Clinical utility of tumor mutational burden in patients with non-small cell lung cancer treated with immunotherapy

Molecular Characteristics and Pretreatment Neutrophil-to-Lymphocyte Ratio as Predictors of Durable Clinical Benefit from Immune Checkpoint Inhibition in Non-Small Cell Lung Cancer

BACKGROUND

Prior research in non-small cell lung cancer (NSCLC) has shown that tumors with specific driver mutations may be less likely to respond to immune checkpoint inhibitors (ICI). In this analysis, we evaluated the characteristics of patients with durable clinical benefit (DCB) to ICI compared to those with no durable clinical benefit (NDB), with emphasis on the role of molecular alterations in EGFR, ALK, and ROS1 and pretreatment neutrophil-to-lymphocyte ratio (NLR).

METHODS

We retrospectively collected clinical characteristics and outcomes for patients who initiated ICI monotherapy for advanced NSCLC at Stanford University between April 2015 and May 2018. Patients were classified as having DCB if time on ICI therapy was greater than or equal to 180 days, or NDB if less than 180 days. Outcomes included best radiographic benefit while on ICI and survival from time of ICI initiation.

RESULTS

Of 123 patients treated with ICI for NSCLC, 28 patients had DCB (23%), while 95 had NDB (77%). Median overall survival from initiation of ICI in the 33 patients with molecular alterations in EGFR (n = 31), ALK, or ROS1 and NLR of 5.9 or higher was 2.0 months, compared to 8.1 months in patients with these genomic alterations and NLR less than 5.9. Median overall survival in patients without alterations in EGFR, ALK, or ROS1 and NLR of 5.9 or higher was 4.3 months, compared to 12.1 months in patients with NLR less than 5.9 (P = .023).

CONCLUSIONS

Elevation in pretreatment NLR was associated with significantly lower overall median survival from initiation of ICI, particularly when in combination with NSCLC with alterations in EGFR, ALK, or ROS1. This finding could influence clinical practice as NLR is readily available through routine blood testing.

The impact of CDCA5 expression on the immune microenvironment and its potential utility as a biomarker for PD-L1/PD-1 inhibitors in lung adenocarcinoma

BACKGROUND

Studies have highlighted the important role of cell division cycle associated 5 (CDCA5) in tumor-associated immune dysfunction. We studied immune dysfunction based on CDCA5 expression in lung adenocarcinoma and investigated its potential as a biomarker for patients undergoing anti-programmed death protein-1/ programmed death ligand-1 (PD-1/PD-L1) inhibitor therapy.

METHODS

We used the CIBERSORTx algorithm to investigate the immune cell distribution based on CDCA5 and explored its potential as a biomarker for PD-1/PD-L1 therapy using Tumor Immune Dysfunction and Exclusion in three lung adenocarcinoma datasets. Thus, we validated the role of CDCA5 as a biomarker in patients treated with PD-1/PD-L1 inhibitors. We also investigated the pathways through which CDCA5 regulates PD-L1 expression in a cell line.

RESULTS

The high CDCA5 expression group showed elevated interferon gamma signature, CD274 expression, CD8+ T cell levels, tumor mutation burden, and microsatellite instability. Higher CDCA5 expression was associated with poorer prognosis in patients not treated with PD-1/PD-L1 inhibitors. However, in patients treated with PD-1/PD-L1 inhibitors, higher CDCA5 expression correlated with better response rates and prognosis. CDCA5 expression positively correlated with inhibitory immune checkpoint molecules. CDCA5 regulated the expression of PD-L1 through the ANXA/AKT pathway, and combined suppression of CDCA5 and PD-L1 synergistically inhibited cell proliferation.

CONCLUSIONS

CDCA5 served as a promising biomarker for patients undergoing PD-L1/PD-1 inhibitor treatment, and co-inhibition of CDCA5 and PD-L1 could serve as an effective therapeutic strategy.

Single cell transcriptomic analysis reveals tumor immune infiltration by NK cells gene signature in lung adenocarcinoma

Background

Natural Killer (NK) cells are vital components of the innate immune system, crucial for combating infections and tumor growth, making them pivotal in cancer prognosis and immunotherapy. We sought to understand the diverse characteristics of NK cells within lung adenocarcinoma (LUAD) by conducting single-cell RNA sequencing analyses.

Methods

Using the scRNA-seq dataset for multiple primary lung cancers (MPLCs), we examined two major NK cell groups, NK1 and NK2, comparing the expression profiles of 422 differentially expressed NK signature genes. We identified eight genes (SPON2, PLEKHG3, CAMK2N1, RAB27B, CTBP2, EFHD2, GOLM1, and PLOD1) that distinguish NK1 from NK2 cells. A prognostic signature, the NK gene signature (NKGS) score, was established through LASSO Cox regression. High NKGS scores were linked to poorer overall survival in TCGA-LUAD patients and consistently validated in other datasets (GSE31210 and GSE14814).

Results

Functional analysis revealed an enrichment of genes related to the TGF-β signaling pathway in the high NKGS score group. Moreover, a high NKGS score correlated with an immunosuppressive tumor microenvironment (TME) driven by immune evasion mechanisms. We also observed reduced T-cell receptor (TCR) repertoire diversity in the high-risk NKGS group, indicating a negative association between inflammation and risk score.

Conclusion

This study introduced the innovative NKGS score, differentiating NK1 from NK2 cells. High NKGS scores were associated with the TGF-β pathway and provided insights into LUAD prognosis and immune activities.

Upregulation and epigenetic modification of the creatine transporter SLC6A8 in non-small cell lung cancer

INTRODUCTION

Lung cancer is a major cause of cancer-related death worldwide and effective therapies, besides surgery, are available only for a small proportion of patients. Since cellular respiration is known to be broadly altered in malignant tumors, the cellular processes of respiration can be a potential therapeutic target. One important element of cellular respiration is creatine and its transport by the creatine transporter SLC6A8. Here we describe the expression of SLC6A8 at the RNA and protein level, epigenetic modifications as well as survival analysis in NSCLC tissues and matched controls.

MATERIALS AND METHODS

We analyzed epigenetic modifications of the SLC68A gene in 32 patients, of which 18 were additionally analyzed by transcriptome analysis. The expression of SLC6A8 at the protein level was assessed by immunohistochemistry using an independent cohort and correlated with clinicopathological data including survival. Kaplan-Meier analysis was performed to analyze the possible effects of the transcriptional levels of SLC6A8 in another separate cohort (n=1925).

RESULTS

SLC6A8 loci are epigenetically modified in NSCLC compared with tumor-free controls. SLC6A8 is upregulated in NSCLC at the RNA and protein level. High mRNA expression of SLC6A8 was associated with an overall poor prognosis in lung adenocarcinoma patients and displayed the strongest adverse prognostic effect in male smokers with adenocarcinomas. Results of transcriptome analysis were partially confirmed at the protein level.

CONCLUSIONS

Our results suggest an important role of creatine and its transport via SLC6A8 in NSCLC.

The clinical features and prognostic implications of the co-mutated TP53 gene in advanced non-small cell lung cancer

BACKGROUND

TP53 is a frequently mutated oncogene within non-small cell lung cancer (NSCLC). However, the clinical and prognostic significance of co-mutations in TP53 in patients with advanced NSCLC has not been fully elucidated.

METHODS

A total of 174 patients with advanced NSCLC were enrolled in this study. All patients were subjected to sequencing analysis of tumor-related genes and information such as PD-L1 expression, TMB, and co-mutation changes were collected. Patients were categorized into TP53 mutant and TP53 wild-type groups according to their TP53 mutation status and then statistically analyzed.

RESULTS

TP53 mutations were the most common among all patients, accounting for 56.32%, followed by epidermal growth factor receptor mutations at 48.27%. The most common mutation sites in the TP53 mutation group were exons 5-8.TP53 mutations were significantly associated with PD-L1 and TMB levels. Univariate Cox analysis showed that gender and EGFR mutation affected the prognosis of TP53-mutated NSCLC patients, and multivariate Cox regression analysis identified EGFR mutation as an independent risk factor. The OS of NSCLC patients in the TP53 mutation group was significantly shorter than that of the TP53wt group. Survival curves in the TP53/EGFR combined mutation group showed that patients with combined EGFR mutation had a lower survival rate.

DISCUSSION

TP53 mutations are associated with different clinical indicators and have important implications in clinical treatment. TP53 is a poor prognostic factor for NSCLC patients, and TP53/EGFR co-mutation will affect the survival time of patients. TP53/EGFR co-mutation may be a new prognostic marker for NSCLC.

