Differential Sensitivity Analysis for Resistant Malignancies (DISARM) Identifies Common Candidate Therapies across Platinum-Resistant Cancers

Circulating tumor cells: advancing personalized therapy in small cell lung cancer patients

Small cell lung cancer (SCLC) is a highly aggressive cancer with a dismal 5-year survival of < 7%, despite the addition of immunotherapy to first-line chemotherapy. Specific tumor biomarkers, such as delta-like ligand 3 (DLL3) and schlafen11 (SLFN11), may enable the selection of more efficacious, novel immunomodulating targeted treatments like bispecific T-cell engaging monoclonal antibodies (tarlatamab) and chemotherapy with PARP inhibitors. However, obtaining a tissue biopsy sample can be challenging in SCLC. Circulating tumor cells (CTCs) have the potential to provide molecular insights into a patient's cancer through a "simple" blood test. CTCs have been studied for their prognostic ability in SCLC; however, their value in guiding treatment decisions is yet to be elucidated. This review explores novel and promising targeted therapies in SCLC, summarizes current knowledge of CTCs in SCLC, and discusses how CTCs can be utilized for precision medicine.

Probiotic-derived amphiphilic exopolysaccharide self-assembling adjuvant delivery platform for enhancing immune responses

Enhancing immune response activation through the synergy of effective antigen delivery and immune enhancement using natural, biodegradable materials with immune-adjuvant capabilities is challenging. Here, we present NAPSL.p that can activate the Toll-like receptor 4 (TLR4) pathway, an amphiphilic exopolysaccharide, as a potential self-assembly adjuvant delivery platform. Its molecular structure and unique properties exhibited remarkable self-assembly, forming a homogeneous nanovaccine with ovalbumin (OVA) as the model antigen. When used as an adjuvant, NAPSL.p significantly increased OVA uptake by dendritic cells. In vivo imaging revealed prolonged pharmacokinetics of NAPSL. p-delivered OVA compared to OVA alone. Notably, NAPSL.p induced elevated levels of specific serum IgG and isotype titers, enhancing rejection of B16-OVA melanoma xenografts in vaccinated mice. Additionally, NAPSL.p formulation improved therapeutic effects, inhibiting tumor growth, and increasing animal survival rates. The nanovaccine elicited CD4+ and CD8+ T cell-based immune responses, demonstrating the potential for melanoma prevention. Furthermore, NAPSL.p-based vaccination showed stronger protective effects against influenza compared to Al (OH)3 adjuvant. Our findings suggest NAPSL.p as a promising, natural self-adjuvanting delivery platform to enhance vaccine design across applications.

Molecular classification of small cell lung cancer subtypes: Characteristics, prognostic factors, and clinical translation

ABSTRACT

Small cell lung cancer (SCLC) is a highly malignant tumor with a very poor prognosis; therefore, more effective treatments are urgently needed for patients afflicted with the disease. In recent years, emerging molecular classifications based on key transcription factors of SCLC have provided more information on the tumor pathophysiology, metastasis, immune microenvironment, and acquired therapeutic resistance and reflected the intertumoral heterogeneity of the various SCLC phenotypes. Additionally, advances in genomics and single-cell sequencing analysis have further revealed the high intratumoral heterogeneity and plasticity of the disease. Herein, we review and summarize these recent lines of evidence and discuss the possible pathogenesis of SCLC.

The Era of Immunotherapy in Small-Cell Lung Cancer: More Shadows Than Light?

Small-cell lung cancer is an extremely chemo-sensitive disease; the addition of immunotherapy to chemotherapy has demonstrated a slight clinical benefit in pivotal trials, even with a statistically significant difference in terms of survival outcomes when compared to chemotherapy alone. In this scenario, the role of radiotherapy as a consolidation treatment in thoracic disease or as a prophylactic therapy in the brain should be clarified. In addition, due to the frailty and the poor prognostic characteristics of these patients, the need for predictive biomarkers that could support the use of immunotherapy is crucial. PD-L1 and TMB are not actually considered definitive biomarkers due to the heterogeneity of results in the literature. A new molecular classification of small-cell lung cancer based on the expression of key transcription factors seems to clarify the disease behavior, but the knowledge of this molecular subtype is still insufficient and the application in clinical practice far from reality; this classification could lead to a better understanding of SCLC disease and could provide the right direction for more personalized treatment. The aim of this review is to investigate the current knowledge in this field, evaluating whether there are predictive biomarkers and clinical patient characteristics that could help us to identify those patients who are more likely to respond to immunotherapy.

