Targeting the Undruggable KRAS Mutation in Lung Cancer – A Review

Dr Clark Jones PhD ORCiD
Pharmaceutical Scientist and Molecular Biologist, Salt Lake City, Utah, USA
Correspondence to: jonesclark828@gmail.com

Abstract
Introduction
The Historically Undruggable KRAS Mutation
Successful Drugs that Target KRAS are Now FDA Approved
In the Pipeline
Combination Therapy with KRAS Inhibitors
Challenges that Still Persist
Future Outlook: The Role of AI in Drug-Discovery for KRAS Targeted Drugs
Conclusion
References

Premier Journal of Science

Additional information

  • Ethical approval: N/a
  • Consent: N/a
  • Funding: No industry funding
  • Conflicts of interest: N/a
  • Author contribution: Clark Jones – Conceptualization, Writing – original draft, review and editing
  • Guarantor: Clark Jones
  • Provenance and peer-review:
    Commissioned and externally peer-reviewed
  • Data availability statement: N/a

Keywords: kras mutation, non-small cell lung cancer, sotorasib, adagrasib, ai-driven drug discovery.

Received: 20 July 2024
Revised: 8 August 2024
Accepted: 11 August 2024
Published: 27 August 2024

Abstract

Targeting the KRAS mutation in lung cancer has proven to be a challenging yet essential task due to its intricate signaling mechanisms and high prevalence in non-small cell lung cancer (NSCLC). Despite historical setbacks, recent advancements have led to the approval of targeted therapies such as sotorasib and adagrasib, offering new hope for patients with KRAS-mutated lung cancer. Ongoing research and development efforts have introduced several promising candidates in the pipeline, showcasing promising compounds like a pan-KRAS inhibitor, which could potentially transform the treatment landscape for KRAS-mutant cancers. Artificial intelligence (AI) in accelerating drug discovery for KRAS-targeted therapies, leveraging machine learning algorithms to analyze vast amounts of data and predict the efficacy of potential drug candidates.

AI-driven drug discovery is revolutionizing the field by enabling researchers to explore novel treatment strategies and develop innovative therapies for KRAS-mutant cancers. AI may be utilized to develop personalized treatment regimens, predict outcomes, and revolutionize the landscape of precision medicine for lung cancer patients with KRAS mutations. Through a combination of cutting-edge research, combination therapies, and AI-driven innovation, recent advancements illustrate profound hope in the field of targeting the historically undruggable KRAS mutation in lung cancer.

Introduction

Lung cancer remains the deadliest form of cancer worldwide, with most cases arising from the epithelial cells that line the airways1. It is often classified into two main types: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC accounting for approximately 85% of all cases2. NSCLC is further categorized into subtypes based on genetic mutations that drive tumor growth and progression. One of the biggest challenges in treating lung cancer is its heavy mutational burden, which makes it difficult to develop effective targeted therapies3,4. While mutations in epidermal growth factor receptors (EGFRs) and anaplastic lymphoma kinases (ALKs) have been successfully targeted with drugs like tyrosine kinase inhibitors (TKIs), drug resistance and relapse remain common issues5,6. Among these mutations, Kirsten Rat Sarcoma (KRAS) discovered in 19827 stands out as one of the most challenging to target due to its unique signaling mechanisms and high frequency in NSCLC.8

KRAS mutations account for 85% of all RAS mutations and are found in approximately 35% of NSCLC cases, making it one of the most prevalent mutations in this type of cancer.9 The KRAS gene encodes a protein that plays a critical role in cell signaling pathways involved in cell proliferation and survival.10 Mutations in KRAS lead to dysregulated signaling that promotes tumor growth and aggressiveness, making it a prime target for therapeutic intervention in lung cancer.11,12 However, the complex and diverse nature of KRAS mutations has posed significant challenges in developing effective targeted therapies, earning it the reputation of being an “undruggable” target in lung cancer research for decades.13 The KRAS mutation is also prevalent in several other cancer types such as colorectal cancer and pancreatic cancer, making it an attract target for novel therapeutics in optimizing cancer treatment.14 In this review, the latest innovations and research will be discussed on the monumental progress being made on targeting the KRAS mutation that has historically been deemed undruggable until the past few years.

The Historically Undruggable KRAS Mutation

KRAS mutation plays a crucial role in driving cancer progression by dysregulating cellular signaling pathways involved in cell growth and survival. Unlike other mutations in lung cancer that have targeted therapies such as EGFR inhibitors, KRAS mutations have been historically considered undruggable due to their intricate mechanisms of action and protein shape. The normal signaling pathway in human cells involves a series of protein interactions that regulate cell proliferation. However, in cancer cells with KRAS mutations, this pathway is constitutively activated, leading to uncontrolled cell growth and tumor progression.15 The mutated KRAS protein acts as a molecular switch that remains in the “on” position, driving continuous cell proliferation.16 KRAS protein differs from other mutational proteins that have extensive targeted therapy options due to its small and irregular shape (Figure 1). The KRAS protein’s characteristics have posed a difficult hurdle to clear in the development of small molecule inhibitors capable of binding irreversibly to a binding pocket in the protein to elicit a change in protein function and signaling.17

3D Structure of KRAS
Figure 1: 3D Structure of KRAS.

