Comparing and contrasting predictive biomarkers for immunotherapy and targeted therapy of NSCLC

Characterization of the Different Subtypes of Immune Cell Infiltration to Aid Immunotherapy

Background?PD-1 ablation or PD-L1 specific monoclonal antibody against PD-1 can recruit the accumulation of functional T cells, leading to tumor rejection in the microenvironment and significantly improving the prognosis of various cancers. Despite these unprecedented clinical successes, intervention remission rates remain low after treatment, rarely exceeding 40%. The observation of PD-1/L1 blocking in patients is undoubtedly multifactorial, but the infiltrating degree of CD8+T cell may be an important factor for immunotherapeutic resistance.

Methods:We proposed two computational algorithms to reveal the immune cell infiltration (ICI) landscape of 1646 lung adenocarcinoma patients. Three immune cell infiltration patterns were defined and the relative ICI scoring depended on principal-component analysis.

Results:A high ICI score was associated with the increased tumor mutation burden and cell proliferation-related signaling pathways. Different cellular signaling pathways were observed in low ICI score subtypes, indicating active cell proliferation, and may be associated with poor prognosis.

Conclusion:Our research identified that the ICI scores worked as an effective immunotherapy index, which may provide promising therapeutic strategies on immune therapeutics for lung adenocarcinoma.

Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we find a significant B cell association with extended OS with PD-L1 blockade, independent of CD8⁺ T cell signals. We then derive gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA sequencing (RNA-seq) data. Importantly, we find increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B and plasma cells are also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to the efficacy of PD-L1 blockade in NSCLC.

Immunosuppressive properties of human PD-1 + , PDL-1 + and CD80 + dendritic cells from lymph nodes aspirates of lung cancer patients

Dendritic cells (DCs) play a pivotal role in the homeostasis of the immune system. The tumor microenvironment impairs the proper function of DCs. The immunomodulatory properties of DCs in lung cancer are of interest. In the present study, we analysed DCs subsets and immune cells with the expression of immunomodulatory molecules: PD-1 and PD-L1 and co-stimulatory molecule CD80 in metastatic, non-metastatic lymph nodes (LNs) and peripheral blood (PB). LNs aspirates were obtained during the EBUS/TBNA procedure of 29 patients with primary lung cancer. The cells were analyzed by flow cytometry. We reported a higher percentage of DCs in the metastatic than in the non-metastatic LNs and the PB (0.709% vs. 0.166% vs. 0.043%, p < 0.0001). The proportions of PD-1 + , PD-L1 + and CD80 + DCs were higher in the metastatic LNs than in the non-metastatic ones. A higher proportion of regulatory DCs (DCregs) was found in the metastatic ones than in the non-metastatic LNs (22.5% vs. 3.1%, p = 0.0189). We report that DCs cells show increased expression of PD-1, PD-L1 and CD80 molecules that can interact with T lymphocytes. It can be assumed that mature DCs infiltrating metastatic LNs can develop into DCregs, which are involved in the suppression of anti-tumor response.

Analysis of miR-375-3p, miR-197-3p, and miR-15a-5p Expression and Their Clinical Relevance as Biomarkers in Lung Cancer

Background: MicroRNAs (miRNAs) play an important regulatory role and serve as biomarkers in various human cancers. However, their role in the prognosis and predicting response to therapy in Indian lung cancer patients is not fully explored. Methods: We collected surgically resected tumors and paired adjacent normal lung tissues from 29 early-stage and tissue biopsies from 103 locally advanced and metastatic lung cancer patients in this prospective study. We quantified the expression levels of miR-375-3p, miR-197-3p, and miR-15a-5p using TaqMan Advanced miRNA Assays. We correlated miRNAs expression with response to therapy and survival outcomes. Results: The median age of lung cancer patients was 60 years. We found significant overexpression of miR-375-3p and miR-197-3p in the tumors compared to paired normal lung tissues. Higher expression of miR-375-3p was observed more frequently in responders compared to nonresponders. The expression of miR-375-3p and miR-197-3p was able to differentiate patients of lung adenocarcinoma from lung squamous cell carcinoma. We did not find any correlation between miRNAs expression and survival outcomes. Conclusion: Overexpression of miR-375-3p and miR-197-3p might contribute to lung carcinogenesis. The expression of miR-375-3p may assist in predicting therapeutic response. More prospective studies are warranted to evaluate the potential of miR-375-3p as a predictive biomarker of response to therapy.

Immunotherapy in Lung Cancer: Current Landscape and Future Directions

Over the past decade, lung cancer treatment has undergone a major paradigm shift. A greater understanding of lung cancer biology has led to the development of many effective targeted therapies as well as of immunotherapy. Immune checkpoint inhibitors (ICIs) have shown tremendous benefit in the treatment of non-small cell lung cancer (NSCLC) and are now being used as first-line therapies in metastatic disease, consolidation therapy following chemoradiation in unresectable locally advanced disease, and adjuvant therapy following surgical resection and chemotherapy in resectable disease. Despite these benefits, predicting who will respond to ICIs has proven to be difficult and there remains a need to discover new predictive immunotherapy biomarkers. Furthermore, resistance to ICIs in lung cancer is frequent either because of a lack of response or disease progression after an initial response. The utility of ICIs in the treatment of small cell lung cancer (SCLC) remains limited to first-line treatment of extensive stage disease in combination with chemotherapy with modest impact on overall survival. It is thus important to explore and exploit additional targets to reap the full benefits of immunotherapy in the treatment of lung cancer. Here, we will summarize the current state of immunotherapy in lung cancer, discuss novel targets, and explore the intersection between DNA repair defects and immunotherapy.

Common DNA methylation changes in biliary tract cancers identify subtypes with different immune characteristics and clinical outcomes

BACKGROUND

DNA methylation-associated studies on biliary tract cancer (BTC), including cholangiocarcinoma (CCA) and gallbladder cancer (GBC), may improve the BTC classification scheme. We proposed to identify the shared methylation changes of BTCs and investigate their associations with genomic aberrations, immune characteristics, and survival outcomes.

METHODS

Multi-dimensional data concerning mutation, DNA methylation, immune-related features, and clinical data of 57 CCAs and 48 GBCs from Eastern Hepatobiliary Surgery Hospital (EHSH) and 36 CCAs in the TCGA-CHOL cohort were analyzed.

RESULTS

In our cohort including 24 intrahepatic CCAs (iCCAs), 20 perihilar CCAs (pCCAs), 13 distal CCAs (dCCAs), and 48 GBCs, 3369 common differentially methylated regions (DMRs) were identified by comparing tumor and non-tumor samples. A lower level of methylation changes of these common DMRs was associated with fewer copy number variations, fewer mutational burden, and remarkably longer overall survival (OS, hazard ratio [HR] = 0.07, 95% confidence interval [CI] 0.01-0.65, P = 0.017). Additionally, a 12-marker model was developed and validated for prognostication after curative surgery (HR = 0.21, 95% CI 0.10-0.43, P < 0.001), which exhibited undifferentiated prognostic effects in subgroups defined by anatomic location (iCCAs, d/pCCAs, GBCs), TNM stage, and tumor purity. Its prognostic utility remained significant in multivariable analysis (HR = 0.26, 95% CI 0.11-0.59, P = 0.001). Moreover, the BTCs with minimal methylation changes exhibited higher immune-related signatures, infiltration of CD8⁺ lymphocytes, and programmed death-ligand 1 (PD-L1) expression, indicating an inflamed tumor immune microenvironment (TIME) with PD-L1 expression elicited by immune attack, potentially suggesting better immunotherapy efficacy.

CONCLUSIONS

In BTCs, DNA methylation is a powerful tool for molecular classification, serving as a robust indicator of genomic aberrations, survival outcomes, and tumor immune microenvironment. Our integrative analysis provides insights into the prognostication after curative surgery and patient selection for immunotherapy.

Clinicopathological implications of lncRNAs, immunotherapy and DNA methylation in lung squamous cell carcinoma: a narrative review

Objective

To explore the clinicopathological impact of lncRNAs, immunotherapy, and DNA methylation in lung squamous cell carcinoma (LUSC), emphasizing their exact roles in carcinogenesis and modes of action.

