Lenalidomide plus R-GDP (R2-GDP) in relapsed/ refractory diffuse large B-cell lymphoma: final results of the R2-GDP-GOTEL trial and immune biomarker subanalysis

Artículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración, si le hubiere, y los autores pertenecientes a la UAMPurpose: New therapeutic options are needed in relapsed/refracResults: After a median follow-up of 37 months, ORR was tory diffuse large B-cell lymphoma (R/R DLBCL). Lenalidomide-60.2% [37.1% complete responses (CR) and 23.1% partial based schedules can reverse rituximab refractoriness in lymphoma. responses (PR)]. Median OS was 12 months (47 vs. 6 months Patients and Methods: In the phase II R2-GDP trial, 78 in CR vs. no CR); median PFS was 9 months (34 vs. 5 months in patients unsuitable for autologous stem cell transplant received CR vs. no CR). In the primary refractory population, ORR was treatment with the following schedule: lenalidomide 10 mg Days 45.5% (21.2% CR and 24.3% PR). Most common grade 3–4 (D)1–14, rituximab 375 mg/m2 D1, cisplatin 60 mg/m2 D1, adverse events were thrombocytopenia (60.2%), neutropenia gemcitabine 750 mg/m2 D1 and D8, and dexamethasone 20 mg (60.2%), anemia (26.9%), infections (15.3%), and febrile neutroD1–3, up to 6 cycles (induction phase), followed by lenalidomide penia (14.1%). Complete responses were associated with a sharp 10 mg (or last lenalidomide dose received) D1–21 every 28 days decrease in circulating myeloid-derived suppressor cells and (maintenance phase). Primary endpoint was overall response regulatory T cells. rate (ORR). Secondary endpoints included progression-free Conclusions: R2-GDP schedule is feasible and highly active survival (PFS), overall survival (OS), safety, and monitorization in R/R DLBCL, including the primary refractory population. of key circulating immune biomarkers (EU Clinical Trials Reg-Immune biomarkers showed differences in responders versus ister number: EudraCT 2014-001620-29). progressorsThis research was funded by the Spanish Lymphoma Oncology Group (GOTEL) with the financial support of Celgene (Investigator Initiated Trials Program); no grant numbers applicable. L. Hontecillas-Prieto is supported by the Consejería de Salud y Familias, Junta de Andalucía (RH-0047-2021). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fac

Genomic analyses of microdissected Hodgkin and Reed-Sternberg cells: mutations in epigenetic regulators and p53 are frequent in refractory classic Hodgkin lymphoma

This work was supported by grants from the Plan Nacional de I + D + I cofinanced by the ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER), PI12/1832, the Spanish Association for Cancer Research (AECC), and Programas para Grupos de Investigación de la Comunidad Autónoma de Madrid (Biomedicina 2017)

Determination of essential biomarkers in lung cancer: a real-world data study in Spain with demographic, clinical, epidemiological and pathological characteristics

Artículo escrito por un elevado número de autores, sólo se referencia el que aparece en primer lugar y los autores pertenecientes a la UAMThe survival of patients with lung cancer has substantially increased in the last decade by about 15%. This increase is, basically, due to targeted therapies available for advanced stages and the emergence of immunotherapy itself. This work aims to study the situation of biomarker testing in Spain. The Thoracic Tumours Registry (TTR) is an observational, prospective, registry-based study that included patients diagnosed with lung cancer and other thoracic tumours, from September 2016 to 2020. This TTR study was sponsored by the Spanish Lung Cancer Group (GECP) Foundation, an independent, scientific, multidisciplinary oncology society that coordinates more than 550 experts and 182 hospitals across the Spanish territory. Nine thousand two hundred thirty-nine patients diagnosed with stage IV non-small cell lung cancer (NSCLC) between 2106 and 2020 were analysed. 7,467 (80.8%) were non-squamous and 1,772 (19.2%) were squamous. Tumour marker testing was performed in 85.0% of patients with non-squamous tumours vs 56.3% in those with squamous tumours (p-value < 0.001). The global testing of EGFR, ALK, and ROS1 was 78.9, 64.7, 35.6% respectively, in non-squamous histology. PDL1 was determined globally in the same period (46.9%), although if we focus on the last 3 years it exceeds 85%. There has been a significant increase in the last few years of all determinations and there are even close to 10% of molecular determinations that do not yet have targeted drug approval but will have it in the near future. 4,115 cases had a positive result (44.5%) for either EGFR, ALK, KRAS, BRAF, ROS1, or high PDL1. Despite the lack of a national project and standard protocol in Spain that regulates the determination of biomarkers, the situation is similar to other European countries. Given the growing number of different determinations and their high positivity, national strategies are urgently needed to implement next-generation sequencing (NGS) in an integrated and cost-effective way in lung cancerThis study was supported by the European Union Horizon 2020 Research and Innovation Program under grant agreement n° 875160 CLARIFY projec

