Oncology最新文献

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.

Introduction: There is ongoing debate about the safety of breast reconstruction for patients with locally advanced breast cancer (LABC) who have undergone total mastectomy (TM). More and more LABC patients are undergoing breast reconstruction after TM, but its long-term survival outcomes remain unclear. This study aimed to compare the survival outcomes of LABC patients who underwent breast reconstruction after TM with those who did not, based on a large sample.

Methods: We collected data for all LABC patients who underwent TM with or without breast reconstruction in the Surveillance, Epidemiology, and End Results (SEER) database. We divided patients into two groups: TM group and total mastectomy with reconstruction (TM+R) group. The primary outcomes were overall survival (OS) and breast cancer-specific survival (BCSS). Propensity score matching (PSM) analysis was used to eliminate imbalances of baseline data between the two groups. Data were analyzed using χ2 tests, Kaplan-Meier methods, and univariate and multivariate Cox regression analyses.

Result: We identified 39,112 eligible patients (33,169 patients received TM and 5,943 received TM+R), and 8,680 patients were matched after PSM (4,340 patients received TM and 4,340 received TM+R). Patients with middle age, white, married, lived in urban, IIB-IIIA stage, invasive ductal carcinoma, pathological grade II-III, hormone receptor-positive, and undergone chemotherapy were more likely to receive breast reconstruction. After PSM, Kaplan-Meier survival analysis showed better OS and BCSS in the TM+R group versus the TM group (OS: p < 0.001; BCSS: p = 0.008). Multivariate Cox regression analysis showed that TM+R significantly improved OS and BCSS (OS: hazard ratio 0.73, 95% confidence interval [CI] [0.68, 0.79], p < 0.001; BCSS: 95% CI [0.79, 0.94], p = 0.001). Subgroup analysis showed that patients with old age, white, and hormone receptor-positive had better OS and BCSS by TM+R compared to TM.

Conclusions: Breast reconstruction after TM is associated with better OS and BCSS in patients with LABC.

Introduction: Fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) improve overall survival (OS) and progression-free survival (PFS) in patients with pancreatic cancer, compared with gemcitabine (GEM). However, whether PFS is a surrogate marker of OS in pancreatic cancer chemotherapy focusing on FOLFIRINOX or GEM plus nab-paclitaxel remains unknown. We aimed to verify whether PFS can be a surrogate marker of OS in prognosis prediction.

Methods: This was an integrated analysis of the NAPOLEON study and retrospective cohort of the NAPOLEON-2 study - a multicenter observational study conducted in Japan, using real-world data. The primary and secondary endpoints were OS and PFS, respectively. The correlation between OS and PFS in first- and second-line treatments was assessed using Method of Moments estimation. An analysis was performed in patients with confirmed OS at the end of follow-up. The NAPOLEON-2 cohort included only patients who received 5-fluorouracil, leucovorin, and nanoliposomal irinotecan (NFF) as second-line treatment.

Results: Among 479 patients, the correlation between PFS and OS from first- and second-line chemotherapies was calculated in 310 and 225 patients, respectively. The R-squared values for the correlation between PFS and OS from first- and second-line chemotherapies were 0.74 and 0.76, respectively. There was no statistically significant difference in first-line treatment between the FOLFIRINOX and GEM plus nab-paclitaxel groups (p = 0.92). Therefore, the FOLFIRINOX group may not have shown a stronger correlation than the NFF group.

Conclusion: PFS can be a surrogate marker of OS in first- and second-line therapies. Appropriate prognostic estimation might contribute to proper treatment selection.

Introduction: Perioperative immunotherapy has shown promise in some patients with early-stage hepatocellular carcinoma (HCC). This study examined tissue and imaging biomarkers associated with pathologic response in a phase II clinical trial in patients with resectable HCC.

Methods: Analysis included 18 patients with biopsy-proven resectable HCC treated with neoadjuvant nivolumab plus ipilimumab or nivolumab alone in a phase II clinical trial at MD Anderson Cancer Center (NCT03222076). Liver MRE (to measure tissue fibrosis) and biopsies (to evaluate immune activation markers) were obtained serially pretreatment and after completing neoadjuvant immunotherapy. A major pathologic response (MPR) was defined as tumor necrosis of more than 70%. Data comparing patients with MPR versus those without were summarized using descriptive statistics and compared using the Wilcoxon rank-sum test.

Results: Patients with MPR after neoadjuvant immunotherapy tended to have larger tumors (mean 9.52 vs. 4.99 centimeters; p = 0.050). They had a significant reduction in tumor size posttreatment (14.67% reduction vs. 9.15% increase in size; p = 0.042) and a nonsignificant decrease in serum AFP (-24.20% vs. -14.00%; p = 0.085). Further, patients with MPR had a greater increase in intratumoral expression levels of CD8 (26.92% vs. -0.04%; p = 0.026), granzyme B (15.56% vs. -2.24%; p = 0.011), and PD-1 (20.17% vs. 0.40%; p = 0.048) but not PD-L1 (7.69% vs. 0.57%; p = 0.26). For imaging biomarkers, tumor and liver fibrosis were comparable before and after neoadjuvant therapy in patients with MPR versus nonresponders.

