De novo and histologically transformed small cell lung cancer is sensitive to lurbinectedin treatment through the modulation of EMT and NOTCH signaling pathways

Abstract

Purpose:

Small cell lung cancer (SCLC) is a high-grade neuroendocrine tumor with dismal prognosis and limited treatment options. Lurbinectedin, conditionally approved as a second-line treatment for metastatic SCLC, drives clinical responses in about 35% of patients and the overall survival of those who benefit from it remains very low (~9.3 months). This highlights the need to develop improved mechanistic insight and predictive biomarkers of response.

Experimental Design:

We used human and PDX-derived SCLC cell lines to evaluate the effect of lurbinectedin in vitro. We also demonstrate the anti-tumor effect of lurbinectedin in multiple de novo and transformed SCLC PDX models. Changes in gene and protein expression pre- and post-lurbinectedin treatment was assessed by RNA sequencing and western blot analysis.

Results:

Lurbinectedin markedly reduced cell viability in majority of SCLC models with the best response on POU2F3-driven SCLC cells. We further demonstrate that lurbinectedin, either as a single agent or in combination with osimertinib, causes an appreciable anti-tumor response in multiple models of EGFR-mutant lung adenocarcinoma with histologic transformation to SCLC. Transcriptomic analysis identified induction of apoptosis, repression of EMT, modulation of PI3K/AKT, NOTCH signaling associated with lurbinectedin response in de novo and transformed SCLC models.

Conclusion:

Our study provides a mechanistic insight into lurbinectedin response in SCLC and the first demonstration that lurbinectedin is a potential therapeutic target after SCLC transformation.

Introduction

Small cell lung cancer (SCLC) is a high-grade neuroendocrine cancer that accounts for 15% of lung cancers and is typically metastatic at diagnosis ^[1]. Annually, SCLC causes more than 200,000 deaths worldwide, ~30,000 deaths in the US, and has a dismal median overall survival of approximately one year, and a two-year survival rate below 5% for advanced disease ^[2]. SCLC is characterized by a ubiquitous loss-of-function mutation in two major tumor suppressors, TP53 and RB1 ^[1]. SCLCs can be divided into four primary, molecularly defined subtypes that differ substantially in biology and response to therapy. These subtypes are classified by the relative expression of four transcriptional factors ASCL-1 (SCLC-A), NEUROD1 (SCLC-N), YAP1 (SCLC-Y), and POU2F3 (SCLC-P) ^[3]. Although mutationally quite similar, work from our group and others has highlighted the intra- and inter-tumoral heterogeneity of SCLCs.

The addition of programmed death-ligand 1 (PD-L1) antibody to first-line chemotherapy in extensive-stage (ES) SCLC provides durable responses in only a minority of patients, improving median progression-free survival by two months. Few treatment options exist after relapse from first-line chemo-immunotherapy in the second line and beyond ^[4]. Lurbinectedin, a synthetic analog of a natural marine-based tetrahydroisoquinoline, is approved by FDA as a second-line treatment for recurrent metastatic or advanced-stage SCLC^[5]. Lurbinectedin binds to the DNA minor groove in the ‘GG rich’ region [6] and blocks RNA Pol II-mediated transcription. The phase II trial with lurbinectedin as second-line therapy in extensive-stage SCLC showed partial response in 35.2% of patients with a median duration of the response of 5.3 months. ^[7] However, in a subsequent Phase 3 trial (ATLANTIS), lurbinectedin in combination with doxorubicin failed to show superiority against the standard of care chemotherapy, cyclophosphamide/doxorubicin/vincristine or topotecan in SCLC patients who have progressed from one line of platinum therapy. ^[8].

Very little is known about the sensitivity of different molecular subtypes of SCLC to lurbinectedin treatment and biomarkers of lurbinectedin response. Therefore, defining the subset of SCLC patients who are most likely to benefit from lurbinectedin treatment is a critical clinical need. Although a previous study proposed biomarkers for lurbinectedin sensitivity, this was based on analysis of human cell lines tested in vitro and in vivo ^[9]. Further studies in cancer- relevant patient-derived xenograft (PDX) models representing the major SCLC subtypes and improved understanding of lurbinectedin-mediated transcriptomic and proteomic changes in SCLC is needed.

In addition to de novo SCLC, previous reports by our group and others have established lineage plasticity as an important mechanism of resistance to targeted therapies in lung cancer. In EGFR-mutant lung adenocarcinomas, up to 14% of acquired resistance to first line osimertinib is attributable to the histologic transformation of SCLC ^{[10] [11]}. Cases of EGFR wild-type LUAD transforming into SCLC have also been previously reported ^[12]. Clinical outcomes of patients after SCLC transformation treated with SCLC-directed therapies are worse than de novo SCLC, with a high but transient response to platinum-based chemotherapy ^[13]. The largest retrospective review of EGFR-mutant SCLC included 67 patients and reported a response rate of 54% to doublet platinum-etoposide, compared to the 60–70% response rates reported for de novo extensive-stage SCLC. Moreover, there were 0/17 responses observed among EGFR-mutant SCLC treated with later-line immunotherapy ^[14]. Therefore, there remains an unmet need for effective therapies for patients with transformed EGFR-mutant SCLC that addresses their unique biology.

In this study, we investigated the preclinical efficacy of lurbinectedin in a panel of human and PDX-derived cell lines and de novo SCLC PDX models, representing the major subtypes. This study also demonstrates the anti-tumor effect of lurbinectedin with or without osimertinib in multiple PDX models of SCLC transformation. We further analyzed transcriptomic and proteomic changes pre- and post-lurbinectedin treatment in vitro and in vivo to improve mechanistic understanding of lurbinectedin response in SCLC.

Materials and Methods

Cell lines and cell cultures

Human SCLC cell lines were obtained from the American Type Culture Collection (ATCC) and the European Collection of Authenticated Cell Cultures (ECACC). PDX-cell lines were derived in-house. Cell lines were maintained in Roswell Park Memorial Institute (RPMI) media supplemented with 10% fetal bovine serum, penicillin (100 U/mL), streptomycin (50 g/mL) and 2 mM L-Glutamine and incubated at 37°C with 5% CO₂. Cell lines were tested and authenticated by short tandem repeat profiling (DNA fingerprinting) and routinely tested for mycoplasma species before any experiments were performed. Generally, the cells were used within the first three to five passages for any experiments.

Chemical compounds

Lurbinectedin was purchased from Selleckchem (Catalog No. S9603) and also provided by Jazz Pharmaceuticals. Osimertinib was purchased from Selleckchem (Catalog No. S7297).

