The BATTLE-2 Study: A Biomarker-Integrated Targeted Therapy Study in Previously Treated Patients With Advanced Non-Small-Cell Lung Cancer

Predicting treatment response and prognosis of immune checkpoint inhibitors-based combination therapy in advanced hepatocellular carcinoma using a longitudinal CT-based radiomics model: a multicenter study

BACKGROUND

Identifying effective predictive strategies to assess the response of immune checkpoint inhibitors (ICIs)-based combination therapy in advanced hepatocellular carcinoma (HCC) is crucial. This study presents a new longitudinal CT-based radiomics model to predict treatment response and prognosis in advanced HCC patients undergoing ICIs-based combination therapy.

METHODS

Longitudinal CT images were collected before and during the treatment for HCC patients across three institutions from January 2019 to April 2022. A total of 1316 radiomic features were extracted from arterial and portal venous phase abdominal CT images for each patient. A model called Longitudinal Whole-liver CT-based Radiomics (LWCTR) was developed to categorize patients into responders or non-responders using radiomic features and clinical information through support vector machine (SVM) classifiers. The area under the curve (AUC) was used as the performance metric and subsequently applied for risk stratification and prognostic assessment. The Shapley Additive explanations (SHAP) method was used to calculate the Shapley value, which explains the contribution of each feature in the SVM model to the prediction.

RESULTS

This study included 395 eligible participants, with a median age of 57 years (IQR 51-66), comprising 344 males and 51 females. The LWCTR model performed well in predicting treatment response, achieving an AUC of 0.883 (95% confidence interval [CI] 0.881-0.888) in the training cohort, 0.876 (0.858-0.895) in the internal validation cohort, and 0.875 (0.860-0.887) in the external test cohort. The Rad-Nomo model, integrating the LWCTR model's prediction score (Rad-score) with the modified Response Evaluation Criteria in Solid Tumors (mRECIST), demonstrated strong prognostic performance. It achieved time-dependent AUC values of 0.902, 0.823, and 0.850 at 1, 2, and 3 years in the internal validation cohort and 0.893, 0.848, and 0.762 at the same intervals in the external test cohort.

CONCLUSION

The proposed LWCTR model performs well in predicting treatment response and prognosis in patients with HCC receiving ICIs-based combination therapy, potentially contributing to personalized and timely treatment decisions.

Next-generation sequencing for guiding matched targeted therapies in people with relapsed or metastatic cancer

BACKGROUND

Matched targeted therapies (MTT) given alone or in combination with systemic anti-cancer therapies have delivered proven survival benefit for many people with newly diagnosed cancer. However, there is little evidence of their effectiveness in the recurrent or late-stage setting. With this uncertainty, alongside the perception that late-stage cancers are too genetically heterogenous or too mutationally diverse to benefit from matched targeted therapies, next-generation sequencing (NGS) of tumours in people with refractory cancer remains a low priority. As a result, next-generation sequencing testing of recurrent or late-stage disease is discouraged. We lack evidence to support the utility of next generation sequencing in guiding matched targeted therapies in this setting.

OBJECTIVES

To evaluate the benefits and harms of matched targeted therapies in people with advanced cancers in randomised controlled trials.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, ClinicalTrials.gov, and the World Health Organisation International Clinical Trials Registry Platform (WHO-ICTRP) search portal up to 30th October 2024. We also screened reference lists of included studies and also the publications that cited these studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that had enroled participants with advanced/refractory solid or haematological cancers who had progressed through at least one line of standard anti-cancer systemic therapy. To be eligible, all participants should have received matched targeted therapy based on next-generation sequencing carried out on their tumour (tumour tissue, blood or bone marrow).

DATA COLLECTION AND ANALYSIS

We systematically searched medical databases (e.g. MEDLINE, Embase) and trial registers for randomised controlled trials (RCTs). Outcomes of interest were progression-free survival (PFS), overall survival (OS), overall response rates (ORR), serious (grade 3 or 4) adverse events (AEs) and quality of life (QOL). We used a random-effects model to pool outcomes across studies and compared predefined subgroups using interaction tests. Grading of Recommendations Assessment, Development and Evaluation (GRADE) assessment of certainty was used to evaluate the quality of evidence.

MAIN RESULTS

We identified a total of 37 studies, out of which 35 studies (including 9819 participants) were included in the meta-analysis. All included studies compared a matched targeted therapy intervention to standard-of-care treatment, non-matched targeted therapies or no treatment (best supportive care): Matched targeted therapy versus standard-of-care treatment Matched targeted therapy (MTT) compared with standard systematic therapy probably reduces the risk of disease progression by 34% (hazard ratio (HR) = 0.66, 95% confidence interval (CI) 0.59 to 0.74; 14 studies, 3848 participants; moderate-certainty evidence). However, MTT might have little to no difference in risk of death (HR = 0.85, 95% CI 0.75 to 0.97; 14 studies, 3848 participants; low-certainty evidence) and may increase overall response rates (low-certainty evidence). There was no clear evidence of a difference in severe (grade 3/4) adverse events between matched targeted therapy and standard-of-care treatment (low-certainty evidence). There was limited evidence of a difference in quality of life between groups (very low-certainty of evidence). Matched targeted therapy in combination with standard-of-care treatment versus standard-of-care treatment alone Matched targeted therapy in combination with standard-of-care treatment compared with standard-of-care treatment alone probably reduces the risk of disease progression by 39% (HR = 0.61, 95% CI 0.53-0.70, 14 studies, 2,637 participants; moderate-certainty evidence) and risk of death by 21% (HR = 0.79, 95% CI 0.70 to 0.89; 11 studies, 2575 participants, moderate-certainty evidence). The combination of MTT and standard-of-care treatment may also increase overall response rates (low-certainty evidence). There was limited evidence of a difference in the incidence of severe adverse events (very low-certainty evidence) and quality of life between the groups (very low-certainty of evidence). Matched targeted therapy versus non-matched targeted therapy Matched targeted therapy compared with non-matched targeted therapy probably reduces the risk of disease progression by 24% (HR = 0.76, 95% CI 0.64 to 0.89; 3 studies, 1568 participants; moderate-certainty evidence) and may reduce the risk of death by 25% (HR = 0.75, 95% CI 0.65 to 0.86, 1307 participants; low-certainty evidence). There was little to no effect on overall response rates between MTT and non-MTT. There was no clear evidence of a difference in overall response rates (low-certainty evidence) and severe adverse events between MTT and non-MTT (low-certainty evidence). None of the studies comparing MTT and non-MTT reported quality of life. Matched targeted therapy versus best supportive care Matched targeted therapy compared with the best supportive care (BSC) i.e. no active treatment probably reduces the risk of disease progression by 63% (HR 0.37, 95% CI 0.28 to 0.50; 4 studies, 858 participants; moderate-certainty evidence). There was no clear evidence of a difference in overall survival between groups (HR = 0.88, 95% CI 0.73 to 1.06, 3 studies, 783 participants; low-certainty evidence). There was no clear evidence of a difference in overall response rates (very low-certainty of evidence) and incidence of severe adverse events (very low-certainty of evidence) between the groups. Quality of life was reported in a single study but did not provide composite scores. Risk of bias The overall risk of bias was judged low for eight studies, unclear for two studies, and the remaining 27 studies were high risk.

AUTHORS' CONCLUSIONS

Matched targeted therapies guided by next-generation sequencing in people with advanced cancer prolongs the time before cancer progresses compared to standard therapies. However, there is limited evidence to suggest that it prolongs overall survival, improves the quality of life or increases adverse events. Importantly, this review supports equitable access to next-generation sequencing technology for all people with advanced cancer and offers them the opportunity to access genotype-matched targeted therapies.

Phosphatidic acid as a cofactor of mTORC1 in platinum-based chemoresistance: Mechanisms and therapeutic potential

Platinum-based chemotherapeutics, such as cisplatin and carboplatin, are widely used to treat various malignancies. However, the development of chemoresistance remains a significant challenge, limiting their efficacy. This review explores the multifaceted mechanisms of platinum-based chemoresistance, with a particular focus on the mammalian target of rapamycin complex 1 (mTORC1) signaling pathway, which plays a critical role in promoting tumor survival and resistance to platinum compounds. Additionally, we examined the role of phosphatidic acid (PA) and its synthesizing enzymes, phospholipase D (PLD) and lysophosphatidic acid acyltransferase (LPAAT), in the regulation of mTORC1 activity. Given the involvement of mTORC1 in chemoresistance, we evaluated the potential of mTOR inhibitors as a therapeutic strategy to overcome platinum resistance. Finally, we discuss combination therapies targeting the mTOR pathway alongside conventional chemotherapy to improve treatment outcomes. This review highlights the potential of targeting mTORC1 and related pathways to improve therapeutic strategies for chemoresistant cancers.

