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Mule, J.

Publications and source records attributed to Mule, J..

3 recordsLinked to original sources

Evaluating the Radiation Sensitivity Index and 12-chemokine gene expression signature for clinical use in a CLIA laboratory

BackgroundThe radiation sensitivity index (RSI) and 12-chemokine gene expression signature (12CK GES) are two gene expression signatures (GES) that were previously developed to predict tumor radiation sensitivity or identify the presence of tertiary lymphoid structures in tumors, respectively. To advance the use of these GES into clinical trial evaluation, their assays must be assessed within the context of the Clinical Laboratory Improvement Amendments (CLIA) process. MethodsUsing HG-U133Plus 2.0 arrays, we first established CLIA laboratory proficiency. Then the accuracy (limit of detection and macrodissection impact), precision (variability by time and operator), sample type (surgery vs. biopsy), and concordance with reference laboratory were evaluated. ResultsRSI and 12CK GES were reproducible (RSI: 0.01 mean difference, 12CK GES 0.17 mean difference) and precise with respect to time and operator. Taken together, the reproducibility analysis of the scores indicated a median RSI difference of 0.06 (6.47% of range) across samples and a median 12CK GES difference of 0.92 (12.29% of range). Experiments indicated that the lower limit of input RNA is 5 ng. Reproducibility with a second CLIA laboratory demonstrated reliability with the median RSI score difference of 0.065 (6% of full range) and 12CK GES difference of 0.93 (12 % of observed range). ConclusionsOverall, under CLIA, RSI and 12CK GES were demonstrated by the Moffitt Cancer Center Advanced Diagnostic Laboratory to be reproducible GES for clinical usage.

genomics↗

Spatial Clustering of CD68+ Tumor Associated Macrophages with Tumor Cells is Associated with Worse Overall Survival in Metastatic Clear Cell Renal Cell Carcinoma

Immune infiltration is typically quantified using cellular density, not accounting for cellular clustering. Tumor-associated macrophages (TAM) activate oncogenic signaling through paracrine interactions with tumor cells, which may be better reflected by local cellular clustering than global density metrics. Using multiplex immunohistochemistry and digital pathologic analysis we quantified cellular density and cellular clustering for myeloid cell markers in 129 regions of interest from 55 samples from 35 patients with metastatic ccRCC. CD68+ cells were found to be clustered with tumor cells and dispersed from stromal cells, while CD163+ and CD206+ cells were found to be clustered with stromal cells and dispersed from tumor cells. CD68+ density was not associated with OS, while high tumor/CD68+ cell clustering was associated with significantly worse OS. These novel findings would not have been identified if immune infiltrate was assessed using cellular density alone, highlighting the importance of including spatial analysis in studies of immune cell infiltration of tumors. SIGNIFICANCEIncreased clustering of CD68+ TAMs and tumor cells was associated with worse overall survival for patients with metastatic ccRCC. This effect would not have been identified if immune infiltrate was assessed using cell density alone, highlighting the importance of including spatial analysis in studies of immune cell infiltration of tumors.

cancer biology↗

Harnessing tumor immune ecosystem dynamics to personalize radiotherapy

Radiotherapy is a pillar of cancer care and augments the response to immunotherapies. However, little is known regarding the relationships between the tumor immune ecosystem (TIES) and intrinsic radiosensitivity, and a pressing question in oncology is how to optimize radiotherapy to improve patient responses to immune therapies. To address this challenge, we profiled over 10,000 primary tumors for their metrics of radiosensitivity and immune cell infiltrate (ICI), and applied a new integrated in silico model that mimics the dynamic relationships between tumor growth, ICI flux and the response to radiation. We then validated this model with a separate cohort of 59 lung cancer patients treated with radiotherapy. These analyses explain radiation response based on its effect on the TIES and quantifies the likelihood that radiation can promote a shift to anti-tumor immunity. Dynamic modeling of the relationship between tumor radiosensitivity and the TIES may provide opportunity to personalize combined radiation and immunotherapy approaches.

cancer biology↗