Western Blot Analysis of Microtubule-Associated Protein Light Chain 3 to Monitor Autophagosomal Dynamics in Mouse-Derived Pancreatic Cancer Cells

Summary

LC3 immunoblotting is a widely used method for monitoring autophagy but requires careful optimization. This protocol describes a robust approach for LC3-II detection and quantification in KPC-derived pancreatic cancer cells, including key technical considerations and a standardized workflow for densitometric analysis using Fiji.

Abstract

Autophagy plays a complex role in pancreatic ductal adenocarcinoma (PDAC), contributing to tumor progression, stress adaptation, and therapy resistance. Accurate assessment of autophagosomal dynamics is therefore essential for studies of cancer biology. Among the available methods, immunoblotting of microtubule-associated protein light chain 3 (LC3) is widely used to monitor autophagosomal dynamics by distinguishing between the cytosolic (LC3-I) and lipidated, autophagosome-associated (LC3-II) forms. However, the low molecular weight of LC3 and the minimal difference in electrophoretic mobility between these isoforms present technical challenges that require careful optimization. Presented here is a reproducible protocol for the semi-quantitative analysis of LC3-II levels by Western blot in KPC-derived murine pancreatic cancer cells. The method incorporates optimized conditions for cell lysis, electrophoresis, protein transfer, and antibody-based detection to ensure reliable separation and detection of LC3 isoforms. In addition, a standardized workflow for densitometric analysis of LC3-II bands using Fiji (ImageJ) is provided. The sensitivity of the method is demonstrated through the detection of increased LC3-II levels under conditions of autophagy induction (gemcitabine treatment) and impaired autophagic flux (VMP1 knockdown). Critical technical parameters that influence data interpretation, including lysis buffer composition and antibody specificity, are also examined, together with common experimental pitfalls. Although LC3 immunoblotting alone is insufficient to fully define autophagic flux, when combined with complementary assays it provides a robust and accessible approach for monitoring autophagic activity. The protocol can be adapted to other experimental contexts, facilitating mechanistic studies of autophagy in cancer models.

Introduction

Macroautophagy (hereafter referred to as autophagy) is a regulated degradative pathway through which cells degrade cytoplasmic material, including proteins and dysfunctional organelles. A hallmark of autophagy is the formation of a double-membraned structure known as the autophagosome, which sequesters cellular cargo and subsequently delivers it to lysosomes for degradation^1,2,3. In normal cells, autophagy contributes to the controlled turnover of proteins and organelles, thereby limiting oxidative stress and reducing the risk of tumor development. In cancer cells, however, this process can be co-opted to support survival under conditions of high metabolic demand, nutrient deprivation, and hypoxia. By facilitating adaptation to a hostile microenvironment, autophagy also contributes to chemotherapy resistance, in part by mitigating treatment-induced cellular damage^4,5.

Pancreatic cancer ranks as the third leading cause of cancer-related mortality in the United States. Approximately 90% of pancreatic cancers are classified as pancreatic ductal adenocarcinoma (PDAC). Unlike several other malignancies, for which early detection and therapeutic advances have improved patient survival, PDAC is diagnosed at an advanced stage in more than 80% of cases. This late-stage presentation, combined with aggressive tumor biology and marked resistance to therapy, results in a 5-year overall survival rate of approximately 11%⁶.

The KPC mouse model, based on pancreas-specific activation of oncogenic Kras and conditional deletion of Trp53 driven by Cre recombinase, is one of the most widely used genetically engineered models of pancreatic ductal adenocarcinoma. These mice spontaneously develop tumors that closely resemble the human disease, progressing from pancreatic intraepithelial neoplasia (PanIN) to invasive carcinoma. Importantly, this model recapitulates key features of pancreatic cancer, including a dense desmoplastic stroma and an immunosuppressive tumor microenvironment. Tumor cells isolated from KPC mice (KPC-derived cells) provide a complementary in vitro system that retains many of the genetic and phenotypic characteristics of the original tumors, enabling mechanistic studies and controlled evaluation of therapeutic responses^7,8.

