Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number.

Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician's office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen's κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.

A Disconnection for Rapid Access to Heterocyclic Benzylic Amines with Fully Substituted α-Carbons.

2- or 4-Pyridyl benzylic amines represent a privileged motif in drug discovery. However, the formation of heterocyclic benzylic amines with fully substituted α-carbons can require the execution of lengthy synthetic routes, which limit their application. Addition of various nucleophilic agents to Ellman's imines has been well established; however, there is no precedented literature reported for pyridyl-type nucleophiles, which are very important for medicinal chemistry. In this letter, we disclose the development of a one-step synthesis of heterocyclic benzylic amines with fully substituted α-carbons from heteroaryl halides and sulfinyl imines. Starting from 2,4-dibromopyridine, regioselective synthesis of 2- or 4-pyridyl benzylic amines could be achieved by choosing toluene or MTBE as a solvent.

Recurrent TRAK1::RAF1 Fusions in pediatric low-grade gliomas.

Fusions involving CRAF (RAF1) are infrequent oncogenic drivers in pediatric low-grade gliomas, rarely identified in tumors bearing features of pilocytic astrocytoma, and involving a limited number of known fusion partners. We describe recurrent TRAK1::RAF1 fusions, previously unreported in brain tumors, in three pediatric patients with low-grade glial-glioneuronal tumors. We present the associated clinical, histopathologic and molecular features. Patients were all female, aged 8 years, 15 months, and 10 months at diagnosis. All tumors were located in the cerebral hemispheres and predominantly cortical, with leptomeningeal involvement in 2/3 patients. Similar to previously described activating RAF1 fusions, the breakpoints in RAF1 all occurred 5' of the kinase domain, while the breakpoints in the 3' partner preserved the N-terminal kinesin-interacting domain and coiled-coil motifs of TRAK1. Two of the three cases demonstrated methylation profiles (v12.5) compatible with desmoplastic infantile ganglioglioma (DIG)/desmoplastic infantile astrocytoma (DIA) and have remained clinically stable and without disease progression/recurrence after resection. The remaining tumor was non-classifiable; with focal recurrence 14 months after initial resection; the patient remains symptom free and without further recurrence/progression (5 months post re-resection and 19 months from initial diagnosis). Our report expands the landscape of oncogenic RAF1 fusions in pediatric gliomas, which will help to further refine tumor classification and guide management of patients with these alterations.

Clinical outcome of pediatric medulloblastoma patients with Li-Fraumeni syndrome.

BACKGROUND: The prognosis for Li-Fraumeni syndrome (LFS) patients with medulloblastoma (MB) is poor. Comprehensive clinical data for this patient group is lacking, challenging the development of novel therapeutic strategies. Here, we present clinical and molecular data on a retrospective cohort of pediatric LFS MB patients. METHODS: In this multinational, multicenter retrospective cohort study, LFS patients under 21 years with MB and class 5 or class 4 constitutional TP53 variants were included. TP53 mutation status, methylation subgroup, treatment, progression free- (PFS) and overall survival (OS), recurrence patterns, and incidence of subsequent neoplasms were evaluated. RESULTS: The study evaluated 47 LFS individuals diagnosed with MB, mainly classified as DNA methylation subgroup "SHH_3" (86%). The majority (74%) of constitutional TP53 variants represented missense variants. The 2- and 5-year (y-) PFS were 36% and 20%, and 2- and 5y-OS were 53% and 23%, respectively. Patients who received postoperative radiotherapy (RT) (2y-PFS: 44%, 2y-OS: 60%) or chemotherapy before RT (2y-PFS: 32%, 2y-OS: 48%) had significantly better clinical outcome then patients who were not treated with RT (2y-PFS: 0%, 2y-OS: 25%). Patients treated according to protocols including high-intensity chemotherapy and patients who received only maintenance-type chemotherapy showed similar outcomes (2y-PFS: 42% and 35%, 2y-OS: 68% and 53%, respectively). CONCLUSIONS: LFS MB patients have a dismal prognosis. In the presented cohort use of RT significantly increased survival rates, whereas chemotherapy intensity did not influence their clinical outcome. Prospective collection of clinical data and development of novel treatments are required to improve the outcome of LFS MB patients.

Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study.

