This document describes a bioinformatic methodology to predict synthetic lethal drug targets for cancers deficient in the tumor suppressor gene E-cadherin (CDH1). The methodology analyzes gene expression data from public databases to identify genes whose expression levels correlate with CDH1. Known synthetic lethal interactions, like between BRCA and PARP1, were correctly predicted. Several candidate synthetic lethal partners of CDH1 were identified and grouped into biological pathways. This bioinformatic approach can efficiently predict synthetic lethal targets to guide experimental validation and help develop targeted therapies for CDH1-deficient cancers.
A new assay for measuring chromosome instability (CIN) and identification of...Enrique Moreno Gonzalez
Aneuploidy is a feature of most cancer cells that is often accompanied by an elevated rate of chromosome mis-segregation termed chromosome instability (CIN). While CIN can act as a driver of cancer genome evolution and tumor progression, recent findings point to the existence of a threshold level beyond which CIN becomes a barrier to tumor growth and therefore can be exploited therapeutically. Drugs known to increase CIN beyond the therapeutic threshold are currently few in number, and the clinical promise of targeting the
CIN phenotype warrants new screening efforts. However, none of the existing methods, including the in vitro micronuclei (MNi) assay, developed to quantify CIN, is entirely satisfactory.
Variant G6PD levels promote tumor cell proliferation or apoptosis via the STA...Enrique Moreno Gonzalez
Glucose-6-phosphate dehydrogenase (G6PD), elevated in tumor cells, catalyzes the first reaction in the pentose-phosphate pathway. The regulation mechanism of G6PD and pathological change in human melanoma growth remains unknown.
As an uncommon malignant tumor, hypopharyngeal cancer accounts for 3–5% of head and neck tumors [1]. Most pathological types of hypopharyngeal cancer are squamous cell carcinoma. Due to the occult anatomical location of hypopharyngeal cancer and poor surgical effect, local recurrence or distant metastasis often occurs in patients with hypopharyngeal cancer following surgery.
A new assay for measuring chromosome instability (CIN) and identification of...Enrique Moreno Gonzalez
Aneuploidy is a feature of most cancer cells that is often accompanied by an elevated rate of chromosome mis-segregation termed chromosome instability (CIN). While CIN can act as a driver of cancer genome evolution and tumor progression, recent findings point to the existence of a threshold level beyond which CIN becomes a barrier to tumor growth and therefore can be exploited therapeutically. Drugs known to increase CIN beyond the therapeutic threshold are currently few in number, and the clinical promise of targeting the
CIN phenotype warrants new screening efforts. However, none of the existing methods, including the in vitro micronuclei (MNi) assay, developed to quantify CIN, is entirely satisfactory.
Variant G6PD levels promote tumor cell proliferation or apoptosis via the STA...Enrique Moreno Gonzalez
Glucose-6-phosphate dehydrogenase (G6PD), elevated in tumor cells, catalyzes the first reaction in the pentose-phosphate pathway. The regulation mechanism of G6PD and pathological change in human melanoma growth remains unknown.
As an uncommon malignant tumor, hypopharyngeal cancer accounts for 3–5% of head and neck tumors [1]. Most pathological types of hypopharyngeal cancer are squamous cell carcinoma. Due to the occult anatomical location of hypopharyngeal cancer and poor surgical effect, local recurrence or distant metastasis often occurs in patients with hypopharyngeal cancer following surgery.
Purpose: An inherited mutation in KRAS (LCS6-variant or rs61764370) results in altered control of the KRAS oncogene. We studied this biomarker’s correlation to anti-EGFR monoclonal antibody (mAb) therapy
response in patients with metastatic colorectal cancer.
Experimental Design: LCS6-variant and KRAS/BRAF mutational status was determined in 512 patients
with metastatic colorectal cancer treated with salvage anti-EGFR mAb therapy, and findings correlated with
outcome. Reporters were tested in colon cancer cell lines to evaluate the differential response of the LCS6-
variant allele to therapy exposure.