Lung cancer vaccination from concept to reality: A critical review of clinical trials and latest advances

Lung cancer is a highly lethal malignancy that poses a significant burden on public health worldwide. There have been numerous therapeutic approaches, among which cancer vaccines have emerged as a promising approach to harnessing the patient's immune system to induce long-lasting anti-tumor immunity. The current study aims to provide an overview of cancer vaccination in the context of lung cancer to establish a clearer landscape for lung cancer treatment. To provide a comprehensive review, we not only gathered the published studies of lung cancer vaccination and discussed their effectiveness and safety profile but also analyzed all the relevant clinical trials registered on www.clinicaltrials.gov until March 2024. We demonstrated all utilized vaccine platforms along with having a glance at novel technologies such as mRNA vaccines. The present review discussed the challenges and shortcomings of lung cancer vaccination, as well as the way they could be managed to pave the way for reaching the most optimized vaccine formulation.

Efficacy of Pembrolizumab vs. Nivolumab Plus Ipilimumab in Metastatic NSCLC in Relation to PD-L1 and TMB Status

The efficacy of immune checkpoint inhibitor (ICI) therapy concerning programmed death ligand 1 (PD-L1) status is well established in patients diagnosed with non-small cell lung cancer (NSCLC). However, there remains a paucity of evidence regarding the efficacy concerning tumor mutational burden (TMB) in both clinical trials and real-world data (RWD). In the current article, clinicopathological and molecular epidemiological data were meticulously collected, and treatment modalities were meticulously recorded. The final analysis included a study population of 194 patients. Median age was 67 years (range 37-86), with the majority being male (71.13%), and 85.71% of patients were either current or former smokers at diagnosis. Adenocarcinoma accounted for most diagnoses (71.65%), followed by squamous cell carcinoma (24.23%). In terms of PD-L1 status, 42.78% had an expression level below 1%, 28.35% had an expression between 1-49%, and 28.87% had an expression above 50%. The TMB ranged from 0 to 75, with a median of 10.31 (range 0-75) for PD-L1 expression below 1%, with a median of 9.73 (range 0.95-39.63) for PD-L1 expression between 1-49%, and a median of 9.72 (range 0.95-48) for PD-L1 expression above 50%. Corresponding to patients with low PDL-1 less than 1% and low TMB (0-5), the median overall survival (mOS) was 16 (p = 0.18), and 15 months (p = 0.22), patients with medium PDL-1 (1-49%) and medium TMB (5-10), the mOS was 15 (p = 0.18) and 16 months (p = 0.22), patients with high PDL-1 (>50) and high TMB (>10), the mOS was 24 (p = 0.18) and 21 (p = 0.22) months. This study represents the largest academic RWD dataset concerning PD-L1 and TMB status in patients with locally advanced and metastatic NSCLC.

Integrative analysis of bulk and single-cell RNA-seq reveals the molecular characterization of the immune microenvironment and oxidative stress signature in melanoma

Background

The immune microenvironment and oxidative stress of melanoma show significant heterogeneity, which affects tumor growth, invasion and treatment response. Single-cell and bulk RNA-seq data were used to explore the heterogeneity of the immune microenvironment and oxidative stress of melanoma.

Methods

The R package Seurat facilitated the analysis of the single-cell dataset, while Harmony, another R package, was employed for batch effect correction. Cell types were classified using Uniform Manifold Approximation and Projection (UMAP). The Secreted Signaling algorithm from CellChatDB.human was applied to elucidate cell-to-cell communication patterns within the single-cell data. Consensus clustering analysis for the skin cutaneous melanoma (SKCM) samples was executed with the R package ConsensusClusterPlus. To quantify immune infiltrating cells, we utilized CIBERSORT, ESTIMATE, and TIMERxCell algorithms provided by the R package Immuno-Oncology Biological Research (IOBR). Single nucleotide variant (SNV) analysis was conducted using Maftools, an R package specifically designed for this purpose. Subsequently, the expression levels of PXDN and PAPSS2 genes were assessed in melanoma tissues compared to adjacent normal tissues. Furthermore, in vitro experiments were conducted to evaluate the proliferation and reactive oxygen species expression in melanoma cells following transfection with siRNA targeting PXDN and PAPSS2.

Results

Malignant tumor cell populations were reclassified based on a comprehensive single-cell dataset analysis, which yielded six distinct tumor subsets. The specific marker genes identified for these subgroups were then used to interrogate the Cancer Genome Atlas Skin Cutaneous Melanoma (TCGA-SKCM) cohort, derived from bulk RNA sequencing data, resulting in the delineation of two immune molecular subtypes. Notably, patients within the cluster2 (C2) subtype exhibited a significantly more favorable prognosis compared to those in the cluster1 (C1) subtype. An alignment of immune characteristics was observed between the C2 subtype and unique immune functional tumor cell subsets. Genes differentially expressed across these subtypes were subsequently leveraged to construct a predictive risk model. In vitro investigations further revealed elevated expression levels of PXDN and PAPSS2 in melanoma tissue samples. Functional assays indicated that modulation of PXDN and PAPSS2 expression could influence the production of reactive oxygen species (ROS) and the proliferative capacity of melanoma cells.

Conclusion

The constructed six-gene signature can be used as an immune response and an oxidative stress marker to guide the clinical diagnosis and treatment of melanoma.

Identifying individualized prognostic signature and unraveling the molecular mechanism of recurrence in early-onset colorectal cancer

BACKGROUND

The incidence and mortality of early-onset colorectal cancer (EOCRC; < 50 years old) is increasing worldwide, with a high recurrence rate. The inherent heterogeneity of EOCRC makes its treatment challenging. Hence, to further understand the biology and reveal the molecular mechanisms of EOCRC, a recurrence risk signature is needed to guide clinical management.

METHODS

Based on the relative expression orderings (REOs) of genes in each sample, a prognostic signature was developed and validated utilizing multiple independent datasets. The underlying molecular mechanisms between distinct prognostic groups were explored via integrative analysis of multi-omics data.

RESULTS

The prognostic signature consisting of 6 gene pairs (6-GPS) could predict the recurrence risk for EOCRC at the individual level. High-risk EOCRC classified by 6-GPS showed a poor prognosis but a good response to adjuvant chemotherapy. Moreover, high-risk EOCRC was characterized by epithelial-mesenchymal transition (EMT) and enriched angiogenesis, and had higher mutation burden, immune cell infiltration, and PD-1/PD-L1 expression. Furthermore, we identified four genes associated with relapse-free survival in EOCRC, including SERPINE1, PECAM1, CDH1, and ANXA1. They were consistently differentially expressed at the transcriptome and proteome levels between high-risk and low-risk EOCRCs. They were also involved in regulating cancer progression and immune microenvironment in EOCRC. Notably, the expression of SERPINE1 and ANXA1 positively correlated with M2-like macrophage infiltration.

CONCLUSION

Our results indicate that 6-GPS can robustly predict the recurrence risk of EOCRC, and that SERPINE1, PECAM1, CDH1, and ANXA1 may serve as potential therapeutic targets. This study provides valuable information for the precision treatment of EOCRC.

Circulating Tumor DNA Monitoring on Chemo-immunotherapy for Risk Stratification in Advanced Non-Small Cell Lung Cancer

PURPOSE

Chemoimmunotherapy (chemoIO) is a prevalent first-line treatment for advanced driver-negative non-small cell lung cancer (NSCLC), with maintenance therapy given after induction. However, there is significant clinical variability in the duration, dosing, and timing of maintenance therapy after induction chemoIO. We used circulating tumor DNA (ctDNA) monitoring to inform outcomes in patients with advanced NSCLC receiving chemoIO.

EXPERIMENTAL DESIGN

This retrospective study included 221 patients from a phase III trial of atezolizumab+carboplatin+nab-paclitaxel versus carboplatin+nab-paclitaxel in squamous NSCLC (IMpower131). ctDNA monitoring used the FoundationOne Tracker involving comprehensive genomic profiling of pretreatment tumor tissue, variant selection using an algorithm to exclude nontumor variants, and multiplex PCR of up to 16 variants to detect and quantify ctDNA.

RESULTS

ctDNA was detected (ctDNA+) in 96% of pretreatment samples (median, 93 mean tumor molecules/mL), and similar ctDNA dynamics were noted across treatment arms during chemoIO. ctDNA decrease from baseline to C4D1 was associated with improved outcomes across multiple cutoffs for patients treated with chemoIO. When including patients with missing plasma or ctDNA- at baseline, patients with ctDNA- at C4D1 (clearance), had more favorable progression-free survival (median 8.8 vs. 3.5 months; HR, 0.32;0.20-0.52) and OS (median not reached vs. 8.9 months; HR, 0.22; 0.12-0.39) from C4D1 than ctDNA+ patients.

CONCLUSIONS

ctDNA monitoring during induction chemoIO can inform treatment outcomes in patients with advanced NSCLC. Importantly, monitoring remains feasible and informative for patients missing baseline ctDNA. ctDNA testing during induction chemoIO identifies patients at higher risk for disease progression and may inform patient selection for novel personalized maintenance or second-line treatment strategies.

