Biology subjects

Palmieri, C.

Publications and source records attributed to Palmieri, C..

4 recordsLinked to original sources

bioRxiv2026

ClonoDynamics enables replicate-resolved inference of longitudinal T cell receptor repertoire dynamics

Longitudinal T cell receptor repertoire analysis can confound biological change with measurement noise and estimator-induced structure. We developed ClonoDynamics, a framework integrating latent abundance inference with replicate-decoupled estimates of directional change and cross-replicate displacement covariance. Pseudo longitudinal series assembled from 12 independently processed technical measurements of one biological sample revealed apparent restoring dynamics caused by reusing measurements for conditioning and change estimation. Separating these roles between replicates largely removed this artifact. Synthetic controls preserving empirical detection patterns showed dose-dependent recovery of temporal accumulation, resolving the two larger imposed effects but not the smallest. Applied to TCR{beta} repertoires from ten healthy adults sampled weekly for six weeks, ClonoDynamics identified abundance-dependent directional change and shared fluctuations exceeding the technical reference. Within the analyzed abundance domain, these fluctuations showed no consistent positive accumulation over 1 to 5 weeks. ClonoDynamics provides an experimentally benchmarked framework for distinguishing estimator-induced patterns, replicate-consistent longitudinal variation, and temporal accumulation.

immunology↗

bioRxiv2022

Automated analysis of PD1 and PDL1 in lymph nodes and the microenvironment of transmissible tumors in Tasmanian devils

The wild Tasmanian devil (Sarchophilus harrisii) population has suffered a devastating decline due to two clonal transmissible cancers. Devil facial tumor 1 (DFT1) was first observed in 1996, followed by a second genetically distinct transmissible tumor, devil facial tumor 2 (DFT2), in 2014. DFT1/2 frequently metastasize, with lymph nodes being common metastatic sites. Downregulation of MHC-I by DFT1 cells is a primary means of evading allograft immunity aimed at polymorphic MHC-I proteins. DFT2 cells constitutively express MHC-I, and MHC-I is upregulated on DFT1/2 cells by interferon gamma, suggesting other immune evasion mechanisms may contribute to overcoming allograft and anti-tumor immunity. Human clinical trials have demonstrated PD1/PDL1 blockade effectively treats patients showing increased expression of PD1 in tumor draining lymph nodes, and PDL1 on peritumoral immune cells and tumor cells. The effects of DFT1/2 on systemic immunity remain largely uncharacterized. This study applied the open-access software QuPath to develop a semiautomated pipeline for whole slide analysis of stained tissue sections to quantify PD1/PDL1 expression in devil lymph nodes. The QuPath protocol provided strong correlations to manual counting. PD-1 expression was approximately 10-fold higher than PD-L1 expression in lymph nodes and was primarily expressed in germinal centers, whereas PD-L1 expression was more widely distributed throughout the lymph nodes. The density of PD1 positive cells was increased in lymph nodes containing DFT2 metastases, compared to DFT1. This suggests PD1/PDL1 exploitation may contribute to the poorly immunogenic nature of transmissible tumors in some devils and could be targeted in therapeutic or prophylactic treatments.

immunology↗

bioRxiv2022

AI-powered pan-species computational pathology: bridging clinic and wildlife care

Cancers occur across species. Understanding what is consistent and varies across species can provide new insights into cancer initiation and evolution, with significant implications for animal welfare and wildlife conservation. We built the pan-species cancer digital pathology atlas (PANCAD) and conducted the first pan-species study of computational comparative pathology using a supervised convolutional neural network algorithm trained on human samples. The artificial intelligence algorithm achieves high accuracy in measuring immune response through single-cell classification for two transmissible cancers (canine transmissible venereal tumour, 0.94; Tasmanian devil facial tumour disease, 0.88). Furthermore, in 18 other vertebrate species (mammalia=11, reptilia=4, aves=2, and amphibia=1), accuracy (0.57-0.94) was influenced by cell morphological similarity preserved across different taxonomic groups, tumour sites, and variations in the immune compartment. A new metric, named morphospace overlap, was developed to guide veterinary pathologists towards rational deployment of this technology on new samples. This study provides the foundation and guidelines for transferring artificial intelligence technologies to veterinary pathology based on a new understanding of morphological conservation, which could vastly accelerate new developments in veterinary medicine and comparative oncology.

cancer biology↗

bioRxiv2017

Enhancers mapping uncovers phenotypic heterogeneity and evolution in patients with luminal breast cancer.

The degree of intrinsic and interpatient phenotypic heterogeneity and its role in tumour evolution is poorly understood. Phenotypic divergence can be achieved via the inheritance of alternative transcriptional programs1,2. Cell-type specific transcription is maintained through the activation of epigenetically-defined regulatory regions including promoters and enhancers1,3,4. In this work, we annotated the epigenome of 47 primary and metastatic oestrogen-receptor (ER)-positive breast cancer specimens from clinical samples, and developed strategies to deduce phenotypic heterogeneity from the regulatory landscape, identifying key regulatory elements commonly shared across patients. Highly shared regions contain a unique set of regulatory information including the motif for the transcription factor YY1. In vitro work shows that YY1 is essential for ER transcriptional activity and defines the critical subset of functional ER binding sites driving tumor growth in most luminal patients. YY1 also control the expression of genes that mediate resistance to endocrine treatment. Finally, we show that H3K27ac levels at active enhancer elements can be used as a surrogate of intra-tumor phenotypic heterogeneity, and to track expansion and contraction of phenotypic subpopulations throughout breast cancer progression. Tracking YY1 and SLC9A3R1 positive clones in primary and metastatic lesions, we show that endocrine therapies drive the expansion of phenotypic clones originally underrepresented at diagnosis. Collectively, our data show that epigenetic mechanisms significantly contribute to phenotypic heterogeneity and evolution in systemically treated breast cancer patients.

cancer biology↗