Faculty Bibliography

Liposarcoma is a malignant soft tissue tumor with several subtypes, the most common of which is well-differentiated liposarcoma (WDL) or atypical lipomatous tumor (ALT). WDL/ALTs are further divided into three histological subtypes, including lipoma-like, sclerosing, and inflammatory. While the majority of these tumors are predominantly fatty, the sclerosing variant demonstrates diverse histologic and radiographic characteristics, including variable amounts of fibrosis and fat. Because of this histological variability and relative rarity, the sclerosing WDL/ALT can present diagnostic dilemmas. We present two cases of sclerosing WDL/ALT, both of which demonstrated high degrees of fibrosis and a paucity of fat, mimicking desmoid fibromatosis and other fibrotic soft tissue tumors. Thus, it is important for radiologists to be aware of the subtypes of liposarcoma and their unique characteristics, and to consider sclerosing WDL/ALT in cases of fibrotic soft tissue tumors.

PURPOSE/OBJECTIVE:Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep learning strategies on histology samples to predict outcome for OSA in the neoadjuvant setting. EXPERIMENTAL DESIGN/METHODS:Our study relies on a training cohort from New York University (New York, NY) and an external cohort from Charles university (Prague, Czechia). We trained and validated the performance of a supervised approach that integrates neural network predictions of necrosis/tumor content, and compared predicted overall survival (OS) using Kaplan-Meier curves. Furthermore, we explored morphology-based supervised and self-supervised approaches to determine whether intrinsic histomorphological features could serve as a potential marker for OS in the setting of neoadjuvant. RESULTS:Excellent correlation between the trained network and the pathologists was obtained for the quantification of necrosis content (R2=0.899, r=0.949, p < 0.0001). OS prediction cutoffs were consistent between pathologists and the neural network (22% and 30% of necrosis, respectively). Morphology-based supervised approach predicted OS with p-value=0.0028, HR=2.43 [1.10-5.38]. The self-supervised approach corroborated the findings with clusters enriched in necrosis, fibroblastic stroma, and osteoblastic morphology associating with better OS (lg2HR; -2.366; -1.164; -1.175; 95% CI=[-2.996; -0.514]). Viable/partially viable tumor and fat necrosis were associated with worse OS (lg2HR;1.287;0.822;0.828; 95% CI=[0.38-1.974]). CONCLUSIONS:Neural networks can be used to automatically estimate the necrosis to tumor ratio, a quantitative metric predictive of survival. Furthermore, we identified alternate histomorphological biomarkers specific to the necrotic and tumor regions themselves which can be used as predictors.

Histologic grading of tumors is associated with prognosis in many organs. In the lung, the most recent grading system proposed by International association for the Study of Lung Cancer (IASLC) and adopted by the World Health Organization (WHO) incorporates the predominant histologic pattern, as well as the presence of high-grade architectural patterns (solid, micropapillary, and complex glandular pattern) in proportions >20% of the tumor surface. This system has shown improved prognostic ability when compared with the prior grading system based on the predominant pattern alone, across different patient populations. Interobserver agreement is moderate to excellent, depending on the study. IASLC/WHO grading system has been shown to correlate with molecular alterations and PD-L1 expression in tumor cells. Recent studies interrogating gene expression has shown correlation with tumor grade and molecular alterations in the tumor microenvironment that can further stratify risk of recurrence. The use of machine learning algorithms to grade nonmucinous adenocarcinoma under this system has shown accuracy comparable to that of expert pulmonary pathologists. Future directions include evaluation of tumor grade in the context of adjuvant and neoadjuvant therapies, as well as the development of better prognostic indicators for mucinous adenocarcinoma.

Mycobacterial spindle cell pseudotumors (MSPs) are a rare and diagnostically challenging manifestation of non-tuberculous mycobacterial (NTM) infections. Proper recognition of these pseudotumors is important because they are treatable and benign. In this study, we evaluated the morphologic patterns of MSPs to improve their pathologic identification. Clinical and morphologic features of 14 MSPs were analyzed. Histologic factors evaluated included the architectural growth pattern of spindled or epithelioid macrophages, granulomas and their location within the lesion, neutrophilic microabscesses, multinucleated giant cells, necrosis, and effacement of background tissue. The composition of inflammatory infiltrates, organism density by acid-fast staining, and stromal changes were also assessed. In addition, 8 of 14 cases underwent molecular microbiology identification by a clinical amplicon-sequencing assay for non-tuberculous mycobacteria. MSP sites included 2 bowel, 10 lymph nodes, 1 liver, and 1 extremity. Cases with available clinical history (n=10) all occurred in immunocompromised patients. All demonstrated effacement of normal structures with spindled cells arranged in a storiform or fascicular architectural pattern. In addition, all cases showed lymphocytic inflammation, with prominent concurrent neutrophilic inflammation in 50% (7/14) of cases. Other morphologic findings included foamy histiocytes (64%, 9/14), peripherally situated granulomas (21%, 3/14), and neutrophilic microabscesses (21%, 3/14). All tested cases were positive for NTM by PCR methods. Mycobacterium avium was the most commonly isolated pathogen (6/8). Mycobacterial spindle cell pseudotumors show predominantly spindled morphology that may be mistaken as a neoplasm. Surgical pathologists who evaluate lymph nodes, soft tissue, and gastrointestinal tissues should be aware of this spindled tumefactive phenomenon in the setting of immunocompromised patients. Recognition of key morphologic features of neutrophilic inflammation, peripheral granulomas, or foamy histiocytes within a spindled lesion can help guide the pathologist to a correct diagnosis of an inflammatory process secondary to infection rather than a spindle cell neoplasm. Accurate diagnosis to facilitate appropriate antimicrobial and/or surgical therapy requires a comprehensive evaluation combining clinical, histopathologic, and microbiological findings.