Cell viability assay

SCLC cell lines were plated in 96-well plates (2000 cells/well) in triplicate for each concentration. Cells were kept in complete RPMI media containing 10% fetal bovine serum, penicillin (100 U/mL), and streptomycin (50 g/mL) and 2 mM L-Glutamine overnight and then they were treated with dimethyl sulfoxide (DMSO) for control or different concentrations of Lurbinectedin for 24 hours. The cell viability was assessed with CellTiter-Glo luminescent cell viability assay reagent (Promega, Madison, WI) according to the manufacturer’s protocol Half-maximal inhibitory concentrations (IC50s) were calculated using GraphPad Prism Ver. 9.0 (GraphPad Software, Inc., San Diego, CA, USA) (RRID:SCR_002798).

RNA-sequencing

Fresh cell pellet or frozen tumor samples were shippedto GENEWIZ for RNA isolation, library preparation, and RNA sequencing. TotalRNA was extracted using the RNeasy Plus Universal mini kit followingmanufacturer’s instructions (Qiagen, Hilden, Germany). RNA sequencing librarieswere prepared using the NEBNext Ultra II RNA Library Prep Kit for Illuminafollowing manufacturer’s instructions (NEB, Ipswich, MA, USA). RNA samples andsequencing libraries were validated on the Agilent TapeStation (AgilentTechnologies, Palo Alto, CA, USA), and quantified by using Qubit 2.0Fluorometer (Invitrogen, Carlsbad, CA) as well as by quantitative PCR (KAPABiosystems, Wilmington, MA, USA). Sequencing libraries were clustered on oneflowcell lane and then loaded on the Illumina HiSeq instrument (4000 orequivalent) (RRID: SCR_020127) according to manufacturer’s instructions. Samples were sequenced using a 2×150bp paired end (PE) configuration. Image analysis and base calling were conducted by the HiSeq Control Software (HCS). Raw sequence data (.bclfiles) was converted into fastq files and de-multiplexed using Illumina’sbcl2fastq 2.17 software (RRID: SCR_015058). One mismatch was allowed for index sequence identification.

RNA-seq analysis for in-vitro samples

The RNA-seq reads were quantified with Salmon v1.1.0 (RRID:SCR_017036) running on raw reads being mapped to 25-mer indexed mm-10 genome. Mapping validation (--validatemappings), bootstrapping with 30 re-samplings (--numBootstraps); sequence specific biases (--seqBias), coverage biases (--posBias) and GC biases corrections (--gcBias) were enabled apart from default settings. Sleuth v0.30.0 in gene mode (RRID:SCR_016883) was used for differential gene expression and PCA analysis along with transcript per million (TPM) normalization. The transcript to gene map was based on Ensembl 92 (RRID:SCR_002344).Wald test was used to identify DEGS and significant genes were marked using False Discovery Rates as per Benjamini-Hochberg method and Sleuth-based estimation of log2 fold change as specified. Across the sets of data of differential gene expression the gene set enrichment analysis (GSEA) (RRID: SCR_003199) was done and genes were ranked on p value scores computed as -log10(p value)*(sign of beta). GSEA annotations of Hallmark genes were taken from Molecular Signatures Database (MSigDB v7.0.1) (RRID: SCR_016863) gene set enrichment analysis for functional enrichment were performed using the clusterProfiler R package (v3.16.0) (RRID:SCR_016884)

RNA-Seq alignment and quality control of the in-vivo studies

A total of 61 RNA-Seq libraries from two different experiments (de-novo and transformed systems) are processed using the same pipeline for compatibility. The de-novo experiment consisted of 30 samples from three cell lines namely Lx110, Lx33, and Lx1322 where each cell line consists of five control replicates, and 5 Lurbinectedin treatment replicates. From this experiment, 16 samples were removed due to high variation between replicates, identified from PCA graphs. (3 from the Lx33 control group, 2 from the Lx33 treatment, 3 from the Lx110 control group, 2 from the Lx110 treatment group, 3 from the Lx1322 control group, 2 from the Lx1322 treatment group.) The transformed experiment consisted of 31 samples from two cell lines Lx831b and Lx1042, each with four conditions, Lurbinectedin treatment, Osimertinib treatment, combination treatment, and a vehicle control. All conditions had four replicates, except for the Lx1042 combination treatment, which had three replicates. From the transformed experiment, 12 samples were removed due to poor PCA clustering from high variation between replicates, one of which also had a unique alignment rate under 5% from the STAR aligner (RRID:SCR_004463) (1 from the Lx831b Lurbinectedin condition, 1 from the Lx831b Osimertinib condition, 2 from the Lx831b Vehicle group, 2 from the Lx831b Combination condition, 2 from the Lx1042 Lurbinectedin condition, 2 from the Lx1042 Vehicle group, 1 from the Lx1042 Osimertinib group, 1 from the Lx1042 combination group.) Quality control of raw reads has been performed using FastQC (v0.11.8) [RRID: SCR_014583]. Trim Galore! (version 0.6.5) has been used to trim the adapter sequences with a quality threshold of 20 [RRID : SCR_011847]. The human genome and transcriptome reference used is GRCh38.p13 genome assembly from GENCODE release 36 (RRID: SCR_014966). The alignment is performed by using STAR aligner (v2.7.5b) (RRID:SCR_004463). Gene level read counts are obtained by using Salmon (v1.2.1) (RRID: SCR_017036) for all libraries using mapping mode. All remaining samples have passed the quality control requirements with > 50% of reads uniquely mapping (>10M uniquely mapped reads for each library) using STAR aligner (RRID: SCR_004463).

Differential expression and functional analysis

Differential expression analysis was performed using the gene level read counts and the DESeq2 (v1.28.1) R package (RRID: SCR_015687). Genes with less than 5 reads in total across all samples are filtered as inactive genes. A gene is considered differentially expressed if the adjusted p-value is less than 0.05 and the absolute log2 fold change is greater than 1. The over-representation and gene set enrichment analysis for functional enrichment are both performed using the clusterProfiler R package (v3.16.0) [RRID:SCR_016884]. The gene sets used for functional analysis are obtained from The Molecular Signatures Database (MSigDB) (RRID: SCR_016863). The Fisher test was used to determine whether the overlap between the DEGs and the genes in the term is statistically significant (p < 0.05). The bold terms with an asterisk in front are the terms that are significantly enriched (p-adjusted < 0.05).

Principal component analysis and heatmaps

We performed the between sample normalization using the variance stabilizing transformation of the DESeq2 package. The 1000 most variable genes are used to perform principal component analysis as well as calculating the Euclidean distances between each sample. Gene expression heatmaps show the z-scores of DESeq2 VST normalized gene-level read counts. All visualizations are generated using plotly R package (v4.9.2.1) (RRID: SCR_013991) except for heatmaps and volcano plots. The heatmaps and volcano plots are generated using heatmaply (v1.1.0) ^[15] and Glimma (v1.16.0) (RRID: SCR_017389) R packages respectively. R (v.4.0.3) (RRID: SCR_001905) is used to perform all bioinformatics analysis.

