Prospects of targeted and immune therapies in SCLC

Construction and validation of a nomogram to predict the overall survival of small cell lung cancer: a multicenter retrospective study in Shandong province, China

BACKGROUND

Patients diagnosed with small cell lung cancer (SCLC) typically experience a poor prognosis, and it is essential to predict overall survival (OS) and stratify patients based on distinct prognostic risks.

METHODS

Totally 2309 SCLC patients from the hospitals in 15 cities of Shandong from 2010 - 2014 were included in this multicenter, population-based retrospective study. The data of SCLC patients during 2010-2013 and in 2014 SCLC were used for model development and validation, respectively. OS served as the primary outcome. Univariate and multivariate Cox regression were applied to identify the independent prognostic factors of SCLC, and a prognostic model was developed based on these factors. The discrimination and calibration of this model were assessed by the time-dependent C-index, time-dependent receiver operator characteristic curves (ROC), and calibration curves. Additionally, Decision Curve Analysis (DCA) curves, Net Reclassification Improvement (NRI), and Integrated Discriminant Improvement (IDI) were used to assess the enhanced clinical utility and predictive accuracy of the model compared to TNM staging systems.

RESULTS

Multivariate analysis showed that region (Southern/Eastern, hazard ratio [HR] = 1.305 [1.046 - 1.629]; Western/Eastern, HR = 0.727 [0.617 - 0.856]; Northern/Eastern, HR = 0.927 [0.800 - 1.074]), sex (female/male, HR = 0.838 [0.737 - 0.952]), age (46-60/≤45, HR = 1.401 [1.104 - 1.778]; 61-75/≤45, HR = 1.500 [1.182 - 1.902]; >75/≤45, HR = 1.869 [1.382 - 2.523]), TNM stage (II/I, HR = 1.119[0.800 - 1.565]; III/I, HR = 1.478 [1.100 - 1.985]; IV/I, HR = 1.986 [1.477 - 2.670], surgery (yes/no, HR = 0.677 [0.521 - 0.881]), chemotherapy (yes/no, HR = 0.708 [0.616 - 0.813]), and radiotherapy (yes/no, HR = 0.802 [0.702 - 0.917]) were independent prognostic factors of SCLC patients and were included in the nomogram. The time-dependent AUCs of this model in the training set were 0.699, 0.683, and 0.683 for predicting 1-, 3-, and 5-year OS, and 0.698, 0.698, and 0.639 in the validation set, respectively. The predicted calibration curves aligned with the ideal curves, and the DCA curves, the IDI, and the NRI collectively demonstrated that the prognostic model had a superior net benefit than the TNM staging system.

CONCLUSION

The nomogram using SCLC patients in Shandong surpassed the TNM staging system in survival prediction accuracy and enabled the stratification of patients with distinct prognostic risks based on nomogram scores.

Delta-like ligand 3 in small cell lung cancer: Potential mechanism and treatment progress

Small cell lung cancer (SCLC) is one of a pathological type of lung cancer, and it is characterized by invasiveness, high malignancy and refractoriness. The mortality rate of SCLC is significantly higher than other types of lung cancer, and the treatment options for SCLC patients are limited. Delta-like ligand 3 (DLL3) is a Notch signaling ligand that plays a role in regulating the proliferation, development and metastasis of SCLC cells. Mnay studies have shown that DLL3 is overexpressed on the surface of SCLC cells, suggesting that DLL3 is a potential target for SCLC patients. A series of drug trials targeting DLL3 are underway. The Phase III clinical trials of Rova-T, a drug targeting DLL3, have not yielded the expected results. However, other drugs that target DLL3, such as AMG119, AMG757 and DLL3-targeted NIR-PIT, bring new ideas for SCLC treatment. Overall, DLL3 remains a valuable target for SCLC.

Analysis of Baseline Serum Lipid Profile for Predicting Clinical Outcomes of Patients with Extensive-Stage Small Cell Lung Cancer

Purpose

Serum lipids were reported to be the prognostic factors of various cancers, but their prognostic value in small cell lung cancer (SCLC) patients remains unclear. This study investigated the relationship between lipid profiles and clinical outcomes in extensive-stage (ES) SCLC by establishing a predictive risk classification model.

