Non‑small cell lung cancer (NSCLC) is characterized by marked spatial immune heterogeneity, commonly manifested as immune‑desert, immune‑excluded and immune‑inflamed phenotypes. These phenotypes are closely associated with variable responses to immune checkpoint inhibitors (ICIs). Emerging evidence suggests that they are shaped not only by canonical immune pathways but also by mitochondrial processes that regulate immune priming, T‑cell trafficking and the maintenance of effector function. The present review summarizes how mitochondrial reactive oxygen species, mitochondrial DNA‑cGAS‑STING signaling, pathways mediated by tricarboxylic acid cycle metabolites, and non‑cell‑autonomous mitochondrial transfer may contribute to the establishment and maintenance of distinct spatial immune phenotypes in NSCLC. It is proposed that insufficient activation of innate immunity and impaired dendritic cell priming are particularly relevant to immune‑desert tumors, whereas chronic oxidative stress may reinforce barriers mediated by cancer‑associated fibroblasts (CAFs), transforming growth factor β, and the extracellular matrix in immune‑excluded tumors. By contrast, immune‑inflamed tumors may represent a state in which pre‑existing immune circuitry remains intact and tumor‑infiltrating lymphocytes retain greater mitochondrial fitness and metabolic resilience. The implications of these mechanisms for ICI sensitivity and cold‑to‑hot tumor conversion strategies were further discussed. Current evidence from human studies remains largely correlative, and prospective, spatially resolved functional studies are needed. Nevertheless, integrating mitochondrial biology with spatial immune architecture within a phenotype‑guided framework may generate testable hypotheses for future biomarker development and combination strategies.

Prostate cancer progression toward an aggressive, therapy‑resistant disease state remains a major clinical challenge, indicating a need to identify novel molecular drivers of such progression and actionable therapeutic targets. The present study analyzed the role of dynein heavy chain domain 1 (DNHD1), a previously uncharacterized regulator of malignancy, in prostate cancer. Integrative transcriptomic analyses across The Cancer Genome Atlas and independent clinical cohorts revealed that DNHD1 is markedly upregulated in advanced‑stage prostate cancer and positively correlated with increasing Gleason scores. Elevated DNHD1 expression was associated with poor overall survival and disease‑free survival, which supports its clinical relevance as a prognostic biomarker. Functional analyses demonstrated that DNHD1 promoted tumor cell proliferation, colony formation, migration and invasion in vitro. Molecular correlation modeling and pathway analyses revealed histone deacetylase 6 (HDAC6) as a key downstream effector of DNHD1. DNHD1 expression was positively correlated with and regulated HDAC6 expression in clinical datasets. Gain‑of‑function and loss‑of‑function experiments further revealed that HDAC6 is required for DNHD1‑mediated oncogenic phenotypes in prostate cancer, positioning HDAC6 as a functional mediator downstream of DNHD1. The DNHD1‑HDAC6 axis was associated with cilium assembly‑related pathways, suggesting a previously unrecognized association between ciliary regulation and prostate cancer progression. HDAC6 inhibition with tubastatin A effectively suppressed DNHD1‑driven tumor growth and motility, as well as increased acetylated α‑tubulin and decreased androgen receptor signaling. These findings indicated a potential therapeutic vulnerability within the DNHD1‑HDAC6 axis. They implied that in prostate cancer, the DNHD1‑HDAC6 axis, a novel regulatory pathway, promotes aggressiveness and that HDAC6 is a targetable mediator of DNHD1‑driven malignancy. This axis can be considered a prognostic indicator and mechanistic foundation for developing targeted therapeutic strategies for advanced prostate cancer.

