Aritro Nath

Phenotypic inference from sparse tumor genomes informs an explainable deep-learning model for cancer prognosis

Sydney Grant, Aritro Nath

ABSTRACT Somatic genomic alterations are widely profiled in cancer and remain the primary source for personalized therapy, yet their clinical utility is limited to few actionable targets. AI/ML models offer opportunities to capture genome-wide complexities, but clinical translation is hindered by poor …

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Multi-state modeling associates proliferation genes with early estrogen receptor-positive breast cancer recurrence and survival

Yongzhe Wang, Christine Quinones, Irene Kang, Hope Rugo et autres

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Baseline gene expression and dynamic endocrine therapy use in ER+ breast cancer: associations with recurrence in a real-world cohort

Veronica Jones, Yongzhe Wang, Christine Quinones, Dana Aljaber et autres

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Dual CDK2 and CDK4/6 inhibition suppresses Rb/E2F signaling and enhances anti-leukemic activity in acute myeloid leukemia

Ellen Weisberg, Basudev Chowdhury, Swati Garg, Taisei Akatsu et autres

The cyclin-dependent kinase 6 (CDK6) is a central regulator of cell cycle progression and an important contributor to the development of acute leukemia, particularly in poor prognosis subtypes. Preclinical studies have demonstrated activity of CDK6-targeting drugs in acute myeloid leukemia (AML) and …

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The IMMUNO-BIOMAP trial in NSCLC: An adaptive multimodal framework for biomarker-guided care

Aritro Nath, Jyoti Malhotra, Isa Mambetsariev, Jeremy Fricke et autres

Tumor heterogeneity and evolution constrain NSCLC immunotherapy, leading to variable and often short-lived responses. This commentary discusses the ARPA-H ADAPT program and IMMUNO-BIOMAP trial, which longitudinally profile tumors and the microenvironment to identify resistance mechanisms in real time and enable adaptive, biomarker-guided, …

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Abstract 2696: Unlocking novel gene-based biomarkers using an explainable deep learning framework for precision oncology.

Sydney R. Grant, Aritro Nath

Abstract Somatic genomic alterations are widely profiled in cancer and remain the primary indicator for personalized therapy, yet their clinical utility is limited to a small set of actionable targets benefiting only a fraction of patients. AI/ML offers a transformative path to …

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A novel combination therapy for ER+ breast cancer suppresses drug resistance via an evolutionary double-bind

Rena Emond, Jeffrey West, Vince Kornél Grolmusz, Patrick A. Cosgrove et autres

Chemotherapy remains a commonly used and important treatment option for metastatic breast cancer. A majority of Estrogen Receptor-positive (ER + ) metastatic breast cancer patients ultimately develop resistance to chemotherapy, resulting in disease progression. We hypothesized that an "evolutionary double-bind", where adapting …

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The ADAPT learning cancer treatment system: ARPA-H’s initiative to revolutionize cancer therapy

Andrea H. Bild, Michelle Cook Sangar, Jasmine A. McQuerry, Trey Ideker et autres

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Divergent oncogenic signaling and immune microenvironment changes in low-grade serous ovarian cancer patients undergoing intraperitoneal chemotherapy

Isaac Bishara, Patrick A. Cosgrove, Sumana Majumdar, Colt A. Egelston et autres

Low-grade serous ovarian carcinoma (LGSOC) is a rare, treatment-resistant subtype of ovarian cancer characterized by peritoneal spread. Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC) delivers chemotherapy directly into the abdomen during serial laparoscopic surgeries, enabling repeated sampling of tumors for longitudinal analysis. Using single-nuclei …

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System analysis links SMARCD3 regulons to growth signaling and MEK inhibitor response in everolimus-resistant ER+ breast cancer cells

Eric F. Medina, Elena Farmaki, Jason I. Griffiths, Andrea H. Bild et autres

Estrogen receptor-positive breast cancer (ER+BC) accounts for ∼70% of all breast tumors, and 20%–40% of patients develop metastases. Everolimus is an mammalian target of rapamycin (mTOR) inhibitor used in combination with exemestane for metastatic ER+BC. However, resistance remains common and leads to …

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Blocking cancer-fibroblast mutualism inhibits proliferation of endocrine therapy resistant breast cancer

Jason I. Griffiths, Feng Chi, Elena Farmaki, Eric F. Medina et autres

Abstract In early-stage estrogen receptor-positive (ER + ) breast cancer, resistance to endocrine therapy (ET) and CDK4/6 inhibitors (CDK4/6i) often involve a shift away from estrogen-driven proliferation. The nature and source of compensatory growth signals driving cancer proliferation remain unknown but represent …

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Abstract 5011: Integrating multimodal data with survival-based variational autoencoders to predict recurrence-free survival in breast cancer

Sydney R. Grant, Aritro Nath

Abstract Breast cancer is the most commonly diagnosed malignancy globally and responsible for over 670, 000 deaths each year. Accurate prediction of recurrence-free survival (RFS) is crucial for clinical management and personalized care in breast cancer, enabling improved surveillance, risk stratification, and …

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