Targeting Fibroblast Growth Factor Receptor 1 for Treatment of Soft-Tissue Sarcoma

Molecular Targeting of the Fibroblast Growth Factor Receptor Pathway across Various Cancers

Fibroblast growth factor receptors (FGFRs) are a family of receptor tyrosine kinases that are involved in the regulation of cell proliferation, survival, and development. FGFR alterations including amplifications, fusions, rearrangements, and mutations can result in the downstream activation of tyrosine kinases, leading to tumor development. Targeting these FGFR alterations has shown to be effective in treating cholangiocarcinoma, urothelial carcinoma, and myeloid/lymphoid neoplasms, and there are currently four FGFR inhibitors approved by the Food and Drug Administration (FDA). There have been developments in multiple agents targeting the FGFR pathway, including selective FGFR inhibitors, ligand traps, monoclonal antibodies, and antibody-drug conjugates. However, most of these agents have variable and low responses, with some intolerable toxicities and acquired resistances. This review will summarize previous clinical experiences and current developments in agents targeting the FGFR pathway, and will also discuss future directions for FGFR-targeting agents.

Heterogeneity in the gene regulatory landscape of leiomyosarcoma

Characterizing inter-tumor heterogeneity is crucial for selecting suitable cancer therapy, as the presence of diverse molecular subgroups of patients can be associated with disease outcome or response to treatment. While cancer subtypes are often characterized by differences in gene expression, the mechanisms driving these differences are generally unknown. We set out to model the regulatory mechanisms driving sarcoma heterogeneity based on patient-specific, genome-wide gene regulatory networks. We developed a new computational framework, PORCUPINE, which combines knowledge on biological pathways with permutation-based network analysis to identify pathways that exhibit significant regulatory heterogeneity across a patient population. We applied PORCUPINE to patient-specific leiomyosarcoma networks modeled on data from The Cancer Genome Atlas and validated our results in an independent dataset from the German Cancer Research Center. PORCUPINE identified 37 heterogeneously regulated pathways, including pathways representing potential targets for treatment of subgroups of leiomyosarcoma patients, such as FGFR and CTLA4 inhibitory signaling. We validated the detected regulatory heterogeneity through analysis of networks and chromatin states in leiomyosarcoma cell lines. We showed that the heterogeneity identified with PORCUPINE is not associated with methylation profiles or clinical features, thereby suggesting an independent mechanism of patient heterogeneity driven by the complex landscape of gene regulatory interactions.

Optimal ranking and directional signature classification using the integral strategy of multi-objective optimization-based association rule mining of multi-omics data

Introduction: Association rule mining (ARM) is a powerful tool for exploring the informative relationships among multiple items (genes) in any dataset. The main problem of ARM is that it generates many rules containing different rule-informative values, which becomes a challenge for the user to choose the effective rules. In addition, few works have been performed on the integration of multiple biological datasets and variable cutoff values in ARM. Methods: To solve all these problems, in this article, we developed a novel framework MOOVARM (multi-objective optimized variable cutoff-based association rule mining) for multi-omics profiles. Results: In this regard, we identified the positive ideal solution (PIS), which maximized the profit and minimized the loss, and negative ideal solution (NIS), which minimized the profit and maximized the loss for all gene sets (item sets), belonging to each extracted rule. Thereafter, we computed the distance (d +) from PIS and distance (d -) from NIS for each gene set or product. These two distances played an important role in determining the optimized associations among various pairs of genes in the multi-omics dataset. We then globally estimated the relative closeness to PIS for ranking the gene sets. When the relative closeness score of the rule is greater than or equal to the pre-defined threshold value, the rule can be considered a final resultant rule. Moreover, MOOVARM evaluated the relative score of the rule based on the status of all genes instead of individual genes. Conclusions: MOOVARM produced the final rank of the extracted (multi-objective optimized) rules of correlated genes which had better disease classification than the state-of-the-art algorithms on gene signature identification.

