Fighting vessel dysmorphia to improve glioma chemotherapy

High-grade gliomas are aggressive and abundantly vascular tumors, and as in most cancer types, blood vessels in advanced lesions are highly abnormal. Poor perfusion and vascular leakage in tumor tissue resulting in hypoxia, necrosis, and high interstitial fluid pressure can hamper the efficient delivery of chemotherapy. Tumor angiogenesis is known to be supported by host leukocytes recruited to the tumor microenvironment, but the mechanisms leading to dysfunctional vascular network formation are incompletely understood. In this issue of EMBO Molecular Medicine, Mathivet et al (2017) present an elegant study, where longitudinal intravital imaging gives new insight on how recruitment and polarization of tumor-associated macrophages regulate aberrant angiogenesis in experimental gliomas. They show that macrophage targeting results in vessel normalization and improved chemotherapy response, suggesting that the combination of these therapeutic modalities could improve the outcome of glioma treatment in the clinic.Non peer reviewe

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry

Objectives: Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes. Setting: A regional cancer centre in Australia. Participants: Disease-specific data from a purpose-built cancer registry (Evaluation of Cancer Outcomes (ECO)) from 869 patients were used to predict survival at 6, 12 and 24 months. The model was validated with data from a further 94 patients, and results compared to the assessment of five specialist oncologists. Machine-learning prediction using ECO data was compared with that using EAR and a model combining ECO and EAR data. Primary and secondary outcome measures: Survival prediction accuracy in terms of the area under the receiver operating characteristic curve (AUC). Results: The ECO model yielded AUCs of 0.87 (95% CI 0.848 to 0.890) at 6 months, 0.796 (95% CI 0.774 to 0.823) at 12 months and 0.764 (95% CI 0.737 to 0.789) at 24 months. Each was slightly better than the performance of the clinician panel. The model performed consistently across a range of cancers, including rare cancers. Combining ECO and EAR data yielded better prediction than the ECO-based model (AUCs ranging from 0.757 to 0.997 for 6 months, AUCs from 0.689 to 0.988 for 12 months and AUCs from 0.713 to 0.973 for 24 months). The best prediction was for genitourinary, head and neck, lung, skin, and upper gastrointestinal tumours. Conclusions: Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes. Importantly, the approach described made use of digital data that is already routinely collected but underexploited by clinical health systems

Emerging pharmacotherapy for cancer patients with cognitive dysfunction

Advances in the diagnosis and multi-modality treatment of cancer have increased survival rates for many cancer types leading to an increasing load of long-term sequelae of therapy, including that of cognitive dysfunction. The cytotoxic nature of chemotherapeutic agents may also reduce neurogenesis, a key component of the physiology of memory and cognition, with ramifications for the patient's mood and other cognition disorders. Similarly radiotherapy employed as a therapeutic or prophylactic tool in the treatment of primary or metastatic disease may significantly affect cognition. A number of emerging pharmacotherapies are under investigation for the treatment of cognitive dysfunction experienced by cancer patients. Recent data from clinical trials is reviewed involving the stimulants modafinil and methylphenidate, mood stabiliser lithium, anti-Alzheimer's drugs memantine and donepezil, as well as other agents which are currently being explored within dementia, animal, and cell culture models to evaluate their use in treating cognitive dysfunction

The non-zero divisor graph of ring of integers modulo six and the hamiltonian quaternion over integers modulo two

The study of graph theory was introduced and widely researched since many practical problems can be represented by graphs. A non-zero divisor graph is a graph in which its set of vertices is the non-zero elements of the ring and the vertices x and y are adjacent if and only if xy ≠ 0. In this study, we introduced the non-zero divisor graphs of some finite commutative rings in specific the ring of in tegers modulo 6, 6 and ring of Hamiltonian quaternion, (2). First, the non-zero divisors of the commutative rings are found. Then, the non-zero divisor graphs are constructed. Finally, some properties of the graph, including the chromatic number, clique number, girth and the diameter are obtained

Using lithium as a neuroprotective agent in patients with cancer

Neurocognitive impairment is being increasingly recognized as an important issue in patients with cancer who develop cognitive difficulties either as part of direct or indirect involvement of the nervous system or as a consequence of either chemotherapy-related or radiotherapy-related complications. Brain radiotherapy in particular can lead to significant cognitive defects. Neurocognitive decline adversely affects quality of life, meaningful employment, and even simple daily activities. Neuroprotection may be a viable and realistic goal in preventing neurocognitive sequelae in these patients, especially in the setting of cranial irradiation. Lithium is an agent that has been in use for psychiatric disorders for decades, but recently there has been emerging evidence that it can have a neuroprotective effect.This review discusses neurocognitive impairment in patients with cancer and the potential for investigating the use of lithium as a neuroprotectant in such patients.<br /

