EPHA5 mutation predicts the durable clinical benefit of immune checkpoint inhibitors in patients with lung adenocarcinoma

Toxicity profiles of immune checkpoint inhibitors in nervous system cancer: a comprehensive disproportionality analysis using FDA adverse event reporting system

BACKGROUND

Immune-related adverse events (irAEs) always occur during treatment with immune checkpoint inhibitors (ICIs). Patients with nervous system cancer (NSC) may gain clinical benefit from ICIs, but irAEs in NSC patients are rarely examined. Therefore, our study systematically summarized reports of irAEs in NSC.

METHODS

We obtained information from the FDA adverse event reporting system from the first quarter (Q1) of 2013 to the fourth quarter (Q4) of 2022. We examined use of a combination of ICIs and chemotherapy (ICI_Chemo) or chemotherapy only (ICI_Chemo) for patients with NSC. Multiple disproportionality analyses were applied to assess irAEs. Multiomics data from the gene expression omnibus (GEO) database were analyzed to explore potential molecular mechanisms associated with irAEs in NSC patients.

RESULTS

Fourteen irAEs were identified in 8,357 NSC patients after removing duplicates; the top five events were seizure, confused state, encephalopathy, muscular weakness and gait disturbance. Older patients were more likely to develop irAEs than were younger patients. From the start of ICIs_Chemo to irAE occurrence, there was a significant difference in the time to onset of irAEs between age groups. irAEs may occur via mechanisms involving the inflammatory response, secretion of inflammatory mediators, and aberrant activation of pathologic pathways.

CONCLUSIONS

This study helps to characterize irAEs in NSC patients treated with ICIs. We combined GEO database analysis to explore the potential molecular mechanisms of irAEs. The results of this study provide a basis for improving the toxic effects of ICIs in NSC patients.

Comprehensive analysis of Epha10 as a predictor of clinical prognosis and immune checkpoint therapy efficacy in non-small cell lung cancer

The EphA family belongs to a large group of membrane receptor tyrosine kinases. Emerging evidence indicates that the EphA family participates in tumour occurrence and progression. Nonetheless, the expression patterns and prognostic values of the nine EphAs in non-small cell lung cancer (NSCLC) have rarely been studied before. In the current study, we comprehensively analysed the expression and prognostic role of EphA family members by different means. The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis databases were used to investigate the expression of EphAs in NSCLC. The cBioPortal database was applied to analyse the prognostic values and genetic mutations of EphAs.We discovered that the expression of EphA10 was significantly higher in NSCLC tissues than in adjacent noncancerous tissues, and survival analyses showed that a higher level of EphA10 predicted poor prognosis. Further exploration into the role of EphA10 by ESTIMATE, CIBERSORT, and ssGSEA analysis found that it was also related to immune infiltration and higher expression of targets of ICI targets. In conclusion, this study revealed that among the EphA family members, EphA10 played an oncogenic role and was a promising biomarker for poor prognosis and better immunotherapy response in NSCLC.

Genomic insights into adaptation and inbreeding among Sub-Saharan African cattle from pastoral and agropastoral systems

Background

In Sub-Saharan Africa (SSA), cattle are crucial for socioeconomic stability yet face numerous environmental stressors such as diseases, parasites, and extreme heat within pastoral and agropastoral systems. Despite their significance, gaps remain in understanding how genetic diversity and inbreeding influence traits essential for disease resistance and environmental adaptability. This study examines the genomic adaptations that enable SSA cattle to thrive under these conditions and assesses the impact of inbreeding on such adaptive traits.

Methods

We analyzed genomic data from 113 cattle across four breeds-Kuri, N'dama, Zebu-Fulani, and Zebu-Bororo-employing Runs of Homozygosity (ROH) and Integrated Haplotype Score (iHS) analyses to identify historical and recent genetic selections. Strict quality controls using PLINK software ensured accurate genomic pattern identification related to adaptation and inbreeding.

Results

ROH analysis revealed islands with genes such as RSAD2, CMPK2, and NOTCH1, which are involved in immune response and cellular stress management, highlighting regions of historical selection that have likely provided adaptive advantages in overcoming environmental and pathogenic stresses. In contrast, iHS analysis identified genes under recent selection like HIPK1, involved in stress response regulation, and EPHA5, which plays a crucial role in neural development and synaptic functions, potentially equipping these breeds with novel adaptations to ongoing and emergent environmental challenges.

Conclusion

This research confirms that selective pressures inherent in pastoral and agropastoral systems profoundly influence the genetic structure of SSA cattle. By delineating the genetic bases of key adaptive traits, our study offers crucial insights for targeted breeding programs to enhance cattle resilience and productivity. These findings provide a valuable framework for future genetic improvements and conservation strategies, crucial for sustainable livestock management and economic stability in SSA.

PCCA variant rs16957301 is a novel AKI risk genotype-specific for patients who receive ICI treatment: Real-world evidence from All of Us cohort

Background

Immune checkpoint inhibitors (ICIs) enhance the immune system's ability to target and destroy cancer cells by blocking inhibitory pathways. Despite their efficacy, these treatments can trigger immune-related adverse events (irAEs), such as acute kidney injury (ICI-AKI), complicating patient management. The genetic predispositions to ICI-AKI are not well understood, necessitating comprehensive genomic studies to identify risk factors and improve therapeutic strategies.

