Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade

Lu, Steve; Stein, Julie E.; Rimm, David L.; Wang, Daphne W.; Bell, Michael A.; Johnson, Douglas B.; Sosman, Jeffrey A.; Schalper, Kurt A.; Anders, Robert A.; Wang, Hao; Hoyt, Clifford; Pardoll, Drew M.; Danilova, Ludmila; Taube, Janis M.

doi:10.1001/jamaoncol.2019.1549

Cited by 452 publications

(372 citation statements)

References 78 publications

(176 reference statements)

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“…Several biomarkers have a higher level of validation such as PD-L1 expression on cancer cells and microsatellite instability (MSI); others, such as BRCA mutation status and tumor mutation burden (TMB) showed more often contradictory results [41].…”

Section: Predictive Biomarkersmentioning

confidence: 99%

“…In the recent review by Lu et al [41], multiplex immunohistochemistry/IF and multimodality biomarker strategies appear to be associated with improved performance over PD-L1 IHC, TMB, or GEP alone. Further studies with composite approaches and a larger number of patients will be required to confirm these findings to determine the most predictive combinations according to tumor type.…”

Section: Tumor Mutation Burdenmentioning

confidence: 99%

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Immune Checkpoint Inhibitors in Epithelial Ovarian Cancer: An Overview on Efficacy and Future Perspectives

et al. 2020

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Epithelial ovarian cancer (EOC) is the leading cause of death among gynecological cancers. Despite improvements in medical treatments, the prognosis for EOC remains poor, and there is an urgent need for new therapeutic strategies. Immune checkpoint inhibitors (CPIs) have dramatically improved survival of several cancers and are under evaluation in OC. Unfortunately, CPIs have shown globally unsatisfactory results. The aim of this manuscript is to critically review the results from early-phase trials with CPIs in terms of safety and activity, discuss the possible reasons for disappointing results and the new therapeutic approaches to improve patient outcomes. However, despite the success of immunotherapy in other malignancies such as in melanoma, non-small cell lung cancer (NSCLC) and urothelial cancers [25,26], the use of antibodies inhibiting the immune checkpoint programmed cell death (PD-1) or its ligand (PD-L1) obtained modest results in EOC so far, with median response rates of 10% up to 15% [18][19][20]27].Interestingly, the combination of the anti-PD1 nivolumab and the anti-lymphocyte-associated protein 4 (anti-CTLA4) ipilimumab showed promising results in platinum-resistant EOC at six-month interim analyses with an overall response rate (ORR) of 34% (doubling the results of nivolumab monotherapy). However, final results are still awaited [28].As a consequence, no immunotherapeutic agent has obtained regulatory approval for EOC thus far. PD1/PD-L1

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Section: Predictive Biomarkersmentioning

confidence: 99%

Section: Tumor Mutation Burdenmentioning

confidence: 99%

Immune Checkpoint Inhibitors in Epithelial Ovarian Cancer: An Overview on Efficacy and Future Perspectives

et al. 2020

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“…Following recent advances in multiplexed immunofluorescence and immunohistochemistry (mIF/IHC) technology (Goltsev et al, 2018;Lin et al, 2016;Reiß et al, 2019;Tsujikawa et al, 2017), it is now possible to visualize tens or hundreds of distinct biomarkers in a single tissue section. On their own, these technologies promise a more personalized medicine through a more granular definition of disease subtypes, and will undoubtedly broaden our understanding of cellular heterogeneity and interaction within the tumor microenvironment, both of which play increasingly important roles in the development and selection of effective treatments (Lu et al, 2019;Yuan, 2016). With a paired H&E and mIF/IHC dataset that encompasses the expression of hundreds of markers within serial tissue sections, we could begin to quantify the mutual information between histology and expression of any biomarker of interest.…”

Section: Discussionmentioning

confidence: 99%

SHIFT: speedy histological-to-immunofluorescent translation of whole slide images enabled by deep learning

Burlingame

McDonnell

Schau

et al. 2019

Preprint

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KEY POINTS• Spatially-resolved molecular profiling is an essential complement to histopathological evaluation of cancer tissues.• Information obtained by immunofluorescence imaging is encoded by features in histological images.• SHIFT leverages previously unappreciated features in histological images to facilitate virtual immunofluorescence staining.• Feature representations of images guide sample selection, improving model generalizability. KEY WORDSDigital pathology, deep learning, generative adversarial networks, hematoxylin and eosin, immunofluorescence ABSTRACT Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we present a deep learning-based method called speedy histological-toimmunofluorescent translation (SHIFT) which takes histologic images of hematoxylin and eosin-stained tissue as input, then in near-real time returns inferred virtual immunofluorescence (IF) images that accurately depict the underlying distribution of phenotypes without requiring immunostaining of the tissue being tested. We show that deep learning-extracted feature representations of histological images can guide representative sample selection, which improves SHIFT generalizability. SHIFT could serve as an efficient preliminary, auxiliary, or substitute for IF by delivering multiplexed virtual IF images for a fraction of the cost and in a fraction of the time required by nascent multiplexed imaging technologies.

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“…Multiplex Immunohistochemistry/Immunofluorescence (mIHC/IF) technologies, which allow the simultaneous detection of multiple markers on a single tissue section, have been introduced and adopted in both research and clinical settings in response to increased demand for improved techniques. A number of highly multiplexed tissue imaging technologies have also emerged, permitting comprehensive studies of cell composition, functional state and cell‐cell interactions which suggest improved diagnostic benefit [1]. These novel imaging techniques are based on cyclic immunofluorescence [2], tyramide‐based mIHC/IF [3‐14], epitope‐targeted mass spectrometry [15, 16], or RNA detection [17, 18].…”

Section: Introductionmentioning

confidence: 99%

“…In a recent publication, Lu et al . [1] demonstrated that mIHC/IF appeared to be associated with improved performance in predicting response to programmed cell death ligand 1 (PD‐L1)/ programmed cell death receptor 1 (PD‐1) treatment in different solid tumor types when compared to PD‐L1 IHC, tumor mutational burden (TMB) or gene expression profiling (GEP) alone. This was shown through a meta‐analysis of studies involving tumor specimen assays of over 10 different solid tumor types in 8135 patients and the results were correlated with anti‐PD‐1/PD‐L1 immunotherapy response.…”

Section: Introductionmentioning

confidence: 99%

Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy

Tan

Nerurkar

Cai

et al. 2020

Cancer Communications

362

295

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Conventional immunohistochemistry (IHC) is a widely used diagnostic technique in tissue pathology. However, this technique is associated with a number of limitations, including high inter-observer variability and the capacity to label only one marker per tissue section. This review details various highly multiplexed techniques that have emerged to circumvent these constraints, allowing simultaneous detection of multiple markers on a single tissue section and the comprehensive study of cell composition, cellular functional and cell-cell interactions. Among these techniques, multiplex Immunohistochemistry/Immunofluorescence (mIHC/IF) has emerged to be particularly promising. mIHC/IF provides high-throughput multiplex staining and standardized quantitative analysis for highly reproducible, efficient and cost-effective tissue studies. This technique has immediate potential for translational research and clinical practice, particularly in the era of cancer immunotherapy.

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Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade

Cited by 452 publications

References 78 publications

Immune Checkpoint Inhibitors in Epithelial Ovarian Cancer: An Overview on Efficacy and Future Perspectives

Immune Checkpoint Inhibitors in Epithelial Ovarian Cancer: An Overview on Efficacy and Future Perspectives

SHIFT: speedy histological-to-immunofluorescent translation of whole slide images enabled by deep learning

Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy

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