TP53, STK11, and EGFR Mutations Predict Tumor Immune Profile and the Response to Anti-PD-1 in Lung Adenocarcinoma

Primary and Acquired Resistance against Immune Check Inhibitors in Non-Small Cell Lung Cancer

Simple Summary

NSCLC accounts for approximately 84% of lung malignancies and the clinical application of ICIs provides a novel and promising strategy. However, approximately 80% of NSCLC patients do not benefit from ICIs due to drug resistance complicated by disciplines and diverse mechanisms. Through this review, we provide a whole map of current understanding of primary and acquired resistance mechanisms in NSCLC. In the first part, resistance mechanisms of 6 FDA-approved ICIs-related primary resistance are collected and arranged into 7 steps of the well-known cancer-immunity cycle. Acquired resistance induced by ICIs are summarized in the second part. In the third part, we discuss the future direction, including the deeper understanding of tumor microenvironment and the combinational treatment. Through this review, clinicians can get clear and direct clues to find the underlying mechanisms in patients and translational researchers can acquire several directions to overcome resistance and apply new combinational treatment.

Abstract

Immune checkpoint inhibitors have emerged as the treatment landscape of advanced non-small cell lung cancer (NSCLC) in recent years. However, approximately 80% of NSCLC patients do not benefit from ICIs due to primary resistance (no initial response) or acquired resistance (tumor relapse after an initial response). In this review, we highlight the mechanisms of primary and secondary resistance. Furthermore, we provide a future direction of the potential predictive biomarkers and the tumor microenvironmental landscape and suggest treatment strategies to overcome these mechanisms.

A TP53 Related Immune Prognostic Model for the Prediction of Clinical Outcomes and Therapeutic Responses in Lung Adenocarcinoma

TP53 is the most frequently mutated gene in lung adenocarcinoma (LUAD). The tumor immune microenvironment (TIM) is considered a vital factor that influences tumor progression and survival rate. The influence of TP53 mutation on TIM in LUAD has not been fully studied. Here we systematically investigated the relationship and potential mechanisms between TP53 mutation status and immune response in LUAD. We constructed an immune prognostic model (IPM) using immune associated genes, which were expressed differentially between the TP53 mutant and wild type LUAD patients. We discovered that TP53 mutations were significantly associated with 5 immune related biological processes. Thirty-six immune genes were expressed differentially between TP53 mutant and wild type LUAD patients. An IPM was constructed using 3 immune genes to differentiate the prognostic survival in LUAD. The high-risk LUAD group displayed significantly higher proportions of dendritic cell resting, T cell CD4 memory resting and mast cell resting, and significantly low proportions of dendritic cell activated, T cell CD4 memory activated, and mast cell activated. Moreover, IPM was found to be an independent clinical feature and can be used to predict immunotherapy responses. In summary, we constructed and validated an IPM using 3 immune related genes, which provides a better understanding of the mechanism from an immunological perspectives.

Identification of prognostic candidate signatures by systematically revealing transcriptome characteristics in lung adenocarcinoma with differing tumor microenvironment immune phenotypes

Accumulated evidence shows that tumor microenvironment plays crucial roles in predicting clinical outcomes of lung adenocarcinoma (LUAD). The current study aimed to identify some potentially prognostic signatures by systematically revealing the transcriptome characteristics in LUADs with differing immune phenotypes. LUAD gene expression data were retrieved from the public TCGA and GEO databases, and the transcriptome characteristics were systematically revealed using a comprehensive bioinformatics method including single-sample gene set enrichment analysis, differentially expressed gene (DEG) analysis, protein and protein interaction (PPI) network construction, competitive endogenous RNA (ceRNA) network construction, weighted gene coexpression network analysis and prognostic model establishment. Finally, 1169 key DEGs associated with LUAD immune phenotype, including 88 immune DEGs, were excavated. Five essential and eight immune essential DEGs were separately identified by constructing two PPI networks based on the above DEGs. Totals of 1085 key DElncRNAs and 45 key DEmiRNAs were excavated and one ceRNA network consisting of 26 DEmRNAs, 3 DEmiRNAs and 57 DElncRNAs were established. The most significant gene coexpression module (cor=0.63 and p=3e-55) associated with LUAD immune phenotypes and three genes (FGR, BTK, SPI1) related to the immune cell infiltration were identified. Three robust prognostic signatures including a 9-lncRNA, an 8-lncRNA and an 8-mRNA were established. The areas under the curves of 5-year correlated with overall survival rate were separately 0.7319, 0.7228 and 0.713 in the receiver operating characteristic curve. The findings provide novel insights into the immunological mechanism in LUAD biology and in predicting the prognosis of LUAD patients.

LKB1: Can We Target an Hidden Target? Focus on NSCLC

LKB1 (liver kinase B1) is a master regulator of several processes such as metabolism, proliferation, cell polarity and immunity. About one third of non-small cell lung cancers (NSCLCs) present LKB1 alterations, which almost invariably lead to protein loss, resulting in the absence of a potential druggable target. In addition, LKB1-null tumors are very aggressive and resistant to chemotherapy, targeted therapies and immune checkpoint inhibitors (ICIs). In this review, we report and comment strategies that exploit peculiar co-vulnerabilities to effectively treat this subgroup of NSCLCs. LKB1 loss leads to an enhanced metabolic avidity, and treatments inducing metabolic stress were successful in inhibiting tumor growth in several preclinical models. Biguanides, by compromising mitochondria and reducing systemic glucose availability, and the glutaminase inhibitor telaglenastat (CB-839), inhibiting glutamate production and reducing carbon intermediates essential for TCA cycle progression, have provided the most interesting results and entered different clinical trials enrolling also LKB1-null NSCLC patients. Nutrient deprivation has been investigated as an alternative therapeutic intervention, giving rise to interesting results exploitable to design specific dietetic regimens able to counteract cancer progression. Other strategies aimed at targeting LKB1-null NSCLCs exploit its pivotal role in modulating cell proliferation and cell invasion. Several inhibitors of LKB1 downstream proteins, such as mTOR, MEK, ERK and SRK/FAK, resulted specifically active on LKB1-mutated preclinical models and, being molecules already in clinical experimentation, could be soon proposed as a specific therapy for these patients. In particular, the rational use in combination of these inhibitors represents a very promising strategy to prevent the activation of collateral pathways and possibly avoid the potential emergence of resistance to these drugs. LKB1-null phenotype has been correlated to ICIs resistance but several studies have already proposed the mechanisms involved and potential interventions. Interestingly, emerging data highlighted that LKB1 alterations represent positive determinants to the new KRAS specific inhibitors response in KRAS co-mutated NSCLCs. In conclusion, the absence of the target did not block the development of treatments able to hit LKB1-mutated NSCLCs acting on several fronts. This will give patients a concrete chance to finally benefit from an effective therapy.

Clinical outcomes and immune phenotypes associated with STK11 co-occurring mutations in non-small cell lung cancer

Background

STK11 mutation in non-small cell lung cancer (NSCLC) is associated with worse survival as well as primary resistance to PD-1/PD-L1 targeting immunotherapy. We hypothesize that co-occurring mutations and tumor mutation burden (TMB) may impact response to therapy and prognosis.

Methods

Forty-one patients with STK11-mutated NSCLC seen in our Thoracic oncology clinic with available next-generation sequencing tumor data were included in the analysis. Data from the Cancer Genome Atlas (TCGA) was used for survival and immune gene expression analysis. Overall and progression-free survival (PFS) was estimated by the Kaplan-Meier method and compared using a log-rank test.

Results

In the 41 patients included, common co-occurring alterations with STK11 were KRAS (54%), TP53 (44%), CDKN2A (37%) and KEAP1 (27%). Overall 17 patients received locoregional therapy with surgery or radiation with median OS of 8.6 years and there was no significant difference in clinical outcomes with KRAS and TP53 co-occurring mutations. Response to both chemotherapy and immunotherapy was poor across all co-occurring mutations. However, TP53 co-mutation was associated with improved clinical benefit with immunotherapy. Patients with higher TMB had longer PFS with immunotherapy. In TCGA survival analysis, tumors with STK11 mutation with or without KRAS co-mutation were associated with worse survival (P<0.05) but tumors with STK11/TP53 co-mutation did not have worst survival compared to STK11 wild type tumors. Moreover, co-occurring mutations had significant effect on intratumoral immune status with both STK11 alone and STK11/KRAS co-mutated tumors showing more enrichment for wound healing immune subtype while STK11/TP53 co-mutated tumors showed more enrichment for IFN-g immune subtype.

Conclusions

Our retrospective analysis in patients with STK11-mutated NSCLC found that both TMB and co-occurring mutations may be predictors for response to immunotherapy with worse outcomes in patients with low TMB or KRAS co-mutation and improved outcomes with TP53 co-mutation. Patients with STK11-mutated NSCLC also demonstrate chemotherapy resistance but have similar outcomes with localized treatment compared to STK11 wild type tumors. Moreover, co-mutations with KRAS or TP53 significantly alter tumor immune landscape of STK11-mutated tumors and therefore response to immunotherapy.

Genome-wide CRISPR/Cas9 screening for therapeutic targets in NSCLC carrying wild-type TP53 and receptor tyrosine kinase genes

Background

Targeted drugs have greatly improved the therapeutic outcome of non‐small cell lung cancer (NSCLC) patients compared with conventional chemotherapy, whereas about one‐third of patients are so far not suitable for targeted therapy due to lack of known driver oncogenes such as a mutated receptor tyrosine kinase (RTK) genes. In this study, we aimed to identify therapeutic targets for this subgroup of NSCLC patients.

