Significance of NKX2-1 as a biomarker for clinical prognosis, immune infiltration, and drug therapy in lung squamous cell carcinoma.

Background: This study was performed to determine the biological processes in which NKX2-1 is involved and thus its role in the development of lung squamous cell carcinoma (LUSC) toward improving the prognosis and treatment of LUSC. Methods: Raw RNA sequencing (RNA-seq) data of LUSC from The Cancer Genome Atlas (TCGA) were used in bioinformatics analysis to characterize NKX2-1 expression levels in tumor and normal tissues. Survival analysis of Kaplan-Meier curve, the time-dependent receiver operating characteristic (ROC) curve, and a nomogram were used to analyze the prognosis value of NKX2-1 for LUSC in terms of overall survival (OS) and progression-free survival (PFS). Then, differentially expressed genes (DEGs) were identified, and Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA) were used to clarify the biological mechanisms potentially involved in the development of LUSC. Moreover, the correlation between the NKX2-1 expression level and tumor mutation burden (TMB), tumor microenvironment (TME), and immune cell infiltration revealed that NKX2-1 participates in the development of LUSC. Finally, we studied the effects of NKX2-1 on drug therapy. To validate the protein and gene expression levels of NKX2-1 in LUSC, we employed immunohistochemistry(IHC) datasets, The Gene Expression Omnibus (GEO) database, and qRT-PCR analysis. Results: NKX2-1 expression levels were significantly lower in LUSC than in normal lung tissue. It significantly differed in gender, stage and N classification. The survival analysis revealed that high expression of NKX2-1 had shorter OS and PFS in LUSC. The multivariate Cox regression hazard model showed the NKX2-1 expression as an independent prognostic factor. Then, the nomogram predicted LUSC prognosis. There are 51 upregulated DEGs and 49 downregulated DEGs in the NKX2-1 high-level groups. GO, KEGG and GSEA analysis revealed that DEGs were enriched in cell cycle and DNA replication.The TME results show that NKX2-1 expression was positively associated with mast cells resting, neutrophils, monocytes, T cells CD4 memory resting, and M2 macrophages but negatively associated with M1 macrophages. The TMB correlated negatively with NKX2-1 expression. The pharmacotherapy had great sensitivity in the NKX2-1 low-level group, the immunotherapy is no significant difference in the NKX2-1 low-level and high-level groups. The analysis of GEO data demonstrated concurrence with TCGA results. IHC revealed NKX2-1 protein expression in tumor tissues of both LUAD and LUSC. Meanwhile qRT-PCR analysis indicated a significantly lower NKX2-1 expression level in LUSC compared to LUAD. These qRT-PCR findings were consistent with co-expression analysis of NKX2-1. Conclusion: We conclude that NKX2-1 is a potential biomarker for prognosis and treatment LUSC. A new insights of NKX2-1 in LUSC is still needed further research.

Immune checkpoint inhibitor (ICI)-based treatment beyond progression with prior immunotherapy in patients with driver-gene negative advanced non-small cell lung cancer.

BACKGROUND: No definite conclusion has yet to be reached for immunotherapy beyond progression(IBP) of first-line immunotherapy as the second-line treatment for advanced NSCLC patients with negative driver genes. Therefore a retrospective study was conducted to evaluate the efficacy of IBP in this population and investigated whether the cycles best response and progressive mode of first-line immunotherapy could affect the results. PATIENTS AND METHODS: The clinical data of patients with advanced NSCLC whose response was evaluated as progressive disease (PD) after receiving a PD-1/PD-L1 inhibitors as first-line therapy were retrospectively collected and the patients were assigned to the IBP and non-IBP groups. The overall survival (OS), progression-free survival (PFS) were evaluated between the two groups. The survival effects of cycles best response and progressive mode of first-line immunotherapy were also evaluated. RESULTS: Between January 2019 and January 2022, a total of 121 patients was evaluated as PD after first-line immunotherapy in our institution; 53 (43.8%) patients were included in the IBP group and 68 (56.2%) patients were included in the non-IBP group. The OS and PFS were no significantly different between the two groups in whole population. Further analysis revealed the OS was prolonged with the prolongation of first-line medication cycle. The median OS was 15.4m (15.4 vs 10.8 p=0.047) 16.1m (16.1 vs 10.8 p=0.039), 16.3m (16.3 vs 10.9 p=0.029) for patients with ≥4, ≥6, ≥8 cycles in first-line immunotherapy, respectively. The advantages of OS and PFS were also seen in the subgroup of PR (best response) and oligo progression of first-line immunotherapy. CONCLUSIONS: The clinical outcomes of IBP were similar to those of non-IBP in patients with PD after first-line immnuotherapy in advanced NSCLC. But more cycles, PR as best response and oligo progression in first-line was benefit.