Results: In this study, 21.2% (109 of 512) of patients with metastatic colorectal cancer had the LCS6-
variant (TG/GG), which was found twice as frequently in the BRAF-mutated versus the wild-type (WT) group
(P = 0.03). LCS6-variant patients had significantly longer progression- free survival (PFS) with anti-EGFR
mAb monotherapy treatment in the whole cohort (16.85 vs. 7.85 weeks; P = 0.019) and in the double WT
(KRAS and BRAF) patient population (18 vs. 10.4 weeks; P = 0.039). Combination therapy (mAbs plus
chemotherapy) led to improved PFS and overall survival (OS) for nonvariant patients, and brought their
outcome to levels comparable with LCS6-variant patients receiving anti-EGFR mAb monotherapy. Combination
therapy did not lead to improved PFS or OS for LCS6-variant patients. Cell line studies confirmed a
unique response of the LCS6-variant allele to both anti-EGFR mAb monotherapy and chemotherapy.
Conclusions: LCS6-variant patients with metastatic colorectal cancer have an excellent response to anti-EGFR
mAb monotherapy, without any benefit from the addition of chemotherapy. These findings further confirm
the importance of thismutation as a biomarker of anti-EGFR mAb response in patients with metastatic colorectal cancer, and warrant further prospective confirmation.
Annals of Mutagenesis is an open access, peer reviewed, scholarly journal dedicated to publish articles covering all areas of Mutagenesis.
The journal aims to promote research communications and provide a forum for doctors, researchers, physicians and healthcare professionals to find most recent advances in all areas of Mutagenesis. Annals of Mutagenesis accepts original research articles, reviews, mini reviews, case reports and rapid communication covering all aspects of mutagenesis.
Annals of Mutagenesis strongly supports the scientific up gradation and fortification in related scientific research community by enhancing access to peer reviewed scientific literary works. Austin Publishing Group brings universally peer reviewed journals under one roof thereby promoting knowledge sharing, mutual promotion of multidisciplinary science.
Newer biomarkers,techniques & their inclusion in 2016 WHO classification for leukaemia/lymphomas increases the responsibility of the pathologists, requiring to develop an integrated multidisciplinary approach for reporting.
Zinc supplementation may reduce the risk of hepatocellular carcinoma using bi...caijjournal
Hepatocellular carcinoma (HCC) is a primary liver cancer with poor survival rates. Gene expression data
of HCC are investigated to screen target genes and core genes, which are employed to propose a new
strategy for the treatment of HCC. New concepts such as gene data streams, gene characteristic strength
(CS), gene impact factor (GIF) and gene force (GF) are proposed. Together with gene community network
(GCN), a novel algorithm, that is, called gene force algorithm (GFA), is presented to screen feature genes,
target genes and core genes. The fifteen target genes are obtained, which can be divided into three
clustering sets including HAMP Cluster = {HAMP, Trans, AQP4, VIPR1}, MT Cluster ={MT1H, MT1B,
MT1G, MT1E, MTIL, RNAHP, DNASE1L3} and GPC3 Cluster ={GPC3}. The core genes of each clusters
are HAMP, Metallothionein genes (MTs) and GPC3 respectively, where MTs is a general name for a group
of metallothionein genes. According to the relationship between the three core genes and the metals
including copper, iron and zinc, a treatment strategy for HCC is proposed, namely, "Supplement Zinc after
surgery" for HCC patients. The proposed treatment method can be used to regulate the expression levels of
HCC core genes.
Proteomics Exploration of Chronic Lymphocytic Leukemia_Crimson PublishersCrimsonpublishersCancer
Chronic Lymphocytic Leukemia (CLL) is an adult heme malignancy characterized by the presence of mature-appearing CD5+ B cells in the blood, bone marrow, and secondary lymphoid organs [1]. In the United States, there will be an estimate of 20,720 new cases and 3,930 deaths according to the American Cancer Society statistics. Symptoms include swollen lymph nodes, frequent infections, and fatigue which negatively impacts the quality of life of people affected [1]. CLL is heterogeneous in its progression and clinical outcomes. Factors that contribute to the heterogeneity include the immunoglobulin heavy chain (IGHV) status and chromosomal aberrations [2,3]. There are two subtypes of CLL: Unmutated(U-CLL) and Mutated CLL(M-CLL). 40% and 60% of patients are diagnosed with unmutated and mutated CLL. U-CLL is characterized by the presence of CLL cells that have less than two percent of their IGHV mutated, whereas M-CLL cells have more than two percent mutated [4]. U-CLL is the more aggressive phenotype [2]. These cells have increased responsiveness to antigens that bind the B cell receptor (BCR) versus M-CLL cells [5]. M-CLL is the more indolent phenotype. Increased BCR signaling results in increased cell survival and proliferation [5].
