Comparative assessment of 5 methods (methylation-specific polymerase chain reaction, MethyLight, pyrosequencing, methylation-sensitive high-resolution melting, and immunohistochemistry) to analyze O6-methylguanine-DNA-methyltranferase in a series of 100 glioblastoma patients

Clinical variables serve as prognostic factors in a model for survival from glioblastoma multiforme: an observational study of a cohort of consecutive non-selected patients from a single institution

Background

Although implementation of temozolomide (TMZ) as a part of primary therapy for glioblastoma multiforme (GBM) has resulted in improved patient survival, the disease is still incurable. Previous studies have correlated various parameters to survival, although no single parameter has yet been identified. More studies and new approaches to identify the best and worst performing patients are therefore in great demand.

Methods

This study examined 225 consecutive, non-selected GBM patients with performance status (PS) 0–2 receiving postoperative radiotherapy with concomitant and adjuvant TMZ as primary therapy. At relapse, patients with PS 0–2 were mostly treated by reoperation and/or combination with bevacizumab/irinotecan (BEV/IRI), while a few received TMZ therapy if the recurrence-free period was >6 months.

Results

Median overall survival and time to progression were 14.3 and 8.0 months, respectively. Second-line therapy indicated that reoperation and/or BEV/IRI increased patient survival compared with untreated patients and that BEV/IRI was more effective than reoperation alone. Patient age, ECOG PS, and use of corticosteroid therapy were significantly correlated with patient survival and disease progression on univariate analysis, whereas p53, epidermal growth factor receptor, and O⁶-methylguanine-DNA methyltransferase expression (all detected by immunohistochemistry), tumor size or multifocality, and extent of primary operation were not. A model based on age, ECOG PS, and corticosteroids use was able to predict survival probability for an individual patient.

Conclusion

The survival of RT/TMZ-treated GBM patients can be predicted based on patient age, ECOG PS, and corticosteroid therapy status.

Double-labelling immunohistochemistry for MGMT and a "cocktail" of non-tumourous elements is a reliable, quick and easy technique for inferring methylation status in glioblastomas and other primary brain tumours

Background

Our aim was to develop a new protocol for MGMT immunohistochemistry with good agreement between observers and good correlation with molecular genetic tests of tumour methylation. We examined 40 primary brain tumours (30 glioblastomas and 10 oligodendroglial tumours) with our new technique, namely double-labelling immunohistochemistry for MGMT and a "cocktail" of non-tumour antigens (CD34, CD45 and CD68). We compared the results with single-labelling immunohistochemistry for MGMT and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA, a recognised molecular genetic technique which we applied as the gold-standard for the methylation status).

Results

Double-labelling immunohistochemistry for MGMT produced a visual separation of tumourous and non-tumourous elements on the same histological slide, making it quick and easy to determine whether tumour cell nuclei were MGMT-positive or MGMT-negative (and thereby infer the methylation status of the tumour). We found good agreement between observers (kappa 0.76) and within observer (kappa 0.84). Furthermore, double-labelling showed good specificity (80%), sensitivity (73.33%), positive predictive value (PPV, 83.33%) and negative predictive value (NPV, 68.75%) compared to MS-MLPA. Double-labelling was quicker and easier to assess than single-labelling and it outperformed quantitative computerised image analysis of MGMT single-labelling in terms of sensitivity, specificity, PPV and NPV.

Conclusions

Double-labelling immunohistochemistry for MGMT and a cocktail of non-tumourous elements provides a "one look" method for determining whether tumour cell nuclei are MGMT-positive or MGMT-negative. This can be used to infer the methylation status of the tumour. There is good observer agreement and good specificity, sensitivity, PPV and NPV compared to a molecular gold-standard.

Incorporation of prognostic and predictive factors into glioma clinical trials

Treatment of brain tumors is increasingly informed by biomarkers that predict patient prognosis and response to therapy. While this progress represents a great opportunity for the field of neuro-oncology, it also presents significant challenges. Biomarkers are not straightforward to identify, and previously used clinical trial paradigms are poorly suited to the task of identifying treatments effective only in selected subsets of patients. Unless investigators adapt new tools and procedures that better account for the biological diversity of gliomas, future clinical trials run the dual risk of missing important treatment effects and exposing patients to interventions destined to prove ineffective for their tumors. In this article, we will review the progress made in the past decade with respect to biomarkers in neuro-oncology, address barriers to ongoing progress, and discuss clinical trial designs that may prove useful in moving neuro-oncology fully into the era of personalized medicine.