[3D tumor spheroids promote activation, expansion, and anti-tumor effects of tumor-infiltrating lymphocytes in vitro].

The adoptive immunotherapy mediated by tumor-infiltrating lymphocytes (TILs) has shown definite efficacy against various solid tumors. However, the inefficiency of the conventional method based on in vitro expansion of TILs fails to achieve the cell count and high tumor-killing activity required for therapeutic purposes. This study investigated the effect of 3D tumor spheroids on the activation and expansion of TILs in vitro, aiming to provide a novel approach for the expansion of TILs. We procured TILs and primary tumor cells from surgical samples of lung cancer patients and then compared the impacts of lung cancer cell line NCI-H1975 and primary lung cancer cells cultured under 2D and 3D conditions on the activation, expansion, and anti-tumor activity of TILs. Furthermore, we added the programmed cell death protein 1 (PD-1) antibody into the co-culture of primary tumor cells and TILs within a 3D environment to assess the effects of the antibody on TILs. The results showed that compared with 2D cultured tumor cells, the 3D cultured H1975 cells significantly enhanced the expansion of TILs, increasing the proportion of CD3+/CD8+ cells in TILs to 61.6%. The 3D primary tumor model also enhanced the proportion of CD3+/CD8+ cells in TILs (45.5%, 54.4%), induced apoptosis of tumor epithelial cells and decreased the overall tumor cells survival rate (16.7%) after co-culture. PD-1 antibodies further improved the in vitro expansion capacity of TILs mediated by 3D tumor spheroids, resulting in the proportions of 50.9% and 57.0% for CD3+/CD8+ cells and enhancing the antitumor activity significantly (reducing the overall tumor survival rate to 9.36%). In summary, the use of 3D tumor spheroids significantly promoted the expansion and improved the anti-tumor effect of TILs, and the use of the PD-1 antibody further promoted the expansion and tumor-killing effect of TILs.

Death associated protein kinase 1 predicts the prognosis and the immunotherapy response of various cancers.

BACKGROUND: Death Associated Protein Kinase 1 (DAPK1) is a calcium/calmodulin-dependent serine/threonine kinase, which has been reported to be a tumor suppressor with unbalanced expression in various tissues. However, its function in tumor immunotherapy is still unclear. METHODS: The online GEPIA2 database was used to support TCGA results. We explored the DAPK1 pan-cancer genomic alteration analysis using the cBioPortal web tool. The Human Protein Atlas (HPA) was employed to mine DAPK1 protein information. We verified the expression of DAPK1 in lung adenocarcinoma samples using RT-qPCR. Subsequently, the relationship between the expression of DAPK1 and the clinical stage was analyzed. We used TIMER2.0 as the primary platform for studying DAPK1-related immune cell infiltration. Associations between DAPK1 and immunotherapy biomarkers were analyzed using Spearman correlation analysis. TMB and MSI expression was also examined. Finally, we used Kaplan-Meier Plots to evaluate the relationship between DAPK1 expression and the efficacy of immunotherapy. RESULTS: DAPK1 is aberrantly expressed in most cancer types and has prognostic power in various cancers. Gene mutation was the most common DAPK1 alteration across pan-cancers. The DAPK1 protein was mainly localized to tumor cell centrosomes. DAPK1 was also significantly associated with immune-activated hallmarks, immune cell infiltration, and the expression of immunomodulators. Notably, DAPK1 can also significantly predict responses to anti-PD1 and anti-CTLA-4 therapy in cancer patients. CONCLUSIONS: Our findings suggest that DAPK1 may not only be an effective prognostic factor in cancer patients but may also function as a promising predictive immunotherapy biomarker for cancer patients treated with immune checkpoint inhibitors.

[Advances in Pseudoprogression of Immune Checkpoint Inhibitors 
in Non-small Cell Lung Cancer].