Diffuse Large B-cell Lymphoma (DLBCL) is a highly heterogeneous cancer of B cells. Apart from cell-of-origin, genetic variations have been observed to contribute towards heterogeneity leading to different pathogenic mechanisms and overall survival outcomes. Various classification schemes have been proposed that may aid in risk stratification and developing new therapeutics for those who fail frontline therapy. This mini review highlights the significance of genetic variations as biomarkers for DLBCL and ease in extending it to clinical setting.
Abnormal expression of Pygopus 2 correlates with a malignant phenotype in hum...Enrique Moreno Gonzalez
Pygopus 2 (Pygo2) is a Pygo family member and an important component of the Wnt signaling transcriptional complex. Despite this data, no clinical studies investigating Pygo2 expression in lung cancer have yet been reported.
Purpose: An inherited mutation in KRAS (LCS6-variant or rs61764370) results in altered control of the KRAS oncogene. We studied this biomarker’s correlation to anti-EGFR monoclonal antibody (mAb) therapy
response in patients with metastatic colorectal cancer.
Experimental Design: LCS6-variant and KRAS/BRAF mutational status was determined in 512 patients
with metastatic colorectal cancer treated with salvage anti-EGFR mAb therapy, and findings correlated with
outcome. Reporters were tested in colon cancer cell lines to evaluate the differential response of the LCS6-
variant allele to therapy exposure.
Results: In this study, 21.2% (109 of 512) of patients with metastatic colorectal cancer had the LCS6-
variant (TG/GG), which was found twice as frequently in the BRAF-mutated versus the wild-type (WT) group
(P = 0.03). LCS6-variant patients had significantly longer progression- free survival (PFS) with anti-EGFR
mAb monotherapy treatment in the whole cohort (16.85 vs. 7.85 weeks; P = 0.019) and in the double WT
(KRAS and BRAF) patient population (18 vs. 10.4 weeks; P = 0.039). Combination therapy (mAbs plus
chemotherapy) led to improved PFS and overall survival (OS) for nonvariant patients, and brought their
outcome to levels comparable with LCS6-variant patients receiving anti-EGFR mAb monotherapy. Combination
therapy did not lead to improved PFS or OS for LCS6-variant patients. Cell line studies confirmed a
unique response of the LCS6-variant allele to both anti-EGFR mAb monotherapy and chemotherapy.
Conclusions: LCS6-variant patients with metastatic colorectal cancer have an excellent response to anti-EGFR
mAb monotherapy, without any benefit from the addition of chemotherapy. These findings further confirm
the importance of thismutation as a biomarker of anti-EGFR mAb response in patients with metastatic colorectal cancer, and warrant further prospective confirmation.
Annals of Mutagenesis is an open access, peer reviewed, scholarly journal dedicated to publish articles covering all areas of Mutagenesis.
The journal aims to promote research communications and provide a forum for doctors, researchers, physicians and healthcare professionals to find most recent advances in all areas of Mutagenesis. Annals of Mutagenesis accepts original research articles, reviews, mini reviews, case reports and rapid communication covering all aspects of mutagenesis.
Annals of Mutagenesis strongly supports the scientific up gradation and fortification in related scientific research community by enhancing access to peer reviewed scientific literary works. Austin Publishing Group brings universally peer reviewed journals under one roof thereby promoting knowledge sharing, mutual promotion of multidisciplinary science.
Newer biomarkers,techniques & their inclusion in 2016 WHO classification for leukaemia/lymphomas increases the responsibility of the pathologists, requiring to develop an integrated multidisciplinary approach for reporting.
