Variation In Expression Research Articles

From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology

AbstractRNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.

Species variation in steroid hormone-related gene expression contributes to species diversity in sexually dimorphic communication in electric fishes

Sexually dimorphic behaviors are often regulated by gonadal steroid hormones. Species diversity in behavioral sex differences may arise as expression of genes mediating steroid action in brain regions controlling these behaviors evolves. The electric communication signals of apteronotid knifefishes are an excellent model for comparatively studying neuroendocrine regulation of sexually dimorphic behavior. These fish produce and detect weak electric organ discharges (EODs) for electrolocation and communication. EOD frequency (EODf), controlled by the medullary pacemaker nucleus (Pn), is sexually dimorphic and regulated by androgens and estrogens in some species, but is sexually monomorphic and unaffected by hormones in other species. We quantified expression of genes for steroid receptors, metabolizing enzymes, and cofactors in the Pn of two species with sexually dimorphic EODf (Apteronotus albifrons and Apteronotus leptorhynchus) and two species with sexually monomorphic EODf (“Apteronotus” bonapartii and Parapteronotus hasemani). The “A.” bonapartii Pn expressed lower levels of androgen receptor (AR) genes than the Pn of species with sexually dimorphic EODf. In contrast, the P. hasemani Pn robustly expressed AR genes, but expressed lower levels of genes for 5α-reductases, which convert androgens to more potent metabolites, and higher levels of genes for 17β-hydroxysteroid dehydrogenases that oxidize androgens and estrogens to less potent forms. These findings suggest that sexual monomorphism of EODf arose convergently via two different mechanisms. In “A.” bonapartii, reduced Pn expression of ARs likely results in insensitivity of EODf to androgens, whereas in P. hasemani, gonadal steroids may be metabolically inactivated in the Pn, reducing their potential to influence EODf.

Demultiplexing of single-cell RNA-sequencing data using interindividual variation in gene expression.

Pooled designs for single-cell RNA sequencing, where many cells from distinct samples are processed jointly, offer increased throughput and reduced batch variation. This study describes expression-aware demultiplexing (EAD), a computational method that employs differential co-expression patterns between individuals to demultiplex pooled samples without any extra experimental steps. We use synthetic sample pools and show that the top interindividual differentially co-expressed genes provide a distinct cluster of cells per individual, significantly enriching the regulation of metabolism. Our application of EAD to samples of six isogenic inbred mice demonstrated that controlling genetic and environmental effects can solve interindividual variations related to metabolic pathways. We utilized 30 samples from both sepsis and healthy individuals in six batches to assess the performance of classification approaches. The results indicate that combining genetic and EAD results can enhance the accuracy of assignments (Min. 0.94, Mean 0.98, Max. 1). The results were enhanced by an average of 1.4% when EAD and barcoding techniques were combined (Min. 1.25%, Median 1.33%, Max. 1.74%). Furthermore, we demonstrate that interindividual differential co-expression analysis within the same cell type can be used to identify cells from the same donor in different activation states. By analysing single-nuclei transcriptome profiles from the brain, we demonstrate that our method can be applied to nonimmune cells. EAD workflow is available at https://isarnassiri.github.io/scDIV/ as an R package called scDIV (acronym for single-cell RNA-sequencing data demultiplexing using interindividual variations).

Temporal insights into molecular and cellular responses during rAAV production in HEK293T cells

The gene therapy field seeks cost-effective, large-scale production of recombinant adeno-associated virus (rAAV) vectors for high-dosage therapeutic applications. Although strategies like suspension cell culture and transfection optimization have shown moderate success, challenges persist for large-scale applications. To unravel molecular and cellular mechanisms influencing rAAV production, we conducted a SWATH-MS proteomic analysis of HEK293T cells transfected using standard, sub-optimal, and optimal conditions. Gene Ontology and pathway analysis revealed significant protein expression variations, particularly in processes related to cellular homeostasis, metabolic regulation, vesicular transport, ribosomal biogenesis, and cellular proliferation under optimal transfection conditions. This resulted in a 50% increase in rAAV titer compared to the standard protocol. Additionally, we identified modifications in host cell proteins crucial for AAV mRNA stability and gene translation, particularly regarding AAV capsid transcripts under optimal transfection conditions. Our study identified 124 host proteins associated with AAV replication and assembly, each exhibiting distinct expression pattern throughout rAAV production stages in optimal transfection condition. This investigation sheds light on the cellular mechanisms involved in rAAV production in HEK293T cells and proposes promising avenues for further enhancing rAAV titer during production.