Western blotting

Protein extraction was done in previously described method ^[16]. Briefly, cells were harvested and washed with ice cold PBS followed by re-suspending the pelleted cells and in ice-cold RIPA buffer (Thermo Fisher, #89901) supplemented with protease and phosphatase inhibitors (Thermo Fisher, #78446). After incubating for 1 hour on ice suspension were centrifuged at 14,000 rpm for 10 min in a refrigerated benchtop centrifuge (Eppendorf, #5340 R) to prepare the cell free protein extracts. Protein lysates were quantified using a micro-BCA protein assay kit (Pierce, #23235). Protein samples were prepared and run on SDS-PAGE followed by wet-transferring proteins to 0.45 μm Immobilon-FL PVDF membrane (Millipore, #IPFL00010). Membranes were blocked with Pierce Starting Block (PBS) Blocking Buffer (Thermo Fisher) at room temperature for 1 hr and then incubated overnight with primary antibodies (1:1000) at 4⁰C. Incubation with horseradish peroxidase-linked secondary antibody was done in room temperature at a concentration of 1:10000 and the bands were detected using iBright Western Blot Imaging Systems (Thermo Fisher). The list of antibodies provided in supplementary material (Supplementary Table 1).

Annexin V-propidium iodide (PI) assay

Apoptosis was detected by Annexin-V – PI assay according to the manufacturer’s protocol in the FITC annexin V Apoptosis Detection Kit I (BD Biosciences). Briefly, in six-well plates 2–4×10⁵ cells were seeded and treated with or without respective IC50 concentrations of lurbinectedin for each cell line for 24 hrs and 48 hrs. After the treatment, harvested cells were stained with annexin-V and propidium iodide (PI) and analyzed using the Cytek Aurora (Cytek) flow cytometer and with FlowJo software (version 10.6, BD Biosciences).

In vivo studies for de novo SCLC PDX models

For this study, 6-week-old female nude mice weighing ~22–24 grams were obtained from ENVIGO (Boyertown, PA). The mice were injected subcutaneously into the right flanks with 2×10⁶ cells mixed in a 1:1 mixture of phosphate-buffered saline (PBS) and Matrigel (#CB40234, Fisher). At a tumor volume of approximately 100–120 mm3, mice were randomized and treated with either vehicle (5% glucose+0.5%HPMC, IV) or lurbinectedin (0.2 mg/kg, once a week, IV). The treatment schedule continued throughout the experiment till the mice were sacrificed. Tumor volumes were measured using calipers and calculated as width2 x0.5xlength. Tumor volume along with body weights were monitored twice a week. To determine statistical significance among the different treatment groups, ANOVA followed by Student t-test were performed using Graph-Pad Prism software Prism Ver. 9.0. The animal study was approved by the Institutional Animal Care and Use Committee (IACUC). The identifying number of the approved protocol is 13-07-007

In vivo studies for transformed SCLC PDX models

For this study 6-week-old female nude mice were obtained from ENVIGO (Boyertown, PA). The mice were injected subcutaneously into the right flanks with 2×10⁶ cells mixed in a 1:1 mixture of phosphate-buffered saline (PBS) and Matrigel (#CB40234, Fisher). At a tumor volume of approximately 120–1500mm³, mice were randomized and treated with either vehicle (5% glucose+0.5%HPMC, IV) or osimertinib (25 mg/kg, PO, 5 days a week),lurbinectedin (0.2 mg/kg, IV, once a week) or combination of osimertinib and lurbinectedin (osimertinib- 25 mg/kg, PO, 5 days a week +lurbinectedin- 0.2 mg/kg, IV, once a week). The treatment schedule continued throughout the experiment till the sacrifice of the mice. Tumor volumes were measured using calipers and calculated as width2 x 0.5xlength. Tumor volume along with body weights were monitored twice a week. To determine statistical significance among the different treatment groups, ANOVA followed by Student t-test were performed using Graph-Pad Prism software Prism Ver. 9.0 (RRID: SCR_002798). The animal study was approved by the Institutional Animal Care and Use Committee (IACUC). The identifying number of the approved protocol is 13–07-007.

Quantification and statistical analysis

Cell viability and flow cytometry data were expressed as means ± standard deviation (SD) and tumor volume data in in-vivo studies were expressed as means ± standard error (SE). GraphPad Prism Ver. 9.0 software (RRID: SCR_002798) was used to determine statistical significance among the biologically distinct groups/cells and p value less than 0.05 was considered to be statistically significant (ns > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001).

Data Availability Statement

The raw and processed RNA sequencing data have been deposited to GEO under accession number: GSE223372.

Results

SCLC cells are sensitive to lurbinectedin treatment

To investigate the subtype-specific effect of lurbinectedin in vitro, a panel of seventeen human SCLC cell lines, including three PDX-derived cell lines (representing all four molecular subtypes of SCLC) were treated with lurbinectedin (drug concentration ranging from 0.3 nM to 30 nM). After 24 hours of treatment, all SCLC lines showed sensitivity to lurbinectedin at a nanomolar range with half-maximal inhibitory concentrations [IC50] between 1.905 to 30 nM (Fig. 1A). Interestingly, SCLC-P (H211, H526, and CORL-311) and SCLC-N (H82, H524, and H2171) cell lines showed relatively enhanced sensitivity to lurbinectedin treatment; and SCLC-A (H69, H146, and H720) cell lines showed relative resistance to lurbinectedin treatment (Fig. 1A). The cell lines were then treated for 24, 48 and 72 hours and showed a time-dependent sensitivity to lurbinectedin (dose-response curves of all cell lines is depicted in Supplementary Fig. S1). The IC50 range is lower than the peak plasma concentration of lurbinectedin reported in a previous clinical trial ^[7].

Figure 1: SCLC in vitro models are highly sensitive to lurbinectedin treatment.

A. Cell viability IC50 values in 14 human and 3 murine SCLC cell lines in response to 24 hrs treatment indicates high susceptibility of SCLC cells to lurbinectedin. B. Flow cytometry analysis of apoptotic induction showing percentage of apoptotic cell in different SCLC cell lines in response to respective IC50 concentration of lurbinectedin for 24hr and 48 hrs treatment. Grey color: Control, Blue: 24 hrs lurbinectedin treatment, Orange: 48 hrs lurbinectedin treatment. Results shown as mean ± SD. P values were calculated by Student’s t test (*p < 0.05, **p < 0.01, ***p < 0.001) C. Spearman correlation showing genes associated with sensitivity and resistance in response to lurbinectedin treatment comparing the gene signature with previously published gene signature of SCLC cell lines.

Although lurbinectedin inhibited SCLC growth in most SCLC models, a subset of SCLC cell lines demonstrated relatively greater resistance to lurbinectedin treatment. To further investigate the potential SCLC subtype-specific effect of lurbinectedin, the IC50 concentrations of the cell lines in our cohort were compared to the baseline gene expression of the cell lines ^[17]. Interestingly, a statistically significant difference in sensitivity between SCLC-A and SCLC-P subtypes (p= 0.044) was observed with SCLC-P cells being more sensitive to lurbinectedin as compared to the SCLC-A subtype (Fig. S2A). Previous reports have clearly demonstrated that preclinical models belonging to SCLC-P and SCLC-N subtypes had higher expression of MYC ^[3]. MYC expression (though statistically not significant) may predict sensitivity to lurbinectedin (Fig. S2B; p=0.065).

