Managing the inflammatory response to SARS-Cov-2 could prevent respiratory insufficiency. Cytokine profiles could identify cases at risk of severe disease.
We designed a randomized phase II clinical ...trial to determine whether the combination of ruxolitinib (5 mg twice a day for 7 days followed by 10 mg BID for 7 days) plus simvastatin (40 mg once a day for 14 days), could reduce the incidence of respiratory insufficiency in COVID-19. 48 cytokines were correlated with clinical outcome.
Patients admitted due to COVID-19 infection with mild disease.
Up to 92 were included. Mean age was 64 ± 17, and 28 (30%) were female. 11 (22%) patients in the control arm and 6 (12%) in the experimental arm reached an OSCI grade of 5 or higher (p = 0.29). Unsupervised analysis of cytokines detected two clusters (CL-1 and CL-2). CL-1 presented a higher risk of clinical deterioration vs CL-2 (13 33% vs 2 6% cases, p = 0.009) and death (5 11% vs 0 cases, p = 0.059). Supervised Machine Learning (ML) analysis led to a model that predicted patient deterioration 48h before occurrence with a 85% accuracy.
Ruxolitinib plus simvastatin did not impact the outcome of COVID-19. Cytokine profiling identified patients at risk of severe COVID-19 and predicted clinical deterioration.
https://clinicaltrials.gov/, identifier NCT04348695.
Although certain genetic alterations have been defined as predictive and prognostic biomarkers in the context of ovarian cancer (OC), data science methods represent alternative approaches to identify ...novel correlations and define relevant markers in these gynecological tumors. Considering this potential, our work focused both on clinical and genomic data information collected from patients with OC to identify relationships between clinical and genetic factors and disease progression-related variables. For this aim, we proposed two analyses: (1) a nonlinear exploration of an OC dataset using autoencoders, a type of neural network that can be used as a feature extraction tool to represent a dataset in 3-dimensional latent space, so that we could assess whether there are intrinsic or natural nonlinear separability patterns between disease progression groups (in our case, platinum-sensitive and platinum-resistant groups); and (2) the identification of relevant variable relationships by means of an adaptation of the informative variable identifier (IVI), a feature selection method that labels each input feature as informative or noisy with respect to the task at hand, identifies the relationships among features, and builds a ranking of features, allowing us to study which input features and relationships may be most informative for the OC disease progression classification to define new biomarkers involved in disease progression. Our interest has been in clinical and genetic factors and in the combination of clinical features and genetic profile. Results with autoencoders suggest a pattern of separability between disease progression groups in the clinical part and for the combination of genes and clinical features of the OC dataset, that is increased via supervised fine tuning. In the genetic part, this pattern of separability is not observed, but it is more defined when a supervised fine tuning is performed. Results of the IVI-mediated feature selection method show significance for relevant clinical variables (such as type of surgery and neoadjuvant chemotherapy), some mutation genes, and low-risk genetic features. These results highlight the efficacy of the considered approaches to better understand the clinical course of OC.
•Data science methods are suitable for identifying biomarkers in OC.•Feature selection methods show predictive roles of variables in an OC dataset.•Features extraction methods reveal some patterns of separability in an OC dataset.
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.
Fibroblast growth factor receptor (FGFR) genomic alterations (GAs) represent an actionable target, key to the pathogenesis of some urothelial cancers (UCs). Though FGFR GAs are common in noninvasive ...UC, little is known about their role in the metastatic(m) setting and response to therapy. This study aimed to assess the impact of FGFR alterations on sensitivity to systemic treatments and survival and to validate Bajorin’s and Bellmunt’s prognostic scores in mUC patients according to their FGFR status. We retrospectively analyzed data from 98 patients with tumor-sequenced UC who received treatment between January 2010 and December 2020. Up to 77 developed metastatic disease and were deemed the study population. Twenty-six showed FGFR GAs. A trend toward a better response to cisplatin and checkpoint inhibitors was suggested favoring FGFR GA tumors. FGFR GA patients who received an FGFR inhibitor as first-line had poorer responses compared with other options (20% vs. 68.4%, p = 0.0065). Median PFS was 6 vs. 5 months in the FGFR GA vs. FGFR WT cohort (p = 0.71). Median OS was significantly worse in the FGFR GA vs. FGFR WT cohort (16.2 vs. 31.9 months, p = 0.045). Multivariate analyses deemed FGFR GAs as a factor independently associated with the outcome (HR 2.59 (95% CI 1.21–5.55)). Bajorin’s model correctly predicted clinical outcomes in the whole study population but not in FGFR GA cases. FGFR GAs are a relevant biomarker in mUC that could condition the response to systemic therapy. New prognostic models, including this molecular determination, should be designed and validated.
Purpose
The identification of subpopulations harboring druggable targets has become a major step forward in the subclassification of solid tumors into small groups suitable for specific therapies.
