ABSTRACT
The incidence of endometrial cancer continues to increase worldwide with growing life expectancy and rates of obesity. While endometrial cancer is primarily a surgical disease managed with hysterectomy, a small proportion of patients are deemed to be poor surgical candidates due to their co-morbidities. These medically inoperable patients should be considered for curative treatment with definitive radiation therapy, and brachytherapy is an integral component of their care. Referral to a high-volume center early on in the care of potentially inoperable patients is crucial to optimize their management. These patients should be evaluated by a high-risk surgical and anesthesia team to confirm their medical inoperability. For inoperable patients, use of image-guided brachytherapy is encouraged. Brachytherapy applicator selection is determined based on a patient's anatomy, uterine size, and extent of tumor. Advances in anatomic and functional imaging including multiparametric magnetic resonance imaging (MRI) have improved clinical staging of these patients and have also allowed for the delivery of three-dimensional image-guided brachytherapy with improved accuracy. With recent consensus guidelines to guide local computed tomography and/or MRI volume-based delineation of targets and organs-at-risk, local outcomes have improved and treatments are delivered with less acute and late morbidity. Ongoing trials are looking at novel systemic agents, such as immunotherapy, to induce a systemic anti-tumor immune response and improve outcomes in these patients.
Subject(s)
Brachytherapy , Endometrial Neoplasms , Brachytherapy/methods , Endometrial Neoplasms/pathology , Female , Humans , Imaging, Three-Dimensional/methods , Magnetic Resonance Imaging/methods , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methodsABSTRACT
OBJECTIVE. The purpose of this study was to test the hypothesis that convolutional neural networks can be used to predict which patients with pure atypical ductal hyperplasia (ADH) may be safely monitored rather than undergo surgery. MATERIALS AND METHODS. A total of 298 unique images from 149 patients were used for our convolutional neural network algorithm. A total of 134 images from 67 patients with ADH that had been diagnosed by stereotactic-guided biopsy of calcifications but had not been upgraded to ductal carcinoma in situ or invasive cancer at the time of surgical excision. A total of 164 images from 82 patients with mammographic calcifications indicated that ductal carcinoma in situ was the final diagnosis. Two standard mammographic magnification views of the calcifications (a craniocaudal view and a mediolateral or lateromedial view) were used for analysis. Calcifications were segmented using an open-source software platform and images were resized to fit a bounding box of 128 × 128 pixels. A topology with 15 hidden layers was used to implement the convolutional neural network. The network architecture contained five residual layers and dropout of 0.25 after each convolution. Patients were randomly separated into a training-and-validation set (80% of patients) and a test set (20% of patients). Code was implemented using open-source software on a workstation with an open-source operating system and a graphics card. RESULTS. The AUC value was 0.86 (95% CI, ± 0.03) for the test set. Aggregate sensitivity and specificity were 84.6% (95% CI, ± 4.0%) and 88.2% (95% CI, ± 3.0%), respectively. Diagnostic accuracy was 86.7% (95% CI, ± 2.9). CONCLUSION. It is feasible to apply convolutional neural networks to distinguish pure atypical ductal hyperplasia from ductal carcinoma in situ with the use of mammographic images. A larger dataset will likely result in further improvement of our prediction model.
ABSTRACT
We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemotherapy (NAC) response using a breast MRI tumor dataset prior to initiation of chemotherapy. An institutional review board-approved retrospective review of our database from January 2009 to June 2016 identified 141 locally advanced breast cancer patients who (1) underwent breast MRI prior to the initiation of NAC, (2) successfully completed adriamycin/taxane-based NAC, and (3) underwent surgical resection with available final surgical pathology data. Patients were classified into three groups based on their NAC response confirmed on final surgical pathology: complete (group 1), partial (group 2), and no response/progression (group 3). A total of 3107 volumetric slices of 141 tumors were evaluated. Breast tumor was identified on first T1 postcontrast dynamic images and underwent 3D segmentation. CNN consisted of ten convolutional layers, four max-pooling layers, and dropout of 50% after a fully connected layer. Dropout, augmentation, and L2 regularization were implemented to prevent overfitting of data. Non-linear functions were modeled by a rectified linear unit (ReLU). Batch normalization was used between the convolutional and ReLU layers to limit drift of layer activations during training. A three-class neoadjuvant prediction model was evaluated (group 1, group 2, or group 3). The CNN achieved an overall accuracy of 88% in three-class prediction of neoadjuvant treatment response. Three-class prediction discriminating one group from the other two was analyzed. Group 1 had a specificity of 95.1% ± 3.1%, sensitivity of 73.9% ± 4.5%, and accuracy of 87.7% ± 0.6%. Group 2 (partial response) had a specificity of 91.6% ± 1.3%, sensitivity of 82.4% ± 2.7%, and accuracy of 87.7% ± 0.6%. Group 3 (no response/progression) had a specificity of 93.4% ± 2.9%, sensitivity of 76.8% ± 5.7%, and accuracy of 87.8% ± 0.6%. It is feasible for current deep CNN architectures to be trained to predict NAC treatment response using a breast MRI dataset obtained prior to initiation of chemotherapy. Larger dataset will likely improve our prediction model.
