Prognostic value of immune-related genes and comparative analysis of immune cell infiltration in lung adenocarcinoma: sex differences

Identification and immunological characteristics of anoikis-associated molecular clusters in lung adenocarcinoma

Anoikis plays a crucial role in the progression, prognosis, and immune response of lung adenocarcinoma (LUAD). However, its specific impact on LUAD remains unclear. In this study, we investigated the intricate interplay of nesting apoptotic factors in LUAD. By analyzing nine key nesting apoptotic factors, we categorized LUAD patients into two distinct clusters. Further examination of immune cell profiles revealed that Cluster A exhibited greater infiltration of innate immune cells than did Cluster B. Additionally, we identified two genes closely associated with prognosis and developed a predictive model to differentiate patients based on molecular clusters. Our findings suggest that the loss of specific anoikis-related genes could significantly influence the prognosis, tumor microenvironment, and clinical features of LUAD patients. Furthermore, we validated the expression and functional roles of two pivotal prognostic genes, solute carrier family 2 member 1 (SLC2A1) and sphingosine kinase 1 (SPHK1), in regulating tumor cell viability, migration, apoptosis, and anoikis. These results offer valuable insights for future mechanistic investigations. In conclusion, this study provides new avenues for advancing our understanding of LUAD, improving prognostic assessments, and developing more effective immunotherapy strategies.

Identification of the consistently differential expressed hub mRNAs and proteins in lung adenocarcinoma and construction of the prognostic signature: a multidimensional analysis

BACKGROUND

This study aimed to elucidate the consistency of differentially expressed hub mRNAs and proteins in lung adenocarcinoma (LUAD) across populations and to construct a comprehensive LUAD prognostic signature.

METHODS

The transcriptomic and proteomics data from different populations were standardized and analyzed using the same criteria to identify the consistently differential expressed mRNAs and proteins across genders and races. We then integrated prognosis-related mRNAs with clinical, pathological, and EGFR (epidermal growth factor receptor) mutation data to construct a survival model, subsequently validating it across populations. Through plasma proteomics, plasma proteins that consistently differential expressed with LUAD tissues were screened and validated, with their associations discerned by measuring expressions in tumor tissues and tumor vascular normalization.

RESULTS

The consistency rate of differentially expressed mRNAs and proteins was ~20-40%, with ethnic factors leading to about 40-60% consistency of differentially expressed mRNA or protein across populations. The survival model based on the identified eight hub mRNAs as well as stage, smoking status, and EGFR mutations, demonstrated good prognostic prediction capabilities in both Western and East Asian populations, with a higher number of unfavorable variables indicating poorer LUAD prognosis. Notably, GPI expression in tumor tissues was inversely correlated with vascular normalization and positively correlated with plasma GPI expression.

CONCLUSION

Our study underscores the significance of integrating transcriptomics and proteomics data, emphasizing the need to account for genetic diversity among ethnic groups. The developed survival model may offer a holistic perspective on LUAD progression, enhancing prognosis and therapeutic strategies.

An emerging link between lncRNAs and cancer sex dimorphism

The prevalence and progression of cancer differ in males and females, and thus, sexual dimorphism in tumor development directly impacts clinical research and medicine. Long non-coding RNAs (lncRNAs) are increasingly recognized as important players in gene expression and various cellular processes, including cancer development and progression. In recent years, lncRNAs have been implicated in the differences observed in cancer incidence, progression, and treatment responses between men and women. Here, we present a brief overview of the current knowledge regarding the role of lncRNAs in cancer sex dimorphism, focusing on how they affect epigenetic processes in male and female mammalian cells. We discuss the potential mechanisms by which lncRNAs may contribute to sex differences in cancer, including transcriptional control of sex chromosomes, hormonal signaling pathways, and immune responses. We also propose strategies for studying lncRNA functions in cancer sex dimorphism. Furthermore, we emphasize the importance of considering sex as a biological variable in cancer research and the need to investigate the role lncRNAs play in mediating these sex differences. In summary, we highlight the emerging link between lncRNAs and cancer sex dimorphism and their potential as therapeutic targets.

Tumor-associated macrophages: Prognostic and therapeutic targets for cancer in humans and dogs

Macrophages are ancient, phagocytic immune cells thought to have their origins 500 million years ago in metazoan phylogeny. The understanding of macrophages has evolved to encompass their foundational roles in development, homeostasis, tissue repair, inflammation, and immunity. Notably, macrophages display high plasticity in response to environmental cues, capable of a strikingly wide variety of dynamic gene signatures and phenotypes. Macrophages are also involved in many pathological states including neural disease, asthma, liver disease, heart disease, cancer, and others. In cancer, most tumor-associated immune cells are macrophages, coined tumor-associated macrophages (TAMs). While some TAMs can display anti-tumor properties such as phagocytizing tumor cells and orchestrating an immune response, most macrophages in the tumor microenvironment are immunosuppressive and pro-tumorigenic. Macrophages have been implicated in all stages of cancer. Therefore, interest in manipulating macrophages as a therapeutic strategy against cancer developed as early as the 1970s. Companion dogs are a strong comparative immuno-oncology model for people due to documented similarities in the immune system and spontaneous cancers between the species. Data from clinical trials in humans and dogs can be leveraged to further scientific advancements that benefit both species. This review aims to provide a summary of the current state of knowledge on macrophages in general, and an in-depth review of macrophages as a therapeutic strategy against cancer in humans and companion dogs.

