An aging-related signature predicts favorable outcome and immunogenicity in lung adenocarcinoma

Exploring the molecular and immune landscape of cellular senescence in lung adenocarcinoma

Introduction

The connection between aging and cancer is complex. Previous research has highlighted the association between the aging process of lung adenocarcinoma (LUAD) cells and the immune response, yet there remains a gap in confirming this through single-cell data validation. Here, we aim to develop a novel aging-related prognostic model for LUAD, and verify the alterations in the genome and immune microenvironment linked to cellular senescence.

Methods

We integrated a comprehensive collection of senescence genes from the GenAge and CellAge databases and employed the least absolute shrinkage and selection operator (LASSO) Cox analysis to construct and validate a novel prognostic model for LUAD. This model was then utilized to examine the relationship between aging, tumor somatic mutations, and immune cell infiltration. Additionally, we explored the heterogeneity of senescence and intercellular communication within the LUAD tumor microenvironment (TME) through single-cell transcriptomic data analysis.

Results

By exploring the expression profiles of 586 cellular senescence-related genes in 428 LUAD patients, we constructed an aging-related genes (ARGs) risk model included 10 ARGs and validated it as an independent prognostic predictor for LUAD patients. Notably, patients with low aging scores (LAS group) exhibited better survival, lower tumor mutation burden (TMB), lower somatic mutation frequency, lower tumor proliferation rate, and an immune activated phenotype compared to patients with high aging scores (HAS group). While the HAS group was enriched in tumor cells and showed a lower infiltration of CD8-CCR7, CD8- CXCL13, CD8-GNLY, FCGR3A NK cells, XCL1 NK cells, plasma cell (PC) and other immune subsets. Furthermore, the SPP1 and TENASCIN pathways, associated with tumor immune escape and tumor progression, were also enriched in the HAS group. Additionally, our study also indicated that senescence levels were heterogeneous in the LUAD tumor microenvironment (TME), especially with tumor cells in the LAS group showing higher age scores compared to those in the HAS group.

Conclusions

Collectively, our findings underscore that ARRS through ARGs serves as a robust biomarker for the prognosis in LUAD.

Aging-associated Alterations in the Gene Regulatory Network Landscape Associate with Risk, Prognosis and Response to Therapy in Lung Adenocarcinoma

Aging is the primary risk factor for many individual cancer types, including lung adenocarcinoma (LUAD). To understand how aging-related alterations in the regulation of key cellular processes might affect LUAD risk and survival outcomes, we built individual (person)-specific gene regulatory networks integrating gene expression, transcription factor protein-protein interaction, and sequence motif data, using PANDA/LIONESS algorithms, for both non-cancerous lung tissue samples from the Genotype Tissue Expression (GTEx) project and LUAD samples from The Cancer Genome Atlas (TCGA). In GTEx, we found that pathways involved in cell proliferation and immune response are increasingly targeted by regulatory transcription factors with age; these aging-associated alterations are accelerated by tobacco smoking and resemble oncogenic shifts in the regulatory landscape observed in LUAD and suggests that dysregulation of aging pathways might be associated with an increased risk of LUAD. Comparing normal adjacent samples from individuals with LUAD with healthy lung tissue samples from those without LUAD, we found that aging-associated genes show greater aging-biased targeting patterns in younger individuals with LUAD compared to their healthy counterparts of similar age, a pattern suggestive of age acceleration. This implies that an accelerated aging process may be responsible for tumor incidence in younger individuals. Using drug repurposing tool CLUEreg, we found small molecule drugs with potential geroprotective effects that may alter the accelerating aging profiles we found. We also observed that, in contrast to chronological age, a network-informed aging signature was associated with survival and response to chemotherapy in LUAD.

A novel signature of seven aging-related genes for risk stratification, prognosis prediction and benefit evaluation of chemotherapy, and immunotherapy in elderly patients with lung adenocarcinoma

Background

Aging, a multifaceted biological process, is thought to be associated with lung adenocarcinoma (LUAD) development and progression. However, it is unclear whether aging-related genes (ARGs) can predict tumor risk, chemotherapy and immunotherapy benefits, and prognosis in LUAD patients at different ages.