Systematic pan-cancer analysis identifies cuproptosis-related gene DLAT as an immunological and prognostic biomarker

Lipoylated dihydrolipoamide S-acetyltransferase (DLAT), the component E2 of the multi-enzyme pyruvate dehydrogenase complex, is one of the key molecules of cuproptosis. However, the prognostic value and immunological role of DLAT in pan-cancer are still unclear. Using a series of bioinformatics approaches, we studied combined data from different databases, including the Cancer Genome Atlas, Genotype Tissue-Expression, the Cancer Cell Line Encyclopedia, Human Protein Atlas, and cBioPortal to investigate the role of DLAT expression in prognosis and tumor immunity response. We also reveal the potential correlations between DLAT expression and gene alterations, DNA methylation, copy number variation (CNV), tumor mutational burden (TMB), microsatellite instability (MSI), tumor microenvironment (TME), immune infiltration levels, and various immune-related genes across different cancers. The results show that DLAT displays abnormal expression within most malignant tumors. Through gene set enrichment analysis (GSEA), we found that DLAT was significantly associated with immune-related pathways. Further, the expression of DLAT was also confirmed to be correlated with the tumor microenvironment and diverse infiltration of immune cells, especially tumor-associated macrophages (TAMs). In addition, we found that DLAT is co-expressed with genes encoding major histocompatibility complex (MHC), immunostimulators, immune inhibitors, chemokines, and chemokine receptors. Meanwhile, we demonstrate that DLAT expression is correlated with TMB in 10 cancers and MSI in 11 cancers. Our study reveals that DLAT plays an essential role in tumorigenesis and cancer immunity, which may be used to function as a prognostic biomarker and potential target for cancer immunotherapy.

First-line immune-checkpoint inhibitor treatment in extensive-disease small-cell lung cancer: A classical and network meta-analysis

Background

Small-cell lung cancer (SCLC) has a poor prognosis. For the last 30 years, first-line systemic treatment has remained unaltered. After the integration of ımmunotherapy, a new first-line gold standard, atezolizumab in combination with carboplatin plus etoposide, was approved in extensive-disease SCLC (ED-SCLC) in 2019.

Materials and Methods

First-line randomized controlled studies that investigated anti-programmed cell death protein 1 (PD-1)/PD-1 ligand-1 (PD-L1) and anti-T-lymphocyte-associated protein 4 (CTLA-4) agents in combination with platinum plus etoposide (EP) were scoured. A total of six studies (two - anti-CTLA-4 and four - anti-PD1/PD-L1) were included and classic and network meta-analyses (NMAs) were performed.

Results

Fixed model for overall survival (OAS) in the PD-1- or PD-L1-treated subgroup yielded a hazard ratio (HR) of 0.746 with a 95% confidence interval (CI) =0.662-0.840 and in the CTLA-4-treated subgroup a HR of 0.941 with a 95% CI = 0.816-1.084 for the immune therapy + chemotherapy versus chemotherapy comparison (CTLA-4-based versus PD-1- or PD-L1-based groups' comparison of OAS effect Q = 6.05, df = 1, P = 0.014). NMA showed that all chemotherapy + immunotherapy combinations were equally potent and more efficient than PE in terms of OAS and progression-free survival (PFS). Rank probability plots demonstrated nivolumab + EP as the most probable effective treatment modality in terms of OAS and PFS.

Conclusion

The usage of anti-PD1/PD-L1 immunotherapy agents results in significant OAS advantage, and anti-PD1/PD-L1 agents are superior to anti-CTLA-4 approach in combination with platinum plus etoposide regimen in ED-SCLC.

Companion diagnostic requirements for spatial biology using multiplex immunofluorescence and multispectral imaging

Immunohistochemistry has long been held as the gold standard for understanding the expression patterns of therapeutically relevant proteins to identify prognostic and predictive biomarkers. Patient selection for targeted therapy in oncology has successfully relied upon standard microscopy-based methodologies, such as single-marker brightfield chromogenic immunohistochemistry. As promising as these results are, the analysis of one protein, with few exceptions, no longer provides enough information to draw effective conclusions about the probability of treatment response. More multifaceted scientific queries have driven the development of high-throughput and high-order technologies to interrogate biomarker expression patterns and spatial interactions between cell phenotypes in the tumor microenvironment. Such multi-parameter data analysis has been historically reserved for technologies that lack the spatial context that is provided by immunohistochemistry. Over the past decade, technical developments in multiplex fluorescence immunohistochemistry and discoveries made with improving image data analysis platforms have highlighted the importance of spatial relationships between certain biomarkers in understanding a patient's likelihood to respond to, typically, immune checkpoint inhibitors. At the same time, personalized medicine has instigated changes in both clinical trial design and its conduct in a push to make drug development and cancer treatment more efficient, precise, and economical. Precision medicine in immuno-oncology is being steered by data-driven approaches to gain insight into the tumor and its dynamic interaction with the immune system. This is particularly necessary given the rapid growth in the number of trials involving more than one immune checkpoint drug, and/or using those in combination with conventional cancer treatments. As multiplex methods, like immunofluorescence, push the boundaries of immunohistochemistry, it becomes critical to understand the foundation of this technology and how it can be deployed for use as a regulated test to identify the prospect of response from mono- and combination therapies. To that end, this work will focus on: 1) the scientific, clinical, and economic requirements for developing clinical multiplex immunofluorescence assays; 2) the attributes of the Akoya Phenoptics workflow to support predictive tests, including design principles, verification, and validation needs; 3) regulatory, safety and quality considerations; 4) application of multiplex immunohistochemistry through lab-developed-tests and regulated in vitro diagnostic devices.

Mitophagy bridges DNA sensing with metabolic adaption to expand lung cancer stem-like cells

While previous studies have identified cancer stem-like cells (CSCs) as a crucial driver for chemoresistance and tumor recurrence, the underlying mechanisms for populating the CSC pool remain unclear. Here, we identify hypermitophagy as a feature of human lung CSCs, promoting metabolic adaption via the Notch1-AMPK axis to drive CSC expansion. Specifically, mitophagy is highly active in CSCs, resulting in increased mitochondrial DNA (mtDNA) content in the lysosome. Lysosomal mtDNA acts as an endogenous ligand for Toll-like receptor 9 (TLR9) that promotes Notch1 activity. Notch1 interacts with AMPK to drive lysosomal AMPK activation by inducing metabolic stress and LKB1 phosphorylation. This TLR9-Notch1-AMPK axis supports mitochondrial metabolism to fuel CSC expansion. In patient-derived xenograft chimeras, targeting mitophagy and TLR9-dependent Notch1-AMPK pathway restricts tumor growth and CSC expansion. Taken together, mitochondrial hemostasis is interlinked with innate immune sensing and Notch1-AMPK activity to increase the CSC pool of human lung cancer.

Oxidative Stress Response Biomarkers of Ovarian Cancer Based on Single-Cell and Bulk RNA Sequencing

Background

The occurrence and development of ovarian cancer (OV) are significantly influenced by increased levels of oxidative stress (OS) byproducts and the lack of an antioxidant stress repair system. Hence, it is necessary to explore the markers related to OS in OV, which can aid in predicting the prognosis and immunotherapeutic response in patients with OV.

Methods

The single-cell RNA-sequencing (scRNA-seq) dataset GSE146026 was retrieved from the Gene Expression Omnibus (GEO) database, and Bulk RNA-seq data were obtained from TCGA and GTEx databases. The Seurat R package and SingleR package were used to analyze scRNA-seq and to identify OS response-related clusters based on ROS markers. The "limma" R package was used to identify the differentially expressed genes (DEGs) between normal and ovarian samples. The risk model was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. The immune cell infiltration, genomic mutation, and drug sensitivity of the model were analyzed using the CIBERSORT algorithm, the "maftools," and the "pRRophetic" R packages, respectively.

Results

Based on scRNA-seq data, we identified 12 clusters; OS response-related genes had the strongest specificity for cluster 12. A total of 151 genes were identified from 2928 DEGs to be significantly correlated with OS response. Finally, nine prognostic genes were used to construct the risk score (RS) model. The risk score model was an independent prognostic factor for OV. The gene mutation frequency and tumor immune microenvironment in the high- and low-risk score groups were significantly different. The value of the risk score model in predicting immunotherapeutic outcomes was confirmed.

Conclusions

OS response-related RS model could predict the prognosis and immune responses in patients with OV and provide new strategies for cancer treatment.

