Axitinib blocks Wnt/ß-catenin signaling and directs asymmetric cell division in cancer.

Oncogenic mutations of the Wnt (wingless)/ß-catenin pathway are frequently observed in major cancer types. Thus far, however, no therapeutic agent targeting Wnt/ß-catenin signaling is available for clinical use. Here we demonstrate that axitinib, a clinically approved drug, strikingly blocks Wnt/ß-catenin signaling in cancer cells, zebrafish, and Apc(min/+) mice. Notably, axitinib dramatically induces Wnt asymmetry and nonrandom DNA segregation in cancer cells by promoting nuclear ß-catenin degradation independent of the GSK3ß (glycogen synthase kinase3ß)/APC (adenomatous polyposis coli) complex. Using a DARTS (drug affinity-responsive target stability) assay coupled to 2D-DIGE (2D difference in gel electrophoresis) and mass spectrometry, we have identified the E3 ubiquitin ligase SHPRH (SNF2, histone-linker, PHD and RING finger domain-containing helicase) as the direct target of axitinib in blocking Wnt/ß-catenin signaling. Treatment with axitinib stabilizes SHPRH and thereby increases the ubiquitination and degradation of ß-catenin. Our findings suggest a previously unreported mechanism of nuclear ß-catenin regulation and indicate that axitinib, a clinically approved drug, would provide therapeutic benefits for cancer patients with aberrant nuclear ß-catenin activation.

Identifying driver mutations from sequencing data of heterogeneous tumors in the era of personalized genome sequencing.

Distinguishing driver mutations from passenger mutations is critical to the understanding of the molecular mechanisms of carcinogenesis and for identifying prognostic and diagnostic markers as well as therapeutic targets. We reviewed the current approaches and software for identifying driver mutations from passenger mutations including both biology-based approaches and machine-learning-based approaches. We also reviewed approaches to identify driver mutations in the context of pathways or gene sets. Finally, we discussed the challenges of predicting driver mutations considering the complexities of inter- and intra-tumor heterogeneity as well as the evolution and progression of tumors.

Context dependent regulatory patterns of the androgen receptor and androgen receptor target genes.

BACKGROUND: Expression of the androgen receptor (AR) is associated with androgen-dependent proliferation arrest and terminal differentiation of normal prostate epithelial cells. Additionally, activation of the AR is required for survival of benign luminal epithelial cells and primary cancer cells, thus androgen deprivation therapy (ADT) leads to apoptosis in both benign and cancerous tissue. Escape from ADT is known as castration-resistant prostate cancer (CRPC). In the course of CRPC development the AR typically switches from being a cell-intrinsic inhibitor of normal prostate epithelial cell proliferation to becoming an oncogene that is critical for prostate cancer cell proliferation. A clearer understanding of the context dependent activation of the AR and its target genes is therefore desirable. METHODS: Immortalized human prostate basal epithelial EP156T cells and progeny cells that underwent epithelial to mesenchymal transition (EMT), primary prostate epithelial cells (PrECs) and prostate cancer cell lines LNCaP, VCaP and 22Rv1 were used to examine context dependent restriction and activation of the AR and classical target genes, such as KLK3. Genome-wide gene expression analyses and single cell protein analyses were applied to study the effect of different contexts. RESULTS: A variety of growth conditions were tested and found unable to activate AR expression and transcription of classical androgen-dependent AR target genes, such as KLK3, in prostate epithelial cells with basal cell features or in mesenchymal type prostate cells. The restriction of androgen- and AR-dependent transcription of classical target genes in prostate basal epithelial cells was at the level of AR expression. Exogenous AR expression was sufficient for androgen-dependent transcription of AR target genes in prostate basal epithelial cells, but did not exert a positive feedback on endogenous AR expression. Treatment of basal prostate epithelial cells with inhibitors of epigenetic gene silencing was not efficient in inducing androgen-dependent transcription of AR target genes, suggesting the importance of missing cofactor(s). CONCLUSIONS: Regulatory mechanisms of AR and androgen-dependent AR target gene transcription are insufficiently understood and may be critical for prostate cancer initiation, progression and escape from standard therapy. The present model is useful for the study of context dependent activation of the AR and its transcriptome.

