MSACL 2018 US Abstract

Topic: Proteomics

Tumor Tissue Proteomics in the CAP/CLIA Laboratory: A 5-year Update

Maryann Vogelsang (Presenter)
NantOmics

Authorship: Todd Hembrough, PhD and Maryann Vogelsang, PhD
NantOmics, Rockville, MD

Short Abstract

By 2024, an estimated 19 million cancer survivors will be living in the United States. Successful treatment is increasingly dependent on detailed molecular characterization of a patient’s cancer to inform selection of personalized therapies. Targeted mass spectrometry can provide precise, multiplexed analysis of treatment-related tumor biomarkers. During the past 5 years, thousands of formalin-fixed, paraffin-embedded tumor samples have been submitted to our CAP/CLIA-certified laboratory for proteomic and genomic profiling. This talk will share data and lessons learned from quantitative mass spectrometric analysis of clinical tumor samples and from research on the relationships between tumor protein expression and response to cancer therapies.

Long Abstract

Introduction

By 2024, an estimated 19 million cancer survivors will be living in the United States. Successful treatment is increasingly dependent on detailed molecular characterization of a patient’s cancer to inform selection of personalized therapies. Targeted mass spectrometry can provide precise, multiplexed analysis of treatment-related tumor biomarkers. During the past 5 years, thousands of formalin-fixed, paraffin-embedded tumor samples have been submitted to our CAP/CLIA-certified laboratory for proteomic and genomic profiling. This talk will share data and lessons learned from quantitative mass spectrometric analysis of clinical tumor samples. We present our process for quantitating large multiplexed assay for many approved drug targets and clinical trial therapies. We will report the prevalence of actionable biomarkers across different cancer indications and our experience in identifying targets for approved chemotherapies in cancer indications.

Methods

Our clinical laboratory received formalin-fixed, paraffin-embedded (FFPE) samples from physicians. We also received cohorts of tumor samples for research from collaborators in Spain, Italy, Korea and the United States. Target proteins were quantitated by selected reaction monitoring mass spectrometry (SRM-MS) as previously described.[1] For each sample, a tissue section cut from each FFPE block was mounted on microscope slides, deparaffinized, and stained with hematoxylin. Tumor areas were marked by a board-certified pathologist to achieve a cumulative tumor area of 12 mm2. Sequential tissue sections were cut from the same FFPE block, mounted onto DIRECTOR® microdissection slides, and deparaffinized. Marked tumor areas were microdissected using a non-contact laser method, and captured tumor cells were solubilized to tryptic peptides using the Liquid Tissue® technology. Total protein concentration of each tryptic peptide mixture was measured using a Micro BCA Assay Kit (Thermo Fisher Scientific, Waltham, MA).

Each sample (1 µg of tryptic peptide mixture) was analyzed by SRM-MS analysis on a TSQ Quantiva™ triple quadrupole mass spectrometer (Thermo Scientific, San Jose, CA). Stable isotope-labeled internal standard peptides were added to each sample for accurate quantitation of analytical targets. Mass spectrometry data analysis was performed using Pinpoint™ software (Version 3.0; Thermo Scientific, San Jose, CA) and Pinnacle software (Optys Tech Corp., Boston, MA).

Progression-free survival (PFS) and overall survival (OS) were estimated by the Kaplan-Meier method. Statistical analyses were carried out using R version 3.1.2, STATA version 12, and Prism.

Results

We present prevalence data from our clinical laboratory and findings from research on the relationships between tumor protein expression and response to cancer therapies across different cancer indications:

• Breast cancer patients with positive human epidermal growth factor receptor 2 (HER2) expression by immunohistochemistry (IHC) expressed a 100-fold range of HER2 protein. A similar range was found among gastric cancer patients determined to be HER2 positive by conventional testing.

• A threshold for response to therapy targeting HER2 was identified by HER2 protein expression above 2200 amol/ug and 1825 amol/ug in breast and gastric cancers, respectively.[2, 3]

• HER2 quantification by SRM-MS demonstrated that 10% of breast tumors and 22% of gastric tumors were falsely positive by HER2 IHC.

• Low TUBB3 expression levels (<700 amol/ug) identified a subset of gastric cancer patients who benefitted from the addition of docetaxel to adjuvant chemotherapy; patients with high TUBB3 expression levels had worse outcomes on a docetaxel-containing regimen than on chemotherapy without docetaxel.

• In patient samples of lung cancer and melanoma, tumor and lymphocytes expressed several immunomarker proteins. There was a differential expression of these immunomarkers between tumor infiltrated lymphocytes (TILs) and tumor regions in each sample.[4]

Conclusions & Discussion

Quantitative proteomic cutoffs can identify patients likely to respond to targeted therapy and conventional chemotherapeutic agents. Among tumor samples deemed “HER2 positive” by IHC, a wide dynamic range of HER2 expression may be quantified by MS. Quantification of HER2 protein and other drug targets by mass spectrometry could prevent missed opportunities for treatment and protect patients from the toxicity of ineffective treatment.


References & Acknowledgements:

1. Hembrough, T., et al., Application of selected reaction monitoring for multiplex quantification of clinically validated biomarkers in formalin-fixed, paraffin-embedded tumor tissue. J Mol Diagn, 2013. 15(4): p. 454-65.

2. An, E., et al., Quantitative proteomic analysis of HER2 expression in the selection of gastric cancer patients for trastuzumab treatment. Ann Oncol, 2016.

3. Nuciforo, P., et al., High HER2 protein levels correlate with increased survival in breast cancer patients treated with anti-HER2 therapy. Mol Oncol, 2016. 10(1): p. 138-47.

4. Schwartz, S., et al., Abstract 2666: Using “omics” to select immunotherapy and conventional therapy combinations. Cancer Research, 2017. 77(13 Supplement): p. 2666-2666.


Financial Disclosure

DescriptionY/NSource
Grantsno
SalaryyesNantOmics
Board Memberno
Stockyes NantOmics
Expensesno

IP Royalty: no

Planning to mention or discuss specific products or technology of the company(ies) listed above:

yes