scholarly journals Geometric network analysis provides prognostic information in patients with high grade serous carcinoma of the ovary treated with immune checkpoint inhibitors

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Rena Elkin ◽  
Jung Hun Oh ◽  
Ying L. Liu ◽  
Pier Selenica ◽  
Britta Weigelt ◽  
...  
Keyword(s):  
High Risk ◽  
Network Analysis ◽  
Immune Checkpoint ◽  
Gene Networks ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Serous Carcinoma ◽  
High Grade ◽  
Kaplan Meier ◽  
Risk Of Mortality

AbstractNetwork analysis methods can potentially quantify cancer aberrations in gene networks without introducing fitted parameters or variable selection. A new network curvature-based method is introduced to provide an integrated measure of variability within cancer gene networks. The method is applied to high-grade serous ovarian cancers (HGSOCs) to predict response to immune checkpoint inhibitors (ICIs) and to rank key genes associated with prognosis. Copy number alterations (CNAs) from targeted and whole-exome sequencing data were extracted for HGSOC patients (n = 45) treated with ICIs. CNAs at a gene level were represented on a protein–protein interaction network to define patient-specific networks with a fixed topology. A version of Ollivier–Ricci curvature was used to identify genes that play a potentially key role in response to immunotherapy and further to stratify patients at high risk of mortality. Overall survival (OS) was defined as the time from the start of ICI treatment to either death or last follow-up. Kaplan–Meier analysis with log-rank test was performed to assess OS between the high and low curvature classified groups. The network curvature analysis stratified patients at high risk of mortality with p = 0.00047 in Kaplan–Meier analysis in HGSOC patients receiving ICI. Genes with high curvature were in accordance with CNAs relevant to ovarian cancer. Network curvature using CNAs has the potential to be a novel predictor for OS in HGSOC patients treated with immunotherapy.

scholarly journals Geometric Network Analysis Provides Prognostic Information in Patients with High Grade Serous Carcinoma of the Ovary Treated with Immune Checkpoint Inhibitors

2021 ◽  
Author(s):  
Rena Elkin ◽  
Jung Hun Oh ◽  
Ying L Liu ◽  
Pier Selenica ◽  
Britta Weigelt ◽  
...  
Keyword(s):  
High Risk ◽  
Network Analysis ◽  
Immune Checkpoint ◽  
Gene Networks ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Serous Carcinoma ◽  
High Grade ◽  
Kaplan Meier ◽  
Risk Of Mortality

Purpose: Network analysis methods can potentially quantify cancer disturbances in gene networks without introducing fitted parameters or variable selection. A new network curvature-based method is introduced to provide an integrated measure of variability within cancer gene networks. The method is applied to high grade serous ovarian cancers (HGSOCs) to predict response to immune checkpoint inhibitors (ICIs), and to rank key genes associated with prognosis. Methods: Copy number alterations (CNAs) from targeted and whole exome sequencing data were extracted for HGSOC patients (n = 45) treated with ICIs. CNAs at a gene level were represented on a protein-protein interaction network to define patient-specific networks with a fixed topology. A version of Ollivier-Ricci curvature was used to identify genes that play a potentially key role in response to immunotherapy and further to stratify patients at high risk of mortality. Overall survival (OS) was defined as the time from the start of ICI treatment to either death or last follow-up. Kaplan-Meier analysis with log-rank test was performed to assess OS between the high and low curvature classified groups. Results: The network curvature analysis stratified patients at high risk of mortality with p=0.00047 in Kaplan-Meier analysis. Genes with high curvature were in accordance with CNAs relevant to ovarian cancer. Conclusion: Network curvature using CNAs has the potential to be a novel predictor for OS in HGSOC patients treated with immunotherapy.

PD-L1 expression of high grade glial tumors at diagnosis and change of expression status at recurrence.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 2035-2035 ◽  
Author(s):  
Basak Oyan ◽  
Seyma Eren ◽  
Ozlem Sonmez ◽  
Ferda Ozkan ◽  
Kaan Yaltırak ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
High Grade ◽  
Cross Sectional ◽  
Glial Tumors ◽  
The Impact ◽  
Expression Status ◽  
Over Time