Background

LUSC is the second most prevalent form, accounting for around 30% of non-small cell lung cancer (NSCLC). To date, molecular-targeted treatments have significantly improved overall survival in lung adenocarcinoma patients but have had little effect on LUSC therapy. As a result, there is an urgent need to discover new treatments for LUSC that are based on existing genomic methods.

Methods

In this review, we summarized and analyzed recent research on the biological activities and processes of lncRNA, immunotherapy, and DNA methylation in the formation of LUSC. The relevant studies were retrieved using a thorough search of Pubmed, Web of Science, Science Direct, Google Scholar, and the university's online library, among other sources.

Conclusions

LncRNAs are the primary components of the mammalian transcriptome and are emerging as master regulators of a number of cellular processes, including the cell cycle, differentiation, apoptosis, and growth, and are implicated in the pathogenesis of a variety of cancers, including LUSC. Understanding their role in LUSC in detail may help develop innovative treatment methods and tactics for LUSC. Meanwhile, immunotherapy has transformed the LUSC treatment and is now considered the new standard of care. To get a better knowledge of LUSC biology, it is critical to develop superior modeling systems. Preclinical models, particularly those that resemble human illness by preserving the tumor immune environment, are essential for studying cancer progression and evaluating novel treatment targets. DNA methylation, similarly, is a component of epigenetic alterations that regulate cellular function and contribute to cancer development. By methylating the promoter regions of tumor suppressor genes, abnormal DNA methylation silences their expression. DNA methylation indicators are critical in the early detection of lung cancer, predicting therapy efficacy, and tracking treatment resistance. As such, this review seeks to explore the clinicopathological impact of lncRNAs, immunotherapy, and DNA methylation in LUSC, emphasizing their exact roles in carcinogenesis and modes of action.

Identifying Actionable Variants Using Capture-Based Targeted Sequencing in 563 Patients With Non-Small Cell Lung Carcinoma

Although the NSCLC diagnostic standards recommend the detection of driver gene mutation, comprehensive genomic profiling has not been used widely in clinical practice. As to the different mutation spectrum characteristics between populations, the research based on Chinese NSCLC cohort is very important for clinical practice. Therefore, we collected 563 surgical specimens from patients with non-small cell lung carcinoma and applied capture-based sequencing using eight-gene panel. We identified 556 variants, with 416 potentially actionable variants in 54.88% (309/563) patients. These single nucleotide variants, insertions and deletions were most commonly found in EGFR (55%), followed by ERBB2 (12%), KRAS (11%), PIK3CA (9%), MET (8%), BRAF (7%), DDR2 (2%), NRAS (0.3%). By using ten protein function prediction algorithms, we also identified 30 novel potentially pathogenic variants. Ninety-eight patients harbored EFGR exon 21 p.L858R mutation and the catalytic domain of the protein tyrosine kinase (PTKc) in EGFR is largely mutated. In addition, there were nine frequent pathogenic variants found in five or more patients. This data provides the potential molecular basis for directing the treatment of lung cancer.

Dysregulated transient receptor potential channel 1 expression and its correlation with clinical features and survival profile in surgical non-small-cell lung cancer patients

BACKGROUND

Transient receptor potential channel 1 (TRPC1) facilitates the tumor growth, metastasis, and chemoresistance in a series of neoplasms, while its correlation with clinical features and survival profile in NSCLC patients remains elusive. Hence, this study aimed to explore this topic.

METHODS

Totally, 192 NSCLC patients were enrolled. Protein and mRNA expression of TRPC1 in carcinoma tissue and para-carcinoma tissue were evaluated by immunohistochemistry (IHC) assay and reverse transcription quantitative polymerase chain reaction (RT-qPCR) assay, respectively.

RESULTS

Immunohistochemistry score and mRNA expression of TRPC1 were higher in carcinoma tissue compared with para-carcinoma tissue (both p < 0.001). Besides, increased TRPC1 IHC score (p = 0.004) and elevated TRPC1 mRNA overexpression (p = 0.016) were linked with occurrence of LYN metastasis; meanwhile, increased TRPC1 IHC score (p = 0.015) and raised TRPC1 mRNA expression (p = 0.009) were also linked with advanced TNM stage, whereas TRPC1 IHC score and TRPC1 mRNA expression were not correlated with other clinical features (all p > 0.05). Additionally, TRPC1 protein high (p = 0.007) and TRPC1 mRNA high (p = 0.015) were correlated with poor disease-free survival (DFS) but not correlated with overall survival (OS). Moreover, multivariate Cox's proportional hazards regression analysis showed that high TRPC1 protein expression (p = 0.046) and advanced TNM stage (p < 0.001) were independently correlated with poor DFS. However, TRPC1 protein and mRNA expression were not linked with OS (both p > 0.05), while poor differentiation (p = 0.003) and advanced TNM stage (p < 0.001) were independently associated with worse OS.

CONCLUSIONS

TRPC1 is unregulated in NSCLC tissue with its overexpression relating to the occurrence of LYN metastasis and worse DFS in NSCLC patients.

Predictive biomarkers for response to immune checkpoint inhibition

Immune checkpoint inhibitors have transformed the prognosis and treatment paradigm of many cancer types, through the potential for durable responses. However, the majority of patients still do not benefit. Response to checkpoint inhibition is determined by dynamic host, tumour and tumour microenvironment factors that display spatial and temporal variability, but our understanding of these interactions is incomplete. Through investigating biomarkers of resistance and response, opportunities arise to discover new therapeutic targets and shape personalised treatment strategies. Here we review approved and emerging biomarkers of response to immune checkpoint inhibitors, in particular the recent rapid progress in host and tumour genomics. It is unlikely that a single biomarker will precisely predict response, but multivariate multiomic markers may provide a balanced assessment of these factors and more accurately identify patients who will benefit. Further efforts are required to translate these groundbreaking discoveries into novel therapeutics and biomarker driven clinical trials, to provide durable treatment response to a greater population of patients.

A short-term follow-up CT based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer

To develop a short-term follow-up CT-based radiomics approach to predict response to immunotherapy in advanced non-small-cell lung cancer (NSCLC) and investigate the prognostic value of radiomics features in predicting progression-free survival (PFS) and overall survival (OS). We first retrospectively collected 224 advanced NSCLC patients from two centers, and divided them into a primary cohort and two validation cohorts respectively. Then, we processed CT scans with a series of image preprocessing techniques namely, tumor segmentation, image resampling, feature extraction and normalization. To select the optimal features, we applied the feature ranking with recursive feature elimination method. After resampling the training dataset with a synthetic minority oversampling technique, we applied the support vector machine classifier to build a machine-learning-based classification model to predict response to immunotherapy. Finally, we used Kaplan-Meier (KM) survival analysis method to evaluate prognostic value of rad-score generated by CT-radiomics model. In two validation cohorts, the delta-radiomics model significantly improved the area under receiver operating characteristic curve from 0.64 and 0.52 to 0.82 and 0.87, respectively (P < .05). In sub-group analysis, pre- and delta-radiomics model yielded higher performance for adenocarcinoma (ADC) patients than squamous cell carcinoma (SCC) patients. Through the KM survival analysis, the rad-score of delta-radiomics model had a significant prognostic for PFS and OS in validation cohorts (P < .05). Our results demonstrated that (1) delta-radiomics model could improve the prediction performance, (2) radiomics model performed better on ADC patients than SCC patients, (3) delta-radiomics model had prognostic values in predicting PFS and OS of NSCLC patients.

CircFOXP1: A novel serum diagnostic biomarker for non-small cell lung cancer

Background

Emerging evidence suggests that circular RNAs (circRNAs) were aberrantly expressed in the patients of non-small cell lung cancer (NSCLC). This study aims to evaluate the diagnostic value of potential serum biomarker in circRNAs.

Methods

Serum circRNAs were extracted and purified by RNA isolated kit and identified by quantitative real time-polymerase chain reaction (qRT-PCR) assay. We then performed a receiver operating characteristic (ROC) curve to estimate the diagnostic efficacy. The relationship between circRNA and clinic characteristics of patients was analyzed by SPSS 25.0. Univariate and multivariate analyses were also used to evaluate its diagnostic capability. The mechanism of circFOXP1 was further excavated by bioinformatics analysis.

