Annals of Surgical Oncology最新文献

Main objectives: We aimed at comparing intratumoral and peritumoral deep learning, radiomics, and fusion models in predicting KRAS mutations in rectal cancer using endorectal ultrasound imaging.

Methods: This study included 304 patients with rectal cancer from Fujian Medical University Union Hospital. The patients were randomly divided into a training group (213 patients) and a test group (91 patients) at a 7:3 ratio. Radiomics and deep learning models were established using primary tumor and peritumoral images. In the optimally performing regions-of-interest, two fusion strategies, a feature-based and a decision-based model, were employed to build the fusion models. The Shapley additive explanation (SHAP) method was used to evaluate the significance of features in the optimal radiomics, deep learning, and fusion models. The performance of each model was assessed using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

Results: In the test cohort, both the radiomics and deep learning models exhibited optimal performance with a 10-pixel patch extension, yielding AUC values of 0.824 and 0.856, respectively. The feature-based DLRexpand10_FB model attained the highest AUC (0.896) across all study sets. In addition, the DLRexpand10_FB model demonstrated excellent sensitivity, specificity, and DCA. SHAP analysis underscored the deep learning feature (DL_1) as the most significant factor in the hybrid model.

Conclusion: The feature-based fusion model DLRexpand10_FB can be employed to predict KRAS gene mutations based on pretreatment endorectal ultrasound images of rectal cancer. The integration of peritumoral regions enhanced the predictive performance of both the radiomics and deep learning models.

Purpose: Breast cancer (BC) is one of the most common causes of death among females. Cancer cells escape from apoptosis, causing the cells to proliferate uncontrollably. MicroRNAs (miRNAs) are known to regulate apoptosis in cancer cells.

Objective: This study aimed to determine the change in miR-484 in different BC cells and its relationship with the apoptosis pathway.

Methods: In the study, tumor and healthy tissue samples adjacent to the tumor were collected from 42 patients (6 benign, 36 malignant). Tissue samples were classified according to tumor type, tumor histological grade, proliferation index, and molecular subtypes. Gene expression levels were determined by quantitative real-time polymerase chain reaction (qRT-PCR), and protein levels were determined using the Western Blot method. The results were analyzed using the delta-delta Ct method.

Results: Findings showed that miR-484 expression levels were higher in malignant tumors than in benign tumors, and higher in tumor tissues than healthy tissues. Additionally, it was determined that as Ki-67 levels and histological grade and aggressiveness increased, miR-484 expression levels also increased. In tumor tissue compared with healthy adjacent tissue, there was an increase in BCL2 expression and a decrease in Casp3 and Casp9 expression. Therefore, a positive correlation was found between miR-484 expression and BCL2, and a negative correlation was found between CASP3 and CASP9 expression.

Conclusion: Our results show that miR-484 may play a roll as an onco-miR in BC. Increased miR-484 and BCL2, and decreased Casp3, in breast tumor tissues suggest that Casp9 expression may increase uncontrolled cell proliferation by suppressing apoptosis in BC cells and may contribute to tumor progression.

Background: This study aimed to evaluate the immunotherapeutic effect of irreversible electroporation (IRE) and IP-001 in pancreatic adenocarcinoma with metastasis.

Methods: Orthotopic models of pancreatic adenocarcinoma with hepatic oligometastasis were established by implantation of tumor tissues (derived from Pan02 or KPC cells) size 2 mm³ into the pancreas and left liver lobe in C57BL/6J mice. One week after implantation, the tumor-burden mice were subjected to saline control, IRE, IP-001, and IRE+IP-001. For IRE therapy (1000 V, 0.1 ms, 10 pulses administered 10 times), the pancreas tumor was treated, whereas the oligometastasis was untreated as the IRE off-target tumor. Intratumoral administration of IP-001(0.4 ml/kg) was performed.

Results: In the KPC oligometastatic model, IRE+IP-001 therapy significantly suppressed the growth of oligometastatic tumor. Flow cytometry showed significantly increased tumor-infiltrating lymphocytes (TILs) (e.g., CD8⁺ cytotoxic T lymphocytes) and significantly increased monocytes/macrophages in the oligometastatic tumor tissues from IRE+IP-001 treatment compared with the sham control. Significantly decreased Treg cells and tumor-associated macrophages (TAMs) also were found in the oligometastatic tumor tissues from IRE+IP-001 treatment compared with the sham control. In the Pan02 oligometastatic model, both IRE+IP-001 therapy and IRE+anti-PD-L1 immunotherapy significantly suppressed the growth of oligometastatic tumor, which was associated with the increased CD8⁺ cytotoxic T lymphocytes. However, increased monocytes/macrophages were found in the mice that had IRE+IP-001 therapy, but not in the mice that had IRE+anti-PD-L1 immunotherapy.

