A Two-Gene Prognostic Classifier for Early-Stage Lung Squamous Cell Carcinoma in Multiple Large-Scale and Geographically Diverse Cohorts

Study on the regulatory mechanism of luteolin inhibiting WDR72 on the proliferation and metastasis of non small cell lung cancer

Non-small cell lung cancer (NSCLC) is a major cause of cancer-related mortality worldwide. Understanding molecular mechanisms and identifying potential therapeutic targets are crucial for improving treatment outcomes. This study aims to explore the effect of luteolin on NSCLC progression by regulating WDR72 and to investigate the related molecular mechanisms using cellular and animal models. The study employed a comprehensive set of experiments to evaluate the impact of luteolin and WDR72 on NSCLC cell proliferation and metastasis. Techniques included the CCK- 8 assay, colony formation assay, scratch test, and Transwell assay. Molecular docking experiments were performed to validate the binding interaction between luteolin and WDR72. Experimental groups included OE-WDR72, OE-WDR72 + Luteolin, Control, Control + Luteolin, and sh-WDR72. Western blot analysis was used to examine protein expression related to apoptosis, epithelial-mesenchymal transition (EMT), AKT signaling, and other markers. Additionally, a nude mouse subcutaneous tumor model was established to assess the in vivo tumor-forming ability of NSCLC cells under different treatments. Luteolin significantly inhibited the proliferation, invasion, and migration of NSCLC cell lines (H1299 and A549) and reduced tumor formation in nude mice. Molecular docking demonstrated strong binding affinity between luteolin and WDR72. Overexpression of WDR72 promoted NSCLC cell proliferation and migration, while WDR72 silencing showed the opposite effects. Western blot analysis revealed that WDR72 overexpression increased phosphorylated AKT and Bcl- 2 levels while decreasing caspase- 3. In contrast, silencing WDR72 reduced these protein levels. Luteolin treatment in WDR72-overexpressing cells resulted in decreased phosphorylated AKT, increased apoptosis, and suppressed EMT. Tumor transplantation experiments indicated that tumors in the OE-WDR72 group exhibited the fastest growth, while the sh-WDR72 group showed the slowest growth. Luteolin treatment significantly reduced WDR72 expression, suggesting a regulatory role in NSCLC progression. Luteolin effectively inhibits EMT, invasion, and migration of NSCLC cells by modulating WDR72. WDR72 plays a pivotal role in stimulating the proliferation and metastasis of NSCLC cells. By downregulating WDR72, luteolin suppresses NSCLC progression, potentially through modulation of the PI3 K/AKT/EMT signaling pathway. These findings highlight luteolin as a promising therapeutic agent for NSCLC treatment.

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to the treatment of lung squamous cell carcinoma (LUSC). However, there is a lack of optimal predictive models that can accurately forecast patient prognosis and guide the selection of targeted therapies. The extensive multi-omic data obtained from multi-level molecular biology provides a unique perspective for understanding the underlying biological characteristics of cancer, offering potential prognostic indicators and drug sensitivity biomarkers for LUSC patients. We integrated diverse datasets encompassing gene expression, DNA methylation, genomic mutations, and clinical data from LUSC patients to achieve consensus clustering using a suite of 10 multi-omics integration algorithms. Subsequently, we employed 10 commonly used machine learning algorithms, combining them into 101 unique configurations to design an optimal performing model. We then explored the characteristics of high- and low-risk LUSC patient groups in terms of the tumor microenvironment and response to immunotherapy, ultimately validating the functional roles of the model genes through in vitro experiments. Through the application of 10 clustering algorithms, we identified two prognostically relevant subtypes, with CS1 exhibiting a more favorable prognosis. We then constructed a subtype-specific machine learning model, LUSC multi-omics signature (LMS) based on seven key hub genes. Compared to previously published LUSC biomarkers, our LMS score demonstrated superior predictive performance. Patients with lower LMS scores had higher overall survival rates and better responses to immunotherapy. Notably, the high LMS group was more inclined toward "cold" tumors, characterized by immune suppression and exclusion, but drugs like dasatinib may represent promising therapeutic options for these patients. Notably, we also validated the model gene SERPINB13 through cell experiments, confirming its role as a potential oncogene influencing the progression of LUSC and as a promising therapeutic target. Our research provides new insights into refining the molecular classification of LUSC and further optimizing immunotherapy strategies.

Comprehensive Analysis of m6A-Related Programmed Cell Death Genes Unveils a Novel Prognostic Model for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) involves complex dysregulated cellular processes, including programmed cell death (PCD), influenced by N6-methyladenosine (m6A) RNA modification. This study integrates bulk RNA and single-cell sequencing data to identify 43 prognostically valuable m6A-related PCD genes, forming the basis of a 13-gene risk model (m6A-related PCD signature [mPCDS]) developed using machine-learning algorithms, including CoxBoost and SuperPC. The mPCDS demonstrated significant predictive performance across multiple validation datasets. In addition to its prognostic accuracy, mPCDS revealed distinct genomic profiles, pathway activations, associations with the tumour microenvironment and potential for predicting drug sensitivity. Experimental validation identified RCN1 as a potential oncogene driving LUAD progression and a promising therapeutic target. The mPCDS offers a new approach for LUAD risk stratification and personalised treatment strategies.

