Small Cell Lung Cancer Subtypes Research Articles

The Evolving Scenario of ES-SCLC Management: From Biology to New Cancer Therapeutics

Small cell lung cancer (SCLC) is an aggressive neuroendocrine carcinoma accounting for 15% of lung cancers with dismal survival outcomes. Minimal changes in therapy and prognosis have occurred in SCLC for the past four decades. Recent progress in the treatment of extensive-stage disease (ES-SCLC) has been marked by incorporating immune checkpoint inhibitors (ICIs) into platinum-based chemotherapy, leading to modest improvements. Moreover, few second-line-and-beyond treatment options are currently available. The main limitation for the molecular study of SCLC has been the scarcity of samples, because only very early diseases are treated with surgery and biopsies are not performed when the disease progresses. Despite all these difficulties, in recent years we have come to understand that SCLC is not a homogeneous disease. At the molecular level, in addition to the universal loss of retinoblastoma (RB) and TP53 genes, a recent large molecular study has identified other mutations that could serve as targets for therapy development or patient selection. In recent years, there has also been the identification of new genetic subtypes which have shown us how intertumor heterogeneity exists. Moreover, SCLC can also develop intratumoral heterogeneity linked mainly to the concept of cellular plasticity, mostly due to the development of resistance to therapies. The aim of this review is to quickly present the current standard of care of ES-SCLC, to focus on the molecular landscapes and subtypes of SCLC, subsequently present the most promising therapeutic strategies under investigation, and finally recap the future directions of ongoing clinical trials for this aggressive disease which still remains a challenge.

Applied models and molecular characteristics of small cell lung cancer.

Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.

Molecular pathology of small cell lung cancer: Overview from studies on neuroendocrine differentiation regulated by ASCL1 and Notch signaling.

Pulmonary neuroendocrine (NE) cells are rare airway epithelial cells. The balance between Achaete-scute complex homolog 1 (ASCL1) and hairy and enhancer of split 1, one of the target molecules of the Notch signaling pathway, is crucial for NE differentiation. Small cell lung cancer (SCLC) is a highly aggressive lung tumor, characterized by rapid cell proliferation, a high metastatic potential, and the acquisition of resistance to treatment. The subtypes of SCLC are defined by the expression status of NE cell-lineage transcription factors, such as ASCL1, which roles are supported by SRY-box 2, insulinoma-associated protein 1, NK2 homeobox 1, and wingless-related integration site signaling. This network reinforces NE differentiation and may induce the characteristic morphology and chemosensitivity of SCLC. Notch signaling mediates cell-fate decisions, resulting in an NE to non-NE fate switch. The suppression of NE differentiation may change the histological type of SCLC to a non-SCLC morphology. In SCLC with NE differentiation, Notch signaling is typically inactive and genetically or epigenetically regulated. However, Notch signaling may be activated after chemotherapy, and, in concert with Yes-associated protein signaling and RE1-silencing transcription factor, suppresses NE differentiation, producing intratumor heterogeneity and chemoresistance. Accumulated information on the molecular mechanisms of SCLC will contribute to further advances in the control of this recalcitrant cancer.

Prognostic Implications of Small Cell Lung Cancer Transcriptional Subtyping for CNS Metastases.

Small cell lung cancer (SCLC) often metastasizes to the brain and has poor prognosis. SCLC subtypes distinguished by expressing transcriptional factors ASCL1 or NEUROD1 have been identified. This study investigates the impact of transcription factor-defined SCLC subtype on incidence and outcomes of brain metastases (BMs). Patients with SCLC with ASCL1 (A) and NEUROD1 (N) immunohistochemical expression status were identified and classified: (1) A+/N-, (2) A+/N+, (3) A-/N+, and (4) A-/N-. Cumulative incidence competing risk analyses were used to assess incidence of CNS progression. Cox proportional hazards models were used for multivariable analyses of overall survival (OS) and CNS progression-free survival (CNS-PFS). Of 164 patients, most were either A+/N- or A+/N+ (n = 62, n = 63, respectively). BMs were present at diagnosis in 24 patients (15%). Among them, the 12-month cumulative incidence of subsequent CNS progression was numerically highest for A+/N- (50% [95% CI, 10.5 to 74.7]; P = .47). Among those BM-free at diagnosis, the 12-month cumulative incidence of CNS progression was numerically the highest for A+/N- (16% [95% CI, 7.5 to 27.9]) and A-/N+ (9.1% [95% CI, 0.0 to 34.8]; P = .20). Both subtypes, A+/N- and A-/N+, had worse OS compared with A+/N+ (A+/N-: hazard ratio [HR], 1.62 [95% CI, 1.01 to 2.51]; P < .05; A-/N+: HR, 3.02 [95% CI, 1.35 to 6.76]; P = .007). Excellent response rates (28, 65% CR/PR) across subtypes were seen in patients who had CNS-directed radiotherapy versus systemic therapy alone (9, 36% CR/PR). To our knowledge, this report is the first to investigate CNS-specific outcomes based on transcription factor subtypes in patients with SCLC. BM-free patients at diagnosis with A+/N- or A-/N+ subtypes had worse outcomes compared with those with transcriptional factor coexpression. Further investigation into the mechanisms and implications of SCLC subtyping on CNS-specific outcomes is warranted to ultimately guide personalized care.