Methods

We performed genome‐wide CRISPR/Cas9 screens in two NSCLC cell lines carrying wild‐type TP53 and receptor tyrosine kinase (wtTP53‐RTK) genes using a GeCKO v2.0 lentiviral library (containing 123411 sgRNAs and targeting 19050 genes). MAGeCKFlute was used to analyse and identify candidate genes. Genetic perturbation and pharmacological inhibition were used to validate the result in vitro and in vivo.

Results

The Genome‐wide CRISPR/Cas9 screening identified MDM2 as a potential therapeutic target for wtTP53‐RTK NSCLC. Genetic and pharmacological inhibition of MDM2 reduced cell proliferation and impaired tumour growth in the xenograft model, thus confirming the finding of the CRISPR/Cas9 screening. Moreover, treatment by a selective MDM2 inhibitor RG7388 triggered both cell cycle arrest and apoptosis in several NSCLC cell lines. Additionally, RG7388 and pemetrexed synergistically blocked the cell proliferation and growth of wtTP53‐RTK tumours but had limited effects for other genotypes.

Conclusions

We identified MDM2 as an essential gene and a potential therapeutic target in wtTP53‐RTK NSCLC via a genome‐wide CRISPR/Cas9 screening. For this subgroup, treatment by RG7388 alone or by its combination with pemetrexed resulted in significant tumour inhibition.

A Somatic Mutation Signature Predicts the Best Overall Response to Anti-programmed Cell Death Protein-1 Treatment in Epidermal Growth Factor Receptor/Anaplastic Lymphoma Kinase-Negative Non-squamous Non-small Cell Lung Cancer

Background

We aimed to exploit a somatic mutation signature (SMS) to predict the best overall response to anti-programmed cell death protein-1 (PD-1) therapy in non-small cell lung cancer (NSCLC).

Methods

Tumor samples of 248 patients with epidermal growth factor receptor (EGFR)/anaplastic lymphoma kinase (ALK)-negative non-squamous NSCLC treated with anti-PD-1 were molecularly tested by targeted next-generation sequencing or whole exome sequencing. On the basis of machine learning, we developed and validated a predictive model named SMS using the training (n = 83) and validation (n = 165) cohorts.

Results

The SMS model comprising a panel of 15 genes (TP53, PTPRD, SMARCA4, FAT1, MGA, NOTCH1, NTRK3, INPP4B, KMT2A, PAK1, ATRX, BCOR, KDM5C, DDR2, and ARID1B) was built to predict best overall response in the training cohort. The areas under the curves of the training and validation cohorts were higher than those of tumor mutational burden and PD-L1 expression. Patients with SMS-high in the training and validation cohorts had poorer progression-free survival [hazard ratio (HR) = 6.01, P < 0.001; HR = 3.89, P < 0.001] and overall survival (HR = 7.60, P < 0.001; HR = 2.82, P < 0.001) than patients with SMS-low. SMS was an independent factor in multivariate analyses of progression-free survival and overall survival (HR = 4.32, P < 0.001; HR = 3.07, P < 0.001, respectively).

Conclusion

This study revealed the predictive value of SMS for immunotherapy best overall response and prognosis in EGFR/ALK-negative non-squamous NSCLC as a potential biomarker in anti-PD-1 therapy.

Deep Sequencing of Plasma Exosomal microRNA Level in Psoriasis Vulgaris Patients

Psoriasis is a chronic skin disease affecting 1% to 3% of the world population. Psoriasis vulgaris (PV) is the most common form of psoriasis. PV patients suffer from inflamed, pruritic and painful lesions for years (even a lifetime). However, conventional drugs for PV are costly. Considering the need for long-term treatment of PV, it is urgent to discover novel biomarkers and therapeutic targets. Plasma exosomal miRNAs have been identified as the reliable biomarkers and therapy targets of human diseases. Here, we described the levels of serum exosomal miRNAs in PV patients and analyzed the functional features of differently expressed miRNAs and their potential target genes for the first time. We identified 1182 miRNAs including 336 novel miRNAs and 246 differently expressed miRNAs in serum exosomes of healthy people and PV patients. Furthermore, the functional analysis found differently expressed miRNA-regulated target genes enriched for specific GO terms including primary metabolic process, cellular metabolic process, metabolic process, organic substance metabolic process, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway containing cellular processes, human diseases, metabolic pathways, metabolism and organismal systems. In addition, we found that some predicted target genes of differentially expressed miRNAs, such as CREB1, RUNX2, EGFR, are both involved in inflammatory response and metabolism. In summary, our study identifies many candidate miRNAs involved in PV, which could provide potential biomarkers for diagnosis of PV and targets for clinical therapies against PV.

A Prognostic Gene Signature for Hepatocellular Carcinoma

Hepatocellular carcinoma is the third most common cause of cancer-related deaths in China and immune-based therapy can improve patient outcomes. In this study, we investigated the relationship between immunity-associated genes and hepatocellular carcinoma from the prognostic perspective. The data downloaded from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) and the Gene Expression Omnibus (GEO) was screened for gene mutation frequency using the maftools package. Immunity-associated eight-gene signature with strong prognostic ability was constructed and proved as an independent predictor of the patient outcome in LIHC. Seven genes in the immune-related eight-gene signature were strongly associated with the infiltration of M0 macrophages, resting mast cells, and regulatory T cells. Our research may provide clinicians with a quantitative method to predict the prognosis of patients with liver cancer, which can assist in the selection of the optimal treatment plan.

Integrated Multi-Omics Analysis Identified PTPRG and CHL1 as Key Regulators of Immunophenotypes in Clear Cell Renal Cell Carcinoma(ccRCC)

Despite the increasing importance and status of immune checkpoint blockade (ICB), little is known about the underlying molecular mechanisms determining the target clear cell renal cell carcinoma (ccRCC) population. In this study, we screened out 6 immune cells strongly correlated with expression levels of PD-L1 and IFN-γ based on the ccRCC samples extracted from GSE and TCGA data sets. By performing unsupervised clustering and lasso regression analysis, we grouped the ccRCC into 4 clusters and selected the two most distinct sub-clusters for further investigation-cluster A1 and B1. Next, we compared the two clusters in terms of mRNA, somatic mutations, copy number variations, DNA methylation, miRNA, lncRNA and constructed the differentially expressed genes (DEGs) hub by combing together the previous results at levels of DNA methylation, miRNA, and lncRNA. PTPRG and CHL1 were identified as key nodes in the regulation hub of immunophenotypes in ccRCC patients. Finally, we established the prognosis model by using Lasso-Cox regression and Kaplan-Meier analysis, recognizing WNT2, C17orf66, and PAEP as independent significant risk factors while IRF4 as an independent protective factor.

Immunotherapy Mechanism of Esophageal Squamous Cell Carcinoma with the Effect of STK11/AMPK Signaling Pathway

This study was aimed at exploring the mechanism of serine threonine protein kinase 11 (STK11)/Adenosine 5'-monophosphate-activated protein kinase (AMPK) signaling pathway after immunotherapy for esophageal squamous cell carcinoma (ESCC), providing basic information for the clinical treatment of ESCC. In this study, tissue specimens from 100 patients with ESCC who underwent surgical treatment in Taizhou People's Hospital (group A) and 20 patients with recurrent or metastatic ESCC who received second-line immunotherapy (group B) were collected. The real-time fluorescent quantitative polymerase chain reaction (PCR) (RT-qPCR) technology was used to detect the expression levels of STK11, interferon-γ (IFN-γ), interleukin 6 (IL-6), and vascular endothelial growth factor (VEGF) in the tissues. The immunohistochemical staining was used to detect the positive expression levels (PELs) of STK11 and AMPKα in the tissues, and immunofluorescence staining was used to detect the PELs Teff cells (CD3 and CD8), Treg cells (CD4 and FOXP3), and neutrophils (CD68 and CD163). RT-qPCR results showed that the expression levels of STK11 and IFN-γ in group A were obviously lower, and those of IL-6 and VEGF were much higher in contrast to group B (P < 0.05). The results of immunohistochemical staining showed that the number of STK11- and AMPKα-positive staining cells in group A was dramatically less than that in group B (P <0.05). The results of immunofluorescence staining revealed that the number of positive staining cells for Teff cells, Treg cells, and neutrophils in group A was also less dramatically than that in group B (P <0.05). In summary, immunotherapy can play a therapeutic effect on ESCC by regulating STK11/AMPK pathway and immune cell infiltration.

Correlation of KRAS G12C Mutation and High PD-L1 Expression with Clinical Outcome in NSCLC Patients Treated with Anti-PD1 Immunotherapy

BACKGROUND

Immune checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 improved the survival of non-small cell lung cancer (NSCLC) patients with PD-L1 expression ≥50% and without alterations in EGFR, ALK, ROS1, RET. However, markers able to predict the efficacy of ICIs, in combination with PD-L1 expression are still lacking. Our aim in this hypothesis-generating pilot study was to evaluate whether the KRAS G12C variant may predict the efficacy of ICIs in advanced NSCLC patients with PD-L1 ≥ 50%.

METHODS

Genomic DNA or tissue sections of 44 advanced ICI-treated NSCLC cases with PD-L1 ≥ 50% without EGFR, ALK, ROS1, RET alterations were tested using Next Generation Sequencing, Fluorescence in Situ Hybridization and immunohistochemistry. Statistical analyses were carried out fitting univariate and multivariate time to event models.

