Sarcoma treatment in the era of molecular medicine

open42siThe authors thank the European EuSARC initiative, which addresses the clinical challenges posed by sarcomas and aims at accelerating the translation of new molecular findings into clinical practice through the organization of annual conferences that foster interdisciplinary and international collaboration in the field of sarcomas (www.eusarc.com).Sarcomas are heterogeneous and clinically challenging soft tissue and bone cancers. Although constituting only 1% of all human malignancies, sarcomas represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. More than 100 histological subtypes have been characterized to date, and many more are being discovered due to molecular profiling. Owing to their mostly aggressive biological behavior, relative rarity, and occurrence at virtually every anatomical site, many sarcoma subtypes are in particular difficult-to-treat categories. Current multimodal treatment concepts combine surgery, polychemotherapy (with/without local hyperthermia), irradiation, immunotherapy, and/or targeted therapeutics. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the latest advances in the molecular biology of sarcomas and their effects on clinical oncology; it is meant for a broad readership ranging from novices to experts in the field of sarcoma.openGrunewald T.G.P.; Alonso M.; Avnet S.; Banito A.; Burdach S.; Cidre-Aranaz F.; Di Pompo G.; Distel M.; Dorado-Garcia H.; Garcia-Castro J.; Gonzalez-Gonzalez L.; Grigoriadis A.E.; Kasan M.; Koelsche C.; Krumbholz M.; Lecanda F.; Lemma S.; Longo D.L.; Madrigal-Esquivel C.; Morales-Molina A.; Musa J.; Ohmura S.; Ory B.; Pereira-Silva M.; Perut F.; Rodriguez R.; Seeling C.; Al Shaaili N.; Shaabani S.; Shiavone K.; Sinha S.; Tomazou E.M.; Trautmann M.; Vela M.; Versleijen-Jonkers Y.M.H.; Visgauss J.; Zalacain M.; Schober S.J.; Lissat A.; English W.R.; Baldini N.; Heymann D.Grunewald T.G.P.; Alonso M.; Avnet S.; Banito A.; Burdach S.; Cidre-Aranaz F.; Di Pompo G.; Distel M.; Dorado-Garcia H.; Garcia-Castro J.; Gonzalez-Gonzalez L.; Grigoriadis A.E.; Kasan M.; Koelsche C.; Krumbholz M.; Lecanda F.; Lemma S.; Longo D.L.; Madrigal-Esquivel C.; Morales-Molina A.; Musa J.; Ohmura S.; Ory B.; Pereira-Silva M.; Perut F.; Rodriguez R.; Seeling C.; Al Shaaili N.; Shaabani S.; Shiavone K.; Sinha S.; Tomazou E.M.; Trautmann M.; Vela M.; Versleijen-Jonkers Y.M.H.; Visgauss J.; Zalacain M.; Schober S.J.; Lissat A.; English W.R.; Baldini N.; Heymann D

Sarcoma treatment in the era of molecular medicine

Sarcomas are heterogeneous and clinically challenging soft tissue and bone cancers. Although constituting only 1% of all human malignancies, sarcomas represent the second most common type of solid tumors in children and adolescents and comprise an important group of secondary malignancies. More than 100 histological subtypes have been characterized to date, and many more are being discovered due to molecular profiling. Owing to their mostly aggressive biological behavior, relative rarity, and occurrence at virtually every anatomical site, many sarcoma subtypes are in particular difficult-to-treat categories. Current multimodal treatment concepts combine surgery, polychemotherapy (with/without local hyperthermia), irradiation, immunotherapy, and/or targeted therapeutics. Recent scientific advancements have enabled a more precise molecular characterization of sarcoma subtypes and revealed novel therapeutic targets and prognostic/predictive biomarkers. This review aims at providing a comprehensive overview of the latest advances in the molecular biology of sarcomas and their effects on clinical oncology; it is meant for a broad readership ranging from novices to experts in the field of sarcoma.Peer reviewe