Abstract 1722: Subtype classification of small cell lung cancer (SCLC) tissues using the EpiCheck methylation sensitive restriction-based PCR platform

Abstract Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with poor survival rates. Despite molecular and clinical heterogeneity, SCLC is currently treated as a single entity without guidance of predictive biomarkers leading to expectedly poor outcomes. A recent study suggested classifying SCLC into four subtypes (“A”, “N”, “P” and “I”), each with unique molecular features and therapeutic vulnerabilities. While initially this classification was based on gene expression (RNA-seq) data, subsequent data suggest it can be recapitulated using reduced-representation bisulfite sequencing (RRBS) methylation profile. While the classification system accurately predicts responses to therapies, including immunotherapies, in retrospective analysis, both tissue-based RNAseq and RRBS are cumbersome, time-consuming and impractical for prospective treatment assignment in an aggressive malignancy. In this pilot study, we developed a methylation-based PCR assay for classification of SCLC subtypes based on the EpiCheck platform, which combines methylation-sensitive restriction endonuclease (MSRE) digestion with qPCR amplification to detect differential methylation at the DNA level. We developed a 13-marker assay and successfully classified, in a blinded study, 96.55% of FFPE tissue samples originating from SCLC patient of A, N and P subtypes. First, a bioinformatic analysis identified 41 candidate biomarkers that are differentially methylated between pairs of SCLC subtypes (A-N, A-P, and N-P) using RRBS data from 56 RNA-seq classified SCLC tumor samples (34 “A”, 19 “N”, 3 “P”). Development of primers and probes for these markers was followed by a biochemical selection process, identifying 13 markers that displayed optimal performance. A PCR EpiCheck assay, employing these 13 markers, was applied to a blinded set of 29 DNA samples from SCLC FFPE tumor tissues (21 “A”, 6 “N”, 2 “P”). Each sample received two ranks based on methylation levels of 5 A-N and 9 P-AN markers and was classified using determined thresholds for each rank. Finally, when comparing PCR-based and RNA-seq-based classifications, the 13-marker PCR assay classified 28/29 (96.55%) of the samples concordantly, misclassifying one "P" sample as "A". This pilot demonstrates the potential of a simple PCR EpiCheck-based assay to accurately differentiate between SCLC subtypes. For complete subtype classification, “I” markers need to be added to the panel, and the assay should be further validated using a larger cohort, particularly for the “P” subtype. Early detection and classification are critical for timely personalized therapy, and such an assay, performed on cfDNA samples, could potentially be used to shorten the time between a patient diagnosis and tailored treatment initiation or clinical study inclusion from a month in best case scenarios to a few days. Citation Format: Orna Savin, Dvir Netanely, Simon Heeke, Carl Michael Gay, Marcos Roberto Estecio, Shacade Danan, Sarah Zaouch, Aharona Shuali, Mathias Ehrich, Lauren Averett Byers, John Victor Heymach, Adam Wasserstrom, Danny Frumkin. Subtype classification of small cell lung cancer (SCLC) tissues using the EpiCheck methylation sensitive restriction-based PCR platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1722.

Abstract 606: The PLK1 inhibitor, onvansertib, synergizes with paclitaxel in small cell lung cancer

Abstract Background: Small cell lung cancer (SCLC) is an aggressive neuroendocrine tumor with rapid disease progression and poor patient survival. Therapeutic options for SCLC remain a challenge due to limited understanding of both the biology of the disease and the major determinants of treatment response. Key transcription factors associated with unique biological phenotypes of SCLC include ASCL1, NEUROD1, YAP1, and POU2F3. Previously, we demonstrated that onvansertib, a highly specific inhibitor of the PLK1 Ser/Thr kinase, was effective in SCLC preclinical models, leading to its ongoing clinical development for relapsed/refractory SCLC patients (NCT05450965). Here we further explored potential strategies to enhance onvansertib activity by assessing its in vitro and in vivo activity in combination treatments. Methods: Human SCLC cell lines were treated for 72 hr with onvansertib in combination with paclitaxel, lurbinectedin or the ATR inhibitors BAY1895344 and AZD6738. Effect on cell proliferation was analyzed by WST1 and CellTiterGlo assays. In vivo activity of onvansertib in combination with paclitaxel was tested in 3 SCLC patient-derived xenograft (PDX) models either cisplatin-sensitive (TKO5- ASCL1 subtype) or cisplatin-resistant (TKO2-ASCL1 subtype, TKO8-NEUROD1 subtype). Tumor-bearing nude mice were treated with vehicle, onvansertib (50 mg/kg, oral, 4 times/week), paclitaxel (15 mg/kg, IP, once a week) or the combination for 5 weeks. Mice were followed for tumor growth and survival (defined as time to reach tumor volume greater than 2000 mm3). Results: The combination of onvansertib and paclitaxel inhibited cell proliferation synergistically in cell lines from 3 SCLC subtypes (ASCL1, NEUROD1, and YAP1), while the combinations with lurbinectedin or ATR inhibitors were not synergistic. We further examined the combination of onvansertib and paclitaxel in SCLC PDXs. The combination exhibited potent anti-tumor activity, resulting in significantly greater tumor growth inhibition and increase in survival compared to the monotherapies in all 3 PDXs. The combination was well tolerated with no observed body weight loss. While onvansertib and paclitaxel had negligible single agent activity in cisplatin-resistant TK02 PDX and TKO8 PDX models, the combination induced durable complete responses in 25% and 100% of treated mice respectively. Conclusion: The PLK1 inhibitor onvansertib in combination with paclitaxel showed synergy in multiple SCLC cell lines in vitro and potent anti-tumor activity in cisplatin-sensitive and -resistant SCLC PDX models in vivo. Tumor tissue analysis is underway to detail the mechanisms of this interaction. Citation Format: John C. Schmitz, Guojing Zhang, Abbe Pannucci, Tod Smeal, Chu-Chiao Wu, Maya Ridinger, Taofeek K. Owonikoko. The PLK1 inhibitor, onvansertib, synergizes with paclitaxel in small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 606.