RESULTS

KRAS G12C mutant patients (N = 11/44) showed a significantly longer progression-free survival (PFS) at univariate and multivariate analyses (p = 0.03). The Kaplan-Meier plot of the PFS time-to-event supports that G12C positive patients have a longer time to progress. PFS improvement was not observed when any KRAS mutations were compared to wild-type cases.

CONCLUSIONS

Given the limitations due to the small sample size and exploratory nature of this study, we tentatively conclude the KRAS G12C mutation should be considered in future trials as a predictive marker of prolonged response to first-line ICIs in NSCLC patients overexpressing PD-L1. This finding could be relevant as anti-KRAS G12C therapies enter the therapeutic landscape of NSCLC.

Diminished Efficacy of Programmed Death-(Ligand)1 Inhibition in STK11- and KEAP1-Mutant Lung Adenocarcinoma Is Affected by KRAS Mutation Status

INTRODUCTION

STK11 and KEAP1 mutations (STK11 mutant [STK11MUT] and KEAP1MUT) are among the most often mutated genes in lung adenocarcinoma (LUAD). Although STK11MUT has been associated with resistance to programmed death-(ligand)1 (PD-[L]1) inhibition in KRASMUT LUAD, its impact on immunotherapy efficacy in KRAS wild-type (KRASWT) LUAD is currently unknown. Whether KEAP1MUT differentially affects outcomes to PD-(L)1 inhibition in KRASMUT and KRASWT LUAD is also unknown.

METHODS

Clinicopathologic and genomic data were collected from September 2013 to September 2020 from patients with advanced LUAD at the Dana-Farber Cancer Institute/Massachusetts General Hospital cohort and the Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center cohort. Clinical outcomes to PD-(L)1 inhibition were analyzed according to KRAS, STK11, and KEAP1 mutation status in two independent cohorts. The Cancer Genome Atlas transcriptomic data were interrogated to identify differences in tumor gene expression and tumor immune cell subsets, respectively, according to KRAS/STK11 and KRAS/KEAP1 comutation status.

RESULTS

In the combined cohort (Dana-Farber Cancer Institute/Massachusetts General Hospital + Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center) of 1261 patients (median age = 61 y [range: 22-92], 708 women [56.1%], 1065 smokers [84.4%]), KRAS mutations were detected in 536 cases (42.5%), and deleterious STK11 and KEAP1 mutations were found in 20.6% (260 of 1261) and 19.2% (231 of 1202) of assessable cases, respectively. In each independent cohort and in the combined cohort, STK11 and KEAP1 mutations were associated with significantly worse progression-free (STK11 hazard ratio [HR] = 2.04, p < 0.0001; KEAP1 HR = 2.05, p < 0.0001) and overall (STK11 HR = 2.09, p < 0.0001; KEAP1 HR = 2.24, p < 0.0001) survival to immunotherapy uniquely among KRASMUT but not KRASWT LUADs. Gene expression ontology and immune cell enrichment analyses revealed that the presence of STK11 or KEAP1 mutations results in distinct immunophenotypes in KRASMUT, but not in KRASWT, lung cancers.

CONCLUSIONS

STK11 and KEAP1 mutations confer worse outcomes to immunotherapy among patients with KRASMUT but not among KRASWT LUAD. Tumors harboring concurrent KRAS/STK11 and KRAS/KEAP1 mutations display distinct immune profiles in terms of gene expression and immune cell infiltration.

Prognostic and Immunological Role of FAT Family Genes in Non-Small Cell Lung Cancer

Background

The FAT atypical cadherin 1/2/3/4 (FAT1/2/3/4) has been linked to the occurrence and development of various cancers. However, the prognostic and immunological role of FAT1/2/3/4 in non-small cell lung cancer (NSCLC) has not been clarified.

Methods

The association of FAT1/2/3/4 mutations with tumor mutation burden (TMB), tumor immunity in the microenvironment, and response to ICIs in NSCLC was investigated. Whole-exome sequencing data of lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) samples from the Cancer Genome Atlas (TCGA), and an immunotherapy data set comprising mutation and survival data of 75 NSCLC patients were analyzed. Two independent pan-cancer cohorts with large samples were used to validate the prognostic value of FAT1/2/3/4 mutations in immunotherapy.

Results

A high mutation rate of FAT1/2/3/4 (57.3%, 603/1052) was observed in NSCLC patients. TMB was significantly higher in samples with mutated FAT1/2/3/4 compared to samples with wildtype FAT1/2/3/4 (P < .05). FAT2 mutation was found to be an independent prognostic biomarker in LUAD. FAT1/2/3/4 were aberrantly expressed in LUAD and LUSC, and high FAT2 expression strongly correlated with high PD-L1 levels in LUAD. Moreover, LUAD patients with FAT1 mutations showed significantly high activated dendritic cells infiltration, whereas those with FAT2/3/4 mutations had high infiltration of CD8⁺ T-cells, M1 macrophages, activated memory CD4⁺ T-cells, and helper follicular T-cells. It was also observed that FAT1/2/4 mutations were significantly associated with better enhanced objective response and durable clinical benefit, whereas FAT1/2/3 mutations correlated with longer progression-free survival in ICI-treated NSCLC cohort. FAT1/4 mutations were related to better overall survival in pan-cancer patients treated with ICIs.

Conclusions

FAT family genes are potential prognostic and immunological biomarkers and correlate with response to ICIs in NSCLC.

Machine learning and bioinformatics analysis revealed classification and potential treatment strategy in stage 3-4 NSCLC patients

BACKGROUND

Precision medicine has increased the accuracy of cancer diagnosis and treatment, especially in the era of cancer immunotherapy. Despite recent advances in cancer immunotherapy, the overall survival rate of advanced NSCLC patients remains low. A better classification in advanced NSCLC is important for developing more effective treatments.

METHOD

The calculation of abundances of tumor-infiltrating immune cells (TIICs) was conducted using Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT), xCell (xCELL), Tumor IMmune Estimation Resource (TIMER), Estimate the Proportion of Immune and Cancer cells (EPIC), and Microenvironment Cell Populations-counter (MCP-counter). K-means clustering was used to classify patients, and four machine learning methods (SVM, Randomforest, Adaboost, Xgboost) were used to build the classifiers. Multi-omics datasets (including transcriptomics, DNA methylation, copy number alterations, miRNA profile) and ICI immunotherapy treatment cohorts were obtained from various databases. The drug sensitivity data were derived from PRISM and CTRP databases.

RESULTS

In this study, patients with stage 3-4 NSCLC were divided into three clusters according to the abundance of TIICs, and we established classifiers to distinguish these clusters based on different machine learning algorithms (including SVM, RF, Xgboost, and Adaboost). Patients in cluster-2 were found to have a survival advantage and might have a favorable response to immunotherapy. We then constructed an immune-related Poor Prognosis Signature which could successfully predict the advanced NSCLC patient survival, and through epigenetic analysis, we found 3 key molecules (HSPA8, CREB1, RAP1A) which might serve as potential therapeutic targets in cluster-1. In the end, after screening of drug sensitivity data derived from CTRP and PRISM databases, we identified several compounds which might serve as medication for different clusters.

CONCLUSIONS

Our study has not only depicted the landscape of different clusters of stage 3-4 NSCLC but presented a treatment strategy for patients with advanced NSCLC.

Genetic mutation profiles and immune microenvironment analysis of pulmonary enteric adenocarcinoma

BACKGROUND

Pulmonary enteric adenocarcinoma (PEAC) has distinctive clinical outcomes, radiographic, pathological and molecular characteristics. The prognosis of patients with PEAC was poor. However, molecular profiles and therapeutic biomarkers of PEAC remain elusive.

METHODS

In the present study, the hospitalized patients with PEAC admitted to Tongji Hospital in Wuhan from January 1, 2014 to November 20, 2020 were retrospectively enrolled and followed until December 10, 2020. Comprehensive genomic profiling of tumor tissue from the PEAC patients were performed and compared with lung adenocarcinoma, colorectal cancer and metastatic colorectal carcinoma. Tumor immune microenvironment analysis were evaluated.

RESULTS

There were 10 patients with PEAC enrolled. 70% of patients were male and the median age of onset was 63 years (interquartile range, 55-72). There were six early-stage patients (Stage IA to IIB) and four stage IV patients. Molecular analysis revealed the most common gene mutations included TP53 (57%, 4/7) and KRAS (57%, 4/7) mutations. There were 40% mutations occurred in genes encoding receptor tyrosine kinases (RTKs). 100% of patients (8/8) were microsatellite stability (MSS). The median level of TMB was 6.0 (interquartile range, 4.5-7.0) mutations/Mb. Three of 10 patients showed low PD-L1 expression (tumor proportion score < 10%) and the others were PD-L1 negative. A small subset of CD8+, CD3+, CD68+ T cells were observed and were mainly distributed in the cancer stroma.

CONCLUSION

This study demonstrated that PEAC was characterized by low-frequency RTK gene mutation, high KRAS mutation, low PD-L1 expression, low TMB, and low CD8+ T cells infiltration.

Multi-omics data identified TP53 and LRP1B as key regulatory gene related to immune phenotypes via EPCAM in HCC

Background

Many studies showed that the prognosis of hepatocellular carcinoma (HCC) was significantly associated with the expressions of TP53 and LRP1B. However, the potential influence of the two genes on the malignant progression of HCC is still to be expounded.

Methods

According to the correlation analysis between immune cells and expression levels of TP53 and LRP1B, we filtered the immune cells to perform unsupervised clustering analysis. Integration of multi‐omic data analysis identified genetic alteration and epigenetic alteration. In addition, pathway analysis was used to explore the potential function of the differentially expressed mRNAs. According to the differentially expressed genes, we established an interaction network to seek the hub gene. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to build a prognosis model.