BACKGROUND: Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. OBJECTIVE: Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS: We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses. RESULTS: Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with "increased motor activity" (NMI>0.55), "insomnia" (NMI=0.6), and "motor inhibition" (NMI=0.75). EDA was associated with "aggressive behavior" (NMI=1.0) and "psychic anxiety" (NMI=0.52). CONCLUSIONS: Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.

Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols.

Vast quantities of Magnetic Resonance Images (MRI) are routinely acquired in clinical practice but, to speed up acquisition, these scans are typically of a quality that is sufficient for clinical diagnosis but sub-optimal for large-scale precision medicine, computational diagnostics, and large-scale neuroimaging collaborative research. Here, we present a critic-guided framework to upsample low-resolution (often 2D) MRI full scans to help overcome these limitations. We incorporate feature-importance and self-attention methods into our model to improve the interpretability of this study. We evaluate our framework on paired low- and high-resolution brain MRI structural full scans (i.e., T1-, T2-weighted, and FLAIR sequences are simultaneously input) obtained in clinical and research settings from scanners manufactured by Siemens, Phillips, and GE. We show that the upsampled MRIs are qualitatively faithful to the ground-truth high-quality scans (PSNR = 35.39; MAE = 3.78E-3; NMSE = 4.32E-10; SSIM = 0.9852; mean normal-appearing gray/white matter ratio intensity differences ranging from 0.0363 to 0.0784 for FLAIR, from 0.0010 to 0.0138 for T1-weighted and from 0.0156 to 0.074 for T2-weighted sequences). The automatic raw segmentation of tissues and lesions using the super-resolved images has fewer false positives and higher accuracy than those obtained from interpolated images in protocols represented with more than three sets in the training sample, making our approach a strong candidate for practical application in clinical and collaborative research.

YAP1-MAML2 fusion in a pediatric NF2-wildtype intraparenchymal brainstem schwannoma.

Biallelic inactivation of NF2 represents the primary or sole oncogenic driver event in the vast majority of schwannomas. We report on a four-year-old female who underwent subtotal resection of a right medullary intraparenchymal schwannoma. RNA sequencing revealed an in-frame fusion between exon 5 of YAP1 and exon 2 of MAML2. YAP1-MAML2 fusions have previously been reported in a variety of tumor types, but not schwannomas. Our report expands the spectrum of oncogenic YAP1 gene fusions an alternative to NF2 inactivation to include sporadic schwannoma, analogous to what has recently been described in NF2-wildtype pediatric meningiomas. Appropriate somatic and germline molecular testing should be undertaken in all young patients with solitary schwannoma and meningioma given the high prevalence of an underlying tumor predisposition syndrome. In such patients, the identification of a somatic non-NF2 driver alteration such as this newly described YAP1 fusion, can help ascertain the diagnosis of a sporadic schwannoma.

Pediatric pineoblastoma: A pooled outcome study of North American and Australian therapeutic data.

Background: Pineoblastoma is a rare brain tumor usually diagnosed in children. Given its rarity, no pineoblastoma-specific trials have been conducted. Studies have included pineoblastoma accruing for other embryonal tumors over the past 30 years. These included only occasional children with pineoblastoma, making clinical features difficult to interpret and determinants of outcome difficult to ascertain. Patients and Methods: Centrally or independently reviewed series with treatment and survival data from North American and Australian cases were pooled. To investigate associations between variables, Fisher's exact tests, Wilcoxon-Mann-Whitney tests, and Spearman correlations were used. Kaplan-Meier plots, log-rank tests, and Cox proportional hazards models were used in survival analyses. Results: We describe a pooled cohort of 178 pineoblastoma cases from Children's Oncology Group (n = 82) and institutional series (n = 96) over 30 years. Children <3 years of age have significantly worse survival compared to older children, with 5-year progression-free survival (PFS) and overall survival (OS) estimates of 13.5 ± 5.1% and 16.2 ± 5.3%, respectively, compared with 60.8 ± 5.6% and 67.3 ± 5.0% for ≥3 years old (both P < .0001). Multivariable analysis showed male sex was associated with worse PFS in children <3 years of age (hazard ratio [HR] 3.93, 95% CI 1.80-8.55; P = .0006), suggestive of sex-specific risks needing future validation. For children ≥3 years of age, disseminated disease at diagnosis was significantly associated with an inferior 5-year PFS of 39.2 ± 9.7% (HR 2.88, 95% CI 1.52-5.45; P = .0012) and 5-year OS of 49.8 ± 9.1% (HR 2.87, 95% CI 1.49-5.53; P = .0016). Conclusion: Given the rarity of this tumor, prospective, collaborative international studies will be vital to improving the long-term survival of these patients.