The advent of immune checkpoint inhibitors (ICIs) has greatly improved the prognosis of advanced lung cancer patients, but can lead to pseudoprogression (PsP), which complicates clinical evaluation and management. PsP is manifested as temporary enlargement of the tumour or the appearance of new lesions, etc., and improvement in imaging occurs with continued treatment, mostly without worsening of clinical symptoms. Currently, there are still difficulties in the early diagnosis of PsP, and its occurrence mechanism is not yet clear, lacking good predictive factors and related biomarkers. This article reviews the current research status of PsP of ICIs in non-small cell lung cancer in order to provide helpful clinical strategies for oncologists using these drugs.
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The role of seven tumor-associated autoantibodies in the diagnosis, staging and treatment guidance of lung cancer.

BACKGROUND: This study assessed the diagnosis, staging and treatment guidance of lung cancer (LC) based on seven tumor-associated autoantibodies (TAAbs) -p53, PGP9.5, SOX2, GBU4-5, MAGE A1, CAGE, and GAGE7. METHODS: ELISA was used to determine the TAAb serum levels in 433 patients diagnosed with LC (161 surgical patients) and 76 patients with benign lung disease (16 surgical patients). The statistical characteristic of the TAAbs was compared among patients with different clinicopathological features. Pre- to postoperative changes in TAAb levels were analyzed to determine their value of LC. RESULTS: Among all patients, the positive rate of the seven TAAbs was 23.4%, sensitivity was 26.3%, accuracy was 36.3%, specificity was 93.4%, positive predictive value was 95.8%, and negative predictive value was 18.2%; the positive rate for the LC group (26.3%) was significantly higher than that for the benign group (6.6%; P < 0.001). Significant differences in the positive rate of the seven autoantibodies according to age (P < 0.001), smoking history (P = 0.009) and clinical LC stage (P < 0.001) were found. Smoking was positively associated with the positive of TAAbs (Τ = 0.118, P = 0.008). The positive rates of the seven TAAbs for squamous carcinoma (54.5%), other pathological types (44.4%) and poorly differentiated LC (57.1%) were significantly higher than those for the other types. The positive rate of GBU4-5 was highest among all TAAbs, and the SOX2 level in stage III-IV patients was much higher than that in other stages. For patients undergoing surgery, compared with the preoperative levels, the postoperative levels of the 7 markers, particularly p53 (P = 0.027), PGP9.5 (P = 0.007), GAGE7 (P = 0.014), and GBU4-5 (P = 0.002), were significantly different in the malignant group, especially in stage I-II patients, while no clear pre- to postoperative difference was observed in the benign group. CONCLUSIONS: When the seven TAAbs was positive, it was very helpful for the diagnosis of LC. The 7 TAAbs was valuable for staging and guiding treatment of LC in surgical patients.

Machine learning-based integration develops an immunogenic cell death-derived lncRNA signature for predicting prognosis and immunotherapy response in lung adenocarcinoma.

Accumulating evidence demonstrates that lncRNAs are involved in the regulation of the immune microenvironment and early tumor development. Immunogenic cell death occurs mainly through the release or increase of tumor-associated antigen and tumor-specific antigen, exposing "danger signals" to stimulate the body's immune response. Given the recent development of immunotherapy in lung adenocarcinoma, we explored the role of tumor immunogenic cell death-related lncRNAs in lung adenocarcinoma for prognosis and immunotherapy benefit, which has never been uncovered yet. Based on the lung adenocarcinoma cohorts from the TCGA database and GEO database, the study developed the immunogenic cell death index signature by several machine learning algorithms and then validated the signature for prognosis and immunotherapy benefit of lung adenocarcinoma patients, which had a more stable performance compared with published signatures in predicting the prognosis, and demonstrated predictive value for benefiting from immunotherapy in multiple cohorts of multiple cancers, and also guided the utilization of chemotherapy drugs.

Tenascin C as a novel zinc finger protein 750 target regulating the immunogenicity via DNA damage in lung squamous cell carcinoma.

