Mustafa Khasraw

Advances in the treatment of malignant gliomas.

Local control with surgery, radiation, and temozolomide chemotherapy remain the pillars of treatment for high-grade gliomas. Novel therapeutic strategies, including a variety of antiangiogenic agents, are under investigation. One of these agents, bevacizumab, was recently given accelerated approval by the US Food and Drug Administration as a single agent for recurrent glioblastoma. Recent trial results are generating important clinical questions regarding which patients to treat and when, and how best to monitor response. Encouraging results of recent studies are driving willingness to undertake aggressive treatment and to improve outcomes in this population. In this era, better understanding of biology, molecular aspects of cancer, and clinical trial methodology are crucial for clinicians. This review focuses on recent advances in the treatment malignant gliomas, especially antiangiogenic therapy.

Epirubicin: is it like doxorubicin in breast cancer? A clinical review.

Anthracyclines are among the most effective chemotherapy treatments available for various types of cancer. The anthracyclines commonly used in treatment of breast cancer are either epirubicin or doxorubicin. Epirubicin is an epimer of doxorubicin with important role in the chemotherapy treatment of both early and metastatic breast cancer. The efficacy of epirubicin is similar to doxorubicin while epirubicin has a different toxicity profile particularly in regard to cardiotoxicity. Epirubicin has been incorporated into most of the anthracycline containing chemotherapy combinations in well-conducted clinical trials involving large numbers of patients. It has also been investigated in studies involving the administration of epirubicin in dose-dense chemotherapy schedules. Short term follow up of dose-dense clinical trials demonstrated safety comparable to that of doxorubicin. This review summarizes published clinical trials investigating epirubicin in the treatment of early and advanced breast cancer.

Intracranial hemorrhage in patients with cancer treated with bevacizumab: the Memorial Sloan-Kettering experience

BACKGROUND Bevacizumab is a monoclonal antibody targeting vascular endothelial growth factor approved for recurrent glioblastoma (GBM), metastatic breast, colorectal and non-small-cell lung cancers (NSCLC). There has been a potentially increased risk of intracranial hemorrhage (ICH) in patients receiving bevacizumab. METHODS We retrospectively identified patients with ICH who received bevacizumab between 1 January 2001 and 10 January 2009. RESULTS We identified 1024 patients with ICH, 4191 patients who received bevacizumab and 12 (0.3%) who met both our criteria. There were eight women and four men with a median age of 66 years. Primary cancers were ovarian (n = 3), NSCLC (n = 3), colon (n = 1), angiosarcoma (n = 1) and GBM (n = 4). Intracranial tumors were present in 9 of the 12 patients; the remaining three (25%) had no evidence of intracranial pathology. Two hundred and fifty-seven patients with these same primary pathologies and brain tumors were treated with bevacizumab; ICH was seen in nine (3.7%), which was comparable to the 3.6% frequency seen in comparable patients not receiving bevacizumab. CONCLUSIONS ICH with bevacizumab treatment in this population is rare and does not appear to increase its frequency over the baseline rate of ICH in a comparable population. Most bevacizumab-related ICH occurs into central nervous system tumors but spontaneous hemorrhages were seen.

Neurological complications of systemic cancer

Neurological complications of systemic cancer-those arising outside the nervous system-can be distressing, disabling, and sometimes fatal. Diagnosis is often difficult because different neurological disorders may present with similar signs and symptoms. Furthermore, comorbid neurological illnesses, common in elderly patients with cancer, can complicate diagnosis. Early diagnosis and aggressive treatment can improve neurological symptoms and can substantially enhance a patients quality of life. We approach the problem of neurological complications of systemic cancer as would a neurologist: first by identifying the anatomical area or areas that are affected (ie, brain, spinal cord, peripheral nerve), then by evaluating the diagnostic approach, considering the symptoms and signs and including appropriate laboratory tests, and finally, by recommending treatment. We focus on disorders that are difficult to diagnose, need neurological consultation, and for which effective treatments exist.

Multicentre phase I/II study of PI-88, a heparanase inhibitor in combination with docetaxel in patients with metastatic castrate-resistant prostate cancer

BACKGROUND Docetaxel (Taxotere) improve survival and prostate-specific antigen (PSA) response rates in patients with metastatic castrate-resistant prostate cancer (CRPC). We studied the combination of PI-88, an inhibitor of angiogenesis and heparanase activity, and docetaxel in chemotherapy-naive CRPC. PATIENTS AND METHODS We conducted a multicentre open-label phase I/II trial of PI-88 in combination with docetaxel. The primary end point was PSA response. Secondary end points included toxicity, radiologic response and overall survival. Doses of PI-88 were escalated to the maximum tolerated dose; whereas docetaxel was given at a fixed 75 mg/m(2) dose every three weeks RESULTS Twenty-one patients were enrolled in the dose-escalation component. A further 35 patients were randomly allocated to the study to evaluate the two schedules in phase II trial. The trial was stopped early by the Safety Data Review Board due to a higher-than-expected febrile neutropenia of 27%. In the pooled population, the PSA response (50% reduction) was 70%, median survival was 61 weeks (6-99 weeks) and 1-year survival was 71%. CONCLUSIONS The regimen of docetaxel and PI-88 is active in CRPC but associated with significant haematologic toxicity. Further evaluation of different scheduling and dosing of PI-88 and docetaxel may be warranted to optimise efficacy with a more manageable safety profile.