The FGF/FGFR system in the microglial neuroinflammation with Borrelia burgdorferi: likely intersectionality with other neurological conditions

BACKGROUND

Lyme neuroborreliosis, caused by the bacterium Borrelia burgdorferi affects both the central and peripheral nervous systems (CNS, PNS). The CNS manifestations, especially at later stages, can mimic/cause many other neurological conditions including psychiatric disorders, dementia, and others, with a likely neuroinflammatory basis. The pathogenic mechanisms associated with Lyme neuroborreliosis, however, are not fully understood.

METHODS

In this study, using cultures of primary rhesus microglia, we explored the roles of several fibroblast growth factor receptors (FGFRs) and fibroblast growth factors (FGFs) in neuroinflammation associated with live B. burgdorferi exposure. FGFR specific siRNA and inhibitors, custom antibody arrays, ELISAs, immunofluorescence and microscopy were used to comprehensively analyze the roles of these molecules in microglial neuroinflammation due to B. burgdorferi.

RESULTS

FGFR1-3 expressions were upregulated in microglia in response to B. burgdorferi. Inhibition of FGFR 1, 2 and 3 signaling using siRNA and three different inhibitors showed that FGFR signaling is proinflammatory in response to the Lyme disease bacterium. FGFR1 activation also contributed to non-viable B. burgdorferi mediated neuroinflammation. Analysis of the B. burgdorferi conditioned microglial medium by a custom antibody array showed that several FGFs are induced by the live bacterium including FGF6, FGF10 and FGF12, which in turn induce IL-6 and/or CXCL8, indicating a proinflammatory nature. To our knowledge, this is also the first-ever described role for FGF6 and FGF12 in CNS neuroinflammation. FGF23 upregulation, in addition, was observed in response to the Lyme disease bacterium. B. burgdorferi exposure also downregulated many FGFs including FGF 5, 7, 9, 11, 13, 16, 20 and 21. Some of the upregulated FGFs have been implicated in major depressive disorder (MDD) or dementia development, while the downregulated ones have been demonstrated to have protective roles in epilepsy, Parkinson's disease, Alzheimer's disease, spinal cord injury, blood-brain barrier stability, and others.

CONCLUSIONS

In this study we show that FGFRs and FGFs are novel inducers of inflammatory mediators in Lyme neuroborreliosis. It is likely that an unresolved, long-term (neuro)-Lyme infection can contribute to the development of other neurologic conditions in susceptible individuals either by augmenting pathogenic FGFs or by suppressing ameliorative FGFs or both.

The Role of the Tumor Suppressor Gene Protein Tyrosine Phosphatase Gamma in Cancer

Members of the Protein Tyrosine Phosphatase (PTPs) family are associated with growth regulation and cancer development. Acting as natural counterpart of tyrosine kinases (TKs), mainly involved in crucial signaling pathways such as regulation of cell cycle, proliferation, invasion and angiogenesis, they represent key parts of complex physiological homeostatic mechanisms. Protein tyrosine phosphatase gamma (PTPRG) is classified as a R5 of the receptor type (RPTPs) subfamily and is broadly expressed in various isoforms in different tissues. PTPRG is considered a tumor-suppressor gene (TSG) mapped on chromosome 3p14-21, a region frequently subject to loss of heterozygosity in various tumors. However, reported mechanisms of PTPRG downregulation include missense mutations, ncRNA gene regulation and epigenetic silencing by hypermethylation of CpG sites on promoter region causing loss of function of the gene product. Inactive forms or total loss of PTPRG protein have been described in sporadic and Lynch syndrome colorectal cancer, nasopharyngeal carcinoma, ovarian, breast, and lung cancers, gastric cancer or diseases affecting the hematopoietic compartment as Lymphoma and Leukemia. Noteworthy, in Central Nervous System (CNS) PTPRZ/PTPRG appears to be crucial in maintaining glioblastoma cell-related neuronal stemness, carving out a pathological functional role also in this tissue. In this review, we will summarize the current knowledge on the role of PTPRG in various human cancers.

