Search

Follicular lymphoma (FL) is the most frequent indolent lymphoma. Some patients (10%-15%) experience histologic transformation (HT) to a more aggressive lymphoma, usually diffuse large B-cell lymphoma (DLBCL). This study aimed to validate and improve a genetic risk model to predict HT at diagnosis.We collected mutational data from diagnosis biopsies of 64 FL patients. We combined them with the data from a previously published cohort (total n = 104; 62 from nontransformed and 42 from patients who did transform to DLBCL). This combined cohort was used to develop a nomogram to estimate the risk of HT. Prognostic mutated genes and clinical variables were assessed using Cox regression analysis to generate a risk model. The model was internally validated by bootstrapping and externally validated in an independent cohort. Its performance was evaluated using a concordance index and a calibration curve. The clinicogenetic nomogram included the mutational status of 3 genes (HIST1HE1, KMT2D, and TNFSR14) and high-risk Follicular Lymphoma International Prognostic Index and predicted HT with a concordance index of 0.746. Patients were classified as being at low or high risk of transformation. The probability HT function at 24 months was 0.90 in the low-risk group vs 0.51 in the high-risk group and, at 60 months, 0.71 vs 0.15, respectively. In the external validation cohort, the probability HT function in the low-risk group was 0.86 vs 0.54 in the high-risk group at 24 months, and 0.71 vs 0.32 at 60 months. The concordance index in the external cohort was 0.552. In conclusion, we propose a clinicogenetic risk model to predict FL HT to DLBLC, combining genetic alterations in HIST1H1E, KMT2D, and TNFRSF14 genes and clinical features (Follicular Lymphoma International Prognostic Index) at diagnosis. This model could improve the management of FL patients and allow treatment strategies that would prevent or delay transformation., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Cancer-derived small extracellular vesicles (sEVs) are capable of modifying the tumor microenvironment and promoting tumor progression. Ovarian cancer (OvCa) is a lethal malignancy that preferentially spreads through the abdominal cavity. Thus, the secretion of such vesicles into the peritoneal fluid could be a determinant factor in the dissemination and behavior of this disease. We designed a prospective observational study to assess the impact of peritoneal fluid-derived sEVs (PFD-sEVs) in OvCa clinical outcome. For this purpose, 2 patient cohorts were enrolled: patients with OvCa who underwent a diagnostic or cytoreductive surgery and nononcological patients, who underwent abdominal surgery for benign gynecological conditions and acted as the control group. Systematic extraction of PFD-sEVs from surgical samples enabled us to observe significant quantitative and qualitative differences associated with cancer diagnosis, disease stage, and platinum chemosensitivity. Proteomic profiling of PFD-sEVs led to the identification of molecular pathways and proteins of interest and to the biological validation of S100A4 and STX5. In addition, unsupervised analysis of PFD-sEV proteomic profiles in high-grade serous ovarian carcinomas (HGSOCs) revealed 2 clusters with different outcomes in terms of overall survival. In conclusion, comprehensive characterization of PFD-sEV content provided a prognostic value with potential implications in HGSOC clinical management.

Purpose: Follicular lymphoma (FL) is the most frequent indolent non-Hodgkin lymphoma. Around 20% of patients suffer early disease progression within 24 months (POD24) of diagnosis. This study examined the significance of circulating tumor DNA (ctDNA) in predicting response to therapy and POD24 in patients with FL., Experimental Design: We collected 100 plasma samples, before and during the treatment, from 36 patients with FL prospectively enrolled in 8 Spanish hospitals. They were treated with a chemotherapy-rituximab regimen and followed up for a median of 3.43 years. We performed targeted deep sequencing in cell-free DNA (cfDNA) and tumor genomic DNA from 31 diagnostic biopsy samples., Results: Of the alterations detected in the diagnostic tissue samples, 73% (300/411) were also identified in basal cfDNA. The mean numbers of alterations per basal cfDNA sample in patients who suffered progression of disease within 24 months (POD24-pos) or did not achieve complete response (non-CR) were significantly higher than in POD24-neg or CR patients (unpaired samples t test, P = 0.0001 and 0.001, respectively). Pretreatment ctDNA levels, as haploid genome equivalents per milliliter of plasma, were higher in patients without CR (P = 0.02) and in POD24-pos patients compared with POD24-neg patients (P < 0.001). Dynamic analysis showed that ctDNA levels decreased dramatically after treatment, although the reduction was more significant in patients with CR and POD24-neg patients., Conclusions: Basal ctDNA levels are associated with the risk of early progression and response to treatment in FL. cfDNA monitoring and genotyping during treatment and follow-up predict response to treatment and early progression., (©2022 The Authors; Published by the American Association for Cancer Research.)