A Nomogram for Predicting Recurrence in Stage I Non-Small Cell Lung Cancer

BACKGROUND

Early-stage non-small cell lung cancer (NSCLC) is being diagnosed increasingly, and in 30% of diagnosed patients, recurrence will develop within 5 years. Thus, it is urgent to identify recurrence-related markers to optimize the management of patient-tailored therapeutics.

METHODS

The eligible datasets were downloaded from TCGA and GEO. In the discovery phase, two algorithms, least absolute shrinkage and selector operation and support vector machine-recursive feature elimination, were used to identify candidate genes. The recurrence-associated signature was developed by penalized Cox regression. The nomogram was constructed and further tested via other independent cohorts.

RESULTS

In this retrospective study, 14 eligible datasets and 7 published signatures were included. A 13-gene based signature was generated by penalized Cox regression categorized training cohort into high-risk and low-risk subgroups (HR = 8.873, 95% CI: 4.228-18.480 p < 0.001). Furthermore, a nomogram integrating the recurrence-related signature, age, and histology was developed to predict the recurrence-free survival in the training cohort, which performed well in the two external validation cohorts (concordance index: 0.737, 95% CI: 0.732-0.742, p < 0.001; 0.666, 95% CI: 0.650-0.682, p < 0.001; 0.651, 95% CI: 0.637-0.665, p < 0.001, respectively). The nomogram was further performed well in the Jiangsu cohort enrolled 163 patients (HR = 2.723, 95% CI: 1.526-4.859, p = 0.001). Post-operative adjuvant therapy achieved evaluated disease-free survival in high and intermediate risk groups (HR = 4.791, 95% CI: 1.081-21.231, p = 0.039).

CONCLUSIONS

The proposed nomogram is a promising tool for estimating recurrence-free survival in stage I NSCLC, which might have tremendous value in management of early stage NSCLC and guiding adjuvant therapy strategies.

Construction of a prognostic model with CAFs for predicting the prognosis and immunotherapeutic response of lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is one of the subtypes of lung cancer (LC) that contributes to approximately 25%-30% of its prevalence. Cancer-associated fibroblasts (CAFs) are key cellular components of the TME, and the large number of CAFs in tumour tissues creates a favourable environment for tumour development. However, the function of CAFs in the LUSC is complex and uncertain. First, we processed the scRNA-seq data and classified distinct types of CAFs. We also identified prognostic CAFRGs using univariate Cox analysis and conducted survival analysis. Additionally, we assessed immune cell infiltration in CAF clusters using ssGSEA. We developed a model with a significant prognostic correlation and verified the prognostic model. Furthermore, we explored the immune landscape of LUSC and further investigated the correlation between malignant features and LUSC. We identified CAFs and classified them into three categories: iCAFs, mCAFs and apCAFs. The survival analysis showed a significant correlation between apCAFs and iCAFs and LUSC patient prognosis. Kaplan-Meier analysis showed that patients in CAF cluster C showed a better survival probability compared to clusters A and B. In addition, we identified nine significant prognostic CAFRGs (CLDN1, TMX4, ALPL, PTX3, BHLHE40, TNFRSF12A, VKORC1, CST3 and ADD3) and subsequently employed multivariate Cox analysis to develop a signature and validate the model. Lastly, the correlation between CAFRG and malignant features indicates the potential role of CAFRG in promoting tumour angiogenesis, EMT and cell cycle alterations. We constructed a CAF prognostic signature for identifying potential prognostic CAFRGs and predicting the prognosis and immunotherapeutic response for LUSC. Our study may provide a more accurate prognostic assessment and immunotherapy targeting strategies for LUSC.

A four-gene-based methylation signature associated with lymph node metastasis predicts overall survival in lung squamous cell carcinoma

We aimed to identify prognostic methylation genes associated with lymph node metastasis (LNM) in lung squamous cell carcinoma (LUSC). Bioinformatics methods were used to obtain optimal prognostic genes for risk model construction using data from the Cancer Genome Atlas database. ROC curves were adopted to predict the prognostic value of the risk model. Multivariate regression was carried out to identify independent prognostic factors and construct a prognostic nomogram. The differences in overall survival, gene mutation and pathways between high- and low-risk groups were analyzed. Finally, the expression and methylation level of the optimal prognostic genes among different LNM stages were analyzed. FGA, GPR39, RRAD and TINAGL1 were identified as the optimal prognostic genes and were applied to establish a prognostic risk model. Significant differences were found among the different LNM stages. The risk model could predict overall survival, showing a moderate performance with AUC of 0.64-0.68. The model possessed independent prognostic value, and could accurately predict 1-, 3- and 5-year survival. Patients with a high risk score showed poorer survival. Lower gene mutation frequencies and enrichment of leukocyte transendothelial migration and the VEGF signaling pathway in the high-risk group may lead to the poor prognosis. This study identified several specific methylation markers associated with LNM in LUSC and generated a prognostic model to predict overall survival for LUSC patients.