Potent molecular-targeted therapies for gastro-entero-pancreatic neuroendocrine carcinoma

Neuroendocrine neoplasms (NENs), which are characterized by neuroendocrine differentiation, can arise in various organs. NENs have been divided into well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs) based on morphological differentiation, each of which has a distinct etiology, molecular profile, and clinicopathological features. While the majority of NECs originate in the pulmonary organs, extrapulmonary NECs occur most predominantly in the gastro-entero-pancreatic (GEP) system. Although platinum-based chemotherapy is the main therapeutic option for recurrent or metastatic GEP-NEC patients, the clinical benefits are limited and associated with a poor prognosis, indicating the clinically urgent need for effective therapeutic agents. The clinical development of molecular-targeted therapies has been hampered due to the rarity of GEP-NECs and the paucity of knowledge on their biology. In this review, we summarize the biology, current treatments, and molecular profiles of GEP-NECs based on the findings of pivotal comprehensive molecular analyses; we also highlight potent therapeutic targets for future precision medicine based on the most recent results of clinical trials.

Novel therapeutic strategies for recurrent SCLC

Therapeutic options for patients with relapsed SCLC are limited, and the prognosis in this setting remains poor. While clinical outcomes for frontline treatment have modestly improved with the introduction of immunotherapy, treatment in the second-line setting persists almost unchanged. In this review, current treatment options and recent advances in molecular biology are described. Emerging therapeutic options in this setting and potential strategies to improve clinical outcomes of these patients are also addressed.

Molecular Classification of Extrapulmonary Neuroendocrine Carcinomas With Emphasis on POU2F3-positive Tuft Cell Carcinoma

Extrapulmonary neuroendocrine carcinomas (EP-NECs) are associated with a poor clinical outcome, and limited information is available on the biology and treatment of EP-NECs. We studied EP-NECs by applying the recent novel findings from studies of pulmonary neuroendocrine carcinomas, including POU2F3, the master regulator of tuft cell variant of small cell lung carcinomas. A cohort of 190 patients with surgically resected EP-NECs or poorly differentiated carcinomas (PDCs) were established. Immunohistochemistry (IHC) for POU2F3 along with ASCL1, NEUROD1, YAP1, and conventional neuroendocrine markers was performed on tissue microarrays. Selected cases with or without POU2F3 expression were subjected to targeted gene expression profiling using nCounter PanCancer Pathway panel. POU2F3-positive tuft cell carcinomas were present in 12.6% of EP-NEC/PDCs, with variable proportions according to organ systems. POU2F3 expression was negatively correlated with the expression levels of ASCL1, NEUROD1, and conventional neuroendocrine markers ( P <0.001), enabling IHC-based molecular classification into ASCL1-dominant, NEUROD1-dominant, POU2F3-dominant, YAP1-dominant, and not otherwise specified subtypes. Compared wih POU2F3-negative cases, POU2F3-positive tuft cell carcinomas showed markedly higher expression levels of PLCG2 and BCL2 , which was also validated in the entire cohort by IHC. In addition to POU2F3, YAP1-positive tumors were a distinct subtype among EP-NEC/PDCs, characterized by unique T-cell inflamed microenvironment. We found rare extrapulmonary POU2F3-positive tumors arising from previously unappreciated cells of origin. Our data show novel molecular pathologic features of EP-NEC/PDCs including potential therapeutic vulnerabilities, thereby emphasizing the need for focusing on unique features of EP-NEC/PDCs.