Use of a tyrosine kinase inhibitor as neoadjuvant therapy for non-small cell lung cancer: A case report

We report here a 66-year-old woman diagnosed with bronchioloalveolar carcinoma of the right lung cT4N2M0. The patient was from the Philippines, had never smoked, and tested positive for an EGFR mutation. She received gefitinib as neoadjuvant therapy for two months and displayed a partial response. The tumour was resected by performing a right pneumonectomy. The residual viable tumour accounted for less than 10%. Adjuvant chemotherapy with carboplatin-taxol was administered for four cycles. Fifteen months post-surgery, two brain metastases were found. Gefitinib was prescribed, and one month later complete radiological response was assessed. The patient remains asymptomatic and without visible disease four months later. Controlled randomised trials are needed to clarify the role of these target therapies in the neoadjuvant settin

Clinical and molecular parameters associated to pneumonitis development in non-small-cell lung cancer patients receiving chemoimmunotherapy from NADIM trial

Background Pneumonitis (Pn) is one of the main immune-related adverse effects, having a special importance in lung cancer, since they share affected tissue. Despite its clinical relevance, Pn development remains an unpredictable treatment adverse effect, whose mechanisms are mainly unknown, being even more obscure when it is associated to chemoimmunotherapy.Methods In order to identify parameters associated to treatment related Pn, we analyzed clinical variables and molecular parameters from 46 patients with potentially resectable stage IIIA non-small-cell lung cancer treated with neoadjuvant chemoimmunotherapy included in the NADIM clinical trial (NCT03081689). Pn was defined as clinical or radiographic evidence of lung inflammation without alternative diagnoses, from treatment initiation to 180 days. Results Among 46 patients, 12 developed Pn (26.1%). Sex, age, smoking status, packs-year, histological subtype, clinical or pathological response, progression free survival, overall survival and number of nivolumab cycles, were not associated to Pn development. Regarding molecular parameters at diagnosis, Pn evelopment was not associated to programmed death ligand 1, TPS, T cell receptor repertoire parameters, or tumor mutational burden. However, patients who developed Pn had statistically significant lower blood median levels of platelet to monocyte ratio (p=0.012) and teratocarcinoma derived growth factor 1 (p=0.013; area under the curve (AUC) 0.801), but higher median percentages of natural killers (NKs) (p=0.019; AUC 0.786), monocytes (p=0.017; AUC 0.791), MSP (p=0.006; AUC 0.838), PARN (p=0.017; AUC 0.790), and E-Cadherin (p=0.022; AUC 0.788). In addition, the immune scenario of Pn after neoadjuvant treatment involves: high levels of neutrophils and NK cells, but low levels of B and T cells in peripheral blood; increased clonality of intratumoral T cells; and elevated plasma levels of several growth factors (EGF, HGF, VEGF, ANG-1, PDGF, NGF, and NT4) and inflammatory cytokines (MIF, CCL16, neutrophil gelatinase-associated lipocalin, BMP-4, and u-PAR). Conclusions Although statistically underpowered, our results shed light on the possible mechanisms behind Pn development, involving innate and adaptative immunity, and open the possibility to predict patients at high risk. If confirmed, this may allow the personalization of both, the surveillance strategy and the therapeutic approaches to manage Pn in patients receiving chemoimmunotherapy

Integrating speculation detection and deep learning to extract lung cancer diagnosis from clinical notes

Despite efforts to develop models for extracting medical concepts from clinical notes, there are still some challenges in particular to be able to relate concepts to dates. The high number of clinical notes written for each single patient, the use of negation, speculation, and different date formats cause ambiguity that has to be solved to reconstruct the patient’s natural history. In this paper, we concentrate on extracting from clinical narratives the cancer diagnosis and relating it to the diagnosis date. To address this challenge, a hybrid approach that combines deep learning-based and rule-based methods is proposed. The approach integrates three steps: (i) lung cancer named entity recognition, (ii) negation and speculation detection, and (iii) relating the cancer diagnosis to a valid date. In particular, we apply the proposed approach to extract the lung cancer diagnosis and its diagnosis date from clinical narratives written in Spanish. Results obtained show an F-score of 90% in the named entity recognition task, and a 89% F-score in the task of relating the cancer diagnosis to the diagnosis date. Our findings suggest that speculation detection is together with negation detection a key component to properly extract cancer diagnosis from clinical notesThis work is supported by the EU Horizon 2020 innovation program under grant agreement No. 780495, project BigMedilytics (Big Data for Medical Analytics). It has been also supported by Fundación AECC and Instituto de Salud Carlos III (grant AC19/00034), under the frame of ERA-NET PerMe