Brain Metastases from Lung Cancer: Is MET an Actionable Target?

Tyrosine kinase inhibitors in cancers: Treatment optimization - Part I

A multitude of TKI has been developed and approved targeting various oncogenetic alterations. While these have provided improvements in efficacy compared with conventional chemotherapies, resistance to targeted therapies occurs. Mutations in the kinase domain result in the inability of TKI to inactivate the protein kinase. Also, gene amplification, increased protein expression and downstream activation or bypassing of signalling pathways are commonly reported mechanisms of resistance. Improved understanding of mechanisms involved in TKI resistance has resulted in the development of new generations of targeted agents. In a race against time, the search for new, more potent and efficient drugs, and/or combinations of drugs, remains necessary as new resistance mechanisms to the latest generation of TKI emerge. This review examines the various generations of TKI approved to date and their common mechanisms of resistance, focusing on TKI targeting BCR-ABL, epidermal growth factor receptor, anaplastic lymphoma kinase and BRAF/MEK tyrosine kinases.

The clinical, molecular, and therapeutic implications of time from primary diagnosis to brain metastasis in lung and breast cancer patients

PURPOSE

Lung cancer (LC) and breast cancer (BC) are the most common causes of brain metastases (BMs). Time from primary diagnosis to BM (TPDBM) refers to the time interval between initial LC or BC diagnosis and development of BM. This research aims to identify clinical, molecular, and therapeutic risk factors associated with shorter TPDBM.

METHODS

We retrospectively reviewed all diagnosed LC and BC patients with BM at Harbin Medical University Cancer Hospital from 2016 to 2020. A total of 570 patients with LC brain metastasis (LCBM) and 173 patients with breast cancer brain metastasis (BCBM) patients who met the inclusion criteria were enrolled for further analysis. BM free survival time curves were generated using Kaplan-Meier analyses. Univariate and multivariate Cox regression analyses were applied to identify risk factors associated with earlier development of BM in LC and BC, respectively.

RESULTS

The median TPDBM was 5.3 months in LC and 44.4 months in BC. In multivariate analysis, clinical stage IV and M1 stage were independent risk factors for early development of LCBM. LC patients who received chemotherapy, targeted therapy, pulmonary radiotherapy, and pulmonary surgery had longer TPDBM. For BC patients, age ≥ 50 years, Ki67 ≥ 0.3, HER2 positive or triple-negative breast cancer subtype, advanced N stage, and no mastectomy were correlated with shorter TPDBM.

CONCLUSIONS

This single-institutional study helps identify patients who have a high risk of developing BM early. For these patients, early detection and intervention could have clinical benefits.

Construction, validation, and visualization of a web-based nomogram to predict overall survival in small-cell lung cancer patients with brain metastasis

INTRODUCTION

Brain metastasis (BM) is an aggressive complication with an extremely poor prognosis in patients with small-cell lung cancer (SCLC). A well-constructed prognostic model could help in providing timely survival consultation or optimizing treatments.

METHODS

We analyzed clinical data from SCLC patients between 2000 and 2018 based on the Surveillance, Epidemiology, and End Results (SEER) database. We identified significant prognostic factors and integrated them using a multivariable Cox regression approach. Internal validation of the model was performed through a bootstrap resampling procedure. Model performance was evaluated based on the area under the curve (AUC) and calibration curve.

RESULTS

A total of 2,454 SCLC patients' clinical data was collected from the database. It was determined that seven clinical parameters were associated with prognosis in SCLC patients with BM. A satisfactory level of discrimination was achieved by the predictive model, with 6-, 12-, and 18-month AUC values of 0.726, 0.707, and 0.737 in the training cohort; and 0.759, 0.742, and 0.744 in the validation cohort. As measured by survival rate probabilities, the calibration curve agreed well with actual observations. Furthermore, prognostic scores were found to significantly alter the survival curves of different risk groups. We then deployed the prognostic model onto a website server so that users can access it easily.

CONCLUSIONS

In this study, a nomogram and a web-based predictor were developed to predict overall survival in SCLC patients with BM. It may assist physicians in making informed clinical decisions and determining the best treatment plan for each patient.

Genomic Alterations and the Incidence of Brain Metastases in Advanced and Metastatic NSCLC: A Systematic Review and Meta-Analysis

INTRODUCTION

Brain metastases (BMs) in patients with advanced and metastatic NSCLC are linked to poor prognosis. Identifying genomic alterations associated with BM development could influence screening and determine targeted treatment. We aimed to establish prevalence and incidence in these groups, stratified by genomic alterations.

METHODS

A systematic review and meta-analysis compliant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses were conducted (PROSPERO identification CRD42022315915). Articles published in MEDLINE, EMBASE, and Cochrane Library between January 2000 and May 2022 were included. Prevalence at diagnosis and incidence of new BM per year were obtained, including patients with EGFR, ALK, KRAS, and other alterations. Pooled incidence rates were calculated using random effects models.

RESULTS

A total of 64 unique articles were included (24,784 patients with NSCLC with prevalence data from 45 studies and 9058 patients with NSCLC having incidence data from 40 studies). Pooled BM prevalence at diagnosis was 28.6% (45 studies, 95% confidence interval [CI]: 26.1-31.0), and highest in patients that are ALK-positive (34.9%) or with RET-translocations (32.2%). With a median follow-up of 24 months, the per-year incidence of new BM was 0.13 in the wild-type group (14 studies, 95% CI: 0.11-0.16). Incidence was 0.16 in the EGFR group (16 studies, 95% CI: 0.11-0.21), 0.17 in the ALK group (five studies, 95% CI: 0.10-0.27), 0.10 in the KRAS group (four studies, 95% CI: 0.06-0.17), 0.13 in the ROS1 group (three studies, 95% CI: 0.06-0.28), and 0.12 in the RET group (two studies, 95% CI: 0.08-0.17).

