Ternary Complex Components Responsible for Rapid LDL Internalization as Biomarkers for Breast Cancer Associated with Proliferation and Early Recurrence

Article

Author: Pan, Tien-Chi ; Kossenkov, Andrew V. ; Troester, Melissa A. ; McDonald, Elizabeth S. ; Chodosh, Lewis A. ; Mankoff, David A. ; Pant, Dhruv K. ; Mach, Robert H.

AbstractThe ternary complex of progesterone receptor membrane component 1 (PGRMC1)–sigma-2 receptor/transmembrane protein 97 (σ2R/TMEM97)–low-density lipoprotein receptor (LDLR) has recently been discovered and plays a role in cholesterol transport. This study investigated whether individual components of that complex are prognostic breast cancer biomarkers and have defined expression in established molecular subtypes. A total of 4,463 invasive breast cancers were analyzed as a function of molecular and phenotypic markers, estimates of cellular proliferation, and recurrence-free survival. A gene expression signature–based assay was utilized to estimate cellular proliferation. Cox proportional hazards regression estimated relapse-free survival and multivariate Cox analysis adjusted for the association of proliferation with early relapse. PGRMC1–σ2R/TMEM97–LDLR expression was stratified by immunohistochemical (IHC) and molecular subtype, tumor grade, and size. TMEM97 exhibited the strongest correlation with proliferation, highest in estrogen receptor (ER)–positive disease (r = 0.59, P = 8.1−114). TMEM97 and PGRMC1 were associated with a risk of early recurrence, dependent upon their association with proliferation. The risk of early recurrence was highest with TMEM97 and only seen in ER+/HER2− disease [HR = 1.5; 95% confidence interval (CI) = 1.35–1.67; P = 5.4−14] and ER+ malignancies (HR = 1.49; 95% CI = 1.31–1.68; P = 3.1−10). There was no increased risk of recurrence with TMEM97 expression in ER−/HER2− (HR = 1.05; 95% CI = 0.88–1.25; P = 0.63) or ER− disease (HR = 1.02; 95% CI = 0.89–1.17; P = 0.75). Components of a ternary complex associated with rapid internalization of low-density lipoprotein are biomarkers associated with cellular proliferation and early recurrence, which should help guide studies exploring them in the context of additional markers of aggressive disease. Elucidating the role of PGRMC1, TMEM97, and LDLR in breast cancer will facilitate a mechanistic understanding of how proliferation interplays with cholesterol metabolism in malignant transformation or propagation.Significance:This first large-scale analysis of the putative ternary complex responsible for rapid low-density lipoprotein internalization in breast cancer reveals a link between component expression and recurrence, with prognostic implications for identifying patients needing supplemental posttreatment surveillance and/or additional therapeutic approaches.

15 Nov 2024·Journal of Clinical Investigation

Parkin activates innate immunity and promotes antitumor immune responses

Article

Author: Camisaschi, Chiara ; Grandvaux, Nathalie ; Kossenkov, Andrew V. ; Altieri, Dario C ; Bertolini, Irene ; Milcarek, Andrew T. ; Perego, Michela ; Ruscetti, Marcus ; Ghosh, Jagadish C ; Auslander, Noam ; Altieri, Dario C. ; Milcarek, Andrew T ; Kossenkov, Andrew V ; Tang, Hsin-Yao ; Preston-Alp, Sarah ; Yeon, Minjeong ; Tempera, Italo ; Ghosh, Jagadish C. ; Agarwal, Ekta

The activation of innate immunity and associated interferon (IFN) signaling have been implicated in cancer, but the regulators are elusive and links to tumor suppression remain undetermined. Here, we found that Parkin, an E3 ubiquitin ligase altered in Parkinson's Disease, was epigenetically silenced in cancer and its reexpression by clinically approved demethylating therapy stimulated transcription of a potent IFN response in tumor cells. This pathway required Parkin E3 ubiquitin ligase activity, involved the subcellular trafficking and release of the alarmin High Mobility Group Box 1 (HMGB1) and was associated with inhibition of NF-κB gene expression. In turn, Parkin-expressing cells released an IFN secretome that upregulated effector and cytotoxic CD8+ T cell markers, lowered the expression of immune inhibitory receptors TIM3 and LAG3, and stimulated high content of the self renewal/stem cell factor, TCF1. PRKN-induced CD8+ T cells selectively accumulated in the microenvironment and inhibited transgenic and syngeneic tumor growth in vivo. Therefore, Parkin is an epigenetically regulated activator of innate immunity and dual mode tumor suppressor, inhibiting intrinsic tumor traits of metabolism and cell invasion, while simultaneously reinvigorating CD8 T cell functions in the microenvironment.

