Search

Purpose/ObjectivesDetermining the optimal postoperative reirradiation volume following salvage surgery for recurrent head and neck squamous cell cancer (HNSCC) is critical given the significant risk of severe reirradiation toxicity and need to provide durable local control. The purpose of this study was to evaluate patterns of locoregional recurrence (LRR) after surgical salvage and adjuvant reirradiation with IMRT.Materials/MethodsPatterns of LRR for 61 patients treated consecutively between 2003-2014 who received post-operative IMRT reirradiation to ≥60 Gy for recurrent HNSCC were determined by 2 methods: 1) physician classification via visual comparison of post-radiotherapy imaging to reirradiation plans; and 2) using deformable image registration (DIR). Those without evaluable CT planning image data were excluded. All recurrences were verified by biopsy or radiological progression. Failures were defined as in-field, marginal, or out-of-field. Logistic regression analyses were performed to identify predictors for LRR.ResultsA total of 55 patients were eligible for analysis and 23 (42%) had documented LRR after reirradiation. Location of recurrent disease prior to salvage surgery (lymphatic vs. mucosal) was the only significant predictor of LRR after post-operative reirradiation (p = 0.037). Physician classification of LRR yielded 14 (61%) in-field failures, 3 (13%) marginal failures, and 6 (26%) out-of-field failures, while DIR yielded 10 (44%) in-field failures, 4 (17%) marginal failures, and 9 (39%) out-of-field failures. Most failures (57%) occurred within the original site of recurrence or first echelon lymphatic drainage. Of patients who had a free flap placed during salvage surgery, 56% of failures occurred within 1 cm of the surgical flap.ConclusionThe majority of locoregional recurrences after surgical salvage and adjuvant reirradiation for recurrent HNSCC occurred marginally or in-field, often in or near the anastomotic site.

A large proportion of patients with cancer are unresponsive to treatment with immune checkpoint blockade and other immunotherapies. Here, we report a mathematical model of the time course of tumour responses to immune checkpoint inhibitors. The model takes into account intrinsic tumour growth rates, the rates of immune activation and of tumour-immune cell interactions, and the efficacy of immune-mediated tumour killing. For 124 patients, four cancer types and two immunotherapy agents, the model reliably described the immune responses and final tumour burden across all different cancers and drug combinations examined. In validation cohorts from four clinical trials of checkpoint inhibitors (with a total of 177 patients), the model accurately stratified the patients according to reduced or increased long-term tumour burden. We also provide model-derived quantitative measures of treatment sensitivity for specific drug-cancer combinations. The model can be used to predict responses to therapy and to quantify specific drug-cancer sensitivities in individual patients.

