Spatial Gene Expression Changes in the Mouse Heart After Base-Targeted Irradiation

Intercellular pathways of cancer treatment-related cardiotoxicity and their therapeutic implications: the paradigm of radiotherapy

Advances in cancer therapeutics have improved patient survival rates. However, cancer survivors may suffer from adverse events either at the time of therapy or later in life. Cardiovascular diseases (CVD) represent a clinically important, but mechanistically understudied complication, which interfere with the continuation of best-possible care, induce life-threatening risks, and/or lead to long-term morbidity. These concerns are exacerbated by the fact that targeted therapies and immunotherapies are frequently combined with radiotherapy, which induces durable inflammatory and immunogenic responses, thereby providing a fertile ground for the development of CVDs. Stressed and dying irradiated cells produce 'danger' signals including, but not limited to, major histocompatibility complexes, cell-adhesion molecules, proinflammatory cytokines, and damage-associated molecular patterns. These factors activate intercellular signaling pathways which have potentially detrimental effects on the heart tissue homeostasis. Herein, we present the clinical crosstalk between cancer and heart diseases, describe how it is potentiated by cancer therapies, and highlight the multifactorial nature of the underlying mechanisms. We particularly focus on radiotherapy, as a case known to often induce cardiovascular complications even decades after treatment. We provide evidence that the secretome of irradiated tumors entails factors that exert systemic, remote effects on the cardiac tissue, potentially predisposing it to CVDs. We suggest how diverse disciplines can utilize pertinent state-of-the-art methods in feasible experimental workflows, to shed light on the molecular mechanisms of radiotherapy-related cardiotoxicity at the organismal level and untangle the desirable immunogenic properties of cancer therapies from their detrimental effects on heart tissue. Results of such highly collaborative efforts hold promise to be translated to next-generation regimens that maximize tumor control, minimize cardiovascular complications, and support quality of life in cancer survivors.

Computational approaches identify a transcriptomic fingerprint of drug-induced structural cardiotoxicity

Structural cardiotoxicity (SCT) presents a high-impact risk that is poorly tolerated in drug discovery unless significant benefit is anticipated. Therefore, we aimed to improve the mechanistic understanding of SCT. First, we combined machine learning methods with a modified calcium transient assay in human-induced pluripotent stem cell-derived cardiomyocytes to identify nine parameters that could predict SCT. Next, we applied transcriptomic profiling to human cardiac microtissues exposed to structural and non-structural cardiotoxins. Fifty-two genes expressed across the three main cell types in the heart (cardiomyocytes, endothelial cells, and fibroblasts) were prioritised in differential expression and network clustering analyses and could be linked to known mechanisms of SCT. This transcriptomic fingerprint may prove useful for generating strategies to mitigate SCT risk in early drug discovery.

Dose-dependent changes in cardiac function, strain and remodelling in a preclinical model of heart base irradiation

BACKGROUND AND PURPOSE

Radiation induced cardiotoxicity (RICT) is as an important sequela of radiotherapy to the thorax for patients. In this study, we aim to investigate the dose and fractionation response of RICT. We propose global longitudinal strain (GLS) as an early indicator of RICT and investigate myocardial deformation following irradiation.

METHODS

RICT was investigated in female C57BL/6J mice in which the base of the heart was irradiated under image-guidance using a small animal radiation research platform (SARRP). Mice were randomly assigned to a treatment group: single-fraction dose of 16 Gy or 20 Gy, 3 consecutive fractions of 8.66 Gy, or sham irradiation; biological effective doses (BED) used were 101.3 Gy, 153.3 Gy and 101.3 Gy respectively. Longitudinal transthoracic echocardiography (TTE) was performed from baseline up to 50 weeks post-irradiation to detect structural and functional effects.

RESULTS

Irradiation of the heart base leads to BED-dependent changes in systolic and diastolic function 50 weeks post-irradiation. GLS showed significant decreases in a BED-dependent manner for all irradiated animals, as early as 10 weeks after irradiation. Early changes in GLS indicate late changes in cardiac function. BED-independent increases were observed in the left ventricle (LV) mass and volume and myocardial fibrosis.

CONCLUSIONS

Functional features of RICT displayed a BED dependence in this study. GLS showed an early change at 10 weeks post-irradiation. Cardiac remodelling was observed as increases in mass and volume of the LV, further supporting our hypothesis that dose to the base of the heart drives the global heart toxicity.

Characterisation of quantitative imaging biomarkers for inflammatory and fibrotic radiation-induced lung injuries using preclinical radiomics

BACKGROUND AND PURPOSE

Radiomics is a rapidly evolving area of research that uses medical images to develop prognostic and predictive imaging biomarkers. In this study, we aimed to identify radiomics features correlated with longitudinal biomarkers in preclinical models of acute inflammatory and late fibrotic phenotypes following irradiation.

MATERIALS AND METHODS

Female C3H/HeN and C57BL6 mice were irradiated with 20 Gy targeting the upper lobe of the right lung under cone-beam computed tomography (CBCT) image-guidance. Blood samples and lung tissue were collected at baseline, weeks 1, 10 & 30 to assess changes in serum cytokines and histological biomarkers. The right lung was segmented on longitudinal CBCT scans using ITK-SNAP. Unfiltered and filtered (wavelet) radiomics features (n = 842) were extracted using PyRadiomics. Longitudinal changes were assessed by delta analysis and principal component analysis (PCA) was used to remove redundancy and identify clustering. Prediction of acute (week 1) and late responses (weeks 20 & 30) was performed through deep learning using the Random Forest Classifier (RFC) model.

