Micropeptide colorectal neoplasia differentially expressed (CRNDE) 84aa encoded by CRNDE elicits a T-cell immune response to breast cancer

Introduction

Tumor antigens are molecules that are found on tumor cells or produced in cancer patients and trigger an immune response (1). Tumor antigens help the immune system recognize tumor cells. They are presented to T cells, activating immune responses to destroy tumor cells. Tumor antigens are targeted in cancer immunotherapy (2,3). Cancer vaccines stimulate the immune system by introducing tumor antigens. Chimeric antigen receptor (CAR)-T-cell therapy engineers T cells to express specific tumor antigen receptors to target and kill tumor cells.

Cryptic peptide antigens are a class of antigens that are not typically recognized by the immune system under normal conditions (4,5). These antigens usually arise from unconventional protein processing pathways or abnormal expression (6). These processes are rare in normal cells, and the resulting peptides are rapidly degraded. However, once exposed to certain conditions, cryptic peptides can be recognized by the immune system, particularly by T cells, triggering a specific immune response. In tumor cells, due to integrated stress response or abnormal protein processing, cryptic peptides can be exposed and serve as targets, prompting the immune system to attack tumor cells (7-9). Research into personalized cancer vaccines using cryptic peptides is emerging (10,11). Thus, cryptic peptide antigens may play a vital role in immune surveillance and therapy, particularly in immunologically “cold” tumors with low mutational burden and few neoantigens. Breast cancer, particularly the triple-negative breast cancer (TNBC), is generally considered an immunologically ‘cold’ tumor, characterized by low tumor mutational burden (TMB), reduced infiltration of cytotoxic T lymphocytes (CTLs), and an immunosuppressive tumor microenvironment (TME) enriched with regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and M2-polarized tumor-associated macrophages (TAMs) (12). These features contribute to the poor response rates observed with immune checkpoint inhibitors (ICIs) in unselected breast cancer patients, with objective response rates typically below 10–20% in monotherapy settings (13). Given these challenges, there is an urgent need to identify novel tumor antigens capable of eliciting robust and specific anti-tumor immune responses, particularly those derived from non-coding regions such as cryptic peptides translated from lncRNAs. Tumor vaccines have brought new opportunities for the treatment of cold tumors (14,15). These emerging classes of antigens may offer new opportunities to overcome the immune evasion mechanisms prevalent in ‘cold’ tumors like breast cancer.

Long non-coding RNAs (lncRNAs) are RNA molecules longer than 200 nucleotides and play crucial roles in gene regulation, chromatin structure, transcription, and posttranscriptional regulation (16,17). Although they are traditionally considered to be noncoding, some lncRNAs have been found to encode small peptides (18,19). These peptides, though short, may have significant roles in cellular functions, signaling pathways and immune response (20,21).

Here, we characterized colorectal neoplasia differentially expressed (CRNDE) and showed that it encoded an immunogenic peptide that could be targeted by T cells in breast cancer. We then used the CRNDE peptide-loaded dendritic cells (DCs) and T cells in a patient-derived xenograft (PDX) model to demonstrate that lncRNA-related peptides can function as precise therapeutic targets for tumor eradication. Additionally, studying these immunogenic peptides may increase the number of candidates for use as immunotherapy. We present this article in accordance with the MDAR and ARRIVE reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2809/rc).

Methods

Patients and tissues

Tumor tissue specimens and peripheral blood samples were obtained from HLA-A*02:01-positive (HLA-A2) individuals who underwent treatment at the Breast and Thyroid Center of Guangzhou Women and Children’s Medical Center of Guangzhou Medical University in Guangzhou, China. Prior to participation, written informed consent was acquired from all enrolled patients. Additionally, this research protocol received official approval from the institutional review committee as well as the Research Ethics Review Committee of Guangzhou Women and Children’s Medical Center of Guangzhou Medical University (No. KTDW-2024-01365). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Cell lines and mice

Female non-obese diabetic (NOD)/severe combined immunodeficient (SCID) mice, between 8 to 12 weeks of age, were procured from the Guangdong Provincial Animal Center and maintained in accordance with the institutional guidelines for animal research at Guangzhou Medical University. The animal experiments were performed under a project license (No. 2024062114382769) granted by the Research Ethics Review Committee of Guangzhou Women and Children’s Medical Center of Guangzhou Medical University, in compliance with the institutional guidelines for the care and use of animals. A protocol was prepared before the study without registration. The breast cancer cell lines MDA-MB-231, MCF-7, T47D, and BT-549, along with the non-malignant breast epithelial cell line MCF-10A and HEK293T cells, were sourced from the Shanghai Cell Bank. Immediately following delivery, both master and working cell banks were generated, and cells from the third and fourth passages were subsequently utilized for in vivo tumor studies.

Quantitative real-time polymerase chain reaction (qRT-PCR)

Gene expression quantification was performed using qRT-PCR with the SYBR Premix Ex Taq Kit (Catalog No. RR820A; Takara Bio Inc.), strictly adhering to the manufacturer’s recommended experimental procedures. The thermal cycling conditions and reaction setup followed the standardized protocol provided with the kit. Amplification and fluorescence detection were carried out using a LightCycler 480 real-time PCR system (Roche Diagnostics), which enabled precise monitoring of PCR product accumulation during each cycle. Subsequent data collection and computational analysis were executed through the instrument’s integrated software package, ensuring accurate quantification of target gene expression levels relative to reference controls. Primer sequences are provided in Table S1.

Plasmids and transfection

To determine the translatability of the predicted open reading frame (ORF) sequence in CRNDE, the complete CRNDE sequences of interest were amplified via PCR, incorporating a 3× FLAG tag immediately upstream of the ORF termination codon. The resulting amplicons were then cloned and inserted into the pcDNA3.1 plasmid (+). The recombinant plasmids were introduced into HEK293T cells through lipid-mediated transfection. Specifically, Lipofectamine 3000 transfection reagent (Catalog No. L3000015; Thermo Fisher Scientific) was employed according to the optimized protocol provided by the manufacturer. This involved preparing DNA-lipid complexes at optimal ratios in serum-free medium, followed by incubation with cells at 37 °C in a 5% CO₂ humidified atmosphere. Transfection efficiency was monitored 24–48 hours post-transfection through fluorescence microscopy and western blot analysis targeting the FLAG-tagged fusion proteins.