Results

By performing qRT-PCR assay, we identified that circFOXP1 (hsa_circ_0008234) and conventional tumor markers (carcinoembryonic antigen (CEA) and cytokeratin fragment 21–1 (CYFRA21-1)) were all significantly overexpressed in the serum of patients with NSCLC when compared with healthy controls ( P < 0.05). While the ROC curves analysis demonstrated that area under the curve of circFOXP1 was obviously superior to CEA and CYFRA21-1, which exerted more diagnostic advantage. Univariate and multivariate analyses revealed that serum circFOXP1 was an independent diagnostic molecule, and was significantly correlated with T stage and lymphatic metastasis in NSCLC ( P < 0.05). Mechanistically, circFOXP1 might target hsa-miR-370-3p and hsa-miR-18a-5p, and be involved in vascular endothelial growth factor signaling pathways to regulate proliferative and metastasis processes.

Conclusion

Our results highlight the preferable diagnostic potential of serum circFOXP1 in NSCLC.

Prognosis and Immunotherapy Response With a Novel Golgi Apparatus Signature-Based Formula in Lung Adenocarcinoma

The Golgi apparatus (GA) is a cellular organelle that participates in the packaging, modification, and transport of proteins and lipids from the endoplasmic reticulum to be further fabricated before being presented to other cellular components. Recent studies have demonstrated that GA facilitates numerous cellular processes in cancer development. Therefore, this study aimed to establish a novel lung adenocarcinoma (LUAD) risk evaluation model based on GA gene signatures. In this study, we used TCGA-LUAD (n = 500) as the training cohort and GSE50081 (n = 127), GSE68465 (442), and GSE72094 (398) as the validation cohorts. Two immunotherapy datasets (GSE135222 and GSE126044) were also obtained from a previous study. Based on machine algorithms and bioinformatics methods, a GA gene-related risk score (GARS) was established. We found that the GARS independently predicted the prognosis of LUAD patients and remained effective across stages IA to IIIA. Then, we identified that the GARS was highly correlated with mutations in P53 and TTN. Further, this study identified that GARS is related to multiple immune microenvironmental characteristics. Furthermore, we investigated GSE135222 and GSE126044 and found that a lower GARS may be indicative of an improved therapeutic effect of PD-1/PD-L1 therapy. We also found that high GARS may lead to a better response to multiple anticancer drugs. Finally, we established a nomogram to better guide clinical application. To our knowledge, this is the first study to demonstrate a novel GA signature-based risk score formula to predict clinical prognosis and guide the treatment of LUAD patients.

Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer: Progress, Challenges, and Prospects

Non-small cell lung cancer is one of the most common types of malignances worldwide and the main cause of cancer-related deaths. Current treatment for NSCLC is based on surgical resection, chemotherapy, radiotherapy, and targeted therapy, with poor therapeutic effectiveness. In recent years, immune checkpoint inhibitors have applied in NSCLC treatment. A large number of experimental studies have shown that immune checkpoint inhibitors are safer and more effective than traditional therapeutic modalities and have allowed for the development of better guidance in the clinical treatment of advanced NSCLC patients. In this review, we describe clinical trials using ICI immunotherapies for NSCLC treatment, the available data on clinical efficacy, and the emerging evidence regarding biomarkers.

Polymorphonuclear Myeloid-Derived Suppressor Cells Are Abundant in Peripheral Blood of Cancer Patients and Suppress Natural Killer Cell Anti-Tumor Activity

Tumor microenvironment (TME) includes a wide variety of cell types and soluble factors capable of suppressing immune-responses. While the role of NK cells in TME has been analyzed, limited information is available on the presence and the effect of polymorphonuclear (PMN) myeloid-derived suppressor cells, (MDSC). Among the immunomodulatory cells present in TME, MDSC are potentially efficient in counteracting the anti-tumor activity of several effector cells. We show that PMN-MDSC are present in high numbers in the PB of patients with primary or metastatic lung tumor. Their frequency correlated with the overall survival of patients. In addition, it inversely correlated with low frequencies of NK cells both in the PB and in tumor lesions. Moreover, such NK cells displayed an impaired anti-tumor activity, even those isolated from PB. The compromised function of NK cells was consequent to their interaction with PMN-MDSC. Indeed, we show that the expression of major activating NK receptors, the NK cytolytic activity and the cytokine production were inhibited upon co-culture with PMN-MDSC through both cell-to-cell contact and soluble factors. In this context, we show that exosomes derived from PMN-MDSC are responsible of a significant immunosuppressive effect on NK cell-mediated anti-tumor activity. Our data may provide a novel useful tool to implement the tumor immunoscore. Indeed, the detection of PMN-MDSC in the PB may be of prognostic value, providing clues on the presence and extension of both adult and pediatric tumors and information on the efficacy not only of immune response but also of immunotherapy and, possibly, on the clinical outcome.

Reflex testing in non-small cell lung carcinoma using DNA- and RNA-based next-generation sequencing-a single-center experience

Background

Targeted treatment modalities for non-small cell lung carcinoma (NSCLC) patients are expanding rapidly and demand a constant adaptation of molecular testing strategies. In this regard, broad reflex testing via next-generation sequencing (NGS) might have several advantages. However, real-world data regarding practical feasibility and clinical relevance are scarce, especially for RNA-based NGS.

Methods

We performed a retrospective study comparing NGS use in two consecutive years (2019 and 2020). In 2019, reflex testing mainly consisted of DNA-based NGS for mutations and immunohistochemistry (IHC) for ALK, ROS1, and NTRK fusion products. At the beginning of 2020, our approach has changed, with DNA- and RNA-based NGS panels now being simultaneously performed. This change in protocol allowed us to retrospectively evaluate if broad molecular reflex testing brings additional value to lung cancer patients.

Results

Within the whole cohort (n=432), both DNA- and RNA-based NGS yielded almost always evaluable results. Only in 6 cases, the RNA content was too little for an appropriate analysis. After integrating RNA-based NGS in the reflex testing approach, the number of detected fusions increased significantly (2.6% vs. 8.2%; P=0.0021), but also more patients received targeted therapies. Furthermore, exceedingly rare alterations were more likely to be detected, including the so far undescribed EGFR-NUP160 fusion.

Conclusions

Our study demonstrates that a comprehensive approach to reflex NGS testing is practically feasible and clinically relevant. Including RNA-based panels in the reflex testing approach results in more detected fusions and more patients receiving targeted therapies. Additionally, this broad molecular profiling strategy identifies patients with emerging biomarkers, underscoring its usefulness in the rapidly evolving landscape of targeted therapies.

Predictive value of TCR Vβ-Jβ profile for adjuvant gefitinib in EGFR mutant NSCLC from ADJUVANT-CTONG 1104 trial

Herein, we characterize the landscape and prognostic significance of the T cell receptor (TCR) repertoire of early-stage non-small cell lung cancer (NSCLC) for patients with an epidermal growth factor receptor (EGFR) mutation. β Chain TCR sequencing was used to characterize the TCR repertoires of paraffin-preserved pretreatment tumor and tumor-adjacent tissues from 57 and 44 patients with stage II/III NSCLC with an EGFR mutation treated with gefitinib or chemotherapy in the ADJUVANT-CTONG 1104 trial. The TCR diversity was significantly decreased in patients with an EGFR mutation, and patients with high TCR diversity had a favorable overall survival (OS). A total of 10 TCR Vβ-Jβ rearrangements were significantly associated with OS. Patients with a higher frequency of Vβ5-6Jβ2-1, Vβ20-1Jβ2-1, Vβ24-1Jβ2-1, and Vβ29-1Jβ2-7 had significantly longer OS. Weighted combinations of the 4 TCRs were significantly associated with OS and disease-free survival (DFS) of patients, which could further stratify the high and low TCR diversity groups. Importantly, Vβ5-6Jβ2-1, Vβ20-1Jβ2-1, and Vβ24-1Jβ2-1 had a significant relationship with gefitinib treatment, while Vβ29-1Jβ2-7 was associated with chemotherapy. Four TCR Vβ-Jβ rearrangements related to favorable OS and DFS for adjuvant gefitinib and chemotherapy in patients with an EGFR mutation with stage II/III NSCLC; this may provide a novel perspective for the adjuvant setting for resectable NSCLC.