Deciphering a cell death-associated signature for predicting prognosis and response to immunotherapy in lung squamous cell carcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell carcinoma, accounting for about 30% of all lung cancers. Yet, the evaluation of prognostic outcome and therapy response of patients with LUSC remains to be resolved. This study aimed to explore the prognostic value of cell death pathways and develop a cell death-associated signature for predicting prognosis and guiding treatment in LUSC.

METHODS

Transcriptome profiles and corresponding clinical information of LUSC patients were gathered from The Cancer Genome Atlas (TCGA-LUSC, n = 493) and Gene Expression Omnibus database (GSE74777, n = 107). The cell death-related genes including autophagy (n = 348), apoptosis (n = 163), and necrosis (n = 166) were retrieved from the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology databases. In the training cohort (TCGA-LUSC), LASSO Cox regression was used to construct four prognostic signatures of respective autophagy, apoptosis, and necrosis pathway and genes of three pathways. After comparing the four signatures, the cell death index (CDI), the signature of combined genes, was further validated in the GSE74777 dataset. We also investigated the clinical significance of the CDI signature in predicting the immunotherapeutic response of LUSC patients.

RESULTS

The CDI signature was significantly associated with the overall survival of LUSC patients in the training cohort (HR, 2.13; 95% CI, 1.62‒2.82; P < 0.001) and in the validation cohort (HR, 1.94; 95% CI, 1.01‒3.72; P = 0.04). The differentially expressed genes between the high- and low-risk groups contained cell death-associated cytokines and were enriched in immune-associated pathways. We also found a higher infiltration of naive CD4⁺ T cells, monocytes, activated dendritic cells, neutrophils, and lower infiltration of plasma cells and resting memory CD4⁺ T cells in the high-risk group. Tumor stemness indices, mRNAsi and mDNAsi, were both negatively correlated with the risk score of the CDI. Moreover, LUSC patients in the low-risk group are more likely to respond to immunotherapy than those in the high-risk group (P = 0.002).

CONCLUSIONS

This study revealed a reliable cell death-associated signature (CDI) that closely correlated with prognosis and the tumor microenvironment in LUSC, which may assist in predicting the prognosis and response to immunotherapy for patients with LUSC.

mRNA markers associated with malignant pleural effusion

Malignant pleural effusions (MPE) commonly result from malignant tumors and represent advanced-stage cancers. Thus, in clinical practice, early recognition of MPE is valuable. However, the current diagnosis of MPE is based on pleural fluid cytology or histologic analysis of pleural biopsies with a low diagnostic rate. This research aimed to assess the diagnostic ability of eight previously identified Non-Small Cell Lung Cancer (NSCLC)-associated genes for MPE. In the study, eighty-two individuals with pleural effusion were recruited. There were thirty-three patients with MPE and forty-nine patients with benign transudate. mRNA was isolated from the pleural effusion and amplified by Quantitative real-time PCR. The logistic models were further applied to evaluate the diagnostic performance of those genes. Four significant MPE-associated genes were discovered in our study, including Dual-specificity phosphatase 6 (DUSP6), MDM2 proto-oncogene (MDM2), Ring finger protein 4 (RNF4), and WEE1 G2 Checkpoint Kinase (WEE1). Pleural effusion with higher expression levels of MDM2 and WEE1 and lower expression levels of RNF4 and DUSP6 had a higher possibility of being MPE. The four-gene model had an excellent performance distinguishing MPE and benign pleural effusion, especially for pathologically negative effusions. Therefore, the gene combination is a suitable candidate for MPE screening in patients with pleural effusion. We also identified three survival-associated genes, WEE1, Neurofibromin 1 (NF1), and DNA polymerase delta interacting protein 2 (POLDIP2), which could predict the overall survival of patients with MPE.

Benefits from Adjuvant Chemotherapy in Patients with Resected Non-Small Cell Lung Cancer: Possibility of Stratification by Gene Amplification of ACTN4 According to Evaluation of Metastatic Ability

Surgical treatment is the best curative treatment option for patients with non-small cell lung cancer (NSCLC), but some patients have recurrence beyond the surgical margin even after receiving curative surgery. Therefore, therapies with anti-cancer agents also play an important role perioperatively. In this paper, we review the current status of adjuvant chemotherapy in NSCLC and describe promising perioperative therapies, including molecularly targeted therapies and immune checkpoint inhibitors. Previously reported biomarkers of adjuvant chemotherapy for NSCLC are discussed along with their limitations. Adjuvant chemotherapy after resective surgery was most effective in patients with metastatic lesions located just outside the surgical margin; in addition, these metastatic lesions were the most sensitive to adjuvant chemotherapy. Thus, the first step in predicting patients who have sensitivity to adjuvant therapies is to perform a qualified evaluation of metastatic ability using markers such as actinin-4 (ACTN4). In this review, we discuss the potential use of biomarkers in patient stratification for effective adjuvant chemotherapy and, in particular, the use of ACTN4 as a possible biomarker for NSCLC.

