Age-Associated Changes in Adverse Events Arising From Anti-PD-(L)1 Therapy

BackgroundImmune-related adverse events (irAEs) may complicate the immune checkpoint inhibition (ICI) therapy. The effect of age on these irAEs is not elucidated. The aim of the study was to compare the occurrence of irAEs in different age groups.MethodsPatients with lung cancer receiving anti-programmed death- (ligand)1 (PD-(L)1) were selected from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Immune cell infiltration data set was obtained from TIMER 2.0 web server. The patients were stratified for age as follows: <65 year-old (young patients, YP), 65 to 75 year-old (middle aged patients, MP), ≥75 year-old (old patients, OP). The severity of irAEs was compared using logistic binary regression model. The distribution differences of immune cell infiltration were estimated using non-parametric tests.ResultsOf all the 17,006 patients treated by anti-PD-(L)1, 7,355 were <65 (YP), 6,706 were 65–75 (MP), and 2,945 were ≥75 (OP). In general, we analyzed a total of 16 irAEs in this article and found that pulmonary toxicity was more frequent in OP (OP vs. YP: OR = 1.45, 95% CI: 1.28–1.64) and MP (MP vs. YP: OR = 1.38, 95% CI: 1.24–1.52), but hepatitis was less frequent in OP (OP vs. YP: OR = 0.56, 95% CI: 0.32–0.97) and MP (MP vs. YP: OR = 0.57, 95%CI: 0.38–0.85). Further analysis demonstrated that older patients showed less B cell, CD8+ T cell and myeloid dendritic cell infiltration than younger patients.ConclusionsElderly patients exhibited higher incidences of pulmonary toxicity, while hepatitis was found at low incidence. Therefore, clinicians should carefully monitor comorbidities in elderly patients.

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Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes

10.21203/rs.3.rs-816357/v2 ◽

2021 ◽

Author(s):

shenglan li ◽

Zhuang Kang ◽

jinyi Chen ◽

Can Wang ◽

Zehao Cai ◽

...

Keyword(s):

Immune Cell ◽

Intracranial Tumor ◽

Cell Infiltration ◽

Molecular Profile ◽

Immune Cell Infiltration ◽

Ppi Network ◽

Hub Genes ◽

Data Set ◽

Hub Gene ◽

External Data

Abstract Background Medulloblastoma is a common intracranial tumor among children. In recent years, research on cancer genome has established four distinct subtypes of medulloblastoma: WNT, SHH, Group3, and Group4. Each subtype has its own transcriptional profile, methylation changes, and different clinical outcomes. Treatment and prognosis also vary depending on the subtype. Methods Based on the methylation data of medulloblastoma samples, methylCIBERSORT was used to evaluate the level of immune cell infiltration in medulloblastoma samples and identified 10 kinds of immune cells with different subtypes. Combined with the immune database, 293 Imm-DEGs were screened. Imm-DEGs were used to construct the co-expression network, and the key modules related to the level of differential immune cell infiltration were identified. Three immune hub genes (GAB1, ABL1, CXCR4) were identified according to the gene connectivity and the correlation with phenotype in the key modules, as well as the PPI network involved in the genes in the modules. Results The subtype marker was recognized according to the immune hub, and the subtype marker was verified in the external data set, the methylation level of immune hub gene among different subtypes was compared and analyzed, at the same time, tissue microarray was used for immunohistochemical verification, and a multi-factor regulatory network of hub gene was constructed. Conclusions Identifying subtype marker is helpful to accurately identify the subtypes of medulloblastoma patients, and can accurately evaluate the treatment and prognosis, so as to improve the overall survival of patients.

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Safety of Biologic Agents in Elderly Patients with Rheumatoid Arthritis

The Journal of Rheumatology ◽

10.3899/jrheum.160012 ◽

2016 ◽

Vol 43 (11) ◽

pp. 1984-1988 ◽

Cited By ~ 11

Author(s):

Atsuko Murota ◽

Yuko Kaneko ◽

Kunihiro Yamaoka ◽

Tsutomu Takeuchi

Keyword(s):

Rheumatoid Arthritis ◽

Risk Factors ◽

Adverse Events ◽

Elderly Patients ◽

Young Patients ◽

Pulmonary Complications ◽

Biologic Agents ◽

Treatment Withdrawal ◽

Old Patients ◽

Independent Risk Factors

Objective.To clarify the safety of biologics in elderly patients with rheumatoid arthritis.Methods.Biologics were analyzed for safety in relation to age in 309 patients.Results.Young (< 65 yrs old, n = 174), elderly (65–74 yrs old, n = 86), and older elderly patients (≥ 75 yrs old, n = 49) were enrolled. Although the incidence of adverse events causing treatment withdrawal was significantly higher in elderly and old elderly compared with young patients, no difference was found between elderly and older elderly patients. Pulmonary complications were independent risk factors.Conclusion.Old patients require special attention, although the safety of biologics in those ≥ 75 years old and 65–74 was comparable.