Several clinical trials and early drug discovery options have attempted to target KRAS mutation in lung cancer, but most have faced challenges such as off-target effects, limited efficacy, and drug resistance. One of the main reasons for the failure of these therapies is the complex nature of KRAS signaling pathways, which involve multiple downstream effectors and feedback loops that contribute to treatment resistance. These failures have highlighted the need for innovative approaches to develop effective therapies for KRAS-mutant cancers. Despite significant efforts to develop effective KRAS inhibitors, targeting this mutation remains a major obstacle in the field of cancer therapy. The inherent complexity of KRAS-driven signaling cascades, coupled with the development of adaptive resistance mechanisms, poses significant challenges for drug development.

Successful Drugs that Target KRAS are Now FDA Approved

In recent years, the field of oncology has witnessed significant advancements in targeting one of the most prevalent mutations in cancer, KRAS, thanks to the relentless efforts of the scientific community. Despite numerous setbacks in the past, the successful development of targeted therapies for KRAS mutations has become a reality for lung cancer patients. These therapies offer hope for subsets of patients with specific KRAS mutations, providing them with a more personalized and effective treatment approach. By targeting the underlying genetic alterations driving the cancer, these drugs aim to improve outcomes and quality of life for patients.

One of the most important drugs to enter through clinical trials that led to the approval of the first KRAS-targeting drug in 2021, sotorasib, demonstrated its efficacy in treating patients with KRAS-mutated lung cancer.18 Sotorasib (Figure 2) works by specifically inhibiting the mutated KRAS protein, disrupting the signaling pathways that drive tumor growth. This small molecule inhibits the G12C mutation in KRAS by covalently and irreversibly binding to a cysteine residue on the protein to hold it in its inactive conformation.19 Sotorasib is currently available for patients with mutated G12C metastatic NSCLC with at least one prior systemic treatment such as chemotherapy. Ongoing efforts are focused on optimizing sotorasib treatment to address emerging challenges and maximize its benefits in the rapidly evolving landscape of oncology. By continuously refining dosing regimens and combination therapies, researchers aim to enhance the drug’s effectiveness and expand its applicability to a broader patient population.

Sotorasib Structure
Figure 2: Sotorasib Structure.

Another significant milestone in the treatment of KRAS-mutated lung cancer was the approval of adagrasib, also a KRAS-targeted therapy with a similar mechanism of action to sotorasib. Adagrasib (Figure 3) has shown promising results in clinical trials, particularly in patients who have developed resistance to other treatments.20,21

Adagrasib also works by targeting the same G12C KRAS mutation and binds to the unique cysteine residue to hold the inactive conformation of the protein and eliminating downstream signaling and cell proliferation (20). Adagrasib is available to patients with advanced G12C mutated NSCLC and colorectal cancer. The main difference is Adagrasib has been shown to have a much longer half-life than sotorasib, and it also may be able to penetrate the blood brain barrier offering hope to those patients who have brain metastasis.22 By offering an alternative treatment option, adagrasib provides new hope for patients with specific KRAS mutations who may not have responded to conventional therapies, or patients whose cancer has spread to the central nervous system. Ongoing efforts to optimize adagrasib treatment strategies aim to further improve patient outcomes and establish it as a valuable addition to the treatment options for KRAS-mutated lung cancer. Looking ahead, several other drugs targeting KRAS mutations are currently in clinical trials, with the potential to further expand treatment options and improve outcomes for patients with this challenging disease.

Adagrasib Structure
Figure 3: Adagrasib Structure.

While the addition of sotorasib and adagrasib to the cancer therapy arsenal was a monumental accomplishment, KRAS mutations are highly diverse, and different variants require tailored treatments. Therefore, efforts are underway to develop drugs capable of targeting other common KRAS mutations, including ones such as G12D and G13C that represent another subpopulation of lung cancer patients with no targeted treatment options.