Objective

To identify genetic predispositions for ICI-AKI using large-scale real-world data.

Methods

A systematic literature search led to 14 candidate variants related to irAEs. We performed a candidate variant association study with these 14 variants using the All of Us cohort (AoU, v7, cutoff date: 7/1/2022). A cohort for cancer patients receiving ICI and a general cohort were established to evaluate ICI-AKI risk. Logistic regression, adjusted for sex, was used to evaluate the impact of each candidate genotype, separately for self-reported and ancestry-estimated race. Kaplan-Meier survival analysis assessed the genetic effects on AKI-free survival.

Results

The ICI cohort (n=414) showed a one-year AKI incidence rate of 23.2%, significantly higher than the general cohort (6.5%, n=213,282). The rs16957301 variant (chr13:100324308, T>C) in the PCCA gene was a significant risk genotype for ICI-AKI among self-reported Caucasians (Beta=0.93, Bonferroni-corrected P-value=0.047) and ancestry estimated Caucasians (Beta = 0.94, Bonferroni-corrected P-value=0.044). Self-reported Caucasians with the rs16957301 risk genotypes (TC/CC) developed AKI significantly earlier (3.6 months) compared to the reference genotype (TT, 7.0 months, log-rank P=0.04). Consistent results were found in ancestry-estimated Caucasians. This variant did not present significant AKI risks in the general cohort (Beta: -0.008-0.035, FDR: 0.75-0.99).

Conclusion

Real-world evidence from the All of Us cohort suggests that, in Caucasians, PCCA variant rs16957301 is a novel AKI risk genotype specific to ICI treatment. Additional studies are warranted to validate rs16957301 as risk marker for AKI in Caucasian patients treated with ICIs and to assess its risk in other ancestral populations.

Eph receptors and ephrins in cancer progression

Evidence implicating Eph receptor tyrosine kinases and their ephrin ligands (that together make up the 'Eph system') in cancer development and progression has been accumulating since the discovery of the first Eph receptor approximately 35 years ago. Advances in the past decade and a half have considerably increased the understanding of Eph receptor-ephrin signalling mechanisms in cancer and have uncovered intriguing new roles in cancer progression and drug resistance. This Review focuses mainly on these more recent developments. I provide an update on the different mechanisms of Eph receptor-ephrin-mediated cell-cell communication and cell autonomous signalling, as well as on the interplay of the Eph system with other signalling systems. I further discuss recent advances in elucidating how the Eph system controls tumour expansion, invasiveness and metastasis, supports cancer stem cells, and drives therapy resistance. In addition to functioning within cancer cells, the Eph system also mediates the reciprocal communication between cancer cells and cells of the tumour microenvironment. The involvement of the Eph system in tumour angiogenesis is well established, but recent findings also demonstrate roles in immune cells, cancer-associated fibroblasts and the extracellular matrix. Lastly, I discuss strategies under evaluation for therapeutic targeting of Eph receptors-ephrins in cancer and conclude with an outlook on promising future research directions.

Identification and validation of a novel HOX-related classifier signature for predicting prognosis and immune microenvironment in pediatric gliomas

Background: Pediatric gliomas (PGs) are highly aggressive and predominantly occur in young children. In pediatric gliomas, abnormal expression of Homeobox (HOX) family genes (HFGs) has been observed and is associated with the development and progression of the disease. Studies have found that overexpression or underexpression of certain HOX genes is linked to the occurrence and prognosis of gliomas. This aberrant expression may contribute to the dysregulation of important pathological processes such as cell proliferation, differentiation, and metastasis. This study aimed to propose a novel HOX-related signature to predict patients' prognosis and immune infiltrate characteristics in PGs. Methods: The data of PGs obtained from publicly available databases were utilized to reveal the relationship among abnormal expression of HOX family genes (HFGs), prognosis, tumor immune infiltration, clinical features, and genomic features in PGs. The HFGs were utilized to identify heterogeneous subtypes using consensus clustering. Then random forest-supervised classification algorithm and nearest shrunken centroid algorithm were performed to develop a prognostic signature in the training set. Finally, the signature was validated in an internal testing set and an external independent cohort. Results: Firstly, we identified HFGs significantly differentially expressed in PGs compared to normal tissues. The individuals with PGs were then divided into two heterogeneous subtypes (HOX-SI and HOX-SII) based on HFGs expression profiles. HOX-SII showed higher total mutation counts, lower immune infiltration, and worse prognosis than HOX-SI. Then, we constructed a HOX-related gene signature (including HOXA6, HOXC4, HOXC5, HOXC6, and HOXA-AS3) based on the cluster for subtype prediction utilizing random forest supervised classification and nearest shrunken centroid algorithm. The signature was revealed to be an independent prognostic factor for patients with PGs by multivariable Cox regression analysis. Conclusion: Our study provides a novel method for the prognosis classification of PGs. The findings also suggest that the HOX-related signature is a new biomarker for the diagnosis and prognosis of patients with PGs, allowing for more accurate survival prediction.

