Back to Authors

Krishna, Saritha

Mayo Clinic

University of California, San Francisco

Citations 2

Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning
Mehari, Mulki , Warrier, Gayathri , Dada, Abraham , Kabir, Aymen , Haskell-Mendoza, Aden , Tripathy, Arushi , Jha, Rohan , Nieblas‐Bedolla, Edwin , Jackson, Joshua , Gonzalez, Ariel T , Reason, Ellery , Flusché, Ann Marie , Reihl, Sheantel , Dalton, Tara , Negussie, Mikias , Gonzales, Cesar Nava, Ambati, Vardhaan , Desjardins, Annick , Krishna, Saritha, Chang, Susan M. , Porter, Alyx B. , Fecci, Peter E. , Hollon, Todd , Chukwueke, Ugonma , Badal, Kimberly , Molinaro, Annette M. , Hervey‐Jumper, Shawn L. , Haskell-Mendoza, Aden P , Reason, Ellery H , Ambati, Vardhaan , Krishna, Saritha , Porter, Alyx , Hollon, Todd , Chukwueke, Ugonma N , Badal, Kimberly , Molinaro, Annette M. , Hervey-Jumper, Shawn L , Reihl, Sheantel J , Fecci, Peter E , Desjardins, Annick , Daniel, Andy G. S.

Science Advances | June 11, 2025 | Volume: 11 | Issue: 23 | Pages: No page available

10.1126/sciadv.adt5708 Get It

Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factors remains limited. To test the interactive effects of demographic, socioeconomic, and oncologic variables on trial enrollment, we designed boosted neural networks (BNNs) for all glioma patients ( n = 1042), women ( n = 445, 42.7%), and minorities ( n = 151, 14.5%) and externally validated these models [whole cohort, n = 230; women, n = 89 (38.7%); minority, n = 66 (28.7%)]. For the whole-cohort BNN, the most influential variables on enrollment were oncologic variables, including KPS [total effect (TE), 0.327], chemotherapy (TE, 0.326), tumor location (TE, 0.322), and seizures (TE, 0.239). The women-only BNN exhibited a similar trend. Conversely, for the minority-only BNN, socioeconomic variables [insurance status (TE, 0.213), occupation classification (TE, 0.204), and employment status (TE, 0.150)] were most influential. These results may help prioritize patient-specific initiatives to increase accrual.
Spatial synaptic connectivity underlies oligodendroglioma evolution and recurrence
Raleigh, David R. , Mirchia, Kanish , Oten, Sena, Ambati, Vardhaan , Vasudevan, Harish N. , Young, Jacob, Taylor, Jennie , Krishna, Saritha, Brang, David , Phillips, Joanna J. , Chang, Susan M. , Hervey‐Jumper, Shawn L. , Raleigh, David , Ambati, Vardhaan , Vasudevan, Harish , Taylor, Jennie W , Phillips, Joanna , Perry, Arie , de Groot, John , Hervey-Jumper, Shawn L , Picart, Thiébaud , Nguyen, Minh, Perry, Arie , Berger, Mitchel S. , Groot, John de

No container title available | April 4, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-6299872/v1 Get It

Abstract Oligodendrogliomas are initially slow-growing brain tumors that are prone to malignant transformation despite surgery and cytotoxic therapy. Understanding of oligodendroglioma evolution and new treatments for patients have been encumbered by a paucity of patient-matched newly diagnosed and recurrent tumor samples for multiplatform analyses, and by a lack of preclinical models for interrogation of therapeutic vulnerabilities that drive oligodendroglioma growth. Here we integrate spatial and functional analyses of tumor samples and patient-derived organoid co-cultures to show that synaptic connectivity is a hallmark of oligodendroglioma evolution and recurrence. We find that patient-matched recurrent oligodendrogliomas are enriched in synaptic gene expression programs irrespective of previous therapy or histologic grade. Analyses of spatial, single-cell, and clinical data reveal epigenetic misactivation of synaptic genes that are concentrated in regions of cortical infiltration and can be used to predict eventual oligodendroglioma recurrence. To translate these findings to patients, we show that local field potentials from tumor-infiltrated cortex at the time of resection and neuronal hyperexcitability and synchrony in patient-derived organoid co-cultures are associated with oligodendroglioma proliferation and recurrence. In preclinical models, we find that neurophysiologic drugs block oligodendroglioma growth and pathologic electrophysiology. These results elucidate mechanisms underlying oligodendroglioma evolution from an indolent tumor to a fatal disease and shed light on new biomarkers and new treatments for patients.