Typhoid fever is endemic in many parts of the world and remains a major public health concern in tropical and sub-tropical developing nations, including Fiji. To address high rates of typhoid fever, the Northern Division of Fiji implemented a mass vaccination with typhoid conjugate vaccine (Vi-polysaccharide conjugated to tetanus toxoid) as a public health control measure in 2023. In this study we define the genomic epidemiology of Salmonella Typhi in the Northern Division prior to island-wide vaccination, sequencing 85% (n=419) of the total cases from the Northern and Central Divisions of Fiji that occurred in the period 2017-2019. We found elevated rates of nucleotide polymorphisms in the tviD and tviE genes (responsible for Vi-polysaccharide synthesis) relative to core genome levels within the Fiji endemic S. Typhi genotype 4.2. Expansion of these findings within a globally representative database of 12 382 S. Typhi (86 genotyphi clusters) showed evidence of convergent evolution of the same tviE mutations across the S. Typhi population, indicating that tvi selection has occurred both independently and globally. The functional impact of tvi mutations on the Vi-capsular structure and other phenotypic characteristics are not fully elucidated, yet commonly occurring tviE polymorphisms localize adjacent to predicted active site residues when overlayed against the predicted TviE protein structure. Given the central role of the Vi-polysaccharide in S. Typhi biology and vaccination, further integrated epidemiological, genomic and phenotypic surveillance is required to determine the spread and functional implications of these mutations.

In the yeast Saccharomyces cerevisiae, two types of trehalase activities have been described. Neutral trehalases (Nth1 and Nth2) are considered to be the main proteins that catalyze intracellular trehalose mobilization. In addition to Nth1 and Nth2, studies have shown that acid trehalase Ath1 is required for extracellular trehalose degradation. Although both neutral and acid-type trehalases have been predominantly investigated in laboratory strains of S. cerevisiae, we sought to examine the phenotypic consequences of disrupting these genes in wild strains. In this study, we constructed mutants of the trehalose degradation pathway (NTH1, NTH2, and ATH1) in five diverse S. cerevisiae strains to examine whether published lab strain phenotypes are also exhibited by wild strains. For each mutant we assessed a number of phenotypes for comparison to trehalose biosynthesis mutants, including trehalose production, glycogen production, cell size, acute thermotolerance, high temperature growth, sporulation efficiency, and growth on a variety of carbon sources in rich and minimal medium. We found that all trehalase mutants including single deletion nth1Δ, nth2Δ, and ath1Δ, as well as double deletion nth1nth2Δ accumulated higher intracellular trehalose levels compared to their isogenic wild type cells. Also, nth1Δ and nth1Δnth2Δ mutants exhibited mild thermal sensitivity, suggesting a potential minor role for trehalose mobilization when cells recover from stress. In addition, we evaluated phenotypes more directly relevant to trehalose degradation, including both extracellular and intracellular trehalose utilization. We discovered that intracellular trehalose hydrolysis is critical for typical spore germination progression, highlighting a role for trehalose in cell cycle regulation, likely as a storage carbohydrate providing glycolytic fuel. Additionally, our work provides further evidence suggesting Ath1 is indispensable for extracellular trehalose utilization as a carbon source, even in the presence of AGT1.

BACKGROUND: This study investigates the mutational profile of the KIT gene in primary and metastatic melanomas, highlighting the significance of genetic heterogeneity.
METHODS: This research is a retrospective cohort that includes formalin-fixed and paraffin-embedded melanoma samples obtained from Hospital São Paulo, Brazil, between the years of 1996 and 2010. The research encompasses primary melanomas of the superficial spreading (SSM) and acral lentiginous (AL) subtypes and their metastases, using next-generation sequencing to explore genetic heterogeneity.
RESULTS: Despite losing 57 samples due to quality issues, 27 samples from 20 patients were analyzed, revealing a nearly equal distribution between AL and SSM subtypes. Both histological subtypes revealed KIT gene variants, including previously undescribed variants and polymorphisms, emphasizing the role of such mutations in melanoma pathogenesis and the potential for targeted therapies. Tumor heterogeneity was also observed in both histological subtypes.
CONCLUSIONS: The study underscores the complexity of melanoma, driven by diverse mutational landscapes within and across tumors and advocates for personalized treatment approaches based on detailed molecular profiling. Despite limitations like sample size, this research lays the groundwork for further investigation into melanoma\'s genetic intricacies and therapeutic vulnerabilities.