VMP1 is an essential autophagy-related protein that initiates autophagy through its interaction with Beclin-1 and recruitment of the PI3KC3 complex^9,10. Beyond initiation, VMP1 participates in multiple stages of autophagy, including autophagosome formation¹⁰, closure¹¹, and selective processes such as mitophagy¹² and zymophagy¹³. VMP1 remains involved throughout autophagic flux and may exert additional functions as a phospholipid scramblase¹⁴. In the pancreas, VMP1 expression is typically low but is strongly induced under stress conditions, including pancreatitis and oncogenic transformation, where it promotes autophagy downstream of mutant KRAS signaling^15,16. VMP1 is overexpressed in pancreatic cancer¹⁷, and experimental mouse models have shown that VMP1-dependent autophagy cooperates with KRAS to promote tumor initiation and PanIN formation¹⁸. Furthermore, VMP1 contributes to chemotherapy resistance because its upregulation by agents such as gemcitabine¹⁹ stimulates autophagy¹⁹ and supports tumor cell survival¹⁷, highlighting its pro-tumorigenic role¹⁵.

Autophagosomes are characterized by the presence of the autophagy-related protein microtubule-associated protein light chain 3 (LC3)²⁰. Under basal conditions, LC3 is predominantly present in a soluble form (LC3-I) distributed throughout the cytoplasm and nucleus. Upon activation of autophagy, LC3 undergoes lipidation through conjugation to phosphatidylethanolamine, generating the membrane-associated form LC3-II^1,21. Although LC3-II has a higher molecular weight than LC3-I due to this modification, it migrates more rapidly during SDS-PAGE, likely because of its increased hydrophobicity. Consequently, the conversion of LC3-I to LC3-II reflects lipidation rather than proteolytic processing, with LC3-I typically detected at approximately 16 kDa and LC3-II at approximately 14 kDa. Because LC3-II levels correlate with autophagosome abundance, LC3 immunoblotting is widely used to monitor autophagic activity²². Accurate assessment of LC3 dynamics is therefore essential for interpreting autophagy-related experimental findings.

This study details the standardization and technical optimization of a classical LC3 immunoblot protocol in a KPC-derived pancreatic cancer cell line. Optimization is particularly important because LC3 is a low-molecular-weight protein, the LC3-I and LC3-II forms differ by only ~2 kDa in electrophoretic mobility, and LC3-II is a lipidated species^21,22. Consequently, minor procedural variations can compromise LC3 detection and lead to suboptimal results. In addition, the species origin of the samples represents an important consideration for achieving optimal immunoreactivity. The optimized protocol is sufficiently sensitive to detect increased LC3-II levels following treatment with the chemotherapeutic agent gemcitabine and following VMP1 knockdown, conditions known to stimulate autophagy and impair autophagic flux, respectively. Finally, two potential technical pitfalls are highlighted to demonstrate their impact on data quality and result interpretation. An overview of this experimental workflow is illustrated in Figure 1.

Figure 1: Schematic representation of the LC3 immunoblot protocol in KPC-derived cells. Schematic overview of the protocol used to detect and quantify LC3-II levels by immunoblotting. KPC-derived pancreatic cancer cells are cultured and subjected to experimental treatments, followed by cell lysis, protein quantification, SDS–PAGE, membrane transfer, antibody-based detection of LC3, chemiluminescent signal acquisition, and densitometric analysis of LC3-II bands normalized to a loading control. The workflow highlights the major procedural steps and critical stages required for reliable assessment of LC3 dynamics. Created with BioRender.com. Please click here to view a larger version of this figure.

Protocol

All procedures involving animals were performed in accordance with institutional guidelines and approved by the Institutional Animal Care and Use Committee (IACUC) of Massachusetts General Hospital under protocol #2019N000111. The KPC-derived pancreatic cancer cell line used in this study was previously established in the Mostoslavsky laboratory under this approved protocol. The list of reagents, chemicals, and equipment information is provided in the Table of Materials.

1. Cell preparation

1. Seed low-passage Kras^G12D; Trp53^f/+; p48-Cre (hereafter referred to as KPC)-derived pancreatic tumor cells in a 6-well plate in Roswell Park Memorial Institute medium (RPMI 1640) containing 10% fetal bovine serum, 100 U/mL penicillin, and 100 µg/mL streptomycin. Adjust the seeding density to obtain 70%–90% confluence on the day of lysis.
   NOTE: A seeding density of 3.5 × 10⁵ cells per well resulted in ~80% confluence after 72 h. Because growth may vary among laboratories and KPC models, determine the optimal seeding density empirically before performing the experiment.
   NOTE: To generate stable VMP1-knockdown cell lines, produce lentiviral particles by co-transfecting HEK293T cells with packaging plasmids and the respective lentiviral vector using polyethylenimine (PEI). Harvest lentiviral supernatants 72 h post-transfection, centrifuge at 300 × g for 10 min at 4 °C to remove cellular debris, and filter through a 0.45 µm syringe filter. Subject KPC cells to a single round of transduction with the harvested viral supernatants. Select stably transduced cells by treatment with 2.5 µg/mL puromycin (1:4,000 dilution from a 10 mg/mL stock solution) for 72 h.
2. Culture the cells at 37 °C in a humidified incubator with 5% carbon dioxide (CO₂).
3. Replace the medium with fresh medium and continue incubation under the same conditions.