In the Pipeline

In the pipeline of drug development for targeting KRAS mutations in lung cancer, there is a wealth of promising compounds that hold the potential to enhance or build upon the current treatment options offered by drugs like sotorasib and adagrasib. These new drugs in early stages of development represent the next frontier in precision medicine, aiming to address the challenges of drug resistance. With ongoing research and advancements in drug discovery, these promising compounds offer hope for more effective and personalized treatment approaches in the future. Among the most promising compounds in preclinical studies are those that have shown encouraging results in cell culture and in vivo experiments targeting KRAS mutations. Given the only two currently FDA approved treatments for KRAS mutation in lung cancer target the same mutation, new compounds look to expand their applicability. One of the most promising small inhibitors to target KRAS and its variety of mutations in preclinical trials is known as compound BI-2865.

Groundbreaking work by Dr. Piro Lito and his team at Memorial Sloan Kettering Cancer Institute has rendered the development of this first pan-KRAS inhibitor (BI-2865). This finding could revolutionize the field by offering a promising new approach to target KRAS mutations more effectively. Their work found that this pan-KRAS inhibitor was able to inhibit cancer growth across multiple cancer types including colon, pancreatic and lung cancer while targeting multiple common KRAS mutations in addition to G12C.23 This novel inhibitor has shown promising results in preclinical studies and holds great potential for improving patient outcomes in the future. While these early-stage compounds show great potential, they may face limitations or drawbacks when transitioning from preclinical studies to clinical trials. Challenges such as off-target effects, toxicity profiles, and pharmacokinetics must be carefully assessed and optimized to ensure the safety and efficacy of these drugs in human patients, underscoring the importance of rigorous preclinical testing and translational research in drug development.

In clinical trials, several promising drugs are working towards FDA approval for targeting KRAS mutations in lung cancer patients. Examples include compounds JNJ-74699157 and LY3499446, which have shown encouraging results in early-phase trials and are progressing towards potential approval in the coming years.24 However, hurdles such as demonstrating significant clinical benefit, managing drug resistance, and navigating regulatory requirements pose challenges for these drugs seeking widespread approval and adoption in clinical practice. The recent approvals of targeted therapies like sotorasib have set a precedent for the efficacy and safety standards expected for new drugs targeting KRAS mutations, influencing the development and approval process for these next-generation compounds in the pipeline of drug development for lung cancer treatment. These novel therapeutic options are only the beginning of the plethora of options that will soon be available thanks to these efforts of opening the door to target a mutation that has historically evaded everything thrown at it until now. Their approval and continued research will represent a pivotal step in combating this common mutation not only in lung cancer but in other cancer types presented with similar mutational burdens as well.

Combination Therapy with KRAS Inhibitors

As KRAS mutations exist as only a small population of cells in lung cancer patients, targeted therapy with KRAS inhibitors is being explored as a second line treatment for patients who have progressed on standard options and have late stage or aggressive cancer types.25 Sotorasib, for example, has shown promising results in preclinical studies when combined with MEK inhibitors like trametinib to optimize its effect and overcome potential resistance mechanisms.26 Sotorasib could also be used in conjunction with immunotherapies with PDL-1 positive cancers along with other targeted therapies that are present in the patient’s tumor. By targeting a vast array of cancer cell subtypes, the tumor may be more efficiently halted or reduced with long remission paired with reduced drug resistance. These combination therapies can demonstrate improved outcomes in patients with KRAS-mutated NSCLC, paving the way for further investigation into the use of KRAS inhibitors in combination regimens.

In cases where patients with KRAS-mutated lung cancer have developed brain metastasis, adagrasib may be a more suitable treatment option due to its ability to penetrate the blood-brain barrier. Adagrasib is being explored as a potential therapy for patients who have had progression on sotorasib or other prior treatments. Combining adagrasib with other targeted therapies such as EGFR inhibitors or immune checkpoint inhibitors may help optimize outcomes for patients with brain metastasis and KRAS mutations.27 By targeting the underlying mechanisms of tumor growth and progression, combination therapy with adagrasib holds promise for improving outcomes in patients with advanced KRAS-mutated lung cancer. The utilization of KRAS inhibitors in combination therapy approaches underscores the importance of personalized treatment strategies for patients with lung cancer. By targeting specific genetic mutations like KRAS, clinicians can tailor treatment regimens to individual patients and their unique tumor profiles. As research continues to uncover new insights into the molecular pathways driving KRAS-mutated lung cancer, the development of novel combination therapies holds great potential for improving outcomes and extending survival for lung cancer patients.

Challenges that Still Persist

Despite the significant advancements made in the development of multiple KRAS inhibitors for the treatment of lung cancer, there are still limitations to the current treatment approaches that need to be addressed. One of the major challenges is drug resistance, which can develop over time and hinder the effectiveness of targeted therapies. This highlights the critical need for combination therapy strategies to optimize outcomes for patients with KRAS-mutated lung cancer. By combining different targeted agents or incorporating other treatment modalities, clinicians may be able to overcome resistance mechanisms and improve patient responses to therapy. Another limitation in the current landscape of KRAS inhibitors is that they mainly target the G12C KRAS mutation, which is the only mutation currently approved by the FDA for targeted therapy in lung cancer. This highlights the importance of developing predictive biomarkers to stratify patient populations and optimize treatment selection. The development of a pan-KRAS inhibitor that can target multiple KRAS mutations would be a significant advancement in the field, allowing for a more comprehensive approach to treating patients with diverse KRAS mutations. Research efforts aimed at expanding the scope of targeted therapies to encompass a broader range of KRAS mutations are crucial for improving treatment options for patients with KRAS-mutated lung cancer.