BACKGROUND: The metastasis of cancer cells is influenced by both their intrinsic characteristics and the tumor microenvironment (TME). However, the molecular mechanisms underlying pre-nodal metastases of breast cancer remain unclear.
METHODS: We integrated a total of 216,963 cells from 54 samples across 6 single-cell datasets to profile the cellular landscape differences between primary tumors and pre-nodal metastases.
RESULTS: We revealed three distinct metastatic epithelial cell subtypes (Epi1, Epi2 and Epi3), which exhibited different metastatic mechanisms. Specifically, the marker gene KCNK15 of the Epi1 subtype exhibited increased gene expression along the cell differentiation trajectory and was specifically regulated by the transcription factor ASCL1. In the Epi3 subtype, we highlighted NR2F1 as a regulator targeting the marker gene MUCL1. Additionally, we found that the Epi2 and Epi3 subtypes shared some regulons, such as ZEB1 and NR2C1. Similarly, we identified specific subtypes of stromal and immune cells in the TME, and discovered that vascular cancer-associated fibroblasts might promote capillary formation through CXCL9+ macrophages in pre-nodal metastases. All three subtypes of metastatic epithelial cells were associated with poor prognosis.
CONCLUSIONS: In summary, this study dissects the intratumoral heterogeneity and remodeling of the TME in pre-nodal metastases of breast cancer, providing novel insights into the mechanisms underlying breast cancer metastasis.

Colorectal cancer (CRC) is one of most common tumors worldwide, causing a prominent global health burden. Cell senescence is a complex physiological state, characterized by proliferation arrest. Here, we investigated the role of cellular senescence in the heterogeneity of CRC. Based on senescence-associated genes, CRC samples were classified into different senescence patterns with different survival, cancer-related biological processes and immune cell infiltrations. A senescence-related model was then developed to calculate the senescence-related score to comprehensively explore the heterogeneity of each CRC sample such as stromal activities, immunoreactivities and drug sensitivity. Single-cell analysis revealed there were different immune cell infiltrations between low and high senescence-related model genes enrichment groups, which was confirmed by multiplex immunofluorescence staining. Pseudotime analysis indicated model genes play a pivotal role in the evolution of B cells. Besides, intercellular communication modeled by NicheNet showed tumor cells with higher enrichment of senescence-related model genes highly expressed CXCL2/3 and CCL3/4, which attracted immunosuppressive cell infiltration and promoted tumor metastasis. Finally, top 6 hub genes were identified from senescence-related model genes by PPI analysis. And RT-qPCR revealed the expression differences of hub genes between normal and CRC cell lines, indicating to some extent the clinical practicability of senescence-related model. To sum up, our study explores the impact of cellular senescence on the prognosis, TME and treatment of CRC based on senescence patterns. This provides a new perspective for CRC treatment.

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). TNBC has a poor prognosis due to high intratumoral heterogeneity and metastasis, pointing to the need to explore distinct molecular subtypes and gene regulatory networks.
METHODS: The scRNA-seq data of five primary BC samples were downloaded from the Gene Expression Omnibus (GEO) database. Clustering was performed based on filtered and normalized data using the Seurat R package to identify marker genes, which were subsequently annotated to each subset using the CellMarker database. AUCell R package was applied to calculate the hallmark score for each epithelial cell. Marker genes of each subset were screened with FindAllMarkers and their biological functions were analyzed using the Database for Annotation Visualization and Integrated Discovery (DAVID) database. Next, cell-cell communication was performed with the CellChat R package. To identify the key regulatory genes, single-cell regulatory network inference and clustering (SCENIC) analysis was conducted. Finally, the expression and potential biological functions of the key regulatory factors were verified through cellular experiments.
RESULTS: A total of 29,101 cells were classified into nine cell subsets, namely, Fibroblasts, Fibroepithelial cells, Epithelial cells 1, Epithelial cells 2, Epithelial cells 3, Endothelial cells, T cells, Plasma B cells and Macrophages. Particularly, the epithelial cells had a higher proportion and higher transforming growth factor-β (TGF-β) activity in the TNBC pathotype as compared to the non-TNBC pathotype. Furthermore, four epithelial cell subsets (marked as Stearoyl-CoA Desaturase (SCD1), marker of proliferation Ki67 (MKI67), Annexin A3 (ANXA3) and aquaporin 5 (AQP5)) were identified as having the greatest impact on the TNBC pathotype. Cell-cell interaction analysis revealed that ANXA3-epithelial cell subset suppressed the T cell function through different mechanisms. C-fos gene (FOS) and X-box binding protein 1 (XBP1) were considered critical regulons involved in TNBC progression. Notably, cellular experiments demonstrated that silencing XBP1 and overexpressing FOS inhibited cancer cell invasion.
CONCLUSIONS: The four epithelial cell subsets and two critical regulons identified based on the scRNA-seq data could help explore the underlying intratumoral heterogeneity molecular mechanism and develop effective therapies for TNBC.