Western blotting

Cellular and tissue protein lysates were prepared using ice-cold radioimmunoprecipitation assay (RIPA) lysis buffer (Product #89900; Thermo Fisher Scientific) containing a 1:100 dilution of complete protease inhibitor cocktail (Catalog #ab65621; Abcam). Following centrifugation at 12,000 ×g for 30 minutes at 4 °C. Equal protein quantities were resolved through discontinuous sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) on 15% Tris-glycine polyacrylamide gels (Catalog #PG112; EpiZyme Biotech) under denaturing conditions.

Electrophoretically separated proteins were subsequently transferred onto 0.45 µm polyvinylidene fluoride (PVDF) membranes (Millipore) using semi-dry transfer apparatus (Bio-Rad). Membranes were subjected to blocking with 5% (w/v) non-fat dry milk in Tris-buffered saline with 0.1% Tween-20 (TBST) for 1 hour at room temperature to prevent non-specific binding. Immunodetection was performed using the following primary antibodies: monoclonal ANTI-FLAG M2 antibody produced in mouse (#F1804; Sigma-Aldrich) and mouse anti-β-actin (C4) antibody (#sc-47778; Santa Cruz Biotechnology) as loading control. All antibody incubations were carried out overnight at 4 °C with gentle agitation.

Identification of target epitopes for CRNDE encodes an 84-amino acid peptide (CRNDE 84aa)

CRNDE 84aa was subjected to major histocompatibility complex (MHC) class I peptide binding prediction via the Immune Epitope Database (IEDB; http://www.iedb.org) and SYFPEITHI (SYFPEITHI.de) algorithms for 8-mers, 9-mers, 10-mers, and 11-mers, which contain the CRNDE 84aa sequence. Each predicted epitope was scored based on established binding affinity thresholds, with particular attention to peptides demonstrating strong predicted interactions with HLA-A*02:01, the most prevalent MHC class I allele in human populations.

Synthetic peptides

Peptides were synthesized by IGE Biotechnology Co. (Guangzhou, China).

DCs differentiation and T-cell priming

DCs were generated with modifications as previously described (10). For DC differentiation, the isolated cells were cultured in DMEM complete medium containing 50 ng/mL granulocyte-macrophage colony-stimulating factor (GM-CSF; Catalog #300-03-20; PeproTech), 20 ng/mL interleukin-4 (IL-4; Catalog #200-04-20; PeproTech), and 10% heat-inactivated AB-type human serum. The culture system was maintained at 37 °C in a humidified 5% CO₂ incubator for a total of 6 days, with complete medium replacement performed every 72 hours to ensure optimal growth conditions. Morphological changes during DC maturation were regularly assessed using phase-contrast microscopy. For antigen loading, mature DCs were incubated with 20 µg/mL of target peptides for 18 hours under standard culture conditions.

For the generation of antigen-specific T cell populations, peripheral blood mononuclear cells (PBMCs) from the same cohort of HLA-A2⁺ breast cancer patients were subjected to T cell isolation using Pan-T-cell microbeads (Catalog #130-096-535; Miltenyi Biotec) according to the manufacturer’s protocol. The purified T lymphocytes were then co-cultured with peptide-pulsed DCs at an optimized effector-to-antigen presenting cell ratio of 5:1 (T cells:DCs). This co-culture system was maintained in RPMI-1640 medium supplemented with 25 U/mL recombinant human interleukin-2 (IL-2; Catalog #200-02-50; PeproTech) to support T cell proliferation and activation. The culture period extended for 9 days, during which cell viability and expansion were monitored daily. The complete medium containing fresh IL-2 was replenished every 48 hours to maintain proper cytokine concentrations for T cell stimulation and growth.

Enzyme-linked immunospot (ELISpot)

To quantitatively assess T cell responsiveness, we performed an interferon-γ (IFN-γ) ELISpot assay using commercially available kits [Catalog No. 3420-4HST-2 (human); Mabtech]. Following the co-culture period, antigen-primed T lymphocytes were carefully collected from the DCs coculture system and subjected to secondary stimulation. This restimulation process involved incubating the harvested T cells with freshly prepared, peptide-loaded DCs for an 18-hour period under standard culture conditions (37 °C, 5% CO₂) to enhance antigen-specific activation. Then, the membrane plates were thoroughly washed and air-dried before spot enumeration. The immunospots representing individual IFN-γ-secreting T cells were quantified using an automated ELISpot plate reader (ImmunoSpot^® Analyzer; Cellular Technology Limited, Shaker Heights, OH, USA). The reader was calibrated according to manufacturer specifications, and spot counts were analyzed using dedicated image analysis software with parameters set for optimal discrimination between true spots and background noise.

Intracellular cytokine staining

To characterize antigen-specific T cell responses, we performed intracellular cytokine staining as follows: freshly isolated T cells were stimulated with 20 µg/mL of target peptide in complete RPMI-1640 medium containing 10 µg/mL brefeldin A (Sigma-Aldrich) for 18 hours at 37 °C in a 5% CO₂ humidified incubator. This stimulation allows cytokine accumulation while blocking secretion.

After stimulation, cells were washed and first stained for surface markers using anti-human CD8-PerCP (Catalog #344707; BioLegend) and anti-human CD3-APC/Fire 750 (Catalog #317351; BioLegend) antibodies in phosphate-buffered saline (PBS) containing 2% fetal bovine serum (FBS) for 20 minutes at 4 °C in the dark. The cells were subsequently fixed and permeabilized.

For intracellular cytokine detection, cells were stained with eFluor 450-conjugated antibodies against IFN-γ (Catalog #48-7319-42), tumor necrosis factor-α (TNF-α; Catalog #48-7349-42), and IL-2 (Catalog #48-7029-42) from eBioscience () for 1 hour at 4 °C. After washing, cells were resuspended in staining buffer and analyzed immediately on a Beckman CytoFLEX S flow cytometer. Data analysis was performed using CytExpert software version 2.4 with sequential gating on lymphocytes, singlets, CD3⁺ T cells, and cytokine-positive populations.

Lactate dehydrogenase (LDH) assay

Target cells were plated at a density of 1×10⁴ cells per well in 96-well flat-bottom tissue culture plates, suspended in 100 µL of high-glucose Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% FBS. These target cells were then co-cultured with peptide-specific CD8⁺ T effector cells at 20:1 effector-to-target (E:T) ratios in a humidified incubator maintained at 37 °C with 5% CO₂ atmosphere for 18 hours.