A haplotype-resolved genome assembly of Malus domestica ‘Red Fuji’

The ‘Red Fuji’ apple (Malus domestica), is one of the most important and popular economic crops worldwide in the fruit industry. Using PacBio HiFi long reads and Hi-C reads, we assembled a high-quality haplotype-resolved genome of ‘Red Fuji’, with sizes of 668.7 and 668.8 Mb, and N50 sizes of 34.1 and 31.4 Mb. About 97.2% of sequences were anchored in 34 chromosomes. We annotated both haploid genomes, identifying a total of 95,439 protein-coding genes in the two haplotype genomes, with 98% functional annotation. The haplotype-resolved genome of ‘Red Fuji’ apple stands as a precise benchmark for an array of analyses, such as comparative genomics, transcriptomics, and allelic expression studies. This comprehensive resource is paramount in unraveling variations in allelic expression, advancing quality improvements, and refining breeding efforts.

The prognostic impact of pathogenic stromal cell-associated genes in lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) stands as the most prevalent subtype among lung cancers. Interactions between stromal and cancer cells influence tumor growth, invasion, and metastasis. However, the regulatory mechanisms of stromal cells in the lung adenocarcinoma tumor microenvironment remain unclear. This study seeks to elucidate the regulatory connections among critical pathogenic genes and their associated expression variations within distinct stromal cell subtypes. MethodAnalysis and investigation were conducted on a total of 114,019 single-cell RNA data and 346 The Cancer Genome Atlas (TCGA) LUAD-related samples using bioinformatics and statistical algorithms. Differential gene expression analysis was performed for tumor samples and controls, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Differential genes between stromal cells and other cell clusters were identified and intersected with the differential genes from TCGA. We employed a combination of LASSO regression and multivariable Cox regression to identify the ultimate set of pathogenic gene. Survival models were trained to predict the relationship between patient survival and these pathogenic genes. Analysis of transcription factor (TF) cell specificity and pseudotime trajectories within stromal cell subpopulations revealed that vascular endothelial cells (ECs) and matrix cancer-associated fibroblasts (CAFs) are key in regulation of the prognosis-associated genes CAV2, COL1A1, TIMP1, ETS2, AKAP12, ID1 and COL1A2. ResultsSeven pathogenic genes associated with LUAD in stromal cells were identified and used to develop a survival model. High expression of these genes is linked to a greater risk of poor survival. Stromal cells were categorized into eight subtypes and one unannotated cluster. Mesothelial cells, vascular endothelial cells (ECs), and matrix cancer-associated fibroblasts (CAFs) showed cell-specific regulation of the pathogenic genes. ConclusionsThe seven disease-causing genes in vascular ECs and matrix CAFs can be used to detect the survival status of LUAD patients, providing new directions for future targeted drug design.

Quantitative estimates of the regulatory influence of long non-coding RNAs on global gene expression variation using TCGA breast cancer transcriptomic data.

Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene's expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25-50% of the putative regulator lncRNAs to be in 'cis' to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA's regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.

Genetic variability of aquaporin expression in maize: From eQTLs to a MITE insertion regulating PIP2;5 expression.

Plant aquaporins are involved in numerous physiological processes, such as cellular homeostasis, tissue hydraulics, transpiration, and nutrient supply, and are key players of the response to environmental cues. While varying expression patterns of aquaporin genes have been described across organs, developmental stages, and stress conditions, the underlying regulation mechanisms remain elusive. Hence, this work aimed to shed light on the expression variability of 4 plasma membrane intrinsic protein (PIP) genes in maize (Zea mays) leaves, and its genetic causes, through expression quantitative trait locus (eQTL) mapping across a 252-hybrid diversity panel. Significant genetic variability in PIP transcript abundance was observed to different extents depending on the isoforms. The genome-wide association study mapped numerous eQTLs, both local and distant, thus emphasizing the existing natural diversity of PIP gene expression across the studied panel and the potential to reveal regulatory actors and mechanisms. One eQTL associated with PIP2;5 expression variation was characterized. Genomic sequence comparison and in vivo reporter assay attributed, at least partly, the local eQTL to a transposon-containing polymorphism in the PIP2;5 promoter. This work paves the way to the molecular understanding of PIP gene regulation and its possible integration into larger networks regulating physiological and stress adaptation processes.

