Browsing by Author "Chan, Michael D."
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Item c-Met Mediated Cytokine Network Promotes Brain Metastasis of Breast Cancer by Remodeling Neutrophil Activities(MDPI, 2023-05-05) Liu, Yin; Smith, Margaret R.; Wang, Yuezhu; D’Agostino, Ralph, Jr.; Ruiz, Jimmy; Lycan, Thomas; Kucera, Gregory L.; Miller, Lance D.; Li, Wencheng; Chan, Michael D.; Farris, Michael; Su, Jing; Song, Qianqian; Zhao, Dawen; Chandrasekaran, Arvind; Xing, Fei; Biostatistics and Health Data Science, School of MedicineThe brain is one of the most common metastatic sites among breast cancer patients, especially in those who have Her2-positive or triple-negative tumors. The brain microenvironment has been considered immune privileged, and the exact mechanisms of how immune cells in the brain microenvironment contribute to brain metastasis remain elusive. In this study, we found that neutrophils are recruited and influenced by c-Met high brain metastatic cells in the metastatic sites, and depletion of neutrophils significantly suppressed brain metastasis in animal models. Overexpression of c-Met in tumor cells enhances the secretion of a group of cytokines, including CXCL1/2, G-CSF, and GM-CSF, which play critical roles in neutrophil attraction, granulopoiesis, and homeostasis. Meanwhile, our transcriptomic analysis demonstrated that conditioned media from c-Met high cells significantly induced the secretion of lipocalin 2 (LCN2) from neutrophils, which in turn promotes the self-renewal of cancer stem cells. Our study unveiled the molecular and pathogenic mechanisms of how crosstalk between innate immune cells and tumor cells facilitates tumor progression in the brain, which provides novel therapeutic targets for treating brain metastasis.Item Comprehensive and Computable Molecular Diagnostic Panel (C2Dx) From Small Volume Specimens for Precision Oncology: Molecular Subtyping of Non-Small Cell Lung Cancer From Fine Needle Aspirates(Frontiers Media, 2021-04-16) Su, Jing; Huang, Lynn S.; Barnard, Ryan; Parks, Graham; Cappellari, James; Bellinger, Christina; Dotson, Travis; Craddock, Lou; Prakash, Bharat; Hovda, Jonathan; Clark, Hollins; Petty, William Jeffrey; Pasche, Boris; Chan, Michael D.; Miller, Lance D.; Ruiz, Jimmy; Biostatistics, School of Public HealthThe Comprehensive, Computable NanoString Diagnostic gene panel (C2Dx) is a promising solution to address the need for a molecular pathological research and diagnostic tool for precision oncology utilizing small volume tumor specimens. We translate subtyping-related gene expression patterns of Non-Small Cell Lung Cancer (NSCLC) derived from public transcriptomic data which establish a highly robust and accurate subtyping system. The C2Dx demonstrates supreme performance on the NanoString platform using microgram-level FNA samples and has excellent portability to frozen tissues and RNA-Seq transcriptomic data. This workflow shows great potential for research and the clinical practice of cancer molecular diagnosis.Item Genomic signature for oligometastatic disease in non-small cell lung cancer patients with brain metastases(Frontiers Media, 2024-09-17) Choi, Ariel R.; D’Agostino, Ralph B., Jr.; Farris, Michael K.; Abdulhaleem, Mohammed; Hunting, John C.; Wang, Yuezhu; Smith, Margaret R.; Ruiz, Jimmy; Lycan, Thomas W.; Petty, W. Jeffrey; Cramer, Christina K.; Tatter, Stephen B.; Laxton, Adrian W.; White, Jaclyn J.; Li, Wencheng; Su, Jing; Whitlow, Christopher; Xing, Fei; Chan, Michael D.; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthPurpose/objectives: Biomarkers for extracranial oligometastatic disease remain elusive and few studies have attempted to correlate genomic data to the presence of true oligometastatic disease. Methods: Patients with non-small cell lung cancer (NSCLC) and brain metastases were identified in our departmental database. Electronic medical records were used to identify patients for whom liquid biopsy-based comprehensive genomic profiling (Guardant Health) was available. Extracranial oligometastatic disease was defined as patients having ≤5 non-brain metastases without diffuse involvement of a single organ. Widespread disease was any spread beyond oligometastatic. Fisher's exact tests were used to screen for mutations statistically associated (p<0.1) with either oligometastatic or widespread extracranial disease. A risk score for the likelihood of oligometastatic disease was generated and correlated to the likelihood of having oligometastatic disease vs widespread disease. For oligometastatic patients, a competing risk analysis was done to assess for cumulative incidence of oligometastatic progression. Cox regression was used to determine association between oligometastatic risk score and oligoprogression. Results: 130 patients met study criteria and were included in the analysis. 