Application of ATAC-seq in tumor-specific T cell exhaustion

Researches show that chronic viral infection and persistent antigen and/or inflammatory signal exposure in cancer causes the functional status of T cells to be altered, mainly by major changes in the epigenetic and metabolic environment, which then leads to T cell exhaustion. The discovery of the immune checkpoint pathway is an important milestone in understanding and reversing T cell exhaustion. Antibodies targeting these pathways have shown superior ability to reverse T cell exhaustion. However, there are still some limitations in immune checkpoint blocking therapy, such as the short-term nature of therapeutic effects and high individual heterogeneity. Assay for transposase-accessible chromatin with sequencing(ATAC-seq) is a method used to analyze the accessibility of whole-genome chromatin. It uses hyperactive Tn5 transposase to assess chromatin accessibility. Recently, a growing number of studies have reported that ATAC-seq can be used to characterize the dynamic changes of epigenetics in the process of T cell exhaustion. It has been determined that immune checkpoint blocking can only temporarily restore the function of exhausted T cells because of an irreversible change in the epigenetics of exhausted T cells. In this study, we review the latest developments, which provide a clearer molecular understanding of T cell exhaustion, reveal potential new therapeutic targets for persistent viral infection and cancer, and provide new insights for designing effective immunotherapy for treating cancer and chronic infection.

Correlation between IL3 signaling pathway-related genes and immune checkpoint inhibitor efficacy in patients with renal cell carcinoma

BACKGROUND

There is a lack of effective biomarkers that predict immunotherapy efficacy in clear cell renal cell carcinoma(KIRC).

OBJECTIVE

We aimed to identify biomarkers that would predict the efficacy of KIRC treatment with immune checkpoint inhibitors (ICIs).

METHODS

Cohort data of KIRC patients with somatic mutations, mRNA expression and survival data from The Cancer Genome Atlas (TCGA) database and immunotherapy cohort and Genomics of Drug Sensitivity in Cancer (GDSC) database were analyzed and divided into interleukin 3 (IL3) pathway-related genes high expression (IL3-High) and IL3 pathway-related genes low expression (IL3-Low) groups according to pathway expression status to assess the relationship between the IL3 pathway-related genes activation status and the prognosis of KIRC patients treated with ICIs. The data were validated by immunohistochemistry experiments, and possible mechanisms of action were explored at the level of gene mutation landscape, immune microenvironment characteristics, transcriptome and copy number variation(CNV) characteristicsRESULTS: The IL3 pathway-related genes was an independent predictor of the efficacy of ICIs in KIRC patients, and the IL3-High group had a longer overall survival (OS); KIRC patients in the IL3-High group had increased levels of chemokines, cytolysis, immune checkpoint gene expression and abundant immunity. The IL3-Low group had poor immune cell infiltration and significant downregulation of complement activation, cytophagy, B-cell activation, and humoral immune response pathways. The high group was more sensitive to targeted drugs of some signaling pathways, and its efficacy in combining these drugs with immunity has been predicted in the published literature.

CONCLUSION

The IL3 pathway-related genes can be used as a predictor of the efficacy of ICIs in KIRC. The IL3 pathway-related genes may affect the therapeutic efficacy of ICIs by affecting the expression of immune-related molecules, immune cell infiltration, and the level of immune response pathways.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

B Cell Receptor Signaling Pathway Mutation as Prognosis Predictor of Immune Checkpoint Inhibitors in Lung Adenocarcinoma by Bioinformatic Analysis

Purpose

The advent of immune checkpoint inhibitors (ICIs) is a revolutionary breakthrough. However, without the selection of a specific target population, the response rate of ICI therapy in lung adenocarcinoma (LUAD) is low, so a clinical challenge has arisen in effectively using biomarkers to determine which patients can benefit from ICI therapy.

Methods

In this study, patients were divided according to whether or not nonsynonymous mutations were present in the BCR signaling pathway, and univariate and multivariate Cox regression models were established based on a LUAD cohort treated with ICIs (Miao-LUAD). Then the relationship between the mutation status of the BCR signaling pathway and the prognosis of immunotherapy was examined. Finally, data from The Cancer Genome Atlas (TCGA) LUAD cohort, the Rizvi-LUAD, the Samstein-LUAD, and the Zhujiang Hospital of Southern Medical University LUAD (Local-LUAD) cohort were combined, and the mutation panorama, immunogenicity, tumor microenvironment (TME) and pathway enrichment analysis between the BCR signaling pathway mutant group (BCR signaling MUT) and the BCR signaling pathway wild group (BCR signaling WT) were comprehensively compared.

Results

It was found that, compared with the BCR signaling WT, the BCR signaling MUT had a significantly improved progression-free survival (PFS) rate and overall survival (OS) rate, higher immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations), and anti-tumor immune microenvironment.

Conclusion

These results revealed that the mutation state of the BCR signaling pathway has potential as a biomarker to predict the efficacy of ICIs in LUAD.

Combination of Tumor Mutational Burden and DNA Damage Repair Gene Mutations with Stromal/Immune Scores Improved Prognosis Stratification in Patients with Lung Adenocarcinoma

Background

Both the tumor environment and the genomic landscape of lung cancer may shape patient responses to treatments, including immunotherapy, but their joint impacts on lung adenocarcinoma (LUAD) prognosis are underexplored.

Methods

RNA sequencing data and whole-exome sequencing results were downloaded from the TCGA database, and only LUAD-related data were included in this study. Based on gene expression data, the ESTIMATE algorithm was used to estimate stromal and immune scores, and CIBERSORT analysis was used for quantification of the relative abundances of immune cells. Somatic mutations were used for calculating tumor mutation burden (TMB). Specific mutations in genes involved in DNA damage repair (DDR) pathways were identified. The individual and joint associations of stromal and immune score, TMB, and DDR gene mutations with 5-year survival were analyzed by the Kaplan–Meier method and multivariate Cox model.