...BRAF
fusions represent a paradigm of uncommon and targetable oncogenic events and have been widely correlated to the development of specific malignancies. However, they are only present in a limited frequency across most common tumor types. At this regard, we performed a genomic screening aimed to identifying rare variants associated to advanced prostate cancer development.
Methods
Tumoral tissue genomic screening of 41 patients developing advanced prostate cancer was performed at our center as part of the GETHI XX study. The project, sponsored by the Spanish Collaborative Group in Rare Cancers (GETHI), aims to analyze the molecular background of rare tumors and to discover unfrequent molecular variants in common tumors.
Results
Here we present the clinical outcome and an in-deep molecular analysis performed in a case harboring a
SND1-BRAF
fusion gene. The identification of such rearrangement in a patient refractory to standard therapies led to the administration of trametinib (MEK inhibitor). Despite unsensitive to standard therapies, the patient achieved a dramatic response to trametinib. A comprehensive study of the tumor demonstrated this event to be a trunk alteration with higher expression of MEK in areas of tumor invasion.
Conclusions
Our study describes the patient-driven discovery of the first
BRAF
fusion-driven prostate cancer effectively treated with trametinib. Consequently, MAPK pathway activation could define a new subtype of prostate cancer susceptible to a tailored management.
Introduction:
Androgenic deprivation therapies have been linked to the development of metabolic syndrome (MS) and cardiovascular diseases, which may lead to a poorer survival in patients with ...metastatic Castration-Resistant Prostate Cancer (mCRPC). We aimed to analyze whether some cardiovascular or neurological disorders, together with other medical and urological complications, may have an effect on survival outcomes, at baseline and during treatment from patients treated with androgen pathway inhibitors (API).
Material and Methods:
A retrospective study of a consecutive series of patients diagnosed with mCRPC between 2010 and 2018 treated with API in the first line setting in a single center.
Results:
Seventy-three patients met the inclusion criteria. Baseline prognostic factors associated with worse survival were diabetes mellitus (DM) with insulin needs compared to patients without DM hazard ratio (HR) = 0.19, p = 0.025, hypertension (HTN) (HR = 0.46, p = 0.035), and a history of stroke (HR = 0.16, p < 0.001). However, previous history of hypercholesterolemia, arrythmias, and cognitive disorders did not result in a significant worsening on survival. During treatment, patients who developed de novo HTN had the best progression free survival (PFS) (HR = 0.38, p = 0.048) and overall survival (OS) (HR 0.08, p = 0.012) compared with patients with previous HTN. Other factors related to worse outcomes included the presence of heart failure (HR = 0.31, p = 0.001), the requirement for major opioids for pain relief (HR = 0.33, p = 0.023), and the presence of bilateral ureterohydronephrosis (HR = 0.12, p = 0.008).
Conclusions:
Some comorbidities may be strongly involved in patient outcomes when receiving API for mCRPC. In this sense, collaborative networking between specialists and caregivers treating prostate cancer (PC) patients should be recommended, focusing on MS features, cardiovascular and neurological disorders in order to anticipate medical and surgical complications.
Ovarian cancer (OC) is the second most common gynecological malignancy and the gynecological tumor with the worst prognosis. To try to improve this situation, Data Science technologies could be a ...useful tool to help clinicians to know more about the disease. In our case, we are interested in exploring OC data to discover relationships between clinical and genetic factors and the disease progression. For it, we propose an analysis framework for simple and univariate statistical descriptions of features of different types, based on bootstrap resampling. Foremost, we define the framework for metric, categorical, and dates variables and determine what are the advantages and disadvantages of using different bootstrap resampling strategies, based on their statistical basis. Then, we use it to perform a univariate analysis over an OC dataset that allows to explore how is the disease progression, having platinum-free interval as indicator, in relation to clinical and genetic features of different types. Also, it provides a first set of variables possibly relevant for survival prediction. Results obtained show that some features have led to individual differences between both platinum resistant (<6 months) and platinum sensitive(>6 months) groups. It can be concluded that this could be an indicator that the database could be discriminatory for the hypotheses studied, though it is convenient to make multivariate analyses to check how relationships among features are influenced.
