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Inframe insertions of three or more base pairs in exon 20 of the epidermal growth factor receptor (EGFR) gene were among the first EGFR mutations to be identified as oncogenic drivers in non-small cell lung cancer (NSCLC). However, unlike the classical EGFR L858R point mutation or exon 19 deletions, which represent the majority of EGFR mutations in NSCLC, low frequency EGFR exon 20 insertion mutations are associated with de novo resistance to targeted EGFR inhibitors and correlate with a poor patient prognosis. Here, we review the developments over the last 5 years in which pre-clinical studies, including elucidation of the crystal structure of an EGFR exon 20 insertion mutant kinase, have revealed a unique mechanism of kinase activation and steric conformation that define the lack of response of these EGFR mutations to clinically approved EGFR inhibitors. The recent development of several novel small molecule compounds that selectively inhibit EGFR exon 20 insertions holds promise for future therapeutic options that will be effective for patients with this molecular subtype of NSCLC.Tailoring therapies for lung cancerActivating mutations in the epidermal growth factor receptor (EGFR) gene are commonly observed in non-small-cell lung cancer (NSCLC). Treatment with EGFR inhibitors has proven successful in many patients harboring such mutations, but patients with EGFR exon 20 insertion mutations do not respond these drugs. Simon Vyse and Paul H Huang at The Institute of Cancer Research in London, UK, review the latest research on the effect that the insertion of three or more nucleotide base pairs into EGFR exon 20 has on the receptor’s structure and activity, which contributes to its poor sensitivity to currently available EGFR inhibitors. Promising preclinical findings with compounds that selectively target the EGFR exon 20 insertion mutant protein may lead to new treatment options for patients with this form of NSCLC.

Osteosarcoma is the most common primary bone sarcoma and is often diagnosed in the 2nd–3rd decades of life. Response to the aggressive and highly toxic neoadjuvant methotrexate-doxorubicin-cisplatin (MAP) chemotherapy schedule is strongly predictive of outcome. Outcomes for patients with osteosarcoma have not significantly changed for over thirty years. There is a need for more effective treatment for patients with high risk features but also reduced treatment-related toxicity for all patients. Predictive biomarkers are needed to help inform clinicians to de-escalate or add therapy, including immune therapies, and to contribute to future clinical trial designs. Here, we review a variety of approaches to improve outcomes and quality of life for patients with osteosarcoma with a focus on incorporating toxicity reduction, immune therapy and molecular analysis to provide the most effective and least toxic osteosarcoma therapy.

The discoidin domain receptors, DDR1 and DDR2, are receptor tyrosine kinases that bind to and are activated by collagens. Similar to collagen-binding β1 integrins, the DDRs bind to specific motifs within the collagen triple helix. However, these two types of collagen receptors recognize distinct collagen sequences. While GVMGFO (O is hydroxyproline) functions as a major DDR binding motif in fibrillar collagens, integrins bind to sequences containing Gxx'GEx\". The DDRs are thought to regulate cell adhesion, but their roles have hitherto only been studied indirectly. In this study we used synthetic triple-helical collagen-derived peptides that incorporate either the DDR-selective GVMGFO motif or integrin-selective motifs, such as GxOGER and GLOGEN, in order to selectively target either type of receptor and resolve their contributions to cell adhesion. Our data using HEK293 cells show that while cell adhesion to collagen I was completely inhibited by anti-integrin blocking antibodies, the DDRs could mediate cell attachment to the GVMGFO motif in an integrin-independent manner. Cell binding to GVMGFO was independent of DDR receptor signalling and occurred with limited cell spreading, indicating that the DDRs do not mediate firm adhesion. However, blocking the interaction of DDR-expressing cells with collagen I via the GVMGFO site diminished cell adhesion, suggesting that the DDRs positively modulate integrin-mediated cell adhesion. Indeed, overexpression of the DDRs or activation of the DDRs by the GVMGFO ligand promoted α1β1 and α2β1 integrin-mediated cell adhesion to medium- and low-affinity integrin ligands without regulating the cell surface expression levels of α1β1 or α2β1. Our data thus demonstrate an adhesion-promoting role of the DDRs, whereby overexpression and/or activation of the DDRs leads to enhanced integrin-mediated cell adhesion as a result of higher integrin activation state.