For assay controls, maximum LDH release control wells received 10 µL of 10× cell lysis buffer (provided in the kit) per 100 µL culture volume and were incubated for 45 minutes under identical conditions.

Following the incubation period, 50 µL of cell-free supernatant from each well was carefully transferred to a fresh 96-well plate. To each supernatant sample, 50 µL of freshly prepared LDH detection reagent (containing INT and diaphorase) was added. The plate was then protected from light and incubated at room temperature for exactly 30 minutes to allow color development. The enzymatic reaction was terminated by adding 50 µL of stop solution to each well.

The absorbance was measured at 490 and 680 nm. The specific cytotoxicity percentage was calculated using the following standardized formula: % cytotoxicity = {[experimental optical density (OD)₄₉₀ − spontaneous release OD₄₉₀]/(maximum release OD₄₉₀ − spontaneous release OD₄₉₀)} × 100%.

Cytotoxicity assays

Target cells were labeled with 5 µM 5-chloromethylfluorescein diacetate (CMFDA; #C7025; Thermo Fisher Scientific) for 15 minutes at 37 °C. Peptide specific CD8⁺ T cells, isolated using CD8 MicroBeads (#130-045-201; Miltenyi Biotec), were co-cultured with targets at 20:1 E:T ratio for 18 hours. Cells were then stained with propidium iodide (PI; #00-6990; eBioscience; 1:500) and analyzed by flow cytometry.

Immunohistochemistry (IHC)

Formalin-fixed, paraffin-embedded tissue samples were sectioned at 4 µm thickness using a rotary microtome and mounted onto poly-L-lysine coated slides. Following deparaffinization through xylene and graded alcohol series, antigen retrieval was performed by heat treatment in citrate buffer. The sections were then incubated overnight at 4 °C with primary antibody specific for CRNDE 84aa. After washing, the sections were treated with HRP-conjugated secondary antibody (#K4001; Dako) for 1 hour at room temperature, followed by development with 3,3'-diaminobenzidine (DAB) chromogen substrate (#K3468; Dako) for 5 minutes. Finally, the sections were counterstained with Mayer’s hematoxylin (#MHS32; Sigma-Aldrich) for 30 seconds, dehydrated, and coverslipped. Digital images were acquired using a Nikon microscope ().

PDX model

Fresh breast cancer tissue samples were obtained from consenting patients following approval by the Institutional Ethics Committee. Immediately after surgical resection, the tumor specimens were cut into small fragments (approximately 2–3 mm³) and subcutaneously engrafted into the flanks of 8- to 10-week-old NOD/SCID mice under sterile conditions. Tumor growth was monitored by using caliper measurements, and once the tumor burden reached approximately 1,500 mg, the mice were euthanized following institutional animal care guidelines. The excised tumors were dissected into smaller fragments and serially passaged into new recipient mice to establish stable PDX models.

For adoptive T cell therapy, PBMCs were isolated from the same patients. Autologous DCs were generated from monocytes and pulsed with 20 µg/mL of target peptides for 4 hours at 37 °C. These peptide-loaded DCs were then co-cultured with purified T cells at a 1:5 ratio (DCs:T cells) in complete RPMI-1640 medium supplemented with 10% human AB serum for 20 hours to prime antigen-specific responses.

When PDX tumors became palpable (~50–100 mm³), the mice received weekly intravenous injections (via tail vein) of 2.5×10⁶ activated T cells and 0.5×10⁶ peptide-pulsed DCs for 2 consecutive weeks. Tumor dimensions were measured by using digital calipers, and volumes were calculated using the formula: (length × width²)/2. Data were recorded until the endpoint was reached.

Tumor-infiltrating lymphocyte (TIL) analysis

Excised tumor tissues were minced into 1–2 mm³ fragments in 5 mL of RPMI-1640 medium (Gibco) using sterile scalpels. The fragments were enzymatically digested in 15 mL of RPMI-1640 containing 50 U/mL collagenase IV (#17104019; Invitrogen), 100 µg/mL hyaluronidase (#H822579-10KU; Macklin), and 20 U/mL DNase I (#D8070-15; Solarbio) for 2 hours at 37 °C with periodic agitation using a gentleMACS™ Dissociator (Miltenyi Biotec).

The digested suspension was filtered through a 40-µm cell strainer (Corning) and washed 3× with PBS (centrifugation: 300 ×g, 5 minutes). Lymphocytes were isolated by Ficoll-Paque PLUS (GE Healthcare) density gradient centrifugation (800 ×g, 20 minutes, brake off). The mononuclear cell layer was collected and washed twice before Pan-T cell isolation using human CD3 MicroBeads (Miltenyi Biotec, #130-095-130) follow manufacturer’s protocol. Purified T cells were magnetically eluted, stained with fluorochrome-conjugated antibodies (30 minutes, 4 °C), and analyzed on a CytoFLEX LX flow cytometer (Beckman Coulter).

Immunofluorescence (IF) staining

Paraffin-embedded tissue samples were sectioned consecutively at 4 µm thickness and deparaffinized. Antigen retrieval was performed in ethylenediaminetetraacetic acid (EDTA) buffer (pH 8.0) using a pressurized heating chamber for 3 minutes. Sections were incubated overnight at 4 °C with a primary anti-human CD8 antibody (Abcam, Catalog #ab17147; dilution 1:50), followed by a 1-hour incubation with an Alexa Fluor-conjugated secondary antibody (Catalog #A-21206; Thermo Fisher Scientific). After thorough PBS washes, nuclei were counterstained with 4',6-diamidino-2-phenylindole (DAPI; Catalog #H21492; Thermo Fisher Scientific) and slides were mounted. Images were acquired using a confocal laser-scanning microscope (Carl Zeiss) equipped with a high-resolution data capture system.

Statistical analysis

Means were compared via Student’s t-test to assess differences between individual treatment groups and corresponding control groups. Statistical differences in medians between two groups were determined via the nonparametric Mann-Whitney U test. All analyses were two-tailed and performed via GraphPad Prism 5.03 software. P values <0.05 were considered statistically significant (*, P≤0.05; **, P≤0.01; ***, P≤0.001).