L718Q/V mutation in exon 18 of EGFR mediates resistance to osimertinib: clinical features and treatment

Osimertinib, a mutant-specific third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), is emerging as the preferred first-line of treatment for EGFR-mutant lung cancer. However, osimertinib resistance inevitably develops among patients treated with the drug. The modal resistance mechanisms of osimertinib include the occurrence of epithelial transition factor (c-MET) amplification and C797S mutation, whereas rare mutations are presented as case reports. Recently, the L718Q/V mutation in exon 18 of EGFR has been reported to contribute to one of the possible mechanisms of resistance. The clinical features and subsequent treatment strategies for this mutation require further research. This study retrospectively enrolled NSCLC patients with the L718Q/V mutation from 2017 to 2021 at the Cancer Hospital of the University of the Chinese Academy of Sciences (Zhejiang Cancer Hospital), as well as additional patients with the same mutation from PubMed literature, to summarize the clinical features of the mutation. The association between the detection of L718Q/V and resistance to osimertinib, as well as impacts on the therapeutic process and outcome, was analyzed. We included a total of two patients diagnosed at Zhejiang Cancer Hospital and twelve patients from the literature. Of the fourteen total patients, 64.3% were male and 35.7% were female. The average age of the group was 60.2 years (range 45-72). A history of tobacco use was common among the group. In all of the cases we considered, the L718Q/V mutation was secondary to the L858R mutation. The second-generation TKI afatinib was found to provide a high disease control rate (DCR) (85.7%, 6/7) and relatively low objective response rate (ORR) (42/9%, 3/7). The median progression free survival (mPFS) for this treatment reached 2 months (1-6 months). The patients failed to benefit from chemotherapy combined with immunotherapy or other TKI medications. Due to the limited number of cases considered in this study, future studies should explore drugs that more precisely target the L718Q/V mutation of EGFR exon 18.

Identification of metastasis-related long non-coding RNAs in lung cancer through a novel tumor mesenchymal score

Long non-coding RNAs (lncRNAs) have been proven to play critical roles in epithelial-mesenchymal transition (EMT) and metastasis of lung cancer. However, the biological functions and related mechanisms of lncRNAs are unclear. In addition, the EMT-based prognosis prediction in lung cancer still lacks investigation. Here, we established the methodology of identifying critical metastasis-related lncRNAs using comprehensive datasets of cancer transcriptome, genome and epigenome, and also provided tools for prognosis prediction in lung cancer. Initially, important mesenchymal marker genes were identified to compose the tumor mesenchymal score, which predicted patient prognosis in lung cancer, especially lung adenocarcinoma (LUAD). The score was also correlated with several crucial biological and physiological processes, such as tumor immune and hypoxia. Based on the score, lung cancer patients was classified into epithelial and mesenchymal subtypes, and lncRNAs which exhibited expressional dysregulation, promotor methylation alteration and copy number variation between the two subtypes in LUAD were identified and underwent further prognostic analyses. Finally, we identified 14 lncRNAs as EMT-related and significant biomarkers in prognosis prediction of LUAD. As validation, lncRNA RBPMS-AS1 was proven to be co-expressed with epithelial biomarkers, suppressive for A549 cell migration, invasion and EMT, and also significantly associated with better outcomes of LUAD patients, suggesting the potential of RBPMS-AS1 to serve as a lncRNA epithelial biomarker in metastasis of LUAD. Based on the identified lncRNAs, an EMT-linked lncRNA prognostic signature was further established. Taken together, our study provides robust predictive tools, potential lncRNA targets and feasible screening strategies for future study of lung cancer metastasis.

Switched alternative splicing events as attractive features in lung squamous cell carcinoma

Background

Alternative splicing (AS) plays important roles in transcriptome and proteome diversity. Its dysregulation has a close affiliation with oncogenic processes. This study aimed to evaluate AS-based biomarkers by machine learning algorithms for lung squamous cell carcinoma (LUSC) patients.

Method

The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database were utilized. After data composition balancing, Boruta feature selection and Spearman correlation analysis were used for differentially expressed AS events. Random forests and a nested fivefold cross-validation were applied for lymph node metastasis (LNM) classifier building. Random survival forest combined with Cox regression model was performed for a prognostic model, based on which a nomogram was developed. Functional enrichment analysis and Spearman correlation analysis were also conducted to explore underlying mechanisms. The expression of some switch-involved AS events along with parent genes was verified by qRT-PCR with 20 pairs of normal and LUSC tissues.

Results

We found 16 pairs of splicing events from same parent genes which were strongly related to the splicing switch (intrapair correlation coefficient = − 1). Next, we built a reliable LNM classifier based on 13 AS events as well as a nice prognostic model, in which switched AS events behaved prominently. The qRT-PCR presented consistent results with previous bioinformatics analysis, and some AS events like ITIH5-10715-AT and QKI-78404-AT showed remarkable detection efficiency for LUSC.