To identify how lurbinectedin decreased viability in SCLC, we next investigated lurbinectedin-mediated apoptosis induction in SCLC. Annexin-V/PI-based flow cytometry was performed in 6 SCLC cell lines including SCLC-P (H211 and H526), SCLC-N (H82 and H446), and SCLC-A (H720 and H69) with or without lurbinectedin treatment for 24 and 48hrs. In agreement with the viability data, the highest apoptosis induction was observed in H526 and H211 (SCLC-P) cells (about 50–55% apoptotic population in 48 hrs post lurbinectedin treatment) (Fig. 1B). The percentage of apoptotic cells ranged between 15–30% in the cell lines of the SCLC-N subtype (Fig. 1B). In agreement with viability data, cell lines of SCLC-A subtype had the lowest apoptotic induction post-treatment ranging from 5–12% (Fig. 1B).

Therefore, SCLC cell lines are sensitive to lurbinectedin treatment with enhanced sensitivity, particularly in the SCLC-P subtype.

Expression of WNT and DNA damage response genes predict sensitivity to lurbinectedin

The genes associated with response and resistance to lurbinectedin are understudied. To identify novel genes that predict response to lurbinectedin, we next correlated the baseline gene expression of the SCLC cell lines ^[17] to the IC50 of lurbinectedin after 24 hours of treatment (Fig. 1C). Genes involved in the Wnt/β-Catenin pathway including WD repeat domain 74 (WDR 74) and RNF43 as well as a DNA damage response (DDR) regulator, FAM117A were top genes associated with lurbinectedin sensitivity. These genes have not been studied in SCLC and the functional role of these novel genes in lurbinectedin response needs to be further investigated in a larger cohort or preclinical models and clinical samples.

Lurbinectedin treatment modulates the expression of neuroendocrine markers and genes involved in tumor progression in SCLC.

Next, transcriptomic analysis of a sensitive (H526; SCLC-P) and a resistant (H69; SCLC-A) SCLC cell lines pre- and post-lurbinectedin treatment to determine treatment-induced changes in genes involved in SCLC tumorigenesis.

More than 70% of SCLC tumors express a high-NE (neuroendocrine) phenotype and expression of NE genes. Interestingly, in both models the predominant transcriptional regulator of the corresponding cell lines, i.e., POU2F3 for H526 and ASCL1 for H69 was significantly suppressed post-lurbinectedin treatment (Fig. 2A and 2B). NEUROD1 has previously been reported to regulate the migration and survival of NE lung carcinoma by regulating NCAM ^[18]. Interestingly, in H69, NEUROD1 and NCAM1 were significantly enriched post-lurbinectedin treatment. NEUROD1, but not NCAM1 was also upregulated in H526 cells. CHGA and SYP were significantly upregulated in H526 (SCLC-P) cell line. Furthermore, expression of non-NE marker YAP1 decreased in H526 cells but increased in H69 (SCLC-A) cells indicating a change in neuroendocrine characteristics of both the cell lines upon lurbinectedin treatment. POU3F2 (BRN2), a transcription factor crucial for cell lineage determination and expression of NE markers including ASCL1, ND1, NCAM1, SYP and CHGA ^[19], was also elevated (Fig. 2A and 2B) post-lurbinectedin treatment. The functional implications of these shifts in gene expression of factors previously implicated in SCLC biology should be investigated in future studies. Western blot analysis of the key transcription factors showed decrease in the expression of ASCL1, NEUROD1 and YAP1 16 hr post-lurbinectedin treatment (Fig. S2C).

Figure 2: Box-plots showing changes in NE and tumor progression markers in pre- and post-lurbinectedin-treated H526 and H69 cells.

A. Box-plots showing relative expression of crucial neuro-endocrine genes of H526 (SCLC-P) cells, pre- and post-lurbinectedin treatment B. Box-plots showing relative expression of crucial neuro-endocrine genes of H69 (SCLC-A) cells, pre- and post-lurbinectedin treatment. Statistical significance (p values) were calculated by Student’s t test. C. Box-plots showing relative expression of crucial tumor progression genes of H526 (SCLC-P) cells, pre- and post-lurbinectedin treatment D. Box-plots showing relative expression of crucial tumor progression genes of H69 (SCLC-A) cells, pre- and post-lurbinectedin treatment. P values are indicated on the top of each box plots and P value <0.05 is considered significant

Next, the expression of multiple genes associated with NE differentiation, tumor progression and therapeutic resistance in SCLC and other cancers were investigated. Interestingly, lurbinectedin treatment enhanced the expression of genes associated with tumor progression like POU class 5 homeobox 1 (POU5F1), insulin-like growth factor binding protein 2 (IGFBP2), RNA Polymerase II, I and III Subunit L (POLR2L) and NANOG (Fig. 2C, 2D) in both cell lines. Collectively, these data demonstrate that lurbinectedin treatment modulates NE genes and genes associated with tumor progression in in-vitro SCLC models.

Pathway analysis highlights the potential role of apoptosis, MYC, and EMT in driving resistance to lurbinectedin treatment in SCLC cell lines

Gene set enrichment analysis (GSEA) pre- vs post-lurbinectedin treatment showed uniquely upregulated pathway in the more sensitive H526 (SCLC-P) cell line (Fig. 3A, C) On the other hand significant enrichment of MYC targets, and EMT pathways; and downregulation of G2-M checkpoint, and mTORC1 pathways were observed post-lurbinectedin treatment in the more resistant H69 (SCLC-A) cells (Fig. 3C, D). Adducts between DNA and lurbinectedin has been previously shown to activate apoptosis-mediated cell death and to inhibit tumor growth by triggering double-strand breaks and S-phase accumulation of cells in different cancer cell lines ^[20]. Both MYC activation ^[21] and EMT ^[22] have been implicated as drivers of tumor proliferation and chemo-resistance. Taken together the involvement of these pathways highlights potential novel mechanisms of lurbinectedin resistance in SCLC.

Figure 3: Lurbinectedin treatment shows SCLC subtype-specific pathway modulation.

A. Hallmark pathway enrichment analysis based on DEGs comparing pre- and post-lurbinectedin treated H526 cells. B. Heat-map highlighting top DEGs of H526 cells comparing pre- and post-lurbinectedin transcription profile. C. Venn diagram comparing common and differentially upregulated and down regulated significant pathways between H526 and H69 cells in response to lurbinectedin treatment. D. Hallmark pathway enrichment analysis based on DEGs comparing pre- and post-lurbinectedin treated H69 cells. E. Heat-map highlighting top DEGs of H69 cells comparing pre- and post-lurbinectedin transcription profile.

