Therapeutic Biomarkers Research Articles

A best practices framework for spatial biology studies in drug discovery and development: enabling successful cohort studies using digital spatial profiling

ABSTRACT The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard ‘omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell–cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

Prediction of synergistic gemcitabine-based combination treatment through a novel tumor stemness biomarker NANOG in pancreatic cancer.

Gemcitabine remains a first-class chemotherapeutic drug for pancreatic cancer. However, due to the rapid development of gemcitabine resistance in pancreatic cancer, gemcitabine alone or in combination with other anti-cancer drugs only showed limited effect in the clinic. It is extremely challenging to effectively and efficiently determine the optimal drug regimens. Thus, identification of appropriate prediction biomarkers is critical for the rational design of gemcitabine-based therapeutic options. Herein, a pancreatic cancer stem cell (PCSC) model exhibiting chemoresistance to gemcitabine was used to test the activity of clinical cancer drugs in the presence or absence of gemcitabine. As determined by combinatorial treatment, several types of drugs resensitized gemcitabine-resistant PCSCs to gemcitabine, with sorafenib (EGFR inhibitor)/gemcitabine and sunitinib (TBK1 inhibitors)/gemcitabine drug combinations being the most preferred treatments for PCSCs. Following the validation of the PCSC model by an antibody array test of 15-gene expression of stemness biomarkers, NANOG showed markedly different expression in PCSCs compared to the parental cells. From comprehensive analysis of stem cell index versus combination index, a stemness-related correlation model was successfully constructed to demonstrate the correlation between NANOG expression and synergism. Cancer cell stemness was ascertained to be highly relevant to NANOG overexpression that can be abrogated by synergized gemcitabine-drug combinations. Therefore, NANOG works as a therapeutic biomarker for predicating efficient combinatorial treatment of gemcitabine in pancreatic cancer.

Clinical sequencing reveals diagnostic, therapeutic, and prognostic biomarkers for adult-type diffuse gliomas

Diffuse gliomas in adults are highly infiltrative and largely incurable. Whole exome sequencing (WES) has been demonstrated very useful in genetic analysis. Here WES was performed to characterize genomic landscape of adult-type diffuse gliomas to discover the diagnostic, therapeutic and prognostic biomarkers. Somatic and germline variants of 66 patients with adult-type diffuse gliomas were detected by WES based on the next-generation sequencing. TCGA and CGGA datasets were included to analyze the integrated diagnosis and prognosis. Among 66 patients, the diagnosis of 9 cases was changed, in which 8 cases of astrocytoma were corrected into IDH-wildtype glioblastoma (GBM), and 1 oligodendroglioma without 1p/19q co-deletion into astrocytoma. The distribution of mutations including ATRX/TP53 differed in three cohorts. The genetic mutations in GBM mainly concentrated on the cell cycle, PI3K and RTK pathways. The mutational landscape of astrocytoma was more similar to that of GBM, with the highest frequency in germline variants. Patients with IDH-mutant astrocytoma harboring SNVs of PIK3CA and PIK3R1 showed a significantly worse overall survival (OS) than wild-type patients. AEBP1 amplification was associated with shorter OS in GBM. Our study suggests that clinical sequencing can recapitulate previous findings, which may provide a powerful approach to discover diagnostic, therapeutic and prognostic markers for precision medicine in adult-type diffuse gliomas.

Identification and validation of a novel robust glioblastoma prognosis model based on bioinformatics

