Prognostic biomarker identification and classification of colorectal cancer patients: a dual gene-based and sample-based approach
| buir.advisor | Güre, Ali Osmay | |
| dc.contributor.author | Naeemaee, Ronak | |
| dc.date.accessioned | 2023-09-11T08:37:47Z | |
| dc.date.available | 2023-09-11T08:37:47Z | |
| dc.date.copyright | 2023-08 | |
| dc.date.issued | 2023-08 | |
| dc.date.submitted | 2023-09-08 | |
| dc.description | Cataloged from PDF version of article. | |
| dc.description | Thesis (Master's): Bilkent University, Department of Molecular Biology and Genetics, İhsan Doğramacı Bilkent University, 2023. | |
| dc.description | Includes bibliographical references (leaves 72-77). | |
| dc.description.abstract | Colorectal cancer (CRC) is one of the most heterogeneous cancer types, with high mortality rates making it the one of the deadliest cancer among men and women. The heterogeneity of CRC comes from the numerous clinicopathological characteristics of these tumors, including; KRAS/BRAF mutation, Microsatellite Instability (MSI), and stage. Another essential factor recently emphasized is the tumor location (proximal or distal). Consequently, many studies have focused on finding prognostic biomarkers for CRC patients to increase the efficiency of their treatment plans. However, despite the attempts, these biomarkers fail in clinical transition as they lack robustness and consistent results in their validation studies. Moreover, understanding the mechanism behind CRC progression can significantly help the personalization of treatments. Recently, the cancer neuroscience field has been focusing on elucidating neuropeptides' role in cancer and CRC as they have been proven to be involved in cancer progression. Accordingly, the thesis was divided into two approaches. The first approach was to further examine the role of neuropeptides by finding a subset of neuropeptides for the classification of the CRC samples and following functional analysis to understand the mechanism of their involvement. Moreover, the second approach attempted the determination of robust prognostic biomarkers in a specific sample group (Proximal, Stages 2 and 3) while controlling for the inconsistencies. In the first approach, a subset of 9 neuropeptide genes was found through Principle Component Analysis (PCA) with the ability to stratify the CRC samples into high and low expression groups. Functional analyses of these groups identified an association between the up-regulation of these neuropeptides and Hedgehog's (HHG) signaling pathway, and these activities are hypothesized to be primarily specific to the stroma of the tumor. Up-regulation of these neuropeptides was also linked with other pathways involved in cancer progression, such as; EMT, angiogenesis, and TGFβ activities. The second approach utilized a new methodology pipeline that aimed to ensure the selection of genes with no discrepancies among their probesets and across different technologies. Following the pipeline, 3 genes were identified, associated with favorable and non-favorable prognoses for Proximal, Stage 2, and 3 samples. However, although a very stringent methodology was used and various clinicopathological parameters such as the stage and location were considered, the prognostic associations observed were not as consistent, indicating the importance of the sample's molecular characteristics. This study also pointed out potential implications of neuropeptides in CRC progression and development. More elaborative studies are required for the clarification of the interactions of neuropeptides with the HHG signaling pathway. Furthermore, the identified prognostic biomarkers need to be validated through comprehensive validation studies in their associating subgroups of samples, as they are robust biomarkers with the potential to be used in clinics. | |
| dc.description.provenance | Made available in DSpace on 2023-09-11T08:37:47Z (GMT). No. of bitstreams: 1 B162499.pdf: 11981715 bytes, checksum: c886bc15cffc0b5cdf2bc924294fcfac (MD5) Previous issue date: 2023-08 | en |
| dc.description.statementofresponsibility | by Ronak Naeemaee | |
| dc.embargo.release | 2024-03-08 | |
| dc.format.extent | xiv, 115 leaves : color illustrations, charts, tables ; 30 cm. | |
| dc.identifier.itemid | B162499 | |
| dc.identifier.uri | https://hdl.handle.net/11693/113844 | |
| dc.language.iso | English | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Colorectal cancer | |
| dc.subject | Prognosis | |
| dc.subject | Survival | |
| dc.subject | Biomarkers | |
| dc.subject | Neuropeptides | |
| dc.subject | Hedgehog signaling pathway | |
| dc.title | Prognostic biomarker identification and classification of colorectal cancer patients: a dual gene-based and sample-based approach | |
| dc.title.alternative | Kolorektal kanser hastalarında prognostik biyomarkör belirleme ve sınıflandırma: ikili gen-temelli ve örnek-temelli yaklaşım | |
| dc.type | Thesis | |
| thesis.degree.discipline | Molecular Biology and Genetics | |
| thesis.degree.grantor | Bilkent University | |
| thesis.degree.level | Master's | |
| thesis.degree.name | MS (Master of Science) |