Results

LUAD patients with a high (>highest 25%) stromal or immune score had prolonged survival as compared to those with a low (<lowest 25%) score (log-rank P=0.05 and 0.035, respectively). Patients with both high stromal and immune scores had the most favorable survival. Although the survival differences between patients with high (>highest 25%) and low (<lowest 25%) TMB, or between patients with mutant- and wild-type DDR genes were not statistically significant, a survival benefit from high TMB or DDR gene mutations was observed in patients with high stromal or immune scores.

Conclusion

A comprehensive evaluation of transcriptomic signatures and genomic biomarkers may provide a novel avenue for improving prognosis stratification in LUAD.

EPHA5 mutation was associated with adverse outcome of atezolizumab treatment in late-stage non-small cell lung cancers

Background

The aim of the study was to investigate predictive value of gene mutation for atezolizumab treatment response from OAK and POPLAR cohorts.

Methods

Several public databases were used for analyzing gene mutation type of EPHA5 and association with alterations of other genes. Survival analysis was performed for patients receiving atezolizumab from OAK and POPLAR cohorts.

Results

EPHA5 mutation have high frequency to harbor TP53 and KEAP1 mutations. The bTMB value has significant difference between EPHA5 mutant and wild-type cases. Patients with EPHA5 mutation got worse survival compared to those without gene mutations receiving atezolizumab (P = 0.0186).

Conclusions

EPHA5 mutant NSCLC may represent a subpopulation which showed worse response after treatment of atezolizumab compared to wild-type ones.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02161-1.

Expression of EPHA5 in lung adenocarcinoma is associated with lymph node metastasis and EGFR mutation

EPHA5 is a member of the Eph family of tyrosine kinase receptors, which affect carcinogenesis. The expression level of the EPHA5 receptor in a set of lung adenocarcinoma tissue samples was checked using immunohistochemistry. The relationship between EPHA5 expression and clinicopathological parameters, and epidermal growth factor receptor (EGFR) and Braf mutations were analyzed. We also checked the expression level of the EPHA5 receptor in four lung cancer cell lines. High expression of EPHA5 was found in NCI-H460 and H1299 cells, while low expression was observed in A549 and SPC-A1 cells. EPHA5 was knocked down in NCI-H460 and H1299 lung cancer cell lines using siRNAs. The proliferation, clone formation, and invasive ability were analyzed in NCI-H460 and H1299 cells with EPHA5 knockdown. The results show that the EPHA5 receptor is differently expressed in lung adenocarcinoma tissues, in which positive and negative expression of EPHA5 was found in 58.1% and 41.9% of tissues, respectively. Positive expression of EPHA5 was associated with lymph node metastasis (p = 0.002), differentiation (p = 0.020), TNM stage (p = 0.002), and EGFR mutation (p = 0.001). The proliferation, clone formation, and invasive ability were significantly decreased after EPHA5 knockdown in NCI-H460 and H1299 cells. Our data suggest that the EPHA5 receptor plays a role in tumor promotion in lung adenocarcinoma and is a potential target for lung adenocarcinoma treatment.

TCR Coexpression Signature Predicts Immunotherapy Resistance in NSCLC

Background: Lung cancer has the highest morbidity and mortality rate among types of malignant tumors, and as such, research into prolonging the survival time of patients is vital. The emergence of immune checkpoint inhibitors (ICIs) has greatly improved the survival of patients with non-small cell lung cancer (NSCLC), however, the lack of effective biomarkers to predict the prognosis of immunotherapy has made it difficult to maximize the benefits. T cell receptor (TCR) is one of the most important components for recognizing tumor cells, and with this study we aim to clarify the relationship between TCR coexpression and the prognosis of NSCLC patients receiving immunotherapy.

Methods: Univariate COX regression, logistics regression, and KM survival analysis were used to evaluate the relationship between TCR coexpression and the prognosis of immunotherapy. Additionally, CIBERSORT, Gene Set Enrichment Analysis (GSEA), and single-sample GSEA (ssGSEA) algorithms were used to evaluate the tumor immune microenvironment (TIME) of NSCLC patients.

Results: Univariate Cox regression analysis showed that the TCR coexpression signature can be used as a clinical prognostic indicator for NSCLC patients receiving immunotherapy (p = 0.0205). In addition, those in the NSCLC group with a high TCR coexpression signature had significantly improved progression-free survival (PFS) (p = 0.014). In the ICI treatment cohort (GSE35640). In addition, there was a high infiltration of CD8+T cells, activated memory CD4+T cells, and M1 macrophages in the TIME of those with a high TCR coexpression signature. The results of pathway enrichment analysis showed that patients with a high TCR coexpression signature had significantly activated signal pathways such as lymphocyte proliferation and activation, chemokine binding, and inflammatory cytokine production. Also, we found that patients with a high TCR coexpression signature had an elevated T cell inflammation gene expression profile (GEP).

Conclusion: We show that the TCR coexpression signature may be useful as a new biomarker for the prognosis of NSCLC patients undergoing immunotherapy, with high signatures indicating better treatment response. Additionally, we found that patients with a high TCR coexpression signature had tumor immune microenvironments with beneficial anti-tumor characteristics.