BackgroundGlioblastoma (GBM) is a very common primary malignant tumor of the central nervous system (CNS). Aging, macrophage, autophagy, and methylation related genes are hypothesized to be crucial to its pathogenesis. In this study, we aimed to explore the role of these genes in the prognosis of GBM. MethodsThe RNA sequence (RNA-seq) and clinical information were downloaded from The Cancer Genome Atlas database (TCGA) and the Chinese Glioma Genome Atlas database (CGGA). We performed univariate and least absolute shrinkage and selection operator (LASSO) multivariate Cox regression analysis to identify risk signatures related to overall survival (OS). We further developed a nomogram to predict individual outcomes. In addition, the immune microenvironment was analyzed by CIBERSORT. Results256 differentially expressed genes (DEGs) were obtained based on aging, macrophage, autophagy, and methylation related genes between GBM samples and normal tissues in TCGA-GBM cohort. We identified five optimal risk signatures with prognostic values in TCGA-GBM cohort and established a prognostic risk score model. The validity of the model was verified in the CGGA cohort and Huanhu cohort. Finally, we constructed a nomogram for clinical application by combining age, O(6)-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, and risk score. Activated NK cells and resting mast cells were highly expressed and memory B cells, plasma cells, resting NK cells, M1 macrophages, and neutrophils exhibited low expression in the high-risk score group. GBM patients with a low-risk score had a higher Tumor Immune Dysfunction and Exclusion (TIDE) score. The risk score of hot tumors was higher than that of the cold tumors. Additionally, 29 genes involved in glucose and lipid metabolism were highly expressed with a high-risk score. 31 metabolism-related pathways were significantly different between high-risk and low-risk groups. ConclusionsWe constructed and validated a novel prognostic model for GBM. Aging, macrophage, autophagy, and methylation related genes may serve as prognostic and therapeutic biomarkers. The model developed may assist in guiding treatment for GBM patients. Our research had great significance in accurately predicting the prognosis of GBM and may offer reference for immunotherapy decision for GBM patients.

Construction of Prognostic ceRNA Network Landscape in Breast Cancer to Explore Impacting Genes on Drug Response by Integrative Bioinformatics Analysis

Background: Breast cancer accounts for 30% of all new female cancers yearly. Bioinformatics serves us to find new biomarkers and facilitate future experimental research. Exploring a distinct network of competing endogenous RNA (ceRNA) that includes potential prognostic, diagnostic, and therapeutic biomarkers is captivating. Methods: Differentially expressed lncRNAs, mRNAs, and miRNAs were collected using Gene Expression Omnibus datasets. DEGs were validated based on TCGA. Functional analysis and pathway activity were also done. Drug sensitivity analyses were done, and IC50 vs. gene expression plots were depicted. Results: A total of 696 mRNAs, 48 lncRNAs, and, 43 miRNAs were identified to have significant differential expression in cancerous breast tissue than normal breast tissue samples. Functional analysis showed significant pathway enrichments in cancer. We found that 13 individual genes, lncRNAs, and miRNAs, CDC6, ERBB2, EZR, HELLS, MAPK13, MCM2, MMP1, SLC7A5, TINCR, TRIP13, hsa-miR-376a, hsa-miR-21, hsa-miR-454 were significantly predictive of poor overall survival and AKAP12, CXCL12, FGF2, IRS2, LINC00342, LINC01140, MEG3, MIR250HG, NAV3, NDRG2, NEAT1, TGFBR3 and, hsa-miR-29c were associated with favorable overall survival. We reached a set of five genes (EGR1, NFIB, TGFBR3, SMARCA4, and MCM2) that exhibit altered expression patterns in breast cancer, resulting in increased susceptibility of cancer cells to certain drug treatments. Conclusion: We successfully made a unique ce-network, providing new clues to understand the regulatory functions of non-coding RNAs (miRNAs and lncRNAs) in the pathogenesis and prognosis of breast cancer and will facilitate further experimental studies to develop new biomarkers in the diagnosis, prognosis and, therapy of breast cancer.

Recent Progress in the Application of Exosome Analysis in Ovarian Cancer Management.

Exosomes are very small (nano-sized) vesicles participating in tumor development by involvement in intercellular communication mediated by transferring biocomponents. Exosomes appear to play vital roles in various cancer development, such as ovarian cancer, a common malignancy in women. Several hallmarks of ovarian cancer are reported to be affected by the exosomemediated cellular cross-talk, including modulating peritoneal dissemination and chemoresistance. Since the expression of some biomolecules, such as miRNAs and mRNA, is changed in ovarian cancer, these exo-biomolecules can be applied as prognostic, diagnostic, and therapeutic biomarkers. Also, the selective loading of specific chemotherapeutic agents into exosomes highlights these biocarries as potential delivery devices. Exosomes could be artificially provided and engineered to better target the site of interest in ovarian cancer. In the present review, we summarize the notable achievement of exosome application in ovarian cancer management to gain applicable transitional insight against this cancer.

