Journal of Cancer Research and Clinical Oncology最新文献

Purpose

To investigate circulating tumor DNA (ctDNA) RAS mutant (MT) incidence before salvage-line treatment and the clinicopathological features and molecular biological factors associated with the efficacy of anti-epithelial growth factor receptor (EGFR) monoclonal antibody (mAb) rechallenge for tissue RAS/BRAF wild type (WT) metastatic colorectal cancer (mCRC).

Methods

This multi-institutional retrospective observational study included 74 patients with mCRC with tissue RAS/BRAF WT refractory to first-line chemotherapy containing anti-EGFR mAb. ctDNA RAS status was assessed using the OncoBEAM™ RAS CRC Kit. We explored the clinicopathological features associated with ctDNA RAS status and the factors related to anti-EGFR mAb rechallenge efficacy in multivariate Cox proportional hazard regression.

Results

The incidence of RAS MT in ctDNA was 40.5% (30/74), which was associated with primary tumor resection (P = 0.016), liver metastasis (P < 0.001), and high tumor marker levels (P < 0.001). Among the 39 patients treated with anti-EGFR mAb rechallenge, those with ctDNA RAS WT showed significantly longer progression-free survival (PFS) than those with ctDNA RAS MT (median 4.1 vs. 2.7 months, hazard ratio [HR] = 0.39, P = 0.045). Patients who responded to first-line anti-EGFR mAb showed significantly longer PFS (HR = 0.21, P = 0.0026) and overall survival (OS) (HR = 0.23, P = 0.026) than those with stable disease.

Conclusions

The incidence of ctDNA RAS MT mCRC was 40.5%, which was associated with liver metastases and high tumor volumes. Anti-EGFR mAb rechallenge may be effective for patients with mCRC who responded to first-line chemotherapy containing anti-EGFR mAb. No patients with RAS MT in ctDNA responded to anti-EGFR mAb rechallenge.

Purpose: Kinase interacting with stathmin (KIS) is a serine/threonine kinase involved in RNA processing and protein phosphorylation. Increasing evidence has suggested its involvement in cancer progression. The aim of this study was to investigate the role of KIS in the development of lung adenocarcinoma (LUAD). Dual luciferase assay was used to explore the relationship between KIS and SOX4, and its effect on ID1/β-catenin pathway.

Methods: Real-time qPCR and western blot were used to assess the levels of KIS and other factors. Cell proliferation, migration, and invasion were monitored, and xenograft animal model were established to investigate the biological functions of KIS in vitro and in vivo.

Results: In the present study, KIS was found to be highly expressed in LUAD tissues and cell lines. KIS accelerated the proliferative, migratory and invasive abilities of LUAD cells in vitro, and promoted the growth of LUAD in a mouse tumor xenograft model in vivo. Mechanistically, KIS activated the β-catenin signaling pathway by modulating the inhibitor of DNA binding 1 (ID1) and was transcriptionally regulated by SOX4 in LUAD cells.

Conclusion: KIS, a target of SOX4, regulates the ID1-mediated enhancement of β-catenin to facilitate LUAD cell invasion and metastasis.

Purpose: Signet ring cell carcinoma (SRCC) is a rare type of lung cancer. The conventional survival nomogram used to predict lung cancer performs poorly for SRCC. Therefore, a novel nomogram specifically for studying SRCC is highly required.

Methods: Baseline characteristics of lung signet ring cell carcinoma were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression and random forest analysis were performed on the training group data, respectively. Subsequently, we compared results from these two types of analyses. A nomogram model was developed to predict 1-year, 3-year, and 5-year overall survival (OS) for patients, and receiver operating characteristic (ROC) curves and calibration curves were used to assess the prediction accuracy. Decision curve analysis (DCA) was used to assess the clinical applicability of the proposed model. For treatment modalities, Kaplan-Meier curves were adopted to analyze condition-specific effects.

Results: We obtained 731 patients diagnosed with lung signet ring cell carcinoma (LSRCC) in the SEER database and randomized the patients into a training group (551) and a validation group (220) with a ratio of 7:3. Eight factors including age, primary site, T, N, and M.Stage, surgery, chemotherapy, and radiation were included in the nomogram analysis. Results suggested that treatment methods (like surgery, chemotherapy, and radiation) and T-Stage factors had significant prognostic effects. The results of ROC curves, calibration curves, and DCA in the training and validation groups demonstrated that the nomogram we constructed could precisely predict survival and prognosis in LSRCC patients. Through deep verification, we found the constructed model had a high C-index, indicating that the model had a strong predictive power. Further, we found that all surgical interventions had good effects on OS and cancer-specific survival (CSS). The survival curves showed a relatively favorable prognosis for T0 patients overall, regardless of the treatment modality.

