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webinar
Jennifer Giltnane MD, PhD

Principal Pathologist-Scientist, Genentech

Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

Length: 46 minutes

Relevant for

FixVUE, InSituPlex

Description Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients. However, most NSCLC patients do not respond to PD-(L)1 blockade as single agents, and intratumoral immune infiltrates involved in the response to these therapies remain poorly characterized. There remains a significant need to understand the biology of response and resistance and the role of infiltrating immune cells. Recent studies have suggested an association between increased B cell infiltration, along with the presence of tertiary lymphoid structures (TLSs) and improved response to immunotherapy in tumors from melanoma, soft tissue sarcoma, and renal cell carcinoma patients. Herein, the webinar will discuss whether intratumoral B cells are beneficial specifically in the context of PD-(L)1 blockade or are a general marker of a better prognosis in metastatic NSCLC.

Webinar Learning Objectives

A better understanding of tumor heterogeneity, its immune environment and contextual relationship requires the spatial quantification of different immune and tumor cells along with the genetic background of the individual cancer.

The utilization of scRNA-seq and multiplexed Immunofluorescence techniques on NSCLC tumors to identify three main populations of intratumoral B and plasma cells.

An overview on the availability of digital tools in histopathology to allow interpreting the high-dimensional complexity of the spatial and immunological heterogeneity in tissue and integrating big (molecular) data to select the best and most effective treatment including combination and advanced therapies.

Meet the host

Jena Giltnane is a translational pathologist-scientist in Genentech’s division of research and early development, where she leads digital and spatial pathology in support of translational oncology and cancer immunology programs through the use of multiplexed immunofluorescence tissue assays, tissue technology evaluation, and the collaborative development of deep learning based image analysis models in digital pathology.

Dr. Giltnane completed her MD, PhD, at Yale University in the laboratory of Dr. David Rimm and postdoctoral training in the laboratory of Dr. Carlos Arteaga at Vanderbilt University, where she also completed her Residency in Anatomic and Clinical Pathology.

She is an expert in genomic and proteomic biomarkers of diagnosis, prediction, and prognosis in breast cancer and the curation and analysis of high-dimensional clinical data.

Author
Jennifer Giltnane MD, PhD

Principal Pathologist-Scientist, Genentech

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