Therapeutic Target In Small Cell Lung Cancer Research Articles

Small Cell Lung Cancer Neuronal Features and Their Implications for Tumor Progression, Metastasis, and Therapy.

Small cell lung cancer (SCLC) is an epithelial neuroendocrine form of lung cancer for which survival rates remain dismal and new therapeutic approaches are greatly needed. Key biological features of SCLC tumors include fast growth and widespread metastasis, as well as rapid resistance to treatment. Similar to pulmonary neuroendocrine cells, SCLC cells have traits of both hormone-producing cells and neurons. In this study, we specifically discuss the neuronal features of SCLC. We consider how neuronal G protein-coupled receptors and other neuronal molecules on the surface of SCLC cells can contribute to the growth of SCLC tumors and serve as therapeutic targets in SCLC. We also review recent evidence for the role of neuronal programs expressed by SCLC cells in the fast proliferation, migration, and metastasis of these cells. We further highlight how these neuronal programs may be particularly relevant for the development of brain metastases and how they can assist SCLC cells to functionally interact with neurons and astrocytes. A greater understanding of the molecular and cellular neuronal features of SCLC is likely to uncover new vulnerabilities in SCLC cells, which may help develop novel therapeutic approaches. More generally, the epithelial-to-neuronal transition observed during tumor progression in SCLC and other cancer types can contribute significantly to tumor development and response to therapy.

FAK-LINC01089 negative regulatory loop controls chemoresistance and progression of small cell lung cancer.

The focal adhesion kinase (FAK) tyrosine kinase is activated and upregulated in multiple cancer types including small cell lung cancer (SCLC). However, FAK inhibitors have shown limited efficacy in clinical trials for cancer treatment. With the aim of identifying potential therapeutic strategies to inhibit FAK for cancer treatment, we investigated long non-coding RNAs (lncRNAs) that potentially regulate FAK in SCLC. In this study, we identified a long non-coding RNA LINC01089 that binds and inhibits FAK phosphorylation (activation). Expression analysis revealed that LINC01089 was downregulated in SCLC tissues and negatively correlated with chemoresistance and survival in SCLC patients. Functionally, LINC01089 inhibited chemoresistance and progression of SCLC in vitro and in vivo. Mechanistically, LINC01089 inhibits FAK activation by blocking binding with Src and talin kinases, while FAK negatively regulates LINC01089 transcription by activating the ERK signaling pathway to recruit the REST transcription factor. Furthermore, LINC01089-FAK axis mediates the expression of drug resist-related genes by modulating YBX1 phosphorylation, leading to drug resistance in SCLC. Intriguingly, the FAK-LINC01089 interaction depends on the co-occurrence of the novel FAK variant and the non-conserved region of LINC01089 in primates. In Conclusion, our results indicated that LINC01089 may serve as a novel high-efficiency FAK inhibitor and the FAK-LINC01089 axis represents a valuable prognostic biomarker and potential therapeutic target in SCLC.

Exploring effective biomarkers and potential immune related gene in small cell lung cancer

Small cell lung cancer (SCLC) is well known as a highly malignant neuroendocrine tumor. Immunotherapy combined with chemotherapy has become a standard treatment for extensive SCLC. However, since most patients quickly develop resistance and relapse, finding new therapeutic targets for SCLC is important. We obtained four microarray datasets from the Gene Expression Omnibus database and screened differentially expressed genes by two methods: batch correction and “RobustRankAggregation”. After the establishment of a protein–protein interaction network through Cytoscape, seven hub genes (AURKB, BIRC5, TOP2A, TYMS, PCNA, UBE2C, and AURKA) with high expression in SCLC samples were obtained by eight CytoHubba algorithms. The Least Absolute Shrinkage and Selection Operator regression and the Wilcoxon test were used to analyze the differences in the immune cells’ infiltration between normal and SCLC samples. The contents of seven kinds of immune cells were considered to differ significantly between SCLC samples and normal samples. A negative association was found between BIRC5 and monocytes in the correlation analysis between immune cells and the seven hub genes. The subsequent in vitro validation of experimental results showed that downregulating the expression of BIRC5 by siRNA can promote apoptotic activity of SCLC cells and inhibit their vitality, migration, and invasion. The use of BIRC5 inhibitor inhibited the vitality of SCLC cells and increased their apoptotic activity. BIRC5 may be a novel therapeutic target option for SCLC.