Abstract 6799: The impact of targeting TRAF2 and NCK-interacting protein kinase on anti-tumor effect and tumor immune environment in cMYC-high small cell lung cancer

Abstract Background: Small cell lung cancer (SCLC) is a highly lethal malignancy with rapidly acquired chemotherapy resistance. While the inflamed SCLC subtype is associated with a significantly improved response to immunotherapy, the non-inflamed SCLC subtypes, encompassing most SCLC patients, experience only modest survival gains with chemo-immunotherapy. Wnt signaling pathway activation is associated with resistance to chemotherapy and an immune checkpoint inhibitor in several tumors. TRAF2 and NCK-interacting protein kinase (TNIK), which interacts with downstream effectors, TCF4/β-catenin transcriptional complex, is an essential activator of Wnt target genes. TNIK is highly expressed in several cancers, but the efficacy of TNIK inhibition in SCLC has not previously been researched. We previously demonstrated that single agent TNIK inhibitors are effective in a subset of SCLC. Here, we hypothesize that targeting TNIK will show an anti-tumor effect based on specific biomarkers and also modify the tumor immune environment in SCLC. Methods: We evaluated susceptibility to a small molecule TNIK inhibitor, NCB-0846, in 29 human-derived SCLC cell lines using 96-hour proliferation assays. To investigate efficacy biomarkers, we correlated NCB-0846 IC50 values with proteomic expression (profiled using reverse phase protein array). cMYC and FOXK1 expression was reduced by siRNA. Chemokine concentrations were determined by ELISA. Results: SCLC cell lines with high cMYC levels, were more sensitive to the TNIK inhibitor, NCB-0846 (F.C.=-2.07, p=0.01), while SCLC cell lines with high expression of TTF-1 were more resistant (F.C.=2.48, p&amp;lt;0.01). Knockdown of cMYC conferred resistance to NCB-0846 in cMYC-high cells, while NCB-0846 treatment resulted in decreased cMYC expression in a concentration-dependent manner. Additionally, NCB-0846 treatment decreased the immunosuppressive chemokine CCL2 levels in the supernatant of human-derived SCLC cell lines and GEMM-derived cell lines. The expression of FOXK1, a transcription factor of CCL2, was also reduced in cell lines treated with NCB-0846. Conclusions: These findings show that TNIK inhibition is more effective in cMYC-high SCLC, acting through downregulating cMYC levels. TNIK inhibition also decreases the production of CCL2, an immunosuppressive chemokine implicated in resistance to anti-PD-L1 immunotherapy. Together, these findings highlight the promising potential of TNIK inhibitors in cMYC-high SCLC. Additionally, suppressing CCL2 by TNIK inhibition supports the rationale for combining the TNIK inhibitor and an anti-PD-L1 antibody in the non-inflamed SCLC subtypes. Citation Format: Azusa Tanimoto, Kavya Ramkumar, Allison Stewart, Bingnan Zhang, Robert Cardnell, Shen Li, Qi Wang, Jing Wang, Carl Gay, Lauren Averett Byers. The impact of targeting TRAF2 and NCK-interacting protein kinase on anti-tumor effect and tumor immune environment in cMYC-high small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6799.

