Cellular Oncology最新文献

Purpose: For patients with osteosarcoma, disease-related mortality most often results from lung metastasis-a phenomenon shared with many solid tumors. While established metastatic lesions behave aggressively, very few of the tumor cells that reach the lung will survive. By identifying mechanisms that facilitate survival of disseminated tumor cells, we can develop therapeutic strategies that prevent and treat metastasis.

Methods: We analyzed single cell RNA-sequencing (scRNAseq) data from murine metastasis-bearing lungs to interrogate changes in both host and tumor cells during colonization. We used these data to elucidate pathways that become activated in cells that survive dissemination and identify candidate host-derived signals that drive activation. We validated these findings through live cell reporter systems, immunocytochemistry, and fluorescent immunohistochemistry. We then validated the functional relevance of key candidates using pharmacologic inhibition in models of metastatic osteosarcoma.

Results: Expression patterns suggest that the MAPK pathway is significantly elevated in early and established metastases. MAPK activity correlates with expression of anti-apoptotic genes, especially MCL1. Niche cells produce growth factors that increase ERK phosphorylation and MCL1 expression in tumor cells. Both early and established metastases are vulnerable to MCL1 inhibition, but not MEK inhibition in vivo. Combining MCL1 inhibition with chemotherapy both prevented colonization and eliminated established metastases in murine models of osteosarcoma.

Conclusion: Niche-derived growth factors drive MAPK activity and MCL1 expression in osteosarcoma, promoting metastatic colonization. Although later metastases produce less MCL1, they remain dependent on it. MCL1 is a promising target for clinical trials in both human and canine patients.

Lung cancer, being the most widespread and lethal form of cancer globally, has a high incidence and mortality rate primarily attributed to challenges associated with early detection, extensive metastasis, and frequent recurrence. In the context of lung cancer development, noncoding RNA molecules have a crucial role in governing gene expression and protein synthesis. Specifically, tRNA-derived fragments (tRFs), a subset of noncoding RNAs, exert significant biological influences on cancer progression, encompassing transcription and translation processes as well as epigenetic regulation. This article primarily examines the mechanisms by which tRFs modulate gene expression and contribute to tumorigenesis in lung cancer. Furthermore, we provide a comprehensive overview of the current bioinformatics analysis of tRFs in lung cancer, with the objective of offering a systematic and efficient approach for studying the expression profiling, functional enrichment, and molecular mechanisms of tRFs in this disease. Finally, we discuss the clinical significance and potential avenues for future research on tRFs in lung cancer. This paper presents a comprehensive systematic review of the existing research findings on tRFs in lung cancer, aiming to offer improved biomarkers and drug targets for clinical management of lung cancer.

Background: In recent years, the significance of the nervous system in the tumor microenvironment has gained increasing attention. The bidirectional communication between nerves and cancer cells plays a critical role in tumor initiation and progression. Perineural invasion (PNI) occurs when tumor cells invade the nerve sheath and/or encircle more than 33% of the nerve circumference. PNI is a common feature in various malignancies and is associated with tumor invasion, metastasis, cancer-related pain, and unfavorable clinical outcomes. The colon and rectum are highly innervated organs, and accumulating studies support PNI as a histopathologic feature of colorectal cancer (CRC). Therefore, it is essential to investigate the role of nerves in CRC and comprehend the mechanisms of PNI to impede tumor progression and improve patient survival.

Conclusion: This review elucidates the clinical significance of PNI, summarizes the underlying cellular and molecular mechanisms, introduces various experimental models suitable for studying PNI, and discusses the therapeutic potential of targeting this phenomenon. By delving into the intricate interactions between nerves and tumor cells, we hope this review can provide valuable insights for the future development of CRC treatments.

Purpose: The lack of validated surrogate biomarkers is still an unmet clinical need in the management of early breast cancer cases that do not achieve complete pathological response after neoadjuvant chemotherapy (NACT). Here, we describe and validate the use of SAMHD1 expression as a prognostic biomarker in residual disease in vivo and in vitro.

Methods: SAMHD1 expression was evaluated in a clinical cohort of early breast cancer patients with stage II-III treated with NACT. Heterotypic 3D cultures including tumor and immune cells were used to investigate the molecular mechanisms responsible of SAMHD1 depletion through whole transcriptomic profiling, immune infiltration capacity and subsequent delineation of dysregulated immune signaling pathways.

Results: SAMHD1 expression was associated to increased risk of recurrence and higher Ki67 levels in post-NACT tumor biopsies of breast cancer patients with residual disease. Survival analysis showed that SAMHD1-expressing tumors presented shorter time-to-progression and overall survival than SAMHD1 negative cases, suggesting that SAMHD1 expression is a relevant prognostic factor in breast cancer. Whole-transcriptomic profiling of SAMHD1-depleted tumors identified downregulation of IL-12 signaling pathway as the molecular mechanism determining breast cancer prognosis. The reduced interleukin signaling upon SAMHD1 depletion induced changes in immune cell infiltration capacity in 3D heterotypic in vitro culture models, confirming the role of the SAMHD1 as a regulator of breast cancer prognosis through the induction of changes in immune response and tumor microenvironment.

