This document provides an overview of key signaling pathways involved in Non-Small Cell Lung Cancer (NSCLC). The information and pathway diagrams are based on the KEGG Non-Small Cell Lung Cancer pathway. You can view the full KEGG pathway diagram here.
Each section includes a brief description of the pathway's role, a link to view the DOT code for generating the diagram, and the resulting image.
The ERK (Extracellular signal-Regulated Kinases) pathway is a critical signaling cascade in NSCLC. It's often dysregulated due to mutations in EGFR, KRAS, or the presence of oncogenic fusion proteins like EML4-ALK. This pathway plays a crucial role in cell proliferation and survival.
View ERK Signaling Pathway DOT code
The PI3K (Phosphatidylinositol 3-Kinase) pathway is another crucial signaling cascade in NSCLC. It's often activated by receptor tyrosine kinases or RAS proteins and promotes cell survival and growth. Dysregulation of this pathway can lead to increased cell survival and resistance to apoptosis.
View PI3K Signaling Pathway DOT code
The Calcium signaling pathway plays a significant role in cell proliferation and is interconnected with other important signaling cascades in NSCLC. It can be activated by growth factor receptors and contributes to the activation of proteins involved in cell cycle progression.
View Calcium Signaling Pathway DOT code
The Cell Cycle pathway is often dysregulated in NSCLC, leading to uncontrolled cell division. Key components of this pathway, such as CDK4/6 and Cyclin D, are frequently altered in lung cancer, resulting in continuous cell cycle progression.
View Cell Cycle Pathway DOT code
The JAK-STAT pathway is involved in cell survival and proliferation in NSCLC, often activated by oncogenic drivers like EML4-ALK. This pathway contributes to cancer cell survival and may play a role in resistance to certain targeted therapies.
View JAK-STAT Signaling Pathway DOT code
RAS signaling extends beyond the ERK pathway and includes interactions with tumor suppressors like RASSF1. These additional RAS-mediated pathways can influence apoptosis and cell cycle progression, contributing to the complex signaling network in NSCLC.
View Other RAS Signaling Pathways DOT code
Transcriptional regulation, particularly through p53, plays a crucial role in NSCLC development and progression. p53 is a key tumor suppressor that regulates genes involved in cell cycle arrest, DNA repair, and apoptosis. Its dysfunction can lead to genomic instability and uncontrolled cell growth.
View Transcription Regulation DOT code
These signaling pathways and their interactions form a complex network that drives NSCLC pathogenesis. Understanding these pathways is crucial for developing targeted therapies and overcoming drug resistance in NSCLC treatment.
For a comprehensive overview of all these pathways and their interactions, refer to the original KEGG Non-Small Cell Lung Cancer pathway diagram linked at the beginning of this document.
Data, information, knowledge and principle: back to metabolism in KEGG
@article{10.1093/nar/gkt1076,
author = {Kanehisa, Minoru and Goto, Susumu and Sato, Yoko and Kawashima, Masayuki and Furumichi, Miho and Tanabe, Mao},
title = "{Data, information, knowledge and principle: back to metabolism in KEGG}",
journal = {Nucleic Acids Research},
volume = {42},
number = {D1},
pages = {D199-D205},
year = {2013},
month = {11},
abstract = "{In the hierarchy of data, information and knowledge, computational methods play a major role in the initial processing of data to extract information, but they alone become less effective to compile knowledge from information. The Kyoto Encyclopedia of Genes and Genomes (KEGG) resource (http://www.kegg.jp/ or http://www.genome.jp/kegg/) has been developed as a reference knowledge base to assist this latter process. In particular, the KEGG pathway maps are widely used for biological interpretation of genome sequences and other high-throughput data. The link from genomes to pathways is made through the KEGG Orthology system, a collection of manually defined ortholog groups identified by K numbers. To better automate this interpretation process the KEGG modules defined by Boolean expressions of K numbers have been expanded and improved. Once genes in a genome are annotated with K numbers, the KEGG modules can be computationally evaluated revealing metabolic capacities and other phenotypic features. The reaction modules, which represent chemical units of reactions, have been used to analyze design principles of metabolic networks and also to improve the definition of K numbers and associated annotations. For translational bioinformatics, the KEGG MEDICUS resource has been developed by integrating drug labels (package inserts) used in society.}",
issn = {0305-1048},
doi = {10.1093/nar/gkt1076},
url = {https://doi.org/10.1093/nar/gkt1076},
eprint = {https://academic.oup.com/nar/article-pdf/42/D1/D199/3561927/gkt1076.pdf},
}