Quantitative Proteomic Analysis of Optimal Cutting Temperature (OCT) Embedded Core-Needle Biopsy of Lung Cancer

Abstract

With recent advances in understanding the genomic underpinnings and oncogenic drivers of pathogenesis in different subtypes, it is increasingly clear that proper pretreatment diagnostics are essential for the choice of appropriate treatment options for non-small cell lung cancer (NSCLC). Tumor tissue preservation in optimal cutting temperature (OCT) compound is commonly used in the surgical suite. However, proteins recovered from OCT-embedded specimens pose a challenge for LC-MS/MS experiments, due to the large amounts of polymers present in OCT. Here we present a simple workflow for whole proteome analysis of OCT-embedded NSCLC tissue samples, which involves a simple trichloroacetic acid precipitation step. Comparisons of protein recovery between frozen versus OCT-embedded tissue showed excellent consistency with more than 9200 proteins identified. Using an isobaric labeling strategy, we quantified more than 5400 proteins in tumor versus normal OCT-embedded core needle biopsy samples. Gene ontology analysis indicated that a number of proliferative as well as squamous cell carcinoma (SqCC) marker proteins were overexpressed in the tumor, consistent with the patient's pathology based diagnosis of "poorly differentiated SqCC". Among the most downregulated proteins in the tumor sample, we noted a number of proteins with potential immunomodulatory functions. Finally, interrogation of the aberrantly expressed proteins using a candidate approach and cross-referencing with publicly available databases led to the identification of potential druggable targets in DNA replication and DNA damage repair pathways. We conclude that our approach allows LC-MS/MS proteomic analyses on OCT-embedded lung cancer specimens, opening the way to bring powerful proteomics into the clinic. Graphical Abstract ᅟ.

Keywords: Biomarker; Drug target; Lung cancer; Pathology; Proteomics; Sample preparation.

Figure 1

Qualitative evaluation of the TCA-based OCT-removal protocol for surgically resected tumor samples. (A) Proteins identified from a frozen surgically resected SqCC tumor, and the same tumor that was embedded in OCT. The Venn diagram shows the proteins that were commonly identified from the two types of samples. Gene Ontology analysis shows the proteins identified from the frozen and OCT-embedded samples were equally represented in terms of cellular component (B) and biological process (C). (D) The number of peptides identified from several representative proteins in the abovementioned two samples. Peptide numbers were normalized by GAPDH and actin.

Figure 2

Quantitative proteomic analysis of OCT-embedded core needle biopsy (CNB) samples. (A) A photograph of the OCT-embedded CNB sample. Red and white arrows indicate the tissue and OCT compound, respectively. (B) Three technical replicate experiments were performed for each sample, i.e., 126,127 and 128 for CNB-tumor; 129, 130 and 131 for CNB-normal. The TMT reporter ion intensity (Signal-to-noise, SN) from all the peptides of a protein was summed, and was plotted for the technical replicate experiments. (C) Representative proteins that are overexpressed in CNB-tumor compared to CNB-normal.

Figure 3

Gene Ontology analysis of the SqCC proteome. (A) Comparison of protein expression between CNB-tumor and CNB-normal samples (ratio converted to a log2 scale). The OCT-embedded CNB-tumor and -normal samples were subject to the TCA-based OCT removal protocol. Proteins were extracted and digested. The resulting peptides were labeled with the TMT reagents, and were quantified using LC-MS/MS experiments. Proteins that are up-regulated or down-regulated by at least 3-fold are highlighted. Biological processes that are represented by these proteins are indicated in (B) (up-regulated) and (C) (down-regulated).

Figure 4

Representative overexpressed proteins identified from the OCT-embedded core needle biopsy samples. The MS2 spectra are shown for (A) KRT17, (B) SERPINB5, (C) S100A2 and (D) MCM6. Three replicate analyses were performed (126, 127 and 128 for CNB-tumor, and 129, 130 and 131 for CNB-normal). The TMT ion cluster is shown with the following channel information: channel 1, 2, 3, 4, 5, 6 for TMT 126, 127, 128, 129, 130 and 131, respectively.

Figure 5

Meta-analysis of the expression of representative SqCC-specific proteins in different lung cancer subtypes. RNA expression levels for (A) KRT17, (B) SERPINB5, (C) S100A2 and (D) MCM6 were extracted from publically available TCGA datasets on lung SqCC, ADC and SqCC matched normal tissues, and are shown as box and whisker plots (***, unpaired t-test, P<1E⁻¹⁵).