KRAS-Positive Vs. -Negative Tumors Exhibited Unique ERK Protein Signatures.

KRAS activates ERK signaling (1, 3, 29). KRAS-positive vs. -negative lung tumors were found to exhibit ERK2 vs. ERK1 activation (Fig. 3 A and B). The KRAS-positive tumors exhibited increased pERK2a, pERK2b, and ERK2, and the KRAS-negative tumors exhibited increased ppERK1 and a decrease in the levels of ERK1 compared with matched normal lung tissue (Fig. 3 C and D). Using NIA, distinction between the different activation of various ERK phosphoisoforms by KRAS was achieved, which corroborates previous observations of ERK induction by KRAS (29, 30).

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Fig. 3.

NIA ERK protein signatures: (A) normal vs. human KRAS-associated lung cancer tissue (n = 6), (B) normal vs. human non-KRAS lung cancer tissue (n = 6), and percentages of total ERK in (C) KRAS tumors and (D) non-KRAS tumors. *Statistical significance by t test for P value <0.05. **Statistical significance by t test for P value <0.01.

KRAS-Positive Tumors Exhibit Unique Lipid Profiles.

DESI-MSI was performed on KRAS-positive mouse and human lung adenocarcinomas (Fig. S1). Tissues were harvested from transgenic mouse models harboring a conditional KRAS activation system (Fig. S2). We show representative mass spectra and selected 2D ion images from tissue samples of KRAS-induced lung adenocarcinoma and a tissue sample of control normal lung tissue (Fig. 4 and Fig. S3). As displayed in the 2D ion images of the KRAS-induced lung adenocarcinoma sample (Fig. 4A), high relative intensities of lipid ions were observed in specific regions of the cancer tissue section. Histopathologic evaluation of H&E-stained adjacent tissues sections confirmed that the high-lipid intensity regions strongly correlated with regions of accumulation of tumor cells (Fig. S3).

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Fig. 4.

DESI mass spectra of lipids: images of several lipid species overexpressed in (Upper) mouse tumor foci compared with normal mouse lung tissue and (Lower) corresponding representative mass spectra.

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Fig. S1.

DESI-MSI instrument setup.

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Fig. S2.

Tetracycline-based conditional oncogene activation. In the absence of doxycycline (dox), rtTA is unable to bind tetO sequences; therefore, oncogene expression does not occur. When dox is added, rtTA binds dox and undergoes a conformational change, which permits it to bind tetO sequences and activate oncogene expression. This system is used to conditionally activate oncogene expression in transgenic mouse models.

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Fig. S3.

DESI-MSI image and representative mass spectra of a solid pattern adenoma focus. H&E staining of the imaged tissue confirms several regions with adenoma, which are marked in red.

Differences in the DESI mass spectra extracted from these cancer regions were seen compared with spectra from normal lung tissues (Fig. 4B). For example, in the m/z region 700–1,000, where most complex glycerophospholipids are observed, an increase in the relative and total abundances of m/z 745.5034, glycerophosphoglycerol (PG; 18:1/16:1); m/z 747.5190, PG(18:1/16:0); m/z 793.5023, PG(18:2/20:4); and m/z 865.5034, PG(22:6/22:6) was detected. Changes in the relative and total abundances of free FAs in the m/z 200–400 were also observed, including m/z 255.2339, palmitic acid FA(16:0); m/z 281.2490, oleic acid FA(18:1); m/z 303.2333, arachidonic acid FA(20:4); and m/z 327.2334, docosahexaenoic acid, FA(22:6). All identifications were made by tandem MS (Table S2). Although the majority of these lipid species are common in both the adjacent normal tissues and normal lung control tissues, the total and relative abundances of these species are remarkably lower in normal tissue than in the cancer tissues. These results were consistently observed in other samples of KRAS-induced lung cancer and normal lung samples from other mice. Our results suggest that KRAS induces overexpression of lipids, including FAs and phospholipids, and is associated with a lipid profile that is distinct from normal lung tissues.

Patient Tissue Samples.

Human lung adenocarcinoma samples with their matched normal tissue controls were purchased from the Vanderbilt University Thoracic Program Bio Repository, where informed consent was obtained from all participants under Institutional Review Board (IRB) Protocol 000616 approved by the Vanderbilt University Medical Center IRB Committee. The patient samples used in this study along with their KRAS mutations status are shown (Table S3).

Tetracycline-Based Conditional Murine Models.

A Tet-On system was used to conditionally activate KRAS4b^G12D, an oncogenic form of a KRAS splice variant, in the lung tissue of transgenic mice. In this system, the gene encoding a reversible tetracycline transactivating factor (rtTA) is placed under the control of the Clara cell secretory protein (CCSP) promoter that drives its constitutive expression in lung Clara cells and type II pneumocytes. KRAS4b^G12D cDNA is placed under the control of the tetracycline-responsive minimal promoter (TetO-KRAS4b^G12D). In the absence of tetracycline, rtTA binds TetO sequences and represses transcription of the oncogene. In the presence of tetracycline, the binding of doxycycline to rtTA renders rtTA unable to bind TetO sequences, resulting in the activation of oncogene transcription. Mutant KRAS is activated by administering doxycycline (Sigma-Aldrich) to the drinking water (100 mg/mL) starting at the age of 4 wk. KRAS-induced lung tumors from four mice and normal lung tissues from three mice were harvested at week 24 and then analyzed by DESI-MSI. All animal studies were approved by the Stanford University Administrative Panel on Laboratory Animal Care. CCSP-rtTA/TetO-KRAS4b^G12D bitransgenic mice were used (23). An illustration of the Tet-On regulatory system present in these transgenic mice is shown (Fig. S2).