Results

The unsupervised clustering analysis showed that the cluster A1 showed the highest immune cell levels and the cluster B2 showed the lowest immune cell levels. Multi‐omics data analysis identified that somatic mutations, copy number variations, and DNA methylation levels had significant differences between cluster A1 and cluster B2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that the upregulated mRNAs in the cluster A1 were mainly concentrated in T cell activation, external side of plasma membrane, receptor ligand activity, and cytokine−cytokine receptor interaction. Importantly, the EPCAM was identified as a critical node in the lncRNAs–miRNAs–mRNAs regulatory network correlated with the immune phenotypes. In addition, based on differentially expressed genes between cluster A1 and cluster B2, the prognostic model established by LASSO could predict the overall survival (OS) of HCC accurately.

Conclusions

The results indicated that the TP53 and LRP1B acted as the key genes in regulating the immune phenotypes of HCC via EPCAM.

Camrelizumab for the treatment of advanced cervical adenocarcinoma: a case report and literature review

Cervical adenocarcinoma belongs to an invasive subtype of cervical carcinoma, presenting poorly prognostic status. Chemotherapy treatment for recurrent cervical carcinoma are thought to be limited and supposed to be noncurative. Because of the poor prognosis of patients with recurrent cervical carcinoma, however, the benefits of second-line chemotherapy have not yet reached a consensus. Immunotherapy is a split-new tactic of overwhelming carcinomas that relies on the instinct of the immune system to recognize and directly kill neoplasm cells. Here, we reported a 55-year-old female patient with clinical stage IVB cervical adenocarcinoma. The patient received four cycles of systematic therapy, with the regimen of docetaxel plus carboplatin in combined with bevacizumab anti-vascular therapy. The progressive disease (PD) was assessed by imaging evaluation and PD was confirmed once more after four cycles of chemotherapy of albumin paclitaxel plus cisplatin. The patient exhibited a good response during the twelve-cycle of immunotherapy of Camrelizumab, whereas PD was observed upon termination of her immunotherapy. This case with the treatment of PD-1 inhibitor Camrelizumab exhibits a good curative effect and tolerable adverse reactions. In addition, some clinical markers and biomarkers expression levels can be served as the predictors of the effect of anti-PD-1 immunotherapy.

Rare Hereditary Gynecological Cancer Syndromes

Hereditary cancer syndromes, which are characterized by onset at an early age and an increased risk of developing certain tumors, are caused by germline pathogenic variants in tumor suppressor genes and are mostly inherited in an autosomal dominant manner. Therefore, hereditary cancer syndromes have been used as powerful models to identify and characterize susceptibility genes associated with cancer. Furthermore, clarification of the association between genotypes and phenotypes in one disease has provided insights into the etiology of other seemingly different diseases. Molecular genetic discoveries from the study of hereditary cancer syndrome have not only changed the methods of diagnosis and management, but have also shed light on the molecular regulatory pathways that are important in the development and treatment of sporadic tumors. The main cancer susceptibility syndromes that involve gynecologic cancers include hereditary breast and ovarian cancer syndrome as well as Lynch syndrome. However, in addition to these two hereditary cancer syndromes, there are several other hereditary syndromes associated with gynecologic cancers. In the present review, we provide an overview of the clinical features, and discuss the molecular genetics, of four rare hereditary gynecological cancer syndromes; Cowden syndrome, Peutz-Jeghers syndrome, DICER1 syndrome and rhabdoid tumor predisposition syndrome 2.

Risk stratification of lung adenocarcinoma using a nomogram combined with ferroptosis-related LncRNAs and subgroup analysis with immune and N6-methyladenosine modification

Background

Determining the prognosis of lung adenocarcinoma (LUAD) is challenging. The present study aimed to identify prognostic ferroptosis-related long noncoding RNAs (FRLs) and construct a prognostic model. Moreover, differential analysis of immune and N6-methyladenosine (m6A)-related genes was systematically conducted.

Methods

A total of 504 patients selected from a dataset from The Cancer Genome Atlas were included. The patients with LUAD were randomly divided into a training group and a test group at a ratio of 1:1. Pearson correlation analysis and univariate Cox regression analysis were used to identify the prognostic FRLs. Then, a prognostic model was constructed from the optimized subset of prognostic FRLs based on the least absolute shrinkage and selection operator (LASSO) algorithm. Subsequently, the receiver operating characteristic (ROC) curve and survival analysis were used to evaluate the performance of the model. The risk score based on the prognostic model was analyzed using Cox regression analysis. Moreover, gene set enrichment analysis and differential analysis of immune- and m6A-related genes were conducted.

Results

After univariate Cox regression analysis and LASSO algorithm analysis, a total of 19 prognostic FRLs were selected to construct the final model to obtain the risk score. The area under the ROC curve of the prognostic model for 1-year, 3-year, and 5-year overall survival (OS) was 0.763, 0.745, and 0.778 in the training set and 0.716, 0.724, and 0.736 in the validation set, respectively. Moreover, the OS of the high-risk group was significantly worse than that of the low-risk group in the training group (P < 0.001) and in the test group (P < 0.001). After univariate and multivariate Cox regression analysis, the risk score [hazard ratio (HR) = 1.734; P < 0.001] and stage (HR = 1.557; P < 0.001) were both considered significant prognostic factors for LUAD. A nomogram was constructed based on clinical features and risk score. The expression of 34 checkpoint genes and 13 m6A-related genes varied significantly between the two risk groups.

Conclusion

This study constructed a prognostic model to effectively predict the OS of patients with LUAD, and these OS-related FRLs might serve as potential therapeutic targets of LUAD.

Immunotherapy in Lung Cancer: Are the Promises of Long-Term Benefit Finally Met?

Over the last few years, agents targeting immune checkpoints have shown potential to improve therapeutic outcomes in patients with lung cancer in multiple clinical settings. Inhibitors of PD-1/PD-L1 have been approved for the treatment of different types of lung cancer by the FDA either alone or in combination with chemotherapy or other immune checkpoint inhibitors, such as anti-CTLA-4 agents. The introduction of these agents in clinical practice has revolutionized the therapeutic approach to lung cancer, keeping the promises of long-term benefit in selected patient populations. The therapeutic indications of immunotherapy in lung cancer are rapidly growing, and multiple combinations entered clinical practice or are under active development. Furthermore, the quest for a reliable predictive biomarker is still ongoing to overcome the limits of currently approved tests for patients' selection. In this review, we summarized the current status and progress of anti-PD-1/PD-L1 agents in lung cancer treatment.

Driver mutations of intrahepatic cholangiocarcinoma shape clinically relevant genomic clusters with distinct molecular features and therapeutic vulnerabilities

Purpose: To establish a clinically applicable genomic clustering system, we investigated the interactive landscape of driver mutations in intrahepatic cholangiocarcinoma (ICC). Methods: The genomic data of 1481 ICCs from diverse populations was analyzed to investigate the pair-wise co-occurrences or mutual exclusivities among recurrent driver mutations. Clinicopathological features and outcomes were compared among different clusters. Gene expression and DNA methylation profiling datasets were analyzed to investigate the molecular distinctions among mutational clusters. ICC cell lines with different gene mutation backgrounds were used to evaluate the cluster specific biological behaviors and drug sensitivities. Results: Statistically significant mutation-pairs were identified across 21 combinations of genes. Seven most recurrent driver mutations (TP53, KRAS, SMAD4, IDH1/2, FGFR2-fus and BAP1) showed pair-wise co-occurrences or mutual exclusivities and could aggregate into three genetic clusters: Cluster1: represented by tripartite interaction of KRAS, TP53 and SMAD4 mutations, exhibited large bile duct histological phenotype with high CA19-9 level and dismal prognosis; Cluster2: co-association of IDH/BAP1 or FGFR2-fus/BAP1 mutation, was characterized by small bile duct phenotype, low CA19-9 level and optimal prognosis; Cluster3: mutation-free ICC cases with intermediate clinicopathological features. These clusters showed distinct molecular traits, biological behaviors and responses to therapeutic drugs. Finally, we identified S100P and KRT17 as "cluster-specific", "lineage-dictating" and "prognosis-related" biomarkers, which in combination with CA19-9 could well stratify Cluster3 ICCs into two biologically and clinically distinct subtypes. Conclusions: This clinically applicable clustering system can be instructive to ICC prognostic stratification, molecular classification, and therapeutic optimization.

The role of distinct co-mutation patterns with TP53 mutation in immunotherapy for NSCLC

TP53 mutations was reported to be correlated to the efficacy of program death-1 (PD-1) and program death ligand-1 (PD-L1). The role of co-mutations of TP53 with other recurrently mutated genes in outcome of anti-PD-(L)1 treatment for non-small cell lung cancer (NSCLC) is unknown. Here we mined a previously generated dataset to address the effect of co-mutations on the progression free survival (PFS) of NSCLC patients. Non-synonymous mutations and clinical data of 240 NSCLC patients with anti-PD-(L)1 based therapy was downloaded from cBioPortal. Totally 206 patients received monotherapy and 34 patients received combination therapy. In 240 NSCLC patients, TP53 mutation rate was 59.2%. For the monotherapy cohort, TP53 mutated NSCLC patients have a significantly longer PFS (4.3 vs. 2.5 months, P = 0.0019) compared with TP53 wild type NSCLC patients. The same tendency was also observed in the combination therapy cohort, but the difference in PFS (6.3 vs. 5.4 months, P = 0.12) was not significant. Ever-smoker had a longer PFS compared to never-smokers (4.0 vs. 2.7 months). For further co-mutation analysis with TP53 including KEAP1 mutation (53/240, 22.1%), KMT3C mutation (26/240, 10.8%), STK11 mutation (56/240, 23.3%), EGFR mutation (28/240, 11.7%) and KRAS mutation (86/240, 35.8%). Patients with both TP53 plus KEAP1 mutations in all 240 patients had a longer PFS compared with co-wild population (PFS 9.2 vs. 4.2 months, P = 0.012) when treated with PD-1/PD-L1 inhibitors. TP53 might be the dominating mutation correlating with longer PFS in PD-1/PD-L1 monotherapy. Different genes displayed distinct effect when co-mutated with TP53 in NSCLC patients.