The role of macrophages in non-small cell lung cancer and advancements in 3D co-cultures

Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Traditional therapeutic approaches such as chemotherapy or radiotherapy have provided only a marginal improvement in the treatment of lung carcinomas. Inhibitors targeting specific genetic aberrations present in non-small cell lung cancer (NSCLC), the most common subtype (85%), have improved the prognostic outlook, but due to the complexity of the LC mutational spectrum, only a fraction of patients benefit from these targeted molecular therapies. More recently, the realization that the immune infiltrate surrounding solid tumors can foster tumor-promoting inflammation has led to the development and implementation of anticancer immunotherapies in the clinic. In NSCLC, one of the most abundant leukocyte infiltrates is macrophages. These highly plastic phagocytes, which are part of the cellular repertoire of the innate immunity, can have a pivotal role in early NSCLC establishment, malignant progression, and tumor invasion. Emerging macrophage-targeting therapies have been focused on the re-differentiation of the macrophages toward an antitumorigenic phenotype, depletion of tumor-promoting macrophage subtypes, or combination therapies combining traditional cytotoxic treatments with immunotherapeutic agents. The most extensively used models employed for the exploration of NSCLC biology and therapy have been 2D cell lines and murine models. However, studying cancer immunology requires appropriately complex models. 3D platforms, including organoid models, are quickly advancing powerful tools to study immune cell-epithelial cell interactions within the tumor microenvironment. Co-cultures of immune cells along with NSCLC organoids allow for an in vitro observation of the tumor microenvironment dynamics closely resembling in vivo settings. Ultimately, the implementation of 3D organoid technology into tumor microenvironment-modeling platforms might facilitate the exploration of macrophage-targeted therapies in NSCLC immunotherapeutic research, thus establishing a new frontier in NSCLC treatment.

Recent Advances in DNA Vaccines against Lung Cancer: A Mini Review

Lung cancer is regarded as the major causes of patient death around the world. Although the novel tumor immunotherapy has made great progress in the past decades, such as utilizing immune checkpoint inhibitors or oncolytic viruses, the overall 5-year survival of patients with lung cancers is still low. Thus, development of effective vaccines to treat lung cancer is urgently required. In this regard, DNA vaccines are now considered as a promising immunotherapy strategy to activate the host immune system against lung cancer. DNA vaccines are able to induce both effective humoral and cellular immune responses, and they possess several potential advantages such as greater stability, higher safety, and being easier to manufacture compared to conventional vaccination. In the present review, we provide a global overview of the mechanism of cancer DNA vaccines and summarize the innovative neoantigens, delivery platforms, and adjuvants in lung cancer that have been investigated or approved. Importantly, we highlight the recent advance of clinical studies in the field of lung cancer DNA vaccine, focusing on their safety and efficacy, which might accelerate the personalized design of DNA vaccine against lung cancer.

Biological Pathway-Derived TMB Robustly Predicts the Outcome of Immune Checkpoint Blockade Therapy

Although immune checkpoint blockade (ICB) therapies have achieved great progress, the patient response varies among cancers. In this study, we analyzed the potential genomic indicators contributing to ICB therapy response. The results showed that high tumor mutation burden (TMB) failed to predict response in anti-PD1 treated melanoma. SERPINB3 was the most significant response-related gene in melanoma and mutations in either SERPINB3 or PEG3 can serve as an independent risk factor in melanoma. Some recurrent mutations in CSMD3 were only in responders or non-responders, indicating their diverse impacts on patient response. Enrichment scores (ES) of gene mutations in 12 biological pathways were significantly higher in responders or non-responders. Next, the P-TMB calculated from genes in these pathways was significantly related to patient response with prediction AUC 0.74–0.82 in all collected datasets. In conclusion, our work provides new insights into the application of TMB in predicting patient response, which will benefit to immunotherapy research.

Classification of Muscle Invasive Bladder Cancer to Predict Prognosis of Patients Treated with Immunotherapy

Background

Recently, immunotherapies have been approved for advanced muscle invasive bladder cancer (MIBC) treatment, but only a small fraction of MIBC patients could achieve a durable drug response. Our study is aimed at identifying tumor microenvironment (TME) subtypes that have different immunotherapy response rates.

Methods

The mRNA expression profiles of MIBC samples from seven discovery datasets (GSE13507, GSE31684, GSE32548, GSE32894, GSE48075, GSE48276, and GSE69795) were analyzed to identify TME subtypes. The identified TME subtypes were then validated by an independent dataset (TCGA-MIBC). The subtype-related biomarkers were discovered using computational analyses and then utilized to establish a random forest predictive model. The associations of TME subtypes with immunotherapy therapeutic responses were investigated in a group of patients who had been treated with immunotherapy. A prognostic index model was constructed using the subtype-related biomarkers. Two nomograms were built by the subtype-related biomarkers or the clinical parameters.

Results

Two TME subtypes, including ECM-enriched class (EC) and immune-enriched class (IC), were found. EC was associated with greater extracellular matrix (ECM) pathways, and IC was correlated with immune pathways, respectively. Overall survival was significantly greater for tumors classified as IC, whereas the EC subtype had a worse prognosis. A total of nine genes (AKAP12, APOL3, CXCL13, CXCL9, GBP4, LRIG1, PEG3, PODN, and PTPRD) were selected by computational analyses to construct the random forest model. The area under the curve (AUC) values for this model were 0.827 and 0.767 in the testing and external validation datasets, respectively. Therapeutic response rates were greater in IC patients than in EC patients (28 percent vs. 18 percent). Patients with a high prognostic index had a poorer prognosis than those with a low prognostic index. The nomogram constructed from nine genes and stage achieved a C-index of 0.71.

Conclusion

The present investigation defined two distinct TME subtypes and developed models to assess immunotherapeutic treatment outcomes.

Identification of mutation patterns and circulating tumour DNA-derived prognostic markers in advanced breast cancer patients

BACKGROUND

The correlations between circulating tumour DNA (ctDNA)-derived genomic markers and treatment response and survival outcome in Chinese patients with advanced breast cancer (ABC) have not been extensively characterized.

METHODS

Blood samples from 141 ABC patients who underwent first-line standard treatment in Peking University Cancer Hospital were collected. A next-generation sequencing based liquid biopsy assay (PredicineCARE) was used to detect somatic mutations and copy number variations (CNVs) in ctDNA. A subset of matched blood samples and tumour tissue biopsies were compared to evaluate the concordance.

RESULTS

Overall, TP53 (44.0%) and PIK3CA (28.4%) were the top two altered genes. Frequent CNVs included amplifications of ERBB2 (24.8%) and FGFR1 (8.5%) and deletions of CDKN2A (3.5%). PIK3CA/TP53 and FGFR1/2/3 variants were associated with drug resistance in hormone receptor-positive (HR +) and human epidermal growth factor receptor 2-positive (HER2 +) patients. The comparison of genomic variants across matched tumour tissue and ctDNA samples revealed a moderate to high concordance that was gene dependent. Triple-negative breast cancer (TNBC) patients harbouring TP53 or PIK3CA alterations had a shorter overall survival than those without corresponding mutations (P = 0.03 and 0.008). A high ctDNA fraction was correlated with a shorter progression-free survival (PFS) (P = 0.005) in TNBC patients. High blood-based tumor mutation burden (bTMB) was associated with a shorter PFS for HER2 + and TNBC patients (P = 0.009 and 0.05). Moreover, disease monitoring revealed several acquired genomic variants such as ESR1 mutations, CDKN2A deletions, and FGFR1 amplifications.

CONCLUSIONS

This study revealed the molecular profiles of Chinese patients with ABC and the clinical validity of ctDNA-derived markers, including the ctDNA fraction and bTMB, for predicting treatment response, prognosis, and disease progression.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT03792529. Registered January 3rd 2019, https://clinicaltrials.gov/ct2/show/NCT03792529 .

Immune Checkpoint Inhibitors in Cancer Therapy

The discovery of immune checkpoint proteins such as PD-1/PDL-1 and CTLA-4 represents a significant breakthrough in the field of cancer immunotherapy. Therefore, humanized monoclonal antibodies, targeting these immune checkpoint proteins have been utilized successfully in patients with metastatic melanoma, renal cell carcinoma, head and neck cancers and non-small lung cancer. The US FDA has successfully approved three different categories of immune checkpoint inhibitors (ICIs) such as PD-1 inhibitors (Nivolumab, Pembrolizumab, and Cemiplimab), PDL-1 inhibitors (Atezolimumab, Durvalumab and Avelumab), and CTLA-4 inhibitor (Ipilimumab). Unfortunately, not all patients respond favourably to these drugs, highlighting the role of biomarkers such as Tumour mutation burden (TMB), PDL-1 expression, microbiome, hypoxia, interferon-γ, and ECM in predicting responses to ICIs-based immunotherapy. The current study aims to review the literature and updates on ICIs in cancer therapy.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Intron-Retention Neoantigen Load Predicts Favorable Prognosis in Pancreatic Cancer

PURPOSE

High tumor mutation burden (TMB) in many cancer types is associated with the production of tumor-specific neoantigens, a favorable outcome and response to immune checkpoint blockade (ICB) therapy. Besides mutation-derived neoantigens, aberrant intron retention also produces tumor neopeptides that could trigger an immune response. The relationship between intron-retention-derived tumor neoantigens (IR-neoAg) and clinical outcomes in pancreatic cancer remains uncertain. Here, we quantify IR-neoAg in pancreatic cancer and evaluate whether IR-neoAg load might serve as a biomarker for selecting patients who may benefit from ICB therapy.

