Spitz melanocytic neoplasms with MLPH::ALK fusions: Report of two cases with previously unreported features and literature review.

ALK-fused Spitz melanocytic neoplasms are a distinct subgroup of melanocytic lesions exhibiting unique histopathologic characteristics. These lesions often manifest as exophytic or polypoid tumors, characterized by fusiform-to-epithelioid melanocytes arranged in a nested, fascicular, or plexiform growth pattern. Several fusion partners of the ALK gene have been identified in spitzoid melanocytic neoplasms, with TPM3 and DCTN1 being the most prevalent. Less common fusion partners include NPM1, TPR, CLIP1, GTF3C2, EEF2, MYO5A, KANK1, and EHBP1. The MLPH gene, which encodes melanophilin (MLPH), playing a crucial role in regulating skin pigmentation by acting as a linker between RAB27A and myosin Va during melanosome transport, has also recently been recognized as a rare fusion partner of ALK in Spitz melanocytic neoplasms. Currently, there exists a sparse documentation within English literature, illustrating a limited number of cases featuring MLPH::ALK fusion in Spitz melanocytic neoplasms. In this report, we present two additional cases, including a previously unreported instance of Spitz melanoma, contributing to the expanding knowledge on ALK-fused Spitz melanocytic neoplasms. In addition, we provide a comprehensive review of the clinical, histopathologic, and molecular features observed in documented cases with this novel fusion.

Machine learning applications and challenges in graft-versus-host disease: a scoping review.

PURPOSE OF REVIEW: This review delves into the potential of artificial intelligence (AI), particularly machine learning (ML), in enhancing graft-versus-host disease (GVHD) risk assessment, diagnosis, and personalized treatment. RECENT FINDINGS: Recent studies have demonstrated the superiority of ML algorithms over traditional multivariate statistical models in donor selection for allogeneic hematopoietic stem cell transplantation. ML has recently enabled dynamic risk assessment by modeling time-series data, an upgrade from the static, "snapshot" assessment of patients that conventional statistical models and older ML algorithms offer. Regarding diagnosis, a deep learning model, a subset of ML, can accurately identify skin segments affected with chronic GVHD with satisfactory results. ML methods such as Q-learning and deep reinforcement learning have been utilized to develop adaptive treatment strategies (ATS) for the personalized prevention and treatment of acute and chronic GVHD. SUMMARY: To capitalize on these promising advancements, there is a need for large-scale, multicenter collaborations to develop generalizable ML models. Furthermore, addressing pertinent issues such as the implementation of stringent ethical guidelines is crucial before the widespread introduction of AI into GVHD care.

Microreticular perineurioma: A new morphological subtype of a rare entity.

Perineurioma is a benign peripheral nerve sheath tumor. Several subtypes have been described, including plexiform, reticular, and sclerosing. The reticular variant has been previously described as having a net or lace-like growth pattern consisting of large anastomosing cords of spindle-shaped cells. We report a case of an 11-year-old male who presented with a 2-year history of a slowly enlarging, tan-white lesion on the finger. Microscopically, the lesion consisted of cells with ovoid nuclei and delicate, elongate cytoplasmic processes, arranged in a microreticular pattern. The lesional cells were markedly positive for epithelial membrane antigen and claudin-1. Based on these features and the unusual morphology, the case was called a microreticular perineuroma. The patient underwent complete excision of the lesion with no recurrence 9 months after follow-up. To our knowledge, this is the first reported case of this morphologic variant. Awareness of this entity is important to avoid inappropriate management.

Reactive Eccrine Syringofibroadenoma (ESFA) in Association With a Merkel Cell Carcinoma Excision Scar.