Integrative analysis of the immunological significances of guanylate binding protein family genes in microsatellite stability colorectal cancer

BackgroundMicrosatellite stability (MSS) colorectal cancer (CRC) has poor sensitivity to immunotherapy and its underlying mechanisms are still unclear. Guanylate binding proteins (GBPs) are a family of GTPase involving innate immune responses by providing defense against invading microbes and pathogens. However, the immunological significances of GBPs in MSS CRC remain unknown. MethodsWe utilized bioinformatic tools to comprehensively analysis the expression pattern, clinical relevance, prognostic value, biological function, and immunoregulation effect of distinct GBP members in MSS CRC. ResultsThe expression of all seven GBPs in MSS samples are remarkably decreased compared to microsatellite instability-high (MSI-H) samples. Among them, GBP1/2/4/5 are obviously correlated with distant metastasis status. High expression of GBP1/4/5/6 was remarkably related to favorable overall survival (OS) and progression-free survival (PFS) in CRC patients with MSS tumor. Subsequent enrichment analysis revealed that Interferon-gamma (IFN-γ) and NOD-like receptor signaling are the most relevant functions. Besides, the expression patterns of GBPs are remarkably associated with several tumor infiltrated immune cells (e.g. regulatory T cells, CD4+ T cells, and macrophages) and diverse immunoregulatory molecules (e.g. immune checkpoint biomarkers (ICBs) and major histocompatibility complex (MHC) molecules). Moreover, high GBP1/2/4/5 expression predicted better immunotherapy responsiveness in immunotherapy cohorts. ConclusionThese findings might provide novel insights for the identification of therapeutic targets and potential prognostic biomarkers of GBP family in CRC with MSS samples.

O69 THE REGULATORY ROLE OF CIRCULAR RNAS IN RESPONSE TO RAAS INHIBITORS

Circular RNAs (circRNAs) are a class of non-coding RNA that may play an important role in disease progression and diagnosis. This study aimed to investigate the role of renal circRNAs in hypertension and to identify circRNAs pathways explaining chronic reset in blood pressure. Two groups of young spontaneously hypertensive rats (SHR) were used: rats treated with or without losartan (RAAS inhibitor, n = 18 in each group). Through established circRNA identification and quantification tools, we identified five significant circular RNA candidates (P < 0.05), each aligning with differentially expressed and biologically significant miRNA. Furthermore, these candidate circRNAs aligned with expression pathways found in both treatment and control groups. In conclusion, this study identified several circRNAs which may play an important role in blood pressure regulation. It may advance our understanding of circRNAs in mediating losartan-induced blood pressure reduction. Future studies on validation, expression networking and methylome analysis may shed light on these circRNAs’ significance and identify potential therapeutic biomarkers.

CircZMYM2 plays a pivotal role in osteosarcoma by regulating the translation of NACA and ARPC1B

Osteosarcoma (OS) is a primary malignant bone tumor in children and young adults because of its intertumoral heterogeneity and absence of molecular targets. This study aimed to elucidate the role of circular RNA in the pathogenesis of OS. Using bioinformatics analysis and OS clinical samples, we found that hsa_circ_0029634 formed during the splicing process of Zinc finger MYM-type containing 2 (circZMYM2) was highly expressed in OS tissues. Nuclear cap-binding protein subunit 2 regulated circZMYM2 bio-generation by binding to flanking sequences of ZMYM2 transcripts. In addition, knockdown circZMYM2 inhibited cell growth and metastasis in OS cell lines in vitro and inhibited tumor growth in vivo. Mechanistically, circZMYM2 competitively bound to FXR1 to regulate the translation of NACA and ARPC1B. CircZMYM2 may be a crucial regulator of OS tumorigenesis and a potential diagnostic and therapeutic biomarker for OS patients.

Bioinformatics analysis-based mining of potential markers for inflammatory bowel disease and their immune relevance.