Recurrent targeted genes of hepatitis B virus in the liver cancer genomes identified by a next-generation sequencing-based approach.

Integration of the viral DNA into host chromosomes was found in most of the hepatitis B virus (HBV)-related hepatocellular carcinomas (HCCs). Here we devised a massive anchored parallel sequencing (MAPS) method using next-generation sequencing to isolate and sequence HBV integrants. Applying MAPS to 40 pairs of HBV-related HCC tissues (cancer and adjacent tissues), we identified 296 HBV integration events corresponding to 286 unique integration sites (UISs) with precise HBV-Human DNA junctions. HBV integration favored chromosome 17 and preferentially integrated into human transcript units. HBV targeted genes were enriched in GO terms: cAMP metabolic processes, T cell differentiation and activation, TGF beta receptor pathway, ncRNA catabolic process, and dsRNA fragmentation and cellular response to dsRNA. The HBV targeted genes include 7 genes (PTPRJ, CNTN6, IL12B, MYOM1, FNDC3B, LRFN2, FN1) containing IPR003961 (Fibronectin, type III domain), 7 genes (NRG3, MASP2, NELL1, LRP1B, ADAM21, NRXN1, FN1) containing IPR013032 (EGF-like region, conserved site), and three genes (PDE7A, PDE4B, PDE11A) containing IPR002073 (3', 5'-cyclic-nucleotide phosphodiesterase). Enriched pathways include hsa04512 (ECM-receptor interaction), hsa04510 (Focal adhesion), and hsa04012 (ErbB signaling pathway). Fewer integration events were found in cancers compared to cancer-adjacent tissues, suggesting a clonal expansion model in HCC development. Finally, we identified 8 genes that were recurrent target genes by HBV integration including fibronectin 1 (FN1) and telomerase reverse transcriptase (TERT1), two known recurrent target genes, and additional novel target genes such as SMAD family member 5 (SMAD5), phosphatase and actin regulator 4 (PHACTR4), and RNA binding protein fox-1 homolog (C. elegans) 1 (RBFOX1). Integrating analysis with recently published whole-genome sequencing analysis, we identified 14 additional recurrent HBV target genes, greatly expanding the HBV recurrent target list. This global survey of HBV integration events, together with recently published whole-genome sequencing analyses, furthered our understanding of the HBV-related HCC.

[Target-resequencing to identify microRNA-associated SNP and predict the effect of SNP on microRNA function in colorectal cancer patients].

OBJECTIVE: To identify SNPs in the miRNA genes in colorectal cancer (CRC) patients and to investigate their association with CRC. METHODS: DNAs were isolated from 30 CRC tumor tissues and 30 tumor-adjacent tissues, and subjected to target capture using a custom miRNA chip covering 685 miRNA genes from NimbleGen. The captured DNAs were then sequenced using the Illumina's sequencing technology, and the data were analyzed. RESULTS: We identified 64 SNPs in 43 miRNA genes and most of these SNPs are novel SNPs not reported previously. Prediction of functional consequences of the SNPs using TargetScan and miRSNP showed that SNPs of hsa-mir-1273-G/A, hsa-mir-548h-3-C/U, hsa-mir-1290-A/G, and hsa-mir-1273-C/U resulted in reduction of their mature miRNA abundance. SNPs of hsa-mir-376b-C/G, hsa-mir-604-T/C, hsa-mir-1268-T/G and hsa-mir-146a-C/G resulted in changes in their targeted genes. Finally, we focused on the analysis of SNPs in mir-146a and we found that mir-146a rs1052918 C>G was predicted to promote tumorigenesis via the Wnt signaling pathway. CONCLUSIONS: SNPs in the miRNA genes are important for tumorigenesis. The changes by hsa-mir-146a rs1052918 C>G may result in loss of Wnt, constant activation of the Wnt signaling pathway, and uncontrolled cell proliferation and tumor progression.

SOX4 inhibits GBM cell growth and induces G0/G1 cell cycle arrest through Akt-p53 axis.