Zinc supplementation may reduce the risk of hepatocellular carcinoma using bi...caijjournal
Hepatocellular carcinoma (HCC) is a primary liver cancer with poor survival rates. Gene expression data
of HCC are investigated to screen target genes and core genes, which are employed to propose a new
strategy for the treatment of HCC. New concepts such as gene data streams, gene characteristic strength
(CS), gene impact factor (GIF) and gene force (GF) are proposed. Together with gene community network
(GCN), a novel algorithm, that is, called gene force algorithm (GFA), is presented to screen feature genes,
target genes and core genes. The fifteen target genes are obtained, which can be divided into three
clustering sets including HAMP Cluster = {HAMP, Trans, AQP4, VIPR1}, MT Cluster ={MT1H, MT1B,
MT1G, MT1E, MTIL, RNAHP, DNASE1L3} and GPC3 Cluster ={GPC3}. The core genes of each clusters
are HAMP, Metallothionein genes (MTs) and GPC3 respectively, where MTs is a general name for a group
of metallothionein genes. According to the relationship between the three core genes and the metals
including copper, iron and zinc, a treatment strategy for HCC is proposed, namely, "Supplement Zinc after
surgery" for HCC patients. The proposed treatment method can be used to regulate the expression levels of
HCC core genes.
Proteomics Exploration of Chronic Lymphocytic Leukemia_Crimson PublishersCrimsonpublishersCancer
Chronic Lymphocytic Leukemia (CLL) is an adult heme malignancy characterized by the presence of mature-appearing CD5+ B cells in the blood, bone marrow, and secondary lymphoid organs [1]. In the United States, there will be an estimate of 20,720 new cases and 3,930 deaths according to the American Cancer Society statistics. Symptoms include swollen lymph nodes, frequent infections, and fatigue which negatively impacts the quality of life of people affected [1]. CLL is heterogeneous in its progression and clinical outcomes. Factors that contribute to the heterogeneity include the immunoglobulin heavy chain (IGHV) status and chromosomal aberrations [2,3]. There are two subtypes of CLL: Unmutated(U-CLL) and Mutated CLL(M-CLL). 40% and 60% of patients are diagnosed with unmutated and mutated CLL. U-CLL is characterized by the presence of CLL cells that have less than two percent of their IGHV mutated, whereas M-CLL cells have more than two percent mutated [4]. U-CLL is the more aggressive phenotype [2]. These cells have increased responsiveness to antigens that bind the B cell receptor (BCR) versus M-CLL cells [5]. M-CLL is the more indolent phenotype. Increased BCR signaling results in increased cell survival and proliferation [5].
Diffuse Large B-cell Lymphoma (DLBCL) is a highly heterogeneous cancer of B cells. Apart from cell-of-origin, genetic variations have been observed to contribute towards heterogeneity leading to different pathogenic mechanisms and overall survival outcomes. Various classification schemes have been proposed that may aid in risk stratification and developing new therapeutics for those who fail frontline therapy. This mini review highlights the significance of genetic variations as biomarkers for DLBCL and ease in extending it to clinical setting.
Abnormal expression of Pygopus 2 correlates with a malignant phenotype in hum...Enrique Moreno Gonzalez
Pygopus 2 (Pygo2) is a Pygo family member and an important component of the Wnt signaling transcriptional complex. Despite this data, no clinical studies investigating Pygo2 expression in lung cancer have yet been reported.
Proteogenomic analysis of human colon cancer reveals new therapeutic opportun...Gul Muneer
We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.
Assessing the clinical utility of cancer genomic and proteomic data across tu...Gul Muneer
Molecular profiling of tumors promises to advance the clinical
management of cancer, but the benefits of integrating
molecular data with traditional clinical variables have not been
systematically studied. Here we retrospectively predict patient
survival using diverse molecular data (somatic copy-number
alteration, DNA methylation and mRNA, microRNA and protein
expression) from 953 samples of four cancer types from The
Cancer Genome Atlas project. We find that incorporating
molecular data with clinical variables yields statistically
significantly improved predictions (FDR < 0.05) for three
cancers but those quantitative gains were limited (2.2–23.9%).
