Abstract INTRODUCTION: Lung cancer is the leading cause of cancer-related deaths worldwide. KRAS is the most frequent mutated driver gen in lung adenocarcinoma (LUAD). KRASG12C inhibitors (G12Ci) have revealed promising results in the clinic, having being approved two G12Ci for the treatment of LUAD patients, which marks the first approved targeted therapy for KRAS-mutant tumors. Nevertheless, these therapies face the same limitation as other targeted therapies, the therapeutic potential of these inhibitors can be impaired by resistance mechanisms. Deciphering resistance mechanisms to G12Ci is of prime relevance to predict which patients may benefit from these therapies and to propose resistance-overcoming therapeutic strategies for maximizing therapeutic impact of these inhibitors. MATERIAL AND METHODS: We generated 10 acquired resistant LUAD cell lines to G12Ci (Sotorasib and Adagrasib), exposing sensitive cells to increasing concentrations of drugs. All the acquired resistant models were characterized at the proteomic (phospho-Array and Western Blot) and transcriptomic (WTS) levels to find signatures that define the resistance.The efficacy of G12Ci was tested in vitro in a panel of 8 cell lines and 7 PDX-derived organoids (PDXDO) models and in vivo in 7 patient-derived xenografts (PDX) models to classify them as resistant, sensitive or partially sensitive. The efficacy of the combination of FGFR1 and G12Ci was tested in vitro in the panel of 10 acquired resistant cell lines but also in the parental cell lines and PDXDOs (sensitive and intrinsic resistant) and in vivo in the intrinsic resistant PDXs. RESULTS AND DISCUSSION: The characterization of 10 acquired resistant cell lines at the proteomic and transcriptomic levels showed differences in the expression and/or activation of Fibroblast Growth Factor Receptors (FGFRs) in more than 50% of them. The combination of KRASG12C and FGFR1 inhibitors in all acquired resistant cell lines showed efficacy, regardless of whether acquired resistance was mediated or not by FGFR1 overexpression/overactivation.In addition, the combination of KRASG12C and FGFR1 inhibitors showed more efficacy than the monotherapies in most intrinsically resistant cell lines, PDXDOs and PDXs models. Finally, we tested the combination with FGFR1i in sensitive or partially responsive models, observing an improvement in efficacy compared to monotherapy with G12Ci. CONCLUSIONS: The activation or overexpression of FGFR1 acts as a mechanism of acquired resistance to KRASG12C inhibitors.-The combination of FGFR and KRASG12C inhibitors is effective as an acquired/intrinsic resistance-overcoming therapeutic strategy in cell lines, PDXDOs and PDXs models.-The combination of FGFR and KRASG12C inhibitors is also synergistic for sensitive models, which could maximize therapeutic impact of KRASG12C inhibitors. Citation Format: Alba Santos, Patricia Plaza, Marta Jimenez, David Gómez-Sánchez, Luis Paz-Ares, Irene Ferrer. Combination of KRASG12C and FGFR1 inhibitors as a resistance-overcoming therapeutic strategy for maximizing therapeutic impact of KRASG12C inhibitors [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 1930.

Abstract Capture-based targeted sequencing is routinely used for small variant detection in cancer clinical care. Alongside targeted DNA, off-target DNA is also sequenced. These off-target reads are distributed across the genome, allowing for a whole genome copy number profile to be derived without the need for a SNP backbone. Here we present CopyRight, a method that generates robust genome-wide copy number profiles, which can be used for downstream chromosomal instability (CIN) quantification, overcoming various sources of technical noise with a novel approach that only requires a single tumor sample. We analyzed a variety of capture-based NGS protocols using our novel computational method, including the TruSight Oncology 500 (TSO500) panel, and compared them to the current gold standard for genome-wide copy number profiling from FFPE tissues: shallow whole genome sequencing (sWGS). Comparable results were obtained from targeted sequencing depending on sample purity, preservation method, and read depth. Additionally, benchmarks of CopyRight against other computational algorithms show an improvement in performance without the need for a matched normal tissue, the usual drawback for other methods in the cancer field. CIN signatures are a new set of emerging biomarkers that reflect the diversity of defective pathways that have operated in a tumor, which require robust genome-wide copy number profiles. These CIN signatures can be used to predict response to cytotoxic agents and targeted therapies and could ultimately help guide therapy selection in patients. As most clinical sequencing workflows rely on targeted sequencing, CopyRight can be included in current clinical assays, enabling CIN biomarker quantification with no extra technical or experimental requirements. Citation Format: David Gómez-Sánchez, Joe Sneath Thompson, Barbara Hernando, Diego García-López, Hector de Galard, Abhipsa Roy, Amy Cullen, Laura Madrid, José Teles, Ania Piskorz, Jason Yip, Alice Cádiz, Maria Escobar-Rey, Roberto Moreno-Vellisca, Nuria Carrizo, Eva Álvarez, Miguel Quintela-Fandino, Mariano Barbacid, Javier Ramos-Paradas, Juan Manuel Coya, Irene Ferrer, Jon Zugazagoitia, Luis Paz-Ares, Geoff Macintyre. Enabling biomarkers of chromosomal instability for tumor only targeted gene panel sequencing [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 7422.

