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Spatial transcriptomics technology enables the mapping of gene expression within tissues, allowing researchers to visualize the spatial distribution of RNA molecules and gain insights into cellular organization, interactions, and functions in their native environments. A variety of spatial technologies are now commercially available, each offering distinct technical parameters such as cellular resolution, detection sensitivity, gene coverage, and throughput. This wide range of options can make it challenges or create confusion for researchers to select the most appropriate platform for their specific research objectives. In this paper, we will analyze and compare seven major commercially available spatial platforms to guide researchers in choosing the most suitable option for their needs.

The diverse cell types of an organ have a highly structured organization to enable their efficient and correct function. To fully appreciate gene functions in a given cell type, one needs to understand how much, when and where the gene is expressed. Classic bulk RNA sequencing and popular single cell sequencing destroy cell structural organization and fail to provide spatial information. However, the spatial location of gene expression or of the cell in a complex tissue provides key clues to comprehend how the neighboring genes or cells cross talk, transduce signals and work together as a team to complete the job. The functional requirement for the spatial content has been a driving force for rapid development of the spatial transcriptomics technologies in the past few years. Here, we present an overview of current spatial technologies with a special focus on the commercially available or currently being commercialized technologies, highlight their applications by category and discuss experimental considerations for a first spatial experiment.

Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived healthy normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min - 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact differential expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice.

Introduction: Endocrine system disorders are a serious public health burden and can be caused by deleterious genetic variants in single genes or by the combined effects of multiple variants along with environmental and lifestyle factors. Methods: The EndoGene database presents the results of next-generation sequencing assays used to genetically profile 5,926 patients who were diagnosed with 450 endocrine and concomitant diseases and were examined and treated at the National Medical Research Center for Endocrinology between November 2017 and January 2024. Among them, 494, 1,785, 692, and 1,941 patients were profiled using four internally developed genetic panels including 220, 250, 376, and 382 genes, respectively, selected based on a literature analysis and clinical recommendations, and 1,245 patients were profiled by whole exome sequencing covering 31,969 genes. Results: 2,711 genetic variants were reported as clinically relevant by medical geneticists and are presented here along with genomic, technical, and clinical annotations. Discussion: This publicly accessible database will be useful to those interested in genetics, epidemiology, population statistics, and a better understanding of the molecular basis of endocrine disorders. [ABSTRACT FROM AUTHOR]

