CCNA2 Human

What is CCNA2 and what is its role in human cells?

CCNA2 (Cyclin A2) functions as a master regulatory gene of the cell cycle that becomes silenced in postnatal mammalian cardiomyocytes . In normal development, CCNA2 plays a crucial role in regulating cell division, particularly during S phase and the G2/M transition.

The methodological approach to studying CCNA2's role typically involves:

• Gene expression analysis through RNA sequencing or qPCR to quantify CCNA2 levels

• Immunohistochemistry to visualize protein localization

• Manipulation of expression through viral vectors or transgenic models

• Time-lapse microscopy to observe cellular division dynamics

Research has demonstrated that reintroduction of CCNA2 in adult human cardiomyocytes can reactivate cell cycle machinery and induce complete cytokinesis with preservation of sarcomere integrity in daughter cells .

How does CCNA2 expression differ between fetal and adult human hearts?

CCNA2 exhibits distinct expression patterns between fetal and adult human cardiac tissues. The methodological approach to investigating this difference includes:

• Bulk RNA sequencing of human fetal and adult heart samples

• Comparative transcriptomic analysis to identify differentially expressed genes

• Pathway enrichment analysis to determine biological processes affected

Research has employed bulk RNA sequencing of pooled human fetal heart RNA (n=3) and adult heart RNA (n=4) to identify key reprogramming genes that are targets for CCNA2-induced cytokinesis . The sequence reads were mapped to the human genome (GRCh38.110) using STAR (version 2.7.9a), and the R package edgeR was used to calculate counts per million values and FDR-adjusted p-values .

What experimental systems are available for studying CCNA2 function in human cardiomyocytes?

Multiple experimental systems have been developed to study CCNA2 function in human cardiomyocytes:

• Isolated adult human cardiomyocytes: Freshly isolated cardiomyocytes from adult human hearts (demonstrated with cells from individuals aged 21, 41, and 55 years) can be used for direct CCNA2 delivery studies .

• Viral vector systems: A human gene therapy vector featuring replication-deficient, E1/E3-deleted human adenovirus 5 encoding human CCNA2 driven by the cardiac Troponin T promoter enables cardiomyocyte-specific expression .

• Transgenic mouse models: CCNA2-Tg mice constitutively expressing CCNA2 in cardiomyocytes provide an in vivo system for studying long-term effects .

• Time-lapse microscopy systems: These enable dynamic visualization of sarcomere-labeled cardiomyocytes, allowing researchers to observe cytokinesis events in real-time .

Each system offers unique advantages for investigating different aspects of CCNA2-mediated cardiac regeneration.

What techniques are most effective for detecting CCNA2 expression in human samples?

Several complementary techniques can be employed for robust detection of CCNA2 expression:

• Immunohistochemistry: Enables visualization of protein expression patterns in tissue context while preserving spatial information. The Human Protein Atlas database provides reference immunohistochemical data for comparative analysis .

• Quantitative RT-PCR: For targeted quantification of CCNA2 mRNA expression. Research has verified CCNA2 expression in paired PAAD tissues and adjacent non-tumor tissues using TRIzol reagent extraction and ABI Prism 5700 Sequence Detection System .

• RNA sequencing: For genome-wide expression profiling and context. Both bulk RNA-seq and single-nucleus RNA-seq (snRNA-seq, 10X Genomics) have been successfully applied to CCNA2 research .

• Western blotting: For protein-level quantification to confirm transcriptional findings.

For optimal results, researchers should employ multiple complementary techniques to validate findings across different analytical platforms.

What are the key reprogramming genes associated with CCNA2-induced cytokinesis?

The identification of key reprogramming genes associated with CCNA2-induced cytokinesis has been accomplished through comparative transcriptomic approaches:

• Single nucleus RNA-seq (snRNA-seq) comparing CCNA2-Tg mice (transgenic mice constitutively expressing CCNA2 in cardiomyocytes) with non-transgenic controls identified a distinct subpopulation of cardiomyocytes enriched with cytokinesis, proliferative, and reprogramming genes .

• Bulk RNA sequencing of human adult and fetal hearts has revealed developmental gene programs that may be reactivated during CCNA2-induced cardiomyocyte proliferation .

