Biology subjects

Tarca, A. L.

Publications and source records attributed to Tarca, A. L..

7 recordsLinked to original sources

bioRxiv2026

MNRR1 is required for Triple Negative Breast Cancer growth and metastasis and can be targeted by repurposed drugs.

Despite progress in recent decades, breast cancers remain the most diagnosed malignancies, and second leading cause of cancer death, in women. Although improved screening and systemic and endocrine adjuvant approaches have contributed to major declines in breast cancer mortality, current standard of care drugs are extremely toxic, and many women continue to be overtreated. Although nearly two-thirds of breast cancers are hormone-responsive, aggressive subtypes, particularly Triple Negative Breast Cancer (TNBC), still lack safe oral medications. Recently the roles that mitochondria play in TNBC carcinogenesis, metastasis, and resistance to treatment have garnered a great deal of attention. Contrary to the popular dogma that cancer cells are powered by glycolysis, metastatic breast cancer cells have enhanced mitochondrial function. Our work identified that Mitochondrial Nuclear Retrograde Regulator 1 (MNRR1; also, CHCHD2, PARK22), a key coordinator of mitochondrial-nuclear crosstalk that is physically present in both compartments, is overexpressed in TNBC cells and is an important regulator of metastasis signaling. We have identified Heat Shock Factor 1 (HSF1) as the main transcription factor that activates the MNRR1 promoter in TNBC cell lines. In the mitochondria, MNRR1 protein facilitates ATP production and inhibits apoptosis, whereas in the nucleus it regulates the transcription of stress-responsive genes including several required for epithelial to mesenchymal transition (EMT), metabolic flexibility, and cell growth. Thus, each of the bi-organellar functions of MNRR1 constitutes processes regarded as hallmarks of cancer. For reasons that are not yet fully understood, MNRR1 levels display a significant and robust ancestry bias, showing increased expression in tumor samples from Non-Hispanic Black (NHB) women when compared to disease-matched tumors from Non-Hispanic White (NHW) patients. It is possible that increased levels of MNRR1 may underlie the aggressive metastatic phenotype observed in many NHB patients. In further support of this observation, loss of MNRR1 function, either genetically or by use of inhibitors, reduces TNBC growth and metastasis. MNRR1 therefore is an attractive therapeutic target that could be exploited for design of novel therapies or as adjuncts to existing ones.

cancer biology↗

bioRxiv2025

Benchmarking Large Language Models for Predictive Modeling in Biomedical Research With a Focus on Reproductive Health

Generative AI, particularly large language models (LLMs), is increasingly being used in computational biology to support code generation for data analysis. In this study, we evaluated the ability of LLMs to generate functional R and Python code for predictive modeling tasks, leveraging standardized molecular datasets from several recent DREAM (Dialogue for Reverse Engineering Assessments and Methods) Challenges focused on reproductive health. We assessed LLM performance across four predictive tasks derived from three DREAM challenges: gestational age regression from gene expression, gestational age regression from DNA methylation profiles, and classification of preterm birth and early preterm birth from microbiome data. LLMs were prompted with task descriptions, data locations, and target outcomes. LLM-generated code was then run to fit and apply prediction models and generate graphics, and they were ranked based on their success in completing the tasks and achieving strong test set performance. Among the eight LLMs tested, o3-mini-high, 4o, DeepseekR1 and Gemini 2.0 completed at least one task without error. Overall, R code generation was more successful (14/16 tasks) than Python (7/16), attributed to the utility of Bioconductor packages for querying Gene Expression Omnibus data. OpenAIs o3-mini-high outperformed others, completing 7/8 tasks. Test set performance of the top LLM matched or exceeded top-performing teams from the original DREAM challenges. These findings underscore the potential of LLMs to enhance exploratory analysis and democratize access to predictive modeling in omics by automating key components of analysis pipelines, and highlight the potential to increase research output when conducting analyses of standardized datasets from public repositories.

bioinformatics↗

bioRxiv2024

Cultivation and molecular characterization of Foley catheterized urine, clean catch urine, and vaginal swabs from pregnant women prior to delivery