Results

CRNDE encodes peptide in breast cancer

By analyzing data from The Cancer Genome Atlas (TCGA) database and PCR testing of tumor tissue samples, we found that CRNDE is highly expressed in breast cancer (Figure 1A,1B). To experimentally validate the translation capacity of this ORF, we engineered an expression construct by cloning the full-length CRNDE sequence into pcDNA3.1 vector, incorporating an in-frame 3× FLAG tag immediately preceding the termination codon. The transfection efficiency of the plasmids was determined by quantitative polymerase chain reaction (qPCR) and fluorescence microscopy (Figure S1). Transient transfection of HEK293T cells with phospho-CRNDE (p-CRNDE) resulted in robust expression of a FLAG-tagged protein product (~9.5 kDa), which was undetectable in mock-transfected controls (Figure 1C).

Figure 1 CRNDE encodes a peptide in breast cancer cells. (A) Elevated levels of CRNDE RNA in human breast cancer compared to adjacent normal tissue, calculated from TCGA datasets. (B) CRNDE levels in breast cancer tissues (n=100) and normal breast tissues (n=100) were detected via qRT-PCR. (C) An anti-FLAG tag antibody was used to detect CRNDE 84aa expression in HEK293T cells transfected with the above vectors. (D) CRNDE expression was detected in breast cancer cells or normal breast cells. (E) Western blotting was used to detect CRNDE 84aa expression in breast cancer cells or normal breast cells. ***, P<0.001; ****, P<0.0001. CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; TCGA, The Cancer Genome Atlas.

Comparative expression profiling revealed CRNDE transcript levels were markedly elevated in malignant breast cancer cell lines (MDA-MB-231, BT-549) compared to the non-tumorigenic mammary epithelial cell line MCF-10A (Figure 1D). To enable specific detection of the endogenous peptide product, we generated and affinity-purified a rabbit polyclonal antibody targeting the predicted 84-amino acid translation product. Western blot analysis confirmed the presence of CRNDE 84aa in multiple breast cancer cell lines, while being virtually absent in normal mammary epithelial cells (Figure 1E).

CRNDE 84aa is immunogenic

Through comprehensive immunoinformatic analysis using the consensus method (version 2.5) of the IEDB (http://www.iedb.org), we identified and prioritized potential MHC class I-binding epitopes within the CRNDE 84aa sequence based on their predicted binding affinity scores (Figure 2A). The affinity was also predicted using the SYFPEITHI algorithm (Figure S2). Subsequent experimental validation demonstrated robust immunogenicity of these CRNDE-derived peptides in human T cell populations.

Figure 2 CRNDE 84aa is immunogenic. (A) The binding predictions for CRNDE 84aa to HLA-A2 via the IEDB (version 2.5) analysis resource NetMHCpan (ver. 4.1) algorithm. (B) CD8⁺ T cells were primed by autologous DCs loaded with CRNDE antigens. The CTLs were restimulated with peptides overnight. The peptide-specific T-cell response was evaluated via an IFN-γ ELISpot. Representative ELISpot images are shown. (C) The primed T cells were restimulated with CRNDE antigens overnight and evaluated by flow cytometry; representative flow cytometry plots of intracellular cytokine staining are shown. The percentages indicate the proportions of CD8⁺ T cells that produced different cytokines (mean ± SD, n=3). P values were determined by two-tailed one-way ANOVA with Dunnett’s multiple-comparisons test. ANOVA, analysis of variance; CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; DC, dendritic cell; CTL, cytotoxic T lymphocyte; ELISpot, enzyme-linked immunospot; poly(I:C), polyinosinic:polycytidylic acid; IEDB, Immune Epitope Database; IFN-γ, interferon-γ; IL-2, interleukin-2; PBS, phosphate-buffered saline; PHA, phytohemagglutinin; SD, standard deviation; TNF-α, tumor necrosis factor-α.

The ELISpot assay revealed significant IFN-γ secretion by T cells stimulated with CRNDE 84aa epitopes compared to negative controls, indicating strong epitope-specific T cell activation (Figure 2B). To further characterize the immune response, we performed multiparametric flow cytometry analysis of cytokine production in antigen-stimulated CD8⁺ T cells. This demonstrated significant elevation of cytokines, including IFN-γ, TNF-α, and IL-2 in CRNDE 84aa-stimulated cultures compared to unstimulated controls (Figure 2C). These findings establish CRNDE-derived peptides as promising targets for T cell-based immunotherapy.

CRNDE 84aa elicited antitumoral activity in vitro

We next investigated whether CRNDE 84aa could elicit a CRNDE 84aa-specific CTL response. We established an in vitro cytotoxicity assay system. CD8⁺ T lymphocytes were isolated from PBMCs and co-cultured with autologous DCs pulsed with either CRNDE 84aa-derived peptides or control peptides for 9 days in the presence of IL-2 (25 U/mL).

The cytolytic activity of these primed CTLs was first assessed against MDA-MB-231 TNBC cells using an LDH release assay. At an E:T ratio of 20:1, CRNDE 84aa-primed CTLs demonstrated significantly higher specific lysis compared to control peptide-primed CTLs after 18 hours of co-culture (Figure 3A). Complementary flow cytometry-based killing assays using CMFDA/PI double staining confirmed these findings, showing that CRNDE 84aa-reactive CTLs induced apoptosis in MDA-MB-231 cells (Figure 3B). Consistently, CD8⁺ T cells primed by CRNDE 84aa were substantially produced high amounts of granzyme B (GZMB) and perforin (Figure 3C,3D).

Figure 3 CRNDE 84aa antigens elicited antitumoral activity in vitro. (A) Primed T cells were cocultured with MDA-MB-231 cells for 18 hours, and their cytotoxicity against MDA-MB-231 cells was assessed via a LDH assay (mean ± SD, n=3). (B) T cells were cocultured with CellTrace CMFDA-labeled MDA-MB-231 cells for 18 hours. Tumor cell death was examined by PI uptake via flow cytometry. The percentages of dead tumor cells are shown (mean ± SD, n=3). (C,D) CD8⁺ T cells were primed by autologous DCs loaded with antigens. Representative flow cytometry plots and quantification of the secretion of perforin (C) and GZMB (D) in T cells. ***, P<0.001, compared with untreated T cells (−). P values were determined by two-tailed one-way ANOVA with Dunnett’s multiple-comparisons test. ANOVA, analysis of variance; CMFDA, 5-chloromethylfluorescein diacetate; CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; DC, dendritic cell; GZMB, granzyme B; LDH, lactate dehydrogenase; PI, propidium iodide; SD, standard deviation.