Impact of tissue-agnostic approvals for patients with sarcoma

Tissue-agnostic drug development is a major step forward in offering treatment options for rare tumors. Sarcomas are heterogeneous rare malignancies with more than 100 subtypes. Recent failure of Phase III trials, nonbiomarker-driven clinical trials, and rarity hamper developmental therapeutics in sarcomas. Since a 'one-size-fits-all' approach continues to be the standard of care, tissue-agnostic approvals assume significance in sarcomas. In this review, we focus on the clinical evidence of recent drug approvals for neurotrophic tyrosine receptor kinase (NTRK) fusion, microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) phenotype, and tumor mutation burden-high (TMB-H) status in the context of sarcomas, and the future landscape of tissue-agnostic targets, such as rearranged during transfection (RET), fibroblast growth factor receptor (FGFR), and neuregulin-1 (NRG1).

Fibroblast Growth Factor Receptor (FGFR) Signaling in GIST and Soft Tissue Sarcomas

Sarcomas are a heterogeneous group of rare malignancies originating from mesenchymal tissues with limited therapeutic options. Recently, alterations in components of the fibroblast growth factor receptor (FGFR) signaling pathway have been identified in a range of different sarcoma subtypes, most notably gastrointestinal stromal tumors, rhabdomyosarcomas, and liposarcomas. These alterations include genetic events such as translocations, mutations, and amplifications as well as transcriptional overexpression. Targeting FGFR has therefore been proposed as a novel potential therapeutic approach, also in light of the clinical activity shown by multi-target tyrosine kinase inhibitors in specific subtypes of sarcomas. Despite promising preclinical evidence, thus far, clinical trials have enrolled very few sarcoma patients and the efficacy of selective FGFR inhibitors appears relatively low. Here, we review the known alterations of the FGFR pathway in sarcoma patients as well as the preclinical and clinical evidence for the use of FGFR inhibitors in these diseases. Finally, we discuss the possible reasons behind the current clinical data and highlight the need for biomarker stratification to select patients more likely to benefit from FGFR targeted therapies.

Inhibition of FGF-FGFR and VEGF-VEGFR signalling in cancer treatment

The sites of targeted therapy are limited and need to be expanded. The FGF‐FGFR signalling plays pivotal roles in the oncogenic process, and FGF/FGFR inhibitors are a promising method to treat FGFR‐altered tumours. The VEGF‐VEGFR signalling is the most crucial pathway to induce angiogenesis, and inhibiting this cascade has already got success in treating tumours. While both their efficacy and antitumour spectrum are limited, combining FGF/FGFR inhibitors with VEGF/VEGFR inhibitors are an excellent way to optimize the curative effect and expand the antitumour range because their combination can target both tumour cells and the tumour microenvironment. In addition, biomarkers need to be developed to predict the efficacy, and combination with immune checkpoint inhibitors is a promising direction in the future. The article will discuss the FGF‐FGFR signalling pathway, the VEGF‐VEGFR signalling pathway, the rationale of combining these two signalling pathways and recent small‐molecule FGFR/VEGFR inhibitors based on clinical trials.

Global Genome Conformational Programming during Neuronal Development Is Associated with CTCF and Nuclear FGFR1-The Genome Archipelago Model

During the development of mouse embryonic stem cells (ESC) to neuronal committed cells (NCC), coordinated changes in the expression of 2851 genes take place, mediated by the nuclear form of FGFR1. In this paper, widespread differences are demonstrated in the ESC and NCC inter- and intra-chromosomal interactions, chromatin looping, the formation of CTCF- and nFGFR1-linked Topologically Associating Domains (TADs) on a genome-wide scale and in exemplary HoxA-D loci. The analysis centered on HoxA cluster shows that blocking FGFR1 disrupts the loop formation. FGFR1 binding and genome locales are predictive of the genome interactions; likewise, chromatin interactions along with nFGFR1 binding are predictive of the genome function and correlate with genome regulatory attributes and gene expression. This study advances a topologically integrated genome archipelago model that undergoes structural transformations through the formation of nFGFR1-associated TADs. The makeover of the TAD islands serves to recruit distinct ontogenic programs during the development of the ESC to NCC.