Novel clinical trial designs emerging from the molecular reclassification of cancer

Next-generation sequencing has revealed the disruptive reality that advanced/metastatic cancers have complex and individually distinct genomic landscapes, necessitating a rethinking of treatment strategies and clinical trial designs. Indeed, the molecular reclassification of cancer suggests that it is the molecular underpinnings of the disease, rather than the tissue of origin, that mostly drives outcomes. Consequently, oncology clinical trials have evolved from standard phase 1, 2, and 3 tissue-specific studies; to tissue-specific, biomarker-driven trials; to tissue-agnostic trials untethered from histology (all drug-centered designs); and, ultimately, to patient-centered, N-of-1 precision medicine studies in which each patient receives a personalized, biomarker-matched therapy/combination of drugs. Innovative technologies beyond genomics, including those that address transcriptomics, immunomics, proteomics, functional impact, epigenetic changes, and metabolomics, are enabling further refinement and customization of therapy. Decentralized studies have the potential to improve access to trials and precision medicine approaches for underserved minorities. Evaluation of real-world data, assessment of patient-reported outcomes, use of registry protocols, interrogation of exceptional responders, and exploitation of synthetic arms have all contributed to personalized therapeutic approaches. With greater than 1 × 1012 potential patterns of genomic alterations and greater than 4.5 million possible three-drug combinations, the deployment of artificial intelligence/machine learning may be necessary for the optimization of individual therapy and, in the near future, also may permit the discovery of new treatments in real time.

Recent advances in the methods and clinical applications of next-generation sequencing in genomic profiling and precision cancer therapy

Cancer is a major cause of death worldwide. Next-generation sequencing (NGS) has dramatically increased the sequencing data output and transformed biomedical investigations. NGS enables the generations of genetic data specific to patients from tumor tissue samples so that targeted therapies can be used. The obtained data further allows the prioritization of effective therapies based on the tumor-specific genotype. Practitioners in the field of clinical genomics can make the best use of testing facilities while lessening the possible off-targets by choosing a priori gene set. Therefore, targeted sequencing has arisen as a more affordable technique for the genomic profiling of tumors. Drug resistance is commonly observed in cancer because of mutations. Thus, precise genetic and molecular profiling of tumors ought to be routinely done prior to the use of targeted therapy or precision cancer therapy. NGS already has the capacity to ameliorate genetic screening in families with previous histories of the high occurrence of various cancer-associated genes, including TP53, APC, BRCA2, and BRCA1. By using NGS system, researchers detected increased variants in cancer cells with greater specificity and sensitivity than conventional diagnostic approaches, which suggest the potential of NGS in diagnosis. The field of precision cancer therapy is continuously growing and because of their specificity at the molecular level has improved the management and treatment of numerous cancers. These therapies are less toxic and more efficient compared to conventional chemotherapies used in cancer treatment. The field of precision cancer therapy is likely to significantly expand as NGS system advances. This review provides extensive information regarding current advances in the NGS field in terms of methods, clinical applications, genomic profiling, and the role of NGS of precision cancer therapy.

Implementation of statistical features of a Bayesian two-armed responsive adaptive randomization trial with post hoc analysis of time trend drift

Bayesian adaptive designs with response adaptive randomization (RAR) have the potential to benefit more participants in a clinical trial. While there are many papers that describe RAR designs and results, there is a scarcity of works reporting the details of RAR implementation from a statistical point exclusively. In this paper, we introduce the statistical methodology and implementation of the trial Changing the Default (CTD). CTD is a single-center prospective RAR comparative effectiveness trial to compare opt-in to opt-out tobacco treatment approaches for hospitalized patients. The design assumed an uninformative prior, conservative initial allocation ratio, and a higher threshold for stopping for success to protect results from statistical bias. A particular emerging concern of RAR designs is the possibility that time trends will occur during the implementation of a trial. If there is a time trend and the analytic plan does not prespecify an appropriate model, this could lead to a biased trial. Adjustment for time trend was not pre-specified in CTD, but post hoc time-adjusted analysis showed no presence of influential drift. This trial was an example of a successful two-armed confirmatory trial with a Bayesian adaptive design using response adaptive randomization.

Synergy of EGFR and AURKA Inhibitors in KRAS-mutated Non-small Cell Lung Cancers

The most common oncogenic driver mutations for non-small cell lung cancer (NSCLC) activate EGFR or KRAS. Clinical trials exploring treatments for EGFR- or KRAS-mutated (EGFRmut or KRASmut) cancers have focused on small-molecule inhibitors targeting the driver mutations. Typically, these inhibitors perform more effectively based on combination with either chemotherapies, or other targeted therapies. For EGFRmut NSCLC, a combination of inhibitors of EGFR and Aurora-A kinase (AURKA), an oncogene commonly overexpressed in solid tumors, has shown promising activity in clinical trials. Interestingly, a number of recent studies have indicated that EGFR activity supports overall viability of tumors lacking EGFR mutations, and AURKA expression is abundant in KRASmut cell lines. In this study, we have evaluated dual inhibition of EGFR and AURKA in KRASmut NSCLC models. These data demonstrate synergy between the EGFR inhibitor erlotinib and the AURKA inhibitor alisertib in reducing cell viability and clonogenic capacity in vitro, associated with reduced activity of EGFR pathway effectors, accumulation of enhanced aneuploid cell populations, and elevated cell death. Importantly, the erlotinib-alisertib combination also synergistically reduces xenograft growth in vivo. Analysis of signaling pathways demonstrated that the combination of erlotinib and alisertib was more effective than single-agent treatments at reducing activity of EGFR and pathway effectors following either brief or extended administration of the drugs. In sum, this study indicates value of inhibiting EGFR in KRASmut NSCLC, and suggests the specific value of dual inhibition of AURKA and EGFR in these tumors.

SIGNIFICANCE

The introduction of specific KRAS G12C inhibitors to the clinical practice in lung cancer has opened up opportunities that did not exist before. However, G12C alterations are only a subtype of all KRAS mutations observed. Given the high expression of AURKA in KRASmut NSCLC, our study could point to a potential therapeutic option for this subgroup of patients.

Doubly adaptive biased coin design to improve Bayesian clinical trials with time-to-event endpoints

Clinical trialists often face the challenge of balancing scientific questions with other design features, such as improving efficiency, minimizing exposure to inferior treatments, and simultaneously comparing multiple treatments. While Bayesian response adaptive randomization (RAR) is a popular and effective method for achieving these objectives, it is known to have large variability and a lack of explicit theoretical results, making its use in clinical trials a subject of concern. It is desirable to propose a design that targets the same allocation proportion as Bayesian RAR and achieves the above objectives but addresses the concerns over Bayesian RAR. We propose the frequentist doubly adaptive biased coin designs (DBCD) targeting ethical allocation proportions from the Bayesian framework to satisfy different objectives in clinical trials with time-to-event endpoints. We derive the theoretical properties of the proposed adaptive randomization design and show through comprehensive numerical simulations that it can achieve ethical objectives without sacrificing efficiency. Our combined theoretical and numerical results offer a strong foundation for the practical use of RAR in real clinical trials.

Efficacy of Sorafenib-Based Therapies for Non-Small Cell Lung Cancer

Lung cancer remains the leading cause of cancer-related deaths, with a poor prognosis. Of the two types, non-small cell lung cancer (NSCLC) is the major and most prevalent type and associated with low response rates to the current treatment options. Sorafenib, a multitargeted tyrosine kinase inhibitor used for various malignancies, gained attention for its potential efficacy in NSCLC. This review paper focuses on the findings of recent in vitro, in vivo, and clinical studies regarding the efficacy of sorafenib. Overall, sorafenib has shown definitive therapeutic potential in NSCLC cell lines, xenografts, and human subjects. Novel approaches to sorafenib delivery may improve its efficacy and should be the focus of further studies.

Bayesian interim analysis for prospective randomized studies: reanalysis of the acute myeloid leukemia HOVON 132 clinical trial

Randomized controlled trials (RCTs) are the gold standard to establish the benefit-risk ratio of novel drugs. However, the evaluation of mature results often takes many years. We hypothesized that the addition of Bayesian inference methods at interim analysis time points might accelerate and enforce the knowledge that such trials may generate. In order to test that hypothesis, we retrospectively applied a Bayesian approach to the HOVON 132 trial, in which 800 newly diagnosed AML patients aged 18 to 65 years were randomly assigned to a "7 + 3" induction with or without lenalidomide. Five years after the first patient was recruited, the trial was negative for its primary endpoint with no difference in event-free survival (EFS) between experimental and control groups (hazard ratio [HR] 0.99, p = 0.96) in the final conventional analysis. We retrospectively simulated interim analyses after the inclusion of 150, 300, 450, and 600 patients using a Bayesian methodology to detect early lack of efficacy signals. The HR for EFS comparing the lenalidomide arm with the control treatment arm was 1.21 (95% CI 0.81-1.69), 1.05 (95% CI 0.86-1.30), 1.00 (95% CI 0.84-1.19), and 1.02 (95% CI 0.87-1.19) at interim analysis 1, 2, 3 and 4, respectively. Complete remission rates were lower in the lenalidomide arm, and early deaths more frequent. A Bayesian approach identified that the probability of a clinically relevant benefit for EFS (HR < 0.76, as assumed in the statistical analysis plan) was very low at the first interim analysis (1.2%, 0.6%, 0.4%, and 0.1%, respectively). Similar observations were made for low probabilities of any benefit regarding CR. Therefore, Bayesian analysis significantly adds to conventional methods applied for interim analysis and may thereby accelerate the performance and completion of phase III trials.

