What It Takes to Improve a First-Generation Inhibitor to a Second- or Third-Generation Small Molecule

Expert consensus on the use of third-generation EGFR-TKIs in EGFR-mutated advanced non-small cell lung cancer with various T790M mutations post-resistance to first-/second-generation EGFR-TKIs

Third-generation epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have emerged as the mainstay of treatment for advanced EGFR-mutant advanced non-small cell lung cancer (NSCLC), effectively overcoming the problems of acquired threonine-to-methionine (T790M) mutations associated with the first- or second-generation TKIs. Evidence from several studies suggests that these agents, including osimertinib and aumolertinib, also show potential benefits in T790M-negative or unknown populations, particularly those with brain metastases, where the high permeability of the blood-brain barrier allows effective control of intracranial lesions. Despite the encouraging results, further high-quality research, including prospective trials, is warranted to fully elucidate the efficacy profiles of these third-generation TKIs in T790M-negative or unknown NSCLC patients after first- or second-line TKI failure. The present expert consensus highlights the evolving role of third-generation EGFR-TKIs in overcoming therapeutic resistance and optimizing patient outcomes.

A demand-offer critical analysis of current drug development. Phase I drugs versus TCGA sequencing data

BACKGROUND

Phase I clinical trials have become increasingly critical to regulatory approvals of novel agents. In phase I drug development, a global problem of unknown magnitude is the multiplicity of similar drugs being investigated against the same target, colloquially known as the 'me too' phenomenon.

METHODS

Ranging from December 2020 to December 2022 we annotated phase I clinical trials present on clinicaltrials.gov. Public databases were queried for annotation of investigational agents (IAs). Extensive literature research and data mining were performed to annotate agents not present in public databases. The Cancer Genome Atlas (TCGA) pan-cancer sequencing cohort was used to perform second-level analyses to evaluate tumour types with a higher number of IA matches.

RESULTS

A total of 1054 unique drug targets were identified. The most frequent IA classes were: cell products (1223), small-molecule inhibitors (1110), antibodies (733), and vaccines (346). Only a minority (8.9%) of phase I IAs were explored against a target without a competitive agent; 7% of agents shared targets with 2-3 other agents. Unfortunately, the majority (84%) shared targets with at least four other agents. Using data from the TCGA pan-cancer sequencing potentially underserved histologies were identified. Analysis of alteration-IA matches revealed potentially frequent and unexplored alterations in many tumour types.

CONCLUSIONS

The majority of IAs (86%) shared targets with at least three other agents. We argue that these duplicative efforts could be redirected toward unmet needs instead.

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

TNIK Inhibition Has Dual Synergistic Effects on Tumor and Associated Immune Cells

Treatment with checkpoint inhibitors can be extraordinarily effective in a fraction of patients, particularly those whose tumors are pre-infiltrated by T cells. In others, efficacy is considerably lower, which has led to interest in developing strategies for sensitization to immunotherapy. Using various colorectal cancer mouse models, it is shown that the use of Traf2 and Nck-interacting protein kinase inhibitors (TNIKi) unexpectedly increases tumor infiltration by PD-1⁺ CD8⁺ T cells, thus contributing to tumor control. This appears to happen by two independent mechanisms, by inducing immunogenic cell death and separately by directly activating CD8. The use of TNIKi achieves complete tumor control in 50% of mice when combined with checkpoint inhibitor targeting PD-1. These findings reveal immunogenic properties of TNIKi and indicate that the proportion of colorectal cancers responding to checkpoint therapy can be increased by combining it with immunogenic kinase inhibitors.

