Modeling the Repertoire of True Tumor-Specific MHC I Epitopes in a Human Tumor

DNA replication has a finite measurable error rate, net of repair, in all cells. Clonal proliferation of cancer cells leads therefore to accumulation of random mutations. A proportion of these mutational events can create new immunogenic epitopes that, if processed and presented by an MHC allele, may be recognized by the adaptive immune system. Here, we use probability theory to analyze the mutational and epitope composition of a tumor mass in successive division cycles and create a double Pölya model for calculating the number of truly tumor-specific MHC I epitopes in a human tumor. We deduce that depending upon tumor size, the degree of genomic instability and the degree of death within a tumor, human tumors have several tens to low hundreds of new, truly tumor-specific epitopes. Parenthetically, cancer stem cells, due to the asymmetry in their proliferative properties, shall harbor significantly fewer mutations, and therefore significantly fewer immunogenic epitopes. As the overwhelming majority of the mutations in cancer cells are unrelated to malignancy, the mutation-generated epitopes shall be specific for each individual tumor, and constitute the antigenic fingerprint of each tumor. These calculations highlight the benefits for personalization of immunotherapy of human cancer, and in view of the substantial pre-existing antigenic repertoire of tumors, emphasize the enormous potential of therapies that modulate the anti-cancer immune response by liberating it from inhibitory influences

Towards accurate detection and genotyping of expressed variants from whole transcriptome sequencing data

BACKGROUND: Massively parallel transcriptome sequencing (RNA-Seq) is becoming the method of choice for studying functional effects of genetic variability and establishing causal relationships between genetic variants and disease. However, RNA-Seq poses new technical and computational challenges compared to genome sequencing. In particular, mapping transcriptome reads onto the genome is more challenging than mapping genomic reads due to splicing. Furthermore, detection and genotyping of single nucleotide variants (SNVs) requires statistical models that are robust to variability in read coverage due to unequal transcript expression levels. RESULTS: In this paper we present a strategy to more reliably map transcriptome reads by taking advantage of the availability of both the genome reference sequence and transcript databases such as CCDS. We also present a novel Bayesian model for SNV discovery and genotyping based on quality scores. CONCLUSIONS: Experimental results on RNA-Seq data generated from blood cell tissue of three Hapmap individuals show that our methods yield increased accuracy compared to several widely used methods. The open source code implementing our methods, released under the GNU General Public License, is available at http://dna.engr.uconn.edu/software/NGSTools/

Heat Shock Protein gp96 Is a Master Chaperone for Toll-like Receptors and Is Important in the Innate Function of Macrophages

Summarygp96 is an endoplasmic reticulum chaperone for cell-surface Toll-like receptors (TLRs). Little is known about its roles in chaperoning other TLRs or in the biology of macrophage in vivo. We generated a macrophage-specific gp96-deficient mouse. Despite normal development and activation by interferon-γ, tumor necrosis factor-α, and interleukin-1β, the mutant macrophages failed to respond to ligands of both cell-surface and intracellular TLRs including TLR2, TLR4, TLR5, TLR7, and TLR9. Furthermore, we found that TLR4 and TLR9 preferentially interacted with a super-glycosylated gp96 species. The categorical loss of TLRs in gp96-deficient macrophages operationally created a conditional and cell-specific TLR null mouse. These mice were resistant to endotoxin shock but were highly susceptible to Listeria monocytogenes. Our results demonstrate that gp96 is the master chaperone for TLRs and that macrophages, but not other myeloid cells, are the dominant source of proinflammatory cytokines during endotoxemia and Listeria infections

Human Tumor-Derived Heat Shock Protein 96 Mediates In Vitro Activation and In Vivo Expansion of Melanoma- and Colon Carcinoma-Specific T Cells