2. Treatment with 20 µM gemcitabine

1. Prepare a 10 mM gemcitabine solution in RPMI medium one day before lysis. Treat each well with 4 µL of the 10 mM solution to achieve a final concentration of 20 µM.
2. Incubate the cells for 24 h at 37 °C in a humidified incubator with 5% carbon dioxide (CO₂).

3. Cell lysates

1. Place the plate on ice and wash three times with cold phosphate-buffered saline (PBS; 137 mM NaCl, 2.7 mM KCl, 8 mM Na₂HPO₄, and 2 mM KH₂PO₄).
2. Add 80 µL of lysis buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 1% Triton X-100, and 0.1% SDS) supplemented with protease inhibitors.
   NOTE: If different confluence levels are observed between wells, adjust the lysis buffer volume to obtain comparable protein concentrations. As a guideline, use ~10 µL of lysis buffer per 10% confluence (e.g., 70 µL for 70% confluence and 90 µL for 90% confluence).
3. Using the wide (proximal) end of a P200 pipette tip, thoroughly scrape the entire surface of each well to detach and collect the cells in the lysis buffer.
4. Collect the lysate into a microcentrifuge tube and keep it on ice for 15 min.
5. Centrifuge the samples at 16,900 × g at 4 °C for 10 min.
6. Transfer the supernatant to a clean microcentrifuge tube.
7. Remove an aliquot for protein quantification and keep it on ice until analysis.
   NOTE: For protein quantification, dilute 2.5 µL of lysate in 7.5 µL of lysis buffer and mix with 200 µL of bicinchoninic acid reagent. Alternative protein quantification methods may also be used.
8. Add 4× Laemmli sample buffer (250 mM Tris-HCl, pH 6.8, 8% SDS, 40% glycerol, 0.04% bromophenol blue, and 20% β-mercaptoethanol) to the lysates and mix thoroughly. For 77.5 µL of lysate, add 25.8 µL of Laemmli sample buffer.
9. Store the samples at −80 °C.
   NOTE: The protocol can be paused at this step. Samples may be stored at −80 °C for up to two weeks before SDS–PAGE.

4. SDS–PAGE and Western blot

1. Heat the samples at 96 °C for 5 min.
2. Load 70 µg of each sample onto a 15% SDS–PAGE gel (1.5 mm thickness) and run electrophoresis at 90 V until the dye front enters the resolving gel. Use a self-cast 15% polyacrylamide resolving gel containing 15% acrylamide/bis-acrylamide, 375 mM Tris-HCl (pH 8.8), and 0.1% SDS.
3. Increase the voltage to 120 V and continue electrophoresis until the dye front reaches or runs off the bottom of the gel. Stop the run before the 10 kDa marker of the molecular weight ladder runs off the gel.
4. Cut the gel at approximately 25 kDa to separate the upper and lower portions.
5. Transfer proteins to a 0.2 µm PVDF membrane pre-activated with methanol in transfer buffer (25 mM Tris base, 192 mM glycine, and 20% [v/v] methanol) at 200 mA for 1 h for the lower gel portion (<25 kDa) and 2.5 h for the upper gel portion (>25 kDa).
6. Block the membrane for 1 h in blocking buffer with gentle agitation.
7. Prepare a 1:1,000 solution of anti-LC3 primary antibody in blocking buffer containing 0.1% Tween-20.
   NOTE: The anti-LC3 primary antibody was used at a 1:1,000 dilution, and the anti-actin loading control antibody was used at a 1:4,000 dilution.
8. Incubate the membrane overnight at 4 °C with anti-LC3 primary antibody under gentle agitation.
9. Wash the membrane four times for 5 min with TBS-T (0.1% Tween-20 in TBS; 20 mM Tris-HCl, pH 7.6, and 150 mM NaCl).
10. Prepare a 1:2,000 solution of horseradish peroxidase-conjugated anti-rabbit secondary antibody in blocking buffer.
11. Incubate the membrane with secondary antibody for 1 h at room temperature under gentle agitation.
12. Wash the membrane four times for 5 min with TBS-T.
13. Wash the membrane twice with TBS.

