Physiologic Medium Rewires Cellular Metabolism and Reveals Uric Acid as an Endogenous Inhibitor of UMP Synthase

A complex interplay of environmental factors impacts the metabolism of human cells, but neither traditional culture media nor mouse plasma mimic the metabolite composition of human plasma. Here, we developed a culture medium with polar metabolite concentrations comparable to those of human plasma (human plasma-like medium [HPLM]). Culture in HPLM, relative to that in traditional media, had widespread effects on cellular metabolism, including on the metabolome, redox state, and glucose utilization. Among the most prominent was an inhibition of de novo pyrimidine synthesis—an effect traced to uric acid, which is 10-fold higher in the blood of humans than of mice and other non-primates. We find that uric acid directly inhibits uridine monophosphate synthase (UMPS) and consequently reduces the sensitivity of cancer cells to the chemotherapeutic agent 5-fluorouracil. Thus, media that better recapitulates the composition of human plasma reveals unforeseen metabolic wiring and regulation, suggesting that HPLM should be of broad utility.National Institutes of Health (U.S.) (Grant R01CA103866)National Institutes of Health (U.S.) (Grant R37AI047389

Correction. "The 5th edition of The World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms" Leukemia. 2022 Jul;36(7):1720-1748

We herein present an overview of the upcoming 5th edition of the World Health Organization Classification of Haematolymphoid Tumours focussing on lymphoid neoplasms. Myeloid and histiocytic neoplasms will be presented in a separate accompanying article. Besides listing the entities of the classification, we highlight and explain changes from the revised 4th edition. These include reorganization of entities by a hierarchical system as is adopted throughout the 5th edition of the WHO classification of tumours of all organ systems, modification of nomenclature for some entities, revision of diagnostic criteria or subtypes, deletion of certain entities, and introduction of new entities, as well as inclusion of tumour-like lesions, mesenchymal lesions specific to lymph node and spleen, and germline predisposition syndromes associated with the lymphoid neoplasms

Hypercalcemia Associated with Isolated Bone Marrow Sarcoidosis in a Patient with Underlying Monoclonal Gammopathy of Undetermined Significance: Case Report and Review of Literature

Bone marrow sarcoidosis is extremely rare. The association between sarcoidosis and lymphoproliferative disorders has been previously speculated, although the diagnosis of sarcoidosis often precedes any hematological derangements. Here, we report for the first time, a case of a 57 year old woman with a previous diagnosis of monoclonal gammopathy of undetermined significance (MGUS) developing hypercalcemia and renal failure with work notable for isolated bone marrow sarcoidosis and not multiple myeloma as expected. The patient was successfully managed with prednisone taper therapy with resolution of her hypercalcemia and repeat bone marrow biopsies demonstrating resolving granulomas. Our case illustrates the diagnostic challenges associated with bone marrow sarcoidosis and suggest that chronic immune stimulation in the bone marrow in the setting of MGUS may be a risk factor for the development of localized sarcoidosis. The long term consequences of steroid therapy targeting sarcoidosis in this patient with underlying MGUS remain unknown. Close followup is planned in light of the increased risk of malignant transformation of MGUS into multiple myeloma in the setting of bone marrow sarcoidosis

Nuclear IHC enumeration: A digital phantom to evaluate the performance of automated algorithms in digital pathology.

Automatic and accurate detection of positive and negative nuclei from images of immunostained tissue biopsies is critical to the success of digital pathology. The evaluation of most nuclei detection algorithms relies on manually generated ground truth prepared by pathologists, which is unfortunately time-consuming and suffers from inter-pathologist variability. In this work, we developed a digital immunohistochemistry (IHC) phantom that can be used for evaluating computer algorithms for enumeration of IHC positive cells. Our phantom development consists of two main steps, 1) extraction of the individual as well as nuclei clumps of both positive and negative nuclei from real WSI images, and 2) systematic placement of the extracted nuclei clumps on an image canvas. The resulting images are visually similar to the original tissue images. We created a set of 42 images with different concentrations of positive and negative nuclei. These images were evaluated by four board certified pathologists in the task of estimating the ratio of positive to total number of nuclei. The resulting concordance correlation coefficients (CCC) between the pathologist and the true ratio range from 0.86 to 0.95 (point estimates). The same ratio was also computed by an automated computer algorithm, which yielded a CCC value of 0.99. Reading the phantom data with known ground truth, the human readers show substantial variability and lower average performance than the computer algorithm in terms of CCC. This shows the limitation of using a human reader panel to establish a reference standard for the evaluation of computer algorithms, thereby highlighting the usefulness of the phantom developed in this work. Using our phantom images, we further developed a function that can approximate the true ratio from the area of the positive and negative nuclei, hence avoiding the need to detect individual nuclei. The predicted ratios of 10 held-out images using the function (trained on 32 images) are within ±2.68% of the true ratio. Moreover, we also report the evaluation of a computerized image analysis method on the synthetic tissue dataset