Molecular Signatures of KRAS-Mutated Lung Adenocarcinoma: Analysis of Concomitant EGFR, ALK, STK11, and PD-L1 Status

Background

KRAS mutations are the most common oncogenic driver mutations of non-small cell lung cancer (NSCLC) in the Western world. Mutations of the KRAS gene are most prevalent in the patient population of current and former cigarette smokers. With the recent pivotal approval of a targeted inhibitor therapy for patients with KRAS p.G12C mutated and pretreated NSCLC, analysis of the heterogeneity of KRAS mutations and concomitant molecular alterations in patients with these tumors at all clinical stages is indicated.

Methods

In this retrospective analysis, patient pathology records were reviewed for all cases receiving a pathologic diagnosis of NSCLC within our hospital system. All data were collected with IRB approval. Cases of indeterminate tumor type favoring a non-lung primary, as well as non-adenocarcinoma NSCLC (eg, squamous) were excluded from the cohort. In this hospital system, molecular testing for KRAS mutations is part of a molecular biomarker panel that is reflex ordered at initial diagnosis by the pathologist and may be performed as a single gene test or as a solid organ cancer hotspot panel by next generation sequencing. For each patient, KRAS mutational status and specific KRAS mutations, if present, were collated. Additional information assessed for this study included patient demographics (age, gender, and smoking history), tumor staging if available, PD-L1 expression levels by immunohistochemistry (IHC), and the presence of other genetic alterations (EGFR, ALK, and STK11).

Results

Between January 1, 2017 and January 1, 2019, there were 276 patients diagnosed with NSCLC of all stages who had KRAS mutational analysis performed in our hospital system and who met the criteria for inclusion into the study cohort. A KRAS driver mutation was detected in 29% of these patients. The most frequently identified KRAS mutation was p.G12C (38%), followed by p.G12D (21%) and p.G12V (13%). KRAS-mutated lung adenocarcinoma was significantly associated with current or former patient smoking status in this cohort (29/202 (14%) smokers and 1/74 (1%) non-smokers; P = .0006). PD-L1 expression of at least 1% by IHC was present in 43% of KRAS-mutated lung adenocarcinomas and 45% of non-KRAS-mutated adenocarcinomas. In this study, KRAS mutations were not found to co-occur with gene alterations in EGFR, ALK, or STK11. In 48% of cases, at least one genetic alteration (KRAS, ALK, EGFR, or STK11) was identified.

Conclusions

In this study cohort, KRAS-mutated lung adenocarcinoma demonstrated significant mutational heterogeneity, which is consistent with previously published studies. KRAS mutational status was also significantly associated with a current or former smoking history. Notably, p.G12C was the most frequently identified KRAS mutation in this cohort, with a frequency of 38%. This finding is particularly relevant given the recent approval of a KRAS p.G12C-specific targeted inhibitor therapy and the continued development of additional KRAS targeted therapies that may prove effective in treating NSCLC. These findings also highlight the necessity of considering molecular testing for KRAS mutations in patients with NSCLC and a smoking history, as this population most frequently harbors KRAS mutations and may benefit from these emerging targeted therapies.

Molecular charcterization of lung adenocarcinoma combining whole exome sequencing, copy number analysis and gene expression profiling

INTRODUCTION

Lung cancer is the leading cause of cancer mortality worldwide; lung adenocarcinoma (LUAD) corresponds to about 40% of lung cancers. LUAD is a genetically heterogeneous disease and the definition of this heterogeneity is of fundamental importance for prognosis and treatment.

AREAS COVERED

Based on primary literature, this review provides an updated analysis of multiomics studies based on the study of mutation profiling, copy number alterations and gene expression allowing for definition of molecular subgroups, prognostic factors based on molecular biomarkers, and identification of therapeutic targets. The authors sum up by providing the reader with their expert opinion on the potentialities of multiomics analysis of LUADs.

EXPERT OPINION

A detailed and comprehensive study of the co-occurring genetic abnormalities characterizing different LUAD subsets represents a fundamental tool for a better understanding of the disease heterogeneity and for the identification of subgroups of patients responding or resistant to targeted treatments and for the discovery of new therapeutic targets. It is expected that a comprehensive characterization of LUADs may provide a fundamental contribution to improve the survival of LUAD patients.

The value of cell-free circulating tumour DNA profiling in advanced non-small cell lung cancer (NSCLC) management

Liquid biopsy (LB) has boosted a remarkable change in the management of cancer patients by contributing to tumour genomic profiling. Plasma circulating cell-free tumour DNA (ctDNA) is the most widely searched tumour-related element for clinical application. Specifically, for patients with lung cancer, LB has revealed valuable to detect the diversity of targetable genomic alterations and to detect and monitor the emergence of resistance mechanisms. Furthermore, its non-invasive nature helps to overcome the difficulty in obtaining tissue samples, offering a comprehensive view about tumour diversity. However, the use of the LB to support diagnostic and therapeutic decisions still needs further clarification. In this sense, this review aims to provide a critical view of the clinical importance of plasma ctDNA analysis, the most widely applied LB, and its limitations while anticipating concepts that will intersect the present and future of LB in non-small cell lung cancer patients.

Graphical Abstract

Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification

Immunotherapy is a mainstay of non-small cell lung cancer (NSCLC) management. While tumor mutational burden (TMB) correlates with response to immunotherapy, little is known about the relationship between the baseline immune response and tumor genotype. Using single-cell RNA sequencing, we profiled 361,929 cells from 35 early-stage NSCLC lesions. We identified a cellular module consisting of PDCD1⁺CXCL13⁺ activated T cells, IgG⁺ plasma cells, and SPP1⁺ macrophages, referred to as the lung cancer activation module (LCAM^hi). We confirmed LCAM^hi enrichment in multiple NSCLC cohorts, and paired CITE-seq established an antibody panel to identify LCAM^hi lesions. LCAM presence was found to be independent of overall immune cell content and correlated with TMB, cancer testis antigens, and TP53 mutations. High baseline LCAM scores correlated with enhanced NSCLC response to immunotherapy even in patients with above median TMB, suggesting that immune cell composition, while correlated with TMB, may be a nonredundant biomarker of response to immunotherapy.

Dual Role of p73 in Cancer Microenvironment and DNA Damage Response

Understanding the mechanisms that regulate cancer progression is pivotal for the development of new therapies. Although p53 is mutated in half of human cancers, its family member p73 is not. At the same time, isoforms of p73 are often overexpressed in cancers and p73 can overtake many p53 functions to kill abnormal cells. According to the latest studies, while p73 represses epithelial–mesenchymal transition and metastasis, it can also promote tumour growth by modulating crosstalk between cancer and immune cells in the tumor microenvironment, M2 macrophage polarisation, Th2 T-cell differentiation, and angiogenesis. Thus, p73 likely plays a dual role as a tumor suppressor by regulating apoptosis in response to genotoxic stress or as an oncoprotein by promoting the immunosuppressive environment and immune cell differentiation.

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.

Impact of cancer cell-intrinsic features on neutrophil behavior

Neutrophils are multifaceted innate immune cells that play a significant role in the progression of cancer by exerting both pro- and anti-tumorigenic functions. The crosstalk between cancer cells and neutrophils is complex and emerging evidence is pointing at cancer cell-intrinsic programs regulating neutrophil abundance, phenotype and function. Cancer cell-derived soluble mediators are key players in modulating the interaction with neutrophils. Here, we review how intrinsic features of cancer cells, including cancer cell genetics, epigenetics, signaling, and metabolism, manipulate neutrophil behavior and how to target these processes to impact cancer progression. A molecular understanding of cancer cell-intrinsic properties that shape the crosstalk with neutrophils will provide novel therapeutic strategies for personalized immunomodulation in cancer patients.

PD-1/PD-L1-Associated Immunoarchitectural Patterns Stratify Pancreatic Cancer Patients into Prognostic/Predictive Subgroups

Immunotherapy, including PD-1/PD-L1 agonists, has shown limited efficacy in pancreatic ductal adenocarcinoma (PDAC). We examined the PD-1/PD-L1 expression and immunoarchitectural features by automated morphometric analysis using multiplex immunofluorescence and 118 microsatellite-stable, treatment-naïve, surgically resected PDACs (study cohort). Five microsatellite-instable cases were stained in parallel (MSI cohort). Molecular analysis was additionally performed. An independent PDAC cohort (n = 226) was immunostained for PD-L1 and used as a validation cohort. PD-L1 expression on tumor cells (TC) and/or immune cells (IC) was present in 32% and 30% of the study and validation cohorts, respectively, and assigned into one of four patterns: "adaptive-1" (TC: 0, IC > 1%), "adaptive-2" (TC > 1% to < 25%, IC > 1%), "constitutive" (TC ≥ 25%, IC: 0), and "combined" (TC ≥ 25%, IC > 1%). "Constitutive" tumors were characterized by reduced numbers of all ICs and poor outcome. In contrast, "adaptive-1" tumors exhibited abundant T cells, including high counts of cytotoxic CD3+CD8+ and PD-1+CD3+CD8+ cells, but low counts of PD-L1+CD3+CD8+ cells and associated with the best outcome. "Adaptive-2" tumors displayed higher proportions of PD-L1+CD3+CD8+ T cells and tumor-associated macrophages (CD68+ and CD68+CD206+) compared with "adaptive-1" tumors. In the "combined" pattern, extensive PD-L1 expression on TCs was accompanied by increased numbers of T cells and improved overall survival. ICs were closer to PD-L1- than to PD-L1+ PDAC cells. TP53 and PIK3CA alterations tended to be more frequent in PD-L1+ tumors. The 5 MSI cases were PD-L1- The distinct PD-1/PD-L1-associated immunoarchitectural patterns underpin the heterogeneity of the immunologic responses and might be used to inform patient outcomes and therapeutic decisions in pancreatic cancer.

