Background/Objectives: Long-term survival in pancreatic ductal adenocarcinoma (PDAC) remains poor. Although neoadjuvant therapy (NAT) has been increasingly investigated in resectable disease, its benefit compared with upfront surgery remains uncertain. This review evaluates evidence from randomized and prospective trials and explores clinical and molecular factors that may refine patient selection. Methods: We reviewed key randomized and prospective clinical trials evaluating NAT in resectable PDAC, including NORPACT-1, PANACHE01/PRODIGE-48, PREP-02/JSAP05, NEONAX, PREOPANC-1, PREOPANC-2, and CASSANDRA (PACT-21), the last two of which directly compared different NAT regimens head-to-head in the neoadjuvant setting, whereas PREOPANC-1 compared neoadjuvant chemoradiotherapy with upfront surgery. Outcomes of interest included overall survival (OS), resection rates, and treatment-related differences across resectable and borderline resectable populations. We also examined emerging clinical and biomarker-driven stratification strategies. Results: Trials in strictly resectable PDAC have demonstrated mixed results. NORPACT-1 reported inferior OS with neoadjuvant FOLFIRINOX compared to upfront surgery (median OS 25.1 vs. 38.5 months; HR 1.52). PANACHE01/PRODIGE-48 showed comparable OS despite higher R0 resection rates with NAT. In contrast, PREP-02/JSAP05 demonstrated improved OS with neoadjuvant gemcitabine plus S-1 (37.0 vs. 26.6 months; HR 0.73). PREOPANC-1 showed a survival advantage with neoadjuvant chemoradiotherapy, although pooled analyses suggest this benefit is primarily driven by borderline resectable disease, with no statistically significant OS improvement in strictly resectable cohorts. PREOPANC-2 demonstrated no OS difference between neoadjuvant FOLFIRINOX and gemcitabine-based chemoradiation. Conclusions: The benefit of NAT in resectable PDAC is not uniform and appears to depend on underlying tumor biology and risk features. High-risk characteristics, including elevated CA19-9, large tumor size, and nodal involvement, may identify patients most likely to benefit from upfront systemic therapy. Integration of molecular biomarkers such as SMAD4, GATA6, and homologous recombination deficiency into prospective trial design is critical. Ongoing phase III trials will further define optimal treatment strategies in this population.
Background/Objectives: Deep networks trained to recognise oral squamous cell carcinoma (OSCC) in histopathology perform well on held-out images from the same collections, but a recent study found that such a network lost most of its discriminative ability on lymph node tissue. We examined whether encoder fine-tuning or label-free adaptation changes this, and how many labelled target patches are needed to recover performance. Methods: The source domain comprised 23,290 images of oral and oropharyngeal mucosa from three public collections. The target domain was PatchCamelyon, a public dataset of sentinel lymph node patches from breast cancer patients; its metastases are breast carcinoma, so the transfer crosses both tissue type and cancer histology. We used 40,000 target patches from 216 slides, split into slide-disjoint adaptation and evaluation pools. We compared nine encoders in ten configurations, including three pathology foundation models (Phikon, Phikon-v2 and the recent Midnight model). We evaluated direct transfer with frozen and fine-tuned encoders, label-free adaptation, and few-shot adaptation, in which we compute class prototypes from k labelled target patches using a frozen encoder. All results are at patch level. Results: Direct transfer failed for every configuration (external AUROC 0.35–0.64), including fine-tuned networks (mean over three seeds 0.44–0.52) and fine-tuned Phikon (0.54–0.58). Label-free methods did not close the gap; a zero-shot vision–language model reached 0.77. With a frozen Phikon encoder, prototypes from 10 and 50 labelled patches per class reached 0.869 ± 0.056 and 0.930 ± 0.015, against 0.82–0.86 at 50 patches for encoders without histology pre-training and 0.977 for a classifier trained on 20,000 labelled patches. Logistic regression on the same patches performed similarly at one and two patches per class and better from five upward (0.955 at 50). Midnight reached 0.922 with prototypes at 50 patches per class, similar to Phikon. The results were similar when support and evaluation patches came from different scanning centres. Conclusions: For the methods and datasets evaluated, no classifier trained on oral tissue transferred to this cross-tissue, cross-cancer target. Our analyses suggest that the change in what the classes contain mattered more than stain or scale, but they do not separate the causal contributions of tissue, cancer histology and acquisition. Frozen pathology foundation models made label-efficient classification on the target domain inexpensive; this replaces the oral-trained classifier and does not use oral images. The findings concern patch-level classification of breast cancer metastases and do not establish clinical performance for OSCC lymph node metastases.
