27-gene Immuno-Oncology (IO) Score is Associated With Efficacy of Checkpoint Immunotherapy in Advanced NSCLC: A Retrospective BC Cancer Study

Saltman, David L.; Varga, Matthew G.; Nielsen, Tyler J.; Croteau, Nicole; Lockyer, Heather; Jain, Amit; Vidal, Gregory A.; Hout, David R.; Schweitzer, Brock L.; Seitz, Robert S.; Ross, Douglas T.; Gandara, David R.

doi:10.1016/j.cllc.2022.11.009

Cited by 4 publications

(6 citation statements)

References 25 publications

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“…Using data from a real-world UNC-108 cohort, the results confirmed the findings of the IMvigor210 study that the IO score is associated with the efficacy of ICI therapy in mUC [18]. Furthermore, this was accomplished using the same binary classification threshold used in all previous studies, and this study will discuss the potential of an evidence-based likelihood of response assessment to inform therapeutic sequencing in the treatment of advanced mUC [15][16][17][18][19][20][21].…”

Section: Introductionsupporting

confidence: 73%

Section: Methodsmentioning

confidence: 99%

“…The IO score classifies cases as positive or negative based on their correlation to established gene expression centroids for immunomodulatory, mesenchymal, and mesenchymal stem-like subtypes [23]. The classification threshold was previously established in breast and lung cancers and validated as a classifier for mUC using TCGA and IMvigor210 datasets [15][16][17][18][19]. To assess data for the UNC-108 cohort, RNA expression analysis was used to determine the IO score of patients with available data downloaded from GSE176307 using the requisite 27-genes as previously described (ITM2A gene missing, Cohen's κ = 0.99 from TCGA-BLCA (RRID:SCR_003193; Project: Bladder Urothelial Carcinoma, Table S1).…”

Section: Io Score Classificationmentioning

confidence: 99%

“…The 27-gene immuno-oncology classifier (IO score) quantifies gene expression to classify the TIME and uses an algorithm that combines results into a continuous score with a pre-specified binary IO positive (IO +) or IO negative (IO− ) classification to predict response to immune therapy [15]. The IO score classification has demonstrated an association with ICI efficacy in multiple tumor types including non-small cell lung cancer (NSCLC), triple negative breast cancer (TNBC), and urothelial carcinoma (UC) [15][16][17][18][19][20][21]. Using data from a real-world UNC-108 cohort, the results confirmed the findings of the IMvigor210 study that the IO score is associated with the efficacy of ICI therapy in mUC [18].…”

Section: Introductionmentioning

confidence: 99%

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The 27-gene IO score is associated with efficacy of PD-1/L1 inhibitors independent of FGFR expression in a real-world metastatic urothelial carcinoma cohort

Nielsen¹,

Varga²,

Cronister³

et al. 2023

Cancer Immunol Immunother

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Multiple targeted therapeutics have been approved by the FDA for mUC, including immune checkpoint inhibitors (ICIs) and more recently targeted agents for both FGFR and Nectin-4. FGFR3-aberrant and Nectin-4 expressing cells have been associated with an immunosuppressed phenotype. Given that less than half of all patients respond to these agents as monotherapies and less than 20% are eligible to receive salvage therapy, effective personalized treatment plans are critical. Typical biomarkers for ICIs such as PD-L1 and TMB have not been definitive in mUC, yet a biomarker-driven optimization of first-line therapy and subsequent sequencing have the potential to achieve higher and more durable response rates. The IO score is a 27-gene tumor immune microenvironment (TIME) classifier that has been associated with the clinical benefits of ICIs in multiple cancer types, including mUC. This study demonstrates that the IO score was associated with both progression-free survival (PFS) and overall survival (OS) in a real-world cohort of mUC patients treated with ICIs. Furthermore, the IO score was independent of and provided information incremental to TMB. Interestingly, the IO score predicted benefit in patients with high FGFR expression, despite conflicting data regarding response rates among the FGFR aberrant population. Taken together, these results demonstrate that the IO score assessment of the TIME is associated with a clinical benefit from ICI therapy and that this novel biomarker may inform therapeutic sequencing decisions in mUC, potentially improving outcomes for this notoriously difficult-to-treat disease.

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Section: Introductionsupporting

confidence: 73%

Section: Methodsmentioning

confidence: 99%

Section: Io Score Classificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The 27-gene IO score is associated with efficacy of PD-1/L1 inhibitors independent of FGFR expression in a real-world metastatic urothelial carcinoma cohort

Nielsen¹,

Varga²,

Cronister³

et al. 2023

Cancer Immunol Immunother

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“…To date, attempts at IO biomarker development have focused on single-site biopsy-derived tumor cell surface markers and tumor genetics. Use of gene microarrays (Bonsang-Kitzis et al, 2016 ) and next generation RNA sequencing (RNA-seq) to analyze the continuously changing cellular transcriptome has emerged to attempt to capture the dynamic patient immune response in ESBC (Iwase et al, 2021 ; Saltman et al, 2022 ; Seitz et al, 2022 ). Despite RNA-seq's enriched capacity, transcriptomic properties from a focal region may not accurately reflect the overall transcriptional behavior of the tumor, or the complexity of the dynamic immune tumor microenvironment (TME).…”

Section: Introductionmentioning

confidence: 99%

Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer

Cook

Biancalana

Liadis

et al. 2023

Front. Artif. Intell.

