**Combined Transcriptomic and Proteomic Profiling to Unravel Osimertinib, CARP-1 Functional Mimetic (CFM 4.17) Formulation and Telmisartan Combo Treatment in NSCLC Tumor Xenografts**

**Ramesh Nimma 1,†, Anil Kumar Kalvala 1,†, Nilkumar Patel <sup>1</sup> , Sunil Kumar Surapaneni <sup>1</sup> , Li Sun <sup>2</sup> , Rakesh Singh <sup>3</sup> , Ebony Nottingham <sup>1</sup> , Arvind Bagde <sup>1</sup> , Nagavendra Kommineni <sup>1</sup> , Peggy Arthur <sup>1</sup> , Aakash Nathani <sup>1</sup> , David G. Meckes, Jr. <sup>2</sup> and Mandip Singh 1,\***


**Abstract:** The epidermal growth factor receptor (EGFR) is highly expressed in many non-small cell lung cancers (NSCLC), necessitating the use of EGFR-tyrosine kinase inhibitors (TKIs) as first-line treatments. Osimertinib (OSM), a third-generation TKI, is routinely used in clinics, but T790M mutations in exon 20 of the EGFR receptor lead to resistance against OSM, necessitating the development of more effective therapeutics. Telmisartan (TLM), OSM, and cell cycle and apoptosis regulatory protein 1 (CARP-1) functional mimetic treatments (CFM4.17) were evaluated in this study against experimental H1975 tumor xenografts to ascertain their anti-cancer effects. Briefly, tumor growth was studied in H1975 xenografts in athymic nude mice, gene and protein expressions were analyzed using next-generation RNA sequencing, proteomics, RT-PCR, and Western blotting. TLM pre-treatment significantly reduced the tumor burden when combined with CFM-4.17 nanoformulation and OSM combination (TLM\_CFM-F\_OSM) than their respective single treatments or combination of OSM and TLM with CFM 4.17. Data from RNA sequencing and proteomics revealed that TLM\_CFM-F\_OSM decreased the expression of Lamin B2, STAT3, SOD, NFKB, MMP-1, TGF beta, Sox-2, and PD-L1 proteins while increasing the expression of AMPK proteins, which was also confirmed by RT-PCR, proteomics, and Western blotting. According to our findings, the TLM\_CFM-F\_OSM combination has a superior anti-cancer effect in the treatment of NSCLC by affecting multiple resistant markers that regulate mitochondrial homeostasis, inflammation, oxidative stress, and apoptosis.

**Keywords:** epidermal growth factor receptor; non-small cell lung cancer; Lamin B2; AMPK; Osimertinib; RNA seq; proteomics; RT-PCR

#### **1. Introduction**

Lung cancer is still the deadliest cancer globally, and the World Health Organization estimates that 2.09 million new cases are reported each year, with 1.76 million deaths (18.4 percent of all cancer deaths) [1]. Non-small cell lung cancer (NSCLC) accounts for over 85% of lung cancer cases, and its incidence is increasing every year, seriously threatening human health [2].

**Citation:** Nimma, R.; Kalvala, A.K.; Patel, N.; Surapaneni, S.K.; Sun, L.; Singh, R.; Nottingham, E.; Bagde, A.; Kommineni, N.; Arthur, P.; et al. Combined Transcriptomic and Proteomic Profiling to Unravel Osimertinib, CARP-1 Functional Mimetic (CFM 4.17) Formulation and Telmisartan Combo Treatment in NSCLC Tumor Xenografts. *Pharmaceutics* **2022**, *14*, 1156. https://doi.org/10.3390/ pharmaceutics14061156

Academic Editors: Vibhuti Agrahari and Prashant Kumar

Received: 15 March 2022 Accepted: 11 May 2022 Published: 28 May 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Tyrosine kinase inhibitors (TKIs) are the majorly front-line agents for treating NSCLC over platinum doublet chemotherapy [3]. Resistance to chemotherapy develops in many patients, and more than 20 percent of NSCLC patients show epidermal growth factor receptor (EFGR) mutations [4,5]. Erlotinib and Gefitinib, which are the first-generation EGFR targeted TKIs, bind to EGFR reversibly, leading cells to acquire resistance by inducing mutations that enhance the affinity to Adenosine triphosphate (ATP) (T790M-mutation), resulting in decreased interaction with its receptors following therapy [6]. Afatinib and Dacomitinib are second-line EGFR TKIs that bind to EGFR permanently and show beneficial effects in cancer therapy, but there have been toxicity concerns due to elevated wild-type EGFR off-target binding [7]. Osimertinib (OSM) is a third-generation EGFR-TKI, irreversibly binds EGFR protein activating mutations (such as L858R and Exon19 del) and also targets EGFR TKIs resistant mutations that reduce interaction with wild-type EGFR [8]. The EGFR C797S mutation has been linked to OSM resistance by enhancing receptor affinity to ATP. Additionally, the combination therapy with various TKIs has been suggested as an excellent way to combat resistance, though there are some drawbacks, such as enhanced toxicity [9]. Even though radiotherapy and chemotherapy can help advanced patients to improve their survival rate [10–16], these approaches are toxic to normal cells resulting in impaired immunity, bone marrow suppression and neurotoxicity [17]. Molecular targeted therapy has gradually become a new choice because of its low dosage, remarkable effect, strong specificity, and low side effects [18].