Conclusion: SAMHD1 expression is a novel prognostic biomarker in early breast cancer that impacts immune-mediated signaling and differentially regulates inflammatory intra-tumoral response.

Purpose: Platinum-based chemotherapy remains a standard-of-care for most patients with advanced non-small cell lung cancer (NSCLC). DNA damage response (DDR) induced by platinum or Etoposide activated a panel of cell cycle-regulatory proteins including p21 through p53 pathway. Previous studies have reported that RanBPM has been involved in various cellular processes such as DDR by interacting with multiple proteins. However, the underlying mechanism remains unclear.

Methods: NSCLC tissue microarrays were used for assessing the expression of RanBPM by immunohistochemical staining. The roles of RanBPM in the DDR of NSCLC progression was examined in in vitro cell lines and in vivo animal models. The regulation of RanBPM on protein stability and ubiquitination levels were investigated by immunoblots and in vivo ubiquitylation assay.

Results: The level of p21 or RanBPM is lower in NSCLC than non-malignant tissues and has a highly positive correlation. Mechanistically, RanBPM protein physically interacts with p21, and RanBPM deubiquitinates p21 by recruiting a deubiquitinase USP11 to maintain protein stability of p21. RanBPM silencing significantly decreased p21 protein level. Conversely, RanBPM overexpression led to the accumulation of endogenous p21 protein regardless of p53 status. Functionally, RanBPM regulates DDR in a p21-dependent manner. Furthermore, DNA damage significantly promoted the nuclear translocation of RanBPM protein through ATM signaling pathways.

Conclusion: RanBPM is a novel regulator of P21 protein stability, and plays a critical role in the regulation of DDR.

Background: Metabolic reprogramming is closely related to the development of gastric cancer (GC), which remains as the fourth leading cause of cancer-related death worldwide. As a tumor suppressor for GC, whether receptor for activated C-kinase 1 (RACK1) play a modulatory role in metabolic reprogramming remains largely unclear.

Methods: GC cell lines and cell-derived xenograft mouse model were used to identify the biological function of RACK1. Flow cytometry and Seahorse assays were applied to examine cell cycle and oxygen consumption rate (OCR), respectively. Western blot, real-time PCR and autophagy double fluorescent assays were utilized to explore the signaling. Immunohistochemistry was performed to detect the expression of RACK1 and other indicators in tissue sections.

Results: Loss of RACK1 facilitated the viability, colony formation, cell cycle progression and OCR of GC cells in a glutamine-dependent manner. Further investigation revealed that RACK1 knockdown inhibited the lysosomal degradation of Alanine-serine-cysteine amino acid transporter 2 (ASCT2). Mechanistically, depletion of RACK1 remarkably decreased PTEN expression through up-regulating miR-146b-5p, leading to the activation of AKT/mTOR signaling pathway which dampened autophagy flux subsequently. Moreover, knockdown of ASCT2 could reverse the promotive effect of RACK1 depletion on GC tumor growth both in vitro and in vivo. Tissue microarray confirmed that RACK1 was negatively correlated with the expression of ASCT2 and p62, as well as the phosphorylation of mTOR.

Conclusion: Together, our results demonstrate that the suppressive function of RACK1 in GC is associated with ASCT2-mediated glutamine metabolism, and imply that targeting RACK1/ASCT2 axis provides potential strategies for GC treatment.

Objective and design: Pancreatic cancer is a highly malignant tumor that is well known for its poor prognosis. Based on glycosylation, we performed integrated quantitative N-glycoproteomics to investigate the synergistic anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells and explore the potential molecular mechanisms of chemotherapy in pancreatic cancer.

Methods and results: Two pancreatic cancer cell lines (PANC-1 and BxPC-3) were treated with gemcitabine, aspirin, and a combination (gemcitabine + aspirin). We found that the addition of aspirin enhanced the inhibitory effect of gemcitabine on the activity of PANC-1 and BxPC-3 cells. Quantitative N-glycoproteome, proteome, phosphorylation, and transcriptome data were obtained from integrated multi-omics analysis to evaluate the anti-tumor effects of aspirin and gemcitabine on pancreatic cancer cells. Mfuzz analysis of intact N-glycopeptide profiles revealed two consistent trends associated with the addition of aspirin, which showed a strong relationship between N-glycosylation and the synergistic effect of aspirin. Further analysis demonstrated that the dynamic regulation of sialylation and high-mannose glycoforms on ECM-related proteins (LAMP1, LAMP2, ITGA3, etc.) was a significant factor for the ability of aspirin to promote the anti-tumor activity of gemcitabine and the drug resistance of pancreatic cancer cells.

