Gene expression profiles have identified five major molecular breast cancer subtypes (Luminal A, Luminal B, Basal-like, HER2+/estrogen receptor− , and Normal Breast-like) that show significant differences in survival. The cost and complexity of gene expression technology has impeded its clinical implementation. By comparison, immunohistochemistry is an economical technique applicable to the standard formalin-fixed, paraffin-embedded material commonly used in hospital labs, and has the advantage of simultaneously interpretation with histomorphology. In this thesis, I hypothesize that a surrogate panel of immunohistochemical biomarkers can be developed to discriminate the breast cancer biological subtypes. The main study cohort consists of over 4000 primary invasive breast tumors, assembled into tissue microarrays. These patients were referred to the British Columbia Cancer Agency between 1986-1992 and have staging, pathology, treatment and follow-up information. In summary, our results demonstrate that (1) the rabbit monoclonal antibody, SP1, is an improved standard for immunohistochemiscal estrogen receptor assessment in breast cancer; (2) the transcription factor, GATA-3, is almost exclusively expressed among estrogen receptor positive tumors but does not seem to predict for tamoxifen response among estrogen receptor positive patients; (3) the proliferation marker, Ki-67, together with HER2 can segregate Luminal A from Luminal B subtypes, which carry distinct risks for breast cancer relapse and death; and (4) the inclusion of the basal markers EGFR and ck5/6 to “triple negative” breast cancers provides a more specific definition of basal-like breast cancer that better predicts patient survival. These results consistently demonstrate that an immunopanel of six biomarkers (estrogen receptor, progesterone receptor, HER2, Ki-67, epidermal growth factor receptor and cytokeratin 5/6) can be readily applied to standard pathology specimens to subtype breast cancer samples based on their underlying molecular biology. These findings have been considered sufficient to justify application of this panel onto NCIC (MA5, MA12) and CALGB (9341 and 9741) clinical trials specimens. This followup work which is underway and will determine if the six marker immunopanel can guide decisions about which patients need aggressive systemic drug treatment, and thereby ensure patients get the most effective, individualized adjuvant systemic therapy for their breast tumor.

Gene expression profiles have identified five major molecular breast cancer subtypes (Luminal A, Luminal B, Basal-like, HER2+/estrogen receptor− , and Normal Breast-like) that show significant differences in survival. The cost and complexity of gene expression technology has impeded its clinical implementation. By comparison, immunohistochemistry is an economical technique applicable to the standard formalin-fixed, paraffin-embedded material commonly used in hospital labs, and has the advantage of simultaneously interpretation with histomorphology. In this thesis, I hypothesize that a surrogate panel of immunohistochemical biomarkers can be developed to discriminate the breast cancer biological subtypes. The main study cohort consists of over 4000 primary invasive breast tumors, assembled into tissue microarrays. These patients were referred to the British Columbia Cancer Agency between 1986-1992 and have staging, pathology, treatment and follow-up information. In summary, our results demonstrate that (1) the rabbit monoclonal antibody, SP1, is an improved standard for immunohistochemiscal estrogen receptor assessment in breast cancer; (2) the transcription factor, GATA-3, is almost exclusively expressed among estrogen receptor positive tumors but does not seem to predict for tamoxifen response among estrogen receptor positive patients; (3) the proliferation marker, Ki-67, together with HER2 can segregate Luminal A from Luminal B subtypes, which carry distinct risks for breast cancer relapse and death; and (4) the inclusion of the basal markers EGFR and ck5/6 to “triple negative” breast cancers provides a more specific definition of basal-like breast cancer that better predicts patient survival. These results consistently demonstrate that an immunopanel of six biomarkers (estrogen receptor, progesterone receptor, HER2, Ki-67, epidermal growth factor receptor and cytokeratin 5/6) can be readily applied to standard pathology specimens to subtype breast cancer samples based on their underlying molecular biology. These findings have been considered sufficient to justify application of this panel onto NCIC (MA5, MA12) and CALGB (9341 and 9741) clinical trials specimens. This followup work which is underway and will determine if the six marker immunopanel can guide decisions about which patients need aggressive systemic drug treatment, and thereby ensure patients get the most effective, individualized adjuvant systemic therapy for their breast tumor.

