*2.9. TotalSeq Assay for Serum EVs*

A thawed mouse serum sample was then mixed with sterile-filtered PBS (1:1) and centrifuged at 10,000× *g* for 15 min to remove debris. For ultracentrifugation, the collected serum was further diluted with 1 mL PBS (particle-free) and centrifuged for one hour at 100,000× *g*. The serum was further diluted and combined with an 8% polyethylene glycol (PEG) solution for 30 min for the Extra PEG procedure. The pellet was resuspended in PBS after a 3000× *g* centrifugation and purified further with ultracentrifugation at 100,000× *g* for 1 h. They were all resuspended to their original volume to make the ultracentrifuged pellets comparable. The isolated EVs were used for TotalSeq assays.

Protein from the EVs sample was lysed with 0.1 percent SDS for the TotalSeq antibody assay. One microgram of EV protein was blotted onto a nitrocellulose membrane strip. On the same strip, 1 microliter of 2.5% casein blocking buffer (sheared salmon sperm ssDNA (100 g/mL and 0.05 percent tween-20 in PBS) was blotted and air-dried. Then, the strip was placed in a 1.7 mL Eppendorf tube, and a casein-blocking buffer was used for

blocking for 1 h at RT. TotalSeq-A antibodies were used in this assay including TotalSeq-A0404 anti-human CD63 Antibody (353035), TotalSeq-A0132 anti-human EGFR Antibody (352923), TotalSeq-A0190 anti-mouse CD274 (PD-L1) Antibody, TotalSeq-A0373 anti-human CD81 (TAPA-1) Antibody (349521) in 100 µL casein blocking solution, a dilution of 1:2000, a TotalSeq-A antibody pool was added and incubated overnight at 4 ◦C. The strips were washed 5 times with PBST (0.05% tween 20 in PBS) and one time with sterile water. Using absorbent paper, excess liquid was collected from the strip and then transferred to a fresh PCR tube. The extension mix consisted of 1X buffer 2, 1 U Klenow enzyme, dNTP, and 3'-Adaptor (500 nM working concentration). Fifteen microliters extension mix was added to the fresh PCR tube to immerse the strip thoroughly. The PCR tube was then incubated for 5 min at RT before being heat-inactivated for 5 min at 95 ◦C on an Eppendorf PCR machine. In a 15 µL qPCR experiment, TotalSeq DNA full-length products were measured using TotalSeq forward primer and universal R primer. For all of the TotalSeq antibodies that had been tested, the supernatant was utilized as a qPCR template. In a 15 µL qPCR run, the TotalSeq DNA full-length products were measured using TotalSeq forward primer and universal-R primer [44].

#### *2.10. Western Blot Analysis*

The whole-cell lysates were prepared from tissues in radioimmunoassay buffer (RIPA) (Cell Signaling, Danvers, MA, USA), which consists of 1:100 protease and phosphatase inhibitors. The supernatant was recovered after centrifuging the tissue homogenates at 10,000× *g* for 20 min at 4◦ C. The bicinchoninic acid (BCA) assay was used to estimate protein levels. The samples (40 µg) were loaded on a precast gel with 10% SDS-PAGE (Mini-PROTEAN® TGX™ Precast Gels) at 80 V, 100 mA for 2 h. The proteins were then transferred into the PVDF membrane (Bio-Rad Laboratories, Hercules, CA, USA) and further blocked with 3% BSA PBS-T for 1 h at RT. The blot was then incubated with primary antibody (Table 2, 1:1000) overnight and washed thrice with 10 mL of PBS-T for 10 min. The blot was then incubated for 1 h at room temperature with the secondary antibody (1:8000). The blots were washed three times with PBS-T for ten minutes each time and then incubated with SuperSignal West Pico Chemiluminescent substrate, and pictures were recorded with a Chemidoc. The blots were also quantified using the NIH ImageJ software's densitometry.


**Table 2.** Antibody list.

#### *2.11. Statistical Analysis 2.11. Statistical Analysis*  The mean ± standard error is used to describe all of the data presented. GraphPad

The mean ± standard error is used to describe all of the data presented. GraphPad Prism version 5.0 (Dr. Harvey Motulsky, San Diego, CA, USA) was used to evaluate a significant difference between the treatment groups using either a Student *t*-test or a one-way ANOVA. When the one-way ANOVA demonstrated statistical significance, Bonferroni's multiple comparisons test was used for post hoc analysis. Statistical significance was defined as a *p*-value < 0.05. Prism version 5.0 (Dr. Harvey Motulsky, San Diego, CA, USA) was used to evaluate a significant difference between the treatment groups using either a Student t-test or a oneway ANOVA. When the one-way ANOVA demonstrated statistical significance, Bonferroni's multiple comparisons test was used for post hoc analysis. Statistical significance was defined as a *p*-value < 0.05. **3. Results** 

