MRPL13 Human

What is MRPL13 and what are its primary functions in human cells?

MRPL13 is a component of the mitochondrial ribosomal protein family, specifically the large (39S) subunit. It plays a crucial role in the synthesis of mitochondrial proteins encoded by mitochondrial DNA. Functionally, MRPL13 contributes to cellular energy metabolism through its involvement in oxidative phosphorylation and mitochondrial protein synthesis. Research has demonstrated that MRPL13 participates in several cellular processes including the cell proliferation cycle, migration, apoptosis, and autophagy, particularly in cancer cells . To investigate its function, researchers typically employ gene silencing techniques such as siRNA or shRNA, followed by functional assays to measure changes in cellular phenotypes.

How is MRPL13 expression regulated in normal human tissues?

MRPL13 expression in normal tissues appears to be tightly regulated through various molecular mechanisms. Analysis of expression data from databases such as UCSC XENA reveals tissue-specific patterns of MRPL13 expression across 33 different normal tissue types . The regulation likely involves transcription factors that control mitochondrial biogenesis and function. Methodologically, researchers can investigate this regulation through promoter analysis, chromatin immunoprecipitation (ChIP) assays to identify transcription factor binding, and reporter gene assays to validate regulatory elements. Additionally, examining epigenetic modifications through methylation analysis can reveal tissue-specific regulatory mechanisms controlling MRPL13 expression.

What experimental techniques are most effective for measuring MRPL13 protein levels in clinical samples?

For clinical samples, a multi-modal approach is recommended for accurately measuring MRPL13 levels. Quantitative reverse transcription PCR (qRT-PCR) provides sensitive detection of MRPL13 mRNA levels, while Western blot analysis offers protein-level confirmation . For tissue samples, immunohistochemistry (IHC) allows visualization of MRPL13 expression patterns and subcellular localization. When working with limited clinical material, techniques like immunofluorescence combined with confocal microscopy can provide both localization and semi-quantitative information. For large-scale studies, tissue microarrays combined with automated image analysis systems can efficiently process numerous samples while maintaining standardized quantification protocols.

How does MRPL13 contribute to cancer progression at the molecular level?

MRPL13 appears to promote cancer progression through multiple molecular mechanisms. Research indicates that MRPL13 influences several critical oncogenic pathways including MYC target activation, oxidative phosphorylation modulation, PI3K/AKT/mTOR signal transduction enhancement, and G2/M checkpoint regulation . In breast cancer, MRPL13 silencing inhibits proliferation by altering EMT-related gene expression patterns through reduction of AKT and mTOR phosphorylation . To investigate these mechanisms, researchers should employ pathway enrichment analysis of genes co-expressed with MRPL13, followed by experimental validation through targeted pathway inhibition. Protein-protein interaction studies using techniques like co-immunoprecipitation or proximity ligation assays can identify direct molecular partners of MRPL13, providing insight into its mechanistic role in cancer development.

What is the relationship between MRPL13 and immune infiltration in various cancer types?

Analysis across multiple cancer types indicates that MRPL13 expression significantly correlates with immune cell infiltration patterns. Using algorithms like TIMER, QUANTISEQ, and XCELL from various databases, researchers have found that MRPL13 expression influences the tumor immune microenvironment . Specifically, MRPL13 appears to promote the transformation of macrophages to the pro-tumorigenic M1 state while reducing the infiltration of anti-tumor T cells . To study this relationship, researchers should implement single-cell RNA sequencing of tumor samples stratified by MRPL13 expression levels, followed by computational deconvolution of immune cell populations. Spatial transcriptomics or multiplex immunofluorescence imaging can further validate these findings by examining the physical relationships between MRPL13-expressing tumor cells and infiltrating immune cell populations.

How can contradictory data regarding MRPL13 function across different cancer types be reconciled?