Gene expression profiles have identified five major molecular breast cancer subtypes (Luminal A, Luminal B, Basal-like, HER2+/estrogen receptor− , and Normal Breast-like) that show significant differences in survival. The cost and complexity of gene expression technology has impeded its clinical implementation. By comparison, immunohistochemistry is an economical technique applicable to the standard formalin-fixed, paraffin-embedded material commonly used in hospital labs, and has the advantage of simultaneously interpretation with histomorphology. In this thesis, I hypothesize that a surrogate panel of immunohistochemical biomarkers can be developed to discriminate the breast cancer biological subtypes. The main study cohort consists of over 4000 primary invasive breast tumors, assembled into tissue microarrays. These patients were referred to the British Columbia Cancer Agency between 1986-1992 and have staging, pathology, treatment and follow-up information. In summary, our results demonstrate that (1) the rabbit monoclonal antibody, SP1, is an improved standard for immunohistochemiscal estrogen receptor assessment in breast cancer; (2) the transcription factor, GATA-3, is almost exclusively expressed among estrogen receptor positive tumors but does not seem to predict for tamoxifen response among estrogen receptor positive patients; (3) the proliferation marker, Ki-67, together with HER2 can segregate Luminal A from Luminal B subtypes, which carry distinct risks for breast cancer relapse and death; and (4) the inclusion of the basal markers EGFR and ck5/6 to “triple negative” breast cancers provides a more specific definition of basal-like breast cancer that better predicts patient survival. These results consistently demonstrate that an immunopanel of six biomarkers (estrogen receptor, progesterone receptor, HER2, Ki-67, epidermal growth factor receptor and cytokeratin 5/6) can be readily applied to standard pathology specimens to subtype breast cancer samples based on their underlying molecular biology. These findings have been considered sufficient to justify application of this panel onto NCIC (MA5, MA12) and CALGB (9341 and 9741) clinical trials specimens. This followup work which is underway and will determine if the six marker immunopanel can guide decisions about which patients need aggressive systemic drug treatment, and thereby ensure patients get the most effective, individualized adjuvant systemic therapy for their breast tumor. / Medicine, Faculty of / Pathology and Laboratory Medicine, Department of / Graduate

Each cancer is unique: it reflects the underlying genetic make-up of the patient and the stochastic mutational processes that occur within the tumour. This uniqueness suggests that each patient should receive a personalized type of therapy. Current predictions of a cancer patient’s outcome or prognosis are highly inaccurate. To aid in the prediction of patient prognosis based on highthroughput molecular datasets I have worked to optimize each step of the experimental pipeline: platform annotation, experimental design, consideration of tumour heterogeneity, data pre-processing and statistical analysis, and feature selection. First, a 12k CpG Island clone library was sequenced and annotated using a BLAT analysis. Second, microarrays built using this library were used in a fully-saturated study to evaluate the importance of ChIP-chip experimental design parameters. Third, intra-tumour heterogeneity was shown to influence specific pathways in a large fraction of genes. Fourth, a systematic empirical evaluation of 19,446 combinations of microarray analysis methods identified key steps of the analysis process and provided insight into their optimization. Finally, the combination of a two-stage experimental design and a novel semi-supervised algorithm yielded a six-gene, mRNA abundance-based classifier that could divide non-small cell lung cancer patients into two groups with significantly different outcomes in four independent validation cohorts. Further, a permutation study showed that millions of six-gene markers exist, but that ours ranked amongst the top 99.98% of all six-gene markers. The knowledge gained from these studies provides a key foundation for the development of personalized therapies for cancer patients.

