Emerging Blood-Based Biomarkers for Predicting Immunotherapy Response in NSCLC

Pan-cancer analysis of super-enhancer-induced LINC00862 and validation as a SIRT1-promoting factor in cervical cancer and gastric cancer

Immune checkpoints inhibitors are effective but it needs more precise biomarkers for patient selection. We explored the biological significance of LINC00862 in pan-cancer by bioinformatics. And we studied its regulatory mechanisms using chromatin immunoprecipitation and RNA immunoprecipitation assays etc. TCGA and single-cell sequencing data analysis indicated that LINC00862 was overexpressed in the majority of tumor and stromal cells, which was related with poor prognosis. LINC00862 expression was related with immune cell infiltration and immune checkpoints expression, and had a high predictive value for immunotherapy efficacy. Mechanistically, LINC00862 competitively bound to miR-29c-3p to unleash SIRT1's tumor-promoting function. SIRT1 inhibitor-EX527 were screened by virtual screening and verified by in vitro and vivo assays. Notably, acetyltransferase P300-mediated super-enhancer activity stimulated LINC00862 transcription. Collectively, LINC00862 could be a diagnostic and prognostic biomarker. LINC00862 could also be a predictive biomarker for immunotherapy efficacy. Super-enhancer activity is the driver for LINC00862 overexpression in cervical cancer and gastric cancer.

MiRNAs and Microbiota in Non-Small Cell Lung Cancer (NSCLC): Implications in Pathogenesis and Potential Role in Predicting Response to ICI Treatment

Lung cancer (LC) is one of the most prevalent cancers in both men and women and today is still characterized by high mortality and lethality. Several biomarkers have been identified for evaluating the prognosis of non-small cell lung cancer (NSCLC) patients and selecting the most effective therapeutic strategy for these patients. The introduction of innovative targeted therapies and immunotherapy with immune checkpoint inhibitors (ICIs) for the treatment of NSCLC both in advanced stages and, more recently, also in early stages, has revolutionized and significantly improved the therapeutic scenario for these patients. Promising evidence has also been shown by analyzing both micro-RNAs (miRNAs) and the lung/gut microbiota. MiRNAs belong to the large family of non-coding RNAs and play a role in the modulation of several key mechanisms in cells such as proliferation, differentiation, inflammation, and apoptosis. On the other hand, the microbiota (a group of several microorganisms found in human orgasms such as the gut and lungs and mainly composed by bacteria) plays a key role in the modulation of inflammation and, in particular, in the immune response. Some data have shown that the microbiota and the related microbiome can modulate miRNAs expression and vice versa by regulating several intracellular signaling pathways that are known to play a role in the pathogenesis of lung cancer. This evidence suggests that this axis is key to predicting the prognosis and effectiveness of ICIs in NSCLC treatment and could represent a new target in the treatment of NSCLC. In this review, we highlight the most recent evidence and data regarding the role of both miRNAs and the lung/gut microbiome in the prediction of prognosis and response to ICI treatment, focusing on the link between miRNAs and the microbiome. A new potential interaction based on the underlying modulated intracellular signaling pathways is also shown.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

Serum immune mediators as novel predictors of response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer patients with high tissue-PD-L1 expression

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related morbidity and mortality worldwide. Immune checkpoint inhibitors (ICIs) including anti-PD-1 and anti-PD-L1 antibodies, have significantly changed the treatment outcomes with better overall survival, but only 15-40% of the patients respond to ICIs therapy. The search for predictive biomarkers of responses is warranted for better clinical outcomes. We aim here to identify pre-treatment soluble immune molecules as surrogate biomarkers for tissue PD-L1 (TPD-L1) status and as predictors of response to anti-PD-1/PD-L1 therapy in NSCLC patients. Sera from 31 metastatic NSCLC patients, eligible for anti-PD-1/PD-L1 or combined chemoimmunotherapy, were collected prior to treatment. Analysis of soluble biomarkers with TPD-L1 status showed significant up/down regulation of the immune inhibitory checkpoint markers (sSiglec7, sSiglec9, sULBP4 and sPD-L2) in patients with higher TPD-L1 (TPD-L1 >50%) expression. Moreover, correlation analysis showed significant positive linear correlation of soluble PD-L1 (sPD-L1) with higher TPD-L1 expression. Interestingly, only responders in the TPD-L1 >50% group showed significant down regulation of the immune inhibitory markers (sPD-L2, sTIMD4, sNectin2 and CEA). When responders vs. non-responders were compared, significant down regulation of other immune inhibitory biomarkers (sCD80, sTIMD4 and CEA) was recorded only in responding patients. In this, the optimal cut-off values of CD80 <91.7 pg/ml and CEA <1614 pg/ml were found to be significantly associated with better progression free survival (PFS). Indeed, multivariate analysis identified the cutoff-value of CEA <1614 pg/ml as an independent predictor of response in our patients. We identified here novel immune inhibitory/stimulatory soluble mediators as potential surrogate/predictive biomarkers for TPD-L1 status, treatment response and PFS in NSCLC patients treated with anti-PD-1/PD-L1 therapy.

