Molecular dynamics simulation-guided drug sensitivity prediction for lung cancer with rare EGFR mutations

From Rarity to Reality: Osimertinib's Promising Horizon in Treating Uncommon EGFR Mutations in Non-Small Cell Lung Cancer

In the realm of advanced non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) therapy with tyrosine kinase inhibitors (TKI), addressing optimal treatment for uncommon EGFR mutations like G719X in exon 18, S768I in exon 20, and L861Q in exon 21 remains a pivotal yet challenging frontier. Contrary to the well-established efficacy of EGFR-TKIs in common EGFR mutations, these uncommon alterations pose unmet medical needs due to a lack of comprehensive evidence. While afatinib, a second-generation EGFR-TKI, has received FDA approval for patients with these uncommon EGFR mutations, the approval was based on a post-hoc analysis of randomized clinical trials. Recent developments include multiple clinical trials investigating the efficacy of both second- and third-generation EGFR-TKIs in patients with uncommon EGFR mutations. A noteworthy example is a prospective phase II trial of osimertinib including the landmark UNICORN study, which has shown promising results in treating uncommon EGFR mutations. Despite various reports on the efficacy of afatinib and osimertinib in treating uncommon EGFR mutations, the appropriate use of these TKIs remains unclear. This review aims to consolidate the findings from the latest clinical trials focused on uncommon EGFR mutations, outlining variations in the therapeutic efficacy of these TKIs based on the specific genetic mutation. By synthesizing these findings, we aim to guide oncologists toward more informed decisions in employing TKIs for NSCLC with uncommon EGFR mutations other than exon 20 insertion. Additionally, we explore potential treatment strategies tailored to these patient populations to address the challenges posed by these mutations.

Future direction of total neoadjuvant therapy for locally advanced rectal cancer

Despite therapeutic advancements, disease-free survival and overall survival of patients with locally advanced rectal cancer have not improved in most trials as a result of distant metastases. For treatment decision-making, both long-term oncologic outcomes and impact on quality-of-life indices should be considered (for example, bowel function). Total neoadjuvant therapy (TNT), comprised of chemotherapy and radiotherapy or chemoradiotherapy, is now a standard treatment approach in patients with features of high-risk disease to prevent local recurrence and distant metastases. In selected patients who have a clinical complete response, subsequent surgery might be avoided through non-operative management, but patients who do not respond to TNT have a poor prognosis. Refined molecular characterization might help to predict which patients would benefit from TNT and non-operative management. Specifically, integrated analysis of spatiotemporal multi-omics using artificial intelligence and machine learning is promising. Three prospective trials of TNT and non-operative management in Japan, the USA and Germany are collaborating to better understand drivers of response to TNT. Here, we address the future direction for TNT.

Computational Analysis of Activation of Dimerized Epidermal Growth Factor Receptor Kinase Using the String Method and Markov State Model

Epidermal growth factor receptor (EGFR) activation is accompanied by dimerization. During the activation of the intracellular kinase domain, two EGFR kinases form an asymmetric dimer, and one side of the dimer (receiver) is activated. Using the string method and Markov state model (MSM), we performed a computational analysis of the structural changes in the activation of the EGFR dimer in this study. The string method reveals the minimum free-energy pathway (MFEP) from the inactive to active structure. The MSM was constructed from numerous trajectories of molecular dynamics simulations around the MFEP, which revealed the free-energy map of structural changes. In the activation of the receiver kinase, the unfolding of the activation loop (A-loop) is followed by the rearrangement of the C-helix, as observed in other kinases. However, unlike other kinases, the free-energy map of EGFR at the asymmetric dimer showed that the active state yielded the highest stability and revealed how interactions at the dimer interface induced receiver activation. As the H-helix of the activator approaches the C-helix of the receiver during activation, the A-loop unfolds. Subsequently, L782 of the receiver enters the pocket between the G- and H-helices of the activator, leading to a rearrangement of the hydrophobic residues around L782 of the receiver, which constitutes a structural rearrangement of the C-helix of the receiver from an outward to an inner position. The MSM analysis revealed long-time scale trajectories via kinetic Monte Carlo.

First-in-human phase I study of BEBT-109 in previously treated EGFR exon 20 insertion-mutated advanced non-small cell lung cancer

BACKGROUND

BEBT-109 is an oral pan-mutant-selective inhibitor of epidermal growth factor receptor (EGFR) that demonstrated promising antitumor potency in preclinical models.

METHODS

This first-in-human study was a single-arm, open-label, two-stage study. Phase Ia dose-escalation study evaluated the safety and pharmacokinetics of BEBT-109 in 11 patients with EGFR T790M-mutated advanced non-small cell lung cancer (aNSCLC). Phase Ib dose-expansion study evaluated the safety and efficacy of BEBT-109 in 18 patients with EGFR exon 20 insertion (ex20ins)-mutated treatment-refractory aNSCLC. The primary outcomes were adverse events and antitumor activity. Clinical trial registration number CTR20192575.

FINDINGS

The phase Ia study demonstrated no dose-limiting toxicity, no observation of the maximum tolerated dose, and no new safety signals with BEBT-109 in the dose range of 20-180 mg/d, suggesting that BEBT-109 had an acceptable safety profile among patients with EGFR T790M-mutated aNSCLC. Plasma pharmacokinetics of BEBT-109 showed a dose-proportional increase in the area under the curve and maximal concentration, with no significant drug accumulation. The dose-expansion study demonstrated that BEBT-109 treatment was tolerable across the three dose levels. The three most common treatment-related adverse events were diarrhea (100%; 22.2% ≥Grade 3), rash (66.7%; 5.6% ≥Grade 3), and anemia (61.1%; 0% ≥Grade 3). The objective response rate was 44.4% (8 of 18). Median progression-free survival was 8.0 months (95% confidence intervals, 1.33-14.67).