Background:Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. We have developed a mechanistic mathematical model for better understanding these factors and their relations in order to predict treatment outcome and optimize personal treatment strategies.Methods:Here, we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate (α), tumor-immune infiltration (Λ), and immunotherapy-mediated amplification of anti-tumor response (µ). The model was calibrated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials.Results:The derived parameters Λ and µ were both significantly different between responding versus nonresponding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within 2 months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology.Conclusions:These results have demonstrated reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis.Funding:We gratefully acknowledge support from the Andrew Sabin Family Fellowship, Center for Radiation Oncology Research, Sheikh Ahmed Center for Pancreatic Cancer Research, GE Healthcare, Philips Healthcare, and institutional funds from the University of Texas M.D. Anderson Cancer Center. We have also received Cancer Center Support Grants from the National Cancer Institute (P30CA016672 to the University of Texas M.D. Anderson Cancer Center and P30CA072720 the Rutgers Cancer Institute of New Jersey). This research has also been supported in part by grants from the National Science Foundation Grant DMS-1930583 (ZW, VC), the National Institutes of Health (NIH) 1R01CA253865 (ZW, VC), 1U01CA196403 (ZW, VC), 1U01CA213759 (ZW, VC), 1R01CA226537 (ZW, RP, WA, VC), 1R01CA222007 (ZW, VC), U54CA210181 (ZW, VC), and the University of Texas System STARS Award (VC). BC acknowledges support through the SER Cymru II Programme, funded by the European Commission through the Horizon 2020 Marie Skłodowska-Curie Actions (MSCA) COFUND scheme and the Welsh European Funding Office (WEFO) under the European Regional Development Fund (ERDF). EK has also received support from the Project Purple, NIH (U54CA210181, U01CA200468, and U01CA196403), and the Pancreatic Cancer Action Network (16-65-SING). MF was supported through NIH/NCI center grant U54CA210181, R01CA222959, DoD Breast Cancer Research Breakthrough Level IV Award W81XWH-17-1-0389, and the Ernest Cockrell Jr. Presidential Distinguished Chair at Houston Methodist Research Institute. RP and WA received serial research awards from AngelWorks, the Gillson-Longenbaugh Foundation, and the Marcus Foundation. This work was also supported in part by grants from the National Cancer Institute to SHC (R01CA109322, R01CA127483, R01CA208703, and U54CA210181 CITO pilot grant) and to PYP (R01CA140243, R01CA188610, and U54CA210181 CITO pilot grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. Here we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate (α), tumor immune infiltration (Λ), and immunotherapy-mediated amplification of anti-tumor response (µ). The model was validated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials. The derived parameters Λ and µ were both significantly different between responding versus non-responding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within two months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology, demonstrating reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these results suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis.SIGNIFICANCECheckpoint inhibitors have revolutionized cancer immunotherapy, but only a subset of patients with solid tumors responds clinically. The ability to predict tumor responses a priori or soon after starting therapy would allow for personalized and timely adaptive clinical applications of checkpoint inhibitor- based immunotherapy in patients. By applying a mechanistic mathematical model, we show that checkpoint inhibitor therapeutic effectiveness is accurately predictable in most patients within two months after treatment initiation. Our method may be implemented directly into clinical practice, as it relies on standard-of-care imaging and pathology. If successful in prospective studies, this model will improve selection of cancer patients for checkpoint inhibitor therapy, and perhaps for other forms of humoral- or cell-based immunotherapy.

To study the deformation of the prostate by a rigid reusable endorectal coil and a balloon-type endorectal coil (BTC) during MRI of the prostate in brachytherapy imaging.The prostate gland was contoured on 157 MRI scans from 52 prostate cancer patients undergoing brachytherapy. The curvature of the posterior prostate surface deformation was computed as a measure of prostate distortion and compared between scans with a BTC, rigid endorectal coil (REC), or no endorectal coil. For the nine patients who had MRIs with all three endorectal scenarios, a mean prostate deformation vector was also calculated between scenarios using deformable image registration. These measures of prostate distortion were compared with the prostate anterior-to-posterior to left-to-right ratio (AP/LR) on the largest prostate axial slice.Significant differences in prostate curvature were found between scans without an endorectal coil versus a REC versus a BTC (p0.001). The mean prostate deformation was 3.9 mm due to the BTC and 2.0 mm for the REC (p = 0.012). The mean AP/LR ratio was 0.62 with a BTC versus 0.76 without a coil or 0.73 with a REC (p0.001), but no difference existed between scans with a REC versus no coil (p = 0.7). The AP/LR ratio showed moderate correlation with prostate curvature (r = 0.48), and with mean prostate deformation (r = -0.64 to 0.68).The REC caused minimal deformation of the prostate compared with a BTC with adequate MR image quality, and calculation of the cross-sectional AP/LR ratio on the largest axial prostate slice can serve as a simple measure of prostate distortion.