Lung squamous cell carcinoma (LUSC) is an aggressive malignancy with a poor prognosis. Given the association between mitochondrial dysregulation and LUSC, the aim of the present study was to identify mitochondrial unfolded protein response (UPR[mt])‑related candidate genes associated with LUSC and to explore their potential functional relevance. In the present study, differential expression, univariate Cox and survival analyses were combined to identify a UPR[mt]‑associated key gene in LUSC. Gene set enrichment analysis was then performed, and overexpression (OE) and knockdown cell lines were used to clarify its function using western blotting, Cell Counting Kit‑8, colony formation and Transwell[®] invasion assays. Using bioinformatics tools and a review of the literature, PTEN‑induced kinase 1 (PINK1) was singled out as a key gene in LUSC samples. Elevated PINK1 expression was associated with worse survival outcomes. A total of 117 pathways were enriched by PINK1, with the top 5 including 'focal adhesion' and 'mitogen‑activated protein kinase signaling pathway'. Using experimental analysis, it was observed that PINK1 significantly enhanced the proliferative, migratory, invasive and colony forming abilities of tumor cells, thereby exacerbating LUSC. Furthermore, these enhancements were diminished by the application of focal adhesion kinase (FAK) inhibitor. It was also noted that the expression levels of protein kinase B (AKT), p‑AKT, Ras homolog family member A (RhoA) and vinculin were all elevated in OE‑PINK1 cells. Collectively, these findings indicated that PINK1 exerted its influence on LUSC through the FAK/AKT/RhoA/vinculin pathway. The present study identified PINK1 as a key gene in LUSC, exerting its influence through the FAK/AKT/RhoA/vinculin pathway, thereby presenting a potential novel therapeutic target for the treatment of LUSC in the future.

Following the publication of the above article, a concerned reader has contacted the Editorial Office to draw attention to the fact that there appeared to be discrepancies between the numbers of patients reported with low‑ or high‑ZNF703 expression in Fig. 3 on p. 1074: Fig. 3A reported 70 patients with low ZNF703 expression and 68 patients with high expression; however, the stage‑stratified Kaplan‑Meier curves showed the following: In Fig. 3B, stages I‑IIIA: 57 low‑expression and 20 high‑expression patients, and in Fig. 3C, stages IIIB‑IV: 20 low‑expression and 41 high‑expression patients (and so 70 vs. 68 patients in Fig. 3A, and 77 vs. 61 patients in Fig. 3B and C). In addition, the AJCC stage‑specific counts reported in Table I also showed internal inconsistencies in terms of the overall numbers of low‑ and high‑expression patients, and finally, an additional discrepancy was noted for the definition of the high expression group: The Materials and methods section stated that an immunohistochemical score of ≥6 was classified as high expression, whereas the Table I column heading defined high expression as '>6'. To clarify these apparent discrepancies, the authors should resolve the following: i) provide the actual numbers of low‑ and high‑expression patients in each AJCC stage group; ii) clarify whether the cutoff used for the Kaplan‑Meier analyses was ≥6 or >6; iii) provide the exact patient numbers used to generate Fig. 3A, B and C; and iv) clarify whether the counts, totals and percentages in Table I require correction. Finally, upon performing an independent analysis of the data in this paper in the Editorial Office, it came to light that, regarding the wound healing assay data shown in Fig. 6A on p. 1076, the '24 h / Control' and '24 h / NC siRNA' panels showed an overlapping section of data, such that data which were intended to show the results of experiments performed under different conditions had apparently been derived from the same original source. The authors have been contacted by the Editorial Office to offer an explanation for the apparent anomalies in the description of the data, and the incorrect assembly of data in Fig. 6, in this paper, and we are awaiting their response. Owing to the fact that the Editorial Office has been made aware of this potential issue concerning the scientific integrity of this paper, we are issuing an Expression of Concern to notify readers of this potential problem while the Editorial Office continues to investigate this matter further. [Oncology Reports 32: 1071‑1077, 2014; DOI: 10.3892/or.2014.3313].