Abstract 3842: Neuroendocrine differentiation and treatment of human SCLC: NRF2 has a role

Abstract SCLC is a lethal form of lung cancer and highly metastatic disease with limited therapeutic options. Four main neuro and non-neuroendocrine SCLC molecular subtypes have been identified which further complicate the efforts of finding targeted therapies. NRF2 is a transcription factor that is known to protect cells from oxidative damage by regulating more than 500 cytoprotective genes. NRF2 is frequently mutated in non-small cell lung cancer (NSCLC), however, whether alterations occur in small cell lung cancer (SCLC) is not clear due to limited sequencing data. Recently, our group has discovered a previously unrecognized role of NRF2 signaling pathway in the development of SCLC using a novel genetically engineered mouse model (GEMM). In this study, we have investigated the role of NRF2 in the progression and regression of human SCLC. Human SCLC cell lines were generated with NRF2E79Q/+ mutation (one of the most common mutations found in human tumors) to allow the constitutive activation of NRF2 in these cells. Results from hSCLC cell lines showed that NRF2 activation in NRF2-negative SCLCs can significantly inhibit their growth. Further, human SCLC gene expression data showed reduced levels of a NRF2 signature as hSCLC neuroendocrine SCLC transforms to non-neuroendocrine subtypes. As an anti-inflammatory pathway, NRF2 is known to inhibit immune cell gene signature. Our in vivo and invitro studies showed that NRF2 inhibits immune cell infiltration in SCLC; and increases PDL1 protein expression. Currently, we are investigating the effect of NRF2 activation in hSCLC growth, neuroendocrine differentiation and immune gene activation in vitro and in vivo. We are also using immune checkpoint inhibitors to determine the best therapeutic options for each SCLC subtype. Citation Format: Samera Hamad, Hansa Joshi, Yahui Li, Helen Toma, Nasrine Bendjilali, Stuart Jefferys, David Corcoran, Weam Elbezanti, Ben Major, Weissman Bernard, Francis Spitz. Neuroendocrine differentiation and treatment of human SCLC: NRF2 has a role [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3842.

Abstract 6392: Activity of HER2-and TROP2- antibody drug conjugates (ADCs) in small cell lung cancer (SCLC) models with SLFN11 as a predictive biomarker

Abstract Background: Small-cell lung cancer (SCLC) is a highly aggressive malignancy with its few treatment options devoid of biomarker selection, and a 5-year survival rate of less than 7%. Our group previously established four transcriptionally defined subtypes of SCLC, each with distinct cell surface targets (Gay et al, Cancer Cell 2021). Further, we identified SLFN11 (a putative DNA/RNA helicase) as a candidate biomarker of sensitivity to DNA-damaging agents, including topoisomerase inhibitors. Human epidermal growth factor receptor 2 (HER2/ERBB2) expression has been previously described in a subset of SCLCs and has been linked to poor prognosis. HER2 antibody-drug conjugates (ADCs) like trastuzumab deruxtecan (T-DXd) (where the payload is a topoisomerase I inhibitor) have received FDA approval for various solid tumors, highlighting their therapeutic potential. Similarly, TROP2 (TACSTD2) ADC sacituzumab govitecan has shown promising clinical efficacy in a SCLC (TROPiCS-03 basket trial). However, it is unclear what the predictive biomarkers are to these ADCs in SCLC. Methods: Expression of ERBB2 and TACSTD2 mRNA was analyzed using publicly available patient datasets. We also characterized surface expression of HER2 and TROP2 by flow cytometry in SCLC cell lines at baseline and after cisplatin/etoposide treatment. We then assessed the cytotoxicity of T-Dxd and sacituzumab govitecan in a panel of SCLC cell lines representative of each SCLC subtype, as well as SLFN11 status. Results: Analyses of HER2/ERBB2 and TROP2/TACSTD2 in SCLC cell lines and patient datasets showed a range of ERBB2 and TACSTD2 expression with enrichment in the non-neuroendocrine subtypes (SCLC-P and SCLC- I subtypes). We further validated HER2 and TROP2 surface levels by flow cytometry in a subset of SCLC cell lines. Intriguingly, we observed that surface expression of both HER2 and TROP2 increase after frontline chemotherapy cisplatin/etoposide treatment. As expected, T-Dxd and sacituzumab govitecan exhibit cytotoxicity in a subset of SCLC cell lines. We found a strong correlation between the in vitro cytotoxicity (IC50) of sacituzumab govitecan with SLFN11 (rho= 0.74, p=0.015). Importantly, SLFN11 is bimodally distributed in SCLC and we found ERBB2 and TACSTD2 to be enriched in the SLFN11-high group of SCLC patients. We also found ERBB2 and TACSTD2 to be correlated with each other (rho = 0.53, p &amp;lt;0.001). Conclusion: In this study, we demonstrate that HER2/ERBB2 and TROP2/TACSTD2 are enriched in a subset of SCLC. FDA-approved ADCs, T-DXd and sacituzumab govitecan each have preclinical activity in SCLC with SLFN11 as a predictive biomarker of payload cytotoxicity. We also found HER2 and TROP2 target levels increase after frontline chemotherapy (cisplatin/etoposide) in SCLC, which suggest their efficacy may be enhanced in relapsed SCLC where treatment options are extremely limited. Citation Format: Bingnan Zhang, Ali Ibrahim, C.Allison Stewart, Lixia Diao, Qi Wang, Li Shen, Yuann xi, Alejandra Serrano, Luisa M. Solis, Wei-Lien Wang, Kavya Ramkumar, Robert J. Cardnell, Runsheng Wang, Alberto Duarte, Jing Wang, Lauren A. Byers, Carl Gay. Activity of HER2-and TROP2- antibody drug conjugates (ADCs) in small cell lung cancer (SCLC) models with SLFN11 as a predictive biomarker [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6392.

