RPL35 Human

What is RPL35 and what is its primary function in human cells?

RPL35 is a component of the large 60S ribosomal subunit that participates in protein synthesis. It belongs to the L29P family of ribosomal proteins and is located in the cytoplasm. As part of the ribosome, RPL35 contributes to the translation machinery that converts mRNA into proteins. The ribosome consists of a small 40S subunit and a large 60S subunit, together composed of 4 RNA species and approximately 80 structurally distinct proteins . Gene Ontology annotations indicate that RPL35 possesses RNA binding and mRNA binding capabilities, which are essential for its function in translation .

How is RPL35 expression regulated across different tissues?

RPL35 expression follows tissue-specific patterns that can be visualized using dimensionality reduction techniques such as t-distributed stochastic neighbor embedding (t-SNE). Analysis of RNA-seq data from The Cancer Genome Atlas (TCGA) has shown that RPL35, along with other ribosomal proteins, displays expression patterns that strongly correlate with tissue type .

While Principal Component Analysis (PCA) can distinguish tissues based on RPL35 expression to some degree, t-SNE analysis more clearly identifies tissue-specific clusters due to its ability to detect non-linear relationships between ribosomal proteins . This tissue-specific regulation suggests that RPL35 may have specialized functions beyond its canonical role in protein synthesis that contribute to tissue identity and function.

What experimental models are recommended for studying RPL35 function?

Several experimental models have proven valuable for RPL35 research:

• Human cancer cell lines: Neuroblastoma cell lines such as BE(2)-C and Kelly cells are frequently used to study RPL35's role in cancer progression .

• E. coli expression systems: These are employed for producing recombinant RPL35 protein for structural and functional studies .

• RNA interference models: siRNA-mediated knockdown of RPL35 in cell culture is effective for examining functional consequences on protein synthesis, cell proliferation, and signaling pathways .

• Mouse models: NIH3T3 mouse fibroblasts have been used to study the transformative potential of ribosomal proteins in cancer contexts .

• Tumor xenograft models: These are valuable for evaluating the in vivo effects of RPL35 modulation on tumor growth and progression.

Each model offers distinct advantages for investigating different aspects of RPL35 biology, from basic molecular interactions to complex disease-related functions.

How does RPL35 contribute to cancer progression, particularly in neuroblastoma?

RPL35 promotes cancer progression in neuroblastoma through several mechanisms:

• Regulation of E2F1 translation: RPL35 binds to both long non-coding RNA lncNB1 and E2F1 mRNA, promoting E2F1 protein translation without affecting its mRNA levels . E2F1 is a transcription factor crucial for cell cycle progression.

• Activation of oncogenic signaling: RPL35 increases DEPDC1B protein expression, which enhances ERK protein phosphorylation and N-Myc protein phosphorylation at S62 . This signaling cascade promotes neuroblastoma cell proliferation and survival.

• Metabolic reprogramming: RPL35 functions as a positive regulator of aerobic glycolysis through the RPL35/ERK/HIF1α axis, supporting the high energy demands of rapidly proliferating cancer cells .

When RPL35 is knocked down in neuroblastoma cell lines, significant reductions are observed in DEPDC1B, N-Myc, and E2F1 protein expression, ERK phosphorylation, and N-Myc phosphorylation at S62 . These findings demonstrate that RPL35 acquires non-canonical functions in cancer cells that extend beyond its role in ribosome biogenesis and protein synthesis.

What is the relationship between RPL35 and long non-coding RNAs?

The interaction between RPL35 and long non-coding RNAs (lncRNAs) represents an emerging paradigm in translational regulation:

• LncNB1 interaction: Mass spectrometry analysis has revealed that lncNB1 specifically binds to RPL35 in neuroblastoma cells . This interaction has significant functional consequences for cancer progression.

• Mechanism of action: RNA immunoprecipitation assays have demonstrated that:

  • RPL35 protein binds to both lncNB1 RNA and E2F1 mRNA

  • Knockdown of lncNB1 reduces RPL35's binding to E2F1 mRNA

  • This suggests lncNB1 facilitates RPL35's interaction with E2F1 mRNA, promoting its translation

• Functional significance: The lncNB1-RPL35-E2F1 axis promotes neuroblastoma tumorigenesis by enhancing E2F1 protein synthesis, which drives cell proliferation .

