FUNCTIONAL SIGNIFICANCE AND EXPRESSION ANALYSIS OF N-ACETYL GALACTOSAMINYL TRANSFERASE-1 IN BREAST CANCER

Ph.DDOCTOR OF PHILOSOPH

The heparan sulfate proteoglycan syndecan-1 regulates colon cancer stem cell function via a focal adhesion kinase—Wnt signaling axis

In colon cancer, downregulation of the transmembrane heparan sulfate proteoglycan syndecan‐1 (Sdc‐1) is associated with increased invasiveness, metastasis, and dedifferentiation. As Sdc‐1 modulates signaling pathways relevant to stem cell function, we tested the hypothesis that it may regulate a tumor‐initiating cell phenotype. Sdc‐1 small‐interfering RNA knockdown in the human colon cancer cell lines Caco2 and HT‐29 resulted in an increased side population (SP), enhanced aldehyde dehydrogenase 1 activity, and higher expression of CD133, LGR5, EPCAM, NANOG, SRY (sex‐determining region Y)‐box 2, KLF2, and TCF4/TCF7L2. Sdc‐1 knockdown enhanced sphere formation, cell viability, Matrigel invasiveness, and epithelial‐to‐mesenchymal transition‐related gene expression. Sdc‐1‐depleted HT‐29 xenograft growth was increased compared to controls. Decreased Sdc‐1 expression was associated with an increased activation of β1‐integrins, focal adhesion kinase (FAK), and wingless‐type (Wnt) signaling. Pharmacological FAK and Wnt inhibition blocked the enhanced stem cell phenotype and invasive growth. Sequential flow cytometric SP enrichment substantially enhanced the stem cell phenotype of Sdc‐1‐depleted cells, which showed increased resistance to doxorubicin chemotherapy and irradiation. In conclusion, Sdc‐1 depletion cooperatively enhances activation of integrins and FAK, which then generates signals for increased invasiveness and cancer stem cell properties. Our findings may provide a novel concept to target a stemness‐associated signaling axis as a therapeutic strategy to reduce metastatic spread and cancer recurrence.DatabasesThe GEO accession number of the Affymetrix transcriptomic screening is GSE58751

PARP Inhibitors in Breast and Ovarian Cancer

Poly (ADP-ribose) polymerase (PARP) inhibitors are one of the most successful examples of clinical translation of targeted therapies in medical oncology, and this has been demonstrated by their effective management of BRCA1/BRCA2 mutant cancers, most notably in breast and ovarian cancers. PARP inhibitors target DNA repair pathways that BRCA1/2-mutant tumours are dependent upon. Inhibition of the key components of these pathways leads to DNA damage triggering subsequent critical levels of genomic instability, mitotic catastrophe and cell death. This ultimately results in a synthetic lethal relationship between BRCA1/2 and PARP, which underpins the effectiveness of PARP inhibitors. Despite the early and dramatic response seen with PARP inhibitors, patients receiving them often develop treatment resistance. To date, data from both clinical and preclinical studies have highlighted multiple resistance mechanisms to PARP inhibitors, and only by understanding these mechanisms are we able to overcome the challenges. The focus of this review is to summarise the underlying mechanisms underpinning treatment resistance to PARP inhibitors and to aid both clinicians and scientists to develop better clinically applicable assays to better select patients who would derive the greatest benefit as well as develop new novel/combination treatment strategies to overcome these mechanisms of resistance. With a better understanding of PARP inhibitor resistance mechanisms, we would not only be able to identify a subset of patients who are unlikely to benefit from therapy but also to sequence our treatment paradigm to avoid and overcome these resistance mechanisms

Analysis of Genetic Variation in CYP450 Genes for Clinical Implementation

<div><p>Background</p><p>Genetic determinants of drug response remain stable throughout life and offer great promise to patient-tailored drug therapy. The adoption of pharmacogenetic (PGx) testing in patient care requires accurate, cost effective and rapid genotyping with clear guidance on the use of the results. Hence, we evaluated a 32 SNPs panel for implementing PGx testing in clinical laboratories.</p><p>Methods</p><p>We designed a 32-SNP panel for PGx testing in clinical laboratories. The variants were selected using the clinical annotations of the Pharmacogenomics Knowledgebase (PharmGKB) and include polymorphisms of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 genes. The CYP2D6 gene allele quantification was determined simultaneously with TaqMan copy number assays targeting intron 2 and exon 9 regions. The genotyping results showed high call rate accuracy according to concordance with genotypes identified by independent analyses on Sequenome massarray and droplet digital PCR. Furthermore, 506 genomic samples across three major ethnic groups of Singapore (Malay, Indian and Chinese) were analysed on our workflow.</p><p>Results</p><p>We found that 98% of our study subjects carry one or more CPIC actionable variants. The major alleles detected include CYP2C9*3, CYP2C19*2, CYP2D6*10, CYP2D6*36, CYP2D6*41, CYP3A5*3 and VKORC1*2. These translate into a high percentage of intermediate (IM) and poor metabolizer (PM) phenotypes for these genes in our population.</p><p>Conclusion</p><p>Genotyping may be useful to identify patients who are prone to drug toxicity with standard doses of drug therapy in our population. The simplicity and robustness of this PGx panel is highly suitable for use in a clinical laboratory.</p></div

Allele frequencies in Malay, Chinese and Indian subjects.

<p>Allele frequencies in Malay, Chinese and Indian subjects.</p

Loci and alleles detected by the assays.

<p>Loci and alleles detected by the assays.</p

Diplotype frequencies and functional classification of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 in the Singapore population (n = 506).

<p>Diplotype frequencies and functional classification of CYP2C9, CYP2C19, CYP2D6, CYP3A5 and VKORC1 in the Singapore population (n = 506).</p

Frequencies of CYP2D6 copy numbers in the Singapore population tested.

<p>Frequencies of CYP2D6 copy numbers in the Singapore population tested.</p

Frequency of metabolizer groups in 3 major ethnic groups of Singapore population.

<p>(A) CYP2C9 (B) CYP2C19 and (C) CYP2D6.</p

Haplotype calls of 10 HapMap samples used for assay validation.

<p>Haplotype calls of 10 HapMap samples used for assay validation.</p