Research

Research Experiences

PhD Thesis

Mirtrons as Emerging Regulators of Cancer, Immune Function, and Metastasis

Summery

Mirtrons, a specialized subclass of intron-derived microRNAs (miRNAs), have emerged as pivotal post-transcriptional regulators that bypass the canonical Drosha-dependent biogenesis pathway. Instead, these small non-coding RNAs are processed through intron splicing and debranching, forming pre-miRNA hairpins capable of entering the Dicer processing pathway. Recent discoveries highlight that mirtrons not only participate in gene expression regulation but also exhibit exceptional structural stability against exonucleolytic degradation. This biochemical resilience promotes their persistence in the tumor microenvironment, enabling sustained regulatory activity during cancer initiation and progression.

This thesis examines four interrelated questions: (1) how mirtrons maintain stability against exoribonucleases in cancer; (2) their role in stem cell differentiation into immune lineages; (3) their contribution to immune suppression; and (4) their association with metastasis. Collectively, emerging research indicates that mirtrons regulate a broad range of molecular pathways linked to oncogenesis, immune function, and metastatic progression. The integration of mirtron biogenesis with disease-related gene networks positions them as both diagnostic biomarkers and therapeutic targets in molecular oncology.

Conceptual Background

MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression post-transcriptionally. Among them, mirtrons form a unique subclass that bypasses canonical Drosha processing, instead arising from spliced introns that directly enter the Dicer pathway. This non-canonical maturation allows mirtrons to remain active even when conventional miRNA processing is impaired—a feature often seen in cancer cells.

Structurally, mirtrons exhibit splicing-derived termini and protective m7G caps, conferring exceptional stability against exoribonucleases (e.g., XRN1/2). Their resilience under stress conditions such as hypoxia or chemotherapy enables sustained regulation of oncogenic signaling pathways, including PI3K/AKT, TGF-β, and Wnt/β-catenin, influencing tumor proliferation, EMT, and immune evasion.

Mirtrons also regulate stem cell differentiation and immune homeostasis, with dysregulation contributing to cancer stemness and immune imbalance. Certain mirtrons enhance tumor immune escape by upregulating SOCS1/3 and stabilizing PD-L1 transcripts, while others suppress metastasis by targeting cytoskeletal and extracellular matrix genes.

Overall, mirtrons represent a highly adaptable class of regulatory RNAs that bridge genetic control, immune modulation, and tumor evolution—positioning them as promising targets for next-generation cancer therapeutics.

Research Question 1:

How mirtrons maintain stability in cancers against exoribonucleases.

Hypothesis 1:

The G-quadruplex (G4) structure of mirtron blocks exoribonucleases- mediated digestion.

Research Question 2:

Do Mirtrons have an Influence on Stem Cell Differentiation into Immune Cells?

Hypothesis 2:

This mirtron-driven shift supports an immune- suppressive environment, which may contribute to tumor immune evasion by dampening anti- tumor immune responses and promoting tumor growth.n blocks exoribonucleases- mediated digestion.

https://promocell.com/research-areas/applications-for-our-cancer-media-toolbox/tumor-microenvironment/

Yao et al; Frontiers, 10.3389/fimmu.2019.00792

Research Question 3:

Do Mirtrons have any effect on Immune Suppression?

Hypothesis 3:

The presence of mirtrons induces a phenotypic shift in macrophages from the M1 pro-inflammatory state to the M2 anti-inflammatory state.

Research Question 4:

How nucleotide tailing of mirtrons impacts their exosomal sorting.

Hypothesis 4:

More 3’ nucleotide addition (longer tailing) to mirtron precursors is related to the aggressiveness of breast cancers, potentially through greater trafficking into exosomes.

Master's Thesis, Part 1:

In silico analysis of Aptamers targeted to MUC1 overexpressed cancer cells

The "Aptabase" database was utilized as a resource to get the aptamers targeted to the MUC1 protein.
The "UNAFold" Web Server was employed to predict the two-dimensional (2D) structure of the aptamers based on thermodynamic calculations and nearest-neighbor energy parameters.
The "Xiao Lab" web server was used to design the three-dimensional (3D) models of the aptamers, employing molecular dynamics simulations and constraint-based modeling.
The Maestro 12.5 software was utilized to minimize and refine the 3D structures of the aptamers.
The 3D structure of the MUC1 protein was retrieved from the RCSB Protein Data Bank and prepared for molecular docking using the Maestro 12.5 software.
Molecular docking between the aptamers and the MUC1 protein was conducted using the "HDOCK" server, known for its capability in DNA-protein molecular docking.
A comprehensive analysis of various parameters was conducted including docking scores, confidence scores, binding affinity, and dG scores, to compare different aptamers.