This relationship illustrates how RPL35 can function beyond its conventional role in ribosome structure, participating in specialized translation regulation through interactions with lncRNAs. This mechanism may represent a broader paradigm of how ribosomal proteins acquire additional functions in disease contexts.

How does RPL35 influence key signaling pathways in cancer cells?

RPL35 has been identified as a key regulator of multiple signaling pathways involved in cancer progression:

• ERK pathway activation:

  • Studies in neuroblastoma have shown that RPL35 knockdown leads to reduced ERK phosphorylation

  • The mechanism involves RPL35's regulation of DEPDC1B expression, which activates ERK signaling

  • Activated ERK signaling promotes cell proliferation and survival

• HIF1α pathway regulation:

  • RPL35 functions as part of the RPL35/ERK/HIF1α axis in neuroblastoma

  • This signaling cascade promotes aerobic glycolysis, a metabolic hallmark of cancer

  • By influencing HIF1α, RPL35 contributes to metabolic reprogramming of cancer cells

• N-Myc stabilization:

  • RPL35 enhances N-Myc protein phosphorylation at S62, a modification that increases N-Myc stability

  • Stabilized N-Myc drives oncogenic transcriptional programs in neuroblastoma

These interconnected signaling effects demonstrate how RPL35 can exert wide-ranging influences on cellular behavior beyond its primary role in ribosome function. The integration of RPL35 into these signaling networks makes it a potential therapeutic target, particularly in cancers where these pathways are dysregulated.

What are the diagnostic and prognostic implications of RPL35 expression patterns?

RPL35 expression patterns have significant diagnostic and prognostic implications in cancer:

• Cancer classification models:

  • Artificial neural network (ANN) models based on ribosomal protein expression patterns, including RPL35, can classify tumors according to their tissue of origin with 93% accuracy

  • Logistic regression models can distinguish tumors from normal tissues with >98% accuracy

• Tumor subtyping:

  • Cancer cohorts possess subtypes with distinct RPL35 expression patterns that correlate with molecular markers and tumor phenotypes

  • These subtypes may indicate different clinical behaviors and therapeutic responses

• Prognostic stratification:

  • Patterns of ribosomal protein expression correlate with patient survival in various cancer types

  • Logistic regression models can stratify certain cancers (like uterine and kidney clear cell tumors) according to prognostic group with >95% accuracy

• Tissue-of-origin identification:

  • While tumors show altered RPL35 expression compared to normal tissues, they retain sufficient tissue-specific patterns to allow their origin to be identified

  • This is valuable for classifying cancers of unknown primary origin

These findings suggest that analyzing RPL35 expression as part of broader ribosomal protein expression patterns could become an important tool in cancer diagnostics, prognostication, and therapeutic decision-making.

What techniques are optimal for studying RPL35 protein-RNA interactions?

Several complementary approaches can be used to characterize RPL35 protein-RNA interactions:

• RNA Immunoprecipitation (RIP):

  • This technique has successfully demonstrated RPL35 binding to both lncNB1 RNA and E2F1 mRNA

  • Protocol: Cells are lysed, and RPL35 protein is immunoprecipitated using a specific anti-RPL35 antibody. Associated RNAs are isolated and analyzed by RT-PCR

  • Control: Parallel immunoprecipitation with control IgG identifies non-specific binding

• Biotin-labeled RNA pull-down:

  • Identifies proteins that bind to specific RNAs of interest

  • Protocol: RNA is in vitro-transcribed with biotin labeling, incubated with cell lysates, and protein-RNA complexes are captured using streptavidin beads. Bound proteins are identified by mass spectrometry

  • This method identified RPL35 as a binding partner of lncNB1 in neuroblastoma cells

• Cross-linking and Immunoprecipitation (CLIP):

  • CLIP methods (including HITS-CLIP, PAR-CLIP, or iCLIP) provide higher resolution mapping of protein-RNA interaction sites

  • These techniques involve UV cross-linking of protein-RNA complexes in live cells, followed by immunoprecipitation and sequencing

• Functional validation assays:

  • Puromycin incorporation assays can measure the impact of RPL35-RNA interactions on protein synthesis

  • siRNA-mediated knockdown of RPL35 followed by assessment of target RNA translation provides evidence for functional significance

A comprehensive approach combining multiple methods provides more robust evidence for specific RPL35-RNA interactions and their functional consequences.