Patients and Methods

We retrospectively analyzed the prognostic values of pretreatment serum lipids and their derivatives in patients with a confirmed diagnosis ES-SCLC. Independent factors of progression-free survival (PFS) were determined by univariate and multivariate cox analysis. Then, prognostic nomograms were established, of which predictive performance was evaluated by concordance index (C-index), calibration curves, receiver operating characteristic (ROC) curves, and decision curve analyses (DCA).

Results

A total of 158 patients was included in this study. Four optimal PFS-related factors, total cholesterol (TC) ≥ 5.30, high-density lipoprotein cholesterol (HDL-C) > 1.30, triglycerides (TG)/HDL-C  > 2.18, and ki67 expression > 70%, were included to construct the predictive nomogram. The C-indexes in training and validation sets were 0.758 and 0.792, respectively. ROC curves, calibration plots, and DCA all suggested favorable discrimination and predictive ability. Besides, the nomogram also performed better predictive ability than ki67 expression. Nomogram-related risk score divided the patients into two groups with significant progression disparities.

Conclusion

The promising prognostic nomogram based on lipid parameters could help clinicians to conveniently and accurately evaluate the prognosis of ES-SCLC patients and identify high-risk groups, so as to formulate individualized therapeutic regimens and follow-up strategies in time.

Potential predictors of immunotherapy in small cell lung cancer

Lung cancer is one of the leading causes of cancer-related deaths worldwide, with small cell lung cancer (SCLC) having the worst prognosis. SCLC is diagnosed late in the disease's progression, limiting treatment options. The most common treatment for SCLC is chemotherapy. As the disease progresses, immunotherapy, most commonly checkpoint inhibitor medication, becomes more important. Efforts should be made in the development of immunotherapy to map specific biomarkers, which play a role in properly assigning a type of immunotherapy to the right cohort of patients, where the benefits outweigh any risks or adverse effects. The objective of this review was to provide a thorough assessment of current knowledge about the nature of the tumor process and treatment options for small cell lung cancer, with a focus on predictive biomarkers. According to the information obtained, the greatest potential, which has already been directly demonstrated in some studies, has characteristics such as tumor microenvironment composition, tumor mutation burden, and molecular subtyping of SCLC. Several other aspects appear to be promising, but more research, particularly prospective studies on a larger number of probands, is required. However, it is clear that this field of study will continue to expand, as developing a reliable method to predict immunotherapy response is a very appealing goal of current medicine and research in the field of targeted cancer therapy.

Prognostic biomarkers and immune cell infiltration characteristics in small cell lung cancer

Background

Small cell lung cancer (SCLC) is a highly malignant and aggressive neuroendocrine tumor. With the rise of immunotherapy, it has provided a new direction for SCLC. However, due to the lack of prognostic biomarkers, the median overall survival of SCLC is still to be improved. This study aimed to explore novel biomarkers and tumor-infiltrating immune cell characteristics that may serve as potential diagnostic and prognostic markers in SCLC.

Methods

Gene expression profiles from patients with SCLC were downloaded from the Gene Expression Omnibus (GEO) database, and tumor microenvironment (TME) infiltration profile data were obtained using CIBERSORT. The robust rank aggregation (RRA) method was utilized to integrate three SCLC microarray datasets downloaded from the GEO database and identify robust differentially expressed genes (DEGs) between normal and tumor tissue samples. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to explore the functions of the robust DEGs. Subsequently, protein-protein interaction networks and key modules were constructed by Cytoscape, and hub genes were selected from the whole network using the plugin cytoHubba. Survival analysis of hub genes was performed by Kaplan-Meier plotter in 18 patients with extensive-stage SCLC.

Results

A total of 312 robust DEGs, including 55 upregulated and 257 downregulated genes, were screened from 129 SCLC tissue samples and 44 normal tissue samples. GO and KEGG enrichment analyses revealed that the robust DEGs were predominantly involved in human T-cell leukemia virus 1 infection, focal adhesion, complement and coagulation cascades, tumor necrosis factor (TNF) signaling pathway, and ECM-receptor interaction, which are closely associated with the development and progression of SCLC. Subsequently, three DEGs modules and six hub genes (ITGA10, DUSP12, PTGS2, FOS, TGFBR2, and ICAM1) were identified through screening with the Cytoscape plugins MCODE and cytoHubba, respectively. Immune cell infiltration analysis by the CIBERSORT algorithm revealed that resting memory CD4+ T cells were the predominant infiltrating immune cells in SCLC. In addition, Kaplan-Meier plotter revealed that the gene prostaglandin-endoperoxide synthase 2 (PTGS2) was a potential prognostic biomarker of SCLC.