CONCLUSION

Preliminary findings showed that BEBT-109 had an acceptable safety profile and favorable antitumor activity in patients with refractory EGFR ex20ins-mutated aNSCLC.

FUNDING

National Natural Science Foundation of China.

Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies

Globally, malignancies cause one out of six mortalities, which is a serious health problem. Cancer therapy has always been challenging, apart from major advances in immunotherapies, stem cell transplantation, targeted therapies, hormonal therapies, precision medicine, and palliative care, and traditional therapies such as surgery, radiation therapy, and chemotherapy. Natural products are integral to the development of innovative anticancer drugs in cancer research, offering the scientific community the possibility of exploring novel natural compounds against cancers. The role of natural products like Vincristine and Vinblastine has been thoroughly implicated in the management of leukemia and Hodgkin's disease. The computational method is the initial key approach in drug discovery, among various approaches. This review investigates the synergy between natural products and computational techniques, and highlights their significance in the drug discovery process. The transition from computational to experimental validation has been highlighted through in vitro and in vivo studies, with examples such as betulinic acid and withaferin A. The path toward therapeutic applications have been demonstrated through clinical studies of compounds such as silvestrol and artemisinin, from preclinical investigations to clinical trials. This article also addresses the challenges and limitations in the development of natural products as potential anti-cancer drugs. Moreover, the integration of deep learning and artificial intelligence with traditional computational drug discovery methods may be useful for enhancing the anticancer potential of natural products.

Preclinical Anticipation of On- and Off-Target Resistance Mechanisms to Anti-Cancer Drugs: A Systematic Review

The advent of targeted therapies has led to tremendous improvements in treatment options and their outcomes in the field of oncology. Yet, many cancers outsmart precision drugs by developing on-target or off-target resistance mechanisms. Gaining the ability to resist treatment is the rule rather than the exception in tumors, and it remains a major healthcare challenge to achieve long-lasting remission in most cancer patients. Here, we discuss emerging strategies that take advantage of innovative high-throughput screening technologies to anticipate on- and off-target resistance mechanisms before they occur in treated cancer patients. We divide the methods into non-systematic approaches, such as random mutagenesis or long-term drug treatment, and systematic approaches, relying on the clustered regularly interspaced short palindromic repeats (CRISPR) system, saturated mutagenesis, or computational methods. All these new developments, especially genome-wide CRISPR-based screening platforms, have significantly accelerated the processes for identification of the mechanisms responsible for cancer drug resistance and opened up new avenues for future treatments.

Evaluating the ability of end-point methods to predict the binding affinity tendency of protein kinase inhibitors

Because of the high economic cost of exploring the experimental impact of mutations occurring in kinase proteins, computational approaches have been employed as alternative methods for evaluating the structural and energetic aspects of kinase mutations. Among the main computational methods used to explore the affinity linked to kinase mutations are docking procedures and molecular dynamics (MD) simulations combined with end-point methods or alchemical methods. Although it is known that end-point methods are not able to reproduce experimental binding free energy (ΔG) values, it is also true that they are able to discriminate between a better or a worse ligand through the estimation of ΔG. In this contribution, we selected ten wild-type and mutant cocrystallized EGFR-inhibitor complexes containing experimental binding affinities to evaluate whether MMGBSA or MMPBSA approaches can predict the differences in affinity between the wild type and mutants forming a complex with a similar inhibitor. Our results show that a long MD simulation (the last 50 ns of a 100 ns-long MD simulation) using the MMGBSA method without considering the entropic components reproduced the experimental affinity tendency with a Pearson correlation coefficient of 0.779 and an R2 value of 0.606. On the other hand, the correlation between theoretical and experimental ΔΔG values indicates that the MMGBSA and MMPBSA methods are helpful for obtaining a good correlation using a short rather than a long simulation period.

Temperature-boosted PAM-less activation of CRISPR-Cas12a combined with selective inhibitors enhances detection of SNVs with VAFs below 0.01

The precise identification of rare single nucleotide variations (SNVs) concomitant with excess wild-type DNA is a valuable method for minimally invasive disease diagnosis and early prediction of drug responsiveness. Selective enrichment of mutant variants via strand displacement reaction offers an ideal approach of SNVs analysis but fails to differentiate wildtype from mutants with variant allele fraction (VAF) < 0.01%. Here, we demonstrate that integration of PAM-less CRISPR-Cas12a and adjacent mutation-enhanced inhibition of wild-type alleles enables highly sensitive measurement of SNVs well below the 0.01% VAF threshold. Raising the reaction temperature to the upper limit of LbaCas12a helps to boost PAM-less activation of collateral DNase activity, which can be further enhanced using PCR additives, leading to ideal discriminative performance for single point mutations. Along with selective inhibitors bearing additional adjacent mutation, it allowed detection of model EGFR L858R mutants down to 0.001% with high sensitivity and specificity. Preliminary investigation on adulterated genomic samples prepared in two different ways also suggests that it can accurately measure ultralow-abundance SNVs extracted directly from clinical samples. We believe that our design, which combines the superior SNV enrichment capability of strand displacement reaction and unparalleled programmability of CRISPR-Cas12a, has the potential to significantly advance current SNV profiling technologies.