Modulation of DNA damage repair in lung squamous cell carcinoma (LUSC) can result in the generation of neoantigens and heightened immunogenicity. Therefore, understanding DNA damage repair mechanisms holds significant clinical relevance for identifying targets for immunotherapy and devising therapeutic strategies. Our research has unveiled that the tumor suppressor zinc finger protein 750 (ZNF750) in LUSC binds to the promoter region of tenascin C (TNC), leading to reduced TNC expression. This modulation may impact the malignant behavior of tumor cells and is associated with patient prognosis. Additionally, single-cell RNA sequencing (scRNA-seq) of LUSC tissues has demonstrated an inverse correlation between ZNF750/TNC expression levels and immunogenicity. Manipulation of the ZNF750-TNC axis in vitro within LUSC cells has shown differential sensitivity to CD8+ cells, underscoring its pivotal role in regulating cellular immunogenicity. Further transcriptome sequencing analysis, DNA damage repair assay, and single-strand break analyses have revealed the involvement of the ZNF750-TNC axis in determining the preference for homologous recombination (HR) repair or non-homologous end joining (NHEJ) repair of DNA damage. with involvement of the Hippo/ERK signaling pathway. In summary, this study sheds light on the ZNF750-TNC axis's role in DNA damage repair regulation in LUSC, laying a groundwork for future translational research in immune cell therapy for LUSC.

Integrated single-cell and bulk RNA-Seq analysis enhances prognostic accuracy of PD-1/PD-L1 immunotherapy response in lung adenocarcinoma through necroptotic anoikis gene signatures.

In addition to presenting significant diagnostic and treatment challenges, lung adenocarcinoma (LUAD) is the most common form of lung cancer. Using scRNA-Seq and bulk RNA-Seq data, we identify three genes referred to as HMR, FAM83A, and KRT6A these genes are related to necroptotic anoikis-related gene expression. Initial validation, conducted on the GSE50081 dataset, demonstrated the model's ability to categorize LUAD patients into high-risk and low-risk groups with significant survival differences. This model was further applied to predict responses to PD-1/PD-L1 blockade therapies, utilizing the IMvigor210 and GSE78220 cohorts, and showed strong correlation with patient outcomes, highlighting its potential in personalized immunotherapy. Further, LUAD cell lines were analyzed using quantitative PCR (qPCR) and Western blot analysis to confirm their expression levels, further corroborating the model's relevance in LUAD pathophysiology. The mutation landscape of these genes was also explored, revealing their broad implication in various cancer types through a pan-cancer analysis. The study also delved into molecular subclustering, revealing distinct expression profiles and associations with different survival outcomes, emphasizing the model's utility in precision oncology. Moreover, the diversity of immune cell infiltration, analyzed in relation to the necroptotic anoikis signature, suggested significant implications for immune evasion mechanisms in LUAD. While the findings present a promising stride towards personalized LUAD treatment, especially in immunotherapy, limitations such as the retrospective nature of the datasets and the need for larger sample sizes are acknowledged. Prospective clinical trials and further experimental research are essential to validate these findings and enhance the clinical applicability of our prognostic model.

The effects of anti-lung cancer in nude mice by a fully human single-chain antibody against associated antigen Ts7TMR between A549 cells and Trichinella spiralis.

Lung cancer is a dangerous disease that is lacking in an ideal therapy. Here, we evaluated the anti-lung cancer effect in nude mice of a fully human single-chain antibody (scFv) against the associated antigen 7 transmembrane receptor (Ts7TMR), which is also called G protein-coupled receptor, between A549 cells and Trichinella spiralis (T. spiralis). Our data showed that anti-Ts7TMR scFv could inhibit lung cancer growth in a dose-dependent manner, with a tumour inhibition rate of 59.1%. HE staining did not reveal any obvious tissue damage. Mechanistically, immunohistochemical staining revealed that the scFv down-regulated the expression of PCNA and VEGF in tumour tissues. Overall, this study found that anti-Ts7TMR scFv could inhibit A549 lung cancer growth by suppressing cell proliferation and angiogenesis, which may provide a new strategy for treating lung cancer.

Human lung cancer-derived mesenchymal stem cells promote tumor growth and immunosuppression.

BACKGROUND: The presence of mesenchymal stem cells has been confirmed in some solid tumors where they serve as important components of the tumor microenvironment; however, their role in cancer has not been fully elucidated. The aim of this study was to investigate the functions of mesenchymal stem cells isolated from tumor tissues of patients with non-small cell lung cancer. RESULTS: Human lung cancer-derived mesenchymal stem cells displayed the typical morphology and immunophenotype of mesenchymal stem cells; they were nontumorigenic and capable of undergoing multipotent differentiation. These isolated cells remarkably enhanced tumor growth when incorporated into systems alongside tumor cells in vivo. Importantly, in the presence of mesenchymal stem cells, the ability of peripheral blood mononuclear cell-derived natural killer and activated T cells to mediate tumor cell destruction was significantly compromised. CONCLUSION: Collectively, these data support the notion that human lung cancer-derived mesenchymal stem cells protect tumor cells from immune-mediated destruction by inhibiting the antitumor activities of natural killer and T cells.

