1,721,017 research outputs found
PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 <50%: a network analysis
No full textBackground
In the dynamic landscape of cancer treatment, immunotherapy plays a pivotal role,
particularly for advanced non-small cell lung cancer (aNSCLC) lacking driver alterations.
While PD-L1 Tumor Proportion Score (TPS) guides patient selection, challenges persist
in refining strategies. The phase II PEOPLE trial addresses this by exploring biomarkers
in aNSCLC patients with PD-L1 TPS < 50% treated with pembrolizumab. Leveraging
network medicine, which maps complex biological interactions, this study integrates highthroughput technologies to analyze circulating immuno-profiling and gene expression
data. The aim is to unveil novel biomarkers critical for immunotherapy response, fostering
personalized treatments. This interdisciplinary collaboration between clinicians and data
scientists is essential for decoding aNSCLC complexities. The thesis outlines objectives:
constructing correlation networks and identifying predictive biomarkers.
Methods:
To explore this challenge, network analysis techniques were employed. The work used
data from the phase II trial PEOPLE (NCT03447678) conducted at the IRCCS Fondazione
Istituto dei Tumori di Milano. This dataset contained comprehensive information on
patients’ circulating immune profiles and gene expression profiles. Data preprocessing
steps ensured quality, and statistical analyses involved network construction, differential
expression analysis, and enrichment analysis. Additionally, community detection was
applied to the differential co-expression network. Patient similarity networks were created,
and survival analysis was conducted to understand the impact of identified biomarkers on
overall survival (OS).
Results:
Survival analysis, with a median follow-up of 26.4 months, revealed a median PFS of 2.9
months and a median OS of 12.1 months. Response rates were 24.1%, and disease control
rate was 53.4%. Differential correlation networks (DCN) of circulating immune profiling
demonstrated distinct patterns in responders and non-responders pre-therapy, shedding
light on key role of NK cells. Gene DCN identified 23 hubs gene and enrichment analysis
of each hub revealed associations with immune-related processes. Community detection
identified modules enriched in immune responses. A patient similarity network based on
hub genes revealed two clusters with significant differences in survival outcomes,
emphasizing the potential prognostic value of molecular heterogeneity in response to
pembrolizumab.
Conclusions:
These findings contribute valuable insights to the evolving landscape of immunotherapy
in aNSCLC, emphasizing the need for further investigations into the intricate relationships
shaping treatment response and patient outcomes.
Background
In the dynamic landscape of cancer treatment, immunotherapy plays a pivotal role, particularly for advanced non-small cell lung cancer (aNSCLC) lacking driver alterations. While PD-L1 Tumor Proportion Score (TPS) guides patient selection, challenges persist in refining strategies. The phase II PEOPLE trial addresses this by exploring biomarkers in aNSCLC patients with PD-L1 TPS < 50% treated with pembrolizumab. Leveraging network medicine, which maps complex biological interactions, this study integrates high-throughput technologies to analyze circulating immuno-profiling and gene expression data. The aim is to unveil novel biomarkers critical for immunotherapy response, fostering personalized treatments. This interdisciplinary collaboration between clinicians and data scientists is essential for decoding aNSCLC complexities. The thesis outlines objectives: constructing correlation networks and identifying predictive biomarkers.
Methods:
To explore this challenge, network analysis techniques were employed. The work used data from the phase II trial PEOPLE (NCT03447678) conducted at the IRCCS Fondazione Istituto dei Tumori di Milano. This dataset contained comprehensive information on patients’ circulating immune profiles and gene expression profiles. Data preprocessing steps ensured quality, and statistical analyses involved network construction, differential expression analysis, and enrichment analysis. Additionally, community detection was applied to the differential co-expression network. Patient similarity networks were created, and survival analysis was conducted to understand the impact of identified biomarkers on overall survival (OS).
Results:
Survival analysis, with a median follow-up of 26.4 months, revealed a median PFS of 2.9 months and a median OS of 12.1 months. Response rates were 24.1%, and disease control rate was 53.4%. Differential correlation networks (DCN) of circulating immune profiling demonstrated distinct patterns in responders and non-responders pre-therapy, shedding light on key role of NK cells. Gene DCN identified 23 hubs gene and enrichment analysis of each hub revealed associations with immune-related processes. Community detection identified modules enriched in immune responses. A patient similarity network based on hub genes revealed two clusters with significant differences in survival outcomes, emphasizing the potential prognostic value of molecular heterogeneity in response to pembrolizumab.
Conclusions:
These findings contribute valuable insights to the evolving landscape of immunotherapy in aNSCLC, emphasizing the need for further investigations into the intricate relationships shaping treatment response and patient outcomes
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Hyperprogressive Disease and Early Hypereosinophilia After Anti-PD-1 Treatment: A Case Report.
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Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Status of correlation between BMI and response to immunocheck-point inhibitor in advanced non-small-cell lung cancer
Get PDFRecently, clinical evidence has raised BMI as an emerging prognostic factor for immunotherapy, regardless of cancer types. In this article we rewirw current data about correlation between BMI and response to immunocheck-point inhibitor in advanced non-small-cell lung cance
Is hyperprogressive disease a specific phenomenom of immunotherapy?
No full textHyperprogressive disease (HPD) is a novel pattern of response during immunotherapy treatment. Several retrospective studies have evaluated its prevalence among various cancer types and, in particular, in nonsmall cell lung cancer patients, based on different definition criteria. If HPD is a just a typical phenomenon of immunotherapy is still an unsolved concern. This paper summarized the available data about HPD in other cancer treatments. Hyperprogressive disease (HPD) is a novel pattern of response during immunotherapy treatment. Several retrospective studies have evaluated its prevalence among various cancer types and, in particular, in non-small cell lung cancer patients, based on different definition criteria. If HPD is a just a typical phenomenon of immunotherapy is still an unsolved concern. This paper summarized the available data about HPD in other cancer treatments
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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