The endocannabinoid system (ECS), a signalling network with immunomodulatory properties, is a potential therapeutic target in multiple sclerosis (MS). Dimethyl fumarate (DMF) is an approved drug for MS whose mechanism of action has not been fully elucidated; the possibility exists that its therapeutic effects could imply the ECS. With the aim of studying if DMF can modulate the ECS, the endocannabinoids 2-arachidonoylglycerol (2-AG), anandamide (AEA), oleoylethanolamide (OEA) and palmitoylethanolamide (PEA) were determined by liquid chromatography-mass spectrometry in peripheral blood mononuclear cells from 21 healthy donors (HD) and 32 MS patients at baseline and after 12 and 24 months of DMF treatment. MS patients presented lower levels of 2-AG and PEA compared to HD. 2-AG increased at 24 months, reaching HD levels. AEA and PEA remained stable at 12 and 24 months. OEA increased at 12 months and returned to initial levels at 24 months. Patients who achieved no evidence of disease activity (NEDA3) presented the same modulation over time as EDA3 patients. PEA was modulated differentially between females and males. Our results show that the ECS is dysregulated in MS patients. The increase in 2-AG and OEA during DMF treatment suggests a possible role of DMF in ECS modulation., (© 2022. The Author(s).)

Background: Neoadjuvant chemoimmunotherapy for non-small cell lung cancer (NSCLC) has improved pathological responses and survival rates compared with chemotherapy alone, leading to Food and Drug Administration (FDA) approval of nivolumab plus chemotherapy for resectable stage IB-IIIA NSCLC (AJCC 7th edition) without ALK or EGFR alterations. Unfortunately, a considerable percentage of tumors do not completely respond to therapy, which has been associated with early disease progression. So far, it is impossible to predict these events due to lack of knowledge. In this study, we characterized the gene expression profile of tumor samples to identify new biomarkers and mechanisms behind tumor responses to neoadjuvant chemoimmunotherapy and disease recurrence after surgery., Methods: Tumor bulk RNA sequencing was performed in 16 pretreatment and 36 post-treatment tissue samples from 41 patients with resectable stage IIIA NSCLC treated with neoadjuvant chemoimmunotherapy from NADIM trial. A panel targeting 395 genes related to immunological processes was used. Tumors were classified as complete pathological response (CPR) and non-CPR, based on the total absence of viable tumor cells in tumor bed and lymph nodes tested at surgery. Differential-expressed genes between groups and pathway enrichment analysis were assessed using DESeq2 and gene set enrichment analysis. CIBERSORTx was used to estimate the proportions of immune cell subtypes., Results: CPR tumors had a stronger pre-established immune infiltrate at baseline than non-CPR, characterized by higher levels of IFNG, GZMB, NKG7 , and M1 macrophages, all with a significant area under the receiver operating characteristic curve (ROC) >0.9 for CPR prediction. A greater effect of neoadjuvant therapy was also seen in CPR tumors with a reduction of tumor markers and IFNγ signaling after treatment. Additionally, the higher expression of several genes, including AKT1, BST2, OAS3, or CD8B ; or higher dendritic cells and neutrophils proportions in post-treatment non-CPR samples, were associated with relapse after surgery. Also, high pretreatment PD-L1 and tumor mutational burden levels influenced the post-treatment immune landscape with the downregulation of proliferation markers and type I interferon signaling molecules in surgery samples., Conclusions: Our results reinforce the differences between CPR and non-CPR responses, describing possible response and relapse immune mechanisms, opening the possibility of therapy personalization of immunotherapy-based regimens in the neoadjuvant setting of NSCLC., Competing Interests: Competing interests: MP reports non-financial support (reagents for TCR sequencing) from ThermoFisher; grants, personal fees and non-financial support from BMS; grants, personal fees and non-financial support from ROCHE; grants, personal fees and non-financial support from ASTRAZENECA; personal fees from MSD; personal fees from TAKEDA; outside the submitted work. EN grants or contracts: Roche, Pfizer, Merck-Serono, BMS, and Nanostring. Consulting fees: Roche, BMS, MSD, Merck-Serono, Pfizer, Lilly, Amgen, Boehringer, AstraZeneca, Takeda, Bayer, and