Small Cell Lung Cancer Biopsies Research Articles

Small-Cell Lung Cancer: Is Liquid Biopsy a New Tool Able to Predict the Efficacy of Immunotherapy?

Small-cell lung cancer (SCLC) cases represent approximately 15% of all lung cancer cases, remaining a recalcitrant malignancy with poor survival and few treatment options. In the last few years, the addition of immunotherapy to chemotherapy improved clinical outcomes compared to chemotherapy alone, resulting in the current standard of care for SCLC. However, the advantage of immunotherapy only applies to a few SCLC patients, and predictive biomarkers selection are lacking for SCLC. In particular, due to some features of SCLC, such as high heterogeneity, elevated cell plasticity, and low-quality tissue samples, SCLC biopsies cannot be used as biomarkers. Therefore, the characterization of the tumor and, subsequently, the selection of an appropriate therapeutic combination may benefit greatly from liquid biopsy. Soluble factors, circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and extracellular vesicles (EVs) are now useful tools in the characterization of SCLC. This review summarizes the most recent data on biomarkers detectable with liquid biopsy, emphasizing their role in supporting tumor detection and their potential role in SCLC treatment choice.

Dissecting small cell lung cancer subtypes with cell-free DNA fragmentomes.

8592 Background: Although small cell lung cancer (SCLC) is managed as a single cancer type, new evidence supports that subtypes (high vs low neuroendocrine) of SCLC acquire diverse transcriptional and epigenetic states. Furthermore, distinct SCLC subtypes acquire unique therapeutic vulnerabilities, such as the low-neuroendocrine highly inflamed SCLC subtype that has been linked to immunotherapy sensitivity. We have previously shown that DELFI (DNA evaluation of fragments for early interception) can be used to non-invasively distinguish SCLC from non-small cell lung cancer (NSCLC). Here, we report a preliminary analysis of using the DELFI approach for distinguishing among SCLC subtypes. Methods: Circulating cell-free DNA (cfDNA) was isolated from plasma samples of patients diagnosed with relapsed SCLC and treated with durvalumab plus olaparib in a phase II trial (NCT02484404). Over 200 cfDNA libraries were prepared for whole genome sequencing in batches with internal controls. To infer tumor gene expression profiles in cfDNA, we investigated genome-wide signals of tissue-specific transcription factors differentially regulated in SCLC, and applied a novel DELFI-based approach to inform SCLC molecular subtypes. Clinical information, patient-matched tissue transcriptome (RNA-seq), and chromatin accessibility data (ATAC-seq) were examined in orthogonal analyses. Results: The DELFI classifier detected SCLC cases (N = 47) with a median DELFI score of 1.0 (95% CI 0.99-1), significantly higher than previously reported scores for other lung cancer subtypes. Comparison of DELFI fragmentome signals to publicly available tumor transcriptomes shows subtype-level concordance ( r = 0.78, p < 0.001, Pearson), particularly in pre-treatment SCLC cases separating high- vs low- neuroendocrine subtypes. High-neuroendocrine SCLCs exhibited a decrease in aggregate cfDNA fragment coverage at ASCL1 transcription factor binding sites relative to low-neuroendocrine SCLCs (r = 0.90, p < 0.001, Pearson). Additionally, low-neuroendocrine SCLCs revealed a significant decrease in aggregate cfDNA fragment coverage at genomic binding sites regulated by hematopoietic transcription factors, reflecting the inflamed phenotype of this SCLC subtype. Integration of these approaches provided a cfDNA fragmentation-based machine learning model that distinguished SCLC subtypes with high performance. Conclusions: Genome-wide cfDNA fragmentome analyses can differentiate high- and low-neuroendocrine SCLC subtypes. Given the challenges for performing SCLC biopsies in a clinical setting, we believe this approach could be a viable method of subtyping SCLC in a non-invasive manner.