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BackgroundImmuno-oncology (IO) therapies targeting the PD-1/PD-L1 axis, such as immune checkpoint inhibitor (ICI) antibodies, have emerged as promising treatments for early-stage breast cancer (ESBC). Despite immunotherapy's clinical significance, the number of benefiting patients remains small, and the therapy can prompt severe immune-related events. Current pathologic and transcriptomic predictions of IO response are limited in terms of accuracy and rely on single-site biopsies, which cannot fully account for tumor heterogeneity. In addition, transcriptomic analyses are costly and time-consuming. We therefore constructed a computational biomarker coupling biophysical simulations and artificial intelligence-based tissue segmentation of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRIs), enabling IO response prediction across the entire tumor.MethodsBy analyzing both single-cell and whole-tissue RNA-seq data from non-IO-treated ESBC patients, we associated gene expression levels of the PD-1/PD-L1 axis with local tumor biology. PD-L1 expression was then linked to biophysical features derived from DCE-MRIs to generate spatially- and temporally-resolved atlases (virtual tumors) of tumor biology, as well as the TumorIO biomarker of IO response. We quantified TumorIO within patient virtual tumors (n = 63) using integrative modeling to train and develop a corresponding TumorIO Score.ResultsWe validated the TumorIO biomarker and TumorIO Score in a small, independent cohort of IO-treated patients (n = 17) and correctly predicted pathologic complete response (pCR) in 15/17 individuals (88.2% accuracy), comprising 10/12 in triple negative breast cancer (TNBC) and 5/5 in HR+/HER2- tumors. We applied the TumorIO Score in a virtual clinical trial (n = 292) simulating ICI administration in an IO-naïve cohort that underwent standard chemotherapy. Using this approach, we predicted pCR rates of 67.1% for TNBC and 17.9% for HR+/HER2- tumors with addition of IO therapy; comparing favorably to empiric pCR rates derived from published trials utilizing ICI in both cancer subtypes.ConclusionThe TumorIO biomarker and TumorIO Score represent a next generation approach using integrative biophysical analysis to assess cancer responsiveness to immunotherapy. This computational biomarker performs as well as PD-L1 transcript levels in identifying a patient's likelihood of pCR following anti-PD-1 IO therapy. The TumorIO biomarker allows for rapid IO profiling of tumors and may confer high clinical decision impact to further enable personalized oncologic care.

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An Immune-Related Gene Expression Signature Predicts Benefit from Adding Atezolizumab to FOLFOXIRI plus Bevacizumab in Metastatic Colorectal Cancer

Antoniotti

Boccaccino

Seitz³

et al. 2023

Clinical Cancer Research

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Background: AtezoTRIBE phase II randomized study demonstrated that adding atezolizumab to first-line FOLFOXIRI (5fluoruracil, oxaliplatin, irinotecan) plus bevacizumab prolongs progression-free survival (PFS) of metastatic colorectal cancer (mCRC) patients, with a modest benefit among proficient mismatch repair (pMMR). DetermaIO is an immune-related 27-gene expression signature able to predict benefit from immune-checkpoint inhibition in triple-negative breast cancer. In this analysis of AtezoTRIBE, we investigated the predictive impact of DetermaIO in mCRC. Methods: mCRC patients unselected for MMR status were randomized(1:2) to FOLFOXIRI plus bevacizumab (control arm) or the same regimen with atezolizumab (atezolizumab arm). RT-qPCR by DetermaIO was performed on RNA purified from pre-treatment tumours of 132(61%) out of 218 enrolled patients. A binary result (IOpos versus IOneg) adopting the pre-established DetermaIO cut-point (0.09) was obtained, and an exploratory optimized cut-point (IOOPT) was computed in the overall population and in pMMR subgroup (IOOPTpos versus IOOPTneg). Results: DetermaIO was successfully determined in 122 (92%) cases, and 23 (27%) tumours were IOpos. IOpos tumours achieved higher PFS benefit from atezolizumab arm than IOneg (HR:0.39 versus 0.83, P interaction=0.066). In pMMR tumours (N=110), a similar trend was observed (HR:0.47 versus 0.93, P interaction=0.139). In the overall population, with the computed IOOPT cut-point (0.277), 16 (13%) tumours were IOOPTpos and they derived higher PFS benefit from atezolizumab than IOOPTneg(HR:0.10 versus 0.85, P interaction=0.004). Similar results were found in the pMMR subgroup. Conclusions :DetermaIO may be useful to predict benefit of adding atezolizumab to first-line FOLFOXIRI plus bevacizumab in mCRC. The exploratory IOOPT cut-point should be validated in independent mCRC cohorts.

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27-gene Immuno-Oncology (IO) Score is Associated With Efficacy of Checkpoint Immunotherapy in Advanced NSCLC: A Retrospective BC Cancer Study

Cited by 4 publications

References 25 publications

The 27-gene IO score is associated with efficacy of PD-1/L1 inhibitors independent of FGFR expression in a real-world metastatic urothelial carcinoma cohort

The 27-gene IO score is associated with efficacy of PD-1/L1 inhibitors independent of FGFR expression in a real-world metastatic urothelial carcinoma cohort

Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer

An Immune-Related Gene Expression Signature Predicts Benefit from Adding Atezolizumab to FOLFOXIRI plus Bevacizumab in Metastatic Colorectal Cancer

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