Methods

Gene expression datasets and clinical information of LUAD patients were downloaded from TCGA and GEO database. Univariate and multivariate Cox regression, and lasso algorithm were employed to identify the ARG signatures. Patients were stratified into high-risk and low-risk groups to evaluate the predictive accuracy using Kaplan-Meier curves, ROC curves, and time-dependent AUC. A nomogram was established to predict the survival probability. GSEA revealed potential pathways, and CIBERSORT indicated different immunologic status. TIDE score was used to predict the potential tumor response to immune checkpoint inhibitors, and GDSC was employed to evaluate the sensitivity of chemotherapeutic drugs. The correlation of TIDE score and patient age, as well as that of ARGs and patient age was investigated. And cell Culture and RT-qPCR for external validation for key gene.

Results

A novel gene signature based on seven ARGs was established, including BMP15, CD79A, CDKN3, CDX2, COL1A1, DKK1, and GRIK2. Our model demonstrated exceptional prediction accuracy for elderly LUAD patients of 71-90 years old. A nomogram model was constructed to predict the survival probability, and the C-index value was 0.737, indicating our prognostic nomogram model has high accuracy. Through external RT-qPCR validation, we found that CD79A expression in H1299 was higher than that of BEAS-2B. And novel immunotherapy and chemotherapy regimens were accordingly proposed for the elderly LUAD patients.

Conclusion

We identified a novel gene signature based on seven ARGs for risk stratification, prognosis prediction and benefit evaluation of immunotherapy and chemotherapy in elderly LUAD patients.

A novel iTreg-related signature for prognostic prediction in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Most patients are diagnosed at an advanced stage, therefore it is crucial to identify novel prognostic biomarkers for LUAD. As important regulatory cells, inducible regulatory T cells (iTregs) play a vital role in immune suppression and are important for the maintenance of immune homeostasis. This study explored the prognostic value and therapeutic effects of iTreg-related genes in LUAD. Data for LUAD patients, including immune infiltration data, RNA sequencing data, and clinical features, were acquired from The Cancer Genome Atlas, Gene Expression Omnibus, and Tumor Immune Single-cell Hub 2 databases. Immune-related subgroups with different infiltration patterns and iTreg-related genes were identified through univariate and multivariate Cox regression analyses and weighted correlation network analysis. Functional enrichment analyses were performed to explore the underlying mechanisms of iTreg-related genes. A prognostic risk signature was constructed using Cox regression analysis with the least absolute shrinkage and selection operator penalty. The ESTIMATE algorithm was applied to determine the immune status of LUAD patients. We applied the constructed signature to predict chemosensitivity and performed single-cell RNA sequencing analysis. The infiltration of iTregs was identified as an independent factor for predicting patient outcomes. We constructed a prognostic signature based on seven iTreg-related genes (GIMAP5, SLA, MS4A7, ZNF366, POU2AF1, MRPL12, and COL5A1), which was applied to subdivide patients into high- and low-risk subgroups. Our results revealed that patients in the iTreg-related low-risk subgroup had a better prognosis and possibly greater sensitivity to traditional chemotherapy. Our study provides a novel iTreg-related signature to elucidate the mechanisms underlying LUAD prognosis and promote individualized chemotherapy treatment.

Prognostic and immune correlation analysis of mitochondrial autophagy and aging-related genes in lung adenocarcinoma

PURPOSE

Mitophagy and aging (MiAg) are very important pathophysiological mechanisms contributing to tumorigenesis. MiAg-related genes have prognostic value in lung adenocarcinoma (LUAD). However, prognostic, and immune correlation studies of MiAg-related genes in LUAD are lacking.

METHODS

MiAg differentially expressed genes (DEGs) in LUAD were obtained from public sequencing datasets. A prognostic model including MiAg DEGs was constructed according to patients divided into low- and high-risk groups. Gene Ontology, gene set enrichment analysis, gene set variation analysis, CIBERSORT immune infiltration analysis, and clinical characteristic correlation analyses were performed for functional annotation and correlation of MiAgs with prognosis in patients with LUAD.

