Biology subjects

Alese, O. B.

Publications and source records attributed to Alese, O. B..

3 recordsLinked to original sources

bioRxiv2026

MetScore and classical-basal subtype intersect to define chemotherapy response and tumor microenvironment architecture in pancreatic ductal adenocarcinoma

Background Transcriptomic heterogeneity in pancreatic ductal adenocarcinoma (PDAC) is conventionally modeled along a single classical-basal axis, but this framework incompletely explains clinical behavior. We hypothesized that MetScore, a single-sample measure of metastatic colonization potential, defines a complementary axis. Objective To determine how MetScore and classical-basal identity jointly shape PDAC biology and clinical outcomes. Design We integrated RNA sequencing, DNA sequencing, clinical, and digital pathology data from 512 tumor biopsies from 510 patients in the Pancreatic Cancer Action Network Know Your Tumor real-world cohort. We assessed associations with biopsy site, survival, chemotherapy response, and tumor microenvironment composition; validated metastatic discrimination in an independent cohort; and examined cancer cell-intrinsic drug sensitivity in vitro. Results MetScore distinguished metastatic from primary biopsies, a finding validated externally. High MetScore and basal identity were independently associated with inferior survival. High MetScore and classical identity were each associated with preferential response to 5-fluorouracil (5-FU)-based rather than gemcitabine-based therapy, with the strongest enrichment for 5-FU responses among classical/MetScore-high patients. In vitro drug-sensitivity experiments did not recapitulate the clinical treatment-response pattern, motivating investigation of cancer cell-extrinsic factors. Transcriptomic deconvolution and histopathologic machine learning-based cell annotation demonstrated that high-MetScore and basal states converged on macrophage/monocyte enrichment but diverged in their associations with cancer-associated fibroblasts. Conclusion Integrating MetScore with classical-basal identity establishes a two-axis framework that better explains metastatic behavior, prognosis, treatment response, and microenvironmental composition than the conventional one-axis model and provides a clinically testable strategy for transcriptome-guided patient stratification.

cancer biology↗

bioRxiv2025

High-Dimensional Protein Analysis Uncovers Distinct Immunological and Stromal Signatures Between Primary and Metastatic Pancreatic Ductal Adenocarcinoma

Our understanding of the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME) primarily stems from murine models or primary patient tumors. While metastatic tumors have generally less immune infiltration compared to primary tumors, the specific cellular features of metastatic PDAC remain understudied. This knowledge gap is impactful as most patients present with metastatic disease and are most often enrolled in clinical trials. We hypothesized PDAC tumors harbor distinct immunologic and stromal features depending on their anatomical site. Using multiplex immunohistochemistry (mIHC), spatial analysis, and single-cell mass cytometry (CyTOF), we uncover dominant immune and stromal cell populations in tumors derived from 27 primary and 26 liver metastases. Metastatic liver tumors from PDAC patients contained fewer T cells and alpha-smooth muscle actin (-SMA+) activated fibroblasts than primary lesions, while CD68+ cells were more abundant. Spatial analyses revealed distinct immune cell communities in primary and metastatic PDAC, whereby CK19+ cells clustered differentially with -SMA+, CD3+, and CD68+ cells, depending on tumor site. When comparing tumor-associated regions, the proportion of peritumoral CK19- cells remained consistent, but their composition varied by disease site. CD8+ T cells were significantly less frequent in metastatic tumors, while both CD4+ and CD8+ T cells present in primary tumors expressed more transcription factors (TFs) associated with suppressive properties, including FoxP3 and ROR{gamma}t. CyTOF revealed that T cells co-expressed multiple inhibitory checkpoint receptors, with LAG-3 and PD-1 predominating. This report reveals that primary and metastatic tumors from PDAC patients harbor vastly distinct immunologic and stromal features at the protein level. Statement of SignificanceProtein level analysis reveals distinct immunological and stromal features between primary and metastatic PDAC tumors, offering a rationale for immunotherapies that target myeloid cells and increase T cell abundance in metastatic disease.

cancer biology↗

bioRxiv2022

Retrotransposons facilitates tissue specific horizontal Transfer of circulating tumor DNA

A variety of organisms have been shown to have altered physiology or developed pathology due to gene transfer, but mammals have never been shown to do so. Here, we show that circulating tumor DNA (ct) can promote cell-specific horizontal gene transfer (HGT) between human cancer cells and explain the mechanisms behind this phenomenon. Once ctDNA enters the host cell, it migrates to the nucleus and integrates into the cells genome, thereby transferring its genetic information. We determine that retrotransposons of the ERVL, SINE, and LINE families are necessary for cell targeting and the integration of ctDNA into host DNA. Using chemically synthesized retrotransposons, we found that AluSp and MER11C reproduced multiple myelomas (MM) ctDNAs cell targeting and integration into MM cells. We also discovered that ctDNA might, as a result of HGT, influence the treatment response of multiple myeloma and pancreatic cancer models. Overall, this is the first study to show that retrotransposon-directed HGT can promote genetic material transfer in cancer. There is, however, a broader impact of our findings than just cancer since cell-free DNA has also been found in physiological and other pathological conditions as well. Furthermore, with the discovery of transposons-mediated tissue-specific targeting, a new avenue for the delivery of genes and therapies will emerge.

cancer biology↗