BACKGROUND:Immunotherapy based on anti-PD1 inhibitors has significantly improved survival in advanced melanoma. However, a significant proportion of patients do not benefit, and predicting response to immunotherapy remains an area of unmet need. Our group previously defined an immune signature able to predict response to anti-PD1 inhibitors in this scenario. METHODS:In this study, we analyzed two cohorts of patients with advanced melanoma treated with anti-PD1 inhibitors: the GEM cohort, previously used to validate our immune signature, and Campbell's cohort, which contains data about different immunotherapy schemes. Using the 107 genes that compose our immune signature and consensus clustering, samples were classified as immune-low or immune-high. Then, CIBERSORTx and Ecotyper were used to estimate the proportion of each immune cell type and carcinoma ecotypes in both cohorts. RESULTS:We confirmed that the immune-low group includes mostly patients who do not response to anti-PD1 inhibitors. We also studied the distribution of carcinoma ecotypes in the immune-high and immune-low groups defined by our immune classification. Ecotypes CE9 and CE10 clustered in the immune-high group, with good response to treatment. The use of combination immunotherapy improved response rate both in immune-low and immune-high tumors. The immune-high group contained a higher number of CD8 T cells, B memory cells and T follicular helper cells. CONCLUSIONS:Our immune-based classification defines an immune-low group of tumors with poor response to anti-PD1 inhibitors. This immune classification is related to carcinoma ecotypes. Finally, a use of a combo scheme improves the rates of response both in immune-high and low groups but in the case of immune-low tumors, our results suggests that a combo treatment approach could be an adequate strategy and should be further explored in these patients. Altogether, our results support the utility of our immune signature in the prediction of response to anti-PD1 inhibitors in advanced melanoma.
This article presents a case study illustrating the contemporary integrative cognitive approach, a multidimensional model that weaves together cognitive, behavioral, affective, motivational, developmental, interpersonal, and sociocultural dimensions. The approach promotes dimensional and idiographic formulation to understand psychopathology as the expression of life trajectories. The case of Sofía, a 30-year-old outpatient with personality-spectrum difficulties, exemplifies how this model guides individualized intervention through collaborative meaning-making. Over two years of psychotherapy, work focused on affect regulation, schema modification, and the reconstruction of autobiographical narratives within a safe therapeutic relationship. Quantitative outcome monitoring and a qualitative first-person evaluation converged to show significant improvements in functioning, emotional awareness, and agency. The case underscores how integrative cognitive psychotherapy can support patients in becoming active protagonists of their own life stories.
Abstract Type 1 diabetes (T1D) is an autoimmune disease characterized by β-cell destruction and insulin deficiency. Circulating microRNAs (miRNAs) are promising biomarkers for disease monitoring and complication risk assessment. This study aimed to describe the epigenetic profile in a multicenter Spanish T1D cohort and its association with clinical variables. We analyzed plasma samples from 125 participants (76 T1D, 49 controls) recruited across nine Spanish hospitals. Eight candidate miRNAs from a prior Asturias cohort study were quantified using RT-PCR. Associations with clinical and biochemical parameters were explored, and enrichment analysis was performed to investigate affected biological pathways. Of the miRNAs analyzed, only hsa-miR-200a-3p was significantly overexpressed in T1D versus controls (p = 0.035). In T1D patients, hsa-miR-200a-3p, hsa-miR-1-3p, and hsa-miR-340-5p showed positive correlations with HbA1c, while hsa-miR-224-5p correlated with body mass index (BMI). Poor glycemic control (HbA1c ≥ 7.5%) was associated with higher expression of hsa-miR-1-3p, hsa-miR-200a-3p, and hsa-miR-340-5p. No significant expression differences were found according to comorbidity or hypertension status. hsa-miR-200a-3p emerges as a potential biomarker for β-cell stress in long-standing T1D, while hsa-miR-1-3p and hsa-miR-340-5p may reflect glycemic control status and vascular risk. These findings support further evaluation of these miRNAs in larger, clinically diverse T1D cohorts.
Abstract Introduction Several biomarkers are emerging in heart failure (HF), although their prognostic value remains incompletely defined. Growth differentiation factor-15 (GDF-15) has attracted interest as a stress-responsive cytokine linked to inflammation and oxidative stress. This study evaluated the prognostic role of GDF-15 regarding the risk of HF rehospitalisation in patients admitted with acute heart failure with reduced ejection fraction (HFrEF). Purpose To assess the association between admission GDF-15 concentrations and HF readmission in acute HFrEF. Methods We conducted a prospective, single-centre study including 104 patients with acute HFrEF. Serum and plasma samples were collected at admission after informed consent. Multiple biomarkers were analysed, including GDF-15. Univariable Cox regression was performed to evaluate associations with HF rehospitalisation. Discriminative capacity was assessed using receiver operating characteristic (ROC) curves, from which predictive cut-off values were derived. Results Among the 104 included patients (78% male; mean age 66.7 years), the mean left ventricular ejection fraction was 21%. At the end of follow-up, 90% were receiving beta-blockers, 87% ACE inhibitors/angiotensin receptor blockers/angiotensin receptor–neprilysin inhibitors, 74% mineralocorticoid receptor antagonists, and 72% sodium–glucose co-transporter-2 inhibitors (Table 1). After a median follow-up of 23.5 months, 21 HF readmissions were recorded. GDF-15 was significantly associated with rehospitalisation for HF (HR 1.22, 95% CI 1.07–1.38) with an AUC of 0.62, higher than that of NT-proBNP for this outcome (AUC 0.44). Using 10.9 ng/ml as the cut-off, sensitivity was 14%, specificity 98.8%, negative predictive value 75%, and positive predictive value 82%, with a prevalence of 19.2%. ROC curves for NT-proBNP and GDF-15 are presented in the figure 1. Conclusion GDF-15 demonstrated acceptable prognostic value for HF rehospitalisation in patients with acute HFrEF and outperformed NT-proBNP for this endpoint. Larger studies are warranted to validate these findings and to clarify the role of GDF-15 across different patient subgroups.Table 1.Baseline characteristicsFor image description, please refer to the figure legend and surrounding text.Figure1Predictive capacity for admissionFor image description, please refer to the figure legend and surrounding text.