Characterization of KRAS Mutation Subtypes in Non-small Cell Lung Cancer

KRAS is the most commonly mutated oncogene in NSCLC and development of direct KRAS inhibitors has renewed interest in this molecular variant. Different KRAS mutations may represent a unique biologic context with different prognostic and therapeutic impact. We sought to characterize genomic landscapes of advanced, KRAS-mutated non-small cell lung cancer (NSCLC) in a large national cohort to help guide future therapeutic development.Molecular profiles of 17,095 NSCLC specimens were obtained using DNA next-generation sequencing of 592 genes (Caris Life Sciences) and classified on the basis of presence and subtype of KRAS mutations. Co-occurring genomic alterations, tumor mutational burden (TMB), and PD-L1 expression [22C3, tumor proportion score (TPS) score] were analyzed by KRAS mutation type.Across the cohort, 4,706 (27.5%) samples harbored a KRAS mutation. The most common subtype was G12C (40%), followed by G12V (19%) and G12D (15%). The prevalence of KRAS mutations was 37.2% among adenocarcinomas and 4.4% in squamous cell carcinomas. Rates of high TMB (≥10 mutations/Mb) and PD-L1 expression varied across KRAS mutation subtypes. KRAS G12C was the most likely to be PD-L1 positive (65.5% TPS ≥ 1%) and PD-L1 high (41.3% TPS ≥ 50%). STK11 was mutated in 8.6% of KRAS wild-type NSCLC but more frequent in KRAS-mutant NSCLC, with the highest rate in G13 (36.2%). TP53 mutations were more frequent in KRAS wild-type NSCLC (73.6%).KRAS mutation subtypes have different co-occurring mutations and a distinct genomic landscape. The clinical relevance of these differences in the context of specific therapeutic interventions warrants investigation.

Deep Learning Predicts EBV Status in Gastric Cancer Based on Spatial Patterns of Lymphocyte Infiltration

EBV infection occurs in around 10% of gastric cancer cases and represents a distinct subtype, characterized by a unique mutation profile, hypermethylation, and overexpression of PD-L1. Moreover, EBV positive gastric cancer tends to have higher immune infiltration and a better prognosis. EBV infection status in gastric cancer is most commonly determined using PCR and in situ hybridization, but such a method requires good nucleic acid preservation. Detection of EBV status with histopathology images may complement PCR and in situ hybridization as a first step of EBV infection assessment. Here, we developed a deep learning-based algorithm to directly predict EBV infection in gastric cancer from H&E stained histopathology slides. Our model can not only predict EBV infection in gastric cancers from tumor regions but also from normal regions with potential changes induced by adjacent EBV+ regions within each H&E slide. Furthermore, in cohorts with zero EBV abundances, a significant difference of immune infiltration between high and low EBV score samples was observed, consistent with the immune infiltration difference observed between EBV positive and negative samples. Therefore, we hypothesized that our model's prediction of EBV infection is partially driven by the spatial information of immune cell composition, which was supported by mostly positive local correlations between the EBV score and immune infiltration in both tumor and normal regions across all H&E slides. Finally, EBV scores calculated from our model were found to be significantly associated with prognosis. This framework can be readily applied to develop interpretable models for prediction of virus infection across cancers.

Cutaneous adverse reactions in a lung cancer patient treated with pembrolizumab: A case report

Lung cancer is the main cause of oncological death in the US and worldwide, constituting a significant public health problem. The incidence of lung cancer is on the increase. In the present study, the diagnostic process was carried out and treatment options were considered to determine the therapeutic response of a patient diagnosed with lung cancer. The case of an early stage lung cancer patient who benefited from surgical treatment was presented. The pathology report stated the complete diagnosis to be pleomorphic lung cancer with an adenocarcinoma component, pT2aN0M0, with focal positivity for thyroid transcription factor 1 (TTF1), without epidermal growth factor receptor (EGFR) mutations and ALK recombinations, having an initial clinical stage of IB and programmed death ligand-1 (PD-L1) positivity with a tumor proportion score of over 70%. The patient underwent radiotherapy treatment and was administered osteoclast inhibitors and immunotherapy, with no favorable therapeutic effect and with the presence of secondary cutaneous adverse effects to pembrolizumab. As a main cause of death, lung cancer registers a low general survival rate even in patients with targeted therapies or immunotherapy. By better identifying the patients at risk, one can establish a more efficient personalized treatment; the future objective of scientific studies is the follow-up of adverse effects of new therapies.

STK11/LKB1 Modulation of the Immune Response in Lung Cancer: From Biology to Therapeutic Impact

The STK11/LKB1 gene codes for liver kinase B1 (STK11/LKB1), a highly conserved serine/threonine kinase involved in many energy-related cellular processes. The canonical tumor-suppressive role for STK11/LKB1 involves the activation of AMPK-related kinases, a master regulator of cell survival during stress conditions. In pre-clinical models, inactivation of STK11/LKB1 leads to the progression of lung cancer with the acquisition of metastatic properties. Moreover, preclinical and clinical data have shown that inactivation of STK11/LKB1 is associated with an inert tumor immune microenvironment, with a reduced density of infiltrating cytotoxic CD8⁺ T lymphocytes, a lower expression of PD-(L)1, and a neutrophil-enriched tumor microenvironment. In this review, we first describe the biological function of STK11/LKB1 and the role of its inactivation in cancer cells. We report descriptive epidemiology, co-occurring genomic alterations, and prognostic impact for lung cancer patients. Finally, we discuss recent data based on pre-clinical models and lung cancer cohorts analyzing the results of STK11/LKB1 alterations on the immune system and response or resistance to immune checkpoint inhibitors.

Complete and Durable Response to Nivolumab in Recurrent Poorly Differentiated Pancreatic Neuroendocrine Carcinoma with High Tumor Mutational Burden

Poorly differentiated pancreatic neuroendocrine carcinomas (NECs) are rare and aggressive malignancies with rapid disease progression and early widespread metastasis. Given histology similarity, they are commonly treated with platinum-based chemotherapy as small cell lung cancer (SCLC). However, no standard treatment has been established for recurrent or progressive disease. We present an Asian patient with recurrent poorly differentiated pancreatic NEC after curative surgery and adjuvant chemotherapy with cisplatin and etoposide. The tumor mutational burden (TMB) was high. The patient received chemotherapy combined with maintenance immunotherapy with nivolumab and achieved promising and durable response, suggesting TMB could be a biomarker to identify NEC patients for immune checkpoint inhibitor (ICI) treatment.

Predictive Value of Max's Giant Associated Protein Mutation in Outcomes of Lung Adenocarcinoma Patients Treated With Immune Checkpoint Inhibitors

Treatment with immune checkpoint inhibitors (ICIs) has considerably improved prognosis in multiple cancers. However, regardless of PD-L1 expression and TMB, better predictive biomarkers are required to identify ICI-responsive patients. We analyzed a pan-cancer cohort as the discovery cohort to identify the role of Max’s giant associated protein (MGA) mutation in the outcome of ICI treatment in different types of cancers. A pooled lung adenocarcinoma (LUAD) cohort was considered as the validation cohort. Another two LUAD cohorts who received conventional treatment were included for prognostic analysis and mechanism exploration. In the discovery cohort, MGA mutation was a favorable survival biomarker for patients with LUAD than in those with other types of cancers. MGA mutation was positively correlated with the TMB score. The results of the validation cohort were consistent with those of the discovery cohort. Patients with MGA mutation in the TMB-low subgroup had longer survival. Two LUAD cohorts who received standard treatment showed that the MGA mutation was not a prognostic biomarker for standard treatment. Mechanically, we found that the co-mutant genes did not affect the prognostic role of MGA mutation. Gene-set enrichment analysis revealed that genes belonging to the immunodeficiency pathway were enriched in the MGA wild-type group in LUAD. Moreover, activated NK cells were more enriched in the MGA mutant LUAD group. In conclusion, our results demonstrated that MGA mutation was an independent predictive biomarker for ICI therapy. These results may provide a novel insight into identifying potential patients with LUAD for ICI therapy.

Tumor immune microenvironment in epidermal growth factor receptor-mutated non-small cell lung cancer before and after epidermal growth factor receptor tyrosine kinase inhibitor treatment: a narrative review

Objective

To review and summarize the characteristics of the tumor immune microenvironment (TIME) in EGFR-mutated non-small cell lung cancer (NSCLC) after EGFR-TKI treatment and its role in TKI resistance.