Conclusions: Our nomogram is demonstrated to be clinically beneficial for the prognosis of LSRCC patients. The surgical intervention was successful regardless of the tumor stage, and the Cox proportional hazard (CPH) model had better performance than the machine learning model in terms of effectiveness.

Background: Currently, there is a lack of effective indicators for predicting the efficacy of immunotherapy in patients with advanced hepatocellular carcinoma (HCC). This study aimed to investigate the expression and prognostic value of peripheral T lymphocyte subsets in advanced HCC.

Methods: Patients with advanced HCC who were treated with immune checkpoint inhibitors (ICIs) from December 2021 to December 2023 were included in the study. Flow cytometry was used to detect lymphocyte subsets before treatment. The patients were divided into disease control (DC) and nondisease control (nDC) groups based on treatment efficacy. Relationships between the clinical characteristics/peripheral T lymphocytes and immunotherapy efficacy were analyzed. The effectiveness of peripheral T lymphocyte subsets in predicting immunotherapy efficacy for patients with advanced HCC was analyzed using receiver operating characteristic (ROC) curves.

Results: A total of 40 eligible patients were included in this study. Non-DC was significantly associated with higher albumin-bilirubin (ALBI) scores. The percentages of γδ⁺Vδ2⁺PD1⁺ T cells and γδ⁺Vδ2⁺Tim3⁺ T cells were greater in the nDC group than in the DC group. Multivariable regression analysis revealed that the ALBI score and T lymphocytes expressing γδ⁺Vδ2⁺PD1⁺ and γδ⁺Vδ2⁺Tim3⁺ were founded to be independent influencing factors. The area under the ROC curve (AUC) values for these combinations was 0.944 (95% CI, 0.882 ~ 1.000).

Conclusions: The calculation of the ALBI score and determination of the percentages CD3⁺γδ⁺Vδ2⁺PD1⁺ T lymphocytes and CD3⁺γδ⁺Vδ2⁺Tim3⁺ T lymphocytes in the peripheral blood of patients with advanced HCC are helpful for predicting the patients' responses to ICIs, helping to screen patients who may clinically benefit from immunotherapy. RETROSPECTIVELY REGISTERED: number: ChiCTR2400080409, date of registration: 2024-01-29.

This study presents a robust approach for the classification of ovarian cancer subtypes through the integration of deep learning and k-nearest neighbor (KNN) methods. The proposed model leverages the powerful feature extraction capabilities of EfficientNet-B0, utilizing its deep features for subsequent fine-grained classification using the fine-KNN approach. The UBC-OCEAN dataset, encompassing histopathological images of five distinct ovarian cancer subtypes, namely, high-grade serous carcinoma (HGSC), clear-cell ovarian carcinoma (CC), endometrioid carcinoma (EC), low-grade serous carcinoma (LGSC), and mucinous carcinoma (MC), served as the foundation for our investigation. With a dataset comprising 725 images, divided into 80% for training and 20% for testing, our model exhibits exceptional performance. Both the validation and testing phases achieved 100% accuracy, underscoring the efficacy of the proposed methodology. In addition, the area under the curve (AUC), a key metric for evaluating the model's discriminative ability, demonstrated high performance across various subtypes, with AUC values of 0.94, 0.78, 0.69, 0.92, and 0.94 for MC. Furthermore, the positive likelihood ratios (LR⁺) were indicative of the model's diagnostic utility, with notable values for each subtype: CC (27.294), EC (9.441), HGSC (12.588), LGSC (17.942), and MC (17.942). These findings demonstrate the effectiveness of the model in distinguishing between ovarian cancer subtypes, positioning it as a promising tool for diagnostic applications. The demonstrated accuracy, AUC values, and LR⁺ values underscore the potential of the model as a valuable diagnostic tool, contributing to the advancement of precision medicine in the field of ovarian cancer research.

Aim: Endometrial cancer (EC) is heterogeneous with respect to epidemiology, clinical course, histopathology and tumor biology. Recently, The Cancer Genome Atlas (TCGA) network has identified four molecular subtypes with distinct clinical courses by an integrated multi-omics approach. These subtypes are of critical importance in the clinical management of EC. However, determination of TCGA molecular subtypes requires a complex methodological approach that is resource intensive and difficult to implement in diagnostic routine procedures. In this context, Talhouk et al. reported the precise determination of modified subtypes based on molecular surrogates obtained by a two-method approach comprising immunohistochemistry and DNA-sequence analysis (Proactive Molecular Risk Classifier for Endometrial Cancer; ProMisE). In this study, we aimed to identify EC molecular subtypes in analogy to TCGA and ProMisE applying an innovative whole exome-sequencing (WES) based single-method approach.