O6-methylguanine-DNA methyltransferase (MGMT) immunohistochemistry as a predictor of resistance to temozolomide in primary CNS lymphoma

Temozolomide, an alkylating agent, has shown promise in treating primary central nervous system lymphoma (PCNSL). The enzyme O(6)-methylguanine-DNA methyltransferase (MGMT) repairs alkylating damage, such as that induced by temozolomide. We hypothesized that MGMT immunohistochemistry would predict resistance to temozolomide in PCNSL. A retrospective study of newly-diagnosed and recurrent PCNSL patients treated at our institution was conducted to study the predictive value of MGMT immunohistochemistry for response to temozolomide. 20 patients who were treated with temozolomide as a single agent were identified during the study time period. 6/20 patients demonstrated a response, corresponding to an objective response rate of 30 % (95 % CI 8-52). Five patients with low MGMT level (<30 %) showed a response to temozolomide. Only one of 10 patients (10 %) with high MGMT level (≥30 %) exhibited a response to temozolomide. Small sample numbers precluded formal statistical comparisons. Two patients with complete response remain alive without progressive disease 6.7 and 7.2 years after temozolomide initiation. Immunohistochemistry can be performed on small biopsies to selectively assess MGMT status in tumor versus surrounding inflammation. MGMT analysis by immunohistochemistry may predict response to temozolomide in PCNSL and should be prospectively investigated.

HPV16 L1 and L2 DNA methylation predicts high-grade cervical intraepithelial neoplasia in women with mildly abnormal cervical cytology

DNA methylation changes in human papillomavirus type 16 (HPV16) DNA are common and might be important for identifying women at increased risk of cervical cancer. Using recently published data from Costa Rica we developed a classification score to differentiate women with cervical intraepithelial neoplasia grade 2 or 3 (CIN2/3) from those with no evident high-grade lesions. Here, we aim to investigate the performance of the score using data from the UK. Exfoliated cervical cells at baseline and 6-months follow-up were analyzed in 84 women selected from a randomized clinical trial of women undergoing surveillance for low-grade cytology. Selection of women for the methylation study was based on detectable HPV16 in the baseline sample. Purified DNA was bisulfite converted, amplified and pyrosequenced at selected CpG sites in the viral genome (URR, E6, L1 and L2), with blinding of laboratory personnel to the clinical data. The primary measure was a predefined score combining the mean methylation in L1 and any methylation in L2. At the second follow-up visit, 73/84 (87%) women were HPV16 positive and of these 25 had a histopathological diagnosis of CIN2/3. The score was significantly associated with CIN2/3 (area under curve = 0.74, p = 0.002). For a cutoff with 92% sensitivity, colposcopy could have been avoided in 40% (95% CI 27–54%) of HPV16 positive women without CIN2/3; positive predictive value was 44% (32–58%) and negative predictive value was 90% (71–97%). We conclude that quantitative DNA methylation assays could help to improve triage among HPV16 positive women.

Imaging descriptors improve the predictive power of survival models for glioblastoma patients

BACKGROUND

Because effective prediction of survival time can be highly beneficial for the treatment of glioblastoma patients, the relationship between survival time and multiple patient characteristics has been investigated. In this paper, we investigate whether the predictive power of a survival model based on clinical patient features improves when MRI features are also included in the model.

METHODS

The subjects in this study were 82 glioblastoma patients for whom clinical features as well as MR imaging exams were made available by The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA). Twenty-six imaging features in the available MR scans were assessed by radiologists from the TCGA Glioma Phenotype Research Group. We used multivariate Cox proportional hazards regression to construct 2 survival models: one that used 3 clinical features (age, gender, and KPS) as the covariates and 1 that used both the imaging features and the clinical features as the covariates. Then, we used 2 measures to compare the predictive performance of these 2 models: area under the receiver operating characteristic curve for the 1-year survival threshold and overall concordance index. To eliminate any positive performance estimation bias, we used leave-one-out cross-validation.

RESULTS

The performance of the model based on both clinical and imaging features was higher than the performance of the model based on only the clinical features, in terms of both area under the receiver operating characteristic curve (P < .01) and the overall concordance index (P < .01).

CONCLUSIONS

Imaging features assessed using a controlled lexicon have additional predictive value compared with clinical features when predicting survival time in glioblastoma patients.

Comparison study of MS-HRM and pyrosequencing techniques for quantification of APC and CDKN2A gene methylation

There is increasing interest in the development of cost-effective techniques for the quantification of DNA methylation biomarkers. We analyzed 90 samples of surgically resected colorectal cancer tissues for APC and CDKN2A promoter methylation using methylation sensitive-high resolution melting (MS-HRM) and pyrosequencing. MS-HRM is a less expensive technique compared with pyrosequencing but is usually more limited because it gives a range of methylation estimates rather than a single value. Here, we developed a method for deriving single estimates, rather than a range, of methylation using MS-HRM and compared the values obtained in this way with those obtained using the gold standard quantitative method of pyrosequencing. We derived an interpolation curve using standards of known methylated/unmethylated ratio (0%, 12.5%, 25%, 50%, 75%, and 100% of methylation) to obtain the best estimate of the extent of methylation for each of our samples. We observed similar profiles of methylation and a high correlation coefficient between the two techniques. Overall, our new approach allows MS-HRM to be used as a quantitative assay which provides results which are comparable with those obtained by pyrosequencing.