The raw expression matrices and sequence files from these analyses are publicly available on the Gene Expression Omnibus (GSE249433 and GSE256519) , allowing researchers to perform further analyses to identify specific gene signatures associated with CCNA2-induced regenerative capacity.

What methodologies are most effective for CCNA2 gene delivery to human cardiomyocytes?

Current research indicates that adenoviral vector systems offer the most effective approach for CCNA2 gene delivery to human cardiomyocytes. The methodological considerations include:

• Vector design: A replication-deficient, E1/E3-deleted human adenovirus 5 encoding human CCNA2 (NCBI Reference Sequence: NM_001237.4; 374-1672 bp) driven by the cardiac Troponin T (cTnT) promoter ensures cardiomyocyte-specific expression .

• Delivery optimization: Transfection of cultured adult human cardiomyocytes with MOI of 100 has demonstrated significant CCNA2 expression induction .

• Expression verification: Comparing test (cTnT-hCCNA2) with control vectors (cTnT-eGFP and/or cTnT-H2B-GFP) enables confirmation of successful gene delivery .

• Functional assessment: Time-lapse microscopy with dynamic sarcomere labeling allows for visualization of the complete cytokinesis process in transfected cardiomyocytes .

This targeted approach ensures cardiomyocyte-specific expression while minimizing off-target effects in non-cardiac tissues, which is crucial for potential therapeutic applications.

How can single nucleus transcriptomics be optimized for studying CCNA2-induced effects in cardiomyocytes?

Optimizing single nucleus transcriptomics (snRNA-seq) for CCNA2 research requires careful consideration of several methodological aspects:

• Sample preparation: Nuclei isolation from heart tissue must be optimized to ensure representation of all cardiomyocyte populations, particularly the rare proliferating subpopulations.

• Sequencing depth: Adequate sequencing depth is essential for detecting low-abundance transcripts associated with cell cycle reactivation.

• Bioinformatic analysis pipeline:

  • STAR (version 2.7.9a) for mapping reads to the appropriate genome (GRCh38.110 for human samples)

  • edgeR (version 3.30.3) for calculating counts per million values

  • Benjamini–Hochberg method for FDR-adjusted p-values

• Cell type identification: Cardiomyocyte-specific markers must be used to distinguish cardiomyocyte nuclei from other cardiac cell types.

• Subpopulation analysis: Clustering approaches should be optimized to identify rare proliferating cardiomyocyte populations enriched with cytokinesis, proliferative, and reprogramming genes .

This approach has successfully identified distinct transcriptional signatures in CCNA2-expressing cardiomyocytes that provide mechanistic insights into CCNA2-induced cardiac regeneration.

What are the mechanistic underpinnings of CCNA2-dependent gene regulation in governing cardiomyocyte cytokinesis?

Understanding the mechanistic underpinnings of CCNA2-dependent gene regulation requires integrated multi-omic approaches:

• Comparative transcriptomics: snRNA-seq analysis comparing CCNA2-Tg and non-transgenic hearts has revealed subpopulations of cardiomyocytes with distinct transcriptional signatures enriched for cytokinesis, proliferation, and reprogramming genes .

• Developmental context: Comparing adult and fetal heart transcriptomes helps identify developmental programs reactivated by CCNA2 expression .

• Pathway analysis: Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using tools like STRING (https://string-db.org/) can identify overrepresented biological processes, molecular functions, and cellular components .

• Functional validation: Time-lapse microscopy with sarcomere labeling provides visual confirmation of complete cytokinesis with preservation of sarcomere integrity in daughter cells following CCNA2 expression .

These approaches collectively suggest that CCNA2 induces a partial reprogramming of adult cardiomyocytes toward a more proliferation-competent state while maintaining essential cardiomyocyte functions.

How can researchers address technical concerns like arrhythmias when translating CCNA2-based therapies to human applications?

Addressing technical concerns in translating CCNA2-based therapies requires multi-faceted approaches:

• Controlled expression systems: Using cardiomyocyte-specific promoters (like cardiac Troponin T) ensures targeted expression in appropriate cell types .

• Dosage optimization: Careful titration of viral vector MOI is essential to achieve sufficient CCNA2 expression for therapeutic effect while minimizing potential arrhythmogenic risk.

• Electrophysiological assessment: Calcium imaging and patch-clamp studies can evaluate functional integration and electrophysiological properties of newly formed cardiomyocytes.