BACKGROUND: SOX4 is a transcription factor required for tissue development and differentiation in vertebrates. Overexpression of SOX4 has been reported in many cancers including glioblastoma multiforme (GBM), however, the underlying mechanism of actions has not been studied. In this study, we investigated the role of SOX4 in GBM. METHODS: Kaplan-Meier analysis was performed to assess the association between SOX4 expression levels and survival times in primary GBM samples. Cre/lox P system was used to generate gain or loss of SOX4 in GBM cells, and microarray analysis uncovered the regulation network of SOX4 in GBM cells. RESULTS: High SOX4 expression was significantly associated with good prognosis of primary GBMs. SOX4 inhibited the growth of GBM cell line LN229, A172G and U87MG, partly via the activation of p53-p21 signaling and down-regulation of phosphorylated AKT1. Gene expression profiling and subsequent gene ontology analysis showed that SOX4 influenced several key pathways including the Wnt/ beta-catenin and TGF-beta signaling pathways. CONCLUSIONS: Our study found that SOX4 acts as a tumor suppressor in GBM cells by induce cell cycle arrest and inhibiting cell growth.

A novel histone H4 arginine 3 methylation-sensitive histone H4 binding activity and transcriptional regulatory function for signal recognition particle subunits SRP68 and SRP72.

BACKGROUND: Histone methylation is believed to recruit specific histone-binding proteins. RESULTS: We identified SRP68/72 heterodimers as major nuclear proteins whose binding of histone H4 tail is inhibited by H4R3 methylation. CONCLUSION: SRP68/72 are novel histone H4-binding proteins. SIGNIFICANCE: Uncovers a novel chromatin regulatory function for SRP68/72 and suggests that histone arginine methylation may function mainly in inhibiting rather than recruiting effector proteins. Arginine methylation broadly occurs in the tails of core histones. However, the mechanisms by which histone arginine methylation regulates transcription remain poorly understood. In this study we attempted to identify nuclear proteins that specifically recognize methylated arginine 3 in the histone H4 (H4R3) tail using an unbiased proteomic approach. No major nuclear protein was observed to specifically bind to methylated H4R3 peptides. However, H4R3 methylation markedly inhibited the binding of two proteins to H4 tail peptide. These proteins were identified as the SRP68 and SRP72 heterodimers (SRP68/72), the components of the signal recognition particle (SRP). Only SRP68/72, but not the SRP complex, bound the H4 tail peptide. SRP68 and SRP72 bound the H4 tail in vitro and associated with chromatin in vivo. The chromatin association of SRP68 and SRP72 was regulated by PRMT5 and PRMT1. Both SRP68 and SRP72 activated transcription when tethered to a reporter via a heterologous DNA binding domain. Analysis of the genome-wide occupancy of SRP68 identified target genes regulated by SRP68. Taken together, these results demonstrate a role of H4R3 methylation in blocking the binding of effectors to chromatin and reveal a novel role for the SRP68/SRP72 heterodimer in the binding of chromatin and transcriptional regulation.

A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas.

Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.

Immunological Findings in a Group of Individuals Who Were Poor or Non-Responders to Standard Two-Dose SARS-CoV-2 Vaccines.

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a pandemic. However, data on the poor or non-responders to SARS-CoV-2 vaccines in the general population are limited. The objective of this study was to comprehensively compare the immunological characteristics of poor or non-responders to SARS-CoV-2 vaccines in the 18-59-year group with those in the ≥60-year group using internationally recognized cut-off values. The main outcome was effective seroconversion characterized by an anti-SARS-CoV-2 spike IgG level of at least a four-fold increase from baseline. Profiling of naïve immune cells was analyzed prior to vaccination to demonstrate baseline immunity. The outcomes of effective seroconversion in patients aged 18-59 years with those in patients aged ≥60 years were compared. The quantitative level of anti-spike IgG was significantly lower in individuals aged ≥60 and men aged 18-59 years. There were 7.5% of poor or non-responders among the 18-59 years and 11.7% of poor or non-responders in the ≥60 years using a four-fold increase parameter. There were 37.0-58.1% with low lymphocyte count (<1000/mm3), 33.3-45.2% with low CD4 cell counts (<500/mm3), and 74.1-96.8% with low B cell counts (<100/mm3) in the non-seroconversion group. An individual with an anti-SARS-CoV-2 spike IgG titer below 50 BAU/mL might be considered a poor or non-responder between 14 and 90 days after the last vaccine dose. Booster vaccination or additional protective measures should be recommended to poor or non-responders as soon as possible to reduce disease severity and mortality.

miR-433 Inhibits Glioblastoma Progression by Suppressing the PI3K/Akt Signaling Pathway Through Direct Targeting of ERBB4.