Anoikis-related genes combined with single cell sequencing: Insights into model specification of lung adenocarcinoma and applicability for prognosis and therapy

Background: Anoikis has therapeutic potential against different malignancies including lung adenocarcinoma. This study used anoikis and bioinformatics to construct a prognostic model for lung adenocarcinoma and explore new therapeutic strategies. Methods: Several bioinformatic algorithms (co-expression analysis, univariate Cox analysis, multivariate Cox analysis, and cross-validation) were used to screen anoikis-related genes (ARGs) to construct a risk model. Lung adenocarcinoma patients were divided into training and testing groups at a ratio of 1:1. The prognostic model was validated by risk score comparison between high- and low-risk groups using receiver operating characteristic curve (ROC), nomograms, independent prognostic analysis and principal component analysis. In addition, two anoikis-related genes patterns were classified utilizing consensus clustering method and were compared with each other in survival time, immune microenvironment, and regulation in pathway. Single cell sequencing was applied to analyze anoikis-related genes constructed the model. Results: This study demonstrated the feasibility of the model based on seven anoikis-related genes, as well as identifying axitinib, nibtinib and sorafenib as potential therapeutic strategies for LUAD. Risk score based on this model had could be used as an independent prognostic factor for lung adenocarcinoma (HR > 1; p < 0.001) and had the highest accuracy to predict survival compared with the clinical characteristics. Single cell sequencing analysis discovered Keratin 14 (KRT14, one of the seven anoikis-related genes) was mainly expressed in malignant cells in various cancers. Conclusion: We identified seven anoikis-related genes and constructed an accurate risk model based on bioinformatics analysis that can be used for prognostic prediction and for the design of therapeutic strategies in clinical practice.

Development and Validation of a Prognostic Nomogram for Lung Adenocarcinoma: A Population-Based Study

PURPOSE

To establish an effective and accurate prognostic nomogram for lung adenocarcinoma (LUAD). Patients and Methods. 62,355 LUAD patients from 1975 to 2016 enrolled in the Surveillance, Epidemiology, and End Results (SEER) database were randomly and equally divided into the training cohort (n = 31,179) and the validation cohort (n = 31,176). Univariate and multivariate Cox regression analyses screened the predictive effects of each variable on survival. The concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) were used to examine and validate the predictive accuracy of the nomogram. Kaplan-Meier curves were used to estimate overall survival (OS).

RESULTS

10 prognostic factors associated with OS were identified, including age, sex, race, marital status, American Joint Committee on Cancer (AJCC) TNM stage, tumor size, grade, and primary site. A nomogram was established based on these results. C-indexes of the nomogram model reached 0.777 (95% confidence interval (CI), 0.773 to 0.781) and 0.779 (95% CI, 0.775 to 0.783) in the training and validation cohorts, respectively. The calibration curves were well-fitted for both cohorts. The AUC for the 3- and 5-year OS presented great prognostic accuracy in the training cohort (AUC = 0.832 and 0.827, respectively) and validation cohort (AUC = 0.835 and 0.828, respectively). The Kaplan-Meier curves presented significant differences in OS among the groups.

CONCLUSION

The nomogram allows accurate and comprehensive prognostic prediction for patients with LUAD.

N6-methylandenosine-related immune genes correlate with prognosis and immune landscapes in gastric cancer

OBJECTIVES

This study aimed to probe into the significance of N6-methyladenosine (m6A)-related immune genes (m6AIGs) in predicting prognoses and immune landscapes of patients with gastric cancer (GC).

METHODS

The clinical data and transcriptomic matrix of GC patients were acquired from The Cancer Genome Atlas database. The clinically meaningful m6AIGs were acquired by univariate Cox regression analysis. GC patients were stratified into different clusters via consensus clustering analysis and different risk subgroups via m6AIGs prognostic signature. The clinicopathological features and tumor microenvironment (TME) in the different clusters and different risk subgroups were explored. The predictive performance was evaluated using the KM method, ROC curves, and univariate and multivariate regression analyses. Moreover, we fabricated a nomogram based on risk scores and clinical risk characteristics. Biological functional analysis was performed based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The connectivity map was used to screen out potential small molecule drugs for GC patients.

RESULTS

A total of 14 prognostic m6AIGs and two clusters based on 14 prognostic m6AIGs were identified. A prognostic signature based on 4 m6AIGs and a nomogram based on independent prognostic factors was constructed and validated. Different clusters and different risk subgroups were significantly correlated with TME scores, the distribution of immune cells, and the expression of immune checkpoint genes. Some malignant and immune biological processes and pathways were correlated with the patients with poor prognosis. Ten small molecular drugs with potential therapeutic effect were screened out.

CONCLUSIONS

This study revealed the prognostic role and significant values of m6AIGs in GC, which enhanced the understanding of m6AIGs and paved the way for developing predictive biomarkers and therapeutic targets for GC.