Natural Language Processing – Finding the Missing Link for Oncologic Data, 2022

Oncology like most medical specialties, is undergoing a data revolution at the center of which lie vast and growing amounts of clinical data in unstructured, semi-structured and structed formats. Artificial intelligence approaches are widely employed in research endeavors in an attempt to harness electronic medical records data to advance patient outcomes. The use of clinical oncologic data, although collected on large scale, particularly with the increased implementation of electronic medical records, remains limited due to missing, incorrect or manually entered data in registries and the lack of resource allocation to data curation in real world settings. Natural Language Processing (NLP) may provide an avenue to extract data from electronic medical records and as a result has grown considerably in medicine to be employed for documentation, outcome analysis, phenotyping and clinical trial eligibility. Barriers to NLP persist with inability to aggregate findings across studies due to use of different methods and significant heterogeneity at all levels with important parameters such as patient comorbidities and performance status lacking implementation in AI approaches. The goal of this review is to provide an updated overview of natural language processing (NLP) and the current state of its application in oncology for clinicians and researchers that wish to implement NLP to augment registries and/or advance research projects

Neuropsychological testing and biomarkers in the management of brain metastases

Prognosis for patients with brain metastasis remains poor. Whole brain radiation therapy is the conventional treatment option; it can improve neurological symptoms, prevent and improve tumor associated neurocognitive decline, and prevents death from neurologic causes. In addition to whole brain radiation therapy, stereotactic radiosurgery, neurosurgery and chemotherapy also are used in the management of brain metastases. Radiosensitizers are now currently being investigated as potential treatment options. All of these treatment modalities carry a risk of central nervous system (CNS) toxicity that can lead to neurocognitive impairment in long term survivors. Neuropsychological testing and biomarkers are potential ways of measuring and better understanding CNS toxicity. These tools may help optimize current therapies and develop new treatments for these patients. This article will review the current management of brain metastases, summarize the data on the CNS effects associated with brain metastases and whole brain radiation therapy in these patients, discuss the use of neuropsychological tests as outcome measures in clinical trials evaluating treatments for brain metastases, and give an overview of the potential of biomarker development in brain metastases research

Post-radiation increase in VEGF enhances glioma cell motility in vitro

<p>Abstract</p> <p>Background</p> <p>Glioblastoma multiforme (GBM) is among the most lethal of all human tumors, with frequent local recurrences after radiation therapy (RT). The mechanism accounting for such a recurrence pattern is unclear. It has classically been attributed to local recurrence of treatment-resistant cells. However, accumulating evidence suggests that additional mechanisms exist that involve the migration of tumor or tumor stem cells from other brain regions to tumor bed. VEGFs are well-known mitogens and can be up-regulated after RT. Here, we examine the effect of irradiation-induced VEGF on glioma cell motility.</p> <p>Materials and methods</p> <p>U251 and LN18 cell lines were used to generate irradiated-conditioned medium (IR-CM). At 72 h after irradiation, the supernatants were harvested. VEGF level in IR-CM was quantified by ELISA, and expression levels for VEGF mRNA were detected by RT-PCR. <it>In vitro </it>cancer cell motility was measured in chambers coated with/without Matrigel and IR-CM as a cell motility enhancer and a VEGF antibody as a neutralizer of VEGF bioactivity. Immunoblots were performed to evaluate the activity of cell motility-related kinases. Proliferation of GBM cells after treatment was measured by flow cytometry.</p> <p>Results</p> <p>Irradiation increased the level of VEGF mRNA that was mitigated by pre-RT exposure to Actinomycin D. U251 glioma cell motility (migration and invasion) was enhanced by adding IR-CM to un-irradiated cells (174.9 ± 11.4% and 334.2 ± 46% of control, respectively). When we added VEGF antibody to IR-CM, this enhanced cell motility was negated (110.3 ± 12.0% and 105.7 ± 14.0% of control, respectively). Immunoblot analysis revealed that IR-CM increased phosphorylation of VEGF receptor-2 (VEGFR2) secondary to an increase in VEGF, with a concomitant increase of phosphorylation of the downstream targets (Src and FAK). Increased phosphorylation was mitigated by adding VEGF antibody to IR-CM. There was no difference in the mitotic index of GBM cells treated with and without IR-CM and VEGF.</p> <p>Conclusions</p> <p>These results indicate that cell motility can be enhanced by conditioned medium from irradiated cells <it>in vitro </it>through stimulation of VEGFR2 signaling pathways and suggest that this effect involves the secretion of radiation-induced VEGF, leading to an increase in glioma cell motility.</p

Dietary alterations modulate the microRNA 29/30 and IGF-1/AKT signaling axis in breast Cancer liver metastasis.