Background/Objectives: Diagnosis-to-treatment care fragmentation may occur when patients visit multiple healthcare institutions before cancer treatment initiation; however, its associations with healthcare expenditures, treatment timing, and clinical outcomes remain unclear. We examined the prevalence, patterns, and associated outcomes of patients with gastric, colorectal, liver, or lung cancer in Korea. Methods: Using the Korea Clinical Data Utilization Network for Research Excellence Cancer Public Library Database, we identified 330,563 patients with a new diagnosis of gastric, colorectal, liver, or lung cancer between 2012 and 2020. Fragmentation was defined as receiving cancer-related care at two or more institutions between the diagnosis and treatment initiation. Outcomes were healthcare expenditures, time to treatment, emergency department visits, intensive care unit (ICU) admission, and 1-year all-cause mortality. Multivariable generalized linear models with a gamma distribution and log link and Cox proportional hazards models were applied, and sensitivity and subgroup analyses were performed. Results: Fragmentation was experienced by 82,436 patients (24.9%) and associated with higher healthcare expenditures, longer time to treatment, and higher risks of emergency department visits, ICU admission, and 1-year all-cause mortality. Associations were strongest among patients who visited three or more institutions. Fragmentation was associated with longer time to treatment and adverse clinical outcomes across subgroups defined by disability status, insurance type, residential region, and SEER summary stage. Conclusions: Implications of diagnosis-to-treatment care fragmentation differed according to institutional transitions. Strengthening coordinated referral pathways, information exchange, and patient navigation may reduce fragmentation and preserve access to specialized cancer care.
Background/Aim: Osteosarcoma (OS) treatment consists of chemotherapy with methotrexate, adriamycin (doxorubicin) and platinol (MAP) combined with intercalated surgery, resulting in a 5-year survival rate of 50–60%. We recently demonstrated that local delivery of doxorubicin via a microparticulate hydroxyapatite-based biomaterial (DASH) could efficiently impede tumor growth in subcutaneous OS; however, its effect in an orthotopic intraosseous OS remains unknown, particularly in conjunction with systemic MAP treatment. In this study, we performed two separate mouse model studies with the aim of (1) evaluating the effect of DASH in an orthotopic osteosarcoma model and (2) evaluating the efficacy and tolerability of DASH in conjunction with systemically administered MAP in a subcutaneous osteosarcoma model. Methods: In the first study, 56 mice were inoculated with human OS cells (i.e., h143B cells) in the proximal tibia. After 10 days, the mice were divided into seven treatment groups, of which group G2 (systemic DOX) was compared with groups G5–G7, which were treated with increasing doses of DOX delivered via DASH. The tumor-impeding response was evaluated via micro-CT (day 14), PET-CT (day 21) and tumor measurements (post-mortem). In the second study, 45 mice were inoculated subcutaneously with 143B cells and, 10 days later, groups G2–G5 were treated locally with increasing DASH doses, followed by two cycles of systemic MAP for all groups. On day 31, the animals underwent PET-CT examination followed by euthanasia and tumor measurements. Results: In both experiments, DASH treatment resulted in significantly lower tumor activity, tumor volume and weight. Micro-CT examination in the orthotopic model demonstrated that DASH treatment protected the bone from osteolysis. The subcutaneous study revealed that the mice were able to tolerate DASH, even in conjunction with systemically administered MAP. Conclusions: Intratumoral administration of DASH impeded OS growth in both animal models and protected bone against tumor-induced osteolysis. Furthermore, DASH was well-tolerated when administered in conjunction with systemic MAP therapy, indicating its potential therapeutic neo-adjuvant value in poor responders.
Cuproptosis, a recently identified form of copper-dependent regulated cell death, is closely associated with mitochondrial metabolism and copper homeostasis. Triple-negative breast cancer (TNBC) remains difficult to treat because of limited targeted therapeutic options and frequent therapeutic resistance. Emerging evidence suggests that cuproptosis-related pathways may influence TNBC progression, treatment response, and the tumor immune microenvironment. Preclinical studies further indicate that combining cuproptosis-targeting strategies with chemotherapy, targeted therapy, or immunotherapy may enhance anti-tumor efficacy. In this review, we summarize the molecular mechanisms of cuproptosis and its potential roles in TNBC progression, drug resistance, and immune regulation. We also discuss emerging therapeutic strategies targeting cuproptosis and their potential combination with existing treatments in TNBC. Finally, we highlight current challenges and future directions for the clinical translation of cuproptosis-based therapies in TNBC. Collectively, cuproptosis represents a promising but still evolving therapeutic vulnerability that requires further mechanistic and clinical validation.
