Biology subjects

Cleveland, M.

Publications and source records attributed to Cleveland, M..

3 recordsLinked to original sources

bioRxiv2026

Weak supervision of H&E slides reveals systems-level biology and functional states that govern therapeutic resistance

Precision oncology lacks scalable methods to identify the mechanisms that mediate therapeutic resistance for individual patients. Resistance often arises from focal cellular niches that are obscured by bulk profiling and costly to resolve with multi-omics. Here, we show that deep learning (DL), applied to routine histology, can localize focal tissue regions enriched for therapeutically relevant biology. Using 3111 breast cancer H&E slides with matched bulk transcriptomics, we trained weakly-supervised DL models to infer activities of immune, metabolic, and tumor-intrinsic phenotypes implicated in therapeutic resistance (AUROC>0.80; PCC>0.64). Accurate inference of these phenotypes should identify tissue regions enriched for the corresponding biological signal. Therefore, we validated phenotype inference and spatial localization with complementary analyses. Tissue-matched multiplexed immunofluorescence showed concordance between inferred immune states and corresponding cell fractions (p=0.006-0.106). Across multi-institutional cohorts, model-derived phenotypes recovered expected relationships with therapeutic outcomes (p<0.045). Finally, in a blinded evaluation, pathologists confirmed that model-derived high-attention regions were enriched for phenotype-specific morphology (p<2.408*10-5). Because evaluated phenotypes represent diverse mechanisms of resistance across therapeutic modalities, these findings provide a foundation for resistance-directed localization using therapeutic outcomes as supervision. By directing deep profiling toward model-prioritized regions, this framework could enable scalable nomination of candidate mediators of resistance for subsequent functional validation across real-world patient populations. One sentence summaryWeakly supervised deep learning localizes focal tissue regions enriched for therapeutically relevant biology in routine histology, thus offering a scalable strategy to study therapeutic resistance across large patient populations.

biophysics↗

bioRxiv2025

Molecular dynamics driving phenotypic divergence among KRAS mutants in pancreatic tumorigenesis

Inflammation in the pancreas drives acinar-to-ductal metaplasia (ADM), a progenitor-like state that can be hijacked by mutant Kras in the formation of pancreatic cancer (PDAC). How these cell fate decisions vary according to KRAS mutation remains poorly understood. To define mutation-specific lineage reversion and tumor initiation, we implement novel Ptf1a-TdTomato mice and multiple KRAS mutants across an array of genetic, pharmacologic, and inflammatory perturbations in vivo. Whereas KRASG12D co-opts injury to enable lineage reversion, enhancer reprogramming, and tumor initiation, KRASG12R/V can initiate but not sustain dedifferentiated and neoplastic transcriptional and epigenetic programs. We find the KRASG12R/V defects consist of a failure to invoke robust EGFR signaling and activate Rac1/Vav1, with constitutive Akt activation in vivo sufficient to rescue the tumorigenic potential of KRASG12R. As the marked heterogeneity among KRAS variants begins early in tumorigenesis, these data are crucial to understanding mutation-specific oncogenic trajectories and directing the implementation of KRAS-directed therapeutics. SIGNIFICANCEDefining how KRAS mutants drive distinct outcomes in human pancreatic cancer is critical for developing allele-specific therapeutic approaches. This study unveils a hierarchy among KRASG12D, KRASG12V, and KRASG12R to drive tumor initiation, owing to heterogeneous activation of EGFR, PI3K/AKT, and RAC1 signaling, thus revealing mutation-specific evolutionary paths in pancreatic tumorigenesis.

cancer biology↗

bioRxiv2023

Structural and functional vascular dysfunction within brain metastases is linked to pembrolizumab inefficacy

Structurally and functionally aberrant vasculature is a hallmark of tumor angiogenesis and treatment resistance. Given the synergistic link between aberrant tumor vasculature and immunosuppression, we analyzed perfusion MRI for 44 patients with brain metastases (BM) undergoing treatment with pembrolizumab. To date, vascular-immune communication, or the relationship between immune checkpoint inhibitor (ICI) efficacy and vascular architecture, has not been well-characterized in human imaging studies. We found that ICI-responsive BM possessed a structurally balanced vascular makeup, which was linked to improved vascular efficiency and an immune-stimulatory microenvironment. In contrast, ICI-resistant BM were characterized by a lack of immune cell infiltration and a highly aberrant vasculature dominated by large-caliber vessels. Peri-tumor region analysis revealed early functional changes predictive of ICI resistance before radiographic evidence on conventional MRI. This study was one of the largest functional imaging studies for BM and establishes a foundation for functional studies that illuminate the mechanisms linking patterns of vascular architecture with immunosuppression, as targeting these aspects of cancer biology may serve as the basis for future combination treatments.

cancer biology↗