Background: Metastatic cancer is incurable and understanding the molecular underpinnings is crucial to improving survival for our patients. The IGF-1/Akt signaling pathway is often impaired in cancer leading to its progression and metastases. Diet modification is known to alter the IGF-1/Akt pathway and affect the expression of microRNA involved in tumor initiation, growth and metastases. Liver metastases are one of the most common type of metastases in breast and colon cancer. In the present study, we looked at the effect of diet modification on the expression of microRNA in normal liver and liver with breast cancer metastases using in vivo model. Methodology: 6-month-old C57BL/6 J mice were put on either an ad libitum (AL) diet, or 40% calorie restricted (CR) diet or were fasted for 24 h (FA) before sacrifice. MicroRNA array analysis, western blot and qRT-PCR were performed using liver tissue to compare the treatment groups. A breast cancer model was also used to study the changes in microRNA expression in liver of a group of BALB/c mice orthotopically injected with 4 T1 cells in the mammary fat pad, put on either an AL or 30% CR diet. Liver and primary tumor tissues were used to perform qRT-PCR to compare the treatment groups. Results: MicroRNA array analysis showed significant changes in miRNA expression in both CR and FA conditions in normal liver. Expression of miR-29 and miR-30 family members was increased in both CR and FA. Western blot analysis of the normal liver tissue showed that CR and FA downregulated the IGF-1/Akt pathway and qRT-PCR showed that the expression of miR-29b, miR-29c, miR-30a and miR-30b were increased with CR and FA. Liver tissue collected from mice in the breast cancer model showed an increase in expression of miR-29b, miR-29c and miR-30b while tumor tissue showed increased expression of miR-29c, miR-30a and miR-30b. Discussion: Members of the miR-29 family are known to target and suppress IGF-1, while members of the miR-30 family are known to target and suppress both IGF-1 and IGF-1R. In the present study, we observe that calorie restriction increased the expression of miR-29 and miR-30 in both the normal liver as well as the liver with breast cancer metastases. These findings suggest that dietary alterations may play a role in the treatment of liver metastasis, which should be evaluated further

Why "Radiation Oncology"

Radiotherapy continues to be a major treatment for solid tumours and is a cornerstone of modern oncology. The term 'radiation oncology' describes the integration of radiation therapy into the complexity of multi-modal therapy. Over the last ten years the crucial role of radiation therapy as part of multi-modality protocols in cancer care has been documented in numerous Phase III trials. Advances in treatment technology as well as the underlying biology of tumour resistance mechanisms will further strengthen the role of radiation oncology. The scientific role of radiation oncology is reflected by the increase in the number of papers related to radiation oncology in resources like Medline. In order to reflect the growing scientific importance of radiation oncology, radiation physics and radiation biology, we have initiated Radiation Oncology as the first open access journal in the field. Open access allows for a rapid and transparent publication process together with an unequalled opportunity to reach the widest reader spectrum possible

3D Multimodal Brain Tumor Segmentation and Grading Scheme based on Machine, Deep, and Transfer Learning Approaches

Glioma is one of the most common tumors of the brain. The detection and grading of glioma at an early stage is very critical for increasing the survival rate of the patients. Computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems are essential and important tools that provide more accurate and systematic results to speed up the decision-making process of clinicians. In this paper, we introduce a method consisting of the variations of the machine, deep, and transfer learning approaches for the effective brain tumor (i.e., glioma) segmentation and grading on the multimodal brain tumor segmentation (BRATS) 2020 dataset. We apply popular and efficient 3D U-Net architecture for the brain tumor segmentation phase. We also utilize 23 different combinations of deep feature sets and machine learning/fine-tuned deep learning CNN models based on Xception, IncResNetv2, and EfficientNet by using 4 different feature sets and 6 learning models for the tumor grading phase. The experimental results demonstrate that the proposed method achieves 99.5% accuracy rate for slice-based tumor grading on BraTS 2020 dataset. Moreover, our method is found to have competitive performance with similar recent works

High throughput evaluation of gamma-H2AX

The DNA double-strand break (DSB) is the primary lethal lesion after therapeutic radiation. Thus, the development of assays to detect and to quantitate these lesions could have broad preclinical and clinical impact. Phosphorylation of histone H2AX to form γ-H2AX is a known marker for irradiation-induced DNA DSBs. However, the first generation assay involves the use of immunofluorescent staining of γ-H2AX foci. This assay is time consuming, operator dependent and is not scalable for high throughput assay development. Thus, we sought to develop a new assay using a high throughput electrochemiluminescent platform from Mesoscale Discovery Systems to quantify γ-H2AX levels. The results show that our assay utilizes significantly less time and labor, has greater intra-assay reproducibility and has a greater dynamic range of γ-H2AX versus irradiation dose