Cervical cancer is a malignant tumor that threatens women's health and radiotherapy represents a major therapeutic approach for its treatment; however, radioresistance frequently leads to treatment failure. The present study aimed to investigate whether loperamide (LOP), a µ‑opioid receptor agonist commonly used as an antidiarrheal agent, could enhance the radiosensitivity of cervical cancer cells by regulating ferroptosis. A Cell Counting Kit‑8 assay was used to evaluate the cytotoxicity of LOP in SiHa and HeLa cells, and EdU and colony formation assays were performed to assess cell proliferation. In addition, wound‑healing and Transwell assays were performed to detect cell migration. Flow cytometry was applied to measure cell apoptosis and intracellular reactive oxygen species (ROS) levels, and colorimetric assays were used to determine malondialdehyde (MDA) and glutathione (GSH) contents. The mRNA and protein expression levels of the ferroptosis‑related markers GSH peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11) were analyzed using reverse transcription‑quantitative PCR and western blotting. The results showed that LOP significantly inhibited the viability of SiHa and HeLa cells, and exerted a synergistic effect with radiotherapy (combination index <1) to suppress cell proliferation and migration. Combined treatment with LOP and radiotherapy markedly increased apoptosis and ROS accumulation, elevated MDA levels and reduced GSH levels. Moreover, the combination treatment significantly downregulated the expression of GPX4 and SLC7A11. These findings indicated that LOP enhances the radiosensitivity of cervical cancer cells, with ferroptosis induction via inhibition of the GPX4/SLC7A11 axis as a contributing mechanism. Both apoptosis and ferroptosis were induced by the combination treatment, suggesting that the radiosensitizing effect may involve multiple cell death pathways. These observations provide a basis for further investigation into LOP as a potential radiosensitizing agent in cervical cancer.

Following the publication of the above article, a concerned author drew to the authors' attention that, regarding the cell migration assay experiments shown in Fig. 4 on p. 1099, Fig. 4B and C, showing the results of the 'NC' and 'Mock' experiments, contained an overlapping section of data, suggesting that these data panels were derived from the same original source where different experiments were intended to have been portrayed. The authors have been contacted by the Editorial Office to offer an explanation for this apparent anomaly in the presentation of the data in this paper, and we are awaiting their response. Owing to the fact that the Editorial Office has been made aware of this potential issue concerning the scientific integrity of this paper, we are issuing an Expression of Concern to notify readers of this potential problem while the Editorial Office continues to investigate this matter further. [Oncology Reports 31: 1096‑1102, 2014; DOI: 10.3892/or.2014.2971].

The present study aimed to characterize the expression pattern and biological function of sphingosine‑1‑phosphate phosphatase 1 (SGPP1) in esophageal squamous cell carcinoma (ESCC), investigate its potential molecular regulatory mechanisms, and evaluate its clinical value as a prognostic biomarker and therapeutic target. SGPP1 expression in ESCC cell lines was assessed by reverse transcription‑quantitative PCR and western blotting. Models of SGPP1 overexpression in KYSE150 cells and SGPP1 knockdown in ECA109 cells were established. 5‑Ethynyl‑2'‑deoxyuridine, Cell Counting Kit‑8, colony formation, terminal deoxynucleotidyl transferase dUTP nick‑end labeling, wound healing and Transwell assays were performed to systematically analyze the effects of SGPP1 on ESCC cell proliferation, apoptosis, migration and invasion. The Cancer Genome Atlas‑ESCC data were integrated with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, gene set enrichment analysis and UpSet plotting to identify key downstream pathways and candidate target genes. SGPP1 protein expression was evaluated by immunohistochemistry in tumor tissues from 68 patients with ESCC, and Cox regression analysis was used to assess its association with patient prognosis. The results demonstrated that SGPP1 expression varied markedly among ESCC cell lines, with low expression in KYSE150 cells and high expression in ECA109 cells. SGPP1 overexpression significantly inhibited ESCC cell proliferation, migration and invasion, and increased apoptosis‑associated DNA fragmentation, whereas SGPP1 knockdown produced the opposite effects. Mechanistically, the data suggested that SGPP1 modulates extracellular matrix remodeling and xenobiotic metabolism, potentially through negative regulation of UGT1A9 and UGT2B28 expression. Clinically, low SGPP1 expression was an independent risk factor for poor prognosis in patients with ESCC (HR=6.016, 95% CI: 3.143‑11.513, P<0.001), and the overall survival was significantly longer in the high‑expression group than in the low‑expression group (P<0.001). In conclusion, SGPP1 functions as a tumor suppressor gene in ESCC and may inhibit tumor progression by regulating UGT1A9/UGT2B28‑mediated metabolic pathways. SGPP1 may therefore serve as a prognostic biomarker and a potential therapeutic target in ESCC.