To determine whether CRNDE 84aa is functionally necessary for tumor immune response, we generated CRNDE 84aa knockdown (KD) MDA-MB-231 cells using two independent siRNAs targeting the specific 252-nucleotide ORF encoding the 84aa peptide. Successful KD was confirmed by qRT-PCR and Western blot analysis. In co-culture assays with primary human CD8⁺ T cells isolated from healthy donors, CRNDE 84aa KD tumor cells exhibited significantly increased susceptibility to T cell-mediated killing compared to control siRNA-treated cells. This effect was associated with enhanced T cell activation, as evidenced by increased Granzyme B expression in T cells co-cultured with control tumor cells (Figure S3).

CRNDE 84aa is expressed in breast tumors

To establish the clinical relevance of CRNDE 84aa as a potential immunotherapeutic target, we systematically evaluated its expression pattern in malignant versus normal tissues. IF demonstrated high CRNDE 84aa expression in tumor cells (Figure 4A). Immunoblot analysis using our characterized anti-CRNDE 84aa polyclonal antibody demonstrated significant overexpression of the 9.5 kDa CRNDE 84aa peptide in primary breast tumor compared to matched adjacent normal tissue controls (Figure 4B).

Figure 4 CRNDE 84aa is expressed in breast cancer. (A) Representative pictures showing the expression and intracellular localization of CRNDE 84aa detected in cells by using IF. (B) Six randomly selected breast cancer patient samples and their paired adjacent normal breast tissues were collected. CRNDE 84aa protein levels were detected by immunoblotting. (C) The expression of CRNDE 84aa was assessed in breast cancer tissue and normal tissue via IHC. (D) The expression of CRNDE 84aa was assessed in several vital organs via IHC. CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; IF, immunofluorescence; IHC, immunohistochemistry.

To assess the tumor specificity of CRNDE 84aa, we first analyzed its expression levels in a cohort of breast cancer tissues (n=60) and paired adjacent normal tissues (n=60) using IHC with a custom-made anti-CRNDE 84aa monoclonal antibody (Figure 4C, Figure S4). The results demonstrated that CRNDE 84aa was significantly upregulated in breast cancer tissues compared to normal breast epithelium. Notably, comprehensive evaluation of normal human tissue demonstrated undetectable CRNDE 84aa expression in critical organs including heart, liver, lung, and kidney, as confirmed by both IHC (Figure 4D).

We analyzed CRNDE 84aa expression in breast cancer tissues of different molecular subtypes and stages by IHC. In addition, the relationship between CRNDE expression and CD8⁺ T cell infiltration was assessed by IF (Figure S4).

CRNDE 84aa generates an immunogenic peptide recognized by human autologous T cells

We therefore synthesized CRNDE 84aa and loaded it onto HLA-A2-positive DCs. To evaluate the immunogenic potential of CRNDE 84aa in a clinically relevant context, we synthesized the full-length peptide and investigated its processing and presentation by antigen-presenting cells. HLA-A2-positive DCs from breast cancer patients were pulsed with either the CRNDE 84aa peptide or the predicted immunodominant epitope FIMELLYWL. Following co-culture with autologous CD8⁺ T cells isolated from peripheral blood, we observed robust cytokine secretion in response to CRNDE 84aa stimulation.

Quantitative enzyme-linked immunosorbent assay (ELISA) analysis revealed significant increased production of cytokines, in supernatants from T cells stimulated with FIMELLYWL-pulsed DCs (Figure 5A,5B). The cytokine response was epitope-specific, as demonstrated by lack of reactivity to irrelevant HLA-A2-binding control peptides.

Figure 5 CRNDE 84aa generates an immunostimulatory epitope recognized by human autologous T cells. (A,B) T cells were primed by autologous DCs loaded with CRNDE 84aa antigens. The production of IFN-γ and TNF-α by T cells in response to CRNDE 84aa was assessed via ELISA. (C,D) The primed T cells were restimulated with CRNDE 84aa antigens overnight and evaluated by qRT-PCR. ***, P<0.001, compared with untreated T cells (−). P values were determined by two-tailed one-way ANOVA with Dunnett’s multiple-comparisons test. ANOVA, analysis of variance; CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; DC, dendritic cell; ELISA, enzyme-linked immunosorbent assay; IFN-γ, interferon-γ; mRNA, messenger RNA; qRT-PCR, quantitative reverse transcription-polymerase chain reaction; TNF-α, tumor necrosis factor-α.

Molecular analysis via qRT-PCR confirmed these findings at the transcriptional level, showing upregulation of IFN-γ messenger RNA (mRNA) (Figure 5C) and increase in TNF-α mRNA (Figure 5D) in T cells stimulated with CRNDE 84aa-loaded DCs compared to unstimulated controls.

Flow cytometry experiments revealed that CRNDE 84aa can activate T cells derived from breast cancer patients (Figure S5).

CRNDE 84aa elicited an antitumoral response in a PDX model

To further explore the therapeutic potential of CRNDE 84aa-directed immunotherapy, we established a PDX model using fresh breast cancer tissue implanted subcutaneously in NOD/SCID mice. When tumors reached 100–150 mm³, mice received weekly intravenous injections of either: (I) autologous DCs pulsed with CRNDE 84aa peptide (2.5×10⁶ DCs); (II) unpulsed control DCs; or (III) PBS alone, along with 5×10⁶ autologous T cells from the same patient.

Longitudinal monitoring revealed striking differences in tumor progression between groups (Figure S6). CRNDE 84aa-DC-treated mice exhibited reduction in final tumor volume and decrease in tumor weight compared to control DC recipients at endpoint (Figure 6A,6B). We prepared paraffin sections of the mouse tumors (Figure S7). IF showed that CD8⁺ T cell infiltration was increased in CRNDE 84aa-DC-treated mice (Figure 6C,6D).

Figure 6 Human CRNDE 84aa elicits an immune response to tumors. (A) Images of PDX tumors in the untreated, unpulsed, or CRNDE 84aa-pulsed DC and T-cell groups. (B) Tumor weights of the mice in each group after sacrifice. (C,D) CD8-stained cancer tissue sections. Proportional CD8⁺ lymphocyte areas in tumor tissue of control (n=6) or treated (n=6) animals. (E) The number of antigen-specific T cells was determined via tetramer staining and flow cytometry. The data are representative of two independent experiments. (F) The secretion of GZMB of TILs was determined via flow cytometry. The data are representative of two independent experiments. ***, P<0.001, compared with untreated T cells (−). P values were determined by two-tailed one-way ANOVA with Dunnett’s multiple-comparisons test. ANOVA, analysis of variance; CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; DC, dendritic cell; GZMB, granzyme B; PDX, patient-derived xenograft; TIL, tumor-infiltrating lymphocyte.

