, revealing it to be highly heterogenous and cell type and time dependent. With the discovery of microRNA, investigators also considered VDR regulation of these non-protein coding RNA. Again, cell and time dependency has emerged. Attempts to integrate mRNA and miRNA regulation patterns are beginning to reveal patterns of co-regulation and interaction that allow for greater control of mRNA expression, and the capacity to govern more complex cellular events. As the awareness of the diversity of non-coding RNA increases, it is increasingly likely it will be revealed that VDR actions are mediated through these molecules also. Key knowledge gaps remain over the VDR transcriptome. The causes for the cell and type dependent transcriptional heterogenetiy remain enigmatic. ChIP-Seq approaches have confirmed that VDR binding choices differ very significantly by cell type, but as yet the underlying causes distilling VDR binding choices are unclear. Similarly, it is clear that many of the VDR binding sites are non-canonical in nature but again the mechanisms underlying these interactions are unclear. Finally, although alternative splicing is clearly a very significant process in cellular transcriptional control, the lack of RNA-Seq data centered on VDR function are currently limiting the global assessment of the VDR transcriptome. VDR focused research that complements publically available data (e.g., ENCODE Birney et al., 2007; Birney, 2012), TCGA (Strausberg et al., 2002), GTEx (Consortium, 2013) will enable these questions to be addressed through large-scale data integration efforts.

A high level of liver-specific expression of oncogenic Kras(V12) drives robust liver tumorigenesis in transgenic zebrafish

Human liver cancer is one of the deadliest cancers worldwide, with hepatocellular carcinoma (HCC) being the most common type. Aberrant Ras signaling has been implicated in the development and progression of human HCC, but a complete understanding of the molecular mechanisms of this protein in hepatocarcinogenesis remains elusive. In this study, a stable in vivo liver cancer model using transgenic zebrafish was generated to elucidate Ras-driven tumorigenesis in HCC. Using the liver-specific fabp10 (fatty acid binding protein 10) promoter, we overexpressed oncogenic kras^V12 specifically in the transgenic zebrafish liver. Only a high level of kras^V12 expression initiated liver tumorigenesis, which progressed from hyperplasia to benign and malignant tumors with activation of the Ras-Raf-MEK-ERK and Wnt–β-catenin pathways. Histological diagnosis of zebrafish tumors identified HCC as the main lesion. The tumors were invasive and transplantable, indicating malignancy of these HCC cells. Oncogenic kras^V12 was also found to trigger p53-dependent senescence as a tumor suppressive barrier in the pre-neoplastic stage. Microarray analysis of zebrafish liver hyperplasia and HCC uncovered the deregulation of several stage-specific and common biological processes and signaling pathways responsible for kras^V12-driven liver tumorigenesis that recapitulated the molecular hallmarks of human liver cancer. Cross-species comparisons of cancer transcriptomes further defined a HCC-specific gene signature as well as a liver cancer progression gene signature that are evolutionarily conserved between human and zebrafish. Collectively, our study presents a comprehensive portrait of molecular mechanisms during progressive Ras-induced HCC. These observations indicate the validity of our transgenic zebrafish to model human liver cancer, and this model might act as a useful platform for drug screening and identifying new therapeutic targets.

Detecting cancer gene networks characterized by recurrent genomic alterations in a population

High resolution, system-wide characterizations have demonstrated the capacity to identify genomic regions that undergo genomic aberrations. Such research efforts often aim at associating these regions with disease etiology and outcome. Identifying the corresponding biologic processes that are responsible for disease and its outcome remains challenging. Using novel analytic methods that utilize the structure of biologic networks, we are able to identify the specific networks that are highly significantly, nonrandomly altered by regions of copy number amplification observed in a systems-wide analysis. We demonstrate this method in breast cancer, where the state of a subset of the pathways identified through these regions is shown to be highly associated with disease survival and recurrence.

Database resources for proteomics-based analysis of cancer

Biological/bioinformatics databases are essential for medical and biological studies. They integrate and organize biologically related information in a structured format and provide researchers with easy access to a variety of relevant data. This review presents an overview of publicly available databases relevant to proteomics studies in cancer research. They include gene/protein expression databases, gene mutation and single nucleotide polymorphisms databases, tumor antigen databases, protein-protein interaction, and biological pathway databases. Automated information retrieval from these databases enables efficient large-scale proteomics data analysis.

Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective

Cell lineage commitment and differentiation are governed by a complex gene regulatory network. Disruption of these processes by inappropriate regulatory signals and by mutational rewiring of the network can lead to tumorigenesis. Cancer cells often exhibit immature or embryonic traits and dysregulated developmental genes can act as oncogenes. However, the prevailing paradigm of somatic evolution and multi-step tumorigenesis, while useful in many instances, offers no logically coherent reason for why oncogenesis recapitulates ontogenesis. The formal concept of "cancer attractors", derived from an integrative, complex systems approach to gene regulatory network may provide a natural explanation. Here we present the theory of attractors in gene network dynamics and review the concept of cell types as attractors. We argue that cancer cells are trapped in abnormal attractors and discuss this concept in the light of recent ideas in cancer biology, including cancer genomics and cancer stem cells, as well as the implications for differentiation therapy.

On the cytotoxicity of HCR-NTPase in the neuroblastoma cell line SH-SY5Y

Background

The human cancer-related nucleoside triphosphatase (HCR-NTPase) is overexpressed in several tumour tissues including neuroblastoma. HCR-NTPase is an enzyme exhibiting a slow in vitro activity in hydrolysing nucleosidetriphosphates. However, its in vivo function is still unknown. To learn more about the physiological role of HCR-NTPase, we both overexpressed and silenced it in the neuroblastoma cell line SH-SY5Y.

Findings

No effect was observed when the expression of endogenously expressed HCR-NTPase in the cells was silenced by RNA interference. On the other hand, overexpression of HCR-NTPase led to cytotoxicity of the protein in SH-SY5Y cells. Even if the catalytic essential amino acid glutamate 114 was replaced by alanine (E114A-HCR-NTPase), the protein remained cytotoxic. The results could be confirmed by successfully rescuing the cells via RNA interference.

Conclusion

Although expressed in several tumours, at least in SH-SY5Y, HCR-NTPase is not essential for the cells to survive. Increased levels of the protein lead to cytotoxicity due to physical intracellular interactions rather than hydrolysis of nucleosidetriphosphates by its intrinsic residual enzymatic activity.

Nicotinic acid, nicotinamide, and nicotinamide riboside: a molecular evaluation of NAD+ precursor vitamins in human nutrition

Although baseline requirements for nicotinamide adenine dinucleotide (NAD+) synthesis can be met either with dietary tryptophan or with less than 20 mg of daily niacin, which consists of nicotinic acid and/or nicotinamide, there is growing evidence that substantially greater rates of NAD+ synthesis may be beneficial to protect against neurological degeneration, Candida glabrata infection, and possibly to enhance reverse cholesterol transport. The distinct and tissue-specific biosynthetic and/or ligand activities of tryptophan, nicotinic acid, nicotinamide, and the newly identified NAD+ precursor, nicotinamide riboside, reviewed herein, are responsible for vitamin-specific effects and side effects. Because current data suggest that nicotinamide riboside may be the only vitamin precursor that supports neuronal NAD+ synthesis, we present prospects for human nicotinamide riboside supplementation and propose areas for future research.

A BAC clone fingerprinting approach to the detection of human genome rearrangements

Fingerprint Profiling (FPP) is a new method which uses restriction digest fingerprints of bacterial artificial chromosome (BAC) clones for detecting and classifying rearrangements in the human genome.

We present a method, called fingerprint profiling (FPP), that uses restriction digest fingerprints of bacterial artificial chromosome clones to detect and classify rearrangements in the human genome. The approach uses alignment of experimental fingerprint patterns to in silico digests of the sequence assembly and is capable of detecting micro-deletions (1-5 kb) and balanced rearrangements. Our method has compelling potential for use as a whole-genome method for the identification and characterization of human genome rearrangements.