Each cancer is unique: it reflects the underlying genetic make-up of the patient and the stochastic mutational processes that occur within the tumour. This uniqueness suggests that each patient should receive a personalized type of therapy. Current predictions of a cancer patient’s outcome or prognosis are highly inaccurate. To aid in the prediction of patient prognosis based on highthroughput molecular datasets I have worked to optimize each step of the experimental pipeline: platform annotation, experimental design, consideration of tumour heterogeneity, data pre-processing and statistical analysis, and feature selection. First, a 12k CpG Island clone library was sequenced and annotated using a BLAT analysis. Second, microarrays built using this library were used in a fully-saturated study to evaluate the importance of ChIP-chip experimental design parameters. Third, intra-tumour heterogeneity was shown to influence specific pathways in a large fraction of genes. Fourth, a systematic empirical evaluation of 19,446 combinations of microarray analysis methods identified key steps of the analysis process and provided insight into their optimization. Finally, the combination of a two-stage experimental design and a novel semi-supervised algorithm yielded a six-gene, mRNA abundance-based classifier that could divide non-small cell lung cancer patients into two groups with significantly different outcomes in four independent validation cohorts. Further, a permutation study showed that millions of six-gene markers exist, but that ours ranked amongst the top 99.98% of all six-gene markers. The knowledge gained from these studies provides a key foundation for the development of personalized therapies for cancer patients.

Colorectal cancer (CRC) is one of the most common causes of death from malignant disease. Nevertheless, no ideal screening method exists and there is a lack of prognostic and predictive factors to support clinical decisions and to aid the development of a more individualized treatment for patients with CRC. The aim of this thesis was to investigate early detection, prognostic and predictive factors of CRC. In the first paper, a novel method to collect cells for DNA quantification from the rectal mucosa was investigated. The sensitivity and specificity of this test to detect CRC or any pathology in colon and rectum were ultimately too low to be acceptable. In the second paper, the prognostic value of growth differentiation factor 15 (GDF 15) was evaluated in patients curatively operated for colorectal cancer. GDF 15 expression was demonstrated to be associated with a negative prognosis in patients with stages I-III and III disease. In the third paper, the prognostic value of BRAF, PIK3CA KRAS and MSI was evaluated in a cohort of patients with CRC stratified by disease and recurrence. The results indicated that patients with CRC stage III without recurrence have a higher frequency of BRAF mutation compared to stage III patients with recurrence. In the fourth paper, histopathological predictors of pathologic complete response (pCR) as well as the association between pre-treatment carcinoembryonic antigen (CEA) levels and pCR in non-smoking and smoking patients receiving preoperative chemo-radiotherapy for rectal cancer were evaluated. Only in non-smokers was a low CEA level significantly associated with pCR, suggesting that the predictive value of CEA for pCR in rectal cancer in smokers can be limited. In sum, this research has investigated a new method for CRC detection and further evaluated the clinical use of prognostic and predictive markers in CRC.

Glioblastoma is the most common and lethal malignant brain tumor with a survival rate of 14.6 months and a tumor recurrence rate of ninety percent. Two key causes for glioblastomas grim outcome derive from the lack of applicable prognostic markers and effective therapeutic targets. By employing a loss of function RNAi screen in glioblastoma cells we found a list of 20 kinases that can be considered glioblastoma survival kinases. These survival kinases which we term as survival kinase genes, (SKGs) were investigated to find prognostic markers as well as therapeutic targets for glioblastoma. Analyzing these survival kinases in The Cancer Genome Atlas patient database, we found that CDCP1, CDKL5, CSNK1𝜀, IRAK3, LATS2, PRKAA1, STK3, TBRG4, and ULK4 genes could be used as prognostic markers for glioblastoma with or without temozolomide chemotherapeutic treatment as a covariate. For the first time, we found that patients with increased levels of NEK9 and PIK3CB mRNA expression had a higher probability of recurrent tumors. We also discovered that expression of CDCP1, IGF2R, IRAK3, LATS2, PIK3CB, ULK4, or VRK1 in primary glioblastoma tumors was associated with tumor recurrence prognosis. To note, of these recurrent prognostic candidates, PIK3CB expression in recurrent tumor tissue had much higher expression compared to primary tissue. Further investigation in the PI3K pathway showed a strong correlation with recurrence rate, days to recurrence and survival emphasizing the role of PIK3CB in tumor recurrence in glioblastoma. In efforts to find effective therapeutic targets for glioblastoma we used SKGs as potential candidates. We chose the serine/threonine kinase, Casein Kinase 1 Epsilon (CSNK1𝜀) as a target for glioblastoma because multiple shRNAs targeted this gene in our loss of function screen and multiple commercially available inhibitors of this gene are available. Casein kinase 1 epsilon protein and mRNA expression were investigated using computational tools. It was revealed that CSNK1𝜀 expression has higher expression in glioblastoma than normal tissue. To further examine this gene we knocked down (KD) or inhibited CSNK1𝜀 in glioblastoma cells lines and noticed a significant increase in cell death without any significant effect on normal cell lines. KD and inhibition of CSNK1𝜀 in cancer stem cells, a culprit of tumor recurrence, also revealed limited self-renewal and proliferation in cancer stem cells and a significant decrease in cell survival without affecting normal stem cells. Further analysis of downstream effects of CSNK1𝜀 knockdown and inhibition indicate a significant increase in the protein expression of β-catenin (CTNNB1). We found that CSNK1𝜀 KD activated β-catenin, which increased GBM cell death, but can be rescued using CTNNB1 shRNA. Our survival kinase screen, computational analyses, patient database analyses and experimental methods contributed to the discovery of novel prognostic markers and therapeutic targets for glioblastoma. / Ph. D.