Subsequently to the publication of the above paper, an interested reader drew to the Editor's attention that the control GAPDH western blots shown in Fig. 1D on p. 1696 were strikingly similar to the GAPDH blots shown in Fig. 2A on p. 1697, even though the experimental conditions were reported to be different for these figures. In addition, upon analyzing the data in this paper independently in the Editorial Office, it came to light that certain of the hnRNPA1 blots shown in Fig. 1B were strikingly similar to blots that had already been published in a paper in the journal Oncotarget that featured two of the authors in common (Jide Wang and Side Liu). The authors were able to consult their original data, and realized that these data had inadvertently been included incorrectly in these two figures. Revised and corrected versions of Figs. 1 and 2, now showing replacement data for the western blots featured in Figs. 1B, 1D and 2A, are shown on the next two pages. Note that the replacement of the original data with the revised data in this pair of figures has not had a significant impact on the conclusions reached in this study. The authors regret the errors that were made during the compilation of the original figures, and are grateful to the editor of Oncology Reports for allowing them the opportunity to publish this corrigendum. All the authors agree with the publication of this corrigendum; furthermore, they apologize to the readership for any inconvenience caused. [Oncology Reports 39: 1693‑1701, 2018; DOI: 10.3892/or.2018.6273].

BRCA1 is a multifunctional tumor suppressor that orchestrates homologous recombination repair, chromatin remodeling, cell cycle control and apoptosis. Although pathogenic BRCA1 mutations are relatively uncommon, decreased BRCA1 protein expression, which is typically driven by accelerated proteasomal degradation, is implicated in aggressive breast cancer (BC), particularly triple‑negative (TN)BC. These mutations may modulate therapeutic response to DNA‑damaging agents. Given the absence of clinically available strategies to restore BRCA1 stability, the present study evaluated whether pemetrexed (Peme), a multitargeted antifolate identified through an in silico US Food and Drug Administration‑approved drug screen, modulates BRCA1 protein homeostasis in TNBC models. BRCA1 protein abundance, ubiquitination and turnover were assessed using immunoblotting, ubiquitin pull‑down and cycloheximide chase analyses and BRCA1 domain mutants. Functional consequences of Peme treatment were measured by apoptosis assay and BRCA1‑dependent signaling readouts. The radiosensitizing effect of Peme was evaluated in vitro and validated in TNBC xenografts. Peme increased BRCA1 protein levels without altering BRCA1 mRNA, indicating post‑translational regulation. Mechanistically, in silico docking and BRCA1 deletion mutant analyses suggested that the BRCA1 C‑terminal domain may contribute to the effect of Peme on BRCA1 stability, suppressing ubiquitin‑mediated proteasomal degradation and resulting in protein stabilization. Stabilized BRCA1 enhanced apoptotic responses, whereas BRCA1 knockdown attenuated these effects. Combined Peme‑radiation treatment significantly potentiated cytotoxicity in vitro and inhibited tumor growth in vivo, demonstrating a radiosensitizing effect linked to BRCA1 stabilization. Collectively, these findings identified Peme as a BRCA1‑stabilizing agent that enhances therapeutic response to radiation in TNBC. Pharmacological restoration of BRCA1 stability represents a promising strategy to overcome therapeutic resistance in BRCA1‑deficient or functionally compromised BC.

