Interaction Structures in Psychodynamic Psychotherapy for Adolescents

Despite advances in psychotherapy research showing an evidence-base for psychodynamic psychotherapy (PDT) in adolescents, developmentally specific treatment characteristics are under-researched. We aimed to identify interaction structures (IS: reciprocal patterns of in-session interactions involving therapist interventions, patient behaviors, and the therapeutic relationship) and assess associations between IS and outcome. The study cohort comprised 43 adolescents (Mage = 13.02 years) with nonclinical, internalizing, and comorbid internalizing–externalizing problems in PDT. A total of 123 sessions from different treatment phases were rated based on the Adolescent Psychotherapy Q-Set (APQ). Outcome was assessed with the Brief Problem Monitor-Youth (BPM-Y) administered repeatedly over the treatment course. Principal component analysis of APQ items resulted in five IS, named “Negative Therapeutic Alliance”, “Demanding Patient, Accommodating Therapist”, “Emotionally Distant Resistant Patient”, “Inexpressive Patient, Inviting Therapist”, and “Exploratory Psychodynamic Technique” (EPT). Multilevel modeling analyses with Bayesian Markov chain Monte Carlo (MCMC) estimations indicated a two-way interaction effect between EPT and problem levels at baseline such that patients with lower problems at baseline showed good outcome in the context of EPT, whereas an inverse relationship was found for patients with higher problems. Findings provide empirical evidence for characteristic components of PDT for adolescents and preliminary answers about who benefits from psychodynamic techniques.

Halofuginone Sensitizes Lung Cancer Organoids to Cisplatin via Suppressing PI3K/AKT and MAPK Signaling Pathways

Lung cancer is the leading cause of cancer death worldwide. Cisplatin is the major DNA-damaging anticancer drug that cross-links the DNA in cancer cells, but many patients inevitably develop resistance with treatment. Identification of a cisplatin sensitizer might postpone or even reverse the development of cisplatin resistance. Halofuginone (HF), a natural small molecule isolated from Dichroa febrifuga, has been found to play an antitumor role. In this study, we found that HF inhibited the proliferation, induced G0/G1 phase arrest, and promoted apoptosis in lung cancer cells in a dose-dependent manner. To explore the underlying mechanism of this antitumor effect of halofuginone, we performed RNA sequencing to profile transcriptomes of NSCLC cells treated with or without halofuginone. Gene expression profiling and KEGG analysis indicated that PI3K/AKT and MAPK signaling pathways were top-ranked pathways affected by halofuginone. Moreover, combination of cisplatin and HF revealed that HF could sensitize the cisplatin-resistant patient-derived lung cancer organoids and lung cancer cells to cisplatin treatment. Taken together, this study identified HF as a cisplatin sensitizer and a dual pathway inhibitor, which might provide a new strategy to improve prognosis of patients with cisplatin-resistant lung cancer.

DDRE-06. TARGETING THE SPHINGOLIPID BALANCE VIA ACID CERAMIDASE INHIBITION TO DECREASE GROWTH OF TMZ-RESISTANT GLIOBLASTOMA AND BLOCK MIGRATION

Dysregulated sphingolipid metabolism is associated with many cancers; allowing cells to evade apoptosis through increases in sphingosine-1-phosphate (S1P) and decreases in ceramides. Ceramides can be hydrolyzed by ceramidases to sphingosine, which can then be phosphorylated by sphingosine kinases to S1P. S1P allows cells to evade apoptosis and increase migration, while shifts toward ceramides favor cell death. Glioblastoma (GBM) exhibits shifts in the sphingolipid balance towards S1P, contributing to chemoresistance and migration. Understanding of sphingolipid metabolism in GBM is still limited, and currently, there are no approved treatments to target the dysregulation. Acid ceramidase (ASAH1), a key enzyme in the production of S1P, is highly expressed in GBM and is associated with worse survival of GBM patients, as per The Cancer Genome Atlas data. To address the altered sphingolipid metabolism and therapeutic resistance in GBM, we explored the efficacy of pharmacologic and genetic inhibition of ASAH1 in both parental and temozolomide (TMZ)-resistant patient-derived xenografts. Cells were infected with ASAH1 shRNA or treated with ASAH1 inhibitors and assessed for cell growth and migration. Our work suggests that pharmacologic inhibition of ASAH1 induces cell death and that this effect is maintained in TMZ-resistant cells. Furthermore, we find a novel role for carmofur, an ASAH1 inhibitor, in the inhibition of GBM migration. Together, these data suggest the potential utility of normalizing the sphingolipid balance in the context of GBM TMZ resistance.

EXPLORING ALEXITHYMIA IN SOMATIZATION USING RORSCHACH PSYCHODIAGNOSTICS

It has been classically postulated that alexithymia is related to a pervasive inability of emotional recognition and expression. This leaves some individuals little choice but to somatise unprocessed emotions commonly caused by internal conflicts. The present study thus aimed to explore the nature of conflicts, controls and stress tolerance, affect, self-perception, and interpersonal perception and behavior in somatization patients with alexithymia. 30 individuals of both sexes and of the age range 20-50 years, diagnosed with somatization disorder and alexithymia, were purposively undertaken for the study. Toronto Alexithymia Scale 20, Sack’s Sentence Completion Test and the Rorschach Test – Exner’s Comprehensive System were used to screen for alexithymia, to measure conflicts and the other aforementioned domains respectively. Results revealed that conflicts related to self-concept, sex, and family were primarily present in this sample. Characteristic patterns of underlying vulnerabilities seemed to account for poor stress tolerance, affective complications, negative self-perception, and maladaptive interpersonal functioning. It is suggested that alexithymia and a tendency to develop conflicts in somatization are based on the foundation of certain fundamental personality predispositions. Identifying said personality patterns could aid in appropriate and effective goal-setting in psychotherapy, specific to this otherwise treatment-resistant patient population.

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi-gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support Vector Machine learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology-based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway-extended support vector machines predicted responses in patients at accuracies of 70% (imatinib), 71% (lapatinib), 83% (sunitinib), 83% (erlotinib), 88% (sorafenib) and 91% (gefitinib). These best performing pathway-extended models demonstrated improved balance predicting both sensitive and resistant patient categories, with many of these genes having a known role in cancer etiology. Ensemble machine learning-based averaging of multiple pathway-extended models derived for an individual drug increased accuracy to >70% for erlotinib, gefitinib, lapatinib, and sorafenib. Through incorporation of novel cancer biomarkers, machine learning-based pathway-extended signatures display strong efficacy predicting both sensitive and resistant patient responses to chemotherapy.