Interestingly, oncogenic PI3K/AKT/mTOR and TGF-β pathway in the sensitive H526 SCLC model showed downregulation post-lurbinectedin treatment (Fig. 3A, C). PI-3K/AKT/mTOR signaling pathway is a major promoter of cell growth, survival, and invasion in multiple cancer types, and is also known to be constitutively active in some subsets of SCLC ^[22]. Dysregulated activation of the TGF-β signaling promotes chemo-resistance, EMT and proliferation in several cancer.

Further analyses of top differentially expressed genes (DEGs) highlighted apoptosis signaling (including HAP1, SAT1, ATF3, and KLF10 genes) and immune pathway (including ATF3, JUNB) genes to be up-regulated post-lurbinectedin treatment in the sensitive H526 model (Fig. 3B). In contrast, upregulation of genes involved in regulating EMT and metastasis (FTL,); NOTCH signaling (NRARP); NFkB (PIDD1, JUNB); WNT-β catenin signaling (LGR4) were observed in the more resistant H69 model post-lurbinectedin treatment nominating them as potential markers of resistance (Fig. 3E).

Taken together the data shows that lurbinectedin treatment induces apoptotic signaling pathways and downregulation of oncogenic PI3K/AKT and TGF-beta pathways in sensitive model. On the other hand, an upregulation of EMT, and MYC targets were observed post-lurbinectedin treatment in resistant models which may nominate these pathways as potential mechanisms of resistance to the drug in SCLC. Future validation studies would reveal the individual contribution of these pathways in SCLC.

Lurbinectedin treatment induces DNA damage response in a subtype-specific manner in SCLC.

Previous studies have shown the effect of lurbinectedin on DNA damage response (DDR) in SCLC models. In this study, RNA-seq. analysis showed increased expression of both H2AX and PARP1 upon lurbinectedin treatment (Fig. S3A) which confirms the modulation of the DDR pathway. Western blot analysis of SCLC-P (H526) and SCLC-A (H146) cells at 8 hrs and 16 hrs post-lurbinectedin treatment demonstrated an upregulation of γ-H2AX, a marker for double-stranded DNA damage in both cell lines (Fig. S3B). Significant upregulation of pRPA32, another marker of DNA damage, was observed in H526 cells post-lurbinectedin treatment. Confirming the apoptosis analysis, cleavage of both PARP and caspase3 were observed in H526 and H146 cell lines post-lurbinectedin treatment (Fig. S3B). Interestingly, lurbinedtedin treatment led to an upregulation of phospho-ATM in H526 (SCLC-P subtype) but not in H146 (SCLC-A subtype) cells. Lurbinectedin treatment enhanced pCHK1 in both H526 and H146 cells. Therefore, these results suggest subtype-specific induction of apoptosis and DNA damage response post-lurbinectedin treatment in SCLC in vitro models (Fig. S3B).

Lurbinectedin treatment results in tumor regression in patient-derived xenograft models of SCLC model in a subtype-specific manner

Previous studies have reported the effect of lurbinectedin in vitro, however, anti-tumor effect of lurbinectedin in cancer-relevant PDX models of SCLC is lacking. In vitro effect in cell lines often does not translate to the anti-tumor effects in vivo due to the inherent complexity of in vivo models and the presence of tumor vasculature. Therefore, we next investigated the anti-tumor effect of lurbinectedin in multiple unique PDX models of SCLC representing the three major subtypes. This study included three PDX models which have been previously characterized by genomic, transcriptomic and proteomic assays with correlative clinical data ^[23]. The three PDX models belong to SCLC-A (LX110), SCLC-N (LX33), and SCLC-P (LX1322) subtypes. Subcutaneous tumor-bearing mice from each model were treated with lurbinectedin (0.2 mg/kg, IV, once / week) or vehicle. Lurbinectedin treatment significantly delayed tumor growth in LX110 model (P < 0.0001) (Fig. 4A). In LX110, the tumors in vehicle group reached a maximum tumor volume of 1,484 mm3 at day 46 whereas the tumor in the lurbinectedin-treated group was only 240 mm³ at day 46 indicating an 84% reduction in tumor growth relative to control (Fig. 4A) (Tumor volume summarized in Table S2). The tumors in the lurbinectedin-treated group reached their maximum tumor volume at day 80 and demonstrated a significant extension of mice survival. Whereas lurbinectedin treatment caused minimal anti-tumor effects in LX33 and LX1322 (Fig. 4A) (Tumor volume summarized in Table S2). Though the in-vitro results indicated SCLC-A to be more resistant to lurbinectedin treatment, the PDX in-vivo model indicated the SCLC-A subtype to be more sensitive than SCLC-P or SCLC-N subtype. This discrepancy highlights the limitations of both systems and the necessity of complementary in vitro and in vivo studies to confirm the anti-tumor effect of therapies.

Figure 4: Lurbinectedin results in tumor regression in de-novo SCLC in-vivo models.

A. Tumor growth curve data of LX110, LX1322 and LX33 representing de-novo SCLC in-vivo PDX models of A, P and N subtypes in response to vehicle (5% glucose+0.5%HPMC once/week) or single agent lurbinectedin (0.2 mg/kg once a week through intravenous route) treatment. The data represents the means ± SD (n ≥9), p values were calculated by Student’s t test (ns > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001). The P value for LX110 is P<0.0001. B. Differentially expressed genes of LX110, LX1322 and LX33 in-vivo models of lurbinectedin treated group compared to vehicle treated group of mice considering log2 fold change of 1 and p value of <0.05 to be significant. Red dots showed upregulated DEGs and blue dots shows downregulated DEGs. C. Hallmark pathway enrichment analysis of DEGs of LX110, LX1322 and LX33 de-novo SCLC mice models treated with vehicle and lurbinectedin. [* (asterisk) marked pathways were statistically significant]

Bulk RNA-sequencing of LX110 vehicle vs lurbinectedin-treated tumors showed upregulation of TRIM72, which suppresses tumor progression and modulates cellular energy state by modulating AKT-AMPK-mTORC1 pathway ^[24] (Fig. 4B); and HSPB7, another PI3K/AKT signaling modulating gene. Upregulation of RYR1 was also observed, which is a predictive marker of resistance to etoposide treatment in SCLC ^[25] and modulates WNT and PI3K/AKT/mTOR pathway. WNT16 and ATF3, which is known to be activated upon DNA damage to promote apoptosis and interact with NF-ĸB, were downregulated upon lurbinectedin treatment (Fig. 4B). Interestingly a downregulation of RSC1A1 (Regulator of Solute Carriers 1) and other solute carrier genes SLC2A1, SLC16A3, SLC34A2 and SLC6A17 were also observed. Many solute carrier family members have been previously linked with pro-tumorigenic activity and ferroptosis. The GSEA of the LX110 model indicated significant suppression of MTORC1, EMT, and glycolysis pathways, from the MSigDB Hallmark databases, post-lurbinectedin treatment in the sensitive LX110 model (Fig. 4C).