Small cell lung cancer (SCLC) is a lethal malignancy with few therapeutic options. Tissue resection or biopsy are unusual, so the scarce sample available has limited our knowledge on the biology of SCLC tumors. Recent advances propose novel molecular subtypes (SCLC-A, SCLC-N, SCLC-P, SCLC-I, NAPI classification) to classify SCLC patients and specific treatment susceptibilities of defined subgroups. In this line, we collected 119 tumor samples from a cohort of early-stage SCLC patients with complete clinical annotation, in order to find specific molecular and immune profiles that define new patient characteristics with potential impact on prognosis or therapy selection. For this, we subjected the tumor tissue to RNA-seq targeted panel of onco-immune-related genes and to immune characterization by IHC. In addition, we analyzed molecular aberrations by whole exome sequencing. All data, including clinical annotations, were integrated by multiparametric computational analysis. Based on the computational analysis of the onco-immune transcriptomic data, we found two major groups of patients with either pro-immunogenic or pro-tumorigenic profiles. The transcriptomic pro-immunogenic group shows better survival and higher infiltration of immune cells (CD4+ T cells, CD8+ T cells, B cells and Macrophages). In contrast, the pro-tumorigenic group presents worse survival and less immune cell infiltration. Using bioinformatics, we described a gene signature that can identify both subgroups. This gene signature includes immune cell markers (MS4A1, CD3D), antigen receptor complex (CD79A), adhesion and migration of T cells (CD2) and immunomodulatory genes (IDO1, TIGIT) expressed in the pro-immunogenic group, and, proliferation (MKI67), transcription regulator (TOP2A) and epithelial and mesenchymal transition-related genes (TWIST1) in the pro-tumorigenic group. Exome sequencing analysis resulted in the expected genomic heterogeneity of SCLC tumors beyond TP53 and RB1 mutations in most patients. However, we found a significant enrichment of XIRP2 gene alterations in the pro-tumorigenic group. Consistent with an early-stage of SCLC, most of the samples were described as SCLC-A subtype by the predominant expression of ASCL1. Interestingly, our findings suggest a relevant biological heterogeneity within SCLC-A tumors that impacts immune infiltrate and disease outcome. Here we show a gene signature that can subclassify early-stage SCLC patients according to their clinical, molecular and immune features, and provides prognostic value independently of the NAPI classification. Since immunogenicity of the tumor impacts response to immunotherapy, we speculate that this gene signature might predict therapy response and therefore contribute to tailored treatment of SCLC. Citation Format: Angel Nunez-Buiza, David Gómez-Sánchez, Jose Maria Gracia-Rodríguez, Esther Conde, Jose Luis Solorzano, Eva María Garrido-Martín, Jose Carlos Machado, Susana Guimarães, Ernest Nadal, Sonia Molina-Pinelo, Miguel Ángel Piris Pinilla, Nuria Romero-Laorden, Fernando Franco, Fernando López-Ríos Moreno, Álvaro Conrado Ucero, Luis Paz-Ares. Multiparametric characterization of early-stage SCLC human tumors reveals novel patient subgroups based on specific molecular to immune landscape associations. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4524.

Background: Lung cancer is the leading cause of cancer-related deaths worldwide. FGFR1 has been associated with tumorigenesis in a variety of tumor types, including lung cancer. As a therapeutic approach, their inhibition has been attempted and was initially focused on FGFR1-amplified tumors, though with limited success. Preliminary data of our group suggests that N-Cadherin play a key role for the oncogenicity of FGFR1 and predict FGFR-targeted therapy efficacy in Non-small cell lung cancer (NSCLC). However, it is possible that other biomarkers, together with N-Cadherin, can determine the response to anti-FGFR therapy. Therefore, it is essential the identification of new biomarkers that could help to predict more accurately those patients that could benefit from anti-FGFR therapy. Materials and Methods: We have treated 15 NSCLC PDX models with high FGFR1 expression levels and variable N-Cadherin expression levels, with the FGFR inhibitor (FGFRi) AZD4547. Based on their sensitivity to treatment, the PDX models were classified into two groups: Responders and Non-responders. All PDX models were characterized at the proteomic, genomic, and transcriptomic levels by western blot, whole exome sequencing, and RNA-Seq, respectively, and we used this information for defining the responder versus the non-responder group. Subsequently, the GDSC repository was used to validated our data in a cohort of lung adenocarcinoma (LUAD) cell lines. Results: Responder and non-responder groups revealed a distinct pattern of genomic alterations and gene expression profile. As expected, GSEA identified an enrichment in Responders group of pathways related to FGFR1 signaling and ECM proteins, among them N-Cadherin stands out. Moreover, we observed an enrichment of KRAS mutations and genes related to the KRAS signature and to the intrinsic resistance to FGFRi in the non-responder group. To validate our findings and using the GDSC repository, we observed an enriched resistance to inhibitors of FGFR1 signaling in a cohort of KRAS mutant LUAD cell lines. Furthermore, we confirm a tendency for increased sensitivity in high N-Cadherin expressing cell lines, but only in KRAS wildtype context. Conclusions: In conclusion, previous research had underlined N-Cadherin as a potential biomarker of response to FGFRi, while not successful in all contexts. Transcriptome study of PDXs classified as responder or non-responder to FGFRi revealed a differential gene expression pattern, with an upregulation of N-Cadherin pathway observed in the Responder group, while an enrichment of KRAS signaling and KRAS mutations in non-Responders. Furthermore, we validated our finding using a cell line repository that confirm that N-Cadherin could predict FGFR-targeted therapy efficacy but only in the KRAS wildtype context. Citation Format: Santiago G. Borrego, Cristina Cirauqui, David Gómez-Sánchez, Haiyun Wang, Alicia Luengo, Chiara Ambrogio, Luis Paz-Ares, Irene Ferrer. N-Cadherin acts as a predictive biomarker for anti-FGFR therapy in KRAS wild-type NSCLC. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4489.