Additional analyses revealed little predictive power across
tumor types except for one case. In clinically relevant genes,
we identified 10,281 somatic alterations across 12 cancer types
in 2,928 of 3,277 patients (89.4%), many of which would
not be revealed in single-tumor analyses. Our study provides
a starting point and resources, including an open-access
model evaluation platform, for building reliable prognostic and
therapeutic strategies that incorporate molecular data
Present and Future Impact of Cytogenetics on Acute Myeloid Leukemialarriva
Cytogenetics is an advancement in which clinicians can look for specific genetic mutations of chromosomal DNA and use that information to determine patient prognosis and individualize therapy. In this presentation I cover what cytogenetics are, how they impact patient risk, what therapies to use based on risk, and how genetically targeted agents may be used in the future.
Detecting clinically actionable somatic structural aberrations from targeted ...Ronak Shah
Structural aberrations including deletions, insertions, inversions, tandem duplications, translocations, and more complex rearrangements constitute a frequent type of alteration in human tumors. Here, we sought to explore the potential to discover such events from targeted DNA sequence data in our CLIA-compliant molecular diagnostics laboratory. To detect somatic structural aberrations in individual tumors, we have developed an analytic framework in Perl & Python to detect these events in data generated by a hybridization capture-based, targeted sequencing clinical assay (MSK-IMPACT), which can reveal structural rearrangements as small as 500bp.
Robert Anders, MD, PhD, Julie R. Brahmer, MD, MSc, and Christopher D. Gocke, MD, prepared useful Practice Aids pertaining to immunotherapy and biomarker testing for this CME/MOC/CC activity titled "Keeping Up With Advances in Cancer Immunotherapy and Biomarker Testing: Implications for Pathologists at the Forefront of the Emerging Precision Immuno-Oncology Era." For the full presentation, monograph, complete CME/MOC/CC information, and to apply for credit, please visit us at http://bit.ly/2L7zlSy. CME/MOC/CC credit will be available until May 2, 2020.
Cardiotoxicity is unfortunately a common side effect of many modern chemotherapeutic agents. The mechanisms that underlie these detrimental effects on heart muscle, however, remain unclear. The Drug Toxicity Signature Generation Center at ISMMS aims to address this unresolved issue by providing a bridge between molecular changes in cells and the prediction of pathophysiological effects. I will discuss ongoing work in which we use next-generation sequencing to quantify changes in gene expression that occur in cardiac myocytes after they are treated with potentially toxic chemotherapeutic agents. I will focus in particular on the computational pipeline we are developing that integrates sophisticated sequence alignment, statistical and network analysis, and dynamical mathematical models to develop novel predictions about the mechanisms underlying drug-induced cardiotoxicity.
Jaehee Shim is a Ph.D candidate in the Biophysics and Systems Pharmacology Program at Icahn School of Medicine at Mount Sinai (ISMMS). As a part of her Ph.D. studies, she is building dynamical prediction models based on analysis of gene expression data generated by the Drug Toxicity Signature Generation Center at ISMMS. She received her B.S in Biochemistry from the University of Michigan-Dearborn. Prior to starting her Ph.D, Jaehee worked at the ISMMS Genomics Core with a team of senior scientists and gained experience in improving and troubleshooting RNA sequencing protocols using Next Generation Sequencing Platforms.
hMSH2 Gly322Asp (rs4987188) Single nucleotide polymorphism and the risk of br...Agriculture Journal IJOEAR
Aim: Breast cancer is the most common cancer in women both in the developed and less developed world. The reported study was designed to explore associations between hMSH2 - Gly322Asp (1032G>A, rs4987188) single nucleotide polymorphism (SNP) and the risk of breast carcinoma in the Polish women.
Material and methods: Blood samples were obtained from women with breast cancer (n=225), treated at the Department of Oncological Surgery and Breast Diseases, Polish Mother’s Memorial Hospital – Research Institute between the years 2005 and 2012. A control group included 220 cancer-free women. Genomic DNA was isolated and the SNP Gly322Asp of hMSH2 was determined by High-Resolution Melter method. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each genotype and allele.