Simple Summary: Endogenous Cushing's syndrome is a rare disorder caused by excessive cortisol most commonly due to elevated ACTH produced by neuroendocrine tumors. These tumors most commonly arise in the pituitary gland (Cushing's disease) but can also originate in other parts of the body (ectopic ACTH syndrome). Distinguishing between pituitary and ectopic causes is essential for choosing the best treatment, yet current tools are not always optimal. Our research compares the transcriptome patterns of pituitary and ectopic tumors to discover unique markers and possible new drug targets. This research provides new insights into specific molecules and pathways linked to each tumor type, common mechanisms of ACTH-secretion, and suggests promising diagnostics and treatment targets for future research. The analysis of the experimental efficacy of existing medications registered for other oncological disorders may provide new perspectives for these rare orphan disorders in cases where traditional treatment options have been exhausted. Background/Objectives: Endogenous Cushing's syndrome (CS) is a rare neuroendocrine disorder often resulting from adrenocorticotropic hormone (ACTH) production by a pituitary or ectopic tumor. The biological mechanisms underlying ACTH-secreting tumors, especially non-pituitary, remain poorly understood. This study aimed to explore the transcriptomic profiles of pituitary and ectopic ACTH-secreting tumors (ASTs) to identify potential biomarkers for differential diagnosis and new therapeutic targets. Methods: In this study, we performed a transcriptome-wide analysis of twenty-pituitary, one pancreatic, and six lung ASTs, along with seven pituitary, eight pancreatic, and eight lung healthy control tissue samples, respectively. Results: The transcriptomic analysis revealed distinct profiles between pituitary and ectopic ACTH-secreting tumors. In all ASTs, except for the pancreatic sample, we found an overexpression of the TBX19 and PITX1 transcription factor genes, which promote the overexpression of POMC. The transcriptional profiles of ectopic lung ASTs showed marked overexpression of the gastrin-releasing peptide and calcitonin genes, which may be potentially useful for diagnostic purposes. We identified several transcriptionally activated molecular pathways in ASTs that might be targetable with existing medications to treat cancer, the most potentially promising of which are RET inhibitors and an IL6R inhibitor. We also predicted and experimentally validated that corticotropinomas express ganglioside 2 molecules, offering new therapeutic targets for Cushing's disease. Conclusions: This study provides new insights into the molecular features of ACTH-secreting tumors and identifies potential diagnostic markers and therapeutic targets. Distinct transcriptomic profiles in pituitary and ectopic tumors highlight unique biomarkers that may improve diagnostic accuracy and facilitate the development of targeted therapies for ACTH-dependent CS. [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitors (ICIs) treatment have shown high efficacy for about 15 cancer types. However, this therapy is only effective in 20-30% of cancer patients. Thus, the precise biomarkers of ICI response are an urgent need. Methods: We conducted a prospective observational study of the prognostic potential ofseveral existing and putative biomarkers of response to immunotherapy in acohort of 85 patients with lung cancer (LC) receiving PD-1 or PD-L1 targeted ICIs. Tumor biosamples were obtained prior to ICI treatment and profiled by whole exome and RNA sequencing. The entire 403 putative biomarkers were screened, including tumor mutation burden (TMB) and number of cancer neoantigens, 131 specific HLA alleles, homozygous state of 11 HLA alleles and their superfamilies; four gene mutation biomarkers, expression of 45 immune checkpoint genes and closely related genes, and three previously published diagnostic gene signatures; for the first time, activation levels of 188 molecular pathways containing immune checkpoint genes and activation levels of 19 pathways algorithmically generated using a human interactome model centered around immune checkpoint genes. Treatment outcomes and/or progression-free survival (PFS) times were available for 61 of 85 patients with LC, including 24 patients with adenocarcinoma and 27 patients with squamous cell LC, whose samples were further analyzed. For the rest 24 patients, both treatment outcomes and PFS data could not be collected. Of these, 54 patients were treated with PD1-specific and 7 patients with PD-L1-specific ICIs. We evaluated the potential of biomarkers based on PFS and RECIST treatment response data. Results: In our sample, 45 biomarkers were statistically significantly associated with PFS and 44 with response to treatment, of which eight were shared. Five of these (CD3G and NCAM1 gene expression levels, and levels of activation of Adrenergic signaling in cardiomyocytes, Growth hormone signaling, and Endothelin molecular pathways) were used in our signature that showed an AUC of 0.73 and HR of 0.27 (p=0.00034) on the experimental dataset. This signature was also reliable (AUC 0.76, 0.87) for the independent publicly available LC datasets GSE207422, GSE126044 annotated with ICI response data and demonstrated same survival trends on independent dataset GSE135222 annotated with PFS data. In both experimental and one independent datasets annotated with samples' histotypes, the signature worked better for lung adenocarcinoma than for squamous cell LC. Conclusion: The high reliability of our signature to predict response and PFS after ICI treatment was demonstrated using experimental and 3 independent datasets. Additionally, annotated molecular profiles obtained in this study were made publicly accessible. [ABSTRACT FROM AUTHOR]

Abstract: The metabolism of zinc and manganese plays a pivotal role in cancer progression by mediating cancer cell growth and metastasis. The SLC30A family proteins SLC30A3 and SLC30A10 mediate the efflux of zinc, manganese, and probably other transition element ions outside the cytoplasm to the extracellular space or into intracellular membrane compartments. The SLC39A family members SLC39A8 and SLC39A14 are their functional antagonists that transfer these ions into the cytoplasm. Recently, the SLC30A10 gene was suggested as a promising methylation biomarker of colorectal cancer. Here, we investigated whether forced overexpression or inactivation of SLC30A and SLC39A family genes has an impact on the phenotype of cancer cells and their sensitivity to cancer therapeutics. In the human colon adenocarcinoma HCT-15 and duodenal adenocarcinoma HuTu80 cell lines, we generated clones with knockouts of the SLC39A8 and SLC39A14 genes and forced overexpression of the SLC30A3, SLC30A10, and SLC39A8 genes. Gene expression in the mutant and control cells was assessed by RNA sequencing. The cell growth rate, mitochondrial activity, zinc accumulation, and sensitivity to the drugs cetuximab and cisplatin were investigated in functional tests. Overexpression or depletion of SLC30A or SLC39A family genes resulted in the deep reshaping of intracellular signaling and provoked hyperactivation of mitochondrial respiration. Variation in the expression of the SLC30A/SLC39A genes did not increase the sensitivity to cetuximab but significantly altered the sensitivity to cisplatin: overexpression of SLC30A10 resulted in an ~2.7–4 times increased IC50 of cisplatin, and overexpression of SLC30A3 resulted in an ~3.3 times decreased IC50 of cisplatin. The SLC30A/SLC39A genes should be considered as potential cancer drug resistance biomarkers and putative therapeutic targets. [ABSTRACT FROM AUTHOR]