Background

Lung cancer is one of the most commonly diagnosed cancer and the leading cause of death from cancer in both men and women around the world. Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are considered a first-line treatment for EGFR-mutated NSCLC. However, almost all patients eventually develop acquired resistance to EGFR-TKIs, with a median progression-free survival (PFS) of 9–14 months. As immunotherapy has developed, it has become apparent that interactions between the TIME and tumor cells also affect EGFR-TKI treatment. The TIME comprises a variety of components but previous studies of the TIME following EGFR-TKI therapy of NSCLC are inconsistent. Here, we reviewed the characteristics of the TIME in NSCLC after EGFR-TKI treatment and its role in TKI resistance.

Methods

PubMed, Embase, and Web of Science were searched to July 1, 2021 with the following key words: “NSCLC”, “EGFR”, and “immunotherapy”.

Conclusions

The TIME of EGFR-mutated NSCLC is different from that of non-mutated NSCLC, an explanation for EGFR-mutated NSCLC displaying a poor response to ICIs. The TIME of EGFR-mutated NSCLC also changes during treatment with EGFR-TKIs. The TIME in EGFR-TKI-resistant lung cancer can be summarized as follows: (I) compared with EGFR-TKI-sensitive tumors, EGFR-TKI-resistant tumors have a greater number of immunosuppressive cells and fewer immune-activated cells, while the tumor microenvironment is in an immunosuppressive state; (II) tumor cells and immunosuppressive cells secrete multiple negative immune regulatory factors, inhibit the recognition and presentation of tumor antigens and the antitumor effect of immune cells, resulting in immune escape; 3.EGFR-TKI-resistant tumors promote EMT. These three characteristics interact, resulting in a regulatory signaling network, which together leads to EGFR-TKI resistance.

A Different Facet of p53 Function: Regulation of Immunity and Inflammation During Tumor Development

As a key transcription factor, the evolutionarily conserved tumor suppressor p53 (encoded by TP53) plays a central role in response to various cellular stresses. A variety of biological processes are regulated by p53 such as cell cycle arrest, apoptosis, senescence and metabolism. Besides these well-known roles of p53, accumulating evidence show that p53 also regulates innate immune and adaptive immune responses. p53 influences the innate immune system by secreted factors that modulate macrophage function to suppress tumourigenesis. Dysfunction of p53 in cancer affects the activity and recruitment of T and myeloid cells, resulting in immune evasion. p53 can also activate key regulators in immune signaling pathways which support or impede tumor development. Hence, it seems that the tumor suppressor p53 exerts its tumor suppressive effect to a considerable extent by modulating the immune response. In this review, we concisely discuss the emerging connections between p53 and immune responses, and their impact on tumor progression. Understanding the role of p53 in regulation of immunity will help to developing more effective anti-tumor immunotherapies for patients with TP53 mutation or depletion.

Prediction of unfavourable response to checkpoint blockade in lung cancer patients through an integrated tumour-immune expression score

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Predictive power of PD response for ICIs was superior than traditional biomarkers;

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Predictive efficacy was improved by integrating tumor-immune-related features;

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When tumor-specific feature was replaced, the model has pan-cancer applicability.

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NRAS and PDPK1 have the potential to induce primary resistance to ICIs.

Background

Treatment by immune checkpoint blockade (ICB) provides a remarkable survival benefit for multiple cancer types. However, disease aggravation occurs in a proportion of patients after the first couple of treatment cycles.

Methods

RNA sequencing data was retrospectively collected. 6 tumour-immune related features were extracted and combined to build a lung cancer-specific predictive model to distinguish responses as progression disease (PD) or non-PD. This model was trained by 3 public pan-cancer datasets and a lung cancer cohort from our institute, and generated a lung cancer-specific integrated gene expression score, which we call LITES. It was finally tested in another lung cancer dataset.

Results

LITES is a promising predictor for checkpoint blockade (area under the curve [AUC]=0.86), superior to traditional biomarkers. It is independent of PD-L1 expression and tumour mutation burden. The sensitivity and specificity of LITES was 85.7% and 70.6%, respectively. Progression free survival (PFS) was longer in high-score group than in low-score group (median PFS: 6.0 vs. 2.4 months, hazard ratio=0.45, P=0.01). The mean AUC of 6 features was 0.70 (range=0.61-0.75), lower than in LITES, indicating that the combination of features had synergistic effects. Among the genes identified in the features, patients with high expression of NRAS and PDPK1 tended to have a PD response (P=0.001 and 0.01, respectively). Our model also functioned well for patients with advanced melanoma and was specific for ICB therapy.

Conclusions

LITES is a promising biomarker for predicting an impaired response in lung cancer patients and for clarifying the biological mechanism underlying ICB therapy.

Case Report: Immune and Genomic Characteristics Associated With Hyperprogression in a Patient With Metastatic Deficient Mismatch Repair Gastrointestinal Cancer Treated With Anti-PD-1 Antibody

Microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR) status of tumors is a distinct predictive biomarker of immune checkpoint inhibitors (ICIs) for colorectal and non-colorectal cancer populations. The overall response rate (ORR) varies from approximately 40% to 60%, indicating that nearly half of MSI-H tumors do not respond to ICIs. The mechanism of response heterogeneity in MSI-H/dMMR cancers is unclear. Some patients who have been treated with ICIs have developed a novel pattern of progression called hyperprogression, which is defined as unexpected accelerated tumor growth. No case of MSI-H/dMMR immunotherapy-associated hyperprogression has been reported in the literature. Here, we present the case of a patient with dMMR gastrointestinal cancer who suffered hyperprogressive disease (HPD) after treatment with nivolumab. We explored the potential mechanisms of HPD by clinical, immune, and genomic characteristics. Extremely high levels of serum LDH, low TMB and TILs, and the disruption of TGFβ signaling, may be related to hyperprogression.

Inactivation of AMPK Leads to Attenuation of Antigen Presentation and Immune Evasion in Lung Adenocarcinoma

PURPOSE

Mutations in STK11 (LKB1) occur in 17% of lung adenocarcinoma (LUAD) and drive a suppressive (cold) tumor immune microenvironment (TIME) and resistance to immunotherapy. The mechanisms underpinning the establishment and maintenance of a cold TIME in LKB1-mutant LUAD remain poorly understood. In this study, we investigated the role of the LKB1 substrate AMPK in immune evasion in human non-small cell lung cancer (NSCLC) and mouse models and explored the mechanisms involved.

EXPERIMENTAL DESIGN

We addressed the role of AMPK in immune evasion in NSCLC by correlating AMPK phosphorylation and immune-suppressive signatures and by deleting AMPKα1 (Prkaa1) and AMPKα2 (Prkaa2) in a Kras^G12D -driven LUAD. Furthermore, we dissected the molecular mechanisms involved in immune evasion by comparing gene-expression signatures, AMPK activity, and immune infiltration in mouse and human LUAD and gain or loss-of-function experiments with LKB1- or AMPK-deficient cell lines.

RESULTS

Inactivation of both AMPKα1 and AMPKα2 together with Kras activation accelerated tumorigenesis and led to tumors with reduced infiltration of CD8⁺/CD4⁺ T cells and gene signatures associated with a suppressive TIME. These signatures recapitulate those in Lkb1-deleted murine LUAD and in LKB1-deficient human NSCLC. Interestingly, a similar signature is noted in human NSCLC with low AMPK activity. In mechanistic studies, we find that compromised LKB1 and AMPK activity leads to attenuated antigen presentation in both LUAD mouse models and human NSCLC.

CONCLUSIONS

The results provide evidence that the immune evasion noted in LKB1-inactivated lung cancer is due to subsequent inactivation of AMPK and attenuation of antigen presentation.

Comprehensive Analysis of Clinical Significance, Immune Infiltration and Biological Role of m6A Regulators in Early-Stage Lung Adenocarcinoma

Recent publications have revealed that N6-methyladenosine (m⁶A) modification is critically involved in tumorigenesis and metastasis. However, the correlation of m⁶A modification and immune infiltration in early-stage lung adenocarcinoma (LUAD) is still uncertain. We performed NMF clustering based on 23 m⁶A regulators and identify three distinct m⁶A clusters and three m⁶A related genes clusters (m⁶A cluster-R) in early-stage LUAD. The immune infiltrating levels were calculated using CIBERSORT, MCPcounter and ssGSEA algorithms. And we established the m⁶A-predictive score to quantify m⁶A modified phenotypes and predict immunotherapeutic responses. Based on the TME characteristics, different immune profiles were also identified among three m⁶A gene-related clusters. And the m⁶A-R-C2 was related to a favorable overall survival (OS), whereas m⁶A-R-C3 had unfavorable overall survival. The m⁶A-predictive score was built according to the expression levels of m⁶A-related genes, and patients could be stratified into subgroups with low/high scores. Patients with high scores had poor overall survival, enhanced immune infiltration, high tumor mutation burden and increased level of somatic mutation. Besides, patients with high scores had unfavorable overall survival in the anti-PD-1 cohort, whereas the overall survival of high-score patients was better in the adoptive T cell therapy cohort. Our work highlights that m⁶A modification is closely related to immune infiltration in early-stage LUAD, which also contributes to the development of more effective immunotherapy strategies.

Identification and validation of tissue or ctDNA PTPRD phosphatase domain deleterious mutations as prognostic and predictive biomarkers for immune checkpoint inhibitors in non-squamous NSCLC

BACKGROUND

With the revolutionary progress of immune checkpoint inhibitors (ICIs) achieved in non-small cell lung cancers (NSCLC), identifying patients benefiting from ICIs becomes critical and urgent. The associations of genomic alterations in protein tyrosine phosphatase receptor-type (PTPRs) and ICIs responses are unknown.