In LX1322 PDX model, lurbinectedin treatment led to the upregulation of IFITM3 which plays pro-tumorigenic role by promoting EMT and affect WNT/β-Catenin pathway and LY6E which also acts as a tumor promoter by modulating PI3K-AKT pathway. Interestingly, e SFRP2 gene which is a negative regulator of WNT/beta-Catenin signaling; and tumor suppression gene ANGPTL2 (angioarrestin) which promotes apoptosis and inhibits EMT post-lurbinectedin treatment was downregulated (Fig. 4B).

In LX33, representing SCLC-N subtype, Matrix metalloprotease 2 (MMP2) was downregulated, which is essential for metastasis and endo-mesenchymal transition; and SFRP2, a modulator of WNT/β-catenin pathway, was also suppressed post-lurbinectedin treatment (Fig. 4B). Furthermore, REL, an important member of NF-KB signaling, and lung cancer-associated transcript 1 (LUCAT1) was upregulated post-lurbinectedin treatment (Fig. 4B). GSEA showed suppression of the EMT pathway and activation of glycolysis and mTORC1 signaling pathways from the MSigDB Hallmark database (Fig. 4C).

In summary, lurbinectedin treatment caused a significant delay in tumor growth in an SCLC-A PDX model and transcriptomic analysis suggested a role of WNT/β-catenin, AKT-PI3K-mTORC1, and EMT signaling in the subtype-specific anti-tumor effect of lurbinectedin treatment in SCLC models.

Lurbinectedin treatment either as a single agent or in combination with osimertinib results in significant tumor regression in transformed SCLC in-vivo models.

Osimertinib shows initial activity in EGFR-mutant lung cancer, however, all patients develop resistance, often through SCLC transformation. There is a critical unmet need for effective later-line therapies for patients with transformed EGFR-mutant SCLC that addresses their unique biology. We hypothesized that combining EGFR- and SCLC- directed therapies may maximize disease response for this unique patient population. Therefore, to test the effect of lurbinectedin with or without osimertinib in transformed SCLC, three unique and novel PDX models of transformed SCLC: LX1042, LX151 and LX831b were used. After an initial tumor size of 120–150mm³, mice from all three models were treated with- (1) lurbinectedin (0.2 mg/kg, IV, once a week); (2) or osimertinib (25 mg/Kg, PO, 5 days/week); (3) combination of lurbinectedin and osimertinib.

In LX1042, at day 47 after tumor initiation, the control group reached the maximum tumor burden of 1808 mm³ (Fig. 5A) (Tumor volume summarized in Table S3). As expected, single-agent osimertinib had no appreciable anti-tumor effect in this transformed SCLC model and the average tumor volume was 1369 mm³. Interestingly, in the lurbinectedin treatment group on day 47, the tumor volume reached only 859 mm³ showing a ~52% inhibition in tumor growth compared to the control group thus confirming the efficacy of lurbinectedin treatment alone in transformed SCLC (P=0.0026) (Fig. 5A). Significant tumor reduction was observed in the osimertinib+lurbinecetdin combination group. The average tumor volume was only 293 mm³ at day 47 showing more than 80% reduction of tumor burden (P<0.0001). Most encouragingly at day 50, 4 out of 10 mice had complete tumor regression. The complete tumor clearance continued till day 65 (Fig. 5A). The study continued with 4 mice till day 92 when the average tumor volume was only 619 mm³, indicating that lurbinectedin in combination with osimertinib caused significant tumor regression and survival benefit of transformed SCLC PDX model (Fig. 5A).

Figure 5: Lurbinectedin with or without Osimertinib results in tumor regression in transformed SCLC models.

A. Tumor-growth curves of PDX model in nude mice subcutaneously injected with LX1042 of transformed SCLC, B. Tumor-growth curves of PDX model in nude mice subcutaneously injected with LX151 of transformed SCLC, C. Tumor-growth curves of PDX model in nude mice subcutaneously injected with LX831B of transformed SCLC. Mice were treated with vehicle (5% glucose+0.5%HPMC once/week), orally administered osimertinib only (25 mg/kg. 5 days / week), intravenously administered Lurbinectedin only (0.2 mg/kg once / week), and osimertinib and lurbinectedin (25 mg/kg. osimertinib 5 days/week with 0.2 mg/kg lurbinectedin once a week) groups. The data represents the means ± SD (n ≥ 8), p values were calculated by Student’s t test (ns > 0.05, *p < 0.05, **p < 0.01, ***p < 0.001). Statistical significance for LX1042 Cont. vs. lurbinetedine arm is P = 0.0026, Cont. vs. combination arm is P < 0.0001. Statistical significance for LX151 Cont. vs. lurbinetedine arm is P = 0.003, Cont. vs. combination arm is P =0.0002. Statistical significance for LX831b Cont. vs. combination arm is P =0.0046.

In LX151, at day 56, the average tumor volume of the control group was 1934 mm³ and in osimertinib treated group was 1226 mm³, showing no significant tumor regression compared to the control (Fig. 5B) (Tumor volume summarized in Table S3). Interestingly single agent lurbinectedin treatment resulted in an average tumor volume of 108 mm³ at day 56 (Fig. 5B) showing a 95% inhibition of tumor growth (P=0.0003). In the lurbinectedin+osimertinib combination group significant tumor regression with an average tumor volume of only 47 mm³ at day 56 (P=0.0002). Most encouragingly 50% of mice had total tumor regression by day 21 in the lurbinectedin and osimertinib combination group (Fig. 5B).

Finally, for LX831b the vehicle group reached an average tumor volume of 1116.62 mm³ at day 55 (Fig. 5C) (Tumor volume summarized in Table S3). Single-agent osimertinib treatment group reached an average tumor volume of 1531.75 mm³ at day 80 (Fig. 5C). In lurbinectedin-treated group mice reached a tumor volume of 1613.20 mm³ at day 77 (Fig. 5C). Finally, at day 27 in the osimertinib+lurbinectedin the average tumor volume was only 457.13 mm³ (P=0.0046). Three mice in the combination group reached a tumor volume of 1023.23 mm³ at day 107 showing a delay in tumor growth and survival benefit.

Therefore, in all three unique SCLC transformation PDX models used in this study, single-agent lurbinectedin treatment was significantly more effective than osimertinib treatment alone and the combination treatment of lurbinectedin and osimertinib caused significant tumor regression opening much-needed avenues for therapeutic intervention in this very aggressive lung cancer subtype.

Transcriptomic analysis showed the involvement of NOTCH, PI3K-mTOR, NF-κB signalling in lurbinectedin and osimertinib-treated transformed SCLC models.

Next, transcriptomic analysis from available tumors in LX1042 and LX831b transformed-SCLC-PDX models was performed.