Conclusion

AS events, especially switched ones from the same parent genes, could provide new insights into the molecular diagnosis and therapeutic drug design of LUSC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02429-2.

ACTN4 gene amplification is a predictive biomarker for adjuvant chemotherapy with UFT in stage I lung adenocarcinomas

Although adjuvant tegafur/uracil (UFT) is recommended for patients with completely resected stage I non‐small‐cell lung cancer (NSCLC) in Japan, only one‐third of cases has received adjuvant chemotherapy (ADJ) according to real‐world data. Therefore, robust predictive biomarkers for selecting ADJ or observation (OBS) without ADJ are needed. Patients who underwent complete resection of stage I lung adenocarcinoma with or without adjuvant UFT were enrolled. The status of ACTN4 gene amplification was analyzed by FISH. Statistical analyses to determine whether the status of ACTN4 gene amplification affected recurrence‐free survival (RFS) were carried out. Formalin‐fixed, paraffin‐embedded samples from 1136 lung adenocarcinomas were submitted for analysis of ACTN4 gene amplification. Ninety‐nine (8.9%) of 1114 cases were positive for ACTN4 gene amplification. In the subgroup analysis of patients aged 65 years or older, the ADJ group had better RFS than the OBS group in the ACTN4‐positive cohort (hazard ratio [HR], 0.084, 95% confidence interval [CI], 0.009‐0.806; P = .032). The difference in RFS between the ADJ group and the OBS group was not significant in ACTN4‐negative cases (all ages: HR, 1.214; 95% CI, 0.848‐1.738; P = .289). Analyses of ACTN4 gene amplification contributed to the decision regarding postoperative ADJ for stage I lung adenocarcinomas, preventing recurrence, improving the quality of medical care, preventing the unnecessary side‐effects of ADJ, and saving medical costs.

A Novel Pyroptosis-Related Gene Signature for Early-Stage Lung Squamous Cell Carcinoma

Background

Diagnosis of early stage lung squamous cell carcinoma (LUSC) has improved; however, a comprehensive analysis of prognostic signatures is needed.

Purpose

To identify, establish, and validate a signature model based on pyroptosis-related genes for prognostic predictions of early stage LUSC.

Patients and Methods

Two independent cohorts were included. RNA-seq transcriptome data from patients with early stage LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Thirty-three pyroptosis-related genes were analyzed between early stage LUSC and normal lung tissues. Cox regression analysis, random survival forest, and least absolute shrinkage and selection operator algorithms established a three-gene signature. Kaplan–Meier survival and receiver-operating characteristic curves assessed the prognostic efficacy of the model. Single-sample gene set enrichment analysis (ssGSEA) assessed the relationship between pyroptosis and immune cells. Patients with early stage LUSC from the GSE74777 dataset were used for validation. Pyroptosis-related genes were verified by RT-qPCR and Western blotting.

Results

Twenty-three differentially expressed pyroptosis-related genes were identified in the LUSC and adjacent normal tissues. Three differentially expressed pyroptosis-related genes were identified as hub genes in early stage LUSC. Patients with early stage LUSC in the TCGA cohort were classified into low- and high-risk subgroups according to the risk score. Overall survival (OS) was significantly short in the high-risk subgroup versus the low-risk subgroup. A similar result was found for the GSE74777 dataset. ssGSEA of immune cells and immune-related pathways between the low- and high-risk subgroups may explain the different OS for patients with early-stage LUSC. IL-6 expression was upregulated, which was inconsistent with the bioinformatic analysis. NOD1 and CASP4 were downregulated in LUSC (all P < 0.05) versus normal lung tissues.

Conclusion

Differentially expressed pyroptosis-related genes may be involved in early stage LUSC. Pyroptosis-related genes are important in tumor immunity and may be potential prognostic predictors for early stage LUSC.

Development of biomarkers for predicting recurrence by determining the metastatic ability of cancer cells

Adjuvant chemotherapy has been carried out for patients with cancer who underwent curative resection, but it is basically not needed for patients without micro-metastatic lesions who undergo a perfectly curative surgical operation. The patients who need adjuvant chemotherapy are defined as those whose micro-metastases cannot be detected by imaging modalities in the other sites of the resective areas, despite curative resection for the primary sites. If biomarkers to efficiently evaluate the metastatic potential of each patient could be developed, we may be able to provide personalized adjuvant chemotherapy in the clinical setting. Actinin-4 (ACTN4, gene name ACTN4) is an actin-bundling protein that we identified in 1998 as a novel molecule involved in cancer invasion and metastasis. Protein overexpression of actinin-4 in cancer cells leads to the invasive phenotype, and patients with gene amplification of ACTN4 have a worse prognosis than patients with a normal copy number in some cancers, including pancreas, lung, and salivary gland cancers. In this review, the biological roles of actinin-4 for cancer invasion and metastasis are summarized, and the potential usefulness of actinin-4 as a biomarker for evaluation of metastatic ability is examined.