Identification and analysis of prognostic immune cell homeostasis characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most invasive malignant tumor of the respiratory system. It is also the common pathological type leading to the death of LUAD. Maintaining the homeostasis of immune cells is an important way for anti-tumor immunotherapy. However, the biological significance of maintaining immune homeostasis and immune therapeutic effect has not been well studied. METHODS: We constructed a diagnostic and prognostic model for LUAD based on B and T cells homeostasis-related genes. Minimum absolute contraction and selection operator (LASSO) analysis and multivariate Cox regression are used to identify the prognostic gene signatures. Based on the overall survival time and survival status of LUAD patients, a 10-gene prognostic model composed of ABL1, BAK1, IKBKB, PPP2R3C, CCNB2, CORO1A, FADD, P2RX7, TNFSF14, and ZC3H8 was subsequently identified as prognostic markers from The Cancer Genome Atlas (TCGA)-LUAD to develop a prognostic signature. This study constructed a gene prognosis model based on gene expression profiles and corresponding survival information through survival analysis, as well as 1-year, 3-year, and 5-year ROC curve analysis. Enrichment analysis attempted to reveal the potential mechanism of action and molecular pathway of prognostic genes. The CIBERSORT algorithm calculated the infiltration degree of 22 immune cells in each sample and compared the difference of immune cell infiltration between high-risk group and low-risk group. At the cellular level, PCR and CKK8 experiments were used to verify the differences in the expression of the constructed 10-gene model and its effects on cell viability, respectively. The experimental results supported the significant biological significance and potential application value of the molecular model in the prognosis of lung cancer. Enrichment analyses showed that these genes were mainly related to lymphocyte homeostasis. CONCLUSION: We identified a novel immune cell homeostasis prognostic signature. Targeting these immune cell homeostasis prognostic genes may be an alternative for LUAD treatment. The reliability of the prediction model was confirmed at bioinformatics level, cellular level, and gene level.

Evaluation of the antitumor effect of neoantigen peptide vaccines derived from the translatome of lung cancer.

Emerging evidence suggests that tumor-specific neoantigens are ideal targets for cancer immunotherapy. However, how to predict tumor neoantigens based on translatome data remains obscure. Through the extraction of ribosome-nascent chain complexes (RNCs) from LLC cells, followed by RNC-mRNA extraction, RNC-mRNA sequencing, and comprehensive bioinformatic analysis, we successfully identified proteins undergoing translatome and exhibiting mutations in the cells. Subsequently, novel antigens identification was analyzed by the interaction between their high affinity and the Major Histocompatibility Complex (MHC). Neoantigens immunogenicity was analyzed by enzyme-linked immunospot assay (ELISpot). Finally, in vivo experiments in mice were conducted to evaluate the antitumor effects of translatome-derived neoantigen peptides on lung cancer. The results showed that ten neoantigen peptides were identified and synthesized by translatome data from LLC cells; 8 out of the 10 neoantigens had strong immunogenicity. The neoantigen peptide vaccine group exhibited significant tumor growth inhibition effect. In conclusion, neoantigen peptide vaccine derived from the translatome of lung cancer exhibited significant tumor growth inhibition effect.

Construction of a prognostic model for extensive-stage small cell lung cancer patients undergoing immune therapy in northernmost China and prediction of treatment efficacy based on response status at different time points.