Simple Summary: Chimeric transcripts frequently function as oncogenic drivers and represent potential targets for tumor-specific therapies. Routine methods for detecting these transcripts include (i) approaches that can detect a limited number of pre-defined targets, such as immunohistochemistry, fluorescence in situ hybridization, and reverse transcription–quantitative polymerase chain reaction, and (ii) approaches that can simultaneously detect multiple fusions, such as NanoString assays and NGS targeted panels. Whole transcriptome sequencing enables the analysis of a wide range of cancer biomarkers, including dysregulated genes, molecular pathways, and both known and novel cancer driver fusion transcripts. However, this method is not commonly employed for fusion discovery due to inadequate coverage at the fusion breakpoint. To address this limitation, we have developed a novel bioinformatics approach that enables the highly accurate prediction of clinically significant ALK fusions from RNA sequencing data. This extends the functionality of whole transcriptome NGS and improves its cost-effectiveness. Background: In clinical practice, various methods are used to identify ALK gene rearrangements in tumor samples, ranging from "classic" techniques, such as IHC, FISH, and RT-qPCR, to more advanced highly multiplexed approaches, such as NanoString technology and NGS panels. Each of these methods has its own advantages and disadvantages, but they share the drawback of detecting only a restricted (although sometimes quite extensive) set of preselected biomarkers. At the same time, whole transcriptome sequencing (WTS, RNAseq) can, in principle, be used to detect gene fusions while simultaneously analyzing an incomparably wide range of tumor characteristics. However, WTS is not widely used in practice due to purely analytical limitations and the high complexity of bioinformatic analysis, which requires considerable expertise. In particular, methods to detect gene fusions in RNAseq data rely on the identification of chimeric reads. However, the typically low number of true fusion reads in RNAseq limits its sensitivity. In a previous study, we observed asymmetry in the RNAseq exon coverage of the 3′ partners of some fusion transcripts. In this study, we conducted a comprehensive evaluation of the accuracy of ALK fusion detection through an analysis of differences in the coverage of its tyrosine kinase exons. Methods: A total of 906 human cancer biosamples were subjected to analysis using experimental RNAseq data, with the objective of determining the extent of asymmetry in ALK coverage. A total of 50 samples were analyzed, comprising 13 samples with predicted ALK fusions and 37 samples without predicted ALK fusions. These samples were assessed by targeted sequencing with two NGS panels that were specifically designed to detect fusion transcripts (the TruSight RNA Fusion Panel and the OncoFu Elite panel). Results: ALK fusions were confirmed in 11 out of the 13 predicted cases, with an overall accuracy of 96% (sensitivity 100%, specificity 94.9%). Two discordant cases exhibited low ALK coverage depth, which could be addressed algorithmically to enhance the accuracy of the results. It was also important to consider read strand specificity due to the presence of antisense transcripts involving parts of ALK. In a limited patient sample undergoing ALK-targeted therapy, the algorithm successfully predicted treatment efficacy. Conclusions: RNAseq exon coverage analysis can effectively detect ALK rearrangements. [ABSTRACT FROM AUTHOR]