Study on PD-L1 Expression in NSCLC Patients and Related Influencing Factors in the Real World

PD-L1 is one of the current biomarkers for immune checkpoint inhibitor (ICI) therapy in patients with non-small-cell lung cancer. However, the expression of PD-L1 in the real world and its related influencing factors remain unclear. We want to observe the expression of PD-L1 in the real world and study the related influencing factors through the collection and analysis of clinical data. R software (version 4.0) was used to perform data analysis and the “corplot” package for correlation analysis. A total of 296 individuals (mean [SD] age, 67 [9] years; 23%female) were assessed. According to the expression amount of PD-L1, the cohort was divided into low nonexpression group (PD‐L1 < 1%, 26.7%), low-expression group (1% ≤ PD‐L1 < 50%, 49.3%), and high-expression group (PD‐L1 ≥ 50%, 23.5%). Age, gender, underlying diseases, smoking status, and PD-L1 expression level were not statistically significant. We found that the expression of PD-L1 was correlated with serum albumin (P < 0.05) and pathological type (P < 0.05) and had a negative correlation with EGFR mutation but did not correlate with gender, age, smoking status, combined with underlying diseases, tumor stage, whether it was initially treated or not, sampling site, specimen type, specimen storage time, R-IFN, CD4, CD8, NLR, CRP, and LDH. The present findings indicated that serum albumin, pathological type, and EGFR mutations are associated with PD-L1 expression in patients with NSCLC, which may provide a new basis for individualized immunotherapy and need further study to confirm. The results of this study help to further reveal the actual expression of PD-L1 in non-small-cell lung cancer patients with real events.

Case Report: Significant Clinical Benefit From Pemetrexed-Based Therapy in ROS1- and ALK-rearranged Lung Cancer With Adenosquamous Histology

Pemetrexed (used as a platinum doublet or as a maintenance regimen) is an established therapy for patients with advanced non-squamous non-small-cell lung cancer (NSCLC). In addition, certain gene rearrangements (e.g., ALK, ROS1, RET) appear to especially benefit from the use of pemetrexed. Inferior outcomes with pemetrexed compared to other chemotherapies in patients with NSCLC demonstrating squamous histology removed these patients from the labeled indication for the drug. While most squamous cases do not harbor driver oncogenes, rare exceptions exist. Whether the poor outcomes with pemetrexed extend to NSCLC with squamous component harboring driver oncogenes remains unexplored. In this case series, we describe two patients with adenosquamous histology harboring an ROS1 and ALK gene arrangement, respectively, who derived significant benefit from pemetrexed-based therapy. These cases suggest that the value of pemetrexed may need to be re-explored in adenosquamous NSCLC harboring such alterations.

circRNA LDLRAD3 Enhances the Malignant Behaviors of NSCLC Cells via the miR-20a-5p-SLC7A5 Axis Activating the mTORC1 Signaling Pathway

Circular RNA LDLRAD3 behaved as an oncogene in several malignancies, but its effects in NSCLC and the involvement of downstream molecules and activation of signaling pathways had not been fully reported. We planned to explore how LDLRAD3 facilitated the malignancy of NSCLC. QRT-PCR was performed to evaluate the expression levels of LDLRAD3, miR-20a-5p, and SLC7A5 in NSCLC tissues and cells. si-LDLRAD3 was transfected to A549 and H1299 cells to knock down intrinsic LDLRAD3 to determine its oncogenic roles. CCK-8 assay and transwell assay were executed to assess cell proliferative, migrative, and invasive abilities. Dual-luciferase reporter (DLR) assay was manipulated to verify the ENCORI-predicted relationships between LDLRAD3 and miR-20a-5p and between miR-20a-5p and SLC7A5. Western blot, immunofluorescent assay, and immunohistochemistry were applied to explore the expression levels of SLC7A5, and the levels of mTORC1 pathway-related proteins were evaluated using western blot. Rescue experiments were conducted by transfecting si-LDLRAD3, miR-20a-5p inhibitor, and si-SLC7A5 to explore the influence of the LDLRAD3-miR-20a-5p-SLC7A5 axis on the malignant behaviors of NSCLC cells. The expression levels of LDLRAD3 and SLC7A5 were boosted, whereas miR-20a-5p was impeded in NSCLC tissues and cell lines. Knockdown of LDLRAD3 weakened the proliferation, migration, and invasion of A549 and H1299 cells. LDLRAD3 was verified to sponge miR-20a-5p and miR-20a-5p targeted SLC7A5. LDLRAD3 activated the mTORC1 singling pathway via the miR-20a-5p-SLC7A5 axis to strengthen the malignant properties of A549 and H1299 cells. We concluded that LDLRAD3 exerted oncogenic effects via the miR-20a-5p-SLC7A5 axis to activate the mTORC1 signaling pathway in NSCLC. Our findings enlightened that LDLRAD3 could become a potential therapeutic target in the treatment and management of NSCLC.

DOK5 as a Prognostic Biomarker of Gastric Cancer Immunoinvasion: A Bioinformatics Analysis

Background

Docking protein 5 (DOK5) is a member of the docking protein group of membrane proteins and is an adapter protein involved in signal transduction. Nevertheless, the role of DOK5 expression in the prognosis of gastric cancer (GC) remains unclear.

Methods

In this study, clinical prognostic parameters and survival data related to DOK5, in patients with GC, were analyzed using bioinformatics analysis comprising Oncomine and TIMER, UALCAN database, Kaplan-Meier plotter, GEPIA, GSEA, DAVID, and cBioPortal websites.

Results

In our study, GC contained various DOK5 expressions, which forecasted poor survival outcomes. Moreover, our research showed that high DOK5 could predict high-level infiltration of several GC immune cells, as evidenced by M1, TAM, M2, B cell, and T cell failure. Hence, DOK5 might become a new gastric cancer biomarker and therapeutic target. In the following analysis, in order to explore the prognostic value of DOK5 in GC, more clinical trials are needed to validate our results.

Conclusions

Through multiple database verifications, DOK5 was found to be part of the pathogenic genes for GC. Thus, it can change the formation and progression of tumors by acting on human immunity.

The effect of neoadjuvant therapy on PD-L1 expression and CD8+lymphocyte density in non-small cell lung cancer

PD-L1 expression is the routine clinical biomarker for the selection of patients to receive immunotherapy in non-small cell lung cancer (NSCLC). However, the application and best timing of immunotherapy in the resectable setting is still under investigation. We aimed to study the effect of chemotherapy on PD-L1 expression and tumor infiltrating lymphocytes (TILs), which is to date still poorly understood. Our retrospective, single-centre neoadjuvant cohort comprised 96 consecutive patients with NSCLC resected 2000-2016 after neoadjuvant therapy, including paired diagnostic chemo-naïve specimens in 53 cases. A biologically matched surgical cohort of 114 primary resected cases was included. PD-L1 expression, CD8 + TILs density and tertiary lymphoid structures were assessed on whole slides and correlated with clinico-pathological characteristics and survival. Seven/53 and 12/53 cases had lower respectively higher PD-L1 expressions after neoadjuvant therapy. Most cases (n = 34) showed no changes in PD-L1 expression, the majority of these harboring PD-L1 < 1% in both samples (21/34 [61.8%]). Although CD8 + TILs density was significantly higher after chemotherapy (p = 0.031) in resections compared to diagnostic biopsies, this might be due to sampling and statistical bias. No difference in PD-L1 expression or CD8 + TILs density was detected when comparing the neoadjuvant and surgical cohort. In univariable analyses, higher CD8 + TILs density, higher numbers of tertiary lymphoid structures but not PD-L1 expression were significantly associated with longer survival. Increased PD-L1 expression after neoadjuvant chemotherapy was not significantly associated with shorter 5-year survival, but the number of cases was very low. In multivariable analysis, only pT category and age remained independent prognostic factors. In summary, PD-L1 expression was mostly unchanged after neoadjuvant chemotherapy compared to diagnostic biopsies. The sample size of cases with changed PD-L1 expression was too small to draw conclusions on any prognostic value.

Single-Cell Digital Microfluidic Mass Spectrometry Platform for Efficient and Multiplex Genotyping of Circulating Tumor Cells

Gene mutation profiling of heterogeneous circulating tumor cells (CTCs) offers comprehensive and real-time molecular information of tumors for targeted therapy guidance, but the lack of efficient and multiplex genotyping techniques for single-CTC analysis greatly hinders its development and clinical application. This paper reports a single-CTC mass spectrometry analysis method for efficient and multiplex mutation profiling based on digital microfluidics. Digital microfluidics affords integrated single-CTC manipulation, from single-CTC isolation to high-performance whole genome amplification, via nanoliter droplet-based wettability trapping and hydrodynamic adjustment of cell distribution. Coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, multiplex mutation information of individual CTCs can be efficiently and accurately identified by the inherent mass differences of different DNA sequences. This platform achieves Kirsten rat sarcoma viral oncogene mutation profiling of heterogeneous CTCs at the single-cell level from cancer patient samples, offering new avenues for genotype profiling of single CTCs and cancer therapy guidance.

