Influence of Different Age Cutoff Points on the Prediction of Prognosis of Cancer Patients Receiving ICIs and Potential Mechanistic Exploration

A specific enterotype derived from gut microbiome of older individuals enables favorable responses to immune checkpoint blockade therapy

Immunotherapy has revolutionized cancer treatment, but inconsistent responses persist. Our study delves into the intriguing phenomenon of enhanced immunotherapy sensitivity in older individuals with cancers. Through a meta-analysis encompassing 25 small-to-mid-sized trials of immune checkpoint blockade (ICB), we demonstrate that older individuals exhibit heightened responsiveness to ICB therapy. To understand the underlying mechanism, we reanalyze single-cell RNA sequencing (scRNA-seq) data from multiple studies and unveil distinct upregulation of exhausted and cytotoxic T cell markers within the tumor microenvironment (TME) of older patients. Recognizing the potential role of gut microbiota in modulating the efficacy of immunotherapy, we identify an aging-enriched enterotype linked to improved immunotherapy outcomes in older patients. Fecal microbiota transplantation experiments in mice confirm the therapeutic potential of the aging-enriched enterotype, enhancing treatment sensitivity and reshaping the TME. Our discoveries confront the prevailing paradox and provide encouraging paths for tailoring cancer immunotherapy strategies according to an individual's gut microbiome profile.

Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

Artificial neural network-based gene screening and immune cell infiltration analysis of osteosarcoma feature

BACKGROUND

The present study aimed to construct an artificial neural network (ANN) model that leverages characteristic genes associated with osteosarcoma (OS) to enable accurate prognostication for OS patients.

METHODS

Our research revealed 467 differentially expressed genes (DEGs) via gene expression contrast analysis, consisting of 345 downregulated genes and 122 upregulated genes. Gene Ontology (GO) enrichment analysis illuminated functions primarily encompassing T-cell activation, secretory granule lumen and antioxidant activity, among others. Through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we discovered significant correlations between the DEGs and certain pathways, including phagosome, Staphylococcus aureus infection and human T-cell leukemia virus 1 infection. We then screened out 30 characteristic DEGs (CDEGs) based on random forest analysis and constructed the ANN model using the gene score matrix. To verify the credibility and accuracy of the ANN model, we performed internal and external validation processes, which affirmed our model's predictive capabilities.

RESULTS

The study further delved into the analysis of immune cell infiltration and its correlation with the target CDEGs, revealing disparities in the infiltration of 22 types of immune cells across different groups and their interrelationships. Moreover, we probed the expression of the two foremost CDEGs (YES1 and MFNG) in OS and normal tissues. We noted a positive relationship between the expression of YES1 and MFNG in OS tissues and the clinicopathological characteristics of OS patients.

CONCLUSIONS

Collectively, the findings of the present study validate the effectiveness of the CDEGs-based ANN model in predicting OS patients, which might facilitate early diagnosis and treatment of OS.

Considerations and Approaches for Cancer Immunotherapy in the Aging Host

Advances in cancer immunotherapy are improving treatment successes in many distinct cancer types. Nonetheless, most tumors fail to respond. Age is the biggest risk for most cancers, and the median population age is rising worldwide. Advancing age is associated with manifold alterations in immune cell types, abundance, and functions, rather than simple declines in these metrics, the consequences of which remain incompletely defined. Our understanding of the effects of host age on immunotherapy mechanisms, efficacy, and adverse events remains incomplete. A deeper understanding of age effects in all these areas is required. Most cancer immunotherapy preclinical studies examine young subjects and fail to assess age contributions, a remarkable deficit given the known importance of age effects on immune cells and factors mediating cancer immune surveillance and immunotherapy efficacy. Notably, some cancer immunotherapies are more effective in aged versus young hosts, while others fail despite efficacy in the young. Here, we review our current understanding of age effects on immunity and associated nonimmune cells, the tumor microenvironment, cancer immunotherapy, and related adverse effects. We highlight important knowledge gaps and suggest areas for deeper enquiries, including in cancer immune surveillance, treatment response, adverse event outcomes, and their mitigation.