Comparative study of deep learning models on the images of biopsy specimens for diagnosis of lung cancer treatment

ObjectiveTo compare the application value of different traditional deep learning models in diagnosing and classifying lung cancer. MethodsAccording to the biopsy samples of our hospital from January 2018 to November 2022, 37 patients treated in this department were selected as the study subjects. Nonsmall and small cell lung cancer biopsy specimens were obtained and stained. Two experienced pathologists diagnosed the biopsy specimens. Multiple in-depth learning methods were used to distinguish between cancer and noncancer biopsies. In this study, we compared the application value of traditional deep learning models in lung cancer diagnosis and Classification. ResultsThe study tested several popular CNN architectures based on image block classification: AlexNet, VGG, ResNet, and SqueezeNet, comparing two types of training schemes: training from scratch and fine-tuning the entire pretrained network. The AUC of the deep learning model is more reasonable (0. 8808–0. 9121). Except for Resnet-50, the AUC of the training is higher than that of the fine-tuning of the whole network. ConclusionDeep learning analysis can accelerate the detection speed of whole section images (WSI) and maintain a similar detection rate with pathologists.

Assessment of Two Commercial Comprehensive Gene Panels for Personalized Cancer Treatment.

(1) Background: Analysis of tumor DNA by next-generation sequencing (NGS) plays various roles in the classification and management of cancer. This study aimed to assess the performance of two similar and large, comprehensive gene panels with a focus on clinically relevant variant detection and tumor mutation burden (TMB) assessment; (2) Methods: DNA from 19 diagnostic small cell lung cancer biopsies and an AcroMetrix™ assessment sample with >500 mutations were sequenced using Oncomine™ Comprehensive Assay Plus (OCAP) on the Ion Torrent platform and TruSight Oncology 500 Assay (TSO500) on the Illumina platform; (3) Results: OCAP and TSO500 achieved comparable NGS quality, such as mean read coverage and mean coverage uniformity. A total of 100% of the variants in the diagnostic samples and 80% of the variants in the AcroMetrix™ assessment sample were detected by both panels, and the panels reported highly similar variant allele frequency. A proportion of 14/19 (74%) samples were classified in the same TMB category; (4) Conclusions: Comparable results were obtained using OCAP and TSO500, suggesting that both panels could be applied to screen patients for enrolment in personalized cancer treatment trials.

Abstract B025: ASCL1 and SOX2 expression levels predict sensitivity to LSD1 inhibition with iadademstat in small cell lung cancer

Abstract Lysine Specific Demethylase 1 (LSD1, also known as KDM1A) is a member of the FAD-containing family of lysine demethylases and is generally involved in repressing transcription by specifically removing methyl groups from mono- and di-methylated lysine 4 of histone 3 - epigenetic marks commonly associated with actively transcribed genes. LSD1 over-expression has been associated with disease progression and worse prognosis in several human cancers, and its inhibition has been shown to reduce cancer cell growth, migration and invasion. LSD1 has therefore been recognized as a target of interest for the development of new drugs to treat cancer. Iadademstat (aka ORY-1001), a highly potent and selective LSD1 inhibitor (LSD1i) in clinical development for malignant indications, and other LSD1is, have been reported to be effective for the treatment of small cell lung cancer (SCLC) in in vitro and in vivo models. However, the published data indicate that while certain SCLC are highly sensitive to LSD1 inhibition this sensitivity is not a universal feature of SCLC cells raising the need to develop methods for identifying sensitive SCLC tumors. Herein, we report the identification of the predictive biomarkers ASCL1 and SOX2 for the enrichment of the SCLC population more likely to respond to iadademstat and other LSD1is. Response to LSD1is was evaluated in a broad panel of SCLC cell lines (from viability assay data obtained internally at Oryzon Genomics with iadademstat and from data published elsewhere using other LSD1is). Additionally, analysis of gene expression was performed in this cell line panel using internal and publicly available datasets (Affymetrix, CCLE). This analysis revealed that the transcription factors ASCL1 and SOX2 are more likely to be highly expressed in SCLC cell lines that respond to LSD1 inhibition. Moreover, the mRNA levels of these biomarkers were highly correlated with their protein levels in both SCLC cell lines and in patient-derived xenografts. In particular, immunofluorescence staining of these patient-derived SCLC samples can discriminate different degrees of ASCL1 and SOX2 protein expression levels (none, low, medium, high), which correlate with their mRNA levels determined by RNAseq in the same samples. Moreover, analysis of ASCL1 and SOX2 protein levels analyzed internally by immunofluorescence in 40 SCLC biopsies showed that 58% samples concomitantly expressed medium to high levels of both biomarkers. Taken together, these data suggest that medium to high expression of both ASCL1 and SOX2 define a SCLC population more likely to respond to LSD1 inhibition, and that this population could account for nearly 60% of SCLC cases. Therefore, ASCL1 and SOX2 expression could be used as predictive biomarkers for personalized medicine with iadademstat in SCLC patients and clinical research to validate this hypothesis is warranted. Citation Format: Natalia Sacilotto, Serena Lunardi, Filippo Ciceri, Cristina Mascaro, Tamara Maes, Ana Limon, Douglas V. Faller. ASCL1 and SOX2 expression levels predict sensitivity to LSD1 inhibition with iadademstat in small cell lung cancer. [abstract]. In: Proceedings of the AACR Special Conference: Cancer Epigenomics; 2022 Oct 6-8; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_2):Abstract nr B025.