ELAVL4 promotes the tumorigenesis of small cell lung cancer by stabilizing LncRNA LYPLAL1-DT and enhancing profilin 2 activation.

Small cell lung cancer (SCLC) is one of the most malignant tumors that has an extremely poor prognosis. RNA-binding protein (RBP) and long noncoding RNA (lncRNA) have been shown to be key regulators during tumorigenesis as well as lung tumor progression. However, the role of RBP ELAVL4 and lncRNA LYPLAL1-DT in SCLC remains unclear. In this study, we verified that lncRNA LYPLAL1-DT acts as an SCLC oncogenic lncRNA and was confirmed in vitro and in vivo. Mechanistically, LYPLAL1-DT negatively regulates the expression of miR-204-5p, leading to the upregulation of PFN2, thus, promoting SCLC cell proliferation, migration, and invasion. ELAVL4 has been shown to enhance the stability of LYPLAL1-DT and PFN2 mRNA. Our study reveals a regulatory pathway, where ELAVL4 stabilizes PFN2 and LYPLAL1-DT with the latter further increasing PFN2 expression by blocking the action of miR-204-5p. Upregulated PFN2 ultimately promotes tumorigenesis and invasion in SCLC. These findings provide novel prognostic indicators as well as promising new therapeutic targets for SCLC.

Plasticity of circulating tumor cells in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor with low five-year survival rates. Recently described molecular phenotypes of SCLC exhibit differential vulnerabilities heralding potential for stratified treatment. Whilst tumor biopsy in SCLC is challenging, circulating tumor cells in the liquid biopsy are prevalent and can be repeatedly sampled accommodating the dynamic plasticity of SCLC phenotypes. The aim of this study was to characterize the heterogeneity of rare circulating cells with confirmed tumor origin and to explore a liquid biopsy approach for future clinical trials of targeted therapies. This study applied the 3rd generation of a previously validated direct imaging platform to 14 chemo-naive SCLC patients and 10 non-cancerous normal donor (ND) samples. Phenotypic heterogeneity of circulating rare cells in SCLC was observed and a patient-level classification model was established to stratify SCLC patients from non-cancerous donors. Eight rare cell groups, with combinations of epithelial, endothelial, and mesenchymal biomarker expression patterns, were phenotypically characterized. The single-cell genomic analysis confirmed the cancer cell plasticity in every rare cell group harboring clonal genomic alterations. This study shows rare cell heterogeneity and confirms cellular plasticity in SCLC providing a valuable resource for better opportunities to discover novel therapeutic targets in SCLC.

DNA-PKcs as an upstream mediator of OCT4-induced MYC activation in small cell lung cancer

Small cell lung cancer (SCLC) is a neuroendocrine tumor noted for the rapid development of both metastases and resistance to chemotherapy. High mutation burden, ubiquitous loss of TP53 and RB1, and a mutually exclusive amplification of MYC gene family members contribute to genomic instability and make the development of new targeted agents a challenge. Previously, we reported a novel OCT4-induced MYC transcriptional activation pathway involving c-MYC, pOCT4S111, and MAPKAPK2 in progressive neuroblastoma, also a neuroendocrine tumor. Using tumor microarray analysis of clinical samples and preclinical models, we now report a correlation in expression between these proteins in SCLC. In correlating c-MYC protein expression with genomic amplification, we determined that some SCLC cell lines exhibited high c-MYC without genomic amplification, implying amplification-independent MYC activation. We then confirmed direct interaction between OCT4 and DNA-PKcs and identified specific OCT4 and DNA-PKcs binding sites. Knock-down of both POU5F1 (encoding OCT4) and PRKDC (encoding DNA-PKcs) resulted in decreased c-MYC expression. Further, we confirmed binding of OCT4 to the promoter/enhancer region of MYC. Together, these data establish the presence of a DNA-PKcs/OCT4/c-MYC pathway in SCLCs. We then disruptively targeted this pathway and demonstrated anticancer activity in SCLC cell lines and xenografts using both DNA-PKcs inhibitors and a protein-protein interaction inhibitor of DNA-PKcs and OCT4. In conclusion, we demonstrate here that DNA-PKcs can mediate high c-MYC expression in SCLCs, and that this pathway may represent a new therapeutic target for SCLCs with high c-MYC expression.