Sex-Based Dimorphism of Anticancer Immune Response and Molecular Mechanisms of Immune Evasion

Purpose

We previously demonstrated that sex influences response to immune-checkpoint inhibitors.

Here we investigate sex-based differences in the molecular mechanisms of anticancer immune-response and immune evasion in patients with NSCLC.

Experimental Design

We analyzed a) transcriptome-data of 2575 early-stage NSCLCs from 7 different datasets; b) 327 tumor-samples extensively characterized at the molecular level from the TRACERx lung study; c) two independent cohorts of respectively 329 and 391 patients with advanced NSCLC treated with anti-PD1/anti-PDL1 drugs.

Results

As compared with men, the tumor microenvironment (TME) of women was significantly enriched for a number of innate and adaptive immune cell-types, including specific T-cell subpopulations.

NSCLCs of men and women exploited different mechanisms of immune evasion.

The TME of females was characterized by significantly greater T-cell dysfunction status, higher expression of inhibitory immune-checkpoint molecules and higher abundance of immune-suppressive cells, including Cancer Associated Fibroblasts, MDSCs and Regulatory T-cells.

By contrast, the TME of males was significantly enriched for a T-cells excluded phenotype.

We reported data supporting impaired neoantigens presentation to immune system in tumors of men, as molecular mechanism explaining the findings observed.

Finally, in line with our results, we showed significant sex-based differences in the association between TMB and outcome of patients with advanced NSCLC treated with anti-PD1/PDL1 drugs.

Conclusions

We demonstrated meaningful sex-based differences of anticancer immune response and immune evasion mechanisms, that may be exploited to improve immunotherapy efficacy for both women and men.

The G4 Resolvase DHX36 Possesses a Prognosis Significance and Exerts Tumour Suppressing Function Through Multiple Causal Regulations in Non-Small Cell Lung Cancer

Lung cancer is one of the most prevalent cancers in both men and women worldwide. The nucleic acid G4 structures have been implicated in the transcriptional programmes of cancer-related genes in some cancers such as lung cancer. However, the role of the dominant G4 resolvase DHX36 in the progression of lung cancer remains unknown. In this study, by bioinformatic analysis of public datasets (TCGA and GEO), we find DHX36 is an independent prognosis indicator in non-small-cell lung carcinoma (NSCLC) with subtype dependence. The stable lentiviral knockdown of the DHX36 results in accelerated migration and aggregation of the S-phase subpopulation in lung cancer cells. The reduction of DHX36 level de-sensitises the proliferation response of lung cancer cells to chemotherapeutic drugs such as paclitaxel with cell dependence. The knockdown of this helicase leads to promoted tumour growth, demonstrated by a 3D fluorescence spheroid lung cancer model, and the stimulation of cell colony formation as shown by single-cell cultivation. High throughput proteomic array indicates that DHX36 functions in lung cancer cells through regulating multiple signalling pathways including activation of protein activity, protein autophosphorylation, Fc-receptor signalling pathway, response to peptide hormone and stress-activated protein kinase signalling cascade. A causal transcriptomic analysis suggests that DHX36 is significantly associated with mRNA surveillance, RNA degradation, DNA replication and Myc targets. Therefore, we unveil that DHX36 presents clinical significance and plays a role in tumour suppression in lung cancer, and propose a potentially new concept for an anti-cancer therapy based on helicase-specific targeting.

Proteomic Analyses of Fibroblast- and Serum-Derived Exosomes Identify QSOX1 as a Marker for Non-invasive Detection of Colorectal Cancer

Simple Summary

Early diagnosis of colorectal cancer (CRC) is crucial to improve patient outcomes. The tumour microenvironment immediately adapts to malignant transformations, including the activation of fibroblasts in the connective tissue nearby. In this study, we investigated fibroblast activity-related protein secretion via extracellular vesicles (EVs). QSOX1, a protein identified to be significantly reduced in activated fibroblasts and derived EVs, was also found to be significantly reduced in circulating blood plasma EVs of CRC patients as compared to control patients. Hence, blood plasma EV-associated QSOX1 represents a promising platform for diagnostic CRC screening.

Abstract

The treatment of colorectal cancer (CRC) has improved during the last decades, but methods for crucial early diagnosis are yet to be developed. The influence of the tumour microenvironment on liquid biopsies for early cancer diagnostics are gaining growing interest, especially with emphasis on exosomes (EXO), a subgroup of extracellular vesicles (EVs). In this study, we established paired cancer-associated (CAFs) and normal fibroblasts (NF) from 13 CRC patients and investigated activation status-related protein abundance in derived EXOs. Immunohistochemical staining of matched patient tissue was performed and an independent test cohort of CRC patient plasma-derived EXOs was assessed by ELISA. A total of 11 differentially abundant EV proteins were identified between NFs and CAFs. In plasma EXOs, the CAF-EXO enriched protein EDIL3 was elevated, while the NF-EXO enriched protein QSOX1 was diminished compared to whole plasma. Both markers were significantly reduced in patient-matched CRC tissue compared to healthy colon tissue. In an independent test cohort, a significantly reduced protein abundance of QSOX1 was observed in plasma EXOs from CRC patients compared to controls and diagnostic ROC curve analysis revealed an AUC of 0.904. In conclusion, EXO-associated QSOX1 is a promising novel marker for early diagnosis and non-invasive risk stratification in CRC.