Developments of richer integrative analysis methods for oncological studies are needed for efficiently leveraging the amount of clinical and genetic data available to provide the clinicians with ...better information. However, analyses of this nature often require mixing data of different types, which are not immediate to address jointly with classical methods. In this work, our aim is to find relationships between clinical and genetic features of different types (metric, categorical, and text) and the ovarian cancer (OC) disease progression. To this end, we first propose a univariate statistical method for text type applying bootstrap resampling to Bag of Words and Latent Dirichlet Allocation in order to include as features the free-text fields of the health recordings. Secondly, we extend bootstrap resampling for metric and categorical feature extraction with Principal Component Analysis (PCA) and Multiple Correspondence Analysis (MCA), respectively. We subsequently formulate a novel and integrative method for jointly considering metric, categorical, and text features. Results obtained in text analysis indicate individual differences in some words between two OC patients groups categorised according to their sensitivity to platinum drugs. These results indicate separability between both groups for text features. Also, regarding the multivariate analysis, clinical data results showed separability patterns for the three methods analysed according to the platinum-sensitivity degree. The use of these analytical tools in our OC cohort has allowed us to demonstrate their strengths by confirming the predictive and prognostic role of widely-known clinical and genetic variables (BRCA status, value of adjuvant therapy and optimal resection, or family history) and demonstrating significant associations in other variables whose role in OC development has been studied to a lesser extent (such as PMS1, GPC3, and SLX4 genes). These results highlight the value of implementing these approaches for the identification of novel biomarkers in the context of OC.
BackgroundThe Tumor Microenvironment (TME) has a key role in solid tumor therapy screening. We have developed a 3D ex vivo immunosuppressive assay mimicking the TME. It enables both allogenic & ...autologous tumor lysis by expanded Tumor Infiltrate Lymphocytes (TILs). It is a valuable 3D assay to study the activity of immune therapy drugs in patient sample.MethodsTME-aligned immunosuppressor media was produced by conditioned media from activated human Mesenchymal Stem Cells (hMSC). The TILs were expanded from patient-derived tumor samples and used for tumor killing potential evaluation. Target tumor cells were obtained from different sources: a) Isolated from patient-derived material and frozen until use in experiments with autologous or allogenic TILs or b) Tumor cell lines purchased from ATCC. The cells were mixed according to desired Effector:Target (E:T) ratios and embedded in 3D matrix in presence of TME-aligned media and immune therapy compounds, as Immune Checkpoint inhibitors (ImmChPi). The cell retrieval was performed at the end of desired timepoints and tumor cell killing and TILs activation profile were analyzed by flow cytometry.ResultsThe in vitro expanded TILs were able to kill autologous and allogenic tumor cells in several different E:T ratios within 24 hours. The% tumor cell killing for allogenic samples of the same cancer type showed a similar range as autologous killing. In a representative autologous E:T experiment we observed 40% of killing at E:T ratio 10:1 (figure 1A). These same TILs showed even higher% tumor killing against allogenic tumor samples (up to 90%, data not shown). The Immune Check Point (ImmChP) expression during expansion may change and was followed to select proper expansion timelines. For example, in a particular ovarian cancer sample TIM3 was expressed in 75% of the expanded TILs (figure 1B) and the treatment with TIM3 blocking antibody increased nearly 2-fold tumor cell killing in a dose dependent manner (figure 1C).Abstract 763 Figure 1Autologous killing: novel ex vivo solid tumor 3D assay using autologous TILs from an ovarian cancer patient sample for Immune Check Points or other IO drugs. A) Autologous TILs kill 40% ovarian cancer cells in 24h incubation. B) 75% TILs express TIM3. C) Adding TIM3 antibody enhances killing of tumor cells in a dose dependent manner.ConclusionsThe Novel TME-Aligned 3D IO Assay is a reliable, and powerful tool to study the mode of action of tumor cells lysis by expanded TILs. Immune Therapy Drugs Screening can be performed in autologous or allogenic E:T conditions, allowing full mode of action description of Bi or Multispecific antibodies, ImmChPI and others, and opens a new door for therapy prediction studies in patient‘s material.Ethics ApprovalThe study was approved by Hospital 12 de Octubre Ethics Board, with approval number 14/199.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.
Over the last decade anticancer treatment has experienced encouraging changes. One of the latest developments is immunotherapy, which is increasingly becoming a mainstay for the treatment of these ...malignancies. Unlike conventional chemotherapy, immunotherapy enhances anti-tumor immune response by blocking inhibitory immune checkpoints, and allowing our own immune system to fight against the tumor cells, arising as a new and innovative mechanism of action. Therefore, although well tolerated, these drugs have a unique side effect profile and are known to cause immune-related adverse events (irAEs). Adverse effects of immunotherapy are most commonly observed in the skin, gastrointestinal tract, liver, lung and endocrine systems. Less common toxicities may include neurological, haematological, cardiac, ocular or rheumatologic involvement. As far as we know, cancer patients are frequently seen in the Emergency Department due to treatment related toxicities, thus there is an increasing necessity to learn about this particular side effect profile
given that they entail a different and unique management than that of classic chemotherapy drugs.
•Immunotherapy blocks inhibitory immune checkpoints allowing our immune system to fight against tumor cells.•Most frequent irAEs affect skin, gastrointestinal, liver, lung and endocrine systems.•Timely intervention with corticosteroids is crucial to limit the severity of irAEs.•Corticosteroids are generally indicated together with dose skipping or discontinuation for persistent grade ≥2 irAEs.•Severe irAEs, grade 3-4, may require additional immunosuppressive agents and a multidisciplinary approach.
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