Retroperitoneal sarcomas are tumours with a poor prognosis. Upfront characterisation of the tumour is difficult, and under-grading is common. Radiomics has the potential to non-invasively characterise the so-called radiological phenotype of tumours. We aimed to develop and independently validate a CT-based radiomics classification model for the prediction of histological type and grade in retroperitoneal leiomyosarcoma and liposarcoma. A retrospective discovery cohort was collated at our centre (Royal Marsden Hospital, London, UK) and an independent validation cohort comprising patients recruited in the phase 3 STRASS study of neoadjuvant radiotherapy in retroperitoneal sarcoma. Patients aged older than 18 years with confirmed primary leiomyosarcoma or liposarcoma proceeding to surgical resection with available contrast-enhanced CT scans were included. Using the discovery dataset, a CT-based radiomics workflow was developed, including manual delineation, sub-segmentation, feature extraction, and predictive model building. Separate probabilistic classifiers for the prediction of histological type and low versus intermediate or high grade tumour types were built and tested. Independent validation was then performed. The primary objective of the study was to develop radiomic classification models for the prediction of retroperitoneal leiomyosarcoma and liposarcoma type and histological grade. 170 patients recruited between Oct 30, 2016, and Dec 23, 2020, were eligible in the discovery cohort and 89 patients recruited between Jan 18, 2012, and April 10, 2017, were eligible in the validation cohort. In the discovery cohort, the median age was 63 years (range 27–89), with 83 (49%) female and 87 (51%) male patients. In the validation cohort, median age was 59 years (range 33–77), with 46 (52%) female and 43 (48%) male patients. The highest performing model for the prediction of histological type had an area under the receiver operator curve (AUROC) of 0·928 on validation, based on a feature set of radiomics and approximate radiomic volume fraction. The highest performing model for the prediction of histological grade had an AUROC of 0·882 on validation, based on a radiomics feature set. Our validated radiomics model can predict the histological type and grade of retroperitoneal sarcomas with excellent performance. This could have important implications for improving diagnosis and risk stratification in retroperitoneal sarcomas. Wellcome Trust, European Organisation for Research and Treatment of Cancer-Soft Tissue and Bone Sarcoma Group, the National Institutes for Health, and the National Institute for Health and Care Research Biomedical Research Centre at The Royal Marsden NHS Foundation Trust and The Institute of Cancer Research.

Chondrosarcoma is a malignant tumor of bones, characterized by the production of cartilage matrix. Due to lack of effective treatment for advanced disease, the clinical management of chondrosarcomas is exceptionally challenging. Current research focuses on elucidating the molecular events underlying the pathogenesis of this rare bone malignancy, with the goal of developing new molecularly targeted therapies. Signaling pathways suggested to have a role in chondrosarcoma include Hedgehog, Src, PI3k-Akt-mTOR and angiogenesis. Mutations in / , present in more than 50% of primary conventional chondrosarcomas, make the development of IDH inhibitors a promising treatment option. The present review discusses the preclinical and early clinical data on novel targeted therapeutic approaches in chondrosarcoma.

Lung cancer is the most common cause of cancer-related deaths globally. Genetic alterations, such as amplifications, mutations and translocations in the fibroblast growth factor receptor (FGFR) family have been found in non-small cell lung cancer (NSCLC) where they have a role in cancer initiation and progression. FGFR aberrations have also been identified as key compensatory bypass mechanisms of resistance to targeted therapy against mutant epidermal growth factor receptor (EGFR) and mutant Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) in lung cancer. Targeting FGFR is, therefore, of clinical relevance for this cancer type, and several selective and nonselective FGFR inhibitors have been developed in recent years. Despite promising preclinical data, clinical trials have largely shown low efficacy of these agents in lung cancer patients with FGFR alterations. Preclinical studies have highlighted the emergence of multiple intrinsic and acquired resistance mechanisms to FGFR tyrosine kinase inhibitors, which include on-target FGFR gatekeeper mutations and activation of bypass signalling pathways and alternative receptor tyrosine kinases. Here, we review the landscape of FGFR aberrations in lung cancer and the array of targeted therapies under clinical evaluation. We also discuss the current understanding of the mechanisms of resistance to FGFR-targeting compounds and therapeutic strategies to circumvent resistance. Finally, we highlight our perspectives on the development of new biomarkers for stratification and prediction of FGFR inhibitor response to enable personalisation of treatment in patients with lung cancer.

Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on histological grading systems as well as sarcoma nomograms. Rapid developments in gene expression profiling technologies presented opportunities for applications in sarcoma. Molecular profiling of sarcomas has improved our understanding of the cancer biology of these rare cancers and identified potential novel therapeutic targets. In particular, transcriptomic signatures could play a role in risk classification in sarcoma to aid prognostication. Unlike other solid and haematological malignancies, transcriptomic signatures have not yet reached routine clinical use in sarcomas. Herein, we evaluate early developments in gene expression profiling in sarcomas that laid the foundations for transcriptomic signature development. We discuss the development and clinical evaluation of key transcriptomic biomarker signatures in sarcomas, including Complexity INdex in SARComas (CINSARC), Genomic Grade Index, and hypoxia-associated signatures. Prospective validation of these transcriptomic signatures is required, and prospective trials are in progress to evaluate reliability for clinical application. We anticipate that integration of these gene expression signatures alongside existing prognosticators and other Omics methodologies, including proteomics and DNA methylation analysis, could improve the identification of ‘high-risk’ patients who would benefit from more aggressive or selective treatment strategies. Moving forward, the incorporation of these transcriptomic prognostication signatures in clinical practice will undoubtedly advance precision medicine in the routine clinical management of sarcoma patients.