Identification and Validation of Cyclin A2 and Cyclin E2 as Potential Biomarkers in Small Cell Lung Cancer

Introduction: Small cell lung cancer (SCLC) is a special type of lung cancer sensitive to radiotherapy and chemotherapy but is prone to drug resistance and recurrence and has a very poor prognosis. This study aimed to explore the potential biomarkers and therapeutic targets for SCLC. Methods: After batch normalization of GSE40275, GSE1037, and GSE44447 datasets, R was used to screen SCLC’s differentially expressed genes (DEGs) and hub genes. We used immunohistochemistry (IHC) to assess the tissue’s expression level of the hub gene. The clinical value of the hub gene was further evaluated based on the collected clinical-pathological data. Results: In this study, a total of 230 DEGs (133 upregulated and 97 downregulated) were screened by the R package. The IHC showed that the expression of CCNA2 and CCNE2 in SCLC tissues was significantly higher than that in normal tissues (p < 0.01). Overexpression of CCNA2 was closely associated with the extensive period of NCCN (p = 0.004), tumor position (p = 0.046), and clinical stage (p = 0.002). The high expression levels of CCNE2 were related to high survival in chemotherapy patients (p = 0.019). Conclusion: CCNA2 and CCNE2 may serve as potential biomarkers of diagnosis and treatment for SCLC.

Implication thérapeutique potentielle de la kinase de l’adhérence focale dans le cancer pulmonaire à petites cellules

The molecular steps leading to small cell lung cancer (SCLC) development and progression are still poorly understood, resulting in the absence of targeted therapy and an extremely poor prognosis. Activation of Focal Adhesion Kinase (FAK) plays a key role in the invasive behavior of this cancer in vitro. Our hypothesis is that FAK could be a therapeutic target in SCLC. Our work aims to describe a mouse model to study the role of FAK and the antitumoral potential of its inhibition in SCLC in vivo.

The NFIB/CARM1 partnership is a driver in preclinical models of small cell lung cancer

The coactivator associated arginine methyltransferase (CARM1) promotes transcription, as its name implies. It does so by modifying histones and chromatin bound proteins. We identified nuclear factor I B (NFIB) as a CARM1 substrate and show that this transcription factor utilizes CARM1 as a coactivator. Biochemical studies reveal that tripartite motif 29 (TRIM29) is an effector molecule for methylated NFIB. Importantly, NFIB harbors both oncogenic and metastatic activities, and is often overexpressed in small cell lung cancer (SCLC). Here, we explore the possibility that CARM1 methylation of NFIB is important for its transforming activity. Using a SCLC mouse model, we show that both CARM1 and the CARM1 methylation site on NFIB are critical for the rapid onset of SCLC. Furthermore, CARM1 and methylated NFIB are responsible for maintaining similar open chromatin states in tumors. Together, these findings suggest that CARM1 might be a therapeutic target for SCLC.

MicroRNA signature of small-cell lung cancer after treatment failure: impact on oncogenic targets by miR-30a-3p control.