P2.10-01 Transcriptional Diversity of Emerging Cell Populations in Refractory Small Cell Lung Cancer Biopsies and Xenografts

Small cell lung cancer (SCLC) is a high-grade neuroendocrine lung carcinoma notable for early dissemination and rapid, albeit transient, responses to standard of care (SOC) treatment [platinum-based chemotherapy plus immune checkpoint blockade (ICB)] that are rapidly undone by refractory relapses. Using single cell profiling, we previously demonstrated that a major factor regulating resistance is an increase in plasticity and transcriptional intratumoral heterogeneity (ITH) in response to treatment.

Hierarchical identification of a transcriptional panel for the histological diagnosis of lung neuroendocrine tumors.

Background: Lung cancer is a complex disease composed of neuroendocrine (NE) and non-NE tumors. Accurate diagnosis of lung cancer is essential in guiding therapeutic management. Several transcriptional signatures have been reported to distinguish between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) belonging to non-NE tumors. This study aims to identify a transcriptional panel that could distinguish the histological subtypes of NE tumors to complement the morphology-based classification of an individual. Methods: A public dataset with NE subtypes, including 21 small-cell lung cancer (SCLC), 56 large-cell NE carcinomas (LCNECs), and 24 carcinoids (CARCIs), and non-NE subtypes, including 85 ADC and 61 SCC, was used as a training set. In the training set, consensus clustering was first used to filter out the samples whose expression patterns disagreed with their histological subtypes. Then, a rank-based method was proposed to develop a panel of transcriptional signatures for determining the NE subtype for an individual, based on the within-sample relative gene expression orderings of gene pairs. Twenty-three public datasets with a total of 3,454 samples, which were derived from fresh-frozen, formalin-fixed paraffin-embedded, biopsies, and single cells, were used for validation. Clinical feasibility was tested in 10 SCLC biopsy specimens collected from cancer hospitals via bronchoscopy. Results: The NEsubtype-panel was composed of three signatures that could distinguish NE from non-NE, CARCI from non-CARCI, and SCLC from LCNEC step by step and ultimately determine the histological subtype for each NE sample. The three signatures achieved high average concordance rates with 97.31%, 98.11%, and 90.63%, respectively, in the 23 public validation datasets. It is worth noting that the 10 clinic-derived SCLC samples diagnosed via immunohistochemical staining were also accurately predicted by the NEsubtype-panel. Furthermore, the subtype-specific gene expression patterns and survival analyses provided evidence for the rationality of the reclassification by the NEsubtype-panel. Conclusion: The rank-based NEsubtype-panel could accurately distinguish lung NE from non-NE tumors and determine NE subtypes even in clinically challenging samples (such as biopsy). The panel together with our previously reported signature (KRT5-AGR2) for SCC and ADC would be an auxiliary test for the histological diagnosis of lung cancer.

