Mucormycosis in a Patient with Chronic Lymphatic Leukemia in Treatment with Ibrutinib

Invasive Fungal Infection (IFI) is a serious complication in patients with hematologic malignancies. We present a case of invasive Mucormycosis in a patient with Chronic Lymphatic Leukemia (CLL). This case of Mucormycosis illustrates invasive fungal infections as a complication to chronic hematologic diseases and adds to other publications that suggest a relationship with novel treatments of CLL such as ibrutinib. Treatment of the IFI was successful without having to stop ibrutinib. We present relevant publications and discuss clinical controversies that arise.

Cytotoxic Polyketide Metabolites from a Marine Mesophotic Zone Chalinidae Sponge-Associated Fungus Pleosporales sp. NBUF144

Two new polyketide natural products, globosuxanthone F (1), and 2′-hydroxy bisdechlorogeodin (2), were isolated from the fungus Pleosporales sp. NBUF144, which was derived from a 62 m deep Chalinidae family sponge together with four known metabolites, 3,4-dihydroglobosuxanthone A (3), 8-hydroxy-3-methylxanthone-1-carboxylate (4), crosphaeropsone C (5), and 4-megastigmen-3,9-dione (6). The structures of these compounds were elucidated on the basis of extensive spectroscopic analysis, including 1D and 2D NMR and high-resolution electrospray ionization mass spectra (HRESIMS) data. The absolute configuration of 1 was further established by single-crystal X-ray diffraction studies. Compounds 1-5 were evaluated for cytotoxicity towards CCRF-CEM human acute lymphatic leukemia cells, and it was found that 1 had an IC50 value of 0.46 µM.

Tumor Therapy with Amanita phalloides: Benefits and Limitation

Background: Classical tumor treatments can fail: surgeries, radiation and chemotherapy not always elongate the life span. Less destructive treatments are possible nowadays. To find and analyse the efficiency of alternate treatments, long term case reports are essential. Aim: To determine long term analyses of Amanita treatment in patients with different tumor types. Methods: Patients are treated with Amanita alone, as long as the tumor growth of cells can be retarded. Other anti tumor therapies are applied in addition, when the retardation of the tumor growth is not sufficiently manageable with Amanita alone. The treatments with Amanita are supported by application of Terebinthina laricina in intervals to eliminate Borrelia. Results: The state of a patient with a thyroid-carcinoma and a rectum-carcinoma can be stabilized for ten years with Amanita alone, until her age of 90 years. The patient cannot further tolerate uptake of Amanita. Thyroid cells start to grow, rectum-carcinoma cells grow slower. The disease state of a patient with prostate-carcinoma can be stabilized with Amanita alone for six years. Other therapies are applied from then on in intervals in addition for further six years. No chemotherapy or radiation is applied. The patient died at the age of 84 with metastases. A patient with B-cell chronic lymphatic leukemia is treated with Amanita as sole antitumor therapy for eleven years. After that period, no further antitumor treatment is necessary, the patient lives now with high but stable leukocyte count for two years after the end of the Amanita therapy. Conclusions: Amanita can inhibit tumor growth of different tumor types for a long period of time, elongation of the life span is possible. A synergistic effect of anti-Borrelia treatment is observed. Occasionally the tumor growth of cells stops without further anti tumor therapy, and no correlation with the origin can be identified.

Bioconjugation of a PNA Probe to Zinc Oxide Nanowires for Label-Free Sensing

Zinc oxide nanowires (ZnONWs) are largely used in biosensing applications due to their large specific surface area, photoluminescence emission and electron mobility. In this work, the surfaces of ZnONWs are modified by covalent bioconjugation of a peptidic nucleic acid (PNA) probe whose sequence is properly chosen to recognize a complementary DNA (cDNA) strand corresponding to a tract of the CD5 mRNA, the main prognostic marker of chronic lymphatic leukemia. The interaction between PNA and cDNA is preliminarily investigated in solution by circular dichroism, CD melting, and polyacrylamide gel electrophoresis. After the immobilization of the PNA probe on the ZnONW surface, we demonstrate the ability of the PNA-functionalized ZnONW platform to detect cDNA in the μM range of concentration by electrical, label-free measurements. The specificity of the sensor is also verified against a non-complementary DNA sequence. These preliminary results highlight the potential application of PNA-bioconjugated ZnONWs to label-free biosensing of tumor markers.

Employment of Machine Learning Models Yields Highly Accurate Hematological Disease Prediction from Raw Flow Cytometry Matrix Data without the Need for Visualization or Human Intervention

Background: Machine Learning (ML) offers automated data processing substituting various analysis steps. So far it has been applied to flow cytometry (FC) data only after visualization which may compromise data by reduction of data dimensionality. Automated analysis of FC raw matrix data has not yet been pursued. Aim: To establish as proof of concept an ML-based classifier processing FC matrix data to predict the correct lymphoma type without the need for visualization or human analysis and interpretation. Methods: A set of 6,393 uniformly analyzed samples (Navios cytometers, Kaluza software, Beckman Coulter, Miami, FL) was used for training (n=5,115) and testing (n=1,278) of different ML models. Entities were chronic lymphatic leukemia (CLL) 1103 (training) and 279 (testing), monoclonal B-cell lymphocytosis (MBL, 831/203), CLL with increased prolymphocytes (CLL-PL, 649/161), lymphoplasmacytic lymphoma (LPL, 560/159), hairy cell leukemia (HCL, 328/88), mantle cell lymphoma (MCL, 259/53), marginal zone lymphoma (MZL, 90/28), follicular lymphoma (FL, 84/16), no lymphoma (1211/291). Three tubes comprising 11 parameters per tube were applied. Besides scatter signals analyzed antigens included: CD3, CD4, CD5, CD8, CD10, CD11c, CD19, CD20, CD22, CD23, CD25, CD38, CD45, CD56, CD79b, CD103, FMC7, HLA-DR, IgM, Kappa, Lambda. Measurements generated LMD files with 50,000 rows of data for each of the 11 parameters. After removing the saturated values (≥ 1023) we produced binned histograms with 16 predefined frequency bins per parameter. Histograms were converted to cumulative distribution functions (CDF) for respective parameters and concatenated to produce a 16x11 matrix per each tube. Following the assumption of independence of parameters this simplification of concatenating CDFs represents the same information as if they were jointly distributed. The first matrix-based classifier was a decision tree model (DT), the second a deep learning model (DL) and the third was an XGBoost (XG) model, an implementation of gradient boosted decision trees ideal for structured tabular data (such as LMD files). The first set of analyses included only three classes which are readily separated by human operators: 1) CLL, 2) HCL, 3) no lymphoma. The second set included all nine entities but grouped into four classes: 1) CD5+ lymphoma (CLL, MBL, CLL-PL, MCL), 2) HCL, 3) other CD5- lymphoma (LPL, MZL, FL), 4) no lymphoma. The third set included each of the nine entities as its own class. Results: Analyzing the three classes from the first set (CLL, HCL, no lymphoma) the models achieved accuracies of 94% (DT), 95% (DL) and 96% (XG) when including all cases. By analysis of cases with prediction probabilities above 90%, DT now reached 97%, DL 97% and XG 98% accuracy, whilst losing 38%, 8% and 6% of samples, respectively. We further observed that accuracy was also dependent on the size of the pathologic clone, which is in line with the experiences from human experts with very small clones (≤ 0.1% of leukocytes) representing a major challenge regarding their correct classification. Focusing on cases with clones > 0.1% but considering all prediction probabilities accuracies were 96% (DT), 97% (DL) and 98% (XG), with loss of 5% of samples for each model. Considering cases only with prediction probabilities > 90% and clones > 0.1% accuracies were 97% (DT), 99% (DL) and 99% (XG) whilst losing 38%, 9% and 9% of samples, respectively. Further analyses were performed applying the best model based on results above, i.e. XG. Analyzing four classes in the second set of analyses (CD5+ lymphoma, HCL, other CD5- lymphoma, no lymphoma) and considering cases only with prediction probabilities > 95% and clones > 0.1% accuracy was 96% while losing 28% of samples. In the third set of analyses with each entity assigned its own class and again considering cases only with prediction probabilities > 95% and clones > 0.1% accuracy was 93% while losing 28% of samples. Conclusions: This first ML-based classifier using the XGboost model with transforming FC matrix data to concatenated distributions, is capable of correctly assigning the vast majority of lymphoma samples analyzing FC raw data without visualization or human interpretation. Cases that need further attention by human experts will be flagged but will not account for more than 30% of all cases. This data will be extended in a prospective blinded study (clinicaltrials.gov NCT4466059). Disclosures Heo: AWS: Current Employment. Wetton:AWS: Current Employment.

First-line therapy of indolent non-Hodgkin’s lymphoma in routine clinical practice

The aim is to evaluate the efficacy of the first-line rituximab-containing therapy of B-cell lymphoproliferative diseases in Russian clinical practice between 2014 and 2017. Materials and methods. In the post-authorisation multicenter study EQUILIBRIUM were included 1 thousand patients aged from 21 to 91 with B-cell non-Hodgkins lymphoma or chronic lymphatic leukemia who had received at least 4 cycles of rituximab-containing therapy using the drug Acellbia. This article was devoted to the group of indolent non-Hodgkins lymphomas and included 253 patients: follicular lymphoma 51% of cases, marginal zone lymphoma 44% of patients, extremely rare were registered lymphoplasmacytic lymphoma and Waldenstrom macroglobulinemia in 3% and in 2% of cases, respectively. The median age in patients with indolent non-Hodgkins lymphomas was 62 years (2191 years). The vast majority of patients were diagnosed with stage IIIIV 190 (75%) of patients. More than 1/2 (53.4%) of patients in routine practice received R-CHOP therapy as a first-line. BR regimen was applied in 15.4% of cases, 14.2% of patients were treated with R-CVP/R-COP. We indicated rare use of rituximab as monotherapy in induction mode only 4.4% of patients. And 2.4% of patients were treated with fludarabine-containing therapy. Results. The final assessment of the effect was carried out after 68 cycles of treatment and as a result the overall effect was more than 90%: the frequency of complete remission was 61%, partial responses 32.9%. The progression admitted only in 17 (6.7%) patients among 253 observed. With a median of 15 months, the median of overall survival and event-free survival was not achieved. Conclusion. The use of the available and appropriate treatment according to the domestic clinical guidelines with the inclusion of the Russian biosimilar anti-CD20 monoclonal antibody Acellbia, demonstrates high direct efficacy and satisfactory long-term treatment results comparable to the retrospective analysis of the previous clinical studies of the original drug rituximab.