Aneuploidy is a frequent feature of human tumors. Germline mutations leading to aneuploidy are very rare in humans, and their tumor-promoting properties are mostly unknown at the molecular level. We report here novel germline biallelic mutations in MAD1L1 , the gene encoding the Spindle Assembly Checkpoint (SAC) protein MAD1, in a 36-year-old female with a dozen of neoplasias, including five malignant tumors. Functional studies in peripheral blood cells demonstrated lack of full-length protein and deficient SAC response, resulting in ∼30-40% of aneuploid cells as detected by cytogenetic and single-cell (sc) DNA analysis. scRNA-seq analysis of patient blood cells identified mitochondrial stress accompanied by systemic inflammation with enhanced interferon and NFkB signaling. The inference of chromosomal aberrations from scRNA-seq analysis detected inflammatory signals both in aneuploid and euploid cells, suggesting a non-cell autonomous response to aneuploidy. In addition to random aneuploidies, MAD1L1 mutations resulted in specific clonal expansions of γδ T-cells with chromosome 18 gains and enhanced cytotoxic profile, as well as intermediate B-cells with chromosome 12 gains and transcriptomic signatures characteristic of chronic lymphocytic leukemia cells. These data point to MAD1L1 mutations as the cause of a new aneuploidy syndrome with systemic inflammation and unprecedented tumor susceptibility.

Lung cancer is the leading cause of cancer-related deaths worldwide. Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR) activating mutations have significantly improved patient´s treatment with these alterations. However, 15-20% of EGFR-mutated patients do not respond to the therapy, even harboring the same mutations than responders. Little is known about the mechanisms involved in this primary resistance. This work aims to characterize molecular aberrations in clones with intrinsic resistance to first and third generation EGFR-TKIs generated from non-small cell lung cancer (NSCLC) cell lines. Three Erlotinib-sensitive (HCC827, PC9 and H4006) and one Osimertinib-sensitive (H1975) NSCLC cell lines were used to generate primary resistance models through a pulsatile method in which cells were treated with a high concentration of the TKI during a short period of time. Survivor colonies were individually expanded in the presence of the inhibitor until resistant cell lines were established. Exome, transcriptome and methylome were then analyzed in selected clones. Erlotinib- and Osimertinib-resistant clones exhibited cross-resistance to other EGFR-targeted therapies, such as Afatinib and Cetuximab, but not to the chemotherapeutics Carboplatin or Cisplatin. Among derived clones, we found several genetic alterations in genes associated with TKI acquired resistance, including NTRK1, ARID2, ERBB3, RET, and other genes. MET amplification was exclusively associated with resistant HCC827-derived clones. We also identified non-genetic alterations that include increased expression and over-activation of well-known TKI resistance-associated proteins, such as AXL, FGFR1, or AKT, as well as induction of epithelial-to-mesenchymal transition (EMT) and stemness-related genes. Transcriptome and methylome analyses revealed EMT plasticity among resistant clones that could reflect different EMT states conferring resistance in pre-treated tumors. Molecular inhibition of MET, a recognized resistance mechanism, sensitizes MET-amplified resistant clones to Erlotinib. Combination treatments or genetic inhibitions will be further performed to validate our findings. Taken together, our results suggest that multiple genetic and non-genetic alterations already present before TKI treatment could account for primary resistance. We will employ integrative analysis of our multi-omic data to identify novel targets that allow to overcome EGFR-TKI resistance. Further clinical validation will help to prospectively select the best treatment option for EGFR-mutated patients for the sake of precision medicine. Citation Format: Juan Manuel Coya, Eva Álvarez, David Gómez-Sánchez, Aranzazu Rosado, Irene Ferrer, Luis Paz-Ares. Comprehensive molecular characterization of mechanisms involved in primary resistance to EGFR tyrosine kinase inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 414.