Comparison of T2 and FLAIR imaging for target delineation in high grade gliomas

<p>Abstract</p> <p>Background</p> <p>FLAIR and T2 weighted MRIs are used based on institutional preference to delineate high grade gliomas and surrounding edema for radiation treatment planning. Although these sequences have inherent physical differences there is limited data on the clinical and dosimetric impact of using either or both sequences.</p> <p>Methods</p> <p>40 patients with high grade gliomas consecutively treated between 2002 and 2008 of which 32 had pretreatment MRIs with T1, T2 and FLAIR available for review were selected for this study. These MRIs were fused with the treatment planning CT. Normal structures, clinical tumor volume (CTV) and planning tumor volume (PTV) were then defined on the T2 and FLAIR sequences. A Venn diagram analysis was performed for each pair of tumor volumes as well as a fractional component analysis to assess the contribution of each sequence to the union volume. For each patient the tumor volumes were compared in terms of total volume in cubic centimeters as well as anatomic location using a discordance index. The overlap of the tumor volumes with critical structures was calculated as a measure of predicted toxicity. For patients with MRI documented failures, the tumor volumes obtained using the different sequences were compared with the recurrent gross tumor volume (rGTV).</p> <p>Results</p> <p>The FLAIR CTVs and PTVs were significantly larger than the T2 CTVs and PTVs (p < 0.0001 and p = 0.0001 respectively). Based on the discordance index, the abnormality identified using the different sequences also differed in location. Fractional component analysis showed that the intersection of the tumor volumes as defined on both T2 and FLAIR defined the majority of the union volume contributing 63.6% to the CTV union and 82.1% to the PTV union. T2 alone uniquely identified 12.9% and 5.2% of the CTV and PTV unions respectively while FLAIR alone uniquely identified 25.7% and 12% of the CTV and PTV unions respectively. There was no difference in predicted toxicity to normal structures using T2 or FLAIR. At the time of analysis, 26 failures had occurred of which 19 patients had MRIs documenting the recurrence. The rGTV correlated best with the FLAIR CTV but the percentage overlap was not significantly different from that with T2. There was no statistical difference in the percentage overlap with the rGTV and the PTVs generated using either T2 or FLAIR.</p> <p>Conclusions</p> <p>Although both T2 and FLAIR MRI sequences are used to define high grade glial neoplasm and surrounding edema, our results show that the volumes generated using these techniques are different and not interchangeable. These differences have bearing on the use of intensity modulated radiation therapy (IMRT) and highly conformal treatment as well as on future clinical trials where the bias of using one technique over the other may influence the study outcome.</p

A dosimetric comparison of four treatment planning methods for high grade glioma

<p>Abstract</p> <p>Background</p> <p>High grade gliomas (HGG) are typically treated with a combination of surgery, radiotherapy and chemotherapy. Three dimensional (3D) conformal radiotherapy treatment planning is still the main stay of treatment for these patients. New treatment planning methods suggest better dose distributions and organ sparing but their clinical benefit is unclear. The purpose of the current study was to compare normal tissue sparing and tumor coverage using four different radiotherapy planning methods in patients with high grade glioma.</p> <p>Methods</p> <p>Three dimensional conformal (3D), sequential boost IMRT, integrated boost (IB) IMRT and Tomotherapy (TOMO) treatment plans were generated for 20 high grade glioma patients. T1 and T2 MRI abnormalities were used to define GTV and CTV with 2 and 2.5 cm margins to define PTV1 and PTV2 respectively.</p> <p>Results</p> <p>The mean dose to PTV2 but not to PTV1 was less then 95% of the prescribed dose with IB and IMRT plans. The mean doses to the optic chiasm and the ipsilateral globe were highest with 3D plans and least with IB plans. The mean dose to the contralateral globe was highest with TOMO plans. The mean of the integral dose (ID) to the brain was least with the IB plan and was lower with IMRT compared to 3D plans. The TOMO plans had the least mean D10 to the normal brain but higher mean D50 and D90 compared to IB and IMRT plans. The mean D10 and D50 but not D90 were significantly lower with the IMRT plans compared to the 3D plans.</p> <p>Conclusion</p> <p>No single treatment planning method was found to be superior to all others and a personalized approach is advised for planning and treating high-grade glioma patients with radiotherapy. Integral dose did not reflect accurately the dose volume histogram (DVH) of the normal brain and may not be a good indicator of delayed radiation toxicity.</p