Pazopanib is the first and only tyrosine kinase inhibitor currently approved for the treatment of multiple histological subtypes of soft tissue sarcoma (STS). Initially developed as a small molecule inhibitor of vascular endothelial growth factor receptors, preclinical work indicates that pazopanib exerts an anticancer effect through the inhibition of both angiogenic and oncogenic signaling pathways. Following the establishment of optimal dosing and safety profiles in early phase studies and approval for the treatment of advanced renal cell carcinoma, pazopanib was investigated in STS. A landmark phase III randomized study demonstrated improved progression-free survival with pazopanib compared to that with placebo in pretreated patients with STS of various subtypes. The efficacy of pazopanib in specific STS subtypes has been further described in real-world-based case series in both mixed and subtype-specific STS cohorts. At present, there are no clinically validated predictive biomarkers for use in selecting patients with advanced STS for pazopanib therapy, limiting the clinical effectiveness and cost-effectiveness of the drug. In this review, we summarize the preclinical and clinical data for pazopanib, outline the evidence base for its effect in STS and explore reported studies that have investigated putative biomarkers.

Correctly diagnosing a rare childhood cancer such as sarcoma can be critical to assigning the correct treatment regimen. With a finite number of pathologists worldwide specializing in pediatric/young adult sarcoma histopathology, access to expert differential diagnosis early in case assessment is limited for many global regions. The lack of highly-trained sarcoma pathologists is especially pronounced in low to middle-income countries, where pathology expertise may be limited despite a similar rate of sarcoma incidence. To address this issue in part, we developed a deep learning convolutional neural network (CNN)-based differential diagnosis system to act as a pre-pathologist screening tool that quantifies diagnosis likelihood amongst trained soft-tissue sarcoma subtypes based on whole histopathology tissue slides. The CNN model is trained on a cohort of 424 centrally-reviewed histopathology tissue slides of alveolar rhabdomyosarcoma, embryonal rhabdomyosarcoma and clear-cell sarcoma tumors, all initially diagnosed at the originating institution and subsequently validated by central review. This CNN model was able to accurately classify the withheld testing cohort with resulting receiver operating characteristic (ROC) area under curve (AUC) values above 0.889 for all tested sarcoma subtypes. We subsequently used the CNN model to classify an externally-sourced cohort of human alveolar and embryonal rhabdomyosarcoma samples and a cohort of 318 histopathology tissue sections from genetically engineered mouse models of rhabdomyosarcoma. Finally, we investigated the overall robustness of the trained CNN model with respect to histopathological variations such as anaplasia, and classification outcomes on histopathology slides from untrained disease models. Overall positive results from our validation studies coupled with the limited worldwide availability of sarcoma pathology expertise suggests the potential of machine learning to assist local pathologists in quickly narrowing the differential diagnosis of sarcoma subtype in children, adolescents, and young adults.

Glioblastoma multiforme (GBM) is the most aggressive brain tumor in adults and remains incurable despite multimodal intensive treatment regimens. EGFRvIII is a truncated extracellular mutant of the EGF receptor (EGFR) commonly found in GBMs that confers enhanced tumorigenic behavior. To gain a molecular understanding of the mechanisms by which EGFRvIII acts, we have performed a large-scale analysis of EGFRvIII-activated phosphotyrosine-mediated signaling pathways and thereby have identified and quantified 99 phosphorylation sites on 69 proteins. Distinct signaling responses were observed as a function of titrated EGFRvIII receptor levels with the phosphatidylinositol 3-kinase pathway being dominant over the MAPK and STAT3 pathways at a high level of EGFRvIII expression. Within this data set, the activating phosphorylation site on the c-Met receptor was found to be highly responsive to EGFRvIII levels, indicating cross-activation of the c-Met receptor tyrosine kinase by EGFRvIII. To determine the significance of this finding, we devised a combined treatment regimen that used a c-Met kinase inhibitor and either an EGFR kinase inhibitor or cisplatin. This regimen resulted in enhanced cytotoxicity of EGFRvIII-expressing cells compared with treatment with either compound alone. These results suggest that the clinical use of c-Met kinase inhibitors in combination with either EGFR inhibitors or standard chemotherapeutics might represent a previously undescribed therapeutic approach to overcome the observed chemoresistance in patients with GBMs expressing EGFRvIII.