SECTM1 is upregulated in immuno-hot tumors and predicts immunotherapeutic efficacy in multiple cancers

Immune checkpoint inhibitors (ICIs) have transformed the management of advanced cancers. However, many patients could not benefit from ICIs therapy, and thus several biomarkers for therapeutic prediction have been uncovered. In this research, more than ten public and in-house cohorts were used to explore the predictive value and immunological correlations of secreted and transmembrane 1 (SECTM1) in cancers. SECTM1 expression was enhanced in tumors from patients with well immunotherapeutic responses in multiple cancers. In addition, SECTM1 was immuno-correlated in pan-cancer and enhanced in immuno-hot tumors. In vitro assays revealed that SECTM1 was upregulated by the IFN-γ/STAT1 signaling. Moreover, analysis of in-house immunotherapy cohorts suggested both tumor-expressed and circulating SECTM1 are promising biomarkers to predict therapeutic responses. Overall, this study reveals that SECTM1 is a biomarker of benefit to ICIs in cancer patients. Further studies including large-scale patients are needed to establish its utilization as a biomarker of benefit to ICIs.

Circulating Biomarkers for Prediction of Immunotherapy Response in NSCLC

Non-small cell lung cancer (NSCLC) constitutes the majority of the lung cancer population and the prognosis is poor. In recent years, immunotherapy has become the standard of care for advanced NSCLC patients as numerous trials demonstrated that immune checkpoint inhibitors (ICI) are more efficacious than conventional chemotherapy. However, only a minority of NSCLC patients benefit from this treatment. Therefore, there is an unmet need for biomarkers that could accurately predict response to immunotherapy. Liquid biopsy allows repeated sampling of blood-based biomarkers in a non-invasive manner for the dynamic monitoring of treatment response. In this review, we summarize the efforts and progress made in the identification of circulating biomarkers that predict immunotherapy benefit for NSCLC patients. We also discuss the challenges with future implementation of circulating biomarkers into clinical practice.

Low on-treatment levels of serum soluble CD8 (sCD8) predict better outcomes in advanced non-small cell lung cancer patients treated with atezolizumab

BACKGROUND

Immunotherapy has changed the paradigm of treating non-small cell lung cancer (NSCLC). But, selecting patients who will achieve long-term benefits from treatment remains unsatisfactory. Here, we investigated the possible use of the soluble form of CD8 antigen (sCD8) in predicting durable disease control after PD-1/PD-L1 blockade. CD8 is a marker of the cytotoxic T lymphocytes. Its soluble form (sCD8) is secreted under activation of the immune system but also has immunosuppressive properties. The data about serum sCD8 in patients dosed with anti-PD-1/PD-L1 drugs are lacking.

METHODS AND RESULTS

We included 42 NSCLC patients and collected samples at baseline and for the first 3 months of atezolizumab immunotherapy. The serum sCD8 concentrations were measured with the ELISA kit and correlated with treatment outcomes. Patients with durable (≥ 12 months) disease control presented lower serum sCD8 than those without long-term benefits. The sCD8 levels measured at the end of cycle 2 (sCD8.2) were the earliest time point that successfully differentiated patients (3.76 vs. 9.68 ng/mL, respectively, p < 0.001). Individuals with low sCD8.2 (≤ 4.09 ng/mL) presented longer progression-free survival (HR = 0.061, p < 0.001) and overall survival (HR = 0.104, p < 0.05) compared to individuals with high sCD8.2 (median values unreached vs. 4.4 months and 14.4 months for PFS and OS, respectively).

CONCLUSIONS

Serum sCD8 could be an early biomarker of durable disease control after anti-PD-L1 treatment. Higher sCD8 in patients with worse outcomes could suggest the inhibitory effect of sCD8 on cytotoxic T-cells activation.