Germline mutations leading to aneuploidy are rare, and their tumor-promoting properties are mostly unknown at the molecular level. We report here novel germline biallelic mutations in MAD1L1 , encoding the spindle assembly checkpoint (SAC) protein MAD1, in a 36-year-old female with a dozen of neoplasias. Functional studies demonstrated lack of full-length protein and deficient SAC response, resulting in ~30 to 40% of aneuploid blood cells. Single-cell RNA analysis identified mitochondrial stress accompanied by systemic inflammation with enhanced interferon and NFκB signaling both in aneuploid and euploid cells, suggesting a non–cell autonomous response. MAD1L1 mutations resulted in specific clonal expansions of γδ T cells with chromosome 18 gains and enhanced cytotoxic profile as well as intermediate B cells with chromosome 12 gains and transcriptomic signatures characteristic of leukemia cells. These data point to MAD1L1 mutations as the cause of a new variant of mosaic variegated aneuploidy with systemic inflammation and unprecedented tumor susceptibility.

Lung cancer has the second highest incidence and leads cancer mortality worldwide, being Non-Small Cell Lung Cancer (NSCLC) the most prevalent subtype. Immunotherapy with checkpoint blockers has shown outstanding benefits in a subset of NSCLC patients, which are not accurately identified due to the lack of robust biomarkers of response. We hypothesize that specific molecular alterations of NSCLC tumor cells impact the immune microenvironment. Defining this association could improve the prediction of response to immunotherapy. This work aims to identify a multiparametric biomarker signature. We studied 178 tumor samples from a cohort of early stage NSCLC with complete clinical annotation. We analyzed their molecular aberrations, calculated their Tumor Mutational Burden and described their immune landscape by immunohistochemistry and a dedicated RNAseq panel. We defined novel subgroups of NSCLC tumors with specific immune, molecular and clinical features, showing an association between their molecular genotype and immune phenotype. Based on these data, subgroups were proposed as pro-immunogenic, pro-tumorigenic or mixed. Adenocarcinomas clustered in 4 groups. The pro-tumorigenic group had a significant higher proportion of alterations in ARID1A, FGF10, ROS1, TP53. One pro-immunogenic group had a significant higher proportion of MET alterations and lower proportion of EGFR alterations. An immune mixed group significantly accrued never smokers and had no alterations in FGF10. Squamous cell carcinomas clustered in 4 groups. The pro-tumorigenic group had a significant higher proportion of alterations in CCND1, FGF3, FGF10, FGF19, NOTCH1, PIK3CA, PIK3CB, TFRC. A pro-immunogenic group had a significant higher infiltration of T CD4+, T CD8+ and B cells and a higher overall survival. Another pro-immunogenic group had a significant absence of MYCN and NF1 alterations. Taken together we identified a set of candidate predictive biomarkers of response to immunotherapy in NSCLC. Genes overexpressed in pro-immunogenic tumors are related to adaptive immune response stimulation (CD28, FCRLA, JCHAIN, LY9, MS4A1, SLAMF7, TNFRSF9, TNFRSF17), antigen presentation (CD1C, CD1D, HLA-A), apoptosis (FAS), immune chemotaxis (CCL20, CCR4, CCR6), and immune regulation (CD53, PDCD1, SH2D1A, ZAP70). On the other hand, genes upregulated in pro-tumorigenic tumors are involved in angiogenesis (VEGFA), cell cycle regulation (BUB1, CCNB2, FOXM1, MAD2L1, TOP2A), cell growth/survival (IGF1R), DNA replication/repair (KIAA0101) and iron metabolism (HMBS, TFRC). These findings are being validated by Digital Spatial Profiling in a cohort of patients with advanced stage NSCLC that were treated with checkpoint blockers. If confirmed, these results could remarkably improve patient selection and the benefit upon immunotherapy. Citation Format: Javier Ramos-Paradas, David Gomez-Sanchez, Aranzazu Rosado, Alvaro Conrado Ucero, Nuria Carrizo, Ana Belen Enguita, Maria Teresa Muñoz, Esther Conde, Luis Paz-Ares, Eva Maria Garrido-Martin. Comprehensive analysis of non-small cell lung cancer identifies molecular genotype-immunophenotype associations and candidate biomarkers predictive of response to immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1245.

