A WIN Consortium phase I study exploring avelumab, palbociclib, and axitinib in advanced non-small cell lung cancer

Significance of novel PANoptosis genes to predict prognosis and therapy effect in the lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the dominant histotype of non-small cell lung cancer. Panoptosis, a comprehensive form of programmed cell death, is central to carcinogenesis. In this study, the expression of PANoptosis-related genes (PRGs) and their impact on the development, prognosis, tumor microenvironment, and treatment response of patients with lung adenocarcinoma (LUAD) were systematically evaluated. PRGs were selected from The Cancer Genome Atlas database and Genecards dataset using differential expression analysis. The signature of included PRGs was identified using univariate Cox regression analysis and LASSO regression analysis. Additionally, a nomogram was developed that includes signature and clinical information. Kaplan-Meier survival analysis and receiver operating characteristic curves were used to assess the predictive validity of these risk models. Finally, functional analysis of the selected PRGs in signature and analysis of immune landscape were also performed. Preliminary identification of 10 genes related to PANoptosis has significant implications for prognosis. Subsequently, seven related genes were integrated to classify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and the TNM stage were as independent prognostic factors and were utilized in creating a nomogram plot. Both the features and the nomogram plot showed accurate performance in predicting the overall survival of LUAD patients. The PRGs were enriched in several biological functions and pathways, and stratified studies were conducted on the differences in immune landscape between high-risk and low-risk groups based on their characteristics. Ultimately, our evaluation focused on the differences in drug treatment efficacy between the high-risk and low-risk groups, providing a foundation for future research directions. Potential associations between PRGs and patient prognosis in LUAD have been identified in this study. Potential biomarkers for clinical application could be considered for the prognostic predictors identified in this study.

CDK4/6 inhibitors promote PARP1 degradation and act synergistically with PARP inhibitors in non-small cell lung cancer

Despite the widespread deregulation of CDK4/6 activity in non-small cell lung cancer (NSCLC), the clinical trials with CDK4/6 inhibitors (CDK4/6is) as a monotherapy have shown poor antitumor activity. However, our preclinical studies have revealed a significant potential for CDK4/6is to collaborate by influencing DNA damage repair pathways during radiotherapy. Given the considerable upregulation of PARP1 expression in NSCLC, we analyzed the efficacy of combined PARP and CDK4/6 inhibition in NSCLC models. Our findings demonstrate that CDK4/6is synergize with PARP inhibitors (PARPis) to inhibit the clonogenic growth of RB-proficient NSCLC models. This synergy is associated with increased accumulation of DNA damage, interrupted cell-cycle checkpoints, and enhanced apoptotic cell death. We showed that CDK4/6is mechanically promote PARP1 protein degradation, leading to decreased availability of DNA repair factors involved in homologous recombination and suppression of DNA repair competency. Furthermore, we showed that PARP trapping is required for this synergy. We then confirmed that combining PARPi and CDK4/6i blocked the growth of NSCLC xenografts in vivo and patient-derived explant models ex vivo. These findings reveal a previously uncharacterized impact of CDK4/6i on PARP1 levels in RB-proficient NSCLC models and the requirement of PARP trapping to render synergy between CDK4/6i and PARPi. Our research suggests that combining CDK4/6i with PARPi could be a promising therapeutic strategy for patients with RB-proficient NSCLC, potentially opening up new and more effective avenues for treatment.

NGEF is a potential prognostic biomarker and could serve as an indicator for immunotherapy and chemotherapy in lung adenocarcinoma

BACKGROUND

Neuronal guanine nucleotide exchange factor (NGEF) plays a key role in several cancers; however, its role in lung adenocarcinoma (LUAD) remains unclear. The aim of this study was to evaluate the efficacy of NGEF as a prognostic biomarker and potential therapeutic target for LUAD.