RESULTS

Seven MiAg DEGs of LUAD were identified: CAV1, DSG2, DSP, MYH11, NME1, PAICS, PLOD2, and the expression levels of these genes were significantly correlated (P < 0.05). The RiskScore of the MiAg DEG prognostic model demonstrated high predictive ability of overall survival of patients diagnosed with LUAD. Patients with high and low MiAg phenotypic scores exhibited significant differences in the infiltration levels of eight types of immune cells (P < 0.05). The multi-factor DEG regression model showed higher efficacy in predicting 5-year survival than 3- and 1-year survival of patients with LUAD.

CONCLUSIONS

Seven MiAg-related genes were identified to be significantly associated with the prognosis of patients diagnosed with LUAD. Moreover, the identified MiAg DEGs might affect the immunotherapy strategy of patients with LUAD.

Clinical Pathological Characteristics and Prognosis of Multigene Co-Mutations in Elderly Patients With Non-Small Cell Lung Cancer: A Retrospective Analysis

Background

With the development and wide application of next-generation sequencing (NGS), multiple-gene mutations related to lung cancer are detected using this technology. Notably, even multigene concomitant mutations (co-mutations), which occur at a relatively low incidence, can be detected more effectively using NGS. It is well-known that the percentages of non-small cell lung cancer (NSCLC) in the elderly lung cancer population are also gradually increasing, while its prognosis is hard and the quality of long-term survival is poor. This study aimed at investigating the common clinicopathologic features of multigene co-mutations for better evaluating the prognosis of elderly NSCLC patients.

Methods

A total of 464 NSCLC patients were divided into 3 groups according to the types of gene mutation, whose clinical data were retrospectively analyzed.

Results

In total, 38.36% (178/464) of NSCLC patients were in the nonmutation group, 50% in the single-gene mutation group, and 11.64% in the multigene co-mutation group. Nonmutation, single-gene mutation, and co-mutation groups were all prone to occur in male adenocarcinoma patients (P < .05). EGFR gene mutation rates were the highest in the single-gene mutation and co-mutation groups (54.31% and 24.35%). In the co-mutation group, the incidence of EGFR/PIK3CA, LK/KRAS, and EGFR/MET co-mutations was the highest (16.67%, 11.11%, and 7.41%). ALK/HER2/MET, EGFR/HER2/MET, and EGFR/HER2/MET/ROS1 multiple-gene co-mutations were, respectively, found in 1 case, and the multigene co-mutation patients commonly had a worse median progression-free survival (PFS) than that of single-gene mutation (7.13 vs 12.34 months, P = .013).

Conclusion

With the application of NGS, the detectable rates of gene co-mutation are increasingly high in elderly patients with NSCLC, which mainly occurs in male adenocarcinoma patients commonly with poor PFS. It will be critically necessary to conduct multigene detections by NGS for directing targeted therapy of elderly NSCLC patients.

[Preliminary Investigation of the Molecular Mechanism of Empagliflozin Suppressing Gastric Cancer Through Mammalian Target of Rapamycin]

Objective

To predict the intervention targets of empagliflozin (EMPA), a specific inhibitor of sodium-glucose cotransporter 2 (SGLT2), in gastric adenocarcinoma through comprehensive network pharmacology, and to validate the effects and the molecular mechanisms of EMPA through cellular and molecular biology experiments.

Methods

Bioinformatics analysis of gastric adenocarcinoma was conducted to assess the correlation between gastric adenocarcinoma prognosis and SGLT2 expression. Network pharmacology was utilized to identify shared targets of EMPA and gastric adenocarcinoma. AGS cells, a human gastric adenocarcinoma cells line, were incubated with EMPA at different concentrations for 24 h and, then, cell proliferation was assessed using the CCK8 assay. After AGS cells were incubated with EMPA at the doses of 0, 3, and 6 mmol/L, real-time cell analysis (RTCA) and 5-ethynyl-2-deoxyuridine (EdU) incorporation were used to evaluate EMPA's inhibitory effects on the proliferation of the AGS cells. In addition, wound healing and Transwell assays were performed to assess the inhibitory effect of EMPA on the migration and invasion of the APC cells and Western blot analysis was conducted to examine the expression of mammalian target of rapamycin (mTOR) and phosphorylated mTOR (p-mTOR). BALB/c (nu/nu) nude mice were implanted with 5×106 AGS cells in the axilla. The mice were divided into three groups, a control group, a low-dose group, and a high-dose group, each consisting of 7 mice. After one week, the control group received daily intraperitoneal injections of normal saline, while the low-dose group and high-dose group received daily intraperitoneal injections of EMPA at the doses of 3 mg/kg and 5 mg/kg, respectively. The tumor volume was measured one week after the drug intervention started.