01 Sep 2024·Fertility and Sterility

Multiplexed serum biomarkers to discriminate nonviable and ectopic pregnancy

Article

Author: Bollig, Kassie J. ; Robins, Jared C ; Chittams, Jesse ; Haisenleder, Daniel J ; Senapati, Suneeta ; Savaris, Ricardo F ; Gimotty, Phyllis ; Bollig, Kassie J ; Koelper, Nathanael C ; Beer, Lynn A. ; Kim, Mansu ; Koelper, Nathanael C. ; Shen, Li ; Barnhart, Kurt T ; Beer, Lynn A ; Wen, Zixuan ; Speicher, David W. ; Robins, Jared C. ; Savaris, Ricardo F. ; Bao, Jingxuan ; Takacs, Peter ; Mumford, Sunni ; Haisenleder, Daniel J. ; Speicher, David W ; Feng, Yanbo ; Barnhart, Kurt T.

OBJECTIVETo evaluate combinations of candidate biomarkers to develop a multiplexed prediction model for identifying the viability and location of an early pregnancy. In this study, we assessed 24 biomarkers with multiple machine learning-based methodologies to assess if multiplexed biomarkers may improve the diagnosis of normal and abnormal early pregnancies.DESIGNA nested case-control design evaluated the predictive ability and discrimination of biomarkers in patients at risk of early pregnancy failure in the first trimester to classify viability and location.SETTINGThree university hospitals.PATIENTSA total of 218 individuals with pain and/or bleeding in early pregnancy: 75 had an ongoing intrauterine gestation; 68 had ectopic pregnancies (EPs); and 75 had miscarriages.INTERVENTIONSSerum levels of 24 biomarkers were assessed in the same patients. Multiple machine learning-based methodologies to evaluate combinations of these top candidates to develop a multiplexed prediction model for the identification of a nonviable pregnancy (ongoing intrauterine pregnancy vs. miscarriage or EP) and an EP (EP vs. ongoing intrauterine pregnancy or miscarriage).MAIN OUTCOME MEASURESThe predicted classification using each model was compared with the actual diagnosis, and sensitivity, specificity, positive predictive value, negative predictive value, conclusive classification, and accuracy were calculated.RESULTSModels using classification regression tree analysis using 3 (pregnancy-specific beta-1-glycoprotein 3 [PSG3], chorionic gonadotropin-alpha subunit, and pregnancy-associated plasma protein-A) biomarkers were able to predict a maximum sensitivity of 93.3% and a maximum specificity of 98.6%. The model with the highest accuracy was 97.4% (with 70.2% receiving classification). Models using an overlapping group of 3 (soluble fms-like tyrosine kinase-1, PSG3, and tissue factor pathway inhibitor 2) biomarkers achieved a maximum sensitivity of 98.5% and a maximum specificity of 95.3%. The model with the highest accuracy was 94.4% (with 65.6% receiving classification). When the models were used simultaneously, the conclusive classification increased to 72.7% with an accuracy of 95.9%. The predictive ability of the biomarkers in the random forest produced similar test characteristics when using 11 predictive biomarkers.CONCLUSIONWe have demonstrated a pool of biomarkers from divergent biological pathways that can be used to classify individuals with potential early pregnancy loss. The biomarkers choriogonadotropin alpha, pregnancy-associated plasma protein-A, and PSG3 can be used to predict viability, and soluble fms-like tyrosine kinase-1, tissue factor pathway inhibitor 2, and PSG3 can be used to predict pregnancy location.

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