Small-cell lung cancer (SCLC) is associated with a high mortality rate and limited treatment efficacy. We created a microRNA (miRNA) expression signature by RNA sequencing using specimens from patients with SCLC who had failed treatment. Forty-nine miRNAs were downregulated in SCLC tissues and were candidate tumor-suppressive miRNAs. In this signature, both guide and passenger strands were downregulated for five miRNAs (miR-30a, miR-34b, miR-34c, miR-223, and miR-4529). Recent studies have revealed that passenger strands of miRNAs are involved in the molecular pathogenesis of human cancer. Although miR-30a-5p (the guide strand) has been shown to be a tumor-suppressive miRNA in various types of cancers, miR-30a-3p (the passenger strand) function is not well characterized in SCLC cells. We investigated the functional significance of miR-30a-3p and oncogenic genes regulated by miR-30a-3p in SCLC cells. Ectopic expression assays showed that miR-30a-3p expression inhibited cell proliferation and induced cell cycle arrest and apoptosis in two SCLC cell lines. Furthermore, in silico database searches and gene expression assays identified 25 genes as putative targets of miR-30a-3p in SCLC cells. Luciferase reporter assays revealed that downstream neighbor of SON (DONSON) was directly regulated by miR-30a-3p in SCLC cells. Knockdown of DONSON induced cell cycle arrest in SCLC cells and DONSON overexpression were detected in SCLC clinical samples. Analyzing the regulatory networks of tumor-suppressive miRNAs may lead to the identification of therapeutic targets in SCLC.

Multi-Omics Integration-Based Prioritisation of Competing Endogenous RNA Regulation Networks in Small Cell Lung Cancer: Molecular Characteristics and Drug Candidates.

BackgroundThe competing endogenous RNA (ceRNA) network-mediated regulatory mechanisms in small cell lung cancer (SCLC) remain largely unknown. This study aimed to integrate multi-omics profiles, including the transcriptome, regulome, genome and pharmacogenome profiles, to elucidate prioritised ceRNA characteristics, pathways and drug candidates in SCLC.MethodWe determined the plasma messenger RNA (mRNA), microRNA (miRNA), long noncoding RNA (lncRNA) and circular RNA (circRNA) expression levels using whole-transcriptome sequencing technology in our SCLC plasma cohort. Significantly expressed plasma mRNAs were then overlapped with the Gene Expression Omnibus (GEO) tissue mRNA data (GSE 40275, SCLC tissue cohort). Next, we applied a multistep multi-omics (transcriptome, regulome, genome and pharmacogenome) integration analysis to first construct the network and then to identify the lncRNA/circRNA-miRNA-mRNA ceRNA characteristics, genomic alterations, pathways and drug candidates in SCLC.ResultsThe multi-omics integration-based prioritisation of SCLC ceRNA regulatory networks consisted of downregulated mRNAs (CSF3R/GAA), lncRNAs (AC005005.4-201/DLX6-AS1-201/NEAT1-203) and circRNAs (hsa_HLA-B_1/hsa_VEGFC_8) as well as upregulated miRNAs (hsa-miR-4525/hsa-miR-6747-3p). lncRNAs (lncRNA-AC005005.4-201 and NEAT1-203) and circRNAs (circRNA-hsa_HLA-B_1 and hsa_VEGFC_8) may regulate the inhibited effects of hsa-miR-6747-3p for CSF3R expression in SCLC, while lncRNA-DLX6-AS1-201 or circRNA-hsa_HLA-B_1 may neutralise the negative regulation of hsa-miR-4525 for GAA in SCLC. CSF3R and GAA were present in the genomic alteration, and further identified as targets of FavId and Trastuzumab deruxtecan, respectively. In the SCLC-associated pathway analysis, CSF3R was involved in the autophagy pathways, while GAA was involved in the glucose metabolism pathways.ConclusionsWe identified potential lncRNA/cirRNA-miRNA-mRNA ceRNA regulatory mechanisms, pathways and promising drug candidates in SCLC, providing novel potential diagnostics and therapeutic targets in SCLC.