Conclusions: In-depth analysis of N-glycosylation-related processes and pathways in pancreatic cancer cells can provide new insight for future studies regarding pancreatic cancer therapeutic targets and drug resistance mechanisms.

Purpose: Acute myeloid leukaemia (AML) is a heterogeneous disease characterised by the rapid clonal expansion of abnormally differentiated myeloid progenitor cells residing in a complex microenvironment. However, the immune cell types, status, and genome profile of the peripheral blood mononuclear cell (PBMC) microenvironment in AML patients after chemotherapy are poorly understood. In order to explore the immune microenvironment of AML patients after chemotherapy, we conducted this study for providing insights into precision medicine and immunotherapy of AML.

Methods: In this study, we used single-cell RNA sequencing (scRNA-seq) to analyse the PBMC microenvironment from five AML patients treated with different chemotherapy regimens and six healthy donors. We compared the cell compositions in AML patients and healthy donors, and performed gene set enrichment analysis (GSEA), CellPhoneDB, and copy number variation (CNV) analysis.

Results: Using scRNA-seq technology, 91,772 high quality cells of 44,950 PBMCs from AML patients and 46,822 PBMCs from healthy donors were classified as 14 major cell clusters. Our study revealed the sub-cluster diversity of T cells, natural killer (NK) cells, monocytes, dendritic cells (DCs), and haematopoietic stem cell progenitors (HSC-Prog) in AML patients under chemotherapy. NK cells and monocyte-DCs showed significant changes in transcription factor expression and chromosome copy number variation (CNV). We also observed significant heterogeneity in CNV and intercellular interaction networks in HSC-Prog cells.

Conclusion: Our results elucidated the PBMC single-cell landscape and provided insights into precision medicine and immunotherapy for treating AML.

Purpose: Obesity is a risk factor and poor prognostic factor for pancreatic ductal adenocarcinoma (PDAC), but the underlying mechanisms remain unclear.

Methods: PDAC cells and obese visceral adipocytes (O-Ad) derived from mice and humans were used to analyze interactions between the two cell types, and human microvascular endothelial cells were used for angiogenesis assay. A xenograft mouse model with subcutaneously injected PDAC cells was used for animal studies. The relationship between visceral fat and prognosis was analyzed using resected tissues from PDAC patients with and without obesity.

Results: Conditioned media (CM) from O-Ad significantly increased PDAC cell growth and migration and angiogenic capacity in both human and mice cells, and blocking osteopontin (OPN) in O-Ad canceled O-Ad-induced effects in both mouse and human cells. In addition, O-Ad directly increased the migratory and tube-forming capacities of endothelial cells, while blocking OPN canceled these effects. O-Ad increased AKT phosphorylation and VEGFA expression in both PDAC and endothelial cells, and OPN inhibition in O-Ad canceled those O-Ad-induced effects. In the xenograft model, PDAC tumor volume was significantly increased in obese mice compared with lean mice, whereas blocking OPN significantly inhibited obesity-accelerated tumor growth. OPN expression in adipose tissues adjacent to human PDAC tumor was significantly higher in obese patients than in non-obese patients. In PDAC patients with obesity, high OPN expression in adipose tissues was significantly associated with poor prognosis.

Conclusion: Obese adipocytes trigger aggressive transformation in PDAC cells to induce PDAC progression and accelerate angiogenesis via OPN secretion.

Purpose: Collagen features in breast tumor microenvironment is closely associated with the prognosis of patients. We aim to explore the prognostic significance of collagen features at breast tumor border by combining multiphoton imaging and imaging analysis.

Methods: We used multiphoton microscopy (MPM) to label-freely image human breast tumor samples and then constructed an automatic classification model based on deep learning to identify collagen signatures from multiphoton images. We recognized three kinds of collagen signatures at tumor boundary (CSTB I-III) in a small-scale, and furthermore obtained a CSTB score for each patient based on the combined CSTB I-III by using the ridge regression analysis. The prognostic performance of CSTB score is assessed by the area under the receiver operating characteristic curve (AUC), Cox proportional hazard regression analysis, as well as Kaplan-Meier survival analysis.

Results: As an independent prognostic factor, statistical results reveal that the prognostic performance of CSTB score is better than that of the clinical model combining three independent prognostic indicators, molecular subtype, tumor size, and lymph nodal metastasis (AUC, Training dataset: 0.773 vs. 0.749; External validation: 0.753 vs. 0.724; HR, Training dataset: 4.18 vs. 3.92; External validation: 4.98 vs. 4.16), and as an auxiliary indicator, it can greatly improve the accuracy of prognostic prediction. And furthermore, a nomogram combining the CSTB score with the clinical model is established for prognosis prediction and clinical decision making.

Conclusion: This standardized and automated imaging prognosticator may convince pathologists to adopt it as a prognostic factor, thereby customizing more effective treatment plans for patients.