9 p38 Cell Signaling Technology 8690 10 P53 Cell Signaling Technology 2527 11 HSC 70 Santa Cruz Biotechnology sc-7298 12 TSG 101 Cell Signaling Technology 28405 13 CD 63 Cell Signaling Technology 28405 14 Calnexin Cell Signaling Technology 2679 15 Flotillin-2 Cell Signaling Technology 3436 16 Caveolin-1 Cell Signaling Technology 3267

#### **3. Results** *3.1. Effect of TLM\_CFM-F\_OSM on Tumor Volume in the In Vivo Mouse Model*

#### *3.1. Effect of TLM\_CFM-F\_OSM on Tumor Volume in the In Vivo Mouse Model* After the 14th day post-treatment, TLM\_CFM-F\_OSM (*p* < 0.001) and TLM\_CFM-

*Pharmaceutics* **2022**, *14*, x FOR PEER REVIEW 7 of 21

After the 14th day post-treatment, TLM\_CFM-F\_OSM (*p* < 0.001) and TLM\_CFM-S\_OSM (*p* < 0.001) combination treatment group substantially reduced the tumor volume when compared to the control, as shown in Figure 1. Further, we observed that TLM\_CFM-F\_OSM demonstrated a superior anti-cancer effect in reducing the tumor burden compared to TLM\_CFM-S\_OSM (*p* < 0.05). However, when compared to normal control, OSM and CFM-F did reduce the tumor volume (*p* < 0.05) on the 14th day (Figure 1). S\_OSM (*p* < 0.001) combination treatment group substantially reduced the tumor volume when compared to the control, as shown in Figure 1. Further, we observed that TLM\_CFM-F\_OSM demonstrated a superior anti-cancer effect in reducing the tumor burden compared to TLM\_CFM-S\_OSM (*p* < 0.05). However, when compared to normal control, OSM and CFM-F did reduce the tumor volume (*p* < 0.05) on the 14th day (Figure 1).

**Figure 1.** The effect of Telmisartan, CFM-F, and Osimertinib on tumor volume in experimental NSCLC. Histogram demonstrating the H1975 tumor volumes in athymic nude mice after treatment with Osimertinib (OSM), CFM4.17 lipid formulation (CFM-F), CFM4.17 solution (CFM-S), Telmisartan (TLM) and their combinations. Data were represented as the mean ± SD of three separate experiments (*n* = 3). \*\*\* *p* < 0.001, \*\* *p* < 0.01 and \* *p* < 0.05 vs. control.

#### *3.2. RNA Sequencing and Differential Gene Expression Analysis in Lung Cancer*

When compared to normal control tissue, RNA sequencing suggested differential regulation of numerous genes after various treatments. The determination of differentially expressed genes (*p*-value < 0.05 and FC > 1.0) between normal control and treated tissues was conducted using a heatmap (Figure 2A), which demonstrated that 950 genes were upregulated, and 1240 were downregulated after treatment. The linkage of biological pathways was determined using the KEGG pathway analysis, demonstrating differentially

elevated genes. According to KEGG pathway analysis, differentially expressed genes after therapy were found to be engaged in many pathways, including spliceosome, metabolic, immunological, inflammation, mitochondrial function, apoptosis, RNA transport, and signaling. Among these, metabolic pathways (AMPK), immunological pathways (PD-L1), mitochondrial function (SOD), inflammation pathway (NFKB, STAT3, TGF beta), and apoptotic pathways (Lamin-B2, Macrophage mannose receptor 1) drew our attention because of their significance in cancer mediation shown in Figure 2. RNA seq data revealed that TLM\_CFM-F\_OSM induces downregulation of Lamin B2, MMP1, EGFR, NFKB, PD-L1, and TGF-beta genes. TLM\_CFM-F\_OSM treatment induced downregulation of Lamin B2 (i.e., 1.4-fold lower), MMP1 (i.e., 3.6-fold), EGFR (i.e., 1.8-fold), NFKB (i.e., 1.4-fold), PD-L1 (i.e., 3.46-fold), and TGF beta (i.e., 2.33-fold), in comparison to control (Figure 2H–M). *Pharmaceutics* **2022**, *14*, x FOR PEER REVIEW 9 of 21

