Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.

Cancer immunotherapy has witnessed rapid advancement in recent years, with a particular focus on neoantigens as promising targets for personalized treatments. The convergence of immunogenomics, bioinformatics, and artificial intelligence (AI) has propelled the development of innovative neoantigen discovery tools and pipelines. These tools have revolutionized our ability to identify tumor-specific antigens, providing the foundation for precision cancer immunotherapy.

CAR Gene Delivery by T-cell Targeted Lentiviral Vectors is Enhanced by Rapamycin Induced Reduction of Antiviral Mechanisms.

Lentiviral vectors (LV) have become the dominant tool for stable gene transfer into lymphocytes including chimeric antigen receptor (CAR) gene delivery to T cells, a major breakthrough in cancer therapy. Yet, room for improvement remains, especially for the latest LV generations delivering genes selectively into T cell subtypes, a key requirement for in vivo CAR T cell generation. Toward improving gene transfer rates with these vectors, whole transcriptome analyses on human T lymphocytes are conducted after exposure to CAR-encoding conventional vectors (VSV-LV) and vectors targeted to CD8+ (CD8-LV) or CD4+ T cells (CD4-LV).

DNA methylation reveals distinct cells of origin for pancreatic neuroendocrine carcinomas and pancreatic neuroendocrine tumors.

Background: Pancreatic neuroendocrine neoplasms (PanNENs) fall into two subclasses: the well-differentiated, low- to high-grade pancreatic neuroendocrine tumors (PanNETs), and the poorly-differentiated, high-grade pancreatic neuroendocrine carcinomas (PanNECs). While recent studies suggest an endocrine descent of PanNETs, the origin of PanNECs remains unknown.

Methods: We performed DNA methylation analysis for 57 PanNEN samples and found that distinct methylation profiles separated PanNENs into two major groups, clearly distinguishing high-grade PanNECs from other PanNETs including high-grade NETG3.

SAMHD1 in cancer: curse or cure?

Human sterile α motif and HD domain-containing protein 1 (SAMHD1), originally described as the major cellular deoxyribonucleoside triphosphate triphosphohydrolase (dNTPase) balancing the intracellular deoxynucleotide (dNTP) pool, has come recently into focus of cancer research. As outlined in this review, SAMHD1 has been reported to be mutated in a variety of cancer types and the expression of SAMHD1 is dysregulated in many cancers. Therefore, SAMHD1 is regarded as a tumor suppressor in certain tumors.

Adaptive T-cell immunity controls senescence-prone MyD88- or CARD11-mutant B-cell lymphomas.

Aberrant B-cell receptor/NF-κB signaling is a hallmark feature of B-cell non-Hodgkin lymphomas, especially in diffuse large B-cell lymphoma (DLBCL). Recurrent mutations in this cascade, for example, in CD79B, CARD11, or NFKBIZ, and also in the Toll-like receptor pathway transducer MyD88, all deregulate NF-κB, but their differential impact on lymphoma development and biology remains to be determined. Here, we functionally investigate primary mouse lymphomas that formed in recipient mice of Eµ-myc transgenic hematopoietic stem cells stably transduced with naturally occurring NF-κB mutants.

Shine-Dalgarno Sequences Play an Essential Role in the Translation of Plastid mRNAs in Tobacco.

In prokaryotic systems, the translation initiation of many, though not all, mRNAs depends on interaction between a sequence element upstream of the start codon (the Shine-Dalgarno sequence [SD]) and a complementary sequence in the 3' end of the 16S rRNA (anti-Shine-Dalgarno sequence [aSD]). Although many chloroplast mRNAs harbor putative SDs in their 5' untranslated regions and the aSD displays strong conservation, the functional relevance of SD-aSD interactions in plastid translation is unclear. Here, by generating transplastomic tobacco () mutants with point mutations in the aSD coupled with genome-wide analysis of translation by ribosome profiling, we provide a global picture of SD-dependent translation in plastids.

DNA copy number changes define spatial patterns of heterogeneity in colorectal cancer.

Genetic heterogeneity between and within tumours is a major factor determining cancer progression and therapy response. Here we examined DNA sequence and DNA copy-number heterogeneity in colorectal cancer (CRC) by targeted high-depth sequencing of 100 most frequently altered genes. In 97 samples, with primary tumours and matched metastases from 27 patients, we observe inter-tumour concordance for coding mutations; in contrast, gene copy numbers are highly discordant between primary tumours and metastases as validated by fluorescent in situ hybridization.