HEY1-NCOA2 fusion is most described in mesenchymal chondrosarcoma. This is the first case report of a primary renal spindle cell neoplasm of uncertain malignant potential with a HEY1::NCOA2 fusion identified by Fusionplex RNA-sequencing that is histologically distinct from mesenchymal chondrosarcoma. The neoplasm was identified in a 33-year-old woman without significant past medical history who underwent partial nephrectomy for an incidentally discovered renal mass. The histologic features of the mass included spindle cells with variable cellularity and monotonous bland cytology forming vague fascicles and storiform architecture within a myxoedematous and collagenous stroma with areas of calcification. The morphologic and immunophenotypic features were not specific for any entity but were most similar to low-grade fibromyxoid sarcoma. To date, the patient has not had recurrence, and the malignant potential of the neoplasm is uncertain.

We describe a case of a myoepithelial carcinoma of the superficial parotid gland in a 46-year-old male harboring a novel CTCF::NCOA2 gene fusion. To our knowledge, this novel gene fusion has not been described previously in myoepithelial carcinoma. A 46-year-old male patient presented with a mass involving the superficial left parotid gland with extension into the external auditory canal (EAC) and erosion of the conchal cartilage. Histologically, the neoplasm was composed of uniform spindled, epithelioid/ovoid cells arranged in cords and nests within hyalinized to myxoid stroma. On immunohistochemistry (IHC), the tumor cells demonstrated patchy and variable staining for low molecular weight cytokeratin (CAM5.2), pan-cytokeratin (OSCAR), and S-100. Overall, the morphological and immunohistochemical attributes supported a locally aggressive tumor of myoepithelial differentiation consistent with myoepithelial carcinoma. Molecular analysis using a custom 115-gene gene panel by targeted RNA sequencing, showed an in-frame CTCF::NCOA2 fusion. In addition to reporting this novel fusion in myoepithelial carcinoma, we also discuss relevant differential diagnosis, and provide a brief review of NCOA2 gene function in both normal and neoplastic contexts.

The 2020 release of the WHO Classification of Soft Tissue and Bone Tumors, 5th edition, contains several changes driven by new knowledge in the field. These include reclassification of some entities, refinement of risk classification systems, and the inclusion of novel disease processes, many of which are driven by recurrent gene fusions. The most notable changes are described here.

Malignant peripheral nerve sheath tumors ( MPNSTs) are aggressive tumors with poor prognosis that do not typically respond well to standard chemotherapy. Recently, point mutations involving BRAF V600E have been demonstrated in a subset of MPNST, offering the possibility of targeted treatment. However, the reported prevalence of these alterations is variable. Mutations involving NRAS, which is also involved in the MAPK/ERK pathway and amenable to targeted inhibitors, have not been well characterized in MPNST. In this study, we validated droplet digital polymerase chain reaction for the detection of BRAF V600E and NRAS Q61 mutations and evaluate the prevalence of BRAF V600E and NRAS Q61 mutations in 79 cases of MPNST, including 45 sporadic, 27 NF-1 associated, and 7 radiation-associated tumors. We detected actionable BRAF or NRAS mutations in 3 of 44 sporadic MPNSTs (6.8%), including 2 BRAF V600 and 1 NRAS Q61 mutations, as well as 1 NRAS Q61 mutation in a tumor that was ultimately considered to represent melanoma. These 3 cases with positive mutations were exclusively in sporadic, high-grade MPNST (FNCLCC grade 3 of 3), with a prevalence of 11.5% in this group (3.8% NRAS Q61 mutations and 7.7% BRAF V600 mutations). None of the tumors associated with NF-1 or prior radiation had detectable mutations in the genes tested. Overall, the prevalence of these alterations offers the possibility of targeted therapy in this aggressive type of sarcoma and suggests the potential benefit of routine clinical testing.

Desmoid fibromatosis (DF) is a locally aggressive soft tissue neoplasm with frequent recurrences. DF is characterized by alterations in the Wnt/β-catenin pathway, with the majority showing sporadic mutations in CTNNB1 , whereas others have germline mutations in APC . Immunohistochemical staining for β-catenin is often difficult to interpret and can be negative in up to 30% of cases. Prior studies have shown that some DFs lacking nuclear expression of β-catenin may carry activating CTNNB1 mutations. Droplet digital polymerase chain reaction (ddPCR) has been used effectively in detecting mutations in formalin-fixed, paraffin-embedded (FFPE) samples of various cancer types. In this study, we assess the diagnostic utility of ddPCR to detect CTNNB1 mutations in DF with β-catenin expression on immunohistochemistry (IHC), as well as in diagnostically challenging cases. Of the 28 DFs with nuclear β-catenin expression by IHC, 24 cases showed a CTNNB1 mutation by ddPCR using primers against the most common point mutations in CTNNB1 . The most frequent mutation was T41A (n=14; 50%), followed by S45F (n=8; 33%) and S45P (n=3;12%). We identified 8 additional (myo)fibroblastic lesions of uncertain classification, which were negative for nuclear β-catenin expression by IHC. We detected CTNNB1 mutations in 3 unknown lesions, including S45F (n=2) and S45P (n=1). ddPCR is a sensitive, rapid and cost-efficient methodology to detect common CTNNB1 mutations in DF, especially in diagnostically challenging cases.