Bioinformatics Analysis of Key Genes and miRNAs Associated with Small-cell Lung Cancer

Small-cell lung cancer (SCLC) is a type of lung cancer, accounting for approximately 15% of lung cancers. SCLC is significantly associated with early recurrence, metastasis, and poor prognosis, with a 2-year survival rate after therapy, which is &lt;5%. The molecular mechanisms underlying the development of SCLC are not clear. In this study, we identified SCLC-specific biomarkers by evaluating the differential expression of mRNA and microRNA (miRNA) profiles in SCLC tissue compared with normal lung tissue. A non-coding RNA sequence dataset (GSE19945) and transcriptome sequencing dataset (GSE6044) were downloaded from the GEO database. We identified 445 DEGs (differentially expressed genes) and 128 DE-miRNAs (differentially expressed miRNAs) using the GEO2R tool of the GEO and R limma software package. Furthermore, using the KEGG database, we identified 15 enrichment pathways, mostly associated with DNA replication, cell cycle, and oocyte meiosis mismatch repair, and the GO function was considerably enriched for 26 items. To investigate the molecular processes of key signaling pathways and cellular activity in SCLC, we used Cytoscape software to construct protein-protein interaction (PPI) networks. Using miRNAWalk, we identified 598 target genes of the 1380 miRNAs and constructed miRNA target networks. In addition, we identified eighteen overlapping genes that are regulated by 28 different miRNAs. The identified hub genes are important because they may be used as biomarkers for prognosis, diagnosis, and therapeutic target for SCLC.

A Fully-Human Antibody Specifically Targeting a Membrane-Bound Fragment of CADM1 Potentiates the T Cell-Mediated Death of Human Small-Cell Lung Cancer Cells.

Small-cell lung cancer (SCLC) is the most aggressive form of lung cancer and the leading cause of global cancer-related mortality. Despite the earlier identification of membrane-proximal cleavage of cell adhesion molecule 1 (CADM1) in cancers, the role of the membrane-bound fragment of CAMD1 (MF-CADM1) is yet to be clearly identified. In this study, we first isolated MF-CADM1-specific fully human single-chain variable fragments (scFvs) from the human synthetic scFv antibody library using the phage display technology. Following the selected scFv conversion to human immunoglobulin G1 (IgG1) scFv-Fc antibodies (K103.1–4), multiple characterization studies, including antibody cross-species reactivity, purity, production yield, and binding affinity, were verified. Finally, via intensive in vitro efficacy and toxicity evaluation studies, we identified K103.3 as a lead antibody that potently promotes the death of human SCLC cell lines, including NCI-H69, NCI-H146, and NCI-H187, by activated Jurkat T cells without severe endothelial toxicity. Taken together, these findings suggest that antibody-based targeting of MF-CADM1 may be an effective strategy to potentiate T cell-mediated SCLC death, and MF-CADM1 may be a novel potential therapeutic target in SCLC for antibody therapy.

Surfaceome profiling to reveal unique therapeutic vulnerabilities in transcriptional subtypes of small cell lung cancer (SCLC).