Results

Gastric adenocarcinoma patients with low expression of SGLT2 exhibited longer survival time and higher survival rate than those with high expression of SGLT2 did. A total of 104 EMPA-related potential targets and 2028 targets associated with gastric adenocarcinoma were identified. Among these, 45 targets associated with gastric adenocarcinoma overlapped with potential targets of EMPA. Further analysis revealed 10 relevant pathways and 4 core genes. The core genes were cyclin-dependent kinase 4 (CDK4), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), mTOR, and cyclin E1 (CCNE1). CCK-8 assay revealed that EMPA at concentrations ranging from 0.39 to 50 mmol/L effectively inhibited the proliferation of AGS cells. RTCA results indicated a downward shift in the cell growth curve. In comparison to the findings for the control group, EdU assay demonstrated that EMPA at the concentrations of 3 mmol/L and 6 mmol/L significantly inhibited AGS cell proliferation (P<0.05). Results from wound healing and Transwell assays indicated a decrease in the levels of cell migration and invasion (P<0.05) and, notably, there was a significant difference between the high and low-dose EMPA groups (P<0.05). Western blot showed no statistically significant difference in the expression of total mTOR protein between the groups. However, the expression of p-mTOR in the 3 mmol/L and 6 mmol/L EMPA groups decreased compared to that of the control group (P<0.05), with the 6 mmol/L EMPA group exhibiting a more pronounced reduction (P<0.05). Nude mice xenograft tumor experiment demonstrated that, compared to that of the control group, the tumor volumes in the EMPA-treatment groups were significantly reduced (P<0.05), with the high-dose group showing a more pronounced reduction (P<0.05).

Conclusion

EMPA inhibits the abnormal proliferation and migration of gastric adenocarcinoma cells, potentially through the modulation of mTOR protein activation. This study provides new potential medication and intervention targets for gastric adenocarcinoma treatment.

Construction and validation of an efferocytosis-related prognostic signature in lung adenocarcinoma

BACKGROUND

Accumulating evidence highlights the potential significance of efferocytosis in tumor progression. This study is directed towards the construction of a prognostic risk model for lung adenocarcinoma (LUAD), grounded on efferocytosis-related genes (ERGs).

METHODS

Employing LASSO-COX regression analysis, a risk-prognostic model was formulated, centered on seven ERGs. Concurrently, a nomogram was established that incorporated patient clinical features and risk scores. The predictive accuracy of the risk model and the nomogram was substantiated via external validation sets. The landscapes of immune infiltration and genetic mutation were evaluated for high- and low-risk groups, with the expression of seven key genes validated through RT-PCR.

RESULTS

Our findings reveal that the high-risk group displayed considerably inferior survival outcomes in comparison to the low-risk group. A diminished abundance of immune cell infiltrates and a higher prevalence of gene mutations characterized the high-risk group. Genes with high expression were markedly enriched in pathways related to cell proliferation. The superior predictive performance of the risk model and nomogram was adequately substantiated by the external validation sets (GSE31210, GSE30219, and GSE50081). In addition, we discerned several potential therapeutic drugs demonstrating different sensitivities across patient risk groups. The differential expression of seven central genes was confirmed in A549, H1299, and BEAS-2B cell lines.

CONCLUSION

The constructed risk model and nomogram display high accuracy in predicting the survival and immune landscape of LUAD patients, thus providing invaluable prognostic tools in clinical scenarios.