Background and Aims: Metastatic urothelial carcinoma (mUC) remains an incurable disease with limited treatment options after platinum-based chemotherapy and immune checkpoint blockade (ICB). Vinflunine has shown a modest increase in overall survival and remains a therapeutic option for chemo- and immunotherapy refractory tumours. However, biomarkers that could identify responding patients to vinflunine and possible alternative therapies after failure to treatment are still missing. In this study, we aimed to identify potential genomic biomarkers of vinflunine response in mUC patient samples and potential management alternatives. Methods: Formalin-fixed paraffin-embedded samples of mUC patients (n = 23) from three university hospitals in Spain were used for genomic targeted-sequencing and transcriptome (using the Immune Profile panel by NanoString) analyses. Patients who received vinflunine after platinum-based chemotherapy failure were classified in non-responders (NR: progressive disease ≤ 3 months; n= 11) or responders (R: response ≥ 6 months; n = 12). Results: Genomic characterization revealed that the most common alteration, TP53 mutations, had comparable frequency in R (6/12; 50%) and NR (4/11; 36%). Non-synonymous mutations in KTM2C (4/12; 33.3%), PIK3CA (3/12; 25%) and ARID2 (3/12; 25%) were predominantly associated with response. No significant difference was observed in tumour mutational burden (TMB) between R and NR patients. The NR tumours showed increased expression of diverse immune-related genes and pathways, including various interferon gamma-related genes. We also identified increased MAGEA4 expression as a potential biomarker of non-responding tumours to vinflunine treatment. Conclusions: Our data may help to identify potential genomic biomarkers of response to vinflunine. Moreover, tumours refractory to vinflunine showed immune signatures potentially associated with response to ICB. Extensive validation studies, including longitudinal series, are needed to corroborate these findings.

Lung cancer is the leading cause of cancer mortality worldwide, with non-small cell lung cancer (NSCLC) being the most prevalent histology. While immunotherapy with checkpoint inhibitors has shown outstanding results in NSCLC, the precise identification of responders remains a major challenge. Most studies attempting to overcome this handicap have focused on adenocarcinomas or squamous cell carcinomas. Among NSCLC subtypes, the molecular and immune characteristics of lung large cell carcinoma (LCC), which represents 10% of NSCLC cases, are not well defined. We hypothesized that specific molecular aberrations may impact the immune microenvironment in LCC and, consequently, the response to immunotherapy. To that end, it is particularly relevant to thoroughly describe the molecular genotype–immunophenotype association in LCC–to identify robust predictive biomarkers and improve potential benefits from immunotherapy. We established a cohort of 18 early-stage, clinically annotated, LCC cases. Their molecular and immune features were comprehensively characterized by genomic and immune-targeted sequencing panels along with immunohistochemistry of immune cell populations. Unbiased clustering defined two novel subgroups of LCC. Pro-immunogenic tumors accumulated certain molecular alterations, showed higher immune infiltration and upregulated genes involved in potentiating immune responses when compared to pro-tumorigenic samples, which favored tumoral progression. This classification identified a set of biomarkers that could potentially predict response to immunotherapy. These results could improve patient selection and expand potential benefits from immunotherapy.

Non-Small-Cell Lung Cancer (NSCLC) leads cancer incidence and mortality. Immune checkpoint blockers showed promising results, yet responders cannot be accurately selected as robust predictive biomarkers are lacking. Our hypothesis is that molecular aberrations of tumor cells impact the immune microenvironment. This association may be crucial to predict response to immunotherapy. We evaluated a retrospective cohort of clinically annotated early stage NSCLC (N=196). We described its immune profile by immunohistochemistry and an immune markers RNAseq panel, and its molecular profile by Next Generation Sequencing (DNA/RNAseq). We defined novel groups of patients with distinct molecular features and two main immunophenotypes. Immune hot tumors had higher infiltration of CD4+, CD8+ and CD20+ cells, while cold tumors accrued mutations in ARID1A, CARD11, CCND1, FGF3, FGF10, FGF19, MYC, NF1, NOTCH1, PIK3CA, PIK3CB and TFRC, dependent on histology. These features, together with the differential expression of immune markers, defined potential predictive biomarkers. Hot tumors were identified by genes related to adaptive immune response (CD28, FCRLA, JCHAIN, LY9, MS4A1, SLAMF7, TNFRSF9, TNFRSF17), antigen presentation (CD1C, CD1D), immune chemotaxis (CCL20, CCR4, CCR6) and immune regulation (CD53, PDCD1, SH2D1A). Cold tumors were defined by genes involved in angiogenesis (VEGFA), cell cycle (BUB1, CCNB2, FOXM1, MAD2L1, TOP2A), growth/survival (IGF1R), DNA replication/repair (KIAA0101) and iron metabolism (HMBS, TFRC). We defined novel patient groups in NSCLC based on multiparametric features and identified potential predictive biomarkers of response to immunotherapy.