How can RPL35 expression be effectively modulated in experimental settings?

Several approaches are available for modulating RPL35 expression in experimental settings:

• RNA interference (RNAi):

  • siRNA transfection: Multiple studies have successfully used siRNAs targeting RPL35. Research has employed independent siRNAs to knock down RPL35 in neuroblastoma cell lines

  • shRNA expression: For stable knockdown, shRNAs can be delivered via lentiviral vectors

  • Advantages: Relatively easy to implement, cost-effective

  • Limitations: Incomplete knockdown, potential off-target effects

• CRISPR-Cas9 genome editing:

  • For complete knockout or knock-in studies

  • Can be used to introduce specific mutations or regulatory elements

  • Advantages: Complete loss of protein expression, ability to create stable cell lines

• Overexpression systems:

  • Plasmid-based expression using vectors with strong promoters

  • Inducible expression systems for temporal control

  • Recombinant protein production: RPL35 has been successfully produced in E. coli expression systems

• Rescue experiments:

  • Combining knockdown of endogenous RPL35 with expression of siRNA-resistant RPL35 variants

  • Essential for confirming specificity of observed phenotypes

When modulating RPL35 expression, researchers should carefully consider potential compensatory mechanisms by other ribosomal proteins and effects on global protein synthesis that may confound interpretation of specific RPL35 functions.

What are the best approaches for investigating RPL35's role in neuroblastoma progression?

To effectively investigate RPL35's role in neuroblastoma progression, a multi-faceted experimental approach is recommended:

• Expression analysis in clinical samples:

  • Quantify RPL35 expression in neuroblastoma tumors versus normal tissue

  • Correlate expression with clinical parameters (stage, MYCN amplification status, patient outcome)

  • Methods: Immunohistochemistry, RT-qPCR, or mining public neuroblastoma datasets

• Functional studies in cell lines:

  • Modulate RPL35 expression using siRNA or CRISPR-Cas9 in neuroblastoma cell lines (e.g., BE(2)-C, Kelly)

  • Assess effects on:

    • Proliferation: MTT/MTS assays, BrdU incorporation

    • Survival: Annexin V/PI staining, caspase activation assays

    • Colony formation: Soft agar assays, clonogenic assays

• Mechanistic investigations:

  • Analyze RPL35's effect on the lncNB1-E2F1 axis:

    • RNA immunoprecipitation to assess RPL35 binding to lncNB1 and E2F1 mRNA

    • Western blotting to measure E2F1, DEPDC1B, and N-Myc protein levels

  • Examine signaling pathway effects:

    • Assess ERK and N-Myc phosphorylation status after RPL35 modulation

    • Evaluate metabolic changes through the RPL35/ERK/HIF1α axis

• Translation-specific analyses:

  • Polysome profiling to assess global translation

  • Puromycin incorporation assays to measure protein synthesis rates

  • Ribosome profiling to identify specifically affected mRNAs

• In vivo studies:

  • Xenograft models with RPL35-modulated neuroblastoma cells

  • Monitor tumor growth, metastasis, and survival

  • Assess potential therapeutic targeting of the RPL35/ERK/HIF1α axis

This comprehensive approach enables researchers to establish RPL35's role in neuroblastoma from multiple angles, strengthening the evidence for its contribution to disease progression and therapeutic potential.

How can bioinformatic approaches be used to analyze RPL35 expression patterns?

Bioinformatic approaches offer powerful tools for analyzing RPL35 expression patterns across tissues and diseases:

• Dimensionality reduction techniques:

  • t-distributed stochastic neighbor embedding (t-SNE) has been shown to effectively identify tissue-specific and cancer-specific clusters based on ribosomal protein expression patterns, including RPL35

  • This approach outperforms Principal Component Analysis (PCA) for distinguishing tissue types based on ribosomal protein expression profiles

• Machine learning classification models:

  • Artificial neural network (ANN) models based on ribosomal protein expression can classify tumors by tissue of origin with 93% accuracy

  • Logistic regression models can:

    • Distinguish tumors from normal tissues with >98% accuracy

    • Identify specific cancer subtypes (e.g., glioblastoma multiforme) with up to 100% accuracy