Structure-Guided Strategies of Targeted Therapies for Patients with EGFR-Mutant Non-Small Cell Lung Cancer

Oncogenic mutations within the EGFR kinase domain are well-established driver mutations in non-small cell lung cancer (NSCLC). Small-molecule tyrosine kinase inhibitors (TKIs) specifically targeting these mutations have improved treatment outcomes for patients with this subtype of NSCLC. The selectivity of these targeted agents is based on the location of the mutations within the exons of the EGFR gene, and grouping mutations based on structural similarities has proved a useful tool for conceptualizing the heterogeneity of TKI response. Structure-based analysis of EGFR mutations has influenced TKI development, and improved structural understanding will inform continued therapeutic development and further improve patient outcomes. In this review, we summarize recent progress on targeted therapy strategies for patients with EGFR-mutant NSCLC based on structure and function analysis.

PD-1+ mast cell enhanced by PD-1 blocking therapy associated with resistance to immunotherapy

BACKGROUND

Programmed cell death protein 1 (PD-1) antibody has been approved for a variety of tumors, but its effective rate is unsatisfactory. New evidence suggests that mast cells are an important component of the tumor microenvironment and are associated with resistance to immunotherapy, but the underlying mechanism is not clear.

METHODS

Bioinformatics analysis of patients with melanoma in TCGA-SKCM and GSE91061 was used to determine the prognostic value of mast cells and their association with anti-PD-1 immunotherapy. HMC-1 cells (mast cell line) and bone marrow-derived mast cells (BMMCs) were used to verify the effect of PD-1 antibody and cromolyn sodium in vitro. The mouse subcutaneous melanoma model was used to verify the effect of the PD-1 antibody on mast cells in vivo.

RESULTS

Bioinformatics analysis showed that mast cells were a poor prognostic factor associated with resistance to anti-PD-1 immunotherapy. PD-1 was expressed on the mast cell membrane. The PD-1 antibody promoted the release of histamine and cytokines from mast cells via the PI3K/AKT pathway and calcium signaling pathway. The activation of mast cells induced by PD-1 antibody could be partially inhibited by cromolyn sodium. In vivo, cromolyn sodium increased the efficacy of PD-1 antibody and decreased the infiltration of mast cells and the density of microvessels.

CONCLUSION

PD-1⁺ mast cell activated by PD-1 antibody plays a negative role in the tumor microenvironment via the enhanced function of releasing histamine and cytokines. Inhibition of mast cell may provide a new solution to solve the low response rate of anti-PD-1 immunotherapy.

Computational Methods for the Analysis and Prediction of EGFR-Mutated Lung Cancer Drug Resistance: Recent Advances in Drug Design, Challenges and Future Prospects

Lung cancer is a major cause of cancer deaths worldwide, and has a very low survival rate. Non-small cell lung cancer (NSCLC) is the largest subset of lung cancers, which accounts for about 85% of all cases. It has been well established that a mutation in the epidermal growth factor receptor (EGFR) can lead to lung cancer. EGFR Tyrosine Kinase Inhibitors (TKIs) are developed to target the kinase domain of EGFR. These TKIs produce promising results at the initial stage of therapy, but the efficacy becomes limited due to the development of drug resistance. In this paper, we provide a comprehensive overview of computational methods, for understanding drug resistance mechanisms. The important EGFR mutants and the different generations of EGFR-TKIs, with the survival and response rates are discussed. Next, we evaluate the role of important EGFR parameters in drug resistance mechanism, including structural dynamics, hydrogen bonds, stability, dimerization, binding free energies, and signaling pathways. Personalized drug resistance prediction models, drug response curve, drug synergy, and other data-driven methods are also discussed. Recent advancements in deep learning; such as AlphaFold2, deep generative models, big data analytics, and the applications of statistics and permutation are also highlighted. We explore limitations in the current methodologies, and discuss strategies to overcome them. We believe this review will serve as a reference for researchers; to apply computational techniques for precision medicine, analyzing structures of protein-drug complexes, drug discovery, and understanding the drug response and resistance mechanisms in lung cancer patients.

Novel Calcium-Binding Ablating Mutations Induce Constitutive RET Activity and Drive Tumorigenesis

Distinguishing oncogenic mutations from variants of unknown significance (VUS) is critical for precision cancer medicine. Here, computational modeling of 71,756 RET variants for positive selection together with functional assays of 110 representative variants identified a three-dimensional cluster of VUSs carried by multiple human cancers that cause amino acid substitutions in the calmodulin-like motif (CaLM) of RET. Molecular dynamics simulations indicated that CaLM mutations decrease interactions between Ca2+ and its surrounding residues and induce conformational distortion of the RET cysteine-rich domain containing the CaLM. RET-CaLM mutations caused ligand-independent constitutive activation of RET kinase by homodimerization mediated by illegitimate disulfide bond formation. RET-CaLM mutants possessed oncogenic and tumorigenic activities that could be suppressed by tyrosine kinase inhibitors targeting RET. This study identifies calcium-binding ablating mutations as a novel type of oncogenic mutation of RET and indicates that in silico-driven annotation of VUSs of druggable oncogenes is a promising strategy to identify targetable driver mutations.

SIGNIFICANCE

Comprehensive proteogenomic and in silico analyses of a vast number of VUSs identify a novel set of oncogenic and druggable mutations in the well-characterized RET oncogene.