Microarray.

Microarray analyses were performed by the Stanford Functional Genomics Facility using the Illumina WG6 mouse microarray platform. Whole-genome gene expression profiling was performed to compare gene expression for lung tissue from transgenic mice with KRAS turned on vs. KRAS turned off. The data were log2-transformed and quantile-normalized.

Cell Culture.

The human nonsmall cell lung carcinoma cell lines, A549 and H1299, were used for in vitro experiments. A549 cells were maintained in DMEM supplemented with 10% (vol/vol) FBS, 1% l-glutamine, 1% sodium pyruvate, 1% nonessential amino acids, and Antibiotic–Antimycotic. H1299 cells were maintained in RPMI medium 1640 supplemented with 10% (vol/vol) FBS, 50 μM β-mercaptoethanol, and Antibiotic–Antimycotic. Trypsin-EDTA was used to passage both A549 and H1299 cells. All cell culture reagents were purchased from Gibco (Thermo Fisher Scientific Inc.).

Small Molecule Inhibitors.

The small molecules, SCH772984 (Cayman) at 125 ng/mL, FTS (Sigma-Aldrich) at 5–20 ng/mL, and cerulenin (Sigma-Aldrich) at 1–10 µg/mL, were added to cell culture medium to achieve inhibition of ERK, KRAS, and FASN, respectively. FTS is a synthetic farnesylcysteine mimetic that interferes with the anchoring of KRAS to the plasma membrane (29). Cerulenin irreversibly inhibits FASN by covalently binding to the enzyme (36). Various levels of these drugs were administered to cells in culture over a time course to assess dose–response relationships.

Cell Counting.

A volume of cells was removed from culture medium and mixed with an equal volume of 0.4% Trypan blue stain. Then, 10 µL were taken out and placed into a hemocytometer for cell counting. Viable cell counts were used as a measure of cell proliferation.

RNA Extraction and cDNA Synthesis.

Total RNA was isolated from cells and lung tissue using the QIAGEN RNeasy Mini Kit. RNA quality and concentration were assessed by the NanoDrop spectrophotometer. The RNA was reverse-transcribed into cDNA using the SuperScript III First-Strand Synthesis System (Invitrogen). All procedures were carried out according to the manufacturer’s protocols.

Real-Time PCR.

Real-time PCR was performed in 384-well plates on the QuantStudio 12K Flex Real-Time PCR System. Amplicons were detected by using SYBR Green I dye as fluorophore. Reactions were carried out in 20-μL volumes that contained 1 μL cDNA, 0.5 μM forward and reverse primers, and SYBR Green PCR Master Mix (Applied Biosystems). The amplification cycle was set as follows: 50 °C for 2 min; 95 °C for 10 min; and 40 cycles of 95 °C for 15 s, 60 °C for 1 min, and 72 °C for 30 s. After the amplification stage, a melt curve was performed to identify any nonspecific amplification. For each gene, a threshold cycle (Ct) number, which represents the number of cycles required to reach the threshold fluorescence, was determined. The Ct values were exported into Excel for statistical analysis. Ubiquitin was used as a housekeeping (reference) gene. The 2^−CT method was used to determine relative mRNA expression levels. Table S4 lists the real-time PCR primers used in this study.

NIA.

NIA was performed using the Nanopro 1000 (Protein Simple) to detect the phosphorylation states of ERK1 and ERK2 in lysates generated from lung tumor tissue. NIA is a highly sensitive capillary-based isoelectric focusing method that uses antibody detection to quantify protein isoforms as well as characterize posttranslational protein modifications, such as phosphorylation. The final protein concentration loaded into each capillary of the Nanopro 1000 was 0.1 µg/µL. The primary rabbit antibody for ERK1/2 (Millipore) was diluted 1:300, and the primary mouse antibody for the loading control, Hsp70 (Santa Cruz Biosciences), was diluted 1:500. The anti-mouse and -rabbit secondary antibodies conjugated to HRP were diluted 1:100. Chemiluminescence signal was recorded after the addition of luminol and peroxide detection reagents. Analysis of NIA data was performed in Compass software (Protein Simple).

We thank Harold Varmus for the CCSP-rtTA/TetO-KRAS4b^G12D bitransgenic mice, and are grateful to Translational Applications Service Center at Stanford for the Nano Immuno Assay experiments. A.M.G. and K.M. acknowledge Stanford Cancer Translational Nanotechnology Training T32 Training Grant T32 CA196585 funded by the National Cancer Institute and the Stanford Center of Molecular Analysis and Design, respectively. This work is supported by NIH Grant R01CA184384.