Results: This study revealed that single nucleotide polymorphism Gly322Asp of hMSH2 is associated with both breast cancer risk and grading. Moreover, it can be linked with breast carcinoma tumor size and lymph node status. The Asp allele in patients may be a risk factor for breast carcinoma (OR 5.12; 95% CI 3.77 –6.97, p<.0001).
Conclusions: Gly322Asp single nucleotide polymorphism of hMSH2 may be a risk factor of breast cancer in the Polish women.
Build it and they will come: An R interface to the Leiden clustering algorithm with reticulate
Presentation at Bio"Pack"athon 2020 #1
Date: 25/02/2020
Venue: RIKEN Yokohama, Japan
Primary language: English
https://sites.google.com/view/biopackathon/biopackathon20201
Learning from and teaching in communities
コミュニティーで学び、そこで教えた事
Can we bring “Software Carpentry” to Japan? 「ソフトウィア・カーペントリー」を日本でやりませんか?
Presentation in English (with slides in English and Japanese)
#TokyoR 73th Meeting 2018-10-20
Tom Kelly (RIKEN IMS, Yokohama, Japan)
How learning, using, and teaching R has helped my career in the life sciences
#TokyoR 2018-7-15
Presented at Yahoo Japan 2.45pm
Tom Kelly, Postdoctoral Fellow (RIKEN IMS)
1. Bioinformatic Prioritisation of Synthetic Lethal Targets
for Drug Activity Against E-cadherin Deficient Cancers
S. Thomas Kelly, Parry J. Guilford, and Michael A. Black
Department of Biochemistry, University of Otago, Dunedin, New Zealand
Te Aho Matatū, Centre for Translational Cancer Research
INTRODUCTION
Expression of the tumour suppressor gene, E-cadherin (CDH1), is lost in a range of
different cancer types, through multiple mechanisms1
. Traditionally, tumour
suppressors have been unattractive drug targets, despite their importance in tumour
growth and development. More recently however, the concept of “synthetic lethality”
has provided a mechanism by which tumour cells exhibiting loss of a specific tumour
suppressor can be precisely targeted through an essential partner gene2
. A synthetic
lethal drug design approach to indirectly target CDH1 deficient cells could therefore
be used to develop effective chemopreventatives and treatments with fewer adverse
effects than existing anti-cancer regimes.
Experimental studies of synthetic lethality have been developed in cancer cell lines
and model organisms. However, high-throughput RNAi and drug screens are costly,
labour-intensive, and conducted in experimental models which may not reflect the
genetic background or variation of tumours in patients. We have developed a
bioinformatics methodology to both overcome some of the limitations of experimental
models, and to augment experimental data. Here we present an example relating to
breast cancers with low E-cadherin expression.
METHODOLOGY
Microarray and RNASeq gene expression data for breast and stomach cancers was
sourced from public databases: TCGA, GEO, ArrayExpress, and caArray3,4
. A statistical
methodology was then developed to predict synthetic lethal partners of a pre-specified
target gene. For ease of use by non-statisticians, this methodology was also placed in a
web-accessible framework using the R Shiny package.
RESULTS
The known synthetic lethal interaction between the BRCA genes and PARP1 was
predicted by our methodology. Predicted synthetic lethal partners of CDH1 are enriched
for chromatin remodelling, cytoskeleton, and cell signalling functions. As shown by
heatmap, significant CDH1 partners have important variation in CDH1 deficient
tumours. Low candidate target expression in suggests therapeutic resistance in basal or
ER negative tumours. High expression clustered the genes into 3 closely correlated
groups corresponding to distinct enriched biological pathways. Considering each group
separately provides biological insights and incentive to develop combination therapies.