METHODS

We developed a computational approach to estimate patient-specific IR-neoAg load from transcriptome data available in The Cancer Genome Atlas pancreatic cancer cohort. Associations between IR-neoAg load and patient overall survival were evaluated using Kaplan-Meier estimates and Cox regression. Differential expression of immune checkpoint and HLA-I genes was evaluated in tumors with high IR-neoAg load.

RESULTS

High IR-neoAg load predicted better overall survival in pancreatic cancer, although no association was found for TMB. IR-neoAg load remained a significant prognostic factor after adjusting for patient age, sex, tumor stage and grade, and TMB. Moreover, pancreatic tumors with both high IR-neoAg load and high HLA-I gene expression had similar gene expression profiles as other tumor types that showed response to anti-programmed cell death protein 1 therapy.

CONCLUSION

IR-neoAg load is associated with favorable survival in pancreatic cancer. These findings provide strong evidence for considering IR-neoAgs when selecting patients who might benefit from ICB therapy.

RNF135 Promoter Methylation Is Associated With Immune Infiltration and Prognosis in Hepatocellular Carcinoma

RING finger protein 135 has an important role in the occurrence of many cancers; however its regulation and function of RNF135 in hepatocellular carcinoma remains unknown. The promoter methylation status and mRNA expression of RNF135 was evaluated by methylation-specific PCR, semi-quantitative RT-PCR, and real-time quantitative PCR in HCC tissues and cell lines, and further analyzed from The Cancer Genome Atlas database. Wound healing assay, transwell migration, cell viability, and colony formation assay were performed to investigate the function of RNF135. GSEA analysis, TIMER database, and ESTIMATE algorithm were used to decipher the associated pathway and immune infiltration. The survival analysis was applied to assess the prognostic value of RNF135. RNF135 expression was downregulated in HCC tissues and 5 of 8 HCC cell lines, and was negatively correlated with its promoter hypermethylation. Demethylating regent decitabine restored RNF135 expression on the cellular level. Knockdown of RNF135 expression enhanced the migration of HCC cells, while RNF135 overexpression and decitabine treatment repressed cell migration. Bioinformatics analysis and immunohistochemistry revealed a positive relationship between RNF135 expression and six immune cell infiltrates (B cells, CD4⁺ T cells, CD8⁺ T cells, neutrophils, macrophages, and dendritic cells). Survival analysis disclosed that RNF135 hypermethylation is independently associated with poor clinical outcomes in HCC. Decreased RNF135 expression driven by promoter hypermethylation frequently occurred in HCC and associated with prognosis of HCC. RNF135 functions as a tumor suppressor and is involved in tumor immune microenvironment in HCC.

Assessment of the albumin-bilirubin grade as a prognostic factor in patients with non-small-cell lung cancer receiving anti-PD-1-based therapy

Introduction

The albumin-bilirubin (ALBI) grade is a novel indicator of the liver function. Some studies showed that the ALBI grade was a prognostic and predictive biomarker for the efficacy of chemotherapy in cancer patients. The association between the ALBI grade and outcomes in patients with non-small-cell lung cancer (NSCLC) treated with cancer immunotherapy, however, is poorly understood.

Methods

We retrospectively enrolled 452 patients with advanced or recurrent NSCLC who received anti-programmed cell death protein 1 (PD-1)-based therapy between 2016 and 2019 at three medical centers in Japan. The ALBI score was calculated from albumin and bilirubin measured at the time of treatment initiation and was stratified into three categories, ALBI grade 1-3, with reference to previous reports. We examined the clinical impact of the ALBI grade on the outcomes of NSCLC patients receiving anti-PD-1-based therapy using Kaplan–Meier survival curve analysis with log-rank test and Cox proportional hazards regression analysis.

Results

The classifications of the 452 patients were as follows: grade 1, n = 158 (35.0%); grade 2, n = 271 (60.0%); and grade 3, n = 23 (5.0%). Kaplan–Meier survival curve analysis showed that the ALBI grade was significantly associated with progression-free survival and overall survival. Moreover, Cox regression analysis revealed that the ALBI grade was an independent prognostic factor for progression-free survival and overall survival.

Conclusion

The ALBI grade was an independent prognostic factor for survival in patients with advanced or recurrent NSCLC who receive anti-PD-1-based therapy. These findings should be validated in a prospective study with a larger sample size.

•

ALBI grade is calculated from albumin and bilirubin.

•

We evaluated the impact of ALBI grade on survival in NSCLC patients receiving immune checkpoint inhibitors.

•

ALBI grade was an independent prognostic factor for progression-free survival (PFS) and overall survival (OS).

•

ALBI grade effectively stratified PFS and OS in patients with performance status 1-3.

•

ALBI grade was significantly associated with PFS and OS, regardless of programmed death ligand-1.

Role of Immune Checkpoint Inhibitor Therapy in Advanced EGFR-Mutant Non-Small Cell Lung Cancer

Over the last decade, the treatment of advanced non-small cell lung cancer (NSCLC) has undergone rapid changes with innovations in oncogene-directed therapy and immune checkpoint inhibitors. In patients with epidermal growth factor receptor (EGFR) gene mutant (EGFRm) NSCLC, newer-generation tyrosine kinase inhibitors (TKIs) are providing unparalleled survival benefit and tolerability. Unfortunately, most patients will experience disease progression and thus an urgent need exists for improved subsequent lines of therapies. The concurrent revolution in immune checkpoint inhibitor (ICI) therapy is providing novel treatment options with improved clinical outcomes in wild-type EGFR (EGFRwt) NSCLC; however, the application of ICI therapy to advanced EGFRm NSCLC patients is controversial. Early studies demonstrated the inferiority of ICI monotherapy to EGFR TKI therapy in the first line setting and inferiority to chemotherapy in the second line setting. Additionally, combination ICI and EGFR TKI therapies have demonstrated increased toxicities, and EGFR TKI therapy given after first-line ICI therapy has been correlated with severe adverse events. Nonetheless, combination therapies including dual-ICI blockade and ICI, chemotherapy, and angiogenesis inhibitor combinations are areas of active study with some intriguing signals in preliminary studies. Here, we review previous and ongoing clinical studies of ICI therapy in advanced EGFRm NSCLC. We discuss advances in understanding the differences in the tumor biology and tumor microenvironment (TME) of EGFRm NSCLC tumors that may lead to novel approaches to enhance ICI efficacy. It is our goal to equip the reader with a knowledge of current therapies, past and current clinical trials, and active avenues of research that provide the promise of novel approaches and improved outcomes for patients with advanced EGFRm NSCLC.

Dysregulation of TFH-B-TRM lymphocyte cooperation is associated with unfavorable anti-PD-1 responses in EGFR-mutant lung cancer

Patients with non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations exhibit an unfavorable response to PD-1 inhibitor through unclear mechanisms. Hypothesizing that EGFR mutations alter tumor-immune interactions, we compare tumor-infiltrating lymphocytes between EGFR mutant (EGFR-MT) and wild type (EGFR-WT) tumors through single-cell transcriptomic analysis. We find that B cells, CXCL13-producing follicular helper CD4⁺ T (T_FH)-like cells, and tissue-resident memory CD8⁺ T (T_RM)-like cells decreased in EGFR-MT tumors. The NOTCH-RBPJ regulatory network, which is vital for persistence of T_RM state, is perturbed, and the interactions between T_FH and B cells through the CXCL13-CXCR5 axis disappear in EGFR-MT tumors. Notably, the proportion of T_RM-like cells is predictive for anti-PD-1 response in NSCLC. Our findings suggest that the impairment of T_FH-B-T_RM cooperation in tertiary lymphoid structure formation, accompanied by the dysregulation of T_RM homeostasis and the loss of T_FH-B crosstalk, underlies unfavorable anti-PD-1 response in EGFR-MT lung tumors.

An Integrative Pan-Cancer Analysis of the Prognostic and Immunological Role of Casein Kinase 2 Alpha Protein 1 (CSNK2A1) in Human Cancers: A Study Based on Bioinformatics and Immunohistochemical Analysis

Background

Although emerging animal- or cell-based evidence supports the relationship between casein kinase 2 alpha protein 1 (CSNK2A1) and cancers, no pan-cancer analysis is available. Thus, this report aimed to display the prognostic landscape of CSNK2A1 in pan-cancer and investigate the relationship between CSNK2A1 and tumor immunity.

Methods

In the current study, we investigated the expression pattern, genetic alterations and survival analysis of CSNK2A1 in pan-cancer across multiple datasets and online platforms. The correlations between CSNK2A1 expression and tumor immunity were explored and visualized via R language software. Following this, immunohistochemical (IHC) staining and Kaplan–Meier survival analysis were conducted in clinical patients for proving the bioinformatic findings. Analysis of protein–protein interaction and gene functional enrichment was conducted using GeneMANIA platform and gene set enrichment analysis (GSEA), respectively.

