A Systematic Approach to the Cutaneous Lymphoid Infiltrates: A Clinical, Morphologic, and Immunophenotypic Evaluation

CONTEXT: The evaluation of cutaneous lymphoid infiltrates, both neoplastic and inflammatory, occurs very frequently in routine dermatopathologic examination and consultation practices. The tough cutaneous lymphoid infiltrate is feared by many pathologists; skin biopsies are relatively small, whereas diagnostic possibilities are relatively broad. It is true that cutaneous lymphomas can be difficult to diagnose and that in many circumstances multiple biopsies are required to establish a correct diagnostic interpretation. As a reminder, one should understand that low-grade cutaneous lymphomas are indolent disorders that usually linger for decades and that therapy does not result in disease cure. It is also important to remember that in most circumstances, those patients will die from another process that is completely unrelated to a diagnosis of skin lymphoma (even in the absence of specific therapy). OBJECTIVE: To use a clinicopathologic, immunophenotypic, and molecular approach in the evaluation of common lymphocytic infiltrates. DATA SOURCES: An in-depth analysis of updated literature in the field of cutaneous lymphomas was done, with particular emphasis on updated terminology from the most recent World Health Organization classification of skin and hematologic tumors. CONCLUSIONS: A diagnosis of cutaneous lymphoid infiltrates can be adequately approached using a systematic scheme following the proposed ABCDE system. Overall, cutaneous T- and B-cell lymphomas are rare and reactive infiltrates are more common. Evaluation of lymphoid proliferations should start with a good sense of knowledge of the clinical presentation of the lesions, the clinical differential considerations, and a conscientious and appropriate use of immunohistochemistry and molecular tools

Molecular-Based Recursive Partitioning Analysis Model for Glioblastoma in the Temozolomide Era: A Correlative Analysis Based on NRG Oncology RTOG 0525.

Importance: There is a need for a more refined, molecularly based classification model for glioblastoma (GBM) in the temozolomide era. Objective: To refine the existing clinically based recursive partitioning analysis (RPA) model by incorporating molecular variables. Design, Setting, and Participants: NRG Oncology RTOG 0525 specimens (n = 452) were analyzed for protein biomarkers representing key pathways in GBM by a quantitative molecular microscopy-based approach with semiquantitative immunohistochemical validation. Prognostic significance of each protein was examined by single-marker and multimarker Cox regression analyses. To reclassify the prognostic risk groups, significant protein biomarkers on single-marker analysis were incorporated into an RPA model consisting of the same clinical variables (age, Karnofsky Performance Status, extent of resection, and neurologic function) as the existing RTOG RPA. The new RPA model (NRG-GBM-RPA) was confirmed using traditional immunohistochemistry in an independent data set (n = 176). Main Outcomes and Measures: Overall survival (OS). Results: In 452 specimens, MGMT (hazard ratio [HR], 1.81; 95% CI, 1.37-2.39; P < .001), survivin (HR, 1.36; 95% CI, 1.04-1.76; P = .02), c-Met (HR, 1.53; 95% CI, 1.06-2.23; P = .02), pmTOR (HR, 0.76; 95% CI, 0.60-0.97; P = .03), and Ki-67 (HR, 1.40; 95% CI, 1.10-1.78; P = .007) protein levels were found to be significant on single-marker multivariate analysis of OS. To refine the existing RPA, significant protein biomarkers together with clinical variables (age, Karnofsky Performance Status, extent of resection, and neurological function) were incorporated into a new model. Of 166 patients used for the new NRG-GBM-RPA model, 97 (58.4%) were male (mean [SD] age, 55.7 [12.0] years). Higher MGMT protein level was significantly associated with decreased MGMT promoter methylation and vice versa (1425.1 for methylated vs 1828.0 for unmethylated; P < .001). Furthermore, MGMT protein expression (HR, 1.84; 95% CI, 1.38-2.43; P < .001) had greater prognostic value for OS compared with MGMT promoter methylation (HR, 1.77; 95% CI, 1.28-2.44; P < .001). The refined NRG-GBM-RPA consisting of MGMT protein, c-Met protein, and age revealed greater separation of OS prognostic classes compared with the existing clinically based RPA model and MGMT promoter methylation in NRG Oncology RTOG 0525. The prognostic significance of the NRG-GBM-RPA was subsequently confirmed in an independent data set (n = 176). Conclusions and Relevance: This new NRG-GBM-RPA model improves outcome stratification over both the current RTOG RPA model and MGMT promoter methylation, respectively, for patients with GBM treated with radiation and temozolomide and was biologically validated in an independent data set. The revised RPA has the potential to contribute to improving the accurate assessment of prognostic groups in patients with GBM treated with radiation and temozolomide and to influence clinical decision making. Trial Registration: clinicaltrials.gov Identifier: NCT00304031