Development and Validation of Multicenter Predictive Nomograms for Locally Advanced Pancreatic Cancer After Chemoradiotherapy

Minimum and Optimal CA19-9 Response After Two Months Induction Chemotherapy in Patients With Locally Advanced Pancreatic Cancer: A Nationwide Multicenter Study

OBJECTIVE

This nationwide multicenter study aimed to define clinically relevant thresholds of relative serum CA19-9 response after 2 months of induction chemotherapy in patients with locally advanced pancreatic cancer (LAPC).

BACKGROUND

CA19-9 is seen as leading biomarker for response evaluation in patients with LAPC, but early clinically useful cut-offs are lacking.

METHODS

All consecutive patients with LAPC after 4 cycles (m)FOLFIRINOX or 2 cycles gemcitabine-nab-paclitaxel induction chemotherapy (±radiotherapy) with CA19-9 ≥5 U/mL at baseline were analyzed (2015-2019). The association of CA19-9 response with median OS (mOS) was evaluated for different CA19-9 cut-off points. Minimum and optimal CA19-9 response were established via log-rank test. Predictors for OS were analyzed using COX regression analysis.

RESULTS

Overall, 212 patients were included, of whom 42 (19.8%) underwent resection. Minimum CA19-9 response demonstrating a clinically significant median OS difference (12.7 vs. 19.6 months) was seen at ≥40% CA19-9 decrease. The optimal cutoff for CA19-9 response was ≥60% decrease (21.7 vs. 14.0 mo, P =0.021). Only for patients with elevated CA19-9 levels at baseline (n=184), CA19-9 decrease ≥60% [hazard ratio (HR)=0.59, 95% CI, 0.36-0.98, P =0.042] was independently associated with prolonged OS, as were SBRT (HR=0.42, 95% CI, 0.25-0.70; P =0.001), and resection (HR=0.25, 95% CI, 0.14-0.46, P <0.001), and duration of chemotherapy (HR=0.75, 95% CI, 0.69-0.82, P <0.001).

CONCLUSIONS

CA19-9 decrease of ≥60% following induction chemotherapy as optimal response cut-off in patients with LAPC is an independent predictor for OS when CA19-9 is increased at baseline. Furthermore, ≥40% is the minimum cut-off demonstrating survival benefit. These cut-offs may be used when discussing treatment strategies during early response evaluation.

Preoperative chemotherapy, radiotherapy and surgical decision-making in patients with borderline resectable and locally advanced pancreatic cancer

Surgical resection combined with systemic chemotherapy is the cornerstone of treatment for patients with localized pancreatic cancer. Upfront surgery is considered suboptimal in cases with extensive vascular involvement, which can be classified as either borderline resectable pancreatic cancer or locally advanced pancreatic cancer. In these patients, FOLFIRINOX or gemcitabine plus nab-paclitaxel chemotherapy is currently used as preoperative chemotherapy and is eventually combined with radiotherapy. Thus, more patients might reach 5-year overall survival. Patient selection for chemotherapy, radiotherapy and subsequent surgery is based on anatomical, biological and conditional parameters. Current guidelines and clinical practices vary considerably regarding preoperative chemotherapy and radiotherapy, response evaluation, and indications for surgery. In this Review, we provide an overview of the clinical evidence regarding disease staging, preoperative therapy, response evaluation and surgery in patients with borderline resectable pancreatic cancer or locally advanced pancreatic cancer. In addition, a clinical work-up is proposed based on the available evidence and guidelines. We identify knowledge gaps and outline a proposed research agenda.

Construction of a cuproptosis-related lncRNA signature for predicting prognosis and immune landscape in osteosarcoma patients

BACKGROUND

Long noncoding RNAs (lncRNAs) influence the onset of osteosarcoma. Cuproptosis is a novel cell death mechanism. We attempted to identify a cuproptosis-related lncRNA signature to predict the prognosis and immune landscape in osteosarcoma patients.

METHODS

Transcriptional and clinical data of 85 osteosarcoma patients were derived from the TARGET database and randomly categorized into the training and validation cohorts. We implemented the univariate and multivariate Cox regression, along with LASSO regression analyses for developing a cuproptosis-related lncRNA risk model. Kaplan-Meier curves, C-index, ROC curves, univariate and multivariate Cox regression, and nomogram were used to assess the capacity of this risk model to predict the osteosarcoma prognosis. Gene ontology, KEGG, and Gene Set Enrichment (GSEA) analyses were conducted for determining the potential functional differences existing between the high-risk and low-risk patients. We further conducted the ESTIMATE, single-smaple GSEA, and CIBERSORT analyses for identifying the different immune microenvironments and immune cells infiltrating both the risk groups.

RESULTS

We screened out four cuproptosis-related lncRNAs (AL033384.2, AL031775.1, AC110995.1, and LINC00565) to construct the risk model in the training cohort. This risk model displayed a good performance to predict the overall survival of osteosarcoma patients, which was confirmed by using the validation and the entire cohort. Further analyses showed that the low-risk patients have more immune activation and immune cells infiltrating as well as a good response to immunotherapy.

CONCLUSIONS

We developed a novel cuproptosis-related lncRNA signature with high reliability and accuracy for predicting outcome and immunotherapy response in osteosarcoma patients, which provides new insights into the personalized treatment of osteosarcoma.