Results

In TCGA, tumor tissue had a higher expression level of CSNK2A1 compared with that in corresponding normal tissue. An increased expression level of CSNK2A1 was related to poor clinical prognosis in most types of cancer such as LIHC. The following expression and survival analysis in clinical liver hepatocellular carcinoma (LIHC) patients confirmed these TCGA findings. CSNK2A1 expression had significant positive correlations with pro-tumor-infiltrating immune cells (TIICs) like M1-macrophages and fibroblasts, and significant negative correlations with anti-tumor-TIICs like activated CD8+ T cells and NK cells, suggesting specific interactions between CSNK2A1 and certain TIICs subtypes. Furthermore, CSNK2A1 expression had the most significant positive correlations with common markers of immune checkpoint including programmed death ligand-1 (PDL1) in LIHC. These findings were validated by an IHC analysis. GSEA analysis demonstrated that high expression of CSNK2A1 was related to cell signaling pathways and immunity-related activities.

Conclusion

These findings suggested that CSNK2A1 was not only related to poor clinical prognosis in cancer like LIHC but also a novel immunotherapy-related biomarker in cancers, especially in LIHC, shedding new light on anti-tumor strategy.

Prognostic effect of coexisting TP53 and ZFHX3 mutations in non-small cell lung cancer patients treated with immune checkpoint inhibitors

In recent years, immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of patients with advanced-stage non-small cell lung cancer (NSCLC). The relationship between TP53 mutation and prognosis of non-small cell lung cancer (NSCLC) remains controversial. We aimed to identify advanced-stage NSCLC patients harboring TP53 mutation who would benefit from ICI treatment. Gene mutations and tumor mutational burden (TMB) data of NSCLC patients who received at least one dose of ICI therapy at the Memorial Sloan Kettering Cancer Center between 2013 and 2017 were extracted from the cBioPortal online platform. Gene clustering analyses were performed for patients with short and long overall survival (OS). The top ten significantly different mutated genes were identified. Furthermore, we analyzed the different OS of coexisting TP53 and other significantly different mutated genes to identify NSCLC patients with TP53 mutations who would benefit from immunotherapy. A total of 350 patients were enrolled in the study. Of these a total of 219 (62.6%) patients were found to harbor TP53 mutations, whereas 131 (37.4%) had wild-type TP53. There was no statistically significant difference in OS between TP53 mutated or wild-type NSCLC patients who underwent ICI treatment. However, coexisting TP53 and ZFHX3 mutations were independent prognostic factors. Higher somatic TMB (highest 20% in each histology) and combination of anti-CTLA-4 and anti-PD-1/PD-L1 therapy were also associated with longer OS in multivariate analysis. Coexisting TP53 and ZFHX3 mutations are independent prognostic factors for advanced-stage NSCLC patients undergoing ICI treatment. These findings could help identify patients harboring TP53 mutations that would benefit from ICI treatment.

Clinicopathologic Features and Response to Therapy of NRG1 Fusion-Driven Lung Cancers: The eNRGy1 Global Multicenter Registry

PURPOSE

Although NRG1 fusions are oncogenic drivers across multiple tumor types including lung cancers, these are difficult to study because of their rarity. The global eNRGy1 registry was thus established to characterize NRG1 fusion-positive lung cancers in the largest and most diverse series to date.

METHODS

From June 2018 to February 2020, a consortium of 22 centers from nine countries in Europe, Asia, and the United States contributed data from patients with pathologically confirmed NRG1 fusion-positive lung cancers. Profiling included DNA-based and/or RNA-based next-generation sequencing and fluorescence in situ hybridization. Anonymized clinical, pathologic, molecular, and response (RECIST v1.1) data were centrally curated and analyzed.

RESULTS

Although the typified never smoking (57%), mucinous adenocarcinoma (57%), and nonmetastatic (71%) phenotype predominated in 110 patients with NRG1 fusion-positive lung cancer, further diversity, including in smoking history (43%) and histology (43% nonmucinous and 6% nonadenocarcinoma), was elucidated. RNA-based testing identified most fusions (74%). Molecularly, six (of 18) novel 5' partners, 20 unique epidermal growth factor domain-inclusive chimeric events, and heterogeneous 5'/3' breakpoints were found. Platinum-doublet and taxane-based (post-platinum-doublet) chemotherapy achieved low objective response rates (ORRs 13% and 14%, respectively) and modest progression-free survival medians (PFS 5.8 and 4.0 months, respectively). Consistent with a low programmed death ligand-1 expressing (28%) and low tumor mutational burden (median: 0.9 mutations/megabase) immunophenotype, the activity of chemoimmunotherapy and single-agent immunotherapy was poor (ORR 0%/PFS 3.3 months and ORR 20%/PFS 3.6 months, respectively). Afatinib achieved an ORR of 25%, not contingent on fusion type, and a 2.8-month median PFS.

CONCLUSION

NRG1 fusion-positive lung cancers were molecularly, pathologically, and clinically more heterogeneous than previously recognized. The activity of cytotoxic, immune, and targeted therapies was disappointing. Further research examining NRG1-rearranged tumor biology is needed to develop new therapeutic strategies.

Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD)

Background

Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD.

Method

First, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool.

Result

The Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively.

Conclusion

AFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02127-z.

The current issues and future perspective of artificial intelligence for developing new treatment strategy in non-small cell lung cancer: harmonization of molecular cancer biology and artificial intelligence

Comprehensive analysis of omics data, such as genome, transcriptome, proteome, metabolome, and interactome, is a crucial technique for elucidating the complex mechanism of cancer onset and progression. Recently, a variety of new findings have been reported based on multi-omics analysis in combination with various clinical information. However, integrated analysis of multi-omics data is extremely labor intensive, making the development of new analysis technology indispensable. Artificial intelligence (AI), which has been under development in recent years, is quickly becoming an effective approach to reduce the labor involved in analyzing large amounts of complex data and to obtain valuable information that is often overlooked in manual analysis and experiments. The use of AI, such as machine learning approaches and deep learning systems, allows for the efficient analysis of massive omics data combined with accurate clinical information and can lead to comprehensive predictive models that will be desirable for further developing individual treatment strategies of immunotherapy and molecular target therapy. Here, we aim to review the potential of AI in the integrated analysis of omics data and clinical information with a special focus on recent advances in the discovery of new biomarkers and the future direction of personalized medicine in non-small lung cancer.

Identification of a predictive metabolic signature of response to immune checkpoint inhibitors in non-small cell lung cancer: METABO-ICI clinical study protocol

BACKGROUND

Immune checkpoints inhibitors (ICI) are becoming new standards of care for the treatment of non-small cell lung cancer (NSCLC), both as first (alone or in association with chemotherapy) and second line. However, no powerful predictive biomarker of therapeutic response to ICI has been found to date. It has been recently shown that microbiota composition could influence the ability of patients to respond to ICI. Indeed, the microbiota produces circulating metabolites that will subsequently act on immune system, the investigators hypothesized that plasma metabolic signature, reflecting a global microbiota function, could represent a predictive biomarker of response to ICI.

METHODS

Monocentric prospective study. Primary objective is to identify baseline metabolic signature (metabolomics analysis by mass spectrometry) associated to ICI response. Secondary objectives are to link metabolic signature with microbiota composition (metagenomics analysis RNA 16S) and immune profile, and altogether with clinic response to ICI. The study will include 60 NSCLC patients treated by ICI in 1st, 2nd or 3rd line of treatment at the Grenoble Alpes University hospital (CHUGA) in 18 months. Patients that have received antibiotic or steroid treatment, 2 or 4 weeks before ICI initiation, respectively, will be excluded. Blood and feces will be collected prior to, at 2 months after ICI treatment initiation, and at 6 months or at progression.

EXPECTED RESULTS

We expect to highlight a metabolic profile predictive of response to ICI. By identifying factors associated with early progression, we could avoid to treat potential non-responding patients. Moreover, by restoring a favorable microbiota, patients' ability to respond to these treatments might be restored.

Is there any opportunity for immune checkpoint inhibitor therapy in non-small cell lung cancer patients with brain metastases?

Although brain metastases occur in almost one-third of non-small cell lung cancer (NSCLC) patients, and immune checkpoint inhibitors (ICI) either as monotherapy or combined with chemotherapy are the new standard of care in the first line setting, most trials excluded patients with asymptomatic and/or untreated brain metastases. Brain metastases have a major clinical impact due to the worsening of the patient's prognosis and quality of life. Furthermore, the incidence of brain metastases is increasing in NSCLC patients, due to a longer survival and better imaging techniques. Therefore, brain metastases are increasingly becoming a research topic. Recent clinical data endorses ICI as a therapeutic strategy in this subpopulation of NSCLC patients, although the immune environment in brain metastases is more immune ignorant compared with the microenvironment in the primary tumour or in the extracranial metastases. In this review we summarize the current evidence of ICI strategy in NSCLC patients with brain metastases, including trial and real-life data. We also state that the different tumor microenvironment between brain metastases and primary tumor may explain the discordance on the response rate during treatment with ICI. Last, we focus on future directions, including the role and optimal sequence of cranial irradiation and ICI, prognostic scores, the best response assessment and new imaging techniques.