• Large animal models: The transition from rodent to large animal models (e.g., porcine) provides crucial translational insights. Previous studies have demonstrated significant cardiac repair in porcine models with decreased fibrosis and increased cardiomyocyte numbers without reported arrhythmias .

• Safety monitoring: Research indicates concerns about arrhythmias noted in primate hearts treated with ES-derived and iPS-derived cardiomyocytes , suggesting the need for careful cardiac rhythm monitoring in any CCNA2-based regenerative approach.

This systematic approach allows researchers to address potential safety concerns while advancing toward clinical translation.

What statistical approaches are recommended for analyzing CCNA2-related transcriptomic data in human cardiac studies?

Analysis of CCNA2-related transcriptomic data requires robust statistical methodologies:

• Differential expression analysis:

  • For bulk RNA-seq: edgeR package calculates counts per million (CPM) values

  • FDR-adjusted p-values using Benjamini–Hochberg method for multiple testing correction

  • Significance threshold typically set at P < 0.05

• Survival analysis:

  • Stratification of patients into high and low CCNA2 expression groups using median expression as cutoff

  • Kaplan-Meier analysis with log-rank test for comparing survival outcomes

  • Hazard ratios with 95% confidence intervals to quantify risk

• Comparative analysis approaches:

  • Student's t-tests for two-class differential expression comparisons (as used in Oncomine database)

  • Unpaired t-tests for experimental data, presenting results as means ± SEM

• Data visualization:

  • Principal component analysis for visualizing separation between sample groups

  • Heatmaps for displaying expression patterns across sample types

  • Volcano plots for highlighting significantly differentially expressed genes

These statistical approaches ensure robust analysis and interpretation of complex transcriptomic datasets in CCNA2 cardiac research.

How does CCNA2 expression correlate with clinical outcomes across different human pathologies?

CCNA2 expression has been correlated with clinical outcomes across several human pathologies, particularly in cancer contexts:

• Pancreatic adenocarcinoma (PAAD):

  • Expression levels of CCNA2 are significantly higher in PAAD compared to control tissues

  • Increased expression is associated with more advanced tumor stage

  • Higher CCNA2 expression correlates with poor prognosis in pancreatic cancer patients

• Cardiac pathologies:

  • CCNA2 is normally silenced in postnatal human cardiomyocytes

  • Reintroduction via gene therapy vectors induces cardiomyocyte proliferation and potential cardiac repair

  • Expression in transgenic models is associated with subpopulations of cardiomyocytes with proliferative capacity

Methodological approaches for correlation analysis include:

• UALCAN database to analyze relationships between gene expression and clinicopathologic parameters

• OncoLnc and GEPIA databases for survival analyses using median expression values to stratify patients

• Kaplan-Meier survival curves with log-rank tests to assess statistical significance

Understanding these correlations helps contextualize potential therapeutic applications while also identifying potential risks of unregulated CCNA2 expression.

What experimental designs are most appropriate for investigating CCNA2's potential in human cardiac regeneration?

Optimal experimental designs for investigating CCNA2's cardiac regenerative potential include:

• In vitro human cardiomyocyte studies:

  • Isolated adult human cardiomyocytes from diverse donors (different ages, genders)

  • Time-lapse microscopy with dynamic sarcomere labeling to visualize cytokinesis events

  • Functional assessment of daughter cells through calcium imaging or patch-clamp studies

• Animal models with varying complexity:

  • Transgenic mouse models (CCNA2-Tg) for mechanistic studies

  • Large animal models (porcine) for translational relevance

  • Injury models (myocardial infarction) to assess functional recovery

• Comprehensive assessment endpoints:

  • Molecular: snRNA-seq to identify transcriptional signatures

  • Cellular: quantification of cardiomyocyte numbers and evidence of proliferation

  • Structural: assessment of fibrosis and cardiomyocyte hypertrophy

  • Functional: multimodality imaging including MRI to evaluate cardiac function

• Control conditions:

  • Non-transgenic controls for genetic models

  • Control vectors (cTnT-eGFP, cTnT-H2B-GFP) for viral delivery experiments

These comprehensive experimental designs enable thorough evaluation of CCNA2's potential for inducing cardiac regeneration while addressing potential limitations and safety concerns.