Tumor heterogeneity refers to the diversity observed among tumor cells: both between different tumors (inter-tumor heterogeneity) and within a single tumor (intra-tumor heterogeneity). These cells can display distinct morphological and phenotypic characteristics, including variations in cellular morphology, metastatic potential and variability treatment responses among patients. Therefore, a comprehensive understanding of such heterogeneity is necessary for deciphering tumor-specific mechanisms that may be diagnostically and therapeutically valuable. Innovative and multidisciplinary approaches are needed to understand this complex feature. In this context, proteogenomics has been emerging as a significant resource for integrating omics fields such as genomics and proteomics. By combining data obtained from both Next-Generation Sequencing (NGS) technologies and mass spectrometry (MS) analyses, proteogenomics aims to provide a comprehensive view of tumor heterogeneity. This approach reveals molecular alterations and phenotypic features related to tumor subtypes, potentially identifying therapeutic biomarkers. Many achievements have been made; however, despite continuous advances in proteogenomics-based methodologies, several challenges remain: in particular the limitations in sensitivity and specificity and the lack of optimal study models. This review highlights the impact of proteogenomics on characterizing tumor phenotypes, focusing on the critical challenges and current limitations of its use in different clinical and preclinical models for tumor phenotypic characterization.

Glioblastoma cell lines derived from different patients are widely used in tumor biology research and drug screening. A key feature of glioblastoma is the high level of inter- and intratumor heterogeneity that accounts for treatment resistance. Our aim was to investigate whether intratumor heterogeneity is maintained in cell models. Single-cell RNA sequencing was used to investigate the cellular composition of a tumor sample and six patient-derived glioblastoma cell lines. Three cell lines preserved the mutational profile of the original tumor, whereas three others differed from their precursors. Copy-number variation analysis showed significantly rearranged genomes in all the cell lines and in the tumor sample. The tumor had the most complex cell composition, including cancer cells and microenvironmental cells. Cell lines with a conserved genome had less diverse cellularity, and during cultivation, a relative increase in the stem-cell-derived progenitors was noticed. Cell lines with genomes different from those of the primary tumors mainly contained neural progenitor cells and microenvironmental cells. The establishment of cell lines without the driver mutations that are intrinsic to the original tumors may be related to the selection of clones or cell populations during cultivation. Thus, patient-derived glioblastoma cell lines differ substantially in their cellular profile, which should be taken into account in translational studies.

Cancer is a significant global health issue, with treatment challenges arising from intratumor heterogeneity. This heterogeneity stems mainly from somatic evolution, causing genetic diversity within the tumor, and phenotypic plasticity of tumor cells leading to reversible phenotypic changes. However, the interplay of both factors has not been rigorously investigated. Here, we examine the complex relationship between somatic evolution and phenotypic plasticity, explicitly focusing on the interplay between cell migration and proliferation. This type of phenotypic plasticity is essential in glioblastoma, the most aggressive form of brain tumor. We propose that somatic evolution alters the regulation of phenotypic plasticity in tumor cells, specifically the reaction to changes in the microenvironment. We study this hypothesis using a novel, spatially explicit model that tracks individual cells\' phenotypic and genetic states. We assume cells change between migratory and proliferative states controlled by inherited and mutation-driven genotypes and the cells\' microenvironment. We observe that cells at the tumor edge evolve to favor migration over proliferation and vice versa in the tumor bulk. Notably, different genetic configurations can result in this pattern of phenotypic heterogeneity. We analytically predict the outcome of the evolutionary process, showing that it depends on the tumor microenvironment. Synthetic tumors display varying levels of genetic and phenotypic heterogeneity, which we show are predictors of tumor recurrence time after treatment. Interestingly, higher phenotypic heterogeneity predicts poor treatment outcomes, unlike genetic heterogeneity. Our research offers a novel explanation for heterogeneous patterns of tumor recurrence in glioblastoma patients.

BACKGROUND: Cellular angiofibroma, a rare benign mesenchymal neoplasm, is classified within the 13q/RB1 family of tumors due to morphological, immunohistochemical, and genetic similarities with spindle cell lipoma. Here, genetic data reveal pathogenetic heterogeneity in cellular angiofibroma.
METHODS: Three cellular angiofibromas were studied using G-banding/Karyotyping, array comparative genomic hybridization, RNA sequencing, and direct cycling sequencing.
RESULTS: The first tumor carried a del(13)(q12) together with heterozygous loss and minimal expression of the RB1 gene. Tumors two and three displayed chromosome 8 abnormalities associated with chimeras of the pleomorphic adenoma gene 1 (PLAG1). In tumor 2, the cathepsin B (CTSB) fused to PLAG1 (CTSB::PLAG1) while in tumor 3, the mir-99a-let-7c cluster host gene (MIR99AHG) fused to PLAG1 (MIR99AHG::PLAG1), both leading to elevated expression of PLAG1 and insulin growth factor 2.
CONCLUSIONS: This study uncovers two genetic pathways contributing to the pathogenetic heterogeneity within cellular angiofibromas. The first aligns with the 13q/RB1 family of tumors and the second involves PLAG1-chimeras. These findings highlight the diverse genetic landscape of cellular angiofibromas, providing insights into potential diagnostic strategies.