Thesis (PhD)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Breast cancer is a heterogeneous disease characterised by marked inter-individual variability in presentation, prognosis and clinical outcome. The recognition that morphological assessment has limited utility in stratifying patients into prognostic subgroups led to clinico-pathological classification of tumour biology, based on receptor expression using immunohistochemical (IHC) techniques. This standard is currently complemented by the development of gene expression profiling methodology that led to the identification of intrinsic molecular subtypes, reflecting tumour genetics as the true driver of biological activity in breast cancer. The study was based on the hypothesis that molecular classification of breast carcinomas integrated with established clinico-pathological risk factors will improve current diagnostic and risk management algorithms used in clinical decision-making. A pathology-supported genetic testing strategy was used to evaluate microarray-based gene profiling against diagnostic pathology techniques as the current standard. Clinico-pathological factors including age, number of positive axillary nodes, tumour size, grade, proliferation index and hormone receptor status was documented for 141 breast cancer patients (143 tumours) referred for microarray-based gene expression profiling between 2007 and 2014. Subsets of patients were selected from the database based on the inclusion criteria defined for three phases in which the study was performed, in order to determine 1) the percentage of patients stratified as having a low as opposed to high risk of distant recurrence using the 70-gene MammaPrint profile within the inclusion criteria, 2) correlation of HER2 status as determined by IHC and fluorescence in situ hybridisation (FISH) with microarray-based mRNA readout (TargetPrint), and 3) the relationship between hormone receptor determination as reported by standard IHC and molecular subtyping using the 80-gene BluePrint profile. Similar distribution patterns for MammaPrint low- and high-risk profiles were obtained irrespective of whether fresh tumour biopsies or formalin-fixed paraffin embedded (FFPE) tissue was used. During the first phase of the study, 60% of the 106 tumour specimens analysed with MammaPrint were classified as low-risk and 40% as high-risk using a newly-developed MammaPrint pre-screen algorithm (MPA) aimed at cost-saving. In the second phase of the study, performed in 102 breast tumours, discordant or equivocal HER2 results were found in four cases. Reflex testing confirmed the TargetPrint results in discordant cases, achieving 100% concordance regardless of whether fresh tumour or FFPE tissue was used for microarray analysis. For the third phase of the study 74 HER2-negative tumour samples were selected for comparative analysis. Statistically significant positive correlations were found between protein expression (IHC score) and mRNA (TargetPrint) levels for estrogen receptor (ER) (R=0.53, p<0.0001) as well as progesterone receptor (PR) (R=0.62, p<0.0001), while combined ER/PR tumour status was reported concordantly in 82.4% of these tumours. BluePrint was essential for interpretation of these results used in treatment decision-making. The MPA developed in South Africa in 2009 was validated in this study as an appropriate strategy to prevent chemotherapy overtreatment in patients with early-stage breast cancer. The use of microarray-based analysis proved to be a reliable ancillary method of assessing HER2 status in breast cancer patients. Risk reclassification based on the TargetPrint results helped to avoid unnecessary high treatment costs in false-positive cases, in addition to providing potentially life-saving treatment to those for whom it was indicated. While neither IHC nor TargetPrint estimation of intrinsic subtype correlated independently with the molecular subtype as indicated by BluePrint profiling, the ability to distinguish between basal-like and luminal tumours was enhanced when the combined protein and mRNA values was considered. Genomic profiling provided information over and above that obtained from routine clinico-pathological assessments. This finding supports the relevance of a pathology-supported genetic testing approach to breast cancer management, whereby advanced genomic testing is combined with existing clinico-pathological risk