RAD51AP1 promotes progression of ovarian cancer via TGF-β/Smad signalling pathway

Ovarian cancer (OC) is one of the leading causes of female deaths. However, the molecular pathogenesis of OC has still remained elusive. This study aimed to explore the potential genes associated with the progression of OC. In the current study, 3 data sets of OC were downloaded from the GEO database to identify hub gene. Somatic mutation data obtained from TCGA were used to analyse the mutation. Immune cells were used to estimate effect of the hub gene to the tumour microenvironment. RNA‐seq and clinical data of OC patients retrieved from TCGA were used to investigate the diagnostic and prognostic values of hub gene. A series of in vitro assays were performed to indicate the function of hub gene and its possible mechanisms in OC. As a result, RAD51AP1 was found as a hub gene, which expression higher was mainly associated with poor survival in OC patients. Up‐regulation of RAD51AP1 was closely associated with mutations. RAD51AP1 up‐regulation accompanied by accumulated Th2 cells, but reduced CD4 + T cells and CD8 + T cells. Nomogram demonstrated RAD51AP1 increased the accuracy of the model. Down‐regulation of RAD51AP1 suppressed proliferation, migration and invasion capabilities of OC cells in vitro. Additionally, scatter plots showed that RAD51AP1 was positively correlated with genes in TGF‐β/Smad pathway. The above‐mentioned results were validated by RT‐qPCR and Western blotting. In conclusion, up‐regulation of RAD51AP1 was closely associated with mutations in OC. RAD51AP1 might represent an indicator for predicting OS of OC patients. Besides, RAD51AP1 might accelerate progression of OC by TGF‐β/Smad signalling pathway.

Advances in image enhancement for sarcoma surgery

The recurrence rate of soft tissue and bone sarcomas strongly correlates to the status of the surgical margin after excision, yet excessive removal of tissue may lead to distinct, otherwise avoidable morbidity. Therefore, adequate margination of sarcomas both pre- and intra-operatively is a clinical necessity that has not yet fully been met. Current guidance for soft-tissue sarcomas recommends an ultrasound scan followed by magnetic resonance imaging (MRI). For bone sarcomas, two plane radiographs are required, followed similarly by an MRI scan. The introduction of more precise imaging modalities may reduce the morbidity associated with sarcoma surgery; the PET-CT and PET-MRI approaches in particular demonstrating high clinical efficacy. Despite advancements in the accuracy in pre-operative imaging, translation of an image to surgical margins is difficult, regularly resulting in wider resection margins than required. For soft tissue sarcomas there is currently no standard technique for image guided resections, while for bone sarcomas fluoroscopy may be used, however margins are not easily discernible during the surgical procedure. Near infra-red (NIR) fluorescence guided surgery offers an intra-operative modality through which complete tumour resection with adequate tumour-free margins may be achieved, while simultaneously minimising surgical morbidity. NIR imaging presents a potentially valuable adjunct to sarcoma surgery. Early reports indicate that it may be able to provide the surgeon with helpful information on anatomy, perfusion, lymphatic drainage, tumour margins and metastases. The use of NIR fluorochromes have also been demonstrated to be well tolerated by patients. However, prior to widespread implementation, studies related to cost-effectiveness and the development of protocols are essential. Nevertheless, NIR imaging may become ubiquitous in the future, carrying the potential to transform the surgical management of sarcoma.

Metastatic adult pancreatoblastoma: Multimodal treatment and molecular characterization of a very rare disease

BACKGROUND

Pancreatoblastoma is a rare malignancy that occurs predominantly in children. Less than 50 adult cases, including 17 patients with metastatic disease, have been published to date. Recent outcome data from children with advanced-stage disease suggest an intensive multimodal treatment approach; however, little is known about the most beneficial therapy in adults. Molecular characterization of pancreatoblastoma is limited to a small number of pediatric cases and revealed few recurrent genetic events without immediate clinical relevance.

METHODS

Patients were treated between 2013 and 2018 at a high-volume German university cancer center. Molecular analyses included whole genome, exome, transcriptome, and fusion gene panel sequencing. Molecularly guided treatment recommendations were discussed within a dedicated molecular tumor board (MTB) embedded in a precision oncology program (NCT MASTER).