Conclusion: The study provided compelling evidence for the efficacy of IRE&IP-001 therapy in suppressing pancreatic tumors, including off-target oligometastatic lesions. The observed off-target effect underscores the importance of systemic immune activation in achieving effective tumor control.

Background: Hematologic changes after splenectomy and hyperthermic intraperitoneal chemotherapy (HIPEC) can complicate postoperative assessment of infection. This study aimed to develop a machine-learning model to predict postoperative infection after cytoreductive surgery (CRS) and HIPEC with splenectomy.

Methods: The study enrolled patients in the national TriNetX database and at the Johns Hopkins Hospital (JHH) who underwent splenectomy during CRS/HIPEC from 2010 to 2024. Demographics, comorbidities, vital signs, daily laboratory values, and documented infections were collected. The patients were divided into infected and non-infected cohorts within 14 days postoperatively. Extreme gradient boost (XGBoost) machine-learning was used to predict postoperative infection. An initial model was generated using the TriNetX dataset and externally validated in the JHH cohort.

Results: From TriNetX, 1016 patients were included: 802 in the non-infected group (79%) and 214 (21%) in the postoperative infection group. The mean age was 61 ± 13 years, and 597 (56%) of the patientswere female. Most of the patients underwent CRS/HIPEC with splenectomy for appendiceal cancer (n = 590, 56%), followed by colorectal malignancy (n = 299, 29%). The remainder (n = 127, 15%) underwent CRS/HIPEC with splenectomy for gastric, pancreatic, ovarian, and small bowel malignancies or peritoneal mesothelioma. In detecting any infection, XGBoost exhibited excellent prediction accuracy (area under the receiver operating characteristic curve [AUC], 0.910 ± 0.073; F1 score, 0.915 ± 0.040) and retained high accuracy upon external validation with 96 demographically similar JHH patients (AUC, 0.823 ± 0.08; F1 score, 0.864 ± 0.03).

Conclusion: A novel machine-learning algorithm was developed to predict postoperative infection after CRS/HIPEC with splenectomy that could aid in the early diagnosis and initiation of treatment.

Background: Neoadjuvant therapy is recommended for treating resectable pancreatic ductal adenocarcinoma (PDAC); however, its appropriate use in patients with resectable PDAC remains debatable.

Objective: This study aimed to identify independent poor prognostic factors and evaluate the clinical significance of neoadjuvant therapy in patients with resectable PDAC.

Methods: We retrospectively reviewed consecutive patients diagnosed with resectable PDAC at our institute between January 2003 and December 2022. We analyzed poor prognostic factors at the time of diagnosis in patients who underwent upfront surgery using the Cox proportional hazards model for overall survival (OS). The prognostic score was calculated by adding the individual prognostic factor scores.

Results: Overall, 359 patients were included in this study, with 308 patients undergoing upfront surgery and the remaining 51 patients receiving neoadjuvant therapy. The R0 resection rate was significantly higher in the neoadjuvant therapy group (70.6%) than in the upfront surgery group (64.0%). Multivariate analysis in the upfront surgery group revealed the following independent poor prognostic factors: tumor size ≥ 35 mm, serum albumin level ≤ .5 g/dL, neutrophil-to-lymphocyte ratio ≥ 3.5, carbohydrate antigen 19-9 level ≥ 250 U/mL, and Duke pancreatic monoclonal antigen type 2 level ≥ 750 U/mL. Among patients with prognostic scores of 0-1 (n = 263), the intention-to-treat OS did not significantly differ between the neoadjuvant therapy and upfront surgery groups. Among those patients with a prognostic score of ≥ 2 (n = 96), the neoadjuvant therapy group had significantly longer intention-to-treat OS than the upfront surgery group.

Conclusions: Prognostic score-based stratification can help identify patients who could benefit from neoadjuvant therapy.