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Molecular profile reveals immune-associated markers of medulloblastoma for different subtypes

10.21203/rs.3.rs-816357/v1 ◽

2021 ◽

Author(s):

Shenglan Li ◽

Zhuang Kang ◽

Jinyi Chen ◽

Can Wang ◽

Zehao Cai ◽

...

Keyword(s):

Immune Cell ◽

Intracranial Tumor ◽

Cell Infiltration ◽

Molecular Profile ◽

Immune Cell Infiltration ◽

Ppi Network ◽

Hub Genes ◽

Data Set ◽

Hub Gene ◽

External Data

Abstract Medulloblastoma is a common intracranial tumor among children. In recent years, research on cancer genome has established four distinct subtypes of medulloblastoma: WNT, SHH, Group3, and Group4. Each subtype has its own transcriptional profile, methylation changes, and different clinical outcomes. Treatment and prognosis also vary depending on the subtype. Based on the methylation data of medulloblastoma samples, methylCIBERSORT was used to evaluate the level of immune cell infiltration in medulloblastoma samples and identified 10 kinds of immune cells with different subtypes. Combined with the immune database, 293 Imm-DEGs were screened. Imm-DEGs were used to construct the co-expression network, and the key modules related to the level of differential immune cell infiltration were identified. Three immune hub genes (GAB1, ABL1, CXCR4) were identified according to the gene connectivity and the correlation with phenotype in the key modules, as well as the PPI network involved in the genes in the modules. The subtype marker was recognized according to the immune hub, and the subtype marker was verified in the external data set, Finally, the methylation level of immune hub gene among different subtypes was compared and analyzed, at the same time, tissue microarray was used for immunohistochemical verification, and a multi-factor regulatory network of hub gene was constructed. Identifying subtype marker is helpful to accurately identify the subtypes of medulloblastoma patients, and can accurately evaluate the treatment and prognosis, so as to improve the overall survival of patients.

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Multi-Omics Analysis Showed the Clinical Value of Gene Signatures of C1QC+ and SPP1+ TAMs in Cervical Cancer

Frontiers in Immunology ◽

10.3389/fimmu.2021.694801 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiong Li ◽

Qinghua Zhang ◽

Gang Chen ◽

Danfeng Luo

Keyword(s):

Cervical Cancer ◽

Immune Cell ◽

Gene Signature ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Single Cell Level ◽

Cell Level ◽

Data Set ◽

Gene Signatures ◽

Cancer Data

PurposeTo evaluate the value of C1QC+ and SPP1+ TAMs gene signatures in patients with cervical cancer.MethodsWe compare the C1QC+ and SPP1+ TAMs gene signatures with the M1/M2 gene signatures at single cell level and bulk RNA-seq level and evaluate which gene signature can clearly divide TAMs and patients with cervical cancer into distinct clinical subclusters better.ResultsAt single-cell level, C1QC+ and SPP1+ TAMs gene signatures, but not M1 and M2 gene signatures, could clearly divided TAMs into two subclusters in a colon cancer data set and an advanced basal cell data set. For cervical cancer data from TCGA, patients with C1QChigh and SPP1low TAMs gene signatures have the best prognosis, lowest proportion (34.21%) of locally advanced cervical cancer (LACC), and highest immune cell infiltration, whereas patients with C1QClow and SPP1high TAMs gene signatures have the worst prognosis, highest proportion (71.79%) of LACC and lowest immune cell infiltration. Patients with C1QChigh and SPP1low TAMs gene signature have higher expression of most of the Immune checkpoint molecules (ICMs) than patients with C1QClow and SPP1high TAMs gene signatures. The GSEA results suggested that subgroups of patients divided by C1QC+ and SPP1+ TAMs gene signatures showed different anti- or pro-tumor state.ConclusionC1QC+ and SPP1+ TAMs gene signatures, but not M1/M2 gene signatures, can divide cervical patients into subgroups with different prognosis, tumor stage, different immune cell infiltration, and ICMs expression. Our findings may help to find suitable treatment strategy for cervical cancer patients with different TAMs gene signatures.

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WISP1 modulates immune cell infiltration upon drug-induced liver injury (DILI)

Zeitschrift für Gastroenterologie ◽

10.1055/s-0035-1567970 ◽

2015 ◽

Vol 53 (12) ◽

Author(s):

AB Widera ◽

L Pütter ◽

S Leserer ◽

G Campos ◽

K Rochlitz ◽

...

Keyword(s):

Liver Injury ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Drug Induced ◽

Drug Induced Liver Injury

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Faculty Opinions recommendation of Human breast cancer invasion and aggression correlates with ECM stiffening and immune cell infiltration.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725485692.793517744 ◽

2016 ◽

Author(s):

Paul Timpson ◽

Claire Vennin

Keyword(s):

Breast Cancer ◽

Human Breast Cancer ◽

Immune Cell ◽

Cancer Invasion ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Human Breast ◽

Breast Cancer Invasion

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Identification of Potential Therapeutic Targets and Immune Cell Infiltration Characteristics in Osteosarcoma Using Bioinformatics Strategy

Frontiers in Oncology ◽

10.3389/fonc.2020.01628 ◽

2020 ◽

Vol 10 ◽

Author(s):

Jianfang Niu ◽

Taiqiang Yan ◽

Wei Guo ◽

Wei Wang ◽

Zhiqing Zhao ◽

...

