Development and validation of the Immune Profile Score (IPS), a novel multi-omic algorithmic assay for stratifying outcomes in a real-world cohort of advanced solid cancer patients treated with immune checkpoint inhibitors DOI Creative Commons
Alia Zander, Rossin Erbe, Yan Liu

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

Abstract Background Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, majority do not benefit from ICIs, indicating a need predictive biomarkers to better inform decisions. Methods A de-identified pan-cancer cohort Tempus multimodal real-world database was used development and validation of Profile Score (IPS) algorithm leveraging xT (648 gene DNA panel) xR (RNAseq). The consisted advanced stage cancer patients treated with any ICI-containing regimen as first or second line therapy. IPS model developed utilizing machine learning framework that includes tumor mutational burden (TMB) 11 RNA-based features. Results IPS-High demonstrated significantly longer overall survival (OS) compared IPS-Low (HR=0.45, 90% CI [0.40-0.52]). consistently prognostic in PD-L1 (positive/negative), TMB (High/Low), microsatellite status (MSS/MSI-H), (ICI only/ICI + other) subgroups. Additionally, remained significant multivariable models controlling TMB, MSI, PD-L1, HRs 0.49 [0.42-0.56], 0.47 [0.41-0.53], 0.45 [0.38-0.53] respectively. In an exploratory utility analysis subset (n=345) receiving first-line (1L) chemotherapy (CT) second-line (2L) ICI, there no effect time next on CT L1 (HR=1.06 [0.85-1.33]). However, OS ICI L2 (HR=0.63 [0.46-0.86]). test interaction statistically (p<0.01). Conclusions Our results demonstrate is generalizable multi-omic biomarker can be widely utilized clinically prognosticator based regimens. Graphical Key Messages What already known this topic – Advancements profiling technology research settings has potential value novel immune forecasting response therapies. despite these advances remains unmet clinical implementation more sensitive predict patient outcomes due limited availability testing cohorts. study adds Importantly, may identify within subgroups (TMB-L, MSS, negative) who beyond what predicted by existing biomarkers. How might affect research, practice policy near term support stratification across pan-solid cohorts help clinicians researchers which are likely future label expansion ICIs into types without current approvals, also potentially improve selection minimize over-treatment unlikely respond.

Language: Английский

Dual blockade immunotherapy targeting PD-1/PD-L1 and CTLA-4 in lung cancer DOI Creative Commons

Weishi Cheng,

Kai Kang, Ailin Zhao

et al.

Journal of Hematology & Oncology, Journal Year: 2024, Volume and Issue: 17(1)

Published: July 27, 2024

Abstract Cancer immunotherapies, represented by immune checkpoint inhibitors (ICIs), have reshaped the treatment paradigm for both advanced non-small cell lung cancer and small cancer. Programmed death receptor-1/programmed receptor ligand-1 (PD-1/PD-L1) cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) are some of most common promising targets in ICIs. Compared to ICI monotherapy, which occasionally demonstrates resistance limited efficacy, dual blockade immunotherapy targeting PD-1/PD-L1 CTLA-4 operates at different stages activation with synergistically enhancing responses against cells. This emerging therapy heralds a new direction immunotherapy, which, however, may increase risk drug-related adverse reactions while improving efficacy. Previous clinical trials explored combination strategy anti-PD-1/PD-L1 anti-CTLA-4 agents cancer, yet its efficacy remains be unclear inevitable incidence immune-related events. The recent advent bispecific antibodies has made this sort more feasible, aiming alleviate toxicity without compromising Thus, review highlights role treating further elucidates pre-clinical mechanisms current advancements trials. Besides, we also provide novel insights into potential combinations therapies other strategies optimize future mode

Language: Английский

Citations

31
A constitutive interferon-high immunophenotype defines response to immunotherapy in colorectal cancer DOI Creative Commons
Amelia Acha‐Sagredo, Pietro Andrei, Kalum Clayton

et al.

Cancer Cell, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

4
MIF and CD74 as Emerging Biomarkers for Immune Checkpoint Blockade Therapy DOI Open Access
Rosalyn M. Fey,

Rebecca A. Nichols,

Thuy Tran

et al.