Abstract 6602: Targeting the SWI/SNF complex in POU2F-POU2AF transcription factor-driven malignancies

Abstract Background: Small cell lung cancer (SCLC) is a rapidly progressing subtype of lung cancer with a high growth rate and early metastasis propensity, often resulting in a more advanced disease stage at diagnosis. A recent transcriptome analysis of human SCLC tumors revealed that SCLC could be characterized by the expression pattern of certain transcription factors (TFs), including ASCL1 (achaete-scute family bHLH transcription factor 1) and POU2F3 (POU domain class 2 transcription factor 3), exemplifying SCLC as a TF-driven malignancy. ASCL1-driven SCLC (SCLC-A) manifests a neuroendocrine phenotype, while POU2F3-driven SCLC (SCLC-P) is characterized as a tuft-cell-like variant. Recent studies revealed that POU domain class 2 transcription factors uniquely rely on coactivators to achieve their lineage-defining functions in the tuft cell and B cell lineages. In tuft-cell-like SCLC cells, the coactivators of POU2F3 (POU2AF2 and POU2AF3) endow POU2F3 with a critical transactivation domain by forming a master regulator complex, which supports enhancer-mediated cancer-promoting gene activation in SCLC-P cells. This indicates a potential therapeutic vulnerability of tuft-cell-like SCLC whereby strategies aimed at blocking POU2F3-POU2AF2/3 function may lead to clinical benefit. Methods: We conducted a domain-targeted CRISPR screen to identify druggable targets for SCLC-P, followed by pharmacological validation in preclinical SCLC models. Multi-omics techniques, including ATAC-seq, ChIP-seq, RNA-seq, and RIME, were employed to elucidate the SWI/SNF complex's regulatory influence on the POU2F-POU2AF axis. Results: Here we identified that the POU2F3 molecular subtype of SCLC (SCLC-P) exhibits an exquisite dependence on the activity of the SWI/SNF epigenetic complex. SCLC-P cell lines were sensitive to low nanomolar levels of a SWI/SNF ATPase degrader when compared to other molecular subtypes of SCLC. Co-factors of POU2F were found to interact with components of the SWI/SNF complex. The POU2F3 transcription factor complex is evicted from chromatin upon SWI/SNF ATPase degradation. A novel, orally bioavailable SWI/SNF ATPase PROTAC degrader demonstrated preferential efficacy in SCLC-P relative to the SCLC-A subtype. The SWI/SNF ATPase PROTAC degrader did not alter normal tuft cell numbers in lung or colon, nor did it exhibit toxicity in mice. B cell malignancies which displayed a dependency on the POU2F co-factor, POU2AF1, were also remarkably sensitive to SWI/SNF ATPase degradation. In a POU2AF1-dependent, disseminated murine model of multiple myeloma, AU-24118 had an enhanced survival benefit as compared to pomalidomide, an approved treatment for multiple myeloma. Conclusions: Taken together, our studies suggest that POU2F-POU2AF driven malignancies have an intrinsic dependence on the SWI/SNF complex representing a striking therapeutic vulnerability. Citation Format: Lanbo Xiao, Tongchen He, Olaf Klingbeil, Young Eleanor, Xiaoli Wu, Yuanyuan Qiao, Abhijit Parolia, Sanjana Eyunni, Rahul Mannan, Somnath Mahapatra, NamHoon Kim, Heng Zheng, Fengyun Su, Xuhong Cao, Susanta Samajdar, Murali Ramachandra, Christopher R. Vakoc, Arul M. Chinnaiyan. Targeting the SWI/SNF complex in POU2F-POU2AF transcription factor-driven malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6602.

Comprehensive analysis of transcription factor-based molecular subtypes and their correlation to clinical outcomes in small-cell lung cancer