PD-1 and PD-L1 expression in rare lung tumors

Background: Our knowledge is still limited about the characteristics and treatment of rare lung tumors. The aim of our study was to determine programmed cell death ligand-1 (PD-L1) and programmed cell death-1 (PD-1) expression in rare pulmonary tumors to assess the potential role of immunotherapy. Methods: 66 pathologically confirmed rare lung tumors including 26 mucoepidermoid carcinomas (MECs), 27 adenoid cystic carcinomas (ACCs), and 13 tracheobronchial papillomas (TBPs) were collected retrospectively. Immunohistochemical (IHC) staining was performed on formalin fixed paraffin embedded (FFPE) tumor tissues, and PD-L1 expression on tumor cells (TCs) and immune cells (ICs), and PD-1 expression on ICs were determined. The cut off value for positive immunostaining was set at 1% for all markers. Results: PD-L1 expression on TCs was observed in two cases of MEC (7.7%), one case of ACC (3.7%), and was absent in TBP samples. PD-L1 expression on ICs could be demonstrated in nine cases of MEC (34.6%), four cases of ACC (14.8%), and was absent in TBPs. All PD-L1 TC positive tumors were also PD-L1 IC positive. Higher expression level than 5% of PD-L1 TC and/or IC was observed only in one ACC and in two MEC patients. Among them, strong PD-L1 immunopositivity of >50% on TCs and of >10% on ICs could be demonstrated in one MEC sample. PD-L1 expression of ≥1% on ICs was significantly more common in MEC, than in TBP (p < 0.001). In MEC ≥1% PD-L1 TC or IC expressions were significantly more common in patients aged 55 or older, than in younger patients (p = 0.046, and p = 0.01, respectively). PD-1 expression on ICs was found in five cases of MEC (19.2%), four cases of ACC (14.8%), and in two cases of TBP (15.4%). Only one MEC case showed a higher than 5% expression level of PD-1 on ICs. Conclusion: This retrospective study comprehensively demonstrated the rare expression of PD-L1 and PD-1 in pulmonary MEC, ACC, and TBP. However, we found very strong PD-L1 immunopositivity on both TCs and ICs in one MEC sample, which warrants further investigations in a larger cohort.

Construction of a pyroptosis-related lncRNAs signature for predicting prognosis and immunotherapy response in glioma

Recent studies have proved that pyroptosis-related long non-coding RNAs (PRlncRNAs) are closely linked to tumor progression, prognosis, and immunity. Here, we systematically evaluated the correlation of PRlncRNAs with glioma prognosis. This study included 3 glioma cohorts (The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gravendeel). Through Pearson correlation analysis, PRlncRNAs were screened from these 3 cohorts. Univariate Cox regression analysis was then carried out to determine the prognostic PRlncRNAs. A pyroptosis-related lncRNAs signature (PRLS) was then built by least absolute shrinkage and selection operator and multivariate Cox analyses. We systematically evaluated the correlation of the PRLS with the prognosis, immune features, and tumor mutation burden in glioma. A total of 14 prognostic PRlncRNAs overlapped in all cohorts and were selected as candidate lncRNAs. Based on The Cancer Genome Atlas cohort, a PRLS containing 7 PRlncRNAs was built. In all cohorts, the PRLS was proved to be a good predictor of glioma prognosis, with a higher risk score related to a poorer prognosis. We observed obvious differences in the immune microenvironment, immune cell infiltration level, and immune checkpoint expression in low- and high-risk subgroups. Compared with low-risk cases, high-risk cases had lower Tumor Immune Dysfunction and Exclusion scores and greater tumor mutation burden, indicating that high-risk cases can be more sensitive to immunotherapy. A nomogram combining PRLS and clinical parameters was constructed, which showed more robust and accurate predictive power. In conclusion, the PRLS is a potentially useful indicator for predicting prognosis and response to immunotherapy in glioma. Our findings may provide a useful insight into clinically individualized treatment strategies for patients.