stratification methods for improved patient management. / AFRIKAANSE OPSOMMING: Borskanker is „n heterogene siekte wat gekenmerk word deur merkbare inter-individuele variasie in kliniese beeld, prognose en uitkoms. Die beperkings van morfologiese klassifikasie vir identifikasie van prognostiese subgroepe het gelei tot klinies-patologiese tumor karakterisering op grond van reseptor uitdrukking deur gebruik van immunohistochemiese (IHC) toetse. Hierdie standaard word tans gekomplementeer deur ontwikkeling van geenuitdrukking tegnologie wat gelei het tot die identifikasie van intrinsieke molekulêre subtipes, wat die tumor genetika reflekteer as die ware drywer van biologiese aktiwiteit in borskanker. Die huidige studie is gebaseer op die hipotese dat integrasie van die molekulêre klassifikasie van borskanker met konvensionele risiko klassifikasie skemas huidige diagnostiese en behandelings algoritmes kan verbeter vir kliniese besluitneming. „n Patologie-gesteunde strategie is gebruik om mikroplaat-gebaseerde geen profilering te evalueer teen standaard patologie diagnotiese tegnieke. Kliniese-patologiese faktore insluitend ouderdom, aantal positiewe aksillêre limfnodes, tumor grootte, gradering, proliferasie indeks en hormoon reseptor status is gedokumenteer in 141 borskanker pasiente (143 tumore) wat verwys is vir mikroplaat-gebaseerde geenuitdrukking profilering tussen 2007 en 2014. Pasiënt subgroepe is geselekteer uit die databasis volgens die insluitingskriteria soos gedefiniëer in die drie fases waarvolgens hierdie studie uitgevoer is, om vas te stel 1) watter proporsie pasiënte geklassifiseer word as lae- of hoë-risiko vir latere herhaling van die borskanker deur gebruik van die 70-geen MammaPrint profile binne die insluitingskriteria, 2) hoe korreleer HER2 status soos vasgestel deur IHC en fluoreserende in situ hybridisasie (FISH) toetsing met mikroplaat-gebaseerde RNA lesings (TargetPrint), en 3) wat die verwantskap is tussen hormoon reseptor status soos deur standaard IHC gerapporteer en molekulëre klassifikasie volgens die 80-geen BluePrint profiel. Soortgelyke verdelingspatrone vir MammaPrint lae- teenoor hoe-risiko profiele is waargeneem ongeag of vars tumor biopsies of formalien-gefikseerde paraffin bevattende weefsel gebruik is. Tydens die eerste fase van die studie is 60% van die 106 tumore as lae-risiko en 40% as hoë-risiko geklassifiseer met toepassing van die nuwe MammaPrint Presifting Algoritme (MPA) wat ontwikkel is met die doel op kostebesparing. In die tweede fase van die studie waar 102 tumore ingesluit is, het die resultate van vier gevalle verskil van mekaar of was onbepaald ten opsigte van HER2 status. Refleks herevaluering het die TargetPrint resultate bevestig in alle nie-ooreenstemmende gevalle, en 100% ooreenstemming is bereik ongeag of vars tumor biopsies of formalien-gefikseerde paraffin bevattende weefsel gebruik is vir mikroplaat analise. In die derde fase van die studie is 74 HER2-negative tumore selekteer vir vergelykende analise. Statisties beduidende positiewe korrelasies is waargeneem tussen proteïen uitdrukking (IHC) en mRNA (TargetPrint) vlakke vir die estrogeen reseptor (ER) (R=0.53, p<0.0001) sowel as progesteroon reseptor (PR) (R=0.62, p<0.0001), terwyl gekombineerde ER/PR reseptor status ooreenstemming getoon het in 82.4% tumore. BluePrint was noodsaaklik vir die korrekte interpretasie van die resultate wat gebruik is in kliniese besluitneming vir behandeling van pasiënte. The MPA wat in Suid Africa ontwikkel is in 2009, is gedurende hierdie studie bevestig as n toepaslike strategie om onnodige handeling met chemoterapie te voorkom in pasiënte met vroeë stadium borskanker. Die gebruik van mikroplaat-gebaseerde analise is aangetoon as „n betroubare aanvullende metode om HER2 status te evalueer. Risiko herklassifikasie gebaseer op TargetPrint resultate het onnodige hoë behandelingskoste in vals-positiewe gevalle vermy, sowel as om die verskaffing van potensieël lewensreddende behandeling vir die toepaslike pasiënte te verseker. Genomiese profilering het inligting addisioneel tot dit wat met roetine klinies-patologies metodes verkry kan word verskaf. Hierdie bevinding ondersteun die relevansie van „n patologie-gesteunde genetiese toets benadering tot hantering van borskanker, waardeur genomiese toetsing gekombineer word met bestaande klinies-patologiese risiko stratifisering metodes om pasiënt behandeling te verbeter.