Purpose/Objective(s) In the setting of head and neck (HN) re-irradiation (reRT), the goal is to adequately cover disease with as small a volume as appropriate to minimize normal tissue toxicity without compromising local control. However, it can be a challenge to gauge the extent microscopic disease beyond the gross tumor to be included in the reRT volume. Here, we aim to determine the patterns of failure after HN reRT. Materials/Methods Patients treated with curative intent intensity modulated radiation therapy (IMRT) or proton reRT from September 1999 – June 2015 were evaluated. A total of 148 patients with inoperable tumors received definitive reRT (intact) and 61 who underwent salvage surgery received post-operative reRT (postop). Those who had locoregional recurrence (LRR) and intact imaging data were analyzed. Using deformable imaging registration, diagnostic images at time of recurrence were overlaid on reRT treatment plans. The site of recurrence was delineated and evaluated by at least 2 radiation oncologists/radiologist with HN expertise. The patterns of failure were classified into five types based on spatial and dosimetric criteria: A (central high dose, or “in-field”), B (peripheral high dose), C (central elective dose), D (peripheral elective dose), and E (extraneous dose, or “out-of-field”). For patients who had multiple sites of recurrences, each site was classified independently. The kappa statistic was used to assess the inter-observer agreement on failure classification. Results Of the 209 patients treated, 67 developed LRR. This represented 44 of 148 (30%) intact patients (median dose 66 Gy) and 23 of 61 (38%) postop patients (median dose 60 Gy). Of these, 41 (61%) had imaging data for analysis, representing 47 sites of failures. Median time to failure was 21 weeks (range: 4 – 220 weeks). Patterns of failure among intact reRT were as follows: 13 Type A (39%), 6 Type B (18%), 1 Type C (3%), and 13 Type E (39%). The majority (79%) of failures were either in the high dose field or completely out of field. Interobserver agreement was 0.92. Patterns of failure among postop reRT were as follows: 4 type A (17%), 5 type B (22%), 5 type C (22%) and 5 type D (22%). The majority (56%) of recurrences were within 1 cm of the reconstructive flap bed, 40% recurred in the same primary subsite, and 17% recurred in the 1st echelon nodal level. Interobserver agreement was 0.68. Conclusion In patients who recurred after reRT, the majority was either within the central high-dose region, or completely outside the high-dose region suggesting poor disease biology. Biologic dose-escalation and or the addition of systemic therapies may offer improved disease control.

Purpose Permanent prostate brachytherapy dosimetry using computed tomography-magnetic resonance imaging (CT-MRI) fusion combines the anatomic detail of MRI with seed localization on CT but requires multimodality imaging acquisition and fusion. The purpose of this study was to compare the utility of MRI only postimplant dosimetry to standard CT-MRI fusion-based dosimetry. Methods and Materials Twenty-three patients undergoing permanent prostate brachytherapy with use of positive contrast MRI markers were included in this study. Dose calculation to the whole prostate, apex, mid-gland, and base was performed via standard CT-MRI fusion and MRI only dosimetry with prostate delineated on the same T2 MRI sequence. The 3-dimensional (3D) distances between seed positions of these two methods were also evaluated. Wilcoxon-matched-pair signed-rank test compared the D90 and V100 of the prostate and its sectors between methods. Results The day 0 D90 and V100 for the prostate were 98% versus 94% and 88% versus 86% for CT-MRI fusion and MRI only dosimetry. There were no differences in the D90 or V100 of the whole prostate, mid-gland, or base between dosimetric methods ( p > 0.19), but prostate apex D90 was high by 13% with MRI dosimetry ( p = 0.034). The average distance between seeds on CT-MRI fusion and MRI alone was 5.5 mm. After additional automated rigid registration of 3D seed positions, the average distance between seeds was 0.3 mm, and the previously observed differences in apex dose between methods was eliminated ( p > 0.11). Conclusions Permanent prostate brachytherapy dosimetry based only on MRI using positive contrast MRI markers is feasible, accurate, and reduces the uncertainties arising from CT-MRI fusion abating the need for postimplant multimodality imaging.

Purpose Pubic arch interference (PAI), when it occurs, is often a limiting factor for patients pursuing brachytherapy treatment of prostate cancer. Pre-brachytherapy pubic arch evaluation is often performed by CT or transrectal ultrasound (TRUS), but MRI has increasingly replaced these modalities for prostate cancer evaluation. The purpose of this study was to determine if staging MRI could be used to evaluate PAI and compare it with these other imaging methods. Methods and Materials Forty-one consecutive patients undergoing brachytherapy evaluation had pelvic MRI-, CT-, and TRUS-based brachytherapy simulation. Pubic arch overlap on T2-weighted MRI and CT was determined by contouring the prostate gland on its largest axial slice and superimposing this contour onto the pubic arch bones. The largest degree of overlap of the prostate gland on MRI and CT was used to predict the existence of PAI as determined by TRUS-based simulation. The correlation between prostate contour overlap was also compared between MRI and CT. Results Nineteen patients (48%) exhibited PAI on TRUS brachytherapy simulation evaluation. The average (±standard error) amount of prostate contour overlap on the pubic arch on CT was 2.9 ± 0.6 mm and on MRI was 2.0 ± 0.6 mm (linear correlation, R, of 0.783, p < 0.001). CT and MRI were equally predictive of PAI on TRUS evaluation (area under the curve = 0.75). Conclusion Pre-brachytherapy pubic arch assessment with diagnostic MRI provides similar predictability of PAI compared with CT, potentially obviating the need for additional pre-brachytherapy CT in the setting of staging MRI.

