No abstract

Translocations involving PLAG1 occur in several tumors, most commonly pleomorphic adenoma and lipoblastoma. Recently, a distinctive soft tissue tumor with a PLAG1 fusion has been reported in the pediatric age group. These are low grade tumors with a fibroblastic or mixed fibroblastic and myxoid morphology but no other lines of differentiation. They are typically immunopositive for desmin and CD34. The partner genes for these tumors have included YWHAZ, EEF1A1, ZFHX4l, CHCHD7, and PCMTD1. We report another case of this fibromyxoid tumor with a PLAG1 fusion, this time with COL3A1 as the partner gene. The fusion placed expression of a full‐length PLAG1 protein under the control of the constitutively active COL3A1 promoter. Overexpression of PLAG1 was confirmed by diffusely positive immunostaining for PLAG1. The most novel aspect of this tumor is the intracranial location. Opinion has been divided over whether these tumors are a specific entity, or related to lipoblastoma, since that tumor also typically occurs in soft tissue in the pediatric age group and shows many of the same gene fusions. However, lipoblastoma has never been reported in an intracranial location and, thus, our case provides compelling evidence that this fibromyxoid tumor is indeed a distinct entity.

Neuroblastoma, the most common extracranial solid tumor in infancy, shows marked biological heterogeneity. Multiple prognostic markers are combined to risk-stratify neuroblastoma patients for treatment. One marker assesses histology, dividing patients into favorable and unfavorable categories based, in part, on the mitosis-karyorrhexis index (MKI). The recommended scoring of 5000 cells is, however, time-consuming and observer-dependent, and accurate counts may not always be performed. In the present study, we investigated using MIB-1 as a surrogate marker for the MKI. Twenty-five cases of neuroblastoma, ranging from low to high MKI, were immunostained for MIB-1. A total of 375 microscopic fields were digitally captured with > 100,000 cells scored. The MIB-1 index was determined by image analysis and MKI, by manual counting of the same immunostained fields. There was a significant correlation between the MIB-1 index and MKI comparing all fields (r = 0.7869, P < 0.01) and an even better correlation comparing individual cases (r = 0.9147, P < 0.01). Using a linear regression model, a formula was generated to calculate MKI from the MIB-1 index as follows: MKI = (MIB-1 index × 0.124) + 1.412. With this formula, a low MKI corresponds to an MIB-1 index < 4.74, intermediate MKI to an MIB-1 index of 4.74 to 20.87, and high MKI to an MIB-1 index > 20.87. For comparison, the calculations were repeated using a manual MIB-1 count on the same images. Similar significant correlations were obtained, with nearly identical cutoff values for MKI categories. This approach can facilitate determination of the MKI by assessing the MIB-1 index, either by image analysis or manual counting.