Spinal Metastases and the Evolving Role of Molecular Targeted Therapy, Chemotherapy, and Immunotherapy

Metastatic involvement of the spine is a common complication of systemic cancer progression. Surgery and external beam radiotherapy are palliative treatment modalities aiming to preserve neurological function, control pain and maintain functional status. More recently, with development of image guidance and stereotactic delivery of high doses of conformal radiation, local tumor control has improved; however recurrent or radiation refractory disease remains a significant clinical problem with limited treatment options. This manuscript represents a narrative overview of novel targeted molecular therapies, chemotherapies, and immunotherapy treatments for patients with breast, lung, melanoma, renal cell, prostate, and thyroid cancers, which resulted in improved responses compared to standard chemotherapy. We present clinical examples of excellent responses in spinal metastatic disease which have not been specifically documented in the literature, as most clinical trials evaluate treatment response based on visceral disease. This review is useful for the spine surgeons treating patients with metastatic disease as knowledge of these responses could help with timing and planning of surgical interventions, as well as promote multidisciplinary discussions, allowing development of an individualized treatment strategy to patients presenting with widespread multifocal progressive disease, where surgery could lead to suboptimal results

Recruited Cells Can Become Transformed and Overtake PDGF-Induced Murine Gliomas In Vivo during Tumor Progression

Gliomas are thought to form by clonal expansion from a single cell-of-origin, and progression-associated mutations to occur in its progeny cells. Glioma progression is associated with elevated growth factor signaling and loss of function of tumor suppressors Ink4a, Arf and Pten. Yet, gliomas are cellularly heterogeneous; they recruit and trap normal cells during infiltration.We performed lineage tracing in a retrovirally mediated, molecularly and histologically accurate mouse model of hPDGFb-driven gliomagenesis. We were able to distinguish cells in the tumor that were derived from the cell-of-origin from those that were not. Phenotypic, tumorigenic and expression analyses were performed on both populations of these cells. Here we show that during progression of hPDGFb-induced murine gliomas, tumor suppressor loss can expand the recruited cell population not derived from the cell-of-origin within glioma microenvironment to dominate regions of the tumor, with essentially no contribution from the progeny of glioma cell-of-origin. Moreover, the recruited cells can give rise to gliomas upon transplantation and passaging, acquire polysomal expression profiles and genetic aberrations typically present in glioma cells rather than normal progenitors, aid progeny cells in glioma initiation upon transplantation, and become independent of PDGFR signaling.These results indicate that non-cell-of-origin derived cells within glioma environment in the mouse can be corrupted to become bona fide tumor, and deviate from the generally established view of gliomagenesis

Dual activating FGFR1

Abstract Background Pilomyxoid astrocytomas are an aggressive subtype of astrocytoma, not graded by WHO, frequently located in hypothalamic/chiasmatic region, affecting diencephalic structures, and characterized by shorter survival and high recurrence rates. Pilomyxoid astrocytoma management remains controversial, with pathologic tissue diagnosis and relief of mass effect being the main goals of surgery while avoiding treatment‐related morbidity, including vision loss, panhypopituitarism, and hypothalamic dysfunction. Chemotherapy (typically vincristine and carboplatin) in all pediatric patients and radiation therapy in pediatric patients over 5 years of age are used for treatment. Methods We report clinical presentation, surgical management, and whole exome sequencing results in a pediatric patient with the subtotally resected pilomyxoid astrocytoma. Results We identified two somatic activating missense mutations affecting FGFR1, including FGFR1 p.K656E and FGFR1 p.V561M. While the former is a known hotspot mutation that is both activating and transforming, the latter has been described as a gatekeeper mutation imparting resistance to FGFR inhibitors. Interestingly, both mutations were present with similar variant allele frequency within the tumor. Conclusion Similar variant allele frequencies of FGFR1 p.K656E and FGFR1 p.V561M mutations in our patient's tumor suggest that these mutations may have occurred at similar time points. Use of FGFR inhibitors in addition to STAT3 or PI3K/mTOR inhibition may prove a useful strategy in targeting our patient's pilomyxoid astrocytoma

MEF Promotes Stemness in the Pathogenesis of Gliomas

High-grade gliomas are aggressive and uniformly fatal tumors, composed of a heterogeneous population of cells that include many with stem cell-like properties. The acquisition of stem-like traits might contribute to glioma initiation, growth and recurrence. Here we investigated the role of the transcription factor myeloid Elf-1 like factor (MEF, also known as ELF4) in glioma. We found that MEF is highly expressed in both human and mouse GBMs and its absence impairs gliomagenesis in a PDGF-driven glioma mouse model. We show that modulation of MEF levels in both mouse neural stem cells and human glioblastoma cells, has a significant impact on neurosphere formation. Moreover, we identify Sox2 as a direct downstream target of MEF. Taken together, our studies implicate MEF as a previously unrecognized gatekeeper gene in gliomagenesis by promoting stem cell characteristics through Sox2 activation

Correlations between genomic subgroup and clinical features in a cohort of more than 3000 meningiomas

OBJECTIVE Recent large-cohort sequencing studies have investigated the genomic landscape of meningiomas, identifying somatic coding alterations in NF2, SMARCB1, SMARCE1, TRAF7, KLF4, POLR2A, BAP1, and members of the PI3K and Hedgehog signaling pathways. Initial associations between clinical features and genomic subgroups have been described, including location, grade, and histology. However, further investigation using an expanded collection of samples is needed to confirm previous findings, as well as elucidate relationships not evident in smaller discovery cohorts. METHODS Targeted sequencing of established meningioma driver genes was performed on a multiinstitution cohort of 3016 meningiomas for classification into mutually exclusive subgroups. Relevant clinical information was collected for all available cases and correlated with genomic subgroup. Nominal variables were analyzed using Fisher's exact tests, while ordinal and continuous variables were assessed using Kruskal-Wallis and 1-way ANOVA tests, respectively. Machine-learning approaches were used to predict genomic subgroup based on noninvasive clinical features. RESULTS Genomic subgroups were strongly associated with tumor locations, including correlation of HH tumors with midline location, and non-NF2 tumors in anterior skull base regions. NF2 meningiomas were significantly enriched in male patients, while KLF4 and POLR2A mutations were associated with female sex. Among histologies, the results confirmed previously identified relationships, and observed enrichment of microcystic features among mutation unknown samples. Additionally, KLF4-mutant meningiomas were associated with larger peritumoral brain edema, while SMARCB1 cases exhibited elevated Ki-67 index. Machine-learning methods revealed that observable, noninvasive patient features were largely predictive of each tumor's underlying driver mutation. CONCLUSIONS Using a rigorous and comprehensive approach, this study expands previously described correlations between genomic drivers and clinical features, enhancing our understanding of meningioma pathogenesis, and laying further groundwork for the use of targeted therapies. Importantly, the authors found that noninvasive patient variables exhibited a moderate predictive value of underlying genomic subgroup, which could improve with additional training data. With continued development, this framework may enable selection of appropriate precision medications without the need for invasive sampling procedures