    • Stratify prognostic groups with >95% accuracy

• Correlation analysis:

  • RPL35 expression can be correlated with:

    • Expression of other genes to identify co-regulated pathways

    • Clinical parameters to identify prognostic associations

    • Molecular subtypes to understand disease heterogeneity

• Multi-omics integration:

  • Combining RPL35 expression data with:

    • Genomic data (mutations, copy number alterations)

    • Proteomic data (protein levels, post-translational modifications)

    • Clinical data (survival, treatment response)

• Network analysis:

  • Constructing protein-protein interaction networks to understand RPL35's functional connections

  • Pathway enrichment analysis to identify biological processes associated with RPL35 dysregulation

These bioinformatic approaches can provide insights into RPL35's tissue-specific functions, role in disease processes, and potential as a biomarker or therapeutic target.

What is known about RPL35's association with Diamond-Blackfan Anemia?

RPL35 has been associated with Diamond-Blackfan Anemia 19 (DBA19), a rare congenital bone marrow failure syndrome characterized by red blood cell aplasia . Key aspects of this association include:

• Genetic basis:

  • DBA19 is linked to mutations in the RPL35 gene

  • This represents one form of DBA, with mutations in different ribosomal protein genes accounting for other forms

  • The OMIM database lists RPL35 under entry 618315 in association with DBA

• Pathophysiological mechanism:

  • Mutations in RPL35 impair ribosome biogenesis

  • This leads to nucleolar stress and activation of p53-dependent apoptosis

  • Erythroid progenitor cells are particularly sensitive to this stress, explaining the predominantly erythroid phenotype

• Clinical implications:

  • Patients typically present with macrocytic anemia in infancy

  • Associated congenital anomalies may be present

  • Knowledge of the specific genetic cause (RPL35 mutation) can guide genetic counseling and family screening

• Relationship to other DBA forms:

  • DBA19 (RPL35-associated) shares clinical features with other forms of DBA

  • This reinforces the central role of ribosome biogenesis in erythropoiesis

  • It also highlights how mutations in different ribosomal proteins can lead to similar clinical phenotypes

This association between RPL35 and DBA demonstrates how disruption of ribosomal proteins can have tissue-specific effects despite their ubiquitous expression, and underscores the critical importance of proper ribosome biogenesis in erythropoiesis.

How is RPL35 dysregulation linked to specific cancer types?

RPL35 dysregulation has been linked to multiple cancer types:

• Neuroblastoma:

  • RPL35 promotes neuroblastoma progression through the lncNB1-RPL35-E2F1 axis

  • It enhances E2F1 protein translation, which drives cell proliferation

  • RPL35 also activates the ERK signaling pathway and stabilizes N-Myc protein

  • The RPL35/ERK/HIF1α axis promotes aerobic glycolysis in neuroblastoma cells

• Cancer type identification:

  • t-SNE analysis of ribosomal protein expression patterns, including RPL35, can distinguish between different cancer types

  • These patterns differ from normal tissues but retain sufficient tissue-specific characteristics to identify the tissue of origin

• Cancer subtypes:

  • Some cancer cohorts show subtypes with distinct RPL35 expression patterns

  • These subtypes correlate with molecular markers, tumor phenotypes, and survival outcomes

  • For example, some tumors (143 tumors from 15 cohorts) show amplification and relative up-regulation of RPL35 along with other ribosomal proteins

• Her2/Neu-amplified cancers:

  • A distinct cluster of tumors shows amplification and relative up-regulation of RPL19, RPL23, and ERBB2 (Her2/Neu) along with RPL35

  • This suggests a potential relationship between RPL35 and Her2/Neu-driven oncogenesis

The diverse roles of RPL35 across cancer types highlight how this ribosomal protein contributes to cancer biology through both canonical functions in protein synthesis and non-canonical roles in specific oncogenic pathways.

What is the role of RPL35 in tumor metabolism and aerobic glycolysis?

