Cancer Science最新文献

Mutations of KRAS, CDKN2A, TP53, and SMAD4 are the four major driver genes for pancreatic ductal adenocarcinoma (PDAC), of which mutations of KRAS and TP53 are the most frequently recognized. However, molecular-targeted therapies for mutations of KRAS and TP53 have not yet been developed. To identify novel molecular targets, we newly established organoids with the Kras mutation (Kras^muOR) and Trp53 loss of function using Cre transduction and CRISPR/Cas9 (Kras^mu/p53^muOR) from murine epithelia of the pancreatic duct in Kras^LSL-G12D mice, and then analyzed the proteomic and metabolomic profiles in both organoids by mass spectrometry. Hyperfunction of the glycolysis pathway was recognized in Kras^mu/p53^muOR compared with Kras^muOR. Loss of function of triosephosphate isomerase (TPI1), which is involved in glycolysis, induced a reduction of cell proliferation in human PDAC cell lines with the TP53 mutation, but not in PDAC or in human fibroblasts without TP53 mutation. The TP53 mutation is clinically recognized in 70% of patients with PDAC. In the present study, protein expression of TPI1 and nuclear accumulation of p53 were recognized in the same patients with PDAC. TPI1 is a potential candidate therapeutic target for PDAC with the TP53 mutation.

Chromosome aberrations (CAs), a genotoxic potential of carcinogens, are believed to contribute to tumorigenesis by chromosomal rearrangements through micronucleus formation. However, there is no direct evidence that proves the involvement of CAs in tumorigenesis in vivo. In the current study, we sought to clarify the involvement of CAs in chemical carcinogenesis using a rat model with a pure CA-inducer hepatocarcinogen, acetamide. Whole-genome analysis indicated that hepatic tumors induced by acetamide treatment for 26–30 weeks showed a broad range of copy number alterations in various chromosomes. In contrast, hepatic tumors induced by a typical mutagen (diethylnitrosamine) followed by a nonmutagen (phenobarbital) did not show such mutational patterns. Additionally, structural alterations such as translocations were observed more frequently in the acetamide-induced tumors. Moreover, most of the acetamide-induced tumors expressed c-Myc and/or MDM2 protein due to the copy number gain of each oncogene. These results suggest the occurrence of chromosomal rearrangements and subsequent oncogene amplification in the acetamide-induced tumors. Taken together, the results indicate that CAs are directly involved in tumorigenesis through chromosomal rearrangements in an acetamide-induced hepatocarcinogenesis rat model.

In the colorectal cancer (CRC) niche, the transcription factors signal transducer and activator of transcription 3 (STAT3) and nuclear factor-κB (NF-κB) are hyperactivated in both malignant cells and tumor-infiltrating leukocytes (TILs) and cooperate to maintain cancer cell proliferation/survival and drive protumor inflammation. Through drug repositioning studies, the anthelmintic drug rafoxanide has recently emerged as a potent and selective antitumor molecule for different types of cancer, including CRC. Here, we investigate whether rafoxanide could negatively modulate STAT3/NF-κB and inflammation-associated CRC. The antineoplastic effect of rafoxanide was explored in a murine model of CRC resembling colitis-associated disease. Cell proliferation and/or STAT3/NF-κB activation were evaluated in colon tissues taken from mice with colitis-associated CRC, human CRC cells, and CRC patient-derived explants and organoids after treatment with rafoxanide. The STAT3/NF-κB activation and cytokine production/secretion were assessed in TILs isolated from CRC specimens and treated with rafoxanide. Finally, we investigated the effects of TIL-derived supernatants cultured with or without rafoxanide on CRC cell proliferation and STAT3/NF-κB activation. The results showed that rafoxanide restrains STAT3/NF-κB activation and inflammation-associated colon tumorigenesis in vivo without apparent effects on normal intestinal cells. Rafoxanide markedly reduces STAT3/NF-κB activation in cultured CRC cells, CRC-derived explants/organoids, and TILs. Finally, rafoxanide treatment impairs the ability of TILs to produce protumor cytokines and promote CRC cell proliferation. We report the novel observation that rafoxanide negatively affects STAT3/NF-κB oncogenic activity at multiple levels in the CRC microenvironment. Our data suggest that rafoxanide could potentially be deployed as an anticancer drug in inflammation-associated CRC.