5. Chemiluminescent detection

1. Prepare the two-component enhanced chemiluminescence substrate by mixing equal volumes of Reagent A (luminol/enhancer solution) and Reagent B (peroxide solution) immediately before use.
2. Gently blot excess liquid from the membrane using a laboratory wipe.
3. Place the membrane in an opaque box.
4. Add the enhanced chemiluminescence solution to the membrane, close the box, and incubate for 5 min.
5. Allow excess solution to drain from the membrane and place the membrane in the imaging system for signal detection.
6. Acquire images according to the manufacturer's instructions for the imaging system.

6. Densitometric analysis using Fiji

1. Drag and drop the image file into the Fiji window to open it.
2. Convert the image to 8-bit grayscale (Image → Type → 8-bit).
3. If necessary, rotate the image to align the bands horizontally (Image → Transform → Rotate).
   1. Enable Preview and set the grid to an appropriate number of lines (e.g., 20).
   2. Adjust the rotation angle until the bands are properly aligned.
4. Use the rectangular selection tool to define a region of interest (ROI) around the first lane, including only the band corresponding to LC3-II.
   NOTE: The selection should not be more than twice as wide as it is tall. Use the same ROI dimensions for all bands included in the analysis.
5. Select Analyze → Gels → Select First Lane.
6. Move the same ROI to the next lane and position it around the corresponding band.
7. Select Analyze → Gels → Select Next Lane.
8. Repeat steps 6.6 and 6.7 until the final lane is selected.
9. Generate intensity profiles (Analyze → Gels → Plot Lanes).
10. Use the straight-line tool to define each peak baseline and quantify band intensity using the wand tool.
11. Normalize the values to a loading control.

Results

This protocol describes Western blotting to monitor LC3 dynamics in a KPC-derived pancreatic cancer cell line under different experimental conditions. The protocol generates chemiluminescent images of LC3 and a loading control. In this study, actin was used as the loading control.

Two representative applications of the protocol are shown. First, control KPC cells were compared with gemcitabine-treated KPC cells. Gemcitabine is a chemotherapeutic agent previously reported to induce autophagy in pancreatic cancer cells¹⁹. Figure 2A shows a representative LC3 immunoblot with actin used as a loading control. The quantification obtained by densitometric analysis in Fiji is presented in Figure 2B. LC3-II levels were normalized to actin. A significant 59% increase in LC3-II levels was observed in gemcitabine-treated cells, consistent with autophagy induction.

Figure 2: LC3 immunoblot analysis in KPC-derived pancreatic cancer cells: (A-B) effects of gemcitabine, (C-F) VMP1 downregulation, and (G-H) suboptimal technical conditions. (A–B) LC3 levels under basal and gemcitabine-treated conditions. KPC-derived pancreatic cancer cells were treated with 20 µM gemcitabine for 24 h or left untreated. Cell lysates were immunolabeled for LC3 and actin as a loading control. (A) Representative immunoblot images of LC3 and actin are shown. (B) The graph shows the quantification of LC3-II band densitometry normalized to actin. Data are presented as mean ± SEM. **p < 0.01 by unpaired Student’s t-test. n = 4 per condition. (C–D) Validation of shRNA-mediated VMP1 knockdown. Cells constitutively expressing either an empty pLKO.1 plasmid (pLKO.1) or a pLKO.1 plasmid encoding an shRNA targeting the mouse VMP1 sequence (VMP1 KD) were lysed and analyzed. (C) Representative Western blot image of VMP1, with GAPDH as a loading control. (D) Quantification of VMP1 expression levels showing a ~90% reduction in VMP1 KD cells. Data are presented as mean ± SEM. ***p < 0.001 by unpaired Student’s t-test. n=3 per condition. (E–F) Effect of VMP1 downregulation on LC3-II accumulation. KPC-derived pancreatic cancer cells constitutively expressing empty pLKO.1 or shVMP1 plasmids were lysed and immunolabeled for LC3 and actin as a loading control. (E) Representative immunoblot images of LC3 and actin are shown. (F) The graph shows the quantification of LC3-II band densitometry normalized to actin. Data are presented as mean ± SEM. **p < 0.01 by unpaired Student’s t-test. n = 5 per condition. (G-H). Suboptimal experiments. KPC-derived pancreatic cancer cells constitutively expressing either an empty pLKO.1 or a shVMP1 plasmid were lysed and immunolabeled for LC3 and actin as a loading control. (G) Representative immunoblot images of LC3 and actin obtained from lysates prepared using a lysis buffer with a low detergent concentration. (H) Representative immunoblot images of LC3 and actin, where LC3 was detected using a primary antibody that does not guarantee reactivity with mouse. Please click here to view a larger version of this figure.