Conclusion: Changes in tumor size, immune cell infiltration, and immune cell activation are candidate predictive markers of pathologic response to neoadjuvant immunotherapy in patients with resectable HCC.

Introduction: We investigated the effectiveness of lenvatinib (LEN) after disease progression following first-line treatment with atezolizumab plus bevacizumab (Atez/Bev) in patients with unresectable hepatocellular carcinoma (HCC).

Methods: One hundred and ten HCC patients treated with Atez/Bev as first-line systemic chemotherapy were enrolled and underwent dynamic computerized tomography/magnetic resonance imaging to determine the treatment response. We evaluated the treatment efficacy and prognosis after second-line LEN treatment, especially in elderly patients.

Results: Of the 110 study patients, 88 patients (80%) were determined to have progressive disease (PD) during the observation periods, and 40 patients received second-line LEN therapy. The 40 patients included 13 patients who were unable to continue LEN until the initial evaluation due to adverse events (AE). The 27 patients who were able to continue LEN therapy (Group A) were significantly younger at initiation of Atez/Bev than those who could not continue (71 vs. 77 years old, p = 0.013). Comparing the OS and PFS between Group A and 44 patients that included 13 patients who were unable to continue LEN and 31 patients did not receive the second-line treatment (Group B), the former had significantly better OS than Group B (31.1 vs. 17.8 months, p = 0.035).

Conclusions: The tolerability of second-line LEN therapy was lower in elderly patients, and the OS from the start of Atez/Bev therapy was different depending on the tolerability of second-line LEN therapy.

Introduction: Studies have shown that immune-related genes play a crucial role in tumor development and treatment. However, the specific roles and potential value of these genes in lung cancer patients are still not fully understood. Therefore, this study aims to establish a novel risk model based on immune-related genes for evaluating the prognostic risk and response to immune therapy in lung cancer patients.

Methods: Gene expression and clinical data of lung cancer patients were retrieved from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, while immune-related genes were obtained from the ImmPort database. A risk signature model was developed using univariate Cox analysis and LASSO regression analysis. The prognostic value of the model and its response to immunotherapy were analyzed by survival analysis, immune infiltration analysis, and immunotherapy response analysis.

Results: We have developed a risk signature model based on eight key immune-related genes, which can classify patients into high-risk and low-risk groups. The prognosis of the high-risk group was significantly lower than that of the low-risk group and was validated in multiple GEO datasets. The mutation frequency was lower in the low-risk group compared to the high-risk group (TP53: 55% vs. 65%; TTN: 52% vs. 60%; CSMD3: 34% vs. 45%). Futhermore, CD274 expression was lower in the low-risk patients, and the high-risk patients in the IMvigor210 cohort had lower survival. Immune infiltration analyses showed that the high-risk group was negatively correlated with the infiltration level of B cells, CD4+ T cells, and NK cells. Importantly, patients in the low-risk group exhibit significantly lower TIDE scores, suggesting that they are more responsive to immunotherapy.

Conclusion: Our study has established a novel and robust immune-related gene risk model that can assist in evaluating the prognostic risk and immune therapy response of lung cancer patients.

Our working group has previously shown that bile acids (BAs) accelerate carcinogenic processes in pancreatic cancer (PC) in which mucin 4 (MUC4) expression has a central role. However, the role of other mucins in PC are less clear, especially in bile-induced cancer progression. The study aim was to investigate expression of MUC17 in BAs- or human serum-treated pancreatic ductal adenocarcinoma (PDAC) cell lines and use different assays with RNA silencing/overexpression to study the role of MUC17 in cancer progression. Protein expression of MUC17 was evaluated in 55 human pancreatic samples by immunohistochemistry, and Kaplan-Meier survival analysis was used to compare survival curves. Expression of MUC17 increased in PDAC patients, especially in obstructive jaundice (OJ) and the elevated MUC17 expression associated with poorer overall survival (10.66±1.99 vs. 15.05±2.03 months; Log rank: 0.0497). Treatment of Capan-1 and AsPC-1 cells with BAs or with human serum obtained from PDAC + OJ patients enhanced the expression of MUC17, as well as the proliferative potential of the cells, whereas knockdown of MUC17 alone or in combination with MUC4 decreased BAs-induced carcinogenic processes. Our results demonstrated that MUC17 has a central role in bile-induced PC progression, and in addition to MUC4, this isoform also can be used as a novel prognostic biomarker.

Introduction: The most frequently used first-line treatment in patients with advanced hepatocellular carcinoma (HCC) is atezolizumab plus bevacizumab. Upon progression after this treatment, the standard of care in many countries is sorafenib, due to the lack of reimbursement for other drugs. Several randomized trials are currently underway to clarify the best second-line therapy in patients with HCC. This real-world study aimed to compare outcomes reached by lenvatinib and sorafenib second-line therapy in this setting.