Subject(s)
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/radiotherapy , Deep Learning , Image Interpretation, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Algorithms , Breast/diagnostic imaging , Datasets as Topic , Female , Humans , Neural Networks, Computer , Predictive Value of Tests , Retrospective Studies , Sensitivity and Specificity , Treatment OutcomeABSTRACT
OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete response (rCR) is a poor predictor of pathologic complete response (pCR) of the axilla. We developed a convolutional neural network (CNN) algorithm to better predict post-NAC axillary response using a breast MRI dataset. METHODS: An institutional review board-approved retrospective study from January 2009 to June 2016 identified 127 breast cancer patients who: (1) underwent breast MRI before the initiation of NAC; (2) successfully completed Adriamycin/Taxane-based NAC; and (3) underwent surgery, including sentinel lymph node evaluation/axillary lymph node dissection with final surgical pathology data. Patients were classified into pathologic complete response (pCR) of the axilla group and non-pCR group based on surgical pathology. Breast MRI performed before NAC was used. Tumor was identified on first T1 postcontrast images underwent 3D segmentation. A total of 2811 volumetric slices of 127 tumors were evaluated. CNN consisted of 10 convolutional layers, 4 max-pooling layers. Dropout, augmentation and L2 regularization were implemented to prevent overfitting of data. RESULTS: On final surgical pathology, 38.6% (49/127) of the patients achieved pCR of the axilla (group 1), and 61.4% (78/127) of the patients did not with residual metastasis detected (group 2). For predicting axillary pCR, our CNN algorithm achieved an overall accuracy of 83% (95% confidence interval [CI] ± 5) with sensitivity of 93% (95% CI ± 6) and specificity of 77% (95% CI ± 4). Area under the ROC curve (0.93, 95% CI ± 0.04). CONCLUSIONS: It is feasible to use CNN architecture to predict post NAC axillary pCR. Larger data set will likely improve our prediction model.
Subject(s)
Algorithms , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Breast Neoplasms/pathology , Carcinoma, Ductal, Breast/pathology , Carcinoma, Lobular/pathology , Neoadjuvant Therapy , Neural Networks, Computer , Adult , Aged , Aged, 80 and over , Axilla , Biomarkers, Tumor/metabolism , Breast Neoplasms/drug therapy , Breast Neoplasms/metabolism , Carcinoma, Ductal, Breast/drug therapy , Carcinoma, Ductal, Breast/metabolism , Carcinoma, Lobular/drug therapy , Carcinoma, Lobular/metabolism , Chemotherapy, Adjuvant , Female , Follow-Up Studies , Humans , Magnetic Resonance Imaging , Middle Aged , Neoplasm Invasiveness , Prognosis , ROC Curve , Receptor, ErbB-2/metabolism , Receptors, Estrogen/metabolism , Retrospective Studies , Survival Rate , Young AdultABSTRACT
BACKGROUND: This study evaluated the relative accuracy of mammography, ultrasound, and magnetic resonance imaging (MRI) in predicting the tumor size of early stage breast tumors in preoperative selection of patients for intraoperative radiotherapy (IORT). METHODS: We identified 156 patients with clinical T1/T2, N0 breast cancer who underwent IORT. Clinical, pathologic, and radiation data were collected. The preoperative tumor size obtained by imaging was compared with tumor pathological size. RESULTS: The median patient age was 66. The mean tumor size at excision was 1.05 cm (0.1-3.0 cm). Out of the 156 patients, 98 had a reported, nonzero tumor size by mammography, 131 by ultrasound, and 76 by MRI. The mean difference between imaging and the tumor size was +0.062 ± 0.54 cm for mammography, -0.11 ± 0.43 cm for ultrasound, and +0.33 ± 0.55 cm for MRI, with positive values indicating an overestimate of the tumor size. MRI produced more overestimates of tumor size of at least 0.5 cm than mammography or ultrasound in a paired analysis of patients who received both modalities. CONCLUSIONS: Accuracy of imaging modalities in determining tumor size can influence patients' eligibility for IORT. Mammography and ultrasound showed acceptable accuracy in predicting size. MRI overestimated tumor size and may inappropriately exclude patients from IORT. We would discourage ruling out candidates for IORT on the basis of large size by MRI alone.