CONCLUSIONS

Comprehensive meta-analysis indicates a higher prevalence and incidence of BM in patients with certain targetable genomic alterations. This supports brain imaging at staging and follow-up, and the need for targeted therapies with brain penetrance.

Advances in the Molecular Landscape of Lung Cancer Brain Metastasis

Lung cancer is one of the most frequent tumors that metastasize to the brain. Brain metastasis (BM) is common in advanced cases, being the major cause of patient morbidity and mortality. BMs are thought to arise via the seeding of circulating tumor cells into the brain microvasculature. In brain tissue, the interaction with immune cells promotes a microenvironment favorable to the growth of cancer cells. Despite multimodal treatments and advances in systemic therapies, lung cancer patients still have poor prognoses. Therefore, there is an urgent need to identify the molecular drivers of BM and clinically applicable biomarkers in order to improve disease outcomes and patient survival. The goal of this review is to summarize the current state of knowledge on the mechanisms of the metastatic spread of lung cancer to the brain and how the metastatic spread is influenced by the brain microenvironment, and to elucidate the molecular determinants of brain metastasis regarding the role of genomic and transcriptomic changes, including coding and non-coding RNAs. We also present an overview of the current therapeutics and novel treatment strategies for patients diagnosed with BM from NSCLC.

Brain penetration and efficacy of tepotinib in orthotopic patient-derived xenograft models of MET-driven non-small cell lung cancer brain metastases

Central nervous system-penetrant therapies with intracranial efficacy against non-small cell lung cancer (NSCLC) brain metastases are urgently needed. We report preclinical studies investigating brain penetration and intracranial activity of the MET inhibitor tepotinib. After intravenous infusion of tepotinib in Wistar rats (n = 3), mean (±standard deviation) total tepotinib concentration was 2.87-fold higher in brain (505 ± 22 ng/g) than plasma (177 ± 20 ng/mL). In equilibrium dialysis experiments performed in triplicate, mean tepotinib unbound fraction was 0.35% at 0.3 and 3.0 µM tepotinib in rat brain tissue, and 4.0% at 0.3 and 1.0 µM tepotinib in rat plasma. The calculated unbound brain-to-plasma ratio was 0.25, indicating brain penetration sufficient for intracranial target inhibition. Of 20 screened subcutaneous patient-derived xenograft (PDX) models from lung cancer brain metastases (n = 1), two NSCLC brain metastases models (LU5349 and LU5406) were sensitive to the suboptimal dose of tepotinib of 30 mg/kg/qd (tumor volume change [%TV]: -12% and -88%, respectively). Molecular profiling (nCounter®; NanoString) revealed high-level MET amplification in both tumors (mean MET gene copy number: 11.2 and 24.2, respectively). Tepotinib sensitivity was confirmed for both subcutaneous models at a clinically relevant dose (125 mg/kg/qd; n = 5). LU5349 and LU5406 were orthotopically implanted into brains of mice and monitored by magnetic resonance imaging (MRI). Tepotinib 125 mg/kg/qd induced pronounced tumor regression, including complete or near-complete regressions, compared with vehicle in both orthotopic models (n = 10; median %TV: LU5349, -84%; LU5406, -63%). Intracranial antitumor activity of tepotinib did not appear to correlate with blood-brain barrier leakiness assessed in T1-weighted gadolinium contrast-enhanced MRI.

Assessment of Effective Dose Received in Various Computed Tomography Protocols and Factors Affecting It

PURPOSE OF STUDY

The purpose of the study was to evaluate the effect of patient characteristics and equipment-related factors on the computed tomography (CT) dose received by patients from positron emission tomography-CT (PET-CT) using system-generated dose-length product (DLP) values and also to check the effective dose (ED) received from various CT protocols at our institute.

MATERIALS AND METHODS

This retrospective study included 78 adult patients who underwent F-18 fluorodeoxyglucose whole-body PET-CT and were divided into three groups based on the area of primary cancerous lesion. In Group A, we had 44 patients who underwent PET-CT (head-and-neck protocol), in Group B, we had 24 patients who underwent PET-CT (whole body with brain protocol), and in Group C, we had 10 patients who underwent PET-CT (pelvis protocol). All of the patients under the study are of South Asian ethnicity. A majority of patients 53.85% were males and remaining 46.15% were females. The product of conversion factor (k-coefficient), as described in "American Association of Physicists in Medicine Report No. 96" and DLP value generated by the scanner, was used to calculate the ED. Moreover, we also performed regression analysis to check relation between body weight, height, scan range, tube current, Volume computed tomography dose index (CTDIvol), DLP, and ED.

RESULTS

The regression analysis shows that scan range, patient height, weight, tube current, and DLP were significantly correlated with ED (P < 0.05 for all). Moreover, the DLP and conversion factor method estimated the ED from various groups. Patients under Group A (head-and-neck protocol), Group B (whole body with brain protocol), Group C (pelvis protocol) received an average ED of 22.45 mSv, 22.40 mSv, and 21.24 mSv, respectively.

CONCLUSION

ED from CT component of PET-CT can be assessed as the product of scanner-generated DLP and conversion factor for selected range. Moreover, body weight, scan range, and tube current had an independent significant effect on ED received from CT.