Immunophenotyping of TILs demonstrated higher frequencies of CRNDE 84aa-specific CD8⁺ T cells (defined by tetramer staining) in the treatment group versus controls (Figure 6E). These infiltrating T cells showed an elevated level of granzyme B (Figure 6F). These findings support clinical development of CRNDE 84aa-targeted therapies.

Figure 7 shows that CRNDE-encoded CRNDE 84aa is presented to T cells by DC cells, and after T cell priming, the T cells can recognize tumor cells with high CRNDE 84aa expression and exert cytotoxicity.

Figure 7 The CRNDE 84aa peptide, encoded by the highly expressed CRNDE in tumor cells, can activate anti-tumor immunity. CRNDE 84aa may serve as a vaccine therapeutic to activate T cells via DCs. When primed T cells recognize the CRNDE 84aa epitope presented by tumor cells, an anti-tumor immune response is elicited. CRNDE, colorectal neoplasia differentially expressed; CRNDE 84aa, CRNDE encodes an 84-amino acid peptide; DC, dendritic cell; GZMB, granzyme B; HLA-I, human leukocyte antigen class I; IFN-γ, interferon-γ; TCR, T cell receptor.

Discussion

Malignant tumors, characterized by uncontrolled proliferation, tissue invasion, and metastasis, continue to pose a major clinical challenge. Immunotherapy has emerged as a transformative approach, offering new hope. Its efficacy relies fundamentally on tumor antigens to initiate anti-tumor immunity. Recent research now highlights non-coding RNAs as a promising frontier for the discovery of these essential antigens.

LncRNAs represent the largest category of non-coding RNA transcripts. They are involved in promoting cancer cell proliferation, metastasis, and resistance to apoptosis. For example, certain lncRNAs can modulate the expression of genes related to cell cycle progression and epithelial-mesenchymal transition (EMT), facilitating tumor growth and invasion (22-24). Additionally, lncRNAs can interact with microRNAs and other molecular pathways, contributing to the complex regulatory networks that drive tumorigenesis (25). Understanding lncRNA functions in cancer could lead to novel therapeutic strategies. LncRNAs have traditionally been considered noncoding because of their lack of protein-coding potential. However, recent studies have revealed that some lncRNAs can encode small peptides, which play significant roles in tumor biology. These lncRNA-encoded peptides, also known as micropeptides, can modulate various cellular processes that contribute to tumorigenesis (26,27). One of the functions of lncRNA-encoded peptides in cancer is the regulation of cell signaling pathways. For example, certain micropeptides can interact with components of the Wnt/β-catenin pathway, a critical regulator of cell proliferation and differentiation, and modulate its activity, leading to altered tumor growth and progression (28). Additionally, micropeptides derived from lncRNAs can influence the ATP synthase activity, which is often dysregulated in cancers and is involved in promoting cell survival, growth, and metabolism (29). Another important role of lncRNA-encoded peptides in cancer is the modulation of the TME. These peptides can affect the behavior of immune cells, fibroblasts, and endothelial cells within the TME, thereby influencing tumor progression and metastasis (30,31). LncRNAs have the potential to be targets for cancer therapy. Our findings indicate that CRNDE is significantly overexpressed in breast cancer, and other studies corroborate its elevated levels in various tumors, highlighting its potential as a therapeutic target. Furthermore, we established that CRNDE can encode a peptide, CRNDE 84aa, which may also represent a promising target for breast cancer treatment.

Recently, it was reported that peptides encoded by non-coding regions can function as cryptic tumor antigens to elicit a T-cell immune response (8). Antigens encoded by non-coding regions, such as those derived from lncRNAs, have emerged as potential targets in cancer immunotherapy. These antigens can be recognized by the immune system, triggering an immune response against tumor cells. By presenting unique peptides from these non-coding regions, cancer cells can be specifically targeted, minimizing damage to normal tissues. This approach enhances the precision and effectiveness of immunotherapies, offering new avenues for treatment. As research progresses, non-coding region-encoded antigens may become pivotal in the development of novel cancer vaccines and immune-based therapies. We determined that the lncRNA CRNDE, which is highly expressed in breast cancer, can encode a small peptide of 84 amino acids, referred to as CRNDE 84aa. CRNDE 84aa is immunogenic and can activate the T-cell immune response. We demonstrated that CRNDE 84aa contains an HLA-A2-restricted epitope, which is recognized by a specific CTL population. These CTLs could effectively kill tumor cells that overexpressed CRNDE. We also confirmed that CRNDE 84aa was overexpressed in breast cancer tissues but not in normal tissues. Through PDX animal models, we observed that T cells activated by CRNDE 84aa effectively inhibited tumor growth in vivo.

Recent advancements have led to significant breakthroughs in tumor vaccine therapies that target neoantigens (32,33). Tumor neoantigens are novel peptides produced by cancer cells due to genetic mutations (34). These unique antigens are not present in normal tissues, making them ideal targets for immunotherapy. Neoantigens can elicit a strong immune response, as they are recognized as foreign by the immune system. This has led to the development of personalized cancer vaccines and T-cell therapies that specifically target these neoantigens, aiming for precise and effective treatment. However, there are significant challenges associated with neoantigen-based therapies. One major drawback is the heterogeneity of tumors; different cells within the same tumor may express different neoantigens, making it difficult to target all cancerous cells (35). Additionally, the identification and validation of neoantigens are complex and time-consuming processes that can delay treatment (36). Another limitation is the potential for tumors to develop resistance by mutating further and losing the expression of targeted neoantigens, thus evading the immune response (37). Moreover, in some tumors with low mutational burden, the limited availability of neoantigens often renders therapeutic approaches ineffective.

