An inflammation-related signature could predict the prognosis of patients with kidney renal clear cell carcinoma

Decoding the crossroads of aging and cancer through single-cell analysis: Implications for precision oncology

Single-cell analysis is a transformative approach to understanding cellular heterogeneity in aging and cancer, interconnected processes driven by mechanisms like senescence and immune modulation. This review explores how aging influences cancer initiation, progression, and treatment resistance within the tumor microenvironment (TME). By examining recent studies using single-cell technologies, we reveal the nuanced roles of aging in tumorigenesis, immune interactions, and therapeutic outcomes. Aging is closely tied to cancer progression, with senescent cells demonstrating heightened proliferative, invasive, and metastatic capabilities. Emerging senolytic therapies targeting aging-related pathways hold promise for enhancing treatment efficacy. Advanced tools such as spatial transcriptomics, molecular probes, and artificial intelligence further refine our understanding of aging-related heterogeneity in the TME. By integrating single-cell analysis with these technologies, future research can clarify the intricate interactions between aging and cancer, advancing precision oncology and improving outcomes for aging cancer patients.

Targeting ferroptosis for the treatment of female reproductive system disorders

Ferroptosis, a regulated form of cell death driven by iron-dependent lipid peroxidation, has emerged as a critical factor in female reproductive health and has been implicated in disorders such as polycystic ovary syndrome, premature ovarian insufficiency, endometriosis, and ovarian cancer. This review explores the intricate molecular mechanisms underlying ferroptosis, emphasizing its reliance on iron metabolism and oxidative stress, which disrupt key processes in reproductive tissues, including granulosa cell function, folliculogenesis, and embryo implantation. Increasing evidence linking ferroptosis to these conditions offers new therapeutic opportunities, with iron chelators, lipid peroxidation inhibitors, and antioxidants showing the potential to alleviate reproductive dysfunction by modulating ferroptotic pathways. In ovarian cancer, ferroptosis inducers combined with conventional cancer therapies, such as chemotherapy, provide promising strategies to overcome drug resistance. This review synthesizes current knowledge on ferroptosis and highlights its importance as a therapeutic target in reproductive health, emphasizing the need for further research to refine and expand treatment options, evaluate their applicability in clinical settings, and explore their role in fertility preservation. By advancing our understanding of ferroptosis regulation, these therapeutic approaches could lead to novel treatments for reproductive disorders and cancers, offering new hope for improving outcomes in women's health and cancer therapy.

Unraveling Alzheimer's disease: insights from single-cell sequencing and spatial transcriptomic

Alzheimer's disease (AD) is a neurodegenerative disorder marked by cognitive decline, primarily affecting memory and executive function. This review highlights recent advancements in single-cell sequencing and spatial transcriptomics, which provide detailed insights into the cellular heterogeneity and neuroimmune mechanisms of AD. The review addresses the need for understanding complex cellular interactions to identify novel therapeutic targets and biomarkers. Single-cell sequencing has revolutionized our understanding by mapping gene expression at the individual cell level, revealing distinct microglial and astrocytic states that contribute to neuroinflammation and neurodegeneration. These technologies have uncovered disease-associated microglial subpopulations and gene expression changes linked to AD risk genes, essential for developing targeted therapies. In conclusion, the integration of single-cell and spatial transcriptomics with other omics data is crucial for a comprehensive understanding of AD, paving the way for personalized medicine. Continued interdisciplinary collaboration will be vital in translating these findings into effective treatments, improving patient outcomes.

Exploring the role of ADAMTSL2 across multiple cancer types: A pan-cancer analysis and validated in colorectal cancer

BACKGROUND

Recent studies have established a correlation between ADAMTSL2 (ADAMTS-like 2) and the development of various cancers. This study aims to conduct a comprehensive pan-cancer analysis in 37 cancer types and investigate its potential role in colon and rectal adenocarcinoma (COADREAD).

METHOD

Pan-cancer and mutation data were sourced from The Cancer Genome Atlas (TCGA) database and analyzed using Sangerbox analysis platform. We explored the expression patterns and prognostic implications of ADAMTSL2, and investigated its relationships with tumor heterogeneity, stemness, immune checkpoint genes, immune cell infiltration, RNA modifications, and mutational profiles across different cancers. Additionally, with Ethics Committee approval, we conducted immunohistochemical (IHC) analysis on 120 COADEAD samples to evaluate ADAMTSL2 expression and its association with clinicopathological parameters.

RESULTS

ADAMTSL2 expression was positively correlated with the hazard ratio of OS, DSS, DFI and PFI for ESCA and COADREAD. A negative correlation was observed between ADAMTSL2 expression and NEO levels in COAD. Gene alterations in ADAMTSL2 were observed, with a mutation frequency of 5.0% in COAD. There is a significant correlation between ADAMTSL2 expression and immune cell infiltration in a variety of cancers. The expression level of ADAMTSL2 protein was associated with T stage, N stage, M stage (p < 0.05). Kaplan‒Meier survival curves demonstrated that the high ADAMTSL2 group had a shorter OS time (p = 0.047) and progression free survival time (p = 0.026) than the low ADAMTSL2 group.