Subject(s)
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/therapy , Adult , Aged , Aged, 80 and over , Breast Neoplasms/radiotherapy , Breast Neoplasms/surgery , Combined Modality Therapy , Female , Humans , Intraoperative Care/methods , Magnetic Resonance Imaging/methods , Mammography/methods , Middle Aged , Neoplasm Staging , Radiotherapy Planning, Computer-Assisted , Retrospective Studies , Ultrasonography, Mammary/methodsABSTRACT
While the global down-regulation of microRNAs (miRNAs) is a common feature of human tumors, its genetic basis is largely undefined. To explore this question, we analyzed the consequences of conditional Dicer1 mutation (Dicer1 "floxed" or Dicer1(fl)) on several mouse models of cancer. Here we show Dicer1 functions as a haploinsufficient tumor suppressor gene. Deletion of a single copy of Dicer1 in tumors from Dicer1(fl/+) animals led to reduced survival compared with controls. These tumors exhibited impaired miRNA processing but failed to lose the wild-type Dicer1 allele. Moreover, tumors from Dicer1(fl/fl) animals always maintained one functional Dicer1 allele. Consistent with selection against full loss of Dicer1 expression, enforced Dicer1 deletion caused inhibition of tumorigenesis. Analysis of human cancer genome copy number data reveals frequent deletion of DICER1. Importantly, however, the gene has not been reported to undergo homozygous deletion, suggesting that DICER1 is haploinsufficient in human cancer. These findings suggest Dicer1 may be an important haploinsufficient tumor suppressor gene and, furthermore, that other factors controlling miRNA biogenesis may also function in this manner.
Subject(s)
Lung Neoplasms/genetics , Lung Neoplasms/physiopathology , Ribonuclease III , Sarcoma/genetics , Sarcoma/physiopathology , Tumor Suppressor Proteins , Animals , Cell Line, Tumor , Disease Models, Animal , Gene Deletion , Humans , Lung Neoplasms/mortality , Mice , Mice, Inbred C57BL , MicroRNAs/metabolism , Mutation/genetics , Ribonuclease III/genetics , Ribonuclease III/metabolism , Sarcoma/mortality , Survival Analysis , Tumor Suppressor Proteins/genetics , Tumor Suppressor Proteins/metabolismABSTRACT
BACKGROUND: Expression vector engineering technology is one of the most convenient and timely method for cell line development to meet the rising demand of novel production cell line with high productivity. Destabilization of dihydrofolate reductase (dhfr) selection marker by addition of AU-rich elements and murine ornithine decarboxylase PEST region was previously shown to improve the specific productivities of recombinant human interferon gamma in CHO-DG44 cells. In this study, we evaluated novel combinations of engineered motifs for further selection marker attenuation to improve recombinant human alpha-1-antitrypsin (rhA1AT) production. Motifs tested include tandem PEST elements to promote protein degradation, internal ribosome entry site (IRES) mutations to impede translation initiation, and codon-deoptimized dhfr selection marker to reduce translation efficiency. RESULTS: After a 2-step methotrexate (MTX) amplification to 50 nM that took less than 3 months, the expression vector with IRES point mutation and dhfr-PEST gave a maximum titer of 1.05 g/l with the top producer cell pool. Further MTX amplification to 300 nM MTX gave a maximum titer of 1.15 g/l. Relative transcript copy numbers and dhfr protein expression in the cell pools were also analysed to demonstrate that the transcription of rhA1AT and dhfr genes were correlated due to the IRES linkage, and that the strategies of further attenuating dhfr protein expression with the use of a mutated IRES and tandem PEST, but not codon deoptimization, were effective in reducing dhfr protein levels in suspension serum free culture. CONCLUSIONS: Novel combinations of engineered motifs for further selection marker attenuation were studied to result in the highest reported recombinant protein titer to our knowledge in shake flask batch culture of stable mammalian cell pools at 1.15 g/l, highlighting applicability of expression vector optimization in generating high producing stable cells essential for recombinant protein therapeutics production. Our results also suggest that codon usage of the selection marker should be considered for applications that may involve gene amplification and serum free suspension culture, since the overall codon usage and thus the general expression and regulation of host cell proteins may be affected in the surviving cells.