The bladder and urine have historically been considered sterile, especially in the context of clinical assessment. Yet, enhanced culture techniques and advances in DNA sequencing surveys have revealed a low microbial biomass microbiota in the bladders of most healthy individuals. Yet very few studies have investigated the urinary microbiota of pregnant women, who are at increased risk of urinary tract infections (UTIs) that can lead to pregnancy complications such as spontaneous preterm birth. To better understand the potential role of a bladder microbiota during pregnancy, we characterized the urinary microbiota of 25 pregnant women (delivering at or beyond 36 weeks gestation) by comparing the bacterial profiles of their paired catheter urine, clean catch urine, and vaginal swabs through both cultivation and molecular microbiological survey methods. For culture, three bacterial taxa were detected in at least 20% of all urine samples (Lactobacillus species, coagulase negative Staphylococcus species, and Ureaplasma urealyticum). All three taxa were detected less frequently in Foley catheter urine than in clean catch urine. Ureaplasma urealyticum was the most frequently recovered bacterium in Foley catheter urine (13/25 women). It was also identified as being more relatively abundant in Foley catheter urine than in the vagina through 16S rRNA gene surveys. Other lower abundance Gram-positive anaerobic cocci (i.e., Finegoldia and Anaerococcus) were also more relatively abundant in Foley catheter urine than clean catch urine or vaginal swabs. However, all sample types had high relative abundances of Lactobacillus and Gardnerella species. Overall, this suggests that, although vaginal microbiota contamination cannot be completely avoided, Foley catheterized urine is effective at characterizing the low abundance bladder microbiota, including Ureaplasma, Finegoldia, and Anaerococcus species. This warrants their further consideration as commensal members of the bladder microbiome during pregnancy.

microbiology↗

bioRxiv2023

The vaginal microbiota of pregnant women varies with gestational age, maternal age, and parity

The composition of the vaginal microbiota is heavily influenced by pregnancy and may factor into pregnancy complications, including spontaneous preterm birth. However, results among studies have been inconsistent, due in part to variation in sample sizes and ethnicity. Thus an association between the vaginal microbiota and preterm labor continues to be debated. Yet, before assessing associations between the composition of the vaginal microbiota and preterm labor, a robust and in-depth characterization of the vaginal microbiota throughout pregnancy in the specific study population under investigation is required. Herein, we report a large longitudinal study (N = 474 women, 1862 vaginal samples) of a primarily African-American cohort- which experiences a relatively high rate of pregnancy complications - evaluating associations between individual identity, gestational age, and other maternal characteristics with the composition of the vaginal microbiota throughout gestation resulting in term delivery. The primary factors influencing the composition of the vaginal microbiota in pregnancy are individual identity and gestational age at sampling. Secondary factors are maternal age, parity, obesity, and self-reported Cannabis use. The principal pattern across gestation is for the vaginal microbiota to remain or transition to a state of Lactobacillus dominance. This pattern can be mitigated by maternal parity and obesity. Regardless, network analyses reveal dynamic associations among specific bacterial taxa within the vaginal ecosystem, which shift throughout the course of pregnancy. This study provides a robust foundational understanding of the vaginal microbiota in pregnancy among African-Americans, in particular, and sets the stage for further investigation of this microbiota in obstetrical disease. IMPORTANCEThere is debate regarding links between the vaginal microbiota and pregnancy complications, especially spontaneous preterm birth. Inconsistencies in results among studies are likely due to differences in sample sizes and cohort ethnicity. Ethnicity is a complicating factor because, although all bacterial taxa commonly inhabiting the vagina are present among all ethnicities, the frequencies of these taxa vary among ethnicities. Therefore, an in-depth characterization of the vaginal microbiota throughout pregnancy in the specific study population under investigation is required prior to evaluating associations between the vaginal microbiota and obstetrical disease. This initial investigation is a large longitudinal study of the vaginal microbiota throughout gestation resulting in a term delivery in a primarily African-American cohort, a population that experiences disproportionally negative maternal-fetal health outcomes. It establishes the magnitude of associations between maternal characteristics, such as age, parity, BMI, and self-reported Cannabis use, on the vaginal microbiota in pregnancy.