ABSTRACT: Eccrine syringofibroadenoma (ESFA) is a rare benign skin adnexal lesion of the acrosyringium of eccrine sweat ducts. Reactive ESFA, a subtype of ESFA, is usually associated with non-neoplastic cutaneous dermatoses or neoplastic skin tumors. Clinically, the lesions can be solitary or multiple, pink, or skin-colored coalescing papules or nodules of variable sizes. Histopathologically, this tumor is composed of numerous anastomosing cords of monomorphic cuboidal epithelial cells with eccrine duct formation. The association of reactive ESFA with benign conditions, such as psoriasis, diabetic polyneuropathy, scars, and leprosy, has been reported. However, the association of reactive ESFA with malignant tumors is extremely rare, with very few cases reported in the literature. We present a case of a 72-year-old woman who developed reactive ESFA associated with Merkel cell carcinoma excision scar. The ESFA tumors developed in the area of the surgical graft 10 months after the Merkel cell carcinoma had been excised. New ESFA tumors have continued to appear in the scar on a yearly basis while, so far, has been no recurrence of the original tumor. However, the presence of new tumor growths in the area suggested the possibility of recurrence of the Merkel cell carcinoma. That possibility was enhanced by the fact that PET scans revealed hypermetabolic activity in the ESFA papules.

Case of recurrent superficial CD34-positive fibroblastic tumor.

Superficial CD34-positive fibroblastic tumor (SCPFT) is a recently described rare superficial mesenchymal tumor. SCPFT has a distinctive morphologic appearance, marked by significant nuclear pleomorphism, low mitotic rate, and diffuse CD34 positivity. SCPFT is underdiagnosed because of its rarity and misdiagnosis as sarcoma, with very few reported cases of local recurrence or metastasis. Recognition and awareness of SCPFT are essential for accurate diagnosis and appropriate clinical management. We describe here the case of a 37-year-old male who presented with a right calf mass diagnosed as SCPFT with subsequent local recurrence of the tumor.

Superficial CD34-positive fibroblastic tumor (SCPFT): A review of pathological and clinical features.

Superficial CD34-positive fibroblastic tumor (SCPFT) is a recently described rare mesenchymal tumor of borderline malignancy. It generally involves superficial soft tissue, with a predilection to the lower extremities. Microscopically this tumor is characterized by a fascicular and storiform growth pattern, spindled to epithelioid cells, nuclear atypia with pleomorphism, and eosinophilic granular, and fibrillar to glassy cytoplasm. Strong diffuse immunoreactivity for CD34 is very characteristic of this entity. Due to under-recognition, this tumor is generally underreported. Additionally, cases of recurrence are rarely reported in the literature. We will comprehensively review the English language literature on all reported cases of SCPFT, with emphasis on recurrence.

Potential Biomarkers for Treatment Response to the BCL-2 Inhibitor Venetoclax: State of the Art and Future Directions.

Intrinsic apoptotic pathway dysregulation plays an essential role in all cancers, particularly hematologic malignancies. This role has led to the development of multiple therapeutic agents targeting this pathway. Venetoclax is a selective BCL-2 inhibitor that has been approved for the treatment of chronic lymphoid leukemia and acute myeloid leukemia. Given the reported resistance to venetoclax, understanding the mechanisms of resistance and the potential biomarkers of response is crucial to ensure optimal drug usage and improved patient outcomes. Mechanisms of resistance to venetoclax include alterations involving the BH3-binding groove, BCL2 gene mutations affecting venetoclax binding, and activation of alternative anti-apoptotic pathways. Moreover, various potential genetic biomarkers of venetoclax resistance have been proposed, including chromosome 17p deletion, trisomy 12, and TP53 loss or mutation. This manuscript provides an overview of biomarkers that could predict treatment response to venetoclax.

Pathology Residency Open-House Events: A Novel Marketing Paradigm.