TET1 mutations as a predictive biomarker for immune checkpoint inhibitors in colon adenocarcinoma

BACKGROUND

The ten-eleven translocation 1 (TET1), which is essential for active DNA demethylation, plays a multifaceted role in the pathogenesis of colorectal cancer. The study has demonstrated the association of TET1 mutations with a high response to immune checkpoint inhibitors (ICIs) in diverse cancers. However, the relationship between TET1 mutations and the response to ICIs in colon cancer is still lacking.

METHODS

The prognosis, predictive markers, immune characteristics, mutation number of DNA damage repair (DDR) pathways, pathway enrichment, and drug sensitivity conditions were all compared between TET1-mutated and wild-type patients with colon adenocarcinoma (COAD).

RESULTS

The overall survival of patients with TET1 mutations in the ICI-treated cohort was significantly longer than those without (p = 0.0059). Compared with the wild-type patients, TET1-mutated patients had higher tumor mutational burden and neoantigen load, enhanced abundance of tumor-infiltrating immune cells, increased expression of immune-related genes, and mutation number of DDR pathways. Additionally, the patients with TET1 mutations were found to be more sensitive to lapatinib and 5-fluorouracil.

CONCLUSION

These findings suggest that TET1 mutations may serve as a potential biomarker for the response to ICIs in COAD patients.

MMP9 Expression Correlates With Cisplatin Resistance in Small Cell Lung Cancer Patients

Background: Cisplatin is the basis of the primary treatment for SCLC chemotherapy. However, the limited objective response rate and definite drug resistance greatly restrict the clinical potential and therapeutic benefits of cisplatin use. Therefore, it is essential to identify biomarkers that can discern the sensitivity of SCLC patients to cisplatin treatment.

Methods: We collected two SCLC cohorts treated with cisplatin that included mutation data, prognosis data and expression data. The sensitivity of cisplatin was evaluated by the pRRophetic algorithm. MCPcounter, quanTIseq, and xCell algorithms were used to evaluate immune cell score. GSEA and ssGSEA algorithms were used to calculate immune-related pathway scores. Univariate and multivariate Cox regression models were employed, and survival analysis was used to evaluate the prognostic value of the candidate genes.

Results: MMP9-High is related to improved clinical prognoses of patients with SCLC (HR = 0.425, p = 0.0085; HR = 0.365, p = 0.0219). Multivariate results showed that MMP-High could be used as an independent predictor of the prognosis of SCLC after cisplatin treatment (HR = 0.216, p = 0.00153; HR = 0.352; p = 0.0199). In addition, MMP9-High displayed a significantly lower IC50 value of cisplatin and higher immunogenicity than MMP9-Low SCLC. Compared with MMP9-Low SCLC, MMP9-High included significantly increased levels of T-cells, cytoxic lymphocytes, B-cells, NK-cells, and dense cells (DCS). Similarly, the activity of cytokine binding, B-cell, NK-cell mediated immune response chemokine binding, and antigen presentation pathways in MMP9-High was significantly higher than that in MMP9-Low.

Conclusion: In this study, we identified that MMP9-High could be potentially considered a novel biomarker used to ascertain the improved prognosis of SCLC patients after cisplatin treatment. Furthermore, we indicated that the tumor immune microenvironment of MMP9-High SCLC is mainly characterized by a large number of infiltrated activated immune cells as well as activated immune-related pathways.

Prognostic Value of Neoantigen Load in Immune Checkpoint Inhibitor Therapy for Cancer

Immune checkpoint inhibitors (ICIs) have made great progress in the field of tumors and have become a promising direction of tumor treatment. With advancements in genomics and bioinformatics technology, it is possible to individually analyze the neoantigens produced by somatic mutations of each patient. Neoantigen load (NAL), a promising biomarker for predicting the efficacy of ICIs, has been extensively studied. This article reviews the research progress on NAL as a biomarker for predicting the anti-tumor effects of ICI. First, we provide a definition of NAL, and summarize the detection methods, and their relationship with tumor mutation burden. In addition, we describe the common genomic sources of NAL. Finally, we review the predictive value of NAL as a tumor prediction marker based on various clinical studies. This review focuses on the predictive ability of NAL’s ICI efficacy against tumors. In melanoma, lung cancer, and gynecological tumors, NAL can be considered a predictor of treatment efficacy. In contrast, the use of NAL for urinary system and liver tumors requires further research. When NAL alone is insufficient to predict efficacy, its combination with other indicators can improve prediction efficiency. Evaluating the response of predictive biomarkers before the treatment initiation is essential for guiding the clinical treatment of cancer. The predictive power of NAL has great potential; however, it needs to be based on more accurate sequencing platforms and technologies.