**Figure 2.** RNA-Seq identified differential mRNA expressions and their RTPCR validation in NSCLC tumor tissues isolated from athymic nude mice (**A**) Heat map illustrations of hierarchical clustering analysis of differentially expressed mRNA in tissues of control and treated H1975 Xenograft mice. Representative volcano plots of differentially expressed genes (DEGs) in between (**B**) control and TLM\_CFM-F\_OSM groups, (**C**) control and TLM\_CFM-S\_OSM groups. Representative Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analysis in between (**D**) control and TLM\_CFM-F\_OSM groups and (**E**) control and TLM\_CFM-S\_OSM groups. Representative bar graphs show RT-PCR analysis of (**F**) Lamin B2 and (**G**) EGFR. Representative box plots show transcriptomic expressions of (**H**) Lamin B2, (**I**) MMP1, (**J**) EGFR, (**K**) NFKB, (**L**) PD-L1, and (**M**) TGF beta. Data were represented as the mean ± SD of three separate experiments (*n* = 3). \*\* *p* < 0.01, \* *p* < 0.05 vs. control. **Figure 2.** RNA-Seq identified differential mRNA expressions and their RTPCR validation in NSCLC tumor tissues isolated from athymic nude mice (**A**) Heat map illustrations of hierarchical clustering analysis of differentially expressed mRNA in tissues of control and treated H1975 Xenograft mice. Representative volcano plots of differentially expressed genes (DEGs) in between (**B**) control and TLM\_CFM-F\_OSM groups, (**C**) control and TLM\_CFM-S\_OSM groups. Representative Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analysis in between (**D**) control and TLM\_CFM-F\_OSM groups and (**E**) control and TLM\_CFM-S\_OSM groups. Representative bar graphs show RT-PCR analysis of (**F**) Lamin B2 and (**G**) EGFR. Representative box plots show transcriptomic expressions of (**H**) Lamin B2, (**I**) MMP1, (**J**) EGFR, (**K**) NFKB, (**L**) PD-L1, and (**M**) TGF beta. Data were represented as the mean ± SD of three separate experiments (*n* = 3). \*\* *p* < 0.01, \* *p* < 0.05 vs. control.

We performed qRT-PCR to validate RNA-Seq data and proteomics data. Here, we selected genes that showed a highly differential expression in the treatment group com-

(1.38-fold) were significantly down-regulated (*p* < 0.05) in the TLM\_CFM-F\_OSM group compared with control, not only at the proteome level (Figure 3) but also at the transcriptome level (Figure 2). As compared to the control group, every treatment group (OSM, CFM-F, and TLM\_CFM-F\_OSM) significantly downregulated the EGFR and Lamin B2 mRNA expression level (*p* < 0.05) but did not show significant difference across different treatment groups (Figure 2F,G). At the transcriptional level, genes showed variable ex-

*3.3. Validation of Differentially Expressed Transcripts via qRT-PCR* 

pression, which would lead to changes in their protein expression.

### *3.3. Validation of Differentially Expressed Transcripts via qRT-PCR*

We performed qRT-PCR to validate RNA-Seq data and proteomics data. Here, we selected genes that showed a highly differential expression in the treatment group compared to the control group. The qRT-PCR showed that Lamin B2 (i.e., 1.33-fold) and EGFR (1.38-fold) were significantly down-regulated (*p* < 0.05) in the TLM\_CFM-F\_OSM group compared with control, not only at the proteome level (Figure 3) but also at the transcriptome level (Figure 2). As compared to the control group, every treatment group (OSM, CFM-F, and TLM\_CFM-F\_OSM) significantly downregulated the EGFR and Lamin B2 mRNA expression level (*p* < 0.05) but did not show significant difference across different treatment groups (Figure 2F,G). At the transcriptional level, genes showed variable expression, which would lead to changes in their protein expression. *Pharmaceutics* **2022**, *14*, x FOR PEER REVIEW 10 of 21

**Figure 3.** Proteomic identified differentially expressed proteins (DEPs) in lung cancer after treatment. (**A**) Representative Volcano plots of DEPs in between (a) Control and Osimertinib (OSM) groups, (b) Control and CFM4.17 nanolipid formulation (CFM-F), (c) Control and CFM-F\_OSM\_ telmisartan (TLM) combination, and (d) Control and CFM4.17 solution (CFM-S) OSM\_TLM combination (**B**) Representing illustrations of hierarchical clustering analysis of differentially expressed proteins in control and treatment groups and proteins with the highest abundance alterations. (**C**) Schematic representation showing proteins with the largest overall increase in expression and (**D**) the proteins with the greatest reduction in expression upon treatment are represented. **Figure 3.** Proteomic identified differentially expressed proteins (DEPs) in lung cancer after treatment. (**A**) Representative Volcano plots of DEPs in between (a) Control and Osimertinib (OSM) groups, (b) Control and CFM4.17 nanolipid formulation (CFM-F), (c) Control and CFM-F\_OSM\_ telmisartan (TLM) combination, and (d) Control and CFM4.17 solution (CFM-S) OSM\_TLM combination (**B**) Representing illustrations of hierarchical clustering analysis of differentially expressed proteins in control and treatment groups and proteins with the highest abundance alterations. (**C**) Schematic representation showing proteins with the largest overall increase in expression and (**D**) the proteins with the greatest reduction in expression upon treatment are represented.