Contradictory findings regarding MRPL13 function across cancer types likely reflect context-dependent roles influenced by tissue-specific factors, genetic background, and tumor microenvironment. To reconcile these contradictions, researchers should implement a systematic multi-cancer comparative approach using matched experimental conditions. This would include:

• Performing parallel MRPL13 knockdown/overexpression experiments across multiple cancer cell lines derived from different tissues

• Conducting comprehensive transcriptomic and proteomic analyses to identify tissue-specific downstream effectors

• Validating findings in patient-derived xenograft models to capture microenvironmental influences

• Employing multi-omics integration techniques to identify conserved versus tissue-specific MRPL13-associated pathways
  This methodological approach enables identification of both the core conserved functions of MRPL13 and the context-dependent mechanisms that explain apparent contradictions in experimental results.

What bioinformatic pipelines are recommended for analyzing MRPL13 expression patterns across cancer datasets?

For comprehensive analysis of MRPL13 expression patterns, a multi-step bioinformatic pipeline is recommended:

• Data acquisition: Extract MRPL13 expression data from TCGA, UCSC XENA, and GEO databases, ensuring batch correction and normalization across datasets

• Differential expression analysis: Implement DESeq2 or limma packages to compare MRPL13 expression between tumor and normal tissues across cancer types

• Survival analysis: Apply Kaplan-Meier and Cox regression models using packages like survival and survminer to correlate MRPL13 expression with patient outcomes

• Co-expression network construction: Utilize WGCNA (Weighted Gene Co-expression Network Analysis) to identify genes with expression patterns correlated with MRPL13

• Functional enrichment: Apply ClusterProfiler package for GO and KEGG pathway analysis of co-expressed genes

• Immune infiltration analysis: Implement ssGSEA algorithm through the GSVA package to analyze immune cell infiltration patterns based on MRPL13 expression levels

• Visualization: Generate comprehensive visualizations using ggplot2 and ComplexHeatmap packages
  This pipeline provides a systematic approach to characterizing MRPL13's role across cancer types while enabling robust statistical comparisons.

What are the most effective techniques for silencing MRPL13 in experimental cancer models?

Based on the literature, several effective techniques for MRPL13 silencing have been validated:

• siRNA transfection: Provides transient silencing suitable for short-term experiments; typically achieves 70-90% knockdown efficiency when optimized

• shRNA lentiviral transduction: Enables stable long-term silencing for extended studies and in vivo experiments

• CRISPR/Cas9-mediated knockout: Most definitive approach for complete elimination of MRPL13 expression
  For optimal experimental design, researchers should:

• Include multiple targeting sequences to control for off-target effects

• Validate knockdown efficiency at both mRNA (qRT-PCR) and protein (Western blot) levels

• Include rescue experiments with MRPL13 re-expression to confirm phenotype specificity

• Consider inducible knockdown systems for studying genes like MRPL13 that may have essential functions
  In cellular models, knockdown of MRPL13 has been shown to significantly inhibit proliferation, delay tumor division and migration, reduce invasion capacity, and increase apoptosis in lung adenocarcinoma cell lines .

How can researchers effectively analyze the interaction between MRPL13 and mitochondrial function in cancer cells?

To comprehensively investigate MRPL13's impact on mitochondrial function in cancer cells, researchers should employ a multi-faceted experimental approach:

• Mitochondrial respiration analysis: Utilize Seahorse XF Analyzer to measure oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in cells with modulated MRPL13 expression

• Mitochondrial membrane potential: Assess using JC-1 or TMRM dyes combined with flow cytometry or live-cell imaging

• Mitochondrial morphology: Examine through transmission electron microscopy or confocal imaging with mitochondria-specific dyes

• Mitochondrial protein synthesis: Implement pulse-labeling with radioactive amino acids to measure translation rates of mitochondrially-encoded proteins

• ROS production: Measure using fluorescent probes like CM-H2DCFDA or MitoSOX Red

• mtDNA copy number: Quantify using qPCR with mitochondrial and nuclear DNA-specific primers
  Since MRPL13 functions in mitochondrial ribosomal protein synthesis, its knockout appears to affect oxidative phosphorylation pathways, as revealed by KEGG pathway analysis . This comprehensive approach would clarify how MRPL13 dysregulation impacts mitochondrial function in cancer progression.