Subject(s)
Internal Ribosome Entry Sites , Protein Engineering/methods , Tetrahydrofolate Dehydrogenase/metabolism , alpha 1-Antitrypsin/genetics , alpha 1-Antitrypsin/metabolism , Animals , Biomarkers/metabolism , CHO Cells , Cricetulus , Gene Amplification , Genetic Vectors/genetics , Genetic Vectors/metabolism , Humans , Methotrexate/metabolism , Mice , Mutation , Ornithine Decarboxylase/genetics , Recombinant Proteins/genetics , Recombinant Proteins/metabolism , Tetrahydrofolate Dehydrogenase/geneticsSubject(s)
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/radiotherapy , Magnetic Resonance Imaging/methods , Patient Selection , Practice Guidelines as Topic , Adult , Aged , Breast Neoplasms/pathology , Breast Neoplasms/surgery , Female , Humans , Middle Aged , Preoperative Care , Retrospective StudiesABSTRACT
There is growing awareness of the importance of sexual health in the quality of life of cancer patients and survivors. Brachytherapy, a vital component for the curative treatment of cervical cancer, leads to both direct and indirect sequelae that result in vaginal and sexual morbidity. The emergence of 3D image-guided adaptive brachytherapy has led to a better understanding of dose-and-effect relationships for critical organs-at-risk and there are new recommendations for vaginal dose reporting in the ongoing EMBRACE II study. An understanding of the vagina as an organ-at-risk and its dose-and-effect relationships can help brachytherapists limit dose to the vagina and improve sexual morbidity. Brachytherapists play a critical role in the primary and secondary prevention of vaginal and sexual sequelae resulting from treatment. Through close surveillance and recognition of common symptoms, brachytherapists can intervene with effective strategies to prevent and treat vaginal and sexual symptoms. This review summarizes the current literature on dosimetric factors that may predict for vaginal morbidity. It will focus on quantitative and qualitative reports of brachytherapy-related vaginal toxicity and sexual dysfunction. Lastly, it will review the available evidence supporting clinical interventions to mitigate the development and progression of vaginal and sexual sequelae to improve functional quality post-treatment.
Subject(s)
Brachytherapy , Uterine Cervical Neoplasms , Female , Humans , Uterine Cervical Neoplasms/radiotherapy , Brachytherapy/methods , Quality of Life , Vagina , Organs at RiskABSTRACT
Adaptive radiation therapy is a feedback process by which imaging information acquired over the course of treatment, such as changes in patient anatomy, can be used to reoptimize the treatment plan, with the end goal of improving target coverage and reducing treatment toxicity. This review describes different types of adaptive radiation therapy and their clinical implementation with a focus on CT-guided online adaptive radiation therapy. Depending on local anatomic changes and clinical context, different anatomic sites and/or disease stages and presentations benefit from different adaptation strategies. Online adaptive radiation therapy, where images acquired in-room before each fraction are used to adjust the treatment plan while the patient remains on the treatment table, has emerged to address unpredictable anatomic changes between treatment fractions. Online treatment adaptation places unique pressures on the radiation therapy workflow, requiring high-quality daily imaging and rapid recontouring, replanning, plan review, and quality assurance. Generating a new plan with every fraction is resource intensive and time sensitive, emphasizing the need for workflow efficiency and clinical resource allocation. Cone-beam CT is widely used for image-guided radiation therapy, so implementing cone-beam CT-guided online adaptive radiation therapy can be easily integrated into the radiation therapy workflow and potentially allow for rapid imaging and replanning. The major challenge of this approach is the reduced image quality due to poor resolution, scatter, and artifacts. Keywords: Adaptive Radiation Therapy, Cone-Beam CT, Organs at Risk, Oncology © RSNA, 2023.
Subject(s)
Radiotherapy Planning, Computer-Assisted , Radiotherapy, Image-Guided , Humans , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy Dosage , Radiotherapy, Image-Guided/methods , Cone-Beam Computed Tomography , Organs at RiskABSTRACT
PURPOSE: Definitive radiation therapy (RT) for locally advanced node-positive cervical cancer confers significant toxicity to pelvic organs including the small bowel. Gross nodal disease exhibits significant shrinkage during RT, and yet conventional RT does not account for this change. We evaluated the reduction in absorbed bowel dose using various adaptive RT schedules. METHODS AND MATERIALS: We obtained 130 evaluable scans (computed tomography simulation and 25 cone beam computed tomography scans per patient) of 5 patients who had received definitive external beam RT for lymph node positive cervical cancer daily over 5 weeks. Using a single universal volumetric modulated arc therapy plan with predefined optimization priorities, we created adapted RT plans in 4 schedules: Daily, Weekly, Twice, and NoAdapt (mimicking conventional nonadapted RT). The in silico (computer modeled) patients were treated to 45 Gy to primary cervical disease with a simultaneous integrated boost to 55 Gy to involved lymph nodes. We evaluated dose metrics including D2cc, D15cc, and V45 to determine the impact of adapted RT schedules on bowel sparing. Statistical tests included the Student t test, analysis of variance, and the Spearman rank correlation. RESULTS: The quantity of reduced bowel dose was significantly associated with the chosen planning schedule in all evaluated metrics and was proportional to the frequency of adaptive RT with significant moderate-to-strong monotonicity. Both D2cc and D15cc were reduced an average of 2.7 Gy using daily replanning compared with a nonadapted approach. A minimally adapted strategy of only 2 replans also confers a significant dosimetric benefit over a nonadapted approach. Reduced standard deviations of D2cc and V45 bowel doses over the treatment courses were significantly associated with the choice of planning schedule with strong monotonicity. CONCLUSIONS: All adaptive RT schedules evaluated confer significant dosimetric advantages in bowel sparing over a conventional nonadapted technique, with greater sparing seen with more frequent replanning schedules. These findings warrant future trials of adaptive RT for pelvic malignancies.