CONCLUSION

In summary, we conducted a comprehensive pan-cancer analysis of ADAMTSL2 and we demonstrated that ADAMTSL2 may serve as a novel prognostic biomarker and immunotherapy target in COADREAD.

The complex interplay of tumor-infiltrating cells in driving therapeutic resistance pathways

Drug resistance remains a significant challenge in cancer treatment. Recently, the interactions among various cell types within the tumor microenvironment (TME) have deepened our understanding of the mechanisms behind treatment resistance. Therefore, this review aims to synthesize current research focusing on infiltrating cells and drug resistance suggesting that targeting the TME could be a viable strategy to combat this issue. Numerous factors, including inflammation, metabolism, senescence, hypoxia, and angiogenesis, contribute to drug resistance could be a viable strategy to combat this issue. Overexpression of STAT3 is commonly associated with drug-resistant cancer cells or stromal cells. Current research often generalizes the impact of stromal cells on resistance, lacking specificity and statistical robustness. Thus, future research should take notice of this issue and aim to provide high-quality evidence. Despite the existing limitations, targeting the TME to overcome therapy resistance hold promising and valuable potential.

Chronobiology of the Tumor Microenvironment: Implications for Therapeutic Strategies and Circadian-Based Interventions

Numerous research works have emphasized the critical role that circadian rhythm plays in the tumor microenvironment (TME). The goal of clarifying chrono-pharmacological strategies for improving cancer treatment in clinical settings is a continuous endeavor. Consequently, to enhance the use of time-based pharmaceutical therapies in oncology, combining existing knowledge on circadian rhythms' roles within the TME is essential. This perspective elucidates the functions of circadian rhythms in the TME across various stages of cancer development, progression, and metastasis. Specifically, aging, angiogenesis, and inflammation are implicated in modulating circadian rhythm within the TME. Furthermore, circadian rhythm exerts a profound influence on current cancer treatments and thereby generates chronotheray to manage tumors. From a TME perspective, circadian rhythm offers promising opportunities for cancer prevention and treatment; nevertheless, further study is needed to address unanswered scientific problems.

Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Despite the rapid evolution of targeted therapies, immunotherapy with checkpoint inhibition (ICI) as well as combination therapies, the cure of metastatic ccRCC (mccRCC) is infrequent, while the optimal use of the various novel agents has not been fully clarified. With the different treatment options, there is an essential need to identify biomarkers to predict therapeutic efficacy and thus optimize therapeutic approaches. This study seeks to explore the diversity in mRNA expression profiles of inflammation and immunity-related circulating genes for the development of biomarkers that could predict the effectiveness of immunotherapy-based treatments using ICIs for individuals with mccRCC. Gene mRNA expression was tested by the RT2 profiler PCR Array on a human cancer inflammation and immunity crosstalk kit and analyzed for differential gene expression along with a machine learning approach for sample classification. A number of mRNAs were found to be differentially expressed in mccRCC with a clinical benefit from treatment compared to those who progressed. Our results indicate that gene expression can classify these samples with high accuracy and specificity.

Decoding Systems Biology of Inflammation Signatures in Cancer Pathogenesis: Pan-Cancer Insights from 12 Common Cancers

Chronic inflammation is an important contributor to tumorigenesis in many tissues. However, the underlying mechanisms of inflammatory signaling in the tumor microenvironment are not yet fully understood in various cancers. Therefore, this study aimed to uncover the gene expression signatures of inflammation-associated proteins that lead to tumorigenesis, and with an eye to discovery of potential system biomarkers and novel drug candidates in oncology. Gene expression profiles associated with 12 common cancers (e.g., breast invasive carcinoma, colon adenocarcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma) from The Cancer Genome Atlas were retrieved and mapped to inflammation-related gene sets. Subsequently, the inflammation-associated differentially expressed genes (i-DEGs) were determined. The i-DEGs common in all cancers were proposed as tumor inflammation signatures (TIS) after pan-cancer analysis. A TIS, consisting of 45 proteins, was evaluated as a potential system biomarker based on its prognostic forecasting and secretion profiles in multiple tissues. In addition, i-DEGs for each cancer type were used as queries for drug repurposing. Narciclasine, parthenolide, and homoharringtonine were identified as potential candidates for drug repurposing. Biomarker candidates in relation to inflammation were identified such as KNG1, SPP1, and MIF. Collectively, these findings inform precision diagnostics development to distinguish individual cancer types, and can also pave the way for novel prognostic decision tools and repurposed drugs across multiple cancers. These new findings and hypotheses warrant further research toward precision/personalized medicine in oncology. Pan-cancer analysis of inflammatory mediators can open up new avenues for innovation in cancer diagnostics and therapeutics.