Poly(ADP-Ribose) Polymerase Inhibition in Small Cell Lung Cancer: A Review

ABSTRACT

Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine malignancy with high and rapid relapse rates and poor outcomes. Treatment for SCLC has historically been limited by the lack of targetable driver genomic lesions, however recent developments in the underpinnings of genomic instability in SCLC and understanding of its transcriptional subtypes have led to increased interest in the use of poly(ADP-ribose) polymerase (PARP) inhibitors as a rationale therapy. Poly(ADP-ribose) polymerase inhibitors, historically designed to target BRCA1/2-mutated malignancies, capitalize on synthetic lethality in homologous recombination-deficient tumors. In this review, we outline the mechanistic rationale for the use of PARP inhibitors in treating SCLC and detail key clinical trials investigating their use in combination with chemotherapy and immunotherapy. We describe developments in the understanding of biomarkers for sensitivity to therapy and highlight further investigational directions for the use of PARP inhibitors in treating SCLC.

Advances in novel molecular typing and precise treatment strategies for small cell lung cancer

Small cell lung cancer (SCLC) is a high-grade neuroendocrine (NE) cancer characterized by high circulating tumor-cell burden and early extensive metastasis. Considering the complexity of SCLC genes and the immune microenvironment, their unique molecular heterogeneity profiles have been continuously explored. The understanding of SCLC subtypes has recently changed from traditional "classical" and "variant" types to "NE" and "non-NE" phenotypes and to the subtypes defined by major transcriptional regulators, which indicates the gradual revelation of high intratumoral heterogeneity and plasticity characteristics of SCLCs. Advances in genomics as well as the development of single-cell sequencing analysis and new preclinical models have helped investigators gain many new insights into SCLCs and the development of targeted therapy and immunotherapy strategies. This article provides an overview of changes in molecular typing, tumor heterogeneity, and plasticity and that of advances in the precise treatment of different subtypes of SCLC.

Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data and non-negative matrix factorization, we identify four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed gene signature (SCLC-A, N, P, and I, respectively). SCLC-I experiences the greatest benefit from the addition of immunotherapy to chemotherapy, while the other subtypes each have distinct vulnerabilities, including to inhibitors of PARP, Aurora kinases, or BCL-2. Cisplatin treatment of SCLC-A patient-derived xenografts induces intratumoral shifts toward SCLC-I, supporting subtype switching as a mechanism of acquired platinum resistance. We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients.

Unbiased Proteomic Profiling Uncovers a Targetable GNAS/PKA/PP2A Axis in Small Cell Lung Cancer Stem Cells

Using unbiased kinase profiling, we identified protein kinase A (PKA) as an active kinase in small cell lung cancer (SCLC). Inhibition of PKA activity genetically, or pharmacologically by activation of the PP2A phosphatase, suppresses SCLC expansion in culture and in vivo. Conversely, GNAS (G-protein α subunit), a PKA activator that is genetically activated in a small subset of human SCLC, promotes SCLC development. Phosphoproteomic analyses identified many PKA substrates and mechanisms of action. In particular, PKA activity is required for the propagation of SCLC stem cells in transplantation studies. Broad proteomic analysis of recalcitrant cancers has the potential to uncover targetable signaling networks, such as the GNAS/PKA/PP2A axis in SCLC.

Common and distinct features of potentially predictive biomarkers in small cell lung carcinoma and large cell neuroendocrine carcinoma of the lung by systematic and integrated analysis

BACKGROUND

Large-cell neuroendocrine carcinoma of the lung (LCNEC) and small-cell lung carcinoma (SCLC) are neuroendocrine neoplasms. However, the underlying mechanisms of common and distinct genetic characteristics between LCNEC and SCLC are currently unclear. Herein, protein expression profiles and possible interactions with miRNAs were provided by integrated bioinformatics analysis, in order to explore core genes associated with tumorigenesis and prognosis in SCLC and LCNEC.

METHODS

GSE1037 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in LCNEC and SCLC, as compared with normal lung tissues, were selected using the GEO2R online analyzer and Venn diagram software. Gene ontology (GO) analysis was performed using Database for Annotation, Visualization and Integrated Discovery. The biological pathway analysis was performed using the FunRich database. Subsequently, a protein-protein interaction (PPI) network of DEGs was generated using Search Tool for the Retrieval of Interacting Genes and displayed via Cytoscape software. The PPI network was analyzed by the Molecular Complex Detection app from Cytoscape, and 16 upregulated hub genes were selected. The Oncomine database was used to detect expression patterns of hub genes for validation. Furthermore, the biological pathways of these 16 hub genes were re-analyzed, and potential interactions between these genes and miRNAs were explored via FunRich.

