Systemic Treatment of Brain Metastases

Association of mutation profiles with metastasis in patients with non-small cell lung cancer

Objective

This study focused on the analysis of the correlation between common gene mutation types and metastatic sites in NSCLC patients.

Methods

We retrospectively studied 1586 NSCLC patients and used fluorescence Polymerase chain reaction (PCR) to detect EGFR, ALK, ROS1, RET, MET, BRAF, HER2, KRAS, NRAS, and PIK3CA gene mutations, and also investigated sex, smoking status, age at diagnosis, histological type and TNM stage. In addition, we analyzed the site of metastasis in patients with stage IV NSCLC.

Results

The EGFR-mutation group more frequently metastasized to lung (18.9%, P = 0.004), brain (18.9%, P = 0.001) and bone (27.1%, P = 0.004) than wild-type patients. ALK-mutation group (71.0%, P < 0.001), BRAF-mutation group (82.4%, P = 0.005) and NRAS-mutation group (100%, P = 0.025) were more likely to metastasize than the wild-type group. In the ALK mutation, lung metastasis (24.2%, P = 0.013), brain (24.2%, P = 0.007), bone metastasis (32.3%, P = 0.024), liver metastasis (19.4%, P = 0.001), and pleural metastasis (29.0%, P = 0.021) were common. In the KRAS-mutation group, lung metastasis (21.7%, P = 0.012) and brain metastasis (23.3%, P = 0.001) were more common. Less metastasis occurred in the HER2-mutation group (28.3%, P = 0.014). There was no difference in the RET, MET and PIK3CA mutations.

Conclusion

Patients with ALK mutant, BRAF mutant or NRAS mutant were more prone to metastasis, while the HER 2 mutation group was less metastatic. Patients with EGFR mutant NSCLC are more likely to develop bone, lung, or brain metastasis.

Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis

Deep learning-assisted digital pathology has demonstrated the potential to profoundly impact clinical practice, even surpassing human pathologists in performance. However, as deep neural network (DNN) architectures grow in size and complexity, their explainability decreases, posing challenges in interpreting pathology features for broader clinical insights into physiological diseases. To better assess the interpretability of digital microscopic images and guide future microscopic system design, we developed a novel method to study the predictive feature length-scale that underpins a DNN's predictive power. We applied this method to analyze a DNN's capability in predicting brain metastasis from early-stage non-small-cell lung cancer biopsy slides. This study quantifies DNN's attention for brain metastasis prediction, targeting features at both the cellular scale and tissue scale in H&E-stained histological whole slide images. At the cellular scale, the predictive power of DNNs progressively increases with higher resolution and significantly decreases when the resolvable feature length exceeds 5 microns. Additionally, DNN uses more macro-scale features associated with tissue architecture and is optimized when assessing visual fields greater than 41 microns. Our study computes the length-scale requirements for optimal DNN learning on digital whole-slide microscopic images, holding the promise to guide future optical microscope designs in pathology applications and facilitating downstream deep learning analysis.

Case report: Long-term intracranial effect of zimberelimab monotherapy following surgical resection of high PD-L1-expressing brain metastases from NSCLC

Non-small cell lung cancer (NSCLC) accounted for the majority of lung cancer cases worldwide. Brain metastases (BM) frequently complicate NSCLC and portend a dismal prognosis. To control neurological symptoms, surgical resection is commonly followed by brain radiotherapy (RT). However, RT is often complicated by neurotoxicity. For patients with tumors that harbor positive driver genes, tyrosine kinase inhibitors are considered the standard of care. Nevertheless, treatment options for those without driver gene mutations are still debated. Programmed death receptor 1 (PD-1)/ligand 1 (PD-L1) inhibition has emerged as a novel therapeutic strategy for NSCLC patients with PD-L1-positive tumors, as well as for those with asymptomatic BM. However, the effect of anti-PD-1 antibodies on active BM within such specific populations is undetermined. Herein we present a case of a 65-year-old patient with NSCLC and high PD-L1-expressing BM. The patient underwent surgical resection of BM followed by first-line monotherapy with 31 cycles of zimberelimab, a novel anti-PD-1 antibody, and has already achieved 24 months of progression-free survival and intracranial recurrence-free survival. To our knowledge, this is the first report regarding the intracranial effect of zimberelimab on BM from primary lung cancer. This case report might facilitate an understanding of the intracranial effects of different anti-PD-1 antibodies for such populations.

