Biology subjects

Martin, M. L.

Publications and source records attributed to Martin, M. L..

9 recordsLinked to original sources

bioRxiv2023

Kinome focused CRISPR-Cas9 screens in African ancestry patient-derived breast cancer organoids identifies essential kinases and synergy of EGFR and FGFR1 inhibition.

Precision medicine approaches to cancer treatment aim to exploit genomic alterations that are specific to individual patients to tailor therapy strategies. These alterations are usually revealed via next generation sequencing of the tumor tissue. Yet, it is clear that some targetable genes and pathways are essential for tumor cell viability even in the absence of direct genomic alterations. This is especially important in under-represented populations, whose mutational landscape and determinants of response to existing therapies are poorly characterized due to limited inclusion in clinical trials and studies. One way to reveal tumor essential genes is with genetic screens. Most screens are conducted on cell lines that bear little resemblance to patient tumors, after years of culture in non-physiological conditions. To address this problem, we aimed to develop a CRISPR screening pipeline in 3D-grown patient-derived tumor organoid (PDTO) models. We focused on identifying essential kinases that may translate to options for targeted therapies, including combination therapies. We first established a breast cancer PDTO biobank focused on underrepresented populations, including West African patients. We then performed a negative selection kinome-focused CRISPR screen to identify kinases essential for organoid growth and potential targets for combination therapy with EGFR or MEK inhibitors. We identified several previously unidentified kinase targets and showed that combination of FGFR1 and EGFR inhibitors synergizes to block organoids proliferation. Together these data demonstrate feasibility of CRISPR-based genetic screens in patient-derived tumor models, including PDTOs from under-represented cancer patients, and identify new targets for cancer therapy.

cancer biology↗

bioRxiv2023

Novel co-culture strategies of tumor organoids with autologous T-cells reveal clinically relevant combinations of immune-checkpoint and targeted therapies

Patient derived tumor organoids (PDTOs) have become relevant pre-clinical models for therapeutic modelling since they highly recapitulate patients response to treatment. Nevertheless, their value for immunotherapy modelling has not been fully explored. We developed a tumor processing protocol that enable the establishment of PDTOs and tumor infiltrating lymphocytes (TILs) isolation. By the optimization of functional assays, we compared the T-cells effector functions of matching PBMCs and TILs, demonstrating that PBMCs after co-culture and TILs after initial expansion display similar responses. In addition, the evaluation of cytokine production by fluorospot in combination with an image-based killing assay enable the screening of different immune-checkpoint inhibitors as well as its combination with target inhibitors. Our proof-of-concept functional assays showed the potential and versatility of PDTOs and T-cells co-culture systems for immunotherapy screening. The optimization of scalable functional assays downstream co-culture represents a significant step forward to increase the value of PDTOs as pre-clinical models for immunotherapeutic screens.

immunology↗

bioRxiv2023

Patient-derived tumor organoids with p53 mutations, and not wild-type p53, are sensitive to synergistic combination PARP inhibitor treatment

Poly (ADP-ribose) polymerase inhibitors (PARPi) are used for patients with BRCA1/2 mutations, but patients with other mutations may benefit from PARPi treatment. Another mutation that is present in more cancers than BRCA1/2 is mutation to the TP53 gene. In 2D breast cancer cell lines, mutant p53 (mtp53) proteins tightly associate with replicating DNA and Poly (ADP-ribose) polymerase (PARP) protein. Combination drug treatment with the alkylating agent temozolomide and the PARPi talazoparib kills mtp53 expressing 2D grown breast cancer cell lines. We evaluated the sensitivity to the combination of temozolomide plus PARPi talazoparib treatment to breast and lung cancer patient-derived tumor organoids (PDTOs). The combination of the two drugs was synergistic for a cytotoxic response in PDTOs with mtp53 but not for PDTOs with wtp53. The combination of talazoparib and temozolomide induced more DNA double-strand breaks in mtp53 expressing organoids than in wild-type p53 expressing organoids as shown by increased {psi}-H2AX protein expression. Moreover, breast cancer tissue microarrays (TMAs) showed a positive correlation between stable p53 and high PARP1 expression in sub-groups of breast cancers, which may indicate sub-classes of breast cancers sensitive to PARPi therapy. These results suggest that mtp53 could be a biomarker to predict response to the combination of PARPi talazoparib-temozolomide treatment.