8515 Background: Effective treatment options for SCLC remain limited and new treatment approaches are needed to improve outcome. We sought to validate the initial observation in cell lines and limited tissue samples of SCLC of a differential expression of cancer/testis (CT) antigens and TACSD2 gene that encodes surface protein, Trop2 across various subtypes of SCLC. We also tested whether overall surfaceome profile as previously described in other tumor types will show hierarchical priority of expression between transcriptionally defined SCLC subtypes. Methods: We conducted a comprehensive surfaceome profiling of SCLC samples using data generated by RNA sequencing (whole transcriptome) at Caris Life Sciences (Phoenix, AZ). SCLC tumors were stratified into 5 subgroups (SCLC-A/N/Y/P and -mixed) based on the relative expression of the four transcription factors. Expression values were converted to z-scores (the expression value for each gene is normalized to the average expression of that specific gene such that the z-score reflects the number of standard deviations above or below the average). The highest positive z-score among the 4 transcription factors determined subgroup. If all transcription factor z-scores for a given sample were negative, the sample was assigned to ‘Mixed’ subgroup. Significance was tested by Chi-square, Fisher’s exact test, or Mann-Whitney U test. Results: We employed data generated from 674 SCLC samples; median age of 66 years and male (48.7%). The SCLC subtype distribution was 241 (35.8%), 120 (17.8%), 40 (5.9%), 143 (21.2%), 130 (19.3%) for types A, N, P, Y and mixed respectively. Supervised analysis for TACSTD2 expression showed highest levels in YAP1 subtype and was overall significantly increased in SCLC-Y (̃3-fold) and SCLC-P (̃2-fold) subtypes compared to A, N and mixed subtypes. Similarly, SCLC-Y subtype showed the highest median expression as well as the strongest correlation with most TACSTD2-interacting and regulatory genes. A top 10 list of candidate surface protein gene out of 3699 surfaceome genes was defined for each subtype based on the strength of correlation. The top candidate surface protein gene and CT antigen gene respectively by subtype were: SCN3A (r = 0.7033, p = 1.08E-101) and NOL4, (r = 0.574, p = 2.46E-60) for SCLC-A; SSTR2, (r = 0.742, p = 8.18E-119) and TMEFF1, (r = 0.3601, p = 4.53E-22) for SCLC-N; TMPRSS13 (r = 0.5699, p = 2.64E-59) and LY6K (r = 0.4778, p = 9.80E-40) for SCLC-P; and CYBRD1 (r = 0.8559, p = 1.18E-194) and CTAGE5 (r = 0.5521, p = 4.95E-55) for SCLC-Y. Conclusions: SCLC-Y subtype showed the highest expression of TACSTD2 and its interacting and regulatory genes. This subtype could serve as an enrichment factor for antibody-drug-construct targeting TROP2. Several candidate CT antigens and surfaceome genes showing strong correlation with lineage-defining transcription factors offer additional therapeutic targets in SCLC.

NRBF2 regulates the chemoresistance of small cell lung cancer by interacting with the P62 protein in the autophagy process

SummaryReversing chemotherapy resistance in small cell lung cancer (SCLC) is crucial to improve patient prognosis. The present study aims to investigate the underlying mechanisms in SCLC chemoresistance. We see that nuclear receptor binding factor 2 (NRBF2) is a poor prognostic factor in SCLC. The effects of NRBF2 on chemoresistance were determined in SCLC. The underlying molecular mechanisms of NRBF2 in the autophagy process in SCLC were examined. NRBF2 positively regulated autophagy, leading to drug resistance in SCLC. The MIT domain of NRBF2 directly interacted with the PB1 domain of P62. This interaction increased autophagic P62 body formation, revealing the regulatory role of NRBF2 in autophagy. Notably, NRBF2 was directly modulated by the transcription factor XRCC6. The MIT domain of NRBF2 interacts with the PB1 domain of P62 to regulate the autophagy process, resulting in SCLC chemoresistance. NRBF2 is likely a useful chemotherapy response marker and therapeutic target in SCLC.

Predicting ROR1/BCL2 combination targeted therapy of small cell carcinoma of the lung

Small cell lung cancer (SCLC) remains a deadly form of cancer, with a 5-year survival rate of less than 10 percent, necessitating novel therapies. Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is an oncofetal protein that is emerging as a therapeutic target and is co-expressed with BCL2 in multiple tumor types due to microRNA coregulation. We hypothesize that ROR1-targeted therapy is effective in small cell lung cancer and synergizes with therapeutic BCL2 inhibition. Tissue microarrays (TMAs) and formalin-fixed paraffin-embedded (FFPE) SCLC patient samples were utilized to determine the prevalence of ROR1 and BCL2 expression in SCLC. Eight SCLC-derived cell lines were used to determine the antitumor activity of a small molecule ROR1 inhibitor (KAN0441571C) alone and in combination with the BCL2 inhibitor venetoclax. The Chou-Talalay method was utilized to determine synergy with the drug combination. ROR1 and BCL2 protein expression was identified in 93% (52/56) and 86% (48/56) of SCLC patient samples, respectively. Similarly, ROR1 and BCL2 were shown by qRT-PCR to have elevated expression in 79% (22/28) and 100% (28/28) of SCLC patient samples, respectively. KAN0441571C displayed efficacy in 8 SCLC cell lines, with an IC50 of 500 nM or less. Synergy as defined by a combination index of <1 via the Chou-Talalay method between KAN0441571C and venetoclax was demonstrated in 8 SCLC cell lines. We have shown that ROR1 inhibition is synergistic with BCL2 inhibition in SCLC models and shows promise as a novel therapeutic target in SCLC.