Expression of the Sonic Hedgehog Embryonic Signalling Pathway Components in Matched Pre-Treatment and Relapsed Small Cell Lung Cancer Biopsies

Abstract Cancer stem cells may be responsible for tumour regrowth and acquisition of resistance in small cell lung cancer (SCLC). The Hedgehog pathway regulates survival and proliferation of tissue progenitor and stem cell populations, promoting the expression of stem cell related and proliferative genes. We evaluated the Sonic Hedgehog (Shh) embryonic signalling pathway in relapsed SCLC. Expression levels of Shh related genes GLI1, SMO, SUFU, PTCH1, HHIP, BCL2, BMI, ZEB1, ZEB2, N-MYC, Twist1 were analysed by qRT-PCR in matched pre-treatment and relapsed tumour fresh frozen biopsies of three SCLC patients. Expression of each gene was compared using the paired samples t-test, as well as comparison of mean expression levels was done. Data were statistically interpreted using the MedCalc version 10.2.0.0 software. 2.9-fold lower mean mRNA expression of the major Hedgehog activation indicator GLI1 was observed in relapsed samples (p = 0.0529). Mean expression of six Shh inducible genes, PTCH1, HHIP, N-MYC, ZEB2, Twist1, ZEB1, was also downregulated by 2.6-, 2.2-, 1.9-, 1.8-, 1.2-, 1.1-fold, respectively (p = 0.4252, p = 0.1268, p = 0.2480, p = 0.1169, p = 0.1480, p = 0.7595, respectively). 1.8-fold mean expression decrease was found for Gli activator Smo (p = 0.4111). Only the Shh pathway inhibitor SUFU and two other examined Hedgehog signalling inducible genes BCL2 and BMI in relapsed SCLC showed 0.8-, 0.9-,and 0.8-fold increase of expression, respectively (p = 0.3074, p = 0.7921, and p = 0.3822, respectively). To our knowledge, this is the first report of comparison of Shh signalling in matched pre-treatment and relapsed SCLC biopsies. Our data show decreased activity for majority of Shh pathway components in relapsed SCLC, although difference did not reach statistical significance.

Dysregulated Pyrimidine Biosynthesis Contributes to 5-FU Resistance in SCLC Patient-Derived Organoids but Response to a Novel Polymeric Fluoropyrimidine, CF10.

Chemo-immunotherapy is central to the treatment of small cell lung cancer (SCLC). Despite modest progress made with the addition of immunotherapy, current cytotoxic regimens display minimal survival benefit and new treatments are needed. Thymidylate synthase (TS) is a well-validated anti-cancer drug target, but conventional TS inhibitors display limited clinical efficacy in refractory or recurrent SCLC. We performed RNA-Seq analysis to identify gene expression changes in SCLC biopsy samples to provide mechanistic insight into the potential utility of targeting pyrimidine biosynthesis to treat SCLC. We identified systematic dysregulation of pyrimidine biosynthesis, including elevated TYMS expression that likely contributes to the lack of efficacy for current TS inhibitors in SCLC. We also identified E2F1-3 upregulation in SCLC as a potential driver of TYMS expression that may contribute to tumor aggressiveness. To test if TS inhibition could be a viable strategy for SCLC treatment, we developed patient-derived organoids (PDOs) from human SCLC biopsy samples and used these to evaluate both conventional fluoropyrimidine drugs (e.g., 5-fluorouracil), platinum-based drugs, and CF10, a novel fluoropyrimidine polymer with enhanced TS inhibition activity. PDOs were relatively resistant to 5-FU and while moderately sensitive to the front-line agent cisplatin, were relatively more sensitive to CF10. Our studies demonstrate dysregulated pyrimidine biosynthesis contributes to drug resistance in SCLC and indicate that a novel approach to target these pathways may improve outcomes.

Success of genomic profiling of non-small cell lung cancer biopsies obtained by trans-thoracic percutaneous needle biopsy.

Genomic profiling for personalized targeted therapy has become standard of care. We report the success of genomic profiling of non-small cell lung cancer (NSCLC) obtained by trans-thoracic needle biopsy (TTNB) in a single center experience. Patients with NSCLC who underwent TTNB for genomic were identified. Pathology specimens were evaluated for tumor adequacy and then analyzed for selected exons of epidermal growth factor receptor, KRAS, BRAF, PIK3CA, and ERBB2. ALK rearrangements were detected with fluorescence in situ hybridization and/or immunohistochemistry. Technical success was recorded and the factors affecting successful profiling were evaluated. Complications (pneumothorax, hemorrhage, and admission) were recorded. Comparison of yield and complications were done between the two groups (core biopsy and fine needle aspiration only group). Utility of PET-CT to guide the needle track for optimized yield was assessed in a subset of patients. Between December 6, 2009, and December 30, 2016, 765 patients with NSCLC underwent TTNB. Five-hundred and seventy-seven of 765 (75%) of all TTNB were profiled, for genomic analysis. Five-hundred and eight of 577 (88%) were successfully profiled. The number of samples obtained ranged from 1 to 10 (1 to 2 cm,18 to 20 G). Lesions biopsied ranged in size from 0.6 to 16 cm. No statistically significant difference was observed in the incidence of pneumothorax between two groups (P = 0.26). PET guidance was not found to be statistically significant ( P = 0.79) in the overall yield. Computed tomographic guided TTNB is a safe and efficacious technique for genomic profiling, enables the acquisition of sufficient tissue for genetic mutation analyses allowing for personalized therapy with an acceptable complication rate.