Subsequently to the publication of the above article, an interested reader drew to the Editor's attention that, in Fig. 2C and D on p. 2921 showing the methylation status of the miR‑148a promoter, the centrally placed 'M' and 'U' lanes in these figure parts apparently showed the same data, albeit with horizonal stretching of the bands in question. Furthermore, in Fig. 6B on p. 2923, which showed the results of cell migration and invasion assay experiments, the 'Mimics‑NC/Migration' and 'Blank/Invasion' data panels apparently showed the same data, albeit with different sizing of the panels, such that these were derived from the same orginal source. Finally, the reader noted that one of the antibodies the authors had used in their study was apparently selected inappropriately: The antibody (cat. no. ab51243) that the authors reported to have used is specific for the protein known as p16‑ARC (or ARPC5), not the apoptosis‑associated protein p16‑INK4a, as was intended. The authors were asked to investigate these various matters, and have fully responded to the reader's queries. Concerning the antibody, after thoroughly examining the original reagent purchase records and raw experimental data, the authors can confirm that the correct anti‑CDKN2A/p16 antibody (cat. no. ab108349; Abcam) was in fact used in this study: As the catalogue number of antibody was not stated in the initial manuscript submission and this information was requested during the editing stage of the paper, the authors inadvertently entered the incorrect catalogue number into the text of the paper (they also provided a copy of the original purchase form to the Editorial Office for our inspection). Therefore, the sentence commencing on p. 2918, left‑hand column, line 20, in the 'Protein extraction and western blot analysis' subsection of the Materials and methods section should have read as follows: 'The primary antibodies used were as follows: DNMT1 (1:500, cat. no. ab188453; Abcam), p16 (1:200, cat. no. ab108349; Abcam)...'.Concerning Figs. 2 and 6, the authors were able to examine their original data, and realized that errors had inadvertently been made when assembling these figures. Corrected versions of Figs. 2 and 6, now showing data from one of the repeated sets of experiments for Fig. 2A‑D and the correct data for the 'Blank/Invasion' data panel in Fig. 6B, are shown on the next two pages. The authors wish to emphasize that the errors made in assembling the data in these figures did not affect the overall conclusions reported in the paper. The authors are grateful to the Editor of Oncology Reports for granting them this opportunity to publish a Corrigendum, and apologize to both the Editor and the readership for any inconvenience caused; they also thank the reader of the article for drawing these matters to their attention. [Oncology Reports 40: 2916‑2925, 2018; DOI: 10.3892/or.2018.6700].

Although immune checkpoint inhibitors (ICIs) have revolutionized the management of advanced melanoma, a major clinical challenge persists: Nearly 50% of patients develop primary or acquired resistance and therefore derive no meaningful clinical benefit. As ICIs are increasingly used in earlier disease settings, including adjuvant and neoadjuvant therapy, the population of patients with ICI‑resistant disease continues to grow. For patients whose disease progresses after first‑line combined programmed cell death 1 (PD‑1) and cytotoxic T‑lymphocyte associated protein 4 (CTLA‑4) blockade, effective salvage options remain limited, highlighting an urgent unmet medical need. Oncolytic viruses (OVs), which exert antitumor effects through the dual mechanisms of selective tumor cell lysis and immunomodulatory remodeling of the tumor microenvironment, represent a compelling therapeutic strategy for overcoming ICI resistance. Recent clinical and preclinical advances have moved OV‑ICI combination regimens from conceptual strategies to clinically evaluable interventions for refractory melanoma. Nevertheless, several translational barriers impede their broader implementation, including interpatient heterogeneity in treatment response, uncertainty regarding the optimal sequencing and dosing of combination therapies, and the lack of validated predictive biomarkers. The present review systematically synthesizes emerging clinical evidence and mechanistic insights into OV‑ICI synergy to inform rational trial design, refine combination strategies, and accelerate the development of precision immuno‑oncology approaches.

Glioblastoma (GBM) is the most malignant primary brain tumor, with limited therapeutic options. Dysregulation of FXYD5 has been reported in multiple malignancies, suggesting FXYD5 as a potential target for precision medicine. In the present study, FXYD5 expression and prognostic significance were analyzed using biological analysis on multiple databases and it was identified that FXYD5 was observably upregulated in GBM and inversely correlated with the prognosis of patients. Functional studies were investigated in LN229 and U251 GBM cell lines through FXYD5 knockdown and overexpression approaches, assessing proliferation (Cell Counting Kit‑8), apoptosis (flow cytometry), migration/invasion (Transwell assays) and lipid metabolism (free fatty acids, triglycerides, cholesterol, Nile Red staining). Knockdown of FXYD5 suppressed GBM cell proliferation, migration and invasion, while increasing apoptosis, indicating that FXYD5 may serve as a therapeutic target for GBM. Mechanistic studies examined the PI3K/AKT/long‑chain acyl‑coenzyme A (CoA) synthase 4 4 (ACSL4) pathway via western blotting and rescue experiments, finding that FXYD5 activated the PI3K/AKT signaling pathway, leading to upregulation of ACSL4 and enhanced lipid metabolism. In vivo, a subcutaneous xenograft mouse model was used to evaluate whether PI3K/AKT inhibition could antagonize FXYD5 overexpression‑induced tumor growth and PI3K/AKT inhibition reversed FXYD5 overexpression‑induced tumor growth in the subcutaneous mouse model. These findings revealed that FXYD5 promotes GBM progression via the PI3K/AKT/ACSL4 signaling axis and represents a potential therapeutic target for GBM.

