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KRAS proto-oncogene, GTPase (KRAS) is a gene that encodes the protein K-Ras (KRAS), involved in multiple signaling pathways that regulate cell proliferation, differentiation, and survival. KRAS is a member of the RAS gene family, which encodes a group of related proteins that play roles in intracellular signal transduction.
The KRAS protein is a GTPase (enzyme that hydrolyzes guanosine triphosphate) that serves as a molecular switch by cycling between active, guanosine triphosphate (GTP)- bound and inactive, guanosine diphosphate (GDP)-bound states in response to extracellular stimuli [1].
Mutations in KRAS are commonly associated with various types of cancer, including pancreatic, colorectal, and lung cancer. These mutations can lead to constitutively active proteins, contributing to uncontrolled cell growth and tumor development.
KRAS mutations are molecularly diverse and heterogeneous, with various nucleotide changes occurring at different codons, and some being more prevalent than others in different types of cancer (Figure 1). KRAS mutations are generally mutually exclusive with other driver mutations such as EGFR and ALK, although co-mutations in other pathways have been observed [2].
In nonsquamous non-small cell lung cancer (NSCLC), activating mutations in KRAS are found in 25 to 30% of cases, representing the most prevalent oncogenic driver in NSCLC [3]. Among KRAS mutations, KRAS p.G12C (G12C), a single-nucleotide variant with glycine substituted by cysteine at codon 12, is the most frequent, with a prevalence of approximately 13% in lung adenocarcinoma [4].
However, geographic variation in prevalence has been reported, and specific mutations may be associated with smoking [4-6]. Though less common, additional KRAS mutations outside of codon 12, including codons 13 and 61, have been identified.
Figure 1. Prevalence of oncogenic drivers in NSCLC and frequency of KRAS variants [5,7].
Mutations in codon 12 interfere with GTP hydrolysis, favoring the GTP-bound activated state and uncontrolled cell growth independent of extracellular stimulation (Figure 2). KRAS p.G12C mutations are generally considered driver events, which arise early in disease pathogenesis and stay throughout disease progression [8].
Because of the high frequency of its variants in cancers, KRAS has been an active area of research for therapeutic development. However, the high affinity of KRAS for GTP and the high intracellular concentration of GTP, along with the lack of binding pockets on GTP-bound KRAS, has led to the long-standing notion that mutant KRAS is challenging to target [1].
This challenge in developing effective approaches for targeting KRAS-mutant lung adenocarcinomas lies in the diversity of KRAS mutations. The heterogeneity in their biology and the mechanisms underlying this diverse biological behavior are not well understood [9].
Furthermore, co-alterations in KRAS may have significant implications for disease progression, and research on mechanisms of resistance, such as secondary mutations or alternate activation pathways, is a complex and evolving area. Thus, research focusing on co-alterations and mechanisms of resistance may elucidate complex interactions and provide insight into the development and progression of cancer.
Figure 2. KRAS signaling pathway [10].
Various testing methodologies are available for detecting KRAS mutations in NSCLC. These include polymerase chain reaction (PCR), Sanger sequencing, and next-generation sequencing (NGS), and formalin-fixed, paraffin-embedded (FFPE) specimens from tissue biopsies or cytology samples are often used in research. More recently, liquid biopsy has emerged as a viable option for molecular testing in the absence of tissue specimens.
NGS is becoming an invaluable method in clinical research, particularly with NSCLC, for its ability to simultaneously analyze multiple genes from limited tumor material. In order to systematically address the heterogeneity and study co-occurring genomic events, the use of NGS is essential. Additionally, related to the increasing number of genes of interest, broad molecular profiling with NGS has been shown to be more cost-effective than single-gene tests [11].
While multiple NGS platforms are available, each differing in panel size, tissue input requirements, and turnaround time, the success of the test is more likely when a technology is appropriately selected taking into consideration the tumor quality and quantity of the sample.
Oncomine Solutions are complete end-to-end NGS workflows, including bioinformatics, for precision oncology research. Requiring as little as 10 ng of DNA or RNA, Oncomine Solutions can generate results from limited tissue and small biopsies in as little as 24 hours.
