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Modulating gene expression in breast cancer via DNA secondary structure and the CRISPR toolbox.

ABSTRACT: Breast cancer is the most commonly diagnosed malignancy in women, and while the survival prognosis of patients with early-stage, non-metastatic disease is ∼75%, recurrence poses a significant risk and advanced and/or metastatic breast cancer is incurable. A distinctive feature of advanced breast cancer is an unstable genome and altered gene expression patterns that result in disease heterogeneity. Transcription factors represent a unique therapeutic opportunity in breast cancer, since they are known regulators of gene expression, including gene expression involved in differentiation and cell death, which are themselves often mutated or dysregulated in cancer. While transcription factors have traditionally been viewed as 'undruggable', progress has been made in the development of small-molecule therapeutics to target relevant protein-protein, protein-DNA and enzymatic active sites, with varying levels of success. However, non-traditional approaches such as epigenetic editing, transcriptional control via CRISPR/dCas9 systems, and gene regulation through non-canonical nucleic acid secondary structures represent new directions yet to be fully explored. Here, we discuss these new approaches and current limitations in light of new therapeutic opportunities for breast cancers.

SUBMITTER: Kretzmann JA

PROVIDER: S-EPMC8693572 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Modulating gene expression in breast cancer via DNA secondary structure and the CRISPR toolbox.

Kretzmann Jessica A JA Irving Kelly L KL Smith Nicole M NM Evans Cameron W CW

NAR cancer 20211222 4

Breast cancer is the most commonly diagnosed malignancy in women, and while the survival prognosis of patients with early-stage, non-metastatic disease is ∼75%, recurrence poses a significant risk and advanced and/or metastatic breast cancer is incurable. A distinctive feature of advanced breast cancer is an unstable genome and altered gene expression patterns that result in disease heterogeneity. Transcription factors represent a unique therapeutic opportunity in breast cancer, since they are k ...[more]

PMID: 34988459

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Project description:BackgroundDNA repair is the general term for the collection of critical mechanisms which repair many forms of DNA damage such as methylation or ionizing radiation. DNA repair has mainly been studied in experimental and clinical situations, and relatively few information-based approaches to new extracting DNA repair knowledge exist. As a first step, automatic detection of DNA repair proteins in genomes via informatics techniques is desirable; however, there are many forms of DNA repair and it is not a straightforward process to identify and classify repair proteins with a single optimal method. We perform a study of the ability of homology and machine learning-based methods to identify and classify DNA repair proteins, as well as scan vertebrate genomes for the presence of novel repair proteins. Combinations of primary sequence polypeptide frequency, secondary structure, and homology information are used as feature information for input to a Support Vector Machine (SVM).ResultsWe identify that SVM techniques are capable of identifying portions of DNA repair protein datasets without admitting false positives; at low levels of false positive tolerance, homology can also identify and classify proteins with good performance. Secondary structure information provides improved performance compared to using primary structure alone. Furthermore, we observe that machine learning methods incorporating homology information perform best when data is filtered by some clustering technique. Analysis by applying these methodologies to the scanning of multiple vertebrate genomes confirms a positive correlation between the size of a genome and the number of DNA repair protein transcripts it is likely to contain, and simultaneously suggests that all organisms have a non-zero minimum number of repair genes. In addition, the scan result clusters several organisms' repair abilities in an evolutionarily consistent fashion. Analysis also identifies several functionally unconfirmed proteins that are highly likely to be involved in the repair process. A new web service, INTREPED, has been made available for the immediate search and annotation of DNA repair proteins in newly sequenced genomes.ConclusionDespite complexity due to a multitude of repair pathways, combinations of sequence, structure, and homology with Support Vector Machines offer good methods in addition to existing homology searches for DNA repair protein identification and functional annotation. Most importantly, this study has uncovered relationships between the size of a genome and a genome's available repair repertoire, and offers a number of new predictions as well as a prediction service, both which reduce the search time and cost for novel repair genes and proteins.

Project description:Our previously published data link P-selectin-reactive chondroitin sulfate structures on the surface of breast cancer cells to metastatic behavior of cells. We have shown that a particular sulfation pattern mediated by the expression of carbohydrate (chondroitin 4) sulfotransferase-11 (CHST11) correlates with P-selectin binding and aggressiveness of human breast cancer cell lines. The present study was performed to evaluate the prognostic value of CHST11 expression and determine whether aberrant DNA methylation controls CHST11 expression in breast cancer. Publicly available datasets were used to examine the association of CHST11 expression to aggressiveness and progression of breast cancer. Methylation status was analyzed using bisulfite genomic sequencing. 5-aza-2'-deoxycytidine (5AzadC) was used for DNA demethylation. Reduced representation bisulfite sequencing was performed in the CpG island of CHST11 with a minimum coverage of 10. Quantitative real-time RT-PCR was employed to confirm the expression profile of CHST11 in breast cancer cell lines. Flow cytometry was also used to confirm the expression of the CHST11 product, chondroitin sulfate A (CS-A). The expression of CHST11 was significantly higher in basal-like and Her2-amplified cell lines compared to luminal cell lines. CHST11 was also highly expressed in cancer tissues compared to normal tissues and the expression levels were significantly associated with tumor progression. We observed very low levels of DNA methylation in a CpG island of CHST11 in basal-like cells but very high levels in the same region in luminal cells. Treatment of MCF7 cells, a luminal cell line with very low expression of CHST11, with 5AzadC increased the expression of CHST11 and its immediate product, CS-A, in a dose-dependent manner. These results suggest that CHST11 may play a direct role in progression of breast cancer and that its expression is controlled by DNA methylation. Therefore, in addition to CHST11 mRNA levels, the methylation status of this gene also has potential as a prognostic biomarker.

Dataset Information

Modulating gene expression in breast cancer via DNA secondary structure and the CRISPR toolbox.

Publications

Modulating gene expression in breast cancer via DNA secondary structure and the CRISPR toolbox.

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