Biology subjects

Montenegro, S.

Publications and source records attributed to Montenegro, S..

5 recordsLinked to original sources

bioRxiv2024

PIWIL1 is recruited to centrosomes during mitosis in Colorectal Cancer Cells and is linked to cell cycle progression.

PIWI proteins, traditionally associated with germline development, have recently gained attention for their expression in various cancers, including colorectal cancer (CRC). However, the molecular mechanisms underlying their reactivation and impact on cancer initiation and progression remain elusive. Here, we found that PIWIL1 is expressed at relatively high levels in CRC-derived samples and cell lines, where it undergoes a dynamic re-localization to the centrosome during mitosis. Knockdown of PIWIL1 induces G2/M arrest associated to disruption of mitotic spindle and aberrant metaphase events, highlighting its role in cell cycle progression. We have also found that expression of PIWIL1 is lost during differentiation of Caco-2 cells into enterocytes and that PIWIL1 is expressed in cells at the base of intestinal crypts in normal human colon tissue, where intestinal stem cells are known to reside. Thus, it is possible that the presence of PIWIL1 in cancer cells reflects a physiological role of this protein in stem cell maintenance, what would argue in favor of the proposed stem cell origin of CRC. Supporting this view, dedifferentiation of human fibroblasts into induced pluripotent stem cells (iPSc) implies reactivation of PIWIL2 expression, another member of the PIWI protein family. Overall, our findings suggest a role of PIWIL1 in mediating cell cycle dynamics, both in colorectal cancer cells and possibly also in intestinal stem cells. In a broader aspect, we provide support for an involvement of PIWI proteins in somatic stem cell maintenance, expanding nongonadal functions for this protein family.

cancer biology↗

bioRxiv2023

An adversarial collaboration to critically evaluate theories of consciousness

Different theories explain how subjective experience arises from brain activity1,2. These theories have independently accrued evidence, yet, confirmation bias and dependence on design choices hamper progress in the field3. Here, we present an open science adversarial collaboration which directly juxtaposes Integrated Information Theory (IIT)4,5 and Global Neuronal Workspace Theory (GNWT)6-10, employing a theory-neutral consortium approach11,12. We investigate neural correlates of the content and duration of visual experience. The theory proponents and the consortium developed and preregistered the experimental design, divergent predictions, expected outcomes, and their interpretation12. 256 human subjects viewed suprathreshold stimuli for variable durations while neural activity was measured with functional magnetic resonance imaging, magnetoencephalography, and electrocorticography. We find information about conscious content in visual, ventro-temporal and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas. These results confirm some predictions of IIT and GNWT, while substantially challenging both theories: for IIT, a lack of sustained synchronization within posterior cortex contradicts the claim that network connectivity specifies consciousness. GNWT is challenged by the general lack of ignition at stimulus offset and limited representation of certain conscious dimensions in prefrontal cortex. Beyond challenging the theories themselves, we present an alternative approach to advance cognitive neuroscience through a principled, theory-driven, collaborative effort. We highlight the challenges to change peoples mind 13 and the need for a quantitative framework integrating evidence for systematic theory testing and building.

neuroscience↗

bioRxiv2023

Spatial Tuning of Alpha Oscillations in Human Visual Cortex

AO_SCPLOWBSTRACTC_SCPLOWNeuronal oscillations at about 10 Hz, called alpha oscillations, are often thought to arise from synchronous activity across occipital cortex, reflecting general cognitive states such as arousal and alertness. However, there is also evidence that modulation of alpha oscillations in visual cortex can be spatially specific. Here, we used intracranial electrodes in human patients to measure alpha oscillations in response to visual stimuli whose location varied systematically across the visual field. We separated the alpha oscillatory power from broadband power changes. The variation in alpha oscillatory power with stimulus position was then fit by a population receptive field (pRF) model. We find that the alpha pRFs have similar center locations to pRFs estimated from broadband power (70-180 Hz) but are several times larger. The results demonstrate that alpha suppression in human visual cortex can be precisely tuned. Finally, we show how the pattern of alpha responses can explain several features of exogenous visual attention. Significance StatementThe alpha oscillation is the largest electrical signal generated by the human brain. An important question in systems neuroscience is the degree to which this oscillation reflects system-wide states and behaviors such as arousal, alertness, and attention, versus much more specific functions in the routing and processing of information. We examined alpha oscillations at high spatial precision in human patients with intracranial electrodes implanted over visual cortex. We discovered a surprisingly high spatial specificity of visually driven alpha oscillations, which we quantified with receptive field models. We further use our discoveries about properties of the alpha response to show a link between these oscillations and the spread of visual attention. Grant support: NIH R01 MH111417 (Petridou, Winawer, Ramsey, Devinsky); JSPS Overseas Research Fellowship (Yuasa) The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health

neuroscience↗

bioRxiv2022

Pro-tumor and prothrombotic activities of hepsin in colorectal cancer cells and suppression by venetoclax

Hepsin is a type II transmembrane serine protease whose expression has been linked to greater tumorigenicity and worse prognosis in different tumors such as prostate and gastric cancer. Recently, our group described hepsin expression in the primary biopsy as a potential biomarker of thrombosis and metastasis in localized colorectal cancer patients. Here we explored the role of hepsin in this tumor. Hepsin overexpression increased Caco-2 cell migration and invasion, higher phosphorylation of Erk1/2 and STAT3 and led to more thrombin generation in plasma. Indeed, our study revealed higher plasma levels of hepsin in metastatic colorectal cancer patients, which was associated with a greater tendency toward thrombosis. By virtual screening of a FDA-approved drug library, we identified venetoclax as a potent hepsin inhibitor, reducing the metastatic and prothrombotic phenotype of Caco-2 cells, but not of other colorectal cancer cells without hepsin expression. Interestingly, pre-treating Caco-2 cells overexpressing hepsin with venetoclax reduced its in vivo invasiveness. Taken together, our results demonstrate that elevated hepsin levels correlate with a more aggressive and prothrombotic tumor phenotype. Likewise, they evidence an antitumor role for venetoclax as a hepsin inhibitor. This lays the groundwork for molecular targeted therapy for colorectal cancer.

cancer biology↗

bioRxiv2021

Temporal dynamics of neural responses in human visual cortex

Neural responses to visual stimuli exhibit complex temporal dynamics, including sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic (ECoG) recordings from patients presented with stimuli that varied in contrast, duration, and inter-stimulus interval (ISI). Aggregating data across patients yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several non-linear features: peak response amplitude saturates with high contrast and longer stimulus durations; the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs; response latency decreases with increasing contrast. These features are accurately captured by a computational model comprised of a small set of canonical neuronal operations: linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex, and demonstrate that a simple model captures these dynamics at millisecond resolution. Significance StatementSensory inputs and neural responses change continuously over time. It is especially challenging to understand a system that has both dynamic inputs and outputs. Here we use a computational modeling approach that specifies computations to convert a time-varying input stimulus to a neural response time course, and use this to predict neural activity measured in the human visual cortex. We show that this computational model predicts a wide variety of complex neural response shapes that we induced experimentally by manipulating the duration, repetition and contrast of visual stimuli. By comparing data and model predictions, we uncover systematic properties of temporal dynamics of neural signals, allowing us to better understand how the brain processes dynamic sensory information.

neuroscience↗