Preoperative symptom severity in cervical spondylotic myelopathy (CSM) can be variable. Radiomic signatures could provide an imaging biomarker for symptom severity in CSM. This study utilizes ...radiomic signatures of T1-weighted and T2-weighted magnetic resonance imaging images to correlate with preoperative symptom severity based on modified Japanese Orthopaedic Association (mJOA) scores for patients with CSM.
Sixty-two patients with CSM were identified. Preoperative T1-weighted and T2-weighted magnetic resonance imaging images for each patient were segmented from C2-C7. A total of 205 texture features were extracted from each volume of interest. After feature normalization, each second-order feature was further subdivided to yield a total of 400 features from each volume of interest for analysis. Supervised machine learning was used to build radiomic models.
The patient cohort had a median mJOA preoperative score of 13; of which, 30 patients had a score of >13 (low severity) and 32 patients had a score of ≤13 (high severity). Radiomic analysis of T2-weighted imaging resulted in 4 radiomic signatures that correlated with preoperative mJOA with a sensitivity, specificity, and accuracy of 78%, 89%, and 83%, respectively (P < 0.004). The area under the curve value for the ROC curves were 0.69, 0.70, and 0.77 for models generated by independent T1 texture features, T1 and T2 texture features in combination, and independent T2 texture features, respectively.
Radiomic models correlate with preoperative mJOA scores using T2 texture features in patients with CSM. This may serve as a surrogate, objective imaging biomarker to measure the preoperative functional status of patients.
Individual MRI characteristics (e.g., volume) are routinely used to identify survival-associated phenotypes for glioblastoma (GBM). This study investigated whether combinations of MRI features can ...also stratify survival. Furthermore, the molecular differences between phenotype-induced groups were investigated.
Ninety-two patients with imaging, molecular, and survival data from the TCGA (The Cancer Genome Atlas)-GBM collection were included in this study. For combinatorial phenotype analysis, hierarchical clustering was used. Groups were defined based on a cutpoint obtained via tree-based partitioning. Furthermore, differential expression analysis of microRNA (miRNA) and mRNA expression data was performed using GenePattern Suite. Functional analysis of the resulting genes and miRNAs was performed using Ingenuity Pathway Analysis. Pathway analysis was performed using Gene Set Enrichment Analysis.
Clustering analysis reveals that image-based grouping of the patients is driven by 3 features: volume-class, hemorrhage, and T1/FLAIR-envelope ratio. A combination of these features stratifies survival in a statistically significant manner. A cutpoint analysis yields a significant survival difference in the training set (median survival difference: 12 months, p = 0.004) as well as a validation set (p = 0.0001). Specifically, a low value for any of these 3 features indicates favorable survival characteristics. Differential expression analysis between cutpoint-induced groups suggests that several immune-associated (natural killer cell activity, T-cell lymphocyte differentiation) and metabolism-associated (mitochondrial activity, oxidative phosphorylation) pathways underlie the transition of this phenotype. Integrating data for mRNA and miRNA suggests the roles of several genes regulating proliferation and invasion.
A 3-way combination of MRI phenotypes may be capable of stratifying survival in GBM. Examination of molecular processes associated with groups created by this combinatorial phenotype suggests the role of biological processes associated with growth and invasion characteristics.
Malignant gliomas are deadly tumours with few therapeutic options. Although immunotherapy may be a promising therapeutic strategy for treating gliomas, a significant barrier is the CD11b+ ...tumour-associated myeloid cells (TAMCs), a heterogeneous glioma infiltrate comprising up to 40% of a glioma's cellular mass that inhibits anti-tumour T-cell function and promotes tumour progression. A theranostic approach uses a single molecule for targeted radiopharmaceutical therapy (TRT) and diagnostic imaging; however, there are few reports of theranostics targeting the tumour microenvironment.
Utilizing a newly developed bifunctional chelator, Lumi804, an anti-CD11b antibody (αCD11b) was readily labelled with either Zr-89 or Lu-177, yielding functional radiolabelled conjugates for PET, SPECT, and TRT.
89Zr/177Lu-labeled Lumi804-αCD11b enabled non-invasive imaging of TAMCs in murine gliomas. Additionally, 177Lu-Lumi804-αCD11b treatment reduced TAMC populations in the spleen and tumour and improved the efficacy of checkpoint immunotherapy.
89Zr- and 177Lu-labeled Lumi804-αCD11b may be a promising theranostic pair for monitoring and reducing TAMCs in gliomas to improve immunotherapy responses.