BACKGROUND AND PURPOSE: Recently, the emergence of immune checkpoint inhibitors has significantly improved the survival of patients with extensive-stage small cell lung cancer. However, not all patients can benefit from immunotherapy; therefore, there is an urgent need for precise predictive markers to screen the population for the benefit of immunotherapy. However, single markers have limited predictive accuracy, so a comprehensive predictive model is needed to better enable precision immunotherapy. The aim of this study was to establish a prognostic model for immunotherapy in ES-SCLC patients using basic clinical characteristics and peripheral hematological indices of the patients, which would provide a strategy for the clinical realization of precision immunotherapy and improve the prognosis of small cell lung cancer patients. METHODS: This research retrospectively collected data from ES-SCLC patients treated with PD-1/PD-L1 inhibitors between March 1, 2019, and October 31, 2022, at Harbin Medical University Cancer Hospital. The study data was randomly split into training and validation sets in a 7:3 ratio. Variables associated with patients' overall survival were screened and modeled by univariate and multivariate Cox regression analyses. Models were presented visually via Nomogram plots. Model discrimination was evaluated by Harrell's C index, tROC, and tAUC. The calibration of the model was assessed by calibration curves. In addition, the clinical utility of the model was assessed using a DCA curve. After calculating the total risk score of patients in the training set, patients were stratified by risk using percentile partitioning. The Kaplan-Meier method was used to plot OS and PFS survival curves for different risk groups and response statuses at different milestone time points. Differences in survival time groups were compared using the chi-square test. Statistical analysis software included R 4.1.2 and SPSS 26. RESULTS: This study included a total of 113 ES-SCLC patients who received immunotherapy, including 79 in the training set and 34 in the validation set. Six variables associated with poorer OS in patients were screened by Cox regression analysis: liver metastasis (P = 0.001), bone metastasis (P = 0.013), NLR < 2.14 (P = 0.005), LIPI assessed as poor (P < 0.001), PNI < 51.03 (P = 0.002), and LDH ≥ 146.5 (P = 0.037). A prognostic model for immunotherapy in ES-SCLC patients was constructed based on the above variables. The Harrell's C-index in the training and validation sets of the model was 0.85 (95% CI 0.76-0.93) and 0.88 (95% CI 0.76-0.99), respectively; the AUC values corresponding to 12, 18, and 24 months in the tROC curves of the training set were 0.745, 0.848, and 0.819 in the training set and 0.858, 0.904 and 0.828 in the validation set; the tAUC curves show that the overall tAUC is > 0.7 and does not fluctuate much over time in both the training and validation sets. The calibration plot demonstrated the good calibration of the model, and the DCA curve indicated that the model had practical clinical applications. Patients in the training set were categorized into low, intermediate, and high risk groups based on their predicted risk scores in the Nomogram graphs. In the training set, 52 patients (66%) died with a median OS of 15.0 months and a median PFS of 7.8 months. Compared with the high-risk group (median OS: 12.3 months), the median OS was significantly longer in the intermediate-risk group (median OS: 24.5 months, HR = 0.47, P = 0.038) and the low-risk group (median OS not reached, HR = 0.14, P = 0.007). And, the median PFS was also significantly prolonged in the intermediate-risk group (median PFS: 12.7 months, HR = 0.45, P = 0.026) and low-risk group (median PFS not reached, HR = 0.12, P = 0.004) compared with the high-risk group (median PFS: 6.2 months). Similar results were obtained in the validation set. In addition, we observed that in real-world ES-SCLC patients, at 6 weeks after immunotherapy, the median OS was significantly longer in responders than in non-responders (median OS: 19.5 months vs. 11.9 months, P = 0.033). Similar results were obtained at 12 weeks (median OS: 20.7 months vs 11.9 months, P = 0.044) and 20 weeks (median OS: 20.7 months vs 11.7 months, P = 0.015). Finally, we found that in the real world, ES-SCLC patients without liver metastasis (P = 0.002), bone metastasis (P = 0.001) and a total number of metastatic organs < 2 (P = 0.002) are more likely to become long-term survivors after receiving immunotherapy. CONCLUSION: This study constructed a new prognostic model based on basic patient clinical characteristics and peripheral blood indices, which can be a good predictor of the prognosis of immunotherapy in ES-SCLC patients; in the real world, the response status at milestone time points (6, 12, and 20 weeks) can be a good indicator of long-term survival in ES-SCLC patients receiving immunotherapy.

Implications of GCLC in prognosis and immunity of lung adenocarcinoma and multi-omics regulation mechanisms.