New clinical trial design in precision medicine: discovery, development and direction

In the era of precision medicine, it has been increasingly recognized that individuals with a certain disease are complex and different from each other. Due to the underestimation of the significant heterogeneity across participants in traditional "one-size-fits-all" trials, patient-centered trials that could provide optimal therapy customization to individuals with specific biomarkers were developed including the basket, umbrella, and platform trial designs under the master protocol framework. In recent years, the successive FDA approval of indications based on biomarker-guided master protocol designs has demonstrated that these new clinical trials are ushering in tremendous opportunities. Despite the rapid increase in the number of basket, umbrella, and platform trials, the current clinical and research understanding of these new trial designs, as compared with traditional trial designs, remains limited. The majority of the research focuses on methodologies, and there is a lack of in-depth insight concerning the underlying biological logic of these new clinical trial designs. Therefore, we provide this comprehensive review of the discovery and development of basket, umbrella, and platform trials and their underlying logic from the perspective of precision medicine. Meanwhile, we discuss future directions on the potential development of these new clinical design in view of the "Precision Pro", "Dynamic Precision", and "Intelligent Precision". This review would assist trial-related researchers to enhance the innovation and feasibility of clinical trial designs by expounding the underlying logic, which be essential to accelerate the progression of precision medicine.

Intestinal Tuft Cells: Morphology, Function, and Implications for Human Health

Tuft cells are a rare and morphologically distinct chemosensory cell type found throughout many organs, including the gastrointestinal tract. These cells were identified by their unique morphologies distinguished by large apical protrusions. Ultrastructural data have begun to describe the molecular underpinnings of their cytoskeletal features, and tuft cell-enriched cytoskeletal proteins have been identified, although the connection of tuft cell morphology to tuft cell functionality has not yet been established. Furthermore, tuft cells display variations in function and identity between and within tissues, leading to the delineation of distinct tuft cell populations. As a chemosensory cell type, they display receptors that are responsive to ligands specific for their environment. While many studies have demonstrated the tuft cell response to protists and helminths in the intestine, recent research has highlighted other roles of tuft cells as well as implicated tuft cells in other disease processes including inflammation, cancer, and viral infections. Here, we review the literature on the cytoskeletal structure of tuft cells. Additionally, we focus on new research discussing tuft cell lineage, ligand-receptor interactions, tuft cell tropism, and the role of tuft cells in intestinal disease. Finally, we discuss the implication of tuft cell-targeted therapies in human health and how the morphology of tuft cells may contribute to their functionality.

Research Reviews: Advances in methods for evaluating child and adolescent mental health interventions

BACKROUND

The evidence base for interventions for child mental health and neurodevelopment is weak and the current capacity for rigorous evaluation limited. We describe some of the challenges that make this field particularly difficult and expensive for evaluation studies.

METHODS

We describe and review the use of novel study designs and analysis methodology for their potential to improve this situation.

RESULTS

While several novel designs appeared ill-suited to our field, systematic review found others that offered potential but had yet to be widely adopted, some not at all.

CONCLUSIONS

While funding is inevitably a constraint, we argue that improvements in the evidence base of both current and new treatments will only be achieved by the adoption of a number of these new technologies and study designs, the consistent application of rigorous constructive but demanding standards, and the engagement of the public, patients, clinical and research services to build a design, recruitment, and analysis infrastructure.

Design and Statistical Innovations in a Platform Trial for Amyotrophic Lateral Sclerosis

Platform trials allow efficient evaluation of multiple interventions for a specific disease. The HEALEY ALS Platform Trial is testing multiple investigational products in parallel and sequentially in persons with amyotrophic lateral sclerosis (ALS) with the goal of rapidly identifying novel treatments to slow disease progression. Platform trials have considerable operational and statistical efficiencies compared with typical randomized controlled trials due to their use of shared infrastructure and shared control data. We describe the statistical approaches required to achieve the objectives of a platform trial in the context of ALS. This includes following regulatory guidance for the disease area of interest and accounting for potential differences in outcomes of participants within the shared control (potentially due to differences in time of randomization, mode of administration, and eligibility criteria). Within the HEALEY ALS Platform Trial, the complex statistical objectives are met using a Bayesian shared parameter analysis of function and survival. This analysis serves to provide a common integrated estimate of treatment benefit, overall slowing in disease progression, as measured by function and survival while accounting for potential differences in the shared control group using Bayesian hierarchical modeling. Clinical trial simulation is used to provide a better understanding of this novel analysis method and complex design. ANN NEUROL 2023;94:547-560.

Autotaxin suppresses cytotoxic T cells via LPAR5 to promote anti-PD-1 resistance in non-small cell lung cancer

Non-small cell lung cancers that harbor concurrent KRAS and TP53 (KP) mutations are immunologically warm tumors with partial responsiveness to anti-PD-(L)1 blockade; however, most patients observe little or no durable clinical benefit. To identify novel tumor-driven resistance mechanisms, we developed a panel of KP murine lung cancer models with intrinsic resistance to anti-PD-1 and queried differential gene expression between these tumors and anti-PD-1-sensitive tumors. We found that the enzyme autotaxin (ATX), and the metabolite it produces, lysophosphatidic acid (LPA), were significantly upregulated in resistant tumors and that ATX directly modulated antitumor immunity, with its expression negatively correlating with total and effector tumor-infiltrating CD8+ T cells. Pharmacological inhibition of ATX, or the downstream receptor LPAR5, in combination with anti-PD-1 was sufficient to restore the antitumor immune response and efficaciously control lung tumor growth in multiple KP tumor models. Additionally, ATX was significantly correlated with inflammatory gene signatures, including a CD8+ cytolytic score in multiple lung adenocarcinoma patient data sets, suggesting that an activated tumor-immune microenvironment upregulates ATX and thus provides an opportunity for cotargeting to prevent acquired resistance to anti-PD-1 treatment. These data reveal the ATX/LPA axis as an immunosuppressive pathway that diminishes the immune checkpoint blockade response in lung cancer.

Stratification of patients with KRAS-mutated advanced non-small cell lung cancer: improving prognostics

INTRODUCTION

KRAS is the most frequently mutated oncogene in cancer and encodes a key signaling protein in tumors. Due to its high affinity for GTP and the lack of a large binding pocket that allosteric inhibitors can occupy, KRAS has long been considered 'non-druggable.' Finding effective treatment measures for patients with KRAS mutations is our top priority.

AREAS COVERED

In this article, we will provide an overview of the KRAS pathway and review the current state of therapeutic strategies for targeting oncogenic KRAS, as well as their potential to improve outcomes in patients with KRAS-mutant malignancies. We will also discuss the development of these strategies and gave an outlook on prospects.

EXPERT OPINION

KRAS mutations have posed a significant challenge in the treatment of advanced non-small cell lung cancer (NSCLC) over the past few decades. However, the emergence of immunotherapy and KRAS inhibitors, such as Sotorasib (AMG 510) and Adagrasib (MRTX849), has marked a new era in cancer therapy. As more research and clinical trials continue, we anticipate the development of more effective treatment strategies and better options for lung cancer patients.

A Bayesian-adaptive decision-theoretic approach can reduce the sample sizes for multiarm exercise oncology trials

OBJECTIVES

Adaptive designs may reduce trial sample sizes and costs. This study illustrates a Bayesian-adaptive decision-theoretic design applied to a multiarm exercise oncology trial.

STUDY DESIGN AND SETTING

In the Physical exercise during Adjuvant Chemotherapy Effectiveness Study (PACES) trial, 230 breast cancer patients receiving chemotherapy were randomized to supervised resistance and aerobic exercise (OnTrack), home-based physical activity (OncoMove) or usual care (UC). Data were reanalyzed as an adaptive trial using both Bayesian decision-theoretic and a frequentist group-sequential approach incorporating interim analyses after every 36 patients. Endpoint was chemotherapy treatment modifications (any vs. none). Bayesian analyses were performed for different continuation thresholds and settings with and without arm dropping and both in a 'pick-the-winner' and a 'pick-all-treatments-superior-to-control' setting.

RESULTS

Treatment modifications occurred in 34% of patients in UC and OncoMove vs. 12% in OnTrack (P = 0.002). Using a Bayesian-adaptive decision-theoretic design, OnTrack was identified as most effective after 72 patients in the 'pick-the-winner' setting and after 72-180 patients in the 'pick-all-treatments-superior-to-control' setting. In a frequentist setting, the trial would have been stopped after 180 patients, and the proportion of patients with treatment modifications was significantly lower for OnTrack than UC.

CONCLUSION

A Bayesian-adaptive decision-theoretic approach substantially reduced the sample size required for this three-arm exercise trial, especially in the 'pick-the-winner' setting.

Response-adaptive randomization in clinical trials: from myths to practical considerations

Response-Adaptive Randomization (RAR) is part of a wider class of data-dependent sampling algorithms, for which clinical trials are typically used as a motivating application. In that context, patient allocation to treatments is determined by randomization probabilities that change based on the accrued response data in order to achieve experimental goals. RAR has received abundant theoretical attention from the biostatistical literature since the 1930's and has been the subject of numerous debates. In the last decade, it has received renewed consideration from the applied and methodological communities, driven by well-known practical examples and its widespread use in machine learning. Papers on the subject present different views on its usefulness, and these are not easy to reconcile. This work aims to address this gap by providing a unified, broad and fresh review of methodological and practical issues to consider when debating the use of RAR in clinical trials.