Proteomic Analyses of Fibroblast- and Serum-Derived Exosomes Identify QSOX1 as a Marker for Non-invasive Detection of Colorectal Cancer

The treatment of colorectal cancer (CRC) has improved during the last decades, but methods for crucial early diagnosis are yet to be developed. The influence of the tumour microenvironment on liquid biopsies for early cancer diagnostics are gaining growing interest, especially with emphasis on exosomes (EXO), a subgroup of extracellular vesicles (EVs). In this study, we established paired cancer-associated (CAFs) and normal fibroblasts (NF) from 13 CRC patients and investigated activation status-related protein abundance in derived EXOs. Immunohistochemical staining of matched patient tissue was performed and an independent test cohort of CRC patient plasma-derived EXOs was assessed by ELISA. A total of 11 differentially abundant EV proteins were identified between NFs and CAFs. In plasma EXOs, the CAF-EXO enriched protein EDIL3 was elevated, while the NF-EXO enriched protein QSOX1 was diminished compared to whole plasma. Both markers were significantly reduced in patient-matched CRC tissue compared to healthy colon tissue. In an independent test cohort, a significantly reduced protein abundance of QSOX1 was observed in plasma EXOs from CRC patients compared to controls and diagnostic ROC curve analysis revealed an AUC of 0.904. In conclusion, EXO-associated QSOX1 is a promising novel marker for early diagnosis and non-invasive risk stratification in CRC.

Discovery and Validation of a Metastasis-Related Prognostic and Diagnostic Biomarker for Melanoma Based on Single Cell and Gene Expression Datasets

Background

Single cell sequencing can provide comprehensive information about gene expression in individual tumor cells, which can allow exploration of heterogeneity of malignant melanoma cells and identification of new anticancer therapeutic targets.

Methods

Single cell sequencing of 31 melanoma patients in GSE115978 was downloaded from the Gene Expression Omniniub (GEO) database. First, the limma package in R software was used to identify the differentially expressed metastasis related genes (MRGs). Next, we developed a prognostic MRGs biomarker in the cancer genome atlas (TCGA) by combining univariate cox analysis and the least absolute shrinkage and selection operator (LASSO) method and was further validated in another two independent datasets. The efficiency of MRGs biomarker in diagnosis of melanoma was also evaluated in multiple datasets. The pattern of somatic tumor mutation, immune infiltration, and underlying pathways were further explored. Furthermore, nomograms were constructed and decision curve analyses were also performed to evaluate the clinical usefulness of the nomograms.

Results

In total, 41 MRGs were screened out from 1958 malignant melanoma cell samples in GSE115978. Next, a 5-MRGs prognostic marker was constructed and validated, which show more effective performance for the diagnosis and prognosis of melanoma patients. The nomogram showed good accuracies in predicting 3 and 5 years survival, and the decision curve of nomogram model manifested a higher net benefit than tumor stage and clark level. In addition, melanoma patients can be divided into high and low risk subgroups, which owned differential mutation, immune infiltration, and clinical features. The low risk subgroup suffered from a higher tumor mutation burden (TMB), and higher levels of T cells infiltrating have a significantly longer survival time than the high risk subgroup. Gene Set Enrichment Analysis (GSEA) revealed that the extracellular matrix (ECM) receptor interaction and epithelial mesenchymal transition (EMT) were the most significant upregulated pathways in the high risk group.

Conclusions

We identified a robust MRGs marker based on single cell sequencing and validated in multiple independent cohort studies. Our finding provides a new clinical application for prognostic and diagnostic prediction and finds some potential targets against metastasis of melanoma.

Role of ACTN4 in Tumorigenesis, Metastasis, and EMT

The actin-binding protein ACTN4 belongs to a family of actin-binding proteins and is a non-muscle alpha-actinin that has long been associated with cancer development. Numerous clinical studies showed that changes in ACTN4 gene expression are correlated with aggressiveness, invasion, and metastasis in certain tumors. Amplification of the 19q chromosomal region where the gene is located has also been reported. Experimental manipulations with ACTN4 expression further confirmed its involvement in cell proliferation, motility, and epithelial-mesenchymal transition (EMT). However, both clinical and experimental data suggest that the effects of ACTN4 up- or down-regulation may vary a lot between different types of tumors. Functional studies demonstrated its engagement in a number of cytoplasmic and nuclear processes, ranging from cytoskeleton reorganization to regulation of different signaling pathways. Such a variety of functions may be the reason behind cell type and cell line specific responses. Herein, we will review research progress and controversies regarding the prognostic and functional significance of ACTN4 for tumorigenesis.