SoFIA: a data integration framework for annotating high-throughput datasets.

Motivation: Integrating heterogeneous datasets from several sources is a common bioinformatics task that often requires implementing a complex workflow intermixing database access, data filtering, format conversions, identifier mapping, among further diverse operations. Data integration is especially important when annotating next generation sequencing data, where a multitude of diverse tools and heterogeneous databases can be used to provide a large variety of annotation for genomic locations, such a single nucleotide variants or genes. Each tool and data source is potentially useful for a given project and often more than one are used in parallel for the same purpose.

Assembly of a comprehensive regulatory network for the mammalian circadian clock: a bioinformatics approach.

By regulating the timing of cellular processes, the circadian clock provides a way to adapt physiology and behaviour to the geophysical time. In mammals, a light-entrainable master clock located in the suprachiasmatic nucleus (SCN) controls peripheral clocks that are present in virtually every body cell. Defective circadian timing is associated with several pathologies such as cancer and metabolic and sleep disorders.

Identification of cis-elements conferring high levels of gene expression in non-green plastids.

Although our knowledge about the mechanisms of gene expression in chloroplasts has increased substantially over the past decades, next to nothing is known about the signals and factors that govern expression of the plastid genome in non-green tissues. Here we report the development of a quantitative method suitable for determining the activity of cis-acting elements for gene expression in non-green plastids. The in vivo assay is based on stable transformation of the plastid genome and the discovery that root length upon seedling growth in the presence of the plastid translational inhibitor kanamycin is directly proportional to the expression strength of the resistance gene nptII in transgenic tobacco plastids.

Clinal variation in the non-acclimated and cold-acclimated freezing tolerance of Arabidopsis thaliana accessions.

Arabidopsis thaliana is a geographically widely spread species consisting of local accessions differing both genetically and phenotypically. These differences may constitute environmental adaptations and a latitudinal cline in freezing tolerance has been shown previously. Many plants, including Arabidopsis, exhibit increased freezing tolerance after cold exposure (cold acclimation).

Matapax: an online high-throughput genome-wide association study pipeline.

High-throughput sequencing and genotyping methods are dramatically increasing the number of observable genetic intraspecies differences that can be exploited as genetic markers. In addition, automated phenotyping platforms and "omics" profiling technologies further enlarge the set of quantifiable macroscopic and molecular traits at an ever-increasing pace. Combined, both lines of technological advances create unparalleled opportunities to identify candidate gene regions and, ideally, even single genes responsible for observed variations in a particular trait via association studies.

Local absence of secondary structure permits translation of mRNAs that lack ribosome-binding sites.

The initiation of translation is a fundamental and highly regulated process in gene expression. Translation initiation in prokaryotic systems usually requires interaction between the ribosome and an mRNA sequence upstream of the initiation codon, the so-called ribosome-binding site (Shine-Dalgarno sequence). However, a large number of genes do not possess Shine-Dalgarno sequences, and it is unknown how start codon recognition occurs in these mRNAs.

SLocX: Predicting Subcellular Localization of Arabidopsis Proteins Leveraging Gene Expression Data.

Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance.

Robin: an intuitive wizard application for R-based expression microarray quality assessment and analysis.

The wide application of high-throughput transcriptomics using microarrays has generated a plethora of technical platforms, data repositories, and sophisticated statistical analysis methods, leaving the individual scientist with the problem of choosing the appropriate approach to address a biological question. Several software applications that provide a rich environment for microarray analysis and data storage are available (e.g.

Single feature polymorphism (SFP)-based selective sweep identification and association mapping of growth-related metabolic traits in Arabidopsis thaliana.

Background: Natural accessions of Arabidopsis thaliana are characterized by a high level of phenotypic variation that can be used to investigate the extent and mode of selection on the primary metabolic traits. A collection of 54 A. thaliana natural accession-derived lines were subjected to deep genotyping through Single Feature Polymorphism (SFP) detection via genomic DNA hybridization to Arabidopsis Tiling 1.

Identification and classification of ncRNA molecules using graph properties.

The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functional and, furthermore, into Rfam families based on their graph properties.