The future of affordable cancer immunotherapy

The treatment of cancer was revolutionized within the last two decades by utilizing the mechanism of the immune system against malignant tissue in so-called cancer immunotherapy. Two main developments boosted cancer immunotherapy: 1) the use of checkpoint inhibitors, which are characterized by a relatively high response rate mainly in solid tumors; however, at the cost of serious side effects, and 2) the use of chimeric antigen receptor (CAR)-T cells, which were shown to be very efficient in the treatment of hematologic malignancies, but failed to show high clinical effectiveness in solid tumors until now. In addition, active immunization against individual tumors is emerging, and the first products have reached clinical approval. These new treatment options are very cost-intensive and are not financially compensated by health insurance in many countries. Hence, strategies must be developed to make cancer immunotherapy affordable and to improve the cost-benefit ratio. In this review, we discuss the following strategies: 1) to leverage the antigenicity of “cold tumors” with affordable reagents, 2) to use microbiome-based products as markers or therapeutics, 3) to apply measures that make adoptive cell therapy (ACT) cheaper, e.g., the use of off-the-shelf products, 4) to use immunotherapies that offer cheaper platforms, such as RNA- or peptide-based vaccines and vaccines that use shared or common antigens instead of highly personal antigens, 5) to use a small set of predictive biomarkers instead of the “sequence everything” approach, and 6) to explore affordable immunohistochemistry markers that may direct individual therapies.</p

The future of affordable cancer immunotherapy

The treatment of cancer was revolutionized within the last two decades by utilizing the mechanism of the immune system against malignant tissue in so-called cancer immunotherapy. Two main developments boosted cancer immunotherapy: 1) the use of checkpoint inhibitors, which are characterized by a relatively high response rate mainly in solid tumors; however, at the cost of serious side effects, and 2) the use of chimeric antigen receptor (CAR)-T cells, which were shown to be very efficient in the treatment of hematologic malignancies, but failed to show high clinical effectiveness in solid tumors until now. In addition, active immunization against individual tumors is emerging, and the first products have reached clinical approval. These new treatment options are very cost-intensive and are not financially compensated by health insurance in many countries. Hence, strategies must be developed to make cancer immunotherapy affordable and to improve the cost-benefit ratio. In this review, we discuss the following strategies: 1) to leverage the antigenicity of “cold tumors” with affordable reagents, 2) to use microbiome-based products as markers or therapeutics, 3) to apply measures that make adoptive cell therapy (ACT) cheaper, e.g., the use of off-the-shelf products, 4) to use immunotherapies that offer cheaper platforms, such as RNA- or peptide-based vaccines and vaccines that use shared or common antigens instead of highly personal antigens, 5) to use a small set of predictive biomarkers instead of the “sequence everything” approach, and 6) to explore affordable immunohistochemistry markers that may direct individual therapies

A review of the antibiotic residues in food in the Arab countries

The safety and quality of foods of animal origin are of great importance to the human health and economy. Food can contain different hazards, including antibiotic residues. In both low and middle-income countries, such as the case of the majority of the Arab countries, the use of antibiotics is not under control, in addition to the poor monitoring of imported foodstuffs. This has been causing antimicrobial resistance (AMR) that is in turn threatening the safety of both animals and humans. The presence of antibiotic residues in food commodities, such as dairy and meat products, in addition to honey, is a public health concern. In this review, literature review from the Arab countries on antibiotic residues in foods was done and a total of 40 published articles were found and analyzed. The findings of these articles in terms of most used antibiotics, exposure levels, detection methods, in addition to understanding the factors that increase their presence in food samples are presented in this review

Phenolic contents and antioxidant activity of barhi date palm (Phoenix dactylifera L.) kernels extracts

Consumption of foods rich in phytochemicals with potential antioxidant properties can reduce the risk of various degenerative diseases such as cancer, atherosclerosis, diabetes, and aging. Several plant materials have been studied as sources of potentially safe natural antioxidants such as vegetables, fruits, cereals, barks, roots, spices and herbs. However, relatively less information is available on the antioxidant potentials of food processing products and agro-industrial wastes which are usually discarded in huge quantities. Some studies reported that the peel and kernel fractions of some fruits have been found to possess higher antioxidant activity than the pulp fraction based on their ferric reducing/antioxidant power (FRAP) values. Accordingly, the search for new natural antioxidants in wastes such as peels, brans and kernels has taken a very high attention in the last decade. The kernels obtained after date processing constitute a very cheap source for the extraction of antioxidant phenols, which makes them suitable for the preparation of dietary supplements, or in the production of phytochemicals, providing an important economic advantage through increase the utilization of date kernels while also additive value will be added to the residue. The aim of this research was, therefore, to investigate the effect of different extraction solvents on the phenolic content and antioxidant activity of Barhi date palm kernels (DPK). The solvent systems used were methanol, ethanol, acetone and distilled water. The antioxidant activity of the Barhi DPK was evaluated using ferric-reducing antioxidant power assay (FRAP), 1,1-diphenyl-2-picrylhydrazyl free radical-scavenging capacity (DPPH), 2,2- azinobis (3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS) and total phenolic compounds (TPC)

Large-Scale Differential Gene Expression Transcriptomic Analysis Identifies a Metabolic Signature Shared by All Cancer Cells