Recent studies have reported the predictive and prognostic value of novel transcriptional factor-based molecular subtypes in small-cell lung cancer (SCLC). We conducted an in-depth analysis pairing multi-omics data with immunohistochemistry (IHC) to elucidate the underlying characteristics associated with differences in clinical outcomes between subtypes. IHC (n=252), target exome sequencing (n=422), and whole transcriptome sequencing (WTS, n=189) data generated from 427 patients (86.4% males, 13.6% females) with SCLC were comprehensively analysed. The differences in the mutation profile, gene expression profile, and inflammed signatures were analysed according to the IHC-based molecular subtype. IHC-based molecular subtyping, comprised of 90 limited-disease (35.7%) and 162 extensive-disease (64.3%), revealed a high incidence of ASCL1 subtype (IHC-A, 56.3%) followed by ASCL1/NEUROD1 co-expressed (IHC-AN, 17.9%), NEUROD1 (IHC-N, 12.3%), POU2F3 (IHC-P, 9.1%), triple-negative (IHC-TN, 4.4%) subtypes. IHC-based subtype showing high concordance with WTS-based subtyping and non-negative matrix factorization (NMF) clusterization method. IHC-AN subtype resembled IHC-A (rather than IHC-N) in terms of both gene expression profiles and clinical outcomes. Favourable median overall survival was observed in IHC-A (15.2 months) compared to IHC-N (8.0 months, adjusted HR 2.3, 95% CI 1.4-3.9, p=0.002) and IHC-P (8.3 months, adjusted HR 1.7, 95% CI 0.9-3.2, p=0.076). Inflamed tumours made up 25% of cases (including 53% of IHC-P, 26% of IHC-A, 17% of IHC-AN, but only 11% of IHC-N). Consistent with recent findings, inflamed tumours were more likely to benefit from first-line immunotherapy treatment than non-inflamed phenotype (p=0.002). This study provides fundamental data, including the incidence and basic demographics of molecular subtypes of SCLC using both IHC and WTS from a comparably large, real-world Asian/non-Western patient cohort, showing high concordance with the previous NMF-based SCLC model. In addition, we revealed underlying biological pathway activities, immunogenicity, and treatment outcomes based on molecular subtype, possibly related to the difference in clinical outcomes, including immunotherapy response. This work was supported by AstraZeneca, Future Medicine 2030 Project of the Samsung Medical Center [grant number SMX1240011], the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) [grant number 2020R1C1C1010626] and the 7th AstraZeneca-KHIDI (Korea Health Industry Development Institute) oncology research program.

Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.

Bromodomain Protein-directed Agents and MYC in Small Cell Lung Cancer.

Small cell lung cancer (SCLC) has a dismal prognosis. In addition to the inactivation of the tumor suppressors TP53 and RB1, tumor-promoting MYC and paralogs are frequently overexpressed in this neuroendocrine carcinoma. SCLC exhibits high resistance to second-line chemotherapy and all attempts of novel drugs and targeted therapy have failed so far to achieve superior survival. MYC and paralogs have key roles in the oncogenic process, orchestrating proliferation, apoptosis, differentiation, and metabolism. In SCLC, MYC-L and MYC regulate the neuroendocrine dedifferentiation of SCLC cells from Type A (ASCL1 expression) to the other SCLC subtypes. Targeting MYC to suppress tumor growth is difficult due to the lack of suitable binding pockets and the most advanced miniprotein inhibitor Omomyc exhibits limited efficacy. MYC may be targeted indirectly via the bromodomain (BET) protein BRD4, which activates MYC transcription, by specific BET inhibitors that reduce the expression of this oncogenic driver. Here, novel BET-directed Proteolysis Targeting Chimeras (PROTACs) are discussed that show high antiproliferative activity in SCLC. Particularly ARV825, targeting specifically BRD4, exhibits superior cytotoxic effects on SCLC cell lines and may become a valuable adjunct to SCLC combination chemotherapy.

Molecular and Pathologic Characterization of YAP1-Expressing Small Cell Lung Cancer Cell Lines Leads to Reclassification as SMARCA4-Deficient Malignancies.

The classification of small cell lung cancer (SCLC) into distinct molecular subtypes defined by ASCL1, NEUROD1, POU2F3, or YAP1 (SCLC-A, -N, -P, or -Y) expression, paves the way for a personalized treatment approach. However, the existence of a distinct YAP1-expressing SCLC subtype remains controversial. To better understand YAP1-expressing SCLC, the mutational landscape of human SCLC cell lines was interrogated to identify pathogenic alterations unique to SCLC-Y. Xenograft tumors, generated from cell lines representing the four SCLC molecular subtypes, were evaluated by a panel of pathologists who routinely diagnose thoracic malignancies. Diagnoses were complemented by transcriptomic analysis of primary tumors and human cell line datasets. Protein expression profiles were validated in patient tumor tissue. Unexpectedly, pathogenic mutations in SMARCA4 were identified in six of eight SCLC-Y cell lines and correlated with reduced SMARCA4 mRNA and protein expression. Pathologist evaluations revealed that SMARCA4-deficient SCLC-Y tumors exhibited features consistent with thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT). Similarly, the transcriptional profile SMARCA4-mutant SCLC-Y lines more closely resembled primary SMARCA4-UT, or SMARCA4-deficient non-small cell carcinoma, than SCLC. Furthermore, SMARCA4-UT patient samples were associated with a YAP1 transcriptional signature and exhibited strong YAP1 protein expression. Together, we found little evidence to support a diagnosis of SCLC for any of the YAP1-expressing cell lines originally used to define the SCLC-Y subtype. SMARCA4-mutant SCLC-Y cell lines exhibit characteristics consistent with SMARCA4-deficient malignancies rather than SCLC. Our findings suggest that, unlike ASCL1, NEUROD1, and POU2F3, YAP1 is not a subtype defining transcription factor in SCLC. See related commentary by Rekhtman, p. 1708.

A Multiplexed Approach to Assess Small Cell Lung Cancer Subtype Heterogeneity in Primary and Patient-Derived Tumor Samples.