Introduction: The differential ratio of nonsynonymous to synonymous nucleotide substitutions (dN/dS) is a common measure of the rate of structural evolution in proteincoding genes. In addition, we recently suggested that the proportion of transposable elements in gene promoters that host functional genomic sites serves as a marker of the rate of regulatory evolution of genes. Such functional genomic regions may include transcription factor binding sites and modified histone binding loci. Methods: Here, we constructed a model of the human interactome based on 600,136 documented molecular interactions and investigated the overall relationship between the number of interactions of each protein and the rate of structural and regulatory evolution of the corresponding genes. Results: By evaluating a total of 4,505 human genes and 1,936 molecular pathways we found a general correlation between structural and regulatory evolution rate metrics (Spearman 0.08–0.16 and 0.25–0.37 for gene and pathway levels, respectively, p < 0.01). Further exploration revealed in the established human interactome model lack of correlation between the rate of gene regulatory evolution and the number of protein interactions on gene level, and weak negative correlation (∼0.15) on pathway level. We also found a statistically significant negative correlation between the rate of gene structural evolution and the number of protein interactions (Spearman −0.11 and −0.3 for gene and pathway levels, respectively, p < 0.01). Discussion: Our result suggests stronger structural rather than regulatory conservation of genes whose protein products have multiple interaction partners. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM) is the most aggressive and lethal central nervous system (CNS) tumor. The treatment strategy is mainly surgery and/or radiation therapy, both combined with adjuvant temozolomide (TMZ) chemotherapy. Historically, methylation of MGMT gene promoter is used as the major biomarker predicting individual tumor response to TMZ. Objectives: This research aimed to analyze genes and molecular pathways of DNA repair as biomarkers for sensitivity to TMZ treatment in GBM using updated The Cancer Genome Atlas (TCGA) data and validate the results on experimental datasets. Methods: Survival analysis of GBM patients under TMZ therapy and hazard ratio (HR) calculation were used to assess all putative biomarkers on World Health Organization CNS5 reclassified TCGA project collection of molecular profiles and experimental multicenter GBM patient cohort. Pathway activation levels were calculated for 38 DNA repair pathways. TMZ sensitivity pathway was reconstructed using a human interactome model built using pairwise interactions extracted from 51,672 human molecular pathways. Results: We found that expression/activation levels of seven and six emerging gene/pathway biomarkers served as high-quality positive (HR < 0.61) and negative (HR > 1.63), respectively, patient survival biomarkers performing better than MGMT methylation. Positive survival biomarkers were enriched in the processes of ATM-dependent checkpoint activation and cell cycle arrest whereas negative—in excision DNA repair. We also built and characterized gene pathways which were informative for GBM patient survival following TMZ administration (HR 0.18–0.44, p < 0.0009; area under the curve 0.68–0.9). Conclusion: In this study, a comprehensive analysis of the expression of 361 DNA repair genes and activation levels of 38 DNA repair pathways revealed 13 potential survival biomarkers with increased prognostic potential compared to MGMT methylation. We algorithmically reconstructed the TMZ sensitivity pathway with strong predictive capacity in GBM. [ABSTRACT FROM AUTHOR]

Inorganic polyphosphates and respective metabolic pathways and enzymes are important factors for yeast active growth in unfavorable conditions. However, particular proteins of polyphosphate metabolism remain poorly explored in this context. Here we report biochemical and transcriptomic characterization of the CRN/PPN2 yeast strain (derived from Ppn1-lacking CRN strain) overexpressing poorly studied Ppn2 polyphosphatase. We showed that Ppn2 overexpression significantly reduced lag phase in the alkaline medium presumably due to the ability of Ppn2 to efficiently hydrolyze inorganic polyphosphates and thus neutralize hydroxide ions in the cell. With RNA-Seq, we compared the molecular phenotypes of CRN/PPN2 and its parent CRN strain grown in YPD or alkaline medium and detected transcriptomic changes induced by Ppn2 overexpression and reflecting the adaptation to alkaline conditions. The core set of upregulated genes included several genes with a previously unknown function. Respective knockout strains (∆ecm8, ∆yol160w, ∆cpp3, ∆ycr099c) exhibited defects of growth or cell morphology in the alkaline medium, proving the functional involvement of the respective proteins in sustaining growth in alkaline conditions. [ABSTRACT FROM AUTHOR]

Fifty-two years have passed since President Nixon launched the "War on Cancer". Despite unparalleled efforts and funds allocated worldwide, the outlined goals were not achieved because cancer treatment approaches such as chemotherapy, radiation therapy, hormonal and targeted therapies have not fully met the expectations. Based on the recent literature, a new direction in cancer therapy can be proposed which targets connections between cancer cells and their microenvironment by chemical means. Cancer–stromal synapses such as immunological synapses between cancer and immune cells provide an attractive target for this approach. Such synapses form ligand–receptor clusters on the interface of the interacting cells. They share a common property of involving intercellular clusters of spatially proximate and cooperatively acting proteins. Synapses provide the space for the focused intercellular signaling molecules exchange. Thus, the disassembly of cancer–stromal synapses may potentially cause the collapse of various tumors. Additionally, the clustered arrangement of synapse components offers opportunities to enhance treatment safety and precision by using targeted crosslinking chemical agents which may inactivate cancer synapses even in reduced concentrations. Furthermore, attaching a cleavable cell-permeable toxic agent(s) to a crosslinker may further enhance the anti-cancer effect of such therapeutics. The highlighted approach promises to be universal, relatively simple and cost-efficient. We also hope that, unlike chemotherapeutic and immune drugs that interact with a single target, by using supramolecular large clusters that include many different components as a target, the emergence of a resistance characteristic of chemo- and immunotherapy is extremely unlikely. [ABSTRACT FROM AUTHOR]

Statins, small molecular 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitors, are widely used to lower cholesterol levels in lipid-metabolism disorders. Recent preclinical and clinical studies have shown that statins exert beneficial effects in the management of breast cancer by increasing recurrence free survival. Unfortunately, the underlying mechanisms remain elusive.