Stromal protein CCN family contributes to the poor prognosis in lower-grade gioma by modulating immunity, matrix, stemness, and metabolism

Background: The CCN family of stromal proteins is involved in the regulation of many important biological functions. However, the role of dysregulated CCN proteins in lower-grade glioma (LGG) remain less understand.Methods: The clinical significance of the CCN proteins was explored based on RNA-seq profiles from multiple cohorts. A CCNScore was constructed using LASSO regression analysis. The PanCanAtlas data and MEXPRESS database were employed to elucidate molecular underpinnings.Results: The expression of CCN4 was associated with poor prognosis in LGG. The CCNScore (CCN1 = 0.06, CCN4 = 0.86) showed implication in prognosis prediction, subtype assessment and therapy selection. The gene mutation pattern of the high-CCNScore group was similar with glioblastoma, including EGFR, PTEN, and NF1 mutation frequently. Besides, the high-CCNScore group was comprised of samples mainly classic-like and mesenchymal-like, had lower methylation levels, higher stemness, higher inflammation, higher levels of extracellular matrix remodel and dysfunction of metabolic pathways. On the other hand, the low-CCNScore group consisted mainly of IDH-mutation LGG, and was characterized by TP53, CIC, and ATRX gene mutations, hyper-methylation status, lower stemness, lower proliferation, immune quietness and low extracellular matrix stiffness.Conclusion: In summary, these results outlined the role of CCN family in LGG and provided a potential and promising therapeutic target

Predicting Rules for Cancer Subtype Classification using Grammar-Based Genetic Programming on various Genomic Data Types

With the advent of high-throughput methods more genomic data then ever has been generated during the past decade. As these technologies remain cost intensive and not worthwhile for every research group, databases, such as the TCGA and Firebrowse, emerged. While these database enable the fast and free access to massive amounts of genomic data, they also embody new challenges to the research community. This study investigates methods to obtain, normalize and process genomic data for computer aided decision making in the field of cancer subtype discovery. A new software, termed FirebrowseR is introduced, allowing the direct download of genomic data sets into the R programming environment. To pre-process the obtained data, a set of methods is introduced, enabling data type specific normalization. As a proof of principle, the Web-TCGA software is created, enabling fast data analysis. To explore cancer subtypes a statistical model, the EDL, is introduced. The newly developed method is designed to provide highly precise, yet interpretable models. The EDL is tested on well established data sets, while its performance is compared to state of the art machine learning algorithms. As a proof of principle, the EDL was run on a cohort of 1,000 breast cancer patients, where it reliably re-identified the known subtypes and automatically selected the corresponding maker genes, by which the subtypes are defined. In addition, novel patterns of alterations in well known maker genes could be identified to distinguish primary and mCRPC samples. The findings suggest that mCRPC is characterized through a unique amplification of the Androgen Receptor, while a significant fraction of primary samples is described by a loss of heterozygosity TP53 and NCOR1

Diverse Roles Of Nuclear Intermediate Filaments In Proliferating Cells

Embryonic tissues and cancer have in common the fact that they are both highly proliferative tissues rapidly moving through the cell cycle, as opposed to most other differentiated tissues in an adult. DNA damage can arrest some embryonic cells but genetic instability is a hallmark of cancer. This thesis studies the contrasting role of two nuclear intermediate filaments - Lamin A and Lamin B1 in the proliferating cells of embryonic hearts and cancer. Lamin B1 is upregulated together with proliferation genes in at least 15 cancers curated in The Cancer Genome Atlas (TCGA), whereas Lamin A trends align with ‘matrix mechanosensititve’ genes. With physicochemical principles in mind, we show Lamin B1 scales with many mitosis genes in cancer, and experiments reveal its role in promoting cell cycle and direct regulation by the cell cycle transcription factor FOXM1. The genes that scale are used in Scaling-informed Machine Learning (SIML) to better predict overall patient survival and to better identify cell lineage in single cell RNA profiles. A distinct role of Lamin A is revealed by experiments on the first organ in its first days – the heart – which show Lamin A levels are modulated in interphase cells through phosphorylation in response to acto-myosin stress. Lamin A levels determine the probability of nuclear rupture and subsequent DNA damage, telomere attrition, and cell cycle arrest. Nuclear lamins thus have different roles in responding to and regulating cell cycle