Cancers, Journal Year: 2024, Volume and Issue: 16(9), P. 1773 - 1773

Published: May 4, 2024

Immune checkpoint blockade (ICB) therapy is used to treat a wide range of cancers; however, some patients are at risk developing treatment resistance and/or immune-related adverse events (irAEs). Thus, there great need for the identification reliable predictive biomarkers response and toxicity. The cytokine MIF (macrophage migration inhibitory factor) its cognate receptor CD74 intimately connected with cancer progression have previously been proposed as prognostic patient outcome in various cancers, including solid tumors such malignant melanoma. Here, we assess their potential ICB irAE development. We provide brief overview function roles context autoimmune disease. also review evidence showing that may be use highlight careful consideration required when assessing serum levels biomarker due reported circadian expression human plasma. Finally, suggest future directions establishment development guide further research this field.

Language: Английский

Citations

8
Tumor-immune partitioning and clustering algorithm for identifying tumor-immune cell spatial interaction signatures within the tumor microenvironment DOI Creative Commons
Mai Chan Lau, Jennifer Borowsky, Juha P. Väyrynen

et al.

PLoS Computational Biology, Journal Year: 2025, Volume and Issue: 21(2), P. e1012707 - e1012707

Published: Feb. 18, 2025

Background Growing evidence supports the importance of characterizing organizational patterns various cellular constituents in tumor microenvironment precision oncology. Most existing data on immune cell infiltrates tumors, which are based counts or nearest neighbor-type analyses, have failed to fully capture organization and heterogeneity. Methods We introduce a computational algorithm, termed Tumor-Immune Partitioning Clustering (TIPC), that jointly measures partitioning between epithelial stromal areas clustering versus dispersion. As proof-of-principle, we applied TIPC prospective cohort incident biobank containing 931 colorectal carcinoma cases. identified subtypes with unique spatial cells T lymphocytes linked certain molecular pathologic prognostic features. lymphocyte identification phenotyping were achieved using multiplexed (multispectral) immunofluorescence. In separate hepatocellular cohort, replaced component specific types—CXCR3 + CD68 CD8+—to profile their relationships CXCL9 cells. Results Six unsupervised distribution identified, comprising two cold four hot subtypes. Three associated significantly longer cancer (CRC)-specific survival compared reference subtype. Our analysis showed variations T-cell densities among did not strictly correlate benefits, underscoring significance patterns. Additionally, revealed spatially distinct density-specific microsatellite instability-high cancers, indicating its potential upgrade subtyping. was also additional types, eosinophils neutrophils, morphology supervised machine learning; here similarly low densities, namely ‘cold, tumor-rich’ stroma-rich’, exhibited differential associations. Lastly, validated our methods results The Cancer Genome Atlas colon rectal adenocarcinoma (n = 570). Moreover, applying cases 27) highlighted critical interactions like CXCL9-CXCR3 CXCL9-CD8. Conclusions Unsupervised discoveries microgeometric tissue novel algorithm can deepen understanding likely inform immunotherapy.

Language: Английский

Citations

0
The IFN-high phenotype: A biomarker-driven breakthrough in colorectal cancer treatment DOI Creative Commons
Lize Allonsius,

Luca Kelecom,

Damya Laoui

et al.

Cell Reports Medicine, Journal Year: 2025, Volume and Issue: 6(3), P. 102025 - 102025

Published: March 1, 2025

Language: Английский

Citations

0
Relative expression orderings based prediction of treatment response to Anti-PD-1 immunotherapy in advanced melanoma DOI Creative Commons
Ya‐Ru Gao,

Yue Huo,

Lingli Wang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 25, 2025

Programmed cell death protein 1 (PD-1) plays a critical role in immune tolerance and evasion within the tumor microenvironment, anti-PD-1 immunotherapy has shown efficacy treating advanced melanoma. However, response rates vary significantly among patients, necessitating identification of reliable biomarkers to predict treatment efficacy. Based on within-sample relative expression orderings, we analyzed RNA sequencing data from melanoma patients construct predictive model comprising gene pairs associated with response. The model's performance was validated across multiple independent datasets assessed for correlations infiltration survival outcomes. constructed 15-pair achieved prediction accuracy 100% training 89.47% validation sets. Validation lacking revealed significant differences between predicted responders non-responders datasets, being an prognostic factor. Increased observed responders, correlating higher levels key checkpoint genes. orderings-based shows promise as tool predicting responses therapy supporting personalized strategies.