An Early-Onset Advanced Rectal Cancer Patient With Increased KRAS Gene Copy Number Showed A Primary Resistance to Cetuximab in Combination With Chemotherapy: A Case Report

Mutations in KRAS (codon 12/13), NRAS, BRAF^V600E, and amplification of ERBB2 and MET account for 70–80% of anti-epidermal growth factor receptor (EGFR) monoclonal antibody primary resistance. However, the list of anti-EGFR monoclonal antibody primary resistance biomarkers is still incomplete. Herein, we report a case of wild-type RAS/BRAF metastatic colorectal cancer (CRC) with resistance to anti-EGFR monoclonal antibody and chemotherapy. Initially, mutation detection in postoperative tumor tissue by using amplification-refractory mutation system polymerase chain reaction indicated wild-type RAS/BRAF without point mutations, insertion deletions, or fusion mutations. Therefore, we recommended combined therapy of cetuximab and FOLFIRI after failure of platinum-based adjuvant chemotherapy, but the disease continued to progress. Next generation sequencing analysis of the postoperative tumor tissue revealed that KRAS copy number was increased and detected SMAD4, RNF43, and PREX2 mutations. This is the first case of advanced CRC with increased copy numbers of KRAS resistant to cetuximab and chemotherapy, which results in poor patient survival, and other mutated genes may be associated with the outcomes. Our findings indicate KRAS copy number alterations should also be examined, especially with anti-EGFR monoclonal antibody therapy in CRC, since it may be related with the primary resistance to these drugs.

Identification of a Three-Gene Signature Based on Epithelial-Mesenchymal Transition of Lung Adenocarcinoma Through Construction and Validation of a Risk-Prediction Model

Epithelial-mesenchymal transition (EMT) process, which is regulated by genes of inducible factors and transcription factor family of signaling pathways, transforms epithelial cells into mesenchymal cells and is involved in tumor invasion and progression and increases tumor tolerance to clinical interventions. This study constructed a multigene marker for lung predicting the prognosis of lung adenocarcinoma (LUAD) patients by bioinformatic analysis based on EMT-related genes. Gene sets associated with EMT were downloaded from the EMT-gene database, and RNA-seq of LUAD and clinical information of patients were downloaded from the TCGA database. Differentially expressed genes were screened by difference analysis. Survival analysis was performed to identify genes associated with LUAD prognosis, and overlapping genes were taken for all the three. Prognosis-related genes were further determined by combining LASSO regression analysis for establishing a prediction signature, and the risk score equation for the prognostic model was established using multifactorial COX regression analysis to construct a survival prognostic model. The model accuracy was evaluated using subject working characteristic curves. According to the median value of risk score, samples were divided into a high-risk group and low-risk group to observe the correlation with the clinicopathological characteristics of patients. Combined with the results of one-way COX regression analysis, HGF, PTX3, and S100P were considered as independent predictors of LUAD prognosis. In lung cancer tissues, HGF and PTX3 expression was downregulated and S100P expression was upregulated. Kaplan-Meier, COX regression analysis showed that HGF, PTX3, and S100P were prognostic independent predictors of LUAD, and high expressions of all the three were all significantly associated with immune cell infiltration. The present study provided potential prognostic predictive biological markers for LUAD patients, and confirmed EMT as a key mechanism in LUAD progression.

TNF-Alpha Pathway Alternation Predicts Survival of Immune Checkpoint Inhibitors in Non-Small Cell Lung Cancer

Translational research on immune checkpoint inhibitors (ICIs) has been underway. However, in the unselected population, only a few patients benefit from ICIs. Therefore, screening predictive markers of ICI efficacy has become the current focus of attention. We collected mutation and clinical data from an ICI-treated non-small cell lung cancer (NSCLC) cohort. Then, a univariate Cox regression model was used to analyze the relationship between tumor necrosis factor α signaling mutated (TNFα-MT) and the prognosis of immunotherapy for NSCLC. We retrospectively collected 36 NSCLC patients (local-cohort) from the Zhujiang Hospital of Southern Medical University and performed whole-exome sequencing (WES). The expression and mutation data of The Cancer Genome Atlas (TCGA)-NSCLC cohort were used to explore the association between TNFα-MT and the immune microenvironment. A local cohort was used to validate the association between TNFα-MT and immunogenicity. TNFα-MT was associated with significantly prolonged overall survival (OS) in NSCLC patients after receiving immunotherapy. Additionally, TNFα-MT is related to high immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations) and enrichment of infiltrating immune cells. These results suggest that TNFα-MT may serve as a potential clinical biomarker for NSCLC patients receiving ICIs.

Glycogen Metabolism Predicts the Efficacy of Immunotherapy for Urothelial Carcinoma

Urothelial cancer (UC) is one of the common refractory tumors and chemotherapy is the primary treatment for it. The advent of immune checkpoint inhibitors (ICI) has facilitated the development of treatment strategies for UC patients. To screen out UC patients sensitive to ICI, researchers have proposed that PD-L1, tumor mutation burden and TCGA molecular subtypes can be used as predictors of ICI efficacy. However, the performance of these predictors needs further validation. We need to identify novel biomarkers to screen out UC patients sensitive to ICI. In our study, we collected the data of two clinical cohorts: the ICI cohort and the TCGA cohort. The result of the multivariate Cox regression analysis showed that glycogen metabolism score (GMS) (HR = 1.26, p = 0.017) was the negative predictor of prognosis for UC patients receiving ICI treatment. Low-GMS patients had a higher proportion of patients achieving complete response or partial response to ICI. After the comparison of gene mutation status between high-GMS and low-GMS patients, we identified six genes with significant differences in mutation frequencies, which may provide new directions for potential drug targets. Moreover, we analyzed the immune infiltration status and immune-related genes expression between high-GMS and low-GMS patients. A reduced proportion of tumor-associated fibroblasts and elevated proportion of CD8⁺ T cells can be observed in low-GMS patients while several immunosuppressive molecules were elevated in the high-GMS patients. Using the sequencing data of the GSE164042 dataset, we also found that myeloid-derived suppressor cell and neutrophil related signature scores were lower in α-glucosidase knockout bladder carcinoma cells when compared to the control group. In addition, angiogenesis, classic carcinogenic pathways, immunosuppressive cells related pathways and immunosuppressive cytokine secretion were mainly enriched in high-GMS patients and cell samples from the control group. Finally, we suspected that the combination treatment of ICI and histone deacetylase inhibitors may achieve better clinical responses in UC patients based on the analysis of drug sensitivity data. In conclusion, our study revealed the predictive value of GMS for ICI efficacy of UC patients, providing a novel perspective for the exploration of new drug targets and potential treatment strategies.

