Target Name: RPL36A-HNRNPH2
NCBI ID: G100529097
Review Report on RPL36A-HNRNPH2 Target / Biomarker Content of Review Report on RPL36A-HNRNPH2 Target / Biomarker
RPL36A-HNRNPH2
Other Name(s): RPL36A-HNRNPH2 readthrough | RPL36A-HNRNPH2 variant 1 | RPL36A-HNRNPH2 readthrough, transcript variant 1 | Protein RPL36A-HNRNPH2 | RPL36A-HNRNPH2 protein | RPL36A-HNRNPH2 readthrough (isoform a)

Introduction to RPL36A-HNRNPH2

RPL36A-HNRNPH2, strongly abbreviated as R-H2, is an emerging drug target and biomarker that has gained significant attention in recent years. This article aims to explore the potential of targeting R-H2 as a therapeutic approach and investigate its utility as a biomarker for various diseases. The in-depth understanding of RPL36A-HNRNPH2 can provide valuable insights into its role in cell processes, disease progression, and the development of innovative therapeutic strategies.

The significance of RPL36A-HNRNPH2 as a Drug Target:

RPL36A-HNRNPH2, a protein complex formed by the interaction between ribosomal protein L36a (RPL36A) and heterogeneous nuclear ribonucleoprotein H2 (HNRNPH2), plays a crucial role in various cellular processes, including mRNA processing, transport, and translation. Dysregulation of R-H2 has been implicated in several diseases, making it an attractive target for drug development.

Studies have shown that aberrant expression of R-H2 is associated with cancer progression and metastasis. For instance, in breast cancer, RPL36A-HNRNPH2 overexpression has been observed, leading to the activation of oncogenic signaling pathways and increased tumor cell proliferation. Thus, targeting R-H2 could potentially disrupt these pathways and inhibit cancer growth. Additionally, R-H2 has been implicated in drug resistance mechanisms, making it a promising target for overcoming chemotherapy resistance in cancer therapy.

Furthermore, R-H2 has also been linked to neurodegenerative diseases such as Alzheimer's and Parkinson's disease. Dysregulation of R-H2 in these conditions contributes to the aberrant splicing and accumulation of disease-associated proteins, leading to neuronal dysfunction and cell death. By targeting R-H2, it may be possible to modulate aberrant splicing events and prevent the accumulation of toxic protein aggregates, offering a potential therapeutic avenue for neurodegenerative diseases.

The Potential of RPL36A-HNRNPH2 as a Biomarker:

In addition to its role as a drug target, RPL36A-HNRNPH2 holds promise as a biomarker for various diseases. Biomarkers are measurable indicators that aid in disease diagnosis, prognosis, and monitoring treatment response. The identification of reliable biomarkers is essential for early detection and effective management of diseases.

In cancer, the aberrant expression of RPL36A-HNRNPH2 has been correlated with poor prognosis and survival outcomes. Increased levels of R-H2 in tumor tissues have been associated with aggressive tumor growth, lymph node metastasis, and reduced overall survival in various cancers, including breast, lung, and colorectal cancer. Therefore, measuring R-H2 expression levels could provide a valuable tool for predicting disease progression, selecting appropriate treatment strategies, and monitoring therapeutic effectiveness.

Moreover, R-H2 has also shown potential as a biomarker in neurodegenerative diseases. Studies have revealed altered R-H2 expression profiles in the brain tissues of individuals with Alzheimer's and Parkinson's disease. These changes in R-H2 levels correlate with disease severity and cognitive decline. Consequently, R-H2 could serve as a biomarker for early disease detection, monitoring disease progression, and assessing treatment response in neurodegenerative disorders.

Challenges and Future Perspectives:

While the potential of RPL36A-HNRNPH2 as both a drug target and a biomarker is promising, several challenges need to be addressed to translate this knowledge into clinical applications. One major challenge is the development of specific inhibitors that can selectively target R-H2 without affecting other important cellular processes. Additionally, optimizing the delivery of targeted therapies to the desired tissues and minimizing off-target effects is crucial for successful clinical implementation.

Furthermore, the standardization of R-H2 measurement techniques and validation in large patient cohorts are necessary to establish its reliability as a biomarker. Implementation of these biomarkers in routine clinical practice will require extensive validation studies and integration into existing diagnostic and treatment algorithms.

In conclusion, RPL36A-HNRNPH2, a protein complex involved in vital cellular processes, holds significant potential as both a drug target and a biomarker. Targeting R-H2 could provide novel therapeutic strategies for various diseases, including cancer and neurodegenerative disorders. Additionally, measuring R-H2 expression levels could serve as a valuable biomarker for disease diagnosis, prognosis, and treatment response assessment. By further exploring the roles of RPL36A-HNRNPH2, researchers can unravel its full potential and pave the way for personalized medicine approaches in the future.

Protein Name: RPL36A-HNRNPH2 Readthrough

The "RPL36A-HNRNPH2 Target / Biomarker Review Report" is a customizable review of hundreds up to thousends of related scientific research literature by AI technology, covering specific information about RPL36A-HNRNPH2 comprehensively, including but not limited to:
•   general information;
•   protein structure and compound binding;
•   protein biological mechanisms;
•   its importance;
•   the target screening and validation;
•   expression level;
•   disease relevance;
•   drug resistance;
•   related combination drugs;
•   pharmacochemistry experiments;
•   related patent analysis;
•   advantages and risks of development, etc.
The report is helpful for project application, drug molecule design, research progress updates, publication of research papers, patent applications, etc. If you are interested to get a full version of this report, please feel free to contact us at BD@silexon.ai

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