Oncology最新文献

Introduction: Immune checkpoint inhibitors provide new treatments for patients with recurrent or metastatic (R/M) head and neck cancers. Herein, we focused on systemic inflammatory markers in peripheral blood, including blood cell fractions, albumin (Alb), and C-reactive protein, and determined their association with nivolumab treatment response. We also examined the potential application of inflammatory markers as prognostic tools.

Methods: We assessed pretreatment systemic inflammatory markers in 61 patients with R/M head and neck cancer treated with nivolumab, determining their association with treatment response using Kaplan-Meier, multivariate, and regression analyses. Using flow cytometry, we investigated circulating T-cell subsets in 36 patients with R/M head and neck cancer. Finally, we examined the correlation between each statistically analyzed parameter and peripheral circulating T-cell activation.

Results: Systemic inflammatory marker values were used to estimate overall survival (OS) time by performing multivariate analysis. Systemic inflammatory markers were assigned importance for each coefficient. Monocyte and lymphocyte counts strongly impacted OS. Indices dependent on white blood cell and monocyte counts, lymphocyte percentage, platelet count, Alb levels, and prognostic nutrition index were useful prognostic tools in the regression analysis. The simplest prognostic index was defined as white blood cells (103/μL) +2 × lymphocyte percentage (%) +12 × number of monocytes (103/μL) + 27 × serum Alb. A high index that was significantly associated with a better prognosis negatively correlated with CD38/CD8 and ki67/CD8 percentages.

Conclusions: According to the findings of the present study, systemic inflammatory markers may help predict the prognosis, activation, and exhaustion of circulating T cells. In patients with R/M head and neck cancer treated with nivolumab, systemic inflammatory markers could provide new insights into rational strategies in cancer immunotherapy for R/M head and neck cancer.

Introduction: A higher body mass index (BMI) has been associated with a better response and overall survival in patients with lung cancer or melanoma receiving immune checkpoint inhibitors (ICIs). Pembrolizumab has been approved for the use of breast cancer, but its relationship with BMI on survival outcomes is unclear.

Methods: We conducted a retrospective, propensity score-matched cohort study using the TriNetX Analytics Network database, which contains de-identified data from over 120 participating healthcare institutions. We included all adult female patients with breast cancer who received pembrolizumab. We excluded patients who were prescribed endocrine or human epidermal growth factor receptor 2-targeted therapies. We compared the 1-year all-cause mortality between patients who were overweight or obese (BMI ≥25 kg/m2) and those who were normal weight (BMI <25 kg/m2). We matched patients on predetermined variables including age, race, breast cancer-directed therapy, cardiovascular and diabetes medications, and underlying comorbidities.

Results: We identified 1,628 eligible patients, of whom 1,163 had a BMI ≥25 kg/m2 and 465 had a BMI <25 kg/m2. After propensity score matching, 410 patients in each cohort were well balanced for demographics, breast cancer-directed therapy, and underlying comorbidities. The mean ages for patients with BMI ≥25 kg/m2 and BMI <25 kg/m2 were 56.7 ± 14.0 and 56.9 ± 15.0, respectively. Over a median follow-up of 1 year, 28 and 53 patients died in the BMI ≥25 kg/m2 and BMI <25 kg/m2 cohorts, respectively. Patients with BMI ≥25 kg/m2 had a 49% lower risk of all-cause mortality compared with those with BMI <25 kg/m2 (hazard ratio, 0.51 [95% CI: 0.33-0.81]).

Conclusions: A BMI ≥25 kg/m2 was associated with a lower all-cause mortality among breast cancer patients receiving pembrolizumab.

Introduction: Durvalumab plus tremelimumab combination therapy (STRIDE regimen) is a new first-line option for unresectable hepatocellular carcinoma (uHCC), but little real-world data are available to determine which patients are most likely to respond.

Methods: This study retrospectively evaluated patients with uHCC who were treated with the STRIDE regimen as the 1st line at our hospital. The primary endpoint of the study was the objective response rate (ORR). We focused on identifying factors associated with cases that had a favorable response.