Hif3α Plays Key Roles in the Progression of Alzheimer's Disease Caused by Circadian Rhythm Disruption through Regulating the m6A/KDM3A/TGF-β1 Axis.

Disrupted circadian rhythms are associated with the onset of chronic diseases and impairments, including cancer, diabetes, and hypertension. However, whether circadian disruptions accelerate the progression of Alzheimer's disease and the respective pathway remains unclear. In this study, we constructed animal models using male C57BL/6N and APP/PS1 mice. Irregular illumination during sleeping hours was administered to the mice in our intervention groups to consistently disrupt their circadian rhythms. The impact of the intervention was evaluated through body weight tracking, cerebral index determination, histopathological staining, and biochemical marker analysis. Transcriptomic sequencing identified critical genes, with the data subsequently validated using RNA m6A detection and site analysis. The evaluations revealed that circadian disruptions impaired normal weight gain, liver and kidney functions, neuronal cells, and overall brain function. Transcriptomic sequencing data revealed a trend of elevating expression of Hif3α mRNA in the intervention groups. Further analysis of specific gene sites revealed that m6A methylation of the Hif3α gene at m6A site 3632 primarily drove the observed variations in HIF3A protein expression in our model. Furthermore, the expression of proteins in PC12 cells, N2a cells, and mice brains validated that an increase in HIF3A expression decreased KDM3A and TGF-β1 protein expression. Our study reveals a hitherto unknown pathway through which the disruption of circadian rhythms, by triggering m6A methylation at m6A site 3632 in the Hif3α gene, leads to the initiation and acceleration of AD. These findings provide valuable insights and guidelines for treating AD patients and enhancing caregiving by professionals.

Exogenous proline regulates pectin demethylation by rescuing pectin methylesterase functioning of cell wall from Cr(VI) toxicity in rice plants

BackgroundPlants are equipped with several sophisticated mechanisms to deal with heavy metals (HMs) toxicity. Cell walls, which are rich in pectin, are important in the sequestration and compartmentalization of HMs. Pectin demethylation is carried out by pectin methylesterase (PME), which is a crucial activity in cell walls for the adsorption of HMs. This study focused on the factors that contribute to chromium (Cr) adsorption in rice plants exposed to Cr(VI) treatments without proline (Pro) “Cr(VI)” and with Pro “Pro + Cr(VI)” application.ResultsThe results exhibited that when rice plants were treated with Cr(VI), their PME activity decreased, because Cr(VI) was bound to certain isoforms of PME and prevented the demethylation of pectin. The application of Pro increased PME activity by promoting the transcription of several PME-related genes. These genes were recognized on the basis of their similarity with PME genes in Arabidopsis. Gene expression variation factors (GEVFs) between the “Cr(VI)” and “Pro + Cr(VI)” treatments revealed that OsPME7 and OsPME9 have the highest positive GEVF values than other OsPME genes of rice. In addition, Pro application increased pectin content significantly in rice plants exposed to Cr(VI) stress. Proline application also leads to an increased concentration of Cr in rice roots compared with “Cr(VI)” treatments alone.ConclusionsThese findings suggest that Pro increased Cr(VI) adsorption in cell walls of rice plants by enhancing the PME activity and pectin content when exposed to “Cr(VI)” treatments, mainly regulated by OsPME7 and OsPME9.Graphical

Integrated analysis of -omic landscapes in breast cancer subtypes

The subtypes of breast cancer exhibit diverse histology, molecular features, therapeutic response, aggressiveness, and patient outcomes. Multi-omics high-throughput technologies, which are widely used in cancer research, generated waste amounts of multimodal omic datasets calling for new approaches of integrated analyses to uncover patterns of transcriptomic, genomic, and epigenetic changes in breast cancer subtypes and connect them to disease clinical characteristics. Here, we applied multi-layer self-organizing map (ml-SOM) algorithms to PAM50-classified TCGA breast cancer samples to disentangle the diversity of the effects of gene expression, methylation, copy number, and somatic single nucleotide variation in the disease subtypes. Furthermore, we studied the association of perturbed gene modules with survival, prognosis, and other clinical characteristics. Our findings highlight the power of multi-omic analyses to offer a better understanding of the molecular diversity of breast cancer subtypes compared to single-omic analyses. Moreover, they highlight the complex subtype-characteristic associations between gene expression and epigenetic/genomic factors and their implications for survival and clinical outcomes.