Several reports suggested that OSM inhibits the activation of several downstream pathways, such as RAS/RAF/MAPK and PI3K/AKT, and regulates different cellular processes, including DNA synthesis and proliferation [19]. Cell cycle and apoptosis regulator protein 1 (CARP-1/CCAR1) is a perinuclear phosphoprotein that co-activates the anaphasepromoting complex/cyclosome (APC/C), an E3-ubiquitin ligase, which affects cell cycle and tumor growth [20,21]. Through p53 co-activation, it also regulates chemotherapyinduced apoptosis [21]. CARP-1 functional mimetics (CFMs) inhibit cell growth in various cancer cells and cause apoptosis via lowering CARP-1 binding to the APC/C component APC2 [22]. Previous research on CARP-1 functional mimetics has primarily investigated their role in CARP-1 signaling, ignoring their ability to suppress EGFR activation. According to molecular docking studies, both CFM4.16 and CFM4.17 have been shown to bind with EGFR's ATP binding site [6]. This is consistent with the work of other investigators who have demonstrated that compounds with the ability to target numerous components in the EGFR signaling cascade are more inhibited than those with only one target [23].

Many anti-cancer drugs are ineffective due to high interstitial pressure or tumor stromal barriers. In addition to its role in decreasing tumor interstitial barriers, telmisartan (TLM) has also been shown to aid in the delivery of nanoparticles and liposomes to tumor cells [24–31]. TLM promotes the peroxisome proliferator-activated receptor (PPAR) pathways by inhibiting PI3K signaling [32,33]. In our laboratory, we have demonstrated that TLM could enhance the anti-cancer effects of sorafenib and CFM 4.16 in the rociletinibresistant H1975 NSCLC xenograft model, lowering the protein expression of p-EGFR/EGFR, Nanog, Sox2, Oct4, pMET/MET, TGF-beta, and MMP9 while raising the expression of E-cadherin protein [34].

Gene mutations are a substantial barrier to lung cancer treatment, and the ability to directly measure the expression levels of molecular drug targets and profile the activation of key molecular pathways allows the personalized prioritization of all molecular-targeted therapies [35]. For high-throughput quantitative transcriptomics, it has been observed that RNA sequencing is the most reliable tool [36]. Our studies used RNA seq analysis to investigate the downstream targets contributing to cancer cell growth in NSCLC.

A thorough understanding of molecular communication will provide new insights into the molecular process behind the disease's medication action. Proteomics, a powerful method for a detailed analysis of protein changes in response to medication therapy, has been widely used to investigate molecular pathways and identify anti-cancer therapeutic targets [37]. A recent study using proteomic analysis observed potential tyrosine kinase inhibitor (OSM) sensitivity indicators in EGFR-mutated lung cancer and identified novel targets for future therapy options [38]. In our studies, proteomics was used to explore the expression of all the proteins in H1975 tumor xenografts treated with various drugs and formulations.

EGFR TKIs are still the leading therapy for a substantial percentage of NSCLCs, and the need for resistance to TKIs remains a critical breakthrough. Herein, we hypothesize that OSM (i.e., which targets EGFR T790M mutation and inhibits activation of AMPK/Lamin-B2/MAPK and PI3K/AKT) in combination with CFM 4.17 NLPFs (i.e., CARP-1 signaling and EGFR activity is inhibited by interacting with EGFR's ATP binding site) and TLM (i.e., disrupts tumor stromal barriers and leads to enhanced permeation of drugs) will provide superior anti-cancer effects in NSCLC, and by using RNA sequence and the quantitative proteomics, we can identify novel targets that have a role to play in tumor regression.