RESULTS

We identified four adult patients with metastatic pancreatoblastoma. In three patients, local approaches were combined with systemic treatment. Oxaliplatin-containing protocols showed an acceptable tumor control as well as an adequate toxicity profile. Overall survival was 15, 17, 18 and 24 months, respectively. Three tumors harbored genetic alterations involving the FGFR pathway that included an oncogenic FGFR2 fusion.

CONCLUSION

Oxaliplatin-containing chemotherapy seems to be a reasonable approach in adult patients with advanced pancreatoblastoma, whereas the benefit of intensified treatment including local ablative techniques or surgical resection remains unclear. Our finding of FGFR alterations in three of four cases indicates a potential role of FGFR signaling in adult pancreatoblastoma whose clinical significance warrants further study.

Genome-wide profiling of prognosis-related alternative splicing signatures in sarcoma

BACKGROUND

Sarcomas (SARCs) are rare malignant tumors with poor prognosis. Increasing evidence has suggested that aberrant alternative splicing (AS) is strongly associated with tumor initiation and progression. We considered whether survival-related AS events might serve as prognosis predictors and underlying targeted molecules in SARC treatment.

METHODS

RNA-Seq data of the SARC cohort were downloaded from The Cancer Genome Atlas (TCGA) database. Survival-related AS events were selected by univariate and multivariate Cox regression analyses. Metascape was used for constructing a gene interaction network and performing functional enrichment analysis. Then, prognosis predictors were established based on statistically significant survival-related AS events and evaluated by receiver operator characteristic (ROC) curve analysis. Finally, the potential regulatory network was analyzed via Pearson's correlation between survival-related AS events and splicing factors (SFs).

RESULTS

A total of 3,610 AS events and 2,291 genes were found to be prognosis-related in 261 SARC samples. The focal adhesion pathway was identified as the most critical molecular mechanism corresponding to poor prognosis. Notably, several prognosis predictors based on survival-related AS events showed excellent performance in prognosis prediction. The area under the curve of the ROC of the risk score was 0.85 in the integrated predictor. The splicing network proved complicated regulation between prognosis-related SFs and AS events. Also, driver gene mutations were significantly associated with AS in SARC patients.

CONCLUSIONS

Survival-related AS events may become ideal indictors for the prognosis prediction of SARCs. Corresponding splicing regulatory mechanisms are worth further exploration.

[Personalized oncology]

CLINICAL ISSUE

Innovative next generation sequencing (NGS) technologies and comprehensive sequencing investigations in large patient cohorts have paved the way for very promising personalized treatment strategies based on the molecular characteristics of individual tumors.

STANDARD TREATMENT

Targeted therapies, such as tyrosine kinase inhibitors, antibodies and modern immunotherapeutic approaches are well established as monotherapy and combination therapy for many hematological and oncological malignancies.

TREATMENT INNOVATIONS

A plethora of innovative therapies targeting various components of intracellular signaling cascades and effective mechanisms against oncogenes as well as the availability of NGS technologies enable personalized cancer treatment based on the molecular profiles of individual tumors and genetic stratification, within clinical trials.

DIAGNOSTIC WORK-UP

Comprehensive genetic approaches including cancer gene panel sequencing, whole exome, whole genome and transcriptome sequencing are carried out to a varying extent and particularly in the academic setting.

PERFORMANCE

Principally, a comprehensive characterization of tumors in addition to DNA and RNA sequencing that also incorporates epigenetic, metabolomic, and proteomic alterations would be desirable. A comprehensive clinical implementation of integrative, multidimensional genetic typing is, however, currently not possible.

ACHIEVEMENTS

It remains to be demonstrated whether these approaches will translate into significantly better outcomes for patients and whether they can be increasingly implemented in the routine diagnostic work-up.

PRACTICAL RECOMMENDATIONS

The selection of diagnostic tools in individual cases and the extent of genomic analyses in the clinical context, need to take the availability of methods as well as the present clinical situation into account.