RESULTS

Radiomics features were identified that correlated with inflammatory and fibrotic phenotypes. Predictive features for fibrosis were detected from PCA at 10 weeks yet overt tissue density was not detectable until 30 weeks. RFC prediction models trained on 5 features were created for inflammation (AUC 0.88), early-detection of fibrosis (AUC 0.79) and established fibrosis (AUC 0.96).

CONCLUSIONS

This study demonstrates the application of deep learning radiomics to establish predictive models of acute and late lung injury. This approach supports the wider application of radiomics as a non-invasive tool for detection of radiation-induced lung complications.

Voxel-based analysis: Roadmap for clinical translation

Voxel-based analysis (VBA) allows the full, 3-dimensional, dose distribution to be considered in radiotherapy outcome analysis. This provides new insights into anatomical variability of pathophysiology and radiosensitivity by removing the need for a priori definition of organs assumed to drive the dose response associated with patient outcomes. This approach may offer powerful biological insights demonstrating the heterogeneity of the radiobiology across tissues and potential associations of the radiotherapy dose with further factors. As this methodological approach becomes established, consideration needs to be given to translating VBA results to clinical implementation for patient benefit. Here, we present a comprehensive roadmap for VBA clinical translation. Technical validation needs to demonstrate robustness to methodology, where clinical validation must show generalisability to external datasets and link to a plausible pathophysiological hypothesis. Finally, clinical utility requires demonstration of potential benefit for patients in order for successful translation to be feasible. For each step on the roadmap, key considerations are discussed and recommendations provided for best practice.

Integration of transcriptomics, metabolomics, and lipidomics reveals the mechanisms of doxorubicin-induced inflammatory responses and myocardial dysfunction in mice

Doxorubicin (DOX) is an anthracycline antineoplastic agent that has limited clinical utility due to its dose-dependent cardiotoxicity. Although the exact mechanism remains unknown, inflammatory responses have been implicated in DOX-induced cardiotoxicity (DIC). In this study, we analyzed the transcriptomic, metabolomic as well as lipidomic changes in the DOX-treated mice to explore the underlying mechanisms of DIC. We found that continuous intraperitoneal DOX injections (3 mg/kg/d) for a period of five days significantly induced cardiac dysfunction and cardiac injury in male C57BL/6 J mice (8 weeks old). This corresponded to a significant increase in the myocardial levels of IL-4, IL-6, IL-10, IL-17 and IL-12p70. Furthermore, inflammation-related genes such as Ptgs2, Il1b, Cxcl5, Cxcl1, Cxcl2, Mmp3, Ccl2, Ccl12, Nfkbia, Fos, Mapk11 and Tnf were differentially expressed in the DOX-treated group, and enriched in the IL-17 and TNF signaling pathways. Besides, amino acids, peptides, imidazoles, toluenes, hybrid peptides, fatty acids and lipids such as Hex1Cer, Cer, SM, PG and ACCa were significantly associated with the expression pattern of inflammation-related genes. In conclusion, the integration of transcriptomic, metabolomic and lipidomic data identified potential new targets and biomarkers of DIC.

Regulation of the Volume-Regulated Anion Channel Pore-Forming Subunit LRRC8A in the Intrahippocampal Kainic Acid Model of Mesial Temporal Lobe Epilepsy

Volume-regulated anion channels (VRACs) are a group of ubiquitously expressed outwardly-rectifying anion channels that sense increases in cell volume and act to return cells to baseline volume through an efflux of anions and organic osmolytes, including glutamate. Because cell swelling, increased extracellular glutamate levels, and reduction of the brain extracellular space (ECS) all occur during seizure generation, we set out to determine whether VRACs are dysregulated throughout mesial temporal lobe epilepsy (MTLE), the most common form of adult epilepsy. To accomplish this, we employed the IHKA experimental model of MTLE, and probed for the expression of LRRC8A, the essential pore-forming VRAC subunit, at acute, early-, mid-, and late-epileptogenic time points (1-, 7-, 14-, and 30-days post-IHKA, respectively). Western blot analysis revealed the upregulation of total dorsal hippocampal LRRC8A 14-days post-IHKA in both the ipsilateral and contralateral hippocampus. Immunohistochemical analyses showed an increased LRRC8A signal 7-days post-IHKA in both the ipsilateral and contralateral hippocampus, along with layer-specific changes 1-, 7-, and 30-days post-IHKA bilaterally. LRRC8A upregulation 1 day post-IHKA was observed primarily in astrocytes; however, some upregulation was also observed in neurons. Glutamate-GABA/glutamine cycle enzymes glutamic acid decarboxylase, glutaminase, and glutamine synthetase were also dysregulated at the 7-day timepoint post status epilepticus. The timepoint-dependent upregulation of total hippocampal LRRC8A and the possible subsequent increased efflux of glutamate in the epileptic hippocampus suggest that the dysregulation of astrocytic VRAC may play an important role in the development of epilepsy.