Aim The aim of this article is to determine if lightning is associated with the frequency of headache in migraineurs. Methods Participants fulfilling diagnostic criteria for International Headache Society-defined migraine were recruited from sites located in Ohio ( n = 23) and Missouri ( n = 67). They recorded headache activity in a daily diary for three to six months. A generalized estimating equations (GEE) logistic regression determined the odds ratio (OR) of headache on lightning days compared to non-lightning days. Other weather factors associated with thunderstorms were also added as covariates to the GEE model to see how they would attenuate the effect of lightning on headache. Results The mean age of the study population was 44 and 91% were female. The OR for headache was 1.31 (95% confidence limits (CL); 1.07, 1.66) during lighting days as compared to non-lightning days. The addition of thunderstorm-associated weather variables as covariates were only able to reduce the OR for headache on lightning days to 1.18 (95% CL; 1.02, 1.37). The probability of having a headache on lightning days was also further increased when the average current of lightning strikes for the day was more negative. Conclusion This study suggests that lightning represents a trigger for headache in migraineurs that cannot be completely explained by other meteorological factors. It is unknown if lightning directly triggers headaches through electromagnetic waves or indirectly through production of bioaerosols (e.g. ozone), induction of fungal spores or other mechanisms. These results should be interpreted cautiously until replicated in a second dataset.

The response of T cells to antigens (T cell activation) is marked by an increase in intracellular Ca2+ levels. Voltage-gated and Ca2+-dependent K+ channels control the membrane potential of human T cells and regulate Ca2+influx. This regulation is dependent on proper accumulation of K+ channels at the immunological synapse (IS) a signaling zone that forms between a T cell and antigen presenting cell. It is believed that the IS provides a site for regulation of the activation response and that K+ channel inhibition occurs at the IS, but the underlying mechanisms are unknown. A mathematical model was developed to test whether K+ efflux through K+ channels leads to an accumulation of K+ in the IS cleft, ultimately reducing K+ channel function and intracellular Ca2+ concentration ([Ca2+]i). Simulations were conducted in models of resting and activated T cell subsets, which express different levels of K+ channels, by varying the K+ diffusion constant and the spatial localization of K+ channels at the IS. K+ accumulation in the IS cleft was calculated to increase K+ concentration ([K+]) from its normal value of 5.0 mM to 5.2–10.0 mM. Including K+ accumulation in the model of the IS reduced calculated K+ current by 1–12% and consequently, reduced calculated [Ca2+]i by 1–28%. Significant reductions in K+ current and [Ca2+]i only occurred in activated T cell simulations when most K+ channels were centrally clustered at the IS. The results presented show that the localization of K+ channels at the IS can produce a rise in [K+] in the IS cleft and lead to a substantial decrease in K+ currents and [Ca2+]i in activated T cells thus providing a feedback inhibitory mechanism during T cell activation.