INTEGRATIVE ANALYSIS OF OMICS DATA IN ADULT GLIOMA AND OTHER TCGA CANCERS TO GUIDE PRECISION MEDICINE

Transcriptomic profiling and gene expression signatures have been widely applied as effective approaches for enhancing the molecular classification, diagnosis, prognosis or prediction of therapeutic response towards personalized therapy for cancer patients. Thanks to modern genome-wide profiling technology, scientists are able to build engines leveraging massive genomic variations and integrating with clinical data to identify “at risk” individuals for the sake of prevention, diagnosis and therapeutic interventions. In my graduate work for my Ph.D. thesis, I have investigated genomic sequencing data mining to comprehensively characterise molecular classifications and aberrant genomic events associated with clinical prognosis and treatment response, through applying high-dimensional omics genomic data to promote the understanding of gene signatures and somatic molecular alterations contributing to cancer progression and clinical outcomes. Following this motivation, my dissertation has been focused on the following three topics in translational genomics. 1) Characterization of transcriptomic plasticity and its association with the tumor microenvironment in glioblastoma (GBM). I have integrated transcriptomic, genomic, protein and clinical data to increase the accuracy of GBM classification, and identify the association between the GBM mesenchymal subtype and reduced tumorpurity, accompanied with increased presence of tumor-associated microglia. Then I have tackled the sole source of microglial as intrinsic tumor bulk but not their corresponding neurosphere cells through both transcriptional and protein level analysis using a panel of sphere-forming glioma cultures and their parent GBM samples.FurthermoreI have demonstrated my hypothesis through longitudinal analysis of paired primary and recurrent GBM samples that the phenotypic alterations of GBM subtypes are not due to intrinsic proneural-to-mesenchymal transition in tumor cells, rather it is intertwined with increased level of microglia upon disease recurrence. Collectively I have elucidated the critical role of tumor microenvironment (Microglia and macrophages from central nervous system) contributing to the intra-tumor heterogeneity and accurate classification of GBM patients based on transcriptomic profiling, which will not only significantly impact on clinical perspective but also pave the way for preclinical cancer research. 2) Identification of prognostic gene signatures that stratify adult diffuse glioma patientsharboring1p/19q co-deletions. I have compared multiple statistical methods and derived a gene signature significantly associated with survival by applying a machine learning algorithm. Then I have identified inflammatory response and acetylation activity that associated with malignant progression of 1p/19q co-deleted glioma. In addition, I showed this signature translates to other types of adult diffuse glioma, suggesting its universality in the pathobiology of other subset gliomas. My efforts on integrative data analysis of this highly curated data set usingoptimizedstatistical models will reflect the pending update to WHO classification system oftumorsin the central nervous system (CNS). 3) Comprehensive characterization of somatic fusion transcripts in Pan-Cancers. I have identified a panel of novel fusion transcripts across all of TCGA cancer types through transcriptomic profiling. Then I have predicted fusion proteins with kinase activity and hub function of pathway network based on the annotation of genetically mobile domains and functional domain architectures. I have evaluated a panel of in -frame gene fusions as potential driver mutations based on network fusion centrality hypothesis. I have also characterised the emerging complexity of genetic architecture in fusion transcripts through integrating genomic structure and somatic variants and delineating the distinct genomic patterns of fusion events across different cancer types. Overall my exploration of the pathogenetic impact and clinical relevance of candidate gene fusions have provided fundamental insights into the management of a subset of cancer patients by predicting the oncogenic signalling and specific drug targets encoded by these fusion genes. Taken together, the translational genomic research I have conducted during my Ph.D. study will shed new light on precision medicine and contribute to the cancer research community. The novel classification concept, gene signature and fusion transcripts I have identified will address several hotly debated issues in translational genomics, such as complex interactions between tumor bulks and their adjacent microenvironments, prognostic markers for clinical diagnostics and personalized therapy, distinct patterns of genomic structure alterations and oncogenic events in different cancer types, therefore facilitating our understanding of genomic alterations and moving us towards the development of precision medicine

Integrative analysis of the colorectal cancer proteome : potential clinical impact