A Multi-Omics Network of a Seven-Gene Prognostic Signature for Non-Small Cell Lung Cancer

There is an unmet clinical need to identify patients with early-stage non-small cell lung cancer (NSCLC) who are likely to develop recurrence and to predict their therapeutic responses. Our previous study developed a qRT-PCR-based seven-gene microfluidic assay to predict the recurrence risk and the clinical benefits of chemotherapy. This study showed it was feasible to apply this seven-gene panel in RNA sequencing profiles of The Cancer Genome Atlas (TCGA) NSCLC patients (n = 923) in randomly partitioned feasibility-training and validation sets (p < 0.05, Kaplan-Meier analysis). Using Boolean implication networks, DNA copy number variation-mediated transcriptional regulatory network of the seven-gene signature was identified in multiple NSCLC cohorts (n = 371). The multi-omics network genes, including PD-L1, were significantly correlated with immune infiltration and drug response to 10 commonly used drugs for treating NSCLC. ZNF71 protein expression was positively correlated with epithelial markers and was negatively correlated with mesenchymal markers in NSCLC cell lines in Western blots. PI3K was identified as a relevant pathway of proliferation networks involving ZNF71 and its isoforms formulated with CRISPR-Cas9 and RNA interference (RNAi) profiles. Based on the gene expression of the multi-omics network, repositioning drugs were identified for NSCLC treatment.

Case Report: Sequential Combination Targeted Therapy With Type I and II MET Inhibitors in a Metastatic EGFR-Mutated, MET-Amplified NSCLC Patient With Acquired MET Y1230H Mutation

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are the standard of care for advanced non-small-cell lung cancer (NSCLC) patients. However, most patients will eventually develop resistance. For EGFR-TKI resistance mediated by MET amplification, the combination of EGFR and MET TKIs has shown promising results in early clinical trials. However, acquired resistance to MET inhibitors forms a formidable challenge to this dual blockade approach. Here, we presented an NSCLC patient with EGFR exon 19 deletion (ex19del) who was resistant to first-line erlotinib treatment but responded to chemotherapy. Given the finding of MET overexpression/amplification after disease progression, the patient received gefitinib plus crizotinib with a partial response. Her disease progressed again, and molecular testing revealed a novel MET Y1230H mutation and a PD-L1 TPS score of 75%. She received a salvage regime consisting of gefitinib, cabozantinib, and pembrolizumab with a partial response. Since we now know that EGFR ex19del NSCLC patients generally do not respond to PD-1 blockade therapy, this response is more likely the contribution from gefitinib plus cabozantinib. Therefore, sequential use of type I and II MET inhibitors in EGFR/MET dual blockade may be an effective therapeutic option for EGFR-mutant, MET-amplified NSCLC.

Comparative study on the efficacy and exposure of molecular target agents in non-small cell lung cancer PDX models with driver genetic alterations

Patient-derived xenografts (PDXs) can adequately reflect clinical drug efficacy. However, the methods for evaluating drug efficacy are not fully established. We selected five non-small cell lung cancer (NSCLC) PDXs with genetic alterations from established PDXs and the corresponding molecular targeted therapy was administered orally for 21 consecutive days. Genetic analysis, measurement of drug concentrations in blood and tumors using liquid chromatography and tandem mass spectrometry, and analysis of drug distribution in tumors using matrix-assisted laser desorption/ionization mass spectrometry were performed. Fifteen (20%) PDXs were established using samples collected from 76 NSCLC patients with genetic alterations. The genetic alterations observed in original patients were largely maintained in PDXs. We compared the drug efficacy in original patients and PDX models; the efficacies against certain PDXs correlated with the clinical effects, while those against the others did not. We determined blood and intratumor concentrations in the PDX model, but both concentrations were low, and no evident correlation with the drug efficacy could be observed. The intratumoral spatial distribution of the drugs was both homogeneous and heterogeneous for each drug, and the distribution was independent of the expression of the target protein. The evaluation of drug efficacy in PDXs enabled partial reproduction of the therapeutic effect in original patients. A more detailed analysis of systemic and intratumoral pharmacokinetics may help clarify the mode of action of drugs. Further development of evaluation methods and indices to improve the prediction accuracy of clinical efficacy is warranted.

Multi-omics analysis of an immune-based prognostic predictor in non-small cell lung cancer

BACKGROUND

Inhibitors targeting immune checkpoints, such as PD-1/PD-L1 and CTLA-4, have prolonged survival in small groups of non-small cell lung cancer (NSCLC) patients, but biomarkers predictive of the response to the immune checkpoint inhibitors (ICIs) remain rare.

METHODS

The nonnegative matrix factorization (NMF) was performed for TCGA-NSCLC tumor samples based on the LM22 immune signature to construct subgroups. Characterization of NMF subgroups involved the single sample gene set variation analysis (ssGSVA), and mutation/copy number alteration and methylation analyses. Construction of RNA interaction network was based on the identification of differentially expressed RNAs (DERs). The prognostic predictor was constructed by a LASSO-Cox regression model. Four GEO datasets were used for the validation analysis.

RESULTS

Four immune based NMF subgroups among NSCLC patients were identified. Genetic and epigenetic analyses between subgroups revealed an important role of somatic copy number alterations in determining the immune checkpoint expression on specific immune cells. Seven hub genes were recognized in the regulatory network closely related to the immune phenotype, and a three-gene prognosis predictor was constructed.

CONCLUSIONS

Our study established an immune-based prognosis predictor, which might have the potential to select subgroups benefiting from the ICI treatment, for NSCLC patients using publicly available databases.

Identification of the ferroptosis-related long non-coding RNAs signature to improve the prognosis prediction and immunotherapy response in patients with NSCLC

BACKGROUND

Non-small cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with an unfavorable prognosis. Ferroptosis is involved in the development of multiple cancers. Whereas, the prognostic value of ferroptosis-related lncRNAs in NSCLC remains uncertain.

METHODS

Gene expression profiles and clinical information of NSCLC were retrieved from the TCGA database. Ferroptosis-related genes (FRGs) were explored in the FerrDb database and previous studies, ferroptosis-related lncRNAs (FRGs-lncRNAs) were identified by the correlation analysis and the LncTarD database. The differentially expressed FRGs-lncRNAs were screened and FRGs-lncRNAs associated with the prognosis were explored by univariate Cox regression analysis and Kaplan-Meier survival analysis. Then, an FRGs-lncRNAs signature was constructed and verified by the Lasso-penalized Cox analysis. Finally, the potential correlation between risk score, immune checkpoint genes, and chemotherapeutic sensitivity was further investigated.

RESULTS

129 lncRNAs with a potential regulatory relationship with 59 differentially expressed FRGs were found in NSCLC, of which 10 were related to the prognosis of NSCLC (P < 0.05). 9 prognostic-related FRGs-lncRNAs were used to construct the prognostic model and stratify NSCLC patients into high- and low-risk groups. A worse outcome was found in patients with high risk (P < 0.05). Moreover, a good predictive capacity of this signature in predicting NSCLC prognosis was confirmed. Additionally, 45 immune checkpoint genes and 4 chemotherapeutics drugs for NSCLC were identified to be correlated with the risk score.

CONCLUSION

A novel FRGs-lncRNAs signature was successfully constructed, which may contribute to improving the management strategies of NSCLC.

Therapeutic advances in non-small cell lung cancer: Focus on clinical development of targeted therapy and immunotherapy

Lung cancer still contributes to nearly one-quarter cancer-related deaths in the past decades, despite the rapid development of targeted therapy and immunotherapy in non-small cell lung cancer (NSCLC). The development and availability of comprehensive genomic profiling make the classification of NSCLC more precise and personalized. Most treatment decisions of advanced-stage NSCLC have been made based on the genetic features and PD-L1 expression of patients. For the past 2 years, more than 10 therapeutic strategies have been approved as first-line treatment for certain subgroups of NSCLC. However, some major challenges remain, including drug resistance and low rate of overall survival. Therefore, we discuss and review the therapeutic strategies of NSCLC, and focus on the development of targeted therapy and immunotherapy in advanced-stage NSCLC. Based on the latest guidelines, we provide an updated summary on the standard treatment for NSCLC. At last, we discussed several potential therapies for NSCLC. The development of new drugs and combination therapies both provide promising therapeutic effects on NSCLC.