Notably, the Ion Torrent Oncomine Precision Assay enables detection of relevant NSCLC biomarkers from tissue and liquid biopsy specimens (Table 1). Simultaneous analysis of relevant biomarkers or relevant co-mutations is essential to understanding the landscape of genomic events as major determinants of the diverse signaling cascades of mutant KRAS.
Oncomine Solutions provide an ideal method for molecular profiling of NSCLC because of the ability to identify diverse mutations in KRAS, simultaneously with other relevant genes, with low input requirements appropriate for NSCLC, and a short turnaround time.
| Ion Torrent Oncomine Precision Assay GX | Ion Torrent Oncomine Comprehensive Assay v3 | Ion Torrent Oncomine Comprehensive Assay Plus | ||
| Panel details | NSCLC biomarkers: ALK, BRAF, EGFR, ERBB2, KRAS, MET, NTRK 1/2/3, ROS1, RET | |||
| Genomic signatures | — | — | MSI, TMB, HRD | |
| Specimen types | FFPE tissue and plasma | FFPE tissue | FFPE tissue | |
| Alteration types | Mutations, insertions, deletions, CNVs, fusions | |||
| Specimen types | DNA and RNA, cell-free total nucleic acid (cfTNA) |
DNA and RNA | DNA and RNA | |
| Number of genes | 50 | 161 | >500 | |
| DNA or RNA input amount | 10 ng | 20 ng | 20 ng | |
| Intrument and turnaround time | Ion Torrent Genexus System (1-day TAT) | Ion Torrent Genexus System (1-day TAT), Ion GeneStudio S5 System (4-day TAT) | Ion Torrent Genexus System (1-day TAT), Ion GeneStudio S5 System (4-day TAT) | |
* Timing varies by number of samples, sample type, and instrument used.
1. Pantsar, T. (2020). The current understanding of KRAS protein structure and dynamics. Comput Struct Biotechnol J 18, 189-198.
2. Jordan EJ, et al. (2017). Prospective comprehensive molecular characterization of lung adenocarcinomas for efficient patient matching to approved and emerging therapies. Cancer Discov, 7(6), 596-609.
3. Skoulidis F, Heymach JV. (2019). Co-occurring genomic alterations in non-small-cell lung cancer biology and therapy. Nat Rev Cancer, 19(9), 495-509.
4. Veluswamy R, et al. (2021). KRAS G12C-mutant non-small cell lung cancer: biology, developmental therapeutics, and molecular testing. J Mol Diagn, 23(5), 507-520.
5. Tan AC, Tan DS. (2022). Targeted therapies for lung cancer patients with oncogenic driver molecular alterations. J Clin Oncol, 40(6), 611-625.
6. Li S, et al. (2014). Coexistence of EGFR with KRAS, or BRAF, or PIK3CA somatic mutations in lung cancer: a comprehensive mutation profiling from 5125 Chinese cohorts. Br J Cancer, 110(11), 2812-2820
7. Salem ME, et al. (2022). Landscape of KRAS G12C, associated genomic alterations, and interrelation with immuno-oncology biomarkers in KRAS-mutated cancers. JCO Precis Oncol, 6, e2100245.
8. McGranahan N, et al. (2015). Clonal status of actionable driver events and the timing of mutational processes in cancer evolution. Sci Transl Med, 7(283), 283ra54.
9. Skoulidis F, et al. (2015). Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov, 5(8), 860-877.
10. Karimi N, Moghaddam SJ. (2023). KRAS-mutant lung cancer: targeting molecular and immunologic pathways, therapeutic advantages and restrictions. Cells, 12(5), 749.
11. Pennell NA, et al. (2019). Economic impact of next-generation sequencing versus single-gene testing to detect genomic alterations in metastatic non–small-cell lung cancer using a decision analytic model. JCO Precis Oncol, 3, 1-9.
For Research Use Only. Not for use in diagnostic procedures.
PMR-008091