KRAS-Mutant Lung Cancer: Targeting Molecular and Immunologic Pathways, Therapeutic Advantages and Restrictions

RAS mutations are among the most common oncogenic mutations in human cancers. Among RAS mutations, KRAS has the highest frequency and is present in almost 30% of non-small-cell lung cancer (NSCLC) patients. Lung cancer is the number one cause of mortality among cancers as a consequence of outrageous aggressiveness and late diagnosis. High mortality rates have been the reason behind numerous investigations and clinical trials to discover proper therapeutic agents targeting KRAS. These approaches include the following: direct KRAS targeting; synthetic lethality partner inhibitors; targeting of KRAS membrane association and associated metabolic rewiring; autophagy inhibitors; downstream inhibitors; and immunotherapies and other immune-modalities such as modulating inflammatory signaling transcription factors (e.g., STAT3). The majority of these have unfortunately encountered limited therapeutic outcomes due to multiple restrictive mechanisms including the presence of co-mutations. In this review we plan to summarize the past and most recent therapies under investigation, along with their therapeutic success rate and potential restrictions. This will provide useful information to improve the design of novel agents for treatment of this deadly disease.

A Meroterpenoid from Tibetan Medicine Induces Lung Cancer Cells Apoptosis through ROS-Mediated Inactivation of the AKT Pathway

As a traditional Tibetan medicine in China, Meconopsis grandis Prain has been used to treat a variety of illnesses by local people for thousands of years. However, the active ingredients contained in Meconopsis grandis Prain and its pharmacodynamic mechanisms have scarcely been reported. We isolated a meroterpenoid named D1399 from Meconopsis grandis Prain endophytic fungi with strong antitumor activity. The structure analysis showed that D1399 is an alkaloid containing a 13-membered macrocyclic structure. The IC₅₀ of D1399 for human lung cancer cells' viability ranged from 0.88 to 2.45 μM. Furthermore, we utilized TUNEL assay and western blotting to investigate the antitumor effectiveness of D1399. The results have shown that D1399 induced the apoptosis of lung cancer cells on the extrinsic and intrinsic pathways by boosting ROS generation and repressing AKT activity. In the mouse xenograft model, the average tumor weight with 30 mg·kg^-1 D1399 treatment exhibited 73.19% inhibition compared with the untreated control, without affecting body weight loss. Above all, for the first time, our study provides a possible mechanism for the antitumor activity of D1399 in vitro and in vivo as a natural product from Tibetan medicine with Meconopsis grandis Prain, which may be a potentially promising antitumor drug candidate.

Transarterial chemoembolization with PD-(L)1 inhibitors plus molecular targeted therapies for hepatocellular carcinoma (CHANCE001)

There is considerable potential for integrating transarterial chemoembolization (TACE), programmed death-(ligand)1 (PD-[L]1) inhibitors, and molecular targeted treatments (MTT) in hepatocellular carcinoma (HCC). It is necessary to investigate the therapeutic efficacy and safety of TACE combined with PD-(L)1 inhibitors and MTT in real-world situations. In this nationwide, retrospective, cohort study, 826 HCC patients receiving either TACE plus PD-(L)1 blockades and MTT (combination group, n = 376) or TACE monotherapy (monotherapy group, n = 450) were included from January 2018 to May 2021. The primary endpoint was progression-free survival (PFS) according to modified RECIST. The secondary outcomes included overall survival (OS), objective response rate (ORR), and safety. We performed propensity score matching approaches to reduce bias between two groups. After matching, 228 pairs were included with a predominantly advanced disease population. Median PFS in combination group was 9.5 months (95% confidence interval [CI], 8.4-11.0) versus 8.0 months (95% CI, 6.6-9.5) (adjusted hazard ratio [HR], 0.70, P = 0.002). OS and ORR were also significantly higher in combination group (median OS, 19.2 [16.1-27.3] vs. 15.7 months [13.0-20.2]; adjusted HR, 0.63, P = 0.001; ORR, 60.1% vs. 32.0%; P < 0.001). Grade 3/4 adverse events were observed at a rate of 15.8% and 7.5% in combination and monotherapy groups, respectively. Our results suggest that TACE plus PD-(L)1 blockades and MTT could significantly improve PFS, OS, and ORR versus TACE monotherapy for Chinese patients with predominantly advanced HCC in real-world practice, with an acceptable safety profile.

Optimizing molecular testing of lung cancer needle biopsy specimens: potential solutions from an interdisciplinary qualitative study

BACKGROUND

Molecular testing can detect actionable genomic alterations and tumor cell surface proteins in patients with non-small cell lung cancer (NSCLC). However, utilization remains suboptimal, representing missed treatment opportunities. This study aimed to identify challenges and potential solutions to obtaining percutaneous lung needle biopsy specimens for successful molecular testing in patients with advanced NSCLC.

METHODS

This interdisciplinary qualitative study included ten radiologists and four pathologists from academic and community settings across the United States who routinely perform and analyze percutaneous lung needle biopsies. Participants underwent semi-structured one-on-one interviews (Phase 1). Interview questionnaires were constructed based on a literature review of key lines of inquiry and conducted by professional market researchers using the theoretical domains framework. Primary barriers to molecular testing were identified using thematic analysis. Subsequently, multidisciplinary focus groups were convened to identify potential solutions (Phase 2).

RESULTS

Four themes emerged as barriers to molecular testing and were matched to the clinical workflow: (1) biopsy request, (2) biopsy procedure, (3) specimen analysis, and (4) communication. The nineteen potential solutions included adding a "checkbox" to indicate molecular testing in the biopsy request, leveraging pre-procedural imaging to guide biopsies, conserving tissue through appropriate allocation strategies and next generation sequencing panels instead of sequential single-gene assays, instituting reflex-molecular testing upon NSCLC diagnosis, tracking and communicating biopsy outcomes at multidisciplinary tumor boards, and improving integration of radiologists and pathologists into oncology care teams.

CONCLUSIONS

Potential solutions exist to increase successful molecular testing of lung needle biopsy specimens in patients with advanced NSCLC.

The evolving landscape of pulmonary arterial hypertension clinical trials

Although it is a rare disease, the number of available therapeutic options for treating pulmonary arterial hypertension has increased since the late 1990s, with multiple drugs developed that are shown to be effective in phase 3 randomised controlled trials. Despite considerable advancements in pulmonary arterial hypertension treatment, prognosis remains poor. Existing therapies target pulmonary endothelial dysfunction with vasodilation and anti-proliferative effects. Novel therapies that target proliferative vascular remodelling and affect important outcomes are urgently needed. There is need for additional innovations in clinical trial design so that all emerging candidate therapies can be rigorously studied. Pulmonary arterial hypertension trial design has shifted from short-term submaximal exercise capacity as a primary endpoint, to larger clinical event-driven trial outcomes. Event-driven pulmonary arterial hypertension trials could face feasibility and efficiency issues in the future because increasing sample sizes and longer follow-up durations are needed, which would be problematic in such a rare disease. Enrichment strategies, innovative and alternative trial designs, and novel trial endpoints are potential solutions that could improve the efficiency of future pulmonary arterial hypertension trials while maintaining robustness and clinically meaningful evidence.

Design and analysis of umbrella trials: Where do we stand?

Background

The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting. Despite the existence of several reviews of master protocols, the statistical considerations of umbrella trials have received more limited attention.

Methods

We conduct a systematic review of the literature on umbrella trials, examining both the statistical methods that are available for their design and analysis, and also their use in practice. We pay particular attention to considerations for umbrella designs applied outside of oncology.

Findings

We identified 38 umbrella trials. To date, most umbrella trials have been conducted in early phase settings (73.7%, 28/38) and in oncology (92.1%, 35/38). The quality of statistical information available about conducted umbrella trials to date is poor; for example, it was impossible to ascertain how sample size was determined in the majority of trials (55.3%, 21/38). The literature on statistical methods for umbrella trials is currently sparse.

Conclusions

Umbrella trials have potentially great utility to expedite drug development, including outside of oncology. However, to enable lessons to be effectively learned from early use of such designs, there is a need for higher-quality reporting of umbrella trials. Furthermore, if the potential of umbrella trials is to be realized, further methodological research is required.

Optimizing a Bayesian hierarchical adaptive platform trial design for stroke patients

BACKGROUND

Platform trials are well-known for their ability to investigate multiple arms on heterogeneous patient populations and their flexibility to add/drop treatment arms due to efficacy/lack of efficacy. Because of their complexity, it is important to develop highly optimized, transparent, and rigorous designs that are cost-efficient, offer high statistical power, maximize patient benefit, and are robust to changes over time.

METHODS

To address these needs, we present a Bayesian platform trial design based on a beta-binomial model for binary outcomes that uses three key strategies: (1) hierarchical modeling of subgroups within treatment arms that allows for borrowing of information across subgroups, (2) utilization of response-adaptive randomization (RAR) schemes that seek a tradeoff between statistical power and patient benefit, and (3) adjustment for potential drift over time. Motivated by a proposed clinical trial that aims to find the appropriate treatment for different subgroup populations of ischemic stroke patients, extensive simulation studies were performed to validate the approach, compare different allocation rules, and study the model operating characteristics.

RESULTS AND CONCLUSIONS

Our proposed approach achieved high statistical power and good patient benefit and was also robust against population drift over time. Our design provided a good balance between the strengths of both the traditional RAR scheme and fixed 1:1 allocation and may be a promising choice for dichotomous outcomes trials investigating multiple subgroups.

