CSF1R and HCST: Novel Candidate Biomarkers Predicting the Response to Immunotherapy in Non-Small Cell Lung Cancer

Further knowledge and developments in resistance mechanisms to immune checkpoint inhibitors

The past decade has witnessed a revolution in cancer treatment, shifting from conventional drugs (chemotherapies) towards targeted molecular therapies and immune-based therapies, in particular immune-checkpoint inhibitors (ICIs). These immunotherapies release the host's immune system against the tumor and have shown unprecedented durable remission for patients with cancers that were thought incurable, such as metastatic melanoma, metastatic renal cell carcinoma (RCC), microsatellite instability (MSI) high colorectal cancer and late stages of non-small cell lung cancer (NSCLC). However, about 80% of the patients fail to respond to these immunotherapies and are therefore left with other less effective and potentially toxic treatments. Identifying and understanding the mechanisms that enable cancerous cells to adapt to and eventually overcome therapy can help circumvent resistance and improve treatment. In this review, we describe the recent discoveries on the onco-immunological processes which govern the tumor microenvironment and their impact on the resistance to PD-1/PD-L1 checkpoint blockade.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

YAP1 as a Novel Negative Biomarker of Immune Checkpoint Inhibitors for EGFR-Mutant Non-Small-Cell Lung Cancer

Background

Immune checkpoint inhibitors (ICIs) have become a standard care in non-small-cell lung cancer (NSCLC). However, its application to epidermal growth factor receptor (EGFR)-mutant NSCLC patients is confronted with drug resistance. This study aimed to clarify the potential role of Yes1-associated transcriptional regulator (YAP1) in ICIs treatment for EGFR-mutant NSCLC population.

Methods

All the clinical data of NSCLC were downloaded from Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) for GSE11969 and GSE72094. Based on YAP1 expression, all the NSCLC patients including the EGFR-mutant and EGFR-wildtype (WT) patients were divided into two groups, YAP1_High and YAP1_Low. Using cBioPortal, genetic alterations were analyzed for identification of immunogenicity in EGFR-mutant NSCLC. MR analysis was used to analyze the hub gene of EGFR. The infiltration of immune cells and the expression of the identified tumor-associated antigens were identified with TIMER. By graph learning-based dimensionality reduction analysis, the immune landscape was visualized. Moreover, survival analysis was performed to verify the predictive value of YAP1 in ICIs treatment for EGFR-mutant NSCLC population using Ren's research data (NCT03513666).

Results

YAP1 was a poor prognostic factor of EGFR-mutant NSCLC population rather than lung adenocarcinoma (LUAD) patients. MR analysis revealed that the EGFR gene regulated YAP1 expression. YAP1 was identified as a hub gene closely associated with immunosuppressive microenvironment and poor prognosis in EGFR-mutant NSCLC population in TCGA LUAD. Tumors with YAP1_High showed an immune-"cold" and immunosuppressive phenotype, whereas those with YAP1_Low demonstrated an immune-"hot" and immunoactive phenotype. More importantly, it was verified that YAP1_High subpopulation had a significantly shorter progression-free survival (PFS) and overall survival (OS) after ICIs treatment in EGFR-mutant NSCLC patients in the clinical trial.

Conclusions

YAP1 mediates immunosuppressive microenvironment and poor prognosis in EGFR-mutant NSCLC population. YAP1 is a novel negative biomarker of ICIs treatment in EGFR-mutant NSCLC population. Clinical Trials. This trial is registered with NCT03513666.

Tumor Suppressor Role of INPP4B in Chemoresistant Retinoblastoma

The chemotherapy of retinoblastoma (RB), a malignant ocular childhood disease, is often limited by the development of resistance against commonly used drugs. We identified inositol polyphosphate 4-phosphatase type II (INPP4B) as a differentially regulated gene in etoposide-resistant RB cell lines, potentially involved in the development of RB resistances. INPP4B is controversially discussed as a tumor suppressor and an oncogenic driver in various cancers, but its role in retinoblastoma in general and chemoresistant RB in particular is yet unknown. In the study presented, we investigated the expression of INPP4B in RB cell lines and patients and analyzed the effect of INPP4B overexpression on etoposide resistant RB cell growth in vitro and in vivo. INPP4B mRNA levels were significantly downregulated in RB cells lines compared to the healthy human retina, with even lower expression levels in etoposide-resistant compared to the sensitive cell lines. Besides, a significant increase in INPP4B expression was observed in chemotherapy-treated RB tumor patient samples compared to untreated tumors. INPP4B overexpression in etoposide-resistant RB cells resulted in a significant reduction in cell viability with reduced growth, proliferation, anchorage-independent growth, and in ovo tumor formation. Caspase-3/7-mediated apoptosis was concomitantly increased, suggesting a tumor suppressive role of INPP4B in chemoresistant RB cells. No changes in AKT signaling were discernible, but p-SGK3 levels increased following INPP4B overexpression, indicating a potential regulation of SGK3 signaling in etoposide-resistant RB cells. RNAseq analysis of INPP4B overexpressing, etoposide-resistant RB cell lines revealed differentially regulated genes involved in cancer progression, mirroring observed in vitro and in vivo effects of INPP4B overexpression and strengthening INPP4B’s importance for cell growth control and tumorigenicity.

