Qualitative and Quantitative Expression Status of the Human Chromosome 20 Genes in Cancer Tissues and the Representative Cell Lines

Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.

PDRG1 predicts a poor prognosis and facilitates the proliferation and metastasis of colorectal cancer

OBJECTIVE

The incidence and mortality of colorectal cancer (CRC) is increasing yearly and CRC patients are becoming younger in global. Evidences have revealed the carcinogenic effect of p53 and DNA damage-regulated gene 1 (PDRG1) in several types of tumors. However, its biological function is yet to be investigated in CRC. This study aimed to unveil the prooncogenic role of PDRG1 in CRC.

METHODS

We detected the expression and clinical pathological features of PDRG1 in CRC tissues and paired non-tumor adjacent tissues. The biological role and molecular mechanism of PDRG1 in CRC were characterized through a range of in vitro and in vivo experiments and datasets analysis.

RESULT

We identified the significant up-regulated expression of PDRG1 both in CRC tissues and cell, and higher expression of PDRG1 was associated with worse clinicopathological stage and poorer survival outcome. Cox regression analysis revealed that PDRG1 is an independent prognostic factor for CRC patients. Silencing of PDRG1 significantly retarded CRC cell vitality, invasion and migration, induced cell apoptosis and G0/G1 phase arrest. PDRG1 knockdown also attenuated tumor growth and metastasis as evidencing in vivo experiment. The expression of p21 and apoptosis related protein was enhanced with the knockdown of PDRG1 while cell cycle protein was inhibited.

CONCLUSION

PDRG1 function as a novel oncogene and participate in malignant progression of CRC by regulating p21-mediated signal pathway, suggesting that it can serve as a valuable predictive biomarker for diagnosing of CRC patient and a promising target for therapy.

Characterisation of the novel spontaneously immortalized and invasively growing human skin keratinocyte line HaSKpw

We here present the spontaneously immortalised cell line, HaSKpw, as a novel model for the multistep process of skin carcinogenesis. HaSKpw cells were established from the epidermis of normal human adult skin that, without crisis, are now growing unrestricted and feeder-independent. At passage 22, clonal populations were established and clone7 (HaSKpwC7) was further compared to the also spontaneously immortalized HaCaT cells. As important differences, the HaSKpw cells express wild-type p53, remain pseudodiploid, and show a unique chromosomal profile with numerous complex aberrations involving chromosome 20. In addition, HaSKpw cells overexpress a pattern of genes and miRNAs such as KRT34, LOX, S100A9, miR21, and miR155; all pointing to a tumorigenic status. In concordance, HaSKpw cells exhibit reduced desmosomal contacts that provide them with increased motility and a highly migratory/invasive phenotype as demonstrated in scratch- and Boyden chamber assays. In 3D organotypic cultures, both HaCaT and HaSKpw cells form disorganized epithelia but only the HaSKpw cells show tumorcell-like invasive growth. Together, HaSKpwC7 and HaCaT cells represent two spontaneous (non-genetically engineered) “premalignant” keratinocyte lines from adult human skin that display different stages of the multistep process of skin carcinogenesis and thus represent unique models for analysing skin cancer development and progression.

Assessing Transcription Regulatory Elements To Evaluate the Expression Status of Missing Protein Genes on Chromosomes 11 and 19

During an investigation of missing proteins with the RNA-seq data acquired from three liver cancer cell lines, the majority of the missing protein coding genes (MPGs) located at chromosome 11 (chr11) had no corresponding mRNAs, while a high percentage of the MPGs on chr19 were detected at the mRNA level. The phenomenon, which was also observed in more than 40 cell lines, led to an inquiry of causation of the different transcriptional statuses of the MPGs in the two chromosomes. We hypothesized that the special chromatin structure was a key element to regulate MPG transcription. Upon a systematical comparison of the effects of DNase I hypersensitive sites (DHSs), transcription factors (TFs), and histone modifications toward these genes or MPGs with/without mRNA evidence in chr11 and 19, we attributed the poor transcription of the MPGs to the weak capacity of these transcription regulatory elements, regardless of which chromosome the MPGs were located. We further analyzed the gene contents in chr11 and found a number of genes related to sensory functions in the presence of chr11. We postulate that a high number of sensory-related genes, which are located within special chromatin structure, could bring a low detection rate of MPGs in chr11.

Insights from ENCODE on Missing Proteins: Why β-Defensin Expression Is Scarcely Detected

β-Defensins (DEFBs) have a variety of functions. The majority of these proteins were not identified in a recent proteome survey. Neither protein detection nor the analysis of transcriptomic data based on RNA-seq data for three liver cancer cell lines identified any expression products. Extensive investigation into DEFB transcripts in over 70 cell lines offered similar results. This fact naturally begs the question—Why are DEFB genes scarcely expressed? After examining DEFB gene annotation and the physicochemical properties of its protein products, we postulated that regulatory elements could play a key role in the resultant poor transcription of DEFB genes. Four regions containing DEFB genes and six adjacent regions on chromosomes 6, 8, and 20 were carefully investigated using The Encyclopedia of DNA Elements (ENCODE) information, such as that of DNase I hypersensitive sites (DHSs), transcription factors (TFs), and histone modifications. The results revealed that the intensities of these ENCODE features were globally weaker than those in the adjacent regions. Impressively, DEFB-related regions on chromosomes 6 and 8 containing several non-DEFB genes had lower ENCODE feature intensities, indicating that the absence of DEFB mRNAs might not depend on the gene family but may be reliant upon gene location and chromatin structure.