Glioblastoma multiforme (GBM) is a highly malignant brain tumor where new biomarkers and drug targets are much needed in the oncology clinic. miR-433 was identified as a tumor-suppressing miRNA in several different types of human cancer. However, the integrative biology of miR-433 in GBM is still largely unknown. By analyzing the expression profiles of miR-433 in 198 patients with glioma at The Cancer Genome Atlas, we found that the miR-433 expression was decreased in glioma whereas the low expression of miR-433 was significantly associated with shorter overall survival. We then conducted in vitro studies and demonstrated that increased expression of miR-433 suppressed the proliferation, migration, and invasion of LN229 and T98G cells, two representative glioma cell lines. Further, using in vivo mouse model, we found that upregulation of miR-433 inhibited the tumor growth of glioma cells. To situate the integrative biology understanding of the action of miR-433 in glioma, we identified ERBB4 as a gene targeted directly by miR-433 in LN229 and T98G cells. Overexpressed ERBB4 rescued the phenotype caused by overexpression of miR-433. Finally, we showed that miR-433 suppressed the PI3K/Akt pathway in glioma cells. In conclusion, our study demonstrated that miR-433 could potentially act as a tumor suppressor for GBM and may serve as a potential therapeutic target for GBM. Further integrative biology and clinical translational research are warranted to evaluate miR-433 in GBM.

Comparison of immune response to SARS-COV-2 vaccine in COVID-recovered versus non-infected Individuals.

To determine the antibody levels at 6 months in SARS-CoV-2 vaccinated individuals in COVID-recovered versus non-infected groups to determine the need to administer booster COVID vaccine in each group. Prospective longitudinal study. Pathology Department, Combined Military Hospital, Lahore for a period of eight months from July 2021 to February 2022. Two hundred and thirty three study participants in both COVID recovered and non-infected groups (105 participants in infected group, 128 participants in non-infected group) were subjected to blood sampling at 6 months post-vaccination. Anti-SARS-CoV-2 IgG antibody test was done using Chemiluminescence method. Comparison of antibody levels between COVID-recovered and non-infected groups was made. Results were compiled and statistically analyzed using SPSS version 21. Out of 233 study participants, males were 183 (78%) while females were 50 (22%), mean age being 35.93 years ± 8.298. Mean Anti-SARS-CoV-2 S IgG levels among COVID-recovered group was 1342 U/ml and among non-infected group was 828 U/ml at 6 months post-vaccination. Mean antibody titers in COVID-19 recovered group are higher than in non-infected group at 6 months post-vaccination in both groups.

Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction.

MOTIVATION: Protein-ligand binding sites are the active sites on protein surface that perform protein functions. Thus, the identification of those binding sites is often the first step to study protein functions and structure-based drug design. There are many computational algorithms and tools developed in recent decades, such as LIGSITE(cs/c), PASS, Q-SiteFinder, SURFNET, and so on. In our previous work, MetaPocket, we have proved that it is possible to combine the results of many methods together to improve the prediction result. RESULTS: Here, we continue our previous work by adding four more methods Fpocket, GHECOM, ConCavity and POCASA to further improve the prediction success rate. The new method MetaPocket 2.0 and the individual approaches are all tested on two datasets of 48 unbound/bound and 210 bound structures as used before. The results show that the average success rate has been raised 5% at the top 1 prediction compared with previous work. Moreover, we construct a non-redundant dataset of drug-target complexes with known structure from DrugBank, DrugPort and PDB database and apply MetaPocket 2.0 to this dataset to predict drug binding sites. As a result, >74% drug binding sites on protein target are correctly identified at the top 3 prediction, and it is 12% better than the best individual approach. AVAILABILITY: The web service of MetaPocket 2.0 and all the test datasets are freely available at http://projects.biotec.tu-dresden.de/metapocket/ and http://sysbio.zju.edu.cn/metapocket.

Digital Transformation in Personalized Medicine with Artificial Intelligence and the Internet of Medical Things.