Discovery of mobocertinib, a new irreversible tyrosine kinase inhibitor indicated for the treatment of non-small-cell lung cancer harboring EGFR exon 20 insertion mutations

Epidermal growth factor receptor (EGFR) is essential for normal cellular functions. Mutations of EGFR’s kinase domain can cause dysregulation leading to non-small cell lung cancer (NSCLC). Exon 20 insertion (ex20ins) mutations in EGFR are one of the leading contributors to oncogenesis and confer insensitivity to most available therapeutics. Mobocertinib is a novel tyrosine kinase inhibitor (TKI) recently approved by the US FDA as a first-in-class small molecule therapeutic for EGFR ex20ins-positive NSCLC. When compared to osimertinib, a TKI indicated for the treatment of EGFR T790M-positive NSCLC, mobocertinib differs only by the presence of an additional C5-carboxylate isopropyl ester group on the middle pyrimidine core. Together with the acrylamide side chain that is responsible for irreversible inhibition, this additional C5-substituent affords mobocertinib high anticancer potency and specificity to EGFR ex20ins-positive lung cancer that is resistant to other EGFR TKIs. This review article provides an overview of the discovery of mobocertinib from osimertinib including their structure-activity relationships, mechanisms of action, preclinical pharmacology, pharmacokinetics, and clinical applications. The discovery and use of mobocertinib and other EGFR TKIs demonstrate the power of structure-based drug design and promising therapeutic outcomes of using precision medicine approaches in the management of molecularly defined tumors.

Predicting the mutation effects of protein–ligand interactions via end-point binding free energy calculations: strategies and analyses

Protein mutations occur frequently in biological systems, which may impact, for example, the binding of drugs to their targets through impairing the critical H-bonds, changing the hydrophobic interactions, etc. Thus, accurately predicting the effects of mutations on biological systems is of great interests to various fields. Unfortunately, it is still unavailable to conduct large-scale wet-lab mutation experiments because of the unaffordable experimental time and financial costs. Alternatively, in silico computation can serve as a pioneer to guide the experiments. In fact, numerous pioneering works have been conducted from computationally cheaper machine-learning (ML) methods to the more expensive alchemical methods with the purpose to accurately predict the mutation effects. However, these methods usually either cannot result in a physically understandable model (ML-based methods) or work with huge computational resources (alchemical methods). Thus, compromised methods with good physical characteristics and high computational efficiency are expected. Therefore, here, we conducted a comprehensive investigation on the mutation issues of biological systems with the famous end-point binding free energy calculation methods represented by MM/GBSA and MM/PBSA. Different computational strategies considering different length of MD simulations, different value of dielectric constants and whether to incorporate entropy effects to the predicted total binding affinities were investigated to provide a more accurate way for predicting the energetic change upon protein mutations. Overall, our result shows that a relatively long MD simulation (e.g. 100 ns) benefits the prediction accuracy for both MM/GBSA and MM/PBSA (with the best Pearson correlation coefficient between the predicted ∆∆G and the experimental data of ~ 0.44 for a challenging dataset). Further analyses shows that systems involving large perturbations (e.g. multiple mutations and large number of atoms change in the mutation site) are much easier to be accurately predicted since the algorithm works more sensitively to the large change of the systems. Besides, system-specific investigation reveals that conformational adjustment is needed to refine the micro-environment of the manually mutated systems and thus lead one to understand why longer MD simulation is necessary to improve the predicting result. The proposed strategy is expected to be applied in large-scale mutation effects investigation with interpretation.

Sunvozertinib, a selective EGFR inhibitor for previously treated non-small cell lung cancer with EGFR exon 20 insertion mutations

Epidermal growth factor receptor exon 20 insertion mutations (EGFR exon20ins) are detected in approximately 2% of patients with non-small cell lung cancer (NSCLC). Due to lack of effective therapy, the prognosis of these patients was poor. Sunvozertinib (DZD9008) was designed as an oral, potent, irreversible and selective EGFR tyrosine kinase inhibitor, showing activity against EGFR exon20ins and other mutations. In both cell lines and xenograft models, sunvozertinib shows potent antitumor activity. In the two ongoing phase 1 clinical studies, sunvozertinib was tolerated up to 400 mg once daily. The most common drug-related adverse events included diarrhea and skin rash. Antitumor efficacy was observed at the doses of 100 mg and above in patients with EGFR exon20ins NSCLC across different subtypes, with prior amivantamab treatment as well as with baseline brain metastasis. The median duration of response (DoR) has not been reached.

Remarkable Differences in Calcification between the Primary Tumor and Metastatic Lymph Nodes in a Patient with ALK-Positive Non-Small-Cell Lung Cancer

Calcified bilateral mediastinal lymph nodes are not common in malignant tumors. A 51-year-old woman presented to our hospital with a 20 mm nodule in the lower left lobe of the lung and extensive calcification in the bilateral mediastinal lymph nodes. Computed tomography indicated no calcification of the primary lesion. Immunohistochemical staining and fluorescent in situ hybridization detected an anaplastic lymphoma kinase (ALK) fusion. Treatment with alectinib, an ALK inhibitor, led to a significant reduction in tumor size and calcification in the lymph nodes. This case shows that different degrees of calcification can be associated with malignant tumors and may be reversible in some cases.