Solid Tumors and Kinase Inhibition: Management and Therapy Efficacy Evolution

The increasing numbers of cancer cases worldwide and the exceedingly high mortality rates of some tumor subtypes raise the question about if the current protocols for cancer management are effective and what has been done to improve upon oncologic patients’ prognoses. The traditional chemo-immunotherapy options for cancer treatment focus on the use of cytotoxic agents that are able to overcome neoplastic clones’ survival mechanisms and induce apoptosis, as well as on the ability to capacitate the host’s immune system to hinder the continuous growth of malignant cells. The need to avert the highly toxic profiles of conventional chemo-immunotherapy and to overcome the emerging cases of tumor multidrug resistance has fueled a growing interest in the field of precision medicine and targeted molecular therapies in the last couple of decades, although relatively new alternatives in oncologic practices, the increased specificity, and the positive clinical outcomes achieved through targeted molecular therapies have already consolidated them as promising prospects for the future of cancer management. In recent years, the development and application of targeted drugs as tyrosine kinase inhibitors have enabled cancer treatment to enter the era of specificity. In addition, the combined use of targeted therapy, immunotherapy, and traditional chemotherapy has innovated the standard treatment for many malignancies, bringing new light to patients with recurrent tumors. This article comprises a series of clinical trials that, in the past 5 years, utilized kinase inhibitors (KIs) as a monotherapy or in combination with other cytotoxic agents to treat patients afflicted with solid tumors. The results, with varying degrees of efficacy, are reported.

The ALK inhibitors, alectinib and ceritinib, induce ALK-independent and STAT3-dependent glioblastoma cell death

Glioblastoma (GBM) is the most common, but extremely malignant, brain tumor; thus, the development of novel therapeutic strategies for GBMs is imperative. Many tyrosine kinase inhibitors (TKIs) have been approved for various cancers, yet none has demonstrated clinical benefit against GBM. Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase (RTK) that is confirmed only during the embryonic development period in humans. In addition, various ALK gene alterations are known to act as powerful oncogenes and therapeutic targets in various tumors. The antitumor activity of various TKIs was tested against three human GBM cell lines (U87MG, LN229, and GSC23), which expressed substantially low ALK levels; second‐generation ALK inhibitors, alectinib and ceritinib, effectively induced GBM cell death. In addition, treatment with either alectinib or ceritinib modulated the activation of various molecules downstream of RTK signaling and induced caspase‐dependent/‐independent cell death mainly by inhibiting signal transducer and activator of transcription 3 activation in human GBM cells. In addition, alectinib and ceritinib also showed antitumor activity against a U87MG cell line with acquired temozolomide resistance. Finally, oral administration of alectinib and ceritinib prolonged the survival of mice harboring intracerebral GBM xenografts compared with controls. These results suggested that treatment with the second‐generation ALK inhibitors, alectinib and ceritinib, might serve as a potent therapeutic strategy against GBM.

Overcoming Resistance to Tumor-Targeted and Immune-Targeted Therapies

Resistance to anticancer therapies includes primary resistance, usually related to lack of target dependency or presence of additional targets, and secondary resistance, mostly driven by adaptation of the cancer cell to the selection pressure of treatment. Resistance to targeted therapy is frequently acquired, driven by on-target, bypass alterations, or cellular plasticity. Resistance to immunotherapy is often primary, orchestrated by sophisticated tumor-host-microenvironment interactions, but could also occur after initial efficacy, mostly when only partial responses are obtained. Here, we provide an overview of resistance to tumor and immune-targeted therapies and discuss challenges of overcoming resistance, and current and future directions of development. SIGNIFICANCE: A better and earlier identification of cancer-resistance mechanisms could avoid the use of ineffective drugs in patients not responding to therapy and provide the rationale for the administration of personalized drug associations. A clear description of the molecular interplayers is a prerequisite to the development of novel and dedicated anticancer drugs. Finally, the implementation of such cancer molecular and immunologic explorations in prospective clinical trials could de-risk the demonstration of more effective anticancer strategies in randomized registration trials, and bring us closer to the promise of cure.

Key genes and drug delivery systems to improve the efficiency of chemotherapy

Cancer cells can develop resistance to anticancer drugs, thereby becoming tolerant to treatment through different mechanisms. The biological mechanisms leading to the generation of anticancer treatment resistance include alterations in transmembrane proteins, DNA damage and repair mechanisms, alterations in target molecules, and genetic responses, among others. The most common anti-cancer drugs reported to develop resistance to cancer cells include cisplatin, doxorubicin, paclitaxel, and fluorouracil. These anticancer drugs have different mechanisms of action, and specific cancer types can be affected by different genes. The development of drug resistance is a cellular response which uses differential gene expression, to enable adaptation and survival of the cell to diverse threatening environmental agents. In this review, we briefly look at the key regulatory genes, their expression, as well as the responses and regulation of cancer cells when exposed to anticancer drugs, along with the incorporation of alternative nanocarriers as treatments to overcome anticancer drug resistance.