51 patients (39%) had extracranial oligometastatic disease. Genetic mutations included in the Guardant panel that were associated (p<0.1) with the presence of oligometastatic disease included ATM, JAK2, MAP2K2, and NTRK1, while ARID1A and CCNE1 were associated with widespread disease. Patients with a positive, neutral and negative risk score for oligometastatic disease had a 78%, 41% and 11.5% likelihood of having oligometastatic disease, respectively (p<0.0001). Overall survival for patients with positive, neutral and negative risk scores for oligometastatic disease was 86% vs 82% vs 64% at 6 months (p=0.2). Oligometastatic risk score was significantly associated with the likelihood of oligoprogression based on the Wald chi-square test. Patients with positive, neutral and negative risk scores for oligometastatic disease had a cumulative incidence of oligometastatic progression of 77% vs 35% vs 33% at 6 months (p=0.03). Conclusions: Elucidation of a genomic signature for extracranial oligometastatic disease derived from non-invasive liquid biopsy appears feasible for NSCLC patients. Patients with this signature exhibited higher rates of early oligoprogression. External validation could lead to a biomarker that has the potential to direct local therapies in oligometastatic patients.Item Modulation of oxidative phosphorylation and mitochondrial biogenesis by cigarette smoke influence the response to immune therapy in NSCLC patients(Elsevier, 2023-04) Wang, Yuezhu; Smith, Margaret; Ruiz, Jimmy; Liu, Yin; Kucera, Gregory L.; Topaloglu, Umit; Chan, Michael D.; Li, Wencheng; Su, Jing; Xing, Fei; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthThe treatment regimen of non-small cell lung cancer (NSCLC) has drastically changed owing to the superior anti-cancer effects generated by the immune-checkpoint blockade (ICB). However, only a subset of patients experience benefit after receiving ICBs. Therefore, it is of paramount importance to increase the response rate by elucidating the underlying molecular mechanisms and identifying novel therapeutic targets to enhance the efficacy of IBCs in non-responders. We analyzed the progression-free survival (PFS) and overall survival (OS) of 295 NSCLC patients who received anti-PD-1 therapy by segregating them with multiple clinical factors including sex, age, race, smoking history, BMI, tumor grade and subtype. We also identified key signaling pathways and mutations that are enriched in patients with distinct responses to ICB by gene set enrichment analysis (GSEA) and mutational analyses. We found that former and current smokers have a higher response rate to anti-PD-1 treatment than non-smokers. GSEA results revealed that oxidative phosphorylation (OXPHOS) and mitochondrial related pathways are significantly enriched in both responders and smokers, suggesting a potential role of cellular metabolism in regulating immune response to ICB. We also demonstrated that all-trans retinoic acid (ATRA) which enhances mitochondrial function significantly enhanced the efficacy of anti-PD-1 treatment in vivo. Our clinical and bioinformatics based analyses revealed a connection between smoking induced metabolic switch and the response to immunotherapy, which can be the basis for developing novel combination therapies that are beneficial to never smoked NSCLC patients.Item Multi-Omics Analysis of Brain Metastasis Outcomes Following Craniotomy(Frontiers Media, 2021-04-06) Su, Jing; Song, Qianqian; Qasem, Shadi; O’Neill, Stacey; Lee, Jingyun; Furdui, Cristina M.; Pasche, Boris; Metheny-Barlow, Linda; Masters, Adrianna H.; Lo, Hui-Wen; Xing, Fei; Watabe, Kounosuke; Miller, Lance D.; Tatter, Stephen B.; Laxton, Adrian W.; Whitlow, Christopher T.; Chan, Michael D.; Soike, Michael H.; Ruiz, Jimmy; Biostatistics, School of Public