A phase I/II study of osimertinib in EGFR exon 20 insertion mutation-positive non-small cell lung cancer

OBJECTIVES

Several preclinical data proposed a potential efficacy of osimertinib, a third-generation EGFR tyrosine kinase inhibitor, for EGFR exon 20 insertion (EGFR ex20ins)-positive non-small cell lung cancer (NSCLC). However, reported case series and a retrospective study proposed controversial efficacy. The efficacy of osimertinib in EGFR ex20ins-positive NSCLC have not been well evaluated in prospective clinical trials. In this study, we performed a prospective, single-arm, multi-center, open-label, non-randomized phase I/II study to evaluate efficacy of osimertinib for EGFR ex20ins-positive NSCLC.

MATERIALS AND METHODS

From August 2018 to January 2020, 14 NSCLC patients with EGFR ex20ins were enrolled, of whom 2 were excluded because they did not meet the inclusion criteria. Efficacy and safety of 80 mg osimertinib were evaluated. In addition, we performed a translational exploratory study to clarify the association of mutation type-specific drug sensitivity, osimertinib pharmacokinetic data, and clinical efficacy.

RESULTS

Of the evaluated patients, none experienced objective response, 7 experienced stable disease (58.3%), and 5 experienced disease progression (41.7%). The median progression free survival (PFS) was 3.8 months, and the median overall survival was 15.8 months. Interestingly, the exploratory study demonstrated statistically significant positive correlation between plasma osimertinib concentration/in vitro IC₅₀ ratio and PFS (R = 0.9912, P = 0.0001), highlighting the mutation type-specific concentration-dependent efficacy of osimertinib for EGFR ex20ins-positive NSCLC.

CONCLUSIONS

Regular dose, 80 mg/day, of osimertinib has limited clinical activity in NSCLC patients with EGFR ex20ins. The translational study proposed the potential efficacy of higher dose osimertinib in a subgroup of EGFR ex20ins-positive NSCLC.

Durable response to immunotherapy plus chemotherapy in a patient with untreated, brain-metastatic, EGFR exon 20 insertion mutation lung adenocarcinoma: A case report

RATIONAL

Epidermal growth factor receptor (EGFR) 20 exon insertion is the second most common EGFR aberrations in non-small cell lung cancer (NSCLC). Despite some novel EGFR inhibitors, clinically obtainable management for this subset of patients remains an unmet need. there are no previous reports of upfront combination therapy with immunotherapy and chemotherapy for lung adenocarcinoma with brain metastasis harboring EGFR 20 insertion.

PATIENT CONCERNS

A 56-year-old man who sought care for dry cough was diagnosed with lung adenocarcinoma with brain metastases indicating a poor prognosis.

DIAGNOSIS

Next-generation sequencing of lung biopsied tissue revealed an EGFR exon 20 in-frame insertion (P772_H773insYNP+H773Y).

INTERVENTIONS

The patient started treatment of pemetrexed and carboplatin plus programmed cell death-1 inhibitor sintilimab in November 2019.

OUTCOMES

The patient achieved partial responses both intra- and extra-cranially. After 6 cycles of treatment, the patient accepted sintilimab plus pemetrexed every 3 weeks as maintenance therapy, which was well-tolerated without any toxicity and is still ongoing after 18 months since initiation of 1st-line treatment.

LESSONS

This is the first case report of the clinical benefit of upfront immune checkpoint inhibitors (ICIs) plus chemotherapy for a brain metastatic NSCLC patient harboring EGFR exon 20 insertion mutation. Further study is needed to validate the predictor involved in responders to ICIs-based therapy with EGFR mutations.

The importance of precision medicine in modern molecular oncology

With the rapid development of modern medical technology, information data modeling has been gradually applied to clinical diagnosis and treatment. Precision medicine is an important approach that focuses on individual patients in terms of their own characteristics, genomic information, proteomics and even social environments. Genome-wide high-throughput technologies, including DNA-seq, RNA-seq, exosome-seq…, contribute enormous amounts of molecular data to aid in diagnosis and analysis. Here, we review the developmental history of different next-generation sequencing platforms, introduce their applications in different tumor diagnosis and therapy, and further discuss the remaining challenges in precision medicine.

Microsecond-timescale MD simulation of EGFR minor mutation predicts the structural flexibility of EGFR kinase core that reflects EGFR inhibitor sensitivity

Approximately 15–30% of patients with lung cancer harbor mutations in the EGFR gene. Major EGFR mutations (>90% of EGFR-mutated lung cancer) are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs). Many uncommon EGFR mutations have been identified, but little is known regarding their characteristics, activation, and sensitivity to various EGFR-TKIs, including allosteric inhibitors. We encountered a case harboring an EGFR-L747P mutation, originally misdiagnosed with EGFR-del19 mutation using a routine diagnostic EGFR mutation test, which was resistant to EGFR-TKI gefitinib. Using this minor mutation and common EGFR-activating mutations, we performed the binding free energy calculations and microsecond-timescale molecular dynamic (MD) simulations, revealing that the L747P mutation considerably stabilizes the active conformation through a salt-bridge formation between K745 and E762. We further revealed why several EGFR inhibitors, including the allosteric inhibitor, were ineffective. Our computational structural analysis strategy would be beneficial for future drug development targeting the EGFR minor mutations.

Identification of Novel Alectinib-Resistant ALK Mutation G1202K with Sensitization to Lorlatinib: A Case Report and in silico Structural Modelling

Background

Drug resistance caused by G1202R/G1202del mutation in anaplastic lymphoma kinase (ALK) represents a great challenge in the clinic. The effect of other mutation(s) at G1202 on the available tyrosine kinase inhibitors (TKIs) in the clinic remains unknown.