A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
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BackgroundWe present a radiomics-based model for predicting response to pembrolizumab in patients with advanced rare cancers.MethodsThe study included 57 patients with advanced rare cancers who were ...enrolled in our phase II clinical trial of pembrolizumab. Tumor response was evaluated using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and immune-related RECIST (irRECIST). Patients were categorized as 20 “controlled disease” (stable disease, partial response, or complete response) or 37 progressive disease). We used 3D-slicer to segment target lesions on standard-of-care, pretreatment contrast enhanced CT scans. We extracted 610 features (10 histogram-based features and 600 second-order texture features) from each volume of interest. Least absolute shrinkage and selection operator logistic regression was used to detect the most discriminatory features. Selected features were used to create a classification model, using XGBoost, for the prediction of tumor response to pembrolizumab. Leave-one-out cross-validation was performed to assess model performance.FindingsThe 10 most relevant radiomics features were selected; XGBoost-based classification successfully differentiated between controlled disease (complete response, partial response, stable disease) and progressive disease with high accuracy, sensitivity, and specificity in patients assessed by RECIST (94.7%, 97.3%, and 90%, respectively; p<0.001) and in patients assessed by irRECIST (94.7%, 93.9%, and 95.8%, respectively; p<0.001). Additionally, the common features of the RECIST and irRECIST groups also highly predicted pembrolizumab response with accuracy, sensitivity, specificity, and p value of 94.7%, 97%, 90%, p<0.001% and 96%, 96%, 95%, p<0.001, respectively.ConclusionOur radiomics-based signature identified imaging differences that predicted pembrolizumab response in patients with advanced rare cancer.InterpretationOur radiomics-based signature identified imaging differences that predicted pembrolizumab response in patients with advanced rare cancer.
Abstract
Background
Treatment options for patients with melanoma brain metastasis (MBM) have changed significantly in the last decade. Few studies have evaluated changes in outcomes and factors ...associated with survival in MBM patients over time. The aim of this study is to evaluate changes in clinical features and overall survival (OS) for MBM patients.
Methods
Patients diagnosed with MBMs from 1/1/2009 to 12/31/2013 (Prior Era; PE) and 1/1/2014 to 12/31/2018 (Current Era; CE) at The University of Texas MD Anderson Cancer Center were included in this retrospective analysis. The primary outcome measure was OS. Log-rank test assessed differences between groups; multivariable analyses were performed with Cox proportional hazards models and recursive partitioning analysis (RPA).
Results
A total of 791 MBM patients (PE, n = 332; CE, n = 459) were included in analysis. Median OS from MBM diagnosis was 10.3 months (95% CI, 8.9–12.4) and improved in the CE vs PE (14.4 vs 10.3 months, P < .001). Elevated serum lactate dehydrogenase (LDH) was the only factor associated with worse OS in both PE and CE patients. Factors associated with survival in CE MBM patients included patient age, primary tumor Breslow thickness, prior immunotherapy, leptomeningeal disease, symptomatic MBMs, and whole brain radiation therapy. Several factors associated with OS in the PE were not significant in the CE. RPA demonstrated that elevated serum LDH and prior immunotherapy treatment are the most important determinants of survival in CE MBM patients.
Conclusions
OS and factors associated with OS have changed for MBM patients. This information can inform contemporary patient management and clinical investigations.
Antiangiogenic therapy can rapidly reduce vascular permeability and cerebral edema but high doses of bevacizumab may induce selective pressure to promote resistance. This trial evaluated the efficacy ...of low dose bevacizumab in combination with lomustine (CCNU) compared to standard dose bevacizumab in patients with recurrent glioblastoma. Patients (N = 71) with recurrent glioblastoma who previously received radiation and temozolomide were randomly assigned 1:1 to receive bevacizumab monotherapy (10 mg/kg) or low dose bevacizumab (5 mg/kg) in combination with lomustine (90 mg/m
2
). The primary end point was progression-free survival (PFS) based on a blinded, independent radiographic assessment of post-contrast T1-weighted and non-contrast T2/FLAIR weighted magnetic resonance imaging (MRI) using RANO criteria. For 69 evaluable patients, median PFS was not significantly longer in the low dose bevacizumab + lomustine arm (4.34 months, CI 2.96–8.34) compared to the bevacizumab alone arm (4.11 months, CI 2.69–5.55, p = 0.19). In patients with first recurrence, there was a trend towards longer median PFS time in the low dose bevacizumab + lomustine arm (4.96 months, CI 4.17–13.44) compared to the bevacizumab alone arm (3.22 months CI 2.5–6.01, p = 0.08). The combination of low dose bevacizumab plus lomustine was not superior to standard dose bevacizumab in patients with recurrent glioblastoma. Although the study was not designed to exclusively evaluate patients at first recurrence, a strong trend towards improved PFS was seen in that subgroup for the combination of low dose bevacizumab plus lomustine. Further studies are needed to better identify such subgroups that may most benefit from the combination treatment.
Cancer Imaging in Immunotherapy Ak, Murat; Eleneen, Yousra; Ayoub, Mira ...