Results: Twenty-one patients were included. In best response, there were 11 partial response cases, with an ORR of 52.4%. Median progression-free survival was 6.8 months, and overall survival did not reach the median time. A high tumor-to-liver ratio of the maximum value of the standardized uptake value (TLR) on baseline fluorodeoxyglucose positron emission tomography (FDG-PET) was associated with response, while TLRs were significantly higher in poorly differentiated uHCC.

Conclusion: The STRIDE regimen may be beneficial for systemic therapy-naive uHCC patients. High TLR on baseline FDG-PET could be a potentially useful biomarker for response.

Introduction: This study aims to evaluate the likelihood of developing a second primary ovarian cancer (OC) considering factors including age, race, and the types of initial malignancies encountered.

Methods: This study employed a retrospective cohort approach, compiling data on individuals diagnosed with OC from the Surveillance, Epidemiology, and End Results (SEER) program databases spanning the years 1975-2019. The analysis used standardized incidence ratios (SIRs) with 95% confidence intervals (CIs) to determine the likelihood of developing OC. The result was further refined by categorizing the data based on patient age, race background, first primary cancer types, the time elapsed since the second primary cancer diagnosis, and radiotherapy treatment.

Results: A total of 1,536,151 patients with second primary cancer being OC were included. The SIR of the second primary OC was observed to be elevated among patients between the ages of 18-64 years (SIR: 1.09, 95% CI: 1.06-1.13). In contrast, for patients who were 65 years of age or older, the SIR for a second primary OC was found to be relatively lower (SIR: 0.87, 95% CI: 0.83-0.91). A lowering, however, not statistically significant, of the SIR of the second primary OC in patients with white race was presented. Within 2 months to 1-year diagnosis interval, the SIR of the second primary OC was highest (SIR: 1.48, 95% CI: 1.37-1.61). Liver, gallbladder, intrahepatic, and other bile ducts (SIR: 2.00, 95% CI: 1.38-2.81), and breast cancer (SIR: 1.20, 95% CI: 1.15-1.25) had higher SIRs of second primary OC.

Conclusion: This study identifies age, ethnicity, the time span between the diagnoses, and the types of initial cancers as factors correlated with the occurrence of a second primary OC. Our findings suggest that targeted surveillance should be considered for high-risk groups.

Introduction: Establishment of sister chromatid cohesion N-acetyltransferase 2 (ESCO2), a member of the EFO2 family, is implicated in the pathogenesis and progression of various cancers. However, there has been limited comprehensive pan-cancer analysis conducted on ESCO2 thus far.

Methods: Publicly available databases, such as the UCSC Xena database, were utilized to examine differential expression patterns across various cancer types. In addition, variations in expression levels were investigated across distinct clinical stages. Univariate Cox regression and Kaplan-Meier survival analyses were conducted to evaluate the impact on overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) at the pan-cancer level. The correlation between ESCO2 expression and immune cell infiltration was examined to gain insight into the tumor microenvironment (TME) in different cancers. The results of the bioinformatic analysis were validated using immunotherapy clinical trials and pathological specimens. CCK-8 and Transwell assay experiments were performed to investigate the biological function of ESCO2.

Results: ESCO2 expression was found to be upregulated in most cancers, with a correlation to TNM stages. Prognostic analysis indicated that overexpression of ESCO2 was associated with poor prognosis in various cancers. Furthermore, the correlation between ESCO2 expression and immune cell infiltration suggested its potential as a predictor for immunotherapy efficacy. Notably, ESCO2 expression showed positive associations with immunoinhibitor, immunostimulator, major histocompatibility complex (MHC) molecule, chemokine receptor, tumor mutation burden (TMB), and microsatellite instability (MSI) levels in bladder cancer (BLCA). The validation cohort for immunotherapy corroborated these findings and substantiated that ESCO2 could function as an autonomous prognostic biomarker and a promising target for cancer treatment via immunotherapy. In addition, in vitro experiments confirmed the role of ESCO2 in influencing the proliferation, invasion, and migration of BLCA cells.

Conclusion: ESCO2 participates in regulating the immune infiltration and affecting the prognosis of patients in many cancers, especially in BLCA. ESCO2 may serve as a prognostic and immunotherapy biomarker in future treatment of human cancer.

