Biology subjects

Litchfield, C.

Publications and source records attributed to Litchfield, C..

3 recordsLinked to original sources

bioRxiv2025

RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology

Clinical implementation of comprehensive genomic profiling, via whole-genome (WGS) or whole-exome sequencing (WES), is constrained by sparse mutation burdens and analytic pipelines reliant on matched transcriptomes. Currently, gene-centric analysis prevails, but overlooks the complex, multigene and pathway perturbations shaping tumor biology. We introduce RIPPLET, a DNA-only framework converting somatic variants into quantitative gene-impact scores and topology-aware pathway-perturbation profiles. By integrating tissue-specific protein-protein interaction networks with cohort-informed reweighting, RIPPLET prioritizes likely functionally relevant alterations. Applied across 33 TCGA cancer types, RIPPLET surpasses four state-of-the-art multi-omic driver-prioritization tools in recovering cancer type-specific drivers. In a cohort of metastatic cutaneous melanomas, it identifies pathway signatures that predict drug response, provide prognostic insight and distinguish immune-infiltration phenotypes without RNA data, independently validated on an in-house cohort. RIPPLET enables DNA-only inference of tumor-specific gene and pathway dysregulation, aligning with clinical sequencing workflows and offering a scalable precision-oncology strategy in transcriptome-limited settings.

bioinformatics↗

bioRxiv2025

Deep visual multi-omics profiling reveals mechanisms that underly cancer cell differentiation and aggressiveness in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits significant intra-tumoral heterogeneity (ITH) at both morphological and genetic levels, complicating treatment and contributing to disease progression. Among these, ccRCCs with focal rhabdoid differentiation stand out as highly aggressive tumors distinguished by cells with unique morphological features. However, the correlation between distinct morphological phenotypes, specific molecular alterations, and their influence on tumor behavior remains poorly understood. In this study, we integrated advanced AI-based image analysis with single-cell isolation and multi-omics profiling to dissect the link between clinically relevant morphological and molecular features of ccRCC cells. Using a novel digital pathology workflow, we quantified low-grade, high-grade, and rhabdoid morphologies in ccRCC diagnostic images with unprecedented precision. Subsequently, isolation of two sets of 1,000 morphologically distinct cells for detailed mRNA and protein expression analyses, revealed significant increasing dysregulation associating with higher histopathological grades. Rhabdoid ccRCC cells (grade 4) demonstrated unique molecular profiles, including upregulated FOXM1-driven proliferation, disrupted cell-matrix interactions, and enhanced immune evasion pathways. Despite high T-cell infiltration in rhabdoid areas, we identified a rhabdoid-specific immunosuppressive network driven by cytokines, IFN-beta, and integrin signaling, likely contributing to T-cell exhaustion. Rhabdoid ccRCC cells develop a distinct immunosuppressive signaling network, involving PD-L1 and novel immunomodulatory factors such as CD38 and ITGB2. These findings provide a basis for novel therapeutic strategies targeting these pathways in combination with immunotherapy to improve outcomes for patients with aggressive rhabdoid ccRCC. Key PointsO_LIccRCC is characterized by well-established morphological heterogeneity but the correlation with the underlying molecular aberrations remained elusive. C_LIO_LIBy integrating AI-based image analysis with single cell isolation and deep multi-omics profiling, we dissect the molecular intricacies of ccRCC, from targeted collection of 1,000 morphologically distinct cells. C_LIO_LIOur results demonstrate significant dysregulation of gene and protein expression correlating with higher histopathological grades in ccRCC. C_LIO_LIAggressive ccRCC cells with rhabdoid differentiation (grade 4) display distinct molecular profiles, as they upregulate FOXM1-mediated proliferation, ECM remodeling and the immune evasion responses, suggesting new therapeutic avenues enhancing ICI efficacy in these patients. C_LI

cancer biology↗

bioRxiv2023

Decreasing the flexibility of the TELSAM-target protein linker and omitting the cleavable fusion tag improves crystal order and diffraction limits

TELSAM crystallization promises to become a revolutionary tool for the facile crystallization of proteins. TELSAM can increase the rate of crystallization and form crystals at low protein concentrations without direct contact between TELSAM polymers and, in some cases, with very minimal crystal contacts overall (Nawarathnage et al., 2022). To further understand and characterize TELSAM-mediated crystallization, we sought to understand the requirements for the composition of the linker between TELSAM and the fused target protein. We evaluated four different linkers Ala-Ala, Ala-Val, Thr-Val, and Thr-Thr, between 1TEL and the human CMG2 vWa domain. We compared the number of successful crystallization conditions, the number of crystals, the average and best diffraction resolution, and the refinement parameters for the above constructs. We also tested the effect of the fusion protein SUMO on crystallization. We discovered that rigidification of the linker improved diffraction resolution, likely by decreasing the number of possible orientations of the vWa domains in the crystal, and that omitting the SUMO domain from the construct also improved the diffraction resolution. SynopsisWe demonstrate that the TELSAM protein crystallization chaperone can enable facile protein crystallization and high-resolution structure determination. We provide evidence to support the use of short but flexible linkers between TELSAM and the protein of interest and to support the avoidance of cleavable purification tags in TELSAM-fusion constructs.

biochemistry↗