Construction of an aging-related risk signature in high-grade serous ovarian cancer for predicting survival outcome and immunogenicity

Studies have shown that aging significantly impacts tumorigenesis, survival outcome, and treatment efficacy in various tumors, covering high-grade serous ovarian cancer (HGSOC). Therefore, the objective for this investigation is to construct an aging-relevant risk signature for the first time, which will help evaluate the immunogenicity and survival status for patients with HGSOC. Totaling 1727 patients with HGSOC, along with their mRNA genomic data and clinical survival data, were obtained based on 5 independent cohorts. The Lasso-Cox regression model was utilized to identify the aging genes that had the most significant impact on prognosis. The risk signature was developed by integrating the determined gene expression and accordant model weights. Additionally, immunocytes in the microenvironment, signaling pathways, and immune-relevant signatures were assessed based on distinct risk subgroups. Finally, 2 cohorts that underwent treatment with immune checkpoint inhibitor (ICI) were employed to confirm the effects of identified risk signature on ICI efficacy. An aging signature was constructed from 12 relevant genes, which showed improved survival outcomes in low-risk HGSOC patients across discovery and 4 validation cohorts (all P < .05). The low-risk subgroup showed better immunocyte infiltration and higher enrichment of immune pathways and ICI predictors based on further immunology analysis. Notably, in the immunotherapeutic cohorts, low-risk aging signature was observed to link to better immunotherapeutic outcomes and increased response rates. Together, our constructed signature of aging has the potential to assess not only the prognosis outcome and immunogenicity, but also, importantly, the efficacy of ICI treatment. This signature provides valuable insights for prognosis prediction and immunotherapeutic effect evaluation, ultimately promoting individualized treatment for HGSOC patients.

SETBP1 mutation determines sensitivity to immune checkpoint inhibitors in melanoma and NSCLC

SET binding protein 1 (SETBP1) plays crucial roles in various biological processes; however, its involvement in cancer immune checkpoint inhibitor (ICI) treatments has never been studied. In this study, we collected a total of 631 melanoma and 109 non-small cell lung cancer (NSCLC) samples treated with ICI agents (i.e., anti-CTLA-4, anti-PD-1/PD-L1, or combination therapy). Additionally, we obtained their corresponding somatic mutational profiles. We observed that SETBP1 mutated (SETBP1-MUT) melanoma patients exhibited significantly prolonged ICI survival outcomes compared to wild-type patients (HR: 0.56, 95% CI: 0.38-0.81, P = 0.002). Consistently, an elevated ICI response rate was also noticed in the SETBP1-MUT group (42.9% vs. 29.1%, P = 0.016). The Association of SETBP1 mutations with favorable immunotherapeutic prognosis and response was further supported by an independent NSCLC cohort (both P < 0.05). Additional immunological analyses revealed that favorable immune infiltration, tumor immunogenicity, and immune response circuits were enriched in SETBP1-MUT patients. Overall, our findings suggest that SETBP1 mutations may serve as a new biomarker for stratifying beneficiaries of ICI treatments in melanoma and NSCLC, which provides possible evidence for tailoring clinical immunotherapeutic strategies.

Identification and Validation of RELN Mutation as a Response Indicator for Immune Checkpoint Inhibitor Therapy in Melanoma and Non-Small Cell Lung Cancer

Remarkable clinical benefits in several advanced cancers are observed under the treatment of immune checkpoint inhibitor (ICI) agents. However, only a smaller proportion of patients respond to the treatments. Reelin (RELN) is frequently mutated in the cancer genome. In this study, the RELN mutation association with ICI treatment efficacy in melanoma and non-small cell lung cancer (NSCLC) was elucidated. Data from 631 melanoma and 109 NSCLC patients with both ICI treatment data and pre-treatment mutational profiles were collected. In addition, from the Cancer Genome Atlas (TCGA) project, we also obtained both tumors to explore the immunologic features behind RELN mutations. Melanoma patients with RELN mutations exhibited a favorable ICI survival benefit when compared with wild-type patients (HR: 0.66, 95% CI: 0.51-0.87, p = 0.003). A higher response rate was also noticed in RELN-mutated patients (38.9% vs. 28.3%, p = 0.017). The association of RELN mutations with a preferable immunotherapy outcome and response was further confirmed in NSCLC. Further exploration demonstrated that favorable immunocyte infiltration and immune response signaling pathways were found in patients with RELN mutations. In this study, RELN mutations were identified to connect with a better immune microenvironment and an improved ICI efficacy in melanoma and NSCLC, which provides a potential biomarker for immunological feature evaluation and immunotherapeutic outcome prediction at the molecular level.