Pexidartinib synergize PD-1 antibody through inhibiting treg infiltration by reducing TAM-derived CCL22 in lung adenocarcinoma

There is a crosstalk between Tumor-associated macrophages (TAM) and tumor-infiltrating T cells in tumor environment. TAM could inhibit the activity of cytotoxic T cells; TAM could also regulate the composition of T cells in tumor immune environment. The combination therapy for TAM and tumor infiltrated T cells has been widely noticed, but the crosstalk between TAM and tumor infiltrated T cells remains unclear in the process of combination therapy. We treated lung adenocarcinoma tumor models with pexidartinib, which targets macrophage colony stimulating factor receptor (M-CSFR) and c-kit tyrosine kinase, to inhibited TAM. Pexidartinib inhibited the ratio of macrophages in the tumor and also altered macrophage polarization. In addition to reprogram TAM, pexidartinib also changed the composition of tumor-invasive T cells. After pexidartinib treatment, the total number of T cells, CD8⁺ T cells and Treg cells were all decreased, the ratio of CD8+T/Treg increased significantly. According to the analysis of cytokines and chemokines during the treatment of pexidartinib, CCL22, as a chemokine for Treg recruitment, significantly decreased after the treatment of pexidartinib. Base on the above observation, the combination of pexidartinib and PD-1 antibody were used in the treatment of lung adenocarcinoma subcutaneous tumor model, the combination therapy has significantly improved the efficacy of tumor treatment compared with the monotherapy. Meanwhile, compared with pexidartinib monotherapy, the combination treatment further switches the polarization status of tumor-associated macrophages. In summary, our results showed that the combination of pexidartinib and PD-1 antibody showed a synergy and significantly improved the anti-tumor efficacy, through pexidartinib increasing CD8T/Treg ratio by reducing TAM-derived CCL22.

Spatial transcriptomics of macrophage infiltration in non-small cell lung cancer reveals determinants of sensitivity and resistance to anti-PD1/PD-L1 antibodies

BACKGROUND

Tumor-associated macrophages (TAMs) having immunosuppressive properties are one of the most abundant immune cells in the tumor microenvironment (TME). Preclinical studies have highlighted the potential role of TAMs in resistance to immune checkpoint blockers (ICBs). Here, we investigated the predictive value of TAM infiltration in patients with non-small cell lung cancer (NSCLC) treated with ICBs and characterized their transcriptomic profiles.

METHODS

Tumor samples were collected from 152 patients with NSCLC before ICB treatment onset. After immunohistochemical staining and image analysis, the correlation between CD163+ cell infiltration and survival was analyzed. Spatial transcriptomic analyses were performed using the NanoString GeoMx Immune Pathways assay to compare the gene expression profile of tumors with high or low levels of CD163+ cell infiltration and to identify determinants of response to ICBs in tumors with high CD163+ infiltration.

RESULTS

Low intratumoral CD163+ cell infiltration was associated with longer progression-free survival (PFS; HR 0.61, 95% CI 0.40 to 0.94, p=0.023) and overall survival (OS; HR 0.48, 95% CI 0.28 to 0.80, p=0.004) under ICB treatment. Spatial transcriptomic profiles of 16 tumors revealed the upregulation of ITGAM, CD27, and CCL5 in tumors with high CD163+ cell infiltration. Moreover, in tumors with high macrophage infiltration, the upregulation of genes associated with the interferon-γ signaling pathway and the M1 phenotype was associated with better responses under immunotherapy. Surprisingly, we found also a significantly higher expression of CSF1R in the tumors of responders. Analysis of three independent data sets confirmed that high CSF1R expression was associated with an increased durable clinical benefit rate (47% vs 6%, p=0.004), PFS (median 10.89 months vs 1.67 months, p=0.001), and OS (median 23.11 months vs 2.66 months, p<0.001) under ICB treatment.