METHODS

NGEF expression data for multiple cancers and LUAD were downloaded from multiple databases. The high- and low-NGEF expression groups were constructed based on median NGEF expression in LUAD samples, and then performed Kaplan-Meier survival analysis. Differentially expressed genes (DEGs) from the two NGEF expression groups were screened and applied to construct a protein-protein interaction network. The primary pathways were obtained using gene set enrichment analysis. The associations between NGEF expression and clinical characteristics, immune infiltration, immune checkpoint inhibitors (ICIs), sensitivity to chemotherapy, and tumor mutation burden (TMB) were investigated using R. Levels of NGEF expression in the lung tissue was validated using single-cell RNA sequencing, quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blot analysis.

RESULTS

The expression of NGEF mRNA was upregulated in multiple cancers. mRNA and protein expression levels of NGEF were higher in patients with LUAD than in controls, as validated using qPCR and western blot. High NGEF expression was an independent prognostic factor for LUAD and was associated with advanced tumor stage, large tumor size, more lymph node metastasis, and worse overall survival (OS). A total of 182 overlapping DEGs were screened between The Cancer Genome Atlas and GSE31210, among which the top 20 hub genes were identified. NGEF expression was mainly enriched in the pathways of apoptosis, cell cycle, and DNA replication. Moreover, elevated NGEF expression were associated with a high fraction of activated memory CD4+ T cells and M0 macrophages; elevated expression levels of the ICIs: programmed cell death 1 and programmed cell death 1 ligand 1 expression; higher TMB; and better sensitivity to bortezomib, docetaxel, paclitaxel, and parthenolide, but less sensitivity to axitinib and metformin.

CONCLUSION

NGEF expression is upregulated in LUAD and is significantly associated with tumor stages, OS probability, immune infiltration, immunotherapy response, and chemotherapy response. NGEF may be a potential diagnostic and prognostic biomarker and therapeutic target in LUAD.

Emerging therapeutic frontiers in cancer: insights into posttranslational modifications of PD-1/PD-L1 and regulatory pathways

The interaction between programmed cell death ligand 1 (PD-L1), which is expressed on the surface of tumor cells, and programmed cell death 1 (PD-1), which is expressed on T cells, impedes the effective activation of tumor antigen-specific T cells, resulting in the evasion of tumor cells from immune-mediated killing. Blocking the PD-1/PD-L1 signaling pathway has been shown to be effective in preventing tumor immune evasion. PD-1/PD-L1 blocking antibodies have garnered significant attention in recent years within the field of tumor treatments, given the aforementioned mechanism. Furthermore, clinical research has substantiated the efficacy and safety of this immunotherapy across various tumors, offering renewed optimism for patients. However, challenges persist in anti-PD-1/PD-L1 therapies, marked by limited indications and the emergence of drug resistance. Consequently, identifying additional regulatory pathways and molecules associated with PD-1/PD-L1 and implementing judicious combined treatments are imperative for addressing the intricacies of tumor immune mechanisms. This review briefly outlines the structure of the PD-1/PD-L1 molecule, emphasizing the posttranslational modification regulatory mechanisms and related targets. Additionally, a comprehensive overview on the clinical research landscape concerning PD-1/PD-L1 post-translational modifications combined with PD-1/PD-L1 blocking antibodies to enhance outcomes for a broader spectrum of patients is presented based on foundational research.

Uniformly shaped harmonization combines human transcriptomic data from different platforms while retaining their biological properties and differential gene expression patterns

Introduction: Co-normalization of RNA profiles obtained using different experimental platforms and protocols opens avenue for comprehensive comparison of relevant features like differentially expressed genes associated with disease. Currently, most of bioinformatic tools enable normalization in a flexible format that depends on the individual datasets under analysis. Thus, the output data of such normalizations will be poorly compatible with each other. Recently we proposed a new approach to gene expression data normalization termed Shambhala which returns harmonized data in a uniform shape, where every expression profile is transformed into a pre-defined universal format. We previously showed that following shambhalization of human RNA profiles, overall tissue-specific clustering features are strongly retained while platform-specific clustering is dramatically reduced. Methods: Here, we tested Shambhala performance in retention of fold-change gene expression features and other functional characteristics of gene clusters such as pathway activation levels and predicted cancer drug activity scores. Results: Using 6,793 cancer and 11,135 normal tissue gene expression profiles from the literature and experimental datasets, we applied twelve performance criteria for different versions of Shambhala and other methods of transcriptomic harmonization with flexible output data format. Such criteria dealt with the biological type classifiers, hierarchical clustering, correlation/regression properties, stability of drug efficiency scores, and data quality for using machine learning classifiers. Discussion: Shambhala-2 harmonizer demonstrated the best results with the close to 1 correlation and linear regression coefficients for the comparison of training vs validation datasets and more than two times lesser instability for calculation of drug efficiency scores compared to other methods.