Sanofi. Payment honoraria: Roche, BMs, MSD, Merck-Serono, Pfizer, Lilly, Amgen, Boehringer, Astrazeneca, Takeda, Bayer, and Sanofi. Support For attending meetings and travel: MSD, Roche, and BMS. AI consulting fees: Pfizer, Amgen, and AstraZeneca. Payment for expert testimony: Bristol, Pfizer, Takeda, Roche, and AstraZeneca. Support for attending meetings or travels: Roche and Bristol. MRG-C reports personal fees from BMS, personal fees from MSD, personal fees from Roche, personal fees from Pfizer, personal fees from AstraZeneca, outside the submitted work; ML-Q: payment for honoraria: BMS, MSD, Ipsen, Astella, AstraZeneca, and Pfizer. Support for attendings meetings/travels: MSD, Takeda, Janssen, Pfizer, and BMS. MD reports personal fees from Astra-Zeneca, personal fees from BMS, personal fees from Boehringer Ingelheim, personal fees from MSD, personal fees from Pfizer, personal fees from Roche, outside the submitted work; MM reports grants and personal fees from BMS, personal fees and non-financial support from MSD, personal fees and non-financial support from Boehringer Ingelheim; personal fees, non-financial support, and other from AstraZeneca; personal fees, non-financial support, and other from Roche; personal fees from Kyowa Kyrin; personal fees from Pierre Fabre, outside the submitted work; DR-A: consulting fees: Roche, AstraZeneca, BMS, MSD, Lilly, Pfizer, and Novartis. Payment for honoraria: Roche, Astrazeneca, BMS, MSD, Lilly, Pfizer, and Novartis. Support for attending meetings/travels: Roche, MSD, and Novartis; AM-M: advisory board: AstraZeneca, BMS, Roche, MSD, and Pfizer. Speaker's bureau: AstraZeneca, BMS, Roche, MSD, and Pfizer. Support for attending meetings or travel: AstraZeneca, BMS, Roche, MSD, Pfizer, and Lilly. Payment for expert testimony: AstraZeneca. Steering committee member: AstraZeneca. JDCC reports personal fees from Astra Zeneca, personal fees from Boehringer Ingelheim, personal fees from Merck Sharp and Dohme, personal fees from Hoffmann-la Roche, personal fees from Bristol-Myers Squibb, personal fees from Takeda, personal fees from Pfizer, personal fees from Novartis, outside the submitted work; IBA reports consulting or advisory board for Bristol Myers, Takeda, Roche, AstraZeneca, and Behringer Inngelheim; BM reports grants and personal fees from Roche, personal fees and other from BMS, personal fees from Takeda, other from MSD, personal fees from Boehringer, other from Takeda, outside the submitted work; AR: consulting fees: AstraZeneca. Payment or honoraria: Vivo diagnóstico. Advisory board: Takeda. VC: payment or honoraria: Roche, BMS, MSD, AstraZeneca, and Boehringer., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Diffuse large B-cell lymphoma (DLBCL), the most frequent non-Hodgkin's lymphoma subtype, is characterized by strong biological, morphological, and clinical heterogeneity, but patients are treated with immunochemotherapy in a relatively homogeneous way. Here, we have used a customized NanoString platform to analyze a series of 197 homogeneously treated DLBCL cases. The platform includes the most relevant genes or signatures known to be useful for predicting response to R-CHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone) in DLBCL cases. We generated a risk score that combines the International Prognostic Index with cell of origin and double expression of MYC/BCL2 , and stratified the series into three groups, yielding hazard ratios from 0.15 to 5.49 for overall survival, and from 0.17 to 5.04 for progression-free survival. Group differences were highly significant ( p  < 0.0001), and the scoring system was applicable to younger patients (<60 years of age) and patients with advanced or localized stages of the disease. Results were validated in an independent dataset from 166 DLBCL patients treated in two distinct clinical trials. This risk score combines clinical and biological data in a model that can be used to integrate biological variables into the prognostic models for DLBCL cases., Competing Interests: M.A.P. declares having received lecture fees and advisory board fees from Millennium/Takeda, Jansen, NanoString, Kyowa Kirin, Gilead, and Celgene.The authors declare that they have no significant relationships with, or financial interests, in any commercial companies pertaining to this article., (© 2022 The Authors. eJHaem published by British Society for Haematology and John Wiley & Sons Ltd.)