EpCAM aptamer-mediated survivin silencing sensitized cancer stem cells to doxorubicin in a breast cancer model

Understanding the molecular basis of drug resistance and utilising this information to overcome chemoresistance remains a key challenge in oncology. Here we report that survivin, a key protein implicated in drug resistance, is overexpressed in cancer stem cell pool of doxorubicin-resistant breast cancer cells. Moreover, by utilising an active targeting system consisting of an RNA aptamer targeted against the epithelial cell adhesion molecule and a Dicer substrate survivin siRNA, we could deliver a high dose of the siRNA to cancer stem cells in xenograft tumours. Importantly, silencing of survivin with this aptamer-siRNA chimera in cancer stem cell population led to the reversal of chemoresistance, such that combined treatment with low dose of doxorubicin inhibited stemness, eliminated cancer stem cells via apoptosis, suppressed tumour growth, and prolonged survival in mice bearing chemoresistant tumours. This strategy for in vivo cancer stem cell targeting has wide application for future effective silencing of anti-death genes and in fact any dysregulated genes involved in chemoresistance and tumour relapse.

Immune checkpoint blockade as a potential therapeutic target: surveying CNS malignancies

BACKGROUND Expression of programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) across glioma grades is undocumented, and their interactions with commonly expressed genetic and epigenetic alterations are undefined but nonetheless highly relevant to combinatorial treatments. METHODS Patients with CNS malignancies were profiled by Caris Life Sciences from 2009 to 2016. Immunohistochemistry findings for PD-1 on tumor-infiltrating lymphocytes (TIL) and PD-L1 on tumor cells were available for 347 cases. Next-generation sequencing, pyrosequencing, immunohistochemistry, fragment analysis, and fluorescence in situ hybridization were used to determine isocitrate dehydrogenase 1 (IDH1), phosphatase and tensin homolog (PTEN), and tumor protein 53 mutational status, O(6)-DNA methylguanine-methyltransferase promoter methylation (MGMT-Me) status, PTEN expression, plus epidermal growth factor receptor variant III and 1p/19q codeletion status. RESULTS PD-1+ TIL expression and grade IV gliomas were significantly positively correlated (odds ratio [OR]: 6.363; 95% CI: 1.263, 96.236)-especially in gliosarcomas compared with glioblastoma multiforme (P = .014). PD-L1 expression was significantly correlated with tumor grade with all PD-L1+ cases (n = 21) being associated with grade IV gliomas. PD-1+ TIL expression and PD-L1 expression were significantly correlated (OR: 5.209; 95% CI: 1.555, 20.144). Mutations of PTEN, tumor protein 53, BRAF, IDH1, and epidermal growth factor receptor or MGMT-Me did not associate with increased intratumoral expression of either PD-1+ TIL or PD-L1 in glioblastoma multiforme even before false discovery rate correction for multiple comparison. CONCLUSIONS Targeting immune checkpoints in combination with other therapeutics based on positive biomarker selection will require screening of large patient cohorts.

Long-term use of temozolomide: Could you use temozolomide safely for life in gliomas?

Temozolomide (TMZ) is an alkylating agent used in the management of gliomas. Although TMZ is generally safe and acute toxicity is well documented, there are limited data on long-term toxicities. We present three patients with glioma; all patients started on TMZ after having progressed following primary treatment. These patients have continued TMZ for 5 years, 7 years and 8 years respectively. So far they have had no serious side effects. We discuss these patients while raising the question of prolonged TMZ use.

The need to examine metastatic tissue at the time of progression of breast cancer: is re-biopsy a necessity or a luxury?

Knowledge of estrogen receptor (ER), progesterone receptor (PgR) and human epidermal growth factor receptor-2 (HER2) status is necessary for determining the optimal treatment of breast cancer patients. At the same time, the discordance between marker profiles (ER/PR and HER2) of primary and metastatic breast cancer is well documented. Whether discordant cases are secondary to “clonal selection” in the face of targeted anti-estrogen or anti-HER2 therapy or whether they are a laboratory artifact is still debated; both scenarios are likely. This article outlines current modalities for ER, PR, and HER2 testing in primary breast carcinoma and its metastases and reviews prospective and retrospective studies that have addressed these issues, as well as recent advances in the field.

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.