Liquid biopsy can transform oncology practice through early detection and real‑time monitoring of cancer progression and response to treatment. Circulating cell‑free tumor RNA offers promise as a novel and emerging alternative to circulating cell‑free tumor DNA for detecting the presence and understanding the biology of liver tumors. Both circulating DNA and RNA, which predominantly reside in extracellular vesicles, carry evidence of vital germline and somatic mutations. High impact single nucleotide changes, insertions and deletions in circulating RNA (ctRNA) serve a key role in cancer development and progression. Tumor cells exploit the RNA splicing machinery to induce structural and functional changes in RNA not transcribed from DNA, thereby promoting tumor growth. Examination of the landscape of mutations in ctRNA using RNA‑sequencing in patients with hepatocellular carcinoma (HCC), cholangiocarcinoma and liver cirrhosis has revealed widespread single nucleotide changes and splicing aberrations associated with patients with cancer. The present study aimed to characterize these next‑generation sequencing‑derived high‑risk circulating mutated RNA (ctmutRNA) variants, and to develop TaqMan chemistry‑based assays for validation of ctmutRNAs in tumor tissues and plasma samples from patients with HCC. The present study identified a short ctmutRNA panel able to distinguish all patients with liver cancer in the discovery cohort, and splicing aberrations, including intron retentions, in tumor tissues were validated. Finally, the present study demonstrated that the assays detecting ctmutRNA analytes in the plasma, if confirmed in larger patient cohorts, could be effectively used to identify patients with HCC. Furthermore, the outstanding questions and challenges that need to be addressed for the development of a robust blood‑based HCC surveillance test are discussed.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the JNK western blotting data shown in Fig. 2E on p. 1138 were strikingly similar to the JNK western blotting data shown in Fig. 4D on p. 1139, even though the experimental conditions reported for these figure parts were apparently different. The authors have been contacted by the Editorial Office to offer an explanation for the apparent re‑use of the same data in this paper, and the authors have replied to explain that these studies were performed several years ago, that they no longer have access to the original data, and moreover, that they are not in a position to repeat any of these experiments. Owing to the fact that the Editorial Office has been made aware of potential issues surrounding the scientific integrity of this paper, we are issuing an Expression of Concern to notify readers of this potential problem associated with the abovementioned data. [Oncology Reports 36: 1135‑1142, 2016; DOI: 10.3892/or.2016.4895].

Following the publication of the above article and a corrigendum (doi: 10.3892/or.2020.7503) that was published to take account of duplications of data noted in Fig. 3 (panels 'C' and 'D') and Fig. 7 (also panels 'C' and 'D'), it has come to light that the originally published version of Fig. 7 also contained a small overlapping section of data comparing Fig. 7A with 7D. Upon receiving notification of this further issue associated with the presentation of data in Fig. 7, owing to the non‑availability of the first author who performed these experiments and the inability to identify the original data for this figure, the authors proposed removing the data from Fig. 7A‑D, and simply presenting Fig. 7E in a revised version of this figure in a subsequent corrigendum; however, the Editor of Oncology Reports requested that the authors repeat the experiments shown in Fig. 7. and submit a new and complete version of this figure for the corrigendum. The authors were agreeable to this course of action, although to date, the proposed revised version of this figure has not been received by the Editorial Office; therefore, we are now issuing an Expression of Concern statement to notify readers of the newly identified problems associated with the presentation of certain of the data in this paper. [Oncology Reports 36: 2951‑2959, 2016; DOI: 10.3892/or.2016.5077].