Citations

Anticipating and understanding cancers’ need for specific gene activities is key for novel therapeutic development. Here we utilized DepMap, a cancer gene dependency screen, to demonstrate that machine learning combined with network biology can produce robust algorithms that both predict what genes a cancer is dependent on and what network features coordinate such gene dependencies. Using network topology and biological annotations, we constructed four groups of novel engineered machine learning features that produced high accuracies when predicting binary gene dependencies. We found that in all examined cancer types, F1 scores were greater than 0.90, and model accuracy remained robust under multiple hyperparameter tests. We then deconstructed these models to identify tumor type-specific coordinators of gene dependency and identified that in certain cancers, such as thyroid and kidney, tumors’ dependencies are highly predicted by gene connectivity. In contrast, other histologies relied on pathway-based features such as lung, where gene dependencies were highly predictive by associations with cell death pathway genes. In sum, we show that biologically informed network features can be a valuable and robust addition to predictive pharmacology models while simultaneously providing mechanistic insights.

Abstract Background and purpose Outcome and rechallenge data on central nervous system (CNS) autoimmunity triggered by immune checkpoint inhibitors (ICIs) are limited. We aim to describe a large series of patients with ICI‐triggered CNS autoimmunity, and to compare these patients with spontaneous paraneoplastic syndromes (PNS). Methods We retrospectively reviewed Mayo Clinic patients with ICI‐triggered CNS autoimmunity (February 2015–June 2021). Clinical characteristics were compared to spontaneous PNS patients (with antineuronal nuclear antibody [ANNA]‐1 or anti‐Hu neurological autoimmunity, and/or neuroendocrine tumors [NET]) evaluated within the same period. Results Thirty‐one patients were included (55% female, median age = 63 years, range = 39–76). Median time from ICI initiation was 3.65 months (range = 0.8–44.5). The most common associated malignancies were melanoma and small cell lung cancer. CNS manifestations included encephalitis ( n = 16), meningoencephalitis ( n = 8), cerebellar ataxia ( n = 4), demyelinating syndrome ( n = 2), and myelopathy ( n = 1). Magnetic resonance imaging was abnormal in 62%. Cerebrospinal fluid was inflammatory in 70%. Neural autoantibodies were identified in 47%, more frequently in patients with NET ( p = 0.046). ICI was discontinued in 97%; 90% received immunosuppressive treatment. After median 6.8 months follow‐up (range = 0.7–46), 39% had unfavorable outcomes (grade ≥ 3). This was associated with higher severity degree at onset, shorter period from ICI to neurological symptom onset, and encephalitis. Four patients were rechallenged with ICI, and one relapsed. Patients with NET and with ANNA‐1 ICI‐triggered CNS autoimmunity had associated peripheral nervous system manifestations more frequently than their spontaneous counterparts ( p = 0.007 and p = 0.028, respectively). Conclusions One third of ICI‐related CNS autoimmunity patients have unfavorable outcomes. Relapses may occur after ICI rechallenge. Neural autoantibodies are often present, more commonly in patients with NET.

Abstract Transmembrane protein 106B (TMEM106B) is a tightly regulated glycoprotein predominantly localized to endosomes and lysosomes. Genetic studies have implicated TMEM106B haplotypes in the development of multiple neurodegenerative diseases with the strongest effect in frontotemporal lobar degeneration with TDP-43 pathology (FTLD-TDP), especially in progranulin (GRN) mutation carriers. Recently, cryo-electron microscopy studies showed that a C-terminal fragment (CTF) of TMEM106B (amino acid residues 120–254) forms amyloid fibrils in the brain of patients with FTLD-TDP, but also in brains with other neurodegenerative conditions and normal ageing brain. The functional implication of these fibrils and their relationship to the disease-associated TMEM106B haplotype remain unknown. We performed immunoblotting using a newly developed antibody to detect TMEM106B CTFs in the sarkosyl-insoluble fraction of post-mortem human brain tissue from patients with different proteinopathies (n = 64) as well as neuropathologically normal individuals (n = 10) and correlated the results with age and TMEM106B haplotype. We further compared the immunoblot results with immunohistochemical analyses performed in the same study population. Immunoblot analysis showed the expected ∼30 kDa band in the sarkosyl-insoluble fraction of frontal cortex tissue in at least some individuals with each of the conditions evaluated. Most patients with GRN mutations showed an intense band representing TMEM106B CTF, whereas in most neurologically normal individuals it was absent or much weaker. In the overall cohort, the presence of TMEM106B CTFs correlated strongly with both age (rs = 0.539, P < 0.001) and the presence of the TMEM106B risk haplotype (rs = 0.469, P < 0.001). Although there was a strong overall correlation between the results of immunoblot and immunohistochemistry (rs = 0.662, P < 0.001), 27 cases (37%) were found to have higher amounts of TMEM106B CTFs detected by immunohistochemistry, including most of the older individuals who were neuropathologically normal and individuals who carried two protective TMEM106B haplotypes. Our findings suggest that the formation of sarkosyl-insoluble TMEM106B CTFs is an age-related feature which is modified by TMEM106B haplotype, potentially underlying its disease-modifying effect. The discrepancies between immunoblot and immunohistochemistry in detecting TMEM106B pathology suggests the existence of multiple species of TMEM106B CTFs with possible biological relevance and disease implications.

Abstract Aims Tricuspid valve regurgitation (TR) is a common valvular disease associated with increased mortality. There is a need for tools to assess the interaction between the pulmonary artery (PA) circulation and the right ventricle in patients with TR and to investigate their association with outcomes. The pulmonary artery pulsatility index (PAPi) has emerged as a haemodynamic risk predictor in left heart disease and pulmonary hypertension (PH). Whether PAPi discriminates risk in unselected patients with greater than or equal to moderate TR is unknown. Methods and results In 5079 patients with greater than or equal to moderate TR (regardless of aetiology) and PA systolic and diastolic pressures measured on their first echocardiogram, we compared all-cause mortality at 5 years based on the presence or absence of PH and PAPi levels. A total of 2741 (54%) patients had PH. The median PAPi was 3.0 (IQR 1.9, 4.4). Both the presence of PH and decreasing levels of PAPi were associated with larger right ventricles, worse right ventricular systolic function, higher NT-pro BNP levels, greater degrees of right heart failure, and worse survival. In a subset of patients who had an echo and right heart catheterization within 24 h, the correlation of non-invasive to invasive PA pressures and PAPi levels was very good (r = 0.76). Conclusion In patients with greater than or equal to moderate TR with and without PH, lower PAPi is associated with right ventricular dysfunction, right heart failure, and worse survival. Incorporating PA pressure and PAPi may help stratify disease severity in patients with greater than or equal to moderate TR regardless of aetiology.