BACKGROUND: Ferroptosis is an iron-dependent type of regulated cell death, and has been implicated in lung adenocarcinoma (LUAD). Evidence has proved the key role of glutamate-cysteine ligase catalytic subunit (GCLC) in ferroptosis, but its role in LUAD remains unclear. Herein, we explored the implications of GCLC and relevant genes in LUAD prognosis and immunity as well as underlying molecular mechanisms. METHODS: This work gathered mRNA, miRNA, DNA methylation, somatic mutation and copy-number variation data from TCGA-LUAD. WGCNA was utilized for selecting GCLC-relevant genes, and a GCLC-relevant prognostic signature was built by uni- and multivariate-cox regression analyses. Immune compositions were estimated via CIBERSORT, and two immunotherapy cohorts of solid tumors were analyzed. Multi-omics regulatory mechanisms were finally assessed. RESULTS: Our results showed that GCLC was overexpressed in LUAD, and potentially resulted in undesirable survival. A prognostic model was generated, which owned accurate and independent performance in prognostication. GCLC, and relevant genes were notably connected with immune compositions and immune checkpoints. High GCLC expression was linked with better responses to anti-PD-L1 and anti-CTLA-4 treatment. Their possible DNA methylation sites were inferred, e.g., hypomethylation in cg19740353 might contribute to GCLC up-regulation. Frequent genetic mutations also affected their expression. Upstream transcription factors (E2F1/3/4, etc.), post-transcriptional regulation of miRNAs (hsa-mir-30c-1, etc.), lncRNAs (C8orf34-AS1, etc.), and IGF2BP1-mediated m6A modification were identified. It was also found NOP58-mediated SUMOylation post-translational modification. CONCLUSIONS: Together, we show that GCLC and relevant genes exert crucial roles in LUAD prognosis and immunity, and their expression can be controlled by complex multi-omics mechanisms.

Prognostic implications of STK11 with different mutation status and its relationship with tumor-infiltrating immune cells in non-small cell lung cancer.

Background: Mutations in STK11 (STK11Mut) gene may present a negative impact on survival in Non-small Cell Lung Cancer (NSCLC) patients, however, its relationship with immune related genes remains unclear. This study is to unveil whether overexpressed- and mutated-STK11 impact survival in NSCLC and to explore whether immune related genes (IRGs) are involved in STK11 mutations. Methods: 188 NSCLC patients with intact formalin-fixed paraffin-embedded (FFPE) tissue available for detecting STK11 protein expression were included in the analysis. After immunohistochemical detection of STK11 protein, patients were divided into high STK11 expression group (STK11High) and low STK11 expression group (STK11Low), and then Kaplan-Meier survival analysis and COX proportional hazards model were used to compare the overall survival (OS) and progression-free survival (PFS) of the two groups of patients. In addition, the mutation data from the TCGA database was used to categorize the NSCLC population, namely STK11 Mutated (STK11Mut) and wild-type (STK11Wt) subgroups. The difference in OS between STK11Mut and STK11Wt was compared. Finally, bioinformatics analysis was used to compare the differences in IRGs expression between STK11Mut and STK11Wt populations. Results: The median follow-up time was 51.0 months (range 3.0 - 120.0 months) for real-life cohort. At the end of follow-up, 64.36% (121/188) of patients experienced recurrence or metastasis. 64.89% (122/188) of patients ended up in cancer-related death. High expression of STK11 was a significant protective factor for NSCLC patients, both in terms of PFS [HR=0.42, 95% CI= (0.29-0.61), P<0.001] and OS [HR=0.36, 95% CI= (0.25, 0.53), P<0.001], which was consistent with the finding in TCGA cohorts [HR=0.76, 95%CI= (0.65, 0.88), P<0.001 HR=0.76, 95%CI= (0.65, 0.88), P<0.001]. In TCGA cohort, STK11 mutation was a significant risk factor for NSCLC in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) histology in terms of OS [HR=6.81, 95%CI= (2.16, 21.53), P<0.001; HR=1.50, 95%CI= (1.00, 2.26), P=0.051, respectively]. Furthermore, 7 IRGs, namely CALCA, BMP6, S100P, THPO, CGA, PCSK1 and MUC5AC, were found significantly overexpressed in STK11-mutated NSCLC in both LUSC and LUAD histology. Conclusions: Low STK11 expression at protein level and presence of STK11 mutation were associated with poor prognosis in NSCLC, and mutated STK11 might probably alter the expression IRGs profiling.

METTL14 regulates CD8+T-cell activation and immune responses to anti-PD-1 therapy in lung cancer.