OBJECTIVES: Due to the continued impact of coronovirus 2019 (COVID-19), residency programs were advised to offer virtual interviews in place of traditional in-person interviews for the 2021 match recruitment season. As a result, many pathology residency programs offered preinterview virtual open-house events to meet prospective applicants before the interview season. This article aims to understand applicants' perspective on those events during the residency recruitment season of 2020 to 2021. METHODS: We performed a cross-sectional survey-based study involving 95 pathology residency applicants. RESULTS: Our results demonstrated that applicants generally have a positive perception of open house events; 91% found virtual open-house events beneficial, 63.2% attended open-house events for programs they were not considering applying to. Considering the high number of offered virtual open house events, 17% of applicants felt overwhelmed by attendance and 30% felt obligated to attend. CONCLUSIONS: This brief report demonstrates the generally positive impact of these events.

Extraskeletal Myxoid Chondrosarcoma of the Vulva Confirmed by EWSR1 FISH: A Case Report and Review of the Literature.

Extraskeletal myxoid chondrosarcoma of the vulva is a very rare tumor, with less than 10 cases reported in the literature. We report a case of a 45-yr-old woman with extraskeletal myxoid chondrosarcoma of the vulva confirmed by EWSR1 fluorescence in situ hybridization. Given the unusual site and prominent myxoid morphology, a broad differential diagnosis and a variety of ancillary testing was required. This article aims to review extraskeletal myxoid chondrosarcoma of the vulva, the differential diagnosis of a myxoid spindle cell neoplasm of the vulva, and the diagnostic importance of immunohistochemistry and EWSR1 fluorescence in situ hybridization.

Quantitative and Qualitative Analysis of Medical Students' Research Output in Five Developing Countries.

Objectives The purpose of this analysis was to investigate the quantity and quality of medical students' research output in Gulf Cooperation Council countries to aid in developing strategies to improve research output. Methods Abstracts presented by medical students in Gulf Cooperation Council countries were subject to analysis. Abstracts that propagated into full-length articles underwent further demographic analysis, in which data regarding the type of study, the field of study, country of origin, mode of presentation, and journal's impact factor were collected. A total of 798 abstracts were surveyed, with 19% (n=155) of the abstracts submitted by Gulf Cooperation Council countries progressing into full-length publications. The average impact factor for Gulf Cooperation Council country publications was found to be 1.85 ± 0.26 (standard error). Countries that recorded the highest conversion rates were, in descending order, Kingdom of Saudi Arabia, United Arab Emirates, Oman, Bahrain, and Kuwait. Moreover, basic biomedical and clinical research topics were more likely to be published in comparison with community-oriented and medical education-related topics. Conclusions Effective efforts to encourage more medical student research output in the Gulf Cooperation Council countries (with a focus on qualitative analysis) should be promoted in order to achieve publication rates comparable with those reported by developed countries.

Machine learning applications in the diagnosis of leukemia: Current trends and future directions.

Machine learning (ML) offers opportunities to advance pathological diagnosis, especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is time-consuming and challenging in many areas globally and there is a growing trend in utilizing ML techniques for its diagnosis. In this review, we aimed to describe the literature of ML utilization in the diagnosis of the four common types of leukemia: acute lymphocytic leukemia (ALL), chronic lymphocytic leukemia (CLL), acute myeloid leukemia (AML), and chronic myelogenous leukemia (CML). Using a strict selection criterion, utilizing MeSH terminology and Boolean logic, an electronic search of MEDLINE and IEEE Xplore Digital Library was performed. The electronic search was complemented by handsearching of references of related studies and the top results of Google Scholar. The full texts of 58 articles were reviewed, out of which, 22 studies were included. The number of studies discussing ALL, AML, CLL, and CML was 12, 8, 3, and 1, respectively. No studies were prospectively applying algorithms in real-world scenarios. Majority of studies had small and homogenous samples and used supervised learning for classification tasks. 91% of the studies were performed after 2010, and 74% of the included studies applied ML algorithms to microscopic diagnosis of leukemia. The included studies illustrated the need to develop the field of ML research, including the transformation from solely designing algorithms to practically applying them clinically.