Unlocking the heterogeneity of cancers is crucial for developing therapeutic approaches that effectively eradicate disease. As our understanding of markers specific to cancer subclones or subtypes expands, there is a growing demand for advanced technologies that enable the simultaneous investigation of multiple targets within an individual tumor sample. Indeed, multiplex approaches offer distinct benefits, particularly when tumor specimens are small and scarce. Here we describe the utility of two fluorescence-based multiplex approaches; fluorescent Western blots, and multiplex immunohistochemistry (Opal™) staining to interrogate heterogeneity, using small cell lung cancer as an example. Critically, the coupling of Opal™ staining with advanced image quantitation, permits the dissection of cancer cell phenotypes at a single cell level. These approaches can be applied to patient biopsies and/or patient-derived xenograft (PDX) models and serve as powerful methodologies for assessing tumor cell heterogeneity in response to therapy or between metastatic lesions across diverse tissue sites.

Abstract LB_A22: Advancing personalized therapies for small cell lung cancer: Exploring HER2-targeting antibody-drug conjugates (ADCs) and SLFN11 biomarker insights

Abstract Background: Small-cell lung cancer (SCLC) is a highly aggressive malignancy constituting 15% of all lung cancers, with a 5-year survival rate of less than 7%. Our group has established four transcriptionally defined subtypes of SCLC, each with distinct cell surface targets (Gay et al, Cancer Cell 2021). Further, we identified SLFN11 (a putative DNA/RNA helicase) as a candidate biomarker of sensitivity to DNA-damaging agents, including topoisomerase I inhibitors. Despite these advances, SCLC is still treated clinically with a “one-size-fits-all” approach. Human epidermal growth factor receptor 2 (HER2/ERBB2) has been previously described in a subset of SCLCs and has been linked to poor prognosis. Notably, HER2-targeting antibody-drug conjugates (ADCs) like Trastuzumab Deruxtecan (T-DXd) (where the payload is a topoisomerase I inhibitor) have received FDA approval for various solid tumors, highlighting their therapeutic potential. Methods: We analyzed ERBB2 mRNA expression in publicly available patient datasets and profiled HER2 protein expression in cell lines and patient-derived xenograft models by flow cytometry and IHC. We then assessed the cytotoxicity of Trastuzumab Deruxtecan in a panel of cell lines representative of the heterogeneity of SCLC to test whether levels of HER2 and/or SLFN11 predicted response. Results: Analyses of HER2/ERBB2 in SCLC cell lines and patient-derived xenograft (PDX) models revealed an enrichment in the SCLC-POU2F3 (SCLC-P) subtype. HER2 expression was validated by IHC and flow cytometry in a subset of SCLC cell lines and PDX models. ERBB2 mRNA expression data was analyzed using publicly available SCLC patient datasets, where we uncovered high expression of ERBB2 in a subset of patient tumors. Consistent with this, single-cell RNA-Seq data revealed ERBB2 expression in POU2F3+ cells in tumors from patients with relapsed SCLC. As predicted, we found a strong correlation between the in vitro cytotoxicity of Trastuzumab Deruxtecan and both the level of surface HER2 expression and SLFN11 level. Importantly, the SCLC cell lines with the highest HER2 surface expression exhibited the lowest IC50 of Trastuzumab Deruxtecan, and the response was predicted by the presence of SLFN11. Conclusion: We demonstrate HER2/ERBB2 mRNA and protein expression in a subset of SCLC, with enrichment in the SCLC-P subtype. Further, the FDA-approved HER2-targeting ADC Trastuzumab Deruxtecan had significant cytotoxicity, correlating with expression of the surface target (HER2) as well as with SLFN11 (a candidate predictive biomarker for the topoisomerase inhibitor payload). These findings suggest the potential of tailoring HER2-targeting strategies based on HER2 and SLFN11 expression in SCLC as an effective and personalized approach for tackling SCLC. Citation Format: Ali H. Ibrahim, Bingnan Zhang, C. Allison Stewart, Alejandra Serrano, Luisa M. Solis, Wei-Lien Wang, Kavya Ramkumar, Robert J. Cardnell, Runsheng Wang, Alberto Duarte Jr, Lixia Diao, Yuanxin Xi, Jing Wang, Lauren A. Byers, Carl M. Gay. Advancing personalized therapies for small cell lung cancer: Exploring HER2-targeting antibody-drug conjugates (ADCs) and SLFN11 biomarker insights [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr LB_A22.

Does subtyping of high-grade pulmonary neuroendocrine carcinomas have an impact on therapy selection?

