Towards a Subtype-Specific and Personalized Approach of Soft Tissue Sarcomas: filling in the gaps of the mosaic

Soft tissue sarcomas form a heterogenous group of rare tumors which are often treated as one entity. The different chapters of this thesis show that a subtype-specific and personalized approach is needed to improve the outcome of these patients

Assessing a digital technology-supported community child health programme in India using the Social Return on Investment framework.

An estimated 5.0 million children aged under 5 years died in 2020, with 82% of these deaths occurring in sub-Saharan Africa and southern Asia. Over one-third of Mumbai's population has limited access to healthcare, and child health outcomes are particularly grave among the urban poor. We describe the implementation of a digital technology-based child health programme in Mumbai and evaluate its holistic impact. Using an artificial intelligence (AI)-powered mobile health platform, we developed a programme for community-based management of child health. Leveraging an existing workforce, community health workers (CHW), the programme was designed to strengthen triage and referral, improve access to healthcare in the community, and reduce dependence on hospitals. A Social Return on Investment (SROI) framework is used to evaluate holistic impact. The programme increased the proportion of illness episodes treated in the community from 4% to 76%, subsequently reducing hospitalisations and out-of-pocket expenditure on private healthcare providers. For the total investment of Indian Rupee (INR) 2,632,271, the social return was INR 34,435,827, delivering an SROI ratio of 13. The annual cost of the programme per child was INR 625. Upskilling an existing workforce such as CHWs, with the help of AI-driven decision- support tools, has the potential to extend capacity for critical health services into community settings. This study provides a blueprint for evaluating the holistic impact of health technologies using evidence-based tools like SROI. These findings have applicability across income settings, offering clear rationale for the promotion of technology-supported interventions that strengthen healthcare delivery

MicroRNA expression and DNA methylation profiles do not distinguish between primary and recurrent well-differentiated liposarcoma

Approximately one-third of the patients with well-differentiated liposarcoma (WDLPS) will develop a local recurrence. Not much is known about the molecular relationship between the primary tumor and the recurrent tumor, which is important to reveal potential drivers of recurrence. Here we investigated the biology of recurrent WDLPS by comparing paired primary and recurrent WDLPS using microRNA profiling and genome-wide DNA methylation analyses. In total, 27 paired primary and recurrent WDLPS formalin-fixed and paraffin-embedded tumor samples were collected. MicroRNA expression profiles were determined using TaqMan® Low Density Array (TLDA) cards. Genome-wide DNA methylation and differentially methylated regions (DMRs) were assessed by methylated DNA sequencing (MeD-seq). A supervised cluster analysis based on differentially expressed microRNAs between paired primary and recurrent WDLPS did not reveal a clear cluster pattern separating the primary from the recurrent tumors. The clustering was also not based on tumor localization, time to recurrence, age or status of the resection margins. Changes in DNA methylation between primary and recurrent tumors were extremely variable, and no consistent DNA methylation changes were found. As a result, a supervised clustering analysis based on DMRs between primary and recurrent tumors did not show a distinct cluster pattern based on any of the features. Subgroup analysis for tumors localized in the extremity or the retroperitoneum also did not yield a clear distinction between primary and recurrent WDLPS samples. In conclusion, microRNA expression profiles and DNA methylation profiles do not distinguish between primary and recurrent WDLPS and no putative common drivers could be identified

Incidence of unplanned excisions of soft tissue sarcomas in the Netherlands:A population-based study

Introduction: Timely recognition of soft tissue sarcomas (STS) remains challenging, potentially leading to unplanned excisions (also known as 'whoops procedures'). This population-based study charted the occurrence of unplanned excisions and identified associated patient, tumour, and treatment-related characteristics. Furthermore, it presents an overview of the outcomes and clinical management following an unplanned excision. Methods: From the Netherlands Cancer Registry (NCR) database, information was obtained on 2187 adult patients diagnosed with STS in 2016-2019 who underwent surgery. Tumours located in the mediastinum, heart or retroperitoneum were excluded, as well as incidental findings. Differences between patients with planned and unplanned excisions were assessed with chi-square tests and a multivariable logistic regression model. Results: Overall, unplanned excisions comprise 18.2% of all first operations for STS, with a quarter of them occurring outside a hospital. Within hospitals, the unplanned excision rate was 14.4%. Unplanned excisions were more often performed on younger patients, and tumours unsuspected of being STS prior to surgery were generally smaller ( Discussion: Potential improvement in preventing unplanned excisions may be achieved by better compliance to preoperative imaging and referral guidelines, and stimulating continuous awareness of STS among general surgeons, general practitioners and private practices. (C) 2021 Elsevier Ltd, BASO similar to The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved

Ras-association domain family 1C protein promotes breast cancer cell migration and attenuates apoptosis

<p>Abstract</p> <p>Background</p> <p>The Ras association domain family 1 (RASSF1) gene is a Ras effector encoding two major mRNA forms, RASSF1A and RASSF1C, derived by alternative promoter selection and alternative mRNA splicing. RASSF1A is a tumor suppressor gene. However, very little is known about the function of RASSF1C both in normal and transformed cells.</p> <p>Methods</p> <p>Gene silencing and over-expression techniques were used to modulate RASSF1C expression in human breast cancer cells. Affymetrix-microarray analysis was performed using T47D cells over-expressing RASSF1C to identify RASSF1C target genes. RT-PCR and western blot techniques were used to validate target gene expression. Cell invasion and apoptosis assays were also performed.</p> <p>Results</p> <p>In this article, we report the effects of altering RASSF1C expression in human breast cancer cells. We found that silencing RASSF1C mRNA in breast cancer cell lines (MDA-MB231 and T47D) caused a small but significant decrease in cell proliferation. Conversely, inducible over-expression of RASSF1C in breast cancer cells (MDA-MB231 and T47D) resulted in a small increase in cell proliferation. We also report on the identification of novel RASSF1C target genes. RASSF1C down-regulates several pro-apoptotic and tumor suppressor genes and up-regulates several growth promoting genes in breast cancer cells. We further show that down-regulation of caspase 3 via overexpression of RASSF1C reduces breast cancer cells' sensitivity to the apoptosis inducing agent, etoposide. Furthermore, we found that RASSF1C over-expression enhances T47D cell invasion/migration <it>in vitro</it>.</p> <p>Conclusion</p> <p>Together, our findings suggest that RASSF1C, unlike RASSF1A, is not a tumor suppressor, but instead may play a role in stimulating metastasis and survival in breast cancer cells.</p

Radiomics approach to distinguish between well differentiated liposarcomas and lipomas on MRI

Background: Well differentiated liposarcoma (WDLPS) can be difficult to distinguish from lipoma. Currently, this distinction is made by testing for MDM2 amplification, which requires a biopsy. The aim of this study was to develop a noninvasive method to predict MDM2 amplification status using radiomics features derived from MRI. Methods: Patients with an MDM2-negative lipoma or MDM2-positive WDLPS and a pretreatment T1-weighted MRI scan who were referred to Erasmus MC between 2009 and 2018 were included. When available, other MRI sequences were included in the radiomics analysis. Features describing intensity, shape and texture were extracted from the tumour region. Classification was performed using various machine learning approaches. Evaluation was performed through a 100 times random-split cross-validation. The performance of the models wa

Reproducible radiomics through automated machine learning validated on twelve clinical applications

Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, findingthe optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-anderror process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows perapplication. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms foreach component. To optimize the workflow per application, we employ automated machine learning using a random search andensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1)liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77);5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis(0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer’s disease (0.87); and 12) head and neck cancer (0.84). Weshow that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performssimilar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automaticallyoptimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications.To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework,and the code to reproduce this study

Misfolded SOD1 Associated with Motor Neuron Mitochondria Alters Mitochondrial Shape and Distribution Prior to Clinical Onset

Mutations in superoxide dismutase (SOD1) are causative for inherited amyotrophic lateral sclerosis. A proportion of SOD1 mutant protein is misfolded onto the cytoplasmic face of mitochondria in one or more spinal cord cell types. By construction of mice in which mitochondrially targeted enhanced green fluorescent protein is selectively expressed in motor neurons, we demonstrate that axonal mitochondria of motor neurons are primary in vivo targets for misfolded SOD1. Mutant SOD1 alters axonal mitochondrial morphology and distribution, with dismutase active SOD1 causing mitochondrial clustering at the proximal side of Schmidt-Lanterman incisures within motor axons and dismutase inactive SOD1 producing aberrantly elongated axonal mitochondria beginning pre-symptomatically and increasing in severity as disease progresses. Somal mitochondria are altered by mutant SOD1, with loss of the characteristic cylindrical, networked morphology and its replacement by a less elongated, more spherical shape. These data indicate that mutant SOD1 binding to mitochondria disrupts normal mitochondrial distribution and size homeostasis as early pathogenic features of SOD1 mutant-mediated ALS