The 180 splice variant of NCAM-containing exon 18-is specifically expressed in small cell lung cancer cells.

The Neural Cell Adhesion Molecule (NCAM) is a glycoprotein expressed as 120, 140 and/or 180 kDa isoforms, all derived through alternative splicing of a single gene. NCAM 120 contains no intracellular domain, whereas NCAM 140 and 180 have different intracellular domains determined by alternative splicing of exon 18. NCAM has been described as a biomarker to discriminate small cell lung cancer (SCLC) from non-SCLC (NSCLC). However, peripheral blood mononuclear cells (PBMC) also express NCAM. We studied the expression of NCAM splice variants in cell lines, tumor tissues and control cells. Using reverse transcriptase-PCR we evaluated the expression of NCAM exon 18 splice variants in lung cancers cell lines, control cell lines, PBMC of healthy controls and SCLC tissue. In addition we studied the expression of the NCAM exon 18 encoded protein (E18) in SCLC by immunocytochemistry and flow cytometry using an E18-specific monoclonal antibody obtained by hybridoma fusion of E18-immunized mouse spleen cells. Finally we looked at immune responses to E18 in mice. We found expression of RNA encoding the NCAM 180 variant in all SCLC cell lines. NCAM exon 18 was not expressed in 23/28 (82%) of the other tumor and leukemia cell lines tested and PBMC. Next, we also evaluated the expression of NCAM exon 18 in human SCLC tissue. Expression of NCAM exon 18 in 8 of the 10 (80%) SCLC biopsy samples was found. The newly raised E18-specific antibodies stained NCAM at the adherent junctions between adjacent cells in SCLC cell lines. The data demonstrate the intracellular location of E18 in SCLC. Furthermore, a specific cytotoxic T cell (CTL) response and significant antibody titers were found in mice upon immunization with recombinant E18 and its encoding DNA. The results of this study can be applied in the diagnosis and immunotherapy of SCLC. A larger study investigating E18 as a marker for SCLC is indicated.

PUB050 Identification of Proteins Associated by Mutation Status in Non Small-Cell Lung Cancer Biopsies

Proteins are the functional players driving both normal and disease physiology. The proteomic changes observed in lung cancer can be a consequence of mutations in cancer associated genes. Some of the most common types of mutations in lung cancer are EGFR, TP53 and KRAS mutations, known to influence treatment response. The purpose of this study was to identify proteins associated with smoking status and EGFR, TP53 and KRAS mutations in lung cancer biopsies which may serve as novel targets to overcome treatment resistance. We have performed a profiling of 300 cancer relevant proteins, of which 60 were in a phosphorylated state, using reverse phase protein arrays (RPPA). We analyzed biopsies from 80 non small-cell lung cancer biopsies and correlated the protein expression pattern with mutation status of EGFR, TP53 and KRAS, in addition to smoking status. The protein expression was correlated with mRNA expression analyzed on hybridization arrays. Ten of the samples were EGFR mutated, 9 were never-smokers, 31 TP53 mutated and 32 KRAS mutated. With a FDR < 0.001, we detected 7 proteins (ATP5A, EIF4EBP1, CCNB1, CDK1, CASP3, FN1 and CDKN2A) differentially expressed between TP53 mutated and wild type samples. Further, 4 proteins (RPS6K, CAV1, YBX1 and VIM) were higher expressed in KRAS mutated samples compared with KRAS wild type samples. For EGFR mutated samples, only the protein EGFR was upregulated. Three proteins were overexpressed in never smokers (EGFR, KRT19 and TUBA1A). A significant correlation between protein expression and mRNA expression were found for all the proteins except YBX1, ATP5A and TUBA1A (p<0.05). These results demonstrate that key driver mutations in lung cancer affect several proteins linked to the same pathway. We observed significant upregulation of the TP53 cell cycle target genes CDK1 and CCNB1 in samples with TP53 mutations. KRAS mutated samples showed an overexpression of cavolin 1 (CAV1), an important regulator of cell proliferation and metastasis, and an increased expression of the mesenchymal protein vimentin (VIM). As of today, we do not have any effective treatment targeting KRAS- and TP53- mutated cells. However, proteins associated with the mutation status may be new potential therapeutic targets to circumvent treatment resistance. In the present study, we identified both known and novel proteins associated with TP53 and KRAS mutated samples.