Systems genomics of salinity stress response in rice.

Populations can adapt to stressful environments through changes in gene expression. However, the role of gene regulation in mediating stress response and adaptation remains largely unexplored. Here, we use an integrative field dataset obtained from 780 plants of Oryza sativa ssp. indica (rice) grown in a field experiment under normal or moderate salt stress conditions to examine selection and evolution of gene expression variation under salinity stress conditions. We find that salinity stress induces increased selective pressure on gene expression. Further, we show that trans-eQTLs rather than cis-eQTLs are primarily associated with rice's gene expression under salinity stress, potentially via a few master-regulators. Importantly, and contrary to the expectations, we find that cis-trans reinforcement is more common than cis-trans compensation which may be reflective of rice diversification subsequent to domestication. We further identify genetic fixation as the likely mechanism underlying this compensation/reinforcement. Additionally, we show that cis- and trans-eQTLs are under different selection regimes, giving us insights into the evolutionary dynamics of gene expression variation. By examining genomic, transcriptomic, and phenotypic variation across a rice population, we gain insights into the molecular and genetic landscape underlying adaptive salinity stress responses, which is relevant for other crops and other stresses.

Transcriptional mechanisms of phenotypic plasticity in glioblastoma.

e14027 Background: Primary glioblastoma (GBM) tumor cells exhibit plasticity and can adopt different cellular states that exhibit dynamic transitions between states. This could be one of the mechanisms for treatment escape and leads to poor prognosis in GBM. In this regard, we sought to uncover transcriptional regulatory mechanisms responsible for this phenotypic plasticity in GBM. Methods: Standard of care (SOC) treatment (radiation and temozolomide) modulates transcriptional regulatory networks (TRNs) of the tumor cells and drives treatment resistance. Since TRNs could be key mechanistic drivers for state transitions, integrated single-cell RNA sequencing (scRNAseq) data of primary and relapse patient samples (11) were analyzed with scMINER. Our method uses a systems biology framework to identify cell states (St_1 to St_n) in terms of regulatory networks and their activities. Clustering of co-regulated gene modules (regulons), enabled the identification of transcriptional programs and regulatory mechanisms that specify tumor cell states. Results: Activity patterns of 38 transcriptional programs clustered tumor cells from the patients into 21 states. Preliminarily, we observed common regulatory network cell states (St_1, St_2, St_5, St_6) across patient tumors. Additionally, primary tumor cells of a patient (UW14) transitioned from initial cell state(s) observed across multiple patients (e.g., St_1) to a recurrent state (e.g., St_9) through a trajectory driven by transcription factors (TFs). Herein, scMINER regulatory network inference method also defines master TFs (TFs that regulate the majority of the other TFs in the network) that were used to characterize initial (St_1) or recurrent (St_9) cell states. Moreover, certain transcription factors (22) and their co-expressed target genes (regulons) also exhibit variation in expression across the pseudotime trajectory (from St_1 to St_9) including masterTFs such as SOX9 and MECOM. Conclusions: Therefore, we observed that shared cell states may exist across patients (primary and relapse) although in different proportions. Our analysis suggests a de-differentiation trajectory from neuronal cells to developing GBM stem cells and predicts transcription factors that could be playing an important role therein. Moreover, similar transcriptional regulatory mechanisms may promote transitions between primary and recurrent tumor cell states that exhibit phenotypic plasticity.

The PDZ domain of the E protein in SARS-CoV induces carcinogenesis and poor prognosis in LUAD