Relationships between psychosocial outcomes in adolescents who are obese and their parents during a multi-disciplinary family-based healthy lifestyle intervention: One-year follow-up of a waitlist controlled trial (Curtin University's Activity, Food and Attitudes Program)

Background: Limited studies have investigated relationships in psychosocial outcomes between adolescents who are obese and their parents and how psychosocial outcomes change during participation in a physical activity and healthy eating intervention. This study examined both adolescent and parent psychosocial outcomes while participating in a one - year multi-disciplinary family-based intervention: Curtin University’s Activity, Food, and Attitudes Program (CAFAP). Methods: Following a waitlist control period, the intervention was delivered to adolescent (n = 56, ages 11–16) and parent participants over 8 weeks, with one-year maintenance follow-up. Adolescent depression and quality of life, family functioning, and parent depression, anxiety, and stress were assessed at six time points: baseline and prior to intervention (e.g., waitlist control period), immediately following intervention, and at 3, 6, and 12 months post-intervention. Relationships between adolescent and parent psychosocial outcomes were assessed using Spearman correlations and changes in both adolescent and parent outcomes were assessed using linear mixed models. Changes in adolescent psychosocial outcomes were compared to changes in behavioural (physical activity and healthy eating) and physical (weight) outcomes using independent samples t-tests.Results: The majority of psychosocial outcomes were significantly correlated between adolescents and parents across the one-year follow-up. Adolescent depression, psychosocial and physical quality of life outcomes significantly improved before or following intervention and were maintained at 6-months or one-year follow-up. Parent symptoms of depression, anxiety, and stress were reduced during waitlist and primarily remained improved. Changes in adolescent psychosocial outcomes were shown to be partially associated with behavioural changes and independent of physical changes. Conclusions: Adolescents in CAFAP improved psychosocial and physical quality of life and reversed the typical trajectory of depressive symptoms in adolescents who are obese during a one-year maintenance period. CAFAP was also effective at maintaining reductions in parent symptoms of depression, anxiety, and stress demonstrated during the waitlist period. Trial Registration: The trial was registered with the Australian and New Zealand Clinical Trials Registry (No. 12611001187932)

The EGFRvIII transcriptome in glioblastoma, a meta-omics analysis.

BACKGROUND: EGFR is among the genes most frequently altered in glioblastoma, with exons 2-7 deletions (EGFRvIII) being amongst its most common genomic mutations. There are conflicting reports about its prognostic role and it remains unclear whether and how it differs in signalling compared with wildtype EGFR. METHODS: To better understand the oncogenic role of EGFRvIII, we leveraged four large datasets into one large glioblastoma transcriptome dataset (n=741) alongside 81 whole-genome samples from two datasets. RESULTS: The EGFRvIII/EGFR expression ratios differ strongly between tumours and ranges from 1% to 95%. Interestingly, the slope of relative EGFRvIII expression is near-linear, which argues against a more positive selection pressure than EGFR wildtype. An absence of selection pressure is also suggested by the similar survival between EGFRvIII positive and negative glioblastoma patients. EGFRvIII levels are inversely correlated with pan-EGFR (all wildtype and mutant variants) expression, which indicates that EGFRvIII has a higher potency in downstream pathway activation. EGFRvIII-positive glioblastomas have a lower CDK4 or MDM2 amplification incidence than EGFRvIII-negative (p=0.007), which may point towards crosstalk between these pathways. EGFRvIII-expressing tumours have an upregulation of 'classical' subtype genes compared to those with EGFR-amplification only (p=3.873e-6). Genomic breakpoints of the EGFRvIII deletions have a preference towards the 3' end of the large intron-1. These preferred breakpoints preserve a cryptic exon resulting in a novel EGFRvIII variant and preserve an intronic enhancer. CONCLUSIONS: These data provide deeper insights into the complex EGFRvIII biology and provide new insights for targeting EGFRvIII mutated tumours