While the concept of sequencing a patient’s tumor and tailoring treatment based on individual genetic profiles holds great promise, the high cost associated with these personalized approaches remains a significant hurdle. The cost of the current FDA approved drugs targeting the KRAS mutation such as sotorasib and adagrasib remain relatively expensive, limiting the patients who can receive them as well. Making these advanced treatments more accessible to a wider patient population is essential for improving outcomes in lung cancer care. The incorporation of machine learning algorithms for predictive biomarker identification and the development of cost-effective combination therapy regimens could be key strategies in addressing the challenges of personalized medicine and advancing the field of targeted therapy for KRAS-mutated lung cancer. By leveraging innovative technologies and research approaches, researchers and clinicians can work towards overcoming these obstacles and improving the standard of care for patients.

Future Outlook: The Role of AI in Drug Discovery for KRAS Targeted Drugs

Artificial intelligence (AI) has emerged as a powerful tool in accelerating drug discovery for KRAS-targeted therapies. By leveraging AI algorithms and machine learning techniques, researchers can analyze vast amounts of data to identify potential drug candidates and predict their efficacy with unprecedented speed and accuracy.28-30 AI-driven drug discovery is revolutionizing the field by enabling researchers to explore novel treatment strategies and develop innovative therapies for KRAS-mutant cancers.31 AI algorithms are being utilized to sift through vast libraries of compounds and identify potential drug candidates based on the binding pockets and conformation of target proteins. By analyzing complex molecular structures and interactions, AI can process and analyze significantly more data than traditional wet lab experiments or previous computer programs, accelerating the drug discovery process and increasing the likelihood of identifying effective KRAS inhibitors for targeted therapy.31

Machine learning algorithms within AI systems are continually adapting to new technologies and findings, enhancing their capabilities in drug discovery for KRAS- targeting drugs.29 By leveraging vast amounts of publicly available genomic data, AI can predict the success rates of potential drug candidates in human patients before they even reach preclinical models.32 This predictive modeling not only streamlines the drug development process but also improves the probability and predictability of identifying successful drug candidates for targeted therapy, ultimately benefiting patients with KRAS-mutated lung cancer by providing more effective treatment options. In addition to drug discovery, AI holds immense potential in developing and predicting combination therapies with KRAS inhibitors to optimize patient outcomes. By analyzing vast datasets and identifying synergistic drug combinations, AI can help clinicians tailor treatment regimens for individual patients, maximizing the efficacy of targeted therapies and reducing the risk of drug resistance. Looking ahead, AI may one day be utilized to generate personalized prognoses, treatment options, and predict outcomes for a wide range of diseases and treatments beyond cancer, revolutionizing the way healthcare is delivered and transforming the landscape of precision medicine.

Conclusion

The KRAS mutation in lung cancer is a significant driver of tumorigenesis, making it a crucial target for therapeutic intervention. Due to its high prevalence in various cancers, including lung cancer, developing targeted therapies against KRAS mutations is imperative for improving patient outcomes. Historically, targeting KRAS has been challenging due to its complex and intrinsic signaling mechanisms, as well as its irregular shape, which hindered the design of effective inhibitors. These obstacles have posed significant hurdles in the development of successful treatments for KRAS- mutated lung cancer. Despite past setbacks, recent advancements have led to the emergence of two successful candidates for targeting KRAS mutations in lung cancer: sotorasib and adagrasib. The approval of these drugs represents a monumental breakthrough in the field of oncology, offering new hope for patients with KRAS-mutated lung cancer and potentially improving treatment outcomes. Furthermore, the pipeline of promising candidates targeting KRAS mutations suggests a bright future for expanding treatment options and potentially targeting additional KRAS mutations to further enhance personalized therapies for patients.

While the current KRAS-targeting drugs have limitations, such as resistance development and cost, the integration of combination therapies and AI holds promise in overcoming these challenges. By leveraging AI to optimize treatment regimens and identify novel drug targets, the field of oncology is poised to enhance further drug development and discovery in the context of KRAS-mutated lung cancer. The exponential growth in the development of KRAS-targeting drugs in recent years signifies a promising future for patients battling lung cancer, with the potential for more effective and tailored treatment strategies on the horizon.

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