In LX1042, combination treatment led to significant upregulation of NOTCH2 (an important member of NOTCH signaling pathway); SFRP2 (regulator of WNT/beta-Catenin signaling); nerve growth factor (NGF) (which promotes tumor invasiveness by activating PI3K/AKT/GSK3β pathway) and PLK2 (gene linked to drug sensitivity by interacting with both NOTCH family of proteins) (Fig. 6A) as compared to the vehicle control. On the other hand, downregulation of HES1 (a NOTCH target gene and which has also been reported to interact with NOTCH-ligands like DLL1); death-associated protein kinase 2 (DAPK2) and SPRY4 (which have been linked to tumor proliferation and apoptosis) along with PHLDA2 which has been known to promote EMT by modulating PI3K/AKT signaling pathway in colorectal cancer were observed (Fig. 6A).

Figure 6. Lurbinectedin and osimertinib treatment modulates NOTCH, nF-κB, PI3K signalling in transformed SCLC in-vivo models.

A. Differentially expressed genes of LX1042 in-vivo model of transformed SCLC in lurbinectedin+osimertinib treated group compared to vehicle treated group considering log2 fold change of 1 and p value of <0.05 to be significant. Red dots showed upregulated DEGs and blue dots shows downregulated DEGs. B. Hallmark pathway enrichment analysis of DEGs of LX1042, transformed SCLC PDX mice model treated with vehicle and lurbinectedin+osimertinib. [* (asterisk) marked pathways were statistically significant]

C. Differentially expressed genes of LX831b in-vivo model of transformed SCLC in lurbinectedin+osimertinib treated group compared to vehicle treated group considering log2 fold change of 1 and p value of <0.05 to be significant. Red dots showed upregulated DEGs and blue dots shows downregulated DEGs. D. Hallmark pathway enrichment analysis of DEGs of LX831b, transformed SCLC PDX mice model treated with vehicle and lurbinectedin+osimertinib.

GSEA in the LX1042 model showed suppression of glycolysis, mTORC1, MYC targets and NOTCH signaling pathways from the MSigDB Hallmark database (Fig. 6B), in the combination treatment as compared to the vehicle, which confirmed the importance of these signaling pathways in SCLC progression.

In LX831b, analysis of top DEGs showed increased expression of JAG1 (a NOTCH ligand) and PLK2 in treated samples compared to untreated control (Fig. 6C). Like LX1042, even in LX831b a downregulation of HES1 and PHLDA2 which promotes EMT by modulating PI3K/AKT signaling pathway in colorectal cancer were observed ^[26]. PKP1 (Plakophilin 1) a tumor suppressor in lung cancer ^[27] and involved in a feedforward loop with MYC in squamous cell lung cancer ^[28] (Fig. 6C) was also downregulated upon combination treatment. Interestingly, GSEA of MSigDB Hallmark database, indicated activation of G2M checkpoint (Fig. 6D) pathway.

Together, these results suggest the involvement of MYC and NOTCH signaling in the appreciable anti-tumor response of lurbinectedin+osimertinib in transformed SCLC models. The exact functional role of these pathways need to be investigated in future investigations.

Discussion

Patients with extensive-stage SCLC typically have robust responses to first-line platinum-based chemotherapy, but most will experience chemo-resistant relapse within the first year. Advances in therapeutic targeting of SCLC have been extremely limited and have resulted in only modest improvement to the dismal prognosis of patients. Combination of atezolizumab and chemotherapy in the first line resulted in a modest increase in PFS of 1 month and OS of 2 months in extensive-stage small-cell lung cancer when compared to chemotherapy alone ^[29]. Similarly, in the CASPIAN study, the durvalumab plus platinum-etoposide group led to only a modest improvement in OS (13·0 months versus 10·3 months) to the platinum-etoposide group ^[30]. The complex genomic landscape, heterogeneity of these tumors, early metastasis of the disease, and almost inevitable drug resistance have made it difficult to identify effective and durable targets for this disease. Lurbinectedin is FDA-approved as a second-line treatment for metastatic SCLC. However, the effect of lurbinectedin in SCLC subtype-specific gene expression changes or the efficacy of lurbinectedin in transformed SCLC has not been investigated. Our current study explored the preclinical efficacy of lurbinectedin in a large and diverse panel of in vitro and in vivo models of de novo SCLC. We further investigated the lurbinectedin-mediated gene expression changes in SCLC models. Finally, the current study is the first to show the effect of lurbinectedin in transformed SCLC preclinical models with or without osimertinib treatment.

SCLC is characterized by a ubiquitous loss-of-function mutation in TP53 and RB1, and amplification/overexpression of MYC family members in a subset of SCLC preclinical models and clinical samples ^[31]. Beyond genomic alterations, SCLC is usually divided into four major subtypes mainly based on the expression of four transcription factors, ASCL1. NEURO-D1, POU2F3 and YAP1. These subtypes have distinct biological characteristics and therapeutic vulnerabilities. A trend towards subtype-specific sensitivity to lurbinectedin was found, with the SCLC-P subtype being the most sensitive, followed by the SCLC-N subtype and SCLC-A subtype showing relatively less sensitivity in the cell line panel tested in this study.

Interestingly, MYC expression was correlated lurbinectedin sensitivity ^[3]. The correlation was not statistically significant which could be due to the limited sample size. MYC overexpression has been linked to increased aggressiveness in SCLC and is a predictive biomarker for DNA damage response inhibitors like CHK1 and ATR ^[32,33]. This result suggests that MYC expression could be a potential predictive biomarker for lurbinectedin response, which needs to be further validated in clinical datasets.

Additionally, genes in the NF-KB signaling pathway (like PLAA, SRGN, and TNFAIP8) were the top predictive biomarkers of resistance to lurbinectedin treatment. On the other hand, genes involved in DDR and WNT/β-catenin pathway predicted sensitivity to lurbinectedin. Aberrant NF-KB and Wnt/β-Catenin signaling has been shown to regulate cell proliferation, cell survival, and immune modulation in multiple cancer types. These pathways need to be further validated in clinical datasets.

There is no information about lurbinectedin-mediated gene expression changes in different SCLC subtypes. Transcriptomic and proteomic analysis of models representing the most sensitive (SCLC-P) and most resistant (SCLC-A) subtypes, pre- and post-lurbinectedin treatment, showed increased expression of DNA damage markers in SCLC models post-lurbinectedin treatment.

Interestingly, activation of apoptosis pathway and suppression of TGFβ and PI3K-AKT-mTOR signaling pathways were observed exclusively in the sensitive SCLC-P model. On the other hand, in the relatively resistant SCLC-A model, lurbinectedin treatment led to an activation of the EMT pathway which has a known role in tumor progression and proliferation. Furthermore, in the SCLC-A model, we found activation of a negative regulator of the NOTCH pathway (NRARP) along with genes involved in NF-kB activation and regulation of Wnt/β-catenin pathway. Notch signaling has known to play a tumor suppressive role in SCLC and to counteract pro-tumorigenic pathways like WNT/β-Catenin and NF-kB in various cancers. Therefore, this study shows modulation of the apoptosis, PI3K-AKT-mTOR and TGFβ pathway to be a notable contributor towards lurbinectedin sensitivity; and EMT pathway enrichment and NOTCH signaling modulation to be a contributor towards lurbinectedin resistance in SCLC models. Further studies are required to delineate the involvement of these pathways in acquired resistant models.