Introduction: Transforming acidic coiled-coil containing protein 3 (TACC3) exerts a vital role in cancer progression by modulating cell division and facilitating tumor growth. Given the lack of comprehensive research on the pancancer implications of TACC3, our study aimed to analyze the functional role of TACC3 in pancancer and validate it through experimental investigations in lung adenocarcinoma.

Methods: We first employed various bioinformatics techniques to investigate the expression and prognostic significance of TACC3 in pancancer. Subsequently, we analyzed the correlation between TACC3 and immune infiltration, immune checkpoints, drug sensitivity, as well as the prediction of immune therapy response. Finally, we validated the association between TACC3 and the proliferation of lung adenocarcinoma, as well as its resistance to docetaxel, through in vitro experiments.

Results: Here, TACC3 exhibited high expression in human cancers and was associated with poor prognosis in various cancer types. It was also involved in immune infiltration and demonstrated a strong predictive ability for immune therapy response. Through drug sensitivity prediction, we further identified a potential association between TACC3 and docetaxel resistance, which was subsequently validated in lung adenocarcinoma.

Conclusion: Our investigation of TACC3 revealed its potential as a promising target both for immunosuppression and docetaxel resistance in pancancer, especially in lung adenocarcinoma.

Introduction: The clinicopathological characteristics and efficacy of perioperative treatment of Epstein-Barr virus-associated gastric cancer (EBVaGC) were investigated.

Methods: The clinicopathological characteristics and perioperative treatment outcomes of patients with EBVaGC who underwent radical gastrectomy in Tianjin Medical University Cancer Hospital from September 2016 to May 2022 were retrospectively reviewed. Disease-free survival (DFS) was analyzed, and Cox regression analysis was performed to identify risk factors.

Results: The study cohort included 128 patients with EBVaGC. Histologically, 126 (98.4%) patients had adenocarcinoma and only 2 (1.6%) had adenosquamous carcinoma. In addition, 18 (14.1%) had nerve invasion and 29 (22.7%) had vascular invasion. Notably, 41 (32.0%) patients had tumors in the proximal stomach and 69 (53.9%) had no lymph node metastasis. Proficient mismatch repair was confirmed in all 104 patients with available results. Overall, 16 (12.5%) patients received neoadjuvant therapy, 81 (63.3%) received adjuvant therapy, and 10 (7.8%) received perioperative immunotherapy combined with chemotherapy. In total, 22 patients experienced disease progression or had died. The 3-year DFS rate was 75.0%. DFS was relatively poorer for patients with advanced tumor (T) stage, lymph node (N) stage, disease stage, and vascular invasion.

Conclusion: EBVaGC had unique clinicopathological characteristics and prognosis. Advanced T, N, and disease stages, in addition to vascular invasion, were predictive of poorer DFS. However, the efficacy of perioperative treatment of EBVaGC remains uncertain.

Introduction: Patients with advanced-stage or intermediate-stage hepatocellular carcinoma (HCC) unsuitable for transarterial chemoembolization (TACE) had poor prognoses. Recent advancements in hepatic arterial infusion chemotherapy (HAIC) and immune checkpoint inhibitors (ICIs) have demonstrated higher tumor response rates, which improved overall survival (OS). HAIC achieves an OS rate of approximately 14.5-15.3 months with a 39.1-42.5% tumor response rate. In comparison, ICIs have a 12-14 month OS rate with a 26-33% tumor response rate. Given these promising responses, this study evaluates the efficacy of conversion therapy with curative intent following HAIC or ICIs, focusing on survival outcomes.

Methods: We retrospectively analyzed 80 patients with advanced or TACE-unsuitable intermediate HCC. Patients completed two HAIC or four ICI cycles, followed by Response Evaluation Criteria in Solid Tumors (RECIST) criteria imaging. Based on demographics, cirrhosis status, Barcelona Clinic Liver Cancer classification (BCLC) stage, treatment responses, and treatment modality, survival impacts were analyzed. OS was compared between HAIC and immunotherapy groups. The effect of conversion therapy with curative intent on survival outcomes was analyzed using a Cox regression model.