A second experiment was performed using KPC-derived pancreatic cancer cells constitutively expressing either an empty pLKO.1 plasmid (pLKO.1) or a pLKO.1 plasmid encoding an shRNA targeting the mouse VMP1 sequence (VMP1 KD). Successful downregulation of VMP1 was first verified. Figure 2C shows a representative VMP1 immunoblot with GAPDH as a loading control, and Figure 2D quantifies a 90% reduction in VMP1 expression in VMP1 KD cells. LC3-II levels were then evaluated in these cells. An increase in LC3-II accumulation was expected because VMP1 is required for autophagosome formation. Although VMP1 downregulation does not prevent the conversion of LC3-I to LC3-II, it impairs autophagosome formation and subsequent cargo degradation, resulting in LC3-II accumulation^11,15. Representative LC3 and actin immunoblots are shown in Figure 2E, and quantification of the LC3-II/actin ratio is presented in Figure 2F. A significant 43% increase in LC3-II levels was observed in VMP1 KD cells compared with pLKO.1 controls.

These results demonstrate that the protocol enables reliable detection and quantification of LC3-II levels in a KPC-derived pancreatic cancer cell model. However, minor deviations from the protocol can lead to suboptimal outcomes.

Because LC3-II is the lipidated form of LC3, efficient extraction requires a lysis buffer containing an adequate concentration of detergents. Figure 2G shows representative LC3 and actin immunoblots obtained from the same experimental model described in Figure 2E–F (pLKO.1 versus VMP1 KD), but using a lysis buffer with a low detergent concentration (50 mM Tris-HCl, pH 7.4, 250 mM NaCl, 25 mM NaF, 2 mM EDTA, and 0.1% Triton X-100). Although the actin signal remained acceptable, the LC3 signal was suboptimal. Only the LC3-I band was clearly visible, whereas the LC3-II band was barely detectable and markedly reduced relative to LC3-I.

Another important variable in LC3 immunoblotting is the selection of the primary antibody. The immunoblots shown in Figures 2A, 2B, 2E, 2F, and 2G were generated using a primary antibody that produced robust LC3 detection in this experimental system. In contrast, Figure 2H shows an LC3 immunoblot generated with a different primary antibody, which yielded suboptimal results. Under these conditions, LC3-I was barely detectable, and the LC3-II signal was substantially weaker than that obtained with the antibody used in the preceding experiments.

Discussion

This article describes the technical optimization and standardization of a classical LC3 immunoblotting protocol in KPC-derived pancreatic cancer cells. Given the increasingly recognized role of autophagy and autophagy-related proteins in pancreatic cancer development and progression²³, this standardized workflow provides a reliable approach for monitoring LC3 dynamics. The protocol can be applied to evaluate the autophagosomal pool under a variety of experimental conditions, including chemotherapy, oxidative stress, hypoxia, endoplasmic reticulum stress, and genetic manipulations such as gene overexpression, knockdown, knockout, or mutation. In addition to assessing LC3 dynamics, the protocol may be adapted to investigate direct or indirect interactions between LC3 and proteins of interest. For example, immunoprecipitation of a target protein followed by LC3 detection in the eluate can be performed using this workflow. Furthermore, LC3 immunoblotting may be applied to the analysis of extracellular vesicles in the context of secretory autophagy, an emerging field with increasing relevance in pancreatic ductal adenocarcinoma^24,25.

As illustrated in Figure 2G–H, several critical steps must be carefully controlled because minor deviations can result in suboptimal outcomes. One of the most important considerations is the composition of the lysis buffer. Efficient extraction of LC3-II requires a buffer with a relatively high detergent concentration, such as RIPA buffer or a similar formulation. Buffers with lower detergent content, commonly used in immunoprecipitation protocols to preserve protein–protein interactions, may fail to adequately solubilize LC3-II. Under these conditions, LC3-I may remain detectable, whereas LC3-II becomes difficult or impossible to detect, compromising data interpretation.