Fibroblast Growth Factor Receptor 1 and Related Ligands in Small-Cell Lung Cancer

Introduction:Small-cell lung cancer (SCLC) accounts for 15% of all lung cancers and has been understudied for novel therapies. Signaling through fibroblast growth factors (FGF2, FGF9) and their high-affinity receptor has recently emerged as a contributing factor in the pathogenesis and progression of non–small-cell lung cancer. In this study, we evaluated fibroblast growth factor receptor 1 (FGFR1) and ligand expression in primary SCLC samples.Methods:FGFR1 protein expression, messenger RNA (mRNA) levels, and gene copy number were determined by immunohistochemistry (IHC), mRNA in situ hybridization, and silver in situ hybridization, respectively, in primary tumors from 90 patients with SCLC. Protein and mRNA expression of the FGF2 and FGF9 ligands were determined by IHC and mRNA in situ hybridization, respectively. In addition, a second cohort of 24 SCLC biopsy samples with known FGFR1 amplification by fluorescence in situ hybridization was assessed for FGFR1 protein expression by IHC. Spearman correlation analysis was performed to evaluate associations of FGFR1, FGF2 and FGF9 protein levels, respective mRNA levels, and FGFR1 gene copy number.Results:FGFR1 protein expression by IHC demonstrated a significant correlation with FGFR1 mRNA levels (p < 0.0001) and FGFR1 gene copy number (p = 0.03). The prevalence of FGFR1 mRNA positivity was 19.7%. FGFR1 mRNA expression correlated with both FGF2 (p = 0.0001) and FGF9 (p = 0.002) mRNA levels, as well as with FGF2 (p = 0.01) and FGF9 (p = 0.001) protein levels. There was no significant association between FGFR1 and ligands with clinical characteristics or prognosis. In the second cohort of specimens with known FGFR1 amplification by fluorescence in situ hybridization, 23 of 24 had adequate tumor by IHC, and 73.9% (17 of 23) were positive for FGFR1 protein expression.Conclusions:A subset of SCLCs is characterized by potentially activated FGF/FGFR1 pathways, as evidenced by positive FGF2, FGF9, and FGFR1 protein and/or mRNA expression. FGFR1 protein expression is correlated with FGFR1 mRNA levels and FGFR1 gene copy number. Combined analysis of FGFR1 and ligand expression may allow selection of patients with SCLC to FGFR1 inhibitor therapy.

Macrophages of M1 phenotype have properties that influence lung cancer cell progression.

Stromal macrophages of different phenotypes can contribute to the expression of proteins that affects metastasis such as urokinase-type plasminogen activator (uPA), its receptor uPAR, and plasminogen activator inhibitor-1 (PAI-1), but knowledge of how essential their contribution is in comparison to the cancer cells in small cell lung cancer (SCLC) and lung squamous cell carcinoma (SCC) is lacking. The expression of uPA, uPAR, and PAI-1 and of the matrix metalloproteinases (MMP)-2 and MMP-9 were studied in human macrophages of M1 and M2 phenotype and compared to a lung SCC (NCI-H520) and a SCLC (NCI-H69) cell line. Effects of treatment with conditioned media (CM) from M1 and M2 macrophages on the expression of these genes in H520 and H69 cells as well as effects on the cell growth were investigated. In addition, data on the stromal macrophages immunoreactivity of uPAR, MMP-2, and MMP-9 in a few SCC and SCLC biopsies was included. uPAR, MMP-2, and MMP-9 were confirmed in stromal cells including macrophages in the SCC and SCLC biopsies. In vitro, both macrophage phenotypes expressed considerably higher mRNA levels of uPA, uPAR, PAI-1, and MMP-9 compared to the cancer cell lines, and regarding uPAR, the highest level was found in the M1 macrophage phenotype. Furthermore, M1 CM treatment not only induced an upregulation of PAI-1 in both H520 and H69 cells but also inhibited cell growth in both cell lines, giving M1 macrophages both tumor-promoting and tumor-killing potential.