Heat shock protein 90 (HSP90) plays an essential role in lung adenocarcinoma, acting as a key chaperone involved in the correct functioning of numerous highly relevant protein drivers of this disease. To this end, HSP90 inhibitors have emerged as promising therapeutic strategies, even though responses to them have been limited to date. Given the need to maximize treatment efficacy, the objective of this study was to use isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic techniques to identify proteins in human lung adenocarcinoma cell lines whose basal abundances were correlated with response to HSP90 inhibitors (geldanamycin and radicicol derivatives). From the protein profiles identified according to response, the relationship between lactate dehydrogenase B (LDHB) and DNA topoisomerase 1 (TOP1) with respect to sensitivity and resistance, respectively, to geldanamycin derivatives is noteworthy. Likewise, rhotekin (RTKN) and decaprenyl diphosphate synthase subunit 2 (PDSS2) were correlated with sensitivity and resistance to radicicol derivatives. We also identified a relationship between resistance to HSP90 inhibition and the p53 pathway by glucose deprivation. In contrast, arginine biosynthesis was correlated with sensitivity to HSP90 inhibitors. Further study of these outcomes could enable the development of strategies to improve the clinical efficacy of HSP90 inhibition in patients with lung adenocarcinoma.

BACKGROUND:Tumor mutational burden (TMB) is a recently proposed predictive biomarker for immunotherapy in solid tumors, including non-small cell lung cancer (NSCLC). Available assays for TMB determination differ in horizontal coverage, gene content and algorithms, leading to discrepancies in results, impacting patient selection. A harmonization study of TMB assessment with available assays in a cohort of patients with NSCLC is urgently needed. METHODS:We evaluated the TMB assessment obtained with two marketed next generation sequencing panels: TruSight Oncology 500 (TSO500) and Oncomine Tumor Mutation Load (OTML) versus a reference assay (Foundation One, FO) in 96 NSCLC samples. Additionally, we studied the level of agreement among the three methods with respect to PD-L1 expression in tumors, checked the level of different immune infiltrates versus TMB, and performed an inter-laboratory reproducibility study. Finally, adjusted cut-off values were determined. RESULTS:Both panels showed strong agreement with FO, with concordance correlation coefficients (CCC) of 0.933 (95% CI 0.908 to 0.959) for TSO500 and 0.881 (95% CI 0.840 to 0.922) for OTML. The corresponding CCCs were 0.951 (TSO500-FO) and 0.919 (OTML-FO) in tumors with <1% of cells expressing PD-L1 (PD-L1<1%; N=55), and 0.861 (TSO500-FO) and 0.722 (OTML-FO) in tumors with PD-L1≥1% (N=41). Inter-laboratory reproducibility analyses showed higher reproducibility with TSO500. No significant differences were found in terms of immune infiltration versus TMB. Adjusted cut-off values corresponding to 10 muts/Mb with FO needed to be lowered to 7.847 muts/Mb (TSO500) and 8.380 muts/Mb (OTML) to ensure a sensitivity >88%. With these cut-offs, the positive predictive value was 78.57% (95% CI 67.82 to 89.32) and the negative predictive value was 87.50% (95% CI 77.25 to 97.75) for TSO500, while for OTML they were 73.33% (95% CI 62.14 to 84.52) and 86.11% (95% CI 74.81 to 97.41), respectively. CONCLUSIONS:Both panels exhibited robust analytical performances for TMB assessment, with stronger concordances in patients with negative PD-L1 expression. TSO500 showed a higher inter-laboratory reproducibility. The cut-offs for each assay were lowered to optimal overlap with FO.