Combination of quantitative features from H&amp;E biopsies and CT scans predicts response to chemotherapy and overall survival in small cell lung cancer (SCLC).

8572 Background: Small Cell Lung Cancer (SCLC) is an aggressive malignancy with a rapid growth, and Chemotherapy remains mainstay of treatment. Identifying therapeutic targets in SCLC presents a challenge, partially due to a lack of accurate and consistently predictive biomarkers. In this study we sought to evaluate the utility of a combination of computer-extracted radiographic and pathology features from pretreatment baseline CT and H&amp;E biopsy images to predict sensitivity to platinum-based chemotherapy and overall survival (OS) in SCLC. Methods: Seventy-eight patients with extensive and limited-stage SCLC who received platinum-doublet chemotherapy were selected. Objective response to chemotherapy (RECIST criteria) and overall survival (OS) as clinical endpoints were available for 51 and 78 patients respectively. The patients were divided randomly into two sets (Training (Sd), Validation (Sv)) with a constraint (equal number of responders and nonresponders in Sd)—Sd comprised twenty-one patients with SCLC. Sv included thirty patients. CT scans and digitized Hematoxylin Eosin-stained (H&amp;E) biopsy images were acquired for each patient. A set of CT derived (46%) and tissue derived (53%) image features were captured. These included shape and textural patterns of the tumoral and peritumoral regions from CT scans and of tumor regions on H&amp;E images. A random forest feature selection and linear regression model were used to identify the most predictive CT and H&amp;E derived image features associated with chemotherapy response from Sd. A Cox proportional hazard regression model was used with these features to compute a risk score for each patients in Sd. Patients in Sv were stratified into high and low-risk groups based on the median risk score. Kaplan-Meier survival analysis was used to assess the prognostic ability of the risk score on Sv. Results: The risk score comprised nine CT (intra and peri-tumoral texture) and six H&amp;E derived (cancer cell texture and shape) features. A linear regression model in conjunction with these 15 features was significantly associated with chemo-sensitivity in Sv (AUC = 0.76, PRC = 0.81). A multivariable model with these 15 features was significantly associated with OS in Sv (HR = 2.5, 95% CI: 1.3-4.9, P = 0.0043). Kaplan-Meier survival analysis revealed a significantly reduced OS in the high-risk group compared to the low-risk group. Conclusions: A combined CT and H&amp;E tissue derived image signature model predicted response to chemotherapy and improved OS in SCLC patients. Image features from baseline CT scans and H&amp;E tissue slide images may help in better risk stratification of SCLC patients. Additional independent validation of these quantitative image-based biomarkers is warranted.

A Novel Graph Neural Network Methodology to Investigate Dihydroorotate Dehydrogenase Inhibitors in Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is a particularly aggressive tumor subtype, and dihydroorotate dehydrogenase (DHODH) has been demonstrated to be a therapeutic target for SCLC. Network pharmacology analysis and virtual screening were utilized to find out related proteins and investigate candidates with high docking capacity to multiple targets. Graph neural networks (GNNs) and machine learning were used to build reliable predicted models. We proposed a novel concept of multi-GNNs, and then built three multi-GNN models called GIAN, GIAT, and SGCA, which achieved satisfactory results in our dataset containing 532 molecules with all R^2 values greater than 0.92 on the training set and higher than 0.8 on the test set. Compared with machine learning algorithms, random forest (RF), and support vector regression (SVR), multi-GNNs had a better modeling effect and higher precision. Furthermore, the long-time 300 ns molecular dynamics simulation verified the stability of the protein–ligand complexes. The result showed that ZINC8577218, ZINC95618747, and ZINC4261765 might be the potentially potent inhibitors for DHODH. Multi-GNNs show great performance in practice, making them a promising field for future research. We therefore suggest that this novel concept of multi-GNNs is a promising protocol for drug discovery.