Peer reviewedPostprin

Genetic and molecular mechanisms of sarcomas

Sarcomas are heterogeneous malignant mesenchymal tumors with diverse biological features and unique clinical characteristics, the genetic alterations of sarcomas are highly variable. With the development of sequencing technologies, efficient and practical approaches to detect gene expressions and gene variants contribute to the prediction of patient prognosis and the choice of treatment modalities. Given the rarity of sarcomas, the comprehensive transcriptomic or genomic profiles are still lacking for many subtypes. In the present thesis, by applying sequencing technology in sarcoma cohorts, combined with bioinformatics data analysis and molecular biology experiments, we have revealed new biological mechanisms dictating sarcoma behavior and provided insights for clinical applications. In Paper I, we characterized the gene signatures related to poor prognosis, first-line treatment failure, and chemotherapy resistance in Ewing sarcoma (ES). High expression of IGF2 was associated with shorter overall survival in ES patients and promoted cell proliferation, radiation resistance, and apoptosis inhibition in vitro. The transcriptome analysis of clinical samples and cell lines uncovered an IGF-dependent signature and potentially related to stem cell-like signatures in ES. Paper II continued to highlight the transcriptome signatures in ES. Here, we identified prognosis-related RNA-binding proteins (RBPs) and constructed an RBP-based prognostic risk model that showed stable predictive power for evaluating overall survival in clinical samples. Within the model, NSUN7 is considered an independent prognostic favorable prognostic marker, which was also validated by immunohistochemistry. In Paper III, we discovered that TERT promoter mutations were present in 45% of patients in a cohort of 190 patients with conventional chondrosarcoma (CHS). The mutation was significantly associated with recurrence, distant metastasis, and high tumor grade. The heterogeneity of primary tumors and the altered mutational status between asynchronous metastatic lesions revealed that CHS is a multiclonal disease that progresses through branching evolution. In Paper IV, we identified three clusters with distinct transcriptomic and genomic patterns in synovial sarcoma (SS), of which SS cluster I (SSC-I) was characterized by hyperproliferation, immune cell silencing, and poor prognosis; SSC-II was characterized by high vascularity and stromal component with the better clinical outcome; SSC-III was characterized by epithelial components with genomic complexity and checkpoint-mediated immune suppression. Collectively, the present thesis illustrated the pathogenic mechanisms of ES, CHS, and SS through the analysis of transcriptomic and genomic data, identified prognostic biomarkers, and at the clinical application-level provided strong evidence for patient stratification, risk prediction, and personalized treatment assessment

ITCC-P4: Molecular characterization and multi-omics analysis of pediatric patient tumor and Patient-Derived Xenograft (PDX) models for preclinical model selection

