Background Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), known to be the causative agent of COVID‐19, has led to a worldwide pandemic. At presentation, individual clinical laboratory blood values, such as lymphocyte counts or C‐reactive protein (CRP) levels, may be abnormal and associated with disease severity. However, combinatorial interpretation of these laboratory blood values, in the context of COVID‐19, remains a challenge. Methods To assess the significance of multiple laboratory blood values in patients with SARS‐CoV‐2 and develop a COVID‐19 predictive equation, we conducted a literature search using PubMed to seek articles that included defined laboratory data points along with clinical disease progression. We identified 9846 papers, selecting primary studies with at least 20 patients for univariate analysis to identify clinical variables predicting nonsevere and severe COVID‐19 cases. Multiple regression analysis was performed on a training set of patient studies to generate severity predictor equations, and subsequently tested on a validation cohort of 151 patients who had a median duration of observation of 14 days. Results Two COVID‐19 predictive equations were generated: one using four variables (CRP, D‐dimer levels, lymphocyte count, and neutrophil count), and another using three variables (CRP, lymphocyte count, and neutrophil count). In adult and pediatric populations, the predictive equations exhibited high specificity, sensitivity, positive predictive values, and negative predictive values. Conclusion Using the generated equations, the outcomes of COVID‐19 patients can be predicted using commonly obtained clinical laboratory data. These predictive equations may inform future studies evaluating the long‐term follow‐up of COVID‐19 patients.

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Castleman disease (CD) is a rare lymphoproliferative disorder known to represent at least four distinct clinicopathologic subtypes. Large advancements in our clinical and histopathologic description of these diverse diseases have been made, resulting in subtyping based on number of enlarged lymph nodes (unicentric versus multicentric), according to viral infection by human herpes virus 8 (HHV-8) and human immunodeficiency virus (HIV), and with relation to clonal plasma cells (POEMS). In recent years, significant molecular and genetic abnormalities associated with CD have been described. However, we continue to lack a foundational understanding of the biological mechanisms driving this disease process. Here, we review all cases of CD with molecular abnormalities described in the literature to date, and correlate cytogenetic, molecular, and genetic abnormalities with disease subtypes and phenotypes. Our review notes complex karyotypes in subsets of cases, specific mutations in PDGFRB N666S in 10% of unicentric CD (UCD) and NCOA4 L261F in 23% of idiopathic multicentric CD (iMCD) cases. Genes affecting chromatin organization and abnormalities in methylation are seen more commonly in iMCD while abnormalities within the mitogen-activated protein kinase (MAPK) and interleukin signaling pathways are more frequent in UCD. Interestingly, there is a paucity of genetic studies evaluating HHV-8 positive multicentric CD (HHV-8+ MCD) and POEMS-associated CD. Our comprehensive review of genetic and molecular abnormalities in CD identifies subtype-specific and novel pathways which may allow for more targeted treatment options and unique biologic therapies.

LIM domain only 2 (LMO2) expression distinguishes T-lymphoblastic leukemia/lymphoma from indolent T-lymphoblastic proliferations Aims: An indolent T-lymphoblastic proliferation (iT-LBP) is a benign, reactive expansion of immature terminal deoxynucleotidyl transferase (TdT)-positive T cells found in extrathymic tissues. iT-LBP can be challenging to distinguish from malignant processes, specifically T-lymphoblastic lymphoma (T-LBL), given the overlapping clinical and histological features. Recently, it has been shown that LIM domain only 2 (LMO2) is overexpressed in T-LBL but not in reactive immature TdT+ T cells in the thymus. On the basis of these findings, the aim of this study was to investigate the expression of LMO2 by using immunohistochemistry and its role in differentiating iT-LBPs from T-LBLs. Methods and results: We retrospectively identified cases of iT-LBP and T-LBL from the pathology archives of four institutions. Seven iT-LBP cases (including five new cases that have not been reported in the literature) and 13 T-LBL cases were analysed. Clinical, morphological, immunophenotypic and molecular data were analysed. Immunohistochemical staining with LMO2 was performed on all iT-LBP and T-LBL cases. A review of five new iT-LBP cases showed similar morphological, immunophenotypic and molecular features to those of previously reported cases. All iT-LBP cases were negative for LMO2 (0/7), whereas 92% of T-LBL cases (12/13) expressed LMO2; the sensitivity was 92% (confidence interval 64-100%) and the specificity was 100% (confidence interval 59-100%). Conclusion: We confirm previously published findings that iT-LBP cases show highly overlapping morphological and immunophenotypic features with T-LBL. Importantly, LMO2 expression is a sensitive and specific marker with which to rule out iT-LBP.

Angioimmunoblastic T-cell lymphoma (AITL) is a uniquely aggressive mature T-cell neoplasm. In recent years, recurrent genetic mutations in ras homolog family member A ( RHOA ), tet methylcytosine dioxygenase 2 ( TET2 ), DNA methyltransferase 3 alpha ( DNMT3A ) and isocitrate dehydrogenase [NADP(+)] 2 ( IDH2 ) have been identified as associated with AITL. However, a deep molecular study assessing both DNA mutations and RNA expression profile combined with digital image analysis is lacking. The present study aimed to evaluate the significance of molecular and morphologic features by high resolution digital image analysis in several cases of AITL. To do so, a total of 18 separate tissues from 10 patients with AITL were collected and analyzed. The results identified recurrent mutations in RHOA , TET2 , DNMT3A , and IDH2 , and demonstrated increased DNA mutations in coding, promoter and CCCTC binding factor (CTCF) binding sites in RHOA mutated AITLs vs. RHOA non-mutated cases, as well as increased overall survival in RHOA mutated patients. In addition, single cell computational digital image analysis morphologically characterized RHOA mutated AITL cells as distinct from cells from RHOA mutation negative patients. Computational analysis of single cell morphological parameters revealed that RHOA mutated cells have decreased eccentricity (more circular) compared with RHOA non-mutated AITL cells. In conclusion, the results from the present study expand our understanding of AITL and demonstrate that there are specific cell biological and morphological manifestations of RHOA mutations in cases of AITL.