Subject(s)
Radiotherapy, Conformal , Radiotherapy, Intensity-Modulated , Uterine Cervical Neoplasms , Female , Humans , Uterine Cervical Neoplasms/radiotherapy , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Conformal/methods , Radiotherapy, Intensity-Modulated/methods , Organs at RiskABSTRACT
Purpose/Objective: We present our single-institution experience in the management of invasive breast cancer with targeted intraoperative radiotherapy (TARGIT-IORT), focusing on patient suitability for IORT determined by the American Society for Radiation Oncology (ASTRO) Accelerated Partial Breast Irradiation (APBI) consensus guidelines. Materials/Methods: We identified 237 patients treated for biopsy-proven early-stage invasive breast cancer using low energy x-ray TARGIT-IORT at the time of lumpectomy between September 2013 and April 2020 who were prospectively enrolled in an institutional review board (IRB) approved database. We retrospectively reviewed preoperative and postoperative clinicopathologic factors to determine each patient's ASTRO APBI suitability (suitable, cautionary or unsuitable) according to the 2017 consensus guidelines (CG). Change in suitability group was determined based on final pathology. Kaplan-Meier methods were used to estimate the survival probability and recurrence probability across time. Results: 237 patients were included in this analysis, based on preoperative clinicopathologic characteristics, 191 (80.6%) patients were suitable, 46 (19.4%) were cautionary and none were deemed unsuitable. Suitability classification changed in 95 (40%) patients based on final pathology from lumpectomy. Increasing preoperative lesion size or a body mass index (BMI) ≥ 30 kg/m2 were significant predictors for suitability group change. Forty-one (17.3%) patients received additional adjuvant whole breast radiotherapy after TARGIT-IORT. At a median follow up of 38.2 months (range 0.4 - 74.5), five (2.1%) patients had ipsilateral breast tumor recurrences (IBTR), including two (0.8%) true local recurrences defined as a recurrence in the same quadrant as the initial lumpectomy bed with the same histology as the initial tumor. IBTR occurred in 1/103 (0.09%) patient in the post-op suitable group, 4/98 (4.08%) patients in the post-op cautionary group, and no patients in the post-op unsuitable group. At 3-years, the overall survival rate was 98.4% and the local recurrence free survival rate was 97.1%. Conclusion: There is a low rate of IBTR after TARGIT-IORT when used in appropriately selected patients. Change in suitability classification pre to postoperatively is common, highlighting a need for further investigation to optimize preoperative patient risk stratification in this setting. Patients who become cautionary or unsuitable based on final pathology should be considered for additional adjuvant therapy.
ABSTRACT
BACKGROUND: Pathologic response at the time of surgery after neoadjuvant therapy for HER2 positive early breast cancer impacts both prognosis and subsequent adjuvant therapy. Comprehensive descriptions of the tumor microenvironment (TME) in patients with HER2 positive early breast cancer is not well described. We utilized standard stromal pathologist-assessed tumor infiltrating lymphocyte (TIL) quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. METHODS: We utilized standard stromal pathologist-assessed TIL quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in 28 patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. RESULTS: Pathologist-assessed stromal TILs were significantly associated with pathologic complete response (pCR). By quantitative multiplex immunofluorescence, univariate analysis revealed significant increases in CD3+, CD3+CD8-FOXP3-, CD8+ and FOXP3+ T-cell densities as well as increased immune cell aggregates in pCR patients. In subsets of paired pre/post-treatment samples, we observed significant changes in gene expression signatures in non-pCR patients and significant decreases in CD8+ densities after treatment in pCR patients. No RNA based pathway signature was associated with pCR. CONCLUSION: TME characterization HER2 positive breast cancer patients revealed several stromal T-cell densities and immune cell aggregates associated with pCR. These results demonstrate the feasibility of these novel methods in TME evaluation and contribute to ongoing investigations of the TME in HER2+ early breast cancer to identify robust biomarkers to best identify patients eligible for systemic de-escalation strategies.