Another critical factor is selecting a primary antibody validated for the experimental system under study. The technical evaluation presented here was limited to a comparison of two antibodies from the same manufacturer and does not constitute a comprehensive validation across multiple clones or suppliers. Nevertheless, the findings illustrate how antibody performance can vary substantially between experimental systems. Although definitive conclusions regarding species specificity cannot be drawn from this limited comparison, the suboptimal performance of the alternative antibody evaluated in this model highlights the importance of empirical validation rather than reliance on predicted cross-reactivity. According to the manufacturer’s datasheet, this antibody is validated for human samples, whereas mouse reactivity is predicted based on sequence homology. While weak LC3 detection was observed in mouse cells (Figure 2H), the same antibody previously failed to generate detectable signals in rat pancreas tissue and rat-derived AR42J cells (data not shown). These observations underscore the importance of validating antibody performance within the specific biological model being investigated.

Additional parameters requiring optimization include gel composition and electrophoresis conditions. A 15% resolving gel provides adequate separation of LC3-I and LC3-II when electrophoresis is terminated between the point at which the dye front reaches the bottom of the gel and before the 10 kDa molecular weight marker migrates off the gel. In contrast, lower-percentage gels, such as 7% gels, do not provide sufficient resolution. Transfer conditions are equally important because LC3 is a low-molecular-weight protein. Insufficient transfer time or current can reduce transfer efficiency, whereas excessive transfer time or current can result in protein loss through the membrane. The use of membranes with larger pore sizes may further increase this risk.

Several modifications to the protocol may be acceptable. Commercial cell scrapers may be used in place of P200 pipette tips during cell collection. Samples may be processed immediately after lysis rather than frozen, provided they are maintained on ice. Commercially available polyacrylamide gels, including 4–20% gradient gels, may also be used. Alternative blocking reagents, such as laboratory-grade milk or 1% BSA in TBS-T, can be used to replace the blocking solution described here. Likewise, alternative antibody incubation buffers may be used, provided that sodium azide is excluded from solutions containing horseradish peroxidase-conjugated secondary antibodies, as it inhibits peroxidase activity.

The protocol can also be adapted to other experimental systems, including cell lines derived from different tissues and tissue lysates. However, because the workflow was optimized primarily in KPC-derived pancreatic cancer cells, its broader applicability should be considered carefully. Differences in cell type, basal autophagy levels, protein expression profiles, and sample composition may significantly affect LC3 detection. Consequently, adaptation to alternative systems will likely require additional optimization, and antibody compatibility with the species under investigation should always be verified.

A fundamental limitation of LC3 immunoblotting must also be emphasized. LC3-II accumulation alone is insufficient to definitively determine autophagy status or distinguish between increased autophagy induction and impaired autophagosome clearance. Although LC3-II is generated during autophagy induction, it is also degraded within lysosomes as part of the autophagic process. Consequently, both enhanced autophagy and impaired autophagic flux downstream of LC3 conjugation can lead to LC3-II accumulation²⁶.

This limitation is illustrated by the experiments shown in Figure 2A, B and Figure 2E, F, in which elevated LC3-II levels were observed under biologically distinct conditions. In gemcitabine-treated cells, LC3-II accumulation reflects active induction of autophagy associated with increased VMP1 expression and enhanced conversion of LC3-I to LC3-II^11,19. In contrast, VMP1 knockdown impairs autophagosome maturation and clearance. Under these conditions, LC3 lipidation remains intact, but LC3-II degradation is compromised because of defective autophagic flux, resulting in LC3-II accumulation despite impaired autophagic progression²². Because these distinct biological states cannot be distinguished solely through LC3 immunoblotting, complementary approaches such as SQSTM1/p62 analysis and lysosomal inhibition assays are required for rigorous assessment of autophagic flux²⁶.