cancer biology↗

bioRxiv2022

Gut bacteria-derived serotonin promotes immune tolerance in early life

The gut microbiome promotes immune system development in early life, but the neonatal gut metabolome remains undefined. Here, we demonstrate that, distinct from adults, the neonatal mouse gut is enriched with neurotransmitters, and specific bacteria produce serotonin directly while downregulating monoamine oxidase A to limit serotonin breakdown. Serotonin inhibits mTOR activation to promote regulatory T cells and suppress T cell responses both ex vivo and in vivo in the neonatal intestine. Oral gavage of serotonin into neonatal mice leads to long-term immune tolerance toward both dietary antigens and commensal bacteria as well as alterations of the gut microbiome. Together, our study has uncovered unique microbiome-dependent mechanisms to maximize serotonin in the neonatal gut and a novel role for intestinal serotonin to promote immune tolerance in early life.

immunology↗

bioRxiv2022

An Automated Method for the Assessment of Memory and Learning in Larval Zebrafish

Zebrafish have shown value in translational research for many human diseases, including neuropsychiatric disorders and cognitive dysfunction, with low cost and rapid testing facilitating drug screening and discovery. However, some endpoints, such as associative learning and long-term memory, have relied historically on manual data tracking that slows data acquisition and increases costs. We automated an associative learning/long-term memory test developed by Hinz et al.1 using a Noldus DanioVision system and EthoVision software to enhance assay throughput and utility for monitoring learning and memory behavior through automated tracking of location and movement of individual fish.

animal behavior and cognition↗

bioRxiv2021

Mobile Footprinting: Linking Individual Distinctiveness in Mobility Patterns to Mood, Sleep, and Brain Functional Connectivity

Mapping individual differences in behavior is fundamental to personalized neuroscience. Here, we establish that statistical patterns of smartphone-based mobility features represent unique "footprints" that allow individual identification. Critically, mobility footprints exhibit varying levels of person-specific distinctiveness and are associated with individual differences in affective instability, circadian irregularity, and brain functional connectivity. Together, this work suggests that real-world mobility patterns may provide an individual-specific signature linking brain, behavior, and mood.

neuroscience↗

bioRxiv2020

CK1 Delta Is an mRNA Cap-Associated Protein That Drives Translation Initiation and Tumor Growth

Whether translation is differentially regulated across liquid and solid tumors remains poorly understood. Here we report the discovery that Casein Kinase 1 delta (CK1{delta}) plays a key role in regulating translation initiation in blood cancers, but interestingly, not in solid tumors. In lymphomas CK1{delta} is a key positive regulator of 4E-BP1 and p70S6K phosphorylation, assembly of eIF4F, and translation initiation. Furthermore, CK1{delta} is pulled down by m7GTP-agarose that mimics the mRNA m7G cap, consistent with the regulatory role of CK1{delta} in translation initiation. Targeting CK1{delta} using a small molecule inhibitor, namely SR-3029, potently kills lymphoma cell lines and primary lymphoma cells across histology subtypes. While SR-3029 shares with mTORC1 inhibitors the overlapping mechanism of repressing 4E-BP1 and p70S6K/RPS6 phosphorylation, the kinetics of repression is slow with SR-3029 and fast with mTORC1 inhibitors such as Torin-1. Remarkably, it is slower-acting SR-3029, but not fast-acting Torin-1, that kills lymphoma cells consistently across multiple histology subtypes. Proteomics and RNA sequencing studies show that SR-3029 represses the expression of many genes preferentially at the translation step, such as genes in the reactome translation initiation pathway. SR-3029 markedly represses the protein level of the C-MYC oncogene without decreasing its mRNA level. In contrast, Torin-1 fails to reduce the protein level of C-MYC in the same lymphoma cells. While SR-3029 also demonstrates potent activity in select solid tumors, its mechanism of action in the solid tumors is different. In breast cancer cells SR-3029 inhibits nuclear localization of {beta}-catenin but at the same concentrations does not inhibit 4E-BP1 and p70S6K phosphorylation or global protein synthesis. Likewise, SR-3029 does not inhibit nuclear localization of {beta}-catenin in lymphoma cells. Our results indicate that CK1{delta} is an mRNA cap-associated protein and an upstream kinase required for 4E-BP1 and p70S6K phosphorylation. CK1{delta} stimulates assembly of eIF4F and translation initiation, and is a critical driver for tumor growth in blood cancers across multiple histology types. CK1{delta} invokes the alternative mechanism of regulating {beta}-catenin in select solid tumors. Our results indicate that CK1{delta} inhibition is a promising therapeutic strategy in both liquid and solid tumors, and the distinct roles of CK1{delta} in these malignancies may serve as biomarkers to enable precision cancer treatment.