AI-guided histopathology predicts brain metastasis in lung cancer patients

Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Lung cancer with brain metastases remaining in continuous complete remission due to pembrolizumab and temozolomide: a case report

Background

Immunotherapy has been shown to improve the overall survival (OS) in patients with advanced or metastatic non-small cell lung cancer (NSCLC) without driver gene mutations. However, monotherapy with immunotherapy alone or combined with chemotherapy in NSCLC patients with untreated brain metastases (BM) is still under debate. Data regarding treatment of BM with immunotherapy and temozolomide (TMZ) in patients with NSCLC is rare.

Case Presentation

A 60-year-old male due to cough and expectoration presented in our hospital. Chest computed tomography (CT), brain magnetic resonance imaging (MRI) and immunohistochemistry of a mediastinal lymph node biopsy were administered, he was diagnosed with stage IIIB lung adenocarcinoma. Without driver gene mutations, he was treated with platinum-based chemotherapy because he refused to accept concurrent radiation therapy (RT). Heavy cough companied with hemoptysis and chest CT scan both revealed progressive disease (PD) after 6 cycles of chemotherapy. Immunotherapy was consequently considered, while two metastatic lesions in the brain were confirmed after combined treatment of pembrolizumab with docetaxel. TMZ was administered in combination with pembrolizumab (200 mg, day 1). A new metastasis in the right occipital lobe was detected on a scan 1 month later, though the other 2 lesions continued to shrink. The treatment was continued, MRI and CT scans suggested complete response (CR) was achieved for both the BM and lung lesions after 3 cycles. Consolidation therapy with TMZ and pembrolizumab (100 mg) per month was considered for another 7 months. Maintenance monotherapy with pembrolizumab (100 mg) was selected because of his stable CR status. At 59 months since diagnosis, the patient remains alive, with CR for both the primary lesions and BM. The patient experienced slight numbness on each side of his feet. There was no occurrence of adverse effects greater than grade 3.

Conclusions

The data indicates that immunotherapy combined with TMZ for untreated BM in NSCLC patients maybe an efficient and safe decision making therapeutic choice. Despite the encouraging efficacy of the combination, it is an isolated case and the speculation of synergism need to be proved in further pharmacokinetic/pharmacodynamic studies even in large randomized controlled trials.

Non-Small-Cell Lung Cancer With CNS Metastasis: Disparities From a Real-World Analysis (GBOT-LACOG 0417)

Despite the advances in the approach to non–small-cell lung cancer (NSCLC) with CNS metastasis, access to timely diagnosis and treatment may not be optimal in many instances. Our main objective was to describe a cohort of patients with NSCLC with brain metastases from public and private cancer centers, and the differences between patients' presentation, treatment, and outcomes.

Worse survival in lung cancer patients with brain metastasis from public institutions.

Impact of PD-L1 expression, driver mutations and clinical characteristics on survival after anti-PD-1/PD-L1 immunotherapy versus chemotherapy in non-small-cell lung cancer: A meta-analysis of randomized trials