Figure. Comparative study of MUC1 targeting aptamers.

Figure A displays the Confidence score, which represents the stability of the interaction between MUC1 and the aptamers. A higher Confidence score indicates a more stable interaction between the two.

Figure B represents the binding affinity of the aptamers to MUC1. The binding affinity is assessed based on the scores, with lower scores indicating a stronger binding between the aptamers and MUC1.

Figure C shows the docking scores of the aptamers and MUC1. The docking scores indicate the strength of the interaction between the aptamers and MUC1. Lower docking scores suggest a more favorable and effective interaction.

Figure D represents the dG score, which reflects the stability of the aptamers. The dG score is used to evaluate the thermodynamic stability of the aptamers, with lower scores indicating greater stability.

Master's Thesis, Part 2:

In vitro analysis of S1.6 Aptamer conjugated liposomal system targeted to MUC1 overexpressed cancer cells

Figure: Overview of the experimental process. 1. Mixing DPPC, Cholesterol, and DSPE-PEG-Mal in a vial. 2. Maintaining the mixer in a vacuum overnight. 3. Hydration with PBS and Dox. 4. Encapsulation of Dox through tip sonication. 5. Formation of Dox-encapsulated liposomes. 6. Visualization of the aptamer S1.6 and its 3D structure. 7. Conjugation of the aptamer with the liposome's malamide. 8. Treatment of MCF-7 cells with lipo-dox-aptamer. 9. Observation of Mucin1 overexpression in MCF-7 cell line. 10. Visual representation of MUC1 protein and its 3D structure. 11. Binding of lipo-dox-aptamer with Muc1 protein. 12. 3D structure depicting the interaction between Lipo-dox-apt and Mucin-1.

Liposome Preparation:

Liposomes were prepared using the film hydration method.
A mixture of DPPC, cholesterol, and PEG 2000-DSPE-Malamide in specific molar ratios was dissolved in a chloroform and methanol mixture.
Solvent evaporation and vacuum drying were performed to remove the organic solvent.
Hydration of the lipid film was achieved using a PBS solution with doxorubicin.
Tip sonication and filtration were used to eliminate non-encapsulated doxorubicin and unwanted residues.
The Nanodrop spectrophotometer was employed to determine the doxorubicin encapsulation rate.

Conjugation of S1.6 to Liposomes:

The aptamer folding process involved heating and cooling under specific conditions.
The liposomes with maleimide groups on their surface were incubated with the S1.6-SS aptamer in the presence of TCEP•HCl.

Characterization:

The efficiency of conjugation was measured using the NanoDrop spectrophotometer and dynamic light scattering (DLS) analysis.
DLS provided information about particle size and charge.
Transmission electron microscopy (TEM) was used to examine the microstructure and morphology of the liposomes.
Gel electrophoresis was conducted to confirm lipo-aptamer conjugation

Analyzing MUC1 Expression:

Immunofluorescence staining was performed to investigate MUC1 presence in MCF7 and MDA-MB-231 cell lines.
Flow cytometry analysis was employed to visualize the MUC1 expression pattern.

Receptor-Mediated Cellular Uptake:

Confocal microscopy was used to evaluate the binding specificity of liposomes in MCF7 and MDA-MB-231 cell lines.
Hoechst dye was utilized for nuclear staining.

Master's Collaborative Project:

Development of cationic pH-responsive albumin binding ligands with enhanced blood half-life for cancer theranostics

Figure. Distinct pH levels as biomarkers in each organ, tissue, and cellular level and their potential application (reproduced from S. Bazban-Shotorbani et al., Journal of Controlled Release 253 (2017) 46–63)

Design of ABL-His:

A pH-responsive albumin-binding ligand (ABL-His) was developed, consisting of a fatty acid-based binding moiety and an imidazole moiety in histidine for charge-exchangeable property at low pH conditions. This design allows ABL-His to bind reversibly to serum albumin and be released in the acidic tumor microenvironment.