Digital transformation is impacting every facet of science and society, not least because there is a growing need for digital services and products with the COVID-19 pandemic. But the need for digital transformation in diagnostics and personalized medicine field cuts deeper. In the past, personalized/precision medicine initiatives have been unable to capture the patients' experiences and clinical outcomes in real-time and in real-world settings. The availability of wearable smart sensors, wireless connectivity, artificial intelligence, and the Internet of Medical Things is changing the personalized/precision medicine research and implementation landscape. Digital transformation in poised to accelerate personalized/precision medicine and systems science in multiple fronts such as deep real-time phenotyping with patient-reported outcomes, high-throughput association studies between omics and highly granular phenotypic variation, digital clinical trials, among others. The present expert review offers an analysis of these systems science frontiers with a view to future applications at the intersection of digital health and personalized medicine, or put in other words, signaling the rise of "digital personalized medicine."

Multi-Omics and Artificial Intelligence-Guided Data Integration in Chronic Liver Disease: Prospects and Challenges for Precision Medicine.

Chronic liver disease (CLD) is a significant planetary health burden. CLD includes a broad range of liver pathologies from different causes, for example, hepatitis B virus infection, fatty liver disease, hepatocellular carcinoma, and nonalcoholic fatty liver disease or the metabolic associated fatty liver disease. Biomarker and diagnostic discovery, and new molecular targets for precision treatments are timely and sorely needed in CLD. In this context, multi-omics data integration is increasingly being facilitated by artificial intelligence (AI) and attendant digital transformation of systems science. While the digital transformation of multi-omics integrative analyses is still in its infancy, there are noteworthy prospects, hope, and challenges for diagnostic and therapeutic innovation in CLD. This expert review aims at the emerging knowledge frontiers as well as gaps in multi-omics data integration at bulk tissue levels, and those including single cell-level data, gut microbiome data, and finally, those incorporating tissue-specific information. We refer to AI and related digital transformation of the CLD research and development field whenever possible. This review of the emerging frontiers at the intersection of systems science and digital transformation informs future roadmaps to bridge digital technology discovery and clinical omics applications to benefit planetary health and patients with CLD.

Landscape of the SOX2 protein-protein interactome.

SOX2 is a key gene implicated in maintaining the stemness of embryonic and adult stem cells that appears to re-activate in several human cancers including glioblastoma multiforme. Using immunoprecipitation (IP)/MS/MS, we identified 144 proteins that are putative SOX2 interacting proteins. Of note, SOX2 was found to interact with several heterogeneous nuclear ribonucleoprotein family proteins, including HNRNPA2B1, HNRNPA3, HNRNPC, HNRNPK, HNRNPL, HNRNPM, HNRNPR, HNRNPU, as well as other ribonucleoproteins, DNA repair proteins and helicases. Gene ontology (GO) analysis revealed that the SOX2 interactome was enriched for GO terms GO:0030529 ribonucleoprotein complex and GO:0004386 helicase activity. These findings indicate that SOX2 associates with the heterogeneous nuclear ribonucleoprotein complex, suggesting a possible role for SOX2 in post-transcriptional regulation in addition to its function as a transcription factor.

The SOX2 response program in glioblastoma multiforme: an integrated ChIP-seq, expression microarray, and microRNA analysis.

BACKGROUND: SOX2 is a key gene implicated in maintaining the stemness of embryonic and adult stem cells. SOX2 appears to re-activate in several human cancers including glioblastoma multiforme (GBM), however, the detailed response program of SOX2 in GBM has not yet been defined. RESULTS: We show that knockdown of the SOX2 gene in LN229 GBM cells reduces cell proliferation and colony formation. We then comprehensively characterize the SOX2 response program by an integrated analysis using several advanced genomic technologies including ChIP-seq, microarray profiling, and microRNA sequencing. Using ChIP-seq technology, we identified 4883 SOX2 binding regions in the GBM cancer genome. SOX2 binding regions contain the consensus sequence wwTGnwTw that occurred 3931 instances in 2312 SOX2 binding regions. Microarray analysis identified 489 genes whose expression altered in response to SOX2 knockdown. Interesting findings include that SOX2 regulates the expression of SOX family proteins SOX1 and SOX18, and that SOX2 down regulates BEX1 (brain expressed X-linked 1) and BEX2 (brain expressed X-linked 2), two genes with tumor suppressor activity in GBM. Using next generation sequencing, we identified 105 precursor microRNAs (corresponding to 95 mature miRNAs) regulated by SOX2, including down regulation of miR-143, -145, -253-5p and miR-452. We also show that miR-145 and SOX2 form a double negative feedback loop in GBM cells, potentially creating a bistable system in GBM cells. CONCLUSIONS: We present an integrated dataset of ChIP-seq, expression microarrays and microRNA sequencing representing the SOX2 response program in LN229 GBM cells. The insights gained from our integrated analysis further our understanding of the potential actions of SOX2 in carcinogenesis and serves as a useful resource for the research community.