Clinical trial design in the era of precision medicine

Recent rapid biotechnological breakthroughs have led to the identification of complex and unique molecular features that drive malignancies. Precision medicine has exploited next-generation sequencing and matched targeted therapy/immunotherapy deployment to successfully transform the outlook for several fatal cancers. Tumor and liquid biopsy genomic profiling and transcriptomic, immunomic, and proteomic interrogation can now all be leveraged to optimize therapy. Multiple new trial designs, including basket and umbrella trials, master platform trials, and N-of-1 patient-centric studies, are beginning to supplant standard phase I, II, and III protocols, allowing for accelerated drug evaluation and approval and molecular-based individualized treatment. Furthermore, real-world data, as well as exploitation of digital apps and structured observational registries, and the utilization of machine learning and/or artificial intelligence, may further accelerate knowledge acquisition. Overall, clinical trials have evolved, shifting from tumor type-centered to gene-directed and histology-agnostic trials, with innovative adaptive designs and personalized combination treatment strategies tailored to individual biomarker profiles. Some, but not all, novel trials now demonstrate that matched therapy correlates with superior outcomes compared to non-matched therapy across tumor types and in specific cancers. To further improve the precision medicine paradigm, the strategy of matching drugs to patients based on molecular features should be implemented earlier in the disease course, and cancers should have comprehensive multi-omic (genomics, transcriptomics, proteomics, immunomic) tumor profiling. To overcome cancer complexity, moving from drug-centric to patient-centric individualized combination therapy is critical. This review focuses on the design, advantages, limitations, and challenges of a spectrum of clinical trial designs in the era of precision oncology.

Preliminary Discovery of Small Molecule Inhibitors of Epidermal Growth Factor Receptor (EGFR) That Bind to the Extracellular Domain

The Epidermal Growth Factor Receptor (EGFR) is a transmembrane glycoprotein belonging to the protein kinase superfamily. It is composed of an extracellular domain, a transmembrane anchoring region and a cytoplasmic region endowed with tyrosine kinase activity. Genetic mutations of EGFR kinase cause higher activity thereby stimulating downstream signaling pathways that, in turn, impact transcription and cell cycle progression. Due to the involvement of mutant EGFR in tumors and inflammatory diseases, in the past decade, several EGFR inhibitory strategies have been extensively studied, either targeting the extracellular domain (through monoclonal antibodies) or the intracellular kinase domain (through ATP-mimic small molecules). Monoclonal antibodies impair the binding to growth factor, the receptor dimerization, and its activation, whereas small molecules block the intracellular catalytic activity. Herein, we describe the development of a novel small molecule, called DSF-102, that interacts with the extracellular domain of EGFR. When tested in vitro in KRAS mutant A549 cells, it impairs EGFR activity by exerting (i) dose-dependent toxicity effects; (ii) a negative regulation of ERK, MAPK p38 and AKT; and (iii) a modulation of the intracellular trafficking and lysosomal degradation of EGFR. Interestingly, DSF-102 exerts its EGFR inhibitory activity without showing interaction with the intracellular kinase domain. Taken together, these findings suggest that DSF-102 is a promising hit compound for the development of a novel class of anti-EGFR compounds, i.e., small molecules able to interact with the extracellular domain of EGFR and useful for overcoming the KRAS-driven resistance to TKI treatment.

Risk and benefit for umbrella trials in oncology: a systematic review and meta-analysis

BACKGROUND

Umbrella clinical trials in precision oncology are designed to tailor therapies to the specific genetic changes within a tumor. Little is known about the risk/benefit ratio for umbrella clinical trials. The aim of our systematic review with meta-analysis was to evaluate the efficacy and safety profiles in cancer umbrella trials testing targeted drugs or a combination of targeted therapy with chemotherapy.

METHODS

Our study was prospectively registered in PROSPERO (CRD42020171494). We searched Embase and PubMed for cancer umbrella trials testing targeted agents or a combination of targeted therapies with chemotherapy. We included solid tumor studies published between 1 January 2006 and 7 October 2019. We measured the risk using drug-related grade 3 or higher adverse events (AEs), and the benefit by objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). When possible, data were meta-analyzed.

RESULTS

Of the 6207 records identified, we included 31 sub-trials or arms of nine umbrella trials (N = 1637). The pooled overall ORR was 17.7% (95% confidence interval [CI] 9.5-25.9). The ORR for targeted therapies in the experimental arms was significantly lower than the ORR for a combination of targeted therapy drugs with chemotherapy: 13.3% vs 39.0%; p = 0.005. The median PFS was 2.4 months (95% CI 1.9-2.9), and the median OS was 7.1 months (95% CI 6.1-8.4). The overall drug-related death rate (drug-related grade 5 AEs rate) was 0.8% (95% CI 0.3-1.4), and the average drug-related grade 3/4 AE rate per person was 0.45 (95% CI 0.40-0.50).

CONCLUSIONS

Our findings suggest that, on average, one in five cancer patients in umbrella trials published between 1 January 2006 and 7 October 2019 responded to a given therapy, while one in 125 died due to drug toxicity. Our findings do not support the expectation of increased patient benefit in cancer umbrella trials. Further studies should investigate whether umbrella trial design and the precision oncology approach improve patient outcomes.

Percutaneous Image-Guided Biopsy for a Comprehensive Hybridization Capture-Based Next-Generation Sequencing in Primary Lung Cancer: Safety, Efficacy, and Predictors of Outcome

Introduction

To evaluate factors associated with successful comprehensive genomic sequencing of image-guided percutaneous needle biopsies in patients with lung cancer using a broad hybrid capture-based next-generation sequencing assay (CHCA).

Methods

We conducted a single-institution retrospective review of image-guided percutaneous transthoracic needle biopsies from January 2018 to December 2019. Samples with confirmed diagnosis of primary lung cancer and for which CHCA had been attempted were identified. Pathologic, clinical data and results of the CHCA were reviewed. Covariates associated with CHCA success were tested for using Fisher's exact test or Wilcoxon ranked sum test. Logistic regression was used to identify factors independently associated with likelihood of CHCA success.

Results

CHCA was requested for 479 samples and was successful for 433 (91%), with a median coverage depth of 659X. Factors independently associated with lower likelihood of CHCA success included small tumor size (OR = 0.26 [95% confidence interval (CI): 0.11-0.62, p = 0.002]), intraoperative inadequacy on cytologic assessment (OR = 0.18 [95% CI: 0.06-0.63, p = 0.005]), small caliber needles (≥20-gauge) (OR = 0.22 [95% CI: 0.10-0.45, p < 0.001]), and presence of lung parenchymal abnormalities (OR = 0.12 [95% CI: 0.05-0.25, p < 0.001]). Pneumothorax requiring chest tube insertion occurred in 6% of the procedures. No grade IV complications or procedure-related deaths were reported.

Conclusions

Percutaneous image-guided transthoracic needle biopsy is safe and has 91% success rate for CHCA in primary lung cancer. Intraoperative inadequacy, small caliber needle, presence of parenchymal abnormalities, and small tumor size (≤1 cm) are independently associated with likelihood of failure.

Treatment-Related Adverse Events of Combination EGFR Tyrosine Kinase Inhibitor and Immune Checkpoint Inhibitor in EGFR-Mutant Advanced Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis

(1) Background: We performed a meta-analysis to examine whether combined epidermal growth factor tyrosine kinase inhibitor (EGFR-TKI) and immune checkpoint inhibitor (ICI) increases treatment-related adverse events (trAEs) in advanced non-small cell lung cancer (NSCLC). (2) Methods: Articles from MEDLINE, EMBASE, and Cochrane databases were searched. Proportions and odds ratios (ORs) of the pooled incidence of overall and organ-specific trAEs in combination EGFR-TKI and ICI were compared to TKI monotherapy. (3) Results: Eight studies fulfilled our selection criteria. Any-grade organ-specific trAEs were more common in combination EGFR-TKI and ICI than TKI monotherapy (skin: OR = 1.19, p = 0.012; gastrointestinal tract: OR = 1.04, p = 0.790; ILD: OR = 1.28, p = 0.001). Grade ≥ 3 trAEs were also more frequent in combination treatment (skin: OR = 1.13, p = 0.082; gastrointestinal tract: OR = 1.13, p = 0.076; ILD: OR = 1.16, p = 0.003). (4) Conclusions: A higher proportion of grade ≥3 skin and gastrointestinal trAEs and ILDs was observed in combination TKI and ICI compared to TKI alone. Caution has to be taken when interpreting the results owing to the small number of studies included in this meta-analysis.

Targeting Mutant Kirsten Rat Sarcoma Viral Oncogene Homolog in Non-Small Cell Lung Cancer: Current Difficulties, Integrative Treatments and Future Perspectives

In the past few decades, several gene mutations, including the anaplastic lymphoma kinase, epidermal growth factor receptor, ROS proto-oncogene 1 and rat sarcoma viral oncogene homolog (RAS), have been discovered in non-small cell lung cancer (NSCLC). Kirsten rat sarcoma viral oncogene homolog (KRAS) is the isoform most frequently altered in RAS-mutated NSCLC cases. Due to the structural and biochemical characteristics of the KRAS protein, effective approaches to treating KRAS-mutant NSCLC still remain elusive. Extensive recent research on KRAS-mutant inhibitors has made a breakthrough in identifying the covalent KRASG12C inhibitor as an effective agent for the treatment of NSCLC. This review mainly concentrated on introducing new covalent KRASG12C inhibitors like sotorasib (AMG 510) and adagrasib (MRTX 849); summarizing inhibitors targeting the KRAS-related upstream and downstream effectors in RAF/MEK/ERK pathway and PI3K/AKT/mTOR pathway; exploring the efficacy of immunotherapy and certain emerging immune-related therapeutics such as adoptive cell therapy and cancer vaccines. These inhibitors are being investigated in clinical trials and have exhibited promising effects. On the other hand, naturally extracted compounds, which have exhibited safe and effective properties in treating KRAS-mutant NSCLC through suppressing the MAPK and PI3K/AKT/mTOR signaling pathways, as well as through decreasing PD-L1 expression in preclinical studies, could be expected to enter into clinical studies. Finally, in order to confront the matter of drug resistance, the ongoing clinical trials in combination treatment strategies were summarized herein.