The prognostic impact of tumor mutational burden (TMB) in the first-line management of advanced non-oncogene addicted non-small-cell lung cancer (NSCLC): a systematic review and meta-analysis of randomized controlled trials

BACKGROUND

The role of tumor mutational burden (TMB) is still debated for selecting advanced non-oncogene addicted non-small-cell lung cancer (NSCLC) patients who might benefit from immune checkpoint inhibitors (ICIs). Of note, TMB failed to predict a benefit in overall survival (OS) among such patients.

MATERIALS AND METHODS

The purpose of this meta-analysis was to compare efficacy outcomes among first-line immune-oncology (IO) agents versus standard platinum-based chemotherapy (CT) within two subgroups (TMB-low and TMB-high on either tissue or blood). We collected hazard ratios (HRs) to evaluate the association for progression-free survival (PFS) and OS, with the relative 95% confidence intervals (CIs). Risk ratios (RRs) were used as an association measure for objective response rate (ORR).

RESULTS

Eight different cohorts of five randomized controlled phase III studies (3848 patients) were analyzed. In TMB-high patients, IO agents were associated with improved ORR (RRs 1.37, 95% CI 1.13-1.66), PFS (HR 0.69, 95% CI 0.61-0.79) and OS (HR 0.67, 95% CI 0.59-0.77) when compared with CT, thus suggesting a possible predictive role of high TMB for IO regimens. In TMB-low patients, the IO strategy did not lead to any significant benefit in survival and activity, whereas the pooled results of both ORR and PFS were intriguingly associated with a statistical significance in favor of CT.

CONCLUSIONS

This meta-analysis resulted in a proven benefit in OS in favor of IO agents in the TMB-high population. Although more prospective data are warranted, we postulated the hypothesis that monitoring TMB, in addition to the existing programmed death-ligand 1 (PD-L1) expression level, could represent the preferable option for future clinical research in the first-line management of advanced non-oncogene addicted NSCLC patients.

Circulating tumor DNA in lung cancer: real-time monitoring of disease evolution and treatment response

Lung cancer is one of the leading causes of all cancer-related deaths. Circulating tumor DNA (ctDNA) is released from apoptotic and necrotic tumor cells. Several sensitive techniques have been invented and adapted to quantify ctDNA genomic alterations. Applications of ctDNA in lung cancer include early diagnosis and detection, prognosis prediction, detecting mutations and structural alterations, minimal residual disease, tumor mutational burden, and tumor evolution tracking. Compared to surgical biopsy and radiographic imaging, the advantages of ctDNA are that it is a non-invasive procedure, allows real-time monitoring, and has relatively high sensitivity and specificity. Given the massive research on non-small cell lung cancer, attention should be paid to small cell lung cancer.

Baseline total metabolic tumour volume on 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography-computed tomography as a promising biomarker in patients with advanced non-small cell lung cancer treated with first-line pembrolizumab

INTRODUCTION

Immune checkpoint inhibitors (ICIs) have become the standard of care in the management of advanced non-small cell lung cancer (NSCLC). Nevertheless, only a small proportion of patients benefit from ICIs. The aim of the present study is to assess whether 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography-computed tomography ([18F]FDG-PET/CT)-derived parameters may be used as biomarkers in patients with advanced NSCLC receiving first-line pembrolizumab.

MATERIALS AND METHODS

This is a monocentric retrospective cohort study including patients with advanced NSCLC (stage IV) and Programmed death-ligand 1 (PD-L1) expression ≥50% treated with pembrolizumab. A control group of patients treated with epidermal growth factor receptor (EGFR) inhibitors for EGFR-mutated NSCLC was also enrolled. Only patients with a positive [18F]18F-FDG PET/CT result within 60 days from treatment initiation were included.Total metabolic tumour volume (tMTV) was calculated for each lesion using a dedicated software (PET VCAR; GE Healthcare), which semiautomatically delineates the tumour's contours with a maximum standardised uptake value (SUVmax) threshold of 42% within the lesion. tMTV was obtained summing each lesion's MTV. Potential prognostic parameters for overall survival (OS) were analysed (tMTV, SUVmax, bone/liver metastasis, neutrophil:lymphocyte ratio ≥4, Eastern Cooperative Oncology Group performance status ≥2, lactate dehydrogenase above the upper limit of normal).

RESULTS

Overall, 34 patients treated with first line-pembrolizumab and 40 patients treated with EGFR tyrosine kinase inhibitors were included. In the pembrolizumab group, the median follow-up was 20.3, while the median OS was 4.7 months (95% confidence interval [CI] = 0.3-9.1) for patients with tMTV ≥75 cm³ vs not reached (NR) for patients with tMTV <75 cm³ (95% CI = NR-NR; hazard ratio [HR] = 5.37; 95% CI = 1.72-16.77; p = 0.004). No difference was found in the control group (HR = 1.43; 95% CI = 0.61-3.34; p = 0.411).

CONCLUSION

Our data suggest that tMTV ≥75cm³ can be used as a prognostic biomarker of poor outcomes in patients with PD-L1-high advanced NSCLC treated with first-line pembrolizumab. This information could be useful for the selection of patients who may require the addition of chemotherapy to pembrolizumab.

Impact of the corticosteroid indication and administration route on overall survival and the tumor response after immune checkpoint inhibitor initiation

Background:

Based on their indications, systemic corticosteroids appear to negatively affect clinical outcomes in immune checkpoint inhibitor (ICI)-treated patients. There are few data on the influence of topical and inhaled corticosteroids on the ICIs’ effectiveness.

Methods:

In a single-center study, we retrospectively investigated the impact of systemic corticosteroids according to their indication [an immune-related adverse event (irAE) or another indication] on overall survival (OS) and the tumor response in all consecutive patients after initiation of ipilimumab, nivolumab or pembrolizumab over a 9-year period. The impacts of topical and inhaled corticosteroids were also examined.

Results:

Three hundred and seventy-two patients were included. The mean ± standard deviation age was 64.0 ± 12.1 years. The most frequently prescribed ICI was nivolumab (in 58.3% of the patients) and the most frequent indications were lung cancer (44.6%) and melanoma (29.6%). Systemic corticosteroid use for an irAE did not have a negative impact on OS [adjusted hazard ratio (HR) [95% confidence interval (CI)] 1.04 (0.56–1.95), p = 0.902] or the best overall tumor response [adjusted odds ratio (OR) (95% CI) 1.69 (0.52–6.56), p = 0.413], while systemic corticosteroid use for another indication was associated with shorter OS [adjusted HR (95% CI) 1.34 (1.05–2.03), p = 0.046] and a poor best overall tumor response [adjusted OR (95% CI) 2.04 (1.07–5.80), p = 0.039] with a cumulative dose cut-off of 3215 mg prednisolone equivalent (specificity 71.4%; sensitivity 65.3%) and a time cut-off of 132 days (specificity 71.4%; sensitivity 89.8%). The use of topical corticosteroids was associated with a longer OS; this was probably due to dermatological irAEs. Inhaled corticosteroid use did not influence OS.

Conclusion:

Systemic corticosteroid use for an irAE does not impact OS or the tumor response, whereas use for other indications (themselves often associated with a worse prognosis) does. Topical and inhaled steroids do not have a negative impact on OS.

Lights and Shadows in Immuno-Oncology Drug Development

The rapidly evolving landscape of immuno-oncology (IO) is redefining the treatment of a number of cancer types. IO treatments are becoming increasingly complex, with different types of drugs emerging beyond checkpoint inhibitors. However, many of the new drugs either do not progress from phase I-II clinical trials or even fail in late-phase trials. We have identified at least five areas in the development of promising IO treatments that should be redefined for more efficient designs and accelerated approvals. Here we review those critical aspects of IO drug development that could be optimized for more successful outcome rates in all cancer types. It is important to focus our efforts on the mechanisms of action, types of response and adverse events of these novel agents. The use of appropriate clinical trial designs with robust biomarkers of response and surrogate endpoints will undoubtedly facilitate the development and subsequent approval of these drugs. Further research is also needed to establish biomarker-driven strategies to select which patients may benefit from immunotherapy and identify potential mechanisms of resistance.

PD-L1 versus tumor mutation burden: Which is the better immunotherapy biomarker in advanced non-small cell lung cancer?

