Person:

Cristea, Simona

A key feature in the pathogenesis of OSCC is genetic instability, which results in altered expression of genes located in amplified/deleted chromosomal regions. In a previous study we have shown that the amplification of the 11q22.1-q22.2 region, encoding cIAP1 and cIAP2, is associated with lymph node metastasis and poor clinical outcome in OSCC. Here, we validate the aCGH results by nuc ish and detect a weak amplification at the 11q22.1-q22.2 locus in 37% of the 182 samples tested. We find positive correlation of 11q22.1-q22.2 amplification with lymph node metastasis, reduced survival, and increased cancer recurrence, and we observe that patients with 11q22.1-q22.2 amplification fail to respond to radiotherapy. We confirm the concurrent overexpression of cIAP1 and cIAP2 and observe differential subcellular localization of the two proteins in OSCC. To ascertain the roles of cIAP1/cIAP2 in lymph node metastasis and radioresistance, we use an in vitro pre-clinical model and confirm the role of cIAP1 in invasion and the role of cIAP2 in invasion and migration. Studies of other tumor types in which cIAP1 is overexpressed suggest that multi-regimen treatments including SMAC mimetics may be effective. Thus, the evaluation of 11q22.1-q22.2 amplifications in OSCC patients may help choose the most effective treatment.

Dissecting cellular differentiation hierarchies in the mammary gland is a prerequisite for understanding both normal development and malignant transformation during tumorigenesis and tumor cell-of-origin. To achieve these goals, several recent papers utilized single cell RNA-seq and lineage tracing to improve our understanding of the composition of the mammary epithelium at different developmental stages.

Most human tumours are heterogeneous, composed of cellular clones with different properties present at variable frequencies. Highly heterogeneous tumours have poor clinical outcomes, yet the underlying mechanism remains poorly understood. Here, we show that minor subclones of breast cancer cells expressing IL11 and FIGF (VEGFD) cooperate to promote metastatic progression and generate polyclonal metastases composed of driver and neutral subclones. Expression profiling of the epithelial and stromal compartments of monoclonal and polyclonal primary and metastatic lesions revealed that this cooperation is indirect, mediated through the local and systemic microenvironments. We identified neutrophils as a leukocyte population stimulated by the IL11-expressing minor subclone and showed that the depletion of neutrophils prevents metastatic outgrowth. Single-cell RNA-seq of CD45+ cell populations from primary tumours, blood and lungs demonstrated that IL11 acts on bone-marrow-derived mesenchymal stromal cells, which induce pro-tumorigenic and pro-metastatic neutrophils. Our results indicate key roles for non-cell-autonomous drivers and minor subclones in metastasis.

The rapid advent of high-throughput omics technologies has created an exponential growth in biological data, often outpacing our ability to derive molecular insights. Large-language models have shown a way out of this data deluge in natural language processing by integrating massive data sets into a joint model with manifold downstream use cases. Here, we envision developing multimodal foundation models, pretrained on diverse omics datasets, including genomics, transcriptomics, epigenomics, proteomics, metabolomics, and spatial profiling. These models are expected to exhibit unprecedented potential for characterizing the molecular states of cells across a broad continuum, thereby facilitating the creation of holistic maps of cells, genes, and tissues. Context-specific transfer learning of the foundation models can empower diverse applications from novel cell type recognition, biomarker discovery, gene regulation inference, to in silico perturbations. This new paradigm could launch an era of AI-empowered analyses, one that promises to unravel the intricate complexities of molecular cell biology, to support experimental design, and, more broadly, to profoundly extend our understanding of life sciences.