Small cell lung cancer tumour cells induce regulatory T lymphocytes, and patient survival correlates negatively with FOXP3+ cells in tumour infiltrate

Small cell lung cancer (SCLC) kills at least one person every 2 hr in the United Kingdom. Some patients do relatively well but most have rapidly progressive disease. There is no effective treatment and overall 2-year survival is less than 5%. Patients with SCLC have poorly understood local and systemic immune defects and can be immunocompromised. As CD4(+) T lymphocytes coordinate and regulate immunity, a better understanding of interactions between SCLC tumour cells and CD4(+) T cells may lead to effective molecular immunotherapy. We show that some, but not all, SCLC tumour cell lines secrete molecules that induce IL-10 secretion by and de novo differentiation of functional CD4(+)CD25(+)FOXP3(+)CD127(lo)Helios(-) regulatory T (Treg) cells in healthy blood lymphocytes. FOXP3(+) T cells were found in SCLC tumour biopsies, and patients with higher ratios of FOXP3(+) cells in tumour infiltrates have a worse survival rate. The inhibitory effect of SCLC tumour cells was not affected by blocking IL-10 receptor or TGF-β signalling but was partially reversed by blocking IL-15, which is reported to be involved in human Treg cells induction. IL-15 was secreted by SCLC cells that inhibited CD4(+) T-cell proliferation and was present in SCLC biopsy tumour cells. These novel findings demonstrate that SCLC tumour cells can induce CD4(+) T-cell-mediated immunosuppression. This gives a potential mechanism by which SCLC tumour cells may downregulate local and systemic immune responses and contribute to poor patient survival. Our data suggest that IL-15 and Treg cells are potential new therapeutic targets to improve immune response and patient survival in SCLC.