How can MRPL13 expression be effectively utilized as a prognostic biomarker in cancer patients?

To implement MRPL13 as a clinically relevant prognostic biomarker, researchers should follow these methodological steps:

What are the most promising approaches for targeting MRPL13 therapeutically in cancer treatment?

Based on current research, several therapeutic approaches targeting MRPL13 show promise:

• Direct targeting strategies:

  • Small molecule inhibitors of MRPL13 function

  • Antisense oligonucleotides or siRNA-based therapeutics for expression knockdown

  • Proteolysis targeting chimeras (PROTACs) for selective protein degradation

• Indirect targeting approaches:

  • Inhibition of downstream signaling pathways activated by MRPL13 (PI3K/AKT/mTOR inhibitors)

  • Targeting synthetic lethal interactions with MRPL13 overexpression

  • Combination with immune checkpoint inhibitors, given MRPL13's influence on immune infiltration patterns

• Delivery considerations:

  • Nanoparticle-based delivery for RNA therapeutics

  • Cancer-specific promoters for targeted expression of inhibitory constructs

  • Cell-penetrating peptides for improved intracellular delivery
    Experimental validation in preclinical models indicates that MRPL13 knockdown significantly reduces cancer cell proliferation, migration, and invasion while increasing apoptosis , supporting its potential as a therapeutic target.

What are the most critical unanswered questions regarding MRPL13's role in cancer development?

Several critical questions remain unexplored in MRPL13 research:

• Upstream regulation: What factors control MRPL13 expression in normal versus cancer cells? Are there specific transcription factors or epigenetic mechanisms that drive its overexpression in tumors?

• Metabolic reprogramming: How does MRPL13 overexpression specifically alter mitochondrial metabolism to promote tumor growth? Does it create metabolic vulnerabilities that can be therapeutically exploited?

• Interactome mapping: What is the complete protein-protein interaction network of MRPL13 in different cancer contexts? How do these interactions contribute to its oncogenic functions?

• Role in therapy resistance: Does MRPL13 contribute to resistance against standard cancer therapies? The MRPL13-ALK fusion has been linked to acquired drug resistance in lung neuroendocrine tumors with EGFR mutation .

• Systemic effects: Does MRPL13 expression in tumor cells influence systemic metabolism or immune function beyond the local tumor microenvironment?
  Addressing these questions requires integrative approaches combining genomics, proteomics, metabolomics, and advanced imaging techniques in both preclinical models and patient samples.

How can single-cell analysis advance our understanding of MRPL13 function in tumor heterogeneity?

Single-cell technologies offer unprecedented opportunities to unravel MRPL13's role in tumor heterogeneity:

• Cellular resolution mapping: Single-cell RNA sequencing can map MRPL13 expression patterns across distinct cellular populations within tumors, revealing potential subpopulation-specific functions

• Trajectory analysis: Using pseudotime analysis, researchers can trace how MRPL13 expression changes during cancer evolution and metastatic progression

• Spatial context: Spatial transcriptomics techniques can reveal how MRPL13-expressing cells spatially interact with stromal and immune components within the tumor microenvironment

• Multi-omics integration: Combined single-cell genomics, transcriptomics, and proteomics can uncover how MRPL13 influences cellular phenotypes at multiple molecular levels

• Functional heterogeneity: Single-cell CRISPR screens targeting MRPL13 can identify context-dependent cellular responses within heterogeneous tumor populations
  Single-cell data analysis has already revealed that modules of metastasis, EMT, cell cycle, DNA repair, invasion, DNA damage, and proliferation positively correlate with MRPL13 expression in lung adenocarcinoma, while hypoxia and inflammation modules show negative correlation .