Cancer-dependent metabolic rewiring is often manifested by selective expression of enzymes essential for the transformed cells&rsquo; viability. However, the metabolic variations between normal and transformed cells are not fully characterized, and therefore, a systematic analysis will result in the identification of unknown cellular mechanisms crucial for tumorigenesis. Here, we applied differential gene expression transcriptome analysis to examine the changes in metabolic gene profiles between a wide range of normal tissues and cancer samples. We found that, in contrast to normal tissues which exhibit a tissue-specific expression profile, cancer samples are more homogenous despite their diverse origins. This similarity is due to a &ldquo;proliferation metabolic signature&rdquo; (PMS), composed of 158 genes (87 upregulated and 71 downregulated gene sets), where 143 are common to all proliferative cells but 15 are cancer specific. Intriguingly, the PMS gene set is enriched for genes encoding rate-limiting enzymes, and its upregulated set with genes associated with poor patient outcome and essential genes. Among these essential genes is ribulose-5-phosphate-3-epimerase (RPE), which encodes a pentose phosphate pathway enzyme and whose role in cancer is still unclear. Collectively, we identified a set of metabolic genes that can serve as novel cancer biomarkers and potential targets for drug development

Identification of telomerase RNAs in species of the Yarrowia Clade provides insights into the co-evolution of telomerase, telomeric repeats and telomere-binding proteins

Telomeric repeats in fungi of the subphylum Saccharomycotina exhibit great inter- and intra-species variability in length and sequence. Such variations challenged telomeric DNA-binding proteins that co-evolved to maintain their functions at telomeres. Here, we compare the extent of co-variations in telomeric repeats, encoded in the telomerase RNAs (TERs), and the repeat-binding proteins from 13 species belonging to the Yarrowia Glade. We identified putative TER loci, analyzed their sequence and secondary structure conservation, and predicted functional elements. Moreover, in vivo complementation assays with mutant TERs showed the functional importance of four novel TER substructures. The TER-derived telomeric repeat unit of all species, except for one, is 10 bp long and can be represented as 5'-TTNNNNAGGG-3', with repeat sequence variations occuring primarily outside the vertebrate telomeric motif 5'-TTAGGG-3'. All species possess a homologue of the Yarrowia lipolytica Tay1 protein, YlTay1p. In vitro, YlTay1p displays comparable DNA-binding affinity to all repeat variants, suggesting a conserved role among these species. Taken together, these results add significant insights into the co-evolution of TERs, telomeric repeats and telomere-binding proteins in yeasts

Ethnic variation in medical and lifestyle risk factors for B cell non-Hodgkin lymphoma: A case-control study among Israelis and Palestinians

<div><p>Background</p><p>Risk factors for B-cell non-Hodgkin lymphoma (B-NHL) have not been assessed among Palestinian Arabs (PA) and Israeli Jews (IJ).</p><p>Methods</p><p>In a case-control study we investigated self-reported medical and lifestyle exposures, reporting odds ratios (ORs) and 95% confidence intervals [CIs], by ethnicity, for overall B-NHL and subtypes.</p><p>Results</p><p>We recruited 823 cases and 808 healthy controls. Among 307 PA/516 IJ B-NHL cases (mean age at diagnosis = 51 [±17] versus 60 [±15] years, respectively) subtype distributions differed, with diffuse large B-cell lymphoma (DLBCL) being prominent among PA (71%) compared to IJ (41%); follicular lymphoma (FL), was observed in 14% versus 28%, and marginal zone lymphoma, in 2% versus 14%, respectively. Overall B-NHL in both populations was associated with recreational sun exposure OR = 1.43 [CI:1.07–1.91], black hair-dye use OR = 1.70 [CI:1.00–2.87], hospitalization for infection OR = 1.68 [CI:1.34–2.11], and first-degree relative with hematopoietic cancer, OR = 1.69 [CI:1.16–2.48]. An inverse association was noted with alcohol use, OR = 0.46 [CI:0.34–0.62]. Subtype-specific exposures included smoking (FL, OR = 1.46 [CI:1.01–2.11]) and >monthly indoor pesticide use (DLBCL, OR = 2.01 [CI:1.35–3.00]). Associations observed for overall B-NHL in PA only included: gardening OR = 1.93 [CI:1.39–2.70]; history of herpes, mononucleosis, rubella, blood transfusion (OR>2.5, P<0.01 for all); while for IJ risk factors included growing fruits and vegetables, OR = 1.87 [CI:1.11–3.15]; and self-reported autoimmune diseases, OR = 1.99 [CI:1.34–2.95].</p><p>Conclusions</p><p>In these geographically proximate populations we found some unique risk factors for B-NHL. Heterogeneity in the observed associations by ethnicity could reflect differences in lifestyle, medical systems, and reporting patterns, while variations by histology infer specific etiologic factors for lymphoma subtypes.</p></div

Life style exposures- Adjusted OR for B-NHL and subtypes, overall and by population^□.

<p>Lists the overall odds ratio (OR) with 95% confidence interval (CI) for all risk factors affecting overall B-cell non-Hodgkin lymphoma (B-NHL) and subtypes: diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL) and marginal zone lymphoma (MZL), stratified by population (Jews, Arabs), frequency matched by sex and age categories (4 year groupings); adjusted for marital status, education (yrs), ethnic origin for Jews (Ashkenazi, North African, West Asian and Sephardic) and residential region for Arabs (North, South, Center, other). The columns list the exposure category and the OR. The colored grid indicates the OR associated with the exposure for each subtype separately. Red (blue) represents the exposure increases (decreases) risk. ^Xindicates an association with P<0.05, whereas ^XXindicates P<0.01. <i>m</i> indicates missing due to lack of data. <i>Int</i> indicates interaction between exposure and sub-populations P<0.05. ^□based on schema designed by Morton et al.</p