Validating Comprehensive Next-Generation Sequencing Results for Precision Oncology: The NCT/DKTK Molecularly Aided Stratification for Tumor Eradication Research Experience

Purpose

Rapidly evolving genomics technologies, in particular comprehensive next-generation sequencing (NGS), have led to exponential growth in the understanding of cancer biology, shifting oncology toward personalized treatment strategies. However, comprehensive NGS approaches, such as whole-exome sequencing, have limitations that are related to the technology itself as well as to the input source. Hence, clinical implementation of comprehensive NGS in a quality-controlled diagnostic workflow requires both the standardization of sequencing procedures and continuous validation of sequencing results by orthogonal methods in an ongoing program to enable the determination of key test parameters and continuous improvement of NGS and bioinformatics pipelines.

Patients and Methods

We present validation data on 220 patients who were enrolled between 2013 and 2016 in a multi-institutional, genomics-guided precision oncology program (Molecularly Aided Stratification for Tumor Eradication Research) of the National Center for Tumor Diseases Heidelberg and the German Cancer Consortium.

Results

More than 90% of clinically actionable genomic alterations identified by combined whole-exome sequencing and transcriptome sequencing were successfully validated, with varying frequencies of discordant results across different types of alterations (fusions, 3.7%; single-nucleotide variants, 2.6%; amplifications, 1.1%; overexpression, 0.9%; deletions, 0.6%). The implementation of new computational methods for NGS data analysis led to a substantial improvement of gene fusion calling over time.

Conclusion

Collectively, these data demonstrate the value of a rigorous validation program that partners with comprehensive NGS to successfully implement and continuously improve cancer precision medicine in a clinical setting.

Long Pentraxin 3-Mediated Fibroblast Growth Factor Trapping Impairs Fibrosarcoma Growth

Fibrosarcomas are soft tissue mesenchymal tumors originating from transformed fibroblasts. Fibroblast growth factor-2 (FGF2) and its tyrosine-kinase receptors (FGFRs) play pivotal roles in fibrosarcoma onset and progression, FGF2 being actively produced by fibroblasts in all stages along their malignant transformation to the fibrosarcoma stage. The soluble pattern recognition receptor long pentraxin-3 (PTX3) is an extrinsic oncosuppressor whose expression is reduced in different tumor types, including soft tissue sarcomas, via hypermethylation of its gene promoter. PTX3 interacts with FGF2 and other FGF family members, thus acting as a multi-FGF antagonist able to inhibit FGF-dependent neovascularization and tumor growth. Here, PTX3 overexpression significantly reduced the proliferative and tumorigenic potential of fibrosarcoma cells in vitro and in vivo. In addition, systemic delivery of human PTX3 driven by the Tie2 promoter inhibited the growth of fibrosarcoma grafts in transgenic mice. In a translational perspective, the PTX3-derived small molecule FGF trap NSC12 prevented activation of the FGF/FGFR system in fibrosarcoma cells and reduced their tumorigenic activity in vivo. In conclusion, impairment of the FGF/FGFR system by FGF trap molecules may represent a novel therapeutic approach for the treatment of fibrosarcoma.

DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles

Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

Protein Tyrosine Phosphatase Receptor Type G (PTPRG) Controls Fibroblast Growth Factor Receptor (FGFR) 1 Activity and Influences Sensitivity to FGFR Kinase Inhibitors

Recently, FGFR1 was found to be overexpressed in osteosarcoma and represents an important target for precision medicine. However, because targeted cancer therapy based on FGFR inhibitors has so far been less efficient than expected, a detailed understanding of the target is important. We have here applied proximity-dependent biotin labeling combined with label-free quantitative mass spectrometry to identify determinants of FGFR1 activity in an osteosarcoma cell line. Many known FGFR interactors were identified (e.g. FRS2, PLCG1, RSK2, SRC), but the data also suggested novel determinants. A strong hit in our screen was the tyrosine phosphatase PTPRG. We show that PTPRG and FGFR1 interact and colocalize at the plasma membrane where PTPRG directly dephosphorylates activated FGFR1. We further show that osteosarcoma cell lines depleted for PTPRG display increased FGFR activity and are hypersensitive to stimulation by FGF1. In addition, PTPRG depletion elevated cell growth and negatively affected the efficacy of FGFR kinase inhibitors. Thus, PTPRG may have future clinical relevance by being a predictor of outcome after FGFR inhibitor treatment.