Abstract Heat shock proteins (hsp) 96 play an essential role in protein metabolism and exert stimulatory activities on innate and adaptive immunity. Vaccination with tumor-derived hsp96 induces CD8+ T cell-mediated tumor regressions in different animal models. In this study, we show that hsp96 purified from human melanoma or colon carcinoma activate tumor- and Ag-specific T cells in vitro and expand them in vivo. HLA-A*0201-restricted CD8+ T cells recognizing Ags expressed in human melanoma (melanoma Ag recognized by T cell-1 (MART-1)/melanoma Ag A (Melan-A)) or colon carcinoma (carcinoembryonic Ag (CEA)/epithelial cell adhesion molecule (EpCAM)) were triggered to release IFN-γ and to mediate cytotoxic activity by HLA-A*0201-matched APCs pulsed with hsp96 purified from tumor cells expressing the relevant Ag. Such activation occurred in class I HLA-restricted fashion and appeared to be significantly higher than that achieved by direct peptide loading. Immunization with autologous tumor-derived hsp96 induced a significant increase in the recognition of MART-1/Melan-A27–35 in three of five HLA-A*0201 melanoma patients, and of CEA571–579 and EpCAM263–271 in two of five HLA-A*0201 colon carcinoma patients, respectively, as detected by ELISPOT and HLA/tetramer staining. These increments in Ag-specific T cell responses were associated with a favorable disease course after hsp96 vaccination. Altogether, these data provide evidence that hsp96 derived from human tumors can present antigenic peptides to CD8+ T cells and activate them both in vitro and in vivo, thus representing an important tool for vaccination in cancer patients

Creating an Antibacterial with in Vivo Efficacy: Synthesis and Characterization of Potent Inhibitors of the Bacterial Cell Division Protein FtsZ with Improved Pharmaceutical Properties

3-Methoxybenzamide (1) is a weak inhibitor of the essential bacterial cell division protein FtsZ. Alkyl derivatives of 1 are potent antistaphylococcal compounds with suboptimal drug-like properties. Exploration of the structure-activity relationships of analogues of these inhibitors led to the identification of potent antistaphylococcal compounds with improved pharmaceutical properties

Effect of Growth Temperature on Bamboo-shaped Carbon–Nitrogen (C–N) Nanotubes Synthesized Using Ferrocene Acetonitrile Precursor

This investigation deals with the effect of growth temperature on the microstructure, nitrogen content, and crystallinity of C–N nanotubes. The X-ray photoelectron spectroscopic (XPS) study reveals that the atomic percentage of nitrogen content in nanotubes decreases with an increase in growth temperature. Transmission electron microscopic investigations indicate that the bamboo compartment distance increases with an increase in growth temperature. The diameter of the nanotubes also increases with increasing growth temperature. Raman modes sharpen while the normalized intensity of the defect mode decreases almost linearly with increasing growth temperature. These changes are attributed to the reduction of defect concentration due to an increase in crystal planar domain sizes in graphite sheets with increasing temperature. Both XPS and Raman spectral observations indicate that the C–N nanotubes grown at lower temperatures possess higher degree of disorder and higher N incorporation

Classification of current anticancer immunotherapies

During the past decades, anticancer immunotherapy has evolved from a promising therapeutic option to a robust clinical reality. Many immunotherapeutic regimens are now approved by the US Food and Drug Administration and the European Medicines Agency for use in cancer patients, and many others are being investigated as standalone therapeutic interventions or combined with conventional treatments in clinical studies. Immunotherapies may be subdivided into “passive” and “active” based on their ability to engage the host immune system against cancer. Since the anticancer activity of most passive immunotherapeutics (including tumor-targeting monoclonal antibodies) also relies on the host immune system, this classification does not properly reflect the complexity of the drug-host-tumor interaction. Alternatively, anticancer immunotherapeutics can be classified according to their antigen specificity. While some immunotherapies specifically target one (or a few) defined tumor-associated antigen(s), others operate in a relatively non-specific manner and boost natural or therapy-elicited anticancer immune responses of unknown and often broad specificity. Here, we propose a critical, integrated classification of anticancer immunotherapies and discuss the clinical relevance of these approaches

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation