Cancer Science最新文献

Long noncoding RNAs (lncRNAs) play pivotal roles in the development of human malignancies, though their involvement in oral squamous cell carcinoma (OSCC) remains incompletely understood. Using The Cancer Genome Atlas (TCGA) dataset, we analyzed expression of 7840 lncRNAs in primary head and neck squamous cell carcinoma (HNSCC) and found that upregulation of LINC02154 is associated with a poorer prognosis. LINC02154 knockdown in OSCC cell lines induced cell cycle arrest and apoptosis, and significantly attenuated tumor growth in vitro and in vivo. Notably, depletion of LINC02154 downregulated FOXM1, a master regulator of cell cycle-related genes. RNA pulldown and mass spectrometry analyses identified a series of proteins that could potentially interact with LINC02154, including HNRNPK and LRPPRC. HNRNPK stabilizes FOXM1 expression by interacting with the 3'-UTR of FOXM1 mRNA, which suggests LINC02154 and HNRNPK promote cell cycling by regulating FOXM1 expression. Additionally, LINC02154 positively regulates HNRNPK expression by inhibiting microRNAs targeting HNRPNK. Moreover, LINC02154 affects mitochondrial function by interacting with LRPPRC. Depletion of LINC02154 suppressed expression of mitochondrial genes, including MTCO1 and MTCO2, and inhibited mitochondrial respiratory function in OSCC cells. These results suggest that LINC02154 exerts its oncogenic effects by modulating the cell cycle and oxidative phosphorylation in OSCC, highlighting LINC02154 as a potential therapeutic target.

We investigated the effectiveness and safety of nelarabine (NEL)-combined chemotherapy for newly diagnosed adult T-cell acute lymphoblastic leukemia (T-ALL) patients. We conducted a phase II trial, T-ALL213-O, where adult T-ALL patients aged 25 to 64 were treated by a regimen based on that used in our previous study, ALL202-O. The main modifications from ALL202-O to T-ALL213-O were as follows: (1) NEL-combined chemotherapy, instead of consolidation (C)1, was used for non-complete remission (CR) patients after induction therapy (IND)1 as IND2; (2) NEL treatments were inserted into C3 and C5 on day 29. Twenty-four patients were analyzed. Ten patients did not receive NEL treatment due to therapy termination prior to C3. Three-year event-free survival (EFS) was 70%, with 52% as the lower limit of its 90% confidence interval, which exceeded the threshold of 25%; thus, the study treatment was considered effective. The CR rates by IND1, IND2, and both were 75%, 100%, and 88%, respectively. The 5-year EFS and 5-year overall survival rates were 66% and 70%, respectively, with median follow-ups of 7.7 and 7.8 years. The addition of NEL improved the CR rate but not survival, compared with T-ALL patients in ALL202-O. Severe neuropathy after NEL administration was observed at a high frequency. Seven (50%) of 14 patients treated with NEL showed grade 3 peripheral neuropathy and/or gait disturbance. The neurotoxicity was considered stronger than that previously reported. Combination therapy of NEL at this dose and intensive multidrug chemotherapy is associated with a high risk of severe neurotoxicity (JALSG T-ALL213-O, UMIN000010642).

Cancer stem cells aggregate to form clusters, which have enhanced stem-like properties and metastasis potential. However, the molecular mechanisms underlying the formation of cancer stem cell cluster-like structures with acquisition of stronger invasion and metastasis abilities remain unclear. Micropapillary carcinoma (MPC) is a subpopulation of small, merulioid, inverted, nonfibrous vascular clusters floating in the stroma present in a range of solid malignant tumors and characterized by frequent vascular/lymphatic vessel invasion and lymph node metastasis. Our results showed that these cell clusters exhibit a stem cell phenotype, supporting the premise that MPC may serve as a promising solid tumor model for studying invasion and metastasis of cancer stem cell clusters. In this review, we discuss the latest advances in MPC research and targeted therapy, focusing on analysis of their stem-like characteristics, mapping their multiomics characteristics, and elucidating the vascular and immune microenvironment of MPC. The existing MPC organoid model was employed to explore potential breakthroughs in targeted therapy and immunotherapy for cancer stem cell clusters.

Adipose tissue and bacterial flora are involved in metabolism in the human body. However, the relationship between the two remains unclear. Recently, the presence of circulating bacterial DNAs has been reported. We previously reported the utility of bacterial DNA in serum extracellular vesicles (EVs) for diagnosing patients with renal cell carcinoma (RCC). In this study, we aimed to assess whether there is a correlation between bacterial DNA in serum EVs and inflammation in adipose tissue. We undertook 16S rRNA metagenomic analysis of bacterial DNA in serum EVs from 77 patients with RCC (the derivation cohort). We discovered that DNAs from Enterobacteriaceae, Polaromonas, and Coxiellaceae were highly expressed in patients with low Mayo adhesive probability (MAP) scores. A lower MAP score reflects a reduced risk of dense adipose tissue and adhesions. Additionally, we combined these bacterial DNAs to create the EPC (Enterobacteriaceae, Polaromonas, Coxiellaceae) index that predicts a MAP score of 0. Subsequently, we undertook 16S rRNA metagenomic analysis of bacterial DNA in serum EVs from 32 patients with RCC (the validation cohort). The EPC index could distinguish patients with low MAP scores from those with high MAP scores in the derivation (area under the curve [AUC], 0.76; sensitivity, 56%; specificity, 85%) and validation (AUC, 0.81; sensitivity, 100%; specificity, 62%) cohorts. These results suggest that bacterial DNA in serum EVs could reflect the inflammation of adherent perinephric fat around the kidney.

Genome-wide association studies (GWAS) statistically assess the association between tens of millions of genetic variants in the whole genome and a phenotype of interest. Genome-wide association studies enable the elucidation of polygenic inheritance of cancer, in which myriad low-penetrance genetic variants collectively contribute to a substantial proportion of the heritable susceptibility. In addition to the robust genotype-phenotype associations provided by GWAS, combining GWAS data with functional genomic datasets or sophisticated statistical genetic methods unlocks deeper insights. Integrating genotype and molecular phenotyping data facilitates functional characterization of GWAS association signals through molecular quantitative trait loci mapping and transcriptome-wide association studies. Furthermore, aggregating genome-wide polygenic signals, including subthreshold associations, enables one to estimate genetic correlations across diverse phenotypes and helps in clinical risk predictions by evaluating polygenic risk scores. In this review, we begin by summarizing the rationale for GWAS of cancer, introduce recent methodological updates in the GWAS-derived downstream analyses, and demonstrate their applications to GWAS of cancers.

Human T-cell leukemia virus type 1 (HTLV-1) broadly impacts host genes, affecting the infected cell population and inducing the development of a disease with a poor prognosis, adult T-cell leukemia-lymphoma (ATL). This study aimed to provide a comprehensive epigenomic characterization of the infected cell population and evaluated the transcriptome and chromatin structures of peripheral blood cells in HTLV-1-infected individuals using RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin sequencing (ATAC-seq). The infected cells showed significant changes in gene expression patterns from the polyclonal stage and before ATL onset while demonstrating similarities to tumor-forming ATL cells. These similarities were a result of large-scale open chromatin changes, supporting the independent early formation of epigenomic aberrations as an underlying mechanism for later clonal propagation. This study also demonstrated that HTLV-1 Tax directly affects the host chromatin structure, thereby developing fundamental epigenomic characteristics. Several Tax target genes, including the RASGRP3-ERK pathway, were recognized, indicating an impact on signaling pathways. This genome-wide variability in chromatin structural property is a novel feature of HTLV-1 infection and may contribute to pathogenic mechanisms. In addition, it has crucial implications for better understanding the impact of HTLV-1 on the host genome and identifying novel therapeutic targets.

Pulmonary pleomorphic carcinoma (PC) is a rare non-small-cell lung carcinoma (NSCLC) with a poor prognosis, characterized by tumor necrosis (TN). NETosis is a form of neutrophil-specific cell death, which is morphologically characterized by prominent neutrophil infiltration and cell detritus in the necrotic foci. Seventy-six patients with pulmonary PC who underwent complete resection were enrolled. Tumor necrosis was evaluated using digitally scanned resected specimens. The regions of NETosis were quantified using citrullinated histone H3 (citH3)- and myeloperoxidase-positive regions. We examined the association between the NETosis area and the prognostic outcomes and assessed the correlation between the NETosis area and systemic inflammation. Tumor necrosis was observed in 70 patients (92%). In all the cases, the TN region was accompanied by a citH3-positive region. The patients with high NETosis area (n = 54) had significantly shorter overall survival than those with low NETosis area (n = 16) (p = 0.013). Furthermore, a high NETosis area was an independent poor prognostic factor in the multivariate analyses. Systemic inflammatory markers, including C-reactive protein (CRP), CRP-to-albumin ratio, and neutrophil-to-lymphocyte ratio, were significantly higher in patients with high NETosis area than in those with low NETosis area. Furthermore, the levels of these inflammatory markers were significantly decreased postsurgery. This study shows that in surgically resected pulmonary PC, patients with high NETosis areas have higher systemic inflammation and worse prognosis.

The expectations for artificial intelligence (AI) technology have increased considerably in recent years, mainly due to the emergence of deep learning. At present, AI technology is being used for various purposes and has brought about change in society. In particular, the rapid development of generative AI technology, exemplified by ChatGPT, has amplified the societal impact of AI. The medical field is no exception, with a wide range of AI technologies being introduced for basic and applied research. Further, AI-equipped software as a medical device (AI-SaMD) is also being approved by regulatory bodies. Combined with the advent of big data, data-driven research utilizing AI is actively pursued. Nevertheless, while AI technology has great potential, it also presents many challenges that require careful consideration. In this review, we introduce the current status of AI-based cancer research, especially from the perspective of clinical application, and discuss the associated challenges and future directions, with the aim of helping to promote cancer research that utilizes effective AI technology.

Leukemia is highly heterogeneous, meaning that different types of leukemia require different treatments and have different prognoses. Current clinical diagnostic and typing tests are complex and time-consuming. In particular, all of these tests rely on bone marrow aspiration, which is invasive and leads to poor patient compliance, exacerbating treatment delays. Morphological analysis of peripheral blood cells (PBC) is still primarily used to distinguish between benign and malignant hematologic disorders, but it remains a challenge to diagnose and type these diseases solely by direct observation of peripheral blood(PB) smears by human experts. In this study, we apply a segmentation-based enhanced residual network that uses progressive multigranularity training with jigsaw patches. It is trained on a self-built annotated dataset of 21,208 images from 237 patients, including five types of benign white blood cells(WBCs) and eight types of leukemic cells. The network is not only able to discriminate between benign and malignant cells, but also to typify leukemia using a single peripheral blood cell. The network effectively differentiated acute promyelocytic leukemia (APL) from other types of acute myeloid leukemia (non-APL), achieving a precision rate of 89.34%, a recall rate of 97.37%, and an F1 score of 93.18% for APL. In contrast, for non-APL cases, the model achieved a precision rate of 92.86%, but a recall rate of 74.63% and an F1 score of 82.75%. In addition, the model discriminates acute lymphoblastic leukemia(ALL) with the Ph chromosome from those without. This approach could improve patient compliance and enable faster and more accurate typing of leukemias for early diagnosis and treatment to improve survival.

Multiple myeloma (MM) cells and osteoclasts (OCs) activate with each other to cause drug resistance. Human Th1-like Vγ9Vδ2 (γδ) T cells, important effectors against tumors, can be expanded and activated ex vivo by the aminobisphosphonate zoledronic acid in combination with IL-2. We previously reported that the expanded γδ T cells effectively targeted and killed OCs as well as MM cells. Because the expanded γδ T cells expressed CD16 on their surface, we investigated the utilization of the expanded γδ T cells for antibody-dependent cellular cytotoxicity (ADCC). Although the expanded γδ T cells alone induced cell death in MM cell lines, the addition of the anti-SLAMF7 monoclonal antibody elotuzumab (ELO) further enhanced their cytotoxic activity only against SLAMF7-expressing MM cell lines and primary MM cells. Intriguingly, ELO was also able to enhance γδ T cell-induced cell death against OCs cultured alone, and against both MM cells and OCs in their coculture settings. SLAMF7 was found to be highly expressed in OCs differentiated in vitro from monocytes by receptor activator of nuclear factor-κ B ligand and M-CSF, although monocytes only marginally expressed SLAMF7. These results demonstrate that SLAMF7 is highly expressed in both MM cells and OCs, and that the ex vivo-expanded γδ T cells can exert ELO-mediated ADCC against SLAMF7-expressing MM cells and OCs besides their direct cytotoxic activity. Further study is warranted for the innovative utilization of γδ T cells.