Conclusions

Hub genes and tumor-infiltrating immune cells may be the molecular mechanisms underlying the development of SCLC, and this finding could contribute to the formulation of individualized immunotherapy strategies for SCLC.

Small-Cell Lung Cancer Long-Term Survivor Patients: How to Find a Needle in a Haystack?

Small-cell lung cancer (SCLC) is an aggressive malignancy characterized by a rapid progression and a high resistance to treatments. Unlike other solid tumors, there has been a scarce improvement in emerging treatments and survival during the last years. A better understanding of SCLC biology has allowed for the establishment of a molecular classification based on four transcription factors, and certain therapeutic vulnerabilities have been proposed. The universal inactivation of TP53 and RB1, along with the absence of mutations in known targetable oncogenes, has hampered the development of targeted therapies. On the other hand, the immunosuppressive microenvironment makes the success of immune checkpoint inhibitors (ICIs), which have achieved a modest improvement in overall survival in patients with extensive disease, difficult. Currently, atezolizumab or durvalumab, in combination with platinum–etoposide chemotherapy, is the standard of care in first-line setting. However, the magnitude of the benefit is scarce and no predictive biomarkers of response have yet been established. In this review, we describe SCLC biology and molecular classification, examine the SCLC tumor microenvironment and the challenges of predictive biomarkers of response to new treatments, and, finally, assess clinical and molecular characteristics of long-term survivor patients in order to identify possible prognostic factors and treatment vulnerabilities.

Cold and heterogeneous T cell repertoire is associated with copy number aberrations and loss of immune genes in small-cell lung cancer

Small-cell lung cancer (SCLC) is speculated to harbor complex genomic intratumor heterogeneity (ITH) associated with high recurrence rate and suboptimal response to immunotherapy. Here, using multi-region whole exome/T cell receptor (TCR) sequencing as well as immunohistochemistry, we reveal a rather homogeneous mutational landscape but extremely cold and heterogeneous TCR repertoire in limited-stage SCLC tumors (LS-SCLCs). Compared to localized non-small cell lung cancers, LS-SCLCs have similar predicted neoantigen burden and genomic ITH, but significantly colder and more heterogeneous TCR repertoire associated with higher chromosomal copy number aberration (CNA) burden. Furthermore, copy number loss of IFN-γ pathway genes is frequently observed and positively correlates with CNA burden. Higher mutational burden, higher T cell infiltration and positive PD-L1 expression are associated with longer overall survival (OS), while higher CNA burden is associated with shorter OS in patients with LS-SCLC.

Immunotherapy in small cell lung cancer: one step at a time: a narrative review

Chemotherapy with or without radiotherapy has been the standard of care for many years for patients with small cell lung cancer (SCLC). Despite exceptionally high responses (up to 80%) with chemotherapy, the majority of patients relapse rapidly within weeks to months after treatment completion. Therefore, new and better treatment options are necessary. Recently, synergistic activity has been reported for the addition of immune checkpoint inhibitors (ICI) to standard platinum-based chemotherapy in the therapeutic strategy of advanced SCLC. For the first time after several decades, a significant survival improvement was achieved for this population. However, the overwhelming majority of patients do not respond to ICI, or relapse rapidly. There is need for better knowledge about the biology, histopathologic features, and molecular pathways of SCLC. This can probably help to identify the optimal predictive biomarkers, which are warranted to develop an individual therapeutic strategy including the rational use of a combination of immunotherapeutic agents. Here, we provide an overview of the rationale for and clinical results of the completed and ongoing trials using different strategies of immunotherapy in SCLC. In addition, opportunities for further improvement of therapies will be discussed, including the addition of radiotherapy, co-stimulatory antibodies, and other immune modifying agents.