#### **2. Materials and Methods**

#### *2.1. Materials*

CFM 4.17 was synthesized by Otava chemicals (Concord, ON, Canada), DMSO, Tween 80, Ethanol, PBS was obtained from VWR International, LLC, (Radnor, PA, USA). All additional components and reagents were bought from Sigma-Aldrich (St. Louis, MI, USA). Cell Signaling Technology provided all primary and secondary antibodies utilized in our research.

#### *2.2. Formulation of CFM 4.17 Lipid Formulation (CFM-F)*

CFM-F was formulated in our laboratory, thereby using an already published procedure that consists of a melt dispersion process (optimized with Design Expert and MATLAB utilizing the Box–Behnken developed surface response methodology). CFM-F showed enhanced efficacy and increased oral bioavailability [6].

#### *2.3. Cell Culture*

The NSCLC cell lines H1975 (E746-A750 deletion) and HCC827 were purchased from ATCC. The cells were cultured in RPMI-1640 media with 10% heat-inactivated fetal bovine serum (FBS) and (5000 units/mL penicillin, 5 mg/mL streptomycin, and 10 mg/mL neomycin; GIBCO) at 37 ◦C in 5% CO2.

#### *2.4. H1975 Xenograft Model of Non-Small Cell Lung Cancer*

The Institutional Animal Use and Care Committee of Florida Agricultural and Mechanical University evaluated and approved all animal experiment procedures as per the NIH standards and all applicable national legislation. Mice were randomly divided into 5 groups, 5 in each group. The H1975 xenograft NSCLC model was developed by injecting 2.5 million H1975 cells (in a 1:1 ratio, suspended in matrigel) into the right flank of athymic female nude mice (Foxn1nu; 20–25 grams' body weight, 5–6 weeks old). When the tumor volume reached 1500 mm<sup>3</sup> , the animals were treated for 2 weeks with CFM-F (40 mg/kg body weight) and OSM (25 mg/kg body weight) alone. For the CFM 4.17 solution, TLM, and OSM combination, animals were pre-treated with TLM (10 mg/kg body weight) three times per week, followed by two weeks of CFM4.17-solution (40 mg/kg body weight) and OSM (25 mg/kg body weight). For the TLM, CFM-F, and OSM combination, animals were given TLM (10 mg/kg body weight) three times a week for two weeks before receiving CFM-F (40 mg/kg body weight) and OSM (25 mg/kg body weight) for two weeks. During the course of the drug treatments, tumor volumes were measured twice a week. The digital vernier calliper was used to measure the width and length of the tumor. The formula used to calculate the tumor volume (TV) was: TV = <sup>1</sup> 2 ab<sup>2</sup> , where 'a' and 'b' denotes the tumor's length and width, respectively. The animals were then monitored regularly for their health and mobility, and when the tumor burden increased beyond 6000 mm<sup>3</sup> , the animals were sacrificed, and tumor and blood sample was collected from all animals for proteomic, RNA-seq, and Western blot experiments. Throughout the treatment, the tumor

volume was measured twice weekly. The blood samples were further processed to collect the serum, then processed for TotalSeq analysis.

#### *2.5. RNA Sequencing and Data Analysis*

The manufacturer's instructions were followed to isolate total RNAs from tumor samples using the Trizol reagent (ThermoFisher, Waltham, MA, USA; 15596018). The DNase I treatment aids in the removal of traces of genomic DNA contamination in the samples. The mRNA library was created using the NEBNext Ultra RNA Library Prep Kit (NEB, E7530) and the NEBNext Poly (A) mRNA Magnetic Isolation Module (NEB, E7490). For quality control, the library was processed on an Agilent Bioanalyzer with HS DNA chip (5067-4626), and the quantification was conducted with the KAPA Library Quantification Kit (KR0405). The library was then pooled at the requisite equal molar concentrations and transferred to the Florida State University (FSU), College of Medicine Translational Laboratory for Illumina NovaSeq 6000 sequencing.

Network Analyst 3.0 software (Guangyan Zhou, Quebec, QC, Canada)was used to analyze the RNA sequencing data; genes with a count of 10%, a variance of 10%, and unannotated were separated and standardized using Log2 counts per million [39]. DEseq2 was used to find the differentially expressed genes [40]. The heatmap aids in the visualization of differentially expressed genes and gene enriched pathways, which may be seen using the same web application. The volcano graphing was conducted using a DESeq2 data set and the log10 (FDR corrected *p*-value) to the log2 (fold change).