Subject(s)
Breast Neoplasms , Neoadjuvant Therapy , Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Breast Neoplasms/drug therapy , Breast Neoplasms/genetics , Breast Neoplasms/pathology , Female , Forkhead Transcription Factors/metabolism , Forkhead Transcription Factors/therapeutic use , Hormones/metabolism , Humans , Lymphocytes, Tumor-Infiltrating , Neoadjuvant Therapy/methods , Prognosis , Receptor, ErbB-2/metabolism , Tumor MicroenvironmentABSTRACT
Reactions of dicarbon molecules (C(2)) with C(4)H(6) isomers such as 1,3-butadiene represent a potential, but hitherto unnoticed, route to synthesize the first aromatic C(6) ring in hydrocarbon flames and in the interstellar medium where concentrations of dicarbon transient species are significant. Here, crossed molecular beams experiments of dicarbon molecules in their X(1)Sigma(g)(+) electronic ground state and in the first electronically excited a(3)Pi(u) state have been conducted with 1,3-butadiene and two partially deuterated counterparts (1,1,4,4-D4-1,3-butadiene and 2,3-D2-1,3-butadiene) at two collision energies of 12.7 and 33.7 kJ mol(-1). Combining these scattering experiments with electronic structure and RRKM calculations on the singlet and triplet C(6)H(6) surfaces, our investigation reveals that the aromatic phenyl radical is formed predominantly on the triplet surface via indirect scattering dynamics through a long-lived reaction intermediate. Initiated by a barrierless addition of triplet dicarbon to one of the terminal carbon atoms of 1,3-butadiene, the collision complex undergoes trans-cis isomerization followed by ring closure and hydrogen migration prior to hydrogen atom elimination, ultimately forming the phenyl radical. The latter step emits the hydrogen atom almost perpendicularly to the rotational plane of the decomposing intermediate and almost parallel to the total angular momentum vector. On the singlet surface, smaller contributions of phenyl radical could not be excluded; experiments with partially deuterated 1,3-butadiene indicate the formation of the thermodynamically less stable acyclic H(2)CCHCCCCH(2) isomer. This study presents the very first experimental evidence, contemplated by theoretical studies, that under single collision conditions an aromatic hydrocarbon molecule can be formed in a bimolecular gas-phase reaction via reaction of two acyclic molecules involving cyclization processes at collision energies highly relevant to combustion flames.
ABSTRACT
Background: During early stages, patients with neurodegenerative diseases (NDG) often present with depressive symptoms. However, because depression is a heterogeneous disorder, more precise delineation of the specific depressive symptom profiles that arise early in distinct NDG syndromes is necessary to enhance patient diagnosis and care. Methods and Findings: Five-hundred and sixty four participants self-reported their depressive symptoms using the Geriatric Depression Scale (GDS), including 111 healthy older control subjects (NC) and 453 patients diagnosed with one of six NDGs who were at the mild stage of disease (CDR® Dementia Staging Instrument ≤ 1) [186 Alzheimer's disease (AD), 76 behavioral variant frontotemporal dementia (bvFTD), 52 semantic variant primary progressive aphasia (svPPA), 46 non-fluent variant PPA (nfvPPA), 49 progressive supranuclear palsy syndrome (PSPS), 44 corticobasal syndrome (CBS)]. The GDS was divided into subscales based on a previously published factor analysis, representing five symptoms (dysphoria, hopelessness, withdrawal, worry, and cognitive concerns). Mixed models were created to examine differences in depression subscale by group, and logistic regression analyses were performed to determine if patterns of depressive symptoms could predict a patient's NDG syndrome. PSPS patients presented with a hopeless, dysphoric, and withdrawn pattern, while patients with CBS presented with a similar but less severe pattern. Worry was a key symptom in the profile of patients with svPPA, while ADs only had abnormally elevated cognitive concerns. Depressive profile accurately predicted NDG diagnosis at a rate of between 70 and 84% accuracy. Conclusions: These results suggest that attention to specific depressive symptom profile can improve diagnostic sensitivity and can be used to provide more individualized patient care.