3T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation.

Deep brain stimulation targeting the subcallosal cingulate area, a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While subcallosal cingulate deep brain stimulation drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 T functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of 12 patients with fully implanted deep brain stimulation devices targeting the subcallosal cingulate area. Four additional subcallosal cingulate deep brain stimulation patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n = 78 acquisitions overall) during (i) inactive deep brain stimulation; (ii) clinically optimal active deep brain stimulation; and (iii) suboptimal active deep brain stimulation. All scans were acquired within a single MRI session, each separated by a 5-min washout period. Analysis of the amplitude of low-frequency fluctuations in each sequence indicated that clinically optimal deep brain stimulation reduced spontaneous brain activity in several areas, including the bilateral dorsal anterior cingulate cortex, the bilateral posterior cingulate cortex, the bilateral precuneus and the left inferior parietal lobule (PBonferroni < 0.0001). Stimulation-induced dorsal anterior cingulate cortex signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings and was related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dorsal anterior cingulate cortex, posterior cingulate cortex and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated amplitude of low-frequency fluctuations changes in these three areas (along with preoperative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally, all three brain areas exhibited significant changes in functional connectivity between active and inactive deep brain stimulation states (PBonferroni < 0.01). These results provide insight into the network-level mechanisms of subcallosal cingulate deep brain stimulation and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.

Safety and tolerability of subcutaneous trastuzumab and intravenous pertuzumab as adjuvant treatment for HER2 positive breast cancer: a pilot study.

BACKGROUND: Subcutaneous (SC) trastuzumab is similar to intravenous trastuzumab in terms of pharmacokinetics, efficacy and tolerability. The use of dual anti-HER2 agents trastuzumab and pertuzumab has become the new standard for node-positive HER2-positive breast cancers at adjuvant setting, but the safety and tolerability of combining SC trastuzumab and intravenous pertuzumab is not well studied. METHODS: This was a prospective single-arm pilot study with locally advanced HER2-positive breast cancer who received adjuvant SC trastuzumab and intravenous pertuzumab after standard anti-HER2 treatment with chemotherapy. Primary outcomes included adverse events (AEs), severe AEs and cardiac AEs. Secondary outcome was invasive disease-free survival (iDFS). RESULTS: With a median follow-up of 21.7 months, 20 patients were enrolled. One patient (5%) developed asymptomatic drop in left ventricular ejection fraction from 69% to 53%. Two patients (10%) developed grade 1 injection site reaction related to SC trastuzumab. There were no grade 2 or above AEs. All AEs were transient. No new AEs were observed. The 1-year iDFS was 90% (95% CI 0.656 to 0.974). CONCLUSIONS: Combination of SC trastuzumab and intravenous pertuzumab for HER2-positive breast cancer is a safe and well-tolerated option in adjuvant setting.

Neoadjuvant Therapy with Concurrent Docetaxel, Epirubicin, and Cyclophosphamide (TEC) in High-Risk HER2-Negative Breast Cancers.

INTRODUCTION: Concurrent anthracycline and taxane is an effective and efficient way to deliver neoadjuvant chemotherapy for HER2-negative breast cancers. Data on efficacy and tolerance to 6 cycles of concurrent docetaxel, epirubicin, and cyclophosphamide (TEC) is limited. METHOD: All patients with HER2-negative breast cancers who received neoadjuvant TEC from January 2013 to December 2019 were reviewed. RESULTS: A total of 71 patients [57 luminal B disease; 14 triple negative breast cancer (TNBC)] received neoadjuvant TEC with prophylactic granulocyte colony-stimulating factor (G-CSF). The pathological complete response (pCR) rate was 26.3% and 28.6% for luminal B and TNBC, respectively. With median follow-up of 48.9 months, 3 years disease-free survival was 85.9%, and 3 years overall survival was 89.6%. Non-hematological toxicities were common but the majority was grade 1 or 2. The most common grade 3 or 4 toxicity were hematological, including neutropenia (26.8%) and anemia (15.5%). There was no cardiotoxicity observed. Half of the patients had at least one dose reduction but all patients completed the planned 6 cycles and had breast surgery done. CONCLUSION: Six cycles of TEC with prophylactic G-CSF is an effective and tolerable neoadjuvant regime for HER2-negative breast cancers. Hematological toxicities were the most common toxicities. Although many patients required dose reduction, all patients completed treatment and there was no observed cardiotoxicity.