BACKGROUND: N6-methyladenosine (m6A) modification plays an important role in lung cancer. However, methyltransferase-like 14 (METTL14), which serves as the main component of the m6A complex, has been less reported to be involved in the immune microenvironment of lung cancer. This study aimed to analyze the relationship between METTL14 and the immune checkpoint inhibitor programmed death receptor 1 (PD-1) in lung cancer. METHODS: CCK-8, colony formation, transwell, wound healing, and flow cytometry assays were performed to explore the role of METTL14 in lung cancer progression in vitro. Furthermore, syngeneic model mice were treated with sh-METTL14 andan anti-PD-1 antibody to observe the effect of METTL14 on immunotherapy. Flow cytometry and immunohistochemical (IHC) staining were used to detect CD8 expression. RIP and MeRIP were performed to assess the relationship between METTL14 and HSD17B6. LLC cells and activated mouse PBMCs were cocultured in vitro to mimic immune cell infiltration in the tumor microenvironment. ELISA was used to detect IFN-γ and TNF-α levels. RESULTS: The online database GEPIA showed that high METTL14 expression indicated a poor prognosis in patients with lung cancer. In vitro assays suggested that METTL14 knockdown suppressed lung cancer progression. In vivo assays revealed that METTL14 knockdown inhibited tumor growth and enhanced the response to PD-1 immunotherapy. Furthermore, METTL14 knockdown enhanced CD8+T-cell activation and infiltration. More importantly, METTL14 knockdown increased the stability of HSD17B6 mRNA by reducing its m6A methylation. In addition, HSD17B6 overexpression promoted the activation of CD8+ T cells. CONCLUSION: The disruption of METTL14 contributed to CD8+T-cell activation and the immunotherapy response to PD-1 via m6A modification of HSD17B6, thereby suppressing lung cancer progression.

Prediction of Prognostic Features Based on Neutrophil-Related Genes for Lung Squamous Cell Carcinoma Reveals Immune Landscape and Drug Candidates.

UNASSIGNED: Background: Since to the prognosis of lung squamous cell carcinoma is generally poor, there is an urgent need to innovate new prognostic biomarkers and therapeutic targets to improve patient outcomes. Objectives: Our goal was to develop a novel multi-gene prognostic model linked to neutrophils for predicting lung squamous cell carcinoma prognosis. Methods: We utilized messenger RNA expression profiles and relevant clinical data of lung squamous cell carcinoma patients from the Cancer Genome Atlas database. Through K-means clustering, least absolute shrinkage and selection operator regression, and univariate/multivariate Cox regression analyses, we identified 12 neutrophil-related genes strongly related to patient survival and constructed a prognostic model. We verified the stability of the model in the Cancer Genome Atlas database and gene expression omnibus validation set, demonstrating the robust predictive performance of the model. Results: Immunoinfiltration analysis revealed remarkably elevated levels of infiltration for natural killer cells resting and monocytes in the high-risk group compared to the low-risk group, while macrophages had considerably lower infiltration in the high risk group. Most immune checkpoint genes, including programmed cell death protein 1 and cytotoxic T-lymphocyte-associated antigen 4, exhibited high expression levels in the high risk group. Tumor immune dysfunction and exclusion scores and immunophenoscore results suggested a potential inclination toward immunotherapy in the "RIC" version V2 revised high risk group. Moreover, prediction results from the CellMiner database revealed great correlations between drug sensitivity (e.g., Vinorelbine and PKI-587) and prognostic genes. Conclusion: Overall, our study established a reliable prognostic risk model that possessed significant value in predicting the overall survival of lung squamous cell carcinoma patients and may guide personalized treatment strategies. (Rev Invest Clin. 2024;76(2):116-31).

Immunotherapy in resectable NSCLC: Answering the question or questioning the answer?

As immunotherapy makes its way into the perioperative setting, a growing number of clinical trials are expanding the evidence base for resectable non-small cell lung cancer (NSCLC) management. Identifying the optimal treatment pattern-whether it's neoadjuvant, adjuvant, or a combination of both-is a crucial next step, particularly in pinpointing which patients benefit the most. This decision-making process requires a multi-disciplinary treatment team capable of utilizing tissue and plasma genomic testing to inform therapeutic choices. Leveraging the perioperative treatment platform, it remains pivotal to integrate circulating tumor DNA (ctDNA) monitoring into clinical trial design efficiently and provide clear guidance on treatment.