Candidate Gene (e.g., SVIL)
Low Medium High
QueryGene
(e.g.,CDH1)
Low
Observed less than
expected
Observed more
than expected
Medium
High
A strategy for synthetic lethal detection using from3-quantile gene expression data
Post Prediction Analysis
Processed by TCGA Database
Raw .FASTQ
Sequence Files
Aligned .BAM
Sequence Files
Normalised by
TCGA
Exclude Genes
with Q3=0
Extract Files in
R and
Combine into
Data Matrix
Query SL
Gene
Chi-Sq
Test +
Direction
SL Table
looploop
Query all Genes for SL
Save Gene Files
Summary Plots
Function
Gene Set
Analysis
Most SL
Candidate
Gene Analysis
Pairwise SL
Interactome
Test
TCGA RNA-Seq
Transcriptome
Profiling
Gene/Exon
Quantification
Combine GAII
and Hi-Seq Data
Quantile
Normalise
Samples on
Log-Scale
Rounding
and
Truncate
Table
Correlation
Gene
Co-expression
matrix
L/M/H Matrix
TS_SL
FUTURE DIRECTIONS
Future directions for this project include replication of findings across datasets from
different sources and microarray platforms. This project is expanding to encompass RNA-
Seq datasets, and the comparison of synthetic lethal predictions across cancers and
tissue types. This procedure can be scaled up for testing multiple query genes in parallel
with high performance computing5
. Other research directions such as functional analysis
of gene sets and gene network analysis are being developed concurrently.
CONCLUSIONS
We have developed a bioinformatics tool which detects known and potentially novel
synthetic lethal interactions. Synthetic lethal interactions are detectable in a
heterogeneous tumour and may occur frequently in the human genome. Synthetic lethal
interactions could be exploited for anti-cancer therapy with the advantage of reduced
adverse effects and specific activity against loss of tumour supressor gene function.
E-cadherin mutations are an ideal case to develop synthetic lethal treatment against
sporadic and hereditary cancers in multiple tissues. The example of CDH1 synthetic
lethal partners demonstrates the value of integrating bioinformatics analysis to facilitate
drug design against tumour supressor mutations.
DISCUSSION
Compared with an experimental screen, a bioinformatics approach has the benefits of
reduced costs, with the potential for automation, scaling up, and replication of the same
gene across populations and cell types. Analysis of public genomic data accounts for real
tumour variation with predictions despite tumour heterogeniety and genomic instability.
Compared with a cell line or xenograft experimental model, we are limited by difficulties in
establishing validity of a novel method, lack of mechanism, or potential for testing drug
activity in the same system. This method may further miss useful therapeutic candidates
from variable genetic background and be limited by the population sampled.
Therefore we intend to apply this method which is integrated with laboratory screening
data to triage drug targets as part of an ongoing collaboration. This proof of concept
analysis with CDH1 synthetic lethal partners shows that we can detect potential synthetic
lethal interactions, even if they occur in only a subset of patients, with functional groups
of gene targets. This approach can increase the efficiency of experimental testing and
integrate into a pipeline to develop personalised medicine against tumour supressor
mutations. Clinical applications include prevention of hereditary cancers and treatment of
sporadic cancers.
1. Guilford, P.J., et al., E-cadherin germline mutations in familial gastric cancer.
Nature, 1998. 392: p. 402-5.
2. Kaelin, W.G., Jr., The concept of synthetic lethality in the context of anticancer
therapy. Nat Rev Cancer, 2005. 5: p. 689-98.
3. Soon, W.W., et al., Combined genomic and phenotype screening reveals secretory
factor SPINK1 as an invasion and survival factor associated with patient prognosis in
breast cancer. EMBO Mol Med, 2011. 3: p. 451-64.
4. Cancer Genome Atlas Research Network, Comprehensive molecular portraits of
human breast tumours. Nature, 2012. 490: p. 61-70.
5. Kelly, S.T., et al., Bioinformatic analysis of synthetic lethal genetic interactions in
breast cancer. Proceedings of eResearch NZ HPC Applications Workshop; 2014 Jun
30-Jul 2; Hamilton, NZ
Normal/Tumour/Metastasis
Ductal/Lobular
Stage
Estrogen Receptor
Progresterone Receptor
HER2 Status
Subtype (PAM50)
CDH1 levels
CDH1 Status
Cluster
Significance
Cluster
A workflow summary of the procedures involved in bioinformatic prediction of synthetic
lethality from a public database such as the cancer genome atlas .