Integrated palliative medicine in public oncology: a 10-year review.

OBJECTIVES: The rapid ageing population of Hong Kong has a high demand on oncology and palliative care (PC) service. This study was the first territory-wide assessment in Hong Kong to assess the palliative service coverage in patients with advanced cancer in the past decade. METHODS: Cancer deaths of all 43 public hospitals of Hong Kong were screened. Randomly selected 2800 cancer deaths formed a representative cohort in all seven service clusters of Hospital Authority at 4 time points (2006, 2009, 2012, 2015). Individual patient records were thoroughly reviewed. Predictors of PC coverage was evaluated in univariable and multivariable analyses. RESULTS: From 2006 to 2015, PC coverage improved steadily from 55.4% to 68.9% (p<0.001). Median time of referral to PC service to death was 25 days (IQR: 53). For duration of inpatient PC, the median time was 22 days (IQR: 44) and it was stable over the past 10 years. Median time of referral to outpatient service to death was 74 days (IQR: 144) and there was an improvement observed (p<0.05). The current system was highly heterogeneous that PC varied between 9.8% and 84.8% in different hospitals depending on the PC service infrastructure. Multivariable Cox model identified patients associated with lower PC coverage: male, <50, rapid disease deterioration and staying in hospitals without multidisciplinary team clinic and designated palliative bed support (all p<0.01). CONCLUSION: There was concrete achievement in palliative service development in the past decade. Heterogeneity and late service provision should be addressed in future.

The Outcomes of Systemic Treatment in Recurrent Hepatocellular Carcinomas Following Liver Transplants.

BACKGROUND: Treatment of hepatocellular carcinoma (HCC) recurrences following liver transplant (LT) is challenging. Most clinical trials of systemic therapies for advanced HCC excluded patients with any history of organ transplant. We aimed to assess the outcomes in using various systemic therapies in patients with post-LT recurrence. METHODS: Consecutive patients with HCC and recurrences following LT at a large tertiary centre from 2005 to 2018 were reviewed. Overall survival (OS), response rates and adverse events (AEs) were analysed. RESULTS: Forty-three consecutive patients with a recurrence of HCC following LT were identified from 2005 to 2018. Median OS from diagnosis of recurrence was 17 months (CI 11.3, 22.7). Early recurrence within 12 months of transplant was associated with a significantly worse median survival of 10 months (CI 8.5, 11.4) compared to 26 months (CI 18.8, 33.2) when recurrences occurred after 12 months from transplant (p < 0.001) with a hazard ratio of 0.104 (log-rank test, p < 0.001). A total of 41 patients had received systemic therapies and 79.1% of them were on sorafenib as the first-line treatment. Among these patients treated with sorafenib, median OS from recurrence was 14 months (CI 7.3, 20.7). Hand-foot syndrome (34.7%) was most common among AEs followed by diarrhoea (26.7%). Overall, AEs led to dose interruptions in 8.8% of patients. Notably, 47.1% of patients received subsequent lines of systemic therapies after sorafenib. CONCLUSIONS: Early recurrence within 1 year from transplant was the most significant risk factor. Treatment efficacy and adverse events and tolerability of sorafenib were comparable with those in the setting of advanced HCC without transplant.

Predicting optimal deep brain stimulation parameters for Parkinson's disease using functional MRI and machine learning.