BackgroundIn both lung adenocarcinoma (LUAD) and severe acute respiratory syndrome (SARS), uncontrolled inflammation can be detected in lung tissue. The PDZ-binding motif (PBM) in the SARS-CoV-1 E protein has been demonstrated to be a virulence factor that induces a cytokine storm. MethodsTo identify gene expression fluctuations induced by PBM, microarray sequencing data of lung tissue infected with wild-type (SARS-CoV-1-E-wt) or recombinant virus (SARS-CoV-1-E-mutPBM) were analyzed, followed by functional enrichment analysis. To understand the role of the screened genes in LUAD, overall survival and immune correlation were calculated. ResultsA total of 12 genes might participate in the initial and developmental stages of LUAD through expression variation and mutation. Moreover, dysregulation of a total of 12 genes could lead to a poorer prognosis. In addition, the downregulation of MAMDC2 and ITGA8 by PBM could also affect patient prognosis. Although the conserved PBM (-D-L-L-V-) can be found at the end of the carboxyl terminus in multiple E proteins of coronaviruses, the specific function of each protein depends on the entire amino acid sequence. ConclusionsIn summary, PBM containing the SARS-CoV-1 E protein promoted the carcinogenesis of LUAD by dysregulating important gene expression profiles and subsequently influencing the immune response and overall prognosis.

Study on the mechanism of heterogeneous tumor-associated macrophages in three subtypes of breast cancer through the integration of single-cell RNA sequencing and in vitro experiments.

Tumor-associated macrophages (TAM) exert a significant influence on the progression and heterogeneity of various subtypes of breast cancer (BRCA). However, the roles of heterogeneous TAM within BRCA subtypes remain unclear. Therefore, this study sought to elucidate the role of TAM across the following three BRCA subtypes: triple-negative breast cancer, luminal, and HER2. This investigation aimed to delineate the variations in marker genes, drug sensitivity, and cellular communication among TAM across the three BRCA subtypes. We identified specific ligand-receptor (L-R) pairs and downstream mechanisms regulated by VEGFA-VEGFR1, SPP1-CD44, and SPP1-ITGB1 L-R pairs. Experimental verification of these pairs was conducted by co-culturing macrophages with three subtypes of BRCA cells. Our findings reveal the heterogeneity of macrophages within the three BRCA subtypes, evidenced by variations in marker gene expression, composition, and functional characteristics. Notably, heterogeneous TAM were found to promote invasive migration and epithelial-mesenchymal transition (EMT) in MDA-MB-231, MCF-7, and SKBR3 cells, activating NF-κB pathway via P38 MAPK, TGF-β1, and AKT, respectively, through distinct VEGFA-VEGFR1, SPP1-CD44, and SPP1-ITGB1 L-R pairs. Inhibition of these specific L-R pairs effectively reversed EMT, migration, and invasion of each cancer cells. Furthermore, we observed a correlation between ligand gene expression and TAM sensitivity to anticancer drugs, suggesting a potential strategy for optimizing personalized treatment guidance. Our study highlights the capacity of heterogeneous TAM to modulate biological functions via distinct pathways mediated by specific L-R pairs within diverse BRCA subtypes. This study might provide insights into precision immunotherapy of different subtypes of BRCA.

Unveiling the relationship between the UGT2B gene family and neoadjuvant treatment response in patients with HER2-positive breast cancer.

e12651 Background: Achieving a pathological complete response (pCR) following neoadjuvant treatment (NAT) in HER2-positive tumors significantly enhances patient survival, resulting in a remarkable 92% reduction in mortality risk. However, it is crucial to identify biomarkers capable of predicting the NAT response, moving towards more personalized medicine. This approach would enable the identification of patients likely to respond to specific therapies, thereby facilitating the implementation of targeted treatment strategies. Our study aims to identify potential molecular biomarkers predictive of NAT response through a comprehensive analysis of differential gene expression in tissue samples from patients with HER2-positive, hormone receptor (HR)-negative breast cancer. Methods: Total RNA was extracted from FFPE tissue samples from two independent cohorts of women diagnosed with localized or locally advanced HER2-positive, HR-negative breast cancer. These patients underwent NAT in several hospitals in Andalusia, Spain. Standard chemotherapy, including taxanes and/or anthracyclines, and targeted anti-HER2 treatment such as trastuzumab and pertuzumab were administered. The patients were stratified into responders (R), achieving pCR, and non-responders (nR). In a discovery cohort (n=20), RNA hybridization using Clariom D microarray was conducted to discern differentially expressed transcripts between R and nR. Subsequently, gene expression patterns, and related pathways involved in NAT response, were analyzed using Transcriptome Analysis Console (TAC). The selected transcripts then underwent validation through quantitative PCR (qPCR) in an independent cohort (n=40). The area under the receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of the genes as predictive biomarkers. Results: Microarray analysis of the discovery cohort, revealed 954 differentially expressed transcripts between R and nR, following criteria of fold change greater than 1.5 or less than -1.5 and a p-value below 0.05. Among these, 643 were upregulated, while 311 were downregulated in nR compared to R. Bioinformatic analysis and a comprehensive literature review guided the selection of genes UGT2B10, UGT2B11, UGT2B15, UGT2B17, and UGT2B28 for further investigation. Subsequent qPCR analysis in the validation cohort, demonstrated the overexpression of these genes in non-responders, with statistical significance achieved only for UGT2B15. Conclusions: The UGT2B family genes encode enzymes involved in glucuronidation and metabolic pathways associated with drug detoxification and elimination. Our findings suggest that variations in the UGT2B15 expression may impact the metabolism rate of specific drugs, underscoring the necessity for additional research in this area.