The incidence of inflammatory bowel disease (IBD) is increasing every year and is characterized by a prolonged course, frequent relapses, difficulty in curing, and a lack of more efficacious therapeutic biomarkers. The aim of this study was to find key core genes as therapeutic biomarkers for IBD. GSE75214 in Gene Expression Omnibus (GEO) was used as the experimental set. The genes in the top 25% of standard deviation of all samples in the experimental set were subjected to systematic weighted gene co-expression network analysis (WGCNA) to find candidate genes. Then, least absolute shrinkage and selection operator (LASSO) logistic regression was used to further screen the central genes. Finally, the validity of hub genes was verified on GEO dataset GSE179285 using "BiocManager" R package. Twelve well-preserved modules were identified in the experimental set using the WGCNA method. Among them, five modules significantly associated with IBD were screened as clinically significant modules, and four candidate genes were screened from these five modules. Then TIMP1, GUCA2B, and HIF1A were screened as hub genes. These hub genes successfully distinguished tumor samples from healthy tissues by artificial neural network algorithm in an independent test set with an area under the working characteristic curve of 0.946 for the subjects. IBD differentially expressed gene (DEGs) are involved in immunoregulatory processes. TIMP1, GUCA2B, and HIF1A, as core genes of IBD, have the potential to be therapeutic targets for patients with IBD, and our findings may provide a new outlook on the future treatment of IBD.

Medullary thyroid cancer: single-cell transcriptome and tumor evolution

BackgroundMedullary thyroid cancer (MTC) is a rare neuroendocrine tumor that originates from the parafollicular C cells of thyroid gland. Understanding the fundamental pathophysiology of MTC is essential for clinical management. Single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for identifying distinct cell types, offering a new biological foundation for comprehending the MTC ecosystem and developing precise treatment.MethodsFormalin fixed and paraffin-embedded (FFPE) samples of primary and adjacent non-cancerous tissues of three MTC cases were collected, and single-cell transcriptome data of MTC were obtained by using scRNA-seq technology. Annotated cell subpopulations were categorized and functionally enriched by principal component analysis, differential gene expression, and cell clustering analysis, to explore the biological process of tumor evolution that may be involved in each cell subpopulation. The copy number variation (CNV) profile was used to distinguish the malignancy of parafollicular thyroid cells, and the evolutionary trajectories of normal cells and tumor cells were revealed by the proposed time series analysis. The highly expressed genes in each cell subpopulation were analyzed by the FindAllMarker function of Seurat software, and verified by immunohistochemistry and fluorescence in situ hybridization. The prognostic value of specific cell subtypes was validated using large-scale public datasets.ResultsA total of 32,544 cells were obtained from the MTC tissue samples and 11,751 cells from the adjacent non-cancerous samples, which were classified into 7 heterogenous subpopulations by using R package of Seurat module. Copy number variations (CNVs) were significantly higher in tumor tissues than in adjacent non-tumor samples, predominantly enriched in subtypes C2 and C4. In addition, the pseudo-time for trajectory analysis suggested that the evolution of MTC tumor cells might begin with the C2 subtype, then transition to the early cancer subgroup C3, and further differentiate into four major malignant cell subpopulations C0, C1, C5 and C6. Survival analysis of a thyroid cancer cohort using the TCGA dataset revealed that high expression of genes linked to the C0 subcluster was correlated with poorer overall survival compared to low expression. Immunohistochemical staining showed that MAP3K4 was highly expressed in MTC tissues compared to adjacent non-cancerous tissues. Fluorescence in situ hybridization also confirmed the amplification of these two genes in MTC samples.ConclusionsBy conducting scRNA-seq on FFPE samples, we mapped the single-cell transcriptome of MTC, uncovering the tumor heterogeneity and unique biological features of each cellular subpopulation. The biological roles of identified tumor cell subpopulations such as C0 and C3 subtypes of parafollicular cells suggested the potential to discover new therapeutic targets and biomarkers for MTC, providing valuable insights for future translational and clinical research.

Comparative Analysis of Circular RNAs Expression and Function between Aortic and Intracranial Aneurysms.