Results: Among the 80 patients, 26 achieved positive response (CR/PR) with HAIC or ICIs, and 9 of them subsequently underwent conversion therapy with curative intent. Key prognostic factors included Child-Pugh stage B versus A (HR = 2.21, p = 0.041), BCLC stage C versus B (HR = 4.38, p = 0.011), and elevated alpha-fetoprotein levels (HR = 5.02, p < 0.001). Positive responders saw substantial survival benefits (HR = 0.26, p = 0.001). Patients undergoing conversion therapy exhibited significantly enhanced survival. Median OS was 13.58 months with standard therapy, while the curative intent surgery group did not reach the median OS (p = 0.002). For CR/PR patients, 48-month survival was 75.0% for the curative surgery group versus 38.0% for standard treatment.

Conclusion: Conversion therapy with curative intent following HAIC or ICIs might enhance survival in patients with advanced or TACE-unsuitable intermediate-stage HCC.

Introduction: This multicenter study aimed to determine whether the pretreatment prognostic nutrition index (PNI) or a change in the index after two treatment courses could be a biomarker for predicting treatment sensitivity in patients with unresectable advanced or recurrent gastric cancer treated using chemotherapy and nivolumab as the first-line treatment.

Methods: This multicenter retrospective study with 104 patients was conducted at 12 institutions. PNI was calculated before treatment and after two courses of treatment in each case. We also focused on changes in PNI from the pretreatment value.

Results: After two courses of chemotherapy plus nivolumab treatment, the high PNI group had significantly better rates of overall survival (OS) (p = 0.0016) and time-to-treatment failure (p = 0.0060). Low PNI was an independent prognostic factor predicting both therapeutic sensitivity to chemotherapy plus nivolumab treatment and poorer OS. Furthermore, correlation with low pretreatment PNI transitioning to high after two courses of treatment was not noted in any patient in the progressive disease group (p = 0.0075).

Conclusions: PNI is a score composed of a patient's albumin level and lymphocyte count that can be easily assessed in daily clinical practice. Evaluating it is easy for each treatment; thus, when there is a focus on its transition, PNI could be a very powerful biomarker for predicting treatment sensitivity.

Introduction: The integration of artificial intelligence (AI) into orthopedics has enhanced the diagnosis of various conditions; however, its use in diagnosing soft-tissue tumors remains limited owing to its complexity. This study aimed to develop and assess an AI-driven diagnostic support system for magnetic resonance imaging (MRI)-based soft-tissue tumor diagnosis, potentially improving accuracy and aiding radiologists and orthopedic surgeons.

Methods: An experienced orthopedic oncologist and radiologist annotated 720 images from 77 cases (41 benign and 36 malignant soft-tissue tumors). Eleven tumor subtypes were identified and classified into benign and malignant groups based on histological diagnosis. Utilizing the standard machine learning classifier pipeline, we examined and down-selected imaging protocols and their predominant radiomic features within the tumor's three-dimensional region to differentiate between benign and malignant tumors. Among the scan protocols, contrast-enhanced T1-weighted fat-suppressed images showed the most accurate classification based on radiomic features. We focused on the two-dimensional features from the largest tumor boundary surface and its neighboring slices, leveraging texture-based radiomic and deep convolutional neural network features from a pretrained VGG19 model.

Results: The test data comprised 44 contrast-enhanced images (22 benign and 22 malignant soft-tissue tumors) containing six malignant and five benign subtypes distinct from the training data. We compared expert and nonexpert human performances against AI by assessing malignancy detection and the time required for classification. The AI model showed comparable accuracy (AUC 0.91) to that of radiologists (AUC 0.83) and orthopedic surgeons (AUC 0.73). Notably, the AI model processed data approximately 400 times faster than its human counterparts, showcasing its capacity to significantly boost diagnostic efficiency.

Conclusion: We developed an AI-driven diagnostic support system for MRI-based soft-tissue tumor diagnosis. While additional refinement is necessary for clinical applications, our system has exhibited promising potential in differentiating between benign and malignant soft-tissue tumors based on MRI.