METHODS

Whole-exome sequencing (WES) of 73 advanced NSCLC tumors sampled before anti-PD-(L)1 therapy was carried out with corresponding clinical data collected as a discovery cohort to find the associations of PTPR mutations and ICI responses. Three validation cohorts consolidated by 7 public cohorts of 1920 NSCLC patients with WES or target sequencing data of tumor tissue-derived DNA or circulating tumor DNA (ctDNA) and relevant clinical data were applied as validation cohorts. The lung adenocarcinoma (LUAD) cohort (n=586) in The Cancer Genome Atlas (TCGA) database was used for analyzing the potential anti-tumor immunologic mechanisms.

RESULTS

With the highest mutation frequency among all PTPRs, PTPRD mutations in non-squamous NSCLC (ns-NSCLC) were linked to longer progression-free survivals (PFS, 324 vs 63 days, hazard ratio (HR)=0.36, p= 0.0152) and higher objective response rate (ORR, p=0.0099). In validation cohort 1 (n=377), ns-NSCLC patients with tissue PTPRD mutations had favorable PFS (9.10 vs 4.33 months, HR=0.62, p=0.0184) and ORR (p=0.013). In validation cohort 2 (n=406), ns-NSCLC patients with tissue PTPRD mutations had favorable overall survivals (OS, over 40 vs 11.94 months, HR=0.57, p=0.011). In validation cohort 3 (n=1137), ns-NSCLC patients with ctDNA PTPRD mutations had longer PFS (6.97 vs 2.73 months, HR=0.63, p=0.028) and higher ORR (p=0.047). Moreover, it was deleterious mutations in phosphatase domains (phosphatase-mut), rather than other mutations (other-mut), that were responsible of PTPRD's prediction efficiency. In addition, in validation cohort 3, ctDNA phosphatase-mut also functioned as a predictive biomarker helping identify patients benefiting more from ICIs than chemotherapy (interaction P for PFS=0.0506, for OS=0.04). Univariate and multivariate regression analysis revealed that phosphatase-mut was independent on PD-L1 expression and tumor mutation burden (TMB) to predict. In silico analysis based on TCGA LUAD cohort discovered enhanced anti-tumor immunity in phosphatase-mut patients.

CONCLUSIONS

Tissue or ctDNA PTPRD phosphatase domain deleterious mutations might function as a both prognostic and predictive biomarker predicting clinical outcomes of ICIs in ns-NSCLC patients, independent on TMB or PD-L1 expression.

The role of ERBB4 mutations in the prognosis of advanced non-small cell lung cancer treated with immune checkpoint inhibitors

BACKGROUND

Immune checkpoint inhibitors (ICIs) have witnessed the achievements of convincing clinical benefits that feature the significantly prolonged overall survival (OS) of patients suffering from advanced non-small cell lung cancer (NSCLC), according to reports recently. Sensitivity to immunotherapy is related to several biomarkers, such as PD-L1 expression, TMB level, MSI-H and MMR. However, a further investigation into the novel biomarkers of the prognosis on ICIs treatment is required. In addition, there is an urgent demand for the establishment of a systematic hazard model to assess the efficacy of ICIs therapy for advanced NSCLC patients.

METHODS

In this study, the gene mutation and clinical data of NSCLC patients was obtained from the TCGA database, followed by the analysis of the detailed clinical information and mutational data relating to two advanced NSCLC cohorts receiving the ICIs treatment from the cBioPortal of Cancer Genomics. The Kaplan-Meier plot method was used to perform survival analyses, while selected variables were adopted to develop a systematic nomogram. The prognostic significance of ERBB4 in pan-cancer was analyzed by another cohort from the cBioPortal of Cancer Genomics.

RESULTS

The mutation frequencies of TP53 and ERBB4 were 54% and 8% in NSCLC, respectively. The mutual exclusive analysis in cBioPortal has indicated that ERBB4 does show co-occurencing mutations with TP53. Patients with ERBB4 mutations were confirmed to have better prognosis for ICIs treatment, compared to those seeing ERBB4 wild type (PFS: exact p = 0.017; OS: exact p < 0.01) and only TP53 mutations (OS: p = 0.021). The mutation status of ERBB4 and TP53 was tightly linked to DCB of ICIs treatment, PD-L1 expression, TMB value, and TIICs. Finally, a novel nomogram was built to evaluate the efficacy of ICIs therapy.

CONCLUSION

ERBB4 mutations could serve as a predictive biomarker for the prognosis of ICIs treatment. The systematic nomogram was proven to have the great potential for evaluating the efficacy of ICIs therapy for advanced NSCLC patients.

TP53 Mutation Status and Biopsy Lesion Type Determine the Immunotherapeutic Stratification in Non-Small-Cell Lung Cancer

Immunotherapy, a chemotherapy-free process, has emerged as a promising therapeutic strategy to prolong the overall survival (OS) of patients with non-small-cell lung cancer (NSCLC). However, effective stratification factors for immunotherapy remain unclear. The purpose of this study was to discuss the potential stratification factors of NSCLC immunotherapy using immune checkpoint inhibitors (ICIs) by integrating genomic profiling and tumor lesion–type information. In this study, 344 patients with NSCLC, whose clinical and tissue (including metastatic and primary lesions) mutation information was available, were included. The potential gene mutation status for predicting the outcomes of immunotherapy was screened by comparing the difference in mutation frequency between responders and non-responders. Our results indicated that the potential predictors of immunotherapy were significantly different, especially between patients with TP53(+) (including metastatic and primary lesions) and TP53(−) (including metastatic and primary lesions). According to this classification, patients with NSCLC who suggested immunotherapy had a higher OS than those who did not (25 months vs. 7 months, P < 0.0001, hazard ratio = 0.39). Collectively, this study provides a new perspective for screening immunotherapy predictors in NSCLC, suggesting that the TP53 mutation status and source of biopsy tissue should be considered during the development of immunotherapy biomarkers.

A novel immune subtype classification of ER-positive, PR-negative and HER2-negative breast cancer based on the genomic and transcriptomic landscape

BACKGROUND

The diversity and plasticity behind ER+/PR-/HER2- breast cancer have not been widely explored. It is essential to identify heterogeneous microenvironment phenotypes and investigate specific genomic events driving the formation of these phenotypes.

METHODS

Based on the immune-related gene expression profiles of 411 ER+/PR-/HER2- breast cancers in the METABRIC cohort, we used consensus clustering to identify heterogeneous immune subtypes and assessed their reproducibility in an independent meta-cohort including 135 patients collected from GEO database. We further analyzed the differences of cellular and molecular characteristics, and potential immune escape mechanism among immune subtypes. In addition, we constructed a transcriptional trajectory to visualize the distribution of individual patient.

RESULTS

Our analysis identified and validated five reproducible immune subtypes with distinct cellular and molecular characteristics, potential immune escape mechanisms, genomic drivers, as well as clinical outcomes. An immune-cold subtype, with the least amount of lymphocyte infiltration, had a poorer prognosis. By contrast, an immune-hot subtype, which demonstrated the highest infiltration of CD8+ T cells, DCs and NK cells, and elevated IFN-γ response, had a comparatively favorable prognosis. Other subtypes showed more diverse gene expression and immune infiltration patterns with distinct clinical outcomes. Finally, our analysis revealed a complex immune landscape consisting of both discrete cluster and continuous spectrum.

CONCLUSION

Overall, this study revealed five heterogeneous immune subtypes among ER+/PR-/HER2- breast cancer, also provided important implications for clinical translations.

Identification and validation of a metabolism-related model and associated with tumor-infiltrating lymphocytes in p53 mutant lung adenocarcinoma patients

Background

The immunosuppressive tumor microenvironment produced by cancer cells is a key mechanisms of cancer immune escape. In this study, we investigated the relationship between the metabolic patterns and tumor immune environment in the TME of lung adenocarcinoma (LUAD) with the p53 mutation.

Methods

The clinical data of 495 LUAD patients was obtained from The Cancer Genome Atlas as transcriptomic and somatic mutation data. Using differential analysis, survival analysis, and a LASSO regression model based on metabolic unigenes from KEGG pathways, a tumor metabolic model was constructed to predict the prognosis of LUAD patients. Subsequently, nomogram, receiver operating characteristic, and decision curve analyses were conducted to assess the predictive ability of the model. In addition, the ESTIMATE and CIBERSORT algorithms were used to detect tumor purity and estimate the fractions of 22 immune cell types in each patient, respectively. We found a correlation between the composition of immune cells and the tumor metabolic model. The results were validated using an independent GSE72094 dataset with 442 patients, as well as an immunohistochemistry assay, RT-qPCR, and western blot.

Results

The tumor metabolic model reassigned the risk score of every patient, and a tumor metabolic risk score (TMRS) was generated to show the predictive ability for patient prognoses (hazard ratio =0.39; 95% confidence interval: 0.18–0.85). Using a combination of TMRS and clinical features, a nomogram was produced with a predictive accuracy of 0.72. Further analysis showed that CD4 memory resting T cells and M1 macrophages may by correlated with the TMRS, which corresponded to immunoediting in p53 mutant patients. Additionally, the similar expression of ALDH3A1 and MGAT5B were also verified by wetlab experiments.

Conclusions

Based on the identified tumor metabolism-immune landscape, we were able to predict a metabolism risk score for patient prognosis and identify a correlation with two types of infiltrating lymphocytes in the TME of p53-mutated LUAD. This landscape provides insights that will help identify the molecular mechanisms of immune-editing tumor metabolism.

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

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.