Keyword(s):

Immune Cell ◽

Therapeutic Targets ◽

Cell Infiltration ◽

Immune Cell Infiltration

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SFTPA1 is a potential prognostic biomarker correlated with immune cell infiltration and response to immunotherapy in lung adenocarcinoma

Cancer Immunology Immunotherapy ◽

10.1007/s00262-021-02995-4 ◽

2021 ◽

Author(s):

Lu Yuan ◽

Xixi Wu ◽

Longshan Zhang ◽

Mi Yang ◽

Xiaoqing Wang ◽

...

Keyword(s):

Lung Cancer ◽

T Cells ◽

Lung Adenocarcinoma ◽

Expression Profile ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Regulatory Pathways ◽

Chronic Lung Diseases ◽

Potential Biomarker

AbstractPulmonary surfactant protein A1 (SFTPA1) is a member of the C-type lectin subfamily that plays a critical role in maintaining lung tissue homeostasis and the innate immune response. SFTPA1 disruption can cause several acute or chronic lung diseases, including lung cancer. However, little research has been performed to associate SFTPA1 with immune cell infiltration and the response to immunotherapy in lung cancer. The findings of our study describe the SFTPA1 expression profile in multiple databases and was validated in BALB/c mice, human tumor tissues, and paired normal tissues using an immunohistochemistry assay. High SFTPA1 mRNA expression was associated with a favorable prognosis through a survival analysis in lung adenocarcinoma (LUAD) samples from TCGA. Further GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that SFTPA1 was involved in the toll-like receptor signaling pathway. An immune infiltration analysis clarified that high SFTPA1 expression was associated with an increased number of M1 macrophages, CD8+ T cells, memory activated CD4+ T cells, regulatory T cells, as well as a reduced number of M2 macrophages. Our clinical data suggest that SFTPA1 may serve as a biomarker for predicting a favorable response to immunotherapy for patients with LUAD. Collectively, our study extends the expression profile and potential regulatory pathways of SFTPA1 and may provide a potential biomarker for establishing novel preventive and therapeutic strategies for lung adenocarcinoma.

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Enhanced CD4+ and CD8+ T cell infiltrate within convex hull defined pancreatic islet borders as autoimmune diabetes progresses

Scientific Reports ◽

10.1038/s41598-021-96327-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Alexander J. Dwyer ◽

Jacob M. Ritz ◽

Jason S. Mitchell ◽

Tijana Martinov ◽

Mohannad Alkhatib ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Convex Hull ◽

Pancreatic Islets ◽

Immune Cell ◽

Nod Mice ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Analytical Strategy ◽

Islet Mass

AbstractThe notion that T cell insulitis increases as type 1 diabetes (T1D) develops is unsurprising, however, the quantitative analysis of CD4+ and CD8+ T cells within the islet mass is complex and limited with standard approaches. Optical microscopy is an important and widely used method to evaluate immune cell infiltration into pancreatic islets of Langerhans for the study of disease progression or therapeutic efficacy in murine T1D. However, the accuracy of this approach is often limited by subjective and potentially biased qualitative assessment of immune cell subsets. In addition, attempts at quantitative measurements require significant time for manual analysis and often involve sophisticated and expensive imaging software. In this study, we developed and illustrate here a streamlined analytical strategy for the rapid, automated and unbiased investigation of islet area and immune cell infiltration within (insulitis) and around (peri-insulitis) pancreatic islets. To this end, we demonstrate swift and accurate detection of islet borders by modeling cross-sectional islet areas with convex polygons (convex hulls) surrounding islet-associated insulin-producing β cell and glucagon-producing α cell fluorescent signals. To accomplish this, we used a macro produced with the freeware software ImageJ equipped with the Fiji Is Just ImageJ (FIJI) image processing package. Our image analysis procedure allows for direct quantification and statistical determination of islet area and infiltration in a reproducible manner, with location-specific data that more accurately reflect islet areas as insulitis proceeds throughout T1D. Using this approach, we quantified the islet area infiltrated with CD4+ and CD8+ T cells allowing statistical comparison between different age groups of non-obese diabetic (NOD) mice progressing towards T1D. We found significantly more CD4+ and CD8+ T cells infiltrating the convex hull-defined islet mass of 13-week-old non-diabetic and 17-week-old diabetic NOD mice compared to 4-week-old NOD mice. We also determined a significant and measurable loss of islet mass in mice that developed T1D. This approach will be helpful for the location-dependent quantitative calculation of islet mass and cellular infiltration during T1D pathogenesis and can be combined with other markers of inflammation or activation in future studies.

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