microbiology↗

bioRxiv2022

The single-cell atlas of the murine reproductive tissues during preterm labor

Preterm birth, the leading cause of perinatal morbidity and mortality worldwide, frequently results from the syndrome of preterm labor. Intra-amniotic infection is the best-established causal link to preterm labor, and involves premature activation of the parturition cascade in the reproductive tissues. Herein, we utilized single-cell RNA-sequencing (scRNA-seq) to generate a single-cell atlas of the murine uterus, decidua, and cervix in a model of infection-induced preterm labor. We show that preterm labor affects the transcriptomic profiles of specific immune and non-immune cell subsets. Shared and tissue-specific gene expression signatures were identified among affected cells. Importantly, determination of intercellular communications implicates specific cell types preterm labor-associated signaling pathways across tissues. Last, in silico comparison of murine and human uterine cell-cell interactions reveals conserved signaling pathways implicated in labor. Thus, scRNA-seq provides new insights into the preterm labor-driven cellular landscape and communications in the reproductive tissues.

immunology↗

bioRxiv2020

Does the human placenta express the canonical cell entry mediators for SARS-CoV-2?

The pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected over 3.8 million people, including pregnant women. To date, no consistent evidence of vertical transmission for SARS-CoV-2 exists. This new coronavirus canonically utilizes the angiotensin-converting enzyme 2 (ACE2) receptor and the serine protease TMPRSS2 for cell entry. Herein, building upon our previous single cell study of the placenta (Pique-Regi, 2019), another study, and new single-cell/nuclei RNA-sequencing data, we investigated the expression of ACE2 and TMPRSS2 throughout pregnancy as well as in third-trimester chorioamniotic membranes. We report that co-transcription of ACE2 and TMPRSS2 is negligible, thus not a likely path of vertical transmission for SARS-CoV-2 at any stage of pregnancy. In contrast, receptors for Zika virus and cytomegalovirus which cause congenital infections are highly expressed by placental cell types. These data suggest that SARS-CoV-2 is unlikely to infect the human placenta through the canonical cell entry mediators; yet, other interacting proteins could still play a role in the viral infection.

genomics↗

bioRxiv2019

Single Cell Transcriptional Signatures of the Human Placenta in Term and Preterm Parturition

More than 135 million births occur each year; yet, the molecular underpinnings of human parturition in gestational tissues, and in particular the placenta, are still poorly understood. The placenta is a complex heterogeneous organ including cells of both maternal and fetal origin, and insults that disrupt the maternal-fetal dialogue could result in adverse pregnancy outcomes such as preterm birth. There is limited knowledge of the cell type composition and transcriptional activity of the placenta and its compartments during physiologic and pathologic parturition. To fill this knowledge gap, we used scRNA-seq to profile the placental villous tree, basal plate, and chorioamniotic membranes of women with or without labor at term and those with preterm labor. Significant differences in cell type composition and transcriptional profiles were found among placental compartments and across study groups. For the first time, two cell types were identified: 1) lymphatic endothelial decidual cells in the chorioamniotic membranes, and 2) non-proliferative interstitial cytotrophoblasts in the placental villi. Maternal macrophages from the chorioamniotic membranes displayed the largest differences in gene expression (e.g. NFKB1) in both processes of labor; yet, specific gene expression changes were also detected in preterm labor. Importantly, several placental scRNA-seq transcriptional signatures were modulated with advancing gestation in the maternal circulation, and specific immune cell type signatures were increased with labor at term (NK-cell and activated T-cell) and with preterm labor (macrophage, monocyte, and activated T-cell). Herein, we provide a catalogue of cell types and transcriptional profiles in the human placenta, shedding light on the molecular underpinnings and non-invasive prediction of the physiologic and pathologic parturition.\n\nOne sentence summaryThe common molecular pathway of parturition for both term and preterm spontaneous labor is characterized using single cell gene expression analysis of the human placenta.

genomics↗