MTAP deficiency creates an exploitable target for antifolate therapy in 9p21-loss cancers

Methylthioadenosine phosphorylase, an essential enzyme for the adenine salvage pathway, is often deficient (MTAPdef) in tumors with 9p21 loss and hypothetically renders tumors susceptible to synthetic lethality by antifolates targeting de novo purine synthesis. Here we report our single arm phase II trial (NCT02693717) that assesses pemetrexed in MTAPdef urothelial carcinoma (UC) with the primary endpoint of overall response rate (ORR). Three of 7 enrolled MTAPdef patients show response to pemetrexed (ORR 43%). Furthermore, a historic cohort shows 4 of 4 MTAPdef patients respond to pemetrexed as compared to 1 of 10 MTAP-proficient patients. In vitro and in vivo preclinical data using UC cell lines demonstrate increased sensitivity to pemetrexed by inducing DNA damage, and distorting nucleotide pools. In addition, MTAP-knockdown increases sensitivity to pemetrexed. Furthermore, in a lung adenocarcinoma retrospective cohort (N = 72) from the published BATTLE2 clinical trial (NCT01248247), MTAPdef associates with an improved response rate to pemetrexed. Our data demonstrate a synthetic lethal interaction between MTAPdef and de novo purine inhibition, which represents a promising therapeutic strategy for larger prospective trials.

Bax/Bcl-2 Cascade Is Regulated by the EGFR Pathway: Therapeutic Targeting of Non-Small Cell Lung Cancer

Non-small cell lung carcinoma (NSCLC) comprises 80%-85% of lung cancer cases. EGFR is involved in several cancer developments, including NSCLC. The EGFR pathway regulates the Bax/Bcl-2 cascade in NSCLC. Increasing understanding of the molecular mechanisms of fundamental tumor progression has guided the development of numerous antitumor drugs. The development and improvement of rationally planned inhibitors and agents targeting particular cellular and biological pathways in cancer have been signified as a most important paradigm shift in the strategy to treat and manage lung cancer. Newer approaches and novel chemotherapeutic agents are required to accompany present cancer therapies for improving efficiency. Using natural products as a drug with an effective delivery system may benefit therapeutics. Naturally originated compounds such as phytochemicals provide crucial sources for novel agents/drugs and resources for tumor therapy. Applying the small-molecule inhibitors (SMIs)/phytochemicals has led to potent preclinical discoveries in various human tumor preclinical models, including lung cancer. In this review, we summarize recent information on the molecular mechanisms of the Bax/Bcl-2 cascade and EGFR pathway in NSCLC and target them for therapeutic implications. We further described the therapeutic potential of Bax/Bcl-2/EGFR SMIs, mainly those with more potent and selectivity, including gefitinib, EGCG, ABT-737, thymoquinone, quercetin, and venetoclax. In addition, we explained the targeting EGFR pathway and ongoing in vitro and in vivo and clinical investigations in NSCLC. Exploration of such inhibitors facilitates the future treatment and management of NSCLC.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Targeted Therapies for Lung Cancer Patients With Oncogenic Driver Molecular Alterations

Lung cancer has traditionally been classified by histology. However, a greater understanding of disease biology and the identification of oncogenic driver alterations has dramatically altered the therapeutic landscape. Consequently, the new classification paradigm of non-small-cell lung cancer is further characterized by molecularly defined subsets actionable with targeted therapies and the treatment landscape is becoming increasingly complex. This review encompasses the current standards of care for targeted therapies in lung cancer with driver molecular alterations. Targeted therapies for EGFR exon 19 deletion and L858R mutations, and ALK and ROS1 rearrangements are well established. However, there is an expanding list of approved targeted therapies including for BRAF V600E, EGFR exon 20 insertion, and KRAS G12C mutations, MET exon 14 alterations, and NTRK and RET rearrangements. In addition, there are numerous other oncogenic drivers, such as HER2 exon 20 insertion mutations, for which there are emerging efficacy data for targeted therapies. The importance of diagnostic molecular testing, intracranial efficacy of novel therapies, the optimal sequencing of therapies, role for targeted therapies in early-stage disease, and future directions for precision oncology approaches to understand tumor evolution and therapeutic resistance are also discussed.

Adaptive Platform Trials to Transform Amyotrophic Lateral Sclerosis Therapy Development

Current therapeutic development in amyotrophic lateral sclerosis (ALS) relies on individual randomized clinical trials to test a specific investigational product in a single patient population. This approach has intrinsic limitations, including cost, time, and lack of flexibility. Adaptive platform trials represent a novel approach to investigate several interventions for a single disease in a continuous manner. Already in use in oncology, this approach is now being employed more often in neurology. Here, we describe a newly launched platform trial for ALS. The Healey ALS Platform Trial is testing multiple investigational products concurrently in people with ALS, with the goal of rapidly identifying novel treatments, biomarkers, and trial endpoints. ANN NEUROL 2022;91:165-175.

The Renaissance of KRAS Targeting in Advanced Non-Small-Cell Lung Cancer: New Opportunities Following Old Failures

Non-small cell lung cancer (NSCLC) represents the perfect paradigm of ‘precision medicine’ due to its complex intratumoral heterogeneity. It is truly characterized by a range of molecular alterations that can deeply influence the natural history of this disease. Several molecular alterations have been found over time, paving the road to biomarker-driven therapy and radically changing the prognosis of ‘oncogene addicted’ NSCLC patients. Kirsten rat sarcoma (KRAS) mutations are present in up to 30% of NSCLC (especially in adenocarcinoma histotype) and have been identified decades ago. Since its discovery, its molecular characteristics and its marked affinity to a specific substrate have led to define KRAS as an undruggable alteration. Despite that, many attempts have been made to develop drugs capable of targeting KRAS signaling but, until a few years ago, these efforts have been unsuccessful. Comprehensive genomic profiling and wide-spectrum analysis of genetic alterations have only recently allowed to identify different types of KRAS mutations. This tricky step has finally opened new frontiers in the treatment approach of KRAS-mutant patients and might hopefully increase their prognosis and quality of life. In this review, we aim to highlight the most interesting aspects of (epi)genetic KRAS features, hoping to light the way to the state of art of targeting KRAS in NSCLC.

Untangling the KRAS mutated lung cancer subsets and its therapeutic implications

The Kirsten rat sarcoma virus transforming protein (KRAS) mutations (predominate in codons 12, 13, and 61) and genomically drive nearly one-third of lung carcinomas. These mutations have complex functions in tumorigenesis, and influence the tumor response to chemotherapy and tyrosine kinase inhibitors resulting in a poorer patient prognosis. Recent attempts using targeted therapies against KRAS alone have met with little success. The existence of specific subsets of lung cancer based on KRAS mutations and coexisting mutations are suggested. Their interactions need further elaboration before newer promising targeted therapies for KRAS mutant lung cancers can be used as earlier lines of therapy. We summarize the existing knowledge of KRAS mutations and their coexisting mutations that is relevant to lung cancer treatment, in this review. We elaborate on the prognostic impact of clinical and pathologic characteristics of lung cancer patients associated with KRAS mutations. We briefly review the currently available techniques for KRAS mutation detection on biopsy and cytology samples. Finally, we discuss the new therapeutic strategies for targeting KRAS-mutant non-small cell lung cancer (NSCLC). These may herald a new era in the treatment of KRAS^G12Cmutated NSCLC as well as be helpful to develop demographic subsets to predict targeted therapies and prognosis of lung cancer patients.

Lung Cancer Models Reveal Severe Acute Respiratory Syndrome Coronavirus 2-Induced Epithelial-to-Mesenchymal Transition Contributes to Coronavirus Disease 2019 Pathophysiology

INTRODUCTION

Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which enters host cells through the cell surface proteins ACE2 and TMPRSS2.

METHODS

Using a variety of normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2.

RESULTS

We find that ACE2 expression is restricted to a select population of epithelial cells. Notably, infection with SARS-CoV-2 in cancer cell lines, bronchial organoids, and patient nasal epithelium induces metabolic and transcriptional changes consistent with epithelial-to-mesenchymal transition (EMT), including up-regulation of ZEB1 and AXL, resulting in an increased EMT score. In addition, a transcriptional loss of genes associated with tight junction function occurs with SARS-CoV-2 infection. The SARS-CoV-2 receptor, ACE2, is repressed by EMT through the transforming growth factor-β, ZEB1 overexpression, and onset of EGFR tyrosine kinase inhibitor resistance. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state, associated with a loss of tight junction components with acute respiratory distress syndrome-protective effects. AXL inhibition and ZEB1 reduction, as with bemcentinib, offer a potential strategy to reverse this effect.