A neoplasia mamária é a doença mais entre as neoplasias em cadelas. As características clínicas dos tumores mamários caninos e sua relação com prognóstico foram discutidos, incluindo idade, raça, estagiamento clínico, diagnóstico histopatológico, hormônios e proliferação celular. Fatores clínicos prognósticos incluindo diâmetro do tumor e comprometimento linfonodal são discutidos em relação a graduação histopatológica e expressão de OCT4 (marcador para célula tronco tumoral). Avaliação imunohistoquímica dos marcadores (RE, RP, Ki-67 e OCT4) de neoplasias mamárias foi descritas. Foi observada marcação positiva para o OCT4, porém não se observou associação com fatores prognósticos clínicos. Assim como a marcação de RE, PR e Ki-67 foram observados. Houve uma forte associação entre graduação histopatológica de malignidade e tipo histológico. / Mammary neoplasms are the most common neoplasm in female dogs. The clinical features of canine mammary gland tumors and their relation to prognosis were discussed, including age, breed, staging, histopathological diagnosis, hormones, cell proliferation. Additional clinical prognostic factors including tumor size, and lymph node status are discussed in relation to graduation histopathological and OCT4 expression (cancer stem cell marker). Immunohistochemical evaluation of the markers (ER, PR, KI-67, OCT4) of the neoplastic canine mammary gland is described. We observed positive staining for OCT4, but was not associated with clinical prognostic factors. And the marking of ER, PR and Ki-67 was observed. There was a strong association between histopathological grade and histological type of malignancy.

A neoplasia mamária é a doença mais entre as neoplasias em cadelas. As características clínicas dos tumores mamários caninos e sua relação com prognóstico foram discutidos, incluindo idade, raça, estagiamento clínico, diagnóstico histopatológico, hormônios e proliferação celular. Fatores clínicos prognósticos incluindo diâmetro do tumor e comprometimento linfonodal são discutidos em relação a graduação histopatológica e expressão de OCT4 (marcador para célula tronco tumoral). Avaliação imunohistoquímica dos marcadores (RE, RP, Ki-67 e OCT4) de neoplasias mamárias foi descritas. Foi observada marcação positiva para o OCT4, porém não se observou associação com fatores prognósticos clínicos. Assim como a marcação de RE, PR e Ki-67 foram observados. Houve uma forte associação entre graduação histopatológica de malignidade e tipo histológico. / Mammary neoplasms are the most common neoplasm in female dogs. The clinical features of canine mammary gland tumors and their relation to prognosis were discussed, including age, breed, staging, histopathological diagnosis, hormones, cell proliferation. Additional clinical prognostic factors including tumor size, and lymph node status are discussed in relation to graduation histopathological and OCT4 expression (cancer stem cell marker). Immunohistochemical evaluation of the markers (ER, PR, KI-67, OCT4) of the neoplastic canine mammary gland is described. We observed positive staining for OCT4, but was not associated with clinical prognostic factors. And the marking of ER, PR and Ki-67 was observed. There was a strong association between histopathological grade and histological type of malignancy.