RPL35 has emerged as a significant regulator of tumor metabolism, particularly aerobic glycolysis (the Warburg effect):

• The RPL35/ERK/HIF1α axis:

  • Research has identified RPL35 as a component of a signaling axis involving ERK and HIF1α

  • This pathway promotes aerobic glycolysis in cancer cells, particularly in neuroblastoma

  • The mechanism involves RPL35's regulation of ERK activity, which subsequently affects HIF1α

• Metabolic reprogramming:

  • By enhancing glycolysis, RPL35 facilitates the metabolic shift that provides cancer cells with:

    • Rapid ATP production

    • Biosynthetic intermediates for macromolecule synthesis

    • Reduced reactive oxygen species generation

  • This metabolic adaptation supports the high proliferation rates observed in many cancers

• Experimental evidence:

  • Studies have shown that RPL35 functions as a positive regulator of aerobic glycolysis

  • Knockdown of RPL35 in neuroblastoma cells reduces glycolytic activity

• Therapeutic implications:

  • The identification of RPL35 as a regulator of cancer metabolism suggests it could be a therapeutic target

  • Inhibiting the RPL35/ERK/HIF1α axis might reverse the metabolic adaptations that support cancer growth

  • This axis "could be a potential therapeutic target for the therapy of NB"

This metabolic role adds another dimension to RPL35's contributions to cancer progression, beyond its effects on protein synthesis and specific oncogenic pathways. It suggests that RPL35 helps coordinate cellular growth signals with the metabolic adaptations required to sustain rapid proliferation in cancer cells.

What are promising therapeutic approaches targeting RPL35 and its pathways?

Several therapeutic approaches targeting RPL35 and its associated pathways show promise for cancer treatment:

• Direct targeting of RPL35:

  • RNA interference-based therapies (siRNA, shRNA) targeting RPL35 have shown efficacy in preclinical models

  • Development of small molecule inhibitors that disrupt RPL35's non-canonical functions while preserving essential ribosomal functions

• Targeting the lncNB1-RPL35-E2F1 axis:

  • Disrupting the interaction between lncNB1 and RPL35 could inhibit E2F1 translation

  • E2F1 inhibitors could complement RPL35-targeted approaches in neuroblastoma

• Inhibiting downstream pathways:

  • ERK pathway inhibitors could counteract the effects of RPL35-mediated ERK activation

  • HIF1α inhibitors might reverse the metabolic reprogramming promoted by the RPL35/ERK/HIF1α axis

• Combination therapies:

  • Combining RPL35-targeted treatments with standard chemotherapy agents

  • Simultaneous targeting of multiple components of the RPL35/ERK/HIF1α pathway

  • Incorporating metabolic inhibitors that target the glycolytic phenotype promoted by RPL35

• Biomarker-guided approaches:

  • Using RPL35 expression patterns to identify patients most likely to respond to specific therapies

  • Monitoring changes in RPL35-associated pathways as markers of treatment response

These approaches highlight the potential of RPL35 as a therapeutic target, particularly in cancers where its non-canonical functions contribute significantly to disease progression.

What aspects of RPL35 function remain to be elucidated?

Despite growing understanding of RPL35's functions, several key aspects remain to be fully elucidated:

• Tissue-specific functions:

  • The mechanisms underlying tissue-specific expression patterns of RPL35

  • Why mutations in RPL35 affect some tissues (like erythroid progenitors) more than others

  • The role of RPL35 in tissue development and differentiation

• Regulatory mechanisms:

  • How RPL35 expression and activity are regulated under normal and stress conditions

  • The role of post-translational modifications in modulating RPL35 function

  • Factors that control RPL35's incorporation into ribosomes versus engagement in non-canonical functions

• RNA specificity:

  • The full spectrum of RNAs that interact with RPL35

  • Structural features that determine RPL35's binding specificity

  • How RPL35 selectively influences translation of specific mRNAs

• Cancer heterogeneity:

  • Why RPL35 expression patterns vary across cancer types and subtypes

  • The context-dependent effects of RPL35 dysregulation in different malignancies

  • How tumor microenvironment influences RPL35 function

• Therapeutic targeting:

  • Strategies for selectively targeting RPL35's non-canonical functions

  • Approaches to overcome potential resistance mechanisms

  • Biomarkers predicting response to RPL35-targeted therapies

Addressing these knowledge gaps will require integrated approaches combining structural biology, functional genomics, systems biology, and translational research. Advances in these areas will enhance our understanding of RPL35's roles in normal physiology and disease pathogenesis.