Cancer persists as one of the prevailing causes of death in children and adolescents aged 0 to 19 years. There remains to be an unmet need for identification of therapeutic biomarkers and better treatment interventions for these patients. Advancements in state-of-the-art molecular profiling techniques have resulted in better understanding of pediatric cancers and their driver events. It has become apparent that pediatric malignancies are significantly more heterogeneous than previously thought as evidenced by the number of novel entities and subtypes that have been identified with distinct molecular and clinical characteristics. For most of these newly recognized entities there are currently extremely limited treatment options available. Unfortunately, there is also a lack of compiled and consistently analysed molecular data available, along with limited data of characterization and documentation of patient-derived models and/or genetic mouse models from high-risk pediatric tumors. Both my studies fall under the “Innovative Therapies for Children with Cancer Pediatric Preclinical Proof-of-concept Platform” (ITCC-P4) consortium which is an international collaboration between different European academic institutes, several partnering pharmaceutical companies and three contract research organizations. The two studies aim to shed light on identification of potential promising treatment options that specifically match the patient’s specific molecular tumour characteristics and the patient’s genetic data. Genetic information at the molecular level from pediatric tumors in relapsed patients has contributed to advancing our understanding of disease progression and treatment resistance. The first study overall aims to establish a sustainable platform of >400 molecularly well- characterized PDX models of high-risk pediatric cancers, including the analysis of their original tumors and matching controls. This will enable the selection of PDX models for in vivo testing of novel mechanism-of-action based treatments. Hence, facilitating the prioritization of pediatric drug development and clinical stratification of patients across entities. In a first batch, 251 models were fully characterized, including 180 brain and 71 non- brain PDX models, representing 112 primary models, 93 relapse, 42 metastasis and 4 progressions under treatment models. Using low-coverage whole-genome and deep whole exome sequencing, complemented with total RNA sequencing and methylation analysis, the aim was to define genetic features in the ITCC-P4 PDX cohort and assess the molecular fidelity of PDX models compared to the original tumor. Based on DNA methylation profiling 43 different tumor subgroups within 18 cancer entities were included. Mutational landscape analysis identified key somatic and germline oncogenic drivers where Ependymoma PDX models displayed the C11orf95-RELA fusion event, YAP1, C11orf95 and RELA structural variants. Medulloblastoma models were driven by MYCN, TP53, GLI2, SUFU and PTEN. High-grade glioma samples showed TP53, ATRX, MYCN and PIK3CA somatic SNVs, along with focal deletions in CDKN2A in chromosome 9. Neuroblastoma models were enriched for ALK SNVs and/or MYCN focal amplification, ATRX SNVs and CDKN2A/B deletions. Sarcoma models displayed characteristic alterations with PAX3-FOXO1 fusions detected in embryonal rhabdomyosarcoma, along with TP53, CDKN2A, NRAS SNVs, NCOA1 gains, NF1 and CDK4 SVs. Ewing sarcoma PDX models displayed the defining EWSR1-FLI1 gene fusion in most cases, along with two rarer cases of EWSR1-ERG and EWSR1-FEV observed in the cohort. Osteosarcomas were defined by highly unstable genomes with large chromosomal alterations, TP53 and RB1 tumor suppressor genes were frequently altered and ATRX loss and MYC gains were observed. Additional sarcomas such as clear cell sarcoma of the kidney showed CDKN2A loss, MYC gain, NF1 loss, TP53 mutations, while Synovial sarcoma models were driven by SSX gene fusions and alterations. Large chromosomal aberrations (deletions, duplications) detected in the PDX models were concurrent with molecular alterations frequently observed in each tumor type –isochromosome 17 was detected in five medulloblastoma models, while deletion of chromosome arm 1p or gain of parts of 17q in neuroblastomas which correlate with tumor progression. Tumor mutational burden across entities and copy number analysis was performed to identify allele-specific copy number events in tumor-normal pairs. Clonal evolution of somatic variants was not only found in certain PDX-tumor pairs but also between disease states. Across the 16 serial model cases, discordance in targetable SNV, SV and CNV, alterations were observed in later disease progressed states compared to the primary models. The multi-omics approach in this study provides insight into the mutational landscape and patterns of the PDX models thus providing an overview of molecular mechanisms facilitating the identification and prioritization of oncogenic drivers and potential biomarkers for optimal treatment. The second study was a Target Actionability Review on replication stress. Detrimental long-term side effects due to chemotherapy drastically affect the lives of patients under treatment, hence there is an urgent need to identify novel target driven therapies. Decades of published data provide evidence for targeting replication stress therapeutically. Hence, in this study, we evaluated specific targets within the replication stress response (RSR) pathway. A comprehensive, well-structured, and critically evaluated overview of literature related to replication stress across 16 pediatric solid malignancies was generated. The methodology focuses on the systemic extraction and structured evaluation of replication stress as a target. This aims to align targeted anti- cancer therapeutic interventions with specific cancer subtypes based on clinical studies. ATR, ATM, PARP, WEEI were observed to represent the most promising targets either using single agents or in combination with chemotherapy or radiotherapy. Evidence on CHK1 and DNA-PK although limited, showed potential to further investigate these promising targets over broader tumor types. The collective data and results from both studies, the “ITCC-P4: Molecular characterization and multi-omics analysis of Patient-Derived Xenograft (PDX) models from high-risk pediatric cancer” and the “Target actionability review on replication stress”, can be explored further on the interactively designed R2 platform, once users create an account to gain access to the cohort data. (https://r2-itcc-p4.amc.nl/)