Case Presentation

A 50-year-old Chinese male non-smoker with lung adenocarcinoma progressed with spinal metastasis after receiving chest radiation together with Pemetrexed and Cisplatin as adjuvant chemotherapy. Targeted next generation sequencing (NGS) identified EML4-ALK gene fusion in the resected left lung tissue. Local radiation followed by Crizotinib were used in the following treatment and the spinal metastasis was found to shrink, but the progression free survival (PFS) only lasted for 2 months with the appearance of brain metastasis. Afterwards, the patient benefited from the therapy of Alectinib with a PFS of 8 months. Then he progressed with metastases in right lung and pleural, and did not show response to the chemotherapy with Docetaxel plus Bevacizumab. The targeted sequencing consistently identified EML4-ALK gene fusion in both plasma and pleural effusion (PE), as well as a novel ALK G1202K mutation (c.3604_3605delGGinsAA). Given the lack of established or known drug treatment for this novel mutation, we implemented molecular dynamics (MD) simulation-guided drug sensitivity prediction, which results suggested Lorlatinib remains potent against G1202K mutant ALK. Therefore, Lorlatinib was used as the fourth-line therapy, which lead to the considerable efficacy with improved performance status (PS) score and reduced lung metastases. The structural mechanism underlying G1202K-induced drug resistance to different ALK-TKIs was also discussed.

Conclusion

Our case suggested the ALK-G1202K mutation may serve as a novel mechanism underlying the resistance to Alectinib, and provide direct evidence to support its sensitization to Lorlatinib. Our work represented an example of integrating in silico predictions into clinical practice.

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

Structural studies of full-length receptor tyrosine kinases and their implications for drug design

Receptor tyrosine kinases (RTKs) are important drug targets for cancer and immunological disorders. Crystal structures of individual RTK domains have contributed greatly to the structure-based drug design of clinically used drugs. Low-resolution structures from electron microscopy are now available for the RTKs, EGFR, PDGFR, and Kit. However, there are still no high-resolution structures of full-length RTKs due to the technical challenges of working with these complex, membrane proteins. Here, we review what has been learned from structural studies of these three RTKs regarding their mechanisms of ligand binding, activation, oligomerization, and inhibition. We discuss the implications for drug design. More structural data on full-length RTKs may facilitate the discovery of druggable sites and drugs with improved specificity and effectiveness against resistant mutants.

Acquired rare recurrent EGFR mutations as mechanisms of resistance to Osimertinib in lung cancer and in silico structural modelling

A growing number of progression on Osimertinib among EGFR-mutated lung cancers represents a great challenge clinically. Our study aims to gain insights into novel mechanisms of acquired resistance to Osimertinib. We performed genomic studies on 2 large independent cohorts of lung cancer patients with progressed diseases on different tyrosine kinase inhibitors (TKIs). In silico modeling was used to study the structural mechanism of selected EGFR mutations. Compared with the 1^st-TKIs-resistant group, EGFR mutations C797S/G, L718Q/V, L792F/H were significantly more enriched in the Osimertinib-resistant cohort, whose sensitivities to Osimertinib were successfully predicted. Importantly, a total of 14 low-frequency EGFR mutations were exclusively or significantly observed in the Osimertinib-resistant group, 7 were predicted to dramatically reduce the binding affinity of EGFR to Osimertinib (G796S, V802F, T725M, Q791L/H, P794S/R). Analysis of pre-Osimertinib treatment samples of two patients supported that EGFR V802F and G796S were acquired during the treatment. In addition, EGFR G796S was predicted to be susceptible to gefitinib. This study represented the largest real-world data so far investigating Osimertinib resistance in EGFR-mutated lung cancer. We identified a collection of coexistent EGFR rare mutations and provided possible guidance for those patients who progressed on the first-line treatment of Osimertinib.

Poor effect of osimertinib on EGFR exon 20 insertion-positive lung adenocarcinoma: A case report

INTRODUCTION

The clinical efficacy of osimertinib for patients with lung adenocarcinoma harboring epidermal growth factor receptor (EGFR) exon 20 insertion mutations is unclear. Few case reports exist on the successful treatment of such tumors with osimertinib. We report a case wherein osimertinib administration had no effect in a patient with EGFR exon 20 insertion-positive lung adenocarcinoma.

PATIENT CONCERNS

A 48-year-old never-smoking woman was referred to our hospital for chronic cough. Computed tomography (CT) and positron emission tomography-CT revealed a nodule in the right middle lobe, consolidation in the right upper lobe, multiple lymph node metastases, liver metastasis, and multiple bone metastases.

DIAGNOSIS

On the basis of further examination using transbronchial lung biopsy, the patient was diagnosed with cT1N3M1 stage IVB lung adenocarcinoma. An EGFR exon 20 insertion, without any additional mutations, was identified.

INTERVENTIONS

Daily oral administration of 80 mg osimertinib was initiated to treat the EGFR exon 20 insertion-positive lung adenocarcinoma.

OUTCOMES

Although the disease appeared to be stable 2.5 months after the administration of osimertinib, the tumor started to grow 3 months after administration, and carcinoembryonic antigen levels became higher than those before treatment. Thus, osimertinib was discontinued, and treatment with carboplatin as well as pemetrexed and bevacizumab was started, which the patient responded to.

CONCLUSION

EGFR exon 20 insertion mutations must be classified in more detail to assess the efficacy of EGFR tyrosine kinase inhibitors. Osimertinib doses that provide favorable therapeutic windows should be considered. Further clinical research is required to clarify the efficacy of osimertinib and other drugs for exon 20 insertion mutations.