Methods: WES was performed in a cohort comprising N = 114 EC patients. WES data were analyzed using the oncology treatment decision support software MH Guide (Molecular Health, Heidelberg, Germany) and EC molecular subtypes in analogy to TCGA and ProMisE were determined. Results from both classifications were compared regarding their prognostic values using overall survival and progression-free survival analyses.

Results: Applying a single-method WES-approach, EC molecular subtypes analogue to TCGA and ProMisE were identified in the study cohort. The surrogate marker-analogue classification precisely identified high-risk and low-risk EC, whereas the TCGA-analogue classification failed to obtain significant prognostic values in this regard.

Conclusion: Our data demonstrate that determination of EC molecular subtypes analogue to TCGA and ProMisE is feasible by using a single-method WES approach. Within our EC cohort, prognostic implications were only reliably provided by applying the surrogate marker-analogue approach. Designation of molecular subtypes in EC will be increasingly important in routine clinical practice. Thus, the single-method WES approach provides an important simple tool to tailor therapeutic decisions in EC.

Background: Skin Cutaneous Melanoma (SKCM) is a highly aggressive malignant tumor with a significant increase in mortality upon metastasis. The molecular mechanisms driving melanoma progression remain largely unclear. Recent studies have highlighted the importance of epigenetic alterations, especially DNA methylation, in melanoma development. This study aims to identify and analyze methylation-regulated differentially expressed genes (MeDEGs) in genome-wide profiles between primary and metastatic melanoma.

Methods: Gene expression profiling datasets GSE8401 and gene methylation profiling datasets GSE86355 were collected from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were systematically identified. Integration of DEGs and DMGs yielded a set of MeDEGs, which subsequently underwent functional enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Survival analysis was used to select prognostic hub genes. In addition, 37 SKCM and 37 normal skin tissues from the First Affiliated Hospital of Soochow University (FAHSU) were collected for immunohistochemical (IHC) staining and evaluation. Furthermore, DNA methylation patterns of CDC6 were analyzed. To validate these findings, SKCM cell cultures were utilized to elucidate the expression and behavioral characteristics of CDC6. Additionally, gene set enrichment analysis (GSEA) and immune infiltration analysis were conducted for CDC6.

Results: In our study, we discovered 120 hypomethylated-upregulated genes and 212 hypermethylated-downregulated genes. The hypomethylated-upregulated genes were notably associated with biological processes such as spindle assembly checkpoint signaling, mitotic spindle assembly, and negative regulation of mitotic metaphase/anaphase transition. Our pathway analysis revealed significant enrichment in pathways related to dilated cardiomyopathy, amino sugar metabolism, progesterone-mediated oocyte maturation, and chemical carcinogenesis. Conversely, hypermethylated-downregulated genes were found to be enriched in processes like epidermis development, keratinocyte differentiation, and skin development. Additionally, pathway analysis highlighted associations with estrogen signaling, Staphylococcus aureus infection, axon guidance, and arachidonic acid metabolism. Following the establishment of PPI networks and survival analysis, we identified 11 prognostic hub genes: CCNA2, CDC6, CDCA3, CKS2, DTL, HJURP, KRT5, KRT14, KRT15, KRT16, and NEK2. Notably, among the 11 hub genes, our findings indicate that CDC6 plays a pivotal role in enhancing the proliferation, migration, and invasion capabilities of melanoma cells in vitro.

Conclusions: Our comprehensive genomic analyses reveal that genes with aberrant methylation exhibit differential expression during the transitio

Purpose: IKAROS family zinc finger 3 (IKZF3) is an oncogene involved in different malignancies, particularly in the development and malignant progression of lymphocytes. However, IKZF3 amplification and clinical significance in gastric cancers (GCs) remain unexplored.

Methods: We examined IKZF3 amplification status in 404 GCs with HER2 amplification status using tissue microarray (TMA) and fluorescence in situ hybridization (FISH) assays.