An aneurysm is an abnormal enlargement or bulging of the wall of a blood vessel. Most often, aneurysms occur in large blood vessels - the aorta (Thoracic Aortic Aneurysm (TAA) and Abdominal Aortic Aneurysm (AAA) and brain vessels (Intracranial Aneurysm (IA)). Despite the presence of significant differences in the pathogenesis of the development and progression of IA and TAA/AAA, there are also similarities. For instance, both have been shown to be strongly influenced by shear stress, inflammatory processes, and enzymatic destruction of the elastic lamellae and extracellular matrix (ECM) proteins of the vascular wall. Moreover, although IA and TAA are predominantly considered arteriopathies with different pathological mechanisms, they share risk factors with AAA, such as hypertension and smoking. However, there is a need for a more in- -depth study of the key elements that may influence the formation and progression of a particular aneurysm to find ways of therapeutic intervention or search for a diagnostic tool. Today, it is known that the disruption of gene expression is one of the main mechanisms that contribute to the development of aneurysms. At the same time, growing evidence suggests that aberrant epigenetic regulation of gene function is strongly related to the genesis of aneurysms. Although much has been studied of the known protein-coding genes, circular RNAs (circRNAs), a relatively new and rapidly evolving large family of transcripts, have recently received much scientific attention. CircRNAs regulate gene expression through the sponging of microRNAs (miRNAs) and can also be used as therapeutic targets and biomarkers. Increasing evidence has implicated circRNAs in the pathogenesis of multiple cardiovascular diseases, including the development of aneurysms. However, the mechanism of dysregulation of certain circRNAs in a particular aneurysm remains to be studied. The discovery of circRNAs has recently advanced our understanding of the latest mode of miRNAs/target genes regulation in the development and progression of IA and TAA/AAA. The aim of this study is to compare the expression profiles of circRNAs to search for similar or different effects of certain circRNAs on the formation and progression of IA and TAA/AAA.

Analysis of HER2 expression changes from breast primary to brain metastases and the impact of HER2-low expression on overall survival.

There are limited data regarding HER2-low expression dynamics between matched primary tumors and brain metastases (BrMs) in breast cancer. HER2-low expression has emerged as a new therapeutic biomarker for highly active antibody-drug conjugates with emerging intracranial activity. Patients with metastatic breast cancer (MBC) and BrMs seen at an NCI-designated center between 2003-2023 were identified. HER2 expression was defined as HER2-positive (3+,2+/ISH amplified), HER2-low (1+,2+/ISH negative), or HER2-0 by ASCO-CAP guidelines. Estrogen receptor (ER) status was defined as ER≥1%. Multivariate survival analyses by Cox proportional hazard models were determined from time of BrM resection to death or last follow-up between the 3 subtypes, controlling for ER and age. Among 197 matched primary and resected BrMs, 81% exhibited HER2 expression in the brain:61% HER2-positive, 20% HER2-low, and 19% HER2-0. Concordance was high in HER2-positive primary tumors with 100% retaining HER2 expression (97% retained HER2+ expression and 2.7% switched to HER2-low). HER2-0 primaries frequently showed HER2 gain in BrMs to HER2-low (35%) or HER2-positive (5.4%) status. Among 48 HER2-low primary tumors, 52% were discordant for HER2 status in the brain with 21% testing HER2-positive and 31% testing HER2-0. In adjusted analyses, patients with HER2-positive BrMs had significantly lower death risk than patients with HER2-low BrMs (HR=0.41, P=0.0006); no difference was observed between HER2-0 and HER2-low. In this retrospective analysis, HER2 expression is common in breast cancer BrMs, emphasizing the need for improved, non-invasive diagnostics. Patients with HER2-low and HER2-0 BrMs face inferior survival, presenting an unmet clinical need.

Exploring the Role of the Gut Microbiota in Modulating Colorectal Cancer Immunity.