Gene expression signatures as candidate biomarkers of response to PD-1 blockade in non-small cell lung cancers

Although anti-PD-1/PD-L1 monotherapy has achieved clinical success in non-small cell lung cancer (NSCLC), definitive predictive biomarkers remain to be elucidated. In this study, we performed whole-transcriptome sequencing of pretreatment tumor tissue samples and pretreatment and on-treatment whole blood samples (WB) samples obtained from a clinically annotated cohort of NSCLC patients (n = 40) treated with nivolumab (anti-PD-1) monotherapy. Using a single-sample gene set enrichment scoring method, we found that the tumors of responders with lung adenocarcinoma (LUAD, n = 20) are inherently immunogenic to promote antitumor immunity, whereas those with lung squamous cell carcinoma (LUSC, n = 18) have a less immunosuppressive tumor microenvironment. These findings suggested that nivolumab may function as a molecular targeted agent in LUAD and as an immunomodulating agent in LUSC. In addition, our study explains why the reliability of PD-L1 expression on tumor cells as a predictive biomarker for the response to nivolumab monotherapy is quite different between LUAD and LUSC.

Prognostic model of lung adenocarcinoma constructed by the CENPA complex genes is closely related to immune infiltration

BACKGROUND

Lung adenocarcinoma (LUAD) is still one of the primary malignant diseases leading to higher mortality worldwide. It has been previously reported that multiple genes in the CENPA-nucleosome associated complex (NAC) complex in lung cancer can be used as prognostic markers; however, there is lack of comprehensive research on the CENPA-NAC complex.

METHODS

The hub genes of lung cancer were obtained by analyzing multiple gene expression omnibus (GEO) lung cancer datasets. The key genes of the CENPA-NAC complex in the evolution of LUAD were identified according to lung cancer data obtained from The Cancer Genome Atlas (TCGA) database, and the key genes were constructed as a survival prognostic model. The relationship between the model and immune cell infiltration was studied by the Tumor Immune Estimation Resource (TIMER) and single-sample gene set enrichment analysis (ssGSEA) studies.Droplet Digital polymerase chain reaction (ddPCR) was used to verify the effectiveness of the prognostic model to predict survival using clinical samples.

RESULTS

A comprehensive study showed that CENPA, CENPH, CENPM, CENPN and CENPU were key genes in the development and evolution of LUAD. The constructed survival prognosis model was an independent risk factor for LUAD and can be used to assess the survival of LUAD patients. The risk score was closely related to the infiltration of multiple immune cells. The independent cohorts GSE31210 and GSE50081 further confirmed the validity of the prognostic model, and finally, the model was validated with clinical samples.

CONCLUSIONS

In conclusion, the results of the present study showed that CENPA, CENPH, CENPM, CENPN, and CENPU are a group of potential prognostic markers in LUAD. The constructed model has been confirmed to be applicable in the clinical setting in evaluating the survival of patients with LUAD, and providing more evidence on immunotherapy for LUAD.

SPTBN2, a New Biomarker of Lung Adenocarcinoma

Objectives

The roles played by β-III-spectrin, also known as spectrin beta, non-erythrocytic 2 (SPTBN2), in the occurrence and development of lung adenocarcinoma (LUAD) have not been previously examined. Our study aimed to reveal the relationship between the SPTBN2 expression and LUAD.

Materials and Methods

Twenty pairs of LUAD tissues and adjacent tissues were collected from patients diagnosed and treated at the Thoracic Surgery Department of The First Affiliated Hospital of Zhengzhou University from July 2019 to September 2020. RNA sequencing (RNA-seq) analysis determined that the expression of SPTBN2 was higher in LUAD samples than in adjacent normal tissues. The expression levels of SPTBN2 were examined in various databases, including the Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA). The Search Tool for the Retrieval of Interacting Genes (STRING) online website was used to examine protein–protein interactions involving SPTBN2, and the results were visualized by Cytoscape software. The Molecular Complex Detection (MCODE) plug-in for Cytoscape software was used to identify functional modules of the obtained protein–protein interaction (PPI) network. Gene enrichment analysis was performed, and survival analysis was conducted using the Kaplan–Meier plotter. The online prediction website TargetScan was used to predict SPTBN2-targeted miRNA sequences by searching for SPTBN2 sequences. Finally, we verified the expression of SPTBN2 in the obtained tissue samples using real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). The human lung cancer cell lines A549 and H1299 were selected for the transfection of small interfering RNA (siRNA) targeting SPTBN2 (si-SPTBN2), and the knockdown efficiency was evaluated by RT-qPCR. The cellular proliferation, migration, and invasion capacities of A549 and H1299 cells were determined using the cell counting kit-8 (CCK-8) proliferation assay; the wound-healing assay and the Transwell migration assay; and the Matrigel invasion assay, respectively.

Results

The expression of SPTBN2 in non–small cell lung cancer (NSCLC) ranked 13th among cancer cell lines based on the CCLE database. At the mRNA and protein levels, the expression levels of SPTBN2 were higher in LUAD tissues than in normal lung tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that proteins related to SPTBN2 were enriched in apoptotic and phagosomal pathways. Kaplan–Meier survival analysis revealed that SPTBN2 expression was significantly related to the prognosis of patients with LUAD. The TargetScan database verified that miR-16 was a negative regulator of SPTBN2 mRNA expression. The results of the CCK-8 cell proliferation assay revealed that SPTBN2 knockdown significantly inhibited the cell proliferation abilities of A549 and H1299 cells. The wound-healing assay indicated that SPTBN2 knockdown resulted in reduced migration after 48 h compared with the control group. The Transwell migration and invasion test revealed that the migration and invasion abilities were greatly decreased by SPTBN2 knockdown compared with control conditions.

Conclusion

We uncovered a novel gene, SPTBN2, that was significantly upregulated in LUAD tissues relative to normal tissue expression. SPTBN2 is highly expressed in LUAD, positively correlated with poor prognosis, and can promote the proliferation, migration, and invasion of LUAD cells.

USP5 facilitates non-small cell lung cancer progression through stabilization of PD-L1

PD-L1(CD274) is a well-known immunosuppressive molecule, which confers immunoescape features to cancer cells and has become one of the major targets in cancer immunotherapies. Understanding the regulatory mechanisms that control PD-L1 protein expression is important for guiding immune checkpoint blockade therapy. Here, we showed that ubiquitin specific peptidase 5 (USP5) was a novel PD-L1 deubiquitinase in non-small cell lung cancer (NSCLC) cells. USP5 directly interacted with PD-L1 and deubiquitinated PD-L1, therefore enhances PD-L1 protein stability. Meanwhile, USP5 protein levels were highly elevated and positively correlated to PD-L1 levels in NSCLC tissues, and were closely correlated with poor prognosis of these patients. In addition, knockdown of USP5 retarded tumor growth in the Lewis lung carcinoma mouse model. Thus, we identified that USP5 was a new regulator of PD-L1 and targeting USP5 is a promising strategy for cancer therapy.

Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms

Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.

Real-world performance of blood-based proteomic profiling in first-line immunotherapy treatment in advanced stage non-small cell lung cancer

Purpose

Immune checkpoint inhibition (ICI) therapy has improved patient outcomes in advanced non-small cell lung cancer (NSCLC), but better biomarkers are needed. A clinically validated, blood-based proteomic test, or host immune classifier (HIC), was assessed for its ability to predict ICI therapy outcomes in this real-world, prospectively designed, observational study.

Materials and methods

The prospectively designed, observational registry study INSIGHT (Clinical Effectiveness Assessment of VeriStrat® Testing and Validation of Immunotherapy Tests in NSCLC Subjects) (NCT03289780) includes 35 US sites having enrolled over 3570 NSCLC patients at any stage and line of therapy. After enrolment and prior to therapy initiation, all patients are tested and designated HIC-Hot (HIC-H) or HIC-Cold (HIC-C). A prespecified interim analysis was performed after 1-year follow-up with the first 2000 enrolled patients. We report the overall survival (OS) of patients with advanced stage (IIIB and IV) NSCLC treated in the first-line (ICI-containing therapies n=284; all first-line therapies n=877), by treatment type and in HIC-defined subgroups.

