Biology subjects

Fineberg, S.

Publications and source records attributed to Fineberg, S..

4 recordsLinked to original sources

bioRxiv2025

Quiescent OXPHOS-high triple-negative breast cancer cells that persist after chemotherapy depend on BCL-XL for survival

The persistent residual tumor cells that survive after chemotherapy are a major cause of treatment failure, but their survival mechanisms remain largely elusive. These cancer cells are typically characterized by a quiescent state with suppressed activity of MYC and MTOR. We observed that the MYC-suppressed persistent triple-negative breast cancer (TNBC) cells are metabolically flexible and can upregulate mitochondrial oxidative phosphorylation (OXPHOS) genes and respiratory function ("OXPHOS-high" cell state) in response to DNA-damaging anthracyclines such as doxorubicin, but not to taxanes. The elevated biomass and respiratory function of mitochondria in OXPHOS-high persistent cancer cells were associated with mitochondrial elongation and remodeling suggestive of increased mitochondrial fusion. A genome-wide CRISPR editing screen in doxorubicin-persistent OXPHOS-high TNBC cells revealed BCL-XL gene as the top survival dependency in these quiescent tumor cells, but not in their untreated proliferating counterparts. Quiescent OXPHOS-high TNBC cells were highly sensitive to BCL-XL inhibitors, but not to inhibitors of BCL2 and MCL1. Interestingly, inhibition of BCL-XL in doxorubicin-persistent OXPHOS-high TNBC cells rapidly abrogated mitochondrial elongation and respiratory function, followed by caspase 3/7 activation and cell death. The platelet-sparing proteolysis targeted chimera (PROTAC) BCL-XL degrader DT2216 enhanced the efficacy of doxorubicin against TNBC xenografts in vivo without induction of thrombocytopenia that is often observed with the first-generation BCL-XL inhibitors, supporting the development of this combinatorial treatment strategy for eliminating dormant tumor cells that persist after treatment with anthracycline-based chemotherapy.

cancer biology↗

bioRxiv2022

Ketamine induces multiple individually distinct whole-brain functional connectivity signatures

BackgroundKetamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamines molecular mechanisms connect to its neural and behavioral effects. MethodsWe conducted a double-blind placebo-controlled study in which 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hour). We quantified resting-state functional connectivity via data-driven global brain connectivity, related it to individual ketamine-induced symptom variation, and compared it to cortical gene expression targets. ResultsWe found that: i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; ii) ketamines data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, implicating the role of SST and PVALB interneurons in ketamines acute effects; and iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level. ConclusionsCollectively, these findings support the possibility for developing individually precise pharmacological biomarkers for treatment selection in psychiatry. FundingThis study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1-190420); Swiss Neuromatrix Foundation (Grant No. 2016-0111m Grant No. 2015 - 010); Swiss National Science Foundation under the frame-work of Neuron Cofund (Grant No. 01EW1908), Usona Institute (2015 - 2056).

neuroscience↗

bioRxiv2020

The Effect of a Ketogenic Diet and Synergy with Rapamycin in a Mouse Model of Breast Cancer.

BackgroundThe effects of diet in cancer, in general, and breast cancer in particular, are not well understood. Insulin inhibition in ketogenic, high fat diets, modulate downstream signaling molecules and are postulated to have therapeutic benefits. Obesity and diabetes have been associated with higher incidence of breast cancer. Addition of anti-cancer drugs together with diet is also not well studied. MethodsTwo diets, one ketogenic, the other standard mouse chow, were tested in a spontaneous breast cancer model in mice. The diets were implemented either with or without added rapamycin, an mTOR inhibitor and potential anti-cancer drug. ResultsBlood glucose and insulin concentrations in mice ingesting the ketogenic diet (KD) were significantly lower, whereas beta hydroxybutyrate (BHB) levels were significantly higher, respectively, than in mice on the standard diet (SD). Growth of primary breast tumors and lung metastases were inhibited, and lifespans were longer in the KD mice compared to mice on the SD (p<0.005). Rapamycin improved survival in both mouse diet groups, but when combined with the KD was more effective than when combined with the SD. ConclusionsThe study provides proof of principle that a ketogenic diet a) results in serum insulin reduction and ketosis in a spontaneous breast cancer mouse model; b) can serve as a therapeutic anti-cancer agent; and c) can enhance the effects of rapamycin, an anti-cancer drug, permitting dose reduction for comparable effect. Further, the ketogenic diet in this model produces superior cancer control than standard mouse chow whether with or without added rapamycin.

cancer biology↗

bioRxiv2018

Amazon Mechanical Turk as a platform for borderline personality disorder research

Researchers investigating the psychological processes underlying specific mental health problems often have difficulties achieving large enough samples for adequately powered studies. This can be particularly problematic when studying psychopathology with low base rates in typical samples (i.e., undergraduate and community). A relatively new approach to recruitment and testing employs online crowdsourcing to rapidly measure the characteristics and behavior of large numbers of people. We tested the feasibility of researching borderline personality disorder (BPD) in this manner using one large crowdsourcing site, Amazon Mechanical Turk (MTurk). Specifically, we examined prevalence rates of psychopathology in a large MTurk sample, as well as the demographic, psychosocial, and psychiatric characteristics of individuals who met criteria for BPD. These characteristics were compared across three groups: those who met criteria for BPD currently, those who met criteria for remitted BPD, and those who had never met criteria for BPD. The results suggest that MTurk may be ideally suited for studying individuals with a wide range of pathology, from healthy to intensely symptomatic to remitted.

animal behavior and cognition↗