The Impact of NOTCH Pathway Alteration on Tumor Microenvironment and Clinical Survival of Immune Checkpoint Inhibitors in NSCLC

The treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) has been proven to induce lasting tumor remission. Screening suitable populations for immunotherapy through predictive markers is an important approach to improving the clinical benefits of patients. Evidence has shown that there may be a close connection between NOTCH signaling and the tumor microenvironment (TME). Hence, we explored the impact of the mutation status of NOTCH signaling on the prognosis of NSCLC patients treated with immunotherapy with the aim to apply NSCLC immunotherapy to the greatest extent possible. We examined two clinical cohorts of NSCLC patients receiving ICIs (MSKCC and NG cohorts). The mutation and prognostic data of the ICI-treated cohort were used to evaluate the association between the mutation status of NOTCH signaling and prognosis following immunotherapy. The expression and mutation data of The Cancer Genome Atlas (TCGA)-NSCLC cohort were used to analyze the differences in the immune microenvironment under different NOTCH signaling mutation states. In the ICI-treated cohorts, the univariate and multivariate Cox regression analyses indicated that high-mutated NOTCH signaling could serve as an independent predictor of NSCLC patients receiving ICIs. Patients with high-mutated NOTCH signaling had significantly improved progression-free survival (PFS) (P = 0.03, HR = 0.69; MSKCC cohort) and prolonged overall survival (OS) (P = 0.004, HR = 0.34; NG cohort). Additionally, high-mutated NOTCH signaling was related to the inflammatory immune microenvironment, inflammatory expression profile, and enhanced immunogenicity. According to this study, high-mutated NOTCH signaling may serve as a biomarker for the prediction of the prognosis of NSCLC patients treated with ICIs. A series of prospective clinical studies and molecular mechanism explorations are still needed in the future.

Age and Mutations as Predictors of the Response to Immunotherapy in Head and Neck Squamous Cell Cancer

The immunosuppressive tumor microenvironment plays an essential role in the treatment of head and neck squamous cell carcinoma (HNSC). Compared to traditional chemoradiotherapy, immune checkpoint inhibitors (ICIs) have become increasingly important in HNSC therapy. Prior studies linked the efficacy of ICIs to PD-L1, microsatellite instability (MSI), HPV infection, tumor mutation burden (TMB), and tumor lymphocyte infiltration in patients with HNSC, but further verification is needed. Additional predictors are needed to recognize HNSC patients with a good response to ICIs. We collected the clinical information and mutation data of HNSC patients from Memorial Sloan Kettering Cancer Center (MSKCC) and The Cancer Genome Atlas (TCGA) databases to generate two clinical cohorts. The MSKCC cohort was used to recognize predictors related to the efficacy of ICIs, and the TCGA cohort was used to further examine the immune microenvironment features and signaling pathways that are significantly enriched in the subgroups of predictors. Multivariate Cox regression analysis indicated that age (HR = 0.50, p = 0.014) and ARID1A (HR = 0.13, p = 0.048), PIK3CA (HR = 0.45, p = 0.021), and TP53 (HR = 1.82, p = 0.035) mutations were potential predictors for ICI efficacy in HNSC patients. Age > 65 years and ARID1A or PIK3CA mutations correlated with good overall survival (OS). TP53 mutant-type (MT) patients experienced a worse prognosis than TP53 wild-type (WT) patients. The subgroups associated with a good prognosis (age > 65 years, ARID1A-MT, and PIK3CA-MT) universally had a high TMB and increased expression of immune checkpoint molecules. Although TP53-MT was associated with a high TMB, the expression of most immune checkpoint molecules and immune-related genes was lower in TP53-MT patients than TP53-WT patients, which may reflect low immunogenicity. Pathways related to the immunosuppressive tumor microenvironment were mostly enriched in the subgroups associated with a poor prognosis (age ≤ 65 years, low TMB, ARID1A-WT, PIK3CA-WT, and TP53-MT). In conclusion, the factors age > 65 years, PIK3CA-MT, and ARID1A-MT predicted favorable efficacy for ICI treatment in HNSC patients, and TP53 mutation was a negative predictor.

Molecular Profiling of Exceptional Responders to Cancer Therapy

BACKGROUND

The vast majority of metastatic cancers cannot be cured. Palliative treatment may relieve disease symptoms by stopping or slowing cancer growth and may prolong patients' lives, but almost all patients will inevitably develop disease progression after initial response. However, for reasons that are not fully understood, a very few patients will have extraordinary durable responses to standard anticancer treatments.