Language: Английский

Citations

0
Insights into the prognostic value and immunological role of CD74 in pan-cancer DOI Creative Commons
Zebiao Liu,

Mingquan Chen,

Wanhua Zheng

et al.

Discover Oncology, Journal Year: 2024, Volume and Issue: 15(1)

Published: June 11, 2024

Abstract Background CD74 is a non-polymorphic type II transmembrane glycoprotein. It involved in the regulation of T and B cell development, dendritic (DC) motility. Numerous studies have found that exerts an essential role tumor immunity, but expression profile still not systematically reported, its value human pan-cancer analysis unknown. In this study, we analyzed pattern 33 cancers, evaluated significance prognosis prediction cancer immunity. Methods Pan-cancer dataset from UCSC Xena.We used Sangerbox website combined with R software’ Timer, CIBERSORT method IOBR package to analyze plot data. Survival was assessed using Kaplan—Meier log—rank test for types (p < 0.05). addition, explore relationship between immune checkpoints, infiltration, mutational burden (TMB) microsatellite instability (MSI), Spearman correlation performed. Results This study comprehensively different types, revealing play crucial formation development. Conclusions gene cancers associated infiltration immunomodulators may provide promising target survival immunotherapy. Our shows has as biomarker during which highlights possibility new targeted therapies.

Language: Английский

Citations

1
Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma DOI Creative Commons

Minxiao Yang,

Noah Shulkin,

Edgar R. Gonzalez

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 23, 2024

Solid carcinomas are often highly heterogenous cancers, arising from multiple epithelial cells of origin. Yet, how the cell origin influences response tumor microenvironment is poorly understood. Lung adenocarcinoma (LUAD) arises in distal alveolar epithelium which populated primarily by type I (AT1) and II (AT2) cells. It has been previously reported that

Language: Английский

Citations

0
Development and validation of the Immune Profile Score (IPS), a novel multi-omic algorithmic assay for stratifying outcomes in a real-world cohort of advanced solid cancer patients treated with immune checkpoint inhibitors DOI Creative Commons
Alia Zander, Rossin Erbe, Yan Liu

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 5, 2024

Abstract Background Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, majority do not benefit from ICIs, indicating a need predictive biomarkers to better inform decisions. Methods A de-identified pan-cancer cohort Tempus multimodal real-world database was used development and validation of Profile Score (IPS) algorithm leveraging xT (648 gene DNA panel) xR (RNAseq). The consisted advanced stage cancer patients treated with any ICI-containing regimen as first or second line therapy. IPS model developed utilizing machine learning framework that includes tumor mutational burden (TMB) 11 RNA-based features. Results IPS-High demonstrated significantly longer overall survival (OS) compared IPS-Low (HR=0.45, 90% CI [0.40-0.52]). consistently prognostic in PD-L1 (positive/negative), TMB (High/Low), microsatellite status (MSS/MSI-H), (ICI only/ICI + other) subgroups. Additionally, remained significant multivariable models controlling TMB, MSI, PD-L1, HRs 0.49 [0.42-0.56], 0.47 [0.41-0.53], 0.45 [0.38-0.53] respectively. In an exploratory utility analysis subset (n=345) receiving first-line (1L) chemotherapy (CT) second-line (2L) ICI, there no effect time next on CT L1 (HR=1.06 [0.85-1.33]). However, OS ICI L2 (HR=0.63 [0.46-0.86]). test interaction statistically (p<0.01). Conclusions Our results demonstrate is generalizable multi-omic biomarker can be widely utilized clinically prognosticator based regimens. Graphical Key Messages What already known this topic – Advancements profiling technology research settings has potential value novel immune forecasting response therapies. despite these advances remains unmet clinical implementation more sensitive predict patient outcomes due limited availability testing cohorts. study adds Importantly, may identify within subgroups (TMB-L, MSS, negative) who beyond what predicted by existing biomarkers. How might affect research, practice policy near term support stratification across pan-solid cohorts help clinicians researchers which are likely future label expansion ICIs into types without current approvals, also potentially improve selection minimize over-treatment unlikely respond.

Language: Английский

Citations

0