The evolutionary pattern of mutations in glioblastoma reveals therapy-mediated selection

Glioblastoma presents as a heterogeneous disease with poor prognosis despite the use of multimodal therapy. Analysis of genomic DNA changes between initial diagnosis and recurrence in response to standard treatment protocols would enhance understanding of disease progression and better inform new treatment strategies. A cohort of 21 patients with primary glioblastoma were examined between diagnosis and first recurrence. This study presented a rare opportunity to characterize molecular alterations in tumors observed in three patients who received no therapeutic intervention, other than surgery, offering a unique control. We focused this study by comparing the dynamic mutation profiles between the primary tumors and their matched recurrent counterparts. Molecular profiling of tumors was performed using multiplexed targeted deep sequencing of 409 well characterized cancer-associated genes, achieving a mean read depth of 1272 x. Three levels of evidence suggested an evolutionary pattern consistent with a response to therapy-mediated selection pressures exists in treated patients: 1) variant burden was reduced in recurrent tumors, 2) neutral evolutionary dynamics apparent in untreated tumors shifted toward a non-neutral mode of evolution in treated patients at recurrence, and 3) the recurrent tumor of one patient displayed an increased mutation rate attributable to a temozolomide-associated hypermutator phenotype. Our observations suggest that current treatment modalities are likely to fail in achieving long term remission with the majority of relapse samples containing distinct mutations when compared to primary diagnostic samples. Oncotarget 2018 9(8):7844-7858

Using lithium as a neuroprotective agent in patients with cancer

Neurocognitive impairment is being increasingly recognized as an important issue in patients with cancer who develop cognitive difficulties either as part of direct or indirect involvement of the nervous system or as a consequence of either chemotherapy-related or radiotherapy-related complications. Brain radiotherapy in particular can lead to significant cognitive defects. Neurocognitive decline adversely affects quality of life, meaningful employment, and even simple daily activities. Neuroprotection may be a viable and realistic goal in preventing neurocognitive sequelae in these patients, especially in the setting of cranial irradiation. Lithium is an agent that has been in use for psychiatric disorders for decades, but recently there has been emerging evidence that it can have a neuroprotective effect.This review discusses neurocognitive impairment in patients with cancer and the potential for investigating the use of lithium as a neuroprotectant in such patients.<br /

Radiotherapy combined with nivolumab or temozolomide for newly diagnosed glioblastoma with unmethylated MGMT promoter: An international randomized phase III trial

BACKGROUND: Addition of temozolomide (TMZ) to radiotherapy (RT) improves overall survival (OS) in patients with glioblastoma (GBM), but previous studies suggest that patients with tumors harboring an unmethylated MGMT promoter derive minimal benefit. The aim of this open-label, phase III CheckMate 498 study was to evaluate the efficacy of nivolumab (NIVO) + RT compared with TMZ + RT in newly diagnosed GBM with unmethylated MGMT promoter. METHODS: Patients were randomized 1:1 to standard RT (60 Gy) + NIVO (240 mg every 2 weeks for eight cycles, then 480 mg every 4 weeks) or RT + TMZ (75 mg/m2 daily during RT and 150-200 mg/m2/day 5/28 days during maintenance). The primary endpoint was OS. RESULTS: A total of 560 patients were randomized, 280 to each arm. Median OS (mOS) was 13.4 months (95% CI, 12.6 to 14.3) with NIVO + RT and 14.9 months (95% CI, 13.3 to 16.1) with TMZ + RT (hazard ratio [HR], 1.31; 95% CI, 1.09 to 1.58; P = .0037). Median progression-free survival was 6.0 months (95% CI, 5.7 to 6.2) with NIVO + RT and 6.2 months (95% CI, 5.9 to 6.7) with TMZ + RT (HR, 1.38; 95% CI, 1.15 to 1.65). Response rates were 7.8% (9/116) with NIVO + RT and 7.2% (8/111) with TMZ + RT; grade 3/4 treatment-related adverse event (TRAE) rates were 21.9% and 25.1%, and any-grade serious TRAE rates were 17.3% and 7.6%, respectively. CONCLUSIONS: The study did not meet the primary endpoint of improved OS; TMZ + RT demonstrated a longer mOS than NIVO + RT. No new safety signals were detected with NIVO in this study. The difference between the study treatment arms is consistent with the use of TMZ + RT as the standard of care for GBM.ClinicalTrials.gov NCT02617589