We used a mathematical approach to investigate the quantitative spatial profile of cancer cells and stroma in lung squamous cell carcinoma tissues and its clinical relevance. The study enrolled 132 patients with 3–5 cm peripheral lung squamous cell carcinoma, resected at the National Cancer Center Hospital East. We utilized machine learning to segment cancer cells and stroma on cytokeratin AE1/3 immunohistochemistry images. Subsequently, a spatial form of Shannon's entropy was employed to precisely quantify the spatial distribution of cancer cells and stroma. This quantification index was defined as the spatial tumor–stroma distribution index (STSDI). The patients were classified as STSDI-low and -high groups for clinicopathological comparison. The STSDI showed no significant association with baseline clinicopathological features, including sex, age, pathological stage, and lymphovascular invasion. However, the STSDI-low group had significantly shorter recurrence-free survival (5-years RFS: 49.5% vs. 76.2%, p < 0.001) and disease-specific survival (5-years DSS: 53.6% vs. 81.5%, p < 0.001) than the STSDI-high group. In contrast, the application of Shannon's entropy without spatial consideration showed no correlation with patient outcomes. Moreover, low STSDI was an independent unfavorable predictor of tumor recurrence and disease-specific death (RFS; HR = 2.668, p < 0.005; DSS; HR = 3.057, p < 0.005), alongside the pathological stage. Further analysis showed a correlation between low STSDI and destructive growth patterns of cancer cells within tumors, potentially explaining the aggressive nature of STSDI-low tumors. In this study, we presented a novel approach for histological analysis of cancer tissues that revealed the prognostic significance of spatial tumor–stroma distribution in lung squamous cell carcinoma.

Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young adult populations, necessitating early diagnosis for effective treatment. This study developed a high-performance artificial intelligence (AI) model to detect osteosarcoma from X-ray images using highly accurate annotated data to improve diagnostic accuracy at initial consultations. Traditional models trained on unannotated data have shown limited success, with sensitivities of approximately 60%–70%. In contrast, our model used a data-centric approach with annotations from an experienced oncologist, achieving a sensitivity of 95.52%, specificity of 96.21%, and an area under the curve of 0.989. The model was trained using 468 X-ray images from 31 osteosarcoma cases and 378 normal knee images with a strategy to maximize diversity in the training and validation sets. It was evaluated using an independent dataset of 268 osteosarcoma and 554 normal knee images to ensure generalizability. By applying the U-net architecture and advanced image processing techniques such as renormalization and affine transformations, our AI model outperforms existing models, reducing missed diagnoses and enhancing patient outcomes by facilitating earlier treatment. This study highlights the importance of high-quality training data and advocates a shift towards data-centric AI development in medical imaging. These insights can be extended to other rare cancers and diseases, underscoring the potential of AI in transforming diagnostic processes in oncology. The integration of this AI model into clinical workflows could support physicians in early osteosarcoma detection, thereby improving diagnostic accuracy and patient care.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value. The Shapley Additive Explanations (SHAP) method was employed to investigate the key factors influencing the prediction process. Survival analysis methods were used to compare the survival rates of different treatment options. The CatBoost model yielded the best results (AUC = 0.939, sensitivity = 0.877, accuracy = 0.877). SHAP interpreters revealed that the T stage, cancer stage, age, cores positive percentage, prostate-specific antigen, and Gleason score were the most critical factors in predicting treatment options. The study found that surgery significantly improved survival rates, with patients undergoing surgery experiencing a 20.36% increase in 10-year survival rates compared with those receiving non-surgical treatments. Among surgical options, radical prostatectomy had the highest 10-year survival rate at 89.2%. This study successfully developed a predictive model to guide treatment decisions for prostate cancer. Moreover, the model enhanced the transparency of the decision-making process, providing clinicians with a reference for formulating personalized treatment plans.

Clear cell renal cell carcinoma (ccRCC) represents a highly heterogeneous kidney malignancy associated with the poorest prognosis. The metastatic potential of advanced ccRCC tumors is notably high, posing significant clinical challenges. There is an urgent imperative to develop novel therapeutic approaches to address ccRCC metastasis. Recent investigations indicated a potential association between GBP2 and tumor immunity. However, the precise functional role of GBP2 in the progression of ccRCC remains poorly understood. The present study revealed a strong correlation between GBP2 and M2 macrophages. Specifically, our findings demonstrated that the inhibition of GBP2 significantly impedes the migratory and invasive capabilities of ccRCC cells. We observed that the presence of M2 macrophages can reverse the effects of GBP2 knockdown on tumor cell migration and invasion. Mechanistically, we demonstrated that M2 macrophages promote the expression of the GBP2/p-STAT3 and p-ERK axis in tumor cells through the secretion of interleukin-10 (IL-10) and transforming growth factor-β (TGF-β), thereby substantially enhancing the migratory and invasive capacities of the tumor cells. Simultaneously, we have identified that GBP2 promotes the polarization of macrophages to the M2 phenotype by stimulating the secretion of interleukin-18 (IL-18). In summary, our investigation anticipates that the GBP2/IL-18/M2 macrophages/IL-10 and the TGF-β/GBP2, p-STAT3, p-ERK loop plays a crucial role in ccRCC metastasis. The collective findings from our research underscore the significant role of GBP2 in tumor immunity and emphasize the potential for modulating GBP2 as a promising therapeutic strategy for targeting ccRCC metastasis.