ABSTRACT
PURPOSE: Intraoperative radiation therapy (IORT) as a form of accelerated partial breast irradiation (APBI) is controversial given the limited evidence to support its efficacy. However, it remains an attractive option for low-risk patients with ductal carcinoma in situ (DCIS), who derive a small absolute benefit in local control with standard whole breast irradiation (WBI). We examine how the American Society for Therapeutic Radiation Oncology (ASTRO) APBI consensus guidelines (CG) may be applied to the preoperative selection of patients with DCIS for IORT and determine treatment outcomes by CG group. METHODS AND MATERIALS: We identified patients with biopsy-proven pure DCIS enrolled in an institutional prospective registry IORT database using the Zeiss Intrabeam® device between September 2013 and February 2017. Based on available preoperative clinicopathologic information, patients were deemed suitable, cautionary, or unsuitable for IORT according to the ASTRO CG. Change in CG group based on final pathologic diagnosis was determined, and additional therapy was recommended for unsuitable patients. Outcome in terms of ipsilateral breast tumor recurrence was determined. RESULTS: A total of 61 DCIS lesions in 60 patients were treated with IORT. Preoperatively, 21 patients (35%) were suitable and 36 (59%) were cautionary. Four (6%) were unsuitable because of lesion size but declined WBI. Final pathologic diagnosis changed the CG grouping of 10 patients (16%) because of either occult high-grade disease in 2 (3%) or close/positive margins in 8 (13%). Ultimately 12 patients total were considered unsuitable, of whom 8 (66%) accepted additional WBI after IORT. At a median follow-up of 2.2 years, ipsilateral breast tumor recurrence was identified among 2 suitable, 1 cautionary, and no unsuitable patients. CONCLUSION: Further investigation is necessary to refine selection of patients with DCIS who may be optimally treated with IORT alone. High acceptance of additional therapy among unsuitable patients resulted in excellent outcomes. The use of biomarkers in addition to traditional clinical and pathologic factors may help to better select patients for IORT.
ABSTRACT
Mammalian host cell lines are the preferred expression systems for the manufacture of complex therapeutics and recombinant proteins. However, the most utilized mammalian host systems, namely Chinese hamster ovary (CHO), Sp2/0 and NS0 mouse myeloma cells, can produce glycoproteins with non-human glycans that may potentially illicit immunogenic responses. Hence, we developed a fully human expression system based on HEK293 cells for the stable and high titer production of recombinant proteins by first knocking out GLUL (encoding glutamine synthetase) using CRISPR-Cas9 system. Expression vectors using human GLUL as selection marker were then generated, with recombinant human erythropoietin (EPO) as our model protein. Selection was performed using methionine sulfoximine (MSX) to select for high EPO expression cells. EPO production of up to 92700 U/mL of EPO as analyzed by ELISA or 696 mg/L by densitometry was demonstrated in a 2 L stirred-tank fed batch bioreactor. Mass spectrometry analysis revealed that N-glycosylation of the produced EPO was similar to endogenous human proteins and non-human glycan epitopes were not detected. Collectively, our results highlight the use of a human cellular expression system for the high titer and xenogeneic-free production of EPO and possibly other complex recombinant proteins.
Subject(s)
Batch Cell Culture Techniques/methods , Erythropoietin/genetics , Erythropoietin/metabolism , Glutamate-Ammonia Ligase/genetics , Protein Engineering/methods , CRISPR-Cas Systems , Gene Expression , Gene Knockout Techniques , Genetic Vectors/genetics , Glycosylation , HEK293 Cells , Humans , Models, Biological , Recombinant Proteins/metabolismABSTRACT
BACKGROUND: Experiments using whole transcriptome microarrays produce massive amounts of data. To gain a comprehensive understanding of this gene expression data it needs to be integrated with other available information such as gene function and metabolic pathways. Bioinformatics tools are essential to handle, organize and interpret the results. To date, no database provides whole transcriptome analysis capabilities integrated with terms describing biological functions for soybean (Glycine max (L) Merr.). To this end we have developed SoyXpress, a relational database with a suite of web interfaces to allow users to easily retrieve data and results of the microarray experiment with cross-referenced annotations of expressed sequence tags (EST) and hyperlinks to external public databases. This environment makes it possible to explore differences in gene expression, if any, between for instance transgenic and non-transgenic soybean cultivars and to interpret the results based on gene functional annotations to determine any changes that could potentially alter biological processes. RESULTS: SoyXpress is a database designed for exploring the soybean transcriptome. Currently SoyXpress houses 380,095 soybean Expressed Sequence Tags (EST), linked with metabolic pathways, Gene Ontology terms, SwissProt identifiers and Affymetrix gene expression data. Array data is presently available from an experiment profiling global gene expression of three conventional and two genetically engineered soybean cultivars. The microarray data is linked with the sequence data, for maximum knowledge extraction. SoyXpress is implemented in MySQL and uses a Perl CGI interface. CONCLUSION: SoyXpress is designed for the purpose of exploring potential transcriptome differences in different plant genotypes, including genetically modified crops. Soybean EST sequences, microarray and pathway data as well as searchable and browsable gene ontology are integrated and presented. SoyXpress is publicly accessible at http://soyxpress.agrenv.mcgill.ca.
