Sorting Transcriptomics Immune Information from Tumor Molecular Features Allows Prediction of Response to Anti-PD1 Therapy in Patients with Advanced Melanoma.

Immunotherapy based on anti-PD1 antibodies has improved the outcome of advanced melanoma. However, prediction of response to immunotherapy remains an unmet need in the field. Tumor PD-L1 expression, mutational burden, gene profiles and microbiome profiles have been proposed as potential markers but are not used in clinical practice. Probabilistic graphical models and classificatory algorithms were used to classify melanoma tumor samples from a TCGA cohort. A cohort of patients with advanced melanoma treated with PD-1 inhibitors was also analyzed. We established that gene expression data can be grouped in two different layers of information: immune and molecular. In the TCGA, the molecular classification provided information on processes such as epidermis development and keratinization, melanogenesis, and extracellular space and membrane. The immune layer classification was able to distinguish between responders and non-responders to immunotherapy in an independent series of patients with advanced melanoma treated with PD-1 inhibitors. We established that the immune information is independent than molecular features of the tumors in melanoma TCGA cohort, and an immune classification of these tumors was established. This immune classification was capable to determine what patients are going to respond to immunotherapy in a new cohort of patients with advanced melanoma treated with PD-1 inhibitors Therefore, this immune signature could be useful to the clinicians to identify those patients who will respond to immunotherapy.

Multi-omics Characterization of Response to PD-1 Inhibitors in Advanced Melanoma.

Immunotherapy improves the survival of patients with advanced melanoma, 40% of whom become long-term responders. However, not all patients respond to immunotherapy. Further knowledge of the processes involved in the response and resistance to immunotherapy is still needed. In this study, clinical paraffin samples from fifty-two advanced melanoma patients treated with anti-PD-1 inhibitors were assessed via high-throughput proteomics and RNA-seq. The obtained proteomics and transcriptomics data were analyzed using multi-omics network analyses based on probabilistic graphical models to identify those biological processes involved in the response to immunotherapy. Additionally, proteins related to overall survival were studied. The activity of the node formed by the proteins involved in protein processing in the endoplasmic reticulum and antigen presentation machinery was higher in responders compared to non-responders; the activity of the immune and inflammatory response node was also higher in those with complete or partial responses. A predictor for overall survival based on two proteins (AMBP and PDSM5) was defined. In summary, the response to anti-PD-1 therapy in advanced melanoma is related to protein processing in the endoplasmic reticulum, and also to genes involved in the immune and inflammatory responses. Finally, a two-protein predictor can define survival in advanced disease. The molecular characterization of the mechanisms involved in the response and resistance to immunotherapy in melanoma leads the way to establishing therapeutic alternatives for patients who will not respond to this treatment.

Biomarkers of Venous Thromboembolism Recurrence after Discontinuation of Low Molecular Weight Heparin Treatment for Cancer-Associated Thrombosis (HISPALIS-Study).

The most appropriate duration of anticoagulant treatment for cancer-associated venous thromboembolism (CAT) remains unclear. We have conducted a prospective multicenter study in CAT patients with more than 6 months of anticoagulant treatment to predict the risk of venous thromboembolism (VTE) recurrence after anticoagulation discontinuation. Blood samples were obtained when patients stopped the anticoagulation, at 21 days and at 90 days. In each sample we assessed different coagulation-related biomarkers: D-dimer (DD), high-sensitivity C-reactive protein (hs-CRP), P-selectin (PS), phospholipids, soluble tissue factor, factor VIII and the thrombin generation test. It was evaluated 325 CAT patients and 166 patients were included in the study, mean age 64 ± 17 years. VTE recurrence until 6 months after stopping anticoagulation treatment was 9.87% [95% confidence interval (CI): 6−15]. The biomarkers sub-distribution hazard ratios were 6.32 for ratio DD basal/DD 21 days > 2 (95% CI: 1.82−21.90), 6.36 for hs-CRP > 4.5 (95% CI: 1.73−23.40) and 5.58 for PS > 40 (95% CI: 1.46−21.30) after 21 days of stopping anticoagulation. This is the first study that has identified the DD ratio, hs-CRP and PS as potential biomarkers of VTE recurrence in cancer patients after the discontinuation of anticoagulation treatment. A risk-adapted strategy may allow the identification of the optimal time to withdraw the anticoagulation in each CAT patient.