Peripheral T-cell lymphoma (PTCL) is a clinically aggressive disease, with a poor response to therapy and a low overall survival rate of approximately 30% after 5 years. We have analyzed a series of 105 cases with a diagnosis of PTCL using a customized NanoString platform (NanoString Technologies, Seattle, WA) that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways, and stromal cell subpopulations. A comparative analysis of the various histological types of PTCL (angioimmunoblastic T-cell lymphoma [AITL]; PTCL with T follicular helper [TFH] phenotype; PTCL not otherwise specified [NOS]) showed that specific sets of genes were associated with each of the diagnoses. These included TFH markers, cytotoxic markers, and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells, and genes belonging to precise survival (NF-κB) and other pathways. Furthermore, the mutational profile was analyzed using a custom panel that targeted 62 genes in 76 cases distributed in AITL, PTCL-TFH, and PTCL-NOS. The main differences among the 3 nodal PTCL classes involved the RHOAG17V mutations (P < .0001), which were approximately twice as frequent in AITL (34.09%) as in PTCL-TFH (16.66%) cases but were not detected in PTCL-NOS. A multivariate analysis identified gene sets that allowed the series of cases to be stratified into different risk groups. This study supports and validates the current division of PTCL into these 3 categories, identifies sets of markers that can be used for a more precise diagnosis, and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL., (© 2021 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Lymphoma research is a paradigm of the integration of basic and clinical research within the fields of diagnosis and therapy. Clinical, phenotypic, and genetic data are currently used to predict which patients could benefit from standard treatment. However, alternative therapies for patients at higher risk from refractoriness or relapse are usually empirically proposed, based on trial and error, without considering the genetic complexity of aggressive B-cell lymphomas. This is primarily due to the intricate mosaic of genetic and epigenetic alterations in lymphomas, which are an obstacle to the prediction of which drug will work for any given patient. Matching a patient's genes to drug sensitivity by directly testing live tissues comprises the "precision medicine" concept. However, in the case of lymphomas, this concept should be expanded beyond genomics, eventually providing better treatment options for patients in need of alternative therapeutic approaches. We provide an overview of the most recent findings in diffuse large B-cell lymphomas genomics, from the classic functional models used to study tumor biology and the response to experimental treatments using cell lines and mouse models, to the most recent approaches with spheroid/organoid models. We also discuss their potential relevance and applicability to daily clinical practice.

Circulating recombinant forms (CRFs) contribute substantially to the HIV-1 pandemic. Among 105 CRFs described in the literature, 16 are BF intersubtype recombinants, most of South American origin, of which CRF12&#95;BF is the most widely spread. A BF recombinant cluster identified in Bolivia was suggested to represent a new CRF&#95;BF. Here we find that it belongs to a larger cluster incorporating 39 viruses collected in 7 countries from 3 continents, 22 of them in Spain, most from Bolivian or Peruvian individuals, and 12 in South America (Bolivia, Argentina, and Peru). This BF cluster comprises three major subclusters, two associated with Bolivian and one with Peruvian individuals. Near full-length genome sequence analyses of nine viruses, collected in Spain, Bolivia, and Peru, revealed coincident BF mosaic structures, with 13 breakpoints, 6 and 7 of which coincided with CRF12&#95;BF and CRF17&#95;BF, respectively. In a phylogenetic tree, they grouped in a clade closely related to these CRFs, and more distantly to CRF38&#95;BF and CRF44&#95;BF, all circulating in South America. These results allowed to identify a new HIV-1 CRF, designated CRF89&#95;BF. Through phylodynamic analyses, CRF89&#95;BF emergence was estimated in Bolivia around 1986. CRF89&#95;BF is the fifth CRF member of the HIV-1 recombinant family related to CRF12&#95;BF.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease whose prognosis is associated with clinical features, cell-of-origin and genetic aberrations. Recent integrative, multi-omic analyses had led to identifying overlapping genetic DLBCL subtypes. We used targeted massive sequencing to analyze 84 diagnostic samples from a multicenter cohort of patients with DLBCL treated with rituximab-containing therapies and a median follow-up of 6 years. The most frequently mutated genes were IGLL5 (43%), KMT2D (33.3%), CREBBP (28.6%), PIM1 (26.2%), and CARD11 (22.6%). Mutations in CD79B were associated with a higher risk of relapse after treatment, whereas patients with mutations in CD79B, ETS1, and CD58 had a significantly shorter survival. Based on the new genetic DLBCL classifications, we tested and validated a simplified method to classify samples in five genetic subtypes analyzing the mutational status of 26 genes and BCL2 and BCL6 translocations. We propose a two-step genetic DLBCL classifier (2-S), integrating the most significant features from previous algorithms, to classify the samples as N1 2-S , EZB 2-S , MCD 2-S , BN2 2-S , and ST2 2-S groups. We determined its sensitivity and specificity, compared with the other established algorithms, and evaluated its clinical impact. The results showed that ST2 2-S is the group with the best clinical outcome and N1 2-S , the more aggressive one. EZB 2-S identified a subgroup with a worse prognosis among GCB-DLBLC cases.