NMR structure and functional characterization of a human cancer-related nucleoside triphosphatase

A screen of the human cancer genome anatomy project (CGAP) database was performed to search for new proteins involved in tumorigenesis. The resulting hits were further screened for recombinant expression, solubility and protein aggregation, which led to the identification of the previously unknown human cancer-related (HCR) protein encoded by the mRNA NM_032324 as a target for structure determination by NMR. The three-dimensional structure of the protein in its complex with ATPgammaS forms a three-layered alpha/beta sandwich, with a central nine-stranded beta-sheet surrounded by five alpha-helices. Sequence and three-dimensional structure comparisons with AAA+ ATPases revealed the presence of Walker A (GPPGVGKT) and Walker B (VCVIDEIG) motifs. Using 1D (31)P-NMR spectroscopy and a coupled enzymatic assay for the determination of inorganic phosphate, we showed that the purified recombinant protein is active as a non-specific nucleoside triphosphatase, with k(cat)=7.6x10(-3) s(-1). The structural basis for the enzymatic activity of HCR-NTPase was further characterized by site-directed mutagenesis of the Walker B motif, which further contributes to making the HCR-NTPase an attractive new target for further biochemical characterization in the context of its presumed role in human tumorigenesis.

Meta-analysis and meta-review of thyroid cancer gene expression profiling studies identifies important diagnostic biomarkers

PURPOSE

An estimated 4% to 7% of the population will develop a clinically significant thyroid nodule during their lifetime. In many cases, preoperative diagnoses by needle biopsy are inconclusive. Thus, there is a clear need for improved diagnostic tests to distinguish malignant from benign thyroid tumors. The recent development of high-throughput molecular analytic techniques should allow the rapid evaluation of new diagnostic markers. However, researchers are faced with an overwhelming number of potential markers from numerous thyroid cancer expression profiling studies.

MATERIALS AND METHODS

To address this challenge, we have carried out a comprehensive meta-review of thyroid cancer biomarkers from 21 published studies. A gene ranking system that considers the number of comparisons in agreement, total number of samples, average fold-change and direction of change was devised.

RESULTS

We have observed that genes are consistently reported by multiple studies at a highly significant rate (P < .05). Comparison with a meta-analysis of studies reprocessed from raw data showed strong concordance with our method.

CONCLUSION

Our approach represents a useful method for identifying consistent gene expression markers when raw data are unavailable. A review of the top 12 candidates revealed well known thyroid cancer markers such as MET, TFF3, SERPINA1, TIMP1, FN1, and TPO as well as relatively novel or uncharacterized genes such as TGFA, QPCT, CRABP1, FCGBP, EPS8 and PROS1. These candidates should help to develop a panel of markers with sufficient sensitivity and specificity for the diagnosis of thyroid tumors in a clinical setting.

An atlas of human gene expression from massively parallel signature sequencing (MPSS)

We have used massively parallel signature sequencing (MPSS) to sample the transcriptomes of 32 normal human tissues to an unprecedented depth, thus documenting the patterns of expression of almost 20,000 genes with high sensitivity and specificity. The data confirm the widely held belief that differences in gene expression between cell and tissue types are largely determined by transcripts derived from a limited number of tissue-specific genes, rather than by combinations of more promiscuously expressed genes. Expression of a little more than half of all known human genes seems to account for both the common requirements and the specific functions of the tissues sampled. A classification of tissues based on patterns of gene expression largely reproduces classifications based on anatomical and biochemical properties. The unbiased sampling of the human transcriptome achieved by MPSS supports the idea that most human genes have been mapped, if not functionally characterized. This data set should prove useful for the identification of tissue-specific genes, for the study of global changes induced by pathological conditions, and for the definition of a minimal set of genes necessary for basic cell maintenance. The data are available on the Web at http://mpss.licr.org and http://sgb.lynxgen.com.

XenDB: full length cDNA prediction and cross species mapping in Xenopus laevis

Background

Research using the model system Xenopus laevis has provided critical insights into the mechanisms of early vertebrate development and cell biology. Large scale sequencing efforts have provided an increasingly important resource for researchers. To provide full advantage of the available sequence, we have analyzed 350,468 Xenopus laevis Expressed Sequence Tags (ESTs) both to identify full length protein encoding sequences and to develop a unique database system to support comparative approaches between X. laevis and other model systems.