Results

OS for HIC-H patients was longer than OS for HIC-C patients across treatment regimens, including ICI. For patients treated with all ICI regimens, median OS was not reached (95% CI 15.4 to undefined months) for HIC-H (n=196) vs 5.0 months (95% CI 2.9 to 6.4) for HIC-C patients (n=88); HR=0.38 (95% CI 0.27 to 0.53), p<0.0001. For ICI monotherapy, OS was 16.8 vs 2.8 months (HR=0.36 (95% CI 0.22 to 0.58), p<0.0001) and for ICI with chemotherapy OS was unreached vs 6.4 months (HR=0.41 (95% CI 0.26 to 0.67), p=0.0003). HIC results were independent of programmed death ligand 1 (PD-L1). In a subgroup with PD-L1 ≥50% and performance status 0–1, HIC stratified survival significantly for ICI monotherapy but not ICI with chemotherapy.

Conclusion

Blood-based HIC proteomic testing provides clinically meaningful information for immunotherapy treatment decision in NSCLC independent of PD-L1. The data suggest that HIC-C patients should not be treated with ICI alone regardless of their PD-L1 expression.

High DSCC1 Level Predicts Poor Prognosis of Lung Adenocarcinoma

Purpose

To evaluate the role of DSCC1 in LUAD.

Patients and Methods

Based on TCGA and GTEx, the Wilcoxon rank-sum test was used to compare the expression differences of DSCC1 between the normal samples of GTEx combined TCGA and the unpaired tumor samples of TCGA, and to compare DSCC1 expression values between tumor tissues and paired normal LUAD tissues in the TCGA cohort. Kruskal–Wallis rank-sum test, Wilcoxon rank-sum test, and logistics regression were used to compare the relationship between the expression of DSCC1 and the clinicopathological parameters. The biological function of DSCC1 was annotated by GSEA and ssGSEA, while Kaplan–Meier and Cox regression analysis were used to evaluate the prognostic value of DSCC1. Furthermore, the time-dependent ROC curve was used to analyze the diagnostic efficacy of DSCC1 in LUAD.

Results

We downloaded the RNA-Seq data of 513 LUAD cases. The expression of DSCC1 was significantly correlated with T stage (OR = 1.04(1.02–1.07), P = 0.002), pathological stage (OR=1.03 (1.01–1.05), P = 0.008) and TP53 status (OR=1.10 (1.07–1.14), P < 0.001). The high expression of DSCC1 was significantly correlated with DSS (HR=1.56 (1.07–2.26), P = 0.021) and OS (HR=1.53 (1.14–2.05), P = 0.004). Moreover, ROC curve analysis (AUC=0.845, CI (0.820-0.870)) indicated DSCC1 as a potential diagnostic molecule for LUAD. In the group with high DSCC1 expression phenotype, down-regulation of EGFR signal, reduction of IL-6 deprivation, cell cycle, and p53 signal pathway were significantly abundant. Spearman correlation analysis showed that the expression of DSCC1 was positively correlated with the infiltration of Th2 cells, T Helper cells.

Conclusion

Our results suggest that DSCC1 may be an important biomarker for the treatment of LUAD.

Response to toripalimab combined with radiotherapy in advanced non-small cell lung cancer-not otherwise specified: A case report

RATIONALE

The targeting of signal transduction through programmed cell death receptor-1 (PD-1) and its ligand programmed cell death-ligand 1 (PD-L1) in patients with non-small cell lung cancer (NSCLC) has been widely applied in clinical research. However, the subtypes and treatment patterns that predict responses to PD-1/PD-L1 inhibitors are not fully understood. Biomarkers, such as PD-L1 expression, tumor mutation load, and DNA mismatch repair defects, have been used to screen patients who respond to PD-1/PD-L1 inhibitors, but the appropriate treatment mode requires further investigation. Immune checkpoint inhibitors combined with radiotherapy provide benefits from remote effects, especially in NSCLC patients with increased PD-L1 expression.

PATIENT CONCERNS

We report a 64-year-old man who presented with left back pain for 40 days. A computed tomography scan showed a mass in the right upper lobe of the lung, with metastases in the right hilar and mediastinal lymph nodes.

DIAGNOSIS

NSCLC-not otherwise specified was diagnosed by computed tomography-guided lung biopsy.

INTERVENTIONS

After the failure of first-line chemotherapy, next-generation sequencing was performed for comprehensive gene analysis, and PD-L1 expression levels were evaluated by immunohistochemistry. The patient was treated with toripalimab (a PD-1 inhibitor) concurrently with radiotherapy for bone metastases.

OUTCOMES

The detection results showed a high tumor mutation burden and increased PD-L1 expression. On the basis of these findings, the patient received toripalimab (PD-1 inhibitor) combined with radiotherapy for bone metastases. Partial response was achieved after 3 cycles, and the patient showed stable disease at the end of the sixth and ninth cycles of toripalimab. The patient was followed up for 26 months. At present, the patient is receiving toripalimab maintenance treatment, which has been well-tolerated without adverse events.

LESSON

Toripalimab combined with radiotherapy may exert a synergistic anti-tumor effect through remote effects in advanced or metastatic NSCLC with high PD-L1 expression. However, the specific treatment mode requires further confirmation by the investigation of additional cases.

The expression landscape of JAK1 and its potential as a biomarker for prognosis and immune infiltrates in NSCLC

Background

Janus-activated kinase-1 (JAK1) plays a crucial role in many aspects of cell proliferation, differentiation, apoptosis and immune regulation. However, correlations of JAK1 with prognosis and immune infiltration in NSCLC have not been documented.

Methods

We analyzed the relationship between JAK1 expression and NSCLC prognosis and immune infiltration using multiple public databases.

Results

JAK1 expression was significantly decreased in NSCLC compared with that in paired normal tissues. JAK1 overexpression indicated a favourable prognosis in NSCLC. In subgroup analysis, high JAK1 expression was associated with a preferable prognosis in lung adenocarcinoma (OS: HR, 0.74, 95% CI from 0.58 to 0.95, log-rank P = 0.017), not squamous cell carcinoma. In addition, data from Kaplan–Meier plotter revealed that JAK1 overexpression was associated with a preferable prognosis in male and stage N2 patients and patients without distant metastasis. Notably, increased levels of JAK1 expression were associated with an undesirable prognosis in patients with stage 1 (OS: HR, 1.46, 95% CI from 1.06 to 2.00, P = 0.02) and without lymph node metastasis (PFS: HR, 2.18, 95% CI from 1.06 to 4.46, P = 0.029), which suggests that early-stage NSCLC patients with JAK1 overexpression may have a bleak prognosis. Moreover, multiple immune infiltration cells, including NK cells, CD8 + T and CD4 + T cells, B cells, macrophages, neutrophils, and dendritic cells (DCs), in NSCLC were positively correlated with JAK1 expression. Furthermore, diverse immune markers are associated with JAK1 expression.

Conclusions

JAK1 overexpression exhibited superior prognosis and immune infiltration in NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04379-y.

Current Landscape of Non-Small Cell Lung Cancer: Epidemiology, Histological Classification, Targeted Therapies, and Immunotherapy

Non-small cell lung cancer (NSCLC) is a subtype of the most frequently diagnosed cancer in the world. Its epidemiology depends not only on tobacco exposition but also air quality. While the global trends in NSCLC incidence have started to decline, we can observe region-dependent differences related to the education and the economic level of the patients. Due to an increasing understanding of NSCLC biology, new diagnostic and therapeutic strategies have been developed, such as the reorganization of histopathological classification or tumor genotyping. Precision medicine is focused on the recognition of a genetic mutation in lung cancer cells called "driver mutation" to provide a variety of specific inhibitors of improperly functioning proteins. A rapidly growing group of approved drugs for targeted therapy in NSCLC currently allows the following mutated proteins to be treated: EGFR family (ERBB-1, ERBB-2), ALK, ROS1, MET, RET, NTRK, and RAF. Nevertheless, one of the most frequent NSCLC molecular sub-types remains without successful treatment: the K-Ras protein. In this review, we discuss the current NSCLC landscape treatment focusing on targeted therapy and immunotherapy, including first- and second-line monotherapies, immune checkpoint inhibitors with chemotherapy treatment, and approved predictive biomarkers.