TRK xDFG Mutations Trigger a Sensitivity Switch from Type I to II Kinase Inhibitors

On-target resistance to next-generation TRK inhibitors in TRK fusion-positive cancers is largely uncharacterized. In patients with these tumors, we found that TRK xDFG mutations confer resistance to type I next-generation TRK inhibitors designed to maintain potency against several kinase domain mutations. Computational modeling and biochemical assays showed that TRKA^G667 and TRKC^G696 xDFG substitutions reduce drug binding by generating steric hindrance. Concurrently, these mutations stabilize the inactive (DFG-out) conformations of the kinases, thus sensitizing these kinases to type II TRK inhibitors. Consistently, type II inhibitors impede the growth and TRK-mediated signaling of xDFG-mutant isogenic and patient-derived models. Collectively, these data demonstrate that adaptive conformational resistance can be abrogated by shifting kinase engagement modes. Given the prior identification of paralogous xDFG resistance mutations in other oncogene-addicted cancers, these findings provide insights into rational type II drug design by leveraging inhibitor class affinity switching to address recalcitrant resistant alterations. SIGNIFICANCE: In TRK fusion-positive cancers, TRK xDFG substitutions represent a shared liability for type I TRK inhibitors. In contrast, they represent a potential biomarker of type II TRK inhibitor activity. As all currently available type II agents are multikinase inhibitors, rational drug design should focus on selective type II inhibitor creation.This article is highlighted in the In This Issue feature, p. 1.

E487K-Induced Disorder in Functionally Relevant Dynamics of Mitochondrial Aldehyde Dehydrogenase 2

Mitochondrial aldehyde dehydrogenase 2 (ALDH2), which is a homotetramer assembled by two equivalent dimers, is an important enzyme that metabolizes ethanol-derived acetaldehyde to acetate in a coenzyme-dependent manner. The highly reactive acetaldehyde exhibits a toxic effect, indicating that the proper functioning of ALDH2 is essential to counteract aldehyde-associated diseases. It is known that the catalytic activity of ALDH2 is drastically impaired by a frequently observed mutation, E487K, in a dominant fashion. However, the molecular basis of the inactivation mechanism is elusive because of the complex nature of the dynamic behavior. Here, we performed microsecond-timescale molecular dynamics simulations of the proteins complexed with coenzymes. The E487K mutation elevated the conformational heterogeneity of the dimer interfaces, which are relatively distal from the substituted residue. Dynamic network analyses showed that Glu487 and the dimer interface were dynamically communicated, and the dynamic community further spanned throughout all of the subunits in the wild-type; however, this network was completely rearranged by the E487K mutation. The perturbation of the dynamic properties led to alterations of the global conformational motions and destabilization of the coenzyme binding required for receiving a proton from the catalytic nucleophile. The insights into the dynamic behavior of the dominant negative mutant in this work will provide clues to restore its function.

Molecular Dynamics Analysis of Binding Sites of Epidermal Growth Factor Receptor Kinase Inhibitors

The development of an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) is an ongoing and challenging research field. However, the dynamic motion of the binding site of EGFR has not been accurately depicted, hindering the improvement of EGFR TKI. For this reason, about 33 protein complexes (32 EGFR proteins plus 1 ErbB4 protein) were carefully curated and subsequently studied for dynamic movements of their binding sites by molecular dynamics simulations in this study. The analysis of root mean square deviation (RMSD) revealed that T790M mutation can make an impact on dynamic motion of binding sites; the RMSD value of the EGFR binding site was unrelated to inhibitory activity. The analysis of the radius of gyration (R _g) revealed that T790M can slightly shrink the value of R _g, thereby influencing the shape of the EGFR binding site. More interestingly, the R _g value can exhibit weak correlation with inhibitory activity of most inhibitors. The relationship between R _g and biological activity deserve our serious interest since the best scoring function, Xscore, cannot distinguish highly active EGFR inhibitors. The root mean square fluctuation (RMSF) analysis of key residues derived from binding sites indicated that the most flexible residue was ASP800 with a large RMSF value against the steady residue ALA743 with a small RMSF value, and two other residues (MET793 and LEU844) were supposed to be involved with molecular recognition. In short, the obtained results would be more effective for guiding the development of a novel EGFR kinase inhibitor.

Variability of EGFR exon 20 insertions in 24 468 Chinese lung cancer patients and their divergent responses to EGFR inhibitors

EGFR exon 20 insertions (EGFR e20ins) account for up to 10% of EGFR mutations in lung cancer; however, tumors with EGFR e20ins had poor response rates to EGFR tyrosine kinase inhibitors (TKIs) including gefitinib, erlotinib, afatinib, and osimertinib, and the heterogeneity of EGFR e20ins further complicates the clinical studies. Here, we retrospectively screened next‐generation sequencing (NGS) data from 24 468 lung cancer patients, and a total of 85 unique EGFR e20ins variants were identified in 547 cases (2.24%), with p.A767_V769dup (25.1%) and p.S768_D770dup (17.6%) being the most prevalent ones. Comprehensive genomic profiling revealed that TP53 mutations frequently coexisted with p.H773dup (77.8%, P = 0.0558) and p.A767_V769dup (62.8%, P = 0.0325), while RB1 mutations usually co‐occurred with p.H773_V774insAH (33.3%, P = 0.0551), implying that different EGFR e20ins variants might require distinct genomic context for tumorigenesis and/or maintenance. Despite that treatment regimens were highly diverse for EGFR e20ins‐positive patients, we observed an overall response rate of 14% and a disease control rate (DCR) of 38.4% in 65 patients who received at least one EGFR TKI. The progression‐free survival (PFS) differs significantly in six representative EGFR e20ins variants (P = 0.017), and EGFR p.A763_Y764insFQEA was associated with better PFS than other EGFR e20ins when treating with various EGFR TKIs. Some EGFR e20ins variants showed at least partial response to first‐generation EGFR TKIs, including p.A767_V769dup, p.S768_D770dup, p.N771_H773dup, p.A763_Y764insFQEA, and p.D770_N771insG. Poziotinib achieved higher DCR for p.S768_D770dup than for p.A767_V769dup, whereas osimertinib showed limited effects for these two insertions when used as the first‐line treatment. Overall, our results demonstrated that EGFR e20ins were highly diversified in terms of insertion patterns and co‐occurring mutations and these EGFR e20ins variants showed different clinical responses to various EGFR TKIs, suggesting the clinical importance of selecting proper EGFR TKI treatment based on the specific EGFR e20ins type.