Association between serum levels of 12 different cytokines and short-term efficacy of anti-PD-1 monoclonal antibody combined with chemotherapy in advanced gastric cancer

BACKGROUND

Gastric cancer (GC) is characterized by aggressive tumor growth and poor prognosis. The benefits of targeted anti-programmed death receptor 1 (PD-1) monoclonal antibody combined with chemotherapy have not yet been characterized. The tumor microenvironment and circulating factors have garnered interest as possible predictors of response and prognosis. The aim of this study was to evaluate whether cytokine levels in the serum of patients were related to tumor response to anti-PD-1 monoclonal antibody combined with chemotherapy and survival in advanced GC.

MATERIALS AND METHODS

Preoperative serum samples were collected from patients with GC (n = 52) and healthy individuals (n = 31). The levels of 12 different cytokines were measured using a multiple microsphere flow immunofluorescence assay. The association between cytokine levels and clinical response was analyzed using nonparametric Wilcoxon matched-pair ranked tests. Progression-free survival (PFS) time for all patients was recorded via evaluation of imaging results and follow-up via telephone. Kaplan-Meier and log-rank tests were used to plot survival curves.

RESULTS

The levels of interleukin (IL)-6, IL-1β, interferon (IFN)-γ, IL-17, and IL-12p70 in the control group were significantly lower than those in the GC group (p = 0.0002, p = 0.0065, p = 0.0003, p = 0.0303, and p = 0.0295, respectively). The level of IL-4 was significantly higher in healthy individuals than that in patients with GC (p = 0.0201). The cytokine levels in the good responder group were higher than those in the poor responder group before therapy. Patients treated with immunochemotherapy showed an overall reduction in all cytokine levels after treatment initiation. A high baseline level of IFN-γ was associated with a better prognosis. However, high IL-6 levels in patients after two cycles of immunochemotherapy indicated resistance. High IL-4 levels in patients treated with four cycles of immunochemotherapy were associated with better PFS.

CONCLUSIONS

Our study suggests that low levels of IFN-γ before immune checkpoint inhibitor treatment may be useful for the detection of a poor immunological status. Hence, a reduction in IL-6 levels is predictive of a longer PFS, and increased IL-4 levels are predictive of a good response. IL-4 and IL-6 may, therefore, serve as promising circulating predictive biomarkers for patients who can benefit from anti-PD-1 monoclonal antibodies administered in combination with chemotherapy.

Integrated single-cell and transcriptome sequencing analyses determines a chromatin regulator-based signature for evaluating prognosis in lung adenocarcinoma

BACKGROUND

Accumulating evidence has highlighted the significance of chromatin regulator (CR) in pathogenesis and progression of cancer. However, the prognostic role of CRs in LUAD remains obscure. We aim to detect the prognostic value of CRs in LUAD and create favorable signature for assessing prognosis and clinical value of LUAD patients.

METHODS

The mRNA sequencing data and clinical information were obtained from TCGA and GEO databases. Gene consensus clustering analysis was utilized to determine the molecular subtype of LUAD. Cox regression methods were employed to set up the CRs-based signature (CRBS) for evaluating survival rate in LUAD. Biological function and signaling pathways were identified by KEGG and GSEA analyses. In addition, we calculated the infiltration level of immunocyte by CIBERSORT algorithm. The expressions of model hub genes were detected in LUAD cell lines by real-time polymerase chain reaction (PCR).

RESULTS

KEGG analysis suggested the CRs were mainly involved in histone modification, nuclear division and DNA modification. Consensus clustering analysis identified a novel CRs-associated subtype which divided the combined LUAD cohort into two clusters (C1 = 217 and C2 = 296). We noticed that a remarkable discrepancy in survival rate among two clusters. Then, a total of 120 differentially expressed CRs were enrolled into stepwise Cox analyses. Four hub CRs (CBX7, HMGA2, NPAS2 and PRC1) were selected to create a risk signature which could accurately forecast patient outcomes and differentiate patient risk. GSEA unearthed that mTORC1 pathway, PI3K/Akt/mTOR and p53 pathway were greatly enriched in CRBS-high cohort. Moreover, the infiltration percentages of macrophage M0, macrophage M2, resting NK cells, memory B cells, dendritic cells and mast cells were statistically significantly different in the two groups. PCR assay confirmed the differential expression of four model biomarkers.

CONCLUSIONS

Altogether, our project developed a robust risk signature based on CRs and offered novel insights into individualized treatment for LUAD cases.