Synthesis and characterization:

RITC (rhodamine B isothiocyanate) was introduced as a fluorescence dye to label the ABLs. The synthesized RITC-ABL-His and RITC-ABL-Gly (non pH-responsive ABL) showed more than 2-fold higher albumin binding capacity compared to free RITC. RITC-ABL-His demonstrated reduced albumin-binding capacity at low pH conditions due to the charge-exchange of the imidazole moiety.

In vitro evaluation:

In vitro studies confirmed the high fluorescent intensity of RITC-ABLs within CT26 cancer cells at neutral pH, indicating their potential for tumor targeting and imaging.

In vivo evaluation:

In CT26 tumor-bearing mice, in vivo and ex vivo fluorescence imaging revealed significantly higher tumor uptake of RITC-ABL-His compared to RITC-ABL-Gly and RITC alone. This demonstrated the superior tumor targeting ability of ABL-His.

Extension to photodynamic/photothermal therapy:

To expand the applications of ABLs, IR780-ABL-His was prepared by immobilizing IR780, a near-infrared light activatable photosensitizer, onto the ABLs. The physicochemical characteristics of IR780-ABL-His were evaluated for potential application in photodynamic/photothermal therapy.

Bachelor’s Project 1:

Prevalence of Multidrug-Resistant Acinetobacter Baumannii in Environmental Samples in a Tertiary Care Hospital

Conducted a study to isolate Acinetobacter baumannii from the hospital environment and assess the prevalence of multidrug-resistant (MDR) patterns.
Identified A. baumannii through colony morphology on culture media and biochemical tests (Catalase test and Oxidase test).
Determined the MDR pattern using the Kirby Bauer Disc Diffusion method with commercially available antibiotic discs including Erythromycin, Colistin, Ceftriaxone, Ciprofloxacin, and Imipenem.
It was found that all isolates were sensitive to Imipenem, while resistance was observed for Erythromycin, Colistin, Ceftriaxone, and Ciprofloxacin.
Highlighted the need for a strict policy to control the spread of MDR A. baumannii through the contaminated environment and the potential benefits of revising infection control procedures.

Bachelor’s Project 2:

Prevalence of Multidrug-Resistant Acinetobacter Baumannii in Environmental Samples in a Tertiary Care Hospital

Utilized bioinformatics tools to predict potent B-cell and T-cell epitopes from the CCHFV glycoprotein and designed a vaccine candidate incorporating 6 CD8+, 3 CD4+, and 7 B-cell epitopes with appropriate linkers.
Enhanced the vaccine's efficiency by adding Mycobacterium tuberculosis lipoprotein LprG (Rv1411c) as an adjuvant.
Constructed a final chimeric vaccine with 468 amino acid residues, demonstrating 98% worldwide population coverage for the included epitopes.
Modeled the three-dimensional (3D) structure of the vaccine, showing stable interactions with toll-like receptor 2 (TLR2).
Conducted dynamics simulations indicating elevated levels of cellular immune activity and faster clearance of antigens from the body.
Ensured optimized codon usage for marked translation efficiency of the vaccine protein in E. coli strain K12 bacterium.
Inserted the construct DNA into the cloning vector pET28a (+) for further development.
Emphasized the potential utility of the designed vaccine chimera in combating CCHFV outbreaks.

Figure: Population coverage, design, and evaluation of vaccine candidates. (A) region-wise % of population coverage by including CD8+ and CD4+ epitopes and their corresponding HLA alleles; (B) Construction of epitope-based chimeric vaccine that includes an adjuvant, T-cell & B-cell epitopes, and linkers. The adjuvant was added to the N-terminal end using EAAAK linker while CD8+, CD4+, and LBC epitopes were fused together with AAY, GPGPG, and KK linkers; (C) tertiary (3D) structure of the vaccine construct (D) Ramachandran plot statistics showing the % of most favored (92.1%), allowed (5.8%), and outlier regions (2.1%) of the vaccine; (E) Z-score of − 7.55 indicate the X-ray-like structural quality of the vaccine protein; (F) docking simulation between vaccine candidate and TLR2 protein; and (G) codon optimization and cloning of the vaccine candidate (pink color) into pET28a (+) expression vector (black color) by placing the vaccine’s DNA between XhoI (158) and NdeI (1569) restriction sites.

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