Subject(s)
Databases, Genetic , Gene Expression Profiling , Genome, Plant , Glycine max/genetics , Computational Biology , Database Management Systems , Expressed Sequence Tags , Oligonucleotide Array Sequence AnalysisABSTRACT
BACKGROUND: In this study we aimed to review the outcomes of nipple-sparing mastectomy (NSM) in the setting of expanded criteria: previous breast surgery/irradiation, neoadjuvant chemotherapy (NAC), post-NSM irradiation, and to assess conversion to acceptable criteria after NAC. PATIENTS AND METHODS: In this single-institution institutional review board-approved retrospective review, we identified patients who underwent NSM after previous breast intervention or NAC from January 2010 to February 2017. Clinicopathologic features, previous breast surgeries, response rate, complications, and recurrences were recorded. RESULTS: Sixty-three patients underwent 106 NSMs. Among 63 patients, 39 (61.9%) received NAC, 30 (47.6%) previous lumpectomy, 4 (6.3%) with cosmetic implants, 4 (6.3%) with mastopexy, 5 (7.9%) with previous radiation therapy, and 21 (33%) underwent post-NSM radiation therapy. Transient epidermolysis occurred in 24 patients (38.1%), with 16 patients (66.6%) having complete flap recovery and nipple loss in 8 patients (12.6%). All 10 patients with central disease on pre-NAC imaging converted to acceptable criteria, with 9 having successful NSM. At mean 67.2-month follow-up, 56 patients (88.9%) were disease-free, 5 (7.9%) experienced a systemic recurrence, and 2 (3.2%) a local recurrence. CONCLUSION: NSM is oncologically acceptable in this patient cohort. Patients with large central tumors who undergo NAC should be reconsidered after completion of chemotherapy because many might convert to successful nipple-areolar preservation.
Subject(s)
Breast Neoplasms/therapy , Mastectomy, Subcutaneous/standards , Neoplasm Recurrence, Local/epidemiology , Nipples/surgery , Organ Sparing Treatments/standards , Adult , Aged , Esthetics , Female , Follow-Up Studies , Humans , Mastectomy, Subcutaneous/methods , Middle Aged , Neoadjuvant Therapy/methods , Neoplasm Recurrence, Local/prevention & control , Organ Sparing Treatments/methods , Patient Selection , Prognosis , Radiotherapy, Adjuvant , Retrospective Studies , Treatment Outcome , Young AdultABSTRACT
PURPOSE: To implement Velocity-based image fusion and adaptive deformable registration to enable treatment planning for preclinical murine models of fractionated stereotactic radiosurgery (fSRS) using the small animal radiation research platform (SARRP). METHODS AND MATERIALS: C57BL6 mice underwent 3 unique cone beam computed tomography (CBCT) scans: 2 in the prone position and a third supine. A single T1-weighted post-contrast magnetic resonance imaging (MRI) series of a murine metastatic brain tumor model was selected for MRI-to-CBCT registration and gross tumor volume (GTV) identification. Two arms were compared: Arm 1, where we performed 3 individual MRI-to-CBCT fusions using rigid registration, contouring GTVs on each, and Arm 2, where the authors performed MRI-to-CBCT fusion and contoured GTV on the first CBCT followed by Velocity-based adaptive registration. The first CBCT and associated GTV were exported from MuriPlan (Xstrahl Life Sciences) into Velocity (Varian Medical Systems, Inc, Palo Alto, CA). In Arm 1, the second and third CBCTs were exported similarly along with associated GTVs (Arm 1), while in Arm 2, the first (prone) CBCT was fused separately to the second (prone) and third (supine) CBCTs, performing deformable registrations on initial CBCTs and applying resulting matrices to the contoured GTV. Resulting GTVs were compared between Arms 1 and 2. RESULTS: Comparing GTV overlays using repeated MRI fusion and GTV delineation (Arm 1) versus those of Velocity-based CBCT and GTV adaptive fusion (Arm 2), mean deviations ± standard deviation in the axial, sagittal, and coronal planes were 0.46 ± 0.16, 0.46 ± 0.22, and 0.37 ± 0.22 mm for prone-to-prone and 0.52 ± 0.27, 0.52 ± 0.36, and 0.68 ± 0.31 mm for prone-to-supine adaptive fusions, respectively. CONCLUSIONS: Velocity-based adaptive fusion of CBCTs and contoured volumes allows for efficient fSRS planning using a single MRI-to-CBCT fusion. This technique is immediately implementable on current SARRP systems, facilitating advanced preclinical treatment paradigms using existing clinical treatment planning software.