Therapeutic Sequencing in ALK+ NSCLC

Anaplastic lymphoma kinase-rearranged non-small-cell lung cancer (ALK⁺ NSCLC) is a model disease for the use of targeted pharmaceuticals in thoracic oncology. Due to higher systemic and intracranial efficacy, the second-generation ALK tyrosine kinase inhibitors (TKI) alectinib and brigatinib have irrevocably displaced crizotinib as standard first-line treatment, based on the results of the ALEX and ALTA-1L trials. Besides, lorlatinib and brigatinib are the preferred second-line therapies for progression under second-generation TKI and crizotinib, respectively, based on the results of several phase II studies. Tissue or liquid rebiopsies at the time of disease progression, even though not mandated by the approval status of any ALK inhibitor, are gaining importance for individualization and optimization of patient management. Of particular interest are cases with off-target resistance, for example MET, HER2 or KRAS alterations, which require special therapeutic maneuvers, e.g., inclusion in early clinical trials or off-label administration of respectively targeted drugs. On the other hand, up to approximately half of the patients failing TKI, develop anatomically restricted progression, which can be initially tackled with local ablative measures without switch of systemic therapy. Among the overall biologically favorable ALK⁺ tumors, with a mean tumor mutational burden uniquely below 3 mutations per Mb and the longest survival among NSCLC currently, presence of the EML4-ALK fusion variant 3 and/or TP53 mutations identify high-risk cases with earlier treatment failure and a need for more aggressive surveillance and treatment strategies. The potential clinical utility of longitudinal ctDNA assays for earlier detection of disease progression and improved guidance of therapy in these patients is a currently a matter of intense investigation. Major pharmaceutical challenges for the field are the development of more potent, fourth-generation TKI and effective immuno-oncological interventions, especially ALK-directed cell therapies, which will be essential for further improving survival and achieving cure of ALK⁺ tumors.

Challenges and Opportunities in Cancer Drug Resistance

There has been huge progress in the discovery of targeted cancer therapies in recent years. However, even for the most successful and impactful cancer drugs which have been approved, both innate and acquired mechanisms of resistance are commonplace. These emerging mechanisms of resistance have been studied intensively, which has enabled drug discovery scientists to learn how it may be possible to overcome such resistance in subsequent generations of treatments. In some cases, novel drug candidates have been able to supersede previously approved agents; in other cases they have been used sequentially or in combinations with existing treatments. This review summarizes the current field in terms of the challenges and opportunities that cancer resistance presents to drug discovery scientists, with a focus on small molecule therapeutics. As part of this review, common themes and approaches have been identified which have been utilized to successfully target emerging mechanisms of resistance. This includes the increase in target potency and selectivity, alternative chemical scaffolds, change of mechanism of action (covalents, PROTACs), increases in blood-brain barrier permeability (BBBP), and the targeting of allosteric pockets. Finally, wider approaches are covered such as monoclonal antibodies (mAbs), bispecific antibodies, antibody drug conjugates (ADCs), and combination therapies.

Mechanism of action of a T cell-dependent bispecific antibody as a breakthrough immunotherapy against refractory colorectal cancer with an oncogenic mutation

T cell-dependent bispecific antibody (TDB)-induced T cell activation, which can eliminate tumor cells independent of MHC engagement, is expected to be a novel breakthrough immunotherapy against refractory cancer. However, the mechanism of action of TDBs has not been fully elucidated thus far. We focused on TDB-induced T cell-tumor cell contact as an important initial step in direct T cell-mediated tumor cell killing via transport of cytotoxic cell proteases (e.g., granzymes) with or without immunological synapse formation. Using an anti-EGFR/CD3 TDB, hEx3, we visualized and quantified T cell-tumor cell contact and demonstrated a correlation between the degree of cell contact and TDB efficacy. We also found that cytokines, including interferon-gamma (IFNγ) and tumor necrosis factor-alpha (TNFα) secreted by activated T cells, damaged tumor cells in a cell contact-independent manner. Moreover, therapeutic experiences clearly indicated that hEx3, unlike conventional anti-EGFR antibodies, was effective against colorectal cancer (CRC) cells with mutant KRAS, BRAF, or PIK3CA. In a pharmacokinetic analysis, T cells spread gradually in accordance with the hEx3 distribution within tumor tissue. Accordingly, we propose that TDBs should have four action steps: 1st, passive targeting via size-dependent tumor accumulation; 2nd, active targeting via specific binding to tumor cells; 3rd, T cell redirection toward tumor cells; and 4th, TDB-induced cell contact-dependent (direct) or -independent (indirect) tumor cell killing. Finally, our TDB hEx3 may be a promising reagent against refractory CRC with an oncogenic mutation associated with a poor prognosis.