PD-L1 and tumor mutation burden (TMB) are the most widely used immunotherapy biomarkers to identify populations who would attain clinical benefit, with the higher values predicting better therapeutic efficacy. This review addresses the predictive values and unresolved challenges of these two biomarkers. PD-1 and PD-L1 inhibitors have induced durable and effective responses in patients with advanced non-small cell lung cancer, confirmed by multiple clinical trials and real-world studies. Different clinical trials, involving both PD-1/PD-L1 inhibitors alone and combination regimens, adopted either PD-L1 or TMB to stratify the patients, although the predictive capabilities of these two biomarkers are different. In the first-line setting, PD-L1 of 50% or more as a cut-off value can help select candidates for pembrolizumab or atezolizumab monotherapy; however, these two biomarkers poorly predict the efficacy of immunotherapy combination regimens as first-line treatments. In the second-line setting, although patients can benefit from nivolumab regardless of PD-L1 expression, both PD-L1 and blood TMB can be used as biomarkers to find patients suitable for atezolizumab. Except for inaccurate predictiveness, there are many unresolved problems with regard to the two biomarkers, such as the lack of standard detection methods, and their susceptibilities to other dynamic changes. The predictive values of TMB and PD-L1 were low in most circumstances; however, PD-L1 expression greater than ≥ 50% can help select appropriate patients for pembrolizumab and atezolizumab, respectively, as first-line monotherapies. Higher PD-L1 or TMB was associated with greater efficacy for atezolizumab as a second-line monotherapy.

Molecular testing and targeted therapy for non-small cell lung cancer: Current status and perspectives

Molecular testing has become a mandatory component of the non-small cell lung cancer (NSCLC) management. The detection of EGFR, BRAF and MET mutations as well as the analysis of ALK, ROS1, RET and NTRK translocations have already been incorporated in the NSCLC diagnostic standards, and the inhibitors of these kinases are in routine clinical use. There are emerging biomarkers, e.g., KRAS G12C substitutions and HER2 activating alterations, which are likely to enter NSCLC guidelines upon the approval of the corresponding drugs. In addition to genetic examination, NSCLCs are usually subjected to the analysis of PD-L1 protein expression in order to direct the use of immune checkpoint inhibitors. Comprehensive NSCLC testing for multiple predictive markers requires the analysis of distinct biological molecules (DNA, RNA, proteins) and, therefore, the involvement of different analytical platforms (PCR, DNA sequencing, immunohistochemistry, FISH). There are ongoing efforts aimed at the integration of multiple NSCLC molecular assays into a single diagnostic pipeline.

Simple parameters to solve a complex issue: predicting response to checkpoint inhibitor therapy in lung cancer

Background:

Noninvasive biomarkers predicting immune checkpoint inhibitor (ICI) response are urgently needed. We evaluated the predictive value of pretreatment neutrophil-to-lymphocyte ratio (NLR), smoking history, smoking intensity, BMI and programmed death ligand 1 (PD-L1) expression in non-small-cell lung cancer (NSCLC) patients treated with ICIs.

Materials & methods:

Single-center retrospective study included 137 patients from July 2015 to February 2018. Outcomes included 3-month disease control rate, progression-free survival, and overall survival. Predictive value of biomarkers was assessed independently and in a multivariable model.

Results:

NLR was associated with all outcomes. Smoking history was predictive of progression-free survival and smoking intensity was predictive of disease control rate. BMI and PD-L1 were not associated with any outcome. High BMI was associated with low NLR.

Conclusion:

Simple clinical biomarkers can predict response to ICIs. A score incorporating both clinical factors and established tissue/serum biomarkers may be useful in identifying NSCLC patients who would benefit from ICIs.

The interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy

The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms.

An increasing number of studies have demonstrated the benefit of tumor mutation burden (TMB), the number of non-silent mutations in the genome, as a predictive biomarker in a clinical setting. Most clinical trials utilize a smaller panel, instead of whole exome sequencing (WES), to estimate the exome-wide mutational load. However, the use of panels introduces panel size dependent sampling noise that could affect the performance of the TMB biomarker. In this work we create a mathematical model of the cancer histology, treatment response, and TMB device system to assess the interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy.

Higher Tumor Mutation Burden and Higher PD-L1 Activity Predicts the Efficacy of Immune Checkpoint Inhibitor Treatment in a Patient With Four Lung Cancers. A Case Report

We experienced a patient who had four lung cancers with different pathological features, with the most advanced being diagnosed as pStage IIA. A month after the resection, the original lung cancer had metastasized to the lung and to the liver. Of the original lung cancers that were resected, the biggest adenocarcinoma of S3 showed 50 × 31 × 17 mm (invasion 50 mm) and pT2bN0M0 (pStage IIA) with epidermal growth factor receptor (EGFR) mutation (–) and anaplastic lymphoma kinase (ALK) translocation (–), but expression of programmed death ligand 1 (PD-L1) (+) tumor proportion score (TPS) 80%. The pleomorphic carcinoma showed 23 × 20 × 17 mm (invasion 23 mm) and pT1cN0M0 (pStage Ic) with EGFR (–), ALK (–), PD-L1 (+), TPS 95%. Tumor mutation burden (TMB), microsatellite instability (MSI), and structural chromosome aberration analysis by DNA microarray were performed. One hundred somatic mutations in the adenocarcinoma and 75 somatic mutations in the pleomorphic carcinoma were identified, which showed an extremely high mutation rate, although only 16 somatic mutations were common between the two cancers. Chromosomal structural aberrations differed greatly between the two cancers, but common aberrations were found in chromosomes 8 and 10 and partially common aberration in chromosomes 4, 14, 17, and X. These results indicated that each lung cancer originated from a common ancestor clone and developed on an individual molecular evolution. The patient received a single injection of pembrolizumab and 13 injections of atezolizumab. Immune checkpoint inhibitor treatment made metastatic pulmonary and liver lesions reduce in size and show as Partial response (PR). Multiple lung cancers with high PD-L1 activity tend to be TMB-high, reflecting rapid molecular evolution and relevance to the patient's response to immune checkpoint inhibitors. Genomic examination could help determine what had happened in multiple cancers on progression and provide useful data to patient treatment. Each lung cancer originated from a common ancestor clone and developed on an individual molecular evolution.

The potentiality of immunotherapy for sarcomas: a summary of potential predictive biomarkers

Sarcomas are rare and heterogeneous malignant tumors of mesenchymal origin. A total of 25-50% of patients treated with initial curative intent will develop as recurrent and metastatic disease. In the recurrent and metastatic setting, effect of chemotherapy is limited; therefore, more effective therapies are urgently desired. As a brake for activation of T cell, PD-1/PD-L1 plays a crucial role in the progression of tumor by altering status of immune surveillance. Some success has been acquired recently in the use of PD-1/PD-L1 inhibitors for the treatment of several solid tumors, for examples, non-small-cell lung cancer and melanoma. Immunotherapeutic strategies based on PD-1/PD-L1 for sarcomas have also been explored these years. As in other cancers, major challenges are identification of biomarkers to predict response for immunotherapy, optimization of patient's benefit and minimization of side effects. Therefore, we focused on potential biomarkers of immunotherapy for treatment of sarcomas in this review.

Immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is considered an immunogenic tumor that arises in chronically inflamed livers due to underlying chronic liver disease caused by viral and non-viral pathogenesis. This inflammation leads to tumor development and is associated to higher tumor immunogenicity. For this reason immunotherapeutic approaches may be suitable therapeutic strategies for HCC. Indeed, several preclinical and clinical data support this hypothesis showing that immunotherapy and even more their combination may be a good alternative candidate for the treatment of HCC patients. However, considering that the liver plays a central role in host defense as well as in the maintenance of self-tolerance, it is characterized by a strong intrinsic immune suppressive microenvironment as well as by a high immune evasion, which may represent a major impediment for an effective immune response against tumor. Furthermore, the low expression of tumor antigens on liver cancer cells leads to a lower T-cell activation and tumor infiltration, resulting in a less efficient control of the tumor growth and, consequently, in a worse clinical outcome. For this reason, strategies should be developed to counteract the different factors in the HCC tumor microenvironment playing a major role in reducing the effects of immunotherapy.

ADP ribose polymerase inhibitors for treating non-small cell lung cancer: new additions to the pharmacotherapeutic armamentarium

INTRODUCTION

Poly (ADP-ribose) polymerase inhibitors (PARPi) are already part of the armamentarium of drugs available against ovarian and breast cancer. There is less data available on the efficacy of these drugs in the treatment of non-small cell lung cancer (NSCLC).

AREAS COVERED

The authors have analyzed the preclinical studies that justified the use of PARPi in NSCLC. They then evaluate the in vivo efficacy of the combination of these drugs with chemotherapy, radiotherapy, and immunotherapy.

EXPERT OPINION

Data from clinical trials available to date have discouraged the use of PARPi in association with chemotherapy or radiotherapy in NSCLC. The knowledge available to date opens the door to the use of PARPi in association with immunotherapy. In fact, the activity of these drugs would not be based only on direct cytotoxic action, but also on the modification of the intra-tumor microenvironment, in particular by increasing the expression of PD-L1 on tumor cells. This action might potentially enhance available treatments with a modest increase in toxicity.