Spermatogenic Failure 32 (SPGF32) Cell Models for Research
Disease Burden and Research Significance
Spermatogenic Failure 32 (SPGF32) is a rare genetic disorder characterized by male infertility due to defective spermatogenesis. The global prevalence is not well-defined, but it is estimated to affect a small fraction of infertile men. According to the World Health Organization (WHO), infertility affects approximately 15% of couples worldwide, with male factors contributing to about 50% of cases. SPGF32 is caused by mutations in the TEX14 gene, which is essential for intercellular bridges during spermatogenesis. The clinical impact is significant, leading to azoospermia or severe oligozoospermia, and affected individuals require assisted reproductive technologies. There is no cure, and research focuses on understanding the molecular mechanisms and developing potential therapies.
SPGF32 serves as an excellent model for studying spermatogenesis and male infertility. The TEX14 gene is highly conserved across species, and its knockout in mice recapitulates the human phenotype. Research on SPGF32 can provide insights into the regulation of germ cell division, intercellular communication, and the development of therapeutic strategies for infertility. Public datasets, such as those from the Genotype-Tissue Expression (GTEx) project, provide expression data for TEX14 in testicular tissues, facilitating mechanistic studies. Open questions include the role of TEX14 in other tissues and the potential for gene therapy.
Core Molecular Pathogenesis
Although SPGF32 is not a cancer, the molecular pathways involved in spermatogenesis are often dysregulated in testicular cancers. Key pathways include:
- • PI3K/AKT signaling: Regulates cell survival and proliferation. Mutations in this pathway are common in testicular germ cell tumors.
- • MAPK/ERK pathway: Involved in cell differentiation and proliferation. Aberrant activation is seen in various cancers.
- • Wnt/β-catenin signaling: Plays a role in stem cell maintenance and differentiation. Dysregulation is linked to tumorigenesis.
- • Apoptosis pathways: Defects in apoptosis can lead to accumulation of abnormal germ cells.
| Gene | Frequency (%) | Mutation Type | Functional Effect |
|---|---|---|---|
| TEX14 | ~100% in SPGF32 | Loss-of-function (nonsense, frameshift) | Disruption of intercellular bridges, impaired spermatogenesis |
| KIT | 10-20% in testicular cancer | Activating mutations | Increased proliferation |
| KRAS | 5-10% in testicular cancer | Point mutations | Activation of MAPK pathway |
| TP53 | 10-15% in testicular cancer | Loss-of-function | Defective apoptosis |
Data from TCGA and COSMIC databases.
In SPGF32, the primary defect is the loss of TEX14, which disrupts intercellular bridges between spermatids. This leads to:
- • Impaired syncytial development: Spermatids fail to share cytoplasmic components, leading to abnormal sperm.
- • Altered gene expression: Transcription factors involved in spermatogenesis are dysregulated.
- • Mitochondrial dysfunction: Affects energy production for sperm motility.
In testicular cancers, common deregulated networks include:
- • PI3K/AKT/mTOR: Promotes cell survival and growth.
- • RAS/RAF/MEK/ERK: Drives proliferation.
- • Wnt/β-catenin: Regulates stemness and differentiation.
Experimental Model Systems
| Cell Line | Origin | Key Mutations |
|---|---|---|
| TCam-2 | Testicular seminoma | KIT mutation, TP53 wild-type |
| 2102Ep | Testicular embryonal carcinoma | TP53 mutation, KRAS mutation |
| NT2/D1 | Testicular teratocarcinoma | TP53 mutation, KRAS mutation |
Organoids derived from testicular tissue are emerging as more physiologically relevant models, allowing the study of spermatogenesis in a 3D context. They can be generated from patient-derived samples and recapitulate key features of the disease.
- • Patient-derived xenografts (PDX): Not commonly used for SPGF32 due to the non-cancerous nature, but can be used for testicular tumors.
- • Genetically engineered mouse models (GEMM): TEX14 knockout mice exhibit azoospermia, mimicking the human condition.
- • Induced models: Chemical or hormonal induction of spermatogenic failure in rodents.
CRISPR-based gene editing enables the creation of isogenic cell lines with specific TEX14 mutations. These models are invaluable for studying the functional consequences of mutations. For example:
- • TEX14 knockout cell lines: Generated by introducing frameshift mutations via CRISPR, leading to loss of protein expression.
- • TEX14 point mutation knock-in lines: Mimic specific patient mutations, allowing the study of hypomorphic alleles.
These engineered cell models are commercially available from various sources and are sequence-verified to ensure accuracy. They accelerate research by providing consistent, reproducible models for drug screening and functional studies.
Related Disease
| Disease name | Disease type |
|---|
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| CFAP43 Knockout HEK293 Cell Line | EDJ-KQ9490 | Human | 80217 | Details Get a Quote |
| SOHLH1 Knockout HEK293 Cell Line | EDJ-KQ11668 | Human | 402381 | Details Get a Quote |
| CFAP43 Knockout HCT 116 Cell Line | EDJ-KQ36221 | Human | 80217 | Details Get a Quote |
| CFAP43 Knockout HeLa Cell Line | EDJ-KQ57310 | Human | 80217 | Details Get a Quote |
| SOHLH1 Knockout HeLa Cell Line | EDJ-KQ60323 | Human | 402381 | Details Get a Quote |
| CFAP43 Knockout A-549 Cell Line | EDJ-KQ65817 | Human | 80217 | Details Get a Quote |
| SOHLH1 Knockout A-549 Cell Line | EDJ-KQ68790 | Human | 402381 | Details Get a Quote |
| SOHLH1 Knockout HCT 116 Cell Line | EDJ-KQ77153 | Human | 402381 | Details Get a Quote |
Applications of Gene-Edited Cells
Gene-edited cell lines are used to validate the role of TEX14 in spermatogenesis. By knocking out TEX14 in testicular cell lines, researchers can observe changes in cell viability, proliferation, and differentiation. For example, TEX14 knockout in TCam-2 cells leads to reduced expression of spermatogenesis markers and altered cell cycle progression. These models help identify downstream targets and pathways.
Isogenic pairs (wild-type vs. TEX14 knockout) are used in high-throughput screens to identify compounds that rescue the defective phenotype. For instance, small molecules that enhance intercellular bridge formation could be potential therapeutic leads. Additionally, these models can be used to test drugs that target spermatogenesis, such as hormonal therapies, and to study resistance mechanisms in testicular cancer.
CRISPR-based synthetic lethality screens can identify genes that are essential in TEX14-deficient cells but not in wild-type cells. This approach can uncover novel therapeutic targets for SPGF32 and related conditions. For example, a screen might reveal that TEX14-deficient cells are sensitive to inhibitors of DNA repair pathways, suggesting a potential treatment strategy.
Public Data Resources
| Database | URL | Description |
|---|---|---|
| TCGA | https://portal.gdc.cancer.gov/ | The Cancer Genome Atlas provides genomic, transcriptomic, and clinical data for various cancers, including testicular germ cell tumors. |
| cBioPortal | https://www.cbioportal.org/ | Visualization and analysis of cancer genomics data, including mutation frequencies and co-occurrence. |
| DepMap | https://depmap.org/portal/ | Dependency Map provides CRISPR screens and RNAi data for cancer cell lines, aiding in identifying vulnerabilities. |
| GEO | https://www.ncbi.nlm.nih.gov/geo/ | Gene Expression Omnibus stores high-throughput gene expression data, including studies on spermatogenesis. |