CONCLUSIONS

Enrichment of TAMs in the TME of NSCLC is associated with resistance to immunotherapy regardless of the programmed death ligand 1 status and is driven by upregulation of CD27, ITGAM, and CCL5 gene expression within the tumor compartment. Our transcriptomic analyses identify new potential targets to alter TAM recruitment/polarization and highlight the complexity of the CSF1R pathway, which may not be a suitable target to improve ICB efficacy.

Comprehensive assessment of cellular senescence in the tumor microenvironment

Cellular senescence (CS), a state of permanent growth arrest, is intertwined with tumorigenesis. Due to the absence of specific markers, characterizing senescence levels and senescence-related phenotypes across cancer types remain unexplored. Here, we defined computational metrics of senescence levels as CS scores to delineate CS landscape across 33 cancer types and 29 normal tissues and explored CS-associated phenotypes by integrating multiplatform data from ~20 000 patients and ~212 000 single-cell profiles. CS scores showed cancer type-specific associations with genomic and immune characteristics and significantly predicted immunotherapy responses and patient prognosis in multiple cancers. Single-cell CS quantification revealed intra-tumor heterogeneity and activated immune microenvironment in senescent prostate cancer. Using machine learning algorithms, we identified three CS genes as potential prognostic predictors in prostate cancer and verified them by immunohistochemical assays in 72 patients. Our study provides a comprehensive framework for evaluating senescence levels and clinical relevance, gaining insights into CS roles in cancer- and senescence-related biomarker discovery.

The roles and potential mechanisms of HCST in the prognosis and immunity of KIRC via comprehensive analysis

OBJECTIVES

Hematopoietic cell signal transducer (HCST) participates in the activation of phosphatidylinositol 3 kinase-dependent signaling pathway and in the natural killer (NK) and T cell responses, which affect cell survival and proliferation. Here, the values of HCST in kidney renal clear cell carcinoma (KIRC) are analyzed.

METHODS

We used GEO, TCGA, GEPIA, UALCAN and TIMER databases to profile the expression of HCST in KIRC tissues, and define its clinical roles. The biological functions and signaling mechanisms modulated by HCST and its co-expressed genes were identified and analyzed via the GO and KEGG databases. On the other hand, the potential value of HCST expression in KIRC immunity was explored using the TIMER and GEPIA databases.

RESULTS

Our analysis demonstrated that HCST is significantly overexpressed in KIRC tissues. The upregulation of HCST is associated with clinical stage, tumor grade, tissue subtype and poor prognosis of KIRC patients. Increased HCST expression might be involved in signaling pathways such as antigen processing and presentation, cell adhesion molecules, cytokine-cytokine receptor, chemokine signaling pathway, T cell receptor signaling pathway, FC gammar mediated phagocytosis and B cell receptor signaling pathway. In addition, the expression of HCST was significantly correlated with the levels of KIRC purity, B cells, CD8⁺ T Cell, CD4⁺ T cells, macrophages, neutrophils and dendritic cells (DC). Furthermore, the HCST expression is associated with levels of immune infiltration B cells, CD8⁺ T Cell, CD4⁺ T cells, macrophages, neutrophils and DC.

CONCLUSIONS

Our data demonstrated that HCST could be a potential prognostic biomarker, and is related to the immune infiltration in KIRC.

Identification of JAK2 and FOXM1 expression as novel candidate biomarkers for predicting the benefit of immunotherapy in lung squamous cell carcinoma

Background

Lung squamous cell carcinoma (LUSC) accounts for about 30% of all non-small cell lung cancers (NSCLC). However, only a small percentage of LUSC patients gain benefit from immune checkpoint inhibitors (ICIs).

Methods

This study analyzed LUSC patients from The Cancer Genome Atlas (TCGA), which were divided into 2 groups: PD-L1 high-expression/TMB-high (TPH) and PD-L1 low-expression/TMB-low (TPL) group based on programmed death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB) status. The differences in tumor-infiltrating immune cells were estimated between the 2 groups. The overlap of differentially expressed genes and proteins (DEGs and DEPs) between 2 groups were used as candidate biomarkers. Kaplan-Meier curves were used to evaluate the association between risk score and overall survival (OS).