BMP2 sensitizes glioblastoma stem-like cells to Temozolomide by affecting HIF-1α stability and MGMT expression

Glioblastoma multiforme (GBM) is the most common brain tumour, characterized by a central and partially necrotic (i.e., hypoxic) core enriched in cancer stem cells (CSCs). We previously showed that the most hypoxic and immature (i.e., CSCs) GBM cells were resistant to Temozolomide (TMZ) in vitro, owing to a particularly high expression of O6-methylguanine-DNA-methyltransferase (MGMT), the most important factor associated to therapy resistance in GBM. Bone morphogenetic proteins (BMPs), and in particular BMP2, are known to promote differentiation and growth inhibition in GBM cells. For this reason, we investigated whether a BMP2-based treatment would increase TMZ response in hypoxic drug-resistant GBM-derived cells. Here we show that BMP2 induced strong differentiation of GBM stem-like cells and subsequent addition of TMZ caused dramatic increase of apoptosis. Importantly, we correlated these effects to a BMP2-induced downregulation of both hypoxia-inducible factor-1α (HIF-1α) and MGMT. We report here a novel mechanism involving the HIF-1α-dependent regulation of MGMT, highlighting the existence of a HIF-1α/MGMT axis supporting GBM resistance to therapy. As confirmed from this evidence, over-stabilization of HIF-1α in TMZ-sensitive GBM cells abolished their responsiveness to it. In conclusion, we describe a HIF-1α-dependent regulation of MGMT and suggest that BMP2, by down-modulating the HIF-1α/MGMT axis, should increase GBM responsiveness to chemotherapy, thus opening the way to the development of future strategies for GBM treatment.

MGMT testing for glioma in clinical laboratories: discordance with methylation analyses prevents the implementation of routine immunohistochemistry

PURPOSE

Glioblastoma is a universally fatal cancer of the central nervous system which responds poorly to treatment. MGMT has potential as a predictive biomarker in glioblastoma patients to determine treatment response. However, methods of measuring MGMT are currently unsatisfactory, and as such, use of this marker has not translated well into the clinic. This paper aims to review current methodology of MGMT measurement, with a focus on immunohistochemistry as a potential way forward. TOPICS AND METHODS: Studies of glioma patients where MGMT immunohistochemistry was undertaken, as well as the literature surrounding methylation analyses and the regulation of MGMT, were reviewed.

RESULTS

All methods of measuring MGMT were disputed in some way in the literature. A trend of discordance between methylation analyses and protein analyses was present. There is a lack of standardisation in the measurement of MGMT, and as a result, it seems that there are highly variable results.

CONCLUSIONS

No single method of MGMT analysis has emerged as a clear choice for routine clinical testing of MGMT in glioma patients. Although methylation analyses are favoured, their expense and inaccessibility are barriers to their use in routine clinical practice. More research into immunohistochemistry is needed to determine whether it can serve as a reliable and cost-effective alternative to methylation analyses.

Clinical Neuropathology Practice News 4-2012: levels of evidence for brain tumor biomarkers

The National Comprehensive Cancer Network (NCCN) recently published a task force report on the evaluation of the clinical utility of tumor biomarkers in oncology. In this report, common terminology and the use of levels of evidence scores to aid the evaluation of biomarker tests in oncology were proposed. Furthermore, the task force applied a level of evidence system to selected biomarkers of several cancer types. According to this system, the highest level of evidence, IA, is granted to a biomarker only if it has been evaluated in at least one adequately powered and specifically designed prospective controlled trial. For gliomas, only 1p/19q testing in oligodendroglial tumors was classified as IA by the NCCN task force. For all of the following biomarkers the present evidence level for clinical utility was regarded as lower than that of 1p/19q status: MGMT gene promoter methylation testing (glioblastoma), IDH mutation testing (diffusely growing gliomas), BRAF fusion testing (pilocytic astrocytoma) and CIMP testing (diffusely growing gliomas). The task force acknowledged that the exact application of levels of evidence needs further refinement. To our mind, the implementation of a brain tumor expert panel seems vital to evaluate the evidence levels of neurooncological biomarkers according to generally accepted criteria on a regular basis. Systematic identification of current research needs and widely accepted up-to-date recommendations for efficient biomarker application in everyday practice could be gained.