Targeting Stress Response Pathways in Soft Tissue Sarcoma: The Role of Hypoxia and Autophagy in Tumor Survival

Soft tissue sarcomas (STS) are a group of malignancies that arise from mesenchymal tissue, consisting of over 50 distinct histiologic subtypes. Unfortunately, the five-year survival rate of sarcoma patients has remained relatively unchanged, and due to the rarity of the disease, research and development of adequate therapeutics for STS lags behind other cancers. Therefore, understanding the molecular drivers of STS is important in developing new therapeutics, as well as discovering druggable processes that occur across multiple subtypes. One feature common to STS is hypoxia, or low O2 conditions. Using molecular biology, biochemical approaches, genetically engineered mouse models, as well as querying publically available data sets, we determined that Hypoxia Inducible Factor (HIF)-2α suppresses fibrosarcoma, dedifferentiated liposarcoma, and undifferentiated pleomorphic sarcoma (UPS) growth in vivo. In addition, we found that STS patient samples express low levels of EPAS1 (the gene encoding HIF-2α). Our results showed increased levels of the calcium activated chloride channel ANO1, in HIF-2α deficient UPS tumors, which increased mTORC1 activity. Additionally, we determined that HIF-2α was epigenetically silenced in STS, and could be re-expressed with histone deacetylation inhibitor (HDACi) treatment. HDACi suppressed STS growth in vivo in a HIF-2α dependent manner. Moreover, we established that autophagy promotes fibrosarcoma and UPS survival under hypoxic and ischemic-like conditions. Autophagic inhibition, either with chloroquine or the more potent autophagy inhibitor Lys05, reduces UPS and fibrosarcoma growth in vitro and in vivo. From these studies, future clinical studies are warranted to test histone deacetylase inhibitors and autophagy inhibitors in patients with the STS subtypes examined here

Identification of Novel Pathways that Promote Anoikis through Genome-wide Screens

Epithelial cells that lose attachment to the extracellular matrix (ECM) undergo a specialized form of apoptosis called anoikis. Anoikis has an important role in preventing oncogenesis, particularly metastasis, by eliminating cells that lack proper ECM cues. The basis of anoikis resistance remains to be determined and to date has not been linked to alterations in expression or activity of previously identified anoikis effector genes. Here, I utilized two different screening strategies to identify novel anoikis effector genes and miRNAs in order to gain a deeper understanding of anoikis and the potential mechanisms of anoikis resistance in cancer. Using large-scale RNA interference (RNAi) screening, I found that KDM3A, a histone H3 lysine 9 (H3K9) mono- and di-demethylase plays a pivotal role in anoikis induction. In attached breast epithelial cells, KDM3A expression is maintained at low levels by integrin signaling. Following detachment, integrin signaling is decreased resulting in increased KDM3A expression. RNAi-mediated knockdown of KDM3A substantially reduces apoptosis following detachment and, conversely, ectopic expression of KDM3A induces cell death in attached cells. I found that KDM3A promotes anoikis through transcriptional activation of BNIP3 and BNIP3L, which encode pro-apoptotic proteins. Using mouse models of breast cancer metastasis I show that knockdown of Kdm3a enhances metastatic potential. Finally, I find defective KDM3A expression in human breast cancer cell lines and tumors. Collectively, my results reveal a novel transcriptional regulatory program that mediates anoikis. Next, I sought to discover miRNAs involved in anoikis by investigated changes in miRNA expression during anoikis using small RNA sequencing technology. Through this approach I discovered that miR-203 is an anoikis effector miRNA that is also highly down-regulated in invasive breast cancer cells. In breast epithelial cells, miR-203 is induced upon the loss of ECM attachment and inhibition of miR-203 activity leads to a resistance to anoikis. I utilized a dual functional- and expression- based RNA sequencing approach and found that miR-203 directly targets a network of pro-survival genes to induce cell death upon detachment. Finally, I found that the loss of miR-203 in invasive breast cancer leads to the elevation of several anoikis-related pro-survival target genes to contribute to anoikis resistance. Taken together, my studies reveal novel pathways through which cell death is induced upon detachment from the ECM and provide insight into potential mechanisms of anoikis resistance in cancer