#### *3.4. Proteomics and Differential Gene Expression Analysis in Drug-Treated H1975 Tumors 3.4. Proteomics and Differential Gene Expression Analysis in Drug-Treated H1975 Tumors*

Briefly, 4299 proteins were identified, and among those, 3948 proteins were quantified under both the control and treatment groups. The statistical significance level was set at *p* < 0.05 with the treatment/control group (considerably equal or greater than 1.5-fold, adjusted with the *p*-value). This parameter gave us 212 (down) and 184 (up) proteins in OSM, 175 (down) and 221 (Up) proteins in CFM-F, 214 (down) and 261 (up) proteins in TLM\_CFM-F\_OSM, 188 (down) and 224 (up) proteins in TLM\_CFM\_F\_OSM when compared with the control (Figure 3A). The quantitative proteome data were used for hierarchical clustering, and the biological functions of H1975 samples are shown in Figure 3B. Briefly, 4299 proteins were identified, and among those, 3948 proteins were quantified under both the control and treatment groups. The statistical significance level was set at *p* < 0.05 with the treatment/control group (considerably equal or greater than 1.5-fold, adjusted with the *p*-value). This parameter gave us 212 (down) and 184 (up) proteins in OSM, 175 (down) and 221 (Up) proteins in CFM-F, 214 (down) and 261 (up) proteins in TLM\_CFM-F\_OSM, 188 (down) and 224 (up) proteins in TLM\_CFM\_F\_OSM when compared with the control (Figure 3A). The quantitative proteome data were used for hierarchical clustering, and the biological functions of H1975 samples are shown in Figure 3B.

The functional alterations in the treatment group were determined using the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Differentially expressed

significantly enriched KEGG pathways (based on *p*-value). The upregulated and downregulated proteins in the treatment group led to various pathways: spliceosome, metabolic, inflammation, immunological, and RNA transport. Based on all the pathways given, SOD, NFKB, TGF beta, C-Myc, STAT3, Lamin-B2, Macrophage mannose receptor 1, and Histone H1.0 proteins attracted attention, which was also observed in RNA-seq, and they

have also been implicated in mediating lung cancer (Table 3).

The functional alterations in the treatment group were determined using the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Differentially expressed proteins were organized into different groups using DAVID software. KEGG enrichment analysis software was used to identify differentially expressed proteins (DEPs) and those significantly enriched KEGG pathways (based on *p*-value). The upregulated and downregulated proteins in the treatment group led to various pathways: spliceosome, metabolic, inflammation, immunological, and RNA transport. Based on all the pathways given, SOD, NFKB, TGF beta, C-Myc, STAT3, Lamin-B2, Macrophage mannose receptor 1, and Histone H1.0 proteins attracted attention, which was also observed in RNA-seq, and they have also been implicated in mediating lung cancer (Table 3).


**Table 3.** Proteins with high abundance values and role in cancer.

The treatment groups were analyzed individually for differentially expressed proteins with a threshold limit of 1.5-fold change. The conclusive results of the upregulated and downregulated proteins from the treatment groups and the control group are listed in Table 2. Among these, only 4–7% were identified, and differentially expressed proteins were commonly regulated in all the treatment groups and had a high abundance ratio. The high abundance of upregulated proteins is shown in Figure 3C and also the downregulated proteins in Figure 3D. The TLM\_CFM-F\_OSM group showed significantly downregulated proteins; Lamin B2, Macrophage mannose receptor 1, Histone H1.0, SOD2, TGF-beta, NFKB, C-Myc, STAT3, NEDD8-MDP1, Solute carrier family 25, Paxillin, and Inter-alpha inhibitor H4 as compared to TLM\_CFM-S\_OSM, CFM-F, OSM, and control group. Among highabundance upregulated proteins, overexpression of AMPK, REST corepressor 1, DNAJB1 protein, and Cytochrome b5 were more significantly upregulated in the TLM\_CFM-F\_OSM group as compared to the TLM\_CFM-S\_OSM, CFM-F, OSM, and control group.