Integrated Gene Expression and Methylation Analyses Identify DLL3 as a Biomarker for Prognosis of Malignant Glioma

Glioma is one of the most common neurological malignancies worldwide. Delta-like ligand 3 (DLL3), an inhibitory ligand-driven activation of the Notch pathway, has been shown to be significantly associated with overall survival in patients with glioma. Therefore, the purpose of this study was to determine whether DLL3 as a biomarker in glioma is associated with patients' clinicopathological features and prognosis. We identified differences in transcriptome and promoter methylation in the Chinese Glioma Genome Atlas (CGGA) in patients with malignant glioma with shorter (less than 1 year) and longer (greater than 3 years) survival time. Further analysis of The Cancer Genome Atlas (TCGA) revealed that four genes (DLL3, TSPAN15, RTN1, PAK7) are highly associated with patient prognosis and play an indispensable role in evolution. We chose the expression level of DLL3 in glioma patients for our study. Patients were divided into groups with low and high expression of DLL3 according to the cutoff values obtained, and Kaplan-Meier and Cox analysis were used to examine the correlation between DLL3 gene expression and patient survival. We then performed a gene set enrichment analysis (GSEA) to identify significantly enriched signaling pathways. Our results confirmed that the overall survival of patients with low DLL3 expression was significantly shorter than that of patients with high DLL3 expression. GSEA showed that the signaling pathways of the immune process and immune response, among others, were enhanced with the DLL3 low-expression phenotype. Collectively, our findings signify that DLL3 is a potent prognostic factor for glioma, which can provide a viable approach for glioma prognostic assessment and valuable insights for anti-tumor immune-targeted therapies.

Opportunities and obstacles of targeted therapy and immunotherapy in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignant tumour which accounts for approximately 13-15% of all newly diagnosed lung cancer cases. To date, platinum-based chemotherapy are still the first-line treatments for SCLC. However, chemotherapy resistance and systemic toxicity limit the long-term clinical outcome of first-line treatment in SCLC. Recent years, targeted therapy and immunotherapy have made great breakthrough in cancer therapy, and researchers aim to exploit both as a single agent or in combination with chemotherapy to improve the survival of SCLC patients, but limited effectiveness and the adverse events remain the major obstacles in the treatment of SCLC. To overcome these challenges for SCLC therapies, prevention and early diagnosis for this refractory disease is very important. At the same time, we should reveal more information about the pathogenesis of SCLC and the mechanism of drug resistance. Finally, new treatment strategies should also be taken into considerations, such as repurposing drug, optimising of targets, combination therapy strategies or prognostic biomarkers to enhance therapeutic effects and decrease the adverse events rates in SCLC patients. This article will review the molecular biology characteristics of SCLC and discuss the opportunities and obstacles of the current therapy for SCLC patients.

Immune Checkpoint Inhibitors in Lung Cancer: Role of Biomarkers and Combination Therapies

Lung cancer is the leading cause of cancer-related death worldwide, with a poor prognosis. Despite aggressive treatment, progression-free survival (PFS) and overall survival are limited. Recently, various kinds of immune checkpoint inhibitors (ICIs) have emerged for several cancers, targeting PD1, PDL1, and CTLA-4. ICIs have made a significant breakthrough in cancer and revolutionized the management of cancer including lung cancer. However, there are a lot of controversies regarding which group of patients is most suitable to be treated with ICIs in terms of monotherapy, combination, and predictive biomarkers. We reviewed various kinds of studies, such as meta-analysis, randomized control trials, multi-center cohort studies, and case-control studies from PubMed written in English from the last five years. ICIs have significant benefits in the overall survival compared with traditional chemotherapy. Patients with a higher level of PDL1 expression and high tumor mutational burden (TMB) have a higher response rate, and those with EGFR-/ALK- were better than those with EGFR+/ALK+. The patient who responded to immunotherapy completely can still maintain the efficacy after two years of treatment. Neoadjuvant immunotherapy in patients with resectable non-small cell lung cancer resulted in a 45% major pathology response (MPR) and 40% downstaging. Combined therapy (ICIs + chemotherapy) was better than chemotherapy alone, irrespective of PD-L1 expression. A combination of ICIs such as CTLA-4 and PD-1/PD-L1 improved PFS as well. Radiochemotherapy ahead of ICIs is promising as well. However, ICIs combined with EGFR/ALK-TKI (tyrosine kinase inhibitor) are not suggested for the time being. PDL1 expression, TMB, and EGFR/ALK mutations are promising predictive biomarkers. Gut microbiota, galectin-3, and intensity of CD8 cell infiltration are other potential predictive biomarkers. These are very important in the future management of lung cancers as they can prevent unnecessary toxicities and cost of treatment.