2035 Background: PD-L1 expression status is the main predictive factor for response to immune checkpoint inhibitors. PD-L1 status may change over time with the impact of therapies. The aim of this study is to determine if PD-L1 expression status changes in recurrent gliomas after chemoradiotherapy. Methods: Thirty eight patients with recurrent high grade gliomas who had surgical excision at least two times were included in this retrospective cross-sectional study. Nine patients were excluded because of the lack of appropriate pathology slides for pathologic evaluation. PD-L1 expression of 29 patients was evaluated by an expert pathologist with immunohistochemical methods. PD-L1 positivity was defined as expression in ≥1% of tumor cells. Change in PD-L1 expression status was defined as an absolute 5% difference between two resections. Results: Of the 29 patients, 15 patients (51.7%) had PD-L1 expression in ≥1% of tumor cells and 7 patients (24.1%) had PD-L1 expression in ≥10% of tumor cells. Tumor PD-L1 expression (defined as expression in ≥1% of tumor cells) was positive in 15 (51.7%) of 29 patients at diagnosis and at the time of recurrence. The PD-L1 status did not change in 17 patients (58.6%). 8 patients had PD-L1 negative tumors both at diagnosis and at recurrence, while 9 patients had PD-L1 positive tumors both at diagnosis and at recurrence. In 6 patients (20.7%) a negative-to-positive switch and in 6 patients (20.7%) a positive to negative switch were seen. Tumor PD-L1 expression increased in 7 of 29 patients (24.1%) and decreased in 9 of 29 patients (31.1%). PD-L1 expression remained stable in 13 of 29 patients (34.4%). The change in PD-L1 status over time was not statistically significant. Conclusions: More than 50% of high grade glial tumors express PD-L1 at diagnosis, so these tumors are good candidates for immune checkpoint inhibitors. The expression status changes in more than 40% of high grade glial tumors at recurrence, so immune responsiveness of glial tumors can be modified by treatments like chemotherapy and radiotherapy.

Multidisciplinary team management for high grade immune-related adverse events (irAEs): A single center experience.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15076-e15076
Author(s):  
PRABHSIMRANJOT SINGH ◽  
Osama Abu-Shawer ◽  
Amanda Brito ◽  
Eric Yenulevich ◽  
Shilpa Grover ◽  
...  
Keyword(s):  
Adverse Events ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Massachusetts General Hospital ◽  
Average Length ◽  
Immunosuppressive Agents ◽  
Future Research ◽  
Inpatient Service ◽  
High Grade

e15076 Background: Immune checkpoint inhibitors (ICIs) are increasingly used in the management of cancer. High grade irAEs are uncommon but can be severe and require hospital admission. There is an urgent need for early identification and triage of patients with irAEs in order to improve their management and outcomes. Methods: We established Immunotherapy toxicity (ITOX) team as the first in nation inpatient service at DFCI and Brigham and Women's Hospital (BWH) along with our partners at Massachusetts General Hospital (MGH) that is specifically devoted to mitigating irAEs. The ITOX service is consistent of 2 PAs and a medical oncology attending with an expertise in immunotherapy. The service utilizes algorithms that are modified from the ASCO and NCCN guidelines by our medical subspecialty experts at BWH. The service uses a multi-disciplinary approach with around the hour consulting service from experts in the field including GI, pulmonary, endocrinology and others. We leveraged EPIC to triage patients who are admitted to BWH and have ever received or currently on immune checkpoint inhibitors (ICIs). The daily list generated by EPIC is then curated manually by a PA to identify patients with potential irAEs. Results: A total of 138 patients with high grade irAEs were admitted to BWH between June 2018 and June 2019. Seventy percent of the 201 irAEs- related admissions were to ITOX service (70% accuracy in triaging). Most common irAEs was colitis (31%), pneumonitis (28%) and hepatitis (13%) which is consistent with the most common reported irAEs due to ICIs. Eighty five percent of the patients had grade 3 irAEs and 15% were admitted with life threatening grade 4 adverse events. About half of the patient had received ICI monotherapy; 33% received combination of ICI and non-ICI (chemotherapy or targeted therapy) and 17% received combination of ICIs. Most patients responded to steroids and only 9% had steroid-refractory irAEs requiring other immunosuppressive agents. The average length of stay for irAEs-related admission was 11 days with readmission rate of 26% within a year. Over 50 patients consented for tissue and blood biospecimen collection at the time of toxicity. Conclusions: We demonstrated the feasibility of empowering EMR to accurately triage patients with suspected irAEs to the ITOX service that is supported by institution developed guidelines and specialists. Our model is adaptable in major academic centers and can have major impact on quality improvement and future research studies that can be conducted in this unique setting.

scholarly journals Identification of a N6-Methyladenosine (m6A)-Related lncRNA Signature for Predicting the Prognosis and Immune Landscape of Lung Squamous Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Chengyin Weng ◽  
Lina Wang ◽  
Guolong Liu ◽  
Mingmei Guan ◽  
Lin Lu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Risk Model ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Lung Squamous Cell Carcinoma ◽  
Risk Groups ◽  
Immune Functions ◽  
Kaplan Meier