Antimetabolite pemetrexed primes a favorable tumor microenvironment for immune checkpoint blockade therapy

Background

The immune checkpoint blockade (ICB) targeting programmed cell death-1 (PD-1) and its ligand (PD-L1) has been proved beneficial for numerous types of cancers, including non-small-cell lung cancer (NSCLC). However, a significant number of patients with NSCLC still fail to respond to ICB due to unfavorable tumor microenvironment. To improve the efficacy, the immune-chemotherapy combination with pemetrexed, cis/carboplatin and pembrolizumab (anti-PD-1) has been recently approved as first-line treatment in advanced NSCLCs. While chemotherapeutic agents exert beneficial effects, the underlying antitumor mechanism(s) remains unclear.

Methods

Pemetrexed, cisplatin and other chemotherapeutic agents were tested for the potential to induce PD-L1 expression in NSCLC cells by immunoblotting and flow cytometry. The ability to prime the tumor immune microenvironment was then determined by NSCLC/T cell coculture systems and syngeneic mouse models. Subpopulations of NSCLC cells responding differently to pemetrexed were selected and subjected to RNA-sequencing analysis. The key signaling pathways were identified and validated in vitro and in vivo.

Results

Pemetrexed induced the transcriptional activation of PD-L1 (encoded by CD274) by inactivating thymidylate synthase (TS) in NSCLC cells and, in turn, activating T-lymphocytes when combined with the anti-PD-1/PD-L1 therapy. Nuclear factor κB (NF-κB) signaling was activated by intracellular reactive oxygen species (ROSs) that were elevated by pemetrexed-mediated TS inactivation. The TS−ROS−NF-κB regulatory axis actively involves in pemetrexed-induced PD-L1 upregulation, whereas when pemetrexed fails to induce PD-L1 expression in NSCLC cells, NF-κB signaling is unregulated. In syngeneic mouse models, the combinatory treatment of pemetrexed with anti-PD-L1 antibody created a more favorable tumor microenvironment for the inhibition of tumor growth.

Conclusions

Our findings reveal novel mechanisms showing that pemetrexed upregulates PD-L1 expression and primes a favorable microenvironment for ICB, which provides a mechanistic basis for the combinatory chemoimmunotherapy in NSCLC treatment.

Identification and Prognostic Value Exploration of Radiotherapy Sensitivity-Associated Genes in Non-Small-Cell Lung Cancer

Background

Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases.

Methods

The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature.

Results

WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT.

Conclusion

We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.

Modulating Tumor Microenvironment: A Review on STK11 Immune Properties and Predictive vs Prognostic Role for Non-small-cell Lung Cancer Immunotherapy

OPINION STATEMENT

The quest for immunotherapy (IT) biomarkers is an element of highest clinical interest in both solid and hematologic tumors. In non-small-cell lung cancer (NSCLC) patients, besides PD-L1 expression evaluation with its intrinsic limitations, tissue and circulating parameters, likely portraying the tumor and its stromal/immune counterparts, have been proposed as potential predictors of IT responsiveness. STK11 mutations have been globally labeled as markers of IT resistance. After a thorough literature review, STK11 mutations condition the prognosis of NSCLC patients receiving ICI-containing regimens, implying a relevant biological and clinical significance. On the other hand, waiting for prospective and solid data, the putative negative predictive value of STK11 inactivation towards IT is sustained by less evidence. The physiologic regulation of multiple cellular pathways performed by STK11 likely explains the multifaceted modifications in tumor cells, stroma, and tumor immune microenvironment (TIME) observed in STK11 mutant lung cancer, particularly explored in the molecular subgroup of KRAS co-mutation. IT approaches available thus far in NSCLC, mainly represented by anti-PD-1/PD-L1 inhibitors, are not promising in the case of STK11 inactivation. Perceptive strategies aimed at modulating the TIME, regardless of STK11 status or specifically addressed to STK11-mutated cases, will hopefully provide valid therapeutic options to be adopted in the clinical practice.

Large cell neuroendocrine lung carcinoma: consensus statement from The British Thoracic Oncology Group and the Association of Pulmonary Pathologists

Over the past 10 years, lung cancer clinical and translational research has been characterised by exponential progress, exemplified by the introduction of molecularly targeted therapies, immunotherapy and chemo-immunotherapy combinations to stage III and IV non-small cell lung cancer. Along with squamous and small cell lung cancers, large cell neuroendocrine carcinoma (LCNEC) now represents an area of unmet need, particularly hampered by the lack of an encompassing pathological definition that can facilitate real-world and clinical trial progress. The steps we have proposed in this article represent an iterative and rational path forward towards clinical breakthroughs that can be modelled on success in other lung cancer pathologies.

Proteome profiling of formalin-fixed, paraffin-embedded lung adenocarcinoma tissues using a tandem mass tag-based quantitative proteomics approach

Over the past few decades, increasing efforts have been made to improve the understanding of, and treatment options for, lung adenocarcinoma (LUAD). However, considering the heterogeneity of LUAD, precise proteomics-based characterization at the molecular level is an urgent clinical requirement for effective treatment. Formalin-fixed, paraffin-embedded (FFPE) tissue is a good option as the working tool for proteomics studies. The present study aimed to obtain a global protein profile using LUAD FFPE tissue samples. Using a quantitative proteomics approach, the study revealed that 360 proteins were significantly more highly expressed in LUAD than in adjacent nontumor lung tissues. Also, 19 differentially expressed membrane proteins were found to be primarily responsible for immune processes. Epidermal growth factor (EGF)-like domain and laminin EGF domain showed markedly different expression levels between cancer tissues and tumor-adjacent normal tissues. Furthermore, Gene Ontology functional enrichment analysis showed that significantly upregulated proteins were associated with the endoplasmic reticulum lumen, protein disulfide isomerase activity, vitamin binding, cell cycle G₁/S phase transition, to name but a few. Also, numerous kinases and post-translational modification enzymes were significantly upregulated across all eight LUAD samples compared with paracarcinoma tissues. Proteomics analysis revealed that AAA domain containing 3A (ATAD3a), a member of the ATPase family, was highly expressed in LUAD tissues, which was supported by immunohistochemical analysis. Furthermore, the study confirmed that ATAD3a enhanced the cisplatin sensitivity of LUAD cells. Collectively, the findings of the present study provide new potential candidate targets in patients with LUAD, and may aid auxiliary LUAD diagnosis and surveillance in a noninvasive manner.

Immune-Omics Networks of CD27, PD1, and PDL1 in Non-Small Cell Lung Cancer

To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. Major immune-checkpoint inhibitors (ICIs) have more DNA copy number variations (CNV) than mutations in The Cancer Genome Atlas (TCGA) NSCLC tumors. Nevertheless, CNV-mediated dysregulated gene expression in NSCLC is not well understood. Integrated CNV and transcriptional profiles in NSCLC tumors (n = 371) were analyzed using Boolean implication networks for the identification of a multi-omics CD27, PD1, and PDL1 network, containing novel prognostic genes and proliferation genes. A 5-gene (EIF2AK3, F2RL3, FOSL1, SLC25A26, and SPP1) prognostic model was developed and validated for patient stratification (p < 0.02, Kaplan-Meier analyses) in NSCLC tumors (n = 1163). A total of 13 genes (COPA, CSE1L, EIF2B3, LSM3, MCM5, PMPCB, POLR1B, POLR2F, PSMC3, PSMD11, RPL32, RPS18, and SNRPE) had a significant impact on proliferation in 100% of the NSCLC cell lines in both CRISPR-Cas9 (n = 78) and RNA interference (RNAi) assays (n = 92). Multiple identified genes were associated with chemoresponse and radiotherapy response in NSCLC cell lines (n = 117) and patient tumors (n = 966). Repurposing drugs were discovered based on this immune-omics network to improve NSCLC treatment.

Identification of prognostic markers by weighted gene co-expression network analysis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8⁺ T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (AURKB, CDC20, TPX2 and KIF2C) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of AURKB, CDC20, TPX2, and KIF2C correlated with the poor prognosis of these patients. In vitro experiments confirmed that CDC20 knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8⁺ T cell infiltration-related biomarkers and therapeutic targets.