Results: IKZF3 amplification was detected in 6.9% (28/404) of all GC patients, with higher rates in intestinal-type gastric cancer (IGC) (11.22%, 22/196) compared to other types (2.88%, 6/208). HER2 amplification was identified in 16.09% (65/404) of all GC patients, with higher rates in IGC (20.92%, 41/196) compared to other types (11.54%, 24/208). Co-amplification of IKZF3 and HER2 was detected in 8.16% (16/196) of IGC patients and in 2.40% (5/208) of other types. IKZF3 amplification showed significant correlation with IGC (P = 0.001) and HER2 amplification (P = 0.0001). IKZF3 amplification exhibited significantly worse disease-free survival (DFS) (P = 0.014) and overall survival (OS) (P = 0.018) in GC patients, particularly in IGC (DFS: P < 0.001; OS: P < 0.001), rather than other types. Cox regression analysis demonstrate IKZF3 amplification as an independent poor prognostic factor in all GCs (P = 0.006, P = 0.004 respectively) and in IGC patients, regardless of stages I-II or III-IV (P = 0.007, P = 0.004 respectively). On the other hand, HER2 amplification was significantly associated with worse DFS (P = 0.008) and OS (P = 0.01) in IGC patients, but not in all GCs and in multivariate analysis. Within the subset of patients with HER2 amplification, those also exhibiting IKZF3 amplification displayed potential poorer prognosis (P = 0.08, P = 0.11 respectively).

Conclusion: IKZF3 amplification was detected in minority of GC patients, especially in IGC, and was an independent indicator of poor prognosis. Our study, for the first time, found the prognostic value of IKZF3 was superior to HER2 for GC patients.

Purpose: This systematic review aims to investigate the role of nuclear imaging techniques in detecting incidentalomas and their impact on patient management.

Methods: Following PRISMA guidelines, a comprehensive literature search was conducted from February to May 2022. Studies in English involving patients undergoing nuclear medicine studies with incidental tumor findings were included. Data on imaging modalities, incidentaloma characteristics, management changes, and follow-up were extracted and analyzed.

Results: Ninety-two studies involving 64.884 patients were included. Incidentalomas were detected in 611 cases (0.9%), with thyroid being the most common site. PET/CT with FDG and choline tracers showed the highest incidentaloma detection rates. Detection of incidentalomas led to a change in therapeutic strategy in 59% of cases. Various radiotracers demonstrated high sensitivity for incidentaloma detection, particularly in neuroendocrine tumors and prostate cancer.

Conclusion: Nuclear imaging techniques play a crucial role in detecting incidentalomas, leading to significant changes in patient management. The high sensitivity of these modalities highlights their potential in routine oncology follow-up protocols. Future directions may include enhancing spatial resolution and promoting theranostic approaches for improved patient care.

Purpose: The Minimal Documentation System (MIDOS2) is recommended as a systematic screening tool for assessing symptom burden and patient needs in advanced cancer patients. Given the absence of an optimal weighting of individual symptoms and a corresponding cut-off value, this study aims to determine a threshold based on inpatient's subjective need for palliative support. Additionally, we investigate the correlation between symptom burden and subjective need for palliative support collected through a patient-reported outcome measure (PROM) with survival duration of less or more than one year.

Methods: Inpatients diagnosed with advanced solid cancer completed an electronic PROM, which included the MIDOS2 questionnaire among other tools. Differences in symptom burden were analysed between patients expressing subjective need for palliative support and those with survival of less or more than one year using ANOVA, Mann-Whitney-U Test, logistic regression, Pearson and Spearman correlation tests. Cut-off analyses were performed using a ROC curve. Youden-Index, sensitivity, and specificity measures were used as well.

Results: Between April 2020 and March 2021, 265 inpatients were included in the study. Using a ROC curve, the MIDOS2 analysis resulted in an Area under the curve (AUC) of 0.732, a corresponding cut-off value of eight points, a sensitivity of 76.36% and a specificity of 62.98% in assessing the subjective need for palliative support. The MIDOS2, with double weighting of the significant symptoms, showed a cut-off value of 14 points, achieving a sensitivity of 78.18% and a specificity of 72.38%. A total of 55 patients (20.8%) expressed a need for support from the palliative care team. This need was independent of the oncological tumour entity and increased among patients with a survival of less than one year. These patients reported significantly poorer physical (p < 0.001) or mental (p < 0.001) condition. Additionally, they reported higher intensities of pain (p = 0.002), depressive symptoms (p < 0.001), weakness (p < 0.001), anxiety (p < 0.001), and tiredness (p < 0.001).

Conclusion: Using the established MIDOS2 cut-off value with an adjusted double weighting in our study, a large proportion of inpatients may be accurately referred to SPC based on their subjective need for palliative support. Additionally, subjective reports of poor general, mental, and physical condition, as well as pain, depressive symptoms, weakness, anxiety, and tiredness, increase the subjective need for palliative support, particularly in patients with a survival prognosis of less than one year.