The gut microbiota plays an essential role in maintaining immune homeostasis and influencing the immune landscape within the tumor microenvironment. This review aims to elucidate the interactions between gut microbiota and tumor immune dynamics, with a focus on colorectal cancer (CRC). The review spans foundational concepts of immuno-microbial interplay, factors influencing microbiome composition, and evidence linking gut microbiota to cancer immunotherapy outcomes. Gut microbiota modulates anti-cancer immunity through several mechanisms, including enhancement of immune surveillance and modulation of inflammatory responses. Specific microbial species and their metabolic byproducts can significantly influence the efficacy of cancer immunotherapies. Furthermore, microbial diversity within the gut microbiota correlates with clinical outcomes in CRC, suggesting potential as a valuable biomarker for predicting response to immunotherapy. Conclusions: Understanding the relationship between gut microbiota and tumor immune responses offers potential for novel therapeutic strategies and biomarker development. The gut microbiota not only influences the natural history and treatment response of CRC but also serves as a critical modulator of immune homeostasis and anti-cancer activity. Further exploration into the microbiome's role could enhance the effectiveness of existing treatments and guide the development of new therapeutic modalities.

CREBBP histone acetyltransferase domain mutations predict response to mTOR inhibition in relapsed/refractory follicular lymphoma.

Despite the clinical and molecular heterogeneity of follicular lymphoma (FL), there remains a lack of biomarker-directed therapeutic approaches in routine clinical practice, with the notable exception of the EZH2 inhibitor tazemetostat in EZH2-mutant FL. Here we examined whether gene mutation status predicts response to clinical mTOR inhibitors (mTORi) in FL, by performing targeted mutational profiling of biopsies from 21 relapsed/refractory FL patients treated with mTORi everolimus or temsirolimus within clinical trials. We observed an enrichment of mutations within the catalytic histone acetyltransferase (HAT) domain of CREBBP in mTORi-responders, and describe distinct transcriptional characteristics and co-occurring mutations of FL harbouring these mutations; reinforcing the growing appreciation of CREBBPHAT mutation as a key biological determinant and its promise as a therapeutic biomarker in FL.

Sarcopenia: recent advances for detection, progression, and metabolic alterations along with therapeutic targets.

Sarcopenia, a disorder marked by muscle loss and dysfunction, is a global health concern, particularly in aging populations. Sarcopenia is intricately related to various health conditions, including obesity, dysphagia, and frailty, which underscores the complexity. Despite recent advances in metabolomics and other omics data for early detection and treatment, the precise characterization and diagnosis of sarcopenia remains challenging. In the present review we provide an overview of the complex metabolic mechanisms that underlie sarcopenia, with particular emphasis on protein, lipid, carbohydrate, and bone metabolism. The review highlights the importance of leucine and other amino acids in promoting muscle protein synthesis and clarifies the critical role played by amino acid metabolism in preserving muscular health. In addition, the review provides insights regarding lipid metabolism on sarcopenia, with an emphasis on the effects of inflammation and insulin resistance. The development of sarcopenia is largely influenced by insulin resistance, especially with regard to glucose metabolism. Overall, the review emphasizes the complex relationship between bone and muscle health by highlighting the interaction between sarcopenia and bone metabolism. Furthermore, the review outlines various therapeutic approaches and potential biomarkers for diagnosing sarcopenia. These include pharmacological strategies such as hormone replacement therapy and anabolic steroids as well as lifestyle modifications such as exercise, nutrition, and dietary changes.

Prognostic and immunological implications of heterogeneous cell death patterns in prostate cancer