Intrapatient variation in PD-L1 expression and tumor mutational burden and the impact on outcomes to immune checkpoint inhibitor therapy in patients with non-small-cell lung cancer

Programmed death receptor ligand 1 (PD-L1) tumor proportion score (TPS) and tumor mutational burden (TMB) are key predictive biomarkers for immune checkpoint inhibitor (ICI) efficacy in non-small-cell lung cancer (NSCLC). Data on their variation across multiple samples are limited. Patients with NSCLC and multiple PD-L1 TPS and/or TMB assessments were included. Clinicopathologic and genomic data were analyzed according to PD-L1 and TMB variation. In total, 402 PD-L1 sample pairs and 413 TMB sample pairs were included. Concordance between pairs was moderate for PD-L1 (ρ= 0.53, P < 0.0001) and high for TMB (ρ= 0.80, P < 0.0001). Shorter time between biopsies correlated with higher concordance in PD-L1, but not in TMB. Major increases (ΔTPS ≥+50%) and decreases (ΔTPS ≤-50%) in PD-L1 were observed in 9.7% and 8.0% of cases, respectively. PD-L1, but not TMB, decreased with intervening ICI (P= 0.02). Acquired copy number loss of CD274, PDCD1LG2, and JAK2 were associated with major decrease in PD-L1 (q < 0.05). Among patients with multiple PD-L1 assessments before ICI, cases where all samples had a PD-L1 ≥1%, compared to cases with at least one sample with PD-L1 <1% and another with PD-L1 ≥1%, achieved improved objective response rate and progression-free survival (PFS). Among patients with at least one PD-L1 <1% and one ≥1% before ICI, cases where the most proximal sample was PD-L1 ≥1% had longer median PFS compared to cases where the most proximal PD-L1 was <1%. Among patients with multiple TMB assessments before ICI, patients with a TMB ≥10 mut/Mb based on the most recent assessment, as compared to those with a TMB <10 mut/Mb, achieved improved PFS and overall survival to ICI; instead, no differences were observed when patients were categorized using the oldest TMB assessment. Despite intrapatient concordance in PD-L1 and TMB, variation in these biomarkers can influence ICI outcomes, warranting consideration for reassessment before ICI initiation when feasible.

Selenoprotein GPX3 is a novel prognostic indicator for stomach adenocarcinoma and brain low-grade gliomas: Evidence from an integrative pan-cancer analysis

BackgroundThe antioxidant enzyme GPX3 is a selenoprotein that transports selenium in blood and maintains its levels in peripheral tissues. Aberrant GPX3 expression is strongly linked to the development of some tumors. However, there is a scarcity of studies examining the pan-cancer expression patterns and prognostic relevance of GPX3. MethodsGPX3 expression levels in normal tissues and multiple tumors were analyzed using TCGA, CCLE, GTEx, UALCAN and HPA databases. Forest plots and KM survival curves were utilized to evaluate the correlation between GPX3 expression and the outcome of tumor patients. The prognostic value of GPX3 in LGG was assessed utilizing the CGGA datasets, and that in STAD was tested by TCGA and GEO databases. A nomogram was then constructed to predict OS in STAD using R software. Additionally, the impact of GPX3 on post-chemoradiotherapy OS in patients with LGG and STAD was evaluated using the KM method. The multiplicative interaction of GPX3 expression, chemotherapy and radiotherapy on STAD and LGG was analyzed using logistic regression models. The correlation of GPX3 with the immune infiltration, immune neoantigens and MMR genes were investigated in TCGA cohort. ResultsGPX3 exhibited downregulation across 21 tumor types, including STAD, with its decreased expression significantly associated with improved OS, DFS, PFS and DSS. Conversely, in LGG, low levels of GPX3 expression were indicative of a poorer prognosis. Univariate and multivariate Cox models further identified GPX3 as an independent predictor of STAD, and a nomogram based on GPX3 expression and other independent factors showed high level of predictive accuracy. Moreover, low GPX3 expression and chemotherapy prolonged the survival of STAD. In LGG patients, chemoradiotherapy, GPX3 and chemotherapy, and GPX3 and chemoradiotherapy may improve prognosis. Our observations reveal a notable connection between GPX3 and immune infiltration, immune neoantigens, and MMR genes. ConclusionsThe variations in GPX3 expression are linked to the controlling tumor development and could act as a promising biomarker that impacts the prognosis of specific cancers like STAD and LGG.