Backgroundm6A-related lncRNAs emerged as potential targets for tumor diagnosis and treatment. This study aimed to identify m6A-regulated lncRNAs in lung squamous cell carcinoma (LUSC) patients.Materials and MethodsRNA sequencing and the clinical data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The m6A-related lncRNAs were identified by using Pearson correlation assay. Univariate and multivariate Cox regression analyses were utilized to construct a risk model. The performance of the risk model was validated using Kaplan–Meier survival analysis and receiver operating characteristics (ROC). Immune estimation of LUSC was downloaded from TIMER, and the correlations between the risk score and various immune cells infiltration were analyzed using various methods. Differences in immune functions and expression of immune checkpoint inhibitors and m6A regulators between high-risk and low-risk groups were further explored. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were utilized to explore the biological functions of AL122125.1.ResultsA total of 351 m6A-related lncRNAs were obtained from TCGA. Seven lncRNAs demonstrated prognostic values. A further multivariate Cox regression assay constructed a risk model consisting of two lncRNAs (AL122125.1 and HORMAD2-AS1). The Kaplan–Meier analysis and area under the curve indicated that this risk model could be used to predict the prognosis of LUSC patients. The m6A-related lncRNAs were immune-associated. There were significant correlations between risk score and immune cell infiltration, immune functions, and expression of immune checkpoint inhibitors. Meanwhile, there were significant differences in the expression of m6A regulators between the high- and low-risk groups. Moreover, GO and KEGG analyses revealed that the upregulated expression of AL122125.1 was tumor-related.ConclusionIn this study, we constructed an m6A-related lncRNA risk model to predict the survival of LUSC patients. This study could provide a novel insight to the prognosis and treatment of LUSC patients.

scholarly journals Immune Checkpoint Myocarditis from Adjuvant Treatment of Melanoma

2020 ◽  
pp. 1-2
Author(s):  
Carrie Lenneman ◽  
John Dasher ◽  
Lavanya Kondapalli ◽  
Carrie Lenneman
Keyword(s):  
T Cells ◽  
High Risk ◽  
Adverse Events ◽  
Adjuvant Treatment ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Effective Therapy ◽  
Stage Iii

Immune checkpoint inhibitors (ICIs) are effective therapy for many metastatic cancers and are now being used as adjuvant treatment for many stage III cancers to reduce the high risk of reoccurrence. ICIs activate a patient’s own T-cells to fight cancer, but in some cases, immune-related adverse events (irAEs) with inflammation of many organs can occur. Rare cases of myocarditis have been reported. More data is needed to improve our ability to monitor, diagnose and treat irAEs.

scholarly journals Proposed diagnostic and treatment paradigm for high-grade neurological complications of immune checkpoint inhibitors

2018 ◽  
Vol 6 (5) ◽  
pp. 340-345 ◽  
Author(s):  
Dustin Anderson ◽  
Grayson Beecher ◽  
Nabeela Nathoo ◽  
Michael Smylie ◽  
Jennifer A McCombe ◽  
...  
Keyword(s):  
Nervous System ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Neurological Complications ◽  
High Grade ◽  
Small Cell Lung ◽  
Cytotoxic Lymphocyte ◽  
Programmed Cell Death 1 ◽  
Treatment Paradigm

Abstract Immune checkpoint inhibitors such as antibodies to cytotoxic lymphocyte-associated protein 4 (ipilimumab) and programmed cell-death 1 (pembrolizumab, nivolumab) molecules have been used in non-small cell lung cancer, metastatic melanoma, and renal-cell carcinoma, among others. With these agents, immune-related adverse events (irAEs) can occur, including those affecting the neurological axis. In this review, high-grade neurological irAEs associated with immune checkpoint inhibitors including cases of Guillain-Barré syndrome (GBS) and myasthenia gravis (MG) are analyzed. Based on current literature and experience at our institution with 4 cases of high-grade neurological irAEs associated with immune checkpoint inhibitors (2 cases of GBS, 1 case of meningo-radiculitis, and 1 case of myelitis), we propose an algorithm for the investigation and treatment of high-grade neurological irAEs. Our algorithm incorporates both peripheral nervous system (meningo-radiculitis, GBS, MG) and central nervous system presentations (myelitis, encephalopathy). It is anticipated that our algorithm will be useful both to oncologists and neurologists who are likely to encounter neurological irAEs more frequently in the future as immune checkpoint inhibitors become more widely used.