When combined with these complementary approaches, LC3 immunoblotting remains one of the most accessible and informative methods for monitoring autophagy. Alternative techniques also have limitations. Quantification of LC3 puncta by immunofluorescence²⁷ cannot reliably distinguish increased autophagy from impaired flux and may be difficult to standardize and automate. However, immunofluorescence requires less biological material and may therefore be advantageous for limited clinical samples, such as human biopsies. In addition, LC3 immunoblotting does not require transfection-based reporter systems, thereby avoiding artifacts associated with protein overexpression. Finally, conventional flow cytometry lacks sufficient resolution to distinguish LC3-I from LC3-II, limiting its utility for assessing autophagic activity.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
C-DiGit Blot Scanner	LI-COR BioScience	3600	Used for chemiluminescent detection in Step 5.6
10x Phosphate-Buffered Saline (PBS)	Corning	46-013-CM	Used to prepare sterile 1x PBS for washing cells prior to passaging in Step 1.1.
2-Mercaptoethanol (β-mercaptoethanol)	Sigma-Aldrich (Merck)	M3148	Used to prepare 4× Laemmli sample buffer for SDS-PAGE sample preparation in Step 3.8.
3D Shaker	DLAB	SK-D1807-E	Used for incubating membranes in blocking, primary, and secondary antibody solutions, as well as during wash steps (Steps 4.6, 4.8, 4.9, 4.11, 4.12, and 4.13).
6 Well- Cell Culture Plate	SORFA	SCP-11-006	Used to seed cells in Step 1.1.
Acrylamide	Sigma-Aldrich (Merck)	A8887	Used to prepare the 15% SDS-PAGE gel required for Steps 4.2–4.5.
Anti-Glyceraldehyde-3-Phosphate Dehydrogenase, mouse monoclonal, clone 6C5	Merck Millipore	MAB374	RRID:AB_2107445 Reactivity: human, feline, pig, mouse, rabbit, fish, canine, rat. Used as a loading control to evaluate knockdown efficiency (Figures 2C and 2D).
Anti-mouse IgG, HRP-linked Antibody	Cell Signaling Technology	7076	RRID: AB_330924. Used to prepare the secondary antibody solution in Step 4.10.
Anti-rabbit IgG, HRP-linked Antibody	Cell Signaling Technology	7074	RRID: AB_2099233. Used to prepare the secondary antibody solution in Step 4.10.
Anti-β-Actin (ACTB) Antibody mouse monoclonal, AC-15	Sigma-Aldrich (Merck)	A1978	RRID:AB_476744 Reactivity: sheep, carp, feline, chicken, rat, mouse, Hirudo medicinalis, rabbit, canine, pig, human, bovine, guinea pig. Used as a loading control in Figures 2A, 2B, 2E, 2F, 2G, and 2H.
Bromophenol blue	Sigma-Aldrich (Merck)	B0126	Used to prepare 4× Laemmli sample buffer for SDS-PAGE sample preparation in Step 3.8.
Ethylenediaminetetraacetic acid (EDTA)	Sigma-Aldrich (Merck)	E9884	Used to prepare the low-detergent lysis buffer (Figures 2G and 2H).
Fetal Bovine Serum	NATOCOR	Lintc-634	Used to prepare complete medium for culturing cells (Steps 1 and 2).
Fiji	Open-source software	N/A	Image analysis software
Glycerol	Sigma-Aldrich (Merck)	G5516	Used to prepare 4× Laemmli sample buffer for SDS-PAGE sample preparation in Step 3.8.
Glycine	Sigma-Aldrich (Merck)	G7126	Used to prepare transfer buffer for Step 4.5.
Immun-Blot PVDF Membrane, Roll, 0.2 µm, 26 cm x 3.3 m	Bio-Rad	1620177	Used for transfer in Step 4.5.
Intercept (TBS) Blocking Buffer	LI-COR BioScience	927-60001	Used for blocking in Step 4.6, and for preparing primary and secondary antibody solutions in Steps 4.7 and 4.10.
LC3 A/B (D3U4C) Rabbit Monoclonal Antibody	Cell Signaling Technology	12741	RRID: AB_2617131 Reactivity: human, mouse, rabbit. Used to prepare the primary antibody solution in Step 4.7.