Small cell lung cancer (SCLC) and large cell neuroendocrine carcinomas (LCNEC) are characterized by a rapid progressive course. Therapy for SCLC has not much changed for decades, and in LCNEC controversies exist, favoring either SCLC-like or non-small cell lung cancer (NSCLC)-like therapy. Three subtypes of SCLC identified in cell cultures, namely ASCL1, NeuroD1, and POU2F3 have been confirmed by immunohistochemistry. The fourth type based on the expression of YAP1 was questioned, and another type, inflamed SCLC, was proposed. SCLC and LCNEC samples were investigated by immunohistochemistry for different subtypes. Additionally, immunohistochemical markers as potential tools to identify patients who might respond to targeted treatment were investigated. For validation a biopsy set was added. ASCL1, NeuroD1, and POU2F3 were expressed in different percentages in SCLC and LCNEC. Similar percentages of expression were found in biopsies. ATOH was expressed in combination with one of the subtypes. YAP1 and TAZ were expressed in some SCLC and LCNEC cases. HES1 expression was seen in few cases. Predominantly stroma cells expressed programmed cell death ligand 1 (PD-L1). The dominant MYC protein was N-MYC. Aurora kinase A (AURKA) was expressed in the majority of both carcinomas, whereas fibroblast growth factor receptor 2 (FGFR2) in few. SCLC and LCNEC can be subtyped into ASCL1-, NeuroD1-, and POU2F3-positive types. AURKA expression and positivity for N-MYC protein was not associated with subtypes. AURKA and FGFR2 are both possible targets for inhibition in SCLC and LCNEC, but patients' selection should be based on expression of the enzyme. Combined chemo- and immunotherapy might be decided by PD-L1 staining of stroma cells.

Extracellular vesicles from non-neuroendocrine SCLC cells promote adhesion and survival of neuroendocrine SCLC cells.

Small cell lung cancer (SCLC) tumors are made up of distinct cell subpopulations, including neuroendocrine (NE) and non-neuroendocrine (non-NE) cells. While secreted factors from non-NE SCLC cells have been shown to support the growth of the NE cells, the underlying molecular factors are not well understood. Here, we show that exosome-type small extracellular vesicles (SEVs) secreted from non-NE SCLC cells promote adhesion and survival of NE SCLC cells. Proteomic analysis of purified SEVs revealed that extracellular matrix (ECM) proteins and integrins are highly enriched in SEVs of non-NE cells whereas nucleic acid-binding proteins are enriched in SEVs purified from NE cells. Addition of select purified ECM proteins identified in purified extracellular vesicles (EVs), specifically fibronectin, laminin 411, and laminin 511, were able to substitute for the role of non-NE-derived SEVs in promoting adhesion and survival of NE SCLC cells. Those same proteins were differentially expressed by human SCLC subtypes. These data suggest that ECM-carrying SEVs secreted by non-NE cells play a key role in supporting the growth and survival of NE SCLC cells.

Deep Learning Based on Enhanced MRI T1 Imaging to Differentiate Small-cell and Non-small-cell Primary Lung Cancers in Patients with Brain Metastases.

To differentiate the primary small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) for patients with brain metastases (BMs) based on a deep learning (DL) model using contrast-enhanced magnetic resonance imaging (MRI) T1 weighted (T1CE) images. Out of 711 patients with BMs of lung cancer origin (SCLC 232, NSCLC 479), the MRI datasets of 192 patients (lesions' widths and heights > 30 pixels) with BMs from lung cancer (73 SCLC and 119 NSCLC) confirmed pathologically were enrolled, retrospectively. A typical convolutional neural network ResNet18 was applied for the automatic classification of BMs lesions from lung cancer based on T1CE images, with training and testing groups randomized per patient to eliminate learning bias. A 5-fold cross-validation was performed to evaluate the classification of the model. The receiver operating characteristic (ROC) curve, accuracy, precision, recall and f1 score were calculated. For a 5-fold cross-validation test, the DL model achieved AUCs of 0.8019 and 0.8024 for SCLC and NSCLC patients with BMs, respectively, and a mean overall accuracy of 0.7515±0.04. The DL model performed well in differentiating the primary SCLC and NSCLC with BMs. The proposed DL model is feasible and effective in differentiating the pathological subtypes of SCLC and NSCLC causing BMs, which may be used as a new tool for oncologists to diagnose noninvasively BMs and guide therapy based on the imaging structure of tumors.

Data-driven structural analysis of small cell lung cancer transcription factor network suggests potential subtype regulators and transition pathways

Small cell lung cancer (SCLC) is an aggressive disease and challenging to treat due to its mixture of transcriptional subtypes and subtype transitions. Transcription factor (TF) networks have been the focus of studies to identify SCLC subtype regulators via systems approaches. Yet, their structures, which can provide clues on subtype drivers and transitions, are barely investigated. Here, we analyze the structure of an SCLC TF network by using graph theory concepts and identify its structurally important components responsible for complex signal processing, called hubs. We show that the hubs of the network are regulators of different SCLC subtypes by analyzing first the unbiased network structure and then integrating RNA-seq data as weights assigned to each interaction. Data-driven analysis emphasizes MYC as a hub, consistent with recent reports. Furthermore, we hypothesize that the pathways connecting functionally distinct hubs may control subtype transitions and test this hypothesis via network simulations on a candidate pathway and observe subtype transition. Overall, structural analyses of complex networks can identify their functionally important components and pathways driving the network dynamics. Such analyses can be an initial step for generating hypotheses and can guide the discovery of target pathways whose perturbation may change the network dynamics phenotypically.