Abstract Lung cancer leads cancer mortality, being Non-Small-Cell Lung Cancer (NSCLC) the most prevalent subtype. Immunotherapy with checkpoint inhibitors has shown promising results in NSCLC, yet this benefit is restricted to a subset of patients. Robust predictive biomarkers of response are lacking. We seek a multiparametric biomarker signature. We hypothesize that specific molecular alterations of NSCLC tumor cells have a deep impact on the immune microenvironment. Describing this relationship is critical to predict response to immunotherapy. We evaluated 178 samples from a retrospective cohort of clinically annotated early stage NSCLC patients. We analyzed their immune profile by immunohistochemistry and a RNAseq immune panel. In parallel, we defined their molecular aberrations and Tumor Mutational Burden by Next Generation Sequencing. We integrated our multiparametric data with Multi-Omics Factor Analysis. Adenocarcinomas (N=80) cluster in 4 groups with two main immunophenotypes. Key factors of this clustering are TOP2A, MKI67, CCNB2, CDK1, JCHAIN, VEGFA, PCLAF, KRT7, FOXM1, BUB1. The proimmune tumors upregulate genes related to immune activation (CD40LG, CD28, MS4A1), signaling (CD79B), chemoattraction (CXCR2), antigen presentation (CD1C, HLA-DQA2), inflammatory cytokines (IL2, IL1B), and immune cells (CD19). Oppositely, the protumoral samples overexpress genes involved in cell cycle (CCNB2, FOXM1, CDKN2A, CDKN3), immune inhibition (CD276), angiogenesis (VEGFA) and proliferation (AKT1, EGFR, PIK3CA, MTOR, MKI67). Regarding molecular characterization, KRAS mutation is enriched in the proimmune subset, while the protumoral one gathers mutations in ARID1A and ALK. Squamous cell carcinomas (N=98) cluster in 4 groups with two main immunophenotypes. Critical factors of this clustering are TRIM29, FOXM1, KRT5, TOP2A, MKI67, TFRC, CCNB2, CD44, EGFR, KREMEN1. The proimmune tumors upregulate genes involved in immune signaling (CD3D, CD3E, CD3G, CD79A, CD79B), activation (CD40LG, CD27, MS4A1), chemoattraction (CXCR5, CXCL13), antigen presentation (CD1C, HLA-DMA/DPB1/DRA/DMB/DOB), inflammatory cytokines (IFNG, IL17F, IL21), immune cells (CD8A, CD19) and immunomodulation (ICOS). Contrarily, the protumoral samples upregulate genes related to cell cycle (FOXM1, BUB1, CCNB2, CDK1), immune cells (FOXP3), angiogenesis (VEGFA), apoptosis (BCL2), immunomodulation (PD-L1) and proliferation (AKT1, MTOR, MYC, PIK3CA, MKI67). Of note, the proimmune subset has higher infiltration of CD8+, CD4+ and B cells. The protumoral one accrues mutations in TFRC, PIK3CA, PIK3CB, FGF3, FGF10. In conclusion, we performed a comprehensive description of novel NSCLC subgroups based on multiparametric data that will improve prediction of response to immunotherapy. Citation Format: Javier Ramos-Paradas, David Gomez-Sanchez, Aranzazu Rosado, Irene Ferrer, Nuria Carrizo, Ana B. Enguita, Maria T. Muñoz, Urbicio Perez-Gonzalez, Ivan Martinez, Luis Paz-Ares, Eva M. Garrido-Martin. Comprehensive multiparametric analysis of non-small cell lung cancer describes novel genotype-immunophenotype relationships and provides putative biomarker signatures of response to checkpoint blockade [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2006.

This study was supported by the Centro de Investigacion Biomedica en Red—Area de Oncologia—del Instituto de Salud Carlos III (CIBERONC; CB16/12/00369; and CB16/12/00489), Instituto de Salud Carlos III/Subdireccion General de Investigacion Sanitaria (FIS No. PI13/02196), Asociacion Espanola Contra el Cancer (GCB120981SAN and the Accelerator Award), CRIS against Cancer foundation grant 2014/0120, and the Black Swan Research Initiative of the International Myeloma Foundation.