Genetic Analysis of Plasmablastic Lymphomas in HIV (+) Patients Reveals Novel Driver Regulators of the Noncanonical NF-κB Pathway

Abstract Introduction: Plasmablastic lymphoma (PL) is an aggressive variant of lymphoma, with strong association with HIV. Despite significant improvements in the survival of other lymphomas, PL has a short overall survival (14 months). The association with Epstein-Barr virus (EBV) infection and MYC chromosomal translocations are defining features of PL. However, the genetic causes and the role of specific mutation in PL are largely unknown. This limitation hinders the design of therapeutic approaches aimed to improve PL survival. Therefore, we performed a comprehensive analysis of the genetic landscape in PL. Methodology: Whole exon sequencing of 52 de novo PL tumors from HIV+ patients and matched normal tissues (15%) using high throughput sequencing on the Illumina platform. Of these 52 patient samples, 10 tumor and 4 normal control samples were removed due to poor sequencing quality. Mapping and variant calls were performed using BWA and Varscan softwares. Variants call filtering criteria include: exon location, minimum coverage of 5%, and onside T-test P value ≤ of 0.01 or 0.02). For immunohistochemistry, we use p-TAK1 Thr184-187 (Cell signaling) and p-BTK Tyr551(Termofisher) antibodies. Results: Analysis of exome sequencing data identified 1562 recurrent somatic mutations (p-value ≤0.01) in 711 genes, including 304 mutations previously identified in cancer driving genes. The most common recurrent pathways affected within the top 2000 gene mutations with p≤0.02 comprised mainly of NF-κB signaling followed by immune response (antigen presentation by MHC class II and the alternative and lectin induced complement pathways), reverse signaling by Ephrin B, mTOR/PTEN and EGFR/RAS pathways. Based on the lack of canonical NF-κB activation previously reported (Chapman J et al. Leukemia 2015; 29: 2270-2273) and the important role of MYD88-p100 signaling pathway in B cell differentiation into plasmablast (Guo et al. Oncogene 2016. 36(29):4224-4232), we investigated the status of p100 signaling in PL using a published gene expression dataset (Chapman J. et al Leukemia 2015). Our analysis demonstrated that most PL (70%) manifest constitutive p100 signaling. Therefore, we focused on mutations in genes involved in the NF-κB activation. Mutations in the NF-κB pathway were identified in all the analyzed cases with an average of 4 mutated genes in each tumor. Consistent with the previously reported downregulation in RNA expression of genes implicated in the BCR and canonical NF-κB signaling, we found deleterious mutations in genes in the BCR pathway that have been previously reported in lymphomas, including MATL1, FYN and SYK (24%, 16% and 15%, respectively). In contrast, we found frequent gene mutations in the MYD88-PI3P pathway that never have been reported in lymphomas, including SHIP2, DOCK8, PLCG2 in 50%, 39% and 37% of the cases, respectively. These findings are of relevance, as this mutations are expected to results in increased MYD88/TAK1 and BTK signaling (Shinners NP et al J. Imm. 2007, 179 (6) 3872-3880) and can be targeted by specific inhibitors. To evaluate the status of phosphorylation of TAK1 and BTK in these tumors, we performed immunohistochemistry analysis in 15 PL, demonstrating high levels of phosphorylation of these proteins in all tumors analyzed. Conclusion: To our knowledge, this is the first in-depth analysis of PL genome. Our data provide the most comprehensive genetic portrait of PL, provides potential genetic causes of this disease and identify potential druggable targets that deserve further clinical exploration. Disclosures Flowers: National Cancer Institute: Research Funding; Millennium/Takeda: Research Funding; Eastern Cooperative Oncology Group: Research Funding; OptumRx: Consultancy; Denovo Biopharma: Consultancy; Genentech/Roche: Research Funding; V Foundation: Research Funding; Abbvie: Consultancy, Research Funding; Acerta: Research Funding; Celgene: Research Funding; Pharmacyclics/ Janssen: Consultancy; Spectrum: Consultancy; Burroughs Wellcome Fund: Research Funding; Bayer: Consultancy; Karyopharm: Consultancy; Gilead: Research Funding; Genentech/Roche: Consultancy; Pharmacyclics: Research Funding; Janssen Pharmaceutical: Research Funding; Abbvie: Research Funding; BeiGene: Research Funding; TG Therapeutics: Research Funding; Gilead: Consultancy. Lossos:Affimed: Research Funding. Bernal-Mizrachi:Takeda Pharmaceutical Company: Research Funding; Kodikaz Therapeutic Solutions: Consultancy, Equity Ownership

Summary statistics of pathologists’ and computer’s estimation of <i>r</i>_<i>n</i> (the ratio of true number of positive to total number of nuclei).

<p>Here denote the estimation of <i>r</i>_<i>n</i> by pathologist 1, pathologist 2, pathologist 3, pathologist 4 and the computer algorithm, respectively.</p

Division of synthetic images into 10 subsets.

<p>Here SS_i correspond to the i^th subset. The second row contains the ratio of positive to all nuclei within each SS_i. The third row contains the number of images in each subset.</p