Adhesion-regulating molecule 1 (ADRM1) can be a potential biomarker and target for bladder cancer

Adhesion-regulating molecule 1 (ADRM1) has been implicated in tumor development, yet its specific role in bladder cancer (BC) remains undefined. This study aimed to elucidate the function of ADRM1 in BC through a combination of bioinformatics analysis and immunohistochemical analysis (IHC). Utilizing R version 3.6.3 and relevant packages, we analyzed online database data. Validation was conducted through IHC data, approved by the Institutional Ethics Committee (Approval No. K20220830). In both paired and unpaired comparisons, ADRM1 expression was significantly elevated in BC tissues compared to adjacent tissues, as evidenced by the results of TCGA dataset and IHC data. Patients with high ADRM1 expression had statistically worse overall survival than those with low ADRM1 expression in TCGA dataset, GSE32548 dataset, GSE32894 dataset, and IHC data. Functional analysis unveiled enrichment in immune-related pathways, and a robust positive correlation emerged between ADRM1 expression and pivotal immune checkpoints, including CD274, PDCD1, and PDCD1LG2. In tumor microenvironment, samples with the high ADRM1 expression contained statistical higher proportion of CD8 + T cells and Macrophage infiltration. Meanwhile, these high ADRM1-expressing samples displayed elevated tumor mutation burden scores and stemness indices, implying potential benefits from immunotherapy. Patients with low ADRM1 expression were sensitive to cisplatin, docetaxel, vinblastine, mitomycin C, and methotrexate. According to the findings from bioinformatics and IHC analyses, ADRM1 demonstrates prognostic significance for BC patients and holds predictive potential for both immunotherapy and chemotherapy responses. This underscores its role as a biomarker and therapeutic target in BC.

A novel endothelial-related prognostic index by integrating single-cell and bulk RNA sequencing data for patients with kidney renal clear cell carcinoma

Background: Endothelial cells in the tumor microenvironment play an important role in the development of kidney renal clear cell carcinoma (KIRC). We wanted to further identify the function of endothelial cells in KIRC patients by integrating single-cell and bulk RNA sequencing data.

Methods: Online databases provide the original data of this study. An endothelial-related prognostic index (ERPI) was constructed and validated by R version 3.6.3 and relative packages.

Results: The ERPI consisted of three genes (CCND1, MALL, and VWF). Patients with high ERPI scores were significantly correlated with worse prognosis than those with low ERPI scores in the TCGA training group, TCGA test group, and GSE29609 group. A positive correlation was identified between the ERPI score and poor clinical features. The results of functional analysis indicated that ERPI was significantly associated with immune-related activities. We suggested that patients with high ERPI scores were more likely to benefit from immunotherapy based on the results of immune checkpoints, tumor microenvironment, stemness index, and TCIA, while patients with low ERPI scores were sensitive to gemcitabine, docetaxel, paclitaxel, axitinib, pazopanib, sorafenib, and temsirolimus according to the results of the “pRRophetic” algorithm. Therefore, this ERPI may help doctors choose the optimal treatment for patients with KIRC.

Conclusion: By integrating single-cell and bulk RNA sequencing data from KIRC patients, we successfully identified the key genes from the perspective of endothelial cells in the tumor microenvironment and constructed ERPIs that had positive implications in precision medicine.

The emerging roles and potential applications of circular RNAs in ovarian cancer: a comprehensive review

Ovarian cancer (OC) is among the most common human malignancies and the first cause of deaths among gynecologic cancers. Early diagnosis can help improving prognosis in those patients, and accordingly exploring novel molecular mechanisms may lead to find therapeutic targets. Circular RNAs (circRNAs) comprise a group of non-coding RNAs in multicellular organisms, which are identified with characteristic circular structure. CircRNAs have been found with substantial functions in regulating gene expression through interacting with RNA-binding proteins, targeting microRNAs, and transcriptional regulation. They have been found to be involved in regulating several critical processes such as cell growth, and death, organ development, signal transduction, and tumorigenesis. Accordingly, circRNAs have been implicated in a number of human diseases including malignancies. They are particularly reported to contribute to several hallmarks of cancer leading to cancer development and progression, although a number also are described with tumor-suppressor function. In OC, circRNAs are linked to regulation of cell growth, invasiveness, metastasis, angiogenesis, and chemoresistance. Notably, clinical studies also have shown potentials in diagnosis, prediction of prognosis, and therapeutic targets for OC. In this review, I have an overview to the putative mechanisms, and functions of circRNAs in regulating OC pathogenesis in addition to their clinical potentials.