RETRACTION: D.-E Tang, Y. Dai, L.-W. Lin, Y. Xu, D.-Z. Liu, X.-P. Hong, H.-W. Jiang, and S.-H. Xu, “STUB1 Suppresseses Tumorigenesis and Chemoresistance Through Antagonizing YAP1 Signaling,” Cancer Science 110, no. 10 (2019): 3145–3156, https://doi.org/10.1111/cas.14166.

The above article, published online on 8 August 2019 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Masanori Hatakeyama; the Japanese Cancer Association; and John Wiley & Sons Australia, Ltd.

The retraction has been agreed due to concerns raised by third parties on the data presented in the article. Specifically, the article shows results from two unknown/unverifiable cell lines, BSG-823 and BGC-803. The corresponding author acknowledged that both cell lines may correspond to the cell line BGC-823 and stated that a typographical mistake was made by the provider in labeling the samples. However, these cell lines have been used as distinct and independent, raising severe concerns on the overall accuracy of the full body of data; the authors failed to comply to our request to provide raw data. Finally, several cell lines used in this study have been reported as problematic (SGC-7901,^{1, 2} MGC-803,^{3, 4} and MKN-28⁵). For these reasons, the editors no longer have trust in the reliability of the data and consider the conclusions of this article to be invalid. The authors have been informed of the decision of retraction. Authors Yong Dai and Haowu Jiang state that they did not directly participate in the experiments conducted for the study and were unaware of its submission; they agree with the decision of retraction considering the detected issues. The corresponding author Song-Hui Xu states that all authors have been duly informed of the submission of the article and agrees with the decision of retraction. The remaining co-authors were unavailable for a final confirmation.

Cancer cells show a dynamic metabolic landscape, requiring a sufficient supply of nucleotides to proliferate. They are highly dependent on de novo purine biosynthetic pathways for their nucleotide requirements. Phosphoribosyl pyrophosphate amidotransferase (PPAT), catalyzing the first step of de novo purine biosynthesis, is highly expressed in various cancers. We observed an increased expression of PPAT in nasopharyngeal carcinoma (NPC). Moreover, our ribonucleic acid sequencing analysis showed high PPAT expression in Epstein–Barr virus-positive NPC, which was supported by in vitro analysis. Through a gene knockdown study, we showed that the suppression of PPAT expression reduced the proliferation and invasion of NPC cells. We also demonstrated the regulation of PPAT by glutamine, a cosubstrate for PPAT. A glutamine antagonist, 6-diazo-5-oxo-L-norleucine, blocked glutamine-mediated induction of PPAT and reduced NPC cell proliferation. Immunohistochemical analysis of PPAT in NPC tissues revealed increased expression of PPAT with disease progression, which was significantly associated with poor prognosis. In summary, this study highlighted the biological function of PPAT in NPC, establishing its potential as a novel prognostic biomarker for aggressive NPC and a promising therapeutic target.

Plasma levels of oncofetal chondroitin sulfate (ofCS)-modified CD44 have emerged as a promising biomarker for multi-cancer detection. Here, we explored its potential to predict the survival of patients with lung cancer. A prospective observational cohort was conducted involving 274 newly diagnosed patients with lung cancer at the Sun Yat-sen University Cancer Center from 2013 to 2015. The plasma levels of ofCS-modified CD44 were measured, and Cox regression analysis was performed to assess the association between plasma-modified CD44 levels and overall survival (OS) as well as other prognostic outcomes. Prognostic nomograms were constructed based on plasma ofCS-modified CD44 levels to predict survival outcomes for patients with lung cancer. Patients with high expression ofCS-modified CD44 exhibited significantly worse outcomes in terms of OS (HR = 1.61, 95%CI = 1.13–2.29, p = 0.009) and progression-free survival (PFS). These findings were consistent across various analyses. The concordance index of the prognostic nomogram for predicting OS in both the training set and validation set were 0.723 and 0.737, respectively. Additionally, time-dependent receiver operating characteristic (ROC) curves showed that the nomogram could serve as a useful tool for predicting OS in patients with lung cancer. Plasma ofCS-modified CD44 may serve as an independent prognosis marker for patients with lung cancer. Further validation of its predictive value could enhance prognostic assessment and guide personalized treatment strategies for patients with lung cancer.