CDK4/6 inhibitor palbociclib promotes SARS-CoV-2 cell entry by down-regulating SKP2 dependent ACE2 degradation

Coronavirus disease 2019 (COVID-19) outbreak has become a global pandemic. CDK4/6 inhibitor palbociclib was reported to be one of the top-scored repurposed drugs to treat COVID-19. As the receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry, expression level of angiotensin-converting enzyme 2 (ACE2) is closely related to SARS-CoV-2 infection. In this study, we demonstrated that palbociclib and other methods could arrest cells in G0/G1 phase and up-regulate ACE2 mRNA and protein levels without altering its subcellular localization. Palbociclib inhibited ubiquitin-proteasome and lysosomal degradation of ACE2 through down-regulating S-phase kinase-associated protein 2 (SKP2). In addition, increased ACE2 expression induced by palbociclib and other cell cycle arresting compounds facilitated pseudotyped SARS-CoV-2 infection. This study suggested that ACE2 expression was down-regulated in proliferating cells. Cell cycle arresting compounds could increase ACE2 expression and facilitate SARS-CoV-2 cell entry, which may not be suitable therapeutic agents for the treatment of SARS-CoV-2 infection.

Signature based on RNA-binding protein-related genes for predicting prognosis and guiding therapy in non-small cell lung cancer

Background: Studies have reported that RNA-binding proteins (RBPs) are dysregulated in multiple cancers and are correlated with the progression and prognosis of disease. However, the functions of RBPs in non-small cell lung cancer (NSCLC) remain unclear. The present study aimed to explore the function of RBPs in NSCLC and their prognostic and therapeutic value.

Methods: The mRNA expression profiles, DNA methylation data, gene mutation data, copy number variation data, and corresponding clinical information on NSCLC were downloaded from The Cancer Genome Atlas, Gene Expression Omnibus, and the University of California Santa Cruz Xena databases. The differentially expressed RBPs were identified between tumor and control tissues, and the expression and prognostic value of these RBPs were systemically investigated by bioinformatics analysis. A quantitative polymerase chain reaction (qPCR) was performed to validate the dysregulated genes in the prognostic signature.

Results: A prognostic RBP-related signature was successfully constructed based on eight RBPs represented as a risk score using least absolute shrinkage and selection operator (LASSO) regression analysis. The high-risk group had a worse overall survival (OS) probability than the low-risk group (p < 0.001) with 1-, 3-, and 5-year area under the receiver operator characteristic curve values of 0.671, 0.638, and 0.637, respectively. The risk score was associated with the stage of disease (p < 0.05) and was an independent prognostic factor for NSCLC when adjusted for age and UICC stage (p < 0.001, hazard ratio (HR): 1.888). The constructed nomogram showed a good predictive value. The P53, focal adhesion, and NOD-like receptor signaling pathways were the primary pathways in the high-risk group (adjusted p value <0.05). The high-risk group was correlated with increased immune infiltration (p < 0.05), upregulated relative expression levels of programmed cell death 1 (PD1) (p = 0.015), cytotoxic T-lymphocyte-associated protein 4 (CTLA4) (p = 0.042), higher gene mutation frequency, higher tumor mutational burden (p = 0.034), and better chemotherapy response (p < 0.001). The signature was successfully validated using the GSE26939, GSE31210, GSE30219, and GSE157009 datasets. Dysregulation of these genes in patients with NSCLC was confirmed using the qPCR in an independent cohort (p < 0.05).

Conclusion: An RBP-related signature was successfully constructed to predict prognosis in NSCLC, functioning as a reference for individualized therapy, including immunotherapy and chemotherapy.