Commonly used for Parkinson's disease (PD), deep brain stimulation (DBS) produces marked clinical benefits when optimized. However, assessing the large number of possible stimulation settings (i.e., programming) requires numerous clinic visits. Here, we examine whether functional magnetic resonance imaging (fMRI) can be used to predict optimal stimulation settings for individual patients. We analyze 3 T fMRI data prospectively acquired as part of an observational trial in 67 PD patients using optimal and non-optimal stimulation settings. Clinically optimal stimulation produces a characteristic fMRI brain response pattern marked by preferential engagement of the motor circuit. Then, we build a machine learning model predicting optimal vs. non-optimal settings using the fMRI patterns of 39 PD patients with a priori clinically optimized DBS (88% accuracy). The model predicts optimal stimulation settings in unseen datasets: a priori clinically optimized and stimulation-naïve PD patients. We propose that fMRI brain responses to DBS stimulation in PD patients could represent an objective biomarker of clinical response. Upon further validation with additional studies, these findings may open the door to functional imaging-assisted DBS programming.

The Use of Cabozantinib in Advanced Hepatocellular Carcinoma in Hong Kong-A Territory-Wide Cohort Study.

(1) Background: Cabozantinib is approved in sorafenib-exposed advanced hepatocellular carcinoma (aHCC). We evaluated the real-life pattern of use, efficacy, and tolerability of cabozantinib in aHCC. (2) Methods: This territory-wide study included consecutive aHCC patients who received cabozantinib between February 2018 and September 2020 in Hong Kong. The objective response rate (ORR), disease control rate (DCR), overall survival (OS), and adverse events (AE) were assessed. (3) Results: Overall, 42 patients were included. Approximately 83.3% had Child-Pugh A cirrhosis. About 64.3% received cabozantinib as a single agent, and the remaining 35.7% received cabozantinib as an add-on to immune checkpoint inhibitors (ICIs). For single-agent patients, the median follow-up was 6.7 months. The ORR was 3.7%, DCR was 44.4%, and the median OS was 8.28 months. About 74.1% of patients experienced any AEs with 7.4% having grade ≥3 AEs. Among patients who received prior ICIs (n = 16), the ORR was 6.3%, and the median OS was 8.28 months. An exploratory analysis of patients who received cabozantinib as an add-on to ICIs showed an ORR of 6.7% and a median OS of 15.1 months, with 73.3% having any AE and 13.3% having grade ≥3 AEs. (4) Conclusions: Cabozantinib had good anti-tumor activity, survival benefits, and acceptable tolerability in real-life aHCC patients.

Recent Advances and Future Prospects in Immune Checkpoint (ICI)-Based Combination Therapy for Advanced HCC.

Advanced, unresectable hepatocellular carcinoma has a dismal outcome. Multiple immune checkpoint inhibitors (ICIs) targeting the programmed-cell death 1 pathway (PD-1/L1) have been approved for the treatment of advanced HCC. However, outcomes remain undesirable and unpredictable on a patient-to-patient basis. The combination of anti-PD-1/L1 with alternative agents, chiefly cytotoxic T-lymphocyte antigen-4 (CTLA-4) ICIs or agents targeting other oncogenic pathways such as the vascular endothelial growth factor (VEGF) pathway and the c-MET pathway, has, in addition to the benefit of directly targeting alterative oncogenic pathways, in vitro evidence of synergism through altering the genomic and function signatures of T cells and expression of immune checkpoints. Several trials have been completed or are underway evaluating such combinations. Finally, studies utilizing transcriptomics and organoids are underway to establish biomarkers to predict ICI response. This review aims to discuss the biological rationale and clinical advances in ICI-based combinations in HCCs, as well as the progress and prospects of the search for the aforementioned biomarkers in ICI treatment of HCC.

Nivolumab + Ipilimumab for patients with hepatocellular carcinoma previously treated with Sorafenib.

INTRODUCTION: The systemic treatment of advanced, unresectable hepatocellular carcinoma (HCC) has undergone an evolution in recent years. In March 2020, a combination of nivolumab and ipilimumab was approved by the FDA for treatment of patients with advanced HCC who received prior sorafenib. This was based on the results of the phase I/II CheckMate-040 cohort 4 trials, which showed a promising overall response rate and encouraging overall survival with a manageable safety profile. AREAS COVERED: This article reviews the pharmacology, efficacy and safety of nivolumab-ipilimumab in advanced HCC with prior sorafenib. Other existing systemic treatment options for advanced HCC will be described and compared to nivolumab-ipilimumab. Impact of different dose regimes, ongoing research and future developments of nivolumab-ipilimumab will be discussed. We focus on the analysis from the aforementioned CheckMate-040 cohort 4 registration trial. EXPERT OPINION: The approval of nivolumab-ipilimumab in the second-line treatment of advanced HCC by the FDA is an important development for treatment of advanced HCC. However, further investigations are needed to optimize dosing regimens and explore the use of nivolumab-ipilimumab in other combinations and settings.