Precision oncology based on omics data: The NCT Heidelberg experience

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high-resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next-generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology-driven stratification of younger adults with advanced-stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole-exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence-based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case-by-case basis toward controlled clinical trials of genomics-guided treatments.

PD-L1 (CD274) copy number gain, expression, and immune cell infiltration as candidate predictors for response to immune checkpoint inhibitors in soft-tissue sarcoma

Soft-tissue sarcomas (STS) are rare malignancies that account for 1% of adult cancers and comprise more than 50 entities. Current therapeutic options for advanced-stage STS are limited. Immune checkpoint inhibitors targeting the PD-1/PD-L1 signaling axis are being explored as new treatment modality in STS; however, the determinants of response to these agents are largely unknown. Using the sarcoma data set of The Cancer Genome Altas (TCGA) and an independent cohort of untreated high-grade STS, we analyzed DNA copy number status and mRNA expression of PD-L1 in a total of 335 STS cases. Copy number gains (CNG) were detected in 54 TCGA cases (21.1%), of which 21 (8.2%) harbored focal PD-L1 CNG and that were most prevalent in myxofibrosarcoma (35%) and undifferentiated pleomorphic sarcoma (34%). In the untreated high-grade STS cohort, we detected CNG in six cases (7.6%). Analysis of co-amplified genes identified a 5.6-Mb core region comprising 27 genes, including JAK2. Patients with PD-L1 CNG had higher PD-L1 expression compared with STS without CNG (fold change, 1.8; p = 0.02), an effect that was most pronounced in the setting of focal PD-L1 CNG (fold change, 3.0; p = 0.0027). STS with PD-L1 CNG showed a significantly higher mutational load compared with tumors with a diploid PD-L1 locus (median number of mutated genes; 58 vs. 40; p = 3.6E-06), and PD-L1 CNG were associated with inferior survival (HR = 1.82; p = 0.025). In contrast, T-cell infiltrates quantified by mRNA expression of CD3Z were associated with improved survival (HR = 0.88; p = 0.024) and consequently influenced the prognostic power of PD-L1 CNG, with low CD3Z levels conferring poor survival in cases with PD-L1 CNG (HR = 1.8; p = 0.049). These data demonstrate that PD-L1 GNG and elevated expression of PD-L1 occur in a substantial proportion of STS, have prognostic impact that is modulated by T-cell infiltrates, and thus warrant investigation as response predictors for immune checkpoint inhibition.

Personalisierte Medizin: Strukturen, Tumorboards, Visionen

Die zunehmende Berücksichtigung molekularer Charakteristika in der Therapieauswahl hat bei etlichen histologisch nicht weiter zu differenzierenden Tumorentitäten zu einer relevanten Prognoseverbesserung geführt. Beispiele wie das EGFR-mutierte Bronchialkarzinom oder das BRAF-mutierte maligne Melanom, die effektiv durch Kinaseinhibitoren behandelt werden können, ebenso wie neue Einblicke in genetische Determinanten des Ansprechens auf eine Immuncheckpointblockade lassen darauf hoffen, dass diese Ansätze auch bei anderen Tumorentitäten, Proteinfamilien und Medikamentenklassen Anwendung finden werden. Moderne Hochdurchsatzverfahren zur Sequenzierung von DNA und RNA können detaillierte Informationen über alle somatischen Alterationen in Krebsgenomen liefern und werden zunehmend bezahlbar. Die Integration dieser Analytik in klinische Abläufe stellt aber eine große Herausforderung dar. Innerhalb des NCT MASTER-Programms wurde ein standardisierter Arbeitsablauf etabliert, der ein interdisziplinäres Molekulares Tumorboard beinhaltet und eine umfassende Tumorgenomsequenzierung im klinischen Kontext ermöglicht. Im Rahmen molekular stratifizierter Studienkonzepte gilt es nun, die Umsetzung individueller Therapieempfehlungen und die Evaluation der Therapieresultate zu optimieren.