Lurbinectedin treatment significantly delayed tumor growth in LX110 (SCLC-A) as compared to LX1322 (SCLC-P) or LX33 (SCLC-N) models. The discrepancy of the subtype-specific effect of lurbinectedin in in vitro and in vivo models can be accounted by- 1) inherent differences between cell lines and complex PDX models which is acquired during cell culture and repeated passaging; 2) distinct mutational profiles of the models; 3) heterogeneity and plasticity of SCLC patient tumors which is not fully represented in cell lines.

GSEA analysis of pre-/post-treatment tumors indicated significant suppression of glycolytic, mTORC1 and EMT pathways in the sensitive LX110 model. Further analysis of top DEGs revealed upregulation of tumor suppressive genes of PI3K-AKT-mTOR and WNT- β-Catenin pathways in LX110 and downregulation of WNT/ β-Catenin pathway antagonist SFRP2 gene in the less responsive models (LX33 and LX1322. Interestingly TRIM72 and HSPB7 were exclusively upregulated in LX110 when compared to the other less responsive PDX models of LX33 and LX1322, highlighting their role in lurbinectedin response. Taken together the in-vivo denovo SCLC PDX model data suggested the crucial role of WNT/ β-Catenin, PI3K-AKT-mTOR and EMT pathway suppression in inducing tumor regression which also corroborated with out in-vitro study findings.

A subset of EGFR-mutant LUAD transforms to SCLC as a mechanism of therapeutic resistance. The FLAURA study indicates SCLC transformation as a mechanism of resistance to osimertinib in patients with T790M-positive NSCLC ^[34]. Patient outcomes following transformation to SCLC are extremely poor. Clinical outcomes of patients after SCLC transformation treated with SCLC-directed therapies are similar to de novo SCLC, with high but transient response to platinum-based chemotherapy ^[14]. As EGFR inhibitors have increased in potency, lineage plasticity is seen more frequently, as a mechanism of adaption that frees the cancer cell from EGFR signaling dependence ^[35]. There is limited data on effective therapies for transformed SCLC with EGFR mutations in the later-line setting. In a recent study with forty seven transformed SCLC patients with EGFR mutations a combination of chemotherapy ± bevacizumab and PD-L1 inhibitor is found to be beneficial and potentially a safe option for SCLC-transformed patients harboring EGFR L858R mutation ^[36]. Beyond RB1 and TP53 loss, very little is known about the biomarker landscape of transformed SCLC and their therapeutic vulnerability thus making it difficult to treat the subset of patient with transformed SCLC which seems to be more aggressive in nature. We are the first to investigate the effect of lurbinectedin as a single agent or in combination with EGFR inhibitor osimertinib in a transformed SCLC PDX model. In all three models single agent lubinectedin treatment showed significantly more anti-tumor response than osimertinib treatment alone. Furthermore, combining lurbinectedin with osimertinib led to a significant delay in tumor growth, and we did not observe any measurable tumor volume in an appreciable subset of mice in two out of three models.

Gene expression analysis showed upregulation of tumor suppressive genes of WNT/ β-Catenin and NOTCH signaling in transformed SCLC PDX models. Moreover, genes which are either targets or promoters of tumor promoting pathways like NOTCH, NF-kB or PI3K/AKT were suppressed post lurbinectedin + osimertinib treatment. It is also interesting to note that upon combination treatment in both PDX models of transformed SCLC, PLK2 gene was upregulated, and we observed downregulation of HES1 and PHLDA2 genes opening up scope for future studies on these genes as probable biomarkers in this subset of patients.

Several reports indicate the complex molecular cross talk of NF-kB, Wnt/β-catenin, PI3K/AKT, and NOTCH signaling which plays crucial role in tumorigenesis. β-catenin physically interact with and inhibit NF-kB in breast and colon cancer by forming a complex with RelA and p50 ^[37]. Additionally, NOTCH1 signaling has been reported to activate NF-kB in breast cancer in an AKT-dependent manner ^[38]. It is further interesting to note that in NSCLC, β-catenin signaling has been reported to be activated in a NOTCH3 dependent manner as a result of EGFR inhibition facilitating survival of a subset of cancer cells ^[39]. Additionally, PI3K-AKT-mTOR pathway has been reported to confer chemo-resistance and phenotypic transition in SCLC ^[40]. This indicates that there is an intricate crosstalk among these pathways which plays a crucial role in tumorigenesis in several cancer type. In this study significant modulation of Wnt/ β-Catenin, PI3K/AKT, NOTCH, NF-kB pathway genes was observed from the DEG and pathway analysis. Future studies combining inhibitors of these pathways (i.e., gedatolisib for PI3K, Rova-T for NOTCH pathway, sulforaphane for Wnt pathway etc.) that are in the clinical trial with lurbinectedin may open up therapeutic avenues to increase the efficacy of lurbinectedin in less responsive SCLC patients.

In conclusion, our data highlights the role of MYC as a predictive biomarker of lurbinectedin response. Tumor-promoting pathways like PI3K-AKT-mTOR, and EMT may play a role in lurbinectedin resistance in de novo SCLC models. This study also provides the first evidence that lurbinectedin, either as a single agent or in combination with osimertinib, causes significant tumor regression in transformed SCLC models. NOTCH plays a crucial role in osimertinib+lurbinectedin- mediated anti-tumor effect.

The clinical implications of these findings are substantial, as future clinical trials of lurbinectedin, in combination with the inhibitor targeting these pathways should be investigated to overcome resistance to lurbinectedin. Moreover, we establish lurbinectedin as an effective therapeutic target in transformed SCLC, a very aggressive and recalcitrant cancer type. Since lurbinectedin is already FDA approved, the inclusion of lurbinectedin in the therapeutic regimen for EGFR-mutant LUAD cases that develops resistance to standard-of-care EGFR-targeted therapies can be readily implemented.

Translational Relevance.

Therapeutic targets for SCLC is very limited leading to a dismal patient prognosis. Moreover, there are no therapeutic options for transformed SCLCs that have emerged as a mechanism of acquired resistance to TKIs in oncogene-driven LUADs, leading to worse prognosis and an aggressive disease progression. Lurbinectedin, conditionally approved as a second-line treatment for metastatic SCLC, drives clinical responses in about 35% of patients. Currently there are no biomarkers and mechanistic insight of lurbinectedin in SCLC. Here we provide mechanistic insight into pathways modulated by lurbinectedin in de novo SCLC. Moreover, this study provides the first evidence of that lurbinectedin alone or in combination with osimertinib causes appreciable tumor regression in transformed SCLC PDX models compared to osimertinib alone. Our study strongly supports the inclusion of lurbinectedin in the therapeutic regimen for transformed SCLC, which can be readily implemented in the clinic.