Exploration of Different Hypoxia Patterns and Construction of a Hypoxia-Related Gene Prognostic Index in Colorectal Cancer

Circadian rhythm, hypoxia, and cellular senescence: From molecular mechanisms to targeted strategies

Cellular senescence precipitates a decline in physiological activities and metabolic functions, often accompanied by heightened inflammatory responses, diminished immune function, and impaired tissue and organ performance. Despite extensive research, the mechanisms underpinning cellular senescence remain incompletely elucidated. Emerging evidence implicates circadian rhythm and hypoxia as pivotal factors in cellular senescence. Circadian proteins are central to the molecular mechanism governing circadian rhythm, which regulates homeostasis throughout the body. These proteins mediate responses to hypoxic stress and influence the progression of cellular senescence, with protein Brain and muscle arnt-like 1 (BMAL1 or Arntl) playing a prominent role. Hypoxia-inducible factor-1α (HIF-1α), a key regulator of oxygen homeostasis within the cellular microenvironment, orchestrates the transcription of genes involved in various physiological processes. HIF-1α not only impacts normal circadian rhythm functions but also can induce or inhibit cellular senescence. Notably, HIF-1α may aberrantly interact with BMAL1, forming the HIF-1α-BMAL1 heterodimer, which can instigate multiple physiological dysfunctions. This heterodimer is hypothesized to modulate cellular senescence by affecting the molecular mechanism of circadian rhythm and hypoxia signaling pathways. In this review, we elucidate the intricate relationships among circadian rhythm, hypoxia, and cellular senescence. We synthesize diverse evidence to discuss their underlying mechanisms and identify novel therapeutic targets to address cellular senescence. Additionally, we discuss current challenges and suggest potential directions for future research. This work aims to deepen our understanding of the interplay between circadian rhythm, hypoxia, and cellular senescence, ultimately facilitating the development of therapeutic strategies for aging and related diseases.

Overcoming immunotherapy resistance in gastric cancer: insights into mechanisms and emerging strategies

Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, with limited treatment options in advanced stages. Immunotherapy, particularly immune checkpoint inhibitors (ICIs) targeting PD1/PD-L1, has emerged as a promising therapeutic approach. However, a significant proportion of patients exhibit primary or acquired resistance, limiting the overall efficacy of immunotherapy. This review provides a comprehensive analysis of the mechanisms underlying immunotherapy resistance in GC, including the role of the tumor immune microenvironment, dynamic PD-L1 expression, compensatory activation of other immune checkpoints, and tumor genomic instability. Furthermore, the review explores GC-specific factors such as molecular subtypes, unique immune evasion mechanisms, and the impact of Helicobacter pylori infection. We also discuss emerging strategies to overcome resistance, including combination therapies, novel immunotherapeutic approaches, and personalized treatment strategies based on tumor genomics and the immune microenvironment. By highlighting these key areas, this review aims to inform future research directions and clinical practice, ultimately improving outcomes for GC patients undergoing immunotherapy.

Molecular subtype identification and prognosis stratification by a immunogenic cell death-related gene expression signature in colorectal cancer

OBJECTIVES

This study intended to develop a new immunogenic cell death (ICD)-related prognostic signature for colorectal cancer (CRC) patients.

RESEARCH DESIGN AND METHODS

The Non-Negative Matrix Factorization (NMF) algorithm was adopted to cluster tumor samples based on ICD gene expression to obtain ICD-related subtypes. Survival analysis and immune microenvironment analysis were conducted among different subtypes. Regression analysis was used to construct the model. Based on riskscore median, cancer patients were classified into high and low risk groups, and independent prognostic ability of the model was analyzed. The CIBERSORT algorithm was adopted to determine the immune infiltration level of both groups.

RESULTS

We analyzed the differential genes between cluster 4 and cluster 1-3 and obtained 12 genes with the best prognostic features finally (NLGN1, SLC30A3, C3orf20, ADAD2, ATOH1, ATP6V1B1, KCNQ2, MUCL3, RGCC, CLEC17A, COL6A5, and INSL4). In addition, patients with lower risk had higher levels of infiltration of most immune cells, lower Tumor Immune Dysfunction and Exclusion (TIDE) level and higher immunophenscore (IPS) level than those with higher risk.

CONCLUSIONS

This study constructed and validated the ICD feature signature predicting CRC prognosis and provide a reference criteria for guiding the prognosis and immunotherapy of CRC cancer patients.

Predictive Models for Colon Adenocarcinoma Diagnosis, Prognosis, and Immune Microenvironment Based on 2 Hypoxia-Related Genes: KDM3A and ENO3

Background: Hypoxia is known to play a critical role in tumor occurrence, progression, prognosis, and therapy resistance. However, few studies have investigated hypoxia markers for diagnosing and predicting prognosis in colon adenocarcinoma (COAD). This study aims to identify a hypoxia genes-based biomarker for predicting COAD patients' prognosis and response to immunotherapy on an individual basis. Methods: Hypoxia-related genes were extracted from the Molecular Signatures Database. Gene expression, clinical data, and mutation data of COAD were collected retrospectively from the Cancer Genome Atlas, the Gene Expression Omnibus, and the International Cancer Genome Consortium databases. Univariate and multivariate cox regression, and the least absolute shrinkage and selection operator method were used to select the genes most associated with the prognosis of COAD patients. Kaplan-Meier survival analysis, receiver operating characteristic curves, calibration curves, and decision curve analyses were performed to validate the efficacy of the signature in predicting the prognosis of COAD patients. EdU incorporation assays, cell survival assays, western blot assays, and trans-well invasion assays were performed to further confirm the function of the screened genes in tumorigenesis. Results: ENO3 and KDM3A were identified as key genes for constructing prognostic and diagnostic signatures, which were found to be independent risk factors for predicting the prognosis and diagnosis of COAD patients. Using these signatures, COAD patients could be stratified into high-risk and low-risk groups, with the latter exhibiting better overall survival outcomes. Moreover, the high-risk group displayed elevated levels of immune checkpoint genes and tumor mutation burden, indicating that these patients may benefit from immune checkpoint inhibitor therapy. Conclusion: The signature developed in this study demonstrates excellent efficacy in prognosticating the outcomes of COAD patients. Moreover, it can serve as a valuable tool for clinicians to identify COAD patients who are suitable for ICI therapy.