Background: Salvage esophagectomy is more complex and associated with higher postoperative morbidity and mortality than standard resection. This study aimed to investigate short-term outcomes and the influence of hospital volume on these outcomes of salvage surgery for esophageal cancer.

Methods: The study enrolled all patients undergoing esophagectomy for esophageal cancer registered in the Dutch Upper Gastrointestinal Cancer Audit (DUCA) between 2012 and 2022. The patients were classified as salvage or non-salvage by registering surgeons. Salvage surgery is defined in the DUCA as surgery after definitive chemoradiotherapy. Postoperative mortality (30-day/in-hospital) and morbidity were compared between the salvage and non-salvage patients using multilevel logistic regression analyses. Hospital variation in the use of salvage esophagectomy was investigated using funnel plots. The influence of hospital volume (≤ 40 to > 40 cases) and salvage volume (< 6 to ≥ 6 cases) on outcomes for salvage patients were investigated. Using backward elimination, relevant baseline characteristics influencing salvage outcomes were identified.

Results: Between 2012 and 2022, 7749 patients underwent esophagectomy, 251 (3%) of whom underwent salvage resection, varying from 0 to 8% between centers. Severe complications (43% vs 28%; odds ratio [OR], 1.81; 95 % confidence interval [CI], 1.40-2.34) and 30-day/in-hospital mortality (11% vs 3%; OR, 3.65; 95% CI, 2.38-5.61) were higher after salvage surgery than after non-salvage surgery. Salvage patients treated in high-volume centers had a lower risk of 30-day/in-hospital mortality than those treated in low-volume centers (9% vs 19%; OR, 0.42; 95% CI, 0.18-0.99), with no relation between salvage volume and outcome. Male sex, older age (> 75 years), and squamous cell carcinoma were associated with worse short-term outcomes of salvage surgery.

Conclusions: Salvage surgery is associated with worse short-term outcomes than non-salvage esophagectomy. Outcomes after salvage surgery were favorable in high-volume esophagectomy centers.

Background: Immunotherapy is a recently recognised FDA-approved treatment for R/M HNSCC. Our goal is to explore the safety profile and the efficacy of immunotherapy in the neoadjuvant setting before surgery in mucosal head and neck cancer.

Methods: Three electronic databases had been systematically searched through March 2024. Demographic and tumour characteristics were extracted. Primary outcomes obtained were disease-free survival (DFS), progression-free survival (PFS), overall survival (OS), complete pathological response (cPR), which was defined as no residual tumour, and major pathological response (MPR), which as defined as <10% residual viable tumour. Safety outcomes examined were grade 3 and above adverse event, median time to surgery, delays to surgery, and death related to neoadjuvant treatment.

Results: A total of 459 patients from 15 studies were included in the analysis. The pooled estimate of cPR for all the studies was 14.9% (95% confidence interval [CI] 8.0-26.2). Subgroup analysis showed chemoimmunotherapy had a higher cPR 30.1% (95% CI 22.8-38.62) compared with immunotherapy alone 1.4% (95% CI 0.3-5.2). There was no treatment-related death. Chemoimmunotherapy had a higher pooled estimate of adverse events 22.9% (95% CI 11.0-41.5) compared with immunotherapy alone 8.5% (95% CI 2.6-24.3). Subgroup analysis demonstrated that chemoimmunotherapy had a higher DFS compared with immunotherapy alone: 89.8% (95% CI 81.4-94.7) versus 80.44% (95% CI 73.9-85.7), respectively. Neoadjuvant immunoradiotherapy had conflicting results.

Conclusions: Neoadjuvant immunotherapy was well tolerated. Neoadjuvant chemoimmunotherapy may be more effective in treating LAHNSCC over immunotherapy alone; however, TRAEs were higher.

We highlight the potential for further analysis and investigation of the article by Sirakaya and colleagues. Specifically, we note that the authors failed to evaluate diaphragm mobility, which is essential for a comprehensive assessment of respiratory function, as well as diaphragm thickness. Assessing diaphragm mobility could enrich our understanding of the impact of surgical approaches on respiratory mechanics and postoperative pulmonary complications. Additionally, we note the absence of socioeconomic status (SES) as a confounding factor in the study. Recognizing the influence of SES on surgical outcomes and patient recovery, we suggest its inclusion in future research. We also emphasize the importance of integrating a multidisciplinary team, including physiotherapists and social workers, to address the physical and socioeconomic challenges faced by patients post-surgery.