HealthBackground: The incidence of brain metastasis continues to increase as therapeutic strategies have improved for a number of solid tumors. The presence of brain metastasis is associated with worse prognosis but it is unclear if distinctive biomarkers can separate patients at risk for CNS related death. Methods: We executed a single institution retrospective collection of brain metastasis from patients who were diagnosed with lung, breast, and other primary tumors. The brain metastatic samples were sent for RNA sequencing, proteomic and metabolomic analysis of brain metastasis. The primary outcome was distant brain failure after definitive therapies that included craniotomy resection and radiation to surgical bed. Novel prognostic subtypes were discovered using transcriptomic data and sparse non-negative matrix factorization. Results: We discovered two molecular subtypes showing statistically significant differential prognosis irrespective of tumor subtype. The median survival time of the good and the poor prognostic subtypes were 7.89 and 42.27 months, respectively. Further integrated characterization and analysis of these two distinctive prognostic subtypes using transcriptomic, proteomic, and metabolomic molecular profiles of patients identified key pathways and metabolites. The analysis suggested that immune microenvironment landscape as well as proliferation and migration signaling pathways may be responsible to the observed survival difference. Conclusion: A multi-omics approach to characterization of brain metastasis provides an opportunity to identify clinically impactful biomarkers and associated prognostic subtypes and generate provocative integrative understanding of disease.Item Prognostic Mutational Signatures of NSCLC Patients treated with chemotherapy, immunotherapy and chemoimmunotherapy(Springer Nature, 2023-03-27) Smith, Margaret R.; Wang, Yuezhu; D’Agostino, Ralph, Jr.; Liu, Yin; Ruiz, Jimmy; Lycan, Thomas; Oliver, George; Miller, Lance D.; Topaloglu, Umit; Pinkney, Jireh; Abdulhaleem, Mohammed N.; Chan, Michael D.; Farris, Michael; Su, Jing; Mileham, Kathryn F.; Xing, Fei; Biostatistics and Health Data Science, School of MedicineDifferent types of therapy are currently being used to treat non-small cell lung cancer (NSCLC) depending on the stage of tumor and the presence of potentially druggable mutations. However, few biomarkers are available to guide clinicians in selecting the most effective therapy for all patients with various genetic backgrounds. To examine whether patients' mutation profiles are associated with the response to a specific treatment, we collected comprehensive clinical characteristics and sequencing data from 524 patients with stage III and IV NSCLC treated at Atrium Health Wake Forest Baptist. Overall survival based Cox-proportional hazard regression models were applied to identify mutations that were "beneficial" (HR < 1) or "detrimental" (HR > 1) for patients treated with chemotherapy (chemo), immune checkpoint inhibitor (ICI) and chemo+ICI combination therapy (Chemo+ICI) followed by the generation of mutation composite scores (MCS) for each treatment. We also found that MCS is highly treatment specific that MCS derived from one treatment group failed to predict the response in others. Receiver operating characteristics (ROC) analyses showed a superior predictive power of MCS compared to TMB and PD-L1 status for immune therapy-treated patients. Mutation interaction analysis also identified novel co-occurring and mutually exclusive mutations in each treatment group. Our work highlights how patients' sequencing data facilitates the clinical selection of optimized treatment strategies.Item Single-cell sequencing reveals the landscape of the human brain metastatic microenvironment(Springer Nature, 2023-07-21) Song, Qianqian; Ruiz, Jimmy; Xing, Fei; Lo, Hui-Wen; Craddock, Lou; Pullikuth, Ashok K.; Miller, Lance D.; Soike, Michael H.; O’Neill, Stacey S.; Watabe, Kounosuke; Chan, Michael D.; Su, Jing; Biostatistics and Health Data Science, School of MedicineBrain metastases is the most common intracranial tumor and account for approximately 20% of all systematic cancer cases. It is a leading cause of death in advanced-stage cancer, resulting in a five-year overall survival rate below 10%. Therefore, there is a