Identification and Development of an Age-Related Classification and Signature to Predict Prognosis and Immune Landscape in Osteosarcoma

Background. In childhood and adolescence, the prevailing bone tumor is osteosarcoma associated with frequent recurrence and lung metastasis. This research focused on predicting the survival and immune landscape of osteosarcoma by developing a prognostic signature and establishing aging-related genes (ARGs) subtypes. Methods. The training group comprised of the transcriptomic and associated clinical data of 84 patients with osteosarcoma accessed at the TARGET database and the validation group consisted of 53 patients from GSE21257. The aging-related subtypes were identified using unsupervised consensus clustering analysis. The ARG signature was developed utilizing multivariate Cox analysis and LASSO regression. The prognostic value was assessed using the univariate and multivariate Cox analyses, Kaplan-Meier plotter, time-dependent ROC curve, and nomogram. The functional enrichment analyses were performed by GSEA, GO, and KEGG analysis, while the ssGSEA, ESTIMATE, and CIBERSORT analyses were conducted to reveal the immune landscape in osteosarcoma. Results. The two clusters of osteosarcoma patients formed based on 543 ARGs, depicted a considerable difference in the tumor microenvironment, and the overall survival and immune cell infiltration rate varied as well. Among these, the selected 23 ARGs were utilized for the construction of an efficient predictive prognostic signature for the overall survival prediction. The testing in the validation group of osteosarcoma patients confirmed the status of the high-risk score as an independent indicator for poor prognosis, which was already identified as such using the univariate and multivariate Cox analyses. Furthermore, the ARG signature could distinguish different immune-related functions, infiltration status of immune cells, and tumor microenvironment, as well as predict the immunotherapy response of osteosarcoma patients. Conclusion. The aging-related subtypes were identified and a prognostic signature was developed in this research, which determined different prognoses and allowed for treatment of osteosarcoma patients to be tailored. Additionally, the immunotherapeutic response of individuals with osteosarcoma could also be predicted by the ARG signature.

Gene fusions and oncogenic mutations in MLH1 deficient and BRAFV600E wild-type colorectal cancers

Gene fusions can act as oncogenic drivers and offer targets for cancer therapy. Since fusions are rare in colorectal cancer (CRC), their universal screening seems impractical. Our aim was to investigate gene fusions in 62 CRC cases with deficient MLH1 (dMLH1) and BRAFV600E wild-type (wt) status from a consecutive real-life series of 2079 CRCs. First, gene fusions were analysed using a novel FusionPlex Lung v2 RNA-based next-generation sequencing (NGS) panel, and these results were compared to a novel Idylla GeneFusion assay and pan-TRK immunohistochemistry (IHC). NGS detected seven (7/62, 11%) NTRK1 fusions (TPM3::NTRK1, PLEKHA6::NTRK1 and LMNA::NTRK1, each in two cases, and IRF2BP2::NTRK1 in one case). In addition, two ALK, four RET and seven BRAF fusions were identified. Idylla detected seven NTRK1 expression imbalances, in line with the NGS results (overall agreement 100%). Furthermore, Idylla detected the two NGS-identified ALK rearrangements as one specific ALK fusion and one ALK expression imbalance, whilst only two of the four RET fusions were discovered. However, Idylla detected several expression imbalances of ALK (n = 7) and RET (n = 1) that were found to be fusion negative with the NGS. Pan-TRK IHC showed clearly detectable, fusion partner-dependent staining patterns in the seven NTRK1 fusion cases. Overall agreement for pan-TRK antibody clone EPR17341 was 98% and for A7H6R 100% when compared to the NGS. Of the 62 CRCs, 43 were MLH1 promoter hypermethylated (MLH1ph) and 39 were RASwt. All fusion cases were both MLH1ph and RASwt. Our results show that kinase fusions (20/30, 67%) and most importantly targetable NTRK1 fusions (7/30, 23%) are frequent in CRCs with dMLH1/BRAFV600Ewt/MLH1ph/RASwt. NGS was the most comprehensive method in finding the fusions, of which a subset can be screened by Idylla or IHC, provided that the result is confirmed by NGS.