Results

More abundant immune infiltration fractions were found in TPH group. Janus kinase 2 (JAK2) and forkhead box protein M1 (FOXM1) were identified as DEGs between the TPH and TPL groups. Subsequently, we developed a risk score that combined the expression of JAK2 and FOXM1 in an effort to accurately determine the survival risk of LUSC patients. Patients with high-risk [hazard ratio (HR), median OS, 43.1 months 1.924; 95% confidence interval (CI): 1.256 to 2.945; P=0.002) had shorter survival than those with low-risk (median OS, 70.0 months). External data verification found that JAK2 and FOXM1 were significantly expressed at a higher level in the responders receiving immunotherapy (P=0.038 and P=0.009, respectively).

Conclusions

The expressions of JAK2 and FOXM1 can be used as novel candidate biomarkers for predicting the benefit of immunotherapy in LUSC.

The Immune-Related Gene HCST as a Novel Biomarker for the Diagnosis and Prognosis of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor worldwide. Analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases showed that the immune-related gene (IRG) hematopoietic cell signal transducer (HCST) could provide guidance for the diagnosis, prognosis, and treatment of ccRCC. The RNA-seq data of ccRCC tissues were extracted from two databases: TCGA (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) and GEO (https://www.ncbi.nlm.nih.gov/geo/). Corresponding clinical information was downloaded from TCGA. Immune-related gene data were extracted from the IMMPORT website (https://www.immport.org/). Differential analysis with R software (https://www.r-project.org/) was used to obtain a prognosis model of ccRCC IRGs. The differences were combined with the clinical data to assess the usefulness of the HCST as a prognostic biomarker. Based on data obtained from the Oncomine (https://www.oncomine.org/), Human Protein Atlas (https://www.proteinatlas.org/), and PubMed (https://pubmed.ncbi.nlm.nih.gov/) databases, the expression levels of the HCST in ccRCC, clinical-pathological indicators of relevance, and influence on prognosis were analyzed. Regulation of the HCST gene in ccRCC was assessed by gene set enrichment analysis (GSEA). In TCGA/GEO databases, the high HCST expression in tumor tissues was significantly correlated to the TMN stage, tumor grade, invasion depth, and lymphatic metastasis (p < 0.05). The overall survival (OS) of patients with high HCST gene expression was significantly lower than that of patients with low HCST gene expression (p < 0.001). Multivariate Cox regression analysis suggested that the HCST expression level [hazard ratio (HR) = 1.630, 95% confidence interval (CI) = 1.042–2.552], tumor cell grade (HR = 1.829, 95% CI = 1.115–3.001), and distant metastasis (HR = 2.634, 95%, CI = 1.562–4.442) were independent risk factors affecting the OS of ccRCC patients (all, p < 0.05). The GSEA study showed that there was significant enrichment in cell adhesion, tumorigenesis, and immune and inflammatory responses in HCST high expression samples. Hematopoietic cell signal transducer expression was closely associated with the levels of infiltrating immune cells around ccRCC tissues, especially dendritic cells (DCs). In conclusion, the present study suggested that the HCST was interrelated to the clinicopathology and poor prognosis of ccRCC. High HCST expression was also closely correlated with the levels of tumor-infiltrating immune cells, especially DCs.

The tumor environment immune phenotype of LUSC by genome-wide analysis

PURPOSE

To compare the landscape of tumor microenvironment (TME) of lung squamous carcinoma (LUSC) in different immune pattern and explore potential factors on immune therapy and prognosis.

METHOD AND MATERIALS

We have obtained the LUSC data from TCGA, GEO, and our department and classified them into 2 TME clusters by random forest model based on the infiltration pattern of 24 immune cell populations. We systemically compared the genomic significance, clinical characteristics, and immune infiltration pattern in 2 TME clusters.

RESULTS

Samples were divided into 2 TME clusters based on the relative abundance of 24 immune cells, and a random forest classifier model was constructed. TME cluster B was a higher immune infiltration group with lower mutation load, richer co-infiltrate immune cells, upregulated immune-related cytokines, immune checkpoint molecules, and higher active immune cells. TME cluster was also an independent predictor in prognosis (B vs. A, p < 0.05) in patients from TCGA, GEO, and our department.

CONCLUSIONS

Our study has described the microenvironment landscape of LUSC in different immune infiltration patterns and systemically analyzed genomic and clinical characteristics with distinct immunophenotypes, thus partly revealed the interaction between tumors and the immune microenvironment, which may guide a more precise and personalized immune therapeutic strategy for LUSC patients.