Abstract CN02-02: CTCs as pharmacodynamic and /or predictive biomarkers

Abstract CTC analysis has potential utility in the development of novel therapeutics and particularly so for the management of those patients with cancer types for which obtaining tumor biopsies poses significant challenge, especially pre and serially post therapy. We have enumerated and begun to characterize CTCs from patients with lung cancer (both small cell lung cancer (SCLC) and non small cell lung cancer (NSCLC)) using two techniques; a) the Veridex CellSearch Platform wherein CTCs are identified based on EpCam and cytokeratin expression together with the absence of the white blood cell surface marker CD45, and b) the Metagenex ISET filter-based system that isolates CTCs on the basis of their size. SCLC accounts for ∼15% of all lung cancers, is highly aggressive with a rapid doubling time, high growth fraction and propensity to metastasise early. Primary SCLC biopsies are often of small volume, highly necrotic and thus present difficulties for biomarker analysis. As SCLC has neuro-endocrine characteristics, we examined initially, the ability of the CellSearch approach (with the epithelial cell marker EpCam as its primary discriminator) to detect SCLC CTCs. In chemo-naive SCLC, CTCs were detected in 86% patients (median 28, range 0–44896, n=50). Tumor stage correlated with CTC number (#) and was highest in patients with liver metastases. The median survival for patients with baseline CTC# &amp;gt;300/7.5ml blood was 134 days compared to 443 days when CTC# &amp;lt;2. We next asked whether the CTCs detected expressed the neuro-endocrine surface marker CD56 using the 4th immunofluorescence channel on the CellSearch platform. Expression of CD56 was heterogeneous but consistent with expression in primary tumors. CTC# was pharmacodynamic, decreasing after one cycle of etoposide/platinum chemotherapy mirroring radiological response. CTC# and % apoptotic CTCs (analyzed by nuclear morphology) are now being applied as pharmacodynamic biomarkers in early clinical trials of novel agents and in particular of pro-apoptotic agents. To test the hypothesis that CTCs could provide added value to novel drug development, we also assessed the feasibility of drug-target characterization in SCLC CTCs. Bcl-2, an antiapoptotic drug target, is amplified in ∼40% SCLC patients and was detectable in SCLC CTCs using fluorescence in situ-hybridization; potentially, Bcl-2 amplification will predict sensitivity to Bcl-2 targeted drugs. In a cohort of 93 chemo-naive stage III/IV NSCLC patients, 2 or more CTCs/7.5ml blood were detected using CellSearch in 6% patients (2/36) with stage IIIA/IIIB disease and 32% (18/57) patients with stage IV disease. A CTC# of &amp;gt;5 at baseline predicted for a worse progression free and overall survival compared to patients with &amp;lt;5 CTCs (p = &amp;lt; 0.0001). For the 20 patients with 2 of more CTCs at baseline, 55 % exhibited reduction in CTC# following a single cycle of standard platinum based chemotherapy, suggesting that CTC# may be useful in early prediction of response to novel therapeutics. Matched blood samples were taken for ISET analysis for 30 of this cohort of NSCLC patients. CTCs were detected in patients in whom no CTCs were identified using CellSearch. This may be due to loss of, or reduction in EpCam expression perhaps during eptithelial to mesenchymal transition and this now requires further investigation. After optimization of immunohistochemical assays using ISET filters, a panel of NSCLC markers including Thyroid Transcription Factor 1 (TTF1, a routinely used diagnostic marker for NSCLC) and EGFR are being used to confirm the identity of NSCLC CTCs distinct from peripheral blood mononuclear cells. This approach is being applied for detection of protein targets of novel therapies. Overall, our data suggest that CTC analysis is a powerful addition to the biomarker portfolio for drug development in lung cancer. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):CN02-02.

Deletion mapping of the short arm of chromosome 3 in Merkel cell carcinoma.

Little is known about the biology of Merkel cell carcinoma (MCC), also called small cell carcinoma of the skin. MCC has similarities with small cell lung cancer (SCLC): both are neuroendocrine malignancies with early metastasis to distant sites and a poor prognosis. Small cell lung cancer biopsies are known to have frequent losses on chromosome 3 in the region 3p21, yet MCCs have not been reported to have 3p deletions by karyotypic analysis. Considering the similarities between SCLC and MCC, we investigated 26 MCC tumours for loss of heterozygosity (LOH) on 3p. First, RFLP analysis was performed using PCR with nine primer sets from six loci. Second, 25 tumours were examined by microsatellite analysis for 3p markers D3S1289 and D3S1285 and SST on 3q. All 26 tumours were informative at one or more loci; of these, 18 (69%) demonstrated LOH for at least one marker on the short arm. For all informative loci the frequency of LOH was greater than 30% (range 33-75%). In a cell line derived from one tumour, it was possible to demonstrate rearrangement of chromosome 3 by in situ hybridisation. No LOH was seen in 15 informative cases for the 3q locus SST. A region 3p13-p21.1, centered on the marker D3S2, was deleted in all tumours demonstrating LOH, with a secondary deletion involving D3S30 detected in some tumours at 3p13. Our results indicate that LOH on 3p is a common occurrence in MCC; however, three tumours for which DNA was also available from a corresponding cell line suggest there may be a subset of MCC whose genesis is independent of deletions of 3p.

Increased expression of N-myc in human small cell lung cancer biopsies predicts lack of response to chemotherapy and poor prognosis.

Amplified and increased expression of the myc family of protooncogenes (c- and N-myc) has been described to be associated with rapid proliferation in a number of cell lines, including small cell lung cancer (SCLC). In SCLC, c-myc was demonstrated to be amplified in a subset of SCLC cell lines denoted as variant type, which show a more aggressive way of growth in vitro. The N-myc oncogene, which has extensive homology in the second exon with c-myc, has been shown to be implicated in the oncogenesis of several primary tumors, including SCLC. The authors describe, using in situ hybridization, that increased expression of the N-myc oncogenes in primary biopsies from 15 untreated patients with SCLC are strongly associated with poor response to chemotherapy, rapid tumor growth, and short survival.