Advances in experimental medicine and biology,
01/2021, Letnik:
1342
Journal Article
Recenzirano
Immune therapeutics are revolutionizing cancer treatments. In tandem, new and confounding imaging characteristics have appeared that are distinct from those typically seen with conventional cytotoxic ...therapies. In fact, only 10% of patients on immunotherapy may show tumor shrinkage, typical of positive responses on conventional therapy. Conversely, those on immune therapies may initially demonstrate a delayed response, transient enlargement followed by tumor shrinkage, stable size, or the appearance of new lesions. Response Evaluation Criteria in Solid Tumors (RECIST) or WHO criteria, developed to identify early effects of cytotoxic agents, may not provide a complete evaluation of new emerging treatment response pattern of immunotherapeutic agents. Therefore, new imaging response criteria, such as the immune-related Response Evaluation Criteria in Solid Tumors (irRECIST), immune Response Evaluation Criteria in Solid Tumors (iRECIST), and immune-related Response Criteria (irRC), are proposed. However, FDA approval of emerging therapies including immunotherapies still relies on the current RECIST criteria. In this chapter, we review the traditional and new imaging response criteria for evaluation of solid tumors and briefly touch on some of the more commonly associated immunotherapy-induced adverse events.
Introduction
The aim of the present study is to assess whether postoperative residual non-enhancing volume (PRNV) is correlated and predictive of overall survival (OS) in glioblastoma (GBM) patients.
...Methods
We retrospectively analyzed a total 134 GBM patients obtained from The University of Texas MD Anderson Cancer Center (training cohort, n = 97) and The Cancer Genome Atlas (validation cohort, n = 37). All patients had undergone postoperative magnetic resonance imaging immediately after surgery. We evaluated the survival outcomes with regard to PRNV. The role of possible prognostic factors that may affect survival after resection, including age, sex, preoperative Karnofsky performance status, postoperative nodular enhancement, surgically induced enhancement, and postoperative necrosis, was investigated using univariate and multivariate Cox proportional hazards regression analyses. Additionally, a recursive partitioning analysis (RPA) was used to identify prognostic groups.
Results
Our analyses revealed that a high PRNV (HR 1.051; p-corrected = 0.046) and old age (HR 1.031; p-corrected = 0.006) were independent predictors of overall survival. This trend was also observed in the validation cohort (higher PRNV: HR 1.127, p-corrected = 0.002; older age: HR 1.034, p-corrected = 0.022). RPA analysis identified two prognostic risk groups: low-risk group (PRNV < 70.2 cm
3
; n = 55) and high-risk group (PRNV ≥ 70.2 cm
3
; n = 42). GBM patients with low PRNV had a significant survival benefit (5.6 months; p = 0.0037).
Conclusion
Our results demonstrate that high PRNV is associated with poor OS. Such results could be of great importance in a clinical setting, particularly in the postoperative management and monitoring of therapy.
Glioblastoma (GBM) is the most aggressive human brain tumor. Although several molecular subtypes of GBM are recognized, a robust molecular prognostic marker has yet to be identified. Here, we report ...that the stemness regulator Sox2 is a new, clinically important target of microRNA-21 (miR-21) in GBM, with implications for prognosis. Using the MiR-21-Sox2 regulatory axis, approximately half of all GBM tumors present in the Cancer Genome Atlas (TCGA) and in-house patient databases can be mathematically classified into high miR-21/low Sox2 (Class A) or low miR-21/high Sox2 (Class B) subtypes. This classification reflects phenotypically and molecularly distinct characteristics and is not captured by existing classifications. Supporting the distinct nature of the subtypes, gene set enrichment analysis of the TCGA dataset predicted that Class A and Class B tumors were significantly involved in immune/inflammatory response and in chromosome organization and nervous system development, respectively. Patients with Class B tumors had longer overall survival than those with Class A tumors. Analysis of both databases indicated that the Class A/Class B classification is a better predictor of patient survival than currently used parameters. Further, manipulation of MiR-21-Sox2 levels in orthotopic mouse models supported the longer survival of the Class B subtype. The MiR-21-Sox2 association was also found in mouse neural stem cells and in the mouse brain at different developmental stages, suggesting a role in normal development. Therefore, this mechanism-based classification suggests the presence of two distinct populations of GBM patients with distinguishable phenotypic characteristics and clinical outcomes.
Molecular profiling-based classification of glioblastoma (GBM) into four subtypes has substantially increased our understanding of the biology of the disease and has pointed to the heterogeneous nature of GBM. However, this classification is not mechanism based and its prognostic value is limited. Here, we identify a new mechanism in GBM (the miR-21-Sox2 axis) that can classify ∼50% of patients into two subtypes with distinct molecular, radiological, and pathological characteristics. Importantly, this classification can predict patient survival better than the currently used parameters. Further, analysis of the miR-21-Sox2 relationship in mouse neural stem cells and in the mouse brain at different developmental stages indicates that miR-21 and Sox2 are predominantly expressed in mutually exclusive patterns, suggesting a role in normal neural development.
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