critical need to identify effective biomarkers that can support frequent surveillance and promote efficient drug guidance in brain metastasis. Recently, the remarkable breakthroughs in single-cell RNA-sequencing (scRNA-seq) technology have advanced our insights into the tumor microenvironment (TME) at single-cell resolution, which offers the potential to unravel the metastasis-related cellular crosstalk and provides the potential for improving therapeutic effects mediated by multifaceted cellular interactions within TME. In this study, we have applied scRNA-seq and profiled 10,896 cells collected from five brain tumor tissue samples originating from breast and lung cancers. Our analysis reveals the presence of various intratumoral components, including tumor cells, fibroblasts, myeloid cells, stromal cells expressing neural stem cell markers, as well as minor populations of oligodendrocytes and T cells. Interestingly, distinct cellular compositions are observed across different samples, indicating the influence of diverse cellular interactions on the infiltration patterns within the TME. Importantly, we identify tumor-associated fibroblasts in both our in-house dataset and external scRNA-seq datasets. These fibroblasts exhibit high expression of type I collagen genes, dominate cell-cell interactions within the TME via the type I collagen signaling axis, and facilitate the remodeling of the TME to a collagen-I-rich extracellular matrix similar to the original TME at primary sites. Additionally, we observe M1 activation in native microglial cells and infiltrated macrophages, which may contribute to a proinflammatory TME and the upregulation of collagen type I expression in fibroblasts. Furthermore, tumor cell-specific receptors exhibit a significant association with patient survival in both brain metastasis and native glioblastoma cases. Taken together, our comprehensive analyses identify type I collagen-secreting tumor-associated fibroblasts as key mediators in metastatic brain tumors and uncover tumor receptors that are potentially associated with patient survival. These discoveries provide potential biomarkers for effective therapeutic targets and intervention strategies.Item Upfront immunotherapy leads to lower brain metastasis velocity in patients undergoing stereotactic radiosurgery for brain metastases(Old City Publishing, 2022) Abdulhaleem, Mohammed; Scott, Emmanuel; Johnston, Hannah; Isom, Scott; Lanier, Claire; LeCompte, Michael; Cramer, Christina K.; Ruiz, Jimmy; Lo, Hui-Wen; Watabe, Kuonosuke; O’Neill, Stacey; Whitlow, Christopher; Tatter, Stephen B.; Laxton, Adrian W.; Su, Jing; Chan, Michael D.; Biostatistics, School of Public HealthBackground: While immunotherapy has been shown to improve survival and decrease neurologic death in patients with brain metastases, it remains unclear whether this improvement is due to prevention of new metastasis to the brain. Method: We performed a retrospective review of patients presenting with brain metastases simultaneously with the first diagnosis of metastatic disease and were treated with upfront immunotherapy as part of their treatment regimen and stereotactic radiosurgery (SRS) to the brain metastases. We compared this cohort with a historical control population (prior to the immunotherapy era) who were treated with pre-immunotherapy standard of care systemic therapy and with SRS to the brain metastases. Results: Median overall survival time was improved in the patients receiving upfront immunotherapy compared to the historical cohort (48 months vs 8.4 months, p=0.001). Median time to distant brain failure was statistically equivalent (p=0.3) between the upfront immunotherapy cohort and historical control cohort (10.3 vs 12.6 months). Brain metastasis velocity was lower in the upfront immunotherapy cohort (median 3.72 metastases per year) than in the historical controls (median 9.48 metastases per year, p=0.001). Cumulative incidence of neurologic death at one year was 12% in the upfront immunotherapy cohort and 28% in the historical control cohort (p=0.1). Conclusions: Upfront immunotherapy appears to improve overall survival and decrease BMV compared to historical controls. While these data remain to be validated, they suggest that brain metastasis patients may benefit from concurrent immunotherapy with SRS.