Cryptic tumor antigens offer significant advantages in cancer immunotherapy. Unlike conventional antigens, cryptic antigens are derived from normally untranslated regions of the genome, making them highly tumor-specific and less likely to induce autoimmunity. Their unique origin allows for the generation of a more targeted immune response, reducing the risk of damage to normal tissues. Additionally, cryptic antigens are less likely to be subject to immune tolerance mechanisms, potentially leading to a more robust and sustained antitumor effect. These advantages make cryptic tumor antigens promising candidates for developing innovative and effective cancer treatments. Unlike neoantigens, a single cryptic tumor antigen can be expressed across different individuals or tumors, enhancing its potential for universal application. Furthermore, these antigens are often derived from novel ORFs (neoORFs), of which its amino acid sequences differ substantially from normal human proteins, endowing them with high intrinsic immunogenicity. Supporting this concept, CRNDE 84aa is consistently expressed in tumor tissues from multiple patients and demonstrates potent immunogenicity. Notably, our data show that CRNDE 84aa remains highly expressed even in immunologically cold tumors, such as breast cancer, which typically harbor a low mutational burden. The preferential association of CRNDE 84aa with immune activation, TNBC and advanced-stage disease may reflect the unique immunological landscape of these contexts, characterized by higher mutational burden, increased antigen presentation, and a more inflamed microenvironment that supports T cell priming and effector function. Conversely, the weaker correlations in luminal and early-stage tumors suggest that additional immunosuppressive mechanisms may dominate in these settings, potentially limiting the efficacy of CRNDE 84aa-directed immune responses. These subtype- and stage-specific insights have important implications for patient stratification in future clinical trials, supporting the rationale for evaluating CRNDE 84aa-targeted therapies primarily in TNBC patients with locally advanced or metastatic disease.

To evaluate the potential of CRNDE 84aa as a tumor vaccine target, we first performed comprehensive immunoinformatic analyses to predict its antigenic properties and HLA-binding affinity. The 84-amino acid sequence of CRNDE 84aa was submitted to the NetMHCpan 4.1 and IEDB databases to identify potential immunogenic epitopes. Based on the HLA restriction of the identified epitopes, HLA-A*02:01 was determined to be the most relevant HLA subtype for subsequent analysis. Given that the efficacy of CRNDE 84aa-targeted therapy may depend on baseline antigen expression, we propose that CRNDE expression levels be routinely evaluated in patients’ breast cancer tissues. Individuals exhibiting high CRNDE expression could be prioritized as candidates for this therapeutic strategy.

While our study provides compelling evidence supporting CRNDE 84aa as a promising immunotherapeutic target in breast cancer, several limitations should be acknowledged when interpreting these findings. First, the PDX models used in our in vivo experiments were established in immunodeficient NOD/SCID/IL-2Rγnull (NSG) mice, which lack a functional adaptive immune system. Although this model is widely used for evaluating tumor growth and response to direct anti-tumor agents, it is inherently unable to recapitulate the complex interactions between tumor cells and the complete human immune system, particularly T cell-mediated immune responses and the effects of immune checkpoint molecules. Consequently, the therapeutic efficacy of anti-CRNDE 84aa monoclonal antibodies observed in these models may not fully reflect their potential activity in immunocompetent hosts, where additional immune effector mechanisms and potential immunosuppressive feedback loops could modulate treatment outcomes. Future studies employing humanized mouse models reconstituted with human hematopoietic stem cells or syngeneic tumor models in immunocompetent mice would provide valuable complementary insights into the immunotherapeutic potential of CRNDE 84aa targeting.

Conclusions

In this study, we revealed that CRNDE encodes an immunogenic peptide and that CRNDE 84aa is expressed in breast cancer cells and can be targeted by specific CD8⁺ T cells. Having established the immunogenic potential of lncRNA-encoded peptides in vitro, we further validated their efficacy as tumor antigen targets for immunotherapy using PDX models in vivo. Thus, lncRNA-associated antigens represent an important source of tumor-specific antigens. Moreover, lncRNA-derived epitopes shared between patients may have relevance to antitumor immunotherapy. Our results support the targeting of cryptic tumor antigens via immunotherapy in breast cancer.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR and ARRIVE reporting checklists. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2809/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2809/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2809/prf