CONCLUSIONS

These observations highlight the use of aerodigestive and, especially, lung cancer model systems in exploring the pathogenesis of SARS-CoV-2 and other respiratory viruses and offer important insights into the potential mechanisms underlying the morbidity and mortality of coronavirus disease 2019 in healthy patients and patients with cancer alike.

Metabolic Phenotypes, Dependencies, and Adaptation in Lung Cancer

Lung cancer is a heterogeneous disease that is subdivided into histopathological subtypes with distinct behaviors. Each subtype is characterized by distinct features and molecular alterations that influence tumor metabolism. Alterations in tumor metabolism can be exploited by imaging modalities that use metabolite tracers for the detection and characterization of tumors. Microenvironmental factors, including nutrient and oxygen availability and the presence of stromal cells, are a critical influence on tumor metabolism. Recent technological advances facilitate the direct evaluation of metabolic alterations in patient tumors in this complex microenvironment. In addition, molecular alterations directly influence tumor cell metabolism and metabolic dependencies that influence response to therapy. Current therapeutic approaches to target tumor metabolism are currently being developed and translated into the clinic for patient therapy.

Personalization of medical treatments in oncology: time for rethinking the disease concept to improve individual outcomes

The agenda of pharmacology discovery in the field of personalized oncology was dictated by the search of molecular targets assumed to deterministically drive tumor development. In this perspective, genes play a fundamental "causal" role while cells simply act as causal proxies, i.e., an intermediate between the molecular input and the organismal output. However, the ceaseless genomic change occurring across time within the same primary and metastatic tumor has broken the hope of a personalized treatment based only upon genomic fingerprint. Indeed, current models are unable in capturing the unfathomable complexity behind the outbreak of a disease, as they discard the contribution of non-genetic factors, environment constraints, and the interplay among different tiers of organization. Herein, we posit that a comprehensive personalized model should view at the disease as a "historical" process, in which different spatially and timely distributed factors interact with each other across multiple levels of organization, which collectively interact with a dynamic gene-expression pattern. Given that a disease is a dynamic, non-linear process - and not a static-stable condition - treatments should be tailored according to the "timing-frame" of each condition. This approach can help in detecting those critical transitions through which the system can access different attractors leading ultimately to diverse outcomes - from a pre-disease state to an overt illness or, alternatively, to recovery. Identification of such tipping points can substantiate the predictive and the preventive ambition of the Predictive, Preventive and Personalized Medicine (PPPM/3PM). However, an unusual effort is required to conjugate multi-omics approaches, data collection, and network analysis reconstruction (eventually involving innovative Artificial Intelligent tools) to recognize the critical phases and the relevant targets, which could help in patient stratification and therapy personalization.

How clinically useful is comprehensive genomic profiling for patients with non-small cell lung cancer? A systematic review

Given the lack of a gold standard, the clinical usefulness of Comprehensive Genomic Profiling (CGP) has not been established. This systematic review aimed to evaluate evidence about the clinical benefit of CGP for patients with Non-small cell lung carcinoma (NSCLC). All controlled studies that evaluated the ability of CGP to detect actionable targets (ATs) reported increases in the number of samples with ATs. The frequency of ATs detected in uncontrolled case series ranged from 0.7 % for RET mutations to 45 % for EGFR mutations. The studies that evaluated therapies targeted to EGFR, ALK, ROS-1, MET, and RET mutations documented significant improvement in clinical outcomes. This review suggests that CGP tests may be clinically helpful for treating patients with NSCLC. Although current evidence is associated with a high risk of bias, the significant impact of NSCLC on individuals and society may justify the routine use of CGP testing for this disease.

Blockade of mutant RAS oncogenic signaling with a special emphasis on KRAS

RAS proteins (HRAS, KRAS, NRAS) participate in many physiological signal transduction processes related to cell growth, division, and survival. The RAS proteins are small (188/189 amino acid residues) and they function as GTPases. These proteins toggle between inactive and functional forms; the conversion of inactive RAS-GDP to active RAS-GTP as mediated by guanine nucleotide exchange factors (GEFs) turns the switch on and the intrinsic RAS-GTPase activity stimulated by the GTPase activating proteins (GAPs) turns the switch off. RAS is upstream to the RAS-RAF-MEK-ERK and the PI3-kinase-AKT signaling modules. Importantly, the overall incidence of RAS mutations in all cancers is about 19% and RAS mutants have been a pharmacological target for more than three decades. About 84% of all RAS mutations involve KRAS. Except for the GTP/GDP binding site, the RAS proteins lack other deep surface pockets thereby hindering efforts to identify high-affinity antagonists; thus, they have been considered to be undruggable. KRAS mutations frequently occur in lung, colorectal, and pancreatic cancers, the three most deadly cancers in the United States. Studies within the last decade demonstrated that the covalent modification of KRAS C12, which accounts for about 10% of all RAS mutations, led to the discovery of an adjacent pocket (called the switch II pocket) that accommodated a portion of the drug. This led to the development of sotorasib as a second-line treatment of KRAS^G12C-mutant non-small cell lung cancer. Considerable effort also has been expended to develop MAP kinase and PI3-kinase pathway inhibitors as indirect RAS antagonists.

Current therapy of KRAS-mutant lung cancer

KRAS mutations are the most frequent gain-of-function alterations in patients with lung adenocarcinoma (LADC) in the Western world. Although they have been identified decades ago, prior efforts to target KRAS signaling with single-agent therapeutic approaches such as farnesyl transferase inhibitors, prenylation inhibition, impairment of KRAS downstream signaling, and synthetic lethality screens have been unsuccessful. Moreover, the role of KRAS oncogene in LADC is still not fully understood, and its prognostic and predictive impact with regards to the standard of care therapy remains controversial. Of note, KRAS-related studies that included general non-small cell lung cancer (NSCLC) population instead of LADC patients should be very carefully evaluated. Recently, however, comprehensive genomic profiling and wide-spectrum analysis of other co-occurring genetic alterations have identified unique therapeutic vulnerabilities. Novel targeted agents such as the covalent KRAS G12C inhibitors or the recently proposed combinatory approaches are some examples which may allow a tailored treatment for LADC patients harboring KRAS mutations. This review summarizes the current knowledge about the therapeutic approaches of KRAS-mutated LADC and provides an update on the most recent advances in KRAS-targeted anti-cancer strategies, with a focus on potential clinical implications.

Prospective high-throughput genome profiling of advanced cancers: results of the PERMED-01 clinical trial

BACKGROUND

The benefit of precision medicine based on relatively limited gene sets and often-archived samples remains unproven. PERMED-01 (NCT02342158) was a prospective monocentric clinical trial assessing, in adults with advanced solid cancer, the feasibility and impact of extensive molecular profiling applied to newly biopsied tumor sample and based on targeted NGS (t-NGS) of the largest gene panel to date and whole-genome array-comparative genomic hybridization (aCGH) with assessment of single-gene alterations and clinically relevant genomic scores.

METHODS

Eligible patients with refractory cancer had one tumor lesion accessible to biopsy. Extracted tumor DNA was profiled by t-NGS and aCGH. We assessed alterations of 802 "candidate cancer" genes and global genomic scores, such as homologous recombination deficiency (HRD) score and tumor mutational burden. The primary endpoint was the number of patients with actionable genetic alterations (AGAs). Secondary endpoints herein reported included a description of patients with AGA who received a "matched therapy" and their clinical outcome, and a comparison of AGA identification with t-NGS and aCGH versus whole-exome sequencing (WES).

RESULTS

Between November 2014 and September 2019, we enrolled 550 patients heavily pretreated. An exploitable complete molecular profile was obtained in 441/550 patients (80%). At least one AGA, defined in real time by our molecular tumor board, was found in 393/550 patients (71%, two-sided 90%CI 68-75%). Only 94/550 patients (17%, 95%CI 14-21) received an "AGA-matched therapy" on progression. The most frequent AGAs leading to "matched therapy" included PIK3CA mutations, KRAS mutations/amplifications, PTEN deletions/mutations, ERBB2 amplifications/mutations, and BRCA1/2 mutations. Such "matched therapy" improved by at least 1.3-fold the progression-free survival on matched therapy (PFS2) compared to PFS on prior therapy (PFS1) in 36% of cases, representing 6% of the enrolled patients. Within patients with AGA treated on progression, the use of "matched therapy" was the sole variable associated with an improved PFS2/PFS1 ratio. Objective responses were observed in 19% of patients treated with "matched therapy," and 6-month overall survival (OS) was 62% (95%CI 52-73). In a subset of 112 metastatic breast cancers, WES did not provide benefit in term of AGA identification when compared with t-NGS/aCGH.

CONCLUSIONS

Extensive molecular profiling of a newly biopsied tumor sample identified AGA in most of cases, leading to delivery of a "matched therapy" in 17% of screened patients, of which 36% derived clinical benefit. WES did not seem to improve these results.

TRIAL REGISTRATION

ID-RCB identifier: 2014-A00966-41; ClinicalTrials.gov identifier: NCT02342158 .

Diffusion kurtosis imaging: correlation analysis of quantitative model parameters with molecular features in advanced lung adenocarcinoma

Background:

Due to development of magnetic resonance-based functional imaging, it is easier to detect micro-structural alterations of tumor tissues. The aim of this study was to conduct a preliminary evaluation of the correlation of non-Gaussian diffusion kurtosis imaging (DKI) parameters with expression of molecular markers (epidermal growth factor receptor [EGFR]; anaplastic lymphoma kinase [ALK]; Ki-67 protein) in patients with advanced lung adenocarcinoma, using routine diffusion-weighted imaging as the reference standard.