Improvement strategies for successful next-generation sequencing analysis of lung cancer

Aim: We aimed to improve the success rate of NGS (next-generation sequencing) analysis through improved strategies of lung cancer sampling. Materials & methods: The improvement strategies are as follows. Surgically resected specimens were preferentially submitted in cooperation with pathologists and surgeons. In bronchoscopic samples, the size of the sample collection device and the number of samples collected was increased. Results: The strategies increased the success rate of NGS analysis of DNA from 69.3 to 91.1%, and that of RNA from 64.6 to 90.0%. Discussion: The introduction of strategies aimed at improving the success of NGS analysis resulted in an improvement in the success rate and brought us closer to the delivery of effective precision medicine in cancer therapy.

Complex EGFR mutations with secondary T790M mutation confer shorter osimertinib progression-free survival and overall survival in advanced non-small cell lung cancer

OBJECTIVES

Osimertinib is active against epidermal growth factor receptor (EGFR) T790M-mutated non-small cell lung cancer (NSCLC). However, its efficacy against complex EGFR mutations with T790M has not been evaluated.

MATERIALS AND METHODS

In order to detect complex EGFR mutations, we consecutively sequenced cancer tissues by RNA reverse transcription polymerase chain reaction. Patients with advanced NSCLC with activating EGFR mutation and secondary T790M who received osimertinib were enrolled. Patients' clinicopathologic characteristics, prior treatment details, and osimertinib treatment outcomes were analyzed.

RESULTS

Totally, 165 sequenced patients were analyzed. Eleven (7%) of them had complex EGFR mutations with T790M. The osimertinib response rate was 27%. They had a shorter progression-free survival (PFS) (median, 2.9 and 9.7 months, p < 0.001) and overall survival (OS) (median, 17.8 and 31.0 months, p = 0.01) than patients with a single EGFR mutation with T790M. After osimertinib failure, seven patients received rebiopsy with molecular analysis. Four lost the T790M, two transformed to small cell and one acquired C797S. Moreover, taking the median as the demarcation, patients received shorter prior EGFR tyrosine kinase inhibitor (TKI) treatment duration had a shorter osimertinib PFS (median, 7.3 and 13.8 months, p < 0.001) and OS (median, 21.5 and 36.7 months, p = 0.003). Multivariate Cox regression analysis confirmed complex EGFR mutations and prior EGFR TKI treatment duration were independent factors for osimertinib PFS and OS.

CONCLUSIONS

Complex EGFR mutations and shorter prior EGFR TKI treatment duration may confer shorter osimertinib PFS and OS in advanced NSCLC with secondary T790M mutation.

Improvement in predicting drug sensitivity changes associated with protein mutations using a molecular dynamics based alchemical mutation method

While molecular-targeted drugs have demonstrated strong therapeutic efficacy against diverse diseases such as cancer and infection, the appearance of drug resistance associated with genetic variations in individual patients or pathogens has severely limited their clinical efficacy. Therefore, precision medicine approaches based on the personal genomic background provide promising strategies to enhance the effectiveness of molecular-targeted therapies. However, identifying drug resistance mutations in individuals by combining DNA sequencing and in vitro analyses is generally time consuming and costly. In contrast, in silico computation of protein-drug binding free energies allows for the rapid prediction of drug sensitivity changes associated with specific genetic mutations. Although conventional alchemical free energy computation methods have been used to quantify mutation-induced drug sensitivity changes in some protein targets, these methods are often adversely affected by free energy convergence. In this paper, we demonstrate significant improvements in prediction performance and free energy convergence by employing an alchemical mutation protocol, MutationFEP, which directly estimates binding free energy differences associated with protein mutations in three types of a protein and drug system. The superior performance of MutationFEP appears to be attributable to its more-moderate perturbation scheme. Therefore, this study provides a deeper level of insight into computer-assisted precision medicine.

Computational approaches for identifying potential inhibitors on targeting protein interactions in drug discovery

In the era of big data, the interplay of artificial and human intelligence is the demanding job to address the concerns involving exchange of decisions between both sides. Drug discovery is one of the key sources of the big data, which involves synergy among various computational methods to achieve a clinical success. Rightful acquisition, mining and analysis of the data related to ligand and targets are crucial to accomplish reliable outcomes in the entire process. Novel designing and screening tactics are necessary to substantiate a potent and efficient lead compounds. Such methods are emphasized and portrayed in the current review targeting protein-ligand and protein-protein interactions involved in various diseases with potential applications.