Expression of 5-methylcytosine regulators is highly associated with the clinical phenotypes of prostate cancer and DNMTs expression predicts biochemical recurrence.

In patients with prostate cancer (PCa), there is a high rate of overdiagnosis and frequent overtreatment. Therefore, there is an urgent need for more accurate prediction of biochemical recurrence (BCR). DNA methylation regulation patterns play crucial roles in tumorigenicity, progression, and treatment efficacy in PCa. However, the global relationship between epigenetic alterations, changes in mRNA levels, and pathologic phenotypes of PCa remain largely undefined. Here, we conducted a systematic analysis to identify global coexpression and comethylation modules in PCa. We identified coregulated methylation and expression modules and the relationships between epigenetic modifications, tumor progression, and the corresponding immune microenvironment in PCa. Our results show that DNA methyltransferases (DNMTs) are strongly associated with pathologic phenotypes and immune infiltration patterns in PCa. We built a two-factor predictive model using the expression features of DNMT3B and DNMT1. The model was used to predict the BCR status of patients with PCa and achieved area under the receiver operating characteristic curve values of 0.70 and 0.88 in the training and independent testing datasets, respectively.

WaveletQuant, an improved quantification software based on wavelet signal threshold de-noising for labeled quantitative proteomic analysis.

BACKGROUND: Quantitative proteomics technologies have been developed to comprehensively identify and quantify proteins in two or more complex samples. Quantitative proteomics based on differential stable isotope labeling is one of the proteomics quantification technologies. Mass spectrometric data generated for peptide quantification are often noisy, and peak detection and definition require various smoothing filters to remove noise in order to achieve accurate peptide quantification. Many traditional smoothing filters, such as the moving average filter, Savitzky-Golay filter and Gaussian filter, have been used to reduce noise in MS peaks. However, limitations of these filtering approaches often result in inaccurate peptide quantification. Here we present the WaveletQuant program, based on wavelet theory, for better or alternative MS-based proteomic quantification. RESULTS: We developed a novel discrete wavelet transform (DWT) and a 'Spatial Adaptive Algorithm' to remove noise and to identify true peaks. We programmed and compiled WaveletQuant using Visual C++ 2005 Express Edition. We then incorporated the WaveletQuant program in the Trans-Proteomic Pipeline (TPP), a commonly used open source proteomics analysis pipeline. CONCLUSIONS: We showed that WaveletQuant was able to quantify more proteins and to quantify them more accurately than the ASAPRatio, a program that performs quantification in the TPP pipeline, first using known mixed ratios of yeast extracts and then using a data set from ovarian cancer cell lysates. The program and its documentation can be downloaded from our website at http://systemsbiozju.org/data/WaveletQuant.

A porous 3D cell culture micro device for cell migration study.

Cell migration under chemoattractant is an important biological step in cancer metastasis that causes the spread of malignant tumor cells. Porous polymeric materials are widely used to mimic the extracellular matrix (ECM) environment for applications such as three dimensional (3D) cell culturing and tissue engineering. In this paper we report a novel 3D cell culture device based on porous polymeric material to study cancer migration. We fabricated a porous channel on a polymeric chip using a selective ultrasonic foaming method. We demonstrate that a chemical concentration gradient could be established through the porous channel due to the slow diffusion process. We show that significant cell migration could be observed through the porous channel within 1-2 weeks of cell culturing when metastatic M4A4-GFP breast cancer cells were induced by 20% fetal bovine serum (FBS).We also developed a mathematical model to evaluate the diffusivity and concentration gradient through the fabricated porous structure.