Methods:

Data from patients with primary lung adenocarcinoma diagnosed at Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) from 2016 to 2019 were collected for retrospective analysis. The pathologic and magnetic resonance imaging data of 96 patients who met the inclusion criteria were included in this study. Specifically, the K_app and D_app parameters measured from the DKI model; apparent diffusion coefficient (ADC) value from the diffusion-weighted imaging model; and the EGFR, ALK, and Ki-67 biomarkers detected by immunohistochemistry and/or molecular biology techniques after biopsy or surgery were evaluated. The relations between quantitative parameters (ADC, K_app, D_app) and pathologic outcomes (EGFR, ALK, and Ki-67 expression) were analyzed by Spearman correlation test.

Results:

Of the 96 lung adenocarcinoma lesions (from 96 patients), the number of EGFR- and ALK-positive and high Ki-67 expressing lesions were 53, 12, and 83, respectively. The K_app values were significantly higher among patients with EGFR-positive mutations (0.81 ± 0.12 vs. 0.66 ± 0.10, t = 6.41, P < 0.001), ALK rearrangement-negative (0.76 ± 0.12 vs. 0.60 ± 0.15, t = 4.09, P < 0.001), and high Ki-67 proliferative index (PI) (0.76 ± 0.12 vs. 0.58 ± 0.13, t = 4.88, P < 0.001). The D_app values were significantly lower among patients with high Ki-67 PI (3.19 ± 0.69 μm²/ms vs. 4.20 ± 0.83 μm²/ms, t = 4.80, P < 0.001) and EGFR-positive mutations (3.11 ± 0.73 μm²/ms vs. 3.59 ± 0.77 μm²/ms, t = 3.12, P = 0.002). The differences in mean D_app (3.73 ± 1.26 μm²/ms vs. 3.26 ± 0.68 μm²/ms, t = 1.96, P = 0.053) or ADC values ([1.34 ± 0.81] × 10⁻³ mm²/s vs. [1.33 ± 0.41] × 10⁻³ mm²/s, t = 0.07, P = 0.941) between the groups with or without ALK rearrangements were not statistically significant. The ADC values were significantly lower among patients with EGFR-positive mutation ([1.19 ± 0.37] × 10⁻³ mm²/s vs. [1.50 ± 0.53] × 10⁻³ mm²/s, t = 3.38, P = 0.001) and high Ki-67 PI ([1.28 ± 0.39] × 10⁻³ mm²/s vs. [1.67 ± 0.77] × 10⁻³ mm²/s, t = 2.88, P = 0.005). K_app was strongly positively correlated with EGFR mutations (r = 0.844, P = 0.008), strongly positively correlated with Ki-67 PI (r = 0.882, P = 0.001), and strongly negatively correlated with ALK rearrangements (r = −0.772, P = 0.001). D_app was moderately correlated with EGFR mutations (r = −0.650, P = 0.024) or Ki-67 PI (r = −0.734, P = 0.012). ADC was moderately correlated with Ki-67 PI (r = −0.679, P = 0.033).

Conclusions:

The K_app value of DKI parameters was strongly correlated with different expression of EGFR, ALK, and Ki-67 in advanced lung adenocarcinoma. The results potentially indicate a surrogate measure of the status of different molecular markers assessed by non-invasive imaging tools.

KRAS-Mutant Non-Small Cell Lung Cancer: An Emerging Promisingly Treatable Subgroup

Lung cancer, the leading cause of cancer-related deaths worldwide, can be classified into small cell lung cancer and non-small cell lung cancer (NSCLC). NSCLC is the most common histological type, accounting for 85% of all lung cancers. Kirsten rat sarcoma viral oncogene (KRAS) mutations, common in NSCLC, are associated with poor prognosis, likely due to poor responses to most systemic therapies and lack of targeted drugs. The latest published clinical trial data on new small-molecule KRAS G12C inhibitors, AMG510 and MRTX849, indicate that these molecules may potentially help treat KRAS-mutant NSCLC. Simultaneously, within the immuno-therapeutic process, immune efficacy has been observed in those patients who have KRAS mutations. In this article, the pathogenesis, treatment status, progress of immunotherapy, and targeted therapy of KRAS-mutant NSCLC are reviewed.

Genetic Analysis and Targeted Therapy Using Buparlisib and MK2206 in a Patient with Triple Metachronous Cancers of the Kidney, Prostate, and Squamous Cell Carcinoma of the Lung: A Case Report

Multiple primary cancers (MPC) occurring in the same individual is considered rare but being increasingly recognized owing to the longer cancer survival nowadays. Despite of accumulating experience in diagnosis, effective treatment remains to be problematic in many scenarios. Genetic testing-based targeted therapy could be an invaluable option for both diagnosis and treatment of such patients. Here we present a 74-year-old male with triple primary cancers including kidney, prostate, and lung with metastatic tumor on the costal bones. The patient visited the hospital for persistent cough and hemoptysis, and a diagnosis of squamous cell carcinoma of the left lung was made by bioptic fiberoptic bronchoscopy. A previous history included renal cancer controlled by Sorafenib and prostate cancer controlled by Goserelin. Radiotherapy and platinum-based chemotherapy failed to help the patient and the tumor size increased over a period of 6 months. In order to seek better therapeutical options, we performed targeted sequencing using the cancerous tissues from his lung, kidney, and prostate cancers. Briefly, the results identified VHL, EGFR, PIK3CA, TP53, and AKT1 mutations in lung cancer, AKT1, FGFR2, and TP53 mutations in renal cancer, and FGFR2 mutations in prostate cancer. A combined medication targeting PIK3CA and AKT1 signaling was recommended and the patient was given BKM120 (PIK3CA, Phase III clinical trial) and MK2206 (AKT, phase III clinical trial). Revisit chest CTs after 4 months and 9 months showed a significant shrinkage of tumor size by 40% and 80%, respectively. Our experience demonstrated a good example that genetic analysis could be valuable to diagnose and precisely treat multiple primary cancers.

AXL Inhibition Induces DNA Damage and Replication Stress in Non-Small Cell Lung Cancer Cells and Promotes Sensitivity to ATR Inhibitors

AXL, a TAM (TYRO3, AXL, and MERTK) family receptor tyrosine kinase, is increasingly being recognized as a key determinant of resistance to targeted therapies, as well as chemotherapy and radiation in non-small cell lung cancer (NSCLC) and other cancers. We further show here that high levels of AXL and epithelial-to-mesenchymal transition were frequently expressed in subsets of both treatment-naïve and treatment-relapsed NSCLC. Previously, we and others have demonstrated a role for AXL in mediating DNA damage response (DDR), as well as resistance to inhibition of WEE1, a replication stress response kinase. Here, we show that BGB324 (bemcentinib), a selective small-molecule AXL inhibitor, caused DNA damage and induced replication stress, indicated by ATR/CHK1 phosphorylation, more significantly in TP53-deficient NSCLC cell lines. Similar effects were also observed in large-cell neuroendocrine carcinoma (LCNEC) cell lines. High AXL protein levels were also associated with resistance to ATR inhibition. Combined inhibition of AXL and ATR significantly decreased cell proliferation of NSCLC and LCNEC cell lines. Mechanistically, combined inhibition of AXL and ATR significantly increased RPA32 hyperphosphorylation and DNA double-strand breaks and induced markers of mitotic catastrophe. Notably, NSCLC cell lines with low levels of SLFN11, a known predictive biomarker for platinum and PARP inhibitor sensitivity, were more sensitive to AXL/ATR cotargeting. These findings demonstrate a novel and unexpected role for AXL in replication stress tolerance, with potential therapeutic implications. IMPLICATIONS: These findings demonstrate that the combination of AXL and ATR inhibitors could be a promising therapeutic combination for NSCLC, LCNEC, and other cancers.

Lung cancer models reveal SARS-CoV-2-induced EMT contributes to COVID-19 pathophysiology

COVID-19 is an infectious disease caused by SARS-CoV-2, which enters host cells via the cell surface proteins ACE2 and TMPRSS2. Using a variety of normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2. We find that ACE2 expression is restricted to a select population of highly epithelial cells. Notably, infection with SARS-CoV-2 in cancer cell lines, bronchial organoids, and patient nasal epithelium, induces metabolic and transcriptional changes consistent with epithelial to mesenchymal transition (EMT), including upregulation of ZEB1 and AXL, resulting in an increased EMT score. Additionally, a transcriptional loss of genes associated with tight junction function occurs with SARS-CoV-2 infection. The SARS-CoV-2 receptor, ACE2, is repressed by EMT via TGFbeta, ZEB1 overexpression and onset of EGFR TKI inhibitor resistance. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state, associated with a loss of tight junction components with acute respiratory distress syndrome-protective effects. AXL-inhibition and ZEB1-reduction, as with bemcentinib, offers a potential strategy to reverse this effect. These observations highlight the utility of aerodigestive and, especially, lung cancer model systems in exploring the pathogenesis of SARS-CoV-2 and other respiratory viruses, and offer important insights into the potential mechanisms underlying the morbidity and mortality of COVID-19 in healthy patients and cancer patients alike.