Funding: This work was partially supported by the National Natural Science Foundation of China (No. 32000430) and the Science and Technology Projects in Guangzhou (No. 2025A03J4469).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2809/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All animal experiments were performed under a project license (No. 2024062114382769) granted by the Research Ethics Review Committee of Guangzhou Women and Children’s Medical Center of Guangzhou Medical University, in compliance with the institutional guidelines for the care and use of animals. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Research Ethics Committee of Guangzhou Women and Children’s Medical Center of Guangzhou Medical University (No. KTDW-2024-01365), and written informed consent was taken from all enrolled patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Chong C, Coukos G, Bassani-Sternberg M. Identification of tumor antigens with immunopeptidomics. Nat Biotechnol 2022;40:175-88. [Crossref] [PubMed]
2. Jhunjhunwala S, Hammer C, Delamarre L. Antigen presentation in cancer: insights into tumour immunogenicity and immune evasion. Nat Rev Cancer 2021;21:298-312. [Crossref] [PubMed]
3. Singh N, Maus MV. Synthetic manipulation of the cancer-immunity cycle: CAR-T cell therapy. Immunity 2023;56:2296-310. [Crossref] [PubMed]
4. Kina E, Larouche JD, Thibault P, et al. The cryptic immunopeptidome in health and disease. Trends Genet 2025;41:162-9. [Crossref] [PubMed]
5. Marcu A, Schlosser A, Keupp A, et al. Natural and cryptic peptides dominate the immunopeptidome of atypical teratoid rhabdoid tumors. J Immunother Cancer 2021;9:e003404. [Crossref] [PubMed]
6. Erhard F, Dölken L, Schilling B, et al. Identification of the Cryptic HLA-I Immunopeptidome. Cancer Immunol Res 2020;8:1018-26. [Crossref] [PubMed]
7. Kikuchi Y, Tokita S, Hirama T, et al. CD8(+) T-cell Immune Surveillance against a Tumor Antigen Encoded by the Oncogenic Long Noncoding RNA PVT1. Cancer Immunol Res 2021;9:1342-53. [Crossref] [PubMed]
8. Schwarz S, Schmitz J, Löffler MW, et al. T cells of colorectal cancer patients' stimulated by neoantigenic and cryptic peptides better recognize autologous tumor cells. J Immunother Cancer 2022;10:e005651. [Crossref] [PubMed]
9. Wang D. Targeting the stage-specific embryonic antigen (SSEA)-0 tumor neoantigen. Curr Trends Immunol 2023;24:1-7.
10. Huang D, Zhu X, Ye S, et al. Tumour circular RNAs elicit anti-tumour immunity by encoding cryptic peptides. Nature 2024;625:593-602. [Crossref] [PubMed]
11. Zeng L, Zheng W, Zhang J, et al. An epitope encoded by uORF of RNF10 elicits a therapeutic anti-tumor immune response. Mol Ther Oncolytics 2023;31:100737. [Crossref] [PubMed]
12. Palomeque JÁ, Serra-Mir G, Blasco-Benito S, et al. Estrogen receptor signaling drives immune evasion and immunotherapy resistance in HR+ breast cancer. J Clin Invest 2026;136:e193153. [Crossref] [PubMed]
13. Wan M, Mei J, Cai Y, et al. Targeting IGF1R Overcomes Armored and Cold Tumor Microenvironment and Boosts Immune Checkpoint Blockade in Triple-Negative Breast Cancer. Adv Sci (Weinh) 2025;12:e01341. [Crossref] [PubMed]
14. Song X, Lu C, Shi T, et al. MHC-II-restricted neoantigen vaccine reverses immune microenvironment and overcomes resistance to immune-checkpoint inhibitors in cold tumors. Med 2026;7:100936. [Crossref] [PubMed]
15. Zhang C, Chen Y, Yu Z, et al. Autologous nanovaccine repolarizes tumor-associated macrophages to M1 phenotype inducing PANoptosis for lung cancer immunotherapy. Chem Eng J 2025;514:163201.
16. Yao RW, Wang Y, Chen LL. Cellular functions of long noncoding RNAs. Nat Cell Biol 2019;21:542-51. [Crossref] [PubMed]
17. Gao X, Lai Y, Zhang Z, et al. Long Non-coding RNA RP11-480I12.5 Promotes the Proliferation, Migration, and Invasion of Breast Cancer Cells Through the miR-490-3p-AURKA-Wnt/β-Catenin Axis. Front Oncol 2020;10:948. [Crossref] [PubMed]
18. Lu S, Zhang J, Lian X, et al. A hidden human proteome encoded by 'non-coding' genes. Nucleic Acids Res 2019;47:8111-25. [Crossref] [PubMed]
19. Liao H, Barra C, Zhou Z, et al. MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer. Nat Commun 2024;15:661. [Crossref] [PubMed]
20. Chen Y, Li Q, Yu X, et al. The microprotein HDSP promotes gastric cancer progression through activating the MECOM-SPINK1-EGFR signaling axis. Nat Commun 2024;15:8381. [Crossref] [PubMed]
21. Zhang M, Zhao K, Xu X, et al. A peptide encoded by circular form of LINC-PINT suppresses oncogenic transcriptional elongation in glioblastoma. Nat Commun 2018;9:4475. [Crossref] [PubMed]
22. Li N, Yang G, Luo L, et al. lncRNA THAP9-AS1 Promotes Pancreatic Ductal Adenocarcinoma Growth and Leads to a Poor Clinical Outcome via Sponging miR-484 and Interacting with YAP. Clin Cancer Res 2020;26:1736-48. [Crossref] [PubMed]
23. Luo H, Zhu G, Xu J, et al. HOTTIP lncRNA Promotes Hematopoietic Stem Cell Self-Renewal Leading to AML-like Disease in Mice. Cancer Cell 2019;36:645-659.e8. [Crossref] [PubMed]
24. Ni C, Fang QQ, Chen WZ, et al. Breast cancer-derived exosomes transmit lncRNA SNHG16 to induce CD73+γδ1 Treg cells. Signal Transduct Target Ther 2020;5:41. [Crossref] [PubMed]
25. Ou C, Sun Z, He X, et al. Targeting YAP1/LINC00152/FSCN1 Signaling Axis Prevents the Progression of Colorectal Cancer. Adv Sci (Weinh) 2020;7:1901380. [Crossref] [PubMed]
26. Zhang Y. LncRNA-encoded peptides in cancer. J Hematol Oncol 2024;17:66. [Crossref] [PubMed]
27. Li L, Shu XS, Geng H, et al. A novel tumor suppressor encoded by a 1p36.3 lncRNA functions as a phosphoinositide-binding protein repressing AKT phosphorylation/activation and promoting autophagy. Cell Death Differ 2023;30:1166-83. [Crossref] [PubMed]
28. Tan Z, Zhao L, Huang S, et al. Small peptide LINC00511-133aa encoded by LINC00511 regulates breast cancer cell invasion and stemness through the Wnt/β-catenin pathway. Mol Cell Probes 2023;69:101913. [Crossref] [PubMed]
29. Ge Q, Jia D, Cen D, et al. Micropeptide ASAP encoded by LINC00467 promotes colorectal cancer progression by directly modulating ATP synthase activity. J Clin Invest 2021;131:e152911. [Crossref] [PubMed]
30. Cheng R, Li F, Zhang M, et al. A novel protein RASON encoded by a lncRNA controls oncogenic RAS signaling in KRAS mutant cancers. Cell Res 2023;33:30-45. [Crossref] [PubMed]
31. Wu P, Mo Y, Peng M, et al. Emerging role of tumor-related functional peptides encoded by lncRNA and circRNA. Mol Cancer 2020;19:22. [Crossref] [PubMed]
32. Ott PA, Hu Z, Keskin DB, et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 2017;547:217-21. [Crossref] [PubMed]
33. Keskin DB, Anandappa AJ, Sun J, et al. Neoantigen vaccine generates intratumoral T cell responses in phase Ib glioblastoma trial. Nature 2019;565:234-9. [Crossref] [PubMed]
34. Kranz LM, Diken M, Haas H, et al. Systemic RNA delivery to dendritic cells exploits antiviral defence for cancer immunotherapy. Nature 2016;534:396-401. [Crossref] [PubMed]
35. Lybaert L, Lefever S, Fant B, et al. Challenges in neoantigen-directed therapeutics. Cancer Cell 2023;41:15-40. [Crossref] [PubMed]
36. Gupta RG, Li F, Roszik J, et al. Exploiting Tumor Neoantigens to Target Cancer Evolution: Current Challenges and Promising Therapeutic Approaches. Cancer Discov 2021;11:1024-39. [Crossref] [PubMed]
37. Van den Eynden J, Jiménez-Sánchez A, Miller ML, et al. Lack of detectable neoantigen depletion signals in the untreated cancer genome. Nat Genet 2019;51:1741-8. [Crossref] [PubMed]
38. Smith CC, Selitsky SR, Chai S, et al. Alternative tumour-specific antigens. Nat Rev Cancer 2019;19:465-78. [Crossref] [PubMed]