Targeting immune and desmoplastic tumor microenvironment to sensitize gynecological cancer cells to therapy

Cancer is a pervasive global threat that manifests with diverse clinical attributes and notable mortality rates, particularly attributable to its metastatic potential in solid cancers. These tumours encompass various types including epithelial cancers like high-grade serous ovarian cancer (HGSC) and mesenchymal cancers like uterine sarcomas (USs). Despite the differing origins of USs and HGSCs, the pivotal concept of the transition between epithelial and mesenchymal states remains remarkably plastic, occurring frequently in these cancers. This plasticity holds immense significance in understanding tumour invasiveness and metastasis. The TME emerges as a crucial influencer as exerting its impact on cancer progression, epithelial-mesenchymal transition (EMT), metastasis, and even chemoresistance. The TME comprises various elements, with the extracellular matrix (ECM) containing structural proteins like collagens, standing out as a key constituent. Moreover, immune cells within the TME, such as lymphocytes and macrophages, actively engage in interactions with both the ECM and cancer cells shaping local responses to kill the cancer cells or support their growth. Understanding the intricate tumour-TME interactions become imperative in formulating effective strategies aimed at modulating the immune response and halting cancer progression. Therefore, a nuanced comprehension of these complexities is crucial in developing strategies to combat cancer effectively. This thesis focuses on identifying TME factors, including ECM components and immune cell interactions in gynaecological cancers for improved precision medicine including immunotherapies and other novel treatments. In Paper I, Uterine sarcomas present distinct immune signatures with prognostic value, independent of tumour type. FOXP3+ cell density and CD8+/FOXP3+ ratio (CFR) correlated with favourable survival in endometrial stromal sarcomas (ESS) and undifferentiated uterine sarcomas (USS). The CFR also highlighted the correlation between CFR high and upregulation of ECM organization pathways. In Paper II conversely, uterine leiomyosarcomas (uLMS) showed distinct behaviours, with lower collagen density and upregulated ECM remodelling enzymes correlating with aggressiveness. MMP-14 and yes-associated protein 1 (YAP) were required for uLMS growth and invasion. In Paper Ⅲ, shifting to HGSC, matrisome, a group of proteins encoded by genes for core ECM proteins 4 (collagens, proteoglycans, and ECM glycoproteins) and ECM-associated proteins (proteins structurally resembling ECM proteins, ECM remodelling enzymes, and secreted factors) in the ECM, showed changes in expression depending on the type of tumour host tissues and after chemotherapy. Collagen VI, among scrutinized proteins, exhibited elevated expression linked to shortened survival in ovarian cancer patients. Mechanistically, collagen VI promoted platinum resistance via the stiffness-dependent β1 integrin-pMLC and YAP/TAZ pathways in HGSC cell lines In summary, this integrated exploration of uterine sarcomas and ovarian cancer provides a comprehensive understating of their TME. The study elucidates diverse immune and molecular features, offering potential prognostic markers and therapeutic targets. The findings underscore the complexity of these gynaecological malignancies, emphasizing the need for tailored approaches in understanding and combating these diseases