PARP Inhibitors in Small-Cell Lung Cancer: Rational Combinations to Improve Responses.

Simple SummarySmall-cell lung cancer carries a dismal prognosis with few long-term treatment options. The enzyme poly-(ADP)-ribose polymerase (PARP), which functions to repair DNA breaks, has emerged as a promising therapeutic target, with modest response rates in early clinical trials prompting investigation of predictive biomarkers and therapeutic combinations. This review summarizes the development and testing of PARP inhibitors in small-cell lung cancer with an emphasis on developing treatment combinations. These combinations can be divided into three categories: (1) contributing to DNA damage; (2) inhibiting the DNA damage response; and (3) activating the immune system. An evolving classification of small-cell lung cancer subtypes and gene expression patterns will guide PARP inhibitor biomarker identification to improve treatments for this challenging cancer.Despite recent advances in first-line treatment for small-cell lung cancer (SCLC), durable responses remain rare. The DNA repair enzyme poly-(ADP)-ribose polymerase (PARP) was identified as a therapeutic target in SCLC using unbiased preclinical screens and confirmed in human and mouse models. Early trials of PARP inhibitors, either alone or in combination with chemotherapy, showed promising but limited responses, suggesting that selecting patient subsets and treatment combinations will prove critical to further clinical development. Expression of SLFN11 and other components of the DNA damage response (DDR) pathway appears to select for improved responses. Combining PARP inhibitors with agents that damage DNA and inhibit DDR appears particularly effective in preclinical and early trial data, as well as strategies that enhance antitumor immunity downstream of DNA damage. A robust understanding of the mechanisms of DDR in SCLC, which exhibits intrinsic replication stress, will improve selection of agents and predictive biomarkers. The most effective combinations will target multiple nodes in the DNA damage/DDR/immune activation cascade to minimize toxicity from synthetic lethality.

NRBF2 Regulates the Chemoresistance of Small Cell Lung Cancer by Interacting With the P62 Protein in the Autophagy Process

SUMMARY Reversing chemotherapy resistance in small cell lung cancer (SCLC) is crucial to improve patient prognosis. It is important to elucidate the mechanisms of chemoresistance and determine therapeutic targets for SCLC. The present study aims to investigate the underlying mechanisms in SCLC chemoresistance. We screen that nuclear receptor binding factor 2 (NRBF2) is a poor prognostic factor in SCLC. A correlation was identified between high NRBF2 expression and poor overall survival in the clinical local-SCLC cohort. The effects of NRBF2 on chemoresistance were determined in SCLC using a patient-derived xenograft model. The effect and underlying molecular mechanisms of NRBF2 in the autophagy process in SCLC were examined. NRBF2 positively regulated autophagy, leading to drug resistance in SCLC. The microtubule interacting and transport (MIT) domain of NRBF2 directly interacted with the PB1 domain of P62, a core autophagy marker. This interaction increased autophagic P62 body formation, revealing the regulatory role of NRBF2 in autophagy. Notably, NRBF2 was directly modulated by the transcription factor XRCC6, likely explaining the differential NRBF2 expression in chemosensitive and chemoresistant SCLC. The MIT domain of NRBF2 interacts with the PB1 domain of P62 to regulate the autophagy process, resulting in SCLC chemoresistance. NRBF2 is likely a useful chemotherapy response marker and therapeutic target in SCLC.