Description

Using a suffix array based clustering approach, we have identified 25,971 clusters and 40,877 singleton sequences. Generation of a consensus sequence for each cluster resulted in 31,353 tentative contig and 4,801 singleton sequences. Using both BLASTX and FASTY comparison to five model organisms and the NR protein database, more than 15,000 sequences are predicted to encode full length proteins and these have been matched to publicly available IMAGE clones when available. Each sequence has been compared to the KOG database and ~67% of the sequences have been assigned a putative functional category. Based on sequence homology to mouse and human, putative GO annotations have been determined.

Conclusion

The results of the analysis have been stored in a publicly available database XenDB . A unique capability of the database is the ability to batch upload cross species queries to identify potential Xenopus homologues and their associated full length clones. Examples are provided including mapping of microarray results and application of 'in silico' analysis. The ability to quickly translate the results of various species into 'Xenopus-centric' information should greatly enhance comparative embryological approaches.

Supplementary material can be found at .

Bioinformatics in Otolaryngology

This article reviews the recent literature on microarray analysis, bioinformatics techniques, and genomics in relation to the study of carcinogenesis of head and neck cancers.

The status, quality, and expansion of the NIH full-length cDNA project: the Mammalian Gene Collection (MGC)

The National Institutes of Health's Mammalian Gene Collection (MGC) project was designed to generate and sequence a publicly accessible cDNA resource containing a complete open reading frame (ORF) for every human and mouse gene. The project initially used a random strategy to select clones from a large number of cDNA libraries from diverse tissues. Candidate clones were chosen based on 5'-EST sequences, and then fully sequenced to high accuracy and analyzed by algorithms developed for this project. Currently, more than 11,000 human and 10,000 mouse genes are represented in MGC by at least one clone with a full ORF. The random selection approach is now reaching a saturation point, and a transition to protocols targeted at the missing transcripts is now required to complete the mouse and human collections. Comparison of the sequence of the MGC clones to reference genome sequences reveals that most cDNA clones are of very high sequence quality, although it is likely that some cDNAs may carry missense variants as a consequence of experimental artifact, such as PCR, cloning, or reverse transcriptase errors. Recently, a rat cDNA component was added to the project, and ongoing frog (Xenopus) and zebrafish (Danio) cDNA projects were expanded to take advantage of the high-throughput MGC pipeline.

A set of BAC clones spanning the human genome

Using the human bacterial artificial chromosome (BAC) fingerprint-based physical map, genome sequence assembly and BAC end sequences, we have generated a fingerprint-validated set of 32 855 BAC clones spanning the human genome. The clone set provides coverage for at least 98% of the human fingerprint map, 99% of the current assembled sequence and has an effective resolving power of 79 kb. We have made the clone set publicly available, anticipating that it will generally facilitate FISH or array-CGH-based identification and characterization of chromosomal alterations relevant to disease.

Sequence-based cancer genomics: progress, lessons and opportunities

Technologies that provide a genome-wide view offer an unprecedented opportunity to scrutinize the molecular biology of the cancer cell. The information that is derived from these technologies is well suited to the development of public databases of alterations in the cancer genome and its expression. Here, we describe the synergistic efforts of research programmes in Brazil, the United Kingdom and the United States towards building integrated databases that are widely accessible to the research community, to enable basic and applied applications in cancer research.

Comprehensive sampling of gene expression in human cell lines with massively parallel signature sequencing

Whereas information is rapidly accumulating about the structure and position of genes encoded in the human genome, less is known about the complexity and relative abundance of their expression in individual human cells and tissues. Here, we describe the characteristics of the transcriptomes of two cultured cell lines, HB4a (normal breast epithelium) and HCT-116 (colon adenocarcinoma), using massively parallel signature sequencing (MPSS). We generated in excess of 10(7) short signature sequences per cell line, thus providing a comprehensive snapshot of gene expression, within the technical limitations of the method. The number of genes expressed at one copy per cell or more in either of the lines was estimated to be between 10,000 and 15,000. The vast majority of the transcripts found in these cells can be mapped to known genes and their polyadenylation variants. Among the genes that could be identified from their signature sequences, approximately 8,500 were expressed by both cell lines, whereas 6,000 showed cellular specificity. Taking into account sequence tags that map uniquely to the genome but not to known transcripts, overall the data are consistent with an upper limit of 17,000 for the total number of genes expressed at more than one copy per cell in one or both of the two cell lines examined.