Hyperprogressive disease in patients with recurrent high grade gliomas treated with immune checkpoint inhibitors or other therapies.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e13575-e13575
Author(s):  
Laura Donovan ◽  
Samuel Gedailovich ◽  
Adela Joanta-Gomez ◽  
Jessica Schulte ◽  
Teri Nguyen Kreisl ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Fold Increase ◽  
Tumor Growth Rate ◽  
Control Group ◽  
High Grade ◽  
Advanced Cancer Patients ◽  
High Grade Gliomas ◽  
Hyperprogressive Disease

e13575 Background: Hyperprogressive disease (HPD) has been described in solid tumor patients treated with immune checkpoint inhibitors (ICI). HPD is defined as a ≥2-fold increase in tumor growth rate (TGR) following initiation of ICI. HPD has not been explored in patients with high grade gliomas (HGG) on ICI or standard cytotoxic regimens. In advanced cancer patients receiving ICI, MDM2/4 amplification or EGFR alterations, both found in HGG, correlated with HPD. We compared the rate of HPD in recurrent HGG patients receiving ICIs to those treated with non-immunotherapy agents. Methods: Patients with HGG on ICIs for 1st or 2nd recurrence were compared to a control group receiving other therapies at 1st recurrence. Patients with prior or concurrent bevacizumab or anti-VEGFR were excluded due to pseudoresponse and decreased enhancement with these drugs. HPD was calculated by comparing TGR immediately before and after treatment. Results: 49 patients met inclusion criteria (27 ICI, 25 control). 25/27 patients treated with ICIs and 20/22 patients in the control group had complete imaging and were eligible for analysis. In the ICI group, 60% were men (15/25) and 88% (22/25) had a diagnosis of GBM. 68% were treated at first progression (17/25). Controls were 80% male (16/20) and all had a diagnosis of GBM. 30% (6/20) were 65 years or older at diagnosis in the control group compared to 28% (7/25) in the ICI group. In total, 7/25 patients met criteria for HPD in the ICI group (28%) compared to 4/20 patients in the control group (20%). 10/25 patients (5/7 with HPD) in the ICI group and 8/20 patients (2/4 with HPD) in the control group had next generation sequencing of their tumors. EGFR alterations and MDM2/4 amplifications were not associated with HPD whereas PTEN mutations were more common in the HPD group (71% HPD vs. 33.3% no HPD). Conclusions: HPD is observed in patients with HGG treated with ICI at comparable rates to those with other cancers, but was also observed in 20% of patients receiving other therapies. While the numbers are small, PTEN mutations may be associated with HPD in patients with HGG. In contrast to other solid tumors, EGFR alterations and MDM2/4 amplifications were not associated with HPD in HGG.

scholarly journals GDPLichi: a DNA Damage Repair-Related Gene Classifier for Predicting Lung Adenocarcinoma Immune Checkpoint Inhibitors Response

2021 ◽  
Vol 11 ◽  
Author(s):  
Yang Leng ◽  
Shiying Dang ◽  
Fei Yin ◽  
Tianshun Gao ◽  
Xing Xiao ◽  
...  
Keyword(s):  
Dna Damage ◽  
T Cells ◽  
High Risk ◽  
Lung Adenocarcinoma ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Risk Group ◽  
Checkpoint Inhibitors ◽  
High Risk Group ◽  
Damage Repair

Lung cancer is one of the most common and mortal malignancies, usually with a poor prognosis in its advanced or recurrent stages. Recently, immune checkpoint inhibitors (ICIs) immunotherapy has revolutionized the treatment of human cancers including lung adenocarcinoma (LUAD), and significantly improved patients’ prognoses. However, the prognostic and predictive outcomes differ because of tumor heterogeneity. Here, we present an effective method, GDPLichi (Genes of DNA damage repair to predict LUAD immune checkpoint inhibitors response), as the signature to predict the LUAD patient’s response to the ICIs. GDPLichi utilized only 7 maker genes from 8 DDR pathways to construct the predictive model and classified LUAD patients into two subgroups: low- and high-risk groups. The high-risk group was featured by worse prognosis and decreased B cells, CD8+ T cells, CD8+ central memory T cells, hematopoietic stem cells (HSC), myeloid dendritic cells (MDC), and immune scores as compared to the low-risk group. However, our research also suggests that the high-risk group was more sensitive to ICIs, which might be explained by increased TMB, neoantigen, immune checkpoint molecules, and immune suppression genes’ expression, but lower TIDE score as compared to the low-risk group. This conclusion was verified in three other LUAD cohort datasets (GSE30219, GSE31210, GSE50081).

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