RESULTS

A total of 384 DEGs were identified. A Venn diagram determined 88 common DEGs. The PPI network was constructed with 48 nodes and 221 protein pairs. Among them, 16 hub genes were extracted, 14 of which were upregulated in SCLC samples, as compared with normal lung specimens, and 10 were correlated with the cell cycle pathway. Furthermore, 57 target miRNAs for 8 hub genes were identified, among which 31 miRNAs were correlated with the progression of carcinoma, drug-resistance, radio-sensitivity, or autophagy in lung cancer.

CONCLUSION

This study provided effective biomarkers and novel therapeutic targets for diagnosis and prognosis of SCLC and LCNEC.

ERK Regulates HIF1α-Mediated Platinum Resistance by Directly Targeting PHD2 in Ovarian Cancer

PURPOSE

Up to 80% of patients with ovarian cancer develop platinum resistance over time to platinum-based chemotherapy. Increased HIF1α level is an important mechanism governing platinum resistance in platinum-resistant ovarian cancer (PROC). However, the mechanism regulating HIF1α stability in PROC remains largely unknown. Here, we elucidate the mechanism of HIF1α stability regulation in PROC and explore therapeutic approaches to overcome cisplatin resistance in ovarian cancer.

EXPERIMENTAL DESIGN

We first used a quantitative high-throughput combinational screen (qHTCS) to identify novel drugs that could resensitize PROC cells to cisplatin. Next, we evaluated the combination efficacy of inhibitors of HIF1α (YC-1), ERK (selumetinib), and TGFβ1 (SB431542) with platinum drugs by in vitro and in vivo experiments. Moreover, a novel TGFβ1/ERK/PHD2-mediated pathway regulating HIF1α stability in PROC was discovered.

RESULTS

YC-1 and selumetinib resensitized PROC cells to cisplatin. Next, the prolyl hydroxylase domain-containing protein 2 (PHD2) was shown to be a direct substrate of ERK. Phosphorylation of PHD2 by ERK prevents its binding to HIF1α, thus inhibiting HIF1α hydroxylation and degradation-increasing HIF1α stability. Significantly, ERK/PHD2 signaling in PROC cells is dependent on TGFβ1, promoting platinum resistance by stabilizing HIF1α. Inhibition of TGFβ1 by SB431542, ERK by selumetinib, or HIF1α by YC-1 efficiently overcame platinum resistance both in vitro and in vivo. The results from clinical samples confirm activation of the ERK/PHD2/HIF1α axis in patients with PROC, correlating highly with poor prognoses for patients.

CONCLUSIONS

HIF1α stabilization is regulated by TGFβ1/ERK/PHD2 axis in PROC. Hence, inhibiting TGFβ1, ERK, or HIF1α is potential strategy for treating patients with PROC.

Integrated Approaches for the Use of Large Datasets to Identify Rational Therapies for the Treatment of Lung Cancers

The benefit and burden of contemporary techniques for the molecular characterization of samples is the vast amount of data generated. In the era of “big data”, it has become imperative that we develop multi-disciplinary teams combining scientists, clinicians, and data analysts. In this review, we discuss a number of approaches developed by our University of Texas MD Anderson Lung Cancer Multidisciplinary Program to process and utilize such large datasets with the goal of identifying rational therapeutic options for biomarker-driven patient subsets. Large integrated datasets such as the The Cancer Genome Atlas (TCGA) for patient samples and the Cancer Cell Line Encyclopedia (CCLE) for tumor derived cell lines include genomic, transcriptomic, methylation, miRNA, and proteomic profiling alongside clinical data. To best use these datasets to address urgent questions such as whether we can define molecular subtypes of disease with specific therapeutic vulnerabilities, to quantify states such as epithelial-to-mesenchymal transition that are associated with resistance to treatment, or to identify potential therapeutic agents in models of cancer that are resistant to standard treatments required the development of tools for systematic, unbiased high-throughput analysis. Together, such tools, used in a multi-disciplinary environment, can be leveraged to identify novel treatments for molecularly defined subsets of cancer patients, which can be easily and rapidly translated from benchtop to bedside.