Abstract Introduction High-throughput sequencing studies have rendered seminal knowledge in monoclonal gammopathies such as multiple myeloma (MM) and Waldenström's macroglobulinemia (WM). Unfortunately, the low incidence of AL amyloidosis and its typically low tumor burden, often masked by a polyclonal plasma cell (PC) background, account for the limited information on its tumor cell biology. Thus, it remains unknown if AL amyloidosis harbors a unifying mutation as occurs in WM or if, in its absence, there are recurrent mutations and if these overlap with those observed in MM. With this background , the aim of this study is to perform a whole exome sequencing (WES) in a series of patients with AL amyloidosis and to compare mutational profiles in AL amyloidosis vs MM and analyze the copy number variation in this series of patients. Methods A total of 27 patients with confirmed diagnosis of AL were included. WES was performed in 56 paired samples of FACSorted bone marrow tumor plasma cells and peripheral blood mononucleated cells. Each tumor sample was captured in triplicate using Agilent's SureSelect Human All Exon V6 + UTR kit and sequenced on the Illumina NextSeq 500 platform. Data was analyzed with Strelka software to discard germinal mutations, ANNOVAR for functional annotation, and a data reduction strategy to identify candidate variants. The mutational signature was analyzed with Mutational Signatures in Cancer (MuSiCa) software. We used the MMRF CoMMpass dataset (895 patients) to compare the mutational landscape of MM vs AL. We also determined immunoglobulin gene rearrangements in AL by next generation sequencing. Besides, we analyzed the copy number variation (CNV) with CNVkit program. Results The mean depth coverage for control and tumor samples was 64x and 186x, respectively. A total of 1983 somatic SNV and 133 INDEL were identified, with an average of 71 (20-281) SNV and 5 (0-25) INDEL per patient. Overall, the most frequently mutated genes in this series were IGLL5 and MUC16 (recurrence of 17% each). When compared to MM (average of 66 SNV and 2,5 INDEL), we observed a similar mutational load. However, none of the most frequently mutated genes in MM (i.e. KRAS, NRAS, FAM46C, BRAF, TP53, DIS3, PRDM1, SP140, RGR1, TRAF3, ATM,CCND1, HISTH1E, LTB, IRF4, FGFR3,RB1, ACTG1, CYLD, MAX, ATR) were recurrently mutated in patients with AL. The only genes commonly mutated in AL amyloidosis and MM were MUC16 (recurrence of 17% and 8%, respectively) and IGLL5 (recurrence of 17% each).Most patients with AL harbored between 1 and 8 mutational signatures, implying that multiple mutational processes are operative. The most frequent mutational signature were (signatures 6, 15 and 20) associated with mismatch repair protein deficiency (MMR) and high microsatellite instability (93%), mutational signature 2 (89%), related with the aberrant activity of APOBECs, a family of proteins that enzymatically modify single-stranded DNA and mutational signature 1 (81%), profile that appear in all types of cancers and has been correlated with the age of cancer diagnosis. The signature 2 is also representative of MM. Regarding the immunoglobulin gene repertoire, we noted that 26% of patients with AL harbored more than one clone; this extent in clonal heterogeneity being similar to that found in MM (23%).The most frequent IGH gene involved was IGHV3-30 in both AL (recurrence of 10%) and MM (recurrence of 12%).Regarding CNV, recurrent gains included chromosomes 1q (29%), 5 (38%), 6p (14%), 7 (43%), 9 (43%), 15 (24%), 18 (14%) and 19 (43%). Recurrent losses affected chromosome 13 (33%), 6q (14%) and 16q (19%). Conclusions This is the first WES study performed in a series of patients with AL. We demonstrated the lack of a common driver mutation in this disease and unveiled that recurrently mutated genes in AL amyloidosis do not overlap with those observed in MM. We also confirm the existence of numerous chromosomal alterations in patients with AL. The frequencies of aberrations and alterations detected by NGS are comparable with those describe in previous studies by copy number array analysis, but here we show some novel recurrent chromosomal aberrations as gain of chromosome 7 (43%) and losses of chromosome 18 (14%). Overall, these results may have significant impact in our understanding of the pathogenesis of AL amyloidosis and its differential diagnosis vs other monoclonal gammopathies. Disclosures Ocio: BMS: Consultancy; Novartis: Consultancy, Honoraria; Sanofi: Research Funding; Takeda: Consultancy, Honoraria; Seattle Genetics: Consultancy; AbbVie: Consultancy; Janssen: Consultancy, Honoraria; Pharmamar: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; Mundipharma: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Array Pharmaceuticals: Research Funding. De La Rubia:Ablynx: Consultancy, Other: Member of Advisory Board. Oriol:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Puig:Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Celgene: Honoraria, Research Funding. Lahuerta:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Mateos:Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. San-Miguel:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; BMS: Honoraria; Novartis: Honoraria; Sanofi: Honoraria; Roche: Honoraria. Martinez Lopez:Novartis: Research Funding, Speakers Bureau; Jansen: Research Funding, Speakers Bureau; BMS: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau.

A broad clinical applicability of some next-generation sequencing (NGS) assays might be limited by analytic difficulties and tissue amount requirements. We successfully applied an amplicon-based NGS panel in advanced non-small-cell lung cancers (NSCLCs; n = 109). In nonsquamous tumors, immunohistochemistry tests for ALK and ROS1 with DNA NGS were combined. Forty NSCLCs had actionable mutations and 10 patients received tailored treatments. Introduction: A substantial fraction of non-small-cell lung cancers (NSCLCs) harbor targetable genetic alterations. In this study, we analyzed the feasibility and clinical utility of integrating a next-generation sequencing (NGS) panel into our routine lung cancer molecular subtyping algorithm.Patients and Methods: After routine pathologic and molecular subtyping, we implemented an amplicon-based gene panel for DNA analysis covering mutational hot spots in 22 cancer genes in consecutive advanced-stage NSCLCs. Results: We analyzed 109 tumors using NGS between December 2014 and January 2016. Fifty-six patients (51%) were treatment-naive and 82 (75%) had lung adenocarcinomas. In 89 cases (82%), we used samples derived from lung cancer diagnostic procedures. We obtained successful sequencing results in 95 cases (87%). As part of our routine lung cancer molecular subtyping protocol, single-gene testing for EGFR, ALK, and ROS1 was attempted in nonsquamous and 3 squamous-cell cancers (n = 92). Sixty-nine of 92 samples (75%) had sufficient tissue to complete ALK and ROS1 immunohistochemistry (IHC) and NGS. With the integration of the gene panel, 40 NSCLCs (37%) in the entire cohort and 30 NSCLCs (40%) fully tested for ALK and ROS1 IHC and NGS had actionable mutations. KRAS (24%) and EGFR (10%) were the most frequently mutated actionable genes. Ten patients (9%) received matched targeted therapies, 6 (5%) in clinical trials. Conclusion: The combination of IHC tests for ALK and ROS1 and amplicon-based NGS is applicable in routine clinical practice, enabling patient selection for genotype-tailored treatments. Copyright (C) 2017 Elsevier Inc. All rights reserved.