WikiPathways Gene Set SL genes in Set Total Genes in Set p-value FDR p-value
GPCRs Class B Secretin-like (WP334) 8 24 0.00017 0.022
Eicosanoid Synthesis (WP167) 5 19 0.0091 .058
G Protein Signaling Pathways (WP35) 13 95 0.017 0.58
Endochronal Ossif cation (WP474) 10 66 0.018 0.58
Steroid Biosynthesis (WP496) 3 10 0.03 0.67
Arrhythmogenic right ventricular cadiomyopathy 10 74 0.036 0.67
ErbB signaling pathway (WP673) 8 55 0.04 0.67
Small Ligand GPCRs (WP247) 4 19 0.042 0.67
Nucleotide GPCRs (WP80) 3 12 0.049 0.67
AMK Signaling (WP1403) 9 68 0.051 0.67
Selenium Pathway (WP15) 8 60 0.062 0.73
Prostaglanding Synthesis and Regulation (WP93) 5 31 0.066 0.73
WikiPathways Gene Set SL genes in Set Total Genes in Set p-value FDR p-value
Adiposgenesis (WP236) 35 133 0.00000046 0.00067
Cytochrome P450 (WP43) 18 61 0.00022 0.016
Metapathway biotransformation (WP702) 36 176 0.00094 0.046
Complement and Coagulation Cascades (WP558) 13 50 0.0055 0.2
Mitochondrial LC-Fatty Acid Beta-Oxidation (WP368) 6 16 0.0087 0.23
Prostaglandin Synthesis and Regulation (WP98) 9 31 0.0094 0.23
19 91 0.012 0.25
Ovarian Infertility Genes (WP34) 8 31 0.028 0.5
Focal Adhesion (WP306) 32 191 0.035 0.5
Monoamine GPCRs (WP58) 8 33 0.04 0.5
Calcium Regulation in the Cardiac Cell (WP536) 26 151 0.04 0.5
Vitamin A and carotenoid metabolism (WP716) 9 39 0.041 0.5
WikiPathways Gene Set SL genes in Set Total Genes in Set p-value FDR p-value
41 191 0.000079 0.011
TFG Beta Signaling Pathway (WP560) 15 54 0.0011 0.064
28 133 0.0015 0.064
29 141 0.0018 0.064
24 117 0.0046 0.093
Arrhythmogenic right ventricular cadiomyopathy 17 74 0.005 0.093
22 105 0.005 0.093
11 40 0.0055 0.093
10 35 0.0059 0.093
11 42 0.0081 0.11
30 163 0.0086 0.11
15 66 0.009 0.11
Gene Set Analysis for WikiPathways (GeneSetDB) of Subgroups of CDH1 SL partners
Neural Crest Diffentiation (WP2064)
Focal Adhesion (WP306)
EGF/EGFR Signaling Pathway (WP437)
Integrin-mediatied cell adhesion (WP185)
IL-5 signaling pathway (WP127)
Signaling of Hepatocyte Growth Factor Receptor (WP313)
IL-2 signaling pathway (WP49)
MAPK signaling pathway (WP382)
Endochronal Ossif cation (WP474)
Adipogenesis (WP236)
TGF beta Signaling Pathway (WP366)
Download Sample
Files
ExpressionProfile
Sample
Significance
Gene
Gene
A gene correlation heatmap of FDR Significant SL partners of CDH1 in CDH1 low samples
A gene expression heatmap of FDR Significant SL partners of CDH1 in CDH1 low samples
ACKNOWLEDGEMENTS
I thank my supervisors, Mik and Parry, for their incredible support throughout this
project. The University of Otago and the Postgraduate Tassell Scholarship in Cancer
Research for course support and funding. The New Zealand eScience Infrastrcture
(NeSI) support team gave helpful advice on scaling up the computational
methodology. Thanks to James Boocock, Murray Cadzow, Augustine Chen, and the
Cancer Genetics Laboratory for assistance with R and biological relevance.
Gene Expression for FDR significant partners of CDH1 in TCGA Breast RNASeq data
Color Key
and Histogram
Color Key
and Histogram
Color Key
and Histogram
Gene Correlation for FDR significant partners of CDH1 in TCGA Breast RNASeq data