#### *2.6. Proteomics*

As per the manufacturer's protocol, in-solution digestion was carried out on an S-trap microcolumn (Prod # CO2-micro-80, Protifi). Briefly, 100 µg of lyophilized protein was resuspended in sodium dodecyl sulphate (5%), TEAB (50 mM) pH 8.5 and reduced by adding 1 µL of TCEP (5 mM final concentration) and incubating for 15 min at 55 ◦C. This was followed by alkylating the mixture by adding 1 µL of alkylating agent (Iodoacetamide, final concentration 20 mM) and incubating at RT in the dark for over 10 min. The mixture was acidified by adding 2.5 µL of phosphoric acid (final concentration ~2.5%) and vortexed thoroughly. Wash/Binding buffer (TEAB-100 mM (final) in 90% methanol, 165 µL) was added to the sample and mixed well. This mixture was transferred onto the S-Trap and placed in a 1.7 mL Eppendorf tube for flow-through (waste). Proteins were trapped onto the column by centrifuging at 4000× *g* for 30 s. Trapped protein was washed thrice with 150 µL of wash buffer (TEAB-100 mM (final) in 90% methanol). To fully remove wash/binding buffer, S-Trap columns were spun at 4000 g for 1 min and transferred to a new 1.7 mL Eppendorf tube for digestion. The protein was digested by adding 5 µg of trypsin in 20 µL of digestion buffer (100 mM TEAB) and incubating the tube at 37 ◦C overnight. Peptides were eluted sequentially by adding 40 µL of 50 mM TEAB in water, followed by formic acid (0.2%) in purified water and finally 50% acetonitrile in purified water and spinning the column at 4000 g for 1 min. Peptides from elution solution dried in a speed vac and dissolved at 1 µg/µL in formic acid (0.1%) and transferred into auto sampler glass vials.

The peptides were analyzed on an Exploris 480 Orbitrap mass spectrometer (Thermo Fischer Scientific, Bremen, Germany) connected to an Easy-nLC-1200 nanoflow liquid chromatography system (Thermo Scientific). One microgram of the peptide was loaded onto a 2 cm trap column (nanoViper, 3 µm C18 Aq) (Thermo Fisher Scientific). The samples were then analyzed on the 100 C18 HPLC Analytical Column (Acclaim™ PepMap™, 0.075 mm internal diameter, 2 mM C18 particle size, and 150 mm long Cat# 164534) using a 180 min linear gradient of buffer B (90% acetonitrile and 0.1% formic acid) at the flow rate of 300 nL/min. Full MS scans were obtained in the range of 350–1700 *m*/*z* at a resolution of 60,000 with a threshold intensity of 5000 and dynamic exclusion of 20 s using the topN method, taking the MS2 of the top 40 ions at 15,000 resolution.

Proteomic raw data were acquired from mass spectrometry by data-dependent acquisition (DDA) method and analyzed by Proteome Discoverer software (Version 2.5, (Thermo Fisher Scientific, Waltham, MA, USA)) using the Mascot software search engine to search against the uniport homo sapiens database [41,42]. The following criteria were applied to obtain differentially expressed proteins: (a) peptides with peptide score ≥ 10; (b) high protein false discovery rate (FDR) confidence < 0.01; and (c) unique peptides after digestion, and a *p*-value at ≤0.05 was used for protein grouping and significantly differentially expressed proteins were identified by setting the threshold fold change value ≥ 1.5. Differentially expressed proteins were organized into different groups with the approach: biological process and molecular functions using Gene Ontology (GO) assignments and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways by DAVID software [43].

#### *2.7. RNA Isolation*

Total RNA was extracted from tissues using TRIzol reagent (Invitrogen, California, USA) and purified using an RNeasy Mini kit (Qiagen, Germantown, MD, USA). Each sample's A260/280 absorbance ratio was measured using a Nanodrop spectrophotometer to evaluate its RNA quality and integrity (ND-1000).

#### *2.8. Reverse Transcription and RT-qPCR*

To examine the mRNA levels of specific genes, cDNA synthesis from total RNA was performed according to the manufacturer's instructions using the Maxima H Minus Firststrand cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA, USA). Various gene primers (Lamin B2, SOX2, STAT3, NFKB, SOD, MRC-1, and Histone 1 were purchased from Integrated DNA Technologies, Inc. (Redwood City, CA, USA) (Table 1). Quantitative PCR was used to detect gene expression using SsoAdvancedTM Universal SYBR Green Supermix (Bio-Rad) and the CFX96 TouchTM Real-Time PCR Detection System (Bio-Rad Laboratories). Post amplification, a melt curve analysis was used to determine the reaction's specificity. The whole mean expression level of both 18S rRNA and GAPDH genes was used as a reference for comparison when assessing relative mRNA expression using the comparative Ct (∆Ct) technique.


**Table 1.** Primer list.