Methods: The overall cohort included 891 patients with HCC from 5 countries treated with atezolizumab plus bevacizumab in first-line setting between October 2018 and April 2022. At the data cut-off (May 2022), 41.5% of patients were continuing a first-line treatment, 5.5% were lost at follow-up, and 53.0% of patients had progressive disease after first-line therapy. 51.5% of patients with progressive disease received a second-line treatment, while 48.5% did not receive any subsequent therapy. Between patients receiving second-line treatment, 11.1% of patients underwent transarterial chemoembolization, 21.0% received sorafenib, 35.4% underwent lenvatinib, and 32.5% were treated with other drugs.

Results: Lenvatinib second-line subgroup achieved a median overall survival (mOS) of 18.9 months, significative longer (p = 0.01; hazard ratio [HR]: 2.24) compared to sorafenib subgroup that reached a mOS of 14.3 months. The multivariate analysis highlighted albumin-bilirubin 1 grade (p < 0.01; HR: 5.23) and lenvatinib second-line therapy (p = 0.01; HR: 2.18) as positive prognostic factors for OS. The forest plot highlighted a positive trend in terms of OS in favor of patients treated with lenvatinib second-line regardless of baseline characteristics before first-line therapy.

Conclusion: These results suggest that, in patients with HCC progressed to first-line atezolizumab plus bevacizumab, lenvatinib second-line therapy is associated to an improved survival compared to sorafenib.

Background: Prostate cancer (PCa) is a malignancy with significant immunosuppressive properties and limited immune activation. This immunosuppression is linked to reduced cytotoxic T cell activity, impaired antigen presentation, and elevated levels of immunosuppressive cytokines and immune checkpoint molecules. Studies demonstrate that cytotoxic CD8+ T cell infiltration correlates with improved survival, while increased regulatory T cells (Tregs) and tumor-associated macrophages (TAMs) are associated with worse outcomes and therapeutic resistance. Th1 cells are beneficial, whereas Th17 cells, producing interleukin-17 (IL-17), contribute to tumor progression. Tumor-associated neutrophils (TANs) and immune checkpoint molecules, such as PD-1/PD-L1 and T cell immunoglobulin-3 (TIM-3) are also linked to advanced stages of PCa. Chemotherapy holds promise in converting the "cold" tumor microenvironment (TME) to a "hot" one by depleting immunosuppressive cells and enhancing tumor immunogenicity.

Summary: This comprehensive review examines the immune microenvironment in PCa, focusing on the intricate interactions between immune and tumor cells in the TME. It highlights how TAMs, Tregs, cytotoxic T cells, and other immune cell types contribute to tumor progression or suppression and how PCa's low immunogenicity complicates immunotherapy.

Key messages: The infiltration of cytotoxic CD8+ T cells and Th1 cells correlates with better outcomes, while elevated T regs and TAMs promote tumor growth, metastasis, and resistance. TANs and natural killer (NK) cells exhibit dual roles, with higher NK cell levels linked to better prognoses. Immune checkpoint molecules like PD-1, PD-L1, and TIM-3 are associated with advanced disease. Chemotherapy can improve tumor immunogenicity by depleting T regs and myeloid-derived suppressor cells, offering therapeutic promise.

Introduction: Although recent data suggest that melphalan high-dose therapy followed by autologous stem cell transplantation (HDT/ASCT) is safe and effective in eligible multiple myeloma (MM) patients up to the age of 75 years, its value in elderly MM patients is still controversially discussed.

Methods: We retrospectively analyzed 607 MM patients ≥60 years old, who were admitted to our institution for first-line or salvage HDT/ASCT between January 2007 and October 2018. We assigned them to three groups according to age at HDT/ASCT: 60-64 years (S1), 65-69 years (S2) and ≥70 years (S3). We compared progression-free and overall survival, duration of hospitalization, complications, transfers to intermediate or intensive care unit, readmissions after discharge and deaths within 100 days after HDT/ASCT between these groups.

Results: Age did not impact progression-free and overall survival after first-line and salvage HDT/ASCT. Patients ≥70 years old at first HDT/ASCT had a longer hospitalization compared to patients 60-64 years old; however, the difference in the length of hospitalization was only marginal. Rates of febrile neutropenia, mucositis, transfers to intermediate or intensive care unit, readmissions after discharge, and deaths within 100 days after HDT/ASCT were similar in the 3 age groups of patients receiving first or salvage HDT/ASCT. Patients with a Charlson Comorbidity Index ≥2 receiving first HDT/ASCT had a higher risk for a transfer to intermediate or intensive care unit.

Conclusion: Our analysis shows that HDT/ASCT is safe and effective in eligible elderly MM patients in first-line treatment and at relapse. A careful patient selection according to biological rather than chronological age is of crucial importance.