Cell-Free Nucleic Acids

The deficits of mammography and the potential of noninvasive diagnostic testing using circulating miRNA profiles are presented in our first review article. Exosomes are important in the transfer of genetic information. The current knowledge on exosome-associated DNAs and on vesicle-associated DNAs and their role in pregnancy-related complications is presented in the next article. The major obstacle is the lack of a standardized technique for the isolation and measurement of exosomes. One review has summarized the latest results on cell-free nucleic acids in inflammatory bowel disease (IBD). Despite the extensive research, the etiology and exact pathogenesis are still unclear, although similarity to the cell-free ribonucleic acids (cfRNAs) observed in other autoimmune diseases seems to be relevant in IBD. Liquid biopsy is a useful tool for the differentiation of leiomyomas and sarcomas in the corpus uteri. One manuscript has collected the most important knowledge of mesenchymal uterine tumors and shows the benefits of noninvasive sampling. Microchimerism has also recently become a hot topic. It is discussed in the context of various forms of transplantation and transplantation-related advanced therapies, the available cell-free nucleic acid (cfNA) markers, and the detection platforms that have been introduced. Ovarian cancer is one of the leading serious malignancies among women, with a high incidence of mortality; the introduction of new noninvasive diagnostic markers could help in its early detection and treatment monitoring. Epigenetic regulation is very important during the development of diseases and drug resistance. Methylation changes are important signs during ovarian cancer development, and it seems that the CDH1 gene is a potential candidate for being a noninvasive biomarker in the diagnosis of ovarian cancer. Preeclampsia is a mysterious disease—despite intensive research, the exact details of its development are unknown. It seems that cell-free nucleic acids could serve as biomarkers for the early detection of this disease. Three research papers deal with the prenatal application of cfDNA. Copy number variants (CNVs) are important subjects for the study of human genome variations, as CNVs can contribute to population diversity and human genetic diseases. These are useful in NIPT as a source of population specific data. The reliability of NIPT depends on the accurate estimation of fetal fraction. Improvement in the success rate of in vitro fertilization (IVF) and embryo transfer (ET) is an important goal. The measurement of embryo-specific small noncoding RNAs in culture media could improve the efficiency of ET

Artificial intelligence (AI) in rare diseases: is the future brighter?

The amount of data collected and managed in (bio)medicine is ever-increasing. Thus, there is a need to rapidly and efficiently collect, analyze, and characterize all this information. Artificial intelligence (AI), with an emphasis on deep learning, holds great promise in this area and is already being successfully applied to basic research, diagnosis, drug discovery, and clinical trials. Rare diseases (RDs), which are severely underrepresented in basic and clinical research, can particularly benefit from AI technologies. Of the more than 7000 RDs described worldwide, only 5% have a treatment. The ability of AI technologies to integrate and analyze data from different sources (e.g., multi-omics, patient registries, and so on) can be used to overcome RDs' challenges (e.g., low diagnostic rates, reduced number of patients, geographical dispersion, and so on). Ultimately, RDs' AI-mediated knowledge could significantly boost therapy development. Presently, there are AI approaches being used in RDs and this review aims to collect and summarize these advances. A section dedicated to congenital disorders of glycosylation (CDG), a particular group of orphan RDs that can serve as a potential study model for other common diseases and RDs, has also been included.info:eu-repo/semantics/publishedVersio

Comprehensive Review of Uterine Leiomyosarcoma: Pathogenesis, Diagnosis, Prognosis, and Targeted Therapy

Uterine leiomyosarcoma (uLMS) is the most common subtype of uterine sarcomas. They have a poor prognosis with high rates of recurrence and metastasis. The five-year survival for uLMS patients is between 25 and 76%, with survival rates approaching 10–15% for patients with metastatic disease at the initial diagnosis. Accumulating evidence suggests that several biological pathways are involved in uLMS pathogenesis. Notably, drugs that block abnormal functions of these pathways remarkably improve survival in uLMS patients. However, due to chemotherapy resistance, there remains a need for novel drugs that can target these pathways effectively. In this review article, we provide an overview of the recent progress in ascertaining the biological functions and regulatory mechanisms in uLMS, from the perspective of aberrant biological pathways, including DNA repair, immune checkpoint blockade, protein kinase and intracellular signaling pathways, and the hedgehog pathway. We review the emerging role of epigenetics and epitranscriptome in the pathogenesis of uLMS. In addition, we discuss serum markers, artificial intelligence (AI) combined with machine learning, shear wave elastography, current management and medical treatment options, and ongoing clinical trials for patients with uLMS. Comprehensive, integrated, and deeper insights into the pathobiology and underlying molecular mechanisms of uLMS will help develop novel strategies to treat patients with this aggressive tumor