LC3B (D11) Rabbit Monoclonal Antibody	Cell Signaling Technology	3868S	RRID: AB_2137707 Reactivity: Human. Used as the LC3 primary antibody in Figure 2H.
Methanol	Anedra	6197	Used to activate the PVDF membrane and prepare transfer buffer in Step 4.5.
Millex-HV Syringe Filter Unit, 0.45 μm PVDF	Merck Millipore	SLHV033RS	Used to filter lentivirus-containing medium (Step 1.1).
Mini digital dry bath	Labnet International, Inc.	D 5060075	Used to heat samples in Step 4.1.
Mini-PROTEAN Tetra electrophoresis system	Bio-Rad	1658025FC	Used for SDS-PAGE and transfer in Steps 4.2, 4.3, and 4.5.
MISSION shRNA targeting mouse Vmp1 (TRCN0000279038)	Sigma-Aldrich (Merck)	SHCLND-NM_029478	Used to generate stable VMP1-knockdown cell lines (Step 1.1).
N,N'-Methylenebisacrylamide (Bis-acrylamide)	Sigma-Aldrich (Merck)	M7279	Used to prepare the 15% SDS-PAGE gel required for Steps 4.2–4.5.
Nabigem 1g Gemcitabine	Microsules Argentina	M3060584-3	Used for gemcitabine treatment in Step 2.
Pen-Strep Solution	Sartorius	03-031-1B	Used to prepare complete medium for culturing cells (Steps 1 and 2).
Pierce BCA Protein Assay Kit	Thermo Fisher Scientific	23227	Used for protein quantification (Step 3.7).
Pierce Protease Inhibitor Tablets	Thermo Fisher Scientific	A32953	Used to prepare lysis buffer in Step 3.2.
Polyethylenimine HCl MAX, Linear (PEI MAX), MW 40,000	Polysciences	24765-1	Used for transfection with lentiviral plasmids (Step 1.1).
Potassium chloride (KCl)	Sigma-Aldrich (Merck)	P9333	Used to prepare PBS in Step 3.1.
Potassium phosphate monobasic (KH2PO4)	Sigma-Aldrich (Merck)	P5655	Used to prepare PBS in Step 3.1.
PowerPac Basic Power Supply	Bio-Rad	1645050	Used for SDS-PAGE and transfer in Steps 4.2, 4.3, and 4.5.
Prestained ProteinLadder	Genbiotech	PM201	Used for SDS-PAGE in Steps 4.2 - 4.4.
Puromycin (10 mg/mL solution)	InvivoGen	ant-pr-1	Used for selection of stably transduced cells (Step 1.1).
RPMI 1640	Genbiotech	MC2012L	Used to prepare complete medium for culturing cells (Steps 1 and 2).
Sodium chloride (NaCl)	Sigma-Aldrich (Merck)	S9888	Used to prepare PBS in Step 3.1, lysis buffers in Step 3.2, and TBS in Step 4.9.
Sodium dodecyl sulfate (SDS)	Sigma-Aldrich (Merck)	L3771	Used to prepare lysis buffer in Step 3.2 and the 15% SDS-PAGE gel required for Steps 4.2–4.5.
Sodium fluoride (NaF)	Sigma-Aldrich (Merck)	S7920	Used to prepare the low-detergent lysis buffer (Figures 2G and 2H).
Sodium phosphate dibasic (Na2HPO4)	Sigma-Aldrich (Merck)	S9763	Used to prepare PBS in Step 3.1.
Sorval ST 16R Centrifuge	Thermo Fisher Scientific	75004380	Used to centrifuge cells in Step 1.1 and lysates in Step 3.5.
Sustrato quimioluminiscente SuperSignal West Pico PLUS	Thermo Fisher Scientific	34577	Used for chemiluminescent detection in Step 5.1.
Thermo Scientific 1300 Series A2 Class II, Type A2 Biosafety Cabinet	Thermo Fisher Scientific	1386	Used for sterile cell culture handling in Steps 1.1, 1.3, and 2.1.
Thermo Scientific BB 150 CO2 Incubator	Thermo Fisher Scientific	BB150-2TCS-L	Used for culturing cells in Steps 1.2, and 2.2.
TMEM49/VMP1 (D1Y3E) Rabbit Monoclonal Antibody	Cell Signaling Technology	12929	RRID: AB_2714018 Reactivity: human, mouse, rat. Used as a primary antibody to verify VMP1 knockdown efficiency in Figures 2C and 2D.
Tris base	Sigma-Aldrich (Merck)	T1503	Used to prepare transfer buffer for Step 4.5.
Tris hydrochloride (Tris-HCl)	Sigma-Aldrich (Merck)	T3253	Used to prepare lysis buffers in Step 3.2, 4× Laemmli sample buffer in Step 3.8, the 15% SDS-PAGE gel required for Steps 4.2–4.5, and TBS in Step 4.9.
Triton X-100	Sigma-Aldrich (Merck)	T8787	Used to prepare lysis buffers in Step 3.2.
Trypsin EDTA	Gibco	11570626	Used to passage cells in Step 1.1.