Choice of the surgical approach for patients with stage I lung squamous cell carcinoma ≤3 cm

Background

We tried to explore the surgical procedures for stage I squamous cell carcinoma (SCC) with a size of ≤3 cm by using the Surveillance, Epidemiology, and End Results (SEER) database. Furthermore, we investigated the relationships between the chosen surgical option and the size of SCC.

Methods

In total, 1,147 patient data sets were collected from 2010 to 2011 using the SEER database. Afterwards, 849 patients with a pT1-2aN0M0 SCC with a size of ≤3 cm after a lobectomy or sublobectomy procedure were identified. Kaplan-Meier curves were conducted to compare the overall survival (OS) rates and the lung cancer-specific survival (LCSS) rates between the two surgical approaches. Cox proportional hazards regressions were performed to discover the independent risk factors for both the OS and LCSS rates. Lastly, subgroup analysis was stratified by the size of the SCC and then classified by the 8^th edition T category.

Results

The sublobectomy procedure did not demonstrate a difference for the OS rate. Additionally, it demonstrated a worse LCSS rate when compared with a lobectomy for stage I SCC. In the subgroup analysis, a lobectomy was shown to have a better survival outcome only when the SCC was >2 and ≤3 cm. Multivariable analysis showed that a size of >2 to ≤3 cm, and an age of >60 were independently associated with poorer OS while the sublobectomy procedure and pleural invasions (PI) were related with a poorer LCSS rate. In the stratification of data for the tumor size, the cox proportional analysis still confirmed the protective effects of the lobectomy in subgroups of SCCs with sizes between >2 to ≤3 cm as well as the T1c category.

Conclusions

The choice of the SCC surgery can be recommended based on the tumor size. A lobectomy procedure demonstrated a better LCSS against the sublobectomy in stage I SCC. SCC with sizes of >2 to ≤3 cm could become a pretty good indicator for lobectomy, while a sublobectomy may be an adequate substitute when the SCC size is ≤2 cm, especially for patients who cannot tolerate a lobectomy. T1c category can also suggest a lobectomy instead of sublobectomy for stage I SCC patients.

5 protein-based signature for resectable lung squamous cell carcinoma improves the prognostic performance of the TNM staging

INTRODUCTION

Prognostic biomarkers have been very elusive in the lung squamous cell carcinoma (SCC) and none is currently being used in the clinical setting. We aimed to identify and validate the clinical utility of a protein-based prognostic signature to stratify patients with early lung SCC according to their risk of recurrence or death.

METHODS

Patients were staged following the new International Association for the Study of Lung Cancer (IASLC) staging criteria (eighth edition, 2018). Three independent retrospective cohorts of 117, 96 and 105 patients with lung SCC were analysed to develop and validate a prognostic signature based on immunohistochemistry for five proteins.

RESULTS

We identified a five protein-based signature whose prognostic index (PI) was an independent and significant predictor of disease-free survival (DFS) (p<0.001; HR=4.06, 95% CI 2.18 to 7.56) and overall survival (OS) (p=0.004; HR=2.38, 95% CI 1.32 to 4.31). The prognostic capability of PI was confirmed in an external multi-institutional cohort for DFS (p=0.042; HR=2.01, 95% CI 1.03 to 3.94) and for OS (p=0.031; HR=2.29, 95% CI 1.08 to 4.86). Moreover, PI added complementary information to the newly established IASLC TNM 8th edition staging system. A combined prognostic model including both molecular and anatomical (TNM) criteria improved the risk stratification in both cohorts (p<0.05).

CONCLUSION

We have identified and validated a clinically feasible protein-based prognostic model that complements the updated TNM system allowing more accurate risk stratification. This signature may be used as an advantageous tool to improve the clinical management of the patients, allowing the reduction of lung SCC mortality through a more accurate knowledge of the patient's potential outcome.

Actinin-4 protein overexpression as a predictive biomarker in adjuvant chemotherapy for resected lung adenocarcinoma

Aim: Although several clinical trials demonstrated the benefits of platinum-combination adjuvant chemotherapy for stage II–IIIA lung adenocarcinoma, predictive biomarkers for the efficacy of such therapy have not yet been identified. We evaluated protein overexpression of actinin-4 as a predictive biomarker of the efficacy of adjuvant chemotherapy in resected lung adenocarcinoma. Materials & methods: We measured actinin-4 protein levels in patients with completely resected stage II–IIIA lung adenocarcinoma using immunohistochemistry and then retrospectively compared survival between adjuvant chemotherapy and observation groups. Results: A total of 148 eligible patients were classified into actinin-4 positive or negative cases by immunohistochemistry. In the former, patients with adjuvant chemotherapy survived significantly longer than those with observation (hazard ratio [HR]: 0.307; p = 0.028). But, no significant survival benefit was noted with adjuvant chemotherapy (HR: 0.926; p = 0.876) in the latter. Conclusion: This marker could predict the efficacy of adjuvant chemotherapy for resected lung adenocarcinoma patients.