Purpose: To investigate the impact of programmed death-ligand 1 (PD-L1) expression, oncogenic mutations, and clinical characteristics on survival after treatment with anti-PD-1/PD-L1 antibodies versus chemotherapy in non-small cell lung cancer (NSCLC). Patients and Methods: This meta-analysis included randomized trials comparing anti-PD-1/PD-L1 antibodies with chemotherapy. Hazard ratios (HRs) and 95% confidence interval (CI) for overall survival (OS) for the trial population and prespecified subgroups were extracted. We calculated pooled estimates of treatment efficacy using the fixed-effects or random-effects model when appropriate. All statistical tests were two sided. Results: Seven trials involving 3871 patients were included. The pooled results showed that anti-PD-1/PD-L1 immunotherapy significantly prolonged OS (HR: 0.73; 95% CI, 0.63 to 0.84) and PFS (HR: 0.84; 95% CI, 0.71 to 0.99) compared to chemotherapy. OS benefit from immunotherapy were observed in all PD-L1 expression subgroups (negative: HR, 0.79; 95% CI, 0.67 to 0.93; weak-positive: HR, 0.80; 95% CI, 0.67 to 0.95; strong-positive: HR, 0.61; 95% CI, 0.47 to 0.78). Strong-positive PD-L1 expression showed a trend towards more benefit compared to weak-positive PD-L1 expression (interaction P = 0.08). KRAS mutant (HR: 0.60; 95% CI, 0.39 to 0.93), EGFR wild-type (HR: 0.73; 95% CI, 0.61 to 0.87) and smoker (HR: 0.70; 95% CI, 0.60 to 0.83) subgroups achieved significant OS benefit from immunotherapy compared to corresponding subgroups. Survival benefit to immunotherapy was not significantly associated with histology, CNS metastases, age, gender and performance status. Conclusion: This study confirmed that treatment with anti-PD-1/PD-L1 improves overall survival compared with chemotherapy. Benefit was seen, regardless of PD-L1 expression levels; however, PD-L1 strong-positive patients trended to have greatest benefit. Patients with a KRAS mutant or EGFR wild-type tumor have improved survival benefit from immunotherapy compared with KRAS wild-type or EGFR mutant NSCLC, respectively.

Targeted drugs for systemic therapy of lung cancer with brain metastases

Brain metastases are very common in lung cancer patients. The condition of these patients is complicated and difficult to treat, and adverse reactions following treatment can affect the nervous system, which severely reduces quality of life. Lung cancers are categorized as small cell lung cancers and non-small cell lung cancers. Patients with brain metastasis of small cell lung cancers are generally treated with brain radiotherapy and systemic chemotherapy, but stage III/IV patients with brain metastasis of non-small cell lung cancers are generally not responsive to radiotherapy or chemotherapy. With the recent development of targeted drugs, tumor molecular profile detection allows the selection of appropriate targeted drugs for adjuvant pharmacological treatment of brain metastasis in lung cancer patients. In recent years, immune checkpoint inhibitors have emerged and have been approved by the Food and Drug Administration (FDA) for the treatment of certain cancers, but their efficacy in lung cancer patients with brain metastases still needs to be confirmed. This paper focuses on highlighting drugs for targeted therapy of brain metastasis in lung cancer patients and their molecular targets and mechanisms of drug resistance.

A study on different therapies and prognosis-related factors for 101 patients with SCLC and brain metastases

OBJECTIVE

There is a need to explore multi-discipline general treatment modes to improve the survival period of patients with SCLC and brain metastases undergoing standard radiotherapy treatment.

METHODS

A total of 101 patients with SCLC and brain metastases were included into this study. These patients were classified into 4 groups, based on different treatment modes: chemotherapy group, brain radiotherapy group, brain radiotherapy combined with sequential chemotherapy, and chemotherapy combined with sequential brain radiotherapy. Recent and long-term curative effects were compared among the 4 groups.

RESULTS

A RR of 42.57% was determined for all 4 groups, and median PFS and OS was 11.56 and 17.32 months, respectively. After SCLC with brain metastases manifested in the limited stage, the difference in median survival period was not statistically significant among the 4 treatment groups (P = 0.29). At the extensive stage of SCLC, survival period was superior in the brain radiotherapy combined with sequential chemotherapy group, compared with other groups (P<0.05). Furthermore, median survival period in the brain radiotherapy combined with sequential chemotherapy group was 15.5 ± 1.03 months. This was followed by 12.0 ± 3.06 months in the chemotherapy combined with sequential brain radiotherapy group, 8.0 ± 1.49 months in the chemotherapy group, and 8.0 ± 0.43 months in the brain radiotherapy group.

CONCLUSION

Combining chemotherapy with brain radiotherapy is a better treatment mode compared with single therapy for treating SCLC with brain metastases. Furthermore, it is recommended for patients in the extensive stage to initially receive brain radiotherapy.