Transcriptomic analysis of cAMP/PKA/CREB signaling in invasive lobular breast cancer.

1109 Background: Invasive lobular breast cancer (ILC) is the most common special type of breast cancer and has unique clinicopathological and molecular hallmarks that differentiate it from the more common invasive carcinoma – no special type (NST). Despite these differences, ILC and NST are treated as a single entity and there is a lack of ILC-targeted therapies. To fill this gap, we sought to identify novel molecular alterations in ILC that could be exploited for targeted therapies. Methods: Differential gene expression and Geneset Enrichment and Variation analyses were performed on RNA-seq data from three large public breast cancer databases – the Sweden Cancerome Analysis Network-Breast (SCAN-B; luminal A ILC N=263, luminal A NST N=1162), The Cancer Genome Atlas (TCGA; luminal A ILC N=157, luminal A NST N=307) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; luminal A ILC N=65, luminal A NST N=533). Pathways enriched in overlapping differentially expressed genes from these datasets were clustered using Jaccard similarity to identify pathways enriched in ILC. The cAMP/PKA/CREB signaling was studied in ILC, ILC-like and NST cell lines and patient-derived organoids (PDOs) using forskolin, an activator of the pathway. Results: Clinicopathological features of patients with ILC and NST in SCAN-B were similar to prior population-based studies. There was a consistent pattern of up-regulation of cAMP/PKA/CREB related signaling in ILC compared to NST in SCAN-B, TCGA and METABRIC. Treatment with forskolin resulted in a greater increase in phospho-CREB in ILC cell lines and organoids than NST. CRISPR deletion of CDH1 in NST cell lines did not alter response of cells to forskolin as measured by phospho-CREB. Forskolin treatment caused growth inhibition in ILC and NST, with ILC cell lines being more sensitive to forskolin-mediated growth inhibition. Conclusions: In three separate datasets, cAMP/PKA/CREB signaling was identified to be higher in ILC than NST. This in silico finding was validated in cell line and organoid models. Loss of CDH1 was not sufficient to mediate this phenotype. Future studies should investigate the mechanisms for differential cAMP/PKA/CREB signaling and the potential for therapeutic targeting in patients with ILC.

Nascent transcription reveals regulatory changes in extremophile fishes inhabiting hydrogen sulfide-rich environments.

Regulating transcription allows organisms to respond to their environment, both within a single generation (plasticity) and across generations (adaptation). We examined transcriptional differences in gill tissues of fishes in the Poecilia mexicana species complex (family Poeciliidae), which have colonized toxic springs rich in hydrogen sulfide (H2S) in southern Mexico. There are gene expression differences between sulfidic and non-sulfidic populations, yet regulatory mechanisms mediating this gene expression variation remain poorly studied. We combined capped-small RNA sequencing (csRNA-seq), which captures actively transcribed (i.e. nascent) transcripts, and messenger RNA sequencing (mRNA-seq) to examine how variation in transcription, enhancer activity, and associated transcription factor binding sites may facilitate adaptation to extreme environments. csRNA-seq revealed thousands of differentially initiated transcripts between sulfidic and non-sulfidic populations, many of which are involved in H2S detoxification and response. Analyses of transcription factor binding sites in promoter and putative enhancer csRNA-seq peaks identified a suite of transcription factors likely involved in regulating H2S-specific shifts in gene expression, including several key transcription factors known to respond to hypoxia. Our findings uncover a complex interplay of regulatory processes that reflect the divergence of extremophile populations of P. mexicana from their non-sulfidic ancestors and suggest shared responses among evolutionarily independent lineages.