cancer biology↗

bioRxiv2019

Intensity Warping for multisite MRI Harmonization

In multisite neuroimaging studies there is often unwanted technical variation across scanners and sites. These \"scanner effects\" can hinder detection of biological features of interest, produce inconsistent results, and lead to spurious associations. We assess scanner effects in two brain magnetic resonance imaging (MRI) studies where subjects were measured on multiple scanners within a short time frame, so that one could assume any differences between images were due to technical rather than biological effects. We propose mica (multisite image harmonization by CDF alignment), a tool to harmonize images taken on different scanners by identifying and removing within-subject scanner effects. Our goals in the present study were to (1) establish a method that removes scanner effects by leveraging multiple scans collected on the same subject, and, building on this, (2) develop a technique to quantify scanner effects in large multisite trials so these can be reduced as a preprocessing step. We found that unharmonized images were highly variable across site and scanner type, and our method effectively removed this variability by warping intensity distributions. We further studied the ability to predict intensity harmonization results for a scan taken on an existing subject at a new site using cross-validation.

neuroscience↗

bioRxiv2019

TAPAS: A Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis

Total brain white matter lesion (WML) volume is the most widely established magnetic resonance imaging (MRI) outcome measure in studies of multiple sclerosis (MS). To estimate WML volume, there are a number of automatic segmentation methods, yet, manual delineation remains the gold standard approach. These approaches often yield a probability map to which a threshold is applied to create lesion segmentation masks. Unfortunately, few approaches systematically determine the threshold employed; many methods use a manually selected threshold, thus introducing human error and bias into the automated procedure. In this study, we propose and validate an automatic thresholding algorithm, Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis (TAPAS), to obtain subject-specific threshold estimates for probability map automatic segmentation of T2-weighted (T2) hyperintense WMLs. Using multimodal MRI, the proposed method applies an automatic segmentation algorithm to obtain probability maps. We obtain the true subject-specific threshold that maximizes Sorensen-Dice Similarity Coefficient (DSC). Then the subject-specific thresholds are modeled on a naive estimate of volume using a general additive model. Applying this model, we predict a subject-specific threshold in data not used for training. We ran a Monte Carlo-resampled split-sample cross-validation (100 validation sets) using two data sets: the first obtained from the Johns Hopkins Hospital (JHH) on a Philips 3 Tesla (3T) scanner (n = 94) and a second collected at the Brigham and Womens Hospital (BWH) using a Siemens 3T scanner (n = 40). By means of the proposed automated technique, in the JHH data, we found an average reduction in subject-level absolute error of 0.1 mL per one mL increase in manual volume. Using Bland-Altman analysis, we found that volumetric bias associated with group-level thresholding is mitigated when applying TAPAS. The BWH data showed similar absolute error estimates using group-level thresholding or TAPAS likely since Bland-Altman analyses indicate no systematic biases associated with group or TAPAS volume estimates. The current study presents the first validated fully automated method for subject-specific threshold prediction to segment brain lesions.

neuroscience↗