Clinical and molecular heterogeneity of pineal parenchymal tumors: a consensus study.

Recent genomic studies have shed light on the biology and inter-tumoral heterogeneity underlying pineal parenchymal tumors, in particular pineoblastomas (PBs) and pineal parenchymal tumors of intermediate differentiation (PPTIDs). Previous reports, however, had modest sample sizes and lacked the power to integrate molecular and clinical findings. The different proposed molecular group structures also highlighted a need to reach consensus on a robust and relevant classification system. We performed a meta-analysis on 221 patients with molecularly characterized PBs and PPTIDs. DNA methylation profiles were analyzed through complementary bioinformatic approaches and molecular subgrouping was harmonized. Demographic, clinical, and genomic features of patients and samples from these pineal tumor groups were annotated. Four clinically and biologically relevant consensus PB groups were defined: PB-miRNA1 (n = 96), PB-miRNA2 (n = 23), PB-MYC/FOXR2 (n = 34), and PB-RB1 (n = 25). A final molecularly distinct group, designated PPTID (n = 43), comprised histological PPTID and PBs. Genomic and transcriptomic profiling allowed the characterization of oncogenic drivers for individual tumor groups, specifically, alterations in the microRNA processing pathway in PB-miRNA1/2, MYC amplification and FOXR2 overexpression in PB-MYC/FOXR2, RB1 alteration in PB-RB1, and KBTBD4 insertion in PPTID. Age at diagnosis, sex predilection, and metastatic status varied significantly among tumor groups. While patients with PB-miRNA2 and PPTID had superior outcome, survival was intermediate for patients with PB-miRNA1, and dismal for those with PB-MYC/FOXR2 or PB-RB1. Reduced-dose CSI was adequate for patients with average-risk, PB-miRNA1/2 disease. We systematically interrogated the clinical and molecular heterogeneity within pineal parenchymal tumors and proposed a consensus nomenclature for disease groups, laying the groundwork for future studies as well as routine use in tumor diagnostic classification and clinical trial stratification.

Thyroid Immune-Related Adverse Events in Patients with Cancer Treated with anti-PD1/anti-CTLA4 Immune Checkpoint Inhibitor Combination: Clinical Course and Outcomes.

OBJECTIVE: Thyroid immune-related adverse events (irAEs) have been reported to have prognostic significance among patients with cancer treated with anti-programmed cell death-1 (PD1) and anti-programmed death-ligand 1 monotherapies. We evaluated the clinical course and predictors of thyroid irAEs in relation to outcomes of patients with advanced cancer treated with combination anti-PD1/anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA4). METHODS: We conducted a regional study and identified patients with advanced cancer who received ≥1 cycle of combination anti-PD1/anti-CTLA4 between 2015 and 2019 in Hong Kong. Thyroid function tests (TFTs) were monitored every 3 weeks. Thyroid irAE was defined by ≥2 abnormal TFTs after initiation of combination anti-PD1/anti-CTLA4 in the absence of other causes. RESULTS: One hundred and three patients were included (median age: 59 years; 71.8% men). About 45% had prior anti-PD1 exposure. Upon median follow-up of 6.8 months, 17 patients (16.5%) developed thyroid irAEs, where 6 initially presented with thyrotoxicosis (overt, n = 4; subclinical, n = 2) and 11 with hypothyroidism (overt, n = 2; subclinical, n = 9). Eventually, 10 patients (58.8%) required continuous thyroxine replacement. Systemic steroid was not required in all cases. Prior anti-PD1 exposure (odds ratio, 3.67; 95% CI, 1.19-11.4; P = .024) independently predicted thyroid irAEs. Multivariable Cox regression analysis revealed that occurrence of thyroid irAEs was independently associated with better overall survival (adjusted hazard ratio, 0.34; 95% CI, 0.17-0.71; P = .004). CONCLUSION: Thyroid irAEs are common in routine clinical practice among patients with advanced cancer treated with anti-PD1/anti-CTLA4 combination and might have potential prognostic significance. Regular TFT monitoring is advised for timely treatment of thyroid irAEs to prevent potential morbidities.