Functional annotation of proteome encoded by human chromosome 22

As part of the chromosome-centric human proteome project (C-HPP) initiative, we report our progress on the annotation of chromosome 22. Chromosome 22, spanning 51 million base pairs, was the first chromosome to be sequenced. Gene dosage alterations on this chromosome have been shown to be associated with a number of congenital anomalies. In addition, several rare but aggressive tumors have been associated with this chromosome. A number of important gene families including immunoglobulin lambda locus, Crystallin beta family, and APOBEC gene family are located on this chromosome. On the basis of proteomic profiling of 30 histologically normal tissues and cells using high-resolution mass spectrometry, we show protein evidence of 367 genes on chromosome 22. Importantly, this includes 47 proteins, which are currently annotated as “missing” proteins. We also confirmed the translation start sites of 120 chromosome 22-encoded proteins. Employing a comprehensive proteogenomics analysis pipeline, we provide evidence of novel coding regions on this chromosome which include upstream ORFs and novel exons in addition to correcting existing gene structures. We describe tissue-wise expression of the proteins and the distribution of gene families on this chromosome. These data have been deposited to ProteomeXchange with the identifier PXD000561.

Chromosome-8-coded proteome of Chinese Chromosome Proteome Data set (CCPD) 2.0 with partial immunohistochemical verifications

We upgraded the preliminary CCPD 1.0 to CCPD 2.0 using the latest deep-profiling proteome (CCPD 2013) of three hepatocellular carcinoma (HCC) cell lines, namely, Hep3B, MHCC97H, and HCCLM3 (ProteomeXchange identifiers: PXD000529, PXD000533, and PXD000535). CCPD 2.0 totally covered 63.6% (438/689) of Chr. 8-coded proteins and 62.6% (439/701) of Chr. 8-coded protein-coding genes. Interestingly, we found that the missing proteins exhibited a tendency to form a cluster region in chromosomes, such as two β-defensins clusters in Chr. 8, caused perhaps by their inflammation-related features. For the 41 Chr. 8-coded proteins being weakly or barely identified previously, we have performed an immunohistochemical (IHC) verification in 30 pairs of carcinoma/para-carcinoma HCC and 20 noncancerous liver tissues and confirmed their expressional evidence and occurrence proportions in tissue samples. We also verified 13 Chr. 8-coded HCC tumorigenesis-associated depleting or deficient proteins reported in CCPD 1.0 using IHC and screened 16 positive and 24 negative HCC metastatic potential-correlated proteins from large-scale label-free proteome quantitation data of CCPD 2013. Our results suggest that the selection of proper samples and the methodology to look for targeted missing proteins should be carefully considered in further verifications for the remaining Chr. 8-coded proteins.

Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines

Cancer genomics unveils many cancer-related mutations, including some chromosome 20 (Chr.20) genes. The mutated messages have been found in the corresponding mRNAs; however, whether they could be translated to proteins still requires more evidence. Herein, we proposed a transomics strategy to profile the expression status of human Chr.20 genes (555 in Ensembl v72). The data of transcriptome and translatome (the mRNAs bound with ribosome, translating mRNAs) revealed that ∼80% of the coding genes on Chr.20 were detected with mRNA signals in three liver cancer cell lines, whereas of the proteome identified, only ∼45% of the Chr.20 coding genes were detected. The high amount of overlapping of identified genes in mRNA and RNC-mRNA (ribosome nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent distribution of the abundance averages of mRNA and RNC-mRNA along the Chr.20 subregions in three liver cancer cell lines indicate that the mRNA information is efficiently transmitted from transcriptional to translational stage, qualitatively and quantitatively. Of the 457 genes identified in mRNAs and RNC-mRNA, 136 were found to contain SNVs with 213 sites, and >40% of these SNVs existed only in metastatic cell lines, suggesting them as the metastasis-related SNVs. Proteomics analysis showed that 16 genes with 20 SNV sites were detected with reliable MS/MS signals, and some SNVs were further validated by the MRM approach. With the integration of the omics data at the three expression phases, therefore, we are able to achieve the overall view of the gene expression of Chr.20, which is constructive in understanding the potential trend of encoding genes in a cell line and exploration of a new type of markers related to cancers.

Genomic instability and colon carcinogenesis: from the perspective of genes

Colon cancer is the second most lethal cancer; approximately 600,000 people die of it annually in the world. Colon carcinogenesis generally follows a slow and stepwise process of accumulation of mutations under the influence of environmental and epigenetic factors. To adopt a personalized (tailored) cancer therapy approach and to improve current strategies for prevention, diagnosis, prognosis, and therapy overall, advanced understanding of molecular events associated with colon carcinogenesis is necessary. A contemporary approach that combines genetics, epigenomics, and signaling pathways has revealed many genetic/genomic alterations associated with colon cancer progression and their relationships to a genomic instability phenotype prevalent in colon cancer. In this review, we describe the relationship between gene mutations associated with colon carcinogenesis and a genomic instability phenotype, and we discuss possible clinical applications of genomic instability studies. Colon carcinogenesis is associated with frequent mutations in several pathways that include phosphatidylinositol 3-kinase, adenomatous polyposis coli, p53 (TP53), F-box and WD repeat domain containing 7, transforming growth factor-β, chromosome cohesion, and K-RAS. These genes frequently mutated in pathways affecting colon cancer were designated colon cancer (CAN) genes. Aberrations in major colon CAN genes have a causal relationship to genomic instability. Conversely, genomic instability itself plays a role in colon carcinogenesis in experimental settings, as demonstrated in transgenic mouse models with high genomic instability. Thus, there is a feedback-type relationship between CAN gene mutations and genomic instability. These genetic/genomic studies have led to emerging efforts to apply the knowledge to colon cancer prognosis and to targeted therapy.