Updated overall survival and final progression-free survival data for patients with treatment-naive advanced ALK-positive non-small-cell lung cancer in the ALEX study

BACKGROUND

The ALEX study demonstrated significantly improved progression-free survival (PFS) with alectinib versus crizotinib in treatment-naive ALK-positive non-small-cell lung cancer (NSCLC) at the primary data cut-off (9 February 2017). We report mature PFS (cut-off: 30 November 2018) and overall survival (OS) data up to 5 years (cut-off: 29 November 2019).

PATIENTS AND METHODS

Patients with stage III/IV ALK-positive NSCLC were randomized to receive twice-daily alectinib 600 mg (n = 152) or crizotinib 250 mg (n = 151) until disease progression, toxicity, withdrawal or death. Primary end point: investigator-assessed PFS. Secondary end points included objective response rate, OS and safety.

RESULTS

Mature PFS data showed significantly prolonged investigator-assessed PFS with alectinib [hazard ratio (HR) 0.43, 95% confidence interval (CI) 0.32-0.58; median PFS 34.8 versus 10.9 months crizotinib]. Median duration of OS follow-up: 48.2 months alectinib, 23.3 months crizotinib. OS data remain immature (37% of events). Median OS was not reached with alectinib versus 57.4 months with crizotinib (stratified HR 0.67, 95% CI 0.46-0.98). The 5-year OS rate was 62.5% (95% CI 54.3-70.8) with alectinib and 45.5% (95% CI 33.6-57.4) with crizotinib, with 34.9% and 8.6% of patients still on study treatment, respectively. The OS benefit of alectinib was seen in patients with central nervous system metastases at baseline [HR 0.58 (95% CI 0.34-1.00)] and those without [HR 0.76 (95% CI 0.45-1.26)]. Median treatment duration was longer with alectinib (28.1 versus 10.8 months), and no new safety signals were observed.

CONCLUSIONS

Mature PFS data from ALEX confirmed significant improvement in PFS for alectinib over crizotinib in ALK-positive NSCLC. OS data remain immature, with a higher 5-year OS rate with alectinib versus crizotinib. This is the first global randomized study to show clinically meaningful improvement in OS for a next-generation tyrosine kinase inhibitor versus crizotinib in treatment-naive ALK-positive NSCLC.

CLINICAL TRIALS NUMBER

NCT02075840.

Computational Approaches for the Design of (Mutant-)Selective Tyrosine Kinase Inhibitors: State-of-the-Art and Future Prospects

Kinases remain one of the major attractive therapeutic targets for a large number of indications such as cancer, rheumatoid arthritis, cardiac failure and many others. Design and development of kinase inhibitors (ATP-competitive, allosteric or covalent) is a clinically validated and successful strategy in the pharmaceutical industry. The perks come with limitations, particularly the development of resistance to highly potent and selective inhibitors. When this happens, the cycle needs to be repeated, i.e., the design and development of kinase inhibitors active against the mutated forms. The complexity of tumor milieu makes it awfully difficult for these molecularly-targeted therapies to work. Every year newer and better versions of these agents are introduced in the clinic. Several computational approaches such as structure-, ligand-based or hybrid ones continue to live up to their potential in discovering novel kinase inhibitors. New schools of thought in this area continue to emerge, e.g., development of dual-target kinase inhibitors. But there are fundamental issues with this approach. It is indeed difficult to selectively optimize binding at two entirely different or related kinases. In addition to the conventional strategies, modern technologies (machine learning, deep learning, artificial intelligence, etc.) started yielding the results and building success stories. Computational tools invariably played a critical role in catalysing the phenomenal progress in kinase drug discovery field. The present review summarized the progress in utilizing computational methods and tools for discovering (mutant-)selective tyrosine kinase inhibitor drugs in the last three years (2017-2019). Representative investigations have been discussed, while others are merely listed. The author believes that the enthusiastic reader will be inspired to dig out the cited literature extensively to appreciate the progress made so far and the future prospects of the field.