MATERIALS AND METHODS

We analyzed exceptional responders treated at Fox Chase Cancer Center between September 2009 and November 2017. An exceptional response was defined as a complete response lasting more than 1 year or a partial response or stable disease for more than 2 years. Tumor samples were analyzed using an Ambry Genetics test kit with a 142-gene panel. Messenger RNA expression was evaluated using NanoString's nCounter PanCancer Pathways Panel and Immune Profiling Panel and compared with matched controls for gender, age, and cancer type.

RESULTS

Twenty-six exceptional responders with metastatic bladder, kidney, breast, lung, ovarian, uterine, and colon cancers were enrolled. Mutations were identified in 45 genes. The most common mutation was an EPHA5 nonsynonymous mutation detected in 87.5% of patients. Mutations in DNA damage repair pathway genes were also frequent, suggesting increased genome instability. We also found varying expression of 73 genes in the Pathways panel and 85 genes in the Immune Profiling panel, many of them responsible for improvement in tumor recognition and antitumor immune response.

CONCLUSIONS

The genomic instability detected in our exceptional responders, plus treatment with DNA damage compounds combined with favorable anticancer immunity, may have contributed to exceptional responses to standard anticancer therapies in the patients studied.

IMPLICATIONS FOR PRACTICE

With recent advances in the treatment of cancer, there is increased emphasis on the importance of identifying molecular markers to predict treatment outcomes, thereby allowing precision oncology. In this study, it was hypothesized that there is a "specific biologic signature" in the biology of the cancer in long-term survivors that allows sensitivity to systemic therapy and durability of response. Results showed that DNA damage repair pathway alterations, combined with favorable anticancer immunity, may have contributed to exceptional responses. It is very likely that an in-depth examination of outlier responses will become a standard component of drug development in the future.

PDL1 high expression without TP53, KEAP1 and EPHA5 mutations could better predict survival for patients with NSCLC receiving atezolizumab

BACKGROUND

Non-small cell lung cancer (NSCLC) patients with high expression of PDL1 are more likely to benefit from atezolizumab. There are no relevant research focusing on the relationship between the PDL1 expression and clinical variables and gene mutation types among NSCLC patients.

METHODS

NSCLC patients with confirmed PDL1 expression and gene mutation information from OAK study were included in our study. Logistic regression proportional model was applied to analyze the risk factors on PDL1 high expression. The biomarker evaluable population (BEP) was screened to analyze the gene mutation informaion among these patients. High frequency gene mutations were screened based on different PDL1 expressions. Moreover, the log rank test was applied to analyze the overall survival (OS) difference based on different gene mutation types.

RESULTS

A total of 838 patients with NSCLC were included in our study. White patients are more likely to have PDL1 ≥ 1% (P = 0.004). ERBB4, EP300, PREX2, SLIT2, EPHB1 and IGF2R mutations were high frequency mutations in patients with high PDL1 expression, and the patients with EGFR, SMARCA4, EPHA5, FAT1, STK11, TET2 mutations were more likely to be seen in negative PDL1 expression group. Worse survival could be found in patients with KEAP1 (P < 0.001), TP53 (P = 0.004) and EPHA5 (P = 0.013) mutations who received atezolizumab compared with those who had none of these gene mutations. Importantly, for PDL1 high patients without KEAP1, EPHA5, TP53 mutations receiving atezolizumab, they all showed relatively longer median survival with 22.47, 22.18 and 23.33 months, respectively (all, P < 0.01).

CONCLUSIONS

Different high frequency gene mutations could be found between the patients with high and negative PDL1. PDL1 expression combined with specific gene mutation may better predict the survival for patients receiving atezolizumab.

Alterations in TP53 Are a Potential Biomarker of Bladder Cancer Patients Who Benefit From Immune Checkpoint Inhibition

In recent years, immune checkpoint inhibitors (ICIs) targeting CTLA-4 or PD1/PDL1 have achieved remarkable success in the treatment of bladder cancer (BLCA), but only a few patients have shown durable clinical benefits. The prognostic role of a mutant form of the tumor suppressor gene TP53 (TP53-MT) in predicting the efficacy of ICIs is highly controversial; therefore, in this study, we obtained data for 210 patients from an immunotherapy cohort, 412 patients from The Cancer Genome Atlas (TCGA)-BLCA cohort and 18 BLCA cell lines from Genomics of Drug Sensitivity in Cancer (GDSC), and we performed integrated bioinformatic analysis to explore the relationships between TP53-MT and clinical benefits derived from ICI treatment and the underlying mechanisms. We conclude that TP53-MT is a potential indicator of a relatively good response to ICIs and associated with prolonged overall survival (OS) (log-rank test, hazard ratio (HR) = 0.65 [95% confidence interval (CI), 0.44-0.99], p = 0.041). Through integrated analysis with several platforms, we found that TP53-MT patients were more likely to benefit from ICIs than wild-type P53 (TP53-WT) patients, which may be the result of 2 major mechanisms. First, the patients with TP53-MT showed stronger tumor antigenicity and tumor antigen presentation, as indicated by a higher tumor mutational load, a higher neoantigen load and increased expression of MHC; second, the antitumor immunity preexisting in tumors was stronger in samples with TP53-MT than in those with TP53-WT, including enrichment of interferon-gamma, positive regulation of TNF secretion pathways and increased expression of some immunostimulatory molecules, such as CXCL9 and CXCL10. This study provided some clues for identifying patients who would potentially benefit from ICIs at the somatic genomic level, developing new indications for targeted second-generation sequencing and promoting the development of precision medicine.