Several studies have reported that migraine headaches are more common in patients with allergic rhinitis and that immunotherapy decreases the frequency of headache in atopic headache sufferers.To determine if the degree of allergic sensitization and the administration of immunotherapy are associated with the prevalence, frequency, and disability of migraine headache in patients with allergic rhinitis.Consecutive patients between the ages of 18-65 presenting to an allergy practice that received a diagnosis of an allergic rhinitis subtype (eg, allergic or mixed rhinitis) were enrolled in this study. All participants underwent allergy testing as well as a structured verbal headache diagnostic interview to ascertain the clinical characteristics of each headache type. Those reporting headaches were later assigned a headache diagnosis by a headache specialist blinded to the rhinitis diagnosis based on 2004 International Classification Headache Disorders-2 (ICHD-2) diagnostic criteria. Migraine prevalence was defined as the percentage of patients with a diagnosis of migraine headache (ICHD-2 diagnoses 1.1-1.5). Migraine frequency represented the number of days per month with migraine headache self-reported during the headache interview and migraine disability was the number of days with disability obtained from the Migraine Disability Assessment questionnaire. Generalized linear models were used to analyze the migraine prevalence, frequency, and disability with the degree of allergic sensitization (percentage of positive allergy tests) and administration of immunotherapy as covariates. Patients were categorized into high (45% positive allergy tests) and low (≤ 45% positive allergy tests) atopic groups based on the number of allergy tests that were positive for the frequency and disability analyses.A total of 536 patients (60% female, mean age 40.9 years) participated in the study. The prevalence of migraine was not associated with the degree of allergic sensitization, but there was a significant age/immunotherapy interaction (P.02). Migraine headaches were less prevalent in the immunotherapy group than the nonimmunotherapy at ages40 years and more prevalent in the immunotherapy group at ages ≥ 40 years of age. In subjects ≤ 45 years of age, increasing percentages of allergic sensitization were associated with a decreased frequency and disability of migraine headache in the low atopic group (risk ratios [RRs] of 0.80 [95% CI; 0.65, 0.99] and 0.81[95% CI; 0.68, 0.97]) while increasing percentages were associated with an increased frequency (not disability) in the high atopic group (RR = 1.60; [95% CI; 1.11, 2.29]). In subjects ≤ 45 years of age, immunotherapy was associated with decreased migraine frequency and disability (RRs of 0.48 [95% CI; 0.28, 0.83] and 0.55 [95% CI; 0.35, 0.87]). In those45 years of age, there was no effect of degree of allergic sensitization or immunotherapy on the frequency and disability of migraine headache.Our study suggests that the association of allergy with migraine headaches depends upon age, degree of allergic sensitization, administration of immunotherapy, and the type of headache outcome measure that are studied. Lower "degrees of atopy" are associated with less frequent and disabling migraine headaches in younger subjects while higher degrees were associated with more frequent migraines. The administration of immunotherapy is associated with a decreased prevalence, frequency, and disability of migraine headache in younger subjects.

Kv1.3 channels of T lymphocytes play an important role in several physiological functions like activation or migration, which are accompanied by the redistribution of channels in the cell membrane. Both processes are characterized by F-actin polymerization indicating the involvement of the actin cytoskeleton in the associated channel's redistribution. Several studies reported that Kv1.x channels are linked to or co-localize with various adapter proteins which also possess actin-binding domains: hDlg1 via the PDZ-binding domain and cortactin through either the cortactin- or the SH3-binding site. In this study we investigated the molecular requirements for Kv1.3 channel lateral membrane diffusion.FLAG/EGFP-tagged Kv1.3 wild-type or mutant constructs were expressed in HEK-293 cells. We designed C-terminal truncated (without (delta1) or with (delta2) cortactin binding sequence, and both without SH3; with cortactin and SH3 binding motif (delta3)) and few-amino-acid Kv1.3 mutants (deltaSH3/deltaPDZ: SH3/PDZ domain ruptured). Biophysical properties of each phenotype were evaluated with patch-clamping. Interaction/co-localization between channel and adaptor proteins was studied with co-immunoprecipitation/confocal microscopy. Lateral mobility of Kv1.3 was assessed with FRAP and defined by the channel's mobile fraction (Mf).Parameters of channel gating for mutants were indistinguishable from those of wild-type Kv1.3. Confocal microscopy images and co-immunoprecipitation experiments demonstrated that cortactin and Kv1.3 interact in HEK-293 cells. Furthermore, wild-type, delta3 and deltaPDZ mutants have reduced Mf upon stimulation of F-actin polymerization/stabilization by jasplakinolide (unlike delta1, delta2 and deltaSH3 constructs). When cortactin was knocked down by shRNA, exposure to jasplakinolide induced no decrease in Mf of wild-type Kv1.3 channels. These findings point out that cortactin serves as a bridge between Kv1.3 and the actin meshwork via the channel's SH3-binding domain, and can regulate mobility/immobility of Kv1.3 channels. (NIH 2R01CA095286).