Immune checkpoint expression and relationships to anti-PD-L1 immune checkpoint blockade cancer immunotherapy efficacy in aged versus young mice

Introduction

Aging is the biggest cancer risk, and immune checkpoint (IC) inhibition (ICI) is a revolutionary cancer immunotherapy approach. Nonetheless, there are limited preclinical/clinical data regarding aging effects on ICI outcomes or age effects on IC expression in different organs or tumors.

Methods

Flow cytometry assessed IC on immune and non-immune cells in various organs in young and aged BL6 mice. Comparisons: aged versus young naïve WT versus interferon-γ ^KO mice and WT challenged with B16F10 melanoma and treated with αPD-1 or αPD-L1 ICI. We co-cultured young and aged T cells and myeloid cells in vitro and used OMIQ analyses to test cell-cell interactions.

Results

αPD-1 ICI treated melanoma in young and aged hosts, whereas αPD-L1 ICI was only effective in young. We found considerable, previously undescribed age effects on expression of various IC molecules participating in the ICI treatment, including PD-1, PD-L1, PD-L2, and CD80, in distinct organs and in the tumor. These data help explain differential ICI efficacy in young and aged hosts. Host interferon-γ influenced age effects on IC expression in both directions depending on specific IC molecule and tissue. IC expression was further affected by tumor challenge on immune, non-immune, and tumor cells in tumor and other organs. In in vitro co-culture, αPD-1 versus αPD-L1 distinctly influenced polyclonal T cells in young versus aged, suggesting mechanisms for distinct age-related ICI outcomes.

Conclusion

Age affects IC expression on specific immune cells in an organ- and tissue-specific manner. ICs were generally higher on aged immune cells. High immune-cell PD-1 could help explain αPD-1 efficacy in aged. High co-expression of CD80 with PD-L1 on dendritic cells could help explain lack of αPD-L1 efficacy in aged hosts. Factors other than myeloid cells and interferon-γ also affect age-related IC expression and T cell function, meriting additional studies.

Potential Reasons for Unresponsiveness to Anti-PD1 Immunotherapy in Young Patients with Advanced Melanoma

The impact of age on the clinical benefit of anti-PD1 immunotherapy in advanced melanoma patients has been evolving recently. Due to a reduced immune function in elderly patients, young patients with a robust immune system are theoretically expected to benefit more from the treatment approach. However, in contrast to this hypothesis, recent studies in patients with metastatic melanoma have demonstrated that immunotherapy, especially with anti-PD1 treatment, is less effective in patients below 65 years, on average, with significantly lower responses and reduced overall survival compared to patients above 65 years of age. Besides, data on young patients are even more sparse. Hence, in this review, we will focus on age-dependent differences in the previously described resistance mechanisms to the treatment and discuss the development of potential combination treatment strategies for enhancing the anti-tumor efficacy of anti-PD1 or PDL1 treatment in young melanoma patients.

TNF-Alpha Pathway Alternation Predicts Survival of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer

Translational research on immune checkpoint inhibitors (ICIs) has been underway. However, in the unselected population, only a few patients benefit from ICIs. Therefore, screening predictive markers of ICI efficacy has become the current focus of attention. We collected mutation and clinical data from an ICI-treated non-small cell lung cancer (NSCLC) cohort. Then, a univariate Cox regression model was used to analyze the relationship between tumor necrosis factor α signaling mutated (TNFα-MT) and the prognosis of immunotherapy for NSCLC. We retrospectively collected 36 NSCLC patients (local-cohort) from the Zhujiang Hospital of Southern Medical University and performed whole-exome sequencing (WES). The expression and mutation data of The Cancer Genome Atlas (TCGA)-NSCLC cohort were used to explore the association between TNFα-MT and the immune microenvironment. A local cohort was used to validate the association between TNFα-MT and immunogenicity. TNFα-MT was associated with significantly prolonged overall survival (OS) in NSCLC patients after receiving immunotherapy. Additionally, TNFα-MT is related to high immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations) and enrichment of infiltrating immune cells. These results suggest that TNFα-MT may serve as a potential clinical biomarker for NSCLC patients receiving ICIs.