BackgroundProstate cancer is one of the most common cancers in men with a significant proportion of patients developing biochemical recurrence (BCR) after treatment. Programmed cell death (PCD) mechanisms are known to play critical roles in tumor progression and can potentially serve as prognostic and therapeutic biomarkers in PCa. This study aimed to develop a prognostic signature for BCR in PCa using PCD-related genes.Materials and methodsWe conducted an analysis of 19 different modes of PCD to develop a comprehensive model. Bulk transcriptomic, single-cell transcriptomic, genomic, and clinical data were collected from multiple cohorts, including TCGA-PRAD, GSE58812, METABRIC, GSE21653, and GSE193337. We analyzed the expression and mutations of the 19 PCD modes and constructed, evaluated, and validated the model.ResultsTen PCD modes were found to be associated with BCR in PCa, with specific PCD patterns exhibited by various cell components within the tumor microenvironment. Through Lasso Cox regression analysis, we established a Programmed Cell Death Index (PCDI) utilizing an 11-gene signature. High PCDI values were validated in five independent datasets and were found to be associated with an increased risk of BCR in PCa patients. Notably, older age and advanced T and N staging were associated with higher PCDI values. By combining PCDI with T staging, we constructed a nomogram with enhanced predictive performance. Additionally, high PCDI values were significantly correlated with decreased drug sensitivity, including drugs such as Docetaxel and Methotrexate. Patients with lower PCDI values demonstrated higher immunophenoscores (IPS), suggesting a potentially higher response rate to immune therapy. Furthermore, PCDI was associated with immune checkpoint genes and key components of the tumor microenvironment, including macrophages, T cells, and NK cells. Finally, clinical specimens validated the differential expression of PCDI-related PCDRGs at both the gene and protein levels.ConclusionIn conclusion, we developed a novel PCD-based prognostic feature that successfully predicted BCR in PCa patients and provided insights into drug sensitivity and potential response to immune therapy. These findings have significant clinical implications for the treatment of PCa.

Up-regulated DSG2 promotes tumor growth and reduces immune infiltration in cervical cancer

BackgroundDesmoglein-2 (DSG2) has been reported to play pivotal roles in various diseases. However, its roles in cervical cancer (CC) remain insufficiently elucidated. Here, we aimed to comprehensively explore the functional mechanisms of DSG2 in CC using bioinformatics and experimental methods. MethodsSeveral online databases, including Gene Expression Profiling Interactive Analysis (GEPIA), ONCOMINE, LinkedOmics, MetaScape, Human protein atlas (HPA), OMICS and single-cell RNA sequencing (scRNA-seq) data were used to explore the expression, prognosis, gene mutations, and potential signaling pathway of DSG2 in CC. Quantitative real-time PCR (qRT-PCR) and western blotting were used to measure DSG2 expression in collected samples. Experimental assays were conducted to verify the effects of dysregulated DSG2 on cervical cell lines in vitro. ResultsBioinformatic analyses revealed that DSG2 was significantly up-regulated in CC compared to normal cervical tissues at both mRNA and protein levels. Elevated DSG2 levels were also associated with poor prognosis and clinical parameters (e.g., cancer stages, tumor grade, nodal metastasis status, etc.). DSG2 expression was predominantly observed in epithelial cells, increasing with disease progression on a single-cell resolution. Additionally, up-regulation of DSG2 significantly enhanced tumor purity by reducing the infiltration of immune cells (e.g., B cells, T cells, NK cells, etc.). Over-expression of DSG2 was further validated in collected CC samples at both mRNA and protein levels. Knockdown of DSG2 markedly reduced the proliferation and invasion of CC cell lines in vitro. ConclusionsIn summary, elevated levels of DSG2 were significantly associated with poor prognosis and diminished immune infiltration in CC. Thus, DSG2 may serve as a potential therapeutic and diagnostic biomarker for CC.

Extracellular Vesicle (EV) Survivin for Cancer Diagnostics and Therapeutics: A Review.

Survivin, an important inhibitor of apoptosis protein, contributes to cancer cells' resistance to apoptosis, proliferation, and survival. It is a promising biomarker and therapeutic target due to being highly expressed in cancer cells relative to normal cells and universally expressed in almost all cancer types. Cancer cells release survivin to the tumour microenvironment (TME) not only as a free protein but also encapsulated in extracellular vesicles (EVs), especially small EVs (sEVs). The release of encapsulated survivin from cancer cells can be taken up by neighbouring cells, eliciting pathological responses such as tumorigenesis and metastasis. Consequently, EV survivin holds potential as a diagnostic, prognostic, and therapeutic biomarker for several types of cancer, including breast cancer, prostate cancer, pancreatic cancer, and glioblastoma. EV survivin expression is significantly elevated in cancer patients and correlates with unfavourable clinicopathologic parameters. Although no clinical studies have explored EV survivin as a therapeutic target, future research should explore survivin-based therapies in combination with EV-targeting therapies to effectively disrupt its roles in tumorigenesis and metastasis.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review.

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.